bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of fractal analysis for quantitative evaluation of graphite inclusions in the cast iron structure
Authors:   Iron and Steel Institute of Z. I. Nekrasov National Academy of Sciences of Ukraine, Parusov E. V. , Borisenko A. Yu. ,   Iron and Steel Institute of Z. I. Nekrasov National Academy of Sciences of Ukraine, Oliinyk E. V. ,   Iron and Steel Institute of Z. I. Nekrasov National Academy of Sciences of Ukraine, Chuiko I. M. ,   Iron and Steel Institute of Z. I. Nekrasov National Academy of Sciences of Ukraine, Parusov O. V. ,   Iron and Steel Institute of Z. I. Nekrasov National Academy of Sciences of Ukraine
Published: January 2025

The application of the theory of fractals in materials science during the analysis or modeling of various types of structures and their relationship with material properties is the most widespread, accessible and reliable direction. The purpose of the work was to determine the fractal dimension of graphite inclusions depending on their shape and distribution in the structure of gray cast iron. The search for the average fractal dimension of graphite inclusions was carried out in a computer program, the essence of which is to determine the closest convergence of fractal dimension values calculated using cell and point methods. An example of the application of the specified computer program and algorithm for determining the fractal dimensions of graphite inclusions and the metal matrix, as well as other structural elements of gray cast iron, is provided. The obtained calculated values have specific numerical values, therefore, in the future, they can be used to create analytical models for the predictive determination of the quality of gray cast iron depending on the type of final structure. It is shown that the problem of reliable and most accurate quantitative determination of graphite inclusions in the structure of gray cast iron can be solved using the method of fractal analysis. The considered method for determining the fractal dimension can be useful when studying the features of structure formation processes and evaluating the evolution of graphite inclusions at different stages of gray cast iron processing, starting from the smelting stage and ending with the final heat treatment. In addition, fractal analysis can be used to determine and evaluate the influence of morphological parameters of graphite inclusions on the formation of gray cast iron quality indicators, which cannot be achieved using traditional methods of quantitative analysis. Further research will be aimed at establishing statistically significant correlations of the fractal dimension with the properties of gray cast irons, in particular the behavior of the hardness change taking into account the formation of mixed or transitional type structures.
Determination of the initial heat output of the soaking pit under conditions of unstable operation of the metallurgical plant
Authors:   Ukrainian State University of Science and Technologies, Radchenko Yu. M. , Gupalo O. V. ,   Ukrainian State University of Science and Technologies, Rebrykov O. A. , Shtatskyi M. O. ,   Ukrainian State University of Science and Technologies
Published: January 2025

Abstract. The study is devoted to finding ways to improve the thermal performance of recuperative soaking pit when operating in modern conditions, which are characterized by unpredictability in the supply of fuel and energy resources to a metallurgical plant, the lack of a sustainable production program, the variety of ingots (billets), etc. The study aims to determine the rational operation mode for heating ingots (billets), which will ensure a minimum specific fuel consumption when fulfilling a production order. As a research method, the authors used methods for calculating metal heating and indicators of thermal performance based on the engineering theory of heating. The engineering model of heat transfer made it possible to obtain data on the temperature distribution across the ingot cross-section during heating without solving the differential heat conduction equation, as well as to calculate the duration of heating periods and heat losses of the working chamber of the well to the environment. Using the concept of thermal power made it possible to determine the main indicators of the thermal operation of the soaking pit: productivity, specific fuel consumption for heating the metal, and the efficiency of the soaking pit. The paper investigates the thermal performance of a recuperative soaking pit according to a typical operation mode of heating ingots (billets): the first period is heating with constant thermal power, the second is holding ingots (billets) at a constant temperature of the furnace chamber. It has been determined that when rectangular steel billets are heated, the minimum specific fuel consumption is ensured by operating a soaking pit with an initial natural gas consumption of 269-398 m3/hour. This heat rating of the soaking pit ensures an acceptable heating time for a metal mass of 29- 32 tons at the level of 3.4- 4.6 hours.
Impact of lean supply chain practices on competitive advantage in the private hospital sector in Sri Lanka
Authors: Wickramathunga Kasun , Patabendige Damindu , Udugampola Neranjan , Dilshan Samith , Karunarathna Navodika , Shamila Pubuddhi
Published: January 2025

