In this paper we investigate the reliability of general type shared protection systems i.e. M for N (M:N) that can typically be applied to various telecommunication network devices. We focus on the reliability that is perceived by an end user of one of N units. We assume that any failed unit is instantly replaced by one of the M units (if available). We describe the effectiveness of such a protection system in a quantitative manner. The mathematical analysis gives the closed-form solution of the availability, the recursive computing algorithm of the MTTFF (Mean Time to First Failure) and the MTTF (Mean Time to Failure) perceived by an arbitrary end user. We also show that, under a certain condition, the probability distribution of TTFF (Time to First Failure) can be approximated by a simple exponential distribution. The analysis provides useful information for the analysis and the design of not only the telecommunication network devices but also other general shared protection systems that are subject to service level agreements (SLA) involving user-perceived reliability measures.

In reliable multicast, feedback and recovery traffic limit the performance and scalability of the multicast session. In this paper, we present an improvement to the many-to-many reliable multicast protocol, Group-Aided Multicast protocol (GAM), with a local-group based recovery by making use of forward error correction (FEC) locally in addition to NACK/retransmission. In contrast to the original GAM, which only makes use of NACK-based recovery, our scheme produces FEC packets and multicasts the packets within the scope of a local group in order to correct uncorrelated errors of the local members in each group of the multicast session, which reduces the need for NACK/retransmission. By using our scheme, redundancy traffic can be localized in each group within a multicast session, and the overall recovery traffic can be reduced.

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.

We address the issue of MIMO channel estimation with the aid of a priori temporal correlation statistics of the channel as well as the spatial correlation. The temporal correlations are incorporated to the estimation scheme by assuming the Gauss-Markov channel model. Under the MMSE criteria, the Kalman filter performs an iterative optimal estimation. To take advantage of the enhanced estimation capability, we focus on the problem of channel estimation from a partial channel measurement in the MIMO antenna selection system. We discuss the optimal training sequence design, and also the optimal antenna subset selection for channel measurement based on the statistics. In a highly correlated channel, the estimation works even when the measurements from some antenna elements are omitted at each fading block.

When we watch television or computer monitor under a certain viewing condition, we partially adapt to the display and partially to the ambient light. As an illumination level and chromaticity change, the eye's subjective white point changes between the display's white point and the ambient light's white point. In this paper, we propose a model that could predict the white point under a mixed adaptation condition including display and illuminant. Finally we verify this model by experimental results.

We report on the spurious suppression effect in low-microwave power transmitters by high temperature superconducting (HTS) bandpass filters (BPFs) which are promising for devices requiring BPFs with high-frequency selectivity. Some of the major issues on the power BPFs with HTS planar circuits for wireless communication applications are reviewed. As a case study for the HTS filter and its spurious suppression effect, this paper describes an example of the measured power spectrum density (PSD) on the suppression effect by one of our developed power BPFs with YBCO films for the 5 GHz band. It was designed with equivalent cascade resonators of 16 poles. We demonstrated the effect by HTS power filter in a power amplifier for the 5 GHz band.

In laparoscopic surgery, the lack of tactile sensation and 3D visual feedback make it difficult to identify the position of a blood vessel intraoperatively. An unintentional partial tear or complete rupture of a blood vessel may result in a serious complication; moreover, if the surgeon cannot manage this situation, open surgery will be necessary. Differentiation of arteries from veins and other structures and the ability to independently detect them has a variety of applications in surgical procedures involving the head, neck, lung, heart, abdomen, and extremities. We have used the artery's pulsatile movement to detect and differentiate arteries from veins. The algorithm for change detection in this study uses edge detection for unsupervised image registration. Changed regions are identified by subtracting the systolic and diastolic images. As a post-processing step, region properties, including color average, area, major and minor axis lengths, perimeter, and solidity, are used as inputs of the LVQ (Learning Vector Quantization) network. The output results in two object classes: arteries and non-artery regions. After post-processing, arteries can be detected in the laparoscopic field. The registration method used here is evaluated in comparison with other linear and nonlinear elastic methods. The performance of this method is evaluated for the detection of arteries in several laparoscopic surgeries on an animal model and on eleven human patients. The performance evaluation criteria are based on false negative and false positive rates. This algorithm is able to detect artery regions, even in cases where the arteries are obscured by other tissues.

