It is indisputable that the internet has become a necessary component of contemporary multi-channel retail, as more consumers are choosing to purchase goods online each year. As online spending continues to grow, many have called into question the future of brick-and-mortar retail. This thesis seeks to empirically prove that brick-and-mortar retail remains not only relevant, but indispensable in direct-to-consumer business models. The basis of this conjecture is the idea of channel synergism, in which online and brick-and-mortar operations are complementary. This theory is predicated on the emergence of the omni-channel retail, which is characterized by the integration of the various direct-to-consumer (D2C) channels to support cross-channel consumer interaction. To empirically test this hypothesis, key operating metrics were examined over the five year period from 2007 to 2011. By examining profitability trends and several D2C channel relationships, empirical support is developed to substantiate the claim that brick-and-mortar operations are not being driven into obsolescence by the growing prevalence of e-commerce transactions.

本篇論文旨在探討台灣貨幣政策的銀行借貸傳遞管道，著重在銀行行為的分析，我們為銀行在借貸管道中所扮演的行為提供了一個理論的解釋架構。實證上利用共整合與衝擊反應函數分析貨幣政策的影響，結果發現因銀行會調整資產負債的組合來抵銷貨幣政策的影響，所以銀行借貸管道在台灣並不是一個重要的貨幣政策傳遞管道。 / This paper investigates the role of the bank lending channel in the monetary policy transmission process in Taiwan. Particularly, we provide a theoretical framework to describe the effect of banks' behaviors on the bank lending channel. In the empirical study, we perform cointegrated relation and impulse response to analyze the effect of monetary policy on bank loans. We find that a bank lending channel is not a relevant transmission mechanism of monetary policy, which can be due to banks' buffer behaviors.

ClC proteins encompass a large protein family consisting of both voltage-dependent chloride channels and chloride/proton exchangers that are found in both eukaryotes and prokaryotes. These proteins mediate Cl- flux across the plasma membrane or intracellular membranes of many cell types including neurons, epithelial cells, and skeletal muscle in mammals. Mutations in genes encoding these channels also contribute to several human diseases. The mechanism of ion conduction through ClC proteins is becoming better defined, largely due to the availability of a crystal structure of a bacterial ClC transporter. Because crystal structures only capture a snapshot a protein in a single conformation, however, the large conformational changes associated with channel opening and closing have remained largely undefined. In the cation channel field, ion conduction and conformational changes that occur during channel gating have been studied using peptide toxin inhibitors isolated from animal venoms. However, only one peptide toxin inhibitor of a chloride channel of known molecular identity has ever been identified. Georgia anion toxin 1 (GaTx1), inhibits the CFTR chloride channel, which is unrelated to ClC proteins on the levels of both three dimensional structure and primary sequence. Here, we describe the characterization of the inhibitory activity of Leiurus quinquestriatus hebraeus scorpion venom against the ClC-2 chloride channel. We found that the venom from this scorpion contains a peptide component that is capable of inhibiting the ClC-2 chloride channel. This component was isolated using standard chromatography techniques, and found that the active component is a 3.2 kDa peptide composed of 29 amino acids. We showed that the active toxin, Georgia anion toxin 2 (GaTx2), interacts with ClC-2 with an affinity in the picomolar range, and appears to slow channel opening. Finally, GaTx2 is not capable of inhibiting other members of the ClC protein family, other major chloride channels, or voltage-gated potassium channels. This toxin will provide a new tool for structure/function studies of ClC-2, and will hopefully serve as only the first toxin inhibitor available for this protein family.

