start-ver=1.4 cd-journal=joma no-vol=51 cd-vols= no-issue=5 article-no= start-page=319 end-page=326 dt-received= dt-revised= dt-accepted= dt-pub-year=2012 dt-pub=20121015 dt-online= en-article= kn-article= en-subject= kn-subject= en-title=Method to Extract Remarkable Words and Grouped Accidents according to Co-occurrence and Frequency of Words kn-title=単語の共起や頻度に注目した注意要因及び類似事例の抽出 en-subtitle= kn-subtitle= en-abstract= Common factors of accident cause are attempted to extract from accident reports by the statistical analysis. The result from the conventional analysis is difficult to show the factor of accident directly because this analysis classifies a vast description of accident reports into existing classification factors such as “mistaken operation” and “lack of ability”. In this paper, the proposed method reveals common factors in accident report automatically by extracting remarkable factors and grouped accidents. The remarkable factor shows appearance frequency in accident report. The grouped accidents which are evaluated as based on the number of accidents in one group have a characteristic of frequent accident. This paper reports our method was applied to PEC-SAFER accident reports to acquire remarkable factors and similar accident cases. kn-abstract= 事故事例の統計解析により,事故の共通要因を抽出する試みがなされている.しかし,その手法は膨大な言葉で記された事故の詳細を,「操作ミス」,「能力不足」といった人為的に定められた分類要因へ分類する統計解析であるため,解析結果から直接事故の要因を知ることは難しい.  そこで本手法は,自然言語処理の機械テキストマイニング技術を用い,形態素解析で事故報告書等の文章中の出現頻度の多い単語を注意要因として抽出し,注意要因を用いて原因表現をグループ化するという方法で類似事例を抽出する.グループ化された類似事例は,事例の数から事故の頻度を定量的に評価でき,頻発する事故の内容を知ることができる特徴がある.本手法をPEC-SAFER事故事例集に適用し注意要因や類似事例を抽出する事ができたので報告する. en-copyright= kn-copyright= en-aut-name=MINOWAHirotsugu en-aut-sei=MINOWA en-aut-mei=Hirotsugu kn-aut-name=箕輪弘嗣 kn-aut-sei=箕輪 kn-aut-mei=弘嗣 aut-affil-num=1 ORCID= en-aut-name=MUNESAWAYoshiomi en-aut-sei=MUNESAWA en-aut-mei=Yoshiomi kn-aut-name=宗澤良臣 kn-aut-sei=宗澤 kn-aut-mei=良臣 aut-affil-num=2 ORCID= en-aut-name=SUZUKIKazuhiko en-aut-sei=SUZUKI en-aut-mei=Kazuhiko kn-aut-name=鈴木和彦 kn-aut-sei=鈴木 kn-aut-mei=和彦 aut-affil-num=3 ORCID= affil-num=1 en-affil= kn-affil=岡山大学大学院 自然科学研究科 産業創生工学専攻 affil-num=2 en-affil= kn-affil=岡山大学大学院 自然科学研究科 産業創生工学専攻 affil-num=3 en-affil= kn-affil=岡山大学大学院 自然科学研究科 産業創生工学専攻 en-keyword=事故事例 kn-keyword=事故事例 en-keyword=形態素解析 kn-keyword=形態素解析 en-keyword=注意要因 kn-keyword=注意要因 en-keyword=テキストマイニグ kn-keyword=テキストマイニグ END start-ver=1.4 cd-journal=joma no-vol=1 cd-vols= no-issue= article-no= start-page=165 end-page=170 dt-received= dt-revised= dt-accepted= dt-pub-year=1995 dt-pub=19953 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=Fuzzy fault diagnostic system based on fault tree analysis en-subtitle= kn-subtitle= en-abstract= kn-abstract=

A method is presented for process fault diagnosis using information from fault tree analysis and uncertainty/imprecision of data. Fault tree analysis, which has been used as a method of system reliability/safety analysis, provides a procedure for identifying failures within a process. A fuzzy fault diagnostic system is constructed which uses the fuzzy fault tree analysis to represent a knowledge of the causal relationships in process operation and control system. The proposed method is applied successfully to a nitric acid cooler process plant

