Search results for: progressive sports operational model

Authors: Gong Zhilin, Jing Yang, Jian Yin

Abstract:

The purpose of this paper is to develop a novel system for credit card fraud detection based on sequential modeling of data using hybrid deep learning models. The projected model encapsulates five major phases are pre-processing, imbalance-data handling, feature extraction, optimal feature selection, and fraud detection with an ensemble classifier. The collected raw data (input) is pre-processed to enhance the quality of the data through alleviation of the missing data, noisy data as well as null values. The pre-processed data are class imbalanced in nature, and therefore they are handled effectively with the K-means clustering-based SMOTE model. From the balanced class data, the most relevant features like improved Principal Component Analysis (PCA), statistical features (mean, median, standard deviation) and higher-order statistical features (skewness and kurtosis). Among the extracted features, the most optimal features are selected with the Self-improved Arithmetic Optimization Algorithm (SI-AOA). This SI-AOA model is the conceptual improvement of the standard Arithmetic Optimization Algorithm. The deep learning models like Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and optimized Quantum Deep Neural Network (QDNN). The LSTM and CNN are trained with the extracted optimal features. The outcomes from LSTM and CNN will enter as input to optimized QDNN that provides the final detection outcome. Since the QDNN is the ultimate detector, its weight function is fine-tuned with the Self-improved Arithmetic Optimization Algorithm (SI-AOA).

Keywords: credit card, data mining, fraud detection, money transactions

Procedia PDF Downloads 131

Authors: Reza Salehi, Peter L. Dold, Yves Comeau

Abstract:

The aim of the present study was to investigate the effect of a total of 6 operating parameters including pH (X1), temperature (X2), stirring speed (X3), chemical oxygen demand (COD) (X4), volatile suspended solids (VSS) (X5) and time (X6) on anaerobic orthophosphate release from enhanced biological phosphorus removal (EBPR) sludge. An 8-run Plackett Burman design was applied and the statistical analysis of the experimental data was performed using Minitab16.2.4 software package. The Analysis of variance (ANOVA) results revealed that temperature, COD, VSS and time had a significant effect with p-values of less than 0.05 whereas pH and stirring speed were identified as non-significant parameters, but influenced orthophosphate release from the EBPR sludge. The mathematic expression obtained by the first-order multiple linear regression model between orthophosphate release from the EBPR sludge (Y) and the operating parameters (X1-X6) was Y=18.59+1.16X1-3.11X2-0.81X3+3.79X4+9.89X5+4.01X6. The model p-value and coefficient of determination (R2) value were 0.026 and of 99.87%, respectively, which indicates the model is significant and the predicted values of orthophosphate release from the EBPR sludge have been excellently correlated with the observed values.

Keywords: anaerobic, operating parameters, orthophosphate release, Plackett-Burman design

Procedia PDF Downloads 279

Authors: A. Bahmanpour, I. Eames, C. Klettner, A. Dimakopoulos

Abstract:

We develop a new set of diagnostic tools to analyze inundation into a model district using three-dimensional CFD simulations, with a view to generating a database against which to test simpler models. A three-dimensional model of Oregon city with different-sized groups of building next to the coastline is used to run calculations of the movement of a long period wave on the shore. The initial and boundary conditions of the off-shore water are set using a nonlinear inverse method based on Eulerian spatial information matching experimental Eulerian time series measurements of water height. The water movement is followed in time, and this enables the pressure distribution on every surface of each building to be followed in a temporal manner. The three-dimensional numerical data set is validated against published experimental work. In the first instance, we use the dataset as a basis to understand the success of reduced models - including 2D shallow water model and reduced 1D models - to predict water heights, flow velocity and forces. This is because models based on the shallow water equations are known to underestimate drag forces after the initial surge of water. The second component is to identify critical flow features, such as hydraulic jumps and choked states, which are flow regions where dissipation occurs and drag forces are large. Finally, we describe how future tsunami inundation models should be modified to account for the complex effects of buildings through drag and blocking.Financial support from UCL and HR Wallingford is greatly appreciated. The authors would like to thank Professor Daniel Cox and Dr. Hyoungsu Park for providing the data on the Seaside Oregon experiment.

Keywords: computational fluid dynamics, extreme events, loading, tsunami

Procedia PDF Downloads 115

Authors: Yan-Ting Lin, Wei-Nian Su

Abstract:

The purpose of this paper is to demonstrate the design of 5kW vertical axis wind turbine (VAWT) using DOE method. The NACA0015 airfoil was implemented for the design and 3D simulation. The critical design parameters are chord length, tip speed ratio (TSR), aspect ratio (AR) and pitch angle in this investigation. The RNG k-ε turbulent model and the sliding mesh method are adopted in the CFD simulation. The results show that the model with zero pitch, 0.3 m in chord length, TSR of 3, and AR of 10 demonstrated the optimum aerodynamic power under the uniform 10m/s inlet velocity. The aerodynamic power is 3.61kW and 3.89kW under TSR of 3 and 4 respectively. The aerodynamic power decreased dramatically while TSR increased to 5.

