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This paper presents results of topic modeling and network models of topics using the ICCS corpus, which contains domain-specific (computational science) papers over sixteen years (a total of 5695 papers). We discuss topical structures of ICCS, how these topics evolve over time in response to the topicality of various problems, technologies and methods, and how all these topics relate to one another. This analysis illustrates multidisciplinary research and collaborations among scientific communities, by constructing static and dynamic networks from the topic modeling results and the authors’ keywords. The results of this study give insights about the past and future trends of core discussion topics in computational science. We used the Non-negative Matrix Factorization(NMF) topic modeling algorithm to discover topics and labeled and grouped results hierarchically. We used Gephi to study static networks of topics, and an R library called DyA to analyze the dynamic networks of topics. [ABSTRACT FROM AUTHOR]

Abstract: Image acquisition has great influence on the performance of any computer vision application. Different methods can be utilized to acquire the digital image of a paper, whilst scanning scheme is among the most attractive methods. This attractiveness is because of the fewer types of potential deformations and the low cost of the scanning devices, e.g. flatbed scanners. However, paper is commonly placed imperfectly on the scanner. This slight rotation is not usually based on a pivot around the paper''s geometrical center (the well known regular rotation) but instead it is based on a pivot placed at the corner of the paper. Thus, the result is a digital image that is deformed with an “irregular rotation”. The characteristic of this deformation phenomenon is currently unknown to computer vision scientists. In this paper we provide an extensive investigation of this deformation. In addition, a new set of equations that sway and measure the transformation is proposed. Our investigation leads to the conclusion that the “irregular rotation” phenomenon produces a shear transformation. Furthermore, the experimental results confirm the theoretical findings. [Copyright &y& Elsevier]

Abstract: The need for applications that are developed especially for Computational Science and Engineering (CSE) has been growing rapidly in the recent years. These applications are often a prerequisite for research and have to be evolved and maintained for considerable periods of time. However, CSE researchers have traditionally put focus on achieving better computational performance and results rather than the software’s comprehensibility, maintainability and extensibility. This paper first presents two case studies on two different CSE research projects, where common and specific problems are identified. Second we propose solutions that intend to apply software engineering methodologies and tools to improve the CSE research software development. [ABSTRACT FROM AUTHOR]

Abstract: We present Open Review, a web-based platform aimed at stimulating executable papers by means of post-publication peer-review. Its goal is to bring computer science researchers to collaboratively build their work upon previous research results, in such a way that transparency, reproducibility and sustainability of research results are greatly improved. The main design goals of the platform are clarity, conciseness, and reproducibility. Its main features are to: (i) provide incentives for making research communities to participate, (ii) make papers executable by means of boards’ annotations, without necessarily involving the authors of an article, and (iii) give snapshots of the current research state on any given article. [Copyright &y& Elsevier]

Abstract: The Workshop for the Executable Paper Grand Challenge, taking place at the 2011 International Conference on Computational Science, is a platform for Grand Challenge contestants and finalists to present their concept of an Executable Paper, a method by which data intensive research is better represented in a scholarly journal article. The Executable Paper Grand Challenge is designed to enhance how scientific information is used and communicated in computer- and computational sciences. [Copyright &y& Elsevier]

Graph mining is one of the significant tasks in the field of computer science. Most of the applications generate a vast amount of data which is represented with the help of a graph. Due to this graph representation, these applications have become complex and increased in size. Finding relevant information from that graph becomes a complicated task. For this community detection algorithms play a vital role in graph partitioning to retrieve relevant information. Finding communities in a graph reduces the complexity of the graph due to related data comes closer to forming a community. Many algorithms have been introduced in the last decade; the Clique percolation method (CPM) is the benchmark algorithm for finding an overlapping community. But in this method, some nodes remain unclassified, nodes that are not part of the clique. Paper proposed the clique-based Louvain algorithm(CBLA), which can classify the non-classified node (NCN) obtained after finding cliques in one of the communities by applying the Louvain algorithm. Louvain algorithm is used to classify the non-overlapped community, but with the help of cliques, it will also detect the overlapped nodes. This paper compared the proposed algorithm with four other benchmark algorithms. The proposed algorithm gives equal or enhanced performance among all compared algorithms. [ABSTRACT FROM AUTHOR]

The research domains and solutions of information technology have been rapidly changed as information technology continuously and deeply deployed into our society. On the other hand, it can be considered that there are some common knowledge creation processes in information technology researches. In this paper, we propose a common research process on creating new researches which were extracted by retrospectively reengineering knowledge creation model of our Information Technology research papers that were conducted with my co-authors. The research creation model is applied and evaluated by our publications. [ABSTRACT FROM AUTHOR]

