Mathematical Programming Models for Influence Maximization on Social Networks

In this dissertation, we apply mathematical programming techniques (i.e., integer programming and polyhedral combinatorics) to develop exact approaches for influence maximization on social networks. We study four combinatorial optimization problems that deal with maximizing influence at minimum cost over a social network. To our knowl- edge, all previous work to date involving influence maximization problems has focused on heuristics and approximation. We start with the following viral marketing problem that has attracted a significant amount of interest from the computer science literature. Given a social network, find a target set of customers to seed with a product. Then, a cascade will be caused by these initial adopters and other people start to adopt this product due to the influence they re- ceive from earlier adopters. The idea is to find the minimum cost that results in the entire network adopting the product. We first study a problem called the Weighted Target Set Selection (WTSS) Prob- lem. In the WTSS problem, the diffusion can take place over as many time periods as needed and a free product is given out to the individuals in the target set. Restricting the number of time periods that the diffusion takes place over to be one, we obtain a problem called the Positive Influence Dominating Set (PIDS) problem. Next, incorporating partial incentives, we consider a problem called the Least Cost Influence Problem (LCIP). The fourth problem studied is the One Time Period Least Cost Influence Problem (1TPLCIP) which is identical to the LCIP except that we restrict the number of time periods that the diffusion takes place over to be one. We apply a common research paradigm to each of these four problems. First, we work on special graphs: trees and cycles. Based on the insights we obtain from special graphs, we develop efficient methods for general graphs. On trees, first, we propose a polynomial time algorithm. More importantly, we present a tight and compact extended formulation. We also project the extended formulation onto the space of the natural vari- ables that gives the polytope on trees. Next, building upon the result for trees---we derive the polytope on cycles for the WTSS problem; as well as a polynomial time algorithm on cycles. This leads to our contribution on general graphs. For the WTSS problem and the LCIP, using the observation that the influence propagation network must be a directed acyclic graph (DAG), the strong formulation for trees can be embedded into a formulation on general graphs. We use this to design and implement a branch-and-cut approach for the WTSS problem and the LCIP. In our computational study, we are able to obtain high quality solutions for random graph instances with up to 10,000 nodes and 20,000 edges (40,000 arcs) within a reasonable amount of time.

A Phylogenetic Classification of the Video-Game Industry’s Business Model Ecosystem

Part 8: Business Strategies Alignment

Integer Linear Programming for Sequence Problems: A general approach to reduce the problem size

Sequence problems belong to the most challenging interdisciplinary topics of the actuality. They are ubiquitous in science and daily life and occur, for example, in form of DNA sequences encoding all information of an organism, as a text (natural or formal) or in form of a computer program. Therefore, sequence problems occur in many variations in computational biology (drug development), coding theory, data compression, quantitative and computational linguistics (e.g. machine translation). In recent years appeared some proposals to formulate sequence problems like the closest string problem (CSP) and the farthest string problem (FSP) as an Integer Linear Programming Problem (ILPP). In the present talk we present a general novel approach to reduce the size of the ILPP by grouping isomorphous columns of the string matrix together. The approach is of practical use, since the solution of sequence problems is very time consuming, in particular when the sequences are long.

An investigation of two real time machine learning techniques that could enhance the adaptability of game AI agents

Developers strive to create innovative Artificial Intelligence (AI) behaviour in their games as a key selling point. Machine Learning is an area of AI that looks at how applications and agents can be programmed to learn their own behaviour without the need to manually design and implement each aspect of it. Machine learning methods have been utilised infrequently within games and are usually trained to learn offline before the game is released to the players. In order to investigate new ways AI could be applied innovatively to games it is wise to explore how machine learning methods could be utilised in real-time as the game is played, so as to allow AI agents to learn directly from the player or their environment. Two machine learning methods were implemented into a simple 2D Fighter test game to allow the agents to fully showcase their learned behaviour as the game is played. The methods chosen were: Q-Learning and an NGram based system. It was found that N-Grams and QLearning could significantly benefit game developers as they facilitate fast, realistic learning at run-time.

Nostalgia videogames as playable game criticism

The aim of this paper is to consider the emergence of nostalgia videogames in the context of playable game criticism. Mirroring the development of the nostalgia film in cinema, an increasing number of developers are creating videogames that are evocative of past gaming forms, designs, and styles. The primary focus of this paper is to explore the extent to which these nostalgia videogames could be considered games-on-games: games that offer a critical view on game design and development, framed by the nostalgia and cultural memory of both gamers and game developers. Theories of pastiche and parody as applied to literature, film, and art are used to form a basis for the examination of recent nostalgia videogames, all of which demonstrate a degree of reflection on the videogame medium.

Factors influencing success in introductory programming courses.

