本論文之研究目的在以成本與利益觀點，驗證產品資訊搜尋過程，消費者於對搜尋時間成本與產品資訊信心程度之主觀估計，在極大化程度對消費者產品資訊搜尋行為影響所扮演的中介變數角色，藉此瞭解產品資訊搜尋階段，極大化程度對消費者資訊搜尋行為與態度之影響機制。 極大化程度為一種個人追求最佳選擇程度之人格特質傾向。過去極大化程度在消費者行為領域之相關研究，多聚焦於探討不同極大化程度消費者之選項數量偏好、時間成本投入意願與決策後情感反應之差異，甚少有消費者資訊搜尋過程相關議題之討論。本研究認為，產品資訊搜尋實為消費者整體選擇與決策歷程最重要之階段，經常影響消費決策之最終品質，因此若要真正瞭解極大化程度對消費者選擇行為與態度差異之影響，除從極大化人格特質基本定義做為影響之解釋外，亦須藉由探討極大化程度在產品資訊搜尋過程，對消費者資訊成本與利益認知之影響中，連結出整段消費者選擇行為歷程之影響機制關係。 本論文以Ratchford (1982) 所提之「資訊搜尋之成本－利益模式 (The Cost-Benefit Model for Information Seeking)」為理論基礎，並將研究分為兩部份，研究一為探討不同極大化程度消費者在產品挑選機制與產品屬性要求標準上的差異，透過受測者對四項產品之屬性重要度評估、對特定屬性規格之期望標準，得知不同極大化程度受測者在產品屬性重視的程度、視為重要的屬性數量，以及產品屬性要求標準上之差異。研究二則採取2 (資訊延遲時間高、低)×2 (產品屬性離散程度高、低) 組間設計實驗，透過本研究設計之虛擬產品購物網站平台，讓受測者執行產品資訊搜尋任務，從中衡量受測者對產品資訊搜尋時間成本與資訊信心之主觀估計，驗證單位搜尋時間估計與單位資訊效用估計在極大化程度對受測者產品資訊搜尋數量、搜尋過程滿意度與產品知覺價值中，扮演之中介變數角色，以瞭解箇中之內在心理機制。 研究結果顯示，極大化程度與產品屬性重視程度及屬性要求標準呈現顯著正向關係，極大化受測者對產品屬性的重視程度與對產品屬性的要求標準皆較滿足化者高。足見不同極大化程度消費者對選擇之追求目標差異，會具體展現於產品遴選機制與屬性要求標準上。而經過中介變數關係檢定後也發現，極大化程度越高之受測者所估計之搜尋時間與對資訊在決策幫助上的信心越低，因而正向影響了搜尋的產品數量，搜尋時間成本與資訊效用估計亦分別成為受測者對搜尋過程滿意度以及對產品知覺價值之中介變數。 本論文之研究成果除驗證極大化選擇目標與產品遴選機制及屬性要求標準之關聯性外，亦進一步得知極大化程度影響消費者產品資訊搜尋行為與態度之內在心理機制，成功將系統性之消費者資訊搜尋經濟模式與極大化概念結合，為極大化程度研究領域帶來更深入且具理論基礎之發現。研究成果亦可作為通路或產品廠商思索產品陳列與資訊呈現方式時之參考依據，以降低顧客之主觀成本花費、提升產品資訊帶給顧客決策上的利益，提高顧客對個人整體消費過程之滿意度與所選產品之知覺價值。 / The purpose of this research is to demonstrate whether consumers’ subjective estimations of search time and product information confidence are the mediators mediating the effects of maximization tendency on consumers’ product information seeking behavior and attitude. From the perspective of information cost-benefit, the psychological mechanism will be found from this effect of personality on consumer behavior in this research. Maximization tendency was conceptualized in recent ten years to describe individual’s personality that strives for pursuing the best choice. After this concept was developed, most of the researches in this domain focused on discussing in the relationships between maximization orientation and consumers’ choice preferences such as the differences in the amount of alternatives, the aspiration to invest search time, and affective response after making decision. However seldom of them paid their attentions to the stage of product information search to probe the mechanism for the effect of maximization tendency on consumers’ searching behaviors about product information. Since the information seeking is the most important process to influence consumers’ decisions, the current study aims to explore the effects of maximization tendency on the individuals’ subjective estimations of time cost and benefit of product information. Hereby, the whole picture of the causal relationship in consumers’ information searching process would be drawn in this study. Referring to the rationales of Ratchford’s cost-benefit model, this research conducts two studies: the first part is to assess the differences in the criteria and attribute standard of consumers’ product selection with differential maximization tendencies. The second part is to conduct a 2 (the delay length of information appearance: low and high)×2 (the the dispersion of information attributes: low and high) between subject design experiments to demonstrate the mediating effect of two variables: consumers’ subjective estimation of time cost and information confidence during searching for information in the relations between maximization tendency and consumers’ information seeking behavior. The result shows the relationship between participants’ maximization orientation and their selection criteria as well as attribute demand standard exists. In general, maximizers have more complex choice criteria and higher picking standards than satisficers do when they choose the same products. The psychological mechanism is confirmed to help us understand how maximization tendency affect seeking behaviors and attitudes of product information from consumer’s product information seeking behavior and attitude. Manufacturers and store owners are suggested to apply these findings in the arrangement of alternatives and the display of product attribute information in order to reduce customers’ subjective estimation of time cost and improve their perception on information utility to, eventually, increase their satisfaction with the whole consumption experiences.

