766 resultados para OBSERVATIONAL ANALYSIS


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In public places, crowd size may be an indicator of congestion, delay, instability, or of abnormal events, such as a fight, riot or emergency. Crowd related information can also provide important business intelligence such as the distribution of people throughout spaces, throughput rates, and local densities. A major drawback of many crowd counting approaches is their reliance on large numbers of holistic features, training data requirements of hundreds or thousands of frames per camera, and that each camera must be trained separately. This makes deployment in large multi-camera environments such as shopping centres very costly and difficult. In this chapter, we present a novel scene-invariant crowd counting algorithm that uses local features to monitor crowd size. The use of local features allows the proposed algorithm to calculate local occupancy statistics, scale to conditions which are unseen in the training data, and be trained on significantly less data. Scene invariance is achieved through the use of camera calibration, allowing the system to be trained on one or more viewpoints and then deployed on any number of new cameras for testing without further training. A pre-trained system could then be used as a ‘turn-key’ solution for crowd counting across a wide range of environments, eliminating many of the costly barriers to deployment which currently exist.

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This paper presents a Six Sigma case study analysis involving three service organizations of Singapore. The organizations are a local hospital, a construction and related engineering service, and a consultancy service. These organizations embarked on their Six Sigma journey around 2003-2004. Though the hospital was slightly ahead than the other two in beginning Six Sigma. These organizations have since achieved significant service improvements through implementation of Six Sigma to their different divisions. Through a series of structured interviews with Six Sigma project champions, team leaders, and members; project reports; public archives; and observations; this study explores the Six Sigma journey of these organizations. The results portray a list of success factors which led to the Six Sigma initiatives, the process of Six Sigma implementation through proper identification of critical-to-quality characteristics, tools and techniques, and the performance indicators which display the improvements due to Six Sigma.

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There is a growing need for parametric design software that communicates building performance feedback in early architectural exploration to support decision-making. This paper examines how the circuit of design and analysis process can be closed to provide active and concurrent feedback between architecture and services engineering domains. It presents the structure for an openly customisable design system that couples parametric modelling and energy analysis software to allow designers to assess the performance of early design iterations quickly. Finally, it discusses how user interactions with the system foster information exchanges that facilitate the sharing of design intelligence across disciplines.

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Obesity has been widely regarded as a public health concern because of its adverse impact on individuals’ health. Systematic reviews have been published in examining the effect of obesity on depression, but with major emphasis on general obesity as measured by the body mass index. Despite a stronger effect of abdominal obesity on individuals’ physical health outcomes, to our best knowledge, no systematic review was undertaken with regard to the relationship between abdominal obesity and depression. This paper reports the results of a systematic review and meta-analysis of cross-sectional studies examining the relationship between abdominal obesity and depression in a general population. Multiple electronic databases were searched until the end of September 2009. 15 articles were systematically reviewed and meta-analyzed. The analysis showed that the odds ratio of having depression for individuals with abdominal obesity was 1.38 (95% CI, 1.22–1.57) as compared to those who are not obese. Furthermore, it was found that this relationship did not vary with potential confounders including gender, age, measurement of depression and abdominal obesity, and study quality.

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Two decades after its inception, Latent Semantic Analysis(LSA) has become part and parcel of every modern introduction to Information Retrieval. For any tool that matures so quickly, it is important to check its lore and limitations, or else stagnation will set in. We focus here on the three main aspects of LSA that are well accepted, and the gist of which can be summarized as follows: (1) that LSA recovers latent semantic factors underlying the document space, (2) that such can be accomplished through lossy compression of the document space by eliminating lexical noise, and (3) that the latter can best be achieved by Singular Value Decomposition. For each aspect we performed experiments analogous to those reported in the LSA literature and compared the evidence brought to bear in each case. On the negative side, we show that the above claims about LSA are much more limited than commonly believed. Even a simple example may show that LSA does not recover the optimal semantic factors as intended in the pedagogical example used in many LSA publications. Additionally, and remarkably deviating from LSA lore, LSA does not scale up well: the larger the document space, the more unlikely that LSA recovers an optimal set of semantic factors. On the positive side, we describe new algorithms to replace LSA (and more recent alternatives as pLSA, LDA, and kernel methods) by trading its l2 space for an l1 space, thereby guaranteeing an optimal set of semantic factors. These algorithms seem to salvage the spirit of LSA as we think it was initially conceived.

