An ensemble of intelligent water drop algorithms and its application to optimization problems

Crown Copyright © 2015 Published by Elsevier Inc. All rights reserved. The Intelligent Water Drop (IWD) algorithm is a recent stochastic swarm-based method that is useful for solving combinatorial and function optimization problems. In this paper, we propose an IWD ensemble known as the Master-River, Multiple-Creek IWD (MRMC-IWD) model, which serves as an extension of the modified IWD algorithm. The MRMC-IWD model aims to improve the exploration capability of the modified IWD algorithm. It comprises a master river which cooperates with multiple independent creeks to undertake optimization problems based on the divide-and-conquer strategy. A technique to decompose the original problem into a number of sub-problems is first devised. Each sub-problem is then assigned to a creek, while the overall solution is handled by the master river. To empower the exploitation capability, a hybrid MRMC-IWD model is introduced. It integrates the iterative improvement local search method with the MRMC-IWD model to allow a local search to be conducted, therefore enhancing the quality of solutions provided by the master river. To evaluate the effectiveness of the proposed models, a series of experiments pertaining to two combinatorial problems, i.e., the travelling salesman problem (TSP) and rough set feature subset selection (RSFS), are conducted. The results indicate that the MRMC-IWD model can satisfactorily solve optimization problems using the divide-and-conquer strategy. By incorporating a local search method, the resulting hybrid MRMC-IWD model not only is able to balance exploration and exploitation, but also to enable convergence towards the optimal solutions, by employing a local search method. In all seven selected TSPLIB problems, the hybrid MRMC-IWD model achieves good results, with an average deviation of 0.021% from the best known optimal tour lengths. Compared with other state-of-the-art methods, the hybrid MRMC-IWD model produces the best results (i.e. the shortest and uniform reducts of 20 runs) for all13 selected RSFS problems.

Emergent behaviour: learning from an artificially intelligent performing software agent

This research investigates the possibility for emergent choreographic behaviour to arise from the interactions between a human dancer and a learning, digital performing agent. The cognitive framework is extended through theories of distributed cognition to take into account the two interacting agents rather than a single agent and its environment. The Artificial Neural Network based performing agent demonstrated emergent dance behaviour when performing live with the human dancer. The agent was able to follow the dancer, create movement phrases based on what the dancer was performing and recognize short movement phrases, as a result of the interaction of the dancer’s motion captured movement data and the agent’s artificial neural network. This emergent behaviour was not explicitly programmed, but emerged as a result of the learning process and the interactions with the human dancer.

Domain-driven classification based on multiple criteria and multiple constraint-level programming for intelligent credit scoring

Extracting knowledge from the transaction records and the personal data of credit card holders has great profit potential for the banking industry. The challenge is to detect/predict bankrupts and to keep and recruit the profitable customers. However, grouping and targeting credit card customers by traditional data-driven mining often does not directly meet the needs of the banking industry, because data-driven mining automatically generates classification outputs that are imprecise, meaningless, and beyond users' control. In this paper, we provide a novel domain-driven classification method that takes advantage of multiple criteria and multiple constraint-level programming for intelligent credit scoring. The method involves credit scoring to produce a set of customers' scores that allows the classification results actionable and controllable by human interaction during the scoring process. Domain knowledge and experts' experience parameters are built into the criteria and constraint functions of mathematical programming and the human and machine conversation is employed to generate an efficient and precise solution. Experiments based on various data sets validated the effectiveness and efficiency of the proposed methods. © 2006 IEEE.

Intelligent risk detection in healthcare contexts of hip and knee athroplasty and paediatric congenital heart disease

Rapid increase of service demands in healthcare contexts today requires a robust framework enabled by IT (information technology) solutions as well as real-time service handling in order to ensure superior decision making and successful healthcare outcomes. Contemporaneous with the challenges facing healthcare, we are witnessing the development of very sophisticated intelligent tools and technologies such as Business Analytics techniques. Therefore, it would appear to be prudent to investigate the possibility of applying such tools and technologies into various healthcare contexts to facilitate better risk detection and support superior decision making. The following serves to do this in the context of Total Hip and Knee Arthroplasty and Congenital Heart Disease.

