This research proposes efficient calculation methods for the transition matrices in discrete event systems, where the adjacency matrices are represented by directed acyclic graphs. The essence of the research focuses on obtaining the Kleene Star of an adjacency matrix. Previous studies have proposed methods for calculating the longest paths focusing on destination nodes. However, in these methods the chosen algorithm depends on whether the adjacency matrix is sparse or dense. In contrast, this research calculates the longest paths focusing on source nodes. The proposed methods are more efficient than the previous ones, and are attractive in that the efficiency is not affected by the density of the adjacency matrix.

Bloom filters are widely used for various network applications. Because of the limited size of on-chip memory and the large volume of network traffic, Bloom filters are often required to update their contents incrementally. Two techniques have been used for this purpose: cold cache and double buffering. Cold cache outperforms double buffering in terms of the average cache ratio. However, double buffering works much better than cold cache for the worst-case cache hit ratio. In this paper, we propose a new updating scheme for Bloom filters, which updates the contents of Bloom filter incrementally while the assigned memory space is fully utilized. The proposed scheme works better than cold cache in terms of the average cache hit ratio. At the same time, it outperforms double buffering for the worst-case cache hit ratio.

We carried out degradation analysis of a blue phosphorescent organic light emitting diode by both impedance spectroscopy and transient electroluminescence (EL) spectroscopy. The number of semicircles observed in the Cole-Cole plot of the modulus became three to two after the device was operated for 567 hours. Considering the effective layer thickness of the initial and degraded devices did not change by degradation and combining the analysis of the Bode-plot of the imaginary part of the modulus, the relaxation times of emission layer and hole-blocking with electron transport layers changed to nearly the same value by the increase of the resistance of emission layer. Decay time of transient EL of the initial device was coincident with that of the degraded one. These phenomena suggest that no phosphorescence quenching sites are generated in the degraded device, but the number of the emission sites decrease by degradation.

This paper presents a new hierarchical mode segmentation of the observed driving behavioral data based on the multi-level abstraction of the underlying dynamics. By synthesizing the ideas of a feature vector definition revealing the dynamical characteristics and an unsupervised clustering technique, the hierarchical mode segmentation is achieved. The identified mode can be regarded as a kind of symbol in the abstract model of the behavior. Second, the grammatical inference technique is introduced to develop the context-dependent grammar of the behavior, i.e., the symbolic dynamics of the human behavior. In addition, the behavior prediction based on the obtained symbolic model is performed. The proposed framework enables us to make a bridge between the signal space and the symbolic space in the understanding of the human behavior.

We present an attractive approach for OFDM transmission using an adaptive pre-FFT equalizer, which can select ICI reduction mode according to channel condition, and a degenerated-inverse-matrix-based channel estimator (DIME), which uses a cyclic sinc-function matrix uniquely determined by transmitted subcarriers. In addition to simulation results, the proposed system with an adaptive pre-FFT equalizer and DIME has been laboratory tested by using a software defined radio (SDR)-based test bed. The simulation and experimental results demonstrated that the system at a rate of more than 100 Mbps can provide a bit error rate of less than 10-3 for a fast multi-path fading channel that has a moving velocity of more than 200 km/h with a delay spread of 1.9 µs (a maximum delay path of 7.3 µs) in the 5-GHz band.

External interferences can severely degrade the performance of an Over-the-horizon radar (OTHR), so suppression of external interferences in strong clutter environment is the prerequisite for the target detection. The traditional suppression solutions usually began with clutter suppression in either time or frequency domain, followed by the interference detection and suppression. Based on this traditional solution, this paper proposes a method characterized by joint clutter suppression and interference detection: by analyzing eigenvalues in a short-time moving window centered at different time position, clutter is suppressed by discarding the maximum three eigenvalues at every time position and meanwhile detection is achieved by analyzing the remained eigenvalues at different position. Then, restoration is achieved by forward-backward linear prediction using interference-free data surrounding the interference position. In the numeric computation, the eigenvalue decomposition (EVD) is replaced by singular values decomposition (SVD) based on the equivalence of these two processing. Data processing and experimental results show its efficiency of noise floor falling down about 10-20 dB.

Delay Tolerant Networks (DTNs) are able to provide communication services in challenged networks where the end-to-end path between the source and destination does not exist. In order to increase the probability of message delivery, DTN routing mechanisms require nodes in the network to store and carry messages in their local buffer and to replicate many copies. When the limited buffer is consumed, choosing appropriate messages to discard is critical to maximizing the system performance. Current approaches for this are sub-optimal or assumed unrealistic conditions. In this paper, we propose an optimal buffer management scheme for the realistic situations where the bandwidth is limited and messages vary in size. In our scheme, we design a message discard policy that maximizes the message delivery rate. Simulation results demonstrate the efficiency of our proposal.

We consider a problem of global asymptotic stabilization of a class of feedforward nonlinear systems that have the unknown linear growth rate and unknown input delay. The proposed output feedback controller employs a dynamic gain which is tuned adaptively by monitoring the output value. As a result, a priori knowledge on the linear growth rate and delay size are not required in controller design, which is a clear benefit over the existing results.

