Search results for: nonlinear logistic regression
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4656

Search results for: nonlinear logistic regression

1206 Achieving Competitive Advantage Through Internal Resources and Competences

Authors: Ibrahim Alkandi

Abstract:

This study aims at understanding how banks can utilize their resources and capabilities to achieve a competitive advantage. The resource-based approach has been applied to assess the resources and capabilities as well as how the management perceives them as sources of competitive advantages. A quantitative approach was implemented using cross-sectional data. The research population consisted of Top managers in financial companies in Saudi Arabia, and the sample comprised 79 managers. The resources were sub divided into tangible and intangible. Among the variables that will be assessed in the research include propriety rights, trademark which is the brand, communication as well as organizational culture. To achieve the objective of the research, Multivariate analysis through multiple regression was used. The research tool used is a questionnaire whose validity is also assessed. According to the results of the study, there is a significant relationship between bank’s performance and the strategic management of propriety rights, trademark, administrative and financial skills as well as bank culture. Therefore, the research assessed four aspects, among the variables in the model, in relation to the strategic performance of these banks. The aspects considered were trademark, communication, administrative and leadership style as well as the company’s culture. Hence, this paper contributes to the body of literature by providing empirical evidence of the resources influencing both banks’ market and economic performance.

Keywords: competitive advantage, Saudi banks, strategic management, RBV

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1205 Efficient Principal Components Estimation of Large Factor Models

Authors: Rachida Ouysse

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This paper proposes a constrained principal components (CnPC) estimator for efficient estimation of large-dimensional factor models when errors are cross sectionally correlated and the number of cross-sections (N) may be larger than the number of observations (T). Although principal components (PC) method is consistent for any path of the panel dimensions, it is inefficient as the errors are treated to be homoskedastic and uncorrelated. The new CnPC exploits the assumption of bounded cross-sectional dependence, which defines Chamberlain and Rothschild’s (1983) approximate factor structure, as an explicit constraint and solves a constrained PC problem. The CnPC method is computationally equivalent to the PC method applied to a regularized form of the data covariance matrix. Unlike maximum likelihood type methods, the CnPC method does not require inverting a large covariance matrix and thus is valid for panels with N ≥ T. The paper derives a convergence rate and an asymptotic normality result for the CnPC estimators of the common factors. We provide feasible estimators and show in a simulation study that they are more accurate than the PC estimator, especially for panels with N larger than T, and the generalized PC type estimators, especially for panels with N almost as large as T.

Keywords: high dimensionality, unknown factors, principal components, cross-sectional correlation, shrinkage regression, regularization, pseudo-out-of-sample forecasting

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1204 Life Course Events, Residential and Job Relocation and Commute Time in Australian Cities

Authors: Solmaz Jahed Shiran, Elizabeth Taylor, John Hearne

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Over the past decade a growing body of research, known as mobility biography approach has emerged that focuses on changes in travel behaviour over the life course of individuals. Mobility biographies suggest that changes in travel behaviour have a certain relation to important key events in life courses such as residential relocation, workplace changes, marriage and the birth of children. Taking this approach as the theoretical background, this study uses data from the Household, Income and Labor Dynamics Survey in Australia (HILDA) to model a set of life course events and their interaction with the commute time. By analysing longitudinal data, it is possible to assign different key events during the life course to change a person’s travel behaviour. Changes in the journey-to-work travel time is used as an indication of travel behaviour change in this study. Results of a linear regression model for change in commute time show a significant influence from socio-demographic factors like income and age, the previous home-to-work commute time and remoteness of the residence. Residential relocation and job change have significant influences on commute time. Other life events such as birth of a child, marriage and divorce or separation have also a strong impact on commute time change. Overall, the research confirms previous studies of links between life course events and travel behaviour.

Keywords: life course events, residential mobility, travel behaviour, commute time, job change

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1203 Kirchoff Type Equation Involving the p-Laplacian on the Sierpinski Gasket Using Nehari Manifold Technique

Authors: Abhilash Sahu, Amit Priyadarshi

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In this paper, we will discuss the existence of weak solutions of the Kirchhoff type boundary value problem on the Sierpinski gasket. Where S denotes the Sierpinski gasket in R² and S₀ is the intrinsic boundary of the Sierpinski gasket. M: R → R is a positive function and h: S × R → R is a suitable function which is a part of our main equation. ∆p denotes the p-Laplacian, where p > 1. First of all, we will define a weak solution for our problem and then we will show the existence of at least two solutions for the above problem under suitable conditions. There is no well-known concept of a generalized derivative of a function on a fractal domain. Recently, the notion of differential operators such as the Laplacian and the p-Laplacian on fractal domains has been defined. We recall the result first then we will address the above problem. In view of literature, Laplacian and p-Laplacian equations are studied extensively on regular domains (open connected domains) in contrast to fractal domains. In fractal domains, people have studied Laplacian equations more than p-Laplacian probably because in that case, the corresponding function space is reflexive and many minimax theorems which work for regular domains is applicable there which is not the case for the p-Laplacian. This motivates us to study equations involving p-Laplacian on the Sierpinski gasket. Problems on fractal domains lead to nonlinear models such as reaction-diffusion equations on fractals, problems on elastic fractal media and fluid flow through fractal regions etc. We have studied the above p-Laplacian equations on the Sierpinski gasket using fibering map technique on the Nehari manifold. Many authors have studied the Laplacian and p-Laplacian equations on regular domains using this Nehari manifold technique. In general Euler functional associated with such a problem is Frechet or Gateaux differentiable. So, a critical point becomes a solution to the problem. Also, the function space they consider is reflexive and hence we can extract a weakly convergent subsequence from a bounded sequence. But in our case neither the Euler functional is differentiable nor the function space is known to be reflexive. Overcoming these issues we are still able to prove the existence of at least two solutions of the given equation.

