https://scholars.lib.cycu.edu.tw/handle/123456789/11 Tue, 18 Aug 2026 02:27:30 GMT 2026-08-18T02:27:30Z https://scholars.lib.cycu.edu.tw/handle/123456789/8053 Title: 薄膜蒸餾技術與其應用 Authors: 莊清榮 Tue, 01 Jan 202211 00:00:00 GMT https://scholars.lib.cycu.edu.tw/handle/123456789/8053 202211-01-01T00:00:00Z https://scholars.lib.cycu.edu.tw/handle/123456789/8030 Title: Using the dimethyl sulfoxide green solvent for the making of antifouling PEGylated membranes by the vapor-induced phase separation process Authors: Venault, Antoine; Aini, Hana Nur; Galeta, Tesfaye Abebe; Chang, Yung https://scholars.lib.cycu.edu.tw/handle/123456789/8030 https://scholars.lib.cycu.edu.tw/handle/123456789/8029 Title: 磷化銦量子點之製程技術與載子復合動力學影響光電轉換效能的研究發展 Authors: 蒲盈志; 范孝銓; 張瑞呈 Sat, 01 Jan 2022 00:00:00 GMT https://scholars.lib.cycu.edu.tw/handle/123456789/8029 2022-01-01T00:00:00Z https://scholars.lib.cycu.edu.tw/handle/123456789/7951 Title: Tensor Slow Feature Analysis for Monitoring Batch Process Authors: Liu, Jingxiang; Chen, Junhui; Mu, Guoqing Abstract: For accurately monitoring complex batch processes, the three-dimensional (3-D) structure and implied dynamics should be fully handled. To this end, a novel tensor slow feature analysis (TSFA) method is proposed to improve the batch process monitoring performance. In the proposed method, the 3-D data can be modeled directly without data unfolding to avoid the deficiency of destroying the raw data structure and increasing the modeling parameters in most existing methods. The slowly varying dynamics within batch processes can be efficiently extracted by solving two sub-optimal problems in the proposed TSFA method. Based on the defined monitoring statistics, within-batch detection can recognize the abnormal situation timely. A penicillin fermentation process is used to illustrate the advantages of the proposed method in comparison with the existing methods. Sat, 01 Jan 2022 00:00:00 GMT https://scholars.lib.cycu.edu.tw/handle/123456789/7951 2022-01-01T00:00:00Z