The performance consistency of an RF MEMS switch matrix is a crucial metric, which directly impacts its operational lifespan. An improved crossbar-based RF MEMS switch matrix topology, the SR-Crossbar, was investigated in this article. An optimized port configuration scheme was proposed for the RF MEMS switch matrix. Both the utilization probability of individual switch nodes and path lengths in the switch matrix achieve best consistency simultaneously under the proposed port configuration scheme. One significant advantage of this scheme lies in that it only adjusts positions of input and output ports, with topology and individual switch nodes kept unchanged. This grants it a high level of generality and feasibility, and also introduces an additional degree of freedom for optimizations. The article also constructed a universal utilization probability function of single nodes, and formulated an optimization objective function for the SR-Crossbar RF MEMS switch matrix, which provides a convenient approach to directly solving the optimized port configuration scheme for practical applications.

This paper reports the novel design of a touch mode capacitive pressure sensor (TMCPS) system with a wireless approach for a full-range continuous monitoring of ventricular pressure. The system consists of two modules: an implantable set and an external reading device. The implantable set, restricted to a 2x2 cm² area, consists of a TMCPS array connected with a dual-layer coil, for making a reliable resonant circuit for communication with the external device. The capacitive array is modelled considering the small deflection regime for achieving a dynamic and full 5-300 mmHg pressure range. In this design, the two inductive-coupled modules are calculated considering proper electromagnetic alignment, based on two planar coils and considering the following: 13.56 MHz frequency to avoid tissue damage and three types of biological tissue as core (skin, fat and muscle). The system was validated with the Comsol Multiphysics and CoventorWare softwares; showing a 90% power transmission efficiency at a 3.5 cm distance between coils. The implantable module includes aluminum- and polyimide-based devices, which allows ergonomic, robust, reproducible, and technologically feasible integrated sensors. In addition, the module shows a simplified and low cost design approach based on PolyMEMS INAOE® technology, featured by low-temperature processing.

This paper describes different variants of broadband and simple attenuator modules for beamforming applications, based on Radio Frequency Micro Electro-Mechanical Systems (RF-MEMS), framed within Coplanar Waveguide (CPW) structures. The modules proposed in the first part of this work differ in their actuation voltage, topology, and desired attenuation level. Fabricated samples of basic 1-bit attenuation modules, characterized by a moderate footprint of 690 x 1960 µm2 and aiming at attenuation levels of -2, -3 and -5 dB in the 24.25-27.5 GHz range, are presented in their variants featuring both low actuation voltages (5-7 V) as well as higher values (~ 45V), the latter ones ensuring larger mechanical restoring force (and robustness against stiction). Beyond the fabrication non-idealities that affected the described samples, the substantial agreement between simulations and measurement outcomes proved that the proposed designs could provide precise attenuation levels up to 40 GHz, ranging up to nearly -3 dB and -5 dB for the series and shunt variants, respectively. Moreover, they could be effective building blocks for future wideband and reconfigurable RF-MEMS attenuators. In fact, in the second part of this work, combinations of the discussed cells and other configurations meant for larger attenuation levels will be investigated.

Triangular resonators re-shaped with the Sierpinski geometry and U-shaped resonators have been designed, linking them with single-pole-double-through (SPDT) RF MEMS switches to provide frequency tuning for potential applications in the K-Band. Prototypes of band-stop narrowband filters working around 20 GHz and 26 GHz, interesting for RADAR and satellite communications, have been studied in coplanar waveguide (CPW) configuration, and the tuning was obtained by switching between two paths of the devices loaded with different resonators. As a result, dual-band operation or fine-tuning can be obtained depending on the choice of the resonator, acting as a building block. The studied filters belong to the more general group of devices inspired by the metamaterial design.

Microelectromechanical System (MEMS) vibrating gyroscope design considerations are always intriguing due to their microscale mechanical, electrical, and material behavior. MEMS vibrating ring gyroscopes have become important inertial sensors in inertial measurement units (IMU) for navigation and sensing applications. The design of a MEMS vibrating ring gyroscope incorporates an oscillating ring structure as a proof mass, reflecting unique design challenges and possibilities. This paper presents a comprehensive design analysis of the MEMS vibrating ring gyroscope from the mechanical, electrical, and damping perspectives. The mechanical design of the MEMS vibrating ring gyroscope investigates the various frame designs of the vibrating ring structure, as well as the various beam structures, including curved, rectangular, and semicircular beam structures, which are analyzed using mathematical models and finite element analysis (FEA) simulations that provide an in-depth analysis of the stiffness and deflection of the vibrating structures. The electrical designs of the MEMS vibrating ring gyroscope were analyzed using various electrode configurations, electrostatic actuation, and capacitive detection mechanisms, respectively. The design analysis of various forms of damping, including viscous, structural, thermoelastic, and anchor damping, has been discussed. The variety of design structures investigated for MEMS vibrating ring gyroscopes' mechanical, electrical, and damping performance.

Integrated Kerr micro-combs, a powerful source of many wavelengths for photonic RF and microwave signal processing, are particularly useful for transversal filter systems. They have many advantages including a compact footprint, high versatility, large numbers of wavelengths, and wide bandwidths. We review recent progress on photonic RF and microwave high bandwidth temporal signal processing based on Kerr micro-combs with spacings from 49-200GHz. We cover integral and fractional Hilbert transforms, differentiators as well as integrators. The potential of optical micro-combs for RF photonic applications in functionality and ability to realize integrated solutions is also discussed.

The electrical signal of micro-transducers operating in electrically conductive fluids must be effectively isolated from the surrounding environment while remaining in contact for sensing purposes. A thermally actuated MEMS viscosity sensor uses a buried resistive heat element for actuating a thin silicon membrane whose movement is monitored with embedded piezoresistive elements since the frequency response and behavior of the membrane are used to correlate the viscosity of the fluid being tested. The post-processing materials, (1) Parylene-C, (2) flouroacrylate-based polymer, and (3) nitrocellulose-based polymer, were coated as thin layers of waterproofing materials on different sensors. All three coating materials provided adequate protection when they were used to waterproof the sensors when tested under normal operating conditions. Although the vibration response of the sensors was slightly modified, it did not affect their functionality in a significant way when measuring conductive fluids based on glycerol-water mixtures. All the treated sensors lasted over 1.2 million actuations without any decay in performance or failures. When the test bias conditions were increased by 5x to accelerate failures, the flouroacrylate-based polymer samples lasted 2x longer than the others. Visual analysis of the failures indicates that the edge of the diaphragm, which undergoes the most significant stress and strain values during actuation, was the location of the mechanical failure. This work guides post-processed waterproofing coatings for micro-scale actuators operating in harsh and damaging environments.

Soliton crystal micro-combs are powerful tools as sources of multiple wavelength channels for radio frequency (RF) signal processing. They offer a compact device footprint, large numbers of wavelengths, very high versatility, and wide Nyquist bandwidths. Here, we demonstrate integral order RF signal processing functions based on a soliton crystal micro-comb, including a Hilbert transformer and first- to third-order differentiators. We compare and contrast results achieved and the tradeoffs involved with varying comb spacing, tap design methods, as well as shaping methods.

We demonstrate an RF photonic fractional Hilbert transformer based on an integrated Kerr micro-comb source featuring a record low free spectral range of 49 GHz. By programming and shaping the comb lines according to calculated tap weights for up to 39 wavelengths across the C-band, we achieve tunable bandwidths ranging from 1.2 to 15.3 GHz as well as variable center frequencies from baseband to 9.5 GHz, for both standard integral and arbitrary fractional orders. We experimentally characterize the RF amplitude and phase response of the tunable bandpass and lowpass Hilbert transformers with 90 and 45-degree phase shifts. The experimental results show good agreement with theory, confirming the effectiveness of our approach as a powerful way to implement standard and fractional order Hilbert transformers with broad and variable bandwidths and center frequencies, with high reconfigurability and greatly reduced size and complexity. Tan, and D. J. Moss are with the Optical Sciences Centre, Swinburne University of Technology, Hawthorn, VIC 3122, Australia. (Corresponding e-mail: dmoss@swin.edu.au). Xu is with the Electro-Photonics Laboratory, Department of Electrical and Computer System Engineering, Monash University, Clayton, 3800 VIC, Australia

This paper describes developing and analyzing an analytical model of Microelectromechanical Systems (MEMS) internal vibrating ring gyroscope. The internal ring structure consists of eight semicircular beams attached to the externally placed anchors. The paper analyses the vibrating ring gyroscope inplane displacement behavior and the resulting elliptical vibrational modes. The elliptical vibrational modes appear as pairs with the same resonance frequency due to the symmetric nature of the design. The analysis commences by conceptualizing the ring as a geometric structure with a circular shape, possessing specific dimensions such as thickness, height, and radius. We construct a linear model that characterizes the vibrational dynamics of the internal vibrating ring. The analysis encompasses comprehensive mathematical formulations for the radial and tangential displacements in local polar coordinates, considering the inextensional displacement of the ring structure. By utilizing the derived equations, we highlight the underlying relationships driving the vibrational characteristics of the MEMS vibrating ring gyroscope. These dynamic vibrational relationships are essential in enabling the vibrating ring gyroscope's future utilization in accurate navigation and motion sensing technologies.

The subject of the research is to Development of laser ablation method for Fabrication of surface acoustic wave sensors on quartz wafer, the target of the GQW – is to design Acoustic wave sensor by using laser ablation method. By using the surface acoustic wave theory to sense by the signal and using this physical phenomenon, We will design the sensor which transduce an input electrical signal into a mechanical wave which unlike an electrical signal, can be easily influenced by physical phenomena. The device then transducers this wave back into an electrical signal on the secondary terminal of the sensor. Changes in amplitude, phase, frequency, or time-delay between the input and output electrical signals can be used to measure the presence of the desired Our work in this part, especially the practical part like temperature, vibration ,etc. we design a combs on the waver of quartz to make like an electrode primary electrode & secondary electrode by putting coats of cuppers & vanadium on the waver and then using the fiber optic laser regime to design this combs to can able transfer the signal by ablation the most important here to use the regime of fiber optic laser then we using this sensor in any electronic circuit How we will select the suitable kind of laser to design, this is the most important part, and what it will be the diameter of that combs of secondary and primary , how much the value of the wave length to select the micro distant combs to avoid any inductance and interference for transferred signal , also take the benefit of using MEMS theory in our project.

A lead zirconate titanate [PZT;Pb(Zr_0.52Ti_0.48)O₃] layer embedded infrared (IR) detector decorated with wavelength-selective plasmonic crystals has been investigated for high-performance non-dispersive infrared (NDIR) spectroscopy. A plasmonic IR detector with an enhanced IR absorption band has been designed based on numerical simulations, fabricated by conventional microfabrication techniques, and characterized with a broadly tunable quantum cascade laser. The enhanced responsivity of the plasmonic IR detector at specific wavelength band has improved the performance of NDIR spectroscopy and pushed the limit of detection (LOD) by an order of magnitude. In this paper, a 13 fold enhancement in the LOD of a methane gas sensing using NDIR spectroscopy is demonstrated with the plasmonic IR detector.

