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.

This paper concerns a problem of on-line model parameter estimations for multiple time-delay systems. In order to estimate unknown model parameters from measured state variables, we propose two schemes using Lyapunov's direct method, called parallel and series-parallel model estimators. It is shown through a numerical example that the proposed parallel and series-parallel model estimators can be effective when sufficiently rich inputs are applied.

Aiming to alleviate the visual tracking problem of drift which reduces the abilities of almost all online visual trackers, a robust visual tracker (called CCMM tracker) is proposed with a coupled-classifier based on multiple representative appearance models. The coupled-classifier consists of root and head classifiers based on local sparse representation. The two classifiers collaborate to fulfil a tracking task within the Bayesian-based tracking framework, also to update their templates with a novel mechanism which tries to guarantee an update operation along the “right” orientation. Consequently, the tracker is more powerful in anti-interference. Meanwhile the multiple representative appearance models maintain features of the different submanifolds of the target appearance, which the target exhibited previously. The multiple models cooperatively support the coupled-classifier to recognize the target in challenging cases (such as persistent disturbance, vast change of appearance, and recovery from occlusion) with an effective strategy. The novel tracker proposed in this paper, by explicit inference, can reduce drift and handle frequent and drastic appearance variation of the target with cluttered background, which is demonstrated by the extensive experiments.

We propose a simple and small phase shifter for a beam-steerable base-station antenna. This phase shifter has no metallic heterojunction, and the phase shift is controlled by moving an M-shaped dielectric plate between the strip conductor and the ground plane of a strip line. We derive a design equation from the condition that at the center frequency f0, the reflection coefficient = 0. In this phase shifter, the reflection coefficient becomes minimum at f0 regardless of the movement distance, r, of the dielectric plate, and the relationship between the phase shift and r is linear. These characteristics are verified by performing simulations and measurements. The size of the M-shaped dielectric phase shifter is 0.27λ00.12λ0, where λ0 is the free-space wavelength at f0. The insertion loss is smaller than about 0.2 dB within a fractional bandwidth of 10%, and the phase shift can vary from 0 to about 80 degrees.

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.

This paper proposes the physical architecture of an electric power system with multiple homes. The notion of home is a unit of small-scale power system that includes local energy source, energy storage, load, power conversion circuits, and control systems. An entire power system consists of multiple homes that are interconnected via a distribution network and that are connected to the commercial power grid. The interconnection is autonomously achieved with a recently developed technology of grid-connected inverters. A mathematical model of slow dynamics of the power system is also developed in this paper. The developed model enables the evaluation of steady and transient characteristics of power systems.

Content addressable memory is widely used for fast lookup table data searching, but it often consumes considerable power. Moreover, designing the suitable content addressable memory architecture for a specific application also consumes lots of time, since the behavioral simulation is often done in the transistor level. SystemC is a system-level modeling language and simulation platform, providing high simulation efficiency for hardware software co-design. Unfortunately, SystemC does not provide the function for estimating power dissipation of a structure design. In this paper, a SystemC-based fast content addressable memory power estimation method is presented for estimating the power dissipation of the match-line circuit, the search-line circuit, and the storage cell array of content addressable memory in the early design stage. The mathematical equations and behavioral patterns are used as the inputs of power estimation model. The simulation results based on 10 Mibench benchmarks show that the simulation time of the proposed method is in average 1233 times faster than that of HSPICE simulator with only 3.51% error rate.

In classical routing protocols, geographical distances/locations are typically used as the metric to select the best route, under the assumption that shorter distances exhibit lower energy consumption and nodes within the communication range of the sender can receive packets with a certain success probability. However, in underwater acoustic sensor networks (UASNs), sound propagation in the ocean medium is more complex than that in the air due to many factors, including sound speed variations and the interaction of sound waves with the sea surface and floor, causing the sound rays to bend. Therefore, propagation of sound is anisotropic in water, and may cause a phenomenon called shadow zone where nodes in the communication range of the sender cannot hear any signal. This renders conventional routing protocols no longer energy-efficient. In this paper, we make use of the ray-model to account for the environment-dependent behavior of the underwater channel, re-define nodes' one-hop neighbors based on signal attenuation rather than geographical distance, and design a distributed energy-efficient routing protocol for UASNs. Results show that our ray-model-based routing policy consistently outperforms the shortest path policy, and performs very close to the optimal one in several scenarios.

