• Journal of Construction Engineering and Project Management
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• v.8 no.4
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• pp.1-24
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• 2018

In the last decade, the use of Building Information Modeling (BIM) as a new technology has been applied with traditional Computer-aided design implementations in an increasing number of architecture, engineering, and construction projects and applications. Its employment alongside construction management, can be a valuable tool in helping move these activities and projects forward in a more efficient and time-effective manner. The traditional stakeholders, i.e., Owner, A/E and the Contractor are involved in this BIM system that is used in almost every activity of construction projects, such as design, cost estimate and scheduling. This article extracts major features of the application of BIM from perspective of participating BIM components, along with the different phrases, and applies to them a logistic analysis using a fuzzy performance tree, quantifying these phrases to judge the effectiveness of the BIM techniques employed. That is to say, these fuzzy performance trees with fuzzy logic concepts can properly translate the linguistic rating into numeric expressions, and are thus employed in evaluating the influence of BIM applications as a mathematical process. The rotational fuzzy models are used to represent the membership functions of the performance values and their corresponding weights. Illustrations of the use of this fuzzy BIM performance tree are presented in the study for the uninitiated users. The results of these processes are an evaluation of BIM project performance as highly positive. The quantification of the performance ratings for the individual factors is a significant contributor to this assessment, capable of parsing vernacular language into numerical data for a more accurate and precise use in performance analysis. It is hoped that fuzzy performance trees and fuzzy set analysis can be used as a tool for the quality and risk analysis for other construction techniques in the future. Baldwin's rotational models are used to represent the membership functions of the fuzzy sets. Three scenarios are presented using fuzzy MEAN, AND and OR gates from the lowest to intermediate levels of the tree, and fuzzy SUM gate to relate the intermediate level to the top component of the tree, i.e., BIM application final performance. The use of fuzzy MEAN for lower levels and fuzzy SUM gates to reach the top level suggests the most realistic and accurate results. The methodology (fuzzy performance tree) described in this paper is appropriate to implement in today's construction industry when limited objective data is presented and it is heavily relied on experts' subjective judgment.

• Korean Journal of Construction Engineering and Management
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• v.20 no.1
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• pp.62-72
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• 2019

Future prospects for the North Korean construction market created by reunification of the Korean Peninsula has consistently been recognized as highly promising. Although rehabilitation projects of the deteriorating construction facilities in North Korea are expected to serve as new source of growth engine to South Korea in future, the status quo of each infrastructure in the North are described verbosely with signs of subjective translation. There has been limited approach on depicting the condition and performance of the North Korean facilities based on quantitative and systematic approach. Thus, this study has been conducted under a twofold purpose. First, this study proposes a performance indicator for identifying the status quo of the major construction facilities in North Korea based on a quantitative approach. Second, this study applies the developed indicator to visualize the results on the conditions of each facility in the form of a report card. This expected to serve as a basis on determining the appropriate level of the construction infrastructure in North Korea and estimating the range of rehabilitation projects along with the investment cost.

• Journal of The Korean Society of Integrative Medicine
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• v.6 no.4
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• pp.171-182
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• 2018

Purpose : The purpose of this study was to examine the relationship between the characteristics of caregivers and adults with intellectual disability, and social support, family function, and rehabilitation needs in caregivers. Methods : A total 98 pairs of adults with intellectual disability and their caregivers participated in this study. The researchers examined the general characteristics of the adults with intellectual disability and their caregivers. The evaluation included analysis of the level of activities of daily living, ability to communicate, and health status of the adults with intellectual disability, while the family income, health status, utility and the need for rehabilitation, social support (multidimensional scaled perceived social support, MSPSS) and family function (adaptation, partnership, growth, affection, resolve, and APGAR index) of the caregivers were measured. The data collected were analyzed to determine the relationship of the characteristics of adults with intellectual disability and the social support, family function, and rehabilitation needs of caregivers using regression and correlation analysis. Results : The rehabilitation needs were significantly correlated with the age of the adults with intellectual disability (p<.01), and the subjective health status of the caregivers (p<.05). The education level of the caregivers affected social support significantly ($R^2=.058$, p=.021). The communication ability of the adults with intellectual disability affected family function ($R^2=.071$, p=.01). The social support of caregivers had a significant effect on family function ($R^2=.488$, p<.001). Conclusion : These findings suggest that the barriers to community rehabilitation should be lowered, and the authors discussed the results of the present investigation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.6
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• pp.751-760
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• 2021

