A linear-correction method is developed for source position and velocity estimation using time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements. The proposed technique first obtains an initial source location estimate using the first-step processing of an existing algebraic algorithm. It then refines the initial localization result by estimating via weighted least-squares (WLS) optimization and subtracting out its estimation error. The new solution is shown to be able to achieve the Cramer-Rao lower bound (CRLB) accuracy and it has better accuracy over several benchmark methods at relatively high noise levels.

Target determination based on Doppler frequency shift (DFS) measurements is a nontrivial problem because of the nonlinear relation between the position space and the measurements. The conventional methods such as numerical iterative algorithm and grid searching are used to obtain the solution, while the former requires an initial position estimate and the latter needs huge amount of calculations. In this letter, to avoid the problems appearing in those conventional methods, an effective solution is proposed, in which two best linear unbiased estimators (BULEs) are employed to obtain an explicit solution of the proximate target position. Subsequently, this obtained explicit solution is used to initialize the problem of original maximum likelihood estimation (MLE), which can provide a more accurate estimate.

A modular serial pipelined sorting architecture for continuous input sequences is presented. It supports continuous sequences, whose lengths can be dynamically changed, and does so using a very simple control strategy. It consists of identical serial cascaded sorting cells, and lends itself to high frequency implementation with any number of sorting cells, because both data and control signals are pipelined. With L cascaded sorting cells, it produces a fully sorted result for sequences whose length N is equal to or less than L+1; for longer sequences, the largest L elements are sorted out. Being modularly designed, several independent smaller sorters can be dynamically configured to form a larger sorter.

In this paper, we propose a framework to allocate code rates of component codes in a Plotkin-type unequal error protection (UEP) code. We derive an equivalent noise variance for each component code using structure of the Plotkin construction and Gaussian assumption. Comparing the equivalent noise variance and Shannon limit, we can find a combination of the code rates for the component codes. We investigate three types of code rate combinations and analyse their UEP performance. We also estimate a performance crossing signal to noise ratio (SNR) of the Plotkin-type UEP code. It indicates that which code has better performance for a given SNR. We confirm that the proposed framework is appropriate to obtain a desired UEP capability.

In conventional spread spectrum (SS) watermarking schemes, random sequences are used for the modulation of watermark information. However, because of the mutual interference among those sequences, it requires complicated removal operation to improve the performance. In this paper, we propose an efficient spread spectrum watermarking scheme by introducing the orthogonal frequency divisiion multiplexing (OFDM) technique at the modulation of watermark information. The SS sequences in the proposed method are the DCT basic vectors modulated by a pseudo-random number (PN) sequence. We investigate the SS-based method considering the host interference at the blind detection scenario and analyze the noise caused by attacks. Because every operation is invertible, the quantization index modulation (QIM)-based method is applicable for the OFDM modulated signals. We also consider the property of watermark extracting operation in SS-based and QIM-based method and formalize their models of noisy channel in order to employ an error correcting code. The performance of their methods with error correcting code is numerically evaluated under the constraints of same distortion level in watermarked content. The experimental results indicated a criteria for the selection of SS-based and QIM-based methods for given content, which is determined by the amount of host interference. In case that the host interference is 0.8 times smaller than a watermark signal, the SS-based method is suitable. When it is 1.0 times larger, the QIM-based method should be selected.

This paper investigates open-loop Stackelberg games for a class of stochastic systems with multiple players. First, the necessary conditions for the existence of an open-loop Stackelberg strategy set are established using the stochastic maximum principle. Such conditions can be represented as solvability conditions for cross-coupled forward-backward stochastic differential equations (CFBSDEs). Second, in order to obtain the open-loop strategy set, a computational algorithm based on a four-step scheme is developed. A numerical example is then demonstrated to show the validity of the proposed method.

When haze exists in an image of an outdoor scene, the visibility of objects in the image is deteriorated. In recent years, to improve the visibility of objects in such images, many dehazing methods have been investigated. Most of the methods are based on the atmospheric scattering model. In such methods, the transmittance and global atmospheric light are estimated from an input image and a dehazed image is obtained by substituting them into the model. To estimate the transmittance and global atmospheric light, the dark channel prior is a major and powerful concept that is employed in many dehazing methods. In this paper, we propose a new dehazing method in which the degree of haze removal can be adjusted by changing its parameters. Our method is also based on the atmospheric scattering model and employs the dark channel prior. In our method, the estimated transmittance is adjusted to a more suitable value by a transform function. By choosing appropriate parameter values for each input image, good haze removal results can be obtained by our method. In addition, a quantitative index for evaluating the quality of a dehazed image is proposed in this paper. It can be considered that haze removal is a type of saturation enhancement. On the other hand, an output image obtained using the atmospheric scattering model is generally darker than the input image. Therefore, we evaluate the quality of dehazed images by considering the balance between the brightness and saturation of the input and output images. The validity of the proposed index is examined using our dehazing method. Then a comparison between several dehazing methods is carried out using the index. Through these experiments, the effectiveness of our dehazing method and the quantitative index is confirmed.

