Journal of Computational Methods in Sciences and Engineering - Volume 24, issue 4-5

Authors: Li, Xiang

Article Type: Research Article

Abstract: In recent years, deep learning technology has developed significantly in the judicial field. More and more scholars are introducing deep learning to solve problems in the judicial field and improve the efficiency of judicial agencies in handling cases. An important task of judicial work is to identify the key elements of complex cases, establish the relationship between entities in the document, accurately grasp the development of the case, provide a basis for the understanding, analysis, and ruling of the case, and increase the interpretability of the case results. However, judging from the actual application situation, the application of deep learning …technology in the judicial field is not yet mature and still faces huge challenges. On the one hand, the existing legal text element identification methods only consider the identification of core elements and ignore the basic elements. However, the basic elements contain necessary legal-related information, which is basic case information unique to the legal field and has important reference value for judicial staff to analyze cases. On the other hand, the traditional method of identifying key elements does not consider the contextual semantic relationship and ignores the element semantic information and global semantic information is lost, resulting in poor recognition of key elements of legal text. Therefore, in the identification of key elements of legal texts, not only the core elements and basic elements must be considered, but also the semantic features of sentences and the semantic features of elements must be comprehensively considered, thereby improving the effect of identifying key elements of legal texts and promoting the efficiency of judicial organs in handling cases. Aiming at the problem of identifying the basic elements of legal texts, this paper proposes a model for identifying the basic elements of legal texts based on dynamic representation. This algorithm uses the dynamic representation capability of the BERT model to vectorize text and considers global domain semantic information during the pre-training process to achieve a more comprehensive vector representation. Secondly, the memory component of the bidirectional long short-term memory network is used to integrate all the feature information between long-distance words in the legal text, effectively express the meaning of the word in the context, and realize the recognition of the basic elements of the legal text. In addition, the conditional random field model is used to learn the transfer rules of labels between entities and output the label sequence that best conforms to the actual rules. Finally, the basic element identification model proposed in this article has been significantly improved by comparing it with the current better methods. Show more

Keywords: Judicial artificial intelligence, basic element recognition, bert model, bidirectional long short-term memory network

DOI: 10.3233/JCM-247453

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2333-2342, 2024

Authors: Xiao, Yue | Yu, Jiajia | Wen, Jiawei

Article Type: Research Article

Abstract: Since the beginning of 2021, the importance of the development of “Industrial Internet” and “Metauniverse” has been mentioned many times in many important documents such as the outline of the 14th Five-Year Plan and the 2021 government work report. Under the background that the industrial Internet has replaced the consumer Internet as the main direction, with the change of digital electronic information technology and the huge demand of the market, the new engineering electronic information specialty will face great opportunities and challenges. Education needs to cultivate a large number of differentiated talents and individualized skilled talents. Therefore, vocational education is …the guarantee of social talents in the process of promoting modern industrialization. Therefore, it is necessary to focus on the major strategy set by the state, closely connect with industrial upgrading, grasp the trend of technological change, promote the integration of production and education, and thoroughly implement the vocational skill grade certificate system. Moreover, the comprehensive education mechanism of “post-class competition certificate” should be promoted. Under the above background, aiming at the demand of electronic information major in new engineering, this paper puts forward the curriculum system reform of “post-class competition certificate”, and analyzes the practice process. On this basis, it completes the integration of teaching content and post work cases, realizes the docking of teaching mode and post work process, and finally realizes the matching of course examination and professional grade certificate standard. Besides, it can also improve curriculum resources, improve the composition of teaching staff, create high-quality curriculum training conditions, etc., and finally promote the rapid development of electronic information industry. Show more

Keywords: New engineering, information major, class certificate, four-dimensional fusion, curriculum system

DOI: 10.3233/JCM-247455

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2343-2355, 2024

Authors: Che, Kai | Yang, Peng | Luo, Peng | Yu, Jinxing | Hou, Haiping | Niu, Xiangnan | Gong, Yunqian | Chen, Chongming

Article Type: Research Article

Abstract: In recent years, wireless charging technology for electric vehicles has received increasing attention. Existing research has been limited to the safety of specific body parts in the electromagnetic environment of wireless charging for electric vehicles, with insufficient consideration for the overall human body and the electromagnetic safety of implanted medical devices. In order to assess its safety in the electromagnetic environment more comprehensively, a three-dimensional electromagnetic simulation software based on the finite element method is used to construct models of the human body and implanted medical devices in the electromagnetic environment of wireless charging for electric vehicles. The study aims …to investigate the impact of this electromagnetic environment on the human body and implanted medical devices. The results indicate that, except for the maximum magnetic induction of 0.47 μ T at the ankle, which exceeds the limit, the magnetic induction intensity and electric field strength in important tissue areas, especially the upper trunk of the human body, are both below the safety limits specified by the International Commission on Non-Ionizing Radiation Protection (ICNIRP) guidelines. For implanted cardiac pacemakers, the effective and peak magnetic field strengths are 13.7 A/m and 19.4 A/m, respectively, when the coil input power is 22 kW, meeting the relevant magnetic field strength requirements. The maximum temperature rise of the pacemaker is 3.2 × 10-3 ∘ C, and there are no significant changes in the temperature of the major organs in the human body after the implantation of the pacemaker. The thermal effects of electromagnetic waves on the temperature rise caused by implanted cardiac pacemakers have minimal impact on the human body. Show more

Keywords: Wireless charging technology, finite element method, implantable medical devices, electromagnetic safety assessment

DOI: 10.3233/JCM-247457

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2357-2374, 2024

Authors: Dong, Xiaoxiang | Zhang, Hui

Article Type: Research Article

Abstract: Regional economic development objectives are improved economic, political, and social conditions in a certain area. Investment, production, innovation, wealth, and affluence are the four stages of regional economic development that may be identified in each selected area. It becomes more reliant on technological advancements in the industry and less on locally sourced production inputs as the economy region grows. The regional economic growth issue is inequality in the rates of improvement of subnational geographic regions and inequalities in the distribution of wealth. Intellectual algorithms or enhanced and hybrid algorithms based on machine learning, such as Fuzzy C-means clustering (FCM), principal …component analysis, and algorithm, can newly achieve more appropriate solutions to practical issues of discrete, non-linear, non-differentiable, and various constraints. A hybrid algorithm combines two or more other algorithms that solve the same problem. Hence, this paper proposes a Principal Component Analysis for the Sustainable Regional Economic Development (PCA-SRED) model to enhance the efficiency in examining regional economic changes and industrial development zones. The data are taken from the Organization for Economic Cooperation and Development (OECD) regional statistics dataset. Using PCA, industries may be categorized based on shared criteria, and the whole spatial distribution law of datasets and common patterns can be uncovered. To create a long-lasting regional economic development plan, it is crucial to categorize, compare, and evaluate the economic growth level of several areas. The research outcomes illustrate that the hybrid algorithms have high accuracy and a fast convergence rate because they can replicate the smart behavior of some clusters in nature while examing the variances in regional economic growth. The experimental outcomes illustrate that the recommended PCA-SRED model enhances the accuracy ratio by 98.2%, industry production ratio by 95.6%, regional economic change prediction ratio by 96.4%, and economic efficiency ratio by 97.8% compared to other popular models. Show more

Keywords: Regional economic development, sustainability, hybrid algorithms, principal component analysis

