• Korean Parent-Child Health Journal
• /
• v.6 no.1
• /
• pp.1-17
• /
• 2003

Thus, I studied Health services supplied by local health centers and the requirements of the inhabitants visiting the health care facilities. The purpose of this study was to provide basic material for the establishment of Health care policy and the development of health care businesses. The target places for this study were 4 health centers; Chungrang-Gu, Nowon-Gu, Eunpyung-Gu, Songpa-Gu, with 509 mothers who were visiting the Centers. The question items of this study concerned a total of 124 health-related services provided by the Health Centers. The data was collected for a total of 92 days; July 1st~September 30th, 1999. 800 questionaries were distributed and 559 answered, 509 were analyzed finally. The collected data were processed using the SAS program to get mean, standard deviation, percentage. Open questions were made to reveal the opinions of mothers using the health care center. The results were as follows : 1. Among the participants of the study, 49.7% were 25~29 years of age, 84.3% were house wives by current occupation, 56.2% were from 4~6 person households. 52.1 were educated at a high school level, and 43.6% were educated at a collage level. 2. The highest percentage(53.6%) of the users were spontaneous in their utilization of health care center. The major reason for using the Health care center is that it is free to 65.8% of those covered and of low cost to 19.3% of those covered. 3. The satisfaction level of those using the health care center appeared to be generally high. The general average value showed up as $3.027{\pm}0.519$. 4. The level of recognition of the value of the heath care center services was high, particularly in the basic item of diagnoses of pregnancy, particularly in the basic item of diagnoses of pregnancy. However, the satisfaction level of health care education In pregnancy is low at 20~40%. In the meantime, the level of recognition in breast- feeding benefits is high at 76.8%. 5. The rate of realizing health care center's service campaign was generally low at 10~20%. 41.3 of the people knew the advertizing material of the health care centers. 32.4% of the people knew the advertizing material of the health care centers. 32.4% of the people knew the campaign of health care center for importance of breast-feeding benefits. 30.1% of the people knew the campaign for testing congenital mechanism disease. In the meantime about 50% was recognised the health care centers campaign for the importance and time of infants vaccination. 6. The need for enhancement of health care center services was shown to be high as $3.266{\pm}0.676$ as an average, chicken pox vaccination being the most highly requested at $3.565{\pm}0.587.$. 7. Among the open questions, the additional service to be provided were as follows ; increase of campaign of health care center services, furnishing advertizing books in public locations, providing shuttle bus service to the health care centers, extension of desire for preventative injections, rest and play areas for the children of the families serviced, consultation rooms, etc.

• Journal of Gifted/Talented Education
• /
• v.21 no.2
• /
• pp.391-405
• /
• 2011

The nature of science has been recognized in a great deal in the field of science education. However, only few innovative programs are offered for science-gifted students to improve their recognition of the nature of science. The current study describes and analyzes science-gifted students' understandings of the nature of science (NOS). In addition, the study looks into contradictory views among the aspects of NOS, which are fundamental data in constructing target programs on NOS for science gifted students. Data used in this study were collected from 73 middle school science-gifted students using an open-ended questionnaire, VNOS. The results of this study showed that the participants' understanding of NOS was significantly distributed on naive or transition view except for 'tentative NOS', and the results revealed inconsistent view among the aspects of NOS. This study proposes two suggestions to enhance the recognition of science-gifted on NOS of science to informed state and to have consistent perspectives with other areas. First, the role of experiment has to be changed-it should be the process in constructing scientific knowledge rather than an instrument to check scientific knowledge to transform perspective on experimental data and scientific knowledge. Second, various opportunities must be provided to science-gifted students, so they can experience the culture and community of scientists and science to gain a wider insight of science.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.17 no.2
• /
• pp.1-9
• /
• 2013

In recent years, numerous mega-size and complex civil infrastructures have been constructed worldwide. For the more precise construction and maintenance process management of these civil infrastructures, the application of a variety of smart sensor-based structural health monitoring (SHM) systems is required. The efficient management of both sensors and collected databases is also very important. Recently, several kinds of database access technologies using Quick Response (QR) code and Augmented Reality (AR) applications have been developed. These technologies provide software tools incorporated with mobile devices, such as smart phone, tablet PC and smart pad systems, so that databases can be accessed very quickly and easily. In this paper, an AR-based structural health monitoring technique is suggested for sensor management and the efficient access of databases collected from sensor networks that are distributed at target structures. The global positioning system (GPS) in mobile devices simultaneously recognizes the user location and sensor location, and calculates the distance between the two locations. In addition, the processed health monitoring results are sent from a main server to the user's mobile device, via the RSS (really simple syndication) feed format. It can be confirmed that the AR-based structural health monitoring technique is very useful for the real-time construction process management of numerous mega-size and complex civil infrastructures.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.1 no.1
• /
• pp.22-32
• /
• 2002

