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2022 IEEE International Conference on electronics, Computing and communication Technologies, CONECCT 2022

作者： Ghosh, Ahona Chatterjee, Siddhartha De, Soumitra Maji, Atindra Kumar Maulana Abul Kalam Azad University of Technology Department of Computer Science and Engineering West Bengal India Imps College of Engineering and Technology Malda Department of Computer Science and Engineering West Bengal India College of Engineering and Management Department of Computer Science and Engineering West Bengal Kolaghat India Techno India Group Department of Electronics and Communication Engineering Jharkhand India

ISBN: (数字)9781665497817

ISBN: (纸本)9781665497817

Recently, research in human-focused robot technologies has aimed to bring closer social-emotional intelligence, which interconnects with human beings' lifestyles doubtlessly. Among several major areas that can benefit from it, the healthcare sector consisting of many possible areas of therapeutic interposition is the most vital one. Recent developments in machine learning have broadened the scope of this work. The present research aims to achieve cognitive rehabilitation for speech disorders using a machine learning approach. Data collected from Electroencephalogram and Kinect sensor has been passed through Chebyshev filter for noise removal, and Autoencoder has been applied to extract features. Finally, Convolutional Neural Network-based transfer learning has shown an accuracy of 96% in classifying speech disorders. The performance of our proposed framework has been quite promising for applying it in real-time scenarios and achieving a better quality of life. © 2022 IEEE.

关键词： Convolutional neural networks

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Seagull Optimization Algorithm for Underwater Sensor Network Localization

Seagull Optimization Algorithm for Underwater Sensor Network...

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2024 IEEE International Conference on communication, Computing and Signal Processing, IICCCS 2024

作者： Alsalami, Zaid Ramya, G. Barolia, Pushpa Arya Yadav, Sachin Satyanarayana, A.N. Pattathu Rani, L. The Islamic University College Of Technical Engineering Department Of Computers Techniques Engineering Najaf Iraq The Islamic University Of Al Diwaniyah College Of Technical Engineering Department Of Computers Techniques Engineering Al Diwaniyah Iraq Prince Shri Venkateshwara Padmavathy Engineering College Chennai India Ies College of Technology Department of Electronics & Communication Engineering M.P. Bhopal India Chandigarh Group of Colleges Chandigarh Engineering College Department of Computer Application Punjab Jhanjeri Mohali140307 India Sreenidhi Institute of Science and Technology Ece Department Hyderabad India Kcg College of Technology Department of Electrical and Electronics Engineering Chennai India

ISBN: (纸本)9798350390759

This paper presents a new technique to a position sensor in UWSNs with the recognition of the Seagull Optimization Algorithm. UWSNs are particularly useful for applications in environmental monitoring and military monitoring, but accurate sensor localization is difficult due to the signal loss in underwater environments and in the presence of external factors. Based on the Motivation Model, the SOA, motivated by the seagulls' distributed foraging behavior, is a possible solution to the dilemma by striking a midway between exploration and exploitation. The synthesis of exact methodology is outlined here along with the creation of synthetic dataset and a proof of concept MATLAB code for the evaluation of the proposed SOA-based localization algorithm. A performance evaluation, which involved the use of computational simulations on a wide variety of antennas, clearly shows that the SOA achieves a higher localization accuracy in much shorter time, while consuming less power compared to other methods such as PSO, GA, or hybrid methods. The stability is one more strongest side of proposed algorithm which has been confirmed by robustness analysis, so it can be effectively used in dynamic underwater environment. The current research is not only useful in showing how the SOA can be used for the UWSN localization in specific domains, but also valuable to the development of the new UWSN localization method that is efficient and accurate, for the further expansion of the UWSN in the vital marine sphere. © 2024 IEEE.

关键词： MATLAB

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Innovative pitcher-shaped antenna with dual notches on a flexible leather substrate for c-band communication

Discover Electronics

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Discover electronics 2025年第1期2卷 1-12页

作者： Saxena, Anurag Agarwal, Raghav Singh, Vinod Kumar Verma, Ramesh Kumar Tiwari, Ratnesh Department of Electrical Engineering S R Group of Institutions Jhansi India Department of Electronics & Communication Engineering University of Technology Jaipur India Department of Computer Science & Engineering IMS Engineering College Ghaziabad India Research and Development Cell Dr. CV Raman University Bilaspur India

