In real financial markets, the certainty equivalent rate is an important factor for investors to consider. From the value of a specific company’s certainty equivalent rate, investors can judge if this company is worth investing in. In this paper, we will explore how to obtain the value of the certainty equivalent rate so that we can evaluate a given company. First, we will introduce the theoretical support of this paper, which is put-call parity. From put-call parity, we will derive the mathematical expression for the certainty equivalent rate. Second, we will use the mathematical expression for the certainty equivalent rate to perform an empirical study. We will consider some extreme examples, including some of the best- and worst-performing stocks up to this point in 2023. Based on these stocks’ data, we will visualize the performance of these stocks and explain the meaning of the data. Finally, we will apply the results to a very popular industry—the electric vehicle industry—to explore the current electric vehicle market situation in the U.S.A.

This article aims to understand the role of tacit knowledge in call center organizations with the objective of understanding how call center representatives use tacit knowledge in their job roles and functions. Extant literature has focused on explicit knowledge but the research on tacit knowledge is still underdeveloped. The complexities and difficulties of the call center job role and the usage and transfer of knowledge is reviewed. Also, it takes into considerations past literature on tacit knowledge, how these respondents employ tacit knowledge in efficiently handling customers, responding to their queries, and engaging this form of knowledge in problem solving. The article concludes with discussion and implications for call center organizations and responders.

Improvements in web platforms for data exchange and trading are creating more opportunities for users to obtain data from data providers of different domains. However, the current data exchange platforms are limited to unilateral information provision from data providers to users. In contrast, there are insufficient means for data providers to learn what kinds of data users desire and for what purposes. In this paper, we propose and discuss the description items for sharing users’ call for data as data requests in the data marketplace. We also discuss structural differences in data requests and providable data using variables, as well as possibilities of data matching. In the study, we developed an interactive platform, treasuring every encounter of data affairs (TEEDA), to facilitate matching and interactions between data providers and users. The basic features of TEEDA are described in this paper. From experiments, we found the same distributions of the frequency of variables but different distributions of the number of variables in each piece of data, which are important factors to consider in the discussion of data matching in the data marketplace.

The positional deviation of the Automatic Emergency Call System (AECS) under collision conditions brings difficulties for post-rescue operations. Currently, there is a lack of analysis on the system operating conditions during collisions in the reliability assessment methods for the Global Navigation Satellite System (GNSS) deployed in AECS. Therefore, this paper establishes an in-vehicle collision environment simulation model for emergency calls to explore the influence of parameters such as temperature and vibration on the data deviation of the simulated GNSS system. We also propose environmental limits applicable to comprehensive AECS tests, which can objec-tively evaluate the reliability of AECS and provide data support for AECS bench test. Through the satellite signal-based semi-physical simulation, AECS is subjected to bench test under different operating conditions. The findings of this study demonstrate that the occurrence of random vibra-tion and impact stress, induced by vibration, exerts considerable disruptive effects on positional signal data during collisions. Consequently, it leads to substantial interference with the accurate detection of post-collision satellite positioning information. When the simulation operates under a 2.4gRMS vibration condition, the maximum phase noise error in the positioning system is 8.95%, which does not meet the AECS test accuracy requirements. On the other hand, the semi-simulation system is less affected by temperature changes, and at the maximum allowable temperature dif-ference of the equipment, the maximum phase noise error in the simulated signal is 2.12%. Therefore, based on the influence of phase noise variation on the accuracy of satellite signal simulation, nec-essary environmental conditions for AECS test are obtained, including the temperature consistent with the maximum operating temperature of the vector generator and the vibration Power Spectral Density (PSD) lower than 1.2gRMS.

Background: Exclusively breastfeeding your newborn while in the hospital is imperative for suc-cessful breastfeeding at home. This study will investigate if having a nurse on-site during rooming-in can enhance the proportion of exclusive breastfeeding. Methods: We carried out a prospective cohort study to assess exclusive breastfeeding in the first three months of life among two Neona-tology Units in Southern Italy with different hospital settings. The Ente Ecclesiastico Miulli of Ac-quaviva delle Fonti had on-site nurses available 24/7 (on-site group), while the Policlinico of Bari had nurses available on call 24/7 from the Neonatology Unit (on-call group). Results: Between January 3rd and March 31st, 2018, a total of 564 sets of mothers and babies were admitted - 299 on-site and 265 on-call. The exclusive breastfeeding rate for the entire group was 76.4% at 90 days, demonstrating the positive impact of rooming-in and nursing, regardless of the setting. Infants delivered via ce-sarean section in the on-site group demonstrated higher rates of exclusive breastfeeding at both 30 and 90 days of life. Conclusions: Our research indicates that having a nurse available at all times is crucial for promptly identifying any problems with breastfeeding. We highly suggest having an on-site nurse present during rooming-in for mothers who have had a caesarean delivery. This nurse should continuously promote exclusive breastfeeding until the baby is three months old.

