A novel fusion method for semantic concept detection in images, called tree fusion, is proposed. Various kinds of features are given to different classifiers. Then, according to the importance of features and effectiveness of classifiers, the results of feature-classifier pairs are ranked and fused using C4.5 algorithm. Experimental results conducted on the MSRC and PASCAL VOC 2007 datasets have demonstrated the effectiveness of the proposed method over the traditional fusion methods.

Ultra-wide band (UWB) radar has a great advantage for range resolution, and is suitable for 3-dimensional (3-D) imaging sensor, such as for rescue robots or surveillance systems, where an accurate 3-dimensional measurement, impervious to optical environments, is indispensable. However, in indoor sensing situations, an available aperture size is severely limited by obstacles such as collapsed furniture or rubles. Thus, an estimated region of target image often becomes too small to identify whether it is a human body or other object. To address this issue, we previously proposed the image expansion method based on the ellipse extrapolation, where the fitting space is converted from real space to data space defined by range points to enhance the extrapolation accuracy. Although this method achieves an accurate image expansion for some cases, by exploiting the feature of the efficient imaging method as range points migration (RPM), there are still many cases, where it cannot maintain sufficient extrapolation accuracy because it only employs the single scattered component for imaging. For more accurate extrapolation, this paper extends the above image expansion method by exploiting double-scattered signals between the target and the wall in an indoor environment. The results from numerical simulation validate that the proposed method significantly expands the extrapolated region for multiple elliptical objects, compared with that obtained using only single scattered signal.

In our previous work, we proposed to combine ConceptNet and WordNet for Word Sense Disambiguation (WSD). The ConceptNet was automatically disambiguated through Normalized Google Distance (NGD) similarity. In this letter, we present several techniques to enhance the performance of the ConceptNet disambiguation and use this enriched semantic knowledge in WSD task. We propose to enrich both the WordNet semantic knowledge and NGD to disambiguate the concepts in ConceptNet. Furthermore, we apply the enriched semantic knowledge to improve the performance of WSD. From a number of experiments, the proposed method has been obtained enhanced results.

The use of cooperative nodes is effective for enhancing the reliability of wireless data transmission between a source and a destination by means of transmit diversity effect. However, in its application to wireless multi-hop networks, how to form cooperative node candidates and how to select multiple cooperative nodes out of them have not been well investigated. In this paper, we propose a multiple cooperative node selection method based on a criterion composed of “quality” and “angle” metrics, which can select and order adequate cooperative nodes. Computer simulation results show that the proposed method can effectively reduce the packet error rate without any knowledge on node location.

We discuss a new high performance computing service (HPCS) platform that has been developed to provide domain-neutral computing service under the governmental support from “EDucation-research Integration through Simulation On the Net” (EDISON) project. With a first focus on technical features, we not only present in-depth explanations of the implementation details, but also describe the strengths of the EDISON platform against the successful nanoHUB.org gateway. To validate the performance and utility of the platform, we provide benchmarking results for the resource virtualization framework, and prove the stability and promptness of the EDISON platform in processing simulation requests by analyzing several statistical datasets obtained from a three-month trial service in the initiative area of computational nanoelectronics. We firmly believe that this work provides a good opportunity for understanding the science gateway project ongoing for the first time in Republic of Korea, and that the technical details presented here can be served as an useful guideline for any potential designs of HPCS platforms.

A smoothing method for minimum phone error linear regression (MPELR) is proposed in this paper. We show that the objective function for minimum phone error (MPE) can be combined with a prior mean distribution. When the prior mean distribution is based on maximum likelihood (ML) estimates, the proposed method is the same as the previous smoothing technique for MPELR. Instead of ML estimates, maximum a posteriori (MAP) parameter estimate is used to define the mode of prior mean distribution to improve the performance of MPELR. Experiments on a large vocabulary speech recognition task show that the proposed method can obtain 8.4% relative reduction in word error rate when the amount of data is limited, while retaining the same asymptotic performance as conventional MPELR. When compared with discriminative maximum a posteriori linear regression (DMAPLR), the proposed method shows improvement except for the case of limited adaptation data for supervised adaptation.

A scalable low voltage signaling (SLVS) transmitter, with asymmetric impedance calibration, is proposed for mobile applications which require low power consumption. The voltage swing of the proposed SLVS transmitter is scalable from 40,mV to 440,mV. The proposed asymmetric impedance calibration asymmetrically controls the pull-up and pull-down drivers for the SLVS transmitter with an impedance of 50,$Omega$. This makes it possible to remove the additional regulator used to calibrate the impedance of an output driver by controlling the swing level of a pre-driver. It also maintains the common mode voltage at the center voltage level of the transmitted signal. The proposed SVLS transmitter is implemented using a 0.18-$mu $m 1-poly 6-metal CMOS process with a 1.2-V supply. The active area and power consumption of the transmitter are $250 imes 123 mu$ m$^{2}$ and 2.9,mW/Gb/s, respectively.