In a world whose attention to environmental and health problems is very high, the issue of properly managing nuclear waste is of a primary importance. Information and Communication Technologies have the due to support the definition of the next-generation plants for temporary storage of such wasting materials. This paper investigates on the adoption of one of the most cutting-edge techniques in computer science and engineering, i.e. Digital Twins, with the combination of other modern methods and technologies as Internet of Things, model-based and data-driven approaches. The result is the definition of a methodology able to support the construction of risk-aware facilities for storing nuclear waste. [ABSTRACT FROM AUTHOR]

The technological progress in computer science (particularly, in machine learning) has contributed to the improvement of medical services, both in detecting and treating diseases. The large volumes of data, that are overwhelming for human experts (doctors, nurses), can easily be managed by automated systems, as long as we have the computational resources. Obviously, human experts are still essential in the process - we think of the use of computer science in medicine as a collaboration between medical staff and artificial intelligence. The usual types of data that can be processed by automated systems are text, sound, and image types. In this paper, we approach the diagnosis subject and focus on data consisting of sound. We created a heart murmur detection system - it analyzes recordings and tells the user whether the sound samples indicate a heart murmur or not, based on a trained machine learning model. One of the main advantages of our system is the fact that we ran a large number of experiments, with different configurations of denoising techniques and features taken into consideration. We were able to draw some interesting conclusions, for example, we found out which features are the most important for the classification and which features are not worth computing. Also, our work denotes a thorough understanding of sound processing. [ABSTRACT FROM AUTHOR]

This article discusses the correlation between first-year students' prior knowledge of programming and their academic achievements. Many students who enroll in the Faculty of Computer Science and Information Technology at Riga Technical University drop out during their first year. Therefore, it is crucial to support first-year students in acquiring programming knowledge successfully. The Faculty of Computer Science and Information Technology provides an additional course called "Algorithmization Practice" for students without prior programming experience. The authors of this paper conducted research to investigate whether this course helps bridge the gap between students with and without prior programming knowledge and whether it improves the academic performance of students without prior knowledge in their first year. The collected data was summarized using descriptive statistics, and the final scores of students from different groups were compared to identify any differences between those who attended the "Algorithmization Practice" course and those who did not. Based on a sample of 1744 introductory programming course students, our analysis indicates that students who attended the additional course demonstrated better academic performance. [ABSTRACT FROM AUTHOR]

Today's production methods are challenged by changing paradigms from a static constraint mass production and mass customization to continuing personalization and regionalization of product, production and markets. It is yet unclear what future production systems will be the most appropriate, how they will look like and how the current, uncertain trends in manufacturing can be tackled most effectively. In this paper, first results from a comprehensive questionnaire on »The Intelligent Production of the Future«, performed by a consortium of researchers from the Institute for Computer Science and Control (SZTAKI) and the Fraunhofer-Institute for Manufacturing Engineering and Automation IPA are outlined. During this survey, stakeholders and peers from more than 70 companies and research institutions in Germany, Austria and Hungary have been asked to share their impressions, describe their opinions and rate central statements on future production systems, methodologies and trends. The paper outlines the most important topics of future production systems and lessons learned during the evaluation of the survey. [ABSTRACT FROM AUTHOR]

This paper aims at identifying the key role of "Smart Energy and Power Systems Modelling", within the context of Energy Informatics. The main objective is to describe how the specific subject of "Smart Energy and Power Systems Modelling" can give a key contribution within the novel domain of Energy Informatics, by successfully linking and integrating the different disciplines involved. First the paper will present how and where the specific subject of "Smart Energy and Power Systems Modelling" can position itself within the broad Energy Informatics domain. Afterwards the paper will explain how Cyber-Physical Systems (CPS) and Information and Communication Technologies (IoT), coupled with "Smart Energy and Power Systems Modelling", can enhance the Energy Informatics domain. In addition, the main challenges and opportunities for Energy Informatics specialists will be outlined, with regard to the interdisciplinary approach that characterises this field. [ABSTRACT FROM AUTHOR]

Automatic grading is not a new approach but the need to adapt the latest technology to automatic grading has become very important. As the technology has rapidly became more powerful on scoring exams and essays, especially from the 1990s onwards, partially or wholly automated grading systems using computational methods have evolved and have become a major area of research. In particular, the demand of scoring of natural language responses has created a need for tools that can be applied to automatically grade these responses. In this paper, we focus on the concept of automatic grading of short answer questions such as are typical in the UK GCSE system, and providing useful feedback on their answers to students. We present experimental results on a dataset provided from the introductory computer science class in the University of North Texas. We first apply standard data mining techniques to the corpus of student answers for the purpose of measuring similarity between the student answers and the model answer. This is based on the number of common words. We then evaluate the relation between these similarities and marks awarded by scorers. We consider an approach that groups student answers into clusters. Each cluster would be awarded the same mark, and the same feedback given to each answer in a cluster. In this manner, we demonstrate that clusters indicate the groups of students who are awarded the same or the similar scores. Words in each cluster are compared to show that clusters are constructed based on how many and which words of the model answer have been used. The main novelty in this paper is that we design a model to predict marks based on the similarities between the student answers and the model answer. We argue that computational methods be used to enhance the reliability of human scoring, and not replace it. Humans are required to calibrate the system, and to deal with situations that are challenging. Computational methods can provide insight into which student answers will be found challenging and thus be a place human judgement is required. [ABSTRACT FROM AUTHOR]

