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무산소조에서 고농도 미생물을 이용한 하수고도처리공정의 처리특성
손동훈,임봉수,박혜숙,Son, Dong-Hun,Lim, Bong-Su,Park, Hye-Sook 한국물환경학회 2004 한국물환경학회지 Vol.32 No.2
This study was accomplished to develope an advanced wastewater treatment process using high MLSS in anoxic tank aimed to improve nutrient removal and to reduce wasting sludge. It was operated with 4 Modes with varing solid concentration and internal recycle ratios. Mode I, II, III was operated 1.0~1.5% MLSS concentration at anoxic tank with 50% sludge recycle rate, however, each internal recycle rate were 100%, 200%, 300% and Mode IV was operated 1.5~2.0% MLSS concentration at anoxic tank with 50% sludge recycle rate and 100% internal recycle rate. The COD removal efficiency didn't show any big difference from Mode I to IV. The average COD removal rate was over than 90%. The T-N removal rate was 73%, the highest rate in all mode. The 36% of SCOD is used for the denitrification and phosphorus release in the anoxic tank. Specific denitrification rate was 3.5mg $NO_3{^-}-N/g$ Mv/hr and denitrification time was 0.7hr. As MLSS concentration is higher in anoxic tank as denitrification time would be shorter. The T-P removal rate was average 70%. The phosphorus release accomplished from the anoxic tank because the anaerobic condition was prevalent in the anoxic due to the prompt completion of denitrification. Sludge production was 0.28 kgVSS/kg $BOD_{removed}$ under the 1.5% MLSS and 17 day SRT. It is prominent result which has 40% sludge reduce comparing with traditional activate sludge system.
손동훈(Dong Hun Son),장진구(Jhin Goo Chang),송후림(Hoo Rim Song),이수영(Su Young Lee),이승훈(Seung Hoon Lee),방수영(Soo-Young Bhang),이미선(Mi-Sun Lee),김현수(Hyun-Soo Kim),홍민하(Minha Hong) 대한사회정신의학회 2021 사회정신의학 Vol.26 No.2
연구목적 : 청소년 범죄에서 정신건강의 문제와 범죄가 관련성이 높다는 것은 잘 알려져 있지만 국내에서는 아동청소년 범죄자들의 정신건강에 관한 연구가 거의 없다. 뿐만 아니라 아동청소년정신건강 영역에서 기계학습을 적용한 연구는 아직 초기단계이다. 본 예비연구에 서는 여자청소년 재소자들에서 정신건강 문제 중 우울증의 예측에 기계학습 알고리즘을 적용하여 적합한 지를 알아보고자 한다. 방 법 : 대상자는 청주소년원에 재소중인 87명의 여자청소년을 대상으로 하였다. 대상자들에게 설문지 패키지 (인구학적 정보, 범죄관련 정보, 자기보고척도 설문지(아동기부정적경험 설문지, 벡우울척도)를 배부하여 정보를 수집하였다. 기계학습 기법을 이용하여 수집된 재소자들의 기본 정보를 바탕으로 우울증을 예측할 수 있는 6개의 모델(Logistic regression, Random forest, Supportive vector machine, Decision tree, Nearest neighbor, Adaboost)을 생성하여 각 모델간의 예측 성능을 비교해 보았다. 결 과 : 대상자를 벡우울척도(절단점 13)로 군을 분류한 결과 정상군 18명(21%)과 우울증군 69명(79%)이었다. 6개 모델의 우울증 예측 정확도는 Logistic regression 81.8%, Random forest 81.8%, Supportive vector machine 68.18%, Decision tree 72.7%, Nearest neighbor 77.3%, Adaboost 63.6%였다. 그중에서 Random forest 모델의 AUC score는 0.75로 다른 모델들과 비교하여 가장 높았다. 결 론 : 본 연구는 재소청소년의 정신건강에 중점을 두어 현황을 파악하고,우울증의 예측에 기계학습 기법을 적용을 하여 높은 정확도를 확인하였다는 점에서 의의가 있다. 또한 취약계층의 정신건강 영역에 기계학습 기법을 적용하여 관리 및 감시에 적용 가능성에 대한 근거를 제공하였다. Objectives : It is well known that mental health problems and crime are highly related to youth crime, but there is little research on the mental health of young offenders in Korea. Furthermore, research on the application of machine learning in the mental health of children and adolescents is still novel. This preliminary study aims to investigate whether it is appropriate to apply machine learning algorithms to predict depression among female adolescent inmates. Methods : The subjects were 87 young females in Cheongju Juvenile Center. A questionnaire was distributed to the subjects to gather their demographic information and crime-related information, as well as their adverse childhood experiences and Beck depression inventory scores using self-reported scale questionnaires. Based on the collected information, six models (logistic regression, random forest, supportive vector machine, decision