scholarly journals A Model for Calculating the Spatial Coverage of Audible Disaster Warnings Using GTFS Realtime Data

2021 ◽  
Vol 13 (23) ◽  
pp. 13471
Author(s):  
Akihiko Nishino ◽  
Akira Kodaka ◽  
Madoka Nakajima ◽  
Naohiko Kohtake
Keyword(s):  
Public Transport ◽  
Large Scale ◽  
General Purpose ◽  
Assessment Model ◽  
Target Area ◽  
Residential Areas ◽  
Geospatial Information ◽  
Exposed Population ◽  
Spatial Coverage ◽  
Central Station

In the event of a large-scale disaster, the dissemination of audible disaster warning information via sirens is effective in ensuring a rapid response. Sirens can be installed not only on fixed towers, but also on public transport and other vehicles passing through residential areas, and at spots where residents congregate, to increase area coverage. Although models to calculate the spatial coverage of audible information delivered from fixed sirens have been constructed, no general-purpose model has been developed to assess the delivery from vehicles. In this study, we focused on the General Transit Feed Specification (GTFS), which is an open format for geospatial information on public transport. We conducted a spatial analysis using a geographic information system (GIS) on the basis of the acquired bus location information. We developed a model to calculate the spatial coverage of the audible information delivery for overlapping hazard maps and population. Assuming a flood occurred in the vicinity of Brisbane Central Station, Queensland, Australia, we confirmed that the developed model was capable of characterizing the time-series changes in the exposed population in the target area. Since the GTFS format is currently distributed across various countries, this assessment model is considered to be highly versatile and widely applicable.

Methods of Network Planning and Management when Implementing Territory Planning Projects

2019 ◽  
pp. 49-54
Keyword(s):  
Large Scale ◽  
Housing Stock ◽  
Network Planning ◽  
Network Models ◽  
Point Of View ◽  
Residential Areas ◽  
Basic Principles ◽  
Planning And Management ◽  
Planning Project ◽  
Complex Process

The success of the Program of housing stock renovation in Moscow depends on the efficiency of resource management. One of the main urban planning documents that determine the nature of the reorganization of residential areas included in the Program of renovation is the territory planning project. The implementation of the planning project is a complex process that has a time point of its beginning and end, and also includes a set of interdependent parallel-sequential activities. From an organizational point of view, it is convenient to use network planning and management methods for project implementation. These methods are based on the construction of network models, including its varieties – a Gantt chart. A special application has been developed to simulate the implementation of planning projects. The article describes the basic principles and elements of modeling. The list of the main implementation parameters of the Program of renovation obtained with the help of the developed software for modeling is presented. The variants of using the results obtained for a comprehensive analysis of the implementation of large-scale urban projects are proposed.

Research on highly parallel embedded control system design and implementation method

Impact ◽  
2019 ◽  
Vol 2019 (10) ◽  
pp. 44-46
Author(s):  
Masato Edahiro ◽  
Masaki Gondo
Keyword(s):  
Computer Architecture ◽  
Intelligent Systems ◽  
Large Scale ◽  
General Purpose ◽  
Heterogeneous Structure ◽  
Single Chip ◽  
Powertrain Control ◽  
Processing Power ◽  
Hardware Description ◽  
Many Core

The pace of technology's advancements is ever-increasing and intelligent systems, such as those found in robots and vehicles, have become larger and more complex. These intelligent systems have a heterogeneous structure, comprising a mixture of modules such as artificial intelligence (AI) and powertrain control modules that facilitate large-scale numerical calculation and real-time periodic processing functions. Information technology expert Professor Masato Edahiro, from the Graduate School of Informatics at the Nagoya University in Japan, explains that concurrent advances in semiconductor research have led to the miniaturisation of semiconductors, allowing a greater number of processors to be mounted on a single chip, increasing potential processing power. 'In addition to general-purpose processors such as CPUs, a mixture of multiple types of accelerators such as GPGPU and FPGA has evolved, producing a more complex and heterogeneous computer architecture,' he says. Edahiro and his partners have been working on the eMBP, a model-based parallelizer (MBP) that offers a mapping system as an efficient way of automatically generating parallel code for multi- and many-core systems. This ensures that once the hardware description is written, eMBP can bridge the gap between software and hardware to ensure that not only is an efficient ecosystem achieved for hardware vendors, but the need for different software vendors to adapt code for their particular platforms is also eliminated.

