Fine-scale habitat change in a marine reserve, mapped using radio-acoustically positioned video transects

2004 ◽  
Vol 55 (3) ◽  
pp. 257 ◽  
Author(s):  
D. M. Parsons ◽  
N. T. Shears ◽  
R. C. Babcock ◽  
T. R. Haggitt
Keyword(s):  
Information System ◽  
Trophic Cascade ◽  
Large Scale ◽  
Sampling Methods ◽  
Marine Reserve ◽  
Kelp Forest ◽  
Habitat Change ◽  
Fine Scale ◽  
Video Footage ◽  
Total Disappearance

Large-scale changes in subtidal reef habitats have occurred within the Leigh Marine Reserve (New Zealand) since its establishment in 1976. To determine the extent of habitat change within Goat Island Bay, video transects positioned by a radio acoustic positioning telemetry (RAPT) system were used to map habitats within a Geographic Information System (GIS) framework. This map was compared to a map of the same area constructed 22 years earlier in 1978. Visual categorisation of habitats was consistent with the quantification of habitat-forming species within quadrats, justifying the creation of a map based on visually interpreted video footage. Furthermore, the large-scale changes in habitats were consistent with smaller-scale changes in community structure identified at permanent sites located in the study area. The most obvious changes were the total disappearance of ‘urchin barrens’ across all depths and the recovery of kelp forest in water <8 m, caused by a trophic cascade related to predator recovery. In water > 12 m, the extent of kelp forest and sponge flats was found to decrease by 25 and 33%, respectively, while turfing algal habitat had increased by 50%. This increase in turfing algal habitat had not been previously documented due to the spatial scale of traditional sampling methods.

scholarly journals Implementing an Integrated Large-Scale Clinical Information System for ISSSTE’s Hospital Network in Mexico

2021 ◽  
Vol 3 (2) ◽  
pp. 444-453
Author(s):  
Arturo Cervantes Trejo ◽  
Sophie Domenge Treuille ◽  
Isaac Castañeda Alcántara
Keyword(s):  
Health Care ◽  
Information System ◽  
Health Care Services ◽  
Large Scale ◽  
Clinical Information System ◽  
Clinical Information ◽  
Public Hospitals ◽  
Care Services ◽  
Cost Reductions

AbstractThe Institute for Security and Social Services for State Workers (ISSSTE) is a large public provider of health care services that serve around 13.2 million Mexican government workers and their families. To attain process efficiencies, cost reductions, and improvement of the quality of diagnostic and imaging services, ISSSTE was set out in 2019 to create a digital filmless medical image and report management system. A large-scale clinical information system (CIS), including radiology information system (RIS), picture archiving and communication system (PACS), and clinical data warehouse (CDW) components, was implemented at ISSSTE’s network of forty secondary- and tertiary-level public hospitals, applying global HL-7 and Digital Imaging and Communications in Medicine (DICOM) standards. In just 5 months, 40 hospitals had their endoscopy, radiology, and pathology services functionally interconnected within a national CIS and RIS/PACS on secure private local area networks (LANs) and a secure national wide area network (WAN). More than 2 million yearly studies and reports are now in digital form in a CDW, securely stored and always available. Benefits include increased productivity, reduced turnaround times, reduced need for duplicate exams, and reduced costs. Functional IT solutions allow ISSSTE hospitals to leave behind the use of radiographic film and printed medical reports with important cost reductions, as well as social and environmental impacts, leading to direct improvement in the quality of health care services rendered.

scholarly journals Accessible Routes Integrating Data from Multiple Sources

2020 ◽  
Vol 10 (1) ◽  
pp. 7
Author(s):  
Miguel R. Luaces ◽  
Jesús A. Fisteus ◽  
Luis Sánchez-Fernández ◽  
Mario Munoz-Organero ◽  
Jesús Balado ◽  
...  
Keyword(s):  
Information System ◽  
Data Model ◽  
Large Scale ◽  
Heterogeneous Data ◽  
Multiple Sources ◽  
Heterogeneous Data Sources ◽  
Different Types ◽  
Software Sensors ◽  
The City

Providing citizens with the ability to move around in an accessible way is a requirement for all cities today. However, modeling city infrastructures so that accessible routes can be computed is a challenge because it involves collecting information from multiple, large-scale and heterogeneous data sources. In this paper, we propose and validate the architecture of an information system that creates an accessibility data model for cities by ingesting data from different types of sources and provides an application that can be used by people with different abilities to compute accessible routes. The article describes the processes that allow building a network of pedestrian infrastructures from the OpenStreetMap information (i.e., sidewalks and pedestrian crossings), improving the network with information extracted obtained from mobile-sensed LiDAR data (i.e., ramps, steps, and pedestrian crossings), detecting obstacles using volunteered information collected from the hardware sensors of the mobile devices of the citizens (i.e., ramps and steps), and detecting accessibility problems with software sensors in social networks (i.e., Twitter). The information system is validated through its application in a case study in the city of Vigo (Spain).

scholarly journals Repeated surveying over 6 years reveals that fine-scale habitat variables are key to tropical mountain ant assemblage composition and functional diversity

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mulalo M. Muluvhahothe ◽  
Grant S. Joseph ◽  
Colleen L. Seymour ◽  
Thinandavha C. Munyai ◽  
Stefan H. Foord
Keyword(s):  
Climate Change ◽  
Species Composition ◽  
High Altitude ◽  
Functional Diversity ◽  
Large Scale ◽  
Climate Models ◽  
Spatial Scales ◽  
Abiotic Factors ◽  
Composition Analysis ◽  
Fine Scale

