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Metaphors that compare the computer to a human brain are common in computer science and can be traced back to a fertile period of research that unfolded after the Second World War. To conceptualize the emerging "intelligent" properties of computing machines, researchers of the era created a series of virtual objects that served as interpretive devices for representing the immaterial functions of the computer. This paper analyses the use of the terms "artificial" and "virtual" in scientific papers, textbooks, and popular articles of the time, and examines how, together, they shaped models in computer science used to conceptualize computer processes. [ABSTRACT FROM AUTHOR]

The relationship between philosophy and science has always been complementary. Today, while science moves increasingly fast and philosophy shows some problems in catching up with it, it is not always possible to ignore such relationships, especially in some disciplines such as philosophy of mind, cognitive science, and neuroscience. However, the methodological procedures used to analyze these data are based on principles and assumptions that require a profound dialogue between philosophy and science. Following these ideas, this work aims to raise the problems that a classical connectionist theory can cause and problematize them in a cognitive framework, considering both philosophy and cognitive sciences but also the disciplines that are near to them, such as AI, computer sciences, and linguistics. For this reason, we embarked on an analysis of both the computational and theoretical problems that connectionism currently has. The second aim of this work is to advocate for collaboration between neuroscience and philosophy of mind because the promotion of deeper multidisciplinarity seems necessary in order to solve connectionism's problems. In fact, we believe that the problems that we detected can be solved by a thorough investigation at both a theoretical and an empirical level, and they do not represent an impasse but rather a starting point from which connectionism should learn and be updated while keeping its original and profoundly convincing core. [ABSTRACT FROM AUTHOR]

Digital computers were invented in the 1940s. They are sophisticated and versatile machines whose functioning is grounded in elaborate theory. Advances in theory and the availability of computers helped computer science to develop as an academic discipline, and university departments for the same started coming up in the 1960s. Computer science covers all phenomenon related to computers and consists primarily of man-made laws governing building, programming, and using computers. Computational thinking is a way of thinking influenced by computers and computer science. There are two schools of thought on computational thinking. The first school sees computational thinking as the use of computers to explore the world, while the other sees computational thinking as the application of concepts from computer science to solve real-world problems. Scholars typically agree that computational thinking has four essential components, viz., abstraction, decomposition, algorithm design, and generalization. Computational thinking is often feted by computer scientists as a useful skill that can be used by anybody anywhere. However, it is necessary to find out ways for successfully using computational thinking in domains other than computer science before it can be declared a universal skill. [ABSTRACT FROM AUTHOR]

The book "Philosophy of Computer Science: An Introduction to the Issues and the Literature" by William J. Rapaport is a comprehensive monograph that analyzes the core issues defining the philosophy of computer science. It covers topics such as the nature of computer science, the definition of algorithms, the Church-Turing Thesis, the ontology of computer programs, and the relationship between computer science, ethics, and artificial intelligence. The book is intended for specialists in the field but can also be used as an introductory textbook for undergraduate teaching, requiring no background in philosophy or computer science. [Extracted from the article]

Deep neural networks are extensively used in text mining and Natural Language Processing is to enable computers to understand, analyze, and generate natural language data, such as text or speech, but semantic resources, such as taxonomies and ontologies, are not fully included in deep learning. In this paper, we use Deep Convolutional Neural Network (Deep CNN) to classify research papers using the Computer Science Ontology, an ontology of research areas in the field of computer science. It takes as input the abstract and keywords of a particular research paper and returns the relevant research topic. To evaluate our ontology, we used a gold standard dataset that includes research articles. To further improve text classification results, we propose to design a Deep CNN model. We then used ontology matching to reduce the classes and get better results. Experimental results show that the proposed approach outperforms the one with the highest precision, recall, and F1-score. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to commemorate the late scholar Loet Leydesdorff for his great academic contribution on the basis of data from Web of Science. In the span of more than 40 years, he had 526 publications, with the years 2004-2021 being the most productive (394 publications). His international collaborations spread widely across 36 countries, with Germany, the USA, the UK, China, Russia, and South Korea being the most significant. His most frequent collaboration partners included Lutz Bornmann (Germany), Staša Milojević (USA), Caroline Wagner (USA), Henry Etzkowitz (USA), Jonathan Adams (UK), Ronald Rousseau (Belgium), and Ping Zhou (China). With a broad and deep knowledge background, Leydesdorff's research extended across multiple disciplines and fields, but he was most active in library and information science and computer science. He made profound contributions to the study of bibliometrics, innovation systems (the Triple Helix model), and communications. Leydesdorff had a remarkable and extensive citation impact, with citations in 221 WoS subject categories from 120 countries. His publications in 1996, 1998, 2000, 2005, 2006, and 2012 are highly cited, and those on university-industry-government relations (the Triple Helix model) are the most cited. [ABSTRACT FROM AUTHOR]

