Available Bit Rate (ABR) flow control is an effective measure in ATM network congestion control. In large scale and high-speed network, the simplicity of algorithm is crucial to optimize the switch performance. Although the binary flow control is very simple, the queue length and allowed cell rate (ACR) controlled by the standard EFCI algorithm oscillate with great amplitude, which has negative impact on the performance, so its applicability was doubted, and then the explicit rate feedback mechanism was introduced and explored. In this study, the model of binary flow control is built based on the fluid flow theory, and its correctness is validated by simulation experiments. The linear model describing the source end system how to regulate the cell rate is obtained through local linearization method. Then, we evaluate and analyze the standard EFCI algorithm using the describing function approach, which is well-developed in nonlinear control theory. The conclusion is that queue and ACR oscillations are caused by the inappropriate nonlinear control rule originated from intuition, but not intrinsic attribute of the binary flow control mechanism. The simulation experiments validate our analysis and conclusion. Finally, the new scheme about parameter settings is put forward to remedy the weakness existed in the standard EFCI switches without any change on the hardware architecture. The numerical results demonstrate that the new scheme is effective and fruitful.

This paper presents a novel layout approach using dual supply voltage technique. In Placing and Routing (P&R) phase, conventional approaches for dual supply voltages need to separate low supply voltage cells from high voltage ones. Consequently its layout tends to be complex compared with single supply voltage layout. Our layout approach uses cells having two supply voltage rails. Making these cells is difficult in bulk due to increase in area by n-well isolation or in delay by negative body bias caused by sharing n-well. On the other hand, making cells with two supply voltage rails is easy in body-tied PD-SOI owing to trench isolation of each body of transistor. Since our approach for dual supply voltages offers freedom for placement as much as conventional ones for single supply voltage, exsting P&R tools can be used without special operation. Simulation results with MCNC circuits and adders show that our approach reduces power by 23% and 25%, respectively, showing almost the same delay with single supply voltage layout.

This paper presents a new analysis result of two-dimensional four-phase abdominal CT images using variational Bayesian mixture of ICA. The four-phase CT images are assumed to be comprised of several exclusive areas, and each area is generated by a set of corresponding independent components. ICA mixture analysis results show that the CT images could be divided into a set of clinically and anatomically meaningful components. Initial analysis of the independent components shows its promising prospects in medical image processing and computer-aided diagnosis.

The window flow control based end-to-end TCP congestion control may cause unfair resource allocation among multiple TCP connections with different RTTs (round trip times) at a bottleneck link. In this paper, in order to improve this unfairness, we propose the active ECN which is an ECN based active queue mechanism (AQM). A bottleneck router with the proposed mechanism marks TCP segments with a probability which depends on the RTT of each connection. By enabling the TCP senders to reduce their transmission rate when their packets are marked, the proposed mechanism can realize the same transmission rate among TCP connections with different RTTs. Furthermore, the active ECN can directly mark ACKs from TCP receivers, while the conventional ECN marks TCP segments coming from the TCP senders. As a result, the queue length distribution at the bottleneck link gets stabilized, because the sender can quickly react to the marking according to variation of the queue length.

We have integrated a phase change random access memory (PRAM), completely based on 0.24 µm-CMOS technologies using nitrogen doped GeSbTe films. The Ge2Sb2Te5 (GST) thin films are well known to play a critical role in writing current of PRAM. Through device simulation, we found that high-resistive GST is indispensable to minimize the writing current of PRAM. For the first time, we found the resistivity of GST film can be controlled with nitrogen doping. Doping nitrogen to GST film successfully reduced writing current. A 0.24 µm PRAM using N-doped GST films were demonstrated with writing pulse of 0.8 mA-50 ns for RESET and 0.4 mA-100 ns for SET. Also, the cell endurance has been enhanced with grain growth suppression effect of dopant nitrogen. Endurance performance of fully integrated PRAM using N-doped GST shows no fail bit up to 2E9 cycles. Allowing 1% failures, extrapolation to 85 indicates retention time of 2 years. All the results show that PRAM is one of the most promising candidates in the market for the next generation memories.

The transformation of a data set using a second-order polynomial mapping to find statistically independent components is considered (quadratic independent component analysis or ICA). Based on overdetermined linear ICA, an algorithm together with separability conditions are given via linearization reduction. The linearization is achieved using a higher dimensional embedding defined by the linear parametrization of the monomials, which can also be applied for higher-order polynomials. The paper finishes with simulations for artificial data and natural images.

Many algorithms have been introduced to obtain giga-bit routing performance by reducing searching time. As most of them, however, have not considered the importance of update time and memory requirement seriously, they couldn't work well in real networks. We propose a flexible and fast IP lookup algorithm, named FFILA, considering these factors and compare the performance of our scheme with that of the conventional scheme of Patricia trie.

