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

Every robotic arm has a specific work envelope and a predefined trajectory that it must follow to complete any task. Geometric calculation for determining joint angles and velocity involves complex trigonometric calculations and derivations which are not simple enough to actuate in a control software. Many times, geometric calculation also tend to become unsolvable due to complex work envelopes. Though iterative algorithms provide generalized solution to every serial link manipulator possible, it is computationally very expensive. If the number of nodes is large, this further aggravates the situation. The paper focuses on the methodology to combine iterative and geometrical methods to find inverse kinematics solutions to a 4 Degree of Freedom (DOF) robotic arm. Thus, the paper aims at establishing a bargain between geometric method complexities and iterative method computational load. Iterative method is employed for certain links and geometry is applied for rest of the links to achieve the desired end location with minimum error possible while adhering to the constraints of the work envelope. © 2019 IEEE.

World University root node

School of Electronics & Communication Engineering

2019 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2019 - Proceedings

Inverse Kinematics Solution for a Robotic Arm Through Geometric and Iterative Fusion Based Modelling

School of Computer Engineering & Technology

IJERT

Social Media Mining for Suspicious and Offensive Keywords : Twitter

Asian Journal For Convergence In Technology (AJCT) ISSN-2350-1146

Mood Detection through Aesthetic Assessment of Videos using Deep Learning

Emotion analysis is very significant from the perspective of many applications like E-learning, cognitive assessment, driver alert system, pain monitoring system, healthcare services, interactive TV, animation etc. Outcome of the work is depicted in the form of emotion profile which is defined as graphical representation of the degree of presence or absence of all the universally accepted seven emotions on a single scale. This simple but unique representation helps in determining the presence of complex/naturalistic emotions. Complex emotions represents the emotional state of a person when he/she is able to feel and express more than one emotions simultaneously at the time of observation. Emotion analysis through facial expressions is experimented on JAFFE and MIST Database-a locally created context specific database of images. Images of the subjects under study are captured and experimented for all seven universally accepted emotions and depicted in the form of emotion profiles. Emotions are categorized as neutral, positive and negative for MIST database and in seven categories of emotions like happy, surprise, anger, sad, disgust, fear and neutral for JAFFE database. Average accuracy obtained as 91.31% for MIST database and 93.84% for JAFFE Database. FPR-false positive rate and FNR-false negative rate, values for JAFFE database are 6.38% and 6.62% respectively. FPR and FNR values for MIST database are 8.18% and 8.60% respectively. Emotion recognition time for JAFFE database 1.108 sec and for MIST database 1.392 Sec. These performance parameters especially the accuracy more than 90% which is at par with the research results published in renowned journals in this domain makes this work qualify to be used for various applications. Analysis of complex emotions is typically useful for the professionals working in the field of Human resource, clinical psychology, cognitive analysis etc. More accurate emotion recognition is still challenging and open research problem.

Journal of theoretical and Applied Information Technology

Hybrid Approach for Facial Cues Based Emotion Profile Generation

This Paper shows the effect of port fuel injection pressure of CNG in 3-cylinder SI Engine at Wide Open Throttle position using sequential port fuel injection system. All trials are performed on 4-stroke, 796 cc MPFI S.I engine at injection pressure of 2.0, 2.2, 2.4, 2.6, 2.8 bar for constant speed of 2500, 3000, 3500, 4000 & 4500 rpm. During the trial compression ratio is kept constant at 9.2 with Maximum Brake Torque (MBT) spark timing of 15oBTDC. Optimum torque is obtained for CNG at injection pressure of 2.6 bar and 3000 rpm. Gasoline trials are performed at same compression ratio for comparison with CNG at same injection pressure. Performance and emission characteristics with combustion analysis are performed at optimum injection pressure of 2.6 bar.

School of Mechanical Engineering

Fulltext

International Journal of Recent Technology and Engineering (IJRTE)

Effects of CNG Injection Pressure on Performance, Emission and Combustion Characteristics of Multi-cylinder SI Engine