In this paper, a 1.8-V 10-bit 100,MS/s successive approximation register (SAR) analog-to-digital converter (ADC) simulated in a TSMC 0.18-$mu$m CMOS process is presented. By applying ten comparators followed by an asynchronous trigger logic, the proposed SAR ADC achieves high speed operation. Compared to the conventional SAR ADC, there is no significant delay in the digital feedback logic in this design. With the sampling rate limited only by the ten delays of the capacitor DAC settling and comparators quantization, the proposed SAR ADC achieves a peak SNDR of 61.2,dB at 100,MS/s and 80,MS/s, consuming 3.2,mW and 3.1,mW respectively.

By exploiting the inherent sparsity of wireless propagation channels, the theory of compressive sensing (CS) provides us with novel technologies to estimate the channel state information (CSI) that require considerably fewer samples than traditional pilot-aided estimation methods. In this paper, we describe the block-sparse structure of the fast time-varying channel and apply the model-based CS (MCS) for channel estimation in orthogonal frequency division multiplexing (OFDM) systems. By exploiting the structured sparsity, the proposed MCS-based method can further compress the channel information, thereby allowing a more efficient and precise estimation of the CSI compared with conventional CS-based approaches. Furthermore, a specific pilot arrangement is tailored for the proposed estimation scheme. This so-called random grouped pilot pattern can not only effectively protect the measurements from the inter-carrier interference (ICI) caused by Doppler spreading but can also enable the measurement matrix to meet the conditions required for MCS with relatively high probability. Simulation results demonstrate that our method has good performance at high Doppler frequencies.

We theoretically analyze the performance of free-space optical (FSO) systems using cooperative-ARQ (C-ARQ), a joint scheme of automatic-repeat-request (ARQ) and cooperative diversity, over atmospheric turbulence channels. We also propose a modified C-ARQ (M-C-ARQ) scheme that allows relay nodes to store a copy of frames for the more efficient response to transmission failure so that both transmission delay and energy consumption can be improved. Using Markov chain-based analytical models for both schemes, the system performance is analytically studied in terms of frame-error rate, goodput and energy efficiency, which directly reflect the transmission delay and energy consumption. Numerical results confirm that the proposed schemes outperform conventional ones. In addition, we discuss cross-layer design strategies for selecting parameters in both physical and link layers in order to optimize the performance of FSO systems over different atmospheric turbulence conditions and channel distances.

This paper proposes the assignment of resource blocks (RBs) to reduce the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) in a multi-user OFDM system. This system ranks the users according to the channel state information (CSI) for RB assignment. In our proposed technique, an RB is assigned to either the first- or second-ranked mobile station (MS) to minimize the PAPR of the OFDM signal. While this process reduces the PAPR, the throughput is also reduced because of the user diversity gain loss. A PAPR-throughput tradeoff is then established. Theoretical analyses and computer simulations confirm that when the number of MSs becomes large, the PAPR-throughput tradeoff is eased because of the minimal effect of the diversity gain loss. Therefore, significant PAPR reduction is achieved with only a slight degradation in the throughput.

Curve extension is a useful function in shape modeling for cyberworlds, while a Ball B-spline Curve (BBSC) has its advantages in representing freeform tubular objects. In this paper, an extension algorithm for the BBSC with G2-continuity is investigated. We apply the extending method of B-Spline curves to the skeleton of the BBSC through generalizing a minimal strain energy method from 2D to 3D. And the initial value of the G2-continuity parameter for the skeleton is selected by minimizing the approximate energy function which is a problem with O(1) time complexity. The corresponding radius function of the control ball points is determined through applying the G2-continuity conditions for the skeleton to the scalar function. In order to ensure the radii of the control ball points are positive, we make a decision about the range of the G2-continuity parameter for the radius and then determine it by minimizing the strain energy in the affected area. Some experiments comparing our method with other methods are given. And at the same time, we present the advantage of our method in modeling flexibility from the aspects of the skeleton and radius. The results illustrate our method for extending the BBSC is effective.

Most existing outlier detection algorithms only utilized location of trajectory points and neglected some important factors such as speed, acceleration, and corner. To address this problem, we present a Trajectory Outlier Detection algorithm based on Multi-Factors (TODMF). TODMF is improved in terms of distance-based outlier detection algorithms. It combines multi-factors into outlier detection to find more meaningful trajectory outliers. We resort to Canonical Correlation Analysis (CCA) to optimize the number of factors when determining what factors will be considered. Finally, the experiments with real trajectory data sets show that TODMF performs efficiently and effectively when applied to the problem of trajectory outlier detection.

