Search results for: regression model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 18602

Search results for: regression model

17342 Scour Depth Prediction around Bridge Piers Using Neuro-Fuzzy and Neural Network Approaches

Authors: H. Bonakdari, I. Ebtehaj

Abstract:

The prediction of scour depth around bridge piers is frequently considered in river engineering. One of the key aspects in efficient and optimum bridge structure design is considered to be scour depth estimation around bridge piers. In this study, scour depth around bridge piers is estimated using two methods, namely the Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN). Therefore, the effective parameters in scour depth prediction are determined using the ANN and ANFIS methods via dimensional analysis, and subsequently, the parameters are predicted. In the current study, the methods’ performances are compared with the nonlinear regression (NLR) method. The results show that both methods presented in this study outperform existing methods. Moreover, using the ratio of pier length to flow depth, ratio of median diameter of particles to flow depth, ratio of pier width to flow depth, the Froude number and standard deviation of bed grain size parameters leads to optimal performance in scour depth estimation.

Keywords: adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN), bridge pier, scour depth, nonlinear regression (NLR)

Procedia PDF Downloads 215
17341 Software Assessment Using Ant Colony Optimization Algorithm

Authors: Saad M. Darwish

Abstract:

Recently, software quality issues have come to be seen as important subject as we see an enormous growth of agencies involved in software industries. However,these agencies cannot guarantee the quality of their products, thus leaving users in uncertainties. Software certification is the extension of quality by means that quality needs to be measured prior to certification granting process. This research participates in solving the problem of software assessment by proposing a model for assessment and certification of software product that uses a fuzzy inference engine to integrate both of process–driven and application-driven quality assurance strategies. The key idea of the on hand model is to improve the compactness and the interpretability of the model’s fuzzy rules via employing an ant colony optimization algorithm (ACO), which tries to find good rules description by dint of compound rules initially expressed with traditional single rules. The model has been tested by case study and the results have demonstrated feasibility and practicability of the model in a real environment.

Keywords: optimization technique, quality assurance, software certification model, software assessment

Procedia PDF Downloads 482
17340 Simulation Study on Vehicle Drag Reduction by Surface Dimples

Authors: S. F. Wong, S. S. Dol

Abstract:

Automotive designers have been trying to use dimples to reduce drag in vehicles. In this work, a car model has been applied with dimple surface with a parameter called dimple ratio DR, the ratio between the depths of the half dimple over the print diameter of the dimple, has been introduced and numerically simulated via k-ε turbulence model to study the aerodynamics performance with the increasing depth of the dimples The Ahmed body car model with 25 degree slant angle is simulated with the DR of 0.05, 0.2, 0.3 0.4 and 0.5 at Reynolds number of 176387 based on the frontal area of the car model. The geometry of dimple changes the kinematics and dynamics of flow. Complex interaction between the turbulent fluctuating flow and the mean flow escalates the turbulence quantities. The maximum level of turbulent kinetic energy occurs at DR = 0.4. It can be concluded that the dimples have generated extra turbulence energy at the surface and as a result, the application of dimples manages to reduce the drag coefficient of the car model compared to the model with smooth surface.

Keywords: aerodynamics, boundary layer, dimple, drag, kinetic energy, turbulence

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17339 A Comparative Analysis of the Performance of COSMO and WRF Models in Quantitative Rainfall Prediction

Authors: Isaac Mugume, Charles Basalirwa, Daniel Waiswa, Mary Nsabagwa, Triphonia Jacob Ngailo, Joachim Reuder, Sch¨attler Ulrich, Musa Semujju

Abstract:

The Numerical weather prediction (NWP) models are considered powerful tools for guiding quantitative rainfall prediction. A couple of NWP models exist and are used at many operational weather prediction centers. This study considers two models namely the Consortium for Small–scale Modeling (COSMO) model and the Weather Research and Forecasting (WRF) model. It compares the models’ ability to predict rainfall over Uganda for the period 21st April 2013 to 10th May 2013 using the root mean square (RMSE) and the mean error (ME). In comparing the performance of the models, this study assesses their ability to predict light rainfall events and extreme rainfall events. All the experiments used the default parameterization configurations and with same horizontal resolution (7 Km). The results show that COSMO model had a tendency of largely predicting no rain which explained its under–prediction. The COSMO model (RMSE: 14.16; ME: -5.91) presented a significantly (p = 0.014) higher magnitude of error compared to the WRF model (RMSE: 11.86; ME: -1.09). However the COSMO model (RMSE: 3.85; ME: 1.39) performed significantly (p = 0.003) better than the WRF model (RMSE: 8.14; ME: 5.30) in simulating light rainfall events. All the models under–predicted extreme rainfall events with the COSMO model (RMSE: 43.63; ME: -39.58) presenting significantly higher error magnitudes than the WRF model (RMSE: 35.14; ME: -26.95). This study recommends additional diagnosis of the models’ treatment of deep convection over the tropics.

Keywords: comparative performance, the COSMO model, the WRF model, light rainfall events, extreme rainfall events

Procedia PDF Downloads 258
17338 Mathematical Model for Output Yield Obtained by Single Slope Solar Still

Authors: V. Nagaraju, G. Murali, Nagarjunavarma Ganna, Atluri Pavan Kalyan, N. Sree Sai Ganesh, V. S. V. S. Badrinath

Abstract:

The present work focuses on the development of a mathematical model for the yield obtained by single slope solar still incorporated with cylindrical pipes filled with sand. The mathematical results obtained were validated with the experimental results for the 3 cm of water level at the basin. The mathematical model and results obtained with the experimental investigation are within 11% of deviation. The theoretical model to predict the yield obtained due to the capillary effect was proposed first. And then, to predict the total yield obtained, the thermal effect model was integrated with the capillary effect model. With the obtained results, it is understood that the yield obtained is more in the case of solar stills with sand-filled cylindrical pipes when compared to solar stills without sand-filled cylindrical pipes. And later model was used for predicting yield for 1 cm and 2 cm of water levels at the basin. And it is observed that the maximum yield was obtained for a 1 cm water level at the basin. It means solar still produces better yield with the lower depth of water level at the basin; this may be because of the availability of more space in the sand for evaporation.

Keywords: solar still, cylindrical pipes, still efficiency, mathematical modeling, capillary effect model, yield, solar desalination

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17337 Iterative Panel RC Extraction for Capacitive Touchscreen

Authors: Chae Hoon Park, Jong Kang Park, Jong Tae Kim

Abstract:

Electrical characteristics of capacitive touchscreen need to be accurately analyzed to result in better performance for multi-channel capacitance sensing. In this paper, we extracted the panel resistances and capacitances of the touchscreen by comparing measurement data and model data. By employing a lumped RC model for driver-to-receiver paths in touchscreen, we estimated resistance and capacitance values according to the physical lengths of channel paths which are proportional to the RC model. As a result, we obtained the model having 95.54% accuracy of the measurement data.

Keywords: electrical characteristics of capacitive touchscreen, iterative extraction, lumped RC model, physical lengths of channel paths

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17336 Identification of Wiener Model Using Iterative Schemes

Authors: Vikram Saini, Lillie Dewan

Abstract:

This paper presents the iterative schemes based on Least square, Hierarchical Least Square and Stochastic Approximation Gradient method for the Identification of Wiener model with parametric structure. A gradient method is presented for the parameter estimation of wiener model with noise conditions based on the stochastic approximation. Simulation results are presented for the Wiener model structure with different static non-linear elements in the presence of colored noise to show the comparative analysis of the iterative methods. The stochastic gradient method shows improvement in the estimation performance and provides fast convergence of the parameters estimates.

Keywords: hard non-linearity, least square, parameter estimation, stochastic approximation gradient, Wiener model

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17335 Prediction of Thermodynamic Properties of N-Heptane in the Critical Region

Authors: Sabrina Ladjama, Aicha Rizi, Azzedine Abbaci

Abstract:

In this work, we use the crossover model to formulate a comprehensive fundamental equation of state for the thermodynamic properties for several n-alkanes in the critical region that extends to the classical region. This equation of state is constructed on the basis of comparison of selected measurements of pressure-density-temperature data, isochoric and isobaric heat capacity. The model can be applied in a wide range of temperatures and densities around the critical point for n-heptane. It is found that the developed model represents most of the reliable experimental data accurately.

