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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Sharma, Neeraj Vivek, V. Kumar, Ashwini Vivekananda Global University Department of Electrical Engineering Jaipur India School of Engineering and Technology Department of Computer Science and Engineering Karnataka Bangalore India Arka Jain University Department of Mechnical Engineering Jharkhand Jamshedpur India

ISBN: (纸本)9798350370249

Iterative function selection techniques are a sort of system mastering technique used for classifying records with capabilities having high non-linearity. Specially, this approach has been implemented to the category of pulmonary effusion data. It entails education a model, selecting a set of functions, and comparing the version overall performance with a purpose to decide which subset of functions is maximum critical for figuring out the class labels. This method is repeated iteratively, choosing the fine acting subset of functions on every occasion until a high-quality degree of accuracy is finished. The blessings of this method include improved accuracy and improved predictive functionality, due to the improved know-how of the relationship between capabilities and training. In addition, the iterative feature selection method can also lessen overfitting, because it reduces the quantity of functions within the version. © 2024 IEEE.

关键词： Blessings Capabilities Choosing Classifying Improved Predictive Quantity Techniques

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Prediction of Covid-19 Recovery Chances Using Supervised Machine Learning Classification 5th

Prediction of Covid-19 Recovery Chances Using Supervised Mac...

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5th International Conference on Innovative Product Design and Intelligent Manufacturing Systems, ICIPDIMS 2023

作者： Dhanalakshmi, R. Nivashini, A. Vijayaraghavan, N. Centre for Cyber Physical Systems School of Computer Science and Engineering Vellore Institute of Technology Chennai India Department of Computer Science and Engineering MNM Jain Engineering College Chennai India Department of Mathematics KCG College of Technology Chennai India

ISBN: (纸本)9789819767311

Predictive analytics if combined with machine learning approaches have the potential to play a significant role in forecasting the spread of respiratory infections. Machine learning approaches aid in the mining of data to better assess and forecast the presence or absence of covid-19 infection. In this paper, XGBoost Ensemble Classification using a fine-tuned approach is being used. Various machine learning algorithms are being analyzed and XGBoost Ensemble Classification algorithm is used to forecast and predict the covid-19 infected patient recovery chances that is the possible outcome of a covid-19 infected patient along with the prediction probability of recovery. The suggested categorization model is applied to a variety of situations. When compared to other ensemble models like random forest, hybrid ensemble and other individual classifiers such as decision tree, logistic regression, K-nearest neighbor, support vector machine and Naive Bayes, the XGBoost Ensemble Classification model gave the highest accuracy. Predicting the correct class is important. Thus, the proposed system discusses the possibility of automated prediction for covid-19 infected patient recovery chances along with the probability of recovery and the effectiveness of such predictions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： COVID-19

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The Future of Smart Factories: Real-Time Automation and Big Data Analytics on the Cloud 15

The Future of Smart Factories: Real-Time Automation and Big ...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Singh, K. Ranjith Arora, Arpit Goud, Dilip Ambika, Krovvidi S B Sandeep, V. More, Priyanka Karpagam Academy of Higher Education Department of Computer Science Coimbatore641021 India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India NNRG Engineering College India ADITYA COLLEGE of ENGINEERING and TECHNOLOGY Department of CSE-AI&ML & DS Surampalem India School of Engineering and Technology Mechaical Engineering Karnataka Bangalore India Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350370249

The evolving future of manufacturing will be all about intelligent factories featuring state-of-the-art technologies. Smart factories combine connected automation and big data in the cloud to streamline production, increase productivity, and lower operational costs. Real-time automation utilizes state-of-the-art sensors, internet of Things (IoT) devices, and artificial intelligence (AI) technology to monitor and control machines or processes in real time independently. This results in faster potential decision-making and bright maintenance works, thus decreasing downtime risk and increasing overall productivity. Big data analytics in the cloud enables real-time collection and analysis of extensive amounts of production processes, machine performance, and supply chain management-related information. The data can then be utilized to discover areas that need improvement, predict maintenance requirements, and even optimize the level of inventories in the sense that it would save costs while at the same time becoming more efficient. Also, real-time automation combined with significant cloud data analytics results in improved communication and collaboration from one production stage to another, hence smooth operations. In other words, it helps create an even more agile and adaptable manufacturing environment where processes can be fine-tuned on the fly to deal with dynamic market shifts. © 2024 IEEE.

关键词： Smart manufacturing

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Understanding the Connection Between Search and Consumer Behavior Models in E-commerce 15

Understanding the Connection Between Search and Consumer Beh...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Sollapur, Shrishail B. Ghosh, Rajkumari Yadav, Surjeet School of Engineering and Technology Department of Aerospace Engineering Karnataka Bangalore India Arka Jain University Department of English Jharkhand Jamshedpur India Vivekananda Global University Department of Mechanical Engineering Jaipur India

ISBN: (纸本)9798350370249

The patron conduct models utilized in ecommerce are based totally on the notion that know-how and predicting patron pastime requires information and modeling individual customer activity throughout the complete variety of sports, from looking for merchandise to creating a buy. Consequently, a better knowledge of seek conduct can help in enhancing client conduct models, which, in turn, can benefit marketers by using a manner of providing greater unique predictions of customer behavior. In this newsletter, we offer a definition of the connection between search and customer conduct fashions determined in e-trade. We discover the techniques used to style how search statistics can be used to tell client conduct models, in addition to the outcomes of looking for facts on improving the accuracy of consumer behavior predictions. In the end, we communicate approximately the fee of searching to expand personalized models for every patron in e-commerce. © 2024 IEEE.

