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Добірка наукової літератури з теми "Algorithmes de course"

Автор: Grafiati

Опубліковано: 12 липня 2022

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Статті в журналах з теми "Algorithmes de course"

STEVENSON, DANIEL E. "IMAGE RELATED APPLICATIONS FOR A CORE ALGORITHMS COURSE." International Journal of Pattern Recognition and Artificial Intelligence 15, no. 05 (August 2001): 845–57. http://dx.doi.org/10.1142/s0218001401001167.

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Image related computations are becoming mainstream in today's computing environment. However, Computer Science departments still offer image related courses mostly as electives or at the graduate level. As imaging's importance increases, one needs to consider its coverage at the core courses. Most departments cannot afford to add another course into their curriculum at this level, so the only remaining choice is to integrate image related applications into the existing core courses. This paper addresses this issue as it relates to an Algorithms course. The specific prerequisites and goals of our Algorithms course are described. The image related applications that have been adopted are presented and their impact on the course is discussed.

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Ülker, Ezgi Deniz. "The effect of applying 4-stages on learning analysis and design of algorithms." Cypriot Journal of Educational Sciences 15, no. 5 (October 29, 2020): 1238–48. http://dx.doi.org/10.18844/cjes.v15i5.4621.

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The ability of analysing and designing an algorithm is quite essential for computer science education. The students in the Analysis and Design of Algorithms (ADA) course are expected to be able to solve problems by choosing one of the proper design methods and to analyse the algorithm’s performance in terms of various aspects. Instead of using traditional teaching approaches, a new 4-stage method is proposed to improve the concept of learning and teaching of algorithms. The instructor applied 4 consecutive stages during the tutorials and practical implementations. The students were asked a series of questions for evaluating not only themselves but also the new method and the instructor capability of handling the course by applying the 4-stages. According to the evaluations, the 4-stage method met the course objectives with noticeable rates and the course learning outcomes were achieved with high success rates when compared with the previous semester. In order to attain a sustainable achievement in teaching ADA, it is recommended to apply the 4-stage method every academic year. The application of 4-stages allows the instructor to be more efficient in programming teaching and the student more confident in programming, therefore it can be suggested for other programming related courses. Keywords: Computer science education; Concepts of learning and teaching; Course learning outcomes; Programming teaching; Teaching approaches

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Atef Yekta, Hoda, and Robert Day. "Optimization-based Mechanisms for the Course Allocation Problem." INFORMS Journal on Computing 32, no. 3 (July 2020): 641–60. http://dx.doi.org/10.1287/ijoc.2018.0849.

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In recent years, several universities have adopted an algorithmic approach to the allocation of seats in courses, for which students place bids (typically by ordering or scoring desirable courses), and then seats are awarded according to a predetermined procedure or mechanism. Designing the appropriate mechanism for translating bids into student schedules has received attention in the literature, but there is currently no consensus on the best mechanism in practice. In this paper, we introduce five new algorithms for this course-allocation problem, using various combinations of matching algorithms, second-price concepts, and optimization, and compare our new methods with the natural benchmarks from the literature: the (proxy) draft mechanism and the (greedy) bidding-point mechanism. Using simulation, we compare the algorithms on metrics of fairness, efficiency, and incentive compatibility, measuring their ability to encourage truth telling among boundedly rational agents. We find good results for all of our methods and that a two-stage, full-market optimization performs best in measures of fairness and efficiency but with slightly worse incentives to act strategically compared with the best of the mechanisms. We also find generally negative results for the bidding-point mechanism, which performs poorly in all categories. These results can help guide the decision of selecting a mechanism for course allocation or for similar assignment problems, such as project team assignments or sports drafts, for example, in which efficiency and fairness are of utmost importance but incentives must also be considered. Additional robustness checks and comparisons are provided in the online supplement.

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Shu, Hong Ping, Kui Li, and Liang Cao. "Research on Algorithm of Conflict Detection and Resolution in Three-Dimension Free Flight Based on Genetic Algorithms." Applied Mechanics and Materials 121-126 (October 2011): 4586–90. http://dx.doi.org/10.4028/www.scientific.net/amm.121-126.4586.

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The research 3d environment of Free Flight is discussed, the substance of the conflict detection and resolution in 3d Free Flight based on genetic algorithms is studied, and a mathematical model is constructed in the paper. The emulation results of applications show that the genetic algorithms is suitable and positive to detect and resolute the conflict in 3d Free Flight. The flight courses of aircrafts, which are as close as possible to the theoretical direct flight course of the least-fuel-consumption, can be generated by genetic algorithms.

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Alsaffar, Ali Hasan. "Empirical study on the effect of using synthetic attributes on classification algorithms." International Journal of Intelligent Computing and Cybernetics 10, no. 2 (June 12, 2017): 111–29. http://dx.doi.org/10.1108/ijicc-08-2016-0029.

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Purpose The purpose of this paper is to present an empirical study on the effect of two synthetic attributes to popular classification algorithms on data originating from student transcripts. The attributes represent past performance achievements in a course, which are defined as global performance (GP) and local performance (LP). GP of a course is an aggregated performance achieved by all students who have taken this course, and LP of a course is an aggregated performance achieved in the prerequisite courses by the student taking the course. Design/methodology/approach The paper uses Educational Data Mining techniques to predict student performance in courses, where it identifies the relevant attributes that are the most key influencers for predicting the final grade (performance) and reports the effect of the two suggested attributes on the classification algorithms. As a research paradigm, the paper follows Cross-Industry Standard Process for Data Mining using RapidMiner Studio software tool. Six classification algorithms are experimented: C4.5 and CART Decision Trees, Naive Bayes, k-neighboring, rule-based induction and support vector machines. Findings The outcomes of the paper show that the synthetic attributes have positively improved the performance of the classification algorithms, and also they have been highly ranked according to their influence to the target variable. Originality/value This paper proposes two synthetic attributes that are integrated into real data set. The key motivation is to improve the quality of the data and make classification algorithms perform better. The paper also presents empirical results showing the effect of these attributes on selected classification algorithms.