Keywords: crossover model, critical region, fundamental equation, n-heptane

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17334 Non-Performing Assets and Credit Risk Performance: An Evidence of Commercial Banks in India

Authors: Sirus Sharifi, Arunima Haldar, S. V. D. Nageswara Rao

Abstract:

This research analyzes the effect of credit risk management practices of commercial banks in India and the relationship with their non-performing assets (NPAs). Required data on credit risk performance was collected through a survey questionnaire from top risk officers of 38 Indian banks. NPA data (period from 2012 to 2016) was collected from Prowess database compiled by the Centre for Monitoring Indian Economy (CMIE). The model was assessed utilizing cross sectional regression method. As expected, the results indicate a negative significant relationship between credit risk management in India banks and their NPA growth. The research has implications for banks given the high level of losses in India and other economies as well, and the implementation of Basel III standards by the central banks. This research would be an evidence on credit risk performance and its relationship with the level of non-performing assets (NPAs) in Indian banks.

Keywords: risk management, risk identification, banks, Non-Performing Assets (NPAs)

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17333 Coordination Polymer Hydrogels Based on Coinage Metals and Nucleobase Derivatives

Authors: Lamia L. G. Al-Mahamad, Benjamin R. Horrocks, Andrew Houlton

Abstract:

Hydrogels based on metal coordination polymers of nucleosides and a range of metal ions (Au, Ag, Cu) have been prepared and characterized by atomic force microscopy (AFM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, ultraviolet-visible absorption spectroscopy, and powder X-ray diffraction. AFM images of the xerogels revealed the formation of extremely long polymer molecules (> 10 micrometers, the maximum scan range). This result is also consistent with TEM images which show a fibrous morphology. Oxidative doping of the Au-nucleoside fibres produces an electrically conductive nanowire. No sharp Bragg peaks were found at the at the X-ray diffraction pattern for metal ions hydrogels indicating that the samples were amorphous, but instead the data showed broad peaks in the range 20 < Q < 40 and correspond to distances d=2μ/Q. The data was analysed using a simplified Rietveld method by fitting a regression model to obtain the distance between atoms.

Keywords: hydrogel, metal ions, nanowire, nucleoside

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17332 Markov Characteristics of the Power Line Communication Channels in China

Authors: Ming-Yue Zhai

Abstract:

Due to the multipath and pulse noise nature, power line communications(PLC) channel can be modelled as a memory one with the finite states Markov model(FSMC). As the most important parameter modelling a Markov channel,the memory order in an FSMC is not solved in PLC systems yet. In the paper, the mutual information is used as a measure of the dependence between the different symbols, treated as the received SNA or amplitude of the current channel symbol or that of previous symbols. The joint distribution probabilities of the envelopes in PLC systems are computed based on the multi-path channel model, which is commonly used in PLC. we confirm that given the information of the symbol immediately preceding the current one, any other previous symbol is independent of the current one in PLC systems, which means the PLC channels is a Markov chain with the first-order. The field test is also performed to model the received OFDM signals with the help of AR model. The results show that the first-order AR model is enough to model the fading channel in PLC systems, which means the amount of uncertainty remaining in the current symbol should be negligible, given the information corresponding to the immediately preceding one.

Keywords: power line communication, channel model, markovian, information theory, first-order

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17331 Estimation of the Effect of Initial Damping Model and Hysteretic Model on Dynamic Characteristics of Structure

Authors: Shinji Ukita, Naohiro Nakamura, Yuji Miyazu

Abstract:

In considering the dynamic characteristics of structure, natural frequency and damping ratio are useful indicator. When performing dynamic design, it's necessary to select an appropriate initial damping model and hysteretic model. In the linear region, the setting of initial damping model influences the response, and in the nonlinear region, the combination of initial damping model and hysteretic model influences the response. However, the dynamic characteristics of structure in the nonlinear region remain unclear. In this paper, we studied the effect of setting of initial damping model and hysteretic model on the dynamic characteristics of structure. On initial damping model setting, Initial stiffness proportional, Tangent stiffness proportional, and Rayleigh-type were used. On hysteretic model setting, TAKEDA model and Normal-trilinear model were used. As a study method, dynamic analysis was performed using a lumped mass model of base-fixed. During analysis, the maximum acceleration of input earthquake motion was gradually increased from 1 to 600 gal. The dynamic characteristics were calculated using the ARX model. Then, the characteristics of 1st and 2nd natural frequency and 1st damping ratio were evaluated. Input earthquake motion was simulated wave that the Building Center of Japan has published. On the building model, an RC building with 30×30m planes on each floor was assumed. The story height was 3m and the maximum height was 18m. Unit weight for each floor was 1.0t/m2. The building natural period was set to 0.36sec, and the initial stiffness of each floor was calculated by assuming the 1st mode to be an inverted triangle. First, we investigated the difference of the dynamic characteristics depending on the difference of initial damping model setting. With the increase in the maximum acceleration of the input earthquake motions, the 1st and 2nd natural frequency decreased, and the 1st damping ratio increased. Then, in the natural frequency, the difference due to initial damping model setting was small, but in the damping ratio, a significant difference was observed (Initial stiffness proportional≒Rayleigh type>Tangent stiffness proportional). The acceleration and the displacement of the earthquake response were largest in the tangent stiffness proportional. In the range where the acceleration response increased, the damping ratio was constant. In the range where the acceleration response was constant, the damping ratio increased. Next, we investigated the difference of the dynamic characteristics depending on the difference of hysteretic model setting. With the increase in the maximum acceleration of the input earthquake motions, the natural frequency decreased in TAKEDA model, but in Normal-trilinear model, the natural frequency didn’t change. The damping ratio in TAKEDA model was higher than that in Normal-trilinear model, although, both in TAKEDA model and Normal-trilinear model, the damping ratio increased. In conclusion, in initial damping model setting, the tangent stiffness proportional was evaluated the most. In the hysteretic model setting, TAKEDA model was more appreciated than the Normal-trilinear model in the nonlinear region. Our results would provide useful indicator on dynamic design.

Keywords: initial damping model, damping ratio, dynamic analysis, hysteretic model, natural frequency

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17330 Spatial Time Series Models for Rice and Cassava Yields Based on Bayesian Linear Mixed Models

Authors: Panudet Saengseedam, Nanthachai Kantanantha

Abstract:

This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.

Keywords: Bayesian method, linear mixed model, multivariate conditional autoregressive model, spatial time series

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17329 Comparison of Accumulated Stress Based Pore Pressure Model and Plasticity Model in 1D Site Response Analysis

Authors: Saeedullah J. Mandokhail, Shamsher Sadiq, Meer H. Khan

Abstract:

This paper presents the comparison of excess pore water pressure ratio (ru) predicted by using accumulated stress based pore pressure model and plasticity model. One dimensional effective stress site response analyses were performed on a 30 m deep sand column (consists of a liquefiable layer in between non-liquefiable layers) using accumulated stress based pore pressure model in Deepsoil and PDMY2 (PressureDependentMultiYield02) model in Opensees. Three Input motions with different peak ground acceleration (PGA) levels of 0.357 g, 0.124 g, and 0.11 g were used in this study. The developed excess pore pressure ratio predicted by the above two models were compared and analyzed along the depth. The time history of the ru at mid of the liquefiable layer and non-liquefiable layer were also compared. The comparisons show that the two models predict mostly similar ru values. The predicted ru is also consistent with the PGA level of the input motions.

