Search results for: protein secondary structure prediction

Authors: Leila Amjad, Mahsa Shafighi

Abstract:

The role of the pollen grain, with to the reproductive process of higher plants, is to deliver the spermatic cells to the embryo sac for egg fertilization. The aim of this project was study the effect of electromagnetic fields on structure and pollen grains development in Chenopodium album. Anthers of Chenopodium album L. were collected at different stages of development from control (without electromagnetic field) and plants grown at 10m from the field sources. Structure and development of pollen grains were studied and compared. The studying pollen structure by Light and Scanning electron microscopy showed that electromagnetic fields reduction of pollen grains number and male sterility, thus , in some anthers, pollen grains were attached together and deformed compared to control ones. The data presented suggest that prolonged exposures of plants to magnetic field may cause different biological effects at the cellular tissue and organ levels.

Keywords: Electromagnetic fields, pollen, Chenopodium albumL.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2196

Authors: Yong-jun Zhao, Heng-li Zhang, Zong-yun Hu

Abstract:

Based on the sources- smoothed rank profile (SRP) and modified minimum description length (MMDL) principle, a method for estimation of the source coherency structure (SCS) and the number of wideband sources is proposed in this paper. Instead of focusing, we first use a spatial smoothing technique to pre-process the array covariance matrix of each frequency for de-correlating the sources and then use smoothed rank profile to determine the SCS and the number of wideband sources. We demonstrate the availability of the method by numerical simulations.

Keywords: Wideband sources, source coherency structure (SCS), smoothed rank profile (SRP).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1317

Authors: G. Reinhart, J. Pohl

Abstract:

Manufacturing companies are facing a broad variety of challenges caused by a dynamic production environment. To succeed in such an environment, it is crucial to minimize the loss of time required to trigger the adaptation process of a company-s production structures. This paper presents an approach for the continuous monitoring of production structures by neurologic principles. It enhances classical monitoring concepts, which are principally focused on reactive strategies, and enables companies to act proactively. Thereby, strategic aspects regarding the harmonization of certain life cycles are integrated into the decision making process for triggering the reconfiguration process of the production structure.

Keywords: Continuous Factory Planning, Production Structure, Production Management.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1447

Authors: P. M. Ikonić, T. A. Tasić, L. S. Petrović, S. B. Škaljac, M. R. Jokanović, V. M. Tomović, B. V. Šojić, N. R. Džinić, A. M. Torbica, B. B. Ikonić

Abstract:

The aim of the study was to determine how different ripening processes (traditional vs. industrial) influenced the proteolysis in traditional Serbian dry-fermented sausage Petrovská klobása. The obtained results indicated more intensive pH decline (0.7 units after 9 days) in industrially ripened products (I), what had a positive impact on drying process and proteolytic changes in these samples. Thus, moisture content in I sausages was lower at each sampling time, amounting 24.7% at the end of production period (90 days). Likewise, the process of proteolysis was more pronounced in I samples, resulting in higher contents of non-protein nitrogen (NPN) and free amino acids nitrogen (FAAN), as well as in faster and more intensive degradation of myosin (≈220 kDa), actin (≈45 kDa) and other polypeptides during processing. Consequently, the appearance and accumulation of several protein fragments were registered.

Keywords: Dry-fermented sausage, Petrovská klobása, proteolysis, ripening process.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4366

Authors: Nimisha R. Shirbhate, Sanjay Bokade

Abstract:

Bone Scaffolds are fundamental architecture or a support structure that allows the regeneration of lost or damaged tissues and they are developed as a crucial tool in biomedical engineering. The structure of bone scaffolds plays an important role in treating bone defects. The shape of the bone scaffold performs a vital role, specifically pore size and shape, which help understand the behavior and strength of the scaffold. In this article, first, fundamental aspects of bone scaffold design are established. Second, the behavior of each architecture of the bone scaffold with biomaterials is discussed. Finally, for each structure, the stress analysis was carried out. This study aimed to design a porous and mechanically strong bone regeneration scaffold that can be successfully manufactured. Four porous architectures of the bone scaffold were designed using Rhinoceros solid modelling software. The structure model consisted of repeatable unit cells arranged in layers to fill the chosen scaffold volume. The mechanical behavior of used biocompatible material is studied with the help of ANSYS 19.2 software. It is also playing significant role to predict the strength of defined structures or 3 dimensional models.

