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RISS 인기검색어
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- 저자 : Masoud Malekzadeh (검색결과 3 건)
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Masoud M Malekzadeh,Alireza Sima,Sudabeh Alatab,Anahita Sadeghi,Nasser Ebrahimi Daryani,Payman Adibi,Iradj Maleki,Hassan Vossoughinia,Hafez Fakheri,Abbas Yazdanbod,Seyed Alireza Taghavi,Rahim Aghazade 대한장연구학회 2019 Intestinal Research Vol.17 No.3
Background/Aims: A recent study revealed increasing incidence and prevalence of inflammatory bowel disease (IBD) in Iran. The Iranian Registry of Crohn’s and Colitis (IRCC) was designed recently to answer the needs. We reported the design, methods of data collection, and aims of IRCC in this paper. Methods: IRCC is a multicenter prospective registry, which is established with collaboration of more than 100 gastroenterologists from different provinces of Iran. Minimum data set for IRCC was defined according to an international consensus on standard set of outcomes for IBD. A pilot feasibility study was performed on 553 IBD patients with a web-based questionnaire. The reliability of questionnaire evaluated by Cronbach’s α. Results: All sections of questionnaire had Cronbach’s α of more than 0.6. In pilot study, 312 of participants (56.4%) were male and mean age was 38 years (standard deviation=12.8) and 378 patients (68.35%) had ulcerative colitis, 303 subjects (54,7%) had college education and 358 patients (64.74%) were of Fars ethnicity. We found that 68 (12.3%), 44 (7.9%), and 13 (2.3%) of participants were smokers, hookah and opium users, respectively. History of appendectomy was reported in 58 of patients (10.48%). The most common medication was 5-aminosalicylate (94.39%). Conclusions: To the best of our knowledge, IRCC is the first national IBD registry in the Middle East and could become a reliable infrastructure for national and international research on IBD. IRCC will improve the quality of care of IBD patients and provide national information for policy makers to better plan for controlling IBD in Iran.
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Masoud Malekzadeh,Necati Catbas,Mustafa Gul,권일범 국제구조공학회 2014 Smart Structures and Systems, An International Jou Vol.14 No.5
Multivariate statistics based damage detection algorithms employed in conjunction with novel sensing technologies are attracting more attention for long term Structural Health Monitoring of civil infrastructure. In this study, two practical data driven methods are investigated utilizing strain data captured from a 4-span bridge model by Fiber Bragg Grating (FBG) sensors as part of a bridge health monitoring study. The most common and critical bridge damage scenarios were simulated on the representative bridge model equipped with FBG sensors. A high speed FBG interrogator system is developed by the authors to collect the strain responses under moving vehicle loads using FBG sensors. Two data driven methods, Moving Principal Component Analysis (MPCA) and Moving Cross Correlation Analysis (MCCA), are coded and implemented to handle and process the large amount of data. The efficiency of the SHM system with FBG sensors, MPCA and MCCA methods for detecting and localizing damage is explored with several experiments. Based on the findings presented in this paper, the MPCA and MCCA coupled with FBG sensors can be deemed to deliver promising results to detect both local and global damage implemented on the bridge structure.
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Malekzadeh, Masoud,Gul, Mustafa,Kwon, Il-Bum,Catbas, Necati Techno-Press 2014 Smart Structures and Systems, An International Jou Vol.14 No.5
Multivariate statistics based damage detection algorithms employed in conjunction with novel sensing technologies are attracting more attention for long term Structural Health Monitoring of civil infrastructure. In this study, two practical data driven methods are investigated utilizing strain data captured from a 4-span bridge model by Fiber Bragg Grating (FBG) sensors as part of a bridge health monitoring study. The most common and critical bridge damage scenarios were simulated on the representative bridge model equipped with FBG sensors. A high speed FBG interrogator system is developed by the authors to collect the strain responses under moving vehicle loads using FBG sensors. Two data driven methods, Moving Principal Component Analysis (MPCA) and Moving Cross Correlation Analysis (MCCA), are coded and implemented to handle and process the large amount of data. The efficiency of the SHM system with FBG sensors, MPCA and MCCA methods for detecting and localizing damage is explored with several experiments. Based on the findings presented in this paper, the MPCA and MCCA coupled with FBG sensors can be deemed to deliver promising results to detect both local and global damage implemented on the bridge structure.
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