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AI-Driven Software Reuse: Optimization and Comparative Performance Analysis

AI-Driven Software Reuse: Optimization and Comparative Perfo...

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Computational Intelligence, Communication Technology and Networking (CICTN), International Conference on

作者： Aditya Pai H Chandrappa S Guru Prasad M S Atul Thakare Sharon Christa Pratik Kumar MIT School of Computing MIT Art Design and Technology University Pune India School of Computer Science and Engineering JAIN Deemed to be University Bengaluru India Dept. of Computer Science and Engineering Graphic Era (Deemed to be University) Dehradun India Department of Computer Application Graphic Era (Deemed-to-be University) Dehradun India

ISBN: (数字)9798331530389

ISBN: (纸本)9798331530396

Software reuse improves productivity and ensures that there is less time delivered to the market by enabling the proper usage of reusable code from the software repositories. The study provides the collaboration between the AI techniques, which includes Convolution Neural Networks (CNN), Random Forest (RF), and Support Vector Machines (SVM), to predict software components' reusability. The comparative analysis shows the effectiveness of different AI- driven algorithms, where CNN has shown the highest accuracy of 92%, thus reducing the human effort in finding the reusable modules. The Case studies in e-commerce and health care show the benefit of using AI-driven reuse of software; this means that the development time is reduced by 25%, and the maintenance cost is decreased by 20%. The paper highlights how different AI algorithm integration with software engineering has some limitations. The findings show that AI has greatly revolutionized software reuse. Thus bringing innovation and efficiency in software engineering.

关键词： Support vector machines Computational modeling Medical services Software Data models Convolutional neural networks Artificial intelligence Software reusability Random forests Software engineering

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Development of Cloud Centric Healthcare Monitoring System For Cardiac Patients embedded in IoT Platform

Development of Cloud Centric Healthcare Monitoring System Fo...

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International Conference on Emerging Trends in engineering and Technology, ICETET

作者： Adarsh Ravi Mishra Ravi Mishra Ragini Shukla Dept. of Computer Application and Information Technology Dr. C.V. Raman University Bilaspur India Dept. of Electronics and Telecommunication G H Raisoni Institute of Engineering and Technology Nagpur India

In terms of profit and employment, the Indian economy’s healthcare sector has emerged as one of the most significant sectors. The Indian healthcare sector is experiencing rapid growth due to improved coverage, expanded functionalities and services and increased public and private spending. Due to which the life expectancy has increased dramatically. As the population of individuals rises in many societies, the number of people affected by chronic diseases, such as diabetes, cardiovascular disease, obesity, and so on, rises as well. As a result, Internet of Things (IoT)-based personalised healthcare is becoming a more significant idea.. This paper’s main goal is to illustrate a cardiac patient e-health data acquisition, transfer, and monitoring system. The smart health monitoring system prototype uses a wireless sensor network to measure various health data, which are then sent to the concerned individual through GPRS. These parameters are also saved in Amazon cloud services for future use.

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Prediction of Cardiac Arrest using Generalized Soft Computing Techniques

Prediction of Cardiac Arrest using Generalized Soft Computin...

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International Conference on Computing for Sustainable Global Development (INDIACom)

作者： Radhanath Hota Sachikant Dash Sujogya Mishra Subhalaxmi Das S Lenka G Pradhan Department of Computer Science Engineering GIET University Gunupur Odisha India Department of Computer Science Engineering Gandhi Institute for Education and Technology Gunupur Odisha India Department of Mathematics Odisha University of Technology and Research Bhubaneswar India Dept. of Computer Science and Engineering Odisha University of Technology and Research Bhubaneswar India Department of Computer Science and Application Utkal University Bhubaneswar India

Cardiac-related diseases always lead to fatal consequences around the globe. This research includes vague data analysis of the data related to cardiac anomalies. This study proposes a method to develop a dimension reduction model using vague data related to cardiac diseases using rough set theory (RST). The overall research is divided into two different sections. The first section of this study proposes analyses of the raw cardiac-related data using RST, and the second section calculates the performance accuracy using Principal Component Analysis (PCA) applied to the universal data set; the performance measures also include a combination of two Universal data sets. The above claims are verified using statistical tests

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Exploring OSINT for Modern Day Reconnaissance

