Intelligent Information Technology Research Articles

Application of BIM+GIS Integration Technology in the Construction of Urban Intelligent Water Informatization

Urban intelligent water informatization is the process of managing and operating urban water systems with the use of contemporary information and communication technology in order to increase productivity, security, and sustainability. Establishing the appropriate infrastructure is the initial stage in building an intelligent water system so that management can choose wisely how to manage and operate the water system. Building information modeling (BIM) is a digital depiction of a building's or infrastructure's structural and functional details. In most metropolitan regions, a fast development phase is predicted to cause several water issues, including water resource shortages, floods, poor drainage, and water resource contamination. As a result, a practical approach is required for urban intelligent water information technology with the help of artificial intelligence techniques. Intelligent water systems may be built using Building Information Modeling (BIM) software to increase the system's effectiveness, stability, and durability. By offering a potent tool for storing and analyzing geographical data connected to the water distribution system, a geographic information system (GIS) can play a crucial role in the development of urban intelligent water informatization using ArcGIS mapping Software. The Internet of Things (IoT) system is used to implement intelligent water informatization, hardware implementation using ESP32, and software development using MQTT Broker and Node-Red. As a result, we recommended utilizing BIM+GIS integration technology for building urban intelligent water informatization. The suggested system is evaluated using management efficiency, urban flood control, innovative Construction, intensive management, and computation cost. In this research, the main objective is to identify where there are water leaks broken pipes and early warning system and monitoring system for flash flood disasters in urban areas. The result findings show that the integration of BIM and GIS provides a comprehensive platform for managing complex water informatization infrastructure projects and maximizes efficiency and sustainability.

인공지능(AI)과 한국 부동산의 부패방지에 관한 연구

This study attempted to present discussions and directions regarding artificial intelligence(AI) and the prevention of corruption in Korean real estate. This Paper dealt with moral hazard, corruption prevention, and trust using real estate, the 4th industrial revolution(4IR), AI, and intelligent information technology as keywords. Prior research is focusing on economic utility and technical benefits related to AI and real estate. In contrast, this study pointed out the risk of moral hazard and corruption arising from the combination of AI and real estate, and conducted a paper to prevent moral hazard and corruption. In this respect, there is a difference between this study and existing previous studies. This is where the originality of this study appears. The results of this study on anti-corruption of AI and Korean real estate are as follows. As a result of the study, the problems of AI and Korean real estate, and anti-corruption were presented in three major categories: 1. AI and the problem of changing times, 2. Korean real estate and corruption problem, and 3. AI and real estate problem. In relation to this, this study largely derived three measures as implications of the research. The contents include, first, responses to the issues of AI and changing times, second, responses to Korean real estate and corruption issues, and third, measures to respond to AI and real estate issues. This study hopes to restore market trust through Artificial Intelligence(AI) and the prevention of corruption in Korean real estate, and to build a future where the benefits and utility provided by real estate, AI, and intelligent information technology are desirable.

Opportunities and Challenges in AI Based Modern Power System

Nowadays, the power grid has transformed into a dynamic and extensive resource generation and management system. This transformation is primarily driven by the widespread adoption of renewable energy sources and the utilization of intelligent information and communication technologies to handle dynamic workloads. The smart grid encompasses various innovative operations, including power electrification, intelligent information integration at the physical layer, and intricate interconnections. These operations leverage data-driven deep learning, big data, and machine learning paradigms to effectively analyze and control transient issues within the electric power system. Artificial intelligence (AI) has emerged as a crucial tool in addressing and resolving challenges associated with transient stability assessment (TSA) and power generation control. In this research paper, we present a comprehensive review that explores the role of AI and its sub-procedures in tackling TSA problems. The article outlines an AI-based intelligent power system structure, along with the rationality of applying AI to transient situations in power system TSA. Distinguishing itself from other reviews, this paper delves into the AI-based TSA framework and design process, highlighting intelligent applications and their analytical capabilities in addressing power system transient problems. Furthermore, our analysis extends beyond AI alone, as we also explore the integration of big data, which aligns seamlessly with AI. The paper discusses future trends, opportunities, challenges, and open issues pertaining to AI-Big data based transient stability assessment in the smart power grid.

