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检索条件"任意字段=18th International Conference on Software Engineering and Knowledge Engineering"

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An Explainable Automated Model for Measuring software Engineer Contribution 24

An Explainable Automated Model for Measuring Software Engine...

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39th ACM/IEEE international conference on Automated software engineering (ASE)

作者： Li, Yue Zhang, He Jin, Yuzhe Ren, Zhong Dong, Liming Lyu, Jun Yang, Lanxin Lo, David Shao, Dong Nanjing Univ State Key Lab Novel Software Technol Nanjing Peoples R China CSIRO Data61 Canberra ACT Australia Singapore Management Univ Singapore Singapore

ISBN: (数字)9798400712487

ISBN: (纸本)9798400712487

software engineers play an important role throughout the software development life-cycle, particularly in industry emphasizing quality assurance and timely delivery. Contribution measurement provides proper incentives to software engineers that motivate them to continuously improve the quality and efficiency of their work. However, existing research tends to ignore contribution measurement for software engineers in practice, relying heavily on peer review and lacking objectivity and transparency. Specifically, these studies still have two weaknesses. First, a few studies explore which metrics can be useful for contribution measurement in practice. Second, managers measure the contribution of software engineers based on their experience and lack of explainable automated tools to assist them. To this end, we conduct mixed-method studies to investigate contribution measurement in the enterprise, and then propose an explainable model for measuring the contribution of software engineers. First, we collect and synthesize 16 metrics for contribution measurement by interviewing 18 industrial practitioners. Second, we propose an explainable model, called MEMENTO, integrating Multi-dimEnsional MEtrics for measuriNg conTributiOn. We conduct an industrial case study with a global enterprise to evaluate and refine MEMENTO. Finally, we administer a survey to industrial practitioners to verify whether the explainable model is useful for contribution analysis, which resulted in 67 valid responses. MEMENTO is used by the enterprise to measure the contribution of 5,174 employees. A total of 100 employees are identified as low contributors by MEMENTO, and the five reasons for their low contribution are determined based on the results of our explainable model. the results indicate that MEMENTO can effectively measure the contribution of software engineers, which provides a practical reference for researchers interested in contribution measurement.

关键词： Contribution measurement mining software repository quantitative measurement

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AI-Driven Personalization of E-therapy Interventions for Anxiety, Stress, and Depression 18

AI-Driven Personalization of E-Therapy Interventions for Anx...

引用

18th international conference on Open Source Systems and Technologies, ICOSST 2024

作者： Ramzan, Hafiz Arslan Abdulah, Fatima Ahmad, Muddaber Ramzan, Sadia Ashraf, Munazza School of Electrical Engineering and Computer Science National University of Sciences and Technology Islamabad Pakistan School of Mechanical and Manufacturing Engineering National University of Sciences and Technology Islamabad Pakistan National University of Computer and Emerging Sciences Department of Computer Science Chiniot Faisalabad Pakistan GIFT University Department of Humanities and Social Sciences Gujranwala Pakistan

ISBN: (纸本)9798331508692

this study explores the use of artificial intelligence (AI) to personalize e-therapy interventions for anxiety, stress, and depression. Leveraging machine learning models, including K-Nearest Neighbors (KNN), Support Vector Machines (SVM), and Decision Trees, we analyze a dataset of depression, anxiety, and stress scales responses to develop predictive models that tailor therapeutic interventions. the accuracy and efficacy of proposed models vary, indicating that AI has the potential to improve the level of personalization of mental health therapies. the results indicate that AI-driven techniques can significantly improve the effectiveness and efficiency of e-therapy platforms. © 2024 IEEE.

关键词： Adversarial machine learning

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Integrating Model-Based Systems engineering for Enhanced Digital Forensics in Crash Investigations 18

Integrating Model-Based Systems Engineering for Enhanced Dig...

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18th Annual IEEE international Systems conference (SysCon)

作者： Rayno, Mars Daily, Jeremy Colorado State Univ Syst Engn Ft Collins CO 80523 USA

ISBN: (纸本)9798350358810;9798350358803

Traffic crashes have been an epidemic in modern life, sometimes with tragic consequences. Traffic safety initiatives have included the use of vehicle event data recorders (EDRs) to help investigators understand what happened before and during a crash event. this paper presents a model-based systems engineering (MBSE) approach aimed at augmenting the digital forensics associated with EDRs in traffic crash investigations. the goal of the modeling effort is to develop system and subsystem requirements to address the needs of the crash investigator and the courts, each as stakeholders. the MBSE approach utilized the MagicGrid V2 method to work through the problem definition with the four pillars of MBSE: requirements, structure, behavior, and parametrics. the modeling effort shows some functionality is driven by compliance with existing and upcoming regulations. Also, data attributed to the identity of the driver may be present, which means privacy concerns exist. Analysis of these requirements reveals potential conflict, which means EDR designers may have to pick one requirement or another to satisfy. the modeling effort also raises the need for privacy and security controls with a compartmentalized architecture to balance the needs for the availability of forensic data with the need to protect user information and manufacturer intellectual property. the application of the MagicGrid modeling methodology sets up the detailed design efforts for a future event data recorder. Forensic models were created for use in developing forensic systems requirements. these models follow the approach an investigator would follow in obtaining data from a crash event, while also highlighting what data is available versus what data could be considered as personally identifiable information (PII) which could be a privacy concern.

