scholarly journals Questionable Reform: The Adoption of the Double-Entry Bookkeeping and Accrual Basis Accounting System in Korea

2018 ◽  
Vol 33 (1) ◽  
pp. 57-80
Author(s):  
Im Tobin ◽  
Lee Hyunkuk ◽  
Lim Dongwan
Keyword(s):  
Physical Properties ◽  
Natural Disasters ◽  
State Level ◽  
Disaster Mitigation ◽  
Mitigation Measures ◽  
School Buildings ◽  
Accounting System ◽  
Seismic Evaluation ◽  
Political Factors ◽  
Double Entry

This study examines the factors that influence human vulnerability to natural disasters by focusing on the seismic evaluation of school buildings in Korea. Since natural disasters such as an earthquake often do not take people’s lives directly, but rather indirectly through the destruction of physical structures, seismic reinforcement of school buildings may reduce the vulnerability of their occupants by strengthening structures to withstand such disasters. Disaster mitigation measures are implemented within a state; however, little is known about how they are distributed when the physical properties of structures are taken into account. This paper analyzes a panel data based on the structural properties of school buildings in eight different provinces between 2011 and 2015 using a logistic regression model. The results show that factors identified in cross-country studies, such as economic capacity and political factors, still have influence on earthquake preparedness at the state level, even when the physical properties of structures or technical factors are considered.

scholarly journals The Distribution of Safety within a State: Seismic Evaluation of School Buildings

2018 ◽  
Vol 33 (1) ◽  
pp. 1-32
Author(s):  
Cho Hee-chan
Keyword(s):  
Physical Properties ◽  
Natural Disasters ◽  
State Level ◽  
Disaster Mitigation ◽  
Mitigation Measures ◽  
School Buildings ◽  
Seismic Evaluation ◽  
Political Factors ◽  
Technical Factors ◽  
Economic Capacity

This study examines the factors that influence human vulnerability to natural disasters by focusing on the seismic evaluation of school buildings in Korea. Since natural disasters such as an earthquake often do not take people’s lives directly, but rather indirectly through the destruction of physical structures, seismic reinforcement of school buildings may reduce the vulnerability of their occupants by strengthening structures to withstand such disasters. Disaster mitigation measures are implemented within a state; however, little is known about how they are distributed when the physical properties of structures are taken into account. This paper analyzes a panel data based on the structural properties of school buildings in eight different provinces between 2011 and 2015 using a logistic regression model. The results show that factors identified in cross-country studies, such as economic capacity and political factors, still have influence on earthquake preparedness at the state level, even when the physical properties of structures or technical factors are considered.

Special Issue on Disaster and Big Data

2016 ◽  
Vol 11 (2) ◽  
pp. 163-163 ◽  
Author(s):  
Shunichi Koshimura ◽  
Keyword(s):  
Big Data ◽  
Natural Disasters ◽  
Social Systems ◽  
Disaster Mitigation ◽  
Mitigation Measures ◽  
Special Issue ◽  
Editorial Committee ◽  
New Findings ◽  
Large Populations ◽  
Working Together

In the years that have passed since the 2011 Great East Japan earthquake, many new findings, insights and suggestions have been made in disaster observation, sensing, simulation, and damage determination on the damage scene. Based on the lessons, challenges for disaster mitigation against future catastrophic natural disasters such as the anticipated Tokyo metropolitan and Nankai Trough earthquakes are made on how we will share visions of potential impact and how we will maximize society's disaster resilience. Much of the ``disaster big data" obtained is related to the dynamic flow of large populations, vehicles and goods inside and outside affected areas. This has dramatically facilitated our understanding of how society has responded to unprecedented catastrophes. The key question is how we will use big data in establishing social systems that respond promptly, sensibly and effectively to natural disasters how this understanding will affect adversity and resilience. Researchers from a wide variety of fields are now working together under the collaborative JST CREST project entitled ``Establishing the most advanced disaster reduction management system by fusion of real-time disaster simulation and big data assimilation." One objective of this project is to identify potential disaster scenarios related to earthquake and tsunami progress in a chained or compound manner and to create new techniques for responsive disaster mitigation measures enabling society to recover. This special issue on disaster and big data consists of 11 papers detailing the recent progress of this project. As an editor of this issue, I would like to express our deep gratitude for the insightful comments and suggestions made by the reviewers and the members of the editorial committee.

