990 resultados para External detection


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The following technical report describes the approach and algorithm used to detect marine mammals from aerial imagery taken from manned/unmanned platform. The aim is to automate the process of counting the population of dugongs and other mammals. We have developed and algorithm that automatically presents to a user a number of possible candidates of these mammals. We tested the algorithm in two distinct datasets taken from different altitudes. Analysis and discussion is presented in regards with the complexity of the input datasets, the detection performance.

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Iconic and significant buildings are the common target of bombings by terrorists causing large numbers of casualties and extensive property damage. Recent incidents were external bomb attacks on multi-storey buildings with reinforced concrete frames. Under a blast load circumstance, crucial damage initiates at low level storeys in a building and may then lead to a progressive collapse of whole or part of the structure. It is therefore important to identify the critical initial influence regions along the height, width and depth of the building exposed to blast effects and the structure response in order to assess the vulnerability of the structure to disproportionate and progressive collapse. This paper discusses the blast response and the propagation of its effects on a two dimensional reinforced concrete (RC) frame, designed to withstand normal gravity loads. The explicit finite element code, LS DYNA is used for the analysis. A complete RC portal frame seven storeys by six bays is modelled with reinforcement details and appropriate materials to simulate strain rate effects. Explosion loads derived from standard manuals are applied as idealized triangular pressures on the column faces of the numerical models. The analysis reports the influence of blast propagation as displacements and material yielding of the structural elements in the RC frame. The effected regions are identified and classified according to the load cases. This information can be used to determine the vulnerability of multi-storey RC buildings to various external explosion scenarios and designing buildings to resist blast loads.

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Isolation of a faulted segment, from either side of a fault, in a radial feeder that has several converter interfaced DGs is a challenging task when current sensing protective devices are employed. The protective device, even if it senses a downstream fault, may not operate if fault current level is low due to the current limiting operation of converters. In this paper, a new inverse type relay is introduced based on line admittance measurement to protect a distribution network, which has several converter interfaced DGs. The basic operation of this relay, its grading and reach settings are explained. Moreover a method is proposed to compensate the fault resistance such that the relay operation under this condition is reliable. Then designed relay performances are evaluated in a radial distribution network. The results are validated through PSCAD/EMTDC simulation and MATLAB calculations.

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Improving the performance of a incident detection system was essential to minimize the effect of incidents. A new method of incident detection was brought forward in this paper based on an in-car terminal which consisted of GPS module, GSM module and control module as well as some optional parts such as airbag sensors, mobile phone positioning system (MPPS) module, etc. When a driver or vehicle discovered the freeway incident and initiated an alarm report the incident location information located by GPS, MPPS or both would be automatically send to a transport management center (TMC), then the TMC would confirm the accident with a closed-circuit television (CCTV) or other approaches. In this method, detection rate (DR), time to detect (TTD) and false alarm rate (FAR) were more important performance targets. Finally, some feasible means such as management mode, education mode and suitable accident confirming approaches had been put forward to improve these targets.

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The role of internal marketing in developing organisational competencies is identified as a key area for continued research (Rafiq and Ahmed, 2003). One competence of particular interest to marketers is market orientation. This paper examines the impact of internal marketing, operationalised as a set of internal market orientated behaviours (IMO) on market orientation (MO), and consequently organisational performance, and provides the first quantitative evidence to support the long held assumption that internal marketing has an impact on marketing success. Data from UK retail managers were analysed using structural equations modelling employing LISREL software. These data indicate significant relationships between internal market orientation, employee motivation and external marketing success (market orientation, financial performance and customer satisfaction). Our results also support previous findings indicating a positive impact of external market orientation on customer satisfaction and financial performance. For marketing practitioners, the role of internal market orientation is developing marketing strategies is discussed.

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The research on project learning has recognised the significance of knowledge transfer in project based organisations (PBOs). Effective knowledge transfer across projects avoids reinventions, enhances knowledge creation and saves lots of time that is crucial in project environment. In order to facilitate knowledge transfer, many PBOs have invested lots of financial and human resources to implement IT-based knowledge repository. However, some empirical studies found that employees would rather turn for knowledge to colleagues despite their ready access to IT-based knowledge repository. Therefore, it is apparent that social networks play a pivotal role in the knowledge transfer across projects. Some scholars attempt to explore the effect of network structure on knowledge transfer and performance, however, focused only on egocentric networks and the groups’ internal social networks. It has been found that the project’s external social network is also critical, in that the team members can not handle critical situations and accomplish the projects on time without the assistance and knowledge from external sources. To date, the influence of the structure of a project team’s internal and external social networks on project performance, and the interrelation between both networks are barely known. In order to obtain such knowledge, this paper explores the interrelation between the structure of a project team’s internal and external social networks, and their effect on the project team’s performance. Data is gathered through survey questionnaire distributed online to respondents. Collected data is analysed applying social network analysis (SNA) tools and SPSS. The theoretical contribution of this paper is the knowledge of the interrelation between the structure of a project team’s internal and external social networks and their influence on the project team’s performance. The practical contribution lies in the guideline to be proposed for constructing the structure of project team’s internal and external social networks.

