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Preprint ARTICLE | doi:10.20944/preprints202306.0459.v1

Car Price Quotes Driven by Data - Comprehensive Predictions Grounded in Deep Learning Techniques

Andreea Dutulescu, Andy Catruna, Stefan Ruseti, Denis Iorga, Vladimir Ghita, Laurentiu Marian Neagu, Mihai Dascălu

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: car price prediction; visual features; cross-market analysis; feature analysis; deep neural networks

Online: 6 June 2023 (12:11:52 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0454.v1

A Deep Learning-Based Automated Framework for Subpeak Designation on Intracranial Pressure Signals

Donatien LEGÉ, Laurent Gergelé, Marion Prud'homme, Jean-Christophe Lapayre, Yoann Launey, Julien Henriet

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: intracranial pressure; cerebral compliance; deep neural networks; recurrent neural networks; convolutional neural networks

Online: 6 June 2023 (11:50:05 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0438.v1

Neuromorphic Dendritic Computation with Silent Synapses for Visual Motion Perception

Eunhye Baek, Sen Song, Zhao Rong, Luping Shi, Carlo Vittorio Cannistraci

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: neuromorphic engineering; neuromorphic computing; dendritic computation; silent synapse; motion perception

Online: 6 June 2023 (10:04:05 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0431.v1

Two-path Multi-behavior Sequence Modeling

Mingyue Qu, Nan Wang, Jinbao Li

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Two-path 1; Multi-Behavior Dependence 2; Contrast Learning 3; Sparse Data 4

Online: 6 June 2023 (09:47:01 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0430.v1

Retrieval-augmented Knowledge Graph Reasoning for Commonsense Question Answering

Yuchen Sha, Yujian Feng, Miao He, Shangdong Liu, Yimu Ji

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Commonsense question answering; Knowledge Graph; Graph Convolutional Network

Online: 6 June 2023 (09:45:47 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0418.v1

A Testing Framework for AI Linguistic Systems (testFAILS)

Yulia Kumar, Patricia Morreale, Peter Sorial, Justin Delgado, J. Jenny Li, Patrick Martins

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: keyword 1; chatbots 2; chatbot validation 3; bots 4; A Testing Framework for AI Linguistic Systems (testFAILS) 5; AIDoctor

Online: 6 June 2023 (08:26:58 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0405.v1

Multus Medium Opinion Mining (MMOM): A Novel Hybrid Deep Learning Approach for Comprehensive Product Review Analysis

Bushra Kanwal, Asif Nawaz, Ghulam Mustafa, Tariq Ali, Muhammad Babar, Basit Qureshi, Anis Koubaa

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Multus Medium; Opinion Mining; Deep Learning; Product Review Analysis; Bidirectional Long Short-Term Memory; Convolutional Neural Network

Online: 6 June 2023 (08:06:40 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0398.v1

Roasted Arabic Coffee Classification Based on Color, Chemical Compositions and Antioxidants Using Machine Learning

Eman S. Alamri, Ghada Altarawneh, Hala M. Bayomy, Ahmad B. Hassanat

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: smart sustainability; smart food; Arabic coffee; classification; color information; antioxi-dant information; chemical composition; mobile application

Online: 6 June 2023 (07:47:58 CEST)

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Preprint REVIEW | doi:10.20944/preprints202306.0395.v1

Deep Learning-based Pose Estimation in Providing Feedback for Physical Movement: a Review

Atima Tharatipyakul, Suporn Pongnumkul

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Pose estimation; Movement assessment; Augmented feedback; Physical movement; Review

Online: 6 June 2023 (07:26:29 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0375.v1

Optimal Combination of Mother Wavelet and AI Model for Precise Classification of Pediatric Electroretinogram Signals

Mikhail Kulyabin, Aleksei Zhdanov, Anton Dolganov, Andreas Maier

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: biomedical research; electroretinography; electroretinogram; ERG; classification; deep learning; cnn; transformer; wavelet; scalogram

Online: 6 June 2023 (04:06:02 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0364.v1

Enhancing Chinese Address Parsing in Low-Resource Scenarios through In-Context Learning

Guangming Ling, Xiaofeng Mu, Chao Wang, Aiping Xu

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Chinese address parsing; low-resource scenarios; In-context learning; GPT; k-nearest neighbors

Online: 6 June 2023 (03:37:27 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0285.v1

Intelligent Identification and Prediction Mineral Resources Deposit Based on Deep Learning

Le Gao, Kun Wang, Xin Zhang, Chen Wang

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Artificial Intelligence; Sustainable development; Deep Learning; Mineral Deposit Prediction; Multi-scale Features; Attention Mechanism

Online: 5 June 2023 (09:05:21 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0186.v1

Age Estimation in Human Gait Extraction using A Combination of Multi-Energy Image with Invariant Moment

Nasser Al Musalhi, Erbuğ Çelebi

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: age estimation; AFDEI; CNN; human gait; neural networks; GEI; invariant moments

Online: 5 June 2023 (08:12:12 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0260.v1

Deep Learning-Based Human Chromosome Classification: Data Augmentation and Ensemble

Mattia D'Angelo, Loris Nanni

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: chromosome classification; convolutional neural networks; ensemble; data augmentation

Online: 5 June 2023 (08:02:04 CEST)

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Preprint REVIEW | doi:10.20944/preprints202306.0243.v1

New Advances in Artificial Intelligence for Biomedical Research and Clinical Decision-Making

Nicolae Iftimia, Raj Pandya, Forest Mahoney

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: AI; artificial intelligence; automation; neural networks; machine learning; deep learning; large language models; biomedical research; imaging; healthcare

Online: 5 June 2023 (05:15:33 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0078.v1

GenCo: A Generative Learning Model for Heterogeneous Text Classification Based on Collaborative Partial Classifications

Zie Eya Ekolle, Ryuji Kohno

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Natural language processing; text classification; probabilistic models; machine learning; generative learning; collaborative learning; explainable AI

Online: 5 June 2023 (02:57:36 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0223.v1

Enhancing Voice Cloning Quality through Data Selection and Alignment-based Metrics

Ander González Docasal, Aitor Álvarez

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Voice Cloning; Speech Synthesis; Speech Quality Evaluation

Online: 5 June 2023 (02:27:49 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0200.v1

Development and Performance of a Fuzzy Logic Control System for the Root-to-Shoot Ratio in an Aeroponics System for Lettuce

