• Informatization Policy
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• v.30 no.1
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• pp.41-66
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• 2023

This study aims to reveal the direction of municipal ordinances for smart cities, while focusing on 74 municipal ordinances from 72 municipal governments through topic modeling. As a result, the main keywords that show a high frequency belong to establishment and operations of the Smart City Committee. From the result of topic modeling Latent Dirichlet Allocation(LDA), it classifies municipal ordinances for smart cities into eight topics as follows: Topic 1(security for process of smart cities), Topic 2(promotion of smart city industry), Topic 3(composition of a smart city consultative body for local residents), Topic 4(support system for smart cities), Topic 5(management for personal information), Topic 6(use of smart city data), Topic 7(implementation for intelligent public administration), and Topic 8(smart city promotion). As for topic categorization by region, Topics 5, 6, and 8 which are mostly related to the practical operation of smart cities have a significant portion of municipal ordinances for smart cities in the Seoul metropolitan area. Then, Topics 2, 3, and 4 which are mostly related to the initial implementation of smart cities have a significant portion of municipal ordinances for smart cities in provincial areas.

• The Journal of the Acoustical Society of Korea
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• v.42 no.2
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• pp.133-142
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• 2023

The office environment is changing according to work types, Information Technology (IT) advancements, and the Coronavirus disease (COVID)-19 situation. In order for office space users to perform their tasks comfortably and efficiently, it is necessary to secure individual privacy as well as easy communication among members. In Korea, the demand for improving the acoustic performance of office spaces is also increasing, but the related performance criteria and guidelines have not been established. In this study, standardization of office space acoustic performance measurement and evaluation methods and European countries' acoustic performance criteria were compared and reviewed. It is proposed to comprehensively review international standardization trends and acoustic performance standards in each country and to establish and utilize criteria for evaluating the acoustic performance and satisfaction of office spaces in Korea through our survey. Considering the international standardization direction and compatibility with communication and Public Address (PA) systems, it is appropriate to establish criteria using the speech transmission index or Speech Transmission Index (STI) application index. This criterion will be highly utilizable and compatible. In addition, since the office furniture industry is interested in improving the acoustic performance of office space, it is necessary to establish a labelling system for speech level reduction of office furniture.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.1
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• pp.47-70
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• 2022

The purpose of this study is to empirically verify the factors(organization managerial factors, relational factors and personal factors) that affect the knowledge sharing intention of records management specialists. A total of 126 responses were used for the final analysis and the findings of this study are as follows: First, managers' interests and supports had a significant positive effect on tacit knowledge sharing intention, but evaluation and compensation system had a negative effect on tacit knowledge sharing intention. Second, job stress was found to have a significant positive effect on the intention of knowledge sharing(tacit, explicit). It is required to form an organizational culture where records management specialists can freely participate in knowledge sharing activities with the interest and support of managers. In addition, the process of continuously improving the causes of one of the causes of job stress, such as awareness improvement and deprivation, should be carried out through records management training for all employees. This study is meaningful in that it provides policy implications for promoting knowledge sharing as a solution to the managerial problems faced by records management specialists by utilizing the current staffing structure.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.129-148
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• 2023

Bitcoin is a blockchain technology-based digital currency that has been recognized as a representative cryptocurrency and a financial investment asset. Due to its highly volatile nature, Bitcoin has gained a lot of attention from investors and the public. Based on this popularity, numerous studies have been conducted on price and trend prediction using machine learning and deep learning. This study employed LSTM (Long Short Term Memory) and CNN (Convolutional Neural Networks), which have shown potential for predictive performance in the finance domain, to enhance the classification accuracy in Bitcoin price trend prediction. XAI(eXplainable Artificial Intelligence) techniques were applied to the predictive model to enhance its explainability and interpretability by providing a comprehensive explanation of the model. In the empirical experiment, CNN was applied to technical indicators and Google trend data to build a Bitcoin price trend prediction model, and the CNN model using both technical indicators and Google trend data clearly outperformed the other models using neural networks, SVM, and LSTM. Then SHAP(Shapley Additive exPlanations) was applied to the predictive model to obtain explanations about the output values. Important prediction drivers in input variables were extracted through global interpretation, and the interpretation of the predictive model's decision process for each instance was suggested through local interpretation. The results show that our proposed research framework demonstrates both improved classification accuracy and explainability by using CNN, Google trend data, and SHAP.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1846-1854
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• 2022

