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퇴직연금 적립금 규모의 성별 격차 분석: 영세사업장 확정기여형 가입자를 중심으로
박준범 ( Park Junbum ),정도영 ( Cheong Do Young ),이경희 ( Lee Kyonghee ) 한국여성경제학회 2021 여성경제연구 Vol.18 No.3
우리나라 노인의 소득 빈곤율은 OECD 국가 중 가장 높으며, 특히 여성의 노후빈곤은 심각한 상황이다. 고령사회로 진행하는 과정에서 다양한 연금정책이 추진되었으나 성별격차는 개선되지 못하고 있다. 본 연구에서는 퇴직연금사업자가 보유한 미시 데이터를 활용하여 30인 이하 영세사업체에 근무하는 확정기여형 퇴직연금 가입자의 적립금 규모에 대한 성별 요인의 영향을 실증분석 하였다. 다른 모든 조건이 동일할 때 여성의 적립금 규모가 남성에 비해 평균적으로 30% 정도 낮으며, 여성의 적립금 규모는 남성에 비해 종사상 지위, 근속기간 및 퇴직연금 가입기간에 더 민감하다는 결론을 얻었다. 실증 분석 결과를 바탕으로 정부 보조금 도입, 표준형 DC제도 활용, 이직 시 퇴직 일시금 수령 금지를 성별 격차 완화를 위한 정책적 대안으로 제시하였다. The poverty rate of older people in Korea is the highest among OECD countries, and that of older women is more serious. Various pension policies have been implemented but the gender gap has not improved. This study analyzed the gender effect on the accumulated assets of DC pension participants who work for small-scale firms. All other things being equal, women's accumulated assets were on average 30% lower than men’s and they are more sensitive to occupational status, tenure, and plan duration. The government subsidies, multi-employer contract-type DC, and the prohibition of cash-outs until full retirement were suggested as policy alternatives.
생명을 위협하는 뇌간 압박과 급성 수두증을 유발한 급성 소뇌염: 사망 증례보고
설재희(Jae Hee Seol,)박준범(JunBum Park,)이경연(Kyung Yeon Lee) 대한소아신경학회 2017 대한소아신경학회지 Vol.25 No.3
Acute cerebellitis is a rare inflammatory disorder that occurs most frequently in child ren. The typical clinical course of acute cerebellitis is benign. However, in some cases of acute cerebellitis, fulminant cerebellar swelling with obliteration of the fourth ventricle causes brain stem compression and acute obstructive hydrocephalus, which can be life-threatening and require emergent neurosurgical procedures. We describe the case of a 4-year-old girl whose acute cerebellitis caused brain stem compression, acute obstructive hydrocephalus, and death. The patient was admitted to the emergency department because of a severe headache that had persisted for 5 days. Neurological examinations revealed no specific abnormality. Brain magnetic resonance imaging (MRI) demonstrated diffuse swelling and high signal intensity lesions in the cerebellar hemispheres and vermis, obliteration of the fourth ven tricle, and brain stem compression on T2-weighted images in conjunction with mild hydrocephalus. Cerebrospinal fluid (CSF) analysis revealed white blood cell and red blood cell counts of 180/mm3 and 0/mm 3 , respectively; protein and glucose con centrations of 263.6 mg/dL and 37 mg/dL, respectively; and negative culture results. Despite aggressive treatment, the patient developed sudden cardiorespiratory arrest on day 2. Although emergency neurosurgery was performed after cardiopulmonary resuscitation, her condition progressed to brain death, and she died on day 29. This case suggests that timely and appropriate neurosurgery should be actively considered to relieve increased intracranial pressure in the early phases of acute cerebellitis.
