A memory address allocation method for digital signal processors of indirect addressing with indexed auto-modification is proposed. At first, address auto-modification amounts for a given program are analyzed. And then, address allocation of program variables are moved and shifted so that both indexed and simple auto-modifications are effectively exploited. For further reduction in overhead codes, a memory address allocation method coupled with computational reordering is proposed. The proposed methods are applied to the existing compiler, and generated codes prove their effectiveness.

This paper newly proposes a method to automatically decompose real scene images into multiple object-oriented component regions. First, histogram patterns of a specific image feature, such as intensity or hue value, are estimated from image sequence and stored up. Next, Gaussian distribution parameters which correspond to object components involved in the scene are estimated by applying the EM algorithm to the accumulated histogram. The number of the components is simultaneously estimated by evaluating the minimum value of Bayesian Information Criterion (BIC). This method can be applied to a variety of computer vision issues, for example, the color image segmentation and the recognition of scene situation transition. Experimental results applied for indoor and outdoor scenes showed the effectiveness of the proposed method.

Hypersequential programming is a new method of concurrent-program development in which the original concurrent program is first serialized, then tested and debugged as a set of sequential programs (scenarios), and finally restored into the target concurrent program by parallelization. Both high productivity and reliability are achieved by hypersequential programming because testing and debugging are done for the serialized versions and the correctness of the serialized programs is preserved during the subsequent parallelization. This paper proposes scenario-based hypersequential programming for reactive multitasking systems that have not only concurrency and nondeterminacy, but also interruption and priority. Petri nets with priority are used to model reactive systems featuring interruption and priority-based scheduling. How reactive systems are made highly reliable by this approach is explained and the effectiveness of the approach is demonstrated through the example of a telephone terminal control program.

Global computing system (GCS) harnesses the idle CPU resources of clients connected to Internet for solving large problems that require high volume of computing power. Since GCS scale to millions of clients, many projects usually adopt coarse-grained scheduling in order to reduce server-side contention at the expense of sacrificing the degree of parallelism and wasting CPU resources. In this paper, we propose a new type of client, i.e., a scheduling proxy that enables adaptive-grained scheduling between the server and clients. While the server allocates coarse-grained work units to scheduling proxies alone, clients download fine-grained work units from a relatively nearby scheduling proxy not from the distant server. By computation of small work units at client side, the turnaround time of work unit can be reduced and the waste of CPU time by timeout can be minimized without increasing the performance cost of contention at the server. In addition, in order not to lose results in the failure of scheduling proxies, we suggest a technique of result caching in clients.

This paper addresses the estimation of time delay between two spatially separated noisy signals by system identification modeling with the input and output corrupted by additive white Gaussian noise. The proposed method is based on a modified adaptive Butler-Cantoni equalizer that decouples noise variance estimation from channel estimation. The bias in time delay estimates that is induced by input noise is reduced by an IIR whitening filter whose coefficients are found by the Burg algorithm. For step time-variant delays, a dual mode operation scheme is adopted in which we define a normal operating (tracking) mode and an interrupt operating (optimization) mode. In the tracking mode, only a few coefficients of the impulse response vector are monitored through L1-normed finite forward differences tracking, while in the optimization mode, the time delay optimized. Simulation results confirm the superiority of the proposed approach at low signal-to-noise ratios.

This paper presents the analysis of the stopping maneuver of the human driver by using a new three-dimensional driving simulator that uses CAVE, which provides stereoscopic immersive vision. First of all, the difference in the driving behavior between 3D and 2D virtual environments is investigated. Secondly, a GMDH is applied to the measured data in order to build a mathematical model of driving behavior. From the obtained model, it is found that the acceleration information has less importance in stopping maneuver under the 2D and 3D environments.

We present a new speech enhancement algorithm in a car environment with two microphones. The car audio signals and other background noises are the target noises to be suppressed. Our algorithm is composed of two main parts, i.e., the spatial and the temporal processes. The multi-channel blind deconvolution (MBD) is applied to the spatial process while the Kalman filter with a second-order high pass filter, for the temporal one. For the fast convergence, the MBD is newly expressed in frequency-domain with a normalization matrix. The final performance evaluated with the severely car noise corrupted speech shows that our algorithm produces noticeably enhanced speech.

In this paper we propose an objective method for assessing the capability of a speech translation system. It automates the translation paired comparison method, which gives a simple, easy to understand TOEIC score proposed by Sugaya et al., to succinctly evaluate a speech translation system. To avoid the expensive evaluation cost of the original method where large manual effort is required, the new objective method automates the procedure by employing an objective metric such as BLEU and DP-based measure. The evaluation results obtained by the proposed method are similar to those of the original method. Also, the proposed method is used to evaluate the usefulness of a speech translation system. It is then found that our speech translation system is useful in general, even to users with higher TOEIC score than the system's.