DSCU-Net: MEMS Defect Detection Using Dense Skip-Connection U-Net

With the rapid development of intelligent manufacturing and electronic information technology, integrated circuits play a vital role in high-end chips. The semiconductor chip manufacturing process requires precise operation and strict control to ensure chip quality. The traditional manual visual inspection method has a high workforce cost and intense subjectivity and is accompanied by a high level of misdetection and leakage. Computer vision-based wafer defect detection technology is gaining popularity in the industry. However, previous methods still find it challenging to meet the production requirements regarding accuracy. To solve the problem, we propose a defect detection network based on a coding and decoding structure, Dense Skip-Connection U-Net (DSCU-Net), which optimizes the skip connection between the encoder and decoder and enhances the profound fusion of high-level semantics and low-level semantics to improve accuracy. To verify the effectiveness of DSCU-Net, we validate it in actual microelectromechanical systems (MEMS) data, and the results show that DSCU-Net reaches an optimal level. Therefore, the DSCU-Net proposed in this paper effectively solves the defect detection problem in semiconductor chip manufacturing. This method reduces workforce cost and subjectivity interference and improves inspection efficiency and accuracy. It will help to promote further development in the field of intelligent manufacturing and electronic information technology.

새로운 노멀, 한국의 부동산과 신뢰에 관한 소고

1. CONTENTS
 (1) RESEARCH OBJECTIVES
 This study conducted research on Korean real estate and trust facing the new normal. The purpose of the thesis is to explore the problems and future that arise from the combination of Korean real estate and artificial intelligence amid changes in the rules of the game called the new normal. This paper pointed out the importance of social capital called trust and explored the sustainability of the Korean real estate industry.
 (2) RESEARCH METHOD
 This study applied descriptive research methods to new normal, artificial intelligence, real estate in Korea, and trusts. Through this, the paper attempted to discuss research topics in an explanatory and normative manner and draw implications.
 (3) RESEARCH FINDINGS
 This study was conducted on the topic of real estate and trust in the new normal. The main keywords of this research were new normal, Korean real estate, trust, Artificial Intelligence(AI), and the 4th industrial revolution(4IR). This paper differs from previous studies. Existing prior research approaches the 4IR(AI) and Korean real estate with a focus on economic utility and technological benefit. In contrast, this study pointed out the importance of social capital called trust and attempted to explore the sustainability of the Korean real estate industry.
 2. RESULTS
 In the new normal, real estate in Korea is presented as three major issues: 1. Problems of Korean real estate in transition, 2. Industrial revolution and collapse of trust, and 3. Transformation of the times and changes in social codes. In relation to this, this study derived three implications: first, compliance with the rule of law, second, discussion and direction on ethical guidelines, and third, response and preparation for information asymmetry and bias. This study predicts that Korea's real estate industry, facing a new normal, will minimize risks based on trust and develop the benefits and utilities provided by artificial intelligence and intelligent information technology in a desirable direction.

An approach to describing the courses of air enemy action using intelligent information technologies

The article analyzes the approach to describing the courses of air enemy action for further automation of the decision-making process for air enemy destruction. The analysis has shown that the development of air attack capabilities justifies the necessity to increase the level of efficiency in the decision-making process by responsible persons through the introduction of intelligent information technologies, such as expert systems and decision support systems, into the automation complexes of the Air Force. It is proposed to use the calculation of first-order predicates to formalize knowledge and aggregate it in the form of a knowledge base that will allow the decision maker to deploy his air defense forces and means to effectively destroy means of air attack.

Research on Network Teaching Collaboration Platform Using Flipped Classroom Teaching Mode

The quick development of intelligent information technology in modern society has accelerated education informatisation. Accordingly, the traditional modes of instruction and methods of instruction are no longer able to satisfy the educational needs of modern society, so the flipped classroom teaching method emerges at the historic moment. While injecting fresh vitality into education, this model can also reflect good teaching effects, which is of enormous practical relevance to the development of education. Additionally, flipped classroom teaching is made possible by the online teaching resources offered by colleges and institutions. In view of the unreasonable distribution of curriculum resources in the current university network teaching platform, this study proposes a university network platform combining flipped classroom teaching mode and improved Apriori algorithm. First of all, to achieve the acceptable allocation and suggestion of learning materials in accordance with students’ learning demands, the Apriori algorithm is introduced to address the university network teaching platform’s lack of adequate planning and organisation. After that, the flipped classroom teaching mode is introduced into the online teaching platform for empirical research. According to the trial findings, more than 90.22 % of the students had improved their study habits. The network teaching platform proposed by the research institute can stimulate college students’ learning interest and improve their learning ability to a certain extent.

