The second generation digital terrestrial broadcasting system (DVB-T2) is the first broadcasting system employing MISO (Multiple-Input Single-Output) algorithms. The potential MISO gain of this system has been roughly predicted through simulations and field tests. Of course, the potential MISO SFN gain (MISO-SFNG) differs according to the simulation conditions, test methods, and measurement environments. In this paper, network gains of SISO-SFN and MISO-SFN are theoretically derived. Such network gains are also analyzed with respect to the receive power imbalance and coverage distances of SISO and MISO SFN. From the analysis, it is proven that MISO-SFNG is always larger than SISO SFN gain (SISO-SFNG) in terms of the achievable SNR. Further, both MISO-SFNG and SISO-SFNG depend on the power imbalance, but the network gains are constant regardless of the modulation order. Once the field strength of the complete SFN is obtained by coverage planning tools or field measurements, the SFN service coverage can be precisely calibrated by applying the closed-form SFNG formula.

We describe a novel idea to improve machine translation by combining multiple candidate translations and extra translations. Without manual work, extra translations can be generated by identifying and hybridizing the syntactic equivalents in candidate translations. Candidate and extra translations are then combined on sentence level for better general translation performance.

Many subjective assessment methods for video quality are provided by ITU-T and ITU-R recommendations, but the differences among these methods have not been sufficiently studied. We compare five subjective assessment methods using four quantitative performance indices for both HD and QVGA resolution video. We compare the Double-Stimulus Continuous Quality-Scale (DSCQS), Double-Stimulus Impairment Scale (DSIS), Absolute Category Rating method (ACR), and ACR with Hidden Reference (ACR-HR) as common subjective assessment methods for HD and QVGA resolution videos. Furthermore, we added ACR with an 11-grade scale (ACR11) for the HD test and Subjective Assessment of Multimedia Video Quality (SAMVIQ) for the QVGA test for quality scale variations. The performance indices are correlation coefficients, rank correlation coefficients, statistical reliability, and assessment time. For statistical reliability, we propose a performance index for comparing different quality scale tests. The results of the performance comparison showed that the correlation coefficients and rank correlation coefficients of the mean opinion scores between pairs of methods were high for both HD and QVGA tests. As for statistical reliability provided by the proposed index, DSIS of HD and ACR of QVGA outperformed the other methods. Moreover, ACR, ACR-HR, and ACR11 were the most efficient subjective quality assessment methods from the viewpoint of assessment time.

To characterize an antenna, the acquisition of its three-dimensional radiation pattern is the fundamental requirement. Spherical antenna measurement is a practical approach to measuring antenna patterns in spherical geometry. However, due to the limitations of measurement range and measurement time, the measured samples may either be incomplete on scanning sphere, or be inadequate in terms of the sampling interval. Therefore there is a need to extrapolate and interpolate the measured samples. Spherical wave expansion, whose band-limited property is derived from the sampling theorem, provides a good tool for reconstructing antenna patterns. This research identifies the limitation of the conventional algorithm when reconstructing the pattern of an antenna which is not located at the coordinate origin of the measurement set-up. A novel algorithm is proposed to overcome the limitation by resampling between the unprimed and primed (where the antenna is centred) coordinate systems. The resampling of measured samples from the unprimed coordinate to the primed coordinate can be conducted by translational phase shift, and the resampling of reconstructed pattern from the primed coordinate back to the unprimed coordinate can be accomplished by rotation and translation of spherical waves. The proposed algorithm enables the analytical and continuous pattern reconstruction, even under the severe sampling condition for deviated AUT. Numerical investigations are conducted to validate the proposed algorithm.

Coupled with the discrete wavelet transform, SPIHT (set partitioning in hierarchical trees) is a highly efficient image compression technique that allows for progressive transmission. One problem, however, is that its decoding can be extremely sensitive to bit errors in the code sequence. In this paper, we address the issue of transmitting SPIHT-encoded images via noisy channels, wherein errors are inevitable. The communication scenario assumed in this paper is that the transmitter cannot get any acknowledgement from the receiver. In our scheme, the original SPIHT code sequence is first segmented into packets. Each packet is classified as either a CP (critical packet) or an RP (refinement packet). For error control, cyclic redundancy check (CRC) is incorporated into each packet. By checking the CRC check sum, the receiver is able to tell whether a packet is correctly received or not. In this way, the noisy channel can be effectively modeled as an erasure channel. For unequal error protection (UEP), each of those packets are repeatedly transmitted for a few times, as determined by a process called diversity allocation (DA). Two DA algorithms are proposed. The first algorithm produces a nearly optimal decoded image (as measured in the expected signal-to-noise ratio). However, its computation cost is extremely high. The second algorithm works in a progressive fashion and is naturally compatible with progressive transmission. Its computation complexity is extremely low. Nonetheless, its decoded image is nearly as good. Experimental results show that the proposed scheme significantly improves the decoded images. They also show that making distinction between CP and RP results in wiser diversity allocation to packets and thus produces higher quality in the decoded images.

