• 아태비즈니스연구
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• 제13권4호
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• pp.45-59
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• 2022

Purpose - This study investigates the performance of investment strategies incorporating estimated stock market cycle based on a lead-lag relationship between business cycle and stock market cycle, thereby deriving empirical implications on risk management. Design/methodology/approach - The data period ranges from June 1953 to September 2022 and de-trended short rate, term spread, credit spread, stock market volatility are considered as major input variables to estimate business cycle and stock market cycle by applying probit model. Based on the estimated stock market cycle, two types of strategies are constructed and their performance relative to the benchmark is empirically examined. Findings Two types of strategies based on stock market cycle are considered: The first strategy is to long(short) on stocks when stock market stage is expected to be an expansion(a recession), and the second one is to long on stocks(bonds) when expecting an expansion(a recession). The empirical results show that the strategies based on stock market cycle outperforms a simple buy and hold strategy in both in-sample and out-of-sample investigation. Also the out-of-sample evidence suggests that the second strategy which is in line with asset allocation is more profitable than the first one. Research implications or Originality The strategies considered in this study are based on the estimated stock market cycle which only depends on a few easily available financial variables, thereby making easier to establish such a strategy. It implies that investors enhance investment performance by constructing a relatively simple trading strategies if they set their position on stocks or choose which asset class to buy conditioning on stock market cycle.

• 대한토목학회논문집
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• 제30권4A호
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• pp.343-352
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• 2010

최근에 탄산화 콘크리트 구조물의 정량적인 사용수명과 장기적인 성능을 확보하고 예측하기 위해서 확률론적인 내구성 해석 및 설계를 수행하는 연구가 많이 진행되고 있다. 이와 관련하여 콘크리트 구조물에 확률론적 내구성 설계 개념을 도입되고 있다. 본 논문에서는 탄산화 콘크리트 구조물의 통계적인 자료를 이용하여 Fick의 첫 번째 법칙에 근거한 탄산화 예측 모델에 적용하였으며, 이를 이용하여 확률론적 내구성 해석을 수행하였다. 이 예측모델에 관련된 설계변수인 $CO_2$ 확산계수, 대기중의 $CO_2$ 농도, $CO_2$ 흡착량, 시멘트 수화도 등의 영향을 검토하였다. 확률론에 기초한 탄산화 예측모델은 여러 환경에 위치한 콘크리트 구조물에 모니터링 자료를 이용하여 탄산화 깊이와 잔존수명을 예측하였다. 그 결과로 본 연구에서 합리적인 탄산화 예측모델을 이용한 적용 방법은 탄산화 콘크리트 구조물의 내구성 확보 및 구조물의 손상 개시시기를 예측하고 구조물을 유지 관리하기 위한 유연한 의사결정을 할 수 있을 것으로 판단된다.

• 한국간호교육학회지
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• 제29권4호
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• pp.450-468
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• 2023

Purpose: This study aimed to conduct a qualitative synthesis of workplace bullying experiences among nurses in Republic of Korea. Methods: Following the PRISMA guideline, a literature search was conducted using seven domestic and three international databases. Studies published in Korean or English from inception to December 31, 2022 were included. A meta-aggregation approach suggested by the Joanna Briggs Institute was used to synthesize the research findings. Results: Fourteen studies were included in this review. As a result of a data analysis of the selected studies, 199 subthemes and supporting illustrations were identified and grouped into 36 related categories. Based on the subthemes and categories, five synthesized findings were developed: (1) the individual and organizational causes of workplace bullying; (2) the various types of physical violence and psychological harassment; (3) the negative impact of workplace bullying and its effect on self-growth; (4) active and passive coping efforts in dealing with bullying; and (5) strategies for preventing bullying incidents. Conclusion: Based on the synthesized findings, four recommendations were made: (1) improving the challenging working conditions for nurses; (2) enhancing educational programs for new nursing graduates; and (3) promoting proactive responses from nursing managers in conjunction with an expansion of resilience training for nursing students. Finally, to address the issue of workplace bullying, (4) multi-center and multi-level research involving nursing organizations needs to be conducted.

• 한국초지조사료학회지
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• 제43권3호
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• pp.190-198
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• 2023

