Based on sample-pair refinement and local optimization, this paper proposes a high-accuracy and quick matting algorithm. First, in order to gather foreground/background samples effectively, we shoot rays in hybrid (gradient and uniform) directions. This strategy utilizes the prior knowledge to adjust the directions for effective searching. Second, we refine sample-pairs of pixels by taking into account neighbors'. Both high confidence sample-pairs and usable foreground/background components are utilized and thus more accurate and smoother matting results are achieved. Third, to reduce the computational cost of sample-pair selection in coarse matting, this paper proposes an adaptive sample clustering approach. Most redundant samples are eliminated adaptively, where the computational cost decreases significantly. Finally, we convert fine matting into a de-noising problem, which is optimized by minimizing the observation and state errors iteratively and locally. This leads to less space and time complexity compared with global optimization. Experiments demonstrate that we outperform other state-of-the-art methods in local matting both on accuracy and efficiency.

In this paper, we propose the Perceptual Shape Decomposition (PSD) to detect fingers for a Kinect-based hand gesture recognition system. The PSD is formulated as a discrete optimization problem by removing all negative minima with minimum cost. Experiments show that our PSD is perceptually relevant and robust against distortion and hand variations, and thus improves the recognition system performance.

In this paper, we propose a novel layered scalable- multiple description coding (LS-MDC) which offers the benefits of both scalable video coding and multiple description coding for robust video transmission over packet lossy networks. In the proposed LS-MDC method, multiple descriptions including base layer, enhancement layers, and their corresponding FEC parity data are allocated into two network paths of a path diversity system. Unlike the conventional approaches, the source base/enhancement data and their own parities in the proposed method are not transmitted together but are transferred over different paths. Therefore, the effect of burst packet losses can be effectively reduced for the descriptions. Furthermore, in order to minimize the overall distortion for the LS-MDC system and exploit the benefits of path diversity, we also propose an optimal rate allocation scheme that can adaptively control the transmission rate as well as the channel coding rate for media senders. Experiments show that the proposed method provides much better peak signal-to-noise ratio (PSNR) than conventional MDC techniques.

This paper introduces two schemes to put the decoding of the convolutional network code (CNC) into practice, which are named the Intermittent Packet Transmission Scheme (IPTS) and the Redundancy Packet Transmission Scheme (RPTS). According to the decoding formula of the sink nodes, we can see that, at the time k+δ in order to decode the source packet generated at time k, the sink node should know all the source packets generated before k-1. This is impractical. The two schemes we devised make it unnecessary. A construction algorithm is also given about the RPTS networks. For the two schemes, we analyze the strengths and weaknesses and point out their implemented condition.

This letter introduces innovative VAD based on horizontal spectral entropy with long-span of time (HSELT) feature sets to improve mobile ASR performance in low signal-to-noise ratio (SNR) conditions. Since the signal characteristics of nonstationary noise change with time, we need long-term information of the noisy speech signal to define a more robust decision rule yielding high accuracy. We find that HSELT measures can horizontally enhance the transition between speech and non-speech segments. Based on this finding, we use the HSELT measures to achieve high accuracy for detecting speech signal form various stationary and nonstationary noises.

This paper introduces open-wire fault-resilient multiple-valued codes for reliable asynchronous point-to-point global communication links. In the proposed encoding, two communication modules assign complementary codewords that change between two valid states without an open-wire fault. Under an open-wire fault, at each module, the codewords don't reach to one of the two valid states and remains as “invalid” states. The detection of the invalid states makes it possible to stop sending wrong codewords caused by an open-wire fault. The detectability of the open-wire fault based on the proposed encoding is proven for m-of-n codes. The proposed code used in the multiple-valued asynchronous global communication link is capable of detecting a single open-wire fault with 3.08-times higher coding efficiency compared with a conventional multiple-valued code used in a triple-modular redundancy (TMR) link that detects an open-wire fault under the same dynamic range of logical values.

In recent years, the growing density and complexity of VLSIs have led to an increase in the numbers of test patterns and fault models. Test patterns used in VLSI testing are required to provide high quality and low cost. Don't care (X) identification techniques and X-filling techniques are methods to satisfy these requirements. However, conventional X-identification techniques are less effective for application-specific fields such as test compaction because the X-bits concentrate on particular primary inputs and pseudo primary inputs. In this paper, we propose a don't care identification method for test compaction. The experimental results for ITC'99 and ISCAS'89 benchmark circuits show that a given test set can be efficiently compacted by the proposed method.

We propose a low-overhead fault-secure parallel prefix adder. We duplicate carry bits for checking purposes. Only one half of normal carry bits are compared with the corresponding redundant carry bits, and the hardware overhead of the adder is low. For concurrent error detection, we also predict the parity of the result. The adder uses parity-based error detection and it has high compatibility with systems that have parity-based error detection. We can implement various fault-secure parallel prefix adders such as Sklansky adder, Brent-Kung adder, Han-Carlson adder, and Kogge-Stone adder. The area overhead of the proposed adder is about 15% lower than that of a previously proposed adder that compares all the carry bits.

