Search results for: protein secondary structure prediction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4338

Search results for: protein secondary structure prediction

4038 Spatial Variation of WRF Model Rainfall Prediction over Uganda

Authors: Isaac Mugume, Charles Basalirwa, Daniel Waiswa, Triphonia Ngailo

Abstract:

Rainfall is a major climatic parameter affecting many sectors such as health, agriculture and water resources. Its quantitative prediction remains a challenge to weather forecasters although numerical weather prediction models are increasingly being used for rainfall prediction. The performance of six convective parameterization schemes, namely the Kain-Fritsch scheme, the Betts-Miller-Janjic scheme, the Grell-Deveny scheme, the Grell-3D scheme, the Grell-Fretas scheme, the New Tiedke scheme of the weather research and forecast (WRF) model regarding quantitative rainfall prediction over Uganda is investigated using the root mean square error for the March-May (MAM) 2013 season. The MAM 2013 seasonal rainfall amount ranged from 200 mm to 900 mm over Uganda with northern region receiving comparatively lower rainfall amount (200–500 mm); western Uganda (270–550 mm); eastern Uganda (400–900 mm) and the lake Victoria basin (400–650 mm). A spatial variation in simulated rainfall amount by different convective parameterization schemes was noted with the Kain-Fritsch scheme over estimating the rainfall amount over northern Uganda (300–750 mm) but also presented comparable rainfall amounts over the eastern Uganda (400–900 mm). The Betts-Miller-Janjic, the Grell-Deveny, and the Grell-3D underestimated the rainfall amount over most parts of the country especially the eastern region (300–600 mm). The Grell-Fretas captured rainfall amount over the northern region (250–450 mm) but also underestimated rainfall over the lake Victoria Basin (150–300 mm) while the New Tiedke generally underestimated rainfall amount over many areas of Uganda. For deterministic rainfall prediction, the Grell-Fretas is recommended for rainfall prediction over northern Uganda while the Kain-Fritsch scheme is recommended over eastern region.

Keywords: Convective parameterization schemes, March-May 2013 rainfall season, spatial variation of parameterization schemes over Uganda, WRF model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1176
4037 Assessment of the Adaptive Pushover Analysis Using Displacement-based Loading in Prediction the Seismic Behaviour of the Unsymmetric-Plan Buildings

Authors: M.O. Makhmalbaf, F. Mohajeri Nav, M. Zabihi Samani

Abstract:

The recent drive for use of performance-based methodologies in design and assessment of structures in seismic areas has significantly increased the demand for the development of reliable nonlinear inelastic static pushover analysis tools. As a result, the adaptive pushover methods have been developed during the last decade, which unlike their conventional pushover counterparts, feature the ability to account for the effect that higher modes of vibration and progressive stiffness degradation might have on the distribution of seismic storey forces. Even in advanced pushover methods, little attention has been paid to the Unsymmetric structures. This study evaluates the seismic demands for three dimensional Unsymmetric-Plan buildings determined by the Displacement-based Adaptive Pushover (DAP) analysis, which has been introduced by Antoniou and Pinho [2004]. The capability of DAP procedure in capturing the torsional effects due to the irregularities of the structures, is investigated by comparing its estimates to the exact results, obtained from Incremental Dynamic Analysis (IDA). Also the capability of the procedure in prediction the seismic behaviour of the structure is discussed.

Keywords: Nonlinear static procedures, Unsymmetric-PlanBuildings, Torsional effects, IDA.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2723
4036 Free Fatty Acid Assessment of Crude Palm Oil Using a Non-Destructive Approach

Authors: Siti Nurhidayah Naqiah Abdull Rani, Herlina Abdul Rahim, Rashidah Ghazali, Noramli Abdul Razak

Abstract:

Near infrared (NIR) spectroscopy has always been of great interest in the food and agriculture industries. The development of prediction models has facilitated the estimation process in recent years. In this study, 110 crude palm oil (CPO) samples were used to build a free fatty acid (FFA) prediction model. 60% of the collected data were used for training purposes and the remaining 40% used for testing. The visible peaks on the NIR spectrum were at 1725 nm and 1760 nm, indicating the existence of the first overtone of C-H bands. Principal component regression (PCR) was applied to the data in order to build this mathematical prediction model. The optimal number of principal components was 10. The results showed R2=0.7147 for the training set and R2=0.6404 for the testing set.

