Issues In Computer Science Research Articles

Deep forest auto-Encoder for resource-Centric attributes graph embedding

Graph embedding is an important technique used for representing graph structure data that preserves intrinsic features in a low-dimensional space suitable for graph-based applications. Graphs containing node attributes and weighted links are commonly employed to model various real-world problems and issues in computer science. In recent years, a hot research topic has been the exploitation of diverse information, including node attributes and topological semantic information, in graph embedding. However, due to limitations in deep learning based on neural networks, such information has not been fully utilized nor adequately integrated in existing models, leaving graph embedding unsatisfactory, especially for large resource graphs (e.g., knowledge graphs and task interaction graphs). In this study, we introduce a resource-centric graph embedding approach based on deep random forests learning, which reconstructs graphs using a deep autoencoder to achieve high effectiveness. To accomplish this, our approach employs three key components. The first component is a preprocessor driven by graph similarity, alongside modularity and self-attention modules, to comprehensively integrate graph representation. The second component utilizes local graph information structures to enhance the raw graph. Finally, we integrate diverse information using multi-grained scanning and dual-level cascade forests in the deep learning extractor and generator, ultimately producing the final graph embedding. Experimental results on seven real-world scenarios show that our approach outperforms state-of-the-art embedding methods.

Generating Random SAT Instances: Multiple Solutions could be Predefined and Deeply Hidden

The generation of SAT instances is an important issue in computer science, and it is useful for researchers to verify the effectiveness of SAT solvers. Addressing this issue could inspire researchers to propose new search strategies. SAT problems exist in various real-world applications, some of which have more than one solution. However, although several algorithms for generating random SAT instances have been proposed, few can be used to generate hard instances that have multiple predefined solutions. In this paper, we propose the KHidden-M algorithm to generate SAT instances with multiple predefined solutions that could be hard to solve by the local search strategy when the number of predefined solutions is small enough and the Hamming distance between them is not less than half of the solution length. Specifically, first, we generate an SAT instance that is satisfied by all of the predefined solutions. Next, if the generated SAT instance does not satisfy the hardness condition, then a strategy will be conducted to adjust clauses through multiple iterations to improve the hardness of the whole instance. We propose three strategies to generate the SAT instance in the first part. The first strategy is called the random strategy, which randomly generates clauses that are satisfied by all of the predefined solutions. The other two strategies are called the estimating strategy and greedy strategy, and using them, we attempt to generate an instance that directly satisfies or is closer to the hardness condition for the local search strategy. We employ two SAT solvers (i.e., WalkSAT and Kissat) to investigate the hardness of the SAT instances generated by our algorithm in the experiments. The experimental results show the effectiveness of the random, estimating and greedy strategies. Compared to the state-of-the-art algorithm for generating SAT instances with predefined solutions, namely, M-hidden, our algorithm could be more effective in generating hard SAT instances.

Language cognition and language computation — human and machine language understanding

Language understanding is the key scientific issue in cognitive science and computer science. However, the two disciplines are quite different in selecting specific research questions. Research in cognitive science focuses on analyzing the working mechanism of the brain and describing its response to language, while only a few research studies investigate the brain's language system as a whole. In contrast, computer scientists focus on the efficiency of practical applications when choosing research questions and often ignore essential laws of language. Thus, the research question becomes: “Can we combine these two disciplines to develop new insights into building intelligent language models and studying cognitive mechanisms?" This paper first reviews the research question, history, and methods of language understanding in cognitive science and computer science, focusing on the current research status and challenges. Then, it compares the commonalities and differences in language understanding between the two fields. Finally, it analyzes the existing work that combines the insights from language cognition and computation and prospects the future development trend.

Architecture Design and Code Implementation of Road Network Path Search System

Path search is a hot issue in computer science and artificial intelligence science. When the user enters the starting point and ending point to be queried in the road network path search system, the system will return the best path to the user. In this paper, the road network path search system that can run and calculate the optimal navigation path to the test data is developed by designing the software architecture through the comprehensive use of database design, programming language, shortest path algorithm, UML diagram, software development model, GIS system source data, and other methods. Based on the software design principles of scalability, flexibility, and pluggability, the design and code in this paper can be practically applied to various systems such as GIS, GPS, logistics robots, unmanned aerial vehicles, and autonomous vehicles to realize their road network path planning and navigation functions.

