Chan, Fai. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 104-108). / Abstracts in English and Chinese. / Chapter 1. --- Introduction --- p.14 / Chapter 1.1. --- Background --- p.14 / Chapter 1.1.1. --- Introduction to Intelligent Surveillance System (ISS) --- p.14 / Chapter 1.1.2. --- Typical architecture of Surveillance System --- p.17 / Chapter 1.1.3. --- Single-camera vs Multi-camera Surveillance System --- p.17 / Chapter 1.1.4. --- Intelligent Surveillance System with Face Recognition (ISFAR) --- p.20 / Chapter 1.1.5. --- Minimal requirements for automatic Face Recognition --- p.21 / Chapter 1.2. --- Motivation --- p.22 / Chapter 1.3. --- Major Contributions --- p.26 / Chapter 1.3.1. --- A unified design framework for IS FAR --- p.26 / Chapter 1.3.2. --- Prototyping of IS FAR (ISFARO) --- p.29 / Chapter 1.3.3. --- Evaluation of ISFARO --- p.29 / Chapter 1.4. --- Thesis Organization --- p.30 / Chapter 2. --- Related Works --- p.31 / Chapter 2.1. --- Distant Human Identification (DHID) --- p.31 / Chapter 2.2. --- Distant Targets Identification System --- p.33 / Chapter 2.3. --- Virtual Vision System with Camera Scheduling --- p.35 / Chapter 3. --- A unified design framework for IS FAR --- p.37 / Chapter 3.1. --- Camera system modeling --- p.40 / Chapter 3.1.1. --- Stereo Triangulation (Human face location estimation) --- p.40 / Chapter 3.1.2. --- Camera system calibration --- p.42 / Chapter 3.2. --- Human face detection --- p.44 / Chapter 3.3. --- Human face tracking --- p.46 / Chapter 3.4. --- Human face correspondence --- p.50 / Chapter 3.4.1. --- Information consistency in stereo triangulation --- p.51 / Chapter 3.4.2. --- Proposed object correspondent algorithm --- p.52 / Chapter 3.5. --- Human face location and velocity estimation --- p.57 / Chapter 3.6. --- Human-Camera Synchronization --- p.58 / Chapter 3.6.1. --- Controlling a PTZ Camera for capturing human facial images --- p.60 / Chapter 3.6.2. --- Mathematical Formulation of the Human Face Capturing Problem --- p.61 / Chapter 4. --- Prototyping of lSFAR (ISFARO) --- p.64 / Chapter 4.1. --- Experiment Setup --- p.64 / Chapter 4.2. --- Speed of the PTZ camera 一 AXIS 213 PTZ --- p.67 / Chapter 4.3. --- Performance of human face detection and tracking --- p.68 / Chapter 4.4. --- Performance of human face correspondence --- p.72 / Chapter 4.5. --- Performance of human face location estimation --- p.74 / Chapter 4.6. --- Stability test of the Human-Camera Synchronization model --- p.75 / Chapter 4.7. --- Performance of ISFARO in capturing human facial images --- p.76 / Chapter 4.8. --- System Profiling of ISFARO --- p.79 / Chapter 4.9. --- Summary --- p.79 / Chapter 5. --- Improvements to ISFARO --- p.80 / Chapter 5.1. --- System Dynamics oflSFAR --- p.80 / Chapter 5.2. --- Proposed improvements to ISFARO --- p.82 / Chapter 5.2.1. --- Semi-automatic camera system calibration --- p.82 / Chapter 5.2.2. --- Velocity estimation using Kalman filter --- p.83 / Chapter 5.2.3. --- Reduction in PTZ camera delay --- p.87 / Chapter 5.2.4. --- Compensation of image blurriness due to motion from human --- p.89 / Chapter 5.3. --- Experiment Setup --- p.91 / Chapter 5.4. --- Performance of human face location estimation --- p.91 / Chapter 5.5. --- Speed of the PTZ Camera - SONY SNC RX-570 --- p.93 / Chapter 5.6. --- Performance of human face velocity estimation --- p.95 / Chapter 5.7. --- Performance of improved ISFARO in capturing human facial images --- p.99 / Chapter 6. --- Conclusions --- p.101 / Chapter 7. --- Bibliography --- p.104

