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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]

This paper considers how a curricular design that integrated computer programming and creative movement shaped students' engagement with computing. We draw on data from a camp for middle schoolers, focusing on an activity in which students used the programming environment NetLogo to re-represent their physical choreography. We analyze the extent to which students noticed incompatibilities (mismatches between possibilities in dance and NetLogo), and how encountering them shaped their coding. Our findings suggest that as students attended to incompatibilities, they experienced struggle, but persisted and engaged in iterative cycles of design. Our work suggests that tensions between arts and programming may promote student engagement. [ABSTRACT FROM AUTHOR]

This paper describes the implementation of a STEM scholarship program which utilized a holistic approach to providing a multi-dimensional student support system. The program has been successful in encouraging and supporting women in Applied Mathematics and Computer Science by offering a diverse suite of extracurricular opportunities, actively engaging them in organized events, research projects, and participation in STEM communities, and helping them achieve higher GPAs and shorter times to graduation. The supported women also benefitted from close mentoring relationships with the faculty mentors. The program emphasized the development of empowering settings for women's engagement and achievement, which act to sustain and expand interest in mathematics and computing, and thereby help them to see themselves as future professionals in the field. [ABSTRACT FROM AUTHOR]

With the advent of technological advancement in learning, such as context-awareness, ubiquity and personalisation, various innovations in teaching and learning have led to improved learning. This research paper aims to develop a system that supports personalised learning through adaptive content, adaptive learning path and context awareness to meet individual learner's requirements and promote the effectiveness and performance of the learning process. Furthermore, the study used an experimental control group to ascertain the significance of learners' learning styles and preferences in improving learning performance. The model considers different modules such as personalisation, location support, learning plan and context awareness while relying on the proper classification of learners' learning styles. The system was experimented using 127 learners of a Computer Science Course. The result obtained using 10-fold cross-validation on various algorithms shows better performance in ROC, Kappa and Accuracy, which were all used to evaluate the quality of classification outcome and compared with learners' performances in assessments. During classification, Naïve Bayes Model has the highest average ROC value of 0.979, TP Rate of 0.951 and FP Rate of 0.045. The results obtained show an improvement in learning. [ABSTRACT FROM AUTHOR]

This editorial introduces the special issue, Resources for Undergraduate Cryptology. We begin by describing possible roles for cryptology in the undergraduate mathematics curriculum together with a brief overview of the subject. We conclude with a brief preview of each paper included in this issue. [ABSTRACT FROM AUTHOR]

In this paper we discuss the types of knowledge used by six middle school students as they engaged with a debugging task designed to integrate ideas from computer science, mathematics and science. Our findings show that the computational thinking practice of debugging is a rich source of opportunities to integrate these different disciplines. The analysis illustrates how the types of knowledge the students did and did not use at each step of the debugging process were related to their ability to succeed at each step. Our work contributes to theory and practice by uncovering implications for studying debugging through two refined frameworks and for designing debugging tasks to support transdisciplinary learning. [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]

Cystic fibrosis (CF) is an inherited, life-limiting chronic health condition that impacts many organ systems including the lungs, pancreas, liver, intestines, and reproductive organs. Given the various organ systems impacted, treatments can be complex, burdensome, and time consuming. In addition, the stress and emotional impact of CF on caregivers as well as patients is significant. This paper describes delivery of psychosocial care across developmental stages in the largest pediatric CF center in the country. The focus will be on goals of care as well as assessment and intervention strategies. Furthermore, clinical informatics and next steps also will be discussed. [ABSTRACT FROM AUTHOR]

Fractional-order derivative is attracting more and more attention of researchers in image processing because of its better property in restoring more texture than the total variation. To improve the performance of fractional-order variation model in image restoration, a truncated fractional-order variation model was proposed in Chan and Liang [Truncated fractional-order variation model for image restoration, J. Oper. Res. Soc. China]. In this paper, we propose a dual approach to solve this truncated fractional-order variation model on noise removal. The proposed algorithm is based on the dual approach proposed by Chambolle [An algorithm for total variation minimisation and applications, J. Math Imaging Vis. 20 (2004), pp. 89–97]. Conversely, the Chambolle's dual approach can be treated as a special case of the proposed algorithm with fractional order α = 1. The work of this paper modifies the result in Zhang et al. [Adaptive fractional-order multi-scale method for image denoising, J. Math. Imaging Vis. 43(1) (2012), pp. 39–49. Springer Netherlands 0924–9907, Computer Science, pp. 1–11, 2011], where the convergence is not analysed. Based on the truncation, the convergence of the proposed dual method can be analysed and the convergence criteria can be provided. In addition, the accuracy of the reconstruction is improved after the truncation is taken. [ABSTRACT FROM AUTHOR]

Highly efficient algorithms for solving the time constrained shortest path problem have been highlighted over the past decades to reduce the cost of vehicle travel in the road network. The paper presents a novel graph algorithm comprising three stages to acquire a time constrained shortest path between any two nodes on the map. In the first stage, the undirected graph is transformed into a directed graph (DT graph) by deleting edges that must not be included in any of the time constrained shortest paths. A variant DT tree with the destination as the root and the source as the leaf is then constructed from the DT graph in the second stage. By finding the minimal difference value between leaves and the root of the variant DT tree, we can eventually obtain a time constrained shortest path from the variant DT tree in the third stage. Experimental results show that our algorithm not only requires less running time than some classical graph algorithms but also can work immediately in the first stage without knowing the information of both the destination and a specific time constraint. [ABSTRACT FROM AUTHOR]

