Search results for: multinomial endogenous switching regression
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3889

Search results for: multinomial endogenous switching regression

3199 Regression for Doubly Inflated Multivariate Poisson Distributions

Authors: Ishapathik Das, Sumen Sen, N. Rao Chaganty, Pooja Sengupta

Abstract:

Dependent multivariate count data occur in several research studies. These data can be modeled by a multivariate Poisson or Negative binomial distribution constructed using copulas. However, when some of the counts are inflated, that is, the number of observations in some cells are much larger than other cells, then the copula based multivariate Poisson (or Negative binomial) distribution may not fit well and it is not an appropriate statistical model for the data. There is a need to modify or adjust the multivariate distribution to account for the inflated frequencies. In this article, we consider the situation where the frequencies of two cells are higher compared to the other cells, and develop a doubly inflated multivariate Poisson distribution function using multivariate Gaussian copula. We also discuss procedures for regression on covariates for the doubly inflated multivariate count data. For illustrating the proposed methodologies, we present a real data containing bivariate count observations with inflations in two cells. Several models and linear predictors with log link functions are considered, and we discuss maximum likelihood estimation to estimate unknown parameters of the models.

Keywords: copula, Gaussian copula, multivariate distributions, inflated distributios

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3198 Modeling of the Effect of Explosives, Geological and Geotechnical Parameters on the Stability of Rock Masses Case of Marrakech: Agadir Highway, Morocco

Authors: Taoufik Benchelha, Toufik Remmal, Rachid El Hamdouni, Hamou Mansouri, Houssein Ejjaouani, Halima Jounaid, Said Benchelha

Abstract:

During the earthworks for the construction of Marrakech-Agadir highway in southern Morocco, which crosses mountainous areas of the High Western Atlas, the main problem faced is the stability of the slopes. Indeed, the use of explosives as a means of excavation associated with the geological structure of the terrain encountered can trigger major ruptures and cause damage which depends on the intrinsic characteristics of the rock mass. The study consists of a geological and geotechnical analysis of several unstable zones located along the route, mobilizing millions of cubic meters of rock, with deduction of the parameters influencing slope stability. From this analysis, a predictive model for rock mass stability is carried out, based on a statistic method of logistic regression, in order to predict the geomechanical behavior of the rock slopes constrained by earthworks.

Keywords: explosive, logistic regression, rock mass, slope stability

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3197 Count Regression Modelling on Number of Migrants in Households

Authors: Tsedeke Lambore Gemecho, Ayele Taye Goshu

Abstract:

The main objective of this study is to identify the determinants of the number of international migrants in a household and to compare regression models for count response. This study is done by collecting data from total of 2288 household heads of 16 randomly sampled districts in Hadiya and Kembata-Tembaro zones of Southern Ethiopia. The Poisson mixed models, as special cases of the generalized linear mixed model, is explored to determine effects of the predictors: age of household head, farm land size, and household size. Two ethnicities Hadiya and Kembata are included in the final model as dummy variables. Stepwise variable selection has indentified four predictors: age of head, farm land size, family size and dummy variable ethnic2 (0=other, 1=Kembata). These predictors are significant at 5% significance level with count response number of migrant. The Poisson mixed model consisting of the four predictors with random effects districts. Area specific random effects are significant with the variance of about 0.5105 and standard deviation of 0.7145. The results show that the number of migrant increases with heads age, family size, and farm land size. In conclusion, there is a significantly high number of international migration per household in the area. Age of household head, family size, and farm land size are determinants that increase the number of international migrant in households. Community-based intervention is needed so as to monitor and regulate the international migration for the benefits of the society.

Keywords: Poisson regression, GLM, number of migrant, Hadiya and Kembata Tembaro zones

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3196 Predictive Models for Compressive Strength of High Performance Fly Ash Cement Concrete for Pavements

Authors: S. M. Gupta, Vanita Aggarwal, Som Nath Sachdeva

Abstract:

The work reported through this paper is an experimental work conducted on High Performance Concrete (HPC) with super plasticizer with the aim to develop some models suitable for prediction of compressive strength of HPC mixes. In this study, the effect of varying proportions of fly ash (0% to 50% at 10% increment) on compressive strength of high performance concrete has been evaluated. The mix designs studied were M30, M40 and M50 to compare the effect of fly ash addition on the properties of these concrete mixes. In all eighteen concrete mixes have been designed, three as conventional concretes for three grades under discussion and fifteen as HPC with fly ash with varying percentages of fly ash. The concrete mix designing has been done in accordance with Indian standard recommended guidelines i.e. IS: 10262. All the concrete mixes have been studied in terms of compressive strength at 7 days, 28 days, 90 days and 365 days. All the materials used have been kept same throughout the study to get a perfect comparison of values of results. The models for compressive strength prediction have been developed using Linear Regression method (LR), Artificial Neural Network (ANN) and Leave One Out Validation (LOOV) methods.

