In this paper we propose a novel RFID anti-collision technique that intelligently combines polling and random access schemes. These two fundamentally different medium access control protocols are coherently integrated in our design while functionally complementing each other. The polling mode is designed to enable fast collision-free identification for the tags that exist within reader's coverage across the sessions. In contrast, the random access mode attempts to read the tags uncovered by the polling mode. Our proposed technique is particularly suited for a class of RFID applications in which a stationary reader periodically attempts to identify the tags with slow mobility. Numerical results show that our proposed technique yields much faster identification time against the existing approaches under various operating conditions.

Circuits utilizing advanced process technologies have to correctly account for device parameter variation to optimize its performance. In this paper, analytical formulas for evaluating path delay variation of Multi-Threshold CMOS (MTCMOS) circuits are proposed. The proposed formulas express path delay and its variation as functions of process parameters that are determined by fabrication technology (threshold voltage, carrier mobility, etc.) and the circuit parameters that are determined by circuit structure (equivalent load capacitance and the concurrently switching gates). Two procedures to obtain the circuit parameter sets necessary in the calculation of the proposed formulas are also defined. With the proposed formulas, calculation time of a path delay variation becomes three orders faster than that of Monte-Carlo simulation. The proposed formulas are suitably applied for efficient design of MTCMOS circuits considering process variation.

Equipping wireless routers with multiple radios further improves the capacity by transmitting over multiple radios simultaneously using orthogonal channels. Efficient channel assignment schemes can greatly alleviate the interference effect of nearby transmissions. One of the distinctive features in wireless multi-hop networks is the lack of any central controller, in which each node makes its own decisions. Therefore, fully cooperative behaviors, such as cooperation for increasing link capacity, alleviating interferences for one another, might not be directly applied. In this paper, we aim to present some applications to show how such a framework can be invoked to design efficient channel assignment algorithms in a non-cooperative, topology-blind environment as well as in environments where the competing players share perfect information about channel usage and topology environment and so on. Simulation results are presented to illustrate the effectiveness of the algorithms.

A new analog mismatch model in circuit level has been developed. MOS transistor's small signal parameters are modeled in term of their matching character for both strong- and weak-inversion operations. Mismatch analysis on basic CMOS amplifiers are conducted with proposed model and Monte Carlo SPICE simulations. We successfully derived simple analytical formula on performance mismatch for analog CMOS circuits, which is verified to be accurate in using actual analog circuit design, within an average error of less than 10%.

In general-synchronous framework, in which the clock is distributed periodically to each register but not necessarily simultaneously, the circuit performance such as the clock period is expected to be improved by delay insertion. However, if the amount of inserted delays is too much, then the circuit is changed too much and the circuit performance might not be improved. In this paper, we propose an efficient delay insertion method that minimizes the amount of inserted delays in the clock period improvement in general-synchronous framework. In the proposed method, the amount of inserted delays is minimized by using an appropriate clock schedule and by inserting delays into appropriate places in the circuit. Experiments show that the proposed method can obtain optimum solutions in short time in many cases.

Because of an increasing number of security cameras, it is crucial to establish a system that protects the privacy of objects in the recorded images. To this end, we propose a framework of image processing and data hiding for security monitoring and privacy protection. First, we state the requirements of the proposed monitoring systems and suggest possible implementation that satisfies those requirements. The underlying concept of our proposed framework is as follows: (1) in the recorded images, the objects whose privacy should be protected are deteriorated by appropriate image processing; (2) the original objects are encrypted and watermarked into the output image, which is encoded using an image compression standard; (3) real-time processing is performed such that no future frame is required to generate on output bitstream. It should be noted that in this framework, anyone can observe the decoded image that includes the deteriorated objects that are unrecognizable or invisible. On the other hand, for crime investigation, this system allows a limited number of users to observe the original objects by using a special viewer that decrypts and decodes the watermarked objects with a decoding password. Moreover, the special viewer allows us to select the objects to be decoded and displayed. We provide an implementation example, experimental results, and performance evaluations to support our proposed framework.

