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Safe cloud: Secure and usable authentication framework for cloud environment
Cloud computing an emerging computing model having its roots in grid and utility computing is gaining increasing attention of both the industry and laymen. The ready availability of storage, compute, and infrastructure services provides a potentially attractive option for business enterprises to process and store data without investing on computing infrastructure. The attractions of Cloud are accompanied by many concerns among which Data Security is the one that requires immediate attention. Strong user authentication mechanisms which prevent illegal access to Cloud services and resources are one of the core requirements to ensure secure access. This paper proposes a user authentication framework for Cloud which facilitates authentication by individual service providers as well as by a third party identity provider. The proposed two-factor authentication protocols uses password as the first factor and a Smart card or Mobile Phone as the second factor. The protocols are resistant to various known security attacks. Springer India 2016. -
Multi-view video summarization
Video summarization is the most important video content service which gives us a short and condensed representation of the whole video content. It also ensures the browsing, mining, and storage of the original videos. The multi- view video summaries will produce only the most vital events with more detailed information than those of less salient ones. As such, it allows the interface user to get only the important information or the video from different perspectives of the multi-view videos without watching the whole video. In our research paper, we are focusing on a series of approaches to summarize the video content and to get a compact and succinct visual summary that encapsulates the key components of the video. Its main advantage is that the video summarization can turn numbers of hours long video into a short summary that an individual viewer can see in just few seconds. Springer India 2016. -
Extraction of Web News from Web Pages Using a Ternary Tree Approach
The spread of information available in the World Wide Web, it appears that the pursuit of quality data is effortless and simple but it has been a significant matter of concern. Various extractors, wrappers systems with advanced techniques have been studied that retrieves the desired data from a collection of web pages. In this paper we propose a method for extracting the news content from multiple news web sites considering the occurrence of similar pattern in their representation such as date, place and the content of the news that overcomes the cost and space constraint observed in previous studies which work on single web document at a time. The method is an unsupervised web extraction technique which builds a pattern representing the structure of the pages using the extraction rules learned from the web pages by creating a ternary tree which expands when a series of common tags are found in the web pages. The pattern can then be used to extract news from other new web pages. The analysis and the results on real time web sites validate the effectiveness of our approach. 2015 IEEE. -
A parallel approach for region-growing segmentation
Image Segmentations play a heavy role in areas such as computer vision and image processing due to its broad usage and immense applications. Because of the large importance of image segmentation a number of algorithms have been proposed and different approaches have been adopted. In this theme I tried to parallelize the image segmentation using a region growing algorithm. The primary goal behind this theme is to enhance performance or speed up the image segmentation on large volume image data sets, i.e. Very high resolution images (VHR). In parliamentary law to get the full advantage of GPU computing, equally spread the workload among the available threads. Threads assigned to individual pixels iteratively merge with adjacent segments and always ensuring the standards that the heterogeneity of image objects should be belittled. An experimental analysis upon different orbital sensor images has made out in order to assess the quality of results. 2015 IEEE. -
Performance analysis of OFF-GRID solar photo voltaic system
Day by day the demand for electrical energy is increasing. We can't rely on conventional energy sources for meeting this increasing demand as they are depleting. So it is necessary to find an alternative method to harness the energy that we are lacking. Solar energy generation seems to be a promising technology for this dilemma. It is environmental friendly and infinite source of energy. Photovoltaic systems can be broadly classified into two-an on-grid system or an off-grid system. The energy generated from a solar PV system is based on several factors like irradiance, types of solar PV used and temperature. Analyzing the existing system efficiency is of prime importance for the characterization of the problems and for the improvements. This study deals with the performance analysis of an on-grid and off-grid system. The analysis is carried out by modeling an existing system in MATLAB/SIMULINK which is already in operation. It can be extended to analyze the grid stability. This study aims the quantification of various performance parameters like power output, losses in the system, system efficiency and the total energy transfer. 2015 IEEE. -
