An adaptive service framework is expected to support real-time multimedia services in wirless/mobile cellular networks with various classes of traffic and diverse bandwidth requirements. Quality of service (QoS) provisioning in an adaptive framework is another challenging consideration, such as quantifying the level of bandwidth degradation of an ongoing calls and guaranteeing stable QoS levels. Considering both the period and the depth of degradation, the degradation area ratio (DAR) represents the average ratio of a call's degradation and is one of the meaningful measures for adaptive service in call level analysis. In this paper, analytical models for estimating the DAR and finding the optimal control parameters are presented in multi-class traffic call management situations. In complete partitioning capacity based threshold-type call admission control (CAC), a one-dimensional Markov chain with an absorbing state is proposed for estimating the DAR in each traffic class. We formulate a two-leveled optimization problem minimizing the total blocking probabilities subject to QoS requirements and present the procedures required in finding the optimal capacities and threshold values by using modified dynamic programming. In complete sharing capacity based threshold-type CAC, the multidimensional Markov model is approximately reduced to a one-dimensional model in order to reduce complexity and hence calculation time. The reduced model is compared with multidimensional Markov model in numerical examples. The optimization problem is formulated minimizing the total blocking probabilities subject to QoS requirements and the optimal threshold parameters are found by using a genetic algorithm. Performance of two adopted admission policies in adaptive framework situations is illustrated by numerical results.

A polarization-independent liquid crystal (LC) grating with a microscale LC molecular alignment pattern is proposed. The microscale LC alignment pattern is achieved using a microrubbing technique. The optical properties of the proposed LC grating are theoretically discussed in detail using Jones matrix method. Optimum condition for obtaining maximum +1st or -1st diffraction efficiencies is derived. The diffraction efficiency of the LC grating is measured and the diffraction efficiency characteristics are compared with the theoretical result. Furthermore, the dependence of the polarization direction of the incident light on the diffraction efficiency is discussed.

This paper proposes a backlight module which drives multiple cold-cathode fluorescent lamps (CCFLs) with a current mirror technique to equalize the driving current for each lamp. We first adopt a half-bridge parallel-resonant inverter as the main circuit and use a single-input, multiple-output transformer to drive the multi-CCFLs. Next, we introduce current-mirror circuits to create a new current-sharing circuit, in which its current reference node and the parallel-connected multi-load nodes are used to accurately equalize all CCFLs' driving current. This will balance each lamp's brightness and, consequently, improve the picture display quality of the related liquid crystal display (LCD). This paper details the design concept for each component value with the assistance of an actual design example. The results of the example are examined with its actual measurements, which consequently verify the correctness of the proposed control strategy.

In virtue of great progress in computer graphics technologies, CG movies have been getting popular. However, cinematography techniques, which contribute to improving the contents' comprehensibility, need to be learned from professional experiences, and not easily acquired by non-professional people. This paper focuses on film cutting as one of the most important cinematography techniques in conversational scenes, and presents a system that automatically generates shot transitions to improve comprehensibility of CG contents. First, we propose a cognitive model of User Involvement serving as constraints on selecting shot transitions. Then, to examine the validity of the model, we analyze shot transitions in TV programs, and based on the analysis, we implement a CG contents creation system. Results of our preliminary evaluation experiment show the effectiveness of the proposed method, specifically in enhancing contents' comprehensibility.

In this study, the new signal model suitable for ultrawide band (UWB) indoor environments with random angle spread is proposed to estimate the angle-of-arrivals (AOAs) of clusters in a UWB wireless communication. The subspace based estimation technique adopted for this model is investigated and the estimates of the AOA and distribution parameter on the received clusters are obtained. The proposed model and estimation technique are verified using computer simulations, and the performance of the estimation error is analyzed.

A rack-mounted DC power-supply system utilizing Li-ion batteries, which have higher energy density than conventional VRLA batteries, was developed. The system was designed to have the management functions of Li-ion batteries, such as overcharge protection, over-discharge protection, and cell-voltage equalization, by taking operational requirements into consideration. The volume and weight of the entire system were decreased to one-fourth and three-fifths, respectively, of the volume and weight of a conventional system, making the proposed system ideal as a high-energy-density backup power supply. The functions, system configuration, and characteristics of this rack-mounted DC power supply system utilizing Li-ion batteries are described.

