• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.370-378
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• 2019

The aim of this study was conducted to investigate the awareness and practice of personal hygiene and clinic hygiene of infection among physical therapist and to analyze the factors affecting it to provide basic data for the establishment of nosocomial infection management programs and policies in the physical therapist unit. In this study, 320 physical therapists were collected and analyzed. The study tool used a self-administered questionnaire to investigate general characteristics and awareness and practice of nosocomial infections. Responses were determined as 5-Likert scales and data were analysed using percentage, independent t-test, ANOVA. As a result of this study, 17.8% of infectious disease management departments were not found, and 41.6% of physical therapists were not educated about nosocomial infection. In addition, physical therapists with sufficient protective equipment for treatment were very low at 25.3%. Thus, in order to increase awareness and practice of nosocomial infection in the future, it is necessary to provide enough protective equipment for the treatment within the hospital, and it is considered that the nosocomial infection education of the physical therapist should be carried out regularly in the hospital itself.

• 재활복지
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• v.18 no.4
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• pp.165-186
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• 2014

The purpose of the study is intended to analysis on students adjustment of students with disabilities in a special class of the elementary school focused on KCI journals through a systematic review. This study was searched from papers published from Jan, 2004 to May, 2014 using KISS, DBPIA, RISS, Google databases. The key words were "inclusive education, special class, inclusive class, student with disabilities, school adjustment, school life, school adjustment scale, elementary school". Results of data analysis were follows; 1. A total of 35 papers were analyzed. Except for 6 papers published in 2004~2007, 29 papers were published after 2008.; 2. The participant of study subject was total 141. Students with intellectual disability were 61.7%. Students with learning disabilities were 17.0%.; 3. The assessment domain of study was analyzed total 51 data.; academic achievement and task performance (25.4%), class attitude and participatory behavior(23.5%), problem behavior(21.5%). The Study in student with intellectual disability was 10 assessment domains.; 4. The method of assessment was total 41.; the use of operational definition(56.1%), the development of test (17.1%), and the use of assessment tool(14.6%).

• Journal of Veterinary Clinics
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• v.36 no.1
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• pp.7-14
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• 2019

In South Korea, six large outbreaks of highly pathogenic avian influenza (HPAI) have occurred since the first confirmation in 2003 from chickens. For the past 15 years, HPAI outbreaks have become an annual phenomenon throughout the country and has extended to wider regions, across rural and urban environments. An understanding of the spatial epidemiology of HPAI occurrence is essential in assessing and managing the risk of the infection; however, local spatial variations of relationship between HPAI incidences in Korea and related risk factors have rarely been derived. This study examined whether spatial heterogeneity exists in this relationship, using a geographically weighted Poisson regression (GWPR) model. The outcome variable was the number of HPAI-positive farms at 252 Si-Gun-Gu (administrative boundaries in Korea) level notified to government authority during the period from January 2014 to April 2016. This response variable was regressed to a set of sociodemographic and topographic predictors, including the number of wild birds infected with HPAI virus, the number of wintering birds and their species migrated into Korea, the movement frequency of vehicles carrying animals, the volume of manure treated per day, the number of livestock farms, and mean elevation. Both global and local modeling techniques were employed to fit the model. From 2014 to 2016, a total of 403 HPAI-positive farms were reported with high incidence especially in western coastal regions, ranging from 0 to 74. The results of this study show that local model (adjusted R-square = 0.801, AIC = 954.5) has great advantages over corresponding global model (adjusted R-square = 0.408, AIC = 2323.1) in terms of model fitting and performance. The relationship between HPAI incidence in Korea and seven predictors under consideration were significantly spatially non-stationary, contrary to assumptions in the global model. The comparison between global Poisson and GWPR results indicated that a place-specific spatial analysis not only fit the data better, but also provided insights into understanding the non-stationarity of the associations between the HPAI and associated determinants. We demonstrated that an empirically derived GWPR model has the potential to serve as a useful tool for assessing spatially varying characteristics of HPAI incidences for a given local area and predicting the risk area of HPAI occurrence. Considering the prominent burden of HPAI this study provides more insights into spatial targeting of enhanced surveillance and control strategies in high-risk regions against HPAI outbreaks.

