• Journal of The Korean Association For Science Education
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• v.40 no.6
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• pp.611-620
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• 2020

The purpose of the study is to find creativity factors of students in the process of small group modeling and relate them to the types of interactions among students. In order to capture students' detailed interactions, this study was conducted as an 'essential case study' through qualitative analysis. We have developed the modules of nine lessons about terraforming, and they were used in an actual classroom. In order to understand the creativity of the students in the process of modeling, students' discourses and interview data were analyzed using 19 creative factors or abilities. The findings are as follows. Frequently found creativity factors are Elaboration, Evaluation, Visualization, Resist premature closer, Originality, Analysis and Concentration. And students' interactions that affect students' creativity in the process of modeling can be classified into four categories: Suggestion, Agreement, Questioning, Refutation, and Conversion. Through each interaction, students demonstrated the process of expressing and modifying their own thoughts and ideas in the modeling process. The findings of the study suggest that it is important to the teachers to understand types of interactions among students and the relationship between the types of interaction and creativity factors for students' creative modeling in modeling-based learning.

• The Journal of the Acoustical Society of Korea
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• v.41 no.5
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• pp.507-517
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• 2022

The PhotoAcoustic Microscopy (PAM) has been proved to be a useful tool for biological and medical applications due to its high spatial and contrast resolution. PAM is based on transmission of laser pulses and reception of PA signals. Since the strength of PA signals is generally low, not only are high-performance optical and acoustic modules required, but high-performance electronics for imaging are also particularly needed for high-quality PAM imaging. Most PAM systems are implemented with a combination of several pieces of equipment commercially available to receive, amplify, enhance, and digitize PA signals. To this end, PAM systems are inevitably bulky and not optimal because general purpose equipment is used. This paper reports a PA signal receiving system recently developed to attain the capability of improved Signal to Noise Ratio (SNR) and Contrast to Noise Ratio (CNR) of PAM images; the main module of this system is a low noise, wideband signal receiver that consists of two low-noise amplifiers, two variable gain amplifiers, analog filters, an Analog to Digital Converter (ADC), and control logic. From phantom imaging experiments, it was found that the developed system can improve SNR by 6.7 dB and CNR by 3 dB, compared to a combination of several pieces of commercially available equipment.

• Journal of the Korean Society of Radiology
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• v.16 no.1
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• pp.25-34
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• 2022

Brain computed tomography (CT) is useful for brain lesion diagnosis, such as brain hemorrhage, due to non-invasive methodology, 3-dimensional image provision, low radiation dose. However, there has been numerous misdiagnosis owing to a lack of radiologist and heavy workload. Recently, object detection technologies based on artificial intelligence have been developed in order to overcome the limitations of traditional diagnosis. In this study, the applicability of a deep learning-based YOLOv5s model was evaluated for brain hemorrhage detection using brain CT images. Also, the effect of hyperparameters in the trained YOLOv5s model was analyzed. The YOLOv5s model consisted of backbone, neck and output modules. The trained model was able to detect a region of brain hemorrhage and provide the information of the region. The YOLOv5s model was trained with various activation functions, optimizer functions, loss functions and epochs, and the performance of the trained model was evaluated in terms of brain hemorrhage detection accuracy and training time. The results showed that the trained YOLOv5s model is able to provide a bounding box for a region of brain hemorrhage and the accuracy of the corresponding box. The performance of the YOLOv5s model was improved by using the mish activation function, the stochastic gradient descent (SGD) optimizer function and the completed intersection over union (CIoU) loss function. Also, the accuracy and training time of the YOLOv5s model increased with the number of epochs. Therefore, the YOLOv5s model is suitable for brain hemorrhage detection using brain CT images, and the performance of the model can be maximized by using appropriate hyperparameters.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2003.09a
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• pp.44-44
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• 2003

