• The Korean Journal of Emergency Medical Services
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• v.3 no.1
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• pp.33-42
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• 1999

The purposes of this study which was conducted by studying the literature on Emergency Medical Dispatch System are to provide some developmental policies of quality management, pre-arrival instructions, priority dispatch protocols, training program for the dispatchers(Emergency Medical Dispatchers or EMDs) in Korea and to promote understanding emergency medical dispatching. The conclusions from this summarized as follows; (1) It is confirmed that there has been little study on the Emergency Medical Dispatch System in Korea, because for the first time, the real Emergency Medical Services were introduced into Korea in 1994, and the importance of the Emergency Medical Dispatch System has not been realized. (2) Only some squads are using a set of dispatch protocols, others aren't. (3) In spite of trying to introduce a new set of dispatch protocols, it isn't the priority dispatch system using a complete set of dispatch protocols which has key questions, pre-arrival instructions, mode & configuration based on patient assessment. (4) The EMS is unable to promote the service capacity by using quality management, because there is no medical control on the emergency medical dispatching and the EMDs. (5) There are no medical directors in the communications center who are in charge of the medical control to detect problems derived from the EMS and to solve them. (6) There are no systematic training program for the EMDs who are taking charge of dispatching. (7) Having a deep relation to the elements of the EMS, the emergency medical dispatching is subject to restriction of those elements.

• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.483-492
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• 2004

This paper presents an efficient algorithm for the estimation of damage location and severity in bridge structures using Probabilistic Neural Network (PNN). Generally, the Back Propagation Neural Network (BPNN)-based damage detection methods need a lot of training patterns for neural network learning process and the optimum architecture of a BPNN is selected by trial and error. In this paper, the PNN instead of the conventional BPNN is used as a pattern classifier. The modal properties of damaged structure are somewhat different from those of undamaged one. The basic idea of proposed algorithm is that the PNN classifies a test pattern which consists of the modal characteristics from damaged structure, how close it is to each training pattern which is composed of the modal characteristics from various structural damage cases. In this algorithm, two PNNs are sequentially used. The first PNN estimates the damage location using mode shape and the results of the first PNN are put into the second PNN for the damage severity estimation using natural frequency. The proposed damage assessment algorithm using the PNN is applied to a cable-stayed bridge to verify its applicability.

• Earthquakes and Structures
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• v.11 no.3
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• pp.461-481
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• 2016

The research described in this paper investigates the seismic behaviour of lightly reinforced concrete (RC) bearing sandwich panels, heavily conditioned by shear deformation. A numerical model has been prepared, within an open source finite element (FE) platform, to simulate the experimental response of this emerging structural system, whose squat-type geometry affects performance and failure mode. Calibration of this equivalent mechanical model, consisting of a group of regularly spaced vertical elements in combination with a layer of nonlinear springs, which represent the cyclic behaviour of concrete and steel, has been conducted by means of a series of pseudo-static cyclic tests performed on single full-scale prototypes with or without openings. Both cantilevered and fixed-end shear walls have been analyzed. After validation, this numerical procedure, including cyclic-related mechanisms, such as buckling and subsequent slippage of reinforcing re-bars, as well as concrete crushing at the base of the wall, has been used to assess the capacity of two- and three-dimensional low- to mid-rise box-type buildings and, hence, to estimate their strength reduction factors, on the basis of conventional pushover analyses.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3286-3300
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• 2016

High Efficiency Video Coding (HEVC) Standard, as the latest coding standard, introduces satisfying compression structures with respect to its predecessor Advanced Video Coding (H.264/AVC). The new coding standard can offer improved encoding performance compared with H.264/AVC. However, it also leads to enormous computational complexity that makes it considerably difficult to be implemented in real time application. In this paper, based on machine learning, a fast partitioning method is proposed, which can search for the best splitting structures for Intra-Prediction. In view of the video texture characteristics, we choose the entropy of Gray-Scale Difference Statistics (GDS) and the minimum of Sum of Absolute Transformed Difference (SATD) as two important features, which can make a balance between the computation complexity and classification performance. According to the selected features, adaptive decision trees can be built for the Coding Units (CU) with different size by offline training. Furthermore, by this way, the partition of CUs can be resolved as a binary classification problem. Experimental results have shown that the proposed algorithm can save over 34% encoding time on average, with a negligible Bjontegaard Delta (BD)-rate increase.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.2
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• pp.108-113
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• 2005

The damageability and repairability of similar platform type vehicles could be very concerned with design optimization. In all the vehicles crash tested, small size passenger vehicles were weakness in aspect of damageability and repairability. The most critical area appears to be repair cost considering that parts cost is the largest portion of total repair cost segments. Besides repair cost, attaching method of front sidemember and subframe are placed special importance for impact energy absorption and damageability and repairability. So in order to improve damageability and repairability of vehicle structure and body component of the monocoque type passenger vehicles, the end of front side member and front back beam should be designed with optimum level and to supply the end of front side member as a partial condition approx 300mm. The effectiveness of design concept on the 40% offset frontal impact characteristics of the passenger vehicle structure is investigated and summarized.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.761-768
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• 2020

This paper explores the barriers to derivative accounting disclosures in Vietnamese companies and ranks their relative importance for effective and efficient remedies. The Delphi technique was applied to get agreement of panel of experts on the measurement of factors hindering disclosure. Unstructured questionnaires were first sent to twelve experts who had both practical experience and academic knowledge in the field to get ideas on the obstructions to derivatives disclosure. The structured questionnaire was designed to get their agreement on barriers to derivative accounting disclosures. The data analysis with mean, median, mode, standard deviation, and quartile has been implemented to ensure the unanimity. Market-related factors, legislation, accountants' attributes, managers' attributes, information technology and communication, and on-site training were the six major obstacles agreed upon by the experts during their in-depth interviews. Then, these factors were ranked by applying the analytical hierarchy process (AHP). The findings confirmed the priority of information technology and communication, which held the greatest weight. Legislation ranked second, followed by market-related factors and on-site training, which explained the impediments to derivatives disclosure. Managers' and accountants' attributes had the least contribution to the barriers to derivative disclosures. The results have important implications for actions to enhance corporate derivative disclosures in Vietnam.

