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关键词： Computer Science   general   Software Engineering/Programming and Operating Systems   Operating Systems   Software Engineering   Artificial Intelligence  

摘要： Sensitive information in organizations is constantly increasing and at the same sense are the risks of attacks that compromise privacy, confidentiality or integrity. The need for automating the tasks for securing data is more evident in big data scenarios. Thus, organizations could maintain tight control over their information using cryptographic techniques, such as document encryption, authentication, and digital signatures. In this paper, we present a case study in document encryption and authentication in organizational environments domains by means of curve-based cryptography. We propose three constructions for documents encryption and signing for acceptable security levels, on the basis of Identity-Based Encryption and Signcryption approaches, both built from elliptic curves. We provide experimentation details that reveal the feasibility of proposed curve-based cryptographic schemes, useful for automating the provision of security services to digital documents in organizational environments.

关键词： Computer Science   general   Software Engineering/Programming and Operating Systems   Operating Systems   Software Engineering   Artificial Intelligence  

摘要： This paper is devoted to event detection as part of news stream analysis. An event is regarded as a group of news texts dedicated to one real-world fact or situation. We analyze news from Russian news agencies. A two-stage clustering method is proposed, which combines a rough clustering algorithm used at the first stage and a refinement classifier used at the second stage. In addition, we present an open labeled dataset for news event detection, which is based on the Yandex News service. Empirical evaluation of the proposed method on this dataset proves its effectiveness for event detection in news texts.

关键词： Social network large-scale decision-making (SN-LSDM)   Punishment-driven consensus reaching model (PDCRM)   Trust-constrained K-means clustering (TCop-Kmeans) algorithm   Trust loss   Social capital selection  

摘要： Clustering and consensus reaching are two crucial processes for solving social network large-scale decision-making (SN-LSDM) problems. This paper explores the moderating effect of trust on the decision-making process, which is decomposed into examining the influence of trust constraint on clustering and the influence of trust loss on consensus reaching. We hold that low-trust experts are not suitable to be assigned to the same subgroup, even though their preferences are sufficiently similar. We propose a punishment-driven consensus reaching model for SN-LSDM problems. The model contains two main stages. In Stage 1, a trust-constrained K-means clustering algorithm is presented, which can overcome the defect of grouping low-trust experts caused by traditional clustering methods based on preference similarity. Then, a weight-determining method combining the size, cohesion, and overall trust degree of a subgroup is proposed. In Stage 2, a punishment-driven consensus reaching process is designed, which identifies four categories of consensus scenarios (high-high, high-low, low-high, low-low) through consensus measures and trust measures. Different adjustment strategies are established, and the moderating effect of trust loss on consensus reaching and consensus cost is investigated. Finally, both a case study on social capital selection in public-private partnership projects and a comparative analysis are implemented to reveal the feasibility and advantages of the clustering algorithm and consensus reaching model proposed in this paper. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Computer Science   general   Software Engineering/Programming and Operating Systems   Operating Systems   Software Engineering   Artificial Intelligence  

摘要： Thereare few on-line platforms related to Natural Language Processing and zero services of machine translation for Nahuatl as a low-resource language. However, Nahuatl has had academical implementations on machine translation, from Statistical Machine Translation (SMT) to Neural Machine Translation (NMT), in specific Recurrent Neural Networks (RNNs). This research aims to create a platform that can address this issue with text, voice and Text-To-Speech features. In particular, the current paper presents several advancements on text translation as a comparative analysis between two attention architectures, transformers and RNNs using several models that combine such architectures, two parallel corpuses, and two tokenization techniques. Additionally, the development of a platform and iOS application client is described. A new and bigger corpus, over 35,000 pairs, is made to improve the state of the art, where a conscious cleaning of it shows a reduction on the religious bias presented on the source text. The model performance is evaluated with % BLEU in order to conduct a direct comparative on previous Nahuatl machine translation works. The results outperformed those works with a score of 66.45 at best using transformers compared to 34.78 and 14.28 for RNNs and SMT respectively, confirming that transformers and a sub-word tokenization are the best combination so far for Nahuatl Machine translation. Moreover, emerging behaviors were observed in the Transformers, where a subtle pleonasm seen only in rural locations where Mexican Spanish is spoken arouse from the model, linking its origin to Nahuatl, as well as the ability of the model of transforming numbers from base 10 to base 20. Finally, some out of corpus translations were presented to a Nahuatl speaker where the model demonstrated a good performance and retention of information for its size. This research seeks to be used as a framework of how a polysynthetic language can be manipulated to be used for different la

关键词： programming   meeting talk   computer science   indexicality   conversational analysis  