As a basic measurement tool in the areas of animal models of human disease, gene expression and therapy, and drug discovery and development, small animal PET imaging is being used increasingly. An ideal small animal PET should have high sensitivity and high and uniform resolution across the field of view to achieve high image quality. However, the combination of long narrow pixellated crystal array and small ring diameter of small animal PET leads to the degradation of spatial resolution for the source located at off center. This degradation of resolution can be improved by determining the depth of interaction (DOI) in the crystal and by taking into account the information in sorting the coincident events. Among a number of 001 identification schemes, dual layer phsowich detector has been widely investigated by many research groups due to its practicability and effectiveness on extracting DOI information. However, the effects of each crystal length composing dual layer phoswich detector on DOI measurements and image qualities were not fully characterized. In order to minimize the DOI effect, the length of each layer of phoswich detector should be optimized. The aim of this study was to perform simulations using a simulation tool, GATE to design the optimum lengths of crystals composing a dual layer phoswich detector. The simulated small PET system employed LSO front layer LuYAP back layer phoswich detector modules and the module consisted of 8${\times}$8 arrays of dual layer crystals with 2 mm ${\times}$ 2 mm sensitive area coupled to a Hamamatsu R7600 00 M64 PSPMT. Sensitivities and variation of radial resolutions were simulated by varying the length of LSO front layer from 0 to 10 mm while the total length (LSO + LuYAP) was fixed to 20 mm for 10 cm diameter ring scanner. The radial resolution uniformity was markedly improved by using DOI information. There existed the optimal lengths of crystal layers to minimize the variation of radial resolutions. In 10 cm ring scanner configuration, the radial resolution was kept below 3.4 mm over 8 cm FOV while the sensitivity was higher than 7.4% for LSO 5 mm : LuYAP 15 mm phoswich detector. In this study, the optimal length of dual layer phoswich detector was derived to achieve high and uniform radial resolution.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.29 no.1
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• pp.27-33
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• 2023

An optimized design of the transportation insulated box must be considered to control the thermal damage in order to maintain the fresh condition for temperature-sensitive medicine and frozen food safety. The inside temperature of the insulated box is a natural convection enclosure state, thermal stratification naturally occurs as time passes in case of with outside heat load. The latent heat material (LHM) placement inside the box maintains the target temperature of the product for temperature fluctuations during transport, and LHM application is a common and efficient method. In this work, inside temperature stratification in an insulated box depending on the LHM pack position is numerically simulated and experimented. The insulated box is made up of vacuum insulation panel (VIP), and LHM modules are placed over six faces inside the box, with the same weight. The temperature curves for 72 hrs as experiment results clearly show the temperature stratification in the upper, middle, and lower at the LHM melting time region. However, the temperature stratification state is uniformly changed in accordance with the condition of the upper and lower placement weight of the LHM pack. And also, the temperature uniformity by changed placement weight of LHM has an effect on maintaining time for target air temperature inside the box. These results provide information on the optimized design of the insulated box with LHM.

• Journal of Radiation Industry
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• v.17 no.1
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• pp.19-32
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• 2023

The amount of radioactive waste is expected to dramatically increase with decommissioning of nuclear power plants such as Kori-1, the first nuclear power plant in South Korea. Accurate nuclide analysis is necessary to manage the radioactive wastes safely, but research on verification of radionuclide analysis has yet to be well established. This study aimed to develop the technology that can verify the results of radionuclide analysis based on artificial intelligence. In this study, we propose an anomaly detection algorithm for inspecting the analysis error of radionuclide. We used the data from 'Updated Scaling Factors in Low-Level Radwaste' (NP-5077) published by EPRI (Electric Power Research Institute), and resampling was performed using SMOTE (Synthetic Minority Oversampling Technique) algorithm to augment data. 149,676 augmented data with SMOTE algorithm was used to train the artificial neural networks (classification and anomaly detection networks). 324 NP-5077 report data verified the performance of networks. The anomaly detection algorithm of radionuclide analysis was divided into two modules that detect a case where radioactive waste was incorrectly classified or discriminate an abnormal data such as loss of data or incorrectly written data. The classification network was constructed using the fully connected layer, and the anomaly detection network was composed of the encoder and decoder. The latter was operated by loading the latent vector from the end layer of the classification network. This study conducted exploratory data analysis (i.e., statistics, histogram, correlation, covariance, PCA, k-mean clustering, DBSCAN). As a result of analyzing the data, it is complicated to distinguish the type of radioactive waste because data distribution overlapped each other. In spite of these complexities, our algorithm based on deep learning can distinguish abnormal data from normal data. Radionuclide analysis was verified using our anomaly detection algorithm, and meaningful results were obtained.

