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Research and application of Machine Learning in Automatic Program Generation

Chinese Journal of Electronics 2020年第6期29卷 1001-1015页

作者： ZHANG Xiaojiang JIANG Ying Yunnan Key Laboratory of Computer Technology Application Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming University of Science and Technology

With the development of artificial intelligence,machine learning has been applied in more and more *** order to improve the quality and efficiency of software,automatic program generation is becoming a research *** recent years,machine learning has also been gradually applied in automatic program *** trees,language models,and cyclic neural networks have been applied in code generation,code completion and code knowledge *** efficiency of software development has been improved to a certain extent using machine *** at the automatic program generation,this paper analyzes and summarizes the models of machine learning,the modifications involved in the models and the application *** research direction is discussed from the aspects of programmer behavior and automatic program generation of machine learning.

关键词： automatic programming data mining decision trees learning (artificial intelligence) neural nets software engineering programmer behavior cyclic neural networks language models decision trees code knowledge mining code completion code generation automatic program generation machine learning Machine learning Code generation Code completion Code knowledge mining application effect

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Automation of data flow class testing using hybrid evolutionary algorithms

Recent Advances in Computer Science and Communications

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Recent Advances in computer Science and Communications 2021年第1期14卷 317-330页

作者： Jain, Neetu Porwal, Rabins Department of Computer Application Faculty of System Sciences Mewar University Chittorgarh India Department of Information Technology Lal Bahadur Shastri Institute of Management New Delhi India

Background: Software testing is a time consuming and costly process. Recent advances in complexity of software have gained attention among researchers towards the automation of generation of test data. Objective: This paper focuses on the structural testing of object oriented paradigm based software and proposes a hybrid approach to automate the class testing applying heuristic algorithms. Methods: The proposed algorithm performs data flow testing of classes applying all defuses adequacy criteria by automatically generating test cases. A nested 2-step methodology is applied using meta-heuristic genetic algorithm and its two variant (GA-variant1 and Ga-variant2) to produce optimized method sequences. Results: An experiment is performed applying proposed algorithm on six test classes. The results suggest that proposed approach with GA-variant1 is better than other techniques in terms of Average d-u coverage and Average iterations. © 2021 Bentham Science Publishers.

关键词： Genetic algorithms

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Improving Search Engine Results Using AI Methods 3

Improving Search Engine Results Using AI Methods

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Katariya, Jitendra Kumar Geetha, B. Mahajan, Rupali A. Singh, Manpreet Yadav, Rakesh Kumar Vivek, V. Vivekananda Global University Department of Computer Science & Application Jaipur India Prince Shri Venkateshwara Padmavathy Engineering College Department of Science and Humanities Chennai127 India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Computer Science and Engineering Karnataka Bangalore India

ISBN: (纸本)9798350319125

This paper examines how artificial Intelligence (AI) algorithms can be used to improve seek engine consequences. It outlines key terms, demanding situations, and opportunities related to AI -based totally search engine optimization. initial studies shows that AI-based totally tactics display promising ability to increase accuracy and relevancy in search engine consequences. AI strategies such as natural language processing (NLP), system getting to know (ML), and sentiment analysis are explored in element. additionally, the paper compares current answers that rent AI algorithms to conventional search engines and evaluates their performance, scalability, and applicability. ultimately, the paper discusses the destiny outlook of AI in seo and its potential implications for web users, corporations, and seeks engine developers. © 2023 IEEE.

关键词： algorithms developers engine potential strategies

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AEP Mobile application Evaluation of Usability, Performance, and Shneiderman's Recommendations 10

AEP Mobile Application Evaluation of Usability, Performance,...

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10th International Conference on ICT for Smart Society, ICISS 2023

作者： Sasmoko Indrianti, Yasinta Koentjoro, Reinhart Previano Manalu, Sonya Rapinta Hermanus, Davy Ronald Research Interest Group in Educational Technology Bina Nusantara University Faculty of Humanities Primary Teacher Education Department Jakarta Indonesia Universitas Agung Podomoro Entrepreneurship Department Jakarta Indonesia School of Computer Science Bina Nusantara University Mobile Application Technology Jakarta Indonesia Computer Science Department Bandung Indonesia Bina Nusantara University Research Interest Group in Educational Technology Jakarta Indonesia

ISBN: (纸本)9798350339543

This study emphasizes the mobile app design, usability, and performance evaluation of AEP Mobile, a self-assessment mobile application to measure users' entrepreneurial abilities and factors as part of ASEAN Entrepreneurship Profiling (AEP). As the mobile app was designed following the Shneiderman's Eight Golden Rules of Interface Design and (Five) Human Factors of Interactive Software, we would like to evaluate whether potential users would consider the mobile app to be user-friendly according to Shneiderman's recommendations. We evaluated multiple mobile app evaluation metrics and methods and ended up adopting MARS and the original Golden Rules to evaluate our app to Indonesian public as part of the beta testing process. Results collected from Indonesian participants show user's high satisfaction in the user interface, despite having issues especially in app error-handling. © 2023 IEEE.