Given the evolving and diverse nature of post-16 computing curricula within England, this papers' primary objective was to identify the factors which influence the decision-making processes for education providers when choosing computing curricula. As a main provider of the vast array of post-16 qualifications, and due to their neglect both politically and in research, further education colleges were chosen as the subject of inquiry. Due to the focus on understanding employee perspectives, a qualitative research method was employed where semi-structured interviews were conducted with thirty-two employees from across thirteen colleges within England. These employees included computing lecturers, heads of departments, and members of senior leadership. Findings indicate the extent of the range of post-16 computing qualifications offered by colleges, in addition to identifying who the key players are for computing curricula decisions. Additionally, ten factors were identified as pivotal to influencing curricula choice, and from these factors, a model has been created classifying four central areas that should be considered regarding curriculum choice: labour market information, qualification relevance to industry needs, qualification attractiveness, and current college resources. This model should help inform education providers in making more informed computing curricula decisions. [ABSTRACT FROM AUTHOR]

Bringing evidence into policy and practice discussions is political; more so when evidence from health studies or programme data are deemed controversial or unexpected, or when results are manipulated and misrepresented. Furthermore, opinion and misinformation in recent years has challenged our notions about how to achieve evidence-informed decision-making (EIDM). Health policy and systems (HPS) researchers and practitioners are battling misrepresentation that only serves to detract from important health issues or, worse, benefit powerful interests. This paper describes cases of politically and socially controversial evidence presented by researchers, practitioners and journalists during the Health Systems Research Symposium 2020. These cases cut across global contexts and range from public debates on vaccination, comprehensive sexual education, and tobacco to more inward debates around performance-based financing and EIDM in refugee policy. The consequences of engaging in controversial research include threats to commercial profit, perceived assaults on moral beliefs, censorship, fear of reprisal, and infodemics. Consequences for public health include research(er) hesitancy, contribution to corruption and leakage, researcher reflexivity, and ethical concerns within the HPS research and EIDM fields. Recommendations for supporting researchers, practitioners and advocates include better training and support structures for responding to controversy, safe spaces for sharing experiences, and modifying incentive structures. [ABSTRACT FROM AUTHOR]

Reviewing is the most important step in the quality accreditation of scientific works, requires the professional expertise of the reviewer as well as there is no conflict of interest in the evaluation process. However, we also acknowledge that reviewers have limited knowledge, experience and opinions about the work of others, so they may misinterpret the author's point of view, leading to the rejection of excellent scientific work or a potentially successful project proposal. Manually selecting reviewers can lead to bias and time-consuming. To solve these problems, we have developed a support system for selecting a group of reviewers to evaluate a particular problem, such as a proposal or a research paper. Our support system consists of three main modules: data collection, reviewer identification and group prediction of reviewers. The Data Collection module collects data from a variety of sources to create the scientist profile database. The reviewer identification module recognizes reviewers on a specific topic. The reviewer prediction module provides a group of exp reviewers to evaluate a submitted paper or a proposal. Experiments on the DBLP computer science bibliography dataset showed that our system achieves better results in terms of accuracy in comparison to other methods. [ABSTRACT FROM AUTHOR]

Cognition in computer sciences refers to the ability of a system to learn at scale, reason with purpose, and naturally interact with humans and other smart systems, such as humans do. To enhance intelligence, as well as to introduce cognitive functions into machines, recent studies have brought humans into the loop, turning the system into a human–AI hybrid. To effectively integrate and manipulate hybrid knowledge, suitable technologies and guidelines are required to sustain the human–AI interface so that communication can occur. However, traditional Knowledge Management (KM) and Knowledge Engineering (KE) approaches encounter problems when dealing with cutting-edge technologies, imposing impediments for the use of traditional methods in cognitive systems (CS). This paper presents a brief overview of the Smart Knowledge Engineering for Cognitive Systems (SKECS), which is based on methods, technologies, and procedures that bring innovations to the fields of KE, KM, and CS. The goal is to bridge the gap in the hybrid cognitive interface by the combination of experience-based knowledge representation with the use of emerging technologies such as deep learning, context-aware indexing/retrieval, active learning with a human-in-the-loop, and stream reasoning. In this work Set of Experience Knowledge Structure (SOEKS) and Decision DNA (DDNA) is extended to the visual domain and utilized for knowledge capture, representation, reuse, and evolution. These technologies are examined throughout the layers of SKECS for applications in knowledge acquisition, formalization, storage/retrieval, learning, and reasoning, with the final goal of achieving knowledge augmentation (wisdom) in CS. Features of the SKECS and their practical implementation is discussed through a case study—the Cognitive Vision Platform for Hazard Control (CVP-HC)—suggesting that methods, techniques and procedures comprising the SKECS are suitable for advancing systems toward augmented cognition. [ABSTRACT FROM AUTHOR]

Sierpinski networks constitute an extensively studied class of graphs of fractal nature applicable in topology, mathematics of Tower of Hanoi, computer science, and Chemical graph theory. Recently the properties of Sierpinski networks have been studied like physico-chemical properties, thermodynamic properties, chemical activity, biological activity, metric dimension and degree based topological indices. In this paper, we further extend the study of Sierpinski networks and computed Zagreb types molecular descriptors (molecular topological indices) and their variants. [ABSTRACT FROM AUTHOR]

