Search results for: regression models.

Authors: Fernanda M. Assef, Maria Teresinha A. Steiner

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The aim of this paper is to compare and discuss better classifier algorithm options for credit risk assessment by applying different Machine Learning techniques. Using records from a Brazilian financial institution, this study uses a database of 5,432 companies that are clients of the bank, where 2,600 clients are classified as non-defaulters, 1,551 are classified as defaulters and 1,281 are temporarily defaulters, meaning that the clients are overdue on their payments for up 180 days. For each case, a total of 15 attributes was considered for a one-against-all assessment using four different techniques: Artificial Neural Networks Multilayer Perceptron (ANN-MLP), Artificial Neural Networks Radial Basis Functions (ANN-RBF), Logistic Regression (LR) and finally Support Vector Machines (SVM). For each method, different parameters were analyzed in order to obtain different results when the best of each technique was compared. Initially the data were coded in thermometer code (numerical attributes) or dummy coding (for nominal attributes). The methods were then evaluated for each parameter and the best result of each technique was compared in terms of accuracy, false positives, false negatives, true positives and true negatives. This comparison showed that the best method, in terms of accuracy, was ANN-RBF (79.20% for non-defaulter classification, 97.74% for defaulters and 75.37% for the temporarily defaulter classification). However, the best accuracy does not always represent the best technique. For instance, on the classification of temporarily defaulters, this technique, in terms of false positives, was surpassed by SVM, which had the lowest rate (0.07%) of false positive classifications. All these intrinsic details are discussed considering the results found, and an overview of what was presented is shown in the conclusion of this study.

Keywords: Artificial Neural Networks, ANNs, classifier algorithms, credit risk assessment, logistic regression, machine learning, support vector machines.

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Authors: Hanifeh Imanian, Morteza Kolahdoozan

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The purpose of this study is to present a mathematical phrase for calculating the dispersion rate of spilled oil in water column under non-breaking waves. In this regard, a multiphase numerical model is applied for which waves and oil phase were computed concurrently, and accuracy of its hydraulic calculations have been proven. More than 200 various scenarios of oil spilling in wave waters were simulated using the multiphase numerical model and its outcome were collected in a database. The recorded results were investigated to identify the major parameters affected vertical oil dispersion and finally 6 parameters were identified as main independent factors. Furthermore, some statistical tests were conducted to identify any relationship between the dependent variable (dispersed oil mass in the water column) and independent variables (water wave specifications containing height, length and wave period and spilled oil characteristics including density, viscosity and spilled oil mass). Finally, a mathematical-statistical relationship is proposed to predict dispersed oil in marine waters. To verify the proposed relationship, a laboratory example available in the literature was selected. Oil mass rate penetrated in water body computed by statistical regression was in accordance with experimental data was predicted. On this occasion, it was necessary to verify the proposed mathematical phrase. In a selected laboratory case available in the literature, mass oil rate penetrated in water body computed by suggested regression. Results showed good agreement with experimental data. The validated mathematical-statistical phrase is a useful tool for oil dispersion prediction in oil spill events in marine areas.

Keywords: Dispersion, marine environment, mathematical-statistical relationship, oil spill.

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Authors: Femi Elegbeleye, Seani Rananga

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This paper focused on cost effective storage architecture using fog and cloud data storage gateway, and presented the design of the framework for the data privacy model and data analytics framework on a real-time analysis when using machine learning method. The paper began with the system analysis, system architecture and its component design, as well as the overall system operations. Several results obtained from this study on data privacy models show that when two or more data privacy models are integrated via a fog storage gateway, we often have more secure data. Our main focus in the study is to design a framework for the data privacy model, data storage, and real-time analytics. This paper also shows the major system components and their framework specification. And lastly, the overall research system architecture was shown, including its structure, and its interrelationships.

Keywords: IoT, fog storage, cloud storage, data analysis, data privacy.

