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The diagonalization of general mass matrices is a more delicate problem when eigenvalue degeneracies exist. In this case, often overlooked in the literature, some difficulties arise related to the freedom in the choice of basis in degenerate subspaces. Here two simple algorithms are developed to deal with quark and neutrino mass matrices with arbitrary degeneracies.

The ability to obtain complex global behaviour from simple local rules makes cellular automata an interesting platform for massively parallel computation. However, manually designing a cellular automaton to perform a given computation can be extremely difficult, and automated design techniques such as genetic programming have their limitations because of the absence of human intuition. In this paper, we propose elements of a framework whose goal is to make the manual synthesis of cellular automata rules exhibiting desired global characteristics more programmer-friendly, while maintaining the simplicity of local processing elements. Although many of the framework elements that we describe here are not new, we group them into a consistent framework and show that they can all be implemented on a traditional cellular automaton, which means that they are merely more human-friendly ways of describing simple cellular automata rules, and not foreign structures that require changing the traditional cellular automaton model.

The paper presents a complete approach to the multithreaded execution of a control program prepared according to IEC61131-3 standard. The program is mapped to a dedicated multiple-core CPU unit. The CPU consists of multiple independent bit and word CPUs. The computation synchronization mechanism is based on memory cells with semaphored access, which enable hardware-level synchronization. The paper presents in detail the architecture, results of implementation and the achieved performance. The custom-developed compiler translates standard programming languages into a multithreaded executable form. It utilizes an original intermediate data flow graph to optimize and recognize program parallelisms. The program is automatically partitioned and mapped to the available computing resources. The paper is concluded with a performance comparison of program executions using the standard single-threaded and proposed approaches.

One of the main goals of the Software Engineering discipline is to find higher abstraction levels and ways to reuse software in order to increase its productivity and quality. Ontologies, which are typically considered as a technique or an artifact used in one or more software lifecycle phases, may be used to help achieve that goal. This paper provides a systematic literature review of the proposed solutions for applying ontologies in automatic and generative programming. The paper aims to identify ontologies and software development tools, frameworks, prototypes, design patterns and methodologies that use them as development artifacts for source code generation or product derivation. The review provides researchers with the state of the art, while also identifying challenges and gaps that require further exploration and development.

ChatGPT, a recently developed product by openAI, is successfully leaving its mark as a multi-purpose natural language based chatbot. In this paper, we are more interested in analyzing its potential in the field of computational biology. A major share of work done by computational biologists these days involve coding up bioinformatics algorithms, analyzing data, creating pipelining scripts and even machine learning modeling and feature extraction. This paper focuses on the potential influence (both positive and negative) of ChatGPT in the mentioned aspects with illustrative examples from different perspectives. Compared to other fields of computer science, computational biology has (1) less coding resources, (2) more sensitivity and bias issues (deals with medical data), and (3) more necessity of coding assistance (people from diverse background come to this field). Keeping such issues in mind, we cover use cases such as code writing, reviewing, debugging, converting, refactoring, and pipelining using ChatGPT from the perspective of computational biologists in this paper.

An adaptive meshless computational system is introduced in this paper to solve two-dimensional elastoplastic contact mechanics. An adaptive element-free Galerkin-finite element coupling computational model based on the gradient of strain energy and a linear programming technique with the initial stiffness method for elastoplastic contact problems are combined. Principle explanation and program realization are carried out. The modularization concept in software engineering is used, and the adaptive change of the influence domain radius and the elastoplastic property of material are also taken into account by the system. A rigid cylinder making contact with an elastic plane is analyzed to validate the system. Some key parameters in adaptive calculation are studied. The adaptive meshless computational system is also applied to elastoplastic contact of rough surfaces. Comparisons of the adaptive refinement solution with the uniform refinement solution are made, and the results show the satisfactory accuracy and efficiency of the solutions from the adaptive refinement model.

