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Intelligent Network Architecture for Home Automation and Efficient Solution for Appliance Control in Smart Grid

Intelligent Network Architecture for Home Automation and Eff...

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international conference on Electrical, Computer & Telecommunication Engineering (ICECTE)

作者： Abdullah Al Mamun Mehedi Hasan Jewel Parag Kumar Paul Saima Ahmed Rahin Department of Electrical and Electronic Engineering Bangladesh Army International University of Science and Technology Cumilla Bangladesh Department of Computer Science and Engineering United International University Dhaka Bangladesh Department of Electrical and Electronic Engineering United International University Dhaka Bangladesh

the field of “Internet of things” (IoT) technology is exploding because of the quick advancements in automation technologies, embedded systems, and networking. It has become an integral part of Home Automation which is the combination of sensor networks, cloud computing, monitoring, and control. this paper discusses networking and provides two distinct methods for managing network-connected appliances as well as two different strategies for controlling the connected appliances and devices resulting in the enhancement of the system's robustness and overall stability. LoRa and 2.4GHz Wi-Fi technology have been used for the networking architecture of the appliances. Direct load control and phase angle-based voltage control methods are designed and developed for controlling the connected appliances. the distinct wireless technologies increase the stability of data transmission while ensuring minimum power consumption. AC voltage control methodology followed in this research also improves the robustness of the control systems. A mobile application platform is also developed and presented in this paper which is used to monitor and control the appliances, also known as sensor nodes.

关键词： Wireless communication Home appliances Wireless sensor networks Home automation Computer architecture Power system stability Robustness

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Cardiovascular Disease Prediction Using KNN Algorithm

Cardiovascular Disease Prediction Using KNN Algorithm

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Advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： Shyam Sagar Singh Choudhary Priyam Singh Dileep Kr. Yadav Computer Science and Engineering Galgotias University Greater Noida Uttar Pradesh India

Innovation has made considerable progress in the course of the most recent couple of years, individuals presently use web as their base vehicle for recovering and trading data. Abundance isn't the main thing of our life which individuals search for nowadays. Well being was, is and it will be the genuine abundance for individual. Wellbeing shouldn't be stayed away from anytime in our life. Coronary illness is one of the most well-known factor for passing’s in individual. Cardiovascular sickness is those which influences veins and causes heart infections. the past strategy of ascertaining the obscure measure of these illnesses ease in taking terms to bring down the higher gamble of *** well being office has colossal measure of information; the ML calculations helps in clearing the path for forecast and to control examination and medicine. In this examination, technique for eliminating missing information and properties characterization is utilized in per-handling for high precision and navigation. A portion of the calculations utilized for this thing like Decision Tree, KNN and Naive Bayes. Our point is to gather information mining techniques in Cardiovascular illness expectation, by utilizing basic boundary with the goal that it very well may be utilized in Machine 2 Machine remote observing.

关键词： Heart Technological innovation Navigation Veins Prediction algorithms Cardiovascular diseases Decision trees

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TCP Performance Enhancement Using Cross-Layer Method in IoT Networks

TCP Performance Enhancement Using Cross-Layer Method in IoT ...

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Advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： Sultana Parween Syed Zeeshan Hussain Department of Computer Science Jamia Millia Islamia New Delhi India

Transmission Control Protocol also known as TCP, utilizes many paths for the simultaneous transmission of data in order to increase its overall performance. But, the previous TCP had a problem to transmit a larger number of subflows in the Internet of things (IoT) networks. We used a cross-layer design to enhance TCP performance in the IoT networks by implementing effective packet scheduling & congestion control in order to address the existing issues. the IoT network uses grid topology and Manhattan distance to improve scalability and flexibility. After network configuration, packet scheduling is conducted using proportional fair scheduling with fitness mechanism (FBPF) and choosing best subflow to minimize transmission latency. Scheduled subflows are sent along optimal paths to increase goodput and throughput. After packet scheduling, the proposed algorithm is used to control congestion in TCP. this algorithm consists of three stages: congestion detection stage, fast retransmission, and fast recovery. To improve fast retransmission time, we utilize a cat and mouse based optimization algorithm (CMBO). the adoption of a metaheuristics algorithm improves the convergence speed thereby improving the user throughput. Simulation findings indicate that our proposed scheme outperforms high TCP performance with respect to goodput, throughput, packet loss, congestion window size, and transmission delay.

