• Journal of Preventive Medicine and Public Health
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• v.57 no.3
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• pp.298-303
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• 2024

Objectives: The aim of this study was to estimate drug prescription indicators in outpatient services provided at Iran Social Security Organization (SSO) healthcare facilities. Methods: Data on all prescribed drugs for outpatient visits from 2017 to 2018 were extracted from the SSO database. The data were categorized into 4 main subgroups: patient characteristics, provider characteristics, service characteristics, and type of healthcare facility. Logistic regression models were used to detect risk factors for inappropriate drug prescriptions. SPSS and IBM Modeler software were utilized for data analysis. Results: In 2017, approximately 150 981 752 drug items were issued to outpatients referred to SSO healthcare facilities in Iran. The average number of drug items per outpatient prescription was estimated at 3.33. The proportion of prescriptions that included an injection was 17.5%, and the rate of prescriptions that included an antibiotic was 37.5%. Factors such as patient sex and age, provider specialty, type of facility, and time of outpatient visit were associated with the risk of inappropriate prescriptions. Conclusions: In this study, all drug prescription criteria exceeded the recommended limits set by the World Health Organization. To improve the current prescription patterns throughout the country, it would be beneficial to provide providers with monthly and annual reports and to consider implementing some prescription policies for physicians.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.5
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• pp.957-966
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• 2020

According to the recent statistics of the National Industrial Security Center, about 80% of the confidential leak are caused by former and current employees in the case of domestic confidential leak accidents. Most of the information leak incidents by these insiders are due to poor security management system and information leak detection technology. Blocking confidential leak of insiders is a very important issue in the corporate security sector, but many previous researches have focused on responding to intrusions by external threats rather than by insider threats. Therefore, in this research, we design an internal information leak scenario to effectively and efficiently detect various abnormalities occurring in the enterprise, analyze the key indicators of the leak symptoms derived from the scenarios by using data analytics and propose a model that accurately detects leak activities.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.297-309
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• 2022

Taking into account the globalization of the economy and the intensification of European integration processes, it has been proved that an important part of evaluating the effectiveness of activity of public sector enterprises should be a comparative analysis of the overall operation environment, namely public procurement, economic environment and tax policy, with the relevant systems of other countries of the world. The indicators and components of international ratings "Doing Business", "Paying Taxes", "Benchmarking Public Procurement" have been studied. Different groups of indicators forming "Doing Business" and "Paying Taxes" in the context of the impact on public sector enterprises have been identified: those which fully comply with the need to evaluate the operating environment of public sector enterprises and those which should be used with restrictions, regarding the peculiarities of creating and functioning of public sector enterprises. A comparative analysis of the place of Ukraine, Lithuania and Slovenia among other countries of the world in accordance with the international rankings of "Doing Business", "Paying Taxes", "Benchmarking Public Procurement" have been made. It has been substantiated that the results of such comparative analysis will allow identifying risk areas, and relevant information can be used in developing of recommendations for improving the effectiveness of activity of public sector enterprises.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.267-273
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• 2015

For newly incoming technologies owing to the advancements in information and communications technology, the new form of information occurs due to the combination form of personal information. In turn, personal information which is combination with existing personal information is on the increase. It is difficult to equalize the method in order to analysis the degree of risk for personal information because it is qualitative method which is defined on the current Personal Information Protection Law. This dissertation presents the model to assess the degree of risk by using the IPA(Importance-Performance Analysis) after measuring the importance and the weighted value for the personal information based on the existing the method of risk assessment. Through the model suggested in this dissertation, the subjective judgement can be excluded, the combination of personal information can be assessed and the standard criteria which is used as the objective indicators from the quantitative degree of risk can be suggested.

• Journal of Information Technology Applications and Management
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• v.14 no.3
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• pp.95-113
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• 2007

To minimize IT operational risks and the opportunity cost for lost business hours. it is necessary to have preparedness in advance and mitigation activities for minimization of a loss due to the business discontinuity. There are few cases that banks have a policy on systematic management, system recovery and protection activities against system failure. and most developers and system administrators response based on their experience and the instinct. This article focuses on the mitigation model development for minimizing the incidents of disk unit in IT operational risks. The model will be represented by a network model which is composed of the three items as following: (1) the risk factors(causes, attributes and indicators) of IT operational risk. (2) a periodic time interval through an analysis of historical data. (3) an index or an operational regulations related to the examination of causes of an operational risk. This article will be helpful when enterprise needs to hierarchically analyze risk factors from various fields of IT(information security, information telecommunication, web application servers and so on) and develop a mitigation model. and it will also contribute to the reduction of operational risks on information systems.