Doctor of Philosophy / All surveillance systems are based on an effective general surveillance system because this is the system that detects emerging diseases and the re-introduction of disease to a previously disease free area. General surveillance requires comprehensive coverage of the population through an extensive network of relationships between animal producers and observers and surveillance system officers. This system is under increasing threat in Australia (and many other countries) due to the increased biomass, animal movements, rate of disease emergence, and the decline in resource allocation for surveillance activities. The Australian surveillance system is state-based and has a complex management structure that includes State and Commonwealth government representatives, industry stakeholders (such as producer bodies) and private organisations. A developing problem is the decline in the effectiveness of the general surveillance system in the extensive (remote) cattle producing regions of northern Australia. The complex organisational structure of surveillance in Australia contributes to this, and is complicated by the incomplete capture of data (as demonstrated by slow uptake of electronic individual animal identification systems), poorly developed and integrated national animal health information systems, and declining funding streams for field and laboratory personnel and infrastructure. Of major concern is the reduction in contact between animal observers and surveillance personnel arising from the decline in resource allocation for surveillance. Fewer veterinarians are working in remote areas, fewer producers use veterinarians, and, as a result, fewer sick animals are being investigated by the general surveillance system. A syndrome is a collection of signs that occur in a sick individual. Syndromic surveillance is an emerging approach to monitoring populations for change in disease levels and is based on statistical monitoring of the distribution of signs, syndromes and associations between health variables in a population. Often, diseases will have syndromes that are characteristic and the monitoring of these syndromes may provide for early detection of outbreaks. Because the process uses general signs, this method may support the existing (struggling) general surveillance system for the extensive cattle producing regions of northern Australia. Syndromic surveillance systems offer many potential advantages. First, the signs that are monitored can be general and include any health-related variable. This generality provides potential as a detector of emerging diseases. Second, many of the data types used occur early in a disease process and therefore efficient syndromic surveillance systems can detect disease events in a timely manner. There are many hurdles to the successful deployment of a syndromic surveillance system and most relate to data. An effective system will ideally obtain data from multiple sources, all data will conform to a standard (therefore each data source can be validly combined), data coverage will be extensive (across the population) and data capture will be in real time (allowing early detection). This picture is one of a functional electronic data world and unfortunately this is not the norm for either human or animal heath. Less than optimal data, lack of data standards, incomplete coverage of the population and delayed data transmission result in a loss of sensitivity, specificity and timeliness of detection. In human syndromic surveillance, most focus has been placed on earlier detection of mass bioterrorism events and this has concentrated research on the problems of electronic data. Given the current state of animal health data, the development of efficient detection algorithms represents the least of the hurdles. However, the world is moving towards increased automation and therefore the problems with current data can be expected to be resolved in the next decade. Despite the lack of large scale deployment of these systems, the question is becoming when, not whether these system will contribute. The observations of a stock worker are always the start of the surveillance pathway in animal health. Traditionally this required the worker to contact a veterinarian who would investigate unusual cases with the pathway ending in laboratory samples and specific diagnostic tests. The process is inefficient as only a fraction of cases observed by stock workers end in diagnostic samples. These observations themselves are most likely to be amenable to capture and monitoring using syndromic surveillance techniques. A pilot study of stock workers in the extensive cattle producing Lower Gulf region of Queensland demonstrated that experienced non-veterinary observers of cattle can describe the signs that they see in sick cattle in an effective manner. Lay observers do not posses a veterinary vocabulary, but the provision of a system to facilitate effective description of signs resulted in effective and standardised description of disease. However, most producers did not see personal benefit from providing this information and worried that they might be exposing themselves to regulatory impost if they described suspicious signs. Therefore the pilot study encouraged the development of a syndromic surveillance system that provides a vocabulary (a template) for lay observers to describe disease and a reason for them to contribute their data. The most important disease related drivers for producers relate to what impact the disease may have in their herd. For this reason, the Bovine Syndromic Surveillance System (BOSSS) was developed incorporating the Bayesian cattle disease diagnostic program BOVID. This allowed the observer to receive immediate information from interpretation of their observation providing a differential list of diseases, a list of questions that may help further differentiate cause, access to information and other expertise, and opportunity to benchmark disease performance. BOSSS was developed as a web-based reporting system and used a novel graphical user interface that interlinked with an interrogation module to enable lay observers to accurately and fully describe disease. BOSSS used a hierarchical reporting system that linked individual users with other users along natural reporting pathways and this encouraged the seamless and rapid transmission of information between users while respecting confidentiality. The system was made available for testing at the state level in early 2006, and recruitment of producers is proceeding. There is a dearth of performance data from operational syndromic surveillance systems. This is due, in part, to the short period that these systems have been operational and the lack of major human health outbreaks in areas with operational systems. The likely performance of a syndromic surveillance system is difficult to theorise. Outbreaks vary in size and distribution, and quality of outbreak data capture is not constant. The combined effect of a lack of track record and the many permutations of outbreak and data characteristics make computer simulation the most suitable method to evaluate likely performance. A stochastic simulation model of disease spread and disease reporting by lay observers throughout a grid of farms was modelled. The reporting characteristics of lay observers were extrapolated from the pilot study and theoretical disease was modelled (as a representation of newly emergent disease). All diseases were described by their baseline prevalence and by conditional sign probabilities (obtained from BOVID and from a survey of veterinarians in Queensland). The theoretical disease conditional sign probabilities were defined by the user. Their spread through the grid of farms followed Susceptible-Infected-Removed (SIR) principles (in herd) and by mass action between herds. Reporting of disease events and signs in events was modelled as a probabilistic event using sampling from distributions. A non-descript disease characterised by gastrointestinal signs and a visually spectacular disease characterised by neurological signs were modelled, each over three outbreak scenarios (least, moderately and most contagious). Reports were examined using two algorithms. These were the cumulative sum (CuSum) technique of adding excess of cases (above a maximum limit) for individual signs and the generic detector What’s Strange About Recent Events (WSARE) that identifies change to variable counts or variable combination counts between time periods. Both algorithms detected disease for all disease and outbreak characteristics combinations. WSARE was the most efficient algorithm, detecting disease on average earlier than CuSum. Both algorithms had high sensitivity and excellent specificity. The timeliness of detection was satisfactory for the insidious gastrointestinal disease (approximately 24 months after introduction), but not sufficient for the visually spectacular neurological disease (approximately 20 months) as the traditional surveillance system can be expected to detect visually spectacular diseases in reasonable time. Detection efficiency was not influenced greatly by the proportion of producers that report or by the proportion of cases or the number of signs per case that are reported. The modelling process demonstrated that a syndromic surveillance system in this remote region is likely to be a useful addition to the existing system. Improvements that are planned include development of a hand-held computer version and enhanced disease and syndrome mapping capability. The increased use of electronic recording systems, including livestock identification, will facilitate the deployment of BOSSS. Long term sustainability will require that producers receive sufficient reward from BOSSS to continue to provide reports over time. This question can only be answered by field deployment and this work is currently proceeding.

