945 resultados para Camden County (N.J.)--Maps.


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Drosophila serrata is a member of the montium group, which contains more than 98 species and until recently was considered a subgroup within the melanogaster group. This Drosophila species is an emerging model system for evolutionary quantitative genetics and has been used in studies of species borders, clinal variation and sexual selection. Despite the importance of D. serrata as a model for evolutionary research, our poor understanding of its genome remains a significant limitation. Here, we provide a first-generation gene-based linkage map and a physical map for this species. Consistent with previous studies of other drosophilids we observed strong conservation of genes within chromosome arms homologous with D. melanogaster but major differences in within-arm synteny. These resources will be a useful complement to ongoing genome sequencing efforts and QTL mapping studies in this species

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Background: Malaria is a major public health burden in the tropics with the potential to significantly increase in response to climate change. Analyses of data from the recent past can elucidate how short-term variations in weather factors affect malaria transmission. This study explored the impact of climate variability on the transmission of malaria in the tropical rain forest area of Mengla County, south-west China. Methods: Ecological time-series analysis was performed on data collected between 1971 and 1999. Auto-regressive integrated moving average (ARIMA) models were used to evaluate the relationship between weather factors and malaria incidence. Results: At the time scale of months, the predictors for malaria incidence included: minimum temperature, maximum temperature, and fog day frequency. The effect of minimum temperature on malaria incidence was greater in the cool months than in the hot months. The fog day frequency in October had a positive effect on malaria incidence in May of the following year. At the time scale of years, the annual fog day frequency was the only weather predictor of the annual incidence of malaria. Conclusion: Fog day frequency was for the first time found to be a predictor of malaria incidence in a rain forest area. The one-year delayed effect of fog on malaria transmission may involve providing water input and maintaining aquatic breeding sites for mosquitoes in vulnerable times when there is little rainfall in the 6-month dry seasons. These findings should be considered in the prediction of future patterns of malaria for similar tropical rain forest areas worldwide.

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The smart phones we carry with us are becoming ubiquitous with everyday life and the sensing capabilities of these devices allow us to provide context-aware services. In this paper, we discuss the development of UniNav, a context-aware mobile application that delivers personalised campus maps for universities. The application utilises university students’ details to provide information and services that are relevant and important to them. It helps students to navigate within the campus and become familiar with their university environment quickly. A study was undertaken to evaluate the acceptability and usefulness of the campus map, as well as the impact on a users’ navigation efficiency by utilising the personal and environmental contexts. The result indicates the integration of personal and environmental contexts on digital maps can improve its usefulness and navigation efficiency.

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Modern mobile computing devices are versatile, but bring the burden of constant settings adjustment according to the current conditions of the environment. While until today, this task has to be accomplished by the human user, the variety of sensors usually deployed in such a handset provides enough data for autonomous self-configuration by a learning, adaptive system. However, this data is not fully available at certain points in time, or can contain false values. Handling potentially incomplete sensor data to detect context changes without a semantic layer represents a scientific challenge which we address with our approach. A novel machine learning technique is presented - the Missing-Values-SOM - which solves this problem by predicting setting adjustments based on context information. Our method is centered around a self-organizing map, extending it to provide a means of handling missing values. We demonstrate the performance of our approach on mobile context snapshots, as well as on classical machine learning datasets.

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This paper addresses the professional development of Kuwaiti teachers in the use of concept maps to teach Family and Consumer Science. A key aim of the study was to evaluate the degree to which the use of concept maps would influence the way Kuwaiti teachers approach and teach Family and Consumer Studies (FCS) subjects and the degree to which concept maps empower students to critically identify and express their knowledge of the subject being taught. A case study methodology was adopted to follow the implementation of lessons using concept maps by four teachers of middle years. An analysis of the data revealed the positive impact that student-centred teaching tools can have on the reformation of traditional teaching environments. For all teachers, the primary strengths of using concept maps were the ability to generate student interest, to motivate student participation and to enhance student understanding of content. Although a case study design may limit the generalisation and comparative value of the study, the findings of this study remain important to the planning of future professional development programs and the use of concept maps within Kuwait’s FCS curriculum area.

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This paper looks at the accuracy of using the built-in camera of smart phones and free software as an economical way to quantify and analyse light exposure by producing luminance maps from High Dynamic Range (HDR) images. HDR images were captured with an Apple iPhone 4S to capture a wide variation of luminance within an indoor and outdoor scene. The HDR images were then processed using Photosphere software (Ward, 2010.) to produce luminance maps, where individual pixel values were compared with calibrated luminance meter readings. This comparison has shown an average luminance error of ~8% between the HDR image pixel values and luminance meter readings, when the range of luminances in the image is limited to approximately 1,500cd/m2.

