For source camera identification, we propose a method to reconstruct the sensor pattern noise map from a size-reduced query image by minimizing an objective function derived from the observation model. Our method can be applied to multiple queries, and can thus be further improved. Experiments demonstrate the superiority of the proposed method over conventional interpolation-based magnification algorithms.

The purpose of this study is to develop an automated scheme of carotid artery calcification (CAC) detection on dental panoramic radiographs (DPRs). The CAC is one of the indices for predicting the risk of arteriosclerosis. First, regions of interest (ROIs) that include carotid arteries are determined on the basis of inflection points of the mandibular contour. Initial CAC candidates are detected by using a grayscale top-hat filter and a simple grayscale thresholding technique. Finally, a rule-based approach and a support vector machine to reduce the number of false positive (FP) findings are applied using features such as area, location, and circularity. A hundred DPRs were used to evaluate the proposed scheme. The sensitivity for the detection of CACs was 90% with 4.3 FPs (80% with 1.9 FPs) per image. Experiments show that our computer-aided detection scheme may be useful to detect CACs.

Scaling up the system size has been the common approach to achieving high performance in parallel computing. However, designing and implementing a large-scale parallel system can be very costly in terms of money and time. When building a target system, it is desirable to initially build a smaller version by using the processing nodes with the same architecture as those in the target system. This allows us to achieve efficient and scalable prediction by using the smaller system to predict the performance of the target system. Such scalability prediction is critical because it enables system designers to evaluate different design alternatives so that a certain performance goal can be successfully achieved. As the de facto standard for writing parallel applications, MPI is widely used in large-scale parallel computing. By categorizing the discrete event simulation methods for MPI programs and analyzing the characteristics of scalability prediction, we propose a novel simulation method, called virtual-actual combined execution-driven (VACED) simulation, to achieve scalable prediction for MPI programs. The basic idea behind is to predict the execution time of an MPI program on a target machine by running it on a smaller system so that we can predict its communication time by virtual simulation and obtain its sequential computation time by actual execution. We introduce a model for the VACED simulation as well as the design and implementation of VACED-SIM, a lightweight simulator based on fine-grained activity and event definitions. We have validated our approach on a sub-system of Tianhe-1A. Our experimental results show that VACED-SIM exhibits higher accuracy and efficiency than MPI-SIM. In particular, for a target system with 1024 cores, the relative errors of VACED-SIM are less than 10% and the slowdowns are close to 1.

In most phrase-based statistical machine translation (SMT) systems, the translation model relies on word alignment, which serves as a constraint for the subsequent building of a phrase table. Word alignment is usually inferred by GIZA++, which implements all the IBM models and HMM model in the framework of Expectation Maximum (EM). In this paper, we present a fully Bayesian inference for word alignment. Different from the EM approach, the Bayesian inference makes use of all possible parameter values rather than estimating a single parameter value, from which we expect a more robust inference. After inferring the word alignment, current SMT systems usually train the phrase table from Viterbi word alignment, which is prone to learn incorrect phrases due to the word alignment mistakes. To overcome this drawback, a new phrase extraction method is proposed based on multiple Gibbs samples from Bayesian inference for word alignment. Empirical results show promising improvements over baselines in alignment quality as well as the translation performance.

Link prediction in social networks, such as friendship networks and coauthorship networks, has recently attracted a great deal of attention. There have been numerous attempts to address the problem of link prediction through diverse approaches. In the present paper, we focused on predicting links in social networks using information flow via active links. The information flow heavily depends on link activeness. The links become active if the interactions happen frequently and recently with respect to the current time. The time stamps of the interactions or links provide vital information for determining the activeness of the links. In the present paper, we introduced a new algorithm, referred to as T_Flow, that captures the important aspects of information flow via active links in social networks. We tested T_Flow with two social network data sets, namely, a data set extracted from Facebook friendship network and a coauthorship network data set extracted from ePrint archives. We compare the link prediction performances of T_Flow with the previous method PropFlow. The results of T_Flow method revealed a notable improvement in link prediction for facebook data and significant improvement in link prediction for coauthorship data.

Lately, access loads on servers are increasing due to larger content size and higher request frequency in content distribution networks. Breadcrumbs (BC), an architecture with guidance information for locating a content cache, is designed to reduce the server load and to form content-oriented network autonomously in cooperation with cached contents over IP network. We also proposed Breadcrumbs+ which solves BC's endless routing loop problem. However, Breadcrumbs takes only a passive approach; BC entries are created only when a content is downloaded and only at routers on the download path but not at any other routers. We expect that active and adaptive control of guidance information with simple complexity improves its performance with keeping scalability. In this paper, we propose Active Breadcrumbs which achieves efficient content retrieval and load-balancing through active and adaptive control of guidance information by cache-nodes themselves. In addition, we show the effectiveness of Active Breadcrumbs through the extensive computer simulation.

This letter investigates the outage performance of a joint transmit and receive antenna selection scheme in an amplify-and-forward two-way relaying system with channel estimation error. A closed-form approximate outage probability expression is derived, based on which the asymptotic outage probability expression is derived to get an insight on system's outage performance at high signal-to-noise (SNR) region. Monte Carlo simulation results are presented to verify the analytical results.