Keywords: high performance concrete, fly ash, concrete mixes, compressive strength, strength prediction models, linear regression, ANN

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3195 A Comparative Analysis of an All-Optical Switch Using Chalcogenide Glass and Gallium Arsenide Based on Nonlinear Photonic Crystal

Authors: Priyanka Kumari Gupta, Punya Prasanna Paltani, Shrivishal Tripathi

Abstract:

This paper proposes a nonlinear photonic crystal ring resonator-based all-optical 2 × 2 switch. The nonlinear Kerr effect is used to evaluate the essential 2 x 2 components of the photonic crystal-based optical switch, including the bar and cross states. The photonic crystal comprises a two-dimensional square lattice of dielectric rods in an air background. In the background air, two different dielectric materials are used for this comparison study separately. Initially with chalcogenide glass rods, then with GaAs rods. For both materials, the operating wavelength, bandgap diagram, operating power intensities, and performance parameters, such as the extinction ratio, insertion loss, and cross-talk of an optical switch, have also been estimated using the plane wave expansion and the finite-difference time-domain method. The chalcogenide glass material (Ag20As32Se48) has a high refractive index of 3.1 which is highly suitable for switching operations. This dielectric material is immersed in an air background with a nonlinear Kerr coefficient of 9.1 x 10-17 m2/W. The resonance wavelength is at 1552 nm, with the operating power intensities at the cross-state and bar state around 60 W/μm2 and 690 W/μm2. The extinction ratio, insertion loss, and cross-talk value for the chalcogenide glass at the cross-state are 17.19 dB, 0.051 dB, and -17.14 dB, and the bar state, the values are 11.32 dB, 0.025 dB, and -11.35 dB respectively. The gallium arsenide (GaAs) dielectric material has a high refractive index of 3.4, a direct bandgap semiconductor material highly preferred nowadays for switching operations. This dielectric material is immersed in an air background with a nonlinear Kerr coefficient of 3.1 x 10-16 m2/W. The resonance wavelength is at 1558 nm, with the operating power intensities at the cross-state and bar state around 110 W/μm2 and 200 W/μm2. The extinction ratio, insertion loss, and cross-talk value for the chalcogenide glass at the cross-state are found to be 3.36.19 dB, 2.436 dB, and -5.8 dB, and for the bar state, the values are 15.60 dB, 0.985 dB, and -16.59 dB respectively. This paper proposes an all-optical 2 × 2 switch based on a nonlinear photonic crystal using a ring resonator. The two-dimensional photonic crystal comprises a square lattice of dielectric rods in an air background. The resonance wavelength is in the range of photonic bandgap. Later, another widely used material, GaAs, is also considered, and its performance is compared with the chalcogenide glass. Our presented structure can be potentially applicable in optical integration circuits and information processing.

Keywords: photonic crystal, FDTD, ring resonator, optical switch

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3194 Examining Bulling Rates among Youth with Intellectual Disabilities

Authors: Kaycee L. Bills

Abstract:

Adolescents and youth who are members of a minority group are more likely to experience higher rates of bullying in comparison to other student demographics. Specifically, adolescents with intellectual disabilities are a minority population that is more susceptible to experience unfair treatment in social settings. This study employs the 2015 Wave of the National Crime Victimization Survey – School Crime Supplement (NCVS/SCS) longitudinal dataset to explore bullying rates experienced among adolescents with intellectual disabilities. This study uses chi-square testing and a logistic regression to analyze if having a disability influences the likelihood of being bullied in comparison to other student demographics. Results of the chi-square testing and the logistic regression indicate that adolescent students who were identified as having a disability were approximately four times more likely to experience higher bullying rates in comparison to all other majority and minority student populations. Thus, it means having a disability resulted in higher bullying rates in comparison to all student groups.

Keywords: disability, bullying, social work, school bullying

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3193 Remote Wireless Communications Lab in Real Time

Authors: El Miloudi Djelloul

Abstract:

Technology nowadays enables the remote access to laboratory equipment and instruments via Internet. This is especially useful in engineering education, where students can conduct laboratory experiment remotely. Such remote laboratory access can enable student to use expensive laboratory equipment, which is not usually available to students. In this paper, we present a method of creating a Web-based Remote Laboratory Experimentation in the master degree course “Wireless Communications Systems” which is part of “ICS (Information and Communication Systems)” and “Investment Management in Telecommunications” curriculums. This is done within the RIPLECS Project and the NI2011 FF005 Research Project “Implementation of Project-Based Learning in an Interdisciplinary Master Program”.

Keywords: remote access, remote laboratory, wireless telecommunications, external antenna-switching controller board (EASCB)

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3192 Gender Estimation by Means of Quantitative Measurements of Foramen Magnum: An Analysis of CT Head Images

Authors: Thilini Hathurusinghe, Uthpalie Siriwardhana, W. M. Ediri Arachchi, Ranga Thudugala, Indeewari Herath, Gayani Senanayake

Abstract:

The foramen magnum is more prone to protect than other skeletal remains during high impact and severe disruptive injuries. Therefore, it is worthwhile to explore whether these measurements can be used to determine the human gender which is vital in forensic and anthropological studies. The idea was to find out the ability to use quantitative measurements of foramen magnum as an anatomical indicator for human gender estimation and to evaluate the gender-dependent variations of foramen magnum using quantitative measurements. Randomly selected 113 subjects who underwent CT head scans at Sri Jayawardhanapura General Hospital of Sri Lanka within a period of six months, were included in the study. The sample contained 58 males (48.76 ± 14.7 years old) and 55 females (47.04 ±15.9 years old). Maximum length of the foramen magnum (LFM), maximum width of the foramen magnum (WFM), minimum distance between occipital condyles (MnD) and maximum interior distance between occipital condyles (MxID) were measured. Further, AreaT and AreaR were also calculated. The gender was estimated using binomial logistic regression. The mean values of all explanatory variables (LFM, WFM, MnD, MxID, AreaT, and AreaR) were greater among male than female. All explanatory variables except MnD (p=0.669) were statistically significant (p < 0.05). Significant bivariate correlations were demonstrated by AreaT and AreaR with the explanatory variables. The results evidenced that WFM and MxID were the best measurements in predicting gender according to binomial logistic regression. The estimated model was: log (p/1-p) =10.391-0.136×MxID-0.231×WFM, where p is the probability of being a female. The classification accuracy given by the above model was 65.5%. The quantitative measurements of foramen magnum can be used as a reliable anatomical marker for human gender estimation in the Sri Lankan context.

