In this paper, we study partial words in relation with pcodes, compatibility, and containment. First, we introduce C⊂(L), the set of all partial words contained by elements of L, and C⊃(L), the set of all partial words containing elements of L, for a set L of partial words. We discuss the relation between C(L), the set of all partial words compatible with elements of the set L, C⊂(L), and C⊃(L). Next, we consider the condition for C(L), C⊂(L), and C⊃(L) to be a pcode when L is a pcode. Furthermore, we introduce some classes of pcodes. An infix pcode and a comma-free pcode are defined, and the inclusion relation among these classes is established.

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.

To improve immunity against process gradients, a common centroid constraint, in which every pair of capacitors should be placed symmetrically with respect to a common center point, is widely used. The pair of capacitors are derived by dividing some original capacitors into two halves. Xiao et al. proposed a method to obtain a placement which satisfies the common centroid constraints, but this method has a defect. In this paper, we propose a decoding algorithm to obtain a placement which satisfies common centroid constraints.

PEiD is a packer identification tool widely used for malware analysis but its accuracy is becoming lower and lower recently. There exist two major reasons for that. The first is that PEiD does not provide a way to create signatures, though it adopts a signature-based approach. We need to create signatures manually, and it is difficult to catch up with packers created or upgraded rapidly. The second is that PEiD utilizes exact matching. If a signature contains any error, PEiD cannot identify the packer that corresponds to the signature. In this paper, we propose a new automated packer identification method to overcome the limitations of PEiD and report the results of our numerical study. Our method applies string-kernel-based support vector machine (SVM): it can measure the similarity between packed programs without our operations such as manually creating signature and it provides some error tolerant mechanism that can significantly reduce detection failure caused by minor signature violations. In addition, we use the byte sequence starting from the entry point of a packed program as a packer's feature given to SVM. That is, our method combines the advantages from signature-based approach and machine learning (ML) based approach. The numerical results on 3902 samples with 26 packer classes and 3 unpacked (not-packed) classes shows that our method achieves a high accuracy of 99.46% outperforming PEiD and an existing ML-based method that Sun et al. have proposed.

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.

We propose an adaptive reversible data hiding method with superior visual quality and capacity in which an adaptive generalized difference expansion (AGDE) method is applied to an integer-to-integer subband transform (I2I-ST). I2I-ST performs the reversible subband transform and the AGDE method is a state-of-the-art method of reversible data hiding. The results of experiments we performed objectively and perceptually show that the proposed method has better visual quality than conventional methods at the same embedding rate due to low variance in the frequency domain.

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.

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.

In this paper, a simple yet efficient texture representation is proposed for texture classification by exploring the joint statistics of local quantized patterns (jsLQP). In order to combine information of different domains, the Gaussian derivative filters are first employed to obtain the multi-scale gradient responses. Then, three feature maps are generated by encoding the local quantized binary and ternary patterns in the image space and the gradient space. Finally, these feature maps are hybridly encoded, and their joint histogram is used as the final texture representation. Extensive experiments demonstrate that the proposed method outperforms state-of-the-art LBP based and even learning based methods for texture classification.

This paper describes a very accurate method of estimating the return-path-capacitance and validates the estimation based on low-error measurements for electric-field intrabody communication. The return-path capacitance, Cg, of a mobile transceiver is estimated in two ways. One uses the attenuation factor in transmission and capacitance, Cb, between a human body and the earth ground. The other uses the attenuation factor in reception. To avoid the influence of the lead wire in the estimation of Cb, Cb is estimated from the attenuation factor measured with an amplifier with a low input capacitance. The attenuation factor in reception is derived by using the applied-voltage dependence of the reception rate. This way avoids the influence of any additional instruments on the return-path capacitance and allows that capacitance to be estimated under the same condition as actual intrabody communication. The estimates obtained by the two methods agree well with each other, which means that the estimation of Cb is valid. The results demonstrate the usefulness of the methods.

This paper presents a new phase unwrapping algorithm, based on an extended particle filter (EPF) for SAR interferometry. This technique is not limited by the nonlinearity of the model, and is able to accurately unwrap noisy interferograms by applying EPF to simultaneously perform noise suppression and phase unwrapping. Results obtained from synthetic and real data validate the effectiveness of the proposed method.

To help student nurses learn to transfer patients from a bed to a wheelchair, this paper proposes a system for automatic skill evaluation in nurses' training for this task. Multiple Kinect sensors were employed, in conjunction with colored markers attached to the trainee's and patient's clothing and to the wheelchair, in order to measure both participants' postures as they interacted closely during the transfer and to assess the correctness of the trainee's movements and use of equipment. The measurement method involved identifying body joints, and features of the wheelchair, via the colors of the attached markers and calculating their 3D positions by combining color and depth data from two sensors. We first developed an automatic segmentation method to convert a continuous recording of the patient transfer process into discrete steps, by extracting from the raw sensor data the defining features of the movements of both participants during each stage of the transfer. Next, a checklist of 20 evaluation items was defined in order to evaluate the trainee nurses' skills in performing the patient transfer. The items were divided into two types, and two corresponding methods were proposed for classifying trainee performance as correct or incorrect. One method was based on whether the participants' relevant body parts were positioned in a predefined spatial range that was considered ‘correct’ in terms of safety and efficacy (e.g., feet placed appropriately for balance). The second method was based on quantitative indexes and thresholds for parameters describing the participants' postures and movements, as determined by a Bayesian minimum-error method. A prototype system was constructed and experiments were performed to assess the proposed approach. The evaluation of nurses' patient transfer skills was performed successfully and automatically. The automatic evaluation results were compared with evaluation by human teachers and achieved an accuracy exceeding 80%.