Lean Practices have been implemented by private hospitals to get counterproductive solutions for reducing costs and gaining a competitive advantage. This research aims to examine the significance of lean practices on competitive advantage in the Sri Lankan private hospital sector to fill the knowledge gap. This research used a quantitative approach in which primary data was collected through a questionnaire-based survey and an analysis was conducted using structural equation modeling using the SmartPLS software. The research reveals the level of impact of lean practices, 5S, Kaizen, Kanban, and Just in Time in achieving a competitive advantage in the private hospital sector. Studies have demonstrated a significant impact of adopting the Just in Time approach in comparison to other established lean practices within the Sri Lankan private hospital sector, highlighting its unique and valuable contribution for health services. Researchers demonstrated when comparing Just in Time with other chosen lean practices for the study from the perspective of supply chain professionals, Just in Time contributes significantly to the competitive advantage of the Sri Lankan private hospital sector.
Digital Protection and Dissemination of Regional Culture Based on Digital Technology
Authors: Di Liang
Published: January 2025

In order to improve the effects of regional culture protection and communication,this paper proposed a digital technology to be used in regional culture protection.The digital algorithm is carried out to improve the digital processing of regional culture, and also effectively analyze the digital transmission process, so as to improve the transmission range and effect of the regional culture. The digital protection of regional culture is mainly focused on two kinds of informations :two-dimensional information and three-dimensional information. The different dimensions information of text, picture and video is obtained, in the meantime the corresponding process is analyzed; and the digital resource database of regional culture is formed which is in line with the museum system to analyze the communication paths of regional culture. In combination with the actual communication situation of traditional culture, the comprehensive protection and communication concept of the regional culture is analyzed which will provide related references for the after research.
Optimization of Cold Landscape Routes Based on GIS Technology - Promoting Economic Development in Ice and Snow Regions
Authors: Kai Zhao
Published: January 2025

Cultural tourism design in cold landscapes should be the focus of attention in the future. With the increasing number of cultural buildings in cold regions, this paper makes an in-depth study on this urgent problem. With people's desire for a healthy life, people's love for natural scenery and climbing is getting stronger and stronger. Mountain scenery has gradually become a favorite tourist destination in people's spare time. With the advent of big data, geographic information system technology can effectively solve the complex and unique problems in Hanshan scenic spot with its powerful spatial analysis function and data processing ability. In this paper, the geographic information system technology is used to make an in-depth analysis of the differences in the height and time of the scenic spots. It calculates the weight of different influencing factors reasonably, and finally provides the best cold and scenic routes for different types of people to climb mountains, keep fit and pilgrimage.
Research on Computer System-Based Home Fitness Gamification
Authors: Shuai Deng
Published: January 2025

With the increasing awareness of health, home fitness has gradually become an important lifestyle. Compared to traditional fitness methods, which are limited by time and space, home fitness offers a more flexible and convenient option. This study aims to explore computer system-based home fitness gamification schemes by reviewing literature, conducting comparative analyses, and analyzing brands to understand the technical characteristics and current usage of existing home fitness systems. By integrating the principles and mechanisms of sports games, we propose innovative home fitness systems. The results indicate that gamification elements significantly enhance users' fitness motivation and effectiveness. Although there are deficiencies in terms of cost, space, and technical support, improvements can be made by optimizing production processes, designing portable equipment, and enhancing technical support, thereby significantly improving user experience. Future research should focus on the application of virtual reality and augmented reality technologies, the development of personalized fitness plans, and the enhancement of social functions to meet diverse user needs. Computer system-based home fitness gamification schemes provide a scientific, efficient, and enjoyable way of fitness for modern households. Through technological innovation and improved user experience, home fitness systems will play a crucial role in the future. It is recommended to further study the application of virtual and augmented reality technologies, develop personalized fitness plans and real-time feedback systems, and integrate more health monitoring functions to provide comprehensive health management solutions, promoting the development and popularization of the home fitness industry.
Research on the Sustainable Development Model of Green Sharing Economy Based on Big Data Security
Authors: Xinzhan Liu
Published: January 2025

As an important product of the Internet era, the essence of green sharing economy is to rely on Internet technology. In particular, big data technology will re-use idle social resources and create new market value. However, with the increasing application of sharing economy in the field of green industry, the problems of data security, circulation, sharing and privacy protection gradually appear. Big data technology has become the biggest bottleneck for the further development of sharing economy. Blockchain technology is a new Internet architecture composed of various technologies and communication protocols. Through its encryption sharing, distributed ledger and other characteristics, it provides new methods and ideas for data circulation and sharing, which complement big data technology. Therefore, the integration of blockchain technology and big data technology can subvert the traditional business model of sharing economy. This can innovate the mode and development of traditional green industry, and provide new opportunities for the development of green sharing economy.
Research on Generative Design of Chinese Traditional Patterns Combining Random Clustering and Shape Grammar
Authors: Hao Hu
Published: January 2025

