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

Crowd density analysis is very imperative for intellectual video surveillance to help in management and control of crowds for safety. In recent years, more and more datasets dedicated to crowd density estimation, crowd analysis and anomaly detection in crowded scenes have been created. The use of these dataset allows us to compare different crowd density estimation methods with the same input data. The survey introduced in this paper compares different crowd datasets for crowd density estimation methods. © 2016 IEEE.

School of Electronics & Communication Engineering

2016 International Conference on Global Trends in Signal Processing, Information Computing and Communication (ICGTSPICC)

A survey of video datasets for crowd density estimation

Flexure mechanisms have massive range in various industrial application required for high precision and frictionless motion. There are many study on concept to make precision manipulators, but only some of them can achieved to satisfy the high speed with precision. Pro-E software is used for parametric modeling of XY positioning table ANSYS is used for Static analysis and dynamic analysis. Deflection of motion is concluded by static analysis with force. The Deformation of XY mechanism is equivalent to S-shaped cantilever beam deformation. Force and deformation curve is linear. There results get compare with mathematical calculation with FEA results

World University root node

School of Mechanical Engineering

International Journal for Research in Technological Studies

Design and Experimental Validation XY Positioning Table

Nucleic acid amplification of biomarkers is increasingly used to monitor microbial activity and assess remedial performance in contaminated aquifers. Previous studies described the use of filtration, elution, and direct isothermal amplification (i.e. no DNA extraction and purification) as a field-able means to quantify Dehalococcoides spp. in groundwater. This study expands previous work with direct loop mediated isothermal amplification (LAMP) for the detection and quantification of Dehalobacter spp. in groundwater. Experiments tested amplification of DNA with and without crude lysis and varying concentrations of humic acid. Three separate field-able methods of biomass concentration with eight aquifer samples were also tested, comparing direct LAMP with traditional DNA extraction and quantitative PCR (qPCR). A new technique was developed where filters were amplified directly within disposable Gene-Z chips. The direct filter amplification (DFA) method eliminated an elution step and provided a detection limit of 102 Dehalobacter cells per 100 mL. LAMP with crudely lysed Dehalobacter had a negligible effect on threshold time and sensitivity compared to lysed samples. The LAMP assay was more resilient than traditional qPCR to humic acid in sample, amplifying with up to 100 mg per L of humic acid per reaction compared to 1 mg per L for qPCR. Of the tested field-able concentrations methods, DFA had the lowest coefficient of variation among Dehalobacter spiked groundwater samples and lowest threshold time indicating high capture efficiency and low inhibition. While demonstrated with Dehalobacter, the DFA method can potentially be used for a number of applications requiring field-able, rapid (&lt; 60 min) and highly sensitive quantification of microorganisms in environmental water samples. © 2016 Elsevier B.V.

School of Civil Engineering

Fulltext

Journal of Microbiological Methods

Direct loop mediated isothermal amplification on filters for quantification of Dehalobacter in groundwater

X.509 certificates empower to reveal the unique identity of the parties participating in the conversation. Right now, during online exchanges, many people and groups are using X.509 certificates to represent their identity, so the level of excellence and reliability of these certificates become dubious. Hence, we introduced a framework which computes risk associated with X.509 certificates with the assistance of certain trust criteria and attributes. For assessing risk related with certificate, we utilized Random Forest ensemble machine learning algorithm, which categorizes risk in three levels- High, Medium and Low. User needs to input the certificate and the system will predict the risk associated with that certificate. If predicted risk is high or medium, system will specify the parameter due to which it triggers risk. Our framework can be applied in browser-server communication and identifying real-time phishing websites which have Https URLs. © Springer International Publishing AG 2016.

School of Computer Engineering & Technology

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Risk evaluation of X.509 certificates–a machine learning application

The commercial and industrial applications, namely, business form reading, bank cheque reading, and full postal address reading, have constituted the majority of the market for handwriting recognition technology. Devanagari is the most popular script in India and is used to write texts in Hindi, Marathi and Nepali languages. Significant amount of work has been done on Devanagari isolated characters. Very few attempts have been made for Indian postal system automation. This paper presents the challenges involved in Indian postal system automation with a case study. This paper also throws light on the existing research literature support available for doing the postal automation.