We demonstrate a photonic RF integrator based on an integrated soliton crystal micro-comb source. By multicasting and progressively delaying the input RF signal using a transversal structure, the input RF signal is integrated discretely. Up to 81 wavelengths are provided by the microcomb source, which enable a large integration time window of ~6.8 ns, together with a time resolution as fast as ~84 ps. We perform signal integration of a diverse range of input RF signals including Gaussian pulses with varying time widths, dual pulses with varying time intervals and a square waveform. The experimental results show good agreement with theory. These results verify our microcomb-based integrator as a competitive approach for RF signal integration with high performance and potentially lower cost and footprint.

Micro-electro-mechanical systems (MEMS) are once proposed in 1970s and evolving rapidly. The current researchers are seeking for better designs and better applications of MEMS actuators. This work presents an electrostatic driven dual-axis scanning micromirror, i.e., two-dimensional (2D) scanning micromirror with a mirror size of 500 μm × 500 μm. The scanning mirror is implemented by using bulk micromachining process on silicon on insulator (SOI) substrate, which is compatible with present complementary metal oxide semiconductor (CMOS) manufacturing technology. The scanning frequencies of the slow and the fast axis are 4.87 kHz and 31.15 kHz, respectively. The impact factors of the dimensions of comb fingers and torsional beams are analyzed and discussed in this study. Under the driving voltage difference of 100 volts and 70 volts, the deviation angle is 4.57° × 13.08°. Therefore, a simple design of a dual-axis MEMS scanning micromirror is proposed, which can be precisely controlled without additional complex sensors or circuits.

Here, we investigate the actuation dynamics of a micro device with different intervening liquids between the actuating components under the influence of Casimir and dissipative hydrodynamic forces. This is enabled via phase space portraits, which demonstrate that by increasing the dielectric response of the intervening layer the device may not come into stiction due to the decreasing in magnitude Casmir force. Moreover, it is feasible to expand area of motion using intervening liquids with lower dynamic viscosity or increasing the slip length of the intervening fluid. Finally, under the influence of an external driven force, which is the realistic case for possible applications, the system can reach stable oscillation at larger separations with an amplitude higher for the liquid that lead to lower Casimir and hydrodynamic forces.

This article presents a new design of supporting tethers through the concept of force distribution. The transmitted force applied on tethers will be distributed on the new tether design area resulting in low acoustic energy transferred to anchor boundaries and stored energy enhancement. This technique achieves an anchor quality factor of 175,000 compared to 58,000 obtained from con-ventional tether design representing 3-fold enhancement. Also, the unloaded quality factor of the proposed design improved from 23,750 to 27,442 representing 1.2-fold improvements.

This paper introduces a chip-level oven-controlled system for improving the temperature stability of MEMS resonators. Wherein the resonator and the micro-hotplate are manufactured by MEMS technology, then wire-bounded in a package shell at the chip level. The proposed resonator is transduced by the AlN film, and its temperature is monitored by temperature-sensing resistors on both sides. The designed micro-hotplate is placed at the bottom of the resonator chip as a heater and insulated by airgel. The PID pulse width modulation (PWM) circuit controls the heater according to the temperature detection result to provide a constant temperature for the resonator. The proposed oven-controlled MEMS resonator (OCMR) exhibits a frequency drift of 3.5ppm in the range of -50°C to 125°C, and the method also can be applied to other MEMS devices that require temperature control.

With the rapid development of MEMS (Micro-electro-mechanical Systems) fabrication technologies, manifolds microelectrodes with various structures and functions have been designed and fabricated for applications in biomedical research, diagnosis and treatment through electrical stimulation and electrophysiological signal recording. The flexible MEMS microelectrodes exhibit multi-aspect excellent characteristics beyond stiff microelectrodes based on silicon or SU-8, which comprising: lighter weight, smaller volume, better conforming to neural tissue and lower fabrication cost. In this paper, we mainly reviewed key technologies on flexible MEMS microelectrodes for neural interface in recent years, including: design and fabrication technology, flexible MEMS microelectrodes with fluidic channels and electrode-tissue interface modification technology for performance improvement. Furthermore, the future directions of flexible MEMS microelectrodes for neural interface were described including transparent and stretchable microelectrodes integrated with multi-aspect functions and next-generation electrode-tissue interface modifications facilitated electrode efficacy and safety during implantation. Finally, the combinations among micro fabrication techniques with biomedical engineering and nanotechnology represented by flexible MEMS microelectrodes for neural interface will open a new gate to human lives and understanding of the world.

Copper nitride (Cu3N), a metastable semiconductor material, but with reasonably-high-stability at room temperature, is drawing a great deal of attention as a very promising next-generation, earth-abundant, thin-film solar absorber. Its non-toxicity, on the other hand, makes it a very attractive eco-friendly semiconducting material. In the present work, Cu3N thin films were grown by employing radio-frequency magnetron sputtering, at room temperature, with 50-W RF-power, and partial nitrogen pressures of 8.0 and 1.0, onto glass substrates. Thus, the influence of argon on the optical properties of the Cu3N thin films was studied, with the goal of being able to achieve a low-cost, light absorber material, with appropriate properties in order to substitute the more conventional silicon, in photovoltaic cells. Variable-angle spectroscopic ellipsometry measurements have been conducted at three angles, 50∘, 60∘, and 70∘, respectively, in order to obtain the two ellipsometric parameters psi, ψ, and delta, Δ, respectively. For the constructed optical model, the bulk planar Cu3N layer is described by a one-dimensional graded-index model, combine with the mixture of a Tauc-Lorentz oscillator and up to four Gaussian oscillators, whereas a BEMA model with 50%-air-void is adopted in order to account for the existing surface-roughness layer. In addition, the optical properties such as the energy-band gap, and refractive index and absorption coefficient, were determined in order to assess the actual capability of this material as a light absorber for solar cells. The direct and indirect band gap energies were accurately calculated, and they were found to be in the ranges of 2.14-2.21 eV and very clse to 1.50 eV, respectively.

Nowadays, great attention has been attributed to the study of runoff and its fluctuation over space and time. There is a crucial need for a good soil and water management system to overcome the challenges of water scarcity and other natural adverse events like floods and landslides, among others. Rainfall-runoff modeling is an appropriate approach for runoff prediction, making it possible to take preventive measures to avoid damage caused by natural hazards such as floods. In the present study, several data driven models, namely: Multiple linear regression (MLR), Multiple adaptive regression splines (MARS), Support vector machine (SVM), and Random Forest (RF), were used for rainfall-runoff prediction of the Gola watershed, located in the south-eastern part of the Uttarakhand. The performance of the models was evaluated based on the coefficient of determination (R2), root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), and percent bias (PBAIS) indices. In addition to the numerical comparison, the models were evaluated and their performances were evaluated base on graphical plotting, i.e., line diagram, scatter plot, Violin plot, relative error plot and Taylor diagram (TD). The comparison results revealed that the four heuristic methods gave higher accuracy than the MLR model. Among the machine learning models, the RF (RMSE (m3/s), R2, NSE, and PBIAS (%) = 6.31, 0.96, 0.94, and -0.20 during the training period, respectively, and 5.53, 0.95, 0.92, and -0.20 during the testing period, respectively) surpassed the MARS, SVM, and the MLR models in forecasting daily runoff for all cases studies. Among all four models, the RF model outperformed in the training and testing periods. It can be summarized that the RF model is best-in-class and delivers a strong potential for runoff prediction of the Gola watershed.

We show that an experimentally plausible system consisting of a modulated wire medium hosted in a metal cavity can preserve the longitudinal field profile shaping predicted by Boyd et al. (2018) on the basis of a perfectly periodic wire-only structure. These new frequency domain numerical results are a significant step towards justifying the construction of an experimental apparatus to test the field profile shaping in practise.

Infrared sensors incorporating suspended zinc oxide (ZnO) pyroelectric films and thermally-insulated silicon substrates are fabricated using conventional MEMS-based thin-film deposition, photolithography, and etching techniques. The responsivity of the pyroelectric film is improved through annealing at 500℃ for 4 h. The voltage response of the fabricated sensors is evaluated experimentally for a substrate thickness of 1 µm over a sensing range of 30 cm. The results show that the voltage signal varies as an inverse exponential function of the distance. A positioning system based on three infrared sensors is implemented in LabVIEW. It is shown that the position estimates obtained using the proposed system are in excellent agreement with the actual locations. In general, the results presented in this study provide a useful source of reference for the further development of MEMS-based pyroelectric infrared sensors.

Inertial navigation system (INS) is a basic component for obtaining a continuous navigation solution in various applications. The INS navigation solution suffers from a growing error over time. In particular, its navigation solution depends mainly on the quality and grade of the inertial measuring unit (IMU) that provides the INS with both accelerations and angular rates. However, low-cost small micro-electro-mechanical systems (MEMS) suffer from tremendous error sources such as bias, scale factor, scale factor instability, and highly non-linear noise. Therefore, MEMS-IMU measurements lead to drifted solutions when used as a control input to the INS. Accordingly, several approaches have been introduced to model and mitigate the errors associated with IMU. In this paper, a machine learning-based adaptive neuro-fuzzy inference system (ML-ANFIS) is proposed to leverage the performance of low-grade IMUs in two phases. The first phase is training 50% of the low-grade IMU measurements with a high-end IMU to generate a suitable error model. The second phase involved testing the developed model on the remaining low-grade IMU measurements. A real road trajectory was conducted to evaluate the performance of the proposed algorithm. The results show the effectiveness of utilizing the proposed ML-ANFIS algorithm in removing errors and improving the INS solution compared to the traditional one. An improvement of 70% in the 2D-positioning and 92% in the 2D-velocity INS solution is attained when the proposed algorithm was applied compared to the traditional INS solution.

RF photonic transversal signal processors, which combine reconfigurable electrical digital signal processing and high-bandwidth photonic processing, provide a powerful solution for achieving adaptive high-speed information processing. Recent progress in optical microcomb technology provides compelling multi-wavelength sources with compact footprint, yielding a variety of microcomb-based RF photonic transversal signal processors implemented by either discrete or integrated components. Although operating based on the same principle, processors in these two forms exhibit distinct performance. This letter presents a comparative investigation into their performance. First, we compare the performance of state-of-the-art processors, focusing on the processing accuracy. Next, we analyze various factors that contribute to the performance differences, including tap number and imperfect response of experimental components. Finally, we discuss the potential for future improvement. These results provide a comprehensive comparison of microcomb-based RF photonic transversal signal processors implemented using discrete and integrated components and provide insights for their future development.

