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The International Journal of Semantic Computing has published a special issue on Semantic Computing, which includes five selected papers from the 17th IEEE International Conference on Semantic Computing. Semantic Computing focuses on the derivation, description, integration, and use of semantics for various resources. The papers in the special issue cover topics such as intent detection, constructing probabilistic models from knowledge graphs, unsupervised estimation of subjective content descriptions, the influence of noisy labels on question answering systems, and automatic domain-adaptive sentiment analysis. Each paper presents innovative approaches and findings in their respective areas of research. [Extracted from the article]

Presents the special issue in the journal "Parallel Processing Letters," which contains the best papers from the Centre Interantional de Rencontres Mathématiques workshopin October 2001. "Scheduling Issues in Survivality Applications Using Hybrid Fault Models," by A. W. Krings, W. S. Harrison, A. Azadmanesh and M. McQueen"; "Parallel Tabu Search Approaches for Two-Dimensional Cutting," by J. Blazewicz, A. Moret-Salvador and R. Walkowiak"; "Strategies for Workload Balancing in Cluster-Based Image Databases," by F. Drews, K. Ecker, O. Kao and S. Schomann.

Currently, there are many research studies that apply and improve mutation testing techniques including traditional mutation testing or first-order mutation testing, and higher-order mutation testing (HOMT) for evaluating the quality of the set of test data in particular, and the quality of test suites in general. The results of those studies have proven the effectiveness of mutation testing in the field of software testing. Mutation testing allows the quality of test cases to be automatically evaluated, thereby helping the testers to improve the quality in the design and execution of the software testing. Besides, these studies have also pointed out the main barriers in applying mutation testing techniques in practice. However, we are the first to introduce a method that can reduce the cost, but keep the quality of testing activity based on evaluating the quality of the mutation operator as well as the quality of the test cases. In this paper, we concentrate on two problems regarding higher-order mutation testing: Evaluating the quality of mutation operators as well as generated mutants and prioritizing test cases based upon its capability of killing mutants. This may help developers allocate suitably their resources during testing phase. The study of this paper is an extended version of our previous study titled "Evaluating Mutation Operator and Test Case Effectiveness by Means of Mutation Testing", which is published in the proceedings of the 13th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2021 (V. N. Do, Q. V. Nguyen and T. B. Nguyen, Evaluating Mutation Operator and Test Case Effectiveness by Means of Mutation Testing, in Intelligent Information and Database Systems. ACIIDS 2021, eds. N. T. Nguyen, S. Chittayasothorn, D. Niyato and B. Trawiński. Lecture Notes in Computer Science, Vol. 12672 (Springer, Cham), https://doi.org/10.1007/978-3-030-73280-6%5f66) to confirm the usefulness of our proposed method. [ABSTRACT FROM AUTHOR]

Automated generation of image captions is a demanding AI crisis as it necessitates the exploitation of numerous methods from diverse computer science fields. Deep learning (DL) approaches have revealed marvelous results in a lot of diverse appliances. On the other hand, data augmentation in DL that imitates the quantity and the variety of training data without the need of gathering additional data is a hopeful area in machine learning (ML). Producing textual descriptions for a specified image is a demanding task using the computer. This survey makes a critical analysis of about 65 papers regarding image captioning. More particularly, varied performance measures that are contributed in diverse articles are analyzed. In addition, a comprehensive study is made regarding the maximal performances and varied features deployed in each work. Moreover, chronological analysis and dataset analysis are done and finally, the survey extends with the determination of varied research challenges, which might be productive for the analysts to endorse enhanced upcoming works on image captioning. [ABSTRACT FROM AUTHOR]

Since the International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems published its first issue in 1993, it has made important contributions to the research field of computer science. In this study, based on the dataset of the publications published in this journal between 1993 and 2016 retrieved from Web of Science, a general overview of this journal is performed using bibliometric methods and visualized networks. First, the productive and influential publications, authors, institutions, countries/territories, and supraregions are analysed based on the total number of citations, publications, and different citation thresholds. Second, network visualization analysis is applied to illustrate the links and connections between terms by using the VOSviewer software. Moreover, the most cited journals and common author keywords of three continents, including North America, Europe, and Asia, are also presented. This paper will hopefully help researchers understand the research patterns of this journal. [ABSTRACT FROM AUTHOR]