The use of multiple antennas at base stations and user devices is a key component in the design of cellular communication systems that can meet the capacity demands of tomorrow. The downlink transmission from base stations to users is particularly limiting, both from a theoretical and a practical perspective, since user devices should be simple and power-efficient, and because many applications primarily create downlink traffic (e.g., video streaming). The potential gain of employing multiple antennas for downlink transmission is well recognized: the total data throughput increases linearly with the number of transmit antennas if the spatial dimension is exploited for simultaneous transmission to multiple users. In the design of practical cellular systems, the actual benefit of multiuser multiantenna transmission is limited by a variety of factors, including acquisition and accuracy of channel information, transmit power, channel conditions, cell density, user mobility, computational complexity, and the level of cooperation between base stations in the transmission design. The thesis considers three main components of downlink communications: 1) estimation of current channel conditions using training signaling; 2) efficient feedback of channel estimates; and 3) allocation of transmit resources (e.g., power, time and spatial dimensions) to users. In each area, the thesis seeks to provide a greater understanding of the interplay between different system properties. This is achieved by generalizing the underlying assumptions in prior work and providing both extensions of previous outcomes and entirely new mathematical results, along with supporting numerical examples. Some of the main thesis contributions can be summarized as follows. A framework is proposed for estimation of different channel quantities using a common optimized training sequence. Furthermore, it is proved that each user should only be allocated one data stream and utilize its antennas for receive combining and interference rejection, instead of using the antennas for reception of multiple data streams. This fundamental result is proved under both exact channel acquisition and under imperfections from channel estimation and limited feedback. This also has positive implications on the hardware and system design. Next, a general mathematical model is proposed for joint analysis of cellular systems with different levels of base station cooperation. The optimal multicell resource allocation can in general only be found with exponential computational complexity, but a systematic algorithm is proposed to find the optimal solution for the purpose of offline benchmarking. A parametrization of the optimal solution is also derived, creating a foundation for heuristic low-complexity algorithms that can provide close-to-optimal performance. This is exemplified by proposing centralized and distributed multicell transmission strategies and by evaluating these using multicell channel measurements. / In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not endorse any of KTH Royal Institute of Technology's products or services. Internal or personal use of this material is permitted. If interested in reprinting/republishing IEEE copyrighted material for advertising or promotional purposes or for creating new collective works for resale or redistribution, please go to http://www.ieee.org/publications_standards/publications/rights/rights_link.html to learn how to obtain a License from RightsLink.QC 20111026

Characterizing probability distribution function for the input of a communication channel that achieves the maximum possible data rate is one of the most fundamental problems in the field of information theory. In his ground-breaking paper, Shannon showed that the capacity of a point-to-point additive white Gaussian noise channel under an average power constraint at the input, is achieved by Gaussian distribution. Although imposing a limitation on the peak of the channel input is also very important in modelling the communication system more accurately, it has gained much less attention in the past few decades. A rather unexpected result of Smith indicated that the capacity achieving distribution for an AWGN channel under peak constraint at the input is unique and discrete, possessing a finite number of mass points. In this thesis, we study multiple access channel under peak constraints at the inputs of the channel. By extending Smith's argument to our multi-terminal problem we show that any point on the boundary of the capacity region of the channel is only achieved by discrete distributions with a finite number of mass points. Although we do not claim uniqueness of the capacity-achieving distributions, however, we show that only discrete distributions with a finite number of mass points can achieve points on the boundary of the capacity region. First we deal with the problem of maximizing the sum-rate of a two user Gaussian MAC with peak constraints. It is shown that generating the code-books of both users according to discrete distributions with a finite number of mass points achieves the largest sum-rate in the network. After that we generalize our proof to maximize the weighted sum-rate of the channel and show that the same properties hold for the optimum input distributions. This completes the proof that the capacity region of a two-user Gaussian MAC is achieved by discrete input distributions with a finite number of mass points.