The fabrication of thin-film multilayer structures by sputtering technique usually requires multi-cathode deposition machine. This study proposes a simpler approach based on the RF power modulation: silicon nitride (SiN$_x$) thin films were prepared by RF reactive sputtering in (Ar + N$_2$) atmosphere at room temperature. The samples were analyzed to highlight the effects of different deposition conditions on the morphological and optical properties of the films in the visible and near/mid-IR regions. The refractive index of the films was changed in the range of 1.5 - 2.5 (at $\lambda$=800 nm) by tuning the sputtering power. IR reflectance measurements revealed the absence of spurious (oxygen- or hydrogen-based) phases, while atomic force and scanning electron microscopies confirmed the presence of flat and defect-free samples surfaces.

We review recent work on narrowband orthogonally polarized optical RF single sideband generators as well as dual-channel equalization, both based on high-Q integrated ring resonators. The devices operate in the optical telecommunications C-band and enable RF operation over a range of either fixed or thermally tuneable frequencies. They operate via TE/TM mode birefringence in the resonator. We achieve a very large dynamic tuning range of over 55 dB for both the optical carrier-to-sideband ratio and the dual-channel RF equalization for both the fixed and tunable devices.

In this paper, we present a study of various ZnO/SiO2-stacked thin film structures for flexible micro-energy harvesting devices. Two groups of micro-energy harvesting devices, SiO2/ZnO/SiO2 micro-energy generators (SZS-MGs) and ZnO/SiO2/ZnO micro-energy generators (ZSZ-MGs), were fabricated by stacking both SiO2 and ZnO thin films, and the resulting devices were characterized. With a particular interest in the fabrication of flexible devices, all the ZnO and SiO2 thin films were deposited on ITO-coated PEN substrates using an RF magnetron sputtering technique. The effects of the thickness and/or position of the SiO2 films on the device performance were investigated by observing the variations of output voltage in comparison with that of a control sample. As a result, compared to the ZnO single-layer device, all the ZSZ-MGs showed much better output voltages, while all the SZS-MG showed only slightly better output voltages. Among the ZSZ-MGs, the highest output voltages were obtained from the ZSZ-MGs where the SiO2 thin films were deposited using a deposition power of 150 W. Overall, the device performance seems to depend significantly on the position as well as the thickness of the SiO2 thin films in the ZnO/ SiO2-stacked multilayer structures, in addition to the processing conditions.

Glass has emerged as a highly versatile substrate for various sensor and MEMS packaging applications, including electromechanical, thermal, optical, biomedical, and RF devices, due to its exceptional properties such as high geometrical tolerances, outstanding heat and chemical resistance, excellent high-frequency electrical properties, and the ability to be hermetically sealed. In these applications, Through-Glass-Via (TGV) plays a vital role in manufacturing and packaging by creating electrical interconnections through glass substrates. This paper provides a comprehensive summary of the research progress in TGV fabrication along with their integrations, including through-via formation and metallization. The paper also reviews the significant qualification and reliability achievements obtained by the scientific community for TGV. Additionally, the paper summarizes the application of TGV technology in various sensors.

: This paper proposes a reem-shape phononic crystal for the performance enhancement of TPoS resonators. The proposed phononic crystal offers an ultra-wide acoustic band gap that prevents energy leakage through the supporting substrate on its placement at the anchoring boundary, resulting in significant improvements in the resonator quality factor. Simulated results show reem-shape Phononic crystals generate a band gap up to 175MHz with BG of 90% and enhance the anchor quality factor from 180,000 to 6,000,000 and unloaded quality factor from 133,000 to 160,000 representing 33.3-fold and 1.2-fold improvements respectively.

Tuning fork gyroscopes (TFGs) are promising for potential high-precision applications. This work proposes and experimentally demonstrates a novel high-Q dual mass tuning fork microelectro-mechanical system (MEMS) gyroscope utilizing three-dimensional (3D) packaging techniques. Except for two symmetrically-decoupled proof masses (PM) with synchronization structures, a symmetrically-decoupled lever structure is designed to force the antiparallel, antiphase drive-mode motion and basically eliminate the low-frequency spurious modes. The thermoelastic damping (TED) and anchor loss are greatly reduced by the linearly-coupled, momentum- and torque-balanced antiphase sense mode. Besides, a novel 3D packaging technique is used to realize high Q-factors. A composite substrate encapsulation cap, fabricated by through-silicon-via (TSV) and glass-in-silicon (GIS) reflow processes, is anodically bonded to the sensing structures at wafer scales. A self-developed control circuit is adopted to realize loop control and characterize gyro-scope performances. It is shown that a high-reliability electrical connection together with a high-air-impermeability package can be fulfilled with this 3D packaging technique. Furthermore, the Q-factors of the drive and sense modes reach up to 51947 and 49249, respectively. This TFG realizes a wide measurement range of ±1800° /s and a high resolution of 0.1° /s with a scale-factor nonlinearity 720 ppm after automatic mode-matching. Besides, the long-term zero-rate output (ZRO) drift can be effectively suppressed by temperature compensation, inducing a small angle random walk (ARW) of 0.923°/√h and a low bias instability (BI) of 9.270°/h.

Compared with liquid crystal clad waveguide, MEMS mirror has some merits, such as high-er-transmissivity, lager-angle of scanning, faster scanning speed and so on. Furthermore, MEMS mirror arrays perform more superior than MEMS mirror when they steer laser beam, which make MEMS arrays much more suitable to be used in devising compact Lidar. Before assembling a Lidar with MEMS arrays, the optical intensity and distributions of the laser diffracted by MEMS arrays should be analyzed, but few published papers about this issue are available so far, this paper will focus on this issue about MEMS arrays. Firstly, the complex amplitudes of laser which is diffracted by 1-D and 2-D arrays are presented, respectively. Then the optical intensity and distributions on the observation plane are presented. Finally, the simulation diagrams of these distributions are shown, and the correctness of the results is indirectly verified by Young’s dou-ble-slit experiment. The results gotten in this letter are essential to design a compacted Lidar based on MEMS arrays.

In the last ten years, plasma waste treatment has gained increasing prominence as a technology in response to growing challenges in waste disposal and the recognition of opportunities for generating valuable by-products. The efficiency and outcomes of this process are intricately linked to the characteristics of the plasma involved, such as plasma enthalpy and heat flux. We employed an experimental radio frequency inductively coupled plasma (RF-ICP) torch operating at atmospheric pressure to generate plasma. Utilizing optical emission spectroscopy (OES), we measured plasma parameters, specifically the effective electron temperature (Teff) and plasma density (ne), while varying argon gas flow rates and RF powers. Our investigations revealed that both flow rate and RF power exert significant control over plasma parameters, and we observed an unusual phenomenon within this range of discharge pressures. Consequently, both the plasma's enthalpy and the heat flux it generates are influenced by variations in both flow rate and RF power.

Electroencephalography (EEG) is essential for tracking brain activity and identifying seizure effects. However, epileptic behaviour can only be detected after a specialist has carefully analysed all EEG recordings along with a proper history of the patient. A skilled physician is required for the right epilepsy diagnosis and therapy. But most of the time, patients visit the clinician in the interictal stage with no proper history documented. Therefore, it was essential to the automatic prediction of stages of seizure. K nearest neighbours (KNN) and random forest (RF) models using raw EEG signals, preictal, ictal, postictal, and interictal stages were identified in this study. The possibility of these characteristics is explored by examining how well time-domain signals work in the prediction of epileptic stages using intracranial EEG datasets from Freiburg Hospital (FH), Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT), and Temple University Hospital (TUHEEG). To test the viability of this approach, two different types of simulations were carried out on three binary classifications (interictal vs. preictal, interictal vs. ictal, preictal vs. postictal, and interictal vs. postictal), and one four-class problem (interictal vs. preictal vs. ictal vs. postictal) was performed for each model. The average accuracy when using time-domain signals in the FH database was 90.5% and 75.0%; CHB-MIT was 92.87% and 75.9%; and TUHEEG was 94.46% and 76.8%, respectively, for the KNN and RF models.

We report a 92 channel RF channelizer based on a 48.9 GHz integrated micro-comb that operates via soliton crystals, together with a passive high-Q ring resonator that acts as a periodic filter with an optical 3dB bandwidth of 121.4 MHz. We obtain an instant RF bandwidth of 8.08 GHz and 17.55 GHz achieved through temperature tuning. These results represent a major advance to achieving fully integrated photonic RF spectrum channelizers with reduced low complexity, size, and high performance for digital-compatible signal detection and broadband analog signal processing.

To investigate the impact of electrode structure on Electrical Stimulation Therapy (EST) for chronic wound healing, this study designed three variants of flexible microelectrodes (FMs) with Ag-Cu coverings (ACCs), each exhibiting distinct geometrical configurations: hexagonal, cross-shaped, and serpentine. These were integrated with PPY@PDA/PANI (3/6) hydrogel dressings. Comprehensive animal studies, coupled with detailed electrical and mechanical modeling and simulations, were conducted to assess their performance. Results indicated that the serpentine-shaped FM outperformed its counterparts in terms of flexibility and safety, exhibiting minimal thermal effects and a reduced risk of burns. Notably, FMs with metal coverings under 3% demonstrated promising potential for optoelectronic self-powering capabilities. Additionally, simulation data highlighted the significant influence of hydrogel non-uniformity on the distribution of electrical properties across the skin surface, providing critical insights for optimizing EST protocols when employing hydrogel dressings.

We present a design of electrostatic comb driver to improve and investigate its actuation performance. The proposed electrostatic comb actuator (ECA) is composed of two set of interdigitated comb microstructures, the inner combs are fixed to form the fish-bone microstructures and the outer combs are movable and connected to crab-leg flexure beams microstructures. The ECA is investigated to optimize the actuation performance by changing the comb shape and the intersection angle of crab-leg flexure beams. The comb shapes are compared between the traditional rectangle shape and the trapezoid shape, while the intersection angles of crab-leg flexure beams are compared between 45°, 60°, and 90° on the influences of ECA displacement and stability characteristics. These parameters are investigated for their impacts on the dynamic comb displacement and driving voltage. Under the condition of a driving DC bias voltage of 100 volts, the ECA displacement is firstly increased and then gradually decreased by increasing the comb finger length. The maximum displacement of ECA with trapezoid comb is 47.2 μm while that of ECA with rectangle comb is 22.4 μm. By using trapezoid comb shape to replace the rectangle comb under the same conditions, the ECA displacement is improved 2-fold. To enhance the stability of ECA system, the intersection angle of 90˚ of crab-leg flexure beams shows highest stability that is great better than the intersection angle of 45° and 60° of crab-leg flexure beams by increasing the driving different DC bias voltage to 100 volts on ECA. The stability of the ECA with the intersection angle of 90° of crab-leg flexure beams is enhanced 1.1-fold and 1.4-fold compared to that of 45° and 60° of crab-leg flexure beams, respectively. This design provides an optimized approach to the electrostatic comb actuator that can be used expansively in the gyroscope, motion sensor, position sensor, imaging sensor, optical sensor, and so on.