ChatGPT, a recently developed product by openAI, is successfully leaving its mark as a multi-purpose natural language based chatbot. In this paper, we are more interested in analyzing its potential in the field of computational biology. A major share of work done by computational biologists these days involve coding up bioinformatics algorithms, analyzing data, creating pipelining scripts and even machine learning modeling and feature extraction. This paper focuses on the potential influence (both positive and negative) of ChatGPT in the mentioned aspects with illustrative examples from different perspectives. Compared to other fields of computer science, computational biology has (1) less coding resources, (2) more sensitivity and bias issues (deals with medical data), and (3) more necessity of coding assistance (people from diverse background come to this field). Keeping such issues in mind, we cover use cases such as code writing, reviewing, debugging, converting, refactoring, and pipelining using ChatGPT from the perspective of computational biologists in this paper. [ABSTRACT FROM AUTHOR]

No abstract received. [ABSTRACT FROM AUTHOR]

The article presents an introduction to the contents in the issue of the journal, "International Journal of Information Technology and Decision Making," Volume 5, No. 1 (2006). The issue has ten papers, in which four of them have theoretical topics. The rest of the papers cover the various applications in the areas of information technology and decision making. There are 22 authors and co-authors who contributed in the issue. Some of them are from China, Greece, and Italy.

In general, models of universe problems in almost all fields, such as engineering, mathematics, medical sciences, computer science, physics, management sciences, artificial intelligence, and operations research, are practically full of complexities and include various types of uncertainties when dealing with them on numerous occasions. Different theories, such as probability, rough sets, fuzzy sets, soft ideals, and so on, have been created to deal with these uncertainties. An algebraic structure, AG-groupoid, is an intermediate structure between two types of structures: commutative semigroup and groupoid. This structure has a very close relationship to a commutative semigroup since a commutative AG-groupoid is always a semigroup. These structures have so many applications in flocks theory, geometry, topology, and many more. We explore several structural properties of an AG-groupoid by using hybrid structures in this paper. The main motivation behind this paper is to present the concepts of hybrid ideals, hybrid bi-ideals and hybrid interior ideals of an AG-groupoid and characterize AG-groupoid in terms of hybrid structures. Also, we show that the hybrid intersection and hybrid product structures will coincide under certain conditions. [ABSTRACT FROM AUTHOR]

No abstract received. [ABSTRACT FROM AUTHOR]

A calendar of events related to computer science to be held between September 2009 and December 2010 is presented, which includes the 18th International Symposium on Methodologies for Intelligent Systems, the 19th International Conference on Artificial Neural Network, and the International Conference on Intelligent Computing.

Please send your abstracts (or copies of papers that you want to see reviewed here) to vladik@utep.edu, or by regular mail to Vladik Kreinovich, Department of Computer Science, University of Texas at El Paso, El Paso, TX 79968, USA... [ABSTRACT FROM AUTHOR]

The article presents an introductory statement to the special issue of the "Parallel Processing Letters." The most recent important advances in the aspects of hardware⁄software support for high performance computing is featured. The editor believe that all of these papers and topics will not only provide novel ideas, new results, work in progress and state-of-the-art techniques in the area, but also stimulate the future research activities in the area of high performance computing with applications.

Introduces several articles about theoretical problems and applications in information technology and decision making, published in the September 1, 2004 issue of "International Journal of Information Technology and Decision Making." Citation of an article on the differences in the habitual domains of technologists in high technology industries; Introduction of a paper on Memex-like application using a self-modifiable Petri-Net model; Presentation of papers on decision-making models.

Introduces articles to the second issue of volume 3 of the "International Journal of Information Technology and Decision Making." Proposal for a flexible negotiation framework based on social constraints and conversation plans; Study on similarity and similarity reasoning based on extension models of the science called Extenics; Presence of multicollinearity both for regression and discriminant functions.

