Search

This document is an editorial summarizing the Applied Geometric Algebras in Computer Science and Engineering (AGACSE) conference held in Brno, Czech Republic in September 2021. The conference aimed to promote the use of geometric algebra in fields such as image processing, robotics, and quantum computing. The conference proceedings were published in the journal Mathematical Methods in the Applied Sciences. The editorial provides a list of accepted papers, covering topics such as applied geometry, technological applications, algebra, and quantum phenomena. One specific paper explores the use of geometric algebra in teaching rotations through neural networks. The document is a compilation of research papers showcasing the applications of geometric algebra in various fields, including robotics, control systems, image processing, cryptography, and physics. Each paper presents a specific problem or application and proposes a unique approach or solution using geometric algebra. The authors compare their methods with existing techniques and provide mathematical analysis to support their claims. Overall, the papers demonstrate the versatility and effectiveness of geometric algebra in different domains. [Extracted from the article]

The development of the computer and what is now known as artificial intelligence (AI) has evolved over more than two centuries in a long series of steps. The date of the invention of the first computer is estimated at 1822, when Charles Babbage (1791-1871) developed his first design of a working computer on paper, based mainly on a Jacquard loom. He worked on his project together with Augusta Ada King, Countess Lovelace (née Byron) (Ada Lovelace) (1815-1852), whom he called the "Sorceress of Numbers." This work will present the profile and achievements of Charles Babbage, Augusta Ada King, Countess Lovelace, and Alan Mathison Turing (1912 - 1954), who is considered the father of computer science and artificial intelligence, and then provide an outline of the tumultuous events affecting AI up to the present. [ABSTRACT FROM AUTHOR]

With the spreading of Industry 4.0, cyber-physical systems, and tools for augmented and virtual reality, Digital Twin (DT) is gaining momentum in several areas of Computer Science and Engineering. This paper presents a systematic literature review that investigates the way DTs are described in Human-Computer Interaction (HCI) scientific literature. The study includes 23 papers selected through a systematic search on the 21 most ranked journals and conferences in the HCI area. As a result of this work, it appears clear that the way humans interact with DTs is a topic still far from being widely studied. A set of hints for future research about the relationship between HCI and DT constitute the main outcome of this paper. [ABSTRACT FROM AUTHOR]

Diversity has become increasingly relevant in computer science and technology development, both in terms of inclusive design teams and as a concept used to design "diversity-aware" technologies. The latter part has received less attention and notions of diversity leveraged to design technologies remain understudied. This paper critically examines diversity concepts employed by computer scientists and designers by reviewing 120 articles in two subfields of computer science: personalized recommendations and human–computer interaction. Drawing on Black feminism and critical race theory-inspired literature, I offer a critique of demographic and cultural user representations and underscore the shortcomings of diversity as a strategy to increase user satisfaction and fairness. Particularly concerning is the unreflected use of binary, static, and individual-level diversity concepts in the design of technologies. Such concepts render structural inequalities between and within groups of users invisible and thereby risk reinforcing existing injustices. The paper closes with considerations on whether and how diversity concepts can be leveraged by designers in a social justice–oriented manner. [ABSTRACT FROM AUTHOR]

The new way of thinking science from Newtonian determinism to nonlinear unpredictability and the dawn of advanced computer science and technology can be summarized in the words of the theoretical physicist Michel Baranger, who, in 2000, said in a conference: "Twenty-first-century theoretical physics is coming out of the chaos revolution; it will be about complexity and its principal tool will be the computer.". This can be extended to natural sciences in general. Modelling and predicting ionosphere variables have been considered since many decades as a paramount objective of research by scientists and engineers. The new approach to natural sciences influenced also ionosphere research. Ionosphere as a part of the solar–terrestrial environment is recognized to be a complex chaotic system, and its study under this new way of thinking should become an important area of ionospheric research. After discussing the new context, this paper will try to review recent advances in the exploration of ionosphere parameter time series in terms of chaos theory and the use of machine-learning algorithms. [ABSTRACT FROM AUTHOR]

