We develop a system for comprehensively evaluating the gaze motions of a person operating a small electronic device such as a PDA or tablet computer. When people operate small electronic devices, they hold the device in their hand and gaze at it. Their hand movements while holding the device are considered part of the movement involved in operating the device. Our measurement system uses a video camera image taken from behind the subject as a substitute for the view camera of an eye-tracking recorder. With our new system, it is also possible to measure the subject's gaze superimposed on the view image by directly inputting the display screen from a small electronic terminal or other display. We converted the subjects' head and hand movements into eye movements and we calculated the gaze from these values; we transformed the gaze coordinates into view image coordinates and superimposed each gaze on the view image. We examined this hand movement in relation to gaze movement by simultaneously measuring the gaze movement and hand movement. We evaluated the accuracy of the new system by conducting several experiments. We first performed an experiment testing gaze movement as the summation of head and eye movements, and then we performed an experiment to test the system's accuracy for measuring hand movements. From the result of experiments, less than approx. 6.1° accuracy was acquired in the horizontal 120° range and the perpendicular 90° range, and we found that the hand motions converted into the angle equivalent to gaze movement could be detected with approx. 1.2° accuracy for 5° and 10° hand movements. When the subjects' hand moved forward, the results were changed into the angle equivalent to gaze movement by converting the distance between the terminal and the subjects' eyes.

Cognitive radio ad hoc networks can be used to solve the problems of limited available spectrum and inefficient spectrum usage by adaptively changing their transmission parameters. Routing protocol design has a significant impact on the network performance. However, an efficient protocol that takes account of primary user flows and the long-term channel assignment issue in route selection is still missing. In this paper, we propose AODV-cog, a cognitive routing protocol for CSMA/CA ad hoc networks based on AODV. AODV-cog chooses a route by considering the effect on the primary users, available channel bandwidth and link reliability. AODV-cog also takes account of future channel utilization which is an important but underexplored issue. AODV-cog switches channels for secondary user flows when network congestion occurs. We use theoretical analysis and computer simulations to show the advantage of AODV-cog over existing alternatives.

The spatial relations between sensors placed for target detection can be inferred from the responses of individual sensors to the target objects. Motivated by this fact, this paper proposes a method for estimating the location of sensors by using their responses to target objects. The key idea of the proposal is that when two or more sensors simultaneously detect an object, the distances between these sensors are assumed to be equal to a constant called the basic range. Thus, new pieces of proximity information are obtained whenever an object passes over the area in which the sensors are deployed. This information is then be aggregated and transformed into a two dimensional map of sensors by solving a nonlinear optimization problem, where the value of the basic range is estimated together. Simulation experiments verify that the proposed algorithm yields accurate estimates of the locations of sensors.

In this paper, generic attacks are presented against hash functions that are constructed by a hashing mode instantiating a Feistel or generalized Feistel networks with an SP-round function. It is observed that the omission of the network twist in the last round can be a weakness against preimage attacks. The first target is a standard Feistel network with an SP round function. Up to 11 rounds can be attacked in generic if a condition on a key schedule function is satisfied. The second target is a 4-branch type-2 generalized Feistel network with an SP round function. Up to 15 rounds can be attacked in generic. These generic attacks are then applied to hashing modes of ISO standard ciphers Camellia-128 without FL and whitening layers and CLEFIA-128.

In this paper, we propose a new structure for a compact matched filter bank for a mutually orthogonal zero-correlation zone (MO-ZCZ) sequence set consisting of ternary sequence pairs obtained by Hadamard and binary ZCZ sequence sets; this construction reduces the number of two-input adders and delay elements. The matched filter banks are implemented on a field-programmable gate array (FPGA) with 51,840 logic elements (LEs). The proposed matched filter bank for an MO-ZCZ sequence set of length 160 can be constructed by a circuit size that is about 8.6% that of a conventional matched filter bank.

Basic block vectorization consists in realizing instruction-level parallelism inside basic blocks in order to generate SIMD instructions and thus speedup data processing. It is however problematic, because the vectorized program may actually be slower than the original one. Therefore, it would be useful to predict beforehand whether or not vectorization will actually produce any speedup. This paper proposes to do so by expressing vectorization profitability as a classification problem, and by predicting it using a machine learning technique called support vector machine (SVM). It considers three compilers (icc, gcc and llvm), and a benchmark suite made of 151 loops, unrolled with factors ranging from 1 to 20. The paper further proposes a technique that combines the results of two SVMs to reach 99% of accuracy for all three compilers. Moreover, by correctly predicting unprofitable vectorizations, the technique presented in this paper provides speedups of up to 2.16 times, 2.47 times and 3.83 times for icc, gcc and LLVM, respectively (9%, 18% and 56% on average). It also lowers to less than 1% the probability of the compiler generating a slower program with vectorization turned on (from more than 25% for the compilers alone).