This article presents a circularly polarized (CP) flexible antenna in the shape of a pitcher that is suited for use in C-band (4 to 8 GHz) applications. The C-band has a wavelength that ranges from 7.5 to 3.75 cm as stated by the IEEE frequency spectrum. In terms of design, the wearable antenna is straightforward and was fashioned after the texture of leather. There is a pitcher-shaped radiating element which is designed with a defective ground. The process known as microstrip linefeed is utilized in order to provide the power in antenna. The impedance bandwidth of the proposed antenna is observed to be 20.35% (1.36 GHz) ranging from 6 to 7.36 GHz. The reflection coefficient at the resonant frequency of 6.704 GHz is rather remarkable and was observed to be − 30 dB. However, the axial ratio bandwidth of the proposed antenna is observed to be 13.74% (900 MHz) ranging from 6.1 to 7 GHz. The utilization of a parametric report serves to provide justification for the appropriateness of the projected antenna. In order to determine whether or not the newly presented antenna is feasible, it is produced and put through a series of tests using a vector network analyzer. A significant amount of comprehension was discovered through the examination of the recreated and estimated findings. The maximum gain achievable with the suggested antenna is 4.67 dBi. The proposed antenna also provides more than 75% efficiency in resonating band.

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Receiver-Based Data communication for Wireless Sensor Networks 2

Receiver-Based Data Communication for Wireless Sensor Networ...

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2nd IEEE International Conference on Advances in Computing, communication and Applied Informatics, ACCAI 2023

作者： Chitra Kiran, N. Parkash, Jai Cheerla, Sreevardhan Shanmugaraja, P. Manohara, M. Madan, Parul Alliance University Department of Electronics and Communication Engineering Karnataka Bangalore560068 India Gulzar Group of Institutes Department of Computer Science and Engineering Punjab Khanna141401 India Koneru Lakshmaiah Education Foundation Department of Electronics and Communications Engineering Andhra Pradesh Vaddeswaram522302 India Sona College of Technology Department of Information Technology Tamil Nadu Salem636005 India Mohan Babu University School of Engineering Andhra Pradesh Tirupati517102 India Graphic Era Deemed to Be University Department of Computer Science and Engineering Uttarakhand Dehradun248002 India

ISBN: (纸本)9798350315905

As the Web of Things (IoT) has created throughout recent years, unlicensed radio range has become more clogged with brilliant wireless gadgets that are utilized in an assortment of use spaces, prominently the 2.4 GHz ISM band. One of the easiest and most productive answers for energy-compelled networks is the wake-up receiver (WuRx). Rather than utilizing a conventional radio, this innovation empowers energy-independent on-request communication for persistent observing. One of the WSN methods that utilizes the most investment is directing. Consequently, planning an energy-effective steering procedure is fundamental. This exploration proposes grouped WuRx based on Multicast wake-up (CWM), a progressive Wake-up Receiver-based directing convention that all the while streamlines energy use and time productivity for indoor conditions. In our proposed technique, bunches are made inside the organization. Estimation discoveries show that, in contrast with past directing conventions, our proposed arrangement has much better execution as far as conveyance delay and further developed energy effectiveness. © 2023 IEEE.

关键词： Wireless sensor networks

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Real-time Traffic Prediction in 5G Networks Using LSTM Networks

Real-time Traffic Prediction in 5G Networks Using LSTM Netwo...

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2024 IEEE International Conference on communication, Computing and Signal Processing, IICCCS 2024

作者： Kumar, Harsh Al-Jawahry, Hassan M. Manohar, Murli Karthika, K. Victor, Melvin Shetty, Aishwarya D. Chandigarh Group of Colleges Chandigarh Engineering College Department of Computer Application Punjab Mohali India The Islamic University College Of Technical Engineering Department Of Computers Techniques Engineering Najaf Iraq The Islamic University Of Al Diwaniyah College Of Technical Engineering Department Of Computers Techniques Engineering Al Diwaniyah Iraq Ies College of Technology Department of Electronics & Communication Engineering M.P. Bhopal India Prince Shri Venkateshwara Padmavathy Engineering College Chennai India School of Business and Management India Department of Cse Nitte India

ISBN: (纸本)9798350390759

This research explores the application of Long Short-Term Memory (LSTM) networks for real-time traffic prediction within 5G networks, aiming to address the critical need for accurate prediction models in dynamic network environments. Leveraging the sequential learning capabilities of LSTM networks, the proposed methodology encompasses dataset preparation, model architecture design, training, and evaluation. Experimental results demonstrate the effectiveness of the LSTM-based prediction model in capturing temporal dependencies and providing reliable predictions across various prediction horizons. While promising, further research is warranted to enhance the model's performance and address remaining challenges. This study contributes to advancing the state-of-the-art in traffic prediction methodologies, facilitating more efficient network management and optimization in 5G environments. © 2024 IEEE.

