This research deals with muffled speech as the evaluation target and introduces a criterion for evaluating the auditory impression in muffled speech. It focuses on the vocal tract area function (VTAF) to evaluate the auditory impression, and the criterion uses temporal differentiation of this function to track the temporal variation of the shape of the mouth. The experimental results indicate that the proposed criterion can be used to evaluate the auditory impression as well as the subjective impression.

The modeling of random telegraph noise (RTN) of MOS transistors is becoming increasingly important. In this paper, a novel method is proposed for realizing automated estimation of two important RTN-model parameters: the number of interface-states and corresponding threshold voltage shift. The proposed method utilizes a Gaussian mixture model (GMM) to represent the voltage distributions, and estimates their parameters using the expectation-maximization (EM) algorithm. Using information criteria, the optimal estimation is automatically obtained while avoiding overfitting. In addition, we use a shared variance for all the Gaussian components in the GMM to deal with the noise in RTN signals. The proposed method improved estimation accuracy when the large measurement noise is observed.

In this paper, we present a computer vision-based human tracking system with multiple stereo cameras. Many widely used methods, such as KLT-tracker, update the trackers “frame-to-frame,” so that features extracted from one frame are utilized to update their current state. In contrast, we propose a novel optimization technique for the “multi-frame” approach that computes resultant trajectories directly from video sequences, in order to achieve high-level robustness against severe occlusion, which is known to be a challenging problem in computer vision. We developed a heuristic optimization technique to estimate human trajectories, instead of using dynamic programming (DP) or an iterative approach, which makes our method sufficiently computationally efficient to operate in realtime. Six video sequences where one to six people walk in a narrow laboratory space are processed using our system. The results confirm that our system is capable of tracking cluttered scenes in which severe occlusion occurs and people are frequently in close proximity to each other. Moreover, minimal information is required for tracking, instead of full camera images, which is communicated over the network. Hence, commonly used network devices are sufficient for constructing our tracking system.

A method of round addition attack on substitution-permutation network (SPN) block ciphers using differential fault analysis (DFA) is presented. For the 128-bit advanced encryption standard (AES), we show that secret keys can be extracted using one correct ciphertext and two faulty ciphertexts. Furthermore, we evaluate the success rate of a round addition DFA attack, experimentally. The proposed method can also be applied to lightweight SPN block cipher such as KLEIN and LED.

In this paper, an image prior based on soft-morphological filters and its application to image recovery are presented. In morphological image processing, a gray-scale image is represented as a subset in a three-dimensional space, which is spanned by spatial and intensity axes. Morphological opening and closing, which are basic operations in morphological image processing, respectively approximate the image subset and its complementary images as the unions of structuring elements that are translated in the three-dimensional space. In this study, the opening and closing filters are applied to an image prior to resolve the regularization problem of image recovery. When the proposed image prior is applied, the image is recovered as an image that has no noise component, which is eliminated by the opening and closing. However, the closing and opening filters are less able to eliminate Gaussian noise. In order to improve the robustness against Gaussian noise, the closing and opening filters are respectively approximated as soft-closing and soft-opening with relaxed max and min functions. In image recovery experiments, image denoising and deblurring using the proposed prior are demonstrated. Comparisons of the proposed prior with the existing priors that impose a penalty on the gradient of the intensity are also shown.

This letter presents a new blind audio watermarking scheme using eigenvalue decomposition (EVD). Initially, the original audio is divided into frames and the samples of each frame are arranged into a square matrix. EVD is applied to each of these matrices. Watermark data is embedded into the largest eigenvalue of each diagonal matrix by quantization. Data embedding rate of the proposed scheme is 172.39bps. Simulation results confirm the imperceptibility of the proposed scheme and its higher robustness against various attacks compared to the state-of-the-art watermarking methods available in the literature.

