Search results for: probability weighted moment estimation

Authors: E. E. S. Uy, T. Noda, K. Nakai, J. R. Dungca

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Cyclic threshold shear strain is the cyclic shear strain amplitude that serves as the indicator of the development of pore water pressure. The parameter can be obtained by performing either cyclic triaxial test, shaking table test, cyclic simple shear or resonant column. In a cyclic triaxial test, other researchers install measuring devices in close proximity of the soil to measure the parameter. In this study, an attempt was made to estimate the cyclic threshold shear strain parameter using full-field measurement technique. The technique uses a camera to monitor and measure the movement of the soil. For this study, the technique was incorporated in a strain-controlled consolidated undrained cyclic triaxial test. Calibration of the camera was first performed to ensure that the camera can properly measure the deformation under cyclic loading. Its capacity to measure deformation was also investigated using a cylindrical rubber dummy. Two-dimensional image processing was implemented. Lucas and Kanade optical flow algorithm was applied to track the movement of the soil particles. Results from the full-field measurement technique were compared with the results from the linear variable displacement transducer. A range of values was determined from the estimation. This was due to the nonhomogeneous deformation of the soil observed during the cyclic loading. The minimum values were in the order of 10-2% in some areas of the specimen.

Keywords: cyclic loading, cyclic threshold shear strain, full-field measurement, optical flow

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Authors: Riofrio Jonathan, Fernandez Guillermo

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Renewable energy represented around 80% of the energy matrix for power generation in Ecuador during 2020, so the deployment of current public policies is focused on taking advantage of the high presence of renewable sources to carry out several electrification projects. These projects are part of the portfolio sent to the United Nations Framework on Climate Change (UNFCCC) as a commitment to reduce greenhouse gas emissions (GHG) in the established national determined contribution (NDC). In this sense, the Ecuadorian Organic Energy Efficiency Law (LOEE) published in 2019 promotes E-mobility as one of the main milestones. In fact, it states that the new vehicles for urban and interurban usage must be E-buses since 2025. As a result, and for a successful implementation of this technological change in a national context, it is important to deploy land surveys focused on technical and geographical areas to keep the quality of services in both the electricity and transport sectors. Therefore, this research presents a technological and energy comparison between a conventional diesel bus and its equivalent E-bus. Both vehicles fulfill all the technical requirements to ride in the study-case city, which is Ambato in the province of Tungurahua-Ecuador. In addition, the analysis includes the development of a model for the energy estimation of both technologies that are especially applied in a highland city such as Ambato. The altimetry of the most important bus routes in the city varies from 2557 to 3200 m.a.s.l., respectively, for the lowest and highest points. These operation conditions provide a grade of novelty to this paper. Complementary, the technical specifications of diesel buses are defined following the common features of buses registered in Ambato. On the other hand, the specifications for E-buses come from the most common units introduced in Latin America because there is not enough evidence in similar cities at the moment. The achieved results will be good input data for decision-makers since electric demand forecast, energy savings, costs, and greenhouse gases emissions are computed. Indeed, GHG is important because it allows reporting the transparency framework that it is part of the Paris Agreement. Finally, the presented results correspond to stage I of the called project “Analysis and Prospective of Electromobility in Ecuador and Energy Mix towards 2030” supported by Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ).

Keywords: high altitude cities, energy planning, NDC, e-buses, e-mobility

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Authors: Yunwei Tang, Linhai Jing, Hui Li, Qingjie Liu, Xiuxia Li, Qi Yan, Haifeng Ding

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The giant panda (Ailuropoda melanoleuca) is an endangered species, mainly live in central China, where bamboos act as the main food source of wild giant pandas. Knowledge of spatial distribution of bamboos therefore becomes important for identifying the habitat of giant pandas. There have been ongoing studies for mapping bamboos and other tree species using remote sensing. WorldView-2 (WV-2) is the first high resolution commercial satellite with eight Multi-Spectral (MS) bands. Recent studies demonstrated that WV-2 imagery has a high potential in classification of tree species. The advanced classification techniques are important for utilising high spatial resolution imagery. It is generally agreed that object-based image analysis is a more desirable method than pixel-based analysis in processing high spatial resolution remotely sensed data. Classifiers that use spatial information combined with spectral information are known as contextual classifiers. It is suggested that contextual classifiers can achieve greater accuracy than non-contextual classifiers. Thus, spatial correlation can be incorporated into classifiers to improve classification results. The study area is located at Wuyipeng area in Wolong, Sichuan Province. The complex environment makes it difficult for information extraction since bamboos are sparsely distributed, mixed with brushes, and covered by other trees. Extensive fieldworks in Wuyingpeng were carried out twice. The first one was on 11th June, 2014, aiming at sampling feature locations for geometric correction and collecting training samples for classification. The second fieldwork was on 11th September, 2014, for the purposes of testing the classification results. In this study, spectral separability analysis was first performed to select appropriate MS bands for classification. Also, the reflectance analysis provided information for expanding sample points under the circumstance of knowing only a few. Then, a spatially weighted object-based k-nearest neighbour (k-NN) classifier was applied to the selected MS bands to identify seven land cover types (bamboo, conifer, broadleaf, mixed forest, brush, bare land, and shadow), accounting for spatial correlation within classes using geostatistical modelling. The spatially weighted k-NN method was compared with three alternatives: the traditional k-NN classifier, the Support Vector Machine (SVM) method and the Classification and Regression Tree (CART). Through field validation, it was proved that the classification result obtained using the spatially weighted k-NN method has the highest overall classification accuracy (77.61%) and Kappa coefficient (0.729); the producer’s accuracy and user’s accuracy achieve 81.25% and 95.12% for the bamboo class, respectively, also higher than the other methods. Photos of tree crowns were taken at sample locations using a fisheye camera, so the canopy density could be estimated. It is found that it is difficult to identify bamboo in the areas with a large canopy density (over 0.70); it is possible to extract bamboos in the areas with a median canopy density (from 0.2 to 0.7) and in a sparse forest (canopy density is less than 0.2). In summary, this study explores the ability of WV-2 imagery for bamboo extraction in a mountainous region in Sichuan. The study successfully identified the bamboo distribution, providing supporting knowledge for assessing the habitats of giant pandas.

