Search results for: mixed effect logistic regression model
Commenced in January 2007
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Edition: International
Paper Count: 31008

Search results for: mixed effect logistic regression model

30618 Approach to Formulate Intuitionistic Fuzzy Regression Models

Authors: Liang-Hsuan Chen, Sheng-Shing Nien

Abstract:

This study aims to develop approaches to formulate intuitionistic fuzzy regression (IFR) models for many decision-making applications in the fuzzy environments using intuitionistic fuzzy observations. Intuitionistic fuzzy numbers (IFNs) are used to characterize the fuzzy input and output variables in the IFR formulation processes. A mathematical programming problem (MPP) is built up to optimally determine the IFR parameters. Each parameter in the MPP is defined as a couple of alternative numerical variables with opposite signs, and an intuitionistic fuzzy error term is added to the MPP to characterize the uncertainty of the model. The IFR model is formulated based on the distance measure to minimize the total distance errors between estimated and observed intuitionistic fuzzy responses in the MPP resolution processes. The proposed approaches are simple/efficient in the formulation/resolution processes, in which the sign of parameters can be determined so that the problem to predetermine the sign of parameters is avoided. Furthermore, the proposed approach has the advantage that the spread of the predicted IFN response will not be over-increased, since the parameters in the established IFR model are crisp. The performance of the obtained models is evaluated and compared with the existing approaches.

Keywords: fuzzy sets, intuitionistic fuzzy number, intuitionistic fuzzy regression, mathematical programming method

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30617 The Influence of the Company's Financial Performance and Macroeconomic Factors to Stock Return

Authors: Angrita Denziana, Haninun, Hepiana Patmarina, Ferdinan Fatah

Abstract:

The aims of the study are to determine the effect of the company's financial performance with Return on Asset (ROA) and Return on Equity (ROE) indicators. The macroeconomic factors with the indicators of Indonesia interest rate (SBI) and exchange rate on stock returns of non-financial companies listed in IDX. The results of this study indicate that the variable of ROA has negative effect on stock returns, ROE has a positive effect on stock returns, and the variable interest rate and exchange rate of SBI has positive effect on stock returns. From the analysis data by using regression model, independent variables ROA, ROE, SBI interest rate and the exchange rate very significant (p value < 0.01). Thus, all the above variable can be used as the basis for investment decision making for investment in Indonesia Stock Exchange (IDX) mainly for shares in the non- financial companies.

Keywords: ROA, ROE, interest rate, exchange rate, stock return

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30616 Effective Parameter Selection for Audio-Based Music Mood Classification for Christian Kokborok Song: A Regression-Based Approach

Authors: Sanchali Das, Swapan Debbarma

Abstract:

Music mood classification is developing in both the areas of music information retrieval (MIR) and natural language processing (NLP). Some of the Indian languages like Hindi English etc. have considerable exposure in MIR. But research in mood classification in regional language is very less. In this paper, powerful audio based feature for Kokborok Christian song is identified and mood classification task has been performed. Kokborok is an Indo-Burman language especially spoken in the northeastern part of India and also some other countries like Bangladesh, Myanmar etc. For performing audio-based classification task, useful audio features are taken out by jMIR software. There are some standard audio parameters are there for the audio-based task but as known to all that every language has its unique characteristics. So here, the most significant features which are the best fit for the database of Kokborok song is analysed. The regression-based model is used to find out the independent parameters that act as a predictor and predicts the dependencies of parameters and shows how it will impact on overall classification result. For classification WEKA 3.5 is used, and selected parameters create a classification model. And another model is developed by using all the standard audio features that are used by most of the researcher. In this experiment, the essential parameters that are responsible for effective audio based mood classification and parameters that do not significantly change for each of the Christian Kokborok songs are analysed, and a comparison is also shown between the two above model.

Keywords: Christian Kokborok song, mood classification, music information retrieval, regression

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30615 Field Saturation Flow Measurement Using Dynamic Passenger Car Unit under Mixed Traffic Condition

Authors: Ramesh Chandra Majhi

Abstract:

Saturation flow is a very important input variable for the design of signalized intersections. Saturation flow measurement is well established for homogeneous traffic. However, saturation flow measurement and modeling is a challenging task in heterogeneous characterized by multiple vehicle types and non-lane based movement. Present study focuses on proposing a field procedure for Saturation flow measurement and the effect of typical mixed traffic behavior at the signal as far as non-lane based traffic movement is concerned. Data collected during peak and off-peak hour from five intersections with varying approach width is used for validating the saturation flow model. The insights from the study can be used for modeling saturation flow and delay at signalized intersection in heterogeneous traffic conditions.