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Authors: Joe Walsh, Mike Climstein, Ian Timothy Heazlewood, Stephen Burke, Jyrki Kettunen, Kent Adams, Mark DeBeliso

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Thousands of masters athletes participate quadrennially in the World Masters Games (WMG), yet this cohort of athletes remains proportionately under-investigated. Due to a growing global obesity pandemic in context of benefits of physical activity across the lifespan, the BMI trends for this unique population was of particular interest. The nexus between health, physical activity and aging is complex and has raised much interest in recent times due to the realization that a multifaceted approach is necessary in order to counteract the obesity pandemic. By investigating age based trends within a population adhering to competitive sport at older ages, further insight might be gleaned to assist in understanding one of many factors influencing this relationship.BMI was derived using data gathered on a total of 6,071 masters athletes (51.9% male, 48.1% female) aged 25 to 91 years ( =51.5, s =±9.7), competing at the Sydney World Masters Games (2009). Using linear and loess regression it was demonstrated that the usual tendency for prevalence of higher BMI increasing with age was reversed in the sample. This trend in reversal was repeated for both male and female only sub-sets of the sample participants, indicating the possibility of improved prevalence of BMI with increasing age for both the sample as a whole and these individual sub-groups.This evidence of improved classification in one index of health (reduced BMI) for masters athletes (when compared to the general population) implies there are either improved levels of this index of health with aging due to adherence to sport or possibly the reduced BMI is advantageous and contributes to this cohort adhering (or being attracted) to masters sport at older ages.

Keywords: Aging, masters athlete, Quetelet Index, sport

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Authors: B. Manshoor, M. Jaat, Amir Khalid

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Circle grid space filling plate is a flow conditioner with a fractal pattern and used to eliminate turbulence originating from pipe fittings in experimental fluid flow applications. In this paper, steady state, incompressible, swirling turbulent flow through circle grid space filling plate has been studied. The solution and the analysis were carried out using finite volume CFD solver FLUENT 6.2. Three turbulence models were used in the numerical investigation and their results were compared with the pressure drop correlation of BS EN ISO 5167-2:2003. The turbulence models investigated here are the standard k-ε, realizable k-ε, and the Reynolds Stress Model (RSM). The results showed that the RSM model gave the best agreement with the ISO pressure drop correlation. The effects of circle grids space filling plate thickness and Reynolds number on the flow characteristics have been investigated as well.

Keywords: Flow conditioning, turbulent flow, turbulent modeling, CFD.

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Authors: G. Parmar, S. Mukherjee, R. Prasad

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The authors present an algorithm for order reduction of linear time invariant dynamic systems using the combined advantages of the eigen spectrum analysis and the error minimization by particle swarm optimization technique. Pole centroid and system stiffness of both original and reduced order systems remain same in this method to determine the poles, whereas zeros are synthesized by minimizing the integral square error in between the transient responses of original and reduced order models using particle swarm optimization technique, pertaining to a unit step input. It is shown that the algorithm has several advantages, e.g. the reduced order models retain the steady-state value and stability of the original system. The algorithm is illustrated with the help of two numerical examples and the results are compared with the other existing techniques.

Keywords: Eigen spectrum, Integral square error, Orderreduction, Particle swarm optimization, Stability.

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Authors: M. Aruna, V. Dhanalaksmi

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Inconel 718, a nickel based super-alloy is an extensively used alloy, accounting for about 50% by weight of materials used in an aerospace engine, mainly in the gas turbine compartment. This is owing to their outstanding strength and oxidation resistance at elevated temperatures in excess of 5500 C. Machining is a requisite operation in the aircraft industries for the manufacture of the components especially for gas turbines. This paper is concerned with optimization of the surface roughness when turning Inconel 718 with cermet inserts. Optimization of turning operation is very useful to reduce cost and time for machining. The approach is based on Response Surface Method (RSM). In this work, second-order quadratic models are developed for surface roughness, considering the cutting speed, feed rate and depth of cut as the cutting parameters, using central composite design. The developed models are used to determine the optimum machining parameters. These optimized machining parameters are validated experimentally, and it is observed that the response values are in reasonable agreement with the predicted values.

