Contributions of higher order terms to nonlinear waves in fluid-filled elastic tubes: strongly dispersive case

In the present work, employing the nonlinear equations of an incompressible, isotropic and elastic thin tube and the approximate equations of an incompressible inviscid fluid, and then utilizing the modified reductive perturbation technique presented by us [15] the amplitude modulation of weakly nonlinear waves is examined. It is shown that the first order term in the perturbation expansion is governed by a nonlinear Schrödinger equation and the second order term is governed by the linearized Schrödinger equation with a nonhomogeneous term. In the longwave limit a travelling wave type of solution to these equations are also given.     

GRAIL: a scalable index for reachability queries in very large graphs

Given a large directed graph, rapidly answering reachability queries between source and target nodes is an important problem. Existing methods for reachability tradeoff indexing time and space versus query time performance. However, the biggest limitation of existing methods is that they do not scale to very large real-world graphs. We present a simple yet scalable reachability index, called GRAIL, that is based on the idea of randomized interval labeling and that can effectively handle very large graphs. Based on an extensive set of experiments, we show that while more sophisticated methods work better on small graphs, GRAIL is the only index that can scale to millions of nodes and edges. GRAIL has linear indexing time and space, and the query time ranges from constant time to being linear in the graph order and size. Our reference C++ implementations are open source and available for download at http://www.code.google.com/p/grail/.     

Monitoring web services’ quality of service: a literature review

Monitoring Quality of Service (QoS) compliance is an important procedure in web service environment. It determines whether users’ expectations are met, and becomes the vital factor for them to decide whether to continue paying for the service or not. The monitoring is performed by checking the actual services performance against the QoS stated in Service Level Agreement (SLA). In relation to that, the need for monitoring vague QoS specifications in SLA has become more apparent nowadays. This paper reviews the published literature on web services QoS monitoring. A total of 60 selected articles were systematically analyzed. There were 23 of the articles selected through restrictive search criteria while the other 37 were selected based on unrestrictive search criteria. The review shows that little evidence exists on monitoring vague QoS specifications of web services. Providing ability for monitoring QoS that is specified vaguely in SLA could give new insights and implications to web services field. This paper concludes with some recommended future works to construct the theory and perform the empirical research.     

An in situ Raman study of the intercalation of supercapacitor-type electrolyte into microcrystalline graphite

An initial Raman study on the effects of intercalation for aprotic electrolyte-based electrochemical double-layer capacitors (EDLCs) is reported. In situ Raman microscopy is employed in the study of the electrochemical intercalation of tetraethylammonium (Et₄N⁺) and tetrafluoroborate (BF₄⁻) into and out of microcrystalline graphite. During cyclic voltammetry experiments, the insertion of Et₄N⁺ into graphite for the negative electrode occurs at an onset potential of +1.0 V versus Li/Li⁺. For the positive electrode, BF₄⁻ was shown to intercalate above +4.3 V versus Li/Li⁺. The characteristic G-band doublet peak (E_2g2(i) (1578 cm⁻¹) and E_2g2(b) (1600 cm⁻¹)) showed that various staged compounds were formed in both cases and the return of the single G-band (1578 cm⁻¹) demonstrates that intercalation was fully reversible. The disappearance of the D-band (1329 cm⁻¹) in intercalated graphite is also noted and when the intercalant is removed a more intense D-band reappears, indicating possible lattice damage. For cation intercalation, such irreversible changes of the graphite structure are confirmed by scanning electron microscopy (SEM).     

Type 2 Diabetes Risk Prediction Using Deep Convolutional Neural Network Based-Bayesian Optimization

Diabetes mellitus is a long-term condition characterized by hyperglycemia. It could lead to plenty of difficulties. According to rising morbidity in recent years, the world’s diabetic patients will exceed 642 million by 2040, implying that one out of every ten persons will be diabetic. There is no doubt that this startling figure requires immediate attention from industry and academia to promote innovation and growth in diabetes risk prediction to save individuals’ lives. Due to its rapid development, deep learning (DL) was used to predict numerous diseases. However, DL methods still suffer from their limited prediction performance due to the hyperparameters selection and parameters optimization. Therefore, the selection of hyper-parameters is critical in improving classification performance. This study presents Convolutional Neural Network (CNN) that has achieved remarkable results in many medical domains where the Bayesian optimization algorithm (BOA) has been employed for hyperparameters selection and parameters optimization. Two issues have been investigated and solved during the experiment to enhance the results. The first is the dataset class imbalance, which is solved using Synthetic Minority Oversampling Technique (SMOTE) technique. The second issue is the model's poor performance, which has been solved using the Bayesian optimization algorithm. The findings indicate that the Bayesian based-CNN model superbases all the state-of-the-art models in the literature with an accuracy of 89.36%, F1-score of 0.88.6, and Matthews Correlation Coefficient (MCC) of 0.88.6.     

