As one of the most widely investigated studies in wireless sensor networks (WSNs), multihop networking is increasingly developed and applied for achieving energy efficient communications and enhancing transmission reliability. To accurately and realistically analyze the performance metric (energy efficiency), firstly we provide a measurement of the energy dissipation for each state and establish a practical energy consumption model for a WSN. According to the analytical model of connectivity, Gaussian approximation approaches to experimental connection probability are expressed for optimization problem on energy efficiency. Moreover, for integrating experimental results with theories, we propose the methodology in multihop wireless sensor networks to maximize efficiency by nonlinear programming, considering energy consumptions and the total quantity of sensing data to base station. Furthermore, we present evaluations adapting to various wireless sensor networks quantitatively with respect to energy efficiency and network configuration, in view of connectivity, the length of data, maximum number of hops and total number of nodes. As the consequence, the realistic analysis can be used in practical applications, especially on self-organization sensor networks. The analysis also shows correlations between the efficiency and maximum number of hops, that is the multihop systems with several hops can accommodate enough devices in ordinary applications. In this paper, our contribution distinguished from others is that our model and analysis are extended from experiments. Therefore, the results of analysis and proposal can be conveniently applied to actual networks.

Cooperative communication has been proposed to improve the disadvantages of the multiple-input multiple-output (MIMO) technique without using extra multiple antennas. In an orthogonal frequency division multiple access (OFDMA) system, a cooperative communication that each user shares their allocated sub-channels instead of the MIMO system has been proposed to improve the throughput. But the cooperative communication has a problem as the decreased throughput because it is necessary that users send and receive the information to each other to improve reliability. In this letter, the modified cooperative transmission scheme is proposed to improve reliability in the fading channel, and it can solve the problem for BER performance that is dependent on the errors in the first phase that exchanges the information between both users during the first time.

A Balanced Neighborhood Classifier (BNEC) is proposed for class imbalanced data. This method is not only well positioned to capture the class distribution information, but also has the good merits of high-fitting-performance and simplicity. Experiments on both synthetic and real data sets show its effectiveness.

This paper shows a method to find a linear transformation that reduces the number of variables to represent a given incompletely specified index generation function. It first generates the difference matrix, and then finds a minimal set of variables using a covering table. Linear transformations are used to modify the covering table to produce a smaller solution. Reduction of the difference matrix is also considered.

The Hierarchical Memory Machine (HMM) is a theoretical parallel computing model that captures the essence of computation on CUDA-enabled GPUs. The offline permutation is a task to copy numbers stored in an array a of size n to an array b of the same size along a permutation P given in advance. A conventional algorithm can complete the offline permutation by executing b[p[i]] ← a[i] for all i in parallel, where an array p stores the permutation P. We first present that the conventional algorithm runs $D_w(P)+2{nover w}+3L-3$ time units using n threads on the HMM with width w and latency L, where Dw(P) is the distribution of P. We next show that important regular permutations including transpose, shuffle, and bit-reversal permutations run $2{nover w}+2{nover kw}+2L-2$ time units on the HMM with k DMMs. We have implemented permutation algorithms for these regular permutations on GeForce GTX 680 GPU. The experimental results show that these algorithms run much faster than the conventional algorithm. We also present an offline permutation algorithm for any permutation running in $16{nover w}+16{nover kw}+16L-16$ time units on the HMM with k DMMs. Quite surprisingly, our offline permutation algorithm on the GPU achieves better performance than the conventional algorithm in random permutation, although the running time has a large constant factor. We can say that the experimental results provide a good example of GPU computation showing that a complicated but ingenious implementation with a larger constant factor in computing time can outperform a much simpler conventional algorithm.

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.

This paper presents an adaptive feedback canceller (AFC) based on a pseudo affine projection (PAP) algorithm that can provide fast and stable adaptation to the time-varying environment. The proposed algorithm utilizes the adaptive linear prediction (LP) to obtain the LP coefficients of input signal model and the inverse gain filter (IGF) to alleviate the effect of compensation gain. As a result, when the input is model as an AR signal, the proposed algorithm satisfies the condition for having an almost unbiased estimatie of the feedback path and then its performance is relatively independent of the gain setting of hearing aids. Simulation results showed that the proposed algorithm is capable of obtaining unbaised feedback path estimates and high speech quality.

The maximization of non-Gaussianity is an effective approach to achieve the complex independent component analysis (ICA) problem. However, the traditional complex maximization of non-Gaussianity (CMN) algorithm does not consider the influence of noise. In this letter, a modification of the fixed-point algorithm is proposed for more practical occasions of the complex noisy ICA model. Simulations show that the proposed method demonstrates significantly improved performance over the traditional CMN algorithm in the noisy ICA model when the sample size is sufficient.

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.

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.

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.

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.

