• The Journal of Korean Academy of Prosthodontics
• /
• v.59 no.1
• /
• pp.146-152
• /
• 2021

Accurate transfer of the maxillo-mandibular relationship to an articulator (i.e., mounting) is critical in prosthetic treatment procedures. In the current study, a PubMed search was performed to review the influencing factors for the maxillo-mandibular relationship's accuracy. The search included digital mounting as well as conventional gypsum cast mounting. The results showed that a greater amount of displacement was introduced during positioning the maxillary and mandibular models to interocclusal records rather than the dimensional change of registration material. Most intraoral scanners resulted in an accurate reproduction of the maxillo-mandibular relationship for posterior quadrant scanning; however, the accuracy was declined as the scan area increased to a complete arch scan. The digital mounting accuracy was also influenced by the image processing algorithms and software versions, especially for complete arch scans.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.17 no.6
• /
• pp.1137-1144
• /
• 2022

In this study, an artificial intelligence(AI) was developed to help with facial expression practice in order to express emotions. The developed AI used multimodal inputs consisting of sentences and facial images for deep neural networks (DNNs). The DNNs calculated similarities between the emotions predicted by the sentences and the emotions predicted by facial images. The user practiced facial expressions based on the situation given by sentences, and the AI provided the user with numerical feedback based on the similarity between the emotion predicted by sentence and the emotion predicted by facial expression. ResNet34 structure was trained on FER2013 public data to predict emotions from facial images. To predict emotions in sentences, KoBERT model was trained in transfer learning manner using the conversational speech dataset for emotion classification opened to the public by AIHub. The DNN that predicts emotions from the facial images demonstrated 65% accuracy, which is comparable to human emotional classification ability. The DNN that predicts emotions from the sentences achieved 90% accuracy. The performance of the developed AI was evaluated through experiments with changing facial expressions in which an ordinary person was participated.

• Journal of Christian Education in Korea
• /
• v.68
• /
• pp.175-216
• /
• 2021

This essay aims to seek an alternative model of catechesis, as this form of education faces various challenges from the Korean Church especially during COVID-19 pandemic. For a long time, catechesis in the Korean Church narrowly focused on the act of producing Christians who would be loyal to the local church, rather than focusing on nurturing members loyal to Christ, an issue that has been problematized in recent publications on catechesis. Thus, the loss of social trust in the Korean Church and the decline of its public image exemplify how this type of catechesis as disciple-making for local church's benefit, mostly nurtures a vertical dimension of faith. The current teaching and learning method mostly employs a unilateral transfer of doctrine from the teacher to the learner and emphasizes the memorization of doctrine. This type of instruction renders the catechesis as the most lackluster and outdated form of Christian education. This essay aims to reconceptualize the traditional model of catechesis. This essay first critically evaluates current situations of catechesis and presents several alternative meanings on the concept of doctrine. Then it explores the theories of catechesis through different models posed by Christian educators such as John Westerhoff III and Richard Osmer. The final section is devoted to presenting an alternative form of catechesis that focuses on seeking holistic faith.

• Journal of the Society of Disaster Information
• /
• v.20 no.1
• /
• pp.199-205
• /
• 2024

Purpose: This study aims to improve the recognition rate of Auto People Counting (APC) in accurately identifying and providing information on remaining evacuees in disaster-vulnerable facilities such as nursing homes to firefighting and other response agencies in the event of a disaster. Methods: In this study, a baseline model was established using CNN (Convolutional Neural Network) models to improve the algorithm for recognizing images of incoming and outgoing individuals through cameras installed in actual disaster-vulnerable facilities operating APC systems. Various algorithms were analyzed, and the top seven candidates were selected. The research was conducted by utilizing transfer learning models to select the optimal algorithm with the best performance. Results: Experiment results confirmed the precision and recall of Densenet201 and Resnet152v2 models, which exhibited the best performance in terms of time and accuracy. It was observed that both models demonstrated 100% accuracy for all labels, with Densenet201 model showing superior performance. Conclusion: The optimal algorithm applicable to APC among various artificial intelligence algorithms was selected. Further research on algorithm analysis and learning is required to accurately identify the incoming and outgoing individuals in disaster-vulnerable facilities in various disaster situations such as emergencies in the future.

