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Research on software Defect Prediction Model Based on ICA-BP

Research on Software Defect Prediction Model Based on ICA-BP

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IEEE International conference on Power, Intelligent Computing and systems (ICPICS)

作者： Yifei Qu Yuncong Wang Shuowen Chai College of information Liaoning University Shenyang China College of Software Jilin University Changchun China School of Computer Science Anhui University of Science and Technology Huainan China

software defect prediction is a popular research direction in software engineering. To address the issue of low prediction accuracy in existing methods, in this paper we propose a software defect prediction model based on Imperialist Competitive Algorithm (ICA) and Backpropagation (BP) neural network. the model employs BP neural network to predict software quality and utilizes ICA to optimize network parameters such as weights and thresholds to seek the optimal network structure, which solves the problem that traditional BP neural networks are prone to local miniaturization. the model's data uses the NASA-MDP dataset, which solves the problem that BP neural networks require a large amount of experimental data. Experiments show that, compared with the standard BP neural network, the proposed model can improve the prediction accuracy by an average of 4%. Furthermore, this model provides new ideas and methods for software defect prediction, offering valuable references for related research.

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Improving Web Application Development Course 5

Improving Web Application Development Course

引用

5th National conference of Saudi computers Colleges, NCCC 2022

作者： Gharaibeh, Natheer Khalif Taibah University College of Computer Science & Engineering at Yanbu Information Systems Department Yanbu Saudi Arabia

ISBN: (纸本)9798350333688

Providing students with the expertise of scientific and practical skills in Web development requires good preparation and practical competencies, the formation of positive attitudes toward the given course and determining suitable learning outcomes is one of the most important trends and issues in instructional design and technology. One of the most important challenges in this paper is to develop the relatively old course plan to cope with the rapid developments in the world of web application development, this requires Curriculum mapping to identify and address academic gaps, and redundancies. For purposes of improving the overall coherence of the course, its relationship with the other prerequisite courses should be explained more, some learning outcomes may be achieved through more than one course, therefore this study traced other related courses to the problem statement, such as Object-Oriented-Programming (OOP), software Modelling and Design and other courses. this interconnected set of courses was motivated by the idea of Crosscutting concepts (CCCs) in Web Application Development, such as design patterns, Model-View-Controller (MVC), Entity Framework, Object Relational Mapping, Application Programming Interface (API), and others. this paper proposed some best practices and guidelines to take students gradually from a simple to more complicated tasks in learning Web development. © 2022 IEEE.

关键词： Curricula

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Innovative Motion Sensing System with Labview 14th

Innovative Motion Sensing System with Labview

引用

14th EAI International conference on Broadband Communications, Networks, and systems, BROADNETS 2024

作者： Vidyadhar, R. Phani Ravindra, J.V.R. Kumar, G. A. E. Satish Sandeep, Yanigandla Ashwitha, Kanugula Mantri, Devansh Vishvakumari, Faldu Department of ECE Vardhaman College of Engineering Telangana Hyderabad India RK University Gujarat Rajkot India

ISBN: (纸本)9783031811678

Nowadays children’s used to play and going near restricted areas like transformers and borewells due to that they are getting affected by such incidents ensure that we are performing a system called Innovative Motion Sensing with LabVIEW. this system will be built to instantly detect motion and send alerts or initiate actions according to the motion. LabVIEW software will be used for terminating this project. this Motion Detection System can be used for automotive safety in addition to restricted locations. the system’s primary objective will be to detect motion in real time and send out notifications or start events according to the motion. Several motion situations will be used to test and evaluate the system, including performance measures like accuracy and detection, different motion situations will be used to test and validate the system, and performance metrics including accuracy and detection time will be assessed. In this project, a GSM module is utilized to communicate with a nearby CELL Tower and transmit the message to a mobile device. Intelligent Motion Detection System for effectively identifying movement or motion inside a predetermined area and prompt timely replies or actions. With the help of this system, security, monitoring, and automation are all intended to be improved in a number of applications, and motion-related events will be handled proactively. © ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering 2025.