Jianmin Gao, Yinan Guo, Mazhar H. Tunio, Jiedong Chen

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Aeroponics; Fuzzy control; sensors; Root-shoot ratio; Lettuce

Online: 2 June 2023 (11:58:58 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0196.v1

Ethical Challenges in the Development of Virtual Assistants Powered by Large Language Models

Andrés Piñeiro-Martín, Carmen Garcia-Mateo, Laura Docío-Fernández, María del Carmen López Pérez

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: ethical challenges; virtual assistants; Large Language Models; ethical AI; ethical guidelines; data privacy; bias mitigation; public services; AI regulation

Online: 2 June 2023 (11:53:26 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0152.v1

Fine-Grained Image Recognition by Integrating Transformer Encoder Blocks in a Robust Single Stage Object Detector

Usman Ali, Seungmin Oh, Tai-Won Um, Minsoo Hann, Jinsul Kim

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Fine-grained Image Recognition; Yolov5; Transformer Encoder Block; Attention Mechanism

Online: 2 June 2023 (08:09:14 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0134.v1

An Intelligent Bat Algorithm for Web Service Selection with QoS Uncertainty

Abdelhak ETCHIALI, Amina BEKKOUCHE, Fethallah HADJILA

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Web service selection; QoS uncertainty; Bat algorithm; Service-oriented computing

Online: 2 June 2023 (05:09:15 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0125.v1

The Development of Peanut Defect Detection Technique Using Hyperspectral Images

Shih-Yu Chen, Yung-Ming Kuo, Rui-Hong Zhang, Tsai-Yi Cheng, Po-Yu Chu, Li-Wei Kang, Chinsu Lin

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Hyperspectral; Deep Learning; Peanuts; Band selection

Online: 2 June 2023 (04:19:23 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0085.v1

Predicting Groundwater Levels at Colorado State of USA Using ARIMA and ANN Models

Hifsa Ghafoor, Rahila Umer, Jan Muhammad, Zahid Rauf, Fatima Ali, Muhammad Naeem Shahwani

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Machine Learning; Groundwater Level; Auto-Regressive Integrated Moving Average; Artificial Neural Network; Data-Driven Models

Online: 1 June 2023 (12:13:24 CEST)

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Preprint REVIEW | doi:10.20944/preprints202306.0042.v1

Principles of Artificial Neural Networks and Machine Learning for Bioinformatics Applications

Konstantinos Krampis, Eric Ross, Olorunseun Ogunwobi, Grace Ma, Raja Mazumder, Claudia Wultsch

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: machine learning; artificial intelligence; bioinformatics; cancer biology; neural networks; sym-metry; group theory; algorithms

Online: 1 June 2023 (07:12:16 CEST)

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Preprint REVIEW | doi:10.20944/preprints202306.0036.v1

Computer-Aided Bleeding Detection Algorithms for Capsule Endoscopy: A Systematic Review

Ahmmad Musha, Rehnuma Hasnat, Abdullah Al Mamun, Em Poh Ping, Tonmoy Ghosh

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Bleeding Classification; Bleeding Detection; Bleeding Recognition; Bleeding Segmentation; Capsule Endoscopy; Wireless Capsule Endoscopy

Online: 1 June 2023 (05:21:04 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0102.v2

Global and Local Knowledge Distillation Method for Few-Shot Classification of Electrical Equipment

Bojun Zhou, Jiahao Zhao, Chunkai Yan, Xinsong Zhang, Juping Gu

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: few-shot classification; electrical equipment images; knowledge distillation

Online: 1 June 2023 (04:39:38 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.2220.v1

A Source Seeking Method for the Implicit Information Field Based on a Balanced Searching Strategy

Kun Liu, Yang Bi, Qi Zhang, JunFang Li

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Source Seeking; Biological Homing Behaviors; Implicit Information Field; Balanced Searching Strategy

Online: 31 May 2023 (10:25:50 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.2209.v1

Breast Cancer Detection in Mammography Images: A CNN-Based Approach with Feature Selection

Zahra Jafari, Ebrahim Karami

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: breast cancer; Convolutional Neural Network (CNN); computer aided diagnosis (CAD); feature selection; feature classification; mammography images

Online: 31 May 2023 (09:02:30 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.2183.v1

The Power of Immersive Media: Enhancing Empathy through Virtual Reality Experiences

Dr. Bharat Dhiman

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: immersive media; virtual reality; empathy; empathy-building simulations

Online: 31 May 2023 (07:32:34 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.2017.v1

A Secure and Privacy-Preserving Blockchain-based XAI-Justice System

Konstantinos Demertzis, Konstantinos Rantos, Lykourgos Magafas, Charalabos Skianis, Lazaros Iliadis

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: justice system; blockchain; differential privacy; homomorphic encryption; explainable artificial intelligence; ChatGPT

Online: 29 May 2023 (13:47:42 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.2009.v1

Proficient Optimization for Precise control of Rehabilitation Robots using Machine Learning Algorithms: PSO and Firefly Comparison

Kamran Joyo, Talha Khan, Kushsairy Kadir, Safdar Rizvi

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Manipulator; DOF; upper extremity; Integral Squared Error; Integral Absolute Error; PSO; Firefly

Online: 29 May 2023 (10:39:41 CEST)

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Diversified techniques have been applied in many research papers for the optimization of rehabilitation robotic movements in order to maintain smoothness and accuracy. Smooth and precise control is needed necessarily for upper limb rehabilitation robotic applications having five degree of freedom. The preferred parameters which are used for the controlling were validated by mathematical model and these tuning parameters were optimized. Designing optimization algorithms to control complex physical robots has been a challenging task. In this study, a number of optimization techniques will be analyzed to determine the optimal parameters of a PID controller with a dynamic model of the upper limb rehabilitation system. For determining optimal control parameters for PID, there exists a number of tuning methods such as Zeigler Nichols and fuzzy logic which are classical methods. Swarm intelligence-based optimization algorithms are inspired by the behaviors of living things in nature. Several researchers have reported the optimal design of PID controller parameters using optimization techniques. The proposed control technique has been implemented on a 5-DOF RAX hardware and before any clinical trials, six healthy subjects went for trials under strict protocol. It has been discovered that the proposed control technique rejects the external unwanted disturbances as well as keeps the system stable under extreme perturbed and harsh conditions. In this research paper mathematical models have been validated to determine the PID parameters for the optimization. The comparative study is carried out with four different cost functions since a well-designed objective function leads to better performance of the system and indicates control design expectations. These objective functions are an integral squared error (ISE) and integral absolute error (IAE). In this research work, the effects of different cost functions on optimization techniques for controller parameters were analyzed. The performance of the controller with different cost functions has examined for robustness analysis. The cost function of particle swarm optimization, Firefly, Ant Bee Colony and Ant Colony optimization were developed for the better optimization results.