Keywords: effective stress, excess pore pressure ratio, pore pressure model, site response analysis

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17328 Investigating the Relationship between Emotional Intelligence and Self-Efficacy of Physical Education Teachers in Ilam Province

Authors: Ali Heyrani, Maryam Saidyousefi

Abstract:

The aim of the present study was to investigate the relationship between emotional intelligence and Self-Efficacy of physical education teachers in Ilam province. The research method is descriptive correlational. The study participants were of 170 physical education teachers (90 males, 80 females) with an age range of 20 to 50 years, who were selected randomly. The instruments for data collection were Emotional Intelligence Questionnaire Bar-on (1997) to assess the Emotional Intelligence teachers and Self-Efficacy Questionnaire to measure their Self-Efficacy. The questionnaires used in the interior are reliable and valid. To analyze the data, descriptive statistics and inferential tests (Kolmogorov-Smirnov test, Pearson correlation and multiple regression) at a significance level of P <0/ 05 were used. The Results showed that there is a significant positive relationship between totall emotional intelligence and Self-Efficacy of teachers, so the more emotional intelligence of physical education teachers the better the extent of Self-Efficacy. Also, the results arising from regression analysis gradually showed that among components of emotional intelligence, three components, the General Mood, Adaptability, and Interpersonal Communication to Self-Efficacy are of a significant positive relationship and are able to predict the Self-Efficacy of physical education teachers. It seems the application of this study ҆s results can help to education authorities to promote the level of teachers’ emotional intelligence and therefore the improvement of their Self-Efficacy and success in learners’ teaching and training.

Keywords: emotional intelligence, self-efficacy, physical education teachers, Ilam province

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17327 The Ability of Forecasting the Term Structure of Interest Rates Based on Nelson-Siegel and Svensson Model

Authors: Tea Poklepović, Zdravka Aljinović, Branka Marasović

Abstract:

Due to the importance of yield curve and its estimation it is inevitable to have valid methods for yield curve forecasting in cases when there are scarce issues of securities and/or week trade on a secondary market. Therefore in this paper, after the estimation of weekly yield curves on Croatian financial market from October 2011 to August 2012 using Nelson-Siegel and Svensson models, yield curves are forecasted using Vector auto-regressive model and Neural networks. In general, it can be concluded that both forecasting methods have good prediction abilities where forecasting of yield curves based on Nelson Siegel estimation model give better results in sense of lower Mean Squared Error than forecasting based on Svensson model Also, in this case Neural networks provide slightly better results. Finally, it can be concluded that most appropriate way of yield curve prediction is neural networks using Nelson-Siegel estimation of yield curves.

Keywords: Nelson-Siegel Model, neural networks, Svensson Model, vector autoregressive model, yield curve

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17326 Understanding Cruise Passengers’ On-board Experience throughout the Customer Decision Journey

Authors: Sabina Akter, Osiris Valdez Banda, Pentti Kujala, Jani Romanoff

Abstract:

This paper examines the relationship between on-board environmental factors and customer overall satisfaction in the context of the cruise on-board experience. The on-board environmental factors considered are ambient, layout/design, social, product/service and on-board enjoyment factors. The study presents a data-driven framework and model for the on-board cruise experience. The data are collected from 893 respondents in an application of a self-administered online questionnaire of their cruise experience. This study reveals the cruise passengers’ on-board experience through the customer decision journey based on the publicly available data. Pearson correlation and regression analysis have been applied, and the results show a positive and a significant relationship between the environmental factors and on-board experience. These data help understand the cruise passengers’ on-board experience, which will be used for the ultimate decision-making process in cruise ship design.

Keywords: cruise behavior, customer activities, on-board environmental factors, on-board experience, user or customer satisfaction

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17325 Model for Assessment of Quality Airport Services

Authors: Cristina da Silva Torres, José Luis Duarte Ribeiro, Maria Auxiliadora Cannarozzo Tinoco

Abstract:

As a result of the rapid growth of the Brazilian Air Transport, many airports are at the limit of their capacities and have a reduction in the quality of services provided. Thus, there is a need of models for assessing the quality of airport services. Because of this, the main objective of this work is to propose a model for the evaluation of quality attributes in airport services. To this end, we used the method composed by literature review and interview. Structured a working method composed by 5 steps, which resulted in a model to evaluate the quality of airport services, consisting of 8 dimensions and 45 attributes. Was used as base for model definition the process mapping of boarding and landing processes of passengers and luggage. As a contribution of this work is the integration of management process with structuring models to assess the quality of services in airport environments.