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Amrulloh, Arif, and Enny Itje Sela. "Course scheduling optimization using genetic algorithm and tabu search." Jurnal Teknologi dan Sistem Komputer 9, no. 3 (June 15, 2021): 157–66. http://dx.doi.org/10.14710/jtsiskom.2021.14137.

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Scheduling courses in higher education often face problems, such as the clashes of teachers' schedules, rooms, and students' schedules. This study proposes course scheduling optimization using genetic algorithms and taboo search. The genetic algorithm produces the best generation of chromosomes composed of lecturer, day, and hour genes. The Tabu search method is used for the lecture rooms division. Scheduling is carried out for the Informatics faculty with four study programs, 65 lecturers, 93 courses, 265 lecturer assignments, and 65 classes. The process of generating 265 schedules took 561 seconds without any scheduling clashes. The genetic algorithms and taboo searches can process quite many course schedules faster than the manual method.

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MITSUBORI, Kunihiko, Takeshi KAMIO, and Takahiro TANAKA. "Finding the Shortest Course of a Ship Based on Reinforcement Learning Algorithm." Journal of Japan Institute of Navigation 110 (2004): 9–18. http://dx.doi.org/10.9749/jin.110.9.

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SANCHEZ, ANGEL, JOSE F. VELEZ, ANA BELEN MORENO, and JOSE L. ESTEBAN. "INTRODUCING ALGORITHM DESIGN TECHNIQUES IN UNDERGRADUATE DIGITAL IMAGE PROCESSING COURSES." International Journal of Pattern Recognition and Artificial Intelligence 15, no. 05 (August 2001): 789–803. http://dx.doi.org/10.1142/s0218001401001155.

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This paper documents the development and first offering of an undergraduate course in Digital Image Processing at the Rey Juan Carlos University, Madrid (Spain). The paper describes how the appropriate introduction of main Algorithm Design Techniques can successfully assist the students to achieve a comprehensive understanding of image operations and related algorithms. Image processing problems offer a natural way to present real world problems where the students can use their algorithmic knowledge. Furthermore, image processing solutions are needed from a methodological development and require efficient well-designed algorithms. This paper presents an effort in the integration of Algorithm Design Techniques in a Digital Image Processing course with a very practical scope.

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Premalatha, M., and V. Viswanathan. "Course Sequence Recommendation with Course Difficulty Index Using Subset Sum Approximation Algorithms." Cybernetics and Information Technologies 19, no. 3 (September 1, 2019): 25–44. http://dx.doi.org/10.2478/cait-2019-0024.

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Abstract Choice Based Course Selection (CBCS) allows students to select courses based on their preferred sequence. This preference in selection is normally bounded by constraints set by a university like pre-requisite(s), minimum and maximum number of credits registered per semester. Unplanned course sequence selection affects the performance of the students and may prolong the time to complete the degree. Course Difficulty Index (DI) also contributes to the decline in the performance of the students. To overcome these difficulties, we propose a new Subset Sum Approximation Problem (SSAP) aims to distribute courses to each semester with approximately equal difficulty level using Maximum Prerequisite Weightage (MPW) Algorithm, Difficulty Approximation (DA) algorithm and Adaptive Genetic Algorithm (AGA). The three algorithms have been tested using our university academic dataset and DA algorithm outperforms with 98% accuracy than the MPW and AGA algorithm during course distribution.

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FINK, EUGENE, and MICHAEL HEATH. "IMAGE-PROCESSING PROJECTS FOR AN ALGORITHMS COURSE." International Journal of Pattern Recognition and Artificial Intelligence 15, no. 05 (August 2001): 859–68. http://dx.doi.org/10.1142/s0218001401001192.

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Courses on algorithm analysis often include little programming, and do not emphasize application of advanced techniques to practical problems. On the other hand, students usually prefer hands-on learning, and may lack motivation to study theory. We augmented an algorithms course with a series of programming tasks, which involved application of the course material to image processing. These tasks motivated the students, and led to better understanding and retention of theoretical material. They also enabled the students to learn the basics of representing and manipulating images, along with the algorithm theory.

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Дисертації з теми "Algorithmes de course"

Nguyen, Vu-Linh. "Imprecision in machine learning problems." Thesis, Compiègne, 2018. http://www.theses.fr/2018COMP2433.

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Nous nous sommes concentrés sur la modélisation et l'imprécision dans les problèmes d'apprentissage automatique, où les données ou connaissances disponibles souffrent d'imperfections importantes. Dans ce travail, les données imparfaites font référence à des situations où certaines caractéristiques ou les étiquettes sont imparfaitement connues, c'est-à-dire peuvent être spécifiées par des ensembles de valeurs possibles plutôt que par des valeurs précises. Les apprentissages à partir de données partielles sont couramment rencontrés dans divers domaines, tels que la biostatistique, l'agronomie ou l'économie. Ces données peuvent être générées par des mesures grossières ou censurées, ou peuvent être obtenues à partir d'avis d'experts. D'autre part, la connaissance imparfaite fait référence aux situations où les données sont spécifiées avec précision, cependant, il existe des classes qui ne peuvent pas être distinguées en raison d'un manque de connaissances (également appelée incertitude épistémique) ou en raison d'une forte incertitude (également appelée incertitude aléatoire). Considérant le problème de l'apprentissage à partir de données partiellement spécifiées, nous soulignons les problèmes potentiels liés au traitement de plusieurs classes optimales et de plusieurs modèles optimaux dans l'étape d'inférence et d'apprentissage, respectivement. Nous avons proposé des approches d'apprentissage actif pour réduire l'imprécision dans ces situations. Pourtant, la distinction incertitude épistémique/aléatoire a été bien étudiée dans la littérature. Pour faciliter les applications ultérieures d'apprentissage automatique, nous avons développé des procédures pratiques pour estimer ces degrés pour les classificateurs populaires. En particulier, nous avons exploré l'utilisation de cette distinction dans les contextes d'apprentissage actif et prudent
We have focused on imprecision modeling in machine learning problems, where available data or knowledge suffers from important imperfections. In this work, imperfect data refers to situations where either some features or the labels are imperfectly known, that is can be specified by sets of possible values rather than precise ones. Learning from partial data are commonly encountered in various fields, such as bio-statistics, agronomy, or economy. These data can be generated by coarse or censored measurements, or can be obtained from expert opinions. On the other hand, imperfect knowledge refers to the situations where data are precisely specified, however, there are classes, that cannot be distinguished due to a lack of knowledge (also known as epistemic uncertainty) or due to a high uncertainty (also known as aleatoric uncertainty). Considering the problem of learning from partially specified data, we highlight the potential issues of dealing with multiple optimal classes and multiple optimalmodels in the inference and learning step, respectively. We have proposed active learning approaches to reduce the imprecision in these situations. Yet, the distinction epistemic/aleatoric uncertainty has been well-studied in the literature. To facilitate subsequent machine learning applications, we have developed practical procedures to estimate these degrees for popular classifiers. In particular, we have explored the use of this distinction in the contexts of active learning and cautious inferences

