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5th International Conference on Data Intelligence and Cognitive Informatics, ICDICI 2024

作者： Balamurugan, K.S. Ramesh, T. Sathish Kumar, P.J. Surendran, R. Tamilvizhi, T. Karpaga Vinayaga College of Engineering and Technology Department of Electronics and Communication Engineering Tamil Nadu Chengalpattu India R.M.K Engineering College Department of Computer Science & Engineering Tamil Nadu Chennai India Panimalar Engineering College Department of Computer Science and Engineering Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350389609

Cancer is one of the global health issues with various complications that lead to fatal. A novel approach is initiated using deep learning techniques. They help in the analysis of complex biological structures which helps to provide potential anti-cancer drugs. They help in the screening of emergent compounds through therapeutic potential. The first stage in the proposed system involves the development of comprehensive datasets that include multi-omics data and protein-protein interaction network structures. They proceeded with preprocessing and feature extraction that led to the contribution of cancer progression stages. The deep learning model involves learning from cancer-associated genes and pathways. They help in the prediction of protein targets that are decisive for cancer development. In the subsequent stage, the deep learning model helps in employing a screen for the collection of emerging compounds from diverse platforms ranging from synthetic libraries. Another stage involves the validation process that leads to in vivo and in vitro experiments. They are proceeded with cellular assays. Compound efficacy is obtained through xenograft and mouse models followed by molecular biology techniques such as protein profiling and gene analysis. Thus the system provides a cumulative approach in obtaining anti-cancer drug targets. © 2024 IEEE.

关键词： Mammals

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A Robust and Efficient Computational Offloading and Task Scheduling Model in Mobile Cloud Computing

A Robust and Efficient Computational Offloading and Task Sch...

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2023 International Conference on Artificial Intelligence and Knowledge Discovery in Concurrent engineering, ICECONF 2023

作者： Chandra, I. Karthikeyan, K.V. Revathi, V. Shankar, K. Tamilselvi, M. Arunkumar, J.R. Department of Computer and Communication Engineering Rajalakshmi Institute of Technology Chennai India Department of Electronics and Communication Engineering Sathyabama Institute of Science and Technology Chennai India Department of Information Technology Veltech Multitech Dr. Rangarajan Dr. Sakunthala Engineering College Chennai India Department of Computer Science and Engineering Easwari Engineering College Chennai India Department of Electronics and Communication Engineering Srm Institute of Technology Ramapuram Campus Chennai India Department of Computer Science and Engineering Modern Institute of Technology and Research Centre Rajasthan Alwar India

ISBN: (纸本)9798350334357

Mobile cloud computing (MCC) has the potential to greatly enhance the computational capabilities of smart mobile devices (SMDs) and reduce their energy consumption by offloading compute-intensive workloads from SMDs onto the resource-rich cloud. Energy-efficient compute offloading remains a problem, especially when applications are under strict time constraints. In response to this issue, this research proposes an Efficient Computational Offloading and Task Scheduling model (ECOTS) strategy to cut down on power use and minimize the time it takes to finish an application. First, we formalize the ECOTS issue as a reduction of energy consumption under the constraints of a task-dependency criterion and an absolute time limit. To solve the issue of offloading computing from mobile devices, we present it as an optimization problem. We then offer two efficient offloading strategies to address the issue. Numerical experiments are used to determine how effective the suggested algorithms are. Finally, we demonstrate using data from a working testbed that the ECOTS method can effectively reduce energy expenditures by properly adjusting the CPU clock speed of SMDs in remote computation and by improving the transmission energy for wireless range circumstances in the cloud. © 2023 IEEE.

关键词： Mobile cloud computing

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Printed MIMO Antenna for C and X band Applications 14

Printed MIMO Antenna for C and X band Applications

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14th International Conference on Computing communication and Networking Technologies, ICCCNT 2023

作者： Rajalakshmi, J. Ranjani, S. Siva Selvi, S. Arun Mozhi Muthuraja, T. Sethu Institute of Technology Department of Electronics & Communication Engineering Kariapatti Virudhunagar India Sethu Institute of Technology Department of Computer Science and Engineering Kariapatti Virudhunagar India Holy Cross Engineering College Department of Computer Science and Engineering Thoothukudi India

ISBN: (纸本)9798350335095

In this paper, MIMO (Multiple-Input Multiple-Output) antenna is introduced. The proposed MIMO antenna is to achieve a multiband response and high efficiency. This antenna is fabricated on FR4 substrate with the thickness of 0.8 mm. The size of the antenna is 30*30mm2. The field distribution of proposed antenna is observed. The fabricated antenna results is tested and compared. The proposed antenna is suitable candidate for C and X band applications. © 2023 IEEE.

关键词： Microwave antennas

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A Switched Capacitor Based Single-Switch Ultrahigh Step-Up DC-DC Converter 7

A Switched Capacitor Based Single-Switch Ultrahigh Step-Up D...