Keywords: optimization, passenger car unit, saturation flow, signalized intersection

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30614 A Stochastic Model to Predict Earthquake Ground Motion Duration Recorded in Soft Soils Based on Nonlinear Regression

Authors: Issam Aouari, Abdelmalek Abdelhamid

Abstract:

For seismologists, the characterization of seismic demand should include the amplitude and duration of strong shaking in the system. The duration of ground shaking is one of the key parameters in earthquake resistant design of structures. This paper proposes a nonlinear statistical model to estimate earthquake ground motion duration in soft soils using multiple seismicity indicators. Three definitions of ground motion duration proposed by literature have been applied. With a comparative study, we select the most significant definition to use for predict the duration. A stochastic model is presented for the McCann and Shah Method using nonlinear regression analysis based on a data set for moment magnitude, source to site distance and site conditions. The data set applied is taken from PEER strong motion databank and contains shallow earthquakes from different regions in the world; America, Turkey, London, China, Italy, Chili, Mexico...etc. Main emphasis is placed on soft site condition. The predictive relationship has been developed based on 600 records and three input indicators. Results have been compared with others published models. It has been found that the proposed model can predict earthquake ground motion duration in soft soils for different regions and sites conditions.

Keywords: duration, earthquake, prediction, regression, soft soil

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30613 Identifying Factors Contributing to the Spread of Lyme Disease: A Regression Analysis of Virginia’s Data

Authors: Fatemeh Valizadeh Gamchi, Edward L. Boone

Abstract:

This research focuses on Lyme disease, a widespread infectious condition in the United States caused by the bacterium Borrelia burgdorferi sensu stricto. It is critical to identify environmental and economic elements that are contributing to the spread of the disease. This study examined data from Virginia to identify a subset of explanatory variables significant for Lyme disease case numbers. To identify relevant variables and avoid overfitting, linear poisson, and regularization regression methods such as a ridge, lasso, and elastic net penalty were employed. Cross-validation was performed to acquire tuning parameters. The methods proposed can automatically identify relevant disease count covariates. The efficacy of the techniques was assessed using four criteria on three simulated datasets. Finally, using the Virginia Department of Health’s Lyme disease data set, the study successfully identified key factors, and the results were consistent with previous studies.

Keywords: lyme disease, Poisson generalized linear model, ridge regression, lasso regression, elastic net regression

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30612 Entropy Production in Mixed Convection in a Horizontal Porous Channel Using Darcy-Brinkman Formulation

Authors: Amel Tayari, Atef Eljerry, Mourad Magherbi

Abstract:

The paper reports a numerical investigation of the entropy generation analysis due to mixed convection in laminar flow through a channel filled with porous media. The second law of thermodynamics is applied to investigate the entropy generation rate. The Darcy-Brinkman Model is employed. The entropy generation due to heat transfer and friction dissipations has been determined in mixed convection by solving numerically the continuity, momentum and energy equations, using a control volume finite element method. The effects of Darcy number, modified Brinkman number and the Rayleigh number on averaged entropy generation and averaged Nusselt number are investigated. The Rayleigh number varied between 103 ≤ Ra ≤ 105 and the modified Brinkman number ranges between 10-5 ≤ Br≤ 10-1 with fixed values of porosity and Reynolds number at 0.5 and 10 respectively. The Darcy number varied between 10-6 ≤ Da ≤10.

Keywords: entropy generation, porous media, heat transfer, mixed convection, numerical methods, darcy, brinkman

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30611 Mixed Convective Heat Transfer of Flow around a Radial Heat Sink

Authors: Benkherbache Souad

Abstract:

This work presents the numerical results of the mixed convective heat transfer of a three-dimensional flow around a radial heat sink composed of horizontal circular base fitted with rectangular fins. The governing equations of mass, momentum, and energy equation are solved by the finite volume method using the commercially available CFD software Fluent 6.3.26. The circular base of the heat sink is subjected to uniform heat generation; the flow enters through the sides of the heat sink around the fins then the heat is transmitted from the base to the fins afterwards the fluid. In this study two fluids are utilized, in the first case, the air for the following Reynolds numbers Re=600,900,1200 and a Grashof number Gr=3.7x10⁶, in the second case a water based nano fluid for which two types of nano particles (Cu and Al₂O₃) are carried out for Re=25 and a Richardson number Ri=2.7(Ri=Gr/Re²). The effect of the number of the fins of the heat sink as well as the type and the volume fraction of nano particles of the nano fluid were investigated. Results have been presented for N=15 and N=20 fins. The effect of the nano particles concentrations and the number of fins on the temperature in the heat sink and the Nusselt number has been studied.