Workflow nets (WF-nets) are Petri nets which represent workflows. Soundness is a criterion of logical correctness defined for WF-nets. It is known that soundness verification is intractable. In this paper, we propose a method to verify soundness using a Linear Temporal Logic (LTL) model checking tool, SPIN. We give an LTL necessary and sufficient condition to verify soundness for WF-nets without livelock. Acyclic WF-nets have no livelock, but cyclic WF-nets may have livelock. We also give a necessary and sufficient condition to verify livelock. Meanwhile, we show that any LTL model checking tool cannot verify soundness for WF-nets with livelock. We give necessary conditions to verify soundness for them. Those conditions enable us to use SPIN even if a given WF-net has livelock. We also develop a tool to verify soundness based on our method. We show effectiveness of our method by comparing our tool with existing soundness verification tools on verification time for 200 cyclic ACWF-nets.

This paper focuses on fusion estimation algorithms weighted by matrices and scalars, and relationship between them is considered. We present new algorithms that address the computation of matrix weights arising from multidimensional estimation problems. The first algorithm is based on the Cholesky factorization of a cross-covariance block-matrix. This algorithm is equivalent to the standard composite fusion estimation algorithm however it is low-complexity. The second fusion algorithm is based on an approximation scheme which uses special steady-state approximation for local cross-covariances. Such approximation is useful for computing matrix weights in real-time. Subsequent analysis of the proposed fusion algorithms is presented, in which examples demonstrate the low-computational complexity of the new fusion estimation algorithms.

This paper addresses linear quadratic control with state-dependent noise for singularly perturbed stochastic systems (SPSS). First, the asymptotic structure of the stochastic algebraic Riccati equation (SARE) is established for two cases. Second, a new iterative algorithm that combines Newton's method with the fixed point algorithm is established. As a result, the quadratic convergence and the reduced-order computation in the same dimension of the subsystem are attained. As another important feature, a high-order state feedback controller that uses the obtained iterative solution is given and the degradation of the cost performance is investigated for the stochastic case for the first time. Furthermore, the parameter independent controller is also given in case the singular perturbation is unknown. Finally, in order to demonstrate the efficiency of the proposed algorithm, a numerical example is given for the practical megawatt-frequency control problem.

The minimum initial marking problem of Petri nets (MIM) is defined as follows: "Given a Petri net and a firing count vector X, find an initial marking M0, with the minimum total token number, for which there is a sequence δ of transitions such that each transition t appears exactly X(t) times in δ, the first transition is enabled at M0 and the rest can be fired one by one subsequently." In a production system like factory automation, economical distribution of initial resources, from which a schedule of job-processings is executable, can be formulated as MIM. AAD is known to produce best solutions among existing algorithms. Although solutions by AMIM+ is worse than those by AAD, it is known that AMIM+ is very fast. This paper proposes new heuristic algorithms AADO and AMDLO, improved versions of existing algorithms AAD and AMIM+, respectively. Sharpness of solutions or short CPU time is the main target of AADO or AMDLO, respectively. It is shown, based on computing experiment, that the average total number of tokens in initial markings by AADO is about 5.15% less than that by AAD, and the average CPU time by AADO is about 17.3% of that by AAD. AMDLO produces solutions that are slightly worse than those by AAD, while they are about 10.4% better than those by AMIM+. Although CPU time of AMDLO is about 180 times that of AMIM+, it is still fast: average CPU time of AMDLO is about 2.33% of that of AAD. Generally it is observed that solutions get worse as the sizes of input instances increase, and this is the case with AAD and AMIM+. This undesirable tendency is greatly improved in AADO and AMDLO.

Invariants of Petri nets are fundamental algebraic characteristics of Petri nets, and are used in various situations, such as checking (as necessity of) liveness, boundedness, periodicity and so on. Any given Petri net N has two kinds of invariants: a P-invariant is a |P|-dimensional vector Y with Yt A = and a T-invariant is a |T|-dimensional vector X with A X = for the place-transition incidence matrix A of N. T-invariants are nonnegative integer vectors, while this is not always the case with P-invariants. This paper deals only with nonnegative integer invariants (invariants that are nonnegative vectors) and shows results common to the two invariants. For simplicity of discussion, only P-invariants are treated. The Fourier-Motzkin method is well-known for computing all minimal support integer invariants. This method, however, has a critical deficiency such that, even if a given Perti net N has any invariant, it is likely that no invariants are obtained because of an overflow in storing intermediate vectors as candidates for invariants. The subject of the paper is to give an overview and results known to us for efficiently computing minimal-support nonnegative integer invariants of a given Petri net by means of the Fourier-Motzkin method. Also included are algorithms for efficiently extracting siphon-traps of a Petri net.

