The need for the OpenGL-family of the 3D rendering API's are highly increasing, especially for graphical human-machine interfaces on various systems. In the case of safety-critical market for avionics, military, medical and automotive applications, OpenGL SC, the safety critical profile of the OpenGL standard plays the major role for graphical interfaces. In this paper, we present an efficient way of implementing OpenGL SC 3D graphics API for the environments with hardware-supported OpenGL 1.1 and its multi-texture extension facility, which is widely available on recent embedded systems. Our approach achieved the OpenGL SC features at the low development cost on the embedded systems and also on general personal computers. Our final result shows its compliance with the OpenGL SC standard specification. From the efficiency point of view, we measured its execution times for various application programs, to show a remarkable speed-up.

For an adaptive system identification filter with a stochastic input signal, a coefficient vector updated with an NLMS algorithm converges in the sense of ensemble average and the expected convergence vector has been revealed. When the input signal is periodic, the convergence of the adaptive filter coefficients has also been proved. However, its convergence vector has not been revealed. In this paper, we derive the convergence vector of adaptive filter coefficients updated with the NLMS algorithm in system identification for deterministic sinusoidal inputs. Firstly, we derive the convergence vector when a disturbance does not exist. We show that the derived convergence vector depends only on the initial vector and the sinusoidal frequencies, and it is independent of the step-size for adaptation, sinusoidal amplitudes, and phases. Next, we derive the expected convergence vector when the disturbance exists. Simulation results support the validity of the derived convergence vectors.

Compressing a JPEG image twice will greatly decrease the values of some of its DCT coefficients. This effect can be easily detected by statistics methods. To defend this forensic method, we establish a model to evaluate the security and image quality influenced by the re-compression. Base on the model, an optimized adjustment of the DCT coefficients is achieved by Genetic Algorithm. Results show that the traces of double compression are removed while preserving image quality.

Recently a simple algorithm was presented by the first author which enables one to successively compute the transformation matrix of various order for the general 1-D to 1-D polynomial transformation. This letter extends the result to the general 1-D to 2-D polynomial transformation. It is also shown that the matrix obtained can be used for the 2-D to 2-D polynomial transformation as well.

This paper presents a new 8T (8-transistor) SRAM cell layout mitigating multiple-bit upset (MBU) in a divided wordline structure. Because bitlines along unselected columns are not activated, the divided wordline structure eliminates a half-select problem and achieves low-power operation, which is often preferred for low-power/low-voltage applications. However, the conventional 8T SRAM with the divided wordline structure engenders MBUs because all bits in the same word are physically adjoining. Consequently, it is difficult to apply an error correction coding (ECC) technique to it. In this paper, we propose a new 8T cell layout pattern that separates internal latches in SRAM cells using both an n-well and a p-substrate. We saw that a SEU cross section of nMOS is 3.5–4.5 times higher than that of pMOS (SEU: single event upset; a cross section signifies a sensitive area to soft error effects). By using a soft-error simulator, iRoC TFIT, we confirmed that the proposed 8T cell has better neutron-induced MBU tolerance. The simulator includes soft-error measurement data in a commercial 65-nm process. The MBU in the proposed 8T SRAM is improved by 90.70% and the MBU soft error rate (SER) is decreased to 3.46 FIT at 0.9 V when ECC is implemented (FIT: failure in time). Additionally, we conducted Synopsys 3-D TCAD simulation, which indicates that the linear energy transfer (LET) threshold in SEU is also improved by 66% in the proposed 8T SRAM by a common-mode effect.

Directional antennas provide numerous benefits, such as higher gains, increased transmission range, and lower interferences. In this paper, we propose a reliable broadcast protocol for directional antenna referred to as beam table-based reliable broadcast for directional antennas (BTRB). The BTRB employs (1) ACK-based scheme to provide full reliability; (2) spatio-temporal ACK combination to resolve the problems of ACK implosion and transmission delay; and (3) beam table caching to represent spatial relationship among destination nodes in the broadcast group. Performance evaluation has shown that the proposed BTRB shows full reliability and outperforms existing reliable broadcast schemes with respect to transmission delay by about 55%.

In this paper, we present a new fault-tolerant, large-scale star network scheme called Scalable Autonomous Fault-tolerant Ethernet (SAFE). The primary goal of a SAFE scheme is to provide network scalability and autonomous fault detection and recovery. SAFE divides a large-scale, mission-critical network, such as the naval combatant network, into several subnets by limiting the number of nodes in each subnet. This network can be easily configured as a star network in order to meet fault recovery time requirements. For SAFE, we developed a novel mechanism for inter-subnet fault detection and recovery; a conventional Ethernet-based heartbeat mechanism is used in each subnet. Theoretical and experimental performance analyses of SAFE in terms of fail-over time were conducted under various network failure scenarios. The results validate our scheme.