Individual age determination based on computed tomography knee analysis using artificial neural networks and computer vision: Preliminary results

BACKGROUND: Currently, studies have focused on the modernization of existing methods of forensic age assessment (bone and skeletal) through the active use of modern methods of medical imaging (e.g., computed tomography) and artificial intelligence for their analysis. This approach enables the creation of new methods for assessing biological age, which is characterized by increased accuracy and reproducibility.
 AIM: To develop and test an algorithm for predicting the biological age of an individual based on computed tomography analysis of the knee joint using artificial neural networks and computer vision.
 MATERIALS AND METHODS: This observational retrospective transverse (one time) study analyzed computed tomography scans (334) of the knee joint performed in the Departments of Radiation Diagnostics of the Priorov Central Institute for Trauma and Orthopedics, Vreden National Medical Center for Traumatology and Orthopedics, between 2018 and 2021. The study enrolled persons of both sexes aged 13–45 years. Cases of developmental abnormalities, knee injuries, signs of general connective tissue pathology were excluded. Research methods include the use of intelligent information technologies (a formalized set of mathematical and software solutions).
 RESULTS: Based on the experiments conducted, an algorithm for assessing age according to the computed tomography scans of the knee joint has been developed. The main components of the developed system are as follows: a preprocessing module, an intelligent computing core, a data analysis module, a three-dimensional reconstruction module, a property extraction module, and a final age assessment module. The essence of the proposed method is the simultaneous use of artificial neural networks and clearly formalized mathematical procedures for calculating the properties of the epiphyseal line. To obtain the results and conduct primary experimental studies that confirmed the feasibility, correctness, and operability of the method, software using the YOLOv5 neural network was developed. The result of the error matrix analysis after training shows a probability of correct recognition of the order of 80%. Verification of experimental studies was performed on 46 cases. At present, the age estimation error is approximately 1 year for children and adolescents.
 CONCLUSIONS: The experimental results have confirmed the adequacy of the age estimates obtained to the actual age of the individual and, consequently, the applicability of the proposed method in forensic medical institutions. The proposed method is currently implemented as a set of software components with subsequent manual integration of automatically calculated data. The plan was to supplement the database of computed tomography images to increase the training sample and the accuracy of age prediction.

An intelligent Fusion Framework for Risk Assessment of Autonomous Ship through Functional Mapping Criterion Sub-Intervals into Single Interval Method

Nowadays, intelligent information technology can implement high-level information processing and decision-making activities that can support risk assessment of autonomous. Risk assessment is a critical process for deploying autonomous ships, ensuring these innovative vessels' safe and efficient operation. There is a need to identify, analyze, and mitigate potential risks associated with system reliability, collision avoidance, cybersecurity, environmental conditions, human interaction, regulatory compliance, sensor performance, data integrity, emergency response, and testing and validation. This work provides an overview of the essential considerations and objectives of risk assessment in autonomous boats. We used the multi-criteria decision-making model to deal with various criteria. The Ranking of Alternatives through Functional Mapping Criterion Sub-Intervals into Single Interval (RAFSI) method is applied to rank the alternatives. We used the ten criteria and twenty options in this study. The results show that the proposed framework can provide a comprehensive risk assessment framework that can enable stakeholders to gain insights into potential hazards and vulnerabilities unique to autonomous ships.

