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;

&nbsp;

MIT World Peace University

Engineering and Technology

Background:Approximately 50% patients with a deep bite possess anatomically extruded mandibular canines. Objective:The objective of this study was to specify an optimum toe (Θ) of the vertical segment of a cantilever from the distal aspect to achieve pure intrusion of a mandibular canine with the segmented arch in lingual orthodontics (LiO). Methods:The geometrical model of a mandibular canine was developed to compute the required values of Θ (positive values – toe-in, negative values – toe-out). Different positions of the cantilever attachment on the lingual bracket top (occlusal) surface were considered according to different heights (h) from the cusp of a canine i.e. 2, 3, 4 and 5 mm in each case of horizontal distance (x) from canine surface i.e. 2 and 3 mm. In x=2mm case, the required values of Θ at h=2,3,4 and 5mm were −5°, 0°, +6° and +11° respectively. While, in x=3mm case, the required values of Θ at h=2,3,4 and 5mm were 0°, +5°, +12° and +17° respectively. Results:In finite element analysis (FEA), the computed values of Θ were verified by displaying the results of a mandibular canine movement in the form of vectors of nodal displacements along with undeformed and deformed models. Conclusions:In the cases of x=2mm and 3mm, no toe angles were required at heights h=3mm and 2mm respectively. Hence, these can be considered as better positions of the cantilever attachment than others.

School of Mechanical Engineering

World University root node

Bio-Medical Materials and Engineering

Optimum pure intrusion of a mandibular canine with the segmented arch in lingual orthodontics

Driving an automobile taxes the driver in almost all of his sensory systems and uses his deduction power to the fullest. The mental state of the driver is vital to safe and correct driving. This paper focuses on identifying the emotional state of the driver based on his interactions with the automobile while driving and inferring when the driver is in an unpleasant state of mind. The driver's actions are monitored and driver profiles are generated which lead to identifying his usual behavior. If the behavior of the driver, based on his actions and interactions with the automobile, implies he is in a negative state of mind, we propose to deviate his mind from negative to positive emotions. For this we have instrumented a system which is both single mode and multimodal to alert the driver with includes feedback in the form of auditory, haptic and visual. © 2016 IEEE.

School of Computer Engineering & Technology

2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)

Automobile driver profiling: Infering emotions through actions for safe driving

While browsing the web, the meaning and importance of time changes as perspectives change. From the communications perspective, speed to data transmission matters. The network perspective webpage load times matter. Search Engine Optimisation perspective focuses on dwell time, total time spent on each webpage from the corpus of webpage's visited. From an average user's perspective, the initial few seconds of a webpage being visited is critical to determine whether the user will stay on the webpage or leave the webpage. The probability of the user leaving the webpage is very high during these first few seconds. After the user stays on the webpage, determining whether it is relevant to the user, is he actually engaged on the content represented on the webpage during the period of the visit is important too. Higher engagement indicates the user has a higher chance of returning to the webpage. This paper tries to address another issue of time, and intends to determine, whether the time spent by a user on a webpage actually indicates its relevancy to the user. © 2016 IEEE.

Time alone is not the clear indicator of relevancy

Selfie is the act of taking self portrait through the front camera of the mobile. By visualizing the captured image one can identify the details regarding the image such as number of objects, location and much more. By the method of object recognition in the image we can identify whether the image taken is a selfie or not. For this we should first segregate both the foreground and background details from an image. From the details of foreground one can identify the object (i.e., the person taking the selfie) and from the background we can tell about the location. Using various object recognition methods such as exhaustive search, segmentation, selective search, Gaussian mixture model the information regarding objects, foreground and background can be detected. And further the value of foreground and background will be compared with a certain threshold value and according to the obtained result can recognized whether an image is a selfie or not. In this paper we are presenting an approach which can be used to detect an image is a selfie. © 2019, Springer Nature Singapore Pte Ltd.

Cognitive Informatics and Soft Computing

An Approach to Detect an Image as a Selfie Using Object Recognition Methods

Heart Attacks are the major cause of death in the world today, particularlyin India. The need to predict this is a major necessity for improving the countrieshealthcare sector. Accurate and precise prediction of the heart disease mainly depends onElectrocardiogram (ECG) data. Heart disease is a major life threatening disease that causeto death and it has a serious long term disability. The time taken to recover from heartdisease depends on patient’s severity. Heart disease diagnosis is complex task whichrequires much experience and knowledge. Nowadays, health care industry contain hugeamount of health care data, which contain hidden information. Advanced data miningtechniques along with computer generated information are used for appropriate results.Neural Network is widely used tool for predicting heart attack. A Heart Attack PredictionSystem we are going to develop using Neural Network and Genetic Algorithm. Thissystem calculates the number of hidden nodes for neural network which train the networkwith proper selection of neural network architecture and uses the global optimization ofgenetic algorithm for initialization of neural network.