The sophistication and diversification of mission equipment for surveillance and reconnaissance is leading to a demand for large-capacity public data links. Overseas, a T4 class(274Mbps) common data link was applied to the Global hwak, a high-altitude unmanned aerial vehicle, and various research and development are being conducted in Korea. In this paper, we propose a structure in which pilot is additionally applied to improve SNR performance while minimizing data transmission rate loss in the DVB-S2 frame structure, which is a european satellite broadcasting standard, for high-capacity transmission of T4 class or higher in the common data link. For the performance evaluation of the proposed structure, the performance of the DVB-S2 was compared and analyzed by simulating the UAV data link channel environment. As a result of simulation, 0.15% of transmission rate loss occurred at T4 class transmission rate compared to DVB-S2 in the proposed structure, but improved SNR reception performance of 0.2~0.3dB was confirmed in the UAV channel environment.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.519-524
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• 2023

In hashing-based image retrieval, the hash code of a manipulated image is different from the original image, making it difficult to search for the same image. This paper proposes and evaluates a self-supervised deephashing model that generates perceptual hash codes from feature information such as texture, shape, and color of images. The comparison models are autoencoder-based variational inference models, but the encoder is designed with a fully connected layer, convolutional neural network, and transformer modules. The proposed model is a variational inference model that includes a SimAM module of extracting geometric patterns and positional relationships within images. The SimAM module can learn latent vectors highlighting objects or local regions through an energy function using the activation values of neurons and surrounding neurons. The proposed method is a representation learning model that can generate low-dimensional latent vectors from high-dimensional input images, and the latent vectors are binarized into distinguishable hash code. From the experimental results on public datasets such as CIFAR-10, ImageNet, and NUS-WIDE, the proposed model is superior to the comparative model and analyzed to have equivalent performance to the supervised learning-based deephashing model. The proposed model can be used in application systems that require low-dimensional representation of images, such as image search or copyright image determination.

• Journal of the Korean Society of Radiology
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• v.18 no.2
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• pp.109-117
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• 2024

In order to determine the level of awareness of nuclear power generation and Fukushima contaminated water, this study conducted an online survey targeting the general public living in the Busan area and analyzed a total of 201 questionnaires. Independent samples t-test and one-way analysis of variance were conducted to verify differences in variables according to the characteristics of the study subjects, and correlation analysis was conducted to confirm the correlation between variables. First, the results of the study showed that women had a more negative perception of nuclear power generation and Fukushima contaminated water than men. In terms of age, it was found that people in their 40s and older had a high level of negative perception. In terms of political inclination, progressive respondents showed a higher negative perception toward nuclear power generation and Fukushima contaminated water. Second, information on nuclear energy was most often collected through the Internet, broadcasting, and SNS. Third, the higher the negative perception of nuclear power generation, the more negative the results were in terms of issues of concern following the discharge of contaminated water at the Fukushima nuclear power plant. Nuclear power cannot be separated from human life. Therefore, it is believed that accurate information and a knowledge delivery system are needed to ensure correct awareness of nuclear power generation.

• Journal of the Economic Geographical Society of Korea
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• v.10 no.1
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• pp.44-63
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• 2007

The purpose of this study is to propose mining processes in the large trip-transaction database of the Metropolitan Seoul area and to analyze the spatial characteristics of travel behavior. For the purpose. this study introduces a mining algorithm developed for exploring trip patterns from the large trip-transaction database produced every day by transit users in the Metropolitan Seoul area. The algorithm computes trip chains of transit users by using the bus routes and a graph of the subway stops in the Seoul subway network. We explore the transfer frequency of the transit users in their trip chains in a day transaction database of three different years. We find the number of transit users who transfer to other bus or subway is increasing yearly. From the trip chains of the large trip-transaction database, trip patterns are mined to analyze how transit users travel in the public transportation system. The mining algorithm is a kind of level-wise approaches to find frequent trip patterns. The resulting frequent patterns are illustrated to show top-ranked subway stations and bus stops in their supports. From the outputs, we explore the travel patterns of three different time zones in a day. We obtain sufficient differences in the spatial structures in the travel patterns of origin and destination depending on time zones. In order to examine the changes in the travel patterns along time, we apply the algorithm to one day data per year since 2004. The results are visualized by utilizing GIS, and then the spatial characteristics of travel patterns are analyzed. The spatial distribution of trip origins and destinations shows the sharp distinction among time zones.