This is a visual arts project consisting of 20% exegesis and 80% practical work. My work explores the visual possibilities of using the digital accumulation of data to convey socio-political concepts in relation to the surveillance of the individual in modern western society. The nature of surveillance is investigated with reference to Michel Foucault's metaphorical use of Jeremy Bentham's panopticon in describing the organization of society in the modern nation state. My critical interest lies in the intrusive aspect of surveillance in regard to the privacy of the individual and the concomitant sense of alienation and disempowerment. The concept of 'abstract reality' has been developed to describe the nature of the surveillance of the individual in the modern nation state.

<p>Wireless Sensor Network (WSN), a collection of “sensor nodes” promises to change the scientist’s approach of gathering the environmental data in various fields. Sensor nodes can be used for non-stop sensing, event detection, location sensing and local control of actuators, this concept gives surety to many latest application areas like agriculture, military, home or factory automation, logistics and so on. Remote surveillance and measurement missions can be performed by using WSNs. The hot research topic now-a-days is to make such networks remotely controllable and adaptive to the environment and mission.</p><p> </p><p>The work carried out in this thesis is the development of a surveillance application using TinyOS/nesC. The purpose of this application is to perform event-detection mission by using any one of the built-in sensor on Mica2 motes as well as a setup protocol is designed to make the WSN remotely controllable and adaptive to the mission. In this thesis, an experimental work is also performed using TinyDB to build up a surveillance system whose purpose is to detect and count the total number of person present at any time in a given room and to view the results at a remote place. Besides these two system applications, a comparative study between TinyDB and nesC is described which concludes that more hardware control can be achieved through nesC which is a more power efficient platform for long-term applications.</p>

