Search results for: parameters selection

Authors: W. Du, X. Wang, Jun Cao, H. F. Wang

Abstract:

Due to the randomness and uncertainty of wind energy, modern power systems integrating large-scale wind generation will be significantly impacted in terms of system performance and technical challenges. System inertia with high wind penetration is decreasing when conventional thermal generators are gradually replaced by wind turbines, which do not naturally contribute to inertia response. The power imbalance caused by wind power or demand fluctuations leads to the instability of system frequency. Accordingly, the need to attach the supplementary virtual inertia control to wind farms (WFs) strongly arises. When multi-wind farms are connected to the grid simultaneously, the selection of which critical WFs to install the virtual inertia control is greatly important to enhance the stability of system frequency. By building the small signal model of wind power systems considering frequency regulation, the installation locations are identified by the geometric measures of the mode observability of WFs. In addition, this paper takes the impacts of grid topology and selection of feedback control signals into consideration. Finally, simulations are conducted on a multi-wind farms power system and the results demonstrate that the designed virtual inertia control method can effectively assist the frequency regulation.

Keywords: frequency regulation, virtual inertia control, installation locations, observability, wind farms

Procedia PDF Downloads 372

Authors: Mukesh Kumar Shah, Tushar Gupta

Abstract:

An Upgraded Cuckoo Search Algorithm is proposed here to solve optimization problems based on the improvements made in the earlier versions of Cuckoo Search Algorithm. Short comings of the earlier versions like slow convergence, trap in local optima improved in the proposed version by random initialization of solution by suggesting an Improved Lambda Iteration Relaxation method, Random Gaussian Distribution Walk to improve local search and further proposing Greedy Selection to accelerate to optimized solution quickly and by “Study Nearby Strategy” to improve global search performance by avoiding trapping to local optima. It is further proposed to generate better solution by Crossover Operation. The proposed strategy used in algorithm shows superiority in terms of high convergence speed over several classical algorithms. Three standard algorithms were tested on a 6-generator standard test system and the results are presented which clearly demonstrate its superiority over other established algorithms. The algorithm is also capable of handling higher unit systems.

Keywords: economic dispatch, gaussian selection operator, prohibited operating zones, ramp rate limits

Procedia PDF Downloads 106

Authors: Aakansha Gupta, Neha Vadnere, Tapasvi Soni, M. Anbarsi

Abstract:

Protein secondary structure prediction is one of the most important goals pursued by bioinformatics and theoretical chemistry; it is highly important in medicine and biotechnology. Some aspects of protein functions and genome analysis can be predicted by secondary structure prediction. This is used to help annotate sequences, classify proteins, identify domains, and recognize functional motifs. In this paper, we represent protein secondary structure as a mathematical model. To extract and predict the protein secondary structure from the primary structure, we require a set of parameters. Any constants appearing in the model are specified by these parameters, which also provide a mechanism for efficient and accurate use of data. To estimate these model parameters there are many algorithms out of which the most popular one is the EM algorithm or called the Expectation Maximization Algorithm. These model parameters are estimated with the use of protein datasets like RS126 by using the Bayesian Probabilistic method (data set being categorical). This paper can then be extended into comparing the efficiency of EM algorithm to the other algorithms for estimating the model parameters, which will in turn lead to an efficient component for the Protein Secondary Structure Prediction. Further this paper provides a scope to use these parameters for predicting secondary structure of proteins using machine learning techniques like neural networks and fuzzy logic. The ultimate objective will be to obtain greater accuracy better than the previously achieved.

Keywords: model parameters, expectation maximization algorithm, protein secondary structure prediction, bioinformatics

Procedia PDF Downloads 445

Authors: Cruz, G. P., Nagamatsu, R. N., Scacchetti, F. A. P., Merlin, F. K.