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7th IEEE International Electrical and Energy Conference, CIEEC 2024

作者： Fu, Yu Ren, Zepei Hao, Shicheng Li, Shouxiang Xie, Wenhao School of Automation Beijing Institute of Technology Beijing China School of Computer and Communication Engineering Northeastern University at Qinhuangdao Qinhuangdao China College of Electrical and Electronic Engineering Wenzhou University Wenzhou China

ISBN: (纸本)9798350359558

This paper proposes a switched capacitor based step-up DC-DC converter with the advantages of single-switch, continuously adjustable ultrahigh voltage gain and low input current ripple. To achieve high gain characteristics, the converter utilizes a quadratic boost converter on the input side to ensure continuous input current. Additionally, it implants the second winding of a coupled inductor within it, connecting it to the first winding of the coupled inductor and a voltage multiplier. The analysis includes a discussion of the operating principle, the derivation of the steady-state key equations, the voltage and current stress on the components, and the boundary condition. A functional prototype is built to confirm the theoretical analysis. © 2024 IEEE.

关键词： Boost converter

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Revolutionizing Home Connectivity with IoT-Enabled Smart Mirrors for Internet Browsing and Smart Home Integration 5

Revolutionizing Home Connectivity with IoT-Enabled Smart Mir...

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5th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2024

作者： Prabha, M. Manicka Jegadeesan, S. Jayavathi, S.D. Rajkumar, G. Vinoth Jothi, J. Nirmal Krishnan, R. Santhana SCAD College of Engineering and Technology Department of Computer Science and Engineering Cheranmahadevi India Velammal College of Engineering and Technology Department of Information Technology Madurai India JP College of Engineering Department of Electronics and Communication Engineering Ayikudi Tenkasi India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Chennai India SCAD College of Engineering and Technology Department of Electronics and Communication Engineering Cheranmahadevi India

ISBN: (纸本)9798350395235

This research study explores the transformative potential of IoT-Enabled Smart Mirrors to redefine home connectivity by enabling seamless internet browsing and smart home integration. It introduces a novel model algorithm, IoT-ViSense (IVS), which leverages IoT sensor data fusion with vision-based Convolutional Neural Networks (CNN) for real-time environmental monitoring and security. A comprehensive simulation analysis of IoT-ViSense is conducted and compared against existing algorithms using pertinent simulation metrics. IoT-Enabled Smart Mirrors serve as multifunctional interfaces, integrating personalized weather updates, news, calendar schedules, and real-time compliments. They also incorporate features such as a built-in camera for capturing high-quality selfies, on-demand workout sessions facilitated by fitness experts, and the ability to browse the internet, make calls, and interact with other connected devices. The proposed IoT-ViSense (IVS) algorithm combines IoT sensor data with Vision-based CNN analysis to enhance environmental monitoring and security. It continuously processes data from IoT sensors and camera feeds, detecting anomalies and patterns in real-time. By fusing these data streams, IVS enhances security by identifying unauthorized access and suspicious activities while concurrently optimizing resource usage and ensuring comfortable living and working environments. The simulation analysis of IoT-ViSense (IVS) is compared with suitable existing algorithms, assessing its efficiency in terms of accuracy, response time, and resource optimization. Results reveal that IoT-ViSense (IVS) outperforms other algorithms, demonstrating its prowess in achieving a harmonious blend of smart home integration and real-time environmental monitoring. © 2024 IEEE.

关键词： Convolutional neural networks

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Enhancing Image Segmentation in the Marine Atmosphere for Time-Sensitive Contextualisation using Convolutional Long Short-Term Memory 2

Enhancing Image Segmentation in the Marine Atmosphere for Ti...

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2nd International Conference on Advances in Computation, communication and Information Technology, ICAICCIT 2024

作者： Reethika, A. Rajeshwari, R. Vijayalakshmi, S. Malathy, S. Gnanasaravanan, S. Suresh Kumar, M. Department of Electronics and Communication Engineering Sri Ramakrishna Engineering College Coimbatore India Department of Computer Science and Engineering CMR Institute of Technology Bengaluru India Department of Information Technolog KPR Institute of Engineering and Technology Coimbatore India Department of Biomedical Engineering Karunya Institute of Technology and Sciences Coimbatore India Department of Information Technology Sri Ranganathar Institute of Engineering and Technology Coimbatore India

ISBN: (纸本)9798331541217

The work investigates autonomous surface vehicle obstacle avoidance and detection using computer vision techniques. It recognizes boundaries in marine environments by using the temporal context from video feeds from unmanned surface vehicles. The study shows how successful LSTM cells are in the CNN topologies that are currently in use, emphasizing how they might perform better. Nevertheless, datasets and network training techniques are not perfect. The work also uses a benchmarking approach to compare new network configurations. © 2024 IEEE.

关键词： Image segmentation

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Variational-AutoEncoder Siamese Network for Change Detection on Satellite Imagery

Variational-AutoEncoder Siamese Network for Change Detection...