This paper presents a new incremental approach for robot navigation using associative memory. We defined the association as node→action→node where node is the robot position and action is the action of a robot (i.e., orientation, direction). These associations are used for path planning by retrieving a sequence of path fragments (in form of (node→action→node) → (node→action→node) →…) starting from the start point to the goal. To learn such associations, we applied the associative memory using Self-Organizing Incremental Associative Memory (SOIAM). Our proposed method comprises three layers: input layer, memory layer and associative layer. The input layer is used for collecting input observations. The memory layer clusters the obtained observations into a set of topological nodes incrementally. In the associative layer, the associative memory is used as the topological map where nodes are associated with actions. The advantages of our method are that 1) it does not need prior knowledge, 2) it can process data in continuous space which is very important for real-world robot navigation and 3) it can learn in an incremental unsupervised manner. Experiments are done with a realistic robot simulator: Webots. We divided the experiments into 4 parts to show the ability of creating a map, incremental learning and symbol-based recognition. Results show that our method offers a 90% success rate for reaching the goal.

This paper presents two halftoning methods to improve efficiency in generating structurally similar halftone images using Structure Similarity Index Measurement (SSIM). Proposed Method I reduces the pixel evaluation area by applying pixel-swapping algorithm within inter-correlated blocks followed by phase block-shifting. The effect of various initial pixel arrangements is also investigated. Proposed Method II further improves efficiency by applying bit-climbing algorithm within inter-correlated blocks of the image. Simulation results show that proposed Method I improves efficiency as well as image quality by using an appropriate initial pixel arrangement. Proposed Method II reaches a better image quality with fewer evaluations than pixel-swapping algorithm used in Method I and the conventional structure aware halftone methods.

A left-handed material with simple structure is proposed. The material is composed of periodic metal strips exhibiting both electric property and magnetic property. The dispersion relations and the transmission characteristics are confirmed experimentally. The main field pattern of guided mode in the material is similar to that of the plane wave, and a transmission characteristic with low reflection is obtained for an impedance matching region.

We propose a new configuration for a parallel fiber amplifier that can amplify both the C- and L-bands simultaneously by employing bundled Er3+-doped fiber (EDF). The bundled EDF is a candidate amplification medium for multi-core optical fiber amplifiers. Our parallel fiber amplifier is another application of the multi-core amplification medium. The amplifier achieves almost the same signal gain of 20 dB for both the C- and L-bands by using a bundled EDF, which is realized by bundling seven identical single-core EDFs.

The Hilbert-Schmidt independence criterion (HSIC) is a kernel-based statistical independence measure that can be computed very efficiently. However, it requires us to determine the kernel parameters heuristically because no objective model selection method is available. Least-squares mutual information (LSMI) is another statistical independence measure that is based on direct density-ratio estimation. Although LSMI is computationally more expensive than HSIC, LSMI is equipped with cross-validation, and thus the kernel parameter can be determined objectively. In this paper, we show that HSIC can actually be regarded as an approximation to LSMI, which allows us to utilize cross-validation of LSMI for determining kernel parameters in HSIC. Consequently, both computational efficiency and cross-validation can be achieved.

Computational Fluid Dynamics (CFD) is used as a common design tool in the aerospace industry. UPACS, a package for CFD, is convenient for users, since a customized simulator can be built just by selecting desired functions. The problem is its computation speed, which is difficult to enhance by using the clusters due to its complex memory access patterns. As an economical solution, accelerators using FPGAs are hopeful candidate. However, the total scale of UPACS is too large to be implemented on small numbers of FPGAs. For cost efficient implementation, partial reconfiguration which dynamically loads only required functions is proposed in this paper. Here, the MUSCL scheme, which is used frequently in UPACS, is selected as a target. Partial reconfiguration is applied to the flux limiter functions (FLF) in MUSCL. Four FLFs are implemented for Turbulence MUSCL (TMUSCL) and eight FLFs are for Convection MUSCL (CMUSCL). All FLFs are developed independently and separated from the top MUSCL module. At start-up, only required FLFs are selected and deployed in the system without interfering the other modules. This implementation has successfully reduced the resource utilization by 44% to 63%. Total power consumption also reduced by 33%. Configuration speed is improved by 34-times faster as compared to full reconfiguration method. All implemented functions achieved at least 17 times speed-up performance compared with the software implementation.

