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

作者： Ranganathaswamy, M.K. Amin, Rahul Dheer, Meenakshi Department of Mechanical Engineering School of Engineering and Technology JAIN Karnataka Bangalore India Department of Journalisim & Mass Communication ARKA JAIN University Jharkhand Jamshedpur India Department of Agriculture Vivekananda Global University Jaipur India

ISBN: (纸本)9798350370249

—QoS-conscious dispensed and cooperative media algorithms for Wi-Fi networks leverage the particular features of a wireless communications platform to allow the transmission of digital media with the progressed pleasant of a carrier (quality of service). The disbursed nature of those algorithms allows the improved quality of service aid by permitting the distribution of media assets throughout a couple of nodes in a Wi-Fi network cooperatively. Through the sensor-based Wi-Fi community, statistics may be used to tell aid allocation decisions, taking into consideration an optimized utilization of media resources. Allotted media algorithms also permit advanced media shipping strategies inclusive of multiple descriptions coding (MDC) and network coding (NC), supplying advanced video streaming, voice, and other media applications under numerous network conditions. The disbursed, cooperative media algorithms can further be greater with quality of service awareness, leveraging community facts and temporal statistics to successfully allocate media resources to enable progressed quality of service performance. By leveraging the unique capabilities of wireless networks, an advanced QoS-conscious distributed and cooperative media gadget may be constructed to meet the needs of modern-day rising media applications. ©2024 IEEE.

关键词： Wi-Fi

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Security Implications of 5G in Modern Health Care Management Models 15

Security Implications of 5G in Modern Health Care Management...

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

作者： Patil, Nagaraj Moharana, Alok Kumar Chauhan, Aakriti Jain School of Engineering and Technology Department of Mechanical Engineering Karnataka Bangalore India Arka Jain University Department of Pharmacy Jharkhand Jamshedpur India Vivekananda Global University Department of Agri-Business Management Jaipur India

ISBN: (纸本)9798350370249

5G has emerged as a chief fashion in modern healthcare management models. In this context, the safety implications of 5G are getting more vital than ever earlier. 5G networks have the potential to offer many extra comfy surroundings for the transfer of touchy healthcare statistics. To this end, 5G networks are predicted to offer more potent consumer authentication, progressed physical security, advanced encryption protocols, progressed manipulation over get admission to manipulate, and more desirable actual-time facts analytics. Furthermore, 5G networks are anticipated to reduce the overall value of turning in fitness care services, particularly for decrease-profits segments of the population. Furthermore, 5G networks can also allow far-flung patient tracking, reducing the want for in-person visits to fitness care facilities. As a way to ensure the security of 5G networks and fitness care records, healthcare companies must put in force rigorous protection controls throughout the network. For instance, companies should make certain of the use of strong authentication protocols for customers and superior encryption for statistics in transit. Furthermore, vendors ought to monitor user and information entry to and hobby for suspicious activity, in addition to implementing robust entry control measures to reduce the chance of unauthorized entry to fitness care facts. Moreover, carriers must take steps to ensure the integrity of healthcare statistics by means of the use of both hardware and software-based solutions © 2024 IEEE.

关键词： Authentication Emerged Encryption Healthcare Management Manipulate Protocols Statistics

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A Deep Learning Based Approach for Detecting Mango Leaf Diseases 6

A Deep Learning Based Approach for Detecting Mango Leaf Dise...