en-copyright= kn-copyright= en-aut-name=YangZong Xiao en-aut-sei=Yang en-aut-mei=Zong Xiao kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=1 ORCID= en-aut-name=SuzukiKazuhiko en-aut-sei=Suzuki en-aut-mei=Kazuhiko kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=2 ORCID= en-aut-name=ShimadaYukiyasu en-aut-sei=Shimada en-aut-mei=Yukiyasu kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=3 ORCID= en-aut-name=SayamaHayatoshi en-aut-sei=Sayama en-aut-mei=Hayatoshi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=4 ORCID= affil-num=1 en-affil= kn-affil=Okayama University affil-num=2 en-affil= kn-affil=Okayama University affil-num=3 en-affil= kn-affil=Okayama University affil-num=4 en-affil= kn-affil=Okayama University en-keyword=Fuzzy expert system kn-keyword=Fuzzy expert system en-keyword=Fault tree analysis kn-keyword=Fault tree analysis en-keyword=Fuzzy sets kn-keyword=Fuzzy sets en-keyword=Fault diagnosis kn-keyword=Fault diagnosis END start-ver=1.4 cd-journal=joma no-vol=45 cd-vols= no-issue=5 article-no= start-page=363 end-page=369 dt-received= dt-revised= dt-accepted= dt-pub-year=1991 dt-pub=199110 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=Effect of a protease inhibitor on the stability of catalase in liver and blood from acatalasemic and normal mice. en-subtitle= kn-subtitle= en-abstract= kn-abstract=

Effects of Gabexate mesilate (GM) (([ethyl-4-(6-guanidino hexanoyloxy) benzoate] methane sulfonate)), a protease inhibitor, on the activities of catalase in liver, erythrocytes and reticulocytes from acatalasemic mice were examined. Preincubation without GM at 37 degrees C for 160 min lowered the catalase activities of liver, erythrocytes and reticulocytes from acatalasemic mice, to 24%, 40% and 10% of the initial levels, respectively. But, preincubation with GM at 37 degrees C for 160 min delayed the rapid decrease in activities of residual catalases in the liver, erythrocytes and reticulocytes of acatalasemic mice to 65%, 93% and 85% of the initial values, respectively. At 20 degrees C or below, no reduction in catalase activity of reticulocytes from acatalasemic mice occurred with or even without GM. At pH 5.0, the decrease in catalase activity of acatalasemic mice was small both in the presence and the absence of GM. In the alkaline range, the reduction in the enzyme activity of the mutant mice without GM was enhanced with increase in pH values up to 8.5. But the presence of GM during preincubation at pH 7.5, retained the catalase activity of acatalasemic mice, to 64% of the activity at pH 6.5. These data suggest that some factors affected by GM, might be responsible for the low stability and activity of catalase in the acatalasemic mice.

en-copyright= kn-copyright= en-aut-name=SuzukiKazuhiko en-aut-sei=Suzuki en-aut-mei=Kazuhiko kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=1 ORCID= en-aut-name=OgataMasana en-aut-sei=Ogata en-aut-mei=Masana kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=2 ORCID= affil-num=1 en-affil= kn-affil=Okayama University affil-num=2 en-affil= kn-affil=Okayama University en-keyword=acatalasemic mouse kn-keyword=acatalasemic mouse en-keyword=residual catalase kn-keyword=residual catalase en-keyword=Gabexate mesilate kn-keyword=Gabexate mesilate en-keyword=protease inhibitor kn-keyword=protease inhibitor END start-ver=1.4 cd-journal=joma no-vol=25 cd-vols= no-issue=2 article-no= start-page=55 end-page=67 dt-received= dt-revised= dt-accepted= dt-pub-year=1991 dt-pub=19910328 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=A Procedure for Settling Multi-Criteria Problem by a Small Group of Decision Makers en-subtitle= kn-subtitle= en-abstract= kn-abstract=AHP can handle decision-making problems involving several criteria when some of these are difficult or impossible to compare other than numerically. When a small group of decision makers settle the multi-criteria problem by AHP, the members of group could not often reach an agreement with hierarchic structure involving objectives, criteria, sub-criteria and alternatives because they have different positions, interests, and opinions. Further, the