A multi-Threshold triggering and QoS aware vertical handover management in heterogeneous wireless networks
Vertical handover management provides seamless connectivity in heterogeneous wireless networks. But still there are different challenges that need to be addressed. These challenges include the inappropriate network selection, wrong cell handover, etc. Therefore, in this article, we proposed a handover management scheme based on the data rate and QoS of available networks. The handover triggering is performed on the data rate requires by different applications. Similarly, the network selection is performed by considering the cost, data rate of available networks and energy consumption by the mobile interface. The proposed scheme is simulated in different mobility scenarios with a random number of applications running on various numbers of mobile nodes. The simulation results show that the proposed scheme requires less energy during the scanning and selection of available networks. 2015 IEEE. -
Stock price forecasting using ANN method
Ability to predict stock price direction accurately is essential for investors to maximize their wealth. Neural networks, as a highly effective data mining method, have been used in many different complex pattern recognition problems including stock market prediction. But the ongoing way of using neural networks for a dynamic and volatile behavior of stock markets has not resulted in more efficient and correct values. In this research paper, we propose methods to provide more accurately by hidden layer data processing and decision tree methods for stock market prediction for the case of volatile markets. We also compare and determine our proposed method against three layer feed forward neural network for the accuracy of market direction. From the analysis, we prove that with our way of application of neural networks, the accuracy of prediction is improved. Springer India 2016. -
Characterization and comparison studies of Bentonite and Flyash for electrical grounding
Earthing or Grounding is an Electrical system consists of electrodes which serves as an electrical connection from an electric circuit in the system to the earth or ground. Traditional Earthing- where we mix charcoal and salt offers low resistance to the fault current flow developed from a Low operating Voltages. Since operating voltages are high now a days, Short circuit current also increased. Traditional method of Earthing is replaced by chemical Earthing.Bentonite which is mainly used in chemical Earthing serves the requirement of Low resistance Earthing pits and also have the property to retain the moisture. In this paper an attempt had been made to assure the Flyash usage in the grounding pit and this paper discusses the Characterization, Comparison and Field Studies on Earthing Pit constructed with Bentonite and Fly ash layers. 2015 IEEE. -
P-phase picker using virtual cloud-based Wireless Sensor Networks
Wireless Sensor Networks, mainly regarded as numerous resource-limited nodes linked via low bandwidth, have been intensively deployed for active volcano monitoring during the few past years. This paper studies the problem of primary waves received by seismic wireless sensors suffering from limited bandwidth, processing capacity, battery life and memory. To address these challenges, a new P-phase picking approach where sensors are virtualized using cloud computing architecture followed by a novel in-network signal processing algorithm, is proposed. The two principal merits of this paper are the clear demonstration that the Cloud Computing model is a good fit with the dynamic computational requirements of volcano monitoring and the novel signal processing algorithm for accurate P-phases picking. The proposed new model has been evaluated on Mount Nyiragongo using Eucalyptus/Open Stack with Orchestra-Juju for Private Sensor Cloud then to some famous public clouds such as Amozon EC2, ThingSpeak, SensorCloud and Pachube. The testing has been successful at 75%. The recommendation for future work would be to improve the effectiveness of virtual sensors by applying optimization techniques and other methods. 2015 IEEE. -
Parallelizing keyframe extraction for video summarization
In current era, most of the information is captured using multimedia techniques. Most used methods for information capturing is through images and videos. In processing a video, large information needs to be processed and a number of frames could contain similar information which could cause unnecessary delay in gathering the required information. Video summarization can speed up video processing. There are different techniques for video summarization. In this paper key frames are used for summarization. Key frames are extracted using discrete wavelet transforms. Two HD videos having 356 frames and 7293 frames were used as test videos and the runtime was 17 seconds and 98 seconds respectively in CPU and 11 seconds and 53 seconds respectively in GPU. 2015 IEEE. -
A Comparative Performance Analysis of Convolution W/O OpenCL on a Standalone System