Keywords: vertical axis wind turbine, CFD, DOE, VAWT

Procedia PDF Downloads 440

Authors: Ime R. Udotong, Justina I. R. Udotong, Ofonime U. M. John

Abstract:

Mobil Producing Nigeria Unlimited (MPNU), a subsidiary of ExxonMobil and the highest crude oil & condensate producer in Nigeria has its operational base and an oil terminal, the Qua Iboe terminal (QIT) located at Ibeno, Nigeria. Other oil companies like Network Exploration and Production Nigeria Ltd, Frontier Oil Ltd; Shell Petroleum Development Company Ltd; Elf Petroleum Nigeria Ltd and Nigerian Agip Energy, a subsidiary of the Italian ENI E&P operate onshore, on the continental shelf and in deep offshore of the Atlantic Ocean, respectively with the coastal waters of Ibeno, Nigeria as the nearest shoreline. This study was designed to delineate the oil-polluted sites in Ibeno, Nigeria using microbiological and physico-chemical characterization of soils, sediments and ground and surface water samples from the study area. Results obtained revealed that there have been significant recent hydrocarbon inputs into this environment as observed from the high counts of hydrocarbonoclastic microorganisms in excess of 1% at all the stations sampled. Moreover, high concentrations of THC, BTEX and heavy metals contents in all the samples analyzed corroborate the high recent crude oil input into the study area. The results also showed that the pollution of the different environmental media sampled were of varying degrees, following the trend: Ground water > surface water > sediments > soils.

Keywords: microbiological characterization, oil-polluted sites, physico-chemical analyses, total hydrocarbon content

Procedia PDF Downloads 416

Authors: Byeongcheol Kang, Junyi Kim, Hyungsik Jung, Hyungjun Yang, Jaewoo An, Jonggeun Choe

Abstract:

It is important to figure out reservoir properties for better production management. Due to the limited information, there are geological uncertainties on very heterogeneous or channel reservoir. One of the solutions is to generate multiple equi-probable realizations using geostatistical methods. However, some models have wrong properties, which need to be excluded for simulation efficiency and reliability. We propose a novel method of model selection scheme, based on distance-based clustering for reliable application of production optimization algorithm. Distance is defined as a degree of dissimilarity between the data. We calculate Hausdorff distance to classify the models based on their similarity. Hausdorff distance is useful for shape matching of the reservoir models. We use multi-dimensional scaling (MDS) to describe the models on two dimensional space and group them by K-means clustering. Rather than simulating all models, we choose one representative model from each cluster and find out the best model, which has the similar production rates with the true values. From the process, we can select good reservoir models near the best model with high confidence. We make 100 channel reservoir models using single normal equation simulation (SNESIM). Since oil and gas prefer to flow through the sand facies, it is critical to characterize pattern and connectivity of the channels in the reservoir. After calculating Hausdorff distances and projecting the models by MDS, we can see that the models assemble depending on their channel patterns. These channel distributions affect operation controls of each production well so that the model selection scheme improves management optimization process. We use one of useful global search algorithms, particle swarm optimization (PSO), for our production optimization. PSO is good to find global optimum of objective function, but it takes too much time due to its usage of many particles and iterations. In addition, if we use multiple reservoir models, the simulation time for PSO will be soared. By using the proposed method, we can select good and reliable models that already matches production data. Considering geological uncertainty of the reservoir, we can get well-optimized production controls for maximum net present value. The proposed method shows one of novel solutions to select good cases among the various probabilities. The model selection schemes can be applied to not only production optimization but also history matching or other ensemble-based methods for efficient simulations.

Keywords: distance-based clustering, geological uncertainty, particle swarm optimization (PSO), production optimization

Procedia PDF Downloads 144

Authors: Jirapat Suriyachaisawat, Ekkit Surakarn

Abstract:

