The physical optics (PO) approximation is one of the widely-used techniques to calculate scattering fields with a reasonable accuracy in the high frequency region. The computational load of PO radiation integral dramatically increases at higher frequencies since it is proportional to the electrical size of scatterer. In order to suppress this load, a variety of techniques, such as the asymptotic evaluation by the stationary phase method (SP), the equivalent edge currents (EECs), the low-order polynomial expansion method and the fast physical optics (FPO), have been proposed and developed. The adaptive sampling method (ASM) proposed by Burkholder is also one of the techniques where the sampling points in radiation integral should be adaptively determined based upon the phase change of integrand. We proposed a quite different approach named ``Localization of the radiation integrals.'' This localization method suggests that only the small portions of the integration with a slow phase change contribute to the scattering field. In this paper, we newly introduce the ASM in the localization method and applied the proposed method into the radar cross section (RCS) analysis of 2-dimensional strip and cylinder. We have confirmed that the proposed method provides the frequency-independent number of division in the radiation integrals and computational time and accuracy. As the starting point for extension to 3-D case, the application of the proposed method for a reflection from an infinite PEC plane and a part of sphere was also examined.

Radar systems using ultra-wideband (UWB) signals have definitive advantages in high range resolution. These are suitable for accurate 3-dimensional (3-D) sensing by rescue robots operating in disaster zone settings, where optical sensing is not applicable because of thick smog or high-density gas. For such applications, where no a priori information of target shape and position is given, an accurate method for 3-D imaging and motion estimation is strongly required for effective target recognition. In addressing this issue, we have already proposed a non-parametric 2-dimensional (2-D) imaging method for a target with arbitrary target shape and motion including rotation and translation being tracked using a multi-static radar system. This is based on matching target boundary points obtained using the range points migration (RPM) method extended to the multi-static radar system. Whereas this method accomplishes accurate imaging and motion estimation for single targets, accuracy is degraded severely for multiple targets, due to interference effects. For a solution of this difficulty, this paper proposes a method based on a novel matching scheme using not only target points but also normal vectors on the target boundary estimated by the Envelope method; interference effects are effectively suppressed when incorporating the RPM approach. Results from numerical simulations for both 2-D and 3-D models show that the proposed method simultaneously achieves accurate target imaging and motion tracking, even for multiple moving targets.

To support the processing of spatial window queries efficiently in a non-flat wireless data broadcasting system, we propose a Two-Tier Spatial Index (TTSI) that uses a two tier data space to distinguish hot and regular data items. Unlike an existing index which repeats regular data items located near hot items at the same time as the hot data items during the broadcast cycle, TTSI makes it possible to repeat only hot data items during a cycle. Simulations show that the proposed TTSI outperforms the existing scheme with respect to access time and energy consumption.

The energy consumption of the Internet has a huge impact on the world economy and it is likely to increase every year. In present backbone networks, pairs of nodes are connected by “bundles” of multiple physical cables that form one logical link and energy saving can be achieved by shutting down unused network resources. The hose model can support traffic demand variations among node pairs in different time periods because it accommodates multiple traffic matrices unlike the pipe model which supports only one traffic matrix. This paper proposes an OSPF (Open Shortest Path First) link weight optimization scheme to reduce the network resources used for the hose model considering single link failures. The proposed scheme employs a heuristic algorithm based on simulated annealing to determine a suitable set of link weights to reduce the worst-case total network resources used, and considering any single link failure preemptively. It efficiently selects the worst-case performance link-failure topology and searches for a link weight set that reduces the worst-case total network resources used. Numerical results show that the proposed scheme is more effective in the reduction of worst-case total network resources used than the conventional schemes, Start-time Optimization and minimum hop routing.

As a promising future network architecture, Information-centric networking (ICN) has attracted much attention, its ubiquitous in-network caching is one of the key technologies to optimize the dissemination of information. However, considering the diversity of contents and the limitation of cache resources in the Internet, it is usually difficult to find a one-fit-all caching strategy. How to manage the ubiquitous in-network cache in ICN has become an important problem. In this paper, we explore ways to improve cache performance from the three perspectives of spatiality, temporality and availability, based on which we further propose an in-network cache management strategy to support differentiated service. We divide contents requested in the network into different levels and the selection of caching strategies depends on the content level. Furthermore, the corresponding models of utilizing cache resources in spatiality, temporality and availability are also derived for comparison and analysis. Simulation verifies that our differentiated service based cache management strategy can optimize the utilization of cache resources and get higher overall cache performance.