Keywords: foramen magnum, forensic and anthropological studies, gender estimation, logistic regression

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3191 Exploring the Dose-Response Association of Lifestyle Behaviors and Mental Health among High School Students in the US: A Secondary Analysis of 2021 Adolescent Behaviors and Experiences Survey Data

Authors: Layla Haidar, Shari Esquenazi-Karonika

Abstract:

Introduction: Mental health includes one’s emotional, psychological, and interpersonal well-being; it ranges from “good” to “poor” on a continuum. At the individual-level, it affects how a person thinks, feels, and acts. Moreover, it determines how they cope with stress, relate to others, and interface with their surroundings. Research has yielded that mental health is directly related with short- and long-term physical health (including chronic disease), health risk behaviors, education-level, employment, and social relationships. As is the case with physical conditions like diabetes, heart disease, and cancer, mitigating the behavioral and genetic risks of debilitating mental health conditions like anxiety and depression can nurture a healthier quality of mental health throughout one’s life. In order to maximize the benefits of prevention, it is important to identify modifiable risks and develop protective habits earlier in life. Methods: The Adolescent Behaviors and Experiences Survey (ABES) dataset was used for this study. The ABES survey was administered to high school students (9th-12th grade) during January 2021- June 2021 by the Centers for Disease Control and Prevention (CDC). The data was analyzed to identify any associations between feelings of sadness, hopelessness, or increased suicidality among high school students with relation to their participation on one or more sports teams and their average daily consumed screen time. Data was analyzed using descriptive and multivariable analytic techniques. A multinomial logistic regression of each variable was conducted to examine if there was an association, while controlling for grade-level, sex, and race. Results: The findings from this study are insightful for administrators and policymakers who wish to address mounting concerns related to student mental health. The study revealed that compared to a student who participated on zero sports teams, students who participated in 1 or more sports teams showed a significantly increased risk of depression (p<0.05). Conversely, the rate of depression in students was significantly less in those who consumed 5 or more hours of screen time per day, compared to those who consumed less than 1 hour per day of screen time (p<0.05). Conclusion: These findings are informative and highlight the importance of understanding the nuances of student participation on sports teams (e.g., physical exertion, social dynamics of team, and the level of competitiveness within the sport). Likewise, the context of an individual’s screen time (e.g., social media, engaging in team-based video games, or watching television) can inform parental or school-based policies about screen time activity. Although physical activity has been proven to be important for emotional and physical well-being of youth, playing on multiple teams could have negative consequences on the emotional state of high school students potentially due to fatigue, overtraining, and injuries. Existing literature has highlighted the negative effects of screen time; however, further research needs to consider the type of screen-based consumption to better understand its effects on mental health.

Keywords: behavioral science, mental health, adolescents, prevention

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3190 Is There a Month Effect on the Deposits Interest Rates? Evidence from the Greek Banking Industry during the Period 2003-13

Authors: Konstantopoulos N., Samitas A., E. Vasileiou, Kinias I.

Abstract:

This article introduces a new view on the month effect study. Applying a Markov Switching Regime model on data from the Greek Time Deposits (TDs) market for the time span January 2003 to October 2013, we examine if there is a month effect on the Greek banking industry. The empirical findings provide convincing evidence for a new king of monthly anomaly. The explanation for the specific abnormality may be the upward deposits window dressing. Further research should be done in order to examine if the specific calendar effect exists in other countries or it is only a Greek phenomenon.

Keywords: calendar anomalies, banking crisis, month effect, Greek banking industry

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3189 Analytics Capabilities and Employee Role Stressors: Implications for Organizational Performance

Authors: Divine Agozie, Muesser Nat, Eric Afful-Dadzie

Abstract:

This examination attempts an analysis of the effect of business intelligence and analytics (BI&A) capabilities on organizational role stressors and the implications of such an effect on performance. Two hundred twenty-eight responses gathered from seventy-six firms across Ghana were analyzed using the Partial Least Squares Structural Equation Modelling (PLS-SEM) approach to validate the hypothesized relationships identified in the research model. Findings suggest both endogenous and exogenous dependencies of the sensing capability on the multiple role requirements of personnel. Further, transforming capability increases role conflict, whereas driving capability of BI&A systems impacts role conflict and role ambiguity. This study poses many practical insights to firms seeking to acquire analytics capabilities to drive performance and data-driven decision-making. It is important for firms to consider balancing role changes and task requirements before implementing and post-implementation stages of BI&A innovations.

