A genetic algorithm for the generalised transportation problem

The generalised transportation problem (GTP) is an extension of the linear Hitchcock transportation problem. However, it does not have the unimodularity property, which means the linear programming solution (like the simplex method) cannot guarantee to be integer. This is a major difference between the GTP and the Hitchcock transportation problem. Although some special algorithms, such as the generalised stepping-stone method, have been developed, but they are based on the linear programming model and the integer solution requirement of the GTP is relaxed. This paper proposes a genetic algorithm (GA) to solve the GTP and a numerical example is presented to show the algorithm and its efficiency.

Information systems design for the community health services

This system is concerned with the design and implementation of a community health information system which fulfils some of the local needs of fourteen nursing and para-medical professions in a district health authority, whilst satisfying the statutory requirements of the NHS Korner steering group for those professions. A national survey of community health computer applications, documented in the form of an applications register, shows the need for such a system. A series of general requirements for an informations systems design methodology are identified, together with specific requirements for this problem situation. A number of existing methodologies are reviewed, but none of these were appropriate for this application. Some existing approaches, tools and techniques are used to define a more suitable methodology. It is unreasonable to rely on one single general methodology for all types of application development. There is a need for pragmatism, adaptation and flexibility. In this research, participation in the development stages by those who will eventually use the system was thought desirable. This was achieved by forming a representative design group. Results would seem to show a highly favourable response from users to this participation which contributed to the overall success of the system implemented. A prototype was developed for the chiropody and school nursing staff groups of Darlington health authority, and evaluations show that a significant number of the problems and objectives of those groups have been successfully addressed; the value of community health information has been increased; and information has been successfully fed back to staff and better utilised.

Выявление Фракталоподобных Структур в ДНК-Последовательностях

Разработан и реализован алгоритм выявления фракталоподобных структур в ДНК- последовательностях. Фрактальность трактуется как самоподобие, основанное на свойстве симметрии или комплементарной симметрии. Локальные фракталы интересны своей способностью аккумулировать множественные палиндромно-шпилечные структуры с потенциально возможными регуляторными функциями. Выявлены реальные случаи проявления фрактальности в различных геномах: от вирусов до человека. Рассмотрена возможность использования фракталоподобных структур в качестве маркеров, различающих близкие классы последовательностей.

Driving licensing renewal policy using neural network-based probabilistic decision support system

This paper investigates neural network-based probabilistic decision support system to assess drivers' knowledge for the objective of developing a renewal policy of driving licences. The probabilistic model correlates drivers' demographic data to their results in a simulated written driving exam (SWDE). The probabilistic decision support system classifies drivers' into two groups of passing and failing a SWDE. Knowledge assessment of drivers within a probabilistic framework allows quantifying and incorporating uncertainty information into the decision-making system. The results obtained in a Jordanian case study indicate that the performance of the probabilistic decision support systems is more reliable than conventional deterministic decision support systems. Implications of the proposed probabilistic decision support systems on the renewing of the driving licences decision and the possibility of including extra assessment methods are discussed.

Linking design and manufacturing domains via web-based and enterprise integration technologies

The manufacturing industry faces many challenges such as reducing time-to-market and cutting costs. In order to meet these increasing demands, effective methods are need to support the early product development stages by bridging the gap of communicating early design ideas and the evaluation of manufacturing performance. This paper introduces methods of linking design and manufacturing domains using disparate technologies. The combined technologies include knowledge management supporting for product lifecycle management systems, Enterprise Resource Planning (ERP) systems, aggregate process planning systems, workflow management and data exchange formats. A case study has been used to demonstrate the use of these technologies, illustrated by adding manufacturing knowledge to generate alternative early process plan which are in turn used by an ERP system to obtain and optimise a rough-cut capacity plan. Copyright © 2010 Inderscience Enterprises Ltd.

The ENCARA system for face detection and normalization

[EN]Facial image processing is becoming widespread in human-computer applications, despite its complexity. High-level processes such as face recognition or gender determination rely on low-level routines that must e ectively detect and normalize the faces that appear in the input image. In this paper, a face detection and normalization system is described. The approach taken is based on a cascade of fast, weak classi ers that together try to determine whether a frontal face is present in the image.