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6th International Conference on Computational Intelligence and Networks, CINE 2024

作者： Pradhan, Astik Kumar Rout, Jitendra Kumar Ghosh, Debanjan Sinha, Shailendra Kumar Arka Jain University School of computer Science and IT Jamshedpur India National Institute of Technology School of computer Science and Engineering Raipur India

ISBN: (纸本)9798331516796

The mango industry faces substantial annual economic losses due to diseases and pests. Farmers encounter difficulties in differentiating between various mango diseases, as their symptoms can closely resemble each other and even occur simultaneously. By making it possible to quickly and accurately detect and identify mango leaf illnesses, this study aims to offer a remedy. To accomplish this, the research employs state-of-the-art Convolutional Neural Networks (CNNs), which are advanced learning algorithms capable of automatically extracting and understanding complex features from raw images. Specifically, the study utilizes EfficientNet, a model based on CNNs, to facilitate the early identification and classification of mango leaf diseases. Additionally, advanced data augmentation techniques such as rotation, reflection, translation, and scaling are applied to enhance the collected dataset. This enhanced data is then used to train the EfficientNet model, which achieves an amazing 98% accuracy rate in identifying and categorizing mango leaf diseases. These findings underscore the CNN method's effectiveness in detecting a wide range of mango leaf diseases, positioning it as an invaluable and practical tool for both farmers and agricultural experts. © 2024 IEEE.

关键词： Fruits

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Novel Signal Processing Techniques for High Angular Resolution Diffusion-Weighted Imaging 15

Novel Signal Processing Techniques for High Angular Resoluti...

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

作者： Babu, Dushyanth V.R. Thakur, Praveen Kumar Shankar, Shiv Shankar School of Engineering and Technology Department of Civil Engineering Karnataka Bangalore India Arka Jain University Jharkhand Jamshedpur India Vivekananda Global University Jaipur India

ISBN: (纸本)9798350370249

Excessive angular decision diffusion-weighted imaging (HARDWI) is an effective approach for visualizing tissue microstructures, which are otherwise hard to look at the usage of conventional MRI technology. To attain this, HARDWI relies on sign-processing techniques to reconstruct images from tremendously anisotropic diffusion-weighted alerts. Novel signal processing strategies advanced in current years have further advanced the abilities of HARDWI. These strategies leverage the sparsity of diffusion signal in more than one angular guideline, allowing the reconstruction of man or woman diffusion occasions within the specimen's microstructure. Wavelet rework-primarily based strategies allow for the advanced decision of the reconstructed images, extended evaluation, and stepped forward signal-to-noise ratio in the resulting photographs. Other strategies, inclusive of diffusion orientation transform, have been advanced to estimate the orientation of fiber tracts better. Furthermore, spatially-variable regularization techniques have been advanced for advanced estimation of the diffusion parameters at a voxel stage. The combination of these signal processing techniques has advanced the application of HARDWI to a spread of biomedical applications, such as neuroanatomy, tumor imaging, and small animal studies. © 2024 IEEE.

关键词： Image reconstruction

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Algorithms for Natural Language Processing and Mining in Patient Records 15

Algorithms for Natural Language Processing and Mining in Pat...

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

作者： Raghu, N. Chakraborty, Shreya Chauhan, Aakriti Jain School of Engineering and Technology Department of Electrical and Electronics Engineering Karnataka Bangalore India Arka Jain University Department of optometry Jharkhand Jamshedpur India Vivekananda Global University Department of Agri-Business Management Jaipur India

ISBN: (纸本)9798350370249

Herbal Language Processing (NLP) and Mining Algorithms are frequently used to research big collections of patient electronic fitness information (EHR) to acquire insights that could be beneficial to patient care. Mining algorithms can assist to automate the technique of reading huge amounts of patient facts and may provide useful facts from affected person facts that would in any other case be difficult to method. NLP is getting used to extract records from unstructured textual content in patient statistics, that may useful resource in determining sicknesses, symptoms, medicines, and chance elements. by using the usage of NLP and system studying algorithms, all the facts from affected person records may be efficiently and as it should be processed, resulting in study's findings which can assist improve healthcare. NLP and mining algorithms for affected person facts can assist to streamline disorder diagnosis, provide extra accurate records approximately clinical selections, and ultimately improve patient results. © 2024 IEEE.

关键词： Accurate Algorithms Approximately Clinical Elements Facts Person Ultimately

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Efficiently Combining Quantum Mechanics and Algorithm Design for Optimization 3

Efficiently Combining Quantum Mechanics and Algorithm Design...

