• Structural Engineering and Mechanics
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• v.78 no.3
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• pp.351-368
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• 2021

This paper, by applying a reliability-based framework, develops seismic vulnerability macrozonation maps for Tehran, the capital and one of the most earthquake-vulnerable city of Iran. Seismic performance assessment of 3-, 4- and 5-story steel moment resisting frames (SMRFs), designed according to ASCE/SEI 41-17 and Iranian Code of Practice for Seismic Resistant Design of Buildings (2800 Standard), is investigated in terms of overall maximum inter-story drift ratio (MIDR) and unit repair cost ratio which is hereafter known as "damage ratio". To this end, Tehran city is first meshed into a network of 66 points to numerically locate low- to mid-rise SMRFs. Active faults around Tehran are next modeled explicitly. Two different combination of faults, based on available seismological data, are then developed to explore the impact of choosing a proper seismic scenario. In addition, soil effect is exclusively addressed. After building analytical models, reliability methods in combination with structure-specific probabilistic models are applied to predict demand and damage ratio of structures in a cost-effective paradigm. Due to capability of proposed methodology incorporating both aleatory and epistemic uncertainties explicitly, this framework which is centered on the regional demand and damage ratio estimation via structure-specific characteristics can efficiently pave the way for decision makers to find the most vulnerable area in a regional scale. This technical basis can also be adapted to any other structures which the demand and/or damage ratio prediction models are developed.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.6
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• pp.385-392
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• 2022

Naval ship could face a variety of threats in isolated seas. In particular, fires and flooding are defined as disasters that are very likely to cause irreparable damage to ships. These disasters have a very high risk of personal injury as well. Therefore, when a disaster occurs, it must be quickly suppressed, but if there are people in the disaster area, the protection of life must be given priority. In order to quickly evacuate the ship crew in case of a disaster, we would like to propose a plan to quickly explore the evacuation route even in urgent situations. Using commercial escape simulation software, we obtain the data for deep neural network learning with simulations according to aisle characteristics and the properties and number of evacuation person. Using the obtained data, the passage prediction model is trained with a deep learning, and the passage time is predicted through the learned model. Construct a numerical map of a naval ship and construct a distance matrix of the vessel using predicted passage time data. The distance matrix configured in one of the path search algorithms, the Dijkstra algorithm, is applied to explore the evacuation path of naval ship.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.32 no.4
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• pp.94-104
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• 2014

This contribution studied knowledges, informations and main project issues for systematic conservation management utilize of Joseon Royal Tombs guaranteeing their Outstanding Universal Value, Authenticity and Integrity, and the outcomes are as follows. The first, regarding the tomb's system, it should be planned to enhance authenticity and integrity of Joseon Royal Tombs through historical facts, measurement, diagnosis and intervention according to international and national charters, statements and general standards. The second, regarding prevention against disasters, the anti-fire system including construction of GIS materials and the Risk Map following investigation the present condition, premising improvement of relevant laws and regulations, should be planned. The third, we should consider, regarding utilize, educational application by the each tomb's story and royal ancestral rite, tourism by the local area of each tomb and industrial application by science and IT technologies.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.549-557
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• 2013

An flood inundation map is able to convey spatial distribution of inundation to a decision maker for flood risk management. A roughness coefficient with unclear values and a discharge obtained from the stage-discharge rating equation are key sources of uncertainty in flood inundation mapping by using a hydraulic model. Also, the uncertainty analysis needs an observation for the flood inundation, and satellite images is useful to obtain spatial distribution of flood. Accordingly, the objective of this study is to quantify uncertainty arising roughness and discharge in flood inundation mapping by using a hydraulic model and a satellite image. To perform this, flood inundations were simulated by HEC-RAS and terrain analysis, and ISODATA (Iterative Self-Organizing Data Analysis) was used to classify waterbody from Landsat 5TM imagery. The classified waterbody was used as an observation to calculate F-statistic (likelihood measure) in GLUE (Generalized Likelihood Uncertainty Estimation). The results from GLUE show that flood inundation areas are 74.59 $km^2$ for lower 5 % uncertainty bound and 151.95 $km^2$ for upper 95% uncertainty bound, respectively. The quantification of uncertainty in flood inundation mapping will play a significant role in realizing the efficient flood risk management.

• Economic and Environmental Geology
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• v.34 no.4
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• pp.385-394
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• 2001

There are serious damage of people and properties every year due to landslides that are occurred by heavy rain. Because these phenomena repeat and the heavy rain is not an atmospheric anomaly, the counter plan becomes necessary. The study area, Ulsan, is one of the seven metropolitan, and largest cities of Korea and has many large facilities such as petrochemical complex and factories of automobile and shipbuilding. So it is necessary assess the landslide hazard potential. In the study. the three steps of landslide hazard assessment techniques such as susceptibility, possibility, and risk were performed to the study area using GIS. For the analyses, the topographic, geologic, soil, forest, meteorological, and population and facility spatial database were constructed. Landslide susceptibility representing how susceptible to a given area was assessed by overlay of the slope, aspect, curvature of topography from the topographic DB, type, material, drainage and effective thickness of soil from the soil DB, lype age, diameter and density from forest DB and land use. Then landslide possibility representing how possible to landslide was assessed by overlay of the susceptibility and rainfall frequency map, Finally, landslide risk representing how dangerous to people and facility was assessed by overlay of the possibil. ity and the population and facility density maps The assessment results can be used to urban and land use plan for landslide hazard prevention.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.2
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• pp.67-74
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• 2017