The purpose of the multi-dimensional uniformity test is to check whether the underlying probability distribution, from which a random sample is drawn, differs from the multi-dimensional uniform distribution. The multi-dimensional uniformity test has applications in various fields such as biology, astronomy and computer science. Various statistical tests have been proposed for the multivariate uniformity. As a special case, the bivariate statistic test is discussed in this paper. To evaluate the performance of the uniformity tests, power comparison is the technique for selecting appropriate statistical test. The Monte Carlo simulations usually used to compare the power of the tests. Berrendero, Cuevas and Vazquez-Grande proposed a distance-to-boundary test, which was one of the latest published statistical tests for multi-dimensional uniformity [J. R. Berrendero, A. Cuevas and F. Vazquez-Grande, Testing multivariate uniformity: The distance-to-boundary method, Canad. J. Stat.34 (2006) 693–707]. Chen and Hu proposed another test for multivariate uniformity [Z. Chen and T. Hu, Statistical test for bivariate uniformity, Adv. Stat.2014 (2014) 740831]. Power comparison was conducted to compare these tests. In order to get more convincing power comparison results, more alternative distributions should be used when power study is conducted. This paper proposes a new bivariate distribution, named the pyramidal distribution, with support set [ 0 , 1 ] × [ 0 , 1 ]. This distribution is quite flexible so that it can be used to produce different shapes of bivariate distributions. Because of that, the proposed distribution can be used as an alternative distribution in power comparison for bivariate uniformity test. [ABSTRACT FROM AUTHOR]

Presents an introduction to several articles published in the June 2005 issue of the "International Journal of Foundations of Computer Science."

Deoxyribonucleic Acid (DNA) coding technology is a new research field developed by the combination of computer science and molecular biology, that has been gradually applied in the field of image encryption in recent years. Furthermore, sensitivity to initial conditions, pseudo-random properties, and state ergodicity of coupled chaotic maps can help produce good pseudo-random number generators and meet the requirements of an image encryption system well. In this paper, an image encryption algorithm based on high-dimensional coupled chaotic maps and DNA coding is proposed. A pseudo-random sequence is generated by a long short-term memory (LSTM) architecture using the proposed maps and evaluated through a set of statistical tests to show the high performance of the proposed generator. All intensity values of an input image are converted to a binary sequence, which is scrambled globally by the high-dimensional coupled chaotic maps. The DNA operations are performed on the scrambled binary sequences instead of binary operations to increase the algorithm efficiency. Simulation results and performance analyses demonstrate that the proposed encryption scheme is extremely sensitive to small changes in secret keys, provides high security and can resist differential attack. [ABSTRACT FROM AUTHOR]

This paper investigates the formation control and obstacle avoidance problem for multi-agent systems (MASs), which aims to coordinate the pursuer agents to capture a mobile target. The target appears at a location randomly and its movement obeys Reactive Rabbit Model. The pursuers and the mobile target can be modeled as a Pursuit-Evasion Game (PEG). During the movement, not all of the pursuer agents can obtain the real-time information of the target. Moreover, the obstacle avoidance makes the formation of pursuer agents a big challenge to encircle the mobile target. In order to tackle these two problems, the formation control and obstacle avoidance algorithm is presented in this paper based on a novel virtual leader-follower strategy and potential functions. The obstacle avoidance problem can then be solved by constructing a velocity potential. The numerical analysis and simulation demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Low-rank matrix completion, which aims to recover a matrix with many missing values, has attracted much attention in many fields of computer science. A low-rank matrix fitting (LMaFit) method has been proposed for fast matrix completion recently. However, this method cannot converge accurately on matrices of real-world images. For improving the accuracy of LMaFit method, an improved low-rank matrix fitting (ILMF) method based on the weighted L 1 , p norm minimization is proposed in this paper, where the L 1 , p norm is the summation of the p -power (0 < p < 2) of L 1 norms of rows in a matrix. In the proposed method, i.e. the ILMF method, the incomplete matrix that may be corrupted by noises is decomposed into the summation of a low-rank matrix and a noise matrix at first. Then, a weighted L 1 , p norm minimization problem is solved by using an alternating direction method for improving the accuracy of matrix completion. Experimental results on real-world images show that the ILMF method has much better performances in terms of both the convergence accuracy and convergence speed than the compared methods. [ABSTRACT FROM AUTHOR]

