Some new indexes of cluster validity

We review two clustering algorithms (hard c-means and single linkage) and three indexes of crisp cluster validity (Hubert's statistics, the Davies-Bouldin index, and Dunn's index). We illustrate two deficiencies of Dunn's index which make it overly sensitive to noisy clusters and propose several generalizations of it that are not as brittle to outliers in the clusters. Our numerical examples show that the standard measure of interset distance (the minimum distance between points in a pair of sets) is the worst (least reliable) measure upon which to base cluster validation indexes when the clusters are expected to form volumetric clouds. Experimental results also suggest that intercluster separation plays a more important role in cluster validation than cluster diameter. Our simulations show that while Dunn's original index has operational flaws, the concept it embodies provides a rich paradigm for validation of partitions that have cloud-like clusters. Five of our generalized Dunn's indexes provide the best validation results for the simulations presented.     

Processing of alumina and zirconia nano-powders and compacts

Magnesia–doped alumina and yttria–doped zirconia nano-powders were synthesized using sucrose as a chelating agent and template material from the aqueous solutions of aluminium nitrate, magnesium nitrate, ytrrium nitrate and zirconyl nitrate, respectively. Synthesis parameters were optimized with varying sucrose to metal ion ratio, calcinations time, and temperature to produce these nano-powders. As-synthesized powders were characterized by room temperature X-ray diffraction, BET surface area analyzer and transmission electron microscopy. Y₂O₃–ZrO₂ nano-powders had particle size in the range of 80–200 nm with specific average surface area of 119 m²/g and for MgO–Al₂O₃ powders, particle sizes were 30–200 nm with the specific average surface area of 250 m²/g. Our results indicate that this synthesis method is a versatile one and can be applied to a variety of oxide-based materials to form nano-powders. Nano-powders were compacted uniaxially and densified in a muffle furnace. Sintered discs were used for hardness testing and density measurements, as well as for microstructural characterization.     

Transmission electron microscopy and theoretical analysis of AuCu nanoparticles: atomic distribution and dynamic behavior

Though the application of bimetallic nanoparticles is becoming increasingly important, the local atomistic structure of such alloyed particles, which is critical for tailoring their properties, is not yet very clearly understood. In this work, we present detailed study on the atomistic structure of Au-Cu nanoparticles so as to determine their most stable configurations and the conditions for obtaining clusters of different structural variants. The dynamic behavior of these nanoparticles upon local heating is investigated. AuCu nanoparticles are characterized by high resolution transmission electron microscopy (HRTEM) and energy filtering elemental composition mapping (EFECM), which allowed us to study the internal structure and the elemental distribution in the particles. Quantum mechanical approaches and classic molecular dynamics methods are applied to model the structure and to determine the lowest energy configurations, the corresponding electronic structures, and understand structural transition of clusters upon heating, supported by experimental evidences. Our theoretical results demonstrate only the core/shell bimetallic structure have negative heat of formation, both for decahedra and octahedral, and energetically favoring core/shell structure is with Au covering the core of Cu, whose reverse core/shell structure is not stable and may transform back at a certain temperature. Experimental evidences corroborate these structures and their structural changes upon heating, demonstrating the possibility to manipulate the structure of such bimetallic nanoparticles using extra stimulating energy, which is in accordance with the calculated coherence energy proportions between the different configurations.     

Effect of shielding gas mixture on gas metal arc welding of HSLA steel using solid and flux-cored wires

In this work, gas metal arc welding of high strength-low alloy (HSLA) steel with solid- and flux-cored arc welding wires using different shielding gas compositions was performed. The composition of filler wire and shielding gas in gas metal arc welds of HSLA steel determines the inclusion characteristics, microstructure and mechanical properties. Thus, acceptable weld metal properties in HSLA steel using gas metal arc welding (GMAW) process could be achieved with the proper combination of filler wire and shielding gas composition.     

