MIT-World Peace University (MIT-WPU) is a top educational institute located in Pune, India. It is recognized within&nbsp;UGC under Government of Maharashtra Act No. XXXV 2017.&nbsp;

It is part of the MIT group of institutions (established in 1983) which covers 10+ campuses across India and has more than 50,000+ students enrolled across various disciplines at a given point of time. The institute houses 15 schools ranging from Engineering &amp; Technology, Design, Pharmacy, Commerce, Governance among others. It offers undergraduate, postgraduate and PhD programs among different disciplines.&nbsp;

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MIT World Peace University

Engineering and Technology

Nowadays, there is a drastic increase in demand for data storage. Due to increasing demand for data storage, the concept of cloud computing is on the rise. This enormous amount of data can be backed-up on the cloud storage but, the problem is that it significantly increases the cost of the storage and its performance. Traditional storage process of data introduces redundancies and hence concept of Data deduplication is developed. Data deduplication is an effective solution for eliminating the redundancies. It uses the concepts of hash values and index tables which help in removal of duplicate data. With the use of Data deduplication process, an effective performance increase and reduction in cost of storage can be observed. In this paper, we have discussed different data deduplication methods considering their advantages and disadvantages. We have also proposed enhanced security method for generating data chunks by using standard encryption method.

School of Computer Engineering & Technology

World University root node

International Journal of Computer Engineering and Applications

Secure Data Deduplication for Cloud Storage: A Survey

In our system, proposed system exhibit another fine-grained two-variable approval (2FA) get theopportunity to control structure for electronic circulated Computing associations .We introduced user cannot accessdata without a secret key and a light weight security device like a finger print scanner ,and user need both secret keyas well as a light weight security device for accessing of any file.If secret key and user thumb match with registeredimage then user can view file as well download it. admin store file in fragmented format also with its replica. If someof uploaded files fragment data loss then we can get backup of our data from replica .We also introduced, If we want toacess any file in a a particular location and for a particular time then we can do it.from user, security key is stolen ordelete from a mail then user can revoke this security key from admin by request. Admin will accept the request andsend key on users mail so user can download the file.

International Journal of Innovative Research in Computer and Communication Engineering (IJIRCCE), ISSN (Online): 2320-9801

Survey on Two Factor Data Security Protection Mechanism for Cloud Services

World Health Organization (WHO) survey asserts that 350 million people suffer from depression globally. Depression is prolonged sadness that persists for long durations causing interferences in the functioning of daily life. Depression is increasing at an alarming rate and it not only affects the depressed individual but also their relatives, society and economy. Chronic pains, loss of something desired, separation or death of someone close, drugs, postnatal phase or menopause may be some of the causes of depression. To monitor clinical depression, we analyze the eye movements of the subject to classify them as whether they are depressed or not. To extract the necessary features of eye movements eye tracking and image processing techniques are used. The distance between eyelids, blinking rate, distances when eye is open or closed are scrutinized to inspect whether a patient is depressed or not.

DEPRESSION DETECTION THROUGH EYE MOVEMENTS USING STATISTICAL ANALYSIS AND MACHINE LEARNING: A SURVEY

Machine learning has gained a lot of traction in the recent years, due to an increase in computing power of personal computers and the quick access to datasets, large enough to train highly accurate ML models. Recent studies have shown a lot of promise in the amalgamation of Machine Learning in the field of Biomedicine. The detection of dementia has also attracted a lot of attention given the increase in life expectancy. The aim of this survey article is to methodically study the various Machine Learning Techniques being used in the Biomedicine research. There is no definite diagnosis for Alzheimer’s Disease currently, the only conclusive diagnosis that can be made is during the autopsy conducted. The objective of this survey could help to develop a method for the conclusive detection of Dementia.

