System Platform Research Articles

Development Trends and Main Problems of P2P and Crowdfunding Platforms in RA Banking System

The work is aimed at highlighting the developments and main problems related to P2P and Crowdfunding platforms in Armenia which may be an obstacle to their mass use. In order to understand whether the mentioned fintech solutions are effective from the point of view of usage in RA we tried to conduct comparisons in the context of international experience and evaluate the environment of the RA banking system from the point of view of introducing and developing the latest fintech solutions, highlighting the positive aspects. The results were the basis for making appropriate conclusions and suggestions for the introduction and development of these technologies in RA.

Research on the Teaching Resource Construction System of Computer VR Online Interactive Experiment Platform for Mechanical Engineering Graphics

The introduction of three-dimensional design experiment teaching in engineering drawing teaching. The experimental platform of "network engineering drawing" is established, and the corresponding multimedia teaching software is developed using WebVR, ASP, database and other technologies. The 3D modeling method of the reducer is established by using UGNX and optimized accordingly. In order to solve the problem that UGNX mode introduces packet loss in the simulation system, the model and data are reconstructed separately. Using VisualStudio2019 as the development platform, the 3D modeling of the reducer is realized. The establishment of the engineering graphics design virtual simulation system helps enterprises to simulate operations before actual production and processing. It greatly improves production efficiency and reduces production costs.

An Automatic Monitoring System for Dragon Fruit Using Convolutional Neural Networks (CNN) and Internet of Things (IoT)

Plant diseases and pests have led to a decline in the quality of dragon fruit produced in Banyuwangi regency, Indonesia. Infections in dragon fruit cause rot, and farmers struggle to identify the pests responsible. To address this problem, this work proposed two concepts for the classification and monitoring systems of dragon fruit. The classification was done by processing some images of dragon fruits captured by DLSR camera and utilizes a convolutional neural network with three layers for training and testing. The monitoring system is based on the Internet of Things to tracks the status of ripe, raw, and rotten fruits. The application of the dragon fruit classification system to ripe, rotten, and raw fruits has yielded results that increase fold accuracy by 0.976, 0.981, and 0.986, respectively, with 200 training data in each of the three training and testing phases. There is a decrease of 0.024, 0.019, and 0.014 in fold loss accuracy. Meanwhile, the monitoring system's platform integrates the classification of dragon fruit to monitor the condition of ripe, raw, and rotting fruit in real time. With the implementation of the classification and monitoring system, farmers will be better equipped to predict when dragon fruit will ripen and prevent the spread of rot to other fruits.

Energy efficiency and performance analysis of a legacy atomic scale materials modeling simulator (VASP)

This work tackles the performance and energy consumption analysis of a legacy scientific application, the VASP (Vienna Ab-initio Simulation Package), an application commonly used by physicists and chemists for modeling materials at the atomic scale. Many of these scientific applications have been implemented in Fortran, where energy metrics instrumentation is not straightforward. We obtained performance figures (execution time and energy consumption) by instrumenting the source code using EML. This energy measurement library has been modified to introduce Fortran interfaces for these metrics. The analysis was carried out using different matrix algebra libraries, parallelization techniques, and hardware platforms, emphasizing on the MPI, OpenMP, and CUDA parallel implementations of the algorithms used in VASP. We employ various material specifications (atomic structures) and molecular sizes of a silicon-based crystal to create a set of benchmarks for these specifications, leading to some recommendations for final users regarding performance improvements. The proposed benchmarking technique assists the user in selecting the right combination of problem size, compilers, and parallelization options available in VASP. For a given system platform, the user will be able to determine not only the architecture to use (GPU or multicore processors), but also the appropriate library and parallelization according to the atomic structure and molecular size.