Abstract:

This study aims to assess a set of technical parameters that provide quality products to the companies that produce caps, APL Apucarana / PR, the city that produces most Brazilian caps, in order to verify the potential of Brazilian caps to compete with international brands, recognized by the standard of excellence when it comes to quality of its products. The determination of the technical parameters was arbitrated from textile ABNT, a total of six technical parameters, providing eight tests for cotton caps. For the evaluation, we used as reference a leading brand recognized worldwide (based on their sales volume in $) for comparison with 3 companies of the APL Apucarana. The results showed that, of the 8 tests, of 8 tests, the companies Apucarana did not obtain better performance than the competitor. They obtained the same results in three tests and lower performance in 5. Given these values, it is concluded that local caps are not far from reaching the quality of leading brand. It is recommended that the APL companies use the parameters to evaluate their products, using this information to support decision-making that seek to improve both the product design and its production process, enabling the feasibility for faster international recognition . Thus, they may have an edge over its main competitor.

Keywords: technical parameters, making caps, quality, evaluation

Procedia PDF Downloads 315

Authors: Polycarp Igbojekwe

Abstract:

The main objective of this study was to determine if emotional labour has become a criterion in performance appraisal, job description, selection, and training schemes in the hotel industry in Nigeria. Our main assumption was that majority of hotel organizations have not built emotional labour into their human resources management schemes. Data were gathered by the use of structured questionnaires designed in Likert format, and interviews. The focus group was managers of the selected hotels. Analyses revealed that majority of the hotels have not built emotional labour into their human resources schemes particularly in the 1, 2, and 3-star hotels. It was observed that service employees of 1, 2, and 3-star hotels have not been adequately trained to perform emotional labour; a critical factor in quality service delivery. Managers of 1, 2, and 3-star hotels have not given serious thought to emotional labour as a critical factor in quality service delivery. The study revealed that suitability of an individual’s characteristics is not being considered as a criterion for selection and performance appraisal for service employees. The implication of this is that, person-job-fit is not seriously considered. It was observed that there has been a disconnect between required emotional competency, its recognition, evaluation, and training. Based on the findings of this study, it is concluded that selection, training, job description and performance appraisal instruments in use in hotels in Nigeria are inadequate. Human resource implications of the findings in this study are presented. It is recommended that hotel organizations should re-design and plan the emotional content and context of their human resources practices to reflect the emotional demands of front line jobs in the hotel industry and the crucial role emotional labour plays during service encounters.

Keywords: emotional labour, employee selection, job description, performance appraisal, person-job-fit, employee compensation

Procedia PDF Downloads 173

Authors: Jaehong Yu, Seoung Bum Kim

Abstract:

Clustering analysis can facilitate the extraction of intrinsic patterns in a dataset and reveal its natural groupings without requiring class information. For effective clustering analysis in high dimensional datasets, unsupervised dimensionality reduction is an important task. Unsupervised dimensionality reduction can generally be achieved by feature extraction or feature selection. In many situations, feature selection methods are more appropriate than feature extraction methods because of their clear interpretation with respect to the original features. The unsupervised feature selection can be categorized as feature subset selection and feature ranking method, and we focused on unsupervised feature ranking methods which evaluate the features based on their importance scores. Recently, several unsupervised feature ranking methods were developed based on ensemble approaches to achieve their higher accuracy and stability. However, most of the ensemble-based feature ranking methods require the true number of clusters. Furthermore, these algorithms evaluate the feature importance depending on the ensemble clustering solution, and they produce undesirable evaluation results if the clustering solutions are inaccurate. To address these limitations, we proposed an ensemble-based feature ranking method with random subspace and multiple-k ensemble (FRRM). The proposed FRRM algorithm evaluates the importance of each feature with the random subspace ensemble, and all evaluation results are combined with the ensemble importance scores. Moreover, FRRM does not require the determination of the true number of clusters in advance through the use of the multiple-k ensemble idea. Experiments on various benchmark datasets were conducted to examine the properties of the proposed FRRM algorithm and to compare its performance with that of existing feature ranking methods. The experimental results demonstrated that the proposed FRRM outperformed the competitors.

Keywords: clustering analysis, multiple-k ensemble, random subspace-based feature evaluation, unsupervised feature ranking

Procedia PDF Downloads 309

Authors: Rafid Saeed Abdulrazak Alshkaki

Abstract:

In this paper, zero-one inflated negative binomial distribution is considered, along with some of its structural properties, then its parameters were estimated using the method of moments. It is found that the method of moments to estimate the parameters of the zero-one inflated negative binomial models is not a proper method and may give incorrect conclusions.