A flooding algorithm is an indispensable and fundamental network control mechanism for achieving some tasks, such notifying all nodes of some information, transferring data with high reliability, getting some information from all nodes, or to reserve a route by flooding the messages in the network. In particular, the flooding algorithm is greatly effective in the heterogeneous and dynamic network environment such as so-called ubiquitous networks, whose topology is indefinite or changes dynamically and whose nodal function may be simple and less intelligent. Actually, it is applied to grasp the network topology in a sensor network or an ad-hoc network, or to retrieve content information by mobile agent systems. A flooding algorithm has the advantages of robustness and optimality by parallel processing of messages. However, the flooding mechanism has a fundamental disadvantages: it causes the message congestion in the network, and eventually increases the processing time until the flooding control is finished. In this paper, we propose and evaluate methods for producing a more efficient flooding algorithm by adopting the growth processes of primitive creatures, such as molds or microbes.

Model-based movement patterns play a crucial role in evaluating the performance of mobility-dependent Personal Communication Service (PCS) strategies. This study proposes a new normal walk model to represent more closely the daily movement patterns of a mobile station (MS) in PCS networks than a conventional random walk model. A drift angle θ in this model is applied to determine the relative direction in which an MS handoffs in the next one step, based on the concepts that most real trips follow the shortest path and the directions of daily motion are mostly symmetric. Hence, θ is assumed to approach the normal distribution with the parameters: µ is set to 0and σ is in the range of 5to 90. Varying σ thus redistributes the probabilities associated with θ to make the normal mobility patterns more realistic than the random ones. Experimental results verify that the proposed normal walk is correct and valid for modeling an n-layer mesh cluster of PCS networks. Moreover, when σ = 79.5, a normal walk can almost represent, and even replace, a random walk.

In this paper, we investigate packet loss and system dimensioning of feedback (FB) type wavelength division multiplexing (WDM) optical routers under asynchronous and variable packet length self-similar traffic. We first study the packet loss performance for two different types of WDM optical routers under asynchronous and variable packet length self-similar traffic. Based on simulation results, we demonstrate that a 1616 FB type WDM optical router employing more than 4 re-circulated ports without using void filling (VF) algorithm has better performance. We then present the system dimensioning issues of FB type WDM optical routers, by showing the performance of FB type WDM optical routers as a function of the number of re-circulated ports, buffer depth, re-circulation limit, basic delay unit in the fiber delay line optical buffers and traffic characteristics. The sensitivity of the mutual effects of the above parameters on packet loss is investigated in details. Based on our results, we conclude that the FB type WDM optical routers must be dimensioned with the appropriate number of re-circulated ports, re-circulation limits, buffer depth, and optimal basic delay unit in the fiber delay line optical buffers under relevant traffic characteristics to achieve high switching performance.

Process-centered software engineering environments (PSEEs) facilitate controlling complicated software processes. Traditional PSEEs are generally centrally controlled, which may result in the following drawbacks: (1) the server may become a bottleneck and (2) when the server is down, processes need to be suspended. To overcome the drawbacks, we developed a decentralized process engine ADPE (agent-based decentralized process engine). ADPE can be embedded in any PSEE to decentralize the PSEE. This paper presents ADPE.

A directly modulated AM-VSB CATV erbium-doped fiber amplifier (EDFA)-repeated system that uses push-pull modulated distributed feedback (DFB) laser diodes and half-split-band technique is proposed and demonstrated. Push-pull modulation scheme enhances the frequency response of the laser diode, and thus improves the overall performance of the fiber optical CATV systems. Good performances of carrier-to-noise ratio (CNR), composite second order (CSO), and composite triple beat (CTB) were achieved for the full channel band over a 100-km single-mode fiber (SMF) transport.

We propose a new method both for automatically creating non-uniform, context-dependent HMM topologies, and selecting the number of mixture components based on the Variational Bayesian (VB) approach. Although the Maximum Likelihood (ML) criterion is generally used to create HMM topologies, it has an over-fitting problem. Recently, to avoid this problem, the VB approach has been applied to create acoustic models for speech recognition. We introduce the VB approach to the Successive State Splitting (SSS) algorithm, which can create both contextual and temporal variations for HMMs. Experimental results indicate that the proposed method can automatically create a more efficient model than the original method. We evaluated a method to increase the number of mixture components by using the VB approach and considering temporal structures. The VB approach obtained almost the same performance as the smaller number of mixture components in comparison with that obtained by using ML-based methods.

This paper proposes the hierarchical cloud-router network (HCRN) to overcome the scalability limit in a multi-layer generalized multi-protocol label switching (GMPLS) network. We define a group of nodes as a virtual node, called the cloud-router (CR). A CR consists of several nodes or lower-level CRs. A CR is modeled as a multiple switching capability (SC) node when it includes more than one kind of SC, which is fiber SC, lambda SC, time-division multiplexing (TDM) SC, packet SC, even if there are no actual multiple switching capability nodes in the CR. The CR advertises its abstracted CR internal structure, which is abstracted link state information inside the CR. A large-scale, multi-layer network can then achieve scalability by advertising the CR internal structure throughout the whole network. In this scheme, the ends of a link connecting two CRs are defined as interfaces of the CRs. We adopt the CR internal cost scheme between CR interfaces to abstract the network. This CR internal cost is advertised outside the CR via the interfaces. Our performance evaluation has shown that HCRN can handle a larger number of nodes than a normal GMPLS network. It can also bear more frequent network topology changes than a normal GMPLS network.

