• 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.

• Information Systems Review
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• v.25 no.4
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• pp.27-45
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• 2023

The importance of information security has grown alongside the development of information and communication technology. However, companies struggle to select suitable countermeasures within their limited budgets. Sönmez and Kılıç (2021) proposed a model using AHP and mixed integer programming to determine the optimal investment combination for mitigating information security breaches. However, their model had limitations: 1) a lack of objective measurement for countermeasure efficacy against security threats, 2) unrealistic scenarios where risk reduction surpassed pre-investment levels, and 3) cost duplication when using a single countermeasure for multiple threats. This paper enhances the model by objectively quantifying countermeasure efficacy using the beta probability distribution. It also resolves unrealistic scenarios and the issue of duplicating investments for a single countermeasure. An empirical analysis was conducted on domestic SMEs to determine investment budgets and risk levels. The improved model outperformed Sönmez and Kılıç's (2021) optimization model. By employing the proposed effectiveness measurement approach, difficulty to evaluate countermeasures can be quantified. Utilizing the improved optimization model allows for deriving an optimal investment portfolio for each countermeasure within a fixed budget, considering information security costs, quantities, and effectiveness. This aids in securing the information security budget and effectively addressing information security threats.

• Information Systems Review
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• v.20 no.2
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• pp.87-110
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• 2018

This study reviews previous studies about the effects of RFID capabilities on strategic supply chain competence and business performance in the Chinese context. This study introduces a new perspective that measures the degree to which RFID capability levels contribute to business performance. Such an assumption is based on the fact that companies build their own capabilities through RFID capabilities and that these capabilities provide a competitive advantage for enterprises. Data on all sorts of logistics, distribution, and manufacturing companies that introduced RFID system in China were collected for data analysis. This study analyzes the structural equation modeling using Smart-PLS 2.0 program. This study confirms that internal reliability, convergent validity, and discriminant validity are satisfied. The hypothesis test result on the relationship between RFID capacity and strategic supply chain competence and strategic supply chain competence and company results is partially adopted. This study aids in establishing a RFID system construction strategy to enhance supply chain competence by suggesting guidelines for the successful introduction of RFID system through identifying the causal relationship between RFID capacity and strategic supply chain competence. This study also suggests the influence of RFID competency on visibility, agility, flexibility, and collaborations.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.461-466
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• 2024

Korean local governments operates the participatory budgeting system autonomously. This study is to classify these entities into clusters. Among the diverse machine learning methodologies(Neural Network, Rule Induction(CN2), KNN, Decision Tree, Random Forest, Gradient Boosting, SVM, Naïve Bayes), the Support Vector Machine technique emerged as the most efficacious in the analysis of 2022 Korean municipalities data. The first cluster C1 is characterized by minimal committee activity but a substantial allocation of participatory budgeting; another cluster C3 comprises cities that exhibit a passive stance. The majority of cities falls into the final cluster C2 which is noted for its proactive engagement in. Overall, most Korean local government operates the participatory busgeting system in good shape. Only a small number of cities is less active in this system. We anticipate that analyzing time-series data from the past decade in follow-up studies will further enhance the reliability of classifying local government types regarding participatory budgeting.

• Korean Journal of Environmental Biology
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• v.42 no.2
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• pp.193-206
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• 2024

This study aimed to quantify changes in forest cover and carbon storage of Korean Peninsular during the last two decades by integrating field measurement, satellite remote sensing, and modeling approaches. Our analysis based on 30-m Landsat data revealed that the forested area in Korean Peninsular had diminished significantly by 478,334 ha during the period of 2000-2019, with South Korea and North Korea contributing 51.3% (245,725 ha) and 48.6% (232,610 ha) of the total change, respectively. This comparable pattern of forest loss in both South Korea and North Korea was likely due to reduced forest deforestation and degradation in North Korea and active forest management activity in South Korea. Time series of above ground biomass (AGB) in the Korean Peninsula showed that South and North Korean forests increased their total AGB by 146.4Tg C (AGB at 2020=357.9Tg C) and 140.3Tg C (AGB at 2020=417.4Tg C), respectively, during the last two decades. This could be translated into net AGB increases in South and North Korean forests from 34.8 and 29.4 Mg C ha^-1 C to 58.9(+24.1) and 44.2(+14.8) Mg C ha^-1, respectively. It indicates that South Korean forests are more productive during the study period. Thus, they have sequestered more carbon. Our approaches and results can provide useful information for quantifying national scale forest cover and carbon dynamics. Our results can be utilized for supporting forest restoration planning in North Korea

• Journal of Preventive Medicine and Public Health
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• v.28 no.2 s.50
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• pp.462-472
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• 1995

This study examined the relation between anger-coping types and hypertension in employed men aged $40\sim60$ who consented to participate during the biannual physical checkup in the department of health management in 1988. The subjects analyzed were five hundred thirteen excluding those having hypertension history and/or current antihypertensive medications. Anger-coping types were constructed from the Harburg's model with two hypothetical anger-provoking situations involving wife and boss. Hypertensives were defined more than 140mmHg systolic blood pressure and/or 90mmHg diastolic blood pressure. Hypertensives were one hundred fifty two(29.6%) and those who suppressed their anger were 61.6% and 62.8% in wife and boss situations respectively. Items of anger, guilt, protest, and suppressed anger in wife situation showed odds ratios of 0.78-0.94 without statistical significance. But four items in boss situation showed odds ratios more than 1, especially anger-in types of anger item had 1.58 times the prevalence of hypertension of anger-out types(95% confidence intervals(CI) $1.06\sim2.35$) and subjects who indicated that suppressed their anger had 1.55 times the prevalence of hypertension of those who expressed their anger(95% CI $1.03\sim2.32$). For anger suppressed vs. expressed types of total suppressed anger index, prevalence of hypertension was 1.31 (95% CI $0.83\sim2.08$). After adjusting for age, body mass index, smoking and drinking, the odds ratios were slightly increased in both situations except guilt items compared with univariate analysis. These results suggest that the relation between Harburg's anger-coping model and hypertension is replicated partially in this subjects.