Keywords: bamboo mapping, classification, geostatistics, k-NN, worldview-2

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Authors: Y. Sunecher, N. Mamode Khan, V. Jowaheer

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This paper considers the modelling of a non-stationary bivariate integer-valued autoregressive moving average of order one (BINARMA(1,1)) with correlated Poisson innovations. The BINARMA(1,1) model is specified using the binomial thinning operator and by assuming that the cross-correlation between the two series is induced by the innovation terms only. Based on these assumptions, the non-stationary marginal and joint moments of the BINARMA(1,1) are derived iteratively by using some initial stationary moments. As regards to the estimation of parameters of the proposed model, the conditional maximum likelihood (CML) estimation method is derived based on thinning and convolution properties. The forecasting equations of the BINARMA(1,1) model are also derived. A simulation study is also proposed where BINARMA(1,1) count data are generated using a multivariate Poisson R code for the innovation terms. The performance of the BINARMA(1,1) model is then assessed through a simulation experiment and the mean estimates of the model parameters obtained are all efficient, based on their standard errors. The proposed model is then used to analyse a real-life accident data on the motorway in Mauritius, based on some covariates: policemen, daily patrol, speed cameras, traffic lights and roundabouts. The BINARMA(1,1) model is applied on the accident data and the CML estimates clearly indicate a significant impact of the covariates on the number of accidents on the motorway in Mauritius. The forecasting equations also provide reliable one-step ahead forecasts.

Keywords: non-stationary, BINARMA(1, 1) model, Poisson innovations, conditional maximum likelihood, CML

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Authors: J. Bahrawi, M. Elhag

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Estimation of evapotranspiration is always a major component in water resources management. Traditional techniques of calculating daily evapotranspiration based on field measurements are valid only for local scales. Earth observation satellite sensors are thus used to overcome difficulties in obtaining daily evapotranspiration measurements on regional scale. The Surface Energy Balance System (SEBS) model was adopted to estimate daily evapotranspiration and relative evaporation along with other land surface energy fluxes. The model requires agro-climatic data that improve the model outputs. Advance Along Track Scanning Radiometer (AATSR) and Medium Spectral Resolution Imaging Spectrometer (MERIS) imageries were used to estimate the daily evapotranspiration and relative evaporation over the entire Nile Delta region in Egypt supported by meteorological data collected from six different weather stations located within the study area. Daily evapotranspiration maps derived from SEBS model show a strong agreement with actual ground-truth data taken from 92 points uniformly distributed all over the study area. Moreover, daily evapotranspiration and relative evaporation are strongly correlated. The reliable estimation of daily evapotranspiration supports the decision makers to review the current land use practices in terms of water management, while enabling them to propose proper land use changes.

Keywords: daily evapotranspiration, relative evaporation, SEBS, AATSR, MERIS, Nile Delta

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Authors: Nazli Uren, Ayse Okur

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Tactile comfort of a textile product is an essential property and a major concern when it comes to customer perceptions and preferences. The subjective nature of comfort and the difficulties regarding the simulation of human hand sensory feelings make it hard to establish a well-accepted link between tactile comfort and objective evaluations. On the other hand, shear behavior of a fabric is a mechanical parameter which can be measured by various objective test methods. The principal aim of this study is to determine the tactile comfort of commercially available denim fabrics by subjective measurements, create a tactile score database for denim fabrics and investigate the relations between tactile comfort and shear behavior. In-plane shear behaviors of 17 different commercially available denim fabrics with a variety of raw material and weave structure were measured by a custom design shear frame and conventional bias extension method in two corresponding diagonal directions. Tactile comfort of denim fabrics was determined via subjective customer evaluations as well. Aforesaid relations were statistically investigated and introduced as regression equations. The analyses regarding the relations between tactile comfort and shear behavior showed that there are considerably high correlation coefficients. The suggested regression equations were likewise found out to be statistically significant. Accordingly, it was concluded that the tactile comfort of denim fabrics can be estimated with a high precision, based on the results of in-plane shear behavior measurements.

Keywords: denim fabrics, in-plane shear behavior, linear regression estimation, tactile comfort

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Authors: S. da Costa, D. Páez, E. Martínez, A. Torres, M. Beramendi, D. Hermosilla, M. Muratori

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This study examined the association between creative performance, organizational climate and leadership, affectivity, shared flow, and group decision making. The sample consisted of 315 cadets of a military academic unit of South America. Satisfaction with the decision-making process during a creative task was associated with the usefulness and effectiveness of the ideas generated by the teams with a weighted average correlation of r = .18. Organizational emotional climate, positive and innovation leadership were associated with this group decision-making process r = .25, with shared flow, r = .29 and with positive affect felt during the performance of the creative task, r = .12. In a sequential mediational analysis positive organizational leadership styles were significantly associated with decision-making process and trough cohesion with utility and efficacy of the solution of a creative task. Satisfactory decision-making was related to shared flow during the creative task at collective or group level, and positive affect with flow at individual level.This study examined the association between creative performance, organizational climate and leadership, affectivity, shared flow, and group decision making. The sample consisted of 315 cadets of a military academic unit of South America. Satisfaction with the decision-making process during a creative task was associated with the usefulness and effectiveness of the ideas generated by the teams with a weighted average correlation of r = .18. Organizational emotional climate, positive and innovation leadership were associated with this group decision-making process r = .25, with shared flow, r = .29 and with positive affect felt during the performance of the creative task, r = .12. In a sequential mediational analysis positive organizational leadership styles were significantly associated with decision-making process and trough cohesion with utility and efficacy of the solution of a creative task. Satisfactory decision-making was related to shared flow during the creative task at collective or group level, and positive affect with flow at individual level.