This article introduces a self-organizing model which builds the topology of a DHT mapping system for ICN. Due to its self-organizing operation and low average degree of maintenance, the management overhead of the system is reduced dramatically, which yields inherent scalability. The proposed model can improve latency by around 10% compared to an existing approach which has a near optimal average distance when the number of nodes and degree are given. In particular, its operation is simple which eases maintenance concerns. Moreover, we analyze the model theoretically to provide a deeper understanding of the proposal.

While Triple modular Redundancy (TMR) is effective in eliminating soft errors in LSIs, the overhead of the triplicated area as well as the triplicated energy consumption is the problem. In addition to the spatial TMR mode where executions are simply tripricated and the majority is taken, the temporal TMR mode is available where only two copies of an operation are executed and the results are compared, then if the results differ, the third copy is executed to get the correct result. Appropriately selecting the power supply voltage is also an effective technique to reduce the energy consumption. In this paper, a method to derive a TMR design is proposed which selects the TMR mode and supply voltage for each operation to minimize the energy consumption within the time and area constraints.

This paper presents a framework for reducing the energy consumption of embedded real-time systems. We implemented the presented framework as both an optimization toolchain and an energy-aware real-time operating system. The framework consists of the integration of multiple techniques to optimize the energy consumption. The main idea behind our approach is to utilize trade-offs between the energy consumption and the performance of different processor configurations during task checkpoints, and to maintain memory allocation during task context switches. In our framework, a target application is statically analyzed at both intra-task and inter-task levels. Based on these analyzed results, runtime optimization is performed in response to the behavior of the application. A case study shows that our toolchain and real-time operating systems have achieved energy reduction while satisfying the real-time performance. The toolchain has also been successfully applied to a practical application.

The index generation function is a multi-valued logic function which checks if the given input vector is a registered or not, and returns its index value if the vector is registered. If the latency of the operation is critical, dedicated hardware is used for implementing the index generation functions. This paper proposes a method implementing the index generation functions using parallel index generator. A novel and efficient algorithm called ‘conflict free partitioning’ is proposed to synthesize parallel index generators. Experimental results show the proposed method outperforms other existing methods. Also, A novel architecture of index generator which is suitable for parallelized implementation is introduced. A new architecture has advantages in the sense of both area and delay.

In this paper, sequential prediction is studied. The typical assumptions about the probabilistic model in sequential prediction are following two cases. One is the case that a certain probabilistic model is given and the parameters are unknown. The other is the case that not a certain probabilistic model but a class of probabilistic models is given and the parameters are unknown. If there exist some parameters and some models such that the distributions that are identified by them equal the source distribution, an assumed model or a class of models can represent the source distribution. This case is called that specifiable condition is satisfied. In this study, the decision based on the Bayesian principle is made for a class of probabilistic models (not for a certain probabilistic model). The case that specifiable condition is not satisfied is studied. Then, the asymptotic behaviors of the cumulative logarithmic loss for individual sequence in the sense of almost sure convergence and the expected loss, i.e. redundancy are analyzed and the constant terms of the asymptotic equations are identified.

In this paper, we consider the lossy source coding problem with delayed side information at the decoder. We assume that delay is unknown but the maximum of delay is known to the encoder and the decoder, where we allow the maximum of delay to change with the block length. In this coding problem, we show an upper bound and a lower bound of the rate-distortion (RD) function, where the RD function is the infimum of rates of codes in which the distortion between the source sequence and the reproduction sequence satisfies a certain distortion level. We also clarify that the upper bound coincides with the lower bound when maximums of delay per block length converge to a constant. Then, we give a necessary and sufficient condition in which the RD function is equal to that for the case without delay. Furthermore, we give an example of a source which does not satisfy this necessary and sufficient condition.

In this paper, we show that if the d-decimation of a (q-1)-ary Sidelnikov sequence of period q-1=pm-1 is the d-multiple of the same Sidelnikov sequence, then d must be a power of a prime p. Also, we calculate the crosscorrelation magnitude between some constant multiples of d- and d'-decimations of a Sidelnikov sequence of period q-1 to be upper bounded by (d+d'-1)√q+3.

The development of high data rate wireless communications systems using Multiple Input — Multiple Output (MIMO) antenna techniques requires detectors with reduced complexity and good Bit Error Rate (BER) performance. In this paper, we present the Semi-fixed Complexity Sphere Decoder (SCSD), which executes the process of detection in MIMO systems with a significantly lower computation cost than the high-performance/reduced-complexity detectors: Sphere Decoder (SD), K-best, Fixed Complexity Sphere Decoder (FSD) and Adaptive Set Partitioning (ASP). Simulation results show that when the Signal-to-Noise Ratio (SNR) is less than 15dB, the SCSD reduces the complexity by up to 90% with respect to SD, up to 60% with respect to K-best or ASP and by up to 90% with respect to FSD. In the proposed algorithm, the BER performance does not show significant degradation and therefore, can be considered as a complexity reduction scheme suitable for implementing in MIMO detectors.

