Search results for: regression rate variations

Authors: V. C. Igwemezie, A. N. Mehmanparast

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The primary focus of this work is to understand how variations in the microstructure and cyclic waveform affect the corrosion fatigue crack growth (CFCG) in steel, especially in the Paris region of the da/dN vs. ΔK curve. This work is important because it provides fundamental information on the modelling, design, selection, and use of steels for various engineering applications in the marine environment. The corrosion fatigue tests data on normalized and thermomechanical control process (TMCP) ferritic-pearlitic steels by the authors were compared with several studies on different microstructures in the literature. The microstructures of these steels are radically different and general comparative fatigue crack growth resistance performance study on the effect of microstructure in these materials are very scarce and where available are limited to few studies. The results, for purposes of engineering application, in this study show less dependency of fatigue crack growth rate (FCGR) on yield strength, tensile strength, ductility, frequency and stress ratio in the range 0.1 – 0.7. The nature of the steel microstructure appears to be a major factor in determining the rate at which fatigue cracks propagate in the entire da/dN vs. ΔK sigmoidal curve. The study also shows that the sine wave shape is the most damaging fatigue waveform for ferritic-pearlitic steels. This tends to suggest that the test under sine waveform would be a conservative approach, regardless of the waveform for design of engineering structures.

Keywords: BS7910, corrosion-fatigue crack growth rate, cyclic waveform, microstructure, steel

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Authors: Chananart Meenanan

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The composition Isan Symphonic Variations for Chorus and Orchestra is a musical composition inspired by Isan Folk music tunes. The composer has created the well crafted melodic variations and cultural sound character of the piece based on the Klon Lum Tang Isan Keaw (Green Isan’s short poems). Meanwhile, the poetic lyric has been motivatedly recreated to bring the abundance of Northeastern Thailand region’s sentiment back to life. Moreover, the sound of xylophone (Ponglang), the instruments of the orchestra and the chorus were blended in order to present Isan folk music’s character via the Western musical idiom. The 3 movement of this composition is divided as following: In Movement I (Allegro), the introduction has been represented the uniqueness in Isan folk music’s liveliness by expressing it through the sound of chorus and orchestra. The composer also added the melodious sound flavor by utilizing the variety of the muting sound style on trumpets and horns. In Movement II (Moderato), the aspect of the heterophonic approach music has been implied to the main idea of the entire movement whereby its formatted transformation worked effectively through chorus and the orchestra. In Movement III (Allegretto) the harmonic chromaticism was modified and applied as the symbolic icon of the entire movement. The transparence of Isan cultural sound was perfectly designed to be the highlight of this spectacular episode.

Keywords: Isan, symphonic variations, chorus, orchestra

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Authors: Jung Hyun Kim, Gyo Woo Lee

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In this study, heat release performances of the three extruded-type heat sinks can be used in the inverter for solar power generation were evaluated. Numbers of fins in the heat sinks (namely E-38, E-47 and E-76) were 38, 47 and 76, respectively. Heat transfer areas of them were 1.8, 1.9 and 2.8 m2. The heat release performances of E-38, E-47, and E-76 heat sinks were measured as 79.6, 81.6, and 83.2%, respectively. The results of heat release performance show that the larger amount of heat transfer area the higher heat release rate. While on the other, in this experiment, variations of the mass flow rates caused by different cross-sectional areas of the three heat sinks may not be the major parameter of the heat release. Despite the 47.4% increment of heat transfer area of E-76 heat sink than that of E-47 one, its heat release rate was higher by only 2.0%; this suggests that its heat transfer area need to be optimized.

Keywords: solar Inverter, heat sink, forced convection, heat transfer, performance evaluation

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Authors: Ekele Alih, Enejo Jalija

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Female Genital Mutilation (FGM) is made up of three types namely: Clitoridectomy, Excision and Infibulation. In this study, we examine the factors responsible for FGM in order to identify the causality variables in a logistic regression approach. From the result of the survey conducted by the Public Health Division, Nigeria Institute of Medical Research, Yaba, Lagos State, the tau statistic, τ was used to screen 9 factors that causes FGM in order to select few of the predictors before multiple regression equation is obtained. The need for this may be that the sample size may not be able to sustain having a regression with all the predictors or to avoid multi-collinearity. A total of 300 respondents, comprising 150 adult males and 150 adult females were selected for the household survey based on the multi-stage sampling procedure. The tau statistic,

Keywords: female genital mutilation, logistic regression, tau statistic, African society

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Authors: Georgios Charizanos, Haydar Demirhan, Duygu Icen