In this paper, we propose a rate control technique for H.264/AVC using subjective quality of video for off line video coding. We propose to use Video Quality Metric (VQM) with an evolution strategy algorithm, which is capable of identifying the best possible quantization parameters for each frame/macroblock to encode the video sequence such that it would maximize the subjective quality of the entire video sequence subjected to the target bit rate. Simulation results suggest that the proposed technique can improve the RD performance of the H.264/AVC codec significantly. With the proposed technique, up to 40% bit rate reduction can be achieved at the same video quality. Furthermore, results show that the proposed technique can improve the subjective quality of the encoded video significantly for video sequences especially with high motion.

The IEEE802.11b WLAN standard employs direct-sequence/spread-spectrum (DS/SS) modulation. With a fractional sampling RAKE receiver, it is possible to achieve diversity and reduce the BER in DS/SS communication. In order to realize the diversity through fractional sampling, the impulse response of the channel must be estimated. In this paper, a channel estimation scheme for a RAKE receiver with fractional sampling in IEEE802.11b WLAN system is investigated through a computer simulation and an experiment. In order to estimate the impulse response of the channel, a pseudo-inverse matrix with a threshold is employed. Numerical results indicate that the channel can be estimated with an optimum threshold in both the simulation and the experiment.

A Policy-based Network Management (PBNM) in Mobile Ad-hoc Networks (MANETs) should be efficient and reliable. In this letter, we propose a mechanism for the policy-based management in ad hoc networks and we discuss methods to discover the Policy Decision Point (PDP), set the management area, and manage the movements of nodes in the PBNM system. Finally, we assess the results through simulations.

In MIMO systems, the deployment of a multiple antenna technique can enhance the system performance. However, since the cost of RF transmitters is much higher than that of antennas, there is growing interest in techniques that use a larger number of antennas than the number of RF transmitters. These methods rely on selecting the optimal transmitter antennas and connecting them to the respective. In this case, feedback information (FBI) is required to select the optimal transmitter antenna elements. Since FBI is control overhead, the rate of the feedback is limited. This motivates the study of limited feedback techniques where only partial or quantized information from the receiver is conveyed back to the transmitter. However, in MIMO/OFDM systems, it is difficult to develop an effective FBI quantization method for choosing the space-time, space-frequency, or space-time-frequency processing due to the numerous subchannels. Moreover, MIMO/OFDM systems require antenna separation of 5 10 wavelengths to keep the correlation coefficient below 0.7 to achieve a diversity gain. In this case, the base station requires a large space to set up multiple antennas. To reduce these problems, in this paper, we propose the link correlation based transmit sector antenna selection for Alamouti coded OFDM without FBI.

In this letter, we propose a computationally efficient search space for QRM-MLD that is used for spatially multiplexed multiple antenna systems. We perform a set of computer simulations to show that the proposed method achieves a performance that is near to that of the original QRM-MLD, while its computational complexity is near to that of rank-QRM-MLD.

The block based motion estimation technique is adopted by various video coding standards to reduce the temporal redundancy in video sequences. The core of that technique is the search algorithm implemented to find the location of the best matched block. Indeed, the full search algorithm is the most straightforward and optimal but computationally demanding search algorithm. Consequently, many fast and suboptimal search algorithms have been proposed. Reduction of the number of location being searched is the approach used to decrease the computational load of full search. In this paper, hybridization between an adaptive search algorithm and the full search algorithm is proposed. The adaptive search algorithm benefits from the correlation within spatial and temporal adjacent blocks. At the same time, a feature domain based matching criteria is used to reduce the complexity resulting from applying the pixel based conventional criteria. It is shown that the proposed algorithm produces good quality performance and requires less computational time compared with popular block matching algorithms.

A new acceleration scheme that decreases the number of required iterations in relaxation methodology is proposed. The proposed scheme uses dynamic error prediction of an improved approximation to the solution during an iterative computation. The proposed scheme's application to circuit simulations required an average of 67.3% fewer iterations compared to un-accelerated relaxation methods.