Keywords: quality airport services, model for identification of attributes quality, air transport, passenger

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17324 Implementing Activity-Based Costing in Architectural Aluminum Projects: Case Study and Lessons Learned

Authors: Amer Momani, Tarek Al-Hawari, Abdallah Alakayleh

Abstract:

This study explains how to construct an actionable activity-based costing and management system to accurately track and account the total costs of architectural aluminum projects. Two ABC models were proposed to accomplish this purpose. First, the learning and development model was introduced to examine how to apply an ABC model in an architectural aluminum firm for the first time and to be familiar with ABC concepts. Second, an actual ABC model was built on the basis of the results of the previous model to accurately trace the actual costs incurred on each project in a year, and to be able to provide a quote with the best trade-off between competitiveness and profitability. The validity of the proposed model was verified on a local architectural aluminum company.

Keywords: activity-based costing, activity-based management, construction, architectural aluminum

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17323 Degumming of Eri Silk Fabric with Ionic Liquid

Authors: Shweta K. Vyas, Rakesh Musale, Sanjeev R. Shukla

Abstract:

Eri silk is a non mulberry silk which is obtained without killing the silkworms and hence it is also known as Ahmisa silk. In the present study, the results on degumming of eri silk with alkaline peroxide have been compared with those obtained by using ionic liquid (IL) 1-Butyl-3-methylimidazolium chloride [BMIM]Cl. Experiments were designed to find out the optimum processing parameters for degumming of eri silk by response surface methodology. The statistical software, Design-Expert 6.0 was used for regression analysis and graphical analysis of the responses obtained by running the set of designed experiments. Analysis of variance (ANOVA) was used to estimate the statistical parameters. The polynomial equation of quadratic order was employed to fit the experimental data. The quality and model terms were evaluated by F-test. Three dimensional surface plots were prepared to study the effect of variables on different responses. The optimum conditions for IL treatment were selected from predicted combinations and the experiments were repeated under these conditions to determine the reproducibility.

Keywords: silk degumming, ionic liquid, response surface methodology, ANOVA

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17322 Dual-Network Memory Model for Temporal Sequences

Authors: Motonobu Hattori

Abstract:

In neural networks, when new patters are learned by a network, they radically interfere with previously stored patterns. This drawback is called catastrophic forgetting. We have already proposed a biologically inspired dual-network memory model which can much reduce this forgetting for static patterns. In this model, information is first stored in the hippocampal network, and thereafter, it is transferred to the neocortical network using pseudo patterns. Because, temporal sequence learning is more important than static pattern learning in the real world, in this study, we improve our conventional dual-network memory model so that it can deal with temporal sequences without catastrophic forgetting. The computer simulation results show the effectiveness of the proposed dual-network memory model.

Keywords: catastrophic forgetting, dual-network, temporal sequences, hippocampal

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17321 Consequences of Employees' Perception of Political Behavior in Kuwaiti Business Organizations

Authors: Ali Muhammad

Abstract:

The purpose of this study is to examine the effect of employees’ perception of political behavior on their behavior and attitudes. The model tested in this study suggests that employees’ perception of political behavior in their organizations leads to lower levels of job satisfaction, and organizational commitment, and higher levels of work-related stress, and intentions to leave the organization. A sample of 182 employees working in six Kuwaiti business organizations were surveyed using a questionnaire, and data was analyzed using correlation analysis, regression analysis, and non-parametric tests. Results reveal that employees’ perception of political behavior is negatively associated with job satisfaction and organizational commitment, and positively associated with work-related stress and employees’ intentions to leave the organization. The results of the current study are discussed and are compared to the results of previous studies in this area. Finally, the directions for future research are suggested.