DOI: 10.3233/JCM-247459

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2375-2390, 2024

Authors: Sun, Lixin | Wang, Qiuying

Article Type: Research Article

Abstract: With the rapid development of the information age, big data technology has been widely penetrated into various industries, and has brought profound impact on its structure and operation mode. In the field of music education, big data provides advanced tools and platforms for teaching, and provides a new perspective for the formulation of music teaching strategies and the sharing of educational resources. The purpose of this study is to deeply study the music teaching strategies based on big data and make a comparative analysis with traditional strategies. Based on an extensive literature review, this study summarizes the basic concepts, core …features and applications of big data in music teaching. In order to have a more comprehensive understanding of the actual effects of big data in music teaching, we designed a series of experiments to compare the performance of music teaching strategies based on big data and traditional strategies in terms of student learning outcomes, learning engagement, student satisfaction, teaching progress and efficiency. The results show that the music teaching strategy based on big data can better meet the personalized learning needs of students, improve the learning engagement, and significantly improve the teaching effect and the quality of resource sharing. This study provides scientific ideas and methods for music teaching, and hopefully provides beneficial enlightenment for the application of big data technology in the field of education. Show more

Keywords: Big data, music teaching strategy, educational resource sharing

DOI: 10.3233/JCM-247462

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2391-2407, 2024

Authors: Xu, Chi | Zheng, Xinyue | Luo, Jingjing | Jin, Linyi | Xu, Ruilin

Article Type: Research Article

Abstract: Forestry listed companies are an important force in the development of the forestry industry, and their human capital level is related to organizational innovation driving ability, comprehensive performance, and thus affects the development of the forestry industry. There is little existing research on this topic. From the perspective of organizational resilience improvement, this article constructs an evaluation index system for human capital of Chinese forestry listed companies based on the annual report data of 61 Chinese forestry listed companies, focusing on knowledge human capital, capacity human capital, and proactive human capital. On the basis of determining the weights of each …indicator in the evaluation index system using analytic hierarchy process and entropy value method, the final weights are determined using the combined weights method. Obtain a comprehensive evaluation value of the human capital level of each forestry listed company and conduct cluster analysis on this basis. In terms of research objects, this article focuses on human capital of forestry listed companies; In terms of research content, establish a systematic evaluation index system; At the research level, quantitative analysis was conducted to achieve innovation. The research results indicate that the comprehensive evaluation value of the overall human capital level of each forestry listed company has a maximum value of 0.8245 and a minimum value of 0.0801, with an average score of only 0.2692. Overall, there is room for improvement. A total of 56 companies were relatively average and poor, reaching 92%. The overall human capital of forestry listed companies is relatively low, which is closely related to the weakness, core competitiveness, and high risk of forestry. Therefore, the following policy recommendations are proposed: attach importance to the reserve of knowledge-based human resources and increase the proportion of employees with junior college degree or above in total employees; strengthen the construction of talent for technological breakthroughs and increase the proportion of R&D technicians ; pay attention to the improvement of the abilities of senior executives, directors, and supervisors, and optimize the structure of professional and technical titles; appropriately increase employee compensation levels and enhance employee proactive human capital utilization. Show more

Keywords: Improvement of organizational resilience, Chinese forestry listed companies, human capital evaluation

DOI: 10.3233/JCM-247464

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2409-2428, 2024

Authors: Duan, Yuanyu | Zhang, Weiwen | Liu, Haoyun | Chen, Jiaqi

Article Type: Research Article

Abstract: This investigation explores the erosion dynamics in sandy soils triggered by underground pipeline fractures, applying transparent soil technology for visualization. Through this approach, the erosion process within the transparent soil model was meticulously recorded using photography, enabling the quantitative analysis of collapse pit dimensions over time. Results reveal that soil erosion primarily manifests directly above the pipeline fracture, varying significantly with hydraulic conditions. In scenarios devoid of water flow within the pipeline, an increase in collapse pit depth is halted, attributed to the accumulation and blockage of soil particles at the fracture point. Contrastingly, under half-pipe and full-pipe flow conditions, …the depth of the collapse pit swiftly reaches the fracture site. The flow of water notably escalates the expansion rate of the erosion pit, especially above the rupture, leading to continuous enlargement of the central area and subsequent secondary and tertiary collapses at the pit’s apex. The study further identifies the impact of water flow on soil scouring near the pipeline rupture, with pronounced effects in full-pipe flow, predominantly ahead of the rupture point, and less significant impacts observed in half-pipe flow scenarios. Differential image analysis facilitated the categorization of soil into distinct zones: collapsed, loosened, stable, and eroded, with a direct correlation observed between the extent of the loosened zone and the velocity of water flow. Show more

Keywords: Road collapse, transparent soil, soil erosion, particle movement

DOI: 10.3233/JCM-247466

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2429-2445, 2024

Authors: Wang, Xiaofei | Wang, Pengfei | Zhang, Yaru | Liu, Bo

Article Type: Research Article

Abstract: Existing research data has been confirmed that the impact of stairs on the overall structure cannot be ignored under the action of earthquakes. To further evaluate the influence of staircases on the seismic resilience of reinforced concrete (Abbreviated as RC) frame structures designed according to Chinese design specifications during infrequent earthquake occurrences, a dynamic elastic-plastic analysis method was utilised. Differences in parameters such as period, vibrational modes, interlayer displacement angle, and base shear force were explored between structures with and without staircases. Data comparisons revealed that, in contrast to frame-only structures, structures with staircases exhibited reduced interstory displacement angles, floor …displacement, and floor shear force under lateral loads, with the maximum reduction amplitude being 1.76%, 0.7%, and 1.82%, respectively. Such findings suggest that staircases enhance the lateral stiffness of the structure, thereby bolstering its seismic performance. Furthermore, it was observed that the variance in seismic performance attributed to staircases diminished as the number of storeys increased. The above research results can provide some reference for how to consider the influence of stairs in concrete structures. Show more

Keywords: Concrete frame structure, stairs, rare earthquakes, dynamic elastoplastic time history analysis, seismic performance

DOI: 10.3233/JCM-247468

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2447-2467, 2024

Authors: Li, Jing | Liu, Songhua | Zheng, Jiannan | He, Fei

Article Type: Research Article

Abstract: The traditional paradigm of visual communication design education is encountering significant challenges in aligning with the dynamic learning preferences of contemporary students. This paper delves into the limitations of conventional educational approaches, particularly their inadequacy in delivering personalized content and hands-on learning experiences. In response, we propose a groundbreaking collaborative teaching model, seamlessly integrated with Artificial Intelligence (AI) technologies. This model emphasizes the transformation of visual communication design education by introducing an AI-enhanced task allocation framework tailored to the course’s specific needs, coupled with a comprehensive scheme for the fusion of knowledge and skill acquisition. Our research not only pioneers …a novel direction in teaching visual communication design but also serves as a valuable reference for educational reform across various disciplines, leveraging the potential of AI to enrich learning outcomes and foster a more engaging, customized, and practice-oriented educational environment. Show more

Keywords: Visual communication design, artificial intelligence (AI), collaborative teaching, teaching mode, task allocation model

DOI: 10.3233/JCM-247471

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2469-2483, 2024

Authors: Jiang, Wenbo | Zhang, Yuan

Article Type: Research Article

Abstract: In an era marked by rapid globalisation and digitalisation, the realms of education and technology are increasingly intersecting, particularly within the sphere of environmental design education. This study ventures into the integration of internet technology with environmental design pedagogy, emphasizing the development of a cross-disciplinary curriculum and a nuanced evaluation of its educational impact. Traditional research methodologies predominantly focus on short-term outcomes, often neglecting the longitudinal growth and deeper experiences of learners. Addressing this oversight, our research introduces an innovative curriculum system founded on knowledge graph techniques, aiming to enrich the educational content. The application of knowledge graph technology in …curriculum development is primarily manifested through the structured representation of course content, academic knowledge points, and their interconnections. By constructing knowledge graphs, educators are enabled to clearly identify the links and intersections between different academic fields, facilitating curriculum design that extends beyond the imparting of knowledge within singular disciplines to an integration of resources across subjects. This approach promotes the comprehensive application of knowledge and the cultivation of innovative capabilities. Alongside this, we employ a time series analysis for a more dynamic and detailed assessment of teaching effectiveness. This not only provides an academic benchmark but also charts a new course, offering actionable insights for educators in the field. Through this study, we aspire to bridge the gap between technology and environmental design education, ensuring a comprehensive and future-ready learning environment for students. In the context of environmental design education, the intrinsic connections between design principles, sustainability, and user experience are revealed through knowledge graphs. Within this framework, students are empowered to explore the application of these concepts in practical design projects. For instance, it becomes apparent that enhancing the user experience of a public space necessitates consideration of aesthetics, functionality, and environmental sustainability factors. Through this methodology, the use of knowledge graph technology not only enhances the coherence and systematic nature of course content but also fosters students’ creative thinking and problem-solving abilities, further driving the integration and innovation of education. Show more

