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This paper mainly focuses on how to construct concept lattice effectively and efficiently based on improved variable precision rough set. On the basis of preprocessing formal concept, one algorithm that can determine the value range of variable precision parameter β according to the approximate classification quality is proposed. An improved β -upper and lower distribution attribute reduction algorithm is also proposed based on the improved variable precision rough set, the algorithm can be used for attribute reduction on the original data of the concept lattice, and to eliminate the redundant knowledge or noises of the formal context. For the reduced formal context, the paper combines the concept construction algorithm with an improved rule acquisition algorithm seamlessly, and proposes a novel approach of concept lattice construction based on improved variable precision rough set. Finally, a concept lattice generation prototype system is developed, this paper also performs comprehensive experiments, and the effectiveness of the improved algorithm is proved through the experimental results. [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]

Graphs in computer science are widely used in social network analysis, computer networks, transportation networks, and many other areas. In general, they can visualize relationships between objects. However, fast drawing of graphs and other structures containing large numbers of data points with readable layouts is still a challenge. This paper describes a novel variant of the Fruchterman–Reingold graph layout algorithm which is adapted to GPU parallel architecture. A new approach based on space-filling curves and a new way of repulsive forces computation on GPU are described. The paper contains both performance and quality tests of the new algorithm. [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 paper reports on the 40 years of development of Computer Graphics and, more recently, Visual computing (VC) at the Technische Universität Darmstadt in Germany, from its beginning in 1975 to the leading “Computer Graphics and Visual Computing Hub” in Europe as of 2014. This development is described along three axes. First, the institutional development and its rational to establish Computer Graphics as a discipline of Computer Science and as an enabling technology for developing our Knowledge Society, are described. Second, the scientific and technological impact based on the teaching activities and the large number of theses submitted in Darmstadt for the area during these 40 years are addressed. Finally, the research road maps of the Computer Graphics and Visual Computing Hub in Darmstadt are presented relatively to the different stages of CG and VC research, relatively to a scientific view to the large number of projects implemented over these 40 years and, finally, also relatively to the project results as seen from the media. In order to manage the quantity as well as the complexity of the information available, the description of these road maps is divided in four time periods: 1975–1984, 1985–1994, 1995–2004 and 2004–2015. The paper also gives the view of the authors on how they see the future of Computer Graphics and Visual Computing. At the end, the paper includes an extensive list of references for the reported content. [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]

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]

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]

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 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]

Icon plays a critical role in computer interface design. Studies on icon taxonomy explain the way in which various types of icon represent the objects and provide designers creation rules by which icons are more in line with users’ cognitive psychology. However, along with larger and larger use of icons, the previous classification criterion causes the boundary between categories blur. What’s more, Single classification standard is not able to well illustrate the icons applied in today’s computer applications. The purpose of this paper is to present an objective-oriented icon taxonomy which proposes to categorize icons into action icon and knowledge icon. To assess this proposition, we analyzed a sample of icons that applied in computer interface and suggest precise application domains to both action icon and knowledge icon categories. The results of this practice manifested that action icon and knowledge icon implied a high relation with applied environment and explicated the development trace of computer icons. This work is one of the first to point out the notion of knowledge icon and to highlight the importance of objective of icon application. Findings in this paper could enrich icon use in computer interface design, especially provides possible way to improve online knowledge sharing by visual tool like icon. [ABSTRACT FROM AUTHOR]

Modern businesses benefit significantly from advances in computer vision technology, one of the important sectors of artificially intelligent and computer science research. Advanced computer vision issues like image processing, object recognition, and biometric authentication can benefit from using deep learning methods. As smart devices and facilities advance rapidly, current networks such as 4 G and the forthcoming 5 G networks may not adapt to the rapidly increasing demand. Classification of images, object classification, and facial recognition software are some of the most difficult computer vision problems that can be solved using deep learning methods. As a new paradigm for 6Core network design and analysis, artificial intelligence (AI) has recently been used. Therefore, in this paper, the 6 G wireless network is used along with Deep Learning to solve the above challenges by introducing a new methodology named Optimizing Computer Vision with AI-enabled technology (OCV-AI). This research uses deep learning – efficiency algorithms (DL-EA) for computer vision to address the issues mentioned and improve the system's outcome. Therefore, deep learning 6 G proposed frameworks (Dl-6 G) are suggested in this paper to recognize pattern recognition and intelligent management systems and provide driven methodology planned to be provisioned automatically. For Advanced analytics wise, 6 G networks can summarize the significant areas for future research and potential solutions, including image enhancement, machine vision, and access control. [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]

