Large eddy simulation of free-shear flows using an algebraic model

Large eddy simulation of the free-shear flows has been performed using an algebraic subgrid stress model. The test cases considered are the temporal planar jet and mixing layer. The results are compared with that of the Smagorinsky, dynamic Smagorinsky, mixed models and the DNS data. For the mean flow quantities none of the models perform exceptionally better over the others. However, both the algebraic and mixed models predict better statistics for the turbulent quantities than the linear models. The results also demonstrate the capability of the algebraic model in depicting backscatter of energy explicitly, which is consistent in both the cases considered.     

Countercurrent water-heating system with a heat exchanger in a solar energy collector loop

The counter current heat exchanger theory with periodic inlet temperatures has been applied to analyze the thermal performance of a water heating system. The theoretical results obtained are in agreement with the experimental data reported in the literature.     

Structural features of an arabinan fragment isolated from the water-soluble fraction of dehulled rapeseed

A water-soluble polysaccharide fraction was prepared from dehulled rapeseed meal (winter rapeseed variety Casino). Further purification yielded two major fractions having a high content of arabinose and galactose residues, with Ara/Gal ratios of 5.4 (G1) and 1.8 (G2). The Ara/Gal ratio of the high molecular weight fraction G1 was stable over the whole gel filtration peak, indicating that the arabinose and galactose residues are part of the same polysaccharide. The high molecular weight fraction G1 was studied further by methylation analysis and several NMR techniques. Structural studies showed G1 to consist mainly of arabian fragments, which have terminal alpha-L-arabinofuranosyl groups with anomeric carbons bound (1-->5) (A) or (1-->2) (B), and 2,5-substituted arabinosyl residues with anomeric carbons bound (1-->5) (D) or (1-->2) (C) to adjacent arabinosyl residues. The A:B:C:D ratios were 2:1:1:1 according to results from NMR and methylation analysis.     

An intelligent hybrid approach for hepatitis disease diagnosis: Combining enhanced k‐means clustering and improved ensemble learning

In real world, the automatic detection of liver disease is a challenging problem among medical practitioners. The intent of this work is to propose an intelligent hybrid approach for the diagnosis of hepatitis disease. The diagnosis is performed with the combination of k‐means clustering and improved ensemble‐driven learning. To avoid clinical experience and to reduce the evaluation time, ensemble learning is deployed, which constructs a set of hypotheses by using multiple learners to solve a liver disease problem. The performance analysis of the proposed integrated hybrid system is compared in terms of accuracy, true positive rate, precision, f‐measure, kappa statistic, mean absolute error, and root mean squared error. Simulation results showed that the enhanced k‐means clustering and improved ensemble learning with enhanced adaptive boosting, bagged decision tree, and J48 decision tree‐based intelligent hybrid approach achieved better prediction outcomes than other existing individual and integrated methods.     

Prediction of burning rate of coal in fluidized-bed combustion

A theory has been proposed to evaluate the burning rate of a single carbon particle in a continuously operated coal-fired fluidized bed. Experimental verification was carried out in a laboratory scale 200 mm × 200 mm combustor. The burning rate increases with the increase of the fluidization velocity and the size of the bed material. The predicted data on burning rate agree fairly well with the experimental values. The gas concentration in the bed and freeboard has also been measured and it is seen that the consumption of oxygen mostly takes place in the bed.     

Eco-friendly electronics,based on nanocomposites of biopolyester reinforced with carbon nanotubes: a review

ABSTRACT

Fabrication of electronic materials from nanocomposite of biopolyesters reinforced with carbon nanotubes can be regarded as the effective alternative for conventional nanocomposites consisting of non-biodegradable polymers. Commercial availability of biopolyester-based nanocomposites is limited because of their high cost compared to other polymers, but the factor of their compostable nature is worthless for environmental protection. Such nanocomposites have potential applications in biodegradable sensors, EMI materials, etc. In this review, the current progress of biopolyester/CNTs nanocomposites in the field of biodegradable electronics is reviewed and also the impact of CNTs dispersion on electrical, thermal and mechanical properties of eco composites is stipulated.     

A free space frequency‐time‐domain technique for electromagnetic characterization of materials using reflection‐based measurement

In this report, a free space frequency‐time‐domain technique is presented for characterizing the electrical properties and thickness of the sample using multiple reflections and fabry‐perot resonance phenomenon. The retrieval of constitutive electromagnetic parameters of the sample has been carried out by comparing the measured reflection coefficient data from the sample at two different incident angles. The relative permittivity as well as relative permeability along with the thickness of different samples viz., beryllia, silicon, and plexiglass have been evaluated with high accuracy in the frequency range 1 to 15 GHz. The method is also experimentally validated by successfully reconstructing the unknown material properties of two different samples. The unique advantage of this method lies in non‐requirement of any prior knowledge of the sample's thickness for measuring the complex relative dielectric constant as well as relative permeability of the sample. To determine the electromagnetic properties of the sample, the sole knowledge of reflection coefficient data are needed. Moreover, the method does not involve any additional measurement for the reference calibration. The simple, cost‐effective proposed scheme is quite useful in many applications like accurate determination of signal strength in indoor wireless communication, through wall imaging, food industry, and so on.     

KP-Rank: a semantic-based unsupervised approach for keyphrase extraction from text data

Automatic key concept identification from text is the main challenging task in information extraction, information retrieval, digital libraries, ontology learning, and text analysis. The main difficulty lies in the issues with the text data itself, such as noise in text, diversity, scale of data, context dependency and word sense ambiguity. To cope with this challenge, numerous supervised and unsupervised approaches have been devised. The existing topical clustering-based approaches for keyphrase extraction are domain dependent and overlooks semantic similarity between candidate features while extracting the topical phrases. In this paper, a semantic based unsupervised approach (KP-Rank) is proposed for keyphrase extraction. In the proposed approach, we exploited Latent Semantic Analysis (LSA) and clustering techniques and a novel frequency-based algorithm for candidate ranking is introduced which considers locality-based sentence, paragraph and section frequencies. To evaluate the performance of the proposed method, three benchmark datasets (i.e. Inspec, 500N-KPCrowed and SemEval-2010) from different domains are used. The experimental results show that overall, the KP-Rank achieved significant improvements over the existing approaches on the selected performance measures.

     

维吾尔语三音节词韵律特征声学分析

本文从文本分析模块入手,利用“维吾尔语语音声学参数库”,选择了以开音节和闭音节结尾的333个三音节词的韵律参数,包括元音时长、音高和音强进行了统计分析,归纳了其元音时长、音高和音强分布模式,探讨了维吾尔语三音节词的韵律节奏模式与三音节词重音之间的关系问题,其目的是为了提高语音合成的自然度即更好的为自然语言处理服务。本项研究对维吾尔语语言乃至整个阿尔泰语系语言的韵律研究具有较高的参考价值。