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3rd International Conference for Innovation in technology, INOCON 2024

作者： Jha, Rakhi Bishnoi, Sunita Vivek, V. Arka Jain University Department of Computer Science & It Jharkhand Jamshedpur India Vivekananda Global University Department of Chemistry Jaipur India Jain School of Engineering and Technology Department of Computer Science and Engineering Karnataka Bangalore India

ISBN: (纸本)9798350381931

Quantum mechanics offers capability benefits for optimization due to its capability to carry out calculations in parallel, but conventional quantum algorithms for optimization have commonly relied on heuristic techniques. Latest advances in algorithm layout have led to the development of new strategies for correctly combining quantum mechanics and set of rules layout for optimization. This paper critiques those new strategies and discusses their capability for enhanced optimization performance. A number of the important thing techniques mentioned encompass quantum annealing, variation quantum Eigen solvers, and quantum walks. Those techniques offer more than a few changes-offs in terms of accuracy and computational complexity. Its miles argued that they could offer positive advantages over traditional optimization algorithms, but careful consideration of the available resources is still critical for attaining the pleasant optimization results. Notwithstanding the modern-day barriers, similarly studies into the capacity of mixing quantum mechanics and set of rules design for optimization holds great promise for the sphere. © 2024 IEEE.

关键词： Optimization

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An Analysis of Image-Based Segmentation Algorithms for Computer Vision Applications 15

An Analysis of Image-Based Segmentation Algorithms for Compu...

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

作者： Deepak, J. Deshmukh, Vishwesh Anandhasilambarasan, D. Kandhari, Harsimrat Jayashankari, J. Goyal, Shitij School of Engineering and Technology Mechaical Engineering JAIN Deemed to be University Karnataka Bangalore India Electrical Vishwakarma Institute of Technology Pune India Department of Computer Science Engineering Karpagam Academy of Higher Education Coimbatore641021 India Centre of Research Impact and Outcome Chitkara University Punjab Rajpura140417 India Department of Information Technology Prince Shri Venkateshwara Padmavathy Engineering College Chennai127 India Quantum University Research Center Quantum University India

ISBN: (纸本)9798350370249

— Photo-based totally segmentation algorithms are an important place in trendy research in laptop vision for an extensive variety of trendy applications together with item popularity, facial recognition, and autonomous navigation. Such algorithms normally hire strategies that contain reading pix to understand edges, shapes, and different features in the surroundings. By means of making use of these techniques, scene objects may be diagnosed and segmented into distinct parts, making an allowance for further analysis and programs. This paper discusses the development and packages of brand-new photograph-based segmentation algorithms, with an emphasis on algorithms based on pattern recognition and machine learning. Examples are supplied to illustrate the present-day country's contemporary art and provide insights into the destiny development of those algorithms. This analysis helps to discover capacity areas for development and provides a top-level view state-of-the-art the overall performance of present-day current algorithms. ©20XX IEEE.

关键词： Image segmentation

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Performance analysis of a solar parabolic trough collector fitted with a helical coiled tube absorber

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International Journal of Ambient Energy 2023年第1期44卷 442-449页

作者： Syed Jafar, K. Venkatesaperumal, R. Beemkumar, N. Santhoshkumar, M. Rajamurugan, T.V. Department of Mechanical Engineering Annamalai University Tamil Nadu Chidhambaram India Department of Mechanical Engineering School of Engineering and Technology JAIN University Bengaluru India Department of Chemistry Government College of Engineering Tamil Nadu Dharmapuri India Department of Manufacturing Engineering Annamalai University Tamil Nadu Chidhambaram India