Preprint ARTICLE | doi:10.20944/preprints202305.1617.v3

ADL: Anomaly Detection and Localization in Crowded Scenes Using Hybrid Methods

Hequn Wu, Bai Rui, Liu Li

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Anomaly detection; YOLACT; Foreground; PWC-Net; Tracking

Online: 29 May 2023 (07:08:13 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1967.v1

A Multi-Scale Object Detector Based on Coordinate and Global Information Aggregation for UAV Aerial Images

Liming Zhou, Zhehao Liu, Hang Zhao, Yan-e Hou, Yang Liu, Xianyu Zuo, Lanxue Dang

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: UAV images; multi-feature fusion; information aggregation; multi-scale object detection

Online: 29 May 2023 (04:52:15 CEST)

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Preprint CONCEPT PAPER | doi:10.20944/preprints202305.1909.v1

A Geometric Interpretation of the Multivariate Gaussian Distribution and its Entropy and Mutual Information

Dah-Jing Jwo, Ta- Shun Cho, Amita Biswal

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: multivariate Gaussians; correlated random variables; visualization; entropy; relative entropy; mutual information

Online: 26 May 2023 (10:00:47 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1885.v1

Tubular Structure Segmentation via Multi-Scale Reverse Attention Sparse Convolution

Xueqiang Zeng, Yingwei Guo, Asim Zaman, Haseeb Hassan, Jiaxi Lu, Jiaxuan Xu, Xiaoqiang Miao, Huihui Yang, Anbo Cao, Yingjian Yang, Rongchang Chen, Yan Kang

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: cerebrovascular; airway; tubular structures; multi-scale; reverse attention; sparse convolution

Online: 26 May 2023 (07:58:26 CEST)

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Preprint COMMUNICATION | doi:10.20944/preprints202305.1540.v3

Revisiting the Political Biases of ChatGPT

Sasuke Fujimoto, Kazuhiro Takemoto

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: ChatGPT; algorithm bias; political bias; large language model

Online: 26 May 2023 (07:37:33 CEST)

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Preprint REVIEW | doi:10.20944/preprints202303.0296.v3

Ultrasound-Based AI for COVID-19 Detection: A Comprehensive Review of Public and Private Lung Ultrasound Datasets and Studies

Abrar Morshed, Abdulla Al Shihab, Md Abrar Jahin, Md Jaber Al Nahian, Md Murad Hossain Sarker, Md Sharjis Ibne Wadud, Mohammad Istiaq Uddin, Muntequa Imtiaz Siraji, Nafisa Anjum, Sumiya Rajjab Shristy, Tanvin Rahman, Mahmuda Khatun, Md Rubel Dewan, Mosaddeq Hossain, Razia Sultana, Ripel Chakma, Sonet Barua Emon, Towhidul Islam, Mohammad Hussain

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: COVID-19; Deep learning; Artificial Intelligence; Ultrasound, Review

Online: 25 May 2023 (02:41:35 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1617.v2

ADL: Anomaly Detection and Localization in Crowded Scenes Using Hybrid Methods

Bai Rui, Hequn Wu

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Anomaly detection; YOLACT; Foreground; PWC-Net; Tracking

Online: 24 May 2023 (04:58:28 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1693.v1

Blockchain-Enabled Quality Improvement Digital Twin for Clinical Trials

Reza Vatankhah Barenji, Reza Wbrahimi Hariry

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Digital twin; Clinical trials; Quality by Design; Blockchain technology; Drug development

Online: 24 May 2023 (04:46:13 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1662.v1

A Hybrid Approach to Representing Shared Conceptualization in Decentralized AI Systems: Integrating Epistemology, Ontology, and Epistemic Logic

Fateh Mohamed Ali Adhnouss, Husam M. Ali El-Asfour, Kenneth McIsaac, Idris El-Feghia

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Artificial intelligence (AI); Knowledge representation; Ontology; Epistemology; Conceptualization; Modal logic

Online: 23 May 2023 (14:20:17 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1658.v1

Employing Molecular Conformations for Ligand-based Virtual Screening with Equivariant Graph Neural Network and Deep Multiple Instance Learning

Yaowen Gu, Jiao Li, Hongyu Kang, Bowen Zhang, Si Zheng

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Virtual screening; Bioactivity prediction; Equivariant graph neural network; Multiple instance learning; Molecular conformation; Benchmark dataset

Online: 23 May 2023 (13:05:48 CEST)

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Ligand-based virtual screening (LBVS) is a promising approach for rapid and low-cost screening of potentially bioactive molecules in the early stage of drug discovery. Compared with traditional similarity-based machine learning methods, deep learning frameworks for LBVS can more effectively extract high-order molecule structure representations from molecular fingerprints or structures. However, the 3D conformation of a molecule largely influences its bioactivity and physical properties, and has rarely been considered in previous deep learning-based LBVS methods. Moreover, the relative bioactivity benchmark dataset is still lacking. To address these issues, we introduce a novel end-to-end deep learning architecture trained from molecular conformers for LBVS. We first extracted molecule conformers from multiple public molecular bioactivity data and consolidated them into a large-scale bioactivity benchmark dataset, which totally includes millions of endpoints and molecules corresponding to 954 targets. Then, we devised a deep learning-based LBVS called EquiVS to learn molecule representations from conformers for bioactivity prediction. Specifically, graph convolutional network (GCN) and equivariant graph neural network (EGNN) are sequentially stacked to learn high-order molecule-level and conformer-level representations, followed by attention-based deep multiple-instance learning (MIL) to aggregate these representations and then predict the potential bioactivity for the query molecule on a given target. We conducted various experiments to validate the data quality of our benchmark dataset, and confirmed EquiVS achieved better performance compared with 10 traditional machine learning or deep learning-based LBVS methods. Further ablation studies demonstrate the significant contribution of molecular conformation for bioactivity prediction, as well as the reasonability and non-redundancy of deep learning architecture in EquiVS. Finally, a model interpretation case study on CDK2 shows the potential of EquiVS in optimal conformer discovery. The overall study shows that our proposed benchmark dataset and EquiVS method have promising prospects in virtual screening applications.

