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检索条件"机构=Departments of Computer Science and Engineering and Electronics and Communication Engineering"

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Design and Analysis of Koch Fractal Slots for Ultra-Wideband Applications 5th

Design and Analysis of Koch Fractal Slots for Ultra-Wideband...

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5th International Conference on Microelectronics, Electromagnetics and Telecommunication, ICMEET 2019

作者： Terlapu, Sudheer Kumar Subba Rao, M. Venkata Chowdary, P. Satish Rama Satapaty, Suresh Chandra Department of Electronics and Communication Engineering Shri Vishnu Engineering College for Women Bhimavaram India Department of Electronics and Communication Engineering Raghu Institute of Technology Visakhapatnam India Department of Computer Science and Engineering KIIT Bhubaneswar India

ISBN: (纸本)9789811538278

In this paper, a design of a dual-band Koch fractal antenna is proposed. Patch antenna has dimensions of 30 mm × 18 mm × 0.76 mm which operates in ultra-wideband (UWB) with a notch band from 5 to 6 GHz. Further, the design is modified using different Koch fractal geometries to observe the multi-band resonant behavior of the antenna. The modified antenna has dimensions of 18 mm × 18 mm × 0.8 mm. By modifying the shape of radiating patch and ground with fractal shapes and by introducing slots, impedance bandwidth and radiation characteristics were improved. The proposed antenna works well for WiMAX and WLAN applications with approximately 95% radiation efficiency. The parametric analysis is carried out for various parameters in order to obtain better return loss characteristics. The design is simulated using HFSS software, and the performance is measured by obtaining the antenna parameters. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Microstrip antennas

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Deep Learning for Time Series Classification

Deep Learning for Time Series Classification

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Intelligent Systems for Cybersecurity (ISCS), International Conference on

作者： Rajesh Sharma R Akey Sungheetha Animesh Kumar Sharma L. Chandra Sekhar Reddy Bandaru Satya Lakshmi Sunanda Ratna. Kandavalli Department of Computer Science and Engineering School of Engineering Alliance University Bangalore India Department of Mathematics The ICFAI University Raipur Department of Computer Science and Engineering (Data Science) CMR College of Engineering & Technology Kandlakoya(v) Medchal Hyderabad Department of Computer Science Engineering Aditya College of Engineering Surampalem Andhra Pradesh Department of Electronics & Communication Engineering Sri Padmavati Mahila Visva Vidyalayam Tirupati Andhra Pradesh India

ISBN: (数字)9798350375237

ISBN: (纸本)9798350375244

Time Series Classification (TSC) has been measured as the most demanding crisis in data mining. With the augment of temporal statistics accessibility, thousands of numerical algorithms have been planned since 2016 because of their ordinary temporal ordering; time series data can be found in all kinds of tasks that require some kind of human thinking process. In the recent past, time series categorization became one of the most important problems to be tackled because of various information-keeping categorization problems. Time series can be found in several applications of the present world from the health sector, to personal activity, and detection of anomalies. As temporal data has been made accessible in recent years many new zones are becoming very interested in time series applications and based on that newer numerical chain algorithms have been suggested. Many machines today can be performed without actually touching them and to serve this purpose this machine store a series of pictures that can analyze the user signals. Recognizing the correct signal from the set of pictures can be a time series classification problem

关键词： Accuracy Recurrent neural networks Scalability Time series analysis Standards organizations Hidden Markov models Organizations

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Deep Reinforcement Learning based Energy Efficient Resource Allocation for Wireless Powered Edge Computing Network 4

Deep Reinforcement Learning based Energy Efficient Resource ...

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4th International Symposium on computer engineering and Intelligent communications, ISCEIC 2023

作者： Feng, Xiao Jia, Jing Wang, Tong Li, Jihao Xu, Haitao Li, Qianqian China Electronics Technology Taiji Group Corporation Limited Beijing China Shunde Innovation School University of Science and Technology Beijing School of Computer and Communication Engineering Beijing China Technology Co. Ltd. Shenzhen China

ISBN: (纸本)9798350306323

This paper considers wireless power edge computing networks with time-varying wireless channel environments. A practical non-linear energy harvesting model is introduced, and a joint optimization problem is formulated to minimize the overall cost of energy consumption. To solve the problem, we design a deep deterministic policy gradient (DDPG) algorithm to jointly optimize computation offloading and resource allocation. Numerical results show that the proposed schemes can significantly ensure the timeliness of data and effectively achieve lower energy consumption. © 2023 IEEE.