Keywords: creativity, innovation, military, organization, teams

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Authors: Vishwa Nath Maurya, Rama Shanker Sharma, Saad Talib Hasson Aljebori, Avadhesh Kumar Maurya, Diwinder Kaur Arora

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Present paper deals with problems of determining the relationship between the variables of corporate governance and financial performance of Islamic banks. Here, we dealt with the corporate governance in the banking sector, where increasing the importance of corporate governance, due to their special nature, as the bankruptcy of banks affects not only the relevant parties from customers, depositors and lenders, but also affect financial stability and then the economy as a whole. Through this paper we dealt to the specificity of governance in Islamic banks, which face double governance: Anglo-Saxon governance system and Islamic governance system. In addition, we focused our attention to measure the impact of corporate governance variables on financial performance through an empirical study on a sample of Islamic banks during the period 2005-2012 in the GCC region. Our present study implies that there is a very strong relationship between the variables of governance and financial performance of Islamic banks, where there is a positive relationship between return on assets and the composition of the Board of Directors, the size of the Board of Directors, the number of committees in the Council, as well as the number of members of the Sharia Supervisory Board, while it is clear that there is a negative relationship between return on assets and concentration ownership.

Keywords: correlation analysis, parametric estimation, corporate governance, financial performance, financial stability, conventional banks, bankruptcy, Islamic governance system

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Authors: M. Saiful Islam, M. Mohandes, S. Rehman, S. Badran

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Increasing necessity of wind power is directing us to have precise knowledge on wind resources. Methodical investigation of potential locations is required for wind power deployment. High penetration of wind energy to the grid is leading multi megawatt installations with huge investment cost. This fact appeals to determine appropriate places for wind farm operation. For accurate assessment, detailed examination of wind speed profile, relative humidity, temperature and other geological or atmospheric parameters are required. Among all of these uncertainty factors influencing wind power estimation, vertical extrapolation of wind speed is perhaps the most difficult and critical one. Different approaches have been used for the extrapolation of wind speed to hub height which are mainly based on Log law, Power law and various modifications of the two. This paper proposes a Artificial Neural Network (ANN) and Genetic Algorithm (GA) based hybrid model, namely GA-NN for vertical extrapolation of wind speed. This model is very simple in a sense that it does not require any parametric estimations like wind shear coefficient, roughness length or atmospheric stability and also reliable compared to other methods. This model uses available measured wind speeds at 10m, 20m and 30m heights to estimate wind speeds up to 100m. A good comparison is found between measured and estimated wind speeds at 30m and 40m with approximately 3% mean absolute percentage error. Comparisons with ANN and power law, further prove the feasibility of the proposed method.

Keywords: wind profile, vertical extrapolation of wind, genetic algorithm, artificial neural network, hybrid machine learning

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Authors: M. Gulam Kibria, Shourav Ahmed, Kais Zaman

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In system analysis, the information on the uncertain input variables cause uncertainty in the system responses. Different probabilistic approaches for uncertainty representation and propagation in such cases exist in the literature. Different uncertainty representation approaches result in different outputs. Some of the approaches might result in a better estimation of system response than the other approaches. The NASA Langley Multidisciplinary Uncertainty Quantification Challenge (MUQC) has posed challenges about uncertainty quantification. Subproblem A, the uncertainty characterization subproblem, of the challenge posed is addressed in this study. In this subproblem, the challenge is to gather knowledge about unknown model inputs which have inherent aleatory and epistemic uncertainties in them with responses (output) of the given computational model. We use two different methodologies to approach the problem. In the first methodology we use sampling-based uncertainty propagation with first order error analysis. In the other approach we place emphasis on the use of Percentile-Based Optimization (PBO). The NASA Langley MUQC’s subproblem A is developed in such a way that both aleatory and epistemic uncertainties need to be managed. The challenge problem classifies each uncertain parameter as belonging to one the following three types: (i) An aleatory uncertainty modeled as a random variable. It has a fixed functional form and known coefficients. This uncertainty cannot be reduced. (ii) An epistemic uncertainty modeled as a fixed but poorly known physical quantity that lies within a given interval. This uncertainty is reducible. (iii) A parameter might be aleatory but sufficient data might not be available to adequately model it as a single random variable. For example, the parameters of a normal variable, e.g., the mean and standard deviation, might not be precisely known but could be assumed to lie within some intervals. It results in a distributional p-box having the physical parameter with an aleatory uncertainty, but the parameters prescribing its mathematical model are subjected to epistemic uncertainties. Each of the parameters of the random variable is an unknown element of a known interval. This uncertainty is reducible. From the study, it is observed that due to practical limitations or computational expense, the sampling is not exhaustive in sampling-based methodology. That is why the sampling-based methodology has high probability of underestimating the output bounds. Therefore, an optimization-based strategy to convert uncertainty described by interval data into a probabilistic framework is necessary. This is achieved in this study by using PBO.

