Indian Institute of Information Technology Allahabad

Allahabad, India

The Indian Institute of Information Technology, Allahabad was established in 1999, as a center of excellence in Information Technology and allied areas. The institute was conferred "Deemed University" status by Govt. of India in the year 2000. The Institute thus became empowered to have a perpetual seal and award degrees subsequent to the conduct of its own examinations. With the passage of IIIT Bill 2014 by the Parliament of India, IIIT Allahabad, along with the other 4 MHRD funded IIITs, became an Institute of National Importance on December 1, 2014. The Institute of National Importance is a status that may be conferred to a higher education institution in India by an act of parliament. They are institutes which "serve as a pivotal player in developing highly skilled personnel within the specified region of the country/state". INIs receive special recognition and funding.The Institute was conceived with the objectives of developing professional expertise and skilled manpower in Information Technology and related areas. This will enable the country to efficiently exploit emerging opportunities and meet economic challenges being thrown up by the rapid global IT revolution which is influencing virtually every area of development and social activity. As one of the leading institutes in the area of IT, the establishment of IIIT-A, was a major step of Govt. of India towards strengthening the indigenous capability necessary for ensuring profitably and harnessing multidimensional facets of IT at all levels, and attaining expertise to enable the country to emerge as a leading player in the global arena.The institute was established by the efforts of Prof. Murli Manohar Joshi, Union Minister of Human Resource Development, GoI. Realizing the vital significance of IT in the years to come, Prof. Joshi, himself a reputed academician, was instrumental in getting the project conceived, initiated and executed in record time. The 100 acre campus, situated at Deoghat, Jhalwa was designed on the Penrose Geometry pattern and is being further topped by fine landscaping to give an all round soothing effect to create a stimulating environment to indulge in the pursuit of excellence in the field of Information Technology and Allied science. The campus is envisaged to be a fully residential one, with all its faculty, staff and students housed in different pockets. All academic and residential areas are connected to the Institutes's network. Wikipedia.

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Anand R.,Indian Institute of Information Technology Allahabad | Kaithwas G.,Babasaheb Bhimrao Ambedkar University
Inflammation | Year: 2014

The present work investigates the anti-inflammatory activity of alpha-linolenic acid (ALA) and linoleic acid (LA) using computational and experimental analysis. The binding affinity of ALA and LA was appraised for cyclooxygenase 1 (COX-1), cyclooxygenase 2 (COX-2), and 5-lipoxygenase (5-LOX) using AutoDock 4.2 and AutoDock Vina 1.1.2. Anti-inflammatory activity of ALA (2 and 4 ml/kg, i.p.) (55.65 % v/v) and LA (2 and 4 ml/kg, i.p.) (55 % v/v) was further assayed using the rat paw edema test against a variety of phlogistic agents including carrageenan, arachidonic acid, prostaglandin, and leukotriene, respectively. ALA (2 and 4 ml/kg, i.p.) and LA (2 and 4 ml/kg, i.p.) were further tested for their efficacy against complete Freund's adjuvant (CFA)-induced (0.05 ml) arthritis in albino rats. Following CFA-induced arthritis, ALA and LA were tested for their inhibitory proficiency against COX-1, COX-2, and 5-LOX in vitro. The present study commends that the anti-inflammatory potential of ALA could be attributed to COX inhibition, in particular, COX-2. © 2014 Springer Science+Business Media.

Deeptimahanti D.K.,University of Limerick | Sanyal R.,Indian Institute of Information Technology Allahabad
Proceedings of the 4th India Software Engineering Conference 2011, ISEC'11 | Year: 2011

Going from requirements analysis to design phase is considered as one of the most complex and difficult activities in software development. Errors caused during this activity can be quite expensive to fix in later phases of software development. One main reason for such potential problems is due to the specification of software requirements in Natural Language format. To overcome some of these defects we have proposed a technique, which aims to provide semi-automated assistance for developers to generate UML models from normalized natural language requirements using Natural Language Processing techniques. This technique initially focuses on generating use-case diagram and analysis class model (conceptual model) followed by collaboration model generation for each use-case. Then it generates a consolidated design class model from which code model can also be generated. It also provides requirement traceability both at design and code levels by using Key-Word-In-Context and Concept Location techniques respectively to identify inconsistencies in requirements. Finally, this technique generates XML Metadata Interchange (XMI) files for visualizing generated models in any UML modeling tool having XMI import feature. This paper is an extension to our existing work by enhancing its complete usage with the help of Qualification Verification System as a case study.