Keywords: heat sink, mixed convection, nano fluid, volumetric heat generation

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30610 Effect of Variable Fluxes on Optimal Flux Distribution in a Metabolic Network

Authors: Ehsan Motamedian

Abstract:

Finding all optimal flux distributions of a metabolic model is an important challenge in systems biology. In this paper, a new algorithm is introduced to identify all alternate optimal solutions of a large scale metabolic network. The algorithm reduces the model to decrease computations for finding optimal solutions. The algorithm was implemented on the Escherichia coli metabolic model to find all optimal solutions for lactate and acetate production. There were more optimal flux distributions when acetate production was optimized. The model was reduced from 1076 to 80 variable fluxes for lactate while it was reduced to 91 variable fluxes for acetate. These 11 more variable fluxes resulted in about three times more optimal flux distributions. Variable fluxes were from 12 various metabolic pathways and most of them belonged to nucleotide salvage and extra cellular transport pathways.

Keywords: flux variability, metabolic network, mixed-integer linear programming, multiple optimal solutions

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30609 Prediction Factor of Recurrence Supraventricular Tachycardia After Adenosine Treatment in the Emergency Department

Authors: Chaiyaporn Yuksen

Abstract:

Backgroud: Supraventricular tachycardia (SVT) is an abnormally fast atrial tachycardia characterized by narrow (≤ 120 ms) and constant QRS. Adenosine was the drug of choice; the first dose was 6 mg. It can be repeated with the second and third doses of 12 mg, with greater than 90% success. The study found that patients observed at 4 hours after normal sinus rhythm was no recurrence within 24 hours. The objective of this study was to investigate the factors that influence the recurrence of SVT after adenosine in the emergency department (ED). Method: The study was conducted retrospectively exploratory model, prognostic study at the Emergency Department (ED) in Faculty of Medicine, Ramathibodi Hospital, a university-affiliated super tertiary care hospital in Bangkok, Thailand. The study was conducted for ten years period between 2010 and 2020. The inclusion criteria were age > 15 years, visiting the ED with SVT, and treating with adenosine. Those patients were recorded with the recurrence SVT in ED. The multivariable logistic regression model developed the predictive model and prediction score for recurrence PSVT. Result: 264 patients met the study criteria. Of those, 24 patients (10%) had recurrence PSVT. Five independent factors were predictive of recurrence PSVT. There was age>65 years, heart rate (after adenosine) > 100 per min, structural heart disease, and dose of adenosine. The clinical risk score to predict recurrence PSVT is developed accuracy 74.41%. The score of >6 had the likelihood ratio of recurrence PSVT by 5.71 times Conclusion: The clinical predictive score of > 6 was associated with recurrence PSVT in ED.

Keywords: clinical prediction score, SVT, recurrence, emergency department

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30608 Optimization of Effecting Parameters for the Removal of H₂S Gas in Self Priming Venturi Scrubber Using Response Surface Methodology

Authors: Manisha Bal, B. C. Meikap

Abstract:

Highly toxic and corrosive gas H₂S is recognized as one of the hazardous air pollutants which has significant effect on the human health. Abatement of H₂S gas from the air is very necessary. H₂S gas is mainly released from the industries like paper and leather industry as well as during the production of crude oil, during wastewater treatment, etc. But the emission of H₂S gas in high concentration may cause immediate death while at lower concentrations can cause various respiratory problems. In the present study, self priming venturi scrubber is used to remove the H₂S gas from the air. Response surface methodology with central composite design has been chosen to observe the effect of process parameters on the removal efficiency of H₂S. Experiments were conducted by varying the throat gas velocity, liquid level in outer cylinder, and inlet H₂S concentration. ANOVA test confirmed the significant effect of parameters on the removal efficiency. A quadratic equation has been obtained which predicts the removal efficiency very well. The suitability of the developed model has been judged by the higher R² square value which obtained from the regression analysis. From the investigation, it was found that the throat gas velocity has most significant effect and inlet concentration of H₂S has less effect on H₂S removal efficiency.

Keywords: desulfurization, pollution control, response surface methodology, venturi scrubber

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30607 Time-Dependent Reliability Analysis of Corrosion Affected Cast Iron Pipes with Mixed Mode Fracture

Authors: Chun-Qing Li, Guoyang Fu, Wei Yang

Abstract:

A significant portion of current water networks is made of cast iron pipes. Due to aging and deterioration with corrosion being the most predominant mechanism, the failure rate of cast iron pipes is very high. Although considerable research has been carried out in the past few decades, most are on the effect of corrosion on the structural capacity of pipes using strength theory as the failure criterion. This paper presents a reliability-based methodology for the assessment of corrosion affected cast iron pipe cracking failures. A nonlinear limit state function taking into account all three fracture modes is proposed for brittle metal pipes with mixed mode fracture. A stochastic model of the load effect is developed, and time-dependent reliability method is employed to quantify the probability of failure and predict the remaining service life. A case study is carried out using the proposed methodology, followed by sensitivity analysis to investigate the effects of the random variables on the probability of failure. It has been found that the larger the inclination angle or the Mode I fracture toughness is, the smaller the probability of pipe failure is. It has also been found that the multiplying and exponential coefficients k and n in the power law corrosion model and the internal pressure have the most influence on the probability of failure for cast iron pipes. The methodology presented in this paper can assist pipe engineers and asset managers in developing a risk-informed and cost-effective strategy for better management of corrosion-affected pipelines.

