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检索条件"任意字段=2nd International Conference on Computer Science and Software Engineering, CSASE 2022"

共 8419 条记录，以下是11-20 订阅

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software Development Effort Estimation Techniques Using Long Short Term Memory 2

Software Development Effort Estimation Techniques Using Long...

引用

2nd international conference on computer science and software engineering (csase)

作者： Ahmad, Farah B. Ibrahim, Laheeb M. Univ Mosul Coll Comp Sci & Math Software Engn Dept Mosul Iraq

ISBN: (纸本)9781665426329

The software Effort Estimation (SEE) process is used to predict the effort involved in developing a software project inaccuracy. This process permeates the development stages of the software project. Although there are many models for estimating the effort, we will do our best to follow the best model for estimating the effort. The main objective of this research is to apply the Long Short-Term Memory (LSTM) algorithm and discover its accuracy in estimating the software effort. Then, compare the results with other models taken from previous work and find the best one among the models. The LSTM algorithm has been used with two data sets: China, which contains 499 projects, and Kitchenham, 145 projects. The metrics adopted to measure the accuracy of the models are Root Mean Squared Error (RMSE), respectively, Mean Absolute Error (MAE), and R_Squared. The results of RMSE, MAE, and R_Squared are 0.016, 0.019, and 0.972, respectively, in the china dataset. At the same time, the RMSE, MAE, and R_Squared results are also 0.017, 0.058, and 0.896, respectively, in the Kitchenham dataset. Therefore, the experiments' results showed the LSTM algorithm's superiority over the other algorithms in both data sets.

关键词： software Effort Estimation (SEE) Long Short-Term Memory (LSTM) Random Forest (RF) Machine Learning (ML) GENERAL LINEAR MODEL (GLM) Analogy Based Estimation (ABE)

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Improved Extended Space Index Modulation 2

Improved Extended Space Index Modulation

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2nd IEEE international conference on Sensors, Electronics and computer engineering, ICSECE 2024

作者： Chen, Zongren Guangdong Polytechnic of Science and Technology Zhuhai China

ISBN: (纸本)9798350373646

In this design scheme, in order to improve the transmit rate and the reliability of the wireless communication links, an improved extended space index modulation (IESIM) scheme is proposed by designing the spatial constellations. Firstly, to transmit more additional information, all of transmit antennas are partitioned into two groups, each of which is used for transmitting one modified ESIM vector. Secondly, based on the design of the ESIM, the spatial vectors with two active transmit antennas are considered for the modified ESIM vectors. Furthermore, the squared minimum Euclidean distances are provided and compared with the existing classic index modulation schemes, and the bit error probability is obtained. Finally, the comparisons of the bit error rate performances are provided by simulation results with the maximum likelihood (ML) detector using MATLAB software. © 2024 IEEE.

关键词： Vectors

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Exploration of software Field Engineer Training Based on AI+Capability Model 24

Exploration of Software Field Engineer Training Based on AI+...

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2nd international conference on Advances in Artificial Intelligence and Applications, AAIA 2024

作者： Zhou, Junjie Wu, Qian School of Information Wuhan Software Engineering Vocational College Wuhan Open University Hubei Wuhan China School of Computer Science Wuhan University Hubei Wuhan China Hubei Engineering Research Center for Intelligent Detection and Identification of Complex Parts Wuhan China

ISBN: (纸本)9798400712883

With the rapid development of artificial intelligence technology, its application in the field of education and teaching is becoming increasingly widespread, bringing revolutionary changes to traditional education models. To cultivate high-quality software vocational skills talents, a digital management platform based on AI+capability model is constructed to explore the innovative application of artificial intelligence in education and teaching, realizing intelligent auxiliary learning functions such as personalized resource recommendation, student growth monitoring, and achievement label portrait. At the same time, a series of intelligent teaching tools such as"AI+Code Generation, AI+Inspection Assistant, AI+Process Map" will be developed to explore and promote the vertical application of big models in talent cultivation. Through innovative models such as"introducing enterprises into education, cultivating students through real-life situations, AI+empowerment, teaching according to students’ aptitude, trinity, innovative training, strengthening processes, and diverse evaluations", it has been fully applied to the talent training scene of software technology field engineers, and its teaching effectiveness is significant. © 2024 Copyright held by the owner/author(s).