摘要： The formulation of computer algorithms requires the elimination of vagueness. This elimination of vagueness requires exactness in programming, and this exactness can be traced to meeting talk, where it intersects with the indexicality of expressions. This article is concerned with sequences in which a team of computer scientists discuss the functionality of prototypes that are already implemented or possibly to be implemented. The analysis focuses on self-repair because this is a practice where participants can be seen to orient to meanings of different expressions as alternatives. By using self-repair, the computer scientists show a concern with exact descriptions when they talk about existing functionality of their prototypes but not when they talk about potential future functionality. Instead, when participants talk about potential future functionality and attend to meanings during self-repair, they use vague expressions to indicate possibilities. Furthermore, when the computer scientists talk to external stakeholders, they indicate through hedges whenever their descriptions approximate already implemented technical functionality but do not describe it exactly. The article considers whether the code of working prototypes can be said to fix meanings of expressions and how we may account for human agency and non-human resistances during development.

关键词： Computer science   Creative thinking   Mathematics   Relationship between musical competence and exact sciences  

摘要： The study aims to examine the relationship between the formation of creative thinking through learning, music achievement, and exact sciences performance. The data were collected for the academic period of 2017-2018 (N = 1042), 2018-2019 (N = 1006) and 2019-2020 (N = 1271). To identify the link between the creative thinking skills of music students and their progress in exact sciences, an adapted creativity questionnaire was introduced. The correlation coefficients were obtained with the help of a regression analysis performed in SPSS. The study relied on the linear regression analysis and the Fisher z-transformation. T-tests were introduced to study group differences in average academic achievement between students who attended music classes and those who did not have them. The size of the Cohen's d effect was calculated in order to determine the mean differences in standard deviations between the groups. In the adapted creativity questionnaire, the reliability coefficient of creative mathematics tests was 0.78 while creative computer science tests received 0.79. There is a symmetrical relationship between music learning and academic performance in exact sciences. According to the findings, creative thinking skills of music students have a positive correlation with student performance in mathematics (r = 0.435, p = 0.05, p = 0.004) and computer science (r = 0.402, p = 0.05, p = 0.000). The results of a positive relationship between the creative thinking skills of students who previously studied music and their success in mastering exact sciences can be sent to educational administrators to maintain and improve programs.

关键词： Electrical engineering   Testing   Computer science   Systematics   Standards organizations   Software engineering   Software   Electrical engineering (EE)   introduction   process   testing   conclusion (IPTC)   genre analysis   macrostructure   research articles (RAs)  

摘要： Background: More than 30 years ago, Harmon distinguished developmental research articles (RAs), which propose a solution to a problem, from experimental RAs, but the developmental format has received little attention. Literature review: Genre analysis of RAs has been largely restricted to articles following the standard experimental/Introduction, Methods, Results, Discussion (IMRD) format, thereby excluding many developmental engineering articles. Recently, a textbook proposed Introduction, Process, Testing, Conclusion (IPTC) as a prototypical format for electrical engineering RAs, but this format has not yet been demonstrated from a corpus. Research questions: 1. What is the macrostructure of electrical engineering RAs? 2. What are the characteristic features of each division of electrical engineering RAs? Methodology: Section headings, wordcount, and notable features were analyzed for 75 RAs from 15 electrical engineering journals and compared with both IPTC and Harmon's developmental structure. Results: Only one article, a case study, followed IMRD. Sixty-seven developmental RAs followed the IPTC format. These are distinguished by the second division (P), where the new solution is described, written in extended style, comprising several sections with headings specific to the research. A paragraph at the end of the Introduction describing the organization of the paper, the location of the theoretical framework and testing methods, and a ubiquitous Conclusion also differ from IMRD. Seven developmental RAs exhibited a hybrid format with the well-known IMRD section headings superimposed on an IPTC structure. Conclusions: Most electrical engineering articles are developmental and follow IPTC format. This can inform future genre analysis research and has pedagogical implications for teaching engineering writing.

关键词： Computer Science   general   Software Engineering/Programming and Operating Systems   Operating Systems   Software Engineering   Artificial Intelligence  

摘要： The scope of volunteer computing systems is permanently expanding. The Berkeley Open Infrastructure for Network Computing (BOINC) is currently the most popular system for volunteer computing. There are many scientific papers devoted to adaptation of various computational algorithms to BOINC. The topic of this paper is the effective adaptation of the evolutionary algorithm to volunteer computing systems. We consider various causes of performance loss, as well as introduce some criteria and metrics for evaluating the performance of the algorithm. The proposed metrics can be used for comparative analysis of various job scheduling policies in the process of computation. The metrics can be evaluated during both actual and simulated computations.