Caching at the Web proxy server plays an important role in reducing the response time, the network traffic, and the load of Web servers. Many recent studies have proposed and examined the replacement and consistency policies for the proxy cache, which plays a central role in the performance of caching components. For better performance, they exploit various metadata of Web objects, such as the reference count, reference time, and modification time information of past behaviors, to estimate the re-reference likelihood and freshness of the objects. However, all of these known to the authors use the metadata only when the actual object is in the cache. We observed from various proxy traces that about 20-30% of clients' requests incurred only the validity checks of cached objects without transferring actual objects from the proxy server. In this case, only the metadata are necessary at the proxy server. This paper proposes a proxy cache consistency policy that uses the metadata even for absent objects. These include the time information of evicted objects from the cache and those out of the header-only replies from Web servers. Trace-driven simulations with public proxy cache traces show that our policy reduces the response time and the number of connections to Web servers significantly.

We propose a new structure of decision feedback adaptive equalizer (DFE) suitable for use in mobile radio systems. The proposed structure named Commutating Decision Feedback Equalizer (CDFE) has two DFEs that operate in a commutating fashion; the two DFEs commutate between training and equalization. Such a commutating operation effectively lengthens the equalizer tracking period over time variant channels. Thus, the CDFE has a superior performance over the conventional DFE in fading channels. Simulation results are presented in the paper.

Using the chirped grating with temperature control, we demonstrated the adaptive dispersion compensation at 40 Gbit/s RZ transmission. The simple monitoring of the 40 GHz frequency component enables us to automatic control of the adaptive dispersion compensator.

Based on filtering ground clutter power directly in the frequency domain, a new non-coefficient Adaptive MTI (AMTI) scheme is presented in this letter. The results of simulation example show that this scheme has smaller signal-to-noise ratio loss than the classical AMTI based on spectral estimation, as well as high improvement factor.

Using the chirped grating with temperature control, we demonstrated the adaptive dispersion compensation at 40 Gbit/s RZ transmission. The simple monitoring of the 40 GHz frequency component enables us to automatic control of the adaptive dispersion compensator.

Infostations serve a demand for multimedia services with high quality and high data rate. The challenge for Infostation system design is how to download as many information bits when a mobile user drives through an Infostation cell. A variable rate TDMA/TDD radio architecture is chosen for study and experimental implementation because of its flexibility in a multi-user environment. A symbol rate and rate compatible punctured convolutional code controlled adaptive transmission scheme is proposed for the Infostation radio design. Data throughput is analyzed for a mobile user passing through an Infostation cell. The analysis indicates that three data rates at 0.25, 1.0 and 2.0 Mbps achieve greater than 85% of the theoretical throughput while simplifying the implementation. The punctured convolutional code is studied to maximize the Infostation throughput. A recommendation is made to use rate 1/2 coding scheme. An efficient rate adaptation algorithm is proposed and it can track the Rayleigh fading channel well and the capacity loss is negligible in various conditions.

Call admission control (CAC) is becoming vital for multimedia services in the ability of wireless/mobile networks to guarantee Quality of Service (QoS) partially due to the network's limited capacity. In this paper, we propose an optimal call admission control scheme with bandwidth reallocation algorithm (multi-class-CAC-BRA) for multi-classes of adaptive multimedia services in wireless/mobile networks. The multi-class-CAC-BRA approach optimizes revenue for service providers and satisfies QoS requirements for service users. The proposed approach adopts semi-Markov Decision Process to model both call admission control and bandwidth reallocation algorithm. In other words, whenever decisions are made, decisions are made for both call admission control and bandwidth reallocation. Since the non-adaptive multimedia traffic is a special case of the adaptive multimedia traffic, the non-adaptive optimal CAC scheme is a special case of our optimal multi-class-CAC-BRA scheme. Furthermore, the Interior-point Method in linear programming is used to solve the optimal decision problem. Simulation results reveal that the proposed multi-class-CAC-BRA scheme adapts itself well to adaptive multi-class multimedia traffic, achieves optimal revenue, and satisfies QoS requirements that are the upper bounds of handoff dropping probabilities. Our approach solves the optimal adaptive multimedia CAC problem. We believe that this work has both theoretical and practical significance.

Off-line state identification methods for a sequential machine using a homing sequence or an adaptive homing sequence (AHS) are well-known in the automata theory. There are, however, so far few studies on the subject of the on-line state estimator such as a state observer (SO) which is used in the linear system theory. In this paper, we shall construct such an SO for a Moore machine based on the state identification process by means of AHSs, and discuss the convergence property of the SO.