Call set up success rate (CSSR) in a mobile network is an important quality parameter, which directly influences overall key performance indicators (KPIs) of the network service providers. Network KPIs especially the CSSR is the fraction of the attempts to make a call that result in a successful connection to the dialled number. Nevertheless, all call attempts do not end with a connection to the dialled number. In this research, six sigma methodology is applied to improve the call quality of a legacy mobile network and subsequently to boost comprehensive CSSR of a telecom service provider. This research elucidates an empirical study of improving overall CSSR by employing DMAIC methodology consisting of five stages, e.g. Define, Measure, Analysis, Improve and Control. In addition, analytic hierarchy process (AHP) technique is used for determining the vital causes out of all the identified network parameters affecting overall CSSR. Furthermore, the identified vital parameters are being upgraded in order to improve the overall CSSR and finally the system achieved a higher CSSR.

Background: ED overcrowding is described as one of the main issues in emergency departments (EDs) of any hospital. In Saudi Arabia, the ministry of health applied new telemedicine technology to serve patients by using the mobile application which include Sehha application and 937 medical call center. The main aim of this study is to determine the role of different telemedicine services in reducing non-urgent visits to EDs in Saudi Arabia. Methods: A cross-section study was conducted during August 2020 - May 2021 among 319 patients were using two telemedicine services in Saudi Arabia, including medical call center, and Sehha smart phone application. The primary endpoint of this study aims to determine the role of different telemedicine services in reducing non-urgent visits to EDs in Saudi Arabia. Results: This study analyzed the data from 319 patients who completed the survey provided by the Saudi Ministry of Health that concerning on information related to their health status, and ED visits. Among patients that had the intention to visit the ED (N=159), 53 of them did not go to EDs after using telemedicine services (p-value < 0.01). Regarding medical call center and Sehha application, 9.6% and 24.4%, respectively of the patients used these telemedicine services had changed their mind concerning visiting ED after taking the medical advice (p-values < 0.01).Conclusion: The implemented telemedicine services in Saudi Arabia, namely Sehha application and medical call center showed to be effective in reducing ED overload by providing medical advices to less- and non-urgent patients and deal with their minor medical issues.

The analysis of the human movement patterns based on the mobile network data makes it possible to examine a very large population cost-effectively, and led to several discoveries about human dynamics. However, the application of this data source is still not common practice. The goal of this study was to analyze the commuting tendencies of the Budapest Metropolitan Area using mobile network data and propose an automatized alternative to the current, questionnaire-based method. Commuting is predominantly analyzed by the census, but that is performed only once in a decade in Hungary. To analyze commuting, the home and the work locations of the subscribers are determined based on their appearances during and outside the working hours. The home locations were compared to census data at a settlement level. Then, the settlement and district level commuting tendencies were identified and compared to the findings of census-based sociological studies. It has been found that commuting analysis based on mobile network data strongly correlates with the census-based findings, even though home and work locations have been estimated by statistical methods. All the examined aspects, including commuting from sectors of the agglomeration to the districts of Budapest and demographic distribution of the commuters, show that mobile network data can be an automatized, fast, cost-effective, and relatively accurate way of commuting analysis, that could provide a powerful tool to the sociologists interested in commuting.

Mobile phones have become an integral part of our lives in the last two decades, leaving a digital trace of our activities and communication. This study aims to develop a data processing framework to evaluate human mobility and socioeconomic status based on call detail records. The methodology proposed first calculates radius of gyration and entropy for each user, then estimates the socioeconomic status by the price and age of the subscribers' phones. Finally, an unsupervised machine learning algorithm was used to group the cells into clusters based on their mobility and socioeconomic metrics. The research showed differences between Buda and Pest during a large scale social event using mobile phone ages and prices. Additionally, the clustering results revealed homogenous groups of cells around Budapest, with similar mobility and socioeconomic metrics. The main conclusion is that mobile network data combined with mobile phone properties offer a useful tool for characterising urban mobility and socioeconomic status.

The COVID19 pandemic had a major impact on emergency medical communication centres (EMCC). A live video facility was made available to second-line physicians in an EMCC with a first-line paramedic to receive emergency calls. The objective of this study was to measure the contribution of live video to remote medical triage. The single-centre retrospective study included all telephone assessments of patients with suspected COVID19 symptoms from 01.04.2020 to 30.04.2021 in Geneva, Switzerland. The organisation of the EMCC and the characteristics of patients who called the two emergency lines (official emergency number and COVID19 number) with suspected COVID19 symptoms were described. A prospective web-based survey of physicians was conducted during the same period to measure the indications, limitations and impact of live video on their decisions. 8,957 patients were included. 2,157 (48.0%) of the 4,493 patients assessed on the official emergency number had dyspnoea. 4,045 (90.6%) of 4,464 patients assessed on the COVID19 number had flu-like symptoms. 1,798 (20.1%) patients were reassessed remotely by a physician, including 405 (22.5%) with live video, successfully in 315 (77.8%) attempts. The web-based survey (107 forms) showed that physicians used live video to assess mainly the breathing (81.3%) and general condition (78.5%) of patients. They felt that their decision was modified in 75.7% (n=81) of cases, and caught 7 (7.7%) patients in life-threatening emergency. Medical triage decisions for suspected COVID19 patients are strongly influenced by the use of live video.