This paper provides a method based on electromagnetic (EM) analysis to predict conducted currents in the bulk current injection (BCI) test system for automotive components. The BCI test system is comprised of an injection probe, equipment under test (EUT), line impedance stabilization networks (LISNs), wires and an electric load. All components are modeled in full-wave EM analysis. The EM model of the injection probe enables us to handle multi wires. By using the transmission line theory, the BCI setup model is divided into several parts in order to reduce the calculation time. The proposed method is applied to an actual BCI setup of an automotive component and the simulated common mode currents at the input terminals of EUT have a good accuracy in the frequency range of 1-400MHz. The model separation reduces the calculation time to only several hours.

In this paper, VLSI architecture design of unified motion vector (MV) and boundary strength (BS) parameter decoder (PDec) for 8K UHDTV HEVC decoder is presented. The adoption of new coding tools in PDec, such as Advanced Motion Vector Prediction (AMVP), increases the VLSI hardware realization overhead and memory bandwidth requirement, especially for 8K UHDTV application. We propose four techniques for these challenges. Firstly, this work unifies MV and BS parameter decoders for line buffer memory sharing. Secondly, to support high throughput, we propose the top-level CU-adaptive pipeline scheme by trading off between implementation complexity and performance. Thirdly, PDec process engine with optimizations is adopted for 43.2k area reduction. Finally, PU-based coding scheme is proposed for 30% DRAM bandwidth reduction. In 90nm process, our design costs 93.3k logic gates with 23.0kB line buffer. The proposed architecture can support real-time decoding for 7680x4320@60fps application at 249MHz in the worst case.

A cascaded video denoising method based on frame averaging is proposed in this paper. A novel segmentation approach using intensity and structure tensor is used for change compensation, which can effectively suppress noise while preserving the structure of an image. The cascaded framework solves the problem of noise residual caused by single-frame averaging. The classical Wiener filter is used for spatial denoising in changing areas. Our algorithm works in real-time on an FPGA, since it does not involve future frames. Experiments on standard grayscale videos for various noise levels demonstrate that the proposed method is competitive with current state-of-the-art video denoising algorithms on both peak signal-to-noise ratio and structural similarity evaluations, particularly when dealing with large-scale noise.

Barrel distortion is a critical problem that can hinder the successful application of wide-angle cameras. This letter presents an implementation method for fast correction of the barrel distortion. In the proposed method, the required scaling factor is obtained by interpolating a mapping polynomial with a non-uniform spline instead of calculating it directly, which reduces the number of computations required for the distortion correction. This reduction in the number of computations leads to faster correction while maintaining quality: when compared to the conventional method, the reduction ratio of the correction time is about 89%, and the correction quality is 35.3 dB in terms of the average peak signal-to-noise ratio.

A feedback vertex set F of an undirected graph G is a vertex subset of G whose removal results in a forest. Such a set F is said to be independent if F forms an independent set of G. In this paper, we study the problem of finding an independent feedback vertex set of a given graph with the minimum number of vertices, from the viewpoint of graph classes. This problem is NP-hard even for planar bipartite graphs of maximum degree four. However, we show that the problem is solvable in linear time for graphs having tree-like structures, more specifically, for bounded treewidth graphs, chordal graphs and cographs. We then give a fixed-parameter algorithm for planar graphs when parameterized by the solution size. Such a fixed-parameter algorithm is already known for general graphs, but our algorithm is exponentially faster than the known one.

Assume that Alice, Bob, and Carol, each of whom privately holds a one-bit input, want to learn the output of some Boolean function, say the majority function, of their inputs without revealing more of their own secret inputs than necessary. In this paper, we show that such a secure three-input function evaluation can be performed with a deck of real cards; specifically, the three players can learn only the output of the function using eight physical cards — four black and four red cards — with identical backs.

Developing a practical and accurate statistical parser for low-resourced languages is a hard problem, because it requires large-scale treebanks, which are expensive and labor-intensive to build from scratch. Unsupervised grammar induction theoretically offers a way to overcome this hurdle by learning hidden syntactic structures from raw text automatically. The accuracy of grammar induction is still impractically low because frequent collocations of non-linguistically associable units are commonly found, resulting in dependency attachment errors. We introduce a novel approach to building a statistical parser for low-resourced languages by using language parameters as a guide for grammar induction. The intuition of this paper is: most dependency attachment errors are frequently used word orders which can be captured by a small prescribed set of linguistic constraints, while the rest of the language can be learned statistically by grammar induction. We then show that covering the most frequent grammar rules via our language parameters has a strong impact on the parsing accuracy in 12 languages.