Keywords: Palm oil, fatty acid, NIRS, regression.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4325
4035 Perception of Secondary Schools’ Students on Computer Education in Federal Capital Territory (FCT-Abuja), Nigeria

Authors: Salako Emmanuel Adekunle

Abstract:

Computer education is referred to as the knowledge and ability to use computers and related technology efficiently, with a range of skills covering levels from basic use to advance. Computer continues to make an ever-increasing impact on all aspect of human endeavours such as education. With numerous benefits of computer education, what are the insights of students on computer education? This study investigated the perception of senior secondary school students on computer education in Federal Capital Territory (FCT), Abuja, Nigeria. A sample of 7500 senior secondary schools students was involved in the study, one hundred (100) private and fifty (50) public schools within FCT. They were selected by using simple random sampling technique. A questionnaire [PSSSCEQ] was developed and validated through expert judgement and reliability coefficient of 0.84 was obtained. It was used to gather relevant data on computer education. Findings confirmed that the students in the FCT had positive perception on computer education. Some factors were identified that affect students’ perception on computer education. The null hypotheses were tested using t-test and ANOVA statistical analyses at 0.05 level of significance. Based on these findings, some recommendations were made which include competent teachers should be employed into all secondary schools. This will help students to acquire relevant knowledge in computer education, technological supports should be provided to all secondary schools; this will help the users (students) to solve specific problems in computer education and financial supports should be provided to procure computer facilities that will enhance the teaching and the learning of computer education.

Keywords: Computer education, perception, secondary school, students.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4019
4034 Pre-Operative Tool for Facial-Post-Surgical Estimation and Detection

Authors: Ayat E. Ali, Christeen R. Aziz, Merna A. Helmy, Mohammed M. Malek, Sherif H. El-Gohary

Abstract:

Goal: Purpose of the project was to make a plastic surgery prediction by using pre-operative images for the plastic surgeries’ patients and to show this prediction on a screen to compare between the current case and the appearance after the surgery. Methods: To this aim, we implemented a software which used data from the internet for facial skin diseases, skin burns, pre-and post-images for plastic surgeries then the post- surgical prediction is done by using K-nearest neighbor (KNN). So we designed and fabricated a smart mirror divided into two parts a screen and a reflective mirror so patient's pre- and post-appearance will be showed at the same time. Results: We worked on some skin diseases like vitiligo, skin burns and wrinkles. We classified the three degrees of burns using KNN classifier with accuracy 60%. We also succeeded in segmenting the area of vitiligo. Our future work will include working on more skin diseases, classify them and give a prediction for the look after the surgery. Also we will go deeper into facial deformities and plastic surgeries like nose reshaping and face slim down. Conclusion: Our project will give a prediction relates strongly to the real look after surgery and decrease different diagnoses among doctors. Significance: The mirror may have broad societal appeal as it will make the distance between patient's satisfaction and the medical standards smaller.

Keywords: K-nearest neighbor, face detection, vitiligo, bone deformity.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 659
4033 A New Predictor of Coding Regions in Genomic Sequences using a Combination of Different Approaches

Authors: Aníbal Rodríguez Fuentes, Juan V. Lorenzo Ginori, Ricardo Grau Ábalo

Abstract:

Identifying protein coding regions in DNA sequences is a basic step in the location of genes. Several approaches based on signal processing tools have been applied to solve this problem, trying to achieve more accurate predictions. This paper presents a new predictor that improves the efficacy of three techniques that use the Fourier Transform to predict coding regions, and that could be computed using an algorithm that reduces the computation load. Some ideas about the combination of the predictor with other methods are discussed. ROC curves are used to demonstrate the efficacy of the proposed predictor, based on the computation of 25 DNA sequences from three different organisms.

Keywords: Bioinformatics, Coding region prediction, Computational load reduction, Digital Signal Processing, Fourier Transform.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1625
4032 Differentiation between Common Tick Species Using Molecular Biology Techniques in Saudi Arabia

Authors: Kholoud A. Al-Shammery , Badr El-Sabah A. Fetoh, Ahmed M. Alshammari

Abstract:

Protein and Esterase electrophoresis were used to genetically identify two Saudi tick species. Engorged females of the camel tick Hyalomma dromedarii (Koch) (Acari: Ixodidae) and the cattle tick Boophilus annulatus (Say) (Acari: Ixodidae) ticks collected from infested camels and cattle in the animals resting house at Hail region in KSA were used. The results showed that there are a variation in both of protein and esterase activity levels and a high polymorphism within and between the genera and species of Hyalomma and Boophilus . In conclusion, the protein and esterase electrophoretic analysis used in the present study could successfully distinguish among tick species, commonly found in Saudi Arabia.

