Earticle

Renewable energies use clean sources for energy generation and have the potential to balance the supply and demand of power. One of the best ways to save energy for high-demand time is to preserve it in a battery energy storage system (BESS). Various methods are presented in the last two decades for battery state of charge (SOC) estimation, however, most of them are focused only on a single battery pack and use data without accurate preprocessing and feature selection strategy. Therefore, in this paper, we conduct a comparative analysis of machine learning (ML) models with a specific preprocessing strategy and suggest a high performer model for battery rack SOC estimation. First, we preprocess the data by cleaning, normalizing, selecting important attributes, and then split it into training and testing sets. Next, four ML models are trained using the training data for SOC estimation, and finally, for better evaluation, each model is evaluated on the testing data using various error metrics. After comprehensive experiments, we suggest multilayer perceptron (MLP) due to high performance for batteries rack SOC estimation.

최근 기후변화와 도시화로 인해 집중호우에 따른 도시침수가 증가하고 있으며, 충청북도에서는 관거 정비 등 개별적인 사후 대응 중심의 대책이 주로 시행되어 유역 전체를 고려한 통합적 관리체계가 부족한 실정이다. 도시침수란 강우에 의해 도시 내부(배수 분구)에서 발생하는 침수로, 빗물이 하수관거· 집수정·펌프장·배수문 등 내부 배수체계의 처리능력(운반·저류·배제)을 초과하거나, 하천 수위·만조 등 으로 외수 배제가 제한되어 물이 도시 내부에 고이거나 역류하는 현상을 말한다. 이에 본 연구에서는 청주시 비하지구를 대상으로 도시침수의 원인과 운영 한계를 분석하고 XP-SWMM 모형을 활용하여 50, 100, 200년 빈도 강우 조건에서 강우-유출 과정, 관거 흐름, 지표 침수 및 하천 수위와의 상호작용을 모의하여 이를 기반으로 통합적 도시침수 대응ㆍ운영체계를 마련하는 것을 목적으로 한다. 이를 위해 모의 결과를 토대로 침수취약구역 지정, 우수관거 설계빈도 상향, 하천-관거 연계 강화, 저지대 구조적 대책 등 통합 운영·관리를 위한 대응전략을 도출하였다.

Recently, urban flooding triggered by heavy rainfall has intensified due to climate change and urbanization. In Chungbuk Province, responses have mainly relied on reactive, facility-specific measures (e.g., sewer/channel maintenance), leaving a lack of watershed-scale integrated management. Urban flooding occurs when rainfall exceeds the conveyance, storage, and discharge capacity of internal drainage systems (sewers, catch basins, pumping stations, and sluice gates) or when external outflow is constrained by high river stages or tides, causing ponding and backflow. This study investigates the causes and operational limitations of flooding in the Biha district of Cheongju City using the XP-SWMM model. The model simulates rainfall–runoff processes, sewer hydraulics, surface inundation, and river–sewer interactions under 50-, 100-, and 200-year design storms. Based on the results, we propose an integrated response and operation framework, including delineation of flood-prone areas, upgrading sewer design standards, strengthening river–sewer connectivity, and implementing structural measures for low-lying zones.

The aerial view diverse action recognition (AR) benchmark provides a valuable resource for researchers and developers in computer vision (CV) for human actions recognition (HAR) from an aerial perspective. With the increasing use of unmanned aerial vehicles (UAVs) for surveillance, delivery, search, and rescue, a robust understanding of human actions from an aerial view is crucial. Existing datasets lack representation of common outdoor actions and are unsuitable for intelligent UAVs. This article proposes a dataset that captured various actions from diverse viewpoints and in different environments. The dataset includes three viewpoints (Top, left, and right) allowing angle-invariant algorithm development. State-of-the-art algorithms (3D, and 2D convolutions with sequential learning) are evaluated on the dataset. The proposed model demonstrates exceptional performance with high accuracy (87.5%), precision (86.3%), and recall (87.2%) rates. The robustness of the model is showcased through real-time testing, indicating that the proposed dataset and model contribute to advancing research from drone view AR and have the potential to enhance surveillance and other UAV applications.