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Naseem, Jat Sadaf. "Genetic algorithms for university course timetabling problems." Thesis, University of Leicester, 2012. http://hdl.handle.net/2381/10997.

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The university course timetabling problem is a difficult optimisation problem due to its highly-constrained nature. Finding an optimal, or even a high quality, timetable is a challenging task, especially when resources (e.g., rooms and time slots) are limited. In the literature, many approaches have been studied to solve this problem. In this thesis, we investigate genetic algorithms to solve the problem because they have been successfully used for a wide range of real-world problems. However, for university course timetabling problems, traditional genetic algorithms are not usually considered as efficient solvers. In this thesis, we investigate genetic algorithms to acquire good solutions for university course timetabling problems. Several ideas are introduced to increase the general performance of genetic algorithms on these problems. Local search strategies are introduced into the traditional genetic algorithm to enhance its performance for the university course timetabling problem. This differs from many works in the literature because it works on time slots of the timetable rather than events directly. A guided search approach is also introduced into genetic algorithms to produce high quality individuals into the population. In the guided search technique, the best parts of selected individuals from the current population are stored in an extra memory (or data structure) and are re-used to guide the generation of new individuals for subsequent populations. In addition to solving university course timetabling problems as a single-objective optimisation problem, we also tackle the multi-objective university course timetabling problem. We integrate the above proposed approaches into multi-objective evolutionary algorithms and propose a framework of multi-objective evolutionary algorithms based on local search and guided search strategies for the multi-objective university course timetabling problem. This framework is then instantiated into a set of multi-objective evolutionary algorithms for the multi-objective university course timetabling problem based on a set of multi-objective evolutionary algorithms that are typically used for general multi-objective optimisation problems. Computational results based on a set of well-known university course timetabling benchmark instances, show the effectiveness of the proposed approaches for both single- and multi-objective university course timetabling problems.

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DANTAS, VITOR CAVALCANTI. "ALGORITHMS FOR POST ENROLLMENT-BASED COURSE TIMETABLING." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2009. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=13807@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
Problemas de Programação de Horários (PPHs) tem sido amplamente estudados, dada a sua importância prática e teórica. A maioria das variações do problema pertence µa classe NP-Difícil. Em geral, trata-se da alocação de recursos materiais e humanos no espaço e no tempo, visando a otimização de um conjunto de objetivos definidos. Na Programação de Horários de Cursos Universitários, por exemplo, o objetivo pode ser a satisfação do corpo docente e o desempenho acadêmico dos alunos. Nos últimos anos, as formulações de PPHs propostas pela International Timetabling Competition (ITC) tem sido bastante utilizadas, sendo notável a predominância de métodos baseados em busca local e metaeurísticas entre as abordagens propostas recentemente. Este trabalho tem como objetivo propor algoritmos para o Problema de Programação de Horários Pós-Matrícula da ITC, focando principalmente em métodos heurísticos baseados em Programação Matemática. Entre os modelos de Programação Linear Inteira Mista que propomos para este problema, destaca-se o modelo baseado na Formulação de Representantes Assimétricos para o Problema de Coloração de Grafos. Abordamos a aplicação da heurística de Local Branching e propomos um esquema de resolução por Geração de Colunas, como forma de viabilizar o tratamento dos modelos propostos, uma vez que a complexidade de tais modelos representa um desafio para os resolvedores de Programação Linear Inteira Mista atualmente disponíveis.
Timetabling Problems have been widely studied, given its practical and theorical relevance. Most of its variations belong to the NP-Hard class of problems. In general, it is about allocation of material and human resources in time and space, aiming to optimize some set of defined objetives. In University Course Timetabling, for example, the objective might be the satisfaction of professors and the academic performance of students. In the last years, the formulations for timetabling problems proposed by the In- ternational Timetabling Competition (ITC) have been widely adopted. The predominance of meta-heuristics and local search-based methods is remark- able among the recently proposed approaches. The objetive of this thesis is to propose algorithms for the Post Enrolment-based Course Timetabling Problem of the ITC, focusing on Mathematical Programming-based heuris- tic methods. Among the Mixed Integer Linear Programming models that we propose for this problem, we highlight the one based on the Asymetric Representatives Formulation for the Graph Coloring Problem. We explore the application of the Local Branching heuristic and we propose a Column Generation solution procedure, as an attempt to handle the proposed models, given that the complexity of such models poses a challenge for currently available Mixed Integer Linear Programming solvers.

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Karrolla, Sanjay. "WEB APPLICATION FOR GRADUATE COURSE ADVISING SYSTEM." CSUSB ScholarWorks, 2017. https://scholarworks.lib.csusb.edu/etd/606.

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The main aim of the course recommendation system is to build a course recommendation path for students to help them plan courses to successfully graduate on time. The Model-View-Controller (MVC) architecture is used to isolate the user interface (UI) design from the business logic. The front-end of the application develops the UI using AngularJS. The front-end design is done by gathering the functionality system requirements -- input controls, navigational components, informational components and containers and usability testing. The back-end of the application involves setting up the database and server-side routing. Server-side routing is done using Express JS.

