Search results for: prediction models

Authors: Mengistu G. Woldu, Hani Y. Zaki, Areeg Faggad, Badreldin E. Abdalla

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Background: Type 2 diabetes mellitus (T2DM) is a complex, degenerative, and multi-factorial disease, which is culpable for huge mortality and morbidity worldwide. Even though relatively significant numbers of studies are conducted on the genetics domain of this disease in the developed world, there is huge information gap in the sub-Saharan Africa region in general and in Eritrea in particular. Objective: The principal aim of this study was to investigate the association of common variants of the Insulin Receptor Substrate 1 (IRS1) and Transcription Factor 7-Like 2 (TCF7L2) genes with T2DM in the Eritrean population. Method: In this cross-sectional case control study 200 T2DM patients and 112 non-diabetes subjects were participated and genotyping of the IRS1 (rs13431179, rs16822615, 16822644rs, rs1801123) and TCF7L2 (rs7092484) tag SNPs were carries out using PCR-RFLP method of analysis. Haplotype analyses were carried out using Plink version 1.07, and Haploview 4.2 software. Linkage disequilibrium (LD), and Hardy-Weinberg equilibrium (HWE) analyses were performed using the Plink software. All descriptive statistical data analyses were carried out using SPSS (Version-20) software. Throughout the analysis p-value ≤0.05 was considered statistically significant. Result: Significant association was found between rs13431179 SNP of the IRS1 gene and T2DM under the recessive model of inheritance (OR=9.00, 95%CI=1.17-69.07, p=0.035), and marginally significant association found in the genotypic model (OR=7.50, 95%CI=0.94-60.06, p=0.058). The rs7092484 SNP of the TCF7L2 gene also showed markedly significant association with T2DM in the recessive (OR=3.61, 95%CI=1.70-7.67, p=0.001); and allelic (OR=1.80, 95%CI=1.23-2.62, p=0.002) models. Moreover, eight haplotypes of the IRS1 gene found to have significant association withT2DM (p=0.013 to 0.049). Assessments made on the interactions of genotypes of the rs13431179 and rs7092484 SNPs with various parameters demonstrated that high density lipoprotein (HDL), low density lipoprotein (LDL), waist circumference (WC), and systolic blood pressure (SBP) are the best T2DM onset predicting models. Furthermore, genotypes of the rs7092484 SNP showed significant association with various atherogenic indexes (Atherogenic index of plasma, LDL/HDL, and CHLO/HDL); and Eritreans carrying the GG or GA genotypes were predicted to be more susceptible to cardiovascular diseases onset. Conclusions: Results of this study suggest that IRS1 (rs13431179) and TCF7L2 (rs7092484) gene polymorphisms are associated with increased risk of T2DM in Eritreans.

Keywords: IRS1, SNP, TCF7L2, type 2 diabetes

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Authors: Rui Teixeira, Alan O’Connor, Maria Nogal

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The statistical theory of extreme events is progressively a topic of growing interest in all the fields of science and engineering. The changes currently experienced by the world, economic and environmental, emphasized the importance of dealing with extreme occurrences with improved accuracy. When it comes to the design of offshore structures, particularly offshore wind turbines, the importance of efficiently characterizing extreme events is of major relevance. Extreme events are commonly characterized by extreme values theory. As an alternative, the accurate modeling of the tails of statistical distributions and the characterization of the low occurrence events can be achieved with the application of the Peak-Over-Threshold (POT) methodology. The POT methodology allows for a more refined fit of the statistical distribution by truncating the data with a minimum value of a predefined threshold u. For mathematically approximating the tail of the empirical statistical distribution the Generalised Pareto is widely used. Although, in the case of the exceedances of significant wave data (H_s) the 2 parameters Weibull and the Exponential distribution, which is a specific case of the Generalised Pareto distribution, are frequently used as an alternative. The Generalized Pareto, despite the existence of practical cases where it is applied, is not completely recognized as the adequate solution to model exceedances over a certain threshold u. References that set the Generalised Pareto distribution as a secondary solution in the case of significant wave data can be identified in the literature. In this framework, the current study intends to tackle the discussion of the application of statistical models to characterize exceedances of wave data. Comparison of the application of the Generalised Pareto, the 2 parameters Weibull and the Exponential distribution are presented for different values of the threshold u. Real wave data obtained in four buoys along the Irish coast was used in the comparative analysis. Results show that the application of the statistical distributions to characterize significant wave data needs to be addressed carefully and in each particular case one of the statistical models mentioned fits better the data than the others. Depending on the value of the threshold u different results are obtained. Other variables of the fit, as the number of points and the estimation of the model parameters, are analyzed and the respective conclusions were drawn. Some guidelines on the application of the POT method are presented. Modeling the tail of the distributions shows to be, for the present case, a highly non-linear task and, due to its growing importance, should be addressed carefully for an efficient estimation of very low occurrence events.