This thesis addresses a challenging problem: “how to let the visually impaired ‘see’ others emotions”. We, human beings, are heavily dependent on facial expressions to express ourselves. A smile shows that the person you are talking to is pleased, amused, relieved etc. People use emotional information from facial expressions to switch between conversation topics and to determine attitudes of individuals. Missing emotional information from facial expressions and head gestures makes the visually impaired extremely difficult to interact with others in social events. To enhance the visually impaired’s social interactive ability, in this thesis we have been working on the scientific topic of ‘expressing human emotions through vibrotactile patterns’. It is quite challenging to deliver human emotions through touch since our touch channel is very limited. We first investigated how to render emotions through a vibrator. We developed a real time “lipless” tracking system to extract dynamic emotions from the mouth and employed mobile phones as a platform for the visually impaired to perceive primary emotion types. Later on, we extended the system to render more general dynamic media signals: for example, render live football games through vibration in the mobile for improving mobile user communication and entertainment experience. To display more natural emotions (i.e. emotion type plus emotion intensity), we developed the technology to enable the visually impaired to directly interpret human emotions. This was achieved by use of machine vision techniques and vibrotactile display. The display is comprised of a ‘vibration actuators matrix’ mounted on the back of a chair and the actuators are sequentially activated to provide dynamic emotional information. The research focus has been on finding a global, analytical, and semantic representation for facial expressions to replace state of the art facial action coding systems (FACS) approach. We proposed to use the manifold of facial expressions to characterize dynamic emotions. The basic emotional expressions with increasing intensity become curves on the manifold extended from the center. The blends of emotions lie between those curves, which could be defined analytically by the positions of the main curves. The manifold is the “Braille Code” of emotions. The developed methodology and technology has been extended for building assistive wheelchair systems to aid a specific group of disabled people, cerebral palsy or stroke patients (i.e. lacking fine motor control skills), who don’t have ability to access and control the wheelchair with conventional means, such as joystick or chin stick. The solution is to extract the manifold of the head or the tongue gestures for controlling the wheelchair. The manifold is rendered by a 2D vibration array to provide user of the wheelchair with action information from gestures and system status information, which is very important in enhancing usability of such an assistive system. Current research work not only provides a foundation stone for vibrotactile rendering system based on object localization but also a concrete step to a new dimension of human-machine interaction. / Taktil Video