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Two of the most impactful issues in classical logistic regression are class imbalance and complete separation. These can result in model predictions heavily leaning towards the imbalanced class on the binary response variable or over-fitting issues. Fuzzy methodology offers key solutions for handling these problems. However, most studies propose the transformation of the binary responses into a continuous format limited within [0,1]. This is called the possibilistic approach within fuzzy logistic regression. Following this approach is more aligned with straightforward regression since a logit-link function is not utilized, and fuzzy probabilities are not generated. In contrast, we propose a method of fuzzifying binary response variables that allows for the use of the logit-link function; hence, a probabilistic fuzzy logistic regression model with the Monte Carlo method. The fuzzy probabilities are then classified by selecting a fuzzy threshold. Different combinations of fuzzy and crisp input, output, and coefficients are explored, aiming to understand which of these perform better under different conditions of imbalance and separation. We conduct numerical experiments using both synthetic and real datasets to demonstrate the performance of the fuzzy logistic regression framework against seven crisp machine learning methods. The proposed framework shows better performance irrespective of the degree of imbalance and presence of separation in the data, while the considered machine learning methods are significantly impacted.

Keywords: fuzzy logistic regression, fuzzy, logistic, machine learning

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Authors: Hui-Yen Lee, Hsiu-Yun Wei, Guey-Jen Lin, Pi-Yueh Lee Lee

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Background: Unplanned hospital readmissions increase healthcare costs and have been considered a marker of poor healthcare performance. The elderly face a higher risk of unplanned readmission due to elderly-specific characteristics such as deteriorating body functions and the relatively high incidence of complications after treatment of acute diseases. Purpose: The aim of this study was exploring the factors that relate to the unplanned readmission of elderly within 14 days of discharge at our hospital in southern Taiwan. Methods: We retrospectively reviewed the medical records of patients aged ≥65 years who had been re-admitted between January 2018 and December 2018.The Charlson Comorbidity score was calculated using previous used method. Related factors that affected the rate of unplanned readmission within 14 days of discharge were screened and analyzed using the chi-squared test and logistic regression analysis. Results: This study enrolled 829 subjects aged more than 65 years. The numbers of unplanned readmission patients within 14 days were 318 cases, while those did not belong to the unplanned readmission were 511 cases. In 2018, the rate of elderly patients in unplanned 14 days readmissions was 38.4%. The majority patients were females (166 cases, 52.2%), with an average age of 77.6 ± 7.90 years (65-98). The average value of Charlson Comorbidity score was 4.42±2.76. Using logistic regression analysis, we found that the gastric or peptic ulcer (OR=1.917 , P< 0.002), diabetes (OR= 0.722, P< 0.043), hemiplegia (OR= 2.292, P< 0.015), metastatic solid tumor (OR= 2.204, P< 0.025), hypertension (OR= 0.696, P< 0.044), and skin ulcer/cellulitis (OR= 2.747, P< 0.022) have significantly higher risk of 14-day readmissions. Conclusion: The results of the present study may assist the healthcare teams to understand the factors that may affect unplanned readmission in the elderly. We recommend that these teams give efficient approach in their medical practice, provide timely health education for elderly, and integrative healthcare for chronic diseases in order to reduce unplanned readmissions.

Keywords: unplanning readmission, elderly, Charlson comorbidity score, logistic regression analysis

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Authors: Shokrya Saleh A. Alshqaq, Abdullah Ali H. Ahmadini

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The Schwarz information criterion (SIC) is a popular tool for selecting the best variables in regression datasets. However, SIC is defined using an unbounded estimator, namely, the least-squares (LS), which is highly sensitive to outlying observations, especially bad leverage points. A method for robust variable selection based on SIC for linear regression models is thus needed. This study investigates the robustness properties of SIC by deriving its influence function and proposes a robust SIC based on the MM-estimation scale. The aim of this study is to produce a criterion that can effectively select accurate models in the presence of vertical outliers and high leverage points. The advantages of the proposed robust SIC is demonstrated through a simulation study and an analysis of a real dataset.

Keywords: influence function, robust variable selection, robust regression, Schwarz information criterion

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Authors: Jossitt Williams Vargas Cruz, Aura Jazmín Pérez Ríos

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The variations of solar dynamics have become a relevant topic of study due to the effects of climate changes generated on the earth. One of the most disconcerting aspects is the variability that the sun has on the climate is the role played by sunspots (extra-atmospheric variable) in the modulation of the Cosmic Rays CR (extra-atmospheric variable). CRs influence the earth's climate by affecting cloud formation (atmospheric variable), and solar cycle influence is associated with the presence of solar storms, and the magnetic activity is greater, resulting in less CR entering the earth's atmosphere. The different methods of climate prediction in Colombia do not take into account the extra-atmospheric variables. Therefore, correlations between atmospheric and extra-atmospheric variables were studied in order to implement a Python code based on neural networks to make the prediction of the extra-atmospheric variable with the highest correlation.