A novel assessment method for rapid structural safety state assessment is developed based on state-of-the-art machine learning technology. In this paper, a deep neural network (DNN), which originated in computer science, is first introduced, including its concept, structure and related training algorithms. Then the evaluation procedure to determine the structural safety state based on the DNN is developed. In the procedure, the pseudo-acceleration spectra and the structural safety states are selected as the input and output of the DNN model, respectively. Finally, the procedure of the novel assessment method is illustrated using a five-story reinforced concrete (RC) frame as an example. The effectiveness and accuracy are validated, and the influence of the number of hidden layers and size of the training data on the performance of the DDN is also investigated. The results demonstrate that the proposed method can evaluate the structural safety state rapidly based on the DNN. The most appropriate number of hidden layers is two considering both training accuracy and test accuracy. The training accuracy and test accuracy were 93.45% and 93.14%, respectively, using the two-hidden-layer DNN model trained on a training dataset of size 66,612. [ABSTRACT FROM AUTHOR]

Hackathons are time-bound, competitive coding contests that are often judged for prizes. Their name originates from joining hacking, playful exploration of hardware and software issues, with marathons, endurance competitions. The intent is to challenge participants to build working prototypes of hardware or software in a short time period, anywhere from one day to several weeks, though typically between 24–28 hours. While they are a mainstay in computer science fields, they are becoming increasingly popular in other domains, including libraries. Libraries have long championed life-long learning, a democratization of data, and access to information. These are similar mentalities of the maker movement, echoed in hackathons. Rapid iteration, problem solving, and cooperative learning are regularly present at events and within library systems. This paper details a case study of one institution's growth from a hackathon event host to deeper library engagement and partnership with an informal learning program. The authors will highlight benefits that both partners observed and will end with a pitch for why other libraries should consider hosting similar events. Finally, several recommended resources for libraries who are contemplating hosting hackathon events will be presented. [ABSTRACT FROM AUTHOR]

Robotics activities engage students in critical and computational thinking, problem solving, and collaboration, as well as engineering and computer science. By integrating robotics into disciplinary courses, educators offer these opportunities to a wider range of students. However, teachers may be less likely to use new technology without evidence that it can support their teaching and student learning. This paper presents two descriptive case studies as a 'proof of concept' for integrating robotics construction activities into disciplinary courses. They focus on teachers' motivation for integration, and how they used robotics to support disciplinary goals. [ABSTRACT FROM AUTHOR]

Overlaying Computer Science (CS) courses on top of inequitable schooling systems will not move us toward "CS for All." This paper prioritizes the perspectives of minoritized students enrolled in high school CS classrooms across a large, urban school district in the Western United States, to help inform how CS can truly be for all. This paper explores what student agency looks like while answering the research question "From the perspective of minoritized students historically underrepresented in computing, what makes a critical difference in their sense of agency in introductory CS high school classes?" Our research-practice partnership used qualitative data (including classroom observations, interviews, student artifacts, and video/photos) and surveys to surface the perspectives and visions of minoritized youth. The research describes what student agency looks like as youth – who have had no prior CS learning experiences – use CS as a tool to resist marginalization and dehumanizing school contexts, while declaring their own "rightful presence" in CS classrooms. Findings demonstrate the importance for CS curricula and pedagogy to center the lives of students in ways that are consequential for minoritized youth. This would support deeper engagement with content learning and student agency with computing. [ABSTRACT FROM AUTHOR]

Highly efficient algorithms for solving the time constrained shortest path problem have been highlighted over the past decades to reduce the cost of vehicle travel in the road network. The paper presents a novel graph algorithm comprising three stages to acquire a time constrained shortest path between any two nodes on the map. In the first stage, the undirected graph is transformed into a directed graph (DT graph) by deleting edges that must not be included in any of the time constrained shortest paths. A variant DT tree with the destination as the root and the source as the leaf is then constructed from the DT graph in the second stage. By finding the minimal difference value between leaves and the root of the variant DT tree, we can eventually obtain a time constrained shortest path from the variant DT tree in the third stage. Experimental results show that our algorithm not only requires less running time than some classical graph algorithms but also can work immediately in the first stage without knowing the information of both the destination and a specific time constraint. [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]

In the following paper titled " I Evaluating Industry 4.0 Implementation Challenges Using Interpretive Structural Modelling and Fuzzy-Analytic Hierarchy Process i " the authors contribute to the Industry 4.0 related works by identifying, modeling, analyzing and prioritizing the challenges in implementing Industry 4.0 in manufacturing industries. The paper introduces a smart support system for selecting a group of reviewers to evaluate a particular problem, such as a research proposal or a research paper. The aim of this Guest Edition of I Cybernetics and Systems i is to present a wide-ranging scale of concepts and processes being currently researched, developed, and evaluated in real life settings in anticipation of incoming Industry 4.0 era. [Extracted from the article]