In this letter, a cooperative scheme based on orthogonal frequency division multiplexing (OFDM) in vehicular communication system is proposed. In the conventional scheme, a destination exploits only one base station to communicate information. The proposed scheme can use an extra source from another base station through a relay, since the restriction of power in vehicle are less than cellular device. If a destination is distant from a base station, the performance is degraded. When a destination is distant from a base station, the proposed scheme employing space time block code (STBC) and cyclic delay diversity (CDD) has a higher bit error rate (BER) performance and throughput than the conventional scheme.

High efficiency video coding (HEVC) is the new generation video compression standard. Sample adaptive offset (SAO) is a new compression tool adopted in HEVC which reduces the distortion between original samples and reconstructed samples. SAO estimation is the process of determining SAO parameters in video encoding. It is divided into two phases: statistic collection and parameters determination. There are two difficulties for VLSI implementation of SAO estimation. The first is that there are huge amount of samples to deal with in statistic collection phase. The other is that the complexity of Rate Distortion Optimization (RDO) in parameters determination phase is very high. In this article, a fast SAO estimation algorithm and its corresponding VLSI architecture are proposed. For the first difficulty, we use bitmaps to collect statistics of all the 16 samples in one 4×4 block simultaneously. For the second difficulty, we simplify a series of complicated procedures in HM to balance the algorithms complexity and BD-rate performance. Experimental results show that the proposed algorithm maintains the picture quality improvement. The VLSI design based on this algorithm can be implemented using 156.32K gates, 8,832bits single port RAM for 8bits depth case. It can be synthesized to 400MHz @ 65nm technology and is capable of 8K×4K @ 120fps encoding.

As the virtualization technology becomes the core ingredient for recent promising IT infrastructures such as utility computing and cloud computing, accurate analysis of the internal behaviors of virtual machines becomes more and more important. In this paper, we first propose a novel I/O fairness analysis tool for virtualization systems. It supports the following three features: fine-grained, multimodal and multidimensional. Then, using the tool, we observe various I/O behaviors in our experimental XEN-based virtualization system. Our observations disclose that 1) I/O fairness among virtual machines is broken frequently even though each virtual machine requests the same amount of I/Os, 2) the unfairness is caused by an intricate combination of factors including I/O scheduling, CPU scheduling and interactions between the I/O control domain and virtual machines, and 3) some mechanisms, especially the CFQ (Completely Fair Queuing) I/O scheduler that supports fairness reasonable well in a non-virtualization system, do not work well in a virtualization system due to the virtualization-unawareness. These observations drive us to design a new virtualization-aware I/O scheduler for enhancing I/O fairness. It gives scheduling opportunities to asynchronous I/Os in a controlled manner so that it can avoid the unfairness caused by the priority inversion between the low-priority asynchronous I/Os and high-priority synchronous I/Os. Real implementation based experimental results have shown that our proposal can enhance I/O fairness reducing the standard deviation of the finishing time among virtual machines from 4.5 to 1.2.

With the shorter time-to-market and the rising cost in SoC development, the demand for post-silicon programmability has been increasing. Recently, programmable accelerators have attracted more attention as an enabling solution for post-silicon engineering change. However, programmable accelerators suffers from 5∼10X less energy efficiency than fixed-function accelerators mainly due to their extensive use of memories. This paper proposes a highly energy-efficient accelerator which enables post-silicon engineering change by a control patching mechanism. Then, we propose a patch compilation method from a given pair of an original design and a modified design. We also propose a design method to add redundant wires in advance to decrease the necessary amount of patch memory for post-silicon engineering change. Experimental results demonstrate that the proposed accelerators offer high energy efficiency competitive to fixed-function accelerators and can achieve about 5X higher efficiency than the existing programmable accelerators. We also show the trade-off between redundant wires and the necessary amount of patch memory.