Keywords: Internet technology, environmental design, cross-disciplinary curriculum, knowledge graph, time series analysis, teaching effect evaluation

DOI: 10.3233/JCM-247473

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2485-2501, 2024

Authors: Wu, Dongrong | Li, Zhongwu | Su, Jiafu

Article Type: Research Article

Abstract: With the rapid development of knowledge economy, the importance of knowledge sharing in the field of higher education is becoming more and more prominent, and university teachers as an important subject, the evaluation of their knowledge sharing level can better understand the status quo and problems of knowledge sharing of university teachers and take timely measures to make greater contributions to the development of universities and social progress. This paper selects willingness of knowledge sharing, ability of knowledge sharing, atmosphere for knowledge sharing, content of knowledge sharing, and the effectiveness of knowledge sharing as indicators for improvement and integration of …AHP, Critic, and fuzzy comprehensive evaluation. The weights obtained are coupled and assigned, and finally, the fuzzy comprehensive evaluation method is used to evaluate and rank the level of knowledge sharing among university teachers. Based on the weight of the five indicators, the article determines the impact of these indicators on the level of knowledge sharing among university teachers and provides corresponding suggestions, hoping to provide references for universities and relevant government departments. Show more

Keywords: The level of knowledge sharing, AHP method, Critic method, fuzzy comprehensive evaluation

DOI: 10.3233/JCM-247475

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2503-2516, 2024

Authors: Li, Jing | Yue, Ruiqi | Lin, Wei | Zhang, Jinbo | Yang, Yong | Qi, Lili | Gu, Qiaolun

Article Type: Research Article

Abstract: The traditional e-commerce’s traffic dividend is gradually declining, while social e-commerce as a new business model has attracted numerous enterprises to jump into by virtue of the advantages of viral traffic aggregation and efficient conversion. How to improve the core competitiveness and stand out from the Red Ocean battle of traffic competition is of great significance for the healthy and sustainable development of social e-commerce platforms. In view of this, this study focuses on the issues related to the attractiveness of social e-commerce platforms from the consumer’s perceptive, with the aim of providing theoretical support for social e-commerce platforms to …enhance their core competitiveness and formulate relevant development strategies and decision-making mechanisms. First, four key factors affecting the attractiveness of social e-commerce platforms based on the AISAS model are proposed: the ability to attract consumers to access, promote consumers’ purchase conversion, maintain consumers’ platform loyalty, and attract to share experiences. Second, an attractiveness assessment model for social e-commerce platform including four secondary indicators and corresponding 14 tertiary indicators is constructed by using Analytic Hierarchy Process, and an arithmetic example is demonstrated. Finally, management suggestions to enhance the attractiveness of social e-commerce platforms are presented. Show more

Keywords: Social e-commerce, platform attractiveness, consumer’s perspective, AISAS model, analytic hierarchy process (AHP)

DOI: 10.3233/JCM-247477

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2517-2547, 2024

Authors: Zhou, Zaohong | Jie, Yiting

Article Type: Research Article

Abstract: In order to identify the greater risks in the implementation of the new construction technology of ‘Embedded positioning construction technology of rotary digging pile hole casing’. And further explore the construction technical risk factors and the relationship between them. On the basis of the existing research and related standards, this paper uses the work decomposition method (WBS-RBS) to construct the construction technical safety risk index system from four dimensions: natural environment, material and equipment, construction quality and working personnel. And use the decision laboratory method (DEMATEL) to establish the internal relationship between the risk evaluation indicators, and then use the …network analytic hierarchy process (ANP) method to determine the weight of the risk evaluation index, establish a risk assessment model based on DEMATEL-ANP and carry on the example operation. The results show that the burying stability, fixing mode, type, upper position and installation stability of the reamer are the key work to ensure the normal implementation of the technology. Show more

Keywords: Risk assessment, casing embedded construction, DEMATEL, ANP

DOI: 10.3233/JCM-247479

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2549-2559, 2024

Authors: Zhou, Hongcheng

Article Type: Research Article

Abstract: Lip print recognition technology originated in the field of forensic medicine, and convolutional neural network has made breakthrough achievements in the field of pattern recognition and machine vision. Convolutional neural network (CNN) algorithm is rarely used in lip pattern recognition. Further exploration and research on the network model suitable for lip pattern recognition. Lip print recognition algorithm based on depth convolution neural network aims to solve the problems of complex image preprocessing, difficult feature extraction and low recognition efficiency in traditional lip print recognition algorithms. It includes collecting lip print images to establish data sets, selecting different CNN models to …conduct performance evaluation experiments on low resolution lip print data sets, and analyzing the experimental results with model evaluation indicators. Show more

Keywords: Lip print recognition, convolution neural network (CNN), low resolution, assessment

DOI: 10.3233/JCM-247482

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2561-2569, 2024

Authors: Pu, Jia | Bu, Yuting | Liu, Xuemei

Article Type: Research Article

Abstract: This study focuses on the steel industry, summarizing and clarifying relevant research by previous academics about investment value. Firstly, based on qualitative research, this study investigated the macro, meso, and micro factors that affect the investment value of listed companies in the iron and steel industry through fundamental analysis. The second part studied the financial factors of listed companies in China’s steel industry at the micro level through quantitative analysis. Ten evaluation indicators are selected from four aspects of growth capability, profitability, solvency and operating capability to establish the evaluation indicator system that reflects the comprehensive investment value of steel …sectors on the Chinese stock main board. 28 steel companies listed on the main board are selected as research sample. Empirical analysis is conducted to study these selected sample companies through the factor analysis method and generate an investment value comprehensive score ranking in which Yongjin Co., Ltd is the top winner. The evaluation method adopted in this study is also applicable to investors in terms of analysis and decision-making to avoid risks and improve returns. Show more

Keywords: Investment value, listed steel industry companies, factor analysis method

DOI: 10.3233/JCM-247484

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2571-2592, 2024

Authors: Zhou, Dan

Article Type: Research Article

Abstract: In this study, the marketing strategy of tourism destination driven by big data is deeply discussed. Firstly, the application of big data in the tourism industry and the current strategy of tourism destination marketing are analyzed, and then the research methods are designed through factor analysis and big data analysis theory. After processing and factor analysis of the collected data, the influence of big data on tourism destination marketing strategy is analyzed, and the possible optimization path is explored. At the same time, the problems and challenges encountered in this process are also found and analyzed. Based on these analysis …results, this study provides some theoretical and practical implications to promote the application of big data in tourism destination marketing strategies. Finally, it emphasizes the importance of big data and factor analysis in the formulation of future tourism destination marketing strategy, and puts forward the direction of future research. Show more

Keywords: Big data, tourist destination, marketing strategy, factor analysis, data analysis