Keywords: Inconel 718, Optimization, Response Surface Methodology (RSM), Surface roughness

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Authors: Ali Pirdavani, Tom Brijs, Tom Bellemans, Geert Wets, Koen Vanhoof

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Signalized intersections on high-volume arterials are often congested during peak hours, causing a decrease in through movement efficiency on the arterial. Much of the vehicle delay incurred at conventional intersections is caused by high left-turn demand. Unconventional intersection designs attempt to reduce intersection delay and travel time by rerouting left-turns away from the main intersection and replacing it with right-turn followed by Uturn. The proposed new type of U-turn intersection is geometrically designed with a raised island which provides a protected U-turn movement. In this study several scenarios based on different distances between U-turn and main intersection, traffic volume of major/minor approaches and percentage of left-turn volumes were simulated by use of AIMSUN, a type of traffic microsimulation software. Subsequently some models are proposed in order to compute travel time of each movement. Eventually by correlating these equations to some in-field collected data of some implemented U-turn facilities, the reliability of the proposed models are approved. With these models it would be possible to calculate travel time of each movement under any kind of geometric and traffic condition. By comparing travel time of a conventional signalized intersection with U-turn intersection travel time, it would be possible to decide on converting signalized intersections into this new kind of U-turn facility or not. However comparison of travel time is not part of the scope of this research. In this paper only travel time of this innovative U-turn facility would be predicted. According to some before and after study about the traffic performance of some executed U-turn facilities, it is found that commonly, this new type of U-turn facility produces lower travel time. Thus, evaluation of using this type of unconventional intersection should be seriously considered.

Keywords: Innovative U-turn facility, Microsimulation, Traveltime, Unconventional intersection design.

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Authors: Maziar Ramezani, Zaidi Mohd Ripin

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In a metal forming process, the friction between the material and the tools influences the process by modifying the stress distribution of the workpiece. This frictional behaviour is often taken into account by using a constant coefficient of friction in the finite element simulations of sheet metal forming processes. However, friction coefficient varies in time and space with many parameters. The Stribeck friction model is investigated in this study to predict springback behaviour of AA6061-T4 sheets during V-bending process. The coefficient of friction in Stribeck curve depends on sliding velocity and contact pressure. The plane-strain bending process is simulated in ABAQUS/Standard. We compared the computed punch load-stroke curves and springback related to the constant coefficient of friction with the defined friction model. The results clearly showed that the new friction model provides better agreement between experiments and results of numerical simulations. The influence of friction models on stress distribution in the workpiece is also studied numerically

Keywords: Friction model, Stress distribution, V-bending.

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Authors: José Leandro Melgar Néris, Claudinéia Brazil, Luciane Teresa Salvi, Isabel Cristina Damin

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The impact the climate change is not recent, the main variable in the hydrological cycle is the sequence and shortage of a drought, which has a significant impact on the socioeconomic, agricultural and environmental spheres. This study aims to characterize and quantify, based on precipitation climatic projections, the rainy and dry events in the region of the Uruguay River Basin, through the Standardized Precipitation Index (SPI). The database is the image that is part of the Intercomparison of Model Models, Phase 5 (CMIP5), which provides condition prediction models, organized according to the Representative Routes of Concentration (CPR). Compared to the normal set of climates in the Uruguay River Watershed through precipitation projections, seasonal precipitation increases for all proposed scenarios, with a low climate trend. From the data of this research, the idea is that this article can be used to support research and the responsible bodies can use it as a subsidy for mitigation measures in other hydrographic basins.

Keywords: Drought index, climatic projections, precipitation of the Uruguay River Basin, Standardized Precipitation Index.