Keywords: correlations, cosmic rays, sun, sunspots and variations.

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Authors: Tahmidul Islam

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Propensity Score Matching (PSM) technique has been widely used for estimating causal effect of treatment in observational studies. One major step of implementing PSM is estimating the propensity score (PS). Logistic regression model with additive linear terms of covariates is most used technique in many studies. Logistics regression model is also used with cubic splines for retaining flexibility in the model. However, choosing the functional form of the logistic regression model has been a question since the effectiveness of PSM depends on how accurately the PS been estimated. In many situations, the linearity assumption of linear logistic regression may not hold and non-linear relation between the logit and the covariates may be appropriate. One can estimate PS using machine learning techniques such as random forest, neural network etc for more accuracy in non-linear situation. In this study, an attempt has been made to compare the efficacy of Generalized Additive Model (GAM) in various linear and non-linear settings and compare its performance with usual logistic regression. GAM is a non-parametric technique where functional form of the covariates can be unspecified and a flexible regression model can be fitted. In this study various simple and complex models have been considered for treatment under several situations (small/large sample, low/high number of treatment units) and examined which method leads to more covariate balance in the matched dataset. It is found that logistic regression model is impressively robust against inclusion quadratic and interaction terms and reduces mean difference in treatment and control set equally efficiently as GAM does. GAM provided no significantly better covariate balance than logistic regression in both simple and complex models. The analysis also suggests that larger proportion of controls than treatment units leads to better balance for both of the methods.

Keywords: accuracy, covariate balances, generalized additive model, logistic regression, non-linearity, propensity score matching

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Authors: Anna M. N. Shifotoka, Richard Walker, Katie Haighton, Richard McNally

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An analysis of trends in Case Notification Rates (CNR) can be used to monitor the impact of Tuberculosis (TB) control interventions over time in order to inform the implementation of current and future TB interventions. A retrospective analysis of trends in TB CNR for two urban regions in Namibia, namely Khomas and Erongo regions, was conducted. TB case notification data were obtained from annual TB reports of the national TB programme, Ministry of Health and Social Services, covering the period from 1997 to 2015. Joinpoint regression was used to analyse trends in CNR for different types of TB groups. A trend was considered to be statistically significant when a p-value was less than 0.05. During the period under review, the crude CNR for all forms of TB declined from 808 to 400 per 100 000 population in Khomas, and from 1051 to 611 per 100 000 population in Erongo. In both regions, significant change points in trends were observed for all types of TB groups examined. In Khomas region, the trend for new smear positive pulmonary TB increased significantly by an annual rate of 4.1% (95% Confidence Interval (CI): 0.3% to 8.2%) during the period 1997 to 2004, and thereafter declined significantly by -6.2% (95%CI: -7.7% to -4.3%) per year until 2015. Similarly, the trend for smear negative pulmonary TB increased significantly by 23.7% (95%CI: 9.7 to 39.5) per year from 1997 to 2004 and thereafter declined significantly by an annual change of -26.4% (95%CI: -33.1% to -19.8%). The trend for all forms of TB CNR in Khomas region increased significantly by 8.1% (95%CI: 3.7 to 12.7) per year from 1997 to 2004 and thereafter declined significantly a rate of -8.7% (95%CI: -10.6 to -6.8). In Erongo region, the trend for smear positive pulmonary TB increased at a rate of 1.2% (95%CI: -1.2% to 3.6%) annually during the earlier years (1997 to 2008), and thereafter declined significantly by -9.3% (95%CI: -13.3% to -5.0%) per year from 2008 to 2015. Also in Erongo, the trend for all forms of TB CNR increased significantly by an annual rate of 4.0% (95%CI: 1.4% to 6.6%) during the years between 1997 to 2006 and thereafter declined significantly by -10.4% (95%CI: -12.7% to -8.0%) per year during 2006 to 2015. The trend for extra-pulmonary TB CNR declined but did not reach statistical significance in both regions. In conclusion, CNRs declined for all types of TB examined in both regions. Further research is needed to study trends for other TB dimensions such as treatment outcomes and notification of drug resistant TB cases.

Keywords: epidemiology, Namibia, temporal trends, tuberculosis

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Authors: Frank Kuebler, Rolf Steinhilper

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Artificial neural networks (ANN) as well as Design of Experiments (DOE) based regression analysis (RA) are mainly used for modeling of complex systems. Both methodologies are commonly applied in process and quality control of manufacturing processes. Due to the fact that resource efficiency has become a critical concern for manufacturing companies, these models needs to be extended to predict resource-consumption of manufacturing processes. This paper describes an approach to use neural networks as well as DOE based regression analysis for predicting resource consumption of manufacturing processes and gives a comparison of the achievable results based on an industrial case study of a turning process.

