Modified stable Euler-number algorithm implementation for real-time image binarization

The stable Euler-number-based image binarization has been shown to give excellent visual results for images containing high amount of image noise. Being computationally expensive, its applications are limited mostly to general-purpose processors and in application specific integrated circuits. In this paper a modified stable Euler-number-based algorithm for image binarization is proposed and its real-time hardware implementation in a Field Programmable Gate Array with a pipelined architecture is presented. The proposed modifications to the algorithm facilitate hardware implementation. The end result is a design that out-performs known software implementations. The amount of noisy pixels introduced during the binarization process is also minimized. Despite the stable Euler-number-based image binarization being computationally expensive, our simulations show that the proposed architecture gives accurate results and this in real time and without consuming all chip resources.     

An integrated approach for groundwater potential zoning in shallow fracture zone aquifers

This study presents an integrated approach for the identification of groundwater occurrences in shallow fracture zone (SFZ) aquifers using remote-sensing, geological, and geophysical data. The Central Eastern Desert of Egypt was selected as a test site for the present study. The distribution of major faults and shear zones was extracted from a fusion image generated by injecting high-spatial resolution phased array L-band synthetic aperture radar (PALSAR) images into Landsat Enhanced Thematic Mapper images. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) digital elevation model was processed to extract the drainage systems, slope, and topographic wetness index (TWI). The multidate PALSAR imagery acquired during rainy and dry seasons was used to estimate the relative soil moisture content. The lithology, fractures, drainage density, slope, TWI, and soil moisture content were used as thematic layers for groundwater occurrence in the SFZ aquifers. A GIS model of groundwater potential was developed by selecting the most probable locations for groundwater in each layer. The results indicate that the spatial distribution of the existing water wells is in agreement with the model where all wells fall in the regions of high groundwater potential zones. A geophysical survey was conducted using ground penetrating radar (GPR), indicating that the high groundwater potential zones are promising for drilling shallow wells. The adopted approach can be used as a cost-effective tool for groundwater exploration in the SFZ aquifers in the study area and in areas of similar geologic and hydrogeologic settings elsewhere.     

Thermal induced transformations in glassy chalcogenides SixTe60−xAs30Ge10

Temperature-induced transformations are considered to be interesting characteristic properties of amorphous materials including the Si _x Te_60–x As₃₀Ge₁₀ system, withx=5, 10, 12 and 20. Density (), X-ray diffraction and differential thermal analysis (DTA) were used to characterize the compositions. DTA traces of each glass composition at different heating rates from 5 to 30° C min^–1 were obtained and interpreted. Fast and slow cooling cycles were used to determine the rate of structure formation. Cycling studies of materials show no memory effect but only ovonic switching action. The compositional dependence of the crystallization activation energy (E) and the coefficient of glass-forming tendency (K _gl) have been calculated. The thermal transition temperatures and associated changes in specific heat have been examined as a function of the Te/Si ratio by differential scanning calorimetry. It was found that andE increase linearly with increasing tellurium content, while the heat capacity (c _p) andK _gl, decrease with increasing tellurium content.E=1.54 eV andc _p=0.246 J g^–1 K^–1 forx=20 whileE=2.74eV andc _p=0.22 J g^–1 K^–1 forx=5.     

Parallel implementation of the Kronecker product technique for numerical solution of parabolic partial differential equations

Using the alternating directional Galerkin technique we show that the approximate solution of the initial boundary value problem of parabolic partial differential equations is equivalent to the least squares solution of the linear system A B = b. In the full rank case, an efficient method for obtaining the solution of the least squares problem suitable for distributive memory computers was presented in (Fausett et al., 1994). This method is extended to solve the rank deficient case using the RRQR factorization of matrices A and B together with the commutatively property of the Kronecker product. Solution algorithm and parallel implementation are discussed. Timing results are presented and compared with previous work.     