This paper describes a unique motion estimation and compensation (ME/MC) hardware architecture for a scene-adaptive algorithm. By statistically analyzing the characteristics of the scene being encoded and controlling the encoding parameters according to the scene, the quality of the decoded image can be enhanced. The most significant feature of the architecture is that the two modules for ME/MC can work independently. Since a time interval can be inserted between the operations of the two modules, a scene-adaptive algorithm can be implemented in the architecture. The ME/MC architecture is loaded on a single-chip MPEG-2 video encoder.

To reduce an amount of computation of full search algorithm for fast motion estimation, we propose a new and fast matching algorithm without any degradation of predicted images. The computational reduction without any degradation comes from adaptive matching scan algorithm according to the image complexity of the reference block in current frame. Experimentally, we significantly reduce the computational load compared with conventional full search algorithm.

This paper evaluates through laboratory and field experiments the combined effect of the coherent adaptive antenna array diversity (CAAAD) receiver and signal-to-interference plus background noise ratio (SINR)-based fast transmit power control (TPC) in order to improve performance beyond that of space diversity (SD) with maximal ratio combining (MRC) in all low-to-high signal-to-interference power ratio (SIR) channels in the W-CDMA reverse link. Although the previously proposed CAAAD receiver comprising an adaptive antenna array based on the minimum mean square error (MMSE) criterion and a coherent Rake combiner was very effective in suppressing interference in low SIR (interference is severe) channels, SD employing MRC in noise limited channels (high SIR) outperformed the CAAAD because of its uncorrelated reception of fading variation due to its large antenna separation. The laboratory experimental results showed that the required average transmit signal energy per bit-to-background noise spectrum density (Eb/N0) with the CAAAD receiver using fast TPC is lower than that with an SD receiver over a wide range of maximum Doppler frequency values from fD = 5 Hz to 500 Hz in a low-to-high SIR channel. The results of the field experiments also showed that combining CAAAD and fast TPC is a powerful means to reduce severe multiple access interference (MAI) from high rate users in a low-to-high SIR environment and is more effective than using the SD receiver with the same number of antennas, i.e., the measured BER was improved by approximately one order of magnitude, when the relative transmit power of the desired user was 8 dB with two antennas at the average received SIR at the antenna input of -12 dB.

This paper describes a method for classification of hematoxylin and eosin (HE)-stained breast tumor images into benign or malignant using the adaptive searching ability of artificial organisms. Each artificial organism has some attributes, such as, age, internal energy and coordinates. In addition, the artificial organism has a differentiation function for evaluating "malignant" or "benign" tumors and the adaptive behaviors of each artificial organism are evaluated using five kinds of texture features. The texture feature of nuclei regions in normal mammary glands and that of carcinoma regions in malignant tumors are treated as "self" and "non-self," respectively. This model consists of two stages of operations for detecting tumor regions, the learning and searching stages. At the learning stage, the nuclei regions are roughly detected and classified into benign or malignant tumors. At the searching stage, the similarity of each organism's environment is investigated before and after the movement for detecting breast tumor regions precisely. The method developed was applied to 21 cases of test images and the distinction between malignant and benign tumors by the artificial organisms was successful in all cases. The proposed method has the following advantages: the texture feature values for the evaluation of tumor regions at the searching stage are decided automatically during the learning stage in every input image. Evaluation of the environment, whether the target pixel is a malignant tumor or not, is performed based on the angular difference in each texture feature. Therefore, this model can successfully detect tumor regions and classify the type of tumors correctly without affecting a wide variety of breast tumor images, which depends on the tissue condition and the degree of malignancy in each breast tumor case.

It is difficult for an adaptive array to reduce interference signals efficiently from received signals when the interference signals and desired signal are closely located. This is a problem for a spatial division multiple access (SDMA) system using the multibeam adaptive array as a multiuser detector. In this paper, we propose a space domain multistage interference canceller (SD-MIC) for the SDMA system. Its performance is evaluated by computer simulations, assuming Japanese personal handy phone system (PHS) uplink environments. The results show remarkable improvement in high spatial correlation situations.

