907 resultados para User-Designer Collaboration, Problem Restructuring, Scenario Building
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A Bayesian optimization algorithm for the nurse scheduling problem is presented, which involves choosing a suitable scheduling rule from a set for each nurse’s assignment. Unlike our previous work that used GAs to implement implicit learning, the learning in the proposed algorithm is explicit, i.e. eventually, we will be able to identify and mix building blocks directly. The Bayesian optimization algorithm is applied to implement such explicit learning by building a Bayesian network of the joint distribution of solutions. The conditional probability of each variable in the network is computed according to an initial set of promising solutions. Subsequently, each new instance for each variable is generated by using the corresponding conditional probabilities, until all variables have been generated, i.e. in our case, a new rule string has been obtained. Another set of rule strings will be generated in this way, some of which will replace previous strings based on fitness selection. If stopping conditions are not met, the conditional probabilities for all nodes in the Bayesian network are updated again using the current set of promising rule strings. Computational results from 52 real data instances demonstrate the success of this approach. It is also suggested that the learning mechanism in the proposed approach might be suitable for other scheduling problems.
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This thesis aims to describe and demonstrate the developed concept to facilitate the use of thermal simulation tools during the building design process. Despite the impact of architectural elements on the performance of buildings, some influential decisions are frequently based solely on qualitative information. Even though such design support is adequate for most decisions, the designer will eventually have doubts concerning the performance of some design decisions. These situations will require some kind of additional knowledge to be properly approached. The concept of designerly ways of simulating focuses on the formulation and solution of design dilemmas, which are doubts about the design that cannot be fully understood nor solved without using quantitative information. The concept intends to combine the power of analysis from computer simulation tools with the capacity of synthesis from architects. Three types of simulation tools are considered: solar analysis, thermal/energy simulation and CFD. Design dilemmas are formulated and framed according to the architect s reflection process about performance aspects. Throughout the thesis, the problem is investigated in three fields: professional, technical and theoretical fields. This approach on distinct parts of the problem aimed to i) characterize different professional categories with regards to their design practice and use of tools, ii) investigate preceding researchers on the use of simulation tools and iii) draw analogies between the proposed concept, and some concepts developed or described in previous works about design theory. The proposed concept was tested in eight design dilemmas extracted from three case studies in the Netherlands. The three investigated processes are houses designed by Dutch architectural firms. Relevant information and criteria from each case study were obtained through interviews and conversations with the involved architects. The practical application, despite its success in the research context, allowed the identification of some applicability limitations of the concept, concerning the architects need to have technical knowledge and the actual evolution stage of simulation tools
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Part 5: Service Orientation in Collaborative Networks
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Part 4: Transition Towards Product-Service Systems
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Tese (doutorado)—Universidade de Brasília, Faculdade de Educação, Programa de Pós-Graduação em Educação, 2016.
Development of new scenario decomposition techniques for linear and nonlinear stochastic programming
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Une approche classique pour traiter les problèmes d’optimisation avec incertitude à deux- et multi-étapes est d’utiliser l’analyse par scénario. Pour ce faire, l’incertitude de certaines données du problème est modélisée par vecteurs aléatoires avec des supports finis spécifiques aux étapes. Chacune de ces réalisations représente un scénario. En utilisant des scénarios, il est possible d’étudier des versions plus simples (sous-problèmes) du problème original. Comme technique de décomposition par scénario, l’algorithme de recouvrement progressif est une des méthodes les plus populaires pour résoudre les problèmes de programmation stochastique multi-étapes. Malgré la décomposition complète par scénario, l’efficacité de la méthode du recouvrement progressif est très sensible à certains aspects pratiques, tels que le choix du paramètre de pénalisation et la manipulation du terme quadratique dans la fonction objectif du lagrangien augmenté. Pour le choix du paramètre de pénalisation, nous examinons quelques-unes des méthodes populaires, et nous proposons une nouvelle stratégie adaptive qui vise à mieux suivre le processus de l’algorithme. Des expériences numériques sur des exemples de problèmes stochastiques linéaires multi-étapes suggèrent que la plupart des techniques existantes peuvent présenter une convergence prématurée à une solution sous-optimale ou converger vers la solution optimale, mais avec un taux très lent. En revanche, la nouvelle stratégie paraît robuste et efficace. Elle a convergé vers l’optimalité dans toutes nos expériences et a été la plus rapide dans la plupart des cas. Pour la question de la manipulation du terme quadratique, nous faisons une revue des techniques existantes et nous proposons l’idée de remplacer le terme quadratique par un terme linéaire. Bien que qu’il nous reste encore à tester notre méthode, nous avons l’intuition qu’elle réduira certaines difficultés numériques et théoriques de la méthode de recouvrement progressif.
