Machine Fault Diagnosis Using Audio Sensors Data and Explainable AI Techniques-LIME and SHAP

Machine fault diagnostics are essential for industrial operations,and advancements in machine learning have significantly advanced these systems by providing accurate predictions and expedited solutions.Machine learning models,especially those utilizing complex algorithms like deep learning,have demonstrated major potential in extracting important information fromlarge operational datasets.Despite their efficiency,machine learningmodels face challenges,making Explainable AI(XAI)crucial for improving their understandability and fine-tuning.The importance of feature contribution and selection using XAI in the diagnosis of machine faults is examined in this study.The technique is applied to evaluate different machine-learning algorithms.Extreme Gradient Boosting,Support Vector Machine,Gaussian Naive Bayes,and Random Forest classifiers are used alongside Logistic Regression(LR)as a baseline model because their efficacy and simplicity are evaluated thoroughly with empirical analysis.The XAI is used as a targeted feature selection technique to select among 29 features of the time and frequency domain.The XAI approach is lightweight,trained with only targeted features,and achieved similar results as the traditional approach.The accuracy without XAI on baseline LR is 79.57%,whereas the approach with XAI on LR is 80.28%.

A Novel High-Efficiency Transaction Verification Scheme for Blockchain Systems

Blockchain can realize the reliable storage of a large amount of data that is chronologically related and verifiable within the system.This technology has been widely used and has developed rapidly in big data systems across various fields.An increasing number of users are participating in application systems that use blockchain as their underlying architecture.As the number of transactions and the capital involved in blockchain grow,ensuring information security becomes imperative.Addressing the verification of transactional information security and privacy has emerged as a critical challenge.Blockchain-based verification methods can effectively eliminate the need for centralized third-party organizations.However,the efficiency of nodes in storing and verifying blockchain data faces unprecedented challenges.To address this issue,this paper introduces an efficient verification scheme for transaction security.Initially,it presents a node evaluation module to estimate the activity level of user nodes participating in transactions,accompanied by a probabilistic analysis for all transactions.Subsequently,this paper optimizes the conventional transaction organization form,introduces a heterogeneous Merkle tree storage structure,and designs algorithms for constructing these heterogeneous trees.Theoretical analyses and simulation experiments conclusively demonstrate the superior performance of this scheme.When verifying the same number of transactions,the heterogeneous Merkle tree transmits less data and is more efficient than traditional methods.The findings indicate that the heterogeneous Merkle tree structure is suitable for various blockchain applications,including the Internet of Things.This scheme can markedly enhance the efficiency of information verification and bolster the security of distributed systems.

Micro,Small,and Medium Enterprises’Cross-Border Business Strategies

This paper explores the operational strategies of cross-border micro, small, and medium enterprises (MSMEs). Against the backdrop of globalization and digitalization, cross-border trade has become one of the important pathways for many MSMEs to achieve growth and competitive advantage. Firstly, the paper outlines the concept and characteristics of cross-border MSMEs, as well as the analysis of their operational environment in the context of globalization, including political, economic, social, technological, environmental, and legal factors. Secondly, the paper proposes operational strategies for cross-border MSMEs, including international market selection and positioning, cross-border marketing strategies, supply chain management, cross-border financial management, and cross-border risk management. Finally, the paper summarizes the importance of effectively implementing these strategies for cross-border MSMEs to seize international market opportunities, reduce operational risks, and enhance competitiveness and profitability.

A Study on the Factors Influencing Consumer Purchase Decision Under the Live-Streaming Sales Model

In recent years,with the rapid development and popularization of Internet information technology,many new media platforms have risen rapidly,and major e-commerce companies have begun to explore the mode of livestreaming.Especially during the COVID-19 pandemic,due to the lockdown,live-streaming has become an important means of economic development in many places.Owing to its remarkable characteristics of timeliness,entertainment,and interactivity,it has become the latest and trendiest sales mode of e-commerce channels,reflecting huge economic potential and commercial value.This article analyzes two models and their characteristics of live-streaming sales from a practical perspective.Based on this,it outlines consumer purchasing decisions and the factors that affect consumer purchasing decisions under the live-streaming sales model.Finally,it discusses targeted suggestions for using the live-streaming sales model to expand the consumer market,hoping to promote the healthy and steady development of the live-streaming sales industry.

