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Kim, Hakhyun,Hwang, Heewon,Baek, Seonhyeok,Kim, Dohyun Elsevier 2018 Sensors and actuators. A, Physical Vol.277 No.-
<P><B>Abstract</B></P> <P>We report <I>for the first time</I> an electrolytic micropump based on an electrode chip fabricated on a printed circuit board (PCB), and compare its performance with that of a micropump based on an electrode chip fabricated using conventional microfabrication. Gold interdigitated (IDT) electrodes are patterned on a PCB to minimize ohmic loss during electrolysis. Custom-built acrylic fixtures are used to characterize pumping performance of various electrode chips with different electrode shapes and materials. Hydrogen and oxygen gas bubbles produced by electrolysis generate liquid flow inside a microchannel. As predicted by the theory of water electrolysis, the micropump produces flow rate increasing linearly with current at a wide range (1 mA–2 A). Our micropump yields the maximum flow rate of 31.6 ml/min and maximum backpressure of 547 kPa (at 34 μl/min), significantly high compared with the previous micropumps based on various actuation mechanisms including piezoelectric actuation, electroosmosis and phase change. The PCB-based micropump with a thick electroplated-gold electrode (0.43 μm) chip shows the overall best performance in terms of flow generation, power consumption and cost, compared with the PCB-based pump using an thin electroless-gold electrode (0.04 μm) and the pump using a microfabricated chip with a sputtered gold electrode (0.2 μm). We anticipate the PCB-based electrolysis pump will be used in portable lab-on-a-chip devices where an integrated microscale pressure source with low power consumption and simple fabrication is crucial.</P> <P><B>Highlights</B></P> <P> <UL> <LI> An electrolytic micropump based on PCB technology for portable lab-on-a-chip devices is designed, fabricated and characterized. </LI> <LI> A theoretical model for pump power consumption as a function of electrode geometry is proposed and experimentally verified. </LI> <LI> Flow rate and backpressure of the micropump are measured as a function of current using custom-built jigs and experimental setups. </LI> <LI> Performance of our micropumps is thoroughly compared with that of the micropump made using conventional microfabrication. </LI> <LI> Our PCB micropump with electroplated gold electrode yields exceptionally high flow rate up to 31.6 ml/min and backpressure up to 547 kPa. </LI> </UL> </P>
Evaluation of Hypertriglyceridemia as a Mediator Between Endocrine Diseases and Pancreatitis in Dogs
Kim, Hakhyun,Kang, Ji-Houn,Heo, Tae-Young,Kang, Byeong-Teck,Kim, Gonhyung,Chang, Dongwoo,Na, Ki-Jeong,Yang, Mhan-Pyo American Animal Hospital Association 2019 The Journal of the American Animal Hospital Associ Vol.55 No.2
Serum 25-hydroxyvitamin D concentrations in dogs with suspected acute pancreatitis
KIM, Dong-In,KIM, Hakhyun,SON, Purum,KANG, Ji-Houn,KANG, Byeong-Teck,YANG, Mhan-Pyo The Japanese Society of Veterinary Science 2017 The Journal of veterinary medical science Vol.79 No.8
<P>The present study aimed to determine whether circulating serum concentrations of 25-hydroxyvitamin D [25-(OH) D] differed between healthy dogs and dogs with acute pancreatitis (AP). Twenty-two healthy dogs and twenty client-owned dogs with AP were enrolled in the study. Serum concentrations of 25-(OH) D, blood ionized calcium (iCa), and serum C-reactive protein (CRP) were measured. Concentrations of serum 25-(OH) D and blood iCa in dogs with AP were significantly lower than those of healthy dogs, and serum concentrations of CRP in dogs with AP were significantly higher than those of healthy dogs. A significant difference in 25-(OH) D serum concentrations was observed between survivor and non-survivor dogs with AP. After resolution of clinical signs, concentrations of serum 25-(OH) D, blood iCa, and serum CRP did not differ compared to those before treatment. This study shows that dogs with AP exhibit decreased 25-(OH) D levels, which might be associated with calcium imbalances and mortality rate in canine AP.</P>
Kim, Hakhyun,Kang, Ji-Houn,Chang, Dongwoo The Korean Society of Veterinary Science 2018 大韓獸醫學會誌 Vol.58 No.2
A 13-year-old spayed female Miniature Schnauzer was presented with complaints of intermittent syncope. Pericardial effusion was confirmed based on the physical examination, thoracic radiographs and echocardiography. Subsequently, prompt pericardiocentesis was performed. Clinical abnormalities were immediately improved after pericardiocentesis. However, the clinical signs associated with acute collapse recurred. After the second pericardiocentesis, thoracic radiographs revealed pleural effusion, and the clinical signs resolved rapidly. The dog underwent pleural aspiration. Analysis of pleural fluid revealed almost similar features as the previous pericardial fluid. It was possible that a pericardial-pleural fistula was created during the pericardiocentesis. The pericardial and pleural effusion disappeared after the procedures.