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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].^
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Recent studies on the economic status of women in Miami-Dade County (MDC) reveal an alarming rate of economic insecurity and significant obstacles for women to achieve economic security. Consistent barriers to women’s economic security affect not only the health and wellbeing of women and their families, but also economic prospects for the community. A key study reveals in Miami-Dade County, “Thirty-nine percent of single female-headed families with at least one child are living at or below the federal poverty level” and “over half of working women do not earn adequate income to cover their basic necessities” (Brion 2009, 1). Moreover, conventional measures of poverty do not adequately capture women’s struggles to support themselves and their families, nor do they document the numbers of women seeking basic self-sufficiency. Even though there is lack of accurate data on women in the county, which is a critical problem, there is also a dearth of social science research on existing efforts to enhance women’s economic security in Miami-Dade County. My research contributes to closing the information gap by examining the characteristics and strategies of women-led community development organizations (CDOs) in MDC, working to address women’s economic insecurity. The research is informed by a framework developed by Marilyn Gittell, who pioneered an approach to study women-led CDOs in the United States. On the basis of research in nine U.S. cities, she concluded that women-led groups increased community participation and “by creating community networks and civic action, they represent a model for community development efforts” (Gittell, et al. 2000, 123). My study documents the strategies and networks of women-led CDOs in MDC that prioritize women’s economic security. Their strategies are especially important during these times of economic recession and government reductions in funding towards social services. The focus of the research is women-led CDOs that work to improve social services access, economic opportunity, civic participation and capacity, and women’s rights. Although many women-led CDOs prioritize building social infrastructures that promote change, inequalities in economic and political status for women without economic security remain a challenge (Young 2004). My research supports previous studies by Gittell, et al., finding that women-led CDOs in Miami-Dade County have key characteristics of a model of community development efforts that use networking and collaboration to strengthen their broad, integrated approach. The resulting community partnerships, coupled with participation by constituents in the development process, build a foundation to influence policy decisions for social change. In addition, my findings show that women-led CDOs in Miami-Dade County have a major focus on alleviating poverty and economic insecurity, particularly that of women. Finally, it was found that a majority of the five organizations network transnationally, using lessons learned to inform their work of expanding the agency of their constituents and placing the economic empowerment of women as central in the process of family and community development.
Development of new scenario decomposition techniques for linear and nonlinear stochastic programming
Resumo:
Une approche classique pour traiter les problèmes d’optimisation avec incertitude à deux- et multi-étapes est d’utiliser l’analyse par scénario. Pour ce faire, l’incertitude de certaines données du problème est modélisée par vecteurs aléatoires avec des supports finis spécifiques aux étapes. Chacune de ces réalisations représente un scénario. En utilisant des scénarios, il est possible d’étudier des versions plus simples (sous-problèmes) du problème original. Comme technique de décomposition par scénario, l’algorithme de recouvrement progressif est une des méthodes les plus populaires pour résoudre les problèmes de programmation stochastique multi-étapes. Malgré la décomposition complète par scénario, l’efficacité de la méthode du recouvrement progressif est très sensible à certains aspects pratiques, tels que le choix du paramètre de pénalisation et la manipulation du terme quadratique dans la fonction objectif du lagrangien augmenté. Pour le choix du paramètre de pénalisation, nous examinons quelques-unes des méthodes populaires, et nous proposons une nouvelle stratégie adaptive qui vise à mieux suivre le processus de l’algorithme. Des expériences numériques sur des exemples de problèmes stochastiques linéaires multi-étapes suggèrent que la plupart des techniques existantes peuvent présenter une convergence prématurée à une solution sous-optimale ou converger vers la solution optimale, mais avec un taux très lent. En revanche, la nouvelle stratégie paraît robuste et efficace. Elle a convergé vers l’optimalité dans toutes nos expériences et a été la plus rapide dans la plupart des cas. Pour la question de la manipulation du terme quadratique, nous faisons une revue des techniques existantes et nous proposons l’idée de remplacer le terme quadratique par un terme linéaire. Bien que qu’il nous reste encore à tester notre méthode, nous avons l’intuition qu’elle réduira certaines difficultés numériques et théoriques de la méthode de recouvrement progressif.
