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Study on Visualization Method of Rice Yield and Quality Data
( Shimpei Saito ),( Hideo Hasegawa ) 한국농업기계학회 2018 한국농업기계학회 학술발표논문집 Vol.23 No.1
One of the problems of Japanese agriculture has been decrease in the number of skilled farmers in order to retirement and aging in recent years. Therefore, it is serious problem to inherit farming techniques to the younger successors. The purpose of this study is to visualize growth situation by using UAV and GIS, and provide young farmers comprehensive data as a technical guidance. In this study, we visualized rice yield and quality of agricultural corporation from 2012 to 2017 in Central Part of Niigata Prefecture, Japan and clarified the growth situation of the paddy field at the young panicle formation stage. We extracted paddy fields to be improved from the stand point of cultivation skill based on data visualization. We overlaid field data on the aerial photograph of the corporation and extracted technological characteristics of rice paddy. In this research, we collected and visualized field information. By expressing the yield of the union fields with blue to red gradation, it was possible to intuitively confirm the state and progress of the fields. It was also easy to compare with adjacent fields, suggesting that not only information accumulation but also their work motivation was improved. The brown rice protein content was positively correlated with the yield, and it is thought that the rise in the protein content by the ground nitrogen influenced it. Sensing by UAV can visualize the variation of NDVI in the panicle formation stage, and the members can intuitively understand the variation in growth. By applying this knowledge to the fertilization work, it is thought that it will lead to added value by stabilizing the quality. In addition, we confirmed the decrease in growth due to field improvement, soil analysis and improvement in the field is required.
Shuichi Shimada,Hideo Saito,Yoshihide Kawasaki,Shinichi Yamashita,Hisanobu Adachi,Narihiko Kakoi,Takashige Namima,Masahiko Sato,Atsushi Kyan,Koji Mitsuzuka,Akihiro Ito,Takuhiro Yamaguchi,Yoichi Arai 대한비뇨의학회 2017 Investigative and Clinical Urology Vol.58 No.4
Purpose: To evaluate renal function 1 year after radical nephrectomy (RN) for renal cell carcinoma, the preoperative predictors of postnephrectomy renal function were investigated by sex, and equations to predict the estimated glomerular filtration rate (eGFR) 1 year after RN were developed. Materials and Methods: A total of 525 patients who underwent RN between May 2007 and August 2011 at Tohoku University Hospital and its affiliated hospitals were prospectively evaluated. Overall, 422 patients were analyzed in this study. Results: Independent preoperative factors associated with postnephrectomy renal function were different in males and females. Preoperative eGFR, age, tumor size, and body mass index (BMI) were independent factors in males, while tumor size and BMI were not independent factors in females. The equations developed to predict eGFR 1 year after RN were: Predicted eGFR in males (mL/min/1.73 m2)=27.99−(0.196×age)+(0.497×eGFR)+(0.744×tumor size)−(0.339×BMI); and predicted eGFR in females=44.57−(0.275×age)+(0.298×eGFR). The equations were validated in the validation dataset (R2=0.63, p<0.0001 and R2=0.31, p<0.0001, respectively). Conclusions: The developed equations by sex enable better prediction of eGFR 1 year after RN. The equations will be useful for preoperative patient counseling and selection of the type of surgical procedure in elective partial or RN cases.
Classication of fNIRS Data Using an Articial Neural Network for Image Sequence Recognition
Sei Takahashi,Nagako Saito,Hideo Nakamura,Hitoshi Tsunashima 대한전자공학회 2009 ITC-CSCC :International Technical Conference on Ci Vol.2009 No.7
We describe classication of functional near-infrared spectroscopy (fNIRS) data acquired during finger tapping and motor imagery tasks performed by a human subject, using an articial neural network for image sequence recognition. Our goal is to develop a brain-computer interface. We used an fNIRS system to collect neural information from brain activity. For discrimination of fNIRS data, we used our previously proposed neural network model called the Neocognitron-type Image Sequence Recognition Model (Neo-ISRM), which is suitable for multichannel temporal patterns. Finger tapping and its motor imagery were used as the motion and mental tasks to be discriminated using Neo-ISRM. The model gave good discrimination results for each category of tasks.
Chronological Endoscopic and Pathological Observations in Russell Body Duodenitis
Atsushi Goto,Takeshi Okamoto,Masaharu Matsumoto,Hiroyuki Saito,Hideo Yanai,Hiroshi Itoh,Isao sakaida 대한소화기내시경학회 2016 Clinical Endoscopy Vol.49 No.4
A 64-year-old man was found to have a nodule in his right lung. He also complained of nausea and abdominal pain during the clinical course. Esophagogastroduodenoscopy revealed a duodenal ulcer associated with severe stenosis and a suspicion of malignancy. However, three subsequent biopsies revealed no evidence of malignancy. The fourth biopsy showed scattered large eosinophilic cells with an eccentric nucleus, leading to a diagnosis of Russell body duodenitis (RBD). RBD is an extremely rare disease, and little is known about its etiology and clinical course. The pathogenesis of RBD is discussed based on our experience with this case.