Development Of System Research Articles

The best machine learning model for fraud detection on e-platforms: a systematic literature review

The internet has been instrumental in the development and facilitation of online payment systems. However, its associated fraudulent activities on eplatforms cannot be overlooked. As a result, there has been a growing interest in the application of machine learning (ML) algorithms for fraud detection on financial e-platforms. The goal of this research is to identify common types of fraud on financial e-platform, highlight different machine learning algorithms employed in fraud detection, and derive the best machine learning algorithms for fraud detection on e-platforms. To achieve this goal, the research followed a nine steps systematic review approach to retrieve Journals and conference publications from science direct, Google Scholar and IEEE Xplore between 2018 and 2023. Out of 2,071 articles identified and screened, 44 publications (23 articles and 21 conference proceedings) satisfied the inclusion criteria for further analysis. The random forest algorithm turned out to be the best ML algorithm because it ranked first in the frequency of usage analysis and ranked first in the performance analysis with an average accuracy of 96.67%. Overall, this review has identified the kinds of fraud on financial e-platforms, and proclaimed the best and least ML algorithm for fraud detection on financial e-platform. This can help guide future research and inform the development of more effective fraud detection systems.

Introduction

Introduction

Efficacy of real-time artificial intelligence-aid endoscopic ultrasonography diagnostic system in discriminating gastrointestinal stromal tumors and leiomyomas: a multicenter diagnostic study

Gastrointestinal stromal tumors (GISTs) represent the most prevalent type of subepithelial lesions (SELs) with malignant potential. Current imaging tools struggle to differentiate GISTs from leiomyomas. This study aimed to create and assess a real-time artificial intelligence (AI) system using endoscopic ultrasonography (EUS) images to differentiate between GISTs and leiomyomas. The AI system underwent development and evaluation using EUS images from 5 endoscopic centers in China between January 2020 and August 2023. EUS images of 1101 participants with SELs were retrospectively collected for AI system development. A cohort of 241 participants with SELs was recruited for external AI system evaluation. Another cohort of 59 participants with SELs was prospectively enrolled to assess the real-time clinical application of the AI system. The AI system's performance was compared to that of endoscopists. This study is registered with Chictr.org.cn, Number ChiCT2000035787. The AI system displayed an area under the curve (AUC) of 0.948 (95% CI: 0.921-0.969) for discriminating GISTs and leiomyomas. The AI system's accuracy (ACC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) reached 91.7% (95% CI 87.5%-94.6%), 90.3% (95% CI 83.4%-94.5%), 93.0% (95% CI 87.2%-96.3%), 91.9% (95% CI 85.3%-95.7%), and 91.5% (95% CI 85.5%-95.2%), respectively. Moreover, the AI system exhibited excellent performance in diagnosing ≤20mm SELs (ACC 93.5%, 95% CI 0.900-0.969). In a prospective real-time clinical application trial, the AI system achieved an AUC of 0.865 (95% CI 0.764-0.966) and 0.864 (95% CI 0.762-0.966) for GISTs and leiomyomas diagnosis, respectively, markedly surpassing endoscopists [AUC 0.698 (95% CI 0.562-0.834) for GISTs and AUC 0.695 (95% CI 0.546-0.825) for leiomyomas]. We successfully developed a real-time AI-assisted EUS diagnostic system. The incorporation of the real-time AI system during EUS examinations can assist endoscopists in rapidly and accurately differentiating various types of SELs in clinical practice, facilitating improved diagnostic and therapeutic decision-making. Science and Technology Commission Foundation of Shanghai Municipality, Science and Technology Commission Foundation of the Xuhui District, the Interdisciplinary Program of Shanghai Jiao Tong University and the Research Funds of Shanghai Sixth people's Hospital.

