• Smart Structures and Systems
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• 제33권1호
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• pp.17-26
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• 2024

The new metro crossing the existing metro will cause the settlement or floating of the existing structures, which will have safety problems for the operation of the existing metro and the construction of the new metro. Therefore, it is necessary to monitor and predict the settlement of the existing metro caused by the construction of the new metro in real time. Considering the complexity and uncertainty of metro settlement, a Gaussian Prior Bayesian Emulator (GPBE) probability prediction model based on Bayesian optimization (BO) is proposed, that is, BO-GPBE. Firstly, the settlement monitoring data are analyzed to get the influence of the new metro on the settlement of the existing metro. Then, five different acquisition functions, that is, expected improvement (EI), expected improvement per second (EIPS), expected improvement per second plus (EIPSP), lower confidence bound (LCB), probability of improvement (PI) are selected to construct BO model, and then BO-GPBE model is established. Finally, three years settlement monitoring data were collected by structural health monitoring (SHM) system installed on Nanjing Metro Line 10 are employed to demonstrate the effectiveness of BO-GPBE for forecasting the settlement.

• Journal of Information Technology Services
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• 제21권1호
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• pp.145-161
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• 2022

The data is a key catalyst for the development of the fourth industry, and has been viewed as an essential element of the new industry, with technology convergence such as artificial intelligence, augmented/virtual reality, self-driving and 5 G. This will determine the price and value of the data as the user uses data in which the data is based on the context of the situation, rather than the data itself of the past supplier-centric data. This study began with, what factors will increase the value of data from a user perspective not a supplier perspective The study was limited to public data and users conducted research on users using data, such as analysis or development based on data. The study was designed to gauge the value of data that was not studied in the user's perspective, and was instrumental in raising the value of data in the jurisdiction of supplying and managing data.

• The Korean Society of Law and Medicine
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• 제22권4호
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• pp.117-157
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• 2021

This research reviewed the HIPAA/HITECH, 21st Century Cures Act, Common Law, and private Guidances from the perspectives in protecting and utilitizing the medical data, while implications were followed. First, the standards for protection and utilization are relatively clearly regulated through single law on personal medical information in the United States. The HIPAA has been introduced in 1996 as fundamental act on protection of medical data. Medical data was divided into personally identifiable information, non-identifying information, and limited dataset under HIPAA. Regulations on de-identification measures for medical information, objects for deletion of limited data sets, and agreement on prohibition of data re-identification were stipulated. Moreover, in the 21st Century Cures Act regulated mutual compatibility for data sharing, prohibition of data blocking, and strengthening of accessibility of data subjects. Common Law introduced comprehensive consent system and clearly stipulates procedures. Second, the regulatory system is relatively simplified and clearly stipulated in the United States. To be specific, the expert consensus and the safe harbor system were introduced as an anonymity measure for identifiable medical information, which clearly defines the process while increasing trust. Third, the protection of the rights of the data subject is specified, the duty of explanation is specified in detail, while the information right of the consumer (opt-out procedure) for identification information is specified. For instance, the HHS rule and FDA regulations recognize the comprehensive consent system for human research, but the consent procedure, method, and requirements are stipulated through the common rule. Fourth, in the case of the United States, a trust-based system is being used throughout the health and medical data legislation. To be specific, Limited Data Sets are allowed to use in condition to the researcher's agreement to prohibit re-identification, and de-identification or consent process is simplified under the system.

• Journal of Electrical Engineering and Technology
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• 제12권1호
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• pp.19-28
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• 2017

False data injection attacks have recently been introduced as one of important issues related to cyber-attacks on electric power grids. These attacks aim to compromise the readings of multiple power meters in order to mislead the operation and control centers. Recent studies have shown that if a malicious attacker has complete knowledge of the power grid topology and branch admittances, s/he can adjust the false data injection attack such that the attack remains undetected and successfully passes the bad data detection tests that are used in power system state estimation. In this paper, we investigate that a practical false data injection attack is essentially a cyber-attack with uncertain information due to the attackers lack of knowledge with respect to the power grid parameters because the attacker has limited physical access to electric facilities and limited resources to compromise meters. We mathematically formulated a method of identifying the most vulnerable locations to false data injection attack. Furthermore, we suggest minimum topology changes or phasor measurement units (PMUs) installation in the given power grids for mitigating such attacks and indicate a new security metrics that can compare different power grid topologies. The proposed metrics for performance is verified in standard IEEE 30-bus system. We show that the robustness of grids can be improved dramatically with minimum topology changes and low cost.

• The Korean Journal of Community Living Science
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• 제15권3호
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• pp.149-165
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• 2004

In Korea, as the elderly population is growing, the quality of life of the rural elderly is becoming a major concern. By the way, social welfare services is less available and accessible to the rural elderly. And we have very limited information about community -oriented welfare services for the elderly. The lack of social welfare services in rural area resulted from mainly geographic isolation and economic deprivation. So, the present research aimed at; 1) to explore what the social welfare service is benefited from governmental or local assembly. 2) to explore what kind of community services is provided for the rural village and elderly. 3) to appear the political propose for the rural elderly. In South Korea, The Rural Development Administration currently operate 'villages which is supported special programs for the improvement of QOL of rural elderly' in 110 villages. It is a model governmental welfare service for rural area. For the purpose, the survey data is gathered from community level data per village (107 villages), individual survey data(881people) who live in the village and qualitative data. Two kinds of quantitative data is combined to form a data. The statistical methods used for data analysis are descriptive statistics, t-test and ANOVA. The major findings of this study were as follows : It was founded that the majority family type of the rural elderly is elderly-only households(75%). In case of poor elderly, they have very limited social insurance benefit and they can not get medical services with satisfaction. The result show that the welfare facilities per village and welfare service for the elderly is extremely low while the needs of welfare service is greate high. A distinctive characteristics in rural villages is that they receive a lot of services from private sectors, like as Women Farmers Union, Adult Union. They operate voluntary welfare services related to food supporting, education for the elderly, free haircut services and so on. In conclusion, the community care services from private sector has specialty in rural area. We conclude it is a distinguishing characteristic of rural community.

