• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.929-937
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• 2023

Human equivalent phantoms manufactured using 3D printers are cheaper and can be manufactured in a short time than conventional human phantoms. However, many phantoms are manufactured with less than 100 % of Infill Density, one of the 3D printer output setting variables. Therefore, this study compared the Bone Phantom CT number, which differs from the ratio of five Infill Density produced using a 3D printer, to the CT number of the actual human body Bone. In addition, the usefulness of the manufactured phantom was evaluated by producing a 100 % elbow joint phantom with Infill Density and setting the Infill Density to 100 % through CT number comparison for each tissue on computed tomography (CT). As a result, the Bone Phantom printed with 100 % Infill Density did not show the most statistically significant difference from the CT number value of the actual human Bone, and the CT number of each tissue did not show a statistically significant difference from the CT number value of each tissue of the actual human elbow joint.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.536-543
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• 2023

Speaker diarization, which labels for "who spoken when?" in speech with multiple speakers, has been studied on a deep neural network-based end-to-end method for labeling on speech overlap and optimization of speaker diarization models. Most deep neural network-based end-to-end speaker diarization systems perform multi-label classification problem that predicts the labels of all speakers spoken in each frame of speech. However, the performance of the multi-label-based model varies greatly depending on what the threshold is set to. In this paper, it is studied a speaker diarization system using single-label classification so that speaker diarization can be performed without thresholds. The proposed model estimate labels from the output of the model by converting speaker labels into a single label. To consider speaker label permutations in the training, the proposed model is used a combination of Permutation Invariant Training (PIT) loss and cross-entropy loss. In addition, how to add the residual connection structures to model is studied for effective learning of speaker diarization models with deep structures. The experiment used the Librispech database to generate and use simulated noise data for two speakers. When compared with the proposed method and baseline model using the Diarization Error Rate (DER) performance the proposed method can be labeling without threshold, and it has improved performance by about 20.7 %.

• Journal of Soil and Groundwater Environment
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• v.28 no.6
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• pp.71-89
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• 2023

A groundwater potential map (GPM) was built for the Nakdonggang River Basin based on ten variables, including hydrogeologic unit, fault-line density, depth to groundwater, distance to surface water, lineament density, slope, stream drainage density, soil drainage, land cover, and annual rainfall. To integrate the thematic layers for GPM, the criteria were first weighted using the Analytic Hierarchical Process (AHP) and then overlaid using the Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) model. Finally, the groundwater potential was categorized into five classes (very high (VH), high (H), moderate (M), low (L), very low (VL)) and verified by examining the specific capacity of individual wells on each class. The wells in the area categorized as VH showed the highest median specific capacity (5.2 m³/day/m), while the wells with specific capacity < 1.39 m³/day/m were distributed in the areas categorized as L or VL. The accuracy of GPM generated in the work looked acceptable, although the specific capacity data were not enough to verify GPM in the studied large watershed. To create GPMs for the determination of high-yield well locations, the resolution and reliability of thematic maps should be improved. Criterion values for groundwater potential should be established when machine learning or statistical models are used in the GPM evaluation process.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.4
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• pp.44-49
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• 2023

In the global pursuit of carbon neutrality, the rapid increase in the adoption of electric vehicles (EVs) has led to a corresponding surge in the demand for batteries. To achieve high efficiency in electric vehicles, considerations of weight reduction and battery safety have become crucial factors. Copper and aluminum, both recognized as lightweight materials, can be effectively joined through laser welding. However, due to the distinct physical characteristics of these two materials, the process of joining them poses technical challenges. This study focuses on conducting simulations to identify the optimal laser parameters for welding copper and aluminum, with the aim of streamlining the welding process. Additionally, a Graphic User Interface (GUI) program has been developed using the Python language to visually present the results. Using machine learning image data, this program is anticipated to predict joint success and serve as a guide for safe and efficient laser welding. It is expected to contribute to the safety and efficiency of the electric vehicle battery assembly process.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.755-770
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• 2023

Due to recent severe climate change, abnormal weather phenomena, and other factors, the frequency and magnitude of natural disasters are increasing. The need for disaster management using artificial satellites is growing, especially during large-scale disasters due to time and economic constraints. In this study, we have summarized the current status of next-generation medium-sized satellites and microsatellites in operation and under development, as well as trends in satellite imagery analysis techniques using a large volume of satellite imagery driven by the advancement of the space industry. Furthermore, by utilizing satellite imagery, particularly focusing on recent major disasters such as floods, landslides, droughts, and wildfires, we have confirmed how satellite imagery can be employed for damage analysis, thereby establishing its potential for disaster management. Through this study, we have presented satellite development and operational statuses, recent trends in satellite imagery analysis technology, and proposed disaster response strategies that utilize various types of satellite imagery. It was observed that during the stages of disaster progression, the utilization of satellite imagery is more prominent in the response and recovery stages than in the prevention and preparedness stages. In the future, with the availability of diverse imagery, we plan to research the fusion of cutting-edge technologies like artificial intelligence and deep learning, and their applicability for effective disaster management.

