Интегративная Структура Мультимедийной Обучающей Системы Лекционного Курса Электротехнической Дисциплины

В статье рассматриваются вопросы активизации учебно-познавательной деятельности студентов на лекционных занятиях. Предложена интегративная структура мультимедийной обучающей системы лекционного курса электротехнической дисциплины.

Интегрированный Комплекс по Моделированию Пользователя и Адаптации СДО

В статье описываются вопросы интеграции системы моделирования пользователя и адаптивной обучающей системы. Основу адаптивной обучающей системы составляет технология LOM, реализующая управление обучающими объектами и поддержанная инструментом VITA-II. Ключевой компонентой процесса адаптации является модель обучающегося. Построение модели производится при помощи инструмента моделирования пользователя Trivium. Задача заключается в интеграции двух средств поддержания адаптивного дистанционного обучения. Кратко рассматриваются архитектуры инструментов VITA-II и Trivium. Рассматривается схема их взаимодействия и возможности интеграции.

Психологические Механизмы Влияния на Мотивационную Сферу Обучающегося

Рассматриваются вопросы, связанные с применением тестирования для создания обучающих программ с учетом типа личности пользователей е-learning системами.

Создание и Оформление ЭУМП

Сегодня, когда Россия переходит на новый уровень жизни, вопросы модернизации образования, образовательных программ и систем стоят особо остро. СПбГЭТУ «ЛЭТИ» несет на себе полную ответственность за все инновации, внедряемые в университете, так как мы являемся одним из 60-ти ВУЗов страны, принимающих участие в Инновационной Образовательной Программе (ИОП). Многие организации и университеты волнуют вопросы, связанные с созданием ЭУМП. Статья посвящена этой теме, причем особое внимание уделяется оформлению ЭУМП.

Использование Сценарного Подхода для Определения Количественной Оценки Эргономичности Интерфейса Обучающих Систем

В статье рассматривается сценарный подход для определения количественной оценки эргономичности интерфейса обучающих систем. Описаны метод декомпозиции и метод сценарной композиции.

Методы Интеграции Учебных Материалов для Дистанционного Обучения

The process of training is the most difficult for effective realization through information technologies. Is suggested the methods for the most complete implementation of original techniques of material description, ensuring versatility of development environment and functioning of interactive systems of training process. The given technology requires as the exact description of teaching model, as application of modern methods of development intelligent skills.

Photographic Plate Libraries at European Astronomical Observatories

ACM Computing Classification System (1998): J.2.

Algebraic theory of minimal nondeterministic finite automata with applications

Since the 1950s, the theory of deterministic and nondeterministic finite automata (DFAs and NFAs, respectively) has been a cornerstone of theoretical computer science. In this dissertation, our main object of study is minimal NFAs. In contrast with minimal DFAs, minimal NFAs are computationally challenging: first, there can be more than one minimal NFA recognizing a given language; second, the problem of converting an NFA to a minimal equivalent NFA is NP-hard, even for NFAs over a unary alphabet. Our study is based on the development of two main theories, inductive bases and partials, which in combination form the foundation for an incremental algorithm, ibas, to find minimal NFAs. An inductive basis is a collection of languages with the property that it can generate (through union) each of the left quotients of its elements. We prove a fundamental characterization theorem which says that a language can be recognized by an n-state NFA if and only if it can be generated by an n-element inductive basis. A partial is an incompletely-specified language. We say that an NFA recognizes a partial if its language extends the partial, meaning that the NFA’s behavior is unconstrained on unspecified strings; it follows that a minimal NFA for a partial is also minimal for its language. We therefore direct our attention to minimal NFAs recognizing a given partial. Combining inductive bases and partials, we generalize our characterization theorem, showing that a partial can be recognized by an n-state NFA if and only if it can be generated by an n-element partial inductive basis. We apply our theory to develop and implement ibas, an incremental algorithm that finds minimal partial inductive bases generating a given partial. In the case of unary languages, ibas can often find minimal NFAs of up to 10 states in about an hour of computing time; with brute-force search this would require many trillions of years.