A novel evolutionary algorithm is described for designing the topology of spanning tree-based communication networks. Two specific performance objectives are dealt with: the optimum communication spanning tree problem (OCSTP), and the quadratic minimum spanning tree problem (q-MST). Improved network performance is reliably obtained when using the proposed algorithm on accepted benchmark instances, in comparison with the previous best-known approaches. The same methodology can be applied straightforwardly to the design of communication networks with other objectives.

IP-over-optical multilayer networks are capable of flexibly dealing with traffic increases and fluctuations because they support both high-speed transmission using lightpaths and scalable IP hop-by-hop transmission. This paper introduces an architecture for quality of service (QoS) control in such networks, based on the differentiated services (DiffServ) concept. The architecture supports both class-based queues and class-based lightpaths to efficiently handle multiple-QoS-class traffic. QoS schemes based on the proposed architecture are categorized into four types according to their traffic-differentiation and transmission mechanisms. Through simulation, the schemes are evaluated in terms of measures that largely determines network costs. Finally, the conditions under which each scheme is feasible are clarified in terms of the traffic volume and the cost of class-based queues for DiffServ.

This investigation proposes a virtual-FIFO (VFIFO) back-off algorithm for wireless networks. The proposed scheme takes advantage of the central unit (CU) in a wireless network to broadcast a common back-off window size to all the users, significantly alleviating the unfairness of bandwidth utilization in conventional binary exponential back-off (BEB) algorithms. The proposed scheme exploits the CU's capability for collision detection to estimate the number of simultaneously competing users. Additionally, packets generated in a given cycle are split into groups according to their times of arrivals and are guaranteed to be serviced one after another within the next cycle. Although the proposed algorithm is not strictly first come fist served, the FIFO principle is virtually accomplished. Simulation results demonstrate that the standard deviation of delay can be improved by more than two orders and the throughput can be maintained at 0.42 when the number of users approaches infinity. The capture effect even further improves system performance.

An efficient hybrid image vector quantization (VQ) technique based on a classification in the DCT domain is presented in this letter. This algorithm combines two kinds of VQ, predictive VQ (PVQ) and discrete cosine transform domain VQ (DCTVQ), and adopts a simple classifier which employs only three DCT coefficients in the 88 block. For each image block, the classifier switches to the PVQ coder if the block is relatively complex, and otherwise switches to the DCTVQ coder. Experimental results show that the proposed algorithm can achieve higher PSNR values than ordinary VQ, PVQ, JPEG, and JPEG2000 at the same bit-rate.

There is increasing evidence from in vivo recordings in monkeys trained to respond to stimuli by making left- or rightward eye movements, that firing rates in certain groups of neurons in oculo-motor areas mimic drift-diffusion processes, rising to a (fixed) threshold prior to movement initiation. This supplements earlier observations of psychologists, that human reaction-time and error-rate data can be fitted by random walk and diffusion models, and has renewed interest in optimal decision-making ideas from information theory and statistical decision theory as a clue to neural mechanisms. We review results from decision theory and stochastic ordinary differential equations, and show how they may be extended and applied to derive explicit parameter dependencies in optimal performance that may be tested on human and animal subjects. We then briefly describe a biophysically-based model of a pool of neurons in locus coeruleus, a brainstem nucleus implicated in widespread norepinephrine release. This neurotransmitter can effect transient gain changes in cortical circuits of the type that the abstract drift-diffusion analysis requires. We also describe how optimal gain schedules can be computed in the presence of time-varying noisy signals. We argue that a rational account of how neural spikes give rise to simple behaviors is beginning to emerge.

Most of analytical models proposed so far for the IEEE 802.11 distributed coordination function (DCF) focus on saturation performance. In this paper, we develop an analytic model for unsaturation performance evaluation of the IEEE 802.11 DCF with and without slow contention window decrease (SCWD). The model explicitly takes into account the carrier sensing mechanism and an additional backoff interval after successful frame transmission, both of which can be ignored under saturation conditions. Expressions are derived for throughput and delay characteristics by means of the equilibrium point analysis. The accuracy of our model is validated through computer simulation. Numerical results based on the IEEE 802.11b with CCK show that the SCWD can stably achieve approximately 20% performance gain over the normal 802.11 DCF under unsaturation conditions as well as saturation ones.