As algorithmic decision-making and data collection become pervasive in higher education, how can educators make sense of the systems that shape life and learning in the twenty-first century? This paper outlines a systematic literature review that investigated gaps in the current framing of data and faculty development, and explores how these gaps prevent the formulation of potential pathways and principles for fostering educators' data literacy. The analysis of 137 papers through classification by relevant categories and key word mapping shows that there is little attention on higher education teachers. It also makes clear that most approaches to educators' data literacy address management and technical abilities, with less emphasis on critical, ethical and personal approaches to datafication in education. The authors conceptualize this situation as a 'complicated' approach to data literacy in the academic profession, as opposed to a complex vision which would bundle management and technical skills together with a critical, systemic approach to professional learning and data. [ABSTRACT FROM AUTHOR]

In Canada, 100,000 people suffer a traumatic brain injury (TBI) every year. The prevalence of moderate to severe TBI is highest for young men, who will live an average of 50 years with this chronic condition associated with physical, emotional and cognitive deficits. Meal preparation, a complex activity with high safety risks, is one of the most significant activities impacted by TBI. Technology shows great promise to support their overall functioning, but no context-aware technology is available to support meal preparation for this population. The main goal of this study was to design and test a technology to support meal preparation with and for persons with severe TBI living in a supported-living residence. As part of a transdisciplinary technology project linking rehabilitation and informatics, COOK (Cognitive Orthosis for coOKing) was designed with and for future users and stakeholders with a user-centred design methodology. COOK was implemented in three participants' apartments, and its usability was evaluated at 1, 3 and 6 months post-implementation. COOK is a context-aware assistive technology consisting of two main systems: security and cognitive support system. After implementation of COOK, participants were able to resume safe preparation of meals independently. Usability testing showed good effectiveness and an acceptable level of satisfaction. COOK appears promising for rehabilitating clients with cognitive disabilities, improving safety in a home environment, and diminishing the need for human supervision. Future studies will need to explore how COOK can be adapted to a broader TBI population, other environments, and other clienteles. This paper presents a promising context-aware assistive technology for cognition designed with and for clients with severe brain injury to support their independence in meal preparation; COOK, (Cognitive Orthesis for coOKing) is the first cooking assistant in which evidence-based cognitive rehabilitation interventions have been translated into smart technological assistance, to support cognition and ensure safety in a real-life context; Its context-aware characteristic ensures that users receive the assistance they need at the right time and at the right moment. The long-term perspective regarding the use of COOK in clinical practice is promising as this technology has the potential of becoming an additional means of supporting the rehabilitation of people with cognitive impairments and becoming part of a comprehensive solution to help them live at home more independently. [ABSTRACT FROM AUTHOR]

This paper contributes to a project that maps the concept of 'data provenance' into qualitative data research. Data provenance is a concept from computer science that allows us to trace the history of sets of data to determine the accuracy and validity of a database. We transform this into a critical concept by arguing that data provenance can be used to trace the acts of governance and rhetoric. We then analyse the forms of discursive power that shape transactions in data. Our approach can create a history of the governance and justifications that are used to build and assemble datasets from multiple sources. Presently, data often lacks this information about its own discursive origins, unlike other forms of data provenance. Critical data provenance gives us a model for thinking about how governance could be mapped onto data. And thus, critical data provenance is also a framework for critiquing the justifications used when dataset owners acquire data – for instance, whether data stewards or users are encouraged to be 'open', to 'share', or be 'transparent'. To this end, we demonstrate this model of thinking and provide the analytical tools necessary to redeploy these ideas into new contexts. [ABSTRACT FROM AUTHOR]

The paper proposes a novel index to classify how well UK Computer Science courses articulate cybersecurity-related content through their course/module pages. The aim of this work is to raise awareness among British Universities to pay more attention to include and standardize cybersecurity content in computer science courses. Our results show that 80% of analyzed courses scored 1 or 2-stars on a 5-Stars scale. The results also suggest the need for a formal delivery of cybersecurity content from the first year of the courses and possibly in a collaborative manner with the British Computer Society (BCS). To emphasize cybersecurity education in mitigating security lapses, the analogy is: it is better if most people know how to use a match than to train many fire-fighters. [ABSTRACT FROM AUTHOR]

Background and Context: Though computer science education is marked by a pronounced racial participation gap, there is little research about effective ways that teachers can be supported in creating racially-just and equitable computer science learning opportunities for students. Objectives: This paper examines how teachers engage in learning about race and equity in computer science education during professional development. Method: Drawing from data collected from 94 participants attending a summer week-long Exploring Computer Science workshop, this mixed-methods study revealed how key curricular and instructional features of professional development foster race-conscious discussions and shifts in beliefs and agency around broadening participation in computing. Findings: Given the importance of developing teacher capacity to increase opportunities for students of color in computing classrooms, the findings of this study highlight how intentionally integrating race education in the center of professional development for teachers can support teachers' equity-based beliefs and practices. Implications: Professional development for teachers that seeks to broaden participation in computing is supported by long-term professional learning that explicitly center issues of race and equity in the curriculum. [ABSTRACT FROM AUTHOR]

Algorithms that quantify the similarity between two sequences of data date back to the mid 20th century. Sequence comparison continues to be active area of research in mathematics, statistics, and computer science, with applications to a wide number of fields including, biology, marketing, and linguistics. While many methods exist for comparing sequences of discrete events, this paper presents a novel method to compare such sequences while also utilizing information available from non-uniform time intervals between events. The Sequence Alignment with Non-Uniform Time Intervals (SAWNUTI) method, an extension of the Smith-Waterman and Needleman-Wunch algorithms, is described and evaluated using a simulation study and two real-world medical data sets (diabetes and eye tracking). Results illustrate the necessity of this method when time is important to consider in the comparison of sequences. [ABSTRACT FROM AUTHOR]