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The project investigated the relationships between diversification in modes ofdelivery, use of information and communication technologies, academics’ teaching practices, and the context in which those practices are employed, in two of the three large universities in Brisbane—Griffith University and the Queensland University of Technology (QUT). The project’s initial plan involved the investigation of two sites: Queensland University of Technology’s Faculty of Education (Kelvin Grove campus) and Griffith University’s Faculty of Humanities(Nathan campus). Interviews associated with the Faculty of Education led to a decision to include a third site—the School of Law within Queensland University of Technology’s Faculty of Law, which is based on the Gardens Point Campus. Here the investigation focused on the use of computer-based flexible learning practices, as distinct from the more text-based practices identified within the original two sites.

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Urban maps discusses new ways and tools to read and navigate the contemporary city. Each chapter investigates a possible approach to unravel the complexity of contemporary urban forms. Each tool is first defined, introducing its philosophical background, and is then discussed with case studies, showing its relevance for the navigation of the built environment. Urbanism classics such as the work of Lynch, Jacobs, Venuti and Scott-Brown, Lefebrve and Walter Benjamin are fundamental in setting the framework of the volume. In the introduction cities and mapping are first discussed, the former are illustrated as ‘a composite of invisible networks devoid of landmarks and overrun by nodes’ (p. 3), and ‘a series of unbounded spaces where mass production and mass consumption reproduce a standardised quasi-global culture’ (p. 6).

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This study presents a segmentation pipeline that fuses colour and depth information to automatically separate objects of interest in video sequences captured from a quadcopter. Many approaches assume that cameras are static with known position, a condition which cannot be preserved in most outdoor robotic applications. In this study, the authors compute depth information and camera positions from a monocular video sequence using structure from motion and use this information as an additional cue to colour for accurate segmentation. The authors model the problem similarly to standard segmentation routines as a Markov random field and perform the segmentation using graph cuts optimisation. Manual intervention is minimised and is only required to determine pixel seeds in the first frame which are then automatically reprojected into the remaining frames of the sequence. The authors also describe an automated method to adjust the relative weights for colour and depth according to their discriminative properties in each frame. Experimental results are presented for two video sequences captured using a quadcopter. The quality of the segmentation is compared to a ground truth and other state-of-the-art methods with consistently accurate results.

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This paper is devoted to the analysis of career paths and employability. The state-of-the-art on this topic is rather poor in methodologies. Some authors propose distances well adapted to the data, but are limiting their analysis to hierarchical clustering. Other authors apply sophisticated methods, but only after paying the price of transforming the categorical data into continuous, via a factorial analysis. The latter approach has an important drawback since it makes a linear assumption on the data. We propose a new methodology, inspired from biology and adapted to career paths, combining optimal matching and self-organizing maps. A complete study on real-life data will illustrate our proposal.

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This paper presents a mapping and navigation system for a mobile robot, which uses vision as its sole sensor modality. The system enables the robot to navigate autonomously, plan paths and avoid obstacles using a vision based topometric map of its environment. The map consists of a globally-consistent pose-graph with a local 3D point cloud attached to each of its nodes. These point clouds are used for direction independent loop closure and to dynamically generate 2D metric maps for locally optimal path planning. Using this locally semi-continuous metric space, the robot performs shortest path planning instead of following the nodes of the graph --- as is done with most other vision-only navigation approaches. The system exploits the local accuracy of visual odometry in creating local metric maps, and uses pose graph SLAM, visual appearance-based place recognition and point clouds registration to create the topometric map. The ability of the framework to sustain vision-only navigation is validated experimentally, and the system is provided as open-source software.

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To understand the survival status of cancer patients and influencing factors, an analysis was undertaken using data of 6450 cancer patients living in Linqu County, Shandong, diagnosed between 1993 and 1999. Survival rates were calculated using life table method with SAS 9.0 software. Overall 1-5 year survival rates for all patients were 53.16%, 28.65%, 21.57%, 18.36% and 17.87%, respectively. Cancers with a 5-year survival rate over 25% included ovarium, breast, uterus, stomach and colorectal cancers. Cancers with a 5-year survival lower than 10% were cancers on liver, cervical, lung and bones.Survival rates differed significantly across gender, age of onset, economic status, year of diagnosis and evidence of diagnosis. Patients' economic status, age of diagnosis and year of diagnosis seem to have strong effects on survival. [目的] 了解临朐县恶性肿瘤患者生存现状,探讨影响生存率的因素. [方法] 对临朐县1993~1999年发病的6450例肿瘤患者的生存资料进行分析,利用SAS9.0软件寿命表法计算生存率. [结果] 临朐县1993~1999年的恶性肿瘤患者1~5年生存率分别为53.16%、28.65%、21.57%、18.36%和17.87%,5年生存率超过25%的恶性肿瘤有卵巢癌、乳腺癌、宫体癌、胃癌、结直肠癌,5年生存率低于10%的有肝癌、宫颈癌、肺癌、骨恶性肿瘤.不同性别、发病年龄、经济状况、诊断时间和诊断依据的恶性肿瘤生存率有显著性差异. [结论] 患者经济条件、诊断年龄和诊断时间影响恶性肿瘤生存率.