Keywords: business intelligence and analytics, dynamic capabilities view, organizational stressors, structural equation modelling

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3188 Association Between Short-term NOx Exposure and Asthma Exacerbations in East London: A Time Series Regression Model

Authors: Hajar Hajmohammadi, Paul Pfeffer, Anna De Simoni, Jim Cole, Chris Griffiths, Sally Hull, Benjamin Heydecker

Abstract:

Background: There is strong interest in the relationship between short-term air pollution exposure and human health. Most studies in this field focus on serious health effects such as death or hospital admission, but air pollution exposure affects many people with less severe impacts, such as exacerbations of respiratory conditions. A lack of quantitative analysis and inconsistent findings suggest improved methodology is needed to understand these effectsmore fully. Method: We developed a time series regression model to quantify the relationship between daily NOₓ concentration and Asthma exacerbations requiring oral steroids from primary care settings. Explanatory variables include daily NOₓ concentration measurements extracted from 8 available background and roadside monitoring stations in east London and daily ambient temperature extracted for London City Airport, located in east London. Lags of NOx concentrations up to 21 days (3 weeks) were used in the model. The dependent variable was the daily number of oral steroid courses prescribed for GP registered patients with asthma in east London. A mixed distribution model was then fitted to the significant lags of the regression model. Result: Results of the time series modelling showed a significant relationship between NOₓconcentrations on each day and the number of oral steroid courses prescribed in the following three weeks. In addition, the model using only roadside stations performs better than the model with a mixture of roadside and background stations.

Keywords: air pollution, time series modeling, public health, road transport

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3187 Solving Dimensionality Problem and Finding Statistical Constructs on Latent Regression Models: A Novel Methodology with Real Data Application

Authors: Sergio Paez Moncaleano, Alvaro Mauricio Montenegro

Abstract:

This paper presents a novel statistical methodology for measuring and founding constructs in Latent Regression Analysis. This approach uses the qualities of Factor Analysis in binary data with interpretations on Item Response Theory (IRT). In addition, based on the fundamentals of submodel theory and with a convergence of many ideas of IRT, we propose an algorithm not just to solve the dimensionality problem (nowadays an open discussion) but a new research field that promises more fear and realistic qualifications for examiners and a revolution on IRT and educational research. In the end, the methodology is applied to a set of real data set presenting impressive results for the coherence, speed and precision. Acknowledgments: This research was financed by Colciencias through the project: 'Multidimensional Item Response Theory Models for Practical Application in Large Test Designed to Measure Multiple Constructs' and both authors belong to SICS Research Group from Universidad Nacional de Colombia.

Keywords: item response theory, dimensionality, submodel theory, factorial analysis

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3186 Application of the Least Squares Method in the Adjustment of Chlorodifluoromethane (HCFC-142b) Regression Models

Authors: L. J. de Bessa Neto, V. S. Filho, J. V. Ferreira Nunes, G. C. Bergamo

Abstract:

There are many situations in which human activities have significant effects on the environment. Damage to the ozone layer is one of them. The objective of this work is to use the Least Squares Method, considering the linear, exponential, logarithmic, power and polynomial models of the second degree, to analyze through the coefficient of determination (R²), which model best fits the behavior of the chlorodifluoromethane (HCFC-142b) in parts per trillion between 1992 and 2018, as well as estimates of future concentrations between 5 and 10 periods, i.e. the concentration of this pollutant in the years 2023 and 2028 in each of the adjustments. A total of 809 observations of the concentration of HCFC-142b in one of the monitoring stations of gases precursors of the deterioration of the ozone layer during the period of time studied were selected and, using these data, the statistical software Excel was used for make the scatter plots of each of the adjustment models. With the development of the present study, it was observed that the logarithmic fit was the model that best fit the data set, since besides having a significant R² its adjusted curve was compatible with the natural trend curve of the phenomenon.

Keywords: chlorodifluoromethane (HCFC-142b), ozone, least squares method, regression models

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3185 Artificial Neural Network Modeling of a Closed Loop Pulsating Heat Pipe

Authors: Vipul M. Patel, Hemantkumar B. Mehta

Abstract:

Technological innovations in electronic world demand novel, compact, simple in design, less costly and effective heat transfer devices. Closed Loop Pulsating Heat Pipe (CLPHP) is a passive phase change heat transfer device and has potential to transfer heat quickly and efficiently from source to sink. Thermal performance of a CLPHP is governed by various parameters such as number of U-turns, orientations, input heat, working fluids and filling ratio. The present paper is an attempt to predict the thermal performance of a CLPHP using Artificial Neural Network (ANN). Filling ratio and heat input are considered as input parameters while thermal resistance is set as target parameter. Types of neural networks considered in the present paper are radial basis, generalized regression, linear layer, cascade forward back propagation, feed forward back propagation; feed forward distributed time delay, layer recurrent and Elman back propagation. Linear, logistic sigmoid, tangent sigmoid and Radial Basis Gaussian Function are used as transfer functions. Prediction accuracy is measured based on the experimental data reported by the researchers in open literature as a function of Mean Absolute Relative Deviation (MARD). The prediction of a generalized regression ANN model with spread constant of 4.8 is found in agreement with the experimental data for MARD in the range of ±1.81%.