As an environmental protection fuel, methanol is widely used in national economy. The tremendous price fluctuation of methanol makes risk avoidance an important issue. However, traditional normal hypothesis in the existing literature underestimates the potential risk and leads to an inefficient hedging strategy, so we studied hedging strategy with methanol futures contracts based on the skewed normal hypothesis. Considering that copula methods allow us to construct a flexible multivariate distribution when solving the problem of asymmetry and nonlinearity, the dependence structure between spot and futures return is modelled through copula functions in this paper. Since likelihood equations do not have explicit solutions in the context of skewed normal, Genetic Algorithm is used to estimate the parameters of a skew normal distribution. To deal with the complexity of the proposed model, the artificial bee colony algorithm is adopted to search for the optimal solutions. Empirical results show that skewed normal distribution can represent the distribution characteristics of return better and improve the hedging effectiveness. Gaussian copula describes the dependence structure of spot and futures quite well. The algorithms designed to obtain the parameters in the marginal distributions and to find the optimal hedge ratio are effective and feasible. [ABSTRACT FROM AUTHOR]

Movement analysis has become an integral part of many disciplines, yet with relatively little overlap. A foresight paper in this journal entitled "Towards an integrated science of movement: converging research on animal movement ecology and human mobility science" argued for a better integration of concepts across the divide of animal and human movement, which would lead to the Integrated Science of Movement, but did so from a top-down perspective based on a series of expert workshops. We argue that for a solid establishment of the Integrated Science of Movement, a bottom-up approach is necessary, one based on existing literature which identifies similarities and differences across disciplines. We therefore review, compare, and contrast movement analysis methodologies from GIScience, movement ecology, geography, transportation, public health, computer science, and physics. We structure our review along the dichotomy of individual versus population-based movement or, using terminology from wildlife ecology, between the Lagrangian and Eulerian perspectives. We further introduce a new unifying framework for movement research that is sufficiently general to cover any type of movement study in any discipline and that spans the Lagrangian/Eulerian divide, with the ambitious goal to bridge the gap between disciplines and lay a solid foundation for a new Integrated Science of Movement. [ABSTRACT FROM AUTHOR]

International Journal of Systems Science (IJSS) is an international journal in the fields of Automation & Control Systems, Computer Science, and Operations Research & Management Science. This paper is a celebration of the 50th anniversary of IJSS. A Web of Science count of 7528 documents were derived from 1970 to 2019 as data sources for the bibliometric analysis. First, the fundamental characteristics of the documents were identified from the bibliometric indicators, and features of keywords were revealed over the half century. A timeline and occurrence analyses were conducted via the software tools, through which popular keywords were visualised in different time periods. These were then grouped into four categories by a hierarchical clustering method, and emerging keywords were selected using burst detection analysis. This was followed by the Autoregressive Integrated Moving Average modelling to predict the future research trends in the four clusters as evidenced in the historical data. Documents were discussed in the recent 20 years towards guiding scholars in three aspects, i.e. problems addressed, popular methodologies, and impact in the relevant fields. Finally, a summary of the main findings was given in the conclusions. [ABSTRACT FROM AUTHOR]

The aim of the paper is to present methodology to personalise learning using learning analytics and to make further decisions on suitability, acceptance and use of personalised learning units. In the paper, first of all, related research review is presented. Further, an original methodology to personalise learning applying learning analytics in virtual learning environments and empirical research results are presented. Using this learning personalisation methodology, decision-making model and method are proposed to evaluate suitability, acceptance and use of personalised learning units. Personalised learning units evaluation methodology presented in the paper is based on (1) well-known principles of Multiple Criteria Decision Analysis for identifying evaluation criteria; (2) Educational Technology Acceptance & Satisfaction Model (ETAS-M) based on well-known Unified Theory on Acceptance and Use of Technology (UTAUT) model, and (3) probabilistic suitability indexes to identify learning components' suitability to particular students' needs according to their learning styles. In the paper, there are also examples of implementing the methodology using different weights of evaluation criteria. This methodology is applicable in real life situations where teachers have to help students to create and apply learning units that are most suitable for their needs and thus to improve education quality and efficiency. [ABSTRACT FROM AUTHOR]