Keywords: Bone scaffold, stress analysis, porous structure, static loading.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 534

Authors: Maha Sharkas, Dahlia ElShafie, Nadder Hamdy

Abstract:

Image watermarking has become an important tool for intellectual property protection and authentication. In this paper a watermarking technique is suggested that incorporates two watermarks in a host image for improved protection and robustness. A watermark, in form of a PN sequence (will be called the secondary watermark), is embedded in the wavelet domain of a primary watermark before being embedded in the host image. The technique has been tested using Lena image as a host and the camera man as the primary watermark. The embedded PN sequence was detectable through correlation among other five sequences where a PSNR of 44.1065 dB was measured. Furthermore, to test the robustness of the technique, the watermarked image was exposed to four types of attacks, namely compression, low pass filtering, salt and pepper noise and luminance change. In all cases the secondary watermark was easy to detect even when the primary one is severely distorted.

Keywords: DWT, Image watermarking, watermarkingtechniques, wavelets.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2711

Authors: Sivapan Choo-In

Abstract:

The main objective of this study was to investigate particulate matter concentration on main and secondary roadsides in urban area and study the concentration of some heavy metals including lead (Pb), zinc (Zn), copper (Cu) and cadmium (Cd) in particulate matter in the Bangkok area.     

  The averaged particle concentration for main roadsides is higher than secondary roadsides. The particulate matter less than 10 micron concentration contribute the majority of the Total Suspended Particulate matter for main roads and zinc concentrations were higher than copper and lead for both sites.

Keywords: Air Pollution, Air Quality, Pollution and monitoring.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2033

Authors: Bilal Alatas, Ahmet Arslan

Abstract:

The main goal of data mining is to extract accurate, comprehensible and interesting knowledge from databases that may be considered as large search spaces. In this paper, a new, efficient type of Genetic Algorithm (GA) called uniform two-level GA is proposed as a search strategy to discover truly interesting, high-level prediction rules, a difficult problem and relatively little researched, rather than discovering classification knowledge as usual in the literatures. The proposed method uses the advantage of uniform population method and addresses the task of generalized rule induction that can be regarded as a generalization of the task of classification. Although the task of generalized rule induction requires a lot of computations, which is usually not satisfied with the normal algorithms, it was demonstrated that this method increased the performance of GAs and rapidly found interesting rules.

Keywords: Classification rule mining, data mining, genetic algorithms.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1594

Authors: D. A. Farinde

Abstract:

One of the most significant threats to the economy of a nation is the bankruptcy of its banks. This study evaluates the susceptibility of Nigerian banks to failure with a view to identifying ratios and financial data that are sensitive to solvency of the bank. Further, a predictive model is generated to guide all stakeholders in the industry. Thirty quoted banks that had published Annual Reports for the year preceding the consolidation i.e. year 2004 were selected. They were examined for distress using the Multilayer Perceptron Neural Network Analysis. The model was used to analyze further reforms by the Central Bank of Nigeria using published Annual Reports of twenty quoted banks for the year 2008 and 2011. The model can thus be used for future prediction of failure in the Nigerian banking system.

Keywords: Bank, Bankruptcy, Financial Ratios, Neural Network, Multilayer Perceptron, Predictive Model

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2704

Authors: Eneli Kindsiko, Kulno Türk

Abstract:

The purpose of the current article is to reveal misconceptions about ICT occupations that keep females away from the field. The study focuses on the three phases in one’s career life cycle: pre-university, university and workplace with the aim of investigating how to attract more females into an ICT-related career. By studying nearly 300 secondary school graduates, 102 university students and 18 female ICT specialists, the study revealed six myths that influence the decision-making process of young girls in pursuing an ICT-related education and career. Furthermore, discriminating conception of ICT as a primarily man’s world is developed before the university period. Stereotypical barriers should be brought out to the public debate, so that a remarkable proportion of possible employees (women) would not stay away from the tech-related fields. Countries could make a remarkable leap in efficiency, when turning their attention to the gender-related issues in the labour market structure.