We calculated propagation constants of supermodes for two-dimensional two-slab waveguides, with small core gap, using second-order perturbation expansion from gapless slab waveguide system, and compared our results with the existing works. In the perturbation calculation, we used trapezoidal method to calculate the integral over the transverse direction in space and obtained second-order expansion of (core gap)/(core width) for propagation constants. Our result can explain the qualitative relationship between the propagation constants and the gap distance in the neighbor of (core gap)/(core width) being zero.

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.

Recently, small cell systems such as femto cell are being considered as a good alternative that can support the increasing demand for mobile data traffic because they can significantly enhance network capacity by increasing spatial reuse. In this paper, we analyze the coverage and capacity of a femto cell when it is deployed in a hotspot to reduce the traffic loads of neighboring macro base stations (BSs). Our analysis results show that the coverage and capacity of femto cell are seriously affected by surrounding signal environment and they can be greatly enhanced by adapting power allocation for channels to the surrounding environment. Thus, we propose an adaptive power partitioning scheme where power allocation for channels can be dynamically adjusted to suit the environment surrounding the femto cell. In addition, we numerically derive the optimal power allocation ratio for channels to optimize the performance of the femto cell in the proposed scheme. It is shown that the proposed scheme with the optimal channel power allocation significantly outperforms the conventional scheme with fixed power allocation for channels.

In the Coordinated Multi-Point (CoMP) system under the condition of limited feedback, a reasonable coordinated set relies heavily on the splitting factor that is used to divide the total feedback bits into channel direction information (CDI) feedback bits and channel quality information (CQI) feedback bits. The relation of splitting factor and coordinated set is examined in this paper. After defining a penalty factor, we derive the net ergodic capacity optimization problem, whose variables to be optimized are the number of coordinated BSs, the divided area's radius and the splitting factor. According to an existing codebook and the quantized channel error model, the downlink received signal model is updated after adding the splitting factor. Through random matrix knowledge, the stochastic property of this model is obtained. A close approximate expression including the splitting factor to be optimized related to coordinated set is given. In addition, a revised adaptive feedback scheme is proposed to split the feedback bits. Simulation results show that the proposed scheme provides a significant performance gain, especially as the user velocity is high.

To reduce perforamnce degradations of LR-WPANs due to interference from WLANs, this letter proposes a protocol to allow a piconet to switch an operating channel to an interference-free channel only for transmitting beacon frames. The proposed method does not only increase network performances because of hgh reliability of the beacon frames, but also increase overerall channel utilizations because of using even interfered-channels.

We theoretically study the performance of multiple-input multiple-output (MIMO) free-space optical (FSO) systems using subcarrier quadrature modulation (SC-QAM) signaling. The system average symbol-error rate (ASER) is derived taking into account the atmospheric turbulence effects on the MIMO/FSO channel, which is modeled by log-normal and the gamma-gamma distributions for weak and moderate-to-strong turbulence conditions. We quantitatively discuss the influence of index of refraction structure parameter, link distance, and different MIMO configurations on the system ASER. We also analytically derive and discuss the MIMO/FSO average (ergodic) channel capacity (ACC), which is expressed in terms of average spectral efficiency (ASE), under the impact of various channel conditions. Monte Carlo simulations are also performed to validate the mathematical analysis, and a good agreement between numerical and simulation results is confirmed.

In signal restoration problems, we expect to improve the restoration performance with a priori information about unknown target signals. In this paper, the parametric Wiener filter with linear constraints for unknown target signals is discussed. Since the parametric Wiener filter is usually defined as the minimizer of the criterion not for the unknown target signal but for the filter, it is difficult to impose constraints for the unknown target signal in the criterion. To overcome this difficulty, we introduce a criterion for the parametric Wiener filter defined for the unknown target signal whose minimizer is equivalent to the solution obtained by the original formulation. On the basis of the newly obtained criterion, we derive a closed-form solution for the parametric Wiener filter with linear constraints.

We first find simple characterizations of $rac{1}{N} mathbb{Z}$-invariance of arbitrary principal shift-invariant space $V(phi)$. Then we find several equivalent conditions for $V(phi)$ to admit periodic oversampling for a class of continuous frame generators $phi$. In particular, when $phi$ is band-limited and $hat{phi}$ is piecewise continuous, we find very simple and general sufficient conditions for $V(phi)$ to admit periodic oversampling, which involve the extra invariance of $V(phi)$, together with an illustrating example.