As the young generation of Chinese consumers pay more and more attention to and identify with traditional culture, the contemporary innovative design of Chinese Traditional Patterns has become a research hot spot in academia and industry. Generative design based on computer code has been widely used in architecture, automobiles, digital media, fashion and other fields, however the application of generative design technology in Chinese Traditional Patterns is still rare. Therefore, this paper tries to explore the generative design method of Chinese Traditional Patterns based on shape grammar theory on the basis of preserving the artistic characteristics of Chinese Traditional Patterns. Firstly, the cluster composition mode is extracted from the Chinese Traditional Pattern composition mode. Second, the concept of random cluster composition is proposed and its visual characteristics are analyzed by applying shape grammar. In the third step, based on the random function and shape operator, the generative design experiment of Chinese Traditional Patterns is carried out by using the visual programming language Grasshopper. Finally, a program code and a special plug-in which can automatically generate patterns are developed to verify the thesis.
Online Art Design Network Security Education System Based on Intelligent Image Processing Algorithm
Authors: Wenpin Zhu
Published: January 2025

In order to improve the effect of online art design education, based on 3D virtual simulation technology, this paper improves the traditional signal processing and image processing algorithms to construct an online art design education system based on 3D virtual simulation technology.The application server side of the online art design education system based on 3D virtual simulation technology constructed in this paper is each computer terminal, that is, a web browser. The database server is placed in the management service center and set up in each teaching service area. Moreover, users are connected to the management service center through the business network to realize data upload and information exchange.In addition, on the basis of algorithm improvement, this paper combines the functional requirements to construct the system structure, and combines the actual situation to verify the system performance.The experimental research results show that the system constructed in this paper has certain effects in the display of art design works and the improvement of teaching effects.
Research on the Safety and Stability of Scraper Conveyor Drive Based on Radial Basis Function Neural Network
Authors: Da Lv
Published: January 2025

In order to finally achieve the purpose of online detection of scraper conveyor jam and chain breakage fault, this paper proposes a method to determine the occurrence of scraper conveyor jam and chain breakage fault by identifying the sudden change characteristics of drive motor current. In this paper, radial basis function neural network is used as the basis for the kernel algorithm calculation of the scraper conveyor drive current characteristic recognition model, and the expansion principle and data fusion method are used to complete the diagnosis and fault tolerance control of the speed sensor, and the diagnosis and fault tolerance of the current sensor are realized by the expansion observer compensation state formula. To verify the feasibility of the method, the current data simulation of the scraper conveyor operation process is combined with the field provided. The simulation results show that the control strategy proposed in this paper can achieve power down diagnosis and fault-tolerant control of speed and current sensors, which is of practical significance for the stable operation of the scraper conveyor.
Design of a College Student Management Platform Based on Embedded Neural Network Algorithm for Network Security Technology
Authors: Meiyan Wang
Published: January 2025

With the rapid development of computer science and network technology, the education system is undergoing unprecedented changes, and the scale of universities continues to expand, which poses more stringent challenges to building an efficient and intelligent campus network environment. In this context, this study focuses on exploring optimization strategies for student management in the context of online culture, particularly by integrating embedded networks and data analysis technologies to deeply analyze new dimensions of learning status monitoring. We innovatively apply an anomaly detection mechanism based on embedded networks to conduct a detailed analysis of students' learning status. By constructing a complex learning behavior model based on embedded networks, the system can intelligently identify students with abnormal learning states and achieve precise control over their learning status. The system is deployed in a Windows environment and integrates high-performance databases to meet and efficiently manage the needs of massive data. The system has specially designed an administrator login interface, which is intuitive and easy to operate, allowing administrators to quickly access and query student management information. These information collected and analyzed with the support of embedded network technology greatly assist university educators in making scientific decisions and efficiently executing student management work.
Research on Aesthetic Image Design Based on Embedded Network
Authors: Huixin Zhang
Published: January 2025