This letter proposes a Non-uniform Cell-based Index (NCI) to enable clients to quickly process window queries in the wireless spatial data broadcast environment. To improve the access time, NCI reduces the probe wait time by equalized spacing between indexes, using non-uniformly partitioned cells of data space. Through the performance evaluation, we show the proposed NCI outperforms the existing index schemes for window queries to spatial data in respect of access time.

Linked data endpoints are online query gateways to semantically annotated linked data sources. In order to query these data sources, SPARQL query language is used as a standard. Although a linked data endpoint (i.e. SPARQL endpoint) is a basic Web service, it provides a platform for federated online querying and data linking methods. For linked data consumers, SPARQL endpoint availability and discovery are crucial for live querying and semantic information retrieval. Current studies show that availability of linked datasets is very low, while the locations of linked data endpoints change frequently. There are linked data respsitories that collect and list the available linked data endpoints or resources. It is observed that around half of the endpoints listed in existing repositories are not accessible (temporarily or permanently offline). These endpoint URLs are shared through repository websites, such as Datahub.io, however, they are weakly maintained and revised only by their publishers. In this study, a novel metacrawling method is proposed for discovering and monitoring linked data sources on the Web. We implemented the method in a prototype system, named SPARQL Endpoints Discovery (SpEnD). SpEnD starts with a “search keyword” discovery process for finding relevant keywords for the linked data domain and specifically SPARQL endpoints. Then, the collected search keywords are utilized to find linked data sources via popular search engines (Google, Bing, Yahoo, Yandex). By using this method, most of the currently listed SPARQL endpoints in existing endpoint repositories, as well as a significant number of new SPARQL endpoints, have been discovered. We analyze our findings in comparison to Datahub collection in detail.

This paper proposes a new approach for generating pseudo random multi-valued (including binary-valued) sequences. The approach uses a primitive polynomial over an odd characteristic prime field ${p}$, where p is an odd prime number. Then, for the maximum length sequence of vectors generated by the primitive polynomial, the trace function is used for mapping these vectors to scalars as elements in the prime field. Power residue symbol (Legendre symbol in binary case) is applied to translate the scalars to k-value scalars, where k is a prime factor of p-1. Finally, a pseudo random k-value sequence is obtained. Some important properties of the resulting multi-valued sequences are shown, such as their period, autocorrelation, and linear complexity together with their proofs and small examples.

The present paper introduces the construction of quadriphase sequences having a zero-correlation zone. For a zero-correlation zone sequence set of N sequences, each of length l, the cross-correlation function and the side lobe of the autocorrelation function of the proposed sequence set are zero for the phase shifts τ within the zero-correlation zone z, such that |τ|≤z (τ ≠ 0 for the autocorrelation function). The ratio $rac{N(z+1)}{ell}$ is theoretically limited to one. When l=N(z+1), the sequence set is called an optimal zero-correlation sequence set. The proposed zero-correlation zone sequence set can be generated from an arbitrary Hadamard matrix of order n. The length of the proposed sequence set can be extended by sequence interleaving, where m times interleaving can generate 4n sequences, each of length 2m+3n. The proposed sequence set is optimal for m=0,1 and almost optimal for m>1.

Microblog, especially twitter, has become an integral part of our daily life for searching latest news and events information. Due to the short length characteristics of tweets and frequent use of unconventional abbreviations, content-relevance based search cannot satisfy user's information need. Recent research has shown that considering temporal and contextual aspects in this regard has improved the retrieval performance significantly. In this paper, we focus on microblog retrieval, emphasizing the alleviation of the vocabulary mismatch, and the leverage of the temporal (e.g., recency and burst nature) and contextual characteristics of tweets. To address the temporal and contextual aspect of tweets, we propose new features based on query-tweet time, word embedding, and query-tweet sentiment correlation. We also introduce some popularity features to estimate the importance of a tweet. A three-stage query expansion technique is applied to improve the relevancy of tweets. Moreover, to determine the temporal and sentiment sensitivity of a query, we introduce query type determination techniques. After supervised feature selection, we apply random forest as a feature ranking method to estimate the importance of selected features. Then, we make use of ensemble of learning to rank (L2R) framework to estimate the relevance of query-tweet pair. We conducted experiments on TREC Microblog 2011 and 2012 test collections over the TREC Tweets2011 corpus. Experimental results demonstrate the effectiveness of our method over the baseline and known related works in terms of precision at 30 (P@30), mean average precision (MAP), normalized discounted cumulative gain at 30 (NDCG@30), and R-precision (R-Prec) metrics.