MACHINE LEARNING ALGORITHMS FOR THE PROGNOSIS OF DEMENTIA: A SURVEY

Depression is a severe, treatable disorder which continues to remain under-detected in the primary care settings and is associated with symptoms such as melancholy, loss of pleasure, loss of energy, difficulty in concentrating, and suicidal thoughts. Stressful life events are one of common precedents in the first episode of depression, and may leave a person more vulnerable to develop subsequent episodes. Various techniques such as psychological questionnaires, measuring cortisol concentration, MRI scanning have been employed to measure the severity of depression. The conventional sources to measure cortisol levels are plasma, urine or saliva, which provide only acute cortisol exposure. Measuring cortisol concentration in hair has emerged over recent years as it provides a long- term, month-by-month systematic cortisol exposure. The purpose of this paper is to survey the promising results of correlation between HCC and mental disorders. A review of statistical techniques and machine learning algorithms used in previous work is included.

A SURVEY OF MENTAL DISORDERS USING HAIR CORTISOLCONCENTRATION

Aluminum 6066 is widely used for applications such as aircrafts and boat and ship building. Thusconsidering the applications, the joining of the metals must be such that minimum residual stresses anddistortion must occur. Two different welding methods i.e. Stir friction welding and metal inert gas welding(MIG) have been compared by making a butt type of joint. Investigations have been carried out to comparethe mechanical properties i.e. tensile strength, hardness and micro-structural properties. The resultsobtained showed that FSW welded joint possessed greater tensile strength and hardness whereas there wasa general decay in the mechanical properties for MIG welded joints. The micro-structural images under SEMshowed that the HAZ region for FSW welded joint is narrower than that for MIG. This is because of the hightemperatures during MIG. Thus considering all these factors FSW is an optimum process for industrialapplications as it saves energy and does not show any fusion related problems.

School of Mechanical Engineering

IJREAM 2018

Comparison between friction stir welding and conventional welding process (MIG)-A case study

A car's engine cannot power all of the wheels alone. That’s why the drive shaft is necessary to propel the vehicle. To propel the drive wheels it is necessary to take power from engine and send it to drive wheels by means of a drive shaft (half shaft). As it is transmitting the torque from the engine to the wheels, the drive shafts are subjected to the torsional stress and shear stress, which cause the failure of drive shaft. Any break down in drive shaft will cut the power flow from engine to the drive wheels. That’s why it is indispensable to analysis the drive shaft. The properties required to the drive shaft are hardness on the surface to resist the wear and toughness in the core to resist the deformation that can be achieved by doing the heat treatment.

International Journal for Research in Engineering Application & Management (IJREAM)

Failure Analysis of Drive Shaft

The rapid transportation of heavy-duty vehicles on our highways all day is a clear proof of the hellish desire toconsume society. This rapid transport of such heavy vehicles drags and creates the subsequent rapid wind on thesurface of the highway. These fast winds generated on the highway may be trapped and then used in anotherpossible form of energy, just as the kinetic energy of natural high-speed winds across high altitudes is captured bywind turbines and used for large-scale power generation. This study provides estimates and possibilities for thiswind power generation.

Design and Development of prototype for harnessing wind energy using moving traffic

Artificial Neural Networks have been a subject of research studies for over 50 years, but Artificial Neural network-based studies have seen an explosive growth due to the availability of large datasets along with advances in hardware systems, giving rise to higher computing power in terms of CPU and GPU. This trend has caught with computer scientists and biomedical researchers alike. There is no definite diagnosis for the detection of Alzheimer’s Disease currently, autopsy being the only conclusive diagnosis available. This has caused a lot of distress at family level and national level. The aim of this survey is to methodically study the various Neural Networks being popularly used in the field of Biomedicine. The objective of this survey could help to develop a method for the conclusive detection of Alzheimer’s Disease.

ARTIFICIAL NEURAL NETWORKS FOR KINEMATIC ANALYSIS OF HANDWRITING IN ALZHEIMER’S DISEASE PATIENTS: A SURVEY

Using the Internet of Things Technology for supervising solar power generation can greatly enhance the performance, monitoring and maintenance of the plant. With advancement of technologies the cost of renewable energy equipment is going down globally encouraging large scale solar plant installations. This massive scale of solar system deployment requires sophisticated systems for automation of the plant monitoring remotely using web based interfaces as majority of them are installed in inaccessible locations and thus unable to be monitored from a dedicated location. The Project is based on implementation of new cost effective methodology based on IoT to remotely monitoring a solar plant for performance evaluation. This will facilitate preventive maintenance, fault detection of the plant in addition to real time monitoring.