Streaming code across audiences and performers: An analysis of computer science communities of inquiry on Twitch.tv

AbstractLive streaming platforms like Twitch.tv count millions of viewers and performers, pointing to novel practices and interactions. Instructional applications of this phenomenon are rising with thematic channels and shows aimed at teaching and debating a variety of subjects ranging from art to programming. However, few research publications have specifically explored trends in pedagogical strategies and learning behaviours of viewing audiences. This study responded to this need by analysing computer science shows on Twitch.tv. A total of 40 hours of live streaming were analysed within a Community of Inquiry framework using the concepts of social affordances, computational thinking, and teaching style. Data collected from both expert and novice streamers included streamers' actions, on‐screen activity, and online discussions. Results pointed to specific tactics employed by both performers and viewers for exploring computer science issues and dynamics together, with instances of peer‐tutoring, construed learning, and significant transparency, even when top‐down instruction was staged. Practitioners notesWhat is already known about this topic Live streaming is a popular media practice all around the world, with Twitch.tv as the leading hosting platform. A rising number of live streaming shows are focusing on education and learning topics, from STEM to art. What this paper adds A first exploration of instructional streaming focused on computer science education. An analysis of best practices in instructional streaming in terms of community building, teaching style, and computational thinking processes. A better understanding of how communities of inquiry can be hosted on Twitch.tv. Implications for practice and/or policy Practitioners can harness this study's results for informing better educational streaming. Educators may refer to this article's highlights for selecting and evaluating educational streaming shows. Policy makers will be able to use this article's insights for monitoring and re‐applying effective computer science activities in other educational environments.

PROBLEMS OF TEACHING ELEMENTS OF DISCRETE MATHEMATICS TO FUTURE COMPUTER SCIENCE TEACHERS

The article deals with the problem of integrated teaching of discrete mathematics elements to the content of the main specialized disciplines in the preparation of future computer science teachers. The ways of solving some problems in the preparation of future computer science teachers on the elements of discrete mathematics and the need for its training are described. The analysis of scientific research of domestic and foreign scientists involved in the issues of teaching computer science in discrete mathematics is carried out. As a result of the research, the necessity of teaching computer science teachers the elements of discrete mathematics is scientifically substantiated. When considering the content of professional disciplines, the necessity of teaching elements of discrete mathematics is revealed, the rationale for including topics in the content of teaching by sections is given. The list of topics that can be considered in the content of specialized disciplines of discrete mathematics elements is described schematically. These topics are presented as an example of the content of specific disciplines and recommendations are given that it is necessary to specifically study the above, develop and present a teaching methodology.

A Hybrid Systematic Review Approach on Complexity Issues in Data-Driven Fuzzy Inference Systems Development

The data-driven approach is popular to automate learning of fuzzy rules and tuning membership function parameters in fuzzy inference systems (FIS) development. However, researchers highlight different challenges and issues of this FIS development because of its complexity. This paper evaluates the current state of the art of FIS development complexity issues in Computer Science, Software Engineering and Information Systems, specifically: 1) What complexity issues exist in the context of developing FIS? 2) Is it possible to systematize existing solutions of identified complexity issues? We have conducted a hybrid systematic literature review combined with a systematic mapping study that includes keyword map to address these questions. This review has identified the main FIS development complexity issues that practitioners should consider when developing FIS. The paper also proposes a framework of complexity issues and their possible solutions in FIS development.

Integration of Brain Based Learning and Intelligent Tutoring System for Developing Pedagogical Software.(Dept.E)

The development of intelligent tutoring systems and learning environments has become an important issue in both computer science and education. This paper presents pedagogical software for a secondary school biology course. The proposed system integrates the concepts of Brain Based Learning (BBL) and intelligent tutoring system to adapt the learning interface according to the student thinking style. The system is formalized as finite automata with some attributes that allow lemur interaction (image, video, text, color, sound and contents) and some user's brain characteristics (right, left, and integrated thinking style). For the same contents and strategy the information of the learner thinking style enables the system to adapt a specific learning environment. The initial student model is formed through personal data and thinking style. The thinking style is obtained by a diagnostic activity, based on brain assessment test offered to the students. The system enables an adaptation in the output learning environment where the resulting user interface is highly personalized and dynamical.