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The establishment of support platforms for the development of a new culture in design education, in order to achieve both research exploitation and its results, as an approach to the industrial community, challenges higher education institutions to rethink their functioning, divided between investigation on their own initiative or on demand, and its usefulness / practical application. At the same time, through design education, how can they be the engine that aggregates all these frequently antagonistic interests? Polytechnic institutes are predisposed to collaboration and interdisciplinarity. In our course of Technology and Design of Furniture, the availability of a production unit, testing laboratories, and expertise in engineering, design and marketing, encourage the development of a holistic project. In order to develop such knowledge, we adapt three important ways of thinking in designing interactions influenced by the traditional approach, namely, 1) identifying and understanding a design problem, i.e. a market need, 2) defining the design process and knowing what can be used for design education, i.e. opportunities for design education, and 3) sustainability of this framework and design projects' alignment with education in the same field. We explain our approach by arguing from the academicenterprise experiences perspective. This concept is proposed as a way to achieve those three ways of thinking in design education. Then, a set of interaction attributes is defined to explain how engineering and product design education can enhance meaningful relations with manufacturers, stakeholders and society in general. A final discussion is presented with the implications and benefits of this approach. The results suggest that through academic-enterprise partnerships in design, several goals such as students' motivation, product design innovation and potential for knowledge transfer to industries can be achieved.
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Community development is centrally concerned with people in communities working together to achieve a common goal, that is, to collaborate, whether within local geographical communities, in communities of shared interests or among groups sharing a common identity. Its overarching goal is one of progressive transformational social change. As Belfast transitions from a conflict to a post-conflict society, there is a need for greater, more effective work at local community level in order to address a range of ongoing social and economic issues facing communities, including high levels of disadvantage and division. Given the significance of leadership in building effective collaboration and the centrality of collaboration for community development, it is important to understand how leadership is currently enacted and what kinds of leadership are required to support communities to collaborate effectively to bring about social change. This thesis thus centers on the kind of leadership practised and required to support collaboration for social change within the community sector in Belfast, a city that contains an estimated 28% of the total number of community and voluntary sector (CVS) organisations in Northern Ireland (Northern Ireland Council for Voluntary Action, 2012). Through a series of qualitative, in-depth interviews with people playing leadership roles in local communities, the study critically explores and analyses their experiences and perceptions in relation to leadership and collaboration. Community development in Belfast today is practised within a wider context of neoliberal policies, characterised by austerity and public spending cuts. Whilst not the only influencing factor, this context has had a particular and profound impact on the nature and role of community development practised, and on the kind of leadership enacted within it. The space for reflection and transformative action appears to be shrinking as the contraction of resources to support community development in local communities continues unabated. Those playing leadership roles increasingly find themselves compelled to spend time seeking resources and managing complex funding arrangements rather than focusing on the social change dimensions of their work. Collaboration as promoted by the state seems to have become an instrumental tactic used to implement its austerity measures and curtail the potential of the community sector. Despite this, local leaders are driving initiatives that attempt to push back, helping the sector refocus on its transformational goals of social change. To do this requires support. Those playing leadership roles require resources, including time, to encourage and enable communities to reconnect with the purpose and underpinning values of community development. Leaders also need support to develop and promote new, progressive narratives and visions and pursue these through building collaboration and solidarity.
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A comprehensive user model, built by monitoring a user's current use of applications, can be an excellent starting point for building adaptive user-centred applications. The BaranC framework monitors all user interaction with a digital device (e.g. smartphone), and also collects all available context data (such as from sensors in the digital device itself, in a smart watch, or in smart appliances) in order to build a full model of user application behaviour. The model built from the collected data, called the UDI (User Digital Imprint), is further augmented by analysis services, for example, a service to produce activity profiles from smartphone sensor data. The enhanced UDI model can then be the basis for building an appropriate adaptive application that is user-centred as it is based on an individual user model. As BaranC supports continuous user monitoring, an application can be dynamically adaptive in real-time to the current context (e.g. time, location or activity). Furthermore, since BaranC is continuously augmenting the user model with more monitored data, over time the user model changes, and the adaptive application can adapt gradually over time to changing user behaviour patterns. BaranC has been implemented as a service-oriented framework where the collection of data for the UDI and all sharing of the UDI data are kept strictly under the user's control. In addition, being service-oriented allows (with the user's permission) its monitoring and analysis services to be easily used by 3rd parties in order to provide 3rd party adaptive assistant services. An example 3rd party service demonstrator, built on top of BaranC, proactively assists a user by dynamic predication, based on the current context, what apps and contacts the user is likely to need. BaranC introduces an innovative user-controlled unified service model of monitoring and use of personal digital activity data in order to provide adaptive user-centred applications. This aims to improve on the current situation where the diversity of adaptive applications results in a proliferation of applications monitoring and using personal data, resulting in a lack of clarity, a dispersal of data, and a diminution of user control.