김학현 ( Hakhyun Kim ),유환규 ( Hwankyu Yoo ),오하영 ( Hayoung Oh ) 한국정보처리학회 2023 정보처리학회논문지. 소프트웨어 및 데이터 공학 Vol.12 No.2
코로나 시대 이후 아파트 가격 상승은 비상식적이었다. 이러한 불확실한 부동산 시장에서 가격 예측 연구는 매우 중요하다. 본 논문에서는 다양한 부동산 사이트에서 자료 수집 및 크롤링을 통해 2015년부터 2020년까지 87만개의 방대한 데이터셋을 구축하고 다양한 아파트 정보와 경제지표 등 가능한 많은 변수를 모은 뒤 미래 아파트 매매실거래가격을 예측하는 모델을 만든다. 해당 연구는 먼저 다중 공선성 문제를 변수제거 및 결합으로 해결하였다. 이후 의미있는 독립변수들을 뽑아내는 전진선택법(Forward Selection), 후진소거법(Backward Elimination), 단계적선택법(Stepwise Selection), L1 Regularization, 주성분분석(PCA) 총 5개의 변수 선택 알고리즘을 사용했다. 또한 심층신경망(DNN), XGBoost, CatBoost, Linear Regression 총 4개의 머신러닝 및 딥러닝 알고리즘을 이용해 하이퍼파라미터 최적화 후 모델을 학습시키고 모형간 예측력을 비교하였다. 추가 실험에서는 DNN의 node와 layer 수를 바꿔가면서 실험을 진행하여 가장 적절한 node와 layer 수를 찾고자 하였다. 결론적으로 가장 성능이 우수한 모델로 2021년의 아파트 매매실거래가격을 예측한 후 실제 2021년 데이터와 비교한 결과 훌륭한 성과를 보였다. 이를 통해 머신러닝과 딥러닝은 다양한 경제 상황 속에서 투자자들이 주택을 구매할 때 올바른 판단을 할 수 있도록 도움을 줄 수 있을 것이라 확신한다. Since the COVID-19 era, the rise in apartment prices has been unconventional. In this uncertain real estate market, price prediction research is very important. In this paper, a model is created to predict the actual transaction price of future apartments after building a vast data set of 870,000 from 2015 to 2020 through data collection and crawling on various real estate sites and collecting as many variables as possible. This study first solved the multicollinearity problem by removing and combining variables. After that, a total of five variable selection algorithms were used to extract meaningful independent variables, such as Forward Selection, Backward Elimination, Stepwise Selection, L1 Regulation, and Principal Component Analysis(PCA). In addition, a total of four machine learning and deep learning algorithms were used for deep neural network(DNN), XGBoost, CatBoost, and Linear Regression to learn the model after hyperparameter optimization and compare predictive power between models. In the additional experiment, the experiment was conducted while changing the number of nodes and layers of the DNN to find the most appropriate number of nodes and layers. In conclusion, as a model with the best performance, the actual transaction price of apartments in 2021 was predicted and compared with the actual data in 2021. Through this, I am confident that machine learning and deep learning will help investors make the right decisions when purchasing homes in various economic situations.