Keywords: extreme events, offshore structures, peak-over-threshold, significant wave data

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Authors: Diana Islam, Juan Fang, Vito Fanelli, Bing Han, Julie Khang, Jianfeng Wu, Arthur S. Slutsky, Haibo Zhang

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Introduction: MSC delivery in preclinical models of ARDS has demonstrated significant improvements in lung function and recovery from acute injury. However, the role of MSC delivery in ARDS associated pulmonary fibrosis is not well understood. Some animal studies using bleomycin, asbestos, and silica-induced pulmonary fibrosis show that MSC delivery can suppress fibrosis. While other animal studies using radiation induced pulmonary fibrosis, liver, and kidney fibrosis models show that MSC delivery can contribute to fibrosis. Hypothesis: The beneficial and deleterious effects of MSC in ARDS are modulated by the lung microenvironment at the time of MSC delivery. Methods: To induce ARDS a two-hit mouse model of Hydrochloric acid (HCl) aspiration (day 0) and mechanical ventilation (MV) (day 2) was used. HCl and injurious MV generated fibrosis within 14-28 days. 0.5x106 mouse MSCs were delivered (via both intratracheal and intravenous routes) either in the active inflammatory phase (day 2) or during the remodeling phase (day 14) of ARDS (mouse fibroblasts or PBS used as a control). Lung injury accessed using inflammation score and elastance measurement. Pulmonary fibrosis was accessed using histological score, tissue collagen level, and collagen expression. In addition alveolar epithelial (E) and mesenchymal (M) marker expression profile was also measured. All measurements were taken at day 2, 14, and 28. Results: MSC delivery 2 days after HCl exacerbated lung injury and fibrosis compared to HCl alone, while the day 14 delivery showed protective effects. However in the absence of HCl, MSC significantly reduced the injurious MV-induced fibrosis. HCl injury suppressed E markers and up-regulated M markers. MSC delivery 2 days after HCl further amplified M marker expression, indicating their role in myofibroblast proliferation/activation. While with 14-day delivery E marker up-regulation was observed indicating their role in epithelial restoration. Conclusions: Early MSC delivery can be protective of injurious MV. Late MSC delivery during repair phase may also aid in recovery. However, early MSC delivery during the exudative inflammatory phase of HCl-induced ARDS can result in pro-fibrotic profiles. It is critical to understand the interaction between MSC and the lung microenvironment before MSC-based therapies are utilized for ARDS.

Keywords: acute respiratory distress syndrome (ARDS), mesenchymal stem cells (MSC), hydrochloric acid (HCl), mechanical ventilation (MV)

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Authors: Aya Rezgui, Lasaad Ajam, Belgacem Jalleli

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The Tunis soft soils present a difficult challenge as construction sites and for Geotechnical works. Currently, different techniques are used to improve such soil properties taking into account the environmental considerations. One of the recent methods is involving plastic wastes as a reinforcing materials. The present study pertains to the development of a numerical model for predicting the behavior of Tunis Soft soil (TSS) improved with recycled Monobloc chair wastes.3D numerical models for unreinforced TSS and reinforced TSS aims to evaluate settlement reduction and the values of consolidation times in oedometer conditions.

Keywords: Tunis soft soil, settlement, plastic wastes, finte -difference, FLAC3D modeling

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Authors: Anurag Niranjan, Michael Fitzpatrick, Yin Jin Janin, Jazeel Chukkan, Niall Smyth

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Fillet welds are used in joining longitudinal stiffeners in ship structures. Welding residual stresses in fillet welds are generally distributed in a non-uniform manner, as shown in previous research the residual stress redistribution occurs under the cyclic loading that is experienced by such joints during service, and the combination of the initial residual stress, local constraints, and loading can alter the stress field in ways that are extremely difficult to predict. As the residual stress influences the crack propagation originating from the toe of the fillet welds, full understanding of the residual stress field and how it evolves is very important for structural integrity calculations. Knowledge of the residual stress redistribution in the presence of a flaw is therefore required for better fatigue life prediction. Moreover, defect assessment procedures such as BS7910 offer very limited guidance for flaw acceptance and the associated residual stress redistribution in the assessment of fillet welds. Therefore the objective of this work is to study a surface-breaking flaw at the weld toe region in a fillet weld under cyclic load, in conjunction with residual stress measurement at pre-defined crack depths. This work will provide details of residual stress redistribution under cyclic load in the presence of a crack. The outcome of this project will inform integrity assessment with respect to the treatment of residual stress in fillet welds. Knowledge of the residual stress evolution for this weld geometry will be greatly beneficial for flaw tolerance assessments (BS 7910, API 591).

Keywords: fillet weld, fatigue, residual stress, structure integrity

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Authors: Abdallah A. Hlayel

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Operations research science (OR) deals with good success in developing and applying scientific methods for problem solving and decision-making. However, by using OR techniques, we can enhance the use of computer decision support systems to achieve optimal management for institutions. OR applies comprehensive analysis including all factors that affect on it and builds mathematical modeling to solve business or organizational problems. In addition, it improves decision-making and uses available resources efficiently. The adoption of OR by universities would definitely contributes to the development and enhancement of the performance of OR techniques. This paper provides an understanding of the structures, approaches and models of OR in problem solving and decision-making.