We propose a pre-filtering system for blind equalization in order to separate orthogonal frequency division multiplexing (OFDM) symbols in a multiple-input multiple-output (MIMO) - OFDM system. In a conventional blind MIMO-OFDM equalization without the pre-filtering system, there is a possibility that originally transmitted streams are permutated, resulting in the receiver being unable to retrieve desired signals. We also note that signal permutation is different for each subcarrier. In order to solve this problem, each transmitted stream of the proposed MIMO-OFDM system is pre-filtered by a unique allpass filter. In this paper, the pre-filter is referred to as transmit tagging filter (TT-Filter). At a receiver, an inverse filter of the TT-filter is used to blindly equalize a MIMO channel without permutation problem. Further, in order to overcome the issue of phase ambiguity, this paper introduces blind phase compensation.

In this paper, a Boolean algebra approach is proposed to encode various acceptability semantics for abstract argumentation frameworks, where each semantics can be equivalently encoded into several Boolean constraint models based on Boolean matrices and a family of Boolean operations between them. Then, we show that these models can be easily translated into logic programs, and can be solved by a constraint solver over Boolean variables. In addition, we propose some querying strategies to accelerate the calculation of the grounded, stable and complete extensions. Finally, we describe an experimental study on the performance of our encodings according to different semantics and querying strategies.

We report on the fabrication of a magnetic metallic contaminant detector using multi-channel high-Tc RF-SQUIDs (superconducting quantum interference devices) for large packaged food. For food safety finding small metallic contaminants is an important issue for a food manufacturer. Hence, a detection method for small sized contaminants is required. Some detection systems for food inspection using high-Tc SQUIDs have been reported to date. The system described here is different from the previous systems in its permitted size for inspection, being larger at 150mm in height × 300mm in width. For inspection of large sized food packages, improvement of the signal to noise ratio (SNR) is an important issue because the signal intensity is inversely proportional to the cube of the distance between the SQUID sensor and the object. Therefore a digital filter was introduced and its parameters were optimized. As a result, a steel ball as small as 0.5mm in diameter at a stand-off distance of 167mm was successfully detected with more than SNR = 3.3.

Zero correlation zone (ZCZ) aperiodic complementary sequence (ZACS) sets have potential applications in multi-carriers (MC) CDMA communication systems, which can support more users than traditional complementary sequence sets. In this letter, methods for constructing ZACS sets based on orthogonal matrices are proposed. The new constructions may propose ZACS sets with optimal parameters. The new ZACS sets can be applied in approximately synchronized MC-CDMA to remove interferences.

The quality assessment of screen content images (SCIs) has been attractive recently. Different from natural images, SCI is usually a mixture of picture and text. Traditional quality metrics are mainly designed for natural images, which do not fit well into the SCIs. Motivated by this, this letter presents a simple and effective method to naturalize SCIs, so that the traditional quality models can be applied for SCI quality prediction. Specifically, bicubic interpolation-based up-sampling is proposed to achieve this goal. Extensive experiments and comparisons demonstrate the effectiveness of the proposed method.

In this review, we present recent advances relating to superconducting nanowire single-photon detectors (SSPDs or SNSPDs) and their broad range of applications. During a period exceeding ten years, the system performance of SSPDs has been drastically improved, and lately excellent detection efficiencies have been realized in practical systems for a wide range of target photon wavelengths. Owing to their advantages such as high system detection efficiency, low dark count rate, and excellent timing jitter, SSPDs have found application in various research fields such as quantum information, quantum optics, optical communication, and also in the life sciences. We summarize the photon detection principle and the current performance status of practical SSPD systems. In addition, we introduce application examples in which SSPDs have been applied.

The impact of intersymbol interference (ISI) on single carrier frequency domain equalization with multiple input multiple output (MIMO-SCFDE) systems is severe. Most existing channel equalization methods fail to solve it completely. In this paper, given the disadvantages of the error propagation and the gap from matched filter bound (MFB), we creatively introduce a decision feedback equalizer with frequency-domain bidirectional noise prediction (DFE-FDBiNP) to tackle intersymbol interference (ISI) in MIMO-SCFDE systems. The equalizer has two-part equalizer, that is the normal mode and the time-reversal mode decision feedback equalization with noise prediction (DFE-NP). Equal-gain combining is used to realize a greatly simplified and low complexity diversity combining. Analysis and simulation results validate the improved performance of the proposed method in quasi-static frequency-selective fading MIMO channel for a typical urban environment.

This paper proposes novel nonlinear precoding for XOR-physical layer network coding (XOR-PNC) to improve the performance of bi-directional MIMO relay systems. The proposed precoder comprises a pre-equalizer and a nonlinear filter, which we also propose in the paper. We theoretically analyze the performance of the XOR-PNC with the proposed nonlinear precoding. As a result, it is shown that the proposed pre-equalizer improves the distribution of the received signals at relays, while the nonlinear precoder not only improves the transmission power efficiency but also simplifies the receiver at the relays. The performance is confirmed by computer simulation. The XOR-PNC with the proposed precoding achieves almost the lower bound in BER performance, which is much better than the amplify-and-forward physical layer network coding (AF-PNC).