'All intelligent subjects' – Presenting scientific collecting and identity at the Hawke's Bay Philosophical Institute Museum, 1865-1899

This paper traces a shift in New Zealand’s Scientific Heritage, and the performance and presentation of scientific knowledge and identity through collecting and museum practice – based on a case study of the Hawke’s Bay Philosophical Institute Museum, during the period 1865 -1899. Two very well-known figures of New Zealand science, Museums and collecting were central in Hawke’s Bay: William Colenso FLS FRS; and Augustus Hamilton, who later became Director of the Colonial Museum in Wellington. Through them, can be traced how scientific collections and identities evolved, from the work of gentlemen of science to that of a newly professionalised vocation, realised within the spaces of Museums.

DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL

To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can intelligently adapt to the evolving conditions and infer new knowledge with algorithms that are not predesigned is crucially needed. This dissertation research studies the integration of the techniques and methodologies resulted from the fields of pattern recognition, intelligent agents, artificial immune systems, and distributed computing platforms, to create technologies that can more accurately describe and control the dynamics of real-world complex systems. The need for such technologies is emerging in manufacturing, transportation, hazard mitigation, weather and climate prediction, homeland security, and emergency response. Motivated by the ability of mobile agents to dynamically incorporate additional computational and control algorithms into executing applications, mobile agent technology is employed in this research for the adaptive sensing and monitoring in a wireless sensor network. Mobile agents are software components that can travel from one computing platform to another in a network and carry programs and data states that are needed for performing the assigned tasks. To support the generation, migration, communication, and management of mobile monitoring agents, an embeddable mobile agent system (Mobile-C) is integrated with sensor nodes. Mobile monitoring agents visit distributed sensor nodes, read real-time sensor data, and perform anomaly detection using the equipped pattern recognition algorithms. The optimal control of agents is achieved by mimicking the adaptive immune response and the application of multi-objective optimization algorithms. The mobile agent approach provides potential to reduce the communication load and energy consumption in monitoring networks. The major research work of this dissertation project includes: (1) studying effective feature extraction methods for time series measurement data; (2) investigating the impact of the feature extraction methods and dissimilarity measures on the performance of pattern recognition; (3) researching the effects of environmental factors on the performance of pattern recognition; (4) integrating an embeddable mobile agent system with wireless sensor nodes; (5) optimizing agent generation and distribution using artificial immune system concept and multi-objective algorithms; (6) applying mobile agent technology and pattern recognition algorithms for adaptive structural health monitoring and driving cycle pattern recognition; (7) developing a web-based monitoring network to enable the visualization and analysis of real-time sensor data remotely. Techniques and algorithms developed in this dissertation project will contribute to research advances in networked distributed systems operating under changing environments.

Hybrid Power System Intelligent Operation and Protection Involving Distributed Architectures and Pulsed Loads

Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available protection concepts and devices for AC systems in a DC network, were presented. A study was also conducted on the effect of changing the distribution architecture and distributing the storage assets on the various zones of the network on the system’s dynamic security and stability. A practical shipboard power system was studied as an example of a hybrid AC/DC power system involving pulsed loads. Generally, the proposed hybrid AC/DC power system, besides most of the ideas, controls and algorithms presented in this dissertation, were experimentally verified at the Smart Grid Testbed, Energy Systems Research Laboratory. All the developments in this dissertation were experimentally verified at the Smart Grid Testbed.

Learning data-driven models of non-verbal behaviors for building rapport using an intelligent virtual agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness.^ Evidence-based patient-centered Brief Motivational Interviewing (BMI) interventions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary.^ Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems.^ To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].^

Hybrid power system intelligent operation and protection involving plug-in electric vehicles