Keywords: aleatory uncertainty, epistemic uncertainty, first order error analysis, uncertainty quantification, percentile-based optimization

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Authors: Wilson P. R. Malebye, Solly M. Seeletse

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Applicants for space in selection problems are usually compared subjectively, and the selection made are not reliable and often cannot be verified scientifically. The paper illustrates objective selection by involving a mathematical measure in selecting a candidate applying for a job, and then using other two independent measures, validates the choice made. The scientific process followed is SToR (SAW, TOPSIS, WP) in which Simple Additive Weighting (SAW) is used to select, and the TOPSIS (technique for order preference by similarity to ideal solution) and weighted product (WP) are used to validate. A practical exercise was obtained from a factual selection problem in a recruitment task undertaken in an organization in which the authors consulted, and their Human Resources (HR) department wanted to check if their selection was justifiable. The result was that our approach was consistent and convincing to that HR, and theirs was not because our selection was satisfactory while theirs could not be corroborated using any method.

Keywords: candidate selection, SToR, SW, TOPSIS, WP

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Authors: Kamran Yazdanbakhsh, Somayeh Mahmoudi

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Three reasons make good use of the decision theory in medicine: 1. Increased medical knowledge and their complexity makes it difficult treatment information effectively without resorting to sophisticated analytical methods, especially when it comes to detecting errors and identify opportunities for treatment from databases of large size. 2. There is a wide geographic variability of medical practice. In a context where medical costs are, at least in part, by the patient, these changes raise doubts about the relevance of the choices made by physicians. These differences are generally attributed to differences in estimates of probabilities of success of treatment involved, and differing assessments of the results on success or failure. Without explicit criteria for decision, it is difficult to identify precisely the sources of these variations in treatment. 3. Beyond the principle of informed consent, patients need to be involved in decision-making. For this, the decision process should be explained and broken down. A decision problem is to select the best option among a set of choices. The problem is what is meant by "best option ", or know what criteria guide the choice. The purpose of decision theory is to answer this question. The systematic use of decision models allows us to better understand the differences in medical practices, and facilitates the search for consensus. About this, there are three types of situations: situations certain, risky situations, and uncertain situations: 1. In certain situations, the consequence of each decision are certain. 2. In risky situations, every decision can have several consequences, the probability of each of these consequences is known. 3. In uncertain situations, each decision can have several consequences, the probability is not known. Our aim in this article is to show how decision theory can usefully be mobilized to meet the needs of physicians. The decision theory can make decisions more transparent: first, by clarifying the data systematically considered the problem and secondly by asking a few basic principles should guide the choice. Once the problem and clarified the decision theory provides operational tools to represent the available information and determine patient preferences, and thus assist the patient and doctor in their choices.

Keywords: decision making, medicine, treatment strategies, patient

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Authors: Tingting Song

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Wetlands are significant ecosystems that provide a variety of ecosystem services for humans, such as, providing water and food resources, purifying water quality, regulating climate, protecting biodiversity, and providing cultural, recreational, and educational resources. Wetlands also provide benefits, such as reduction of flood, storm damage, and soil erosion. The flood protection ecosystem services of wetlands are often ignored. Due to climate change, the flood caused by extreme weather in recent years occur frequently. Flood has a great impact on people's production and life with more and more economic losses. This study area is in the Tone river basin in the Kanto area, Japan. It is the second-longest river with the largest basin area in Japan, and it is still suffering heavy economic losses from floods. Tone river basin is one of the rivers that provide water for Tokyo and has an important impact on economic activities in Japan. The purpose of this study was to investigate land-use changes of wetlands in the Tone River Basin, and whether there are spatial differences in the value of wetland functions in mitigating economic losses caused by floods. This study analyzed the land-use change of wetland in Tone River, based on the Landsat data from 1980 to 2020. Combined with flood economic loss, wetland area, GDP, population density, and other social-economic data, a geospatial weighted regression model was constructed to analyze the spatial difference of wetland ecosystem service value. Now, flood protection mainly relies on such a hard project of dam and reservoir, but excessive dependence on hard engineering will cause the government huge financial pressure and have a big impact on the ecological environment. However, natural wetlands can also play a role in flood management, at the same time they can also provide diverse ecosystem services. Moreover, the construction and maintenance cost of natural wetlands is lower than that of hard engineering. Although it is not easy to say which is more effective in terms of flood management. When the marginal value of a wetland is greater than the economic loss caused by flood per unit area, it may be considered to rely on the flood storage capacity of the wetland to reduce the impact of the flood. It can promote the sustainable development of wetlands ecosystem. On the other hand, spatial analysis of wetland values can provide a more effective strategy for flood management in the Tone river basin.

Keywords: wetland, geospatial weighted regression, ecosystem services, environment valuation

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Authors: Hazem M. Al-Mofleh, John E. Daniels, Joseph W. McKean

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In this paper numerous robust fitting procedures are considered in estimating spatial variograms. In spatial statistics, the conventional variogram fitting procedure (non-linear weighted least squares) suffers from the same outlier problem that has plagued this method from its inception. Even a 3-parameter model, like the variogram, can be adversely affected by a single outlier. This paper uses the Hogg-Type adaptive procedures to select an optimal score function for a rank-based estimator for these non-linear models. Numeric examples and simulation studies will demonstrate the robustness, utility, efficiency, and validity of these estimates.