In all engineering discipline in universities, introductory programming is an essential part of the curriculum. However, many students find great difficulty with the learning of programming without instructor assistance and it becomes a barrier to their further studies of computer science and other disciplines. Intelligent Programming Tutors (IPTs) assist students to overcome difficulties in solving programming exercises, when they don't know how to proceed or they unable to find an error in their current state. Such a student may benefit from hints, guiding her toward a more complete and/or more correct version and allowing her to continue working on her own (Aleven et al., 2016). However, traditional IPTs take much time to create the expert knowledge because in computer programming tasks, the space of possible solutions is too large (Piech et al., 2015b). New development methods have emerged in recent years, which provide hints without an expert model. These techniques are based on data-driven approaches and/or program repair techniques and provide hints in the form of edits (such as inserting or deleting a piece of code). Students can apply these hints in their current state to change it into a more correct and/or more complete state. This paper aims to provide a best understanding of these new techniques and presents a comparative study between different approaches of automatic hint generation by presenting the forces and weaknesses of each approach. [ABSTRACT FROM AUTHOR]

Diagrams continue to play an important role in different areas of computer science. In this paper, we discuss how the cognitive processing of such diagrams can be conceptually understood. To this end, we refer to the CogniDia framework, a recent framework that describes the consecutive phases of cognitive processing. We discuss experimental results for the four categories of the framework. We conclude with an outlook on future research. [ABSTRACT FROM AUTHOR]

This paper describes the application of a community detection algorithm, namely LinkRank algorithm, on a citation network. Community detection is a task in network analysis which aims to find sets of tightly connected nodes that are loosely connected with other nodes outside of those sets. In our study, we focused on a citation network which depicts relationships between cited papers and the papers which cite those papers. The objectives of our study are to identify communities of papers based on the citation relationships and analyze the similarities of topics within each community. The approach of our study to reach the objectives is by applying LinkRank algorithm to a citation network. LinkRank algorithm is chosen because it can be applied to a directed network where other algorithms that we have surveyed can only be used on undirected network. The citation network that we used in our study is from Aminer website. In applying the algorithm, we had to port the original source code which is written in C programming language into Python programming language for our convenience in doing the experiment. The result shows that the algorithm able to detect 10,442 communities from 188,514 nodes. Once the communities have been detected, we sampled top three communities (the ones with the largest number of members) and took the top 10 nodes with the highest PageRank score in each of those communities. The samples show that most of the nodes have similar topic, but there are still some nodes with different topics mixed inside the same community. We found the ratio between nodes with similar and different topics to be 7 to 3, that is 70% of the nodes have similar topic while the other 30% have different topics. Thus, the homophily of each community does not reach 100%. Nevertheless, our study confirms that LinkRank algorithm can be used for community detection on directed network. [ABSTRACT FROM AUTHOR]

Directed Acyclic Graphs (DAGs) are directed graphs in which there is no path from a vertex to itself. DAGs are an omnipresent data structure in computer science and the problem of counting the DAGs of a given number of vertices has been solved in the 70's by Robinson. In many applications one needs to construct connected DAGs and to control their number of edges, but the adaptation of Robinson's enumeration to take this into account led to counting formulas based on the inclusion-exclusion principle, inducing a high computational cost for the uniform random sampling of DAGs based on this formula. In the present paper we propose two contributions. First we enumerate a new class of DAGs, enriched with an independent ordering of the children of each vertex, according to their numbers of vertices and edges. We obtain a constructive recursive counting formula for them (i.e. without using the inclusion-exclusion principle) using a new decomposition scheme. Then we show the applicability of our method by proposing a constructive enumeration of Robinson's labelled DAGs, by vertices and edges, based on the same decomposition. As a consequence we are able to derive efficient uniform random samplers for both models. [ABSTRACT FROM AUTHOR]

In the paper, the important role of tools and distributed IT resources in the dynamic development of astrophysics, astronomy, and space exploration are discussed. New possibilities and approaches to conducting research in the field of astronomy and astrophysics with the use of cloud computing and advanced data visualization techniques are also presented. Finally, some examples of the use of digital sky survey databases in scientific research are shown. [ABSTRACT FROM AUTHOR]