DOI: 10.3233/JCM-247486

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2593-2609, 2024

Authors: Liu, Hongyu

Article Type: Research Article

Abstract: With the rapid development of music digitization and online streaming services, automatic analysis and classification of music content has become an urgent need. This research focuses on music sentiment analysis, which is the identification and classification of emotions expressed by music through algorithms. The study defines and classifies possible emotions in music. Then, advanced artificial intelligence techniques, including traditional machine learning and deep learning methods, were employed to perform sentiment analysis on music fragments. In the process of creating and validating the model, the combination of convolutional neural network and long term memory network shows excellent performance in various performance …indicators. However, for some complex or culturally ambiguous music fragments, the model may also suffer from misclassification problems. This provides the direction for further optimization of future research aimed at achieving more accurate music emotion analysis. Show more

Keywords: Music emotion analysis, artificial intelligence, deep learning, music classification, cultural difference

DOI: 10.3233/JCM-247488

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2611-2628, 2024

Authors: Zhang, Yingting | Deng, Yanyi

Article Type: Research Article

Abstract: With the improvement of environmental awareness, green logistics, as a kind of logistics mode that can realize the unity of economic benefits and environmental benefits, has been paid more and more attention by the academia and the industry. However, how to effectively evaluate the operation effect of green logistics is still a problem to be solved. To solve this problem, this paper proposes a green logistics evaluation index system based on factor analysis, and verifies its effectiveness through simulation data. In the process of building and validating the model, rigorous mathematical modeling methods were used, combined with a large number …of actual data. The results show that the evaluation index system of this study can accurately predict the operation effect of green logistics, and provide a practical evaluation tool for enterprises. Finally, the model is optimized to further improve its prediction accuracy. This study is of great significance to theoretical research and practical application. Show more

Keywords: Green logistics, evaluation index system, factor analysis, model verification, optimization strategy

DOI: 10.3233/JCM-247491

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2629-2642, 2024

Authors: Liu, Tengwen | Bai, Yun | Li, Hao | Jiang, Shuai | Li, Qing

Article Type: Research Article

Abstract: With the continuous development and application of big data technology, its potential and value in the field of education are gradually emerging, especially in oral English teaching, big data is placed on high hopes. However, the research on how to effectively use big data to improve the efficiency of oral English teaching is still in its infancy. This study aims to fill this research gap and explore and analyze how oral English teaching strategies based on big data can improve teaching efficiency through in-depth literature review and empirical research. The results show that big data can help teachers assess students’ …oral ability more accurately, and significantly improve students’ oral expression ability and learning efficiency by optimizing teaching strategies. However, oral English teaching strategies based on big data also have certain limitations, which need further research and improvement. This study provides a powerful theoretical basis and practical guidance for promoting the application of big data in oral English teaching. Show more

Keywords: Big data, oral english teaching, teaching strategy, teaching efficiency, evaluation system

DOI: 10.3233/JCM-247493

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2643-2656, 2024

Authors: Li, Rui | Zhao, Feng | Zhao, Boyu

Article Type: Research Article

Abstract: In the context of global economic integration and Industry 4.0, digital manufacturing has become crucial. As one of the economic cores of China, the digitization process of the manufacturing industry in the Yangtze River Delta is particularly critical to the overall economic growth. Based on the theory of Industry 4.0 and digital manufacturing, this study deeply analyzes the current digital development of the manufacturing industry in the Yangtze River Delta. More importantly, this paper successfully constructs a fuzzy control model to quantitatively evaluate and guide the process of digital transformation of manufacturing industry in this region. The empirical results of …the model reveal how key factors such as capital, talent, technology and data security affect the digitization process, and provide concrete and operational transformation strategies for the Yangtze River Delta region. In addition, combined with industrial advantages, policy support, technological progress and market demand, this paper predicts the digital development prospects of the manufacturing industry in the Yangtze River Delta. Overall, the study not only provides in-depth insights on the digitization of manufacturing in the Yangtze River Delta, but also provides practical guidance for actual operation, which has high theoretical and practical value. Show more

Keywords: Digital manufacturing, the yangtze river delta, development of manufacturing industry, challenge and possibility

DOI: 10.3233/JCM-247495

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2657-2671, 2024

Authors: Guo, Debing

Article Type: Research Article

Abstract: Financial securities fraud is one of the serious problems facing the global financial market at present, which not only destroys the fairness of the market, but also has a serious negative impact on investors and the economic system. The aim of this research is to develop and implement a deep learning-based approach to the identification and prevention of financial securities fraud. Firstly, the definition, types and characteristics of financial securities fraud are deeply discussed, and a financial securities fraud detection model is constructed with the help of deep learning technology. The model is trained, tested and optimized by collecting and …preprocessing large amounts of securities trading data and corporate financial reporting data. The empirical results show that our model has high accuracy and precision in the task of financial securities fraud detection. However, this study also reveals some challenges and limitations, such as problems with the model’s interpretability and adaptability to novel fraud strategies. Nevertheless, we believe that as deep learning technology is further developed and improved, its application in financial securities fraud identification and prevention will become more widespread and effective. Show more

Keywords: Financial securities fraud, deep learning, fraud recognition model, data preprocessing

DOI: 10.3233/JCM-247497

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2673-2688, 2024

Authors: Li, Zhiyuan | Luo, Fangyuan

Article Type: Research Article

Abstract: With the rapid development of Internet of Things technology, its application value in various fields has been widely concerned, especially in enterprise supply chain management. By connecting the physical world with the digital world, IoT technology helps companies monitor and manage all aspects of the supply chain in real time, thereby increasing efficiency, reducing costs, improving risk management, and increasing customer satisfaction. This paper studies the application and value of the Internet of Things in enterprise supply chain management in detail, first introduces the basic concept of the Internet of Things and its role in supply chain management, then builds …an enterprise supply chain management model based on the Internet of Things, and analyzes the specific application of the Internet of Things in each link of the supply chain. Then, using relevant data and formulas to simulate and analyze the specific value of IoT technology in improving supply chain efficiency, reducing cost and improving risk management, the research results are summarized, and suggestions are put forward on how to better apply IoT technology. The results show that the Internet of Things technology provides important support for the optimization of enterprise supply chain management and helps enterprises to improve their competitiveness. Show more

Keywords: Internet of Things, supply chain management, enterprise efficiency

DOI: 10.3233/JCM-247499

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2689-2703, 2024

Authors: Zhang, Yiming | Shang, Kejian

Article Type: Research Article

Abstract: In the current manufacturing process of enterprises, there are some problems such as poor predictability and low level of intelligence, which lead to high product error rate and affect production efficiency. Therefore, this paper introduces the building information model in the field of engineering construction, and proposes a big data predictive manufacturing model based on the building information model, which divides the production process into production service system, resource planning system, production control system and after-sales service system, and realizes the overall process optimization of planning-production-sales on the basis of the close combination of each system and virtual model system. …Finally, the application of error correction process in production line is verified from an empirical point of view, which provides a reference method and path for reducing production error rate and improving work efficiency. Show more

Keywords: Building information model, production process, the architecture, overall optimization

DOI: 10.3233/JCM-247502

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2705-2718, 2024

Authors: Dou, Xinfeng | Yin, Shengpeng

Article Type: Research Article

Abstract: The fixed effects regression has become an important method for estimating causal effects from panel data. Drawing on a sample of 282 companies in heavily-polluting industries in China from 2018 to 2021, this study utilized the linear fixed effects regression method to empirically examine the relationship between ESG and financial performance. Specifically, the study employed variable replacement and IV-GMM approaches to conduct robustness tests. The empirical results reveal a significant positive correlation between ESG composite scores and financial performance. Among the dimensions (E, S, G), the E dimension shows a significant positive correlation, while the S and G dimensions lack …a significant correlation. Notably, the E dimension most prominently promotes financial performance. In China, the impact is significant in the East but not in the Central or Western regions. Show more