Keywords: zero one inflated models, negative binomial distribution, moments estimator, non negative integer sampling

Procedia PDF Downloads 258

Authors: Mohita Singh, Sunil Sachdev, Amrita Singh

Abstract:

Background and Aim: Physical aerobic exercises promote positive changes in one’s mental health, intelligence, and ability to cope with stressful encounters. The present study was designed to explore the correlation between intelligence and stress parameters and to assess the correlation between the same parameters after the practice of one month of moderate-intensity physical exercise. Method: The study was conducted on thirty-five healthy male volunteer students to assess the correlation between stress parameters in subjects with varying level of general intelligence (GI) and emotional intelligence (EI). Correlation studies were again conducted after one month between the same parameters to evaluate the effect of moderate-intensity physical exercise (MIPE). Baseline values were recorded using standard scales. Result: IQ and EQ correlated negatively with both acute and chronic stress parameters and positively with each other. A positive correlation was found between acute and chronic stress. With the practice of one month of moderate-intensity physical exercise, there was significant increment between the parameters under study and hence improved results. Conclusion: MIPE improved correlation between GI, EI, stress parameters, and thus reduced stress and improved intelligence.

Keywords: emotional intelligence, general intelligence, moderate intensity physical exercise, stress response

Procedia PDF Downloads 113

Authors: Huai-Feng Wang, Meng-Lin Lou, Ru-Lin Zhang

Abstract:

One good analysis method in seismic response analysis is direct time integration, which widely adopts Rayleigh damping. An approach is presented for selection of Rayleigh damping coefficients to be used in seismic analyses to produce a response that is consistent with Modal damping response. In the presented approach, the expression of the error of peak response, acquired through complete quadratic combination method, and Rayleigh damping coefficients was set up and then the coefficients were produced by minimizing the error. Two finite element modes of soil layers, excited by 28 seismic waves, were used to demonstrate the feasibility and validity.

Keywords: Rayleigh damping, modal damping, damping coefficients, seismic response analysis

Procedia PDF Downloads 416

Authors: Churamani Pokhrel, C. B. Jha, S. R. Niraula, P. R. Pokharel

Abstract:

Human identification is one of the most challenging subjects that man has confronted. The determination of adult sex and stature are two of the four key factors (sex, stature, age, and race) in identification of an individual. Craniofacial and odontometric parameters are important tools for forensic anthropologists when it is not possible to apply advanced techniques for identification purposes. The present study provides anthropometric correlation of the parameters with stature and gender and also devises regression formulae for reconstruction of stature. A total of 312 Nepalese students with equal distribution of sex i.e., 156 male and 156 female students of age 18-35 years were taken for the study. Total of 10 parameters were measured (age, sex, stature, head circumference, head length, head breadth, facial height, bi-zygomatic width, mesio-distal canine width and inter-canine distance of both maxilla and mandible). Co-relation and regression analysis was done to find the association between the parameters. All parameters were found to be greater in males than females and each was found to be statistically significant. Out of total 312 samples, the best regressor for the determination of stature was head circumference and mandibular inter-canine width and that for gender was head circumference and right mandibular teeth. The accuracy of prediction was 83%. Regression equations and analysis generated from craniofacial and odontometric parameters can be a supplementary approach for the estimation of stature and gender when extremities are not available.

Keywords: craniofacial, gender, odontometric, stature

Procedia PDF Downloads 157

Authors: A. Čelan, M. Ćosić, D. Rušić, N. Kuzmanić

Abstract:

Conducting crystallization in an agitated vessel requires a proper selection of mixing parameters that would result in a production of crystals of specific properties. In dual impeller systems, which are characterized by a more complex hydrodynamics due to the possible fluid flow interactions, revealing a clear link between mixing parameters and crystallization kinetics is still an open issue. The aim of this work is to establish this connection by investigating how fluid flow patterns, generated by two impellers mounted on the same shaft, reflect on metastable zone width of borax decahydrate, one of the most important parameters of the crystallization process. Investigation was carried out in a 15-dm³ bench scale batch cooling crystallizer with an aspect ratio (H/T) equal to 1.3. For this reason, two radial straight blade turbines (4-SBT) were used for agitation. Experiments were conducted at different impeller spacings at the state of complete suspension. During the process of an unseeded batch cooling crystallization, solution temperature and supersaturation were continuously monitored what enabled a determination of the metastable zone width. Hydrodynamic conditions in the vessel achieved at different impeller spacings investigated were analyzed in detail. This was done firstly by measuring the mixing time required to attain the desired level of homogeneity. Secondly, fluid flow patterns generated in a described dual impeller system were both photographed and simulated by VisiMix Turbulent software. Also, a comparison of these two visualization methods was performed. Experimentally obtained results showed that metastable zone width is definitely affected by the hydrodynamics in the crystallizer. This means that this crystallization parameter can be controlled not only by adjusting the saturation temperature or cooling rate, as is usually done, but also by choosing a suitable impeller spacing that will result in a formation of crystals of wanted size distribution.

Keywords: dual impeller crystallizer, fluid flow pattern, metastable zone width, mixing time, radial impeller

Procedia PDF Downloads 167

Authors: Sheikh Samsuzzhan Alam

Abstract:

The present study investigates the selection of variogram model in analyzing spatial variations of environmental variables with the trend. Sometimes, the autofitted theoretical variogram does not really capture the true nature of the empirical semivariogram. So proper exploration and analysis are needed to select the best variogram model. For this study, an open source data collected from California Soil Resource Lab1 is used to explain the problems when fitting a theoretical variogram. Five most commonly used variogram models: Linear, Gaussian, Exponential, Matern, and Spherical were fitted to the experimental semivariogram. Ordinary kriging methods were considered to evaluate the accuracy of the selected variograms through cross-validation. This study is beneficial for selecting an appropriate theoretical variogram model for environmental variables.

Keywords: anisotropy, cross-validation, environmental variables, kriging, variogram models

Procedia PDF Downloads 303

Authors: A. I. Al-Bassam, A. M. El-Nggar

Abstract:

Polycrystalline Cu In I-x GaxSe2 thin films have been fabricated. Some physical properties such as lattice parameters, crystal structure and microstructure of Cu In I-x GaxSe2 were determined using X-ray diffractometry and scanning electron microscopy. X-ray diffraction analysis showed that the films with x ≥ 0.5 have a chalcopyrite structure and the films with x ≤ 0.5 have a zinc blende structure. The lattice parameters were found to vary linearly with composition over a wide range from x = 0 to x =1.0. The variation of lattice parameters with composition was found to obey Vegard's law. The variation of the c/a with composition was also linear. The quality of a wide range of Cu In I-xGaxSe2 thin film absorbers from CuInSe to CuGaSe was evaluated by Photoluminescence (PL) measurements.

Keywords: grain size, polycrystalline, solar cells, lattice parameters

Procedia PDF Downloads 479

Authors: Nicolas Lipchak, Franco Aiducic, Santiago Baieli

Abstract:

The present work is a part of the research project called ‘Testing of gas turbine KingTech with biodiesel’, carried out by the Department of Industrial Engineering of the National Technological University at Buenos Aires. The research group aims to experiment with biodiesel in a gas turbine Kingtech K-100 to verify the correct operation of it. In this sense, tests have been developed to obtain real data of parameters inherent to the work cycle, to be used later as parameters of comparison and performance analysis. In the first instance, the study consisted in testing the gas turbine with a mixture composition of 50% Biodiesel and 50% Diesel. The parameters arising from the measurements made were compared with the parameters of the gas turbine with a composition of 100% Diesel. In the second instance, the measured parameters were used to calculate the power generated and the thermal efficiency of the Kingtech K-100 turbine. The turbine was also inspected to verify the status of the internals due to the use of biofuels. The conclusions obtained allow empirically demonstrate that it is feasible to use biodiesel in this type of gas turbines, without the use of this fuel generates a loss of power or degradation of internals.

Keywords: biodiesel, efficiency, KingTech, turbine

Procedia PDF Downloads 202

Authors: Hammoudi Abderazek

Abstract:

The present paper introduces a modified adaptive mixed differential evolution (MAMDE) to select the main geometry parameters of specific cylindrical spur gear. The developed algorithm used the self-adaptive mechanism in order to update the values of mutation and crossover factors. The feasibility rules are used in the selection phase to improve the search exploration of MAMDE. Moreover, the elitism is performed to keep the best individual found in each generation. For the constraints handling the normalization method is used to treat each constraint design equally. The finite element analysis is used to confirm the optimization results for the maximum bending resistance. The simulation results reached in this paper indicate clearly that the proposed algorithm is very competitive in precision gear design optimization.

