Hard boron rich boron nitride nanoglasses

Boron‐rich amorphous boron nitride (B_xN_1?x, 0.55 ≤ x ≤ 0.95) alloys are generated by means of ab initio molecular dynamics simulations and their local structure, mechanical properties and electronic structure are exposed. BN:B phase separations are perceived in all amorphous networks, suggesting that these materials can serve as nanoglass ceramics. The sp² hybridization is the main building unit in the BN‐rich regions for low boron concentrations, and the models carry locally the signature of the two‐dimensional hexagonal BN structure. The amorphous states having both sp² and sp³ hybridizations form for boron contents between 70% and 80%. At higher boron concentrations, sp³ hybridization with a fraction of ~90%‐98% is detected as seen in the cubic or wurtize BN crystals. In the boron rich regions, the ideal and defective pentagonal pyramids emerge at 60% boron content, and the first complete B₁₂ molecule develops at 70% boron concentration. In addition to the B₁₂ icosahedron, the formation of a cage‐like B₁₆ molecule is, for the first time, discovered in some amorphous alloys. The isolated B₁₆ molecule is, however, found to be unstable. The Vickers harness calculations reveal that some of these amorphous alloys can serve as hard materials. When their electron properties are considered, all amorphous materials are predicted to be semiconducting.     

Supercapacitor device performances of polycarbazole/graphene and polycarbazole/nanoclay/graphene nanocomposites

In this study, graphene oxide (GO) is chemically reacted with sodium borohydride (NaBH₄) to form reduced graphene oxide (rGO). rGO, polycarbazole (PCz)/rGO and PCz/nanoclay/rGO materials were obtained by chemical polymerisation method. These three materials were characterised by Fourier-transform infra-red spectroscopy-attenuated transmission reflectance, scanning electron microscopy, energy-dispersive X-ray analysis, cyclic voltammetry (CV), galvanostatic charge–discharge and electrochemical impedance spectroscopy. The PCz/nanoclay/rGO nanocomposite shows significantly improved capacitance (C_sp?=?187.78?F?g^?1) compared to that of PCz/rGO (C_sp?=?74.18?F?g^?1) and rGO (C_sp?=?20.78?F?g^?1) at the scan rate of 10?mV?s^?1 by CV method. The supercapacitor device performance results show high power density (P?=?1057.81?W?kg^?1) and energy density (E?=?1.7?Wh?kg^?1) obtained from Ragone plot for PCz/nanoclay/rGO material. Stability tests were also examined by the CV method for 1000 cycles.     

Neural network based instant parameter prediction for wireless sensor network optimization models

Wireless Networks - Optimal operation configuration of a Wireless Sensor Network (WSN) can be determined by utilizing exact mathematical programming techniques such as Mixed Integer Programming...     

Speech recognition with artificial neural networks

In this paper, artificial neural networks were used to accomplish isolated speech recognition. The topic was investigated in two steps, consisting of the pre-processing part with Digital Signal Processing (DSP) techniques and the post-processing part with Artificial Neural Networks (ANN). These two parts were briefly explained and speech recognizers using different ANN architectures were implemented on Matlab. Three different neural network models; multi layer back propagation, Elman and probabilistic neural networks were designed. Performance comparisons with similar studies found in the related literature indicated that our proposed ANN structures yield satisfactory results.     

Ad-hoc limited scale-free models for unstructured peer-to-peer networks

Several protocol efficiency metrics (e.g., scalability, search success rate, routing reachability and stability) depend on the capability of preserving structure even over the churn caused by the ad-hoc nodes joining or leaving the network. Preserving the structure becomes more prohibitive due to the distributed and potentially uncooperative nature of such networks, as in the peer-to-peer (P2P) networks. Thus, most practical solutions involve unstructured approaches while attempting to maintain the structure at various levels of protocol stack. The primary focus of this paper is to investigate construction and maintenance of scale-free topologies in a distributed manner without requiring global topology information at the time when nodes join or leave. We consider the uncooperative behavior of peers by limiting the number of neighbors to a pre-defined hard cutoff value (i.e., no peer is a major hub), and the ad-hoc behavior of peers by rewiring the neighbors of nodes leaving the network. We also investigate the effect of these hard cutoffs and rewiring of ad-hoc nodes on the P2P search efficiency.     