退休金是退休人未來生活的依靠，確保在退休後能得到適足的退休給付，政府在退休金上實施保證收益制度，此制度為最低保證利率與投資報酬率連結。本文探討退休金給付標準為確定提撥制，當退休金的投資報酬率是根據其連結之股價指數的表現來計算時，股價指數報酬率的模型假設為馬可夫調控跳躍過程模型，考慮市場狀態與布朗運動項、跳躍項的跳躍頻率相關，即為Elliot et al. (2007) 的模型特例。使用1999年至2012年的道瓊工業指數與S&P 500指數的股價指數對數報酬率作為研究資料，採用EM演算法估計參數及SEM演算法估計參數共變異數矩陣。透過概似比檢定說明馬可夫調控跳躍過程模型比狀態轉換模型、跳躍風險下狀態轉換模型更適合描述股價指數報酬率變動情形，也驗證馬可夫調控跳躍過程模型具有描述報酬率不對稱、高狹峰及波動叢聚的特性。最後，假設最低保證利率為固定下，利用Esscher轉換法計算不同模型下型I保證之確定提撥制退休金的評價公式，從公式中可看出受雇人提領的退休金價值可分為政府補助與個人帳戶擁有之退休金兩部分。以執行敏感度分析探討估計參數對於馬可夫調控跳躍過程模型評價公式的影響，而型II保證之確定提撥制退休金的價值則以蒙地卡羅法模擬並探討其敏感度分析結果。 / Pension plan make people a guarantee life in their retirement. In order to ensure the appropriate amount of pension plan, government guarantees associated with pension plan which ties minimum rate of return guarantees and underlying asset rate of return. In this paper, we discussed the pension plan with defined contribution (DC). When the return of asset is based on the stock indices, the return model was set on the assumption that markov-modulated jump diffusion model (MMJDM) could the Brownian motion term and jump rate be both related to market states. This model is the specific case of Elliot et al. (2007) offering. The sample observations is Dow-Jones industrial average and S&P 500 index from 1999 to 2012 by logarithm return of the stock indices. We estimated the parameters by the Expectation-Maximization (EM) algorithm and calculated the covariance matrix of the estimates by supplemented EM (SEM) algorithm. Through the likelihood ratio test (LRT), the data fitted the MMJDM better than other models. The empirical evidence indicated that the MMJDM could describe the asset return for asymmetric, leptokurtic, volatility clustering particularly. Finally, we derived different model's valuation formula for DC pension plan with type-I guarantee by Esscher transformation under rate of return guarantees is constant. From the formula, the value of the pension plan could divide into two segment: government supplement and employees deposit made pension to their personal bank account. And then, we done sensitivity analysis through the MMJDM valuation formula. We used Monte Carlo simulations to evaluate the valuation of DC pension plan with type-II guarantee and discussed it from sensitivity analysis.

科学研究費補助金 研究種目:基盤研究(C) 課題番号:12630097 研究代表者:奥野 信宏 研究期間:2000－2001年度

The primary goal of artificial intelligence research is to develop a machine capable of learning to solve disparate real-world tasks autonomously, without relying on specialized problem-specific inputs. This dissertation suggests that such machines are realistic: If No Free Lunch theorems were to apply to all real-world problems, then the world would be utterly unpredictable. In response, the dissertation proposes the information-maximization principle, which claims that the optimal optimization methods make the best use of the information available to them. This principle results in a new algorithm, evolutionary annealing, which is shown to perform well especially in challenging problems with irregular structure. / text

