In recent years, researchers have tried to create unhindered human-computer interaction by giving virtual agents human-like conversational skills. Predicting backchannel feedback for agent listeners has become a novel research hot-spot. The main goal of this paper is to identify appropriate features and methods for backchannel prediction in Mandarin conversations. Firstly, multimodal Mandarin conversations are recorded for the analysis of backchannel behaviors. In order to eliminate individual difference in the original face-to-face conversations, more backchannels from different listeners are gathered together. These data confirm that backchannels occurring in the speakers' pauses form a vast majority in Mandarin conversations. Both prosodic and visual features are used in backchannel prediction. Four types of models based on the speakers' pauses are built by using support vector machine classifiers. An evaluation of the pause-based prediction model has shown relatively high accuracy in consideration of the optional nature of backchannel feedback. Finally, the results of the subjective evaluation validate that the conversations performed between humans and virtual listeners using backchannels predicted by the proposed models is more unhindered compared to other backchannel prediction methods.

The number of states is a very important matter for model checking approach in Petri net's analysis. We first gave a formal definition of state number calculation problem: For a Petri net with an initial state (marking), how many states does it have? Next we showed the problem cannot be solved in polynomial time for a popular subclass of Petri nets, known as free choice workflow nets, if P≠NP. Then we proposed a polynomial time algorithm to solve the problem by utilizing a representational bias called as process tree. We also showed effectiveness of the algorithm through an application example.

This paper proposes a novel greedy algorithm, called Creditability-Estimation based Matching Pursuit (CEMP), for the compressed sensing signal recovery. As proved in the algorithm of Stagewise Orthogonal Matching Pursuit (StOMP), two Gaussian distributions are followed by the matched filter coefficients corresponding to and without corresponding to the actual support set of the original sparse signal, respectively. Therefore, the selection for each support point is interpreted as a process of hypothesis testing, and the preliminarily selected support set is supposed to consist of rejected atoms. A hard threshold, which is controlled by an input parameter, is used to implement the rejection. Because the Type I error may happen during the hypothesis testing, not all the rejected atoms are creditable to be the true support points. The creditability of each preliminarily selected support point is evaluated by a well-designed built-in mechanism, and the several most creditable ones are adaptively selected into the final support set without being controlled by any extra external parameters. Moreover, the proposed CEMP does not necessitate the sparsity level to be a priori control parameter in operation. In order to verify the performance of the proposed algorithm, Gaussian and Pulse Amplitude Modulation sparse signals are measured in the noiseless and noisy cases, and the experiments of the compressed sensing signal recoveries by several greedy algorithms including CEMP are implemented. The simulation results show the proposed CEMP can achieve the best performances of the recovery accuracy and robustness as a whole. Besides, the experiment of the compressed sensing image recovery shows that CEMP can recover the image with the highest Peak Signal to Noise Ratio (PSNR) and the best visual quality.

Cloud computing is a widely used computing platform in business and academic communities. Performance is an important issue when a user runs an application in the cloud. The user may want to estimate the application-execution time beforehand to guarantee the application performance or to choose the most suitable cloud. Moreover, the cloud system architect and the designer need to understand the application performance characteristics, such as the scalability or the utilization of cloud platforms, to improve performance. However, because the application performance in clouds sometime fluctuates, estimation of the application performance is difficult. In this paper, we discuss the performance fluctuation of Hadoop jobs in both a public cloud and a community cloud for one to three months. The experimental results indicate phenomena that we cannot see without long-term experiments and phenomena inherent in Hadoop. The results suggest better ways to estimate Hadoop application performances in clouds. For example, we should be aware of application characteristics (CPU intensive or communication intensive), datacenter characteristics (busy or not), and time frame (time of day and day of the week) to estimate the performance fluctuation due to workload congestion in cloud platforms. Furthermore, we should be aware of performance degradation due to task re-execution in Hadoop applications.

Assume that Alice, Bob, and Carol, each of whom privately holds a one-bit input, want to learn the output of some Boolean function, say the majority function, of their inputs without revealing more of their own secret inputs than necessary. In this paper, we show that such a secure three-input function evaluation can be performed with a deck of real cards; specifically, the three players can learn only the output of the function using eight physical cards — four black and four red cards — with identical backs.