This paper proposes a mixed-grained reconfigurable architecture consisting of fine-grained and coarse-grained fabrics, each of which can be configured for different levels of reliability depending on the reliability requirement of target applications, e.g. mission-critical applications to consumer products. Thanks to the fine-grained fabrics, the architecture can accommodate a state machine, which is indispensable for exploiting C-based behavioral synthesis to trade latency with resource usage through multi-step processing using dynamic reconfiguration. In implementing the architecture, the strategy of dynamic reconfiguration, the assignment of configuration storage and the number of implementable states are key factors that determine the achievable trade-off between used silicon area and latency. We thus split the configuration bits into two classes; state-wise configuration bits and state-invariant configuration bits for minimizing area overhead of configuration bit storage. Through a case study, we experimentally explore the appropriate number of implementable states. A proof-of-concept VLSI chip was fabricated in 65nm process. Measurement results show that applications on the chip can be working in a harsh radiation environment. Irradiation tests also show the correlation between the number of sensitive bits and the mean time to failure. Furthermore, the temporal error rate of an example application due to soft errors in the datapath was measured and demonstrated for reliability-aware mapping.

This paper represents an illumination modeling method for lighting control which can model the illumination distribution inside office buildings. The algorithm uses data from the illumination sensors to train Radial Basis Function Neural Networks (RBFNN) which can be used to calculate 1) the illuminance contribution from each luminaire to different positions in the office 2) the natural illuminance distribution inside the office. This method can be used to provide detailed illumination contribution from both artificial and natural light sources for lighting control algorithms by using small amount of sensors. Simulations with DIALux are made to prove the feasibility and accuracy of the modeling method.

As one of the most widely investigated studies in wireless sensor networks (WSNs), multihop networking is increasingly developed and applied for achieving energy efficient communications and enhancing transmission reliability. To accurately and realistically analyze the performance metric (energy efficiency), firstly we provide a measurement of the energy dissipation for each state and establish a practical energy consumption model for a WSN. According to the analytical model of connectivity, Gaussian approximation approaches to experimental connection probability are expressed for optimization problem on energy efficiency. Moreover, for integrating experimental results with theories, we propose the methodology in multihop wireless sensor networks to maximize efficiency by nonlinear programming, considering energy consumptions and the total quantity of sensing data to base station. Furthermore, we present evaluations adapting to various wireless sensor networks quantitatively with respect to energy efficiency and network configuration, in view of connectivity, the length of data, maximum number of hops and total number of nodes. As the consequence, the realistic analysis can be used in practical applications, especially on self-organization sensor networks. The analysis also shows correlations between the efficiency and maximum number of hops, that is the multihop systems with several hops can accommodate enough devices in ordinary applications. In this paper, our contribution distinguished from others is that our model and analysis are extended from experiments. Therefore, the results of analysis and proposal can be conveniently applied to actual networks.

The physical optics (PO) approximation is one of the widely-used techniques to calculate scattering fields with a reasonable accuracy in the high frequency region. The computational load of PO radiation integral dramatically increases at higher frequencies since it is proportional to the electrical size of scatterer. In order to suppress this load, a variety of techniques, such as the asymptotic evaluation by the stationary phase method (SP), the equivalent edge currents (EECs), the low-order polynomial expansion method and the fast physical optics (FPO), have been proposed and developed. The adaptive sampling method (ASM) proposed by Burkholder is also one of the techniques where the sampling points in radiation integral should be adaptively determined based upon the phase change of integrand. We proposed a quite different approach named ``Localization of the radiation integrals.'' This localization method suggests that only the small portions of the integration with a slow phase change contribute to the scattering field. In this paper, we newly introduce the ASM in the localization method and applied the proposed method into the radar cross section (RCS) analysis of 2-dimensional strip and cylinder. We have confirmed that the proposed method provides the frequency-independent number of division in the radiation integrals and computational time and accuracy. As the starting point for extension to 3-D case, the application of the proposed method for a reflection from an infinite PEC plane and a part of sphere was also examined.

