Cognitive Surveillance Architecture for Scenario Understanding

Uno de los mayores retos para la comunidad científica es conseguir que las máquinas posean en un futuro la capacidad del sistema visual y cognitivo humanos, de forma que, por ejemplo, en entornos de video vigilancia, puedan llegar a proporcionar de manera automática una descripción fiable de lo que está ocurriendo en la escena. En la presente tesis, mediante la propuesta de un marco de trabajo de referencia, se discuten y plantean los pasos necesarios para el desarrollo de sistemas más inteligentes capaces de extraer y analizar, a diferentes niveles de abstracción y mediante distintos módulos de procesamiento independientes, la información necesaria para comprender qué está sucediendo en un conjunto amplio de escenarios de distinta naturaleza. Se parte de un análisis de requisitos y se identifican los retos para este tipo de sistemas en la actualidad, lo que constituye en sí mismo los objetivos de esta tesis, contribuyendo así a un modelo de datos basado en el conocimiento que permitirá analizar distintas situaciones en las que personas y vehículos son los actores principales, dejando no obstante la puerta abierta a la adaptación a otros dominios. Así mismo, se estudian los distintos procesos que se pueden lanzar a nivel interno así como la necesidad de integrar mecanismos de realimentación a distintos niveles que permitan al sistema adaptarse mejor a cambios en el entorno. Como resultado, se propone un marco de referencia jerárquico que integra las capacidades de percepción, interpretación y aprendizaje para superar los retos identificados en este ámbito; y así poder desarrollar sistemas de vigilancia más robustos, flexibles e inteligentes, capaces de operar en una variedad de entornos. Resultados experimentales ejecutados sobre distintas muestras de datos (secuencias de vídeo principalmente) demuestran la efectividad del marco de trabajo propuesto respecto a otros propuestos en el pasado. Un primer caso de estudio, permite demostrar la creación de un sistema de monitorización de entornos de parking en exteriores para la detección de vehículos y el análisis de plazas libres de aparcamiento. Un segundo caso de estudio, permite demostrar la flexibilidad del marco de referencia propuesto para adaptarse a los requisitos de un entorno de vigilancia completamente distinto, como es un hogar inteligente donde el análisis automático de actividades de la vida cotidiana centra la atención del estudio. ABSTRACT One of the most ambitious objectives for the Computer Vision and Pattern Recognition research community is that machines can achieve similar capacities to the human's visual and cognitive system, and thus provide a trustworthy description of what is happening in the scene under surveillance. Thus, a number of well-established scenario understanding architectural frameworks to develop applications working on a variety of environments can be found in the literature. In this Thesis, a highly descriptive methodology for the development of scene understanding applications is presented. It consists of a set of formal guidelines to let machines extract and analyse, at different levels of abstraction and by means of independent processing modules that interact with each other, the necessary information to understand a broad set of different real World surveillance scenarios. Taking into account the challenges that working at both low and high levels offer, we contribute with a highly descriptive knowledge-based data model for the analysis of different situations in which people and vehicles are the main actors, leaving the door open for the development of interesting applications in diverse smart domains. Recommendations to let systems achieve high-level behaviour understanding will be also provided. Furthermore, feedback mechanisms are proposed to be integrated in order to let any system to understand better the environment and the logical context around, reducing thus the uncertainty and noise, and increasing its robustness and precision in front of low-level or high-level errors. As a result, a hierarchical cognitive architecture of reference which integrates the necessary perception, interpretation, attention and learning capabilities to overcome main challenges identified in this area of research is proposed; thus allowing to develop more robust, flexible and smart surveillance systems to cope with the different requirements of a variety of environments. Once crucial issues that should be treated explicitly in the design of this kind of systems have been formulated and discussed, experimental results shows the effectiveness of the proposed framework compared with other proposed in the past. Two case studies were implemented to test the capabilities of the framework. The first case study presents how the proposed framework can be used to create intelligent parking monitoring systems. The second case study demonstrates the flexibility of the system to cope with the requirements of a completely different environment, a smart home where activities of daily living are performed. Finally, general conclusions and future work lines to further enhancing the capabilities of the proposed framework are presented.