The IEEE 802.11 wireless LAN (WLAN) is based on carrier sense multiple access with collision avoidance (CSMA/CA) protocol. CSMA/CA uses a backoff mechanism to avoid collisions among stations (STAs). One disadvantage of backoff mechanisms is that STAs must wait for some period of time before transmission, which degrades spectral efficiency. Moreover, a backoff algorithm cannot completely avoid collisions. We have proposed a novel medium access control (MAC) scheme called the visual recognition-based medium access control (VRMAC) scheme, which uses an LED-camera communication technique. STAs send media-access request messages by blinking their LEDs in VRMAC scheme. An access point (AP) receives the messages via its camera, and then allocates transmission opportunities to the STAs by transmitting control frames. Since the transmission rate of the LED-camera communication is lower than WLAN transmission, the delay of access requesting causes and it could decrease the system throughput of the VRMAC system based WLAN. We reveal the effect of the delay for TCP flows and propose enhanced access procedures to eliminate the effect of the delay. Our simulation results demonstrate that VRMAC scheme increases the system throughput in UDP and TCP traffic. Moreover, the scenario-based evaluations reveal that VRMAC scheme also decreases the session delay which is a metric of quality of experience (QoE) for TCP applications.

Recently, Hadoop has attracted much attention from engineers and researchers as an emerging and effective framework for Big Data. HDFS (Hadoop Distributed File System) can manage a huge amount of data with high performance and reliability using only commodity hardware. However, HDFS requires a single master node, called a NameNode, to manage the entire namespace (or all the i-nodes) of a file system. This causes the SPOF (Single Point Of Failure) problem because the file system becomes inaccessible when the NameNode fails. This also causes a bottleneck of efficiency since all the access requests to the file system have to contact the NameNode. Hadoop 2.0 resolves the SPOF problem by introducing manual failover based on two NameNodes, Active and Standby. However, it still has the efficiency bottleneck problem since all the access requests have to contact the Active in ordinary executions. It may also lose the advantage of using commodity hardware since the two NameNodes have to share a highly reliable sophisticated storage. In this paper, we propose a new HDFS architecture to resolve all the problems mentioned above.

It is well-known that program readability is important for maintenance tasks. Method names are important identifiers for program readability because they are used for understanding the behavior of methods without reading a part of the program. Although developers can create a method name by arbitrarily choosing a verb and objects, the names are expected to represent the behavior consistently. However, it is not easy for developers to choose verbs and objects consistently since each developer may have a different notion of a suitable lexicon for method names. In this paper, we propose a technique to recommend candidate verbs for a method name so that developers can use various verbs consistently. We recommend candidate verbs likely to be used as a part of a method name, using association rules extracted from existing methods. To evaluate our technique, we have extracted rules from 445 open source projects written in Java and confirmed the accuracy of our approach by applying the extracted rules to several open source applications. As a result, we found that 84.9% of the considered methods in four projects are recommended the existing verb. Moreover, we found that 73.2% of the actual renamed methods in six projects are recommended the correct verb.

A precise measurement of Cosmic Microwave Background (CMB) provides us rich information about the universe. In particular, its asymmetric polarization patterns, $B$-modes, are smoking gun signature of inflationary universe. Magnitude of the $B$-modes is order of 10,nK. Its measurement requires a high sensitive millimeter-wave telescope with a large number of superconducting detectors on its focal plane. Microwave Kinetic Inductance Detector (MKID) is appropriate detector for this purpose. MKID camera has been developed in cooperation of National Astronomical Observatory of Japan (NAOJ), Institute of Physical and Chemical Research (RIKEN), High Energy Accelerator Research Organization (KEK), and Okayama University. Our developments of MKID include: fabrication of high-quality superconducting film; optical components for a camera use; and readout electronics. For performance evaluation of total integrated system of our MKID camera, a calibration system was also developed. The system was incorporated in a 0.1 K dilution refrigerator with modulated polarization source. These developed technologies are applicable to other types of detectors.

Compressive sensing (CS) exploits the sparsity or compressibility of signals to recover themselves from a small set of nonadaptive, linear measurements. The number of measurements is much smaller than Nyquist-rate, thus signal recovery is achieved at relatively expense. Thus, many signal processing problems which do not require exact signal recovery have attracted considerable attention recently. In this paper, we establish a framework for parameter estimation of a signal corrupted by additive colored Gaussian noise (ACGN) based on compressive measurements. We also derive the Cramer-Rao lower bound (CRB) for the frequency estimation problems in compressive domain and prove some useful properties of the CRB under different compressive measurements. Finally, we show that the theoretical conclusions are along with experimental results.

Secure sets and defensive alliances in graphs are studied. They are sets of vertices that are safe in some senses. In this paper, we first present a fixed-parameter algorithm for finding a small secure set, whose running time is much faster than the previously known one. We then present improved bound on the smallest sizes of defensive alliances and secure sets for hypercubes. These results settle some open problems paused recently.