Keywords: ICT, women, education, stereotypes, computers.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1639

Authors: Ahmed Kayad Abdourazak, Abderafi Souad, Zejli Driss, Idriss Abdoulkader Ibrahim

Abstract:

In this paper Artificial Neural Network (ANN) is used to predict the solar irradiation in Djibouti for the first Time that is useful to the integration of Concentrating Solar Power (CSP) and sites selections for new or future solar plants as part of solar energy development. An ANN algorithm was developed to establish a forward/reverse correspondence between the latitude, longitude, altitude and monthly solar irradiation. For this purpose the German Aerospace Centre (DLR) data of eight Djibouti sites were used as training and testing in a standard three layers network with the back propagation algorithm of Lavenber-Marquardt. Results have shown a very good agreement for the solar irradiation prediction in Djibouti and proves that the proposed approach can be well used as an efficient tool for prediction of solar irradiation by providing so helpful information concerning sites selection, design and planning of solar plants.

Keywords: Artificial neural network, solar irradiation, concentrated solar power, Lavenberg-Marquardt.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1082

Authors: Salvatore Marra, Francesco C. Morabito

Abstract:

In this paper we present an efficient approach for the prediction of two sunspot-related time series, namely the Yearly Sunspot Number and the IR5 Index, that are commonly used for monitoring solar activity. The method is based on exploiting partially recurrent Elman networks and it can be divided into three main steps: the first one consists in a “de-rectification" of the time series under study in order to obtain a new time series whose appearance, similar to a sum of sinusoids, can be modelled by our neural networks much better than the original dataset. After that, we normalize the derectified data so that they have zero mean and unity standard deviation and, finally, train an Elman network with only one input, a recurrent hidden layer and one output using a back-propagation algorithm with variable learning rate and momentum. The achieved results have shown the efficiency of this approach that, although very simple, can perform better than most of the existing solar activity forecasting methods.

Keywords: Elman neural networks, sunspot, solar activity, time series prediction.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1854

Authors: Gabriele Bedon, Marco Raciti Castelli, Ernesto Benini

Abstract:

A dynamic stall-corrected Blade Element-Momentum algorithm based on a hybrid polar is validated through the comparison with Sandia experimental measurements on a 5-m diameter wind turbine of Troposkien shape. Different dynamic stall models are evaluated. The numerical predictions obtained using the extended aerodynamic coefficients provided by both Sheldal and Klimas and Raciti Castelli et al. are compared to experimental data, determining the potential of the hybrid database for the numerical prediction of vertical-axis wind turbine performances.

Keywords: Darrieus wind turbine, Blade Element-Momentum Theory, extended airfoil database, hybrid database, Sandia 5-m wind turbine.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2560

Authors: Perumal Nallagownden, Ravindra N. Mukerjee, Syafrudin Masri

Abstract:

In a competitive energy market, system reliability should be maintained at all times. Power system operation being of online in nature, the energy balance requirements must be satisfied to ensure reliable operation the system. To achieve this, information regarding the expected status of the system, the scheduled transactions and the relevant inputs necessary to make either a transaction contract or a transmission contract operational, have to be made available in real time. The real time procedure proposed, facilitates this. This paper proposes a quadratic curve learning procedure, which enables a generator-s contribution to the retailer demand, power loss of transaction in a line at the retail end and its associated losses for an oncoming operating scenario to be predicted. Matlab program was used to test in on a 24-bus IEE Reliability Test System, and the results are found to be acceptable.