A complete model was developed to simulate the behavior of a circular clamped axisymmetric fluid-coupled Piezoelectric Micromachined Ultrasonic Transducer (PMUT). Combining Finite Difference and Boundary Element Matrix (FD-BEM), this model is based on the discretization of the partial differential equation used to translate the mechanical behavior of a PMUT. In the model, both the axial and the transverse displacements are preserved in the equation of motion and used to properly define the neutral line position. To introduce fluid coupling, a Green’s function dedicated to axisymmetric circular radiating sources is employed. The resolution of the behavioral equations is used to establish the equivalent electroacoustic circuit of a PMUT that preserves the average particular velocity, the mechanical power, and the acoustic power. Particular consideration is given to verifying the validity of certain assumptions that are usually made across various steps of previously reported analytical models. In this framework, the advantages of the membrane discretization performed in the FD-BEM model are highlighted through accurate simulations of the first vibration mode and especially the cutoff frequency that many other models do not predict. This high cutoff frequency corresponds to cases where the spatial average velocity of the plate is null and is of great importance for PMUT design because it defines the upper limit above which the device is considered to be mechanically blocked. These modeling results are compared with electrical and dynamic membrane displacement measurements of AlN-based PMUTs in air and fluid. This complete PMUT model using the FD-BEM approach is shown to be very efficient in terms of computation time and accuracy.

We present the design, fabrication, and response of a polymer-based Laterally Amplified Chemo-Mechanical (LACM) humidity sensor based on mechanical leveraging and parametric amplification. The device consists of a sense cantilever asymmetrically patterned with a polymer and flanked by two stationary electrodes on the sides. When exposed to a humidity change, the polymer swells after absorbing the analyte and causes the central cantilever to bend laterally towards one side, causing a change in the measured capacitance. The device features an intrinsic gain due to parametric amplification resulting in an enhanced signal-to-noise ratio (SNR). 11-fold magnification in sensor response was observed via voltage biasing of the side electrodes without the use of conventional electronic amplifiers. The sensor showed a repeatable and recoverable capacitance change of 11% when exposed to a change in relative humidity from 25-85%. The dynamic characterization of the device also revealed a response time ~1s and demonstrated a competitive response with respect to a commercially available reference chip.

Over the past decade, plasma waste treatment has become a more prominent technology due to increasing problems with waste disposal and realizing opportunities to generate valuable co-products. Plasma waste treatment extensively uses atmospheric pressure (RF) inductive coupled plasma (ICP) torches. In situ Optical Emission Spectroscopy (OES) is used to evaluate the developed RF ICP torch for Municipal Solid Waste (MSW) treatment and ascertain the plasma parameters to understand the physical mechanism involved. The argon plasma jet's electron temperature and plasma density outside the torch chamber are calculated using the Boltzmann plot and Stark broadening at different gas flow rates, and RF power. The expected electron temperature and plasma density behaviour were observed at a low gas flow rate. The electron temperature decreases with the RF power from 8089 K to 6097 K as demand for increasing the plasma density. An energy loss mechanism was revealed while raising the gas flow rate, as the electron temperature increases with RF power from 5750 K to 6221 K, and the plasma density decreases. This behaviour is due to the anomalous skin effect. Detecting and avoiding this phenomenon is essential as it negatively affects torch energy efficiency and waste treatment.

The Unmanned Aerial Vehicles (UAVs), used in civilian applications such as emergency medical deliveries, precision agriculture, wireless communication provisioning, etc., face the challenge of limited flight time due to their reliance on the on-board battery. Therefore, developing efficient mechanisms for in-situ power transfer to recharge UAV batteries hold potential in extending their mission time. In this paper, we study the use of far-field wireless power transfer (WPT) technique from specialized, transmitter UAVs (tUAVs) carrying Multiple Input Multiple Output (MIMO) antennas for transferring wireless power to receiver UAVs (rUAVs) in a mission. The tUAVs can fly and adjust their distance to the rUAVs to maximize energy transfer. The use of MIMO antennas further boost the energy reception by narrowing the energy beam toward the rUAVs. The complexity of their dynamic operating environment increases with the growing number of tUAVs, and rUAVs with varying levels of energy consumption and residual power. We propose an intelligent trajectory selection algorithm for the tUAVs based on a deep reinforcement learning model called Proximal Policy Optimization (PPO) to optimize the energy transfer gain. Simulation results demonstrate that with the use of PPO, the system achieves a tenfold flight time extension compared to no wireless recharging. Further, PPO outperforms the benchmark movement strategies of ’Traveling Salesman Problem’ and ’Low Battery First’ when used by the tUAVs.

A simulation test system for the two-dimensional (2D) fuze overload loading process was designed to address the loading issues of recoil overload and centrifugal overload in fuze safety and arming (S&A) devices. By incorporating centrifuge rotation energy storage, impact acceleration simulation, and equivalent centrifugal rotation simulation, a block equipped with a fuze S&A device was accelerated instantly upon being impacted by a centrifuge-driven impact hammer, simulating recoil overload loading. The impact hammer was retracted instantaneously by adopting an electromagnetic brake, which resulted in the centrifugal rotation of the block around its track, to simulate the centrifugal overload loading. The dynamic equations of the simulation test system and the equations of impact hammer motions were established, whereby the rotation speed of the centrifuge and the braking force of the electromagnetic brake were calculated and selected. A dynamic model of the collision between the impact hammer and block was established using ANSYS/LS-DYNA software for simulation analysis. The acceleration curves of the recoil overload and centrifugal overload with variations in the centrifuge speed, cushion material, and buffer thickness were obtained, which verified the feasibility of the proposed loading simulation method. 2D overload loading simulation tests were performed using the developed simulation system, and the acceleration curves of the recoil overload and centrifugal overload were measured. The test results indicated that the proposed system can accomplish 2D overload loading simulations for a recoil overload of several 10000 g and centrifugal overload of several 1000 g.

In order to realize the accurate measurement of wearable sphygmomanometer, this paper selects the micro electro mechanical system (MEMS) pressure sensor with small size, low cost and high accuracy, and proposes a flexible packaging method combining Parylene and Polydimethylsiloxane (PDMS). The flexible packaging sensor protects the sensor chip while ensuring the comfort of the measured person. It can be worn for a long time, and the encapsulated sensor has good accuracy and sensitivity. At the same time, the encapsulated MEMS pressure sensor was used to collect good pulse signals and extract multiple pulse wave characteristic parameters. A blood pressure measurement method based on the combination of arterial tonometry method and pulse wave parameters method was proposed, and multiple machine learning algorithms were compared and analyzed to select the algorithm model with the smallest error as the optimal regressor. The experimental results show that the blood pressure measurement method combining the arterial tonometry method and the pulse wave parameters method can effectively improve the accuracy of blood pressure measurement. The experimental results demonstrate that the combination of arterial tonometry and pulse wave parameter methods can effectively enhance the accuracy of blood pressure measurement, with the random forest model serving as the optimal regressor. The average deviation between the systolic blood pressure measured by our self-made sphygmomanometer and the commercial sphygmomanometer was 0.86mmHg, with a standard deviation of 4.04mmHg. The average deviation of diastolic blood pressure was 0.63mmHg, with a standard deviation of 5.15mmHg, meeting the AAMI standard for clinical practice.

With the development of designing and manufacturing level for micro-electromechanical system (MEMS) gyroscopes, the control circuit system becomes a key point to determine their internal performances. Nevertheless, phase delay of electron components may result in some serious hazards. This paper describes a real-time circuit phase delay correction system for MEMS vibratory gyroscopes. A detailed theoretical analysis is provided to clarify the influences of circuit phase delay on the in-phase and quadrature (IQ) coupling characteristics and zero rate output (ZRO) utilizing force-to-rebalance (FTR) closed-loop detection and quadrature correction system. By deducing the relationship between amplitude-frequency, phase-frequency of MEMS gyroscope and the phase relationship of the whole control loop, a real-time correction system is proposed to automatically adjust the phase reference value of phase-locked loop (PLL) and thus compensate for the real-time circuit phase delay. The experimental results show that the correction system can accurately measure and compensate the circuit phase delay in real time. Furthermore, the unwanted IQ coupling can be eliminated and the ZRO is decreased by 755% to 0.095°/s. This correction system realizes a small angle random walk of 0.978°/√h, and a low bias instability of 9.458°/h together with a scale factor nonlinearity of 255 ppm at room temperature. Besides, the thermal drift of ZRO is reduced to 0.0034°/s/°C at a temperature range from -20°C to 70°C.

The escalating reliance of modern society on information and communication technology has rendered it vulnerable to an array of cyber-attacks, with distributed denial-of-service (DDoS) at-tacks emerging as one of the most prevalent threats. This paper delves into the intricacies of DDoS attacks, which exploit compromised machines numbering in the thousands or more to disrupt data services and online commercial platforms, resulting in significant downtime and financial losses. Recognizing the gravity of this issue, various detection techniques have been explored, yet the quantitative and prior detection of DDoS attacks has seen a decline in recent methods. This research introduces an innovative approach by integrating evolutionary optimization algorithms and machine learning techniques. Specifically, the study proposes XGB-GA Optimization, RF-GA Optimization, and SVM-GA Optimization methods, employing Evolutionary Algorithms Opti-mization with TOPOT-Genetic Programming. Datasets pertaining to DDoS attacks were utilized to train machine learning models based on XGB, RF, and SVM algorithms, and 10-fold cross-validation was employed. The models were further optimized using evolutionary algo-rithms, achieving remarkable accuracy scores: 99.99% with the XGB-GA method, 99.50% with RF-GA, and 99.99% with SVM-GA. Furthermore, the study employed TPOT to identify the optimal algorithm for constructing a machine learning model, with the genetic algorithm pinpointing XGB-GA as the most effective choice. This research significantly advances the field of DDoS attack detection by presenting a robust and accurate methodology, thereby enhancing the cybersecurity landscape and fortifying digital infrastructures against these pervasive threats.

The processes of hydrogen reduction of silicon and germanium chlorides under the conditions of radio-frequency (40.68 MHz) counteracted arc discharge stabilized between two rod electrodes were investigated. The main gas-phase and solid products of plasma-chemical transformations were determined. Thermodynamic analysis of SiCl4 + H2 and GeCl4 + H2 systems was carried out. It is shown that under the implemented experimental conditions, equilibrium components of the products are established. The detected spectra of chemical activity were studied, which gave reason to assume that the molecular mechanism of the hydrogen reduction process is the main one. The impurity composition of gas-phase and solid reaction products was investigated. The possibility of single-stage production of high-purity Si and Ge mainly in the form of compact ingots, as well as high-purity chlorosilanes and trichlorogermane, was shown.

