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Empirical techniques for effort estimation in designing effective ML models

International Journal of computers and Applications 2025年第2期47卷 226-234页

作者： Padmanabha Reddy, Y.C.A. Kosuru, Sai Sathwik Sirisalla, Nageswara Rao Vivekananda, G.N. Perala, Venkata Akanksha Department of Artificial Intelligence and Machine Learning Chaitanya Bharati Institute of Technology Telangana Hyderabad India Department of CSE B V Raju Institute of Technology Telangana Narsapur India Department of Computer Science and Engineering K.S.R.M. College of Engineering AP Kadapa India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

machine learning Research often involves the use of diverse libraries, modules, and pseudocodes for data processing, cleaning, filtering, pattern recognition, and computer intelligence. Quantization of Effort Required for the above cumulative processes is rarely discussed in the existing works and The time to reach the desired level of the model's functionality is essential to gauge the environment training for the model training and pre-deployment testing. In this study, we empirically defined the manual-cum-computational effort required for the model development in terms of 2-time factors: time-to-live (time until 1st code modification) and time-for-modification (time between 2 codebase changes) taken together in a mathematical model to compute Effort Factor(quantitative measure of determining effort needed to design ML algorithms). The study is novel in terms of how the effort required to create ML models is calculated with a particular focus on the manual effort direction. The results and the findings obtained can be used for determining the total time needed to synthesize ML models and frameworks in terms of code change cycles and implementation strategies marking a 25% performance increase in the current method above the Standard Pipeline. © 2025 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Pipeline codes

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A Comprehensive Food Identification and Waste Reduction Solution with Built-in Nutritional Tracking using machine learning 8

A Comprehensive Food Identification and Waste Reduction Solu...

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8th International Conference on Inventive Systems and Control, ICISC 202

作者： Jonathan, J. Benjamin, Ruth Moly Prasad, Gunji Prem Karunya Institute of Technology and Sciences Computer Science Engineering Coimbatore India Karunya Institute of Technology and Sciences Division of Artificial Intelligence and Machine Learning Coimbatore India Karunya Institute of Technology and Sciences Division of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350386578

Food Solutions and Nutrition Checker is an innovative and comprehensive project aimed at providing users with a reliable tool to identify various foods and dishes, while also offering a custom-built database for detecting fresh and wasted food items. With this system, users can easily determine the nutritional value of different foods, making informed decisions about their dietary choices. This study incorporates advanced technology that enables the recognition of a wide range of food items. By simply capturing an image or specifying the dish, users can obtain accurate information about the food, including its ingredients and origin. This feature is particularly helpful for individuals with specific dietary needs or restrictions, allowing them to easily identify suitable menu options. Additionally, this study includes a custom-built data system that helps to identify fresh and wasted food. By analyzing factors such as expiration dates, storage conditions, and quality indicators, the proposed system can determine the freshness status of various food items. This capability promotes food waste reduction by enabling users to make informed decisions regarding the consumption or disposal of perishable goods. Moreover, this study incorporates a nutritional tracker that provides users with comprehensive information regarding the nutritional composition of different foods. This feature includes details such as calorie count, macronutrient breakdown, vitamins, and minerals, empowering users to make healthier food choices aligned with their dietary goals and requirements. Overall, the proposed model offers a holistic approach for food identification, waste reduction, and nutritional tracking. By incorporating advanced technology and a robust database, this study aims to facilitate informed decision-making and promote healthier dietary practices. © 2024 IEEE.

关键词： Food ingredients

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Quantum Chain of Things: 'The Quantum triad - Integrating Blockchain, IoT and Quantum Computing for a Transcendent Future'

Quantum Chain of Things: 'The Quantum triad - Integrating Bl...