This paper presents an electrically small and circularly polarized antenna with an omnidirectional radiation pattern. The antenna consists of a horizontal loop element enclosed by two U-shaped elements and a vertical element from the feeding point. The radiation pattern of the circular polarization is omnidirectional and has a maximum gain of -2dBic in parallel to the ground plane at the 900MHz band. The antenna dimensions are 48 × 20 × 13.8mm (0.14λ × 0.06λ × 0.04λ) with ka =0.476 (i.e. < 0.5), where k is the wavenumber at the resonant frequency and a is the radius of a sphere surrounding the antenna. The dimension corresponds to the definition of an electrically small antenna. The omnidirectional circularly polarized pattern of a prototype antenna shows good agreement with that of the simulation. In addition, this paper introduces a mechanism that generates omnidirectional circular polarization from electrically small antennas.

This paper presents an optimal cooperative routing protocol (OCRP) aiming to improve the in-network cache utilization of the Content-Centric Networking (CCN). The objective of OCRP is to selectively aggregate the multiple flows of interest messages onto the same path in order to improve the cache utilization while mitigating the cache contention of the Content Stores (CSs) of CCN routers on the routing path. The proposed routing protocol consists of three processes: (1) Prefix Popularity Observation; (2) Prefix Group (Un)Subscription; and (3) Forwarding Information Base (FIB) Reconstruction. Prefix Popularity Observation observes the popularly cited prefixes to activate a prefix group (un)subscription function, which lets the Designated Router (DR) know which requester router wants to either join or leave a prefix group. Prefix Group (Un)Subscription lets the DR know which requester router is demanding to join or leave which prefix group. FIB Reconstruction reconstructs the FIB entries of the CCN routers involved in the newly computed optimal cooperative path of all prefix groups. The optimal routing path is obtained by binary linear optimization under a flow conservation constraint, cache contention mitigating constraint, and path length constraint. Two metrics of server load and round-trip hop distance are used to measure the performance of the proposed routing protocol. Simulation results from various network scenarios and various settings show advantages over the shortest path routing and our previously proposed cooperative routing schemes.

This letter presents a new blind audio watermarking scheme using eigenvalue decomposition (EVD). Initially, the original audio is divided into frames and the samples of each frame are arranged into a square matrix. EVD is applied to each of these matrices. Watermark data is embedded into the largest eigenvalue of each diagonal matrix by quantization. Data embedding rate of the proposed scheme is 172.39bps. Simulation results confirm the imperceptibility of the proposed scheme and its higher robustness against various attacks compared to the state-of-the-art watermarking methods available in the literature.

Recently, design of sparse finite impulse response (FIR) digital filters has attracted much attention due to its ability to reduce the implementation cost. However, finding a filter with the fewest number of nonzero coefficients subject to prescribed frequency domain constraints is a rather difficult problem because of its non-convexity. In this paper, an algorithm based on binary particle swarm optimization (BPSO) is proposed, which successively thins the filter coefficients until no sparser solution can be obtained. The proposed algorithm is evaluated on a set of examples, and better results can be achieved than other existing algorithms.

As the virtualization technology becomes the core ingredient for recent promising IT infrastructures such as utility computing and cloud computing, accurate analysis of the internal behaviors of virtual machines becomes more and more important. In this paper, we first propose a novel I/O fairness analysis tool for virtualization systems. It supports the following three features: fine-grained, multimodal and multidimensional. Then, using the tool, we observe various I/O behaviors in our experimental XEN-based virtualization system. Our observations disclose that 1) I/O fairness among virtual machines is broken frequently even though each virtual machine requests the same amount of I/Os, 2) the unfairness is caused by an intricate combination of factors including I/O scheduling, CPU scheduling and interactions between the I/O control domain and virtual machines, and 3) some mechanisms, especially the CFQ (Completely Fair Queuing) I/O scheduler that supports fairness reasonable well in a non-virtualization system, do not work well in a virtualization system due to the virtualization-unawareness. These observations drive us to design a new virtualization-aware I/O scheduler for enhancing I/O fairness. It gives scheduling opportunities to asynchronous I/Os in a controlled manner so that it can avoid the unfairness caused by the priority inversion between the low-priority asynchronous I/Os and high-priority synchronous I/Os. Real implementation based experimental results have shown that our proposal can enhance I/O fairness reducing the standard deviation of the finishing time among virtual machines from 4.5 to 1.2.