This work investigates the physical layer security for three cooperative automatic-repeat-request (CARQ) protocols, including the decode-and-forward (DF) CARQ, opportunistic DF (ODF) CARQ, and the distributed space-time code (DSTC) CARQ. Assuming that there is no instantaneous channel state information (CSI) of legitimate users' channel and eavesdropper's channel at the transmitter, the connection outage performance and secrecy outage performance are derived to evaluate the reliability and security of each CARQ protocol. Then, we redefine the concept of the secrecy throughput to evaluate the overall efficiency of the system in terms of maintaining both reliable and secure transmission. Furthermore, through an asymptotic analysis in the high signal-to-noise ratio (SNR) regime, the direct relationship between reliability and security is established via the reliability-security tradeoff (RST). Numerical results verify the analysis and show the efficiency of the CARQ protocols in terms of the improvement on the secrecy throughput. More interestingly, increasing the transmit SNR and the maximum number of transmissions of the ARQ protocols may not achieve a security performance gain. In addition, the RST results underline the importance of determining how to balance the reliability vs. security, and show the superiority of ODF CARQ in terms of RST.

Objects tracking methods have been wildly used in the field of video surveillance, motion monitoring, robotics and so on. Particle filter is one of the promising methods, but it is difficult to apply to real-time objects tracking because of its high computation cost. In order to reduce the processing cost without sacrificing the tracking quality, this paper proposes a new method for real-time 3D objects tracking, using parallelized particle filter algorithms by MapReduce architecture which is running on GPGPU. Our methods are as follows. First, we use a Kinect to get the 3D information of objects. Unlike the conventional 2D-based objects tracking, 3D objects tracking adds depth information. It can track not only from the x and y axis but also from the z axis, and the depth information can correct some errors in 2D objects tracking. Second, to solve the high computation cost problem, we use the MapReduce architecture on GPGPU to parallelize the particle filter algorithm. We implement the particle filter algorithms on GPU and evaluate the performance by actually running a program on CUDA5.5.

A renal biopsy is a procedure to get a small piece of kidney for microscopic examination. With the development of tissue sectioning and medical imaging techniques, microscope renal biopsy image sequences are consequently obtained for computer-aided diagnosis. This paper proposes a new context-based segmentation algorithm for acquired image sequence, in which an improved genetic algorithm (GA) patching method is developed to segment different size target. To guarantee the correctness of first image segmentation and facilitate the use of context information, a boundary fusion operation and a simplified scale-invariant feature transform (SIFT)-based registration are presented respectively. The experimental results show the proposed segmentation algorithm is effective and accurate for renal biopsy image sequence.

The capacity maximization of line-of-sight (LoS) two-input and multiple-output (TIMO) channels in indoor environments is investigated in this paper. The 3×2 TIMO channel is mainly studied. First, the capacity fluctuation number (CFN) which reflects the variation of channel capacity is proposed. Then, the expression of the average capacity against the CFN is derived. The CFN is used as a criterion for optimization of the capacity by changing inter-element spacings of transmit and receive antenna arrays. Next, the capacity sensitivity of the 3×2 TIMO channel to the orientation and the frequency variation is studied and compared with those of 2×2 and 4×2 TIMO channels. A small capacity sensitivity of the 3×2 TIMO channel is achieved and verified by both simulation and measurement results. Furthermore, the CFN can also be used as a criterion for optimization of average capacity and the proposed optimization method is validated through numerical results.

To enhance the privacy of vehicle owners, combinatorial certificate management schemes assign each certificate to a large enough group of vehicles so that it will be difficult to link a certificate to any particular vehicle. When an innocent vehicle shares a certificate with a misbehaving vehicle and the certificate on the misbehaving vehicle has been revoked, the certificate on the innocent vehicle also becomes invalid and is said to be covered. When a group of misbehaving vehicles collectively share all the certificates assigned to an innocent vehicle and these certificates are revoked, the innocent vehicle is said to be covered. We point out that the previous analysis of the vehicle cover probability is not correct and then provide a new and exact analysis of the vehicle cover probability.

This paper proposes a novel iterative multiple-input multiple-output (MIMO) receiver for orthogonal frequency division multiplexing (OFDM) systems, named as an “iterative MIMO receiver employing virtual channels with a Turbo decoder.” The proposed MIMO receiver comprises a MIMO detector with virtual channel detection and a Turbo decoder, between which signals are exchanged iteratively. This paper proposes a semi hard input soft output (SHISO) iterative decoding for the iterative MIMO receiver that achieves better performance than a soft input soft output (SISO) iterative decoding. Moreover, this paper proposes a new criterion for the MIMO detector to select the most likely virtual channel. The performance of the proposed receiver is verified in a 6×2 MIMO-OFDM system by computer simulation. The proposed receiver achieves better performance than the SISO MAP iterative receiver by 1.5dB at the bit error rate (BER) of 10-4, by optimizing the number of the Turbo iteration per the SHISO iteration. Moreover, the proposed detection criterion enables the proposed receiver to achieve a gain of 3.0dB at the BER of 10-5, compared with the SISO MAP iterative receiver with the Turbo decoder.