Frequency reconfigurable microstrip patch antenna for multiband applications

Wireless communication technology is well-established, and several antennas have been developed and produced specifically for this purpose. However, antenna performance and communication system development need to be enhanced in order to adapt to the present era. The performance of the antenna is significantly influenced by its design. Thus, this work produced a novel wideband antenna design via the use of a frequency reconfigurable approach. In the recommended study, microstrip patch antennas (MPAs) were used in wideband applications to switch frequencies using shunt-series microelectromechanical systems (MEMS). The suggested antenna, which has two switches built into it, is tested in ON-ON, OFF-ON, and OFF-OFF switching scenarios. Radiation pattern, voltage standing wave ratio (VSWR), gain, bandwidth, and return loss are among the antenna performance metrics used to assess the suggested antenna's performance in each switching situation. The simulation findings suggest that the optimal antenna design for usage in wireless communication systems is one that works well with a shunt-series MEMS switch.

Rancang Bangun Sistem Informasi Manajemen Penjualan Kopi Pada Coffee Shop Konamu Menggunakan Sistem Point Of Sale

The purpose of this research is to develop a coffee sales management information system at the KonamuCoffee Shop using a Point of Sale system to increase efficiency in sales management. The method used in thisstudy is the system development life cycle method, starting from system requirements analysis, system design,system implementation, to system testing. In the system requirements analysis stage, assistance is providedfor the problems faced by Konamu Coffee Shop in sales management. Furthermore, a system design is carriedout using the Point of Sale system to facilitate the transaction process and sales management. The result ofthis research is a coffee sales management information system that is integrated with the Point of Sale system.This system can assist Konamu Coffee Shop in managing sales transactions, as well as generating sales andfinancial reports. With this system, it is hoped that the Konamu Coffee Shop can increase efficiency inmanaging coffee sales.

3D Modelling and Simulation Based on Kinematic Analysis for Hippotherapy

The engineering perspective on the physiology and anatomy of living things has led to the emergence of the science of biomechanics. Developing computer technologies have made it possible to examine the behaviour of living things in more detail and to develop technologies that enable kinetic and kinematic analysis of movements to imitate real limbs. In this study, the natural gaits of horses (Walk, Canter and Trot) were analysed with image processing techniques, kinematic analyses were made and three-dimensional solid models were created. Giving movement ability to the extracted solid models was carried out with the simulation software prepared on the Matlab-SimMechanic platform. By comparing the findings obtained as a result of image processing and simulation, the success of transferring the movements to a developed system was evaluated. After mathematical equations were created in the MATLAB environment, the equations were tested on the developed system and their performance rates were determined. With the developed system, joint angles, ability to reach the correct position and movement ability were analysed and it was shown how the mathematical equations required to perform the movements could be derived. As a result, a design process model for movement analysis, simulation and control of different living groups is presented with the equations obtained by formulating the information obtained from the developed system.

Evaluasi dan Pengembangan Model Sistem Informasi Manajemen Skrining Resep di Instalasi Farmasi RSUD Dr. Hasri Ainun Habibie Gorontalo dengan Metode EUCS

Introduction: Management information systems (SIMs) can provide data and information that can help facilitate prescription screening such as administrative, pharmaceutical, and clinical data. Data and information from the hospital management information system (SIMRS) are also to make it easier to screen prescriptions and prevent medication errors. Objective: This study aims to evaluate the need for a screening management information system at dr. Hasri Ainun Habibie Gorontalo and developed. As well as seeing the level of user satisfaction after the development of a prescription screening management information system Methods: The research conducted is quantitative descriptive. The data collection of system needs analysis was carried out by looking directly at the system at dr. Hasri Ainun Habibie Gorontalo Hospital. As well as evaluating the system using the End User Computing Satisfaction (EUCS) method by distributing questionnaires to pharmaceutical officers. After obtaining an analysis of the system needs, the design of the prescription screening management system was made using context diagrams, data flow diagrams (DFD), and entity relationship data (ERD). Data analysis to see the increase in satisfaction using the wilcoxon signed rank test. Results: The results of the observation of the completeness of prescription screening in the system at dr. Hasri Ainun Habibie Gorontalo Hospital show that administrative, pharmaceutical and clinical screening has not been fully completed. Meanwhile, the pretest results of the evaluation of the system that has been implemented in the hospital show that the frequency of respondents' answers in the dissatisfaction scale category in variable content is 97.2% and accuracy is 55.6%. However, after system development and re-evaluation as a result of the posttest, the results were obtained that the suitability of administrative, pharmaceutical and clinical screening on the satisfactory scale in variable content was 58.3%, format 51.9%, ease of use 66.7%, timeliness 55.8%, and very satisfied scale at variable accuracy 55.6%. Analysis of pretest and posttest data using the Wilcoxon test showed a significant value (p) of 0.007. Conclusion: The results of the evaluation and design of the prescription screening management information system have met the criteria and received increased satisfaction from system users. So that the system is ready to be implemented at dr. Hasri Ainun Habibie Gorontalo Hospital.