Special Issue on Disaster and Big Data Part 2

2017 ◽  
Vol 12 (2) ◽  
pp. 225-225
Author(s):  
Shunichi Koshimura ◽  
Keyword(s):  
Big Data ◽  
Natural Disasters ◽  
New Technologies ◽  
Social Systems ◽  
Disaster Mitigation ◽  
Mitigation Measures ◽  
Special Issue ◽  
Editorial Committee ◽  
New Findings ◽  
Working Together

6 years have passed since the 2011 Great East Japan earthquake. Many new findings, insights and suggestions have been made and were implemented in disaster observation, sensing, simulation, and damage determination. The challenges for disaster mitigation against future catastrophic natural disasters, such as the Tokyo metropolitan earthquake and Nankai Trough earthquake, are how we share the visions of the possible impacts and prepare for mitigating the losses and damages, and how we enhance society’s disaster resilience. A huge amount of information called “disaster big data” obtained, which are related to the dynamic flow of a large number of people, vehicles and goods inside and outside the affected areas. This has dramatically facilitated our understanding of how our society has responded to the unprecedented catastrophes. The key question is how we use big data in establishing the social systems that respond promptly, sensibly and effectively to natural disasters, and in withstanding the adversities with resilience. Researchers with various expertise are working together under the collaborative project called JST CREST “Establishing the most advanced disaster reduction management system by fusion of real-time disaster simulation and big data assimilation.” The project aims to identify possible disaster scenarios caused by earthquake and tsunami that occur and progress in a chained or compound manner and to create new technologies to lead responses and disaster mitigation measures that encourages the society to get over the disaster. This special issue titled “Disaster and Big Data Part 2,” including 13 papers, aims to share the recent progress of the project as the sequel of Part 1 published in March 2016. As an editor of this issue, I would like to express our deep gratitude for the insightful comments and suggestions made by the reviewers and the members of the editorial committee.

Special Issue on Disaster and Big Data Part 3

2018 ◽  
Vol 13 (2) ◽  
pp. 233-233
Author(s):  
Shunichi Koshimura
Keyword(s):  
Big Data ◽  
Natural Disasters ◽  
New Technologies ◽  
Social Systems ◽  
Disaster Mitigation ◽  
Mitigation Measures ◽  
Editorial Committee ◽  
Tsunami Disaster ◽  
New Findings ◽  
Working Together

The 2011 Great East Japan Earthquake and Tsunami Disaster left behind many lessons to learn, and there have since been many new findings and insights that have led to suggestions made and implemented in disaster observation, sensing, simulation, and damage determination. The challenges for mitigating the damage from future catastrophic natural disasters, such as the Tokyo Metropolitan Earthquake or the Nankai Trough Earthquake and Tsunami, are in how we share our visions of the possible impacts, how we prepare to mitigate the losses and damages, and how we enhance society’s disaster resilience. The huge amount of information obtained, called “disaster big data,” is related to the dynamic movement, as IoT, of a large number people, vehicles, and goods from inside and outside the affected areas. This has dramatically facilitated our understanding of how our society has responded to unprecedented catastrophes. The key question is how to utilize big data in establishing social systems that respond promptly, sensibly, and effectively to natural disasters, and in withstanding adversity with resilience. Researchers with various types of expertise are working together under a collaborative project called JST CREST “Establishing the advanced disaster reduction management system by fusion of real-time disaster simulation and big data assimilation.” The project aims to identify possible earthquake and tsunami disaster scenarios that occur and progress in a chained or compound manner and to create new technologies to lead responses and disaster mitigation measures to help society to recover from disasters. As we have published two previous special issues entitled “Disaster and Big Data” since 2016, this issue is our third. Included are 14 papers that aim to share the recent progress of the project as the sequel to Part 2, published in March 2017. As one of the guest editors of this issue, I would like to express our deep gratitude for the insightful comments and suggestions made by the reviewers and the members of the editorial committee. I do hope that this work will be utilized in disaster management efforts to mitigate the damage and losses in future catastrophic disasters.

