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AbstractFor a young science and even for most old ones, the intensity and variety of activities involved in computer science are unsurpassed. In an effort to provide the extremely varied training needed in the field, curriculum planners have tended to slight probability and statistics. Rarely has it been a requisite and only occasionally a desired electiveHowever, not only is an adequate foundation in probability and statistics necessary for such external computer applications as tracking and other data reduction, Monte Carlo techniques, gaming, operations research, traffic analyses, etc., but it also plays an important role in internal applications to computer science and technologyThis effort in Rand's continuing study of computational mathematics and its applications offers a number of examples in various areas of computational mathematics and computing machine arithmetic‐to say nothing of computer design, time sharing, and the like‐to support the thesis that probability and statistics should be a requisite, not simply an elective or, even worse, ignored, at any institution offering a program in computer science. Further more, a potentially profitable source of research problems can be found in the interface between probability and statistics and computer science.

Our times are characterized by strong changes in technology that have become reality in many areas of society. When compared to production, transport, services, etc education, as a rule, slowly opens to new technologies. However, children at their homes and outside the schools live in a technologically rich environment, and they expect the change in education in accordance with the imperatives of the education for the twenty-first century. In this sense, systems for automated data processing, multimedia systems, then distance learning, virtual schools and other technologies are being introduced into education. They lead to an increase in students' activities, quality evaluation of their knowledge and finally to their progress, all in accordance with individual abilities and knowledge. Mathematics and computers often appear together in the teaching process. Taking into account the teaching of mathematics, computers and software packages have a significant role. The program requirements are not dominant. The emphasis is on mathematical content and the method of presentation. Computers are especially used in solving various mathematical tasks and self-learning of mathematics. Still, many problems that require solutions appear in the process: how to organise lectures, practice, textbooks, collected mathematical problems, written exams, how to assign and check homework. The answers to these questions are not simple and they will probably be sought continuously, with an increasing use of computers in the teaching process. In this paper I have tried to solve some of the questions above.

This article presents the results of a survey that investigated two related issues for blind and partially sighted students: (1) mathematical-access difficulties and (2) general experiences using computer technology. The survey was part of the formative evaluation of a workstation for Mathematic Access to Technology and Science (commonly called MATHS). The participants included teachers and blind, partially sighted, and sighted students from a range of special, integrated, and mainstream Irish and Belgian schools.

The authors of the article consider the issue of how future teachers of Computer Science and Mathematics are going to perceive the terminology of the digital world. The authors note that the terminological system "digital" arises as a result of digitalisation of all spheres of human activity. The results of the classification of digital terminology into thematic groups on the basis of decoding their lexical and semantic meaning are presented. The authors consider the issue of the most productive understanding of digital terminology based on the allocation of thematic groups "Space", "Time". "Form and Matter", "Consumption", "Technological Transformations", "Human in the Digital World". The authors review scientific works from different fields of science, they select phrases with the adjective "digital". The authors create assignments to identify understanding of digital terminology. The authors determine special attention to the most accessible and complicated understanding of the lexical meaning of the thematic group, they compare the volumes of thematic groups. The novelty of the research lies in the definition of the lexical and semantic group of digital terminology. Topicality of the research lies in the need to expand the vocabulary of a teacher of Computer Science and Mathematics of digital terminology, to build a digital terminology system. The authors prove that the most capacious thematic group is the group "People in the Digital World". The authors conclude that an assessment of the current level of mastering digital terminology by a Computer Science and Mathematics teacher is to reveal problems in the lexical interpretation of new words in schoolchildren.

Then involvement is essential. You cannot stand aside as a member of a community. The real involvement presupposes first a connection at the level of understanding the phenomenon, an empathic relationship with the studied phenomena and processes, relationship that generate intuitions, leaps in understanding and knowledge, discoveries, revelations. The paper is based on the idea that information technology and communications today generate a global interaction based on a complex computer network, which forms a sphere that covers the planet, assimilated with a global intelligence, to which we can consciously adhere becoming a synapse. a global neural network.

The aim of this paper is to briefly explore creative thinking in computer science, and compare it to natural sciences, mathematics or engineering. It is also meant as polemics with some theses of the pioneer work under the same title by Daniel Saunders and Paul Thagard because I point to important motivations in computer science the authors do not mention, and give examples of the origins of problems they explicitly deny. Computer science is a very specific field for it relates the abstract, theoretical discipline – mathematics, on the one hand, and engineering, often concerned with very practical tasks of building computers, on the other. It is like engineering in that it is concerned with solving practical problems or implementing solutions, often with strongly financial reasons, e.g. increasing a company's income. It is like mathematics in that is deals with abstract symbols, logical relations, algorithms, computability problems, etc. Saunders and Thagard analyse rich experimental material from historical and contemporary work in computer science and argue that, as opposed to natural sciences, computer science is not concerned with describing and explaining natural phenomena. Now, I argue that there is a field of research in artificial intelligence (which, in turn, is a branch of computer science), called machine discovery, where explanation of natural phenomena, finding experimental laws and explanatory models is the primary goal. This goal is achieved by constructing computer systems whose job is to simulate various processes involved in scientific discovery done by human researchers, and help them in making new discoveries. On the other hand, motivations that give rise to ingenious projects in computer science can be very strange and include curiosity, fun or attempts to be famous out of boring, stable life of a successful programmer in a big corporation. A good example is the phenomenon of open-source software, especially the development of the Linux operating system and its applications when, from economical point of view, Microsoft absolutely dominated the software market of personal computers.