Keywords: Euler functional, p-Laplacian, p-energy, Sierpinski gasket, weak solution

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1202 Characterization and Predictors of Community Integration of People with Psychiatric Problems: Comparisons with the General Population

Authors: J. Cabral, C. Barreto Carvalho, C. da Motta, M. Sousa

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Community integration is a construct that an increasing body of research has shown to have a significant impact in well-being and recovery of people with psychiatric problems. However, there are few studies that explore which factors can be associated and predict community integration. Moreover, community integration has been mostly studied in minority groups, and currently literature on the definition and manifestation of community integration in the more general population is scarce. Thus, the current study aims to characterize community integration and explore possible predictor variables in a sample of participants with psychiatric problems (PP, N=183) and a sample of participants from the general population (GP, N=211). Results show that people with psychiatric problems present above average values of community integration, but are significantly lower than their healthy counterparts. It was also possible to observe that community integration does not vary in terms of the socio-demographic characteristics of both groups in this study. Correlation and multiple regression showed that, among several variables that literature present as relevant in the community integration process, only three variables emerged as having the most explanatory value in community integration of both groups: sense of community, basic needs satisfaction and submission. These results also shown that those variables have increased explanatory power in the PP sample, which leads us to emphasize the need to address this issue in future studies and increase the understanding of the factors that can be involved in the promotion of community integration, in order to devise more effective interventions in this field.

Keywords: community integration, mental illness, predictors, psychiatric problems

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1201 The Determinants of the Operational Performance in Airline Industry: A Case of a Turkish Airline Company

Authors: Mustafa K. Yilmaz, Ahmet Kaplan, Murat Guven, Vildan Kesici

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Aviation industry influences the social and economic growth across the countries. Further, airline companies are highly affected by social, political, and financial crises and show a high degree of cyclicity in operational performance. Hence, this paper investigates the effects of available seat kilometers (ASK), revenue per kilometer (RPK), passenger load factor (PLF) as well as socio-political crisis on the number of passengers carried (PC) by Turkish Airlines company over the period of 2010M1-2018M12. To conduct the analysis, we employ fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), and canonical cointegration regression (CCR) techniques using monthly data. We use ASK, RPK, PLF as independent variables to identify the determinants of the PC, as a dependent variable. We also test the effect of the socio-political crisis. The results reveal that there is a significant and negative relationship between ASK and PC, while the relationship between RPK and PC is positive and significant. We also find that there is an insignificant relationship between PLF and PC. Further, we also find a negative effect of the crisis on the PC. These findings show although the crisis had an immediate effect on the operational performance of Turkish Airlines, the company recovered from the crisis and cope with the situation very promptly. Thus, this proves the resilience and agile management ability of the company.

Keywords: airline industry, operational performance, air traffic, socio-political crisis

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1200 Simulation of Soil-Pile Interaction of Steel Batter Piles Penetrated in Sandy Soil Subjected to Pull-Out Loads

Authors: Ameer A. Jebur, William Atherton, Rafid M. Alkhaddar, Edward Loffill

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Superstructures like offshore platforms, tall buildings, transition towers, skyscrapers and bridges are normally designed to resist compression, uplift and lateral forces from wind waves, negative skin friction, ship impact and other applied loads. Better understanding and the precise simulation of the response of batter piles under the action of independent uplift loads is a vital topic and an area of active research in the field of geotechnical engineering. This paper investigates the use of finite element code (FEC) to examine the behaviour of model batter piles penetrated in dense sand, subjected to pull-out pressure by means of numerical modelling. The concept of the Winkler Model (beam on elastic foundation) has been used in which the interaction between the pile embedded depth and adjacent soil in the bearing zone is simulated by nonlinear p-y curves. The analysis was conducted on different pile slenderness ratios (lc⁄d) ranging from 7.5, 15.22 and 30 respectively. In addition, the optimum batter angle for a model steel pile penetrated in dense sand has been chosen to be 20° as this is the best angle for this simulation as demonstrated by other researcher published in literature. In this numerical analysis, the soil response is idealized as elasto-plastic and the model piles are described as elastic materials for the purpose of simulation. The results revealed that the applied loads affect the pullout pile capacity as well as the lateral pile response for dense sand together with varying shear strength parameters linked to the pile critical depth. Furthermore, the pile pull-out capacity increases with increasing the pile aspect ratios.

Keywords: slenderness ratio, soil-pile interaction, winkler model (beam on elastic foundation), pull-out capacity

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1199 The Effect of Artificial Intelligence on the Production of Agricultural Lands and Labor

Authors: Ibrahim Makram Ibrahim Salib

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Agriculture plays an essential role in providing food for the world's population. It also offers numerous benefits to countries, including non-food products, transportation, and environmental balance. Precision agriculture, which employs advanced tools to monitor variability and manage inputs, can help achieve these benefits. The increasing demand for food security puts pressure on decision-makers to ensure sufficient food production worldwide. To support sustainable agriculture, unmanned aerial vehicles (UAVs) can be utilized to manage farms and increase yields. This paper aims to provide an understanding of UAV usage and its applications in agriculture. The objective is to review the various applications of UAVs in agriculture. Based on a comprehensive review of existing research, it was found that different sensors provide varying analyses for agriculture applications. Therefore, the purpose of the project must be determined before using UAV technology for better data quality and analysis. In conclusion, identifying a suitable sensor and UAV is crucial to gather accurate data and precise analysis when using UAVs in agriculture.