Keywords: asymptotic relative efficiency, non-linear rank-based, rank estimates, variogram

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Authors: Eleni Tsalaporta, Sebastien Vaesen, James M. D. MacElroy, Wolfgang Schmitt

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Carbon dioxide capture has attracted the attention of many governments, industries and scientists over the last few decades, due to the rapid increase in atmospheric CO2 composition, with several studies being conducted in this area over the last few years. In many of these studies, CO2 capture in complex Pressure Swing Adsorption (PSA) cycles has been associated with high energy consumption despite the promising capture performance of such processes. The purpose of this study is the economic capture of atmospheric carbon dioxide for its transformation into a clean type of energy. A single column Temperature /Vacuum Swing Adsorption (TSA/VSA) process is proposed as an alternative option to multi column Pressure Swing Adsorption (PSA) processes. The proposed adsorbent is SIFSIX-3-Ni, a newly developed MOF (Metal Organic Framework), with extended CO2 selectivity and capacity. There are three stages involved in this paper: (i) SIFSIX-3-Ni is synthesized and pelletized and its physical and chemical properties are examined before and after the pelletization process, (ii) experiments are designed and undertaken for the estimation of the diffusion and adsorption parameters and limitations for CO2 undergoing capture from the air; and (iii) the CO2 adsorption capacity and dynamical characteristics of SIFSIX-3-Ni are investigated both experimentally and mathematically by employing a single column TSA/VSA, for the capture of atmospheric CO2. This work is further supported by a technical-economical study for the estimation of the investment cost and the energy consumption of the single column TSA/VSA process. The simulations are performed using gProms.

Keywords: carbon dioxide capture, temperature/vacuum swing adsorption, metal organic frameworks, SIFSIX-3-Ni

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Authors: Ainura Tursunalieva, Irene Hudson

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Continuous improvement of both the quality and safety of health care is an important goal in Australia and internationally. The intensive care unit (ICU) receives patients with a wide variety of and severity of illnesses. Accurately identifying patients at risk of developing complications or dying is crucial to increasing healthcare efficiency. Thus, it is essential for clinicians and researchers to have a robust framework capable of evaluating the risk profile of a patient. ICU scoring systems provide such a framework. The Acute Physiology and Chronic Health Evaluation III and the Simplified Acute Physiology Score II are ICU scoring systems frequently used for assessing the severity of acute illness. These scoring systems collect multiple risk factors for each patient including physiological measurements then render the assessment outcomes of individual risk factors into a single numerical value. A higher score is related to a more severe patient condition. Furthermore, the Mortality Probability Model II uses logistic regression based on independent risk factors to predict a patient’s probability of mortality. An important overlooked limitation of SAPS II and MPM II is that they do not, to date, include interaction terms between a patient’s vital signs. This is a prominent oversight as it is likely there is an interplay among vital signs. The co-existence of certain conditions may pose a greater health risk than when these conditions exist independently. One barrier to including such interaction terms in predictive models is the dimensionality issue as it becomes difficult to use variable selection. We propose an innovative scoring system which takes into account a dependence structure among patient’s vital signs, such as systolic and diastolic blood pressures, heart rate, pulse interval, and peripheral oxygen saturation. Copulas will capture the dependence among normally distributed and skewed variables as some of the vital sign distributions are skewed. The estimated dependence parameter will then be incorporated into the traditional scoring systems to adjust the points allocated for the individual vital sign measurements. The same dependence parameter will also be used to create an alternative copula-based model for predicting a patient’s probability of mortality. The new copula-based approach will accommodate not only a patient’s trajectories of vital signs but also the joint dependence probabilities among the vital signs. We hypothesise that this approach will produce more stable assessments and lead to more time efficient and accurate predictions. We will use two data sets: (1) 250 ICU patients admitted once to the Chui Regional Hospital (Kyrgyzstan) and (2) 37 ICU patients’ agitation-sedation profiles collected by the Hunter Medical Research Institute (Australia). Both the traditional scoring approach and our copula-based approach will be evaluated using the Brier score to indicate overall model performance, the concordance (or c) statistic to indicate the discriminative ability (or area under the receiver operating characteristic (ROC) curve), and goodness-of-fit statistics for calibration. We will also report discrimination and calibration values and establish visualization of the copulas and high dimensional regions of risk interrelating two or three vital signs in so-called higher dimensional ROCs.

Keywords: copula, intensive unit scoring system, ROC curves, vital sign dependence

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Authors: Reina Kawase

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World GHG emissions should be reduced 50% by 2050 compared with 1990 level. CO2 emission reduction from steel sector, an energy-intensive sector, is essential. To estimate CO2 emission from steel sector in the world, estimation of steel production is required. The world steel production by process is estimated during the period of 2005-2050. The world is divided into aggregated 35 regions. For a steel making process, two kinds of processes are considered; basic oxygen furnace (BOF) and electric arc furnace (EAF). Steel production by process in each region is decided based on a current production capacity, supply-demand balance of steel and scrap, technology innovation of steel making, steel consumption projection, and goods trade. World steel production under moderate countermeasure scenario in 2050 increases by 1.3 times compared with that in 2012. When domestic scrap recycling is promoted, steel production in developed regions increases about 1.5 times. The share in developed regions changes from 34 %(2012) to about 40%(2050). This is because developed regions are main suppliers of scrap. 48-57% of world steel production is produced by EAF. Under the scenario which thinks much of supply-demand balance of steel, steel production in developing regions increases is 1.4 times and is larger than that in developed regions. The share in developing regions, however, is not so different from current level. The increase in steel production by EAF is the largest under the scenario in which supply-demand balance of steel is an important factor. The share reaches 65%.

Keywords: global steel production, production distribution scenario, steel making process, supply-demand balance

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Authors: Alisawi Alaa T., Collins P. E. F.