Using public participation gis to understand texas coastal communities’ perceptions and preferences for urban green space development in connection to their perceptions of flood risk

Urban green spaces, a form of green infrastructure, provide cities with a number of opportunities to build urban resilience to withstand a wide range of urban challenges, such as land-use change, climate change, biodiversity loss, and physical and mental health. Despite their benefits to communities, urban green spaces are among the most valuable and attractive areas for development and are most susceptible to urban development. Therefore, careful planning of the green space network is needed,requiring diverse voices from not only city policymakers and planning experts but also local residents. This study investigated residents’ perceptions and preferences for green space development and its association with perceived flood risk. Data were collected from residents residing in two Texas Gulf Coast cities via a Public Participation Geographic Information System (PPGIS) platform. Our analyses revealed that Texas Gulf Coast residents assigned a full spectrum of landscape values to their existing urban green spaces with aesthetic and recreation values being most frequently identified. Notably, across the city landscape, urban green spaces that were most favored by residents tended to be green spaces with water bodies, large in scale and offered a broader array of facilities/amenities. These spaces were also identified as flood-prone areas, presenting opportunities for green space improvement, flood protection, and preservation. In addition, we observed a significant association between residents’ risk perception and the number of locations across the city landscape they perceived as posing the greatest flooding threat. Our findings illustrate a need to promote multiple landscape values of urban green spaces, especially in its ability to protect the city from future flooding. This research highlights how PPGIS can support green infrastructure planning as well as enhance public participation in green infrastructure planning processes.

A Nano Scale Machine Learning Assisted Natural Language Processing Framework for Sentiment Classification in Smart System Platform

A Nano Scale Machine Learning Assisted Natural Language Processing Framework for Sentiment Classification in Smart System Platform

SiC@NiO Core-Shell Nanowire Networks-Based Optoelectronic Synapses for Neuromorphic Computing and Visual Systems at High Temperature.

1D nanowire networks, sharing similarities of structure, information transfer, and computation with biological neural networks, have emerged as a promising platform for neuromorphic systems. Based on brain-like structures of 1D nanowire networks, neuromorphic synaptic devices can overcome the von Neumann bottleneck, achieving intelligent high-efficient sensing and computing function with high information processing rates and low power consumption. Here, high-temperature neuromorphic synaptic devices based on SiC@NiO core-shell nanowire networks optoelectronic memristors (NNOMs) are developed. Experimental results demonstrate that NNOMs attain synaptic short/long-term plasticity and modulation plasticity under both electrical and optical stimulation, and exhibit advanced functions such as short/long-term memory and "learning-forgetting-relearning" under optical stimulation at both room temperature and 200°C. Based on the advanced functions under light stimulus, the constructed 5×3 optoelectronic synaptic array devices exhibit a stable visual memory function up to 200°C, which can be utilized to develop artificial visual systems. Additionally, when exposed to multiple electronic or optical stimuli, the NNOMs effectively replicate the principles of Pavlovian classical conditioning, achieving visual heterologous synaptic functionality and refining neural networks. Overall, with abundant synaptic characteristics and high-temperature thermal stability, these neuromorphic synaptic devices offer a promising route for advancing neuromorphic computing and visual systems.

Exploring the prevalence of internet crimes among undergraduate students in a Nigerian University: A case study of the university of Ilorin

Internet crime, also known as cybercrime, encompasses various illicit activities conducted through computer system and online platforms. It is a global menace that has become a pervasive issue in our contemporary society. This study delves into exploring the prevalence of internet crime among undergraduate students at the University of Ilorin with the view to examine the level of involvement of undergraduate students, identify the underlying factors, the perceived consequences, and potential control measures associated with undergraduates' involvement in internet crime. The study engaged a sample size of 400 undergraduate students, employing a stratified sample technique for comprehensive data collection using a structured questionnaire. The research revealed that the participants acknowledged the prominence of internet crime within their peer group. It uncovered the multifaceted factors contributing to the prevalence of internet crimes. The respondents acknowledged the perceived consequences of undergraduates' involvement in internet crime, encompassing financial mismanagement, expulsion from educational institutions, societal stigma, loss of personal integrity, legal consequences, and limited access to future opportunities. To mitigate this growing concern, respondents recommended various control and combative measures. These encompass the implementation of stringent rules within educational institutions, effective monitoring of students' financial activities, awareness campaigns against internet crime, provision of employment opportunities, engaging experts to address the issue, banning tools facilitating internet crime, and organizing training workshops to enhance legitimate ICT skills and wealth generation. This study sheds light on the pressing need for proactive interventions to curb internet crime among undergraduate students, emphasizing education, awareness, and policy implementation to foster a safer online environment and deter involvement in criminal activities.