Keywords: agriculture land, agriculture land loss, Kabul city, urban land expansion, urbanization agriculture yield growth, agriculture yield prediction, explorative data analysis, predictive models, regression models drone, precision agriculture, farmer income

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1198 Drying Kinects of Soybean Seeds

Authors: Amanda Rithieli Pereira Dos Santos, Rute Quelvia De Faria, Álvaro De Oliveira Cardoso, Anderson Rodrigo Da Silva, Érica Leão Fernandes Araújo

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The study of the kinetics of drying has great importance for the mathematical modeling, allowing to know about the processes of transference of heat and mass between the products and to adjust dryers managing new technologies for these processes. The present work had the objective of studying the kinetics of drying of soybean seeds and adjusting different statistical models to the experimental data varying cultivar and temperature. Soybean seeds were pre-dried in a natural environment in order to reduce and homogenize the water content to the level of 14% (b.s.). Then, drying was carried out in a forced air circulation oven at controlled temperatures of 38, 43, 48, 53 and 58 ± 1 ° C, using two soybean cultivars, BRS 8780 and Sambaíba, until reaching a hygroscopic equilibrium. The experimental design was completely randomized in factorial 5 x 2 (temperature x cultivar) with 3 replicates. To the experimental data were adjusted eleven statistical models used to explain the drying process of agricultural products. Regression analysis was performed using the least squares Gauss-Newton algorithm to estimate the parameters. The degree of adjustment was evaluated from the analysis of the coefficient of determination (R²), the adjusted coefficient of determination (R² Aj.) And the standard error (S.E). The models that best represent the drying kinetics of soybean seeds are those of Midilli and Logarítmico.

Keywords: curve of drying seeds, Glycine max L., moisture ratio, statistical models

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1197 The Impact of Perception of Transformational Leadership and Factors of Innovation Culture on Innovative Work Behavior in Junior High School's Teacher

Authors: Galih Mediana

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Boarding school can helps students to turn all good qualities into habits. The process of forming one's personality can be done in various ways. In addition to gaining general knowledge at school during learning hours, teachers can instill values in students which can be done while in the dormitory when the learning process has ended. This shows the important role that must be played by boarding school’s teachers. Transformational leadership and a culture of innovation are things that can instill innovative behavior in teachers. This study aims to determine the effect of perceptions of transformational leadership and a culture of innovation on innovative work behavior among Islamic boarding school teachers. Respondents in this study amounted to 70 teachers. To measure transformational leadership, a modified measuring tool is used, namely the Multifactor Leadership Questionnaire (MLQ) by Bass (1985). To measure innovative work behavior, a measurement tool based on dimensions from Janssen (2000) is used. The innovation culture in this study will be measured using the innovation culture factor from Dobni (2008). This study uses multiple regression analysis to test the hypothesis. The results of this study indicate that there is an influence of perceptions of transformational leadership and innovation culture factors on innovative work behavior in Islamic boarding school’s teachers by 57.7%.

Keywords: transformational leadership, innovative work behavior, innovation culture, boarding school, teacher

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1196 The Impact of Resource-oriented Music Listening on Oversea Dispatch Employees Work Stress Relief

Authors: Wei Yaming

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Objective: In order to compare the stress of employees sent overseas with (GRAS) before and after, we used the resource-oriented music listening intervention in this study. We also collected pertinent experimental data. Methods: The experiment involved 47 employees who were sent abroad by the Chinese side. They completed the stress scale test and documented it before the intervention. They tested for stress after five interventions and performed one-on-one interviews. Quantitative data and SPSS software were used to analyze relationships between stress reduction and resource-oriented music listening, as well as Pearson's correlation, multiple regression levels, and ANOVA. For the qualitative analysis, content analysis of one-on-one interviews was performed. Results: A comparison of data from before and after demonstrates how resource-focused music listening activities can lessen and relieve stress in remote workers. In the qualitative study, stress is broken down into six categories: relationship stress, health stress, emotional stress, and frustration stress. External pressures include work pressure and cultural stress. And it has been determined that listening to music that is resource-oriented can better ease internal stress (health, emotion, and dissatisfaction). Conclusion: The Guide Resource-oriented Music Listening (GROML) Program appears to have had some effect on the participants' stress levels. The resources that the participants encountered while listening to music are bravery, calm, letting go, and relaxing.

Keywords: resource-oriented, music listening, oversea dispatch employees, work stress

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1195 Simulation of Hydrogenated Boron Nitride Nanotube’s Mechanical Properties for Radiation Shielding Applications

Authors: Joseph E. Estevez, Mahdi Ghazizadeh, James G. Ryan, Ajit D. Kelkar

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Radiation shielding is an obstacle in long duration space exploration. Boron Nitride Nanotubes (BNNTs) have attracted attention as an additive to radiation shielding material due to B10’s large neutron capture cross section. The B10 has an effective neutron capture cross section suitable for low energy neutrons ranging from 10-5 to 104 eV and hydrogen is effective at slowing down high energy neutrons. Hydrogenated BNNTs are potentially an ideal nanofiller for radiation shielding composites. We use Molecular Dynamics (MD) Simulation via Material Studios Accelrys 6.0 to model the Young’s Modulus of Hydrogenated BNNTs. An extrapolation technique was employed to determine the Young’s Modulus due to the deformation of the nanostructure at its theoretical density. A linear regression was used to extrapolate the data to the theoretical density of 2.62g/cm3. Simulation data shows that the hydrogenated BNNTs will experience a 11% decrease in the Young’s Modulus for (6,6) BNNTs and 8.5% decrease for (8,8) BNNTs compared to non-hydrogenated BNNT’s. Hydrogenated BNNTs are a viable option as a nanofiller for radiation shielding nanocomposite materials for long range and long duration space exploration.