Introduction: To improve early detection and mortality rate of In- Hospital Cardiac arrest, Emergency Response Team (ERT) system was planned and implemented since June 2009 to detect pre-arrest conditions and for any concerns. The ERT consisted of on duty physicians and nurses from emergency department. ERT calling criteria consisted of acute change of HR < 40 or > 130 beats per minute, systolic blood pressure < 90mmHg, respiratory rate <8 or > 28 breaths per minute, O2 saturation < 90%, acute change in conscious state, acute chest pain or worried about the patients. From the data on ERT system implementation in our hospital in early phase (during June 2009-2011), there was no statistic significance in difference in In-Hospital cardiac arrest incidence and overall hospital mortality rate. Since the introduction of the ERT service in our hospital, we have conducted continuous educational campaign to improve awareness in an attempt to increase use of the service. Methods: To investigate outcome of ERT system in In-Hospital cardiac arrest and overall hospital mortality rate. We conducted a prospective, controlled before-and after examination of the long term effect of a ERT system on the incidence of cardiac arrest. We performed Chi -square analysis to find statistic significance. Results: Of a total 623 ERT cases from June 2009 until December 2012, there were 72 calls in 2009, 196 calls in 2010 ,139 calls in 2011 and 245 calls in 2012.The number of ERT calls per 1000 admissions in year 2009-10 was 7.69, 5.61 in 2011 and 9.38 in 2013. The number of Code blue calls per 1000 admissions decreased significantly from 2.28 to 0.99 per 1000 admissions (P value < 0.001). The incidence of cardiac arrest decreased progressively from 1.19 to 0.34 per 1000 admissions and significant in difference in year 2012 (P value < 0.001). The overall hospital mortality rate decreased by 8 % from 15.43 to 14.43 per 1000 admissions (P value 0.095). Conclusions: ERT system implementation was associated with progressive reduction in cardiac arrests over three year period, especially statistic significant in difference in 4th year after implementation. We also found an inverse association between number of ERT use and the risk of occurrence of cardiac arrests, But we have not found difference in overall hospital mortality rate.

Keywords: emergency response team, ERT, cardiac arrest, emergency medicine

Procedia PDF Downloads 310

Authors: A. Abdikian

Abstract:

Using the linearized quantum hydrodynamic model (QHD) and by considering the role of quantum parameter (Bohm’s potential) and electron exchange-correlation potential in conjunction with Maxwell’s equations, electromagnetic wave propagation in a single-walled carbon nanotubes was studied. The electronic excitations are described. By solving the mentioned equations with appropriate boundary conditions and by assuming the low-frequency electromagnetic waves, two general expressions of dispersion relations are derived for the transverse magnetic (TM) and transverse electric (TE) modes, respectively. The dispersion relations are analyzed numerically and it was found that the dependency of dispersion curves with the exchange-correlation effects (which have been ignored in previous works) in the low frequency would be limited. Moreover, it has been realized that asymptotic behaviors of the TE and TM modes are similar in single wall carbon nanotubes (SWCNTs). The results show that by adding the function of electron exchange-correlation potential lead to the phenomena and make to extend the validity range of QHD model. The results can be important in the study of collective phenomena in nanostructures.

Keywords: transverse magnetic, transverse electric, quantum hydrodynamic model, electron exchange-correlation potential, single-wall carbon nanotubes

Procedia PDF Downloads 451

Authors: Akram Khaleghei, Ghosheh Balagh, Viliam Makis

Abstract:

In this paper, we investigate the residual life prediction problem for a partially observable system subject to two failure modes, namely a catastrophic failure and a failure due to the system degradation. The system is subject to condition monitoring and the degradation process is described by a hidden Markov model with unknown parameters. The parameter estimation procedure based on an EM algorithm is developed and the formulas for the conditional reliability function and the mean residual life are derived, illustrated by a numerical example.

Keywords: partially observable system, hidden Markov model, competing risks, residual life prediction

Procedia PDF Downloads 415

Authors: Carlos Gonzales, Zaida Quiroz, Marcos Prates

Abstract:

Several spatial variables collected at the same location that share a common spatial distribution can be modeled simultaneously through a multivariate geostatistical model that takes into account the correlation between these variables and the spatial autocorrelation. The main goal of this model is to perform spatial prediction of these variables in the region of study. Here we focus on a geostatistical multivariate formulation that relies on sharing common spatial random effect terms. In particular, the first response variable can be modeled by a mean that incorporates a shared random spatial effect, while the other response variables depend on this shared spatial term, in addition to specific random spatial effects. Each spatial random effect is defined through a Gaussian process with a valid covariance function, but in order to improve the computational efficiency when the data are large, each Gaussian process is approximated to a Gaussian random Markov field (GRMF), specifically to the block nearest neighbor Gaussian process (Block-NNGP). This approach involves dividing the spatial domain into several dependent blocks under certain constraints, where the cross blocks allow capturing the spatial dependence on a large scale, while each individual block captures the spatial dependence on a smaller scale. The multivariate geostatistical model belongs to the class of Latent Gaussian Models; thus, to achieve fast Bayesian inference, it is used the integrated nested Laplace approximation (INLA) method. The good performance of the proposed model is shown through simulations and applications for massive data.

Keywords: Block-NNGP, geostatistics, gaussian process, GRMF, INLA, multivariate models.