The separation time-overlapping ultrasound signals is necessary to obtain accurate estimate of transit time and material properties. In this letter, a method to determine the optimal transform order of fractional Fourier transform (FRFT) for decomposition of overlapping ultrasonic signals is proposed. The optimal transform order is obtained by minimizing the mean square error (MSE) between the output and the reference signal. Furthermore, windowing in FRFT domain is discussed. Numerical simulation results show the performances of the proposed method in separating signals overlapping in time.

An augmented PAKE (Password-Authenticated Key Exchange) protocol provides password-only authentication in the presence of an attacker, establishment of session keys between the involving parties, and extra protection for server compromise (i.e., exposure of password verification data). Among many augmented PAKE protocols, AMP variants (AMP2 [16] and AMP+ [15]) have been standardized in IEEE 1363.2 [9] and ISO/IEC 11770-4 [10]. In this paper, we thoroughly investigate APKAS-AMP (based on AMP2 [16]) and KAM3 (based on AMP+ [15]) which require several validity checks on the values, received and computed by the parties, when using a secure prime. After showing some attacks on APKAS-AMP and KAM3, we suggest new sanity checks that are clear and sufficient to prevent an attacker from doing these attacks.

This paper deals with an integral equation method for analyzing the diffraction of a transverse magnetic (TM) plane wave by a perfectly conductive periodic surface. In the region below the periodic surface, the extinction theorem holds, and the total field vanishes if the field solution is determined exactly. For an approximate solution, the extinction theorem does not hold but an extinction error field appears. By use of an image Green's function, new formulae are given for the extinction error field and the mean square extinction error (MSEE), which may be useful as a validity criterion. Numerical examples are given to demonstrate that the formulae work practically even at a critical angle of incidence.

We analyzed polarization characteristics of gammadion-shaped planar chiral nano-gratings (PCNGs), using Jones matrix and FDTD simulation. Optical activity (OA) was found to take place at wavelengths where long-lifetime modes appeared in the chiral layer. Among two kinds of resonance phenomena that concern the extension of the lifetime, guided-mode resonance and Fabry-Perot resonance, the latter was found to be a key to generate practically-important, broad peaks in the OA spectrum. Through the calculation of dispersion relations of Bloch modes in the chiral layer, we showed that the interference of multiple modes with group velocity dispersion played a critical role in the generation of such long-lifetime modes.

The implementation security of the RSA cryptosystem, under the threat of side-channel analysis, has attracted the attentions of many researchers. Boer et al. had proposed the MRED-DPA attack on RSA-CRT by choosing ciphertexts of equi-distant data. Their attack can be applied to RSA-OAEP decryption but not RSA-PSS signing because of the PSS random padding. We propose a new DPA attack on an implementation of RSA-CRT, with the Montgomery reduction. The proposed attack assumes only known ciphertexts, and can be applied to both RSA-OAEP decryption and RSA-PSS signing even if a random padding technique is used in practice. This study also presents experimental results to verify the proposed attack. Finally, this study proposes a CRT-based message blinding technique as a low-cost DPA countermeasure.

The traditional reinforcement learning (RL) methods can solve Markov Decision Processes (MDPs) online, but these learning methods cannot effectively use a priori knowledge to guide the learning process. The exploration of the optimal policy is time-consuming and does not employ the information about specific issues. To tackle the problem, this paper proposes heuristic function negotiation (HFN) as an online learning framework. The HFN framework extends MDPs and introduces heuristic functions. HFN changes the state-action dual layer structure of traditional RL to the triple layer structure, in which multiple heuristic functions can be set to meet the needs required to solve the problem. The HFN framework can use different algorithms to let the functions negotiate to determine the appropriate action, and adjust the impact of each function according to the rewards. The HFN framework introduces domain knowledge by setting heuristic functions and thus speeds up the problem solving of MDPs. Furthermore, user preferences can be reflected in the learning process, which improves the flexibility of RL. The experiments show that, by setting reasonable heuristic functions, the learning results of the HFN framework are more efficient than traditional RL. We also apply HFN to the air combat simulation of unmanned aerial vehicles (UAVs), which shows that different function settings lead to different combat behaviors.

