2181.  An Interactive Real-Time Locating System Based on Bluetooth Low-Energy Beacon Network

You-Wei Lin; Chi-Yi Lin ,  2018-05-21
[Graduate Institute & Department of Computer Science and Information Engineering] Journal Article
Sensors 18(5), 1637(17 pages)
You-Wei Lin Chi-Yi Lin An Interactive Real-Time Locating System Based on Bluetooth Low-Energy Beacon Network MDPI Bluetooth low energy;location

2182.  Opportunity for Early Warnings of Typhoon Lekima from Two Global Ensemble Model Forecasts of Formation with 7-Day Intensities along Medium-Range Tracks

Tsai, Hsiao-Chung; Elsberry, Russell L.; Chin, Wei-Chia; Marchok, Timothy P. ,  2020-10-27
[Graduate Institute & Department of Water Resources and Environmental Engineering] Journal Article
Atmosphere 11(11), 1162
Weather Forecasts and the National Centers for Environmental Predictions have been used to provide time-to-formation timing and positions along

2183.  Activities of Daily Living Recognition with Binary Environment Sensors Using Deep Learning: A Comparative Study

Wang, Aiguo; Zhao, Shenghui; Zheng, Chundi; Yang, Jing; Chen, Guilin; Chang, Chih-Yung ,  2021-02-15
[Graduate Institute & Department of Computer Science and Information Engineering] Journal Article
IEEE Sensors Journal 21(4), p.5423-5433
studies systematically investigate how to properly encode the time-series firings of binary environment sensors that typically work in an event-triggering

2184.  Artificial Chromosomes with Genetic Algorithm 2 (ACGA2) for Single Machine Scheduling Problems with Sequence-Dependent Setup Times

Chen, S. H.; Chen, M. C.; Liou, Y. C. ,  2014-04
[Graduate Institute & Department of Computer Science and Information Engineering] Journal Article
Applied Soft Computing 17, p.167-175
to the fact that the previous job will influence the processing time of the next job. Simply capturing ordinal information from the parental

2185.  Option Pricing with Markov Switching

Fuh, Cheng-der; Ho, Kwok Wah Remus; Hu, Inchi; Wang, Ren-her ,  2012-07
[Graduate Institute & Department of Banking and Finance] Journal Article
Journal of Data Science 10(3), pp.483-509
; implied volatility; Laplace transform; Markovian tree In this article, we consider a model of time-varying volatility which generalizes the classical Black

2186.  動態樣本選擇模型之貝氏分析

黃河泉 ,  2003
[Graduate Institute & Department of Banking and Finance] Research Paper
on the modeling strategy when time series data are used. The novel dynamic sample selection model is estimated via the Gibbs sampler with data

2187.  日本股匯市非對稱長短因果關係之比較

何月冠; Ho, Yueh-kuan ,  2009
[E-Learning Executive Master's Program of Business Administration (EMBA) in Global Chinese Management] Thesis
, 624-643. Bhargava, A. (1986), “On the theory of testing for unit roots in observed time series,” Review of Economic Studies, 53, 369-384. Chan, K. S

2188.  短期利率的動態行為：GARCH-X模型之應用

洪棠譑; Hung, Tang-chiao ,  2007
[Graduate Institute & Department of Banking and Finance] Thesis
Studies, vol. 12, pp. 721-762. Aït-Sahalia, Y. (1996), "Testing Continuous-time Models of the Spot Interest Rate", Review of Financial Studies, vol

2189.  匯率相關跳躍強度共移分析 : 雙變量跳躍模型探討

張鼎煥; Chang, Ting-huan ,  2006
[Graduate Institute & Department of Banking and Finance] Thesis
,” and incorporates the volatility and jump intensity spillover effects, in order to examine the discontinuous jump and the time-varying correlated jump

2190.  短期利率動態模型-偏態分配之實證研究

洪堯基; Hung, Yao-chi ,  2008
[Graduate Institute & Department of Banking and Finance] Thesis
rate that nest one-factor CEV model with linear drift and level effect. Second, the paper nested the discrete-time GARCH models that incorporate