본 연구에서는 쓰레기 매립지의 토양으로부터 파생된 유해가스류의 환경영향평가에 초점을 맞추었다. 장소는 접근 허용을 기준으로 전체 3개 지역으로 선택되었다. 구체적으로 목천 쓰레기 매립지와 전천 및 병천의 쓰레기 산이 대상이다. 목천의 쓰레기 매립지는 여러 개의 수직 가스 집수정을 갖고 있어 측정의 중심지는 가장 오래된 매립지점으로 선정하고, 또한 측정 거리는 0 ~ 400m(100m 간격)으로 하였다. 두 개의 쓰레기 산의 측정 중심지는 가장 적치량이 많은 곳으로 측정 거리는 0 ~ 600m(150m 간격)으로 하였다. 실험은 가스텍과 복합가스측정기를 이용하여 중심지로부터 거리별 유해가스의 농 도를 측정하는 것으로 실시하였다. 쓰레기 매립지의 경우 CO와 HCHO의 농도가 중심지로부터 300m 부근에서 2.2배 증가하였고, 쓰레기 산의 경우 CO와 HCHO의 농도가 쓰레기 매립지보다 변곡점에서 확연히 증가하였다. 이 연구를 통해 쓰레기 매립지의 환경영향성이 정량적으로 평가되어 쓰레기 매립 지 토양에 함유된 유해가스에 대한 경각심을 가질 필요가 있다

In this study, we focused on the evaluation of environmental effects by harmful gases derived from waste landfills soil. Places were selected to total three areas by the criteria for permitting access on fields. Concretely they are a waste landfill at Mokcheon, and waste mountains at Jincheon and Byeongcheon. Mokcheon's waste landfill contain several vertical wells, and then the center of determination was selected to the oldest landfill spot, also the distance of determination was set up 0 ~ 400m(100m spaced). The center of determination at waste mountains was selected to the highest load spot, setting up the distance of determination 0 ~ 600m(150m spaced). Experiments were conducted to measure harmful gases concentration by the distance from center using Gastec and multi-gas monitors. In case of a waste landfill, CO and HCHO concentration were increased to 2.2 times at the nearby 300m from the center. And also, in case of waste mountains, the concentration of CO and HCHO increased dramatically at the point of inflection than a waste landfill. Therefore, environmental effects of waste landfills were conducted from the quantitative analysis, and then we would bring to senses for harmful gases contained in waste landfills soil.

Mushroom survey and collection were conducted in the Phousabous National Protected Area (PNPA), which is located at the Northeastern area 230km from the capital city of Lao-PDR, Vientiane, from April 2017 to September 2018. During this periods, mushroom specimens were collected from 8 different locations, and then they were identified and classified into 284 species, 142 genera, 56 families, 20 orders and 7 classes by morphological and molecular analyses. The mushrooms belongs to Ascomycota were classified into 10 species, 5 genera, 5 families, 4 orders and 3 classes, while those belongs to Basidiomycota were classified into 274 species, 137 genera, 51 families, 16 orders, and 4 classes, respectively. Among these mushrooms, the most species-rich families are Boletaceae (16.06%), Polyporaceae (10.12%), Russulaceae (9.94%), Amanitaceae (7.68%), Agaricaceae (4.54%), Marasmiaceae (4.36%), Cortinariaceae (3.66%), Entolomataceae (3.66%), Mycenaceae (2.79%), Xylariaceae (2.44%), Physalacriaceae (2.09%), Omphalotaceae (2.09%), Hydnangitaceae (2.09%), Lyophyllaceae (1.92%), Tricholomataceae (1.75%) and comprised 75.19% of the total specimens identified.

Mushroom survey was conducted in the Phou Khao Khuoay National Protected Area (PKKNPA) located at east direction 65km from Vientiane, the capital city of Lao-PDR from September 2015 to November 2016. During this periods, mushroom specimens were collected from 10 different survey sites, and then were identified and classified into 149 species, 113 genera, and 55 families by morphological and molecular analyses. The mushrooms belongs to Ascomycota were classified into 13 species, 7 genera, 5 families, and 5 orders, while those belongs to Basidiomycota were classified into 136 species, 113 genera, 55 families, and 18 orders, respectively. Among these mushrooms, the most species-rich families were Polyporaceae (18.1%), Marasmiaceae (11.0%), Ganodermataceae (8.6%), Xylariaceae (5.8%), Russulaceae (5.4%), Agaricaceae (4.7%), Boletaceae (4.7%), Hymenochaetaceae (3.9%), and Amanitaceae (3.6%), and comprised 65.8% of the total specimens identified.