scholarly journals Joint regression and learning from pairwise rankings for personalized image aesthetic assessment

2021 ◽  
Author(s):  
Jin Zhou ◽  
Qing Zhang ◽  
Jian-Hao Fan ◽  
Wei Sun ◽  
Wei-Shi Zheng
Keyword(s):  
Large Scale ◽  
Assessment Model ◽  
Generic Model ◽  
Small Subset ◽  
Deep Convolutional Neural Networks ◽  
Personal Taste ◽  
Hinge Loss ◽  
Novel Approach ◽  
Large Scale Dataset ◽  
Image Pairs

AbstractRecent image aesthetic assessment methods have achieved remarkable progress due to the emergence of deep convolutional neural networks (CNNs). However, these methods focus primarily on predicting generally perceived preference of an image, making them usually have limited practicability, since each user may have completely different preferences for the same image. To address this problem, this paper presents a novel approach for predicting personalized image aesthetics that fit an individual user’s personal taste. We achieve this in a coarse to fine manner, by joint regression and learning from pairwise rankings. Specifically, we first collect a small subset of personal images from a user and invite him/her to rank the preference of some randomly sampled image pairs. We then search for the K-nearest neighbors of the personal images within a large-scale dataset labeled with average human aesthetic scores, and use these images as well as the associated scores to train a generic aesthetic assessment model by CNN-based regression. Next, we fine-tune the generic model to accommodate the personal preference by training over the rankings with a pairwise hinge loss. Experiments demonstrate that our method can effectively learn personalized image aesthetic preferences, clearly outperforming state-of-the-art methods. Moreover, we show that the learned personalized image aesthetic benefits a wide variety of applications.

Microcomputers in Political Science

1983 ◽  
Vol 38 ◽  
pp. 1-9
Author(s):  
Herbert F. Weisberg
Keyword(s):  
Data Analysis ◽  
Political Science ◽  
Large Scale ◽  
Turnaround Time ◽  
General Purpose ◽  
Batch Mode ◽  
New Era ◽  
Large Scale Data ◽  
The Social ◽  
Frequency Counts

We are now entering a new era of computing in political science. The first era was marked by punched-card technology. Initially, the most sophisticated analyses possible were frequency counts and tables produced on a counter-sorter, a machine that specialized in chewing up data cards. By the early 1960s, batch processing on large mainframe computers became the predominant mode of data analysis, with turnaround time of up to a week. By the late 1960s, turnaround time was cut down to a matter of a few minutes and OSIRIS and then SPSS (and more recently SAS) were developed as general-purpose data analysis packages for the social sciences. Even today, use of these packages in batch mode remains one of the most efficient means of processing large-scale data analysis.

scholarly journals Prevention of Mountain Disasters and Maintenance of Residential Area through Real-Time Terrain Rendering

2021 ◽  
Vol 13 (5) ◽  
pp. 2950
Author(s):  
Su-Kyung Sung ◽  
Eun-Seok Lee ◽  
Byeong-Seok Shin
Keyword(s):  
Real Time ◽  
Graphics Processing Units ◽  
High Speed ◽  
Large Scale ◽  
Civil Engineering ◽  
Three Dimensional ◽  
Sampled Data ◽  
Residential Areas ◽  
Terrain Rendering ◽  
Mountain Disasters

Climate change increases the frequency of localized heavy rains and typhoons. As a result, mountain disasters, such as landslides and earthworks, continue to occur, causing damage to roads and residential areas downstream. Moreover, large-scale civil engineering works, including dam construction, cause rapid changes in the terrain, which harm the stability of residential areas. Disasters, such as landslides and earthenware, occur extensively, and there are limitations in the field of investigation; thus, there are many studies being conducted to model terrain geometrically and to observe changes in terrain according to external factors. However, conventional topography methods are expressed in a way that can only be interpreted by people with specialized knowledge. Therefore, there is a lack of consideration for three-dimensional visualization that helps non-experts understand. We need a way to express changes in terrain in real time and to make it intuitive for non-experts to understand. In conventional height-based terrain modeling and simulation, there is a problem in which some of the sampled data are irregularly distorted and do not show the exact terrain shape. The proposed method utilizes a hierarchical vertex cohesion map to correct inaccurately modeled terrain caused by uniform height sampling, and to compensate for geometric errors using Hausdorff distances, while not considering only the elevation difference of the terrain. The mesh reconstruction, which triangulates the three-vertex placed at each location and makes it the smallest unit of 3D model data, can be done at high speed on graphics processing units (GPUs). Our experiments confirm that it is possible to express changes in terrain accurately and quickly compared with existing methods. These functions can improve the sustainability of residential spaces by predicting the damage caused by mountainous disasters or civil engineering works around the city and make it easy for non-experts to understand.