Usable security involves designing security measures that accommodate users' needs and behaviors. Balancing usability and security poses challenges: the more secure the systems, the less usable they will be. On the contrary, more usable systems will be less secure. Numerous studies have addressed this balance. These studies, spanning psychology and computer science/engineering, contribute diverse perspectives, necessitating a systematic review to understand strategies and findings in this area. This systematic literature review examined articles on usable security from 2005 to 2022. A total of 55 research studies were selected after evaluation. The studies have been broadly categorized into four main clusters, each addressing different aspects: (1) usability of authentication methods, (2) helping security developers improve usability, (3) design strategies for influencing user security behavior, and (4) formal models for usable security evaluation. Based on this review, we report that the field's current state reveals a certain immaturity, with studies tending toward system comparisons rather than establishing robust design guidelines based on a thorough analysis of user behavior. A common theoretical and methodological background is one of the main areas for improvement in this area of research. Moreover, the absence of requirements for Usable security in almost all development contexts greatly discourages implementing good practices since the earlier stages of development. [ABSTRACT FROM AUTHOR]

Complex systems, as interwoven miscellaneous interacting entities that emerge and evolve through self-organization in a myriad of spiraling contexts, exhibit subtleties on global scale besides steering the way to understand complexity which has been under evolutionary processes with unfolding cumulative nature wherein order is viewed as the unifying framework. Indicating the striking feature of non-separability in components, a complex system cannot be understood in terms of the individual isolated constituents' properties per se, it can rather be comprehended as a way to multilevel approach systems behavior with systems whose emergent behavior and pattern transcend the characteristics of ubiquitous units composing the system itself. This observation specifies a change of scientific paradigm, presenting that a reductionist perspective does not by any means imply a constructionist view; and in that vein, complex systems science, associated with multiscale problems, is regarded as ascendancy of emergence over reductionism and level of mechanistic insight evolving into complex system. While evolvability being related to the species and humans owing their existence to their ancestors' capability with regards to adapting, emerging and evolving besides the relation between complexity of models, designs, visualization and optimality, a horizon that can take into account the subtleties making their own means of solutions applicable is to be entailed by complexity. Such views attach their germane importance to the future science of complexity which may probably be best regarded as a minimal history congruent with observable variations, namely the most parallelizable or symmetric process which can turn random inputs into regular outputs. Interestingly enough, chaos and nonlinear systems come into this picture as cousins of complexity which with tons of its components are involved in a hectic interaction with one another in a nonlinear fashion amongst the other related systems and fields. Relation, in mathematics, is a way of connecting two or more things, which is to say numbers, sets or other mathematical objects, and it is a relation that describes the way the things are interrelated to facilitate making sense of complex mathematical systems. Accordingly, mathematical modeling and scientific computing are proven principal tools toward the solution of problems arising in complex systems' exploration with sound, stimulating and innovative aspects attributed to data science as a tailored-made discipline to enable making sense out of voluminous (-big) data. Regarding the computation of the complexity of any mathematical model, conducting the analyses over the run time is related to the sort of data determined and employed along with the methods. This enables the possibility of examining the data applied in the study, which is dependent on the capacity of the computer at work. Besides these, varying capacities of the computers have impact on the results; nevertheless, the application of the method on the code step by step must be taken into consideration. In this sense, the definition of complexity evaluated over different data lends a broader applicability range with more realism and convenience since the process is dependent on concrete mathematical foundations. All of these indicate that the methods need to be investigated based on their mathematical foundation together with the methods. In that way, it can become foreseeable what level of complexity will emerge for any data desired to be employed. With relation to fractals, fractal theory and analysis are geared toward assessing the fractal characteristics of data, several methods being at stake to assign fractal dimensions to the datasets, and within that perspective, fractal analysis provides expansion of knowledge regarding the functions and structures of complex systems while acting as a potential means to evaluate the novel areas of research and to capture the roughness of objects, their nonlinearity, randomness, and so on. The idea of fractional-order integration and differentiation as well as the inverse relationship between them lends fractional calculus applications in various fields spanning across science, medicine and engineering, amongst the others. The approach of fractional calculus, within mathematics-informed frameworks employed to enable reliable comprehension into complex processes which encompass an array of temporal and spatial scales notably provides the novel applicable models through fractional-order calculus to optimization methods. Computational science and modeling, notwithstanding, are oriented toward the simulation and investigation of complex systems through the use of computers by making use of domains ranging from mathematics to physics as well as computer science. A computational model consisting of numerous variables that characterize the system under consideration allows the performing of many simulated experiments via computerized means. Furthermore, Artificial Intelligence (AI) techniques whether combined or not with fractal, fractional analysis as well as mathematical models have enabled various applications including the prediction of mechanisms ranging extensively from living organisms to other interactions across incredible spectra besides providing solutions to real-world complex problems both on local and global scale. While enabling model accuracy maximization, AI can also ensure the minimization of functions such as computational burden. Relatedly, level of complexity, often employed in computer science for decision-making and problem-solving processes, aims to evaluate the difficulty of algorithms, and by so doing, it helps to determine the number of required resources and time for task completion. Computational (-algorithmic) complexity, referring to the measure of the amount of computing resources (memory and storage) which a specific algorithm consumes when it is run, essentially signifies the complexity of an algorithm, yielding an approximate sense of the volume of computing resources and seeking to prove the input data with different values and sizes. Computational complexity, with search algorithms and solution landscapes, eventually points toward reductions vis à vis universality to explore varying degrees of problems with different ranges of predictability. Taken together, this line of sophisticated and computer-assisted proof approach can fulfill the requirements of accuracy, interpretability, predictability and reliance on mathematical sciences with the assistance of AI and machine learning being at the plinth of and at the intersection with different domains among many other related points in line with the concurrent technical analyses, computing processes, computational foundations and mathematical modeling. Consequently, as distinctive from the other ones, our special issue series provides a novel direction for stimulating, refreshing and innovative interdisciplinary, multidisciplinary and transdisciplinary understanding and research in model-based, data-driven modes to be able to obtain feasible accurate solutions, designed simulations, optimization processes, among many more. Hence, we address the theoretical reflections on how all these processes are modeled, merging all together the advanced methods, mathematical analyses, computational technologies, quantum means elaborating and exhibiting the implications of applicable approaches in real-world systems and other related domains. [ABSTRACT FROM AUTHOR]