Spectrum sensing is one of the main functions in cognitive radio networks. To improve the sensing performance and increase spectrum efficiency, a number of cooperative spectrum sensing methods have been proposed. However, most of these methods focused on a single-channel environment. In this letter, we present a novel cooperative spectrum sensing method based on cooperator selection in a multi-channel cognitive radio network. Using reinforcement learning, a cognitive radio user can select reliable and robust cooperators, without any a priori knowledge. Using the proposed method, a cognitive radio user can achieve better sensing capability and overcome performance degradation problems due to malicious users or erratic user behavior. Numerical results show that the proposed method can achieve excellent performance.

A method to estimate sound source orientation in a reverberant room using a microphone array is proposed. We extend the conventional modeling of a room transfer function based on the image method in order to take into account the directivity of a sound source. With this extension, a transfer function between a sound source and a listener (or a microphone) is described by the superposition of transfer functions from each image source to the listener multiplied by the source directivity; thus, the sound source orientation can be estimated by analyzing how the image sources are distributed (power distribution of image sources) from observed signals. We applied eigenvalue analysis to the spatial correlation matrix of the microphone array observation to obtain the power distribution of image sources. Bsed on the assumption that the spatial correlation matrix for each set of source position and orientation is known a priori, the variation of the eigenspace can be modeled. By comparing the eigenspace of observed signals and that of pre-learned models, we estimated the sound source orientation. Through experiments using seven microphones, the sound source orientation was estimated with high accuracy by increasing the reverberation time of a room.

In this paper, a method is introduced that can detect the number of incident signals (NIS) even there are fewer antennas than NIS. Previous works on NIS detection methods assumed that the number of antennas always exceeded NIS. In the DOA estimation field, the DOA estimation is possible, even if NIS exceeds the number of antennas, by extending the degrees of freedom of array (DOFA) using a modified array configuration, such as a nested array (NA). The information of NIS is required in advance to accurately estimate DOA, however, it has not been investigated deeply when NIS is larger than the number of antennas. In this paper, a NIS detection method based on the DOFA extending process using NA is proposed. One of the important issues in NIS detection is the detection metric. As one of the simple metrics, the ratio of adjacent eigenvalues (RAE) has been used. However, the direct application of RAE may not achieve adequate NIS detection performance. Therefore, we propose a metric based on the modified ratio of adjacent eigenvalues (MRAE) avoids the issue of RAE. Numerical results show that the metric based on MRAE can achieve proper NIS detection performance even if NIS is larger than the number of antennas.

The Log-structured File System (LFS) transforms random writes to a huge sequential one to provide superior write performance on storage devices. However, LFS inherently suffers from overhead incurred by cleaning segments. Specifically, when file system utilization is high and the system is busy, write performance of LFS degenerates significantly due to high cleaning cost. Also, in the newer flash memory based SSD storage devices, cleaning leads to reduced SSD lifetime as it incurs more writes. In this paper, we propose an enhancement to the original LFS to alleviate the performance degeneration due to cleaning when the system is busy. The new scheme, which we call Slack Space Recycling (SSR), allows LFS to delay on-demand cleaning during busy hours such that cleaning may be done when the load is much lighter. Specifically, it writes modified data directly to invalid areas (slack space) of used segments instead of cleaning on-demand, pushing back cleaning for later. SSR also has the added benefit of increasing the lifetime of the now popular SSD storage devices. We implement the new SSR-LFS file system in Linux and perform a large set of experiments. The results of these experiments show that the SSR scheme significantly improves performance of LFS for a wide range of storage utilization settings and that the lifetime of SSDs is extended considerably.

As a network evolves following initial deployment, its service functions remain diversified through the openness of the network functions. This indicates that appropriate simplification of the service functions is essential if the evolving network is to achieve the required scalability of service processing and service management. While the screening of service functions is basically performed by network users and the market, several service functions will be automatically simplified based on the growth of the evolving network. This paper verifies the simplification of service functions resulting from the evolution of the network itself. First, the principles that serve as the basis for simplifying the service functions are explained using several practical examples. Next, a simulation model is proposed to verify the simplification of service functions in terms of the priority control function for path routing and load balancing among multiple paths. From the results of the simulation, this study clarifies that the anticipated simplification of service functions is actually realizable and the service performance requirements can be reduced as the network evolves after deployment. When the simplification of service functions can improve network quality, it accelerates the evolution of the network and increases the operator's revenue.