The Construction of Wisdom Teaching Mode of Physical Education and Training in Colleges and Universities in the Internet Era

Abstract The rise of the intelligent teaching model, relying on artificial intelligence and digital information technology, provides students with personalized and autonomous learning pathways. The model encourages students to learn independently and develop personally by integrating online and offline learning resources, enhancing their innovation and practical skills. Educational innovation has focused on exploring how to effectively incorporate competent teaching resources to improve teaching efficiency and students’ physical education skills. This study designed a new smart teaching mode for physical training science using blended learning theory and artificial intelligence technology. The differences in students’ physical education performance, participation, and satisfaction between the traditional and intelligent teaching modes were analyzed by comparison. The students who used innovative teaching methods in the study were better than those who used conventional teaching methods in 100-meter sprint and basketball shooting accuracy, with an average improvement rate of 15%. According to the study, the intelligent teaching mode can effectively enhance students’ physical education learning efficiency and mastery of movement skills, paving the way for a new development direction in college physical education.

Deep Integration Practice of Intelligent Information Technology and Art Design Education under the Background of Scientific Programming

Deep Integration Practice of Intelligent Information Technology and Art Design Education under the Background of Scientific Programming

Intelligent System for Detecting Plagiarism in Technical Texts

The authors of the article developed a scientific reasoning, designed, and developed an intelligent system for detecting plagiarism in technical texts. The work defines the problem of plagiarism in the modern world and its relevance and analyzes the latest research and publications devoted to the latest methods of using intelligent information technologies to detect plagiarism. The need and expediency of developing and improving intellectual information technologies for detecting plagiarism, as well as the use of various methods of identifying matches in texts for the further development of such technologies, are substantiated. The authors developed a general algorithm for detecting plagiarism in technical texts based on the vector comparison method. The practical result of the study is the development of an intelligent system for detecting plagiarism in technical texts and confirmation of its efficiency by applying it to specific examples of technical texts.

Energizing Sustainability: Solar Cell Radio Wave AI Transformations in Business and Health, with a Focus on Vaccines and Antibiotics

This review article provides a comprehensive examination of the synergistic integration of several technologies, including radio waves, solar cell technology, artificial intelligence (AI), business information technology (IT), immunizations, and antibiotics, with the aim of fostering sustainable innovation. A comprehensive analysis is carried out, highlighting the connections between smart technology, healthcare, and renewable energy sources. The abstract looks at how solar energy and radio waves might advance technology, with artificial intelligence and business IT aiming to maximize productivity. The evaluation also explores the potentially innovative ways in which vaccinations and antibiotics could enhance public health. By linking different disciplines together, the article aims to shed light on the holistic and long-term strategy that emerges when many technologies come together for the good of business and society. This paper explores the intricate connections between solar cell technology and artificial intelligence (AI), showing how advances formerly unimaginable are propelled by the convergence of advanced computing power and renewable energy sources. When it comes to facilitating the seamless integration of many technologies to optimize productivity and decision-making processes, business IT plays a critical role. The important sector of medicine, where immunizations and antibiotics are critical for creating resilient populations, is also covered in the article. This study explains the potential for comprehensive and long-lasting solutions by combining these technological and medical advancements, while also emphasizing the necessity of multidisciplinary cooperation in tackling the challenges of our rapidly changing environment.

Digitalization of motivational features as a way to organize independent work of bachelors

Problem statement . Effective organization of extracurricular work for future bachelors involves the construction of individual learning trajectories, based, among other things, on the level of motivation to study specialized disciplines. The expediency of using intelligent information technologies in classifying the composition and forms of independent work of bachelors of applied mathematics is substantiated. Methodology. Applying the developed mobile application, multi-parameter motivational characteristics of students were identified. The resulting motivational profiles are clustered into five motivational groups, similar in sign values. The construction and analysis of multi-parameter classification were carried out via cluster analysis and neural network technologies. Clustering of motivational groups and the application of appropriate strategies for organizing independent work were realized at the Faculty of Computer Technologies and Applied Mathematics of Kuban State University. Results. The constructed neural network classifies the bachelor's motivational profile, assigns him a strategy for independent work, defining the specific values of the variable elements of the strategy. Strategies for organizing independent work have been established for clustered motivational groups. Conclusion. Construction and clustering of motivational profiles allows you to adjust individual strategies for independent learning of bachelors of applied mathematics, determine the values of variable elements and, as a result, not only develop professional skills, but also develop skills in organizing your own work process, resource allocation, and identifying work stages.

