The current development of video quality assessment algorithms suffers from the lack of available video sequences for training, verification and validation to determine and enhance the algorithm's application scope. The Joint Effort Group of the Video Quality Experts Group (VQEG-JEG) is currently driving efforts towards the creation of large scale, reproducible, and easy to use databases. These databases will contain bitstreams of recent video encoders (H.264, H.265), packet loss impairment patterns and impaired bitstreams, pre-parsed bitstream information into files in XML syntax, and well-known objective video quality measurement outputs. The database is continuously updated and enlarged using reproducible processing chains. Currently, more than 70,000 sequences are available for statistical analysis of video quality measurement algorithms. New research questions are posed as the database is designed to verify and validate models on a very large scale, testing and validating various scopes of applications, while subjective assessment has to be limited to a comparably small subset of the database. Special focus is given on the principles guiding the database development, and some results are given to illustrate the practical usefulness of such a database with respect to the detailed new research questions.

In this paper, the Quality of Experience (QoE) on Dynamic Adaptive Streaming based on HTTP (DASH) is researched. To study users' experience on DASH, extensive subjective tests are firstly designed and conducted, based on which, we research QoE enhancement in DASH and find that DASH ensures more fluent playback (less stall) than constant bitrate (CBR) streaming to promote users' satisfaction especially in mobile networks. Then we adopt two-way analysis of variance (ANOVA) tests in statistics to identify the effect of specific factors (segment bitrate, bitrate fluctuation pattern, and bitrate switching) that impair users' experience on DASH. The impairment functions are then derived for these influence factors based on the Primacy and Recency Effect, a psychological phenomenon that has been proved to exist in users' experience on DASH in this paper. And the final QoE evaluation model is proposed to provide high correlation assessment for QoE of DASH. The good performance of our QoE model is validated by the subjective tests. In addition, our QoE study on DASH is also applied for QoE management to propose a QoE-based bitrate adaptation strategy, which promotes users' experience on DASH more strongly than the strategy based on QoS.

Computation in the brain is realized in complicated, heterogeneous, and extremely large-scale network of neurons. About a hundred billion neurons communicate with each other by action potentials called “spike firings” that are delivered to thousands of other neurons from each. Repeated integration and networking of these spike trains in the network finally form the substance of our cognition, perception, planning, and motor control. Beyond conventional views of neural network mechanisms, recent rapid advances in both experimental and theoretical neuroscience unveil that the brain is a dynamical system to actively treat environmental information rather passively process it. The brain utilizes internal dynamics to realize our resilient and efficient perception and behavior. In this paper, by considering similarities and differences of the brain and information networks, we discuss a possibility of information networks with brain-like continuing internal dynamics. We expect that the proposed networks efficiently realize context-dependent in-network processing. By introducing recent findings of neuroscience about dynamics of the brain, we argue validity and clues for implementation of the proposal.

Support of incoming traffic differentiation and Quality of Service (QoS) assurance is very important for the development of high performance packet switches, capable of separating traffic flows. In our previous paper, we proposed the implementation of two buffers at each crosspoint of a crossbar fabric that leads to the Dual Crosspoint Queued (DCQ) switch. Inside DCQ switch, one buffer is used to store the real-time traffic and the other for the non-real-time traffic. We also showed that the static priority algorithms can provide the QoS only for the real-time traffic due to their greedy nature that gives the absolute priority to that type of traffic. In order to overcome this problem, in our paper we propose the DCQ switch with the Largest Weighted Occupancy First scheduling algorithm that provides the desired QoS support for both traffic flows. Detailed analysis of the simulation results confirms the validity of proposed solution.

This paper proposes a speech watermarking method based on the concept of formant tuning. The characteristic that formant tuning can improve the sound quality of synthesized speech was employed to achieve inaudibility for watermarking. In the proposed method, formants were firstly extracted with linear prediction (LP) analysis and then embedded with watermarks by symmetrically controlling a pair of line spectral frequencies (LSFs) as formant tuning. We evaluated the proposed method by two kinds of experiments regarding inaudibility and robustness compared with other methods. Inaudibility was evaluated with objective and subjective tests and robustness was evaluated with speech codecs and speech processing. The results revealed that the proposed method could satisfy both inaudibility and robustness that required for speech watermarking.

