Towards an Integrated Framework for Applying the Agile Project Methodology to Manage Task Uncertainty in Disaster Management

Natural and man-made disasters are a constant threat to cultural civilizations and pose various risks to the basic foundations of our known existence. Not only do these situations occur at any time and place; they have various unknown determinants until the tragedy exists. Task uncertainty remains a critical factor in disaster management. This research study examines different facets of task uncertainty and develops an integrated research framework that applies the agile project methodology, in particular Scrum, to properly manage the impact of task uncertainty in disaster response, coordination, mitigation and recovery. Our framework provides insights to researchers and practitioners alike and offers guidelines for effective management of task uncertainty in projects. Implications for future research and practice are discussed

Development of a health management information system using agile software-engineering methods

>Magister Scientiae - MScThe purpose of this thesis is to discuss the development of a web application from scratch. It serves to build a health management information system from basic principles and covers all the software engineering activities starting from the gathering of requirements, evaluating these and eventually implementing a health management information system by applying several iterations of the Agile-extreme-programming-software-engineering approach to develop a Health Management System for the Kabul University Poly-clinic located at Kabul University campus in order to computerize clerical activities at the hospital. Questionnaires were used to uncover the clerical problems experienced by the hospital sta . Attempts to address these problems by designing and im- plementing software and re ne the software after some iterations of feedback- redesign-and-implementation following the guidelines of Agile extreme pro- gramming. The previous Health management systems at the hospital were paper based. The new computerized system has eased the burdens of tracking the les of patients at the hospital, leading to easier and more e cient access to information by the health-care professionals at the hospital. An assessment of the impact this has had on the medical and clerical sta and the smoother administration of the hospital by repeated user acceptance testing by means of questionnaires con rms the success of the project

Reliability Analysis of On-Demand High-Speed Machining

Current trends in high-speed machining aim to increase manufacturing efficiency by maximizing material removal rates and minimizing part cycle times. This project explores three related technologies and presents a system design for rapid production of custom machined parts. First a reliability analysis in high-speed machining of thin wall features is put forth with experimental results. Second an implementation of on-demand manufacturing is presented with emphasis on flexibility and automation. Finally innovative manufacturing cell design is used to drive costs down by optimizing material and information flow. The resulting high-speed on-demand machining cell design employs effective techniques to reduce production time, meet changing customer needs, and drive down costs

Hydrogen Sensor Application of Anodic Titanium Oxide Nanostructures

Hydrogen (H2) fuel cells have been considered a promising renewable energy source. The recent growth of H2 economy has required highly sensitive, micro-sized and cost-effective H2 sensor for monitoring concentrations and alerting to leakages due to the flammability and explosiveness of H2 Titanium dioxide (TiO2) made by electrochemical anodic oxidation has shown great potential as a H2 sensing material. The aim of this thesis is to develop highly sensitive H2 sensor using anodized TiO2. The sensor enables mass production and integration with microelectronics by preparing the oxide layer on suitable substrate. Morphology, elemental composition, crystal phase, electrical properties and H2 sensing properties of TiO2 nanostructures prepared on Ti foil, Si and SiO2/Si substrates were characterized. Initially, vertically oriented TiO2 nanotubes as the sensing material were obtained by anodizing Ti foil. The morphological properties of tubes could be tailored by varying the applied voltages of the anodization. The transparent oxide layer creates an interference color phenomena with white light illumination on the oxide surface. This coloration effect can be used to predict the morphological properties of the TiO2 nanostructures. The crystal phase transition from amorphous to anatase or rutile, or the mixture of anatase and rutile was observed with varying heat treatment temperatures. However, the H2 sensing properties of TiO2 nanotubes at room temperature were insufficient. H2 sensors using TiO2 nanostructures formed on Si and SiO2/Si substrates were demonstrated. In both cases, a Ti layer deposited on the substrates by a DC magnetron sputtering method was successfully anodized. A mesoporous TiO2 layer obtained on Si by anodization in an aqueous electrolyte at 5°C showed diode behavior, which was influenced by the work function difference of Pt metal electrodes and the oxide layer. The sensor enabled the detection of H2 (20-1000 ppm) at low operating temperatures (50–140°C) in ambient air. A Pd decorated tubular TiO2 layer was prepared on metal electrodes patterned SiO2/Si wafer by anodization in an organic electrolyte at 5°C. The sensor showed significantly enhanced H2 sensing properties, and detected hydrogen in the range of a few ppm with fast response/recovery time. The metal electrodes placed under the oxide layer also enhanced the mechanical tolerance of the sensor. The concept of TiO2 nanostructures on alternative substrates could be a prospect for microelectronic applications and mass production of gas sensors. The gas sensor properties can be further improved by modifying material morphologies and decorating it with catalytic materials.Siirretty Doriast

Human Machine Interaction

In this book, the reader will find a set of papers divided into two sections. The first section presents different proposals focused on the human-machine interaction development process. The second section is devoted to different aspects of interaction, with a special emphasis on the physical interaction