Keywords: boron nitride nanotube, radiation shielding, young modulus, atomistic modeling

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1194 Optimization of Poly-β-Hydroxybutyrate Recovery from Bacillus Subtilis Using Solvent Extraction Process by Response Surface Methodology

Authors: Jayprakash Yadav, Nivedita Patra

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Polyhydroxybutyrate (PHB) is an interesting material in the field of medical science, pharmaceutical industries, and tissue engineering because of its properties such as biodegradability, biocompatibility, hydrophobicity, and elasticity. PHB is naturally accumulated by several microbes in their cytoplasm during the metabolic process as energy reserve material. PHB can be extracted from cell biomass using halogenated hydrocarbons, chemicals, and enzymes. In this study, a cheaper and non-toxic solvent, acetone, was used for the extraction process. The different parameters like acetone percentage, and solvent pH, process temperature, and incubation periods were optimized using the Response Surface Methodology (RSM). RSM was performed and the determination coefficient (R2) value was found to be 0.8833 from the quadratic regression model with no significant lack of fit. The designed RSM model results indicated that the fitness of the response variable was significant (P-value < 0.0006) and satisfactory to denote the relationship between the responses in terms of PHB recovery and purity with respect to the values of independent variables. Optimum conditions for the maximum PHB recovery and purity were found to be solvent pH 7, extraction temperature - 43 °C, incubation time - 70 minutes, and percentage acetone – 30 % from this study. The maximum predicted PHB recovery was found to be 0.845 g/g biomass dry cell weight and the purity was found to be 97.23 % using the optimized conditions.

Keywords: acetone, PHB, RSM, halogenated hydrocarbons, extraction, bacillus subtilis.

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1193 Examining Motivational Strategies of Foreign Manufacturing Firms in Ghana

Authors: Samuel Ato Dadzie

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The objective of this study is to examine the influence of eclectic paradigm on motivational strategy of foreign subsidiaries in Ghana. This study uses binary regression model, and the analysis was based on 75 manufacturing investments made by MNEs from different countries in 1994–2008. The results indicated that perceived market size increases the probability of foreign firms undertaking a market seeking (MS) in Ghana, while perceived cultural distance between Ghana and foreign firm’s home countries decreased the probability of foreign firms undertaking an market seeking (MS) foreign direct investment (FDI) in Ghana. Furthermore, extensive international experience decreases the probability of foreign firms undertaking a market seeking (MS) foreign direct investment (FDI) in Ghana. Most of the studies done by earlier researchers were based on the advanced and emerging countries and offered support for the theory, which was used in generalizing the result that multinational corporations (MNCs) normally used the theory regarding investment strategy outside their home country. In using the same theory in the context of Ghana, the result does not offer strong support for the theory. This means that MNCs that come to Sub-Sahara Africa cannot rely much on eclectic paradigm for their motivational strategies because prevailing economic conditions in Ghana are different from that of the advanced and emerging economies where the institutional structures work.

Keywords: foreign subsidiary, motives, Ghana, foreign direct investment

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1192 Influence of Some Psychological Factors on the Learning Gains of Distance Learners in Mathematics in Ibadan, Nigeria

Authors: Adeola Adejumo, Oluwole David Adebayo, Muraina Kamilu Olanrewaju

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The purpose of this study was to investigate the influence of some psychological factors (i.e, school climate, parental involvement and classroom interaction) on the learning gains of university undergraduates in Mathematics in Ibadan, Nigeria. Three hundred undergraduates who are on open distance learning education programme in the University of Ibadan and thirty mathematics lecturers constituted the study’s sample. Both the independent and dependent variables were measured with relevant standardized instruments and the data obtained was analyzed using multiple regression statistical method. The instruments used were school climate scale, parental involvement scale and classroom interaction scale. Three research questions were answered in the study. The result showed that there was significant relationship between the three independent variables (school climate, parental involvement and classroom interaction) on the students’ learning gain in mathematics and that the independent variables both jointly and relatively contributed significantly to the prediction of students’ learning gain in mathematics. On the strength of these findings, the need to enhance the school climate, improve the parents’ involvement in the student’s education and encourage students’ classroom interaction were stressed and advocated.

Keywords: school climate, parental involvement, ODL, learning gains, mathematics

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1191 The Role of High Performance Liquid Chromatography in Identification of Rat Liver Microsomes Responsible for the in vitro Metabolite Formation of Dipyrone

