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software engineering, Social Network Analysis and Intelligent Computing (SSAIC), asia-pacific conference on

作者： Wei Ren Shenyang City University Shenyang Liaoning China

ISBN: (数字)9798350393682

ISBN: (纸本)9798350393699

Web opinion expresses the will of the public to a certain extent. Although it has the commonness of public opinion in the general society, it has the basic characteristics of a complex system in the virtual society because of the influence scope and communication speed of the Internet, so its communication tendency and development direction are paid attention to. Mobile Internet has become an irreversible trend, which is profoundly changing people’s living habits and even their way of life. In this article, a public opinion propagation model of news APP network based on improved collaborative filtering (CF) algorithm is proposed. The results show that the model constructed in this article can not only describe the change of the proportion of communication subjects in the network, but also simulate the communication vitality and scope of news APP mobile web opinion. Web opinion presents more complicated and difficult-to-describe communication and evolution characteristics than traditional public opinion, which makes traditional research methods and means unsustainable. The model constructed in this article has certain reference value for public opinion analysis, judgment and pre-alarm of mobile networks.

关键词： Analytical models Social networking (online) Publishing Collaborative filtering software algorithms Predictive models Market research

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Integrating Feedback From Application Reviews Into software Development

Integrating Feedback From Application Reviews Into Software ...

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asia-pacific conference on software engineering

作者： Omar Abdelaziz Zadia Codabux Kevin Schneider Department of Computer Science University of Saskatchewan

ISBN: (数字)9798331534011

ISBN: (纸本)9798331534028

In application (app) development, effectively harnessing user feedback is crucial for enhancing app quality and user feedback. However, the vast and unstructured nature of user reviews often complicates these efforts, posing challenges in accurately capturing and integrating this feedback into the development processes. We automate the classification of issues in app reviews and examine how these issues correlate with code quality metrics (code smells and bug reports) and development activities (additions, deletions, and time to merge in pull requests). We aim to provide evidence-based guidance for effectively prioritizing and addressing user feedback. Employing a Mining software Repositories (MSR) approach, we gathered and analyzed reviews from seven open-source Android apps. We evaluated the efficacy of three machine learning models-Support Vector Machines (SVM), BERT, and a fine-tuned GPT-3.5-for classifying issues in app reviews. The GPT-3.5 model achieved the highest accuracy at 95.0%. We found statistically significant correlations between the classified issues, code quality metrics, and development activities. However, these relationships varied across applications, highlighting the complex relationship between user feedback and the development process. Our study highlights the effectiveness of automated tools in identifying and classifying feedback within app reviews. Our automated approach enhances developers' ability to manage feedback effectively and supports optimal resource allocation to improve app quality and user feedback.

关键词： Measurement Support vector machines Sentiment analysis Codes Accuracy Toxicology Reviews Vectors Resource management software engineering

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Strengthening Teaching and Learning Based Multi-population Symbiotic Organism Search Algorithm

Strengthening Teaching and Learning Based Multi-population S...

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software engineering, Social Network Analysis and Intelligent Computing (SSAIC), asia-pacific conference on

作者： Qiwen Zhang Bingting Liu Lanzhou University of Technology Lanzhou Gansu China

ISBN: (数字)9798350393682

ISBN: (纸本)9798350393699

A Strengthening Teaching and Learning based Multi-population Symbiotic Organism Search algorithm (STLMSOS) is proposed to address the shortcomings of the symbiotic biological algorithm in solving complex high-dimensional problems, such as low accuracy, poor diversity and the tendency to fall into local optimality. The algorithm divides the ecosystem into three populations based on the evolutionary characteristics of organisms, and draws on the powerful search capability of the “teaching” phase and the excellent search capability of the “learning” phase of the teaching optimization algorithm, so that the mutualism population and commensalism population can evolve in stages, enhancing the solution accuracy and diversity of the algorithm. At the same time, by taking into account the complex connection between biological migration and species evolution, the information interaction between multiple populations is improved so that stagnant populations can interact in time to jump out of the local optimum. The proposed STLMSOS was fully evaluated on the CEC2017 problem set, and the simulation results show that STMSOS outperforms other state-of-the-art algorithms and is an effective algorithm for solving complex high-dimensional problems.