Procedia PDF Downloads 97

Authors: Darrol Stanley, Levan Efremidze, Jannie Rossouw

Abstract:

We investigate the predictability of the USD/ZAR (South African Rand) exchange rate with sample entropy analytics for the period of 2004-2015. We calculate sample entropy based on the daily data of the exchange rate and conduct empirical implementation of several market timing rules based on these entropy signals. The dynamic investment portfolio based on entropy signals produces better risk adjusted performance than a buy and hold strategy. The returns are estimated on the portfolio values in U.S. dollars. These results are preliminary and do not yet account for reasonable transactions costs, although these are very small in currency markets.

Keywords: currency trading, entropy, market timing, risk factor model

Procedia PDF Downloads 271

Authors: Emre Ozaslan, Bulent Acar, Mehmet Ali Guler

Abstract:

Unidirectional composites are very popular structural materials used in aerospace, marine, energy and automotive industries thanks to their superior material properties. However, the mechanical behavior of composite materials is more complicated than isotropic materials because of their anisotropic nature. Also, a stress concentration availability on the structure, like a hole, makes the problem further complicated. Therefore, enormous number of tests require to understand the mechanical behavior and strength of composites which contain stress concentration. Accurate finite element analysis and analytical models enable to understand mechanical behavior and predict the strength of composites without enormous number of tests which cost serious time and money. In this study, unidirectional Carbon/Epoxy composite specimens with central circular hole were investigated in terms of stress concentration factor and strength prediction. The composite specimens which had different specimen wide (W) to hole diameter (D) ratio were tested to investigate the effect of hole size on the stress concentration and strength. Also, specimens which had same specimen wide to hole diameter ratio, but varied sizes were tested to investigate the size effect. Finite element analysis was performed to determine stress concentration factor for all specimen configurations. For quasi-isotropic laminate, it was found that the stress concentration factor increased approximately %15 with decreasing of W/D ratio from 6 to 3. Point stress criteria (PSC), inherent flaw method and progressive failure analysis were compared in terms of predicting the strength of specimens. All methods could predict the strength of specimens with maximum %8 error. PSC was better than other methods for high values of W/D ratio, however, inherent flaw method was successful for low values of W/D. Also, it is seen that increasing by 4 times of the W/D ratio rises the failure strength of composite specimen as %62.4. For constant W/D ratio specimens, all the strength prediction methods were more successful for smaller size specimens than larger ones. Increasing the specimen width and hole diameter together by 2 times reduces the specimen failure strength as %13.2.

Keywords: failure, strength, stress concentration, unidirectional composites

Procedia PDF Downloads 156

Authors: Sonia Perez-Gamboa, Qingquan Sun, Yan Zhang

Abstract:

Non-intrusive sensor-based human activity recognition (HAR) is utilized in a spectrum of applications, including fitness tracking devices, gaming, health care monitoring, and smartphone applications. Deep learning models such as convolutional neural networks (CNNs) and long short term memory (LSTM) recurrent neural networks (RNNs) provide a way to achieve HAR accurately and effectively. In this paper, we design a multi-layer hybrid architecture with CNN and LSTM and explore a variety of multi-layer combinations. Based on the exploration, we present a lightweight, hybrid, and multi-layer model, which can improve the recognition performance by integrating local features and scale-invariant with dependencies of activities. The experimental results demonstrate the efficacy of the proposed model, which can achieve a 94.7% activity recognition rate on a benchmark human activity dataset. This model outperforms traditional machine learning and other deep learning methods. Additionally, our implementation achieves a balance between recognition rate and training time consumption.

Keywords: deep learning, LSTM, CNN, human activity recognition, inertial sensor

Procedia PDF Downloads 150

Authors: Cheng Zhang, James Marco, Walid Allafi, Truong Q. Dinh, W. D. Widanage

Abstract:

Equivalent circuit models (ECMs) are widely used in battery management systems in electric vehicles and other battery energy storage systems. The battery dynamics and the model parameters vary under different working conditions, such as different temperature and state of charge (SOC) levels, and therefore online parameter identification can improve the modelling accuracy. This paper presents a way of online ECM parameter identification using a continuous time (CT) estimation method. The CT estimation method has several advantages over discrete time (DT) estimation methods for ECM parameter identification due to the widely separated battery dynamic modes and fast sampling. The presented method can be used for online SOC estimation. Test data are collected using a lithium ion cell, and the experimental results show that the presented CT method achieves better modelling accuracy compared with the conventional DT recursive least square method. The effectiveness of the presented method for online SOC estimation is also verified on test data.