Authors: Salem Abdalla

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Objective: Dipyrone is a widely used, well tolerated analgesic drug which, however, is compromised by agranulocytosis as an adverse effect. Subsequent to no enzymatic hydrolysis, the primary metabolic step is N-demethylation of 4-methylaminoantipyrine (4-MAA) to 4-aminoantipyrine (4-AA). The aim of the present study was to identify the cytochrome P-450 enzyme (CYP) mediating this reaction. Methods: We identified the relevant CYP using virus expressed isolated rat liver microsomes with chemical inhibition studies. The substrate of 4-methylaminantipyrine was employed at six different concentrations (25, 50, 100, 400, 800, and 1200 µmol/l) with varying concentrations of selective inhibitors of CYP1A2 (furafylline, fluvoxamine), CYP3A4 (ketoconazole), CYP2A6 (coumarin), CYP2D6 (quinidine), CYP2C19 (omeprazole, fluvoxamine, tranylcypromine), CYP2C9 (sulfaphenazole), and CYP1A1 (alpha-naphthoflavone). 4-MAA and 4-AA were analyzed by HPLC, and enzyme kinetic parameters (Km and Vmax) were determined by regression (Sigma plot 9.0). Results: The N-demethylation of 4-MAA by microsomes prepared from baculovirus-expressing human CYP was pronounced with CYP2C19. Intrinsic clearances of the most active enzymes were 0.092, 0.027, and 0.026 for the CYP enzymes 2C19, 2D6, and 1A2, respectively. Metabolism by rat liver microsomes was strongly inhibited by omeprazole (IC50 of 0.05). Conclusion: The enzyme CYP2C19 apparently has an important role in N-demethylation of 4-methylaminoantipyrine which should be further analyzed in clinical studies and which may also be interesting concerning the agranulocytosis.

Keywords: dipyrone, 4-methylaminoantipyrine (4-MAA), 4- aminoantipyrine (4-AA), metabolism, human CYP2C19

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1190 Short Answer Grading Using Multi-Context Features

Authors: S. Sharan Sundar, Nithish B. Moudhgalya, Nidhi Bhandari, Vineeth Vijayaraghavan

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Automatic Short Answer Grading is one of the prime applications of artificial intelligence in education. Several approaches involving the utilization of selective handcrafted features, graphical matching techniques, concept identification and mapping, complex deep frameworks, sentence embeddings, etc. have been explored over the years. However, keeping in mind the real-world application of the task, these solutions present a slight overhead in terms of computations and resources in achieving high performances. In this work, a simple and effective solution making use of elemental features based on statistical, linguistic properties, and word-based similarity measures in conjunction with tree-based classifiers and regressors is proposed. The results for classification tasks show improvements ranging from 1%-30%, while the regression task shows a stark improvement of 35%. The authors attribute these improvements to the addition of multiple similarity scores to provide ensemble of scoring criteria to the models. The authors also believe the work could reinstate that classical natural language processing techniques and simple machine learning models can be used to achieve high results for short answer grading.

Keywords: artificial intelligence, intelligent systems, natural language processing, text mining

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1189 The Effect of Family Support on Employee Satisfaction and Perception of Work-Family Conflict: The Case of Oil Sector Employees in Kuwait

Authors: Ali H. Muhammad

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This paper investigates both instrumental and emotional family support on employee job satisfaction and perception of work-family conflict. Instrumental family support is manifested in family behavior that contributes to the reduction of employee’s family responsibilities and keeping the physical home environment in a proper shape. Emotional family support includes the encouragement and praise that the employee receives from his family and families for the employee’s work problem and their role in assisting the employees in dealing with these problems. The paper suggests that instrumental and emotional family support increases employee’s job satisfaction. Furthermore, the study proposes that family support decreases employee’s perception of work-family conflict. In addition, this study examines the reliability and validity of the family support index developed by Lynda King and her colleagues in 1995. Confirmatory factor analysis is used to test the validity of the instrument in an Arab business setting. A paper-pencil questionnaire was used to collect data from a random sample of 70 Kuwaiti employees working in the oil sector. Data were analyzed using factor analysis, reliability tests, and regression analysis. Results confirmed the research hypothesis. Family support had a positive effect on job satisfaction. Furthermore, family support significantly contributed to the reduction of employee perception of work-family conflict.

Keywords: family support, job satisfaction, work-family conflict, Kuwait oil sector

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1188 A Soft Computing Approach Monitoring of Heavy Metals in Soil and Vegetables in the Republic of Macedonia

Authors: Vesna Karapetkovska Hristova, M. Ayaz Ahmad, Julijana Tomovska, Biljana Bogdanova Popov, Blagojce Najdovski

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The average total concentrations of heavy metals; (cadmium [Cd], copper [Cu], nickel [Ni], lead [Pb], and zinc [Zn]) were analyzed in soil and vegetables samples collected from the different region of Macedonia during the years 2010-2012. Basic soil properties such as pH, organic matter and clay content were also included in the study. The average concentrations of Cd, Cu, Ni, Pb, Zn in the A horizon (0-30 cm) of agricultural soils were as follows, respectively: 0.25, 5.3, 6.9, 15.2, 26.3 mg kg-1 of soil. We have found that neural networking model can be considered as a tool for prediction and spatial analysis of the processes controlling the metal transfer within the soil-and vegetables. The predictive ability of such models is well over 80% as compared to 20% for typical regression models. A radial basic function network reflects good predicting accuracy and correlation coefficients between soil properties and metal content in vegetables much better than the back-propagation method. Neural Networking / soft computing can support the decision-making processes at different levels, including agro ecology, to improve crop management based on monitoring data and risk assessment of metal transfer from soils to vegetables.

Keywords: soft computing approach, total concentrations, heavy metals, agricultural soils

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1187 Parent and Child Body Dissatisfaction: The Roles of Implicit Behavior and Child Gender in Middle Childhood

Authors: Vivienne Langhorne, Helen Sharpe

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Body dissatisfaction begins developing in middle childhood, with wide-ranging implications for mental health and well-being. Previous research on parent behavior has focused on the role of explicit parent behaviors in adolescent and young adult body dissatisfaction, leaving a gap in understanding how implicit parent behaviors relate to body dissatisfaction in childhood. The current study investigated how implicit parent behavior (such as modeling own body dissatisfaction and dieting) relates to parent and child body dissatisfaction. It was hypothesized that implicit behavior would be directly related to parent and child body dissatisfaction and mediate the relationship between the two. Furthermore, this study aimed to examine child gender as a potential moderator in this mediation, as research shows that boys and girls experience body dissatisfaction differently. This study analyzed survey responses on parent body dissatisfaction, implicit behavior, and child body dissatisfaction measures from a sample of 166 parent-child dyads with children between the ages of 6 to 9 years old. Regression analyses revealed that parent body dissatisfaction is related to both parent-implicit behavior and child body dissatisfaction. However, implicit behavior did not mediate the relationship between the two body dissatisfaction variables. Additionally, the results of moderated mediation indicated there were no child gender differences in the strength of the association between parental implicit behaviors and child body dissatisfaction. These findings highlight the need for further research into the mechanisms behind parent and child body dissatisfaction to better understand the process through which intergenerational transmission occurs.

