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您的检索式：作者名="Choon Lim Ho"
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| 1 | Pancreatic pseudocystocolonic fistula treated without surgical or endoscopic intervention显示文摘We report here a case of pancreatic pseudocystocolic fistula that was treated without surgical or endoscopic intervention.A 76-year-old woman,presenting with a fever and epigastric pain,was referred to our institution.Three months prior to this admission,the patient had been admitted to the hospital for acute pancreatitis.Abdominal computerized tomography(CT)revealed a 9 cm pseudocyst containing air,and a fistular opening was observed via colonoscopy.After colonoscopy,the abdominal pain was slightly improved,the fever subsided and laboratory results showed decreased C-reactive protein levels.The observed improvement was likely due to the cleansing of the bowel,which induced spontaneous drainage from the pseudocyst into the colon.Antibiotic therapy was administered and daily bowel cleansing was performed using a polyethylene glycol solution.After three weeks,a follow-up CT revealed that the size of the pseudocyst had decreased significantly from 9 to 5.3 cm.In addition,laboratory tests were improved.The patient was able to resume a normal diet and was discharged in good overall health from the hospital,without aggravation of the symptoms.A colonoscopy performed 3 mo later and a follow-up CT performed 6 mo later confirmed that both the fistula and pseudocyst had completely disappeared. | Jae Choon Kwon Bo Yean Kim Ah Lim Kim Tae Hoon Kim Myung Il Park Ho Jin Jung Jang Hwan Lim Jae Kwon Jung Hyun Soo Kim Dong Wook Lee | 2014 | World Journal of Gastroenterology2014，20，7： | 0 |
| 2 | Prediction of product roughness,profile,and roundness using machine learning techniques for a hard turning process显示文摘High product quality is one of key demands of customers in the field of manufacturing such as computer numerical control(CNC)machining.Quality monitoring and prediction is of great importance to assure high-quality or zero defect production.In this work,we consider roughness parameter Ra,profile deviation Pt and roundness deviation RONt of the machined products by a lathe.Intrinsically,these three parameters are much related to the machine spindle parameters of preload,temperature,and rotations per minute(RPMs),while in this paper,spindle vibration and cutting force are taken as inputs and used to predict the three quality parameters.Power spectral density(PSD)based feature extraction,the method to generate compact and well-correlated features,is proposed in details in this paper.Using the efficient features,neural network based machine learning technique turns out to be able to result in high prediction accuracy with R2 score of 0.92 for roughness,0.86 for profile,and 0.95 for roundness. | Chunling Du Choon Lim Ho Jacek Kaminski | 2021 | Advances in Manufacturing2021，9，2： | 0 |
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