Keywords: corrosion, inclined surface cracks, pressurized cast iron pipes, stress intensity

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30606 The Effect of Second Victim-Related Distress on Work-Related Outcomes in Tertiary Care, Kelantan, Malaysia

Authors: Ahmad Zulfahmi Mohd Kamaruzaman, Mohd Ismail Ibrahim, Ariffin Marzuki Mokhtar, Maizun Mohd Zain, Saiful Nazri Satiman, Mohd Najib Majdi Yaacob

Abstract:

Background: Aftermath any patient safety incidents, the involved healthcare providers possibly sustained second victim-related distress (second victim distress and reduced their professional efficacy), with subsequent negative work-related outcomes or vice versa cultivating resilience. This study aimed to investigate the factors affecting negative work-related outcomes and resilience, with the triad of support; colleague, supervisor, and institutional support as the hypothetical mediators. Methods: This was a cross sectional study recruiting a total of 733 healthcare providers from three tertiary care in Kelantan, Malaysia. Three steps of hierarchical linear regression were developed for each outcome; negative work-related outcomes and resilience. Then, four multiple mediator models of support triad were analyzed. Results: Second victim distress, professional efficacy, and the support triad contributed significantly for each regression model. In the pathway of professional efficacy on each negative work-related outcomes and resilience, colleague support partially mediated the relationship. As for second victim distress on negative work related outcomes, colleague and supervisor support were the partial mediator, and on resilience; all support triad also produced a similar effect. Conclusion: Second victim distress, professional efficacy, and the support triad influenced the relationship with the negative work-related outcomes and resilience. Support triad as the mediators ameliorated the effect in between and explained the urgency of having good support for recovery post encountering patient safety incidents.

Keywords: second victims, patient safety incidents, hierarchical linear regression, mediation, support

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30605 Hydrothermal Synthesis of ZIF-7 Crystals and Their Composite ZIF-7/CS Membranes for Water/Ethanol Separation

Authors: Kai-Sheng Ji, Yi-Feng Lin

Abstract:

The pervaporation process for solvent and water separation has attracted research attention due to its lower energy consumption compared with conventional distillation processes. The membranes used for the pervaporation approach should exhibit high flux and separation factors. In this study, the ZIF-7 crystal particles were successfully incorporated into chitosan (CS) membranes to form ZIF-7/CS mixed-matrix membranes. The as-prepared ZIF-7/CS mixed-matrix membranes were used to separate mixtures of water/ethanol at 25℃ in the pervaporation process. The mixed-matrix membranes with different ZIF-7 wt% incorporation showed better separation efficiency than the pristine CS membranes because of the smaller pore size of the mixed-matrix membranes. The separation factor and the flux of the ZIF-7/CS membranes clearly exceed the upper limit of the previously reported CS-based and mixed-matrix membranes.

Keywords: pervaporation, chitosan, ZIF-7, memberane separation

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30604 Count Data Regression Modeling: An Application to Spontaneous Abortion in India

Authors: Prashant Verma, Prafulla K. Swain, K. K. Singh, Mukti Khetan

Abstract:

Objective: In India, around 20,000 women die every year due to abortion-related complications. In the modelling of count variables, there is sometimes a preponderance of zero counts. This article concerns the estimation of various count regression models to predict the average number of spontaneous abortion among women in the Punjab state of India. It also assesses the factors associated with the number of spontaneous abortions. Materials and methods: The study included 27,173 married women of Punjab obtained from the DLHS-4 survey (2012-13). Poisson regression (PR), Negative binomial (NB) regression, zero hurdle negative binomial (ZHNB), and zero-inflated negative binomial (ZINB) models were employed to predict the average number of spontaneous abortions and to identify the determinants affecting the number of spontaneous abortions. Results: Statistical comparisons among four estimation methods revealed that the ZINB model provides the best prediction for the number of spontaneous abortions. Antenatal care (ANC) place, place of residence, total children born to a woman, woman's education and economic status were found to be the most significant factors affecting the occurrence of spontaneous abortion. Conclusions: The study offers a practical demonstration of techniques designed to handle count variables. Statistical comparisons among four estimation models revealed that the ZINB model provided the best prediction for the number of spontaneous abortions and is recommended to be used to predict the number of spontaneous abortions. The study suggests that women receive institutional Antenatal care to attain limited parity. It also advocates promoting higher education among women in Punjab, India.