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The analysis and evaluation of slope stability and landslide hazards are landslide hazards are critically important in civil engineering projects and broader considerations of safety. The level of slope stability risk should be identified due to its significant and direct financial and safety effects. Slope stability hazard analysis is performed considering static and/or dynamic loading circumstances. To reduce and/or prevent the failure hazard caused by landslides, a sophisticated and practical hazard analysis method using advanced constitutive modeling should be developed and linked to an effective solution that corresponds to the specific type of slope stability and landslides failure risk. Previous studies on slope stability analysis methods identify the failure mechanism and its corresponding solution. The commonly used approaches include used approaches include limit equilibrium methods, empirical approaches for rock slopes (e.g., slope mass rating and Q-slope), finite element or finite difference methods, and district element codes. This study presents an overview and evaluation of these analysis techniques. Contemporary source materials are used to examine these various methods on the basis of hypotheses, the factor of safety estimation, soil types, load conditions, and analysis conditions and limitations. Limit equilibrium methods play a key role in assessing the level of slope stability hazard. The slope stability safety level can be defined by identifying the equilibrium of the shear stress and shear strength. The slope is considered stable when the movement resistance forces are greater than those that drive the movement with a factor of safety (ratio of the resistance of the resistance of the driving forces) that is greater than 1.00. However, popular and practical methods, including limit equilibrium approaches, are not effective when the slope experiences complex failure mechanisms, such as progressive failure, liquefaction, internal deformation, or creep. The present study represents the first episode of an ongoing project that involves the identification of the types of landslides hazards, assessment of the level of slope stability hazard, development of a sophisticated and practical hazard analysis method, linkage of the failure type of specific landslides conditions to the appropriate solution and application of an advanced computational method for mapping the slope stability properties in the United Kingdom, and elsewhere through geographical information system (GIS) and inverse distance weighted spatial interpolation(IDW) technique. This study investigates and assesses the different assesses the different analysis and solution techniques to enhance the knowledge on the mechanism of slope stability and landslides hazard analysis and determine the available solutions for each potential landslide failure risk.

Keywords: slope stability, finite element analysis, hazard analysis, landslides hazard

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Authors: Lu Ren, You-Liang Fang, Yan-Gang Zhao

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In recent years, the application of BIM (Building Information Modelling) to construction schedule plan has been the focus of more and more researchers. In order to assess the reasonable level of the BIM-based construction schedule plan, that is whether the schedule can be completed on time, some researchers have introduced reliability theory to evaluate. In the process of evaluation, the uncertain factors affecting the construction schedule plan are regarded as random variables, and probability distributions of the random variables are assumed to be normal distribution, which is determined using two parameters evaluated from the mean and standard deviation of statistical data. However, in practical engineering, most of the uncertain influence factors are not normal random variables. So the evaluation results of the construction schedule plan will be unreasonable under the assumption that probability distributions of random variables submitted to the normal distribution. Therefore, in order to get a more reasonable evaluation result, it is necessary to describe the distribution of random variables more comprehensively. For this purpose, cubic normal distribution is introduced in this paper to describe the distribution of arbitrary random variables, which is determined by the first four moments (mean, standard deviation, skewness and kurtosis). In this paper, building the BIM model firstly according to the design messages of the structure and making the construction schedule plan based on BIM, then the cubic normal distribution is used to describe the distribution of the random variables due to the collecting statistical data of the random factors influencing construction schedule plan. Next the reliability analysis of the construction schedule plan based on BIM can be carried out more reasonably. Finally, the more accurate evaluation results can be given providing reference for the implementation of the actual construction schedule plan. In the last part of this paper, the more efficiency and accuracy of the proposed methodology for the reliability analysis of the construction schedule plan based on BIM are conducted through practical engineering case.

Keywords: BIM, construction schedule plan, cubic normal distribution, reliability analysis

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Authors: Michael McCann

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Managerial theories propose that, in joint stock companies, executives may be tempted to waste excess free cash on unprofitable projects to keep control of resources. In order to conceal their projects' poor performance, they may seek to engage in earnings management. On the one hand, managers may manipulate earnings upwards in order to post ‘good’ performances and safeguard their position. On the other, since managers pursuit of unrewarding investments are likely to lead to low long-term profitability, managers will use negative accruals to reduce current year’s earnings, smoothing earnings over time in order to conceal the negative effects. Agency models argue that boards of directors are delegated by shareholders to ensure that companies are governed properly. Part of that responsibility is ensuring the reliability of financial information. Analyses of the impact of board characteristics, particularly board independence on the misuse of free cash flow and earnings management finds conflicting evidence. However, existing characterizations of board independence do not account for such directors gaining firm-specific knowledge over time, influencing their monitoring ability. Further, there is little analysis of the influence of the relative experience of independent directors and executives on decisions surrounding the use of free cash. This paper contributes to this literature regarding the heterogeneous characteristics of boards by investigating the influence of independent director tenure on earnings management and the relative tenures of independent directors and Chief Executives. A balanced panel dataset comprising 51 companies across 11 annual periods from 2005 to 2015 is used for the analysis. In each annual period, firms were classified as conducting earnings management if they had discretionary accruals in the bottom quartile (downwards) and top quartile (upwards) of the distributed values for the sample. Logistical regressions were conducted to determine the marginal impact of independent board tenure and a number of control variables on the probability of conducting earnings management. The findings indicate that both absolute and relative measures of board independence and experience do not have a significant impact on the likelihood of earnings management. It is the level of free cash flow which is the major influence on the probability of earnings management. Higher free cash flow increases the probability of earnings management significantly. The research also investigates whether board monitoring of earnings management is contingent on the level of free cash flow. However, the results suggest that board monitoring is not amplified when free cash flow is higher. This suggests that the extent of earnings management in companies is determined by a range of company, industry and situation-specific factors.