Cloud-Based Institutional Quality Assurance Model for a Local Higher Education Institution Using Data Mining Techniques

This study presents a Cloud-Based Institutional Quality Assurance Model for Local Higher Education Institutions (LHEIs). It utilizes advanced data mining techniques and custom data models that enhance the monitoring, assessment, and improvement of quality assurance processes through the utilization of cloud computing infrastructure in a developed system that offers scalability, flexibility, and accessibility, empowering policymakers to make data-driven decisions and to efficiently analyze vast amounts of data collected from various sources and be guided by algorithms. The findings advance quality assurance methodologies and offer valuable insights for practitioners, policymakers, and researchers in higher education.

Cucurbit[8]uril Mediated Supramolecular Heterodimerisation and Photoinduced [2+2] Heterocycloaddition to Generate Unexpected [2]Rotaxanes.

In contrast to the self-assembly of homosupramolecules, the self-assembly of heterosupramolecules is more challenging and significant in various fields. Herein, we design and investigate a cucurbit[8]uril-mediated heterodimerisation using an arene-fluoroarene strategy. Moreover, the resulting heteroternary complex is found to be able to undergo a photoinduced [2+2] heterocycloaddition, resulting in the formation of an unexpected [2]rotaxane structure. This work demonstrates a novel supramolecular heterodimerisation system, not only contributing to the development of photoisomerisation systems, but also enriching synthetic methodologies of mechanically interlocked molecules.

An advanced kernel search optimization for dynamic economic emission dispatch with new energy sources

Integrating renewable energy sources, such as wind and photovoltaic power generation, into the power grid is crucial for sustainable power system development and mitigating pollutant emissions. However, these sources’ inherent uncertainty and randomness pose significant challenges to grid operations. Metaheuristic algorithms offer efficient solutions to optimization problems in this context and are widely employed in practice. Kernel Search Optimization (KSO) has emerged as a prominent metaheuristic algorithm due to its parameter-free nature and applicability to power dispatch problems. Nevertheless, KSO’s limited local search capabilities necessitate enhancements for improved performance. This paper introduces an enhanced variant of KSO, termed Upgraded Kernel Search Optimization (UKSO), which incorporates differential evolution techniques, including mutation, crossover, and selection mechanisms, to bolster KSO’s search capabilities and overall performance. The efficacy and feasibility of UKSO are evaluated through comprehensive testing using the CEC2017 benchmark. Comparative analysis demonstrates that UKSO outperforms other algorithms by achieving more optimal solutions. To address power dispatch challenges in the context of renewable energy sources, a Two-Time Energy Dispatch (TTED) model is proposed, leveraging a weighted summation approach to minimize total fuel costs and pollution emissions simultaneously. The application of the Prophet model, based on Bayesian fitting, facilitates accurate prediction of wind and photovoltaic power outputs. Through experimentation across small (8 and 14 units) and large (58 units) systems, the feasibility of UKSO and TTED is validated. In complex scenarios, UKSO demonstrates a 0.69% to 3.64% reduction in pollution emissions and a 0.99% to 1.23% decrease in economic costs compared to KSO under varying weight configurations. Furthermore, UKSO achieves a renewable energy generation utilization rate exceeding 90%, emphasizing its ability to iterate efficiently through complex problems and its efficacy in addressing renewable power dispatch challenges. These results highlight the practical significance of UKSO in optimizing power systems and provide valuable insights for future research and applications in this domain.

