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9th International Conference on Computer and Communications, ICCC 2023

作者： Yang, He Le, Wei Yumin, Li Chengdu University of Information Technology School of Software Engineering Chengdu China Chengdu University of Information Technology Automatic Software Generation & Intelligence Service Key Laboratory of Sichuan Province Sichuan Manufacturing Information Industry Collaborative Innovation Center Chengdu China Sichuan Top It Vocational Institute College of Information Engineering Chengdu China

ISBN: (纸本)9798350317251

To address the limitations of existing code defect detection methods, which only analyze code defects from a single perspective and produce uninterpretable results, we introduce a new approach known as Defect Detection Method based on code defect knowledge Graph (DDMB). This method involves several steps. First, we clean and organize defect-related knowledge, defining concepts of defect entities, attributes, and relationships to establish a code defect knowledge graph. Next, using abstract syntax trees, we extract various information from the code, including control flow diagrams, control dependency graphs, data dependency graphs, program dependency graphs, and code attribute graphs, to capture relevant details about nodes and edges. Based on the structural and logical information represented by node-edge associations, we employ the Deepwalk algorithm to construct a directed graph of the code and generate random walk sequences. These sequences serve as a foundation for learning and vector representation. Finally, we compare the vector similarities between the generated representations and a candidate code list from the defect knowledge graph, which has undergone initial semantic threshold filtering. By querying the defect labels of the most similar code in the defect code knowledge graph, we determine whether the code under inspection contains defects. Experimental results reveal that DDMB improves defect detection accuracy by 2.02% compared to existing methods. Additionally, it enhances the interpretability and reliability of defect detection while facilitating multi-dimensional analysis of code defects, thus providing better support for practical applications. © 2023 IEEE.

关键词： Graphic methods

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Emotion and Mentality Monitoring Assistant (EMMA) 8

Emotion and Mentality Monitoring Assistant (EMMA)

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8th International Conference on Communication and Electronics Systems, ICCES 2023

作者： Kiridena, Ishini Marasinghe, Dayan Karunarathne, Ruvini Wijethunga, Kavindu Fernando, Harinda Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798350396638

Human emotions, psychology, and social well-being are all parts of mental health. It has an impact on how people feel, think, and act. It aids in figuring out how individuals act under pressure, interact with each other, and arrive at decisions. Every period of life, from childhood and adolescence to maturity, is vital for mental health. There are several elements that affect mental health issues, such as experiences with trauma or abuse in life, work-life stress, relationship difficulties, etc. Help is available for many of the mental health issues that are identified within a person. The proposed solution is implementing a friendly chatbot that is capable of capturing human emotional states (happy, angry, sad, etc.) and mental health states (depression, anxiety, stress, etc.) using human computer interaction and health record management. The proposed solution has been developed by considering both regular users and mental health practitioners. The user can communicate with the proposed assistant using text or voice to identify their emotions and mental health based on keywords, particular characteristics of voice and facial recognition used during the conversation. Once the mental health and emotion statuses are analyzed the electronic health records will be readily available on the blockchain as blockchain tokens, this could be shared with the practitioners securely. © 2023 IEEE.

关键词： Blockchain

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Evaluation of Different Machine Learning Classifiers on New IoT Dataset CICIoT2023

Evaluation of Different Machine Learning Classifiers on New ...

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2024 International Conference on Intelligent Systems for Cybersecurity, ISCS 2024

作者： Kumar, Anmol Geetesh Rastogi, Ansh Ranga, Virender Delhi Technological University Department of Software Engineering New Delhi India Delhi Technological University Department of Information Technology New Delhi India

ISBN: (纸本)9798350375237

In today's society, Internet of Things is playing a profound role in revolutionizing a number of industries. It's use in sectors like transportation, smart home appliances, & healthcare is rapidly growing, with new services constantly being developed. Over the past decade, there has been an exponential surge in IoT connections, and this trend is expected to continue in the coming years across different domains. However, it has also exposed a new frontier for cyber-attacks. The sensitive nature of data collected by IoT devices demands stringent security measures. This paper analyzes the classification performance of various cyber-attacks in the IoT domain. For performance evaluation, the cutting-edge CICIoT2023 dataset is used [1]. The dataset encompasses a variety of attacks carried out against 105 IoT devices, which includes benign traffic, DoS and DDoS attacks, reconnaissance and information gathering, web-based attacks, spoofing, brute-force threats, and Mirai botnet attacks. This dataset encompasses wide range of cyber threats & serves as a valuable tool for understanding and mitigating IoT-related security threats. © 2024 IEEE.