Stock Price Prediction Based on the Bi-GRU-Attention Model

The stock market, as one of the hotspots in the financial field, forms a data system with a huge volume of data and complex relationships between various factors, making stock price prediction an area of keen interest for further in-depth mining and research. Mathematical statistics methods struggle to deal with nonlinear relationships in practical applications, making it difficult to explore deep information about stocks. Meanwhile, machine learning methods, particularly neural network models and composite models, which have achieved outstanding results in other fields, are being applied to the stock market with significant results. However, researchers have found that these methods do not grasp the essential information of the data as well as expected. In response to these issues, researchers are exploring better neural network models and combining them with other methods to analyze stock data. Thus, this paper proposes the ABiGRU composite model, which combines the attention mechanism and bidirectional gated recurrent unit (GRU) that can effectively extract data features for stock price prediction research. Models such as LSTM, GRU, and Bi-LSTM are selected for comparative experiments. To ensure the credibility and representativeness of the research data, daily stock price indices of BYD are chosen for closing price prediction studies across different models. The results show that the ABiGRU model has a lower prediction error and better fitting effect on three index-based stock prices, enhancing the learning efficiency of the neural network model and demonstrating good prediction stability. This suggests that the ABiGRU model is highly adaptable for stock price prediction.

Exploration of Human Resource Management in Enterprise Business Management

Human resource management is an integral part of enterprise operation and management,contributing to the avoidance of financial risks,alleviation of performance problems,promotion of organizational development,enhancement of operational efficiency,and fostering sustainable enterprise development.Enterprise management should prioritize attention to human resource management by establishing an independent human resource management department and strategically planning human resource management tasks.This involves building an information management platform,developing a professional human resource management model to mitigate market risks,actively recruiting human resource management talents to form a competent team,and enhancing the human resource management and supervision system.These measures are essential for comprehensively improving the level of enterprise operation and management.

Research on Work-Life Balance of Female Employees

Nowadays,the pace of work and life is accelerating rapidly,accompanied by significant changes in work content and family structure.Enterprises and employees are encountering various pressures and conflicts.Female employees,in particular,are experiencing increasing pressure in both social labor and family affairs,resulting in ongoing conflicts between work and life.Achieving a balance between these two domains is crucial for female employees.This article aims to analyze the influencing factors of work-life balance for female employees and to propose useful strategies to help them improve it.

Study on the Promotion of Digital Trade to Northeast Asian Regional Economy

Society is currently transitioning from the era of informatization and digitization to the era of intelligence.Advanced technologies such as artificial intelligence,the Internet of Things,and big data are permeating every aspect of production and life.This penetration presents a rare opportunity for the development of digital trade and catalyzes innovation in traditional trade patterns.This paper first analyzes the inevitability of digital trade development in Northeast Asia.Secondly,it delves into the challenges faced by digital trade development and explores in-depth the promotion strategy for digital trade’s impact on the economic development of the Northeast Asia region,providing insights from various perspectives for reference.

基于三阶段集成学习的信用卡欺诈检测研究

信用卡欺诈是银行业面临的严峻问题,全球每年因信用卡欺诈造成的损失高达数十亿美元。然而信用卡交易数据存在特征冗余和样本不平衡的问题,这无疑增加了模型对少数欺诈交易的检测难度。针对以上问题,本文提出了三阶段集成学习模型“FS-IFKK-Stacking”:基于FS方法的特征选择、基于IFKK方法的不平衡数据处理和基于Stacking方法的异构模型集成。该模型同时解决了由于特征冗余和样本不均衡性导致的过拟合问题,能够更加准确地检测信用卡欺诈交易。基于Kaggle欧洲信用卡交易数据的实验表明:本文提出的“FS-IFKK-Stacking”模型对信用卡欺诈的检测效果明显优于基于原始样本训练的单类模型:在AUC提升0.44%的同时,对欺诈交易的召回率提升了3.27%。