Keywords: Molecular biology, The camel tick Hyalomma dromedarii, The cattle tick Boophilus annulatus , Ticks.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2887
4031 The Reliability of the Improved e-N Method for Transition Prediction as Checked by PSE Method

Authors: Caihong Su

Abstract:

Transition prediction of boundary layers has always been an important problem in fluid mechanics both theoretically and practically, yet notwithstanding the great effort made by many investigators, there is no satisfactory answer to this problem. The most popular method available is so-called e-N method which is heavily dependent on experiments and experience. The author has proposed improvements to the e-N method, so to reduce its dependence on experiments and experience to a certain extent. One of the key assumptions is that transition would occur whenever the velocity amplitude of disturbance reaches 1-2% of the free stream velocity. However, the reliability of this assumption needs to be verified. In this paper, transition prediction on a flat plate is investigated by using both the improved e-N method and the parabolized stability equations (PSE) methods. The results show that the transition locations predicted by both methods agree reasonably well with each other, under the above assumption. For the supersonic case, the critical velocity amplitude in the improved e-N method should be taken as 0.013, whereas in the subsonic case, it should be 0.018, both are within the range 1-2%.

Keywords: Boundary layer, e-N method, PSE, Transition

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1470
4030 A Proposed Performance Prediction Approach for Manufacturing Processes using ANNs

Authors: M. S. Abdelwahed, M. A. El-Baz, T. T. El-Midany

Abstract:

this paper aims to provide an approach to predict the performance of the product produced after multi-stages of manufacturing processes, as well as the assembly. Such approach aims to control and subsequently identify the relationship between the process inputs and outputs so that a process engineer can more accurately predict how the process output shall perform based on the system inputs. The approach is guided by a six-sigma methodology to obtain improved performance. In this paper a case study of the manufacture of a hermetic reciprocating compressor is presented. The application of artificial neural networks (ANNs) technique is introduced to improve performance prediction within this manufacturing environment. The results demonstrate that the approach predicts accurately and effectively.

Keywords: Artificial neural networks, Reciprocating compressor manufacturing, Performance prediction, Quality improvement

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1744
4029 TanSSe-L System PIM Manual Transformation to Moodle as a TanSSe-L System Specific PIM

Authors: Kalinga Ellen A., Bagile Burchard B.

Abstract:

Tanzania Secondary Schools e-Learning (TanSSe-L) system is a customized learning management system (LMS) developed to enable ICT support in teaching and learning functions. Methodologies involved in the development of TanSSe-L system are Object oriented system analysis and design with UML to create and model TanSSe-L system database structure in the form of a design class diagram, Model Driven Architecture (MDA) to provide a well defined process in TanSSe-L system development, where MDA conceptual layers were integrated with system development life cycle and customization of open source learning management system which was used during implementation stage to create a timely functional TanSSe-L system. Before customization, a base for customization was prepared. This was the manual transformation from TanSSe-L system platform independent models (PIM) to TanSSe-L system specific PIM. This paper presents how Moodle open source LMS was analyzed and prepared to be the TanSSe-L system specific PIM as applied by MDA.

Keywords: Customization, e-Learning, MDA Transformation, Moodle, Secondary Schools, Tanzania.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1978
4028 ANN based Multi Classifier System for Prediction of High Energy Shower Primary Energy and Core Location

Authors: Gitanjali Devi, Kandarpa Kumar Sarma, Pranayee Datta, Anjana Kakoti Mahanta

Abstract:

Cosmic showers, during the transit through space, produce sub - products as a result of interactions with the intergalactic or interstellar medium which after entering earth generate secondary particles called Extensive Air Shower (EAS). Detection and analysis of High Energy Particle Showers involve a plethora of theoretical and experimental works with a host of constraints resulting in inaccuracies in measurements. Therefore, there exist a necessity to develop a readily available system based on soft-computational approaches which can be used for EAS analysis. This is due to the fact that soft computational tools such as Artificial Neural Network (ANN)s can be trained as classifiers to adapt and learn the surrounding variations. But single classifiers fail to reach optimality of decision making in many situations for which Multiple Classifier System (MCS) are preferred to enhance the ability of the system to make decisions adjusting to finer variations. This work describes the formation of an MCS using Multi Layer Perceptron (MLP), Recurrent Neural Network (RNN) and Probabilistic Neural Network (PNN) with data inputs from correlation mapping Self Organizing Map (SOM) blocks and the output optimized by another SOM. The results show that the setup can be adopted for real time practical applications for prediction of primary energy and location of EAS from density values captured using detectors in a circular grid.