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Lovelace, April L. "On the Complexity of Scheduling University Courses." DigitalCommons@CalPoly, 2010. https://digitalcommons.calpoly.edu/theses/245.

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It has often been said that the problem of creating timetables for scheduling university courses is hard, even as hard as solving an NP-Complete problem. There are many papers in the literature that make this assertion but rarely are precise problem definitions provided and no papers were found which offered proofs that the university course scheduling problem being discussed is NP-Complete. This thesis defines a scheduling problem that has realistic constraints. It schedules professors to sections of courses they are willing to teach at times when they are available without overloading them. Both decision and optimization versions are precisely defined. An algorithm is then provided which solves the optimization problem in polynomial time. From this it is concluded that the decision problem is unlikely to be NP-Complete because indeed it is in P. A second more complex timetable design problem, that additionally seeks to assign appropriate rooms in which the professors can teach the courses, is then introduced. Here too both decision and optimization versions are defined. The second major contribution of this thesis is to prove that this decision problem is NP-Complete and hence the corresponding optimization problem is NP-Hard.

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Ritzenthaler, Christophe. "Problèmes arithmétiques relatifs à certains familles de courbes sur les corps finis." Paris 7, 2003. https://tel.archives-ouvertes.fr/tel-00003070.

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Dhumal, Sayali. "WEB APPLICATION FOR GRADUATE COURSE RECOMMENDATION SYSTEM." CSUSB ScholarWorks, 2017. https://scholarworks.lib.csusb.edu/etd/605.

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The main aim of the course advising system is to build a course recommendation path for students to help them plan courses to successfully graduate on time. The recommendation path displays the list of courses a student can take in each quarter from the first quarter after admission until the graduation quarter. The courses are filtered as per the student’s interest obtained from a questionnaire asked to the student. The business logic involves building the recommendation algorithm. Also, the application is functionality-tested end-to-end by using nightwatch.js which is built on top of node.js. Test cases are written for every module and implemented while building the application.

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Rao, Michaël. "Décompositions de graphes et algorithmes efficaces." Metz, 2006. http://docnum.univ-lorraine.fr/public/UPV-M/Theses/2006/Rao.Michael.SMZ0607.pdf.

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Ce mémoire traite de la décomposition modulaire ainsi que différentes de ses généralisations. Dans un premier temps, on explique comment se servir de décompositions pour résoudre efficacement certains problèmes sur les graphes. En particulier, en utilisant la décomposition modulaire, on obtient des algorithmes linéaires pour les problèmes " ensemble stable ", " clique ", " nombre chromatique " et " partition en cliques " sur les graphes sans P_5 et gem induit. On étudie également comment la décomposition en coupes peut servir pour calculer le nombre chromatique, et on exhibe une nouvelle classe de problèmes de partitionnements pour lesquels on peut obtenir des algorithmes polynomiaux sur les graphes de largeur de clique bornée. Dans un second temps, on s'intéresse à généraliser la décomposition modulaire. On étudiera une nouvelle décomposition appelée décomposition bi-joint. On donne notamment différentes caractérisations des graphes complètement décomposables par cette décomposition, et un algorithme linéaire pour la calculer. On donne également des généralisations paramétrées de la décomposition modulaire, qui s'avèrent relativement proches de la largeur de clique
This thesis deals with the modular decomposition and several of its generalizations. In a first time we show how graph decompositions can be used to solve efficiently some problems on graphs. We show how the modular decomposition can be used to obtain linear algorithms for " independent set ", " clique ", " chromatic number " and " partition into cliques " on (P_5,gem)-free graphs. We also show how the split decomposition can be used to compute the chromatic number, and we give a new class of vertex partitioning problems which can be solved in polynomial time on graphs of bounded clique width. In a second time, we are interested to generalize the modular decomposition. We study a new decomposition called the bi-join decomposition. We give in particular several characterizations of completely decomposable graphs, and a linear time decomposition algorithm. We introduce some parametrized generalization of the modular decomposition, and we show that theses generalizations are relatively close to the clique width

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Silva, Jose, Noel Varela, Jesus Varas, Omar Lezama, José Maco, and Martín Villón. "Comparison of bioinspired algorithms applied to the timetabling problem." Springer Science and Business Media Deutschland GmbH, 2021. http://hdl.handle.net/10757/654075.

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The problem of timetabling events is present in various organizations such as schools, hospitals, transportation centers. The purpose of timetabling activities at a university is to ensure that all students attend their required subjects in accordance with the available resources. The set of constraints that must be considered in the design of timetables involves students, teachers and infrastructure. This study shows that acceptable solutions are generated through the application of genetic, memetic and immune system algorithms for the problem of timetabling. The algorithms are applied to real instances of the University of Mumbai in India and their results are comparable with those of a human expert.
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Despiegel, Vincent. "Boîtes de substitutions : courbes hyperelliptiques et algorithmes de minimalisation." Université Joseph Fourier (Grenoble), 2007. http://www.theses.fr/2007GRE10162.

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Les travaux effectués au cours de cette thèse portent sur l'optimisation de boîtes de substitutions vis à vis de la cryptanalyse linéaire et différentielle. Parallèlement à ceci, le but est de les rendre résistantes aux attaques algébriql ! telles que celles proposées par N. Courtois et 1. Pieprzyk, et ainsi de combler une faiblesse potentielle de l'AES. Pour cela, on explore diverses pistes. Dans un premier temps, la généralisation des boîtes de substitution elliptiques proposées par R. Gillard et F. Leprevost aux courbes hyperelliptiques permet d'augmenter sensiblement l'espace de recherche de boîtes de substitutions satisfaisantes et conduit à des résultats similaires. Dans un second temps, des algorithmes de minimalisation de boîtes de substitutions vis à vis des paramètres de résistance linéaire et différentielle permettent, à l'aide de stratégies gloutonnes et de permutations judicieusement choisies, d'obtenir des résultats qui s'approchent de la boîte de substitution de l'AES
Ln this thesis, the airn is the optimisation ofkey tools usually used in blocks cyphers: substitution boxes. The goal is the optimization of their linear and differential resistance and their protection against algebraic attacks, developped by ! N. Courtois and 1. Pieprzyk, which are a potential weakness of the AES (Advanced Encryption System). Various means of optimization are studied. First, the generalisation of elliptic substitution boxes developped by R. Gillard and F. Leprevost to hyperelliptic curves leads to similar results, but increased the space of research. Secondly, we develop minirnalisation algorithms of substitution boxes, relatively to linear and differential resistance. A greedy heuristic and clever choices of permutations leads to results close to the substitution box of the AES

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Книги з теми "Algorithmes de course"

S, Wagon, ed. A course in computational number theory. New York: Key College Pub. in cooperation with Springer, 2000.