Keywords: corporate governance, boards of directors, agency theory, earnings management

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Authors: Mohammad Tarek Al Muallim, Ozhan Duzenli, Ceyhun Ilguy

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Passive sonar is a method for detecting acoustic signals in the ocean. It detects the acoustic signals emanating from external sources. With passive sonar, we can determine the bearing of the target only, no information about the range of the target. Target Motion Analysis (TMA) is a process to estimate the position and speed of a target using passive sonar information. Since bearing is the only available information, the TMA technique called Bearing-only TMA. Many TMA techniques have been developed. However, until now, there is not a very effective method that could be used to always track an unknown target and extract its moving trace. In this work, a design of effective Bearing-only TMA Algorithm is done. The measured bearing angles are very noisy. Moreover, for multi-beam sonar, the measurements is quantized due to the sonar beam width. To deal with this, modified gain extended Kalman filter algorithm is used. The algorithm is fine-tuned, and many modules are added to improve the performance. A special validation gate module is used to insure stability of the algorithm. Many indicators of the performance and confidence level measurement are designed and tested. A new method to detect if the target is maneuvering is proposed. Moreover, a reactive optimal observer maneuver based on bearing measurements is proposed, which insure converging to the right solution all of the times. To test the performance of the proposed TMA algorithm a simulation is done with a MATLAB program. The simulator program tries to model a discrete scenario for an observer and a target. The simulator takes into consideration all the practical aspects of the problem such as a smooth transition in the speed, a circular turn of the ship, noisy measurements, and a quantized bearing measurement come for multi-beam sonar. The tests are done for a lot of given test scenarios. For all the tests, full tracking is achieved within 10 minutes with very little error. The range estimation error was less than 5%, speed error less than 5% and heading error less than 2 degree. For the online performance estimator, it is mostly aligned with the real performance. The range estimation confidence level gives a value equal to 90% when the range error less than 10%. The experiments show that the proposed TMA algorithm is very robust and has low estimation error. However, the converging time of the algorithm is needed to be improved.

Keywords: target motion analysis, Kalman filter, passive sonar, bearing-only tracking

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Authors: Mekdelawit Teferi Alamirew

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As a practical tool, the Geographical information system (GIS) was used for data integration, collection, management, analysis, and output presentation in pavement mangement systems . There are many GIS techniques to improve the maintenance activities like Dynamic segmentation and weighted overlay analysis which considers Multi Criteria Decision Making process. The results indicated that the developed MPI model works sufficiently and yields adequate output for providing accurate decisions. Hence considering multi criteria to prioritize the pavement sections for maintenance, as a result of the fact that GIS maps can express position, extent, and severity of pavement distress features more effectively than manual approaches, lastly the paper also offers digitized distress maps that can help agencies in their decision-making processes.

Keywords: pavement, flexible, maintenance, index

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Authors: Dinesh Inamadar, R. Venugopalan, K. Padmini

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An attempt has been made in the present communication to elucidate the efficacy of robust ANOVA methods to analyze horticultural field experimental data in the presence of outliers. Results obtained fortify the use of robust ANOVA methods as there was substantiate reduction in error mean square, and hence the probability of committing Type I error, as compared to the regular approach.

Keywords: outliers, robust ANOVA, horticulture, cook distance, type I error

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Authors: Hayder H. Kareem

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Groundwater recharge is a crucial parameter for any groundwater management system. The variability of the recharge rates and the difficulty in estimating this factor in many processes by direct observation leads to the complexity of estimating the recharge value. Various methods are existing to estimate the groundwater recharge, with some limitations for each method to be able for application. This paper focuses particularly on a real study area, Al-Najaf City, Iraq. In this city, there are few groundwater aquifers, but the aquifer which is considered in this study is the closest one to the ground surface, the Dibdibba aquifer. According to the Aridity Index, which is estimated in the paper, Al-Najaf City is classified as a region located in an arid climate, and this identified that the most appropriate method to estimate the groundwater recharge is Thornthwaite's formula or Thornthwaite's method. From the calculations, the estimated average groundwater recharge over the period 1980-2014 for Al-Najaf City is 40.32 mm/year. Groundwater recharge is completely affected the groundwater table level (groundwater head). Therefore, to make sure that this value of recharge is true, the MODFLOW program has been used to apply this value through finding the relationship between the calculated and observed heads where a groundwater model for the Al-Najaf City study area has been built by MODFLOW to simulate this area for different purposes, one of these purposes is to simulate the groundwater recharge. MODFLOW results show that this value of groundwater recharge is extremely high and needs to be reduced. Therefore, a further sensitivity test has been carried out for the Al-Najaf City study area by the MODFLOW program through changing the recharge value and found that the best estimation of groundwater recharge value for this city is 16.5 mm/year where this value gives the best fitting between the calculated and observed heads with minimum values of RMSE % (13.175) and RSS m² (1454).

Keywords: Al-Najaf City, groundwater modelling, recharge estimation, visual MODFLOW

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Authors: Majid Abdolrazzagh-Nezhad, Salwani Abdullah

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The job-shop scheduling problem (JSSP) is an important decision facing those involved in the fields of industry, economics and management. This problem is a class of combinational optimization problem known as the NP-hard problem. JSSPs deal with a set of machines and a set of jobs with various predetermined routes through the machines, where the objective is to assemble a schedule of jobs that minimizes certain criteria such as makespan, maximum lateness, and total weighted tardiness. Over the past several decades, interest in meta-heuristic approaches to address JSSPs has increased due to the ability of these approaches to generate solutions which are better than those generated from heuristics alone. This article provides the classification, constraints and objective functions imposed on JSSPs that are available in the literature.