As an alternative biomass, the giant miscanthus was introduced for raising the bio industry in Korea. Unlike the expectations, however, its application has been limited due to its low economical value. To utilize it as a high added value material, in this study, the feasibility of nanofiber production from giant miscanthus holocellulose treated with delignification by peracetic acid method and their properties were investigated. The yield of the cellulose nanofiber produced by the acid hydrolysis method using sulfuric acid was calculated on the base of percentage of moisture content of the obtained suspension. As results, the yields were affected by sulfuric acid concentration, reaction time and temperature. The higher the reaction temperature, the smaller the length and width of the fiber were observed by TEM analysis. In addition, TEMPO oxidized giant miscanthus cellulose fiber treated with ball mill was shorter in fiber length than that of by homogenizer treatment. Moreover, the particle size was manufactured with uniform size with increase of the ball mill and homogenizer processing speed and time. In the FT-IR analysis, the carboxylation reaction of cellulose was confirmed. It was confirmed by X-ray diffraction analysis that the intensity of 002 was shifted after the ball mill and homogenizer treatment of TEMPO oxidized giant miscanthus cellulose.

최근 반복되는 대형 재난사고는 국민적 충격을 불러일으키며 안전에 대한 사회적 경각심을 고조시켰다. 특히, 기후변화와 도시화로 인한 복합재난 발생이 증가하면서 지역 단위의 안전문화 정착 필요성이 강조되고 있으며, 기존 중앙정부 중심의 안전정책은 일정 수준 구축되어 있으나, 지역사회 특성과 주민 행동양식을 반영한 맞춤형 안전문화 진단 및 전략은 여전히 미흡한 상황이다. 이에 따라 주민의 인식ㆍ태 도ㆍ행동을 통합적으로 평가할 수 있는 지역 단위 안전문화 지수 개발 필요성이 높아지고 있다. 본 연구는 충청북도를 대상으로 도민의 안전문화 수준을 계량적으로 진단하고 상황ㆍ인식ㆍ행동 요소를 기반으로 한 충북형 안전문화지수를 개발하는 것을 목표로 이를 위해 설문조사와 실증분석을 통한 도민의 안전문화 수준을 유형화하고 각 유형별 취약요인 개선 및 정책적 시사점을 도출하였다. 본 연구에 서는 지역 기반의 안전문화 진단 체계를 고도화하고, 충청북도 특성을 반영한 실행 중심의 안전정책 수립에 기여하고자 한다.

Recently, a series of large-scale disasters have profoundly shocked the nation, heightening public awareness and concern for safety. As complex disasters driven by climate change and urbanization continue to increase, the establishment of a localized safety culture has become a crucial issue. Although national-level safety policies have been developed to a certain extent, region-specific strategies that reflect the unique characteristics and behavioral patterns of local communities remain insufficient. This study aims to quantitatively assess the level of safety culture among residents of Chungcheongbuk-do and to develop a Chungbuk-type Safety Culture Index based on three key dimensions: situational, cognitive, and behavioral factors. A survey and empirical analysis were conducted to classify residents’ safety culture types, identify vulnerable factors for each type, and derive corresponding policy implications. The findings of this study are expected to contribute to the establishment of a sustainable, community-based safety culture within Chungcheongbuk-do.

Bioassay and HPLC-UV guided fractionations of the crude extract of marine-derived Streptomyces sp. SNA-077 have led to the isolation of a red pigment, undecylprodigiosin. The chemical structure of undecylprodigiosin was revealed by the interpretation of NMR and mass spectroscopic (MS) data. Further, anti-melanogenic effects of undecylprodigiosin were investigated. First, the melanin contents of undecylprodigiosi-treated B16 cells were evaluated. Furthermore, undecylprodigiosin significantly inhibited the key enzymes involved in melanogenesis, including tyrosinase, tyrosinase related protein-1 (TYRP- 1), and dopachrome tautomerase (DCT). The mRNA and protein expression levels of Microphthalmiaassociated transcriptian factor (MiTF), a critical transcription factor for tyrosinase gene expression, were also suppressed by undecylprodigiosin treatment in B16 analyses. Collectively, our results suggest for the first time that undecylprodigiosin, a potent component isolated from an extract of marine Streptomyces sp. SNA-077, critically exerts the anti-melanogenic ability for melanin synthesis.