Fulltext

International Journal of Latest Trends in Engineering and Technology

A survey on ECG signal monitoring through sensor and prediction of heart attack with the help of optimized neural network using genetic algorithm

This paper proposed development of Electric wheelchair for Brain Computing Interface(BCI) system to make contribution in biomedical field, these devices assist people who are physically handicapped, paraplegic patients can easily use the electric wheelchair using joystick or by some other interfaces but there is segment of people who suffer from diseases like motor neuron disease (MND) and they can not operate the wheelchair using interfaces like joystick, such people can only drive the wheelchair using eye blinking or brain signals. In some cases, electric wheelchair can be operated using BCI (Brain Computing Interface) and providing absolute control to such wheelchair is important, configuration of these wheelchair is discussed in this proposed system. Utilizing various resources to build cost efficient system, how sensors and drivers are being interfaced with the Microcontroller and their working to drive the wheelchair according to the acquired signal by brain.

School of Electronics & Communication Engineering

International journal of Engineering and Technology

Design and development of electric wheel chair for differently abled person

In this paper, an electromagnetic compatibility estimator is proposed using an artificial neural network with a scaled conjugate gradient algorithm. Neural networks are trained with the help of seven different optimization algorithms in MATLAB. Their performance is evaluated on the basis of number of neurons, desired output, and mean-squared error in offline mode in MATLAB. Among seven algorithms, scaled conjugate gradient algorithm is found to be the best choice. Hence, it is implemented in LabVIEW for online assessment of electromagnetic compatibility issues. Voltage dip, swell, and harmonics are generated with the help of an experimental setup. It consists of 230 V, 50 Hz input voltage supply, microcontroller, variac, and solid-state relays. It is interfaced to the LabVIEW software with the help of an NI USB 6361 data acquisition system. It enabled the continuous online monitoring of various signals. Along with voltage dip and swell, harmonics are also evaluated with the help of spectrum analyzer in LabVIEW. The detailed description of a hardware setup and mathematical modeling of trained network is given in this paper.

School of Electrical Engineering

IEEE Transactions on Industrial Informatics

Electromagnetic Compatibility Estimator Using Scaled Conjugate Gradient Backpropagation Based Artificial Neural Network

Subgrade strength is mostly affected by thickness of pavement, in Highway design. California Bearing Ratio (CBR) is the one of the method to determine the sub grade strength.CBR test is laborious and time consuming, hence a method is proposed for correlating CBR value with the LL, PL, SL, PI, OMC and MDD. In the present study, different soils samples (having 20

School of Civil Engineering

International Journal of Engineering Research in Mechanical and Civil Engineering

Establishing Relationship between CBR Value and Physical Properties of Soil

With enterprises collecting feedback down to every possible detail, data repositories are being over flooded with information. In-order to access valuable information, these data should be processed using sophisticated statistical analysis. Traditional analytical tools, existing statistical software and data management systems find it challenging to perform deep analysis upon large data libraries. Users demand a service platform that can store and handle large quantities of data with some features such as easy accessibility, fast performance, durable and secure. These features can be availed without having to spend too much on hardware, upgrading, configuring etc to perform analysis of big data. This project intends to overcome all these obstacles and built a user friendly SAAS platform. It is cloud based web application which stores data in Amazon S3. As this system supports dynamic and optimized cluster nodes size as per the desired time, user doesn't need to calculate and estimate the number of nodes. The system uses Amazon EMR and MapReduce paradigm using opensource R scripting language to perform analysis of bigdata analysis in desire time. © 2016 IEEE.

Proceedings of 2016 International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2016

High performance analytics of bigdata with dynamic and optimized hadoop cluster

Now a days, a lot of people and groups are using X.509 certificates to represent their identity, during online trade, so the level of purity and trustworthiness of these certificates becomes dubious. Hence, we have suggested a model which calculates the risk associated with X.509 certificates by evaluating Certificate Practice statement (CPS) document and by using certain trust criteria. For evaluating CPS document we have proposed a novel algorithm which locates certain attributes, in the CPS document. We are referring to these attributes from the prior paper of Omar and Lindsay. Our model categorizes risk in three levels-High, Medium and Low risk. It has application in detecting phishing websites which contain Https URL. © 2016 IEEE.