关键词： Symbiosis Accuracy Sociology Education software algorithms Search problems Organisms

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Implementation of Mental Medical Registration Algorithm Based on Psychopathology Model

Implementation of Mental Medical Registration Algorithm Base...

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software engineering, Social Network Analysis and Intelligent Computing (SSAIC), asia-pacific conference on

作者： Zhuoxin He Shantou University Medical College Shantou Guangdong China

ISBN: (数字)9798350393682

ISBN: (纸本)9798350393699

Psychopathology also refers to psychopathology, which is a scientific study of various psychological disorders. Strictly speaking, the research fields it involves include psychologists, psychiatrists, neuroscientists, endocrinologists and pharmacologists, which are different from the medical practice of clinical psychologists and psychiatrists who treat psychological disorders. In this paper, we propose a mental medical registration algorithm based on psychopathology model, which sets the search direction as the initial orthogonal search direction again after every complete update of the search direction. The experiment shows that the registration algorithm in this paper only needs about 150 iterations to reach the optimal solution, while the genetic algorithm needs 210 times. The experimental data fully show that the registration algorithm has a good global search ability, and has achieved good results. The registration technology is used to fuse the image information obtained under different conditions, integrate the advantages of various imaging devices, and express the patient’s mental information as much as possible in psychopathology, becoming a strong backing for clinical medical observation, diagnosis and treatment of boils in psychiatry.

关键词： Social networking (online) Computational modeling software algorithms Psychology Medical treatment Medical diagnostic imaging Optimization

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User Behavior Analysis and Prediction Algorithm Design of E-commerce Platform Based on Big Data Analysis

User Behavior Analysis and Prediction Algorithm Design of E-...

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software engineering, Social Network Analysis and Intelligent Computing (SSAIC), asia-pacific conference on

作者： Xiao Gao Xiangtan Institute of Technology Xiangtan Hunan China

ISBN: (数字)9798350393682

ISBN: (纸本)9798350393699

From the consumer’s point of view, e-commerce is online shopping, which is deeply loved by consumers because of its convenient price comparison, unlimited commodity selection, rapidity and convenience. Faced with a large number of EC (Electronic Commerce) website shopping users, it is particularly difficult to analyze users’ behaviors. Therefore, this paper designs the user behavior analysis and prediction algorithm of e-commerce platform based on big data analysis, and through experimental analysis, it can be found that the types of books purchased by students in traditional bookstores are also different from those purchased online. Students often buy exam guidance books in traditional bookstores, accounting for an average of 47.51% of all books; The most frequently purchased books in online bookstores are exam counseling, accounting for an average of 82.61% of all books. This shows that the algorithm designed in this paper can provide marketing decisions for EC websites, reduce marketing costs, guard against operational risks, expand the scale of EC users and the successful shopping rate, enhance EC benefits and enhance market competitiveness.

关键词： Social networking (online) software algorithms Big Data Prediction algorithms Internet Electronic commerce Noise measurement

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S²LMMD: Cross-Project software Defect Prediction via Statement Semantic Learning and Maximum Mean Discrepancy 28

S<SUP>2</SUP>LMMD: Cross-Project Software Defect Prediction ...