Keywords: count data, spontaneous abortion, Poisson model, negative binomial model, zero hurdle negative binomial, zero-inflated negative binomial, regression

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30603 Prevalence of Cerebral Microbleeds in Apparently Healthy, Elderly Population: A Meta-Analysis

Authors: Vidishaa Jali, Amit Sinha, Kameshwar Prasad

Abstract:

Background and Objective: Cerebral microbleeds are frequently found in healthy elderly individuals. We performed a meta- analysis to determine the prevalence of cerebral microbleeds in apparently healthy, elderly population and to determine the effect of age, smoking and hypertension on the occurrence of cerebral microbleeds. Methods: Relevant literature was searched using electronic databases such as MEDLINE, EMBASE, PubMed, Cochrane database, Google scholar to identify studies on the prevalence of cerebral microbleeds in general elderly population till March 2016. STATA version 13 software was used for analysis. Fixed effect model was used if heterogeneity was less than 50%. Otherwise, random effect model was used. Meta- regression analysis was performed to check any effect of important variables such as age, smoking, hypertension. Selection Criteria: We included cross-sectional studies performed in apparently healthy elderly population, who had age more than 50 years. Results: The pooled proportion of cerebral microbleeds in healthy population is 12% (95% CI, 0.11 to 0.13). No significant effect of age was found on the prevalence of cerebral microbleeds (p= 0.99). A linear relationship between increase in hypertension and the prevalence of cerebral microbleeds was found, however, this linear relationship was not statistically significant (p=0.16). Similarly, A linear relationship between increase in smoking and the prevalence of cerebral microbleeds was found, however, this linear relationship was also not statistically significant (p=0.21). Conclusion: Presence of cerebral microbleeds is evident in apparently healthy, elderly population, in more than 10% of individuals.

Keywords: apparently healthy, elderly, prevalence, cerebral microbleeds

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30602 Study of the ZnO Effect on the Properties of HDPE/ ZnO Nanocomposites

Authors: F. Z. Benabid, F. Zouai, N. Kharchi, D. Benachour

Abstract:

A HDPE/ZnO nano composites have been successfully performed using the co-mixing. The ZnO was first co-mixed with the stearic acid then added to the polymer in the plastograph. The nano composites prepared with the co-mixed ZnO were compared to those prepared with the neat TiO2. The nano composites were characterized by different techniques as the wide-angle X-ray scattering (WAXS). The micro and nano structure/properties relationships were investigated. The present study allowed establishing good correlations between the different measured properties.

Keywords: exfoliation, ZnO, nano composites, HDPE, co-mixing

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30601 Analysis of Ferroresonant Overvoltages in Cable-fed Transformers

Authors: George Eduful, Ebenezer A. Jackson, Kingsford A. Atanga

Abstract:

This paper investigates the impacts of cable length and capacity of transformer on ferroresonant overvoltage in cable-fed transformers. The study was conducted by simulation using the EMTP RV. Results show that ferroresonance can cause dangerous overvoltages ranging from 2 to 5 per unit. These overvoltages impose stress on insulations of transformers and cables and subsequently result in system failures. Undertaking Basic Multiple Regression Analysis (BMR) on the results obtained, a statistical model was obtained in terms of cable length and transformer capacity. The model is useful for ferroresonant prediction and control in cable-fed transformers.

Keywords: ferroresonance, cable-fed transformers, EMTP RV, regression analysis

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30600 Single Species vs Mixed Microbial Culture Degradation of Pesticide in a Membrane Bioreactor

Authors: Karan R. Chavan, Srivats Gopalan, Kumudini V. Marathe

Abstract:

In the current work, the comparison of degradation of malathion by single species, Pseudomonas Stutzeri, and Activated Sludge/Mixed Microbial Culture is studied in a Membrane Bioreactor. Various parameters were considered to study the effect of single species degradation compared to degradation by activated sludge. The experimental results revealed 85-90% reduction in the COD of the Malathion containing synthetic wastewater. Complete reduction of malathion was observed within 24 hours in both the cases. The critical flux was 10 LMH for both the systems. Fouling propensity, Cake and Membrane resistances were calculated thus giving an insight regarding the working of Membrane Bioreactor-based on single species and activated sludge.

Keywords: fouling, membrane bioreactor, mixed microbial culture, single species

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30599 Detection Efficient Enterprises via Data Envelopment Analysis

Authors: S. Turkan

Abstract:

In this paper, the Turkey’s Top 500 Industrial Enterprises data in 2014 were analyzed by data envelopment analysis. Data envelopment analysis is used to detect efficient decision-making units such as universities, hospitals, schools etc. by using inputs and outputs. The decision-making units in this study are enterprises. To detect efficient enterprises, some financial ratios are determined as inputs and outputs. For this reason, financial indicators related to productivity of enterprises are considered. The efficient foreign weighted owned capital enterprises are detected via super efficiency model. According to the results, it is said that Mercedes-Benz is the most efficient foreign weighted owned capital enterprise in Turkey.