Piezoelectric sensing and non-parametric statistical signal processing for health monitoring of hysteretic dampers used in seismic-resistant structures

The paper proposes a new application of non-parametric statistical processing of signals recorded from vibration tests for damage detection and evaluation on I-section steel segments. The steel segments investigated constitute the energy dissipating part of a new type of hysteretic damper that is used for passive control of buildings and civil engineering structures subjected to earthquake-type dynamic loadings. Two I-section steel segments with different levels of damage were instrumented with piezoceramic sensors and subjected to controlled white noise random vibrations. The signals recorded during the tests were processed using two non-parametric methods (the power spectral density method and the frequency response function method) that had never previously been applied to hysteretic dampers. The appropriateness of these methods for quantifying the level of damage on the I-shape steel segments is validated experimentally. Based on the results of the random vibrations, the paper proposes a new index that predicts the level of damage and the proximity of failure of the hysteretic damper

A role for intracellular pH in membrane IgM-mediated cell death of human B lymphomas

We show that anti-IgM-induced cell death in a human B lymphoma cell line, B104, is associated with early intracellular acidification and cell shrinkage. In contrast, another human B cell lymphoma line, Daudi, less susceptible to B cell antigen receptor-mediated cell death, responded to anti-IgM with an early increase in intracellular pH (pHi). The anti-IgM-induced changes of pHi were associated with different levels of activation of the Na+/H+ exchanger isoform 1 (NHE1) as judged by its phosphorylation status. Prevention of anti-IgM-induced cell death in B104 cells by the calcineurin phosphatase inhibitor, cyclosporin A, abrogated both intracellular acidification and cell shrinkage and was associated with an increase in the phosphorylation level of NHE1 within the first 60 min of stimulation. This indicates a key role for calcineurin in regulating pHi and cell viability. The potential role of pHi in cell viability was confirmed in Daudi cells treated with an Na+/H+ exchanger inhibitor 5-(N,N-hexamethylene)amiloride. These observations indicate that the outcome of the anti-IgM treatment depends on NHE1-controlled pHi. We suggest that inactivation of the NHE1 in anti-IgM-stimulated cells results in intracellular acidification and subsequently triggers or amplifies cell death.

Teaching as a fractal: from experience to model

The aim of this work is to improve students’ learning by designing a teaching model that seeks to increase student motivation to acquire new knowledge. To design the model, the methodology is based on the study of the students’ opinion on several aspects we think importantly affect the quality of teaching (such as the overcrowded classrooms, time intended for the subject or type of classroom where classes are taught), and on our experience when performing several experimental activities in the classroom (for instance, peer reviews and oral presentations). Besides the feedback from the students, it is essential to rely on the experience and reflections of lecturers who have been teaching the subject several years. This way we could detect several key aspects that, in our opinion, must be considered when designing a teaching proposal: motivation, assessment, progressiveness and autonomy. As a result we have obtained a teaching model based on instructional design as well as on the principles of fractal geometry, in the sense that different levels of abstraction for the various training activities are presented and the activities are self-similar, that is, they are decomposed again and again. At each level, an activity decomposes into a lower level tasks and their corresponding evaluation. With this model the immediate feedback and the student motivation are encouraged. We are convinced that a greater motivation will suppose an increase in the student’s working time and in their performance. Although the study has been done on a subject, the results are fully generalizable to other subjects.

Simulation Results of AgriPoliS about Diminishing Capital Subsidies and Restrictions. Factor Markets Working Document No. 55, June 2013

This paper investigates the impacts of high interest rates for borrowed capital and credit restrictions on the structural development of four European regions. The method used is the model AgriPoliS which is a spatial-dynamic agent-based model. It is able to provide aggregated results at the regional level, but very individual results as well by considering farms as independent entities. Farms can choose between different investment options during the simulation. Several scenarios with different interest rates for borrowed capital on the one hand as well as with different levels of credit restrictions on the other hand are tested and compared. Results show that higher interest rates have less impact on declining production branches than on expanding ones. If they have the possibility farms invest in the most profitable production branch which relative profitability might have changed with high interest rates. Credit restrictions lead farms to choose smaller and cheaper investments than expensive and large ones. Results also show that income losses in both cases due to under-investment compared to the reference situation are partially compensated by lower rental prices. The impacts on structural change also differ depending on the region and the initial situation. In summary, credit subsidies or imperfections on credit markets might have indirect impacts on the type of dominant investment and therefore on the whole regional agricultural sector as well.

Effects of Interspecific Gene Flow on the Phenotypic Variance-Covariance Matrix in Lake Victoria Cichlids

Quantitative genetics theory predicts adaptive evolution to be constrained along evolutionary lines of least resistance. In theory, hybridization and subsequent interspecific gene flow may however rapidly change the evolutionary constraints of a population and eventually change its evolutionary potential, but empirical evidence is still scarce. Using closely related species pairs of Lake Victoria cichlids sampled from four different islands with different levels of interspecific gene flow, we tested for potential effects of introgressive hybridization on phenotypic evolution in wild populations. We found that these effects differed among our study species. Constraints measured as the eccentricity of phenotypic variance-covariance matrices declined significantly with increasing gene flow in the less abundant species for matrices that have a diverged line of least resistance. In contrast we find no such decline for the more abundant species. Overall our results suggest that hybridization can change the underlying phenotypic variance-covariance matrix, potentially increasing the adaptive potential of such populations.

