Search results for: energy 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

Procedia PDF Downloads 261

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: 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: Kuladeep Kumar Sadevi

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The shift towards raising global urban population has intense implications on the sustainability of the urban livelihoods. Rapid urbanization has made governments, companies and civil societies recognize that they are barely equipped to deal with growing urban demands, especially water, waste and energy management. Effective management of land, water, energy and waste at a community level should be addressed well to attain greener cities. In pursuit of Green livelihoods; various norms, codes, and green rating programmes have been followed by stakeholders at various levels. While the sustainability is being adapted at smaller scale developments, greening the urban environment at community/city level is still finding its path to reality. This is due to lack of the sense of ownership in the citizens for their immediate neighborhoods and city as a whole. This phenomenon can be well connected to the theory of 'tragedy of commons' with respect to the community engagement to manage the common pool resources. The common pool resource management has been well addressed by Elinor Ostrom, who shared the Nobel Prize in Economics in 2009 for her lifetime of scholarly work investigating how communities succeed or fail at managing common pool (finite) resources. This paper examines the applicability of Elinor Ostrom's 8 Principles for Managing a Commons, to meet urban sustainability. The key objective of this paper is to come up with a model for effective urban common pool resource management, which ultimately leads to sustainability as a whole. The paper brings out a methodology to understand various parameters involved in urban sustainability, examine the synergies of all such parameters, and application of Ostrom’s principles to correlate these parameters in order to attain effective urban resource management.

Keywords: common pool resources, green cities, green communities, participatory management, sustainable development, urban resource management, urban sustainability

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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: N. Dahbi, M. Daoudi

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This paper deals with the use of computational method based on Monte Carlo simulation in order to investigate the transport phenomena of the electron in HgCdTe narrow band gap semiconductor. Via this method we can evaluate the time dependence of the transport parameters: velocity, energy and mobility of electrons through matter (HgCdTe).

Keywords: Monte Carlo, transport parameters, HgCdTe, computational mechanics

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Authors: Soney C. George, Thomasukutty Jose, Sabu Thomas

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Membrane based separation is the most important energy –efficient separation processes. There are wide ranges of membrane based separation process such as Micro-filtration, ultra filtration, reverse osmosis, electro-dialysis etc. Among these pervaporation is one of the most promising techniques. The promising technique is in the sense that it needs an ease of process design, low energy consumption, environmentally clean, economically cost effective and easily separate azeotropic composition without losing any components, unlike distillation in a short period of time. In the present work, we developed a new bentonite clay reinforced cross-linked PVA nano-composite membranes by solution casting method. The membranes were used for the pervaporation separation of azeotropic composition of isopropanol and water mixtures. The azeotropic composition of water and isopropanol is difficult to separate and we can’t get a better separation by normal separation processes. But the better separation was achieved here using cross-linked PVA/Clay nano-composite membranes. The 2wt% bentonite clay reinforced 5vol% GA cross-linked nano-composite membranes showed better separation efficiency. The selectivity of the cross-linked membranes increases 65% upon filler loading. The water permeance is showed tremendous enhancement upon filler loading. The permeance value changes from 4100 to 8200, due to the incorporation hydrophilic bentonite clay to the cross-linked PVA membranes. The clay reinforced membranes shows better thermal stability upon filler loading was confirmed from TGA and DSC analysis. The dispersion of nanoclay in the polymeric matrix was clearly evident from the TEM analysis. The better dispersed membranes showed better separation performance. Thus the developed cross-linked PVA/Clay membranes can be effectively used for the separation of azeotropic composition of water and isopropanol.