In this paper, we propose a novel texture analysis method capable of estimating multiple primitives, which are elements repetitively arranged to compose a texture, in multi-structured textures. The approach is based on a texture description model that uses mathematical morphology, called the “Primitive, Grain, and Point Configuration (PGPC)” texture model. The estimation of primitives based on the PGPC texture model involves searching the optimal structuring element for primitives according to a size distribution function and a magnification. The proposed method achieves the following two improvements: (1) the simultaneous estimation of a multiple number of primitives in multi-structured textures with a ranking of primitives on the basis of their significance. and (2) the introduction of flexibility in the process of magnification to obtain a higher degree of fitness of large grains. With a computational combination of different primitives, the method provides an ordered priority to denote the significance of elements. The promising performance of the proposed method is experimentally shown by a comparison with conventional methods.

We propose a novel dynamic hierarchical optical path network architecture that achieves efficient optical fast circuit switching. In order to complete wavelength path setup/teardown efficiently, the proposed network adaptively manages waveband paths and bundles of optical paths, which provide virtual mesh connectivity between node pairs for wavelength paths. Numerical experiments show that operational and facility costs are significantly reduced by employing the adaptive virtual waveband connections.

This paper presents a compact metal plate lens antenna for evaluating a wave absorber placed on ceiling of the ETC gate. The focal distance of the lens was derived to be 129 cm by the geometrical optics procedure. By arranging the lens in front of a horn antenna, the gain and beamwidth characteristics were improved from 18 dBi to 26 dBi and from 22 degrees to 7 degrees, respectively. Then the antenna characteristics were evaluated when the distance between the antenna and the lens was changed in order to miniaturize the lens antenna. As the result, the changes in beamwidth were held to within 1 dB when the lens came close to the horn antenna. Scattering, phase and electric field intensity of electromagnetic wave were evaluated to clarify the foundation of the given characteristics. It was found that the field intensity for the miniaturized lens antenna is stronger than that for GO designed one though the phase uniformity is worse. The distance between the horn antenna and lens can be reduced to 80 cm. The absorption characteristics for the arranged absorbers which have different absorptions were measured, and it was shown that the proposed method was suitable for specifying the deteriorated absorber in the ETC system.

This paper proposes a virtual layered successive detector with adaptive transmit signal phase rotation for quadrature amplitude modulation (QAM) that enables high speed communication even in downlinks of wireless communication systems. It is shown that the detection performance is degraded when the eigenvalue of a virtual channel becomes close to the power of the additive white Gaussian noise (AWGN). Therefore, adaptive transmit signal phase rotation is introduced for the detector to improve the transmission performance. For the transmit phase rotation, three techniques to search the rotation angles are proposed, which can reduce the feedback information from the receiver to the transmitter. Among the three proposed techniques, the technique called “iterative variable step step search” is shown to achieve the best performance. Actually, it is confirmed by computer simulation that the variable step search makes the detector attain about 17 dB of a gain at the bit error rate (BER) of 10-5 in 42 multiple-input-multiple-output (MIMO) systems.

A novel method for automatically creating an optimum direction-of-arrival (DOA) estimation algorithm for a given radio environment using a genetic algorithm (GA) is proposed. DOA estimation algorithms are generally described by parameters and operators. The performance of a DOA estimation algorithm is evaluated using root mean square error (RMSE) through computer simulations. A GA searches for the combination of parameters and operators that gives the lowest RMSE. Because a GA can treat only bit strings, Polish notation is used to convert bit strings into a DOA estimation algorithm. A computer simulation showed that the proposed method can create a new angle spectrum function. The created angle spectrum function has higher resolution than the Capon method.

In this paper, we study how to automatically classify mathematical expressions written in MathML (Mathematical Markup Language). It is an essential preprocess to resolve analysis problems originated from multi-meaning mathematical symbols. We first define twelve equation classes based on chapter information of mathematics textbooks and then conduct various experiments. Experimental results show an accuracy of 94.75%, by employing the feature combination of tags, operators, strings, and “identifier & operator” bigram.

In this letter, we adopt a new factor analysis of neighborhood-preserving embedding (NPE) for speaker verification. NPE aims at preserving the local neighborhood structure on the data and defines a low-dimensional speaker space called neighborhood-preserving embedding space. We compare the proposed method with the state-of-the-art total variability approach on the telephone-telephone core condition of the NIST 2008 Speaker Recognition Evaluation (SRE) dataset. The experimental results indicate that the proposed NPE method outperforms the total variability approach, providing up to 24% relative improvement.