Keywords: ESG, financial performance, heavily-polluting industries, fixed effects, IV-GMM

DOI: 10.3233/JCM-247504

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2719-2731, 2024

Authors: Liu, Hongkui

Article Type: Research Article

Abstract: The texture mapping technique based on irregular surfaces is widely used in many fields such as film and television, industry and games, etc. In order to adapt to the rapid development in the field of computer graphics and further enhance the uniformity and effectiveness of the texture mapping effect, a triangular mesh simplified texture mapping technique based on the optimized spring-fingertip is proposed. Firstly, a complex two-dimensional graph is established through the spring-fingertip model, which is parameterized and normalized to reduce the deformation of the texture; subsequently, the concept of triangular mesh simplification is introduced to optimize the model timeliness, …which replaces the traditional way of folding the edges; finally, the weight of each edge is further analyzed through local curvature calculation. In order to verify the effectiveness of the texture mapping method, simulation and analysis experiments are done, and the experimental results show that the accuracy of the model reaches 99.25%, which is an average improvement of 7.19% relative to the remaining four models. Therefore, the texture mapping model based on optimized triangular mesh effectively improves the realism of the mapping effect and reduces the computational burden of the model. Show more

Keywords: Texture mapping, surface, spring-particle, edge fold, triangular mesh

DOI: 10.3233/JCM-247506

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2733-2746, 2024

Authors: Zhang, Min | Sun, Xiaoliang

Article Type: Research Article

Abstract: With the rapid development of big data and artificial intelligence technology, the methods and approaches of literature research have also undergone profound changes. This study aims to explore and analyze how these technologies are integrated with literary studies and the new perspectives and opportunities that this integration brings to literary studies. The study investigates the use of advanced techniques in literary analysis, with a particular focus on the analysis of metaphors in literary works, the interaction between literature and social media, and statistical methods in literary criticism. Further, the influence of these technologies on literary theory and education is discussed, …and a series of revelatory conclusions are drawn. Collectively, these technologies have opened new portals to literary research, providing a wealth of tools and resources for literary researchers. Show more

Keywords: Big data, English literature, machine learning, intelligent literary criticism

DOI: 10.3233/JCM-247509

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2747-2762, 2024

Authors: Zhang, Shunli

Article Type: Research Article

Abstract: Under the influence of the Internet and social media, the network public opinion environment in colleges and universities has become a key factor in shaping campus culture and maintaining a harmonious society. The purpose of this study is to build a network public opinion evaluation model suitable for university environment through fuzzy evaluation method, and design an effective network public opinion guidance strategy based on this model. The results show that the fuzzy evaluation method can effectively deal with the uncertainty in the network public opinion environment and improve the accuracy and credibility of the evaluation. The guidance strategy based …on the evaluation results is helpful to improve the network public opinion environment and promote its healthy development. Show more

Keywords: College network public opinion, fuzzy evaluation method, evaluation model, network public opinion guidance strategy, network public opinion environment

DOI: 10.3233/JCM-247511

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2763-2779, 2024

Authors: Liu, Yuan | Chen, Guangwei

Article Type: Research Article

Abstract: With the continuous development of big data and machine learning technology, its application in literature research has gradually attracted attention. This study aims to explore how big data analysis techniques can reveal deep themes and emotional trends in 19th century British fiction. Through a comprehensive questionnaire survey, text mining and sentiment analysis, this paper studies and analyzes a large number of text data of 19th century English novels. Preliminary results show that deep neural networks and latent Dirichlet distribution (LDA) models can effectively reveal the theme and emotional changes in literary works. In addition, the analysis also reveals the literary …emotional changes in 19th century English society under the background of industrialization, urbanization and other important events. Overall, this study confirms the value of big data technology in literary research and provides new perspectives and methods for future research. Show more

Keywords: Big data, nineteenth-century English novels, emotion analysis, literary study

DOI: 10.3233/JCM-247513

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2781-2797, 2024

Authors: Qin, Nan

Article Type: Research Article

Abstract: Under the background of globalization, cultural and creative tourism has gradually become a new trend of tourism, providing tourists with rich and diverse travel experience. This paper discusses the development status, characteristics and integration strategies of cultural and creative tourism under the new normal. Through the analysis of the existing literature, it is found that cultural creative tourism not only brings economic benefits to the region, but also promotes the protection and inheritance of local culture. At the same time, technological advances and data convergence provide new opportunities for the promotion and management of cultural and creative tourism. But it …also brings challenges, such as how to ensure sustainable development and how to meet the growing demand of tourists. Finally, based on the method of multiple linear regression analysis, the paper analyzes the factors that affect the development of cultural creative tourism. Show more

Keywords: Cultural and creative tourism, data fusion, industrial chain integration

DOI: 10.3233/JCM-247514

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2799-2813, 2024

Authors: Cheng, Long | Wang, Hongyu | Wang, Tong

Article Type: Research Article

Abstract: With the wide application of deep learning technology in various fields, its potential in artistic creation has gradually attracted attention. This research focuses on the application of deep learning in the creation of traditional Chinese landscape painting and its cultural and aesthetic impact. First, the research comprehensively analyzes the existing deep learning algorithms and the basic elements of Chinese landscape painting to determine the most suitable model architecture. Then, through several rounds of experiments, various training parameters are adjusted and the optimal network configuration is determined. In terms of assessment, the study uses a variety of indicators, including visual quality …and technical performance, as well as in-depth cultural and aesthetic analysis. The results show that deep learning not only effectively improves visual quality and technical performance, but also has a positive impact on culture and aesthetics. Although there are some limitations, such as high computational requirements and reliance on large amounts of training data, corresponding solutions are also proposed. This study provides a powerful experimental basis for the integration of Chinese traditional art and modern science and technology, and promotes the research in this field. Show more

Keywords: Deep learning, Chinese landscape painting, visual quality, technical performance, cultural and aesthetic analysis

DOI: 10.3233/JCM-247516

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2815-2830, 2024

Authors: Wu, Jiaofeng

Article Type: Research Article

Abstract: With the rise of artificial intelligence, ships are gradually becoming intelligent. Ship path planning, as the foundation of ship intelligence, has become a current research hotspot. To achieve the planning of ship collision avoidance paths, a hybrid ant colony algorithm and artificial potential field for optimal safety path planning was proposed. The model makes up for the disadvantages of the slow convergence rate and the easy local optimum. At the same time, the ant colony algorithm in turn makes up for the poor global search ability of the artificial potential field method, so that the algorithm can achieve accurate path …planning. The test results show that in a simple environment, the hybrid ant colony algorithm, improved tangent and Dijkstra algorithm, and improved fast extended random tree * algorithm iterated about 7, 25, and 40 times respectively before starting to converge; In complex environments, the improved tangent and Dijkstra algorithms do not converge, while the improved fast expanding random tree * algorithm and hybrid ant colony algorithm iterate about 40 and 8 times respectively to begin convergence. It is clear that the mixed ant colony algorithm converges fast and can obtain the optimal path in the shortest time. The number of unsafe path points for the optimal path in a simple environment is 6, 1, and 0, respectively, for the improved tangent and Dijkstra algorithm, the improved fast expanding random tree * algorithm, and the hybrid ant colony algorithm; The number of unsafe path points for the optimal path in a complex environment is 9, 3, and 0, respectively; It can be seen that the path planned by the hybrid ant colony algorithm has higher security. The above results show that the mixed ant colony algorithm can effectively shorten the search time of optimal paths while improving the security of pathways. Show more

Keywords: Ant colony algorithm, artificial potential field, path planning, path smoothing strategy, inland river navigation, ship avoiding collision