Keywords: Deregulation, learning coefficients, reliability, prediction, competitive energy market.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1478

Authors: Latha Parthiban, R. Subramanian

Abstract:

Heart disease (HD) is a major cause of morbidity and mortality in the modern society. Medical diagnosis is an important but complicated task that should be performed accurately and efficiently and its automation would be very useful. All doctors are unfortunately not equally skilled in every sub specialty and they are in many places a scarce resource. A system for automated medical diagnosis would enhance medical care and reduce costs. In this paper, a new approach based on coactive neuro-fuzzy inference system (CANFIS) was presented for prediction of heart disease. The proposed CANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach which is then integrated with genetic algorithm to diagnose the presence of the disease. The performances of the CANFIS model were evaluated in terms of training performances and classification accuracies and the results showed that the proposed CANFIS model has great potential in predicting the heart disease.

Keywords: CANFIS, genetic algorithms, heart disease, membership function.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3993

Authors: H. Elftouh, N. T. Amar, M. Aghoutane, M. Boussouis

Abstract:

In this paper, two bandstop filters resonating at 5.25 GHz and 7.3 GHz using Defected Microstrip Structure (DMS) are discussed. These slots are incorporated in the feed lines of filters to perform a serious LC resonance property in certain frequency and suppress the spurious signals. Therefore, this method keeps the filter size unchanged and makes a resonance frequency that is due to the abrupt change of the current path of the filter. If the application requires elimination of this band of frequencies, additional filter elements are required, which can only be accomplished by adding this DMS element resonant at desired frequency band rejection. The filters are optimized and simulated with Computer Simulation Technology (CST) tool.

Keywords: Defected microstrip structure, microstrip filters, passive filter.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1373

Authors: Le Thuy Mai, Vu Nguyen Thanh

Abstract:

β-Glucosidase is an important enzyme for production of ethanol from lignocellulose. With hydrolytic activity on cellooligosaccharides, especially cellobiose, β-glucosidase removes product inhibitory effect on cellulases and forms fermentable sugars. In this study, β-glucosidase encoding gene (BGL1) from traditional starter yeast Saccharomycosis fibuligera BMQ908 was cloned and expressed in Pichia pastoris. BGL1 of S. fibuligera BMQ 908 shared 98% nucleotide homology with the closest GenBank sequence (M22475) but identity in amino-acid sequences of catalytic domains. Recombinant plasmid pPICZαA/BGL1 containing the sequence encoding BGL1 mature protein and α-factor secretion signal was constructed and transformed into methylotrophic yeast P. pastoris by electroporation. The recombinant strain produced single extracellular protein with molecular weight of 120 kDa and cellobiase activity of 60 IU/ml. The optimum pH of the recombinant β-glucosidase was 5.0 and the optimum temperature was 50°C.

Keywords: β-Glucosidase, Pichia pastoris, Saccharomycopsisfibuligera, recombinant enzyme.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4972

Authors: S. J. Matlan, M. Mukhlisin, M. R. Taha

Abstract:

Characterization of the engineering behavior of unsaturated soil is dependent on the soil-water characteristic curve (SWCC), a graphical representation of the relationship between water content or degree of saturation and soil suction. A reasonable description of the SWCC is thus important for the accurate prediction of unsaturated soil parameters. The measurement procedures for determining the SWCC, however, are difficult, expensive, and timeconsuming. During the past few decades, researchers have laid a major focus on developing empirical equations for predicting the SWCC, with a large number of empirical models suggested. One of the most crucial questions is how precisely existing equations can represent the SWCC. As different models have different ranges of capability, it is essential to evaluate the precision of the SWCC models used for each particular soil type for better SWCC estimation. It is expected that better estimation of SWCC would be achieved via a thorough statistical analysis of its distribution within a particular soil class. With this in view, a statistical analysis was conducted in order to evaluate the reliability of the SWCC prediction models against laboratory measurement. Optimization techniques were used to obtain the best-fit of the model parameters in four forms of SWCC equation, using laboratory data for relatively coarse-textured (i.e., sandy) soil. The four most prominent SWCCs were evaluated and computed for each sample. The result shows that the Brooks and Corey model is the most consistent in describing the SWCC for sand soil type. The Brooks and Corey model prediction also exhibit compatibility with samples ranging from low to high soil water content in which subjected to the samples that evaluated in this study.