In a recent paper (M. Barash, A. Okhotin, “An extension of context-free grammars with one-sided context specifications”, Inform. and Comput. , 2014), the authors introduced an extension of the context-free grammars equipped with an operator for referring to the left context of the substring being defined. This paper proposes a more general model, in which context specifications may be two-sided, that is, both the left and the right contexts can be specified by the corresponding operators. The paper gives the definitions, presents several examples of grammars and establishes a basic normal form theorem. This normal form, in particular, leads to a simple parsing algorithm working in time O ( n 4 ) , where n is the length of the input string. [ABSTRACT FROM AUTHOR]

Context: Crowdsourcing, or tapping into the power of the crowd for problem solving, has gained ever-increasing attraction since it was first introduced. Crowdsourcing has been used in different disciplines, and it is becoming well-accepted in the marketplace as a new business model which utilizes Human Intelligence Tasks (HITs). Objective: While both academia and industry have extensively delved into different aspects of crowdsourcing, there seems to be no common understanding of what crowdsourcing really means and what core and optional features it has. Also, we still lack information on the kinds and disciplines of studies conducted on crowdsourcing and how they defined it in the context of their application area. This paper will clarify this ambiguity by analysing the distribution and demographics of research in crowdsourcing and extracting taxonomy of the variability and commonality in the constructs defining the concept in the literature. Method: We conduct a systematic mapping study and analyse 113 papers, selected via a formal process, and report and discuss the results. The study is combined by a content analysis process to extract a taxonomy of features describing crowdsourcing. Results: We extract and describe the taxonomy of features which characterize crowdsourcing in its four constituents; the crowd, the crowdsourcer, the crowdsourced task and the crowdsourcing platform. In addition, we report on different mappings between these features and the characteristics of the studied papers. We also analyse the distribution of the research using multiple criteria and draw conclusions. For example, our results show a constantly increasing interest in the area, especially in North America and a significant interest from industry. Also, we illustrate that although crowdsourcing is shown to be useful in a variety of disciplines, the research in the field of computer science still seems to be dominant in investigating it. Conclusions: This study allows forming a clear picture of the research in crowdsourcing and understanding the different features of crowdsourcing and their popularity, what type of research was conducted, where and how and by whom. The study enables researchers and practitioners to estimate the current status of the research in this new field. Our taxonomy of extracted features provides a reference model which could be used to configure crowdsourcing and also define it precisely and make design decisions on which of its variation to adopt. [ABSTRACT FROM AUTHOR]

This paper proposes a methodology for identifying data samples that are likely to be mislabeled in a c -class classification problem (dataset). The methodology relies on an assumption that the generalization error of a model learned from the data decreases if a label of some mislabeled sample is changed to its correct class. A general classification model used in the paper is OP-ELM; it also provides a fast way to estimate the generalization error by PRESS Leave-One-Out. It is tested on two toy datasets, as well as on real life datasets for one of which expert knowledge about the identified potential mislabels has been sought. [ABSTRACT FROM AUTHOR]

Induction plays a key role in reasoning in many areas of mathematics and computer science. A central problem in the automation of proof by induction is the non-analytic nature of induction invariants. In this paper we present an algorithm for proving universal statements by induction that separates this problem into two phases. The first phase consists of a structural analysis of witness terms of instances of the universal statement. The result of such an analysis is a tree grammar which induces a quantifier-free unification problem which is solved in the second phase. Each solution to this problem is an induction invariant. The arguments and techniques used in this paper heavily exploit a correspondence between tree grammars and proofs already applied successfully to the generation of non-analytic cuts in the setting of pure first-order logic. [ABSTRACT FROM AUTHOR]