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International Conference on computer Vision and Internet of Things 2023, ICCVIoT 2023

作者： Jain, Shweta Aggarwal, Rishit Gandhi, Anju Bhandari Department of Artificial Intelligence and Machine Learning Panipat Institute of Engineering and Technology Panipat India Department of Computer Science and Engineering Graphic Era University Dehradun India

ISBN: (纸本)9781839539848

The Internet of Things (IoT), which is building a new world where everything is interconnected and can be remotely operated, is one of the developing technologies. The epoch of machines conquering the universe is just getting warmed up. The next technological innovation is blockchain, which uses a peer-to-peer communication link to preserve general transactional data and information (or blocks) across several repositories (or chains). The terminology "Digital Ledger" alludes to an instance of block storage. Quantum computing is the next quickly developing technology. It incorporates the use of numerous quantum physics aspects, notably superposition and entanglement. Every foundational premise of the computational game is amended by quantum excellence. A new paradigm dubbed Quantum - Chain of Things (QCoT), which is the most potent technology from the sub-emerging technologies is presented when we scrutinize the collaboration of the three powerful advanced. The BC-IOT (Blockchain coupled with IOT leveraging Arduino) and QC-IOT (Quantum computing merged with IOT using IBM Qiskit) subsystems are the cornerstones of QCoT technology. The prevailing breakthroughs in blockchain, quantum computing, and IOT will be addressed in this paper, followed by an exploration of the recommended architectural model for the improved technology. © The Institution of Engineering & Technology 2023.

关键词： Blockchain

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Internet of Animal Health Things (IoAHT) Framework for Clinical Mastitis Detection in Dairy Cows 1

Internet of Animal Health Things (IoAHT) Framework for Clini...

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1st International Conference on Recent Advances in Information Technology for Sustainable Development, ICRAIS 2023

作者： Ankitha, K. Venugopala, P.S. Kunder, Harish Shetty, Ankitha NMAMIT Nitte Dept. of Artificial Intelligence and Data Science Karkala India Alvas Institute of Engineering and Technology Dept. of Artificial Intelligence and Machine Learning Moodbidri India

ISBN: (纸本)9798350306637

The Earth serves as a shared habitat not just for humans but also for an array of animal species and organisms. Throughout history, animals have played a crucial role in preserving the natural ecosystem balance and meeting diverse human needs. They contribute significantly to various sectors, such as Agriculture, Dairy, Poultry, and animal husbandry, thus bolstering a country's economy. Human responsibility lies in ensuring the well-being of these animals, which is overseen by Veterinary science. In India, a major milk and milk product producer, the dairy industry actively contributes to the nation's economy. Among the primary milk sources-cows, buffaloes, goats, and sheep-cows hold a revered place in different faiths. Particularly in the dairy industry, cows are vital for milk production. However, monitoring cow health poses challenges. Clinical Mastitis, an inflammation affecting cows' mammary glands, hampers milk production. Automatic milking machines are commonly used, but identifying and segregating mastitis-infected cows from healthy ones remains difficult. The contagious nature of the disease increases the risk of widespread infection among cows. To combat this issue, we propose a solution called the Internet of Animal Health Things (IoAHT), based on the Internet of Things (IoT). IoAHT employs IoT technology for animal health, aiming to accurately identify cases of clinical mastitis in cows. The implementation of IoAHT has the potential to revolutionize health monitoring in the dairy industry, safeguarding cow well-being and ensuring sustainable milk production. © 2023 IEEE.

关键词： Internet of things

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Cyber Security in IoT Research Method for Securing IoT Devices and Network from Threats 15

Cyber Security in IoT Research Method for Securing IoT Devic...

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15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Firdose, Afsha Nischitha, A.R. Dhruva, M.S. Kumar, Anil K.B. Dept.of Information Science and Engg. ACU BGSIT India Dept.of Computer Science and Engg. ACU BGSIT India Dept.of Artificial Intelligence & Machine Learning ACU BGSIT India

ISBN: (纸本)9798331300579

Ensuring the security of IoT devices and networks becomes paramount as the Internet of Things (IoT) continues to spread across various *** abstract outlines research methods aimed at enhancing cybersecurity in IoT ecosystems to mitigate emerging *** research methodology strives to contribute to the advancement of cybersecurity practices in IoT by providing actionable insights and best practices for securing devices and networks against emerging cyber *** rigorous empirical analysis, interdisciplinary collaboration, and proactive defense strategies, the study aims to bolster the resilience of IoT ecosystems and safeguard critical infrastructure, data, and privacy in an increasingly interconnected world. © Grenze Scientific Society, 2024.

