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

Chassis is the term used to define the basic structure of the vehicle. It is also referred to as carrying unit as all the units including body are mounted on it. There are various loads acting on the chassis like inertia loads, static loads, over loads, etc. also it has to withstand the forces induced due to sudden braking and acceleration. In this paper a review has been made on the stress analysis of chassis by finite element analysis software packages like ANSYS, HyperWorks, etc. Weight reduction is gaining importance as the designers are trying to reduce the excess weight form the existing vehicle design. A review of the various techniques for weight reduction for the chassis is presented.

School of Mechanical Engineering

World University root node

International Journal of Research in Engineering and Technology

A Review on Stress Analysis And Weight Reduction of Automobile Chassis

Aluminium Honeycomb sandwich panel is structure which has very sleight to weight ratio. Its main application in past observed in aerospace ,marine and high end automobile sector This structure can effectively used to eliminate one major drawback in Indian passenger car which is Pedestrian damage .By reference of test conducted by Euro NCAP we are having data the major passenger car which is day today part of life have fail in safety measure of European countries.

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Innovative Research in Science, Engineering and Technology

Analysis of Bumper Beam in Frontal collision

In the present study, an attempt has been made to identify the trends of patenting activity in mechanical engineering in India using data from value added databases. It is a first time full data compilation of patent filing and granted data at Indian Patent Office from year 1961 and patent filing data in the different areas of inventions from 1986. Further for this study a separate search was conducted using patent information databases with focus (IPC based) on mechanical engineering sector to understand and identify the companies working in this area. More than 10,000 patent applications and grants exclusively related to mechanical engineering have been considered for analysis. The study indicates focus of research of different organizations/industries in specific areas of mechanical engineering, R&amp;D collaboration between the companies. The paper also addresses various trends and discusses the R&amp;D partnership observed in Indian organizations and foreign organizations. The study further highlights the important directions for future path of R&amp;D.

School of Electronics & Communication Engineering

Journal of Intellectual Property Rights

Study of patents filed in India in mechanical engineering sector

Optimizing Adaptive Beam-forming Method in Smart Antennas

The seismic vulnerability of steel moment resisting frame with passive dampers is assessed with 13 different seismic resisting systems. The structural frames are analysed and designed for the loading conditions in Pune. The stiffness effect on the stories is demonstrated through the lateral displacement profile of the building. Hybrid passive dampers with buckling restrained brace of mild steel and aluminium are used to improve lateral stiffness of the structure. Mild steel braces have increased lateral strength and proved to be good energy dissipating devices. The aluminium sections are chosen as energy dissipating device due to its low yield strength. Aluminium buckling restrained braces has improved performance of the structure in the form of reduced storey drift and displacement as compared to basic steel moment resisting frame. By the use of these devices either alone or in combination with BRB, the performance of SMRF has been improved significantly. Copyright © 2015 Inderscience Enterprises Ltd.

School of Civil Engineering

International Journal of Structural Engineering

Effect of energy dissipating devices on storey drift and displacement by nonlinear time history analysis

Normal moles are mostly small brown in color that are spots or growths on the skin that is by birth or emerge in the first few decades of life in almost everyone. Skin cancer most often appears as moles. Seldom people are aware about the skin cancer. If detected at early stages then it can be cured. We propose an improved design of Gabon filter which is combined with Vedic algorithm (Urdhva Triyagbhyam) to give faster convolution result. The exertion has proved the efficiency of Urdhva Triyagbhyam which is the Vedic method of multiplication that enables parallel generation of intermediary products that eliminates unwanted multiplication steps with zeros and scaled to higher bit. In this paper we employ the filter design appropriate for detecting the early stages of skin cancer using textural properties of skin. © 2015 IEEE.

School of Computer Engineering & Technology

Proceedings - 1st International Conference on Computing, Communication, Control and Automation, ICCUBEA 2015

Efficient gabor filter using vedic mathematic for high speed convolution in skin cancer detection

Depression is one of the most common mental health disorders with strong adverse effects on personal and social functioning which can hamper the lives of individuals. The absence of any objective diagnostic aid for depression leads to a range of biases in the diagnosis and ongoing monitoring. This study throws light upon the contribution of gestures and facial points for depression analysis. This paper discusses a novel cumulative video analysis proposed by us based on action units and fictional points for analysis of facial moment. Experimental results are carried out using real world clinical data and interactive sessions with neuro experts. This smart framework developed by us is useful for detection of depression disorders through gesture recognition. The diagnosis is done and appropriate action is taken according to scale of the depression in the patient and the severity of it. © 2015 IEEE.

2015 International Conference on Pervasive Computing: Advance Communication Technology and Application for Society, ICPC 2015

Cumulative video analysis based smart framework for detection of depression disorders

There is a long list of words that describe depression; sadness, unhappiness, sorrow, dejection, low spirit, despondency, woe, gloom, pessimism, desolation, despair, hopelessness, moodiness, and a host of others. This study throws light upon the contribution EEG signal for depression analysis. In this paper, classification of depressed patients from normal subjects are identified by using EEG signal. Experimental results are carried out with the help of 13 depressed patients and 12 normal subjects. This paper tries to classify person's mental state either normal or depressed with the help of EEG signal using signal processing technique FFT and machine learning technique SVM. These noninvasive signal techniques are useful for detection of depression disorders through EEG signals. The proposed work is compared with the other methods. The diagnosis is done and appropriate remedies are taken according to scale of the depression in the patient. This work shows that linear analysis of EEG can be an efficient method for identifying depressed patients from normal subjects. It is recommended that this analysis may be a supporting aid for psychiatrists to identify severity level of depressed patients. © 2015 IEEE.

IntelliSys 2015 - Proceedings of 2015 SAI Intelligent Systems Conference

Non invasive EEG signal processing framework for real time depression analysis

Facial expression analysis plays pivotal role for all the applications which are based on emotion recognition. Some of the significant applications are driver alert system, animation, pain monitoring for patients and clinical practices. Emotion recognition is carried out in diverse ways and facial expressions based method is one of the most prominent in non verbal category of emotion recognition. The paper presents detection of all the six universal emotions based on statistical moments i.e. Zernike moments. The features extracted by Zernike moments are further classified through Na{\"{i}}ve Bayesian classifier. Rotation Invariance is one of the important properties of Zernike moments which is also experimented. The simulation based experimentation provides average detection accuracy as 81.66% and recognition time less than 2 seconds for frontal face images. The average precision with respect to positives is 81.85 and average sensitivity is obtained as 80.60%. Robustness of system is verified against rotation of images till 360 degrees with step size as 45 degrees. The detection accuracy varies with reference to emotion under consideration but the average accuracy and detection time remains at par with frontal face images.