Mobile Smart App and its Application in Improving the Efficiency of English Homework Correction

The heavy amount of English homework correction has resulted in Teachers’ lax examination of homework, insufficient attention to homework problems, and low attention to homework correction. With the continuous growth of the number of educated people, more and more schools begin to have the problem of low efficiency of English homework correction. Therefore, in order to optimize the homework correction system, improve the efficiency of English teachers’ homework correction, and give full play to teachers’ positive feedback on homework, a smart app on mobile phone can be developed to scan and correct traditional paper homework. Based on image processing technology and neural network algorithm, this paper designs and establishes a mobile app that can recognize and extract English homework topics and handwriting with nearly 90\% accuracy through Android system platform. Based on the homework answers entered in the database, the rapid correction of English homework can be realized. After using this software, the overall efficiency of English homework grading has significantly improved. For multiple-choice and fill in the blank questions, the total factor productivity of 14 and 15 units was greater than 1, accounting for 63.6\% and 68.1\% of the nursing units participating in the study, respectively. This indicates that the efficiency of English homework grading in most units is constantly improving and showing a good development trend. Among them, the homework correction efficiency for multiple-choice questions is only 6 units, and the pure technical efficiency is less than 1, indicating that the improvement of technical means has a significant impact on efficiency. In order to verify the applicability of the software, data envelopment analysis is used to analyze the application of the mobile app to improve the efficiency of English homework correction. the results show that when the smart phone software is not put into use, the efficiency of teachers’ English homework correction is poor, and the technical level in the process of correction is too low. After the mobile intelligent software is put into use, the overall efficiency of English homework correction has increased significantly, which can greatly alleviate the pressure faced by English teachers in the process of correcting homework.

Design and Implementation of an SGX Based Electricity Information Collection and Management System

With the rapid growth of the number and scale of smart grid users, traditional data encryption transmission methods can no longer meet the performance requirements of data aggregation. In response, a power consumption information collection and management system based on SGX software protection extension is proposed. The system mainly consists of three parts: user electricity data acquisition terminal, SGX data security processing and distributed storage module on the chain, and data monitoring management display platform. The user electricity data collection terminal collects electricity data from various buildings, residences, rooms, and other smart meters, analyzes and uploads it. After calling the trusted function of SGX technology, it enters the security zone provided by SGX for data processing. Finally, the data security processing results and data are uploaded to the blockchain for storage. In order to visually display user electricity usage data, an intelligent monitoring platform for user electricity collection and management has been established. This system can reduce the workload of user electricity data collection, ensure the accuracy of data collection, and provide an efficient and highly reliable system platform for user electricity data management.

The Comparison of Experiments in Embedded System Course

The embedded system is designed to perform specific computation tasks and usually embedded in other devices. Unlike normal personal computer and cloud server, it is not for daily use but production environment with higher stability and reliability demands in various fields with fixed functionalities, smaller size and lower power consumption for the use of portable and power limit situations. The course of embedded system generally contains fundamental concepts, hardware architecture, software development, bootloader and kernel development, etc. It is a course closely integrating theory and experiments, with the purpose of making resource optimization and management, power efficiency, security and integrity. As a course in university, there are many factors that teacher needs to take into consideration before conducting the experiments in embedded system. In this paper, various factors relevant to the experiments, such as the system architecture, platform, and principles, are discussed in details for the comparison of embedded system experiments.