Most bridges in Korea are over 20 years old, and many problems linked to their deterioration are being reported. The current practice for bridge inspection mainly depends on expert evaluation, which can be subjective. Recent studies have introduced data-driven methods using building information modeling, which can be more efficient and objective, but these methods require manual procedures that consume time and money. To overcome this, this study developed an image-based automaticbridge component classification network to reduce the time and cost required for converting the visual information of bridges to a digital model. The proposed method comprises two convolutional neural networks. The first network estimates the type of the bridge based on the superstructure, and the second network classifies the bridge components. In avalidation test, the proposed system automatically classified the components of 461 bridge images with 96.6 % of accuracy. The proposed approach is expected to contribute toward current bridge maintenance practice.

• Fashion & Textile Research Journal
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• v.24 no.5
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• pp.655-665
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• 2022

This study evaluated the validity of a newly developed mobility protocol examining the comfort functions and requirements of personal protective equipment (PPE) for COVID-19 healthcare workers. Eight males (age: 24.7 ± 3.0 y, height: 173.4 ± 2.3 cm, and body weight 69.9 ± 3.7 kg) participated in the following three PPE conditions: (1) Plastic gown ensemble, (2) Level D ensemble, and (3) Powered air purifying respirator (PAPR) ensemble. The mobility protocol consisted of 10 different tasks in addition to donning and doffing. The 10 tasks were repeated twice at an air temperature of 25oC with 74% RH. The results showed significant differences among the three PPE conditions in mean skin temperature, local skin temperatures (the forehead, thigh, calf, and foot), clothing microclimate (the chest and back), thermal sensation, thermal comfort, and humidity sensation, while there were no significant differences in heart rate or total sweat rate. At rest, the subjects felt less warm and more comfortable in the PAPR than in the Level D condition (P<0.05). However, subjective perceptions in the PAPR and Level D conditions became similar as the tasks progressed and mean skin and leg temperature became greater for the PAPR than the Level D condition (P<0.05). An interview was conducted just after completing the mobility test protocol, and suggestions for improving each PPE item were obtained. To sum up, the mobility test protocol was valid for evaluating the comfort functions of PPE for healthcare workers and obtaining requirements for improving the mobility of each PPE item.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.1100-1118
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• 2021

In a wide range of ML applications, the training data contains privacy-sensitive information that should be kept secure. Training the ML systems by privacy-sensitive data makes the ML model inherent to the data. As the structure of the model has been fine-tuned by training data, the model can be abused for accessing the data by the estimation in a reverse process called model inversion attack (MIA). Although, MIA has been applied to shallow neural network models of recognizers in literature and its threat in privacy violation has been approved, in the case of a deep learning (DL) model, its efficiency was under question. It was due to the complexity of a DL model structure, big number of DL model parameters, the huge size of training data, big number of registered users to a DL model and thereof big number of class labels. This research work first analyses the possibility of MIA on a deep learning model of a recognition system, namely a face recognizer. Second, despite the conventional MIA under the white box scenario of having partial access to the users' non-sensitive information in addition to the model structure, the MIA is implemented on a deep face recognition system by just having the model structure and parameters but not any user information. In this aspect, it is under a semi-white box scenario or in other words a gray-box scenario. The experimental results in targeting five registered users of a CNN-based face recognition system approve the possibility of regeneration of users' face images even for a deep model by MIA under a gray box scenario. Although, for some images the evaluation recognition score is low and the generated images are not easily recognizable, but for some other images the score is high and facial features of the targeted identities are observable. The objective and subjective evaluations demonstrate that privacy cyber-attack by MIA on a deep recognition system not only is feasible but also is a serious threat with increasing alert state in the future as there is considerable potential for integration more advanced ML techniques to MIA.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.538-544
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• 2021

