International Journal for Research in Applied Science and Engineering Technology
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(FIVE YEARS 10557)



Published By International Journal For Research In Applied Science And Engineering Technology (Ijraset)


Suraj Ingle

Abstract: The Energy Efficiency Design Index (EEDI) is a necessary benchmark for all new ships to prevent pollution from ships. MARPOL has also applied the Ship Energy Efficiency Management Plan (SEEMP) to all existing ships. The Energy Efficiency Operational Indicator (EEOI) provided by SEEMP is used to measure a ship's operational efficiency. The shipowner or operator can make strategic plans, such as routing, hull cleaning, decommissioning, new construction, and so on, by monitoring the EEOI. Fuel Oil Consumption is the most important factor in calculating EEOI (FOC). It is possible to measure it when a ship is in operation. This means that the EEOI of a ship can only be calculated by the shipowner or operator. Other stakeholders, such as the shipbuilding firm and Class, or those who do not have the measured FOC, can assess how efficiently their ships are working relative to other ships if the EEOI can be determined without the real FOC. We present a method to estimate the EEOI without requiring the actual FOC in this paper. The EEOI is calculated using data from the Automatic Identification System (AIS), ship static data, and publicly available environmental data. Big data technologies, notably Hadoop and Spark, are used because the public data is huge. We test the suggested method with real data, and the results show that it can predict EEOI from public data without having to use actual FOC Keywords: Ship operational efficiency, Energy Efficiency Operational Indicator (EEOI), Fuel Oil Consumption (FOC), Automatic Identification System (AIS), Big data

Krunal A Moharkar

Abstract: Today’s technology has been evolved into stand-alone systems which can do all necessary processes by themselves without any additional hardware. Advance microcontrollers have become microcomputers that are also known as single board computers. These systems take their power from powerful microcontrollers. These microcontrollers have many integrated circuits on board so they can achieve many different processes by themselves. They are being used in many applications from powerful industrial devices to simple home appliances. In today’s market, there are many different microcontrollers with different structure and capabilities. Therefore, understanding the concepts related to the microcontrollers is really important for choosing the best hardware. This paper presents the main concepts of microcontrollers and reveals the basis of their structure. Their components and abilities have been discussed and a comparison of well-known single board computers has been given. Keywords: Microcontrollers, Integrated Circuits, Arduino UNO, Raspberry PI, BeagleBone Black, ESP8266.

Prince Nathan S

Abstract: Travelling Salesmen problem is a very popular problem in the world of computer programming. It deals with the optimization of algorithms and an ever changing scenario as it gets more and more complex as the number of variables goes on increasing. The solutions which exist for this problem are optimal for a small and definite number of cases. One cannot take into consideration of the various factors which are included when this specific problem is tried to be solved for the real world where things change continuously. There is a need to adapt to these changes and find optimized solutions as the application goes on. The ability to adapt to any kind of data, whether static or ever-changing, understand and solve it is a quality that is shown by Machine Learning algorithms. As advances in Machine Learning take place, there has been quite a good amount of research for how to solve NP-hard problems using Machine Learning. This reportis a survey to understand what types of machine algorithms can be used to solve with TSP. Different types of approaches like Ant Colony Optimization and Q-learning are explored and compared. Ant Colony Optimization uses the concept of ants following pheromone levels which lets them know where the most amount of food is. This is widely used for TSP problems where the path is with the most pheromone is chosen. Q-Learning is supposed to use the concept of awarding an agent when taking the right action for a state it is in and compounding those specific rewards. This is very much based on the exploiting concept where the agent keeps on learning onits own to maximize its own reward. This can be used for TSP where an agentwill be rewarded for having a short path and will be rewarded more if the path chosen is the shortest. Keywords: LINEAR REGRESSION, LASSO REGRESSION, RIDGE REGRESSION, DECISION TREE REGRESSOR, MACHINE LEARNING, HYPERPARAMETER TUNING, DATA ANALYSIS

Santosh Dhaigude

Abstract: In todays world during this pandemic situation Online Learning is the only source where one could learn. Online learning makes students more curious about the knowledge and so they decide their learning path . But considering the academics as they have to pass the course or exam given, they need to take time to study, and have to be disciplined about their dedication. And there are many barriers for Online learning as well. Students are lowering their grasping power the reason for this is that each and every student was used to rely on their teacher and offline classes. Virtual writing and controlling system is challenging research areas in field of image processing and pattern recognition in the recent years. It contributes extremely to the advancement of an automation process and can improve the interface between man and machine in numerous applications. Several research works have been focusing on new techniques and methods that would reduce the processing time while providing higher recognition accuracy. Given the real time webcam data, this jambord like python application uses OpenCV library to track an object-of-interest (a human palm/finger in this case) and allows the user to draw bymoving the finger, which makes it both awesome and interesting to draw simple thing. Keyword: Detection, Handlandmark , Keypoints, Computer vision, OpenCV

