• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.57-64
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• 2023

The ROK military faces a significant challenge in its vigilance mission due to demographic problems, particularly the current aging population and population cliff. This study demonstrates the crucial role of the 4th industrial revolution and its core artificial intelligence algorithm in maximizing work efficiency within the Command&Control room by mechanizing simple tasks. To achieve a fully developed military surveillance system, we have chosen multi-object tracking (MOT) technology as an essential artificial intelligence component, aligning with our goal of an intelligent and automated surveillance system. Additionally, we have prioritized data visualization and user interface to ensure system accessibility and efficiency. These complementary elements come together to form a cohesive software application. The CCTV video data for this study was collected from the CCTV cameras installed at the 1st and 2nd main gates of the 00 unit, with the cooperation by Command&Control room. Experimental results indicate that an intelligent and automated surveillance system enables the delivery of more information to the operators in the room. However, it is important to acknowledge the limitations of the developed software system in this study. By highlighting these limitations, we can present the future direction for the development of military surveillance systems.

• Journal of Korean Elementary Science Education
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• v.42 no.3
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• pp.399-408
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• 2023

This study developed and applied a maker education program for an elementary school's science unit on 'Animal Life'. It examined the program's impact on students' academic achievement and creative problem-solving ability. The theme of the maker education program was 'creating a robot virtual reality (VR) exhibition hall mimicking animal characteristics'. It explored scientific concepts and creatively created a robot VR exhibition hall in accordance with the TMI maker education model. Findings revealed that the program significantly improved students' academic achievement and creative problem-solving ability (p<.05). This study provides evidence for the effectiveness of maker education in elementary school science classes and suggests that using maker education can increase students' interest in and engagement with science learning. To implement maker education more actively in elementary school science classes, stakeholders should develop various topics and programs. Additional research investigating the effectiveness of maker education in different age groups and various other areas of elementary science education is required to generalize the results of this study. Moreover, educational and teacher capacity building is required for educators to utilize maker education effectively.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.177-188
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• 2023

The purpose of this study is to develop and validate a scale for measuring digital literacy by identifying the factors consisting of digital literacy and extracting items for each factor. Preliminary items for the Delphi study were developed through the analysis of previous literature and the deliberation of the research team. As a result of two rounds of the expert Delphi study, 65 items were selected for the main survey. The validation of the items was carried out in the process of exploratory and confirmatory factor analyses, reliability test, and criterion validity test using the data collected in the main survey. As a result, a 4-factor structure composed of 31 questions(factor 1: digital technology & data literacy- 9 questions, factor 2: digital content & media literacy- 8 questions, factor 3: digital communication & community literacy- 9 questions, factor 4: digital wellness literacy - 5 questions) was confirmed. Also, the goodness of fit indices of the model were found to be good and the result of reliability test revealed the scale had a very appropriate level of Cronbach's alpha(α=.956). In addition, a statistically significantly positive correlations(p<.001) were found between digital literacy and internet self-efficacy and between digital literacy and self-directed learning ability, which were predicted in the existing evidence, therefore the criterion validity of the developed scale was secured. Finally, practical and academic implications of the study are provided and future study and limitations of the study are discussed.

• Nutrition Research and Practice
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• v.17 no.2
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• pp.371-385
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• 2023

BACKGROUND/OBJECTIVES: Soy isoflavone (SIF) and soy lecithin (SL) have beneficial effects on many chronic diseases, including neurodegenerative diseases. Regretfully, there is little evidence to show the combined effects of these soy extractives on the impairment of cognition and abnormal cerebral blood flow (CBF). This study examined the optimal combination dose of SIF + SL to provide evidence for improving CBF and protecting cerebrovascular endothelial cells. MATERIALS/METHODS: In vivo study, SIF50 + SL40, SIF50 + SL80 and SIF50 + SL160 groups were obtained. Morris water maze, laser speckle contrast imaging (LSCI), and hematoxylin-eosin staining were used to detect learning and memory impairment, CBF, and damage to the cerebrovascular tissue in rat. The 8-hydroxy-2'-deoxyguanosine (8-OHdG) and the oxidized glutathione (GSSG) were detected. The anti-oxidative damage index of superoxide dismutase (SOD) and glutathione (GSH) in the serum of an animal model was also tested. In vitro study, an immortalized mouse brain endothelial cell line (bEND.3 cells) was used to confirm the cerebrovascular endothelial cell protection of SIF + SL. In this study, 50 µM of Gen were used, while the 25, 50, or 100 µM of SL for different incubation times were selected first. The intracellular levels of 8-OHdG, SOD, GSH, and GSSG were also detected in the cells. RESULTS: In vivo study, SIF + SL could increase the target crossing times significantly and shorten the total swimming distance of rats. The CBF in the rats of the SIF50 + SL40 group and SIF50 + SL160 group was enhanced. Pathological changes, such as attenuation of the endothelium in cerebral vessels were much less in the SIF50 + SL40 group and SIF50 + SL160 group. The 8-OHdG was reduced in the SIF50 + SL40 group. The GSSG showed a significant decrease in all SIF + SL pretreatment groups, but the GSH showed an opposite result. SOD was upregulated by SIF + SL pretreatment. Different combinations of Genistein (Gen)+SL, the secondary proof of health benefits found in vivo study, showed they have effective anti-oxidation and less side reaction on protecting cerebrovascular endothelial cell. SIF50 + SL40 in rats experiment and Gen50 + SL25 in cell test were the optimum joint doses on alleviating cognitive impairment and regulating CBF through protecting cerebrovascular tissue by its antioxidant activity. CONCLUSIONS: SIF+SL could significantly prevent cognitive defect induced by β-Amyloid through regulating CBF. This kind of effect might be attributed to its antioxidant activity on protecting cerebral vessels.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1177-1185
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• 2022