The D-InSAR is a technique for precisely measuring the subsidence of subsidence using difference of two SAR images. In order to calculate the subsidence using D-InSAR, a high coherence between master image and the slave image is essential. Since the existing D-InSAR method calculates the displacement based on the total coherence, the accuracy of the subsidence is lowered when the coherence map contains mountains or bare-land. In order to solve this problem, in this study, a point having a temporal coherence and spatial coherence of 0.7 or more was extracted to form TIN, and the subsidence was calculated based on this TIN. In addition, we compared the existing D-InSAR technique with the new D-InSAR technique considering spatial and temporal coherence. As a result, the new D-InSAR technique showed smaller standard deviation, relative variance, variation coefficient and quadrature deviation than the existing D-InSAR technique. It is also easy to grasp the trend of the subsidence.

• Journal of the Society of Disaster Information
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• v.17 no.2
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• pp.206-217
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• 2021

Purpose: Recently, a series of large social disasters have led to a lot of research to prevent social disasters as well as natural disasters and reduce damage. However, this paper aims to select the types of social disasters that local governments should focus on and create basic data for effective countermeasures and mitigation efforts. Method: Among 43 types of disasters announced by the Ministry of Public Administration and Security, 11 types of disasters were selected and collected to select the main types of disasters, and risk types were derived by region with risk maps. In order to derive the risk map, each detailed index was rescheduled to be 0-1 and weights were determined through entropy technique. Result: As a result, about 41% of the major disasters announced by the Ministry of Public Administration and Security were consistent, and the rest of the major types were disasters that could not be obtained or have not occurred in the past 20 years. Conclusion: Therefore, in order to establish an effective prevention and recovery plan for social disasters through this study, it was intended to present social disaster-focused disasters for each local government.

• The Journal of Engineering Geology
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• v.32 no.2
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• pp.221-239
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• 2022

Unknown geotechnical characteristics are key challenges in the design of piles for the plant, civil and building works. Although the N-values which were read through the standard penetration test are important, those N-values of the whole area are not likely acquired in common practice. In this study, the N-value is predicted by means of regression analysis with artificial intelligence (AI). Big data is important to improve learning performance of AI, so circular augmentation method is applied to build up the big data at the current study. The optimal model was chosen among applied AI algorithms, such as artificial neural network, decision tree and auto machine learning. To select optimal model among the above three AI algorithms is to minimize the margin of error. To evaluate the method, actual data and predicted data of six performed projects in Poland, Indonesia and Malaysia were compared. As a result of this study, the AI prediction of this method is proven to be reliable. Therefore, it is realized that the geotechnical characteristics of non-boring points were predictable and the optimal arrangement of structure could be achieved utilizing three dimensional N-value distribution map.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.10
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• pp.4587-4590
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• 2016

Background: In many countries gastric cancer has the highest incidence among the gastrointestinal cancers and is the second most common cancer in Iran. The aim of this study was to identify and map high risk gastric cancer regions at the county-level in Iran. Methods: In this study we analyzed gastric cancer data for Iran in the years 2003-2010. Area-to-area Poisson kriging and Besag, York and Mollie (BYM) spatial models were applied to smoothing the standardized incidence ratios of gastric cancer for the 373 counties surveyed in this study. The two methods were compared in term of accuracy and precision in identifying high risk regions. Result: The highest smoothed standardized incidence rate (SIR) according to area-to-area Poisson kriging was in Meshkinshahr county in Ardabil province in north-western Iran (2.4,SD=0.05), while the highest smoothed standardized incidence rate (SIR) according to the BYM model was in Ardabil, the capital of that province (2.9,SD=0.09). Conclusion: Both methods of mapping, ATA Poisson kriging and BYM, showed the gastric cancer incidence rate to be highest in north and north-west Iran. However, area-to-area Poisson kriging was more precise than the BYM model and required less smoothing. According to the results obtained, preventive measures and treatment programs should be focused on particular counties of Iran.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.11-13
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• 2013

Background: Esophagus cancer, the third most common gastrointestinal cancer overall, demonstrates high incidence in parts of Iran. The counties of Iran vary in size, shape and population size. The aim of this study was to account for spatial support with Area-to-Area (ATA) Poisson Kriging to increase precision of parameter estimates and yield correct variance and create maps of disease rates. Materials and Methods: This study involved application/ecology methodology, illustrated using esophagus cancer data recorded by the Ministry of Health and Medical Education (in the Non-infectious Diseases Management Center) of Iran. The analysis focused on the 336 counties over the years 2003-2007. ATA was used for estimating the parameters of the map with SpaceStat and ArcGIS9.3 software for analysing the data and drawing maps. Results: Northern counties of Iran have high risk estimation. The ATA Poisson Kriging approach yielded variance increase in large sparsely populated counties. So, central counties had the most prediction variance. Conclusions: The ATAPoisson kriging approach is recommended for estimating parameters of disease mapping since this method accounts for spatial support and patterns in irregular spatial areas. The results demonstrate that the counties in provinces Ardebil, Mazandaran and Kordestan have higher risk than other counties.