关键词： Motion sensors

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Application of AutomationML/OPC UA in Robot Interoperability

Application of AutomationML/OPC UA in Robot Interoperability

引用

Artificial Intelligence and computer engineering (ICAICE), International conference on

作者： Siyuan Chang Hualiang Zhang Software Engineering Institute Shenyang University of Technology Shenyang China

ISBN: (数字)9798331528911

ISBN: (纸本)9798331528928

this paper focuses on the application of AutomationML (AML) and Open Platform Communications Unified Architecture (OPC UA) in robot interoperability, aiming to promote the intelligence and interoperability of production systems in the era of Industry 4.0. By analyzing the current challenges of industrial robot interoperability, especially in terms of data standardization, a robot system architecture is proposed to improve the compatibility and information exchange efficiency between different types of robots. Research methods include system architecture design, integration of AML and OPCUA methods, and their empirical application in real-world manufacturing environments. the results confirm the feasibility and practicability of the method in the application of industrial robots, and give different devices higher interoperability and flexible response ability. It provides a theoretical basis and practical guidance for the development of intelligent manufacturing systems in the future, and has important practical significance and application value in improving the level of industrial digitalization and intelligence.

关键词： Systematics Service robots Computational modeling systems architecture Standardization Industrial robots Data models Servers Interoperability Testing

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Dynamic Image Deblurring based on Crosshatch Attention Adversarial Network and Hybrid Loss

Dynamic Image Deblurring based on Crosshatch Attention Adver...

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International conference on Advancements in Computational Sciences (ICACS)

作者： Ummama Aslam Arslan Shaukat Basim Azam Dept. of Computer and Software Engineering College of Electrical and Mechanical Engineering (CEME) National University of Sciences and Technology (NUST) Islamabad Pakistan Institute of Integrated and Intelligent Systems Griffith University Brisbane Australia

Image deblurring techniques that uses deep learning have shown great potential but due to low generalizability, noise immunity and the correlation among different pixels is not addressed in detail that results in unwanted artifact that appears in the deblurred image. To tackle this problem an end-to-end approach is proposed for the recovery of sharp image from blurred one without the estimation of blur kernel. A special type of attention module known as crosshatch attention is used after Residual Block of Generator model for removing noise and for the collection of correlation of different pixels in an image. Hybrid Loss function is defined which focus on different part of image and improve edges and texture details. the performance of the model for deblurring is measured on GoPro dataset. Our proposed model has slightly higher objective and subjective evaluation i-e PSNR, SSIM value and the visual results.

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SWS-NET: An Image Segmentation Framework For Chronic Wounds Based On Self-Supervised Learning 35

SWS-NET: An Image Segmentation Framework For Chronic Wounds ...

引用

35th International conference on software engineering and Knowledge engineering, SEKE 2023

作者： Li, Jiyun Yang, Sheng Qian, Chen School of Computer Science and Technology Donghua University Shanghai China

Automatic monitoring and evaluation of chronic wounds usually requires massive labeled data sets for segmentation training. Because of the high cost of time and labor, these data are usually difficult to obtain. In order to improve the segmentation effect of the wound image with a small number of labeled samples for training, this paper proposes an image segmentation framework based on self-supervision, summarize a relatively optimal pre-training task for chronic wound image segmentation, minimizes the redundancy between the symmetric network projection output by learning the feature information of two views generated by the same chronic wound image under different distortion transformation, and finally learns valuable knowledge that is conducive to the downstream wound image segmentation task. In addition, this framework also optimize the network structure and loss of the segmentation model. the experimental results show that after self-supervised learning pre-training with a full amount of unlabeled data, the segmentation framework can achieve significant improvement in precision(up to 8%), recall(up to 5%), and MIoU(up to 9%) by fine-tuning with only a small amount of labeled data, this can provide a clear optimization direction for the application of self-supervised learning to specific image segmentation. © 2023 Knowledge systems Institute Graduate School. All rights reserved.