Keywords: EAS, Shower, Core, ANN, Location.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1262
4027 Production of H5N1 Hemagglutinin inTrichoplusia ni Larvae by a Novel Bi-cistronic Baculovirus Expression Vector

Authors: Tzyy Rong Jinn, Nguyen Tiep Khac, Tzong Yuan Wu

Abstract:

Highly pathogenic avian influenza (HPAI) H5N1 viruses have created demand for a cost-effective vaccine to prevent a pandemic of the disease. Here, we report that Trichoplusia ni (T. ni) larvae can act as a cost-effective bioreactor to produce recombinant HA5 (rH5HA) proteins as an potential effective vaccine for chickens. To facilitate the recombinant virus identification, virus titer determination and access the infected larvae, we employed the internal ribosome entry site (IRES) derived from Perina nuda virus (PnV, belongs to insect picorna like Iflavirus genus) to construct a bi-cistronic baculovirus expression vector that can express the rH5HA protein and enhanced green fluorescent protein (EGFP) simultaneously. Western blot analysis revealed that the 70 kDa rH5HA protein and partially cleaved products (40 kDa H5HA1) were generated in T. ni larvae infected with recombinant baculovirus carrying the H5HA gene. These data suggest that the baculovirus-larvae recombinant protein expression system could be a cost-effective platform for H5N1 vaccine production.

Keywords: Avian Influenza, baculovirus, hemagglutinin, Trichoplusia ni larvae

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1769
4026 Generation of Highly Ordered Porous Antimony-Doped Tin Oxide Film by A Simple Coating Method with Colloidal Template

Authors: Asep Bayu Dani Nandiyanto, Asep Suhendi, Yutaka Kisakibaru, Takashi Ogi, Kikuo Okuyama

Abstract:

An ordered porous antimony-doped tin oxide (ATO) film was successfully prepared using a simple coating process with colloidal templates. The facile production was effective when a combination of 16-nm ATO (as a model of an inorganic nanoparticle) and polystyrene (PS) spheres (as a model of the template) weresimply coated to produce a composite ATO/PS film. Heat treatment was then used to remove the PS and produce the porous film. The porous film with a spherical pore shape and a highly ordered porous structure could be obtained. A potential way for the control of pore size could be also achieved by changing initial template size. The theoretical explanation and mechanism of porous formation were also added, which would be important for the scaling-up prediction and estimation.

Keywords: Porous structure film; ATO particle; Ultra-low refractive index; vertical drop method; Low-density material;

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1536
4025 Application of Thermoplastic Microbioreactor to the Single Cell Study of Budding Yeast to Decipher the Effect of 5-Hydroxymethylfurfural on Growth

Authors: Elif Gencturk, Ekin Yurdakul, Ahmet Y. Celik, Senol Mutlu, Kutlu O. Ulgen

Abstract:

Yeast cells are generally used as a model system of eukaryotes due to their complex genetic structure, rapid growth ability in optimum conditions, easy replication and well-defined genetic system properties. Thus, yeast cells increased the knowledge of the principal pathways in humans. During fermentation, carbohydrates (hexoses and pentoses) degrade into some toxic by-products such as 5-hydroxymethylfurfural (5-HMF or HMF) and furfural. HMF influences the ethanol yield, and ethanol productivity; it interferes with microbial growth and is considered as a potent inhibitor of bioethanol production. In this study, yeast single cell behavior under HMF application was monitored by using a continuous flow single phase microfluidic platform. Microfluidic device in operation is fabricated by hot embossing and thermo-compression techniques from cyclo-olefin polymer (COP). COP is biocompatible, transparent and rigid material and it is suitable for observing fluorescence of cells considering its low auto-fluorescence characteristic. The response of yeast cells was recorded through Red Fluorescent Protein (RFP) tagged Nop56 gene product, which is an essential evolutionary-conserved nucleolar protein, and also a member of the box C/D snoRNP complexes. With the application of HMF, yeast cell proliferation continued but HMF slowed down the cell growth, and after HMF treatment the cell proliferation stopped. By the addition of fresh nutrient medium, the yeast cells recovered after 6 hours of HMF exposure. Thus, HMF application suppresses normal functioning of cell cycle but it does not cause cells to die. The monitoring of Nop56 expression phases of the individual cells shed light on the protein and ribosome synthesis cycles along with their link to growth. Further computational study revealed that the mechanisms underlying the inhibitory or inductive effects of HMF on growth are enriched in functional categories of protein degradation, protein processing, DNA repair and multidrug resistance. The present microfluidic device can successfully be used for studying the effects of inhibitory agents on growth by single cell tracking, thus capturing cell to cell variations. By metabolic engineering techniques, engineered strains can be developed, and the metabolic network of the microorganism can thus be manipulated such that chemical overproduction of target metabolite is achieved along with the maximum growth/biomass yield.  

