• Therapeutic Science for Rehabilitation
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• v.10 no.2
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• pp.109-128
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• 2021

Objective : The purpose of this study was to develop a Korean version of the Activities of Daily Living (ADL)-focused Occupation-Based Neurobehavioral Evaluation (A-ONE) through cross-cultural adaptation and examine its validity and reliability. Methods : This study translated the A-ONE into Korean and performed cross-cultural adaptation for the Korean population. After the development of the Korean version of the A-ONE, cross-cultural and concurrent validities were analyzed. Internal consistency, test-retest reliability, and inter-rater reliability were also evaluated. Results : We adapted three items to the Korean culture. The Korean version of the A-ONE showed high cross-cultural validity with a content validity index (I-CVI) >0.9. It correlated with the Functional Independence Measure (FIM) (r=0.52-0.77, p<0.001), except for communication. Cronbach's α was 0.58-0.93 for the functional independence scale (FI) and 0.42-0.93 for the neurobehavioral specific impairment subscale (NBSIS). Intraclass correlation coefficients (ICCs) indicated high test-retest and inter-rater reliability for FI (ICC=0.79-1.00 and 0.75-1.00, respectively) and NBSIS (ICC=0.74-1.00 and 0.72-1.00, respectively). Conclusion : The Korean version of the A-ONE is well adapted to the Korean culture and has good validity and reliability. It is recommended to evaluate ADL performance skills and neurobehavioral impairments simultaneously in Korea.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.89-106
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• 2022

Recently, the amount of video data collected from smartphones, CCTVs, black boxes, and high-definition cameras has increased rapidly. According to the increasing video data, the requirements for analysis and utilization are increasing. Due to the lack of skilled manpower to analyze videos in many industries, machine learning and artificial intelligence are actively used to assist manpower. In this situation, the demand for various computer vision technologies such as object detection and tracking, action detection, emotion detection, and Re-ID also increased rapidly. However, the object detection and tracking technology has many difficulties that degrade performance, such as re-appearance after the object's departure from the video recording location, and occlusion. Accordingly, action and emotion detection models based on object detection and tracking models also have difficulties in extracting data for each object. In addition, deep learning architectures consist of various models suffer from performance degradation due to bottlenects and lack of optimization. In this study, we propose an video analysis system consists of YOLOv5 based DeepSORT object tracking model, SlowFast based action recognition model, Torchreid based Re-ID model, and AWS Rekognition which is emotion recognition service. Proposed model uses single-linkage hierarchical clustering based Re-ID and some processing method which maximize hardware throughput. It has higher accuracy than the performance of the re-identification model using simple metrics, near real-time processing performance, and prevents tracking failure due to object departure and re-emergence, occlusion, etc. By continuously linking the action and facial emotion detection results of each object to the same object, it is possible to efficiently analyze videos. The re-identification model extracts a feature vector from the bounding box of object image detected by the object tracking model for each frame, and applies the single-linkage hierarchical clustering from the past frame using the extracted feature vectors to identify the same object that failed to track. Through the above process, it is possible to re-track the same object that has failed to tracking in the case of re-appearance or occlusion after leaving the video location. As a result, action and facial emotion detection results of the newly recognized object due to the tracking fails can be linked to those of the object that appeared in the past. On the other hand, as a way to improve processing performance, we introduce Bounding Box Queue by Object and Feature Queue method that can reduce RAM memory requirements while maximizing GPU memory throughput. Also we introduce the IoF(Intersection over Face) algorithm that allows facial emotion recognized through AWS Rekognition to be linked with object tracking information. The academic significance of this study is that the two-stage re-identification model can have real-time performance even in a high-cost environment that performs action and facial emotion detection according to processing techniques without reducing the accuracy by using simple metrics to achieve real-time performance. The practical implication of this study is that in various industrial fields that require action and facial emotion detection but have many difficulties due to the fails in object tracking can analyze videos effectively through proposed model. Proposed model which has high accuracy of retrace and processing performance can be used in various fields such as intelligent monitoring, observation services and behavioral or psychological analysis services where the integration of tracking information and extracted metadata creates greate industrial and business value. In the future, in order to measure the object tracking performance more precisely, there is a need to conduct an experiment using the MOT Challenge dataset, which is data used by many international conferences. We will investigate the problem that the IoF algorithm cannot solve to develop an additional complementary algorithm. In addition, we plan to conduct additional research to apply this model to various fields' dataset related to intelligent video analysis.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.91-107
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• 2023

