998 resultados para Line Islands


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The use of appropriate features to represent an output class or object is critical for all classification problems. In this paper, we propose a biologically inspired object descriptor to represent the spectral-texture patterns of image-objects. The proposed feature descriptor is generated from the pulse spectral frequencies (PSF) of a pulse coupled neural network (PCNN), which is invariant to rotation, translation and small scale changes. The proposed method is first evaluated in a rotation and scale invariant texture classification using USC-SIPI texture database. It is further evaluated in an application of vegetation species classification in power line corridor monitoring using airborne multi-spectral aerial imagery. The results from the two experiments demonstrate that the PSF feature is effective to represent spectral-texture patterns of objects and it shows better results than classic color histogram and texture features.

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The size of rat-race and branch-line couplers can be reduced by using periodic loading or artificial transmission lines. The objective of this work is to extend the idea of size reduction through periodic loading to coupled-line 90° hybrids. A procedure for the extraction of the characteristic parameters of a coupled-line 4-port from a single set of S-parameters is described. This method can be employed to design of coupled artificial transmission line couplers of arbitrary geometry. The procedure is illustrated through the design a broadside-coupled stripline hybrid, periodically loaded with stubs. Measured results for a prototype coupler confirm the validity of the theory.

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Retrotransposons are a class of transposable elements that represent a major fraction of the repetitive DNA of most eukaryotes. Their abundance stems from their expansive replication strategies. We screened and isolated sequence fragments of long terminal repeat (LTR), gypsy-like reverse transcriptase (rt) and gypsy-like envelope (env) domains, and two partial sequences of non-LTR retrotransposons, long interspersed element (LINE), in the clonally propagated allohexaploid sweet potato (Ipomoea batatas (L.) Lam.) genome. Using dot-blot hybridization, these elements were found to be present in the ~1597 Mb haploid sweet potato genome with copy numbers ranging from ~50 to ~4100 as observed in the partial LTR (IbLtr-1) and LINE (IbLi-1) sequences, respectively. The continuous clonal propagation of sweet potato may have contributed to such a multitude of copies of some of these genomic elements. Interestingly, the isolated gypsy-like env and gypsy-like rt sequence fragments, IbGy-1 (~2100 copies) and IbGy-2 (~540 copies), respectively, were found to be homologous to the Bagy-2 cDNA sequences of barley (Hordeum vulgare L.). Although the isolated partial sequences were found to be homologous to other transcriptionally active elements, future studies are required to determine whether they represent elements that are transcriptionally active under normal and (or) stressful conditions.

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Perhaps the most innovative of all independent OLD ventures specialising in ROW content is Jaman. Founded in 2007 by IT entrepreneur Gaurav Dhillon, and based in San Mateo, California, Jaman is a quality specialist distributor of non-Hollywood films. As of late 2010, Jaman had 1.8 million registered users and attracts viewers from most countries in the world. 75% of all use is generated from outside the U.S. Jaman does very well in English speaking parts of the world, particularly current and former Commonwealth countries. The United Kingdom accounts for 29% of users, North America (U.S. and Canada) 26%, and India represents 23%. Jaman is sometimes referred to as ‘social cinema’: a website which brings together the critique and review of a cinephile website (the forums of Rue-morgue.com for cinefantastique movie fans for example) with the social interaction, community and functionality of a social media site (for example Facebook.com). Jaman could be considered a pioneer in this space; a first mover in wrapping commercial movie downloading in an interactive social experience.

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Trees, shrubs and other vegetation are of continued importance to the environment and our daily life. They provide shade around our roads and houses, offer a habitat for birds and wildlife, and absorb air pollutants. However, vegetation touching power lines is a risk to public safety and the environment, and one of the main causes of power supply problems. Vegetation management, which includes tree trimming and vegetation control, is a significant cost component of the maintenance of electrical infrastructure. For example, Ergon Energy, the Australia’s largest geographic footprint energy distributor, currently spends over $80 million a year inspecting and managing vegetation that encroach on power line assets. Currently, most vegetation management programs for distribution systems are calendar-based ground patrol. However, calendar-based inspection by linesman is labour-intensive, time consuming and expensive. It also results in some zones being trimmed more frequently than needed and others not cut often enough. Moreover, it’s seldom practicable to measure all the plants around power line corridors by field methods. Remote sensing data captured from airborne sensors has great potential in assisting vegetation management in power line corridors. This thesis presented a comprehensive study on using spiking neural networks in a specific image analysis application: power line corridor monitoring. Theoretically, the thesis focuses on a biologically inspired spiking cortical model: pulse coupled neural network (PCNN). The original PCNN model was simplified in order to better analyze the pulse dynamics and control the performance. Some new and effective algorithms were developed based on the proposed spiking cortical model for object detection, image segmentation and invariant feature extraction. The developed algorithms were evaluated in a number of experiments using real image data collected from our flight trails. The experimental results demonstrated the effectiveness and advantages of spiking neural networks in image processing tasks. Operationally, the knowledge gained from this research project offers a good reference to our industry partner (i.e. Ergon Energy) and other energy utilities who wants to improve their vegetation management activities. The novel approaches described in this thesis showed the potential of using the cutting edge sensor technologies and intelligent computing techniques in improve power line corridor monitoring. The lessons learnt from this project are also expected to increase the confidence of energy companies to move from traditional vegetation management strategy to a more automated, accurate and cost-effective solution using aerial remote sensing techniques.