Keywords: COP, HMF, ribosome biogenesis, thermoplastic microbioreactor, yeast.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 635
4024 Comparison of Nutritional and Chemical Parameters of Soymilk and Cow milk

Authors: Bahareh Hajirostamloo

Abstract:

Cow milk, is a product of the mammary gland and soymilk is a beverage made from soybeans; it is the liquid that remains after soybeans are soaked. In this research effort, we compared nutritional parameters of this two kind milk such as total fat, fiber, protein, minerals (Ca, Fe and P), fatty acids, carbohydrate, lactose, water, total solids, ash, pH, acidity and calories content in one cup (245 g). Results showed soymilk contains 4.67 grams of fat, 0.52 of fatty acids, 3.18 of fiber, 6.73 of protein, 4.43 of carbohydrate, 0.00 of lactose, 228.51 of water, 10.40 of total solids and 0.66 of ash, also 9.80 milligrams of Ca, 1.42 of Fe, and 120.05 of P, 79 Kcal of calories, pH=6.74 and acidity was 0.24%. Cow milk contains 8.15 grams of fat, 5.07 of fatty acids, 0.00 of fiber, 8.02 of protein, 11.37 of carbohydrate, ´Çá4.27 of lactose, 214.69 of water, 12.90 of total solids, 1.75 of ash, 290.36 milligrams of Ca, 0.12 of Fe, and 226.92 of P, 150 Kcal of calories, pH=6.90 and acidity was 0.21% . Soy milk is one of plant-based complete proteins and cow milk is a rich source of nutrients as well. Cow milk is containing near twice as much fat as and ten times more fatty acids do soymilk. Cow milk contains greater amounts of mineral (except Fe) it contain more than three hundred times the amount of Ca and nearly twice the amount of P as does soymilk but soymilk contains more Fe (ten time more) than does cow milk. Cow milk and soy milk contain nearly identical amounts of protein and water and fiber is a big plus, dairy has none. Although what we choose to drink is really a mater of personal preference and our health objectives but looking at the comparison, soy looks like healthier choices.

Keywords: Soymilk, cow milk, nutritional, comparison.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7275
4023 A Spatial Information Network Traffic Prediction Method Based on Hybrid Model

Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

Abstract:

Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: Spatial Information Network, Traffic prediction, Wavelet decomposition, Time series model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 574
4022 Simulation Study on the Thin-walled Tube Structure of a Vehicle Simulator Crash Testing Equipment

Authors: Xu Zhang, Qi Jiang, Liwei Li, Weiwei Cui, Jijun Cui, Yang Cao, Hairong Zhao

Abstract:

A kind of crash energy absorption structure adopted by vehicle simulator crash testing equipment based on mechanical energy storage was studied. Dynamic explicit finite element simulation was achieved for thin-walled tube structure under different conditions of section shape, thickness and inducement groove style. Crash energy absorption property of the structure was obtained. After optimization, a reasonable structure was given which can meet current vehicle crash regulation. And the optimized structure can be adopted in vehicle simulator, which can increase the practicability of the testing equipment.

Keywords: thin-walled tube structure, crash energy absorption, deceleration, finite element simulation

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1709
4021 On Adaptive Optimization of Filter Performance Based on Markov Representation for Output Prediction Error

Authors: Hong Son Hoang, Remy Baraille

Abstract:

This paper addresses the problem of how one can improve the performance of a non-optimal filter. First the theoretical question on dynamical representation for a given time correlated random process is studied. It will be demonstrated that for a wide class of random processes, having a canonical form, there exists a dynamical system equivalent in the sense that its output has the same covariance function. It is shown that the dynamical approach is more effective for simulating and estimating a Markov and non- Markovian random processes, computationally is less demanding, especially with increasing of the dimension of simulated processes. Numerical examples and estimation problems in low dimensional systems are given to illustrate the advantages of the approach. A very useful application of the proposed approach is shown for the problem of state estimation in very high dimensional systems. Here a modified filter for data assimilation in an oceanic numerical model is presented which is proved to be very efficient due to introducing a simple Markovian structure for the output prediction error process and adaptive tuning some parameters of the Markov equation.

Keywords: Statistical simulation, canonical form, dynamical system, Markov and non-Markovian processes, data assimilation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1261
4020 Prediction of Henry's Constant in Polymer Solutions using the Peng-Robinson Equation of State

Authors: Somayeh Tourani, Alireza Behvandi

Abstract:

The peng-Robinson (PR), a cubic equation of state (EoS), is extended to polymers by using a single set of energy (A1, A2, A3) and co-volume (b) parameters per polymer fitted to experimental volume data. Excellent results for the volumetric behavior of the 11 polymer up to 2000 bar pressure are obtained. The EoS is applied to the correlation and prediction of Henry constants in polymer solutions comprising three polymer and many nonpolar and polar solvents, including supercritical gases. The correlation achieved with two adjustable parameter is satisfactory compared with the experimental data. As a result, the present work provides a simple and useful model for the prediction of Henry's constant for polymer containing systems including those containing polar, nonpolar and supercritical fluids.