• Journal of Korean Biological Nursing Science
• /
• v.4 no.1
• /
• pp.25-39
• /
• 2002

The purpose of this study is to develop and evaluate a web-based instruction Program(WBI) to help nurses improving their knowledge and skill of cardiopulmonary resuscitation. Using the model of web-based instruction(WBI) program designed by Rhu(1999), this study was carried out during February-April 2002 in five different steps; analysis, design, data collection and reconstruction, programming and publishing, and evaluation. The results of the study were as follows; 1) The goal of this program was focused on improving accuracy of knowledge and skills of cardiopulmonary resuscitation. The program texts consists of the concepts and importances of cardiopulmonary resuscitation(CPR), basic life support(BLS), advanced cardiac life support(ACLS), treatment of CPR, nursing care after CPR treatment. And in the file making step, photographs, drawings and image files were collected and edited by web-editor(Namo), scanner and Adobe photoshop program. Then, the files were modified and posted on the web by file transfer protocol(FTP). Finally, the program was demonstrated and once again revised by the result, and then completed. 2) For the evaluation of the program, 36 nurses who in K university hospital located in D city, and related questionnaire were distributed to them as well. Higher scores were given by the nurses in its learning contents with $4.2{\pm}.67$, and in its structuring and interaction of the program with $4.0{\pm}.79$, and also in its satisfactory of the program with $4.2{\pm}.58$ respectively. In conclusion, if the contents of this WBI educational program upgrade further based upon analysis and applying of the results the program evaluation, it is considered as an effective tool to implement for continuing education as life-long educational system for nurse.

• International Commerce and Information Review
• /
• v.15 no.4
• /
• pp.481-508
• /
• 2013

The purpose of this study is to research the specific ways of successful localization by analyzing the success and failures case for localization through the theoretical background and the strategic models of localization. The strategic models of localization are divided by management aspects such as the localization of production and sourcing, the localization of human resources, the localization of marketing, the localization of R&D, harmonious relationship with the local community and authority transfer between headquarters and local subsidiaries. And the specific measures of the successful localization are proposed within the framework of the strategic models by comparing and analyzing the success and failures case for localization of individual companies operating in Indonesia. The results indicate that there are successful companies which develop a suitable products for the local climate and failed automobile company which is weak for assembly of complete vehicle in terms of localization of production and sourcing. In case of localization of human resources, most companies recognize the importance of this part and endeavor to secure superior human resource through a related education. It is found that most of the companies perform R & D in their native country. In part of a harmonious relationship with the local community, Korean companies should contribute to the community and be friendly with local residents and make a good image of the company focusing on the cultural environment. In aspect of authority transfer between headquarters and local subsidiaries, there is a tendency to be determined by the head office rather than the joint participation. In the future, in order for Korean enterprise to be successful one in Indonesia market, a highly interdependent and complex forms between headquarters and local subsidiaries shall be performed and an active exchange of information and the selection of best talent regardless of nationality shall be promoted.

• Journal of Intelligence and Information Systems
• /
• v.18 no.1
• /
• pp.109-123
• /
• 2012

Many kinds of the education systems are provided to students. Many kinds of the contents like School subjects, license, job training education and so on are provided through many kinds of the media like text, image, video and so on. Students will apply the knowledge they learnt and will use it when they learn other things. In the existing education system, there have been many situations that the education system isn't really helpful to the students because too hard contents are transferred to them or because too easy contents are transferred to them and they learn the contents they already know again. To solve this phenomenon, a method that transfers the most proper lecture contents to the students is suggested in the thesis. Because the difficulty is relative, the contents A can be easier than the contents B to a group of the students and the contents B can be easier than the contents A to another group of the students. Therefore, it is not easy to measure the difficulty of the lecture contents. A method considering this phenomenon to transfer the proper lecture contents is suggested in the thesis. The whole lecture contents are divided into many lecture modules. The students solve the pattern recognition questions, a kind of the prior test questions, before studying the lecture contents and the system selects and provides the most proper lecture module among many lecture modules to the students according to the score about the questions. When the system selects the lecture module and transfer it to the student, the students' answer and the difficulty of the lecture modules are considered. In the existing education system, 1 kind of the content is transferred to various students. If the same lecture contents is transferred to various students, the contents will not be transferred efficiently. The system selects the proper contents using the students' pattern recognition answers. The pattern recognition question is a kind of the prior test question that is developed on the basis of the lecture module and used to recognize whether the student knows the contents of the lecture module. Because the difficulty of the lecture module reflects the all scores of the students' answers, whenever a student submits the answer, the difficulty is changed. The suggested system measures the relative knowledge of the students using the answers and designates the difficulty. The improvement of the suggested method is only applied when the order of the lecture contents has nothing to do with the progress of the lecture. If the contents of the unit 1 should be studied before studying the contents of the unit 2, the suggested method is not applied. The suggested method is introduced on the basis of the subject "English grammar", subjects that the order is not important, in the thesis. If the suggested method is applied properly to the education environment, the students who don't know enough basic knowledge will learn the basic contents well and prepare the basis to learn the harder lecture contents. The students who already know the lecture contents will not study those again and save more time to learn more various lecture contents. Many improvement effects like these and so on will be provided to the education environment. If the suggested method that is introduced on the basis of the subject "English grammar" is applied to the various education systems like primary education, secondary education, job education and so on, more improvement effects will be provided. The direction to realize these things is suggested in the thesis. The suggested method is realized with the MySQL database and Java, JSP program. It will be very good if the suggested method is researched developmentally and become helpful to the development of the Korea education.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.14 no.2
• /
• pp.166-171
• /
• 2010