• Therapeutic Science for Rehabilitation
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• v.8 no.1
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• pp.51-62
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• 2019

Objective: To develop and verify the usability of a cognitive rehabilitation system with diverse cognitive functional levels based on tangible objects for the elderly population. Methods: A study was conducted to investigate the system's strengths and weaknesses by upgrading it with responses from two groups of 15 patients and 4 occupational therapists. After undergoing three forms of training - regarding executive function, memory, and concentration for a total of 20-30 min, the participants were asked to answer a structured questionnaire about contents of the three forms of training, hardware including the tablet PC functioning as a CPU and display media and tangible objects, and satisfaction of experiential usage of the system. Results: Both groups responded that the most interesting training area was executive function while the least interesting was concentration. Six participants reported that the size of the screen of the tablet PC was inappropriate, and five responded that the size of the tool was inappropriate. All therapists and 40% of the patients responded that they were satisfied with this system. Conclusion: This system's features include easy manipulation of tangible tools for performing training tasks, easy selection of and training in cognitive areas based on users' needs, and automatic adjustment of difficulty level based on users' performance. The training environment was designed to be similar to the natural environment by using tangible objects in both hands as input devices for the system, and the system was considered as an alternative to the lack of community cognitive rehabilitation specialists.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.11-20
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• 2019

In this study, a novel virtual reality (VR) experience environment is proposed for enabling walking adaptation of visually impaired people. The core of proposed VR environment is based on immersive walking interactions and deep learning based braille blocks recognition. To provide a realistic walking experience from the perspective of visually impaired people, a tracker-based walking process is designed for determining the walking state by detecting marching in place, and a controller-based VR white cane is developed that serves as the walking assistance tool for visually impaired people. Additionally, a learning model is developed for conducting comprehensive decision-making by recognizing and responding to braille blocks situated on roads that are followed during the course of directions provided by the VR white cane. Based on the same, a VR application comprising an outdoor urban environment is designed for analyzing the VR walking environment experience. An experimental survey and performance analysis were also conducted for the participants. Obtained results corroborate that the proposed VR walking environment provides a presence of high-level walking experience from the perspective of visually impaired people. Furthermore, the results verify that the proposed learning algorithm and process can recognize braille blocks situated on sidewalks and roadways with high accuracy.

• Journal of Korean Society of Neurocognitive Rehabilitation
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• v.10 no.2
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• pp.45-52
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• 2018

The purpose of the present study was to determine correlations between the Berg Balance Scale (BBS), Montreal Cognitive Assessment-Korean (MoCA-K) and Modified Barthel Index (MBI) targeting stroke patients, and it seeks to analyze the influence among each factor to establish the fundamental research in evaluating the functional performance capability of stroke patients. The study was conducted between December 2017 and March 2018 and the target of the study was 34 stroke patients who are hospitalized and treated in Y rehabilitation hospital located in Goyang city. Following in criteria of how participants were selected. First, a person without the onset of 6months or more. Second, a person who can communicate and score over 20 points on MMSE-K. Third, a person without unilateral neglect. Fourth, a person without lower motor neuron lesion and orthopedic disease on the bilateral lower extremity. Fifth, a person without audiovisual problem and history of using drug or surgery that influence athletic function. sixth, patients who agreed on participating in the study. The evaluation was processed by measuring BBS, MoCA-K, and MBI with the occupational therapist and physical therapist. Also, one assistant was participated in measuring balanced ability for the safety reason. It was found that significantly correlates (p<.01) with BBS and MoCA-K (r=.459), BBS and MBI (r=.550), MoCA-K and MBI (r=.565). This study is meaningful that it provided the basis for the active use of BBS, MoCA-K and MBI as a clinical evaluation tool and its usefulness.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.6
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• pp.23-35
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• 2009