In recent years, space-time block coding (STBC) has emerged as an effective transmit-diversity technique to combat the detrimental effects of channel fading. In addition to STBC, high-order modulation schemes will be used in future wireless communication systems aiming to provide ubiquitous-broadband wireless access. Hence, advanced receiver schemes are necessary to achieve high performance. In this thesis, advanced and computationally-efficient receiver schemes are investigated and developed for single-carrier space-time (ST) block-coded transmissions over frequency-selective fading (FSF) channels. First, we develop an MMSE-based turbo equalization scheme for Alamouti ST block-coded systems. A semi-analytical method to estimate the bit error rate (BER) is devised. Our results show that the proposed turbo equalization scheme offers significant performance improvements over one-pass equalization. Second, we analyze the convergence behavior of the proposed turbo equalization scheme for Alamouti ST block-coded systems using the extrinsic information transfer (EXIT)-band chart technique. Third, burst-wise (BW)-STBC is applied for uplink transmission over FSF channels in block-spread-CDMA systems with multiuser interference-free reception. The performances of different decision feedback sequence estimation (DFSE) schemes are investigated. A new scheme combining frequency-domain (FD) linear equalization and modified unwhitened-DFSE is proposed. The proposed scheme is very promising as the error-floor behavior observed in the existing unwhitened DFSE schemes is eliminated. Fourth, we develop a FD-MMSE-based turbo equalization scheme for the downlink of ST block-coded CDMA systems. We adopt BW-STBC instead of Alamouti symbol-wise (SW)-STBC considered for WCDMA systems and demonstrate its superior performance in FSF channels. Block spreading is shown to be more desirable than conventional spreading to improve performance using turbo equalization. We also devise approximate implementations (AprxImpls) that offer better trade-offs between performance and complexity. Semi-analytical upper bounds on the BER are derived. Fifth, turbo multicode detection is investigated for ST block-coded downlink transmission in DS-CDMA systems. We propose symbol-by-symbol and chip-by-chip FD-MMSE-based multicode detectors. An iterative channel estimation scheme is also proposed. The proposed turbo multicode detection scheme offers significant performance improvements compared with non-iterative multicode detection. Finally, the impact of channel estimation errors on the performance of MMSE-based turbo equalization in ST block-coded CDMA systems is investigated.

A new promising approach for wireless network optimization is from a cross-layer perspective. This thesis focuses on exploiting channel state information (CSI) from the physical layer for optimal transmission scheduling at the medium access control (MAC) layer. The first part of the thesis considers exploiting CSI via a distributed channel-aware MAC protocol. The MAC protocol is analysed using a centralized design approach and a non-cooperative game theoretic approach. Structural results are obtained and provably convergent stochastic approximation algorithms that can estimate the optimal transmission policies are proposed. Especially, in the game theoretic MAC formulation, it is proved that the best response transmission policies are threshold in the channel state and there exists a Nash equilibrium at which every user deploys a threshold transmission policy. This threshold result leads to a particularly efficient stochastic-approximation-based adaptive learning algorithm and a simple distributed implementation of the MAC protocol. Simulations show that the channel-aware MAC protocols result in system throughputs that increase with the number of users. The thesis also considers opportunistic transmission scheduling from the perspective of a single user using Markov Decision Process (MDP) approaches. Both channel state information and channel memory are exploited for opportunistic transmission. First, a finite horizon MDP transmission scheduling problem is considered. The finite horizon formulation is suitable for short-term delay constraints. It is proved for the finite horizon opportunistic transmission scheduling problem that the optimal transmission policy is threshold in the buffer occupancy state and the transmission time. This two-dimensional threshold structure substantially reduces the computational complexity required to compute and implement the optimal policy. Second, the opportunistic transmission scheduling problem is formulated as an infinite horizon average cost MDP with a constraint on the average waiting cost. An advantage of the infinite horizon formulation is that the optimal policy is stationary. Using the Lagrange dynamic programming theory and the supermodularity method, it is proved that the stationary optimal transmission scheduling policy is a randomized mixture of two policies that are threshold in the buffer occupancy state. A stochastic approximation algorithm and a Q-learning based algorithm that can adaptively estimate the optimal transmission scheduling policies are then proposed.

