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민윤정(Younjeong Min),서주영(Jooyoung Seo),최병주(Byoungju Choi) 한국정보과학회 2005 한국정보과학회 학술발표논문집 Vol.32 No.2
소프트웨어의 품질 향상을 위해서는 무엇보다도 프로세스의 개선이 필요하다는 인식이 증대되고 있다. 그 중에서도 실질적으로 프로덕트의 품질과 직결된 테스트 프로세스의 개선이 무엇보다 시급한데, 그러기 위해서는 테스트 프로세스의 현재 상태를 파악하고 분석하는 과정이 선행되어야 한다. 본 논문에서는 테스팅 관점에서 소프트웨어의 품질을 고려하여 개발된 SETP(Simple and Easy Test Process) 핵심 모델과, 이를 바탕으로 테스트 프로세스를 평가하고 분석하는 자동화 도구 Legba를 제안한다.
( Younjeong Lee ),( Kyung-jin Min ),( Sanghoon Lee ),( Jin Hwa Hong ),( Jae Yun Song ),( Jae-kwan Lee ),( Nak Woo Lee ) 대한산부인과학회 2018 대한산부인과학회 학술대회 Vol.104 No.-
Objective: To prove that making distinction between the cytology of Atypical Squamous Cells of Undetermined Significance (ASCUS) and Low-grade squamous intraepithelial lesion (LSIL) or between Atypical Squamous Cells cannot exclude HSIL (ASC-H) and High-grade Squamous Intraepithelial Lesion (HSIL) in clinical practice may not be necessary. Methods: Including the referrals from local hospitals, we investigated women who visited Korea university medical center, Guro hospital for cervical cancer screening from February 2004 to December 2014. Through chart review, we collected data of cervical biopsy of four groups: ASCUS, LSIL, ASC-H, and HSIL. Using Cochran-Mantel-Haenszel statistics method, we compared the pathologic results of cervical biopsy of ASCUS group to LSIL group, and ASC-H group to HSIL group in the same manner. Results: Of 216,723 women enrolled for Papanicolaou (Pap) smears, after excluding the results of cervical biopsy other than WNL, CIN1, CIN2, CIN3/CIS, and cervical cancer, total 855 women were included in this study. There were 161 women with cytology result of ASCUS, 425 women with LSIL, 22 women with ASC-H, and 247 women with HSIL. According to the Cochran-Mantel-Haenszel statistics, the p-value for the comparison between ASCUS group and LSIL group was 0.00068 (p< 0.05), which was statistically significant by proving differentiation between two groups. Conversely, the p-value for the association between ASC-H and HSIL was 0.26834 (p >0.05) which accepted the hypothesis of the study by not distinguishing two groups. Overall, the results of cervical biopsy between ASCUS and LSIL did show differentiation, yet ASC-H and HSIL did not have significant difference. Conclusion: Although the cytology results of ASCUS and LSIL are necessary to be distinguished, making distinction between the cytology of ASC-H and HSIL in the clinical practice may not be necessary. Further studies of comparing cytology of these groups may be helpful to simplify the colposcopy results in the real world.
Monitoring Cattle Disease with Ingestible Bio-Sensors Utilizing LoRaWAN
Heejin Kim,Younjeong Min,Byoungju Choi 한국정보기술학회 2018 한국정보기술학회논문지 Vol.16 No.4
Livestock diseases lead to the decline in farm income by causing lower farm productivity, chronic disease developments or even culling. Therefore, monitoring the health condition of livestock in real-time to predict and swiftly respond to any diseases is very important because it directly affects the profit and productivity of farms. For an effective disease prediction system, we propose a cattle disease monitoring method with orally administered bio-sensors utilizing Long Range Wide-Area Network(LoRaWAN). In addition, we provide case analysis by applying this prediction system on cattle. The bio-sensor used in the proposed method is orally administered and settles in the rumen, allowing for a stable measurement of core body temperature without the interference of external environment. With the proposed method, cattle disease can be monitored on a regular basis and thus enable swift response to any disease occurrences. We expect this method to contribute in lowering the cost of economic damage caused by livestock diseases.
AI Anaalysis Method Utilizing Ingestible Bio-Sensors for Bovine Calving Predictions
Heejin Kim,Younjeong Min,Changhyuk Choi,Byoungju Choi 한국정보기술학회 2018 한국정보기술학회논문지 Vol.16 No.12
Parturition is an important event for farmers as it provides economic gains for the farms. Thus, the effectivemanagement of parturition is essential to farm management. In particular, the unit price of cattle is higher than otherlivestock and the productivity of cattle is closely associated to farm income. In addition, 42% of calving occurs inthe nighttime so accurate parturition predictions are all the more important. In this paper, we propose a method thataccurately predicts the calving date by applying core body temperature of cattle to deep learning. The bodytemperature of cattle can be measured without being influenced by the ambient environment by applying an ingestiblebio-sensor in the cattle’s rumen. By experiment on cattle, we confirmed this method to be more accurate forpredicting calving dates than existing parturition prediction methods, showing an average of 3 hour 40 minute error.This proposed method is expected to reduce the economic damages of farms by accurately predicting calving timesand assisting in successful parturitions.
Validation of Methods Based on PCR for the Detection of GM Events in South Korea
Young Rae Cho,Min Ki Shin,Eun-ju Song,Jun Hyun Sung,Younjeong Han,Min Young Bae,Ji Hyun Yoo,Sunmi Kim,Jyongeun Myung,Jisoo Hong,Sewook Park,Chohee Kim,Dongmi Choi,Mee Kyung Kim 한국식품영양과학회 2019 한국식품영양과학회 학술대회발표집 Vol.2019 No.10