The percentage of pedestrian deaths in traffic accidents is on the rise in Japan. In recent years, there have been calls for measures to be introduced to protect vulnerable road users such as pedestrians and cyclists. In this study, a method to detect and track pedestrians using an in-vehicle camera is presented. We improve the technology of detecting pedestrians by using the highly accurate images obtained with a monocular camera. In the detection step, we employ ECoHOG as the feature descriptor; it accumulates the integrated gradient intensities. In the tracking step, we apply an effective motion model using optical flow and the proposed feature descriptor ECoHOG in a tracking-by-detection framework. These techniques were verified using images captured on real roads.

In this letter, we propose an energy-aware source routing protocol for maximizing the network lifetime in mobile ad hoc networks. We define a new routing cost by considering both transmit and receive power consumption and remaining battery level in each node simultaneously and present an efficient route discovery procedure to investigate the proposed routing cost. Intensive simulation verifies that the proposed routing protocol has similar performance to the conventional routing protocols in terms of the number of transmission hops, transmission rate, and energy consumption while significantly improving the performance with respect to network lifetime.

We propose a lightweight scheme for fault diagnosis in time-triggered (TT) systems. An existing scheme is preferable in its capability but incurs computation time that can be prohibitively large for some real-time systems, such as automotive control systems. Our proposed scheme, which we call voting sharing, can substantially reduce the computation time by sharing the diagnosis result obtained by each node with all nodes in the system. We clarify the properties of the voting sharing scheme with respect to fault tolerance and show some experimental results.

Lane detection plays an important role in Driver Assistance Systems and Autonomous Vehicle System. In this paper, we propose a parallel-snake model combined with balloon force for lane detection. Parallel-snake is defined as two open active contours with parallel constrain. The lane boundaries on the left and right sides are assumed as parallel curves, parallel-snake is deformed to estimate these two boundaries. As lane regions between left and right boundaries usually have low gradient, snake will lose external force on these regions. Furthermore, inspired by balloon active contour model, the balloon force is introduced into parallel-snake to expand two parallel curves from center of road to the left and right lane boundaries. Different from closed active contour, stretching force is adopted to prevent the head and tail of snake from converging together. The experimental results on three different datasets show that parallel-snake model can work well on images with shadows and handle the lane with broken boundaries as the parallel property.

This paper reports the use of haptic augmented reality in breast tumor palpation. In general, lumps in the breast are stiffer than surrounding tissues, allowing us to haptically detect them through self-palpation. The goal of the study is to assist self-palpation of lumps by haptically augmenting stiffness around lumps. The key steps are to estimate non-linear stiffness of normal tissues in the offline preprocessing step, detect areas that show abnormally stiffer responses, and amplify the difference in stiffness through a haptic augmented reality interface. The performance of the system was evaluated in a user-study, demonstrating the potential of the system.

The conventional covariance matrix technique based subspace methods, such as the 2-D Capon algorithm and computationally efficient ESPRIT-type algorithms, are invalid with a single snapshot in a bistatic MIMO radar. A novel matrix pencil method is proposed for the direction of departures (DODs) and direction of arrivals estimation (DOAs) estimation. The proposed method constructs an enhanced matrix from the direct sampled data, and then utilizes the matrix pencil approach to estimate DOAs and DODs, which are paired automatically. The proposed method is able to provide favorable and unambiguous angle estimation performance with a single snapshot. Simulation results are presented to verify the effectiveness of the proposed method.

Workflow nets are a standard way for modeling and analyzing workflows. There are two aspects in a workflow: definition and instance. In form of workflow nets, a workflow definition and a workflow instance are respectively represented as a net structure and a marking. The correctness of the workflow definition can be checked by using a workflow nets' property, called soundness. On the other hand, the correctness of the workflow instance can be checked by using a Petri nets' well-known property, called reachability. The reachability problem is known to be intractable. In this paper, we have shown that the reachability problem for (i) sound extended free-choice workflow nets with a marking representing one workflow instance or (ii) acyclic well-structured workflow nets with a marking representing one or more workflow instances can be solved in polynomial time.