Graph theory has been since long time very helpful either in science or in real life. Since it has been introduced, it was considered like a crossroad in science. Many problems are computer science, in logistics, in physics, in electrical engineering, in automatic science were all inspired by graph theory. Moreover, sone algorithms such as the shortest path are omnipresent within our life. That is why nobody could ignore the importance of graph theory. Nowadays, the graph theory, as is, could not answer correctly to our new needs. In my point, for the current graph theory to answer much better to our new problem-solving requirements, the theory must include two more main pillars: the semantic factor and the superimposition factor. In this paper we introduce the all-new graph theory: the semantic superposed graph theory. [ABSTRACT FROM AUTHOR]

The treatment of concepts as decision functions characteristic for computer science and Artificial Intelligence has its roots in the logical tradition of Gottlob Frege. In its modern incarnation, decision functions, embedded in concrete knowledge representations, describe either crisp or vague assignments of categorization decisions to objects. In order to allow for effective communication between humans and computer systems, these decisions should be either effectively explained by the system or explainable with respect to the system, which in turn depends on the degree of epistemic transparency of the computer system and the conceptual representations it uses. In this, paper we distinguish between two basic types of representation: logic-based and nature-based. With respect to the latter, we identify five contributing factors to their relative epistemic opacity: A. structural complexity, B. learning procedures, C. operating on uncertain data, D. lack of translation procedures for low-level rules and representations, and E. lack of complete knowledge about natural computing systems. We consider the fourth factor (D.) to be the most important source of opacity on the level of computer systems and the fifth (E.) the main contributing factor on the level of human knowledge. [ABSTRACT FROM AUTHOR]

In the area of computer sciences there is a rapidly developing subject of mechatronics and robotics since its relevance to the fourth industrial revolution, especially in preprofessional education – schools etc. On the other side, technologies of virtual reality (VR technologies) have been spreading in education so far, including computer sciences and mechatronics and robotics education in Russian leading research universities. In National Research Nuclear University MEPhI we have a broad experience of application of hi-tech in education. In this paper we present the results of our practical research of application of VR instruments in preprofessional education in the area of mechatronics and robotics. One of the features of our research is that we have developed the educational program for obtaining practical skills in the area of VR digital technologies in compliance with the CDIO standards. [ABSTRACT FROM AUTHOR]

The importance of derivatives in financial markets has known an exponential growth in the last decades, especially in risk management and speculation fields: this explains researchers’ interest in answering questions about this kind of contracts. In particular, in this paper we restrict our attention on European vanilla and barrier options , and we propose a statistical procedure to solve efficiently the problem of determining the no arbitrage price of this type of derivatives in an IoT context: starting form an Internet of Things (IoT) data flow, an IoT system takes information from several sources and stores it into a suitable database; this information is used in our estimation problem. Our scheme is based on some strong assumptions about the market model, in particular the completeness of the market , the log-normality of the underlying asset with a constant volatility. We conclude this paper with an application of our framework to a real case. [ABSTRACT FROM AUTHOR]

A number of studies have revealed and investigated how the clusters organized by cooperators emerge in a spatial prisoner’s dilemma. However, a qualitative analysis of the clusters formed by the cooperators has not yet been studied. This paper aims to propose a new technique for quantifying clusters that consist of players with cooperative strategies. The proposed method can be applied to the spatial prisoner’s dilemma in a square lattice network. In the proposed method, a minimum cluster is defined as a group of the cooperators based on a small square (2 by 2). This paper also defines a degree of the clusters by extending the small squares that based on how the players organize themselves into coordinated groups. The authors analyze and compare with typical examples of the clusters in the spatial prisoner’s dilemma. By analyzing the examples, this paper demonstrates that the proposed method quantifies the degree of the clusters organized by the cooperators. The authors also examine the significance of the proposed method by the simulations of the spatial prisoner’s dilemma. [ABSTRACT FROM AUTHOR]

This paper proposes a concise overview of Probabilistic Semantics according to a technology-oriented perspective. Indeed, while the progressive consolidation of Semantic Technology in a wide context and on a large scale is going to be a fact, the non-deterministic character of many problems and environments suggests the rise of additional researches around semantics to integrate the mainstream. Probabilistic extensions and their implications to the current semantic ecosystems are discussed in this paper with an implicit focus on the Web and its evolution. The critical literature review undertaken shows valuable theoretical works, effective applications, evidences of an increasing research interest as the response to real problems, as well as largely unexplored research areas. [ABSTRACT FROM AUTHOR]

In computer science, robustness is the ability of a computer system to cope with errors during execution. Robust codes are new nonlinear systematic error detecting codes that provide uniform protection against all errors, whereas classical linear error detection code detects only a certain class of errors. Therefore, defence by the linear codes can be ineffective in many channels and environments, when error distribution is unknown. The probability of error masking can increase depending on codeword distribution. However, mapping the most probable codewords to a predefined set can reduce the maximum of the error masking distribution. The algorithm proposed in this paper is based on the second-order wavelet decomposition of B-splines under non-uniform nets. In this paper, we propose a general approach to the algorithm construction of spline-wavelet decompositions of linear space over an arbitrary field. This approach is based on the generalization of calibration relations and functional systems, which are biorthogonal to basic systems of relevant space. The obtained results permit the construction of second-order spline-wavelet robust code. [ABSTRACT FROM AUTHOR]