Accuracy of a method for analyzing the interface defect properties; time-domain charge pumping method, is evaluated. The method monitors the charge pumping (CP) current in time domain, and thus we expect that it gives us a noble way to investigate the interface state properties. In this study, for the purpose of evaluating the accuracy of the method, the interface state density extracted from the time-domain data is compared with that measured using the conventional CP method. The results show that they are equal to each other for all measured devices with various defect densities, demonstrating that the time-domain CP method is sufficiently accurate for the defect density evaluation.

At Indocrypt 2005, Coglianese and Goi [1] suggested a new public key cryptosystem, MaTRU, which is a variant of NTRU. MaTRU is defined over ring M of k×k matrices whose elements are in the quotient ring R = Z[X]/(Xn-1). In addition, five example parameter sets suitable for this new structure were proposed. In this paper, we prove that it is impossible to generate appropriate key pairs for four parameter sets among the five proposed in [1] according to the key generation procedure described in [1]. The only parameter set where key pair generation is possible is when p, one of the parameters of MaTRU, is 2 and df, another parameter, is odd. Even with this parameter set, however, the decryption operation defined in [1] cannot recover an original plaintext from a given ciphertext because the value of another parameter, q, has been defined too small in [1]. Therefore, we propose an alternative method for key generation and suggest corrected parameter sets. In addition, a refined analysis for the key security of MaTRU is provided, and it is demonstrated that the key security may be significantly lower than that of the original analysis.

Negative feedback technique employing high DC gain operational amplifier (op-amp) is one of the most important techniques in analog circuit design. However, high DC gain op-amp is difficult to realize in scaled technology due to a decrease of intrinsic gain. In this paper, high DC gain op-amp using common-gate topology with high power efficiency is proposed. To achieve high DC gain, large output impedance is required but input transistors' drain conductance decreases output impedance of conventional topology such as folded cascode topology with complementary input. This is because bias current of the output side transistors is not separated from the bias current of the input transistors. On the other hand, proposed circuit can suppress a degradation of output impedance by inserting common-gate topology between input and output side. This architecture separates bias current of the input transistors from that of the output side, and hence the effect of the drain conductance of input transistors is reduced. As the result, proposed circuit can increase DC gain about 10,dB compared with the folded cascode topology with complementary input in 65,nm CMOS process. Moreover, power consumption can be reduced because input NMOS and PMOS share bias current. According to the simulation results, for the same power consumption, in the proposed circuit gain-bandwidth product (GBW) is improved by approximately 30% and noise is also reduced in comparison to the conventional topology.

Monopulse is a classical technique for radar angle estimation and still adopted for fast angle estimation in phased array antenna. The classical formula can be applied to a 2-dimentional phased array antenna if two conditions---the unbiasedness and the independence of the azimuth and the elevation estimate---are satisfied. However, if the sum and difference beams are adapted to suppress the interference under jamming condition, they can be severely distorted. Thus the difference beams become highly correlated and violate the conditions. In this paper, we show the numerical implementation of the generalized monopulse estimation using the distorted and correlated beams, especially for a subarray configured antenna. Because we use the data from the measured subarray patterns rather than the mathematical model, this numerical method can be easily implemented for the complex array configuration and gives good performance for the uncertainty of the real system.

In this paper, an energy harvesting architecture in an Underlay Cooperative Cognitive Network (UCCN) is investigated, in which power constrained Decode-and-Forward relays harvest energy from radio-frequency signals received from a source, and then consume the harvested energy by forwarding the recoded signals to their destination. These recoded signals are launched by a transmitting power which is the harvested energy per a time interval. Based on the energy harvesting architectures that have been studied, two operation protocols are proposed: UCCN with Power Splitting architecture (UCCN-PS), and UCCN with Time Switching architecture (UCCN-TS). The best cooperative relay in both protocols is taken to be the one that satisfies the following conditions: maximum harvested energy, and maximum decoding capacity. As a result of the best relay selection, the signal quality of the selected link from the best relay to the destination is enhanced by the maximum harvested energy. The system performance of the secondary network in the UCCN-PS and UCCN-TS protocols is analyzed and evaluated by the exact closed-form outage probabilities and throughput analyses over Rayleigh fading channels. The Monte Carlo simulation method is performed to verify the theoretical expressions. Evaluations based on outage probability and throughput show that the system performance of the secondary network in the UCCN-PS and UCCN-TS protocols improves when the number of cooperative relays and the interference constraint increase as well as when the primary receiver is farther from the transmitting nodes such as the source and relays of the secondary network. In addition, the throughput performance of the UCCN-PS protocol outperforms that of the UCCN-TS protocol. Finally, the effects of the power splitting ratio, energy harvesting time, energy conversion efficiency, target Signal-to-Noise Ratio (SNR), and location of cooperative relays on the system performance of the secondary network are presented and discussed.