Keywords: best candidates' method, decision making, decision support system, operations research

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Authors: Łukasz Grabowski, Michał Gęca, Mirosław Wendeker

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This paper presents the simulation results of a new opposed piston diesel engine to power a light aircraft. Created in the AVL Boost, the model covers the entire charge passage, from the inlet up to the outlet. The model shows fuel injection into cylinders and combustion in cylinders. The calculation uses the module for two-stroke engines. The model was created using sub-models available in this software that structure the model. Each of the sub-models is complemented with parameters in line with the design premise. Since engine weight resulting from geometric dimensions is fundamental in aircraft engines, two configurations of stroke were studied. For each of the values, there were calculated selected operating conditions defined by crankshaft speed. The required power was achieved by changing air fuel ratio (AFR). There was also studied brake specific fuel consumption (BSFC). For stroke S1, the BSFC was lowest at all of the three operating points. This difference is approximately 1-2%, which means higher overall engine efficiency but the amount of fuel injected into cylinders is larger by several mg for S1. The cylinder maximum pressure is lower for S2 due to the fact that compressor gear driving remained the same and boost pressure was identical in the both cases. Calculations for various values of boost pressure were the next stage of the study. In each of the calculation case, the amount of fuel was changed to achieve the required engine power. In the former case, the intake system dimensions were modified, i.e. the duct connecting the compressor and the air cooler, so its diameter D = 40 mm was equal to the diameter of the compressor outlet duct. The impact of duct length was also examined to be able to reduce the flow pulsation during the operating cycle. For the so selected geometry of the intake system, there were calculations for various values of boost pressure. The boost pressure was changed by modifying the gear driving the compressor. To reach the required level of cruising power N = 68 kW. Due to the mechanical power consumed by the compressor, high pressure ratio results in a worsened overall engine efficiency. The figure on the change in BSFC from 210 g/kWh to nearly 270 g/kWh shows this correlation and the overall engine efficiency is reduced by about 8%. Acknowledgement: This work has been realized in the cooperation with The Construction Office of WSK "PZL-KALISZ" S.A." and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish National Centre for Research and Development.

Keywords: aircraft, diesel, engine, simulation

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Authors: Meysam Naeimi, Zili Li, Roumen Petrov, Rolf Dollevoet, Jilt Sietsma, Jun Wu

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The substantial similarity of fatigue mechanism in a new test rig for rolling contact fatigue (RCF) has been investigated. A new reduced-scale test rig is designed to perform controlled RCF tests in wheel-rail materials. The fatigue mechanism of the rig is evaluated in this study using a combined finite element-fatigue prediction approach. The influences of loading conditions on fatigue crack initiation have been studied. Furthermore, the effects of some artificial defects (squat-shape) on fatigue lives are examined. To simulate the vehicle-track interaction by means of the test rig, a three-dimensional finite element (FE) model is built up. The nonlinear material behaviour of the rail steel is modelled in the contact interface. The results of FE simulations are combined with the critical plane concept to determine the material points with the greatest possibility of fatigue failure. Based on the stress-strain responses, by employing of previously postulated criteria for fatigue crack initiation (plastic shakedown and ratchetting), fatigue life analysis is carried out. The results are reported for various loading conditions and different defect sizes. Afterward, the cyclic mechanism of the test rig is evaluated from the operational viewpoint. The results of fatigue life predictions are compared with the expected number of cycles of the test rig by its cyclic nature. Finally, the estimative duration of the experiments until fatigue crack initiation is roughly determined.

Keywords: fatigue, test rig, crack initiation, life, rail, squats

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Authors: Adeniyi G. Adeogun, Bolaji F. Sule, Adebayo W. Salami, Michael O. Daramola

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Estimation of water yield and water balance in a river catchment is critical to the sustainable management of water resources at watershed level in any country. Therefore, in the present study, Soil and Water Assessment Tool (SWAT) interfaced with Geographical Information System (GIS) was applied as a tool to predict water balance and water yield of a catchment area in Nigeria. The catchment area, which was 12,992km2, is located upstream Jebba hydropower dam in North central part of Nigeria. In this study, data on the observed flow were collected and compared with simulated flow using SWAT. The correlation between the two data sets was evaluated using statistical measures, such as, Nasch-Sucliffe Efficiency (NSE) and coefficient of determination (R2). The model output shows a good agreement between the observed flow and simulated flow as indicated by NSE and R2, which were greater than 0.7 for both calibration and validation period. A total of 42,733 mm of water was predicted by the calibrated model as the water yield potential of the basin for a simulation period 1985 to 2010. This interesting performance obtained with SWAT model suggests that SWAT model could be a promising tool to predict water balance and water yield in sustainable management of water resources. In addition, SWAT could be applied to other water resources in other basins in Nigeria as a decision support tool for sustainable water management in Nigeria.

Keywords: GIS, modeling, sensitivity analysis, SWAT, water yield, watershed level

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Authors: Upasana Bhumbla

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Background: Hepatitis C virus is a major cause of chronic hepatitis, which can further lead to cirrhosis of the liver and hepatocellular carcinoma. Worldwide the burden of Hepatitis C infection has become a serious threat to the human race. Hepatitis C virus (HCV) has population-specific genotypes and provides valuable epidemiological and therapeutic information. Genotyping and assessment of viral load in HCV patients are important for planning the therapeutic strategies. The aim of the study is to study the changing trends of prevalence and genotypic distribution of hepatitis C virus in a tertiary care hospital in Western India. Methods: It is a retrospective study; blood samples were collected and tested for anti HCV antibodies by ELISA in Dept. of Microbiology. In seropositive Hepatitis C patients, quantification of HCV-RNA was done by real-time PCR and in HCV-RNA positive samples, genotyping was conducted. Results: A total of 114 patients who were seropositive for Anti HCV were recruited in the study, out of which 79 (69.29%) were HCV-RNA positive. Out of these positive samples, 54 were further subjected to genotype determination using real-time PCR. Genotype was not detected in 24 samples due to low viral load; 30 samples were positive for genotype. Conclusion: Knowledge of genotype is crucial for the management of HCV infection and prediction of prognosis. Patients infected with HCV genotype 1 and 4 will have to receive Interferon and Ribavirin for 48 weeks. Patients with these genotypes show a poor sustained viral response when tested 24 weeks after completion of therapy. On the contrary, patients infected with HCV genotype 2 and 3 are reported to have a better response to therapy.