Keywords: poly(vinyl alcohol), membrane, gluraldehyde, permeance

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Authors: Davide Cocchi, Andrea Zucchelli, Luca Raimondi, Maria Brugo Tommaso

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The increasing attention is given to the issues of environmental pollution and climate change is exponentially stimulating the development of electrically propelled vehicles powered by renewable energy, in particular, the solar one. Given the small amount of solar energy that can be stored and subsequently transformed into propulsive energy, it is necessary to develop vehicles with high mechanical, electrical and aerodynamic efficiencies along with reduced masses. The reduction of the masses is of fundamental relevance especially for the unsprung masses, that is the assembly of those elements that do not undergo a variation of their distance from the ground (wheel, suspension system, hub, upright, braking system). Therefore, the reduction of unsprung masses is fundamental in decreasing the rolling inertia and improving the drivability, comfort, and performance of the vehicle. This principle applies even more in solar propelled vehicles, equipped with an electric motor that is connected directly to the wheel hub. In this solution, the electric motor is integrated inside the wheel. Since the electric motor is part of the unsprung masses, the development of compact and lightweight solutions is of fundamental importance. The purpose of this research is the design development and optimization of a CFRP 16 wheel hub motor for solar propulsion vehicles that can carry up to four people. In addition to trying to maximize aspects of primary importance such as mass, strength, and stiffness, other innovative constructive aspects were explored. One of the main objectives has been to achieve a high geometric packing in order to ensure a reduced lateral dimension, without reducing the power exerted by the electric motor. In the final solution, it was possible to realize a wheel hub motor assembly completely comprised inside the rim width, for a total lateral overall dimension of less than 100 mm. This result was achieved by developing an innovative connection system between the wheel and the rotor with a double purpose: centering and transmission of the driving torque. This solution with appropriate interlocking noses allows the transfer of high torques and at the same time guarantees both the centering and the necessary stiffness of the transmission system. Moreover, to avoid delamination in critical areas, evaluated by means of FEM analysis using 3D Hashin damage criteria, electrospun nanofibrous mats have been interleaved between CFRP critical layers. In order to reduce rolling resistance, the rim has been designed to withstand high inflation pressure. Laboratory tests have been performed on the rim using the Digital Image Correlation technique (DIC). The wheel has been tested for fatigue bending according to E/ECE/324 R124e.

Keywords: composite laminate, delamination, DIC, lightweight vehicle, motor hub wheel, nanofiber

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Authors: Zunaira Zaman, David Bohannon

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This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

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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: Anna V. Zaporozhchenko, Dmytro Kutnyakhov, Katherina Medjanik, Christian Tusche, Hans-Joachim Elmers, Olena Fedchenko, Sergey Chernov, Martin Ellguth, Sergej A. Nepijko, Gerd Schoenhense

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Graphene reveals a unique electronic structure that predetermines many intriguing properties such as massless charge carriers, optical transparency and high velocity of fermions at the Fermi level, opening a wide horizon of future applications. Hence, a detailed investigation of the electronic structure of graphene is crucial. The method of choice is angular resolved photoelectron spectroscopy ARPES. Here we present experiments using time-of-flight (ToF) momentum microscopy, being an alternative way of ARPES using full-field imaging of the whole Brillouin zone (BZ) and simultaneous acquisition of up to several 100 energy slices. Unlike conventional ARPES, k-microscopy is not limited in simultaneous k-space access. We have recorded the whole first BZ of graphene on Ir(111) including all six Dirac cones. As excitation source we used synchrotron radiation from BESSY II (Berlin) at the U125-2 NIM, providing linearly polarized (both polarizations p- and s-) VUV radiation. The instrument uses a delay-line detector for single-particle detection up the 5 Mcps range and parallel energy detection via ToF recording. In this way, we gather a 3D data stack I(E,kx,ky) of the full valence electronic structure in approx. 20 mins. Band dispersion stacks were measured in the energy range of 14 eV up to 23 eV with steps of 1 eV. The linearly-dispersing graphene bands for all six K and K’ points were simultaneously recorded. We find clear features of hybridization with the substrate, in particular in the linear dichroism in the angular distribution (LDAD). Recording of the whole Brillouin zone of graphene/Ir(111) revealed new features. First, the intensity differences (i.e. the LDAD) are very sensitive to the interaction of graphene bands with substrate bands. Second, the dark corridors are investigated in detail for both, p- and s- polarized radiation. They appear as local distortions of photoelectron current distribution and are induced by quantum mechanical interference of graphene sublattices. The dark corridors are located in different areas of the 6 Dirac cones and show chirality behaviour with a mirror plane along vertical axis. Moreover, two out of six show an oval shape while the rest are more circular. It clearly indicates orientation dependence with respect to E vector of incident light. Third, a pattern of faint but very sharp lines is visible at energies around 22eV that strongly remind on Kikuchi lines in diffraction. In conclusion, the simultaneous study of all six Dirac cones is crucial for a complete understanding of dichroism phenomena and the dark corridor.