Αντικείμενο αυτής της μεταπτυχιακής εργασίας είναι ο εντοπισμός της ύπαρξης μιας κυρίαρχης ευρείας ζώνης ισοτροπικής πηγής κι η εκτίμηση των συντεταγμένων θέσης αυτής, όταν αυτή βρίσκεται σ’ έναν τρισδιάστατο ή δισδιάστατο χώρο, ο οποίος εποπτεύεται και παρακολουθείται από ένα δίκτυο τυχαία διασκορπισμένων αισθητήρων. Οι κόμβοι του δικτύου μπορούν να περιέχουν ακουστικά, παλμικά κι άλλου είδους μικροηλεκτρομηχανολογικά στοιχεία αίσθησης του περιβάλλοντος. Κατά την αίσθηση ενός γεγονότος ενδιαφέροντος μπορούν να αυτοοργανωθούν σ’ ένα συγχρονισμένο ασύρματο ραδιοδίκτυο χρησιμοποιώντας χαμηλής κατανάλωσης πομποδέκτες spread spectrum, ώστε να επικοινωνούν μεταξύ τους και με τους κεντρικούς επεξεργαστές. Ο εντοπισμός της ύπαρξης μιας κυρίαρχης πηγής σ’ ένα δίκτυο αισθητήρων, με τα παραπάνω χαρακτηριστικά, επιτεύχθηκε με τη χρήση μιας τυφλής μεθόδου μορφοποίησης λοβού, γνωστή ως μέθοδος συλλογής της μέγιστης ισχύος. Η μέθοδος αυτή, η οποία υλοποιήθηκε στα πλαίσια αυτής της εργασίας, παρέχει τις εκτιμήσεις των σχετικών χρόνων καθυστέρησης άφιξης του σήματος της κυρίαρχης πηγής στους αισθητήρες του δικτύου ως προς έναν αισθητήρα αναφοράς. Κύριο αντικείμενο μελέτης αυτής της εργασίας είναι ο υπολογισμός του κυρίαρχου ιδιοδιανύσματος του δειγματοληπτημένου πίνακα αυτοσυσχέτισης. Αυτό επιτυγχάνεται στη βιβλιογραφία που μελετήθηκε είτε με χρήση της δυναμικής μεθόδου είτε με χρήση της μεθόδου ιδιοανάλυσης. Ανά στιγμιότυπο δειγμάτων απαιτείται η ανανέωση του πίνακα αυτοσυσχέτισης κι ο υπολογισμός του κυρίαρχου ιδιοδιανύσματος. Όμως, οι δύο παραπάνω μέθοδοι για τον υπολογισμό αυτό χρειάζονται αυξημένη πολυπλοκότητα μιας κι η διάσταση του πίνακα είναι αρκετά μεγάλη. Η συνεισφορά της εργασίας αυτής έγκειται στη μείωση αυτής της πολυπλοκότητας με τη χρήση μιας προσαρμοστικής μεθόδου υπολογισμού του κυρίαρχου ιδιοδιανύσματος. Τέλος, αντικείμενο της εργασίας αυτής είναι και το πρόβλημα εντοπισμού και παρακολούθησης των συντεταγμένων θέσης της κυρίαρχης πηγής από τις εκτιμήσεις των σχετικών χρόνων καθυστέρησης άφιξης. / Object of this postgraduate work are the detection of presence of an isotropic wideband dominant source and the estimate of its coordinates of placement (localization), when the source is found in a three or two dimensional space, which is supervised and watched by a randomly distributed sensor network. The nodes of the network may contain acoustical, vibrational and other MEM-sensing (Micro-Electro-Mechanical) elements. Upon sensing an event of interest, they can self-organize into a synchronized wireless radio network using low-power spread-spectrum transceivers to communicate among themselves and central processors. The detection of presence of a dominant source in a sensor network, with the above characteristics, was achieved with the use of a blind beamforming method, known as the maximum power collection method. This method, which was implemented in the context of this work, provides estimates of the relative time delays of arrival (relative TDEs - Time Delay Estimations) of the dominant source’s signal to the sensors of the network referenced to a reference sensor. The main object of study of the work is the calculation of the dominant eigenvector of the sampled correlation matrix. This is achieved, in the bibliography that was studied, either by using the power method or with use of the SVD method (Singular Value Decomposition). Per snapshot of samples it is required to update the autocorrelation matrix and to calculate the dominant eigenvector. However, the above two methods for this calculation have an increased complexity because the dimension of the matrix is high enough. The contribution of this work lies in the reduction of that complexity by using an adaptive method for the dominant eigenvector calculation. Finally, this work also focuses on the problem of localization and tracking of the coordinates of placement of the dominant source from the estimates of the relative time delays of arrival.

Nous y introduisons une nouvelle classe de distributions bivariées de type Marshall-Olkin, la distribution Erlang bivariée. La transformée de Laplace, les moments et les densités conditionnelles y sont obtenus. Les applications potentielles en assurance-vie et en finance sont prises en considération. Les estimateurs du maximum de vraisemblance des paramètres sont calculés par l'algorithme Espérance-Maximisation. Ensuite, notre projet de recherche est consacré à l'étude des processus de risque multivariés, qui peuvent être utiles dans l'étude des problèmes de la ruine des compagnies d'assurance avec des classes dépendantes. Nous appliquons les résultats de la théorie des processus de Markov déterministes par morceaux afin d'obtenir les martingales exponentielles, nécessaires pour établir des bornes supérieures calculables pour la probabilité de ruine, dont les expressions sont intraitables. / In this contribution, we introduce a new class of bivariate distributions of Marshall-Olkin type, called bivariate Erlang distributions. The Laplace transform, product moments and conditional densities are derived. Potential applications of bivariate Erlang distributions in life insurance and finance are considered. Further, our research project is devoted to the study of multivariate risk processes, which may be useful in analyzing ruin problems for insurance companies with a portfolio of dependent classes of business. We apply results from the theory of piecewise deterministic Markov processes in order to derive exponential martingales needed to establish computable upper bounds of the ruin probabilities, as their exact expressions are intractable.