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Uehara, Ryuhei. First Course in Algorithms Through Puzzles. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-3188-6.

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Adamson, Iain T. Data Structures and Algorithms: A First Course. London: Springer London, 1996.

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Data structures and algorithms: A first course. London: Springer, 1996.

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Adamson, Iain T. Data Structures and Algorithms: A First Course. London: Springer London, 1996. http://dx.doi.org/10.1007/978-1-4471-1023-1.

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Barnett, Michael P. Animated algorithms: A self-teaching course in data structures and fundamental algorithms. New York: McGraw-Hill, 1986.

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Gass, Saul I. Decision making, models and algorithms: A first course. Malabar, Fla: Krieger Pub. Co., 1991.

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Decision making, models and algorithms: A first course. New York: Wiley, 1985.

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Vabishchevich, P. N. Computational technologies: A first course. Berlin: de Gruyter, 2015.

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1965-, Greif Chen, ed. A first course in numerical methods. Philadelphia: Society for Industrial and Applied Mathematics, 2011.

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Частини книг з теми "Algorithmes de course"

Domkin, Vsevolod. "A Crash Course in Lisp." In Programming Algorithms in Lisp, 11–28. Berkeley, CA: Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-6428-7_3.

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Uehara, Ryuhei. "Randomized Algorithms." In First Course in Algorithms Through Puzzles, 129–39. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-3188-6_6.

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Junginger, Werner. "Course Scheduling by Genetic Algorithms." In Evolutionary Algorithms in Management Applications, 357–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-642-61217-6_21.

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Adamson, Iain T. "Sorting Algorithms." In Data Structures and Algorithms: A First Course, 127–70. London: Springer London, 1996. http://dx.doi.org/10.1007/978-1-4471-1023-1_7.

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Adamson, Iain T. "Graph Algorithms." In Data Structures and Algorithms: A First Course, 171–213. London: Springer London, 1996. http://dx.doi.org/10.1007/978-1-4471-1023-1_8.

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Amrutkar, Saurabh, Shantanu Mahakal, and Ajay Naidu. "Recommender Systems for University Elective Course Recommendation." In Algorithms for Intelligent Systems, 247–57. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4862-2_27.

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Socha, Krzysztof, Joshua Knowles, and Michael Sampels. "A MAX-MIN Ant System for the University Course Timetabling Problem." In Ant Algorithms, 1–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45724-0_1.

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Adamson, Iain T. "Algorithms and Complexity." In Data Structures and Algorithms: A First Course, 113–25. London: Springer London, 1996. http://dx.doi.org/10.1007/978-1-4471-1023-1_6.

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Adamson, Iain T. "Some Miscellaneous Algorithms." In Data Structures and Algorithms: A First Course, 215–34. London: Springer London, 1996. http://dx.doi.org/10.1007/978-1-4471-1023-1_9.

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Cohen, Henri. "Algorithms on Polynomials." In A Course in Computational Algebraic Number Theory, 108–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-662-02945-9_3.

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Тези доповідей конференцій з теми "Algorithmes de course"

Grober, Florian, Andreas Janßen, and Ferit Küçükay. "Customer-Focussed Automatic Test Course Design." In FISITA World Congress 2021. FISITA, 2021. http://dx.doi.org/10.46720/f2020-dgt-007.

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Customer centricity gains increasing importance in vehicle development. With respect to durability testing and approval of prototypes, it causes the requirement for testing procedures which highly comply with the occurring loads during customer operation. In this manner, lightweight construction is enabled and considerable economic advantages are raised by avoiding oversizing as well as undersizing of components. As current state of the art, vehicle manufacturers use special test courses on proving grounds or public roads which must be endured damage-free by the vehicle prototype until a compulsory mileage is reached. Alternatively, the course's loads can be reproduced on a test rig to reduce the required test time. The definition of these test courses is based on long-standing experiences. According to new trends in the automotive sector, as for example electrification and shared mobility, it can be predicted that the customer loads will change in accelerating cycles. Correspondingly, these previous experiences cannot be used offhandedly for such new questions and existing test courses become invalid. To solve the described problem of inflexibility, this article presents a technology for automatic generation of appropriate test courses from customer field data. The developed algorithm transforms customer-oriented load spectra into a test course that reproduces the occurred loads as good as possible. For this purpose, digital map data is combined with measured track load data and consecutive road segments are assembled to a complete test course by heuristic methods. This resulting course requires a minimum driving distance and induces approximately the same loads as the destination load spectra derived from customer field data. The optimisation can be processed simultaneously for several different load channels. Via using automation and heuristics, a good performance arises and enables a fast as well as flexible generation of tailored test courses pursuant to current demands. In contrast to the inflexible test course concept used so far, the described technique represents a good improvement of customer-oriented testing methodology. Therefore, it provides a great novelty value. In the article, the process of an automatic test course design is demonstrated and validated by means of a real example, which shows the practical applicability. The latter is also proved by the fact that the described method has already been used successfully in the research and development of Volkswagen AG.

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Robinson, Simon, Anil Kokaram, and Mike Seymour. "Visual algorithms for post production." In ACM SIGGRAPH 2009 Courses. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1667239.1667262.

