Visual comparability of 3D regular sampling and reconstruction

The Body-Centered Cubic (BCC) and Face-Centered Cubic (FCC) lattices have been analytically shown to be more efficient sampling lattices than the traditional Cartesian Cubic (CC) lattice, but there has been no estimate of their visual comparability. Two perceptual studies (each with N = 12 participants) compared the visual quality of images rendered from BCC and FCC lattices to images rendered from the CC lattice. Images were generated from two signals: the commonly used Marschner-Lobb synthetic function and a computed tomography scan of a fish tail. Observers found that BCC and FCC could produce images of comparable visual quality to CC, using 30-35 percent fewer samples. For the images used in our studies, the L(2) error metric shows high correlation with the judgement of human observers. Using the L(2) metric as a proxy, the results of the experiments appear to extend across a wide range of images and parameter choices.     

Relaxed constraints support vector machines for noisy data

Real-world data collected for computer-based applications are frequently impure. Differentiation of outliers and noisy data from normal ones is a major task in data mining applications. On the other hand, elimination of noisy and outlier data from training samples of a dataset may lead to over-fitting or information loss. A fuzzy support vector machine (FSVM) provides an effective means to deal with this problem. It reduces the effect of the noisy data and outliers by using a fuzzy membership functions. In this paper, a new formation for SVMs is introduced that considers importance degrees for training samples. The constraints of the SVM are converted to fuzzy inequalities. The proposed method, RSVM, shows better efficiency in the classification of data in different domains. Especially, using the proposed RSVM for multi-class classification of arrhythmia disease is presented at the end of this paper as a practical case study to show the effectiveness of the proposed system.     

Multiple model bank selection based on nonlinearity measure and H-gap metric

This paper provides a systematic method for model bank selection in multi-linear model analysis for nonlinear systems by presenting a new algorithm which incorporates a nonlinearity measure and a modified gap based metric. This algorithm is developed for off-line use, but can be implemented for on-line usage. Initially, the nonlinearity measure analysis based on the higher order statistic (HOS) and the linear cross correlation methods are used for decomposing the total operating space into several regions with linear models. The resulting linear models are then used to construct the primary model bank. In order to avoid unnecessary linear local models in the primary model bank, a gap based metric is introduced and applied in order to merge similar linear local models. In order to illustrate the usefulness of the proposed algorithm, two simulation examples are presented: a pH neutralization plant and a continuous stirred tank reactor (CSTR).     

Experimental investigation of the flow-induced motion of a square-section cylinder

The flow-induced motion(FIM)of an elastically mounted square-section cylinder is experimentally investigated over a wide range of Reynolds numbers(1.5×104＜Re＜7....     

Error propagation analysis using FPGA-based SEU-fault injection

Error propagation analysis is one of the main objectives of fault injection experiments. This analysis helps designers to detect design mistakes and to provide effective mechanisms for fault tolerant systems. However, error propagation analysis requires that the chosen fault injection technique provides a high degree of observability (i.e., the ability to observe the internal values and events of a circuit after a fault is injected). Simulation-based fault injection provides a high observability adequate for error propagation analysis. However, the performance of the simulation-based technique is inadequate to handle today’s hardware complexity. As an alternative, FPGA-based fault injection can be used to accelerate the fault injection experiments, but the communication time needed for observing the circuit behavior from outside of the FPGA imposes severe limitations on the observability. In this paper, an observation technique for FPGA-based fault injection is proposed which significantly reduces the communication time as compared with previous scan-based observation techniques. Furthermore, this paper describes a SEU-fault injection technique based on a chain of parallel registers which reduces the time needed for injecting SEU faults as compared to the previous scan-based fault-injection techniques. As a case study, a 32-bit pipelined processor has been used in the fault injection experiments. The experimental results show that when a high degree of observability is required (e.g., error propagation analysis), the proposed fault injection technique is over 1166 times faster than simulation-based fault injection, whereas the traditional scan-based technique can achieve only a speedup of about 2–3 – which means that the proposed technique is about 500 times faster than the traditional scan-based technique. Such results are supported by theoretical performance analysis. This speed increase has been achieved without excessive increase in FPGA resource overhead, for example, the FPGA overhead of the proposed technique is only 2  3% higher than that of the traditional scan-based technique.     

