Scalable satisfiability checking and test data generation from modeling diagrams

We explore the automatic generation of test data that respect constraints expressed in the Object-Role Modeling (ORM) language. ORM is a popular conceptual modeling language, primarily targeting database applications, with significant uses in practice. The general problem of even checking whether an ORM diagram is satisfiable is quite hard: restricted forms are easily NP-hard and the problem is undecidable for some expressive formulations of ORM. Brute-force mapping to input for constraint and SAT solvers does not scale: state-of-the-art solvers fail to find data to satisfy uniqueness and mandatory constraints in realistic time even for small examples. We instead define a restricted subset of ORM that allows efficient reasoning yet contains most constraints overwhelmingly used in practice. We show that the problem of deciding whether these constraints are consistent (i.e., whether we can generate appropriate test data) is solvable in polynomial time, and we produce a highly efficient (interactive speed) checker. Additionally, we analyze over 160 ORM diagrams that capture data models from industrial practice and demonstrate that our subset of ORM is expressive enough to handle their vast majority.     

A genetic algorithm-based artificial neural network model for the optimization of machining processes

Artificial intelligent tools like genetic algorithm, artificial neural network (ANN) and fuzzy logic are found to be extremely useful in modeling reliable processes in the field of computer integrated manufacturing (for example, selecting optimal parameters during process planning, design and implementing the adaptive control systems). When knowledge about the relationship among the various parameters of manufacturing are found to be lacking, ANNs are used as process models, because they can handle strong nonlinearities, a large number of parameters and missing information. When the dependencies between parameters become noninvertible, the input and output configurations used in ANN strongly influence the accuracy. However, running of a neural network is found to be time consuming. If genetic algorithm-based ANNs are used to construct models, it can provide more accurate results in less time. This article proposes a genetic algorithm-based ANN model for the turning process in manufacturing Industry. This model is found to be a time-saving model that satisfies all the accuracy requirements.     

Curvature and entropy based wall boundary condition for the high order spectral volume Euler solver

A curvature and entropy based wall boundary condition is implemented in the high order spectral volume (SV) context. This method borrows ideas from the “curvature-corrected symmetry technique” developed by (Dadone A, Grossman B. Surface Boundary Conditions for Compressible Flows. AIAA J 1994; 32(2): 285–93), for a low order structured grid Euler solver. After numerically obtaining the curvature, the right state (by convention, the left state is inside the computational domain and the right state lies outside of the computational domain) face pressure values are obtained by solving a linearised system of equations. This is unlike that of the lower order finite volume and difference simulations, wherein the right state face values are trivial to obtain. The right state face density values are then obtained by enforcing entropy conservation. Accuracy studies show that simulations performed by employing the new boundary conditions deliver much more accurate results than the ones which employ traditional boundary conditions, while at the same time asymptotically reaching the desired order of accuracy. Numerical results for two-dimensional inviscid flows around the NACA0012 airfoil and over a bump with the new boundary condition showed dramatic improvements over those with the conventional approach. In all cases and orders, spurious entropy productions with the new boundary treatment are significantly reduced. In general, the numerical results are very promising and indicate that the approach has a great potential for 3D high order simulations.     

Influence ofβ-cyclodextrin as an encapsule and as an inclusion complex dopant on conducting polyaniline

An investigation on the effect ofβ-cyclodextrin (CD) in both free and inclusion-complexed forms with a guest anionic metal complex, dioxalatodiaquochromate(III) (DDC), on the characteristics of conducting polyaniline (PANI) is carried out. Four materials, PANI (i.e. PANI-SO ₄ ²⁻ ), PANI-DDC, PANI-CD and PANI-CD + DDC were prepared byin situ chemical oxidative polymerization in aqueous H ₂SO₄ at pH 1 and subjected to electrical conductivity and spectral (IR and UV-vis bd measurements. DDC and CD when separately incorporated, reduce the conductivity of PANI by about half whilst their inclusion complex CD + DDC enhances it. Spectral characterization reveals that DDC as a dopant and CD as an encapsule exhibit their effects through adverse interaction with imine-amine N centres and benzenoid moiety of PANI. The inclusion complex CD + DDC, on the contrary, functions as a dopant by lying in between the chains and seems to promote the extended conformation of PANI chain and hence theπ -electron delocalization. Exposure of the material to methanol vapour causes a decrease in conductivity in PANI and PANI-CD while an increase in PANI-CD + DDC. This study makes explicit the distinct role of CD as an encapsule and CD + DDC inclusion complex as a dopant in altering the electrical property of PANI.     