关键词： Prediction models

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Comparative Analyses of Multi-Wavelength Converters Based on Electro Absorption Modulators at Various Data Rates

Comparative Analyses of Multi-Wavelength Converters Based on...

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2023 IEEE World Conference on Applied Intelligence and Computing, AIC 2023

作者： Kaur, Taranjeet Kaur, Jatinder Jambu, Mohit Saxena, Aditi Shah, Sanjeev Kumar Saxena, Antima Chandigarh Engineering College Department of Ece Jhanjeri Mohali140307 India Gulzar Group of Institutes Eee Department Punjab Khanna141401 India Gla University Department of Ece Mathura281406 India Uttaranchal Institute of Technology Uttaranchal University Electronics and Communication Engineering Dehradun248007 India Ies College of Technology Department of Computer Science and Engineering Bhopal India

ISBN: (纸本)9798350310061

The performance analysis of an electro absorption modulator based multi-wavelength converter that uses a radio frequency generator has been investigated at various input powers (ranging from -3 dBm to 10 dBm) and at various data rates (5 Gbps, 10 Gbps, and 20 Gbps). This was done in order to eliminate the need for an additional pump signal by utilising the RZ (Return to Zero) modulation format. This was done in order to make the solution a more cost-effective one. In this article, a comprehensive investigation of the trade-off between diverse power and varied data rate has been carried out. The input power and data rate are the two most essential operational parameters for wavelength conversion. Because of this, the effect of input power and data rate on the performance of wavelength conversion is investigated in great depth by monitoring the timing diagrams of the signal that has been wavelength converted. © 2023 IEEE.

关键词： Cost effectiveness

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Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm

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computers, Materials & Continua 2023年第8期76卷 2261-2279页

作者： Ayman Khallel Al-Ani Shams Ul Arfeen Laghari Hariprasath Manoharan Shitharth Selvarajan Mueen Uddin Cybersecurity Research Group Faculty of Computing and InformaticsUniversity Malaysia SabahJalan UMSKota KinabaluSabah88400Malaysia National Advanced IPv6 Centre(NAv6) Universiti Sains MalaysiaGelugorPenang11800Malaysia Department of Electronics and Communication Engineering Panimalar Engineering CollegePoonamalleeChennai600123TamilnaduIndia Department of Computer Science&Engineering Kebri Dehar UniversityKebri Dehar250Ethiopia College of Computing and Information Technology University of Doha for Science and TechnologyDoha24449Qatar

In this paper,the application of transportation systems in realtime traffic conditions is evaluated with data handling *** proposed method is designed in such a way as to detect the number of loads that are present in a vehicle where functionality tasks are computed in the *** to the existing approach,the design model in the proposed method is made by dividing the computing areas into several cluster regions,thereby reducing the complex monitoring system where control errors are ***,a route management technique is combined with Artificial Intelligence(AI)algorithm to transmit the data to appropriate central ***,the combined objective case studies are examined as minimization and maximization criteria,thus increasing the efficiency of the proposed ***,four scenarios are chosen to investigate the projected design’s *** all simulated metrics,the proposed approach provides better operational outcomes for an average percentage of 97,thereby reducing the amount of traffic in real-time conditions.

关键词： Transportation Artificial Intelligence(AI) data-driven Internet of Things(IoT)

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Optimal Fusion Technique for Multi-Scale Remote Sensing Images Based on DWT and CNN 8

Optimal Fusion Technique for Multi-Scale Remote Sensing Imag...

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8th International Conference on Smart Structures and Systems, ICSSS 2022

作者： Basheer, P.I. Prasad, K. Purushotham Gupta, Ayan Das Pant, Bhasker Vijavan, Vinodh P Kapila, Dhiraj Ssm Polytechnic College Tirur Department of Electronics and Communication Engineering Kerala Malappuram India Siddartha Educational Academy Group of Institutions Department of Electronics and Communication Engineering Tirupati India Chandernagore Government College Department of Geography West Bengal Hugli India Graphic Era Deemed to Be University Department of Computer Science and Engineering Uttarakhand Dehradun India Mangalam College of Engineering Kerala Kottayam India Lovely Professional University Department of Computer Science and Engineering Phagwara India

ISBN: (纸本)9781665497619

The practise of fusing multiple photographs of the same scene captured at different focal lengths into a single all-focus image is known as multifocal image fusion. Local filters are utilised in most well-known fusion algorithms to capture high-frequency data before applying various fusion rules to create fused images. By decomposing the source and fusion images into numerous states, this work uses a discrete wavelet to create high-frequency and low-frequency images. The core CNN architecture in this study includes multistate extraction features & learning in residual, resulting in a multi scale & depth pan sharpening CNN data through remote sensing. Features from the images are extracted using D W T algorithms which is pre-trained. MATLAB is used to implement the suggested DWT -based picture fusion algorithm. © 2022 IEEE.

