Computer Science and Engineering

<p>Shiv Nadar University is a comprehensive, multidisciplinary, research-focused, and student-centric University offering a full range of academic programs at the undergraduate, postgraduate and doctoral level. With state-of-the-art infrastructure, the University comprises of academic wings, sophisticated labs, international standard sports facilities, amphitheaters, auditorium, conference rooms and smart classrooms. The University&rsquo;s goal is to become internationally recognized for the quality of its research and creative endeavors and their applicability to improving quality of life, generating new insights and expanding the boundaries of human knowledge creativity. Committed to excellence in teaching, research and service, the University aims to serve the higher education needs of India and the world beyond.</p>

Shiv Nadar University

This paper designs a novel fuzzy competition and attitude based bidding strategy (FCA-Bid), in which the final best bid is calculated on the basis of the attitude of the bidders and the competition for the goods in the market. The estimation of attitude is based on the bidding item's attribute assessment, which adapts the fuzzy sets technique to handle uncertainty of the bidding process as well it uses heuristic rules to determine attitude of bidding agents. The bidding strategy also uses and determines competition in the market (based on the two factors i.e. no. of the bidders participating and the total time elapsed for an auction) using Mamdani's Direct Method. Then the final price of the best bid will be determined based on the assessed attitude and the competition in the market using fuzzy reasoning technique. © 2010 Springer-Verlag Berlin Heidelberg.

World University root node

(SoE) School of Engineering

Studies in Computational Intelligence

Automated fuzzy bidding strategy using agent's attitude and market competition

In this work we have extended and implemented an ontology based approach for email classification based on user characteristics proposed by Kim et al.(2007). The approach focuses on finding relationships between user interests and their responses to emails. Rules and Ontology are created using the data and metadata of user characteristics, their preferences and responses to emails. Rules and ontology are then used to predict the response of a user to a new email. In Kim et al. (2007) approach, labels to emails were provided manually by a human expert. We have endeavored to remove the human intervention by developing an Automated Email Categorizer to provide label to an email based on its contents. We have also proposed a new term weighing method for emails to incorporate prominence of subject terms. Finally, we have integrated and tested the Ontology Based Classifier in conjunction with Email Categorizer where the former effectively uses the label provided by latter to classify an email based on user preferences.

KEOD 2010 - Proceedings of the International Conference on Knowledge Engineering and Ontology Development

Automatic email classification using user preference ontology

We propose a graph theoretic technique for recognizing actions at a distance by modeling the visual senses associated with human poses. Identifying the intended meaning of poses is a challenging task because of their variability and such variations in poses lead to visual sense ambiguity. Our methodology follows a bag-of-words approach. Here "word" refers to the pose descriptor of the human figure corresponding to a single video frame and a "document" corresponds to the entire video of a particular action. From a large vocabulary of poses we prune out ambiguous poses and extract 'meaningful' [6] poses - for each action type in a supervised fashion - using centrality measure of graph connectivit [16]. The number of 'meaningful' poses per action is determined by setting a bound on the centrality measure. We evaluate our methodology on four standard activity recognition datasets and the results clearly demonstrate the superiority of our approach over the present state-of-the-art. © 2010 ACM.

ACM International Conference Proceeding Series

Human action recognition in video by 'meaningful' poses

In this paper we study the important problems of message routing, sorting, and selection in a radio network. A radio network consists of stations where each station is a hand-held device. We consider a single-hop radio network. In a single-hop network it is assumed that each station is within the transmission range of every other station. Let RN(p, k) stand for a single-hop network that has p stations and k communication channels. The problems of sorting and selection have been studied on RN(p, k). For these problems it is assumed that there are n/p elements to start with at each station. At the end of sorting, the least n/p elements should be in the first station, the next smallest n/p elements should be in the second station, and so on. The best known prior algorithm for sorting takes 4n/k +o (n/k) broadcast rounds on a RN(p, k). In this paper we present a randomized algorithm that takes only 3n k + o (n/k) broadcast rounds with high probability. For the selection problem, it is known that the maximum or minimum element can be found in O(log n) rounds on a RN(n, 1), provided broadcast conflicts can be resolved in O(1) time. The problem of general selection has not been addressed. In this paper we present a randomized selection algorithm that takes O (p k) rounds on a RN(p, k) with high probability. An important message routing problem that is considered in the literature is one where there are n/p packets originating from each station and there are n/p packets destined for each station. The best known routing. © 2010 IEEE.

Proceedings of the International Conference on Parallel Processing

An efficient randomized routing protocol for single-hop radio networks

This paper designs a novel fuzzy attributes and competition based bidding strategy (FAC-Bid), in which the final best bid is calculated on the basis of the assessment of multiple attributes of the goods and the competition for the goods in the market. The assessment of attributes adapts the fuzzy sets technique to handle uncertainty of the bidding process. The bidding strategy also uses and determines competition in the market (based on the two factors i.e. no. of the bidders participating and the total time elapsed for an auction) using Mamdani's Direct Method. Then the final price of the best bid will be determined based on the assessed attributes and the competition in the market using fuzzy reasoning technique.