Ojha M.,Indian Institute of Information Technology Allahabad
Advances in Intelligent and Soft Computing | Year: 2012

Supply chain management is a very dynamic operation research problem where one has to quickly adapt according to the changes perceived in environment in order to maximize the benefit or minimize the loss. Therefore we require a system which changes as per the changing requirements. Multi agent system technology in recent times has emerged as a possible way of efficient solution implementation for many such complex problems. Our research here focuses on building a Multi Agent System (MAS), which implements a modified version of Gravitational Search swarm intelligence Algorithm (GSA) to find out an optimal strategy in managing the demand supply chain. We target the grains distribution system among various centers of Food Corporation of India (FCI) as application domain. We assume centers with larger stocks as objects of greater mass and vice versa. Applying Newtonian law of gravity as suggested in GSA, larger objects attract objects of smaller mass towards itself, creating a virtual grain supply source. As heavier object sheds its mass by supplying some to the one in demand, it loses its gravitational pull and thus keeps the whole system of supply chain perfectly in balance. The multi agent system helps in continuous updation of the whole system with the help of autonomous agents which react to the change in environment and act accordingly. This model also reduces the communication bottleneck to greater extents. © 2012 Springer India Pvt. Ltd.

Kala R.,Indian Institute of Information Technology Allahabad
Journal of Advanced Transportation | Year: 2016

Research on intelligent transportation systems is so far focussed on decreasing the travel time of vehicles and avoiding congestions. However, the importance of reaching on time is different for different vehicles and depends upon the purpose of the journey. In a human-operated queue, it is generally considered courteous to give priority to people running very late. They may be running late to catch a flight or may be in an emergency for a medical check-up. There is a very small discomfort to the other people as long as the number of people in an emergency and running late is low. However, such prioritization is an invaluable help to the people running late. In this paper the same behaviour is modelled, wherein the transportation system is made biased towards the vehicles on an important task and running late. The paper presents the mechanism by which a vehicle may judge its running status, decide whether to ask for cooperation and decide how much of cooperation to ask for. The vehicle lane changes and traffic lights operating policy are made cooperative. Experimental results show that such a cooperation leads to lesser number of important vehicles reaching their destinations late. © 2015 John Wiley & Sons, Ltd.

Rautaray S.S.,Indian Institute of Information Technology Allahabad | Agrawal A.,Indian Institute of Information Technology Allahabad
Artificial Intelligence Review | Year: 2012

As computers become more pervasive in society, facilitating natural human–computer interaction (HCI) will have a positive impact on their use. Hence, there has been growing interest in the development of new approaches and technologies for bridging the human–computer barrier. The ultimate aim is to bring HCI to a regime where interactions with computers will be as natural as an interaction between humans, and to this end, incorporating gestures in HCI is an important research area. Gestures have long been considered as an interaction technique that can potentially deliver more natural, creative and intuitive methods for communicating with our computers. This paper provides an analysis of comparative surveys done in this area. The use of hand gestures as a natural interface serves as a motivating force for research in gesture taxonomies, its representations and recognition techniques, software platforms and frameworks which is discussed briefly in this paper. It focuses on the three main phases of hand gesture recognition i.e. detection, tracking and recognition. Different application which employs hand gestures for efficient interaction has been discussed under core and advanced application domains. This paper also provides an analysis of existing literature related to gesture recognition systems for human computer interaction by categorizing it under different key parameters. It further discusses the advances that are needed to further improvise the present hand gesture recognition systems for future perspective that can be widely used for efficient human computer interaction. The main goal of this survey is to provide researchers in the field of gesture based HCI with a summary of progress achieved to date and to help identify areas where further research is needed. © 2012, Springer Science+Business Media Dordrecht.

Verma G.K.,Indian Institute of Information Technology Allahabad | Tiwary U.S.,Indian Institute of Information Technology Allahabad
NeuroImage | Year: 2014

The purpose of this paper is twofold: (i) to investigate the emotion representation models and find out the possibility of a model with minimum number of continuous dimensions and (ii) to recognize and predict emotion from the measured physiological signals using multiresolution approach. The multimodal physiological signals are: Electroencephalogram (EEG) (32 channels) and peripheral (8 channels: Galvanic skin response (GSR), blood volume pressure, respiration pattern, skin temperature, electromyogram (EMG) and electrooculogram (EOG)) as given in the DEAP database. We have discussed the theories of emotion modeling based on i) basic emotions, ii) cognitive appraisal and physiological response approach and iii) the dimensional approach and proposed a three continuous dimensional representation model for emotions. The clustering experiment on the given valence, arousal and dominance values of various emotions has been done to validate the proposed model. A novel approach for multimodal fusion of information from a large number of channels to classify and predict emotions has also been proposed. Discrete Wavelet Transform, a classical transform for multiresolution analysis of signal has been used in this study. The experiments are performed to classify different emotions from four classifiers. The average accuracies are 81.45%, 74.37%, 57.74% and 75.94% for SVM, MLP, KNN and MMC classifiers respectively. The best accuracy is for 'Depressing' with 85.46% using SVM. The 32 EEG channels are considered as independent modes and features from each channel are considered with equal importance. May be some of the channel data are correlated but they may contain supplementary information. In comparison with the results given by others, the high accuracy of 85% with 13 emotions and 32 subjects from our proposed method clearly proves the potential of our multimodal fusion approach. © 2013 Elsevier Inc.

