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Gupta S.R.,Ram Meghe Institute of Technology and Research
Proceedings - International Conference on Electronic Systems, Signal Processing, and Computing Technologies, ICESC 2014 | Year: 2014

Because of increase in social networking, more and more people are connected. The people use to share information using these sites and also through the personal blogs. This information sharing is done globally. As the Internet Technology is becoming reliable, people feel safe while sharing the information. Other than messages and photos, this information also includes opinions, experiences and feedbacks regarding any product. These opinions and feedbacks are very important for the organizations that are selling or manufacturing the products, which can be used for changing designs, personalization and better understanding of product. This information is very useful for people or customer for buying the product. But for a customer, it is very difficult to review all the opinions or feedbacks available on net for a particular product. So, data mining approaches are used to mine the opinions, perform summarization of reviews for a particular product based on features or any other category. Most of the existing methods are processing the reviews in terms of positive and negative comments. But this approach is not enough for a customer to make decision about product. The proposed approach not only finding the positive and negative comments for any product or product features, but also rating them in the order of positivity and negativity. Also, the proposed approach gives the degree of comparisons for a particular product and product features. © 2014 IEEE.


Alvi A.S.,Ram Meghe Institute of Technology and Research
ACM International Conference Proceeding Series | Year: 2016

In any preemptive real time system restricting preemption plays a vital role in maintaining the schedulability of task set. Preemptions are necessary so as to allow high priority tasks, but may induce additional overhead cost. In this paper we propose a dynamic pre-emption threshold assignment algorithm that will minimize number of preemptions and improves hit ratio. © 2016 ACM.


Bamnote G.R.,Ram Meghe Institute of Technology and Research
ACM International Conference Proceeding Series | Year: 2016

The main innovation in modern human society is the presence and influence of Information Technologies. Everybody uses different technological devices and computers for either personal, academic, professional, scientific, clinical and other needs. These, extremely numerous, groups of Information Technology's users generate very large amounts of data. A technique in recommender systems is called as Collaborative filtering. It predicts the user rating of an item by association of similar users who have similar interests. An approach in collaborative querying is known as query clustering, which means to group similar queries automatically without using predetermined class descriptions. In this paper, we proposed an approach which works in two stages. In the first stage, the services are divided into small number of clusters for processing and later hybrid collaborative filtering algorithm is used on one of the clusters. We have compared the results by calculating the different similarity values such as functional similarity, description similarity and characteristic similarity by using the clustering method. The experimentation is done with MovieLens dataset which is available for research purpose provided by the GroupLens. The comparative analysis and comprehensive study shows that clustering based collaborative filtering algorithm puts forward for better performance among the other comparative algorithms. © 2016 ACM.


Chitlange M.R.,Government Polytechnic | Bang R.S.,Government Polytechnic | Pajgade P.S.,Ram Meghe Institute of Technology and Research
Journal of the Institution of Engineers (India): Civil Engineering Division | Year: 2010

Conventionally concrete is a mixture of cement, sand and aggregate. The large variation in the strength of concrete is due to the variation in the strength of aggregates used. There'is a scarcity of natural sand due to heavy demand in the growing construction activities. This necessitates that a suitable substitute be found. The cheapest substitute for natural sand is obtained by crushing natural stone to get artificial sand of desired size and grade, which would be free from all impurities. This paper presents the feasibility of using artificial sand obtained by crushing basalt, over natural sand considering the technical, environmental and commercial factors. For the purpose of experimentation concrete mixes were designed for M20, M30 and M40 grades with 100% replacement of natural sand by artificial sand. The compressive, flexural and spilt tensile tests were conducted to study the strength of concrete using artificial sand and the results are compared with that of natural sand concrete.


Kshirsagar S.V.,NBN Sinhgad Technical Institute Campus | Bhuyar L.B.,Ram Meghe Institute of Technology and Research
International Journal of Applied Engineering Research | Year: 2011

In this paper, a novel approach to the crack detection in cantilever beam by vibration signature analysis is established. The crack detection method is based on the vibration analysis under harmonic excitation. An experimental setup is designed in which a cracked cantilever beam is excited by an exciter and the signature is obtained using an accelerometer attached to the beam. To avoid non-linearity, it is assumed that the crack is always open. Natural frequencies obtained from modal analysis as a criterion for crack detection has been extensively used in the last decades due to its simplicity. However the online crack detection and condition monitoring using vibration signature is not straightforward. An efficient technique is necessary to obtain significant results. To identify the crack, contours of the normalized frequency in terms of the normalized crack depth and location are plotted. The intersection of contours with the constant damage index planes is used to relate the crack location and depth. The proposed method is based on the change in natural frequencies extracted from vibration signature of the beam. © Research India Publications.


Mohod S.W.,Ram Meghe Institute of Technology and Research | Mohod S.W.,Visvesvaraya National Institute of Technology | Aware M.V.,Visvesvaraya National Institute of Technology
2010 IEEE International Conference on Sustainable Energy Technologies, ICSET 2010 | Year: 2010

The wind energy generation, utilization and its grid penetration in electrical grid is increasing world wide. The wind generated power is always fluctuating due to its time varying nature and causing stability problem. This weak interconnection of wind generating source in the electrical network affect the power quality and reliability. The localized energy storages shall compensate the fluctuating power and support to strengthen the wind generator in the power system. In this paper, it is proposed to control the voltage source inverter (VSI) in current control mode with energy storage, that is, batteries across the dc bus. The generated wind power can be extracted under varying wind speed and stored in the batteries. This energy storage maintains the stiff voltage across the dc bus of the voltage source inverter. The propose scheme enhances the stability and reliability and maintain unity power factor as well as operated in stand alone mode in the power system. The power exchange across the wind generation and the load under dynamic situation is feasible while maintaining the power quality norms at the common point of coupling , strengthen the weak grid in the power system. This control strategy is evaluated on the test system under dynamic condition by using simulation. ©2010 IEEE.