Exploring the Impact of Educational Informatization on Sustainable Development in Global Education Systems

Education informatization uses intelligent algorithms and information technology to develop educational resources, optimize the educational process, and establish a modern education concept. The global education system is the general term for the education system of different countries and regions. There are internal connections but also significant differences. Education informatization can reuse the educational resources of developed countries, improve the education level of developing countries, and realize the undifferentiated development of global education. The research on education informatization mainly stays at the theoretical level and lacks the optimization technology of the educational process, which limits the sustainable development of the global education system. Therefore, this paper proposes a global education system optimization method based on information technology, which classifies educational resources, concepts and processes in different regions and countries. Then, the system education is built through the B/S framework, and the educational resources of different B/S layers are transmitted through the wireless transmission protocol to complete the construction of the global education system. Finally, the global education system is evaluated. The results show that the global education system optimization method proposed in this paper can improve the sustainability of educational resources, the optimization rate of educational resources is greater than 80%, the optimization accuracy of the educational process is greater than 90%, and the improvement rate of educational philosophy is greater than 80%., significantly higher than the previous network information platform. Therefore, this paper proposes that the wireless transmission protocol can support education informatization, promote the sustainable development of the global education system, promote the balance of educational resources in different countries and regions, and enhance the modern education concept.

Preface

The International Conference on Software Engineering and Machine Learning (CONF-SEML) is an annual conference focusing on research areas including software engineering, artificial intelligence, and other information technology areas. It aims to establish a broad and interdisciplinary platform for experts, researchers, and students worldwide to present, exchange, and discuss the latest advance and development in engineering and machine learning.This volume contains the papers of the 2023 International Conference on Software Engineering and Machine Learning (CONF-SEML 2023). Each of these papers has gained a comprehensive review by the editorial team and professional reviewers. Each paper has been examined and evaluated for its theme, structure, method, content, language, and format.CONF-SEML 2023 organized four workshops in cooperation with famous universities worldwide. Dr. Marco Manca chaired the workshop “BioDynaMo: Building the Future Today” in Bologna, Italy. Dr. Christopher Windmill and Dr. Patrick Merritt chaired the workshop “Software development practices for digitally augmented traditional business workflows” at the University of Derby. Dr. Marwan Omar chaired the workshop “Recovering Data in a Digital Forensics Examination” at the Illinois Institute of Technology. Prof. Anil Fernando chaired the workshop “Explainable AI for Stock Market Prediction” at the University of Strathclyde.Besides these workshops, CONF-SEML 2023 also held an online session. Eminent professors from top universities were invited to deliver keynote speeches in this online session, including Prof. Roman Bauer from the University of Surrey, Prof. Michael Harre from the University of Sydney, Prof. Richa Gupta from Jamia Hamdard University, etc. They have given keynote speeches on related topics of utilization of machine learning, digital healthcare intervention, computational model, etc.On behalf of the committee, we would like to give sincere gratitude to all authors and speakers who have made their contributions to CONF-SEML 2023, editors and reviewers who have guaranteed the quality of papers with their expertise, and the committee members who have devoted themselves to the success of the conference.

디지털 전환에 따른 근로의 권리 실현 방안

Digital transformation has emerged as a hot topic around the world, attracting attention as an opportunity to overcome various crises and discover new growth engines. This paper examines the impact and problems of digital transformation in realizing Right to Work and suggests normative responses.
 Digital transformation may increase unemployment and lead to job polarization and subsequent expansion of income inequality and poverty. Additionally, as the number of unstable workers increases, blind spots in protection of labor laws and social insurance may increase. In addition, as work flexibility increases, the risk of work-life balance, health, and privacy being violated may increase. Furthermore, as recruitment and personnel management using intelligent information technology expands, problems such as trans- parency, fairness, and the possibility of infringement on personal information and privacy may arise.
 The normative response to these problems is to maintain the principle that digital transformation is ultimately for the benefit of humans and must contribute to the guarantee of basic rights, while keeping in mind the harmony of autonomy and regulation, strengthening transparency, and securing social integration.
 Above all, policies are needed to revitalize industrial dynamics to promote employment. The introduction of basic income may be considered, but sufficient prior review and social consensus must be obtained. In addition, we must be able to adapt to various new problems in the work area that arise due to digital transformation by expanding the scope of application of labor-related laws and including new disciplinary content. First, the requirements for recognizing worker status must be newly established and a social security system that can cover all unemployed individuals must be established. Next, in response to problems that may arise as digital work and full-time work becomes possible, the right to disconnect is needed to be specified and the paradigm of the occupational safety and health legislation must be changed. Furthermore, it is necessary to respond to situations where recruitment and personnel management using intelligent information technology are widely used. Measures are needed to establish minimum standards for data use and ensure transparency while being careful not to excessively restrict the possibility of data use or infringe on autonomy by imposing excessive regulations.