Keywords: evolutionary algorithm, spur gear, tooth profile, meta-heuristics

Procedia PDF Downloads 107

Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

Abstract:

The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

Procedia PDF Downloads 218

Authors: Sangeeta Yadav, Mantosh Biswas

Abstract:

In this paper, we proposed an improved color based K-mean algorithm for clustering of satellite Image (SAR). Our method comprises of two stages. The first step is an interactive selection process where users are required to input the number of colors (ncolor), number of clusters, and then they are prompted to select the points in each color cluster. In the second step these points are given as input to K-mean clustering algorithm that clusters the image based on color and Minimum Square Euclidean distance. The proposed method reduces the mixed pixel problem to a great extent.

Keywords: cluster, ncolor method, K-mean method, interactive selection process

Procedia PDF Downloads 263

Authors: Jutta Hämmerle-Uhl, Georg Penn, Gerhard Pötzelsberger, Andreas Uhl

Abstract:

Iris codes contain bits with different entropy. This work investigates different strategies to reduce the size of iris code templates with the aim of reducing storage requirements and computational demand in the matching process. Besides simple sub-sampling schemes, also a binary multi-resolution representation as used in the JBIG hierarchical coding mode is assessed. We find that iris code template size can be reduced significantly while maintaining recognition accuracy. Besides, we propose a two stage identification approach, using small-sized iris code templates in a pre-selection satge, and full resolution templates for final identification, which shows promising recognition behaviour.

Keywords: iris recognition, compact iris code, fast matching, best bits, pre-selection identification, two-stage identification

Procedia PDF Downloads 415

Authors: Yue Hu, Xilu Zhao, Takao Yamaguchi, Manabu Sasajima, Yoshio Koike, Akira Hara

Abstract:

This study optimized the design parameters of a cone loudspeaker as an example of high flexibility of the product design. We developed an acoustic analysis software program that considers the impact of damping caused by air viscosity. In sound reproduction, it is difficult to optimize each parameter of the loudspeaker design. To overcome the limitation of the design problem in practice, this study presents an acoustic analysis algorithm to optimize the design parameters of the loudspeaker. The material character of cone paper and the loudspeaker edge were the design parameters, and the vibration displacement of the cone paper was the objective function. The results of the analysis showed that the design had high accuracy as compared to the predicted value. These results suggested that although the parameter design is difficult, with experience and intuition, the design can be performed easily using the optimized design found with the acoustic analysis software.

Keywords: air viscosity, design parameters, loudspeaker, optimization

Procedia PDF Downloads 486

Authors: Robert Jedrys, Zdzislaw Kobos, Justyna Skrzynska, Zbigniew Wochynski

Abstract:

Professions connected to aviation require an assessment of the suitability of health, psychological and psychomotor skills and overall physical fitness of the organism, who applies. Assessment of the physical condition is conducted by the committees consisting of aero-medical specialists in clinical medicine and aviation. In addition, psychological predispositions should be evaluated by specialized psychologists familiar with the specifics of the tasks and requirements for the various positions in aviation. Both, physical abilities and general physical fitness of candidates for aviation shall be assessed during the selection exams, which also test the ability to deal with stress what is very important in aviation. Hence, the mentioned exams in physical education not only help to judge on the ranking in candidates in terms of their efficiency and performance, but also allows to evaluate the functioning under stress measured using psychological tests. Moreover, before-test stress is a predictors of successfulness in the next stages of education and practical training in the aviation. The aim of the study was to evaluate the influence of temperamental traits on strategies used for coping with stress during selection exams in physical education, deciding on admission to aviation school. The study involved 30 candidates for fighter pilot training in aviation school . To evaluate the temperament 'The Formal Characteristics of Behavior-Temperament Inventory' (FCB-TI) by B. Zawadzki and J.Strelau was used. To determine the pattern of coping with stress 'The Coping Inventory for Stressful Situations' (CISS) to N. S. Endler and J. D. A. Parker were engaged. Study of temperament and styles of coping with stress was conducted directly before the exam selection of physical education. The results were analyzed with 'Statistica 9' program. The studies showed that:-There is a negative correlation between such a temperament feature as 'perseverance' and preferred style of coping with stress concentrated on the task (r = -0.590; p < 0.004); -There is a positive correlation between such a feature of temperament as 'emotional reactivity,' and preference to deal with a stressful situation with ‘style centered on emotions’ (r = 0.520; p <0.011); -There is a negative correlation between such a feature of temperament as ‘strength’ and ‘style of coping with stress concentrated on emotions’ (r = -0.580; p < 0.004). Studies indicate that temperament traits determine the perception of stress and preferred coping styles used during the selection, as during the exams in physical education.