• Korean Journal of Environmental Biology
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• v.39 no.1
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• pp.100-107
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• 2021

Along with an increase in the frequency of high-concentration fine particulate matter in Korea, interest and research on ammonia (NH₃) are actively increasing. It is obvious that agriculture has contributed significantly to NH₃ emissions. However, studies on the long-term effect of fertilizer use on the ambient NH₃ concentration of agricultural land are insufficient. Therefore, in this study, NH₃ concentration in the atmosphere of agricultural land was monitored for 11 months using a passive sampler. The average ambient NH₃ concentration during the total study period was 2.02 ㎍ m^-3 and it was found that the effect of fertilizer application on the ambient NH₃ concentration was greatest in the month immediately following fertilizer application (highest ambient NH₃ concentration as 11.36㎍ m^-3). After that, it was expected that the NH₃ volatilization was promoted by increases in summer temperature and the concentration in the atmosphere was expected to increase. However, high NH₃ concentrations in the atmosphere were not observed due to strong rainfall that lasted for a long period. After that, the ambient NH₃ concentration gradually decreased through autumn and winter. In summary, when studying the contribution of fertilizer to the rate of domestic NH₃ emissions, it is necessary to look intensively for at least one month immediately after fertilizer application, and weather information such as precipitation and no-rain days should be considered in the field study.

• Journal of Environmental Impact Assessment
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• v.33 no.4
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• pp.143-154
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• 2024

Heat waves caused by climate change are rapidly increasing health damage to vulnerable groups, and to prevent this, the national, regional, and local governments are establishing climate crisis adaptation policy. A representative climate crisis adaptation policy to reduce heat wave damage is to expand the number of cooling centers. Because it is highly effective in a short period of time, most metropolitan local governments, except Jeonbuk, include the project as an adaptation policy. However, the criteria for selecting a cooling centers are different depending on the budget and non-budget, so the utilization rate and effectiveness of the cooling centers are all different. Therefore, in this study, we developed logistic regression models that can predict and evaluate areas with a high probability of expanding cooling centers in order to implement adaptation policy in local governments. In Incheon Metropolitan City, which consists of various heat wave-vulnerable environments due to the coexistence of the old city and the new city, a logistic model was developed to predict areas where heat waves can be cooling centered by dividing it into Ganghwa·Ongjin-gun and other regions, taking into account socioeconomic and environmental differences. As a result of the study, the statistical model for the Ganghwa·Ogjin-gun region showed that the higher the ground surface temperature and the more and more the number of elderly people over 65 years old, the higher the possibility of location of cooling centers, and the prediction accuracy was about 80.93%. The developed logistic regression model can predict and evaluate areas with a high potential as cooling centers by considering regional environmental and social characteristics, and is expected to be used for priority selection and management when designating additional cooling centers in the future.

• Korean Journal of Environmental Biology
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• v.41 no.4
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• pp.505-518
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• 2023

The key to invasive pest management lies in preemptive action. However, most current research using species distribution models is conducted after an invasion has occurred. This study modeled the potential distribution of the globally notorious sweet potato pest, the sweet potato weevil(Cylas formicarius), that has not yet invaded Korea using MaxEnt. Using global occurrence data, bioclimatic variables, and topsoil characteristics, MaxEnt showed high explanatory power as both the training and test areas under the curve exceeded 0.9. Among the environmental variables used in this study, minimum temperature in the coldest month (BIO06), precipitation in the driest month (BIO14), mean diurnal range (BIO02), and bulk density (BDOD) were identified as key variables. The predicted global distribution showed high values in most countries where the species is currently present, with a significant potential invasion risk in most South American countries where C. formicarius is not yet present. In Korea, Jeju Island and the southwestern coasts of Jeollanam-do showed very high probabilities. The impact of climate change under shared socioeconomic pathway (SSP) scenarios indicated an expansion along coasts as climate change progresses. By applying the 10th percentile minimum training presence rule, the potential area of occurrence was estimated at 1,439 km² under current climate conditions and could expand up to 9,485 km² under the SSP585 scenario. However, the model predicted that an inland invasion would not be serious. The results of this study suggest a need to focus on the risk of invasion in islands and coastal areas.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.2
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• pp.91-101
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• 2006

Researches on services of vehicles have been mainly focused on how to provide useful information and entertainment for an in-vehicle driver. However, the needs are appreciably increased for more advanced services that help drivers to check and manage their vehicles conveniently, without requiring drivers to attach to their vehicles. It is a sort of ubiquitous computing, providing an intelligent interactive services for human at any time and any where. In this paper, we present an intelligent vehicle information system to enable a driver to remotely diagnose and control a vehicle via CDMA communication network connected to the Internet. The system improves mobility for diagnosis and control of vehicle by implementing a cut and call back mechanism, which allows the vehicle terminal to have access to the information server on the Internet via CDMA call. No matter where the driver is, he can obtain the remote diagnosis and control services on the web browser without any additional application installation. Design methodology is introduced and evaluation results are analyzed for the CDMA-based intelligent vehicle information system. The experimental results show that the response time of the vehicle terminal to a web client request is 10.302 seconds at the beginning and 646.44ms thereafter. The average response time of CAN sensor node to a vehicle terminal request is 6.669ms.