In software testing through reverse engineering, the programming semiotics are to be transformed to Unified Modeling Language (UML) semiotics. This process needs the abstraction of UML syntactics, semantics from the programming system. As a preamble, this paper attempts to develop an automated methodology to abstract object oriented technology (OOT) components required for the class diagram from the programming system to be tested for its correctness & completeness. The methodology comprises of initial classing & slicing the programming system on the referenced attributes of the entry with no defined attributes and then using the sole referenced entry and sole defined entry on these sliced programming units the candidate key/s are identified which are used to find individual object structure of the class in our classing technique. The programming system is sliced based on individual class structure and then these slices are used to obtain the object methods through whose nature of the parameters we identify the interrelationship between the classes and their types. The intermediate clairvoyant study of parameter indicates the visibility of the object methods. This paper contains the detailed procedure for each method of our automated methodology. Therefore, their correctness and completeness is self evident. The proposed procedures are based on sound logical positivism and implicitly incorporate good database design and good software engineering principles. This paper reengineers the programming system into various appropriate UML design diagrams so as to reduce the enormity of the syntactics and semantics of programming language into limited syntactics and semantics. This enables to develop the correct and complete software testing methodology. [ABSTRACT FROM AUTHOR]

Integer Factorization is a vital number theoretic problem frequently finding application in public-key cryptography like RSA encryption systems, and other areas like Fourier transform algorithm. The problem is computationally intractable because it is a one-way mathematical function. Due to its computational infeasibility, it is extremely hard to find the prime factors of a semi prime number generated from two randomly chosen similar sized prime numbers. There has been a recently growing interest in the community with regards to evolutionary computation and other alternative approaches to solving this problem as an optimization task. However, the results still seem to be very rudimentary in nature and there's much work to be done. This paper emphasizes on such approaches and presents a critic study in details. The paper puts forth criticism and ideas in this aspect. [ABSTRACT FROM AUTHOR]

Employability is somebody's prospective for gaining and maintaining employment. Basically employability depends on basic three parameters and these parameters are as education, understanding power and personal development. It is the capability to achieve the preliminary employment, to continue it and to obtain different one, if it is required. This paper introduced an innovative knowledgeable system for valuation of employability through some fuzzy rules. The purpose and scope of this concern research is to observe the optimal valuation for employability. This concern research considers three employability skills as an input namely Education, Understanding power and Personal development and find out a novel crisp value for employability which is basically characterize the ability of employee. This paper uses twenty seven fuzzy rules, by using Mamdani type fuzzy inference system in Mat-lab for catches solitary value of output named as employability. [ABSTRACT FROM AUTHOR]

The notion of time is an important element in such systems as real-time embedded systems. Real-time systems have strict timing constraints, and their complexity is continuously increasing, making their design very challenging. This paper concerns a very high level of requirements specification used for system understanding and communication among stakeholders and as a base for development. It introduces a diagrammatic description of functional behavior of a system with nonfunctional constraints including timing plan. Specifically, this paper explores the presentation of time at this level of system description. The usability and feasibility of the proposed method are illustrated by applying it to examples. [ABSTRACT FROM AUTHOR]

Mastering the programming is no easy job because proper science of software does not yet exist. Solid and fundamental theories that apply universally are needed. Universalities ease mastering any kind of job. To ease mastering the programming, software science must answer what are the universal main concepts in programming, and the categories of token. This paper proposes punctuator and qualifier as two supplementary concepts of programming. Together with value, operation, type, and object; punctuator and universal serve as six main concepts of programming. This paper shows the six main concepts of programming serves as universal categories of tokens. The new theory for code-translation takes into account the universal categories for tokens. [ABSTRACT FROM AUTHOR]

Constraints that express relationships among objects are used to model and solve various problems arising from fields such as artificial intelligence, software, and computer graphics. Soft constraints are often important for applications that involve complex relationships among objects. This paper proposes a new method for solving soft constraints. The method treats soft nonlinear con- straints with hierarchical preferences, and computes solutions that satisfy as many constraints with strong preferences as possible. It adopts the method of Lagrange multipliers to enable the accurate computation of local solutions. The paper also presents the result of a preliminary experiment using a simple geometric example. [ABSTRACT FROM AUTHOR]