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2024 IEEE International Students' Conference on Electrical, electronics and computer Science, SCEECS 2024

作者： Choudhury, Aritro Pal Nath Tripathy, Soumyo Mandal, Soumya Kanti Halder, Tamesh De, Shaunak Gayen, Rintu Kumar Chakravarty, Debashish Institute of Engineering & Management Department of Electronics and Communication Engineering Kolkata India Institute of Engineering & Management Computer Science Engineering Kolkata India Iit Kharagpur Ndl India Indian Institute of Technology Department of Mining Engineering Kharagpur India Capella Space San FranciscoCA United States

ISBN: (纸本)9798350348460

Capturing changes in certain areas has assumed huge importance due to both man-made and natural phenomenon. Our novel research is aimed at urban classification using an unsupervised Variational Auto-encoder based Siamese network model for change detection on satellite imagery. It works well on Polarimetric Synthetic Aperture Radar (PolSAR) images of Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) as well as optical satellite images. The model encodes the images to get the latent feature vectors, on which the Siamese difference is performed and the resultant latent space is decoded to get the difference image. The metrics which help us determine how well our model predicts the mask are the recall score and the receiver operating characteristic curve. We have archived a recall score of 0.87 and the area under the receiver operating characteristic curve is 0.98 © 2024 IEEE.

关键词： Change Detection Latent Features Receiver Operating Characteristic Curve Siamese Network unsupervised Variational AutoEncoder

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Machine Learning Methods Analysis for Indian Currency Counterfeiting 14

Machine Learning Methods Analysis for Indian Currency Counte...

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14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Prathibha, T. Prakash, H.N. Padmajadevi Rajeev Institute of Technology Department of Computer Science and Engineering Hassan India Dept. of CSE Rajeev Institute of Technology Department of Computer Science and Engineering Hassan India Malnad College of Engineering Department of Electronics and Communication and Engineering Hassan India

Imitation of currency made with the intention of misleading people is referred to as counterfeit money. One of the risks that harms a country's economy and so slows global growth is counterfeit money. Producing counterfeit money or creating false features for currency is illegal activity, which needs to be properly analysed. Demonetization resulted in an unexpected inflow of fake currency into banks, which in turn lead an increase in doubtful activities. The review focused on the methodology used to detect counterfeit currency, as well as the success rate of each method. Numerous fake currency detection strategies offered by different researchers are presented in the study. This paper discusses the challenge of determining whether or not a particular sample of cash is fake or real. There are various conventional strategies and methods to detect illegal currency based on the basic features like colors, width, and serial numbers specified on the currency. As per the comparative survey analysis KNN and regression methods will give good accuracy for identifying the fake currency. © Grenze Scientific Society, 2023.

关键词： Feature extraction

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An IoT-based Smart Waste Management System for Efficient Waste Segregation and Collection

An IoT-based Smart Waste Management System for Efficient Was...

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2024 International Conference on Innovations in Science, engineering and Technology, ICISET 2024

作者： Hoque, Md. Jiabul Tayef, Sanzid Hossain Noman, Abdullah Al Bhuiyan, Md. Emdadul Hoque Ahmed, Md. Razu Zilani, Md. Abdul Kader International Islamic University Chittagong Department of Computer and Communication Engineering Chittagong Bangladesh International Islamic University Chittagong Department of Computer Science and Engineering Chittagong Bangladesh International Islamic University Chittagong Department of Electronics and Telecommunication Engineering Chittagong Bangladesh International Islamic University Chittagong Department of Electrical and Electronic Engineering Chittagong Bangladesh

ISBN: (纸本)9798350355499

Rapid urbanization in densely populated countries like Bangladesh presents significant challenges for traditional waste management systems. This inefficiency leads to environmental degradation and increased costs. Daily waste generation in urban areas is substantial, yet collection methods remain outdated, relying on fixed schedules and neglecting waste segregation. These practices contribute to soil and groundwater contamination from plastics and polythene. Modernizing waste collection necessitates the adoption of intelligent waste management systems. This paper proposes an Internet of Things (IoT) - based waste monitoring and management solution. Our system promotes waste segregation, reduces collection frequency, and optimizes bin placement. We introduce an intelligent bin that integrates with a central administration system. This bin monitors fill levels and analyzes data to inform bin placement strategies and collection route optimization. The resulting benefits include reduced workforce costs, lower fuel consumption, and minimized air pollution from waste collection vehicles. Additionally, the system alleviates traffic congestion and fosters a healthier living environment. © 2024 IEEE.

关键词： Groundwater pollution

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SpectrumChain: a disruptive dynamic spectrum-sharing framework for 6G

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Science China(Information Sciences) 2023年第3期66卷 26-39页

作者： Qihui WU Wei WANG Zuguang LI Bo ZHOU Yang HUANG Xianbin WANG College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology No.8511 Research Institute of CASIC Department of Electrical and Computer Engineering Western University

The sixth-generation(6G) wireless network will support ubiquitous connectivity and diversified scenarios to satisfy the requirements of various emerging applications. Full spectrum is a key enabler for6G to achieve the ambitious goal of a Tbps-scale data rate. In this paper, we first review the scenario and potential spectrum plan for 6G and then focus on SpectrumChain, a blockchain-based dynamic spectrumsharing(DSS) framework for 6G. The unique characteristics of blockchain for DSS are presented along with key technologies. Finally, the conclusion and future development trends are discussed.

关键词： dynamic spectrum sharing blockchain 6G

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