The SPTC is used for medium- and high-temperature applications. Several works are carried out for the enhancement of heat transfer of SPTC using size variation, absorber with inserts, nanofluid with working medium and different configurations of the absorber. The development of turbulence effect in the working fluid is important for heat transfer enhancement. Therefore, a novel idea is introduced to use a helical coiled tube absorber in the PTC, which enhances the heat transfer between the tube and the flowing fluid by providing swirling motion. The current research work uses the helical coiled tube absorber which consists of 42 turns and 2 m in length, 10 mm in internal diameter and 12.5 mm in outer diameter. It is enclosed by a glass envelope to reduce thermal losses. The experiments are conducted by varying the mass flow rate of water from 0.01 kg s−1 to –0.03 kg s−1. The maximum achieved useful heat gain, water temperature and instantaneous efficiency are 800 W, 64°C and 56%, respectively while using the flow rate of 0.01 kg s−1. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

关键词： High temperature applications

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Network Inference Using Deep Reinforcement Learning for Early Disease Detection 3

Network Inference Using Deep Reinforcement Learning for Earl...

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3rd International Conference for Innovation in technology, INOCON 2024

作者： Sahoo, Jyotirmaya Lora, Chandra Prakash Shankar, Amar Arka Jain Universit Department of Pharmacy Jharkhand Jamshedpur India Vivekananda Global University Department of Chemistry Jaipur India Jain School of Engineering and Technology Department of Food Technology Karnataka Bangalore India

ISBN: (纸本)9798350381931

Community Inference the use of Deep Reinforcement mastering for early sickness Detection is an effective approach for predicting disorder onset early based totally on community dynamics. This technique applies a unique set of algorithms for education deep reinforcement gaining knowledge of fashions. The fashions are educated to locate early disease onset from the community shape and dynamics through reading complicated relationships between nodes inside the network. The fashions assemble a couple of synthetic agents which engage with the nodes inside the community and acquire capabilities based totally on connectivity and hobby. Primarily based on accumulated features, the version classifies the nodes as either wholesome or diseased to construct a sickness-specific chance profile. Similarly, the reinforcement mastering approach is implemented to enhance the performance of the version by way of supplying rewards while the version chooses appropriate movements for the duration of the education. In conclusion, community Inference using Deep Reinforcement mastering for early sickness Detection is an effective tool for predicting and stopping sickness earlier than it becomes enormous. This approach allows sickness professionals to become aware of key individuals in a community and alert them to scientific help, as a consequence preventing the disorder from spreading and growing the chances of survival for the ones affected. © 2024 IEEE.

关键词： Diseases

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Integrating Smart Contracts in IoT Networks Powered by Blockchain technology 3

Integrating Smart Contracts in IoT Networks Powered by Block...

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3rd International Conference for Innovation in technology, INOCON 2024

作者： Sengupta, Pompi Das Chauhan, Aakriti Raja Praveen, K.N. Arka Jain University Department of Management Jharkhand Jamshedpur India Vivekananda Global University Department of Agri-Business Management Jaipur India Jain School of Engineering and Technology Department of Computer Science and Engineering Karnataka Bangalore India

ISBN: (纸本)9798350381931

integrating smart contracts into the Internet of Factors (Iota) networks powered by using block chain technology presents a unique set of challenges and possibilities. Smart contracts offer an automatic technique to facilitate transaction processing and facilitate cozy and reliable statistics sharing across the dispensed Iota community. At the same time, understanding the safety implications of this technology, techniques for addressing such implications, and sensible answers for integration remains an ongoing region of research. Block chain technology is revolutionizing the structure of the Iota. By utilizing clever contracts, block chain can enable trustless, relaxed verbal exchange channels and automatic validation of transactions. It presents a unique method for safely storing, authorizing, and sharing information throughout numerous distributed nodes. Smart contracts also allow the cost-powerful and cozy execution of multiple clever contracts at the identical Iota network. The security of any Iota gadget is substantially impacted by using the integration of clever contracts. This integration calls for the addressing of troubles related to scaling, failure control, and machine integrity. It additionally calls for the robust encryption of records and the authentication of requests through virtual signatures. © 2024 IEEE.

关键词： Smart contract

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