Keywords: hepatocellular, genotype, ribavarin, seropositive

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Authors: Assel Thami Lahlou, Soufiane Stouti, Ismail Lagrat, Hamid Mounir, Oussama Bouazaoui

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The purpose of this research work is to predict the helicopter from stalling by finding the minimum and maximum values that the pitch angle can take in order to fly in a hover state condition. The stall of a helicopter in hover occurs when the pitch angle is too small to generate the thrust required to support its weight or when the critical angle of attack that gives maximum lift is reached or exceeded. In order to find the minimum pitch angle, a 3D CFD simulation was done in this work using ANSYS FLUENT as the CFD solver. We started with a small value of the pitch angle θ, and we kept increasing its value until we found the thrust coefficient required to fly in a hover state and support the weight of the helicopter. For the CFD analysis, the Multiple Reference Frame (MRF) method with k-ε turbulent model was used to study the 3D flow around the rotor for θmin. On the other hand, a 2D simulation of the airfoil NACA 0012 was executed with a velocity inlet Vin=ΩR/2 to visualize the flow at the location span R/2 of the disk rotor using the Spallart-Allmaras turbulent model. Finding the critical angle of attack at this position will give us the ability to predict the stall in hover flight. The results obtained will be exposed later in the article. This study was so useful in analyzing the limitations of the helicopter’s main rotor and thus, in predicting accidents that can lead to a lot of damage.

Keywords: aerodynamic, CFD, helicopter, stall, blades, main rotor, minimum pitch angle, maximum pitch angle

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Authors: Filipa Cortez, Vanessa Pereira

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Introduction: The main challenge of obesity treatment is long-term weight loss maintenance. The 3 phases method is a weight loss program that combines a low carb and moderately high-protein diet, food supplements and a weekly one-to-one consultation with a certified nutritionist. Sustained weight control is the ultimate goal of phase 3. Success criterion was the minimum loss of 10% of initial weight and its maintenance after 12 months. Objective: The aim of this study was to identify factors associated with successful weight loss maintenance after 12 months at the end of 3 phases method. Methods: The study included 199 subjects that achieved their weight loss goal (phase 3). Weight and body mass index (BMI) were obtained at the baseline and every week until the end of the program. Therapeutic adherence was measured weekly on a Likert scale from 1 to 5. Subjects were considered in compliance with nutritional recommendation and supplementation when their classification was ≥ 4. After 12 months of the method, the current weight and number of previous weight-loss attempts were collected by telephone interview. The statistical significance was assumed at p-values < 0.05. Statistical analyses were performed using SPSS TM software v.21. Results: 65.3% of subjects met the success criterion. The factors which displayed a significant weight loss maintenance prediction were: greater initial percentage weight loss (OR=1.44) during the weight loss intervention and a higher number of consultations in phase 3 (OR=1.10). Conclusion: These findings suggest that the percentage weight loss during the weight loss intervention and the number of consultations in phase 3 may facilitate maintenance of weight loss after the 3 phases method.

Keywords: obesity, weight maintenance, low-carbohydrate diet, dietary supplements

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Authors: Bilel Chalghaf, Mathieu Varin

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Forest characterization in Quebec, Canada, is usually assessed based on photo-interpretation at the stand level. For species identification, this often results in a lack of precision. Very high spatial resolution imagery, such as DigitalGlobe, and Light Detection and Ranging (LiDAR), have the potential to overcome the limitations of aerial imagery. To date, few studies have used that data to map a large number of species at the tree level using machine learning techniques. The main objective of this study is to map 11 individual high tree species ( > 17m) at the tree level using an object-based approach in the broadleaf forest of Kenauk Nature, Quebec. For the individual tree crown segmentation, three canopy-height models (CHMs) from LiDAR data were assessed: 1) the original, 2) a filtered, and 3) a corrected model. The corrected CHM gave the best accuracy and was then coupled with imagery to refine tree species crown identification. When compared with photo-interpretation, 90% of the objects represented a single species. For modeling, 313 variables were derived from 16-band WorldView-3 imagery and LiDAR data, using radiance, reflectance, pixel, and object-based calculation techniques. Variable selection procedures were employed to reduce their number from 313 to 16, using only 11 bands to aid reproducibility. For classification, a global approach using all 11 species was compared to a semi-hierarchical hybrid classification approach at two levels: (1) tree type (broadleaf/conifer) and (2) individual broadleaf (five) and conifer (six) species. Five different model techniques were used: (1) support vector machine (SVM), (2) classification and regression tree (CART), (3) random forest (RF), (4) k-nearest neighbors (k-NN), and (5) linear discriminant analysis (LDA). Each model was tuned separately for all approaches and levels. For the global approach, the best model was the SVM using eight variables (overall accuracy (OA): 80%, Kappa: 0.77). With the semi-hierarchical hybrid approach, at the tree type level, the best model was the k-NN using six variables (OA: 100% and Kappa: 1.00). At the level of identifying broadleaf and conifer species, the best model was the SVM, with OA of 80% and 97% and Kappa values of 0.74 and 0.97, respectively, using seven variables for both models. This paper demonstrates that a hybrid classification approach gives better results and that using 16-band WorldView-3 with LiDAR data leads to more precise predictions for tree segmentation and classification, especially when the number of tree species is large.