Image restoration based on Bayesian estimation in most previous studies has assumed that the noise accumulated in an image was independent for each pixel. However, when we take optical effects into account, it is reasonable to expect spatial correlation in the superimposed noise. In this paper, we discuss the restoration of images distorted by noise which is spatially correlated with translational symmetry in the realm of probabilistic processing. First, we assume that the original image can be produced by a Gaussian model based on only a nearest-neighbor effect and that the noise superimposed at each pixel is produced by a Gaussian model having spatial correlation characterized by translational symmetry. With this model, we can use Fourier transformation to calculate system characteristics such as the restoration error and also minimize the restoration error when the hyperparameters of the probabilistic model used in the restoration process coincides with those used in the formation process. We also discuss the characteristics of image restoration distorted by spatially correlated noise using a natural image. In addition, we estimate the hyperparameters using the maximum marginal likelihood and restore an image distorted by spatially correlated noise to evaluate this method of image restoration.

Frame loss of the optical layer protection switching using Plumbum Lanthanum Zirconium Titanium (PLZT) optical switch is evaluated. Experimental results show that typically 62 µs guard time is required for commercially available non-burst mode 10 Gigabit Ethernet modules.

In RFID systems, collision resolution is a significant issue in fast tag identification. This letter presents a dynamic frame-slotted ALOHA algorithm that uses a collision factor (DFSA-CF). This method enables fast tag identification by estimating the next frame size with the collision factor in the current frame. Simulation results show that the proposed method reduces slot times Required for RFID identification. When the number of tags is larger than the frame size, the efficiency of the proposed method is greater than those of conventional algorithms.

In low bit-rate video transmission, the payload of a single packet can often contain a whole coded frame due to the high compression ratio in both spatial and temporal domains. Thus, the loss of a single packet can lead to the loss of a whole video frame. In this paper, we propose a novel error concealment algorithm that can effectively reconstruct the lost frame and protect the quality of video streams from the degradation caused by propagation errors. The proposed algorithm employs a bilateral motion estimation scheme where the weighted sum of the received motion vectors (MVs) in the neighboring frames is utilized to construct the MV field for the concealed frame. Unlike the conventional algorithms, the proposed scheme does not produce any overlapped pixel and hole region in the reconstructed frame. The proposed algorithm can be applied not only to the case of single frame loss but also adaptively extended to the case of multiframe loss. Experimental results show that the proposed algorithm outperforms other conventional techniques in terms of both peak signal-to-noise ratio (PSNR) performance and subjective visual quality.

In this paper, a Kalman filter-based method for restoration of video images acquired by an in-vehicle camera in foggy conditions is proposed. In order to realize Kalman filter-based restoration, the proposed method clips local blocks from the target frame by using a sliding window and regards the intensities in each block as elements of the state variable of the Kalman filter. Furthermore, the proposed method designs the following two models for restoration of foggy images. The first one is an observation model, which represents a fog deterioration model. The proposed method automatically determines all parameters of the fog deterioration model from only the foggy images to design the observation model. The second one is a non-linear state transition model, which represents the target frame in the original video image from its previous frame based on motion vectors. By utilizing the observation and state transition models, the correlation between successive frames can be effectively utilized for restoration, and accurate restoration of images obtained in foggy conditions can be achieved. Experimental results show that the proposed method has better performance than that of the traditional method based on the fog deterioration model.

The purpose of this study is the real-time estimation of Doppler spectral moments for precipitation in the presence of ground clutter overlap. The proposed method is a frequency domain approach that uses a Gaussian model both to remove clutter spectrum and to estimate weather spectrum. The main advantage of this method is that it does not use processes like several fitting procedures and enables to estimate profiles of precipitation in a short processing time. Therefore this method is efficient for real-time radar observation with high range and time resolution. The performance of this method is evaluated based on simulation data and the observation data acquired by the Ku-band broad band radar (BBR) [1].

IPv4 private addresses are commonly used in local area networks (LANs). With the increasing popularity of virtual private networks (VPNs), it has become common that a user connects to multiple LANs at the same time. However, private address ranges for LANs frequently overlap. In such cases, existing systems do not allow the user to access the resources on all LANs at the same time. In this paper, we propose name-based address mapping for VPNs, a novel method that allows connecting to hosts through multiple VPNs at the same time, even when the address ranges of the VPNs overlap. In name-based address mapping, rather than using the IP addresses used on the LANs (the real addresses), we assign a unique virtual address to each remote host based on its domain name. The local host uses the virtual addresses to communicate with remote hosts. We have implemented name-based address mapping for layer 3 OpenVPN connections on Linux and measured its performance. The communication overhead of our system is less than 1.5% for throughput and less than 0.2 ms for each name resolution.