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Despite changes in surgical techniques, radiotherapy targeting and the apparent earlier detection of cancers, secondary lymphoedema is still a significant problem for about 20–30% of those who receive treatment for cancer, although the incidence and prevalence does seem to be falling. The figures above generally relate to detection of an enlarged limb or other area, but it seems that about 60% of all patients also suffer other problems with how the limb feels, what can or cannot be done with it and a range of social or psychological issues. Often these ‘subjective’ changes occur before the objective ones, such as a change in arm volume or circumference. For most of those treated for cancer lymphoedema does not develop immediately, and, while about 60–70% develop it in the first few years, some do not develop lymphoedema for up to 15 or 20 years. Those who will develop clinically manifest lymphoedema in the future are, for some time, in a latent or hidden phase of lymphoedema. There also seems to be some risk factors which are indicators for a higher likelihood of lymphoedema post treatment, including oedema at the surgical site, arm dominance, age, skin conditions, and body mass index (BMI).

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Purpose: In the present work we consider our (in progress) spectroscopy study of zinc and iron phosphates under the influence external high pressure to determine zinc ion change coordination from tetrahedral to octahedral (or hexahedral) structure.----- Design/methodology/approach: The standard equipment is the optical high pressure cell with diamond (DAC). The DAC is assembled and then vibrational or electronic spectra are collected by mounting the cell in an infrared, Raman, EXAFS or UV-visible spectrometer.----- Findings: Mechanism by which zinc and iron methaphosphate material is transformed to glassy meta-phosphate is enhancing mechanical properties of tribofilm. The two decades of intensive study demonstrates that Zn (II) and Fe (III) ions participate to cross-link network under friction, hardening the phosphate.----- Research limitations/implications: Transition metal atoms with d orbital have flexible coordination numbers, for example zinc acts as a cross-linking agent increasing hardness, by changing coordination from tetrahedral to octahedral. Perhaps the external pressure effect on the [Zn–(O-P-)4 ] complex causes a transformation to an [Zn –(O-P-)6] grouping.----- Originality/value: This paper analyses high-pressure spectroscopy which has been applied for the investigation of 3D transition metal ions in solids. When studying pressure effects on coordination compounds structure, we can expect changes in ground electronic state (spin-crossovers), electronic spectra due to structural distortions (piezochromism), and changes in the ligand field causing shifts in the electronic transitions.

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Spatial information captured from optical remote sensors on board unmanned aerial vehicles (UAVs) has great potential in automatic surveillance of electrical infrastructure. For an automatic vision-based power line inspection system, detecting power lines from a cluttered background is one of the most important and challenging tasks. In this paper, a novel method is proposed, specifically for power line detection from aerial images. A pulse coupled neural filter is developed to remove background noise and generate an edge map prior to the Hough transform being employed to detect straight lines. An improved Hough transform is used by performing knowledge-based line clustering in Hough space to refine the detection results. The experiment on real image data captured from a UAV platform demonstrates that the proposed approach is effective for automatic power line detection.

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The application of object-based approaches to the problem of extracting vegetation information from images requires accurate delineation of individual tree crowns. This paper presents an automated method for individual tree crown detection and delineation by applying a simplified PCNN model in spectral feature space followed by post-processing using morphological reconstruction. The algorithm was tested on high resolution multi-spectral aerial images and the results are compared with two existing image segmentation algorithms. The results demonstrate that our algorithm outperforms the other two solutions with the average accuracy of 81.8%.

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This paper describes the development and preliminary experimental evaluation of a visionbased docking system to allow an Autonomous Underwater Vehicle (AUV) to identify and attach itself to a set of uniquely identifiable targets. These targets, docking poles, are detected using Haar rectangular features and rotation of integral images. A non-holonomic controller allows the Starbug AUV to orient itself with respect to the target whilst maintaining visual contact during the manoeuvre. Experimental results show the proposed vision system is capable of robustly identifying a pair of docking poles simultaneously in a variety of orientations and lighting conditions. Experiments in an outdoor pool show that this vision system enables the AUV to dock autonomously from a distance of up to 4m with relatively low visibility.

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Aims: Influenza is commonly spread by infectious aerosols; however, detection of viruses in aerosols is not sensitive enough to confirm the characteristics of virus aerosols. The aim of this study was to develop an assay for respiratory viruses sufficiently sensitive to be used in epidemiological studies. Method: A two-step, nested real-time PCR assay was developed for MS2 bacteriophage, and for influenza A and B, parainfluenza 1 and human respiratory syncytial virus. Outer primer pairs were designed to nest each existing real-time PCR assay. The sensitivities of the nested real-time PCR assays were compared to those of existing real-time PCR assays. Both assays were applied in an aerosol study to compare their detection limits in air samples. Conclusions: The nested real-time PCR assays were found to be several logs more sensitive than the real-time PCR assays, with lower levels of virus detected at lower Ct values. The nested real-time PCR assay successfully detected MS2 in air samples, whereas the real-time assay did not. Significance and Impact of the Study: The sensitive assays for respiratory viruses will permit further research using air samples from naturally generated virus aerosols. This will inform current knowledge regarding the risks associated with the spread of viruses through aerosol transmission.