The International Planning Competition is organized in the context of the International Conference on Automated Planning and Scheduling (ICAPS) and it is considered a reference source for the planning and scheduling community. The competition is typically organized every two years and deals with relevant issues for the community such as the definition of evaluation standards, the publication of benchmarks and the collection and dissemination of data about state-of-the-art planners. This paper focuses on the deterministic part, the longest-running part of the International Planning Competition. The paper describes its format, the participants, the selection of benchmarks and the generated results accompanied with analysis from different perspectives. The paper also examines the results of a brand new track created to explore the potential of planners that exploit the power of multi-core processors. Overall, the results of the competition indicate significant progress with respect to previous competitions, but they also reveal that some issues remain open and need further research, such as the coverage of temporal planners when concurrency is required and the performance in the multi-core track. As a novelty, all the data and the software generated for running the competition have been made publicly available allowing researchers to reproduce the competition and to carry out different analysis of the results. [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]

This paper presents a model for semantic network representation. According to the model, the main purpose of a semantic network is to help to correctly and quickly understand the features and structure of the solutions, and then make reliable predictions about their outcomes and rewards. These objectives are achieved under constrains like limited resources (e.g., memory size and access), time limitations, and variations of solution characteristics. The paper summarizes the elements of the model and presents a set of properties that describe the effectiveness of semantic networks in creative problem solving, including design. Six examples (based on three case studies from the related literature and three experimental studies conducted by the authors) discuss the model elements, characteristics, and properties. [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]

Many problems in Computer Science can be abstracted to the following question: given a set of objects and rules respectively, which new objects can be produced? In the paper, we consider a succinct version of the question: given a set of binary strings and several operations like conjunction and disjunction , which new binary strings can be generated? Although it is a fundamental problem, to the best of our knowledge, the problem hasn't been studied yet. In this paper, an O ( m 2 n ) algorithm is presented to determine whether a string s is representable by a set W , where n is the number of strings in W and each string has the same length m . However, looking for the minimum subset to represent a given string is shown to be NP -hard. Also, finding the smallest subset to represent each string in the original set is NP -hard. We establish tight inapproximability results and approximation algorithms for these NP -hard problems. In addition, we prove that counting the number of representable strings is # P -complete. We then explore how the problems change when the operator negation is available. For example, if the operator negation can be used, the counting problem is as simple as some power of 2. This difference may help us to better understand the problem. [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]

Finding heavy-elements (heavy-hitters) in streaming data is one of the central, and well-understood tasks. Despite the importance of this problem, when considering the sliding windows model of streaming (where elements eventually expire) the problem of finding L 2 -heavy elements has remained completely open despite multiple papers and considerable success in finding L 1 -heavy elements. Since the L 2 -heavy element problem doesn't satisfy certain conditions, existing methods for sliding windows algorithms, such as smooth histograms or exponential histograms are not directly applicable to it. In this paper, we develop the first polylogarithmic-memory algorithm for finding L 2 -heavy elements in the sliding window model. Our technique allows us not only to find L 2 -heavy elements, but also heavy elements with respect to any L p with 0 < p ≤ 2 on sliding windows. By this we completely “close the gap” and resolve the question of finding L p -heavy elements in the sliding window model with polylogarithmic memory, since it is well known that for p > 2 this task is impossible. We demonstrate a broader applicability of our method on two additional examples: we show how to obtain a sliding window approximation of the similarity of two streams, and of the fraction of elements that appear exactly a specified number of times within the window (the α -rarity problem). In these two illustrative examples of our method, we replace the current expected memory bounds with worst case bounds. [ABSTRACT FROM AUTHOR]