scholarly journals Navigability assessment of large-scale redesigns in nine public transport networks: Open timetable data approach

2021 ◽  
Vol 147 ◽  
pp. 212-229
Author(s):  
Christoffer Weckström ◽  
Miloš N. Mladenović ◽  
Rainer Kujala ◽  
Jari Saramäki
Keyword(s):  
Public Transport ◽  
Large Scale ◽  
Transport Networks

scholarly journals An information theoretic approach to link prediction in multiplex networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Seyed Hossein Jafari ◽  
Amir Mahdi Abdolhosseini-Qomi ◽  
Masoud Asadpour ◽  
Maseud Rahgozar ◽  
Naser Yazdani
Keyword(s):  
Real World ◽  
Link Prediction ◽  
Large Scale ◽  
Similarity Measures ◽  
Prediction Method ◽  
General Purpose ◽  
Fast Method ◽  
Theoretic Approach ◽  
Multiplex Networks ◽  
Wide Range

AbstractThe entities of real-world networks are connected via different types of connections (i.e., layers). The task of link prediction in multiplex networks is about finding missing connections based on both intra-layer and inter-layer correlations. Our observations confirm that in a wide range of real-world multiplex networks, from social to biological and technological, a positive correlation exists between connection probability in one layer and similarity in other layers. Accordingly, a similarity-based automatic general-purpose multiplex link prediction method—SimBins—is devised that quantifies the amount of connection uncertainty based on observed inter-layer correlations in a multiplex network. Moreover, SimBins enhances the prediction quality in the target layer by incorporating the effect of link overlap across layers. Applying SimBins to various datasets from diverse domains, our findings indicate that SimBins outperforms the compared methods (both baseline and state-of-the-art methods) in most instances when predicting links. Furthermore, it is discussed that SimBins imposes minor computational overhead to the base similarity measures making it a potentially fast method, suitable for large-scale multiplex networks.

scholarly journals Greenspace and depression in Japanese Older Adults considering physical activities: JAGES study

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
M Nishigaki ◽  
C Koga ◽  
M Hanazato ◽  
K Kondo
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Large Scale ◽  
Depression Scale ◽  
Public Health Problem ◽  
Evaluation Study ◽  
Physical Activities ◽  
Residential Areas ◽  
Cross Sectional ◽  
Local Climate

Abstract Introduction Older adult's depression is a public health problem. In recent years, exposure to local greenspace is beneficial to mental health via increased physical activity in people. However, few studies approach the relationship between greenspace and depression while simultaneously considering the frequency, time, and the number of types of physical activity, and large-scale surveys targeting the older adults. Methods Cross-sectional data conducted in 2016 by the Japan Gerontological Evaluation Study was used. The analysis included older adults aged 65 and over who did not require care or assistance, and a total of 126,878 people in 881 School districts. The explanatory variable is the percentage of the greenspace of the area, and the greenspace data used is data created from satellite photographs acquired by observation satellites of the Japan Aerospace Exploration Agency. The objective variable was depression (Geriatric Depression Scale 5 points or more). The analysis method was a multi-level logistic regression analysis. Physical activity was the number of sports-related hobbies, the frequency of participation in sports meetings, and walking time in daily life. Other factors such as personal attributes, population density of residential areas, and local climate were also considered. Results Depression in the survey was 20.4%. The abundance of greenspace was still associated with depression, considering all physical activity. The odds ratio of depression in areas with more greenspace was 0.92 (95% CI 0.87 - 0.98) compared to areas with less greenspace. Conclusions It became clear that areas with many greenspace were still associated with low depression, even considering the frequency, time and number of physical activities. It is conceivable that the healing effect of seeing greenspace, the reduction of air pollution and noise, etc. are related to the lack of depression without going through physical activity. Key messages In Japan, older adults are less depressed when there are many local greenspace. It became clear that areas with many greenspace were still associated with low depression, even considering physical activities.

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