Keywords: ANN models, CLPHP, filling ratio, generalized regression, spread constant

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3184 Climate Related Variability and Stock-Recruitment Relationship of the North Pacific Albacore Tuna

Authors: Ashneel Ajay Singh, Naoki Suzuki, Kazumi Sakuramoto,

Abstract:

The North Pacific albacore (Thunnus alalunga) is a temperate tuna species distributed in the North Pacific which is of significant economic importance to the Pacific Island Nations and Territories. Despite its importance, the stock dynamics and ecological characteristics of albacore still, have gaps in knowledge. The stock-recruitment relationship of the North Pacific stock of albacore tuna was investigated for different density-dependent effects and a regime shift in the stock characteristics in response to changes in environmental and climatic conditions. Linear regression analysis for recruit per spawning biomass (RPS) and recruitment (R) against the female spawning stock biomass (SSB) were significant for the presence of different density-dependent effects and positive for a regime shift in the stock time series. Application of Deming regression to RPS against SSB with the assumption for the presence of observation and process errors in both the dependent and independent variables confirmed the results of simple regression. However, R against SSB results disagreed given variance level of < 3 and agreed with linear regression results given the assumption of variance ≥ 3. Assuming the presence of different density-dependent effects in the albacore tuna time series, environmental and climatic condition variables were compared with R, RPS, and SSB. The significant relationship of R, RPS and SSB were determined with the sea surface temperature (SST), Pacific Decadal Oscillation (PDO) and multivariate El Niño Southern Oscillation (ENSO) with SST being the principal variable exhibiting significantly similar trend with R and RPS. Recruitment is significantly influenced by the dynamics of the SSB as well as environmental conditions which demonstrates that the stock-recruitment relationship is multidimensional. Further investigation of the North Pacific albacore tuna age-class and structure is necessary for further support the results presented here. It is important for fishery managers and decision makers to be vigilant of regime shifts in environmental conditions relating to albacore tuna as it may possibly cause regime shifts in the albacore R and RPS which should be taken into account to effectively and sustainability formulate harvesting plans and management of the species in the North Pacific oceanic region.

Keywords: Albacore tuna, Thunnus alalunga, recruitment, spawning stock biomass, recruits per spawning biomass, sea surface temperature, pacific decadal oscillation, El Niño southern oscillation, density-dependent effects, regime shift

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3183 Development of a Regression Based Model to Predict Subjective Perception of Squeak and Rattle Noise

Authors: Ramkumar R., Gaurav Shinde, Pratik Shroff, Sachin Kumar Jain, Nagesh Walke

Abstract:

Advancements in electric vehicles have significantly reduced the powertrain noise and moving components of vehicles. As a result, in-cab noises have become more noticeable to passengers inside the car. To ensure a comfortable ride for drivers and other passengers, it has become crucial to eliminate undesirable component noises during the development phase. Standard practices are followed to identify the severity of noises based on subjective ratings, but it can be a tedious process to identify the severity of each development sample and make changes to reduce it. Additionally, the severity rating can vary from jury to jury, making it challenging to arrive at a definitive conclusion. To address this, an automotive component was identified to evaluate squeak and rattle noise issue. Physical tests were carried out for random and sine excitation profiles. Aim was to subjectively assess the noise using jury rating method and objectively evaluate the same by measuring the noise. Suitable jury evaluation method was selected for the said activity, and recorded sounds were replayed for jury rating. Objective data sound quality metrics viz., loudness, sharpness, roughness, fluctuation strength and overall Sound Pressure Level (SPL) were measured. Based on this, correlation co-efficients was established to identify the most relevant sound quality metrics that are contributing to particular identified noise issue. Regression analysis was then performed to establish the correlation between subjective and objective data. Mathematical model was prepared using artificial intelligence and machine learning algorithm. The developed model was able to predict the subjective rating with good accuracy.

Keywords: BSR, noise, correlation, regression

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3182 An Investigation of Commitment to Marital Relationship Precedents through Self-Expansion in Students from the Medical Science University of Iran

Authors: Mehravar Javid, Laura Reid Harris, Zahra Khodadadi, Rachel Walton

Abstract:

The study aimed to explore commitment precedence through self-expansion among students at the Medical Science University of Shiraz, Iran. Method: The statistical population was comprised of students at Shiraz University of Medical Science during the academic years 2013 to 2014. Using random sampling, 133 married students (50 males and 83 females) were selected. The commitment condition of this studied group was assessed using Adam and Jones' (1999) Marital Commitment Dimensions Scale (DCI), and self-expansion was measured using Aron and Lewandowski's (2002) Self-Expansion Questionnaire. Simple regression analyses investigated commitment precedence via self-expansion. Results: The data revealed a positive correlation between total commitment (r=0.35, p < 0.01), the subscales of commitment to the spouse (r=0.43, p < 0.01), and commitment to marriage (r=0.31, p < 0.01). Regression analyses indicated that perceived self-expansion positively correlated with commitment to marital relationships in married students. The findings suggest that an increased possibility of self-expansion in a marital relationship corresponds with heightened commitment.

Keywords: commitment to marital relationship, married students, relationship dynamics, self-expansion

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3181 Food Insecurity Assessment, Consumption Pattern and Implications of Integrated Food Security Phase Classification: Evidence from Sudan

Authors: Ahmed A. A. Fadol, Guangji Tong, Wlaa Mohamed

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This paper provides a comprehensive analysis of food insecurity in Sudan, focusing on consumption patterns and their implications, employing the Integrated Food Security Phase Classification (IPC) assessment framework. Years of conflict and economic instability have driven large segments of the population in Sudan into crisis levels of acute food insecurity according to the (IPC). A substantial number of people are estimated to currently face emergency conditions, with an additional sizeable portion categorized under less severe but still extreme hunger levels. In this study, we explore the multifaceted nature of food insecurity in Sudan, considering its historical, political, economic, and social dimensions. An analysis of consumption patterns and trends was conducted, taking into account cultural influences, dietary shifts, and demographic changes. Furthermore, we employ logistic regression and random forest analysis to identify significant independent variables influencing food security status in Sudan. Random forest clearly outperforms logistic regression in terms of area under curve (AUC), accuracy, precision and recall. Forward projections of the IPC for Sudan estimate that 15 million individuals are anticipated to face Crisis level (IPC Phase 3) or worse acute food insecurity conditions between October 2023 and February 2024. Of this, 60% are concentrated in Greater Darfur, Greater Kordofan, and Khartoum State, with Greater Darfur alone representing 29% of this total. These findings emphasize the urgent need for both short-term humanitarian aid and long-term strategies to address Sudan's deepening food insecurity crisis.

