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Accepted Papers

  • CINNAMONS: A COMPUTATION MODEL UNDERLYING CONTROL NETWORK PROGRAMMING
    Kostadin Kratchanov, Yasar University, Turkey
    ABSTRACT

    We give the easily recognizable name “cinnamon” and “cinnamon programming” to a new computation model intended to form a theoretical foundation for Control Network Programming (CNP). CNP has established itself as a programming paradigm combining declarative and imperative features, built-in search engine, powerful tools for search control that allow easy, intuitive, visual development of heuristic, nondeterministic, and randomized solutions. We define rigorously the syntax and semantics of the new model of computation, at the same time trying to keep clear the intuition behind and to include enough examples. The purposely simplified theoretical model is then compared to both while-programs (thus demonstrating its Turing completeness), and the “real” CNP. Finally, future research possibilities are mentioned that would eventually extend the cinnamon programming into the directions of nondeterminism, randomness and fuzziness.

  • AN INNOVATIVE SOCIAL MOBILE PLATFORM TO SUPPORT REAL-TIME COMMUNICATION IN PEER TUTORING
    Meghan Wang1 and Yu Sun2, 1Valencia High School, USA and 2California State Polytechnic University, USA
    ABSTRACT

    This paper looks into the reasoning, context, and process behind the creation of the Step Up App to be used in the Step Up Club. The Step Up Club is a peer tutoring high school organization that allows students to tutor one another. The paper explains the background and the issues that exist with peer tutoring regarding challenges in communication between tutors and tutees. The app aims to provide the solution for many of those problems in creating a new platform in which students can communicate to one another about any questions regarding school academics.

  • SECURE AND AUTHENTIC DUAL STEGANOGRAPHY THROUGH HLSB WITH BLOWFISH ALGORITHM AND DWT TECHNIQUE
    Babita and Gurjeet Kaur, SBBSU University, India
    ABSTRACT

    Steganography and cryptography are two terms which are used for sending private information in a secret form. This paper represent a method for privacy so that information is not only in encrypted form but also not visible to intruder that is generated by combination of both techniques steganography and cryptography. There are many method used for both techniques. For cryptography AES, RSA, DES etc. algorithms are used and for steganography LSB, DWT, DCT etc. are used. But in this paper two methods are used. First technique Hash-LSB with blowfish algorithm is used and then DWT algorithm is used for double security. First of all, encrypted the secret message through BLOWFISH algorithm and embedded that encrypted message with cover image with using Hash- LSB. After that the stego image to be embedded into another cover image with using DWT for double security. All system is based on PSNR, MSE and BER parameters. Proposed method offered better results than existing methods.

  • USING NATURAL LANGUAGE PROCESSING FOR ANALYZING ARABIC POETRY RHYME
    Munef Abdullah Ahmed, University polytechnic of Bucharest, Romania
    ABSTRACT

    One of the challenges for the natural language processing is its use in the field of poetry especially Arabic poetry. In this paper, we have introduced an automatic novel way to find the properties of the Arabic poem. The most important of these characteristics is the rhyme and it is classification based on the theory of Al-Khalil bin Ahmed Al Farahidi. Also from the other feature like the short vowels “kasra”, “fatha”, “dammah”, “shade”, and the types of “tanween” which can be classified into “tanween fatha”, “tanween kasra”, “tanween dammah”.

  • PREDICTING SOFTWARE LAUNCH READINESS IN A COMPLEX PRODUCT
    Abhinav Sharma, HCL Technologies, UK
    ABSTRACT

    A simple model used successfully for estimating and tracking software defects to predict launch readiness of software in a complex product is described in this paper. The model is based on tracking the number of defects estimated to be found, actually found and resolved to measure the quality of the product. Defect estimates can also help identify quality and process issues in the development and testing phases.

    The defect estimation tracking method described here covers the whole project and is split into the three phases Initial Defect Estimates (based on historical data), Interim Revised Estimates (based on actual performance of the project) and Final Defect Tracking (based on testing still to do). The method is based on existing development processes of the team so is easier to implement and has been successfully applied in several projects.