关键词： Cross layer design Protocols Scheduling algorithms Scalability throughput Scheduling Windows

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Improving Medical Predictions with Label Noise Tolerant Classification

Improving Medical Predictions with Label Noise Tolerant Clas...

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Advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： Shivam Vernekar Arun Ayyar Arun Rajagopalan Bijendra Kumar Vivek Kumar Mishra Evive Software Analytics Pvt. Ltd. Bengaluru India Santa Fe Research Pvt Ltd Chennai India Data Science Evive Software Analytics Pvt. Ltd. Bengaluru India Electrical and Electronics Engineering Galgotia College of Engineering and Technology Greater Noida India

Supervised machine learning algorithms depend crucially on availability of a large pool of correctly labelled instances. However many real world datasets may contain noisy features and label values. this is even more problematic for medical datasets since noise can be asymmetric (class dependent) due to imprecise class definitions or subjective human biases during data collection. there is easy availability of a large pool of unlabelled instances which can’t be directly used for training, for example raw data from medical devices like fitness trackers, data from health surveys etc. Labelling them (with respect to certain task) with the help of human experts might be a time consuming and a costly process. Besides, learning algorithms trained on noisy datasets can reduce the quality of future inferences making them unsuitable for business use-cases. In this paper we propose a semi-supervised learning based approach where we combine information embedded in unlabelled and incorrectly labelled instances with a very small set of correctly labelled instances. To the best of our knowledge this is the first work based on semi-supervised learning for reducing the noise in generated predictions using imperfect datasets. It is demonstrated through extensive experimentation using a medical diagnostic diabetes dataset, that by using only a fraction of correctly labelled instances, we are able to generate high quality predictions on unseen data.

关键词： Training Medical devices Machine learning algorithms Noise reduction Semisupervised learning Diabetes Noise measurement

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High Performance computing in Decentralized Network

High Performance Computing in Decentralized Network

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Sustainable Technologies for Industry 4.0 (STI), international conference on

作者： Md. Abdullah Antor Tasmin Jannat Tahsin Minhas Abedin Sohan Syed Ahsanul Kabir Dept of Computer Science and Engineering Green University of Bangladesh Bangladesh

With the vast growth of information technology, faster communication and better processing has become the most important concern for modern civilization. For decades we have been using centralized cloud systems for using the internet. Client-Server communication system has both advantages and disadvantages. then came the Blockchain based networks which is growing more popular day by day. But it is not efficient enough to integrate with existing cloud systems. We know that faster data transmission and better processing is currently a great necessity for Sustainable Technology and Industry 4.0. In this paper we are going to show a new system to achieve High Performance computing with the help of decentralized networking infrastructure using Fog server, Content Delivery Network (CDN) and Peer to Peer communication. Content retrieval is the primary usage of the internet. this research is going to uncover how efficient decentralized network is for both providing content and gaining High Performance computing. To solve content availability and download/browsing time issues, CDN is used as virtual overlay networks. It makes the content distributed and closer to the users. the content can be made even closer using dedicated Fog servers. We are proposing a system where each end device would be able to communicate with other nearby devices and whenever a certain content would not exist on nearby devices, the request would be thrown to the Fog server, then to the CDN. Besides content retrieval, the end devices would also act as hosting servers for providing cloud processing to get a complicated task done in a very short time.

关键词： Cloud computing High performance computing Web and internet services Computer architecture Software Peer-to-peer computing Fourth Industrial Revolution

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An Optimum Approach to Indian Sign Language Recognition using Efficient Convolution Neural Networks

An Optimum Approach to Indian Sign Language Recognition usin...