Feature sequencing in the rapid design system using a genetic algorithm

This paper addresses the feature sequencing problem in the Rapid Design System (RDS). The RDS is a feature-based design system that integrates product design and process planning. An important issue in feature-based process planning for machined parts is the order in which material is removed to form the resultant part. The order, or sequence, is partially dependent on the geometric relationships between features. The sequence affects the safety, the time it takes to machine the part, and the quality of the finished part. The sequence of material removal depends on two types of relations between features: (1) intersections and (2) interfeature associations. Both types of relations compound the search for an optimal sequence of material removal. Therefore, the research problem has been the discovery and development of a genetic algorithm (GA) that efficiently searches the solution space for all possible sequences and identifies the best sequences in terms of safety, time and quality.     

Novel mixed ligand complexes of Co(II), Ni(II), Cu(II), and Zn(II) with 1,10-phenanthroline and acesulfame. Synthesis,structural analysis and hydrogen adsorption study

Four novel metal organic framework (MOF) structures containing acesulfame (ace) and 1,10-phenanthroline (phen) ligands of Co²⁺, Ni²⁺, Cu²⁺ and Zn²⁺ metal cations were synthesized. The crystal structure analysis of three compounds (1, 2, and 3) was also performed. The structural formula for complex 4 is proposed based on spectroscopic and thermal analysis data. It has been determined that structures 1, 2, and 4 are in a distorted octahedral geometry. It has been suggested that the charge balance of the coordination sphere with 2+ is provided by two monoanionic ace ligands located outside the coordination sphere as counter-ion. In structure 3, there are two Cu^II metal cations, two phen ligands coordinated as bidentate to each metal cation and ace ligand that provides monoanionic-monodentate coordination. The Cu²⁺ cation has distorted bipyramidal geometry. The maximum hydrogen gas adsorption has been found 1.4575 mL/g (0.046 wt%) for the Ni complex.     

Sign Language to Sentence Formation: A Real Time Solution for Deaf People

Communication is a basic need of every human being to exchange thoughts and interact with the society. Acute peoples usually confab through different spoken languages, whereas deaf people cannot do so. Therefore, the Sign Language (SL) is the communication medium of such people for their conversation and interaction with the society. The SL is expressed in terms of specific gesture for every word and a gesture is consisted in a sequence of performed signs. The acute people normally observe these signs to understand the difference between single and multiple gestures for singular and plural words respectively. The signs for singular words such as I, eat, drink, home are unalike the plural words as school, cars, players. A special training is required to gain the sufficient knowledge and practice so that people can differentiate and understand every gesture/sign appropriately. Innumerable researches have been performed to articulate the computer-based solution to understand the single gesture with the help of a single hand enumeration. The complete understanding of such communications are possible only with the help of this differentiation of gestures in computer-based solution of SL to cope with the real world environment. Hence, there is still a demand for specific environment to automate such a communication solution to interact with such type of special people. This research focuses on facilitating the deaf community by capturing the gestures in video format and then mapping and differentiating as single or multiple gestures used in words. Finally, these are converted into the respective words/sentences within a reasonable time. This provide a real time solution for the deaf people to communicate and interact with the society.     

Identification of Ti incorporation into β-SiAlON crystal structure through transmission electron microscopy techniques

In this paper, we report the transmission electron microscopy (TEM) observations on the incorporation of Ti transition metal element into β-SiAlON crystal structure in a bulk β-SiAlON–TiN composite material. Considering our energy dispersive X-ray (EDX) and electron energy loss (EEL) spectroscopy results acquired by using nanometre-scale focused electron probe in scanning transmission electron microscopy (STEM) mode, the Ti-K characteristic X-ray lines and Ti-L_3,2 edges were detected in the chemical composition of the β-SiAlON grains. These results clearly reveal that Ti can enter into the β-SiAlON crystal structure. It is anticipated that this data will provide the new engineering insights on the production of transition metal element doped SiAlON-based materials for different applications.