No abstract received. [ABSTRACT FROM AUTHOR]

Large-scale benchmark datasets are crucial in advancing research within the computer science communities. They enable the development of more sophisticated AI models and serve as "golden" benchmarks for evaluating their performance. Thus, ensuring the quality of these datasets is of utmost importance for academic research and the progress of AI systems. For the emerging vision-language tasks, some datasets have been created and frequently used, such as Flickr30k, COCO, and NoCaps, which typically contain a large number of images paired with their ground-truth textual descriptions. In this paper, an automatic method is proposed to assess the quality of large-scale benchmark datasets designed for vision-language tasks. In particular, a new cross-modal matching model is developed, which is capable of automatically scoring the textual descriptions of visual images. Subsequently, this model is employed to evaluate the quality of vision-language datasets by automatically assigning a score to each 'ground-truth' description for every image picture. With a good agreement between manual and automated scoring results on the datasets, our findings reveal significant disparities in the quality of the ground-truth descriptions included in the benchmark datasets. Even more surprising, it is evident that a small portion of the descriptions are unsuitable for serving as reliable ground-truth references. These discoveries emphasize the need for careful utilization of these publicly accessible benchmark databases. [ABSTRACT FROM AUTHOR]

A graph structure is a useful tool in solving the combinatorial problems in different areas of computer science and computational intelligence systems. In this paper, we introduce the concept of cubic soft graph, complete cubic soft graph, (internal, external) cubic soft graphs and investigate some of their properties. Then we deal with fundamental operations, union, intersection, Cartesian product, composition of cubic soft graphs and illustrate these notions by several examples. We prove that cubic soft graphs under these operations are also a cubic soft graph. Finally, we describe an application of cubic soft graphs in decision making. [ABSTRACT FROM AUTHOR]

The amount of information available on the Web has grown considerably in recent years, leading to the need to structure it in order to access it in a quick and accurate way. In order to develop techniques to automate the structuring process, the Knowledge Base Population (KBP) track of the Text Analysis Conference (TAC) was created. This forum aims to encourage research in automated systems capable of capturing knowledge in unstructured information. One of the tasks proposed in the context of the KBP track is named entity linking, and its goal is to link named entities mentioned in a document to instances in a reference knowledge base built from Wikipedia. This paper focuses on the entity linking task in the context of KBP 2010, where two different varieties of this task were considered, depending on whether the use of the text from Wikipedia was allowed or not. Specifically, the paper proposes a set of modifications to a system that participated in KBP 2010, named WikiIdRank, in order to improve its performance. The different modifications were evaluated in the official KBP 2010 corpus, showing that the best combination increases the accuracy of the initial system in a 7.04%. Though the resultant system, named WikiIdRank++, is unsupervised and does not take advantage of Wikipedia text, a comparison with other approaches in KBP indicates that the system would rank as 4th (out of 16) in the global comparison, outperforming other approaches that use human supervision and take advantage of Wikipedia textual contents. Furthermore, the system would rank as 1st in the category of systems that do not use Wikipedia text. [ABSTRACT FROM AUTHOR]

With the untimely passing of Patrick Dehornoy in September 2019, the world of mathematics lost a brilliant scholar who made profound contributions to set theory, algebra, topology, and even computer science and cryptography. And I lost a dear friend and a strong influence in the direction of my own research in mathematics. In this paper, I will concentrate on his remarkable discovery that the braid groups are left-orderable, and its consequences, and its strong influence on my own research. I'll begin by describing how I learned of his work. [ABSTRACT FROM AUTHOR]

No abstract received. [ABSTRACT FROM AUTHOR]

Given several number sequences, determining the longest common subsequence is a classical problem in computer science. This problem has applications in bioinformatics, especially determining transposable genes. Nevertheless, related works only consider how to find one longest common subsequence. In this paper, we consider how to determine the uniqueness of the longest common subsequence. If there are multiple longest common subsequences, we also determine which number appears in all/some/none of the longest common subsequences. We focus on four scenarios: (1) linear sequences without duplicated numbers; (2) circular sequences without duplicated numbers; (3) linear sequences with duplicated numbers; (4) circular sequences with duplicated numbers. We develop corresponding algorithms and apply them to gene sequencing data. [ABSTRACT FROM AUTHOR]