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Advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： Ritik Kumar Nikunj Bhardwaj N. Suresh Kumar School of Computing Science and Engineering Galgotias University Greater Noida India

the most important component of every discussion is language, and sign language is the most formal mode of communication for persons who are deaf or mute. Communication, as we all know, is one of the most important components of modern life. the importance of communication is increasing in tandem with our maturation in life. the purpose of this project is to develop a system capable of recognizing all of these signs and serving as a bridge for signers and non-signers to communicate and interpret sign meanings. Technology is rapidly evolving, and now that we have powerful systems, a wealth of data, and a diverse set of sources, we can design a system to assist people with disabilities. We will develop a user-independent framework for automatically recognizing Indian Sign Language in this project, which will allow for feature extraction, recognition, and interpretation of a variety of one-handed, dynamic isolated signals. the two most important and fundamental aspects of SLR research are isolated sign recognition and continuous sign recognition. Hand form, hand position, and so on are the primary hand traits that can be used in sign language. the extra-clung functionality can be implemented in two ways. Either one is tracking-based or it is not. this essay focuses on one such approach that we devised to overcome significant communication barriers. the technique is divided into three stages: pre-processing, texture extraction, and recognition.

关键词： Convolution Neural networks Gesture recognition Assistive technologies Feature extraction Real-time systems Smart devices

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data Analysis using Robot Process Automation Study on Web Scraping using UI Path Studio

Data Analysis using Robot Process Automation Study on Web Sc...

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Advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： Anant Mishra Shivam Mishra N. Suresh Kumar School of Computing Science & Engineering Galgotias University Greater Noida India

Automation has been into existence since the mid Fifties but had simplest began to gain attention lately. the RPA software program makes use of existing generation’s interface to automate the human detail in the technique. So, essentially, there's no want for human intervention. web scraping is a software of robot system Automation that is used in almost all of the industries. either or not it's a e-trade internet site, commodities buying and selling web sites, or any internet site and so forth. you can scrape the information from any of them based on your hobby. Now, the problem with guide scraping by hand is that it's miles at risk of mistakes and takes numerous times. also, the facts available on websites does now not change in any respect. up to date regularly, for this reason facts saved domestically might not usually be terrible. So, industries can actually automate this mission. the main objective of the project is to save time and send the updated information to the person using RPA technology. As this COVID-19 Global Pandemic going on, we thought of creating a project around COVID-19. So, in the project we will use data Scrapping to extract Web Table (which contains COVID-19 data such as number of affected people, recovered people etc.) from web page. And, write the extracted data into Excel then we will send that excel over the email as attachment. In this project we researched how we can send data through email using RPA and extract the data from live covid_19 website. For software automation, there are many software’s that are available in market. the main RPA vendors are UiPath, Automation Anywhere, and Blue Prism. So, to complete our RPA project, we have chosen UiPath which the best in the field of automation. You should be familiar with at least one of these tools before working on the following projects. this paper aims to provide RPA reviews as technical, as well as its implementation applications.

关键词： COVID-19 Industries Automation Pandemics Web pages Closed box data mining

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Cyber Security With Emerging Technologies & Challenges

Cyber Security With Emerging Technologies & Challenges

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Advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： Ashish Choudhary Adarsh Chaudhary Suman Devi School of Computer Science & Engineering Galgotias University Greater Noida India

In order to save the online information systems of private, cooperative, and government organisations and prevent them from attacks that enters into organizations system must use flawless and smart cybersecurity technologies. Some industries technologies which are now emerging are machine learning, blockchain, forecast security, cloud computing and Artificial intelligence (AI). Likewise, security operations centers (SOCs) should increment the development of safety techniques to conquer defensive cases. For every user the advanced cyber security future protocols should be develop with the help of emerging security *** Security has a key aspect in the plot of IT. data storage has been one of the biggest jobs of our time. Cyber crimes is the first thing which occurs in our mind when we start talking about cyber security that is increasing more & more with time. Different governments and organization took several steps to stop these cases. Exclusive of many covers cyber security is still a major challenge for many people. Challenges & difficulties faced by cyber security on the latest developed technologies and emerging cyber security techniques upgrading the world of cyber security will be discussed in this paper. Increasing of cybersecurity threat is overbearing and very unacceptable. A cyber-attack is visualized with the damage done by cyber-threats, but they are impossible to held – except for a digger situation between nations or *** which successfully created protective techniques should show them and provide it to the world. Fastly developing era increases the demand of safe and intelligent cyber defense techniques, including private cybersecurity groups, research centers of universities and government, corporations, public institutions, start-ups, etc.

