Mining Health Examination Records A Graph Based Approach

EHR Electronic Health Records collects data on yearly basis and it is used in many countries for healthcare.HER Health Examination Records collects the data on regular basis and identifies the participants at risk that is important for early warning and prevention.the fundamental challenge is for learning classification model for risk prediction with unlabelled data and live data string that established the majority of the collected dataset.the unlabelled data string describes the participants in health examintions whose health conditions can be vary from healthy to highly risky or very ill.in this paper, we propose a graph based,semisupervised learning algorithm called SHG health semi supervised heterogenous graph on Health for risk prediction and assessment to classify a progressively developing condition with the majority of the data unlabelled. An efficient iterative algorithm is designed and developed to proof the convergence is given.extensive experiments based on both real health examination dataset and live datasets to show effectiveness of our method. 

BY Jayashri A. Sonawane | Dr. Swati A. Bhavsar "Mining Health Examination Records - A Graph Based Approach"

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019,

URL: https://www.ijtsrd.com/papers/ijtsrd22810.pdf

Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/22810/mining-health-examination-records---a-graph-based-approach/jayashri-a-sonawane

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Smart Solar Grass Cutter Robot

Today, we know that solar energy is a renewable source of energy. And the fossils fuel may not be available in the future and it also pollutes to our environment. So we have to use, one of the most promising source of energy where everyone focusing on the concept of solar power and its utilization. Smartly grass cutting robot detects obstacles by the ultrasonic sensor with servo in wide range for avoiding obstacles without any need of human interaction. All the motors, sensors and cutting operation are automatically controlled by the Arduino and manually by Bluetooth module. And the cutting operation is performed by single metallic thread which is operated by DC motor 10000 rpm . Cutting robot batteries charged by a charging dock which is located in the ground separately. Charging dock is attached with the Solar panel and charging controller.

BY  Ajit Singh Shekhawat | Nikesh Kumar | Roopal Yadav | Siddharth Tyagi | Arun Pratap Singh "Smart Solar Grass Cutter Robot"

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019,

URL: https://www.ijtsrd.com/papers/ijtsrd23320.pdf

Paper URL: https://www.ijtsrd.com/engineering/mechanical-engineering/23320/smart-solar-grass-cutter-robot/ajit-singh-shekhawat

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Gesture Control Robot using Arduino

According to the World Federation of the Deaf, only 10 percent of the worlds Deaf population receives any education, and only 3 percent receives this education in sign language. Another problem these deaf and face is inability to communicate with a person who does not understand the sign language. This project aims to reduce these problems by presenting a Sign Language. The project uses a hepatic glove to acquire signals corresponding to various hand gestures. The glove is interfaced with robot using an Arduino. Accelerometers are used to measure the angular displacement of human hand motion .The accelerometer controls the movement of the robot. Device is made of mainly two parts, one is RF transmitter and another is RF receiver. The RF transmitter will transmit the signal according to the position of accelerometer attached on your hand and the RF receiver will receive the signal and make the robot move in respective direction. 

BY Deepanshu Kiran | Himanshu Singh | Kushal Kant Singh Saxeriya "Gesture Control Robot using Arduino"

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019,

URL: https://www.ijtsrd.com/papers/ijtsrd23411.pdf

Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/23411/gesture-control-robot-using-arduino/deepanshu-kiran

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Analytical Study of Municipal Solid Waste Characteristics at Deonar Dumping Yard in Mumbai Region, Maharashtra, India

Waste management is an international sensation, rising population, industrialization and urbanization are accountable to produce a tremendous amount of waste. Today's daily waste generation rate is about 760,000 tons. By 2025, this rate will be increased to about 1.8 million tons per day. These approximations are conservative the real values are probably double of this amount. 1 The estimated municipal solid waste generation by 8 Municipal Corporations and 9 Municipal Councils in Mumbai Metropolitan Region MMR cumulatively generate more than 10,000 metric tons of solid waste per day. Due to growth in population, industrialization and urbanization, the generation of solid waste has increased frighteningly. There is a high need for systematic management of municipal solid waste and for that understanding of characteristics play a vital role in it. In these research paper characteristics of Deonar dumping, yard has been studied on pre monsoon and post monsoon bases and encounter that, it contained some amount of organic and recyclable part, which if managed well, will reduce the load on dumping yard considerably.