The Residue Neutrosophic Set (RNS) is a new idea in image additional pixel level. Our idea is to make an analysis based on the additional pixel amount. In recent decades, computer vision has revolutionized image analysis by researchers. Image segmentation is a more investigated topic in the science of computer vision. Neutrosophic is a sophisticated mathematical idea to solve a myriad of challenges. The objective is to invent a neutrosophic technique to execute image thresholding. In the article, the residue methodology was applied, which denotes the residual values of neutrosophic membership intensities. This article will explore a novel idea for image thresholding termed RNS. There will be three types of RNS techniques: minimum, average, and maximum. The concepts of existing thresholding techniques in neutrosophic solvation are considered in this proposal. This article adopts novel methodologies to provide an integrated visionary path segmentation methodology. Furthermore, the proposed technique reaches a better average accuracy score. [ABSTRACT FROM AUTHOR]

Letters of Recommendation (LORs) are widely utilized for admission to both undergraduate and graduate programs, and are becoming even more important with the decreasing role that standardized tests play in the admissions process. However, LORs are highly subjective and thus can inject recommender bias into the process, leading to an inequitable evaluation of the candidates' competitiveness and competence. Our study utilizes natural language processing methods and manually determined ratings to investigate gender and cultural differences and biases in LORs written for STEM Master's program applicants. We generate features to measure important characteristics of the LORs and then compare these characteristics across groups based on recommender gender, applicant gender, and applicant country of origin. One set of features, which measure the underlying sentiment, tone, and emotions associated with each LOR, is automatically generated using IBM Watson's Natural Language Understanding (NLU) service. The second set of features is measured manually by our research team and quantifies the relevance, specificity, and positivity of each LOR. We identify and discuss features that exhibit statistically significant differences across gender and culture study groups. Our analysis is based on approximately 4000 applications for the MS in Data Science and MS in Computer Science programs at Fordham University. To our knowledge, no similar study has been performed on these graduate programs. [ABSTRACT FROM AUTHOR]

Especially on the Internet, popular topics in computer sciences which are artificial intelligence, big data, business analytics, data mining, data science, deep learning, and machine learning have been compared or classified using confusing Venn diagrams without any scientific proof. Relationships among the topics have been visualized in this study with the help of Venn diagrams to add scientificity to visualizations. Therefore, this study aims to determine the interactions among the seven popular topics in computer sciences. Five books for each topic (35 books) were included in the analysis. To illustrate the interactions among these topics, the Latent Dirichlet Allocation (LDA) analysis, a topic modeling analysis method, was applied. Further, the pairwise correlation was applied to determine the relationships among the chosen topics. The LDA analysis produced expected results in differentiating the topics, and pairwise correlation results revealed that all the topics are related to each other and that it is challenging to differentiate between them. [ABSTRACT FROM AUTHOR]

