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

Presently there is major interest in visual surveillance systems for crowd analysis. For preventing the problems caused by large crowd, proper control and management is necessary. In this paper a novel individual feature is introduced and used in combination with the holistic features, to describe crowd density. Various databases are analyzed to check the validity of the feature extraction process. In order to cluster the crowd frames according to congestion degree Support Vector Machine and Artificial Neural Network are used as classifiers. Results obtained shows that the proposed feature performs well in classifying real-world crowd scenes. © 2019 IEEE.

School of Electronics & Communication Engineering

2019 International Conference on Innovative Trends and Advances in Engineering and Technology (ICITAET)

Feature based approach for Efficient Crowd Density Estimation

Development of new construction materials, capable of absorbing more energy is the need of the society and this the area in which research needs. Because of the excellent behavior under flexural and impact strength, ferrocement is the widely used structural element under such circumstances. Also it has excellent mechanical properties. The thickness of ferrocement panel considered is 40 mm and 50 mm. As the thickness of the ferrocement panel is very less, M50 grade of mortar is used. The ferrocement panels are casted using galvanized welded square mesh and galvanized woven square mesh with 04, 05 and 06 mesh layers. For crack controlling, few ferrocement panels are casted using corrugated steel fibers and hooked steel Fibers in addition to the regular mesh (1% by weight of sample). The ferrocement specimens are tested under drop weight impact test. The drop weight impact test is done by dropping a weight of 3.5 Kg from a height of 0.5m and 0.75m. It is concluded that, the impact strength of the ferrocement panel reinforced with galvanized welded square mesh is excellent than the ferrocement panels reinforced with galvanized woven square mesh. When the steel fibers are added in the ferrocement panel, the energy absorption capacity of the ferrocement panel under impact loading is increased. The ductility index is found to be decreased with increase in the drop weight height. © IJSTR 2019.

School of Civil Engineering

World University root node

International Journal of Scientific and Technology Research

Effect of different meshes on the energy absorption of ferrocement panel

Due to the recent increase in various terrorist activities all over the world, the safety of the structures should be designed to resist bomb blasts. Blast loads are basically dynamic loads of a type that needs to be attentively calculated like wind and seismic loads and the structures should be designed by considering them to make it blast resistant. The behavior of Steel Fibre Reinforced Concrete (SFRC) under the condition of blast loading is presented in this paper. The panel of 50mm thickness is taken into consideration. The effect of varying the aspect ratio of fibres in the fibre reinforced concrete is studied.

INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH

Comparative Study On SFRC Composites Under Blast Load By Varying Aspect Ratio Of Fibres

Effective human machine interaction systems areneed of the time so the work carried out deals with one of suchsignificant HMI tasks- automatic emotion recognition. Theexperimentation carried out for this study is focused to facialexpressions based emotion recognition. Two techniques ofemotion recognition based on hybrid features are designed andexperimented using JAFFE database. The first techniquereferred as "Hybrid Method1" is designed around featuredescriptor obtained through local directional number &amp;principal component analysis and feed forward neural networkused as classifier. The second technique referred as "HybridMethod 2" is designed around feature descriptor obtainedthrough histogram of oriented gradients, local binary patternand Gabor filters. PCA- principal component analysis is used fordimensionality reduction of feature descriptor and k-nearestneighbors as classifier. The average emotion recognitionaccuracy achieved through method 1 and method 2 is 85.24%and 93.86% respectively. Effectiveness of both the techniques iscompared on the basis of performance parameters such asaccuracy, false positive rate, false negative rate and emotionrecognition time. Emotion recognition has wide applicationareas so the work carried out can be applied for suitableapplication development.