High efficiency video coding (HEVC) is the new generation video compression standard. Sample adaptive offset (SAO) is a new compression tool adopted in HEVC which reduces the distortion between original samples and reconstructed samples. SAO estimation is the process of determining SAO parameters in video encoding. It is divided into two phases: statistic collection and parameters determination. There are two difficulties for VLSI implementation of SAO estimation. The first is that there are huge amount of samples to deal with in statistic collection phase. The other is that the complexity of Rate Distortion Optimization (RDO) in parameters determination phase is very high. In this article, a fast SAO estimation algorithm and its corresponding VLSI architecture are proposed. For the first difficulty, we use bitmaps to collect statistics of all the 16 samples in one 4×4 block simultaneously. For the second difficulty, we simplify a series of complicated procedures in HM to balance the algorithms complexity and BD-rate performance. Experimental results show that the proposed algorithm maintains the picture quality improvement. The VLSI design based on this algorithm can be implemented using 156.32K gates, 8,832bits single port RAM for 8bits depth case. It can be synthesized to 400MHz @ 65nm technology and is capable of 8K×4K @ 120fps encoding.

The modeling of random telegraph noise (RTN) of MOS transistors is becoming increasingly important. In this paper, a novel method is proposed for realizing automated estimation of two important RTN-model parameters: the number of interface-states and corresponding threshold voltage shift. The proposed method utilizes a Gaussian mixture model (GMM) to represent the voltage distributions, and estimates their parameters using the expectation-maximization (EM) algorithm. Using information criteria, the optimal estimation is automatically obtained while avoiding overfitting. In addition, we use a shared variance for all the Gaussian components in the GMM to deal with the noise in RTN signals. The proposed method improved estimation accuracy when the large measurement noise is observed.

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.

Mobile ad hoc networks (MANETs) consist of mobile terminals that directly connect with one another to communicate without a network infrastructure, such as base stations and/or access points of wireless local area networks (LANs) connected to wired backbone networks. Large-scale disasters such as tsunamis and earthquakes can cause serious damage to life, property as well as any network infrastructure. However, MANETs can function even after severe disasters have destroyed regular network infrastructure. We have proposed an autonomous decentralized structure formation technology based on local interaction, and have applied it to implement autonomous decentralized clustering on MANETs. This method is known to configure clusters that reflect the network condition, such as residual battery power and the degree of each node. However, the effect of clusters that reflect the network condition has not been evaluated. In this study, we configure clusters using our method, the back-diffusion method, and a bio-inspired method, which is a kind of autonomous decentralized clustering that cannot reflect the network condition. We also clarify the importance of clustering that reflects the network condition, with regard to power consumption and data transfer efficiency.

A generalized chirp-like (GCL) sequence of period N is constructed by modulating a Zadoff-Chu sequence of period N with an arbitrary unimodular sequence of period m, where m divides N. Under some specific conditions, the cross-correlations between two GCL sequences are shown to have exactly the same magnitudes as those of their corresponding Zadoff-Chu sequences regardless of the employed unimodular sequences. In this paper, we first investigate the sufficient conditions under which such a relation holds. We then use them to construct a new class of optimal zero-correlation zone (ZCZ) sequence sets which can be considered to be an extension of the so-called GCL-ZCZ sequence sets.

Although multi-user multiple-input multiple-output (MI-MO) systems provide high data rate transmission, they may suffer from interference. Block diagonalization and eigenbeam-space division multiplexing (E-SDM) can suppress interference. The transmitter needs to determine beamforming weights from channel state information (CSI) to use these techniques. However, MIMO channels change in time-varying environments during the time intervals between when transmission parameters are determined and actual MIMO transmission occurs. The outdated CSI causes interference and seriously degrades the quality of transmission. Channel prediction schemes have been developed to mitigate the effects of outdated CSI. We evaluated the accuracy of prediction of autoregressive (AR)-model-based prediction and Lagrange extrapolation in the presence of channel estimation error. We found that Lagrange extrapolation was easy to implement and that it provided performance comparable to that obtained with the AR-model-based technique.

In this paper, with a modification of our earlier construction in [12], new classes of optimal LHZ FHS sets with new parameters are obtained which are optimal in the sense that their parameters meet the Peng-Fan-Lee bound. It is shown that all the sequences in the proposed FHS sets are shift distinct. The proposed FHS sets are suitable for quasi-synchronous time/frequency hopping code division multiple access systems to eliminate multiple-access interference.

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.

An asymmetric zero correlation zone (A-ZCZ) sequence set is a type of ZCZ sequence set and consists of multiple sequence subsets. It is the most important property that is the cross-correlation function between arbitrary sequences belonging to different sequence subsets has quite a large zero-cross-correlation zone (ZCCZ). Our proposed A-ZCZ sequence sets can be constructed based on interleaved technique and orthogonality-preserving transformation by any perfect sequence of length P=Nq(2k+1) and Hadamard matrices of order T≥2, where N≥1, q≥1 and k≥1. If q=1, the novel sequence set is optimal ZCZ sequence set, which has parameters (TP,TN,2k+1) for all positive integers P=N(2k+1). The proposed A-ZCZ sequence sets have much larger ZCCZ, which are expected to be useful for designing spreading sequences for QS-CDMA systems.