In recent years, cellular neural networks (CNNs) have become a popular apparatus for simulations in neuroscience, biology, medicine, computer sciences and engineering. In order to create more adequate models, researchers have considered memory effects, reaction–diffusion structures, impulsive perturbations, uncertain terms and fractional-order dynamics. The design, cellular aspects, functioning and behavioral aspects of such CNN models depend on efficient stability and control strategies. In many practical cases, the classical stability approaches are useless. Recently, in a series of papers, we have proposed several extended stability and control concepts that are more appropriate from the applied point of view. This paper is an overview of our main results and focuses on extended stability and control notions including practical stability, stability with respect to sets and manifolds and Lipschitz stability. We outline the recent progress in the stability and control methods and provide diverse mechanisms that can be used by the researchers in the field. The proposed stability techniques are presented through several types of impulsive and fractional-order CNN models. Examples are elaborated to demonstrate the feasibility of different technologies. [ABSTRACT FROM AUTHOR]

Business Information Systems (BIS) is a professional discipline that combines Computer Science, Management, and Business Administration. In this article the researchers evaluate the evolution of BIS curriculum in terms of its past, present and future, considering its historical background, the existing strengths and weaknesses, and how it can be developed to meet market needs. The study reveals the skills required by a BIS graduate and highlights how the existing/existed BIS curricula have made their graduates weaker when compared with Computer Science and Business Administration specialists. The research further compares the existential crisis of BIS with Library and Information Science (LIS) discipline, which have also faced a similar controversial crisis concerning their disciplinary boundaries, whether it belong to Social and Behavioral Sciences or Computer Science and Engineering and yet succeeded in its growth and contributions. This research concludes that the BIS curriculum is still budding and needs to be re-evaluated and updated regularly to meet the changing demands of the market highlighting the need for collaboration between academia and industry to ensure that BIS graduates are equipped with the skills that employers require. The paper finally proposes a balanced model of BIS curriculum that incorporates the latest technology updates. The proposed curriculum model aims to address the current gaps in BIS education and meets the changing demands of the market. [ABSTRACT FROM AUTHOR]

The present study uses bio-bibliometrics to examine the contributions made by Prof. K.R. Venugopal, the Vice-Chancellor of Bangalore University. He was the Principal of the University Visvesvaraya College of Engineering (UVCE) for 15 years and Chairman of the Department of Electronics and Communications, Computer Science Engineering, and Information Science Engineering at UVCE. He has an illustrious, distinguished, and brilliant academic career with eleven degrees, including two Ph.Ds. He was a post-doctoral research scholar and visiting professor at the University of Southern California, USA. It is essential to study his contributions to understand the magnitudes and contributions in a particular domain. Data has been collected based on his curriculum vitae, available on the website of Bangalore University. Further, the paper highlights Prof. K.R. Venugopal's author productivity, year-wise distribution, collaboration, communications channels, highly cited documents and research papers, and most downloaded books. [ABSTRACT FROM AUTHOR]

This paper attempts to scrutinise the publication productivity of Prof. Sunilkumar S. Manvi, Dean of Engineering and Technology at REVA University, Bengaluru, by data obtained from Scopus, Web of Science, and Google Scholar databases. In a total of 24 productive years (1999-2022), he has 292 publications (September 2022), and the highest number of documents was published in the year 2011 with 33 publications. His publications were analysed by types of document, year-wise distribution, distribution of articles in different domains, citation productivity, authorship pattern, measure of collaborations, collaboration indices, most prolific journals with number publication, highly cited articles, and citations during the study period of 1999-2022. As per collaboration indices, his highest Collaborative Coefficient is 0.67, MCC is 1.00 in the year 1999 and 2000 respectively. The highest Degree of Collaboration is 1.00, Collaborative Index is 3.11 in the year 2007. He published 98 documents during the period of 2009-2013. His major contributions to the field of Computer Science and Engineering are numerous. [ABSTRACT FROM AUTHOR]

Nowadays, with the development of computer science and technology, computer intelligent algorithms are more and more widely used in various industries. Every calculation formula in the computer intelligent algorithm has systematic logic and singleness, in order to expound the dynamic algorithm of football training optimized by the computer intelligent algorithm in detail. In this paper, the monitoring system using the computer intelligent algorithm can dynamically observe people or objects and systematically analyze them. This paper mainly studies the research of a football training dynamic monitoring system based on the computer intelligent algorithm and the design and optimization of the computer intelligent dynamic monitoring system in football training. Finally, the overall composition of the computer intelligent dynamic monitoring system and the application of the optimized computer intelligent dynamic monitoring system to the analysis of sample data are studied. [ABSTRACT FROM AUTHOR]