School of Computer Engineering & Technology

Fulltext

International Journal of Recent Technology and Engineering (IJRTE)

Facial Features Based Hybrid Methods for Emotion Recognition

In India, the concept of smart city has evolved since lastfew years. Smart city includes smart electricity distributions,smart parking, smart lighting on streets, smart water distribution,smart drainage system, smart pipe gas system, smart trafficcontrol system etc. All smart systems listed need smart use oftechnical solution so that all systems will play critical role inmaking city as smart. As far as smart traffic control is concerned,there were few solutions suggested and implanted such as sensorwith CCTV, camera with IR sensor and tags etc. The technicalsolution may include software, hardware, communicationmodels, networking, usage of data and of-course data analytics.As large amount of data may be generated by theobjects/components involved in the system, it must be analyzedproperly. The data may be in structured or un-structured format.In this paper, smart traffic control system with efficient algorithmhas been proposed with data analytics to control traffic, whichcontrols the timing of the signal dynamically. At a junction, thereis need to control the traffic and signal timing such that air andnoise pollution also will be monitored and controlled. In thismodel, IoT system has been proposed with ultrasonic sensors tocontrol the traffic. The signal timing will be dynamicallymonitored and adjusted with traffic density within a region. Thiswill give solution to control, monitor the traffic at every signal ina city

IJEAT

Proposed Algorithm for Smart Traffic Control using Ultrasonic Sensors

eLearning is the use of technology in providing education via various online resources. It has the potential to change the whole education system. Recommendation Systems are schemes that aim to provide the user with the most appropriate and precise products by filtering helpful data from a wide information base. A recommender system in the eLearning environment is a software agent that tries to intelligently recommend actions to a learner by various methods. This paper is a compilation of various techniques that are used by recommender systems in eLearning platforms. Also it focuses on deep learning techniques to enhance eLearning Recommendation system.

2019 IEEE Pune Section International Conference, PuneCon 2019

Recommendation System for Enhancing eLearning using Deep Learning

Blind people have been using a simple white foldable stick as an aid for their daily activities since many years. The idea in this project is to develop an intelligent solution - A Smart Blind Stick, an IoT-based project that has Ultrasonic Sensors using which the distance of any obstacle can be measured and provides output in the form of buzzers. RF transmitter and receiver will be used to locate the stick. Additionally, GPS navigation will be provided for the complete navigation and guidance of the blind person. Live location tracking of the blind will be facilitated to the nearest help centres or their relatives in case of any emergency. Face detection

Recent Trends in Information Technology and its Application

Smart Stick for Blind: A Survey

The number of mobile users is increasing every day. Increased user cause extra stress on base trans-receiver station (BST) covering particular area, which result into extra power requirement of that antenna. Because of less energy, developing an intelligent energy management system for switch mode power supply (SMPS) is more important to use power efficiently. Objective is to distribute the energy to four different telecom operator effectively. Measure energy consumption by each of the telecom operator using that SMPS. Another objective is to monitor energy consumptions at remote location for each operator using Internet of the things (lOT). © 2018 IEEE.

Proceedings of the 2nd International Conference on Intelligent Computing and Control Systems, ICICCS 2018

Design and Development of Smart Energy Management Scheme for SMPS Used in Mobile Towers

Underwater acoustic sensor networks (UASNs) are used to explore underwater environment, study aquatic life and gather data regarding geographical variations. Since the communication medium used in UASN is water, they are different from other networks. Major Challenges that affect data transmission include higher energy consumption, higher propagation delay and low bandwidth. The proposed method reduces the energy consumption of the network. Firstly the node forms a group of forwarding nodes based on fitness factor and density (i.e. no. of neighbor present around source node). Among the group of forwarding nodes, the node having maximum packet delivery ratio and highest energy is selected using fuzzy logic based relay selection (FLSR). As huge amount of energy is wasted during collisions among packets while transmission. Since the sensor nodes have restricted energy, the main challenge is to send packet till destination. Therefore to counter this problem, holding time is set for each of the group of relay nodes to avoid collisions. The simulations are performed in Aqua-sim and the results are compared with other protocols. © 2018 IEEE.

Energy Efficient Routing Protocol for Underwater Acoustic Sensor Network

Personality is an important parameter as it differentiates various individuals from one another. Personality prediction is an evergreen area of research. Predicting personality with the help of data through social media is a promising approach as this method does not require any questionnaires to be filled by users thus reducing time and increasing credibility. Thus having knowledge of personality is an interesting domain for researchers to work on. Predicting personality has many applications in real world. Use of social media is increasing day by day. Huge amount of textual data as well as images continue to explode to the web daily. Current work focuses on Linear Discriminate Analysis, Multinomial Naive Bayes and AdaBoost over Twitter standard dataset. © 2019 IEEE.