Keywords: artificial neural network, design of experiments, regression analysis, resource efficiency, manufacturing process

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Authors: Entisar A. Elgmati

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Recurrent infant diarrhea is studied using daily data collected in Salvador, Brazil over one year and three months. A logistic regression model is fitted instead of Aalen's additive model using the same covariates that were used in the analysis with the additive model. The model gives reasonably similar results to that using additive regression model. In addition, the problem with the estimated conditional probabilities not being constrained between zero and one in additive model is solved here. Also martingale residuals that have been used to judge the goodness of fit for the additive model are shown to be useful for judging the goodness of fit of the logistic model.

Keywords: additive model, cumulative probabilities, infant diarrhoea, recurrent event

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Authors: Jim J. Catina, Jackee M. Gwynn, Jin S. Kang

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Additive manufacturing (AM) for hybrid rocket engines is becoming increasingly attractive due to its ability to create complex grain configurations with improved regression rates when compared to cast grains. However, the presence of microvoids in parts produced through the additive manufacturing method of Fused Deposition Modeling (FDM) results in a lower fuel density and is believed to cause a decrease in regression rate compared to ideal performance. In this experiment, FDM was used to create hybrid rocket fuel grains with a star configuration composed of acrylonitrile butadiene styrene (ABS). Testing was completed to determine the effect of heat treatment as a post-processing method to improve the combustion performance of hybrid rocket fuel grains manufactured by FDM. For control, three ABS star configuration grains were printed using FDM and hot fired using gaseous oxygen (GOX) as the oxidizer. Parameters such as thrust and mass flow rate were measured. Three identical grains were then heat treated to varying degrees and hot fired under the same conditions as the control grains. This paper will quantitatively describe the amount of improvement in engine performance as a result of heat treatment of the AM hybrid fuel grain. Engine performance is measured in this paper by specific impulse, which is determined from the thrust measurements collected in testing.

Keywords: acrylonitrile butadiene styrene, additive manufacturing, fused deposition modeling, heat treatment

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Authors: Hasan Serdar Öge, Esra Çiftçi, Kazım Karaboğa

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The main purpose of the research is to address the role of psychological harassment behaviors (mobbing) to which employees are exposed and personality characteristics over work alienation. Research population was composed of the employees of Provincial Special Administration. A survey with four sections was created to measure variables and reach out the basic goals of the research. Correlation and step-wise regression analyses were performed to investigate the separate and overall effects of sub-dimensions of psychological harassment behaviors and personality characteristic on work alienation of employees. Correlation analysis revealed significant but weak relationships between work alienation and psychological harassment and personality characteristics. Step-wise regression analysis revealed also significant relationships between work alienation variable and assault to personality, direct negative behaviors (sub dimensions of mobbing) and openness (sub-dimension of personality characteristics). Each variable was introduced into the model step by step to investigate the effects of significant variables in explaining the variations in work alienation. While the explanation ratio of the first model was 13%, the last model including three variables had an explanation ratio of 24%.

Keywords: alienation, five-factor personality characteristics, mobbing, psychological harassment, work alienation

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Authors: Aizati N. A. Daud, Jorieke E. H. Bergman, Wilhelmina S. Kerstjens-Frederikse, Pieter Van Der Vlies, Eelko Hak, Rolf M. F. Berger, Henk Groen, Bob Wilffert

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Prenatal use of SRIs was previously associated with Congenital Heart Anomalies (CHA). The aim of the study is to explore whether pharmacogenetics plays a role in this teratogenicity using a gene-environment interaction study. A total of 33 case-mother dyads and 2 mother-only (children deceased) registered in EUROCAT Northern Netherlands were included in a case-only study. Five case-mother dyads and two mothers-only were exposed to SRIs (paroxetine=3, fluoxetine=2, venlafaxine=1, paroxetine and venlafaxine=1) in the first trimester of pregnancy. The remaining 28 case-mother dyads were not exposed to SRIs. Ten genes that encode the enzymes or proteins important in determining fetal exposure to SRIs or its mechanism of action were selected: CYPs (CYP1A2, CYP2C9, CYP2C19, CYP2D6), ABCB1 (placental P-glycoprotein), SLC6A4 (serotonin transporter) and serotonin receptor genes (HTR1A, HTR1B, HTR2A, and HTR3B). All included subjects were genotyped for 58 genetic variations in these ten genes. Logistic regression analyses were performed to determine the interaction odds ratio (OR) between genetic variations and SRIs exposure on the risk of CHA. Due to low phenotype frequencies of CYP450 poor metabolizers among exposed cases, the OR cannot be calculated. For ABCB1, there was no indication of changes in the risk of CHA with any of the ABCB1 SNPs in the children and their mothers. Several genetic variations of the serotonin transporter and receptors (SLC6A4 5-HTTLPR and 5-HTTVNTR, HTR1A rs1364043, HTR1B rs6296 & rs6298, HTR3B rs1176744) were associated with an increased risk of CHA, but with too limited sample size to reach statistical significance. For SLC6A4 genetic variations, the mean genetic scores of the exposed case-mothers tended to be higher than the unexposed mothers (2.5 ± 0.8 and 1.88 ± 0.7, respectively; p=0.061). For SNPs of the serotonin receptors, the mean genetic score for exposed cases (children) tended to be higher than the unexposed cases (3.4 ± 2.2, and 1.9 ± 1.6, respectively; p=0.065). This study might be among the first to explore the potential gene-environment interaction between pharmacogenetic determinants and SRIs use on the risk of CHA. With small sample sizes, it was not possible to find a significant interaction. However, there were indications for a role of serotonin receptor polymorphisms in fetuses exposed to SRIs on fetal risk of CHA which warrants further investigation.