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Este estudio de caso busca identificar los elementos del portafolio de política exterior de Trinidad y Tobago que le permitieron promover exitosamente sus intereses en el Protocolo de Kioto. Al hacer esto, este texto analizará las limitaciones de Trinidad y Tobago en términos de vulnerabilidades de localización, burocracia y recursos. Posteriormente, una revisión del portafolio de política exterior de este Estado ilustrará el uso de estrategias de creación de capacidades y de organización como lo son el contacto con actores institucionales y no gubernamentales, la formación de coaliciones y estrategias argumentativas, entre otras. Finalmente, este artículo concluirá que dichas acciones permitieron la promoción de la agenda de política exterior de Trinidad y Tobago a través de la creación de hojas de ruta y la coordinación de la incertidumbre con el Protocolo de Kioto. Para hacer esto, este trabajo se concentrará en examinar conceptos como vulnerabilidad y priorización, asimismo contrastando diferentes artículos académicos en la materia junto con documentos oficiales de Trinidad y Tobago.
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Early definitions of Smart Building focused almost entirely on the technology aspect and did not suggest user interaction at all. Indeed, today we would attribute it more to the concept of the automated building. In this sense, control of comfort conditions inside buildings is a problem that is being well investigated, since it has a direct effect on users’ productivity and an indirect effect on energy saving. Therefore, from the users’ perspective, a typical environment can be considered comfortable, if it’s capable of providing adequate thermal comfort, visual comfort and indoor air quality conditions and acoustic comfort. In the last years, the scientific community has dealt with many challenges, especially from a technological point of view. For instance, smart sensing devices, the internet, and communication technologies have enabled a new paradigm called Edge computing that brings computation and data storage closer to the location where it is needed, to improve response times and save bandwidth. This has allowed us to improve services, sustainability and decision making. Many solutions have been implemented such as smart classrooms, controlling the thermal condition of the building, monitoring HVAC data for energy-efficient of the campus and so forth. Though these projects provide to the realization of smart campus, a framework for smart campus is yet to be determined. These new technologies have also introduced new research challenges: within this thesis work, some of the principal open challenges will be faced, proposing a new conceptual framework, technologies and tools to move forward the actual implementation of smart campuses. Keeping in mind, several problems known in the literature have been investigated: the occupancy detection, noise monitoring for acoustic comfort, context awareness inside the building, wayfinding indoor, strategic deployment for air quality and books preserving.
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In rural and isolated areas without cellular coverage, Satellite Communication (SatCom) is the best candidate to complement terrestrial coverage. However, the main challenge for future generations of wireless networks will be to meet the growing demand for new services while dealing with the scarcity of frequency spectrum. As a result, it is critical to investigate more efficient methods of utilizing the limited bandwidth; and resource sharing is likely the only choice. The research community’s focus has recently shifted towards the interference management and exploitation paradigm to meet the increasing data traffic demands. In the Downlink (DL) and Feedspace (FS), LEO satellites with an on-board antenna array can offer service to numerous User Terminals (UTs) (VSAT or Handhelds) on-ground in FFR schemes by using cutting-edge digital beamforming techniques. Considering this setup, the adoption of an effective user scheduling approach is a critical aspect given the unusually high density of User terminals on the ground as compared to the on-board available satellite antennas. In this context, one possibility is that of exploiting clustering algorithms for scheduling in LEO MU-MIMO systems in which several users within the same group are simultaneously served by the satellite via Space Division Multiplexing (SDM), and then these different user groups are served in different time slots via Time Division Multiplexing (TDM). This thesis addresses this problem by defining a user scheduling problem as an optimization problem and discusses several algorithms to solve it. In particular, focusing on the FS and user service link (i.e., DL) of a single MB-LEO satellite operating below 6 GHz, the user scheduling problem in the Frequency Division Duplex (FDD) mode is addressed. The proposed State-of-the-Art scheduling approaches are based on graph theory. The proposed solution offers high performance in terms of per-user capacity, Sum-rate capacity, SINR, and Spectral Efficiency.