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This paper emerges from an interdisciplinary collaboration between prosthesis-using disabled dance artists, computer scientists, dance researchers and engineers to explore the transformative potential of digital technologies to co-create aesthetically personalised prosthetics from dance movements. Beginning with the dancers performing improvised movement sequences in motion capture suits, which drove a computational design algorithm, an 'aesthetic seed' for each dancer was generated: a kind of personal signature from their movement. These seeds were then algorithmically mapped onto the shapes of prosthetic limb covers that could be 3D printed in a variety of materials. The paper will share some of the reflections from the dancers on how the process generated questions about agency, appropriation, ownership and the political implications of disability as a site of resistance. It will suggest some ways in which digital methods can offer disabled artists different routes towards making and sharing work, whilst foregrounding the importance of inclusion to challenge normative thinking around what 'connection' and 'access' means in the context of digital innovation. [ABSTRACT FROM AUTHOR]

This paper addresses the solution of a cardinality Boolean quadratic programming problem using three different approaches. The first transforms the original problem into six mixed-integer linear programming (MILP) formulations. The second approach takes one of the MILP formulations and relies on the specific features of an MILP solver, namely using starting incumbents, polishing, and callbacks. The last involves the direct solution of the original problem by solvers that can accomodate the nonlinear combinatorial problem. Particular emphasis is placed on the definition of the MILP reformulations and their comparison with the other approaches. The results indicate that the data of the problem has a strong influence on the performance of the different approaches, and that there are clear-cut approaches that are better for some instances of the data. A detailed analysis of the results is made to identify the most effective approaches for specific instances of the data. [ABSTRACT FROM AUTHOR]

The present essay is a reflection inspired by the excellent book “Human Face of Computing” (editor Cristian S. Calude, published by Imperial College, Press, 2016) that is the outcome of a participatory exploration carried out by and insider (C. Calude) on the history of computing science with with its wide and deep ramification that are influencing all human activities. The book is based on interviews with outstanding researchers in computing science, mathematics, Internet, physics and technological sciences who have landmark contributions to computing science and are deeply interested in its applications, impact, uses and abuses in social life. The book explores the consequences of this field on the quality, production and democratization of knowledge.

The distance between two objects determines how far apart they are with respect to each other. In this paper, we provide an overview of the distance concept in multimedia phylogeny, a novel research field that aims at discovering the phylogenetic relationships among digital objects that belong to the same population. With applications in digital forensics, copyright enforcement, and security, existing approaches are often based on dissimilarity computations among digital objects in a nonmetric space, but with enough information to correctly reconstruct the underlying relationships of these objects. As we discuss throughout the paper, a proper and well-designed dissimilarity is paramount for differentiating whether two multimedia objects are related and, also, the directionality of such relationship. In phylogeny setups, there is also the additional requirement of low complexity: fast and accurate dissimilarity measures to cope with the massive amount of data we often have to handle. [ABSTRACT FROM AUTHOR]

Computing Science and Systems Theory can gain much from unified mathematical models and methodology, in particular formal reasoning ("letting the symbols do the work"). This is achieved by a wide-spectrum formalism. The language uses just four constructs, yet suffices to synthesize familiar notations (minus the defects) as well as new ones. It supports formal calculation rules convenient for hand calculation and amenable to automation. The basic framework has two main elements. First, a functional predicate calculus makes formal logic practical for engineers, allowing them to calculate with predicates and quantifiers as easily as with derivatives and integrals. Second, concrete generic functionals support smooth transition between pointwise and point-free formulations, facilitating calculation with functionals and exploiting formal commonalities between CS and Systems Theory. Elaborating a few small but representative examples shows how formal calculational reasoning about diverse topics such as mathematical analysis, program semantics, transform methods, systems properties (causality, LTI), data types and automata provides a unified methodology.

Goal of this article is to document evolution of the Interface and its Symposia, from their conception and birth when small data were analyzed with Statistics in the mid 20th Century until Big Data are now analyzed with Data Science in the early 21st Century. Wilfrid Dixon's 1961 BMD Statistical Program Package was a pioneer predictor of Computing in Statistics, and Arthur Samuel's 1965 presentation on using game-branch probabilities in teaching ILLIAC I to play checkers was a pioneer predictor of Statistics in Computing. Such predictors produced a perception that future interactions of Computing and Statistics might constitute a significant and productive Interface of Computing and Statistics. Another perception included Computing and Statistics with Computing in Statistics and Statistics in Computing. This presented the challenge of organizing an Interface Symposium, to introduce the Interface to a vibrant environment for Computing and Statistics in Southern California. Presentations at the Symposia reveal that small data are in the process of becoming Big Data, while Computing in Statistics and Machine Learning are becoming the Interface, and the Interface is becoming Data Science. Data Science, the first comprehensive Journal on Data Science, another 1 of the 15 ASA Journals as well as 3 of 21 ASA Sections constitute a proud heritage for Interface and its Symposia. Perspective of the article is shaped by 60 years of pioneering and continuously contributing to the Interface and its Symposia, which few can match. WIREs Comput Stat 2014, 6:367-377. doi: 10.1002/wics.1316 For further resources related to this article, please visit the . Conflict of interest: The author has declared no conflicts of interest for this article. [ABSTRACT FROM AUTHOR]