Password-Authenticated Key Exchange (PAKE) Protocol is a useful tool for secure communication conducted over open networks without sharing a common secret key or assuming the existence of the public key infrastructure (PKI). It seems difficult to design efficient PAKE protocols using RSA, and thus many PAKE protocols are designed based on the Diffie-Hellman key exchange (DH-PAKE). Therefore it is important to design an efficient PAKE based on RSA function since the function is suitable for designing a PAKE protocol for imbalanced communication environment. In this paper, we propose a computationally-efficient key exchange protocol based on the RSA function that is suitable for low-power devices in imbalanced environment. Our protocol is more efficient than previous RSA-PAKE protocols, required theoretical computation and experiment time in the same environment. Our protocol can provide that it is more 84% efficiency key exchange than secure and the most efficient RSA-PAKE protocol CEPEK. We can improve the performance of our protocol by computing some costly operations in offline step. We prove the security of our protocol under firmly formalized security model in the random oracle model.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1131-1139
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• 2020

The static analysis of the source code is to find the remaining security weaknesses for a wide range of source codes. The static analysis tool is used to check the result, and the static analysis expert performs spying and false detection analysis on the result. In this process, the amount of analysis is large and the rate of false positives is high, so a lot of time and effort is required, and a method of efficient analysis is required. In addition, it is rare for experts to analyze only the source code of the line where the defect occurred when performing positive/false detection analysis. Depending on the type of defect, the surrounding source code is analyzed together and the final analysis result is delivered. In order to solve the difficulty of experts discriminating positive and false positives using these static analysis tools, this paper proposes a method of determining whether or not the security weakness found by the static analysis tools is a spy detection through artificial intelligence rather than an expert. In addition, the optimal size was confirmed through an experiment to see how the size of the training data (source code around the defects) used for such machine learning affects the performance. This result is expected to help the static analysis expert's job of classifying positive and false positives after static analysis.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.340-348
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• 2021

Continuous monitoring of RGB (Red, Green, Blue) vegetation indices is important to apply remote sensing technology for the estimation of crop growth. In this study, we evaluated the performance of eight vegetation indices derived from soybean RGB images with various agronomic parameters under drought stress condition. Drought stress influenced the behavior of various RGB vegetation indices related soybean canopy architecture and leaf color. In particular, reported vegetation indices such as ExGR (Excessive green index minus excess red index), Ipca (Principal Component Analysis Index), NGRDI (Normalized Green Red Difference Index), VARI (Visible Atmospherically Resistance Index), SAVI (Soil Adjusted Vegetation Index) were effective tools in obtaining canopy coverage and leaf chlorophyll content in soybean field. In addition, the RGB vegetation indices related to leaf color responded more sensitively to drought stress than those related to canopy coverage. The PLS-DA (Partial Squares-Discriminant Analysis) results showed that the separation of RGB vegetation indices was distinct by drought stress. The results, yet preliminary, display the potential of applying vegetation indices based on RGB images as a tool for monitoring crop environmental stress.

• The korean journal of orthodontics
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• v.52 no.1
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• pp.3-19
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• 2022

Objective: The purpose of this study was to investigate the accuracy of one-step automated orthodontic diagnosis of skeletodental discrepancies using a convolutional neural network (CNN) and lateral cephalogram images with different qualities from nationwide multi-hospitals. Methods: Among 2,174 lateral cephalograms, 1,993 cephalograms from two hospitals were used for training and internal test sets and 181 cephalograms from eight other hospitals were used for an external test set. They were divided into three classification groups according to anteroposterior skeletal discrepancies (Class I, II, and III), vertical skeletal discrepancies (normodivergent, hypodivergent, and hyperdivergent patterns), and vertical dental discrepancies (normal overbite, deep bite, and open bite) as a gold standard. Pre-trained DenseNet-169 was used as a CNN classifier model. Diagnostic performance was evaluated by receiver operating characteristic (ROC) analysis, t-stochastic neighbor embedding (t-SNE), and gradient-weighted class activation mapping (Grad-CAM). Results: In the ROC analysis, the mean area under the curve and the mean accuracy of all classifications were high with both internal and external test sets (all, > 0.89 and > 0.80). In the t-SNE analysis, our model succeeded in creating good separation between three classification groups. Grad-CAM figures showed differences in the location and size of the focus areas between three classification groups in each diagnosis. Conclusions: Since the accuracy of our model was validated with both internal and external test sets, it shows the possible usefulness of a one-step automated orthodontic diagnosis tool using a CNN model. However, it still needs technical improvement in terms of classifying vertical dental discrepancies.