Mitigating bias in algorithmic systems is a critical issue drawing attention across communities within the information and computer sciences. Given the complexity of the problem and the involvement of multiple stakeholders—including developers, end users, and third-parties—there is a need to understand the landscape of the sources of bias, and the solutions being proposed to address them, from a broad, cross-domain perspective. This survey provides a “fish-eye view,” examining approaches across four areas of research. The literature describes three steps toward a comprehensive treatment—bias detection, fairness management, and explainability management—and underscores the need to work from within the system as well as from the perspective of stakeholders in the broader context. [ABSTRACT FROM AUTHOR]

The incursion of tech companies into wider aspects of our lives means that computational thinking has become increasingly enmeshed with physiological, emotional, creative and social aspects of human life. We suggest that advanced computational thinking should be considered in wider terms than the limited scope of computer sciences and that we should recognise the expansion of the 'computer world' and its incursion into lived life: the pervasive encroachment of technology into physical, emotional, spatial, culturally complex and, strictly speaking, non-logical areas of our lives. The proposal is that we use a new term, advanced computational thinking, with the appropriate and relevant acronym of ACT, to suggest a social performative bias to existing ideas of computational thinking in education. The expansion of the computer world is the backdrop for exploring thinking as a 'kinship' with things (thing-kin) traversing human and material forms. In this article, ACT engages with the cultural scaffolding of the makerSpace, supporting a thinking space where kinship between 'things' and makers promotes diversity of learning style and an idea of epistemological pluralism. By recognising thinking and things as being closely entangled with sociomaterial realms, advanced computational thinking incorporates the wider social consequences of technology: expanding early definitions of computational thinking as tools exclusively focused on mathematical, logical or algorithmic thinking. [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]

For the sake of development of modern sciences, there has been a tendency in education to make use of integration processes between sciences. Interdisciplinary integration and coordination is one of the characteristic features of the learning process which is an interconnected and fully integrated discipline. Creating interdisciplinary integration, focusing on strengthening student knowledge and skills, teaching Computer Science in relationship with other disciplines, such as mathematics, physics, biology and others, is an area of interest. This method of teaching requires instructors to be fluent not only in their own discipline, but also in other disciplines. The method of interdisciplinary relationship can be widely used in the teaching of Computer Science in relation to the course of Physics, and this opportunity is one of the actual problems. For the purpose of fulfilling this task, curriculums of both disciplines have been researched and analyzed. Certain topics from the Physics course are reminded students as a refresh to reinforce the knowledge once again, and then on the basis of this knowledge, Computer Science topics are taught, which helps consciously master the new knowledge and increase cognitive activity of students. In this study, to solve physics problems we have employed the programming language C ++, which is a universal language with a wide range of capabilities. This article justifies actuality of the issue, gives background on the existing work, and presents goals and tasks of this research, as well as methodological basics, scientific novelty, and theoretical and practical importance of this work. Experiments have been conducted with the key points emerging from the context have been presented in the conclusion section. In conclusion, one of the ways to improve the teaching of Computer Science is the use of interdisciplinary relationships in the educational process. These interdisciplinary relationships play an important role for students in acquisition of scientific, theoretical and practical knowledge and skills. These relationships can be a prerequisite for a comprehensive approach to education. [ABSTRACT FROM AUTHOR]

This paper proposes two novel approaches to measure the similarity of co-cited authors for the task of document clustering, a) paragraph-level content-based author co-citation analysis (PCACA) and b) section-level content-based author co-citation analysis (SCACA), by mining the textual cited reference at the paragraph and the section level within a given scientific publication, respectively. Using over 2000 full-text publications, indexed in the field of Computer and Information Sciences, indexed in PLOS.org, we extract the useful information from a full-text publication such as citing sentences, location of citing sentences, cited first author name, and title of cited. We show that our proposed SCACA method of clustering outperforms existing clustering methods by exhibiting more optimal clusters with minimum graph density and an average degree in SCACA, i.e., 0.327 and 27.143, respectively. Finally, we show that SCACA produces the optimum number of clusters that comprehensively explains sub-disciplines of co-cited author pairs. [ABSTRACT FROM AUTHOR]

Currently, there is a tendency to use Islamic Geometric Patterns (IGPs) as important identities and cultural elements of building design in the Middle East. Despite high demand, lack of information about the potential of IGPs principles have led to formal inspiration in the design of existing buildings. Many research studies have been carried out on the principles of IGPs. However, comprehensive studies relating to new possibilities, such as structure-based, sustainable-based, and aesthetic-based purposes, developed by computer science and related technologies, are relatively rare. This article reviews the state-of-the-art knowledge of IGPs, provides a survey of the main principles, presents the status quo, and identifies gaps in recent research directions. Finally, future prospects are discussed by focussing on different aspects of the principles in accordance with collected evidence obtained during the review process. [ABSTRACT FROM AUTHOR]