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Defence organisations perform information security evaluations to confirm that electronic communications devices are safe to use in security-critical situations. Such evaluations include tracing all possible dataflow paths through the device, but this process is tedious and error-prone, so automated reachability analysis tools are needed to make security evaluations faster and more accurate. Previous research has produced a tool, SIFA, for dataflow analysis of basic digital circuitry, but it cannot analyse dataflow through microprocessors embedded within the circuit since this depends on the software they run. We have developed a static analysis tool that produces SIFA compatible dataflow graphs from embedded microcontroller programs written in C. In this paper we present a case study which shows how this new capability supports combined hardware and software dataflow analyses of a security critical communications device.

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Data flow analysis techniques can be used to help assess threats to data confidentiality and integrity in security critical program code. However, a fundamental weakness of static analysis techniques is that they overestimate the ways in which data may propagate at run time. Discounting large numbers of these false-positive data flow paths wastes an information security evaluator's time and effort. Here we show how to automatically eliminate some false-positive data flow paths by precisely modelling how classified data is blocked by certain expressions in embedded C code. We present a library of detailed data flow models of individual expression elements and an algorithm for introducing these components into conventional data flow graphs. The resulting models can be used to accurately trace byte-level or even bit-level data flow through expressions that are normally treated as atomic. This allows us to identify expressions that safely downgrade their classified inputs and thereby eliminate false-positive data flow paths from the security evaluation process. To validate the approach we have implemented and tested it in an existing data flow analysis toolkit.

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Objective: To determine whether remote monitoring (structured telephone support or telemonitoring) without regular clinic or home visits improves outcomes for patients with chronic heart failure. Data sources: 15 electronic databases, hand searches of previous studies, and contact with authors and experts. Data extraction: Two investigators independently screened the results. Review methods: Published randomised controlled trials comparing remote monitoring programmes with usual care in patients with chronic heart failure managed within the community. Results: 14 randomised controlled trials (4264 patients) of remote monitoring met the inclusion criteria: four evaluated telemonitoring, nine evaluated structured telephone support, and one evaluated both. Remote monitoring programmes reduced the rates of admission to hospital for chronic heart failure by 21% (95% confidence interval 11% to 31%) and all cause mortality by 20% (8% to 31%); of the six trials evaluating health related quality of life three reported significant benefits with remote monitoring, and of the four studies examining healthcare costs with structured telephone support three reported reduced cost and one no effect. Conclusion: Programmes for chronic heart failure that include remote monitoring have a positive effect on clinical outcomes in community dwelling patients with chronic heart failure.

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National Housing Relics and Scenic Sites (NHRSSs) in China are the equivalent of National Parks in the West but have contrasting features and broader roles when compared to their Western counterparts. By reviewing and analysing more than 370 academic sources, this paper identifies 6 major issue clusters and future challenges that will influence the management of NHRSSs over time. It also provides a number of cases to illustrate the particular features of NHRSSs. Identifying the hot issues and important challenges in Chinese NHRSSs will provide valuable insights into priorities now being discussed in highly populated areas of the World.

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Aims and objectives: This study will describe the oral health status of critically ill children over time spent in the paediatric intensive care unit, examine influences on the development of poor oral health and explore the relationship between dysfunctional oral health and healthcare-associated infections. Background: The treatment modalities used to support children experiencing critical illness and the progression of critical illness may result in dysfunction in the oral cavity. In adults, oral health has been shown to worsen during critical illness as well as influence systemic health. Design: A prospective observational cohort design was used. Method: The study was undertaken at a single tertiary-referral Paediatric Intensive Care Unit. Oral health status was measured using the Oral Assessment Scale and culturing oropharyngeal flora. Information was also collected surrounding the use of supportive therapies, clinical characteristics of the children and the occurrence of healthcare-associated infections. Results: Of the 46 participants, 63% (n = 32) had oral dysfunction and 41% (n = 19) demonstrated pathogenic oropharyngeal colonisation during their critical illness. The potential systemic pathogens isolated from the oropharynx and included Candida sp., Staphylococcus aureus, Haemophilus influenzae, Enterococcus sp. and Pseudomonas aeruginosa. The severity of critical illness had a significant positive relationship (p < 0·05) with pathogenic and absent colonisation of the oropharynx. Sixty-three percent of healthcare-associated infections involved the preceding or simultaneous colonisation of the oropharynx by the causative pathogen. Conclusions: This study suggests paediatric oral health to be frequently dysfunctional and the oropharynx to repeatedly harbour potential systemic pathogens during childhood critical illness. Relevance to clinical practice: Given the frequency of poor oral health during childhood critical illness in this study and the subsequent potential systemic consequences, evidence based oral hygiene practices should be developed and validated to guide clinicians when nursing critically ill children.