Academic research on automated vehicles (AVs) has to date been dominated by the fields of engineering and computer science. Questions of how this potentially transformative technology should be governed remain under-researched and tend to concentrate on governing the technology's early development. We respond in this paper by exploring the possible longer-term effect of government (lack of) intervention. The paper tests the hypothesis that a "laissez-faire" governance approach is likely to produce less desirable outcomes in a scenario of mass uptake of AVs than would a well-planned set of government interventions. This is done using two prominent themes in transport policy - traffic flow and accessibility - in a scenario of high market penetration of Level-5 automated vehicles in capitalist market economies. The evidence used is drawn from a literature review and from the findings of a set of workshops with stakeholders. We suggest that a laissez-faire approach will lead to an increase in traffic volume as a result of a growing population of "drivers" and a probable increase in kilometres driven per passenger. At the same time, the hoped-for increases in network efficiency commonly claimed are not guaranteed to come about without appropriate government intervention. The likely consequence is an increase in congestion. And, with respect to accessibility, it is likely that the benefits of AVs will be enjoyed by wealthier individuals and that the wider impacts of AV use (including sprawl) may lead to a deterioration in accessibility for those who depend on walking, cycling or collective transport. We consider the range of possible government intervention in five categories: Planning/land-use; Regulation/policy; Infrastructure/technology; Service provision; and Economic instruments. For each category, we set out a series of interventions that might be used by governments (at city, region or state level) to manage congestion or protect accessibility in the AV scenario described. Many of these (e.g. road pricing) are already part of the policy mix but some (e.g. ban empty running of AVs) would be new. We find that all interventions applicable to the management of traffic flow would also be expected to contribute to the management of accessibility; we define a small number of additional interventions aimed at protecting the accessibility of priority groups. Our general finding is that the adoption of a package of these interventions could be expected to lead to better performance against generic traffic-flow and accessibility objectives than would a laissez-faire approach, though questions of extent of application remain. In our conclusions, we contrast laissez-faire with both anticipatory governance and "precautionary" governance and acknowledge the political difficulty associated with acting in the context of uncertainty. We point out that AVs do not represent the first emerging technology to offer both opportunities and risks and challenge governments at all levels to acknowledge the extent of their potential influence and, in particular, to examine methodically the options available to them and the potential consequences of pursuing them. [ABSTRACT FROM AUTHOR]

Quantum Machine Learning (QML) is one of the core research fields in the larger paradigm of Quantum Computing (also known alternatively as Quantum Information). In recent years, researchers have taken deep interest in QML, given the potential time and cost advantages that solutions to real-life problems using QML algorithms provide, in comparison to their classical (or digital) machine learning equivalents. This is still a very new and exciting area of research with new algorithms and their uses being developed almost every other day. Deep research interest in this area has picked up only in the past 5–6 years. Given the background, this paper focuses on studying Scopus and Web of Science databases for the past 6 years (2014–2019) to identify various publication trends in the areas of Quantum Machine Learning. The authors have done an in-depth study of the Scopus and Web of Science publication data pertaining to this area and have come up with interesting insights. The survey covers 276 publications in Scopus and 154 publications in Web of Science. From the Scopus database, it is found that there has been a consistent growth in the number of publications in this period. Four research areas, namely, Physics, Astronomy, Computer Science, and Mathematics, have contributed 68.1% of the research publications. The USA leads the top 10 countries with nearly half (49.2%) of the research publications. A total of 148 patents have been published with 94 of these being published in the last four years (2016–2019). This essentially translates to one patent for every two publications. The Web of Science database, though bringing out 154 publications in the period, shows similar trends across the metrics. We have carried out a comparative study of some of the metrics in Scopus and Web of Science databases. Overall the study identifies the top 10 Institutions, authors, and research journals. [ABSTRACT FROM AUTHOR]

Computing hardware has mostly thrashed out the physical limits for speeding up individual computing cores. Consequently, the main line of progress for new hardware is growing the number of computing cores within a single CPU. This makes the study of efficient parallelization schemes for computation-intensive algorithms more and more important. A natural precondition to achieving reasonable speedups from parallelization is maintaining a high workload of the available computational resources. At the same time, reproducibility and reliability are key requirements for software that is used in industrial applications. In this paper, we present the new parallelization concept for the state-of-the-art MIP solver FICO Xpress-Optimizer. MIP solvers like Xpress are expected to be deterministic. This inevitably results in synchronization latencies which render the goal of a satisfying workload a challenge in itself. We address this challenge by following a partial information approach and separating the concepts of simultaneous tasks and independent threads from each other. Our computational results indicate that this leads to a much higher CPU workload and thereby to an improved, almost linear, scaling on modern high-performance CPUs. As an added value, the solution path that Xpress takes is not only deterministic in a fixed environment, but also, to a certain extent, thread-independent. This paper is an extended version of Berthold et al. [Parallelization of the FICO Xpress-Optimizer, in Mathematical Software - ICMS 2016: 5th International Conference, G.-M. Greuel, T. Koch, P. Paule, and A. Sommere, eds., Springer International Publishing, Berlin, 2016, pp. 251-258] containing more detailed technical descriptions, illustrative examples and updated computational results. [ABSTRACT FROM AUTHOR]

In this paper, the authors define a new approach that addresses the challenge of efficiently designing informational artefacts for optimal knowledge acquisition, an important issue in cognitive ergonomics. Termed Industrial Knowledge Design (or InK'D), it draws from information-related (e.g. informatics) and neurosciences-related (e.g. neuroergonomics) disciplines. Although it can be used for a broad scope of communication-driven business functions, our focus as learning professionals is on conveying knowledge for purposes of training, education, and performance support. This paper discusses preliminary principles of InK'D practice that can be employed to maximise the quality and quantity of transferred knowledge through interaction design. The paper codifies tacit knowledge into explicit concepts that can be leveraged by expert and non-expert knowledge designers alike. [ABSTRACT FROM PUBLISHER]

This theoretical paper explores the need for enhanced, intersectional computing identity theory for the purpose of developing a diverse group of computer scientists for the future. Greater theoretical understanding of the identity formation process specifically for computing is needed in order to understand how students come to understand themselves as computer scientists. To ensure that the next generation of computer scientists is diverse, this paper presents a case for examining identity development intersectionally, understanding the ways in which women and underrepresented students may have difficulty identifying as computer scientists and be systematically oppressed in their pursuit of computer science careers. Through a review of the available scholarship, this paper suggests that creating greater theoretical understanding of the computing identity development process will inform the way in which educational stakeholders consider computer science practices and policies. [ABSTRACT FROM AUTHOR]