Radar systems using ultra-wideband (UWB) signals have definitive advantages in high range resolution. These are suitable for accurate 3-dimensional (3-D) sensing by rescue robots operating in disaster zone settings, where optical sensing is not applicable because of thick smog or high-density gas. For such applications, where no a priori information of target shape and position is given, an accurate method for 3-D imaging and motion estimation is strongly required for effective target recognition. In addressing this issue, we have already proposed a non-parametric 2-dimensional (2-D) imaging method for a target with arbitrary target shape and motion including rotation and translation being tracked using a multi-static radar system. This is based on matching target boundary points obtained using the range points migration (RPM) method extended to the multi-static radar system. Whereas this method accomplishes accurate imaging and motion estimation for single targets, accuracy is degraded severely for multiple targets, due to interference effects. For a solution of this difficulty, this paper proposes a method based on a novel matching scheme using not only target points but also normal vectors on the target boundary estimated by the Envelope method; interference effects are effectively suppressed when incorporating the RPM approach. Results from numerical simulations for both 2-D and 3-D models show that the proposed method simultaneously achieves accurate target imaging and motion tracking, even for multiple moving targets.

Tenant network provisioning in multi-tenancy data centers is time-consuming and error-prone due to the need to configure network devices with hundreds of parameter values (e.g., VLAN ID, IP address) determined according to complicated operational rules. Past works have aimed to automate such operational rule-based provisioning processes by implementing data center-specific provisioning programs, but a crucial problem is the high cost of adapting the programs to suit multiple data centers. In this paper, we aim to solve this problem by enabling to describe the provisioning processing, which has been hard-coded programs in conventional approaches, in easy-to-edit “provisioning template” files. The key component of the provisioning template is the parameter decision rule, which is a declarative abstract representation of parameter dependency and parameter assignment. We design the provisioning template so that it can handle various configuration items while preserving its editability for tenant provisioning. We design and implement the provisioning platform, and the evaluation based on a production data center shows that the provisioning platform can adopt multiple data centers with a single program, leading to less development cost compared to past approaches (i.e., program development for each data center).

Using “clean-slate approach” to redesign the Internet has attracted considerable attention. ZNA (Z Network Architecture) is one of clean-slate network architectures based on the layered model. The major features of ZNA are as follows: (1) introducing the session layer to provide the applications with sophisticated communication services, (2) employing inter-node cross-layer cooperation to adapt to the dynamically changing network conditions, (3) splitting the node identifier and the node locator for mobility, multi-homing, and heterogeneity of network layer protocols, (4) splitting the data plane and the control plane for high manageability, and (5) introducing a recursive layered model to support network virtualization. This paper focuses on the first three topics as well as the basic design of ZNA.

This paper proposes an efficient two-scan labeling algorithm for binary hexagonal images. Unlike conventional labeling algorithms, which process pixels one by one in the first scan, our algorithm processes pixels two by two. We show that using our algorithm, we can check a smaller number of pixels. Experimental results demonstrated that our method is more efficient than the algorithm extended straightly from the corresponding labeling algorithm for rectangle binary images.

While Triple modular Redundancy (TMR) is effective in eliminating soft errors in LSIs, the overhead of the triplicated area as well as the triplicated energy consumption is the problem. In addition to the spatial TMR mode where executions are simply tripricated and the majority is taken, the temporal TMR mode is available where only two copies of an operation are executed and the results are compared, then if the results differ, the third copy is executed to get the correct result. Appropriately selecting the power supply voltage is also an effective technique to reduce the energy consumption. In this paper, a method to derive a TMR design is proposed which selects the TMR mode and supply voltage for each operation to minimize the energy consumption within the time and area constraints.

The index generation function is a multi-valued logic function which checks if the given input vector is a registered or not, and returns its index value if the vector is registered. If the latency of the operation is critical, dedicated hardware is used for implementing the index generation functions. This paper proposes a method implementing the index generation functions using parallel index generator. A novel and efficient algorithm called ‘conflict free partitioning’ is proposed to synthesize parallel index generators. Experimental results show the proposed method outperforms other existing methods. Also, A novel architecture of index generator which is suitable for parallelized implementation is introduced. A new architecture has advantages in the sense of both area and delay.