• Journal of Bio-Environment Control
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• v.15 no.4
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• pp.306-316
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• 2006

In this study, the effect of the shade level, water flow rate applied to the shades and the temperature of water on the greenhouse cooling was investigated depending on the shade level of 0, 35, 55, 75%, and water flow rate and water temperature by the test on the small wooden frames to find out the low cost cooling method. With increasing of the dry bulb temperature of outside air, the dry bulb temperature in the wooden frames increased. For the frames with the shade and water, inside temperatures of the frames were lower of -0.2$\sim$-1.2$^{\circ}C$ than the temperature of the outside air and higher than the water temperature. For the frames without water, inside temperatures of the frames were higher of 1.7$\sim$4$^{\circ}C$ than the outside and not affected by the shade level very much. The water flow rate and the temperature of the water were not the important factors to decrease the inside temperatures in the frames. The black globe temperature became lower with increasing of shade level. The shade frames with water curtain showed the best cooling effect because of reducing thermal radiation and cooling the plastic film cover. The surface temperatures of the plastic film cover for the water supplied modules became lower with increasing of the shade level. The relative humidity was decreased with the dry bulb temperature in the frame increasing and not affected by the dry bulb temperature of the outside air for the frames with the shade and water.

• Journal of The Korean Association For Science Education
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• v.33 no.2
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• pp.425-443
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• 2013

We developed problem-solving type inquiry learning programs reflecting scientists' research process and analyzed the activities of science-gifted high school students, and the understanding and the effects of the programs after implementation in class. For this study, twelve science-gifted students in the 10th grade participated in the program, which consisted of three different modules - making a cycloidal pendulum, surface growth, and synchronization using metronomes. Diet Cola Test (DCT) was used to find out the effect on the improvement of the ability to design experiments by comparing pre/post scores, with a survey and an interview being conducted after the class. Each module consisted of a series of processes such as questioning the phenomenon scientifically, designing experiments to find solutions, and doing activities to solve the problems. These enable students to experience problem-solving type research process through the program class. According to this analysis, most students were likely to understand the characteristics of problem-solving type inquiry learning programs reflecting the scientists' research process. According to the students, there are some differences between this program class and existing school class. The differences are: 'explaining phenomenon scientifically,' 'designing experiments for themselves,' and 'repeating the experiments several times.' During the class students have to think continuously, design several experiments, and carry them out to solve the problems they found at first. Then finally, they were able to solve the problems. While repeating this kind of activities they have been able to experience the scientists' research process. Also, they showed a positive attitude toward the scientists' research by understanding problem-solving type research process. These problem-solving type inquiry learning programs seem to have positive effects on students in designing experiments and offering the opportunity for critical argumentation on the causes of the phenomena. The results of comparing pre/post scores for DCT revealed that almost every student has improved his/her ability to design experiments. Students who were accustomed to following teacher's instructions have had difficulty in designing the experiments for themselves at the beginning of the class, but gradually, they become used to doing it through the class and finally were able to do it systematically.

• The korean journal of orthodontics
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• v.37 no.1 s.120
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• pp.5-15
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• 2007

Objective: The purpose of this study was to evaluate the mechanical performance of mini-screws during insertion into artificial bone with use of the driving torque tester (Biomaterials Korea, Seoul, Korea), as well as testing of Pull-out Strength (POS). Methods: Experimental bone blocks with different cortical bone thickness were used as specimens. Three modules of commercially available drill-free type mini-screws (Type A; pure cylindrical type, Biomaterials Korea, Seoul, Korea, Type B; partially cylindrical type, Jeil Medical, Seoul, Korea, Type C; combination type of cylindrical and tapered portions, Ortholution, Seoul, Korea), were used. Results: Difference in the cortical bone thickness had little effect on the maximum insertion torque (MIT) in Type A mini-screws. But in Type B and C, MIT increased as the cortical bone thickness Increased. MIT of Type C was highest in all situations, then Type B and Type A in order. Type C showed lower POS than Type A or B in all situations. There were statistically significant correlations between cortical bone thickness and MIT, and POS for each type of the mini-screws. Conclusion: Since different screw designs showed different insertion torques with increases in cortical bone thickness, the best suitable screw design should be selected according to the different cortical thicknesses at the implant sites.

• Journal of the Korea Society of Computer and Information
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• v.20 no.3
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• pp.115-124
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• 2015

In this paper we analyse the previous (Quality of Services) and QoE(Quality of Experience) methods, and propose a high reliable network system framework and its service forwarding method that is able to provide seamless N-Screen services for proliferating disaster informations. The service satisfaction measurement, i.e., QoE, of contents consumers in N-screens services is going to be important the factor in disaster information proliferation because N-Screen services in the previous methods based on multi devices only focused on information transmission. The proposed system around these services is composed of a disaster information process framework for accepting user's service requirement, push service modules for minimizing the number of packets to be caused when carrying out the push service, and a push service controller for maximizing QoE measures. In order to provide a seamless N-Screen service on diverse screens, such as smartphone, PC, and big screen, we also have Open API(Application Programming Interface) functions. Through these results, we expect to evaluate QoS and QoE quality in the seamless N-Screen service.