2024년 4월, 대한민국에서 고양이들로부터 원인을 알 수 없는 병증 사례가 다수 보고되었다. 동물보호단 체 라이프에 따르면 같은 달 21일 오후 6시까지 163가구 263마리의 고양이가 이러한 병증을 보였으며 이 중 94마리가 사망하였다고 한다. 이 단체는 특정 제조원에서 같은 해 1~4월에 만든 사료를 먹은 것이 원인이라고 주장하고 있다. 한편 같은 달 19일 농림축산식품부는 사료 3건을 검사했는데, 아직까지 고양이 사료와 병증과의 인과관계는 명확하게 파악되지 않는 것이다. 본 연구에서는 ‘책임의 사슬’에 특히 주목하면서 고양이 신경·근육병증의 원인을 찾기 위하여 농림축산식품부로부터 독립되는 별도의 조직이 나서야 한다는 것을 주장하고자 한다. 축소 또는 은폐의 유혹을 받을 가능성이 있다는 구조가 존재하는 한 농림축산식품부의 조사 결과를 국민들이 불신할 수 있기 때문에 이러한 구조로부터 빠르게 탈피하는 방안을 모색해야 한다는 것이다.

In April 2024, numerous cases of an unidentified ailment among cats have been reported in the Republic of Korea. According to the animal welfare organization LIFE, as of 6 p.m. on the April 21st, 263 cats from 163 households exhibited this ailment, 94 of them succumbing to it. The organization claims that the cause lies in the consumption of pet food produced by a specific manufacturer between January and April 2024. However, on April 19th, the Ministry of Agriculture, Food and Rural Affairs (MAFRA) announced that out of 36 pet food samples submitted for examination, three were tested with no issues found. However, the link between cat food and the ailment remains unclear. This study argues for the necessity of an independent organization separate from the MAFRA, focusing on the "chain of responsibility," to identify the cause of the feline neurological and muscular ailment. Given the potential for influence or concealment, the public may distrust investigation results from the MAFRA, highlighting the need to swiftly break away from such a structure and explore alternative solutions.

기후위기를 해결하기 위하여 정부의 정책과 기업의 윤리적 운영이 동반되어야 하고 개인의 의식적인 환경 행동이 무엇보다 중요하다. 지속가능한 사회에 대한 인식과 이러한 인식이 환경 행동 의도 형성에 미치는 영향을 파악하고자 하였다. 본 연구는 개인의 사회문제 및 지속가능한 사회에 대한 인식이 환경 행동 의도 형성에 미치는 영향을 살펴본다. 전반적인 사회인식, 사회문제에 대한 인식, 지속가능한 사회 와 환경문제, 적극적 사회참여 변수를 바탕으로 Stata 18 SE을 활용하여 위계적 다중회귀분석을 사용했다. 연구 결과, 전반적 사회인식은 적극적 사회참여에 유의한 영향을 미치지 않는 것으로 확인되었으나, 사회문제에 대한 인식, 지속가능한 사회와 환경문제는 적극적 사회참여에 유의한 긍정적인 영향을 미치 는 것으로 나타났다. 본 연구는 다양한 배경을 바탕으로 형성된 개인의 환경 행동에 대한 인식을 실증적 으로 연구했다는 데 의의가 있다.

To address the climate crisis, government policies and ethical business practices must be complemented by conscious environmental behaviors at the individual level. This study aims to understand how perceptions of a sustainable society influence the formation of intentions toward environmental behavior. It examines the impact of an individual's current status on their intention to engage in environmentally responsible actions. Hierarchical multiple regression analysis was conducted using Stata 18 SE, with variables including active social participation, general social perception, awareness of social issues, and sustainable social and environmental issues. The findings reveal that while general social perception did not significantly influence active social participation, awareness of social issues, and perceptions related to sustainable social and environmental issues, had a significant positive impact on active social participation. This study empirically validated the perceptions of individual environmental behaviors that are formed based on diverse backgrounds.

This research explores the dynamics of outsourced labor while specifically analyzing personnel expense proportions in various business categories. Utilizing a Quadrant Framework, businesses are classified based on expertise and autonomy, thereby providing a comprehensive overview. Type I businesses encompass daycare centers with distinct revenue structures regulated by the "Early Childhood Education and Care Act." Type II businesses include General Meal Service and General Transportation, which operate autonomously without budget support. Type III businesses, which comprise Social Welfare, Call Centers, and others, typically receive budget support and range in expertise from low to moderate. Lastly, Type IV businesses include Education, Health Care, and Technology, and they receive budget support while having moderate to high expertise requirements. However, it is difficult to draw definitive conclusions due to the issues involved in precise segmentation of expertise and the division of "budget-supported to autonomous". The results of this analysis are expected to aid stakeholders in resource allocation strategies, ultimately allowing those within diverse business classifications to optimize their workforce management.

