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2nd International Conference on Emerging Trends in Information technology and Engineering, ic-ETITE 2024

作者： Mariammal, G. Sridevi, S. Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Chennai India

ISBN: (纸本)9798350328202

In research, the examination of agriculture is increasing rapidly. Crop yield prediction is an important aspect in agriculture. In earlier days, farmers get good yielding. due to the inefficiency in soil nutrients level and climatic changes crop yield level decreasing day by day. Hence, estimating the production is a crucial role in agriculture area also it helps to farmer for storing and marketing their yielded products. For predicting the precise agricultural yield, a variety of techniques, including remote sensing and machine learning, are used. This paper discussed a number of strategies for predicting crop yields that had been used by various researchers. In accordance to this review, the deployment of machine learning in agriculture indicates more effective and precise farming with fewer human assistance, as well as higher quality goods. © 2024 IEEE.

关键词： remote sensing

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A Novel Parasitic Mushroom-Like Structure with High Gain Microstrip Patch Antenna for Broadband Applications

A Novel Parasitic Mushroom-Like Structure with High Gain Mic...

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International Conference on Machine Learning and Big data Analytics, ICMLBdA 2023

作者： Sahaya Sheela, M. Syam Sudheer Babu, G. Sai durga Prasad, S.N.V. Vasanth Kumar, M.d. Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr Sagunthala R&D Institute of science and Technology Chennai India

ISBN: (纸本)9783031513374

In this research, a design for a microstrip patch antenna loaded with a parasitic mushroom-like structure is proposed. Antenna components include a rectangular microstrip patch as the main radiating element and one or more metallic patches as parasitic elements, separated by a dielectric layer. The parasitic patches are arranged in a pattern that resembles a mushroom growth, and their dimensions are optimized to improve the antenna’s performance. According to simulation results, the suggested antenna has a bandwidth of up to 20% and a high gain of up to 10dBi, which is much broader than that of a typical microstrip patch antenna. The radiation characteristics of the antenna are also improved, with a more uniform radiation pattern and higher front-to-back ratio. The suggested antenna design is appropriate for a variety of uses, including wireless communications, radar systems, and satellite communications, which call for high gain and broad coverage. The simplicity and low profile of the antenna make it easy to manufacture and integrate into various systems. Overall, the proposed parasitic mushroom-shaped microstrip patch antenna, which has broadband and high gain, is a promising solution for achieving improved antenna performance without increasing the antenna’s size or complexity. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Slot antennas

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A Novel Blockchain-Assisted deep Learning Model For Secure Edge Intelligence in IoT Networks

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Journal of The Institution of Engineers (India): Series C 2024年 1-14页

作者： Sekhar, G. Chandra Aruna, r. Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R & ampD Institute of Science and Technology Tamilnadu Chennai India

The Internet is being connected to billions of mobile and Internet of Things (IoT) devices, generating zillions of Bytes of data at the network edge. This is in addition to developments in mobile computing and the Internet of Things (IoT). In the context of edge computing, applications are placed closer to data sources such as IoT sensors, local edge devices, and edge servers. data are transmitted from edge devices to dedicated computer infrastructures for a range of activities in any edge computing environment. For the reason that data are regularly sent from IoT edge devices to centralized virtualization technologies, it is more vulnerable to security vulnerabilities and complexity measures. Finally, to preserve the privacy of the IoT devices, the performance of the proposed algorithms is evaluated using datasets in a large-scale network prototyped system. According to the data, the suggested strategy is both more effective and secure than the alternatives. © The Institution of Engineers (India) 2024.

关键词： Internet of things

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Suppression of Harmonics in an Air-Filled dual Triangular Slotted Substrate-Integrated Waveguide-Based C-Band Filter for Satellite Applications

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Journal of The Institution of Engineers (India): Series B 2023年第1期104卷 269-275页

作者： Souprayen, Oudaya Coumar Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology Chennai India

A compact configuration of dual triangular slotted C-band filter using substrate-integrated waveguide for high-frequency harmonics suppression is presented. The C-band filter with unique dual triangular-shaped structure is used to optimize the performance in terms of harmonic suppression. Triangular slots are defected on top of C-band filter for harmonic suppression. SIW arrangement in the design provides extra control mechanisms to achieve desired response. The filter has very sharp pass band ranged from 3.65 to 8.28 GHz for insertion loss of 1.75 dB and return loss of 34.46 dB. The dimensions of proposed C-band filter are (30 × 25 × 1.6) mm3. A smooth agreement is observed between simulation and measurement results with good harmonic suppression. The proposed filter suppressed higher-order harmonics till 16 GHz at − 20 dB level. © 2022, The Institution of Engineers (India).