Khan Z.S.,B S Patel Acs College | Ingale N.B.,Ram Meghe Institute of Technology and Research | Omanwar S.K.,Sant Gadge Baba Amravati University
Optik | Year: 2016

The polycrystalline sample of dysprosium doped NaSr4 (BO3)3 is prepared by employing modified solution combustion synthesis method. The as-synthesized phosphors were characterized by X-ray powder diffraction (XRD), photoluminescence excitation (PLE) and photoluminescence (PL) spectra. By Exposing with gamma-rays, its thermoluminescence properties were studied. Kinetic parameters were calculated using peak shape method. The effect of dose variation of gamma rays on NaSr4 (BO3)3 were also studied. The PLE spectra show the excitation peaks from 300 nm to 400 nm is due to the 4f-4f transitions of Dy3+. This mercury-free excitation is useful for solid state lighting and light-emitting diodes. The emission of Dy3+ ions upon 350 nm excitation, is observed at 482 nm (blue) due to the 4F9/2 → 6H15/2 transitions and 574 nm (yellow) due to 4F9/2 → 6H13/2 transitions. The CIE chromaticity coordinates (x = 0.35 and y = 0.40) for NaSr4 (BO3)3:Dy3+ phosphors are simulated and located in the bluish-white region. © 2016 Elsevier GmbH. All rights reserved.


Kelo S.,Ram Meghe Institute of Technology and Research | Dudul S.,Sant Gadge Baba Amravati University
International Journal of Electrical Power and Energy Systems | Year: 2012

In this paper, a novel combination of wavelet and Elman network as a recurrent neural network is proposed to predict 1-day-ahead electrical power load under the influence of temperature. Using wavelet multi-resolution analysis, the load series are decomposed to different sub-series, showing different frequency characteristics of the load. Elman network (EN) is optimally designed and trained using static back propagation algorithm based on the optimization of performance measures such as mean square error, correlation coefficient and mean absolute percentage error on test prediction dataset. Feasibility of Daubechies wavelet at different scales with suitable number of decomposition levels is investigated to choose the best order for different seasonal load series. The estimated models are evaluated over different temperature and humidity in order to examine their impact on accurate load prediction. The reliability and consistency in prediction by the adopted technique is maintained even in the presence of controlled Gaussian noise to the predicted temperature series. © 2012 Elsevier Ltd. All rights reserved.


Kalamkar N.B.,Ram Meghe Institute of Technology and Research | Ali M.S.,Ram Meghe Institute of Technology and Research
International Conference and Workshop on Emerging Trends in Technology 2011, ICWET 2011 - Conference Proceedings | Year: 2011

This paper presents a methodology to identifying a facial expression of human being based on the information theory approach of coding. This task is consists of two major phases: Extraction of appropriate facial features and consequent recognition of the user's emotional state that can be robust to facial expression variations among different users is the topic of this paper. 1) Identifying maximum matching face from database. 2) Extracting a facial expression from matched image. First phase consist of feature extraction using Principal Component analysis & face recognition using feed forward back propagation Neural Network with the use of eigen vector for calculating eigen values of images. The architecture considered for implementation is a Neuro-Fuzzy system with concepts of artificial intelligence. The approach chosen for the implementation is Soft Computing which is basically a synergistic integration computing paradigms: neural networks, fuzzy logic to provide a flexible framework to construct computationally intelligent systems. A Evolving Emotional Intelligence may contains simulated emotions, including sadness, joy, anger, fear, hope, relief, disappointment, gratitude, pride, shame, love and hate. Research on human psychology had long considered the notion of an emotion (e.g., happy) to be a matter of degree; however, Using fuzzy modeling proved to produce a more representative picture of the emotional process. By testing the above task over 1000 to 10000 images including both color, grayscale images of same & different human faces & may get the 80 to 90% accurate result. Copyright © 2011 ACM.


Borade A.B.,Jawaharlal Darda Institute of Engineering and Technology | Bansod S.V.,Ram Meghe Institute of Technology and Research
International Journal of Advanced Manufacturing Technology | Year: 2012

Vendor-managed inventory (VMI) is the latest supply chain management technology adopted by organizations to improve their business performance. In the recent years, many Indian organizations have also started adopting VMI in its supply chain. This paper identifies the variables that are important for VMI adoption. The variables are grouped as objectives, drivers, obstacles, and affected operations. The contextual relationship between the variables is established. This study employs an interpretive structural modeling approach to investigate the mutual relationship between the variables. These variables are then classified into four categories, namely, autonomous, driver, dependent, and linkage, to understand their relative impact. With the help of ISM, variables those which support other variables (driving variable) and those variables which are most influenced by other variables (dependent variables) are identified. The aim of this paper is to understand these mutual influences and develop a framework. Such an integrated framework would enable a better understanding of important issues while implementing VMI strategies in the Indian context. © 2011 Springer-Verlag London Limited.

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