Preprint ARTICLE | doi:10.20944/preprints202305.1654.v1

Finding IoT Anomaly using Rough Fuzzy Periodic Subspace Clustering Approach

Fokrul Alom Alom Mazarbhuiya, Mohamed Shenify

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Anomaly detection; Information system; High-dimensional data; Dominance relation; CORE of attribute set; Distance function; k-means algorithm

Online: 23 May 2023 (12:00:44 CEST)

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Finding anomalies in the real-time system is recognized as one of most challenging study in information security. It has so many applications like IoT, and Stock-Market. In any IoT system the data generated are real-time, and temporal in nature. Since due to the extreme exposure to Internet and interconnectivity of devices, the IoT systems often face issues like fraud, anomalies, intrusions etc. Discovering anomaly in such domain can be interesting. Clustering and rough set theory have been tried in many cases. Considering the time-stamp associated with IoT data, time-dependent patterns like periodic clusters can be generated which could be helpful for the efficient detection of anomalies by providing more in-depth analysis of the system. In this paper, a mixed method comprising of nano topology, a modified k-means clustering and an interval superimposition technique is used for finding fuzzy periodic clusters in the subspace generated by the nano topology. For every clusters there will be an associated sequence of time-intervals where it exists. The sequence time-intervals accompanying with each clusters may exhibit some remarkable patterns. For example, there may exist different types of periodicity namely yearly, monthly, daily, and hourly etc. For finding such fuzzy periodicity, an operation called interval-superimposition has been used. The time-intervals associated with each cluster are superimposed if they have reasonable overlapping. Each superimposed time-interval generates a fuzzy time-interval. The data instances are thought to be anomalous if they either belong to sparse clusters or don't belong to any clusters. The efficacy of the method can be assessed by means of both time-complexity analysis and comparative studies with existing clustering-based anomaly detection algorithms with a real-life and a synthetic dataset. It can been found experimentally that our method can extract anomaly with 98% of accuracy and it runs cubic time approximately.

Preprint REVIEW | doi:10.20944/preprints202305.1649.v1

Sentiment Analysis for E-commerce Product Reviews: Current Trends and Future Directions

Salma Elzeheiry, Wael A. Gab-Allah, Nagham Mekky, Mohammed Elmogy

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: E-commerce; Sentiment analysis; Natural language processing; Deep learning; Spam; Product reviews.

Online: 23 May 2023 (10:58:37 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1617.v1

ADL: Anomaly Detection and Localization in Crowded Scenes Using Hybrid Methods

Bai Rui, Hequn Wu

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Anomaly detection; YOLACT; Foreground; PWC-Net; Tracking

Online: 23 May 2023 (08:22:57 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1614.v1

Intriguing Self-optimization: Gradient Sign and Fractional Order Gradient

Sunfu Tan, Yifei Pu

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Caputo fractional derivative; fractional order gradient; gradient sign; adversarial samples; DNNs

Online: 23 May 2023 (08:11:44 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1583.v1

Integration of the Wang & Mendel Algorithm into the Application of Fuzzy Expert Systems to Intelligent Clinical Decision Support Systems

Manuel Casal-Guisande, Jorge Cerqueiro-Pequeño, José-Benito Bouza-Rodríguez, Alberto Comesaña-Campos

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Design; Machine Learning; Expert Systems; Fuzzy Logic; Automatic Rule Generation; Information Fusion; Intelligent System; Decision-making; Wang–Mendel

Online: 23 May 2023 (05:36:00 CEST)

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Preprint REVIEW | doi:10.20944/preprints202303.0296.v2

Ultrasound-Based AI for COVID-19 Detection: A Comprehensive Review of Public and Private Lung Ultrasound Datasets and Studies

Abrar Morshed, Abdulla Al Shihab, Md Abrar Jahin, Md Jaber Al Nahian, Md Murad Hossain Sarker, Md Sharjis Ibne Wadud, Mohammad Istiaq Uddin, Muntequa Imtiaz Siraji, Nafisa Anjum, Sumiya Rajjab Shristy, Tanvin Rahman, Mahmuda Khatun, Fakrul Islam Javed, Md Rubel Dewan, Mosaddeq Hossain, Razia Sultana, Ripel Chakma, Sonet Barua Emon, Towhidul Islam, Mohammad Hussain

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: COVID-19; Deep learning; Artificial Intelligence; Ultrasound, Review

Online: 23 May 2023 (03:42:44 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1532.v1

Hierarchical Model-Based Deep Reinforcement Learning For Single-Asset Trading

Adrian Millea

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: deep reinforcement learning; trading; clustering; hierarchy; prediction; risk; bitcoin

Online: 22 May 2023 (16:24:21 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1522.v1

CDF-LS:Contrastive Network for Emphasizing Feature Differences with Fusing Long and Short-term Interest Features

Kejian Liu, Wei Wang, Rongju Wang, Xuran Cui, Liying Zhang, Xianzhi Yuan, Xianyong Li

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Recommendation system; Contrast learning; Deep Learning

Online: 22 May 2023 (11:55:55 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1519.v1

Crop Prediction Model using Machine Learning Algorithms

Ersin Elbasi, Chamseddine ZAKI, Ahmet E. Topcu, Wiem Abdelbaki, Aymen I Zreikat, Elda Cina, Ahmed Younes Shdefat, Louai Saker

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: crop prediction; machine learning; feature selection; artificial intelligent; smart farming

Online: 22 May 2023 (11:24:05 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1460.v1

An AI Enhanced Strategy of Service Offloading for IoV in Mobile Edge Computing

Peng Hong Yu, Zhang Xiao Song, Li Hong Wu, Xu Le Xi, Wang Xiao Dong

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: 6G; IoV; AI; edge computing; QoS; CNN; LSTM

Online: 22 May 2023 (04:41:28 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1455.v1

N-STGAT：Spatio-Temporal Graph Neural Network Based Network Intrusion Detection for Near-earth Remote Sensing

Yalu Wang, Jie Li, Wei Zhao, Zhijie Han, Hang Zhao, Lei Wang, Xin He

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: near-earth remote sensing; network intrusion; temporal features; spatio-temporal graph attention network