DOI: 10.3233/JCM-247518

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2831-2845, 2024

Authors: Bu, Weijun

Article Type: Research Article

Abstract: Data support is already driving the development of artificial intelligence. But it cannot solve the semantic problem of artificial intelligence. This requires improving the semantic understanding ability of artificial intelligence. Therefore, a question answering system based on semantic problem processing is proposed in this study. The question answering system utilizes an improved unsupervised method to extract keywords. This technology integrates the semantic feature information of text into traditional word graph model algorithms. On this basis, semantic similarity information is used to calculate and allocate the initial values and edge weights of each node in the PageRank model. And corresponding restart …probability matrices and transition probability matrices are constructed for iterative calculation and keyword extraction. Simultaneously, an improved semantic dependency tree was utilized for answer extraction. The improved keyword extraction method shows a decreasing trend in P and R values. The improved answer extraction method has a maximum P -value of 0.876 in the training set and 0.852 in the test set. In a question answering system based on keyword and answer extraction, the improved method has lower loss function values and running time. The improved method has a larger area under ROC. The results of the validation analysis confirm that the improved method in this experiment has high accuracy and robustness when dealing with semantic problems. Show more

Keywords: Data logic, artificial intelligence, semantic issues, keyword, answer, extraction

DOI: 10.3233/JCM-247520

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2847-2861, 2024

Authors: Tian, Qiaoyu | Xu, Wen | Xu, Jin

Article Type: Research Article

Abstract: The Bayesian optimization algorithm uses Bayesian networks as the probability model of its solution space. Although the research on this algorithm has steadily developed, there are still some problems in its application process, such as excessive computational complexity. To solve various problems in Bayesian algorithm, reduce its computational complexity, and enable it to better achieve image segmentation. The study chooses to improve the Bayesian algorithm on the basis of immune algorithm, and solves the problem of computational complexity by reducing the number of Bayesian network construction times, thereby improving the individual fitness of the population. Through simulation experiments, it has …been shown that the average number of times the improved Bayesian algorithm reaches the optimal value is 30, which is higher than the traditional algorithm’s 20 times. Its excellent optimization ability searches for the optimal threshold to complete image segmentation. The improved Bayesian optimization algorithm based on immune algorithm can effectively reduce computational complexity, shorten computational time, and improve convergence. And applying Bayesian algorithm to image segmentation has broadened the application field of the algorithm and found new exploration directions for image segmentation. Show more

Keywords: Bayesian algorithm, image segmentation, immune algorithm, merit-seeking capability, Bayesian network, multi threshold images, algorithm application

DOI: 10.3233/JCM-247522

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2863-2877, 2024

Authors: Yang, Yong

Article Type: Research Article

Abstract: To improve the economic benefits of river dredging engineering construction, studies have been undertaken to optimize construction period costs. This study suggests a scheme for optimizing schedule costs through the use of three algorithms: non-dominated sorting genetic algorithm with elite strategy, simulated annealing colony algorithm, and ant colony algorithm. To achieve the preliminary algorithm selection of construction duration cost, the objectives have single and multi-objective, and iterative models are constructed separately. The validation results showed that the simulated annealing algorithm achieved the optimal solution in single objective optimization after the 81st iteration. The optimal solution of genetic algorithm in multi-objective …optimization was a construction period of 49 days and a cost of 1788.15 million yuan. The non-dominated algorithm reduced the construction period to 313 days, which can save 52 days of construction period and reduce costs by 52.32 million yuan. This optimization algorithm has high efficiency in predicting shorter construction periods and lower costs, and has strategic foresight in the decision plans of decision-makers. Show more

Keywords: Dredging engineering, NSGA-II, GA, SA, ACO, duration cost

DOI: 10.3233/JCM-247524

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2879-2894, 2024

Authors: Mei, Qian | Zhang, Peng | Si, Zhiyong

Article Type: Research Article

Abstract: Internet of Things development is of great significance for modern society progress. However, the limited information in some areas with incomplete infrastructure restricts Internet of Things development, so the long-distance information transmission task of sensor nodes needs to be put on the agenda. The research introduces beamforming technology for clustering wireless sensor nodes, and proposes a clustering algorithm based on wireless sensor node’s energy consumption rate for nodes energy management to achieve remote information sharing and transmission. The results confirm that the success rate of clustering algorithm based on beamforming event triggering increases with node density increasing, and the success …rate is infinitely close to 1. In addition, when the sensor node is 120, the average charging delay time based on machine learning energy consumption prediction is only 946 seconds, which is reduced by 521 seconds compared to the Mean-shift algorithm. When sensor node is 120, the algorithm has a successful access count of up to 1288 times. These two clustering algorithms have good clustering performance and significant practical application effects, providing reliable technical support for remote data transmission in the modern Internet of Things. Show more

Keywords: Clustering algorithm, sensor nodes, remote transmission, beamforming, energy consumption prediction

DOI: 10.3233/JCM-247527

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2895-2907, 2024

Authors: Li, Yanxue | Ma, Xiaohang | Song, Jianwei

Article Type: Research Article

Abstract: With the continuous advancement of the global industrialization process, industrial cultural heritage has gradually attracted the attention of all parties, but its protection and excavation still face multiple challenges. The purpose of this study is to explore the conservation and mining strategies of global industrial cultural heritage based on big data. Through a comprehensive analysis of the value and status quo of industrial cultural heritage, this study integrates multi-source data and constructs a big data processing and analysis model by using the questionnaire method. The research results show that big data has significant application potential and practical value in the …protection of industrial cultural heritage, and can provide more accurate and personalized protection strategies. Based on the data analysis, this study further proposes a series of practical conservation and excavation strategies to provide strong support for the sustainable development of industrial cultural heritage. This comprehensive analysis and practical recommendations are expected to advance scientific research and policy implementation in this area. Show more

Keywords: Industrial cultural heritage, big data, protection policy, data mining, sustainable development

DOI: 10.3233/JCM-247529

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2909-2926, 2024

Authors: Zhang, Ning | Wu, Chunyan

Article Type: Research Article

Abstract: With the continuous development of deep learning and artificial intelligence, its application potential in the field of education has attracted wide attention. This study mainly discusses the application of deep learning in college students’ career planning and entrepreneurship. First, through a comprehensive review of existing literature, the gaps and challenges of current research are revealed. Subsequently, empirical research methods were used to collect data on college students’ attitudes and feelings towards deep learning in career planning and entrepreneurship. This study develops and validates a model that predicts how deep learning interventions affect college students’ career choices and entrepreneurial intentions, while …also proposing a series of strategic recommendations. The findings suggest that deep learning can be used as an effective tool to help college students better plan their careers and enhance their entrepreneurial abilities. This study not only provides a new perspective for theoretical research, but also provides useful insights and tools for practitioners. Show more

Keywords: Deep learning, career planning, college student entrepreneurship

DOI: 10.3233/JCM-247531

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2927-2942, 2024

Authors: Zhang, Kewang | Shu, Zhixu

Article Type: Research Article

Abstract: For the problem that massive data and cloud computing in the industrial Internet of Things cannot meet the requirements of low latency, a cloud hybrid network architecture is proposed. In the single user scenario, RS coding is used to realize data redundancy, and the security evaluation method is put forward on this basis. By using the ant colony algorithm, the data transmission delay and security objective function are established to obtain the best allocation scheme. In the multi-user scenario, the SD-CFIIoT architecture is constructed by combining SDN and fog computing technology. The optimal solution is found by applying the ant …colony algorithm to solve the objective function of the data transmission delay. Simulation results show that when the security constraint is 0.9, the data transmission delay of RS is 5.04 s, which is 0.18 s less than LDPC; 0.19 s less than MBR. When the safety constraint is 0.9, the delay of the cloud mixed structure is 5.82 seconds; 1.53 seconds less than the cloud core structure and 1.20 seconds less than the fog core structure. When the data volume reached 80 MB, the delay of SD-CFIIoT was 2.20 s, 6.61 s lower than the fog structure and 15.80 s lower than the cloud structure. The simulation results prove the effectiveness of the proposed scheme, which can ensure data security while realizing low delay data transmission, improve the efficiency of the Internet of Things, and then improve the industrial production efficiency. This has a certain positive significance to the industrial modernization and intelligent development. Show more

