4 resultados para Context and activity Recognition

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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Context-aware computing is currently considered the most promising approach to overcome information overload and to speed up access to relevant information and services. Context-awareness may be derived from many sources, including user profile and preferences, network information, sensor analysis; usually context-awareness relies on the ability of computing devices to interact with the physical world, i.e. with the natural and artificial objects hosted within the "environment”. Ideally, context-aware applications should not be intrusive and should be able to react according to user’s context, with minimum user effort. Context is an application dependent multidimensional space and the location is an important part of it since the very beginning. Location can be used to guide applications, in providing information or functions that are most appropriate for a specific position. Hence location systems play a crucial role. There are several technologies and systems for computing location to a vary degree of accuracy and tailored for specific space model, i.e. indoors or outdoors, structured spaces or unstructured spaces. The research challenge faced by this thesis is related to pedestrian positioning in heterogeneous environments. Particularly, the focus will be on pedestrian identification, localization, orientation and activity recognition. This research was mainly carried out within the “mobile and ambient systems” workgroup of EPOCH, a 6FP NoE on the application of ICT to Cultural Heritage. Therefore applications in Cultural Heritage sites were the main target of the context-aware services discussed. Cultural Heritage sites are considered significant test-beds in Context-aware computing for many reasons. For example building a smart environment in museums or in protected sites is a challenging task, because localization and tracking are usually based on technologies that are difficult to hide or harmonize within the environment. Therefore it is expected that the experience made with this research may be useful also in domains other than Cultural Heritage. This work presents three different approaches to the pedestrian identification, positioning and tracking: Pedestrian navigation by means of a wearable inertial sensing platform assisted by the vision based tracking system for initial settings an real-time calibration; Pedestrian navigation by means of a wearable inertial sensing platform augmented with GPS measurements; Pedestrian identification and tracking, combining the vision based tracking system with WiFi localization. The proposed localization systems have been mainly used to enhance Cultural Heritage applications in providing information and services depending on the user’s actual context, in particular depending on the user’s location.

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Ambient Intelligence (AmI) envisions a world where smart, electronic environments are aware and responsive to their context. People moving into these settings engage many computational devices and systems simultaneously even if they are not aware of their presence. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. The dependence on a large amount of fixed and mobile sensors embedded into the environment makes of Wireless Sensor Networks one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes, simple devices that typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. In order to handle the large amount of data generated by a WSN several multi sensor data fusion techniques have been developed. The aim of multisensor data fusion is to combine data to achieve better accuracy and inferences than could be achieved by the use of a single sensor alone. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas: Multimodal Surveillance and Activity Recognition. Novel techniques to handle data from a network of low-cost, low-power Pyroelectric InfraRed (PIR) sensors are presented. Such techniques allow the detection of the number of people moving in the environment, their direction of movement and their position. We discuss how a mesh of PIR sensors can be integrated with a video surveillance system to increase its performance in people tracking. Furthermore we embed a PIR sensor within the design of a Wireless Video Sensor Node (WVSN) to extend its lifetime. Activity recognition is a fundamental block in natural interfaces. A challenging objective is to design an activity recognition system that is able to exploit a redundant but unreliable WSN. We present our activity in building a novel activity recognition architecture for such a dynamic system. The architecture has a hierarchical structure where simple nodes performs gesture classification and a high level meta classifiers fuses a changing number of classifier outputs. We demonstrate the benefit of such architecture in terms of increased recognition performance, and fault and noise robustness. Furthermore we show how we can extend network lifetime by performing a performance-power trade-off. Smart objects can enhance user experience within smart environments. We present our work in extending the capabilities of the Smart Micrel Cube (SMCube), a smart object used as tangible interface within a tangible computing framework, through the development of a gesture recognition algorithm suitable for this limited computational power device. Finally the development of activity recognition techniques can greatly benefit from the availability of shared dataset. We report our experience in building a dataset for activity recognition. Such dataset is freely available to the scientific community for research purposes and can be used as a testbench for developing, testing and comparing different activity recognition techniques.

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This thesis reports an integrated analytical approach for the study of physicochemical and biological properties of new synthetic bile acid (BA) analogues agonists of FXR and TGR5 receptors. Structure-activity data were compared with those previous obtained using the same experimental protocols on synthetic and natural occurring BA. The new synthetic BA analogues are classified in different groups according also to their potency as a FXR and TGR5 agonists: unconjugated and steroid modified BA and side chain modified BA including taurine or glycine conjugates and pseudo-conjugates (sulphonate and sulphate analogues). In order to investigate the relationship between structure and activity the synthetic analogues where admitted to a physicochemical characterization and to a preliminary screening for their pharmacokinetic and metabolism using a bile fistula rat model. Sensitive and accurate analytical methods have been developed for the quali-quantitative analysis of BA in biological fluids and sample used for physicochemical studies. Combined High Performance Liquid Chromatography Electrospray tandem mass spectrometry with efficient chromatographic separation of all studied BA and their metabolites have been optimized and validated. Analytical strategies for the identification of the BA and their minor metabolites have been developed. Taurine and glycine conjugates were identified in MS/MS by monitoring the specific ion transitions in multiple reaction monitoring (MRM) mode while all other metabolites (sulphate, glucuronic acid, dehydroxylated, decarboxylated or oxo) were monitored in a selected-ion reaction (SIR) mode with a negative ESI interface by the following ions. Accurate and precise data where achieved regarding the main physicochemical properties including solubility, detergency, lipophilicity and albumin binding . These studies have shown that minor structural modification greatly affect the pharmacokinetics and metabolism of the new analogues in respect to the natural BA and on turn their site of action, particularly where their receptor are located in the enterohepatic circulation.

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This thesis tends to study the origins and developments of the restoration in Iran from its very first moments till the Islamic revolution of 1978. The thesis is its first study of its kind. While almost all recent occidental ideologies regarding the thematic of restoration and conservation of historic monuments are translated and published in Iran, very little efforts have been done regarding the study of the origins of the formation of restoration in the country. The diversity of Iranian contexts, multiplicity of the intervening factors and other factors characterized a different background for the raise and developments of restoration in the country; in the thesis the influencing and characterizing factors in the formation and development of restoration in Iran will be defined and studied in detail with relative examples; due to the complexity of the Iranian context and in order to consider all influencing and characterizing factors the thesis, parallel to have formation and development of restoration, as the main scope of the research, the developments influencing factors will be confronted with necessary flashbacks to the main theme, when and where necessary. A great care will be given to the period of the activity of the restoration experts of IsMEO which is thesis will be called as the period of the introduction of the modern principles of restoration into Iranian context; the fundamental ideologies, practical and theoretical principles of IsMEO will be identified and studied in details; important case of studies of the restoration of IsMEO will be analyzed in details and the innovative aspect of the presence of Italian experts of IsMEO will be revealed.