Keywords: Soil-water characteristic curve (SWCC), statistical analysis, unsaturated soil.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2665

Authors: Amin Abedi, Naser Vosoughi, Mohammad Bagher Ghofrani

Abstract:

Double heterogeneity of randomly located pebbles in the core and Coated Fuel Particles (CFPs) in the pebbles are specific features in pebble bed reactors and usually, because of difficulty to model with MCNP code capabilities, are neglected. In this study, characteristics of HTR-10, Tsinghua University research reactor, are used and not only double heterogeneous but also truncated CFPs and Pebbles are considered.Firstly, 8335 CFPs are distributed randomly in a pebble and then the core of reactor is filled with those pebbles and graphite pebbles as moderator such that 57:43 ratio of fuel and moderator pebbles is established.Finally, four different core configurations are modeled. They are Simple Cubic (SC) structure with truncated pebbles,SC structure without truncated pebble, and Simple Hexagonal(SH) structure without truncated pebbles and SH structure with truncated pebbles. Results like effective multiplication factor (Keff), critical height,etc. are compared with available data.

Keywords: Double Heterogeneity, HTR-10, MCNP, Pebble Bed Reactor, Stochastic Geometry.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2855

Authors: Dhahri Maher, Aouinet Hana

Abstract:

The presence of bubbles in the boundary layer introduces corrections into the log law, which must be taken into account. In this work, a logarithmic wall law was presented for bubbly two phase flows. The wall law presented in this work was based on the postulation of additional turbulent viscosity associated with bubble wakes in the boundary layer. The presented wall law contained empirical constant accounting both for shear induced turbulence interaction and for non-linearity of bubble. This constant was deduced from experimental data. The wall friction prediction achieved with the wall law was compared to the experimental data, in the case of a turbulent boundary layer developing on a vertical flat plate in the presence of millimetric bubbles. A very good agreement between experimental and numerical wall friction prediction was verified. The agreement was especially noticeable for the low void fraction when bubble induced turbulence plays a significant role.

Keywords: Bubbly flows, log law, boundary layer.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1127

Authors: Z. Pavlík, J. Fořt, J. Žumár, M. Pavlíková, R. Černý

Abstract:

The cup method is applied for the measurement of water vapor transport properties of porous materials worldwide. However, in practical applications the experimental results are often used without taking into account some secondary effects which can play an important role under specific conditions. In this paper, the effect of temperature on water vapor transport properties of cellular concrete is studied, together with the influence of sample thickness. At first, the bulk density, matrix density, total open porosity and sorption and desorption isotherms are measured for material characterization purposes. Then, the steady state cup method is used for determination of water vapor transport properties, whereas the measurements are performed at several temperatures and for three different sample thicknesses.

Keywords: Water vapor transport, cellular concrete, cup method, temperature, sample thickness.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1896

Authors: Riaz A. Bhatti, Wang Yanrong

Abstract:

Particle damping is a technique to reduce the structural vibrations by means of placing small metallic particles inside a cavity that is attached to the structure at location of high vibration amplitudes. In this paper, we have presented an analytical model to simulate the particle damping of two dimensional transient vibrations in structure operating under high centrifugal loads. The simulation results show that this technique remains effective as long as the ratio of the dynamic acceleration of the structure to the applied centrifugal load is more than 0.1. Particle damping increases with the increase of particle to structure mass ratio. However, unlike to the case of particle damping in the absence of centrifugal loads where the damping efficiency strongly depends upon the size of the cavity, here this dependence becomes very weak. Despite the simplicity of the model, the simulation results are considerably in good agreement with the very scarce experimental data available in the literature for particle damping under centrifugal loads.