关键词： event data recorders model-based systems engineering digital forensics traffic crash reconstruction investigation magicgrid

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software Defect Prediction via Code Grayscale Pixel Visualization with Fusion Attention 36

Software Defect Prediction via Code Grayscale Pixel Visualiz...

引用

36th international conference on software engineering and knowledge engineering, SEKE 2024

作者： Qiu, Shaojian Wang, Shaosheng Rong, Wei Liao, Lili Lin, Yishen College of Software Engineering South China Agricultural University China School of Computer Science and Engineering South China University of Technology China Guangdong Tobacco Meizhou Limited Company China

ISBN: (纸本)1891706594

software defect prediction helps quality assurance teams find defects in software, thereby enhancing the reliability of the systems. In existing code-visualization-based defect prediction methods, challenges arise from mixing code information and the potential omission of critical defect features. To enhance the completeness of code features, this paper proposes a defect prediction model based on code grayscale pixel visualization with a fusion attention mechanism (Gpv2DP). Gpv2DP converts code into grayscale images and reshapes the images to a standard size, effectively alleviating the information loss problem caused by element mixing and image cropping. Furthermore, it constructs a code feature extracting network that simultaneously integrates the channel, spatial and 3D attention. We conduct empirical experiments on ten open-source Java projects from the PROMISE repository. the results show that the F-measure and AUC metrics of Gpv2DP outperform related defect prediction methods. © 2024 knowledge Systems Institute Graduate School. All rights reserved.

关键词： software reliability

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White Spot Syndrome Detection in Shrimp using Neural Network Model 18

White Spot Syndrome Detection in Shrimp using Neural Network...

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18th INDIAcom;11th international conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Vembarasi, K. thotakura, Vishnu Priya Senthilkumar, S. Ramachandran, L. Lakshmi Praba, V. Vetriselvi, S. Chinnadurai, M. E.G.S. Pillay Engineering College Department of Electronics and Communication Engineering Nagapattinam India Srk Institute of Technology Department of Electronics and Communication Engineering Vijayawada India E.G.S. Pillay Engineering College Department of Computer Science and Engineering Nagapattinam India

ISBN: (纸本)9789380544519

White Spot Syndrome Virus (WSSV) epidemics have seriously harmed penaeid shrimp aquaculture all over the world. there remains an absence of information concerning these complicated viral-host interactions, despite significant attempts to describe the virus, the circumstances that cause infection, and the processes of infection. this understanding is required to develop reliable and efficient treatment strategies for WSSV. Mechanisms for segmenting and categorizing images offer a method for extracting features from images based on their objects. those certain objects are produced using an image segmentation technique in which segments are formed by grouping together pixels with similar spectral properties that are close to one another. the area of interest on any underlying image is protected by image segmentation, a crucial step before actual analysis is recommended in any image processing methodology. In fact, the effectiveness of the segmentation algorithm used will have a big impact on how accurate any image processing performs. this study proposes a typical segmentation technique for segmenting shrimp variability by using essential Canny-GLCM (Gray Level Co-occurrence Matrix) features with a simple Artificial Neural Network (ANN) model. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Artificial Neural Network segmentation algorithm shrimp White spot syndrome virus

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Double-Differential Direct-Sequence Spread Spectrum Receiver in Underwater Acoustic Channel with Rapidly Time-Varying Doppler Shifts 24

Double-Differential Direct-Sequence Spread Spectrum Receiver...

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18th ACM international conference on Underwater Networks and Systems, WUWNET 2024

作者： Deng, Jinhao Wu, Jie Cui, Hongyu Harbin Engineering University China

ISBN: (纸本)9798400711602

the Doppler effect is a significant factor that limits the performance of direct-sequence spread spectrum (DSSS) communications. Although constant Doppler can be mitigated through double differential modulation, time-varying Doppler still severely impacts communication performance. the rapid variation in Doppler frequency shift leads to performance degradation in conventional receivers. In this paper, we have enhanced the Doppler estimation algorithm within the conventional receiver, achieving high-precision Doppler estimation results by utilizing the amplitude and phase information from autocorrelation. Data from the lake test demonstrate that the proposed receiver can effectively estimate the time-varying Doppler of the signal and has resulted in improved communication performance. © 2024 Copyright held by the owner/author(s).