This study looked at the reasons why Vanier College students in computer programming are encountering difficulties in their learning process, Factors such as prior academic background, prior computer experience, mother tongue, and learning styles were examined to see how they play a role in students' success in programming courses. The initial research hypotheses were the following : Computer science students using understanding and integrating succeed better than students using following coding, or problem solving. Students using problem solving succeed better than those who use participating and enculturation. Students who use coding perform better than those who prefer participating ans enculturation. In addition, this study hoped to examine whether there is a gender difference in how students learn programming.||Résumé :||La présente étude a examiné les raisons pour lesquelles les étudiants en informatique du Collège Vanier rencontrent des difficultés dans leurs études en programmation. Les facteurs tel que le niveau des études précédentes, l'expérience en informatique, la langue maternelle e les méthodes d'apprentissage ont été considérés pour voir quel rôle ces facteurs jouent pour promouvoir la réussite dans les cours de programmation.Les hypothèses initiales de recherche ont été formulées comme suit : 1. Les étudiants en informatique utilisant la compréhension et l'intégration réussissent mieux que ceux utilisant «suivre», le codage ou la résolution des problèmes. 2, Les étudiants utilisant la résolution des problèmes réussissent mieux que ceux qui utilisent la participation dans la culture informatique. 3, Les étudiants utilisant le codage réussissent mieux que ceux qui utilisent la participation dans la culture informatique.

Computer and laboratory simulation in the teaching of neonatal nursing: innovation and impact on learning

Objectives: to evaluate the cognitive learning of nursing students in neonatal clinical evaluation from a blended course with the use of computer and laboratory simulation; to compare the cognitive learning of students in a control and experimental group testing the laboratory simulation; and to assess the extracurricular blended course offered on the clinical assessment of preterm infants, according to the students. Method: a quasi-experimental study with 14 Portuguese students, containing pretest, midterm test and post-test. The technologies offered in the course were serious game e-Baby, instructional software of semiology and semiotechnique, and laboratory simulation. Data collection tools developed for this study were used for the course evaluation and characterization of the students. Nonparametric statistics were used: Mann-Whitney and Wilcoxon. Results: the use of validated digital technologies and laboratory simulation demonstrated a statistically significant difference (p = 0.001) in the learning of the participants. The course was evaluated as very satisfactory for them. The laboratory simulation alone did not represent a significant difference in the learning. Conclusions: the cognitive learning of participants increased significantly. The use of technology can be partly responsible for the course success, showing it to be an important teaching tool for innovation and motivation of learning in healthcare.

Constraint Programming-based Job Dispatching for Modern HPC Applications

A High-Performance Computing job dispatcher is a critical software that assigns the finite computing resources to submitted jobs. This resource assignment over time is known as the on-line job dispatching problem in HPC systems. The fact the problem is on-line means that solutions must be computed in real-time, and their required time cannot exceed some threshold to do not affect the normal system functioning. In addition, a job dispatcher must deal with a lot of uncertainty: submission times, the number of requested resources, and duration of jobs. Heuristic-based techniques have been broadly used in HPC systems, at the cost of achieving (sub-)optimal solutions in a short time. However, the scheduling and resource allocation components are separated, thus generates a decoupled decision that may cause a performance loss. Optimization-based techniques are less used for this problem, although they can significantly improve the performance of HPC systems at the expense of higher computation time. Nowadays, HPC systems are being used for modern applications, such as big data analytics and predictive model building, that employ, in general, many short jobs. However, this information is unknown at dispatching time, and job dispatchers need to process large numbers of them quickly while ensuring high Quality-of-Service (QoS) levels. Constraint Programming (CP) has been shown to be an effective approach to tackle job dispatching problems. However, state-of-the-art CP-based job dispatchers are unable to satisfy the challenges of on-line dispatching, such as generate dispatching decisions in a brief period and integrate current and past information of the housing system. Given the previous reasons, we propose CP-based dispatchers that are more suitable for HPC systems running modern applications, generating on-line dispatching decisions in a proper time and are able to make effective use of job duration predictions to improve QoS levels, especially for workloads dominated by short jobs.

Utilização da discriminação grafica de Fisher para indicação dos dermatoglifos como referencial de potencialidade de atletas de basquetebol

Universidade Estadual de Campinas. Faculdade de Educação Física

As relações de gênero em uma escola de futebol : quando o jogo é possível? = Genders relations at a football school : when the game happen?

Universidade Estadual de Campinas . Faculdade de Educação Física

Desenvolvimento de ferramentas de análise de desempenho de atletas em 3 diferentes modalidades : Handebol, Provas Combinadas e Salto com Vara

Universidade Estadual de Campinas. Faculdade de Educação Física

Explorando a intensidade de esforço em atletas de basquetebol, segundo tipos de fundamentos e posições : estudo a partir de equipe infanto-juvenil do Campeonato Paulista de 1996

Universidade Estadual de Campinas. Faculdade de Educação Física

Rastreamento automatico de trajetorias de jogadores de futebol por videogrametria : validação do metodo e analise dos resultados

Universidade Estadual de Campinas . Faculdade de Educação Física