We present a smart steering wheel that detects the gripping position and area, as well as the distance to the approaching driver's hands by measuring the resonant frequency and its resistance value in an LCR circuit composed of the floating capacitance between the gripping hand and the electrode of the steering, and the body resistance. The resonant frequency measurement provides a high sensitivity that enables the estimation of the distance to the approaching hand, the gripping area of a gloved hand, and for covering the steering surface with any type of insulating material. This system can be applied for drowsiness detection, driving technique improvements, and for customization of the driving settings.

In this paper, we study Wi-Fi mesh networks (WMNs) as a promising candidate for wireless networking infrastructure that interconnects a variety of access networks. The main performance bottleneck of a WMN is their limited capacity due to the packet collision from the contention-based IEEE 802.11s MAC. To mitigate this problem, we present the distributed link-activation (DLA) protocol which activates a set of collision-free links for a fixed amount of time by exchanging a few control packets between neighboring MRs. Through the rigorous proof, it is shown that the upper bound of the DLA rounds is O(Smax), where Smax is the maximum number of (simultaneous) interference-free links in a WMN topology. Based on the DLA, we also design the distributed throughput-maximal scheduling (D-TMS) scheme which overlays the DLA protocol on a new frame architecture based on the IEEE 802.11 power saving mode. To mitigate its high latency, we propose the D-TMS adaptive data-period control (D-TMS-ADPC) that adjusts the data period depending on the traffic load of a WMN. Numerical results show that the D-TMS-ADPC scheme achieves much higher throughput performance than the IEEE 802.11s MAC.

High-resolution image and video communication in home networks is highly expected to proliferate with the spread of Wi-Fi devices and the introduction of multiple-input multiple-output (MIMO) systems. This paper proposes a joint transmission and coding scheme for broadcasting high-resolution video streams over multiuser MIMO systems with an eigenbeam-space division multiplexing (E-SDM) technique. Scalable video coding makes it possible to produce the code stream comprised of multiple layers having unequal contribution to image quality. The proposed scheme jointly assigns the data of scalable code streams to subcarriers and spatial streams based on their signal-to-noise ratio (SNR) values in order to transmit visually important data with high reliability. Simulation results show that the proposed scheme surpasses the conventional unequal power allocation (UPA) approach in terms of both peak signal-to-noise ratio (PSNR) of received images and correct decoding probability. PSNR performance of the proposed scheme exceeds 35dB with the probability of over 95% when received SNR is higher than 6dB. The improvement in average PSNR by the proposed scheme compared to the conventional UPA comes up to approx. 20dB at received SNR of 6dB. Furthermore, correct decoding probability reaches 95% when received SNR is greater than 4dB.

Heart disease is one of the major causes of death in many advanced countries. For prevention or treatment of heart disease, getting an early diagnosis from a long time period of electrocardiogram (ECG) examination is necessary. However, it could be a large burden on medical experts to analyze this large amount of data. To reduce the burden and support the analysis, this paper proposes an arrhythmia detection method based on a deformable part model, which absorbs individual variation of ECG waveform and enables the detection of various arrhythmias. Moreover, to detect the arrhythmia in low processing delay, the proposed method only utilizes time domain features. In an experimental result, the proposed method achieved 0.91 F-measure for arrhythmia detection.

The Helmholtz-Kohlraush effect is a visual characteristic that humans perceive color having higher saturation as brighter. In the proposed method, the pixel value is reduced by increasing the saturation while maintaining the hue and value of HSV color space, resulting in power saving of OLED displays since the power consumption of OLED displays directly depends on the pixel value. Although the luminance decreases, brightness of image is maintained by the Helmholtz-Kohlraush effect. In order to suppress excessive increase of saturation, the increase factor of saturation is reduced with an increase in brightness. As maximum increase factor of saturation, kMAX, increases, more power is reduced but unpleasant color change takes place. From the subjective evaluation experiment with the 23 test images consisting of skin, natural and non-natural images, it is found that kMAX is less than 2.0 to suppress the unpleasant color change. When kMAX is 2.0, the power saving is 8.0%. The effectiveness of the proposed technique is confirmed by using a smart phone having 4.5 inches diagonal RGB AMOLED display.