Boolean logic is widely used in almost every discipline including linguistics, philosophy, mathematics, computer science and engineering. Boolean logic is characterized by the two possible truth values, and various logical connectives/operations allow us to make compound statements, conditions. Most of the programming languages, if not all, have some of the logic operations: conjunction, disjunction and negation. Actually, since the set of these three operations form a basis, any logical statement can be formed by them. However, on the one hand, there are smaller bases as well, i.e., one of the conjunction or disjunction is already superfluous. Moreover, there are bases with only one operation, e.g., by NAND. On the other hand, one may allow other operations helping the programmer/user to define the conditions of conditional statements and loops in a simpler manner. In this paper we discuss these issues, including some practical points, implementation issues and short cut evaluations for various operations. [ABSTRACT FROM AUTHOR]

Boolean functions have important applications in information technology and computer science. Certificate complexity is an important combinatorial measure of Boolean function complexity. In this paper, we first introduce many concise and efficient notations then we study the elementary symmetric Boolean functions and obtain their certificate complexities when their degrees are odd or powers of 2. We show that both upper and lower bounds of certificate complexities can be attained. [ABSTRACT FROM AUTHOR]

Analyzing the results from the experimental research environment to the user environment of technology products in the computer science industry is very necessary. In this study, firstly, we applied the local binary pattern and K-Nearest Neighbor method to create a facial gender recognition application with a database of 6000 images divided by male and female, the degree to which the accuracy of the model on recognition is 95.4%. Secondly, we use a 2-layer research model to analyze the results of the user survey about facial gender recognition technology products. Most of the previous studies on facial gender recognition techniques focused on analyzing the impact of factors affecting applications using single-step structure equation modeling (SEM). The purpose of this study, based on the technology acceptance method (TAM) theory, describes the artificial neural network (ANN) method to perform in-depth analysis, yielding more accurate results than the SEM model. The study measures the relationship between the readiness for new technologies (optimism, innovation, discomfort, and insecurity). Technology acceptance (Perceived ease of use, Perceived usefulness). Expectations confirmed and Information systems acceptance (service quality, system quality, and information quality) and user satisfaction on facial gender recognition systems such as personal information declaration systems at customs gates at domestic and international airports. This paper outlines the research model of the multi-analysis approach by combining Partial Least Squares - Structure Equation Modeling (PLS-SEM) and Artificial Neural Network (ANN) analysis. First, the PLS-SEM model evaluates the factors affecting the intention to use the facial gender recognition system. Second, ANN ranks the impact factors of important predictors from the PLS-SEM model. The findings from the PLS-SEM and ANN approach research model confirm the results obtained from PLS-SEM by ANN. In addition, ANN performs linear and non-linear relational modeling with high prediction accuracy compared with the SEM model. In addition, An Importance Performance Map Analysis (IPMA) analyzes the results accurately for factors' important performance. [ABSTRACT FROM AUTHOR]

Local fractional calculus (fractal calculus) plays a crucial role in applications, especially in computer sciences and engineering. One of these applications appears in the theory of chaos. Therefore, this paper studies the dynamics of a fractal complex logistic map and then employs this map to generate chaotic sequences for a new symmetric image encryption algorithm. Firstly, we derive the fractional complex logistic map and investigate its dynamics by determining its equilibria, geometric properties, and chaotic behavior. Secondly, the fractional chaotic sequences of the proposed map are employed to scramble and alter image pixels to increase resistance to decryption attacks. The output findings indicate that the proposed algorithm based on fractional complex logistic maps could effectively encrypt various kinds of images. Furthermore, it has better security performance than several existing algorithms. [ABSTRACT FROM AUTHOR]