Keywords: Equation of state, Henry's constant, Peng-Robinson, polymer solution.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2087
4019 Artificial Neural Networks Modeling in Water Resources Engineering: Infrastructure and Applications

Authors: M. R. Mustafa, M. H. Isa, R. B. Rezaur

Abstract:

The use of artificial neural network (ANN) modeling for prediction and forecasting variables in water resources engineering are being increasing rapidly. Infrastructural applications of ANN in terms of selection of inputs, architecture of networks, training algorithms, and selection of training parameters in different types of neural networks used in water resources engineering have been reported. ANN modeling conducted for water resources engineering variables (river sediment and discharge) published in high impact journals since 2002 to 2011 have been examined and presented in this review. ANN is a vigorous technique to develop immense relationship between the input and output variables, and able to extract complex behavior between the water resources variables such as river sediment and discharge. It can produce robust prediction results for many of the water resources engineering problems by appropriate learning from a set of examples. It is important to have a good understanding of the input and output variables from a statistical analysis of the data before network modeling, which can facilitate to design an efficient network. An appropriate training based ANN model is able to adopt the physical understanding between the variables and may generate more effective results than conventional prediction techniques.

Keywords: ANN, discharge, modeling, prediction, sediment,

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5605
4018 Aggregate Angularity on the Permanent Deformation Zones of Hot Mix Asphalt

Authors: Lee P. Leon, Raymond Charles

Abstract:

This paper presents a method of evaluating the effect of aggregate angularity on hot mix asphalt (HMA) properties and its relationship to the Permanent Deformation resistance. The research concluded that aggregate particle angularity had a significant effect on the Permanent Deformation performance, and also that with an increase in coarse aggregate angularity there was an increase in the resistance of mixes to Permanent Deformation. A comparison between the measured data and predictive data of permanent deformation predictive models showed the limits of existing prediction models. The numerical analysis described the permanent deformation zones and concluded that angularity has an effect of the onset of these zones. Prediction of permanent deformation help road agencies and by extension economists and engineers determine the best approach for maintenance, rehabilitation, and new construction works of the road infrastructure.

Keywords: Aggregate angularity, asphalt concrete, permanent deformation, rutting prediction.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2044
4017 Introduction of the Fluid-Structure Coupling into the Force Analysis Technique

Authors: Océane Grosset, Charles Pézerat, Jean-Hugh Thomas, Frédéric Ablitzer

Abstract:

This paper presents a method to take into account the fluid-structure coupling into an inverse method, the Force Analysis Technique (FAT). The FAT method, also called RIFF method (Filtered Windowed Inverse Resolution), allows to identify the force distribution from local vibration field. In order to only identify the external force applied on a structure, it is necessary to quantify the fluid-structure coupling, especially in naval application, where the fluid is heavy. This method can be decomposed in two parts, the first one consists in identifying the fluid-structure coupling and the second one to introduced it in the FAT method to reconstruct the external force. Results of simulations on a plate coupled with a cavity filled with water are presented.

Keywords: Fluid-structure coupling, inverse methods, naval, vibrations.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1117
4016 Traffic Flow Prediction using Adaboost Algorithm with Random Forests as a Weak Learner

Authors: Guy Leshem, Ya'acov Ritov

Abstract:

Traffic Management and Information Systems, which rely on a system of sensors, aim to describe in real-time traffic in urban areas using a set of parameters and estimating them. Though the state of the art focuses on data analysis, little is done in the sense of prediction. In this paper, we describe a machine learning system for traffic flow management and control for a prediction of traffic flow problem. This new algorithm is obtained by combining Random Forests algorithm into Adaboost algorithm as a weak learner. We show that our algorithm performs relatively well on real data, and enables, according to the Traffic Flow Evaluation model, to estimate and predict whether there is congestion or not at a given time on road intersections.

Keywords: Machine Learning, Boosting, Classification, TrafficCongestion, Data Collecting, Magnetic Loop Detectors, SignalizedIntersections, Traffic Signal Timing Optimization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3861
4015 Prediction of the Characteristics of Transformer Oil under Different Operation Conditions

Authors: EL-Sayed M. M. EL-Refaie, Mohamed R. Salem, Wael A. Ahmed

Abstract:

Power systems and transformer are intrinsic apparatus, therefore its reliability and safe operation is important to determine their operation conditions, and the industry uses quality control tests in the insulation design of oil filled transformers. Hence the service period effect on AC dielectric strength is significant. The effect of aging on transformer oil physical, chemical and electrical properties was studied using the international testing methods for the evaluation of transformer oil quality. The study was carried out on six transformers operate in the field and for monitoring periods over twenty years. The properties which are strongly time dependent were specified and those which have a great impact on the transformer oil acidity, breakdown voltage and dissolved gas analysis were defined. Several tests on the transformers oil were studied to know the time of purifying or changing it, moreover prediction of the characteristics of it under different operation conditions.