The maximum matching problem is of great interest in many areas, for example, statistical physics and theoretical computer science. However, precise determining of maximum matchings in general graphs is a challenge and calculationally intractable. In this paper, we study analytically maximum matching problem in the pseudofractal scale-free web. We derive exact expressions for size and number of maximum matchings of the network based on self-similar structure and iterative construction of network, and obtain asymptotic incremental constant for the number of maximum matchings. The obtained results are helpful to understand the structural characteristics of scale-free networks with pseudofractality. [ABSTRACT FROM AUTHOR]

We are fully aware that an ordered semigroup has a very close relation with theoretical computer science, especially with the theory of pattern recognition, decision processes, artificial intelligence, information retrieval and so on. We are eager to introduce the new concepts of hybrid interior ideals and hybrid simple in an ordered semigroup in this paper. We discuss characteristic hybrid structures using ideals and interior ideals, and characterize ordered semigroup in terms of different hybrid ideal structures. Further, we establish the equivalent condition for an ordered semigroup to be simple. [ABSTRACT FROM AUTHOR]

The object deployment of a distributed software has a great impact on its performance. In this paper an analytical model for performance evaluation of different object deployments, is presented. The key advantage of the proposed model over the traditional Queuing Network models is the usefulness in the deployment optimization when the search space is huge and automatic instantiation of Queuing performance models corresponding to an object deployment is costly. Since our model produces an optimal deployment corresponding to each input load separately, the runtime behavior of the software corresponding to each input load should be profiled using simulation first. In this paper a translation scheme for generating the simulate-able Labeled Transition Systems (LTS) from scenarios is also presented. Moreover, two deployment algorithms (a GA-based and an INLP-based) are implemented and the results are compared. [ABSTRACT FROM AUTHOR]

Data stream learning in non-stationary environments and skewed class distributions has been receiving more attention in machine learning communities. This paper proposes a novel ensemble classification method (ECSDS) for classifying data streams with skewed class distributions. In the proposed ensemble method, back-propagation neural network is selected as the base classifier. In order to demonstrate the effectiveness of our proposed method, we choose three baseline methods based on ECSDS and evaluate their overall performance on ten datasets from UCI machine learning repository. Moreover, the performance of incremental learning is also evaluated by these datasets. The experimental results show our proposed method can effectively deal with classification problems on non-stationary data streams with class imbalance. [ABSTRACT FROM AUTHOR]

With the gradual maturity of component oriented software development method, component-based software evolution technology has become hot research in academia and industry. Although many evolution rules are designed, they rarely consider component type-mismatched problem in evolution rules. This has led to evolution rules that often run error in software evolution execution. Hence, focusing on the mismatch problem of component type in software evolution, this paper addresses various evolution rules with condition constrains to support component type matching. First, we use the bigraph theory to model the software architecture and employ bigraph term language to describe the basic component evolution operations. Second, we join type system into the term language and use the type term language to express the condition constraints on position and connection for component evolution rules. These condition constraints can guarantee the type-matched among components that participate in software evolution. Furthermore, we show that the component type-matched still kept during a number of different evolution rules are used in the whole software evolution reaction system. Finally, two cases study of evolution progress of ATM system and tourism information system are presented. Two cases illustrate the effectiveness of our approach. [ABSTRACT FROM AUTHOR]

The paper describes the evolution of the design of a motivational social visualization. The visualization shows the contributions of users to an online community to encourage social comparison and more participation. The newest design overcomes shortcomings in the previous two, by using more attractive appearance of the graphic elements in the visualization, better clustering algorithm and by giving up the largely unused in the previous design user customization options. The visualization integrates more information in one view, and uses an improved user clustering approach for representing graphically their different levels of contribution. A case study of the new design with a group of 32 students taking a class on Ethics and Computer Science is presented. The results show that the visualization had a significant effect on participation with respect to two activities (logging into the community and rating resources). [ABSTRACT FROM AUTHOR]