Keywords: gene-environment interaction, heart defects, pharmacogenetics, serotonin reuptake inhibitors, teratogenicity

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Authors: C. M. Mat Isa, H. Mohd Saman, S. R. Mohd Nasir, A. Jaapar

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International market expansion involves a strategic process of market entry decision through which a firm expands its operation from domestic to the international domain. Hence, entry timing choices require the needs to balance the early entry risks and the problems in losing opportunities as a result of late entry into a new market. Questionnaire surveys administered to 115 Malaysian construction firms operating in 51 countries worldwide have resulted in 39.1 percent response rate. Factor analysis was used to determine the most significant factors affecting entry timing choices of the firms to penetrate the international market. A logistic regression analysis used to examine the firms’ entry timing choices, indicates that the model has correctly classified 89.5 per cent of cases as late movers. The findings reveal that the most significant factor influencing the construction firms’ choices as late movers was the firm factor related to the firm’s international experience, resources, competencies and financing capacity. The study also offers valuable information to construction firms with intention to internationalize their businesses.

Keywords: factors, early movers, entry timing choices, late movers, logistic regression model, principal axis factorial analysis, Malaysian construction firms

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Authors: Mustafa Sertçelik, Turan Çalban, Hacali Necefoğlu, Sabri Çolak

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In this study, Chevreul’s salt solubility and its dissolution kinetics in ammonium chloride solutions were investigated. Chevreul’s salt that we used in the studies was obtained by using the optimum conditions (ammonium sulphide concentration; 0,4 M, copper sulphate concentration; 0,25 M, temperature; 60°C, stirring speed; 600 rev/min, pH; 4 and reaction time; 15 mins) determined by T. Çalban et al. Chevreul’s salt solubility in ammonium chloride solutions and the kinetics of dissolution were investigated. The selected parameters that affect solubility were reaction temperature, concentration of ammonium chloride, stirring speed, and solid/liquid ratio. Correlation of experimental results had been achieved using linear regression implemented in the statistical package program statistica. The effect of parameters on Chevreul’s salt solubility was examined and integrated rate expression of dissolution rate was found using kinetic models in solid-liquid heterogeneous reactions. The results revealed that the dissolution rate of Chevreul’s salt was decreasing while temperature, concentration of ammonium chloride and stirring speed were increasing. On the other hand, dissolution rate was found to be decreasing with the increase of solid/liquid ratio. Based on result of the applications of the obtained experimental results to the kinetic models, we can deduce that Chevreul’s salt dissolution rate is controlled by diffusion through the ash (or product layer). Activation energy of the reaction of dissolution was found as 74.83 kJ/mol. The integrated rate expression along with the effects of parameters on Chevreul's salt solubility was found to be as follows: 1-3(1-X)2/3+2(1-X)= [2,96.1013.(CA)3,08 .(S/L)-038.(W)1,23 e-9001,2/T].t

Keywords: Chevreul's salt, copper, ammonium chloride, ammonium sulphide, dissolution kinetics

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Authors: Zhidong Zhang, Amanda Resendez

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This study is to examine how teachers’ perspective on education technology use in their class influence their students’ achievement. The authors hypothesized that teachers’ perspective can directly or indirectly influence students’ learning, performance, and achievements. In this study, a questionnaire entitled, Teacher’s Perspective on Educational Technology, was delivered to 63 teachers and 1268 students’ mathematics and reading achievement records were collected. The questionnaire consists of four parts: a) demographic variables, b) attitudes on technology integration, c) outside factor affecting technology integration, and d) technology use in the classroom. Kruskal-Wallis and hierarchical regression analysis techniques were used to examine: 1) the relationship between the demographic variables and teachers’ perspectives on educational technology, and 2) how the demographic variables were causally related to students’ mathematics and reading achievements. The study found that teacher demographics were significantly related to the teachers’ perspective on educational technology with p < 0.05 and p < 0.01 separately. These teacher demographical variables included the school district, age, gender, the grade currently teach, teaching experience, and proficiency using new technology. Further, these variables significantly predicted students’ mathematics and reading achievements with p < 0.05 and p < 0.01 separately. The variations of R² are between 0.176 and 0.467. That means 46.7% of the variance of a given analysis can be explained by the model.

