MPLS-based path technology shows promise as a means of realizing reliable IP networks. Real-time services such as VoIP and video-conference supplied through a multi-domain MPLS network must be able to guarantee end-to-end QoS of the inter-domain paths. Thus, it is important to allocate an appropriate QoS class to the inter-domain paths in each domain traversed by the inter-domain paths. Because each domain has its own policy for QoS class allocation, it is necessary to adaptively allocate the optimum QoS class based on estimation of the QoS class allocation policies in other domains. This paper proposes two kinds of adaptive QoS class allocation schemes, assuming that the arriving inter-domain path requests include the number of downstream domains traversed by the inter-domain paths and the remaining QoS value toward the destination nodes. First, a measurement-based scheme, based on measurement of the loss rates of inter-domain paths in the downstream domains, is proposed. This scheme estimates the QoS class allocation policies in the downstream domains, using the measured loss rates of path requests. Second, a state-dependent type scheme, based on measurement of the arrival rates of path requests in addition to the loss rates of paths in the downstream domains, is also proposed. This scheme allows an appropriate QoS class to be allocated according to the domain state. This paper proposes an application of the Markov decision theory to the modeling of state-dependent type scheme. The performances of the proposed schemes are evaluated and compared with those of the other less complicated non-adaptive schemes using a computer simulation. The results of the comparison reveal that the proposed schemes can adaptively increase the number of inter-domain paths accommodated in the considered domain, even when the QoS class allocation policies change in the other domains and the arrival pattern of path requests varies in the considered domain.

This paper presents methods for controlling the intensity of emotional expressions and speaking styles of an arbitrary speaker's synthetic speech by using a small amount of his/her speech data in HMM-based speech synthesis. Model adaptation approaches are introduced into the style control technique based on the multiple-regression hidden semi-Markov model (MRHSMM). Two different approaches are proposed for training a target speaker's MRHSMMs. The first one is MRHSMM-based model adaptation in which the pretrained MRHSMM is adapted to the target speaker's model. For this purpose, we formulate the MLLR adaptation algorithm for the MRHSMM. The second method utilizes simultaneous adaptation of speaker and style from an average voice model to obtain the target speaker's style-dependent HSMMs which are used for the initialization of the MRHSMM. From the result of subjective evaluation using adaptation data of 50 sentences of each style, we show that the proposed methods outperform the conventional speaker-dependent model training when using the same size of speech data of the target speaker.

A receiver access control scheme is proposed to protect the multicast distribution tree from DoS attack induced by unauthorized use of IGMP, by extending the security-related functionality of IGMP. Based on a specific network and business model adopted for commercial deployment of IP multicast applications, a key management scheme is also presented for bootstrapping the proposed access control as well as accounting and billing for CP (Content Provider), NSP (Network Service Provider), and group members.

Resource search is a fundamental problem in large-scale and highly dynamic Peer-to-Peer (P2P) systems. Unstructured search approaches are widely used because of their flexibility and robustness. However, such approaches incur high communication cost. The index-dissemination-based search is a kind of efficient unstructured search approach. We investigate such approaches with respect to minimize the system communication cost. Based on a dynamic system model that peers continuously leave and join, we solve two problems. One problem is how to efficiently disseminate and maintain a given number of indices. Another is to determine the optimal number of indices for each resource object of a given popularity. Finally, we propose an optimized index dissemination scheme which is fully decentralized and self-adaptive. A remarkable advantage is that the scheme yields no additional communication cost to achieve the self-adaptive feature.

Trust negotiation is an authorizing technique based on digital credentials, in which both a user and a server gradually establish trust in each other by repeatedly exchanging their credentials. A trust negotiation strategy is a function that answers a set of credentials to disclose to the other party, depending on policies and the set of already disclosed credentials. The disclosure tree strategy (DTS), proposed by Yu et al., is one of the strategies that satisfies preferable properties. DTS in a simple implementation requires exponential time and space; however, neither an efficient algorithm nor the lower-bound of its complexity was known. In this paper, we investigate the computational complexity of DTS. We formulate subproblems of DTS as problems on derivation trees of a context-free grammar (CFG), and analyze the computational complexity of the subproblems using the concepts of CFGs. As a result, we show that two subproblems EVL and MSET of DTS are NP-complete and NP-hard, respectively, while both are solvable in polynomial time if we modify EVL not to require non-redundancy and MSET not to answer any subset useless for leading the negotiation to success.

