Sureka A.,Indian Institute of Technology Delhi |
Lal S.,Indian Institute of Technology Delhi |
Proceedings - Asia-Pacific Software Engineering Conference, APSEC | Year: 2011
Defect tracking systems such as Bugzilla and JIRA and source code version control systems such as CVS and SVN are widely used applications to support software development and maintenance activities. Previous studies show that bug databases and version databases are often used as standalone and separate repositories without explicit linkages between issue reports and corresponding commit transactions. This is because developers often do not explicitly mention or tag commit transactions with the relevant bug report IDs. The lack of explicit links between these two databases has been identified as a serious process data quality issue (incomplete and biased data) having implications in predictive model building (such as defect density and error proneness computation) and hypothesis-testing based on the dataset. Researchers have proposed solutions to link the two databases and performed experiments on open source projects such as FireFox Mozilla. We review previous approaches and propose a novel technique (based on Fellegi-Sunter (FS) Model for record linkages) to automatically integrate the two databases that overcomes some of the drawbacks of traditional methods. We validate the proposed approach by performing experiments on publicly available bug and version dataset obtained from two open-source projects (Apache HTTP Server and WikiMedia). The results of our experiments demonstrate that the proposed solution is effective in recovering traceability links (missing links) between bug-fixing commits and corresponding bug reports. © 2011 IEEE.
Nathani A.,Dhirubhai Ambani Institute of ICT |
Chaudhary S.,Dhirubhai Ambani Institute of ICT |
Future Generation Computer Systems | Year: 2012
In present scenario, most of the Infrastructure as a Service (IaaS) clouds use simple resource allocation policies like immediate and best effort. Immediate allocation policy allocates the resources if available, otherwise the request is rejected. Best-effort policy also allocates the requested resources if available otherwise the request is placed in a FIFO queue. It is not possible for a cloud provider to satisfy all the requests due to finite resources at a time. Haizea is a resource lease manager that tries to address these issues by introducing complex resource allocation policies. Haizea uses resource leases as resource allocation abstraction and implements these leases by allocating Virtual Machines (VMs). Haizea supports four kinds of resource allocation policies: immediate, best effort, advanced reservation and deadline sensitive. This work provides a better way to support deadline sensitive leases in Haizea while minimizing the total number of leases rejected by it. Proposed dynamic planning based scheduling algorithm is implemented in Haizea that can admit new leases and prepare the schedule whenever a new lease can be accommodated. Experiments results show that it maximizes resource utilization and acceptance of leases compared to the existing algorithm of Haizea. © 2010 Elsevier B.V. All rights reserved.
Kant V.,LNMIIT |
Dwivedi P.,Motilal Nehru National Institute of Technology
17th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2015 - Proceedings | Year: 2015
Memory-based collaborative filtering (CF) techniques have been widely implemented for predicting ratings to unseen items by aggregating ratings of similar users or items in recommender systems (RS). Usually, sufficient ratings from similar users or similar items are not available in the rating matrix, due to the data sparsity problem. Further, these techniques suffer from correlation based problems inherent in used similarity measures. Consequently, higher prediction accuracy cannot be achieved. In this paper, we propose the use of fuzzy Naïve Bayesian (FNB) classifier for user based CF and item based CF for implicitly computing similarity between users as well as items on the basis of conditional probabilities and develop fuzzy Naïve Bayesian classifier to user based CF (FNB-UB-CF) and item based CF (FNB-IB-CF). We further develop a hybrid RS (FNB-UB-IB-CF) by combining the proposed FNB-UB-CF and FNB-IB-CF. Their combinations would be helpful in alleviating the sparsity because both user ratings and item ratings are employed. Experimental results demonstrate that the proposed methods are indeed more robust against data sparsity and give better recommendation quality using a popular MovieLens dataset. © 2015 ACM.
Shukla J.,The LNM Institute of Information Technology |
Alwani M.,LNMIIT |
ICCET 2010 - 2010 International Conference on Computer Engineering and Technology, Proceedings | Year: 2010
In this paper we are describing some important state-of the-art algorithms used for lossless compression of images. These algorithms are broadly classified as prediction based methods and transform based methods. Motivation behind this work is to provide a detailed analysis of such algorithms and to give future research direction based on the analysis to the new researchers. © 2010 IEEE.
Saini S.C.,Riga Technical University |
Sharma Y.,Riga Technical University |
Bhandari M.,Riga Technical University |
Proceedings - International Conference on Communication Systems and Network Technologies, CSNT 2012 | Year: 2012
This work presents a comparative study of two different control strategies for a flexible single-link manipulator. The dynamic model of the flexible manipulator involves modeling the rotational base and the flexible link as rigid bodies using the Euler Lagrange's method. The resulting system has one Degree-Of-Freedom (one DOF) and it provide freedom to increase the degree as well. Two types of regulators are studied, the State-Regulator using Pole Placement, and the Linear-Quadratic regulator (LQR). The LQR is obtained by resolving the Ricatti equation, in this work, we apply and compare two strategies to control the tip of the flexible link: state-feedback and linear quadratic regulator. These regulators are designed to reduce tip vibrations and increase system stability due to the flexibility of the arm. © 2012 IEEE.