Keywords: teacher's perception of technology use, mathematics achievement, reading achievement, Kruskal-Wallis test, hierarchical regression analysis

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Authors: Fatemeh Valizadeh Gamchi, Edward L. Boone

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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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Authors: Muhammad Bahrul Ilmi

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The purpose of this research is to analyze the influence of Islamic financing and work relation founding simultaneously and partially towards non-performing financing in Islamic banks. This research was regression quantitative field research, and had been done in Muammalat Indonesia Bank and Islamic Danamon Bank in 3 months. The populations of this research were 15 account officers of Muammalat Indonesia Bank and Islamic Danamon Bank in Surakarta, Indonesia. The techniques of collecting data used in this research were documentation, questionnaire, literary study and interview. Regression analysis result shows that Islamic financing and work relation founding simultaneously has positive and significant effect towards non performing financing of two Islamic Banks. It is obtained with probability value 0.003 which is less than 0.05 and F value 9.584. The analysis result of Islamic financing regression towards non performing financing shows the significant effect. It is supported by double linear regression analysis with probability value 0.001 which is less than 0.05. The regression analysis of work relation founding effect towards non-performing financing shows insignificant effect. This is shown in the double linear regression analysis with probability value 0.161 which is bigger than 0.05.

Keywords: Syariah financing, work relation founding, non-performing financing (NPF), Islamic Bank

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Authors: Chen Li-Ching

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The multinomial logistic regression model is used popularly for inferring the relationship of risk factors and disease with multiple categories. This study based on the discrepancy between the nonparametric maximum likelihood estimator and semiparametric maximum likelihood estimator of the cumulative distribution function to propose a Kolmogorov-Smirnov type test statistic to assess adequacy of the multinomial logistic regression model for case-control data. A bootstrap procedure is presented to calculate the critical value of the proposed test statistic. Empirical type I error rates and powers of the test are performed by simulation studies. Some examples will be illustrated the implementation of the test.

Keywords: case-control studies, goodness-of-fit test, Kolmogorov-Smirnov test, multinomial logistic regression

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Authors: Nicola Rubino

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This paper presents an analysis of a group of commodity exporting countries' nominal exchange rate movements in relationship to the US dollar. Using a series of Unrestricted Self-exciting Threshold Autoregressive models (SETAR), we model and evaluate sixteen national CPI price differentials relative to the US dollar CPI. Out-of-sample forecast accuracy is evaluated through calculation of mean absolute error measures on the basis of two-hundred and fifty-three months rolling window forecasts and extended to three additional models, namely a logistic smooth transition regression (LSTAR), an additive non linear autoregressive model (AAR) and a simple linear Neural Network model (NNET). Our preliminary results confirm presence of some form of TAR non linearity in the majority of the countries analyzed, with a relatively higher goodness of fit, with respect to the linear AR(1) benchmark, in five countries out of sixteen considered. Although no model appears to statistically prevail over the other, our final out-of-sample forecast exercise shows that SETAR models tend to have quite poor relative forecasting performance, especially when compared to alternative non-linear specifications. Finally, by analyzing the implied half-lives of the > coefficients, our results confirms the presence, in the spirit of arbitrage band adjustment, of band convergence with an inner unit root behaviour in five of the sixteen countries analyzed.

Keywords: transition regression model, real exchange rate, nonlinearities, price differentials, PPP, commodity points

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Authors: Yan Wang, Yasushi Asami, Yukio Sadahiro

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In urban area, several landmarks may affect housing price and rents, hedonic analysis should employ distance variables corresponding to each landmarks. Unfortunately, the effects of distances to landmarks on housing prices are generally not consistent with the true price. These distance variables may cause magnitude error in regression, pointing a problem of spatial multicollinearity. In this paper, we provided some approaches for getting the samples with less bias and method on locating the specific sampling area to avoid the multicollinerity problem in two specific landmarks case.