As the use of information technology (IT) is explosively spreading, reducing the power consumption of IT devices such as servers has become an important social challenge. Nevertheless, while the efficiency of the power supply modules integrated into computers has recently seen significant improvements, their overall efficiency generally depends on load rates. This is especially true under low power load conditions, where it is known that efficiency decreases drastically. Recently, power-saving techniques that work by controlling the power module configuration under low power load conditions have been considered. Based on such techniques, further efficiency improvements can be expected by an adaptive efficiency controls which interlocks the real-time data processing load status with the power supply configuration control. In this study, the performance counters built into the processor of a computer are used to predict power load variations and an equation that predicts the power consumption levels is defined. In a server application experiment utilizing prototype computer hardware and regression analysis, it is validated that the equation could precisely predict processor power consumption. The evaluation shows that significant power supply efficiency improvements could be achieved especially for light load condition. The dependency of the efficiency improvement and operation period is investigated and preferable time scale of the adaptive control is proposed.

This paper summarizes the current status of regulations, standardization efforts and trials around the world regarding white space (WS) communications, especially television band WS (TVWS). After defining WS communication systems configurations and function and the categories of white space database, the TVWS regulations in United States, United Kingdom, and Japan are summarized. Then regarding status of standardization for TVWS devices, IEEE 802 and IEEE 1900 standards are summarized. Finally ongoing pilot projects and trials of WS communications in the world are summarized, and trends and future direction of research on WS communication systems are summarized.

Cognitive Radio (CR) is aimed at increasing the efficiency of spectrum utilization by allowing unlicensed users to access, in an opportunistic and non-interfering manner, some licensed bands temporarily and/or spatially unoccupied by the licensed users. The analysis of CR systems usually requires the spectral activity of the licensed system to be represented and characterized in a simple and tractable, yet accurate manner, which is accomplished by means of spectrum models. In order to guarantee the realism and accuracy of such models, the use of empirical spectrum occupancy data is essential. In this context, this paper explains the complete process of spectrum modeling, from the realization of field measurements to the obtainment of the final validated model, and highlights the main relevant aspects to be taken into account when developing spectrum usage models for their application in the context of the CR technology.

We developed a device to measure gaze and hand movement in a natural setting such as while reading a book on a train or bus. We examined what kind of cooperation exists among the head, eye and hand movements while subjects were reading a book held in the hand.

In this paper, we propose a robust speech/music classification algorithm to improve the performance of speech/music classification in the selectable mode vocoder (SMV) of 3GPP2 using deep belief networks (DBNs), which is a powerful hierarchical generative model for feature extraction and can determine the underlying discriminative characteristic of the extracted features. The six feature vectors selected from the relevant parameters of the SMV are applied to the visible layer in the proposed DBN-based method. The performance of the proposed algorithm is evaluated using the detection accuracy and error probability of speech and music for various music genres. The proposed algorithm yields better results when compared with the original SMV method and support vector machine (SVM) based method.

We have designed a novel fiber-optic light concentrator with scattering layers and evaluated the light concentration characteristics by ray-trace simulations as functions of the parameters of the incident light angle and wavelength, as well as the waveguide structure. Unlike well-known luminescent solar concentrators, in our models, illuminating light is directly captured through the proposed waveguide structure. The optical efficiency in our fiber-optic models is remarkably improved in long-length regions compared with that in simple slab waveguides. In addition, the waveguide length required to effectively collect light is extended to 300mm and 1.5m for optical fibers with 1- and 10-mm core diameters, respectively, which are ten times longer than those in slab waveguides with an equivalent scale. Because of the cylindrical structure of optical fibers, we have also evaluated the sensitivity of our models to surrounding light. Consequently, an obvious directional property containing single or three peaks of the sensitivity is clarified, and their widths can be tuned by changing the width of the scattering parts. These results suggest that our models are suited for sensor devices such as optical receiving antennas, rather than simple light concentrators. Finally, we model a fiber-optic probe as an application and evaluate the light concentration characteristics when the concentrator is serially concatenated with a normal optical fiber.