With the continuous development of poster aesthetic image design, multidimensionality is not only related to visual and spatial aesthetics, but also involves the process of constructing human comprehensive thinking. Promote the development of spatial dimensions, element diversity, means diversity, and innovative thinking in the field of design. The three-dimensional representation method demonstrates high efficiency in multi-dimensional dynamic element design. In the aesthetic image design of embedded networks, the multidimensional presentation of dynamic elements mainly depends on design psychology, the development of new materials and processes, and the application of digital technology. This article takes the Qingming dynamic poster art design as an example to create a dynamic poster with Qingming culture as the theme. The main purpose of aesthetic image design software is to complete the design of the entire dynamic plane by creating framework concepts. Fully consider the dynamic elements and their proportional relationship with static elements in dynamic aesthetic image design, and control the time and rhythm of the entire screen. Ensure the balance of its related elements to design posters that are well-known, interesting, and in line with the concept of dynamic poster art design.
Construction of University Human Resources Model Based on Big Data Information Security Technology
Authors: Ning Wang
Published: January 2025

In order to improve the innovation effect of human resources management of university teachers, this paper has developed a university human resource management software. Through the application of the system, the automation, systematization and standardization of management can finally be realized, which reduces the cost of manual management and the probability of errors, enhances the accuracy, practicability, and efficiency, so that the teacher's human resources can be used to the best economic benefits. In addition, this paper combines big data technology to analyze the status quo of human resource management of university teachers, and builds an intelligent analysis model with the support of big data technology to analyze the problems existing in traditional human resource management of university teacher. Through experimental research, it can be seen that the innovative model of human resources management of university teachers based on intelligent big data technology constructed in this paper can effectively enhance the innovation effect of human resources management of university teachers, and provide theoretical references for subsequent human resources management of university teachers.
Application of Artificial Intelligence Information Security Technology in the Construction of Enterprise Financial Shared Centers
Authors: Fuling Liu
Published: January 2025

This work intends to assist SMEs in clarifying financial and enterprise management ideas in the functional implementation of the smart Financial Shared Service (FSS) Center and pointing out a specific optimal implementation path. To begin, this paper examines the primary variables influencing the smart FSS Center's functional orientation as a result of corporate demand and technical advancement. Then, utilizing the Grey Clustering Trigonometric function model, the smart FSS Center-oriented function Evaluation Index System (EIS) is built, and the functional evaluation indexes are weighted and evaluated. Finally, the 0-1 Integer Programming (IP) model is used to create the smart FSS Center-oriented function optimization path. Entropy Weight Method (EWM) and Decision-Making Trial and Evaluation Laboratory are used to determine the weight connection (DEMATEL). The findings demonstrate that the suggested smart FSS-oriented functional EIS overcomes challenges for domestic SMEs in building the smart FSS Center with limited cost, time, and technology. It can encourage the use of intelligent technology and innovative development in domestic FSS Centers. The findings have significant reference and guiding relevance for the establishment of China's smart FSS Centers.
Information Security Model for Evaluating the Competence of Preschool Teachers Using Data Mining Technology
Authors: Zhi Zhang
Published: January 2025

Kindergarten is an important part of basic education. Creating high-quality early childhood education and promoting the healthy growth of young children need to be achieved through teachers. Kindergarten teachers' core literacy is the basic professional literacy that kindergarten teachers should possess, which is an important foundation for ensuring the quality of kindergarten teachers' teaching and is the key and prerequisite for developing children's core literacy. Through the construction of teacher competency based on children's core literacy and the curriculum of teacher education based on teachers' core literacy, we try to promote the progress of kindergarten teachers, optimize the construction of kindergarten teachers, promote the quality and competence of kindergarten teachers, and lay the foundation for ensuring the quality of preschool education by continuously strengthening the training and cultivation methods of kindergarten teachers. Therefore, the demand for high-quality early childhood education will eventually translate into the demand for teachers. Adopting a scientific approach to assess the competence of preschool teachers can help improve the teaching and research ability of preschool teachers and the overall level of early childhood teaching and learning. In order to improve the shortcomings of traditional preschool teachers' teaching quality assessment in which the weights of each index are susceptible to human influence, based on the study of index coefficient analysis, feature reorganization and feature analysis, this paper constructs a model for evaluating preschool teachers' educational competence in a big data environment and proposes to establish an evaluation scheme for preschool teachers' educational competence based on data mining technology. The simulation results further verify the superiority of the proposed model in improving the evaluation of preschool teachers' educational competence.
An Secure Design of Zigbee-based Wireless Forest Air Quality Monitoring
Authors: Pucheng Zhang
Published: January 2025