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The aetiology of secondary lymphoedema seems to be multifactorial, with acquired abnormalities as well as pre-existing conditions being contributory factors. Many characteristics bear inconsistent relationships to lymphoedema risk, and the few that are consistently associated with an increased risk of developing the condition, do not alone distinguish the at-risk population. Further, our current prevention and management recommendations are not backed by strong evidence. Consequently, there remains much to be learned about who gets it, how can it be prevented and how can we best treat it. Nonetheless, it is clear that lymphoedema is associated with adverse side effects, which have a profound impact on daily life, and that preliminary evidence suggests that early detection may lead to more effective treatment and lack of treatment may lead to progression. These represent important reasons as to why lymphoedema deserves clinical attention. However, several pragmatic issues must be considered when discussing whether a routine objective measure of lymphoedema could be integrated among the standard clinical care of those undertaking treatment for cancers known to be associated with the development of lymphoedema.

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Surveillance networks are typically monitored by a few people, viewing several monitors displaying the camera feeds. It is then very difficult for a human operator to effectively detect events as they happen. Recently, computer vision research has begun to address ways to automatically process some of this data, to assist human operators. Object tracking, event recognition, crowd analysis and human identification at a distance are being pursued as a means to aid human operators and improve the security of areas such as transport hubs. The task of object tracking is key to the effective use of more advanced technologies. To recognize an event people and objects must be tracked. Tracking also enhances the performance of tasks such as crowd analysis or human identification. Before an object can be tracked, it must be detected. Motion segmentation techniques, widely employed in tracking systems, produce a binary image in which objects can be located. However, these techniques are prone to errors caused by shadows and lighting changes. Detection routines often fail, either due to erroneous motion caused by noise and lighting effects, or due to the detection routines being unable to split occluded regions into their component objects. Particle filters can be used as a self contained tracking system, and make it unnecessary for the task of detection to be carried out separately except for an initial (often manual) detection to initialise the filter. Particle filters use one or more extracted features to evaluate the likelihood of an object existing at a given point each frame. Such systems however do not easily allow for multiple objects to be tracked robustly, and do not explicitly maintain the identity of tracked objects. This dissertation investigates improvements to the performance of object tracking algorithms through improved motion segmentation and the use of a particle filter. A novel hybrid motion segmentation / optical flow algorithm, capable of simultaneously extracting multiple layers of foreground and optical flow in surveillance video frames is proposed. The algorithm is shown to perform well in the presence of adverse lighting conditions, and the optical flow is capable of extracting a moving object. The proposed algorithm is integrated within a tracking system and evaluated using the ETISEO (Evaluation du Traitement et de lInterpretation de Sequences vidEO - Evaluation for video understanding) database, and significant improvement in detection and tracking performance is demonstrated when compared to a baseline system. A Scalable Condensation Filter (SCF), a particle filter designed to work within an existing tracking system, is also developed. The creation and deletion of modes and maintenance of identity is handled by the underlying tracking system; and the tracking system is able to benefit from the improved performance in uncertain conditions arising from occlusion and noise provided by a particle filter. The system is evaluated using the ETISEO database. The dissertation then investigates fusion schemes for multi-spectral tracking systems. Four fusion schemes for combining a thermal and visual colour modality are evaluated using the OTCBVS (Object Tracking and Classification in and Beyond the Visible Spectrum) database. It is shown that a middle fusion scheme yields the best results and demonstrates a significant improvement in performance when compared to a system using either mode individually. Findings from the thesis contribute to improve the performance of semi-automated video processing and therefore improve security in areas under surveillance.

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This research investigates wireless intrusion detection techniques for detecting attacks on IEEE 802.11i Robust Secure Networks (RSNs). Despite using a variety of comprehensive preventative security measures, the RSNs remain vulnerable to a number of attacks. Failure of preventative measures to address all RSN vulnerabilities dictates the need for a comprehensive monitoring capability to detect all attacks on RSNs and also to proactively address potential security vulnerabilities by detecting security policy violations in the WLAN. This research proposes novel wireless intrusion detection techniques to address these monitoring requirements and also studies correlation of the generated alarms across wireless intrusion detection system (WIDS) sensors and the detection techniques themselves for greater reliability and robustness. The specific outcomes of this research are: A comprehensive review of the outstanding vulnerabilities and attacks in IEEE 802.11i RSNs. A comprehensive review of the wireless intrusion detection techniques currently available for detecting attacks on RSNs. Identification of the drawbacks and limitations of the currently available wireless intrusion detection techniques in detecting attacks on RSNs. Development of three novel wireless intrusion detection techniques for detecting RSN attacks and security policy violations in RSNs. Development of algorithms for each novel intrusion detection technique to correlate alarms across distributed sensors of a WIDS. Development of an algorithm for automatic attack scenario detection using cross detection technique correlation. Development of an algorithm to automatically assign priority to the detected attack scenario using cross detection technique correlation.