Keywords: food insecurity, consumption patterns, logistic regression, random forest analysis

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3180 Full Mini Nutritional Assessment Questionnaire and the Risk of Malnutrition and Mortality in Elderly, Hospitalized Patients: A Cross-Sectional Study

Authors: Christos E. Lampropoulos, Maria Konsta, Tamta Sirbilatze, Ifigenia Apostolou, Vicky Dradaki, Konstantina Panouria, Irini Dri, Christina Kordali, Vaggelis Lambas, Georgios Mavras

Abstract:

Objectives: Full Mini Nutritional Assessment (MNA) questionnaire is one of the most useful tools in diagnosis of malnutrition in hospitalized patients, which is related to increased morbidity and mortality. The purpose of our study was to assess the nutritional status of elderly, hospitalized patients and examine the hypothesis that MNA may predict mortality and extension of hospitalization. Methods: One hundred fifty patients (78 men, 72 women, mean age 80±8.2) were included in this cross-sectional study. The following data were taken into account in analysis: anthropometric and laboratory data, physical activity (International Physical Activity Questionnaires, IPAQ), smoking status, dietary habits, cause and duration of current admission, medical history (co-morbidities, previous admissions). Primary endpoints were mortality (from admission until 6 months afterwards) and duration of admission. The latter was compared to national guidelines for closed consolidated medical expenses. Logistic regression and linear regression analysis were performed in order to identify independent predictors for mortality and extended hospitalization respectively. Results: According to MNA, nutrition was normal in 54/150 (36%) of patients, 46/150 (30.7%) of them were at risk of malnutrition and the rest 50/150 (33.3%) were malnourished. After performing multivariate logistic regression analysis we found that the odds of death decreased 20% per each unit increase of full MNA score (OR=0.8, 95% CI 0.74-0.89, p < 0.0001). Patients who admitted due to cancer were 23 times more likely to die, compared to those with infection (OR=23, 95% CI 3.8-141.6, p=0.001). Similarly, patients who admitted due to stroke were 7 times more likely to die (OR=7, 95% CI 1.4-34.5, p=0.02), while these with all other causes of admission were less likely (OR=0.2, 95% CI 0.06-0.8, p=0.03), compared to patients with infection. According to multivariate linear regression analysis, each increase of unit of full MNA, decreased the admission duration on average 0.3 days (b:-0.3, 95% CI -0.45 - -0.15, p < 0.0001). Patients admitted due to cancer had on average 6.8 days higher extension of hospitalization, compared to those admitted for infection (b:6.8, 95% CI 3.2-10.3, p < 0.0001). Conclusion: Mortality and extension of hospitalization is significantly increased in elderly, malnourished patients. Full MNA score is a useful diagnostic tool of malnutrition.

Keywords: duration of admission, malnutrition, mini nutritional assessment score, prognostic factors for mortality

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3179 Estimation of Coefficient of Discharge of Side Trapezoidal Labyrinth Weir Using Group Method of Data Handling Technique

Authors: M. A. Ansari, A. Hussain, A. Uddin

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A side weir is a flow diversion structure provided in the side wall of a channel to divert water from the main channel to a branch channel. The trapezoidal labyrinth weir is a special type of weir in which crest length of the weir is increased to pass higher discharge. Experimental and numerical studies related to the coefficient of discharge of trapezoidal labyrinth weir in an open channel have been presented in the present study. Group Method of Data Handling (GMDH) with the transfer function of quadratic polynomial has been used to predict the coefficient of discharge for the side trapezoidal labyrinth weir. A new model is developed for coefficient of discharge of labyrinth weir by regression method. Generalized models for predicting the coefficient of discharge for labyrinth weir using Group Method of Data Handling (GMDH) network have also been developed. The prediction based on GMDH model is more satisfactory than those given by traditional regression equations.

Keywords: discharge coefficient, group method of data handling, open channel, side labyrinth weir

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3178 Analysis of Labor Behavior Effect on Occupational Health and Safety Management by Multiple Linear Regression

Authors: Yulinda Rizky Pratiwi, Fuji Anugrah Emily

Abstract:

Management of Occupational Safety and Health (OSH) are appropriately applied properly by all workers and pekarya in the company. K3 management application also has become very important to prevent accidents. Violation of the rules regarding the K3 has often occurred from time to time. By 2015 the number of occurrences of a violation of the K3 or so-called unsafe action tends to increase. Until finally in January 2016, the number increased drastically unsafe action. Trigger increase in the number of unsafe action is a decrease in the quality of management practices K3. While the application of K3 management performed by each individual thought to be influenced by the attitude and observation guide the actions of each of the individual. In addition to the decline in the quality of K3 management application may result in increased likelihood of accidents and losses for the company as well as the local co-workers. The big difference in the number of unsafe action is very significant in the month of January 2016, making the company Pertamina as the national oil company must do a lot of effort to keep track of how the implementation of K3 management on every worker and pekarya, one at PT Pertamina EP Cepu Field Asset IV. To consider the effort to control the implementation of K3 management can be seen from the attitude and observation guide the actions of the workers and pekarya. By using Multiple Linear Regression can be seen the influence of attitude and action observation guide workers and pekarya the K3 management application that has been done. The results showed that scores K3 management application of each worker and pekarya will increase by 0.764 if the score pekarya worker attitudes and increase one unit, whereas if the score Reassurance action guidelines and pekarya workers increased by one unit then the score management application K3 will increase by 0.754.