members have different importances for criteria and sub-criteria, and have dissimilar preferences for alternatives. In this article, we reveal the troubleness of AHP in case of being used by a small group of decision makers. Moreover, we proposed a procedure of AHP which the members of group could easily agree with the structure of problem and the weights of criteria etc. en-copyright= kn-copyright= en-aut-name= en-aut-sei= en-aut-mei= kn-aut-name=OhkuraAkira kn-aut-sei=Ohkura kn-aut-mei=Akira aut-affil-num=1 ORCID= en-aut-name=KameyamaYoshimasa en-aut-sei=Kameyama en-aut-mei=Yoshimasa kn-aut-name=亀山嘉正 kn-aut-sei=亀山 kn-aut-mei=嘉正 aut-affil-num=2 ORCID= en-aut-name=SayamaHayatoshi en-aut-sei=Sayama en-aut-mei=Hayatoshi kn-aut-name=佐山隼敏 kn-aut-sei=佐山 kn-aut-mei=隼敏 aut-affil-num=3 ORCID= en-aut-name=SuzukiKazuhiko en-aut-sei=Suzuki en-aut-mei=Kazuhiko kn-aut-name=鈴木和彦 kn-aut-sei=鈴木 kn-aut-mei=和彦 aut-affil-num=4 ORCID= en-aut-name= en-aut-sei= en-aut-mei= kn-aut-name=FukumotoShuichi kn-aut-sei=Fukumoto kn-aut-mei=Shuichi aut-affil-num=5 ORCID= affil-num=1 en-affil= kn-affil=Department of Mechanical Engineering affil-num=2 en-affil= kn-affil=Department of Mechanical Engineering affil-num=3 en-affil= kn-affil=Department of Mechanical Engineering affil-num=4 en-affil= kn-affil=Department of Mechanical Engineering affil-num=5 en-affil= kn-affil=Daio Seishi Corporation END start-ver=1.4 cd-journal=joma no-vol=27 cd-vols= no-issue=1 article-no= start-page=33 end-page=44 dt-received= dt-revised= dt-accepted= dt-pub-year=1992 dt-pub=19921125 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=Process Fault Diagnosis using Neural Networks and Fault Tree Analysis Information en-subtitle= kn-subtitle= en-abstract= kn-abstract=Neural nets have recently become the focus of much attention, largely because of their wide range of complex and nonlinear problems. This paper presents a new integrated approach using neural networks for diagnosing process failures. The fault propagation in process is modeled by causal relationships from the fault tree and its minimal cut sets. The measurement patterns required for training and testing the neural network were obtained from fault propagation model. The network is able to diagnose even in the presence of malfunction of certain sensors. We demonstrate via a nitric acid cooler process how the neural network can learn and successfully diagnose the faults. en-copyright= kn-copyright= en-aut-name=ShimadaYukiyasu en-aut-sei=Shimada en-aut-mei=Yukiyasu kn-aut-name=島田行恭 kn-aut-sei=島田 kn-aut-mei=行恭 aut-affil-num=1 ORCID= en-aut-name=SuzukiKazuhiko en-aut-sei=Suzuki en-aut-mei=Kazuhiko kn-aut-name=鈴木和彦 kn-aut-sei=鈴木 kn-aut-mei=和彦 aut-affil-num=2 ORCID= en-aut-name=SayamaHayatoshi en-aut-sei=Sayama en-aut-mei=Hayatoshi kn-aut-name=佐山隼敏 kn-aut-sei=佐山 kn-aut-mei=隼敏 aut-affil-num=3 ORCID= affil-num=1 en-affil= kn-affil=Department of Mechanical Engineering affil-num=2 en-affil= kn-affil=Department of Mechanical Engineering affil-num=3 en-affil= kn-affil=Department of Mechanical Engineering END start-ver=1.4 cd-journal=joma no-vol= cd-vols= no-issue= article-no= start-page= end-page= dt-received= dt-revised= dt-accepted= dt-pub-year=1991 dt-pub=19911231 dt-online= en-article= kn-article= en-subject= kn-subject= en-title=アカタラセミアマウスと正常マウスの肝臓及び血液中カタラーゼの安定性に及ぼすたん白質分解酵素阻害剤の影響 kn-title=Effect of a protease inhibitor on the stability of catalase in liver and blood from acatalasemic and normal mice en-subtitle= kn-subtitle= en-abstract= kn-abstract= en-copyright= kn-copyright= en-aut-name= en-aut-sei= en-aut-mei= kn-aut-name=鈴木和彦 kn-aut-sei=鈴木 kn-aut-mei=和彦 aut-affil-num=1 ORCID= affil-num=1 en-affil= kn-affil=岡山大学 END