The dynamic characteristics of the class E power amplifier with frequency modulation are derived. Such an analysis is essential for designing amplitude and frequency modulated amplifier systems such as an EER scheme. Conventionally, an analytical expression for the frequency response of a frequency modulated class E amplifier has not been derived yet. This omission is rectified here by modeling the circuit with both a low-frequency model and a high-frequency model. Further, a time domain waveform is derived from the frequency domain transfer function for some typical time varying drive signals. The analytical results for the frequency response of a 1-MHz class E amplifier are shown to match PSpice simulations and measured values well.

We propose a novel IDDQ outlier screening flow through a two-phase approach: a clustering-based filtering and an estimation-based current-threshold determination. In the proposed flow, a clustering technique first filters out chips that have high IDDQ current. Then, in the current-threshold determination phase, device-parameters of the unfiltered chips are estimated based on measured IDDQ currents through Bayesian inference. The estimated device-parameters will further be used to determine a statistical leakage current distribution for each test pattern and to calculate a and suitable current-threshold. Numerical experiments using a virtual wafer show that our proposed technique is 14 times more accurate than the neighbor nearest residual (NNR) method and can achieve 80% of the test escape in the case of small leakage faults whose ratios of leakage fault sizes to the nominal IDDQ current are above 40%.

With the development of personal electronic equipment, the use of a smartphone with a tri-axial accelerometer to detect human physical activity is becoming popular. In this paper, we propose a new feature based on FFT for activity recognition from tri-axial acceleration signals. To improve the classification performance, two fusion methods, minimal distance optimization (MDO) and variance contribution ranking (VCR), are proposed. The new proposed feature achieves a recognition rate of 92.41%, which outperforms six traditional time- or frequency-domain features. Furthermore, the proposed fusion methods effectively improve the recognition rates. In particular, the average accuracy based on class fusion VCR (CFVCR) is 97.01%, which results in an improvement in accuracy of 4.14% compared with the results without any fusion. Experiments confirm the effectiveness of the new proposed feature and fusion methods.

The paper presents ultra-high-capacity transmission technologies based on multi-core space-division-multiplexing. In order to realize high-capacity multi-core fiber (MCF) transmission, investigation of low crosstalk fiber and connection technology is important, and high-density signal generation using multilevel modulation and crosstalk management are also key technologies. 1Pb/s multi-core fiber transmission experiment using space-division-multiplexing is also described.

This paper covers new architectures, technologies, and performance benchmarking together with prospects for high productivity and high performance computing enabled by photonics. The exponential and sustained increases in computing and data center needs are driving the demands for exascale computing in the future. Power-efficient and parallel computing with balanced system design is essential for reaching that goal as should support ∼billion total concurrencies and ∼billion core interconnections with ∼exabyte/second bisection bandwidth. Photonic interconnects offer a disruptive technology solution that fundamentally changes the computing architectural design considerations. Optics provide ultra-high throughput, massive parallelism, minimal access latencies, and low power dissipation that remains independent of capacity and distance. In addition to the energy efficiency and many of the fundamental physical problems, optics will bring high productivity computing where programmers can ignore locality between billions of processors and memory where data resides. Repeaterless interconnection links across the entire computing system and all-to-all massively parallel interconnection switch will significantly transform not only the hardware aspects of computing but the way people program and harness the computing capability. This impacts programmability and productivity of computing. Benchmarking and optimization of the configuration of the computing system is very important. Practical and scalable deployment of photonic interconnected computing systems are likely to be aided by emergence of athermal silicon photonics and hybrid integration technologies.

This paper presents a novel decoupling network consisting of transmission lines and a bridge resistance for a two-element array antenna and evaluates its performance through simulations and measurements. To decouple the antennas, the phase of the mutual admittance between the antenna ports is rotated by using the transmission lines, and a pure resistance working as a bridge resistance is inserted between the two antenna ports to cancel the mutual coupling. The simulation results indicate that the proposed decoupling network can provide a wider bandwidth than the conventional approach. The proposed decoupling network is implemented and tested as a demonstration to confirm its performance. The measurement results indicate that the mutual coupling between the two antenna ports is lowered by about 47dB at the resonant frequency.

The effect of transceiver impairments (consisting of frequency offset, phase noise and doubly-selective channel) is a key factor for determining performance of an orthogonal frequency-division multiplexing (OFDM) system since the transceiver impairments trigger intercarrier interference (ICI). These impairments are well known and have been investigated separately in the past. However, these impairments usually arise concurrently and should be jointly considered from the perspectives of both receiver design and system evaluation. In this research, impact of these impairments on an OFDM system is jointly analyzed and the result degenerates to the special case where only a specific impairment is present. A mitigation method aided by segment-by-segment time-domain interpolation (STI) is then proposed following the analysis. STI is general, and its weights can be specified according to the interpolation method and system requirements. Computer simulation is used to validate the analysis and to compare the performance of the proposed method with those of other proposals.