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

Engineering changes in product are unavoidable and necessary to guarantee a high quality end-product. Focus should therefore to the reduction of costs per change rather than reduction in frequency of change. This will lead to lower overall product development costs and reduced time to market. Hence, the improvement of engineering change will most likely contribute to improve overall product life cycle management. Managing engineering changes across supply chain and disciplines within a single company is a non-trivial task. Thus, every time when change related information crosses company borders, translation and interpretation of data is needed. There is a need for individual ECM processes to communicate across the supply chain using a 'universal language' for ECM. This paper is providing focus to ensure quality of the modified data during change management and also to have good level of discipline across the supply chain.

World University root node

School of Mechanical Engineering

International Journal of Product Lifecycle Management

Implementing Engineering Change Management Through Product Life Cycle Management in Automotive Field

School of Computer Engineering & Technology

International Journal of Computer Applications (0975 – 8887)

Recognition of Isolated Handwritten Marathi Vowels using Symmetric Density and Moment Invariant Features

This paper presents the study of Support Vector Regression (SVR) to forecast the future streamflow discharge using past streamflow and rainfall data, which is closely related to regularization network and Gaussian processes. A Gaussian Radial Basis Function (RBF) kernel framework was built on the dataset to optimize the tuning parameters and to obtain the moderated output. It has been observed from various studies that the prediction ability of RBF kernel function is better for regression problems. The training process of Support Vector Machine (SVM) involves the selection of both kernel parameters and regularization constants. The constants such as $\gamma$, $\epsilon$, C and $\sigma$ are the parameters of SVR which were optimized to obtain the desired outputs. Where parameter C determines trade-off between model complexity and degree to which deviations are larger than $\epsilon$ are tolerated in optimization formulation and the parameter $\epsilon$ controls the width of $\epsilon$-sensitive zone. The study area include the upstream part of Jayakwadi dam. The prediction is based on flow at two Gauge and Discharge Sites (GDS) i.e. Kopargaon and Nagamthan and rainfall data at three Standard Rain gauge Stations (SRG) i.e. Rahata, Khirdisathe and Wadala Mahadev in Maharashtra, India. The daily data values of these stations for 18 years were collected from Hydrological Data User Group (HDUG), Nashik. About 70% of data were used for training purpose and remaining 30% of data were used for testing purpose. The experimental results showed that the SVR algorithm is reliable and efficient method for streamflow prediction, which has an important impact on the water resources management of region.

School of Civil Engineering

HYDRO 2015 INTERNATIONAL - 20th International Conference on Hydraulics, Water Resources and River Engineering

Streamflow Forecasting by using Support Vector Regression

Cloud computing are the modern way of staring data and other important resources the company wants to retrieve safely and conveniently. It offers an innovative way of investment especially to start up enterprises and adopt IT operations without high upfront costs. Despite its potential, cloud computing is affected by various security issues. These include account highjacking, data breaches, malware injection, data recovery, wicked inside attackers, segregation of data, lack of investigative support and shared vulnerabilities. The challenges facing cloud computing include security and privacy, application issues, accessibility, continuous evolvement, interoperability issues, service level agreements and data center issues.

Iarjset

Security Issues and Challenges in Cloud Computing

Medical image segmentation using PCA and k-mean clustering algorithm

Now-a-days Cloud computing is become more popular as cloud infrastructure for storing the data. Data owners are storedtheir data in public cloud for the flexibility and cost-saving. In data privacy protection, before saving sensitive data it is encrypted. Usertrust, privacy and security are more concerns. Most frequently used queries for online data analytic is the range query. Consumercentriccloud computing is used for development of smart electronic devices combined with the cloud computing technologies. Differentcloud services are provided to the customers with the premise that an effective and efficient cloud search service is provided. Localitysensitivehashing is provided the approximate queries that to distributed data servers which give problem of the imbalanced load andspace inefficiency, in which limits the query accuracy and incurs long query latency between users and cloud servers. This type of queryservices could be expensive for data owner. More incremented services computing and cloud computing, it is possible to outsource largedatabases to database service providers and the providers maintain the range-query service. Using outsourced services, the data ownercan reduce the cost of storing data in cloud infrastructure. Cloud computing providing reliable, customized, and guaranteed computingdynamic environment for end users.

International Journal of Science and Research (IJSR), ISSN (Online): 2319-7064

Survey on: Query services in Cloud Security

Wireless Sensor Networks represent one of the most prominent technologies in recent years. In WSN node architectures, the increasing complexity and high number of intensive tasks of today’s higher-end applications limits the use of traditional ultra-low power microcontrollers having sufficient but limited computational capacity and low scalability. The high performance high capacity FPGA based WSN node architectures provide the advantages of the intrinsic acceleration due to hardware parallelism, the use of partial reconfiguration capabilities for changeable environments, as well as a careful power aware management techniques for energy savings. This paper analyses different research prototypes available on FPGA based Wireless Sensor Network nodes and gives an understanding in this technology.

School of Electronics & Communication Engineering

International Journal of VLSI and Embedded Systems-IJVES

FPGA Based Wireless Sensor Network Node: Survey

International Conference on Global Business, Economics, Finance and Social {…}

Sustainable Development in Manufacturing Sector in India

International Journal of Electronics, Electrical and Computational System

SURVIVOR ROBOT

Vehicular Delay tolerant network (DTN) is mainly characterized by intermittent connectivity, long and variable delay, asymmetric data rates and high error rates. Nodes are operated by using store-carry-and-forward mechanism to forward the packets. DTN nodes are mobile in nature and they have limited time to hold a packet to forward it to the other nodes. Therefore, after specified amount of time bundle dropping event happens. Velocity and bundle holding time are the two major parameters which cause bundle dropping. In this paper, we studied and analyze the impact of velocity and bundle holding time on the bundle dropping event. More the velocity of a DTN node and the bundle holding time, more the probability a DTN node can contact with other DTN nodes which increases the bundle delivery. © 2015 IEEE.