This study was conducted to calculate the damage of Italian ryegrass (IRG) by abnormal climate using machine learning and present the damage through the map. The IRG data collected 1,384. The climate data was collected from the Korea Meteorological Administration Meteorological data open portal.The machine learning model called xDeepFM was used to detect IRG damage. The damage was calculated using climate data from the Automated Synoptic Observing System (95 sites) by machine learning. The calculation of damage was the difference between the Dry matter yield (DMY)_normal and DMY_abnormal. The normal climate was set as the 40-year of climate data according to the year of IRG data (1986~2020). The level of abnormal climate was set as a multiple of the standard deviation applying the World Meteorological Organization (WMO) standard. The DMY_normal was ranged from 5,678 to 15,188 kg/ha. The damage of IRG differed according to region and level of abnormal climate with abnormal temperature, precipitation, and wind speed from -1,380 to 1,176, -3 to 2,465, and -830 to 962 kg/ha, respectively. The maximum damage was 1,176 kg/ha when the abnormal temperature was -2 level (+1.04℃), 2,465 kg/ha when the abnormal precipitation was all level and 962 kg/ha when the abnormal wind speed was -2 level (+1.60 ㎧). The damage calculated through the WMO method was presented as an map using QGIS. There was some blank area because there was no climate data. In order to calculate the damage of blank area, it would be possible to use the automatic weather system (AWS), which provides data from more sites than the automated synoptic observing system (ASOS).

• 대한한의학원전학회지
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• 제36권4호
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• pp.93-108
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• 2023

Objectives : This paper aims to study the characteristics of zhongfeng treatment by examining the eight principles of zhongfeng treatment in the Zhongfeng Jiaoquan of Zhang Shanlei along with Zhang Bolong's treatment of 'Yangxu Leizhongfeng[Yang deficiency pseudo Wind damage]' which is missing from the eight principles. Methods : The treatment methods in the Zhongfeng Jiaoquan was organized in the order of cause, characteristic, symptom, treatment, and precautions, in order to analyze features that were emphasized by Zhang in zhongfeng treatment. Results : First, treatment for bizheng is to 'open and close', then apply methods of 'qianyang jiangqi(潛陽降氣)' and 'zhenni huatan(鎭逆化痰)' while that for tuozheng is to 'lianyin yiye(戀陰益液)' accompanied by medicinals that 'qianzhen xutang(潛鎭虛陽)'. Second, treatment for ganyang shangnizheng is to 'qianzhen rougan', while for tanzian yongsezheng, one must 'dangdi(蕩滌)' for those who are strong in qi, 'xiehua(泄化)' for those who are weak in qi, while for those who have qinizheng[qi reverse syndrome] to 'shunqi(順氣).' Third, for deficiency in xinye and ganyin, one must 'yuyin yangxue[育陰養血]', while for deficiency in shenyin, one must first 'qianjiang shena[潛降攝納]' then slowly apply the method of 'ziyang shenyin[滋養腎陰]' if there is no phlegm turbidity. Fourth, in order to communicate the meridians and unfold collaterals, if the pathogen is external, apply the method of 'yangxue tongluo[養血通絡]', while if the pathogen is internal, calm by doing 'qianyang zhenni[潛陽鎭逆].' Fifth, in order to treat pseudo zhongfeng caused by yang deficiency, one must 'lianyin gutuo[戀陰固脫]' while using medicinals that 'jiangxiang[潛降]'. Conclusions : Treatment of zhongfeng in the Zhongfeng Jiaoquan diverged from 'wenjing sanhan', the usual approach to zhongfeng which sees it as external, and established the 'qianjiang zhenshe [潛降鎭攝]' treatment method based on the internal wind theory. It suggests a new Korean Medical pathology based on theories of Western medicine, and introduces eight principles in treating zhongfeng, which would influence the treatment of zhongfeng in the future.

• 응용통계연구
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• 제36권5호
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• pp.489-499
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• 2023

온라인 플랫폼을 통한 애널리스트 보고서의 공유가 가능해짐에 따라 애널리스트들이 생성한 보고서는 시장 참여자들 간 금융 정보 격차를 줄일 수 있는 유용한 도구가 되었으며, 애널리스트 보고서의 정량적 정보가 주식수익률 예측에 다수 활용되었다. 하지만 상대적으로 애널리스트 보고서 내 텍스트 정보의 주식수익률 예측 정보력에 대한 국내 자료 기반 연구는 상대적으로 많이 부족하다. 본 연구는 애널리스트 보고서에서 추출 가능한 텍스트로부터 어조 변수를 생성하여 주식수익률 예측에 정보력이 있는지를 검증하되, 기존 연구들의 선형모형 가정 기반 검정의 한계를 해결하고자 랜덤 포레스트 기반의 F-test를 사용하여 기업수익률 예측력을 검증하였다.