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Pettré, Julien, and Ming Lin. "New generation crowd simulation algorithms." In ACM SIGGRAPH 2014 Courses. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2614028.2615446.

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Ward, Greg. "Irradiance caching algorithm." In ACM SIGGRAPH 2007 courses. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1281500.1281619.

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Owens, John. "Data-parallel algorithms and data structures." In ACM SIGGRAPH 2007 courses. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1281500.1281644.

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Melo, Guilherme Afonso Melo Sousa, and Carlos de Salles Soares Neto. "Ballgorithm - Uma Ferramenta Introdutória Para Conceitos de Programação." In XXIV Simpósio Brasileiro de Sistemas Multimídia e Web. Sociedade Brasileira de Computação - SBC, 2018. http://dx.doi.org/10.5753/webmedia.2018.4589.

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The Computer Science Course presents one of the highest dropouts rates among higher education courses in Brazil. Besides that, it’s known that the Algorithms discipline is the base of the knowledge learnt throughout the course and the first contact of students with computer programming. Having that said, the Ballgorithm was idealized to be a tool that includes a simple programming language and a ludical approach, making use of digital games visual elements. This paper aims to presente the development process of the Ballgorithm tool, the Ballcode language and the design decisions regarding to the system architecture.

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Alliez, Pierre, and Andreas Fabri. "Computational geometry algorithms library." In ACM SIGGRAPH ASIA 2009 Courses. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1665817.1665821.

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Lefohn, Aaron E., Joe M. Kniss, Charles D. Hansen, and Ross T. Whitaker. "A streaming narrow-band algorithm." In ACM SIGGRAPH 2005 Courses. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1198555.1198796.

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P. Britto, Nathalino, Maria Elizabeth S. Furtado, and Rafaela P. L. Cardoso. "Uma Estratégia para Institucionalização de Iniciativas para Interdisciplinaridade de IHC aplicada ao Ensino de Programação." In XVII Simpósio Brasileiro de Fatores Humanos em Sistemas Computacionais. Sociedade Brasileira de Computação (SBC), 2018. http://dx.doi.org/10.5753/ihc.2018.4217.

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IHC's interdisciplinarity teaching solutions generally focus on supporting teachers to plan classes and organise didactic content. Given this context, some studies show that in the algorithms ' disciplines of a computational course there is a logical complexity that requires more attention. In this perspective, we perceive the need to support those involved to implant the interdisciplinarity of IHC in a course that had algorithm discipline. Thus, this article defines and describes a strategy that describes the key elements and activities for such deployment and evaluation. To do so, a case study was carried out to analyze the difficulties in a course for the students of the algorithm discipline to analyze and correct an example with usability error, verified through a heuristic inspection.

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Krüger, Jens, and Rüdiger Westermann. "Linear algebra operators for GPU implementation of numerical algorithms." In ACM SIGGRAPH 2005 Courses. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1198555.1198795.

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Звіти організацій з теми "Algorithmes de course"

Prokaznikova, E. N. The distance learning course «The Mathematical Logic and Theory of Algorithms». OFERNIO, December 2018. http://dx.doi.org/10.12731/ofernio.2018.23531.

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Wachen, John, and Steven McGee. Qubit by Qubit’s Four-Week Quantum Computing Summer School Evaluation Report for 2021. The Learning Partnership, September 2021. http://dx.doi.org/10.51420/report.2021.4.

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Qubit by Qubit’s Quantum Computing Summer School is a four-week summer course for high school and university students in their first or second year of studies. The aim of the summer school is to introduce the field of Quantum Information Sciences and Engineering (QISE), specifically quantum computing. Through the course, students learn about quantum mechanics, quantum computation and information (quantum gates, circuits, and algorithms and protocols, including Grover’s Algorithm and Quantum Key Distribution), applications of quantum computing, and quantum hardware. Students also learn how to program in Qiskit and basic mathematics for quantum, including matrices and vectors. The Quantum Computing Summer School program enrolled a diverse population of high school and undergraduate students with 48% of participants identifying at female or non-binary, 20% of students identifying as Hispanic, 17% identifying as Black, and 38% identifying as Asian. The program substantially increased participants’ knowledge about quantum computing, as exhibited by large gains on a technical assessment that was administered at the beginning and end of the program. On a survey of student motivation, students in the program showed a statistically significant increase in their expectancy of being successful in quantum computing and valuing quantum computing. From the beginning of the program to the end of the program, there was a statistically significant increase in students’ reported sense of belonging in quantum. Participation in the program increased students’ interest in pursuing additional coursework and careers in STEM generally and in quantum specifically.

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Heiser, G., K. Hinrichs, A. Meier, and J. Nievergelt. Proceedings of the Course on Algorithms and Data Structures for Geometric Computations Held at CISM (Centre International des Sciences Mecaniques) in Udine (Italy) on 8-12 July 1985,. Fort Belvoir, VA: Defense Technical Information Center, July 1985. http://dx.doi.org/10.21236/ada159513.

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Kompaniets, Alla, Hanna Chemerys, and Iryna Krasheninnik. Using 3D modelling in design training simulator with augmented reality. [б. в.], February 2020. http://dx.doi.org/10.31812/123456789/3740.

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The article is devoted to the theoretical consideration of the problem and the use of innovative technologies in the educational process in the educational establishment of secondary education in the process of studying the school course of computer science. The main advantages of using educational simulators in the educational process are considered, based on the new state standard of basic and complete general secondary education. Based on the analysis of scientific and methodological literature and network sources, the features of the development of simulators for educational purposes are described. Innovative tools for simulator development have been investigated, as augmented reality with the use of three-dimensional simulation. The peculiarities of using a simulator with augmented reality when studying the topic of algorithmization in the course of studying a school computer science are considered. The article also describes the implementation of augmented reality simulator for the formation of algorithmic thinking skills by students, presents the results of development and describes the functionality of the software product. In the further prospects of the study, it is planned to conduct an experimental study to determine the effectiveness of the use of software development in the learning process.