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Authors: Görkem Arslan Kılınç

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Due to the high construction, operation, and maintenance costs of tall buildings, quantification of the area in the plan layout which provides a financial return is an important design criterion. The area of the “core and the structural system elements” does not provide financial return but must exist in the plan layout. Some characteristic items of tall office buildings affect the size of these areas. From this point of view, 15 tall office buildings were systematically investigated. The typical office floor plans of these buildings were re-produced digitally. The area of the “core and the structural system elements” in each building and the characteristic items of each building were calculated. These characteristic items are the size of the long and short plan edge, plan length/width ratio, size of the core long and short edge, core length/width ratio, core area, slenderness, building height, number of floors, and floor height. These items were analyzed by correlation and regression analyses. Results of this paper put forward that; characteristic items which affect the area of "core and structural system elements" are plan long and short edge size, core short edge size, building height, and the number of floors. A one-unit increase in plan short side size increases the area of the "core and structural system elements" in the plan by 12,378 m2. An increase in core short edge size increases the area of the core and structural system elements in the plan by 25,650 m2. Subsequent studies can be conducted by expanding the sample of the study and considering the geographical location of the building.

Keywords: Core area, correlation analysis, floor area, regression analysis, space efficiency, tall office buildings.

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Authors: Lihui Ma, Kunlun Xin, Suiqing Liu

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Modern managements of water distribution system (WDS) need water quality models that are able to accurately predict the dynamics of water quality variations within the distribution system environment. Before water quality models can be applied to solve system problems, they should be calibrated. Although former researchers use GA solver to calibrate relative parameters, it is difficult to apply on the large-scale or medium-scale real system for long computational time. In this paper a new method is designed which combines both macro and detailed model to optimize the water quality parameters. This new combinational algorithm uses radial basis function (RBF) metamodeling as a surrogate to be optimized for the purpose of decreasing the times of time-consuming water quality simulation and can realize rapidly the calibration of pipe wall reaction coefficients of chlorine model of large-scaled WDS. After two cases study this method is testified to be more efficient and promising, and deserve to generalize in the future.

Keywords: Metamodeling, model calibration, radial basisfunction, water distribution system, water quality model.

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Authors: Chad Goldsworthy, B. Rajeswari Matam

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The use of deep learning for species identification in camera trap images has revolutionised our ability to study, conserve and monitor species in a highly efficient and unobtrusive manner, with state-of-the-art models achieving accuracies surpassing the accuracy of manual human classification. The high imbalance of camera trap datasets, however, results in poor accuracies for minority (rare or endangered) species due to their relative insignificance to the overall model accuracy. This paper investigates the use of Focal Loss, in comparison to the traditional Cross Entropy Loss function, to improve the identification of minority species in the “255 Bird Species” dataset from Kaggle. The results show that, although Focal Loss slightly decreased the accuracy of the majority species, it was able to increase the F1-score by 0.06 and improve the identification of the bottom two, five and ten (minority) species by 37.5%, 15.7% and 10.8%, respectively, as well as resulting in an improved overall accuracy of 2.96%.

Keywords: Convolutional neural networks, data imbalance, deep learning, focal loss, species classification, wildlife conservation.

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Authors: H. Sayyaadi, N. Shokouhi

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In rail vehicles, air springs are very important isolating component, which guarantee good ride comfort for passengers during their trip. In the most new rail–vehicle models, developed by researchers, the thermo–dynamical effects of air springs are ignored and secondary suspension is modeled by simple springs and dampers. As the performance of suspension components have significant effects on rail–vehicle dynamics and ride comfort of passengers, a complete nonlinear thermo–dynamical air spring model, which is a combination of two different models, is introduced. Result from field test shows remarkable agreement between proposed model and experimental data. Effects of air suspension parameters on the system performances are investigated here and then these parameters are tuned to minimize Sperling ride comfort index during the trip. Results showed that by modification of air suspension parameters, passengers comfort is improved and ride comfort index is reduced about 10%.

Keywords: Air spring, Ride comfort improvement, Thermo– dynamical effects.