Self-efficacy and task performance: An investigation from two levels of analysis and specificity

This research adopts a resource allocation theoretical framework to generate predictions regarding the relationship between self-efficacy and task performance from two levels of analysis and specificity. Participants were given multiple trials of practice on an air traffic control task. Measures of task-specific self-efficacy and performance were taken at repeated intervals. The authors used multilevel analysis to demonstrate dynamic main effects, dynamic mediation and dynamic moderation. As predicted, the positive effects of overall task specific self-efficacy and general self-efficacy on task performance strengthened throughout practice. In line with these dynamic main effects, the effect of general self-efficacy was mediated by overall task specific self-efficacy; however this pattern emerged over time. Finally, changes in task specific self-efficacy were negatively associated with changes in performance at the within-person level; however this effect only emerged towards the end of practice for individuals with high levels of overall task specific self-efficacy. These novel findings emphasise the importance of conceptualising self-efficacy within a multi-level and multi-specificity framework and make a significant contribution to understanding the way this construct relates to task performance.

International technology transfer:perceptions and reality of quality and reliability

Impressions about product quality and reliability can depend as much on perceptions about brands and country of origin as on data regarding performance and failure. This has implications for companies in developing countries that need to compete with importers. For manufacturers in industrialised countries it has implications for the value of transferred technologies. This article considers the issue of quality and reliability when technology is transferred between countries with different levels of development. It is based on UK and Chinese company case studies and questionnaire surveys undertaken among three company groups: UK manufacturers; Chinese manufacturers; Chinese users. Results show that all three groups recognise quality and reliability as important and support the premise that foreign technology based machines made in China carry a price premium over Chinese machines based on local technology. Closer examination reveals a number of important differences concerning the perceptions and reality of quality and reliability between the groups.

The Mechanisms of wear of the video head

      This thesis examines the mechanism of wear occuring to the video head and their effect on signal reproduction. in particular it examines the wear occuring to manganese-zinc ferrite heads in sliding contact with iron oxide media.       A literature survey is presented, which covers magnetic recording technologies, focussing on video recording. Existing work on wear of magnetic heads is also examined, and gaps in the theoretical account of wear mechanisms presented in the literature are identified.       Pilot research was carrried out on the signal degradation and wear associated witha number of commercial video tapes, containing a range of head cleaning agents. From this research, the main body of the research was identified. A number of methods of wear measurement were examined for use in this project. Knoop diamond indentation was chosen because experimentation showed it to be capable of measuring wear occuring in situ. This technique was then used to examine the wear associated with different levels of A12O3 and Cr2O3 head cleaning agents.      The results of the research indicated that, whilst wear of the video head increases linearly with increasing HCA content, signal degradation does not vary significantly. The most significant differences in wear and signal reproduction were observed between the two HCAs. The signal degradation of heads worn with tape samples containing A12O3 HCA was found to be lower than heads worn with tapes containing Cr2O3 HCA.      The results also indicate that the wear to the head is an abrasive process characterised by ploughing of the ferrite surface and chipping of the edges of the head gap. Both phenomena appear to be caused by poor iron oxide and head cleaning particles, which create isolated asperities on the tape surface.   

The application of artificial neural networks to the interpretation and classification of freshwater benthic invertebrate communities

This thesis presents a thorough and principled investigation into the application of artificial neural networks to the biological monitoring of freshwater. It contains original ideas on the classification and interpretation of benthic macroinvertebrates, and aims to demonstrate their superiority over the biotic systems currently used in the UK to report river water quality. The conceptual basis of a new biological classification system is described, and a full review and analysis of a number of river data sets is presented. The biological classification is compared to the common biotic systems using data from the Upper Trent catchment. This data contained 292 expertly classified invertebrate samples identified to mixed taxonomic levels. The neural network experimental work concentrates on the classification of the invertebrate samples into biological class, where only a subset of the sample is used to form the classification. Other experimentation is conducted into the identification of novel input samples, the classification of samples from different biotopes and the use of prior information in the neural network models. The biological classification is shown to provide an intuitive interpretation of a graphical representation, generated without reference to the class labels, of the Upper Trent data. The selection of key indicator taxa is considered using three different approaches; one novel, one from information theory and one from classical statistical methods. Good indicators of quality class based on these analyses are found to be in good agreement with those chosen by a domain expert. The change in information associated with different levels of identification and enumeration of taxa is quantified. The feasibility of using neural network classifiers and predictors to develop numeric criteria for the biological assessment of sediment contamination in the Great Lakes is also investigated.