ICEIS 2010 - Proceedings of the 12th International Conference on Enterprise Information Systems

Using fuzzy set approach in multi-attribute automated auctions

A digital repository is a digital archive for depositing and providing access to digital contents. It harvests metadata for providing an access framework of digital content to multiple users. In existing systems, query and retrieval is done on centralized basis and do not consider semantics of the query. Since the repositories are distributed, distinct and autonomous, there is a need for a framework which is capable of providing an efficient integrated and semantically enriched query retrieval mechanism over multiple repositories. We have proposed and implemented a multi-agent based framework for querying multiple disjoint repositories that is equipped with well defined semantic web technologies such as ontology [7, 8]. The system has been implemented using Jena framework for semantic web, Jade for agents and Java Swing for user interfaces. © 2010 IEEE.

2010 International Conference on Machine and Web Intelligence, ICMWI 2010 - Proceedings

Multi-agent based architecture for querying disjoint data repositories

Web services provide a promising solution to an age old need of fast and flexible information sharing among people and businesses. One of the key research issues in web services is selection of most pertinent web services. Selection of web service has become a tedious job because of the increasing number of service providers providing services with similar functionality. Therefore, a framework for selection and discovery of web service that can meet the non-functional requirements is needed. In this work, we have developed a selection tool (WSS-NFP) for web services which can rank services based on their non functional properties such as performance, delay etc. We have used soft computing techniques for selection and discovery of web services based on non functional properties. These properties are fuzzy in nature. A tool is developed and implemented that is generic in nature and can be customized for any application domain. As a core of this tool, it consists of Fuzzy System for ranking web services and Neural Network for fine tuning the membership functions for linguistic terms. Appropriate and fine tuned membership functions help in minimizing the output error measure and maximizing the performance index of the proposed tool. This tool is basically a Neuro-Fuzzy system for ranking web services of any domain. © 2010 IEEE.

WSS-NFP: Tool for web service selection based on non-functional properties using soft computing

The multiplex polymerase chain reaction (MP-PCR) is a quick and inexpensive technique in molecular biology for amplifying multiple DNA loci in a single Polymerase Chain Reaction (PCR). One of the criteria to achieve highly specific reaction products is to keep the concentration of the amplification primers low. In research, the dilemma associated with primer minimization for MP-PCR reactions has been formulated as the Multiple Degenerate Primer Selection Problem (MDPSP). MDPSP is related to the earlier Degenerate Primer Design (DPD) problem that has proven to be NP-complete. This paper formulates a new, so far, unexplored variant, the Multiple Degenerate Primer Selection Problem with Errors (MDPSPE) and introduces new algorithms for solving this new version. Furthermore, we implement an exact algorithm, DPS-HDR for solving the earlier MDPSP and compare the algorithm's performance on randomly generated data sets with DPS-HD, thus far the most efficient algorithm for solving MDPSP introduced in [2]. We expect to reduce the execution time of the algorithm in comparison to DPS-HD. © 2009 IEEE.

2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2009 - Proceedings

Degenerate primer selection algorithms1

In this paper, we have presented a new approach to predict pattern of the financial time series in stock market for next 10 days and compared it with the existing method of exact value prediction [2, 3, and 4]. The proposed pattern prediction technique performs better than value prediction. It has been shown that the average for pattern prediction is 58.7% while that for value prediction is 51.3%. Similarly, maximum for pattern and value prediction are 100% and 88.9% respectively. It is of more practical significance if one can predict an approximate pattern that can be expected in the financial time series in the near future rather than the exact value. This way one can know the periods when the stock will be at a high or at a low and use the information to buy or sell accordingly. We have used Support Vector Machine based prediction system as a basis for predicting pattern. MATLAB has been used for implementation. © Springer-Verlag Berlin Heidelberg 2009.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Pattern prediction in stock market

Extracting meaningful patterns from voluminous amount of biological data is a very big challenge. Motifs are biological patterns of great interest to biologists. There are different versions of the Motif Finding Problem. In this paper we concentrate on the Planted (l, d) Motif Search Problem. There have been numerous algorithms designed to solve this problem. Many instances of the Planted (l, d) Motif Problem have been identified as challenging instances. The algorithm proposed here is an extension of PMS3 [1]. It uses a very simple approach and solves challenging instances ((21, 8), for example) that have not been reported solved before in the literature. We also propose a new algorithm PMS3p. We expect PMS3p to be significantly faster than PMS3. © 2009 IEEE.