An adaptive region segmentation combining surrogate model applied to correlate design variables and performance parameters in a transonic axial compressor

Surrogate models have been widely applied to correlate design variables and performance parameters in turbomachinery optimization applications. With more design variables and uncertain factors taken into account in an optimization design problem, the mathematical relations between the design variables and the performance parameters might present linear, low-order nonlinear or even high-order nonlinear characteristics, and are usually analytically unknown. Therefore, it is required that surrogate models have high adaptability and prediction accuracy for both the linear and nonlinear characteristics. The paper mainly investigates the effectiveness of an adaptive region segmentation combining surrogate model based on support vector regression and kriging model applied to a transonic axial compressor to approximate the complicated relationships between geometrical variables and objective performance outputs with different sampling methods and sizes. The purpose is to explore the prediction accuracy and computational efficiency of this adaptive surrogate model in real turbomachinery applications. Three different sampling techniques are studied: (1) uniform design; (2) Latin hypercube sampling method; (3) Sobol quasi-random design. For the low dimensional case with five variables, the adaptive region segmentation combining surrogate model performs better (not worse) than the single component surrogate in terms of prediction accuracy and computational efficiency. In the meanwhile, it is also noted that the uniform design applied to the adaptive surrogate model has more advantages over the Latin hypercube sampling method especially for the small sample size cases, both performing better than the Sobol quasi-random design. Moreover, a high dimensional case with 12 variables is also utilized to further validate the prediction advantage of the adaptive region segmentation combining surrogate model over the single component surrogate, and the computational results favor it. Overall, the adaptive region segmentation combining surrogate model has produced acceptable to high prediction accuracy in presenting complex relationships between the geometrical variables and the objective performance outputs and performed robustly for a transonic axial compressor problem.

     

Negation as Failure as Resolution

Providing a clean procedural semantics of the Negation As Failure rule in Logic Programming has been an open problem for some time now. This rule has been treated as a technique in nonmonotonic reasoning, not as a rule in classical logic. This paper contains a demonstration of the negation as failure rule as a resolution procedure in first-order logic. We present a sound and complete resolution scheme for negation as failure rule for the larger class of constraint logic programs. The approach is to consider a canonical partition of the completion of a definite (constraint) program into the IF and the FI programs. We show that a negated goal, provable from the completed definite program is provable from just the FI part. The clauses in this program have a structure dual to that of definite Horn clauses. We describe a sound and complete linear resolution rule for this fragment, and show that a resolution proof of the negated goal from the FI part corresponds to a finite failure tree resulting from classical linear resolution applied to the goal on the If part of the original definite program. Our work shows that negation as failure rule can be computationally efficient in the sense that the SLD-resolution on the If part of a definite program along with the negation as failure rule is more efficient than a direct resolution procedure on the completion of that program.     

Selection of optimized features for fusion of palm print and finger knuckle‐based person authentication

The impact of digital technology in biometrics is much more efficient at interpreting data than humans, which results in completely replacement of manual identification procedures in forensic science. Because the single modality‐based biometric frameworks limit performance in terms of accuracy and anti‐spoofing capabilities due to the presence of low quality data, therefore, information fusion of more than one biometric characteristic in pursuit of high recognition results can be beneficial. In this article, we present a multimodal biometric system based on information fusion of palm print and finger knuckle traits, which are least associated to any criminal investigation as evidence yet. The proposed multimodal biometric system might be useful to identify the suspects in case of physical beating or kidnapping and establish supportive scientific evidences, when no fingerprint or face information is present in photographs. The first step in our work is data preprocessing, in which region of interest of palm and finger knuckle images have been extracted. To minimize nonuniform illumination effects, we first normalize the detected circular palm or finger knuckle and then apply line ordinal pattern (LOP)‐based encoding scheme for texture enrichment. The nondecimated quaternion wavelet provides denser feature representation at multiple scales and orientations when extracted over proposed LOP encoding and increases the discrimination power of line and ridge features. To best of our knowledge, this first attempt is a combination of backtracking search algorithm and 2D²LDA has been employed to select the dominant palm and knuckle features for classification. The classifiers output for two modalities are combined at unsupervised rank level fusion rule through Borda count method, which shows an increase in performance in terms of recognition and verification, that is, 100% (correct recognition rate), 0.26% (equal error rate), 3.52 (discriminative index), and 1,262 m (speed).     

Strength evaluation of granite block samples with different predictive models

Over the last decade, application of soft computing techniques has rapidly grown up in different scientific fields, especially in rock mechanics. One of these cases relates to indirect assessment of uniaxial compressive strength (UCS) of rock samples with different artificial intelligent-based methods. In fact, the main advantage of such systems is to readily remove some difficulties arising in direct assessment of UCS, such as time-consuming and costly UCS test procedure. This study puts an effort to propose four accurate and practical predictive models of UCS using artificial neural network (ANN), hybrid ANN with imperialism competitive algorithm (ICA–ANN), hybrid ANN with artificial bee colony (ABC–ANN) and genetic programming (GP) approaches. To reach the aim of the current study, an experimental database containing a total of 71 data sets was set up by performing a number of laboratory tests on the rock samples collected from a tunnel site in Malaysia. To construct the desired predictive models of UCS based on training and test patterns, a combination of several rock characteristics with the most influence on UCS has been used as input parameters, i.e. porosity (n), Schmidt hammer rebound number (R), p-wave velocity (V_p) and point load strength index (Is(50)). To evaluate and compare the prediction precision of the developed models, a series of statistical indices, such as root mean squared error (RMSE), determination coefficient (R²) and variance account for (VAF) are utilized. Based on the simulation results and the measured indices, it was observed that the proposed GP model with the training and test RMSE values 0.0726 and 0.0691, respectively, gives better performance as compared to the other proposed models with values of (0.0740 and 0.0885), (0.0785 and 0.0742), and (0.0746 and 0.0771) for ANN, ICA–ANN and ABC–ANN, respectively. Moreover, a parametric analysis is accomplished on the proposed GP model to further verify its generalization capability. Hence, this GP-based model can be considered as a new applicable equation to accurately estimate the uniaxial compressive strength of granite block samples.