Under the background of aggravated global warming caused by the accelerated worldwide industrialization process, all countries are pursuing carbon neutrality and carbon peak. Meanwhile, considering that the tree growth is subject to concentrations of oxygen and carbon dioxide in forest areas[1], and people’s daily life is closely related to the content of all kinds of gases in urban air, an outdoor air quality monitoring device is designed based on Zigbee wireless transmission. By taking the STM32F103ZET6 embedded processor as the core controller, this device applies high-precision AO-03 oxygen sensors and M702-A seven-in-one air quality sensors to collect the concentration of various gases in the air. Then, relevant data, after being read and processed by the micro-processor, is transmitted to a computer terminal through the DL-22 module so as to evaluate whether the gas concentrations have reached alarm thresholds, thereby initiating corresponding procedures if so. According to the results of comparison between data collected in different environments and the real-time data from the China National Environmental Monitoring Center, the designed monitoring system offers higher measurement accuracy, and features better energy eﬀiciency as well as longer battery life.
Research on the Optimization of Jiangsu Province Talent Policy Under the Background of Digital Economy: A Comparative Analysis of Shenzhen's Talent Policy Based on Machine Learning Models
Authors: Shuangshuang Chen, Huaqiang Lai, Zhuo Tao
Published: January 2025

Under the background of digital economy, big data, visual analysis and intelligent technology are deeply applied in regional policy formulation. As a leading demonstration area of domestic talent policy, Shenzhen has successfully attracted a large number of talents through its policy of ' speed, strength and richness '. This study focuses on the talent policy, uses interview research, carries out detailed policy text analysis with the help of the powerful function of the big language model, analyzes the highlights of Shenzhen 's talent policy from the aspects of talent introduction, talent cultivation and talent service, and further puts forward the talent policy of Jiangsu Province based on the benchmark of Shenzhen from the four aspects of talent introduction, cultivation, incentive and service. Based on the guiding ideology of accelerating the construction of the world 's important talent center and innovation highland, this paper puts forward the countermeasures and suggestions for the optimization of Jiangsu's talent policy under the background of digital economy from the aspects of talent introduction, talent cultivation, talent utilization and talent service. The research conclusions provide reference for promoting the formation of a more competitive talent policy environment in Jiangsu 's digital economy.
Bidirectional DC-DC Control Strategy for Photovoltaic Energy Storage based on Fuzzy Second-Order Active Disturbance Rejection
Authors: Binjun Cai
Published: January 2025

A bidirectional DC-DC converter (BDC) control strategy rested on fuzzy second-order linear active disturbance rejection control (FS-LADRC) is proposed to make independent photovoltaic energy storage system (IPESS) better adapt to various external conditions. The linear model of IPESS is constructed. Rested on the control characteristics of BDC on the energy storage side, traditional voltage and current double closed-loop control (VCDCC) is used. PI control is adopted for the current loop, and second-order linear active disturbance rejection control (LADRC) is adopted for the voltage loop. Fuzzy adaptive logic is combined with linear state error feedback (LSEF) control rate, so that the system has higher control accuracy. Compared with traditional PI control and traditional LADRC, the stability of direct current busbar (DCB) voltage and the power generation performance of the system under different conditions are analyzed by changing the intensity of PV irradiance. Simulation results illustrate that FS-LADRC is more excellent to traditional PI and LADRC control strategies in improving the steadiness of DCB voltage, power generation performance and of the system.
Many-Objective Decomposition-based Evolutionary Algorithm with Adaptive Weights
Authors: Qing Xu
Published: January 2025

Many-objective evolutionary algorithms are difficult to maintain good individual convergence and population diversity. As the number of objectives increases, there are more and more non-dominated solutions, and some existing diversity metrics are no longer useful. In this paper, a many-objective decomposition-based evolutionary algorithm with adaptive weights (MaOEA-AWM) is proposed. The convergence and diversity of individuals in high-dimensional target space are balanced in the proposed MaOEA-AWM through the use of a scaling method known as angle penalty distance. Additionally, a weight vector adaptation approach is proposed to adjust the weight vector distribution. Experiments show that MaOEA-AWM has strong competitiveness in many-objective optimization problems compared with seven advanced algorithms.
A Qualitative Study on the Trends and Demands of Time Bank Mutual Assistance Elderly Care Volunteer Services Based on Big Data Analysis
Authors: Min Qing
Published: January 2025