This paper is a further development of our “Proposal of a new double-nozzle technique for in-gas-jet laser resonance ionization spectroscopy” published in journal Atoms earlier in this year. Here, we propose to equip the proposed double-nozzle technique with the RF-only funnel and RF-buncher placed in the gas-jet chamber at 70 mm distance downstream the double-nozzle exit. It allows for highly effective extraction into vacuum heavy ion beams, produced in two-steps laser resonance ionization in the argon supersonic jet. We explored the operation of this new full version of the double-nozzle technique through detailed gas dynamic and then Monte Carlo trajectory simulations, which results are presented and discussed. In particularly, we have shown by calculations that more than 80% of all nobelium-254 neutral atoms, extracted by argon flow from the gas stopping cell through the double-nozzle into the supersonic jet can be extracted into vacuum in a form of pulsed ion beam having low transverse and longitudinal emittance.s dynamic and Monte Carlo simulations

This paper presents a calibration and thermal compensation method that aims to minimize cost and processing time while maintaining high accuracy. First, the number of positions to perform the calibration procedure is optimized, and then, based on this optimized calibration number, thermal compensation is performed, which is necessary for environments with large temperature variations, since calibration parameters change at different temperatures. The calibration procedures and algorithms were experimentally validated on marketed accelerometers. Based on the optimized calibration method, the calibrated results have been obtained nearly 100 times improvement. Thermal drift calibration experiments on the triaxial accelerometer show that the thermal compensation scheme in this paper can effectively reduce drift in the temperature range of -40°C to 60°C. The temperature drifts of x- and y-axes are reduced from -13.2 and 11.8 mg to -0.9 and -1.1 mg, respectively. The z-axis temperature drift is reduced from -17.9 to 1.8 mg. We have conducted various experiments on the proposed calibration method and demonstrated its capacity to calibrate the sensor frame error model (SFEM) parameters. Therefore, the MEMS sensors calibrated in this paper have certain engineering application values for tilt measurement.

MEMS (Micro-electromechanical Systems) becomes important increasingly due to the smarter and smaller fuze used in OICW (Objective Individual Combat Weapon). MEMS Safety and Arming (S&A) device is employed in different platforms and regions for small caliber projectile. Therefore, it is necessary to make a parametric study of the MEMS S&A device in different apply environments and explore the main sensitive factors of the MEMS S&A device to provide reference for designs. In this paper, based on the MEMS S&A device designed by our term, theory and finite element models are established, and the centrifugal insurance mechanism of the MEMS S&A device is parametric studied under the different speeds, temperature and thickness of the model by nonlinear dynamic method. By comparing the experimental and predicted results, the established FEM model is verified, and the conclusion is that the temperature and the centrifugal force are the main sensitive factors in the centrifugal insurance mechanism. In summary, we can suggest that the application environment, which the MEMS S&A device is suitable for, is the temperature equal to or slightly greater than normal temperature and the rotating speed higher than35000r/min of small caliber projectile.

This paper proposes a circuit model of Cross-Coupled CMOS AC – DC Charge Pump (XC – CP) operating in subthreshold region. The aim is improving the efficiency to design XC – CPs with variety of specifications, e.g., input and output voltages and AC input frequency. First, it is shown that the output resistance (Ro) of XC – CP is much higher than those of CPs with single diodes (SD – CP) and ultra-low-power diodes (ULPD – CP) as charge transfer switches (CTSs). Second, the reason behind the above feature of XC – CP is identified by a simple model that the gate-to-source voltages of CTS MOSFETs are independent of the output voltage of the CP. Third, high but finite Ro of XC – CP is explainable with a more accurate model that includes the dependence of the saturation current of MOSFETs operating in subthreshold region on the drain-to-source voltage which is a function of the output voltage of CP. The model was in good agreement with measured and simulated results of XC – , SD – and ULPD – CPs fabricated in 250 nm CMOS.

The gate resistance is a parasitic element in transistors for RF and millimeter-wave circuits that can negatively impact power gain and noise figure. To develop accurate device models, a reliable measurement methodology is crucial. This article reviews the standard measurement methodology used in the literature and proposes also an additional method, which is evaluated using suitable test structures in a 16nm FinFET process. The advantages and disadvantages of the two approaches are discussed along with their respective application scenarios

Observing cultivated crops and other forms of land use is an important environmental and economic concern for agricultural land management and crop classification. Crop categorization offers significant crop management data, ensuring food security, and developing agricultural policies. Remote sensing data, especially publicly available Sentinel 1 and 2 data, has effectively been used in crop mapping and classification in cloudy places because of their high spatial and temporal resolution. This study aimed to improve crop type classification by combining Sentinel-1 (Synthetic Aperture Rader (SAR)) data and the Sentinel-2 Multispectral Instrument (MSI) data. In the study, Random Forest (RF) and Classification and Regression Trees (CART) classier were used to classify grain crops (Barley and Wheat). The classification results based on the combination of Sentinel-2 and Sentinel-1 data indicated an overall accuracy (OA) of 93 % and a kappa coefficient (K) of 0.896 for RF and (89.15%, 0.84) for the CART classifier. It is suggested to employ a mix of radar and optical data to attain the highest level of classification accuracy since doing so improves the likelihood that the details will be observed in comparison to the single-sensor classification technique and yields more accurate results.

The present work is an effort to explain theoretically the physics of some processes we have observed in our previous experiments. They occur under any mechanical excitation in solutions of strong electrolytes. We assume that the occurrence of the low-frequency Debye ionic vibration potential (IVP) and the deviation of the RF polarization vector are conjugated, but only in the sense that the power flux density of some physical process "X" responsible for the rotation of the polarization vector is proportional to the square of the electric potential voltage. While the independence of the RF anisotropy appearance from the applied voltage and from the Debye potential in particular has been proved experimentally. An equivalent electrical circuit that simulates the observed effects within the solution excited by an acoustic wave is proposed and tested for physical feasibility. Special attention is paid to the basic theory of the ionic vibrational potential, namely, its predictions in the low-frequency range, which contradict both experiment and the energy conservation law. Given the futility of describing the "memory" effect as a process of electrical or molecular origin, several arguments are presented in favor of the fluid-gyroscopic mechanism. It was suggested that the rotation of the polarization vector of the RF signal is due to a change in the electric moment of the liquid atoms and/or the nuclear moment of ions having an odd mass number. The applications of the research are also supplemented. The results of new experiments show that the RF anisotropy of the solution is transported by the carrier. Accordingly, it is possible to create a completely contactless unitary sensor of velocity and inhomogeneities of the liquid, moreover, the experimental setup has previously confirmed the affordability of the idea.

The expanding use of devices emitting Pulsed Telecommunication Signals (PTS) has launched a serious debate over the possible effects of electromagnetic radiation (EMR) on living organisms. Our previous work has indicated that PTS exposure alters Amyloid Precursor Protein (APP) and alpha-synuclein (α-syn) metabolism in human cells of neural origin, providing a possible connection between exposure and neurodegeneration. This investigation aimed to reveal, in vitro in human non-neural cells (HEK293), the aftermath of the same exposure on the processing of APP and α-syn. Data presented here, indicate changes in APP metabolism, acquisition of different cellular topologies of the newly generated APP fragments, changes in monomeric α-syn accumulation and multimerization, indicating that APP and α-syn processing is possibly altered in the periphery by EMR. These effects are accompanied by a substantial increase in the levels of Reactive Oxygen Species (ROS). Further investigation is required in order to provide insights into the interaction of PTS with non-neural cells affecting the peripheral systemic functional stability. This is necessary because nowadays whole body human exposure from various EMR sources is a fact in normal life with the valid estimation that they may be increased in view of the forthcoming 5G telecommunications network implementation.

Zero-rate output (ZRO) drift induces deteriorated micro-electromechanical system (MEMS) gy-roscope performances, severely limiting its practical applications. Hence, it is vital to explore an effective method toward ZRO drift reduction. In this work, we conduct an elaborate investigation on the impacts of the internal and packaging stresses on the ZRO drift at the thermal start-up stage, and propose a temperature-induced stress release method to reduce the duration and magnitude of ZRO drift. Self-developed high-Q dual mass tuning fork gyroscopes (TFGs) are adopted to study the correlations between temperature, frequency and ZRO drift. Furthermore, a rigorous finite element simulation model is built based on the actual device and packaging structure, revealing the temperature and stresses distribution inside TFGs. Meanwhile, the relationship between temperature and stresses are deeply explored. Moreover, we introduce a temperature-induced stress release process to generate thermal stresses and reduce the temperature-related device sensitivity. By this way, the ZRO drift duration is drastically reduced from ~2000 s to ~890 s, and the drift magnitude decreases from ~0.4 °/s to ~0.23 °/s. This stress release method achieves a small bias instability (BI) of 7.903 °/h and a low angle random walk (ARW) of 0.792 °/√h, and the long-term bias performance is significantly improved.

This paper discusses a MEMS switch that can be fabricated using low temperature (<100^oC) deposition and patterning techniques suitable for the back-end-of-the-line integration with CMOS. The resulting cross-bar switches can be used for electrostatic discharge protection, FPGA implementation, chip security assessment and lock-down, and circuit block power management. We discuss platinum and iron switch with turn-on voltages of ~ 1.8 V. In the case of the iron switches, we also show that they can be magnetized to have “memory” and stay on when turned on. Platinum switch cycling of up to 1000 times did not show any changes in their turn-on voltage and their contact resistance was unchanged. The 10-100 nm switch airgaps were formed using low temperature sputtered sacrificial polysilicon and XeF₂ etching. XeF₂ does not attack any of the metals used in CMOS enabling fabrication of cross-bar switches with any of these metals. Once activated, it takes ∿ 6 to mechanically turn on the switch that can be decreased to ~1 ns by optimizing the device structure. Interestingly, the nm-scale gaps can be used as spark gap as a fast plasma switch to discharge first followed by the activation of the MEMS switch.

Geological disposal facilities for radioactive waste pose significant challenges for robust monitoring of environmental conditions within the engineered barriers that surround the waste canister. Temperatures are elevated, due to the presence of heat generating waste, relative humidity varies from 20% to 100%, and swelling pressures within the bentonite barrier can typically be 2-10 MPa. Here, we test the robustness of a bespoke design MEMS sensor-based monitoring system, which we encapsulate in polyurethane resin. We place the sensor within an oedometer cell and show that despite a rise in swelling pressure to 2 MPa, our relative humidity (RH) measurements are unaffected. We then test the sensing system against a traditional RH sensor, using saturated bentonite with a range of RH values between 50% and 100%. Measurements differ, on average, by 2.87% RH, and are particularly far apart for values of RH greater than 98%. However, bespoke calibration of the MEMS sensing system using saturated solutions of known RH, reduces the measurement difference to an average of 1.97% RH, greatly increasing the accuracy for RH values close to 100%.