Keywords: aviation, physical education, stress, temperamental traits

Procedia PDF Downloads 230

Authors: Swati Bhomia, C. M. Kishtawal, Neeru Jaiswal

Abstract:

Traditionally, monsoon forecasts have encountered many difficulties that stem from numerous issues such as lack of adequate upper air observations, mesoscale nature of convection, proper resolution, radiative interactions, planetary boundary layer physics, mesoscale air-sea fluxes, representation of orography, etc. Uncertainties in any of these areas lead to large systematic errors. Global circulation models (GCMs), which are developed independently at different institutes, each of which carries somewhat different representation of the above processes, can be combined to reduce the collective local biases in space, time, and for different variables from different models. This is the basic concept behind the multi-model superensemble and comprises of a training and a forecast phase. The training phase learns from the recent past performances of models and is used to determine statistical weights from a least square minimization via a simple multiple regression. These weights are then used in the forecast phase. The superensemble forecasts carry the highest skill compared to simple ensemble mean, bias corrected ensemble mean and the best model out of the participating member models. This approach is a powerful post-processing method for the estimation of weather forecast parameters reducing the direct model output errors. Although it can be applied successfully to the continuous parameters like temperature, humidity, wind speed, mean sea level pressure etc., in this paper, this approach is applied to rainfall, a parameter quite difficult to handle with standard post-processing methods, due to its high temporal and spatial variability. The present study aims at the development of advanced superensemble schemes comprising of 1-5 day daily precipitation forecasts from five state-of-the-art global circulation models (GCMs), i.e., European Centre for Medium Range Weather Forecasts (Europe), National Center for Environmental Prediction (USA), China Meteorological Administration (China), Canadian Meteorological Centre (Canada) and U.K. Meteorological Office (U.K.) obtained from THORPEX Interactive Grand Global Ensemble (TIGGE), which is one of the most complete data set available. The novel approaches include the dynamical model selection approach in which the selection of the superior models from the participating member models at each grid and for each forecast step in the training period is carried out. Multi-model superensemble based on the training using similar conditions is also discussed in the present study, which is based on the assumption that training with the similar type of conditions may provide the better forecasts in spite of the sequential training which is being used in the conventional multi-model ensemble (MME) approaches. Further, a variety of methods that incorporate a 'neighborhood' around each grid point which is available in literature to allow for spatial error or uncertainty, have also been experimented with the above mentioned approaches. The comparison of these schemes with respect to the observations verifies that the newly developed approaches provide more unified and skillful prediction of the summer monsoon (viz. June to September) rainfall compared to the conventional multi-model approach and the member models.

Keywords: multi-model superensemble, dynamical model selection, similarity criteria, neighborhood technique, rainfall prediction

Procedia PDF Downloads 112

Authors: H. Nakamura

Abstract:

This study analyzes international strategic alliances in the information industry. The purpose of this study is to clarify the strategic intention of an international alliance. Secondly, it investigates the influence of differences in the target markets of partner companies on alliances. Using an international strategy theory approach to analyze the global strategies of global companies, the study compares a database business and an electronic publishing business. In particular, these cases emphasized factors attributable to "people" and "learning", reliability and communication between organizations and the evolution of the IT infrastructure. The theory evolved in this study validates the effectiveness of these strategies.