Query Optimization in Multidatabase Systems

Global query execution in a multidatabase system can be done parallelly, as all the local databases are independent. In this paper, a cost model that considers parallel execution of subqueries for a global query is developed. In order to obtain maximum parallelism in query execution, it is required to find a query execution plan that is represented in the form of a bushy tree and this query tree should be balanced to the maximal possible extent with respect to execution time. A new bottom up approach called Agglomerative Approach (AA) is proposed to construct balanced bushy trees with respect to execution time. By the deterministic nature of this approach, it generates local optimal solutions. This local minima problem will be severe in the case of graph queries, i.e., queries that are represented with a graph structure. A Simulated annealing Approach (SA) is employed to obtain a (near) optimal solution. These approaches (AA and SA) are suitable for handling on-line and off-line queries respectively. A Hybrid Approach (HA), that is an integration of AA and SA, is proposed to optimize queries for which the estimated time to be spent on optimization is known a priori. Results obtained with AA and SA on both tree and graph structured queries are presented.     

Cryo-X-ray analysis-A novel tool to better understand the physicochemical reactions at the bioglass/biological fluid interface

The present study deals with the short-term physicochemical reactions at the interface between bioactive glass particles [55SiO(2)-20CaO-9P(2)O(5)-12Na(2)O-4MgO. mol%] and biological fluid (Dulbecco Modified Eagle's Medium (DMEM)). The physicochemical reactions within the interface are characterized by scanning transmission electron microscopy (TEM) (STEM) associated with Energy-dispersive X-ray spectroscopy (EDXS). Microanalysis of diffusible ions such as sodium, potassium, or oxygen requires a special care. In the present investigation the cryo-technique was adopted as a suitable tool for the specimen preparation and characterization. Cryosectioning is essential for preserving the native distribution of ions so that meaningful information about the local concentrations can be obtained by elemental microanalysis. The bioglass particles immersed in biological fluid for 24 h revealed five reaction stages: (i) dealkalization of the surface by cationic exchange (Na(+), Ca(2+) with H(+) or H(3)O(+)); (ii) loss of soluble silica in the form of Si(OH)(4) to the solution resulting from the breakdown of Si--O--Si bonds (iii); repolymerization of Si(OH)(4) leading to condensation of SiO(2)); (iv) migration of Ca(2+) and PO(4) (3-) to the surface through the SiO(2)-rich layer to form CaO-P(2)O(5) film; (v) crystallization of the amorphous CaO-P(2)O(5) by incorporating OH-- or CO(3) (2-) anions with the formation of three different surface layers on the bioactive glass periphery. The thickness of each layer is approximately 300 nm and from the inner part to the periphery they consist of Si--OH, which permits the diffusion of Ca(2+) and PO(4) (3-) ions and the formation of the middle Ca--P layer, and finally the outer layer composed of Na--O, which acts as an ion exchange layer between Na(+) ions and H(+) or H(3)O(+) from the solution.     

Dealloying corrosion of anodic and nanometric Mg41Nd5 in solid solution-treated Mg-3Nd-1Li-0.2Zn alloy

The microstructure and chemical compositions of the solid solution-treated Mg-3Nd-1Li-0.2Zn alloy were characterized using optical microscope,scanning electron microscope(SEM),transmission electron microscope(TEM),electron probe micro-analyzer(EPMA)and X-ray photoelectron spectroscopy(XPS).The corrosion behaviour of the alloy was investigated via electrochemical polarization,electrochemical impedance spectroscopy(EIS),hydrogen evolution test and scanning Kelvin probe(SKP).The results showed that the microstructure of the as-extruded Mg-3Nd-1Li-0.2Zn alloy contained α-Mg matrix and nanometric second phase Mg41 Nd5.The grain size of the alloy increased significantly with the increase in the heat-treatment duration,whereas the volume fraction of the second phase decreased after the solid solution treatment.The surface film was composed of oxides(Nd2O3,MgO,Li2O and ZnO)and carbonates(MgCO3 and Li2CO3),in addition to Nd.The as-extruded alloy exhibited the best corrosion resistance after an initial soaking of 10 min,whereas the alloy with 4h-solution-treatment possessed the lowest corrosion rate after a longer immersion(1 h).This can be attributed to the formation of Nd-containing oxide film on the alloys and a dense corrosion product layer.The dealloying corrosion of the second phase was related to the anodic Mg41Nd5 with a more negative Volta potential relative to α-Mg phase.The preferential corrosion of Mg41Nd5 is proven by in-situ observation and SEM.The solid solution treatment of Mg-3Nd-1Li-0.2Zn alloy led to a shift in corrosion type from pitting corrosion to uniform corrosion under long-term exposure.     