This research aims to gain a comprehensive understanding of the current status and future needs of nursing students’ volunteer activities in the Time Bank mutual support elderly care model, use big data analysis, providing a reference for the project, "Nursing Students’ Volunteering in Time Bank Mutual Support Elderly Care". The phenomenological research method was used to conduct semi-structured interviews with 12 nursing student volunteers, data were analyzed by the Colaizzi 7-step analysis method, data were statistically analyzed using SPSS28.0 software. The interviews yielded a total of 8 themes and 21 sub-themes: 1) Elderly care issues among nursing homes residents, such as feeling loneliness, needing companionship, having negative mindsets, and difficulty in health education. 2) Challenges among nursing student volunteers, including low enthusiasm, insufficient professional and communication skills. 3) Shortcomings in volunteer activities, such as lack of sustainability and limited activity variety. 4) Limited volunteer training courses and non-standardized formats. 5) The positive impact of participating in elderly care volunteer activities on both the elderly and nursing students. 6) The need for innovation in volunteer activities from a professional perspective and improvement of the reward mechanism. 7) The desire for comprehensive and integrated training courses. 8) The expectation of flexible and diverse training methods. The following conclusions are drawn from statistical analysis: Elderly residents in nursing homes require various forms of psychological care, with health education among them presenting particular challenges. Simultaneously, nursing student volunteers exhibit deficiencies in professional skills, communication abilities, and enthusiasm, highlighting a pressing need for comprehensive training. In order to promote the official implementation of the Time Bank mutual support elderly care model in the local area, it is suggested to enhance the level of nursing student volunteer services through specialized training and improve the points-based reward system.
Model of Cultivating Digital Citizenship in Universities through the Integration of Artificial Intelligence and Data Analysis
Authors: Peihua Li
Published: January 2025

The engineering background provides a solid foundation in the field of artificial intelligence, particularly in computer science, mathematics, and electronic engineering. These disciplines offer essential theoretical knowledge and practical skills for algorithm design, model construction, and system implementation in artificial intelligence. College graduates are the future of the nation, and strengthening the cultivation of civic qualities among college graduates is of great practical significance for promoting their physical and mental wellbeing and successful development. This paper analyzes the current state of civic qualities among university students and the necessity of enhancing quality education, exploring methods to cultivate civic qualities in university students in the context of the internet. Focusing on a model for cultivating digital citizenship in universities by integrating artificial intelligence and data analysis, this paper conducts corresponding discussions.
Research on the Application of Computer Technology in Multi-variety and Small-batch Material Production
Authors: Weixuan Hu
Published: January 2025

This paper employs the Autoregressive Integrated Moving Average Model (ARIMA) and regression analysis to examine the equilibrium relationship between inventory and service level. A survey questionnaire was used to study the data changes of inventory managers under different inventory conditions. This article adopts the Analytic Hierarchy Process (AHP) to accurately select 6 representative materials and establish an ARIMA model based on historical data for weekly prediction. Multiple predictions are made on interpolation data, interpolation data, and different parameters, and compared with historical data to provide the optimal prediction model. At the same time, this article combines historical data of manufacturing enterprises and uses regression analysis methods to explore the equilibrium state between inventory and service levels, providing more guidance for optimizing production arrangements. A regression model was established to analyze inventory data and the questionnaire on digital management of inventory. The optimal value of inventory was analyzed while ensuring the full utilization of computers to strengthen inventory management, providing production guidance for maximizing the interests of enterprises and consumers. By utilizing model predictions and conducting surveys and analyses on the application of computer technology in inventory management, the optimal inventory level can be determined, thereby assessing the extent to which computer technology plays a role in inventory management.
Enhancing Automotive Engineering Education with Interactive Virtual Simulation: A Research Perspective
Authors: Qiyu Wang
Published: January 2025

