Browsing by Author "Tsai, Wen-Chih"

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Cloud Computing Architecture for Social Computing - A Comparison Study of Facebook and Google
(2011)
Yang, Bo-Wen
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Tsai, Wen-Chih
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Chen, An-Pin
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Ramandeep, Singh
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資訊管理與財務金融系註：原資管所+財金所
As far as we know, cloud computing is a new business model and the cloud computing architecture is the famous topic recently. Today, everyone enjoy the innovative search engine or social network application for new Internet services no longer require the large capital outlays in hardware to access those service or the human expense to operate it. Currently, Google is the largest search engine and Facebook is the largest social network in the Software as a Service (SaaS). But how them can support the huge requests from world thought each personal computer, mobile device, and smart phone. In this paper, we will try to analysis their backend cloud computing architecture to support future SaaS especially in large social network.
Global Asset Allocation using XCS Experts in Country-Specific ETFs
(2008)
Tsai, Wen-Chih
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Chen, An-Pin
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資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
There are several studies extended classification system (XCS) in past years, the model can dynamically learn and adapt to the change of environments for maximizing the desired goals. This paper conducts simulation the experiment to evolve XCS for global asset allocation in the country-specific Exchanged Traded Funds (ETFs). Since international stock price trend is influenced by unknown and unpredictable surrounding, using XCS to model the fluctuations on global financial market allows' for the capability to discover the patterns of the future trends. The benefits of international diversification can be achieved with country-specific ETFs at a low cost, with a low transaction cost, tracking error and in a tax-efficient way. These empirical results indicate that XCS is capable of evolving from generation to generation, and in this way can provide the highest profit for future global asset allocation decision-making.
Self-detection of Delamination in Active Fiber Composites
(2009)
Wang, Dwo-Wen
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Tsai, Wen-Chih
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Yin, Ching-Chung
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機械工程學系
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Department of Mechanical Engineering
This paper presents a novel method to monitor the bonding condition of active fiber composites (AFCs). AFCs can be used as integrated acoustic sensors/actuators to compose functional structures because of their excellent properties. Debonds between AFC patch and host structure should be avoided and surveyed through its service life. A partially debonded patch bears an axial extensional vibration which is excited by a sinusoidal voltage and detected by the interdigital electrodes symmetrically aligned on opposite surfaces of the patch. The electric impedance and mechanical displacement of the AFC patch adhered on an aluminum plate were investigated in a broad frequency range. The modal characteristics depend on the size of debond and stiffness of adhesive in front of the edge of delamination. The debonding ratio of the AFC patch is in inverse proportion to the resonant frequency of the fundamental mode. Feasibility of self-detecting the progressive delamination between AFC patch and host plate is demonstrated through computational and experimental results.
Strategy of global asset allocation using extended classifier system
(2010-09-01)
Tsai, Wen-Chih
;
Chen, An-Pin
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
There are several studies about extended classification system (XCS) in past years. XCS model can dynamically learn and adapt to the change of environments for maximizing the desired goals. This paper conducts simulation to apply XCS to global asset allocation in the country-specific exchanged traded funds (ETFs). Since international stock price trend is influenced by unknown and unpredictable surroundings, using XCS to model the fluctuations on global financial market allows for the discovery of the patterns of the future trends. As such, the benefits of international asset diversification can be achieved in a tax-efficient way with country-specific ETFs at a low transaction cost with minimized tracking error. These empirical results indicate that XCS is capable of evolving over time, and thus XCS can provide a good indicator for future global asset allocation decision-making aiming at maximized profit. (C) 2010 Elsevier Ltd. All rights reserved.
Using the XCS classifier system for portfolio allocation of MSCI index component stocks
(2011-01-01)
Tsai, Wen-Chih
;
Chen, An-Pin
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
In a recent study, Schulenburg and Ross (2001) proposed the LCS for short-term stock forecast. Studley and Bull (2007) proposed the extended classifier system (XCS) agent to model different traders by supplying different input information. Announcement made by Morgan Stanley Capital Investment (MSCI) regarding the additions, removals, and even the weights of the component stocks in its country indices every quarter generally would cause changes to the prices and/or trade volumes of the associated component stocks. This paper takes an XCS in artificial intelligence to dynamically learn and adapt to the changes to the component stocks in order to optimize portfolio allocation of the component stocks. Since these price trends of MSCI component stocks are influenced by unknown and unpredictable surroundings, using XCS to model the fluctuations on financial market allows for the capability to discover the patterns of future trends. This simulation works on the basis of the changes to 121 component stocks in the MSCI Taiwan index between 1998 and 2009 suggests the XCS can produce the great profit and optimize portfolio allocation. Crown Copyright (C) 2010 Published by Elsevier Ltd. All rights reserved.