Flexible diamond-like carbon films on rubber: Friction and the effect of viscoelastic deformation of rubber substrates

This paper focuses on the frictional behavior of flexible diamond-like carbon (DLC) film-coated hydrogenated nitrile butadiene rubber. By making use of the substantial thermal mismatch between DLC film and rubber substrate, a dense network of cracks forms in the DLC films and contributes to flexibility. The influence of the size of DLC film microsegments on the frictional performance is studied. The effect of viscoelasticity of the rubber substrate on the frictional behavior of the DLC film-coated system is scrutinized by tribo-tests and theoretical analysis. The importance of adhesive and hysteresis contributions to friction is revealed, and an overarching model is presented.     

Optimization of friction stir welding process using NSGA-II and DEMO

In welding processes, the selection of optimal process parameter settings is very important to achieve best weld qualities. In this work, neuro-multi-objective evolutionary algorithms (EAs) are proposed to optimize the process parameters in friction stir welding process. Artificial neural network (ANN) models are developed for the simulation of the correlation between process parameters and mechanical properties of the weld using back-propagation algorithm. The weld qualities of the weld joint, such as ultimate tensile strength, yield stress, elongation, bending angle and hardness of the nugget zone, are considered. In order to optimize those quality characteristics, two multi-objective EAs that are non-dominated sorting genetic algorithm II and differential evolution for multi-objective are coupled with the developed ANN models. In the end, multi-criteria decision-making method which is technique for order preference by similarity to the ideal solution is applied on the Pareto front to extract the best solutions. Comparisons are conducted between results obtained from the proposed techniques, and confirmation experiments are performed to verify the simulated results.

     

Visualization of Babble–Speech Interactions Using Andrews Curves

Visualizing multidimensional data such as the mel frequency cepstral coefficients (MFCCs) proves difficult, especially when the number of dimensions is greater than 3. As a result, it becomes extremely difficult to spot trends in high-dimensional signal interactions. Andrews curves seam to aid in the process of performing graphical analysis of high-dimensional data. This study examines the properties of the babble in the feature domain as well as the effect of the babble noise on the MFCCs of clean speech. Experiments have been conducted using two babble models: the overlapping conversation model and the overlapping speaker model. The purpose of this paper was to provide an insight into the effect of the babble noise on the first thirteen MFCCs of clean speech through the use of Andrews curves. The investigations of this paper give a visual comparison of the signals to expose trends, which the conventional visualization methods do not. The use of Andrews curves not only allows the signal to be observed, but also allows for a statistical comparisons between signals. With a better understanding of the difference between the models, it would be possible to develop systems, which are more robust in babble-corrupted environment.     

Dextrin crosslinked with poly(lactic acid): A novel hydrogel for controlled drug release application

A new class of biodegradable crosslinked hydrogel, consisting of hydrophobic polylactic acid (PLA) and hydrophilic dextrin in presence of crosslinker N,N‐methylene bisacrylamide (MBA) has been synthesized by free‐radical polymerization technique using potassium persulfate (KPS) as initiator. By variation of crosslinker concentration, a series of hydrogels have been prepared and the optimized grade has been selected on the basis of higher crosslinking efficiency as well as lower equilibrium swelling characteristics, XRD analysis. The hydrogels have been characterized by FTIR spectra, ¹³C‐NMR spectra, CHN analysis, SEM analysis, swelling characteristics, and toxicity study. In vitro release study of model drugs (ciprofloxacin and ornidazole) from hydrogel matrix has been performed in various buffer solutions at 37°C. The drug release kinetics and mechanism have been studied using zero order, first‐order kinetic models, Korsemeyar–Peppas model, Higuchi model, Hixson–Crowell model, and nonlinear Kopcha model. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40039.     

Optimizing roller operation in the 5000 mill at OAO MMK

Since 2009, numerous failures of the working rollers in the 5000 mill at OAO MMK have been observed, on account of fracture of the drive pins. Efforts to resolve this problem are described.