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Authors: Eva Nedeliakova, Juraj Camaj, Jaroslav Masek

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This contribution is focused on the methodology for identifying levels of quality and improving quality through new logistics model in railway transport. It is oriented on the application of dynamic quality models, which represent an innovative method of evaluation quality services. Through this conception, time factor, expected, and perceived quality in each moment of the transportation process within logistics chain can be taken into account. Various models describe the improvement of the quality which emphases the time factor throughout the whole transportation logistics chain. Quality of services in railway transport can be determined by the existing level of service quality, by detecting the causes of dissatisfaction employees but also customers, to uncover strengths and weaknesses. This new logistics model is able to recognize critical processes in logistic chain. It includes service quality rating that must respect its specific properties, which are unrepeatability, impalpability, their use right at the time they are provided and particularly changeability, which is significant factor in the conditions of rail transport as well. These peculiarities influence the quality of service regarding the constantly increasing requirements and that result in new ways of finding progressive attitudes towards the service quality rating.

Keywords: Logistics model, quality, railway transport.

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Authors: M. Ezzat, Y. Zaghloul, T. Sorour, A. Hefny, M. Eid

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Ultimate capacity of large diameter bored piles is usually determined from pile loading tests as recommended by several international codes and foundation design standards. However, loading of this type of piles till achieving apparent failure is practically seldom. In this paper, numerical analyses are carried out to simulate load test of a large diameter bored pile performed at the location of Alzey highway bridge project (Germany). Test results of pile load settlement relationship till failure as well as results of the base and shaft resistances are available. Apparent failure was indicated in this test by the significant increase of the induced settlement during the last load increment applied on the pile head. Measurements of this pile load test are used to assess the quality of the numerical models investigated. Three different material soil models are implemented in the analyses: Mohr coulomb (MC), Soft soil (SS), and Modified Mohr coulomb (MMC). Very good agreement is obtained between the field measured settlement and the calculated settlement using the MMC model. Results of analysis showed also that the MMC constitutive model is superior to MC, and SS models in predicting the ultimate base and shaft resistances of the large diameter bored pile. After calibrating the numerical model, behavior of large diameter bored piles under axial loads is discussed and the formation of the plastic zone around the pile is explored. Results obtained showed that the plastic zone below the base of the pile at failure extended laterally to about four times the pile diameter and vertically to about three times the pile diameter.

Keywords: Ultimate capacity, large diameter bored piles, plastic zone, failure, pile load test.

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Authors: Michael Lissack

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We depend upon explanation in order to “make sense" out of our world. And, making sense is all the more important when dealing with change. But, what happens if our explanations are wrong? This question is examined with respect to two types of explanatory model. Models based on labels and categories we shall refer to as “representations." More complex models involving stories, multiple algorithms, rules of thumb, questions, ambiguity we shall refer to as “compressions." Both compressions and representations are reductions. But representations are far more reductive than compressions. Representations can be treated as a set of defined meanings – coherence with regard to a representation is the degree of fidelity between the item in question and the definition of the representation, of the label. By contrast, compressions contain enough degrees of freedom and ambiguity to allow us to make internal predictions so that we may determine our potential actions in the possibility space. Compressions are explanatory via mechanism. Representations are explanatory via category. Managers are often confusing their evocation of a representation (category inclusion) as the creation of a context of compression (description of mechanism). When this type of explanatory error occurs, more errors follow. In the drive for efficiency such substitutions are all too often proclaimed – at the manager-s peril..

Keywords: Coherence, Emergence, Reduction, Model

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Authors: Hao-Hsiang Ku, Ching-Ho Chi

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Big data applications have become an imperative for many fields. Many researchers have been devoted into increasing correct rates and reducing time complexities. Hence, the study designs and proposes an Ontology-based backpropagation neural network classification and reasoning strategy for NoSQL big data applications, which is called ON4NoSQL. ON4NoSQL is responsible for enhancing the performances of classifications in NoSQL and SQL databases to build up mass behavior models. Mass behavior models are made by MapReduce techniques and Hadoop distributed file system based on Hadoop service platform. The reference engine of ON4NoSQL is the ontology-based backpropagation neural network classification and reasoning strategy. Simulation results indicate that ON4NoSQL can efficiently achieve to construct a high performance environment for data storing, searching, and retrieving.

Keywords: Hadoop, NoSQL, ontology, backpropagation neural network, and high distributed file system.