Keywords: data envelopment analysis, super efficiency, logistic regression, financial ratios

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30598 Regression Analysis in Estimating Stream-Flow and the Effect of Hierarchical Clustering Analysis: A Case Study in Euphrates-Tigris Basin

Authors: Goksel Ezgi Guzey, Bihrat Onoz

Abstract:

The scarcity of streamflow gauging stations and the increasing effects of global warming cause designing water management systems to be very difficult. This study is a significant contribution to assessing regional regression models for estimating streamflow. In this study, simulated meteorological data was related to the observed streamflow data from 1971 to 2020 for 33 stream gauging stations of the Euphrates-Tigris Basin. Ordinary least squares regression was used to predict flow for 2020-2100 with the simulated meteorological data. CORDEX- EURO and CORDEX-MENA domains were used with 0.11 and 0.22 grids, respectively, to estimate climate conditions under certain climate scenarios. Twelve meteorological variables simulated by two regional climate models, RCA4 and RegCM4, were used as independent variables in the ordinary least squares regression, where the observed streamflow was the dependent variable. The variability of streamflow was then calculated with 5-6 meteorological variables and watershed characteristics such as area and height prior to the application. Of the regression analysis of 31 stream gauging stations' data, the stations were subjected to a clustering analysis, which grouped the stations in two clusters in terms of their hydrometeorological properties. Two streamflow equations were found for the two clusters of stream gauging stations for every domain and every regional climate model, which increased the efficiency of streamflow estimation by a range of 10-15% for all the models. This study underlines the importance of homogeneity of a region in estimating streamflow not only in terms of the geographical location but also in terms of the meteorological characteristics of that region.

Keywords: hydrology, streamflow estimation, climate change, hydrologic modeling, HBV, hydropower

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30597 The Impact of Unconditional and Conditional Conservatism on Cost of Equity Capital: A Quantile Regression Approach for MENA Countries

Authors: Khalifa Maha, Ben Othman Hakim, Khaled Hussainey

Abstract:

Prior empirical studies have investigated the economic consequences of accounting conservatism by examining its impact on the cost of equity capital (COEC). However, findings are not conclusive. We assume that inconsistent results of such association may be attributed to the regression models used in data analysis. To address this issue, we re-examine the effect of different dimension of accounting conservatism: unconditional conservatism (U_CONS) and conditional conservatism (C_CONS) on the COEC for a sample of listed firms from Middle Eastern and North Africa (MENA) countries, applying quantile regression (QR) approach developed by Koenker and Basset (1978). While classical ordinary least square (OLS) method is widely used in empirical accounting research, however it may produce inefficient and bias estimates in the case of departures from normality or long tail error distribution. QR method is more powerful than OLS to handle this kind of problem. It allows the coefficient on the independent variables to shift across the distribution of the dependent variable whereas OLS method only estimates the conditional mean effects of a response variable. We find as predicted that U_CONS has a significant positive effect on the COEC however, C_CONS has a negative impact. Findings suggest also that the effect of the two dimensions of accounting conservatism differs considerably across COEC quantiles. Comparing results from QR method with those of OLS, this study throws more lights on the association between accounting conservatism and COEC.

Keywords: unconditional conservatism, conditional conservatism, cost of equity capital, OLS, quantile regression, emerging markets, MENA countries

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30596 Cybernetic Modeling of Growth Dynamics of Debaryomyces nepalensis NCYC 3413 and Xylitol Production in Batch Reactor

Authors: J. Sharon Mano Pappu, Sathyanarayana N. Gummadi

Abstract:

Growth of Debaryomyces nepalensis on mixed substrates in batch culture follows diauxic pattern of completely utilizing glucose during the first exponential growth phase, followed by an intermediate lag phase and a second exponential growth phase consuming xylose. The present study deals with the development of cybernetic mathematical model for prediction of xylitol production and yield. Production of xylitol from xylose in batch fermentation is investigated in the presence of glucose as the co-substrate. Different ratios of glucose and xylose concentrations are assessed to study the impact of multi substrate on production of xylitol in batch reactors. The parameters in the model equations were estimated from experimental observations using integral method. The model equations were solved simultaneously by numerical technique using MATLAB. The developed cybernetic model of xylose fermentation in the presence of a co-substrate can provide answers about how the ratio of glucose to xylose influences the yield and rate of production of xylitol. This model is expected to accurately predict the growth of microorganism on mixed substrate, duration of intermediate lag phase, consumption of substrate, production of xylitol. The model developed based on cybernetic modelling framework can be helpful to simulate the dynamic competition between the metabolic pathways.