International Journal of Applied Engineering Research

A survey on devanagari character recognition for Indian postal system automation

Due to the sheer volume of data available on the internet, the problem of information overload is an ever increasing one. Personalization systems based on user profiles tend to assist the user in his day-to-day tasks by recommending 'relevant' content to the user based on his previous web usage and navigation patterns. These user profiles hold more and more information about the user, his likes, dislikes as it learns about the user over time. Privacy and security issues of the 'user profiles' becomes far the more important as the user profiles actually reflect the user itself albeit in a pseudo form. © 2016 IEEE.

2016 International Conference on Internet of Things and Applications (IOTA)

Personalization in user profiling: privacy and security issues

The Web is a vast pool of resources which comprises of a lot of web pages covering all aspects of life. Understanding a user’s interests is one of the major research areas towards understanding the web today. Identifying the relevance of the surfed web pages for the user is a tedious job. Many systems and approaches have been proposed in literature, to try and get information about the user’s interests by user profiling. This paper proposes an improvement in determining the relevance of the webpage to the user, which is an extension to the relevance formula that was proposed earlier. The current work aims to create user profiles automatically and implicitly depending on the various web pages a user browses over a period of time and the user’s interaction with them. This automatically generated user profile assigns weights to web pages proportional to the user interactions on the webpage and thus indicates relevancy of web pages to the user based on these weights. © Springer International Publishing Switzerland 2016.

Proceedings of First International Conference on Information and Communication Technology for Intelligent Systems: Volume 1

A Framework to Infer Webpage Relevancy for a User

User profiles are important in many areas in which it is essential to obtain knowledge about users of software applications. Knowledge about a user includes his likes, dislikes, even his emotional state can be determined by user profiling. In this paper we examine what information constitutes a user profile; and how the profile information is used to get the emotional state of a user. We also study the main issues regarding user profiles from the perspectives of these research fields. © 2016 IEEE.

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

Inferring emotional state of a user by user profiling

Hydrodynamic cavitation offers distinct advantages for water disinfection and waste watei treatment particularly at large scales of operations. For applying hydrodynamic cavitation foi water disinfection/treatment, water stream to be treated is passed through a fluidic device ir which there exists a low pressure region. Cavities are generated in this region when the pressurt falls below vapour pressure (in absence of any dissolved gases). These cavities are then collapsec when they travel to regions of higher pressure and lead to very high shear, temperatures anc pressures in localized regions. These high pressure/temperature as well as high shear facilitati disinfection as well as reduction in chemical oxygen demand, colour and amonical nitrogen in the water. In this work, we have investigated hydrodynamic cavitation generated by five difieren orifices have been studied which have different shapes with same fractional open area and have tested their effectiveness for water disinfection. The efficacy of generated cavitation on wate disinfection was quantified based on measurements of non-pathogenic E. coli colony forminj units (CFU/mL). The presented results and analysis will be useful for designing hydrodynamii cavitation based systems for water disinfection.

School of Chemical Engineering

Pollution Research

Effect of Orifice Shape on Water Disinfection Efficacy

Due to ever increasing size of datasets with an extremely high number of attributes, mining of datasets turns out to be a universal scenario in various fields such as, industry, social and scientific areas. In order to search with very large databases, clustering is an important tasks required in various applications. Moreover, clustering algorithms that provide better scaling to very big data are significant and useful. When the size of the data become too big, it is unfeasible to store it in a single computer memory and also it consume more time for entire kernel matrix computation. In order to alleviate this problem, we propose a multiple kernel and a swarm-based MapReduce framework for big data clustering to improve the clustering accuracy. To map the input data, we implement a new clustering algorithm using tangential kernel and spherical kernel, which is used for calculating the relevant cluster centroid. Then, particle swarm based optimization (PSO) is utilized in reducer function, where the fitness value is calculated using Davis-Bouldin (DB) index. The proposed multi kernel swarm based MapReduce framework is experimented with skin and localization data sets. It can be concluded that, the proposed MKSMRF achieves higher clustering accuracy of 81% and 85% for localization and skin dataset respectively, as compared with other clustering algorithms.