SETTING UP AN INDUSTRIAL ACCOUNTING SYSTEM AT SAINT-GOBAIN (1820–1880)

1990 ◽  
Vol 17 (2) ◽  
pp. 73-93 ◽  
Author(s):  
Marc Nikitin
Keyword(s):  
Board Of Directors ◽  
Industrial Revolution ◽  
Cost Accounting ◽  
Accounting System ◽  
Full Cost ◽  
The Board Of Directors ◽  
Double Entry

In 1820, the Manufacture Royale des Glaces, founded in 1665 and also named Compagnie de Saint-Gobain, opted for double entry bookkeeping and cost accounting. At that time, both economic (industrial revolution) and juridical (abolition of the privileges and emergence of competition) events explain that change of accounting methods. From 1820 to 1880, the accounting system was progressively improved; most of today's cost accounting problems were discussed by the Board of Directors and in 1880 the accounting system was already very similar to today's full cost method.

Engagement Through the Diaspora Channel

2017 ◽  
Author(s):  
Michael S. Danielson
Keyword(s):  
Civil Society ◽  
Statistical Models ◽  
State Level ◽  
The State ◽  
Multivariate Statistical ◽  
Political Factors ◽  
Data Set ◽  
Level Data ◽  
Municipal Level

The first empirical task is to identify the characteristics of municipalities which US-based migrants have come together to support financially. Using a nationwide, municipal-level data set compiled by the author, the chapter estimates several multivariate statistical models to compare municipalities that did not benefit from the 3x1 Program for Migrants with those that did, and seeks to explain variation in the number and value of 3x1 projects. The analysis shows that migrants are more likely to contribute where migrant civil society has become more deeply institutionalized at the state level and in places with longer histories as migrant-sending places. Furthermore, the results suggest that political factors are at play, as projects have disproportionately benefited states and municipalities where the PAN had a stronger presence, with fewer occurring elsewhere.

scholarly journals Modeling Epidemic Spread among a Commuting Population Using Transport Schemes

Mathematics ◽  
2021 ◽  
Vol 9 (16) ◽  
pp. 1861
Author(s):  
Daniela Calvetti ◽  
Alexander P. Hoover ◽  
Johnie Rose ◽  
Erkki Somersalo
Keyword(s):  
Network Model ◽  
Transport Theory ◽  
Optimal Transport ◽  
State Level ◽  
Compartment Model ◽  
Census Bureau ◽  
Mitigation Strategies ◽  
Mitigation Measures ◽  
Metapopulation Model ◽  
Infection Dynamics

Understanding the dynamics of the spread of COVID-19 between connected communities is fundamental in planning appropriate mitigation measures. To that end, we propose and analyze a novel metapopulation network model, particularly suitable for modeling commuter traffic patterns, that takes into account the connectivity between a heterogeneous set of communities, each with its own infection dynamics. In the novel metapopulation model that we propose here, transport schemes developed in optimal transport theory provide an efficient and easily implementable way of describing the temporary population redistribution due to traffic, such as the daily commuter traffic between work and residence. Locally, infection dynamics in individual communities are described in terms of a susceptible-exposed-infected-recovered (SEIR) compartment model, modified to account for the specific features of COVID-19, most notably its spread by asymptomatic and presymptomatic infected individuals. The mathematical foundation of our metapopulation network model is akin to a transport scheme between two population distributions, namely the residential distribution and the workplace distribution, whose interface can be inferred from commuter mobility data made available by the US Census Bureau. We use the proposed metapopulation model to test the dynamics of the spread of COVID-19 on two networks, a smaller one comprising 7 counties in the Greater Cleveland area in Ohio, and a larger one consisting of 74 counties in the Pittsburgh–Cleveland–Detroit corridor following the Lake Erie’s American coastline. The model simulations indicate that densely populated regions effectively act as amplifiers of the infection for the surrounding, less densely populated areas, in agreement with the pattern of infections observed in the course of the COVID-19 pandemic. Computed examples show that the model can be used also to test different mitigation strategies, including one based on state-level travel restrictions, another on county level triggered social distancing, as well as a combination of the two.