Implicit feedback is an approach that utilizes uplink channel state information (CSI) for downlink transmit beamforming on multiple-input multiple-output (MIMO) systems, relying on over-the-air channel reciprocity. The implicit feedback improves throughput efficiency because overhead of CSI feedback for change of over-the-air channel responses is omitted. However, it is necessary for the implicit feedback to calibrate circuitry responses that uplink CSI includes, because actual downlink and uplink channel responses do not match due to different transmit and receive circuitry chains. This paper presents our proposed calibration scheme, weighted-combining calibration (WCC); it offers improved calibration accuracy. In WCC, an access point (AP) calculates multiple calibration coefficients from ratios of downlink and uplink CSI, and then combines coefficients with minimum mean square error (MMSE) weights. The weights are derived using a linear approximation in the high signal to noise power ratio (SNR) regime. Analytical mean square error (MSE) of calibration coefficients with WCC and calibration schemes for comparison is expressed based on the linear approximation. Computer simulations show that the analytical MSE matches simulated one if the linear approximation holds, and that WCC improves the MSE and signal to interference plus noise power ratio (SINR). Indoor experiments are performed on a multiuser MIMO system with implicit feedback based on orthogonal frequency division multiplexing (OFDM), built using measurement hardware. Experimental results verify that the channel reciprocity can be exploited on the developed multiuser MIMO-OFDM system and that WCC is also effective in indoor environments.

In this paper, a novel synchronization method is proposed for a heterogeneous cognitive radio that combines public safety mobile communication systems (PMCSs) with commercial mobile wireless communication systems (CMWCSs). The proposed method enables self-synchronization of the PMCSs as well as co-synchronization of PMCSs and CMWCSs. In this paper, the self-synchronization indicates that each system obtains own timing synchronization. The co-synchronization indicates that a system recognizes data transmitted from other systems correctly. In our research, we especially focus on PMCS self-synchronization because it is one of the most difficult parts of our proposed cognitive radio that improves PMCS's communication quality. The proposed method is utilized for systems employing differentially encoded π/4 shift QPSK modulation. The synchronization can be achieved by correlating envelopes calculated from a PMCS's received signals with subsidiary information (SI) sent via a CMWCS. In this paper, the performance of the proposed synchronization method is evaluated by computer simulation. Moreover, because this SI can also be used to improve the bit error rate (BER) of PMCSs, BER improvement and efficient SI sending methods are derived, after which their performance is evaluated.

This paper presents a downlink interference mitigation framework for two-tier heterogeneous networks, that consist of spectrum-sharing macrocells and femtocells*. This framework establishes cooperation between the two tiers through two algorithms, namely, the restricted waterfilling (RWF) algorithm and iterative reweighted least squares interference alignment (IRLS-IA) algorithm. The proposed framework models the macrocell-femtocell two-tier cellular system as an overlay cognitive radio system in which the macrocell system plays the role of the primary user (PU) while the femtocell networks play the role of the cognitive secondary users (SUs). Through the RWF algorithm, the macrocell basestation (MBS) cooperates with the femtocell basestations (FBSs) by releasing some of its eigenmodes to the FBSs to do their transmissions even if the traffic is heavy and the MBS's signal to noise power ratio (SNR) is high. Then, the FBSs are expected to achieve a near optimum sum rate through employing the IRLS-IA algorithm to mitigate both the co-tier and cross-tier interference at the femtocell users' (FUs) receivers. Simulation results show that the proposed IRLS-IA approach provides an improved sum rate for the femtocell users compared to the conventional IA techniques, such as the leakage minimization approach and the nuclear norm based rank constraint rank minimization approach. Additionally, the proposed framework involving both IRLS-IA and RWF algorithms provides an improved total system sum rate compared with the legacy approaches for the case of multiple femtocell networks.

A readout technique using single-flux-quantum (SFQ) circuits enables superconducting single photon detectors (SSPDs) to operate at further high-speed, where a mutually-coupled dc-to-SFQ (MC-dc/SFQ) converter is used as an interface between SSPDs and SFQ circuits. In this work, we investigated pulse response of the MC-dc/SFQ converter. We employed on-chip pulse generators to evaluate pulse response of the MC-dc/SFQ converter for various pulses. The MC-dc/SFQ converter correctly operated for the pulse current with the amplitude of 52,$mu$A and the width of 179,ps. In addition, we examined influence of the pulse amplitude and width to operation of the MC-dc/SFQ converter by numerical simulation. The simulation results indicated that the MC-dc/SFQ converter had wide operation margins for pulse current with amplitudes of 30--60,$mu$A irrespective of the pulse widths.