Two key solutions to reduce the greenhouse gas emissions and increase the overall energy efficiency are to maximize the utilization of renewable energy resources (RERs) to generate energy for load consumption and to shift to low or zero emission plug-in electric vehicles (PEVs) for transportation. The present U.S. aging and overburdened power grid infrastructure is under a tremendous pressure to handle the issues involved in penetration of RERS and PEVs. The future power grid should be designed with for the effective utilization of distributed RERs and distributed generations to intelligently respond to varying customer demand including PEVs with high level of security, stability and reliability. This dissertation develops and verifies such a hybrid AC-DC power system. The system will operate in a distributed manner incorporating multiple components in both AC and DC styles and work in both grid-connected and islanding modes. ^ The verification was performed on a laboratory-based hybrid AC-DC power system testbed as hardware/software platform. In this system, RERs emulators together with their maximum power point tracking technology and power electronics converters were designed to test different energy harvesting algorithms. The Energy storage devices including lithium-ion batteries and ultra-capacitors were used to optimize the performance of the hybrid power system. A lithium-ion battery smart energy management system with thermal and state of charge self-balancing was proposed to protect the energy storage system. A grid connected DC PEVs parking garage emulator, with five lithium-ion batteries was also designed with the smart charging functions that can emulate the future vehicle-to-grid (V2G), vehicle-to-vehicle (V2V) and vehicle-to-house (V2H) services. This includes grid voltage and frequency regulations, spinning reserves, micro grid islanding detection and energy resource support. ^ The results show successful integration of the developed techniques for control and energy management of future hybrid AC-DC power systems with high penetration of RERs and PEVs.^

Do intelligent heating controls out-smart ordinary users?

Nearly a third of UK gas and electricity is used in homes, of which 80% is for space heating and hot water provision. Rising consumer bills, concerns about climate change and the surge in personal digital technology use has provoked the development of intelligent domestic heating controls. Whilst the need for having suitable control of the home heating system is essential for reducing domestic energy use, these heating controls rely on appropriate user interaction to achieve a saving and it is unclear whether these ‘smart’ heating controls enhance the use of domestic heating or reduce energy demand. This paper describes qualitative research undertaken with a small sample of UK householders to understand how people use new heating controls installed in their homes and what the requirements are for improved smart heating control design. The paper identifies, against Nielsen’s usability heuristics, the divergence between the householder’s use, understanding and expectations of the heating system and the actual design of the system. Digital and smart heating control systems should be designed to maximise usability so that they can be effectively used for efficient heating control by all users. The research highlights the need for development of new systems to readdress the needs of users and redefine the system requirements.

Intelligent outcome measures in liaison psychiatry:essential even if not desirable. Commentary on... a multidimensional Framework for Routine Outcome Measurement in Liaison Psychiatry (FROM-LP)

Service development is guided by outcome measures that inform service commissioners and providers. Those in liaison psychiatry should be encouraged to develop a positive approach that integrates the collection of outcome measures into everyday clinical practice. The Framework for Routine Outcome Measurement in Liaison Psychiatry (FROM-LP) is a very useful tool to measure service quality and clinical effectiveness, using a combination of clinician-rated and patient-rated outcome measures and patient-rated experience measures. However, it does not include measures of cost-effectiveness or training activities. The FROM-LP is a significant step towards developing nationally unified outcome measures.

A importância da animação turística como complemento à oferta em hotéis de luxo

Hoje em dia o turismo apresenta-se como um dos principais potenciais económicos no sector dos serviços. Dentro do vasto sector que é o turismo, a hotelaria desempenha um papel fulcral para o sucesso de um destino. Embora seja um setor com elevado potencial de crescimento, é também conhecido pela elevada concorrência, os hotéis necessitam de inovar constantemente os seus serviços e oferecer experiências autênticas e únicas para se conseguirem diferenciar num mercado muito competitivo. Este trabalho surge de forma a procurar entender o papel que a animação turística pode desempenhar para complementar a oferta hoteleira. O caso de estudo para este trabalho é o Hotel Maria Cristina no País Basco, um hotel que se posiciona como hotel de luxo. Visto este posicionamento do hotel, vão ser apresentados conceitos e dados estatísticos do turismo no País Basco e do relacionamento da hotelaria com a animação turística e com o luxo.