With the continuous progression of computer software and hardware technologies, particularly 3D engine technology, interactive virtual simulation technology has achieved an increasingly realistic emulation of the physical characteristics of the real world. It has consequently found extensive applications across diverse fields, including gaming, military, and industrial sectors. China, being a significant global force in automobile research, development, production, and manufacturing, has consistently exhibited a robust demand for automotive industry professionals. In an endeavor to cultivate applied undergraduate talents commensurate with the requirements of China's automotive sector, we have initiated the introduction of virtual simulation technology into automotive engineering education and established a virtual simulation experimental teaching center. This center is structured into three integral components: a teaching hub, a research and innovation nexus, and an experiential facility. Specifically, it encompasses a new energy vehicle virtual simulation platform, a VR walking platform, and a creative development platform. These platforms are empowered to conduct a variety of experimental undertakings, such as intelligent connected vehicle algorithm virtual simulation testing experiments, vehicle power performance testing experiments, new energy electric vehicle structure and principle training simulations, and new energy vehicle powertrain assembly simulation training. Following over two years of pedagogical implementation, the virtual simulation experimental teaching center has garnered unanimous acclaim from both faculty and students. It has effectively buttressed the college's educators and learners in executing teaching reforms and engaging in subject competition activities related to new energy vehicles, thereby making a substantial contribution to the development of automotive education.
Research on Intelligent Operation and Maintenance Decision-Making of Electric Vehicle Charging and Discharging Equipment based on Full Life Cycle Management
Authors: Songling Pang
Published: January 2025

The electric vehicle (EV) charging and discharging process involves a large number of energy devices, and the full life-cycle cost of these devices can significantly impact the energy usage strategy of electric vehicles. To address this, the article proposes an optimization mathematical model for electric vehicle charging and discharging that considers the system’s electricity cost, equipment operation and maintenance costs, and depreciation costs of the devices. Based on the consideration of the equipment's full life-cycle costs, an optimization scheduling model for daily operating costs is established with the goal of minimizing the operating costs of electric vehicle charging and discharging equipment. An adaptive genetic algorithm is used to schedule the charging plan for electric vehicles throughout the day. The results of case studies show that the proposed optimization strategy reduces the full life-cycle costs, improves energy utilization efficiency, and optimizes the energy consumption structure. Since the full life-cycle costs of the equipment are taken into account, this strategy has better practical application value in engineering.
Blockchain Security Protocols: Enhancing the Resilience of Distributed Networks
Authors: Padmavati Shrivastava
Published: January 2025

Blockchain technology has emerged as a transformative solution for securing distributed networks, offering decentralized and immutable data management. However, the resilience of blockchain systems faces challenges from various security threats, including double-spending, Sybil attacks, and vulnerabilities in smart contracts. This paper explores the effectiveness of various blockchain security protocols in enhancing the security and stability of distributed networks. The study provides a comprehensive review of cryptographic techniques, consensus algorithms, and privacy-enhancing technologies, such as Zero-Knowledge Proofs and Multi-Party Computation. Through a detailed analysis of case studies involving Bitcoin, Ethereum, and Hyperledger Fabric, the paper highlights the strengths and limitations of different security protocols. Additionally, the paper discusses the future direction of blockchain security, including the impact of emerging threats such as quantum computing on current security measures. The findings emphasize the need for ongoing innovation in security protocols to ensure the long-term resilience of blockchain networks. The paper concludes with recommendations for improving the security frameworks in both public and permissioned blockchains, with a focus on scalability, privacy, and resistance to emerging attacks.
Enhancing Cyber Fraud Detection Using Machine Learning Algorithms
Authors: Namrata Verma
Published: January 2025

This research explores the enhancement of cyber fraud detection through the application of machine learning algorithms. As cyber threats continue to evolve in sophistication and frequency, traditional detection methods often fall short in identifying and mitigating fraudulent activities. This study examines various machine learning techniques, including supervised and unsupervised learning models, to improve detection accuracy and response times. By analyzing large datasets from diverse sources, the research identifies key features that contribute to fraudulent behavior, enabling the development of predictive models that can adapt to new patterns. Results indicate that advanced algorithms, such as Random Forest, Gradient Boosting, and Neural Networks, significantly outperform conventional methods in terms of precision, recall, and overall effectiveness.
Quantum Cryptography in Secure Communication: Opportunities and Challenges
Authors: Harsha Avinash Bhute
Published: January 2025

Quantum cryptography represents a breakthrough in secure communication, leveraging the principles of quantum mechanics to create encryption methods that are theoretically immune to classical computational attacks. This paper explores the opportunities and challenges associated with implementing quantum cryptography in real-world communication systems. It examines key technologies, such as Quantum Key Distribution (QKD), and their potential to enhance data privacy. Additionally, the paper discusses the limitations, including technological feasibility, high costs, and integration with existing infrastructures. The challenges of scalability and resistance to quantum computing threats are also analyzed.
Modeling of Bus Holding Strategy in Public Transit Systems with Multi-Agent Reinforcement Learning
Authors: Chunxiao Chen
Published: January 2025