The problem of automated theorem finding is one of the 33 basic research problems in automated reasoning which was originally proposed by Wos in 1988, and it is still an open problem. To solve the problem, an approach of forward deduction based on the strong relevant logics was proposed. Following the approach, this paper presents a systematic methodology for automated theorem finding. To show the effectiveness of our methodology, the paper presents two case studies, one is automated theorem finding in NBG set theory and the other is automated theorem finding in Peano's arithmetic. Some known theorems have been found in our case studies. [ABSTRACT FROM AUTHOR]

In the last decade, many computer science disciplines have been manipulating large amounts of data like artificial neural networks, data recognition, data mining and big data. Recently, many programmers and application designers have relied on the matrices in their algorithms to handle large numbers of data simultaneously to enriching the parallelism for their systems. However, due to the growth of the data amount in the matrices, there is a need to reshaping these matrices according to the capabilities of the computer systems that are processing these data. Consequently, our idea is developing algebraic operations that can represent the reshaping of matrices within the mathematical equations. In this paper, we develop fully two novel compatible algebraic matrices operations to solve this problem. The first operation called "Matrix-Separation" and the second operation denoted by "Matrices-Joining". These two novel operations assist the programmers and scientists to perform their programs evaluations and developments. [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]

The paper presents the results of the cognitive modeling of the COMPUTER SCIENCE terminological system in the form of a thesaurus. The thesaurus comprises over 3000 units, which are drawn from explanatory monolingual and bilingual dictionaries of computer science terms representing the basic phenomena and processes in the professional context. Methodologically, the analysis is based on the frame model and focuses on semantic relations specific to the sphere of computer science in terms of ontological and epistemological features. The thesaurus facilitates the detailed description and effective arrangement of the terminological system characterized by a complicated hierarchical structure, and thus plays a crucial role in forming and developing professional competencies. [ABSTRACT FROM AUTHOR]

This paper is about two generalizations of the mistake bound model to online multiclass classification. In the standard model , the learner receives the correct classification at the end of each round, and in the bandit model , the learner only finds out whether its prediction was correct or not. For a set F of multiclass classifiers, let opt std (F) and opt bandit (F) be the optimal bounds for learning F according to these two models. We show that an opt bandit (F) ≤ (1 + o (1)) (| Y | ln ⁡ | Y |) opt std (F) bound is the best possible up to the leading constant, closing a Θ (log ⁡ | Y |) factor gap. [ABSTRACT FROM AUTHOR]

Pattern languages have been an object of study in various subfields of computer science for decades. This paper introduces and studies a decision problem on patterns called the finite distinguishability problem: given a pattern π , are there finite sets T + and T − of strings such that the only pattern language containing all strings in T + and none of the strings in T − is the language generated by π ? This problem is related to the complexity of teacher-directed learning, as studied in computational learning theory, as well as to the long-standing open question whether the equivalence of two patterns is decidable. We show that finite distinguishability is decidable if the underlying alphabet is of size other than 2 or 3, and provide a number of related results, such as (i) partial solutions for alphabet sizes 2 and 3, and (ii) decidability proofs for variants of the problem for special subclasses of patterns, namely, regular, 1-variable, and non-cross patterns. For the same subclasses, we further determine the values of two complexity parameters in teacher-directed learning, namely the teaching dimension and the recursive teaching dimension. [ABSTRACT FROM AUTHOR]

Proteomics is the extensive investigation of proteins which has empowered the recognizable proof of consistently expanding quantities of protein. Proteins are necessary part of living life form, with numerous capacities. The proteome is the complete arrangement of proteins that are created or altered by a life form or framework of the organism. Proteome fluctuates with time and unambiguous prerequisites, or stresses, that a cell or organism experiences. Proteomics is an interdisciplinary area that has derived from the hereditary data of different genome ventures. Much proteomics information is gathered with the assistance of high throughput techniques, for example, mass spectrometry and microarray. It would regularly take weeks or months to analyze the information and perform examinations by hand. Therefore, scholars and scientific experts are teaming up with computer science researchers and mathematicians to make projects and pipeline to computationally examine the protein information. Utilizing bioinformatics procedures, scientists are prepared to do quicker investigation and protein information storing. The goal of this paper is to brief about the review of machine learning procedures and its application in the field of proteomics. • Study of machine learning algorithm, proteomics,artificial neural network. • Study of machine learning algorithm for protein secondary structure prediction. • Study of machine learning algorithm for protein tertiary structure prediction. • Study of machine learning algorithm for protein torsion angle prediction. • Study of machine learning algorithm for protein loop modeling. [ABSTRACT FROM AUTHOR]