AbstractHigh-altitude-adapted ectotherms can escape competition from dominant species by tolerating low temperatures at cooler elevations, but climate change is eroding such advantages. Studies evaluating broad-scale impacts of global change for high-altitude organisms often overlook the mitigating role of biotic factors. Yet, at fine spatial-scales, vegetation-associated microclimates provide refuges from climatic extremes. Using one of the largest standardised data sets collected to date, we tested how ant species composition and functional diversity (i.e., the range and value of species traits found within assemblages) respond to large-scale abiotic factors (altitude, aspect), and fine-scale factors (vegetation, soil structure) along an elevational gradient in tropical Africa. Altitude emerged as the principal factor explaining species composition. Analysis of nestedness and turnover components of beta diversity indicated that ant assemblages are specific to each elevation, so species are not filtered out but replaced with new species as elevation increases. Similarity of assemblages over time (assessed using beta decay) did not change significantly at low and mid elevations but declined at the highest elevations. Assemblages also differed between northern and southern mountain aspects, although at highest elevations, composition was restricted to a set of species found on both aspects. Functional diversity was not explained by large scale variables like elevation, but by factors associated with elevation that operate at fine scales (i.e., temperature and habitat structure). Our findings highlight the significance of fine-scale variables in predicting organisms’ responses to changing temperature, offering management possibilities that might dilute climate change impacts, and caution when predicting assemblage responses using climate models, alone.

scholarly journals Measuring Community Green Inequity: A Fine-Scale Assessment of Beijing Urban Area

Land ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1197
Author(s):  
Yuyang Zhang ◽  
Qilin Wu ◽  
Lei Wu ◽  
Yan Li
Keyword(s):  
Urban Area ◽  
Evaluation System ◽  
Large Scale ◽  
Green Space ◽  
Community Gardens ◽  
Data Availability ◽  
Green Spaces ◽  
Fine Scale ◽  
Macro Scale ◽  
Community Residents

Green space exposure is beneficial to the physical and mental health of community residents, but the spatial distribution of green space is inequitable. Due to data availability, green equality or justice studies typically use administrative units as contextual areas to evaluate green spaces exposure, which is macro-scale and may lead to biased estimates as it ignores fine-scale green spaces (e.g. community gardens, lawns), that community residents are more frequently exposed to. In this study, we used the community as the unit of analysis, considered the green exposure of community residents in their daily social and physical activities, obtained data on three types of green spaces including fine-scale green spaces in the communities, surrounding large-scale parks and streetscape images. We propose a series of metrics for assessing community green equity, including a total of 11 metrics in three major categories of morphology, visibility and accessibility and applied them to 4,544 communities in Beijing urban area. Through spatial visualization, spatial clustering, radar plots, and correlation analysis, we comprehensively analyzed the equity of green space at the community scale, identified the cold and hot spots of homogeneity, and then analyzed the equity of green space among regions under the urbanization process. The measurement results of these metrics showed that there are large differences and complementarities between different categories of metrics, but similarities exist between metrics of the same category. The proposed methodology represents the development of a green space evaluation system that can be used by decision makers and urban green designers to create and maintain more equitable community green spaces. In addition, the large-scale, comprehensive and fine-scale green space measurement of this study can be combined with other studies such as public health and environmental pollution in the future to obtain more comprehensive conclusions and better guide the construction and regeneration of green spaces.

scholarly journals Phát triển Framework ứng dụng AI hỗ trợ tự động khai thác lỗ hổng bảo mật

2022 ◽  
Vol 1 (13) ◽  
pp. 80-92
Author(s):  
Nguyễn Mạnh Thiên ◽  
Phạm Đăng Khoa ◽  
Nguyễn Đức Vượng ◽  
Nguyễn Việt Hùng
Keyword(s):  
Information System ◽  
Reinforcement Learning ◽  
Information Security ◽  
Vulnerability Assessment ◽  
Large Scale ◽  
Learning Technology ◽  
Security Assessment ◽  
Security Vulnerability ◽  
Different Levels

Tóm tắt—Hiện nay, nhiệm vụ đánh giá an toàn thông tin cho các hệ thống thông tin có ý nghĩa quan trọng trong đảm bảo an toàn thông tin. Đánh giá/khai thác lỗ hổng bảo mật cần được thực hiện thường xuyên và ở nhiều cấp độ khác nhau đối với các hệ thống thông tin. Tuy nhiên, nhiệm vụ này đang gặp nhiều khó khăn trong triển khai diện rộng do thiếu hụt đội ngũ chuyên gia kiểm thử chất lượng ở các cấp độ khác nhau. Trong khuôn khổ bài báo này, chúng tôi trình bày nghiên cứu phát triển Framework có khả năng tự động trinh sát thông tin và tự động lựa chọn các mã để tiến hành khai thác mục tiêu dựa trên công nghệ học tăng cường (Reinforcement Learning). Bên cạnh đó Framework còn có khả năng cập nhật nhanh các phương pháp khai thác lỗ hổng bảo mật mới, hỗ trợ tốt cho các cán bộ phụ trách hệ thống thông tin nhưng không phải là chuyên gia bảo mật có thể tự động đánh giá hệ thống của mình, nhằm giảm thiểu nguy cơ từ các cuộc tấn công mạng. Abstract—Currently, security assessment is one of the most important proplem in information security. Vulnerability assessment/exploitation should be performed regularly with different levels of complexity for each information system. However, this task is facing many difficulties in large-scale deployment due to the lack of experienced testing experts. In this paper, we proposed a Framework that can automatically gather information and automatically select suitable module to exploit the target based on reinforcement learning technology. Furthermore, our framework has intergrated many scanning tools, exploited tools that help pentesters doing their work. It also can be easily updated new vulnerabilities exploit techniques.

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