Technologies Behind the Smart Grid and Internet of Things: A System Survey

Electric smart grids enable a bidirectional flow of electricity and information among power system assets.For proper monitoring and con-trolling of power quality,reliability,scalability and flexibility,there is a need for an environmentally friendly system that is transparent,sustainable,cost-saving,energy-efficient,agile and secure.This paper provides an overview of the emerging technologies behind smart grids and the internet of things.The dependent variables are identified by analyzing the electricity consumption patterns for optimal utilization and planning preventive maintenance of their legacy assets like power distribution transformers with real-time parameters to ensure an uninterrupted and reliable power supply.In addition,the paper sorts out challenges in the traditional or legacy electricity grid,power generation,transmission,distribution,and revenue management challenges such as reduc-ing aggregate technical and commercial loss by reforming the existing manual or semi-automatic techniques to fully smart or automatic systems.This article represents a concise review of research works in creating components of the smart grid like smart metering infrastructure for postpaid as well as in prepaid mode,internal structure comparison of advanced metering methods in present scenarios,and communication systems.

Comparative Study of Internationalized Talent Cultivation Models in International Higher Education Programs

The internationalization of talent cultivation in the field of international higher education is a widely discussed topic among higher education institutions worldwide.This paper conducts a comparative study of domestic and foreign higher education institutions and identifies some differences in the internationalization of talent cultivation among different countries and regions.Firstly,the study summarizes the changes in talent cultivation through domestic study abroad programs and overseas study programs.Then,this paper introduces the“Knowledge-Practice-Research”international talent cultivation model in China and the international talent cultivation model in Japan as an example.Finally,this study compares the international talent cultivation models in domestic and foreign higher education institutions.The results indicate that the internationalization of talent cultivation models needs to be adjusted according to different training objectives,specific countries,and even regional circumstances to adapt to local characteristics and the international environment.Overall,different countries and regions have different emphases and characteristics in the internationalization of talent cultivation in higher education institutions.However,regardless of the country,higher education institutions should focus on enhancing students’international perspectives and cross-cultural communication skills to adapt to the globalized economic and social environment.

Features and Trends of Chinese Management Style in the New Economic Era

According to the historical environment and national policies in different perods,Chinese business managers have gradually explored and formed management capabilities in accordance with market needs.Chinese management style has been established,based on the characteristics of Chinese society and the specific conditions of Chinese enterprises,applying China's excellent philosophy to business management.It absorbs global scientific management concepts and forms a management model with Chinese characteristics.Chinese management style has gradually influenced the development of world management.It is of great significance to study the Chinese management style.Studying the formation of the Chinese management style is not only to examine and analyze its own development process but also to deeply explore the characteristics of the Chinese management style and provide new ideas for management models for companies in other countries.This paper analyzes the reasons and characteristics of the formation of the Chinese management style and puts forward suggestions for the development trend of the.Chinese management style through comparative and SWOT analyses.

Exploring a Typical Regional Model for Rural Industrial Revitalization:Using Shimen Township as a Case Study

Implementing the strategy of rural revitalization and embarking on the path of socialist rural revitalization with distinctive Chinese characteristics are essential steps in addressing existing gaps in agricultural and rural modernization.These steps aim to swiftly increase farmers’incomes,enhance agricultural production capabilities,foster high-quality rural economic development,and rectify issues related to uneven development.Revitalizing rural areas and alleviating poverty among the majority of farmers represent major decisions made by the state regarding the“three rural issues.”This paper conducts an analysis and discussion centered on Shimen Township in She County within the context of the agricultural and rural development revitalization strategy.The objective is to identify prevailing challenges and propose relevant solutions.

Research on Enterprise Operation Mechanism Innovation Under Economic Transformation

With the rapid development of the market economy, complex changes have occurred in the market environment, and the competition among enterprises has become extremely fierce. The transformation of the structure of the market economy has prompted enterprises to seek for new developments and innovations. Under the background of the new economy, enterprises must begin from the perspective of internal management and internal strategic development to ensure quality enterprise operation mechanism innovation. This would help direct enterprise operation and development as well as demonstrate the value of enterprise internal management. In this way, enterprises will be able to array their overall competitiveness. This paper comprises a detailed analysis of the connotation and innovation of enterprise operation mechanism under the economic transformation, with the purpose of investigating the innovation strategy of enterprise operation mechanism under the economic transformation.