Harmonic Resonance Mechanisms and Influencing Factors of Distributed Energy Grid-Connected Systems

With the rapid development of global energy transformation and new power system, ensuring the stability of distributed energy grid connections is the key to maintaining the reliable operation of the whole power system. This paper constructs detailed impedance models of grid-following (GFL) and grid-forming (GFM) inverters using a harmonic linearization method and thoroughly investigates the mechanisms of resonance when inverters are connected to the grid, as well as the impact of model parameters on the stability of the grid system. This paper also briefly analyzes the scenario where distributed energy and electric vehicles are integrated into the grid simultaneously, demonstrating that grid system stability can be ensured in complex grid situations through reasonable parameter design. Lastly, the accuracy of the proposed impedance models and analysis is verified through MATLAB/Simulink simulations.

Банковская паника в условиях цифровой трансформации общества: особенности возникновения и меры предотвращения

This article delves into the specifics of bank run emergence amidst society’s digital transformation, highlighting features such as rapid information transmission, increasing vulnerability risks of financial systems to new forms of fraud and cyber threats, utilization of artificial intelligence, and investments in payment systems and cryptocurrency. The banking system, as the main instrument of financial activity, is exposed to transformational changes, which necessitates its constant adaptation to new operating conditions, including to prevent uncontrolled panic reactions on the part of depositors, the consequences of which any financial organizations may face. The author proposes a few measures aimed at preventing or mitigating the consequences of bank runs in the financial sector, encompassing both urgent steps in the field of cybersecurity and risk management, as well as regulatory actions by the state and financial organizations. In general, the successful prevention of bank runs requires an integrated approach that includes information, technical and financial measures, as well as the development of an economic education system and an increase in financial literacy.

Edge computing and AI-driven intelligent traffic monitoring and optimization

Intelligent transportation system is a comprehensive system engineering, involving real-time data processing, security and privacy protection and other challenges. This paper discusses the key role of edge computing in intelligent transportation, especially its combination with SLAM technology. Edge computing enables faster data processing and response times by placing computing and data storage resources near the data source and end users, improving the efficiency and reliability of intelligent transportation systems. At the same time, edge computing can also enhance information security and privacy protection, and bring more possibilities for the future development of intelligent transportation systems. In the future, with the progress and development of technology, we can look forward to the deeper application of edge computing and SLAM technology in the field of intelligent transportation, bringing more innovation and development to smart city transportation.

Challenges of resilience training for military personnel in the Lithuanian Armed Forces

Resilience is a complex phenomenon that results from the natural human response to adapt to change through the ability to cope with or respond to threats. In today’s security challenges, military personnel are responsible for the defense of their country, and exposure to unfamiliar situations can harm the ability of military personnel to perform successfully. Therefore, this study aims to identify the challenges in resilience training for the Lithuanian Armed Forces military personnel. The study uses a qualitative research method and an in-depth interview. Eight military psychologists participated in the study. The selection criteria for the informants were currently employed/serving in the military with at least five years of experience and participating in resilience training. The results revealed that there has been significant recent attention to and need for resilience training in the Lithuanian Armed Forces, but that resilience development is fragmented. The findings show that the lack of a unified concept of resilience in the Lithuanian Armed Forces complicates the development of a unified resilience training system. Summarizing the organizational aspects of resilience training for military personnel in the Lithuanian Armed Forces, the following key challenges were identified. There is a lack of leadership support for resilience education; the need for the development of trainers or responsible persons involved in resilience education; the lack of a clear perception of the value of resilience education among trainers; the need for unification and systematization of the education system through the updating/creation of the use of a system for feedback and evaluation. AcknowledgmentWe acknowledge General Jonas Žemaitis Military Academy of Lithuania for financial support in publishing this article.