Exploring OSINT for Modern Day Reconnaissance

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IEEE International Conference on engineering Education: Innovative Practices and Future Trends (AICERA)

作者： Ajay S Ram Arya Thalakkat Devika Udayan Aiby A Khader Hari K Vipin George Dept. of Computer Science and Engg. Government Engineering College Thrissur India Dept. of Cyber Forensics School of Technology and Applied Science Kottayam India Dept. of Computer Application Kerala Police Academy Thrissur India Police Computer Lab Kerala Police Academy Thrissur India Faculty Kerala Police Academy Thrissur India

The Internet's growth has connected users globally, forming a vast network of data. As new social media platforms with diverse features emerge, individuals are drawn to sharing their personal data online. This inclination stems from a desire to display social status. However, this openness poses risks, as personal data uploaded to the internet can easily unveil one's online identity. Extracting such data is a straightforward process, as a simple correlation of evidence with an online profile can summarize a user's identity. By combining various sources of information linked to a specific individual, a comprehensive profile can be created. As the digital landscape expands, Open Source Intelligence (OSINT) has become an invaluable tool for gathering information. OSINT involves searching and accessing publicly available data to extract relevant information, analyze patterns, and draw conclusions. It encompasses activities like web scraping, data mining, social media monitoring, and online research. OSINT is crucial for understanding public sentiment, identifying potential threats, conducting background checks, investigating crimes, and performing competitive analysis. This paper investigates the impact of OSINT as a modern day reconnaissance tool. Through case studies and real-world examples, the research demonstrates the effectiveness of OSINT in enhancing situational awareness, supporting decision-making for law enforcement agencies, and using OSINT as a modern-day reconnaissance tool.

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Distributed secondary voltage control of islanded AC microgrids: A comparative study 5

Distributed secondary voltage control of islanded AC microgr...

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5th International Conference on Electronics, Materials engineering and Nano-Technology, IEMENTech 2021

作者： Ganguly, Arijit Bhadra, Shantanu Bhowmick, Parijat Sen, Sawan University of Engineering And Management Dept. of Electrical Engg. Kolkata India Institute of Hotel And Restaurant Management Dept. of Computer Science And Application Sonarpur India University of Engineering And Management Dept. of Basic Science And Humanities Kolkata India Kalyani Government Engineering College Dept. of Electrical Engg. Nadia West Bengal Kalyani India

ISBN: (纸本)9781665418034

This paper proposes a distributed secondary voltage control (DSVC) scheme of DG based islanded AC microgrids employing cooperative control design. The controller design has been further strengthened by introducing a bilayered adaptive control formulation. The centralized control scheme for inverter-based DGs in an islanded microgrid poses significant challenges in terms of voltage control, connectivity issues among all DGs and handling contaminated signals of the DG units under influence of unwanted signals i.e. noise and disturbances. The objective here is to design an optimal control input employing linear quadratic regulator (LQR) principle in cooperative and adaptive control formulation. An exhaustive comparative analysis driven by an exhaustive Matlab simulation has been done in order to demonstrate the effect of Algebraic Riccati Equation (ARE) parameters in the proposed cooperative and adaptive control algorithm to specify the variations in time domain specifications of the microgrid voltage response. Simulation analysis has been done to check the effectiveness of the adaptive controller over the cooperative design of the microgrid controller where DGs are subjected to variable frequency disturbance (VFD). © 2021 IEEE.

关键词： Controllers

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Adaptive secondary frequency control of islanded AC microgrids subjected to disturbances 12

Adaptive secondary frequency control of islanded AC microgri...

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12th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2021

作者： Ganguly, Arijit Bhadra, Shantanu Bhowmick, Parijat Sen, Sawan University of Engineering and Management Dept. of Electrical Engg. Kolkata India Institute of Hotel and Restaurant Management Dept. of Computer Science and Application Sonarpur India University of Engineering and Management Dept. of Basic Science and Humanities Kolkata India Kalyani Government Engineering College Kalyani Dept. of Electrical Engg. West Bengal Nadia India

ISBN: (纸本)9781665400664

This paper proposes a distributed secondary frequency control (DSFC) of distributed generation (DG) based islanded AC microgrid employing cooperative control scheme. The controller potential has been extended to form adaptive control framework considering coupling gain dynamics. The distributed control framework provides multiple advantages over centralized control schemes for DG based islanded microgrids in terms of reference frequency tracking, frequency control and multiple disturbances rejection. The linear quadratic regulator (LQR) algorithm calculates the control gain for both cooperative and adaptive control schemes. A detailed analysis for islanded AC microgrid operating in healthy condition and the same subjected to multiple disturbances has been presented for both the proposed control designs. An exhaustive Matlab simulation has been done to validate the effectiveness of the above mentioned schemes. © 2021 IEEE.