This thesis is related to the Bit Error Rate (BER) estimation for any digital communication system. In many designs of communication systems, the BER is a Key Performance Indicator (KPI). The popular Monte-Carlo (MC) simulation technique is well suited to any system but at the expense of long time simulations when dealing with very low error rates. In this thesis, we propose to estimate the BER by using the Probability Density Function (PDF) estimation of the soft observations of the received bits. First, we have studied a non-parametric PDF estimation technique named the Kernel method. Simulation results in the context of several digital communication systems are proposed. Compared with the conventional MC method, the proposed Kernel-based estimator provides good precision even for high SNR with very limited number of data samples. Second, the Gaussian Mixture Model (GMM), which is a semi-parametric PDF estimation technique, is used to estimate the BER. Compared with the Kernel-based estimator, the GMM method provides better performance in the sense of minimum variance of the estimator. Finally, we have investigated the blind estimation of the BER, which is the estimation when the sent data are unknown. We denote this case as unsupervised BER estimation. The Stochastic Expectation-Maximization (SEM) algorithm combined with the Kernel or GMM PDF estimation methods has been used to solve this issue. By analyzing the simulation results, we show that the obtained BER estimate can be very close to the real values. This is quite promising since it could enable real-time BER estimation on the receiver side without decreasing the user bit rate with pilot symbols for example.

獨立因子模型廣泛的應用在信用風險領域，此模型可用來估計經濟資本與投資組合的損失率分配。然而獨立因子模型假設因子獨立地服從同分配，因而可能會得到估計不精確的違約機率與資產相關係數。因此我們在本論文中提出序列相關因子模型來改進獨立因子模型的缺失，同時可以捕捉違約率的動態行為與授信戶間相關性。我們也分別從古典與貝氏的角度下估計序列相關因子模型。首先，我們在序列相關因子模型下利用貝氏的方法應用馬可夫鍊蒙地卡羅技巧估計違約機率與資產相關係數，使用標準普爾違約資料進行外樣本資料預測，能夠證明序列相關因子模型是比獨立因子模型合理。第二，蒙地卡羅期望最大法與蒙地卡羅最大概似法這兩種估計方法也使用在本篇論文。從模擬結果發現，若違約資料具有較大的序列相關與資產相關特性，蒙地卡羅最大概似法能夠配適的比蒙地卡羅期望最大法好。 / The independent factor model has been widely used in the credit risk field, and has been applied in estimating the economic capital allocations and loss rate distribution on a credit portfolio. However, this model assumes independent and identically distributed common factor which may produce inaccurate estimates of default probabilities and asset correlation. In this thesis, we address a serially dependent factor model (SDFM) to improve this phenomenon. This model can capture both dynamic behavior of default risk and dependence among individual obligors. We also address the estimation of the SDFM from both frequentist and Bayesian point of view. Firstly, we consider the Bayesian approach by applying Markov chain Monte Carlo (MCMC) techniques in estimating default probability and asset correlation under SDFM. The out-of-sample forecasting for S&P default data provide strong evidence to support that the SDFM is more reliable than the independent factor model. Secondly, we use two frequentist estimation methods to estimate the default probability and asset correlation under SDFM. One is Monte Carlo Expectation Maximization (MCEM) estimation method along with a Gibbs sampler and an acceptance method and the other is Monte Carlo maximum likelihood (MCML) estimation method with importance sampling techniques.

We present a variational method for unfolding of the cortex based on a user-chosen point of view as an alternative to more traditional global flattening methods, which incur more distortion around the region of interest. Our approach involves three novel contributions. The first is an energy function and its corresponding gradient flow to measure the average visibility of a region of interest of a surface from a given viewpoint. The second is an additional energy function and flow designed to preserve the 3D topology of the evolving surface. This latter contribution receives significant focus in this thesis as it is crucial to obtain the desired unfolding effect derived from the first energy functional and flow. Without it, the resulting topology changes render the unconstrained evolution uninteresting for the purpose of cortical visualization, exploration, and inspection. The third is a method that dramatically improves the computational speed of the 3D topology-preservation approach by creating a tree structure of the triangulated surface and using a recursion technique.