Keywords: landmarks, hedonic regression, distance variables, collinearity, multicollinerity

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Authors: Orkide Donma, Mustafa M. Donma

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Basal metabolic rate is questioned as a risk factor for weight gain. The relations between basal metabolic rate and body composition have not been cleared yet. The impact of fat mass on basal metabolic rate is also uncertain. Within this context, indices based upon total body mass as well as total body fat mass are available. In this study, the aim is to investigate the potential clinical utility of these indices in the adult population. 287 individuals, aged from 18 to 79 years, were included into the scope of the study. Based upon body mass index values, 10 underweight, 88 normal, 88 overweight, 81 obese, and 20 morbid obese individuals participated. Anthropometric measurements including height (m), and weight (kg) were performed. Body mass index, diagnostic obesity notation model assessment index I, diagnostic obesity notation model assessment index II, basal metabolic rate-to-weight ratio were calculated. Total body fat mass (kg), fat percent (%), basal metabolic rate, metabolic age, visceral adiposity, fat mass of upper as well as lower extremities and trunk, obesity degree were measured by TANITA body composition monitor using bioelectrical impedance analysis technology. Statistical evaluations were performed by statistical package (SPSS) for Windows Version 16.0. Scatterplots of individual measurements for the parameters concerning correlations were drawn. Linear regression lines were displayed. The statistical significance degree was accepted as p < 0.05. The strong correlations between body mass index and diagnostic obesity notation model assessment index I as well as diagnostic obesity notation model assessment index II were obtained (p < 0.001). A much stronger correlation was detected between basal metabolic rate and diagnostic obesity notation model assessment index I in comparison with that calculated for basal metabolic rate and body mass index (p < 0.001). Upon consideration of the associations between basal metabolic rate-to-weight ratio and these three indices, the best association was observed between basal metabolic rate-to-weight and diagnostic obesity notation model assessment index II. In a similar manner, this index was highly correlated with fat percent (p < 0.001). Being independent of the indices, a strong correlation was found between fat percent and basal metabolic rate-to-weight ratio (p < 0.001). Visceral adiposity was much strongly correlated with metabolic age when compared to that with chronological age (p < 0.001). In conclusion, all three indices were associated with metabolic age, but not with chronological age. Diagnostic obesity notation model assessment index II values were highly correlated with body mass index values throughout all ranges starting with underweight going towards morbid obesity. This index is the best in terms of its association with basal metabolic rate-to-weight ratio, which can be interpreted as basal metabolic rate unit.

Keywords: basal metabolic rate, body mass index, children, diagnostic obesity notation model assessment index, obesity

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Authors: Ren-Jieh Kuo, Chun-Shou Huang

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The research of juice flavor forecasting has become more important in China. Due to the fast economic growth in China, many different kinds of juices have been introduced to the market. If a beverage company can understand their customers’ preference well, the juice can be served more attractively. Thus, this study intends to introduce the basic theory and computing process of grapes juice flavor forecasting based on support vector regression (SVR). Applying SVR, BPN and LR to forecast the flavor of grapes juice in real data, the result shows that SVR is more suitable and effective at predicting performance.

Keywords: flavor forecasting, artificial neural networks, Support Vector Regression, China

Procedia PDF Downloads 451

Authors: Trevor C. Brown, David J. Miron

Abstract:

Gas-solid physical adsorption methods are central to the characterization and optimization of the effective surface area, pore size and porosity for applications such as heterogeneous catalysis, and gas separation and storage. Properties such as adsorption uptake, capacity, equilibrium constants and Gibbs free energy are dependent on the composition and structure of both the gas and the adsorbent. However, challenges remain, in accurately calculating these properties from experimental data. Gas adsorption experiments involve measuring the amounts of gas adsorbed over a range of pressures under isothermal conditions. Various constant-parameter models, such as Langmuir and Brunauer-Emmett-Teller (BET) theories are used to provide information on adsorbate and adsorbent properties from the isotherm data. These models typically do not provide accurate interpretations across the full range of pressures and temperatures. The Langmuir adsorption isotherm is a simple approximation for modelling equilibrium adsorption data and has been effective in estimating surface areas and catalytic rate laws, particularly for high surface area solids. The Langmuir isotherm assumes the systematic filling of identical adsorption sites to a monolayer coverage. The BET model is based on the Langmuir isotherm and allows for the formation of multiple layers. These additional layers do not interact with the first layer and the energetics are equal to the adsorbate as a bulk liquid. This BET method is widely used to measure the specific surface area of materials. Both Langmuir and BET models assume that the affinity of the gas for all adsorption sites are identical and so the calculated adsorbent uptake at the monolayer and equilibrium constant are independent of coverage and pressure. Accurate representations of adsorption data have been achieved by extending the Langmuir and BET models to include pressure-varying uptake capacities and equilibrium constants. These parameters are determined using a novel regression technique called flexible least squares for time-varying linear regression. For isothermal adsorption the adsorption parameters are assumed to vary slowly and smoothly with increasing pressure. The flexible least squares for pressure-varying linear regression (FLS-PVLR) approach assumes two distinct types of discrepancy terms, dynamic and measurement for all parameters in the linear equation used to simulate the data. Dynamic terms account for pressure variation in successive parameter vectors, and measurement terms account for differences between observed and theoretically predicted outcomes via linear regression. The resultant pressure-varying parameters are optimized by minimizing both dynamic and measurement residual squared errors. Validation of this methodology has been achieved by simulating adsorption data for n-butane and isobutane on activated carbon at 298 K, 323 K and 348 K and for nitrogen on mesoporous alumina at 77 K with pressure-varying Langmuir and BET adsorption parameters (equilibrium constants and uptake capacities). This modeling provides information on the adsorbent (accessible surface area and micropore volume), adsorbate (molecular areas and volumes) and thermodynamic (Gibbs free energies) variations of the adsorption sites.