A code shift keying (CSK) using pseudo-noise (PN) codes for optical wireless communications with intensity/modulation and direct detection (IM/DD) is considered. Since CSK has several PN codes, the data transmission rate and the bit error rate (BER) performance can be improved by increasing the number of PN codes. However, the conventional optical PN codes are not suitable for optical CSK with IM/DD because the ratio of the number of PN codes and the code length of PN code, M/L is smaller than 1/√L. In this paper, an optical CSK with a new PN code, which combines the generalized modified prime sequence code (GMPSC) and Hadamard code is analyzed. The new PN code can achieve M/L=1. Moreover, the BER performance and the data transmission rate of the CSK system with the new PN code are evaluated through theoretical analysis by taking the scintillation, background-noise, avalanche photodiode (APD) noise, thermal noise, and signal dependent noise into account. It is found that the CSK system with the new PN code outperforms the conventional optical CSK system.

In consideration of the image noise captured by photoelectric cameras at nighttime, a robust motion detection algorithm based on sparse representation is proposed in this study. A universal dictionary for arbitrary scenes is presented. Realistic and synthetic experiments demonstrate the robustness of the proposed approach.

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.

In this paper, the spatial smoothing (SS) method is extended to the wideband multipath case. By reordering the array input signal and the weight vector, the corresponding covariance matrix of each subarray can be constructed conveniently. Then, a novel wideband beamforming algorithm, based on the SS method (SS-WB), can be achieved by linearly constrained minimum variance (LCMV). Further improvement of the output signal-to-interference-plus-noise ratio (SINR) for SS-WB can be obtained by removing the desired signal in the observed array data with the reconstruction of covariance matrix, which is denoted as wideband beamformer based on modified SS method (MSS-WB). Both proposed algorithms can reduce the desired signal cancellation due to the super decorrelation ability of SS method and MSS-WB can lead to a significantly improved output SINR. The simulations verify their effectiveness in the multipath environment.

We consider an improved control method based on the Stability Transformation Method. Stability Transformation Method detects unknown and unstable periodic orbits of chaotic dynamical systems. Based on the approach to realize the Stability Transformation Method in real systems, we have proposed a control method which can stabilize unknown and unstable periodic orbits embedded in chaotic attractors. However, setting of the control parameters of the control system has remained as unsolved issue. When the dynamics of a target system are unknown, the control parameters have to be set by trial and error. In this paper, we improve the control method with the automatic adjustment function of the control parameters. We show an example of stabilizing unstable periodic orbits of the 3-dimensional hysteresis chaos generator by using the proposed control method. Some results are confirmed by laboratory measurements. The results imply that any unknown and unstable periodic orbits can be stabilized by using the proposed method, if the target chaos system is reduced to 1-dimensional return map.

This paper presents a prediction model based on historical data to achieve optimal values of pipelining, concurrency and parallelism (PCP) in GridFTP data transfers in Cloud systems. Setting the correct values for these three parameters is crucial in achieving high throughput in end-to-end data movement. However, predicting and setting the optimal values for these parameters is a challenging task, especially in shared and non-predictive network conditions. Several factors can affect the optimal values for these parameters such as the background network traffic, available bandwidth, Round-Trip Time (RTT), TCP buffer size, and file size. Existing models either fail to provide accurate predictions or come with very high prediction overheads. The author shows that new model based on historical data can achieve high accuracy with low overhead.

The Internet Engineering Task Force (IETF) has been actively standardizing distributed mobility management (DMM) schemes with multiple Mobility Anchors (MAs). Yet, all existing schemes have limitations that preclude the efficient distribution of mobile data traffic, including single point failure problems, heavy tunneling overheads between MAs, and a restrictive traffic distribution for external nodes in a mobility domain. Therefore, this paper proposes an efficient mobility management scheme with a virtual Local Mobility Anchor (vLMA). While the vLMA is designed assuming multiple replicated LMAs for a PMIPv6 domain, it acts virtually as a single LMA for the internal and external nodes in the PMIPv6 domain. Furthermore, the vLMA distributes mobile data traffic using replicated LMAs, and routes packets via a replicated LMA on the optimal routing path. Performance evaluations confirm that the proposed scheme can distribute mobile data traffic more efficiently and reduce the end-to-end packet delay than the Distributed Local Mobility Anchor (DLMA) and the Proxy Mobile IPv6 (PMIPv6).

Let p be an odd prime such that p ≡ 3 mod 4 and n be an odd positive integer. In this paper, two new families of p-ary sequences of period $N = rac{p^n-1}{2}$ are constructed by two decimated p-ary m-sequences m(2t) and m(dt), where d=4 and d=(pn+1)/2=N+1. The upper bound on the magnitude of correlation values of two sequences in the family is derived by using Weil bound. Their upper bound is derived as $rac{3}{sqrt{2}} sqrt{N+rac{1}{2}}+rac{1}{2}$ and the family size is 4N, which is four times the period of the sequence.