Initial approach of this paper is to provide a deep understanding of OpenCL architecture. Secondly, it proposes an implementation of a matrix and image convolution implemented in C (Serial Programming) and OpenCL (Parallel Programming), to describe detailed OpenCL programming flow and to provide a comparative performance analysis. The implementation is being carried on AMD A10 APU and various algebraic scenarios are created, to observe the performance improvement achieved on a single system when using Parallel Programming. In the related works authors have worked on AMDAPPSDK samples such as N-body & SimpleGL to understand the concept of vector data types in OpenCL and OpenCL-GL interoperability, have also implemented 3-D particle bouncing concept in OpenCL & 3D-Mesh rendering using OpenCL. Lastly, authors have also illuminated about their future work, where they intend to implement a novel algorithm for mesh segmentation using OpenCL, for which they have tried to form a strong knowledge base through this work. 2015 IEEE. -
Feature extraction of clothing texture patterns for classification
Different features are extracted for Pattern Recognition using an efficient algorithms like Scale Invariant Feature Transform, Rotation invariant Radon Transform and extracting statistical features of a texture image. Support vector machine with RBF kernel in Weka is used in this paper for classification. This paper shows method to classify the clothing texture patterns like strips, plaid, pattern less and irregular pattern. This paper also proposes a method which can be efficient method to apply for the real time natural texture patterns and colors recognition systems. This paper gives the experiments results and the proposed method to enhance the experiments accuracy in future scope. 2015 IEEE. -
Empirical estimation of multilayer perceptron for stock market indexes
The return on investment of stock market index is used to estimate the effectiveness of an investment in different savings schemes. To calculate Return on Investment, profit of an investment is divided by the cost of investment. The purpose of the paper is to perform empirical evaluation of various multilayer perceptron neural networks that are used for obtaining high quality prediction for Return on Investment based on stock market indexes. Many researchers have already implemented different methods to forecast stock prices, but accuracy of the stock prices are a major concern. The multilayer perceptron feed forward neural network model is implemented and compared against multilayer perceptron back propagation neural network models on various stock market indexes. The estimated values are checked against the original values of next business day to measure the actual accuracy. The uniqueness of the research is to achieve maximum accuracy in the Indian stock market indexes. The comparative analysis is done with the help of data set NSEindia historical data for Indian share market. Based on the comparative analysis, the multilayer perceptron feed forward neural network performs better prediction with higher accuracy than multilayer perceptron back propagation. A number of variations have been found by this comparative experiment to analyze the future values of the stock prices. With the experimental comparison, the multilayer perceptron feed forward neural network is able to forecast quality decision on return on investment on stock indexes with average accuracy rate as 95 % which is higher than back propagation neural network. So the results obtained by the multilayer perceptron feed forward neural networks are more satisfactory when compared to multilayer perceptron back propagation neural network. Springer International Publishing Switzerland 2016. -
Speech disabilities in adults and the suitable speech recognition software tools - A review
Speech impairment, though not a major obstacle, is still a problem for people who suffer from it, while they are making public presentations. This paper describes the different speech disabilities in adults and reviews the available software and other computer based tools that facilitate better communication for people with speech impairment. The motivation for this writing has been the fact that stuttering, one of the types of speech disability has affected about 1 percentage of the people worldwide. This fact was provided by the Stuttering Foundation of America, a Non-profit Organization, functioning since 1947. A solution to stuttering is expected to benefit a considerable population. Speech recognition software tools help people with disabilities use their computers and other hand held devices to satisfy their day-to-day needs which otherwise, require dedicated domestic help and also question the person's ability to be independent. ASR (Automatic Speech Recognition) systems are popular among the common people and people with motor disabilities, while using these techniques for the treatment of speech correction is a current research field and is of interest to SLPs/SLTs (Speech Language Pathologist / Speech Language Therapist). On-going research also includes development of ASR based software to facilitate comfortable oral communication with people suffering from speech dysfunctions, i.e., in the domain of AAC (Augmentative and Alternative Communication). 2015 IEEE. -
Performance optimization for extraction, transformation, loading and reporting of data
Enterprise Resource Planning has become the cornerstone for making data acquisition and related operations more efficient. Recent advances in hardware and software technologies have enabled us to think about performance optimization. Ninety percent of ERP projects spend more than their allocated budgets and have exceeded the time schedule for implementation. There are many factors that can be attributed to the low success rate of implementation but one main factor is the performance of the ERP package itself. In this paper, we have described the Business Intelligence tool and database which is related to Systems, Applications and Products. It is popularly known as SAP. Based on this, a new, mulch-dimensional performance metric is proposed for extracting, transforming, loading and reporting the data. 2015 IEEE. -