Keywords: Dissolved Gas Analysis, Prediction, Purifying and Changing.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3681
4014 Numerical Prediction of NOX in the Exhaust of a Compression Ignition Engine

Authors: A. A. Pawar, R. R. Kulkarni

Abstract:

For numerical prediction of the NOX in the exhaust of a compression ignition engine a model was developed by considering the parameter equivalence ratio. This model was validated by comparing the predicted results of NOX with experimental ones. The ultimate aim of the work was to access the applicability, robustness and performance of the improved NOX model against other NOX models.

Keywords: Biodiesel fueled engine, equivalence ratio, Compression ignition engine, exhausts gas temperature, NOX formation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2046
4013 Funding Innovative Activities in Firms: The Ownership Structure and Governance Linkage - Evidence from Mongolia

Authors: Ernest Nweke, Enkhtuya Bavuudorj

Abstract:

The harsh realities of the scandalous failure of several notable corporations in the past two decades have inextricably resulted in a surge in corporate governance studies. Nevertheless, little or no attention has been paid to corporate governance studies in Mongolian firms and much less to the comprehension of the correlation among ownership structure, corporate governance mechanisms and trend of innovative activities. Innovation is the bed rock of enterprise success. However, the funding and support for innovative activities in many firms are to a great extent determined by the incentives provided by the firm’s internal and external governance mechanisms. Mongolia is an East Asian country currently undergoing a fast-paced transition from socialist to democratic system and it is a widely held view that private ownership as against public ownership fosters innovation. Hence, following the privatization policy of Mongolian Government which has led to the transfer of the ownership of hitherto state controlled and state directed firms to private individuals and organizations, expectations are high that sufficient motivation would be provided for firm managers to engage in innovative activities. This research focuses on the relationship between ownership structure, corporate governance on one hand and the level of innovation on the hand. The paper is empirical in nature and derives data from both reliable secondary and primary sources. Secondary data for the study was in respect of ownership structure of Mongolian listed firms and innovation trend in Mongolia generally. These were analyzed using tables, charts, bars and percentages. Personal interviews and surveys were held to collect primary data. Primary data was in respect of corporate governance practices in Mongolian firms and were collected using structured questionnaire. Out of a population of three hundred and twenty (320) companies listed on the Mongolian Stock Exchange (MSE), a sample size of thirty (30) randomly selected companies was utilized for the study. Five (5) management level employees were surveyed in each selected firm giving a total of one hundred and fifty (150) respondents. Data collected were analyzed and research hypotheses tested using Chi-Square test statistic. Research results showed that corporate governance mechanisms were better and have significantly improved overtime in privately held as opposed to publicly owned firms. Consequently, the levels of innovation in privately held firms were considerably higher. It was concluded that a significant and positive relationship exists between private ownership and good corporate governance on one hand and the level of funding provided for innovative activities in Mongolian firms on the other hand.

Keywords: Corporate governance, innovation, ownership structure, stock exchange.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1720
4012 Integration of Educational Data Mining Models to a Web-Based Support System for Predicting High School Student Performance

Authors: Sokkhey Phauk, Takeo Okazaki

Abstract:

The challenging task in educational institutions is to maximize the high performance of students and minimize the failure rate of poor-performing students. An effective method to leverage this task is to know student learning patterns with highly influencing factors and get an early prediction of student learning outcomes at the timely stage for setting up policies for improvement. Educational data mining (EDM) is an emerging disciplinary field of data mining, statistics, and machine learning concerned with extracting useful knowledge and information for the sake of improvement and development in the education environment. The study is of this work is to propose techniques in EDM and integrate it into a web-based system for predicting poor-performing students. A comparative study of prediction models is conducted. Subsequently, high performing models are developed to get higher performance. The hybrid random forest (Hybrid RF) produces the most successful classification. For the context of intervention and improving the learning outcomes, a feature selection method MICHI, which is the combination of mutual information (MI) and chi-square (CHI) algorithms based on the ranked feature scores, is introduced to select a dominant feature set that improves the performance of prediction and uses the obtained dominant set as information for intervention. By using the proposed techniques of EDM, an academic performance prediction system (APPS) is subsequently developed for educational stockholders to get an early prediction of student learning outcomes for timely intervention. Experimental outcomes and evaluation surveys report the effectiveness and usefulness of the developed system. The system is used to help educational stakeholders and related individuals for intervening and improving student performance.

