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정상근 ( Sang Keun Chung ),오근영 ( Keun Young O ),최명수 ( Myung Soo Choi ) 전북대학교 의과학연구소 2002 全北醫大論文集 Vol.26 No.2
비정형 항정신병 약물은 정신분열병이나 다른 정신병적 증상이 있는 질환의 치료에 효과적으로 사용되나, 이로 인한 체중증가는 환자의 신체적, 정신적 건강의 해로운 요소로 작용할 뿐만 아니라, 정신과 질환의 치료에도 매우 좋지 않은 영향을 미칠 수 있고, 결국 환자의 삶의 질을 심각하게 손상시킨다. 따라서, 이러한 모순을 해결하기 위해 보다 적극적인 노력이 필요하다. 본 증례에서는 비정형 항정신병 약물중 흔히 사용되는 olanzapine에 의한 체중증가 사례와 이들 중 충분한 기간 동안 식사조절과 운동 및 행동변화에도 체중조절 효과가 없거나 이를 지속적으로 시행하지 못한 3명의 환자에서 topiramate를 사용하였고, 3명 모두에서 체중감소 효과가 있었음을 확인하였다. Excessive increase in body weight as a treatment-emergent effect of atypical antipsychotics has become the major concerns of clinical and research interest. These concerns are far greater than purely cosmetic, drug-induced weight gain has been identified as a major risk factor for various medical disorders, and higher weight may lead or reinforce to a stigma about psychiatric disorder, and may increase noncompliance and risk of relapse, subsequentely reinforce social withdrawal and impair quality of life of patients. Olanzapine is one of atypical antipsychotics, used to treatment of schizophrenia or other psychotic symptoms. But olanzapine-induced increasing appetite and weight gain are more common reported than typical antipsychotics and other atypical antipsychotics. Topiramate is an antiepileptic agent, which is being investigated as a mood-stabilizer or antidepressant, and is reported to be effective with weight losing. Base on above studies we investigate height, body weight and body mass index(BMI) in the cases of olanzpine-induced weight gain and weight control with topiramate, and estimate its usefulness.
문상근(Sang-Keun Moon),김성열(Sung-Yul Kim),우상민(Sang-Min Woo),김진오(Jin-O Kim) 대한전기학회 2011 대한전기학회 학술대회 논문집 Vol.2011 No.10
Electric Vehicles(EVs) and Plug-in Hybrid Electric Vehicles(PHEVs) which have the grid connection capability, represent an important power system issue of charging demands. Analyzing impacts EVs charging demands of the power system such as increased peak demands, developed by means of modeling a stochastic distribution of charging and a demand dispatch calculation. Optimization processes proposed to determine optimal demand distribution portions so that charging costs and demand can possibly be managed. The purpose of this paper is that to suggest a scenario of load leveling for a power system operator side and analyze impacts of the system. In case study results, the vehicles as regular load with time constraints, battery charging patterns and changed daily demand in the charging areas are investigated and optimization results are analyzed regarding cost and operation aspects by determining optimal demand distribution portions.
전기자동차의 충전부하 모델링 및 충전 시나리오에 따른 전력계통 평가
문상근(Sang-Keun Moon),곽형근(郭炯根),김진오(Jin-O Kim) 대한전기학회 2012 전기학회논문지 Vol.61 No.6
Electric Vehicles(EVs) and Plug-in Hybrid Electric Vehicles(PHEVs) which have the grid connection capability, represent an important power system issue of charging demands. Analyzing impacts EVs charging demands of the power system such as increased peak demands, developed by means of modeling a stochastic distribution of charging and a demand dispatch calculation. Optimization processes proposed to determine optimal demand distribution portions so that charging costs and demand can possibly be managed. In order to solve the problems due to increasing charging demand at the peak time, alternative electricity rate such as Time-of-Use(TOU) rate has been in effect since last year. The TOU rate would in practice change the tendencies of charging time at the peak time. Nevertheless, since it focus only minimizing costs of charging from owners of the EVs, loads would be concentrated at times which have a lowest charging rate and would form a new peak load. The purpose of this paper is that to suggest a scenario of load leveling for a power system operator side. In case study results, the vehicles as regular load with time constraints, battery charging patterns and changed daily demand in the charging areas are investigated and optimization results are analyzed regarding cost and operation aspects by determining optimal demand distribution portions.