Keywords: occupational safety and health, management of occupational safety and health, unsafe action, multiple linear regression

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3177 Sustainability Assessment of Food Delivery with Last-Mile Delivery Droids, A Case Study at the European Commission's JRC Ispra Site

Authors: Ada Garus

Abstract:

This paper presents the outcomes of the sustainability assessment of food delivery with a last-mile delivery service introduced in a real-world case study. The methodology used in the sustainability assessment integrates multi-criteria decision-making analysis, sustainability pillars, and scenario analysis to best reflect the conflicting needs of stakeholders involved in the last mile delivery system. The case study provides an application of the framework to the food delivery system of the Joint Research Centre of the European Commission where three alternative solutions were analyzed I) the existent state in which individuals frequent the local cantine or pick up their food, using their preferred mode of transport II) the hypothetical scenario in which individuals can only order their food using the delivery droid system III) a scenario in which the food delivery droid based system is introduced as a supplement to the current system. The environmental indices are calculated using a simulation study in which decision regarding the food delivery is predicted using a multinomial logit model. The vehicle dynamics model is used to predict the fuel consumption of the regular combustion engines vehicles used by the cantine goers and the electricity consumption of the droid. The sustainability assessment allows for the evaluation of the economic, environmental, and social aspects of food delivery, making it an apt input for policymakers. Moreover, the assessment is one of the first studies to investigate automated delivery droids, which could become a frequent addition to the urban landscape in the near future.

Keywords: innovations in transportation technologies, behavioural change and mobility, urban freight logistics, innovative transportation systems

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3176 Predictors of School Safety Awareness among Malaysian Primary School Teachers

Authors: Ssekamanya, Mastura Badzis, Khamsiah Ismail, Dayang Shuzaidah Bt Abduludin

Abstract:

With rising incidents of school violence worldwide, educators and researchers are trying to understand and find ways to enhance the safety of children at school. The purpose of this study was to investigate the extent to which the demographic variables of gender, age, length of service, position, academic qualification, and school location predicted teachers’ awareness about school safety practices in Malaysian primary schools. A stratified random sample of 380 teachers was selected in the central Malaysian states of Kuala Lumpur and Selangor. Multiple regression analysis revealed that none of the factors was a good predictor of awareness about school safety training, delivery methods of school safety information, and available school safety programs. Awareness about school safety activities was significantly predicted by school location (whether the school was located in a rural or urban area). While these results may reflect a general lack of awareness about school safety among primary school teachers in the selected locations, a national study needs to be conducted for the whole country.

Keywords: school safety awareness, predictors of school safety, multiple regression analysis, malaysian primary schools

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3175 Assessment of Soil Salinity through Remote Sensing Technique in the Coastal Region of Bangladesh

Authors: B. Hossen, Y. Helmut

Abstract:

Soil salinity is a major problem for the coastal region of Bangladesh, which has been increasing for the last four decades. Determination of soil salinity is essential for proper land use planning for agricultural crop production. The aim of the research is to estimate and monitor the soil salinity in the study area. Remote sensing can be an effective tool for detecting soil salinity in data-scarce conditions. In the research, Landsat 8 is used, which required atmospheric and radiometric correction, and nine soil salinity indices are applied to develop a soil salinity map. Ground soil salinity data, i.e., EC value, is collected as a printed map which is then scanned and digitized to develop a point shapefile. Linear regression is made between satellite-based generated map and ground soil salinity data, i.e., EC value. The results show that maximum R² value is found for salinity index SI 7 = G*R/B representing 0.022. This minimal R² value refers that there is a negligible relationship between ground EC value and salinity index generated value. Hence, these indices are not appropriate to assess soil salinity though many studies used those soil salinity indices successfully. Therefore, further research is necessary to formulate a model for determining the soil salinity in the coastal of Bangladesh.

Keywords: soil salinity, EC, Landsat 8, salinity indices, linear regression, remote sensing

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3174 The Olympic Games’ Effect on National Company Growth

Authors: Simon Strande Henriksen

Abstract:

When a city and country decide to undertake an Olympic Games, they do so with the notion that hosting the Olympics will provide direct financial benefits to the city, country, and national companies. Like many activities, the Olympic Games tend to be more popular when it is warm, and the athletes are known, and therefore this paper will only focus on the two latest Olympic Summer Games. Cities and countries continue to invest billions of dollars in infrastructure to secure the role of being Olympic hosts. The multiple investments expect to provide both economic growth and a lasting legacy for the citizens. This study aims to determine whether host country companies experience superior economic impact from the Olympics. Building on existing work within the Olympic field of research, it asks: Do companies in host countries of the Olympic Summer Games experience a superior increase in operating revenue and return on assets compared to other comparable countries? In this context, comparable countries are the two candidates following the host city in the bidding procedure. Based on methods used by scholars, a panel data regression was conducted on revenue growth rate and return on assets, to determine if host country companies see a positive relation with hosting the Olympic Games. Combined with an analysis of motivation behind hosting the Olympics, the regression showed no significant positive relations across all analyses, besides in one instance. Indications of a relationship between company performance and economic motivation were found to be present. With the results indicating a limited effect on company growth, it is recommended that prospective host cities and countries carefully consider possible implications the role of being an Olympic host might have on national companies.