关键词： MATLAB

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Automatic Fast Fuzzy Clustering Algorithm for Nucleus Segmentation of Color Pathology Images

Automatic Fast Fuzzy Clustering Algorithm for Nucleus Segmen...

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IEEE India Conference (INDICON)

作者： Arunita Das Amrita Namtirtha Animesh Dutta Dept. of Computer Sc. & Application Midnapore College (Autonomous) Midnapore West Bengal India Dept. of Computer Sc.& Engineering National Institute of Technology Durgapur West Bengal India Dept. of Computer Sc. & Engineering JIS College of Engineering Kalyani Nadia India

ISBN: (纸本)9781665452724

Due to the repeated computation of the distance between pixels and cluster centres, the effective image clustering technique fuzzy c-means (FCM) takes a long time to process. In other words, FCM’s computational time greatly depends on image size or number of pixels. Therefore, researchers utilized histogram of the image for clustering for developing time-reduced clustering approach. However, finding the histogram for color image is very challenging. Another challenge of FCM is the selecting the required number of clusters before segmentation process. Therefore, this study proposes a novel automatic color image clustering approach called fully automatic histogram based fast fuzzy clustering (FAHBFFC) to overcome the both mentioned demerits. The proposed FAHBFFC automatically find the required number of clusters for the segmentation of the color images. It also utilized the histograms of the color channels of the images and hence, the proposed approach is very fast. Finally morphological reconstruction has been applied for membership filtering of the FCM to incorporate the noise-immunity. In comparison to other state-of-the-art algorithms for pathology picture segmentation, the FAHBFFC produces results that are competitive.

关键词： Image segmentation Histograms Pathology Image color analysis Filtering Clustering methods Clustering algorithms

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TB Chest X-Ray Diagnostic Technique Using Deep Learning

TB Chest X-Ray Diagnostic Technique Using Deep Learning

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Delhi Section Conference (DELCON), IEEE

作者： Manish Kumar Goyal Dhananjay Kumar Yadav Khushmeen Kaur Brar Manisha Mittal Ananta Ojha Laith H. Alzubaidi Ashish Pathani Dept. of Computer Science & Application Vivekananda Global University Jaipur India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Dept. of Electronics and Communication Engineering Chandigarh University Mohali India Guru Tegh Bahadur Institute of Technology New Delhi India Dept. of Computer Science and Information Technology Jain (Deemed to be University) Bangalore India The Islamic University Najaf Iraq Department of Civil Engineering Uttaranchal Institute of Technology Uttaranchal University Dehradun India

ISBN: (数字)9798331518592

ISBN: (纸本)9798331518608

The bacteria Mycobacterium tuberculosis is responsible for the infectious illness tuberculosis (TB). Although the lungs are the primary organs affected, the kidneys, bones, and brain may also be affected. Whenever an infected person coughs, sneezes, or talks, small droplets comprising the bacteria are released into the air and spread through the airborne system. The elimination of tuberculosis (TB) remains a problem due to factors such medication resistance, co-infection with HIV, and scarce resources in high-burden configurations, even with substantial efforts to treat the disease. As a major worldwide health concern, tuberculosis (TB) necessitates quick and precise diagnosis in order to be effectively managed. This study aimed to develop a TB detection model using chest X-ray images obtained from ***, utilizing Google's Collaboration Platform. The model was trained to recognize patterns within the TB chest X-rays to efficiently recognize TB within patients in order to be treated in time. We introduce a technique for transfer learning that proves preferable to the traditional methodology of adopting ImageN et weights. The hybrid methodology utilizes best first search technique in fusion with ResNet 50 model. The SVM classifier is used for categorizing the classes. An accuracy of 93.91 % is attained.