Keywords: tree species, object-based, classification, multispectral, machine learning, WorldView-3, LiDAR

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Authors: Sabyasachi Mukhopadhyay, Joseph Ogutu, Gundula Bartzke, Hans-Peter Piepho

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Rainfall is a critical component of climate governing vegetation growth and production, forage availability and quality for herbivores. However, reliable rainfall measurements are not always available, making it necessary to predict rainfall values for particular locations through time. Predicting rainfall in space and time can be a complex and challenging task, especially where the rain gauge network is sparse and measurements are not recorded consistently for all rain gauges, leading to many missing values. Here, we develop a flexible Bayesian model for predicting rainfall in space and time and apply it to Narok County, situated in southwestern Kenya, using data collected at 23 rain gauges from 1965 to 2015. Narok County encompasses the Maasai Mara ecosystem, the northern-most section of the Mara-Serengeti ecosystem, famous for its diverse and abundant large mammal populations and spectacular migration of enormous herds of wildebeest, zebra and Thomson's gazelle. The model incorporates geographical and meteorological predictor variables, including elevation, distance to Lake Victoria and minimum temperature. We assess the efficiency of the model by comparing it empirically with the established Gaussian process, Kriging, simple linear and Bayesian linear models. We use the model to predict total monthly rainfall and its standard error for all 5 * 5 km grid cells in Narok County. Using the Monte Carlo integration method, we estimate seasonal and annual rainfall and their standard errors for 29 sub-regions in Narok. Finally, we use the predicted rainfall to predict large herbivore biomass in the Maasai Mara ecosystem on a 5 * 5 km grid for both the wet and dry seasons. We show that herbivore biomass increases with rainfall in both seasons. The model can handle data from a sparse network of observations with many missing values and performs at least as well as or better than four established and widely used models, on the Narok data set. The model produces rainfall predictions consistent with expectation and in good agreement with the blended station and satellite rainfall values. The predictions are precise enough for most practical purposes. The model is very general and applicable to other variables besides rainfall.

Keywords: non-stationary covariance function, gaussian process, ungulate biomass, MCMC, maasai mara ecosystem

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Authors: Ali K. M. Al-Nasrawi, Uday A. Al-Hamdany, Sarah M. Hamylton, Brian G. Jones, Yasir M. Alyazichi

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Surface elevation dynamics have always responded to disturbance regimes. Creating Digital Elevation Models (DEMs) to detect surface dynamics has led to the development of several methods, devices and data clouds. DEMs can provide accurate and quick results with cost efficiency, in comparison to the inherited geomatics survey techniques. Nowadays, remote sensing datasets have become a primary source to create DEMs, including LiDAR point clouds with GIS analytic tools. However, these data need to be tested for error detection and correction. This paper evaluates various DEMs from different data sources over time for Apple Orchard Island, a coastal site in southeastern Australia, in order to detect surface dynamics. Subsequently, 30 chosen locations were examined in the field to test the error of the DEMs surface detection using high resolution global positioning systems (GPSs). Results show significant surface elevation changes on Apple Orchard Island. Accretion occurred on most of the island while surface elevation loss due to erosion is limited to the northern and southern parts. Concurrently, the projected differential correction and validation method aimed to identify errors in the dataset. The resultant DEMs demonstrated a small error ratio (≤ 3%) from the gathered datasets when compared with the fieldwork survey using RTK-GPS. As modern modelling approaches need to become more effective and accurate, applying several tools to create different DEMs on a multi-temporal scale would allow easy predictions in time-cost-frames with more comprehensive coverage and greater accuracy. With a DEM technique for the eco-geomorphic context, such insights about the ecosystem dynamic detection, at such a coastal intertidal system, would be valuable to assess the accuracy of the predicted eco-geomorphic risk for the conservation management sustainability. Demonstrating this framework to evaluate the historical and current anthropogenic and environmental stressors on coastal surface elevation dynamism could be profitably applied worldwide.

Keywords: DEMs, eco-geomorphic-dynamic processes, geospatial Information Science, remote sensing, surface elevation changes,

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Authors: Andrej Golowin, Viktor Denk, Axel Riepe

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Solid fan blades and discs in aero engines are subjected to high combined low and high cycle fatigue loads especially around the contact areas between blade and disc. Therefore, special coatings (e.g. dry film lubricant) and surface treatments (e.g. shot peening or laser shock peening) are applied to increase the strength with respect to combined cyclic fatigue and fretting fatigue, but also to improve damage tolerance capability. The traditional deterministic damage tolerance assessment based on fracture mechanics analysis, which treats service damage as an initial crack, often gives overly conservative results especially in the presence of vibratory stresses. A probabilistic damage tolerance methodology using crack initiation data has been developed for fan discs exposed to relatively high vibratory stresses in cross- and tail-wind conditions at certain resonance speeds for limited time periods. This Monte-Carlo based method uses a damage databank from similar designs, measured vibration levels at typical aircraft operations and wind conditions and experimental crack initiation data derived from testing of artificially damaged specimens with representative surface treatment under combined fatigue conditions. The proposed methodology leads to a more realistic prediction of the minimum damage tolerance life for the most critical locations applicable to modern fan disc designs.

Keywords: combined fatigue, damage tolerance, engine, surface treatment

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Authors: R. Mkahl, A. Nait-Sidi-Moh, M. Wack

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Batteries of electric vehicles (BEV) are becoming more attractive with the advancement of new battery technologies and promotion of electric vehicles. BEV batteries are recharged on board vehicles using either the grid (G2V for Grid to Vehicle) or renewable energies in a stand-alone application (H2V for Home to Vehicle). This paper deals with the modeling, sizing and control of a photo voltaic stand-alone application that can charge the BEV at home. The modeling approach and developed mathematical models describing the system components are detailed. Simulation and experimental results are presented and commented.