Active Surveillance (AS) for the clinical management of prostate cancer (PC) is a treatment option for men with low-risk PC. Screening procedures have led to the overdetection of PCs that would have never caused problems. Active treatment (e.g., surgery or radiation) for these non-aggressive tumors may not be necessary given the slow-growing nature of PC. AS provides a way to monitor the disease and delay treatment-related compromises on quality of life until clinically indicated (e.g., rising PSA level). However, the intensive monitoring in AS may be a stressful experience and lead to greater anxiety, an emotional state that has been associated with undergoing active treatment despite physician recommendation for AS. The current study aimed to identify psychosocial correlates of anxiety in men undergoing AS. Using Mishel’s Reconceptualized Uncertainty in Illness Model as a framework, the proposed study aimed to examine the relationships between perceived stress management skills, PC psychosocial concerns, and anxiety/arousal. Hierarchical multiple regression analyses were conducted on a sample of 71 men undergoing AS, who were on average 65.40 years old (SD=7.85) and ethnically diverse (52% non-Hispanic White; 31% Hispanic; 17% African American). Results indicated that greater PSMS were significantly associated with less IES-R anxiety (β=-.28, p<.04). PSMS were not significantly associated with PC concerns (β=-.02, p>.05), but greater PC concerns were significantly associated with greater IES-R anxiety (β=.61, p<.01) and PSA anxiety (β=.42, p<.01). These associations held after controlling for relevant covariates. The results suggest a possible role for stress management skills as perceived ability to manage stress was related to less anxiety in the AS experience. Future studies should examine the relationship among these factors in longitudinal designs and whether greater stress is associated with unnecessary active treatment in low-risk PC.

Cette thèse défend l’idée que, dans la lignée des événements qui ont suivi les attentats terroristes du 11 septembre 2001, le paradigme de la gestion du risque est devenu central dans les études de sécurité et dans les analyses de relations internationales. Dans le climat de risque engendré par les actes de terreur, le discours politique a mis en œuvre une biopolitique de la peur dans le but de normaliser les populations. Conséquemment, la surveillance est devenue une méthode de gouvernance de la société du risque, elle-même née d’une culture de la peur et du risque. Cette société du risque est construite politiquement et véhiculée par des récits précis qui ont pour but de gouverner un monde qui se gère de plus en plus difficilement, comme le montre l’ambiguïté des interprétations données aux attentats du 11 septembre 2001 et des différents langages pour les expliquer.

The purpose of this study is to better understand the ways in which scientific discourse contributes to the individualization and moralization of obesity, through reality television. Popular reality television programs emphasize the importance of lifestyle to health and wellness, often focusing on participant weight loss. Within this research, I describe the ways in which the obesity epidemic is approached in popular reality television, specifically in NBCs The Biggest Loser, and identify how the discourse of obesity is tied to issues of individualization, surveillance, and morality. Specifically, I undertake a laboratory study of The Biggest Loser to illustrate how this methodology can be extended from the traditional laboratory into a space of science that has no formal walls. With a focus on the seventh season of The Biggest Loser, I argue that the program is based on a human experiment that illustrates the interconnectedness of science and society, while perpetuating individualized and moralized obesity discourse. By conducting a laboratory study of a popular television program, I offer a new way to address obesity discourse