Keywords: band structure, graphene, momentum microscopy, LDAD

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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: Abderrahmane Diaf, Assia Cherfa, Lamia Karadaniz

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Multiple tray solar distillation offers an interesting alternative for small-scale desalination and production high quality distilled water at a competitive cost using solar energy. In this work, we present indoor/outdoor trial performance data of our multiple tray solar distillation as well as the results of cost estimation analysis.

Keywords: solar desalination, tray distillation, multi-étages solaire, solar distillation

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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: 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: Jayakrishnan U.

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A concept of adding two strokes to a four stroke Otto or Diesel engine cycle presented here for the waste heat recovery in a four stroke internal combustion engine. Four stroke Diesel cycle and Otto cycle engines have very low thermal efficiency due to high amount of energy loss in exhaust and also on the cooling of the engine. It is estimated about 35 percent of fuel energy is lost in exhaust of engine and 30 percent in cooling of engine. So by modifying a four-stroke Otto or Diesel engine by adding two-stroke heat recovery steam cycle is presented here. Water injection is used to get an additional power stroke by partial compression of the exhaust gases at the end of third stroke in a four stroke I.C.Engine. It is the conversion of a four-stroke cycle to a six-stroke cycle. By taking a four stroke petrol engine of known dimensions, an ideal thermodynamic model is used to analyse and calculate the events of exhaust gas compression and following two strokes of water injection. By changing the exhaust valve closing timing during exhaust stroke and analysing it on various points, an optimum amount of exhaust gas re-compression and amount of water injection can be found for maximizing efficiency and fuel economy. It is achieved by changing the exhaust valve timing and finding an optimum amount of exhaust re-compression, maximizing the net mean effective pressure of the steam expansion stroke (MEPsteam). Specific fuel consumption of the engine also decreases increasing the fuel economy. The valve closing timings for maximum MEPsteam is limited by either 1 bar or dew point temperature of expansion gas or moisture mixture to avoid moisture formation. By modifying the four-stroke Otto or Diesel cycle by adding two water injection stroke has the potential to significantly increase the engine efficiency and fuel economy.

Keywords: internal combustion engine, engine efficiency, six-stroke cycle, water injection, specific fuel consumption

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Authors: Mamouni Mohammed Dhiya Eddine

Abstract:

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: Pabitra Sahu, M. Manohari, S. Priyadharshini, R. Santhanam, S. Chandrasekaran, B. Venkatraman