Purpose: The SPECT/CT is able to acquire diagnostic information resolved the difficult problems that discriminate regions of focals by intergrating functional images and anatomical images. We introduce the usefulness of "Volumetrix Suite" which can describe 3D images by the convergence of the SPECT/CT images and reference CT images. Materials and Methods: We applied Volumetrix Suite program (Volumetrix IR, Volumetrix 3D) to patients, Bone, Venography, Parathyroid, WBC, taken diagnostic CT examination which have same regions of focal in Seoul Metropolitan Government Seoul National University Boramae Medical Center. After acquiring SPECT/CT images and reference CT images, we fused a couple of scans applying for this programs. The CT scan of Infinia Hawkeye 4 shows limitation of anatomical information. For this reason, we tried to transfer CT images that have lots of diagnostic informations as the form of Dicom file in PACS, and changed from 2D images to 3D images after image registering in Xeleris Workstaion of Hawkeye 4. Results & Conclusion: By using Volumetrix Suite program, we're able to acquire more accurate anatomical informations with 3D rendering which can distinguish both location and range of focals in Infinia Hawkeye 4. Thus, the result of utilizing this program indicate that nuclear medicine anatomical images can be improved by providing more diagnostic imformations produced by its program.

• Korean Journal of Heritage: History & Science
• /
• v.57 no.3
• /
• pp.24-35
• /
• 2024

Recently, research using deep learning technologies such as artificial intelligence, convolutional neural networks, etc. has been actively conducted in various fields including healthcare, manufacturing, autonomous driving, and security, and is having a significant influence on society. In line with this trend, the present study attempted to apply deep learning to the classification of archaeological artifacts, specifically ancient Korean roof-end tiles. Using 100 images of roof-end tiles from each of the Goguryeo, Baekje, and Silla dynasties, for a total of 300 base images, a dataset was formed and expanded to 1,200 images using data augmentation techniques. After building a model using transfer learning from the pre-trained EfficientNetB0 model and conducting five-fold cross-validation, an average training accuracy of 98.06% and validation accuracy of 97.08% were achieved. Furthermore, when model performance was evaluated with a test dataset of 240 images, it could classify the roof-end tile images from the three dynasties with a minimum accuracy of 91%. In particular, with a learning rate of 0.0001, the model exhibited the highest performance, with accuracy of 92.92%, precision of 92.96%, recall of 92.92%, and F1 score of 92.93%. This optimal result was obtained by preventing overfitting and underfitting issues using various learning rate settings and finding the optimal hyperparameters. The study's findings confirm the potential for applying deep learning technologies to the classification of Korean archaeological materials, which is significant. Additionally, it was confirmed that the existing ImageNet dataset and parameters could be positively applied to the analysis of archaeological data. This approach could lead to the creation of various models for future archaeological database accumulation, the use of artifacts in museums, and classification and organization of artifacts.

• Journal of Bio-Environment Control
• /
• v.32 no.4
• /
• pp.434-441
• /
• 2023

Determining the size or area of a plant's leaves is an important factor in predicting plant growth and improving the productivity of indoor farms. In this study, we developed a convolutional neural network (CNN)-based model to accurately predict the length and width of lettuce leaves using photographs of the leaves. A callback function was applied to overcome data limitations and overfitting problems, and K-fold cross-validation was used to improve the generalization ability of the model. In addition, ImageDataGenerator function was used to increase the diversity of training data through data augmentation. To compare model performance, we evaluated pre-trained models such as VGG16, Resnet152, and NASNetMobile. As a result, NASNetMobile showed the highest performance, especially in width prediction, with an R_squared value of 0.9436, and RMSE of 0.5659. In length prediction, the R_squared value was 0.9537, and RMSE of 0.8713. The optimized model adopted the NASNetMobile architecture, the RMSprop optimization tool, the MSE loss functions, and the ELU activation functions. The training time of the model averaged 73 minutes per Epoch, and it took the model an average of 0.29 seconds to process a single lettuce leaf photo. In this study, we developed a CNN-based model to predict the leaf length and leaf width of plants in indoor farms, which is expected to enable rapid and accurate assessment of plant growth status by simply taking images. It is also expected to contribute to increasing the productivity and resource efficiency of farms by taking appropriate agricultural measures such as adjusting nutrient solution in real time.