The identification of anomalies in industrial settings poses a significant challenge, especially when there is a lack of negative samples and when the anomalous regions are small. Although existing computer vision methods have automated this task to some extent, these approaches struggle to extract salient features for inspecting defective chips. To tackle this problem, a deep learning-based framework is proposed for detecting anomalies in industrial settings. The framework utilizes a fine-tuned backbone convolutional neural network model and incorporates an enhanced attention mechanism. The attention module generates discriminative feature maps along two dimensions: channel and spatial. This is achieved by processing intermediate features obtained from the backbone model. These attention maps are then multiplied with the input feature map to dynamically enhance the relevant features. Extensive experiments demonstrate the effectiveness of our proposed method in maintaining a high level of detection accuracy for industrial product inspections. Consequently, our results conclude a suitable solution for optical chip inspection systems in industrial settings.

Fire detection is a significant attempt for preserving public safety in complex surveillance environments. Although advances in deep learning for fire detection, the task remains challenging due to the natural irregularity in fire images, including differences in lighting conditions, occlusions, and background complexity. To address these challenges, we present a novel framework for fire detection named fire channel attention network (FCAN), which is capable of differentiating challenging fire scenes. Our approach is motivated by the need to enhance the accuracy of fire detection by selectively emphasizing the most informative channels of the input image through a channel attention (CA). Furthermore, our model captures the salient features from the input image and suppresses the irrelevant ones, thereby overcoming the aforementioned challenges of fire detection. The FCAN is evaluated on two benchmark datasets and surpassed existing methods in terms of accuracy and F1 score. The proposed model demonstrates the effectiveness of fire detection, highlighting its potential for practical applications in fire safety and prevention.

A crucial component of designing intelligent and ecologically friendly environments nowadays is electricity consumption forecasting. The generation of energy can be enhanced to effectively meet the population's rising requirements by using the prediction of future electricity consumption. Due to the broad variety of consumption patterns, it is difficult to anticipate the energy requirements of buildings. Therefore, this work uses a dual-steam approach with multi-head attention to anticipate the power consumption of the building to address this issue and produce precise predictions. The proposed network concurrently learns temporal representations through a Bidirectional Gated Recurrent Unit (BGRU) and spatial patterns through Atrous Convolutional Neural Network (ACNN). The obtained features are combined to create a single feature vector that is used as the input for the multi-head attention, which finds the features that are most suited to forecasting the electricity consumption of a building. Finally, the dense layer receives the effective features and uses them to forecast short-term power consumption. In this paper, the proposed dual-stream network with attention outperforms competing models, achieving the lowest error value for hourly building power consumption prediction, according to experimentation on the household electricity consumption dataset.

Accurate detection of small targets in aerial images is crucial but challenging due to the limited computational resources of UAVs. This paper presents an efficient approach based on YOLO-V5S for detecting and classifying distant vehicles in aerial scenes. Extensive ablation study is conducted to find the optimal YOLO architecture. The proposed method is efficient and effective, making it applicable for real-time deployment. A dataset of 1000 annotated images are developed to validate the proposed method's effectiveness. The proposed network outperforms existing state-of-the-art methods in accuracy, speed, and resource efficiency, making it a promising solution for aerial vision-based applications.

Animal detection and classification are crucial for effective wildlife management (WM) and reducing risks associated with animals related road accidents and attacks. Previous attempts trained the models using imbalanced data with fewer representative features and baseline models without improvement. This paper presents a new dataset of five animal classes captured in various poses, lighting conditions, and intraclass variations. The standard coupled detection head of the YoloV4 algorithm faces limitations when performing simultaneous classification and localization due to shared parameters and inputs. To address this issue, we propose a decoupled detection head (DDH) that handles these tasks separately, improving performance. We conducted extensive experiments using the proposed dataset. We found that the optimal backbone features marginally improve the performance of the modified network compared to state-of-the-art (SOTA) works in the subject domain. Our work contributes by addressing the limitations of the standard YoloV4 algorithm and proposing a new dataset for researchers to use in future studies.