Algebraic Theory of Minimal Nondeterministic Finite Automata with Applications

Since the 1950s, the theory of deterministic and nondeterministic finite automata (DFAs and NFAs, respectively) has been a cornerstone of theoretical computer science. In this dissertation, our main object of study is minimal NFAs. In contrast with minimal DFAs, minimal NFAs are computationally challenging: first, there can be more than one minimal NFA recognizing a given language; second, the problem of converting an NFA to a minimal equivalent NFA is NP-hard, even for NFAs over a unary alphabet. Our study is based on the development of two main theories, inductive bases and partials, which in combination form the foundation for an incremental algorithm, ibas, to find minimal NFAs. An inductive basis is a collection of languages with the property that it can generate (through union) each of the left quotients of its elements. We prove a fundamental characterization theorem which says that a language can be recognized by an n-state NFA if and only if it can be generated by an n-element inductive basis. A partial is an incompletely-specified language. We say that an NFA recognizes a partial if its language extends the partial, meaning that the NFA's behavior is unconstrained on unspecified strings; it follows that a minimal NFA for a partial is also minimal for its language. We therefore direct our attention to minimal NFAs recognizing a given partial. Combining inductive bases and partials, we generalize our characterization theorem, showing that a partial can be recognized by an n-state NFA if and only if it can be generated by an n-element partial inductive basis. We apply our theory to develop and implement ibas, an incremental algorithm that finds minimal partial inductive bases generating a given partial. In the case of unary languages, ibas can often find minimal NFAs of up to 10 states in about an hour of computing time; with brute-force search this would require many trillions of years.

A ROS-based Workspace Control and Trajectory Planner for a seven degrees of freedom Robotic arm

In this Bachelor Thesis I want to provide readers with tools and scripts for the control of a 7DOF manipulator, backed up by some theory of Robotics and Computer Science, in order to better contextualize the work done. In practice, we will see most common software, and developing environments, used to cope with our task: these include ROS, along with visual simulation by VREP and RVIZ, and an almost "stand-alone" ROS extension called MoveIt!, a very complete programming interface for trajectory planning and obstacle avoidance. As we will better appreciate and understand in the introduction chapter, the capability of detecting collision objects through a camera sensor, and re-plan to the desired end-effector pose, are not enough. In fact, this work is implemented in a more complex system, where recognition of particular objects is needed. Through a package of ROS and customized scripts, a detailed procedure will be provided on how to distinguish a particular object, retrieve its reference frame with respect to a known one, and then allow navigation to that target. Together with technical details, the aim is also to report working scripts and a specific appendix (A) you can refer to, if desiring to put things together.

AMBIENTE DE PROGRAMAÇÃO SCRATCH VOLTADA PARA CRIANÇAS SOB A PERSPECTIVA DA ENGENHARIA SEMIÓTICA

Neste atual cenário mundial, em que as mudanças acontecem em uma velocidade espantosa, novos desafios, novas tecnologias e novos atores aparecem e participam ativamente dessas mudanças. Esta pesquisa apresenta exatamente um desses novos atores, as crianças, as quais interagem cada vez mais cedo com essa diversidade tecnológica. A participação das crianças nesse cenário passa a ser mais ativa quando as mesmas começam a aprender linguagem de programação através de ambientes computacionais. Esses ambientes são avaliados através de sua metacomunicação com aplicação de métodos da Engenharia Semiótica. Assim, a pesquisa tenta compreender e avaliar o processo de metacomunicação usuário-sistema e a contribuição do mesmo no processo de aprendizagem infantil. Com o objetivo de verificarmos essas ocorrências de rupturas entre o ambiente de programação Scratch e seu público-alvo específico, aplicamos a metodologia denominada MAC – Método de Avaliação da Comunicabilidade –, uma técnica conhecida pela Engenharia Semiótica desde 1999. Diversos resultados foram percebidos, porém um merece destaque especial, em que percebemos que as mensagens foram, em sua maioria, identificadas e interpretadas pelos usuários finais. Por outro lado, ocorreram rupturas de comunicação em todos os voluntários, mesmo para aqueles que concluíram todas as tarefas.