We present the concept of an on-line electric vehicle (OLEV) and its wireless power transfer mechanism and analyze the electromagnetic compatibility characteristics. As magnetic fields transfer 100kW of power to the vehicle, reduction of electromagnetic field (EMF) noise is a critical issue for protection of the human body. Also, with respect to electromagnetic interference (EMI) noise, a proper measurement method has not yet been established for this low frequency high power system. In this paper, low frequency magnetic field shielding methods and application of the shields to the OLEV system are presented. Furthermore, a standard low frequency magnetic field measurement is suggested as an EMI test.

Conventional adaptive notch filter based on an infinite impulse response (IIR) filter is well known. However, this kind of adaptive notch filter has a problem of stability due to its adaptive IIR filter. In addition, tap coefficients of this notch filter converge to solutions with bias error. In order to solve these problems, an adaptive notch filter using Fourier sine series (ANFF) is proposed. The ANFF is stable because an adaptive IIR filter is not used as an all-pass filter. Further, the proposed adaptive notch filter is robust enough to overcome effects of a disturbance signal, due to a structure of the notch filter based on an exponential filter and line symmetry of auto correlation.

This letter deals with a sparse signal recovery problem and proposes a new algorithm based on the iterative reweighted least squares (IRLS) algorithm. We assume that the non-zero values of a sparse signal is always greater than a given constant and modify the IRLS algorithm to satisfy this assumption. Numerical results show that the proposed algorithm recovers a sparse vector efficiently.

Ultra-wideband pulse radar exhibits high range resolution, and excellent capability in penetrating dielectric media. With that, it has great potential as an innovative non-destructive inspection technique for objects such as human body or concrete walls. For suitability in such applications, we have already proposed an accurate permittivity estimation method for a 2-dimensional dielectric object of arbitrarily shape and clear boundary. In this method, the propagation path estimation inside the dielectric object is calculated, based on the geometrical optics (GO) approximation, where the dielectric boundary points and its normal vectors are directly reproduced by the range point migration (RPM) method. In addition, to compensate for the estimation error incurred using the GO approximation, a waveform compensation scheme employing the finite-difference time domain (FDTD) method was incorporated, where an initial guess of the relative permittivity and dielectric boundary are employed for data regeneration. This study introduces the 3-dimensional extension of the above permittivity estimation method, aimed at practical uses, where only the transmissive data are effectively extracted, based on quantitative criteria that considers the spatial relationship between antenna locations and the dielectric object position. Results from a numerical simulation verify that our proposed method accomplishes accurate permittivity estimations even for 3-dimensional dielectric medium of wavelength size.

Single view distributed video coding (DVC) is a coding method that allows for the computational complexity of the system to be shifted from the encoder to the decoder. This property promotes the use of DVC in systems where processing power or energy use at the encoder is constrained. Examples include wireless devices and surveillance. This paper proposes a multi-hypothesis transform domain single-view DVC system that performs symbol level coding with a non-binary low-density parity-check code. The main contributions of the system relate to the methods used for combining multiple side information hypotheses at the decoder. The system also combines interpolation and extrapolation in the side information creation process to improve the performance of the system over larger group-of-picture sizes.

We present an iterative method for inverse transform of nonlinear image processing. Its convergence is verified for image enhancement by an online software. We also show its application to amplification of the opacity in foggy or underwater images.

In a live 3D TV program, since a change and processing of an image is performed in real time, it is difficult to check depth perception in advance. From such a background, we made the trial 3D TV program where various visual effects were used and analyzed subject's vergence while viewing them.