Computer Science Framework Research Articles

Analyzing Non-Markovian Systems by Using a Stochastic Process Calculus and a Probabilistic Model Checker

The non-Markovian systems represent almost all stochastic processes, except of a small class having the Markov property; it is a real challenge to analyze these systems. In this article, we present a general method of analyzing non-Markovian systems. The novel viewpoint is given by the use of a compact stochastic process calculus developed in the formal framework of computer science for describing concurrent systems. Since phase-type distributions can approximate non-Markovian systems with arbitrary precision, we approximate a non-Markovian system by describing it easily in our stochastic process calculus, which employs phase-type distributions. The obtained process (in our calculus) are then translated into the probabilistic model checker PRISM; by using this free software tool, we can analyze several quantitative properties of the Markovian approximation of the initial non-Markovian system.

Redefining Creativity in the Era of AI? Perspectives of Computer Scientists and New Media Artists

ABSTRACT Artificial intelligence (AI) has breached creativity research. The advancements of creative AI systems dispute the common definitions of creativity that have traditionally focused on five elements: actor, process, outcome, domain, and space. Moreover, creative workers, such as scientists and artists, increasingly use AI in their creative processes, and the concept of co-creativity has emerged to describe blended human–AI creativity. These issues evoke the question of whether creativity requires redefinition in the era of AI. Currently, co-creativity is mostly studied within the framework of computer science in pre-organized laboratory settings. This study contributes from a human scientific perspective with 52 interviews of Finland-based computer scientists and new media artists who use AI in their work. The results suggest scientists and artists use similar elements to define creativity. However, the role of AI differs between the scientific and artistic creative processes. Scientists need AI to produce accurate and trustworthy outcomes, whereas artists use AI to explore and play. Unlike the scientists, some artists also considered their work with AI co-creative. We suggest that co-creativity can explain the contemporary creative processes in the era of AI and should be the focal point of future creativity research.

International Trends in K–12 Computer Science Curricula Through Comparative Analysis: Implications for the Primary Curricula

The purpose of this study was to identify international trends in K–12 computer science curricula in countries that have introduced computer science education. Content analysis method was used to analyze the country-wide curricula of 10 countries which have introduced computer science education at the primary level. The K–12 Computer Science Framework was used as a theoretical frame to analyze the curricula. The results show that most countries begin their curricula with subconcepts of algorithms, program development, and under impact of computing, along with the practice of creating computational artifacts; then, countries expand upon computer science concepts and practices as learners progressed through the higher grades. Further, countries tend to introduce computer science concepts and practices in stages; once concepts and practices are introduced, they continue across multiple grades. Three approaches to implementing computer science education into the country-wide curriculum were found: introducing computer science (a) as an independent subject, (b) within multiple subjects, and/or (c) as a part of transversal competencies or an independent computer science curriculum with a cross-curricular approach. These study findings can contribute to a worldwide effort to introduce computer science education at the primary level.

An Advanced Analysis of Cloud Computing Concepts Based on the Computer Science Ontology

Our primary research hypothesis stands on a simple idea: The evolution of top-rated publications on a particular theme depends heavily on the progress and maturity of related topics. And this even when there are no clear relations or some concepts appear to cease to exist and leave place for newer ones starting many years ago. We implemented our model based on Computer Science Ontology (CSO) and analyzed 44 years of publications. Then we derived the most important concepts related to Cloud Computing (CC) from the scientific collection offered by Clarivate Analytics. Our methodology includes data extraction using advanced web crawling techniques, data preparation, statistical data analysis, and graphical representations. We obtained related concepts after aggregating the scores using the Jaccard coefficient and CSO Ontology. Our article reveals the contribution of Cloud Computing topics in research papers in leading scientific journals and the relationships between the field of Cloud Computing and the interdependent subdivisions identified in the broader framework of Computer Science.

Is Church’s Thesis Still Relevant?