Controversies in artificial intelligence.

To review four recent controversial topics arising from deep learning applications in ophthalmology. The controversies of four recent topics surrounding deep learning applications in ophthalmology are discussed, including the following: lack of explainability, limited generalizability, potential biases and protection of patient confidentiality in large-scale data transfer. These controversial issues spanning the domains of clinical medicine, public health, computer science, ethics and legal issues, are complex and likely will benefit from an interdisciplinary approach if artificial intelligence in ophthalmology is to succeed over the next decade.

“Bibliosphere” Journal over Fifteen-Year Period: Analytical Review of Methodological and General Theoretical Articles

In 2005, the State Public Scientific Technological Library of the Siberian Branch of the Russian Academy of Sciences established the “Bibliosphere” Journal, well known in our sector multidisciplinary periodical on library science, bibliography, computer science, book studies and related cultural issues. It formed the synthetic heading covering issues common to the entire bibliosphere, and the word “Bibliosphere” has become a professional term with its own definition. The Journal constantly maintains the columns on library science, bibliology, bibliography science and others.The article presents the review of the publications of synthetic nature that have methodological and general theoretical significance for the complex of the related disciplines that form bibliosphere: library science, bibliography science, bibliology, book culture and computer science. Maintaining the column “Methodology of Scientific Research Works” is specific particular to “Bibliosphere” Journal and refers to its undoubted success. From the very first issues, the Journal crossed the planned regional scale and declared itself as a serious periodical of theoretical and methodological level.

Performance Analysis of Search Algorithms on Workstation system

Searching is a common issue in computer science. It is defined as a process in which elements are to be found from a given list. Search algorithms used in daily life for finding values in array or list, data retrieving, finding passwords and combinations, etc.In the past, many search algorithms have been introduced and existing ones have been improved keeping a view of performance in terms of time and space complexity.Search algorithms are defined based on their framework. Well-known types of search algorithms are binary, linear, jump, and interpolation search.Binary search (interval, logarithmic search) is defined as a search algorithm, which finds the position of an element or target value within a sorted array;linearsearch (sequential search) is a search over the list of items in a sequential way (step-by-step process). Jump search focuses on fewer elements by jumping (skipping) to the next elements in fixed steps while Interpolation search is an improvement over binary search may go to different locations according to the value of the key being searched.In this paper, we have performed a comparative analysis of these search algorithms on the workstation system. Lenovo S-20 workstation with windows as an operating system is used forexperimentation and analysis. Finding out which search algorithm is best in an associated scenario with a comparison of a single-core processor to a workstation of a six-core processor.

The Effect of Homophily on Disparate Visibility of Minorities in People Recommender Systems

Evaluating (and mitigating) the potential negative effects of algorithms has become a central issue in computer science. While research on algorithmic bias in ranking systems has dealt with disparate exposure of products or individuals, less attention has been devoted to the analysis of the disparate exposure of subgroups of online users.In this paper, we investigate the visibility of minorities in people recommender systems in social networks. Specifically, we consider a bi-populated social network, i.e., a graph where the nodes belong to two different groups (majority and minority) and, by applying state-of-the-art people recommenders, we analyze how disparate visibility can be amplified or mitigated by different levels of homophily within each subgroup.We start our analysis on real-world social graphs, where the two subgroups are defined by sensitive demographic attributes such as gender or age. Our findings suggest that the way and the extent to which people recommenders can produce disparate visibility on the two subgroups, might depend in large part on the level of homophily within the subgroups. % To verify these findings, we move our analysis to synthetic datasets, where we can control characteristics of the input social graph, such as the size of the minority and the level of homophily. Our results show that homophily plays a key role in promoting or reducing visibility for different subgroups under various combinations of dataset characteristics and recommendation algorithms.

What Graph Properties Are Constant-Time Testable?