Keywords: perceptions of political behavior, organizational commitment, job satisfaction, intention to leave

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17320 A Comparative Study of Dengue Fever in Taiwan and Singapore Based on Open Data

Authors: Wei Wen Yang, Emily Chia Yu Su

Abstract:

Dengue fever is a mosquito-borne tropical infectious disease caused by the dengue virus. After infection, symptoms usually start from three to fourteen days. Dengue virus may cause a high fever and at least two of the following symptoms, severe headache, severe eye pain, joint pains, muscle or bone pain, vomiting, feature skin rash, and mild bleeding manifestation. In addition, recovery will take at least two to seven days. Dengue fever has rapidly spread in tropical and subtropical areas in recent years. Several phenomena around the world such as global warming, urbanization, and international travel are the main reasons in boosting the spread of dengue. In Taiwan, epidemics occur annually, especially during summer and fall seasons. On the other side, Singapore government also has announced the amounts number of dengue cases spreading in Singapore. As the serious epidemic of dengue fever outbreaks in Taiwan and Singapore, countries around the Asia-Pacific region are becoming high risks of susceptible to the outbreaks and local hub of spreading the virus. To improve public safety and public health issues, firstly, we are going to use Microsoft Excel and SAS EG to do data preprocessing. Secondly, using support vector machines and decision trees builds predict model, and analyzes the infectious cases between Taiwan and Singapore. By comparing different factors causing vector mosquito from model classification and regression, we can find similar spreading patterns where the disease occurred most frequently. The result can provide sufficient information to predict the future dengue infection outbreaks and control the diffusion of dengue fever among countries.

Keywords: dengue fever, Taiwan, Singapore, Aedes aegypti

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17319 Extending Early High Energy Physics Studies with a Tri-Preon Model

Authors: Peter J. Riley

Abstract:

Introductory courses in High Energy Physics (HEP) can be extended with the Tri-Preon (TP) model to both supplements and challenge the Standard Model (SM) theory. TP supplements by simplifying the tracking of Conserved Quantum Numbers at an interaction vertex, e.g., the lepton number can be seen as a di-preon current. TP challenges by proposing extended particle families to three generations of particle triplets for leptons, quarks, and weak bosons. There are extensive examples discussed at an introductory level in six arXiv publications, including supersymmetry, hyper color, and the Higgs. Interesting exercises include pion decay, kaon-antikaon mixing, neutrino oscillations, and K+ decay to muons. It is a revealing exercise for students to weigh the pros and cons of parallel theories at an early stage in their HEP journey.

Keywords: HEP, particle physics, standard model, Tri-Preon model

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17318 A Generalized Model for Performance Analysis of Airborne Radar in Clutter Scenario

Authors: Vinod Kumar Jaysaval, Prateek Agarwal

Abstract:

Performance prediction of airborne radar is a challenging and cumbersome task in clutter scenario for different types of targets. A generalized model requires to predict the performance of Radar for air targets as well as ground moving targets. In this paper, we propose a generalized model to bring out the performance of airborne radar for different Pulsed Repetition Frequency (PRF) as well as different type of targets. The model provides a platform to bring out different subsystem parameters for different applications and performance requirements under different types of clutter terrain.

Keywords: airborne radar, blind zone, clutter, probability of detection

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17317 Machine Learning Based Anomaly Detection in Hydraulic Units of Governors in Hydroelectric Power Plants

Authors: Mehmet Akif Bütüner, İlhan Koşalay

Abstract:

Hydroelectric power plants (HEPPs) are renewable energy power plants with the highest installed power in the world. While the control systems operating in these power plants ensure that the system operates at the desired operating point, it is also responsible for stopping the relevant unit safely in case of any malfunction. While these control systems are expected not to miss signals that require stopping, on the other hand, it is desired not to cause unnecessary stops. In traditional control systems including modern systems with SCADA infrastructure, alarm conditions to create warnings or trip conditions to put relevant unit out of service automatically are usually generated with predefined limits regardless of different operating conditions. This approach results in alarm/trip conditions to be less likely to detect minimal changes which may result in serious malfunction scenarios in near future. With the methods proposed in this research, routine behavior of the oil circulation of hydraulic governor of a HEPP will be modeled with machine learning methods using historical data obtained from SCADA system. Using the created model and recently gathered data from control system, oil pressure of hydraulic accumulators will be estimated. Comparison of this estimation with the measurements made and recorded instantly by the SCADA system will help to foresee failure before becoming worse and determine remaining useful life. By using model outputs, maintenance works will be made more planned, so that undesired stops are prevented, and in case of any malfunction, the system will be stopped or several alarms are triggered before the problem grows.

