CST 2014 International Conference on Foundations of Computer Science & Technology

Accepted Papers

  • RECOOP: An Eclipse Plug-In for Collaborative Programming Learning
    Sharifah Mashita Syed-Mohamad, Nurliana Yusri, Nur'Aini Abdul Rashid and Nurul Malim,Universiti Sains Malaysia, Malaysia
    ABSTRACT
    There is general agreement on the difficulty of teaching and learning programming. One of the key issues is the ways in which the participants teach and learn. Several reports in the literature indicate that the learning experience is enhanced when students learn to program by working together. This paper describes the architecture and initial implementation of a tool suite called ReCOOP: a real-time collaborative tool with communication supports to aid teaching and learning programming through the practice of party programming. This tool is being implemented as an Eclipse plug-in that provides a number of features in Computer-Supported Collaborative Learning (CSCL) environment. Collaborative editor, session recorder, screen share, video conference and chat features will enable participants to learn programming collaboratively. Once its implementation is finished it is expected that the tool will be valuable in aiding the process of teaching and learning programming.
  • Pronominal anaphora resolution using XML tagged documents
    Allaoua Refoufi,University of Setif,Algeria
    ABSTRACT
    Anaphora resolution has become a major issue in NLP systems; in this work we propose a resolution approach in which texts are parsed by a definite clause grammar and then converted into an XML-tagged representation, where sentence elements are marked with discourse, syntactic, and semantic attributes. This extension was made primarily to test the viability of using XML tagged documents for anaphora resolution. The XML representation allows valuable text's enrichment with anaphoric information in an elegant and easy way. The system's performance arises primarily from the integration of multiple knowledge sources in a modular architecture and uses constraints and preferences to select the antecedent. The developed system proposes to resolve pronominal anaphora, namely personal pronouns.
  • On Selection of Periodic Kernels Parameters in Time Series Prediction
    Marcin Michalak,Silesian University of Technology,Poland
    ABSTRACT
    In the paper the analysis of the periodic kernels parameters is described. In the basis of the Periodic Kernel Estimator (PerKE) the prediction of real time series is performed. This paper describes an easy methodology of finding values of parameters of periodic kernels. Two different error measures were taken into consideration as the prediction qualities. The methodology was tested on benchmark and real datasets.
  • Analysis of Intraday Trading of Index Option in Korean Option Market
    Young-Hoon Ko, Hyupsung University, South Korea
    ABSTRACT
    The option market in South Korea began on 7 July 1997. After then, the amount of option market has increased steeply. In these days, average daily payments is beyond 1 trillion won. It is impossible to predict the market. But using the statistics, investors can get a profit steadly. The open interest contracts of index future has increased over 4000 after start time of a day and decrease down to about 0 when closing time. As for this characteristics of index future, Ko[1] suggested the volatility strategy and brought the result of simulation with the profit of 1.07 % per a day. This profit comes to real if an investor finds a brokerage firm with low commissions. This paper suggests another strategy. The price of options consists of time value and intrinsic value. And the fall of index future is faster than rising. Therefore velocity of moving index cause the price of options. The simulation results give a fascinating fact that put option tends to increase in the morning and call option tends to increase in the afternoon. With this velocity strategy, investors get the profit 1.4% per a day except commissions of 0.15% per one trade.
  • A SAT Encoding for Solving Games with Energy Objectives
    Raffaella Gentilini,Universit`a di Perugia,Italy
    ABSTRACT
    Recently, a reduction from the problem of solving parity games to the satisfiability problem in propositional logic (SAT) have been proposed in [5], motivated by the success of SAT solvers in symbolic verification.With analogous motivations, we show how to exploit the notion of energy progress measure to devise a reduction from the problem of energy games to the satisfiability problem for formulas of propositional logic in conjunctive normal form.
  • FESA: Fuzzy-controlled Energy-efficient Selective Allocation And Reallocation of Tasks Among Mobile Robots
    Anuradha Banerjee1, Dr. Paramartha Dutta2,1Kalyani Govt. Engg. College,India,2Visva-Bharati University,India
    ABSTRACT
    Energy aware operation is one of the visionary goals in the area of robotics because operability of robots is greatly dependent upon their residual energy. Practically, the tasks allocated to robots carry different priority and often an upper limit of timestamp is imposed within which the task needs to be completed. If a robot is unable to complete one particular task given to it the task is reallocated to some other robot. The collection of robots is controlled by a Central Monitoring Unit (CMU). Selection of the new robot is performed by a fuzzy controller called Task Reallocator (TRAC). It accepts the parameters like residual energy of robots, possibility that the task will be successfully completed by the new robot within stipulated time, distance of the new robot (where the task is reallocated) from distance of the old one (where the task was going on) etc. The proposed methodology increases the probability of completing globally assigned tasks and saves huge amount of energy as far as the collection of robots is concerned.
  • Cost-effective Route Discovery (CERD) For Mobile Ad Hoc Networks
    Anuradha Banerjee,Kalyani Govt. Engg. College,India
    ABSTRACT
    A mobile ad hoc network is an infrastructure less network, where nodes are free to move independently in any direction. The nodes have limited battery power; hence we require energy efficient route discovery technique to enhance their lifetime and network performance. In this paper, I propose an energy-efficient route discovery technique CERD that greatly reduces the number of route-requests flooded into the network and also gives priority to the route-request packets sent from the routers that has communicated with the destination very recently, in single or multi-hop paths. This not only enhances the lifetime of nodes but also decreases the delay in tracking the destination.