关键词： Students

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A Component-Based Event-Driven Architecture Design for Autonomous Flying software 2

A Component-Based Event-Driven Architecture Design for Auton...

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2nd IEEE international conference on Image Processing and computer Applications, ICIPCA 2024

作者： Wang, Jianhua Zhou, Zhongze Yu, Haixin Li, Jingsong Li, Chuan Wang, Qun Beijing Institute of Control Engineering Software Department Beijing China

ISBN: (纸本)9798350360240

Some satellites are designed to be capable of autonomous flight in order to be intelligent. However, many autonomous flight tasks need to be designed because of the complexity of satellite system, which brings heavy software development workload. A component-based event-driven architecture is proposed in this paper, which exacts software components from the complex system for reuse, and designs basic events for the event-driven architecture. This method simplifies the software development logic and significantly improves the development efficiency of autonomous flight software. © 2024 IEEE.

关键词： software architecture

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Enhanced Visuals through software-Optimized Memory Pipeline 2

Enhanced Visuals through Software-Optimized Memory Pipeline

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2nd international conference on computer, Communication and Control, IC4 2024

作者： Ramesh, P.S. Senthilvadivu, S. Sudha, I. Kumar, T. Rajesh Naveen, V. Nagarajan, B. Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India Saveetha University Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Simats Department of Computer Science and Engineering Tamil Nadu Chennai India Madanapalle Institute of Technology and Science Department of Computer Science and Technology Madanapalle India Kpr Institute of Engineering and Technology Department of Computer Science and Engineering Tamilnadu Coimbatore India

ISBN: (纸本)9798350387933

Image processing algorithms, which supply the image quality, are used by modern mobile devices to capture images. These methods need more RAM to process an image and fix these problems. software pipelines are utilized to reduce memory usage as much as feasible while maintaining the highest level of flexibility and affordability. Our method uses a line-based buffer software pipeline, which improves image quality and runs at a minimal cost. By transferring only the output to the next phase, the algorithm operates on an individual basis. Each step is completed in less time. Using picture enhancement and noise reduction techniques results in increased productivity, reduced memory consumption, and greater image quality. The applied framework demonstrates noise reduction with the PSNR algorithm and yields good results. © 2024 IEEE.

关键词： Image quality

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software Bug Report Detection Methods Based on Machine Learning Techniques 2

Software Bug Report Detection Methods Based on Machine Learn...

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2nd international conference on Advancement in Computation and computer Technologies, InCACCT 2024

作者： Srinivasarao, Ulligaddala Chaganti, Akhil Mannam, Ajay Kotrikeline, Dhanush Katta, Hemanth University Department of Computer Science and Engineering Hyderabad India University Department of Computer Science and Engineering and Hyderabad Hyderabad India

ISBN: (纸本)9798350371314

software defect prediction, an integral facet of software engineering, proactively identifies and resolves potential flaws before they escalate into disruptive issues during production. Insights gleaned from dedicated research serve as solid support for development teams, pinpointing vulnerable areas within their codebase and optimizing resource allocation. This strategic approach significantly reduces overall expenditure on defect rectification. This paper conducts a comprehensive study, meticulously examining various machine learning algorithms in this domain. It intricately dissects deployment, functionality, and the comparative effectiveness of models like Logistic Regression, K-Nearest Neighbours, Naive-Bayes Classifier, Random Forest Classifier, and Recurrent Neural Networks. This thorough exploration enhances understanding of defect prediction methodologies. It provides a detailed roadmap for optimal strategies, reinforcing software quality measures and mitigating the impact of potential coding irregularities on system integrity and reliability. According to the experimental findings, RNN outperformed the baseline methods in terms of accuracy, F1 score, recall, and precision when identifying software bug reports. © 2024 IEEE.

关键词： Nearest neighbor search

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Smart Health Management Application Using IoT and Smart Sensors 2

Smart Health Management Application Using IoT and Smart Sens...