An important issue of fragile watermarking for image is to locate and restore the tampered pixels individually and accurately. This issue is resolved for concentrated tampering. In contrast, for diverse tampering, only localization is realized. This paper presents a restoration method for the most accurate scheme tolerant against diverse tampering. We analyze the error probability and experimentally confirm that the proposed method accurately restores the tampered pixels. We also show two variations based on the fact that the authentication data used for deriving the watermark is a maximum length sequence code.

Multimedia contents can be enriched by introducing navigation with image codes readable by camera-mounted mobile devices such as smartphones. Data hiding technologies were utilized for embedding such codes to make their appearances inconspicuous, which can reduce esthetic damage on visual media. This article proposes a method of embedding two-dimensional codes into images based on successive color mixture for a blue-color channel. This technology can make the color of codes mimic those used on a cover image, while preserving their readability for current general purpose image sensors.

Segmenting foreground objects from highly dynamic scenes with missing data is very challenging. We present a novel unsupervised segmentation approach that can cope with extensive scene dynamic as well as a substantial amount of missing data that present in dynamic scene. To make this possible, we exploit convex optimization of total variation beforehand for images with missing data in which depletion mask is available. Inpainting depleted images using total variation facilitates detecting ambiguous objects from highly dynamic images, because it is more likely to yield areas of object instances with improved grayscale contrast. We use a conditional random field that adapts to integrate both appearance and motion knowledge of the foreground objects. Our approach segments foreground object instances while inpainting the highly dynamic scene with a variety amount of missing data in a coupled way. We demonstrate this on a very challenging dataset from the UCSD Highly Dynamic Scene Benchmarks (HDSB) and compare our method with two state-of-the-art unsupervised image sequence segmentation algorithms and provide quantitative and qualitative performance comparisons.

We previously proposed a query-by-sketch image retrieval system that uses an edge relation histogram (ERH). However, it is difficult for this method to retrieve partial objects from an image, because the ERH is a feature of the entire image, not of each object. Therefore, we propose an object-extraction method that uses edge-based features in order to enable the query-by-sketch system to retrieve partial images. This method is applied to 20,000 images from the Corel Photo Gallery. We confirm that retrieval accuracy is improved by using the edge-based features for extracting objects, enabling the query-by-sketch system to retrieve partial images.

We propose a new multi-label feature selection method that does not require the multi-label problem to be transformed into a single-label problem. Using quadratic programming, the proposed multi-label feature selection algorithm provides markedly better learning performance than conventional methods.

Rainbow is one of signature schemes based on the problem solving a set of multivariate quadratic equations. While its signature generation and verification are fast and the security is presently sufficient under suitable parameter selections, the key size is relatively large. Recently, Quaternion Rainbow — Rainbow over a quaternion ring — was proposed by Yasuda, Sakurai and Takagi (CT-RSA'12) to reduce the key size of Rainbow without impairing the security. However, a new vulnerability emerges from the structure of quaternion ring; in fact, Thomae (SCN'12) found that Quaternion Rainbow is less secure than the same-size original Rainbow. In the present paper, we further study the structure of Quaternion Rainbow and show that Quaternion Rainbow is one of sparse versions of the Rainbow. Its sparse structure causes a vulnerability of Quaternion Rainbow. Especially, we find that Quaternion Rainbow over even characteristic field, whose security level is estimated as about the original Rainbow of at most 3/4 by Thomae's analysis, is almost as secure as the original Rainbow of at most 1/4-size.

In this paper, we propose a new structure for a compact matched filter bank for a mutually orthogonal zero-correlation zone (MO-ZCZ) sequence set consisting of ternary sequence pairs obtained by Hadamard and binary ZCZ sequence sets; this construction reduces the number of two-input adders and delay elements. The matched filter banks are implemented on a field-programmable gate array (FPGA) with 51,840 logic elements (LEs). The proposed matched filter bank for an MO-ZCZ sequence set of length 160 can be constructed by a circuit size that is about 8.6% that of a conventional matched filter bank.

This paper investigates the performance of an overloaded multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system with a repetition code. It has been demonstrated that diversity with block coding prevents the performance degradation induced by signal multiplexing. However, the computational complexity of a joint decoding scheme increases exponentially with the number of multiplexed signal streams. Thus, this paper proposes the use of a repetition code in the overloaded MIMO-OFDM system. In addition, QR decomposition with M-algorithm (QRM) maximum likelihood decoding (MLD) is applied to the decoding of the repetition code. QRM-MLD significantly reduces the amount of joint decoding complexity. In addition, virtual antennas are employed in order to increase the throughput that is reduced by the repetition code. It is shown that the proposed scheme reduces the complexity by about 1/48 for 6 signal streams with QPSK modulation while the BER degradation is less than 0.1dB at the BER of 10-3.