In DHT network, a node can get/put a requested data by only log N look-up steps. However, conventional DHT network only supports single query look-up to search data. From the reason, each node in a DHT network must execute look-up process for each query even if a large number of put and get operations are executed. Therefore, this results in high network load in massive data management such as MapReduce, sensor network, and web information. To address the problem, we propose multiple queries look-up architecture using range information feedback (MARIF). MARIF extends the conventional KBR protocol to supports range information that is a scope of ID space a node keeps. When a source node receives range information from a destination node, the source node checks all queries in the range information and forwards queries matching the range information to the destination node directly. This effectively reduces the number of look-up queries and the network load for the IP network. In addition, MARIF can be implemented into conventional DHT networks and can easily be combined to effective DHT routing algorithms such as Chord, Kademlia, Pastry, and one-hop DHT. In evaluation, we implement MARIF into three DHT networks and compare its performance with that of conventional query bundling mechanisms based on the KBR protocol. The results show that MARIF reduces by up to 40% the total number of forwarding queries to put data compared with other mechanisms. In addition, MARIF saves the number of forwarding queries per look-up process by up to 85% compared to other mechanisms with low bundling overhead.

We propose an accurate and scalable solution to the perspective-n-point problem, referred to as ASPnP. Our main idea is to estimate the orientation and position parameters by directly minimizing a properly defined algebraic error. By using a novel quaternion representation of the rotation, our solution is immune to any parametrization degeneracy. To obtain the global optimum, we use the Grobner basis technique to solve the polynomial system derived from the first-order optimality condition. The main advantages of our proposed solution lie in accuracy and scalability. Extensive experiment results, with both synthetic and real data, demonstrate that our proposed solution has better accuracy than the state-of-the-art noniterative solutions. More importantly, by exploiting vectorization operations, the computational cost of our ASPnP solution is almost constant, independent of the number of point correspondences n in the wide range from 4 to 1000. In our experiment settings, the ASPnP solution takes about 4 milliseconds, thus best suited for real-time applications with a drastically varying number of 3D-to-2D point correspondences.

The 10-gigabit Ethernet passive optical network (10G-EPON) is a promising candidate for the next generation of fiber-to-the-home access systems. In the symmetric 10G-EPON system, the gigabit Ethernet passive optical network (GE-PON) and 10G-EPON will have to co-exist on the same optical network. For this purpose, an optical triplexer (10G-transmitter, 1G-transmitter, and 10G/1G-receiver) for optical line terminal (OLT) transceivers in 10G/1G co-existing EPON systems has been developed. Reducing the size and cost of the optical triplexer has been one of the largest issues in the effort to deploy 10G-EPON systems for practical use. In this paper, we describe a novel small and low-cost dual-rate optical triplexer for use in 10G-EPON applications. By reducing the optical path length by means of a light collection system with a low-magnification long-focus coupling lens, we have successfully miniaturized the optical triplexer for use in 10G-EPON OLT 10-gigabit small form factor pluggable (XFP) transceivers and decreased the number of lenses. A low-cost design of sub-assemblies also contributes to cost reduction. The triplexer's performance complies with IEEE 802.3av specifications.

In this letter, a property of the characteristic matrix of the Rotation Symmetric Boolean Functions (RSBFs) is characterized, and a sufficient and necessary condition for RSBFs being 1st correlation-immune (1-CI for simplicity) is obtained. This property is applied to construct resilient RSBFs of order 1 (1-resilient for simplicity) on pq variables, where p and q are both prime consistently in this letter. The results show that construction and counting of 1-resilient RSBFs on pq variables are equivalent to solving an equation system and counting the solutions. At last, the counting of all 1-resilient RSBFs on pq variables is also proposed.

This study investigated the relationship between human use of automation and their sensitivity to changes in automation and manual performance. In the real world, automation and manual performance change dynamically with changes in the environment. However, a few studies investigated whether changes in automation or manual performance have more effect on whether users choose to use automation. We used two types of experimental tracking tasks in which the participants had to select whether to use automation or conduct manual operation while monitoring the variable performance of automation and manual operation. As a result, we found that there is a mutual relationship between human use of automation and their sensitivity to automation and manual performance changes. Also, users do not react equally to both automation and manual performance changes although they use automation adequately.

This work presents a four-channel headset achieving a 5.1-channel-like hearing experience using a low-complexity head-related transfer function (HRTF) model and a simplified reverberator. The proposed down-mixing architecture enhances the sound localization capability of a headset using the HRTF and by simulating multiple sound reflections in a room using Moorer's reverberator. Since the HRTF has large memory and computation requirements, the common-acoustical-pole and zero (CAPZ) model can be used to reshape the lower-order HRTF model. From a power consumption viewpoint, the CAPZ model reduces computation complexity by approximately 40%. The subjective listening tests in this study shows that the proposed four-channel headset performs much better than stereo headphones. On the other hand, the four-channel headset that can be implemented by off-the-shelf components preserves the privacy with low cost.

