Criteria Overview for Functional Performance Evaluation Pertaining to Refurbished Historical Building

Author(s):  
Hasnizan Aksah ◽  
Ahmad Ezanee Hashim ◽  
Elma Dewiyana Ismail ◽  
Zarina Isnin
1991 ◽  
Vol 11 (4) ◽  
pp. 227-237
Author(s):  
Elizabeth Stanton ◽  
William C. Mann ◽  
James P. Klyczek

1987 ◽  
Vol 54 (4) ◽  
pp. 195-199 ◽  
Author(s):  
Margaret M. Brockett

In comparing the scores obtained in the Bay Area Functional Performance Evaluation test by two groups of acute psychiatric patients, one in San Francisco, California and the other in Vancouver, British Columbia, this paper examines aspects of performance which may be culturally determined. Given the limitations of the medical model used in many acute psychiatric programs, it considers possible alternative uses of this standardized test beyond the traditional occupational therapy initial assessment which may enhance its value: in identifying important information for treatment planning by the occupational therapist and providing a way of measuring a patient's readiness for discharge.


2019 ◽  
Vol 136 ◽  
pp. 04069
Author(s):  
Huan Liu ◽  
Peng Liu ◽  
Qiuyu Peng

Because of the deficiency of the index of cement pavement performance evaluation and the defect of the evaluation method in the specification, the performance of the pavement is comprehensively evaluated by seven optimized indexes and grading standards that reflect functional performance and structure of the pavement. Because the discrete Hopfield neural network is available with simple construction procedure, less training samples, and strong objectivity.The DHNN is constructed by MATLAB to evaluate the performance of test pavement. The ideal cement pavement performance grading evaluation index matrix and 6 places unclassified of test pavement performance evaluation index matrix are input to the neural network then the evaluation result is obtained after simulating and learning. Finally, comparing the result of the DHNN with the fuzzy complex matter element method and the nonlinear fuzzy method, it is proved that the discrete Hopfield neural network evaluation method is reliable.


1989 ◽  
Vol 43 (3) ◽  
pp. 170-183 ◽  
Author(s):  
D. Houston ◽  
S. L. Williams ◽  
J. Bloomer ◽  
W. C. Mann

2019 ◽  
Vol 42 (3) ◽  
Author(s):  
Nurnadiah Ahmad ◽  
Hemabarathy Bharatham ◽  
Zariyantey Abdul Hamid ◽  
Enoch Kumar Perimal ◽  
Penny George

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