The objectives of this article were to review the literature on endodontic procedures published in various journals during the last two decades. The various obturation techniques, viz. single -cone technique, multiple-cone technique, chemo-plasticized gutta-percha, thermo-plasticized injectable gutta-percha, obturation using pastes, and SPAD/resorcinol formaldehyde, have been described and compared. The various methods used for qualitative and quantitative evaluation of micro-leakage, viz. micro-computed tomography, radiography, CT scans, cone-beam computed tomography, scanning electron microscope, fluid filtration method, dye penetration test, and bacterial leakage technique, have been described and studied by various researchers. The consultation with endodontic experts indicates that substantial improvements can be recommended on obturation procedure, and also, a few modifications may be required in obturation devices from productivity as well as ergonomics point of view. A total of 250 research papers and patents (19 Nos) have been shortlisted for conducting literature survey. The shortlisted paper was classified into various categories, viz. root canal obturation techniques (63 Nos), micro-leakage evaluation techniques (80 Nos), and root canal obturation sealing ability (75 Nos), root canal obturator design (36 Nos), and root canal geometrical parameters (25 Nos). The following statements are deduced from the above literature survey: (1) End outcome of the comparison of the various techniques revealed that warm vertical condensation is the best technique. (2) Consultation with the experts revealed that there is a need of obturator device which combines heat and vibration source. (3) The fluid filtration is the best technique as compared to other experimental techniques. Micro-computed tomography is the best qualitative and nondestructive technique. (4) There is a need for the development of an analytical model which can quantify the root canal obturation.

Lecture Notes in Mechanical Engg, Elsevier

A review of contemporary research on root canal obturation and related quality assessment techniques

Feature extraction of images are crucial in image retrieval systems. Many approaches are stated and proved by researchers for image feature extraction and processing. Research is being done from low-level feature extraction toward high-level feature extraction. This paper discusses the feature extraction from the DFT transformed color images in multiple color planes. DFT image transform provides effective way to differentiate the image textures. For dimensionality reduction statistical parameters such as kurtosis, standard deviation, and variance are used for feature vector generation. Euclidian distance is used in the proposed approach. Four different types of feature vectors are created and tested for each image class. The images are retrieved based on the image pixel values of DFT phase information and DFT magnitude information of different color spaces like RGB, YIQ, HSV, and YCbCr similar to that of image class. Image retrieval performance of the proposed approach is compared for database of 1000 images of ten different categories. Precision of image retrieval is above 60% for all classes and more than 80% for some of the image classes. © Springer Nature Singapore Pte Ltd. 2019.

Advances in Intelligent Systems and Computing

Color image retrieval using statistically compacted features of DFT transformed color images

Poor geometric accuracy of formed parts is one of the key drawbacks in incremental sheet forming (ISF) process. In present experimental study, ISF is combined with stretch forming (SF) to improve the accuracy of formed parts. Influence of process parameters namely preforming, preform tool radius, wall angle, and tool offset on the geometric accuracy of parts formed in ISF process is investigated. A hemispherical ended forming tool of stainless steel (SS-304) is used to form frustum of cones with wall angle from 30° to 70°. Experiments are designed according to Taguchi’s orthogonal array (OA). From the experimental results, it is found that there is considerable influence of wall angle, preforming, and tool offset on the geometric accuracy of formed part. As the wall angle increases, geometric error reduces considerably resulting in accurate part shapes. The results obtained in present study will certainly be helpful to improve geometric accuracy of sheet metal parts formed using ISF in industries. © Springer Nature Singapore Pte Ltd. 2019.

Lecture Notes in Mechanical Engineering

Incremental sheet forming: An experimental study on the geometric accuracy of formed parts

Breast cancer is a very aggressive type of cancer with a very low median survival. Today the deaths of women in the age group 15-55 are increasing because of malignant cells are increasing in breast. For the death of women it is the main cause. So, the possibility of improvement is only the early diagnosis of patients. Machine Learning (ML) techniques can assist the physicians by expanding tools for detection at initial stage and analysis of breast cancer thus increasing the probability of patient's survival [1]. At present, mammography is the best imaging strategy utilized by radiologist for screening breast tumours. In this paper, author proposes a system using different classification method like Support Vector Machine (SVM), Naive Bayes, Decision tree and MLP (Multi-Layer Perceptron) for early detection of cancer. Propose system extracts the texture based features and shape based features using LBP, GLCM, Otsu, Compactness, Fourier Transform. The main focus of the presented work is on application of MLP for breast cancer classification. In addition medical images data has been used to improve accuracy. Proposed system will do the comparative study between both datasets by extracting the feature with and without removing pectoral muscles. © 2019 IEEE.

2019 Global Conference for Advancement in Technology, GCAT 2019

Classification Methods to Improve Performance in Breast Cancer Screening

Design of Post-installed chemical anchors can be designed by referring European Guidelines. Evaluation of Service Report is done by ETA 16/0143. Design method is as per given in ETAG BOND (EOTA TR 029). Design and analysis of Chemical anchors are carried out by structural engineers. Newly developed Component Based Finite Element Analysis (CBFEM) method is used for determining the Anchor forces for Non Rigid Base plate. Rigid Base-plate assumption and non-rigid baseplate CBFEM methods are used for Anchor Calculation. Differences between results of these two methods are observed. Chemical Anchors are used for the study. Design is done on the Profis Engineering Software. © 2019 IJSTR.