• Economic and Environmental Geology
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• v.56 no.2
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• pp.155-166
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• 2023

Through COVID-19, the importance of supply chain management of raw material minerals has been maximized. In particular, supply chain management is important for rare metals, which are difficult to manage demand and supply, in order to secure raw materials for the parts and materials industry that Korea is actively promoting. In this study, a system was established and evaluated to select Critical minerals that need to respond to Korea's industrial structure and global risks by quantifying tangible and intangible risk factors. Global Supply Concentration, Supplying country risk, Policy Social Environment Regulation, Domestic Import Instability, Risk responsiveness, Market Scale, Demand Fluctuation and Economic Importance were evaluated as evaluation indicators. The degree of risk and risk impact were quantitatively measured using the criticality matrix-criticality level. After evaluating 40 types of minerals used in domestic new growth businesses, 15 types of Critical minerals(Li, Pt, Co, V, REE, Mg, Mo, Cr, Ti, W, C, Ni, Al, Mn, Si) in Korea were selected. The results are expected to be used to establish policies to strengthen resource security and to make decisions to form a company's raw material portfolio.

• Journal of Korean Society of Disaster and Security
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• v.16 no.2
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• pp.33-47
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• 2023

Under the "Act on Safety Control of Small Public Facilities (enacted in 2015)", each local government selects and conducts annual safety inspections for small public facilities. Among small public facilities, small bridges pose high risks and are heavily utilized by local residents, making them challenging to manage due to their large numbers and limited resources. Therefore, there is a need for a rational selection method that considers the management capacity of local governments, as well as the establishment of objective risk evaluation and maintenance planning for small hazardous facilities. In this study, we propose a selection method based on structural and functional classification of small bridges, considering the management capacity of local governments. Additionally, we present quantitative evaluation indicators for ten risk evaluation criteria, aiming to facilitate objective risk evaluation.

• Advanced Industrial SCIence
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• v.2 no.1
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• pp.21-38
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• 2023

An attempt has been made in this article to discuss the fundamentals of technical analysis of the stock market. A retail investor or trader may not have the wherewithal to source that kind of information. Technical analysis requires a candlestick chart only. Most of the brokers in India provide charting solutions as well. Studying the price action of a security or commodity or Forex generally indicates a price pattern. Prices react at certain levels and widely known as support and resistance levels. Since whatever is happening with the price of the security is considered to be a part of a pattern or cycle which has already played out sometime in the past, these studies help a keen technical analyst to identify with certain probability, the future movement of the price. Study of the candlestick patterns, price action, volumes and indicators offer the opportunities to identify a high probability trade with probable target and a stop loss. A trader or investor can take high probability trade or position and control only her losses.

• Journal of Korean Society of Disaster and Security
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• v.16 no.2
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• pp.1-13
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• 2023

As interest in urban safety has increased since COVID-19, various institutions have developed and used indicators that evaluate the safety city model. Yongsan-gu was ranked No. 1 in 2021 by Social Safety Index evaluation and was selected as the safest city in Korea. However, the Itaewon disaster in Yongsan-gu in 2022 caused many casualties. The study of indicators for evaluating cities' safety was necessary. This study aims to examine domestic and foreign safe city models and review the differences between each model and the indicators used to evaluate safe cities. As a result of collecting 11 safe city models and analyzing each evaluation index, safe city models can be classified into program-based safe city models, such as the World Health Organization's International safe community and the UN Office for Disaster Risk Reduction's International Safe city. Considering the diversification of threats to safety, it is reasonable to comprehensively consider digital security, health safety, infrastructure safety, personal safety, environmental safety, traffic safety, fire safety, crime safety, life safety, suicide, and infectious diseases when evaluating safe cities as evaluation parameters.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.17-25
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• 2023

The alarming global prevalence of Type 2 Diabetes Mellitus (T2DM) has catalyzed an urgent need for robust, early diagnostic methodologies. This study unveils a pioneering approach to predicting T2DM, employing the Extreme Gradient Boosting (XGBoost) algorithm, renowned for its predictive accuracy and computational efficiency. The investigation harnesses a meticulously curated dataset of 4303 samples, extracted from a comprehensive Chinese research study, scrupulously aligned with the World Health Organization's indicators and standards. The dataset encapsulates a multifaceted spectrum of clinical, demographic, and lifestyle attributes. Through an intricate process of hyperparameter optimization, the XGBoost model exhibited an unparalleled best score, elucidating a distinctive combination of parameters such as a learning rate of 0.1, max depth of 3, 150 estimators, and specific colsample strategies. The model's validation accuracy of 0.957, coupled with a sensitivity of 0.9898 and specificity of 0.8897, underlines its robustness in classifying T2DM. A detailed analysis of the confusion matrix further substantiated the model's diagnostic prowess, with an F1-score of 0.9308, illustrating its balanced performance in true positive and negative classifications. The precision and recall metrics provided nuanced insights into the model's ability to minimize false predictions, thereby enhancing its clinical applicability. The research findings not only underline the remarkable efficacy of XGBoost in T2DM prediction but also contribute to the burgeoning field of machine learning applications in personalized healthcare. By elucidating a novel paradigm that accentuates the synergistic integration of multifaceted clinical parameters, this study fosters a promising avenue for precise early detection, risk stratification, and patient-centric intervention in diabetes care. The research serves as a beacon, inspiring further exploration and innovation in leveraging advanced analytical techniques for transformative impacts on predictive diagnostics and chronic disease management.