To be adaptive to the bursty traffic of the wireless personal area network (WPAN), a superframe structure adjustment algorithm of IEEE 802.15.4 is proposed. According to the channel utilization ratio which is an index of the traffic load, the algorithm adjusts the duty cycle of the superframe automatically. The simulation results show that the algorithm is adaptive to the traffic variations effectively and saves much more energy not only for the end devices but also for the PAN coordinator. Moreover, the algorithm results in better performance on the lower delay and lower packet dropping rate.

In this paper, we propose an extension to GridFTP that optimizes its performance by dynamically adjusting the number of parallel TCP connections. GridFTP has been used as a data transfer protocol to effectively transfer a large volume of data in Grid computing. GridFTP supports a feature called parallel data transfer that improves throughput by establishing multiple TCP connections in parallel. However, for achieving high GridFTP throughput, the number of TCP connections should be optimized based on the network status. In this paper, we propose an automatic parallelism tuning mechanism called GridFTP-APT (GridFTP with Automatic Parallelism Tuning) that adjusts the number of parallel TCP connections according to information available to the Grid middleware. Through simulations, we demonstrate that GridFTP-APT significantly improves the performance of GridFTP in various network environments.

The reduction of the peak power consumption of LSI is required to reduce the instability of gate operation, the delay increase, the noise, and etc. It is possible to reduce the peak power consumption by clock scheduling because it controls the switching timings of registers and combinational logic elements. In this paper, we propose a fast peak power wave estimation method for clock scheduling and fast clock scheduling methods for the peak power reduction. In experiments, it is shown that the peak power wave estimated by the proposed method in a few seconds is highly correlated with the peak power wave obtained by HSPICE simulation in several days. By using the proposed peak power wave estimation method, proposed clock scheduling methods find clock schedules that greatly reduce the peak power consumption in a few minutes.

We propose and experimentally demonstrate an all-optical broadband wavelength conversion scheme with simultaneous power amplification based on a pump-modulated fiber optic parametric amplifier (FOPA). All-optical tunable wavelength conversion from one to two wavelengths was achieved with ≥13 dB extinction ratio and <2.7-dB power penalty, accompanied by a high (≥37 dB) and flat ( 3 dB variation) FOPA gain spectrum over 47 nm.

In this paper, a recursive Gauss-Newton (RGN) algorithm is first developed for adaptive tracking of the amplitude, frequency and phase of a real sinusoid signal in additive white noise. The derived algorithm is then simplified for computational complexity reduction as well as improved with the use of multiple forgetting factor (MFF) technique to provide a flexible way of keeping track of the parameters with different rates. The effectiveness of the simplified MFF-RGN scheme in sinusoidal parameter tracking is demonstrated via computer simulations.

In 3D computer graphics, mesh parameterization is a key technique for digital geometry processings such as morphing, shape blending, texture mapping, re-meshing and so on. Most of the previous approaches made use of an identical primitive domain to parameterize a mesh model. In recent works of mesh parameterization, more flexible and attractive methods that can create direct mappings between two meshes have been reported. These mappings are called "cross-parameterization" and typically preserve semantic feature correspondences between target meshes. This paper proposes a novel approach for parameterizing a mesh into another one directly. The main idea of our method is to combine a competitive learning and a least-square mesh techniques. It is enough to give some semantic feature correspondences between target meshes, even if they are in different shapes or in different poses.

This paper proposes a MAC protocol for presence information discovery in ubiquitous networks. The proposed protocol is designed for proactive discovery in which wireless devices periodically broadcast packets containing presence information. The protocol is based on Framed Aloha. The objective of the protocol is to assure the discovery time of single-hop neighbors considering wireless collisions and also power consumption. In this paper, we show that the proposed protocol is able to assure specified discovery time in distributed networks with random topology.