The Business Process (BP) requirements is specified in the form of software requirements specification (SRS). This SRS serves as a base for software development. The software needs to be developed in a syllogized software development life cycle (SDLC) stages. The SRS which denote the requirements of BP is used as input to the analysis stage from which the paradigm dependent components are to be abstracted. Hither to the components are abstracted manually with the exception of hiatuses of semi-automated methods for few of the components. The SRS is construed with reference to the specific paradigm through which the design is to be developed. Unfortunately, no complete automated methodology exists for the abstraction of all paradigm dependent components. The automated methodology eliminates the possible human errors which would have ripple effect to damage the entire software. This paper develops an innovative, unique methodology to resurrect the SRS statements as modular statements. Further develops an automated methodology for abstraction of control and data flow graphs. Further it develops an automated methodology for abstraction of useful components required for the class diagram. The class diagram emphasizes both structural and behavioral aspects. This facility is effectively used to abstract object class attributes, object methods, visibility, signature, return type etc. Information systems are developed through software projects which use the specific software requirements specification (SRS) provided for them as the base. The SRS contains details of the information system through which appropriate software can be developed. The information systems are also viewed perceptively with different pragmatics like work, work process or usecase. The usecase is one of the prime perspective views whose sum forms the information system. In this paper, an attempt is made to abstract object class, object class attributes, object methods, interrelationships between object classes and starting with/ending with actor from unformatted, unstructured SRS text. This is achieved through our own developed classing and slicing techniques to identify respectively the class structure & object methods. Then usecase is developed through the interrelationships between object methods of different classes and start with or end with the actor. The stages involve moulding the SRS, designing control flow graph for the SRS & data flow table for the SRS statements, developing appropriate classing and slicing criteria, creating actor & actors’ interface attributes table, create slicing criteria for each usecase and then slice relevant statements for each usecase. Here, we have attempted to use Weiser modified algorithm 1 to abstract exact usecase. The slicing criterion is obtained through the intersection of actor's interface attributes and the referenced/defined attributes present between two consecutive actors. Attempts have been made to resolve synonyms & heteronyms present in the SRS. The correctness & completeness of the proposed methodology depends on the realization of actor & actors’ interface attributes. [ABSTRACT FROM AUTHOR]

The primary cause for the slowness of the Border Gateway Protocol (BGP) convergence delay is the Minimum Route Advertisement Interval (MRAI). The MRAI is a timer with a default value of 30 seconds, which forces the BGP routers to wait for at least that amount of time before sending an advertisement for the same prefix. This process can delay important BGP advertisements. To date, there has been no specific value used by all the networks around the Internet. This paper aims to find the optimum value for the MRAI timer that maximally reduces the convergence time without increasing the number of advertisement messages. The optimal MRAI value founded by this paper reduced the convergence time by minimum 45%. [ABSTRACT FROM AUTHOR]

Enterprise Information Systems maintain data with respect to various business processes. These processes consist of business operations restricted by business rules expressed as preconditions and post-conditions. Each rule must be considered and enforced throughout the system, from user interface to persistence storage. Such rule evaluation in multiple contexts results in both significant rule restatement and high maintenance complexity, as there is no single focal point for capturing and reusing these rules. In this paper, we apply the Aspect-Oriented Design Approach to the persistence layer to simplify business rules management, enforce business rules throughout the system and consequently decrease development and maintenance efforts. Our preliminary results show that it is possible to define business rules in a single place and then apply them automatically in a persistence layer. We retrieve data sets restricted by given operation post-conditions with respect to current execution context without any manual rule restatement. This paper provides a small case study emphasizing the benefits and future challenges. [ABSTRACT FROM AUTHOR]

In computer science, robustness is the ability of a computer system to cope with errors during execution. Robust codes are new nonlinear systematic error detecting codes that provide uniform protection against all errors, whereas classical linear error detection code detects only a certain class of errors. Therefore, defence by the linear codes can be ineffective in many channels and environments, when error distribution is unknown. The probability of error masking can increase depending on codeword distribution. However, mapping the most probable codewords to a predefined set can reduce the maximum of the error masking distribution. The algorithm proposed in this paper is based on the second-order wavelet decomposition of B-splines under non-uniform nets. In this paper, we propose a general approach to the algorithm construction of spline-wavelet decompositions of linear space over an arbitrary field. This approach is based on the generalization of calibration relations and functional systems, which are biorthogonal to basic systems of relevant space. The obtained results permit the construction of second-order spline-wavelet robust code. [ABSTRACT FROM AUTHOR]

The Flower Pollination Algorithm (FPA) is a novel bio-inspired optimization algorithm that mimics the real life processes of the flower pollination. In this paper, we review the applications of the Single Flower Pollination Algorithm (SFPA), Multi-objective Flower Pollination Algorithm an extension of the SFPA and the Hybrid of FPA with other bio-inspired algorithms. The review has shown that there is still a room for the extension of the FPA to Binary FPA. The review presented in this paper can inspire researchers in the bio-inspired algorithms research community to further improve the effectiveness of the PFA as well as to apply the algorithm in other domains for solving real life, complex and nonlinear optimization problems in engineering and industry. Further research and open questions were highlighted in the paper. [ABSTRACT FROM AUTHOR]

