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IJIRTM: Volume-5, Issue-2, 2021

Paper Title : Image Compression using Machine Learning: A Review
Author Name : Atul Kumar Yadav, Prof.Jitendra Mishra
Keywords : Image processing, Computer vision, Neural network, Convolution neural network.
Abstract :

Apart from the existing technology on image compression represented by series of JPEG and MPEG, new technology such as neural networks, genetic algorithms, deep learning method and optimization techniques are being developed to explore the future of Image compression and coding. Successful applications of neural networks to vector quantization have now become well established, and other aspects of neural network involvement in this area are stepping up to play significant roles in assisting with those traditional technologies. This paper presents an extensive survey on the development of neural networks, deep neural network and optimization techniques for image compression.

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Paper Title : Overview on Development of Simulation and Implementation of Micro-grids with Distributed Solar PV for Efficiency Improvement
Author Name : Jia Ul Haq, Prof.Abhishek Chourey, Prof.Balram Yadav
Keywords : Energy supply system, Microgrid, Minimum energy losses, Solar power plant, efficiency, Short cut power, Useful power.
Abstract :

The work with the use of simulation in the software Matlab / Simulink / Sym Power Systems environment considers construction of a local Smart Grid energy supply system with distributed solar power plants. The obtained model allows us to investigate the work of the intelligent network in any quasi-steady and transitional modes, including emergency ones. A distinctive feature of the proposed model is the localization of places for the installation of power active filter-compensating devices, the use of which allows providing the necessary quality of electric energy and achieving the minimum energy losses in the elements of the energy supply system. According to the results of the simulation, the comparison of the energy efficiency of the traditional energy supply system and Smart Grid has been made. The implementation of microgrid with solar power plants allows increasing the efficiency of the ESS. The reserve for increasing the efficiency through the implementation of microgrid has two components, the first one is related to the normalization of the power consumption mode, and the second one to the optimization of the structure of the network, when the distances between energy sources and consumers are reduced, and the density of the network energy flow and trunk line decreases. Moreover, the second component makes a more significant contribution to increasing the efficiency of the energy supply system. The aim of the research is to study of the operating modes and energy efficiency assessment of local microgrid on the basis of distributed solar power plants, power consuming storage and power filtering devices using simulation tools.

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Paper Title : Improvement of Power System Using Dynamic Pricing Mechanism
Author Name : Md. Faiyazussalekin, Prof.Abhishek Chourey, Prof.Balram Yadav
Keywords : Dynamic pricing scheme, Demand response, Microgrid, Renewable energy resources, Particle swarm optimization.
Abstract :

The renewable energy resources (RERs) have brought green revolution in mitigation of greenhouse gaseous emission resulted from traditional energy resources (TERs). Moreover, the effective utilization of these resources is influenced by pricing schemes which have limitations. Therefore, this research aims at optimization modeling for dynamic price-based demand response (DR) which includes flexible and inflexible loads along with the effective utilization of RERs i.e. photovoltaic (PVs) and wind turbines (WTs) in a microgrid (MG). The optimization problem regarding profit maximization for loads (flexible and inflexible) is solved via particle swarm optimization (PSO). Two cases are used to evaluate the performance of proposed dynamic pricing scheme. The simulation results have shown that proposed scheme is suitable in term of profit and comfort for flexible and inflexible loads as compared to fixed pricing scheme in both cases. In addition, the dynamic pricing scheme is exemplified as plug and play devices because of its easy implementation in present market structure without any modification. This research aims at profit maximization for both flexible and inflexible load customers. For this purpose, the dynamic pricing scheme for demand response in microgrids is designed which utilizes the renewable energy resources and main grid in efficient way. The simulation results of elaborated that the profit of load customers through dynamic pricing scheme is higher than fixed pricing scheme. In, flexible and inflexible loads are used in dynamic and fixed pricing schemes.

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Paper Title : A Review on Routing Protocol in Vehicular Ad-hoc Network
Author Name : Pankaj Patidar, Prof.Sarwesh Site
Keywords : Intelligent transport systems, Mobile Ad-hoc Network, Vehicular Ad-hoc Network, Global Positioning System.
Abstract :

Nowadays, a tremendous evolution of advanced technologies and sophisticated solutions applied to intelligent transport systems (ITS) has been observed. For instance, Internet of Vehicle (IoV) allowing both appealing infotainment systems and traffic management applications which require internet access is a core component of future ITS. In VANET, each vehicle acting as the network node communicates with another vehicle and constitutes a large ad-hoc network. Considering a huge number of vehicles the market and benefit of VANET would increase exponentially in the future. Here presents the literature study to routing protocol in vehicular ad-hoc network.

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Paper Title : Recent Trends in Machine Learning for Health Care Sector
Author Name : Mr.Deepak Kumar Rathore, Dr.Praveen Kumar Mannepalli
Keywords : Information and Communication Technology, Artificial Intelligence, Machine Learning, Health Care.
Abstract :

Nowadays computer-aided disease diagnosis from medical data through deep learning methods has become a wide area of research. Disease prediction from healthcare data which substantiates useful information in large quantity related to patients with various diseases is a problem related to the medical domain. Predicting disease risk entails probability prediction of disease and establish a preventive measure for either decreasing disease risk effect upon the patients in a particular way or preventing the risk of the disease altogether. Disease prediction has many benefits such as early-stage disease diagnosis, limit morbidity, and prevent mortality. In this paper, we mentioned the machine learning techniques for the health care sector to predict the disease detection ratio.

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Paper Title : A Review on Direct Absorption Solar Collector
Author Name : Alok Kumar, Prof.Jagdish Prasad
Keywords : Solar energy; nano fluids; nano composites; Selective coating.
Abstract :

A review on applications of nano fluids and nano composites shows the desired improvement in thermal and optical properties of solar energy conversion systems from the efficiency and reliability points of view. Solar energy conversion systems play a very important role in the solar energy field, which includes concentrated and non-concentrated systems that convert solar energy into electricity or thermal power. The conversion efficiencies of these systems can possibly be enhanced by using a nano fluid as the heat transfer medium and a nano composite as the selective coating.

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Paper Title : Iris Data Classification using Unsupervised and Supervised Learning Techniques
Author Name : Dr.Pankaj Kawadkar
Keywords : Data Mining, Supervised Learning, Unsupervised Learning, Health Care.
Abstract :

Data mining gives various types of clustering classification algorithm for the various number of applications such as banking, education, medical science, fraud detection, pattern representation, feature extraction for the respective filed etc., there are various algorithm such as supervised learning methods, unsupervised learning methods and semi supervised learning methods. There are various algorithm we can used with the data mining techniques to improve the performance of the system or any algorithm for the various number of field such as information retrieval and mining of the data, fraud detection, education sector, medical science, business transaction etc.

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