Cover Page -- Halftitle Page -- Title Page -- Copyright Page -- AldineTransaction Introduction -- Content Page -- Preface -- 1 Mathematics of Social Action -- Causal processes -- Purposive action -- Causal theory and models of action -- Bernoulli events and the Poisson process -- Extensions of Bernoulli trials -- The deficient diagonal, and three extensions of Markov chains -- Extensions of Bernoulli trials: heterogeneity in response probabilities -- Extensions of the Poisson process: continuous-time Markov process -- The deficient diagonal: response unreliability -- Dependence of transition rates on other factors -- Transition rates dependent on numbers of preceding events -- Initiated and terminating processes -- Purposive action theory -- 2 Concepts of Rational Action -- Rational action under varying circumstances -- 3 Collective Actions -- Definitions -- Structural definitions -- A framework for collective action -- The problem of maximization -- The probabilistic decision rule -- 4 Further Concepts and Applications -- Additional concepts -- List of concepts in the theory -- Examples of applications -- The problem of data Appendix: Notes on Trad 11: Computer program to solve for equilibrium -- 5 The Dynamic System, and Other Elaborations -- Dynamics and the movement to equilibrium -- Maximization versus proportional allocation of interests -- Relaxing the probabilistic decision rule -- Sequential introduction of events -- Multi-stage decision processes Appendix: Notes on Trad 12: Computer program for systems of vote exchange -- References -- Computer Program and Output -- Index

Braille-reading mathematicians, scientists, and computer scientists were asked to examine the usability of the Unified English Braille Code (UEB) for technical materials. They had little knowledge of the code prior to the study. The research included two reading tasks, a short tutorial about UEB, and a focus group. The results indicated that the participants believed that UEB could be effectively used by people who are employed in technical fields.

Intro -- Preface -- Contents -- Exploring the Application of Machine Learning for Downscaling Climate Projections -- 1 Introduction -- 2 Data and Methods -- 2.1 Description of Datasets Used -- 2.2 Machine Learning Techniques -- 2.3 Data Preparation -- 3 Results -- 3.1 Experiment 1: Predicting Training Data -- 3.2 Experiment 2: Predicting ERAi Data -- 3.3 Experiment 3: Predicting Weather Station Data -- 4 Discussion and Conclusions -- References -- Approaches to Analyzing the Vulnerability of Community Water Systems to Groundwater Contamination in Los Angeles County -- 1 Introduction -- 2 Workshop Objectives -- 3 Data Cleaning and Processing -- 4 Method Selection and Description -- 5 Discussion -- References -- The Measurement of Disaster Recovery Efficiency Using Data Envelopment Analysis: An Application to Electric Power Restoration -- 1 Introduction -- 2 Previous Literature Assessing Power Restoration Performance -- 3 Methodology -- 3.1 Framework -- 3.2 Empirical Strategy -- 3.2.1 Stage 1: Radial Super-Efficiency DEA Method -- 3.2.2 Stage 2: Environmental Harshness -- 3.2.3 Stage 3: Adjusted Super-Efficiency DEA Model -- 3.3 Sample and Variables -- 3.3.1 Output Variables -- 3.3.2 Input Variables -- 3.3.3 Environmental Variables -- 4 Results -- 4.1 Stage 1 Super-Efficient Values -- 4.2 Stage 2 -- 4.3 Stage 3 Final Super-Efficiency Values -- 5 Discussion -- References -- Transparency Tools for Fairness in AI (Luskin) -- 1 Introduction -- 1.1 The Toolkit -- 1.2 Prior Fairness Definitions and Our Contributions -- 1.3 Additional Related Work -- 1.4 Organization -- 2 Preliminaries -- 3 Controlled Fairness -- 3.1 Algorithm 1: Synthetic Data via Selective Risk Adjustment -- 3.2 Algorithm 2: Synthetic Data via Risk Based Flipping -- 3.3 Choice of Dataset -- 3.4 Type of Models for Our Algorithms -- 3.5 Experimental Result.

Are the keyboards weightier than the biros? This question is the focus of the present study in which the investigation of the modes of testing in mathematics (computer-based testing-CBT and paper-based testing-PBT) was carried out using mathematics achievement and mathematics anxiety as dependent measures. Through a pre-test post-test experimental research, the study tested two null hypotheses at 0.05 level of significance using an independent samples t-test. The study lasted for four weeks in two Nigerian senior secondary schools. Results showed that there was no statistically significant difference between the mean mathematics achievement scores of students tested by the computer-based test and the paper-based test. Also, there was no significant difference between the mean mathematics anxiety scores of students tested by the computer-based test and the paper-based test. The implication of these results is that assessing students using the two modes showed no variations in their achievement and anxiety in mathematics. Thus, the mode of testing showed no differential effect on students' learning outcomes in mathematics. Based on the findings of this study, government at levels in Nigeria need to put in place the enabling environment and infrastructural facilities needed for schools to benefit fully from the advantages inherent in the CBT mode of assessment.

AbstractMost physics theories are deterministic, with the notable exception of quantum mechanics which, however, comes plagued by the so-called measurement problem. This state of affairs might well be due to the inability of standard mathematics to "speak" of indeterminism, its inability to present us a worldview in which new information is created as time passes. In such a case, scientific determinism would only be an illusion due to the timeless mathematical language scientists use. To investigate this possibility it is necessary to develop an alternative mathematical language that is both powerful enough to allow scientists to compute predictions and compatible with indeterminism and the passage of time. We suggest that intuitionistic mathematics provides such a language and we illustrate it in simple terms.