Increased demand for animal disease surveillance information has led to the development and refinement of methodologies for qualitative and quantitative surveillance system evaluations to maximize efficiency and efficaciousness. The impetus for this surveillance evaluation project was chronic wasting disease (CWD) and the objectives were to apply both qualitative and quantitative methodologies to examine the components of CWD surveillance in Saskatchewan.<p> A retrospective review of deer pathology and hunter-harvest submissions in Saskatchewan was conducted through the Canadian Cooperative Wildlife Health Centre. Qualitative evaluation methods outlined by Klauke et al (1988) were used and included key stakeholder interviews. A quantitative evaluation, with specific focus on disease detection, was conducted to examine system sensitivity, confidence of disease freedom and to compare system components using methods described by Martin et al (2007). The analysis was conducted using a scenario tree and Monte Carlo simulation.<p> Sampling rates of dead and clinically ill deer were low with a high degree of variability by season, year, location and nature of submissions. Ultimately, variability of submission patterns likely affected when and where diseases were detected. Poor data quality reduced the amount of available data for analysis but quality dramatically improved over time.<p> The surveillance evaluation demonstrated that the current surveillance system places more emphasis on monitoring trends in CWD-positive areas, at the expense of early detection. This is explained mostly by the coupling of disease control efforts and surveillance, in that harvests are heavily focused in CWD-positive areas. The system is not sufficient to detect disease in new areas where the disease prevalence is low, primarily due to low submission rates.<p> The quantitative evaluation found that overall sensitivity of the surveillance system and confidence of disease freedom was highly dependent on detection prevalence and the ongoing risk of disease introduction. Surveillance in the eastern part of Saskatchewan was not adequate from 1997-2006 to detect CWD at 0.5-1% prevalence. However, if risk of CWD introduction over this time period was assumed to be low, it can be concluded that the prevalence in this region was not 5% or higher.<p> A detection goal of 0.5-1% prevalence is an ambitious surveillance goal, especially in areas where the risk of disease introduction is high. The use of more targeted surveillance strategies should be further explored to help better meet surveillance these surveillance objectives.

Dans ce travail nous proposons une adaptation du paradigme de la programmation par contrat - contrats exprimés sous forme de protocoles de comportement - au contexte des architectures orientées services, et ce à travers la conception d'un cadre d'applications (framework) supportant l'ensemble du processus de contractualisation, à savoir, la définition des contrats, la surveillance dynamique et la réaction en fonction du respect ou non des règles établies. La solution proposée permet de détecter les ruptures de contrat à chaud, c'est-à-dire en cours d'exécution des compositions de services, ouvrant ainsi la porte à l'instauration de mécanismes dynamiques de compensation. Les contrats surveillés représentent des protocoles de comportements de processus BPEL, ce qui permet de définir des contraintes sur l'ordre d'exécution des opérations publiques des services partenaires. Nous en présentons également une mise en œuvre, BPEL.RPM, qui est adaptable, dans le sens où elle peut aisément intégrer des modules externes de compensation, mais qui est aussi portable, puisqu'elle fonctionne indépendamment de l'environnement d'exécution des services Web. ______________________________________________________________________________ MOTS-CLÉS DE L’AUTEUR : services Web, programmation par contrat, surveillance dynamique, BPEL.

ABSTRACT A FOUCAULDIAN ANALYSIS OF NCLB: STUDENT DATA AS PANOPTIC SURVEILLANCE by Chris King The No Child Left Behind Act of 2001 (NCLB; Public Law 107-110) reauthorizes and expands the Elementary and Secondary Education Act of 1965 to require large amounts of student data for the purpose of academic surveillance. This study investigates the historical and philosophical components of Jeremy Bentham’s Panopticon as a model of surveillance to identify similarities between panopticism and the rubric of collecting student data required by NCLB. All public school districts are evaluated annually for adequate yearly progress (AYP). Under the auspices of this evaluation, all students must be tested, and all results must be included in each district’s AYP calculation. All African American, Hispanic, White, economically disadvantaged, special education, and limited English proficient (LEP) students must meet the same performance and participation standards. States individually develop minimum size criteria for evaluation of student groups. High schools must meet a graduation rate standard set by the state. NCLB’s comprehensive data compilation and student tracking initiatives are consistent with previous federal education policies to conduct data surveillance on students and teachers. Similar to Jeremy Bentham’s 18th century Panopticon model of penal supervision and rehabilitation, NCLB is transforming the schoolhouse into a correction house by unveiling technologies of surveillance and power. By using Benthamian and Foucauldian philosophical analyses, this dissertation examines NCLB’s worldview of student data and tracking, specifically from student subgroups, and their effects of panoptic surveillance. This dissertation proceeds with a review of the historical context of Jeremy Bentham’s Panopticon and Michel Foucault’s panopticism. This study recognizes various American educational reform movements from 1776 to 2002 in identifying the following panoptic disciplines: constant surveillance, hierarchical observation and categorization, and panoptic power. It considers the NCLB doctrine of data collection for student and teacher tracking purposes and presents an anticolonial analysis of NCLB’s methods of compiling and tracking student subgroup data using the works of anticolonial scholars Frantz Fanon, Sylvia Wynter, and Carter Woodson. The dissertation concludes with a synthesis of the questions and the problems presented by NCLB and the implications of this analysis for students and teachers.