• Communications of Mathematical Education
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• v.37 no.3
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• pp.349-368
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• 2023

The revised 2022 educational curriculum highlighted the significance of mathematical literacy as a foundational competency that can be cultivated through the learning of various subjects, along with language proficiency and digital literacy. However, due to the lack of a precise definition for mathematical literacy, there exists a challenge in systematically implementing it across all subjects in the educational curriculum. The aim of this study is to clarify the definition of mathematical literacy in the curriculum through a literature review and to analyze the application patterns of mathematical literacy in other subjects so that mathematical literacy can be systematically applied as a basic literacy in Korea's curriculum. To achieve this, the study first clarifies and categorizes the meaning of mathematical literacy through a comparative analysis of terms such as numeracy and mathematical competence via a literature review. Subsequently, the study compares the categories of mathematical literacy identified in both domestic and international educational curricula and analyzes the application of mathematical literacy in the education curriculum of New South Wales (NSW), Australia, where mathematical literacy is reflected in the achievement standards across various subjects. It is expected that understanding each property by subdividing the meaning of mathematical literacy and examining the application modality to the curriculum will help construct a curriculum that reflects mathematical literacy in subjects other than mathematics.

• Journal of Digital Policy
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• v.2 no.4
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• pp.1-10
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• 2023

This study conducted preliminary study to identify effective ways to use ChatGPT in traffic policing by analyzing ChatGPT's responses to the driver's license test and the road traffic accident appraiser test. I collected ChatGPT responses for the driver's license test item pool and the road traffic accident appraiser test using the OpenAI API with Python code for 30 iterative experiments, and analyzed the percentage of correct answers by test, year, section, and consistency. First, the average correct answer rate for the driver's license test and the for road traffic accident appraisers test was 44.60% and 35.45%, respectively, which was lower than the pass criteria, and the correct answer rate after 2022 was lower than the average correct answer rate. Second, the percentage of correct answers by section ranged from 29.69% to 56.80%, showing a significant difference. Third, it consistently produced the same response more than 95% of the time when the answer was correct. To effectively utilize ChatGPT, it is necessary to have user expertise, evaluation data and analysis methods, design a quality traffic law corpus and periodic learning.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.9
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• pp.263-272
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• 2023

Industrial Internet of Things (IIoT) is an important factor in increasing production efficiency in industrial sectors, along with data collection, exchange and analysis through large-scale connectivity. However, as traffic increases explosively due to the recent spread of IIoT, an allocation method that can efficiently process traffic is required. In this thesis, I propose a two-stage task offloading decision method to increase successful task throughput in an IIoT environment. In addition, I consider a hybrid offloading system that can offload compute-intensive tasks to a mobile edge computing server via a cellular link or to a nearby IIoT device via a Device to Device (D2D) link. The first stage is to design an incentive mechanism to prevent devices participating in task offloading from acting selfishly and giving difficulties in improving task throughput. Among the mechanism design, McAfee's mechanism is used to control the selfish behavior of the devices that process the task and to increase the overall system throughput. After that, in stage 2, I propose a multi-armed bandit (MAB)-based task offloading decision method in a non-stationary environment by considering the irregular movement of the IIoT device. Experimental results show that the proposed method can obtain better performance in terms of overall system throughput, communication failure rate and regret compared to other existing methods.

• Journal of Korean Elementary Science Education
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• v.43 no.1
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• pp.136-147
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• 2024

It has recently be emphasized in science education that lessons that can develop "scientific participation and action" should be implemented to scientifically recognize various problems and respond to them as well as risks that occur in real life. This study aims to analyze the characteristics of scientific participation and action lessons as perceived by the preservice primary school teachers. To do that, the researchers collected and analyzed the lesson plans designed by the preservice teachers based on the achievement standard related to noise for grades 3-4 in 2022 revised science curriculum. Focusing on the stages of "problem recognition," "data collection and analysis," and "implementation and sharing," the results identity the four main characteristics as problem-solving activity, inquiry activity, investigative activity, and activity that encourages practical actions. The two or three features were found to be combinated in a lesson depending on its context. In some cases, only one feature was seen in a lesson. Based on the results, educational implications were discussed in terms of the teaching and learning methods and teacher education for implementing scientific participation and action.

• Journal of Korean Elementary Science Education
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• v.43 no.1
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• pp.170-184
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• 2024

This study focused on the practical research needed to improve elementary school science lesson plans. Specifically, a video clip-based pedagogical reasoning activity that included elementary student misconceptions was presented and the influences of this activity on preservice teachers' science lesson planning were assessed. First, the eight preservice teacher participants were asked to write a lesson plan for a dissolution and solution unit, after which a first semi-structured interview was conducted. Then, the participants participated in a video clip-based pedagogical reasoning activity. Based on the activity results, the participants revised their previously planned lessons, and second semi-structured interviews were conducted. The data from the preservice teachers' lesson plans and interview transcripts were analyzed using a constant comparative method to investigate the lesson plan changes. It was found that after the video clip-based pedagogical reasoning activity, the preservice teacher tightened the activity or changed the material to understand the students' thinking processes. In addition, they supplemented their goals and assessment criteria to accommodate the diverse students' thinking. Some also specified motivational strategies that considered student interests, motivation, and possible misconceptions. However, some preservice teachers still set goals that did not sufficiently account for student misconceptions and some planned the student assessments based only on the learning goals rather than the students' thinking. The few preservice teachers were able to develop motivational strategies that considered interest, motivation, and misconceptions. The preservice teachers claimed that they had difficulty predicting the misconceptions and connecting these to the lesson content. Discussions were then held to assist the preservice teachers to consider possible student misconceptions when planning their lessons.