关键词： Cyber attacks

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From Clustering to Intelligent Decision Support System: An Application to 3D Printing 26

From Clustering to Intelligent Decision Support System: An A...

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26th International Conference of the Catalan Association for artificial intelligence, CCIA 2024

作者： Karna, Ashutosh Gibert, Karina Knowledge Engineering and Machine Learning Group Intelligent Data Science and Artificial Intelligence Research Centre Universitat Politècnica de Catalunya Barcelona Spain

ISBN: (纸本)9781643685434

This study focuses on developing an intelligent decision support system (IDSS) that helps a human operator make data-driven decisions. To put IDSS in production, it is necessary to develop two additional components: one oriented to recognize the cluster of new data and the other a knowledge-based resulting from the interpretation of clusters and further association of actions to each cluster, constituting a knowledge base with the alerts and recommendations associated to every profile. Bootstrap-CURE technique is used to handle the initial component, whereas a meta-clustering framework is suggested for interpreting the clusters and providing recommendations. A detailed strategy is presented for handling a print job, examining patterns, and executing actions through IDSS, thus improving predictive accuracy and operational efficiency. Two distinct machine learning models were developed, one to detect the operational mode and another to choose the best meta-cluster for the type of printing jobs and detained steps are provided for implementing the recommendations. © 2024 The Authors.

关键词： Printing presses

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Prediction of COVID-19 Severity Using Patient’s PHR 6th

Prediction of COVID-19 Severity Using Patient’s PHR

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6th International Conference on Information and Communication Technology for Intelligent Systems, ICTIS 2021

作者： Bharathi, M.A. Meghana Kumar, K.J. Department of Artificial Intelligence and Machine Learning BMS Institute of Technology and Management Bangalore India Department of Computer Science BMS Institute of Technology and Management Bangalore India

ISBN: (纸本)9789811935749

A significant health crisis, including the current COVID-19 outbreak, presents us for an opportunity to think about it and focus on how we may improve the way we handle health care in the future to make us humans better prepared and capable of dealing with such an *** the COVID-19 trend has swayed irregularly, they have remained in the dark, unsure how much resources they will have even in the future *** these instances, difficult period to be capable of predicting exactly what sort of resources a person have it necessary now of a positive test, or perhaps even earlier, would take place extremely beneficial to organizations, as they will be able to get or make preparations with their resource required to save that patient’s *** aim of the work is to devise a system that would be both outlay and reliable. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： COVID-19

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From 5G to 6G: The Role of AI, machine learning, and Deep learning in Wireless Systems 4

From 5G to 6G: The Role of AI, Machine Learning, and Deep Le...

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4th International Conference on Sentiment Analysis and Deep learning, ICSADL 2025

作者： Gote, Pradnyawant M. Kumar, Praveen Verma, Prateek Yesankar, Prajyot Pawar, Adesh Saratkar, Saniya Faculty of Engineering and Technology Department of Computer Science & Design Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Computer Science & Medical Engineering Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Artificial Intelligence & Machine Learning Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Artificial Intelligence & Data Science Maharashtra Wardha442001 India

ISBN: (纸本)9798331523923

The swift progression of wireless communication technologies-specifically from 5G to 6G is an approach that could be the most significant revolutionary leap towards changing connectivity and data transmission forever. Additionally, algorithms of machine learning (ML) and deep learning (DL) in 5G and 6G can offer promising advancements toward predictive maintenance, dynamic spectrum management, and enhanced security. The review of the potentially transformative nature of these technologies underlines the need for future directions of research efforts called for in circumventing challenges towards making full capability exploitation of 6G possible. © 2025 IEEE.