• Journal of the Korean Geotechnical Society
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• v.35 no.11
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• pp.121-129
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• 2019

An Earthquake Early Warning (EEW) system is a technology that alerts people to an incoming earthquake by using P waves that are detected before the arrival of more severe seismic waves. P-wave analysis is therefore an important factor in the production of rapid seismic information as it can be used to quickly estimate the earthquake magnitude and epicenter through the amplitude and predominant period of the observed P-wave. However, when a large-magnitude teleseismic earthquake is observed in a local seismic network, the significantly attenuated P wave phases may be mischaracterized as belonging to a small-magnitude local earthquake in the initial analysis stage. Such a misanalysis may be sent to the public as a false alert, reducing the credibility of the EEW system and potentially causing economic losses for infrastructure and industrial facilities. Therefore, it is necessary to develop methods that reduce misanalysis. In this study, the possibility of seismic misclassifying teleseimic earthquakes as local events was reviewed using the Filter Bank method, which uses the attenuation characteristics of P waves to classify local and outside Korean peninsula (regional and teleseismic) events with filtered waveform depending on frequency and epicenter distance. The data used in our analysis were analyzed for maximum P_v values using 463 events with local magnitudes (2 < M_L ≦ 3), 44 (3 < M_L ≦ 4), 4 (4 < M_L ≦ 5), 3 (M_L > 5), and 89 outside Korean peninsula earthquakes recorded by the KMA seismic network. The results show that local and telesesimic earthquakes can be classified more accurately when combination of filtering bands of No. 3 (6-12 Hz) and No. 6 (0.75-1.5 Hz) is applied.

• Journal of Korean Society for Atmospheric Environment
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• v.26 no.5
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• pp.543-553
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• 2010

Almost five million citizens a day are using subways as a means of traffic communication in the Seoul metropolitan. As the subway system is typically a closed environment, indoor air pollution problems frequently occurs and passengers complain of mal-health impact. Especially $PM_{10}$ is well known as one of the major pollutants in subway indoor environments. The purpose of this study was to compare the indoor air quality in terms of $PM_{10}$ and to quantitatively compare its source contributions in a Seoul subway platform before and after installing platform screen doors (PSD). $PM_{10}$ samples were collected on the J station platform of Subway Line 7 in Seoul metropolitan area from Jun. 12, 2008 to Jan. 12, 2009. The samples collected on membrane filters using $PM_{10}$ mini-volume portable samplers were then analyzed for trace metals and soluble ions. A total of 18 chemical species (Ba, Mn, Cr, Cd, Si, Fe, Ni, Al, Cu, Pb, Ti, $Na^+$, $NH_4^+$, $K^+$, $Mg^{2+}$, $Ca^{2+}$, $Cl^-$, and ${SO_4}^{2-}$) were analyzed by using an ICP-AES and an IC after performing proper pre-treatments of each sample filter. Based on the chemical information, positive matrix factorization (PMF) model was applied to identify the source of particulate matters. $PM_{10}$ for the station was characterized by three sources such as ferrous related source, soil and road dust related source, and fine secondary aerosol source. After installing PSD, the average $PM_{10}$ concentration was decreased by 20.5% during the study periods. Especially the contribution of the ferrous related source emitted during train service in a tunnel route was decreased from 59.1% to 43.8% since both platform and tunnel areas were completely blocked by screen doors. However, the contribution of the fine secondary aerosol source emitted from various outside combustion activities was increased from 14.8% to 29.9% presumably due to ill-managed ventilation system and confined platform space.