In this paper, we survey what graph properties have been found to be constant-time testable at present. How to handle big data is a very important issue in computer science. Developing efficient algorithms for problems on big data is an urgent task. For this purpose, constant-time algorithms are powerful tools, since they run by reading only a constant-sized part of each input. In other words, the running time is invariant regardless of the size of the input. The idea of constant-time algorithms appeared in the 1990s and spread quickly especially in this century. Research on graph algorithms is one of the best studied areas in theoretical computer science. When we study constant-time algorithms on graphs, we have three models that differ in the way that the graphs are represented: the dense-graph model, the bounded-degree model, and the general model. The first one is used to treat properties on dense graphs, and the other two are used to treat properties on sparse graphs. In this paper, we survey one by one what properties have been found to be constant-time testable in each of the three models.

Virtual Display System of Geological Body Based on Key Algorithms of Three-dimensional Modelling

In order to study the virtual display system of geological body, the key algorithm of three-dimensional modelling is used to analyze it, and the virtual display scheme of geological body is realized. Three-dimensional modelling of geological bodies is a frontier field of current geoscience research, and also a hot issue in computer science. Its research can complement and improve the theoretical basis of virtual reality technology and expand its application fields. Geological body three-dimensional modelling software can meet the needs of geoscientists to study geological problems more effectively from three-dimensional space, and has considerable practical value. In the network environment, users' information needs are diversified and individualized, and special attention is paid to the breadth, novelty and timeliness of information. Faced with massive information resources, the information users need is a drop in the ocean in the huge and disorderly network information space. Users need to spend a lot of time and energy to find valuable information in all kinds of uniform systems. Traditional system information services can no longer help users effectively get rid of information overload and information lost. Therefore, the concept of personalized service system has become a hot spot of people' s attention as soon as it is put forward. In recent years, personalized systems have emerged in endlessly. In the early stage of formulation and implementation of personalized service strategy, the existing personalized service generally lacks the attention to context information such as user' s environment. There are weak links in personalization and intellectualization of service, which damages user experience. Therefore, Shepard algorithm and Kriging algorithm of three-dimensional modelling are used to study the virtual display system of geological bodies. The results show that these two key algorithms play a very important role in the research process of geological virtual display system, and also provide a new idea for further research on the popularization of geological knowledge.

Effective protection of information systems and networks against attacks in the era of globalization

The problem of ensuring the security of networks and computer systems of transnational companies is one of the most important issues of modern computer science. In scientific centers around the world, numerous studies are carried out to ensure the security of operating systems and application programs. The aim of the work is to provide theoretical and practical knowledge related to threats, security methods and the latest trends in effective protection of networks and information systems against attacks.

A REVIEW - CAPTCHA AS GRAPHICAL PASSWORDS—A NEW SECURITY PRIMITIVE BASED ON HARD AI PROBLEMS

Most of the safety primeval square measure supported mathematical issues. This analysis goals to check existing parole and to style a brand new improved graphical parole pattern. Captcha as a graphical parole. during this paper, we tend to discuss a brand new security primeval supported exhausting computer science issues, a innovative of graphical parole systems created on dominant of Captcha technology, what we are saying Captcha as graphical passwords (CaRP). CaRP is each a Captcha and a graphical parole pattern. With the mix of CAPTCHA and graphical parole addresses a like on-line estimation attacks, relay attacks, combination of with dual-view technology, and shoulder-surfing attacks. If the parole is in search nominative then CaRP parole are often found solely risk by automatic on-line estimation attack.

Optimizing Sorting Algorithms Using Ubiquitous Multi-core Massively Parallel GPGPU Processors

While developing naive code is uncomplicated, optimizing extremely parallel algorithms requires deep understanding of the core architecture. Recent years have witnessed a phenomenal growth in the computational capabilities and applications of GPUs. High performance of modern Graphics Processing Units may be used not only for graphics related application but also for general computing. Out of the vast applications which require parallel computing, some broadly classified are real-world applications like scientific computing, numerical simulations, healthcare, energy, data-analysis, etc. All of these applications involve wide data-intensive tasks, often subject to time constraints and space complexity. One of the fundamental issues in computer science is ordering a list of items. Bitonic sort is one of the most basic computing problems which also play a very important role in plenty of algorithms commonly used in graphics applications, such as visibility ordering or collision detection. This paper makes use of the parallel property of GPU and accelerates the function of bitonic sort which in itself is designed explicitly for parallel networks.