关键词： Internet of things

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Managerial Coaching Impact on Turnover Intentions: A Computational Study 24

Managerial Coaching Impact on Turnover Intentions: A Computa...

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2024 International Conference on Machine Learning, Pattern Recognition and Automation engineering, MLPRAE 2024

作者： Chen, Yanqin Huang, Haihui School of Business Macau University of Science and Technology China School of Information Science and Engineering Provincial Demonstration Software Institute Shaoguan University China

ISBN: (纸本)9798400709876

This study investigates the role of managerial coaching in mitigating employee turnover intentions. The investigation utilizes a computational framework to assess the mediating role of organizational commitment and the moderating impact of leader-member exchange (LMX) in this context. Leveraging cross-sectional survey data from diverse industries, advanced computational techniques, including Lasso regression analysis, are applied to identify the intricate relationships between managerial coaching, LMX, and turnover intentions. The computational analysis reveals a significant negative correlation between managerial coaching and turnover intentions, with organizational commitment serving as a partial mediator. Additionally, the study employs computational models to explore how LMX moderates the influence of managerial coaching on organizational commitment. The findings highlight the predictive power of computational approaches in identifying key determinants of employee turnover, emphasizing the vital roles of managerial coaching and LMX. This research provides a novel computational perspective on the mechanisms through which coaching, and leader-member relationships translate into reduced turnover intentions, offering actionable insights for organizations seeking to minimize voluntary turnover. Furthermore, it contributes to the discourse on integrating leadership concepts into turnover prediction models and elucidates the computational underpinnings of how develop-mental leadership influences employee attitudes and behaviors. © 2024 ACM.

关键词： Regression analysis

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SEVGGNet-LSTM: A Fused Deep Learning Model for ECG Classification 19th

SEVGGNet-LSTM: A Fused Deep Learning Model for ECG Classifi...

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19th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2023

作者： He, Tongyue Chen, Yiming Fang, Bo Chen, Junxin College of Medicine and Biological Information Engineering Northeastern University Shenyang110167 China School of Software Dalian University of Technology Dalian116620 China

ISBN: (纸本)9783031651250

With the dramatic progress of smart sensing and wearable device, continuous and real-time acquisition of electrocardiograph (ECG) tends to be realized in a convenient way. Data mining of ECG signals has therefore been extensively researched, among which ECG classification is a hot topic. This paper presents a fused deep learning algorithm for ECG classification. It takes advantages of the combined convolutional and recurrent neural network for ECG classification, and the weight allocation capability of attention mechanism. The input ECG signals are firstly segmented and normalized, and then fed into the combined VGG and LSTM network for feature extraction and classification. An attention mechanism (SE block) is embedded into the core network for increasing the weight of important features. Two databases from different sources and devices are employed for performance validation, and the results well demonstrate the effectiveness and robustness of the proposed algorithm for classifying ECG signals obtained from wearable ECG devices and professional medical equipment. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Recurrent neural networks

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Event-enhanced synthetic aperture imaging

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Science China(information Sciences) 2025年第3期68卷 388-390页

作者： Siqi LI Shaoyi DU Jun-Hai YONG Yue GAO Beijing National Research Center for Information Science and Technology School of SoftwareTsinghua University Institute for Brain and Cognitive Sciences Beijing Laboratory of Brain and Cognitive IntelligenceTsinghua University National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual Information and ApplicationsInstitute of Artificial Intelligence and Robotics Xi'an Jiaotong University

Synthetic aperture imaging(SAI) methods aim to see through dense occlusions and reconstruct the target scene behind occlusions. Traditional frame-based SAI methods,e.g., DeOccNet [1], take the occluded light field ima...

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CapsiScan: Autonomous Robotic System for Monitoring and Managing Greenhouse-Based Capsicum Farms 5

CapsiScan: Autonomous Robotic System for Monitoring and Mana...