Keywords: electric vehicles, photovoltaic energy, lead-acid batteries, charging process, modeling, simulation, experimental tests

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Authors: Ashenafi Beyene Fanta, Daniel Makina

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Economic theory predicts that finance promotes economic growth. Although the finance-growth link is among the most researched areas in financial economics, our understanding of the link between the two is still incomplete. This is caused by, among others, wrong econometric specifications, using weak proxies of financial development, and inability to address the endogeneity problem. Studies on the finance growth link in South Africa consistently report economic growth driving financial development. Early studies found that economic growth drives financial development in South Africa, and recent studies have confirmed this using different econometric models. However, the monetary aggregate (i.e. M2) utilized used in these studies is considered a weak proxy for financial development. Furthermore, the fact that the models employed do not address the endogeneity problem in the finance-growth link casts doubt on the validity of the conclusions. For this reason, the current study examines the finance growth link in South Africa using data for the period 1990 to 2011 by employing a generalized method of moments (GMM) technique that is capable of addressing endogeneity, simultaneity and omitted variable bias problems. Unlike previous cross country and country case studies that have also used the same technique, our contribution is that we account for the development of bond markets and non-bank financial institutions rather than being limited to stock market and banking sector development. We find that bond market development affects economic growth in South Africa, and no similar effect is observed for the bank and non-bank financial intermediaries and the stock market. Our findings show that examination of individual elements of the financial system is important in understanding the unique effect of each on growth. The observation that bond markets rather than private credit and stock market development promotes economic growth in South Africa induces an intriguing question as to what unique roles bond markets play that the intermediaries and equity markets are unable to play. Crucially, our results support observations in the literature that using appropriate measures of financial development is critical for policy advice. They also support the suggestion that individual elements of the financial system need to be studied separately to consider their unique roles in advancing economic growth. We believe that our understanding of the channels through which bond market contribute to growth would be a fertile ground for future research.

Keywords: bond market, finance, financial sector, growth

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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The widespread use of machine learning applications in production is significantly accelerated by improved computing power and increasing data availability. Predictive quality enables the assurance of product quality by using machine learning models as a basis for decisions on test results. The use of real Bosch production data based on geometric gauge blocks from machining, mating data from assembly and hydraulic measurement data from final testing of directional valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: machine learning, classification, predictive quality, hydraulics, supervised learning

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Authors: Hakimeh Sharififard, Mansooreh Soleimani

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In this work, the magnetic activated carbon nanocomposite (Fe-CAC) has been synthesized by anchorage iron hydr(oxide) nanoparticles onto commercial activated carbon (CAC) surface and characterized using BET, XRF, SEM techniques. The influence of various removal parameters such as pH, contact time and initial concentration of vanadium on vanadium removal was evaluated using CAC and Fe-CAC in batch method. The sorption isotherms were studied using Langmuir, Freundlich and Dubinin–Radushkevich (D–R) isotherm models. These equilibrium data were well described by the Freundlich model. Results showed that CAC had the vanadium adsorption capacity of 37.87 mg/g, while the Fe-AC was able to adsorb 119.01 mg/g of vanadium. Kinetic data was found to confirm pseudo-second-order kinetic model for both adsorbents.

Keywords: magnetic activated carbon, remove, vanadium, nanocomposite, freundlich

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Authors: Haruna Maama

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Environmental, social and governance (ESG) reporting is gaining considerable attention despite being voluntary. Meanwhile, it consumes resources to provide ESG reporting, raising a question of its value relevance. The study examined the impact of ESG reporting on the market value of listed firms in SSA. The annual and integrated reports of 276 listed sub-Sahara Africa (SSA) firms. The integrated reporting scores of the firm were analysed using a content analysis method. A multiple regression estimation technique using a GMM approach was employed for the analysis. The results revealed that ESG has a positive relationship with firms’ market value, suggesting that investors are interested in the ESG information disclosure of firms in SSA. This suggests that extensive ESG disclosures are attempts by firms to obtain the approval of powerful social, political and environmental stakeholders, especially institutional investors. Furthermore, the market value analysis evidence is consistent with signalling theory, which postulates that firms provide integrated reports as a signal to influence the behaviour of stakeholders. This finding reflects the value placed on investors' social, environmental and governance disclosures, which affirms the views that conventional investors would care about the social, environmental and governance issues of their potential or existing investee firms. Overall, the evidence is consistent with the prediction of signalling theory. In the context of this theory, integrated reporting is seen as part of firms' overall competitive strategy to influence investors' behaviour. The findings of this study make unique contributions to knowledge and practice in corporate reporting.

Keywords: environmental accounting, ESG accounting, signalling theory, sustainability reporting, sub-saharan Africa

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Authors: Masayuki Higashino, Toshiya Kawato, Takao Kawamura

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A monolithic service is based on the N-tier architecture in many cases. In order to divide a monolithic service into microservices, it is necessary to redefine a model as a new microservice by extracting and merging existing models across layers. Refactoring a monolithic service into microservices requires advanced technical capabilities, and it is a difficult way. This paper proposes a design and concept to ease the migration of a monolithic service to microservices using the mobile agent technology. Our proposed approach, mobile agents-based design and concept, enables to ease dividing and merging services.