关键词： Support vector machines Tuberculosis Lungs Transfer learning X-rays Bacteria Pattern recognition X-ray imaging Medical diagnostic imaging Kidney

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QoS provisioning based cost-effective routing in WSN based IoT network using fuzzy IDA∗ technique 8

QoS provisioning based cost-effective routing in WSN based I...

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8th International Conference on Computing for Sustainable Global Development, INDIACom 2021

作者： Lenka, Stitapragyan Nanda, Arabinda Pradhan, Sateesh Kumar Utkal University P. G. Dept. of Comp. Sc. and Application Bhubaneswar Odisha India Eastern Academy of Science and Technology Dept. of Computer Science and Engineering Bhubaneswar Odisha India

ISBN: (纸本)9789380544434

Wireless Sensor Network(WSN) is an integral part of Internet of Things (IoT) application network. Cost-effective WSN routing will help IoT applications to offer faster services in an efficient way. Routing in WSN is one of the challenging task due to node mobility and need on small battery to ruins active in the network. Flat routing shows poor performance for WSN if number of node increase. Cluster based routing is the alternative that is scalable and shows better utilization of network resources. The data transmission cost will be more, if the sender nodes send data directly to sink node due to large distance of data transmission and the node battery power dry very soon. To overcome this problem data packets send from sender node to sink node via cluster head node. The member nodes of a cluster send data packets to its header node, then the header node send the data packets to sink node. In our proposed method, the fuzzy inference system uses three Quality of Service (QoS) parameters distance, energy and angle to select the chance of a node becomes cluster head. Iterative Deepening A*(IDA*) search used to discover the shortest route that send data packets from supply node to the sink node. The fuzzy system is used to select the cluster head and IDA∗ search algorithm used to select the minimal cost path. The proposed method - Cost Effective Routing in WSN Using Fuzzy IDA*(CERWFI) is used to find an optimal route from starting node to ending node (sink). The research concludes by stating that space complexity of Dijkstra's and A∗ algorithm can be improved by IDA∗ algorithm. © 2021 Bharati Vidyapeeth, New Delhi. Copy Right in Bulk will be transferred to IEEE by Bharati Vidyapeeth.

关键词： Quality of service

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The Symphony of Style: An Extensive Examination of Determination Mechanisms in Deep Learning-Inspired Outfit Suggestions

The Symphony of Style: An Extensive Examination of Determina...

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Computational Intelligence, Communication Technology and Networking (CICTN), International Conference on

作者： Guru Prasad M S Ravatappa A Bhosagi Madhusudhana K Prithviraj Chandrappa S Vikash Kumar Department of Computer Science and Engineering Graphic Era (Deemed to be University) Dehradun India School of Computing and Information Technology Reva University Bengaluru India Dept. of Electronics & Communication Engineering SDM Institute of Technology Ujire India Department of Computer Science and Engineering Nitte (Deemed to be University) NMAMIT Mangalore India Department of Computer Science and Engineering Jain (Deemed-to-be University) Bengaluru India Department of Computer Application Graphic Era Deemed University Dehradun India

ISBN: (数字)9798331530389

ISBN: (纸本)9798331530396

In the field of the fashion industry, the introduction of deep learning technology has taken an innovative revolution by providing assistance in the construction of intellectual systems that are intelligent to deliver personalized ensemble recommendations. In this research work, an innovative ensemble recommendation structure called Deep Learning VGG16 (Visual Geometry Group 16) recommender is presented. The proposed method allows a deep learning model VGG16 to understand complex patterns and developments resulting from a vast group of fashion images. In order to increase the user experience and greater participation in the well-established fashion industry, the system offers personalized ensemble ideas. The important, core and fundamental component of the system is VGG16, consisting of 13 convolutional layers and 3 fully connected layers, which is used to support the analysis of fashion images. A cutting-edge convolutional neural network (CNN) model is improved over a large and diverse collection of fashion images. Model will extract advanced high-level information and statistics with the capability to distinguish particulars in colour patterns, clothing combinations, and stylistic elements. Using this process of development, the system becomes better at identifying user preferences and fashion trends.

关键词： Deep learning Adaptation models Visualization Virtual assistants Clothing Market research Clothing industry User experience Convolutional neural networks Recommender systems

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