Analysis of the Standardization of Administrative Management in Colleges and Universities Under the Background of Information Technology

In the development of the information age,universities should recognize the significant impact of information technology on their own development.In practice,it is possible to effectively improve the efficiency and quality of work by dealing with and constructing information-based methods,innovating administrative management models,and adopting more efficient and scientific methods to address various problems and shortcomings encountered in work.As an important part of university management,administrative management is a complex task.Establishing a standardized management model through information technology can further improve the comprehensive efficiency of administrative management.In this regard,the administrative standardization in universities under the background of information technology is analyzed and studied in this paper.

Research on the Incentive System of Human Resource Management in Universities

Based on the actual situation of the establishment of the incentive system for human resource management in universities,the constituent elements and relevant principles of the incentive system for human resources in universities are expounded on,the current situation of the actual needs of the faculty and staff in universities is studied and analyzed,and practical plans for establishing the concept and implementing the incentive system in universities are proposed,with relevant incentive mechanisms for human resource management focusing on differentiated needs developed for reference.

Design and Application of Experimental Teaching in Consumer Behavior Courses

This article mainly elaborates on the design and application of experimental teaching in the teaching of consumer behavior.To study consumer behavior,it is necessary to understand their information collection activities before acquiring goods and services,as well as the evaluation and selection of goods,services,or brands.It is also important to pay attention to how they handle products and activities based on their satisfaction after purchasing products or services.In addition,through inquiry experiments,the learning effects of students can be improved,thereby highlighting the significance of inquiry experiments.

Investigating the Evolution of Human Resource Management in Enterprises in the Era of Big Data

Human resource(HR)management plays a crucial role in the overall management of enterprises,exerting a significant influence on their growth and development.With China now firmly entrenched in the era of big data,the conventional HR management approach is no longer adequate to meet the evolving demands of enterprise progress.Therefore,there is a pressing need to actively revamp the management strategies to improve the quality.This article outlines the importance of reforming enterprise HR management in the context of big data,scrutinizes the prevailing challenges in this domain,explores strategies for transforming HR management within enterprises in the era of big data,and provides illustrative examples to summarize valuable managerial insights,thereby offer enterprise leaders a valuable source of reference information.

Development Path of Innovation and Entrepreneurship Education in Universities Under the Digital Economy

With the development of digital technology and new models of digital economy,innovation and entrepreneurship education in colleges and universities is facing a new development situation.New methods such as online courses,digital platforms,and value co-creation have brought new opportunities and challenges to the content,mode,and mechanism of innovation and entrepreneurship education.This paper discusses the content and new opportunities of digital entrepreneurship,analyzes the differences between traditional entrepreneurship and digital entrepreneurship,and puts forward the strategy path of entrepreneurship education under the digital economy.

From Grammar to Critical Thinking in Seven Steps at 2013 KOTESOL DCC Symposium

＂From Grammar to Critical Woosong University, 2013 Thinking in Seven The purpose of the Steps＂ was presented at the 2013 KOTESOL DCC Symposium, project was to accelerate the learning curve of students with a higher than average IQ （intelligence quotient）, but functionally low in English. The students were required to write an essay, in the last hour of a four hour class. The students were challenged to fix sentences, write the reason they chose, and speak their answer. To determine if this was a one book idea, another test was tried with regular students, using an off the shelf grammar book. Using the same step by step process, the ability of students to make a story from a standard grammar book, was accomplished in a 90-minute class. Students enjoyed the activity and were able to use previously learned ideas in their sequencing and logical choices. This in turn strengthened the writing process, which was the goal. After four sessions, students in the initial trial class achieved better writing and story development skills. The second group did not continue the process due to class and schedule changes. Their understanding of the process was enlarged, but not tested