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Belkin, Shimshon, Sylvia Daunert, and Mona Wells. Whole-Cell Biosensor Panel for Agricultural Endocrine Disruptors. United States Department of Agriculture, December 2010. http://dx.doi.org/10.32747/2010.7696542.bard.

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Objectives: The overall objective as defined in the approved proposal was the development of a whole-cell sensor panel for the detection of endocrine disruption activities of agriculturally relevant chemicals. To achieve this goal several specific objectives were outlined: (a) The development of new genetically engineered wholecell sensor strains; (b) the combination of multiple strains into a single sensor panel to effect multiple response modes; (c) development of a computerized algorithm to analyze the panel responses; (d) laboratory testing and calibration; (e) field testing. In the course of the project, mostly due to the change in the US partner, three modifications were introduced to the original objectives: (a) the scope of the project was expanded to include pharmaceuticals (with a focus on antibiotics) in addition to endocrine disrupting chemicals, (b) the computerized algorithm was not fully developed and (c) the field test was not carried out. Background: Chemical agents, such as pesticides applied at inappropriate levels, may compromise water quality or contaminate soils and hence threaten human populations. In recent years, two classes of compounds have been increasingly implicated as emerging risks in agriculturally-related pollution: endocrine disrupting compounds (EDCs) and pharmaceuticals. The latter group may reach the environment by the use of wastewater effluents, whereas many pesticides have been implicated as EDCs. Both groups pose a threat in proportion to their bioavailability, since that which is biounavailable or can be rendered so is a priori not a threat; bioavailability, in turn, is mediated by complex matrices such as soils. Genetically engineered biosensor bacteria hold great promise for sensing bioavailability because the sensor is a live soil- and water-compatible organism with biological response dynamics, and because its response can be genetically “tailored” to report on general toxicity, on bioavailability, and on the presence of specific classes of toxicants. In the present project we have developed a bacterial-based sensor panel incorporating multiple strains of genetically engineered biosensors for the purpose of detecting different types of biological effects. The overall objective as defined in the approved proposal was the development of a whole-cell sensor panel for the detection of endocrine disruption activities of agriculturally relevant chemicals. To achieve this goal several specific objectives were outlined: (a) The development of new genetically engineered wholecell sensor strains; (b) the combination of multiple strains into a single sensor panel to effect multiple response modes; (c) development of a computerized algorithm to analyze the panel responses; (d) laboratory testing and calibration; (e) field testing. In the course of the project, mostly due to the change in the US partner, three modifications were introduced to the original objectives: (a) the scope of the project was expanded to include pharmaceuticals (with a focus on antibiotics) in addition to endocrine disrupting chemicals, (b) the computerized algorithm was not fully developed and (c) the field test was not carried out. Major achievements: (a) construction of innovative bacterial sensor strains for accurate and sensitive detection of agriculturally-relevant pollutants, with a focus on endocrine disrupting compounds (UK and HUJ) and antibiotics (HUJ); (b) optimization of methods for long-term preservation of the reporter bacteria, either by direct deposition on solid surfaces (HUJ) or by the construction of spore-forming Bacillus-based sensors (UK); (c) partial development of a computerized algorithm for the analysis of sensor panel responses. Implications: The sensor panel developed in the course of the project was shown to be applicable for the detection of a broad range of antibiotics and EDCs. Following a suitable development phase, the panel will be ready for testing in an agricultural environment, as an innovative tool for assessing the environmental impacts of EDCs and pharmaceuticals. Furthermore, while the current study relates directly to issues of water quality and soil health, its implications are much broader, with potential uses is risk-based assessment related to the clinical, pharmaceutical, and chemical industries as well as to homeland security.

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Burks, Thomas F., Victor Alchanatis, and Warren Dixon. Enhancement of Sensing Technologies for Selective Tree Fruit Identification and Targeting in Robotic Harvesting Systems. United States Department of Agriculture, October 2009. http://dx.doi.org/10.32747/2009.7591739.bard.

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The proposed project aims to enhance tree fruit identification and targeting for robotic harvesting through the selection of appropriate sensor technology, sensor fusion, and visual servo-control approaches. These technologies will be applicable for apple, orange and grapefruit harvest, although specific sensor wavelengths may vary. The primary challenges are fruit occlusion, light variability, peel color variation with maturity, range to target, and computational requirements of image processing algorithms. There are four major development tasks in original three-year proposed study. First, spectral characteristics in the VIS/NIR (0.4-1.0 micron) will be used in conjunction with thermal data to provide accurate and robust detection of fruit in the tree canopy. Hyper-spectral image pairs will be combined to provide automatic stereo matching for accurate 3D position. Secondly, VIS/NIR/FIR (0.4-15.0 micron) spectral sensor technology will be evaluated for potential in-field on-the-tree grading of surface defect, maturity and size for selective fruit harvest. Thirdly, new adaptive Lyapunov-basedHBVS (homography-based visual servo) methods to compensate for camera uncertainty, distortion effects, and provide range to target from a single camera will be developed, simulated, and implemented on a camera testbed to prove concept. HBVS methods coupled with imagespace navigation will be implemented to provide robust target tracking. And finally, harvesting test will be conducted on the developed technologies using the University of Florida harvesting manipulator test bed. During the course of the project it was determined that the second objective was overly ambitious for the project period and effort was directed toward the other objectives. The results reflect the synergistic efforts of the three principals. The USA team has focused on citrus based approaches while the Israeli counterpart has focused on apples. The USA team has improved visual servo control through the use of a statistical-based range estimate and homography. The results have been promising as long as the target is visible. In addition, the USA team has developed improved fruit detection algorithms that are robust under light variation and can localize fruit centers for partially occluded fruit. Additionally, algorithms have been developed to fuse thermal and visible spectrum image prior to segmentation in order to evaluate the potential improvements in fruit detection. Lastly, the USA team has developed a multispectral detection approach which demonstrated fruit detection levels above 90% of non-occluded fruit. The Israel team has focused on image registration and statistical based fruit detection with post-segmentation fusion. The results of all programs have shown significant progress with increased levels of fruit detection over prior art.

