2301.  Applying Loss-rate Driven Network Coding to Transmission Control Protocol

蔡憶佳; 江肇元 ,  2014-07-08
[資訊工程學系暨研究所] 會議論文
-
segment loss or time-out, such as interference, fading, or temporary fault in the intermediate network devucu. The retransmission and congestion

2302.  台灣電梯產業之供應鏈整合、供應鏈能力與供應鏈績效關聯性研究 : 以整合程度為調節中介

陳思婷; Chen, Szu-Ting ,  2015
[管理科學學系暨研究所] 學位論文
. (1996). Supply Chain Management: A Time-Based strategy. Industrial Management, 38(5), 24-27. Barut, M., Faisst, W., and Kanet, J. J. (2002

2303.  建材業員工辦公室節能行為影響因素之研究

蘇志宗; Su, Chih-Tsung ,  2015
[企業管理學系暨研究所] 學位論文
” on architecture employee energy saving behavior in the office time. The total sample size was 211 respondents. Confirmatory factor analysis (CFA

2304.  The empirical study of asymmetric relationships in the commodity and financial markets

卓訓方; Cho, Hsun-Fang ,  2016
[財務金融學系暨研究所] 學位論文
between corn, rice, soybean, and wheat prices and the oil price during the time period investigated. Furthermore, we examined the short-run causal

2305.  Optimal capacitor placement in distribution systems using a combination fuzzy-GA method

Hsiao, Ying-tung; Chen, Chia-hong; Chien, Cheng-chih ,  2004-02-19
[電機工程學系暨研究所] 期刊論文
International Journal of Electrical Power & Energy Systems 26(7),　p.501-508
monotonically Kj; the energy cost per unit for load level j: decreasing and continuous function. Fig. 1 shows the graph Tj; the time duration

2306.  An EOQ inventory model for items with Weibull distribution deterioration, ramp type demand rate and partial backlogging

吳坤山; Wu, Kun-shan ,  2001-12-01
[企業管理學系暨研究所] 期刊論文
Production Planning & Control 12(8), pp.787-793
is in nite. (2) Lead time is zero. (3) T is the xed length of each ordering cycle. (4) S is the maximum inventory level for each order- ing cycle

2307.  Real-time recurrent learning neural network for stream-flow forecasting

張麗秋; Chang, Li-chiu; Chang, F. J.; Huang, H. L. ,  2002-09-01
[水資源及環境工程學系暨研究所] 期刊論文
Hydrological processes 16(13), pp.2577-2588
淡江大學水資源及環境工程學系 張麗秋 Chang, Li-chiu Chang, F. J. Huang, H. L. Real-time recurrent learning neural network for stream-flow forecasting Wiley Online

2308.  Optimal order policy in response to announced price increase for deteriorating items with limited special order quantity

Ouyang, Liang-Yuh; Wu, Kun-Shan; Yang, Chih-Te; Yen, Hsiu-Feng ,  2016-02-01
[企業管理學系暨研究所] 期刊論文, [管理科學學系暨研究所] 期刊論文
International Journal of Systems Science 47(3), pp.718-729
. This is a common industrial practice. (3) The replenishment rate is infinite and the lead-time is zero. (4) Shortages are not allowed. (5

2309.  A Novel Method for Mining Temporally Dependent Association Rules in Three-Dimensional Microarray Datasets

Liu, Yu-cheng; Lee, Chao-hui; Chen, Wei-chung; Shin, J. W.; Hsu, Hui-huang; Tseng, Vincent S. ,  2010-12
[資訊工程學系暨研究所] 會議論文
Proc. 2010 International Computer Symposium, pp. 759-764
association rule mining on microarray, but there is no concrete framework proposed on three-dimensional gene-sample-time microarray datasets yet

2310.  A Time-Domain Viscous Damping Model Based on Frequency-Dependent Damping Ratios

Chang, D. W.; Roesset, J. M.; Wen, C. H. ,  2000-12
[土木工程學系暨研究所] 期刊論文
Soil Dynamics and Earthquake Engineering 19(8), pp.551-558
淡江大學土木工程學系 Chang, D. W. Roesset, J. M. Wen, C. H. Chang, Der-Wen A Time-Domain Viscous Damping Model Based on Frequency-Dependent Damping Ratios