In this paper, we propose an efficient channel estimation scheme in bi-directional wireless orthogonal frequency division multiplexing (OFDM) relay systems applying analog network coding (ANC). In the relay systems applying ANC, channel separation is needed to estimate each of the bi-directional channels simultaneously from the combined received signal. In the conventional channel estimation schemes, relatively higher-ratio pilots are needed to obtain accurate channels. In contrast, we propose a channel estimation scheme with sparse pilots, while maintaining high accuracy for channel estimation. In the proposed scheme, Walsh codes are inserted as the pilot symbols at both end nodes, and the individual channels are obtained by correlation processing from the combined signals. The improved bit error rate (BER) and throughput performances of the proposed scheme are shown through computer simulations.

A specification for digital cinema systems which deal with movies digitally from production to delivery as well as projection on the screens is recommended by DCI (Digital Cinema Initiative), and the systems based on this specification have already been developed and installed in theaters. The parameters of the systems that play an important role in determining image quality include image resolution, quantization bit depth, color space, gamma characteristics, and data compression methods. This paper comparatively discusses a relation between required bit depth and gamma quantization using both of a human visual system for grayscale images and two color difference models for color images. The required bit depth obtained from a contrast sensitivity function against grayscale images monotonically decreases as the gamma value increases, while it has a minimum value when the gamma is 2.9 to 3.0 from both of the CIE 1976 L* a* b* and CIEDE2000 color difference models. It is also shown that the bit depth derived from the contrast sensitivity function is one bit greater than that derived from the color difference models at the gamma value of 2.6. Moreover, a comparison between the color differences computed with the CIE 1976 L* a* b* and CIEDE2000 leads to a same result from the view point of the required bit depth for digital cinema systems.

Many successful methods for recognizing human action are spatio-temporal interest point (STIP) based methods. Given a test video sequence, for a matching-based method using a voting mechanism, each test STIP casts a vote for each action class based on its mutual information with respect to the respective class, which is measured in terms of class likelihood probability. Therefore, two issues should be addressed to improve the accuracy of action recognition. First, effective STIPs in the training set must be selected as references for accurately estimating probability. Second, discriminative STIPs in the test set must be selected for voting. This work uses ε-nearest neighbors as effective STIPs for estimating the class probability and uses a variance filter for selecting discriminative STIPs. Experimental results verify that the proposed method is more accurate than existing action recognition methods.

In a sign-magnitude representation of binary lattice codevectors, only a few least significant bit-planes are constrained due to the structure of the lattice, while there is no restriction on other more significant bit-planes. Hence, any convenient bit-plane coding method can be used to encode the lattice codevectors, with modification required only for the lattice-defining, least-significant bit-planes. Simple encoding methods for the lattice-defining bit-planes of the D4, RE8, and Barnes-Wall 16-dimensional lattices are described. Simulation results for the encoding of a uniform source show that standard bit-plane coding together with the proposed encoding provide about the same performance as integer lattice vector quantization when the bit-stream is truncated. When the entire bit-stream is fully decoded, the granular gain of the lattice is realized.

In this paper, a stochastic asymptotic stabilization method is proposed for deterministic input-affine control systems, which are randomized by including Gaussian white noises in control inputs. The sufficient condition is derived for the diffusion coefficients so that there exist stochastic control Lyapunov functions for the systems. To illustrate the usefulness of the sufficient condition, the authors propose the stochastic continuous feedback law, which makes the origin of the Brockett integrator become globally asymptotically stable in probability.

This paper shows a virus scanning engine using two-stage matching. In the first stage, a binary CAM emulator quickly detects a part of the virus pattern, while in the second stage, the MPU detects the full length of the virus pattern. The binary CAM emulator is realized by an index generation unit (IGU) based on row-shift decomposition. The proposed system uses two off-chip SRAMs and a small FPGA. Thus, the cost and the power consumption are lower than the TCAM-based system. The system loaded 1,290,617 ClamAV virus patterns. As for the area and throughput, this system outperforms existing two-stage matching systems using FPGAs.