Abstract The article analyses the role of Church’s Thesis (hereinafter CT) in the context of the development of hypercomputation research. The text begins by presenting various views on the essence of computer science and the limitations of its methods. Then CT and its importance in determining the limits of methods used by computer science is presented. Basing on the above explanations, the work goes on to characterize various proposals of hypercomputation showing their relative power in relation to the arithmetic hierarchy. The general theme of the article is the analysis of mutual relations between the content of CT and the theories of hypercomputation. In the main part of the paper the arguments for abolition of CT caused by the introduction of hypercomputable methods in computer science are presented and critique of these views is presented. The role of the efficiency condition contained in the formulation of CT is stressed. The discussion ends with a summary defending the current status of Church’s thesis within the framework of philosophy and computer science as an important point of reference for determining what the notion of effective calculability really is. The considerations included in this article seem to be quite up-to-date relative to the current state of affairs in computer science.1

Alignment and representation in computer science: an analysis of picture books and graphic novels for K-8 students

ABSTRACT Background and Content Many children’s books related to computer science have been published in the last five years, creating opportunities to integrate these texts into the classroom. Objective Determine where the children’s books support an inclusive computing culture by representing people with diverse intersectional identities engaging in the computer science practices from the K-12 Computer Science Framework. Method We analyzed 45 picture books and graphic novels published between 2015 and 2019 targeted at K-8 students. We compiled evidence of the seven computer science practices and representation of diverse characters. Findings Three or four practices appear in 64% of the books. The characters that engage in computing in the books are 56% female and 38% people of color. The books offer few examples of nonfictional people of color engaged in computer science, with no representation of adult males of color.

Linear Prediction of Overlapping Codons in a Genome Sequence

The concept of overlapping n-ary codons was proposed in this paper as a novel approach to the study of genome sequences in the framework of theoretical computer science. Given a genome sequence of length N, one can have (N/n) non-overlapping n-ary codons with 0 or 1 or up to n-1 unused nucleotides left out in the sequence. Unused nucleotides are not considered in the scheme of genetic code. Alternatively, one can have (N-n+1) overlapping n-ary codons with no unused nucleotide left out in the sequence.

Computational Thinking in Secondary and Higher Education

One of the most important challenges of education is the formation of proper computational thinking (CT). In line with K-12 Computer Science Framework (k12cs.org) the term of CT refers to the “thought processes involved in expressing solutions as computational steps or algorithms that can be carried out by a computer”. CT is a problem solving process essential to the development of computer applications, but it is also used in supporting problem solving across many other disciplines. It has gained some grounds in secondary education in the last few years and there are ongoing efforts to introduce it to elementary education as well. Taking into consideration that algorithms play a central role in computational thinking, the aim of our research was to assess the skills of secondary school students and university students in this area, CT, that they faced an apparently computer science – free task but with obvious algorithmic background. According to the aims of our research there were two target populations: secondary school students and university students. In order to measure the level of computational thinking we elaborated a worksheet (test with problems to be solved). The tasks contained algorithms that can be applied on computer, and they did not need any IT knowledge, only structured and logical thinking. The results provide a reliable guide regarding those cognitive skills, among secondary school-children and university students, which need improvement, so transfer of knowledge could work in practical, life-like situations.

Linear Prediction of Non-Overlapping Codons in a Genome Sequence

The concept of ‘non-overlapping n-ary codons’ is proposed in this paper as a novel approach to the study of genome sequences in the framework of theoretical computer science. Given a genome sequence of length N, one can have (N/n) non-overlapping n-ary codons with 0 or 1 or up to n-1 unused nucleotides left out in the sequence. Unused nucleotides are not considered in the scheme of genetic code.

An Evaluation of Primary School Children Coding Using a Text-Based Language (Java)

All primary school children in England are required to write computer programs and learn about computational thinking. There are moves in other countries to this effect such as the U.S. K-12 Computer Science Framework (CSF) for development. Debates on how to program and what constitutes computational thinking are ongoing. Here we report on a study of programing by children aged 7 – 11 using Java and elements of computational thinking they experience. Our platform comprises a novel Story-Writing-Coding engine we have developed. We compare novice (children’s) processes of coding an animated story with that of experts (college students) and evaluate the differences using four measures based on the progressive coding of a complete program. We also analyze the use of novice (children’s) computational thinking in this coding process. This research is set against a backdrop of approaches to teaching programing and concepts of computational thinking in recent educational literature.