Practical, low complexity time of arrival (TOA) estimation method with high accuracy are attractive in ultra wideband (UWB) ranging and localization. In this paper, a generalized maximum likelihood energy detection (GML-ED) ranging method is proposed and implemented. It offers low complexity and can be applied in various environments. An error model is first introduced for TOA accuracy evaluation, by which the optimal integration interval can be determined. Aiming to suppress the significant error created by the false alarm events, multiple pulses are utilized for accuracy promotion at the cost of extra energy consumption. For this reason, an energy efficiency model is also proposed based on the transmitted pulse number. The performance of the analytical research is evaluated and verified through practical experiments in a typical indoor environment.

NAND multi-level cell (MLC) flash memories are widely used due to low cost and high capacity. However, the increased number of levels in MLC results in larger interference and errors. The errors in MLC flash memories tend to be directional and limited-magnitude. Many related works focus on asymmetric errors, but bidirectional errors also occur because of the bidirectional interference and the adjustment of the hard-decision reference voltages. To take advantage of the characteristics, we propose t bidirectional (lu,ld) limited-magnitude error correction codes, which can reduce errors more effectively. The proposed code is systematic, and can correct t bidirectional errors with upward and downward magnitude of lu and ld, respectively. The proposed method is advantageous in that the parity size is reduced, and it has lower bit error rate than conventional error correction codes with the same code rate.

In this letter, we present a fast image/video super resolution framework using edge and nonlocal constraint. The proposed method has three steps. First, we improve the initial estimation using content-adaptive bilateral filtering to strengthen edge. Second, the high resolution image is estimated by using classical back projection method. Third, we use joint content-adaptive nonlocal means filtering to get the final result, and self-similarity structures are obtained by the low resolution image. Furthermore, content-adaptive filtering and fast self-similarity search strategy can effectively reduce computation complexity. The experimental results show the proposed method has good performance with low complexity and can be used for real-time environment.

To establish seamless and highly robust content distribution, we proposed the new concept of Inter-Stream Forward Error Correction (FEC), an efficient data recovery method leveraging several video streams. Our previous research showed that Inter-Stream FEC had significant recovery capability compared with the conventional FEC method under ideal modeling conditions and assumptions. In this paper, we design the Inter-Stream FEC architecture in detail with a view to practical application. The functional requirements for practical feasibility are investigated, such as simplicity and flexibility. Further, the investigation clarifies a challenging problem: the increase in processing delay created by the asynchronous arrival of packets. To solve this problem, we propose a pragmatic parity stream construction method. We implement and evaluate experimentally a prototype system with Inter-Stream FEC. The results demonstrate that the proposed system could achieve high recovery performance in our experimental environment.

The optimization of polarimetric contract enhancement (OPCE) is one of the important problems in radar polarimetry since it provides a substantial benefit for target enhancement. Considering different scattering mechanisms between the desired targets and the undesired targets, Yang et al. extended the OPCE model to the generalized OPCE (GOPCE) problem. Based on a modified GOPCE model and the linear discriminant analysis, a ship detector is proposed in this paper to improve the detection performance for polarimetric Synthetic Aperture Radar (SAR) imagery. In the proposed method, we modify the combination form of the three polarimetric parameters (i.e., the plane scattering similarity parameter, the diplane scattering similarity parameter and the Cloude entropy), then use an optimization function resembling the classical Fisher criterion to optimize the optimal polarization states corresponding to the radar received power and the fusion vector corresponding to the polarimetric parameters. The principle of the optimization detailed in this paper lies in maximizing the difference between the desired targets and sea clutter, and minimizing the clutter variance at the same time. RADARSAT-2 polarimetric SAR data acquired over Tanggu Port (Tianjin, China) on June 23, 2011 are used for validation. The experimental results show that the proposed method improves the contrast of the targets and sea clutter and meanwhile reduces the clutter variance. In comparison to another GOPCE based ship detector and the classical polarimetric whitening filter (PWF), the proposed method shows a better performance for weak targets. In addition, we also use the RADARSAT-2 data acquired over San-Francisco on April 9, 2008 to further demonstrate the improvement of this method for target contrast.

Feature selection is a technique to screen out less important features. Many existing supervised feature selection algorithms use redundancy and relevancy as the main criteria to select features. However, feature interaction, potentially a key characteristic in real-world problems, has not received much attention. As an attempt to take feature interaction into account, we propose 1-LSMI, an 1-regularization based algorithm that maximizes a squared-loss variant of mutual information between selected features and outputs. Numerical results show that 1-LSMI performs well in handling redundancy, detecting non-linear dependency, and considering feature interaction.

Square root-raised-cosine (SRRC) filters are used in many systems for spectrum shaping, which leads to a high peak-to-average power ratio (PAPR). Nevertheless, some applications demand a low PAPR in terms of both the error performance and the strict restriction of the spectrum mask. In this letter, we propose a PAPR reduction method based on the modified active constellation extension for systems using SRRC filters. Results show that the proposed method substantially reduces the PAPR, and therefore it is applicable to satellite communications to improve the power efficiency at the transmitter.