Nowadays, the trend of developing micro-processor with hundreds of cores brings a promising prospect for embedded systems. Realizing a high performance and low power many-core processor is becoming a primary technical challenge. Generally, three major issues required to be resolved includes: 1) realizing efficient massively parallel processing, 2) reducing dynamic power consumption, and 3) improving software productivity. To deal with these issues, we propose a solution to use many low-performance but small and very low-power cores to obtain very high performance, and develop a referential many-core architecture and a program development environment. This paper introduces a many-core architecture named SMYLEref and its prototype system with off-the-shelf FPGA evaluation boards. The initial evaluation results of several SPLASH2 benchmark programs conducted on our developed 128-core platform are also presented and discussed in this paper.

Multichannel MAC protocols with a single control channel in a cognitive radio ad hoc network (CRAN) suffer from the bottleneck problem. So a multichannel MAC protocol that can realize a virtual control channel on all available channels is preferred. Discontiguous-Orthogonal Frequency Division Multiplexing (D-OFDM) enables multiple data to be sent and received on discontiguous multiple channels. In this paper, we propose a new cooperative multichannel MAC (CM-MAC) protocol using D-OFDM in a CRAN. In the proposed CM-MAC protocol, a new approach utilizing multiple discontiguous control channels is presented and a remedy to tackle new collision types by the approach using D-OFDM is provided. The proposed mechanism mitigates the bottleneck problem of the protocol using single control channel, but does not need to share hopping patterns between a sender and a receiver. In addition, cooperative communications with relays reduce the time required to send the data of low-rate secondary users (SUs) by enabling relay SUs to relay the data of source SUs. The proposed CM-MAC protocol is shown to enhance throughput. Analysis and simulations indicate that throughput performance improves compared to the MAC protocol using the split phase control channel (SPCC) approach.

Multi-label classification allows a sample to belong to multiple classes simultaneously, which is often the case in real-world applications such as text categorization and image annotation. In multi-label scenarios, taking into account correlations among multiple labels can boost the classification accuracy. However, this makes classifier training more challenging because handling multiple labels induces a high-dimensional optimization problem. In this paper, we propose a scalable multi-label method based on the least-squares probabilistic classifier. Through experiments, we show the usefulness of our proposed method.

This paper explores the problem of semantic enrichment of mathematical expressions. We formulate this task as the translation of mathematical expressions from presentation markup to content markup. We use MathML, an application of XML, to describe both the structure and content of mathematical notations. We apply a method based on statistical machine translation to extract translation rules automatically. This approach contrasts with previous research, which tends to rely on manually encoded rules. We also introduce segmentation rules used to segment mathematical expressions. Combining segmentation rules and translation rules strengthens the translation system and archives significant improvements over a prior rule-based system.

A selfish routing game is a simple model of selfish behaviors in networks. It is called that Braess's paradox occurs in the selfish routing game if an equilibrium flow achieved by players' selfish behaviors is not the optimal minimum latency flow. In order to make the minimum latency flow a Nash equilibrium, a marginal cost tax has been proposed. Braess graphs have also been proposed to discuss Braess's paradox. In a large population of selfish players, conflicts between purposes of each player and the population causes social dilemmas. In game theory, to resolve the social dilemmas, a capitation tax and/or a subsidy has been introduced, and players' dynamical behaviors have been formulated by replicator dynamics. In this paper, we formulate replicator dynamics in the Braess graphs and investigate stability of the minimum latency flow with and without the marginal cost tax. An additional latency caused by the marginal cost tax is also shown. To resolve the problem of the additional latency, we extend the capitation tax and the subsidy to a state-dependent tax and apply it to the stabilization problem of the minimum latency flow.

With the technology scaling down, leakage power becomes an important part of total power consumption. The relatively large leakage current weakens the energy recovery capability of adiabatic circuits and reduces its superiority, compared with static CMOS circuits in the field of low-power design. In this paper, we rebuild three types of adiabatic circuits (2N2N2P, IPAL and DCPAL) based on FinFET devices to obtain a large leakage power reduction by rationally utilizing the different operating modes of FinFET devices (SG, LP, and IG). A 16-bit adiabatic adder has been investigated to demonstrate the advantages of FinFET adiabatic circuits. The Predictive Technology Model (PTM) is used for 32-nm bulk MOSFET and FinFET devices and all of the simulations are based on HSPICE. The results evince the proposed FinFET adiabatic circuits have a considerable reduction (more than 60% for SG mode FinFET and more than 80% for LP mode FinFET) of power consumption compared with the bulk MOSFET ones. Furthermore, the FinFET adiabatic circuits also have higher limiting frequency of clock source and better noise immunity.