关键词： Bandpass filters

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IoT Enabled Three Phase Smart Electrical Consumption Monitoring System Using AdE9000 15

IoT Enabled Three Phase Smart Electrical Consumption Monitor...

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

作者： Maitreya, Jaldu Krishna Nath, Gunda Uday Kanagachidambaresan, G.r. Arun, C.A. Arvind, A.r. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Dept of Ece Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Dept of Cse Chennai India Ashok Leyland Ennore India

ISBN: (纸本)9798350370249

In today's industries, optimizing energy consumption is critical, but outdated monitoring devices cause inefficiencies. Our paper proposes an IoT-based solution utilizing the AdE9000 chip for real-time monitoring of energy parameters like current, voltage, frequency, power, power factor and power quality. By leveraging the AdE9000's high accuracy and unique power quality measurement capabilities, industries can identify areas of overconsumption and implement targeted efficiency measures. For example, real-time power quality analysis aids in detecting and mitigating issues such as voltage fluctuations, thereby reducing downtime. data analytics enables industries to make informed decisions, optimize operations, and cut costs, demonstrating IoT's transformative potential in improving industrial energy efficiency and sustainability. Our approach for this idea aligns perfectly with the capabilities of the AdE9000 chip. Overall the AdE9000 can provide real-time alerts in addition to sending data to the cloud for every 100 milli seconds, which is pivotal in bolstering the performance, efficiency, and sustainability of industrial operations. Our solution, powered by the AdE9000 chip, ensures industry-leading accuracy, with a precision rate of 99.89%, enabling precise monitoring of energy parameters. This high level of accuracy enhances decision-making and empowers industries to achieve unparalleled efficiency gains and sustainability objectives. © 2024 IEEE.

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5G ready: A Compact Two-Port Antenna for Sub-6GHz Applications

5G Ready: A Compact Two-Port Antenna for Sub-6GHz Applicatio...

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2025 International Conference on Multi-Agent Systems for Collaborative Intelligence, ICMSCI 2025

作者： Murugan, C. Kavitha, T. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Chennai India

ISBN: (数字)9798331509828

ISBN: (纸本)9798331509828

The new design is proposed based on Two-port antenna and Simulation outcome with an operating frequency range of 3.3-5.,5GHz, which covers N77, N78, N79 and Wireless Local Area Network (WLAN) bands. The newly coined antenna design achieves gain of 3dB and ensure trustworthy and effective communication in 5th Generation networks. Multiple Input and Multiple output (MIMO) parameters like Envelope Correlation Coefficient (ECC), Total Active reflection Coefficient (TArC)., diversity gain, Channel Capacity Loss (CCL) and radiation Efficiency which are measured in a multi-antenna system. The proposed antenna design illustrates excellent MIMO performance which achieves 5G Privileges likeenhanced mobile broadband (eMBB), ultra-reliable low-latency communications (UrLLC), and massive machine-type communications (mMTC). The Compact Size and Antenna radiation which makes it fit into 5G devices, like smartphones, tablets, and laptops. © 2025 IEEE.

关键词： Wireless local area networks (WLAN)

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A Feature Selection technique–Based Approach for Author Profiling Using Word Embedding techniques 8th

A Feature Selection Technique–Based Approach for Author Pro...

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8th International Conference on Computers, Management and Mathematical sciences, ICCM 2022

作者： Kavuri, Karunakar Kavitha, M. CSE Department Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India

ISBN: (纸本)9783031511660

Textual data are tremendously increasing on the World Wide Web through different social networking platforms, such as blogs, review sites, Facebook, Instagram, Twitter, etc. Crimes or frauds are also growing with the development of text in these platforms. Most of the users on these platforms create accounts with false information and send harassing and threatening messages. Knowing the details or basic information of text posted on these platforms is a very important task to control fraud. Author profiling (AP) is one technique used by the research community and social network administrators to know the author’s information related to messages posted on social networking platforms. Author profiling is a method of detecting demographic profiles such as age, gender, education, etc., of authors based on their written texts. Author profiling techniques are used in various applications of text processing, such as marketing, forensic analysis, and security-related fields. Most author profiling techniques use the content information of text to differentiate the writing styles of authors. The dataset contains a huge number of content words and, the identification of relevant words for differentiating the writing style of different authors is one challenging task to the research community. Feature selection algorithms are proposed by the researchers to find relevant features in the dataset. In this article, we developed a feature selection technique–based approach by using word embedding techniques for predicting the gender and age from the selected dataset. The PAN competition author profiling datasets are considered in this article for experimentation. In the proposed approach, word embedding techniques are used for converting words into word vectors. The similarity measure is used for finding the similarity among the word vectors. Similar words are grouped into clusters. Select the most important words from these clusters and consider them for experimentation. Selected w

