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检索条件"任意字段=Proceedings of the 9th Knowledge-Based Software Engineering Conference"

共 20290 条记录，以下是461-470 订阅

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Raspberry pi based Automated Reminder Pill Box for Elderly People 9

Raspberry pi Based Automated Reminder Pill Box for Elderly P...

引用

9th International conference on Communication and Electronics Systems, ICCES 2024

作者： Padma Priya, K. Nagarajan, R. Saveetha Engineering college Department of Electronics and Communication Engineering TamilNadu Chennai India

ISBN: (数字)9798350377972

ISBN: (纸本)9798350377972

this paper presents a comprehensive smart medication reminder system designed to address medication adherence challenges among elderly patients with chronic illnesses. the proposed system employs a Raspberry Pi 3B+ as the central controller, integrating infrared (IR) sensors for real-time tracking, a real-time clock (RTC) for precise scheduling, and a GSM module for caregiver notifications. the system uses visual (LEDs) and audio (buzzers) alerts to remind patients to take their medication, while real-time updates keep caregivers informed about adherence. this ensures that patients follow their medication regimen, reducing health risks and enabling remote monitoring by caregivers. the design is scalable and cost-effective, making it suitable for diverse healthcare applications. Future work includes integrating wearable health sensors and machine learning algorithms for personalized reminders, further enhancing medication management for the elderly. © 2024 IEEE.

关键词： Clocks

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Vulnerability Detection based on Pre-trained Code Language Model and Convolutional Neural Network 36

Vulnerability Detection Based on Pre-trained Code Language M...

引用

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

作者： Liao, Tingfeng Lu, Lu Liang, Zhihong Suo, Siliang School of Computer Science and Engineering South China University of Technology Guangzhou China Pazhou Laboratory Guangzhou China Pengcheng Laboratory Shenzhen China Electric Power Research Institute CSG Guangzhou China Guangdong Provincial Key Laboratory of Power System Network Security Guangzhou China

ISBN: (纸本)1891706594

software vulnerabilities damage the reliability of software systems. Recently, many methods based on deep learning have been proposed for vulnerability detection by learning features from code sequences or various property graphs. However, sequence-based methods frequently fail to consider the structural information of the code, whereas graph-based methods often encounter difficulties in capturing long-distance contextual semantic information. To overcome these limitations, we propose PTCN, a novel vulnerability detection method that integrates Pre-Trained code language model and Convolutional Neural Network (CNN). First, the code tokens sequence and the propagation chains are constructed from the source code in preparation for the subsequent feature extraction. Next, GraphCodeBERT, a graph-based pre-trained code language model, is introduced as a means of learning both the semantic and structural information contained in the code tokens sequence and the propagation chains. then, a CNN architecture is designed to effectively extract the crucial vulnerability features from the hidden states of the last Transformer layer of GraphCodeBERT for vulnerability detection. the experiments on the public benchmark dataset REVEAL indicate that PTCN outperforms the state-of-the-art methods with respect to the Accuracy and F1-score metrics by 3.41%-15.80% and 22.68%-104.27%, respectively. © 2024 knowledge Systems Institute Graduate School. All rights reserved.

关键词： Convolutional neural networks

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Edge-Assisted Over-the-Air software Updates 9

Edge-Assisted Over-the-Air Software Updates

引用

IEEE 9th International conference on Collaboration and Internet Computing (CIC)

作者： Bhattacharjee, Arpan Mahmood, Hamza Lu, Sidi Ammar, Nejib Ganlath, Akila Shi, Weisong Univ Delaware Newark DE 19716 USA William & Mary Williamsburg VA 23185 USA Toyota InfoTech Lab Toyota Japan

ISBN: (纸本)9798350339123

the imperative transformation of future connected vehicles into intelligent computing platforms necessitates the implementation of software-defined Vehicles (SDVs). SDVs enable the progressive addition and upgrading of automotive applications throughout the vehicle's lifecycle, facilitated by software Over-the-Air (OTA) update technology. However, the exploration of OTA updates for automotive applications is currently very limited. To the best of our knowledge, our work is pioneering in implementing an edge-assisted framework for automotive OTA updates. It meticulously considers the heterogeneity of vehicular software models and vehicle computing units, varied communication distances, and diverse sizes of vehicle clusters. We offer crucial insights based on pertinent evaluation metrics, such as update latency, transmission bandwidth, and successful rate, alongside an in-depth scalability analysis. Our study employs three distinct sizes of fundamental vehicle models: ResNet-18 (46.8 MB), ResNet-50 (102.5 MB), and Faster R-CNN (175.2 MB). these models are employed to evaluate the update performance across eight distance groups ranging from 0 to 21 meters with a 3-meter gap. We also exploit heterogeneous computing platforms to appraise the success rate and execute comprehensive scalability analysis. this novel approach significantly advances the current understanding and implementation of OTA updates in the automotive community.