인접한 미래에 안전 위협이 개인의 삶에 부정적인 영향을 미칠 것이라는 우려가 제시됨에 따라 본 연구는 현재 시점에서 미래까지의 인식에 영향을 미치는 요인을 탐색하고자 수행되었다. 사회를 바라보 는 가치관, 사회활동 참여의지, 기업활동에 대한 평가 등을 기반으로 stata 17 se를 활용한 다중회귀분석 을 수행하였다. 연구를 통하여 사회에 대한 긍정적 가치관을 지니고, 무엇보다 Covid 대응체계에 대한 긍정적 평가를 내린 사람일수록 미래 안전 위협에 대해 삶에 대한 부정적인 영향력을 낮게 평가하는 경향이 있는 것으로 나타났다. 반면, 사회문제해결을 위한 활동을 다양하게 참여하는 경향이 있는 사람 의 경우 미래 안전 위협에 대해 삶에 대한 부정적인 영향력을 높게 평가한 것으로 나타났다. 사회문제 해결 주체로서 기업은 유의미한 결과가 나타나지 않았다. ‘안전’에 대한 요구가 지속적으로 사회 이슈로 대두되는 것은 공동체가 받아들여야 하는 위험요소의 증가와 함께 사회에 대한 이해를 기반으로 제도 의 정비가 요구되는 지점이 발생하기 때문이다. 이러한 점에서 본 연구는 다양한 배경에 의해 형성되는 개인 안전인식에 대한 실증적 연구를 수행했다는 점에서 의의가 있다.

As concerns have been raised about the potential negative impacts of future safety threats on individuals' lives, this study aimed to explore the factors that influence perceptions of the future in the present moment. Using multiple regression analysis in Stata 17 SE, the study was based on variables related to social perspectives, willingness to participate in social activities, and evaluations of corporate activities. The results showed that individuals who held positive social values tended to evaluate the negative impacts of future safety threats on their lives as less severe. On the other hand, individuals who tended to participate in various activities to solve social problems tended to evaluate the negative impacts of future safety threats on their lives as more severe. The continued prominence of "safety" as a social issue reflects the increasing need for institutional improvements based on societal understanding. In this regard, the significance of this study lies in its empirical research on individual perceptions of safety awareness formed based on various backgrounds.

한국의 생명윤리 법제는 진자의 떨림같이 크게 요동친 경험을 가지고 있다. 본 연구에서는 과학기술과 생명윤리 정책을 입안하는 데 있어서 잠깐의 분위기에 치중할 것이 아니라 충분한 검토를 통해 크게 흔들리지 않는 기준점의 필요성을 주장한다. 우리나라의 제도는 다수의 행위자의 참여가 보장되어 왔으 나, 그 정책에 이르는 과정과 내용에서 합리성과 전문성은 다소 미흡한 측면이 있다. 일본은 특유의 관료제적 성격으로 인하여 정책의 결정과정에 다수의 참여가 보장되거나 의사결정이 빠른 것은 아니지 만, 전문가들의 참여를 통하여 전문성 있는 구체적인 의사결정이 가능하다. 우리나라 기구들이 일본과 같은 수준의 충분한 회의 내용 및 자료를 제공한다면, 생명과학 연구자들이 연구할 수 있는 범위를 예측가능하게 함으로써 일탈을 막을 것이다. 또한, 시민 사회의 전문성을 높여 활동을 지속하면서 감시를 계속하게 하여, 제도의 변화가 생명윤리를 훼손하는 방향으로 일어나지 않도록 함으로써, 우리나라의 생명윤리와 안전의 보장에 기여할 수 있을 것이다.

In Korea, bioethics legislation has experienced great fluctuations like a pendulum swinging. After Professor Hwang's research ethics issue, embryonic stem cell research in Korea lost its vitality. In this study, we insist that Korea needs a reference point that is not greatly shaken. We review the establishment of Korea and Japan's life science and ethics-related laws and the operation of their organizations. Then, we compare the strengths and weaknesses of Korea and Japan. Finally, we will propose Korea's strategy to improve bioscience and bioethics systems. In Japan, it is possible to make specific decisions with expertise through the participation of experts. If Korean institutions provide sufficient meeting contents and data at the same level as Japan, deviations will be prevented by making the range of research available to life science researchers predictable. In addition, it will be possible to contribute to the guarantee of Korea's bioethics and safety by increasing the professionalism of civil society to continue monitoring while continuing activities.

Good communication between members contributes to coordinating and resolving conflicts within the organization (Lee et. al., 2012). There was a special office space on the 3rd floor of the main building of Cheongju City Hall. That was BICHAENAUM, named after "Empty, fill, and share, and newness springs up." In BICHAENAUM, about 50 officers from three departments worked freely in an open space. In this study, in preparation for the expansion of spatial innovation in the Cheongju City Hall, was to analyze the work relevance by the department and refer to the arrangement of departments with high relevance in the same space. The working relationship between departments was examined through social network analysis. As a result, departments in Cheongju City Hall were classified into 9 groups. In the long term, we hope that this study will serve as a basis for achieving the goal of improving working methods for spatial innovation.