Multilevel processes and cultural adaptation: examples from past and present small-scale societies

The last two decades have seen a proliferation of research frameworks that emphasise the importance of understanding adaptive processes that happen at different levels. We contribute to this growing body of literature by exploring how cultural (mal)adaptive dynamics relate to multilevel social-ecological processes occurring at different scales, where the lower levels combine into new units with new organizations, functions, and emergent properties or collective behaviors. After a brief review of the concept of “cultural adaptation” from the perspective of cultural evolutionary theory, the core of the paper is constructed around the exploration of multilevel processes occurring at the temporal, spatial, social, and political scales. We do so by using insights from cultural evolutionary theory and by examining small-scale societies as case studies. In each section, we discuss the importance of the selected scale for understanding cultural adaptation and then present an example that illustrates how multilevel processes in the selected scale help explain observed patterns in the cultural adaptive process. The last section of the paper discusses the potential of modeling and computer simulation for studying multilevel processes in cultural adaptation. We conclude by highlighting how elements from cultural evolutionary theory might enrich the multilevel process discussion in resilience theory.

Aplicaciones de los modelos de predicción bio-inspirados en la administración

Las organizaciones y sus entornos son sistemas complejos. Tales sistemas son difíciles de comprender y predecir. Pese a ello, la predicción es una tarea fundamental para la gestión empresarial y para la toma de decisiones que implica siempre un riesgo. Los métodos clásicos de predicción (entre los cuales están: la regresión lineal, la Autoregresive Moving Average y el exponential smoothing) establecen supuestos como la linealidad, la estabilidad para ser matemática y computacionalmente tratables. Por diferentes medios, sin embargo, se han demostrado las limitaciones de tales métodos. Pues bien, en las últimas décadas nuevos métodos de predicción han surgido con el fin de abarcar la complejidad de los sistemas organizacionales y sus entornos, antes que evitarla. Entre ellos, los más promisorios son los métodos de predicción bio-inspirados (ej. redes neuronales, algoritmos genéticos /evolutivos y sistemas inmunes artificiales). Este artículo pretende establecer un estado situacional de las aplicaciones actuales y potenciales de los métodos bio-inspirados de predicción en la administración.

EEG-based Brain-Computer Interfaces: An Overview of Basic Concepts and Clinical Applications in Neurorehabilitation

Some patients are no longer able to communicate effectively or even interact with the outside world in ways that most of us take for granted. In the most severe cases, tetraplegic or post-stroke patients are literally `locked in` their bodies, unable to exert any motor control after, for example, a spinal cord injury or a brainstem stroke, requiring alternative methods of communication and control. But we suggest that, in the near future, their brains may offer them a way out. Non-invasive electroencephalogram (EEG)-based brain-computer interfaces (BCD can be characterized by the technique used to measure brain activity and by the way that different brain signals are translated into commands that control an effector (e.g., controlling a computer cursor for word processing and accessing the internet). This review focuses on the basic concepts of EEG-based BC!, the main advances in communication, motor control restoration and the down-regulation of cortical activity, and the mirror neuron system (MNS) in the context of BCI. The latter appears to be relevant for clinical applications in the coming years, particularly for severely limited patients. Hypothetically, MNS could provide a robust way to map neural activity to behavior, representing the high-level information about goals and intentions of these patients. Non-invasive EEG-based BCIs allow brain-derived communication in patients with amyotrophic lateral sclerosis and motor control restoration in patients after spinal cord injury and stroke. Epilepsy and attention deficit and hyperactive disorder patients were able to down-regulate their cortical activity. Given the rapid progression of EEG-based BCI research over the last few years and the swift ascent of computer processing speeds and signal analysis techniques, we suggest that emerging ideas (e.g., MNS in the context of BC!) related to clinical neuro-rehabilitation of severely limited patients will generate viable clinical applications in the near future.