  • Ant Colony Algorithm Based View On Intelligent Path Planning Application For Mobile Robots
    GUO Yue1,XU Si2,1Ningbo University of Technology,China,2Jiangxi Vocational College of Finance and Economics,China
    ABSTRACT
    With the development of robotics and artificial intelligence field unceasingly thorough, path planning as an important field of robot calculation has been widespread concern. This paper analyzes the current development of robot and path planning algorithm and focuses on the advantages and disadvantages of the traditional intelligent path planning as well as the path planning. The problem of mobile robot path planning is studied by using ant colony algorithm, and it also provides some solving methods.
  • Dictionary-Based Concept Mining: An Application for Turkish
    Cem Rıfkı Aydın, Ali Erkan and Tunga Gungor,Boğazici University, Istanbul, Turkey
    ABSTRACT
    In this study, a dictionary-based method is used to extract expressive concepts from documents. So far, there have been many studies concerning concept mining in English, but this area of study for Turkish, an agglutinative language, is still immature. We used dictionary instead of WordNet, a lexical database grouping words into synsets that is widely used for concept extraction. The dictionaries are rarely used in the domain of concept mining, but taking into account that dictionary entries have synonyms, hypernyms, hyponyms and other relationships in their meaning texts, the success rate has been high for determining concepts. This concept extraction method is implemented on documents, that are collected from different corpora.
  • A content based watermarking scheme using radial symmetry transform and singular value decomposition
    Lakehal Elkhamssa1,Benmohammed Mohamed2,1Batna University,Algeria,2Mentouri University,Algeria
    ABSTRACT
    The Watermarking techniques represent actually a very important issue in digital multimedia content distribution. To protect digital multimedia content we embed an invisible watermark into images which facilitate the detection of different manipulations, duplication, illegitimate distributions of these images. In this paper we present an approach to embedding invisible watermarks into color images using a robust transform of images that is the Radial symmetry transform. The watermark is inserted in blocs of eight pixels large of the blue channel using the Singular Value Decomposition (SVD) of these blocs and those of the radial symmetry transform. The insertion in the blue channel is justified when we know that many works states that the human visual system is less sensible to perturbation in the blue channel of the image. Results obtained after tests show that the imperceptibility of the watermark using this approach is good and its robustness face to different attacks leads to think that the proposed approach is a very promising one.
  • SOMSN: An Effective Self Organizing Map for Clustering of Social Networks
    Fatemeh Ghaemmaghami, Sattar Hashemi,Shiraz University,Iran
    ABSTRACT
    Graph Clustering is a fundamental problem in many areas of research. The purpose of clustering is to organize people, objects, and events in different clusters in such a way that there exist a relatively strong degree of association between the members of each cluster and a relatively weak degree of association between members of different clusters.
    In this paper, a new algorithm named self-organizing map for clustering social networks (SOMSN) is proposed for detecting such groups and use it to analyze some well-known social networks. SOMSN is based on self-organizing map neural network. In SOMSN, by adapting new weight-updating method, a social network is divided into different clusters according to the topological connection of each node. These clusters are the communities we mentioned above, in social networks
  • Finding important nodes in social networks based on modified Pagerank
    Li -qing Qiu1, Yong-quan Liang1, Jing-Chen2,1Shandog University of Science and Technology,China,2Shandong labor vocational and technical college,China
    ABSTRACT
    Important nodes are individuals who have huge influence on social network. Finding important nodes in socail networks is of great significance for research on the structure of the social networks. Based on the core idea of pagerank,a new ranking method is proposed by considering the link similarity between the nodes. The key concept of the method is the use of the link vector which records the contact times between nodes. Then the link similarity is computed based on the vectors through the similarity function. The proposed method incorporates the link similarity into original pagerank. The experiment results show that the proposed method can get better performance.
  • Use of Prediction Algorithms in Smart Homes
    Aditi Dixit and Anjali Naik,Cummins College of Engineering For Women,India
    ABSTRACT
    'Smart Homes' or 'Intelligent Homes' are capable in making smart or rational decisions and increase home automation. This is done to maximize inhabitant comfort and minimize operation cost. Tracing and predicting the mobility patterns and usages of devices by the inhabitant, sets a step towards the objective. The paper discusses in detail, the role of certain Prediction algorithms to bring about next event recognition. Further, an Episode Discovery helps in finding the frequency of occurrence of these events and targeting the particular events for automation. The effectiveness of the Prediction algorithms used is demonstrated ;making it clear how they prove to be a key component in the efficient implementation of a Smart Home architecture.
  • Quality of Service Management in Distributed Feedback Control Scheduling Architecture using Different Replication Policies
    Malek Ben Salem1, Emna Bouazizi1, Rafik Bouaziz1, Claude Duvallet2,1Sfax University, Tunisia,2Universit'e du Havre,France
    ABSTRACT
    In our days, there are many real-time applications that use data which are geographically dispersed. The distributed real-time database management systems (DRTDBMS) have been used to manage large amount of distributed data while meeting the stringent temporal requirements in real-time applications. Providing Quality of Service (QoS) guarantees in DRTDBMSs is a challenging task. To address this problem, different research works are often based on distributed feedback control real-time scheduling architecture (DFCSA). Data replication is an efficient method to help DRTDBMS meeting the stringent temporal requirements of real-time applications. In literature, many works have designed algorithms that provide QoS guarantees in distributed real-time databases using only full temporal data replication policy. In this paper, we have applied two data replication policies in a distributed feedback control scheduling architecture to manage a QoS performance for DRTDBMS. The first proposed data replication policy is called semitotalreplication, and the second is called partial replication policy.