The use of artificial intelligence (AI) applications in government is receiving increasing attention from global research and practice communities. This article, introducing a Special Issue on Artificial Intelligence in Government published in the Social Science Computer Review, presents an overview of some of the main policy initiatives across the world in relation to AI in government and discusses the state of the art of existing research. Based on an analysis of current trends in research and practice, we highlight four areas to be the focus of future research on AI in government: governance of AI, trustworthy AI, impact assessment methodologies, and data governance. [ABSTRACT FROM AUTHOR]

Researchers across cognitive, neuro- and computer sciences increasingly reference 'human-like' artificial intelligence and 'neuroAI'. However, the scope and use of the terms are often inconsistent. Contributed research ranges widely from mimicking behaviour, to testing machine learning methods as neurally plausible hypotheses at the cellular or functional levels, or solving engineering problems. However, it cannot be assumed nor expected that progress on one of these three goals will automatically translate to progress in others. Here, a simple rubric is proposed to clarify the scope of individual contributions, grounded in their commitments to human-like behaviour, neural plausibility or benchmark/engineering/computer science goals. This is clarified using examples of weak and strong neuroAI and human-like agents, and discussing the generative, corroborate and corrective ways in which the three dimensions interact with one another. The author maintains that future progress in artificial intelligence will need strong interactions across the disciplines, with iterative feedback loops and meticulous validity tests—leading to both known and yet-unknown advances that may span decades to come. This article is part of a discussion meeting issue 'New approaches to 3D vision'. [ABSTRACT FROM AUTHOR]

This article, which is the result of research, presents the design of an application as a proposal to implement free Arduino software and hardware as a facilitating axis for learning skills in natural sciences, technology, engineering, and mathematics (stem). The objective of this research was to carry out a didactic and technological innovation in the teaching and learning process of the subject of technology and computer science to develop stem competencies in students necessary to perform in a digital world. The qualitative methodology consisted of delivering didactic planning in an application based on a project-based pedagogy and integrative didactics. In this way, it was possible to identify the development of research skills, critical thinking, problem-solving, creativity, communication, and collaboration, all related to the stem approach. In addition, the educational community where the research experience took place showed great interest in using these resources in the classroom and the possibility of applying them in productive projects of the institution's technical agricultural, livestock, and business management modalities. The application can be used by technology and computer science teachers in the eleventh grade and can be adapted to other educational levels. [ABSTRACT FROM AUTHOR]

Fractional metric dimension of connected graph G was introduced by Arumugam et al. in [Discrete Math. 312, (2012), 1584-1590] as a natural extension of metric dimension which have many applications in different areas of computer sciences for example optimization, intelligent systems, networking and robot navigation. In this paper fractional metric dimension of generalized prism graph Pm × Cn is computed using combinatorial criterion devised by Liu et al. in [Mathematics, 7(1), (2019), 100]. [ABSTRACT FROM AUTHOR]

Graph energies and spectral radii have application in molecular computing and computer sciences. In this paper, we concentrate on new findings about the Symmetric Division Deg, (SDD) energies, and (SDD) spectral radii of p splitting and p shadow graphs built on the foundation of any regular graph. In fact it becomes natural to ask how the SDD energies and spectral radii of newly formed graphs depend on the SDD energies and spectral radii of the given regular graph. [ABSTRACT FROM AUTHOR]

Since Wing Communications of the ACM, 49, 33–35, (2006) popularized computational thinking (CT) as a skill for every student, it has gained significant traction as an approach to bring computer science tools and practices into K-12 classrooms. At the same time, teachers often see the relevance of CT as a tool to introduce problem solving and thinking strategies in the classroom. Despite the increasing use of CT in K-12, questions remain about its role in supporting teaching and learning of disciplinary ideas. While CT can be used to bring computer science to all students, we believe that it can serve a bigger purpose to explicitly teach metacognitive strategies, which play a significant role in academic outcomes. In the paper, we discuss the connections between CT and metacognition and how CT could support the development of metacognition in K-12 classrooms. [ABSTRACT FROM AUTHOR]

Rapid advances in biology, electronics, computer and data science have turned invention into products, changing the lives and lifestyles of millions of people around the world. This mini-review will describe some remarkable progress made over the last 10 years which serves both healthy individuals and patients alike. With a forward looking lens towards long term space missions and the potential colonisation of the Moon and Mars, we discuss three technologies under development. We conclude with a distant looking perspective on the prospect of gene mediated human enhancement and highlight the importance of aligning benefit for people on Earth with goals for future space missions and the need to establish regulatory and ethical guidelines. [ABSTRACT FROM AUTHOR]