Community detection is an important task in the social network analysis field. Many detection methods have been developed; however, they provide little semantic interpretation for the discovered communities. We develop a framework based on joint matrix factorization to integrate network topology and node content information, such that the communities and their semantic labels are derived simultaneously. Moreover, to improve the detection accuracy, we attempt to make the community relationships derived from two types of information consistent. Experimental results on real-world networks show the superior performance of the proposed method and demonstrate its ability to semantically annotate communities.

The objectives of this survey are to provide an in-depth coverage of a few selected research papers that have made significant contributions to the development of Network Function Virtualization (NFV), and to provide readers insights into the key advantages and disadvantages of NFV and Software Defined Networks (SDN) when compared to traditional networks. The research papers covered are classified into four categories: NFV Infrastructure (NFVI), Network Functions (NFs), Management And Network Orchestration (MANO), and service chaining. The NFVI papers describe “framework” software that implement common functions, such as dynamic scaling and load balancing, required by NF developers. Papers on NFs are classified as offering solutions for software switches or middleboxes. MANO papers covered in this survey are primarily on resource allocation (virtual network embedding), which is an orchestrator function. Finally, service chaining papers that offer examples and extensions are reviewed. Our conclusions are that with the current level of investment in NFV from cloud and Internet service providers, the promised cost savings are likely to be realized, though many challenges remain.

We previously proposed a lossless image coding scheme using example-based probability modeling, wherein the probability density function of image signals was dynamically modeled pel-by-pel. To appropriately estimate the peak positions of the probability model, several examples, i.e., sets of pels whose neighborhoods are similar to the local texture of the target pel to be encoded, were collected from the already encoded causal area via template matching. This scheme primarily makes use of non-local information in image signals. In this study, we introduce a prediction technique into the probability modeling to offer a better trade-off between the local and non-local information in the image signals.

This letter proposes an extended image-source model to simulate the room transfer function for a rotatable complex source in a three-dimensional reverberant room. The proposed model uses spherical harmonic decomposition to describe the exterior sound field from the complex source. Based on “axis flip” concept, the mirroring relations between the source and images are summarized by a unified mirroring operator that occurs on the soundfield coefficients. The rotation movement of the source is taken into account by exploiting the rotation property of spherical harmonics. The accuracy of our proposed model is verified through the appropriate simulation examples.

High-dynamic-range imaging (HDRI) technologies aim to extend the dynamic range of luminance against the limitation of camera sensors. Irradiance information of a scene can be reconstructed by fusing multiple low-dynamic-range (LDR) images with different exposures. The key issue is removing ghost artifacts caused by motion of moving objects and handheld cameras. This paper proposes a robust ghost-free HDRI algorithm by visual salience based bilateral motion detection and stack extension based exposure fusion. For ghost areas detection, visual salience is introduced to measure the differences between multiple images; bilateral motion detection is employed to improve the accuracy of labeling motion areas. For exposure fusion, the proposed algorithm reduces the discontinuity of brightness by stack extension and rejects the information of ghost areas to avoid artifacts via fusion masks. Experiment results show that the proposed algorithm can remove ghost artifacts accurately for both static and handheld cameras, remain robust to scenes with complex motion and keep low complexity over recent advances including rank minimization based method and patch based method by 63.6% and 20.4% time savings averagely.