An energy-efficient clustering scheme to maximize the network lifetime is presented in IEEE 802.15.4 networks. In the proposed clustering scheme, even though the cluster is divided into several sub-clusters in order to decrease data redundancies, the sub-CH does not transmit the beacon frame due to the problem of beacon collision. Our clustering scheme also allows the CH to control the size of the sub-cluster according to the residual energy of the sub-CH. The performance of the proposed scheme is verified by simulations that demonstrate how our scheme provides a better network lifetime than the conventional scheme.

Body Area Networks (BAN) can provide a wide range of applications including medical support, healthcare monitoring, and consumer electronics with increased convenience or comfort. To harmonize with the strong demands from both medical and healthcare societies, and information and communications technology (ICT) industries, IEEE 802.15.6 task group (TG6) was set up to develop an IEEE wireless standard on BAN. This paper presents a general guidance to TG6. Some pre-works to set up TG6 are reviewed. The objectives, main topics, current status are described in details.

A Feedback Error Learning (FEL) scheme was found to be applicable to joint angle control by Functional Electrical Stimulation (FES) in our previous study. However, the FEL-FES controller had a problem in learning of the inverse dynamics model (IDM) in some cases. In this paper, methods of applying the FEL to FES control were examined in controlling 1-DOF movement of the wrist joint stimulating 2 muscles through computer simulation under several control conditions with several subject models. The problems in applying FEL to FES controller were suggested to be in restricting stimulation intensity to positive values between the minimum and the maximum intensities and in the case of very small output values of the IDM. Learning of the IDM was greatly improved by considering the IDM output range with setting the minimum ANN output value in calculating ANN connection weight change.

This work elucidates the evolution of three generations of the laboratory information system in the National Taiwan University Hospital, which were respectively implemented in an IBM Series/1 minicomputer, a client/server and a plug-and-play HL7 interface engine environment respectively. The experience of using the HL7 healthcare information exchange in the hospital information system, laboratory information system, and automatic medical instruments over the past two decades are illustrated and discussed. The latest design challenge in developing intelligent laboratory information services is to organize effectively distributed and heterogeneous medical instruments through the message gateways. Such experiences had spread to some governmental information systems for different purposes in Taiwan; besides, the healthcare information exchange standard, software reuse mechanism, and application service provider adopted in developing the plug-and-play laboratory information system are also illustrated.

This paper investigates and analyzes the resistive averaging network and interpolation technique to estimate the power consumption of preamplifier arrays in a flash analog-to-digital converter (ADC). By comparing the relative power consumption of various configurations, flash ADC designers can select the most power efficient architecture when the operation speed and resolution of a flash ADC are specified. Based on the quantitative analysis, a compact 5-bit flash ADC is designed and fabricated in a 0.13-µm CMOS process. The proposed ADC consumes 180 mW from a 1.2-V supply and occupies 0.16-mm2 active area. Operating at 3.2 GS/s, the ENOB is 4.44 bit and ERBW 1.65 GHz. At 4.2 GS/s, the ENOB is 4.20 bit and ERBW 1.75 GHz. This ADC achieves FOMs of 2.59 and 2.80 pJ/conversion-step at 3.2 and 4.2 GS/s, respectively.

The medical body area network (MBAN) is an emerging technology to resolve the small area connection issues around human body, especially for the medical applications. This paper proposes a dynamic TDMA (DTDMA) protocol for MBAN with focus on the dependability and power efficiency. In DTDMA, the slots are allocated by the MBAN coordinator only to the devices which have buffered packets and released to other devices after the current allocation. Through the adaptive allocation of the slots in a DTDMA frame, the MBAN coordinator adjusts the duty cycle adaptively with the traffic load. Comparing with the IEEE 802.15.4 MAC protocol, the DTDMA provides more dependability in terms of lower packet dropping rate and less energy consumption especially for an end device of a MBAN.

An adaptive zero forcing maximum likelihood soft input soft output (AZFML-SISO) detector for multiple input multiple output (MIMO) wireless systems is presented. Its performance in an iterative MIMO receiver is analyzed. The AZFML-SISO detector calculates the soft outputs, applying the ML approach to the list that contains only those signal vectors limited by a hypersphere around the zero forcing (ZF) solution. The performance of the algorithm is evaluated on a communication system based on the standard for single carrier broadband wireless communication IEEE 802.16, with three transmit and three receive antennas. It is shown by computer simulation that the computational complexity in an average sense of the receiver running the AZFML-SISO algorithm is reduced by 90% at the SNR values of 30 dB and by 50% for SNR values of 15 dB in comparison to the receiver with an ML detector, while the system performance degrades by less than 1 dB.