Foreign students coming to study in Russia learn the Russian language at all levels, enriching their vocabulary. Besides possessing the lexical minimum of the Russian language, foreign students studying at the preparatory department of the Russian university need to master specialised terminology used in computer science, physics and mathematics. These subjects are included in the list of disciplines of the supplementary general programme, which aims to provide a preparation course for foreign citizens and stateless persons to master professional educational programmes in the Russian language. This article describes the need and conditions for enriching and activating the vocabulary of foreign students, while providing a general description of research methods. It expounds on the structure and content of the computer science course at the pre-university stage of training for foreign citizens. The paper considers the process of teaching foreign studentsthe terminology used in the computer science course. This paper provides a number of examples of new terms as well as exercises related to their acquisition. It is concluded that teaching computer-science vocabulary to foreign students is one of the most important components of teaching information science and expanding the learners’ vocabulary in general. [ABSTRACT FROM AUTHOR]

Full waveform inversion (FWI) plays a major role in the oil and gas industry as a state-of-the-art technique that produces quantitative subsurface structures with high-fidelity images. Various FWI studies have been conducted, and these suggest that FWI is a promising inversion method. Recently, many attempts have been made toward three-dimensional (3D) and four-dimensional FWI applications (which were difficult to perform in the past) because of the progress made in computer science and the growth of computer resources. To manage the very large data requirement of 3D problems, a time-domain FWI that is relatively efficient in terms of memory demands must be implemented. However, it could encounter practical issues, leading to failure in its convergence. In this paper, we introduce these practical issues and several alternative methods for mitigating them. The first issue is the bandpass filtering of the observed seismograms. We suggest that the frequency-domain filter based on a reference wavelet would be optimal in terms of both bandpass filtering and source wavelet estimation. The second issue is related to acoustic approximation. We show that a simple density model comprising only water and solid layers is a reasonable option to address seafloor reflectivity properly. The last issue is the accumulation of round-off errors due to the massive computation of the objective function. We demonstrate that a simple modification of the error calculation can resolve this round-off error problem. [ABSTRACT FROM AUTHOR]

There is continuing debate about which climate-policy instruments are most appropriate to reduce emissions. Undertaking a global survey among scientists who published on climate policy, we provide a systematic overview of (dis)agreements about six main types of policy instruments. The survey includes various fields across the social and natural sciences. The results show that, on average, all instruments are considered important, with direct regulation receiving the highest rating and adoption subsidies and cap-and-trade the lowest. The latter is surprising given the theoretical advantages and real-world success of the EU-ETS. Next, clustering scientific fields based on how important they consider the instruments, we determine five distinct groups, with (a) ecological economists and (b) mathematics/computer science being most dissimilar from other discipline clusters. We explain disagreement through assessing the relative importance assigned to policy criteria effectiveness, efficiency, equity and socio-political feasibility, as well as researchers' attitudes and background. Paying special attention to carbon pricing, motivated by its contested key role, we identify three respondent clusters, namely 'enthusiasts', 'undecided', and 'skeptics'. Examining various policy arguments, we find that agreeing that carbon pricing effectively limits energy/carbon rebound and has potential to be harmonized globally have the strongest association with giving importance to this policy. • We survey researchers from diverse fields to examine views on climate policies. • Direct regulation is on average rated as most important. • Environmental and ecological economists hold contrasting views on cap-and-trade. • Support for carbon pricing relates to expectations of curbing rebound and global harmonization. • Many other factors are assessed, such as policy criteria, climate worry and ideology. [ABSTRACT FROM AUTHOR]

the evaluation of the plan for the area of technology and computer science in the schools of Villavicencio allows the reader to learn about the methodologies, plans and programs that are developed in the area. The results will enable the reader to have a clear vision of the way in which the teaching process is developed and, based on this, to identify the actions that could eventually be developed in an educational institution that intends to promote the use of computer science and technology. This research, with a qualitative approach began with interviews of teachers and culminated with the review of the subject plan; these data were categorized to be submitted to the triangulation of results in order to evaluate the plans for the area. It was found in some cases that there is a lack of knowledge of the concepts of pedagogical planning; that each institution has a specific model that deviates from the Ministry's guidelines based on the protection of school autonomy, and that area planning often follows the teacher's interests. All these generalities made it possible to demonstrate that there is no common path, but that there are many individual endeavors that try, with much effort, to make the development of the area more efficient. The research leads to the deduction that the area of technology and computer science could be developed in a transversal and interdisciplinary way with the other areas of the academic curriculum so that it can become the support required by basic secondary education in the city of Villavicencio. [ABSTRACT FROM AUTHOR]

The IEEE Computer Society awards program honors technology leaders who have had a great impact on the advancement of innovation while serving the computer profession and the Society. We're pleased to announce 2021 award recipients (as of September 2021) that represent the brightest luminaries and pioneers within the field of computer science and computer engineering. [ABSTRACT FROM AUTHOR]