This paper describes about non-burial AVI (Automatic Vehicle Identification) system using general vehicle as probe car for obtaining more accurate traffic information while conserving road pavement surface. Existing spot traffic detectors have their own limits of not obtaining right information owing to its mathematical method. Burial AVI systems have some defects, causing traffic jam, needing much maintenance cost because of frequent cutting of loop and piezo-electric sensors. Especially, they have hard time to make right detection, when it comes to jamming time. Therefore, in this paper, we propose non-burial AVI system with laser trigger unit. Proposed non-burial AVI system is developed to obtain regional traffic information from normal Passing vehicle by automatic license number recognition technology. We have adapted it to national highway section between Suwon city and Pyong$\~$Taek city(9.5km) and get affirmative results. Vehicle detection rate of laser trigger unit is more than 95$\%$, vehicle recognition rate is 87.8$\%$ and vehicle matching rate is about 14.3$\%$. So we regard these as satisfying results to use the system for traffic information service. We evaluate proposed AVI system by regulation of some institutions which are using similar AVI system and the proposed system satisfies all conditions. For future study, we have plan of detailed research about proper lane number from all of the target lanes, optimal section length, information service period, and data fusion method for existing spot detector.

• Resources Recycling
• /
• v.26 no.6
• /
• pp.73-83
• /
• 2017

Used small household appliances have a wide variety of product types and component materials, and contain high percentage of black plastics. However, they are not being recycled efficiently as conventional sensors such as near-infrared ray (NIR), etc. are not able to detect black plastic by types. In the present study, an automatic sorting system was developed based on laser-induced breakdown spectroscopy (LIBS) to promote the recycling of waste plastics. The system we developed mainly consists of sample feeder, automatic position recognition system, LIBS device, separator and control unit. By applying laser pulse on the target sample, characteristic spectral data can be obtained and analyzed by using CCD detectors. The obtained data was then treated by using a classifier, which was developed based on artificial intelligent algorithm. The separation tests on waste plastics also were carried out by using a lab-scale automatic sorting system and the test results will be discussed. The classification rate of the radial basis neural network (RBFNNs) classifier developed in this study was about > 97%. The recognition rate of the black plastic by types with the automatic sorting system was more than 94.0% and the sorting efficiency was more than 80.0%. Automatic sorting system based on LIBS technology is in its infant stage and it has a high potential for utilization in and outside Korea due to its excellent economic efficiency.

• KIPS Transactions on Computer and Communication Systems
• /
• v.12 no.2
• /
• pp.85-92
• /
• 2023

Respiratory infections such as COVID-19 mainly occur within enclosed spaces. The presence or absence of abnormal symptoms of respiratory infectious diseases is judged through initial symptoms such as fever, cough, sneezing and difficulty breathing, and constant monitoring of these early symptoms is required. In this paper, image matching correction was performed for the RGB camera module and the thermal imaging camera module, and the temperature of the thermal imaging camera module for the measurement environment was calibrated using a blackbody. To detection the target recommended by the standard, a deep learning-based object recognition algorithm and the inner canthus recognition model were developed, and the model accuracy was derived by applying a dataset of 100 experimenters. Also, the error according to the measured distance was corrected through the object distance measurement using the Lidar module and the linear regression correction module. To measure the performance of the proposed model, an experimental environment consisting of a motor stage, an infrared thermography temperature screening system and a blackbody was established, and the error accuracy within 0.28℃ was shown as a result of temperature measurement according to a variable distance between 1m and 3.5 m.

• The Journal of Bigdata
• /
• v.7 no.1
• /
• pp.15-27
• /
• 2022

In the past five years, the fatality rate of single-vehicle accidents has been 4.7 times higher than that of all accidents, so it is necessary to establish a system that can detect and respond to single-vehicle accidents immediately. The IoT(Internet of Thing)-based real-time traffic accident recognition system proposed in this study is as following. By attaching an IoT sensor which detects the impact and vehicle ingress to the guardrail, when an impact occurs to the guardrail, the image of the accident site is analyzed through artificial intelligence technology and transmitted to a rescue organization to perform quick rescue operations to damage minimization. An IoT sensor module that recognizes vehicles entering the monitoring area and detects the impact of a guardrail and an AI-based object detection module based on vehicle image data learning were implemented. In addition, a monitoring and operation module that imanages sensor information and image data in integrate was also implemented. For the validation of the system, it was confirmed that the target values were all met by measuring the shock detection transmission speed, the object detection accuracy of vehicles and people, and the sensor failure detection accuracy. In the future, we plan to apply it to actual roads to verify the validity using real data and to commercialize it. This system will contribute to improving road safety.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.10
• /
• pp.461-470
• /
• 2023