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28th asia-pacific software engineering conference (APSEC)

作者： Liu, Wangshu Zhu, Yongteng Chen, Xiang Gu, Qing Wang, Xingya Gu, Shenkai Nanjing Tech Univ Sch Comp Sci & Technol Nanjing Peoples R China Nanjing Univ State Key Lab Novel Software Technol Nanjing Peoples R China Nantong Univ Sch Informat Sci & Technol Nantong Peoples R China

ISBN: (纸本)9781665437844

Different from within-project software defect prediction (WPDP), cross-project software defect prediction (CPDP) does not require sufficient training data and can help developers in the early stages of software development. Recent studies tried to learn semantic features for CPDP by feeding neural networks with abstract syntax tree (AST) token vectors. However, the ASTs directly parsed from software modules usually have complex structures, which are reflected on more nodes and deeper size, and the transfer learning is not regularly adopted to further reduce the data distribution difference between the source project and the target project. To solve these problems, we aim to joint learn the statement level trees (SLT) and alleviate data distribution difference with maximum mean discrepancy (MMD) to improve defect prediction performance on CPDP. Specifically, we propose a novel cross-project defect prediction method (SLMMD)-L-2 via statement semantic learning and MMD. We first construct the SLT by splitting the original AST on specified node. Then we generate more effective semantic features by learning of sequence embedding with Bi-GRU neural network. Finally, a transfer loss MMD is carried out to keep more common characteristics across different project datasets to further improve CPDP performance. To verify the effectiveness of our proposed method, we conducted experiments on ten widely used open-source projects and evaluated the experimental performance by using AUC measures. Our empirical results show that our proposed method (SLMMD)-L-2 can significantly outperform eight state-of-the-art baselines. In addition, for semantic learning, SLT has a higher influence on CPDP, while MMD is of great significance in transfer learning.

关键词： cross-project defect prediction source code representation statement semantic learning maximum mean discrepancy

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Construction of Music Curriculum Resource Management System Based on Collaborative Filtering Algorithm

Construction of Music Curriculum Resource Management System ...

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software engineering, Social Network Analysis and Intelligent Computing (SSAIC), asia-pacific conference on

作者： Donglin Li Anshan Normal University Anshan Liaoning China

ISBN: (数字)9798350393682

ISBN: (纸本)9798350393699

Strengthening university students’ cultural quality education is a necessary condition for the country to cultivate all-round high-quality talents, and improving university students’ scientific and cultural quality in an all-round way is inseparable from the effective development and utilization of curriculum resources. Therefore, relevant personnel should make use of the integration of music curriculum resources to continuously improve the quality of music teaching. This article discusses how to develop music curriculum resources, and proposes and constructs a personalized music curriculum resource management system. Based on CF (Collaborative filtering) algorithm, the system can recommend instructional resources that users may be interested in according to their browsing records, browsing habits and preferences. Finally, the proposed algorithm is compared with other algorithms on related data sets. The test results show that the RMSE of this algorithm is low, which is 0.525, and the recall and F1 value are at a high level, which can reach more than 94%. It is hoped that this research can effectively broaden students’ musical horizons and make students truly develop their musical literacy in the stage of innovation in music teaching.

关键词： Technological innovation Social networking (online) Collaborative filtering Education software algorithms Music Internet

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Numerical Simulation of 'Wet' State Critical Speed of the Wet Submersible Motor Rotor System

Numerical Simulation of 'Wet' State Critical Speed of the We...

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2022 IEEE asia-pacific conference on Image Processing, Electronics and Computers, IPEC 2022

作者： Wang, Haoyu Wang, Yanfeng Illinois Institute of Technology Chicago60616 United States Henan University of Technology School of Mechanical and Electronic Engineering Zhengzhou450001 China

ISBN: (纸本)9781665409025

The water friction generated by the viscosity of axial cooling water in wet submersible motor could affect the rotor dynamic characteristics, which is applied to rotor outer surface in a prestressed manner. We take an 850QS-3200 type wet submersible motor as the research object. In this work, the internal fluid flow is simulated based on the numerical simulation through ANSYS Fluent software. For studying the quantitative relationship the surface roughness of rotor outer surface, rotor speed and axial cooling water flow rate between stator and rotor. After this, the finite element method is used to get 'wet' state critical speed by loading the water friction on the rotor system. Then the quantitative relationship is compared and analyzed between the 'wet' and 'dry' state critical speed of rotor system. Results show that the rotor rotating speed has a great influence on the 'wet' state critical speed, but the water friction upon that is negligible. The simulation analysis is verified through vibration experiment. The results of this study would provide a theoretical basis for the improvement of the rotor system in wet submersible motor. © 2022 IEEE.