Keywords: hydroelectric, governor, anomaly detection, machine learning, regression

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17316 Enhancement Method of Network Traffic Anomaly Detection Model Based on Adversarial Training With Category Tags

Authors: Zhang Shuqi, Liu Dan

Abstract:

For the problems in intelligent network anomaly traffic detection models, such as low detection accuracy caused by the lack of training samples, poor effect with small sample attack detection, a classification model enhancement method, F-ACGAN(Flow Auxiliary Classifier Generative Adversarial Network) which introduces generative adversarial network and adversarial training, is proposed to solve these problems. Generating adversarial data with category labels could enhance the training effect and improve classification accuracy and model robustness. FACGAN consists of three steps: feature preprocess, which includes data type conversion, dimensionality reduction and normalization, etc.; A generative adversarial network model with feature learning ability is designed, and the sample generation effect of the model is improved through adversarial iterations between generator and discriminator. The adversarial disturbance factor of the gradient direction of the classification model is added to improve the diversity and antagonism of generated data and to promote the model to learn from adversarial classification features. The experiment of constructing a classification model with the UNSW-NB15 dataset shows that with the enhancement of FACGAN on the basic model, the classification accuracy has improved by 8.09%, and the score of F1 has improved by 6.94%.

Keywords: data imbalance, GAN, ACGAN, anomaly detection, adversarial training, data augmentation

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17315 A Business Model Design Process for Social Enterprises: The Critical Role of the Environment

Authors: Hadia Abdel Aziz, Raghda El Ebrashi

Abstract:

Business models are shaped by their design space or the environment they are designed to be implemented in. The rapidly changing economic, technological, political, regulatory and market external environment severely affects business logic. This is particularly true for social enterprises whose core mission is to transform their environments, and thus, their whole business logic revolves around the interchange between the enterprise and the environment. The context in which social business operates imposes different business design constraints while at the same time, open up new design opportunities. It is also affected to a great extent by the impact that successful enterprises generate; a continuous loop of interaction that needs to be managed through a dynamic capability in order to generate a lasting powerful impact. This conceptual research synthesizes and analyzes literature on social enterprise, social enterprise business models, business model innovation, business model design, and the open system view theory to propose a new business model design process for social enterprises that takes into account the critical role of environmental factors. This process would help the social enterprise develop a dynamic capability that ensures the alignment of its business model to its environmental context, thus, maximizing its probability of success.

Keywords: social enterprise, business model, business model design, business model environment

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17314 The Role of Organizational Culture, Work Discipline, and Employee Motivation towards Employees Performance at Personal Care and Cosmetic Department Flammable PT XYZ Cosmetics

Authors: Novawiguna Kemalasari, Ahmad Badawi Saluy

Abstract:

This research is a planned activity to find an objective answer to PT XYZ problem through scientific procedure. In this study, It was used quantitative research methods by using samples taken from a department selected by researchers. This study aims to analyze the influence of organizational culture, work discipline and work motivation on employee performance of Personal Care & Cosmetic Department (PCC) Flammable PT XYZ. This research was conducted at PT XYZ Personal Care & Cosmetic Department (PCC) Flammable involving 82 employees as respondents, the data were obtained by using questionnaires filled in self-rating by respondents. The data were analyzed by multiple linear regression model processed by using SPSS version 22. The result of research showed that organizational culture variable, work discipline and work motivation had significant effect to employee performance.

Keywords: organizational culture, work discipline, employee motivation, employees performance

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17313 An Extended Inverse Pareto Distribution, with Applications

Authors: Abdel Hadi Ebraheim

Abstract:

This paper introduces a new extension of the Inverse Pareto distribution in the framework of Marshal-Olkin (1997) family of distributions. This model is capable of modeling various shapes of aging and failure data. The statistical properties of the new model are discussed. Several methods are used to estimate the parameters involved. Explicit expressions are derived for different types of moments of value in reliability analysis are obtained. Besides, the order statistics of samples from the new proposed model have been studied. Finally, the usefulness of the new model for modeling reliability data is illustrated using two real data sets with simulation study.

Keywords: pareto distribution, marshal-Olkin, reliability, hazard functions, moments, estimation

Procedia PDF Downloads 79