关键词： Energy utilization

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Development and Evaluation of Sequential Batch Reactor with Natural Coagulants for Dairy Waste Water Treatment

Development and Evaluation of Sequential Batch Reactor with ...

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Mobile Computing and Sustainable Informatics (ICMCSI), International Conference on

作者： R. Sheela Daniel S. Sundararajan C. Antony Vasantha Kumar J. Nirmal Jothi R. Santhana Krishnan C. Ramasamy Sankar Ram Department of Civil Engineering SCAD College of Engineering and Technology Cheranmahadevi India Department of Mechanical Engineering SCAD College of Engineering and Technology Cheranmahadevi India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology School of Electrical and Communication Chennai India Department of Electronics and Communication Engineering SCAD College of Engineering and Technology Cheranmahadevi India Department of Computer Science and Engineering University College of Engineering Anna University Tiruchirappalli India

India is often heralded as the "Cynosure" of the global dairy industry, boasting a staggering valuation of INR 14,899.8 billion in 2022. This industry has exhibited remarkable and sustained growth in milk product availability since the year 1998. However, it's imperative to concede that the dairy sector concurrently bears the dubious distinction of being one of the most ecologically burdensome industries, primarily due to its substantial effluent output. Approximately 50% of the total dairy wastewater emanates from the rinsing of processing units intricately involved in the production of dairy commodities. The sources of this wastewater are multifarious, encompassing spills and seepage from pipelines, suboptimal tanker drainage, foaming incidents, tank spillages, cleaning operations, and liquid losses. This wastewater comprises milk solids, detergents, sanitizers, milk remnants, and cleaning water. It is typified by elevated concentrations of nutrients, both organic and inorganic, and may also encompass acids, alkalis, active agents, disinfectants, in conjunction with a substantial microbiological load, inclusive of pathogenic viruses and bacteria. In recognition of the imperative need to reclaim valuable milk solids to reinvigorate agriculture, particularly in regions grappling with water scarcity, a comprehensive wastewater treatment strategy was proffered. This strategic framework encompassed the meticulous scrutiny of pivotal parameters such as pH, BOD (Biological Oxygen Demand), and turbidity during the treatment regimen. Moreover, an ongoing discourse pertains to the utilization of natural coagulants for the efficacious treatment of dairy wastewater. Diverse ratios of these coagulants were judiciously introduced to the wastewater under treatment, and the levels of pH, BOD, and turbidity were assiduously assessed upon the culmination of each processing stage. The determination of the treatment process's effectiveness hinged upon the discerning comparison of out

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A Robust DL Approach for Detection of Invasive Ductal Carcinoma in Whole Slide Images using DenseNet169

A Robust DL Approach for Detection of Invasive Ductal Carcin...

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2024 International Conference on communication, computer sciences and engineering, IC3SE 2024

作者： Menaka, C. Sharma, Sunil Naval, Preeti Brar, Khushmeen Anand, Rohit Alabdeli, Haider Pant, Shivani Department Of Computer Science And Information Technology Bangalore India Vivekananda Global University Department Of Computer Science & Application Jaipur India Maharishi University Of Information Technology Maharishi School Of Engineering & Technology Uttar Pradesh India Chandigarh University Department Of Electronics And Communication Engineering Punjab Mohali India G.B Pant Okhla-1 Campus Department Of Ece New Delhi India The Islamic University Najaf Iraq Uttaranchal University Uttaranchal Institute Of Technology Uttarakhand India

ISBN: (纸本)9798350366846

The present research introduces a deep learning method for automatically recognizing and evaluating tissue areas that correspond to invasive ductal carcinoma (IDC) in whole slide images (WSI) of breast cancer (BCa). Learn-from-data techniques which utilize computational simulations of the learning process are called deep learning approaches. It has been demonstrated that these methodologies outperform conventional methods in resolving the challenging issues in a number of domains, particularly object and speech recognition. The main reason why making an invasive breast cancer evaluation is an exhausting and laborious process is that, it necessitates a pathologist to scan a huge number of benign regions with the aim to determine the spots that are malignant. Effectively characterizing IDC in WSI is a prerequisite for evaluating the severity of tumors and predicting patient prognosis. In order to support diagnosis, the DL approach in this study draws out many convolutional neural networks (CNNs) for perceptible semantic examination of tumor locations. A WSI database of 162 patients with IDC diagnoses is exploited to assess the technique, and 170 slides were chosen for training. The objective of the experimental analysis was to assess the accuracy of the classifier in identifying IDC tissue areas in WSI. A fusion of optimization techniques namely Best First and Evolutionary Search has been employed for feature reduction and improvement. When using DenseNet169, our approach produced the highest quantitative outcomes for the computerized identification of IDC sections in WSI with regard to accuracy 87.46% in comparison with an approach using EfficientNetB0 and ML classifiers for invasive tumor categorization employing Random Forest, BayesNet, SVM, Naïve Bayes and Decision Tree with accuracy of 80.65%. © 2024 IEEE.