Keywords: database business, electronic library, international strategic alliances, partner selection

Procedia PDF Downloads 349

Authors: D. Kari Basavaraja, M. G. Skanda, C. Soumya, V. Ramesh

Abstract:

This paper discusses the effects of sodium hypophosphite concentration, pH, and temperature on deposition rate. This paper also discusses the evaluation of coating strength, surface, and subsurface by varying the bath parameters, percentage of phosphate, plating temperature, and pH of the plating solution. Taguchi technique has been used for the analysis. In the experiment, nickel chloride which is a source of nickel when mixed with sodium hypophosphite has been used as the reducing agent and the source of phosphate and sodium hydroxide has been used to vary the pH of the coating bath. The coated samples are tested for impact energy by conducting impact test. Finally, the effects of coating bath parameters on the impact energy absorbed have been plotted, and analysis has been carried out. Further, percentage contribution of coating bath parameters using Design of Experiments approach (DOE) has been analysed. Finally, it can be concluded that the bath parameters of the Ni-P coating will certainly influence on the strength of the specimen.

Keywords: bath parameters, coatings, design of experiment, fracture toughness, impact strength

Procedia PDF Downloads 329

Authors: Nima E. Gorji

Abstract:

The performance and characteristics of a hybrid heterojunction single-walled carbon nanotube and GaAs solar cell is modelled and numerically simulated using AMPS-1D device simulation tool. The device physics and performance parameters with different junction parameters are analysed. The results suggest that the open-circuit voltage changes very slightly by changing the work function, acceptor and donor density while the other electrical parameters reach to an optimum value. Increasing the concentration of a discrete defect density in the absorber layer decreases the electrical parameters. The current-voltage characteristics, quantum efficiency, band gap and thickness variation of the photovoltaic response will be quantitatively considered.

Keywords: carbon nanotube, GaAs, hybrid solar cell, AMPS-1D modelling

Procedia PDF Downloads 303

Authors: Kaleb Shiferaw, Berhanu Geberemedhin, Dereje Legesse

Abstract:

Access to credit is often viewed as a key to transform semi-subsistence smallholders into market oriented producers. However, only a few studies have examined factors that affect farmers’ decision to allocate credit on farm activities in general and livestock production in particular. A trivariate probit model with double selection is employed to identify factors that affect farmers’ decision to allocate credit on livestock production using data collected from smallholder farmers in Ethiopia. After controlling for two sample selection bias – taking credit for the production season and decision to allocate credit on farm activities – land ownership and access to a livestock centered extension service are found to have a significant (p<0.001) effect on farmers decision to use credit for livestock production. The result showed farmers with large land holding, and access to a livestock centered extension services are more likely to utilize credit for livestock production. However since the effect of land ownership squared is negative the effect of land ownership for those who own a large plot of land lessens. The study highlights the fact that improving access to credit does not automatically translate into more productive households. Improving farmers’ access to credit should be followed by a focused extension services.

Keywords: livestock production, credit access, credit allocation, household decision, double sample selection

Procedia PDF Downloads 296

Authors: P. Shrivastava, A. Shukla, K. Verma, S. Rungta

Abstract:

Parkinson's disease is a chronic neurological disorder that directly affects human gait. It leads to slowness of movement, causes muscle rigidity and tremors. Gait serve as a primary outcome measure for studies aiming at early recognition of disease. Using gait techniques, this paper implements efficient binary bat algorithm for an early detection of Parkinson's disease by selecting optimal features required for classification of affected patients from others. The data of 166 people, both fit and affected is collected and optimal feature selection is done using PSO and Bat algorithm. The reduced dataset is then classified using neural network. The experiments indicate that binary bat algorithm outperforms traditional PSO and genetic algorithm and gives a fairly good recognition rate even with the reduced dataset.

Keywords: parkinson, gait, feature selection, bat algorithm

Procedia PDF Downloads 515

Authors: Louis Denis Kevin Catherine, Raja Aziz Raja Ma’arof, Azrina Arshad, Sangeeth Suresh

Abstract:

Machining parameters are very important in determining the surface quality of any material. In the past decade, some new engineering materials were developed for the manufacturing industry which created a need to conduct an investigation on the impact of the said parameters on their surface roughness. The polyurethane (PU) block is widely used in the automotive industry to manufacture parts such as checking fixtures that are used to verify the dimensional accuracy of automotive parts. In this paper, the design of experiment (DOE) was used to investigate the effect of the milling parameters on the PU block. Furthermore, an analysis of the machined surface chemical composition was done using scanning electron microscope (SEM). It was found that the surface roughness of the PU block is severely affected when PU undergoes a flood machining process instead of a dry condition. In addition, the step over and the silicon content were found to be the most significant parameters that influence the surface quality of the PU block.