In modern hardware security applications, silicon physical unclonable functions (PUFs) are of interest for their potential use as a unique identity or secret key that is generated from inherent characteristics caused by process variations. However, arbiter-based PUFs utilizing the relative delay-time difference between equivalent paths have a security issue in which the generated challenge-response pairs (CRPs) can be predicted by a machine learning attack. We previously proposed the RG-DTM PUF, in which a response is decided from divided time domains allocated to response 0 or 1, to improve the uniqueness of the conventional arbiter-PUF in a small circuit. However, its resistance against machine learning attacks has not yet been studied. In this paper, we evaluate the resistance against machine learning attacks by using a support vector machine (SVM) and logistic regression (LR) in both simulations and measurements and compare the RG-DTM PUF with the conventional arbiter-PUF and with the XOR arbiter-PUF, which strengthens the resistance by using XORing output from multiple arbiter-PUFs. In numerical simulations, prediction rates using both SVM and LR were above 90% within 1,000 training CRPs on the arbiter-PUF. The machine learning attack using the SVM could never predict responses on the XOR arbiter-PUF with over six arbiter-PUFs, whereas the prediction rate eventually reached 95% using the LR and many training CRPs. On the RG-DTM PUF, when the division number of the time domains was over eight, the prediction rates using the SVM were equal to the probability by guess. The machine learning attack using LR has the potential to predict responses, although an adversary would need to steal a significant amount of CRPs. However, the resistance can exponentially be strengthened with an increase in the division number, just like with the XOR arbiter-PUF. Over one million CRPs are required to attack the 16-divided RG-DTM PUF. Differences between the RG-DTM PUF and the XOR arbiter-PUF relate to the area penalty and the power penalty. Specifically, the XOR arbiter-PUF has to make up for resistance against machine learning attacks by increasing the circuit area, while the RG-DTM PUF is resistant against machine learning attacks with less area penalty and power penalty since only capacitors are added to the conventional arbiter-PUF. We also attacked RG-DTM PUF chips, which were fabricated with 0.18-µm CMOS technology, to evaluate the effect of physical variations and unstable responses. The resistance against machine learning attacks was related to the delay-time difference distribution, but unstable responses had little influence on the attack results.

In multi-static sonar systems, the least square (LS) and maximum likelihood (ML) are the typical estimation criteria for target location estimation. The LS localizaiton has the advantage of low computational complexity. On the other hand, the performance of LS can be degraded severely when the target lies on or around the straight line between the source and receiver. We examine mathematically the reason for the performance degradation of LS. Then, we propose a location adaptive — least square (LA-LS) localization that removes the weakness of the LS localizaiton. LA-LS decides the receivers that produce abnormally large measurement errors with a proposed probabilistic measure. LA-LS achieves improved performance of the LS localization by ignoring the information from the selected receivers.

A macroscopic structure was analyzed for a system comprising multiple elements in which the dynamics is affected by their distribution. First, a nonlinear Boltzmann equation, which has an integration term with respect to the distribution of the elements, was derived. Next, the moment vector equation (MVE) for the Boltzmann equation was derived. The average probability density function (pdf) in a steady state was derived using eigen analysis of the coefficient matrix of the MVE. The macroscopic structure of the system and the mechanism that provides the average pdf and the transient response were then analyzed using eigen analysis. Evaluation of the average pdf and transient response showed that using eigen analysis is effective for analyzing not only the transient and stationary properties of the system but also the macroscopic structure and the mechanism providing the properties.