• Geomechanics and Engineering
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• v.29 no.6
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• pp.599-614
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• 2022

In this study, the reliability analysis of internal and external stabilities of Reinforced Soil Walls (RSWs) under static and seismic loads are investigated so that it can help the geotechnical engineers to perform the design more realistically. The effect of various variables such as angle of internal soil friction, soil specific gravity, tensile strength of the reinforcements, base friction, surcharge load and finally horizontal earthquake acceleration are examined assuming the variables uncertainties. Also, the correlation coefficient impact between variables, sensitivity analysis, mean change, coefficient of variation and type of probability distribution function were evaluated. In this research, external stability (sliding, overturning and bearing capacity) and internal stability (tensile rupture and pull out) in both static and seismic conditions were investigated. Results of this study indicated sliding as the predominant failure mode in the external stability and reinforcing rupture in the internal stability. First-Order Reliability Method (FORM) are applied to estimate the reliability index (or failure probability) and results are validated using the Monte Carlo Simulation (MCS) method. The results showed among all variables, the internal friction angle and horizontal earthquake acceleration have dominant impact on the both reinforced soil wall internal and external stabilities limit states. Also, the type of probability distribution function affects the reliability index significantly and coefficient of variation of internal friction angle has the greatest influence in the static and seismic limits states compared to the other variables.

• Archives of Plastic Surgery
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• v.50 no.2
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• pp.200-209
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• 2023

Background As the coronavirus disease 2019 virus made its way throughout the world, there was a complete overhaul of our day-to-day personal and professional lives. All aspects of health care were affected including academics. During the pandemic, teaching opportunities for resident training were drastically reduced. Consequently, medical universities in many parts across the globe implemented online learning, in which students are taught remotely and via digital platforms. Given these developments, evaluating the existing mode of teaching via digital platforms as well as incorporation of new models is critical to improve and implement. Methods We reviewed different online learning platforms used to continue regular academic teaching of the plastic surgery residency curriculum. This study compares the four popular Web conferencing platforms used for online learning and evaluated their suitability for providing plastic surgery education. Results In this study with a response rate of 59.9%, we found a 64% agreement rate to online classes being more convenient than normal classroom teaching. Conclusion Zoom was the most user-friendly, with a simple and intuitive interface that was ideal for online instruction. With a better understanding of factors related to online teaching and learning, we will be able to deliver quality education in residency programs in the future.

• Journal of Korea Water Resources Association
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• v.33 no.5
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• pp.537-550
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• 2000

In this study, Neural Networks models were used to forecast daily streamflow at Jindong station of the Nakdong River basin. Neural Networks models consist of CASE 1(5-5-1) and CASE 2(5-5-5-1). The criteria which separates two models is the number of hidden layers. Each model has Fletcher-Reeves Conjugate Gradient BackPropagation(FR-CGBP) and Scaled Conjugate Gradient BackPropagation(SCGBP) algorithms, which are better than original BackPropagation(BP) in convergence of global error and training tolerance. The data which are available for model training and validation were composed of wet, average, dry, wet+average, wet+dry, average+dry and wet+average+dry year respectively. During model training, the optimal connection weights and biases were determined using each data set and the daily streamflow was calculated at the same time. Except for wet+dry year, the results of training were good conditions by statistical analysis of forecast errors. And, model validation was carried out using the connection weights and biases which were calculated from model training. The results of validation were satisfactory like those of training. Daily streamflow forecasting using Neural Networks models were compared with those forecasted by Multiple Regression Analysis Mode(MRAM). Neural Networks models were displayed slightly better results than MRAM in this study. Thus, Neural Networks models have much advantage to provide a more sysmatic approach, reduce model parameters, and shorten the time spent in the model development.

• Therapeutic Science for Rehabilitation
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• v.10 no.2
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• pp.95-108
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• 2021

Objective : This study aimed to develop prototypes of "smart stacking cones" by combining ICT to evaluate and train the upper extremity function and dual task performance in patients with central nervous system impairment, and to identify the complementary point to the completion of the device through a usability test. Methods : This prototype comprised of a hardware and software system that enabled the evaluation and training of patients and the management of data obtained from patients' performance. Specific measurement variables were established so that patient performance could be measured correctly. Based on the measurement variables, a the prototype included a 'single task evaluation modes', 'dual task evaluation mode', 'single task training mode', and 'dual task training modes'. Additionally, a usability test was conducted to assess clinical applicability and overall satisfaction for the prototype. Results : The results of the usability test were generally found to be appropriate. The 'content adequacy' in the usability test was the area with the highest level of adequacy and the lowest level of inadequacy. Additionally, overall 'satisfaction' in the usability test was the area with the highest appropriate and inappropriate levels. Hence, the overall satisfaction results were unstable. Conclusion : Future studies should be conducted to identify the clinical effectiveness of the device by applying an upgraded smart stacking cone to an actual patient group.