Lazy evaluations are playing important roles in various fields of computer science including hardware design, programming, decision making. In this paper one of the most known and used fuzzy logic system, the Łukasiewicz logic is considered. Pruning algorithms are presented to quicken the evaluations of logical formulae in Łukasiewicz logic by cutting out those branches of the formula tree that have no influence on the final result for some reasons. Correctness of the algorithm is also proven. [ABSTRACT FROM AUTHOR]

Combinatorial problems are a fundamental research subject of theoretical computer science, and for a general graph many combinatorial problems are NP-hard and even #P-complete. Thus, it is interesting to seek or design special graphs for which these difficult combinatorial problems can be exactly solved. In this paper, we study some combinatorial problems for the Farey graphs, which are translated from Farey sequences and have received considerable attention from the scientific community. We determine exactly the domination number, the independence number, and the matching number. Moreover, we derive exact or recursive solutions to the number of minimum dominating sets, the number of dominating sets, the number of maximum independent sets, the number of independent sets, the number of maximum matchings, as well as the number of matchings. Finally, we obtain explicit expressions for the number of acyclic orientations and the number of root-connected acyclic orientations. Since the considered combinatorial problems have found wide applications in diverse fields, such as network science and graph data miming, this work is helpful for deepening our understanding of the applications for these combinatorial problems. [ABSTRACT FROM AUTHOR]

The burning number b (G) of a graph G was introduced by Bonato, Janssen, and Roshanbin [Lecture Notes in Computer Science 8882(2014)] to measure the speed of the spread of contagion in a graph. The graph burning problem is NP-complete even for trees. In this paper, we show that the burning number of any theta graph of order n = q 2 + r with 1 ≤ r ≤ 2 q + 1 is either q or q + 1. Furthermore, we characterize all theta graphs that have burning number q or q + 1. [ABSTRACT FROM AUTHOR]

• A novel SMO inspired by mimicking behavior to solve optimization problems is presented. • SMO includes a mimic operator to simulate search in the response space. • SMO does not require control operator respect to other Meta heuristic methods. • SMO solve optimization problems with minimum population size. • SMO is compared with 14 well-known and state of the art optimization algorithms. Increase in complexity of real world problems has provided an area to explore efficient methods to solve computer science problems. Meta-heuristic methods based on evolutionary computations and swarm intelligence are instances of techniques inspired by nature. This paper presents a novel social mimic optimization (SMO) algorithm inspired by mimicking behavior to solve optimization problems. The proposed algorithm is evaluated using 23 test functions. Obtained results are compared with 14 known optimization algorithms including Whale optimization algorithm (WOA), Grasshopper optimization algorithm (GOA), Particle Swarm Optimization (PSO), Stochastic fractal search (SFS), Grey Wolf Optimizer (GWO), Optics Inspired Optimization (OIO), League Championship Algorithm (LCA), Wind Driven Optimization (WDO), Harmony search (HS), Firefly Algorithm (FA), Artificial Bee Colony (ABC), Biogeography Based Optimization (BBO), Bat Algorithm (BA), and Teaching Learning Based Optimization (TLBO). Obtained results indicate higher capability of the SMO algorithm in solving high-dimensional decision variables. Furthermore, SMO is used to solve two classic engineering design problems. Three important features of SMO are simple implementation, solving optimization problems with minimum population size and not requiring control parameters. Results of various evaluations show superiority of the proposed method in finding the optimal solution with minimum function evaluations. This superiority is achieved based on reducing number of initial population. The proposed method can be applied to applications like automatic evolution of robotics, automatic control of machines and innovation of machines in finding better solutions with less cost. [ABSTRACT FROM AUTHOR]