A Generalized Symbol-rate-increased (GSRI) Pragmatic Adaptive Trellis Coded Modulation (ATCM) is applied to a Multi-carrier CDMA (MC-CDMA) system with bi-orthogonal keying is analyzed. The MC-CDMA considered in this paper is that the input sequence of a bi-orthogonal modulator has code selection bit sequence and sign bit sequence. In, an efficient error correction code using Reed-Solomon (RS) code for the code selection bit sequence has been proposed. However, since BPSK is employed for the sign bit modulation, no error correction code is applied to it. In order to realize a high speed wireless system, a multi-level modulation scheme (e.g. MPSK, MQAM, etc.) is desired. In this paper, we investigate the performance of the MC-CDMA with bi-orthogonal keying employing GSRI ATCM. GSRI TC-MPSK can arbitrarily set the bandwidth expansion ratio keeping higher coding gain than the conventional pragmatic TCM scheme. By changing the modulation scheme and the bandwidth expansion ratio (coding rate), this scheme can optimize the performance according to the channel conditions. The performance evaluations by simulations on an AWGN channel and multi-path fading channels are presented. It is shown that the proposed scheme has remarkable throughput performance than that of the conventional scheme.

In this paper, we propose a new modeling method to express discrete-time hybrid systems with parameter uncertainty as a mixed logical dynamical (MLD) model. In analysis and control of hybrid systems, there are problem formulations in which convex polyhedra are computed, but for high-dimensional systems, it is difficult to solve these problems within a practical computation time. The key idea of this paper is to use an interval method, which is one of the classical methods in verified numerical computation, and to regard an interval as an over-approximation of a convex polyhedron. By using the obtained MLD model, analysis and synthesis of robust control systems are formulated.

Measurement of an individual molar provides rich information for forensic personal identification. We propose a computer-based system for extracting an individual molar from dental panoramic radiographs. A molar is obtained by extracting the region-of-interest, separating the maxilla and mandible, and extracting the boundaries between teeth. The proposed system is almost fully automatic; all that the user has to do is clicking three points on the boundary between the maxilla and the mandible.

Quantification of the hip cartilages is clinically important. In this study, we propose an automatic technique for segmentation and visualization of the acetabular and femoral head cartilages based on clinically obtained multi-slice T1-weighted MR data and a hybrid approach. We follow a knowledge based approach by employing several features such as the anatomical shapes of the hip femoral and acetabular cartilages and corresponding image intensities. We estimate the center of the femoral head by a Hough transform and then automatically select the volume of interest. We then automatically segment the hip bones by a self-adaptive vector quantization technique. Next, we localize the articular central line by a modified canny edge detector based on the first and second derivative filters along the radial lines originated from the femoral head center and anatomical constraint. We then roughly segment the acetabular and femoral head cartilages using derivative images obtained in the previous step and a top-hat filter. Final masks of the acetabular and femoral head cartilages are automatically performed by employing the rough results, the estimated articular center line and the anatomical knowledge. Next, we generate a thickness map for each cartilage in the radial direction based on a Euclidian distance. Three dimensional pelvic bones, acetabular and femoral cartilages and corresponding thicknesses are overlaid and visualized. The techniques have been implemented in C++ and MATLAB environment. We have evaluated and clarified the usefulness of the proposed techniques in the presence of 40 clinical hips multi-slice MR images.

Recently proposed coded bi-directional relaying protocols increase the spectral efficiency by using network codes, which rely on joint packet encoding and exploitation of previously transmitted and stored information. In this letter, we derive the cumulative density function (CDF) and the probability density function (PDF) of received signal-to-noise ratios (SNRs) for two-phase and three-phase bi-directional coded relaying protocols, respectively, over Rayleigh fading channels. Using these results, we compare the outage performances as well as the average capacities of the protocols. From the numerical observations, we can see that the two-phase protocol has better link-level performances than the three-phase protocol when required data rate is greater than 2 for outate performance and transmit SNR at each node is greater than 18 dB for average capacity, respectively. Otherwise, the three-phase protocol performs better.

To explain the variation of the address discharge during an address period, the wall voltage variation during an address period was investigated as a function of the address-on-time by using the Vt closed curves. It was observed that the wall voltage between the scan and address electrodes was decreased with an increase in the address-on-time. It was also observed that the wall voltage variation during an address period strongly depended on the voltage difference between the scan and address electrodes. Based on this result, the modified driving waveform to raise the level of Vscanw, was proposed to minimize the voltage difference between the scan and address electrodes. However, the modified driving waveform resulted in the increase in the falling time of scan pulse. Finally, the overlapped double scan waveform was proposed to reduce a falling time of scan pulse under the raised voltage level of Vscanw, also.

We propose a 2D display and camera arrangement for video communication systems that supports both spatial information between distant sites and user mobility. The implementation of this arrangement is called the "surrounding back screen method." The method enables users to freely come from and go into other users' spaces and provides every user with the direct pointing capability, since there is no apparent spatial barrier separating users, unlike the case of conventional video communication systems. In this paper, we introduce two properties ("sharedness" and "exclusiveness") and three parameters (a distance and two angles) to represent the geometrical relationship between two users. These properties and parameters are used to classify the shared spaces created by a video communication system and to investigate the surrounding back screen method. Furthermore, to demonstrate and explore our surrounding back screen method, we have developed a prototype system, called t-Room. Taking into account practical situations, we studied a practical case where two t-Rooms with different layouts are connected.