Tool wear and tool life estimation based on linear regression learning
Tools have remained an integral part of the society without which stimulation of certain aspects of human evolution would not have been possible. In recent times the modern tools are used in the manufacturing of high precision components. We know that the accuracy and surface finish of these components can be achieved only by the usage of accurate tools. Sharp edged tools may loosen their sharpness due to repeated usage and machining parameters. Hence to address this issue we propose a system to monitor tool wear by using the captured image of cutting tool tip. We used vision system since it is the primitive method of predicting tool wear and two main machining parameters feed rate and depth of cut. The image of flank wear cutting edge at tool tip is captured by examining under profile projector. The system uses linear regression model to calculate tool wear which is mapped onto continuous 2-D coordinates with feed rate and depth of cut as axis from a captured digital image. Thus the proposed intelligent system uses profile projector and digital image processing methods to estimate tool wear continuously and predictively like humans rather than using strict rules. By estimating tool wear continuously the machine can better perform and machine components accurately by using the resultant values of feed rate and depth of cut as a threshold which are arrived as a result. 2015 IEEE. -
A novel scheme for energy enhancement in wireless sensor networks
Wireless sensor networks consists of a large amount of miniaturized battery-powered wireless networked sensors which are intended to function for years without any human intervention. Because of the large number of sensors and the restrictions on the environment of their deployment, replacing the components cannot be thought of. So the only viable way out is to efficiently use the available resources. Energy efficiency is a major matter of concern in such networks even though energy harvesting techniques exists. Recent times have shown a growing interest on understanding and developing new strategies of wireless sensor network routing especially focussing on the optimal use of the limited and constrained resources like energy, memory and processing capabilities. Routing have to be given due importance as it consumes major part of the energy compared to that of sensing and processing. Adopting the natures self organising system intelligence for the emerging technologies is quite interesting and has proved to be efficient. This article sheds some light on the existing bio inspired routing protocols and explains a new procedure with mobile sinks for energy efficient routing in wireless sensor networks. 2015 IEEE. -
How much can we trust high-resolution spectroscopic stellar chemical abundances?
To study stellar populations, it is common to combine chemical abundances from different spectroscopic surveys/studies where different setups were used. These inhomogeneities can lead us to inaccurate scientific conclusions. In this work, we studied one aspect of the problem: When deriving chemical abundances from high-resolution stellar spectra, what differences originate from the use of different radiative transfer codes? 2016 Proceedings of the 12th Scientific Meeting of the Spanish Astronomical Society - Highlights of Spanish Astrophysics IX, SEA 2016. All rights reserved. -
Demand response for residential loads using artificial bee colony algorithm to minimize energy cost
Power performance expectations are increasing, impacting designs and requiring advanced technology to improve system reliability. Demand Response (DR) is a highly flexible customer driven program in which customer voluntarily changes his energy usage patterns during the peak demand to maintain the system stability and reliability and thereby improves the performance of the gird. This paper proposes a novel algorithm for optimization of the DR schedule of the residential loads for various hours of the day using Artificial Bee Colony (ABC) algorithm. Here, the objective function is subjected to the constraints like cost constraints, time constraints and load demand. The results show that the proposed approach enhances potential in solving problems with good reliability compared with existing approaches. 2015 IEEE. -
Microhardness studies of vapour grown tin (II) sulfide single crystals
Earth abundant tin sulfide (SnS) has attracted considerable attention as a possible absorber material for low-cost solar cells due to its favourable optoelectronic properties. Single crystals of SnS were grown by physical vapour deposition (PVD) technique. Microindentation studies were carried out on the cleaved surfaces of the crystals to understand their mechanical behaviour. Microhardness increased initially with the load, giving sharp maximum at 15 g. Quenching effect has increased the microhardness, while annealing reduced the microhardness of grown crystals. The hardness values of as-grown, annealed and quenched samples at 15 g load are computed to be 99.69, 44.52 and 106.29 kg/mm 2 respectively. The microhardness of PVD grown crystals are high compared to CdTe, a leading low-cost PV material. The as-grown faces are found to be fracture resistant. 2015 AIP Publishing LLC.