  • GENERATING WORD CLOUDS FROM PH.D. THESES AT THE PHD UNS DIGITAL LIBRARY
    Georgia Kapitsaki1 and Dragan Ivanovic2, 1University of Cyprus, Cyprus2University of Novi Sad, Serbia
    ABSTRACT

    Many systems provide search and recommendation capabilities to scholars that search for scientific documents including research papers and dissertations. The appearance of search results may largely affect the system use. Traditional approaches provide textual formats for showing the results to users, whereas more recent approaches concentrate on other forms, e.g., on two dimensions. Moreover, this presentation may be adapted to user needs providing a personalized user experience combined with other contextual factors, such as enriching user search with keywords from recently used documents. In this paper, we present our work on results representation in the framework of a dissertation search engine in the Serbian language with the ultimate aim to provide a more personalized experience to users. We have integrated our approach in the PhD UNS digital library system of the University of Novi Sad, a research information, library and educational information system, and are discussing how users are perceiving this approach outlining also our vision for a context-aware digital library system. The initial results demonstrate the usefulness of providing more choices to the users adapting application to their needs.

  • COMPUTATIONAL ARCHITECTURE FOR ORGANIZATIONAL LEARNING IN RESEARCH AND DEVELOPMENT CENTERS (R&D)
    Marco Javier Suárez Barón, UNITEC/FODESEP, Colombia
    ABSTRACT

    This paper shows the construction of an organizational memory model focused on R&D centers. The model uses lessons learned extracted from corporative social networks; the model aims to promote learning and management of organizational knowledge at these types of organizations. The analysis is applied initially from lessons learned on topics of R&D in Spanish language. The model use natural languages processing together with ontologies for analyze the semantic and lexical the each lesson learned. The final result involves a knowledge base integrated by RDF files interrogated by SPARQL queries.

  • USABILITY TESTING OF FITNESS MOBILE APPLICATION: METHODOLOGY AND QUANTITATIVE RESULTS
    Ryan Alturki and Valerie Gay, University of Technology Sydney, Australia
    ABSTRACT

    Obesity is a major health problem around the world. Saudi Arabia is a nation where obesity is increasing at an alarming rate. Mobile apps could help obese individuals but they need to be usable and personalized to be adopted by those users. This paper aims at testing the usability of a fitness mobile app” Twazon”, an app in Arabic language. This paper presents an extensive literature review on the attributes that improve the usability of fitness apps. Then, it explains our methodology and our set up of a trial to test the usability of Twazon app that is popular in Saudi Arabia. The usability attributes tested are effectiveness, efficiency, satisfaction, memorability, errors, learnability and cognitive load. The trial is done in collaboration with participants from the Armed Forces Hospitals - Taif Region in Saudi Arabia. The results highlight that the app failed to meet with the usability attributes.

  • INTRODUCING COMPETITIVENESS AND INDUSTRY INVOLVEMENT AS LEARNING TOOLS
    Fernando Llopis1 and Fernando Guerrero2, 1University of Alicante, Spain and 2SolidQ, Spain
    ABSTRACT

    Continuous changes in the real world of technology involve adapting the learning content and models to the new requirements of the industry. To keep up with these changes, the industry must be deeply involved in the training experience of new students. On the other hand, increasing competitiveness in the learning experience improves students motivation and inspire them to reach higher levels of excellence. In this paper, we describe a learning environment that is being used to engage and empower students following an undergraduate software engineering course. The methodology is a combination of three main ideas: competition between student teams; Project Based Learning (PBL); and engaging an industry expert to lead each team of students, acting as product owner, or project manager. In this way, four teams of students will compete to design and develop the best possible software project based on the same requirements. Each team will have an industry expert, playing the role of product owner or project manager, leading a group of over ten students.

  • AN INTELLIGENT SELF-ADAPTIVE SYSTEM TO AUTOMATE THE SPRINKLER CONTROL
    Jiahao Li1, Yu Sun2 and Fangyan Zhang3, 1Northwood High School, USA, 2California State Polytechnic University, USA and 3Mississippi State University, USA
    ABSTRACT

    It has been seven years since California is in serious drought. The dam holds rare water, and for some area the plants and people are suffered. While the technologies of desalination and reusing water is improving, it is significant if we solve the problem from the root, which is reducing water usage and saving water. Since eighty percent of water in California is used for agriculture and greening, it is efficient if we break through the system of irrigation. Currently, there are many ways to reduce watering in agriculture such as dropping water drops from pipes instead of spraying water; however, there are now resolution addressing the system of private watering yard in communities. The sprinkler device that we designed can contribute to reduce the water that is sprayed through sprinkler by adjusting the status of sprinklers (turning on or turning off) base on real-time weather conditions (temperature and soil humidity). Our purpose is to reduce the spraying water as much as possible if the weather condition allowed.