Given the bivariate polynomial f(x,y), let φ(y) be a root of f(x,y) = 0 with respect to x, i.e. φ(y) is a function of y such that f(φ(y),y) = 0. If φ(y) is analytic at y = 0, then we have its power series expansion φ(y) = α0 + α1y + α2y2 + + αpyp + .(1)Let φ(p)(y) denote φ(y) truncated at yp, i.e. φ(p)(y) = α0 + α1y + α2y2 + + αpyp.(2) It is well-known that we can compute power series roots φ(p)(y) by Newton's method. In fact, given the initial value φ(0)(y) = α0 C, the following Newton's methodφ(k)(y) φ(k-1)(y) - (mod yk+1) (3) computes φ(k)(y) (1 k) in expression (2) efficiently (applying the above formula for k = 1,2,, we can compute the power series root φ(p)(y) of any degree p). The above formula (3) is referred to as "symbolic Newton's method" in this paper. From this formula (3), we can see that the numerical errors in the coefficients αs (s = 0,1,...,k - 1) directly affect the numerical error in the coefficient αk. This implies that the symbolic Newton's method is numerically unstable, i.e., a numerical error in the coefficient αk accumulates as the index k increases. Moreover, with the symbolic Newton's method, even if we need only one coefficient αk, we must compute all coefficients αs (s = 0,1,,k - 1). Thus, when we require only one high degree coefficient αk, the symbolic Newton's method is numerically unstable and inefficient. In this paper, given the integer k (> 0), we present a new algorithm to compute the coefficient αk of (1). The new algorithm is numerically stable and requires no computation of the coefficients other than αk itself.

In this paper, we propose a new feature extraction method that combines both HMT-based denoising and weighted filter bank analysis for robust speech recognition. The proposed method is made up of two stages in cascade. The first stage is denoising process based on the wavelet domain Hidden Markov Tree model, and the second one is the filter bank analysis with weighting coefficients obtained from the residual noise in the first stage. To evaluate performance of the proposed method, recognition experiments were carried out for additive white Gaussian and pink noise with signal-to-noise ratio from 25 dB to 0 dB. Experiment results demonstrate the superiority of the proposed method to the conventional ones.

In this paper, we present Scalable Data Collection (SDC) protocol, a tree-based protocol for collecting data over multi-hop, wireless sensor networks. The design of the protocol aims to satisfy the requirements of sensor networks that every sensor transmits sensed data to a sink node periodically or spontaneously. The sink nodes construct the tree by broadcasting a HELLO packet to discover the child nodes. The sensor receiving this packet decides an appropriate parent to which it will attach, it then broadcasts the HELLO packet to discover its child nodes. Based on this process, the tree is quickly created without flooding of any routing packets. SDC avoids periodic updating of routing information but the tree will be reconstructed upon node failures or adding of new nodes. The states required on each sensor are constant and independent of network size, thereby SDC scales better than the existing protocols. Moreover, each sensor can make forwarding decisions regardless of the knowledge on geographical information. We evaluate the performance of SDC by using the ns-2 simulator and comparing with Directed Diffusion, DSR, AODV, and OLSR. The simulation results demonstrate that SDC achieves much higher delivery ratio and lower delay as well as scalability in various scenarios.

This paper proposes a channel allocation principle that prevents TCP throughput degradation in multihop transmissions in a mesh network based on the carrier sense multiple access with collision avoidance (CSMA/CA) MAC protocol. We first address the relationship between the network topology of wireless nodes and the TCP throughput degradation based on computer simulations. The channel allocation principle is discussed in terms of resolution into a coloring problem based on throughput degradation. The number of required channels for the proposed channel allocation principle is evaluated and it is shown that two channels are sufficient for more than 96% simulated multihop patterns. The proposed channel allocation principle is extendable to generic mesh networks. We also clarify the number of required channels for mesh networks. The simulation results show that three channels are sufficient for more than 98% patterns in the generic mesh networks when the number of nodes is less than 10.

To avoid over-engineered and expensive systems, it is important that the design takes account of variations in optical fiber characteristics due to the presence of many fiber pieces and splices in optical fiber networks. We present a design method for optical fiber networks that employ distributed Raman amplification (DRA), that considers variations in both optical losses at signal and pump wavelengths, Raman gain characteristics and splice losses. Our method can be applied to the design of both newly developed systems and installed systems. We show design examples based on our method and reveal the practicability of our method.