Ship Operational Efficiency from AIS Data Using Big Data Technology

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

Impact of Indias Export on Indian GDP after Liberalisation

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.

Medical Image Fusion Using Deep Learning Mechanism

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.

A Survey on Crime Detection And Prediction Techniques

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

Devanagari Handwritten Character Recognition Using Deep Learning

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.

Channel Estimation for Massive MIMO Systems

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

Experimental Study on Light Weight Concrete Using Coconut Shell and Fly Ash

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.

A Survey on Secrete Communication through QR Code Steganography for Military Application

The quick response code (QR) has become most popular barcode because of its larger data capacity and increased damage resistance. Barcode scanners can easily extract information hidden in the QR code when scanning data forms. However, some confidential data stored directly in QR codes are not secure in real world QR apps. To proposed approach to visual secret sharing scheme to encode a secret QR code into distinct shares. In assessment with other techniques, the shares in proposed scheme are valid QR codes that may be decoded with some unique that means of a trendy QR code reader, so that escaping increases suspicious attackers. An existing sharing technique is subjected to loss of security. On this premise, consider the strategy for (k, n) get to structures by using the (k, k) sharing occurrence on each k-member subset dependent on specific relationship. In addition, the secret message is recovered with the aid of XOR-ing the qualified shares. This operation which can effortlessly be achieved the use of smartphones or different QR scanning gadgets. Contribution work is, working on optimal partitioning methods and compare original message with shared message using hashing techniques. Keywords: Hashing, partitioning algorithm, error correction capacity, high security, Quick Response code, visual secret sharing scheme

Challenges Faced in Prefabrication or Modular Construction

The prefabricated materials used in construction has indeed been hailed amongst the most efficient approaches, there is a difficulty in implementing this process in the construction industry. The article included an outline of the obstacles and factors that influence prefabrication or modular construction in India. The issues of prefabrication and modular construction were investigated through case studies. Prefabricated elements have been demonstrated to be an efficient and efficient approach for improving productivity and the process of construction, as well as assuring the quality of construction & reducing time and cost. However, there are a number of issues with this strategy in practise, including initial high building costs, lack of understanding of the prefabricated method of construction, technical and installation hurdles, and the inability to find prefabrication businesses locally. Because of the nature of the city and also the growing population, the use of such prefabricated materials in the construction of buildings is beneficial. Keywords: Prefabricated construction, Challenges, fabricated elements, Installation hurdles

A Study on Impact of Environment Friendly Product Attributes on Consumer Purchase Decisions

The study aims to find out the influence of environment friendly attributes on the willingness of consumers to purchase the product. It also aims to determine the type of emotions elicited by these kinds of consumer products. It was hypothesized that buying eco products can elicit different kinds of emotions in consumers. These emotions are usually positive that cause attraction to consumers and eventually the actual purchase of the product. An exploratory pre-purchase affect survey was conducted through field and online survey to determine what shoppers feel while looking for eco products to buy. Results revealed that participants significantly experience more positive feelings/emotions than negative feelings/ emotions when buying eco-products while participants are indifferent in experiencing positive and negative feelings/emotions when buying non-eco products. This study provided information on the importance of incorporating ecological attributes to the design of consumer products. As of now, not all companies offer eco-friendly products because it is not known if consumers are willing to pay more for the “environment friendly” attribute. This study hopes to shift the paradigm of companies as it will try to establish the emotional attachment of consumers to product attributes related to the environment.