Exploring the impact of maternal factors and dietary habits on human milk oligosaccharide composition in early breastfeeding among Mexican women

Human milk oligosaccharides (HMOs) promote adequate intestinal microbiota development and favor the immune system's maturation and cognitive development. In addition to non-modifiable factors, HMOs composition can be influenced by other factors like body mass index and eating habits, but the reports are discrepant. The aim of this work was to describe the correlation between maternal factors and HMOs concentration in colostrum in 70 women from northeastern Mexico categorized into women with normal weight and women with overweight or obesity. The absolute concentration of six HMOs were significantly lower in women with overweight or obesity compared to women with normal weight (LNFPI p = 0.0021, 2’-FL p = 0.0304, LNT p = 0.0492, LNnT p = 0.00026, 3’-SL p = 0.0476, 6’-SL p = 0.00041). Another main finding was that the frequency of consumption of food groups such as vegetables, fruits and meats was positively correlated to specific HMOs (Poblano chili and 2’-FL; rs = 0.702, p = 0.0012; Orange or tangerine and 3-FL; rs = 0.428, p = 0.0022; Chicken and 2'-FL; rs = 0.615, p = 0.0039). This study contributes to the elucidation of how maternal factors influence the composition of HMOs and opens possibilities for future research aimed at mitigating overweight or obesity, consequently improving the quality of human milk.

A Bibliometric Analysis of Suspension System Development for Enhancing Comfort in Family Passenger Vehicles

In daily-used family passenger cars, passenger comfort is crucial. Vehicle suspension is a major factor in passenger comfort. A detailed suspension domain knowledge evaluation is necessary. Despite continual comfort technology advances, studies have yet to use bibliometric analysis to track suspension system history and expansion. This study analyzes keywords, citations, h-index, publishing years, journals, affiliations, nations, authors, and review articles in a novel way. Based on Scopus, the analysis is performed in CSV format and incorporated into bibliometric.org's Biblioshiny, VOSviewer, and R-studio apps. The US leads this study, followed by India and Canada. Indian publications are the most prolific. For suspension technology makers, this research may help them discover rivals and predict future trends. This study promotes suspending technology development through educated decision-making, strategic planning, and innovation.

An eddy current sensor for end-point detection in chemical mechanical planarization using composition signal filtration and a digital potentiometer

End-point detection (EPD) is important for controlling the chemical mechanical polishing process to prevent underpolishing and overpolishing. One EPD method using the relative current density on a Cu wafer involves an eddy current, which has advantages of noncontact and a fast response speed. However, the eddy current method has a large mean error at a low relative current density. To overcome the disadvantage, composition signal filtration uses a high mean error and long delay time using a moving average and 1-D Kalman filtration. After applying composition filtration, the mean error improved by approximately 94.7 %. Still, it is difficult to measure a thickness of 4000 Å or less with existing systems. A digital potentiometer was developed that changed the resistance in real time and improved the detection range. The step number for changing the resistance was 120 steps in the resistance range of 100–5000 Ω at approximately 40 Ω/step. When a digital potentiometer was applied, the EPD detection range improved by 85.8 % over the existing system. In other words, the developed system could measure a Cu wafer thickness of 586 Å.

The Current State of Research on the Development of Entrepreneurial Competence in Vocational Education