Keywords: body dissatisfaction, implicit behaviour, middle childhood, parenting

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1186 Long Term Monitoring and Assessment of Atmospheric Aerosols in Indo-Gangetic Region of India

Authors: Ningombam Linthoingambi Devi, Amrendra Kumar

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The long term sampling at one of the most populated city in Indo-Gangetic region shows higher mass concentration of atmospheric aerosol (PM₂.₅) during spring season (144.70µg/m³), summer season (91.96 µg/m³), the autumn season (266.48µg/m³) and winter season (367.09 µg/m³) respectively. The concentration of PM₂.₅ in Patna across the year shows much higher than the limit fixed by the national ambient air quality level fixed by central pollution control board India (CPCB, India) and World Health Organization (WHO). Different water-soluble cation (Na⁺, K⁺, Ca²⁺, NH₄⁺ , and Mg²⁺) and anion (Cl⁻, NO₃⁻ , and SO₄²⁻) species were detected in PM₂.₅. Results show the significantly higher loaded of water-soluble ions during winter and spring seasons. The acidity of the atmosphere was revealed and calculated using selected major cations (K⁺, Ca²⁺ , and NH₄⁺) and anions (SO₄²⁻, and NO₃⁻). A regression correlation was analyzed to check the significant linkage between the acidity and alkalinity ions. During the winter season (r² = 0.79) and spring season (r² = 0.64) shows good significant correlation between the cations and anions. The ratio of NO₃⁻/SO₄²⁻ indicates the sources of secondary pollutants were mainly influenced by industrial and vehicular emission however SO₄²⁻ mostly emitted from industries during the winter season.

Keywords: aerosols, inorganic species, source apportionment, Indo-Gangetic region

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1185 Relationship of Silent Myocardial Ischemia to Erectile Dysfunction in Patients with Diabetes Mellitus

Authors: Ali Kassem, Esam Nada, Amro Abdelhamed, Shigeo Horie

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Objective: Diabetes mellitus (DM) is associated with macrovascular complications, including coronary artery disease (CAD), and microvascular complications that contribute to the pathogenesis of erectile dysfunction (ED). On the other hand, silent myocardial ischemia (SMI) is more common in diabetic patients and is a strong predictor of cardiac events and mortality in diabetic and non-diabetic patients. Recently, Multidetector computed tomographic coronary angiography (MDCT-CA) has become a reliable non-invasive imaging modality for screening diabetic patients for SMI. We aim to evaluate the presence of SMI using (MDCT-CA) in patients with type 2DM having ED. Methods: This study evaluated 20 patients (mean age 61.45 ± 10.7 years), with DM and ED without any history of angina or angina equivalent. ED was tested with the Sexual Health Inventory for Men score, erection hardness score (EHS), and maximal penile circumferential change by an erect meter. Results: Of twenty studied patients, coronary artery stenosis was detected in 13 (65%) patients in the form of one-vessel disease (n = 6, 30%), two-vessel disease (n = 2, 10%), and three-vessel disease (n = 5, 25%). Maximum coronary artery stenosis was positively correlated with age (P < 0.016,) and negatively correlated with EHS (P <04). Multivariate regression analysis using age and EHS showed that age was the only independent predictor of SMI (P <04). Conclusion: MDCT-CA is a useful tool to identify SMI in patients with diabetes mellitus and ED. One should consider the possibility of SMI especially in elderly patients with DM who have ED.

Keywords: diabetes mellitus, erectile dysfunction, microvascular, silent ischemia

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1184 Analysis of Bridge-Pile Foundation System in Multi-layered Non-Linear Soil Strata Using Energy-Based Method

Authors: Arvan Prakash Ankitha, Madasamy Arockiasamy

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The increasing demand for adopting pile foundations in bridgeshas pointed towardsthe need to constantly improve the existing analytical techniques for better understanding of the behavior of such foundation systems. This study presents a simplistic approach using the energy-based method to assess the displacement responses of piles subjected to general loading conditions: Axial Load, Lateral Load, and a Bending Moment. The governing differential equations and the boundary conditions for a bridge pile embedded in multi-layered soil strata subjected to the general loading conditions are obtained using the Hamilton’s principle employing variational principles and minimization of energies. The soil non-linearity has been incorporated through simple constitutive relationships that account for degradation of soil moduli with increasing strain values.A simple power law based on published literature is used where the soil is assumed to be nonlinear-elastic and perfectly plastic. A Tresca yield surface is assumed to develop the soil stiffness variation with different strain levels that defines the non-linearity of the soil strata. This numerical technique has been applied to a pile foundation in a two - layered soil strata for a pier supporting the bridge and solved using the software MATLAB R2019a. The analysis yields the bridge pile displacements at any depth along the length of the pile. The results of the analysis are in good agreement with the published field data and the three-dimensional finite element analysis results performed using the software ANSYS 2019R3. The methodology can be extended to study the response of the multi-strata soil supporting group piles underneath the bridge piers.