• Journal of the Korean earth science society
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• 제34권6호
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• pp.524-535
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• 2013

Catastrophe risk models require the damage functions of each vulnerable item in inventory to estimate volcanic ash losses. The damage functions are used to represent the relation between damage factors and damage and also widely used in engineering and natural hazard studies to calculate the vulnerability. In most cases, damage functions are constructed as fragility or vulnerability curves, and researchers are confused by the similarities between them particularly when they perform interdisciplinary research. Thus, we aim to explain the similarities and differences between fragility and vulnerability curves and their relationship by providing case studies to construct them. In addition, we suggest a simple method to construct the damage functions between damage ratio and volcanic ash thickness using limited damage data. This study comes from the fact that damage functions are generally constructed using damage data. However, there is no available volcanic ash damage data in Korea, and not even enough volcanic disaster data to construct damage functions in the world, compared to other hazards. Using the method suggested in the study and the limited damage data from Japan and New Zealand, we construct Weibull-type functions or linear functions dependent of available data to calculate volcanic ash loss estimation, which we think need to be corrected to make it more suitable for inventory characteristics and environmental conditions in Korea.

• International conference on construction engineering and project management
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.232-235
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• 2015

Defect data contains experiential knowledge about specific work conditions. And the number of projects performed by a company is too limited for an individual to experience the various defects under the current complex construction environment. Therefore, in order to manage and prevent a reoccurrence of defects, a proper data feedback mechanism is required. However, most defect data are stored in unstructured ways, resulting in the fundamental problem of data utilization. In this paper, a new framework is proposed by using linked data technologies to improve defect data utilization. The target of this framework is to convert defect data to the ontology-based linked data format for sharing defect data from different data sources. To demonstrate it, some technical solutions are implemented by using real cases. The proposed approach can reduce data search time and improve the accuracy of search results as well. Moreover, the proposed approach can be applied to other domains that need to refer to external sources such as safety, specification, product, and regulation.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 한국농림기상학회 2016년도 추계 학술발표논문집
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• pp.25-28
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• 2016

Recently, because of the weather forecasts through the low-resolution data has been limited, the demand of the high-resolution data is sharply increasing. Therefore, in this study, we restore the ultra-high resolution synthetic precipitation and temperature data for 2000-2014 due to small-scale topographic effect using the QPM (Quantitative Precipitation Model)/QTM (Quantitative Temperature Model). First, we reproduce the detailed precipitation and temperature data with 1km resolution using the distribution of Automatic Weather System (AWS) data and Automatic Synoptic Observation System (ASOS) data, which is about 10km resolution with irregular grid over South Korea. Also, we recover the precipitation and temperature data with 1km resolution using the MERRA reanalysis data over North Korea, because there are insufficient observation data. The precipitation and temperature from restored current climate reflect more detailed topographic effect than irregular AWS/ASOS data and MERRA reanalysis data over the Korean peninsula. Based on this analysis, more detailed prospect of regional climate is investigated.

• Journal of Korea Multimedia Society
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• 제22권7호
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• pp.749-758
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• 2019

This paper proposes a data augmentation algorithm to improve the performance of DNN(Deep Neural Network) based speech enhancement. Many deep learning models are exploring algorithms to maximize the performance in limited amount of data. The most commonly used algorithm is the data augmentation which is the technique artificially increases the amount of data. For the effective data augmentation algorithm, we used a formant enhancement method that assign the different weights to the formant frequencies. The DNN model which is trained using the proposed data augmentation algorithm was evaluated in various noise environments. The speech enhancement performance of the DNN model with the proposed data augmentation algorithm was compared with the algorithms which are the DNN model with the conventional data augmentation and without the data augmentation. As a result, the proposed data augmentation algorithm showed the higher speech enhancement performance than the other algorithms.

• The Korean Journal of Pain
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• 제30권3호
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• pp.183-191
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• 2017

Background: Current therapy for the treatment of neuropathic pain is often unsatisfactory. Considerable variation in treatment pattern still exists in spite of availability of sufficient literature from various guidelines. Recent Indian market data suggested that the utilization (sale) of drugs such as amitriptyline, pregabalin, and gabapentin was more for low-dose unit packs than that of the high-dose unit packs, raising the belief that these drugs are prescribed at a lower dose than is actually recommended in the guidelines. To test this hypothesis, a survey was conducted across speciality throughout the country to observe the prescription pattern of these drugs amongst the health care providers in India. Methods: Three hundred fifty survey forms were distributed of which 281 forms were included for analysis. Results: It was observed that the commonly used initiation and maintenance dose for amitriptyline, pregabalin, and gabapentin was 5-10 mg/day, 50-75 mg/day, and 100-300 mg/day, respectively. The reason to select the lower dosages was to have a balancing effect to achieve good efficacy with minimum side effects. Care-givers reported no side effects/not many side effects as a reason in 22.2%, 16.88%, and 23.86% patients with amitriptyline, pregabalin, and gabapentin, respectively. Sedation and giddiness were commonly reported with all three drugs. Conclusions: Commonly prescribed drugs for management of neuropathic pain, such as amitriptyline, pregabalin, and gabapentin are preferred at lower doses in Indian clinical settings. Acceptable efficacy and low tolerance to the standard dosage is believed to be the reason behind the prescribed dose.