     

Isolation enhancement between tightly spaced compact unidirectional patch‐antennas on multilayer EBG surfaces

In this article, ultracompact unidirectional patch antennas are used in different two‐antenna systems for biomedical applications at 5.2 GHz. Multilayer mushroom type electromagnetic bandgap (EBG) structures are designed as slow‐wave medium to reduce the size of the individual patch antennas to 0.1λ₀ by 0.18λ₀. Various techniques are investigated herein to improve antenna isolation for an enhanced Multiple‐Input Multiple‐Output (MIMO) performance. First, the coupling between 0.3λ₀‐spaced antennas is verified to occur dominantly through radiation and near‐field coupling between the patches rather than through substrate‐bound modes. Second, various configurations are proposed to suppress antenna coupling. These approaches include reorientation of the antennas and employment of parasitic radiators between the patches. A novel design is presented in which a unidirectional parasitic slot radiator on an EBG reflector is inserted between the antennas to decouple them. Measurement results confirm efficacy of these approaches in mitigating antenna coupling by more than 11 dB in the operating bandwidth of the antennas. The compact patch antennas maintain efficiency values of higher than 70%. © 2014 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:30–38, 2015.     

Application of Fuzzy Logic to Estimate Flow of Methane for Energy Generation at a Sanitary Landfill

This paper proposes the use of a multicriteria assessment technique to evaluate the methane flow during gas extraction from a sanitary landfill. A number of parameters determine the gas generation and the feasibility for its extraction from a landfill. These parameters form a complex set of information with unknown mathematical interrelationships making potential gas flow evaluations difficult and elusive. In addition, the data available for a particular landfill are very often imprecise, uncertain, or subjective, making it even more difficult to evaluate the potential for gas extraction without conducting pilot tests. The method proposed in this paper uses fuzzy composite programming that allows for the use of imprecise information. A landfill gas potential index has been defined, which can be determined by easily obtainable climatological, geological, and landfill parameters. The landfill gas (LFG) potential index is related to the landfill gas flow using an empirical equation. The LFG potential model was calibrated and verified using data obtained from 61 landfills where gas extraction is being conducted. A sensitivity analysis was done to study the impact of variations in the input data on model output.     

Boundary-layer flow of the power-law fluid over a moving wedge: a linear stability analysis

We study the stability of the two-dimensional boundary-layer flow of a power-law (Ostwald de Waele) non-Newtonian fluid over a moving wedge. The mainstream velocity is assumed to have a power of distance from the leading boundary layer, such that the system admits to the self-similar solutions. We discuss the problem in question for both shear-thickening and shear-thinning fluids which lead to a non-uniqueness (double solutions) in the base flow solutions. We then address an issue of the stability of the non-unique solutions. A linear eigenvalue analysis of the double solution reveals that the basic flow represented by the first solution is always stable, and this flow is practically encountered. The system becomes unstable to the second solutions which have the mode-two perturbations with larger boundary-layer thickness. The first and second solutions form a tongue-like structure in the solution space. Furthermore, the modification of the viscosity for the power-law fluids reveals that the system predicts an infinite viscosity in the confinement of the boundary-layer region. Extensive comparisons of the solutions with the existing models with Newtonian fluid are made, and a physical explanation behind these solutions is proposed.

     

SOL: A Verifiable Synchronous Language for Reactive Systems

SOL (Secure Operations Language) is a synchronous programming language for implementing reactive systems. The utility of SOL hinges upon the fact that it is a secure language, i.e., most programs in SOL are amenable to fully automated static analysis techniques, such as automatic theorem proving using decision procedures or model checking. Among the unique features of SOL is the ability to express a wide class of enforceable safety and security policies (including the temporal aspects of software component interfaces) in the language itself, thereby opening up the possibility of eliminating runaway computations and malicious code, such as worms and viruses.     

Agile Spectrum Imaging: Programmable Wavelength Modulation for Cameras and Projectors

We advocate the use of quickly‐adjustable, computer‐controlled color spectra in photography, lighting and displays. We present an optical relay system that allows mechanical or electronic color spectrum control and use it to modify a conventional camera and projector. We use a diffraction grating to disperse the rays into different colors, and introduce a mask (or LCD/DMD) in the optical path to modulate the spectrum. We analyze the trade‐offs and limitations of this design, and demonstrate its use in a camera, projector and light source. We propose applications such as adaptive color primaries, metamer detection, scene contrast enhancement, photographing fluorescent objects, and high dynamic range photography using spectrum modulation.     

The effect of copper oxide on sintering, microstructure, mechanical properties and hydrothermal ageing of coated 2.5Y-TZP ceramics

Copper oxide dopants in amounts up to 1 wt% were added to 2.5 mol% yttria-coated zirconia powders in studies of sintering, microstructure, mechanical properties and hydrothermal ageing behaviour. High densities (>6 Mgm^–3), high tetragonal phase content (>95%), and phenomenal fracture toughness values (>17 MPam^1/2), were obtained for lower dopant levels. Grain sizes of 0.13 to 0.25 m were measured for all samples sintered at 1300°C. Rounded pores in some doped samples indicated that a liquid phase was involved during sintering. Copper oxide additions aid low temperature sintering and offer potential for property enhancement with a particularly high toughness being measured as well as improving resistance to structural degradation in 180°C hydrothermal ageing.