Tomar D.,Indian Institute of Information Technology Allahabad | Agarwal S.,Indian Institute of Information Technology Allahabad
International Journal of Bio-Science and Bio-Technology | Year: 2013

Data Mining is one of the most motivating area of research that is become increasingly popular in health organization. Data Mining plays an important role for uncovering new trends in healthcare organization which in turn helpful for all the parties associated with this field. This survey explores the utility of various Data Mining techniques such as classification, clustering, association, regression in health domain. In this paper, we present a brief introduction of these techniques and their advantages and disadvantages. This survey also highlights applications, challenges and future issues of Data Mining in healthcare. Recommendation regarding the suitable choice of available Data Mining technique is also discussed in this paper. © 2013 SERSC.

Tomar D.,Indian Institute of Information Technology Allahabad | Agarwal S.,Indian Institute of Information Technology Allahabad
Knowledge-Based Systems | Year: 2015

Least Squares Twin Support Vector Machine (LSTSVM) is a binary classifier and the extension of it to multiclass is still an ongoing research issue. In this paper, we extended the formulation of binary LSTSVM classifier to multi-class by using the concepts such as "One-versus-All", "One-versus-One", "All-versus-One" and Directed Acyclic Graph (DAG). This paper performs a comparative analysis of these multi-classifiers in terms of their advantages, disadvantages and computational complexity. The performance of all the four proposed classifiers has been validated on twelve benchmark datasets by using predictive accuracy and training-testing time. All the proposed multi-classifiers have shown better performance as compared to the typical multi-classifiers based on 'Support Vector Machine' and 'Twin Support Vector Machine'. Friedman's statistic and Nemenyi post hoc tests are also used to test significance of predictive accuracy differences between classifiers. © 2015 Elsevier B.V.

Rautaray S.S.,Indian Institute of Information Technology Allahabad | Agrawal A.,Indian Institute of Information Technology Allahabad
2011 International Conference on Multimedia, Signal Processing and Communication Technologies, IMPACT 2011 | Year: 2011

Hand gesture recognition systems for virtual reality applications provides the users an enhanced interaction experience as it integrates the virtual and the real world object. Growth in virtual environments based upon computer systems and development of user interfaces influence the changes in the Human-Computer Interaction (HCI). Gesture recognition based interaction interface, endow with more realistic and immersive interaction compared to the traditional devices. The system enables a physically realistic mode of interaction to the virtual environment. The Hand gesture recognition system based interface proposed and implemented in this paper consists of a detection, tracking and recognition module. For the implementation of these modules various image processing algorithms as Camshift, Lucas Kanade, Haar like features etc has been employed. Comprehensive user acceptability has been considered to exhibit the accuracy, usefulness and ease of use to the proposed and implemented hand gesture recognition system. Hand gesture communication based vocabulary offers many variations ranging from simple action of using our finger to point at to using hands for moving objects around to the rather complex one like expression of the feelings. The proposed hand gesture recognition system offers intensions to traditional input devices for interaction with the virtual environments. The gesture based interaction interface being proposed here can be substantially applied towards many applications like Virtual Reality, Sign Language and Games. Though the present paper considered games as the application domain. © 2011 IEEE.

Kala R.,Indian Institute of Information Technology Allahabad
Applied Intelligence | Year: 2016

Probabilistic Roadmaps are increasingly being used for robot motion planning. The method makes use of an offline construction of a roadmap. Even though the method is offline, it needs to be initially constructed as quickly as possible for an efficient and near-real time initial motion of the robot. The challenge lies in sampling of multiple narrow corridors wherein the probability of samples is very low. It is important to discover all homotopic groups very early to make good initial decisions from the roadmap. Missing out of even a single homotopic group can lead to no solution or poor solutions. The proposed method uses a multi-strategized approach for sampling of the initial points and then intelligently constructs edges between the points in a multi-strategized manner. The aim is to increase sampling at the narrow corridors and then to facilitate edge connectivity of nodes inside the corridor with the rest of the roadmap, so as to lead to the discovery of all possible homotopic groups between any pair of sources and goals. The approach results in a better performance as compared to uniform sampling and obstacle based sampling. © 2016 Springer Science+Business Media New York

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