The Role of Low Lactose Feeding for Preventing Childhood Malnutrition and Long-Term Gut Damage Caused by Recurrent Diarrhoeal Disease

Even though it has decreased over the past three decades, diarrheal sickness continues to be a major global cause of death for children. There is a strong correlation between childhood rotavirus, diarrhea, climate factors, and malnutrition. On the other hand, a significant nutritional shift (lower levels of undernutrition) among children mal five has been documented in the last ten years, especially in developing nations like Bangladesh, where rotavirus infection has also been on the rise. Given the pathophysiology of rotavirus, there may be a link between the changing diet, the environment, and other artificial factors in urban areas such as Dhaka, Bangladesh, and the rise in rotavirus infections. Under-five malnutrition is still a major problem in Bangladesh, despite significant socioeconomic progress and ten years of initiatives to reduce it. Many research have been conducted in an attempt to identify the primary risk factors for malnutrition; however, none of these have looked into the importance of low birth weight (LBW) 36%. Bangladesh has seen a notable decline in the incidence of pediatric diarrhea deaths in recent decades. Over the past few decades, Bangladesh, a heavily populated country with limited resources, has managed to achieve a notable reduction in the death rate of pediatric diarrhea. Some of the obstacles that still need to be overcome in order to further lower the burden of disease and mortality brought on by diarrhea are enhancing hand hygiene practices, expanding zinc coverage for diarrhea treatment, and maintaining nutritional improvement. To increase intervention coverage and hasten the end of diarrheal mortality among children in Bangladesh, ongoing collaboration with non-governmental organizations and the private sector is necessary, as is the adoption of pluralistic health system platforms for the delivery of preventative and curative services.

Epidemiological characteristics and genotype trends of rotavirus diarrhea in China from 2009 to 2020

Objective: To investigate the epidemiological characteristics and genotype trends of rotavirus infection among the population with diarrhea in China, from 2009 to 2020 and provide evidence for strategic surveillance and prevention. Methods: Surveillance data on diarrhea syndrome from 252 sentinel hospitals across 28 provinces (municipalities, autonomous regions) were obtained from the information management system of the Infectious Disease Surveillance Technology Platform of the National Science and Technology Major Project. Descriptive epidemiological methods were employed to analyze the distribution of rotavirus diarrhea cases in different climatic zones, populations, and times from 2009 to 2020, as well as the genotyping characteristics and changing trends of group A rotavirus diarrhea cases. Results: From 2009 to 2020, a total of 114 606 diarrhea cases were tested for rotavirus, and the positive rate was 19.1% (21 872/114 606); group A rotavirus was dominant (98.2%, 21 471/21 872). The positive rate of rotavirus was the highest in 2009 (36.9%, 2 436/6 604) and 2010 (30.6%, 5 130/16 790), fluctuated between 14.0% to 18.0% from 2011 to 2017, raised slightly in 2018 (20.3%, 2 211/10 900), and declined continuously in the following two years (15.5%, 2 262/14 611 and 9.5%, 470/4 963). The positive rate of males (20.2%, 13 660/67 471) was significantly higher than that of females (17.4%, 8 212/47 135). Children under five had the highest positive rate (28.4%, 18 261/64 300), more than four times that of adults. The positive rate peaked from December to February in the mediate temperate zone, warm temperate zone, and subtropical zone, while there were two peaks from November to January and May to June in the frigid zone of the plateau. The dominant genotype of group A rotavirus gradually changed from G3P[8] and G1P[8] to G9P[8] during 2009-2020. Conclusions: The overall rotavirus infection rate in China was on a downward trend. Meanwhile, significant variations of positive rates were observed in seasonal epidemics and different age groups from 2009 to 2020. Rotavirus diarrhea in children was still a prominent concern. Vaccination of rotavirus vaccine should be promoted, and the epidemiological characteristics and genotypes of rotavirus diarrhea should be continuously monitored.