tree, nearest neighbor, Adaboost) that can predict depression were created to compare the predictive performance between models using machine learning techniques. Results : Results showed that 29 victims (25.7%) met the criteria of PTSD and 19 victims (16.8%) met the rigid criteria of PTSD. But, according to the subscales, 41 victims (36.3%) were diagnosed as PTSD. Victims with PTSD had more serious depression, anxiety, sleep disturbance, anger, social withdrawal and life stresses. Conclusion : This study identified the current mental health status of female inmates with high accuracy by applying machine learn-ing techniques to predict depression. The applicability of machine learning techniques to the management and surveillance of mental health in vulnerable groups was also highlighted.
손동훈(Dong-Hun Son),강광희(Kwang-Hee Kang),최지호(Ji-Ho Choi),박도훈(Do-Hoon Park) 한국소음진동공학회 2014 한국소음진동공학회 학술대회논문집 Vol.2014 No.10
The development of a vehicle-mounted radar to detect the location of enemy artillery is mainly mounted during operation to the mobility of the equipment and efficiency of utilization range. It is equipped with an electronic device responsible for the operation of the radar system. El ectronic equipments is performed functionality imparted without an error-specific in spite of disturbances such as vibration / shock caused by vehicle movement. Therefore, vibration / shock resistance is held to prevent damaging from vibration / shock generated from the outside environment during operation. In addition, a standardized and specified cabinet structure equipped with electronic equipment is placed in shelter to ensure additional safety for vibration / shock. In this study, it is evaluated by analytical method with vibration / shock resistance of the cabinet structures for ensuring structural safety factor is applied to the aluminum. It is verified the reliability of the structure and structural dynamics to verify by calculated natural frequencies adding the weight of the cabinet structure and the structural displacement and stress results confirmed with vibration / shock caused by the vehicle movement.
무산소조에서 고농도 미생물을 이용한 하수고도처리공정의 처리특성
손동훈 ( Son Dong Hun ),임봉수 ( Im Bong Su ),박혜숙 ( Park Hye Sug ) 한국물환경학회 2004 한국물환경학회지 Vol.20 No.1
This study was accomplished to develope an advanced wastewater treatment process using high MISS in anoxic tank aimed to improve nutrient removal and to reduce wasting sludge. It was operated with 4 Modes with varing solid concentration and internal recycle ratios. Mode Ⅰ, Ⅱ, Ⅲ was operated 1.0 - 1.5% MLSS concentration at anoxic tank with 50% sludge recycle rate, however, each internal recycle rate were 100%, 200%, 300% and Mode Ⅵ was operated 1.5 - 2.0% MLSS concentration at anoxic tank with 50% sludge recycle rate and 100% internal recycle rate. The COD removal efficiency didn`t show any big difference from Mode Ⅰ to Ⅵ. The average COD removal rate was over than 90%. The T-N removal rate was 73%, the highest rate in all mode. The 36% of SCOD is used for the denitrification and phosphorus release in the anoxic tank. Specific denitrification rate was 3.5㎎ NO₃^(-)-N/g M v h and denitrification time was 0.7hr. As MLSS concentration is higher in anoxic tank as denitrification time would be shorter. The T-P removal rate was average 70%. The phosphorus release accomplished from the anoxic tank because the anaerobic condition was prevalent in the anoxic due to the prompt completion of denitrification. Sludge production was 0.28 ㎏VSS/㎏ BOD_(removed) under the 1.5% MLSS and 17 day SRT. It is prominent result which has 40% sludge reduce comparing with traditional activate sludge system.