关键词： Wavelet domain Frequency-domain analysis Transforms Feature extraction Discrete wavelet transforms Convolutional neural networks Intelligent structures

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Blockchain-based security solutions for IOT networks: Analysing efficacy and implementation challenges

Blockchain-based security solutions for IOT networks: Analys...

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2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Kumar, Gotte Ranjith Chamaraju, Y.S. Mulani, Umar M Naveenkumar, R. Datta, Auadhati Kanwer, Budesh Sr University School of Cs & Ai Telangana Warangal India Govt Cpc Polytechnic Department of Electronics & Communication Engineering Karnataka Mysore570007 India Kj College of Engineering and Management Research Pune India Chandigarh Group of Colleges Jhanjeri Chandigarh Colleges of Engineering Department of Computer Science and Engineering Punjab Mohali140307 India Vignan's Institute of Information Technology Department of Management Studies Andhra Pradesh Duvvada India Poornima Institute of Engineering and Technology Rajasthan Jaipur India

ISBN: (纸本)9798331508685

Blockchain innovation has gathered significant attention from both scholars and industry professionals after years of development. This technology enables the creation of smart contracts, which facilitate automated deal execution among users. Today, blockchain is also employed as a specialized infrastructure in some IT applications, helping prevent data duplication, similar to how Bitcoin and other cryptocurrencies manage transaction records. Bitcoin records, for instance, are exceptionally secure as the currency circulates across hundreds of thousands of servers, making it nearly impossible to alter. For a successful breach, an attacker would need to manipulate records on 51% of these servers simultaneously. In contrast, private data stored on single servers, such as those managed by Amazon and Google, are more vulnerable to cyberattacks. In this paper, the study propose leveraging blockchain to address security concerns in the Internet of Things. The study identifies and categorizes common security challenges, with a focus on data privacy issues, as well as the protocols used for network organization, communication, and management. Following this, the study outline security solutions for IoT and illustrate scenarios in which blockchain is applied within IoT applications. © 2025 IEEE.

关键词： Smart contract

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Identification and Segmentation of Tumour in Brain MRI using Deep Learning Techniques 2

Identification and Segmentation of Tumour in Brain MRI using...

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2nd International Conference on electronics and Renewable Systems, ICEARS 2023

作者： Mahendran, N. Muthuvel, P. Arunprasath, T. Rajasekaran, M. Pallikonda Nirmala, J. Bridget Kottaimalai, R. Kalasalingam Academy of Research and Education Department of Electrical and Electronics Engineering Tamilnadu Krishnankoil India Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamilnadu Krishnankoil India Kalasalingam Academy of Research and Education Department of Biomedical Engineering Tamilnadu Krishnankoil India Kalasalingam Academy of Research and Education Department of Electronics and Communication Engineering Tamilnadu Krishnankoil India St. Michael Group of Institutions Chief Executive Officer Tamilnadu Kalaiyarkoil India

ISBN: (纸本)9798350346640

Medical image segmentation is an essential task to dissect the infected portion present in the raw medical images. Gliomas are the most widespread and abrasive form of brain tumour, resulting in a very short expected lifespan in their most severe form. As a matter of fact, diagnosis preparation is a vital step in enhancing the overall eminence of lifespan of cancer patients. Magnetic resonance imaging (MRI) is a popular scanning method for examining these tumours, but the large volume of information generated by MRI precludes manual segmentation in an acceptable time period, restricting the utilization of concise quantitative assessments in medical practice. Gliomas and their intra-tumoral structures must be precisely dissected not just to make clinical judgement as well as for further investigations. Moreover, it is a difficult task because the form, structure, and site of these anomalies vary significantly. As a result, fully automated and reliable dissection methods are desired;moreover, the wide structural and spatial diversity between brain tumours makes automatic delineation a tough problem. This work reviews some recent researches on glioma identification and segmentation and also discussed about the performance metrics. © 2023 IEEE.

关键词： Image segmentation

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