Background: In Spring 2020, the COVID‐19 pandemic sent universities into emergency remote education. The pandemic has been disruptive but offers the opportunity to learn about ways to support students in other situations where abrupt changes to teaching and learning are necessary. Purpose/Hypothesis: We described the responses of engineering and computer science students to a series of prompts about their experiences with remote learning. Design/Method: Data about students' remote learning experiences were collected from undergraduate engineering and computer science students at four different universities through an end‐of‐semester survey. Descriptive statistics were calculated, and qualitative responses were analyzed using qualitative content analysis through the lenses of master narrative theory and sociocultural theory. Results: Student responses revealed how their individual circumstances combined to reduce motivation, create home environments detrimental to completing schoolwork, and increase stress. Many students described the negative impacts of remote learning, but some students found positive aspects of the situation. The majority of students did not indicate a change in their desire or plans to pursue engineering or computer science majors. Conclusions: There was wide variation in how students experienced the disruption to university learning during Spring 2020. Implications of this paper can help not only in cases where emergency remote learning is needed in the future but also as universities seek to return to "normal" operations in 2022 and beyond. [ABSTRACT FROM AUTHOR]

With the rapid rise in the number of people buying houses, the demand for interior space design has also increased accordingly. The diversification of existing room types and the diversity of the public's perception of fashion make interior designers in short supply. The future of computer science and technology in the field of automatic design of indoor areas will be immeasurable. This paper proposes an automatic layout method for spatial area design based on convolutional neural networks (CNN). CNN methods are a fast and efficient method. By mimicking the designer's design process, it proposes a two-stage algorithm that defines the room first and the wall later, and the algorithm also provides a large-scale dataset called RPLAN that contains more than 80,000 interior layout plans from real residential buildings. Starting from the prediction living room, the automatic layout of the indoor areas is completed by iteration. A large number of empirical results show that the interior area design effect of this method is comparable to the interior design floor plan of professional designers. [ABSTRACT FROM AUTHOR]

Models are a universal instrument in science, technology, and daily life. They function as instruments in almost every scenario. Any human activity can be (and is) supported by models, e.g. reason, explain, design, act, predict, explore, communicate, collaborate, interact, orient, direct, guide, socialises, perceive, reflect, develop, making sense, teach, learn, imagine, etc. This universal suitability is also the basis for a wide use of models and modelling in Computer Science and Engineering. We claim that models form the fourth dimension in Computer Science. This paper sketches and systematises the main ingredients of the study model and modelling. [ABSTRACT FROM AUTHOR]

Fuzzy Switch Graphs (FSG s) are reactive fuzzy graphs that model systems in which accessibility relations and fuzzy values are changed whenever an edge is crossed [19]. Reversal Fuzzy Switch Graphs (R F S G s) were presented in [6] and model fuzzy reactive systems which provide the activation and deactivation of resources, a functionality that FSG s do not offer [19]. Activation and deactivation of arrows in a switch graph makes its applicability wider in fields like computer science and engineering. In this sense, the definition of operations for R F S G s is an important issue, since it enables to understand the algebraic structure of these graphs and allows to generate new model of systems from the previous one. This paper introduces some aggregation-based operations: union, intersection and extension for R F S G s. For each operation, the paper verify some properties. It ends with an application for engineering. [ABSTRACT FROM AUTHOR]

In their paper 'RIS-Assisted Secure UAV Communications with Resource Allocation and Cooperative Jamming', Guo et al. combine an RIS with unmanned aerial vehicles (UAVs) to improve the physical layer security of a wireless network. Current 5G wireless systems depend heavily on the quality of the wireless propagation environment, which had conventionally been modelled as an exogenous entity that can only be adapted and not controlled. This new vision of wireless network design is enabled by an emerging technology of reconfigurable intelligent surfaces (RISs), also known as intelligent reflecting surfaces (IRSs). [Extracted from the article]

