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

Deep bite is a condition in which the maxillary and mandibular arch of teeth overlap with each other. Mandibular central incisor and mandibular canine are extruded significantly in this case. Hence, they need to intrude apically. The segmented arch technique is more effective than any other method for the correction of deep bite. However, there is no significant research to use a segmented arch technique in lingual orthodontics. Hence, the aim of the present research study is to specify accurate tilt (toe) angles in lingual orthodontics (LiO) required for intrusion of the mandibular central incisor and mandibular canine tooth for different positions from respective occlusal plane and to state comparative assessment of required tilt angles for both the teeth. For this purpose, single intrusive force was considered to act from top surface of a lingual bracket of the mandibular tooth. The position of application of intrusive force was considered from two factors, i.e. horizontal distance of bracket top surface from tooth surface and vertical distance of bracket top surface from an occlusal plane. In the present study, four different values of vertical distance of bracket top surface from an occlusal plane were considered. Thus, four different positions of application of intrusive force were considered for both the teeth (mandibular central incisor and mandibular canine). Required (optimum) tilt angles were computed mathematically for each tooth to pass the intrusive force vector through Cres. It is then verified with finite element analysis of CAD models of tooth assemblies. For the mandibular central incisor, the tilt angle was found to be 0 degrees for vertical distance of 3 mm from an occlusal plane (OP). While, for mandibular canine, the tilt angle was found to be 0 degrees for vertical distance of 2 mm from an occlusal plane (OP). Hence, these positions of point of application of intrusive force can be considered as better positions than others clinically.

School of Mechanical Engineering

Materials Today: Proceedings

Computation of optimum parameters to achieve the intrusion of mandibular central incisor and mandibular canine for deep bite treatment

Traditionally welding is considered as an art rather than a science. The quality of the weld is dependent on the skill and intuition of the welder. The welding process is mostly not reliable and labor-intensive. The solution to the problems in welding lies in utilizing intelligent welding techniques where in the selection of weld parameters like voltage, current, speed etc and defect control is done intelligently by the automated welding system. The intelligent welding system shall comprise elements, viz., control system, sensing, design and modeling of process and application of artificial intelligence. The application of intelligent welding system has developed into a new field of automation called as 'Integrated Computational Welding Engineering (ICWE)'. The welding of titanium and its alloys is predominantly dependent on the skill of the welder. Majority of research and industrial practice is based on the traditional manual welding process and hence it is prone to defects deterioration of metallurgical, mechanical and corrosion properties. There is scope in adopting ICWE in welding of titanium and its alloys. © Published under licence by IOP Publishing Ltd.

World University root node

Journal of Physics

An Insight into the Scope of Implementation of Intelligent Welding in Welding of Titanium

High Pressure Grinding Rolls - HPGR is a relatively new technology first implemented in Europe into Cement Industry and later incorporated into Mineral industry in the late 20th century as replacement to conventional mills like rod and ball mills due to the higher efficiencies offered by them in comminuting the material fed to the mill. These are heavy duty machines designed to operate for 60–100 thousand hours, hence making millions of revolutions in their lifetime at the operating speed of 14–17 RPM sustaining thousands of Kilo-Newtons of force. As a result these machines are very expensive and bulky which makes their failure and other serious damages a very expensive affair. Hence, it is necessary to make sure they are designed and operated properly so as to avoid serious breakdowns without compromising. One such HPGR was found to be failing at half of its designed lifetime. This paper covers the detailed Finite Element Simulation done on Ansys Workbench 2019 R2 which is validated through numerical calculations of shaft design under combined and fluctuating load according to ASME code standards. The design shortcomings are found out and minimum strength required for the roll and shaft assembly is proposed. © 2021

Materials Today Proceedings

Finite element analysis of high- pressure grinding rolls for crack prediction to determine safe working conditions

Ever since the start of the electronic age, soldering has been an important interconnecting method in microelectronic packaging. Since the 1960s, development of information technology (IT)-infrastructure has witnessed rapid advancement owing to development of novel electronic equipment. This, in turn, has led to growth and progression of industries and improved human lifestyle. Present-day electronic gadgets are highly sophisticated and comprise several components. Sn-Pb based solder alloys have always delivered excellent results, offering several amazing benefits, namely, easy handling, low melting temperature, good working condition, ductility, and exceptional wetting on Cu and its alloys. Owing to its lethal and harmful effects on health and the environment, the US Congress introduced the legislation on the limited use of Pb in 1990. Consequently, alternatives to lead free solders are being developed for last three decades. This literature review discusses the effect of Gallium, Phosphorus and Nickel addition on solder alloy microstructure and mechanical properties. © 2020 Elsevier Ltd. All rights reserved.

Effects of gallium, phosphorus and nickel addition in lead-free solders: A review