引用

2nd international conference on Disruptive Technologies, ICDT 2024

作者： Arnika Shaikh, Asmat Ara Kumar, Mukesh Sharma, Bhasker Yadav, Dinesh Kumar Aeri, Manisha Sharda School of Engineering and Technology Sharda University Department of Computer Science and Applications Up Greater Noida India Parle Tilak Vidyalaya Association's Institute of Management Department of Marketing Management Maharashtra Mumbai India Graphic Era Hill University Department of Computer Science & Engineering Uttarakhand Dehradun India Hitech Institute of Engineering and Technology Department of Computer Science UP Ghaziabad India Lloyd Institute of Engineering & Technology Department of Mechanical Engineering UP Greater Noida India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350371055

Clever fitness management software using the Internet of Factors (IoT) and smart sensors are a modern answer for powerful and personalized health care. This technology integrates innovative sensors with IoT, creating a community of connected gadgets that can music and screen a character's health and well-being. The utility collects facts in actual time, which are then analyzed and processed to provide valuable insights and recommendations for stepped-forward fitness management. The software uses diverse clever sensors, including health trackers, blood strain monitors, and glucose video display units, to constantly display the consumer's vital signs, symptoms, and physical activities. This record is then transmitted to the cloud for garage and analysis. © 2024 IEEE.

关键词： Garage Health care Management Sumptoms Transmitted

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engineering Challenges for AI-Supported computer Vision in Small Uncrewed Aerial Systems 2

Engineering Challenges for AI-Supported Computer Vision in S...

引用

IEEE/ACM 2nd international conference on AI engineering - software engineering for AI (CAIN)

作者： Chowdhury, Muhammed Tawfiq Cleland-Huang, Jane Univ Notre Dame Dept Comp Sci & Engn Notre Dame IN 46556 USA

ISBN: (纸本)9798350301137

computer Vision (CV) is used in a broad range of Cyber-Physical Systems such as surgical and factory floor robots and autonomous vehicles including small Unmanned Aerial Systems (sUAS). It enables machines to perceive the world by detecting and classifying objects of interest, reconstructing 3D scenes, estimating motion, and maneuvering around objects. CV algorithms are developed using diverse machine learning and deep learning frameworks, which are often deployed on limited resource edge devices. As sUAS rely upon an accurate and timely perception of their environment to perform critical tasks, problems related to CV can create hazardous conditions leading to crashes or mission failure. In this paper, we perform a systematic literature review (SLR) of CV-related challenges associated with CV, hardware, and software engineering. We then group the reported challenges into five categories and fourteen sub-challenges and present existing solutions. As current literature focuses primarily on CV and hardware challenges, we close by discussing implications for software engineering, drawing examples from a CV-enhanced multi-sUAS system.

关键词： Small Uncrewed Aerial Systems computer Vision Artificial Intelligence

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Comparative Analysis of Large Language Models in Solidity Smart Contract Vulnerability Detection: Review 2

Comparative Analysis of Large Language Models in Solidity Sm...

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2nd international conference on Advanced Innovations in Smart Cities, ICAISC 2025

作者： Almaghthawi, Amjad Yafooz, Wael M.S. College of Computer Science and Engineering Taibah University Computer Science Department Madinah Saudi Arabia

ISBN: (纸本)9798331506995

Blockchain (BC) technology and Artificial Intelligence (AI) are promising areas with potential for powerful, secure, and decentralized applications in various sectors. Also, LLMs, are essential advanced machine learning frameworks, which are now used in various applications, including customer service, chatbots, code generation, and language translation. In terms of software development, LLMs are being investigated as a potential way to create smart contracts, focusing on their ability to emulate human programming techniques. For that purpose, this study reviews the capabilities and limitations of Large Language Models (LLMs) like GPT-3.5, PaLM2, and Code Llama in detecting vulnerabilities in Solidity smart contract code. © 2025 IEEE.

关键词： Report generators

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Enhancing Cybersecurity through Advanced Keylogging Techniques 2

Enhancing Cybersecurity through Advanced Keylogging Techniqu...

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2nd IEEE international conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： Sanjay, K. Ratheesh, J.K. Johin, R.R. Krishnamoorthy, A. Vellore Institute of Technology Department of Computer Science Engineering Tamil Nadu India

ISBN: (纸本)9798350368109

As the viruses are increasing efficiently, our project aims to develop a keylogger software. The purpose of this software is to continuously monitor and assess the activities of employees, and to address security concerns that may arise for both children and professionals who can encounter and install unwanted software. Using the Java programming language, keylogger is crafted for specialized testing purposes within this project. This software is a solution for monitoring the activities of employees and children. This program is tested in a controlled environment to attain its efficiency. The outcomes suggest that the software functions effectively, indicating the areas for potential enhancement in future research endeavors. © 2024 IEEE.

关键词： Cyber attacks

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