关键词： Underwater acoustics

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Managing Traceability for software Life Cycle Processes 18th

Managing Traceability for Software Life Cycle Processes

引用

18th international conference on theoretical Aspects of software engineering (TASE)

作者： Wen, Hao Wu, Jinzhao Jiang, Jianmin Li, Jianqing Hong, Zhong Chinese Acad Sci Chengdu Inst Comp Applicat Chengdu Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Chengdu Univ Informat Technol Chengdu Peoples R China Fujian Normal Univ Fuzhou Peoples R China

ISBN: (纸本)9783031646256;9783031646263

Various types of software artifacts are produced in the software life cycle processes. Although traceability between different artifacts is beneficial for software development, the actual practice of modeling and maintaining traceability is not always entirely successful. In this paper, we explore how to manage traceability for the software life cycle process, including a new solution for formally constructing and preserving traceability under various management operations. Such a solution allows flexibility and extensibility to define new types of traceability links (dependency relationships). Its traceability information does not pollute the inner relationships of existing artifacts. We first present a formal model called a structure model that is used to describe software systems, and then a traceability concept is formally defined. Based on the structure model, we investigate in theory how to preserve traceability under various management operations. Finally, a prototype tool is developed for supporting our work.

关键词： Traceability Management operation Formal method

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Pinch Detection of Power Window Using Disturbance Observer for Obstacles with Wide Range of Force Deflection Ratios 18

Pinch Detection of Power Window Using Disturbance Observer f...

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18th international conference on Control Automation Robotics and Vision

作者： Tashiro, Tsutomu Osaka Sangyo Univ Dept Mech Engn Transportat 3-1-1 Nakagaito Daito Osaka Japan

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509;9798331518493

this paper proposes a pinch detection method for an automotive power window. Due to a power window system, we can easily rise and lower a window glass only by pressing a switch. However, if the window is rising while there is a finger or an arm between the window frame and the window glass, it might occur a pinching accident. In order to avoid injuries by the accident, an anti-pinch control that detects the pinching and lowers the window glass, is installed in a power window system. In this paper, an anti-pinch control that can detect pinching of the object with both small and large force deflection ratios is proposed. In order to achieve it, the pinch state index is calculated from the motor angular speed and detects pinching when it exceeds the threshold. the main process of calculating the index is realized by a disturbance observer and a non-linear gain. When an object with small force deflection ratio is pinched, the index moves like a pinch force, and when an object with large force deflection ratio is pinched, the index increases faster than a pinch force by the non-linear gain. Performance and effectiveness of the anti-pinch control is evaluated by the experimental data measured on a power window test

关键词： Power measurement Force Glass Switches Disturbance observers Windows Indexes Robots Automotive engineering Accidents

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Bridging the Gap between Academia and Industry in Machine Learning software Defect Prediction: thirteen Considerations 38

Bridging the Gap between Academia and Industry in Machine Le...

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38th IEEE/ACM international conference on Automated software engineering (ASE)

作者： Stradowski, Szymon Madeyski, Lech Nokia Mobile Networks Radio Frequency Wroclaw Poland Wroclaw Univ Sci & Technol Dept Appl Informat Wroclaw Poland

ISBN: (纸本)9798350329964

this experience paper describes thirteen considerations for implementing machine learning software defect prediction (ML SDP) in vivo. Specifically, we provide the following report on the ground of the most important observations and lessons learned gathered during a large-scale research effort and introduction of ML SDP to the system-level testing quality assurance process of one of the leading telecommunication vendors in the world - Nokia. We adhere to a holistic and logical progression based on the principles of the business analysis body of knowledge: from identifying the need and setting requirements, through designing and implementing the solution, to profitability analysis, stakeholder management, and handover. Conversely, for many years, industry adoption has not kept up the pace of academic achievements in the field, despite promising potential to improve quality and decrease the cost of software products for many companies worldwide. therefore, discussed considerations hopefully help researchers and practitioners bridge the gaps between academia and industry.

关键词： machine learning software defect prediction Nokia 5G industry introduction experience paper

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IoT Integrated Intelligent Entry Monitoring System for Covid-19 Detection 18

IoT Integrated Intelligent Entry Monitoring System for Covid...

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18th INDIAcom;11th international conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Prasanna, B. Lakshmi Reddy, M. Pala Prasad Kumar, S. Satheesh Karthik, A. Devaraju, T. Reddy, N. Sreeramula Institute of Aeronautical Engineering Department of Ece Hyderabad India Institute of Aeronautical Engineering Department of Eee Hyderabad India Institute of Aeronautical Engineering Department of It Hyderabad India Department of Eee Tirupati India Annamacharya Institute of Technology and Sciences Department of Eee Rajampet India

ISBN: (纸本)9789380544519

the occurrence of the COVID-19 disease has led to a decline in the number of visitors to public spaces such as Schools, Colleges, parks, libraries, and museums. Despite the Indian Government easing restrictions for public visits to these places in early 2021, people are hesitant to venture out due to the lingering fear associated with the impact of the disease even for today. To overcome this issue a Bilateral Screening Process is proposed for safe visiting procedure. It involves measuring the body temperature of a person using IR temperature sensor and the availability of a face mask will be monitored by Open Computer Vision. If any deviation is detected the system promptly triggers mail alerts to notify relevant people and also prevent access through gate control. With seamless connectivity and centralized management facilitated by IoT integration, the system enables real-time monitoring, analysis, and data processing. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： COVID-19 Face mask detection IoT MLX90614 Pi Camera Raspberry Pi3 Temperature detection

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