  • ON THE IMPLEMENTATION OF GOLDBERG'S MAXIMUM FLOW ALGORITHM IN EXTENDED MIXED NETWORK
    Nguyen Dinh Lau and Tran QuocChien, The University of Danang, Vietnam
    ABSTRACT

    In this paper, we solve this problem of finding maximum flow in extended mixed networkby Revisedpreflow-push methods of GoldbergThis algorithm completely different algorithm postflow-pull in [15]. However, we share some common theory with [4], [5] and [15].

  • AUTOMATIC LEARNING OF SEMANTIC RELATIONSHIPS FOR THE ONTOLOGY CONSTRUCTION - APPLICATION ON ARABIC TEXT
    Ali Benabdallah and Nour Elhouda Boughari, University of Abou Bekr Belkaïd, Algeria
    ABSTRACT

    The construction of an ontology from a textual corpus begins with the extraction of concepts constituting this ontology, and these concepts will be linked by semantic relationships. In this paper, we propose an extraction approach of the most important elements of the ontology, based first on a statistical method of extraction of the terms which is called “repeated segments method”, followed by the application of a weight filter to choose the most common terms. Then, in order to extract the semantic relationships linking the extracted concepts, we apply a machine learning technique based on a set of syntactic and semantic features of the sentences of the corpus. And finally we will discuss the results that can be obtained by applying our approach on a textual corpus of the Arabic language

  • A SUSTAINABLE CITY PLANNING ALGORITHM BASED ON TLBO AND LOCAL SEARCH
    Ke Zhang, Li Lin, Xuanxuan Huang, Yiming Liu and Yonggang Zhang, Jilin University, China
    ABSTRACT

    Nowadays, how to design a city with more sustainable features has become a centre problem in the field of social development, meanwhile it has provided a broad stage for the application of artificial intelligence theories and methods. Because the design of sustainable city is essentially a constraint optimization problem, the swarm intelligence algorithm of extensive research has become a natural candidate for solving the problem. TLBO (Teaching-Learning-Based Optimization) algorithm is a new swarm intelligence algorithm. Its inspiration comes from the "teaching" and "learning" behaviour of teaching class in the life. The evolution of the population is realized by simulating the "teaching" of the teacher and the student "learning" from each other, with features of less parameters, efficient, simple thinking, easy to achieve and so on. It has been successfully applied to scheduling, planning, configuration and other fields, which achieved a good effect and has been paid more and more attention by artificial intelligence researchers. Based on the classical TLBO algorithm, we propose a TLBO_LS algorithm combined with local search. We design and implement the random generation algorithm and evaluation model of urban planning problem. The experiments on the small and medium-sized random generation problem showed that our proposed algorithm has obvious advantages over DE algorithm and classical TLBO algorithm in terms of convergence speed and solution quality

  • STUDY THE GRAY SCALE IMAGES OF DROPWISE CONDENSATION ON TEXTURED SURFACES
    Helene Martin1,Solmaz Boroomandi Barati2,Jean-Charles Pinoli1,Stephane Valette2,and Yann Gavet1, 1Ecole Nationale Superieure des Mines de Saint-Etienne, France and 2University Lyon, France
    ABSTRACT

    Nowadays, how to design a city with more This study deals with developing an image processing algorithm that is able to recognize spherical and ellipsoidal droplets growing on pillared surfaces during heterogonous dropwise condensation. The problem with recognizing droplets on the pillared substrates is that droplets are very similar to the pillars or they cover several pillars at the same time, so characterizing the pillars is very important. On the other hand the droplets are not always perfectly spherical or they are connected and form irregular shapes, in such cases the ability to recognizing and separating connected droplets is anotherchallenging step. The method that is used here consists of three main parts: pillars characterization, droplets categorizing and droplets segmentation. The result of this algorithm will be binarized images that enable to extract the information related to the size and density of droplets neededfor studying droplets evolution during time. Also a computer simulation method is proposed to generate ellipsoidal droplets on pillared substrate. The results of this algorithm then are validated by comparing with results from experimental procedure.






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