Excessive fluctuations in travel time between stops and demand at bus stops during bus operations can lead to operational instability in bus systems, such as bus bunching. To tackle this issue, this paper presents a dynamic bus holding control strategy leveraging multi-agent reinforcement learning to stabilize bus system operations and prevent bus bunching. First, bus motion system is constructed, and the rules for bus operation and passenger behavior are defined. Then, agent-based transit operation management is established, the elements of the multi-agent reinforcement learning framework are outlined, and a centralized training and decentralized execution method is proposed. Additionally, an event-driven simulation environment is developed for training and testing the agents. Finally, extensive numerical simulations are conducted to evaluate the proposed method against baseline approaches using various performance metrics. The results demonstrate that the proposed method effectively captures the dynamics of the bus system and accounts for the long-term impacts of current decisions, resulting in the most balanced bus trajectories, optimal passenger load distribution, and minimal total holding time.
Artificial Intelligence: Its Impact on the Education System
Authors: Verónica Ximena Olmedo Zambrano
Published: January 2025

Artificial intelligence has demonstrated its potential to transform numerous fields, and education has been no exception. This research aims to analyze the impact of this technology on the teaching and learning process, and how it is transforming the educational system. The methodology applied in this study was a quantitative approach through a descriptive non-experimental design by means of a survey applied to graduate students of the Pontificia Universidad Católica del Ecuador located in Manabí. This approach was complemented with a bibliographic documentary type qualitative methodology. The results obtained indicated that artificial intelligence is very useful for education, with 70%. Also, that it can help identify and support students with learning difficulties 77%. Challenges were examined highlighting over-dependence on technology with 79%, and equitable access to technology with 75%. The areas in which this tool can have a positive impact are assessment and feedback with 84%, and personalization of learning with 81%. It could be seen that in recent years artificial intelligence has had a positive impact on the educational system, its use in the teaching and learning process has improved the academic performance of students.
School Dropout in a Rural Educational Unit in Manabí
Authors: Paolo Wladimir Sornoza Ostaíza
Published: January 2025

School dropout is a social problem that significantly affects the most depressed areas of the population, such as rural areas. The objective of the research was to determine the causes of school dropout in the Alajuela fiscal educational unit in the rural area of the province of Manabí, Ecuador. A mixed approach methodology, non-experimental design, descriptive and explanatory level, was used through the application of a survey structured in 24 questions to an intentional sample of 30 former students, who could be accessed, given the considerable distances from homes in this rural community; An interview was conducted with an education professional and was used in the discussion of the results. 11 causes of school dropout were identified, of which the precarious economic situation due to lack of money and work tops the list of causes, lack of pleasure in studying, emotional situations of pressure due to living with family members, learning problems, pregnancy, free union, loss of the school year, work at home, absences from school, parental problems, and traffic accidents. As a conclusion, it is necessary that the economic measures that are established in each new government significantly affect the income of households, particularly in rural sectors, which do not have a fixed income, and which depend on the sale of agricultural products according to the summer or winter season, making minors who study in rural schools, are forced to make the decision to abandon them because of the expenses they incur to be able to educate themselves.
Social Networks and Their Impact on Higher Education
Authors: María Gema Vera Mera
Published: January 2025

Social network platforms and technology apps for education have become essential in all educational environments and have acquired significant importance in high-education contexts due to their ability to encourage students' participation and strengthen ties within the academic community, institutional communication, and community participation, helping to enrich the educational experience, thus allowing greater dissemination and accessibility to information. The study carried out a descriptive approach, starting from observing and applying a survey to students, generating quantitative and qualitative research to obtain a deeper and more complete understanding. This research aims to determine the impact of social networks on higher education. For this purpose, 650 graduate students of the Pontificia Universidad Católica del Ecuador – located in Manabí, were surveyed using observation and virtual surveys. The results showed that social media significantly influence the daily lives of students (76%). Regarding the educational use of digital communication platforms, they are widely used for academic tasks (54%) and the exchange of educational links (30%). WhatsApp (28%) and Facebook (25%) were the most used platforms. These tools offer advantages such as access to educational resources and facilitate collaborative learning; it is necessary to mention that these platforms also present challenges such as distraction and access to unverified information, for which it is necessary to address these challenges and maximize the benefits of social networks in higher education. Social networks have a positive impact because they facilitate communication and allow access to educational resources, which contribute to academic success and personal growth of students, positively affecting academic performance.