Keywords: polyurethane (PU), design of experiment (DOE), scanning electron microscope (SEM), surface roughness

Procedia PDF Downloads 492

Authors: Ayat Adnan Atwah, Muhammad A. Khan

Abstract:

Self-cleaning surfaces are getting significant attention in industrial fields. Especially for textile fabrics, it is observed that self-cleaning textile fabric surfaces are created by manipulating the surface features with the help of coatings and nanoparticles, which are considered costly and far more complicated. However, controlling the fabrication parameters of textile fabrics at the microscopic level by exploring the potential for self-cleaning has not been addressed. This study aimed to establish the context of self-cleaning textile fabrics by controlling the fabrication parameters of the textile fabric at the microscopic level. Therefore, 3D-printed textile fabrics were fabricated using the low-cost fused filament fabrication (FFF) technique. The printing parameters, such as orientation angle (O), layer height (LH), and extruder width (EW), were used to control the microscopic features of the printed fabrics. The combination of three printing parameters was created to provide the best self-cleaning textile fabric surface: (LH) (0.15, 0.13, 0.10 mm) and (EW) (0.5, 0.4, 0.3 mm) along with two different (O) of (45º and 90º). Three different thermoplastic flexible filament materials were used: (TPU 98A), (TPE felaflex), and (TPC flex45). The printing parameters were optimised to get the optimum self-cleaning ability of the printed specimens. Furthermore, the impact of these characteristics on mechanical strength at the fabric-woven structure level was investigated. The study revealed that the printing parameters significantly affect the self-cleaning properties after adjusting the selected combination of layer height, extruder width, and printing orientation. A linear regression model was effectively developed to demonstrate the association between 3D printing parameters (layer height, extruder width, and orientation). According to the experimental results, (TPE felaflex) has a better self-cleaning ability than the other two materials.

Keywords: 3D printing, self-cleaning fabric, microscopic features, printing parameters, fabrication

Procedia PDF Downloads 54

Authors: S. Aghanajafizadeh, M. Poursina

Abstract:

We studied the selection of winter habitat by Persian Gazelle (Gazella subguttrosa) in Bydoyeh protected area. Habitat variables such as plant species number, vegetation percent, distance to the nearest water sources and plant patch of present sites were compared with randomly selected non- used sites. The results showed that the most important factors influencing habitat selection were number and vegetation percent of Artemisia sieberi. Vegetation percent of plants. vegetation percent and number of Artemisia sieberi were significantly higher compared with the control area.

Keywords: Persian gazelle, habitat use, Bydoyeh protected area, Kerman, Iran

Procedia PDF Downloads 357

Authors: Arnab Adhikari, Adrija Majumdar, Gaurav Gupta, Arnab Bisi

Abstract:

Team formation plays an instrumental role in the sports like cricket. Existing literature reveals that most of the works on player selection focus only on the players’ efficiency and ignore the consistency. It motivates us to design an improved player selection method based on both player’s efficiency and consistency. To measure the players’ efficiency measurement, we employ a modified data envelopment analysis (DEA) technique namely ‘super-efficient DEA model’. We design a modified consistency index based on semi variance approach. Here, we introduce a new parameter called ‘fitness index’ for consistency computation to assess a player’s fitness level. Finally, we devise a single performance score using both efficiency score and consistency score with the help of a linear programming model. To test the robustness of our method, we perform a rigorous numerical analysis to determine the all-time best One Day International (ODI) Cricket XI. Next, we conduct extensive comparative studies regarding efficiency scores, consistency scores, selected team between the existing methods and the proposed method and explain the rationale behind the improvement.

Keywords: decision support systems, sports, super-efficient data envelopment analysis, semi variance approach

Procedia PDF Downloads 375