The water and sewage system is an infrastructure that provides safe and clean water to people. In particular, since the water and sewage pipelines are buried underground, it is very difficult to detect system defects. For this reason, the diagnosis of pipelines is limited to post-defect detection, such as system diagnosis based on the images taken after taking pictures and videos with cameras and drones inside the pipelines. Therefore, real-time detection technology of pipelines is required. Recently, pipeline diagnosis technology using advanced equipment and artificial intelligence techniques is being developed, but AI-based defect detection technology requires a variety of learning data because the types and numbers of defect data affect the detection performance. Therefore, in this study, various defect scenarios are implemented using 3D printing model to improve the detection performance when detecting defects in pipelines. Afterwards, the collected images are performed to pre-processing such as classification according to the degree of risk and labeling of objects, and real-time defect detection is performed. The proposed technique can provide real-time feedback in the pipeline defect detection process, and it would be minimizing the possibility of missing diagnoses and improve the existing water and sewerage pipe diagnosis processing capability.

• Journal of Korean Elementary Science Education
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• v.42 no.1
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• pp.149-160
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• 2023

A Korean-version science curiosity questionnaire (Science Curiosity in Learning Environments [SCILE(15)]) was developed after factor analysis of the Korean-version SCILE(30) questionnaire. Pre-service elementary school teachers were surveyed using the Korean-version SCILE(30), and a factor analysis based on their responses was performed. The factor analysis demonstrated that the Korean-version SCILE(15) consisted of three curiosity factors: a 'science practices' factor, a 'stretching' factor, and an 'embracing' factor. Confirmatory factor analysis of the factor structure revealed correlations between all the factors, thus confirming their commonality as a science curiosity factors. The Cronbach alpha for the reliability of all items in the Korean-version SCILE(15) and of items by factor was greater than 0.700. The Korean-version SCILE(15) was therefore evaluated to be reliable as a science curiosity questionnaire. Pre-service elementary teachers who participated in the survey for the development of the SCILE(15) were aware of the 'science practices', 'stretching', and 'embracing' science curiosity factors. Analysis in a general linear model of the degree of recognition accorded by pre-service elementary teachers to the three science curiosity factors demonstrated significant differences between the curiosity factors in terms of recognition. This cohort of pre-service elementary teachers showed the highest level of recognition of the 'stretching' curiosity factor and the lowest level of recognition of the 'embracing' curiosity factor.

• Journal of the Korea Society of Computer and Information
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• v.14 no.9
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• pp.11-19
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• 2009

A RAM-based Neural Net(RBNN) which has multi-discriminators is more effective than RBNN with a discriminator. Experience Sensitive Cumulative Neural Network and 3-D Neuro System(3DNS) that accumulate the features point improved the performance of BNN, which were enabled to train additional and repeated patterns and extract a generalized pattern. In recognition process of Neural Net with multi-discriminator, the selection of class was decided by the value of MRD which calculates the accumulated sum of each class. But they had a saturation problem of its memory cells caused by learning volume increment. Therefore, the decision of MRD has a low performance because recognition rate is decreased by saturation. In this paper, we propose the method which improve the MRD ability. The method consists of the optimum MRD and the matching ratio prototype to generalized image, the cumulative filter ratio, the gap of prototype response MRD. We experimented the performance using NIST database of NIST without preprocessor, and compared this model with 3DNS. The proposed MRD method has more performance of recognition rate and more stable system for distortion of input pattern than 3DNS.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.1
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• pp.371-401
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• 2022

If the blockchain means storing information in a distributed environment that cannot be forged or altered, it is mentioned that this is similar to what librarians collect, preserve, and share authoritative information. In this way, this study examined blockchain technology as a way to collect and provide reliable information, increase work efficiency inside and outside the library, and strengthen cooperative networks. This study attempted to propose various ways to utilize blockchain technology in book relations based on literature surveys and case studies in other fields. To this end, this study first analyzed the field and cases of blockchain application to confirm the possibility and value of blockchain application in the library field, and proposed 12 ways to utilize it based on this. The utilization model was proposed by dividing it into operation and service sectors. In the operation sector, it is a digital identity-based user record storage and authentication function, transparent management and traceable monitoring function, voting-based personnel and recruitment system, blockchain governance-based network efficiency function, and blockchain-based next-generation device management and information integration function. The service sector includes improved book purchase and sharing efficiency due to simplification of intermediaries, digital content copyright protection and management functions, customized service provision based on customer behavior analysis, blockchain-based online learning platforms, sharing platforms, and P2P-based reliable information sharing platforms.