Keywords: pile foundations, deep foundations, multilayer soil strata, energy based method

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1183 A Comparative Asessment of Some Algorithms for Modeling and Forecasting Horizontal Displacement of Ialy Dam, Vietnam

Authors: Kien-Trinh Thi Bui, Cuong Manh Nguyen

Abstract:

In order to simulate and reproduce the operational characteristics of a dam visually, it is necessary to capture the displacement at different measurement points and analyze the observed movement data promptly to forecast the dam safety. The accuracy of forecasts is further improved by applying machine learning methods to data analysis progress. In this study, the horizontal displacement monitoring data of the Ialy hydroelectric dam was applied to machine learning algorithms: Gaussian processes, multi-layer perceptron neural networks, and the M5-rules algorithm for modelling and forecasting of horizontal displacement of the Ialy hydropower dam (Vietnam), respectively, for analysing. The database which used in this research was built by collecting time series of data from 2006 to 2021 and divided into two parts: training dataset and validating dataset. The final results show all three algorithms have high performance for both training and model validation, but the MLPs is the best model. The usability of them are further investigated by comparison with a benchmark models created by multi-linear regression. The result show the performance which obtained from all the GP model, the MLPs model and the M5-Rules model are much better, therefore these three models should be used to analyze and predict the horizontal displacement of the dam.

Keywords: Gaussian processes, horizontal displacement, hydropower dam, Ialy dam, M5-Rules, multi-layer perception neural networks

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1182 Preclinical Studying of Stable Fe-Citrate Effect on 68Ga-Citrate Tissue Distribution

Authors: A. S. Lunev, A. A. Larenkov, O. E. Klementyeva, G. E. Kodina

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Background and aims: 68Ga-citrate is one of prospective radiopharmaceutical for PET-imaging of inflammation and infection. 68Ga-citrate is 67Ga-citrate analogue using since 1970s for SPECT-imaging. There's known rebinding reaction occurs past Ga-citrate injection and gallium (similar iron Fe3+) binds with blood transferrin. Then radiolabeled protein complex is delivered to pathological foci (inflammation/infection sites). But excessive gallium bindings with transferrin are cause of slow blood clearance, long accumulation time in foci (24-72 h) and exception of application possibility of the short-lived gallium-68 (T½ = 68 min). Injection of additional chemical agents (e.g. Fe3+ compounds) competing with radioactive gallium to the blood transferrin joining (blocking of its metal binding capacity) is one of the ways to solve formulated problem. This phenomenon can be used for correction of 68Ga-citrate pharmacokinetics for increasing of the blood clearance and accumulation in foci. The aim of real studying is research of effect of stable Fe-citrate on 68Ga-citrate tissue distribution. Materials and methods: 68Ga-citrate without/with extra injection of stable Fe-citrate (III) was injected nonlinear mice with inflammation models (aseptic soft tissue inflammation, lung infection, osteomyelitis). PET/X-RAY Genisys4 (Sofie Bioscience, USA) was used for non-invasive PET imaging (for 30, 60, 120 min past injection 68Ga-citrate) with subsequent reconstruction of imaging and their analysis (value of clearance, distribution volume). Scanning time is 10 min. Results and conclusions: I. v. injection of stable Fe-citrate blocks the metal-binding capability of transferrin serum and allows decreasing gallium-68 radioactivity in blood significantly and increasing accumulation in inflammation (3-5 time). It allows receiving more informative PET-images of inflammation early (for 30-60 min after injection). Pharmacokinetic parameters prove it. Noted there is no statistically significant difference between 68Ga-citrate accumulation for different inflammation model because PET imaging is indication of pathological processes and is not their identification.

Keywords: 68Ga-citrate, Fe-citrate, PET imaging, mice, inflammation, infection

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1181 Chemometric Analysis of Raw Milk Quality Originating from Conventional and Organic Dairy Farming in AP Vojvodina, Serbia

Authors: Sanja Podunavac-Kuzmanović, Denis Kučević, Strahinja Kovačević, Milica Karadžić, Lidija Jevrić

Abstract:

The present study describes the application of chemometric methods in analysis of milk samples which were collected in a conventional dairy farm and an organic dairy farm in AP Vojvodina, Republic of Serbia. The chemometric analysis included the application of univariate regression modeling and Analysis of Variance (ANOVA) method. The ANOVA was used in order to determine the differences in fatty acids content in the milk samples from conventional and organic farm. The results of the ANOVA testing indicate that there is a highly statistically significant difference between the content of fatty acid (saturated fatty acid vs. unsaturated fatty acids) in different dairy farming. Besides, the linear univariate models have been obtained as a result of modeling the linear relationships between the milk fat content and saturated fatty acids content, and the linear relationships between the milk fat content and unsaturated fatty acids content. The models obtained on the basis of the milk samples which originate from the organic farming are statistically better than the models based on the milk samples from conventional farming.