In this letter, we propose a novel approach to speech/music classification based on the support vector machine (SVM) to improve the performance of the 3GPP2 selectable mode vocoder (SMV) codec. We first analyze the features and the classification method used in real time speech/music classification algorithm in SMV, and then apply the SVM for enhanced speech/music classification. For evaluation of performance, we compare the proposed algorithm and the traditional algorithm of the SMV. The performance of the proposed system is evaluated under the various environments and shows better performance compared to the original method in the SMV.

Break prediction is an important step in text-to-speech systems as break indices (BIs) have a great influence on how to correctly represent prosodic phrase boundaries. However, an accurate prediction is difficult since BIs are often chosen according to the meaning of a sentence or the reading style of the speaker. In Japanese, the prediction of an accentual phrase boundary (APB) and major phrase boundary (MPB) is particularly difficult. Thus, this paper presents a method to complement the prediction errors of an APB and MPB. First, we define a subtle BI in which it is difficult to decide between an APB and MPB clearly as a variable break (VB), and an explicit BI as a fixed break (FB). The VB is chosen using the classification and regression tree, and multiple prosodic targets in relation to the pith and duration are then generated. Finally, unit-selection is conducted using multiple prosodic targets. The experimental results show that the proposed method improves the naturalness of synthesized speech.

Symmetry constrains are the constraints that the given cells should be placed symmetrically in design of analog ICs. We use O-tree to represent placements and propose a decoding algorithm which can obtain one of the minimum placements satisfying the constraints. The decoding algorithm uses linear programming, which is too much time consuming. Therefore we propose a graph based method to recognize if there exists no placement satisfying both the given symmetry and O-tree constraints, and use the method before application of linear programming. The effectiveness of the proposed method was shown by computational experiments.

In this paper, we study deterministic linear pushdown tree automata (deterministic L-PDTAs) and some variations. Since recognition of an input tree by a deterministic L-PDTA can be done in linear time, deterministic L-PDTAs are applicable to many kinds of applications. A strict hierarchy will be shown among the classes of tree languages defined by a variety of deterministic L-PDTAs. It will be also shown that deterministic L-PDTAs are weakly equivalent to nondeterministic L-PDTAs.

We consider the problem of secret key agreement in Gaussian Maurer's Model. In Gaussian Maurer's model, legitimate receivers, Alice and Bob, and a wire-tapper, Eve, receive signals randomly generated by a satellite through three independent memoryless Gaussian channels respectively. Then Alice and Bob generate a common secret key from their received signals. In this model, we propose a protocol for generating a common secret key by using the result of soft-decision of Alice and Bob's received signals. Then, we calculate a lower bound on the secret key rate in our proposed protocol. As a result of comparison with the protocol that only uses hard-decision, we found that the higher rate is obtained by using our protocol.

A graph is an interval graph if and only if each vertex in the graph can be associated with an interval on the real line such that any two vertices are adjacent in the graph exactly when the corresponding intervals have a nonempty intersection. A number of interesting applications for interval graphs have been found in the literature. In order to find structural features common to structural data which can be represented by intervals, this paper proposes new interval graph structured patterns, called linear interval graph patterns, and a polynomial time algorithm for finding a minimally generalized linear interval graph pattern explaining a given finite set of interval graphs.

The spanning tree problem is to find a tree that connects all the vertices of G. This problem has many applications, such as electric power systems, computer network design and circuit analysis. Klein and Stein demonstrated that a spanning tree can be found in O(log n) time with O(n+m) processors on the CRCW PRAM. In general, it is known that more efficient parallel algorithms can be developed by restricting classes of graphs. Circular permutation graphs properly contain the set of permutation graphs as a subclass and are first introduced by Rotem and Urrutia. They provided O(n2.376) time recognition algorithm. Circular permutation graphs and their models find several applications in VLSI layout. In this paper, we propose an optimal parallel algorithm for constructing a spanning tree on circular permutation graphs. It runs in O(log n) time with O(n/log n) processors on the EREW PRAM.

Let T be a node-weighted tree with n nodes, and let π(u,v) denote the path between two nodes u and v in T. We address two problems: (i) Path Maximum Query: Preprocess T so that, for a query pair of nodes u and v, the maximum weight on π(u,v) can be found quickly. (ii) Path Maximum Sum Query: Preprocess T so that, for a query pair of nodes u and v, the maximum weight sum subpath of π(u,v) can be found quickly. For the problems we present solutions with O(1) query time and O(n log n) preprocessing time.