关键词： software-Defined Vehicle (SDV) Edge Computing software Over-the-Air (OTA) update Autonomous Vehicles and Vehicle Computing

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Permittivity Retrieval based on Fully Connected Neural Networks 9

Permittivity Retrieval Based on Fully Connected Neural Netwo...

引用

9th International conference on Mechanical and Electronics engineering, ICMEE 2023

作者： Li, Xiaofeng Yang, Xiaoqing Tan, Bo School Of Electronic And Information Engineering Xi'an Technological University Xi'an China School Of Electronic And Information Engineering Sichuan University Chengdu China

ISBN: (纸本)9798350307146

In order to accurately and quickly extract the dielectric constant of materials, this paper designs CST software to simulate the scattering parameters corresponding to different dielectric constants under the frequency of 1 - 18GHz based on the traditional transmission/reflection method. these scattering parameters are used as the data source of deep learning, and the amplitude and phase of S11 and S21 are used as the input. Permittivity is used as output to construct a fully connected neural network model. Compared with linear regression, Knearest neighbor regression and random forest algorithm, the final experimental results show that the fully connected neural network inversion has certain correctness and effectiveness, and the inversion effect is the best. © 2023 IEEE.

关键词： Permittivity

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Implementation of Data Analysis for Affordable Smart Farming based on IoT and Machine Learning 9

Implementation of Data Analysis for Affordable Smart Farming...

引用

9th International conference on Communication and Electronics Systems, ICCES 2024

作者： Rohini, M. Amarnath, K. Lokesh, B. Saveetha Engineering College Department of Electronics and Communication Engineering Chennai India

the significance of agriculture in any country cannot be overlooked. Actually, about 70% of the population practices agriculture and this fills one third of the country9;s capital. Nonetheless, agriculture related ... 详细信息

ISBN: (数字)9798350377972

ISBN: (纸本)9798350377972

the significance of agriculture in any country cannot be overlooked. Actually, about 70% of the population practices agriculture and this fills one third of the country's capital. Nonetheless, agriculture related challenges have always affected the country's economic growth. the answer to the problems posed above is the adoption of modern farming techniques. this project is concerned with the monitoring of temperature and moisture levels in the fields using appropriate sensors also known as smart agriculture. this way these techniques are incorporated into the agricultural system for crop yielding without excessive spraying with chemical insecticides, less cost of farming, more efficient water used, better control of land and crops. the communication technology makes it possible to monitor the field in question and to take corrective measures whenever necessary. Moreover, this project investigates how image processing systems and different types of sensors can be used for further enhancement of crop growth and yield. © 2024 IEEE.

关键词： Smart agriculture

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Optimal Operation of Electric-hydrogen Integrated Energy System Considering Carbon-trading and Demand Response 9

Optimal Operation of Electric-hydrogen Integrated Energy Sys...

引用

9th Asia conference on Power and Electrical engineering, ACPEE 2024

作者： Li, Ruiqi Wu, Qiong Ren, Hongbo Shi, Shanshan Shanghai University of Electric Power College of Energy and Mechanical Engineering Shanghai China State Grid Shanghai Electric Power Research Institute Grid Technology Centre Shanghai China

ISBN: (纸本)9798350309638

To achieve low-carbon and environmentally friendly operation of the integrated energy system while considering the interests of both operators and users, this paper proposes a master-slave game optimization model considering China Certified Emission Reductions (CCERs) and supply and demand side responses. First, a master-slave game optimization model is constructed with the operator as the leader and the load aggregator as the follower, and an objective function with the goal of maximizing the operator's return is established based on the consideration of the carbon trading mechanism and CCERs. Second, the load aggregator conducts trading based on the energy price set by the operator, exploits the cluster dispatchability and demand response potential of the customer-side EV, determines its operation strategy as an energy storage unit, and commissions the aggregator to sell the CCERs generated from EV charging to minimize the energy costs of the load aggregator. Finally, the comparison of the results of multiple scenarios illustrates the rationality of the model, which can effectively reduce carbon emissions, increase the operator's revenue, and reduce the user's energy cost. © 2024 IEEE.

关键词： Carbon

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LLM-based Chatbots for Mining software Repositories: Challenges and Opportunities 24

LLM-Based Chatbots for Mining Software Repositories: Challen...

引用

28th International conference on Evaluation and Assessment in software engineering (EASE)

作者： Abedu, Samuel Abdellatif, Ahmad Shihab, Emad Concordia Univ Montreal PQ Canada Univ Calgary Calgary AB Canada

ISBN: (纸本)9798400717017

software repositories have a plethora of information about software development, encompassing details such as code contributions, bug reports and code reviews. this rich source of data can be harnessed to enhance not only software quality and development velocity but also to gain insights into team collaboration and inform strategic decision-making throughout the software development lifecycle. Previous studies show that many stakeholders cannot benefit from the project information due to the technical knowledge and expertise required to extract the project data. To lower the barrier to entry by automating the process of extracting and analyzing repository data, we explored the potential of using an LLM to develop a chatbot for answering questions related to software repositories. We evaluated the chatbot on 150 software repository-related questions. We found that the chatbot correctly answered one question. this result prompted us to shift our focus to investigate the challenges in adopting LLMs for the out-of-thebox development of software repository chatbots. We identified five main challenges related to retrieving data, structuring the data, and generating the answer to the user's query. Among these challenges, the most frequent (83.3%) is the inaccurate retrieval of data to answer questions. In this paper, we share our experience and challenges in developing an LLM-based chatbot to answer software repository-related questions within the SE community. We also provide recommendations on mitigating these challenges. Our findings will serve as a foundation to drive future research aimed at enhancing LLMs for adoption in extracting useful information from software repositories, fostering advancements in natural language understanding, data retrieval, and response generation within the context of software repository-related questions and analytics.