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Radiation workers of reprocessing plants have a potential for internal exposure due to actinides and fission products. Radionuclides like Americium, lead, Polonium and Europium are bone seekers and get accumulated in the skeletal part. As the major skeletal content is in the skull (13%) and knee (22%), measurements of old intake have to be carried out in the skull and knee. At the Indira Gandhi Centre for Atomic Research, a twin HPGe-based actinide monitor is used for the measurement of actinides present in bone. Efficiency estimation, which is one of the prerequisites for the quantification of radionuclides, requires anthropomorphic phantoms. Such phantoms are very limited. Hence, in this study, efficiency curves for a Twin HPGe-based actinide monitoring system are established theoretically using the FLUKA Monte Carlo method and ICRP adult male voxel phantom. In the case of skull measurement, the detector is placed over the forehead, and for knee measurement, one detector is placed over each knee. The efficiency values of radionuclides present in the knee and skull vary from 3.72E-04 to 4.19E-04 CPS/photon and 5.22E-04 to 7.07E-04 CPS/photon, respectively, for the energy range 17 to 3000keV. The efficiency curves for the measurement are established, and it is found that initially, the efficiency value increases up to 100 keV and then starts decreasing. It is found that the skull efficiency values are 4% to 63% higher than that of the knee, depending on the energy for all the energies except 17.74 keV. The reason is the closeness of the detector to the skull compared to the knee. But for 17.74 keV the efficiency of the knee is more than the skull due to the higher attenuation caused in the skull bones because of its greater thickness. The Minimum Detectable Activity (MDA) for 241Am present in the skull and knee is 9 Bq. 239Pu has a MDA of 950 Bq and 1270 Bq for knee and skull, respectively, for a counting time of 1800 sec. This paper discusses the simulation method and the results obtained in the study.

Keywords: FLUKA Monte Carlo Method, ICRP adult male voxel phantom, knee, Skull.

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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

Procedia PDF Downloads 406

Authors: Henry Gonzalo Acurio Flores, Alvaro Nicolas Corral Naveda, Juan Francisco Fonseca Palacios

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In Ecuador, subventions on fossil fuels for the road transportation sector have always been part of its economy throughout time, mainly because of demagogy and populism from political leaders. It is clearly seen that the government cannot maintain the subsidies anymore due to its commercial balance and its general state budget; subsidies are a key barrier to implementing the use of cleaner technologies. However, during the last few months, the elimination of subsidies has been done gradually with the purpose of reaching international prices. It is expected that with this measure, the population will opt for other means of transportation, and in a certain way, it will promote the use of private electric vehicles and public, e.g., taxis and buses (urban transport). Considering the three main elements of sustainable development, an analysis of the social, economic, and environmental impacts of eliminating subsidies will be generated at the country level. To achieve this, four scenarios will be developed in order to determine how the subsidies will contribute to the promotion of electro-mobility. 1) A Business as Usual BAU scenario; 2) the introduction of 10 000 electric vehicles by 2025; 3) the introduction of 100 000 electric vehicles by 2030; 4) the introduction of 750 000 electric vehicles by 2040 (for all the scenarios buses, taxis, lightweight duty vehicles, and private vehicles will be introduced, as it is established in the National Electro Mobility Strategy for Ecuador). The Low Emissions Analysis Platform (LEAP) will be used, and it will be suitable to determine the cost for the government in terms of importing derivatives for fossil fuels and the cost of electricity to power the electric fleet that can be changed. The elimination of subventions generates fiscal resources for the state that can be used to develop other kinds of projects that will benefit Ecuadorian society. It will definitely change the energy matrix, and it will provide energy security for the country; it will be an opportunity for the government to incentivize a greater introduction of renewable energies, e.g., solar, wind, and geothermal. At the same time, it will also reduce greenhouse gas emissions (GHG) from the transportation sector, considering its mitigation potential, which as a result, will ameliorate the inhabitant quality of life by improving the quality of air, therefore reducing respiratory diseases associated with exhaust emissions, consequently, achieving sustainability, the Sustainable Development Goals (SDGs), and complying with the agreements established in the Paris Agreement COP 21 in 2015. Electro mobility in Latin America and the Caribbean can only be achieved by the implementation of the right policies at the central government, which need to be accompanied by a National Urban Mobility Policy (NUMP) and can encompass a greater vision to develop holistic, sustainable transport systems at local governments.

Keywords: electro mobility, energy, policy, sustainable transportation

Procedia PDF Downloads 76

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

Procedia PDF Downloads 369

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

Abstract:

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

Procedia PDF Downloads 133