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Authors: Omer Ishag Eldai, Ahmed Hassan M. H. Ali, S. Raviraja

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Web-based systems have become increasingly important due to the fact that the Internet and the World Wide Web have become ubiquitous, surpassing all other technological developments in our history. The Internet and especially companies websites has rapidly evolved in their scope and extent of use, from being a little more than fixed advertising material, i.e. a "web presences", which had no particular influence for the company's business, to being one of the most essential parts of the company's core business. Traditional software engineering approaches with process models such as, for example, CMM and Waterfall models, do not work very well since web system development differs from traditional development. The development differs in several ways, for example, there is a large gap between traditional software engineering designs and concepts and the low-level implementation model, many of the web based system development activities are business oriented (for example web application are sales-oriented, web application and intranets are content-oriented) and not engineering-oriented. This paper aims to introduce Increment Iterative extreme Programming (IIXP) methodology for developing web based systems. In difference to the other existence methodologies, this methodology is combination of different traditional and modern software engineering and web engineering principles.

Keywords: Web based systems, Web engineering.

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Authors: Gururaj S Punekar, N K Kishore Senior, H S Y Shastry

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Charge Simulation Method (CSM) is one of the very widely used numerical field computation technique in High Voltage (HV) engineering. The high voltage fields of varying non uniformities are encountered in practice. CSM programs being case specific, the simulation accuracies heavily depend on the user (programmers) experience. Here is an effort to understand CSM errors and evolve some guidelines to setup accurate CSM models, relating non uniformities with assignment factors. The results are for the six-point-charge model of sphere-plane gap geometry. Using genetic algorithm (GA) as tool, optimum assignment factors at different non uniformity factors for this model have been evaluated and analyzed. It is shown that the symmetrically placed six-point-charge models can be good enough to set up CSM programs with potential errors less than 0.1% when the field non uniformity factor is greater than 2.64 (field utilization factor less than 52.76%).

Keywords: Assignment factor, Charge Simulation Method, High Voltage, Numerical field computation, Non uniformity factor, Simulation errors.

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Authors: Ahmed S. Al-Abdulwahab

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Generation system reliability assessment is an important task which can be performed using deterministic or probabilistic techniques. The probabilistic approaches have significant advantages over the deterministic methods. However, more complicated modeling is required by the probabilistic approaches. Power generation model is a basic requirement for this assessment. One form of the generation models is the well known capacity outage probability table (COPT). Different analytical techniques have been used to construct the COPT. These approaches require considerable mathematical modeling of the generating units. The unit-s models are combined to build the COPT which will add more burdens on the process of creating the COPT. Decimal to Binary Conversion (DBC) technique is widely and commonly applied in electronic systems and computing This paper proposes a novel utilization of the DBC to create the COPT without engaging in analytical modeling or time consuming simulations. The simple binary representation , “0 " and “1 " is used to model the states o f generating units. The proposed technique is proven to be an effective approach to build the generation model.

Keywords: Decimal to Binary, generation, reliability.

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Authors: Lari Kela

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An adaptive Helmholtz resonator was designed and adapted to hydraulics. The resonator was controlled by open- and closed-loop controls so that 20 dB attenuation of the peak-to-peak value of the pulsating pressure was maintained. The closed-loop control was noted to be better, albeit it was slower because of its low pressure and temperature variation, which caused variation in the effective bulk modulus of the hydraulic system. Low-pressure hydraulics contains air, which affects the stiffness of the hydraulics, and temperature variation changes the viscosity of the oil. Thus, an open-loop control loses its efficiency if a condition such as temperature or the amount of air changes after calibration. The instability of the low-pressure hydraulic system reduced the operational frequency range of the Helmholtz resonator when compared with the results of an analytical model. Different dampers for hydraulics are presented. Then analytical models of a hydraulic pipe and a hydraulic pipe with a Helmholtz resonator are presented. The analytical models are based on the wave equation of sound pressure. Finally, control methods and the results of experiments are presented.