Moth-flame Optimisation Algorithm (MFO) is a new metaheuristics optimisation algorithm presented by Mirjalili in 2015 which inspired by the navigation method of moths in nature. It has gained a huge interest due to its impressive characteristics mainly: no derivation information needed in the starting phase, few numbers of parameters, simple in implementation, scalable and flexible. Till now, different variants to solve various optimisation problems such as binary, real(continuous), constraint, single-objective, multi-objective, and multimodal MFO has been introduced. Many research papers have been presented and summarised. In this review, a general overview of MFO is presented at first. Then, different variants of MFO are described which are classified into three classes: modified, hybridised, and multi-objective. Furthermore, applications of MFO in Engineering, Computer Science, Wireless Sensor Networks, and other fields are discussed. Finally, many possible and future directions are provided. [ABSTRACT FROM AUTHOR]

This paper deals with the reconstruction of small-amplitude perturbations in the electric properties (permittivity and conductivity) of a medium from boundary measurements of the electric field at a fixed frequency. The underlying model is the three-dimensional time-harmonic Maxwell equations in the electric field. Sensitivity analysis with respect to the parameters is performed, and explicit relations between the boundary measurements and the characteristics of the perturbations are found from an appropriate integral equation and extensive numerical simulations in 3D. The resulting non-iterative algorithm allows to retrieve efficiently the centre and volume of the perturbations in various situations from the simple sphere to a realistic model of the human head. [ABSTRACT FROM AUTHOR]

Background and Context: Non-traditional training grounds such as coding boot camps that attract a higher proportion of women are important sites for understanding how to broaden participation in computing. Objective: This work aims to help us better understand the women choosing boot camps and their pathways through these camps and into the computing workforce. Method: This paper reports on a longitudinal, qualitative study investigating female boot camp attendees. Findings: Findings show that women attending boot camps are career changers that develop an interest in software development too late to major in CS, discovering a post-college enjoyment of programming undertaken to support work goals at a current job or an aspirational job. Implications: Women at boot camps illustrate a missed opportunity to diversify postsecondary CS classrooms when not recruited early, not given interdisciplinary options, not exposed to enjoyable programming tasks, and not exposed to the array and number of job prospects. [ABSTRACT FROM AUTHOR]

Parallel computing has led to fundamental changes in almost all research areas associated with computer science; cryptography is no exception. Besides improved speed and resource utilization, parallel cryptography is also promising from the security point of view. In particular, cryptographic hash functions (CHFs) – "the swiss knife" of the cryptography toolkit – stand to gain a lot from parallelism. Consequently, there has been an increasing interest in research towards the development of parallel CHFs for faster, more secure and more efficient hashing, particularly since the competition for the SHA-3 standard. This paper attempts to consolidate the research efforts in the field of parallel hashing, exploring various approaches in this direction. Within each approach discussed in the article, CHFs have been classified on the basis of construction and their design, implementation and performance have been explained, with the primary focus on parallelism. Finally, a broad temporal overview of the developments in the field of parallel hashing has been presented. [ABSTRACT FROM AUTHOR]

The invention of the computer has led to the establishment of a new research paradigm, computation, which has recently become more and more popular in scientific exploration. However, computation is not well represented in high school and university curricula in science and engineering, although it applies to a wide range of disciplines beyond computer science and software engineering. In light of the increasing need to provide students with computational education, this paper presents a novel way to develop computational thinking among students. The proposed approach is based on the implementation of Papert's theory of constructionism in electronic spreadsheets. In this approach, students build their knowledge while constructing the difference equation that describes a physical (or engineering) phenomenon, based on specific cases investigated in the spreadsheet. The method does not require the students to write code or perform complex calculations in the spreadsheet and makes it possible to teach advanced subjects at a relatively early stage. The method is demonstrated through contents taken from the secondary and tertiary curricula in mechanics and electromagnetism. [ABSTRACT FROM AUTHOR]

This study aims to examine research collaboration between universities and industry in the field of computer science using bibliometric methods. To further understand the impact of individual countries on university-industry (UI) collaboration, data were retrieved from the computer science journal papers included in the Science Citation Index and published during the period 2002--2011. The density, degree centrality, betweenness centrality, and closeness centrality of UI collaborative networks were calculated in order to ascertain the core countries involved in international UI collaboration. This study investigates university-industry collaborative papers (UI papers) at the global and country levels. At the global level, the results show an increasing trend in UI papers and a stable UI collaboration ratio during the last decade. The average number of authors for UI papers is 4.13, which is higher than that for all other papers. Most UI papers result from two-institution collaboration, but we observed an increase in the number of UI papers produced by multiple universities and industrial entities. At the country level, the results also show that international UI paper collaboration has intensified. Meanwhile, the USA is the dominant collaborative partner with many countries and has produced the highest number of UI papers globally. [ABSTRACT FROM AUTHOR]