BY  Dabhi Jagrutiben | Abhay Shelar "Analytical Study of Municipal Solid Waste Characteristics at Deonar Dumping Yard in Mumbai Region, Maharashtra, India"

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019,

URL: https://www.ijtsrd.com/papers/ijtsrd23333.pdf

Paper URL: https://www.ijtsrd.com/engineering/environment-engineering/23333/analytical-study-of-municipal-solid-waste-characteristics-at-deonar-dumping-yard-in-mumbai-region-maharashtra-india/dabhi-jagrutiben

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Comparative CFD and Simulative Analysis of Flow Behaviour to Calculate Losses in Different Geometrical Pipes

In order to transport the fluid effectively without suffering much energy loss it becomes very important to understand the frictional losses in fluid flow. And here basically two very crucial types of Losses are discussed such as Major Energy Loss this occur due to friction and other one is Minor Energy Loss this is due to sudden expansion, sudden contraction and bend in a pipe . This study will focus on calculating Losses like Major and Minor loss in turbulent fluid flow through pipes of different geometries expansion, contraction and bend . And the whole study will be performed using three different techniques firstly being experimentally performed in Fluid Mechanics and Machinery Laboratory, secondly at nodal centre of IIT DELHI using programme Virtual Labs, a project initiated by the MHRD, Govt. of India, and thirdly using ANSYS FLUENT a simulation and modelling software. The results obtained by using the three above discussed methods would be used for result validation and pointing the most effective method to calculate losses in flow through pipes. 

BY Er. Ajay Rana | Er. Nishant Kumar "Comparative CFD and Simulative Analysis of Flow Behaviour to Calculate Losses in Different Geometrical Pipes"

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019,

URL: https://www.ijtsrd.com/papers/ijtsrd23381.pdf

Paper URL: https://www.ijtsrd.com/engineering/mechanical-engineering/23381/comparative-cfd-and-simulative-analysis-of-flow-behaviour-to-calculate-losses-in-different-geometrical-pipes/er-ajay-rana

ugc approved journals for computer science, ugc approved journals for management, ugc approved journals in commerce

Design and Analysis of Pedal Box with Braking System

A design process for an automotive pedal box system is presented in this paper. The work begins with a review of research carried out on pedal box system. It is followed by the process of designing a complete pedal box system. Reverse engineering process by using a steel pedal box system by use of MS Plate. The Pedal box design with proper pedal ratio and the use of single brake for both front and rear braking is designed.

BY Md. Hameed | B. Praveen Kumar | B. Rohit | B. Surya Sai | G. Sai Kiran "Design and Analysis of Pedal Box with Braking System"

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019,

URL: https://www.ijtsrd.com/papers/ijtsrd23413.pdf

Paper URL: https://www.ijtsrd.com/engineering/mechanical-engineering/23413/design-and-analysis-of-pedal-box-with-braking-system/md-hameed

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EEG Classification using Semi Supervised Learning

The major challenge in the current brain–computer interface research is the accurate classification of time varying electroencephalographic EEG signals. The labeled EEG samples are usually scarce, while the unlabeled samples are available in large quantities and easy to collect in real applications. Semi supervised learning SSL methods can utilize both labeled and unlabeled data to improve performance over supervised approaches. However, it has been reported that the unlabeled data may undermine the performance of SSL in some cases. This study proposes a three stages technique for automatic detection of epileptic seizure in EEG signals. In practical application of pattern recognition, there are often diverse features extracted from raw data which needs to be recognized. Proposed method is based on time series signal, spectral analysis and recurrent neural networks RNNs . Decision making was performed in three stages i feature extraction using Welch method power spectrum density estimation PSD ii dimensionality reduction using statistics over extracted features and time series signal samples iii EEG classification using recurrent neural networks. This study shows that Welch method power spectrum density estimation is an appropriate feature which well represents EEG signals. We achieved higher classification accuracy specificity, sensitivity, classification accuracy in comparison with other researches to classify EEG signals exactly 100 in this study. To improve the safety of SSL, we proposed a new safety control mechanism by analyzing the differences between unlabeled data analysis in supervised and semi supervised learning. We then develop and implement a safe classification method based on the semi supervised extreme learning machine SS ELM . Following this approach, the Wasserstein distance is used to measure the similarities between the predictions obtained from ELM and SS ELM algorithms, and a different risk degree is thereby calculated for each unlabeled data instance. A risk based regularization term is then constructed and embedded into the objective function of the SS ELM. Extensive experiments were conducted using benchmark and EEG datasets to evaluate the effectiveness of the proposed method. Experimental results show that the performance of the new algorithm is comparable to SS ELM and superior to ELM on average. It is thereby shown that the proposed method is safe and efficient for the classification of EEG signals. 

BY Shivshankar Kumar Yadav | Veena S. "EEG Classification using Semi Supervised Learning"

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019,

URL: https://www.ijtsrd.com/papers/ijtsrd23355.pdf

Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/23355/eeg-classification-using-semi-supervised-learning/shivshankar-kumar-yadav

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