关键词： Industries Cloud computing Protocols Government Memory Machine learning Safety

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Implementation of Decision Tree with Pruning for Predicting the Outcomes of Myocardial Infarction

Implementation of Decision Tree with Pruning for Predicting ...

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Advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： Akashdeep Singh Chaudhary Ravinder Saini Nitika Kapoor Department of Computer Science and Engineering Chandigarh University Mohali Punjab India

Over the last decade, the fast growing area of artificial intelligence and machine learning has made its vast impact in various fields such as healthcare sector, security, market, image processing, etc. Deep learning has also evolved these days for prediction and forecasting as the performance of the machine learning algorithms does not show good results with large amounts of data. Whereas, Deep learning shows better results and performance with large amounts of data but it requires large computational power. Nowadays, computational power is not the limitation, hence deep learning is at its boost. the healthcare sector is using deep learning techniques for human disease classification, detection, or even predictions related to disease. Our research is also based upon the technique which is known as Decision Trees. the objective of our research is to predict the various outcomes of Myocardial Infarction (commonly known as a heart attack) using the Decision Trees but also using one more technique to improve the accuracy of prediction and this technique is known as Pruning. this is a type of Cardiovascular disease which affects the blood vessels as well as the heart. Cardiovascular diseases cause deaths in large numbers globally. Due to Cardiovascular diseases, nearly 17.9 million people died in 2019 in which heart attack and stroke were the main reasons for 85% of deaths. A heart attack which is also known as Myocardial Infarction causes damage to the heart muscles because of the decrease in the flow of blood or when the flow of blood completely stops to the coronary artery of the heart.

关键词： Deep learning Heart Machine learning algorithms Systematics Medical services Cardiac arrest Myocardium

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Detection of diabetic Retinopathy using Retinal Fundus Images

Detection of diabetic Retinopathy using Retinal Fundus Image...

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Advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： Lalitha Krishnasamy Rajesh Kumar Dhanaraj Monika Gupta Priti Rai K. Sruthi Gopika T Department of IT Kongu Engineering College India School of Computing Science and Engineering Galgotias University India Chitkara Business School Chitkara University Rajpura Punjab India PGDM & MIB IMS Noida Uttar Pradesh

Diabetic retinopathy is one of the diabetes consequences that affects the eyes. this is caused by damage to the blood vessels in the retina, the light-sensitive tissue in the rear of the eye. It may create no symptoms at first, or it may cause minor eyesight difficulties. When the blood vessels become damaged, they may leak and this leakage can cause dark spots on our vision. the DR can be detected by finding the Hard Exudate present in it. the deep networks are becoming deeper and more complex. So that adding more number of layers to a neural network can make it stronger for image related tasks. But the main disadvantage in adding more layers is that, it may greatly reduces the accuracy of the image and also the data models are complex. In order to overcome this drawback, Recurrent Neural Network can be introduced. the fundamental benefit of using a recurrent neural network is that it can represent a collection of data in such a way that each pattern may be presumed to be reliant on the one before it. It can process inputs of any length. Even if the input size is large, the model size will not change. It makes the training process faster and attains more accuracy while compared to other neural networks. this method greatly reduces the loss of accuracy because each layer knows the information of the top layers while updating the weights. this Recurrent Neural Network has more number of parameters , so it is obvious that it can produce better result as compared to other net.

关键词： Training Recurrent neural networks Sensitivity Retinopathy Blood vessels Retina Diabetes

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