Optimizing Warehousing Strategies for Retail Food Live Streaming on Supply Chain Cost: A Case Study of TikTok

The outbreak has indeed left a significant impact on the traditional offline sales model. However, it has simultaneously catalyzed the flourishing growth of the e-commerce live-streaming industry. Consumers have progressively adapted to this novel online shopping mode, signifying a paradigm shift in retail dynamics. Therefore, this paper studies the cost problem under different strategic choices of logistics and warehousing for retail food from the perspective of a platform system and analyzes the after-sale cost of a two-level retail food supply chain consisting of a manufacturer and an e-commerce platform by combining data and theory. This study further analyzes the optimal decision problem for e-commerce cloud warehousing, traditional warehousing systems and a combination of e-commerce cloud warehousing and traditional warehousing systems. This study not only enhances our understanding of the profound shifts in the retail food sector but also equips e-commerce platforms with concrete theoretical insights and practical references to bolster their supply chain cost management strategies in a post-outbreak era characterized by evolving consumer preferences and dynamic market conditions.

Optimization Techniques and Evaluation for Building an Integrated Lightweight Platform for AI and Data Collection Systems on Low-Power Edge Devices

Amidst an energy crisis stemming from increased energy costs and the looming threat of war, there has been a burgeoning interest in energy conservation and management worldwide. Industrial complexes constitute a significant portion of total energy consumption. Hence, reducing energy consumption in these complexes is imperative for energy preservation. Typically, factories within similar industries aggregate in industrial complexes and share similar energy utilities. However, they often fail to capitalize on this shared infrastructure efficiently. To address this issue, a network system employing a virtual utility plant has been proposed. This system enables proactive measures to counteract energy surplus or deficit through AI-based predictions, thereby maximizing energy efficiency. Nevertheless, deploying conventional server systems within factories poses considerable challenges. Therefore, leveraging edge devices, characterized by low power consumption, high efficiency, and minimal space requirements, proves highly advantageous. Consequently, this study focuses on constructing and employing data collection and AI systems to utilize edge devices as standalone systems in each factory. To optimize the AI system for low-performance edge devices, we employed the integration-learning AI modeling technique. Evaluation results demonstrate that the proposed system exhibits high stability and reliability.

Ultrasensitive detection of PSA in human serum using Label-Free electrochemical biosensor with magnetically induced Self-Assembly based on α-Fe2O3/Fe3O4@Au nanocomposites

To achieve the goals of early diagnosis, screening, and precision medicine for prostate cancer, this research designed a label-free electrochemical biosensor by combining magnetic probes (PSAA/α-Fe2O3/Fe3O4@Au) with magnetically induced self-assembly (MISA) technology to explore the application of prostate-specific antigen (PSA) in precise detection. Magnetic α-Fe2O3/Fe3O4 nanoparticles (NPs) were constructed using a hydrothermal-calcination reduction method. Subsequently, α-Fe2O3/Fe3O4@Au nanocomposites were prepared by reducing HAuCl4 with NaBH4 at a low temperature. The self-assembly method was adopted in two steps: firstly, the sulfhydryl-modified PSA aptamer is immobilized onto the material surface using Au–S bonds; secondly, the magnetic NPs and magnetic glassy carbon electrode (MGCE) undergo self-assembly. The biosensor showed good linear response in the range of 100 fg/mL to 100 ng/mL, with a detection limit of 0.78 pg/mL (S/N = 3) under optimal conditions. Repeatability, stability, selectivity, reproducibility, and the capability to analyze real samples were also investigated. With its cost-effectiveness, operational simplicity, and speed of analysis, the biosensing system platform holds great potential as a valuable tool in clinical PSA detection for point-of-care testing (POCT).