La percepción como muestreo estocástico en grafos dinámicos

Esta tesis estudia y desarrolla técnicas novedosas que permiten a los robots percibir apropiadamente el entorno de forma autónoma. Para conseguir esto es posible y conveniente usar la información del entorno de la que se disponga. Generalmente, dicha información queda plasmada en el código del robot como construcciones if-then-else difíciles de entender cuando el mundo del robot es considerablemente complejo. Se propone el uso de “Active Grammar-based Modeling” (AGM), una técnica desarrollada dentro de la tesis, que usa descripciones de muy alto nivel que permiten al desarrollador obtener más flexibilidad y escalabilidad, así como reducir el tiempo de desarrollo y la cantidad de errores que se cometen al programar los robots. La solución propuesta pasa por describir la gramática del entorno en un lenguaje específico de dominio que posteriormente se traduce a PDDL, permitiendo usar así planificadores de Inteligencia Artificial clásicos para decidir qué ha de hacer el robot para cumplir sus objetivos y comprobar que las modificaciones que el robot hace al modelo del entorno son válidas de acuerdo a la gramática. Además, AGM permite coordinar fácilmente diferentes filtros de partículas para su ejecución simultánea, pudiendo además elegir distintos filtros de partículas dependiendo del contexto en el que el robot se encuentre, optimizando así el sistema perceptivo de los robots. Además de dicha técnica la tesis presenta diferentes algoritmos usados dentro de AGM, así como varios experimentos relacionados con el modelado activo de entornos de interior usando cámaras RGBD.This thesis develops and studies novel techniques that allow robots to properly model their environments autonomously. For this purpose it is possible and feasible to use all the available information that robots can use. Generally this information results in if-then-else constructs that are hard to understand then the environments of the robots are considerably complex. It is proposed to use “Active Grammar-based Modeling” (AGM), a new technique developed within this thesis. It uses very high-level descriptions that allow developers to achieve higher flexibility and scalability, as well as reducing the development time and the amount of programming errors. The solution consists on describing the grammar of the environment using a domain-specific language that is compiled into PDDL, allowing AGM-based systems to use classic AI planners to decide what robots should do to achieve their goales and incrementally verify that the model generated is valid according to the grammar described. Moreover, AGM can coordinate different particle filters so they can work simultaneously, allowing to choose the most appropriate filters depending on the context. This enhances the accuracy and effectivenes of the perceptual systems of the robots Along AGM, this thesis also presents the different algorithms used by AGM, as well as different experiment related to active indoor modeling using RGBD cameras

Tools and Technologies for Enabling Characterisation in Synthetic Biology

Synthetic Biology represents a movement to utilise biological organisms for novel applications through the use of rigorous engineering principles. These principles rely on a solid and well versed understanding of the underlying biological components and functions (relevant to the application). In order to achieve this understanding, reliable behavioural and contextual information is required (more commonly known as characterisation data). Focussing on lowering the barrier of entry for current research facilities to regularly and easily perform characterisation assays will directly improve the communal knowledge base for Synthetic Biology and enable the further application of rational engineering principles. Whilst characterisation remains a fundamental principle for Synthetic Biology research, the high time costs, subjective measurement protocols, and ambiguous data analysis specifications, deter regular performance of characterisation assays. Vitally, this prevents the valid application of many of the key Synthetic Biology processes that have been derived to improve research yield (with regards to solving application problems) and directly prevent the intended goal of addressing the ad hoc nature of modern research from being realised. Designing new technologies and tools to facilitate rapid ‘hands off’ characterisation assays for research facilities will improve the uptake of characterisation within the research pipeline. To achieve this two core problem areas have been identified that limit current characterisation attempts in conventional research. Therefore, it was the primary aim of this investigation to overcome these two core problems to promote regular characterisation. The first issue identified as preventing the regular use of characterisation assays was the user-intensive methodologies and technologies available to researchers. There is currently no standardised characterisation equipment for assaying samples and the methodologies are heavily dependent on the researcher and their application for successful and complete characterisation. This study proposed a novel high throughput solution to the characterisation problem that was capable of low cost, concurrent, and rapid characterisation of simple biological DNA elements. By combining in vitro transcription-translation with microfluidics a potent solution to the characterisation problem was proposed. By utilising a completely in vitro approach along with excellent control abilities of microfluidic technologies, a prototype platform for high throughput characterisation was developed. The second issue identified was the lack of flexible, versatile software designed specifically for the data handling needs that are quickly arising within the characterisation speciality. The lack of general solutions in this area is problematic because of the increasing amount of data that is both required and generated for the characterisation output to be considered as rigorous and of value. To alleviate this issue a novel framework for laboratory data handling was developed that employs a plugin strategy for data submission and analysis. Employing a plugin strategy improves the shelf life of data handling software by allowing it to grow with the needs of the speciality. Another advantage to this strategy is the increased ability for well documented processing and analysis standards to arise that are available for all researchers. Finally, the software provided a powerful and flexible data storage schema that allowed all currently conceivable characterisation data types to be stored in a well-documented manner. The two solutions identified within this study increase the amount of enabling tools and technologies available to researchers within Synthetic Biology, which in turn will increase the uptake of regular characterisation. Consequently, this will potentially improve the lateral transfer of knowledge between research projects and reduce the need to perform ad hoc experiments to investigate facets of the fundamental biological components being utilised.Open Acces