Keywords: adaptive, damper, hydraulics, pressure, pulsating

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Authors: Asaiel Alohaly

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A theoretical framework for corporate governance is needed to bridge the gap between the corporate governance of private companies and State-Owned Enterprises (SOEs). The two dominant models, being shareholder and stakeholder, do not always address the specific requirements and challenges posed by ‘hybrid’ companies; namely, previously national bodies that have been privatised while the government retains significant control or holds a majority of shares. Thus, an exploratory theoretical study is needed to identify how ‘hybrid’ companies should be defined and why the state model should be acknowledged since it is the less conspicuous model in comparison with the shareholder and stakeholder models. This research focuses on the state model of corporate governance to understand the complex ownership, control pattern, goals, and corporate governance of these hybrid companies. The significance of this research lies in the fact that there is a limited available publication on the state model. This research argues for the state model, which proceeds from an understanding of the institutionally embedded characteristics of hybrid companies, where the government as a shareholder, is either a majority of the total shares, or has been granted power based on the rule of law; the company bylaws.

Keywords: Corporate governance, control, shareholders, state model.

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Authors: Rim Bouhaouel, Naoufel Kraïem, Zuhoor Al Khanjari

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Unified Modeling Language (UML) is considered as one of the widespread modeling language standardized by the Object Management Group (OMG). Therefore, the model driving engineering (MDE) community attempts to provide reuse of UML diagrams, and do not construct it from scratch. The UML model appears according to a specific software development process. The existing method generation models focused on the different techniques of transformation without considering the development process. Our work aims to construct an UML component from fragments of UML diagram basing on an agile method. We define UML fragment as a portion of a UML diagram, which express a business target. To guide the generation of fragments of UML models using an agile process, we need a flexible approach, which adapts to the agile changes and covers all its activities. We use the software product line (SPL) to derive a fragment of process agile method. This paper explains our approach, named RECUP, to generate UML fragments following an agile process, and overviews the different aspects. In this paper, we present the approach and we define the different phases and artifacts.

Keywords: UML, component, fragment, agile, SPL.

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Authors: Yogesh Aggarwal, Paratibha Aggarwal

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The paper presents a comparative performance of the models developed to predict 28 days compressive strengths using neural network techniques for data taken from literature (ANN-I) and data developed experimentally for SCC containing bottom ash as partial replacement of fine aggregates (ANN-II). The data used in the models are arranged in the format of six and eight input parameters that cover the contents of cement, sand, coarse aggregate, fly ash as partial replacement of cement, bottom ash as partial replacement of sand, water and water/powder ratio, superplasticizer dosage and an output parameter that is 28-days compressive strength and compressive strengths at 7 days, 28 days, 90 days and 365 days, respectively for ANN-I and ANN-II. The importance of different input parameters is also given for predicting the strengths at various ages using neural network. The model developed from literature data could be easily extended to the experimental data, with bottom ash as partial replacement of sand with some modifications.

Keywords: Self compacting concrete, bottom ash, strength, prediction, neural network, importance factor.

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Authors: Radim Farana, Bogdan Walek, Michal Janosek, Jaroslav Zacek

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This paper presents the advantages of fuzzy control use in technological processes control. The paper presents a real application of the Linguistic Fuzzy-Logic Control, developed at the University of Ostrava for the control of physical models in the Intelligent Systems Laboratory. The paper presents an example of a sensitive non-linear model, such as a magnetic levitation model and obtained results which show how modern information technologies can help to solve actual technical problems. A special method based on the LFLC controller with partial components is presented in this paper followed by the method of automatic context change, which is very helpful to achieve more accurate control results. The main advantage of the used system is its robustness in changing conditions demonstrated by comparing with conventional PID controller. This technology and real models are also used as a background for problem-oriented teaching, realized at the department for master students and their collaborative as well as individual final projects.

Keywords: Control, fuzzy logic, sensitive system, technological proves.