This research paper delves into the current state of outline of entrepreneurial competence development in vocational education. It analyzes the research problems of domestic and international researchers from 2016 to the present, drawing conclusions about the effectiveness of the economic component of content in vocational education and the level of development of entrepreneurial competence for changing students' economic behavior. The research identified a prevalence of theory over practice, highlighting the challenge of implementing entrepreneurial practices, internships, mobility programs, and grant project participation for educators and students. The study underscores the need for state support and assistance for future entrepreneurs, improvement of the quality and quantitative indicators of the effectiveness of students, and official registration of youth startups. The study offers recommendations for enhancing the pedagogical effectiveness of entrepreneurial competence development in the vocational education system: curriculum revision: review and update the content, means, and methods of instruction to incorporate interactive learning forms that foster entrepreneurial competence development; personnel education: training future teachers of vocational (technical and vocational education) who are capable of developing entrepreneurial competence; institutional collaboration: establish cooperation between state institutions (vocational education institutions and employment centers) to provide graduates of vocational educational institutions with non-reimbursable state financial assistance for entrepreneurial activities. The study emphasizes the crucial role of entrepreneurial competence development in preparing students for the dynamic and competitive labor market. By implementing the proposed recommendations, vocational education institutions can effectively equip students with the necessary skills, knowledge and attitudes to navigate the entrepreneurial activities and contribute to economic growth.

Controlled Fluid Flow Without Controlling Pump Through Arduino

Various Industries like Chemical, Energy, Nuclear, Process, Manufacturing, Healthcare, and Agriculture require the flow rate to be controlled. It may be constant, steady state, or between the specific upper and lower range. The article explained the development of a cost-effective fluid flow control system using an Arduino microcontroller. The direct use of the pump is not good because there are a lot of challenges (Corrosion, Power fluctuations, Pressure leak) with the pump and with time as it gets old, the chances of getting good, desired flow from it are not possible. We achieved the controlled flow rate (volume rate and mass rate) in a very precise and cost-effective manner. Because the flow corresponding to the height is steadier and more constant than getting steady flow from the pump. Hence, our solution is that we don’t get direct flow from the pump but from Tank B. Tank B must be very carefully designed (especially its height and cross section) to get the desired value of the flow rate from it, as per Bernoulli’s Theorem the flow velocity has a direct relation with the height. We just used the pump to refill tank B up to the desired level. In this case, the flow rate only varies when there is a larger change in the head of the tank from which it is coming (It is tank B in our case). The pump automatically becomes ON when the flow rate drops below 2 and fills tank B again to the height which corresponds to the flow rate 3 and when the flow rate becomes 3 the pump becomes OFF automatically. The process is repeated until the desired process is completed. After Completion the valve from Tank B can be closed. The Hardware integrations, Software Programming Logic, and Physical experimental setup are discussed.

AR Platform for Indoor Navigation: New Potential Approach Extensible to Older People with Cognitive Impairment

Abstract: Background: Cognitive loss is one of the biggest health problems for older people. The incidence of dementia increases with age, so Alzheimer’s disease (AD), the most prevalent type of dementia, is expected to increase. Patients with dementia find it difficult to cope with their daily activities and resort to family members or caregivers. However, aging generally leads to a loss of orientation and navigation skills. This phenomenon creates great inconvenience for autonomous walking, especially in individuals with Mild Cognitive Impairment (MCI) or those suffering from Alzheimer’s disease. The loss of orientation and navigation skills is most felt when old people move from their usual environments to nursing homes or residential facilities. This necessarily involves a person’s constant presence to prevent the patient from moving without a defined destination or incurring dangerous situations. Methods: A navigation system is a support to allow older patients to move without resorting to their caregivers. This application meets the need for helping older people to move without incurring dangers. The aim of the study was to verify the possibility of applying the technology normally used for video games for the development of an indoor navigation system. There is no evidence of this in the literature. Results: We have developed an easy-to-use solution that can be extended to patients with MCI, easing the workload of caregivers and improving patient safety. The method applied was the use of the Unity Vuforia platform, with which an augmented reality APK application was produced on a smartphone. Conclusion: The model differs from traditional techniques because it does not use arrows or labels to identify the desired destination. The solution was tested in the laboratory with staff members. No animal species have been used. The destinations were successfully reached, with an error of 2%. A test was conducted against some evaluation parameters on the use of the model. The values are all close to the maximum expected value. Future developments include testing the application with a predefined protocol in a real-world environment with MCI patients.