While speech animation generation employing deep learning has been actively researched for English, there has been no prior work for Korean. Given the fact, this paper for the very first time employs supervised deep learning to generate Korean speech animation. By doing so, we find out the significant effect of deep learning being able to make speech animation research come down to speech recognition research which is the predominating technique. Also, we study the way to make best use of the effect for Korean speech animation generation. The effect can contribute to efficiently and efficaciously revitalizing the recently inactive Korean speech animation research, by clarifying the top priority research target. This paper performs this process: (i) it chooses blendshape animation technique, (ii) implements the deep-learning model in the master-servant pipeline of the automatic speech recognition (ASR) module and the facial action coding (FAC) module, (iii) makes Korean speech facial motion capture dataset, (iv) prepares two comparison deep learning models (one model adopts the English ASR module, the other model adopts the Korean ASR module, however both models adopt the same basic structure for their FAC modules), and (v) train the FAC modules of both models dependently on their ASR modules. The user study demonstrates that the model which adopts the Korean ASR module and dependently trains its FAC module (getting 4.2/5.0 points) generates decisively much more natural Korean speech animations than the model which adopts the English ASR module and dependently trains its FAC module (getting 2.7/5.0 points). The result confirms the aforementioned effect showing that the quality of the Korean speech animation comes down to the accuracy of Korean ASR.

• Journal of the Korea Computer Graphics Society
• /
• v.24 no.3
• /
• pp.33-41
• /
• 2018

We present a secondary camera optimization method that helps the user exploring 3D virtual environment to precisely observe possible collisions between objects. The first role of our secondary camera is to automatically detect the area with the greatest possible collision. The second role is to show the detected area from a new angle of view that the current main camera cannot show. However, as the shapes of target objects are complex, the shape of the empty space between objects is also complex and narrow. It means that the space for the secondary camera position is highly constrained and its optimization can be very difficult. To avoid this difficulty and increase the efficiency of the optimization, we first compute a bisector surface between two target objects. Then, we limit the domain of the secondary camera's position on the bisector surface in the optimization process. To verify the utility of our method, we built a demonstration program in which the user can explore in a 3D virtual world and interact with objects by using a hand motion recognition device and conducted a user study.

• Journal of Periodontal and Implant Science
• /
• v.47 no.5
• /
• pp.292-311
• /
• 2017

Purpose: Beyond the limited scope of non-specific polyclonal regulatory T cell (Treg)-based immunotherapy, which depends largely on serendipity, the present study explored a target Treg subset appropriate for the delivery of a novel epitope spreader Pep19 antigen as part of a sophisticated form of immunotherapy with defined antigen specificity that induces immune tolerance. Methods: Human polyclonal $CD4^+CD25^+CD127^{lo-}$ Tregs (127-Tregs) and $na\ddot{i}ve$ $CD4^+CD25^+CD45RA^+$ Tregs (45RA-Tregs) were isolated and were stimulated with target peptide 19 (Pep19)-pulsed dendritic cells in a tolerogenic milieu followed by ex vivo expansion. Low-dose interleukin-2 (IL-2) and rapamycin were added to selectively exclude the outgrowth of contaminating effector T cells (Teffs). The following parameters were investigated in the expanded antigen-specific Tregs: the distinct expression of the immunosuppressive Treg marker Foxp3, epigenetic stability (demethylation in the Treg-specific demethylated region), the suppression of Teffs, expression of the homing receptors CD62L/CCR7, and CD95L-mediated apoptosis. The expanded Tregs were adoptively transferred into an $NOD/scid/IL-2R{\gamma}^{-/-}$ mouse model of collagen-induced arthritis. Results: Epitope-spreader Pep19 targeting by 45RA-Tregs led to an outstanding in vitro suppressive T cell fate characterized by robust ex vivo expansion, the salient expression of Foxp3, high epigenetic stability, enhanced T cell suppression, modest expression of CD62L/CCR7, and higher resistance to CD95L-mediated apoptosis. After adoptive transfer, the distinct fate of these T cells demonstrated a potent in vivo immunotherapeutic capability, as indicated by the complete elimination of footpad swelling, prolonged survival, minimal histopathological changes, and preferential localization of $CD4^+CD25^+$ Tregs at the articular joints in a mechanistic and orchestrated way. Conclusions: We propose human $na\ddot{i}ve$ $CD4^+CD25^+CD45RA^+$ Tregs and the epitope spreader Pep19 as cellular and molecular targets for a novel antigen-specific Treg-based vaccination against collagen-induced arthritis.