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Child Health Line is a 24-hour Australian helpline that offers information and support for parents and families on child development and parenting. The helpline guidelines suggest that nurses should not offer medical advice, however they regularly receive calls seeking such advice. This paper examines how the service guidelines are talked into being through the nurses’ management of caller’s requests for medical advice and information, and shows how nurses orient to the boundaries of their professional role and institutionally regulated authority. Three ways in which the child health nurses manage medical advice and information seeking are discussed: using membership as a nurse to establish boundaries of expertise, privileging parental authority regarding decision making about seeking treatment for their child, and respecifying a ‘medical’ problem as a child development issue. The paper contributes to research on medical authority, and nurse authority in particular, by demonstrating the impact of institutional roles and guidelines on displays of knowledge and expertise. More generally, it contributes to an understanding of the interactional enactment and consequences of service guidelines for telehealth practice, with implications for training, policy and service delivery.

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The conventional manual power line corridor inspection processes that are used by most energy utilities are labor-intensive, time consuming and expensive. Remote sensing technologies represent an attractive and cost-effective alternative approach to these monitoring activities. This paper presents a comprehensive investigation into automated remote sensing based power line corridor monitoring, focusing on recent innovations in the area of increased automation of fixed-wing platforms for aerial data collection, and automated data processing for object recognition using a feature fusion process. Airborne automation is achieved by using a novel approach that provides improved lateral control for tracking corridors and automatic real-time dynamic turning for flying between corridor segments, we call this approach PTAGS. Improved object recognition is achieved by fusing information from multi-sensor (LiDAR and imagery) data and multiple visual feature descriptors (color and texture). The results from our experiments and field survey illustrate the effectiveness of the proposed aircraft control and feature fusion approaches.

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Distribution feeder voltage reinforcement by multiple site reactive power compensation systems has recently been reported by many researchers. However, voltage control by multiple DSTATCOMs across a distribution feeder may introduce control interactions and/or voltage instability. This paper addresses these control interaction issues and proposes a control scheme that alleviates interactions among controllers. The proposed control scheme also enhances proper sharing of reactive power among DSTATCOMs. A mathematical model of a distribution system with any number of DSTATCOMs is developed to investigate the performance of the control system. This mathematical model is used to conduct eigenvalue analysis to develop the criterion for controller design. The proposed control scheme is tested in time domain on a sample radial distribution feeder installed with multiple DSTATCOMs and test results are presented.

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In recent times considerable research attention has been directed to understanding dark networks, especially criminal and terrorist networks. Dark networks are those in which member motivations are self rather than public interested, achievements come at the cost of other individuals, groups or societies and, in addition, their activities are both ‘covert and illegal’ (Raab & Milward, 2003: 415). This ‘darkness’ has implications for the way in which these networks are structured, the strategies adopted and their recruitment methods. Such entities exhibit distinctive operating characteristics including most notably the tension between creating an efficient network structure while retaining the ability to hide from public view while avoiding catastrophic collapse should one member cooperate with authorities (Bouchard 2007). While theoretical emphasis has been on criminal and terrorist networks, recent work has demonstrated that corrupt police networks exhibit some distinctive characteristics. In particular, these entities operate within the shadows of a host organisation - the Police Force and distort the functioning of the ‘Thin Blue Line’ as the interface between the law abiding citizenry and the criminal society. Drawing on data derived from the Queensland Fitzgerald Commission of Enquiry into Police Misconduct and related documents, this paper examines the motivations, structural properties and operational practices of corrupt police networks and compares and contrasts these with other dark networks with ‘bright’ public service networks. The paper confirms the structural differences between dark corrupt police networks and bright networks and suggests. However, structural embeddedness alone is found to be an insufficient theoretical explanation for member involvement in networks and that a set of elements combine to impact decision-making. Although offering important insights into network participation, the paper’s findings are especially pertinent in identifying additional points of intervention for police corruption networks.

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Background: Cabergoline is an ergotamine derivative that increases the expression of glial cell line-derived neurotrophic factor (GDNF) in vitro. We recently showed that GDNF in the ventral tegmental area (VTA) reduces the motivation to consume alcohol. We therefore set out to determine whether cabergoline administration decreases alcohol-drinking and -seeking behaviors via GDNF. Methods: Reverse transcription polymerase chain reaction (RT-PCR) and Enzyme-Linked ImmunoSorbent Assay (ELISA) were used to measure GDNF levels. Western blot analysis was used for phosphorylation experiments. Operant self-administration in rats and a two-bottle choice procedure in mice were used to assess alcohol-drinking behaviors. Instrumental performance tested during extinction was used to measure alcohol-seeking behavior. The [35S]GTPγS binding assay was used to assess the expression and function of the dopamine D2 receptor (D2R). Results: We found that treatment of the dopaminergic-like cell line SH-SY5Y with cabergoline and systemic administration of cabergoline in rats resulted in an increase in GDNF level and in the activation of the GDNF pathway. Cabergoline treatment decreased alcohol-drinking and -seeking behaviors including relapse, and its action to reduce alcohol consumption was localized to the VTA. Finally, the increase in GDNF expression and the decrease in alcohol consumption by cabergoline were abolished in GDNF heterozygous knockout mice. Conclusions: Together, these findings suggest that cabergoline-mediated upregulation of the GDNF pathway attenuates alcohol-drinking behaviors and relapse. Alcohol abuse and addiction are devastating and costly problems worldwide. This study puts forward the possibility that cabergoline might be an effective treatment for these disorders. © 2009 Society of Biological Psychiatry.