One may expect the Internet to evolve from being information centric to knowledge centric. This paper introduces the concept of a Knowledge Society Operating System (KSOS) that allows users to form knowledge societies in which members can search, create, manipulate and connect geographically distributed knowledge resources (including data, documents, tools, people, devices, etc.) based on semantics (“meaning”, “intention”) in order to solve problems of mutual interest. Built on top of the current Internet infrastructure, a KSOS can take advantage of existing resources to enable the use of applications or services through a web browser. This paper discusses some crucial aspects of a KSOS.

Consider an M × N chess board with each space colored one of K colors. A chromatic rectangle is a rectangular collection of spaces with all four corner spaces colored the same. An M × N : K NCR board is an M × N board for which there exists a K coloring with no chromatic rectangles. If every K coloring includes a chromatic rectangle, then that board is called an M × N : K CR board. The classification as NCR versus CR has been settled for K ∈ {1, 2, 3} and all positive integers N and M.

Note that transposition, or interchanging rows, columns, or colors, will preserve the existence of chromatic rectangles within a coloring. With this in mind, two colorings of a board are called equivalent if one can be produced from the other by such manipulations. This paper establishes that all 10 × 10 : 3 NCR colorings are equivalent.

The results stem from characterizations of NCR colorings. These characterizations permit devising and implementing a backtracking algorithm for finding NCR colorings within a significantly restricted search space. In the 10 × 10 : 3 case, the restricted search space is small enough to complete an exhaustive search in about an hour.

Several NCR colorings for larger boards, with K > 3, are also included.

The present value of interest in the amortization schedule or the sinking fund schedule is derived in the theorem. Even though that people prefer the level payments with smaller total amount of interest, the sum of the present value of interest and the present value of principal remains unchanged in all payment methods. The sum is just the loan amount. Rather than the traditional spreadsheet, the free MIT App Inventor is applied to create the amortization schedule and the sinking fund schedule in the mobile computing environment.

In this technological era, programming skill has become highly valuable across IT and non-IT sectors. Teaching programming can be challenging, requiring a deep understanding of the subject and effective communication skills. Traditional pedagogy, focused on lectures, textbooks, and written assessments, tends to emphasize content over student-centered learning, resulting in limited practical application and knowledge retention. This chapter explores the potential of “Game-Based Learning” (GBL) and gamification as an alternative pedagogy to improve learner’s engagement, problem-solving skills, and learning skills. This chapter provides insights on GBL and its application in programming education, which enables instructors to make better decisions in their teaching practices for programming courses and improve students’ learning experiences.

This paper presents an analysis of Filipino and Japanese students’ facial expressions and hand gestures while solving a series of computer programming exercises. Frequently occurring Facial Action Coding System (FACS) muscle movements such as the widening of the eye (AU-5) and sucking of the lip (AU-28), as well as the occurrence of hand gestures, are identified and discussed in relation to the reported affective states of engagement and confusion. We show that it is possible to build models for predicting engagement and confusion using facial expressions and typing information. We believe that this study can help in the development of affectively aware computer systems for learning programming that can work with different cultures.

This study presents evidence that executable computer programs and human genomes contain similar patterns of repetitive code. When viewed with sequence visualization tools, these similarities are both striking and pervasive. The primary similarities are listed in order of scale: (1) homopolymers, (2) tandem repeats, (3) distributed repeats, (4) isochores, (5) and entire chromosome/file organization. Most strikingly, data visualization reveals that executable codes regularly make extensive use of tandem repeats which exhibit similar visual patterns as seen in higher genomes. In biology these tandem repeat patterns are normally attributed to replication errors, insertions, deletions, and substitutions. Similarly, on a larger scale, executable codes display regions with different ratios of 1's and 0's which parallel the isochore patterns within chromosomes, caused by local variation in the number of A/T vs. G/C. Further, blocks of data are stored at the beginning or end of a file, while the primary instructions occupy the middle of a file. This creates the same organizational patterns observed in human chromosome arms, where repetitive sequences are grouped near the telomeres and centromeres.

I propose that these similarities can be explained by universal constraints in efficient information encoding and execution. The genome may be viewed as the executable program that encodes life. Given the evidence that computer programs and genomes use many of the same patterns of organization, despite having very different context, it should be informative to explore the ways in which knowledge of computer architecture can be applied to biology and vice versa.