We propose a learning method combining query learning and a "genetic translator" we previously developed. Query learning is a useful technique for high-accuracy, high-speed learning and reduction of training sample size. However, it has not been applied to practical optical character readers (OCRs) because human beings cannot recognize queries as character images in the feature space used in practical OCR devices. We previously proposed a character image reconstruction method using a genetic algorithm. This method is applied as a "translator" from feature space for query learning of character recognition. The results of an experiment with hand-written numeral recognition show the possibility of training sample size reduction.

In this letter, we propose a protocol sensitive random early detection algorithm for active queue management to improve fairness between TCP and UDP flows and to reduce delay time with small overheads. The algorithm classifies the packets into responsive and unresponsive flows, and applies the RED algorithm individually to each classified group. Using ns-2 simulations, we showed the effectiveness of the proposed PSRED algorithm compared with several well-known AQM schemes, such as RED and RED-PD algorithms.

Performance of the minimum mean square error (MMSE) detection is far below that of the maximum likelihood (ML) detection in a multiuser environment and decreases significantly as the number of co-channel users increases. In this paper, we propose a combined MMSE and ML multiuser detection scheme for space-time block coded (STBC) orthogonal frequency division multiplexing (STBC-OFDM) which has improved performance but with low complexity. In particular, we propose a reduced complexity ML post-detection (ML-PDP) scheme which can correct erroneously estimated bits from the outputs of MMSE multiuser detection. The proposed ML-PDP scheme performs sequential search to detect a predefined number of bits with higher probability of error and then uses ML detection to correct them. Upon controlling the number of corrected bits it is possible to balance the system performance with complexity associated with the ML-PDP. We show that significant improvement can be achieved at the cost of only small additional complexity compared with the MMSE multiuser detection.

Multi-swing trajectories, which refer to those trajectories which oscillate several cycles and then become unbounded, has been a nuisance in general simulation programs for power system stability study since the corresponding transient stability is very difficult to access accurately. In this letter, two possible models are developed to explain possible scenarios of such multi-swing behaviors. Theoretical investigation has strongly indicated a close relationship between multi-swing instability problems and chaotic behaviors of the power system.

The purpose of this paper is to improve a feedback-type adaptive array antenna (AAA) with feedback information quantized by one bit which was presented recently on TDMA system by an author of this paper. The improvement is made by using adaptive, instead of constant, update size of adaptive antenna weights control. Computer simulation results show that the performance of this system is improved to be almost equivalent to the performance of a system without quantization of the feedback information for wide range of fading speed. The results include the effect of control delay time and the maximum Doppler frequency under flat fading and frequency-selective fading.

We present an efficient method to optimize network resource allocations under nonlinear Quality of Service (QoS) constraints. We first propose a suite of generalized proportional allocation schemes that can be obtained by minimizing the information-theoretic function of relative entropy. We then optimize over the allocation parameters, which are usually design variables an engineer can directly vary, either for a particular user or for the worst-case user, under constraints that lower bound the allocated resources for all other users. Despite the nonlinearity in the objective and constraints, we show this suite of resource allocation optimization can be efficiently solved for global optimality through a convex optimization technique called geometric programming. This general method and its extensions are applicable to a wide array of resource allocation problems, including processor sharing, congestion control, admission control, and wireless network power control.

We define discretized Markov transformations and find an algorithm to give the number of maximal-period sequences based on discretized Markov transformations. In this report, we focus on the discretized dyadic transformations and the discretized golden mean transformations. Then we find an algorithm to give the number of maximal-period sequences based on these discretized transformations. Moreover, we define a number-theoretic function related to the numbers of maximal-period sequences based on these discretized transformations. We also introduce the entropy of the maximal-period sequences based on these discretized transformations.

We present a new method to detect weak linear frequency modulated (LFM) signals in strong noise using the chaos oscillator. Chaotic systems are sensitive to specific signals yet immune to noise. With our new method we firstly use the Radon-Wigner transform to dechirp the LFM signal. Secondly, we set up a chaotic oscillator sensitive to weak signals based on the Duffing equation, and poising the system at its critical state. Finally, we input the dechirped sequence into the system as a perturbation of the driving force. A weak signal with the same frequency will lead to a qualitative transition in the system state. The weak signal in the presence of strong noise can then be detected from the phase transition of the phase plane trajectory of the chaotic system. Computer simulation results show that LFM signals with an SNR lower than -27 dB can be detected by this method.