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Purpose To investigate the trend of malignancies incidence and mortality in Linqu county, and to provide scientific evidence for the government to design and adjust polices on cancer prevention and control. [Methods] The cancer registration data of new cases from 1995 to 2004 and death cases from 1998 to 2004 were used to analyse the incidence and mortality and the trend in Linqu county. Results Cancer general incidence significantly increased from 1995 to 2004 (P<0.05). The increasing speed incidence in male was faster than that in female. The incidence of lung cancer, colon/rectum cancer and pancreas cancer increased significantly (P<0.05), especially of lung cancer with an acceleration incidence rate of 2.12/100,000 peryear in average. The general mortality increased gradually from 1998 to 2004 with no significance (P>0.05). Both incidence and mortality in population aged 80 or over increased significantly (P<0.05). Conclusion The cancer incidence is rising during recent 10 years , and the prevention and control for lung cancer are getting increasingly important. [目的] 了解临朐县恶性肿瘤发病与死亡趋势,为政府制订和调整防治对策提供科学依据. [方法] 利用临朐县1995~2004年恶性肿瘤发病登记资料和1998~2004年的死亡登记资料,计算各种癌症发病率和死亡率,并做趋势分析. [结果] 1995~2004年临朐县恶性肿瘤总发病率呈明显上升趋势(P<0.05),男性发病率上升速度高于女性.肺癌、肠癌、胰腺癌发病率上升显著(P<0.05),以肺癌最为迅速(年均升高2.12/10万).1998~2004年恶性肿瘤总死亡率略有上升,但无显著性(P>0.05);80岁及以上人群恶性肿瘤发病率与死亡率均呈上升趋势. [结论] 临朐县恶性肿瘤发病率近10年来呈现上升趋势,肺癌防治地位日益突出.

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Objectives To describe the intervention protocol for the first multilevel ecological intervention for physical activity in retirement communities that addresses individual, interpersonal and community influences on behavior change. Design A cluster randomized controlled trial design was employed with two study arms: a physical activity intervention and an attention control successful aging condition. Setting Sixteen continuing care retirement communities in San Diego County. Participants Three hundred twenty older adults, aged 65 years and older, are being recruited to participate in the trial. In addition, peer leaders are being recruited to lead some study activities, especially to sustain the intervention after study activities ceased. Intervention Participants in the physical activity trial receive individual, interpersonal and community intervention components. The individual level components include pedometers, goal setting and individual phone counseling. The interpersonal level components include group education sessions and peer-led activities. The community level components include resource audits and enumeration, tailored walking maps, and community improvement projects. The successful aging group receives individual and group attention about successful aging topics. Measurements The main outcome is light to moderate physical activity, measured objectively by accelerometry. Other objective outcomes included physical functioning, blood pressure, physical fitness, and cognitive functioning. Self report measures include depressive symptoms and health related quality of life. Results The intervention is being delivered successfully in the communities and compliance rates are high. Conclusion Ecological Models call for interventions that address multiple levels of the model. Previous studies have not included components at each level and retirement communities provide a model environment to demonstrate how to implement such an intervention.

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Operating in vegetated environments is a major challenge for autonomous robots. Obstacle detection based only on geometric features causes the robot to consider foliage, for example, small grass tussocks that could be easily driven through, as obstacles. Classifying vegetation does not solve this problem since there might be an obstacle hidden behind the vegetation. In addition, dense vegetation typically needs to be considered as an obstacle. This paper addresses this problem by augmenting probabilistic traversability map constructed from laser data with ultra-wideband radar measurements. An adaptive detection threshold and a probabilistic sensor model are developed to convert the radar data to occupancy probabilities. The resulting map captures the fine resolution of the laser map but clears areas from the traversability map that are induced by obstacle-free foliage. Experimental results validate that this method is able to improve the accuracy of traversability maps in vegetated environments.