Online: 22 May 2023 (03:27:46 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1393.v1

Agriculture Named Entity Recognition - Towards FAIR, Reusable Scholarly Contributions in Agriculture

Jennifer D’Souza

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: information extraction; named entity recognition; natural language processing; dataset; sequence labeling; scholarly knowledge graphs; open research knowledge graph

Online: 19 May 2023 (07:33:48 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1363.v1

GPR Target Recognition Based on Improved YOLOv3-SPP

Yunjie Zhong, Kang Li, Site Mo, Xing Liu

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: YOLOv3-SPP; ground-penetrating radar; EIOU; target detection

Online: 19 May 2023 (03:09:36 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1323.v1

Deep Image Analysis Methods for Microalgae Identification

Jeffrey Soar, Oh Shu Lih, Loh Hui Wen, Aletha Ward, Ekta Sharma, Ravinesh Deo, Prabal Datta Barua, Ru-San Tan, Eliezer Rinen, U Rajendra Acharya

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: microalgae; artificial intelligence; deep learning; sustainability

Online: 18 May 2023 (10:12:31 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202304.0282.v2

Coastal Wave Modeling and Forecasting with LSTM Optimization For Sustainable Energy Harvesting

Zaharaddeeen Karami Lawal, Hayati Yassin, Daphne Teck Ching Lai, Azam Che Idris

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Numerical methods; Hyperparameters optimization; Ocean energy; Sustainable Energy; Recur-rent neural network (RNN); Time series forecasting; Sustainability and environmental man-agement

Online: 18 May 2023 (07:09:21 CEST)

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Coastal wave modeling and forecasting are essential in oceanography, sustainable marine energy, and ocean engineering. Precise forecasting of wave speed and direction are crucial for offshore operations, marine energy, risk management, environmental management, coastal and sustainable maritime management. The coastline of Brunei Darussalam can generate between 15 and 126 Giga Watt of wave energy. In this experimental research, we used two numerical approaches, the finite difference, and spectral element methods, to model and simulate wave speed and direction. We calculated the mean error between numerical and analytical solutions. We proposed a novel, promising, univariate time series forecasting model by combining the Long Short-Term (LSTM) with KerasTuner hyperparameters tuning and optimization techniques. This method helps us to improve the accuracy and efficiency of time-series forecasting.. The experimental data was computed from high-precision Acoustic Doppler Current Profiler (ADCP) sensor data. This research is part of the preliminary feasibility analysis of wave energy production in Brunei Darussalam and net zero commitment for a sustainable environment. Seven independent forecast experiments were performed for wave speed and direction in degree and radian units for 1, 3, 6, 8, 10, 12, and 24 hours. Mean squared error (MSE) was adopted as a metric for both training and testing. The experimental results reveal that the wave speed forecast has the lowest MSE compared to direction, regardless of the unit of measure, but has a longer duration. In addition, the direction forecast in the degree unit has the lowest errors compared to the unit of radians; the latter has a longer running time than the former. The model has delivered optimal results throughout the experiments with minor training and test errors. We conducted a thorough evaluations on two benchmark time series datasets, which include the study dataset and air quality index dataset, to validate the performance of the proposed model with other models. The proposed model outperforms cutting-edge forecasting models, such as the conventional LSTM, ARIMA, and Prophet. The model has the slightest forecast error compared to the existing literature’s result.

Preprint ARTICLE | doi:10.20944/preprints202305.1245.v1

The Impact of Irrationals on the Range of Arctan Activation Function for Deep Learning Models

Talya Tümer-Sivri, Nergis Pervan-Akman, Ali Berkol

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Deep neural networks; Activation functions; Multiclass classification; Time-Series prediction; Reuters data; Energy trade value

Online: 17 May 2023 (11:11:21 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0833.v2

On the Applicability of Quantum Machine Learning

Sebastian Raubitzek, Kevin Mallinger

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: quantum machine learning; Variational Quantum Circuit; Quantum Kernel Estimator; Qiskit; Ridge; Lasso; XGBoost; LightGBM; CatBoost; classification; quantum computing; boost classifiers; neural networks

Online: 17 May 2023 (10:24:58 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1132.v1

SG-Det: Shuffle-GhostNet-based Detector for Real-Time Maritime Object Detection in UAV Images

Lili Zhang, Ning Zhang, Rui Shi, Gaoxu Wang, Yi Xu, Zhe Chen

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: object detection; UAV images; lightweight network; maritime search and rescue

Online: 16 May 2023 (09:03:19 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1115.v1

A Real-Time Lightweight Detection Algorithm for Deck Crew and the Use of Fishing Nets based on Improved YOLOv5s Network

Wang Jiaming, Yin Xiangbo, Li Guodong

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: YOLOv5s; deck crew detection; fishing net detection; deep learning model lightweight

Online: 16 May 2023 (07:18:38 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1083.v1

LogBD: A Log Anomaly Detection Method Based on Pre-trained Models and Domain Adaptation

Le Deng, Shuxian Liu, Huan Xu, Wei Wang

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: log anomaly detection; pre-trained models; domain adaptation

Online: 16 May 2023 (04:49:53 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1065.v1

A ResNet-based Audio-visual Fusion Model for Piano Skill Evaluation

Xujian Zhao, Yixin Wang, Xuebo Cai

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Multimodal Machine Learning; Automated Piano Skill Evaluation; Residual Network

Online: 16 May 2023 (02:06:02 CEST)

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With the rise of piano teaching in recent years, many people have joined the team of piano learners. However, the expensive cost of manual instruction and the unique one-on-one teaching model have made piano learning an extravagant event. Most existing approaches based on the audio modality aim to evaluate piano players' skills. Unfortunately, these methods ignored the information contained in the video, which led to a one-sided and simplistic evaluation of the piano player's skills. More recently, multimodal-based methods are proposed to assess the skill level of piano players using both video and audio information. However, existing multimodal approaches use shallow networks to extract video and audio features, which are deficient in extracting complex spatio-temporal and time-frequency features from piano performance. Furthermore, the fingering and the pitch-rhythm information of the piano performance is contained in the spatio-temporal and time-frequency features, respectively. In the paper, we propose a ResNet-based audio-visual fusion model that combines video and audio features to assess the skill level of piano players. Firstly, ResNet18-3D is used as the backbone network for our visual branches, which can extract feature information from the video data. Then, we consider ResNet18-2D as the backbone network of the aural branch and extract the feature information from the audio data. The extracted video features are fused with the audio features to generate multimodal features for the final piano skill evaluation. The experimental results on the PISA dataset show that our proposed audio-visual fusion model, with a validation accuracy of 70.80%, outperforms the state-of-the-art methods in both performance and efficiency. Then, we also explore the impact of different layers of ResNet on model performance, and the experimental results show that the audio-visual fusion model dealing with the piano skill assessment problem can make full use of both feature information when the number of video features is close to the number of audio features.