The African American Researchers in Computing Sciences (AARCS) program aims to broaden the participation of African Americans from historically Black colleges and universities in the computing sciences at the faculty and research scientist levels. The AARCS program serves as a model that can be incorporated into larger programmatic endeavors at institutions of higher education to target African Americans and other underrepresented groups. This study highlights features of the program, presents key research questions and findings of the evaluation, and generates specific programmatic knowledge for those interested in interventions designed to increase the representation of African American computing scientists, as well as other scientific-related disciplines within higher education. [ABSTRACT FROM AUTHOR]

Abstract: This paper explores the origins and content of neurocybernetics and its links to artificial intelligence, computer science and knowledge engineering. Starting with three remarkable pieces of work, we center attention on a number of events that initiated and developed basic topics that are still nowadays a matter of research and inquire, from goal directed activity theories to circular causality and to reverberations and learning. Within this context, we pay tribute to the memory of Prof. Ricciardi documenting the importance of his contributions in the mathematics of brain, neural nets and neurophysiological models, computational simulations and techniques. [Copyright &y& Elsevier]

According to Csikszentmihalyi (1990, pg. 4), flow is "an optimal, extremely enjoyable state in which people are so involved in an activity that nothing else seems to matter...". In this study flow has been measured with the Flow Questionnaire (Csikszentmihalyi & Csikszentmihalyi, 1988). The research was conducted on the sample of 200 students. The aim of this research was to determine whether there was a difference in the flow experience during studies among the students of the Faculty of Teacher Education (FTE) (Informatics, Primary education) and the students of the Faculty of Science (FS), Department of Mathematics (Teachers). It was also investigated which variables (knowledge and skills in computing science/informatics, subjective well-being) contribute to the more intense and more frequent flow experience during studies. Conclusions: There were no statistically significant differences in flow between students studying at the FTE and FS found, and the average flow during studies for both groups was M=4.93, measured on the scale ranging from 1 to 8. The proportion of the variance of flow explained by the inspected variables was 37.6% and it was statistically significant (F=20.68; df=6; p<0.001), but the only significant predictors were positive affect (β=045; p<0.001) and negative affect (β=-0.25; p<0.001). Students' grades were used as means of measuring knowledge and skill; however, it was found that they were not connected with the intensity or frequency of the occurrence of flow. [ABSTRACT FROM AUTHOR]

Enrollment in Computing Science university programs is at a dangerously low level. A major reason for this is the general lack of interest in Computing Science by females. In this paper, we discuss our experience with using a computer game construction environment as a vehicle to encourage female participation in Computing Science. Experiments with game construction in grade 10 English classes showed that females enjoyed this activity as much as males and were just as successful. In this paper, we argue that: a) computer game construction is a viable activity for teaching higher-order thinking skills that are essential for Science; b) computer game construction that involves scripting teaches valuable Computing Science abstraction skills; c) this activity is an enjoyable introduction to Computing Science; and d) outcome measures for this activity are not male-dominated in any of the three aspects (higher-order thinking, Computing Science abstraction skills, activity enjoyment). Therefore, we claim that this approach is a viable gender-neutral approach to teaching Computing Science in particular and Science in general that may increase female participation in the discipline. [Copyright &y& Elsevier]

Which cultural factors offer an explanation for girls' reluctance to choose technological subjects, such as computing science? This question is explored by critically analysing data from individual interviews and focus-group interviews with 86 Dutch adolescents. According to what the authors call the 'self-to-profession matching' theory, adolescents systematically compare what they are good at, what they want from a job, and what activities they like, with their (in)correct expectations of a particular profession. Examples are given of how this process can lead to gender-based segregation in computing science. The interviews illustrate this tendency when girls say, for instance, 'I'd rather work with people than with computers'. However, by analysing the interview material 'against the grain', the authors argue that the so-called 'self-to-prototype matching' theory may offer a better description of how a choice of profession is made. Adolescents tend to choose based on a prototype of someone working in a profession, even when they know this prototype is incorrect, and even when this prototype includes characteristics that are irrelevant for that profession, such as sexual attractiveness. [ABSTRACT FROM AUTHOR]

Background and objectives: Epidemiological models of epidemic spread are an essential tool for optimizing decision-making. The current literature is very extensive and covers a wide variety of deterministic and stochastic models. However, with the increase in computing resources, new, more general, and flexible procedures based on simulation models can assess the effectiveness of measures and quantify the current state of the epidemic. This paper illustrates the potential of this approach to build a new dynamic probabilistic model to estimate the prevalence of SARS-CoV-2 infections in different compartments. Methods: We propose a new probabilistic model in which, for the first time in the epidemic literature, parameter learning is carried out using gradient-free stochastic black-box optimization techniques simulating multiple trajectories of the infection dynamics in a general way, solving an inverse problem that is defined employing the daily information from mortality records. Results : After the application of the new proposal in Spain in the first and successive waves, the result of the model confirms the accuracy to estimate the seroprevalence and allows us to know the real dynamics of the pandemic a posteriori to assess the impact of epidemiological measures by the Spanish government and to plan more efficiently the subsequent decisions with the prior knowledge obtained. Conclusions: The model results allow us to estimate the daily patterns of COVID-19 infections in Spain retrospectively and examine the population's exposure to the virus dynamically in contrast to seroprevalence surveys. Furthermore, given the flexibility of our simulation framework, we can model situations —even using non-parametric distributions between the different compartments in the model— that other models in the existing literature cannot. Our general optimization strategy remains valid in these cases, and we can easily create other non-standard simulation epidemic models that incorporate more complex and dynamic structures. [ABSTRACT FROM AUTHOR]