Управление дистрибуцией межрегиональных цепей поставок в рамках взаимодействия с технологиями искусственного интеллекта

Target: in the article, the authors reveal new approaches to managing logistics supply chains within the framework of the sixth technological order: the main structural elements of a modern infrastructure for managing logistics flows are presented, including a production complex equipped with industrial specialized 3D printers; warehouse complex in regions close to sources of raw materials and to regions of the largest volumes of orders; infrastructure of logistics regional distribution systems, including the transport component within all types of transport, including unmanned vehicles. Methods: the author’s view on management objects, supply flow management models within the framework of the formation of a new interregional spatial infrastructure is proposed; identified features of supply chain management within the framework of adding elements of remote and virtual reality technologies; the author’s approach to the interpretation of the concept of “supply chain management” is formulated within the framework of the formation of an expanded data system and ordered space with the aim of organizing interregional warehouses with the possibility of duplicating them in the region where the order is placed. Results: the authors have developed an algorithm for the functioning of a flow management model within the framework of a logistics system platform and a new spatial infrastructure using industrial specialized 3D printers under the control of artificial intelligence technologies, which make it possible to reproduce the necessary goods in the region where the order is made. Practical significance: in addition, the article reveals the principles of implementing the process of managing logistics flows; approaches to the classification of distribution types from the location of sources of raw materials within the processes of production of goods and intangible delivery of goods to the location of consumers are proposed; The prospects for the development of global supply chains are discussed using the example of a specific macroregion — Uzbekistan.

Hardware-in-the-loop simulation test platform for UAV flight control system

The flight control system is the integrated command center and core component of the UAV system. Aiming at the problems of poor accuracy and low efficiency in the field measurement of flight control system parameters, combined with the configuration of the flight attitude sensor-vertical gyroscope, hardware-in-the-loop simulation technology, and integrated automatic test methods are adopted. The hardware-in-the-loop simulation test platform for the UAV flight control system composed of a low-cost, high-precision miniaturized UAV attitude calibration platform and a control piston deflection angle test device is designed. The main controller replaces the ground master control station of the UAV and directly sends remote control commands to the aircraft. By changing the attitude of the aircraft, and measuring the voltage of the control signal, the feedback signal, and the rudder angle, the comprehensive performance test of the parameters of the flight control system is realized. The performance test of the platform shows that the platform can meet the test requirements of angular position, system voltage, and control piston deflection angle.

IJCM_262A: Digital Health Boon or Bane: From Community Health Worker’s Perspective in an Aspirational District

Background: Digital health technologies are pivotal for achieving Universal Health Coverage (UHC) and Sustainable Development Goal 3. This study investigates Community Health Workers (CHWs) perspectives on digital health platforms in an aspirational district in India, aligning with the World Health Organization’s emphasis on fostering an enabling environment for digital health adoption. Objectives: To assess CHWs’ current practices and knowledge of digital health applications/platforms and to understand their perceptions regarding the need and use of digital health platforms in the public health system. Methodology: A mixed-methods approach was utilized, involving 95 CHWs in quantitative surveys and 30 CHWs in qualitative interviews and focus group discussions. The study was conducted in Muzaffarpur, Bihar, India’s most populated aspirational district, using stratified random sampling and purposive sampling methods. Results: Findings reveal varied app usage patterns among CHWs, with challenges like non-functional government-provided devices. Qualitative insights highlight the importance of peer support and training quality alongside concerns about device accessibility and app rationalization. Despite government provision of smartphones, CHWs face obstacles in utilizing digital health tools effectively. Conclusion: This research illuminates the availability and utilization of digital health applications among CHWs, emphasizing the need to address challenges and tailor digital tools to enhance healthcare delivery in aspirational districts.

Automation of determining the compliance of domestic stainless steels with ISO classification material codes

For domestic stainless steels, criteria are developed for compliance with M group of processed materials according to the international ISO classification. An algorithm is proposed for determining codes according to the Coromant classification for stainless steels based on the grade of material, chemical composition, hardness and method of obtaining of the workpiece. The algorithm is implemented as part of an integrated CAM system for the KOMPAS-3D platform and is intended for use in calculation of cutting modes with imported carbide tools. Keywords:material, cutting mode, SANDVIK, KOMPAS-3D, CAM system, CNC schekin@inbox.ru, mayorovam@mail.ru