Lean startup is a concept that combines the words "lean," meaning an efficient way of running a business, and "startup," meaning a new business. It is often cited as a strategy for minimizing failure in early-stage businesses, especially in software-based startups. By scrutinizing the case of a startup L, this study suggests that lean startup methodology(LSM) can be useful for hardware and manufacturing companies and identifies ways for early startups to successfully implement LSM. To this end, the study explained the core of LSM including the concepts of hypothesis-driven approach, BML feedback loop, minimum viable product(MVP), and pivot. Five criteria to evaluate the successful implementation of LSM were derived from the core concepts and applied to evaluate the case of startup L . The early startup L pivoted its main business model from defecation alert system for patients with limited mobility to one for infants or toddlers, and finally to a smart bottle for infants. In developing the former two products, analyzed from LSM's perspective, company L neither established a specific customer value proposition for its startup idea and nor verified it through MVP experiment, thus failed to create a BML feedback loop. However, through two rounds of pivots, startup L discovered new target customers and customer needs, and was able to establish a successful business model by repeatedly experimenting with MVPs with minimal effort and time. In other words, Company L's case shows that it is essential to go through the customer-market validation stage at the beginning of the business, and that it should be done through an MVP method that does not waste the startup's time and resources. It also shows that it is necessary to abandon and pivot a product or service that customers do not want, even if it is technically superior and functionally complete. Lastly, the study proves that the lean startup methodology is not limited to the software industry, but can also be applied to technology-based hardware industry. The findings of this study can be used as guidelines and methodologies for early-stage companies to minimize failures and to accelerate the process of establishing a business model, scaling up, and going global.

• Journal of Broadcast Engineering
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• v.19 no.5
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• pp.640-655
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• 2014

Many of today's video systems have additional depth camera to provide extra features such as 3D support. Thanks to these changes made in multimedia system, it is now much easier to obtain depth information of the video. Depth information can be used in various areas such as object classification, background area recognition, and so on. With depth information, we can achieve even higher coding efficiency compared to only using conventional method. Thus, in this paper, we propose the 2D video coding algorithm which uses depth information on top of the next generation 2D video codec HEVC. Background area can be recognized with depth information and by performing HEVC with it, coding complexity can be reduced. If current CU is background area, we propose the following three methods, 1) Earlier stop split structure of CU with PU SKIP mode, 2) Limiting split structure of CU with CU information in temporal position, 3) Limiting the range of motion searching. We implement our proposal using HEVC HM 12.0 reference software. With these methods results shows that encoding complexity is reduced more than 40% with only 0.5% BD-Bitrate loss. Especially, in case of video acquired through the Kinect developed by Microsoft Corp., encoding complexity is reduced by max 53% without a loss of quality. So, it is expected that these techniques can apply real-time online communication, mobile or handheld video service and so on.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.10
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• pp.920-929
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• 2014

Recently, embedded system which demand is explosively increasing in the fields of communication, traffic, medical and industry facilities, expands to cyber physical system (CPS) which monitors and controls the networked embedded systems. In addition, internet of things(IoT) technology using wearable devices such as Google Glass, Samsung Galaxy Gear and Sony Smart Watch are gaining attention. In this situation, Samsung Smart Home and LG Home Chat are released one after another. However, since these services can be available only between smart phones and home appliances, there is a disadvantage that information cannot be passed to other terminals without commercial global messaging server. In this paper, to solve above issues, we propose the structure of an indoor location network based on unit space, which prevents the information of the devices or each individual person from leaking to outside and can selectively communicate to all existent terminals in the network using IoT chatting. Also, it is possible to control general devices and prevent external leakage of private information.