A novel proposal for all-optical Galois field adder based on photonic crystals

In this paper we are going to propose an all-optical structure for implementing Galois field adder. To do so, we will use four optical XOR gates. The working principle of the proposed structure is based on destructive interference of optical waves. By choosing different lengths for the input waveguides, 180\(^\circ \) of phase difference will be generated between the optical waves. In the final structure, the normalized power for logic 0 and 1 at the output ports was 1 and 45%. Time delay of the proposed structure is about 1.5 ps.     

Hybrid FeNiOOH/α‐Fe2O3/Graphene Photoelectrodes with Advanced Water Oxidation Performance

In this study, the photoelectrochemical behavior of electrodeposited FeNiOOH/Fe₂O₃/graphene nanohybrid electrodes is investigated, which has precisely controlled structure and composition. The photoelectrode assembly is designed in a bioinspired manner where each component has its own function: Fe₂O₃ is responsible for the absorption of light, the graphene framework for proper charge carrier transport, while the FeNiOOH overlayer for facile water oxidation. The effect of each component on the photoelectrochemical behavior is studied by linear sweep photovoltammetry, incident photon‐to‐charge carrier conversion efficiency measurements, and long‐term photoelectrolysis. 2.6 times higher photocurrents are obtained for the best‐performing FeNiOOH/Fe₂O₃/graphene system compared to its pristine Fe₂O₃ counterpart. Transient absorption spectroscopy measurements reveal an increased hole‐lifetime in the case of the Fe₂O₃/graphene samples. Long‐term photoelectrolysis measurements in combination with Raman spectroscopy, however, prove that the underlying nanocarbon framework is corroded by the photogenerated holes. This issue is tackled by the electrodeposition of a thin FeNiOOH overlayer, which rapidly accepts the photogenerated holes from Fe₂O₃, thus eliminating the pathway leading to the corrosion of graphene.     

Embedded benzocyclobutene in silicon: An integrated fabrication process for electrical and thermal isolation in MEMS

This paper reports a novel fabrication process to develop planarized isolated islands of benzocyclobutene (BCB) polymer embedded in a silicon substrate. Embedded BCB in silicon (EBiS) can be used as an alternative to silicon dioxide in fabrication of electrostatic micromotors, microgenerators, and other microelectromechanical devices. EBiS takes advantage of the low dielectric constant and thermal conductivity of BCB polymers to develop electrical and thermal isolation integrated in silicon. The process involves conventional microfabrication techniques such as photolithography, deep reactive ion etching, and chemical mechanical planarization (CMP). We have characterized CMP of BCB polymers in detail since CMP is a key step in EBiS process. Atomic force microscopy (AFM) and elipsometry of blanket BCB films before and after CMP show that higher polishing down force pressure and speed lead to higher removal rate at the expense of higher surface roughness, non-uniformity, and scratch density. This is expected since BCB is a softer material compared to inorganic films such as silicon dioxide. We have observed that as the cure temperature of BCB increases beyond 200 °C, the CMP removal rate decreases drastically. The results from optical microscopy, scanning electron microscopy, and optical profilometry show excellent planarized surfaces on the EBiS islands. An average step height reduction of more than 95% was achieved after two BCB deposition and three CMP steps.     

An efficient method for impulse noise reduction from images using fuzzy cellular automata

Impulse noise reduction from corrupted images plays an important role in image processing. This problem will also affect on image segmentation, object detection, edge detection, compression, etc. Generally, median filters or nonlinear filters have been used for noise reduction but these methods will destroy the natural texture and important information in the image like the edges. In this paper, to eliminate impulse noises from noisy images, we used a hybrid method based on cellular automata (CA) and fuzzy logic called Fuzzy Cellular Automata (FCA) in two steps. In the first step, based on statistical information, noisy pixels are detected by CA; then using this information, the noisy pixel will change by FCA. Regularly, CA is used for systems with simple components where the behavior of each component will be defined and updated based on its neighbors. The proposed hybrid method is characterized as simple, robust and parallel which keeps the important details of the image effectively. The proposed approach has been performed on well-known gray scale test images and compared with other conventional and famous algorithms, is more effective.