Keywords: electric circuit model, continuous time domain estimation, linear integral filter method, parameter and SOC estimation, recursive least square

Procedia PDF Downloads 383

Authors: J. Satya Eswari, Ch. Venkateswarlu

Abstract:

The formulation of a commercial pharmaceutical product involves several composition factors and response characteristics. When the formulation requires to satisfy multiple response characteristics which are conflicting, an optimal solution requires the need for an efficient multiobjective optimization technique. In this work, a regression is combined with a non-dominated sorting differential evolution (NSDE) involving Naïve & Slow and ε constraint techniques to derive different multiobjective optimization strategies, which are then evaluated by means of a trapidil pharmaceutical formulation. The analysis of the results show the effectiveness of the strategy that combines the regression model and NSDE with the integration of both Naïve & Slow and ε constraint techniques for Pareto optimization of trapidil formulation. With this strategy, the optimal formulation at pH=6.8 is obtained with the decision variables of micro crystalline cellulose, hydroxypropyl methylcellulose and compression pressure. The corresponding response characteristics of rate constant and release order are also noted down. The comparison of these results with the experimental data and with those of other multiple regression model based multiobjective evolutionary optimization strategies signify the better performance for optimal trapidil formulation.

Keywords: pharmaceutical formulation, multiple regression model, response surface method, radial basis function network, differential evolution, multiobjective optimization

Procedia PDF Downloads 409

Authors: Bishwa Nath Oli

Abstract:

Nepal is highly impacted by climate change and adaptation has been a major focus. This paper investigates the gaps and coherence in national policies across water, forestry, local development and agriculture sectors, identifies their links to climate change adaptation and national development plans and analyzes the effectiveness of climate change policy on adaptation. The study was based on a content analysis of relevant policy documents on the level of attention given to adaptation and key informant interviews. Findings show that sectoral policies have differing degrees of cross thematic coherence, often with mismatched priorities and differing the paths towards achieving climate change goal. They are somewhat coherent in addressing immediate disaster management issues rather than in climate adaptation. In some cases, they are too broad and complicated and the implementation suffers from barriers and limits due to lack of capacity, investment, research and knowledge needed for evidence-based policy process. They do not adequately provide operational guidance in supporting communities in adapting to climate change. The study recommends to a) embrace longer-term cross-sectoral planning within government structures to foster greater policy coherence and integrated adaptation planning, b) increase awareness and flow of information on the potential role of communities in climate change, c) review the existing development sectors from the climate change perspectives, and d) formulate a comprehensive climate change legislation based on the need to implement the new Constitution.

Keywords: agriculture, climate change adaptation, forestry, policies

Procedia PDF Downloads 223

Authors: Yadgar Tayfur, Antony Darby, Tim Ibell, Mark Evernden, John Orr

Abstract:

Fabric form-work is a technique to cast concrete structures with a great advantage of saving concrete material of up to 40%. This technique is particularly associated with the optimized concrete structures that usually have smaller cross-section dimensions than equivalent prismatic members. However, this can make the structural system produced from these members prone to smaller serviceability safety margins. Therefore, it is very important to understand the serviceability issue of non-prismatic concrete structures. In this paper, an analytical computer-based model to optimize concrete beams and to predict load-deflection behaviour of both prismatic and non-prismatic concrete beams is presented. The model was developed based on the method of sectional analysis and integration of curvatures. Results from the analytical model were compared to load-deflection behaviour of a number of beams with different geometric and material properties from other researchers. The results of the comparison show that the analytical program can accurately predict the load-deflection response of concrete beams with medium reinforcement ratios. However, it over-estimates deflection values for lightly reinforced specimens. Finally, the analytical program acceptably predicted load-deflection behaviour of on-prismatic concrete beams.

Keywords: fabric-formed concrete, continuous beams, optimisation, serviceability

Procedia PDF Downloads 372

Authors: Arun Prabhakar

Abstract:

Threat modeling is an important activity carried out in the initial stages of the development lifecycle that helps in building proactive security measures in the product. Though there are many techniques and tools available today, one of the common challenges with the traditional methods is the lack of a systematic approach in identifying security threats. The proposed solution describes an organized model by defining ontologies that help in building patterns to enumerate threats. The concepts of graph theory are applied to build the pattern for discovering threats for any given scenario. This graph-based solution also brings in other benefits, making it a customizable and scalable model.

Keywords: directed acyclic graph, ontology, patterns, threat identification, threat modeling

Procedia PDF Downloads 139

Authors: Reza Moslemi, Sebastien Perrier

Abstract:

Water infrastructure deterioration can result in increased operational costs owing to increased repair needs and non-revenue water and consequently cause a reduced level of service and customer service satisfaction. Various water main condition assessment technologies have been introduced to the market in order to evaluate the level of pipe deterioration and to develop appropriate asset management and pipe renewal plans. One of the challenges for any condition assessment and inspection program is to determine the percentage of the water network and the combination of pipe segments to be inspected in order to obtain a meaningful representation of the status of the entire water network with a desirable level of accuracy. Traditionally, condition assessment has been conducted by selecting pipes based on age or location. However, this may not necessarily offer the best approach, and it is believed that by using a smart sampling methodology, a better and more reliable estimate of the condition of a water network can be achieved. This research investigates three different sampling methodologies, including random, stratified, and systematic. It is demonstrated that selecting pipes based on the proposed clustering and sampling scheme can considerably improve the ability of the inspected subset to represent the condition of a wider network. With a smart sampling methodology, a smaller data sample can provide the same insight as a larger sample. This methodology offers increased efficiency and cost savings for condition assessment processes and projects.