• Journal of Internet Computing and Services
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• v.14 no.1
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• pp.15-22
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• 2013

WAVE(Wireless Access for Vehicular Environment) is new concepts and Vehicles communications technology using for ITS(Intelligent Transportation Systems) service by IEEE standard 802.11p. Also it increases the efficiency and safety of the traffic on the road. However, the efficiency of Scrambler bit computational algorithms of OFDM modulation in WAVE systems will fall as it is not able to process in parallel in terms of hardware and software. This paper proposes an algorithm to configure 64-bits matrix table in scambler bit computation as well as an algorithm to compute 64-bits matrix table and input data in parallel. The proposed algorithm on this thesis is executed using 64-bits matrix table. In the result, the processing speed for 1 and 1000 times is improved about 40.08% ~ 40.27% and processing rate per sec is performed more than 468.35 compared to bit operation scramble. And processing speed for 1 and 1000 times is improved about 7.53% ~ 7.84% and processing rate per sec is performed more than 91.44 compared to 32-bits operation scramble. Therefore, if the 64 bit-CPU is used for 64-bits executable scramble algorithm, it is improved more than 40% compare to 32-bits scrambler.

• The Korean Journal of Emergency Medical Services
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• v.3 no.1
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• pp.7-19
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• 1999

Background : We are in the edge of some human made disasters such as hazardous materials and air pollution, for example, the world news reported that the city of Bhopal, India had serious victims related with a leaking out of the chemical materials, Methyl Isocyanate and many people in India were killed by. These situations many people who live in this world are world are worrying about are not others, but just ours and people consider about that kind of the disasters are the possible situation to happen to all the people. Therefore, we performed this basic study to recognize the risk of Methyl Isocyanate leak accident and to prepare local disaster plan with EMS system. Method : Trace 8.0, a simulation software made by the U.S. company Safer System was used as a tool to estimate the diffusion distance, area and its victims at the concentrations of 0.02ppm, 0.2ppm 5ppm respectively for an assumed B-city of 2 hundred thousands population count in which was presumed 500kg Methyl Isocyanate gas to leak out. Results : 1. During 1 hour, maximum diffusion distances of 0.02ppm 0.2ppm and 5ppm were 5.41km, 1.61km and 0.29km respectively on the plume impact. 2. Maximum population counts influenced by Methyl Isocyanate gas at the concentrations of 0.02ppm 0.2ppm and 5ppm were 40838, 4346 and 222 on the plume impact, while those were 138238, 17261 and 1588 on the vulnerability impact, respectively. 3. Therefore, 17261 persons must put on respiratory device and 138283 persons must be evacuated to safety place within 1 hour. Conclusions : Only small amount leak of Methyl Isocyanate may cause tremendous chemical disaster in urban area, so its disaster plan must be prepared with an accident simulation program and Material Safety Data Sheets(MSDS). Especially, nearby emergency center of an industrial complex must have a strong position about preparation of chemical disaster plan and perform a disaster dill of hazardous material accident annually.

• The Journal of the Korea Contents Association
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• v.12 no.10
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• pp.195-204
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• 2012

The purpose of this study is to suggest the improvement plan for the welfare in the park through the empirical test on the park facilities, which are the hardware, and the service contents, which are the software, in the urban parks of Busan. Therefore, to identify the welfare of the parks in Busan, this study took 7 urban parks as samples according to the plate method of experts, and conducted the questionnaire survey from 1,500 persons using these parks. The IPA analysis results on the importance and the satisfaction of the users on the form of use, facilities and the contents of the park are as follows. First, the convenient facilities, which are the hardware of the park, are represented as a intensive management item. Second, the importance and the satisfaction for all the facilities and the contents of each park are significant differences. according to the location of each park and the characteristics of each principal park users. Such results mean that the Busan urban park operation does not satisfy the expectation of the park users for the welfare facilities in the parks. Therefore, it implies that to activate the urban parks and to improve the quality of life than the present, the aceessibility of the local residents to the information should be reinforced through the development of contents to reflect the region and the desires of the users and through building and managing the homepage of the urban parks.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.16
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• pp.6987-6990
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• 2015