关键词： Diagnosis

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Design of Alcohol Detection and Alert System for Vehicles

Design of Alcohol Detection and Alert System for Vehicles

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Advances in Computing, communication and Networking (ICAC2N), International Conference on

作者： Indu Bhardwaj Saravanan D Ajay Bhardwaj Daman Yadav Vijeta Kumari R Ramesh Kumar Dept. of Electrical Electronics and Communication Engineering Galgotias University Greater Noida India Dept. of Electrical and Electronics Engineering Madanapalle Institute of Technology & Science India Dept. of Computer Science and Engineering Delhi Technological University New Delhi India

ISBN: (数字)9798350356816

ISBN: (纸本)9798350356823

Recent days accidents are increasing on an exponential basis due to drinking and drive. Driving after drinking alcohol is a major cause of the majority of the accidents due to which sometimes innocent people lose their lives. As the number of vehicles is increasing day by day, accidents are also occurring due to many reasons but alcohol consumption is a major factor in many of the accidents. To avoid these accidents, an alcohol detection and alert system for vehicles is proposed in this paper that is based on MQ3 sensor. The proposed system gives a coherent solution to control injuries because of consumption of alcohol while driving. The alcohol detected by the MQ-3 sensor is processed via an ATmega328P Microcontroller that collate it with a fixed threshold for compliance. The device will nonstop monitor concentration of alcohol by the alcohol recognition sensor and consequently flip off the working of automobile’s engine if the alcohol concentration is exceeding threshold value. The replica can even send the alert of locality of the car via SIM900A (GSM module). The model presents an adequate answer to regulate injuries by the influence of alcohol driving. The LCD module is used to show that alcohol has been identified. The proposed system is cost effective, less bulky and more reliable.

关键词： GSM Costs Microcontrollers Alcoholic beverages Liquid crystal displays Reliability Injuries Monitoring Engines Accidents

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Performance Comparison of IRS and DF Relay Assisted Mixed RF-Underwater Optical communication System

Performance Comparison of IRS and DF Relay Assisted Mixed RF...

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2022 IEEE International Conference on Advanced Networks and Telecommunications Systems, ANTS 2022

作者： Salam, Rehana Srivastava, Anand Bohara, Vivek Ashok Ashok, Ashwin IIIT-Delhi Department of Electronics and Communication Engineering New Delhi110020 India Georgia State University Department of Computer Science AtlantaGA30303 United States

ISBN: (纸本)9781665473408

This work compares the performance of mixed radio-frequency (RF) optical underwater communication under two types of signal relaying strategies: (i) intelligent reflective surfaces (IRS), which is a physical surface fit with passive elements that can reflect and redirect the electromagnetic signals with high precision and at low energy cost, and (ii) decode-and-forward (DF), a traditional mechanism that deploys an active repeater that decodes the incoming signal (packets) and redirects it to the destination. The model we consider in this paper is a land RF base-station signals to a close-to-shore repeater which redirect the radio signals to a buoy in the sea. The buoy re-transmits the signals to the underwater destination (e.g., submarine) through an optical wireless (visible light communication) link. Through theoretical modeling and simulation analysis, we study and compare the spectral efficiency (SE) and energy efficiency (EE) of the two methods using Shannon capacity formulation. © 2022 IEEE.

关键词： Energy efficiency

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Path Planning for Self-driving Vehicles using Metaverse in 6G era with AI-enabled Networks

Path Planning for Self-driving Vehicles using Metaverse in 6...

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International Symposium on Advanced Networks and Telecommunication Systems (ANTS)

作者： Rachit Choudhary Rahul Prakash Rajat Chaudhary Ishan Budhiraja Amit Choudhary Electronics and Communication Sir Chhotu Ram Institute of Engineering and Technology Meerut Uttar Pradesh India School of Computer Science and Engineering Technology Bennett University Greater Noida India Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