Keywords: mobile agent, microservice, web service, distributed system

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Authors: Valentin Nickolai, Florian Pfeffel, Christian Louis Kühner

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In many industrialized nations, the demand for skilled workers rises, causing the current market for employees to be more candidate-driven than employer-driven. Therefore, losing highly skilled and experienced employees due to early or partial retirement negatively impacts firms. Therefore, finding new ways to incentivize older employees (Silver Workers) to stay longer with the company and in their job can be crucial for the success of a firm. This study analyzes how working remotely can be a valid incentive for experienced Silver Workers to stay in their job and instead work from home with more flexible working hours. An online survey with n = 684 respondents, who are employed in the service sector, has been conducted based on 13 constructs that influence job satisfaction. These have been further categorized into three groups “classic influencing factors,” “influencing factors changed by remote working,” and new remote working influencing factors,” and were analyzed using structural equation modeling (SEM). Here, Cronbach’s alpha of the individual constructs was shown to be suitable. Furthermore, the construct validity of the constructs was confirmed by face validity, content validity, convergent validity (AVE > 0.5: CR > 0.7), and discriminant validity. Additionally, confirmatory factor analysis (CFA) confirmed the model fit for the investigated sample (CMIN/DF: 2.567; CFI: 0.927; RMSEA: 0.048). It was shown in the SEM-analysis that the influencing factor on job satisfaction, “identification with the work,” is the most significant with β = 0.540, followed by “Appreciation” (β = 0.151), “Compensation” (β = 0.124), “Work-Life-Balance” (β = 0.116), and “Communication and Exchange of Information” (β = 0.105). While the significance of each factor can vary depending on the work model, the SEM-analysis also shows that the identification with the work is the most significant factor in all three work models mentioned above and, in the case of the traditional office work model, it is the only significant influencing factor. The study shows that employees between the ages of 56 and 65 years have the highest job satisfaction when working entirely from home or remotely. Furthermore, their job satisfaction score of 5.4 on a scale from 1 (very dissatisfied) to 7 (very satisfied) is the highest amongst all age groups in any of the three work models. Due to the significantly higher job satisfaction, it can be argued that giving Silver Workers the offer to work from home or remotely can incentivize them not to opt for early retirement or partial retirement but to stay in their job full-time Furthermore, these findings can indicate that employees in the Silver Worker age are much more inclined to leave their job for early retirement if they have to entirely work in the office.

Keywords: home office, remote work instead of early or partial retirement, silver worker, structural equation modeling

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Authors: Lei Ren, Michael Hartnett, Stephen Nash

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The abundant measured surface current from HF radar system in coastal area is assimilated into model to improve the modeling forecasting ability. A simple sequential data assimilation scheme, Direct Insertion (DI), is applied to update model forecast states. The influence of Direct Insertion data assimilation over time is analyzed at one reference point. Vector maps of surface current from models are compared with HF radar measurements. Root-Mean-Squared-Error (RMSE) between modeling results and HF radar measurements is calculated during the last four days with no data assimilation.

Keywords: data assimilation, CODAR, HF radar, surface current, direct insertion

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Authors: Abdelfetah Laouzai, Rachid Ouafi

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In a traffic network, users usually choose their way so that it reduces their travel time between pairs origin-destination. This behavior might seem selfish as it produces congestions in different parts of the network. The traffic assignment problem (TAP) models the interactions between congestion and user travel decisions to obtain vehicles flows over each axis of the traffic network. The resolution methods of TAP serve as a tool allows predicting users’ distribution, identifying congesting points and affecting the travelers’ behavior in the choice of their route in the network following dynamic data. In this article, we will present a review about specific resolution approach of TAP. A comparative analysis is carried out on those approaches so that it highlights the characteristics, advantages and disadvantages of each.

Keywords: network traffic, travel decisions, approaches, traffic assignment, flows

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Authors: Mamouni Mohammed Dhiya Eddine

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This work aims at studying the exploitation of high-speed networks of clusters for distributed storage. Parallel applications running on clusters require both high-performance communications between nodes and efficient access to the storage system. Many studies on network technologies led to the design of dedicated architectures for clusters with very fast communications between computing nodes. Efficient distributed storage in clusters has been essentially developed by adding parallelization mechanisms so that the server(s) may sustain an increased workload. In this work, we propose to improve the performance of distributed storage systems in clusters by efficiently using the underlying high-performance network to access distant storage systems. The main question we are addressing is: do high-speed networks of clusters fit the requirements of a transparent, efficient and high-performance access to remote storage? We show that storage requirements are very different from those of parallel computation. High-speed networks of clusters were designed to optimize communications between different nodes of a parallel application. We study their utilization in a very different context, storage in clusters, where client-server models are generally used to access remote storage (for instance NFS, PVFS or LUSTRE). Our experimental study based on the usage of the GM programming interface of MYRINET high-speed networks for distributed storage raised several interesting problems. Firstly, the specific memory utilization in the storage access system layers does not easily fit the traditional memory model of high-speed networks. Secondly, client-server models that are used for distributed storage have specific requirements on message control and event processing, which are not handled by existing interfaces. We propose different solutions to solve communication control problems at the filesystem level. We show that a modification of the network programming interface is required. Data transfer issues need an adaptation of the operating system. We detail several propositions for network programming interfaces which make their utilization easier in the context of distributed storage. The integration of a flexible processing of data transfer in the new programming interface MYRINET/MX is finally presented. Performance evaluations show that its usage in the context of both storage and other types of applications is easy and efficient.