Comparison between Informatics Curriculum in Korea and Computer Science Framework of CSTA in US

Comparison between Informatics Curriculum in Korea and Computer Science Framework of CSTA in US

Hodgkin and Huxley's legacy: the science of neural supercomputing

The small sub-tropical island of Okinawa, some 400 miles south of Japan, is home to a unique colony of creatures. About the size of large rabbits, they possess strange translucent heads into which a single eye is embedded. They spend most of their time foraging and mating and communicate with each other using a luminescent bulb located towards the small of their backs. Their predilection for reproduction has allowed their primitive genome to evolve rapidly to adapt to their unusual circumstances. For their food is a power supply to charge their battery packs, and mating involves infrared data transfer from their hard drives. They are cyber-rodents: mobile, autonomous robots confined only to their home in the Okinawa Institute of Science and Technology by the doors of the laboratory. There are two remarkable things about the cyber-rodents. First, they demonstrate that remarkably little computational power can sustain ‘awake’, behaving organisms. Their brain is a small four-CPU onboard computer, not a giant supercomputer as you might expect. Second, many algorithms used by the rodents are based on those thought to be implemented by live rats and indeed humans. These algorithms control basic behaviours of self-preservation, mimicking the functions thought to be controlled by neuromodulators such as serotonin and dopamine. This second fact underpins a basic fact about neuroscience: if we want to understand the brain, we need to understand how it actually processes information. Like it or not, the brain is a computer, and in the same way, as we cannot hope to understand the brain of the cyber-rodent without a fair knowledge of computer science, so too we are not going to understand the human brain without some sort of neural computer science framework. It is easy to feel a bit daunted by this prospect. With 100 billion neuronal processing units …

The influence of software intangibility on computer science and software engineering education

In this short essay I will discuss how the fact that software is an intangible object influences Computer Science (CS) and Software Engineering (SE) education. Based on several observations that result from this analysis (Part A), I will then highlight the importance of teaching soft ideas in the framework of CS and SE education (Part B).

Discovering frequent episodes and learning hidden Markov models: a formal connection

This paper establishes a formal connection between two common, but previously unconnected methods for analyzing data streams: discovering frequent episodes in a computer science framework and learning generative models in a statistics framework. We introduce a special class of discrete hidden Markov models (HMMs), called episode generating HMMs (EGHs), and associate each episode with a unique EGH. We prove that, given any two episodes, the EGH that is more likely to generate a given data sequence is the one associated with the more frequent episode. To be able to establish such a relationship, we define a new measure of frequency of an episode, based on what we call nonoverlapping occurrences of the episode in the data. An efficient algorithm is proposed for counting the frequencies for a set of episodes. Through extensive simulations, we show that our algorithm is both effective and more efficient than current methods for frequent episode discovery. We also show how the association between frequent episodes and EGHs can be exploited to assess the significance of frequent episodes discovered and illustrate empirically how this idea may be used to improve the efficiency of the frequent episode discovery.

Neural and Super-Turing Computing

``Neural computing'' is a research field based on perceiving the human brain as an information system. This system reads its input continuously via the different senses, encodes data into various biophysical variables such as membrane potentials or neural firing rates, stores information using different kinds of memories (e.g., short-term memory, long-term memory, associative memory), performs some operations called ``computation'', and outputs onto various channels, including motor control commands, decisions, thoughts, and feelings. We show a natural model of neural computing that gives rise to hyper-computation. Rigorous mathematical analysis is applied, explicating our model's exact computational power and how it changes with the change of parameters. Our analog neural network allows for supra-Turing power while keeping track of computational constraints, and thus embeds a possible answer to the superiority of the biological intelligence within the framework of classical computer science. We further propose it as standard in the field of analog computation, functioning in a role similar to that of the universal Turing machine in digital computation. In particular an analog of the Church-Turing thesis of digital computation is stated where the neural network takes place of the Turing machine.

Three Myths of Computer Science

In this paper I will discuss a basic concept of computer science-the concept of a computer program-and three related distinctions of computer science-software vs. hardware, digital vs. analogue, and model vs. theory. I believe all of these notions are important, and if properly understood, provide an important part of the conceptual framework of computer science. But, when these notions are misunderstood, certain myths tend to evolve. With regard to artificial intelligence work these myths perpetuate sloppy research, and with regard to philosophy these myths promote misconceptions related to the mind-body problem and scientific methodology.