Current IP network has become the dominant paradigm for all networking environments. The significant cause of packet losses in such heterogenous networks is no longer limited to network congestion. Traditional TCP interprets every packet loss as caused by congestion which may be not the case in the current Internet. Misinterpretation of wireless random loss as an indication of network congestion results in TCP slowing down its sending rate unnecessarily. In this paper, we propose a new variant of TCP Vegas named RedVegas. By using the innate nature of Vegas and congestion indications marked by routers, RedVegas may detect random packet losses precisely. Through the packet loss differentiation, RedVegas reacts appropriately to the losses, and therefore the throughput of connection over heterogeneous networks can be significantly improved.

As the Internet proliferates, there has been a growing interest in supporting multiparty collaborative applications. It has led to the emergence of many-to-ma ny reliable multicast. Congestion control is a key task in reliable multicast along with error control. However, existing tree-based congestion control schemes such as TRAMCC and MTCP are designed for one-to-many reliable multicast and have some drawbacks when they are used for many-to-many reliable multicast. We propose an efficient congestion control mechanism, MTRMCC, for tree-based many-to-many reliable multicast protocols. The proposed scheme is based on the congestion windowing mechanism and a rate controller is used in addition. The feedback for error recovery is exploited for congestion control as well to minimize the overhead at the receivers. The ACK timer and the NACK timers are set dynamically reflecting the network traffic changes. The rate regulation algorithm in the proposed scheme is designed to help the flows sharing the same link to achieve the fair share quickly. The performance of the proposed scheme is evaluated using network simulator ns-2. The simulation results show that the proposed scheme outperforms TRAMCC in terms of intra-session fairness and supports responsiveness, TCP-friendliness, and scalability.

The artifacts of low-bit rate quantization in images cannot be removed satisfactorily by known methods. We propose decomposition of images as HSI and LSI (higher- and lower- significance images), followed by subsampling and reconstruction methods for LSI. Experiments show significant improvement in image quality, as compared to other methods.

This paper presents a study on acoustic modeling for speech recognition of predominantly monosyllabic languages. Various speech units used in speech recognition systems have been investigated. To evaluate the effectiveness of these acoustic models, the Thai language is selected, since it is a predominantly monosyllabic language and has a complex vowel system. Several experiments have been carried out to find the proper speech unit that can accurately create acoustic model and give a higher recognition rate. Results of recognition rates under different acoustic models are given and compared. In addition, this paper proposes a new speech unit for speech recognition, namely onset-rhyme unit. Two models are proposed-the Phonotactic Onset-Rhyme Model (PORM) and the Contextual Onset-Rhyme Model (CORM). The models comprise a pair of onset and rhyme units, which makes up a syllable. An onset comprises an initial consonant and its transition towards the following vowel. Together with the onset, the rhyme consists of a steady vowel segment and a final consonant. Experimental results show that the onset-rhyme model improves on the efficiency of other speech units. The onset-rhyme model improves on the accuracy of the inter-syllable triphone model by nearly 9.3% and of the context-dependent Initial-Final model by nearly 4.7% for the speaker-dependent systems using only an acoustic model, and 5.6% and 4.5% for the speaker-dependent systems using both acoustic and language model respectively. The results show that the onset-rhyme models attain a high recognition rate. Moreover, they also give more efficiency in terms of system complexity.

We present a method for recognition of continuous Korean Sign Language (KSL). In the paper, we consider the segmentation problem of a continuous hand motion pattern in KSL. For this, we first extract sign sentences by removing linking gestures between sign sentences. We use a gesture tension model and fuzzy partitioning. Then, each sign sentence is disassembled into a set of elementary motions (EMs) according to its geometric pattern. The hidden Markov model is adopted to classify the segmented individual EMs.

We present a novel adaptive method to improve the binarization quality of degraded word color images. The objective of this work is to solve a nonlinear problem concerning the binarization quality, that is, to achieve edge enhancement and noise reduction in images. The digitized data used in this work were extracted automatically from real world photos. The motion of objects with reference to static camera and bad environmental conditions provoked serious quality problems on those images. Conventional methods, such as the nonlinear adaptive filter method proposed by Mo, or Otsu's method cannot produce satisfactory binarization results for those types of degraded images. Among other problems, we note mainly that contrast (between shapes and backgrounds) varies greatly within every degraded image due to non-uniform illumination. The proposed method is based on the automatic extraction of background information, such as luminance distribution to adaptively control the intensity levels, that is, without the need for any manual fine-tuning of parameters. Consequently, the new method can avoid noise or inappropriate shapes in the output binary images. Otsu's method is also applied to automatic threshold selection for classifying the pixels into background and shape pixels. To demonstrate the efficiency and the feasibility of the new adaptive method, we present results obtained by the binarization system. The results were satisfactory as we expected, and we have concluded that they can be used successfully as data in further processing such as segmentation or extraction of characters. Furthermore, the method helps to increase the eventual efficiency of a recognition system for poor-quality word images, such as number plate photos with non-uniform illumination and low contrast.