The ball state tracking and detection technology plays a significant role in volleyball game analysis, whose performance is limited due to the challenges include: 1) the inaccurate ball trajectory; 2) multiple numbers of the ball event category; 3) the large intra-class difference of one event. With the goal of broadcasting supporting for volleyball games which requires a real time system, this paper proposes a ball state based parallel ball tracking and event detection method based on a sequential estimation method such as particle filter. This method employs a parallel process of the 3D ball tracking and the event detection so that it is friendly for real time system implementation. The 3D ball tracking process uses the same models with the past work [8]. For event detection process, a ball event change estimation based multiple system model, a past trajectory referred hit point likelihood and a court-line distance feature based event type detection are proposed. First, the multiple system model transits the ball event state, which consists the event starting time and the event type, through three models dealing with different ball motion situations in the volleyball game, such as the motion keeping and changing. The mixture of these models is decided by estimation of the ball event change estimation. Secondly, the past trajectory referred hit point likelihood avoids the processing time delay between the ball tracking and the event detection process by evaluating the probability of the ball being hit at certain time without using future ball trajectories. Third, the feature of the distance between the ball and the specific court line are extracted to detect the ball event type. Experimental results based on multi-view HDTV video sequences (2014 Inter High School Men's Volleyball Games, Japan), which contains 606 events in total, show that the detection rate reaches 88.61% while the success rate of 3D ball tracking keeps more than 99%.

Network traffic forecasts, as it is well known, can be useful for network resource optimization. In order to minimize the forecast error by maximizing information utilization with low complexity, this paper concerns the difference of traffic trends at large time scales and fits a dual-related model to predict it. First, by analyzing traffic trends based on user behavior, we find both hour-to-hour and day-to-day patterns, which means that models based on either of the single trends are unable to offer precise predictions. Then, a prediction method with the consideration of both daily and hourly traffic patterns, called the dual-related forecasting method, is proposed. Finally, the correlation for traffic data is analyzed based on model parameters. Simulation results demonstrate the proposed model is more effective in reducing forecasting error than other models.

This paper reports on the relationships between the performance of retro-reflectors and the sharpness of an aerial image formed with aerial imaging by retro-reflection (AIRR). We have measured the retro-reflector divergence angle and evaluated aerial image sharpness by use of the contrast-transfer function. It is found that the divergence angle of the retro-reflected light is strongly related to the sharpness of the aerial image formed with AIRR.

The heart of Network Functions Virtualization (NFV) is both the softwarization of existing network middleboxes as Virtual Network Functions (VNFs) and the Service Function Chaining (SFC), also known as Service Chaining of them. Most existing VNFs are realized as VM-based general purpose appliances and shared by multiple user VMs. However, the cover range of VNF can be extended to directly reinforce network functionality of user VMs by introducing VM-specific VNFs. In this study, we propose micro-VNFs (µVNFs) and a VM-specific service chaining framework (vNFChain). Micro-VNFs are VM-specific lightweight VNFs that directly attach to a user VM, and can support not only traditional L2-L4 protocols but also stateful custom L7 protocols. The vNFChain framework constructs local service chains of µVNFs and transparently attaches the chain to the VM. Importantly, our framework achieves zero touch configuration for user VMs as well as no modification for existing system environments, such as virtual switch, hypervisor, and OS. In this paper, we describe architectural design and implementation of the framework. In addition, we evaluate the proposed approach in terms of throughput and CPU usage by comparing it with a DPDK-enabled VM-based µVNF model.

This paper presents an interactive locomotion controller using motion capture data and an inverted pendulum model (IPM). The motion data of a character is decomposed into those of upper and lower bodies, which are then dimension-reduced via what we call hierarchical Gaussian process dynamical model (H-GPDM). The locomotion controller receives the desired walking direction from the user. It is integrated into the IPM to determine the pose of the center of mass and the stance-foot position of the character. They are input to the H-GPDM, which interpolates the low-dimensional data to synthesise a redirected motion sequence on an uneven surface. The locomotion controller allows the upper and lower bodies to be independently controlled and helps us generate natural locomotion. It can be used in various real-time applications such as games.

This study investigates whether learners consider constraints while posing arithmetic word problems. Through log data from an interactive learning environment, we analyzed actions of 39 first grade elementary school students and conducted correlation analysis between the frequency of actions and validity of actions. The results show that the learners consider constraints while posing arithmetic word problems.