Keywords: SDN, Internet of Things, data storage, ant colony algorithm, multi-user scenarios

DOI: 10.3233/JCM-247533

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2943-2956, 2024

Authors: Yu, Jianxi

Article Type: Research Article

Abstract: The field of engineering is becoming increasingly complex. In order to adapt to the numerical simulation of solving the partial differential equation of functionally graded beam vibration, a higher order stable numerical algorithm has been constructed. Differential quadrature method is used in discrete space domain. The discrete variational method is constructed in the time domain. The index differential Algebraic equation are obtained by combining the two methods. The discrete variational scheme is constructed for simulation. The results indicate that under long-term simulation, both the velocity and displacement constraints of the Runge Kutta method have defaulted. Displacement constraint values differ by …5 × 10 - 10 . The velocity, displacement and acceleration constraints of the discrete variational method are stable. Compared with the Runge Kutta method, the constraint magnitude is reduced. The speed constraint is maintained at within 2.5 × 10 - 15 . The displacement constraint level is maintained at within 1 × 10 - 16 . This indicates that the discrete variational method has high accuracy and good stability when solving problems such as the vibration equation of functionally graded beams. When the step sizes are h = 0.1 m and h = 0.01 m, the accuracy of the discrete variational method is close. The larger the step size h , the higher the computational efficiency of the discrete variational method. The discrete variational method can maintain structural and energy conservation, making it suitable for long-term simulations. This has a good effect on solving complex problems in the field of partial differential equations. Show more

Keywords: Functional gradient, partial differential equations, discrete variational method, differential quadrature method, rungekutta method

DOI: 10.3233/JCM-247536

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2957-2971, 2024

Authors: Liu, Yuan | Dong, Fang

Article Type: Research Article

Abstract: With globalization and technological progress, the demand for language translation is increasing. Especially in the fields of education and research, accurate and efficient translation is considered essential. However, most existing translation models still have many limitations, such as inadequacies in dealing with cultural and contextual differences. This study aims to solve this problem by combining big data analysis, machine learning and translation theory, and proposes a comprehensive translation quality evaluation model. On the basis of screening and constructing a representative sample database, pre-processing and standardization, feature selection is carried out by combining multi-dimensional features such as grammatical complexity and cultural …adaptability factors, and different machine learning algorithms are used for model construction and parameter optimization. Finally, by training and testing the model, the performance and effectiveness of the model are evaluated, and a comprehensive evaluation standard is constructed. The results show that this model can not only effectively improve the translation quality, but also has a high system application and universality. Show more

Keywords: Translation quality evaluation, big data analysis, machine learning, cultural adaptability, syntactic complexity

DOI: 10.3233/JCM-247538

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2973-2988, 2024

Authors: Liu, Bei | Zhou, Danqing | Zhang, Yaxuan | Xie, Hongyu | Shi, Jiayan

Article Type: Research Article

Abstract: Due to China’s thriving economy and culture, the performing arts sector has grown remarkably. To study its development, this study has examined the closing prices of performing arts companies. The GA-BPN model was used to analyze the daily closing prices of Funshine Culture (ticker: 300860) and Sanxiang Impression (ticker: 000863) for the predictions of their future daily closing prices. Next, the study compared the predicted prices with the actual closing prices. By comparing four models, namely GA, 7-4-1, 7-4-4-1, and 7-4-4-4-1, the GA-BPN model has a mean square error (MSE) of 2472.580273 and a root mean square error (RMSE) of …49.72504674, which is the smallest value and the smallest error among the four assessment metrics, it was determined that the GA-BPN model yielded the most accurate prediction results, so it was suitable for forecasting stock closing prices. Show more

Keywords: GA-BPN model, performing arts companies, business strategies, closing prices

DOI: 10.3233/JCM-247540

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2989-3002, 2024

Authors: Peng, Yun

Article Type: Research Article

Abstract: To enhance the precision of the music recommendation environment system, a novel design approach has been introduced, utilizing multi-label propagation and hierarchical clustering analysis for a dual music recommendation environment. First of all, the process model of music recommendation environmental system is built based on music recognition system, which is composed of music signal preprocessing module, music model, sound model and music recognizer; second, on the basis of further study on the clustering validity, a new clustering validity function is established by describing the intra-class compactness and inter-class separation of clustering through fuzzy similarity relation; finally, the validity of the …proposed music double recommendation environmental system using multi-label propagation hierarchical clustering analysis is verified by simulation experiment. The results show that the recommendation method based on comprehensive evaluation of user characteristics is suitable for single-category users, while the recommendation method based on multi-category evaluation is suitable for multi-category users. This approach offers an effective and precise means to enhance the accuracy and customization of music recommendation systems, thereby increasing user satisfaction. Show more

Keywords: Multi-label propagation, hierarchical clustering, music recommendation system, signal preprocessing, comprehensive evaluation of user characteristics

DOI: 10.3233/JCM-247542

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 3003-3014, 2024

Authors: Chen, Xiaoyong | Zong, Xuanyi | Yue, Haohao

Article Type: Research Article

Abstract: This work aims to address the evolving demands of logistics development by proposing an innovative solution: the Intelligent Cloud-based Logistics Service Platform (LSP), which seamlessly integrates Cloud Computing (CC) and the Internet of Things (IoT). The primary objective is to enhance the efficiency and effectiveness of logistics operations through advanced technology integration. Then, short-term logistics Demand Forecasting Model (DFM) and real-time Information Tracking System (ITS) are designed based on the proposed Cloud-based LSP. Specifically, based on Deep Learning, Ensemble Empirical Mode Decomposition (EEMD), and Local Mean Decomposition (LMD), the EEMD-LMD is employed for the logistics DFM. Simultaneously, the proposed real-time …logistics ITS is optimized by updating its hardware equipment through the wireless sensor. Then, the Kalman filter is employed for data processing. This work contributes to the ongoing transformation of logistics management, offering practical solutions to meet the dynamic challenges of modern supply chain management. Show more

Keywords: Cloud-based logistics, local mean decomposition (LMD), information tracking, deep learning, Internet of Things

DOI: 10.3233/JCM-247545

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 3015-3030, 2024

Authors: Zhao, Zijian | Liang, Jin | Chen, Jing | Shi, Xiaoling | Tong, Hui | Yuan, Yue | Pu, Qun | Perez, Hector Monzales

Article Type: Research Article

Abstract: This study seeks to enhance the entrepreneurial quality of college students by introducing advanced technologies such as deep learning and blockchain. A student majoring in electronic information at a university is the research object. Based on the background of the Internet of Things and blockchain technology, the innovation and entrepreneurship information data platform for college students is constructed. The results show that the α values of students’ background, students’ professional ability, students’ practical ability, and students’ development ability are greater than 0.7. When determining the number of neurons in the hidden layer, the training error curve decreases …continuously. The test error rises and then decreases when the number of neurons in the hidden layer is 10, 11, and 12. The Levenberg-Marquardt algorithm, selected as the training function, exhibits optimal performance with a training step count of 1,000 and achieves a performance score of 4.9. The actual values of the enhanced BPNN align closely with the expected values, demonstrating minimal deviation. The findings emphasize the importance for students in electronic information majors to actively engage in diverse social practices. This study serves as a valuable reference for enhancing the entrepreneurial quality of college students. Show more