Vaishnav M.,LNMIIT |
Tiwari A.K.,IIT Jodhpur
Data Compression Conference Proceedings | Year: 2014
In this paper, a novel method for lossless compression of video is proposed. Almost all the prediction based methods reported in literature are of two pass. In the first pass, motion compensated frame is obtained and in the second, some sophisticated method is used to predict the pixels of the current frame. The proposed method is an efficient replacement for the first method that predicts current pixel using an estimate of deviation from the pixel at same temporal location in the previous frame. In this scheme, causal pixels are divided into bins based on the distance between the current and causal pixels. The novelty of the work is in finding out the fixed coefficients of the bins for a particular type of video sequence. The overall performance of the proposed method is same with much lower computational complexity. © 2014 IEEE.
Jadhav T.,IIT IndoreMadhya Pradesh |
Misra R.,IIT IndoreMadhya Pradesh |
Biswas S.,LNMIIT |
Sharma G.D.,R and nter for Science and Engineering
Physical Chemistry Chemical Physics | Year: 2015
In this study, we have used three D-A type carbazole substituted BODIPY (carbazole connected to the meso position of BODIPY) small molecules as donors along with PC71BM as an electron acceptor for the fabrication of solution processed bulk heterojunction organic solar cells. The devices based on the as cast active layer showed power conversion efficiency in the range of 2.20-2.70%, with high open circuit voltage (Voc) in the range of 0.94-1.08 V. The high Voc is related to the deeper highest occupied molecular orbital energy level of these small molecules. The power conversion efficiency (PCE) of devices based on thermally annealed and solvent vapor annealed (TSVA) 3a:PC71BM and 3c:PC71BM processed active layers improved up to 5.05% and 4.80%, respectively, attributed to the improved light harvesting ability of active layers, better phase separation for exciton dissociation and balanced charge transport, induced by the TA and TSVA treatment. This journal is © the Owner Societies.
Shekhawat G.K.,LNMIIT |
International Conference on Ubiquitous and Future Networks, ICUFN | Year: 2016
Cooperative Spectrum Sensing (CSS) is a reliable detection approach that performs better over faded channel. In CSS, all Secondary Users (SU) have equal weight. We have studied performance of Centralized CSS (CCSS) using Normal Factor Graph (NFG) model with logical OR and Neyman-Pearson based Likelihood Ratio Testing (LRT) fusion rules. Here, we have proposed a novel Weighted CCSS (WCCSS) using NFG based probabilistic inference model. Sum Product algorithm (SPA) has been used for message passing and different weight assignment strategies have been used. The performance of WCCSS approach in Cognitive Radio Network (CRN) under different channels have been studied through simulation. © 2016 IEEE.
Nahar S.,LNMIIT |
Joshi M.V.,Dhirubhai Ambani Institute of ICT
Proceedings - 3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015 | Year: 2015
In this work, we propose to use an Inhomogeneous Gaussian Markov Random Field (IGMRF) and sparsity based priors in a regularization framework in order to estimate the dense disparity map. The IGMRF prior captures the spatial variation among disparities locally as well as it preserves sharp discontinuities. The sparsity prior captures the additional structure such as sparseness in the disparity map. The sparseness of the disparities are represented over the overcomplete dictionary which is learned from the estimated disparity map of the given stereo pair, using K-singular value decomposition (K-SVD) algorithm. The dictionary atoms are adaptive to the disparities of the given stereo pair. The sparse representation of disparities is used as a prior which is combined with the IGMRF prior in an energy minimization framework for estimating the disparity map. Disparity map is estimated using a two phase, iterative algorithm. In phase one, IGMRF parameters are computed at each pixel location and the dictionary is learned as well as the sparseness of disparities are obtained while keeping the disparity map fixed, and in phase two, disparity map is estimated by keeping the other parameters fixed. Experimental results on the standard dataset demonstrate the effectiveness of the proposed approach. © 2015 IEEE.
Saxena N.,Sungkyunkwan University |
Sahu B.J.R.,LNMIIT |
Han Y.S.,Sungkyul University
IEEE Communications Letters | Year: 2014
Commercial deployment of 4G LTE networks and rapid penetration of smart phones have exponentially increased the wireless data traffic, thus increasing the energy consumption and greenhouse (CO2) gas emission. The concept of green 4G LTE networks lies in the development of energy efficient LTE systems for reducing the greenhouse emissions as well as operators' energy bill. In this letter we first identify the complexity of the optimal traffic awareness in LTE networks and subsequently design a cooperative communication framework for traffic-aware energy optimization. The LTE eNBs explore an information theoretic approach to capture the dynamics and uncertainty of network traffic. Subsequently, using an online, stochastic game theoretic algorithm, the eNBs communicate amongst themselves to optimize the traffic awareness. Optimal traffic awareness helps in reducing the network energy consumption. Simulation results demonstrate that our framework results in almost 22% (40 KW-Hr) daily energy savings across a LTE network of 400 cells. © 2012 IEEE.