ISBN: (数字)9798350391725

ISBN: (纸本)9798350391732

Self-driving vehicles are the future of technology which is having the potential to reshape mobility by improving the safety, efficiency, and accessibility of transportation system in 6G networks. Critical task like safety is a crucial factor which is included in the planning of motions of the vehicle through an environment where other vehicles and other objects are part of analysis based on feedback control. This paper mainly focuses on decision-making for autonomous driving, specifically on lane change decisions by using deep reinforcement learning (DRL) in metaverse environment. The challenges of the lane change and path planning addresses the importance of considering both longitudinal speed and lateral lane changes in self-driving vehicle scenarios. The study defines the actions for the autonomous agent like either to stay in the current lane otherwise, changing lanes to the left and right. Thus, safety and efficiency are key concerns in the decision-making process based on rewards and penalties defined to encourage safe driving behavior. The paper limits the self-driving vehicle to drive in the three right lanes of the road to ensure safety and adherence to lane regulations. The goal is to drive as fast as possible within the speed limits, avoid collisions, and minimize unnecessary lane changes in self-driving robots environment. This paper implements longitudinal speed control through rule-based methods while focusing on the lane change decision-making process using reinforcement learning algorithms. Finally, the performance evaluation is performed on Matlab and Simulink to compute the path followed by the proposed model.

关键词： 6G mobile communication Metaverse Software packages Decision making Velocity control Transportation Path planning Safety Telecommunications Robots

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Greenhouse Monitoring and Controlling using Cloud-Based Android Application

Greenhouse Monitoring and Controlling using Cloud-Based Andr...

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International Conference for Convergence of Technology (I2CT)

作者： Tarun Kumar Samli Dilip Kumar Department of Electronics and Communication Engineering Sant Longowal Institute of Engineering and Technology Longowal India Department of Computer Science and Engineering Galgotias College of Engineering and Technology Greater Noida

Wireless sensor network (WSN) technology is the amalgamation of numerous sensors exploited for monitoring and controlling the physical climate conditions. The integration of WSN technology in greenhouse farming has offered a new direction towards the production of crops. Greenhouse presents a protected environment for the plants/crops and facilitates the farmers in boosting their production. The paper presents a real-time greenhouse monitoring and controlling system. Humidity-Temperature sensor (DHT11), Soil Moisture sensor and Light sensor (LDR) are explored to measure the climate parameters accurately. To collect the real-time monitoring data from these sensors and transmit the data to the Firebase Cloud, the Wi-Fi module ESP8266 is attached to Arduino UNO. Further, an android application is developed for monitoring and controlling climate parameters via smart devices. The proposed model is efficient in terms of services and cost. The proposed automatic greenhouse monitoring and control system can facilitate the farmers in monitoring and controlling the climate conditions automatically as well as manually if the need arises. The developed application is user-friendly and can be efficiently utilized by farmers.

关键词： Wireless sensor networks Cloud computing Atmospheric modeling Green products Prototypes Control systems Real-time systems

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Hybrid Grey Wolf and Particle Swarm Optimized (HGW-PSO) Scheduling in Containerized Cloud Computing Environment

Hybrid Grey Wolf and Particle Swarm Optimized (HGW-PSO) Sche...

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Emerging Technology (INCET), International Conference for

作者： S.M. Udhaya sankar Martin Joel Rathnam Aswanth Babu Harikumar G J Keerthi Nadh Department of Computer Science and Engineering(Cyber Security) R.M.K College of Engineering and Technology Chennai Tamilnadu India Department of Electronics and Communication Engineering Sri Sairam college of Engineering Bengaluru Karnataka India

ISBN: (数字)9798350361155

ISBN: (纸本)9798350361162

The concept of containerization consists of encapsulating applications with their libraries with the help of operating system level virtualization, ensuring they are separated from other processes on the same machine. Containers gained popularity in several data centers due to their lightweight nature and simplified deployment. Application containerization technology is a fundamental technology that enables the deployment of numerous containers on a single physical node. A single physical node has the capability to offer several services to users. The adoption of microservice architecture is on the rise as it offers several benefits over monolithic designs, such as simplified deployment, enhanced versatility, and improved accessibility. The rise of containerization has significantly increased the significance of microservices, enhancing their scalability and portability. Many researchers have developed theories and solutions for the microservice container scheduling problem, yet limits remain. The algorithm's tendency to become stuck in local optimization and its slow optimal solution search are examples. In this work we present a proposal for grey wolf and particle swarm optimized (GW-PSO) scheduling in a Containerized Cloud Computing Environment. During the first phase of the search, the GW's global search can direct the PSO away from local optima, preventing early convergence. In the last phases of the search, the PSO can improve GW search along the Pareto optimum frontier. The research findings demonstrate, in comparison to the other 3 methods, the algorithm achieves a 19.06% reduction in network transmission cost, a 15.57% improvement in load balancing performance, and a 6.67% enhancement in service stability.

关键词： Cloud computing Scheduling algorithms Scalability Microservice architectures Containers Resource management Proposals

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