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Authors: Rafayel A. Azizyan, Aram E. Gevogyan, Valeri B. Arakelyan, Emil S. Gevorgyan

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The mathematical modeling of different biological processes is usually used to predict or assess behavior of systems in which these processes take place. This study deals with mathematical and computer modeling of bi-substrate enzymatic reactions with ping-pong mechanism, which play an important role in different biochemical pathways. Besides that, three models of competitive inhibition were designed using different software packages. The main objective of this study is to represent the results from in silico investigation of bi-substrate enzymatic reactions with ordered pingpong mechanism in the presence of competitive inhibitors, as well as to describe in details the inhibition effects. The simulation of the models with certain kinetic parameters allowed investigating the behavior of reactions as well as determined some interesting aspects concerning influence of different cases of competitive inhibition. Simultaneous presence of two inhibitors, competitive to the S1 and S2 substrates have been studied. Moreover, we have found the pattern of simultaneous influence of both inhibitors.

Keywords: Mathematical modeling, bi-substrate enzymatic reactions, ping-pong mechanism, competitive inhibition.

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Authors: Delfim Soares Jr., Webe J. Mansur

Abstract:

The Time-Domain Boundary Element Method (TDBEM) is a well known numerical technique that handles quite properly dynamic analyses considering infinite dimension media. However, when these analyses are also related to nonlinear behavior, very complex numerical procedures arise considering the TD-BEM, which may turn its application prohibitive. In order to avoid this drawback and model nonlinear infinite media, the present work couples two BEM formulations, aiming to achieve the best of two worlds. In this context, the regions expected to behave nonlinearly are discretized by the Domain Boundary Element Method (D-BEM), which has a simpler mathematical formulation but is unable to deal with infinite domain analyses; the TD-BEM is employed as in the sense of an effective non-reflexive boundary. An iterative procedure is considered for the coupling of the TD-BEM and D-BEM, which is based on a relaxed renew of the variables at the common interfaces. Elastoplastic models are focused and different time-steps are allowed to be considered by each BEM formulation in the coupled analysis.

Keywords: Boundary Element Method, Dynamic Elastoplastic Analysis, Iterative Coupling, Multiple Time-Steps.

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Authors: Elena Carcano, Mirzi Betasolo

Abstract:

This study aims to provide sub-hourly streamflow predictions and associated rating curves for small catchments of intermittent and torrential flow regime characterized by flash floods occurring especially during April and November. The methodology entails two lumped conceptual hydrological models which work in series. The total model is based upon eleven parameters and shows good flexibility in handling different input sets. Runoff Coefficient has contributed to improving the model’s performances and has been treated as an additional parameter; while Sensitivity Analysis has highlighted how slight changes in the model’s input can lead to changes in model’s output. The adopted procedure is steady and useful to give very practical engineering information at the expense of a parsimonious request both in input data and in the number of adopted parameters. According to the obtained results, the authors encourage the test of this combined procedure on different hydrological scenarios in order to provide information for poorly monitored catchments and not updated sites.

Keywords: Streamflow rating curve, chronological data, streamflow sequences, conceptual models.

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Authors: M. Sadeghi, H. Pezeshk, R. Tusserkani, A. Sharifi Zarchi, A. Malekpour, M. Foroughmand, S. Goliaei, M. Totonchi, N. Ansari–Pour

Abstract:

The role and relative importance of intrinsic and extrinsic factors in the development of complex diseases such as cancer still remains a controversial issue. Determining the amount of variation explained by these factors needs experimental data and statistical models. These models are nevertheless based on the occurrence and accumulation of random mutational events during stem cell division, thus rendering cancer development a stochastic outcome. We demonstrate that not only individual genome sequencing is uninformative in determining cancer risk, but also assigning a unique genome sequence to any given individual (healthy or affected) is not meaningful. Current whole-genome sequencing approaches are therefore unlikely to realize the promise of personalized medicine. In conclusion, since genome sequence differs from cell to cell and changes over time, it seems that determining the risk factor of complex diseases based on genome sequence is somewhat unrealistic, and therefore, the resulting data are likely to be inherently uninformative.

Keywords: Cancer risk, extrinsic factors, genome sequencing, intrinsic factors.

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