Deep Learning-based Human Action Recognition to Prevent Industrial Workplace Accidents
Jongmok Lee(이종목),Changyun Choi(최창윤),Junbum Park(박준범),Sungmin Kim(김성민),Seokman Sohn(손석만),Seungchul Lee(이승철) 대한기계학회 2021 대한기계학회 춘추학술대회 Vol.2021 No.4
A significant number of accidents at industrial workplaces such as power plants have always been a serious social issue. Various solutions were sought to prevent such problems, but these accidents constantly occurred at unexpected times and places. This paper proposes a human action recognition method to resolve this problem using images taken from the surveillance and security cameras (or CCTV) at the industrial workplace. Video frames are continuously gathered in real-time from CCTV, which is installed throughout the workplace. Then extracted skeleton data from workers feeds into a deep learning model to predict workers’ action. The goal is to check if the predicted behavior belongs to the predetermined risky class and then determine whether that worker is safe or not. In detail, the OpenPose method was applied to extract 2D skeleton data from human, and object detection and super-resolution were employed to improve the performance by enhancing the visibility of human within image frames. The Graph Convolutional Network (GCN) method is widely used in deep learning when dealing with locational-related information. Therefore, this paper used DGNN model, which used GCN method to predict human action from skeleton data. 3D NTU public datasets were processed in 2D and then trained with 2D DGNN models. The model showed 97.4% accuracy on tests, targeting five risky behaviors. We plan to conduct transfer learning on the pre-trained model with skeleton data obtained by filming selected behaviors with CCTV and then test it in the actual industrial workplace.
권호진,박준범,김재형 광주대학교 산업기술연구소 2002 産業技術硏究 Vol.16 No.-
Phytoremediation은 토양오염을 정화하기 위하여 식물을 이용하는 방법이다. 식물은 금속, 살충제, 폭발물, 기름 등의 오염물질을 정화시킬 수 있으며, 오염물질이 바람, 비, 지하수 등에 의하여 다른 장소로 이동하는 것을 억제하기도 한다. 식물은 자연적으로 성장하며, 식물을 이용한 정화작업을 하는 데 있어서 상대적으로 장비나 인력이 덜 필요하다. Phytoremediation은 오염토양을 굴착하거나 지하수를 양수하지 않고서도 오염된 토양을 정화할 수 있으며, 작업자가 직접 오염물질에 노출되는 것을 막아주기도 한다. Phytoremediation은 여러 지역에서 성공적으로 연구 중에 있으며, 여러 Superfund 현장에서 실제 적용되고 있다. Closed Phytoremediation uses plants to clean up pollution in the environment. Plants can help clean up many kinds of pollution including metals, pesticides, explosives, and oil. The plants also help prevent wind, rain, and groundwater from carrying pollution away from sites to other areas. EPA uses Phytoremediation because it takes advantage of natural plant processes. It requires less equipment and labor than other methods since plants do most of the work. Trees and plans can make a site more attractive as well. The site can be cleaned up without removing polluted soil or pumping polluted groundwater. This allows workers to avoid contact with harmful chemicals. Phytoremediation has been successfully tested in many locations, and is being used at several Superfund sites.
복막 평형 검사에 영향을 주는 인자 및 시행시기에 관한 분석
정항재,조규향,박준범,배성화,김영진,도준영,윤경우 대한신장학회 1999 Kidney Research and Clinical Practice Vol.18 No.4
The peritoneal equilibration test(PET) is used as a tool for determining the characteristics of the peritoneal membrane. Initial PET is recommended at least 1 month after peritoneal dialysis, but PET after 1 month may be difficult to perform on an out- patients basis. Two standard PETs(D/P4Cr) were performed in 60 CAPD patients(DM:non DM=22:38). Initial PETs, within one week after starting CAPD and follow up PETs, at least 3 months after CAPD were performed. The initial PET values were compared with subsequent PET values. Clinical data (age, sex, body surface area, BMI, presence of diabetes mellitus, ascites) and laboratory indices(serum albumin, dialysate creatinine clearance, KT/V, protein catabolic rate) were compared with the results of the PETs. In initial PET result, there was negative correlation between D/P4Cr and serum albumin(r=-0.522, p$lt;0.001 N=60). There was no significant difference between initial and follow up(mean±S.D.:8.84±5.2months after CAPD) D/P4Cr(0.68±0.14 vs 0.68±0.13). But with pge of time, delta D/P4Cr and delta serum albumin were also negatively correlated (r=-0.459, p$lt;0.001). According to the linear regression analysis, the factor significantly associated with D/P4Cr was serum albumin(coefficients -0.111). In conclusion, serum albumin level is the most important predictor of the peritoneal membrane transport characteristics, and it seems that the timing of PET does not matter, rather the changes of with time are strongly correlated with the changes of the serum albumin level.