We propose a new methodology for long-time biopotential recording based on MEMS multisensor integrated platform featuring a commercial electrostatic charge transfer sensor. That family of sensors was originally intended for presence tracking in automotive, so the existing setup has been engineered for the acquisition of electrocardiogram, electroencephalogram, electrooculogram and electromyography, designing a dedicated front-end and writing a proper firmware for the specific application. Systematic tests on controls and nocturnal acquisitions from patients in domestic environment will be discussed in detail. The excellent results candidate this technology to provide a low power, unexplored solution to biopotentials acquisition. The technology breakthrough is in that it enables adding this type of functionality to existing MEMS boards at near-zero additional power consumption. For these reasons, they open to additional possibilities for wearable sensing and strengthen the role of MEMS technology in medical wearable applications for long time synchronous acquisition of a wide range of signals.

Background: Sensor usage in the classical scientific process has allowed new experimentation in medicine. We report on the design process of a MEMS sensor being used for muscle trauma evaluation in diagnosing acute compartment syndrome (ACS), a medical ailment costing society billions of dollars per year. Objectives: Modeling the disease with scientific process allows a more complete under-standing of the disease. The goal was to formulate a hypothesis that could be tested to aid in making the diagnosis of ACS accurately. Methods: Scientific process was observed throughout the disease modelling process. Background information was improved and clarified, new pre-clinical models were de-signed and verified, a hypothesis built on pressure measurement with MEMS sensors was carried out, and the testing of the model as verified against previous clinical data was accomplished. Results: Scientific process resulted in hypothesis generation around the relationship of intracompartmental pressure measurement and the disease process and therapy. This resulted in new understanding of ACS, accurate modelling, and sensor design resulting in a MEMS device that has an extremely high sensitivity and specificity (over 99%) in treating and diagnosing the disease. Conclusion: MEMS sensor technology defines the new gold standard of implanting a sensor in a muscle compartment that allows accurate diagnosis of ACS with continuous trends in pressure.

The work is devoted to the study of a MEMS resonator dynamics under the action of phase-locked and automatic gain control loops. Particular attention is directed to the study of the nonlinearity factor of the resonator elastic restoring force. It was found that the determination of control system parameters based on the stability analysis of the operating resonant mode, in the general case, does not provide the required phase adjustment and stabilization of the oscillation amplitude. Stable multifrequency modes of oscillations are found, an analytical study of the mechanisms of their appearance and evolution is carried out under variation of the key parameters of the system. The real regions of the control system stable operation are determined (which do not coincide, as was found, with the regions of stability of the operating resonant mode, due to the presence of hidden attractors in the phase space of the system). A methodology has been developed for identifying such areas of stable operation. A significant complication of the structure of possible motions in the system with an increase in the Q-factor of the resonator is revealed.

We investigated layered titanium nitride (TiN) and aluminum nitride (AlN) for color glasses in Building Integrated Photovoltaic (BIPV) systems. AlN and TiN are among suitable and cost-effective optical materials to be used as thin multilayer films, owing to the significant difference in their refractive index. To fabricate the structure, we used radio frequency magnetron deposition method to achieve the target thickness uniformly. A simple, fast, and cheap fabrication method is achieved by depositing the multilayer films in a single sputtering chamber. It is demonstrated that a multilayer stack that allows light to move from a low refractive index layer to a high refractive index layer or vice-versa can effectively create various distinct color reflections for different film thicknesses and multilayer structures. It is investigated from simulation based on wave optics that, TiN/AlN multilayer offers better color design freedom and cheaper fabrication process as compared to AlN/TiN multilayer films. Blue, green, and yellow color glasses with optical transmittance of more than 80% was achieved by ITO coated glass/TiN/AlN multilayer films. This technology exhibits good potential in commercial BIPV system applications.

This paper presents tea leaves moisture monitoring system based on RF reflectometry techniques. The system was divided into two parts which are the sensor and reflectometer parts. The large coaxial probe was used as a sensor of the system. The reflectometer part plays a role as signal generator and also data acquisition. The reflectometer-sensor system was operated with a graphical user interface at 1.529 GHz at room temperature. The system was able to measure the moisture content of tea leaves ranging 0% m.c to 50% m.c on a wet basis. In this study, up to five kinds of tea leaves bulk were tested. The mean of absolute errors in the moisture measurement for tea leaves was ±2.

Thermal processing of Zr-loaded ion-exchangers is a facile route to synthetize (ZrO2, ZrC)@C composites. The chemical character of the functional groups in the cation exchanger is an essential factor in the composition and properties of the (ZrO2, ZrC)@C composites. In the present paper furnace and RF-thermal plasma processing of ZrOCl2 loaded thiourea-functionalized styrene-divinylbenzene copolymer was investigated that led to various composites containing ZrO2 and ZrC. Depending on the synthesis conditions, different ZrO2@C composites were formed between 1000 and 1400 °C in 2 h, whereas the composite containing ZrC was created at 1400 °C in 8 h. The ratio of ZrO2/ZrC, the prevailing ZrO2 modifications, and the crystallite sizes strongly depend on the synthesis conditions. The ZrC-containing composites formed only at 1400 °C in 8 hours and by the plasma treatment of the ZrO2@C sample prepared in the furnace, resulting in 8 and 16% ZrC content, with 44 and 41 nm ZrC crystallite sizes, respectively. The ZrO2-containing composites (tetragonal, monoclinic, and cubic modifications with 65–88 nm ZrO2 crystallite sizes and 15–43 m2/g BET surface areas, depending on the carbonization temperature) formed in a tube furnace between 1000 and 1400 °C in 2 h. The tube furnace–prepared sample formed at 1400 °C in 8 h contained ZrC, ZrO2 modifications, and amorphous carbon, whereas the plasma-treated sample contained ZrC, ZrO2 modifications, and graphite. All ZrO2@C composites had both amorphous carbon and graphite, and their ratio is temperature-dependent. The carbonaceous compounds of the prepared composites were characterized by Raman spectroscopy, with analysis of the G and D band intensities. XPS studies showed the surface oxidation of ZrC.

In the paper the experimental methodology for the single-crystal circular plate deformation measurement and subsequent procedure for mechanical properties quantitation are developed. The procedure is based on a new numerical-analytical solution of nonlinear boundary-value problem for finite deformations of a circular anisotropic plate. Using the developed method, a study of the deformation of single-crystal circular plates formed on the basis of a silicon-on-insulator structure was carried out. The values of residual stresses are determined and it is shown that the presence of these stresses increases the flexural rigidity of the plate in several times.

The use of sensors in monitoring of lateral accelerations in delivery van transport focuses on measuring lateral accelerations on routes with roundabouts and curves to increase road safety. Using microelectromechanical system (MEMS) sensors, it measures the lateral accelerations acting on the vehicle and the load being transported during the test drives to study vehicle dynamics for cargo securing. Using an accelerometer and position tracking, accelerations can be detected when traversing curves and roundabouts at selected locations on the vehicle. The level of accelerations on the roof of the vehicle was found to be like those occurring on a lashed load with limited movements, where regression analysis can be used to determine the relationship between lateral accelerations at different sensor positions. If we compare the mean values of the lateral accelerations of the individual events between the sensors, the sensor on the side of the vehicle body at the height of the sensor on the load had approximately 5% lower mean values than the sensor on the roof. The sensor on the load measured approximately 5% higher mean values than the sensor on the roof. Hence, the mean lateral accelerations of the individual events for the sensor on the load are 10% higher than for the sensor at the same height on the vehicle body. From the above testing, we can say that the values of the mean lateral accelerations of the van from the sensor on the roof of the vehicle, are closer to the values of the accelerations of the sensor on the load than to the values of the sensor on the body of the vehicle at the same height.

Structural health monitoring of lightweight constructions made of composite materials can be performed using guided ultrasonic waves. If modern fiber metal laminates are used, this requires integrated sensors that can record the inner displacement oscillations caused by the propagating guided ultrasonic waves. Therefore, we have developed a robust MEMS vibrometer that can be integrated with structural and functional compliance. This vibrometer is directly sensitive to the high-frequency displacements from structure-borne ultrasound when excited between its first and second natural frequency. The vibrometer is mostly realized by processes earlier developed for a pressure sensor but with additional femtosecond laser ablation and wafer bonding. The piezoresistive transducer made from silicon is encapsulated between top and bottom glass lids. The natural frequencies are experimentally determined using an optical micro vibrometer setup. The vibrometer functionality and usability for structural health monitoring are demonstrated on a customized test rig by recording application-relevant guided ultrasonic wave packages with a central frequency of 100 kHz at a distance of 200 mm from the exciting ultrasound transducer.

Experimental evidence showed how various complex systems, characterized by a fluctuation scaling, satisfy the well-known Taylor's law. The present work aims to apply for the first time Taylor's law, given its general treatment, for a flow field at $Re$ around $10^4$, since activity of each fluid particle is highly fluctuating, especially in the context of vortex shedding. In addition, the further element of innovation is the use of an innovative thin-films based device consisting of an elastic piezoelectric flapping flag that is proposed as a measuring instrument of the flow field. The oscillations of the flapping flag, due to the vortexes release downstream to an obstacle of cylindrical shape, generate an alternating piezoelectric voltage whose time history is similar to the chaotic components of the fully developed turbulent speed. Preliminary experimental results about the use of thin-films based device in a flume channel are reported together with a second order analysis on the voltage difference and a scaling law of the exponent scale.

In the framework of 2D circular membrane Micro-Electric-Mechanical-Systems (MEMS), a new non-linear second-order differential model with singularity in the steady-state case is presented in this paper. In particular, starting from the fact that the electric field magnitude is locally proportional to the curvature of the membrane, the problem is formalized in terms of the mean curvature. Then, a result of existence of at least one solution is achieved. Finally, two different approaches prove that the uniqueness of the solutions is not ensured.