The authors present R2Power, an effective approach to the realizable reduction of RC networks with independent current sources. The proposed approach is based on the entrywise perturbation theory for diagonally dominant M-matrices. The accuracy of the node voltages of the reduced network, as compared to those of the original network, is maintained on the order of the entrywise perturbation performed during reduction. R2Power can be used to reduce the size of RC networks used to model the power networks of SoCs, for efficient IR-drop analysis. Experiments showed that R2Power reduced the size of industrial examples by more than 95%, with maximum relative node voltage errors of less than 0.012%.

A novel bimodal method for face recognition under low-level lighting conditions is proposed. It fuses an enhanced gray level image and an illumination-invariant geometric image at the feature-level. To further improve the recognition performance under large variations in attributions such as poses and expressions, discriminant features are extracted from source images using the wavelet transform-based method. Features are adaptively fused to reconstruct the final face sample. Then FLD is used to generate a supervised discriminant space for the classification task. Experiments show that the bimodal method outperforms conventional methods under complex conditions.

Two-Terminal Series Parallel (TTSP, for short) graphs are used as data models in applications for electric networks and scheduling problems. We propose a TTSP term graph which is a TTSP graph having structured variables, that is, a graph pattern over a TTSP graph. Let TGTTSP be the set of all TTSP term graphs whose variable labels are mutually distinct. For a TTSP term graph g in TGTTSP, the TTSP graph language of g, denoted by L(g), is the set of all TTSP graphs obtained from g by substituting arbitrary TTSP graphs for all variables in g. Firstly, when a TTSP graph G and a TTSP term graph g are given as inputs, we present a polynomial time matching algorithm which decides whether or not L(g) contains G. The minimal language problem for the class LTTSP={L(g) | g ∈ TGTTSP} is, given a set S of TTSP graphs, to find a TTSP term graph g in TGTTSP such that L(g) is minimal among all TTSP graph languages which contain all TTSP graphs in S. Secondly, we give a polynomial time algorithm for solving the minimal language problem for LTTSP. Finally, we show that LTTSP is polynomial time inductively inferable from positive data.

A new constant false alarm rate (CFAR) detection scheme based on the goodness-of-fit (GoF) test is proposed to deal with the problem of extended object detection in high resolution synthetic aperture radar (SAR) images. The performance of this detector is compared with that of the traditional detectors using the MSTAR database. Results show that the proposed detector is superior to the traditional detectors in controlling false alarms in nonhomogeneous environment where boundaries widely exist.

This letter proposes a neurobiological approach for action recognition. In this approach, actions are represented by a visual-neuron feature (VNF) based on a quantitative model of object representation in the primate visual cortex. A supervised classification technique is then used to classify the actions. The proposed VNF is invariant to affine translation and scaling of moving objects while maintaining action specificity. Moreover, it is robust to the deformation of actors. Experiments on publicly available action datasets demonstrate the proposed approach outperforms conventional action recognition models based on computer-vision features.

A novel automatic quality factor (Q) tuning scheme for an low-power and wideband active-RC filter is presented. Although Q-tuning is effective to reduce the power consumption of wideband active-RC filters, there are several problems since the Q-tuning normally relies on a magnitude locked loop (MLL). MLL is not accurate due to the amplitude detection circuits, and occupied area and power consumption tends to be large due to its complexity. In addition, flexibility to the reference signal may be the problem, since the reference signal which has a fixed accurate frequency is required. In order to solve these problems, we propose a Q-tuning scheme, which does not require a MLL. Therefore, proposed Q-tuning scheme has good accuracy, small die area, low power consumption and flexibility to the reference signal. In our proposed scheme, Q is tuned by adjusting the phase of an integrator to 90 degrees. The phase of an integrator is adjusted by detecting and controlling the oscillation frequency of a two-stage ring-integrator to the cutoff frequency of a filter, since the phase shift of an integrator is exactly 90 degrees at the oscillation frequency. The frequency is easily detected and controlled by counters and variable resistors, respectively. The Q-tuning circuit with a 5th-order Chebyshev LPF is implemented in a 0.13 µm CMOS technology. The tuning circuit occupies 0.12 mm2 and consumes 2.6 mW from 1.2 V supply.