'Artificial Immune Systems Tutorial'

The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body as self-cells or non-self cells. It does this with the help of a distributed task force that has the intelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years. A novel computational intelligence technique, inspired by immunology, has emerged, called Artificial Immune Systems. Several concepts from the immune have been extracted and applied for solution to real world science and engineering problems. In this tutorial, we briefly describe the immune system metaphors that are relevant to existing Artificial Immune Systems methods. We will then show illustrative real-world problems suitable for Artificial Immune Systems and give a step-by-step algorithm walkthrough for one such problem. A comparison of the Artificial Immune Systems to other well-known algorithms, areas for future work, tips & tricks and a list of resources will round this tutorial off. It should be noted that as Artificial Immune Systems is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from time to time and from those examples given here.

'Artificial Immune Systems Tutorial'

The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body as self-cells or non-self cells. It does this with the help of a distributed task force that has the intelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years. A novel computational intelligence technique, inspired by immunology, has emerged, called Artificial Immune Systems. Several concepts from the immune have been extracted and applied for solution to real world science and engineering problems. In this tutorial, we briefly describe the immune system metaphors that are relevant to existing Artificial Immune Systems methods. We will then show illustrative real-world problems suitable for Artificial Immune Systems and give a step-by-step algorithm walkthrough for one such problem. A comparison of the Artificial Immune Systems to other well-known algorithms, areas for future work, tips & tricks and a list of resources will round this tutorial off. It should be noted that as Artificial Immune Systems is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from time to time and from those examples given here.

Problem solving and computer-assisted instruction in science education : analysis of research findings and the research process /

The quantitative component of this study examined the effect of computerassisted instruction (CAI) on science problem-solving performance, as well as the significance of logical reasoning ability to this relationship. I had the dual role of researcher and teacher, as I conducted the study with 84 grade seven students to whom I simultaneously taught science on a rotary-basis. A two-treatment research design using this sample of convenience allowed for a comparison between the problem-solving performance of a CAI treatment group (n = 46) versus a laboratory-based control group (n = 38). Science problem-solving performance was measured by a pretest and posttest that I developed for this study. The validity of these tests was addressed through critical discussions with faculty members, colleagues, as well as through feedback gained in a pilot study. High reliability was revealed between the pretest and the posttest; in this way, students who tended to score high on the pretest also tended to score high on the posttest. Interrater reliability was found to be high for 30 randomly-selected test responses which were scored independently by two raters (i.e., myself and my faculty advisor). Results indicated that the form of computer-assisted instruction (CAI) used in this study did not significantly improve students' problem-solving performance. Logical reasoning ability was measured by an abbreviated version of the Group Assessment of Lx)gical Thinking (GALT). Logical reasoning ability was found to be correlated to problem-solving performance in that, students with high logical reasoning ability tended to do better on the problem-solving tests and vice versa. However, no significant difference was observed in problem-solving improvement, in the laboratory-based instruction group versus the CAI group, for students varying in level of logical reasoning ability.Insignificant trends were noted in results obtained from students of high logical reasoning ability, but require further study. It was acknowledged that conclusions drawn from the quantitative component of this study were limited, as further modifications of the tests were recommended, as well as the use of a larger sample size. The purpose of the qualitative component of the study was to provide a detailed description ofmy thesis research process as a Brock University Master of Education student. My research journal notes served as the data base for open coding analysis. This analysis revealed six main themes which best described my research experience: research interests, practical considerations, research design, research analysis, development of the problem-solving tests, and scoring scheme development. These important areas ofmy thesis research experience were recounted in the form of a personal narrative. It was noted that the research process was a form of problem solving in itself, as I made use of several problem-solving strategies to achieve desired thesis outcomes.

Analyzing smooth flowcharts : teaching structured programming in a computer-based education environment /

Vita.