Background: Oral cancer is one of the most prevalent cancers and one of the top ten causes of death in the whole world. Most oral cancers are diagnosed at late stages. Since dentists play a critical role in early detection of oral cancer, they should be knowledgeable and skillful in oral cancer diagnosis. The aim of this study was to survey dentist knowledge about oral cancer in Southern Khorasan Province. Materials and Methods: This descriptive, cross-sectional study was conducted with dentists who participated in an in-service educational program at the Faculty of Dentistry of Birjand University of Medical Sciences in spring 2014. A questionnaire including demographic information with 11 questions regarding oral cancer was prepared. The participants were required to be complete the questionnaires within a specific time span. The data were analyzed using SPSS 15 software by t-test and one-way ANOVA at 0.05 confidence level. Results: A total of 73 dentists out of 80 answered the questionnaires - 36 (49.3%) were females and 37 (50.7%) were males. Total mean score of knowledge was $7.91{\pm}1$ of 11. Mean scores of knowledge of male and female participants were $7.70{\pm}1.83$ and $8.13{\pm}1.94$ respectively. Mean knowledge score of general dentists was $7.41{\pm}1.79$ and of dental specialists was $9.44{\pm}1.0$ In spite of higher knowledge score of women compared to men and general dentists compared to dental specialists, these differences were not statistically significant (p=0.09). Tukey testing showed a significant difference between groups with 1-4 years of experience (8.74) and over twenty years of experience (6.50) ( p=0.001). Conclusions: Considering the good knowledge level of young dentists and the specialists and the importance of early diagnosis of oral cancer, it seems necessary to pay more attention to academic education for dentistry students, as well as holding retraining courses for experienced dentists, so that their knowledge not be reduced over time.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.9
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• pp.1225-1233
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• 2017

Objective: Calving ease (CE) is a complex reproductive trait of economic importance in dairy cattle. This study was aimed to investigate the genetic merits of CE for Holsteins in Korea. Methods: A total of 297,614 field records of CE, from 2000 to 2015, from first parity Holstein heifers were recorded initially. After necessary data pruning such as age at first calving (18 to 42 mo), gestation length, and presence of sire information, final datasets for CE consisted of 147,526 and 132,080 records for service sire calving ease (SCE) and daughter calving ease (DCE) evaluations, respectively. The CE categories were ordered and scores ranged from CE1 to CE5 (CE1, easy; CE2, slight assistance; CE3, moderate assistance; CE4, difficult calving; CE5, extreme difficulty calving). A linear transformation of CE score was obtained on each category using Snell procedure, and a scaling factor was applied to attain the spread between 0 (CE5) and 100% (CE1). A sire-maternal grandsire model analysis was performed using ASREML 3.0 software package. Results: The estimated direct heritability ($h^2$) from SCE and DCE evaluations were $0.11{\pm}0.01$ and $0.08{\pm}0.01$, respectively. Maternal $h^2$ estimates were $0.05{\pm}0.02$ and $0.04{\pm}0.01$ from SCE and DCE approaches, respectively. Estimates of genetic correlations between direct and maternal genetic components were $-0.68{\pm}0.09$ (SCE) and $-0.71{\pm}0.09$ (DCE). The average direct genetic effect increased over time, whereas average maternal effect was low and consistent. The estimated direct predicted transmitting ability (PTA) was desirable and increasing over time, but the maternal PTA was undesirable and decreasing. Conclusion: The evidence on sufficient genetic variances in this study could reflect a possible selection improvement over time regarding ease of calving. It is expected that the estimated genetic parameters could be a valuable resource to formulate sire selection and breeding plans which would be directed towards the reduction of calving difficulty in Korean Holsteins.