关键词： Behavior Connection E-Commerce Patterns Personalized Predictions Understanding

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Predictive Intelligence Enhanced Fuzzy Model for Underwater Network Optimization 5th

Predictive Intelligence Enhanced Fuzzy Model for Underwater ...

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5th International Conference on Data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Praveena, K.N. Mishra, Awakash Kamalraj, R. Belwal, S. Ankit School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Department of Computer Science and Information Technology Jain University Karnataka Bangalore India Department of Civil Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Manduwala Dehradun Navgaon India

ISBN: (纸本)9789819780426

This paper gives a predictive intelligence-enhanced fuzzy version for underwater network optimization. It combines predictive intelligence technology with fuzzy common sense, which can lessen the functionality gap of underwater community optimization. This proposed version is implemented in an underwater cooperative tracking community. With the proposed model, objectives can be tracked with sensors within the network, and their national statistics can also be appropriately anticipated. Similarly, the version has excessive scalability and robustness because of the mixing of predictive intelligence. In the end, simulation experiments suggest that the proposed model correctly improves the precision of tracking challenges and improves the scalability of the network. The Predictive Intelligence superior Fuzzy model (PIE-FUZMO) for underwater network optimization is a singular method developed to cope with the complex optimization issues confronted through underwater networks. The PIE-FUZMO uses a couple of laptops with imaginative and prescient sample recognition techniques and fuzzy good judgment to enhance the underwater community performance while decreasing the running fee. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Scalability

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Flammability Studies of Natural Fiber-Reinforced Polymer Composites fabricated by Additive Manufacturing technology: A Review

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Journal of The Institution of Engineers (India): Series D 2024年第2期105卷 1291-1303页

作者： Kanaginahal, Gangadhar M. Tambrallimath, Vijay Murthy, Madhav Mahale, Rayappa S. Patil, Adarsh Pawar, Suyash Y. Kakkamari, Prashant P. Department of Mechanical Engineering Jain College of Engineering and Research Karnataka Belagavi India Department of Aeronautical and Automobile Engineering Manipal Institute of Technology Manipal Academy of Higher Education Karnataka Manipal India Department of Buisness Design Welingkar Institute of Management Development and Research Karnataka Bengaluru India School of Mechanical Engineering REVA University Karnataka Bengaluru India School of Mechanical Engineering KLE Technological University Karnataka Hubli India Department of Mechanical Engineering MVPS’s KBT College of Engineering Maharashtra Nashik India Department of Mechanical Engineering Kls Gogte Institute of Technology Belagavi Karnataka Belagavi India

Natural fiber-reinforced polymer composites (NFRPCs) have garnered greater attention lately due to higher strength, good aspect ratio, easy availability, sustainable in nature, and excellent flame-retardant properties. Polymers decompose thermally when heated by creating smoke and volatiles. A polymer, naturally occurring biopolymer known as casein, forms char after burning. Under certain conditions, the phenomenon known as the "scaffolding effect" can give rise to the creation of a charred structure. This structure is formed when the fiber reinforcement of a composite material prevents the molten degradation products of the polymer from coming into direct contact with the heat source, potentially leading to an increase in the material’s thermal resistance. Additive manufacturing (AM) is one prominent process, which helps in fabricating any complex structure with ease. NFRPC composites exhibit multifaceted applicability across a range of fields, including construction, aerospace, automobile, and biomedicine. Nevertheless, it is crucial to consider the inadequate fire resistance of these materials, given their inextricable link to the preservation of human life and safety. Understanding the various flammability testing procedures for NFRPC has been a primary goal of this review paper. The article also focuses on various AM processes utilized for fabricating NFRPC. © The Institution of Engineers (India) 2023.

关键词： Reinforcement

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Autonomous UAV-based Network Path Optimization for Telecommunications Systems 15

Autonomous UAV-based Network Path Optimization for Telecommu...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Sharma, Mukesh Kumar Singh, Vishvendra Beemkumar, N. Arka Jain University Department of Mechnical Engineering Jharkhand Jamshedpur India Vivekananda Global University Department of Agriculture Jaipur India School of Engineering and Technology Department of Mechanical Engineering Karnataka Bangalore India

ISBN: (纸本)9798350370249

Self-sufficient UAV-based community path optimization for Telecommunications structures is a revolutionary method to enhance community overall performance at the brink of cell telecommunications networks. This approach utilizes unmanned aerial vehicles (UAVs) to discover the most suitable community paths, screen and discover community congestion and outages, and automatically reconfigure network bottlenecks in real time. UAVs equipped with radio-frequency sensors, cameras, and other generations can offer quite accurate metrics from their vantage point and feed these into a machine-mastering optimized computerized route optimization set of rules. This set of rules is designed to discover congestion inside the network and promptly alter the routing in keeping with the greenest paths to be had at the time. With the capability to dynamically adjust the ideal path selection in real time, networks are able to manage congestion and reduce latency in delivering offerings to their clients. © 2024 IEEE.