Keywords: job-shop scheduling, classification, constraints, objective functions

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Authors: Amal A. Mashali, Omar Eltaweel, Elerian Ekladious

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Stature of an individual has an important role in identification, which is often required in medico-legal practice. The estimation of stature is an important step in the identification of dismembered remains or when only a part of a skeleton is only available as in major disasters or with mutilation. There is no published data on anthropological data among Jordanian population. The present study was designed in order to find out relationship of stature to some anthropometric measures among a sample of Jordanian population and to determine the most accurate and reliable one in predicting the stature of an individual. A cross sectional study was conducted on 336 adult healthy volunteers , free of bone diseases, nutritional diseases and abnormalities in the extremities after taking their consent. Students of Faculty of Medicine, Mutah University helped in collecting the data. The anthropometric measurements (anatomically defined) were stature, humerus length, hand length and breadth, foot length and breadth, foot index and knee height on both right and left sides of the body. The measurements were typical on both sides of the bodies of the studied samples. All the anthropologic data showed significant relation with age except the knee height. There was a significant difference between male and female measurements except for the foot index where F= 0.269. There was a significant positive correlation between the different measures and the stature of the individuals. Three equations were developed for estimation of stature. The most sensitive measure for prediction of a stature was found to be the humerus length.

Keywords: foot index, foot length, hand length, humerus length, stature

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Authors: M. Reni Sagayaraj, S. Anand Gnana Selvam, R. Reynald Susainathan

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We analyze stochastic integrals associated with a mutation process. To be specific, we describe the cell population process and derive the differential equations for the joint generating functions for the number of mutants and their integrals in generating functions and their applications. We obtain first-order moments of the processes of the two-way mutation process in first-order moment structure of X (t) and Y (t) and the second-order moments of a one-way mutation process. In this paper, we obtain the limiting behaviour of the integrals in limiting distributions of X (t) and Y (t).

Keywords: stochastic integrals, single–server queue model, catastrophes, busy period

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Authors: Ahmad Sarfaraz, Raiyad Herwies

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In this paper, a multi-criteria decision making analysis is used to help any organization selects the best KM tool that fits and serves its needs. The AHP model is used based on a previous study to highlight and identify the main criteria and sub-criteria that are incorporated in the selection process. Different KM tools alternatives with different criteria are compared and weighted accurately to be incorporated in the GP model. The main goal is to combine the GP model with the AHP model to ensure that selecting the KM tool considers the resource constraints. Two important issues are discussed in this paper: how different factors could be taken into consideration in forming the AHP model, and how to incorporate the AHP results into the GP model for better results.

Keywords: knowledge management, analytical hierarchy process, goal programming, multi-criteria decision making

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Authors: E. Ateia, L. M. Salah, A. H. El-Bassuony

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Physical properties of nanocrystalline Ni1-xZnxCryFe2-yO4, (x=0.3, 0.5 and y=0.0, 0.1) with estimated crystallite size of 16.4 nm have been studied. XRD pattern of all prepared systems shows that, the nanosamples without Cr3+ have a cubic spinel structure with the appearance of small peaks designated as a secondary phase. Magnetic constants such as saturation magnetization, (MS) remanent magnetization (Mr) and coercive field (Hc) were obtained and reported. The obtained data shows that, the addition of Cr3+ (0.1mol) decreases the saturation magnetization. This is due to the decrease of magnetic moment of Cr3+ ion (3.0 μB) with respect to Fe3+ ion (5.85 μB). The electrical properties of the investigated samples were also investigated.

Keywords: electrical conductivity, ferrites, grain size, sintering

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Authors: María-Luisa Pinto-Salamanca, Wilson-Javier Pérez-Holguín

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Reconstruction of contact forces is a fundamental technique for analyzing the properties of a touched object and is essential for regulating the grip force in slip control loops. This is based on the processing of the distribution, intensity, and direction of the forces during the capture of the sensors. Currently, efficient hardware alternatives have been used more frequently in different fields of application, allowing the implementation of computationally complex algorithms, as is the case with tactile signal processing. The use of hardware for smart tactile sensing systems is a research area that promises to improve the processing time and portability requirements of applications such as artificial skin and robotics, among others. The literature review shows that hardware implementations are present today in almost all stages of smart tactile detection systems except in the force reconstruction process, a stage in which they have been less applied. This work presents a hardware implementation of a model-driven reported in the literature for the contact force reconstruction of flat and rigid tactile sensor arrays from normal stress data. From the analysis of a software implementation of such a model, this implementation proposes the parallelization of tasks that facilitate the execution of matrix operations and a two-dimensional optimization function to obtain a vector force by each taxel in the array. This work seeks to take advantage of the parallel hardware characteristics of Field Programmable Gate Arrays, FPGAs, and the possibility of applying appropriate techniques for algorithms parallelization using as a guide the rules of generalization, efficiency, and scalability in the tactile decoding process and considering the low latency, low power consumption, and real-time execution as the main parameters of design. The results show a maximum estimation error of 32% in the tangential forces and 22% in the normal forces with respect to the simulation by the Finite Element Modeling (FEM) technique of Hertzian and non-Hertzian contact events, over sensor arrays of 10×10 taxels of different sizes. The hardware implementation was carried out on an MPSoC XCZU9EG-2FFVB1156 platform of Xilinx® that allows the reconstruction of force vectors following a scalable approach, from the information captured by means of tactile sensor arrays composed of up to 48 × 48 taxels that use various transduction technologies. The proposed implementation demonstrates a reduction in estimation time of x / 180 compared to software implementations. Despite the relatively high values of the estimation errors, the information provided by this implementation on the tangential and normal tractions and the triaxial reconstruction of forces allows to adequately reconstruct the tactile properties of the touched object, which are similar to those obtained in the software implementation and in the two FEM simulations taken as reference. Although errors could be reduced, the proposed implementation is useful for decoding contact forces for portable tactile sensing systems, thus helping to expand electronic skin applications in robotic and biomedical contexts.

Keywords: contact forces reconstruction, forces estimation, tactile sensor array, hardware implementation

Procedia PDF Downloads 178