Improvement of direct sequence spread spectrum (DSSS) communication systems' performance using a lattice based adaptive infinite impulse response (IIR) notch filter with a simplified adaptation algorithm is presented. The improvement is shown to be achieved by rejection of a narrowband interference in a received DSSS binary phase shift keying (BPSK) signal. Sources of noise generated by an adaptive IIR notch filter are also studied. Apart from noise associated with input additive white gaussian noise, noise attributed to leakage sinusoids due to fluctuation of steady-state variable coefficient is also analysed. Using statistical properties of notch filter and pseudonoise (PN) correlator outputs, improvement of the performance of a DSSS system gained by the use of interference rejection filter is shown. Computer simulation results are used to confirm analytically derived expressions.

In this paper, a novel cumulant-based adaptive notch filtering technique for the enhancement and tracking of a single sinusoid in additive noise is presented. In this technique, the enhanced signal is obtained as the output of a narrow bandpass filter implemented using a second-order pole-zero constraint IIR adaptive notch filter, which needs only one coefficient to be updated. The filter coefficient, which leads to identifying and tracking the sinusoidal frequency, is updated using a suggested adaptive algorithm employing a recursive estimate of the kurtosis and only one-sample-lag point of a selected one-dimensional fourth-order cumulant slice of the input signal. Therefore, the proposed technique provides automatically resistance to additive Gaussian noise. It is also shown that the presented technique outperforms the correlation-based counterpart in handling additive non-Gaussian noise. Simulation results are provided to show the effectiveness of the proposed algorithm in comparison with the correlation-based lattice algorithm.

This paper presents efficient time slot assignment algorithms applicable to the uplink of SDMA system. A frame consists of one control time slot and multiple communication time slots where terminals in different angular positions share the same time slot. In the proposed algorithms, a time slot is assigned to a new terminal considering not only the signal quality of the new terminal but also the signal quality of active terminals. Simple calculation method for estimated signal-to-interference plus noise ratio (SINR) is employed to decrease the computational complexity. The performance of the proposed algorithms is evaluated by computer simulation and compared with sectorized systems to show the validity of the proposed algorithms.

A speaker adaptation technique that maximizes the observation probability of an input speech is proposed. It is applied to semi-continuous hidden Markov model (SCHMM) speech recognizers. The proposed algorithm adapts the mean µ and the covariance Σ iteratively by the gradient search technique so that the features of the adaptation speech data could achieve maximum observation probabilities. The mixture coefficients and the state transition probabilities are adapted by the model interpolation scheme. The main advantage of this scheme is that the means and the variances, which are common to all states in SCHMM, are adapted independently from the other parameters of SCHMM. It allows fast and precise adaptation especially when there is a large acoustic mismatch between the reference model and a new speaker. Also, it is possible that this scheme could be adopted to other areas which use codebook. The proposed adaptation algorithm was evaluated by a male speaker-dependent, a female speaker-dependent, and a speaker-independent recognizers. The experimental results on the isolated word recognition showed that the proposed adaptation algorithm achieved 46.03% average enhancement in the male speaker-dependent recognizer, 52.18% in the female speaker-dependent recognizer, and 9.84% in the speaker-independent recognizer.

In this paper we propose a new simplified algorithm for cascaded second order adaptive notch filters implemented using an allpass filter, for elimination of multiple sinusoids. Each of the stages of the notch filter is implemented using direct form second order allpass filter. We also present an analysis which compares the proposed algorithm with the conventional simplified algorithm, and which indicates that the proposed algorithm has a reduced bias in the estimation of the multiple input sinusoids. Simulation results that have been provided confirm this analysis.

This paper proposes a new adaptation-mode control (AMC) for a robust adaptive microphone array with an adaptive blocking matrix (RAMA-ABM). The proposed AMC is based on cross correlations of two microphone signals and uses a state machine for controlling the adaptation to avoid target-signal cancellation. Evaluation with sound data obtained in different acoustic environments demonstrates that the noise reduction by the proposed AMC is 3 dB better than that by the AMC based on the SNR estimate. Subjective listening tests show that the quality of the output signal by the proposed AMC is comparable to or even better than those by the conventional AMCs.

This paper proposes a low-distortion noise canceller and its learning algorithm which is robust against crosstalk and is applicable for continuous sounds. The proposed canceller consists of two stages: cancellation of the crosstalk and cancellation of the noise. A recursive filter reduces the number of computations for noise cancellation stage. Separate filters for the adaptation and the filtering are introduced for crosstalk cancellation. Computer simulations show 10 dB improvement of the error power.