Keywords: condition assessment, pipe degradation, sampling, water main

Procedia PDF Downloads 150

Authors: Mohammad Zamani, Ramin Mansouri

Abstract:

Spillways are one of the most important hydraulic structures of dams that provide the stability of the dam and downstream areas at the time of flood. A circular vertical spillway with various inlet forms is very effective when there is not enough space for the other spillway. Hydraulic flow in a vertical circular spillway is divided into three groups: free, orifice, and under pressure (submerged). In this research, the hydraulic flow characteristics of a Circular Vertical Spillway are investigated with the CFD model. Two-dimensional unsteady RANS equations were solved numerically using Finite Volume Method. The PISO scheme was applied for the velocity-pressure coupling. The mostly used two-equation turbulence models, k-ε and k-ω, were chosen to model Reynolds shear stress term. The power law scheme was used for the discretization of momentum, k, ε, and ω equations. The VOF method (geometrically reconstruction algorithm) was adopted for interface simulation. In this study, three types of computational grids (coarse, intermediate, and fine) were used to discriminate the simulation environment. In order to simulate the flow, the k-ε (Standard, RNG, Realizable) and k-ω (standard and SST) models were used. Also, in order to find the best wall function, two types, standard wall, and non-equilibrium wall function, were investigated. The laminar model did not produce satisfactory flow depth and velocity along the Morning-Glory spillway. The results of the most commonly used two-equation turbulence models (k-ε and k-ω) were identical. Furthermore, the standard wall function produced better results compared to the non-equilibrium wall function. Thus, for other simulations, the standard k-ε with the standard wall function was preferred. The comparison criterion in this study is also the trajectory profile of jet water. The results show that the fine computational grid, the input speed condition for the flow input boundary, and the output pressure for the boundaries that are in contact with the air provide the best possible results. Also, the standard wall function is chosen for the effect of the wall function, and the turbulent model k-ε (Standard) has the most consistent results with experimental results. When the jet gets closer to the end of the basin, the computational results increase with the numerical results of their differences. The mesh with 10602 nodes, turbulent model k-ε standard and the standard wall function, provide the best results for modeling the flow in a vertical circular Spillway. There was a good agreement between numerical and experimental results in the upper and lower nappe profiles. In the study of water level over crest and discharge, in low water levels, the results of numerical modeling are good agreement with the experimental, but with the increasing water level, the difference between the numerical and experimental discharge is more. In the study of the flow coefficient, by decreasing in P/R ratio, the difference between the numerical and experimental result increases.

Keywords: circular vertical, spillway, numerical model, boundary conditions

Procedia PDF Downloads 86

Authors: Rianne Voet

Abstract:

This paper uses a literature review to search for keys of success for entrepreneurial regional media collaborations in the Netherlands and elsewhere. It specifies keys on general aspects: a digital-first strategy, innovation, a particular journalistic mission and a new role for the public. It outlines keys in practicalities: competencies, revenue model, legal structure, communication structure and organization structure. The paper elaborates on a new public function and a new concept of citizenship which, according to several authors in the literature, are required in order to be successful. Finally, it offers a model of keys for success in regional entrepreneurial media collaboration.

Keywords: media collaboration, factors of success, keys of success, regional media cooperation

Procedia PDF Downloads 269

Authors: Aitana Alonso-Nogueira, Helia Estévez-Fernández, Isaías García

Abstract:

This paper presents an approach to reduce some of its current flaws in the requirements phase inside the software development process. It takes the software requirements of an application, makes a conceptual modeling about it and formalizes it within JSON documents. This formal model is lodged in a NoSQL database which is document-oriented, that is, MongoDB, because of its advantages in flexibility and efficiency. In addition, this paper underlines the contributions of the detailed approach and shows some applications and benefits for the future work in the field of automatic code generation using model-driven engineering tools.