关键词： Cooling water

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Methods to Enable Evolvable Digital Twins for Flexible Automated Production Systems

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asia-pacific JOURNAL OF OPERATIONAL RESEARCH 2024年第0期

作者： Vogel-Heuser, Birgit Lahrsen, Bjarne Wilch, Jan Ji, Fan Zhang, Mingxi Neumann, Eva-Maria Tech Univ Munich Inst Automat & Informat Syst TUM Sch Engn & Design Boltzmannstr 15 D-85748 Garching Germany Tech Univ Munich MIRMI MDSI Garching Germany

Changing requirements cause flexible automated Production Systems (aPS) to evolve over decades. Digital Twins (DT) of the different hierarchy levels and design steps ease this evolution, e.g., by enabling requirement analysis and compatibility checks ahead of any physical changes. To ensure up-to-date models and integrate additional knowledge, information gained during operation is included in DTs. Consequently, evolvability, decomposability, control software modularity, and learning during operation are identified as four requirements to achieve such evolvable DTs. Concepts to realize every requirement are introduced and exemplarily validated using a demonstrator machine. AutomationML (AML), the XML-based vendor neutral language for information modeling and exchange in between different disciplines and their tools and product classification systems like ECLASS that specify components attributes vendor neutral enable evolvability during the design phase. Decomposability is achieved by assembling DTs of components according to ISA 88 levels from control unit to facility. A control primitive concept that realizes control software modularity is introduced and validated. Based on data analytics and operation data the DT can be updated by using the versioning mechanism of AML. Thereby, the DT for the next machine generation is improved with knowledge from operation and represents the already existing machine more precisely.

关键词： Digital twin model-based interdisciplinary engineering life cycle automated production systems control software flexibility ECLASS

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Design of Extended RISC-V for Q-Learning Hardware Accelerator using HW/SW Co-Design

Design of Extended RISC-V for Q-Learning Hardware Accelerato...

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IEEE asia-pacific conference on Circuits and Systems

作者： Infall Syafalni Muhammad Sulthan Mazaya Muhammad Raihan Elfazri Eko Mursito Budi Nana Sutisna Rahmat Mulyawan Trio Adiono Makoto Ikeda School of Electrical Engineering and Informatics Bandung Institute of Technology Indonesia University Center of Excellence on Microelectronics Bandung Institute of Technology Indonesia System Design Laboratory School of Engineering The University of Tokyo Tokyo Japan Faculty of Industrial Technology Bandung Institute of Technology Indonesia Graduate School of Engineering The University of Tokyo Tokyo Japan

ISBN: (数字)9798350378771

ISBN: (纸本)9798350378788

In this paper, we propose a novel RISC-V ISA extension for a reinforcement learning-based hardware accelerator called RISC-Q. We introduce new instructions i.e., ***_constant, ***, ***, ***, and ***. Each instruction corresponds to a hardware module. The ***_constant sets necessary constants for the Q-learning by storing it in dedicated registers. The *** and *** instructions write and read the data to the main memory. The *** instruction controls the max seeker hardware module to find $\mathbf{Q}$-max values. The *** instruction accesses the $\mathbf{Q}$-updater hardware module to update the $\mathbf{Q}$-value with the corresponding state, action, and reward. Experimental result shows that the RISC-V extended reinforcement learning hardware accelerator (RISC-Q), which is implemented in the Nexys FPGA board, outperforms the software implementation up to $1.5 \times$ speed up. The work is useful for edge-computing applications such as smart navigation, smart communications, and robotics.

关键词： Q-learning Navigation Circuits and systems asia software Registers Hardware acceleration Robots Field programmable gate arrays

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