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Соловйов, Володимир Миколайович, Vladimir Saptsin, and Dmitry Chabanenko. Prediction of financial time series with the technology of high-order Markov chains. AGSOE, March 2009. http://dx.doi.org/10.31812/0564/1131.

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In this research the technology of complex Markov chains, i.e. Markov chains with a memory is applied to forecast the ﬁnancial time-series. The high-order Markov chains can be simpliﬁed to ﬁrst-order ones by generalizing the states in Markov chains. Considering the *generalized state* as the sequence of states makes a possibility to model high-order Markov chains like ﬁrst-order ones. The adaptive method of deﬁning the states is proposed, it is concerned with the statistic properties of price returns. The algorithm of prediction includes the next steps: (1) Generate the hierarchical set of time discretizations; (2) Reducing the discretiza- tion of initial data and doing prediction at the every time-level (3) Recurrent conjunction of prediction series of diﬀerent discretizations in a single time-series. The hierarchy of time discretizations gives a possibility to review long-memory properties of the series without increasing the order of the Markov chains, to make prediction on the diﬀerent frequencies of the series. The technology is tested on several time-series, including: EUR/USD Forex course, the World’s indices, including Dow Jones, S&P 500, RTS, PFTS and other.

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Osadchyi, Viacheslav V., Hanna Y. Chemerys, Kateryna P. Osadcha, Vladyslav S. Kruhlyk, Serhii L. Koniukhov, and Arnold E. Kiv. Conceptual model of learning based on the combined capabilities of augmented and virtual reality technologies with adaptive learning systems. [б. в.], November 2020. http://dx.doi.org/10.31812/123456789/4417.

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The article is devoted to actual problem of using modern ICT tools to increase the level of efficiency of the educational process. The current state and relevance of the use of augmented reality (AR) and virtual reality (VR) technologies as an appropriate means of improving the educational process are considered. In particular, attention is paid to the potential of the combined capabilities of AR and VR technologies with adaptive learning systems. Insufficient elaboration of cross-use opportunities for achieving of efficiency of the educational process in state-of-the-art research has been identified. Based on analysis of latest publications and experience of using of augmented and virtual reality technologies, as well as the concept of adaptive learning, conceptual model of learning based on the combined capabilities of AR and VR technologies with adaptive learning systems has been designed. The use of VR and AR technologies as a special information environment is justified, which is applied in accordance with the identified dominant type of students' thinking. The prospects of using the proposed model in training process at educational institutions for the implementation and support of new teaching and learning strategies, as well as improving learning outcomes are determined by the example of such courses as “Algorithms and data structures”, “Computer graphics and three-dimensional modeling”, “Circuit Engineering”, “Computer Architecture”.

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Amela, R., R. Badia, S. Böhm, R. Tosi, C. Soriano, and R. Rossi. D4.2 Profiling report of the partner’s tools, complete with performance suggestions. Scipedia, 2021. http://dx.doi.org/10.23967/exaqute.2021.2.023.

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This deliverable focuses on the proling activities developed in the project with the partner's applications. To perform this proling activities, a couple of benchmarks were dened in collaboration with WP5. The rst benchmark is an embarrassingly parallel benchmark that performs a read and then multiple writes of the same object, with the objective of stressing the memory and storage systems and evaluate the overhead when these reads and writes are performed in parallel. A second benchmark is dened based on the Continuation Multi Level Monte Carlo (C-MLMC) algorithm. While this algorithm is normally executed using multiple levels, for the proling and performance analysis objectives, the execution of a single level was enough since the forthcoming levels have similar performance characteristics. Additionally, while the simulation tasks can be executed as parallel (multi-threaded tasks), in the benchmark, single threaded tasks were executed to increase the number of simulations to be scheduled and stress the scheduling engines. A set of experiments based on these two benchmarks have been executed in the MareNostrum 4 supercomputer and using PyCOMPSs as underlying programming model and dynamic scheduler of the tasks involved in the executions. While the rst benchmark was executed several times in a single iteration, the second benchmark was executed in an iterative manner, with cycles of 1) Execution and trace generation; 2) Performance analysis; 3) Improvements. This had enabled to perform several improvements in the benchmark and in the scheduler of PyCOMPSs. The initial iterations focused on the C-MLMC structure itself, performing re-factors of the code to remove ne grain and sequential tasks and merging them in larger granularity tasks. The next iterations focused on improving the PyCOMPSs scheduler, removing existent bottlenecks and increasing its performance by making the scheduler a multithreaded engine. While the results can still be improved, we are satised with the results since the granularity of the simulations run in this evaluation step are much ner than the one that will be used for the real scenarios. The deliverable nishes with some recommendations that should be followed along the project in order to obtain good performance in the execution of the project codes.

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van der Sloot, Bart. The Quality of Life: Protecting Non-personal Interests and Non-personal Data in the Age of Big Data. Universitätsbibliothek J. C. Senckenberg, Frankfurt am Main, 2021. http://dx.doi.org/10.21248/gups.64579.

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Under the current legal paradigm, the rights to privacy and data protection provide natural persons with subjective rights to protect their private interests, such as related to human dignity, individual autonomy and personal freedom. In principle, when data processing is based on non-personal or aggregated data or when such data pro- cesses have an impact on societal, rather than individual interests, citizens cannot rely on these rights. Although this legal paradigm has worked well for decades, it is increasingly put under pressure because Big Data processes are typically based indis- criminate rather than targeted data collection, because the high volumes of data are processed on an aggregated rather than a personal level and because the policies and decisions based on the statistical correlations found through algorithmic analytics are mostly addressed at large groups or society as a whole rather than specific individuals. This means that large parts of the data-driven environment are currently left unregu- lated and that individuals are often unable to rely on their fundamental rights when addressing the more systemic effects of Big Data processes. This article will discuss how this tension might be relieved by turning to the notion ‘quality of life’, which has the potential of becoming the new standard for the European Court of Human Rights (ECtHR) when dealing with privacy related cases.

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