关键词： software Chatbots Large Language Model Conversational Development Assistant

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A Transient Angle Stability Assessment Method for DFIG Grid-Connected Systems based on Heterogeneous Graph Attention Networks 9

A Transient Angle Stability Assessment Method for DFIG Grid-...

引用

9th Asia conference on Power and Electrical engineering, ACPEE 2024

作者： Li, Xianzhen Qin, Wenping Zhu, Zhilong Lu, Ruipeng Qin, Penghui Cui, Junjie Taiyuan University of Technology College of Electrical and Power Engineering Taiyuan China

ISBN: (纸本)9798350309638

this paper presents a novel approach to assessing transient stability by utilizing a heterogeneous graph attention network (HAN). this method is proposed in response to the limitations of existing deep learning-based methods which fail to consider the intricate dynamic responses of power electronic equipment control on the transient angle stability of power systems with large-scale new energy. the proposed approach involves joint simulation modeling using the transient security assessment tool (TSAT) and real-time digital simulation system (RTDS) to divide the power grid into electromagnetic transient time scale and electromechanical transient time scale, obtaining measurement data for each generator node and variables of doubly fed induction generator (DFIG) inverter control, and establishing the generator graph topology. then, the HAN model is applied to perform weighted aggregation of nodes, constructing the mapping relationship between the original input features and transient angle stability states. Finally, the proposed method is validated using a modified IEEE 39-bus system to demonstrate its effectiveness in transient angle stability assessment accuracy, adaptability to topological changes, and overall interpretability. © 2024 IEEE.

关键词： Deep learning

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Autonomy and Turnover: A Survey Applied to Distributed software Teams 15

Autonomy and Turnover: A Survey Applied to Distributed Softw...

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15th International conference on knowledge Management and Information Systems, KMIS 2023 as part of the 15th International Joint conference on knowledge Discovery, knowledge engineering and knowledge Management, IC3K 2023

作者： Amorim, Luis de Farias, Ivaldir Marinho, Marcelo PE Recife52071-000 Brazil PE Garanhuns Brazil

ISBN: (纸本)9789897586712

Distributed teams have gained prominence in software companies. However, studies indicate that Distributed software Development (DSD) companies often face challenges related to high developer turnover. Conversely, other research suggests that autonomy and its associated factors can mitigate or prevent such turnover. this study investigates the relationship between autonomy and turnover within DSD teams. To accomplish this, we conducted a survey based on previous Systematic Literature Review (SLR) research involving 181 software engineers worldwide. Our findings shed light on the key autonomy factors that impact turnover in DSD projects, including recognition, communication, collaboration, trust, and task balance. By offering a comprehensive understanding of these autonomy factors, our study provides software companies and organizations with valuable insights for addressing the issue of turnover in DSD projects. Copyright © 2023 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： software design

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Compensation Analysis Dynamic Voltage Restorer based Jellyfish Search Optimizer PI Control for Voltage Sag mitigation 9

Compensation Analysis Dynamic Voltage Restorer Based Jellyfi...

引用

9th Asia conference on Power and Electrical engineering, ACPEE 2024

作者： Bacha, Umair Tao, Jinsong Ali, Samejo Aftab Ahmad, Shakeel Haider, Hussain Ali, Zeenab Wuhan University Electrical Engineering and Automation wuhan China

ISBN: (纸本)9798350309638

In advancing science and technology, the widespread use of high-tech equipment, particularly those with microprocessors at their core component, has intensified the demand for high highly stable power quality. this demand is further intensified by the integration of numerous distributed energy sources into the grid, resulting in serious power quality issues, with voltage sag emerging as a particularly most severe concern. A proposed approach based on a distribution system is investigated to examine the actual effect of voltage sag. To compensate voltage sag, dynamic voltage restorer (DVR) uses a control system that works efficiently. An integral-proportional (PI) control is one of the most widely used control methods in DVR, owing to its simplicity and high-speed of design. To improve accuracy in nonlinear systems, PI control must be regulated. this paper proposes a PI Tuned Jellyfish Search (JFS) Optimizer to control a DVR for mitigating voltage sag issue. As a result, JFS has a high level of effectiveness and speed in voltage compensation. the MATLAB/Simulink simulation results are presented to validate the feasibility and significance of the presented controller in enhancing the voltage output of the load. © 2024 IEEE.

关键词： Power quality

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