O surfista e a sua satisfação na componente da experiência turística de surf

Nos últimos anos o surf atingiu uma dimensão avassaladora, quer em termos de mediatização, quer em termos da importância e impacto que tem na economia das sociedades em geral. O caso português é exemplo disso, e muito particularmente Peniche, com o fenómeno a fazer já parte dos documentos estratégicos da chamada economia do mar, por via do denominado turismo de surf. Hoje em dia Portugal é referenciado como um dos países com maior atratividade ao nível de destinos turísticos para a prática do surf, e Peniche pelas suas particulares características naturais, constitui-se como um dos principais polos dinamizadores desta atividade, o que se reflete na crescente oferta de produtos turísticos diretamente relacionados com o surf. O presente estudo, para além do enquadramento histórico-cronológico imprescindível à compreensão do fenómeno surf, teve como propósito a caracterização sumária do perfil do surfista/turista de surf que se desloca a Peniche, bem como aferir da sua satisfação relativamente a Peniche como destino turístico de surf e verificar se essa satisfação é passível de sofrer alterações consoante o nível de surf em que se julga encontrar. Para atingir os objetivos, foi construído um questionário que foi aplicado a turistas praticantes de surf que se tenham deslocado a Peniche, extraindo-se uma amostra de 363 indivíduos. Os resultados obtidos e o conhecimento produzido por esta investigação, para além de permitirem tipificar o turista praticante de surf que se desloca a Peniche e os seus níveis de satisfação, permitirão ainda a possibilidade de adequar políticas e estratégias condizentes com as expectativas deste nicho de mercado de modo a que de forma sustentável se possa retirar o máximo partido desta atividade.

A incorporação sociocultural como Fator Intensificador da Experiência Turística – o caso do Mercado Medieval de Óbidos

A Gestão da Experiência Turística Global dos Destinos tem vindo a assumir-­se nas Ciências do Turismo como uma base incontornável no âmbito da atratividade e consequentemente da própria Imagem Turística. O diagnóstico e compreensão dos mecanismos culturais, sociais, económicos e espaciais que influenciam o processo de intensificação da Experiência Turística é uma matéria em aberto, fazendo jus ao imenso campo de estudo que define a intangibilidade como elemento diferenciador da oferta turística de outros tipos de produtos. Mercê do seu percurso nos últimos anos, o Mercado Medieval de Óbidos (MMO) surgiu-­nos como um estudo de caso, suscetível de evidenciar num curto espaço temporal e numa área territorial totalmente definida, Fatores Intensificadores da Experiência Turística, cuja estratificação estará ainda numa fase embrionária. Com recurso a uma metodologia quantitativa e qualitativa, o presente estudo evidenciou a Incorporação sociocultural por parte do Turista ou Visitante como uma ferramenta de apropriação e integração na realidade local, perspetivando-­a como Fator Intensificador da Experiência Turística no MMO.

Relatório de estágio de marketing e promoção turística no grupo hoteleiro Lux Hotels

O presente relatório retrata a experiência vivida num estágio de marketing e promoção turística no grupo nacional hoteleiro Lux Hotels. Este relatório está estruturado em quatro capítulos de acordo com o estágio realizado. O estágio teve duração de nove meses, sendo que os primeiros sete meses decorreram no Lisboa Carmo Hotel, um dos hotéis do grupo, e os outros dois meses no departamento de marketing do grupo. O primeiro capítulo aborda a fundamentação teórica, onde são expostos e desenvolvidos os conceitos de marketing turístico, a importância do marketing no setor hoteleiro, o marketing e as relações públicas e, por fim, a importância da internet e das redes sociais no turismo. Todos estes temas estão diretamente ligados com as tarefas realizadas ao longo do estágio. O segundo capítulo descreve a empresa onde decorreu o estágio. Neste capítulo é apresentado, de forma pormenorizada, o grupo hoteleiro, a sua história, conceito e desenvolvimento, bem como uma análise pessoal ao marketing do grupo. Também neste capítulo é possível encontrar alguns aspetos personalizados acerca do Lisboa Carmo Hotel. O terceiro capítulo descreve todas as tarefas realizadas ao longo do estágio, relacionadas com marketing e promoção no turismo. Por último, o capítulo quatro são as conclusões, onde se pode ler uma análise critica acerca do estágio e tarefas desenvolvidas. Com este trabalho pretendo mostrar as funções de um agente de marketing num grupo hoteleiro a nível nacional.