关键词： Adversarial machine learning

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Enhancing Web Security: An Advanced Automated Kitterman Tool for Comprehensive Network Vulnerability Detection

Enhancing Web Security: An Advanced Automated Kitterman Tool...

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2024 IEEE International Students' Conference on Electrical, Electronics and computer science, SCEECS 2024

作者： Sasikumar, R. Anita, C.S. Rajalakshmi, D. Sudharson, K. Alekhya, Badi Kumar, N. Sathish R.M.D. Engineering College Department of Computer Science and Engineering Chennai India R.M.D. Engineering College Department of Artificial Intelligence and Machine Learning Chennai India

ISBN: (纸本)9798350348460

Strong security is essential in the ever-changing world of web applications to ward off potential dangers. To identify various network vulnerabilities like Cross-Site Scripting, Database Injection, Information Disclosure, Subdomain Enumeration, Cache Deception, Banner Grabbing, Technology Fingerprinting, Apache Denial-of-Service, Apache Struts Remote Code Execution, and Clickjacking, this paper presents a novel automated Kitterman tool. The application uses a powerful crawler to extract links and systematically find vulnerabilities using a URL input. Our investigation shows that our technology outperforms all previous tools with an astounding output level of 91.8%. With the proactive features of our automated Kitterman tool, you can fortify your online defences and make sure that your web applications are resilient against a wide range of possible threats. © 2024 IEEE.

关键词： automated kitterman tool cross-site scripting database injection network vulnerability detection web security

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Non-Destructive Detection of Fillet Fish Quality Using MQ135 Gas Sensor and Neutrosophic Logic-Enhanced System

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Neutrosophic Sets and Systems 2025年 80卷 540-563页

作者： Shams, M.Y. Darwesh, M.R. Bhatnagar, Roheet Al-Sattary, N.S.A. Salama, A.A. Ghoname, M.S. Deptartment of Machine Learning Faculty of Artificial Intelligence Kafrelsheikh University Kafrelsheihk33516 Egypt Department of Agriculture Engineering Faculty of Agriculture Tanta University Tanta31527 Egypt Department of Food Processing Faculty of Industry and Energy Samannoud Technological University Egypt Department of Computer Science and Engineering Manipal University Rajasthan Jaipur India Department of Mathematics and Computer Science Faculty of Science Port Said University Egypt

This paper demonstrates the feasibility of using an electronic nose to assess fish quality by analyzing air quality and examining volatile organic compounds (VOCs) alongside physical variables, with pH, protein content, and VOCs serving as chemical reference points. artificial intelligence algorithms were employed to predict quality and calculate regression coefficients. Using the reference neural network algorithm based on chemical and physical compounds, regression coefficients (R values) achieved were 0.99, 0.98, and 0.97, respectively. Additionally, ANFIS (Adaptive Neuro-Fuzzy Inference System) produced R values of 0.99, 0.85, and 0.98. Both fuzzy logic and ANFIS proved effective for predicting fish quality. Image processing techniques, including histogram analysis, color mapping, and edge detection, were also applied to assess fish quality. To enhance the inference process, Neutrosophic Logic-Enhanced Fuzzy Logic Systems were utilized, addressing uncertainty and imprecision in fish quality assessment. Neutrosophic logic combines fuzzy logic's partial truth with indeterminacy, represented by three membership functions: truth, indeterminacy, and falsity. Neutrosophic fuzzy inference integrates steps like neutrosophication, rule evaluation, aggregation, and defuzzification, ensuring improved expressiveness and fidelity. For instance, neutrosophic fuzzy rules evaluated fish freshness and appearance to determine quality ratings such as poor, good, or excellent. This integration enhances decision-making by accurately modeling complex real-world uncertainties. These methods, combining electronic nose technology, artificial intelligence, and neutrosophic inference, provide a robust, non-destructive, and cost-effective approach to detecting spoilage in fillet fish. © 2025, University of New Mexico. All rights reserved.

关键词： Volatile organic compounds

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