Community detection is a major issue in network analysis. This paper combines a socio-historical approach with an experimental reconstruction of programs to investigate the early automation of clique detection algorithms, which remains one of the unsolved NP-complete problems today. The research led by the archaeologist Jean-Claude Gardin from the 1950s on non-numerical information and graph analysis is retraced to demonstrate the early contributions of social sciences and humanities. The limited recognition and reception of Gardin's innovative computer application to the humanities are addressed through two factors, in addition to the effects of historiography and bibliographies on the recording, discoverability, and reuse of scientific productions: (1) funding policies, evidenced by the transfer of research effort on graph applications from temporary interdisciplinary spaces to disciplinary organizations related to the then-emerging field of computer science; and (2) the erratic careers of algorithms, in which efficiency, flaws, corrections, and authors' status, were determining factors. [ABSTRACT FROM AUTHOR]

ACM-W is the community within the Association for Computing Machinery (ACM) that is dedicated to issues of gender equality in Computer Science. ACM-W works globally to support, celebrate and advocate for the full participation of women in all aspects of the computing field. This article presents a brief history of ACM-W with an emphasis on the global growth of the organization. A summary of the primary programs of ACM-W is provided to further highlight the global impact of our work. Also included are examples of how ACM-W is partnering with other computing and scientific organizations to realize greater impact in the arena of gender equality. [ABSTRACT FROM AUTHOR]

Computing reachability probabilities is a fundamental problem in the analysis of randomized programs. This article aims at a comprehensive and comparative account of various martingale-based methods for over- and under-approximating reachability probabilities. Based on the existingworks that stretch across different communities (formal verification, control theory, etc.), we offer a unifying account. In particular, we emphasize the role of order-theoretic fixed points--a classic topic in computer science--in the analysis of randomized programs. This leads us to two new martingale-based techniques, too. We also make an experimental comparison using our implementation of template-based synthesis algorithms for those martingales. [ABSTRACT FROM AUTHOR]

Contribution: In a context where hands-on courses are biased toward specific technologies, a novel creativity-provoking instructional approach for networking undergraduate courses is successfully applied following action research principles and active and creative learning techniques. Background: Extensive engineering-oriented networking courses have been proposed with a strong focus on specific protocol solutions. At the same time, the amount and complexity of techniques is notably increasing with the advent of the Future Internet. As a result, the curricula looses focus on the fundamentals of networking algorithms. Intended Outcomes: We address algorithmic learning in networking for computer sciences, where students are expected to 1) create; 2) develop; 3) analyze; and 4) compare algorithms and processes regardless of protocol-specific technologies. At least 70% of the students are expected to meet this goal while enhancing their engagement and motivation in a time-constrained course schedule. Application Design: To achieve 1) and 2), we instrument an active experimental strategy, while objectives 3) and 4) are tackled with creative learning techniques, both applied in an action research framework. The approach is supported by state-of-the-art networking application interfaces and simulators. Furthermore, a blended and game learning component favors the engagement via comparison and competition of students’ project metrics. Findings: The experiment is carried out by professors of the Computer Science Bachelor’s degree taught in FAMAF. Results show that the applied methodology met the intended outcomes, and improved by 7% in a two-year cycle. Furthermore, the approach was very well received based on student’s feedback. [ABSTRACT FROM AUTHOR]

Modern climate science, Earth system science, physical geography, oceanography, meteorology, and related disciplines have increasingly turned into highly quantitative, computational fields, dealing with processing, analysis and visualization of large numerical data sets. Students of these and many other disciplines thus need to acquire robust scientific computing and data analysis skills, which have universal applicability. In addition, the increasing economic importance and environmental significance of solar power and sustainable practices such as passive building design have recently increased the importance of understanding of the apparent motions of the Sun on the celestial sphere, for a wider array of students and professionals. In this paper, I introduce and describe AstroGeoVis v1.0: open-source software that calculates solar coordinates and related parameters and produces astronomical visualizations relevant to the Earth and climate sciences. The software is written in MATLAB©; while its primary intended purpose is pedagogical, research use is envisioned as well. Both the visualizations and the code are intended to be used in the classroom in a variety of courses, at a variety of levels (targeting high school students to undergraduates), including Earth and climate sciences, geography, physics, astronomy, mathematics, statistics and computer science. I provide examples of classroom use and assignment ideas, as well as examples of ways I have used these resources in my college-level teaching. [ABSTRACT FROM AUTHOR]