Keywords: cross-country analysis, mega-event, multiple regression, quantitative analysis

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3173 Proportion and Factors Associated with Presumptive Tuberculosis among Suspected Pediatric Tuberculosis Patients

Authors: Naima Nur, Safa Islam, Saeema Islam, Md. Faridul Alam

Abstract:

Background: The worldwide increase in pediatric presumptive tuberculosis (TB) is the most life-threatening challenge in effectively controlling TB. The objective of this study was to determine the proportion of presumptive TB and the factors associated with it. Methods: A cross-sectional study was conducted between March and November 2013 at ICDDR-Bangladesh. Two hundred twelve pulmonary and extra-pulmonary specimens were collected from 84 suspected pediatric patients diagnosed with TB based on their clinical symptoms/radiological findings. Presumptive TB and confirmed TB were considered presumptive TB and non-presumptive TB and were isolated by smear-microscopy, culture, and GeneXpert. Logistic regression was used to analyze associations between outcome and predictor variables. Results: The proportion of presumptive TB was 85.7%, and 14.3% of non-presumptive TB. In presumptive TB, vaccine scars, family TB history, and school-going children were 16.6%, 33.3%, and 56.9%, respectively. In contrast, vaccine scars and family TB history were 8.3%, and school-going children were 58.3% in non-presumptive TB. Significant factors did not appear in the logistic regression analysis. Conclusion: Despite the high proportion of presumptive TB, there was no statistically significant between presumptive TB and non-presumptive TB.

Keywords: presumptive tuberculosis, confirmed tuberculosis, patient's characteristics, diagnosis

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3172 A Medical Resource Forecasting Model for Emergency Room Patients with Acute Hepatitis

Authors: R. J. Kuo, W. C. Cheng, W. C. Lien, T. J. Yang

Abstract:

Taiwan is a hyper endemic area for the Hepatitis B virus (HBV). The estimated total number of HBsAg carriers in the general population who are more than 20 years old is more than 3 million. Therefore, a case record review is conducted from January 2003 to June 2007 for all patients with a diagnosis of acute hepatitis who were admitted to the Emergency Department (ED) of a well-known teaching hospital. The cost for the use of medical resources is defined as the total medical fee. In this study, principal component analysis (PCA) is firstly employed to reduce the number of dimensions. Support vector regression (SVR) and artificial neural network (ANN) are then used to develop the forecasting model. A total of 117 patients meet the inclusion criteria. 61% patients involved in this study are hepatitis B related. The computational result shows that the proposed PCA-SVR model has superior performance than other compared algorithms. In conclusion, the Child-Pugh score and echogram can both be used to predict the cost of medical resources for patients with acute hepatitis in the ED.

Keywords: acute hepatitis, medical resource cost, artificial neural network, support vector regression

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3171 Credit Risk and Financial Stability

Authors: Zidane Abderrezzaq

Abstract:

In contrast to recent successful developments in macro monetary policies, the modelling, measurement and management of systemic financial stability has remained problematical. Indeed, the focus of most effort has been on improving individual, rather than systemic, bank risk management; the Basel II objective has been to bring regulatory bank capital into line with the (sophisticated) banks’ assessment of their own economic capital. Even at the individual bank level there are concerns over appropriate diversification allowances, differing objectives of banks and regulators, the need for a buffer over regulatory minima, and the distinction between expected and unexpected losses (EL and UL). At the systemic level the quite complex and prescriptive content of Basel II raises dangers of ‘endogenous risk’ and procyclicality. Simulations suggest that this latter could be a serious problem. In an extension to the main analysis we study how liquidity effects interact with banking structure to produce a greater chance of systemic breakdown. We finally consider how the risk of contagion might depend on the degree of asymmetry (tiering) inherent in the structure of the banking system. A number of our results have important implications for public policy, which this paper also draws out.

Keywords: systemic stability, financial regulation, credit risk, systemic risk

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3170 Retirement and Tourism Consumption - Evidence from the Elderly in China

Authors: Sha Fan, Renuka Mahadevan

Abstract:

In recent years, the subject of how retirement influences consumption behaviours has garnered attention in economic research. However, a significant gap persists in our understanding of how retirement precisely impacts tourism consumption patterns among the elderly demographic. To address this gap, this research conducts an in-depth exploration into the multifaceted relationship between retirement and elderly tourism consumption.To achieve this, the study employs regression discontinuity design, using three waves of panel data from China covering a span of six years. This approach aims to identify the causality between retirement and tourism consumption. Furthermore, the study scrutinizes the pathways through which retirement's impact on tourism consumption unfolds. It adopts a dual-pronged perspective, examining the roles played by economic status and the availability of leisure time. The economic dimension underscores the financial adjustments that retirees make as they transition into a new phase of life, impacting their propensity to allocate resources towards tourism activities. Meanwhile, considering leisure time recognizes that retirement often heralds an era of newfound freedom, allowing retirees the luxury to engage in leisurely pursuits like tourism.

Keywords: tourism consumption, retirement, the elderly, regression discontinuity design

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