Microwave imaging techniques, in particular, synthetic aperture radar (SAR), are promising tools for terrain surface measurement, irrespective of weather conditions. The coherent change detection (CCD) method is being widely applied to detect surface changes by comparing multiple complex SAR images captured from the same scanning orbit. However, in the case of a general damage assessment after a natural disaster such as an earthquake or mudslide, additional about surface change, such as surface height change, is strongly required. Given this background, the current study proposes a novel height change estimation method using a CCD model based on the Pauli decomposition of fully polarimetric SAR images. The notable feature of this method is that it can offer accurate height change beyond the assumed wavelength, by introducing the frequency band-divided approach, and so is significantly better than InSAR based approaches. Experiments in an anechoic chamber on a 1/100 scaled model of the X-band SAR system, show that our proposed method outputs more accurate height change estimates than a similar method that uses single polarimetric data, even if the height change amount is over the assumed wavelength.

In this paper, an improved lattice reduction (LR)-aided soft-output multiple-input multiple-output (MIMO) detector is proposed. Conventional LR-aided soft-output MIMO detectors involve the empty set problem (ESP), in which an entry with a particular bit in the candidate list might not exist. To overcome the performance degradation resulting from this ESP, a post-processing algorithm that modifies the candidate list is proposed. The proposed algorithm efficiently resolves the ESP by utilizing the near-orthogonality of the lattice-reduced system model so that the bit error rate (BER) performance is enhanced. In addition, as the complexity of the candidate list generation is reduced with the aid of the post-processing algorithm, the overall complexity is also reduced. Simulation results and the complexity comparisons demonstrate that our proposed method lowers the required Eb/No by 4-5 dB at the BER of 10-5 and the complexity by 13%-55%, compared to the conventional method.

A single-dimensional interface which enables users to obtain diverse localizations of audio sources is proposed. In many conventional interfaces for arranging audio sources, there are multiple arrangement parameters, some of which allow users to control positions of audio sources. However, it is difficult for users who are unfamiliar with these systems to optimize the arrangement parameters since the number of possible settings is huge. We propose a simple, single-dimensional interface for adjusting arrangement parameters, allowing users to sample several diverse audio source arrangements and easily find their preferred auditory localizations. To select subsets of arrangement parameters from all of the possible choices, auditory-localization space vectors (ASVs) are defined to represent the auditory localization of each arrangement parameter. By selecting subsets of ASVs which are approximately orthogonal, we can choose arrangement parameters which will produce diverse auditory localizations. Experimental evaluations were conducted using music composed of three audio sources. Subjective evaluations confirmed that novice users can obtain diverse localizations using the proposed interface.

In this paper, we propose a low-invasive framework to predict changes in cognitive performance using only heart rate variability (HRV). Although a lot of studies have tried to estimate cognitive performance using multiple vital data or electroencephalogram data, these methods are invasive for users because they force users to attach a lot of sensor units or electrodes to their bodies. To address this problem, we proposed a method to estimate cognitive performance using only HRV, which can be measured with as few as two electrodes. However, this can't prevent loss of worker productivity because the workers' productivity had already decreased even if their current cognitive performance had been estimated as being at a low level. In this paper, we propose a framework to predict changes in cognitive performance in the near future. We obtained three principal contributions in this paper: (1) An experiment with 45 healthy male participants clarified that changes in cognitive performance caused by mental workload can be predicted using only HRV. (2) The proposed framework, which includes a support vector machine and principal component analysis, predicts changes in cognitive performance caused by mental workload with 84.4 % accuracy. (3) Significant differences were found in some HRV features for test participants, depending on whether or not their cognitive performance changes had been predicted accurately. These results lead us to conclude that the framework has the potential to help both workers and managerial personnel predict what their performances will be in the near future. This will make it possible to proactively suggest rest periods or changes in work duties to prevent losses in productivity caused by decreases of cognitive work performance.