scholarly journals Analysis of Stress Drop Variations in Fault and Subduction Zones of Maluku and Halmahera Earthquakes in 2019

2019 ◽  
Vol 9 (2) ◽  
pp. 152
Author(s):  
Rahmat Setyo Yuliatmoko ◽  
Telly Kurniawan
Keyword(s):  
Subduction Zone ◽  
Stress Drop ◽  
Subduction Zones ◽  
Slip Rate ◽  
Disaster Mitigation ◽  
Mitigation Measures ◽  
Reverse Fault ◽  
Nonlinear Inversion ◽  
Rock Structure ◽  
Geological Conditions

The amount of stress released by an earthquake can be calculated with a stress drop, the stress ratio before and after an earthquake where the stress accumulated in a fault or a subduction zone is immediately released during an earthquake. The purpose of this research is to calculate the amount of stress drop in faults and subduction in Maluku and Halmahera and their variations and relate them to the geological conditions in the area so that the tectonic characteristics in the area can be identified. This research employed mathematical analysis and the Nelder Mead Simplex nonlinear inversion methods. The results show that Maluku and Halmahera are the area with complex tectonic conditions and large earthquake impacts. The Maluku sea earthquake generated a stress drop of 0.81 MPa with a reverse fault mechanism in the zone of subduction, while for the Halmahera earthquake the stress drop value was 52.72 MPa, a typical strike-slip mechanism in the fault zone. It can be concluded that there is a difference in the stress drop between the subduction and fault zones; the stress drop in the fault was greater than that in the subduction zone due to different rock structure and faulting mechanisms as well as differences in the move slip rate that plays a role in the process of holding out the stress on a rock. This information is very important to know the amount of pressure released from the earthquake which has a very large impact as part of disaster mitigation measures.

scholarly journals INSTITUTIONAL CAPACITY BUILDING OF DISASTER-RESILIENT VILLAGE IN GARUT REGENCY

2020 ◽  
Vol 22 (3) ◽  
Author(s):  
Rd. Ahmad Buchari ◽  
Ivan Darmawan ◽  
Kurnia Muhamad Ramdhan
Keyword(s):  
Disaster Management ◽  
Research Method ◽  
Qualitative Method ◽  
Research Result ◽  
Disaster Mitigation ◽  
Mitigation Measures ◽  
Research Objects ◽  
Institutional Capacity Building ◽  
The Relationship ◽  
Institutional Relationships

Disaster may occur anytime and anywhere, and is generally unpredictable. Therefore, the most important to do is disaster management to minimize any harmful impacts of disaster. To be more effective and efficient, it needs to involve all related parties. In regions, the relationship between village institutions is of high importance in disaster mitigation. This is because it is village administration (government) that is in direct relationship with community, and that the latter is one directly impacted by disasters in regions. Thus, in the context of disaster mitigation, the relationship between village institutions should be strengthened. Accordingly, the problem studied in the present research was, how is the strengthening of institutional relationships of villages in Garut Regency?. The research method used was a qualitative method. The data collection techniques used were interview and observation. Interview was conducted with village officials and Destana volunteers. And observation was performed in the field on the activities conducted relating to disaster mitigation measures in the four villages which were the research objects, namely, Pasawahan, Rancabango, Mekarjaya, and Karyamekar.The research result revealed that the institutions in the four villages have been good enough but still need to be strengthened in the context of disaster management. The four villages were vulnerable to disasters and have had Destana instrument as a guard of disaster management at village level. In view of the research result, it is suggested that village officials improve their disaster management by, among others, conducting socialization on disaster risks, ways of lessening disaster occurrences, and ways of minimizing losses in case a disaster really occurs. 

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