Of late, the research world has been vigorously involved in, inventing strategy and techniques to improve the spontaneity of Human Computer Interaction (HCI). Gesture recognition is one of the most probable techniques in this area. The eventual aim here is to introduce an intelligent system for hand gesture recognition in both static and dynamic area, which is still a challenging point due to the lag of valuable beneficial methods. The main intent of this paper is to implement an efficient hand gesture recognition model considering both static and dynamic datasets for Indian Sign Languages (ISL). In static type, images are taken for processing, whereas video frames are used for processing the dynamic type. The proposed recognition model involves five main steps "(a) Image pre-processing, (b) gesture segmentation, (c) Feature extraction, (d) Optimal Feature Selection, and (e) Recognition". In the pre-processing phase, greyscale conversion and histogram equalization are performed. The pre-processed image is subjected to the segmentation process, where the Active Contour model and Canny Edge Detection is implemented. In the feature extraction phase, both the contour image, and the edge detected image is deployed, in which Histogram of Oriented Gradients (HOG) features are extracted from the contour image, and Edge Oriented Histogram (EOH) features are extracted from edge detected images. To reduce the dimension of HOG, and EOH features, Principle Component Analysis (PCA) is applied. Further, the region props features are extracted for both contour and edge detected image. Finally, all these features are summed, and the optimal feature selection process performs here to select the unique feature giving different information with less correlation. Finally, the recognition classifier called Neural Network (NN) is adopted, where the new training algorithm is used to update network weight. Dynamic Time Warping (DTW) method helps to remove the repeated frames in the video and to reduce the time consumption of testing. In both feature selection and classification, a hybrid algorithm Deer Hunting-based Grey Wolf Optimization (DH-GWO) is used for selecting the features and weight update in NN as well. Hence, the integration of a hybrid meta-heuristic algorithm is highly efficient for recognizing the characters for images and words for videos with high recognition accuracy. © 2020 Elsevier Inc.

School of Electronics & Communication Engineering

Computer Science Review

Automatic hand gesture recognition using hybrid meta-heuristic-based feature selection and classification with Dynamic Time Warping

Application of polymer and polymeric composite materials in dental implant has shown a drastic increase due to their added advantages. Since dental implant material has been limited to continuous usage of metal/composites, but it possesses certain limitations urging the researchers to find a substitute to the orthodox dental implants. With surface and bulk alterations done polymer materials can be regarded as a futuristic substitute for conventional materials with induction of promising properties like less weight than metals. With the further addition of nano-fillers and reinforcements, biocompatibility and bioactivity shows significant improvement. This review document assess the various articles published in the domain of polymer materials which have been tested in various scenarios of in-vivo and invitro conditions, which are supported by several laboratory observations recorded providing concrete evidence of possible usage in dental applications. Tests mentioned for these materials includes biocompatibility, strength and Finite element analysis in predicting the properties of the polymer/polymer Composites.

Current advancements in polymer/polymer matrix composites for dental implants: A systematic review

A dental implant’s success and survival rate is often affected by the complexities involved during the dental implantation. This has led the dental implant research towards the techniques and ideas in minimizing the complexities during surgery and increasing the survival. The implantation involving the unavailability of bone quantity must be treated with a solution of complicated bone augmentation techniques. Short implants are now considered as a viable alternative to these complicated techniques. The emphasis of this review article has been on the information about the various influences that govern the success of short implants. It is important to consider the various biomechanical factors and prosthetic design parameters so as to avoid the failure of short implants. Also, several Randomized Controlled Clinical Trials (RCTs) of short implants have been considered that experimentally test the effectiveness of short implants. A review of FEA studies has been included that give the solution for difficult problems involving complex geometries. Thus, a detailed understanding of the short implants would help the dentist to decide the length and diameter of the short implants which are important parameters. This can also help in reducing the complex surgical procedures. However, further research is necessary so as to see how the variation in several factors at the same time affects the survival rate and success of short implants

AIP Conference Proceedings

A review on biomechanical factors and prosthetic design parameters on survival rate of short implants

Depression is a common and severe medical condition which adversely affects your feeling, thinking and acting. Depression can lead to suicide. It can trigger a slew of physical and emotional issues, as well as a reduction in your ability to function at work and home. Globally, depression affects more than 264 million individuals of all ages [1]. Since the younger generation is more reliant on social media, analyzing posts on social media will benefit in detecting depression. This research work has proposed a system to detect depression using ensembled learning and Natural Language Processing (NLP) techniques. Also, the proposed research work has compared the performance of multiple machine learning algorithms and the best performing configuration gave us the accuracy of 96.35%.

School of Computer Engineering & Technology

2021 Second International Conference on Electronics and Sustainable Communication Systems (ICESC)

Use of Ensemble Machine Learning to Detect Depression in Social Media Posts

Human behaviour and actions are greatly affected by their emotions. Through human computer interactions (HCI) interpreting of emotions has become easier. Modals like Facial Emotion Recognition(FER) that considers the facial features of the human, Speech Emotion Recognition (SER) that concentrates on the texture of human speech, Electroencephalography (EEG) that deals with brain waves and Electroencephalogram(ECG) that focuses on one’s heart rate are few of the widely used unimodels that are in place for recognizing emotions. In this paper we see how multimodal system tends to provide higher accurate results than the unimodels in existence. In order to implement the multimodal system two fusion methods were considered that are Feature Level Fusion and Decision Level Fusion. It was observed that Feature Level Fusion was preferred by most researchers due to its capability of providing more valid results in case of compatible features. Facial-Speech, Speech-ECG and Speech-Facial are few of the well liked multimodals that have been implemented by varied researchers. Out of these Facial-EEG provided most robust and efficient outputs.

2021 International Conference on Computational Intelligence and Computing Applications (ICCICA)

Multimodal Techniques for Emotion Recognition

Maritime surveillance is very crucial for every nation even if it is surrounded by land. The surveillance can not only inform about the threats and illegal activities but also manage the traffic and regulate a lot of movement on water. With more and more satellites with Synthetic-Aperture Radar (SAR) and other capabilities to capture high-resolution images being launched, automation of ship detection from these images is now a necessity. The experiments are performed on satellite image datasets where various encoders and loss functions for the Unet model are evaluated based on segmentation results over the test dataset. Our research and analysis of these encoders and loss functions for the Unet model lead us to certain conclusions as to which situation would benefit from which of the loss function and encoder and their combination. The research shows that the modes are robust and can perform well even with difficult backgrounds like clouds, waves etc. Our best model archived 0.823 on F2 score at different IOU thresholds on Airbus ship detection challenge test dataset. © 2021 IEEE