Keywords: conceptual modelling, JSON, NoSQL databases, requirements engineering, software development

Procedia PDF Downloads 378

Authors: Seyedtaghi Mirmohammadi, Jamshid Yazdani, Syavash Etemadi Nejad

Abstract:

One of the main indoor air parameters in classrooms is dust pollution and it depends on the particle size and exposure duration. However, there is a lake of data about the exposure level to PM2.5 concentrations in rural area classrooms. The objective of the current study was exposure assessment for PM2.5 for students in the classrooms. One year monitoring was carried out for fifteen schools by time-series sampling to evaluate the indoor air PM2.5 in the rural district of Sari city, Iran. A hygrometer and thermometer were used to measure some psychrometric parameters (temperature, relative humidity, and wind speed) and Real-Time Dust Monitor, (MicroDust Pro, Casella, UK) was used to monitor particulate matters (PM2.5) concentration. The results show the mean indoor PM2.5 concentration in the studied classrooms was 135µg/m3. The regression model indicated that a positive correlation between indoor PM2.5 concentration and relative humidity, also with distance from city center and classroom size. Meanwhile, the regression model revealed that the indoor PM2.5 concentration, the relative humidity, and dry bulb temperature was significant at 0.05, 0.035, and 0.05 levels, respectively. A statistical predictive model was obtained from multiple regressions modeling for indoor PM2.5 concentration and indoor psychrometric parameters conditions.

Keywords: classrooms, concentration, humidity, particulate matters, regression

Procedia PDF Downloads 335

Authors: Muhammad Zaman, Guohua Fang, Muhammad Saifullah,

Abstract:

The presented study emphasize at an optimal model to compare past and future optimal hydropower generation. In order to get maximum benefits from the Xin’anjiang hydropower station a model is developed. A Particle Swarm Optimization (PSO) has purposed and past and future water flow is used to get the maximum benefits from future water resources in this study. The results revealed that the future hydropower generation is more than the past generation. This paper gives us idea that what could we get in the past using optimal method of electricity generation and what can we get in the future using this technique.

Keywords: PSO, future water resources, optimization, Xin’anjiang,

Procedia PDF Downloads 444

Authors: J. Bernasovska, I. Boronova, J. Poracova, M. Mydlarova Blascakova, V. Szabadosova, P. Ruzbarsky, E. Petrejcikova, I. Bernasovsky

Abstract:

The paper presents the results of the molecular genetics analysis in sports research, with special emphasis to use genetic information in diagnosing of motoric predispositions in Roma boys from East Slovakia. The ability and move are the basic characteristics of all living organisms. The phenotypes are influenced by a combination of genetic and environmental factors. Genetic tests differ in principle from the traditional motoric tests, because the DNA of an individual does not change during life. The aim of the presented study was to examine motion abilities and to determine the frequency of ACTN3 (R577X) gene in Roma children. Genotype data were obtained from 138 Roma and 155 Slovak boys from 7 to 15 years old. Children were investigated on physical performance level in association with their genotype. Biological material for genetic analyses comprised samples of buccal swabs. Genotypes were determined using Real Time High resolution melting PCR method (Rotor-Gene 6000 Corbett and Light Cycler 480 Roche). The software allows creating reports of any analysis, where information of the specific analysis, normalized and differential graphs and many information of the samples are shown. Roma children of analyzed group legged to non-Romany children at the same age in all the compared tests. The % distribution of R and X alleles in Roma children was different from controls. The frequency of XX genotype was 9.26%, RX 46.33% and RR was 44.41%. The frequency of XX genotype was 9.26% which is comparable to a frequency of an Indian population. Data were analyzed with the ANOVA test.

Keywords: ACTN3 gene, R577X polymorphism, Roma children, sport performance, Slovakia

Procedia PDF Downloads 334

Authors: Jaypalsinh B. Parmar, Pintu Nakrani, Ashish Chaurasia

Abstract:

Digital Elevation Model (DEM) is considered as an important data in GIS-based terrain analysis for many applications and assessment of processes such as environmental and climate change studies, hydrologic modelling, etc. Vertical accuracy of DEM having geographically dynamic nature depends on different parameters which affect the model simulation outcomes. Vertical accuracy assessment in Indian landscape especially in low-lying coastal urban terrain such as lower Tapi Basin is very limited. In the present study, attempt has been made to evaluate the vertical accuracy of 30m resolution open source Indian National Cartosat-1 DEM v3 for Lower Tapi Basin (LTB) from western India. The extensive field investigation is carried out using stratified random fast static DGPS survey in the entire study region, and 117 high accuracy ground control points (GCPs) have been obtained. The above open source DEM was compared with obtained GCPs, and different statistical attributes were envisaged, and vertical error histograms were also evaluated.