关键词： Image segmentation

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software Re-engineering using Cloud Computing Platform

Software Re-Engineering using Cloud Computing Platform

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International conference on Smart systems and Inventive Technology (ICSSIT)

作者： A Ravi Raja K R Raghunandan Radhakrishna Dodmane Asmita Dixit M Sunil Kumar Dhiraj Kapila ECE department Velagapudi Ramakrishna Siddhartha Engineering College Vijayawada India Department of Computer Science and Engineering N. M. A. M Institute of Technology (Deemed to be university) Nitte India Department of Informaton Technology ABES Engineering College Ghaziabad India Department of Computer Science and Engineering School of Computing Mohan Babu University Vijayawada India Department of Computer Science and Engineering Lovely Professional University Phagwara India

Economic and technological progress in the cloud are the main topics of this article. the essay examines the question of whether or not it makes financial sense to build software in the cloud, vs in-house. this research work provides an overview of the current model-based re-engineering practises. A novel and more thorough method is outlined in Business Process Model and Notation (BPMN) with some example activities, inputs, and outputs. As an integral element of the primary re-engineering process, reverse engineering is also something to be considered. therefore, it expands on the concept of “SBSE for the cloud,” providing actionable formulations of problems associated with cloud computing. the system has been built in the cloud to track the health of analytical services while they are being called into use. As an example of analytical services, a number of implementations of data mining methods are hosted from a number of packages. their Quality of Service (QoS) values are also sampled by running them on certain real datasets. Based on the analysis of the KSEA National Math Competition event management system, this project will suggest some guidelines for software reengineering using AWS cloud computing services and web application technologies. Using these best practises, the informational gaps in software reengineering are bridged for web applications built in with cloud computing frameworks.

关键词： Cloud computing Visualization Data analysis Databases software architecture Object oriented modeling Quality of service

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Graph theory-Based User Profile Extraction and Community Detection in LinkedIn—A Study 1

引用

5th International conference on Soft Computing and Signal Processing, ICSCSP 2022

作者： Sneha Latha, S. Lathika, D. Srehari, T. Yaswanthram, P. Sabarish, B.A. Department of Computer Science and Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (数字)9789811986697

ISBN: (纸本)9789811986680

Online hiring and unpredictable job movement in the IT sector provides a need to analyze the pattern of movement of software professionals. Career trajectory is the trace of the list of jobs shifted by the professional through his career including the key skills acquired. Understanding the career trajectories of employees is a crucial tool for recruiting an employee to provide better stability in the industry. Career trajectory data is abundantly available and needs to be processed for extracting crucial features like educational qualification, work experience, and skill set acquired before each job shift. Career trajectories are forever evolving considering digitalization and enormous amounts of data generated. LinkedIn is being one such social media platform for job search, and it contains a lot of data that could be leveraged to understand the problem of career trajectory analysis. Data for the study has been extracted using web scraping from LinkedIn. Analyzing and recognizing trends and patterns in everlasting data require graphical data visualization. Graphical representation aids in the rapid processing of huge amounts of data and can assist in the making of predictions and well-informed judgments. Community detection algorithm is applied over the dataset to identify the employee communities available and identify relationships between them. this paper analyzes performance of several community detection algorithms on career trajectory graphs using the Girvan–Newman modularity score. Based on the analysis, Louvain algorithm has achieved a better modularity score of 0.85, and Girvan–Newman has the least score of 0.78. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Graph theory

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Integration of DL on Multi-Carrier Non-Orthogonal Multiple Access System with Simultaneous Wireless Information and Power Transfer 11

Integration of DL on Multi-Carrier Non-Orthogonal Multiple A...