Enhanced Merge Sort- A New Approach to the Merging Process

One of the major fundamental issues of Computer Science is arrangement of elements in the database. The efficiency of the sorting algorithms is to optimize the importance of other sorting algorithms11. The optimality of these sorting algorithms is judged while calculating their time and space complexities12. The idea behind this paper is to modify the conventional Merge Sort Algorithm and to present a new method with reduced execution time. The newly proposed algorithm is faster than the conventional Merge Sort algorithm having a time complexity of O(n log2 n). The proposed algorithm has been tested, implemented, compared and the experimental results are promising.

A New Asymptotic Notation: Weak Theta

Algorithms represent one of the fundamental issues in computer science, while asymptotic notations are widely accepted as the main tool for estimating the complexity of algorithms. Over the years a certain number of asymptotic notations have been proposed. Each of these notations is based on the comparison of various complexity functions with a given complexity function. In this paper, we define a new asymptotic notation, called “Weak Theta,” that uses the comparison of various complexity functions with two given complexity functions. Weak Theta notation is especially useful in characterizing complexity functions whose behaviour is hard to be approximated using a single complexity function. In addition, in order to highlight the main particularities of Weak Theta, we propose and prove several theoretical results: properties of Weak Theta, criteria for comparing two complexity functions, and properties of a new set of complexity functions (also defined in the paper) based on Weak Theta. Furthermore, to illustrate the usefulness of our notation, we discuss an application of Weak Theta in artificial intelligence.

Editorial

Hamid Mcheick is currently an associate professor in computer science department at the University of Quebec At Chicoutimi (UQAC), Quebec, Canada. He holds a PhD degree in software engineering and distributed system from Montreal University, Canada. He holds a master degree from the University of Quebec at Montreal, Canada in information retrieval system. Professor Mcheick is interested in distributed software architecture, mobiles applications and pervasive computing, as well as in separation of concerns (component, services, aspect, etc.). He works also in ubiquitous computing, service composition of business process. He has given many talks in congresses and conferences as a keynote or invited speaker. He is a chief in editor and guest editor of several international journals. His research is supported by many research grants he has received from the Canadian government, University of Montreal, CRIM (Centre de Recherche informatique de Montreal), University of UQAM, and University of Quebec At Chicoutimi, Canada. The missions of Bentham Journal volume aim to bring, for both academics as well as for industrial practitioners, a set of articles discussing and answering the recent patents on core topics of software computing and intelligence and improving the state-of-the-art of worldwide research in the areas of computer science issues by publishing high-quality articles in this area, and by exposing the readers to various methodologies, tools, technologies, algorithms, results, and types of articles. It is our pleasure to highlight in June 2014, the 7th volume of the Journal Recent Patents on Computer Science (CSENG) that includes a selected and reviewed research papers. This issue includes papers of Software Defined Networks for Data Center Optimization, Intelligent techniques and systems in credit risk analysis and forecasting, Cultivating Software Solutions Development in the Scientific Academia, Information Security and Threats in Mobile Appliances, Hybrid Swarm Intelligence and Artificial Neural Network for Mitigating Malware Effects, An Experimental Investigation of MLPNN and GRNN Classification Methods for Evaluation of Different sEMG-Extracted Features, Review on Patents in Mobile Augmented Reality, and Exploring various information in DVC side information generation. A challenge to leap forward for the contributing Authors of this issue was to present the critical underlying of many research topics, such as possibility of optimizing data management, various software developmental models, credit risk domain, information security in mobile devices, and many others. Acting as the Editor-in-Chief of Recent Patents on Computer Science issue, I wish to express our gratitude to the Authors, my particular thanks to Bentham Science for their on-going commitment to the highest quality science, to Elma Tabita Bashir and Sumaiya Azhar, Publication Managers, and the entire Bentham Editorial Staff that have done an exceptional job in insuring the highest standards of peer review. I would like to particularly acknowledge the untiring contributions of our distinguished cadre of Editorial Board Members who do the lion’s share of the reviews and are largely responsible for the exceptional quality of the current and past issues. Also, I would appreciate to thank our readers and encourage you to contact me for any suggestions, criticismsand ideas that can help us to all make “Recent Patents on Computer Science” meet the expectations that it is targeted to do.