• Journal of Trauma and Injury
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• 제36권4호
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• pp.421-424
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• 2023

This case report presents the case of a 49-year-old man who presented to our level I trauma center after sustaining injuries in an altercation with local law enforcement in which he was shot with a less lethal bean bag and tased. In a primary survey, a penetrating left supraclavicular wound was noted in addition to a taser dart lodged in his flank. No other traumatic findings were noted in a secondary survey. Given hemodynamic stability, completion imaging was obtained, revealing a foreign body in the left lung, a left open clavicle fracture, a C5 tubercle fracture, a possible grade I left vertebral injury, and a left first rib fracture. Soft tissue gas was seen around the left subclavian and axillary arteries, although no definitive arterial injury was identified. The bean bag projectile was embedded in the parenchyma of the left lung on cross-sectional imaging. The patient underwent thoracotomy for removal of the projectile and hemostasis. A thoracotomy was chosen as the operative approach due to concerns about significant bleeding upon foreign body removal. A chest tube was placed and subsequently removed on postoperative day 5. The patient was discharged on postoperative day 7. At a 2-week outpatient follow-up visit, the patient was doing well. This case report is the first to describe this outcome for a drag-stabilized bean bag. Although law enforcement officers utilize bean bag projectiles as a "less lethal" means of crowd control and protection, these ballistics pose significant risk and can result in serious injury.

• International Journal of Computer Science & Network Security
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• 제23권11호
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• pp.128-132
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• 2023

Investment authorities are broad financial institutions that carefully manage investments on behalf of the national government using a long-term value development approach. To provide a stronger structure or framework for In-vestment Authorities to govern the distribution of funds to public and private markets, we've started research to create a blockchain-based prototype for managing and tracking numerous finances of such authorities. We have taken the case study of Oman Investment Authority (OIA) of Sultanate of Oman. Oman's wealth is held in OIA. It is an organization that oversees and utilizes the additional capital generated by oil and gas profits in public and private markets. Unlike other Omani funds, this one focus primarily on assets outside the Sultanate. The operation of the OIA entails a huge number of transactions, necessitating a high level of transparency and administration among the parties involved. Currently, OIA relies on various manuals to achieve its goals, such as the Authorities and Responsibilities manual, the In-vestment Manual, and the Code of Business Conduct, among others. In this paper, we propose a Blockchain based framework to manage the operations of OIA. Blockchain is a part of the Fourth Industrial Revolution, and it is re-shaping every industry. The main components of every blockchain are assets and participants. The funds are the major assets in the proposed study, and the participants are the various fund shareholders/recipients. The block-chain's transactions are all safe, secure, and immutable, and it's part of a trustless network. The transactions are simple to follow and verify. By replacing intermediary firms with smart contracts, blockchain-based solutions eliminate any middlemen in the fund allocation process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권12호
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• pp.3330-3344
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• 2023

This paper proposes an antenna performance prediction model in the autonomous driving radar manufacturing process. Our research work is based upon a challenge dataset, Driving Radar Manufacturing Process Dataset, and a typical AutoML machine learning workflow engine, Pycaret open-source Python library. Note that the dataset contains the total 70 data-items, out of which 54 used as input features and 16 used as output features, and the dataset is properly built into resolving the multi-output regression problem. During the data regression analysis and preprocessing phase, we identified several input features having similar correlations and so detached some of those input features, which may become a serious cause of the multicollinearity problem that affect the overall model performance. In the training phase, we train each of output-feature regression models by using the AutoML approach. Next, we selected the top 5 models showing the higher performances in the AutoML result reports and applied the ensemble method so as for the selected models' performances to be improved. In performing the experimental performance evaluation of the regression prediction model, we particularly used two metrics, MAE and RMSE, and the results of which were 0.6928 and 1.2065, respectively. Additionally, we carried out a series of experiments to verify the proposed model's performance by comparing with other existing models' performances. In conclusion, we enhance accuracy for safer autonomous vehicles, reduces manufacturing costs through AutoML-Pycaret and machine learning ensembled model, and prevents the production of faulty radar systems, conserving resources. Ultimately, the proposed model holds significant promise not only for antenna performance but also for improving manufacturing quality and advancing radar systems in autonomous vehicles.

• Journal of Information Science Theory and Practice
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• 제12권2호
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• pp.49-63
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• 2024

Information behavior played a significant role in minimizing the risks of the COVID-19 pandemic. When faced with such a situation, an individual needs information for decision-making and in order to determine the best course of action relating to their health. This study aims to explore information behavior during each phase of the COVID-19 pandemic in Indonesia, which is known for its close-knit collective culture. A sensemaking approach is used, which emphasizes the process individuals go through to understand their situation and give meaning to the information they are getting from their environment. Data was collected through in-depth interviews with 10 participants to obtain a description of their information behaviors during the pandemic. Data analysis was carried out using open, axial, and selective coding. We propose a sensemaking-based information behavior strategy framework for mitigating risk and reducing ongoing health crises. Changes in information behavior strategies, including search, prevention, and restriction of information exposure, were random at the beginning of the pandemic, but became more regular in later phases. This was influenced by the "knowledge gap fulfillment" and "use of local knowledge" among the participants throughout the pandemic. In conclusion, the participants developed a sensemaking process including an understanding of the pandemic situation and the risks that they faced. They used a number of information behavior strategies to prevent transmission, and their perception of the risks changed across the course of the pandemic, up til the situation began to be considered back to normal again in Indonesia.