关键词： Community Congestion Generations Optimization Performance Promptly Revolutionary Telecommunications

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Designing Strategies for Power Optimization Utilizing Formal Methods in Embedded Computer Systems 15

Designing Strategies for Power Optimization Utilizing Formal...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Bishnoi, Sunita Manu, S.E. Kumari, Anupam Vivekananda Global University Department of Chemistry Jaipur India School of Engineering and Technology Department of Civil Engineering Karnataka Bangalore India ARKA JAIN University Department of Mechnical Engineering Jharkhand Jamshedpur India

ISBN: (纸本)9798350370249

In recent years, embedded laptop structures have emerged as an increasing number of complicated and strength-hungry, posing a vast assignment for designers. Dealing with power intake has end up a critical thing within the design of embedded systems, as it significantly influences battery existence and device performance. Formal techniques, a mathematically total technique to device design and verification, can resource designers in reaching strength optimization in embedded systems. This paper presents several strategies for using formal techniques in designing powergreen embedded structures. The first method entails modeling the machine at different ranges of abstraction and the usage of formal strategies inclusive of model checking and theorem proving. It Ulets in for early detection of electricity-related layout problems and allows designers to make knowledgeable decisions. The second strategy involves using formal energy analysis techniques to pick out and analyze power bottlenecks within the gadget. It may help optimize the machine by figuring out electricity-hungry components and optimizing their utilization. Every other approach is the use of formal synthesis, which entails routinely generating a poweroptimized implementation from an excessive-stage specification. It eliminates manual layout efforts and guarantees correctness by means of production. Additionally, formal strategies may be used for dynamic energy control, where runtime verification strategies can be applied to ensure that the system is operating within designated strength limits. Furthermore, formal techniques may be applied to the design of electricity. © 2024 IEEE.

关键词： Designing Electricity Embedded Knowledgeable Production Strategies Techniques

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Investigating the Security Considerations of Interactive Communication Media Algorithms for Networking Applications 15

Investigating the Security Considerations of Interactive Com...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Dheer, Meenakshi Sollapur, Shrishail B. Sharma, Mukesh Kumar Vivekananda Global University Department of Agriculture Jaipur India School of Engineering and Technology Department of Aerospace Engineering Karnataka Bangalore India Arka Jain University Department of Mechnical Engineering Jharkhand Jamshedpur India

ISBN: (纸本)9798350370249

This technical abstract discusses the safety considerations of interactive verbal exchange media algorithms for network programs. The focal point is given to have a look at the algorithms used for authenticating, figuring out, and authorizing user-level sports. The research concentrates on analyzing the design goals, information float, consider fashions, and network protocols that comfy the interactive verbal exchange media algorithms to defend personal facts and interactions. In addition, important protection controls are recognized and mentioned, which include authentication, confidentiality, right of entry to manipulate integrity, availability, and non-repudiation. Lastly, the paper concludes with an evaluation of satisfactory practices for growing cosy algorithms to shield system convergence and get entry to assets over a network. © 2024 IEEE.

关键词： Authentication Protocol

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Current Techniques of Interactive Communication Media Algorithms for Networking Applications 15

Current Techniques of Interactive Communication Media Algori...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： David, Roshita Tirkey, Rashmi Sharma, Mohit Kumar School of Engineering and Technology Department of Civil Engineering Karnataka Bangalore India ARKA JAIN University Department of Pharmacy Jharkhand Jamshedpur India Vivekananda Global University Department of Electrical Engineering Jaipur India

ISBN: (纸本)9798350370249

The advancement of conversation media algorithms for networking applications has supplied an array of competencies for present-day interactive communication networks. Networking applications use current interactive verbal exchange media algorithms to create extra sturdy, comfortable, and efficient networks. Those algorithms provide a variety of features to enhance network overall performance and provide a powerful manner to ship and get hold of data over networks. Present-day communication media algorithms employ dynamic community techniques such as adaptive protocols, allotted networking architectures, self-organizing structures, and dynamic protocols. Such algorithms enable conversation networks to research and adapt to changing community conditions and adapt their transmission and conversation techniques as a result. Furthermore, contemporary interactive verbal exchange media algorithms can detect and mitigate malicious visitors, detect misbehaving clients, and offer ease of cease-to-end community provisioning. Moreover, contemporary communication media algorithms can assist more than one kind of multimedia content, which includes streaming video, audio, and text with the use of codecs and XML records schemas. Such algorithms can also support voice-over IP (VoIP), record transfer, and other superior realtime conversation strategies. Current communication media algorithms have also unlocked the potential for superior application assistance. © 2024 IEEE.

关键词： Audio streaming

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