Keywords: CartoDEM, Digital Elevation Model, GPS, lower Tapi basin

Procedia PDF Downloads 358

Authors: Ganratchakan Ninlawan, Witthaya Mekhum

Abstract:

The objective of this research was to investigate motivation needs in working of the employees in Rayong Province at Panakom Co., Ltd. The sample group included 59 operational employees of Panakom Co., Ltd divided into 2 main parts to complete the questionnaires. Part 1 dealt with personal information of the staff in the form of checklist questions. Part 2 was about the motivation needs in working in the form of 5 rating scales. The data were analyzed to find frequency, percentage, arithmetic mean, and SD with the results as follows. They reported their working conditions in the moderate level while the first aspect was on the regulation of the Working Support Department. The second rated aspect was on the modern facilities and office stationeries followed by the working environment such as lighting, temperature, sound system, and atmosphere. The last aspect was on the provision of enough working equipment. On the part of work stability and work progress, they rated this aspect at the moderate level with the details below. The first aspect was their satisfaction in work rotation followed by the encouragement in joining training and seminar to increase working knowledge. The third aspect was their perception on the progress of their careers. The last aspect was on the chance to get promoted in special cases. On the payment and fringe benefit, they rated this part in the moderate level with the highest aspect being on the provided fringe benefit such as health care. The second aspect was on the suitable salary compared to their knowledge and proficiency. The third aspect was on the satisfaction on the activities and seminars provided by the company. Finally, the last aspect was on the sufficient salary when compared with the current cost of living.

Keywords: motivation needs, working, employees, Rayong Province

Procedia PDF Downloads 254

Authors: Faroudja Mohellebi, Fayrouz Khalida Kies, Moncef Rezzik El Marhoun, Feriel Yahiat

Abstract:

The purpose of this study is to valorize an agro-food waste (orange peels) by its use as an adsorbent in the treatment of water loaded with pharmaceutical micropollutant present in aquatic environments, oxytetracycline. The tests, carried out in batch mode, made it possible to study the influence on the sorptive capacity of calcined orange peels of several parameters: the contact time, the initial concentration of oxytetracycline, the adsorbent dose, and the initial pH of the solution. The pseudo-second-order model is best adapted to represent the adsorption kinetics. The Langmuir model describes the adsorption isotherm of oxytetracycline. The adsorption is favored in a basic environment.

Keywords: adsorption, emerging pollutants, oxytetracycline, water treatment

Procedia PDF Downloads 154

Authors: WooJin KANG

Abstract:

Contrary to the ideal, in the cartelized democracy, meritocracy is revealed to be a system that gives arrogance to the winners and humiliation to the losers, and more and more studies are asserting the upper-class bias of meritocracy. However, only some studies have analyzed the determinants of the perception of meritocracy and fairness among young people. This article was an attempt to fill this gap. According to the empirical results of this article, the determinants of fairness of the meritocracy in the youth were multidimensional. The social status model, the political ideology model, and the future prospect model all significantly impacted the perception of meritocracy fairness among young people. Contrary to the predictions of the system justification theory and the compensatory control theory of previous studies, the lower-class youth were critical of meritocracy. In addition, the more negative the future outlook, the less they accepted the fairness of meritocracy. In addition, ideological debates over solutions to inequality of opportunity, which began in earnest during the 20th presidential election, turned out to be a variable that significantly influenced the perception of fairness based on meritocracy among young people. The results of the empirical analysis in this article reaffirmed the multidimensional structure of the youth. This suggests the need for policy responses leading to education tailored to various subgroups within the youth.

Keywords: Meritocracy, Exam-Meritocracy, Fairness, Multiple-inequality

Procedia PDF Downloads 63

Authors: Jocelyn Solomons, Sheree Bekker, Ryan Groom, Wilbur Kraak

Abstract:

Sports coaching is marked by inherent elements of complexity. Coaches constantly encounter ambiguity, as they are unable to have complete certainty regarding the perspectives and expectations of stakeholders. Moreover, the coaching environment is characterised by its dynamic nature and intricate micro-political dynamics which further add to the complexity that coaches must navigate. This research study offers a unique perspective on the practical manifestation of coaching effectiveness in the South African (SA) context, where the sport is in its early stages of development. With a predominant presence of male coaches training female players and players originating from diverse sporting backgrounds, including a majority of those who commence their rugby careers at the university level, this exploration, along with practical recommendations, becomes essential. It allows for a nuanced understanding of coaching practices within a rugby system that concurrently focuses on development and high performance. By integrating the views of both players and coaches, insights are gained that extend traditional assessments, enabling a comprehensive understanding of coaching effectiveness and its implications in this evolving Women’s Rugby landscape. Through semi-structured interviews, the research delves into their assessments of coaching strategies, methodologies, and outcomes, aiming to understand coaching efficacy and its impact on player development. The findings contribute to a nuanced understanding of coaching effectiveness, paving the way for evidence-based recommendations to enhance coaching development and positively impact the sport's growth and success in SA.

Keywords: women’s rugby, coaching effectiveness, coaching, rugby, coaching education

Procedia PDF Downloads 53