Preprint ARTICLE | doi:10.20944/preprints202305.1047.v1

Bridging History with AI: A Comparative Evaluation of GPT- 3.5, GPT-4, and Google-BARD in Predictive Accuracy and Fact- Checking

Davut Emre Tasar, Ceren Öcal Taşar

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Artificial Intelligence; Large Language Models; GPT-3.5; GPT-4; Google-BARD; Historical Fact-Checking; Distance to Reality; History; AI in Education; Gap Bridging

Online: 15 May 2023 (12:53:11 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1031.v1

Combining Computer Vision, Artificial Intelligence and 3D Printing in Wheelchair Design Customization: The Kyklos 4.0 Approach

Mahmoud Gharra, Yacine Rebahi, Luca Rizzi, Ilias Zournatzis

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Additive manufacturing; Artificial intelligence; Design customisation; Wheelchair; Footrest; Kyklos 4.6; Circular economy

Online: 15 May 2023 (10:48:22 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1018.v1

Active Identity Function as Activation Function

Ali Akbar Kiaei, Mahnaz Boush, Danial Safaei, Sadegh Abadijou, Nima Baselizadeh, Nader Salari, Masoud Mohammadi

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Activation Function; Neural Network; Deep Learning; RELU; SWISH

Online: 15 May 2023 (10:13:00 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0990.v1

Research on Multilingual News Clustering Based on Cross-Language Word Embeddings

Lin Wu, Rui Li, Wong-Hing Lam

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: news; cross-language word embedding; LDA model; text clustering

Online: 15 May 2023 (07:29:01 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0982.v1

A Deep Learning Approach to Analyze NMR Spectra of SH-SY5Y Cells for Alzheimer’s Disease Diagnosis

Filippo Costanti, Arian Kola, Franco Scarselli, Daniela Valensin, Monica Bianchini

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Alzheimer’s Disease; SH-SY5Y cells; Nuclear Magnetic Resonance (NMR); Convolutional autoencoders; Embedding of NMR spectra; Data augmentation.

Online: 15 May 2023 (05:42:08 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0923.v1

Effective Quantization Evaluation Method of Functional Movement Screening with Improved Gaussian Mixture Model

Ruiwei Hong, Qingjun Xing, Yuanyuan Shen, Yanfei Shen

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Injury prevention; FMS; depth camera; Gaussian Mixture Model; machine learning

Online: 12 May 2023 (10:21:23 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0908.v1

Integrating Text Classification in Topic Discovery with Semantic Embedding Models

Ana Laura Lezama-Sánchez, Mireya Tovar Vidal, José A. Reyes-Ortiz

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Deep Learning; Topic Discovery; Latent Dirichlet Allocation; Latent Semantic Analysis; Probabilistic Latent Semantic Analysis

Online: 12 May 2023 (08:52:57 CEST)

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Topic discovery is finding the main idea of large amounts of textual data. It indicates the recurring topics in the documents, allowing an overview of the texts. Current topic discovery models receive the texts, with or without pre-processing of Natural Language Processing. The processing consists of stopwords removal, text cleaning and normalization (lowercase conversion). A topic discovery model that receives texts with or without processing generates general topics since the input data is many uncategorized texts. The general topics do not offer a detailed overview of the input texts, and manual text categorization is a time-consuming and tedious task. Accordingly, it is necessary to integrate an automatic text classification task in the topic discovery process to obtain specific topics with their top words that contain relevant relationships based on belonging to a class. Text classification performs a word analysis that makes up a document to decide what class or category is being identified; then, integrating the text classification before a topic discovery process will provide latent topics depicted by top words with a high coherence in each topic based on the previously obtained classes. Therefore, this paper exposes a approach that integrates text classification into topic discovery from large amounts of English textual data, such as 20-Newsgroup and Reuters corpora. The text classification is accomplished with a Convolutional Neural Network(CNN) incorporating three embedding models based on semantic relationships. The topic discovery over categorized texts is realized with Latent Dirichlet Analysis(LDA), Probabilistic Latent Semantic Analysis(PLSA), and Latent Semantic Analysis(LSA) algorithms. An evaluation process was performed based on the normalized topic coherence metric. The 20-Newsgroup corpus was classified, and twenty topics with ten top words were discovered for each class, obtaining 0.1723 normalized topic coherence when applying LDA, 0.1622 with LSA, and 0.1716 with PLSA. The Reuters corpus was also classified, obtaining 0.1441 normalized topic coherence when applying the LDA algorithm to obtain 20 topics for each class.

Preprint REVIEW | doi:10.20944/preprints202305.0900.v1

Unraveling the Mysteries of AI Chatbots

Raj Bridgelall

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Generative Artificial Intelligence; Large Language Models; ChatGPT; Bard; Transformer Architecture; Prompt Engineering

Online: 12 May 2023 (07:47:13 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0875.v1

White Box Watermarking for Convolution Layers in Fine-Tuning Model Using the Constant Weight Code

Minoru Kuribayashi, Tatsuya Yasui, Asad Malik

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: DNN Watermark; Fine-Tuning Model, Constant Weight Code; Detection, Non-Fungible Token

Online: 12 May 2023 (03:42:44 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0833.v1

On the Applicability of Quantum Machine Learning

Sebastian Raubitzek, Kevin Mallinger

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: quantum machine learning; Variational Quantum Circuit; Quantum Kernel Estimator; Qiskit; Ridge; Lasso; XGBoost; LightGBM; CatBoost; classification; quantum computing; boost classifiers; neural networks

Online: 11 May 2023 (09:04:31 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0828.v1

Parking Time Violation Tracking using Yolov8 and DeepSORT

Nabin Sharma, Sushish Baral, May Phu Paing, Rathachai Chawuthai

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: DeepSORT; Object Detection; Parking Time Tracking; Parking Violation Detection; Vehicle Tracking, Yolov8