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5th International Conference on Advancements in Computing, ICAC 2023

作者： Jayakody, E.R.T. Rabel, W.T.T. Estrop, R.D.V. Herath, K.G.L.P. Harshanath, S.M.B. Abeygunawardhana, Pradeep K. W. Sri Lanka Institute Information Technology Dept. of Computer Systems Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Dept. of Software Engineering Colombo Sri Lanka

ISBN: (纸本)9798350358131

The automation of processes in greenhouses provides a significant advantage to the agricultural sector. Due to the rapid growth of the population, increasing demand for food and labor shortage make the autonomous monitoring and management of agricultural work more important. Capsicum is a largely consumed vegetable in South Asia, which can be efficiently grown in greenhouses. Although there are many capsicum farms, they lack quality and efficient production to match the increasing demand. This paper proposes a robotic system for use in capsicum greenhouses that can navigate and monitor the plants to identify diseases, track the yield, and take remediation actions. The robot navigates to each plant in the greenhouse autonomously by using the SLAM approach with the use of laser range sensor data. The 4 DoF robotic arm of the robot has a camera and a sprayer attached to its end to investigate plants and spray remedies to diseased plants. The robotic arm moves around the plant to capture the images to detect deceases and count the pods to estimate the yield. The sprayer of the robot sprays remedies precisely to targeted plants to control pests and diseases. The system was successfully implemented and tested with the proposed functions. © 2023 IEEE.

关键词： Greenhouses

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Blended teaching questionnaire analysis based on multi-platform integration of swarm intelligence 24

Blended teaching questionnaire analysis based on multi-platf...

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2024 International Symposium on Artificial Intelligence for Education, ISAIE 2024

作者： Xia, Xiangli Daud, Siti Norbaya Binti Built Environment &Information Technology SEGi University Kota Damansara Malaysia Software Engineering Chongqing Finance and Economics College Chongqing Banan China

ISBN: (纸本)9798400707100

This study aims to analyze students' learning participation in the blended teaching model based on swarm intelligence and multi-platform integration. Through a questionnaire survey, data from 666 college students were collected and analyzed using the SPSSAU software for descriptive statistical analysis, reliability and validity testing, correlation analysis, and regression analysis. The study found that students have a high acceptance of the blended teaching model, but their overall enthusiasm for learning is at a medium level. Gender has no significant impact on online learning participation, but there is a significant difference between senior and junior students. Learning resources are the most influential factor on students' online learning participation, while the influence of peer participation is minimal. The research results indicate that constructing a learning environment based on swarm intelligence and utilizing multi-platform integration can enhance teaching quality and student learning experience, promoting educational equity and accessibility. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Federated learning

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Global Path Planning Algorithm for Mobile Robots: A Review

Journal of Network Intelligence

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Journal of Network Intelligence 2024年第2期9卷 643-657页

作者： Yu, Jie Nguyen, Toan Tan Dao, Thi-Kien Nguyen, Trong-The Fujian Key Laboratory of Automotive Electronics and Electric Drive Fujian University of Technology Fuzhou35118 China Shool of Mechanical and Automotive Engineering Fujian University of Technology Fuzhou35118 China Faculty of Software Engineering University of Information Technology Ho Chi Minh City700000 Viet Nam Vietnam National University Ho Chi Minh City700000 Viet Nam University of Information Technology Ho Chi Minh City700000 Viet Nam

Global path planning is a fundamental task for mobile robots operating in dynamic environments. It involves finding an optimal path from a start to a goal location while avoiding obstacles and considering various constraints. Over the years, numerous global path planning algorithms have been developed to address this challenge. This paper provides a comprehensive review of modern global path planning algorithms for mobile robots. We categorize these algorithms based on their underlying principles, advantages, disadvantages, applications, and the year of their introduction. By analyzing and comparing these algorithms, we aim to provide researchers and practitioners with an overview of the state-of-the-art in global path planning and highlight the strengths and limitations of each approach. © 2024, J. Network Intell. All rights reserved.

关键词： Mobile robots

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Using Blockchain to Overcome the Issues in Land Registry Management: A Systematic Review 1

Using Blockchain to Overcome the Issues in Land Registry Man...

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1st International Conference in Advanced Innovation on Smart City, ICAISC 2023

作者： Riaz, Ayesha Ikram, Muhammad Jawad Asadullah, Najmussaba University of Engineering and Technology Department of Computer Software Engineering Mardan Pakistan Jeddah International College Department of Computer Science and Information Technology Jeddah Saudi Arabia

ISBN: (纸本)9781665472753

A Blockchain network contains a distributed ledger that is used to store a secure and permanent record of transactions among multiple parties. As the registries of land records are historically stored in the form of paper documentation where, there might arise the issue of losing, destroying, and modifying needed documents. This land registration process is complicated and time-consuming and required a lot of effort to transfer ownership of the land registry or change any information. For this purpose, various contributions have been made by different researchers to overcome the problem of the classical land registration process by using blockchain technology. In this survey, we shed light on some advantages (reduce time and effort, security, permanency, etc.) of blockchain to identify some early problems in the paper-based land registration process. © 2023 IEEE.

关键词： Blockchain

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