Keywords: distributed storage, remote file access, cluster, high-speed network, MYRINET, zero-copy, memory registration, communication control, event notification, application programming interface

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Authors: Yutae Lee

Abstract:

In this paper, we consider the performance and availability of a redundancy model. The redundancy model is a form of resilience that ensures service availability in the event of component failure. This paper considers a 2N redundancy model. In the model there are at most one active service unit and at most one standby service unit. The active one is providing the service while the standby is prepared to take over the active role when the active fails. We design our analysis model using Stochastic Reward Nets, and then evaluate the performance and availability of 2N redundancy model using Stochastic Petri Net Package (SPNP).

Keywords: availability, performance, stochastic reward net, 2N redundancy

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Authors: Mikhail V. Khachaturyan, Inga A. Koryagina, Maria Nikishova

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The study investigates the impact of the ongoing financial crisis, started in the 2^nd half of 2014, on marketing budgets spent by Fast-moving consumer goods companies. In these conditions, special importance is given to efficient possessory risk management systems. The main objective for establishing and developing possessory risk management systems for FMCG companies in a crisis is to analyze the data relating to the external environment and consumer behavior in a crisis. Another important objective for possessory risk management systems of FMCG companies is to develop measures and mechanisms to maintain and stimulate sales. In this regard, analysis of risks and threats which consumers define as the main reasons affecting their level of consumption become important. It is obvious that in crisis conditions the effective risk management systems responsible for development and implementation of strategies for consumer demand stimulation, as well as the identification, analysis, assessment and management of other types of risks of economic security will be the key to sustainability of a company. In terms of financial and economic crisis, the problem of forming and developing possessory risk management systems becomes critical not only in the context of management models of FMCG companies, but for all the companies operating in other sectors of the Russian economy. This study attempts to analyze the specifics of formation and development of company possessory risk management systems. In the modern economy, special importance among all the types of owner’s risks has the risk of reduction in consumer activity. This type of risk is common not only for the consumer goods trade. Study of consumer activity decline is especially important for Russia due to domestic market of consumer goods being still in the development stage, despite its significant growth. In this regard, it is especially important to form and develop possessory risk management systems for FMCG companies. The authors offer their own interpretation of the process of forming and developing possessory risk management systems within owner’s management models of FMCG companies as well as in Russian economy in general. Proposed methods and mechanisms of problem analysis of formation and development of possessory risk management systems in FMCG companies and the results received can be helpful for researchers interested in problems of consumer goods market development in Russia and overseas.

Keywords: FMCG companies, marketing budget, risk management, owner, Russian economy, organization, formation, development, system

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Authors: V. A. Dubovsky, V. V. Savchenko, A. A. Baryskevich

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The current trend in the automotive industry towards automatic vehicles is creating new challenges related to human factors. This occurs due to the fact that the driver is increasingly relieved of the need to be constantly involved in driving the vehicle, which can negatively impact his/her situation awareness when manual control is required, and decrease driving skills and abilities. These new problems need to be studied in order to provide road safety during the transition towards self-driving vehicles. For this purpose, it is important to develop an appropriate conceptual model of the interaction between the driver and the automated vehicle, which could serve as a theoretical basis for the development of mathematical and simulation models to explore different aspects of driver behaviour in different road situations. Well-known driver behaviour models describe the impact of different stages of the driver's cognitive process on driving performance but do not describe how the driver controls and adjusts his actions. A more complete description of the driver's cognitive process, including the evaluation of the results of his/her actions, will make it possible to more accurately model various aspects of the human factor in different road situations. This paper presents a conceptual model of the 'driver – highly automated vehicle' system based on the P.K. Anokhin's theory of functional systems, which is a theoretical framework for describing internal processes in purposeful living systems based on such notions as goal, desired and actual results of the purposeful activity. A central feature of the proposed model is a dynamic coupling mechanism between the decision-making of a driver to perform a particular action and changes of road conditions due to driver’s actions. This mechanism is based on the stage by stage evaluation of the deviations of the actual values of the driver’s action results parameters from the expected values. The overall functional structure of the highly automated vehicle in the proposed model includes a driver/vehicle/environment state analyzer to coordinate the interaction between driver and vehicle. The proposed conceptual model can be used as a framework to investigate different aspects of human factors in transitions between automated and manual driving for future improvements in driving safety, and for understanding how driver-vehicle interface must be designed for comfort and safety. A major finding of this study is the demonstration that the theory of functional systems is promising and has the potential to describe the interaction of the driver with the vehicle and the environment.

Keywords: automated vehicle, driver behavior, human factors, human-machine system

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Authors: Xiaoqing Li

Abstract:

Social entrepreneurship drives the global movement as social enterprises create best ways to satisfy social needs through connecting international resources. However, what determines social enterprises to internationalize is underexplored. This study aims to answer this question by conducting a systematic review of studies of past 20 years on social enterprises' internationalization. Findings reveal that factors at the individual (entrepreneur), firm, and environment (home and host country) levels determine the degree of social enterprises' internationalization. Future research is challenged by: a. adopting an integrated approach examining the three levels to explain social enterprises' internationalization; b. the different nature of social enterprises from commercial businesses demands scholars to refine and develop appropriate theoretical models to capture the dynamism of social enterprises' internationalization behavior.

Keywords: determinants, entrepreneurship, internationalization, social enterprises

Procedia PDF Downloads 211