Using visual spatial search interface for WWW applications

Most Internet search engines are keyword-based. They are not efficient for the queries where geographical location is important, such as finding hotels within an area or close to a place of interest. A natural interface for spatial searching is a map, which can be used not only to display locations of search results but also to assist forming search conditions. A map-based search engine requires a well-designed visual interface that is intuitive to use yet flexible and expressive enough to support various types of spatial queries as well as aspatial queries. Similar to hyperlinks for text and images in an HTML page, spatial objects in a map should support hyperlinks. Such an interface needs to be scalable with the size of the geographical regions and the number of websites it covers. In spite of handling typically a very large amount of spatial data, a map-based search interface should meet the expectation of fast response time for interactive applications. In this paper we discuss general requirements and the design for a new map-based web search interface, focusing on integration with the WWW and visual spatial query interface. A number of current and future research issues are discussed, and a prototype for the University of Queensland is presented. (C) 2001 Published by Elsevier Science Ltd.

Hand gesture recognition system based in computer vision and machine learning : applications on human-machine interaction

Sendo uma forma natural de interação homem-máquina, o reconhecimento de gestos implica uma forte componente de investigação em áreas como a visão por computador e a aprendizagem computacional. O reconhecimento gestual é uma área com aplicações muito diversas, fornecendo aos utilizadores uma forma mais natural e mais simples de comunicar com sistemas baseados em computador, sem a necessidade de utilização de dispositivos extras. Assim, o objectivo principal da investigação na área de reconhecimento de gestos aplicada à interacção homemmáquina é o da criação de sistemas, que possam identificar gestos específicos e usálos para transmitir informações ou para controlar dispositivos. Para isso as interfaces baseados em visão para o reconhecimento de gestos, necessitam de detectar a mão de forma rápida e robusta e de serem capazes de efetuar o reconhecimento de gestos em tempo real. Hoje em dia, os sistemas de reconhecimento de gestos baseados em visão são capazes de trabalhar com soluções específicas, construídos para resolver um determinado problema e configurados para trabalhar de uma forma particular. Este projeto de investigação estudou e implementou soluções, suficientemente genéricas, com o recurso a algoritmos de aprendizagem computacional, permitindo a sua aplicação num conjunto alargado de sistemas de interface homem-máquina, para reconhecimento de gestos em tempo real. A solução proposta, Gesture Learning Module Architecture (GeLMA), permite de forma simples definir um conjunto de comandos que pode ser baseado em gestos estáticos e dinâmicos e que pode ser facilmente integrado e configurado para ser utilizado numa série de aplicações. É um sistema de baixo custo e fácil de treinar e usar, e uma vez que é construído unicamente com bibliotecas de código. As experiências realizadas permitiram mostrar que o sistema atingiu uma precisão de 99,2% em termos de reconhecimento de gestos estáticos e uma precisão média de 93,7% em termos de reconhecimento de gestos dinâmicos. Para validar a solução proposta, foram implementados dois sistemas completos. O primeiro é um sistema em tempo real capaz de ajudar um árbitro a arbitrar um jogo de futebol robótico. A solução proposta combina um sistema de reconhecimento de gestos baseada em visão com a definição de uma linguagem formal, o CommLang Referee, à qual demos a designação de Referee Command Language Interface System (ReCLIS). O sistema identifica os comandos baseados num conjunto de gestos estáticos e dinâmicos executados pelo árbitro, sendo este posteriormente enviado para um interface de computador que transmite a respectiva informação para os robôs. O segundo é um sistema em tempo real capaz de interpretar um subconjunto da Linguagem Gestual Portuguesa. As experiências demonstraram que o sistema foi capaz de reconhecer as vogais em tempo real de forma fiável. Embora a solução implementada apenas tenha sido treinada para reconhecer as cinco vogais, o sistema é facilmente extensível para reconhecer o resto do alfabeto. As experiências também permitiram mostrar que a base dos sistemas de interação baseados em visão pode ser a mesma para todas as aplicações e, deste modo facilitar a sua implementação. A solução proposta tem ainda a vantagem de ser suficientemente genérica e uma base sólida para o desenvolvimento de sistemas baseados em reconhecimento gestual que podem ser facilmente integrados com qualquer aplicação de interface homem-máquina. A linguagem formal de definição da interface pode ser redefinida e o sistema pode ser facilmente configurado e treinado com um conjunto de gestos diferentes de forma a serem integrados na solução final.