Tumor detection in T1, T2, FLAIR and MPR brain images using a combination of optimization and fuzzy clustering improved by seed‐based region growing algorithm

Tumor and Edema region present in Magnetic Resonance (MR) brain image can be segmented using Optimization and Clustering merged with seed‐based region growing algorithm. The proposed algorithm shows effectiveness in tumor detection in T1 ‐ w, T2 – w, Fluid Attenuated Inversion Recovery and Multiplanar Reconstruction type MR brain images. After an initial level segmentation exhibited by Modified Particle Swarm Optimization (MPSO) and Fuzzy C – Means (FCM) algorithm, the seed points are initialized using the region growing algorithm and based on these seed points; tumor detection in MR brain images is done. The parameters taken for comparison with the conventional techniques are Mean Square Error, Peak Signal to Noise Ratio, Jaccard (Tanimoto) index, Dice Overlap indices and Computational Time. These parameters prove the efficacy of the proposed algorithm. Heterogeneous type tumor regions present in the input MR brain images are segmented using the proposed algorithm. Furthermore, the algorithm shows augmentation in the process of brain tumor identification. Availability of gold standard images has led to the comparison of the suggested algorithm with MPSO‐based FCM and conventional Region Growing algorithm. Also, the algorithm recommended through this research is capable of producing Similarity Index value of 0.96, Overlap Fraction value of 0.97 and Extra Fraction value of 0.05, which are far better than the values articulated by MPSO‐based FCM and Region Growing algorithm. The proposed algorithm favors the segmentation of contrast enhanced images. © 2017 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 27, 33–45, 2017     

Random 3-SAT: The Plot Thickens

This paper presents an experimental investigation of the following questions: how does the average-case complexity of random 3-SAT, understood as a function of the order (number of variables) for fixed density (ratio of number of clauses to order) instances, depend on the density? Is there a phase transition in which the complexity shifts from polynomial to exponential in the order? Is the transition dependent or independent of the solver? Our experiment design uses three complete SAT solvers embodying different algorithms: GRASP, CPLEX, and CUDD. We observe new phase transitions for all three solvers, where the median running time shifts from polynomial in the order to exponential. The location of the phase transition appears to be solver-dependent. GRASP shifts from polynomial to exponential complexity near the density of 3.8, CPLEX shifts near density 3, while CUDD exhibits this transition between densities of 0.1 and 0.5. This experimental result underscores the dependence between the solver and the complexity phase transition, and challenges the widely held belief that random 3-SAT exhibits a phase transition in computational complexity very close to the crossover point.     

A simple finite-difference frequency-domain (FDFD) algorithm for analysis of switching noise in printed circuit boards and packages

Simultaneous switching noise (SSN) compromises the integrity of the power distribution structure on multilayer printed circuit boards (PCB). Several methods have been used to investigate SSN. These methods ranged from simple lumped circuit models to full-wave (dynamic) three-dimensional Maxwell equations simulators. In this work, we present an efficient and simple finite-difference frequency-domain (FDFD) based algorithm that can simulate, with high accuracy, the capacity of a PCB board to introduce SSN. The FDFD code developed here also allows for simulation of real-world decoupling capacitors that are typically used to mitigate SSN effects at sub 1 GHz frequencies. Furthermore, the algorithm is capable of including lumped circuit elements having user-specified complex impedance. Numerical results are presented for several test boards and packages, with and without decoupling capacitors. Validation of the FDFD code is demonstrated through comparison with other algorithms and laboratory measurements.