Technology readiness assessment is a procedure for managing defense project risk factors based on the preemptive identification of technical risks. Under current regulations, technology readiness is determined based on considerations of the ratings of factors itemized on a checklist, whether unsatisfied factors have a fatal impact on the project, and whether countermeasures for unsatisfied factors have been established. However, objective criteria for assessing the impact of unsatisfied factors have not been presented, and thus, at present, the results of technology readiness level determinations are largely subjective. In addition, the importance of questions on the checklist is dependent on individual project characteristics and this is not considered during the assessment process. In this paper, we propose an improved technology readiness assessment procedure that considers the characteristics of each project. Using the proposed procedure, we quantitatively determined the importance of each checklist item using a weighting method. We found the devised procedure improved the reliability and objectivity of technology readiness assessment results. A case analysis of a complex weapons system is presented to demonstrate these improvements.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.411-422
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• 2021

The purpose of this study is to examine the relationships between quality of life and demographic characteristics and health-related behavioral characteristics, and their relevance to variables that represent health conditions among metropolitan-dwelling older adults. The study subjects were 380 senior citizens aged 65 or older living in the D metropolitan area, and data collection was conducted by visiting them for interviews in June 2019. A binomial logistic regression analysis was performed to examine the relationship between independent variables (demographic characteristics, health-related behavioral characteristics, health condition variables) and the dependent variable (quality of life) while controlling for gender and age. As a result, the factors related to quality of life for those surveyed were education level, spousal status, living status, bear for living expenses, average monthly allowance, satisfaction with daily life, evaluation of sleep quality, smoking and eating habits, amount of regular exercise, hobbies, subjective health status, physical disability (if any), hearing ability, visual acuity, mastication ability, urinary incontinence (present or not), and amnesia. The above results suggest that quality of life for the elderly living in urban areas is significantly related to variables that indicate demographic characteristics, health-related behavioral characteristics, and health condition.

• The Journal of the Acoustical Society of Korea
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• v.40 no.6
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• pp.593-606
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• 2021

The present study investigated the sounds at 13 points in the four districts in Cheongju including commercial district, historic district, urban walking district and university campus in order to realize the soundscape of the city. In order to this, questionnaire survey was conducted to 65 citizens and 5 acoustic experts on sites to find both sound loudness and annoyance of each district. At the same time, information about loud, unpleasant, preferred and representative sound of each district were acquired by selecting three from 35 sounds which consist of natural, artificial and machinery sounds. As a result, it was found that there is a very close correlation between sound loudness and annoyance. Through the analysis of sounds at each district, it was revealed that machinery sounds dominate in commercial area as figure sound, It was also shown that artificial and natural sounds dominate in historic area, artificial sounds in both urban area and university campus respectively. Laboratory listening tests were undertaken to 20 people using recorded sounds and video captured on site. The results denote that machinery and artificial sounds are regarded as most loud, machinery sounds as most unpleasant, natural and artificial sounds as most pleasant which shows similar tendency of on-site evaluation.

• Journal of Broadcast Engineering
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• v.28 no.2
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• pp.213-229
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• 2023

In this paper, we introduce a spatial sound rendering system that provides 6DoF spatial sound in real time in response to the movement of a listener located in a virtual environment. This system was implemented using MPEG-I AEP as a development environment for the CfP response of MPEG-I Immersive Audio and consists of an encoder and a renderer including a decoder. The encoder serves to offline encode metadata such as the spatial audio parameters of the virtual space scene included in EIF and the directivity information of the sound source provided in the SOFA file and deliver them to the bitstream. The renderer receives the transmitted bitstream and performs 6DoF spatial sound rendering in real time according to the position of the listener. The main spatial sound processing technologies applied to the rendering system include sound source effect and obstacle effect, and other ones for the system processing include Doppler effect, sound field effect and etc. The results of self-subjective evaluation of the developed system are introduced.