Brain-computer interface (BCI): a methodological proposal to assess the impacts of medical applications in 2022

Based on the report for “Project IV” unit of the PhD programme on Technology Assessment (Doctoral Conference) at Universidade Nova de Lisboa (December 2011). This thesis research has the supervision of António Moniz (FCT-UNL and ITAS-KIT) and Armin Grunwald (Karlsruhe Institute of Technology-ITAS, Germany). Other members of the thesis committee are Mário Forjaz Secca (FCT-UNL) and Femke Nijboer (University of Twente, Netherlands).

Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.

Hand gesture recognition system based in computer vision and machine learning: Applications on human-machine interaction

Tese de Doutoramento em Engenharia de Eletrónica e de Computadores

THE USE OF SIMULATIONS IN EVOLUTIONARY POPULATION GENETICS: APPLICATIONS ON HUMANS, OWLS AND VIRTUAL ORGANISMS

Summary (in English) Computer simulations provide a practical way to address scientific questions that would be otherwise intractable. In evolutionary biology, and in population genetics in particular, the investigation of evolutionary processes frequently involves the implementation of complex models, making simulations a particularly valuable tool in the area. In this thesis work, I explored three questions involving the geographical range expansion of populations, taking advantage of spatially explicit simulations coupled with approximate Bayesian computation. First, the neutral evolutionary history of the human spread around the world was investigated, leading to a surprisingly simple model: A straightforward diffusion process of migrations from east Africa throughout a world map with homogeneous landmasses replicated to very large extent the complex patterns observed in real human populations, suggesting a more continuous (as opposed to structured) view of the distribution of modern human genetic diversity, which may play a better role as a base model for further studies. Second, the postglacial evolution of the European barn owl, with the formation of a remarkable coat-color cline, was inspected with two rounds of simulations: (i) determine the demographic background history and (ii) test the probability of a phenotypic cline, like the one observed in the natural populations, to appear without natural selection. We verified that the modern barn owl population originated from a single Iberian refugium and that they formed their color cline, not due to neutral evolution, but with the necessary participation of selection. The third and last part of this thesis refers to a simulation-only study inspired by the barn owl case above. In this chapter, we showed that selection is, indeed, effective during range expansions and that it leaves a distinguished signature, which can then be used to detect and measure natural selection in range-expanding populations. Résumé (en français) Les simulations fournissent un moyen pratique pour répondre à des questions scientifiques qui seraient inabordable autrement. En génétique des populations, l'étude des processus évolutifs implique souvent la mise en oeuvre de modèles complexes, et les simulations sont un outil particulièrement précieux dans ce domaine. Dans cette thèse, j'ai exploré trois questions en utilisant des simulations spatialement explicites dans un cadre de calculs Bayésiens approximés (approximate Bayesian computation : ABC). Tout d'abord, l'histoire de la colonisation humaine mondiale et de l'évolution de parties neutres du génome a été étudiée grâce à un modèle étonnement simple. Un processus de diffusion des migrants de l'Afrique orientale à travers un monde avec des masses terrestres homogènes a reproduit, dans une très large mesure, les signatures génétiques complexes observées dans les populations humaines réelles. Un tel modèle continu (opposé à un modèle structuré en populations) pourrait être très utile comme modèle de base dans l'étude de génétique humaine à l'avenir. Deuxièmement, l'évolution postglaciaire d'un gradient de couleur chez l'Effraie des clocher (Tyto alba) Européenne, a été examiné avec deux séries de simulations pour : (i) déterminer l'histoire démographique de base et (ii) tester la probabilité qu'un gradient phénotypique, tel qu'observé dans les populations naturelles puisse apparaître sans sélection naturelle. Nous avons montré que la population actuelle des chouettes est sortie d'un unique refuge ibérique et que le gradient de couleur ne peux pas s'être formé de manière neutre (sans l'action de la sélection naturelle). La troisième partie de cette thèse se réfère à une étude par simulations inspirée par l'étude de l'Effraie. Dans ce dernier chapitre, nous avons montré que la sélection est, en effet, aussi efficace dans les cas d'expansion d'aire de distribution et qu'elle laisse une signature unique, qui peut être utilisée pour la détecter et estimer sa force.