This letter presents a new blind audio watermarking scheme using eigenvalue decomposition (EVD). Initially, the original audio is divided into frames and the samples of each frame are arranged into a square matrix. EVD is applied to each of these matrices. Watermark data is embedded into the largest eigenvalue of each diagonal matrix by quantization. Data embedding rate of the proposed scheme is 172.39bps. Simulation results confirm the imperceptibility of the proposed scheme and its higher robustness against various attacks compared to the state-of-the-art watermarking methods available in the literature.

As the quantity of mobile application traffic keeps increasing, operators are facing the scalability limits of VoIP protocols. Higher queuing delays at the Session Initiation Protocol (SIP) server create significantly more retransmissions in the network. When the message arrival rate including retransmissions exceeds the message serving capacity of a SIP server, the queue size increases and eventually the SIP server can crash. Our analysis demonstrates that server crash can be prevented if the buffer size of the SIP server is limited. However, having smaller buffer sizes yields side effects such as lower successful transaction ratio for bursty traffic. In this paper, we propose a new SIP server scheduling mechanism in which the original incoming SIP requests have strict priority over the retransmitted requests. The priority based scheduling mechanism provides network administrator with the ability to configure the buffer size of a SIP server to a moderately high value. We implement the proposed priority-based scheduling mechanism in the JAIN-SIP stack and confirm that the implementation requires minimal changes to the SIP standard. Numerical experiments show that the proposed scheduling mechanism provides significantly and consistently better scalability at high buffer sizes compared to the heavily used first-in-first-out scheduling, thus enabling us to avoid server overloads.

The reliability of electromagnetic relay (EMR) which contains a permanent magnet (PM) can be improved by a robust design method. In this parameter design process, the calculation of electromagnetic system is very important. In analytical calculation, PM is often equivalent to a lumped parameter model of one magnetic resistance and one magnetic potential, but significant error is often caused; in order to increase the accuracy, a distributed parameter calculation model (DPM) of PM bar is established; solution procedure as well as verification condition of this model is given; by a case study of the single PM bar, magnetic field lines division method is adopted to build the DPM, the starting point and section magnetic flux of each segment are solved, a comparison is made with finite element method (FEM) and measured data; the accuracy of this magnetic field line based distributed parameter model (MFDPM) in PM bar is verified; this model is applied to the electromagnetic system of a certain type EMR, electromagnetic system calculation model is established based on MFDPM, and the static force is calculated under different rotation angles; compared with traditional lumped parameter model and FEM, it proves to be of acceptable calculation accuracy and high calculation speed which fit the requirement of robust design.

The present paper introduces a novel method for the construction of sequences that have a zero-correlation zone. For the proposed sequence set, both the cross-correlation function and the side lobe of the autocorrelation function are zero for phase shifts within the zero-correlation zone. The proposed scheme can generate a set of sequences, each of length 16n2, from an arbitrary Hadamard matrix of order n and a set of 4n trigonometric function sequences of length 2n. The proposed construction can generate an optimal sequence set that satisfies, for a given zero-correlation zone and sequence period, the theoretical bound on the number of members. The peak factor of the proposed sequence set is equal to √2.

A generalized chirp-like (GCL) sequence of period N is constructed by modulating a Zadoff-Chu sequence of period N with an arbitrary unimodular sequence of period m, where m divides N. Under some specific conditions, the cross-correlations between two GCL sequences are shown to have exactly the same magnitudes as those of their corresponding Zadoff-Chu sequences regardless of the employed unimodular sequences. In this paper, we first investigate the sufficient conditions under which such a relation holds. We then use them to construct a new class of optimal zero-correlation zone (ZCZ) sequence sets which can be considered to be an extension of the so-called GCL-ZCZ sequence sets.

In this paper, with a modification of our earlier construction in [12], new classes of optimal LHZ FHS sets with new parameters are obtained which are optimal in the sense that their parameters meet the Peng-Fan-Lee bound. It is shown that all the sequences in the proposed FHS sets are shift distinct. The proposed FHS sets are suitable for quasi-synchronous time/frequency hopping code division multiple access systems to eliminate multiple-access interference.

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.