A two-dimensional (2D) wireless power transmission (WPT) system that handles a wide range of transmitted and received power is proposed and evaluated. A transmitter outputs the power to an arbitrary position on a 2D waveguide sheet by using a beam-forming technique. The 2D waveguide sheet does not require an absorber on its edge. The minimum propagation power on the sheet is increased 18 times by using the beam-forming technique. Power amplifier (PA) efficiency was improved from 19% to 46% when the output power was 10dB smaller than peak power due to the use of a PA supply-voltage and input power control method. Peak PA efficiency was 60%. A receiver inputs a wide range of power levels and drives various load impedances with a parallel rectifier. This rectifier enables a number of rectifying units to be tuned dynamically. The rectifier efficiency was improved 1.5 times while input power range was expanded by 6dB and the load-impedance range was expanded fourfold. The rectifier efficiency was 66-73% over an input power range of 18-36dBm at load impedances of 100 and 400Ω.

The present paper introduces a novel method for the construction of sequences that have a zero-correlation zone. For the proposed sequence set, both the cross-correlation function and the side lobe of the autocorrelation function are zero for phase shifts within the zero-correlation zone. The proposed scheme can generate a set of sequences, each of length 16n2, from an arbitrary Hadamard matrix of order n and a set of 4n trigonometric function sequences of length 2n. The proposed construction can generate an optimal sequence set that satisfies, for a given zero-correlation zone and sequence period, the theoretical bound on the number of members. The peak factor of the proposed sequence set is equal to √2.

Frequently interrupting someone who is busy will decrease his or her productivity. To minimize this risk, a number of interruptibility estimation methods based on PC activity such as typing or mouse clicks have been developed. However, these estimation methods do not take account of the effect of conversations in relation to the interruptibility of office workers engaged in intellectual activities such as scientific research. This study proposes an interruptibility estimation method that takes account of the conversation status. Two conversation indices, “In conversation” and “End of conversation” were used in a method that we developed based on our analysis of 50 hours worth of recorded activity. Experiments, using the conversation status as judged by the Wizard-of-OZ method, demonstrated that the estimation accuracy can be improved by the two indices. Furthermore, an automatic conversation status recognition system was developed to replace the Wizard-of-OZ procedure. The results of using it for interruptibility estimation suggest the effectiveness of the automatically recognized conversation status.

This paper proposes a method of improving the performance of blind reverberation time (RT) estimation in noisy environments. RT estimation is conducted using a maximum likelihood (ML) method based on the autocorrelation function of the linear predictive residual signal. To reduce the effect of environmental noise, a noise reduction technique is applied to the noisy speech signal. In addition, a frequency coefficient selection is performed to eliminate signal components with low signal-to-noise ratio (SNR). Experimental results confirm that the proposed method improves the accuracy of RT measures, particularly when the speech signal is corrupted by a colored noise with a narrow bandwidth.

Because of the popularity of rich content, such as video files, the amount of traffic on the Internet continues to grow every year. Not only is the overall traffic increasing, but also the temporal fluctuations in traffic are increasing, and differences in the amounts of traffic between peak and off-peak periods are becoming very large. Consequently, efficient use of link bandwidth is becoming more challenging. In this paper, we propose a new system for content distribution: storage aware routing (SAR). With SAR, routers having large storage capacities can exploit those links that are underutilized. Our performance evaluations show that SAR can smooth the fluctuations in link utilization.

We propose an unsharp-masking technique which preserves the hue of colors in images. This method magnifies the contrast of colors and spatially sharpens textures in images. The contrast magnification ratio is adaptively controlled. We show by experiments that this method enhances the color tone of photographs while keeping their perceptual scene depth.

In this paper, we consider distributed estimation where the measurement at each of the distributed sensor nodes is quantized before being transmitted to a fusion node which produces an estimate of the parameter of interest. Since each quantized measurement can be linked to a region where the parameter is found, aggregating the information obtained from multiple nodes corresponds to generating intersections between the regions. Thus, we develop estimation algorithms that seek to find the intersection region with the maximum likelihood rather than the parameter itself. Specifically, we propose two practical techniques that facilitate fast search with significantly reduced complexity and apply the proposed techniques to a system where an acoustic amplitude sensor model is employed at each node for source localization. Our simulation results show that our proposed algorithms achieve good performance with reasonable complexity as compared with the minimum mean squared error (MMSE) and the maximum likelihood (ML) estimators.