Keywords: co-substrate, cybernetic model, diauxic growth, xylose, xylitol

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30595 Analysis of Factors Affecting the Number of Infant and Maternal Mortality in East Java with Geographically Weighted Bivariate Generalized Poisson Regression Method

Authors: Luh Eka Suryani, Purhadi

Abstract:

Poisson regression is a non-linear regression model with response variable in the form of count data that follows Poisson distribution. Modeling for a pair of count data that show high correlation can be analyzed by Poisson Bivariate Regression. Data, the number of infant mortality and maternal mortality, are count data that can be analyzed by Poisson Bivariate Regression. The Poisson regression assumption is an equidispersion where the mean and variance values are equal. However, the actual count data has a variance value which can be greater or less than the mean value (overdispersion and underdispersion). Violations of this assumption can be overcome by applying Generalized Poisson Regression. Characteristics of each regency can affect the number of cases occurred. This issue can be overcome by spatial analysis called geographically weighted regression. This study analyzes the number of infant mortality and maternal mortality based on conditions in East Java in 2016 using Geographically Weighted Bivariate Generalized Poisson Regression (GWBGPR) method. Modeling is done with adaptive bisquare Kernel weighting which produces 3 regency groups based on infant mortality rate and 5 regency groups based on maternal mortality rate. Variables that significantly influence the number of infant and maternal mortality are the percentages of pregnant women visit health workers at least 4 times during pregnancy, pregnant women get Fe3 tablets, obstetric complication handled, clean household and healthy behavior, and married women with the first marriage age under 18 years.

Keywords: adaptive bisquare kernel, GWBGPR, infant mortality, maternal mortality, overdispersion

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30594 Effect of Different Model Drugs on the Properties of Model Membranes from Fishes

Authors: M. Kumpugdee-Vollrath, T. G. D. Phu, M. Helmis

Abstract:

A suitable model membrane to study the pharmacological effect of pharmaceutical products is human stratum corneum because this layer of human skin is the outermost layer and it is an important barrier to be passed through. Other model membranes which were also used are for example skins from pig, mouse, reptile or fish. We are interested in fish skins in this project. The advantages of the fish skins are, that they can be obtained from the supermarket or fish shop. However, the fish skins should be freshly prepared and used directly without storage. In order to understand the effect of different model drugs e.g. lidocaine HCl, resveratrol, paracetamol, ibuprofen, acetyl salicylic acid on the properties of the model membrane from various types of fishes e.g. trout, salmon, cod, plaice permeation tests were performed and differential scanning calorimetry was applied.

Keywords: fish skin, model membrane, permeation, DSC, lidocaine HCl, resveratrol, paracetamol, ibuprofen, acetyl salicylic acid

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30593 The Growth Curve of Gompertz Model in Body Weight of Slovak Mixed-Sex Goose Breeds

Authors: Cyril Hrncar, Jozef Bujko, Widya P. B. Putra

Abstract:

The growth curve of poultry is important to evaluate the farming management system. This study was aimed to estimate the growth curve of body weight in goose. The growth curve in this study was estimated with non-linear Gompertz model through CurveExpert 1.4. software. Three Slovak mixed-sex goose breeds of Landes (L), Pomeranian (P) and Steinbacher (S) were used in this study. Total of 28 geese (10 L, 8 P and 10 S) were used to estimate the growth curve. Research showed that the asymptotic weight (A) in those geese were reached of 5332.51 g (L), 6186.14 g (P) and 5048.27 g (S). Thus, the maturing rate (k) in each breed were similar (0.05 g/day). The weight of inflection was reached of 1960.48 g (L), 2274.32 g (P) and 1855.98 g (S). The time of inflection (ti) was reached of 25.6 days (L), 26.2 days (P) and 27.80 days (S). The maximum growth rate (MGR) was reached of 98.02 g/day (L), 113.72 g/day (P) and 92.80 g/day (S). Hence, the coefficient of determination (R2) in Gompertz model was 0.99 for each breed. It can be concluded that Pomeranian geese had highest of growth trait than the other breeds.

Keywords: body weight, growth curve, inflection, Slovak geese, Gompertz model

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30592 Generalized Correlation Coefficient in Genome-Wide Association Analysis of Cognitive Ability in Twins

Authors: Afsaneh Mohammadnejad, Marianne Nygaard, Jan Baumbach, Shuxia Li, Weilong Li, Jesper Lund, Jacob v. B. Hjelmborg, Lene Christensen, Qihua Tan

Abstract:

Cognitive impairment in the elderly is a key issue affecting the quality of life. Despite a strong genetic background in cognition, only a limited number of single nucleotide polymorphisms (SNPs) have been found. These explain a small proportion of the genetic component of cognitive function, thus leaving a large proportion unaccounted for. We hypothesize that one reason for this missing heritability is the misspecified modeling in data analysis concerning phenotype distribution as well as the relationship between SNP dosage and the phenotype of interest. In an attempt to overcome these issues, we introduced a model-free method based on the generalized correlation coefficient (GCC) in a genome-wide association study (GWAS) of cognitive function in twin samples and compared its performance with two popular linear regression models. The GCC-based GWAS identified two genome-wide significant (P-value < 5e-8) SNPs; rs2904650 near ZDHHC2 on chromosome 8 and rs111256489 near CD6 on chromosome 11. The kinship model also detected two genome-wide significant SNPs, rs112169253 on chromosome 4 and rs17417920 on chromosome 7, whereas no genome-wide significant SNPs were found by the linear mixed model (LME). Compared to the linear models, more meaningful biological pathways like GABA receptor activation, ion channel transport, neuroactive ligand-receptor interaction, and the renin-angiotensin system were found to be enriched by SNPs from GCC. The GCC model outperformed the linear regression models by identifying more genome-wide significant genetic variants and more meaningful biological pathways related to cognitive function. Moreover, GCC-based GWAS was robust in handling genetically related twin samples, which is an important feature in handling genetic confounding in association studies.

Keywords: cognition, generalized correlation coefficient, GWAS, twins

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30591 River Catchment’s Demography and the Dynamics of Access to Clean Water in the Rural South Africa

Authors: Yiseyon Sunday Hosu, Motebang Dominic Vincent Nakin, Elphina N. Cishe

Abstract:

Universal access to clean and safe drinking water and basic sanitation is one of the targets of the 6th Sustainable Development Goals (SDGs). This paper explores the evidence-based indicators of Water Rights Acts (2013) among households in the rural communities in the Mthatha River catchment of OR Tambo District Municipality of South Africa. Daily access to minimum 25 litres/person and the factors influencing clean water access were investigated in the catchment. A total number of 420 households were surveyed in the upper, peri-urban, lower and coastal regions of Mthatha Rivier catchment. Descriptive and logistic regression analyses were conducted on the data collected from the households to elicit vital information on domestic water security among rural community dwellers. The results show that approximately 68 percent of total households surveyed have access to the required minimum 25 litre/person/day, with 66.3 percent in upper region, 76 per cent in the peri-urban, 1.1 percent in the lower and 2.3 percent in the coastal regions. Only 30 percent among the total surveyed households had access to piped water either in the house or public taps. The logistic regression showed that access to clean water was influenced by lack of water infrastructure, proximity to urban regions, daily flow of pipe-borne water, household size and distance to public taps. This paper recommends that viable integrated rural community-based water infrastructure provision strategies between NGOs and local authority and the promotion of point of use (POU) technologies to enhance better access to clean water.

Keywords: domestic water, household technology, water security, rural community

Procedia PDF Downloads 329
30590 Competitiveness of African Countries through Open Quintuple Helix Model

Authors: B. G. C. Ahodode, S. Fekkaklouhail

Abstract:

Following the triple helix theory, this study aims to evaluate the innovation system effect on African countries’ competitiveness by taking into account external contributions; according to the extent that developing countries (especially African countries) are characterized by weak innovation systems whose synergy operates more at the foreign level than domestic and global. To do this, we used the correlation test, parsimonious regression techniques, and panel estimation between 2013 and 2016. Results show that the degree of innovation synergy has a significant effect on competitiveness in Africa. Specifically, while the opening system (OPESYS) and social system (SOCSYS) contribute respectively in importance order to 0.634 and 0.284 (at 1%) significant points of increase in the GCI, the political system (POLSYS) and educational system (EDUSYS) only increase it to 0.322 and 0.169 at 5% significance level while the effect of the economic system (ECOSYS) is not significant on Global Competitiveness Index.

Keywords: innovation system, innovation, competitiveness, Africa

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30589 Sustainability of Green Supply Chain for a Steel Industry Using Mixed Linear Programing Model

Authors: Ameen Alawneh

Abstract:

The cost of material management across the supply chain represents a major contributor to the overall cost of goods in many companies both manufacturing and service sectors. This fact combined with the fierce competition make supply chains more efficient and cost effective. It also requires the companies to improve the quality of the products and services, increase the effectiveness of supply chain operations, focus on customer needs, reduce wastes and costs across the supply chain. As a heavy industry, steel manufacturing companies in particular are nowadays required to be more environmentally conscious due to their contribution to air, soil, and water pollution that results from emissions and wastes across their supply chains. Steel companies are increasingly looking for methods to reduce or cost cut in the operations and provide extra value to their customers to stay competitive under the current low margins. In this research we develop a green framework model for the sustainability of a steel company supply chain using Mixed integer Linear programming.

Keywords: Supply chain, Mixed Integer linear programming, heavy industry, water pollution

Procedia PDF Downloads 424