Recently, fuzzy set theory has been widely employed in building portfolio selection models where uncertainty plays a role. In these models, future security returns are generally taken for fuzzy variables and mathematical models are then built to maximize the investment profit according to a given risk level or to minimize a risk level based on a fixed profit level. Based on existing works, this paper proposes a portfolio selection model based on fuzzy birandom variables. Two original contributions are provided by the study: First, the concept of technical analysis is combined with fuzzy set theory to use the security returns as fuzzy birandom variables. Second, the fuzzy birandom Value-at-Risk (VaR) is used to build our model, which is called the fuzzy birandom VaR-based portfolio selection model (FBVaR-PSM). The VaR can directly reflect the largest loss of a selected case at a given confidence level and it is more sensitive than other models and more acceptable for general investors than conventional risk measurements. To solve the FBVaR-PSM, in some special cases when the security returns are taken for trapezoidal, triangular or Gaussian fuzzy birandom variables, several crisp equivalent models of the FBVaR-PSM are derived, which can be handled by any linear programming solver. In general, the fuzzy birandom simulation-based particle swarm optimization algorithm (FBS-PSO) is designed to find the approximate optimal solution. To illustrate the proposed model and the behavior of the FBS-PSO, two numerical examples are introduced based on investors' different risk attitudes. Finally, we analyze the experimental results and provide a discussion of some existing approaches.

This paper describes low-power dynamic multiple-input and multiple-output (MIMO) detection for a 4×4 MIMO-orthogonal frequency-division multiplexing (MIMO-OFDM) receiver. MIMO-OFDM systems achieve high-speed and large capacity communications. However, they impose high computational cost in MIMO detection when separating spatially multiplexed signals and they consume vast amounts of power. We propose low-power dynamic MIMO detection that controls detection speed according to wireless environments. The power consumption is reduced by dynamic voltage and frequency scaling (DVFS) that controls the operating voltage and clock frequency in the MIMO detector. We implemented dynamic MIMO detection in a pipelined minimum mean square error (MMSE) MIMO detector that we developed in our previous work. A power saving of 92% was achieved under lowest clock frequency mode conditions.

1+1 protection provides instantaneous proactive recovery from any single link failure by duplicating and sending the same source data onto two disjoint paths. Other resource efficient recovery techniques to deal with single link failure require switching operations at least at both ends, which restrict instantaneous recovery. However, the 1+1 protection technique demands at least double network resources. Our goal is to minimize the resources required for 1+1 protection while maintaining the advantage of instantaneous recovery. It was reported that the network coding (NC) technique reduces resource utilization in 1+1 protection, and in order to determine an optimum NC aware set of routes that minimizes the required network resources for 1+1 protection, an Integer Quadratic Programming (IQP) formulation has already been addressed. Solving an IQP problem requires large amount of memory (cannot be determined exactly) and special algorithms by the mathematical programming solver. In this paper our contributions consist of two parts. First, we formulate the optimization problem, corresponding to the IQP model, as an Integer Linear Programming (ILP) formulation, which is solvable by any linear programming solver, and so its memory and time requirements are smaller. However, the presented ILP model works well in small-scale and medium-scale networks, but fails to support large-scale networks due to excessive memory requirements and calculation time. Second, to deal with these issues, a heuristic algorithm is proposed to determine the best possible NC aware set of routes in large-scale networks. Numerical results show that our strategies achieve almost double the resource saving effect than the conventional minimal-cost routing policy in the examined medium-scale and large scale networks.

We propose a new, compact, center-fed reflector antenna that is capable of one-dimensional electronic beam scanning. The reflector profile in the vertical section (beam-scanning) is set to an imaging reflector configuration, while the profile in the orthogonal horizontal section (non-beam-scanning) is set to a Cassegrain antenna configuration. The primary radiator is a one-dimensional phased array antenna. We choose a center-fed configuration in order to reduce the antenna size as much as possible, despite the fact that the increased blocking area from the primary radiator causes degradation in efficiency compared to the typical offset-type configuration. In the proposed configuration, beam scanning is limited to one dimension, but utilize a compact, center-fed configuration that maintains the features of an imaging reflector antenna. We present the antenna configuration and design method and show that results obtained from the prototype antenna verify the predicted performance.

In this paper, the authors present a CAM-based Information Detection Hardware System for fast, exact and approximate image matching on 2-D data, using FPGA. The proposed system can be potentially applied to fast image matching with various required search patterns, without using search principles. In designing the system, we take advantage of Content Addressable Memory (CAM) which has parallel multi-match mode capability and has been designed, using dual-port RAM blocks. The system has a simple structure, and does not employ any Central Processor Unit (CPU) or complicated computations.

Two classes of 3rd order correlation immune symmetric Boolean functions have been constructed respectively in [1] and [2], in which some interesting phenomena of the algebraic degree have been observed as well. However, a good explanation has not been given. In this paper, we obtain the formulas for the degree of these functions, which can well explain the behavior of their degree.