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박종필,정민수 한국경영정보학회 2024 경영정보학연구 Vol.26 No.4
Globally, prices are soaring, and among these, agricultural product prices are experiencing significant increases. Agricultural products are essential for human survival and have a direct impact, making this a highly sensitive issue. This problem has been further exacerbated by the COVID-19 pandemic and the Ukraine-Russia war, leading to even greater price hikes. Consequently, this situation places a considerable burden not only on consumers but also on the companies that process and produce these agricultural products. In particular, South Korea, a country with a high dependency on imports, relies on foreign markets for many agricultural products. However, despite this reliance, there is a lack of research on predicting the prices of imported agricultural products. For this reason, this study implements an AI model that predicts the retail prices of final products based on fluctuations in the prices of imported agricultural products, focusing on key research questions (RQs) and the distribution process. In addition, it examines the impact of global issues such as supply chain disruptions caused by COVID-19 and the Ukraine-Russia war on price inflation. In this study, the top three imported agricultural products―corn, wheat, and soybeans―are selected as key imported agricultural items, and the prediction model is implemented focusing on the processed foods most commonly consumed in daily life that are manufactured from these products. At this time, key variables are added by taking into account the distribution and manufacturing processes involved in the processing of agricultural products. Specifically, the relationships between these variables are analyzed through correlation analysis, and a prediction model is implemented using big data analysis to select the model with the highest prediction accuracy. In this study, the VAR model showed the highest prediction accuracy among machine learning models, while the LSTM model demonstrated the highest accuracy among deep learning models. In conclusion, the academic implications of this study demonstrate that the impact of the international commodity market and global trade on the production and distribution of domestic companies can be scientifically analyzed and proposed through AI models. Additionally, the study systematically identified and explained the raw material supply disruptions caused by the COVID-19 pandemic from an academic perspective. Furthermore, the practical implications of this study for companies are significant. By utilizing this research, companies can identify how price fluctuations in imported agricultural products affect the pricing of final products. It allows them to proactively respond to changes in the prices of final products by applying the forecasting model. Additionally, companies can confirm the relationship between the prices of imported agricultural products and the retail prices of final products, gaining a clearer understanding of the costs incurred during domestic and international distribution processes. It can be used to drive innovations in the distribution structure.
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저비용 고성능 광촉매를 활용한 콘크리트 이형박리제 개발
박종필,황병일,유병현,이동규 한국산학기술학회 2020 한국산학기술학회논문지 Vol.21 No.11
최근 미세먼지 및 배기가스로 인한 환경문제를 해결하고자 도로구조물의 광촉매 적용이 시도되고 있다. 이에 본 연구에서는 폐수슬러지에서 제조 후 재활용된 저비용 고성능 광촉매(GST)의 혼합 및 분산방안을 검토하고, 질소산화물(NOx) 제거 성능을 최종 평가하여 저비용 고성능 광촉매를 활용한 콘크리트 이형박리제를 개발하고자 한다. 광촉매 적용을 위한 분산방안을 검토하기 위해 분산된 시료를 4주간 옥외폭로하여 분리유무를 통한 안정성을 평가한 결과, 분산형 증점제 사용량 20 % 적용시 층분리 및 침전현상 없이 안정적인 상태를 보였다. 저비용 고성능 광촉매를 활용한 이형박리제를 거푸집에 도포시켜 탈형한 시편의 NO 및 NOx 제거율은 Plain 대비 200~400 %의 우수한 효과를 나타내었다. 저비용 고성능 광촉매를 활용한 콘크리트 이형박리제의 성능을 증진시키기 위해서는 나노사이즈인 광촉매의 분산성 향상 및 사용량 증가가 필요할 것으로 사료된다. 또한, 저비용 고성능 광촉매를 활용한 이형박리제를 도로구조물 및 노출콘크리트에 사용하게 되면 NOx 제거효율을 증가시킬 수 있을 것으로 판단된다. Recently, the application of a photocatalyst to road structures is being attempted to solve environmental problems caused by fine particulate matter and automobile exhaust. The purpose of this study was to develop a release agent with GST (low-cost, high-performance photocatalyst produced from wastewater sludge). For this, the method of mixing and dispersing GST with the release agent was used first, and the removal performance of nitrogen oxide (NOx) was then checked. The best performance without a precipitation reaction was achieved using a stabilizing agent at 20 % in an outdoor exposure test for four weeks. The NO and NOx removal rate of the specimen demolded by applying the GST release agent developed in this study showed excellent effects of 200 to 400 % compared to the Plain material. To increase the performance of the GST release agent, it is necessary to improve the dispersibility of GST in the release agent and increase the amount of the nano-sized photocatalyst. In addition, the use of GST release agent in road structures and exposed concrete is expected to increase the NOx removal efficiency.