• Research in Community and Public Health Nursing
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• v.33 no.1
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• pp.13-31
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• 2022

Purpose: This study conducted a job analysis of visiting nurses in the process of change. Methods: Participants were the visiting nurses working for the Seoul Metropolitan city. On the basis of the Public Health Intervention Wheel model, two times of the focus group interview (FGI) with seven visiting nurses and one time of the Developing a Curriculum (DACUM) with 34 visiting nurses were performed. A questionnaire survey of 380 visiting nurses was conducted to examine the frequency, importance and difficulty levels of the tasks created by using the FGI and DACUM. Results: Visiting nurses' job was derived as the theme of present versus transitional roles. The present role was categorized as 'providing individual- and group-focused services' and 'conducting organization management', while the transitional role was categorized as 'providing district-focused services' and 'responding to new health issues'. The job generated 13 duties, 28 tasks, and 73task elements. The tasks showed the levels of frequency (3.65 scores), importance (4.27 scores), and difficulty (3.81 scores). All the tasks were determined as important, exceeding the average 4.00 scores. The group- and district-focused services of the tasks were recognized as more difficult but less frequent tasks. Conclusion: The visiting nurses exert both present and transitional roles. The transitional roles identified in the present study should be recognized as an extended role of visiting nurses in accordance with the current changing healthcare needs in South Korea. Finally, the educational curriculum for visiting nurses that reflects the transitional roles from the present study is needed.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.448-448
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• 2021

최근 급격한 기후변화와 도시화 및 산업화로 인한 지류하천에서의 수량과 수질의 변동은 생물 다양성 감소와 수생태계 건강성 저하에 큰 영향을 미치고 있다. 효율적인 수생태 관리를 위해서는 지속적인 유량, 수질, 그리고 수생태 모니터링을 통한 데이터 축적과 더불어 면밀한 상관 분석을 통해 수생태계 건강성의 악화 원인을 규명해야 할 필요가 있다. 그러나 수많은 지류하천을 대상으로 한 지속적인 모니터링은 현실적으로 어려움이 있으며, 수생태계의 특성 상 단일 영향 인자만으로 수생태계의 건강성 변화와의 관계를 정확히 파악하는데 한계가 있다. 따라서 지류하천에서의 유량 및 수질의 시공간적인 변동성과 다양한 영향 인자를 고려하여 수생태계의 건강성을 효율적으로 예측할 수 있는 기술이 필요하다. 이에 본 연구에서는 경험적 데이터 기반의 머신러닝 모델 구축을 통해 미계측 하천에서의 수생태계 건강성 지수(BMI, TDI, FAI)의 등급(A to E)을 예측하고자 하였다. 머신러닝 모델은 학습 데이터셋의 양과 질에 따라 성능이 크게 달라질 수 있으며, 학습 데이터셋의 분포가 불균형적일 경우 과적합 또는 과소적합 문제가 발생할 수 있다. 이를 보완하고자 본 연구에서는 실제 측정망 데이터셋을 바탕으로 생성적 적대 신경망 GAN(Generative Adversarial Network) 알고리즘을 통해 머신러닝 모델 학습에 필요한 추가 데이터셋(유량, 수질, 기상, 수생태 등급)을 확보하였다. 머신러닝 모델의 성능은 5차 교차검증 과정을 통해 평가하였으며, GAN 데이터셋의 정확도는 실제 측정망 데이터셋의 정규분포와의 비교 분석을 통해 평가하였다. 최종적으로 SWAT(Soil and Water Assessment Tool) 모형을 통해 예측 된 미계측 하천에서의 데이터셋을 머신러닝 모델의 검증 자료로 사용하여 수생태계 건강성 등급 예측 정확도를 평가하였다. 본 연구에서의 GAN에 의해 강화된 머신러닝 모델은 수질 및 수생태 관리가 필요한 우심 지류하천 선정과 구조적/비구조적 최적관리기법에 따른 수생태계 건강성 개선 효과를 평가하는데 활용될 수 있을 것이다. 또한 이를 통해 예측된 미계측 하천에서의 수생태계 건강성 등급 자료는 수량-수질-수생태를 유기적으로 연계한 통합 물관리 정책을 수립하는데 기초자료로 활용될 수 있을 것이라 사료된다.