In this paper we have presented validation of proposed usability driven web based software process model (UdWbM) through simulation. We have used Software Engineering gaming tool SimSE for making simulation of a system (taken as case study) by following the steps proposed by the model. Simulation was also developed for some existing models using the same constraints. UdWbM is then compared with some existing models to show the results. Paper also shows comparative study of existing models with UdWbM through literature. [ABSTRACT FROM AUTHOR]

Big data is an ocean of data sets. The revolution of big data can transform the world and business overnight. The data and information can be outsourced to an untrusted cloud while maintaining the velocity and veracity of big data. Big data helps in decision making. It also laid foundation for advancement in science, medicine and Business. Mapreduce and Hadoop frameworks are used to improve the processing speed of data. Can big data really revolutionize our world? This research paper explores how the explosion of information will impact on our lives? This paper illustrates the power of big data. Big data may lead to more accurate analyses. The combination of cloud and Big data is a beginning of a beautiful friendship. E-commerce companies take advantage of the wide variation in sales tax and local taxes by operating from low geographical regions like Flipkart. Big data analytics can improve efficiency and effectiveness across the broad range of government responsibilities, by improving existing processes and operations and enabling completely new ones. Moreover it is used in the areas of medicine, crime, education and business. It increases the storage capacity, processing power and also risk of security. So big data is not only a volume, it refers as technology. [ABSTRACT FROM AUTHOR]

Due to the increasing amount of data, knowledge aggregation, representation and reasoning are highly important for companies. In this paper, knowledge aggregation is presented as the first step. In the sequel, successful knowledge representation, for instance through graphs, enables knowledge-based reasoning. There exist various forms of knowledge representation through graphs; some of which allow to handle uncertainty and imprecision by invoking the technology of fuzzy sets. The paper provides an overview of different types of graphs stressing their relationships and their essential features. An example is included for didactical reasons. [ABSTRACT FROM AUTHOR]

Due to the self configuring and infra-structure less nature of MANET(Mobile Ad-hoc Network) optimization crunches, QOS(Quality of Service) contention and security breaches tend to occur. So, to rivet security of the mobile ad-hoc networks the proposed algorithm sifted in this paper cogitate biometric perception as the most innovative solution which incorporates exclusive iris features elicited by iris image procurement and perception system. QOS based issues of MANET are elucidated by genetic algorithm in this approach which results in optimized performance of the network. Significance of the approach conferred in the paper is stated through improved and better results compared with conventional secured approach of MANET. [ABSTRACT FROM AUTHOR]

Two concepts currently at the leading edge of todays information technology revolution are Analytics and Big Data. The public transportation industry has been at the forefront in utilizing and implementing Analytics and Big Data, from ridership forecasting to transit operations Rail transit systems have been especially involved with these IT concepts, and tend to be especially amenable to the advantages of Analytics and Big Data because they are generally closed systems that involve sophisticated processing of large volumes of data. The more that public transportation professionals and decision makers understand the role of Analytics and Big Data in their industry in perspective, the more effectively they will be able to utilize its promise. This paper gives an overview of Big Data technologies in context of transportation with specific to Railways. This paper also gives an insight on how the existing data modules from the transport authority combines Big Data and how can be incorporated in providing maintenance decision making. [ABSTRACT FROM AUTHOR]

This paper looks at graphical models and discusses the quality of tree approximations by ex- amining information measures and formulating the problem as a detection problem. One of the widely used algorithms for tree-structured approximation and modeling is the Chow-Liu algo- rithm. While this algorithm is optimal for Gaussian distributions in the sense of the Kullback- Leibler (KL) divergence, it is not optimal when compared with other information divergences and criteria such as Area Under the detection Curve (AUC) and reverse KL divergence. In this paper, we discuss the optimality of tree approximation methods. We show that different information theory divergences and criteria such as the KL divergence, the Jeffreys divergence and the AUC are all related of the correlation approximation matrix (CAM), Δ . We also show some explicit relations between these different information divergences and criteria and investigate the relation between quality of the tree approximation by formulating a detection problem and considering the AUC and the Jefferys divergence which is a distance between two conditional means, as alternative approaches for the tree approximation. The tree structure approximation algorithms have interesting applications. In general, the tree structured enables us to do distributed algorithms such as belief propagation and also to do inference. Because of computational complexity, it is important to consider simpler graphical models such as trees when modeling systems for many applications. We previously discuss the problem of convergence of the distributed state estimation algorithm for electric distribution grids, “mi- crogrids,” with distributed renewable energy generation. The correlations between distributed renewable energy generators was approximated by a simpler tree-structured graphical model. This paper carries the research further by looking at real spatial solar irradiation data and approximating correlation matrices by a tree structured graph. We also conduct simulations on synthetic data with larger number of nodes. [ABSTRACT FROM AUTHOR]