How to retrieve the closest content from an in-network cache is one of the most important issues in Information-Centric Networking (ICN). This paper proposes a novel content discovery scheme called Local Tree Hunting (LTH). By adding branch-cast functionality to a local tree for content requests to a Content-Centric Network (CCN) response node, the discovery area for caching nodes expands. Since the location of such a branch-casting node moves closer to the request node when the content is more widely cached, the discovery range, i.e. the branch size of the local tree, becomes smaller. Thus, the discovery area is autonomously adjusted depending on the content dissemination. With this feature, LTH is able to find the “almost true closest” caching node without checking all the caching nodes in the in-network cache. The performance analysis employed in Zipf's law content distribution model and which uses the Least Recently Used eviction rule shows the superiority of LTH with respect to identifying the almost exact closest cache.

A new technology for video frame rate up-conversion (FRUC) is presented by combining a median filter and motion estimation (ME) with an occlusion detection (OD) method. First, ME is performed to obtain a motion vector. Then, the OD method is used to refine the MV in the occlusion region. When occlusion occurs, median filtering is applied. Otherwise, bidirectional motion compensated interpolation (BDMC) is applied to create the interpolated frames. The experimental results show that the proposed algorithm provides better performance than the conventional approach. The average gain in the PSNR (Peak Signal to Noise Ratio) is always better than the other methods in the Full HD test sequences.

We previously proposed an inaudible non-blind digital-audio watermarking approach based on cochlear delay (CD) characteristics. There are, however, three remaining issues with regard to blind-detectability, frame synchronization related to confidentiality, and reversibility. We attempted to solve these issues in developing the proposed approach by taking blind-detectability and reversibility of audio watermarking into consideration. Frame synchronization was also incorporated into the proposed approach to improve confidentiality. We evaluated inaudibility, robustness, and reversibility with the new approach by carrying out three objective tests (PEAQ, LSD, and bit-detection or SNR) and six robustness tests. The results revealed that inaudible, robust, blindly-detectable, and semi-reversible watermarking based on CD could be accomplished.

Network traffic load usually differs significantly at different times of a day due to users' different time-preference. Network congestion may happen in traffic peak times. In order to prevent this from happening, network service providers (NSPs) can either over-provision capacity for demand at peak times of the day, or use dynamic time-dependent pricing (TDP) scheme to reduce the demand at traffic peak times. Since over-provisioning network capacity is costly, many researchers have proposed TDP schemes to control congestion as well as to improve the revenue of NSPs. To the best of our knowledge, all the studies on TDP schemes consider only the monopoly or duopoly NSP case. In our previous work, the duopoly NSP case has been studied with the assumption that each NSP has complete information of quality of service (QoS) of the other NSP. In this paper, an oligopoly NSP case is studied. NSPs try to maximize their overall revenue by setting time-dependent price, while users choose NSPs by considering their own time preference, congestion status in the networks and the price set by the NSPs. The interactions among NSPs are modeled as an oligopoly Bertrand game. Firstly, assuming that each NSP has complete information of QoS of all NSPs, a unique Nash equilibrium of the game is established under the assumption that users' valuation of QoS is uniformly distributed. Secondly, the assumption of complete information of QoS of all NSPs is relaxed, and a learning algorithm is proposed for NSPs to achieve the Nash equilibrium of the game. Analytical and experimental results show that NSPs can benefit from TDP scheme, however, not only the competition effect but also the incomplete information among NSPs causes revenue loss for NSPs under the TDP scheme.

For digital forensic investigations, the proposed scheme verifies the integrity of video contents in legacy surveillance camera systems with no built-in integrity protection. The scheme exploits video frames remaining in slack space of storage media, instead of timestamp information vulnerable to tampering. The scheme is applied to integrity verification of video contents formatted with AVI or MP4 files in automobile blackboxes.

The Boolean network can be used as a mathematical model for gene regulatory networks. An attractor, which is a state of a Boolean network repeating itself periodically, can represent a stable stage of a gene regulatory network. It is known that the problem of finding an attractor of the shortest period is NP-hard. In this article, we give a fixed-parameter algorithm for detecting a singleton attractor (SA) for a Boolean network that has only AND and OR Boolean functions of literals and has bounded treewidth k. The algorithm is further extended to detect an SA for a constant-depth nested canalyzing Boolean network with bounded treewidth. We also prove the fixed-parameter intractability of the detection of an SA for a general Boolean network with bounded treewidth.

We considered the oxygen diffusivity around a conductive filament of resistive switching oxides, with the aim of designing material appropriate for highly reliable non-volatile memory. Both theoretical and experimental analyses were performed for this consideration. The theoretically obtained oxygen chemical potential difference, which works as a driving force for diffusion, significantly depends on a material. Then, we experimentally confirmed that the oxygen diffusion behaviors vary greatly depending on the chemical potential differences.