Delineating compositionally different dykes in the Ulukışla basin (Central Anatolia,Turkey) using computer‐enhanced multi‐spectral remote sensing data

In the Uluk??la basin (Central Anatolia, Turkey) several geological mapping campaigns were carried out using conventional field methods to delineate compositionally different Middle–Upper Eocene dykes. However, complete and correct mapping of these dykes was hampered by rugged terrain, lack of road access, wide spatial dyke distributions with small exposures and diverse weathering of these dykes. For these reasons, Landsat‐5 Thematic Mapper (TM) satellite image of the study area was used to facilitate delineation of the exact boundaries of gabbroic, dioritic and trachytic dykes found in the area. Remotely sensed data were analysed using several image enhancement procedures, including colour composites, band ratios, principal components analysis (PCA), and Crosta technique. Results obtained from all the processes were examined, and it was found that dyke boundaries are best visible in the PCA123 image; RGB 731 colour composite; TM band ratio 5/7, 5/1, 4 combination; and 1457‐PC4 image obtained by Crosta technique. The alteration differences of three dyke groups are enhanced much better in the 1457‐PC4 image obtained by Crosta technique, which highlights the hydroxyl‐bearing minerals as white‐coloured pixels. Using computer‐enhanced multi‐spectral remote sensing data, we were able to map the boundaries and spatial distributions of compositionally different dykes, which otherwise is an overwhelmingly difficult task to achieve using conventional field methods. In similar settings, remote sensing techniques applied in this study may provide an efficient and low‐cost alternative to time‐consuming and physically demanding field‐mapping campaigns.     

Privacy-preserving Naïve Bayes classification

Privacy-preserving data mining—developing models without seeing the data – is receiving growing attention. This paper assumes a privacy-preserving distributed data mining scenario: data sources collaborate to develop a global model, but must not disclose their data to others. The problem of secure distributed classification is an important one. In many situations, data is split between multiple organizations. These organizations may want to utilize all of the data to create more accurate predictive models while revealing neither their training data/databases nor the instances to be classified. Naïve Bayes is often used as a baseline classifier, consistently providing reasonable classification performance. This paper brings privacy-preservation to that baseline, presenting protocols to develop a Naïve Bayes classifier on both vertically as well as horizontally partitioned data.     

Linear approximation of Bidirectional Reflectance Distribution Functions

Various empirical and theoretical models of the surface reflectance have been introduced so far. Most of these models are based on functions with non-linear parameters and therefore faces some computational difficulties involved in non-linear optimization processes. In this paper, we introduce a new approach for approximating Bidirectional Reflectance Distribution Functions (BRDF) by employing response surface methodology. The proposed model employs principal component transformations of the explanatory variables which are essentially functions of incoming and outgoing light directions. The resulting model is linear and can be used to represent both isotropic and anisotropic reflectance for diffuse and glossy materials. Considering some widely used reflection models including the Ward model, the Ashikhmin–Shirley model and the Lafortune model, we demonstrate empirically that satisfactory approximations can be made by means of the proposed general, simple and computationally efficient linear model.     

Preparation and characterization of Bombyx mori silk fibroin and wool keratin

Silk and wool are well‐known protein‐based fibers. Their environmental stability, biocompatibility, and unique mechanical properties provide an important basis for using these natural proteins in biomedical applications. To use them as biomaterials in the form of fibers, films, or membranes, it is necessary to characterize these proteins in their solution and solid states because structural characteristics and morphological features have a great influence on the physical and mechanical properties of these new regenerated protein forms. Therefore, in the present study, silk fibroin and wool keratin were dissolved and their solution behaviors and secondary structures are analyzed and compared, using particle size distribution, molecular weight distribution (SDS‐PAGE), Fourier transform infrared, and X‐ray diffraction techniques. It was shown that keratin is more stable in solution and more amorphous in the solid state. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100:4260–4264, 2006