Online: 11 May 2023 (08:47:32 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0808.v1

Exploring the Potential Impact of Artificial Intelligence (AI) on International Students in Higher Education: Generative AI, Chatbots, Analytics, and International Student Success

Ting Wang, Brady D. Lund, Agostino Marengo, Alessandro Pagano, Nishith Reddy Mannuru, Zoë A. Teel, Jenny Pange

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: artificial intelligence; AI; education; international students; personalized learning; adaptive learning; predictive analytics; chatbots

Online: 11 May 2023 (05:57:02 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0796.v1

A Light-Weight Network for Small Insulator and Defect Detection Using UAV Imaging Based on Improved YOLOv5

Tong Zhang, Yinan Zhang, Min Xin, Jiashe Liao, Qingfeng Xie

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: keyword light-weight; insulator and defect detection; YOLOv5; Ghost module; convolutional block attention module; unmanned aerial vehicles

Online: 11 May 2023 (05:21:17 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0780.v1

Humans are Still Better than ChatGPT: Case of the IEEEXtreme Competition

Anis Koubaa, Basit Qureshi, Adel Ammar, Zahid Khan, Wadii Boulila, Lahouari Ghouti

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: ChatGPT; GPT-4; GPT-3.5; GPT Performance; GPT Limitations; OpenAI; NLP; Computer Programming

Online: 11 May 2023 (04:15:32 CEST)

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Preprint DATA DESCRIPTOR | doi:10.20944/preprints202305.0777.v1

Data Synthesis Technique for Categorical Pestes Des Petits Ruminants (PPR) Data Using CTGAN Model

Devotha G. Nyambo, Nguse Ngulumbi, Neema Mduma, Ramadhani Sinde, Tumaini Lyimo

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Data synthesis; Livestock health; PPR disease; Machine Learning; Prediction

Online: 11 May 2023 (03:56:47 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0755.v1

Text to Causal Knowledge Graph: A Framework to Synthesize Knowledge from Unstructured Business Texts into Causal Graphs

Seethalakshmi Gopalakrishnan, Victor Z. Chen, Wenwen Dou, Gus Hahn-Powell, Sreekar Nedunuri, Wlodek W. Zadrozny

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Causality extraction; Organizational data; Stakeholder Taxonomy; Natural Language Processing; NLP

Online: 10 May 2023 (13:36:31 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0733.v1

An Efficient and Effective Framework for Intestinal Parasite Egg Detection using YOLOv5

Abdullah S. Alotaibi, Satish Kumar, Tasleem Arif

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Intestinal Parasites; Transfer learning; CNN; YOLOv5

Online: 10 May 2023 (10:13:47 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0729.v1

YOLOv5s-Fog: An Improved Model Based on YOLOv5s for Object Detection in Foggy Weather Scenarios

Xianglin Meng, Yi Liu, Lili Fan, Jingjing Fan

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: foggy weather scenarios; deep learning; SwinFoucs; decoupled head; Soft-NMS

Online: 10 May 2023 (10:05:03 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0722.v1

Anomaly Detection in Endemic Disease Surveillance Data Using Machine Learning Techniques

Peter U. Eze, Nicholas Geard, Ivo Mueller, Iadine Chades

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Anomaly detection; Malaria data; Machine learning; big data; epidemic

Online: 10 May 2023 (09:34:36 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0713.v1

ECG Recordings as Predictors of Very Early Autism Likelihood: A Machine Learning Approach

Deepa Tilwani, Jessica Bradshaw, Amit P. Sheth, Christian O'Reilly

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Autism Spectrum Disorder, Biomarker, Electrocardiograms, Machine Learning, Heart rate variability.

Online: 10 May 2023 (08:42:42 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0708.v1

Framework for Representing, Building and Reusing Novel State-of-the-art 3D Object Detection Models in Point Clouds Targeting Self-Driving Applications

António Linhares Silva, Pedro Oliveira, Dalila Durães, Duarte Fernandes, Rafael Névoa, João Monteiro, Pedro Melo-Pinto, José Machado, Paulo Novais

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Autonomous Driving; Deep learning Methods; LiDAR Sensing Technology; 3D Object Detection

Online: 10 May 2023 (08:21:46 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0670.v1

Feet Segmentation for Regional Analgesia Monitoring using Convolutional RFF and Layer-Wise Weighted CAM Interpretability

Juan Aguirre-Arango, Andrés Marino Álvarez-Meza, German Castellanos-Dominguez

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Infrared Thermal Segmentation; Regional Neuraxial Analgesia; Deep Learning; Random Fourier Features; Class Activation Maps

Online: 9 May 2023 (14:52:00 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0252.v2

Neural Networks and Adapted Optimal Transport

Matteo Garbelli, Luca Di Persio

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Neural Network; Machine Learning; Adapted Optimal Transport; Mean Field function

Online: 9 May 2023 (04:33:48 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0513.v1

Classification of Dental Teeth X-Ray Images Using a Deep Learning CNN Model

Dankai Liao, Carol Anne Hargreaves

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: deep learning; medical imaging; clinical decision support system; Teeth X-Rays; Images; CNN model; transfer learning; NASNetMobile feature extractor; classification model

Online: 8 May 2023 (10:25:36 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0479.v1

The Applicability of Machine Learning Methods to the Characterization of Fibrous Gas Diffusion Layers

Dieter Froning, Eugen Hoppe, Ralf Peters

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: PEFCs; Lattice–Boltzmann Method; stochastic modeling; machine learning

Online: 8 May 2023 (08:47:08 CEST)

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Preprint REVIEW | doi:10.20944/preprints202305.0473.v1

Unlocking the Potential of Quantum Machine Learning to Advance Drug Discovery

Maria Avramouli, Ilias K. Savvas, Anna Vasilaki, Georgia Garani

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Drug Discovery; Drug Design; Drug Development, Quantum Computing, Quantum Machine Learning

Online: 8 May 2023 (08:37:23 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0467.v1

Multi-Stream Graph-based Deep Neural Networks for Skeleton-based Sign Language Recognition

Abu Saleh Musa Miah, Md. Al Mehedi Hasan, Si-Woong Jang, Hyoun-Sup Lee, Jungpil Shin