关键词： Embeddings

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Improving Energy Efficiency in Wireless Sensor Network with Intelligent Energy Prediction Using Machine Learning Approach

Improving Energy Efficiency in Wireless Sensor Network with ...

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2024 International Conference on Computational Intelligence for Green and Sustainable technologies, ICCIGST 2024

作者： Panneerselvam, Bhuvaneswari devarasu, Neelamegam Pasupulati, Baburao Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electronics and Communication Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electrical and Electronics Engineering Chennai India

ISBN: (纸本)9798350381887

In our day-to-day life, one of the emerging roles of green energy in wireless sensor network shoves the investigations of recent technological and economical solutions for solar energy. Saving external energy is one of the fundamental factors in any wireless sensor network with limited storage capacity. due to different environmental conditions, the energy conversation is too fast in the solar system and unconstrained atmospheric resource energy leads to operate the rechargeable batteries in the outdoor systems. However, some fluctuations occur in the environmental side. It is very crucial to predict the unnecessary errors in the sensing devices. Also, to examine the future energy and to maintain the system reliability in the solar powered wireless sensor network, the accurate prediction models are required. In this work, the Energy Efficient Nonlinear Autoregressive (EENA) algorithm using Machine Learning approach is proposed. With this approach, the algorithm effectively predicts the future energy status with respect to different time slots. The proposed algorithm gives a promising solution to prolong a battery life and the accurate predictions in the outdoor energy harvesting network. © 2024 IEEE.

关键词： Energy Harvesting Error Prediction Machine Learning Sensor network Solar

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Machine Learning in Human resources Management for Higher Education institutes 1

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7th International Conference on Intelligent Computing and Optimization, ICO 2023

作者： Karthikeyan, M. Mariyappan, M.S.r. Sridevi, J. Kumar, S. Vishnu School of Management Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi600062 India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi600062 India

ISBN: (数字)9783031733185

ISBN: (纸本)9783031733178

This research article explores the intersection of Machine Learning (ML) and the Internet within the domain of Human resource Management (HrM) in Higher Education institutes (HEIs). It investigates how these technologies can reshape Human resource (Hr) practices, specifically focusing of faculty retention. The ML model is designed to act upon the collected data to provide immediate support in aiding Hr professionals in predicting and managing employee retention. The research also highlights the importance of data collection using Internet, ensuring speeding and ethical data handling practices. The article encompasses a comprehensive review of existing literature, detailed methodology, practical implementation, and rigorous assessment of the proposed model, aiming to provide a holistic view of this transformative landscape in HrM. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Adversarial machine learning

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detection of Tongue-Based Myeloid Sarcoma Using Novel Cat Swarm Optimization and Comparison with Particle Swarm Optimization Algorithm 7

Detection of Tongue-Based Myeloid Sarcoma Using Novel Cat Sw...

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7th International Conference on Circuit Power and Computing technologies, ICCPCT 2024

作者： Nalini, N. deva Shahila, d Ferlin Ashwini, A. Vaishnavi, T. rosi, A. Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Electronics and Communication Engineering India

ISBN: (纸本)9798350372816

the exact scope of this research work is to compare novel cat swarm optimisation to particle swarm optimisation for tongue-based Myeloid Sarcoma detection. To perform the detection of tumor and leukemia, ten sample tongue datasets were subjected to novel Cat Swarm Optimisation and Particle Swarm Optimisation (PSO) methods, and the fiducial interval remaining at 95%. According to the simulation's performance metrics, Novel Cat Swarm Optimisation outperforms PSO (79%) in terms of accuracy, with a significant level of p = 0.001 (p0.05) in SPSS statistical analysis. From this study, the accuracy of detection of tumor and leukemia using Novel Cat Swarm Optimization showed better results than the PSO algorithm for the considered sample images. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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