Keywords: Impact damping, particle damping, vibration control, vibration suppression.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1799

Authors: Darren Zou

Abstract:

Forecasting the stock market is a very challenging task. Various economic indicators such as GDP, exchange rates, interest rates, and unemployment have a substantial impact on the stock market. Time series models are the traditional methods used to predict stock market changes. In this paper, a machine learning method, Bayesian Additive Regression Tree (BART) is used in predicting stock market indexes based on multiple economic indicators. BART can be used to model heterogeneous treatment effects, and thereby works well when models are misspecified. It also has the capability to handle non-linear main effects and multi-way interactions without much input from financial analysts. In this research, BART is proposed to provide a reliable prediction on day-to-day stock market activities. By comparing the analysis results from BART and with time series method, BART can perform well and has better prediction capability than the traditional methods.

Keywords: Bayesian, Forecast, Stock, BART.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 734

Authors: Christian Rathgeber, Franz Winkler, Dirk Odenthal, Steffen Muller

Abstract:

In this contribution a structure for high level lateral vehicle tracking control based on the disturbance observer is presented. The structure is characterized by stationary compensating side forces disturbances and guaranteeing a cooperative behavior at the same time. Driver inputs are not compensated by the disturbance observer. Moreover the structure is especially useful as it robustly stabilizes the vehicle. Therefore the parameters are selected using the Parameter Space Approach. The implemented algorithms are tested in real world scenarios.

Keywords: Disturbance observer, trajectory tracking, robust control, autonomous driving, cooperative driving

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3024

Authors: Laima Silina, Ilze Gramatina, Lija Dukalska, Liga Skudra, Tatjana Rakcejeva, Dace Klava, Anita Blija

Abstract:

The objective of the present study was to determine quality parameters changes of red wine marinade marinated venison during storage. Beef as a control was analysed. Protein, fat, moisture and pH content dynamics as well microbiological quality was analyzed. The meat pieces were marinated in red wine marinade at 4±2ºC temperature for 48±1h. Marinated meat was placed in polypropylene trays, hermetically sealed with high barrier polymer film Multibarrier 60 under modified atmosphere (CO₂ 40%+N₂ 60%) without and with oxygen absorber sachets, as a control packaging in air ambiance packed marinated venison and beef was used. Meat samples were analyzed after 0, 4, 7, 11 and 14 days of storage. During the storage of meat, protein and moisture content significantly (p<0.05) decreased, pH and colony forming units significantly (p<0.05) increased, fat content does not change in all treatments irrespective of the packaging method.

Keywords: Marinating, modified atmosphere, quality, venison.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2392

Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

Abstract:

Rainfall and runoff phenomenon is a chaotic and complex outcome of nature which requires sophisticated modelling and simulation methods for explanation and use. Time Series modelling allows runoff data analysis and can be used as forecasting tool. In the paper attempt is made to model river runoff data and predict the future behavioural pattern of river based on annual past observations of annual river runoff. The river runoff analysis and predict are done using ARIMA model. For evaluating the efficiency of prediction to hydrological events such as rainfall, runoff and etc., we use the statistical formulae applicable. The good agreement between predicted and observation river runoff coefficient of determination (R²) display that the ARIMA (4,1,1) is the suitable model for predicting Karkheh River runoff at Iran.

Keywords: Time series modelling, ARIMA model, River runoff, Karkheh River, CLS method.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 799

Authors: Kong Fah Tee, Lutfor Rahman Khan, Hongshuang Li

Abstract:

An advanced Monte Carlo simulation method, called Subset Simulation (SS) for the time-dependent reliability prediction for underground pipelines has been presented in this paper. The SS can provide better resolution for low failure probability level with efficient investigating of rare failure events which are commonly encountered in pipeline engineering applications. In SS method, random samples leading to progressive failure are generated efficiently and used for computing probabilistic performance by statistical variables. SS gains its efficiency as small probability event as a product of a sequence of intermediate events with larger conditional probabilities. The efficiency of SS has been demonstrated by numerical studies and attention in this work is devoted to scrutinise the robustness of the SS application in pipe reliability assessment. It is hoped that the development work can promote the use of SS tools for uncertainty propagation in the decision-making process of underground pipelines network reliability prediction.