Deep Multimodal Fusion: A Hybrid Approach

We propose a novel hybrid model that exploits the strength of discriminative classifiers along with the representation power of generative models. Our focus is on detecting multimodal events in time varying sequences as well as generating missing data in any of the modalities. Discriminative classifiers have been shown to achieve higher performances than the corresponding generative likelihood-based classifiers. On the other hand, generative models learn a rich informative space which allows for data generation and joint feature representation that discriminative models lack. We propose a new model that jointly optimizes the representation space using a hybrid energy function. We employ a Restricted Boltzmann Machines (RBMs) based model to learn a shared representation across multiple modalities with time varying data. The Conditional RBMs (CRBMs) is an extension of the RBM model that takes into account short term temporal phenomena. The hybrid model involves augmenting CRBMs with a discriminative component for classification. For these purposes we propose a novel Multimodal Discriminative CRBMs (MMDCRBMs) model. First, we train the MMDCRBMs model using labeled data by training each modality, followed by training a fusion layer. Second, we exploit the generative capability of MMDCRBMs to activate the trained model so as to generate the lower-level data corresponding to the specific label that closely matches the actual input data. We evaluate our approach on ChaLearn dataset, audio-mocap, as well as the Tower Game dataset, mocap-mocap as well as three multimodal toy datasets. We report classification accuracy, generation accuracy, and localization accuracy and demonstrate its superiority compared to the state-of-the-art methods.     

Non-linear diffusion of image noise with minimal iterativity

Non-linear diffusion (ND) is an iterative difference equation used in several image processing applications such as denoising, segmentation, or compression. The number of iterations required to achieve optimal processing can be very high, making ND not suitable for real-time requirements. In this paper, we study how to reduce complexity of ND so as to achieve minimal number of iterations for real-time image denoising. To do this, we first study the relations between parameters of the iterative equation: the number of iterations, the time step, and the edge strength. We then proceed by estimating the minimally required number of iterations to achieve effective denoising. Then, we relate the edge strength to the number of iterations, to noise, and to the image structure. The resulted minimal iterativity ND is very fast, while still achieves similar or better noise reduction compared to related ND work. This paper also shows how the proposed spatial filter is suitable for structure-sensitive object segmentation and temporal noise reduction.     

Conformance testing in systems with semicontrollable interfaces

In a conformance testing environment, an implementation under test (iut) communicates with multiple entities. A tester may have differing degrees of control on the interactions between these entities and the iut : directly controllable, semicontrollable, or uncontrollable. Semi-controllable inputs most likely render portions of an IUT untestable. In addition, multiple communicating entities may create race conditions during testing. This paper presents a test generation methodology for systems where the semicontrollable inputs can be generated indirectly. The test sequences obtained from the converted graph fully utilize the semicontrollable inputs (where possible) while avoiding the race conditions. Although, for the most general case, the graph conversion results in a exponentially large number of nodes, practical considerations make the converted graph size feasible. This approach is used to generate tests for mil-std 188-220B. By applying the proposed graph conversion and the race condition elimination techniques, the number of testable state transitions increased from approximately 200 to over 700, which represents a coverage of 95% of the transitions defined in the specification.     

MOF-derived bimetallic NiCo nanoalloys for the hydrogenation of biomass-derived levulinic acid to γ-valerolactone

The selective hydrogenation of biomass-derived levulinic acid (LA) to γ-valerolactone (GVL) is one of pivotal reactions in many of the biorefinery schemes for the production of value-added chemicals and biofuels. Herein, we have fabricated carbon-supported bimetallic NiCo catalysts based on the metal–organic framework (MOF) material via a pyrolysis method. The as-obtained Ni₁Co₁ bimetallic catalyst outperforms monometallic counterparts in the catalytic performance of LA-to-GVL, with a nearly full conversion of LA and a GVL yield of 95.2%, in particular with an excellent catalyst stability up to seven consecutive runs at 160°C and 4 MPa H₂. Based on a combined characterization study by employing advanced techniques, for example, extended x-ray absorption fine structure (EXAFS), high-angle annular dark-field scanning transmission electron microscopy (HADDF-STEM), and electron paramagnetic resonance (EPR), we reveal that the enhanced catalytic performance, in particular the excellent stability, could be attributed to the formation of the bimetallic alloys, which efficiently alleviates the metal leaching and sintering during catalysis.     

Simultaneously achievement of high recoverable energy density and efficiency in sodium niobate-based ceramics

Journal of Materials Science: Materials in Electronics - Single lead-free Na0.73Bi0.09(Nb1???xTax)O3 (x?=?0, 0.10, 0.20, 0.30, and 0.40) ceramic phases were processed...