The traditional urban landscape planning and design method cannot integrate the design into the whole planning scene and cannot express the planning effect of multiple schemes and large scenes in an efficient, intuitive, and coordinated way. With the development of computer science and technology, virtual reality technology based on AI is playing an important role in many aspects of urban landscape planning and design. In this paper, on the basis of 3D visualization landscape planning and design, 3D visualization urban landscape modeling is carried out using VR combined with the constructed deep neural network (DNN) to establish a 3D database and virtual scene model of the landscape, and 3D representation of the virtual scene landscape is realized. The designed solution allows the user to grab the object and release it into the workspace. If any placement is needed, the user can pick up the layer again and move it to a new location. Finally, the simulation experiment and its result analysis were conducted to effectively analyze the site of the real model and its matching rate, to realize the integration of the 3D image, 3D stereo, and system integration technology, and to finally complete the landscape design task. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI), machine learning (ML) and deep learning (DL) techniques have made a breakthrough in many different research fields, such as computer vision, natural language processing, network management and mobile communication. One of the primary goals in 5G network pursues high efficiency, higher spectrum and energy efficiency, higher system capacity and data rates, and lower latency with cost reduction. The papers on the topic of "AI-enabled intelligent networks for 5G and beyond" contain novel network architectures and mechanisms by using AI/ML/DL approaches for 5G/B5G networks. [Extracted from the article]

The study attempts to map the trends across the scholarly publications published in the field of "Fake News." Data were collected from one of the extensive indexing/abstracting services, Web of Science, the top indexing/abstracting service and a proprietary of Clarivate Analytics. The study reveals that the research on "Fake News" is mainly published as "articles" in English. Research on "Fake News" in terms of publication count and citation score shows a steady increase. "Lecture Notes in Computer Science," "Professional De La Informacion," and "New Media Society" stay as the prioritised platforms for researchers to publish their research. "Computer Science," "Communication," "Engineering," "Information Science and Library Science," and "Government Law" are the prioritised research domains in which research on "Fake News" stays a high priority. The highest number of articles are published from the U.S.A. The U.S.A., England, and Germany have the highest collaboration (links) with other countries, and the USA-China collaboration ranks first. Arizona State University is the top-ranked institute with the highest number of articles published on "Fake News," and "Pennycook G" stays the most productive author. Six hundred ninety funding agencies support the funded research papers with The National Science Foundation N.S.F., U.S.A. as the top sponsor. [ABSTRACT FROM AUTHOR]

Over the last 20 years Machine Learning (ML) has been applied to a wide variety of applications in the fields of engineering and computer science. In the field of material science in particular, it has been used to help speed up predictions of structure property relationships and in general enhance the material design process. In this paper, we review the current status of ML and its specific application to polymer composites process simulation. We also review some case studies going beyond this focus, especially in the fields of computational fluid dynamics, solid mechanics and Computer Aided Engineering (CAE), to show the potential for further application in our research area. The types of ML algorithms, tools, techniques used in the various applications and their couplings with other CAE software tools are summarized and the overall result/potential of each application/method is highlighted. [ABSTRACT FROM AUTHOR]

• A total of 75 studies was categorized within a systematic process. • A stage-based categorization was proposed. • Rigorous evaluation methodology was carried. The patterns present in biosignals, such as fetal heart rate (FHR), are valuable indicators of fetal well-being. In designing biosignal analysis systems, the variety of approaches and technology usage impairs the decision-making for the fundamental units of the systems. There is a need for an updated overview of studies encompassing the biosignal-based fetal state assessment systems. Therefore, we propose a systematic mapping study to identify and synthesize recent research regarding the building blocks that compose these systems. We followed well-established guidelines to perform a systematic mapping of studies regarding the building-blocks that compose the fetal state assessment systems and published between January 2016 and January 2021. A search string was determined based on the mapping questions and the PI (population and intervention) divisions. The search string was applied in digital libraries covering the fields of computer science, engineering, and medical informatics. Then, we applied the forward snowballing technique to complement the resulting set. This process resulted in 75 primary studies selected from a total of 871 papers. Selected studies were classified according to the publication types, systems design stages, datasets, and predictive capabilities. The results revealed that (i) The majority of the selected studies refer to the method as a type of publication and there is a lack of validation studies; (ii) The CTU-UHB was the most frequent biosignal-based dataset and UCI-CTG was the most frequent feature-based data; (iii) The selected studies made use of the system design stages alone or in a mixed-mode. The results indicated that the well-established classification models achieved competitive results compared with the state-of-the-art methods in data-constrained system designs. Moreover, we identified the need for validation studies in the clinical environment. [ABSTRACT FROM AUTHOR]