A global trend nowadays is shifting the attention from the overall university ranking towards the ranking in a particular scientific field: “Ranking by Subject” and/or “Field Ranking”. The objective of the research presented in this paper is the review of the Information and Communication Technologies (ICT) aspect of the universities performance. The major concern of the study is the uncertainty and sensitivity of ICT field ranking, regarding the weighting scheme of a particular ranking methodology. The paper thus examines the ICT field-based section of the Quacquarelli Symonds (QS) and URAP rankings and gives a detailed comparison of the stability of these ranking methods. According to the results, URAP ICT ranking is shown to be more stable than QS ICT ranking, with a lower level of uncertainty and sensitivity to different model assumptions. Moreover, we gave an overview of particular standings of Indian universities in both QS and URAP ICT rankings, tackling the issue of the uncertainty and sensitivity of their positions. [ABSTRACT FROM AUTHOR]

Building Computational Thinkers, a three-year research study, explored how educators and designers can most effectively support the development of computational thinking capacity, and how these learning experiences could be customized to meet the needs of different learners. This research study focused on three specific exhibit design approaches that conveyed problem decomposition content in The Science Behind Pixar (Pixar), a 13,000 square foot traveling exhibition about the computer science, mathematics, and science behind Pixar's innovative films. Phase One investigated how novice learners could be supported to interact with exhibits and understand problem solving strategies that tackle complex, creative challenges in computer programming. Phase Two investigated the affordances of these exhibits to build capacity, feelings of efficacy, and interest in problem decomposition content in middle and high school youth. The findings in this paper describe the types of scaffolds that can be used to support computational thinking in novice youth, as well as how a combination of exhibit approaches were found to increase youth perceptions, understanding, and beliefs of computer programming. It will also discuss how two exhibit approaches worked particularly well for engaging girls in problem decomposition content. [ABSTRACT FROM AUTHOR]

Responses to breaches in cybersecurity are increasingly reliant on criminal justice practitioners. However, while the demand for criminal justice participation in cybersecurity increases daily, most universities are lagging in their educational and training opportunities for students entering criminal justice agencies. This paper discusses the need for cybersecurity programs in criminal justice, and examines how the evolution of this "new crime" has become an issue for criminal justice professionals in addition to computer science experts. A review of existing cybersecurity programs in Texas suggests that most four-year universities have yet to develop courses/programs in criminal justice. Course recommendations, sample syllabi for cybersecurity courses in criminal justice, and recommendations for development of these programs are included. [ABSTRACT FROM AUTHOR]

Objective: Neuropsychology is poised for a fundamental shift as we modernize the ways in which behavior is measured. The amount and complexity of data generated by these new methods will be several orders of magnitude greater than what is currently created by analog measures and will quickly adopt characteristics of "Big Data." Adequate preparation for managing the influx of data will be critical for technology integration and modernization to be successful. Drawing from information technology, mathematics, statistics, computer science, and engineering, as well as, biology, genetics, and medicine, the field of biomedical informatics has rapidly evolved from its early days in computational biology to a burgeoning independent discipline that has much to offer neuropsychology. Method: Following a critical review of the relevant literature, the present article (1) provides an introductory overview of biomedical informatics and how these concepts are relevant to neuropsychology; (2) describes how biomedical informatics applications can be utilized to leverage existing data sources more effectively; and (3) discusses ideas for future developments designed to facilitate integration of new data derived from novel, technologically driven measurement tools. Within this context, applications intended for use by both the individual neuropsychologist to increase clinical efficiencies, as well as, larger field-wide initiatives intended to generate new information and derive new knowledge are discussed. Conclusions: By no means a comprehensive review of biomedical informatics, the present paper highlights that our approach to data needs to become a multidisciplinary endeavor in order to develop applications capable of effectively utilizing modern data sources. [ABSTRACT FROM AUTHOR]

Geospatial librarianship has always been inherently tied to technology, requiring that GIS librarians have specialized computer literacy. In recent years, the push for open science, transparency, and improved reproducibility in research has led to increased use of open source geospatial technology. These developments have led to a blending of GIScience with the emerging field of Data Science, and many students and researchers are increasingly using free and open source programming languages to complement or replace traditional GIS software. New data formats, modern modes of data exchange, and the data as a service trend require an intricate understanding of computer science. If GIS librarians are to meet the needs of current and future patrons, code-literacy will soon be a necessity, yet a discussion of these tools and skills are lacking in the literature of geospatial librarianship. This paper discusses the present revolution in geospatial technology, recommending an integration of coding skills into the most elemental levels of the Core Competencies for GIS Librarianship. We review two programming languages, R and Python, for their suitability for librarians wishing to advance their technical skills by either learning a new language or learning to program for the first time. Drawing from our own experiences, we discuss the potential of coding to transform how GIS librarians engage with their work. [ABSTRACT FROM AUTHOR]

This paper examines the ways in which computer science and a selection of multisensory digital devices modulate the term culture. Three self-identified, 'cultural computing' devices are examined: ZENetic, Alice's Adventures and GRIOT'S Japanese Renku. The devices variously configure relationships between bodies and culture so that the body is thought to provide a window into particular cultures, as well as a universal tool of their transmission. These delineations of the term culture occur in continuity with surrounding political histories and projects, including racial and ethnic ones. Dividing the body between the extra cultural and the culturally specific works to secure the communicability as well as the exclusivity of cultural practices. It is an instance of what Merleau-Ponty terms a divergence, a gap within the body between two imbricated parts. In this way, these devices present culture as a source of innovation that combats global and abstracted computing practices. [ABSTRACT FROM AUTHOR]