Space–air–ground integrated network (SAGIN) is considered as an enabler for the sixth-generation (6G) networks. By integrating terrestrial and non-terrestrial (satellite, aerial) networks, SAGIN seem to be a quite promising solution to provide reliable connectivity everywhere and all the time. Their availability can be further enhanced if hybrid free space optical (FSO)/radio frequency (RF) links are adopted. In this paper, the performance of a hybrid FSO/RF communication system operating in SAGIN has been analytically evaluated. In the considered system, a high altitude platform station (HAPS) is used to forward the satellite signal to the ground station. Moreover, the FSO channel model assumed takes into account the turbulence, pointing errors and path losses, while for the RF links, a relatively new composite fading model has been considered. In this context, a new link selection scheme has been proposed that is designed to reduced the signaling overhead required for the switching operations between the RF and FSO links. The analytical framework that has been developed is based on the Markov chain theory. Capitalizing on this framework, the performance of the system has been investigated using the criteria of outage probability and the average number of link estimations. The numerical results presented reveal that the new selection scheme offers a good compromise between performance and complexity.

Wireless power transfer promises to revolutionize the way we use and power mobile devices. However, low transfer efficiencies prevent this technology from seeing wide scale real-world adoption. The aim of this work is to use quasioptics to develop a system composed of a dielectric lens fed by a phased array to reduce spillover losses, increasing the beam efficiency, while working on the antenna system’s Fresnel zone. The DC-RF electronics, digital beamforming and beam-steering by an FPGA, and radiating 4x4 microstrip patch phased array have been developed and experimented upon, while the lens has been designed and simulated. This paper details these preliminary results, where the phased array radiation pattern was measured, showing that the beam is being generated and steered as expected, prompting the lens construction for the complete system experimentation.

IoT system becomes hot topic nowadays for smart home, IoT helps devices to communicate together without human intervention inside home, so it is offering many challenges. A new smart home IoT platform powered using electromagnetic energy harvesting is proposed in this paper. It contains a high gain transmitted antenna array and efficient circular polarized array rectenna system to harvest enough power from any direction to increase life time of the batteries used in IoT system. Optimized energy consumption, the software with adopting the Zigbee protocol of the sensor node and low power microcontroller are used to operate in lower power modes. The proposed system has an 84.6 days lifetime which is approximately 10 times the lifetime for similar system. On the other hand, the proposed power management circuit operated at 0.3 V DC to boost the voltage to ~3.7V from radio frequency energy harvesting and manage battery level to increase the batteries lifetime. A predictive indoor environment monitoring system is designed based on a novel hybrid system to provide a non-static plan, approve energy consumption and avoiding failure of sensor nodes in smart home.

In the past few years, the possibility to transfer power wirelessly has experienced growing interest from the research community. Since the wireless channel is subject to a large number of random phenomena, a crucial aspect is the statistical characterization of the energy that can be harvested by a given device. For this characterization to be reliable, a powerful model of the propagation channel is necessary. The recently proposed Generalized-K model has proven to be very useful, as it encompasses the effects of path-loss, shadowing and fast fading for a broad set of wireless scenarios, and it is analytically tractable. Accordingly, the purpose of this paper is to characterize, from a statistical point of view, the energy harvested by a static device from an unmodulated carrier signal generated by a dedicated source, assuming that the wireless channel obeys the Generalized-K propagation model. Specifically, using simulation-validated analytical methods, this paper provides exact closed-form expressions for the average and variance of the energy harvested over an arbitrary time period. The derived formulation can be used to determine a power transfer plan that allows multiple or even massive numbers of low-power devices to operate continuously, as expected from future network scenarios such as IoT or 5G/6G.

Imaging lidars are one of the hottest topics in the optronics industry. The need to sense the surroundings of every autonomous vehicle has pushed forward a career to decide the final solution to be implemented. The diversity of state-of-the art approaches to the solution brings, however, a large uncertainty towards such decision. This results often in contradictory claims from different manufacturers and developers. Within this paper we intend to provide an introductory overview of the technology linked to imaging lidars for autonomous vehicles. We start with the main single-point measurement principles, and then present the different imaging strategies implemented 8 in the different solutions. An overview of the main components most frequently used in practice is also presented. Finally, a brief section on pending issues for lidar development has been included, 10 in order to discuss some of the problems which still need to be solved before an efficient final implementation.Beyond this introduction, the reader is provided with a detailed bibliography containing both relevant books and state of the art papers.

In order to meet the military requirements of the fuze, such as precision strike, efficient mutilates ability and low collateral damages, the microminiaturization is an inevitable trend of secure system. Based on the silicon-based MEMS S&A device designed by our term, the design principles of each module and fabrication process are introduced. The average fracture strength and Young's modulus of the silicon are 726 MPa and 175 GPa from the tensile test, respectively. From Hopkinson impact experiment, we can get the threshold-value judging mechanism being safety under the impact overload of 20526 g, and this value is much more than the standard of the drop overload 12000g; the arming value under the centrifugal overload obtained from theory, simulation and experiment is at the range of 28200 g and 32000 g, it shows that the threshold-value judging mechanism can be arming compared with the value 35951g of design principle. Therefore, the threshold-value judging mechanism can meet the design requirements of overload. Furthermore, the relationship of fracture threshold-values obtained by different theories is found out through parametric design method, as shown in Figure 14, it provides the theory evidence to the follow parametric design.

In recent years, computer-aided analysis techniques have emerged as valuable tools in assisting dermatologists by providing objective and efficient analysis of skin cancer images. This paper utilizes the combination of the Contourlet Transform (CT) and Local Binary Pattern (LBP) techniques for accurately recognizing borders, contrast changes, and shapes of skin cancer images. These results often contain many features, leading to high computational costs and potential over-fitting issues. Hence, we applied Particle Swarm Optimization (PSO) to select the most informative and discriminating features, reducing the dimensionality while retaining important information for accurate classification. After reducing the feature set with PSO, we applied these sets to Machine learning classification algorithms: Support Vector Machine (SVM), Random Forest (RF), and Neural Networks (NN). The results show that SVM has the lowest time complexity of 0.0458 seconds, followed by the Neural Network at 0.08730 seconds, and the Random Forest model has the highest time complexity of 0.1622 seconds. The SVM and Neural Network models are faster to train than the Random Forest model, making them more suitable for real-time or latency-sensitive applications. We also compared our proposed model with the state-of-the-art models and obtained the accuracy of 86.9%, which is the highest among the models.

The goal of this paper is to present a low-cost, low-power prototype of a pulsed Ultra Wide Band UWB) oscillator and an UWB elliptical dipole antenna integrated on the same Radio Frequency (RF) Printed Circuit Board (PCB) and its digital control board for Real Time Locating System (RTLS) applications. The design is compatible with IEEE 802.15.4 high rate pulse repetition UWB standard being able to work between 6 GHz and 8.5 GHz with 500 MHz bandwidth and with a pulse duration of 2 ns. The UWB system has been designed using the CST Microwave Studio transient Electro-Magnetic (EM) circuit co-simulation method. This method integrates the functional circuit simulation together with the full wave (EM) simulation of the PCB’s 3D model allowing fast parameter tuning. The PCB has been manufactured and the entire system has been assembled and measured. Simulated and measured results are in excellent agreement with respect to the radiation performances as well as the power consumptions.

Abstract: The Micro-Electro-Mechanical System (MEMS) LiDAR point cloud in autonomous vehicles has a large deflection range, which results in slow registration speed and poor applicability. To maximize speed, an improved NDT (Normal Distribution Transform) method that integrates point cloud density features has been proposed. First, the point cloud is reduced using a modified voxel filter and a pass-through filter. Next, the ISS (Intrinsic Shape Signature) algorithm is utilized to analyze the point cloud features and extract keypoints, the 4PCS (4-Point Congruent Sets) algorithm is then employed to calculate the initial pose under the constraints of the keypoint set to complete the coarse registration. Finally, the self-adaptive segmentation model is constructed by using KD-tree to obtain the density features of keypoints, and the NDT algorithm is combined with this model to form an SSM-NDT algorithm, which is used for fine registration. Each algorithm was compared on the autonomous vehicle dataset PandaSet and actual collected data sets, the results show that the novel method increases the speed by at least 60% and takes into account good registration accuracy and strong anti-interference.

This article develops algorithms for the characterization and the visualization of micro-scale features by using a small number of sample points, and with a goal to mitigate for the measurement shortcomings which are often destructive or time consuming. We implement the algorithms to rapidly examine the microscopic features of a Microelectromechanical System (MEMS) surface. Such images are highly dense; therefore, traditional image processing techniques might be computationally expensive. The contribution of this research include first, we develop local and global algorithm based on modified Thin Plate Spline (TPS) model to reconstruct high resolution images of the micro-surface’s topography, and its derivatives by using low resolution images. Second, we obtain a bending energy algorithm from our modified TPS model, and use it to filter out image defects. Finally, we develop a computationally efficient Windowing technique, which combines TPS and Linear Sequential Estimation (LSE), to enhance the visualization of images. The Windowing technique allows rapid image reconstruction based on the reduction of inverse problem.

Since 2007, at the Electron Science Research Institute (ESRI) nano-fabrication laboratories, Edith Cowan University, Australia, we have devoted research efforts to the synthesis and characterization of bismuth-containing ferrite-garnet-type thin-film magneto-optic (MO) materials of different compositions. We report on the development and properties of highly bismuth-substituted iron-garnet thin films prepared by using radio frequency (RF) magnetron sputtering. We study the process parameters associated with the RF magnetron sputter deposition technique and investigate the results of optimizing process parameters and implementing several special techniques including the fabrication of co-sputtered nanocomposite films, all-garnet multilayer structures, applying oxygen plasma treatment on amorphous garnet layers just after the deposition process, and designing modifications of the annealing crystallization process and regimes for achieving the best MO properties. We demonstrated significant improvement in MO properties of Bi-containing ferrite-type garnet thin-film materials, including record-high MO figures of merit and improved conventional and un-conventional hysteresis loops of Faraday rotation. The attractive optical, magnetic, and magneto-optic properties obtained in highly bismuth-substituted iron garnet thin-film materials of multiple composition types are relevant in the context of manufacturing next-generation ultra-fast optoelectronic devices, such as light intensity switches and modulators, high-speed flat panel displays, and high-sensitivity sensors.

This paper presents a demonstration of the feasibility of fabricating micro-cantilever harvesters with extended stress distribution and enhanced bandwidth by exploiting an M-shaped two-degrees-of-freedom design. The measured mechanical response of the fabricated device displays the predicted dual resonance peak behavior with the fundamental peak at the intended frequency. This design has the features of high energy conversion efficiency in a miniaturized environment where the available vibrational energy varies in frequency. It makes such a design suitable for future large volume production of integrated self powered sensors nodes for the Internet-of-Things.

The identification of informal settlements in urban areas is an important step in developing and implementing pro-poor urban policies. Understanding when, where and who lives inside informal settlements is critical to efforts to improve their resilience. This study aims to analyse the capability of machine-learning (ML) methods to map informal areas in Jeddah, Saudi Arabia, using very-high-resolution (VHR) imagery and terrain data. Fourteen indicators of settlement characteristics were derived and mapped using an object-based ML approach and VHR imagery. These indicators were categorised according to three different spatial levels: environ, settlement and object. The most useful indicators for prediction were found to be density and texture measures, (with random forest (RF) relative importance measures of over 25% and 23% respectively). The success of this approach was evaluated using a small, fully independent validation dataset. Informal areas were mapped with an overall accuracy of 91%. Object-based ML as a hybrid approach performed better (8%) than object-based image analysis alone due to its ability to encompass all available geospatial levels.