CA Naveen Kumar Tiwari

Abstract: Economic and political policy interventions were reflected on the economic development of the countries with respect to improving economic and social well-being of poor, market productivity and considerable growth rate in GDP. Specifically, in Indian context, these economic decisions have been a considerable influence on inclusive growth of the nation. It is evidence that India embarked on economic reforms in July, 1991, from the effect of a balance of payment crisis. The government initiated economic reforms basically is to provide an environment of sustainable growth and stability. Thereby the LPG (Liberalization, Privatization and Globalization) system has come to the picture for economic progress of the country. Thepresent study investigates the linkage between foreign trade trends of India and its economic development in the light of economic reforms in India since 25 years (1991-2016). The outcomes of the study strongly support that there is a causal relationship between exports to GDP and GDP to exports and also causality between imports to exports in India.

Nukapeyyi Tanuja

Abstract: Sparse representation(SR) model named convolutional sparsity based morphological component analysis is introduced for pixel-level medical image fusion. The CS-MCA model can achieve multicomponent and global SRs of source images, by integrating MCA and convolutional sparse representation(CSR) into a unified optimization framework. In the existing method, the CSRs of its gradient and texture components are obtained by the CSMCA model using pre-learned dictionaries. Then for each image component, sparse coefficients of all the source images are merged and then fused component is reconstructed using the corresponding dictionary. In the extension mechanism, we are using deep learning based pyramid decomposition. Now a days deep learning is a very demanding technology. Deep learning is used for image classification, object detection, image segmentation, image restoration. Keywords: CNN, CT, MRI, MCA, CS-MCA.

Vinod Gendre

Abstract: Crime is a preeminent issue where the main concern has been worried by individual, the local area and government. Wrongdoing forecast utilizes past information and in the wake of investigating information, anticipate the future wrongdoing with area and time. In present days sequential criminal cases quickly happen so it is a provoking assignment to anticipate future wrongdoing precisely with better execution. This paper examines about various wrongdoing expectation and location. A productive wrongdoing forecast framework speeds up the method involved with addressing violations.. Wrongdoing Prediction framework utilizes recorded information and examinations the information utilizing a few dissecting strategies and later can anticipate the examples and patterns of wrongdoing utilizing any of the underneath referenced methodologies. Keywords: Crime Analysis, Data Mining, Classifiaction , Clustering

Kannuru Padmaja

Abstract: In this paper, we present the implementation of Devanagari handwritten character recognition using deep learning. Hand written character recognition gaining more importance due to its major contribution in automation system. Devanagari script is one of various languages script in India. It consists of 12 vowels and 36 consonants. Here we implemented the deep learning model to recognize the characters. The character recognition mainly five steps: pre-processing, segmentation, feature extraction, prediction, post-processing. The model will use convolutional neural network to train the model and image processing techniques to use the character recognition and predict the accuracy of rcognition. Keywords: convolutional neural network, character recognition, Devanagari script, deep learning.

Polireddi Sireesha

Abstract: In MIMO millimeter-wave (mmWave) systems, while the hybrid digital/analog precoding structure provides the ability to increase the reach rate, it also faces the challenge of reducing the channel time limit due to the large number of horns on both sides of the Tx / Rx. . In this paper, channel measurement is done by searching with multiple beams, and a new hierarchical multi-beam search system is proposed, using a pre-designed analog codebook. Performance tests show that, compared to a highperformance system, the proposed system not only achieves a high level of success in getting multiple beams under normal system settings but also significantly reduces channel estimation time Keywords: Massive MIMO, Channel Estimation, precoding

Barkha Verma

Abstract: Aggregates provide volume at low cost, comprising 66% to 78% of the concrete. With increasing concern over the excessive exploitation of natural and quality aggregates, the aggregate produced from industrial wastes and agricultural wastes is the viable new source for building material. This study was carried out to determine the possibilities of using coconut shells as aggregate in concrete. Utilizing coconut shells as aggregate in concrete production not only solves the problem of disposing of this solid waste but also helps conserve natural resources. In this paper, the physical properties of crushed coconut shell aggregate were presented. The fresh concrete properties such as the density and slump and 28 days compressive strength of lightweight concrete made with coconut shell as coarse aggregate were also presented. The findings indicate that water absorption of the coconut shell aggregate was high about 24% but crushing value and impact value were comparable to that of other lightweight aggregates. The average fresh concrete density and 28days cube compressive strength of the concrete using coconut shell aggregate 1975kg/m3 and 19.1 N/mm2 respectively. It is concluded that crushed coconut shell is suitable when it is used as a substitute for conventional aggregates in lightweight concrete production. Keywords: Coarse Aggregate, Cement, Concrete, Fly Ash, Coconut shell Aggregate, Water, Compressive Strength, Workability, Fine Aggregate.

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