In the case of a die-casting process, defects that are difficult to confirm by visual inspection, such as shrinkage bubbles, may occur due to an error in maintaining a vacuum state. Since these casting defects are discovered during post-processing operations such as heat treatment or finishing work, they cannot be taken in advance at the casting time, which can cause a large number of defects. In this study, we propose an approach that can predict the occurrence of casting defects by defect type using machine learning technology based on casting parameter data collected from equipment in the die casting process in real time. Die-casting parameter data can basically be collected through the casting equipment controller. In order to perform classification analysis for predicting defects by defect type, labeling of casting parameters must be performed. In this study, first, the defective data set is separated by performing the primary clustering based on the total defect rate obtained during the post-processing. Second, the secondary cluster analysis is performed using the defect rate by type for the separated defect data set, and the labeling task is performed by defect type using the cluster analysis result. Finally, a classification learning model is created by collecting the entire labeled data set, and a real-time monitoring system for defect prediction using LabView and Python was implemented. When a defect is predicted, notification is performed so that the operator can cope with it, such as displaying on the monitoring screen and alarm notification.

Iron deficiency is known to be a common nutritional disorder in many countries, especially among children, women of childbearing age and pregnant women. SUNACTIVE Fe-P80 is a new type of iron supplement that applies nanotechnlateology for the purpose of overcoming the disadvantages of food supplements. This study was conducted to investigate the potential adverse effects of a 28-day repeated oral dose of SUNACTIVE Fe-P80 in rats. SUNACTIVE Fe-P80 was administered once daily by gavage to Sprague-Dawley rats for 28 days at doses of 0, 500, 1,000, and 2,000 mg/kg/day. Additional recovery groups from the control and highdose groups were observed for a 14-day recovery period. At the scheduled termination, the animals were sacrificed, their organs weighed, and blood samples collected. There were no treatment-related effects in the context of clinical signs, body weight, food intake, ophthalmoscopy, urinalysis, necropsy findings, organ weights, and hematologic, serum biochemical and histopathological parameters at any dose tested. Under the present experimental conditions, the no-observed-adverse-effect level of SUNACTIVE Fe-P80 was ≥ 2,000 mg/kg/day in both the sexes, and no target organs were identified. Thus, the results suggest that SUNACTIVE Fe-P80 is relatively safe, as no treatment-related adverse effects were observed following a 28-day repeated oral dose experiment.

Over the past decade, platelet-rich plasma (PRP) and platelet derivatives have been widely investigated in the field of regenerative medicine due to their high concentrations of platelet- related growth factors, cytokines, and other proteins. Recently, many clinical studies have suggested their regenerative therapeutic efficacy in treating several disorders in medical field. However, their therapeutic applications are not well characterized in veterinary medicine as in human and experimental animals. This article reviews functional roles of platelets, scientific concepts, and clinical use of PRP and platelet derivatives in veterinary medicine. It also presents guidelines for veterinary applications of PRP in the future.

Various non-face-to-face services are being activated due to the influence of the Corona 19 virus around the world. However, unlike the rapid development of delivery services, social awareness of delivery services is causing many problems. Therefore, in this study, we analyze the quality attributes of delivery services from the consumer's point of view, and based on the results, we try to derive a direction for service improvement. In this study, quality factors were established through interviews and surveys with actual consumers, and quality attributes were classified through the Kano model and Timko’s customer satisfaction coefficient. “Attractive” is (‘Ease of ordering, Accurate delivery to the designated place’), “One Dimensional” is (‘Variety of payment methods, Accurate delivery on time, Accurate delivery of ordered food, Degree of non-deformation of packaging conditions, etc., Convenience of use time’), “Must be” is (‘Kindness of the delivery person’), “Reverse” is (‘provision of services, service response to order discrepancies’). This study has academic significance in that it compensated for the disadvantage of not being able to interpret the mathematical meaning of the Kano model with Teamco’s customer satisfaction coefficient. It also has practical implications in that it provides an indirect clue to future improvement directions.

본 연구는 자살을 생각하는 학생들의 대학생활 적응, 심리상담 실태, 그리고 자살생각 영향요인을 파악 하고자 한다. 편의표집이나 특정전공자들을 대상으로 할 경우 자살생각 대학생들의 실태를 파악하기 어려 운 제한점이 있다. 따라서 비임상군인 재학생 전수를 대상으로 실시한 실태조사 결과를 분석함으로써 대학 생 자살생각의 심각성을 파악하고자 했다. 본 연구는 서울 소재 A대의 <학생실태 및 요구도 조사>(2021년 5~6월 실시, 재학생의 74.8%인 4,129명 응답)의 데이터를 사용하였다. 본 연구는 응답결과 중에서 기본정 보, 정신건강, 상담, 학교생활에 관한 내용을 중심으로 ‘자살을 생각한 집단’과 ‘자살을 생각하지 않은 집단’ 간의 차이를 비교하여 분석하였다. 자살을 생각한 집단은 혼자 거주하는 비율이 높고, 흡연량이 많고, 스마 트폰 사용 장애를 겪는 나타났다. 그리고 그들은 입학만족도, 전공만족도, 자아존중감 및 교우관계에 대한 만족도가 낮았고, 학업스트레스가 높은 것으로 나타났다. 또한 그들은 교내보다는 교외에서 심리상담을 받 은 비율이 높은 것으로 나타났다. 한편, 자살생각에 영향을 미치는 요인으로는 성별, 학년, 흡연량, 입학만족 도, 학업스트레스, 자아존중감, 심리상담 여부 등인 것으로 확인되었다. 이런 연구결과를 토대로 본 연구는, 심리상담에 대한 접근성을 제고할 수 있는 상담시스템의 구축과 자살위험군에 대한 체계적인 관리시스템의 구축을 제언하였다.