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Sign Language Recognition (SLR); Large Scale Dataset; American Sign Language; Turkey Sign Language; Chinese Sign Language; AUTSL; CSL

Online: 8 May 2023 (08:24:04 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0445.v1

Multi-Country and Multi-Horizon GDP Forecasting Using Temporal Fusion Transformers

Juan Laborda, Sonia Ruano, Ignacio Zamanillo

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: GDP; deep learning; time fusion transformers; multi-horizon forecasting; interpretability

Online: 8 May 2023 (04:47:10 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0426.v1

Ensemble Learning for Breast Cancer Lesion Classification: A Pilot Validation using Correlated Spectroscopic Imaging and Diffusion-Weighted Imaging

Ajin Joy, Marlene Lin, Melissa Joines, Andres Saucedo, Stephanie Lee-Felker, Jennifer Baker, AiChi Chien, Uzay E Emir, Paul M. Macey, M Albert Thomas

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Correlated Spectroscopic Imaging; Diffusion weighted imaging; Machine Learning; Breast Cancer; Choline; Myo-inositol; Glycine; Water; Lipids

Online: 8 May 2023 (02:53:22 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0421.v1

An Optimized Approach to Translate Technical Patents from English to Japanese Using Machine Translation Models

Maimoonah Ahmed, Abdelkader Ouda, Mohamed Abusharkh, Sandeep Singh Kohli, Khushwant Rai

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Machine Translation; Technical Patents; Natural Language Processing; Translation Quality; Cross-Lingual Information Retrieval; Corpus-based Translation; Domain Adaptation; Language Model Fine-tuning; Neural Machine Translation

Online: 6 May 2023 (10:43:14 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0389.v1

Monitoring of the Quality and Perception of Service in Colombian Public Service Companies via Twitter

Dante Conti, Carlos Gomez, Juan Guillermo Jaramillo, Victoria Eugenia Ospina

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: LDA; Topic Modeling; Twitter; Time Series; Sentiment Analysis; CIER

Online: 6 May 2023 (08:13:29 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0374.v1

ESarDet: An Efficient SAR Ship Detection Method Based on Context Information and Large Effective Receptive Field

Yimin Zhang, Chuxuan Chen, Ronglin Hu, Yongtao Yu

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: ship detection; synthetic aperture radar (SAR); context information; effective receptive field; you only look once (YOLO)

Online: 6 May 2023 (04:17:18 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0333.v1

DroidDetectMW: A Hybrid Intelligent Model for Android Malware Detection

Fatma Taher, Omar AlFandi, Mousa Al Kfairy, Hussam Al Hamadi, Saed Alrabaee

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: malware; harris hawks optimization, feature selection; benign; multiclass classification; multi-verse optimization; moth-flame optimization; machine learning.

Online: 5 May 2023 (08:57:31 CEST)

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Malicious apps specifically aimed at the Android platform have increased in tandem with the proliferation of mobile devices. Malware is now so carefully written that it is difficult to detect. Due to the exponential growth in malware, manual methods of malware are increasingly ineffec-tive. Although prior writers have proposed numerous high-quality approaches, static and dy-namic assessments inherently necessitate intricate procedures. The obfuscation methods used by modern malware are incredibly complex and clever. As a result, it cannot be detected using only static malware analysis. As a result, this work presents a hybrid analysis approach, partially tai-lored for multiple-feature data, for identifying Android malware and classifying malware families to improve Android malware detection and classification. This paper offers a hybrid method that combines static and dynamic malware analysis to give a full view of the threat. Three distinct phases make up the framework proposed in this research. Normalization and feature extraction procedures are used in the first phase of pre-processing. Both static and dynamic features undergo feature selection in the second phase. Two feature selection strategies are proposed to choose the best subset of features to use for both static and dynamic features. The third phase involves ap-plying a newly proposed detection model to classify android apps; this model uses a neural net-work optimized with an improved version of HHO. Application of binary and multi-class classi-fication is used, with binary classification for benign and malware apps and multi-class classifica-tion for detecting malware categories and families. By utilizing the features gleaned from static and dynamic malware analysis, several machine-learning methods are used for malware classifi-cation. According to the results of the experiments, the hybrid approach improves the accuracy of detection and classification of Android malware compared to the scenario when considering static and dynamic information separately.

Preprint ARTICLE | doi:10.20944/preprints202305.0328.v1

Traffic Flow Techniques Applied to the Modeling of the Intersection of East 53rd and East 56th Streets in Panama City: A Practical Case

Carlos Rovetto, Edmanuel Cruz, Ivonne Nunez, Keyla Santana, Andrzej Smolarz, José Rangel, Elia Esther Cano

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Vehicular traffic flow; queuing theory; optimal traffic light control; optimization; simulation; simulation

Online: 5 May 2023 (08:04:34 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0319.v1

Hyperspectral Image Classification Based on Fusion of Convolutional Neural Network and Graph Network

Luyao Gao, Shulin Xiao, Changhong Hu, Yang Yan

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: hyperspectral images; convolutional neural networks; graph convolutional networks; feature fusion

Online: 5 May 2023 (07:40:07 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0044.v2

A Robust Distributed Deep Learning Approach to Detect Alzheimer’s Disease from MRI Images

Tapotosh Ghosh, Md Istakiak Adnan Palash, Mohammad Abu Yousuf, Md. Abdul Hamid, Muhammad Mostafa Monowar, Madini O. Alassafi

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Federated Learning; Alzheimer’s Disease; medical imaging; MRI Image

Online: 5 May 2023 (04:49:41 CEST)

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Preprint REVIEW | doi:10.20944/preprints202305.0298.v1

Expert Systems for Farmed Fish Disease Diagnosis: An Overview and a Proposal

Ioannis Hatzilygeroudis, Konstantinos Dimitropoulos, Konstantinos Kovas, John A. Theodorou

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: expert systems; aquaculture; fish health management; fish disease diagnosis

Online: 5 May 2023 (04:36:58 CEST)

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Preprint CONCEPT PAPER | doi:10.20944/preprints202305.0287.v1

Training Natural Language Processing Models on Encrypted Text for Enhanced Privacy

Davut Emre TAŞAR, Ceren ÖCAL TAŞAR

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Natural language processing; encrypted text; data privacy; cloud computing; Doc2Vec; XGBoost; LSTM

Online: 5 May 2023 (03:38:42 CEST)

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Computer Science and Mathematics