Empowering Agriculture: Exploring User Sentiments and Suggestions for Plantix, a Smart Farming Application

Farming activities are transforming from traditional skill-based agriculture into knowledge-based and technology-driven digital agriculture. The use of intelligent information and communication technology introduces the idea of smart farming that enables farmers to collect weather data, monitor crop growth remotely and detect crop diseases easily. The introduction of Plantix, a pest and disease management tool in the form of a mobile application has allowed farmers to identify pests and diseases of the crop using their mobile devices. Hence, this study collected the reviews of Plantix to explore the response of the users on the Google Play Store towards the application through Latent Dirichlet Allocation (LDA) topic modeling. Results indicate four latent topics in the reviews: two positive evaluations (compliments, appreciation) and two suggestions (plant options, recommendations). We found the users suggested the application to additional plant options and additional features that might help the farmers with their difficulties. In addition, the application is expected to benefit the farmer more by having an early alert of diseases to farmers and providing various substitutes and a list of components for the remedial measures.

Analysis of Walmarts Marketing Strategy in the Context of New Retail

With continuous innovation and wide application of technologies such as the Internet and big data, the Internet economy has flourished, laying the foundation for the transformation of physical retailing to new retailing. The main advantage of new retailing lies in the combination of the quality experience of physical stores with the high efficiency of online retailing, which points the way for the development of the retail industry. Taking Walmart Company, a world-renowned retail industry giant, as a case study, the paper adopts the 7PS marketing mix theory to study the current marketing situation of Walmart Company. The research found that Walmart has problems such as unreasonable packaging and display of some products and an inefficient logistics supply chain. To this end, this paper proposes optimization solutions including the improvement in product quality, the investment in intelligent information technology, and the construction of a centralized supply chain management model.

지능정보사회에서 사회보장 영역의 정보화와 기본권 보호

In the field of social security, the transition to the ‘Digital Welfare States’ is accelerating as we detect fraud, and discover welfare blind spots using intelligent information technology. However, this can increase concerns about privacy protection and the advent of a surveillance society, and fixation of prejudice. The balance between innovation using new technologies and protection of fundamental rights is raised as an important task. In relation to these issues, this paper analyzes the Hague District Court’s case on the System Risk Indication (SyRI) to examine the impact of informatization in the social security area on the guarantee of basic rights and the implications to South Korea related to the direction of normative response to it.
 SyRI is a legal instrument used by the Dutch government to detect various forms of fraud, including social benefits, allowances, and taxes fraud. The court has ruled that the legislation regulating the use of SyRI does not comply with Article 8 of the European Convention on Human Rights (ECHR), which protects the right to respect for private and family life, home and correspondence. The court has decided that the legislation does not strike a fair balance, as required under the ECHR, which would warrant a sufficiently justified violation of private life. In that respect, the application of SyRI is insufficiently transparent and verifiable.
 The SyRI case has an important meaning for many countries pursuing a digital welfare state in that it warned of such dangers regarding the digitalization of welfare, which has been promoted with only the convenience and efficiency of social security administration. Even if it is need to use intelligent information technology for a legitimate purpose, it can cause various risks and side effects, so we must first establish a legal basis through sufficient social discussion and agreement. In addition, rather than obsessing over efficiency and administrative convenience, it is necessary to think about fundamental measures to solve the problems of fraud and blind spots in the social security field, and focus on using technology for this purpose. Also, the legislation should accommodate enhanced transparency regarding risk models and algorithms, provision of information to the data subjects, objective evaluation procedures for the need for data processing and the adequacy of the process, and data protection impact assessment. Through this, it will be possible to prevent damage to constitutional values such as human autonomy, the right to self-determination of personal information, the privacy or the right to respect for private life, and equality, and to minimize restrictions on fundamental rights.