Using the Proportional Integral Derivative (PID) principle of classical feedback control theory, this paper develops two general congestion control algorithms for routers implementing Active Queue Management (AQM) while supporting TCP/IP traffic flows. The general designs of non-interacting (N-PID) and interacting (I-PID) congestion control algorithms are tailored for practical network scenarios using the Ziegler-Nichols guidelines for tuning such controllers. Discrete event simulations using ns are performed to evaluate the performance of an existing F-PID and new N-PID and I-PID algorithms. The performance of N-PID and I-PID is compared mutually as well as with the F-PID algorithm. It reveals that N-PID and I-PID have higher speed of response but lower stability margins than F-PID. In general the accurate following of the target queue size by the PID principle congestion control algorithms, while providing high link utilization, low loss rate and low queuing delays, is also demonstrated.

During the period from dusk to dark, when it is difficult for drivers to see other vehicles, or when visibility is poor due to rain, snow, etc., the contrast between nearby vehicles and the background is lower. Under such conditions, conventional surveillance systems have difficulty detecting the outline of nearby vehicles and may thus fail to recognize them. To solve this problem, we have developed a rear and side surveillance system for vehicles that uses image processing. The system uses two stereo cameras to monitor the areas to the rear and sides of a vehicle, i.e., a driver's blind spots, and to detect the positions and relative speeds of other vehicles. The proposed system can estimate the shape of a vehicle from a partial outline of it, thus identifying the vehicle by filling in the missing parts of the vehicle outline. Testing of the system under various environmental conditions showed that the rate of errors (false and missed detection) in detecting approaching vehicles was reduced to less than 10%, even under conditions that are problematic for conventional processing.

This letter proposes a millimeter-wave band transformer to connect a standard waveguide to a very thin post-wall waveguide. The post-wall waveguide height is the same as a microstrip or coplanar line. A dielectric substrate with slits etched on both edges is inserted in the standard waveguide for matching. A 22 GHz transformer gives 3.6% bandwidth for a 0.5 mm-height post-wall waveguide. The effects of various mechanical misalignments upon the frequency characteristics of the reflection are also estimated by analysis and measurements.

This paper proposes the design of a physically accurate spine model and its application to estimate three dimensional spine posture from the frontal and lateral views of a human body taken by two conventional video cameras. The accurate spine model proposed here is composed of rigid body parts approximating vertebral bodies and elastic body parts representing intervertebral disks. In the estimation process, we obtain neck and waist positions by fitting the Connected Vertebra Spheres Model to frontal and lateral silhouette images. Then the virtual forces acting on the top and the bottom vertebrae of the accurate spine model are computed based on the obtained neck and waist positions. The accurate model is deformed by the virtual forces, the gravitational force, and the forces of repulsion. The model thus deformed is regarded as the current posture. According to the preliminary experiments based on one real MR image data set of only one subject person, we confirmed that our proposed deformation method estimates the positions of the vertebrae within positional shifts of 3.2 6.8 mm. 3D posture of the spine could be estimated reasonably by applying the estimation method to actual human images taken by video cameras.

In this paper, a new method is proposed to construct a visual secret sharing scheme with a general access structure for plural secret images. Although the proposed scheme can be considered as an extension of Droste's method that can encode only black-white images, it can encode plural gray-scale and/or color secret images.

We present a method for recognition of two-hand gestures. Two-hand gestures include fine-grain descriptions of hands under a complicated background, and have complex dynamic behaviors. Hence, assuming that two-hand gestures are an interacting process of two hands whose shapes and motions are described by switching linear dynamics, we propose a coupled switching linear dynamic model to capture interactions between both hands. The parameters of the model are learned via EM algorithm using approximate computations. Recognition is performed by selection of the model with maximum likelihood out of a few learned models during tracking. We confirmed the effectiveness of the proposed model in tracking and recognition of two-hand gestures through some experiments.

In this paper, we propose a scalable Extended Differentiated-Services (EDS) architecture to guarantee edge-to-edge explicit rate allocation. In presence of flows with explicit rate allocation, to share bandwidth fairly, a new fairness definition is proposed. Based on EDS and the proposed fairness definition, a scalable fair Edge-to-Edge Congestion Control Algorithm with Explicit Rate Allocation (ECC-ERA) is presented to solve the bandwidth assurance problem facing Differentiated Service architecture, where EDS uses congestion control packets to carry the flow-related states and congestion control information. By designing efficiency control and fairness control separately, the ECC-ERA can achieve good scalability to link capacity, round-trip time and number of flows. It will be shown that EDS plus ECC-ERA outperforms the general Diff-Serv bandwidth guarantee approaches. The main advantages of EDS+ECC-ERA are as follows: (1) it not only can guarantee explicit rate allocation, but also can guarantee near-zero packet loss in core routers, high utilization, lower and smoother queueing delay, better fairness and better protection from unresponsive traffic. (2) Neither resource pre-reservation nor sophisticated scheduling mechanisms are required. The simple FIFO at core routers is enough. (3) EDS plus EC-ERA is very efficient and can be used as end-to-end QoS building block.