Keywords: Underground pipelines, Probability of failure, Reliability and Subset Simulation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3554

Authors: Karuna Tuchinda, Sasithon Bland

Abstract:

This work investigates the wear of a steam turbine blade coated with titanium nitride (TiN), and compares to the wear of uncoated blades. The coating is deposited on by physical vapor deposition (PVD) method. The working conditions of the blade were simulated and surface temperature and pressure values as well as flow velocity and flow direction were obtained. This data was used in the finite element wear model developed here in order to predict the wear of the blade. The wear mechanisms considered are erosive wear due to particle impingement and fluid jet, and fatigue wear due to repeated impingement of particles and fluid jet. Results show that the life of the TiN-coated blade is approximately 1.76 times longer than the life of the uncoated one.

Keywords: Physical vapour deposition, steam turbine blade, titanium-based coating, wear prediction.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3153

Authors: Jing Zhang, Lian Wu, Jie-ming Qu, Chun-xue Bai, Mervyn J Merrilees, Peter N Black

Abstract:

COPD is characterized by loss of elastic fibers from small airways and alveolar walls, with the decrease in elastin increasing with disease severity. It is unclear why there is a lack of repair of elastic fibers. We have examined fibroblasts cultured from lung tissue from normal and COPD subjects to determine if the secretory profile explains lack of tissue repair. In this study, fibroblasts were cultured from lung parenchyma of bronchial carcinoma patients with varying degrees of COPD; controls (non-COPD, n=5), mild COPD (GOLD 1, n=5) and moderate-severe COPD (GOLD 2-3, n=12). Measurements were made of proliferation, senescence-associated beta-galactosidase-1, mRNA expression of IL-6, IL-8, MMP-1, tropoelastin and versican, and protein levels for IL-6, IL-8, PGE2, tropoelastin, insoluble elastin, and versican. It was found that GOLD 2-3 fibroblasts proliferated more slowly (p<0.01) and had higher levels of senescence-associated beta-galactosidase-1 (p<0.001) than controls (non-COPD). GOLD 2-3 fibroblasts showed significant increases in mRNA and/or protein for IL-6, IL-8, MMP-1, PGE2, versican (p<0.01) and tropoelastin (p<0.05). mRNA expression and/or protein levels of tropoelastin (p<0.01), versican (p<0.02), IL-6 (p<0.05) and IL-8 (p<0.05) were negatively correlated with FEV1%. Insoluble elastin was not increased. In summary, fibroblasts from moderate to severe COPD subjects display a secretory phenotype with up-regulation of inflammatory molecules including the matrix proteoglycan versican, and increased soluble, but not insoluble, elastin. Versican inhibits assembly of tropoelastin into insoluble elastin and we conclude that the pro-inflammatory phenotype of COPD fibroblasts it is not compatible with repair elastic fibers.

Keywords: COPD, pulmonary fibroblasts, pro-inflammatory phenotype, versican, elastin

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1555

Authors: H.Mohammadi Majd, M.Jalali Azizpour , Foad Saadi

Abstract:

In this paper back-propagation artificial neural network (BPANN) is employed to predict the deformation of the upsetting process. To prepare a training set for BPANN, some finite element simulations were carried out. The input data for the artificial neural network are a set of parameters generated randomly (aspect ratio d/h, material properties, temperature and coefficient of friction). The output data are the coefficient of polynomial that fitted on barreling curves. Neural network was trained using barreling curves generated by finite element simulations of the upsetting and the corresponding material parameters. This technique was tested for three different specimens and can be successfully employed to predict the deformation of the upsetting process

Keywords: Back-propagation artificial neural network(BPANN), prediction, upsetting

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1552