The paper describes an ontology-based methods and framework for design of learning courses covering the HPC and Big Data areas and how to include these into Computational Science training within the remit of existing courses of Master Programme entitled “Applied Mathematics and Computer Science” (Faculty of Mechanics and Mathematics, Perm State University, Russia). It helped bringing together the university and IT-companies around a real industry projects in the field of Big Data with active participation of master's students. In this paper, the visual tools and ontology-based methods for computer-supported collaborative learning environment will be also presented. [ABSTRACT FROM AUTHOR]

Since the critical graphs of order n ≤ 14 were studied so far [1–4,6,11] , in this paper, we are concerned with 5-critical graphs of order 15. This paper gives the complete possible list of degree sequences of 5-critical graphs of order 15. [ABSTRACT FROM AUTHOR]

Let G be finite non trivial graph. In the earlier papers idegree, odegree,iodegree, oEnergy and soEnergy were discussed and they are calculated for some standard graphs. In this paper energy graph is obtained for path and cycle and soEnergy is also found out. [ABSTRACT FROM AUTHOR]

The term solution space is widely used in the engineering community; yet there is little known about their evolution. Theoretical research in the field of systems science indicates that requirements can only reduce the solution space. Yet, some authors state that on the contrary requirements can be used to expand to or open new solution spaces. Furthermore, some practitioners defend that the requirement to use a previously nonexistent technology would actually increase the solution space or move it to a new area, while others state that more requirements make life more difficult. Who is right then? The present paper provides initial answers to this question using systems theory. In order to achieve this, the present paper differentiates between various types of solutions spaces, which depend on the systems they include. Finally, the paper provides practical examples to showcase the results of the theoretical findings within real contexts. [ABSTRACT FROM AUTHOR]

This paper will produce three areas of discussion in the field of cost estimation for unmanned autonomous systems. First, this paper will propose a common definition of an Unmanned Autonomous system. Second, it will introduce a method to estimate the cost of unmanned autonomous systems utilizing existing parametric cost estimation tools: SEER – HDR, COCOMO II, COSYSMO, and two relationships – weight and performance. The third discussion will focus on challenges surrounding autonomy. To address these challenges from a cost perspective, this paper recommends modifications to parameters within COCOMO II – via the use of object oriented function points in lieu of current methods, and COSYSMO – via the introduction of two cost driving parameters, namely, TVED and HRI-T. Finally, in summary this paper will identify areas of further research. [ABSTRACT FROM AUTHOR]

This paper discusses the use of model-based systems engineering (MBSE) models for physical protection systems (PPS) evaluation. We discuss why MBSE methodologies can be valuable in assessment of PPS. Next, we review the steps in vulnerability assessment (VA) and describe the use of SysML models in these steps. The paper presents examples of SysML models for a VA scenario. Such models can enable the development and integration of other VA tools and reduce the time and cost of conducting VA, which will lead to safer facilities. [ABSTRACT FROM AUTHOR]

The main scope of software configuration management is control of software evolution process to include at final version only valid and tested items. To achieve this, software configuration management have to prepare solutions for tasks such as identification of software configuration items, version control, build and deploy management etc. The paper provides new model-driven approach for implementation of software configuration management. New approach is supported by set of models to describe software configuration management process from different sides. New approach helps to organize existing solutions in parameterized way that increase ability of its reuse. Current paper introduces to problems in software configuration management area and main trends of new solutions. After introduction, new model-driven approach described. The second part of paper provides models for new approach. Presentation of models combined with simplified use case, which illustrates practical application of models. Finally, directions of further researches are provided. [ABSTRACT FROM AUTHOR]

India produces over two million engineering graduates a year as well as another million graduates in related fields such as computer science, biotechnology etc. Employers cite new graduates lack communication skills, problem solving skills and technical skills. The Indian Information Technology (IT) sector has fast changing technical requirements and understanding its requirement is very important for academics and professional trainers so that they can better prepare students with relevant skills. In this paper, we have developed a simple methodology to analyse the requirements of the Indian IT industry by parsing their job portals and extracting information from their job descriptions. We selected the top 10 IT companies by market cap to conduct our analysis. We extracted the number of jobs that contained each keywords like Java, CCNA, SAP, Agile and computed the popularity of each skill and ranked them accordingly. We find that IT industry requires software and skills like Java, Python, SQL are covered by most universities but paid and in demand commercial software tools like SAP, Oracle are not part of the curriculum. This methodology can also track the evolution of skills and predict new skills that can become popular in Industries in the future. [ABSTRACT FROM AUTHOR]