付記する学位プログラム名: 京都大学卓越大学院プログラム「先端光・電子デバイス創成学」 / 京都大学 / 新制・課程博士 / 博士(工学) / 甲第23905号 / 工博第4992号 / 新制||工||1779(附属図書館) / 京都大学大学院工学研究科電子工学専攻 / (主査)教授 木本 恒暢, 教授 白石 誠司, 准教授 小林 圭 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Identity verification or biometric recognition systems play an important role in our daily lives. Applications include Automatic Teller Machines (ATM), banking and share information retrieval, and personal verification for credit cards. Among the biometric techniques, authentication of speakers by his/her voice is of great importance, since it employs a non-invasive approach and is the only available modality in many applications. However,the performance of Automatic Speaker Verification (ASV) systems degrades significantly under adverse conditions which cause recordings from the same speaker to be different.The objective of this research is to investigate and develop robust techniques for performing automatic speaker recognition over various channel conditions, such as telephony and recorded microphone speech. This research is shown to improve the robustness of ASV systems in three main areas of feature extraction, speaker modelling and score normalization. At the feature level, a new set of dynamic features, termed Delta Cepstral Energy (DCE) is proposed, instead of traditional delta cepstra, which not only greatly reduces thedimensionality of the feature vector compared with delta and delta-delta cepstra, but is also shown to provide the same performance for matched testing and training conditions on TIMIT and a subset of the NIST 2002 dataset. The concept of speaker entropy, which conveys the information contained in a speaker's speech based on the extracted features, facilitates comparative evaluation of the proposed methods. In addition, Frequency Modulation features are combined in a complementary manner with the Mel Frequency CepstralCoefficients (MFCCs) to improve the performance of the ASV system under channel variability of various types. The proposed fused system shows a relative reduction of up to 23% in Equal Error Rate (EER) over the MFCC-based system when evaluated on the NIST 2008 dataset. Currently, the main challenge in speaker modelling is channel variability across different sessions. A recent approach to channel compensation, based on Support Vector Machines (SVM) is Nuisance Attribute Projection (NAP). The proposed multi-component approach to NAP, attempts to compensate for the main sources of inter-session variations through an additional optimization criteria, to allow more accurate estimates of the most dominant channel artefacts and to improve the system performance under mismatched training and test conditions. Another major issue in speaker recognition is that the variability of score distributions due to incompletely modelled regions of the feature space can produce segments of the test speech that are poorly matched to the claimed speaker model. A segment selection technique in score normalization is proposed that relies only on discriminative and reliable segments of the test utterance to verify the speaker. This approach is particularly useful in noisy conditions where using speech activity detection is not reliable at the feature level. Another source of score variability comes from the fact that not all phonemes are equally discriminative. To address this, a new score re-weighting technique is applied to likelihood values based on the discriminative level of each Gaussian component, i.e. each particular region of the feature space. It is found that a limited number of Gaussian mixtures, herein termed discriminative components are responsible for the overall performance, and that inclusion of the other non-discriminative components may only degrade the system performance.

Multiple Input Multiple Output with Orthogonal Frequency Division Multiplexing (MIMOOFDM) has been widely adopted as one of the most promising air interface solutions for future broadband wireless communication systems due to its high rate transmission capability and robustness against multipath fading. However, these MIMO-OFDM advantages cannot be achieved unless the channel state information (CSI) can be obtained accurately and promptly at the receiver to assist coherent detection of data symbols. Channel estimation and training sequence design are, therefore, still open challenges of great interest. In this work, we investigate the Linear Minimum Mean Square Error (LMMSE) channel estimation and design nearly optimal training sequences for MIMO-OFDM systems in spatially correlated fading. We, first, review the LMMSE channel estimation model for MIMO-OFDM in spatially correlated fading channels. We, then, derive a tight theoretical lower bound of the channel estimation Mean Square Error (MSE). By exploiting the information on channel correlation matrices which is available at the transmitter, we design a practical and nearly optimal training sequence for MIMO-OFDM systems . The optimal transmit power allocation for training sequences is found using the Iterative Bisection Procedure (IBP). We also propose an approximate transmit power allocation algorithm which is computationally more efficient than the IBP while maintaining a similar MSE performance. The proposed training sequence design method is also applied to MIMO-OFDM systems where Cyclic Prefixing OFDM (CP-OFDM) is replaced by Zero Padding OFDM - OverLap-Add method (ZP-OFDM-OLA). The simulation results show that the performance of the proposed training sequence is superior to that of all existing training sequences and almost achieves the MSE theoretical lower bound.