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현장검안 시 외상성 머리안출혈 진단을 위한 근적외선 분광분석기의 유용성에 대한 고찰
박종필,이탁수,최민성,양경무,박정우,원유진,최승규,이경홍,김정환,강채린,최승우 대한법의학회 2020 대한법의학회지 Vol.44 No.1
Near-infrared spectroscopy is a device used to determine whether traumatic intracranial hemorrhage has occurred and is primarily used for screening in emergency situations. In this study we examined the applicability of this equipment in postmortem inspection. This study included 124 autopsy cases and 59 postmortem inspection cases performed in the National Forensic Service from July 2017 to October 2018. We carried out the test using Infrascanner Model 2000 (Infrascan Inc.). Autopsy cases were divided into four groups (epidural hemorrhage or subdural hemorrhage group, traumatic subarachnoid hemorrhage or cerebral contusion group, nontraumatic intracerebral hemorrhage group, and control group) and analyzed. There was no difference in the test results according to the presence and type of intracranial hemorrhage. The possibility that variables related to postmortem change affected the test results was considered. In conclusion, this study confirmed that nearinfrared spectroscopy is not suitable for the detection of traumatic intracranial hemorrhage in postmortem inspection.
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B2C SNS 사용에 있어서 촉진인자(Enablers)와 억제인자(Inhibitors) 규명과 영향에 관한 연구: 듀얼펙터접근으로
박종필,최영은,이은곤 엘지씨엔에스 2012 Entrue Journal of Information Technology Vol.11 No.2
Various streams of IS research has been focused extensively on the factors that enable IS adoption and usage. Relatively, much less attention to what perceptions inhibit IS adoption and usage. This study presents a theoretical model of enablers and inhibitors in B2C SNS usage, using a dual-factor model of technology usage. For research methodology, two steps have been undertaken to empirically test the research model. First, we conducted open-ended question test to extract enablers and inhibi-tors of B2C SNS usage. Then, it is also empirically tested using data gathered from 117 B2C SNS users through online sur-vey. Through the empirical evidence, we find that enablers have positive effects on usage intention. On the contrary, inhibitors have negative effects on usage intentions, as well as on enablers. 정보기술 관련 연구들의 주된 흐름 중 하나는, 정보기술의 수용 혹은 사용과 관련해 소위 촉진인자에 주로 초점을 맞추어 수행되어 왔다. 그러나, 상대적으로 정보기술 수용과 사용을 저해하는 억제요인과 관련한 연구에 대해서는 적은 관심을 가져 왔다. 이에, 본 연구에서는 듀얼펙터접근으로, B2C 소셜네트워크 사용과 관련해 촉진인자와 억제인자의 규명과 그 영향에 대해 살펴보았다. 이를 위해, 우선 개방형 설문방식으로 촉진인자와 억제인자들을 추출하고, 117명의 실제 B2C 소셜네트워크 이용자들을 대상으로 실증적으로 검증해 보았다. 분석 결과, 촉진인자들은 B2C SNS 사용의도에 긍정적인 영향을 미쳤다. 그러나, 이와는 대조적으로 억제인자는 B2C SNS 사용의도뿐만 아니라, 촉진인자에까지 부정적인 영향을 미치는 것으로 밝혀졌다.
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