Keywords: Academic performance prediction system, prediction model, educational data mining, dominant factors, feature selection methods, student performance.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 918
4011 A Novel Strategy for Oriented Protein Immobilization

Authors: Ching-Wei Tsai, Chih-I Liu, Ruoh-Chyu Ruaana

Abstract:

A new strategy for oriented immobilization of proteins was proposed. The strategy contains two steps. The first step is to search for a docking site away from the active site on the protein surface. The second step is trying to find a ligand that is able to grasp the targeted site of the protein. To avoid ligand binding to the active site of protein, the targeted docking site is selected to own opposite charges to those near the active site. To enhance the ligand-protein binding, both hydrophobic and electrostatic interactions need to be included. The targeted docking site should therefore contain hydrophobic amino acids. The ligand is then selected through the help of molecular docking simulations. The enzyme α-amylase derived from Aspergillus oryzae (TAKA) was taken as an example for oriented immobilization. The active site of TAKA is surrounded by negatively charged amino acids. All the possible hydrophobic sites on the surface of TAKA were evaluated by the free energy estimation through benzene docking. A hydrophobic site on the opposite side of TAKA-s active site was found to be positive in net charges. A possible ligand, 3,3-,4,4- – Biphenyltetra- carboxylic acid (BPTA), was found to catch TAKA by the designated docking site. Then, the BPTA molecules were grafted onto silica gels and measured the affinity of TAKA adsorption and the specific activity of thereby immobilized enzymes. It was found that TAKA had a dissociation constant as low as 7.0×10-6 M toward the ligand BPTA on silica gel. The increase in ionic strength has little effect on the adsorption of TAKA, which indicated the existence of hydrophobic interaction between ligands and proteins. The specific activity of the immobilized TAKA was compared with the randomly adsorbed TAKA on primary amine containing silica gel. It was found that the orderly immobilized TAKA owns a specific activity twice as high as the one randomly adsorbed by ionic interaction.

Keywords: Protein Oriented immobilization, Molecular docking, ligand design, surface modification.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1735
4010 Nutritional Evaluation of Sorghum Flour (Sorghumbicolor L. Moench) During Processing of Injera

Authors: Noha A. Mohammed, Isam A. Mohamed Ahmed, Elfadil E. Babiker

Abstract:

The present study was carried out to evaluate the nutritional value of sorghum flour during processing of injera (unleavened thick bread). The proximate composition of sorghum flour before and after fermentation and that of injera was determined. Compared to the raw flour and fermented one, injera had low protein (11.55%), ash (1.57%) and fat (2.40%) contents but high in fiber content. Moreover, injera was found to have significantly (P ≤ 0.05) higher energy (389.08 Kcal/100g) compared to raw and fermented sorghum flour. Injera contained lower levels of anti-nutritional factors (polyphenols, phytate and tannins) compared to raw and fermented sorghum. Also it was found to be rich in Ca (4.75mg/100g), Fe (3.95 mg/100g), and Cu (0.7 mg/100g) compared to that of raw and fermented flour. Moreover, both the extractable minerals and protein digestibility were high for injera due to low amount of anti-nutrients. Injera was found to contain an appreciable amount of amino acids except arginine and tyrosine.

Keywords: Cooking, Fermentation, Malt, Protein fractions, Sorghum.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4054
4009 Construction of Recombinant E.coli Expressing Fusion Protein to Produce 1,3-Propanediol

Authors: Rosarin Rujananon, Poonsuk Prasertsan, Amornrat Phongdara, Tanate Panrat, Jibin Sun, Sugima Rappert, An-Ping Zeng

Abstract:

In this study, a synthetic pathway was created by assembling genes from Clostridium butyricum and Escherichia coli in different combinations. Among the genes were dhaB1 and dhaB2 from C. butyricum VPI1718 coding for glycerol dehydratase (GDHt) and its activator (GDHtAc), respectively, involved in the conversion of glycerol to 3-hydroxypropionaldehyde (3-HPA). The yqhD gene from E.coli BL21 was also included which codes for an NADPHdependent 1,3-propanediol oxidoreductase isoenzyme (PDORI) reducing 3-HPA to 1,3-propanediol (1,3-PD). Molecular modeling analysis indicated that the conformation of fusion protein of YQHD and DHAB1 was favorable for direct molecular channeling of the intermediate 3-HPA. According to the simulation results, the yqhD and dhaB1 gene were assembled in the upstream of dhaB2 to express a fusion protein, yielding the recombinant strain E. coliBL21 (DE3)//pET22b+::yqhD-dhaB1_dhaB2 (strain BP41Y3). Strain BP41Y3 gave 10-fold higher 1,3-PD concentration than E. coliBL21 (DE3)//pET22b+::yqhD-dhaB1_dhaB2 (strain BP31Y2) expressing the recombinant enzymes simultaneously but in a non-fusion mode. This is the first report using a gene fusion approach to enhance the biological conversion of glycerol to the value added compound 1,3- PD.

Keywords: Recombinant E.coli, 1, 3-propanediol, glycerol, fusion protein.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1977