关键词： application programs

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Understanding the Impact AI has on Data Access Performance and Efficiency 3

Understanding the Impact AI has on Data Access Performance a...

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Rege, Pallavi R. Ahluwalia, Gunveen Kumar, Ritesh Narasimhayya, B.E. Yadav, Surendra Karthikeyan, Kavitha Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Computer Science and Engineering Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Application Jaipur India Prince Shri Venkateshwara Padmavathy Engineering College Department of Civil Engineering Chennai127 India

ISBN: (纸本)9798350319125

AI has come to be more and more outstanding in recent years in records get entry to overall performance and efficiency. As a result, there were big modifications to how facts are processed and accessed. AI has enabled organizations to extra effectively and efficaciously technique facts, ensuing in accelerated operational efficiency and improved customer satisfaction. This paper presents a comprehensive exploration of the effect of AI on records get entry to performance and performance. It examines the usage of AI to streamline statistics processing and get admission to, and discusses the impact it has on consumer revel in and patron satisfaction. additionally, the paper considers the capacity for future innovation and the way facts get admission to overall performance and performance may be further more desirable via AI. The paper concludes with implications for similarly research and improvement. © 2023 IEEE.

关键词： Capacity Implications Satisfaction Similarly

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Usability Evaluation Through Fuzzy AHP-TOPSIS Approach: Security Requirement Perspective

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computers, Materials & Continua 2021年第7期68卷 1203-1218页

作者： Yoosef BAbushark Asif Irshad Khan Fawaz Jaber Alsolami Abdulmohsen Almalawi Md Mottahir Alam Alka Agrawal Rajeev Kumar Raees Ahmad Khan Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical and Computer Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow226025India Department of Computer Application Shri Ramswaroop Memorial UniversityBarabanki225003India

Most of the security strategies today are primarily designed to provide security protection,rather than to solve one of the basic security issues related to adequate software product *** models,frameworks and methodologies have been introduced by the researchers for a secure and sustainable software development life *** it is important to assess the usability of the popular security requirements engineering(SRE)approaches.A significant factor in the management and handling of successful security requirements is the assessment of security requirements engineering method *** assessment will allow changes to the engineering process of security *** consistency of security requirements depends heavily on the usability of security requirements *** SRE approaches are available for use and each approach takes into account several factors of usability but does not cover every element of *** seems to be no realistic implementation of such models because the concept of usability is not *** paper aims at specifying the different taxonomy of usability and design hierarchical usability *** taxonomy takes into account the common quality assessment parameters that combine variables,attributes,and characteristics identified in different approaches used for security requirements *** multiple-criteria decision-making(MCDM)model used in this paper for usability evaluation is called the fuzzy AHP-TOPSIS model which can conveniently be incorporated into the current approach of software *** significant usability criteria are identified and used to evaluate the six different *** strategies are graded as per their expected values of usability.

关键词： Security requirements engineering cyber-security usability fuzzy logic MCDM

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A Hybrid Reinforcement Learning Framework for Optimizing Node Deployment in WSNs 14

A Hybrid Reinforcement Learning Framework for Optimizing Nod...

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14th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2025

作者： Priyadarshi, Rahul Rout, Jayant Kumar Gupta, Akash Kumar Ranjan, Rakesh Verma, Amit Teja, Panduranga Ravi Faculty of Engineering and Technology ITER SOA Bhubaneswar India School of Computer Application KIIT Bhubaneswar India Dept of ECE BIT Mesra Deoghar India School of Computer Science UPES Dehradun India

ISBN: (纸本)9798331531935

Efficient node deployment in Wireless Sensor Networks (WSNs) is critical for maximizing network coverage, enhancing energy efficiency, and prolonging network lifetime. However, achieving optimal node placement is challenging due to the limited energy resources and dynamic environmental conditions in WSNs. This paper presents a novel hybrid approach that combines Reinforcement Learning (RL) with the Differential Evolution (DE) algorithm to optimize node deployment in WSNs. In this method, RL dynamically adapts node positions based on local network states, while DE performs global optimization to refine these placements and improve coverage. Simulation results demonstrate that the proposed RL-DE hybrid approach significantly outperforms traditional deployment methods, standalone RL, and DE in terms of coverage, energy conservation, and network longevity. The results suggest that the RL-DE approach provides an adaptive and robust solution for node deployment in WSNs, with potential applications in real-world sensor network deployments. © 2025 IEEE.