Keywords: Langmuir adsorption isotherm, BET adsorption isotherm, pressure-varying adsorption parameters, adsorbate and adsorbent properties and energetics

Procedia PDF Downloads 193

Authors: Novriyanti Lubis, Riska Prasetiawati, Wulan Septiani

Abstract:

The quantitative analysis of vitamin C content from variations beverage packaging containing red guava (Psidium Guajava Linn) fruit juice had been done. In this study, four samples were obtained from the shopping center in Garut and Bandung City. Samples were tested quantitatively by 2,6-dichlorophenol indophenol titration method. The results showed different concentration of 4 samples consist of tetra pack packaging, tin, glass, and plastic bottles, such as; 17.99 mg/100 gr, 31.46 mg/100 gr, 13.00 mg/100 gr, and 12.01 mg/100 gr, respectively. These results indicated that the packaging variations affected the level of vitamin C content which was characterized by decreased levels of vitamin C. It means the levels of vitamin C from this research were not in accordance with nutritional value information on the packaging. Tetra pack packaging was the most stable compared to other packaging even though it had a shorter expired date than with other.

Keywords: vitamin C, variations beverage packaging, red guava, titration 2, 6- dichlorophenol indophenol

Procedia PDF Downloads 209

Authors: Rajeshwar Singh

Abstract:

The presence of multicollinearity is common in handling with several explanatory variables simultaneously due to exhibiting a linear relationship among them. A great problem arises in understanding the impact of explanatory variables on the dependent variable. Thus, the method of least squares estimation gives inexact estimates. In this case, it is advised to detect its presence first before proceeding further. Using the ridge regression degree of its occurrence is reduced but principal components regression gives good estimates in this situation. This paper discusses well-known techniques of the ridge and principal components regressions and applies to get the estimates of coefficients by both techniques. In addition to it, this paper also discusses the conflicting claim on the discovery of the method of ridge regression based on available documents.

Keywords: conflicting claim on credit of discovery of ridge regression, multicollinearity, principal components and ridge regressions, variance inflation factor

Procedia PDF Downloads 374

Authors: Naji Ali Albakay, Abdulrahman Alothaim, Isa Barshushi

Abstract:

The most common quadrature amplitude modulator (QAM) applies two Mach-Zehnder Modulators (MZM) and one phase shifter to generate high order modulation format. The bias of MZM changes over time due to temperature, vibration, and aging factors. The change in the biasing causes distortion to the generated QAM signal which leads to deterioration of bit error rate (BER) performance. Therefore, it is critical to be able to lock MZM’s Q point to the required operating point for good performance. We propose a technique for automatic bias control (ABC) of QAM transmitter using BER measurements and gradient descent optimization algorithm. The proposed technique is attractive because it uses the pertinent metric, BER, which compensates for bias drifting independently from other system variations such as laser source output power. The proposed scheme performance and its operating principles are simulated using OptiSystem simulation software for 4-QAM and 16-QAM transmitters.

Keywords: automatic bias control, optical fiber communication, optical modulation, optical devices

Procedia PDF Downloads 158

Authors: T. Manzur, S. Iffat, M. A. Noor

Abstract:

In this paper, relationship between different properties of IC concrete and water cement ratio, obtained from a comprehensive experiment conducted on IC using local materials (Burnt clay chips- BC) is presented. In addition, saturated SAP was used as an IC material in some cases. Relationships have been developed through regression analysis. The focus of this analysis is on developing relationship between a dependent variable and an independent variable. Different percent replacements of BC and water cement ratios were used. Compressive strength, modulus of elasticity, water permeability and chloride permeability were tested and variations of these parameters were analyzed with respect to water cement ratio.

Keywords: compressive strength, concrete, curing, lightweight, aggregate, superabsorbent polymer, internal curing

Procedia PDF Downloads 438