The article "IN MEMORIAM KARL F. STOCK (13.01.1937–10.06.2022)" describes the life and career of Karl F. Stock, a significant Austrian librarian. Stock was born on January 13, 1937, in Graz and began studying mathematics and physics at the University of Graz after his father's death in 1943. However, due to financial reasons, he discontinued his studies and instead worked in the university library. Stock completed specialized training in data processing for library science and became the director of the library at the Graz University of Technology in 1974. He was a pioneer in the introduction of automated library management and published numerous works on bibliography, computer science, and library organization. Stock was also an artist and created graphic works for decades. He will be remembered as a significant librarian, bibliography expert, and exlibris artist. [Extracted from the article]

The study is perceived to find the research performance of Jordanian Institutes during the last five years in scopus database. Jordan has produced a total of 14722 research articles published in national and international journals during 2015 to 2019 with a continuous gradual increase both in publications as well as in citations. The public and older universities have performed better as compared to the private and newly established universities. Although, the major chunk of articles has been published in national journals however, as far as the citations are concerned, the international journals have taken a lead. A total of 4767 journals have been used for publications, however, 227 have been identified as the core collection journals. The non local journals with high impact factor and citescore have got the maximum citations, although very less no. of articles have been published by Jordanian researchers. The medicine, engineering, computer science, mathematics, etc. are the top contributing subjects while as the finance, economics, neuroscience, veterinary, and decision sciences are weaker subjects. The keywords analysis also reflects the strong hold of medicine and health researches in the country. The Lancet has been identified as the top cited journal followed by New England Journal of Medicine, The Lancet Neurology, IEEE Access, JAMA Oncology and the less cited journal were International Journal of Recent Technology and Engineering, Journal of Engineering and Applied Sciences, Jordan Journal of Physics, International Journal of Scientific and Technology Research. Khader YS with 195 articles, Alzoubi KH with 143 articles and Khabour OF with 106 articles all from the Jordan University of Science and Technology are the top authors in Jordan. A total of 2208 articles are written by single authors and 12514 by multiple authors with a highly skewed correlation been identified between the authors and the no. of authors with 27979 authors contributing only single publication while as 195 articles have been published by only one author. The United States followed by Saudi Arabia and United Kingdom has been identified as the top collaborated countries of Jordan and the countries like Tajikistan, Solomon Islands and Cambodia are weakly collaborated. It is found that the highly cited articles are published in the Lancet Journal and with more collaboration of authors more citations have been identified. The top ranked articles in terms of citations have been published by the highly collaborated authors. The Jordanian researchers are citing mostly the newer research which may be related with the stronger areas of knowledge like medicine, computer sciences, engineering as per the Reference Publication Year Spectroscopy (RPYS). [ABSTRACT FROM AUTHOR]

In response to the underrepresentation of minoritized groups employed in the computer science (CS) field, this study aims to enhance underrepresented minoritized (URM) students' motivation for CS through an intervention informed by culturally relevant pedagogy theory in a required high school mathematics course. This intervention integrated culture, art, geometry, and coding through the virtual presentation of a Native American star quilt design using Python coding language and a video of a CS role model of Latino descent. Participants were 133 URM high school students across six 10th grade geometry classes. Three of the six geometry classes were randomly assigned to receive the intervention. Both quantitative and qualitative analysis were conducted to assess the effects of this intervention. Results indicated that the intervention had a positive effect on the development of URM students' computer science-oriented possible selves. Moreover, several qualitative themes emerged in how URM students connected with the CS role model. [ABSTRACT FROM AUTHOR]

Background: Visualizations are used to communicate data about important political, social, environmental, and health topics to a wide range of audiences; however, perceptions of graphs as objective conduits of factual data make them an easy means for spreading misinformation. Research questions: 1. Are people deceived by common deceptive tactics or exaggerated titles used in data visualizations about non-controversial topics? 2. Does a person's previous data visualization coursework mitigate the extent to which they are deceived by deceptive tactics used in data visualizations? 3. What parts of data visualizations (title, shape, data labels) do people use to answer questions about the information being presented in data visualizations? Literature review: Although scholarship from psychology, human-computer interaction, and computer science has examined how data visualizations are processed by readers, scholars have not adequately researched how susceptible people are to a range of deceptive tactics used in data visualizations, especially when paired with textual content. Methodology: Participants (n = 329) were randomly assigned to view one of four treatments for four different graph types (bar, line, pie, and bubble) and then asked to answer a question about each graph. Participants were asked to rank the ease with which they read each graph and comment on what they used to respond to the question about each graph. Results/Discussion: Results show that deceptive tactics caused participants to misinterpret information in the deceptive versus control visualizations across all graph types. Neither graph titles nor previous coursework impacted responses for any of the graphs. Qualitative responses illuminate people's perceptions of graph readability and what information they use to read different types of graphs. Conclusions: Recommendations are made to improve data visualization instruction, including critically examining software defaults and the ease with which people give agency over to software when preparing data visualizations. Avenues of future research are discussed. [ABSTRACT FROM AUTHOR]