关键词： Energy efficiency

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A Hybrid Reinforcement Learning Framework for Optimizing Node Deployment in WSNs

A Hybrid Reinforcement Learning Framework for Optimizing Nod...

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International Conference on Communication Systems and Network Technologies (CSNT)

作者： Rahul Priyadarshi Jayant Kumar Rout Akash Kumar Gupta Rakesh Ranjan Amit Verma Panduranga Ravi Teja Faculty of Engineering and Technology ITER SOA Bhubaneswar India School of Computer Application KIIT Bhubaneswar India Dept of ECE BIT Mesra Deoghar India School of Computer Science UPES Dehradun India

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

关键词： Wireless sensor networks Adaptive systems Recurrent neural networks Smart cities Simulation Scalability Metaheuristics Reinforcement learning Energy efficiency Real-time systems

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Significance of deep learning for Covid-19: state-of-the-art review

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Research on Biomedical Engineering 2022年第1期38卷 243-266页

作者： Nayak, Janmenjoy Naik, Bighnaraj Dinesh, Paidi Vakula, Kanithi Dash, Pandit Byomakesha Pelusi, Danilo K Kotturu AP Tekkali532201 India Department of Computer Application Veer Surendra Sai University of Technology Odisha Burla768018 India Department of Computer Science and Engineering Sri Sivani College of Engineering AP Srikakulam532402 India Faculty of Communication Sciences University of Teramo Coste Sant&#39 Agostino Campus Teramo Italy

Purpose: The appearance of the 2019 novel coronavirus (Covid-19), for which there is no treatment or a vaccine, formed a sense of necessity for new drug discovery advances. The pandemic of NCOV-19 (novel coronavirus-19) has been engaged as a public health disaster of overall distress by the World Health Organization. Different pandemic models for NCOV-19 are being exploited by researchers all over the world to acquire experienced assessments and impose major control measures. Among the standard techniques for NCOV-19 global outbreak prediction, epidemiological and simple statistical techniques have attained more concern by researchers. Insufficiency and deficiency of health tests for identifying a solution became a major difficulty in controlling the spread of NCOV-19. To solve this problem, deep learning has emerged as a novel solution over a dozen of machine learning techniques. Deep learning has attained advanced performance in medical applications. Deep learning has the capacity of recognizing patterns in large complex datasets. They are identified as an appropriate method for analyzing affected patients of NCOV-19. Conversely, these techniques for disease recognition focus entirely on enhancing the accurateness of forecasts or classifications without the ambiguity measure in a decision. Knowing how much assurance present in a computer-based health analysis is necessary for gaining clinicians’ expectations in the technology and progress treatment consequently. Today, NCOV-19 diseases are the main healthcare confront throughout the world. Detecting NCOV-19 in X-ray images is vital for diagnosis, treatment, and evaluation. Still, analytical ambiguity in a report is a difficult yet predictable task for radiologists. Method: In this paper, an in-depth analysis has been performed on the significance of deep learning for Covid-19 and as per the standard search database, this is the first review research work ever made concentrating particularly on Deep Learning for NC

关键词： Coronavirus

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A 7nm-Based Decodable Self-Resetting Regfile Circuit 15

A 7nm-Based Decodable Self-Resetting Regfile Circuit

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15th IEEE International Conference on ASIC, ASICON 2023

作者： Zhao, Wanlong Zhang, Yuejun Ren, Mingze Wen, Liang Wang, Pengjun Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo China Ningbo University Zhejiang Key Laboratory of Mobile Network Application Technology Ningbo China China Coast Guard Academy Department of Electronic Technology Ningbo China Wenzhou University College of Electrical and Electronic Engineering Wenzhou325035 China

ISBN: (纸本)9798350312980

This paper presents a novel design scheme for a decodable self-resetting Regfile circuit that aims to reduce the power consumption caused by massive data and high computing power. The scheme consists of three steps: first, it analyzes the working principle and the energy consumption process of the decoding circuit;second, it proposes a self-resetting decoding circuit structure that uses the clock to control the decoding state and automatically resets when the clock is low, thus avoiding the extra power consumption due to the inversion of the memory cell state during the non-working period of the decoding circuit;third, it implements a two-read, two-write, decodable self-resetting Regfile circuit using a full-custom design method under the TSMC 7nm FinFET process. The experimental results demonstrate that the circuit has an area of 5593μm2 and an energy-delay product of 0.41pJ•nS, and it can operate stably at 4GHz under various temperatures and process corner conditions. © 2023 IEEE.

关键词： 7nm process high speed low power consumption Regfile circuit

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