INTAMAP: the design and implementation of an interoperable automated interpolation web service

INTAMAP is a Web Processing Service for the automatic spatial interpolation of measured point data. Requirements were (i) using open standards for spatial data such as developed in the context of the Open Geospatial Consortium (OGC), (ii) using a suitable environment for statistical modelling and computation, and (iii) producing an integrated, open source solution. The system couples an open-source Web Processing Service (developed by 52°North), accepting data in the form of standardised XML documents (conforming to the OGC Observations and Measurements standard) with a computing back-end realised in the R statistical environment. The probability distribution of interpolation errors is encoded with UncertML, a markup language designed to encode uncertain data. Automatic interpolation needs to be useful for a wide range of applications and the algorithms have been designed to cope with anisotropy, extreme values, and data with known error distributions. Besides a fully automatic mode, the system can be used with different levels of user control over the interpolation process.

Use of dual-grating sensors formed by different types of fiber Bragg gratings for simultaneous temperature and strain measurements

We report on a systematic investigation of the dependence of both temperature and strain sensitivities on the fiber Bragg grating type, including the well-known Type I, Type IIA, and a new type that we have designated Type IA, using both hydrogen-free and hydrogenated B/Ge codoped fibres. We have identified distinct sensitivity characteristics for each grating type, and we have used them to implement a novel dual-grating, dual-parameter sensor device. Three dual-grating sensing schemes with different combinations of grating type have been constructed and compared, and that of a Type IA-Type IIA combination exhibits the best performance, which is also superior to that of previously reported grating-based structures. The characteristics of the measurement errors in such dual-grating sensor systems is also presented in detail. © 2004 Optical Society of America.

Methods of Regularities Searching Based on Optimal Partitioning

The purpose of discussed optimal valid partitioning (OVP) methods is uncovering of ordinal or continuous explanatory variables effect on outcome variables of different types. The OVP approach is based on searching partitions of explanatory variables space that in the best way separate observations with different levels of outcomes. Partitions of single variables ranges or two-dimensional admissible areas for pairs of variables are searched inside corresponding families. Statistical validity associated with revealed regularities is estimated with the help of permutation test repeating search of optimal partition for each permuted dataset. Method for output regularities selection is discussed that is based on validity evaluating with the help of two types of permutation tests.

The effect of ocular nutritional supplements on macular pigment optical density

This thesis describes the investigation of the effects of ocular supplements with different levels of nutrients on the macular pigment optical density (MPOD) in participants with healthy eyes. Abstract A review of the literature highlighted that ocular supplements are produced in various combinations of nutrients and concentrations. The ideal concentrations of nutrients such as lutein (L) have not been established. It was unclear whether different stages of eye disease require different concentrations of key nutrients, leading to the design of this study. The primary aim was to determine the effects of ocular supplements with different concentrations of nutrients on the MPOD of healthy participants. The secondary aim was to determine L and zeaxanthin (Z) intake at the start and end of the study through completion of food diaries. The primary study was split into two experiments. Experiment 1 was an exploratory study to determine sample size and experiment 2 the main study. Statistical power was calculated and a sample size of 38 was specified. Block stratification for age, gender and smoking habit was applied and from 101 volunteers 42 completed the study, 31 with both sets of food diaries. Four confounders were accounted for in the design of the study; gender, smoking habit, age and diet. Further factors that could affect comparability of results between studies were identified during the study and were not monitored; ethnicity, gastro-intestinal health, alcohol intake, body mass index and genetics. Comparisons were made between the sample population and the Sheffield general population according to recent demographic results in the public domain. Food diaries were analysed and shown to have no statistical difference when comparing baseline to final results. The average L and Z intake for the 31 participants who returned both sets of food diaries was initially 1.96mg and 1.51mg for the final food diaries. The effect of the two ocular supplements with different levels of xanthophyll (6mg lutein/zeaxanthin and 10mg lutein only) on MPOD was not significantly different over a four-month period.

The development of attenuation compensation models of fluorescence spectroscopy signals

This study examines the effect of blood absorption on the endogenous fluorescence signal intensity of biological tissues. Experimental studies were conducted to identify these effects. To register the fluorescence intensity, the fluorescence spectroscopy method was employed. The intensity of the blood flow was measured by laser Doppler flowmetry. We proposed one possible implementation of the Monte Carlo method for the theoretical analysis of the effect of blood on the fluorescence signals. The simulation is constructed as a four-layer skin optical model based on the known optical parameters of the skin with different levels of blood supply. With the help of the simulation, we demonstrate how the level of blood supply can affect the appearance of the fluorescence spectra. In addition, to describe the properties of biological tissue, which may affect the fluorescence spectra, we turned to the method of diffuse reflectance spectroscopy (DRS). Using the spectral data provided by the DRS, the tissue attenuation effect can be extracted and used to correct the fluorescence spectra.