Keywords: Deep learning, blockchain, entrepreneurship quality, entrepreneurial education evaluation, back propagation neural network

DOI: 10.3233/JCM-247547

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 3031-3045, 2024

Authors: Duan, Liusheng | Wu, Nan

Article Type: Research Article

Abstract: Studying the seismic performance of assembled concrete structures is an effective means to improve the quality of buildings. In this paper, the primary focus was on elucidating the research objectives. Initially, seismic performance experiments for assembled concrete structures were meticulously designed, and subsequently, concrete structural frames were assembled for comprehensive experimental analysis. A finite element model was developed for the nodes of the assembled concrete structure, incorporating the concrete principal structure model, concrete damage plasticity model, and steel principal structure model. Numerical simulations and finite element analysis were performed to verify the specific factors affecting the seismic performance of the …assembled concrete structure. The results show that the hysteresis curves of the assembled concrete frame obtained from the simulation and the test curves basically match, and the difference in the maximum forward beam end displacement is only 1.76 mm, with an error rate of only 3.98%. When the axial compression ratio of the assembled concrete structural frame is within 0.3, there is no decrease in the bearing capacity when the assembled concrete is loaded to 2.3% lateral displacement. This shows that the seismic performance of assembled concrete structures can be effectively analyzed by using finite element models, and also provides a new research direction for improving the seismic quality of buildings. Show more

Keywords: Finite element model, concrete principal, hysteresis curve, seismic performance, assembled concrete

DOI: 10.3233/JCM-247549

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 3047-3061, 2024

Authors: Li, Ting

Article Type: Research Article

Abstract: Traditional music emotion recognition (MER) faces problems such as lack of contextual information, inaccurate recognition of music emotions, and difficulty in handling nonlinear relationships. This article first used long short-term memory (LSTM) networks to capture global information and contextual relationships of music. Subsequently, the DCNN was chosen to process sequence data and capture global dependencies to improve the accuracy of MER. Finally, a MER model was constructed based on DCNN to recognize and classify music emotions. This article obtained the impact of different parameter values on model training iterations by adjusting hyperparameters related to training. The optimal values for learning …rate μ , momentum coefficient α , weight attenuation coefficient γ , and Dropout coefficient were 0.01, 0.7, 0.0003, and 0.5, respectively. The DCNN used in this article was iteratively trained with recurrent neural networks, convolutional recurrent neural networks, and transform domain neural networks for audio spectrograms, and the results were compared. The experimental findings indicated that the spectral recognition accuracy of DCNN was stable at 95.68%, far higher than the other three different networks. The results showed that the DCNN method used in this article could more accurately distinguish different negative emotions and positive emotions. Show more

Keywords: Deep convolutional neural network, music emotion recognition, audio feature extraction, long short term memory, self-attention network

DOI: 10.3233/JCM-247551

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 3063-3078, 2024

Authors: Chen, Yi | Lin, Xiaopin | Li, Zheng

Article Type: Research Article

Abstract: In order to effectively improve students’ learning outcomes and teachers’ teaching quality, this paper explores an optimization measure for students’ autonomous learning based on deep learning and Human-Computer Interaction (HCI) technology. Our proposed optimization measure constructs an interactive micro-video teaching model from teaching resources, teaching process, and teaching evaluation perspectives. The experimental results demonstrate that our proposed optimization measure can effectively improve students’ learning outcomes and satisfaction while enhancing their autonomous learning abilities and learning motivations.

Keywords: Micro-video design, human-computer interaction, teaching experiment, autonomous learning ability, knowledge test

DOI: 10.3233/JCM-247554

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 3079-3091, 2024

Authors: Xu, Jin

Article Type: Research Article

Abstract: This study introduces a novel risk assessment model for university student innovation and entrepreneurship, grounded in decision tree (DT) methodology. It tackles the challenges faced by traditional models in merging multi-source data and understanding nonlinear relationships. This advanced approach aims to enhance both the precision and reliability of risk evaluations in the context of student-led entrepreneurial ventures. From the four dimensions of entrepreneurial environment, entrepreneurial education, entrepreneurial groups, and entrepreneurs, relevant college student innovation and entrepreneurship data was collected, and the collected data was preprocessed to select the most relevant feature from all available features. The C4.5 algorithm was optimized …by cross validation to determine the depth of the number and the minimum sample size of leaf nodes, and a post-pruning strategy was adopted. The optimized C4.5 model was compared with Iterative Dichotomiser 3 (ID3), Classification and Regression Trees (CART), and C4.5 model, and risk assessment was applied to three entrepreneurial plan instances. The experimental findings indicated that the optimized C4.5 model had an average accuracy rate of 90.7% for the risk classification of college students’ innovation and entrepreneurship, and could accurately assess the risk of multiple entrepreneurial conditions in a comprehensive entrepreneurial plan. Show more

Keywords: Innovation and entrepreneurship, college students, risk assessment, decision trees, post-pruning strategies

DOI: 10.3233/JCM-247556

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 3093-3111, 2024

Authors: Ma, Xiaowen

Article Type: Research Article

Abstract: To study the application of convolutional neural networks (CNN) in microblog sentiment analysis, a microblog sentiment dictionary is established first. Then, latent Dirichlet allocation (LDA) is proposed for user forwarding sentiment analysis. The sentiment analysis models of CNN and long short-term memory network (LSTM) are established. Experiments are conducted to verify the application effect. The main contributions of this work encompass the establishment of a sentiment lexicon for Weibo, the optimization of two sentiment analysis models, namely CNN and LSTM, as well as the comparison and analysis of the performance of three sentiment analysis approaches: CNN, LSTM, and LDA. The …research findings indicate that the CNN model achieves a prediction accuracy of 78.6% and an actual output precision of 79.3%, while the LSTM model attains a prediction accuracy of 83.9% and an actual output precision of 84.9%. The three analysis models all have high sentiment analysis accuracy. Among them, LDA analysis model has the advantages of universality and irreplaceable in text classification, while LSTM analysis model has relatively higher accuracy in sentiment analysis of users forwarding microblog. In short, each sentiment analysis model has its own strengths, and reasonable allocation and use can better classify microblog sentiment. Show more

Keywords: Convolutional neural networks (CNN) model, deep learning, human-computer interaction, latent dirichlet allocation (LDA) model, long short-term memory network (LSTM) model, microblog sentiment

DOI: 10.3233/JCM-247558

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 3113-3135, 2024

Authors: Zhang, Shu

Article Type: Research Article

Abstract: In order to solve these problems, this paper introduced the grey system theory (GST) method in the real-time application of intelligent traffic signal optimization (ITSO). In this paper, the deep Q-network (DQN) algorithm was used to realize the dynamic signal light setting of real-time traffic conditions, which can improve the overall operating efficiency of the traffic system, and the PPO (Proximal Policy Optimization) algorithm was used to solve the problem of the lack of real-time performance of the traditional traffic signal optimization methods. By comparing the traffic congestion index of S city before and after the application of the GST …method, the paper found that the average one week before the application was 60.1%, but it dropped to 26.6% after the application. In the experimental test of average speed comparison, the speed after applying the GST method was generally higher than the value before application, and the overall speed increase was about 20 km/h. This paper emphasizes the importance of evaluating the robustness of the GST method, particularly in its ability to manage unexpected scenarios. The research concentrates on assessing four critical indicators: outlier handling, noise tolerance, handling missing data, and nonlinear coping ability. Show more

Keywords: Grey system theory, intelligent transportation, traffic signal optimization, real-time data, optimization algorithm

DOI: 10.3233/JCM-247560

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 3137-3153, 2024