Keywords: hemometrics, milk, organic farming, quality control

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1180 Pre-Analytical Laboratory Performance Evaluation Utilizing Quality Indicators between Private and Government-Owned Hospitals Affiliated to University of Santo Tomas

Authors: A. J. Francisco, K. C. Gallosa, R. J. Gasacao, J. R. Ros, B. J. Viado

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The study focuses on the use of quality indicators (QI)s based on the standards made by the (IFCC), that could effectively identify and minimize errors occurring throughout the total testing process (TTP), in order to improve patient safety. The study was conducted through a survey questionnaire that was given to a random sample of 19 respondents (eight privately-owned and eleven government-owned hospitals), mainly CMTs, MTs, and Supervisors from UST-affiliated hospitals. The pre-analytical laboratory errors, which include misidentification errors, transcription errors, sample collection errors and sample handling and transportation errors, were considered as variables according to the IFCC WG-LEPS. Data gathered were analyzed using the Mann-Whitney U test, Percentile, Linear Regression, Percentage, and Frequency. The laboratory performance of both hospitals is High level. There is no significant difference between the laboratory performance between the two stated variables. Moreover, among the four QIs, sample handling and transportation errors contributed most to the difference between the two variables. Outcomes indicate satisfactory performance between both variables. However, in order to ensure high-quality and efficient laboratory operation, constant vigilance and improvements in pre-analytical QI are still needed. Expanding the coverage of the study, the inclusion of other phases, utilization of parametric tests are recommended.

Keywords: pre-analytical phase, quality indicators, laboratory performance, pre-analytical error

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1179 Developing an ANN Model to Predict Anthropometric Dimensions Based on Real Anthropometric Database

Authors: Waleed A. Basuliman, Khalid S. AlSaleh, Mohamed Z. Ramadan

Abstract:

Applying the anthropometric dimensions is considered one of the important factors when designing any human-machine system. In this study, the estimation of anthropometric dimensions has been improved by developing artificial neural network that aims to predict the anthropometric measurements of the male in Saudi Arabia. A total of 1427 Saudi males from age 6 to 60 participated in measuring twenty anthropometric dimensions. These anthropometric measurements are important for designing the majority of work and life applications in Saudi Arabia. The data were collected during 8 months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining fifteen dimensions were set to be the measured variables (outcomes). The hidden layers have been varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was significantly able to predict the body dimensions for the population of Saudi Arabia. The network mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found 0.0348 and 3.225 respectively. The accuracy of the developed neural network was evaluated by compare the predicted outcomes with a multiple regression model. The ANN model performed better and resulted excellent correlation coefficients between the predicted and actual dimensions.

Keywords: artificial neural network, anthropometric measurements, backpropagation, real anthropometric database

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1178 Verification of a Simple Model for Rolling Isolation System Response

Authors: Aarthi Sridhar, Henri Gavin, Karah Kelly

Abstract:

Rolling Isolation Systems (RISs) are simple and effective means to mitigate earthquake hazards to equipment in critical and precious facilities, such as hospitals, network collocation facilities, supercomputer centers, and museums. The RIS works by isolating components acceleration the inertial forces felt by the subsystem. The RIS consists of two platforms with counter-facing concave surfaces (dishes) in each corner. Steel balls lie inside the dishes and allow the relative motion between the top and bottom platform. Formerly, a mathematical model for the dynamics of RISs was developed using Lagrange’s equations (LE) and experimentally validated. A new mathematical model was developed using Gauss’s Principle of Least Constraint (GPLC) and verified by comparing impulse response trajectories of the GPLC model and the LE model in terms of the peak displacements and accelerations of the top platform. Mathematical models for the RIS are tedious to derive because of the non-holonomic rolling constraints imposed on the system. However, using Gauss’s Principle of Least constraint to find the equations of motion removes some of the obscurity and yields a system that can be easily extended. Though the GPLC model requires more state variables, the equations of motion are far simpler. The non-holonomic constraint is enforced in terms of accelerations and therefore requires additional constraint stabilization methods in order to avoid the possibility that numerical integration methods can cause the system to go unstable. The GPLC model allows the incorporation of more physical aspects related to the RIS, such as contribution of the vertical velocity of the platform to the kinetic energy and the mass of the balls. This mathematical model for the RIS is a tool to predict the motion of the isolation platform. The ability to statistically quantify the expected responses of the RIS is critical in the implementation of earthquake hazard mitigation.

Keywords: earthquake hazard mitigation, earthquake isolation, Gauss’s Principle of Least Constraint, nonlinear dynamics, rolling isolation system

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1177 Study of University Course Scheduling for Crowd Gathering Risk Prevention and Control in the Context of Routine Epidemic Prevention

Authors: Yuzhen Hu, Sirui Wang

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As a training base for intellectual talents, universities have a large number of students. Teaching is a primary activity in universities, and during the teaching process, a large number of people gather both inside and outside the teaching buildings, posing a strong risk of close contact. The class schedule is the fundamental basis for teaching activities in universities and plays a crucial role in the management of teaching order. Different class schedules can lead to varying degrees of indoor gatherings and trajectories of class attendees. In recent years, highly contagious diseases have frequently occurred worldwide, and how to reduce the risk of infection has always been a hot issue related to public safety. "Reducing gatherings" is one of the core measures in epidemic prevention and control, and it can be controlled through scientific scheduling in specific environments. Therefore, the scientific prevention and control goal can be achieved by considering the reduction of the risk of excessive gathering of people during the course schedule arrangement. Firstly, we address the issue of personnel gathering in various pathways on campus, with the goal of minimizing congestion and maximizing teaching effectiveness, establishing a nonlinear mathematical model. Next, we design an improved genetic algorithm, incorporating real-time evacuation operations based on tracking search and multidimensional positive gradient cross-mutation operations, considering the characteristics of outdoor crowd evacuation. Finally, we apply undergraduate course data from a university in Harbin to conduct a case study. It compares and analyzes the effects of algorithm improvement and optimization of gathering situations and explores the impact of path blocking on the degree of gathering of individuals on other pathways.

Keywords: the university timetabling problem, risk prevention, genetic algorithm, risk control

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