引用

11th International conference on System Modeling and Advancement in Research Trends, SMART 2022

作者： Chaturvedi, Abhay Bhardwaj, Ankit Singh, Digvijay Pant, Bhasker Gonzales, Jose Luis Arias Firos, A. GLA University Department of Electronics and Communication Engineering Uttar Pradesh Mathura281406 India The Math Company University of Connecticut Department of Computer Science and Engineering University of Connecticut StorrsCT United States Uttaranchal Institute of Technology Uttaranchal University India Graphic Era Deemed to Be University Department of Computer Science and Engineering Uttarakhand Dehradun248002 India Graphic Era Hill University Department of Computer Science and Engineering Uttarakhand Dehradun248002 India Pontifical Catholic University of Peru Business Department Peru Department of Computer Science and Engineering Rono-Hills Arunachal Pradesh Doimukh India

ISBN: (纸本)9781665487320

Simultaneous Multi-Carrier (MC) NOMA&Wireless Information (SWIPT) are exciting ideas for coming net within the 5th generation and beyond because of their capability for allowing bandwidth and power effective system designs. Using the pattern-division-multiple-access (PDMA) approach, this study investigates the concurrent downlink scalability issue for a SWIPT-enabled MCNOMA system incorporating time swapping receivers. We put a lot of effort into reducing the systems overall transmit power while still providing each user with the level of service they expect in terms of gathered power and data rate. the corresponding optimization problem is a challenging quasi mixed integer computing problem. We present an effective deep learning (DL) based method as opposed to the traditional repetitive searching-based techniques for finding an approximation of the ideal answer. We particularly use a deep belief network (DBN), a common kind of DL model. the created technique's thorough technique is divided into three parts: data generation, testing, and execution. the simulated Results show that the suggested DBN-based strategy works. might produce results in terms of power usage that are similar to those of the thorough search technique. the findings also show that MCNOMA with PDMA outperforms MCNOMA with the other methods in terms of power consumption in systems that support SWIPT. © 2022 IEEE.

关键词： Integer programming

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An Empirical Analysis and Overview of a Green 6-G Paradigms and its Various Implementation Applications 4

An Empirical Analysis and Overview of a Green 6-G Paradigms ...

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4th IEEE International conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2024

作者： Rao, D.T.V. Dharmajee Sharma, Kuldeep Joshi, Sanjeev Kumar Rani, T Sudha Alsalami, Zaid Angadi, Sanjeevkumar Cmr Technical Campus Department of Cse Telangana Hyderabad India Chitkara University Centre of Research Impact and Outreach Punjab Rajpura140401 India Uttaranchal Institute of Technology Uttaranchal University Department of Mechanical Engineering Dehradun248007 India Aditya Engineering College Department of Computer Science and Engineering Surampalem India The Islamic University Najaf Iraq Computer Science and Engineering Nutan College of Engineering and Research Pune Maharashtra Talegaon Dabhade India

ISBN: (纸本)9798350360165

the advent of green 6G technologies holds promise for revolutionary improvements across different areas such as data transmission speed, latency, and traffic volume. Incorporating features like sub-terahertz communication and advanced multiple-input multiple-output (MIMO) technologies, Green 6 G networks aim to surpass the data transmission rates of 5 G while slashing latency to a mere fraction. However, this rapid expansion in network data transfer poses notable hurdles concerning data processing systems and energy usage. Despite strides in energy-efficient computing methods such as green cloud and edge computing, unresolved issues persist, including substantial energy consumption during data migration and idle server power usage. To tackle these challenges, this study proposes a novel strategy called 'In-Network Computing' (INC), which relocates processing tasks from hosts to network devices, leveraging idle resources to alleviate data transmission burdens and mitigate pressure on cloud computing resources. In contrast to edge computing, INC exhibits advantages in the 6 G landscape due to the enhanced computing capabilities and application awareness of network devices. the proposed approach prioritizes energy efficiency by minimizing data centre inputs and integrating host and network node computing environments through virtualization and software-based models. the paper introduces innovative implementations by implementing green 6 g paradigms, focusing on task scheduling and the creation of a prototype system utilizing low-power multicore processors. Experimental validation across diverse application scenarios demonstrates substantial reductions in system energy consumption and network traffic. © 2024 IEEE.

关键词： Data transfer

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