Test power has become a critical issue, especially for low-power devices with deeply optimized functional power profiles. Particularly, excessive capture power in at-speed scan testing may cause timing failures that result in test-induced yield loss. This has made capture-safety checking mandatory for test vectors. However, previous capture-safety checking metrics suffer from inadequate accuracy since they ignore the time relations among different transitions caused by a test vector in a circuit. This paper presents a novel metric called the Transition-Time-Relation-based (TTR) metric which takes transition time relations into consideration in capture-safety checking. Detailed analysis done on an industrial circuit has demonstrated the advantages of the TTR metric. Capture-safety checking with the TTR metric greatly improves the accuracy of test vector sign-off and low-capture-power test generation.

We experimentally investigate and analyze faults in optical fiber connections with refractive index matching material that have incorrectly cleaved fiber ends. We explain that incorrectly cleaved fiber ends, which are not ideal because they are uneven and not perpendicular to the fiber axis, are caused by defective optical fiber cleavers. We discover that the optical performance of field installable connections using incorrectly cleaved fiber ends might change greatly. We also infer that the significant change in insertion and return losses might be attributed to partially air-filled gaps by using scatter diagrams of measured insertion and return losses. Our experiment results reveal that the optical performance might deteriorate to more than 40dB in terms of insertion loss and less than 30dB in terms of return loss.

In this paper, we propose a hybrid fuzzy geometric active contour method, which embeds the spatial fuzzy clustering into the evolution of geometric active contour. In every iteration, the evolving curve works as a spatial constraint on the fuzzy clustering, and the clustering result is utilized to construct the fuzzy region force. On one hand, the fuzzy region force provides a powerful capability to avoid the leakages at weak boundaries and enhances the robustness to various noises. On the other hand, the local information obtained from the gradient feature map contributes to locating the object boundaries accurately and improves the performance on the images with heterogeneous foreground or background. Experimental results on synthetic and real images have shown that our model can precisely extract object boundaries and perform better than the existing representative hybrid active contour approaches.

This paper reports an advanced millimeter-wave radar system to enable detection of vehicles and pedestrians in wide areas around the radar site such as an intersection. We focus on a pulse coding scheme using complementary codes to reduce range sidelobe for discriminating vehicles from pedestrians with high accuracy. In order to suppress sidelobe increase created by RF circuit imperfections, a π/2 shift pulse modulation method with a complementary code pair cycle is presented. Moreover, in order to improve the angular resolution, a high-resolution direction of arrival estimation involving Tx beam scanning is presented. Experiments on a prototype confirm its range sidelobe suppression exceeds 40dB and its angular resolution is 5° for two human's separation at the distance of about 10m in an anechoic chamber. In a trial intersection experiment, a pedestrian detection rate of 95% was achieved at the false alarm rate of 10% in the range from 5m to 40m. The results prove the system's feasibility for future automotive safety application.

This paper investigates potential to improve fault-detection coverage by means of on-chip redundancy. The international standard on functional safety, namely, IEC61508 Ed. 2.0 Part 2 Annex E.3 prescribes the upper bound of βIC (common cause failure (CCF) ratio to all failures) is 0.25 to satisfy frequency upper bound of dangerous failure in the safety function for SIL (Safety Integrated Level) 3. On the other hand, this paper argues that the βIC does not necessarily have to be less than 0.25 for SIL 3, and that the upper bound of βIC can be determined depending on failure rate λ and CCF detection coverage. In other words, the frequency upper bound of dangerous failure for SIL3 can also be satisfied with βIC higher than 0.25 if the failure rate λ is lower than 400[fit]. Moreover, the paper shows that on-chip redundancy has potential to satisfy SIL 4 requirement; the frequency upper bound of dangerous failure for SIL4 can be satisfied with feasible ranges of βIC, λ and CCF coverage which can be realized by redundant code.

A mixed storage-type design using flip-flops and latches (FF/latch-based design) has advantages on such as area and power compared to single storage-type design (only flip-flops or latches). Considering FF/latch-based design at high-level synthesis is necessary, because resource binding process significantly affects the quality of resulting circuits. One of the fundamental aspects in FF/latch-based design is that different resource binding solutions could lead to the different numbers of latch-replacable registers. Therefore, as a first step, this paper addresses a datapath design problem in which resource binding and selecting storage-types of registers are simultaneously optimized for datapath area minimization (i.e., latch replacement maximization). An efficient algorithm based on the compatibility path decomposition and an integer linear programming-based exact approach are presented. Experiments confirm the effectiveness of the proposed approaches.

Comparable Corpora are valuable resources for many NLP applications, and extensive research has been done on information mining based on comparable corpora in recent years. While there are not enough large-scale available public comparable corpora at present, this paper presents a bi-directional CLIR-based method for creating comparable corpora from two independent news collections in different languages. The original Chinese document collections and English documents collections are crawled from XinHuaNet respectively and formatted in a consistent manner. For each document from the two collections, the best query keywords are extracted to represent the essential content of the document, and then the keywords are translated into the language of the other collection. The translated queries are run against the collection in the same language to pick up the candidate documents in the other language and candidates are aligned based on their publication dates and the similarity scores. Results show that our approach significantly outperforms previous approaches to the construction of Chinese-English comparable corpora.