In this study, the degradation characteristics of radio-frequency (RF) low-noise amplifier (LNA) based on silicon-germanium (SiGe) heterojunction bipolar transistors (HBTs) due to total ionizing dose (TID) are investigated. The small-signal equivalent model of a SiGe HBT is utilized to analyze circuit-level performance including the input and the output matching and noise figure (NF). As a target circuit, an LNA with a cascode common-emitter stage with emitter degeneration is studied and the equation of each performance parameter is derived. The RF LNA fabricated using commercial 350 nm SiGe technology was exposed to X-ray irradiation with the total dose up to 3 Mrad (SiO2). The experimental results exhibit that modeled device parameters estimate the degraded circuit performance. In addition, the relative impact of each parameter on the circuit metrics is revealed, which is expected from the derived design equations. The key device parameters for modeling TID-induced circuit degradations include the base resistance, the transconductance, and the base-to-emitter capacitance.

Tree species composition is an important key element for biodiversity and sustainable forest management, and hyperspectral data provide detailed spectral information, which can be used for tree species classification. There are two main challenges for using hyperspectral imagery: a) Hughes phenomena, meaning by increasing the number of bands in hyperspectral imagery, the number of required classification samples would increase exponentially, and b) in a more complex environment, such as riparian mixed forest, focusing on spectral variability per pixel may not be adequate for definability of tree species. Therefore, the focus of this study is to assess spectral-spatial dimensionality reduction of airborne hyperspectral imagery by using minim noise fraction (MNF) transformation, and object-based image analysis (OBIA). An airborne prism experiment (APEX) hyperspectral imagery was used. A study area was a riparian mixed forest located along the Salzach river, and six tree species including Picea abies, Populus (canadensis and balsamifera), Fraxinus excelsior, Alnus incana, and Salix alba were selected. A machine learning algorithm random forest (RF) was used to train and apply a prediction model for classification. Using a spectral dimensionality reduced APEX, a pixel-level classification was also done. According to a confusion matrix, the object-level classification of MNF-derived components achieved the overall accuracy of 85 %, and kappa coefficient of 0.805. The performance of classes according to producer’s accuracy varied between 80% for Fraxinus excelsior, Alnus incana, and Populus canadensis to 90% for Salix alba and Picea abies. Comparison the results to a pixel-level classification, showed a better performance of object-level classification (an overall accuracy of 63% and Kappa coefficient of 0.559 were achieved for pixel-level classification). The performance of classes using pixel-based classification varied 45 % for Alnus incana to 80% for Picea abies. In general, Spectral-spatial complexity reduction using MNF transformation and object-level classification yielded a statistically satisfactory results.

A developed six-port reflectometry (SPR) system was integrated to measure the relative permittivity of tumor and normal breast tissue for medical diagnostic purpose. In order to obtain an accurate and precise measurement, the calibration process was done to the SPR using the well-known three-standard technique. Next, the studied dielectric probe was connected to the calibrated measurement-port of the SPR. The open end of the probe aperture was dibbed into the normal and tumor synthetic breast tissue samples to measure the synthetic breast tissues dielectric constant, ɛrʹ, and loss factor, ɛrʺ in the frequency range of 1.5 GHz to 3.3 GHz. Finally, the comparative studies were conducted between commercial VNA with Keysight 85070E dielectric probe and the studied SPR-probe system based on the measured magnitude of the reflection coefficient, phase shift, dielectric constant, and loss factor of the synthetic breast samples. The maximum absolute errors of the measured reflection coefficient magnitude, phase shift, dielectric constant, and loss factor were found to be 0.01, 1.07°, 1.12, and 0.75, respectively. It was ascertained that the predicted dielectric constant, ɛrʹ, is able to differentiate between normal, (ɛrʹ &lt; 50) and tumor, (ɛrʹ &gt; 50) breast tissues.

Exercise-based cardiac rehabilitation requires patients to perform a set of certain prescribed exercises a specific number of times. Local muscular endurance (LME) exercises are an important part of the rehabilitation program. Automatic exercise recognition and repetition counting, from wearable sensor data is an important technology to enable patients to perform exercises independently in remote settings, e.g. their own home. In this paper we first report on a comparison of traditional approaches to exercise recognition and repetition counting, corresponding to supervised machine learning and peak detection from inertial sensing signals respectively, with more recent machine learning approaches, specifically Convolutional Neural Networks (CNNs). We investigated two different types of CNN: one using the AlexNet architecture, the other using time-series array. We found that the performance of CNN based approaches were better than the traditional approaches. For exercise recognition task, we found that the AlexNet based single CNN model outperformed other methods with an overall 97.18% F1-score measure. For exercise repetition counting , again the AlexNet architecture based single CNN model outperformed other methods by correctly counting repetitions in 90% of the performed exercise sets within an error of ±1. To the best of our knowledge, our approach of using a single CNN method for both recognition and repetition counting is novel. In addition to reporting our findings, we also make the dataset we created, the INSIGHT-LME dataset, publicly available to encourage further research.

This article reviews recent innovations in piezoelectric actuators, then indicates the future research targets. In the materials, the piezoelectric performances of relaxor-lead titanate (PZN-PT, PMN-PT) single crystals have been improved significantly by an AC electric poling technique. Also new loss characterization techniques facilitate developing high-power density piezoelectrics. The RMS vibration velocity reaches 0.6 m/s in the k₃₁ mode in lead zirconate titanate (PZT) nowadays, which corresponds to power density 30 W/cm³. Pb-free materials are urged due to the recent political regulation on toxic materials. In device designs, the original multilayer actuators (MLA) with Ag/Pd electrode have been switched to the ones with Cu or pure Ag, in order to suppress the heat generation, then to enhance the device power density. Piezoelectric micro-electro-mechanical-systems (MEMS’s) started to utilize the <1 0 0> oriented epitaxial films of rhombohedral PZT compositions, which exhibits enhanced piezoelectric properties. Also for higher-power applications, aero-sol deposition (AD) methods have been introduced to 10 -thick films. Regarding drive/control techniques in piezo-actuators, three developments are on-going, that is, “negative capacitance” power supplies for driving off-resonance (pseudo-DC) piezo-actuators, capacitive AC power supplies for efficiently driving resonance piezo-actuators, and DC/DC converters for harvesting electric energy from high-impedance piezoelectric devices under noise vibration. The applications of piezoelectric actuators in the 21^st century seem to be oriented toward “politico-engineering” with four keywords, “cooperation, protection, reduction, and continuation”. The sustainability technologies include the following piezoelectric items: (a) Pb-free piezoelectrics, (b) ultrasonic technology for decomposing hazardous materials, (c) reduction of contamination gas, (d) piezoelectric energy harvesting, and (e) device improvement with high energy-efficiency. On the other hand, the following crisis technologies have been developed with piezoelectrics: (a) detection and neutralization technologies of infectious/epidemic diseases such as anthrax, (b) autonomous unmanned underwater, aerial, and land vehicles with piezoelectric actuators, (c) pin-point target weapons, (d) high voltage supplies with piezoelectric transformers, and (e) compact energy sources for remote actuating/sensing systems.

Software project estimating (SPE) is a powerful but necessary step in the production of projects for software. Software project estimating includes several components, estimating software time, software resources, software costs, and software effort estimation (SEE). SEE seeks to estimate the number of "hours-person" and "months-person" of work required for developing or managing a software program. During the initial phase of the development of software, future efforts are impossible to predict. To estimate effort, many deep learning (DL) and machine learning (ML) models were previously created. For estimate, single-model techniques and ensemble methods were investigated in this research. Ensemble methods involve a combination of multiple separate models. Bagging, boosting, and voting were the ensemble methods looked into for estimation. Datasets considered for estimation were COCOMO81, COCOMONasa I, COCOMONasa II, Albrecht, Maxwell, China, Desharnais, Desharnais_1_1, Kitchenham, Boehm, and Belady. The evaluation criteria used MAE, RAE, RMSE, RRSE, and CC. The result from previous studies is that the total size of the set of data utilized is small in predicting the effort, as the largest size of the set of data used is the China dataset containing only 499 projects. So, in this study, the dataset has been merged to increase the total size of the set of data and increase the accuracy of prediction. The results indicated that the suggested merged dataset increased effort estimation accuracy.

Structural health monitoring (SHM) is critical for ensuring the safety of infrastructures like bridges. This article presents a digital twin solution for SHM of railway bridges using low-cost wireless accelerometers and Machine Learning (ML). The system architecture combines edge on-premises computing and cloud analytics to enable efficient real-time monitoring and complete storage of relevant time-history datasets. After train crossings, accelerometers stream raw vibration data, which is processed in the frequency domain and analyzed via machine learning to detect anomalies indicating potential structural issues. The digital twin approach is demonstrated on an in-service railway bridge, where vibration data was collected over two years under normal operating conditions. By learning allowable ranges for vibration patterns, the digital twin model identifies abnormal spectral peaks, suggesting changes in structural integrity. The long-term pilot proves that this affordable SHM system can provide automated and real-time warning of bridge damage and also supports the use of in-house designed sensors of lower-cost and edge computing capabilities than those used in the demonstration. The successful on-premises-cloud hybrid implementation provides a cost effective and scalable model for expanding monitoring to thousands of railway bridges, democratizing SHM to improve safety by avoiding catastrophic failures.

This review article is focused on the analysis of the state of the art of sensors for guided 9 ultrasonic waves for the detection and localization of impacts, therefore of interest for the structural 10 health monitoring (SHM). The recent developments in sensor technologies are then reported and 11 discussed through the many references in recent scientific literature. The physical phenomena re-12 lated to impact event and the main physical quantities are then introduced to discuss their im-13 portance in the development of the hardware and software components for SHM systems. An im-14 portant aspect of the article is the description of the different ultrasonic sensor technologies cur-15 rently present in the literature and what advantages and disadvantages they could bring, in relation 16 to the various phenomena investigated. In this context, the analysis of the front-end electronics is 17 deepened, the type of data transmission both in terms of wired and wireless technology and in terms 18 of online and offline signal processing. The integration aspects of sensors for the creation of net-19 works with autonomous nodes with the possibility of powering through energy harvesting devices 20 and the embedded processing capacity is also studied. Finally, the emerging sector of processing 21 techniques using deep learning and artificial intelligence concludes the review by indicating the 22 potential for the detection and autonomous characterization of the impacts.