Search results for: business models

Authors: J. Dumrongsak, A. M. Savill

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Non-premixed turbulent combustion Computational Fluid Dynamics (CFD) has been carried out in a simplified methanefuelled coaxial jet combustor employing Large Eddy Simulation (LES). The objective of this study is to evaluate the performance of LES in modelling non-premixed combustion using a commercial software, FLUENT, and investigate the effects of the grid density and chemistry models employed on the accuracy of the simulation results. A comparison has also been made between LES and Reynolds Averaged Navier-Stokes (RANS) predictions. For LES grid sensitivity test, 2.3 and 6.2 million cell grids are employed with the equilibrium model. The chemistry model sensitivity analysis is achieved by comparing the simulation results from the equilibrium chemistry and steady flamelet models. The predictions of the mixture fraction, axial velocity, species mass fraction and temperature by LES are in good agreement with the experimental data. The LES results are similar for the two chemistry models but influenced considerably by the grid resolution in the inner flame and near-wall regions.

Keywords: Coaxial jet, reacting LES, non-premixed combustion, turbulent flow.

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Authors: Hafizuddin W. Yussof, Syamsutajri S. Bahri, Adam P. Harvey

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Strong anion exchange resins with QN+OH-, have the potential to be developed and employed as heterogeneous catalyst for transesterification, as they are chemically stable to leaching of the functional group. Nine different SIERs (SIER1-9) with QN+OH-were prepared by suspension polymerization of vinylbenzyl chloridedivinylbenzene (VBC-DVB) copolymers in the presence of n-heptane (pore-forming agent). The amine group was successfully grafted into the polymeric resin beads through functionalization with trimethylamine. These SIERs are then used as a catalyst for the transesterification of triacetin with methanol. A set of differential equations that represents the Langmuir-Hinshelwood-Hougen- Watson (LHHW) and Eley-Rideal (ER) models for the transesterification reaction were developed. These kinetic models of LHHW and ER were fitted to the experimental data. Overall, the synthesized ion exchange resin-catalyzed reaction were welldescribed by the Eley-Rideal model compared to LHHW models, with sum of square error (SSE) of 0.742 and 0.996, respectively.

Keywords: Anion exchange resin, Eley-Rideal, Langmuir-Hinshelwood-Hougen-Watson, transesterification.

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Authors: Zhidong Zhang, Zhi-Chao Zhang

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This study examined the mental health and behavioral problems in early adolescence with the instrument of Achenbach System of Empirically Based Assessment (ASEBA). The purpose of the study was stratified sampling method was used to collect data from 1975 participants. Multiple regression models and hierarchical regression models were applied to examine the relations between the background variables and internalizing problems, and the ones between students’ performance and internalizing problems. The results indicated that several background variables as predictors could significantly predict the anxious/depressed problem; reading and social study scores could significantly predict the anxious/depressed problem. However the class as a hierarchical macro factor did not indicate the significant effect. In brief, the majority of these models represented that the background variables, behaviors and academic performance were significantly related to the anxious/depressed problem.

Keywords: Behavioral problems, anxious/depression problems, empirical-based assessment, hierarchical modeling.

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Authors: B. Sir, M. Podhoranyi, S. Kuchar, T. Kocyan

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Rainfall runoff models play important role in hydrological predictions. However, the model is only one part of the process for creation of flood prediction. The aim of this paper is to show the process of successful prediction for flood event (May 15 – May 18 2014). Prediction was performed by rainfall runoff model HEC–HMS, one of the models computed within Floreon+ system. The paper briefly evaluates the results of automatic hydrologic prediction on the river Olše catchment and its gages Český Těšín and Věřňovice.

Keywords: Flood, HEC-HMS, Prediction, Rainfall – Runoff.

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Authors: E. Al Daoud

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In many cases, theoretical treatments are available for models for which there is no perfect physical realization. In this situation, the only possible test for an approximate theoretical solution is to compare with data generated from a computer simulation. In this paper, Monte Carlo tools are used to study and compare the elementary particles models. All the experiments are implemented using 10000 events, and the simulated energy is 13 TeV. The mean and the curves of several variables are calculated for each model using MadAnalysis 5. Anomalies in the results can be seen in the muons masses of the minimal supersymmetric standard model and the two Higgs doublet model.

Keywords: Feynman rules, hadrons, Lagrangian, Monte Carlo, simulation.

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Authors: Khaing Win Mar, Thinn Thu Naing

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Nowadays, precipitation prediction is required for proper planning and management of water resources. Prediction with neural network models has received increasing interest in various research and application domains. However, it is difficult to determine the best neural network architecture for prediction since it is not immediately obvious how many input or hidden nodes are used in the model. In this paper, neural network model is used as a forecasting tool. The major aim is to evaluate a suitable neural network model for monthly precipitation mapping of Myanmar. Using 3-layerd neural network models, 100 cases are tested by changing the number of input and hidden nodes from 1 to 10 nodes, respectively, and only one outputnode used. The optimum model with the suitable number of nodes is selected in accordance with the minimum forecast error. In measuring network performance using Root Mean Square Error (RMSE), experimental results significantly show that 3 inputs-10 hiddens-1 output architecture model gives the best prediction result for monthly precipitation in Myanmar.

Keywords: Precipitation prediction, monthly precipitation, neural network models, Myanmar.

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Authors: Petr Teply

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While the form of crises may change, their essence remains the same (such as a cycle of abundant liquidity, rapid credit growth, and a low-inflation environment followed by an asset-price bubble). The current market turbulence began in mid-2000s when the US economy shifted to imbalanced both internal and external macroeconomic positions. We see two key causes of these problems – loose US monetary policy in early 2000s and US government guarantees issued on the securities by government-sponsored enterprises what was further fueled by financial innovations such as structured credit products. We have discovered both negative and positive lessons deriving from this crisis and divided the negative lessons into three groups: financial products and valuation, processes and business models, and strategic issues. Moreover, we address key risk management lessons and exit strategies derived from the current crisis and recommend policies that should help diminish the negative impact of future potential crises.

Keywords: exist strategy, global crisis, risk management, corporate governance

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Authors: Aykut Bedük, Kemalettin Eryeşil

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Together with the industrialization, women began to be included in business life by peeling off of the tasks given them by society and they have become a factor of production creating value in economic and social sense. Thus, women have taken place in the labor market, majority of which has been formed by men. In this study, the experiences of women entrepreneurs, who succeed in business activities, will be analyzed. By the study, current state of the women entrepreneurs in the labor market of Turkey will be put down, as a result of interferences obtained from the shared experiences of women entrepreneurs. Findings obtained at the end of the study are thought to light the way of future studies for increasing women entrepreneurship.

Keywords: Women Entrepreneurship, Entrepreneurship, Turkey.

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Authors: T. Ito, K. Kawaguchi, R. Ohta

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The purpose of this study is to provide a guideline to assist globally-minded companies in developing task-based English- language programs for their employees. After conducting an online self-assessment questionnaire comprised of 45 job-related tasks, we analyzed responses received from 3,000 Japanese company employees and developed a checklist that considered three areas; i) the percentage of those who need to accomplish English-language tasks in their workplace (need for English), ii) a five-point self-assessment score (task performance level), and iii) the impact of previous task experience on perceived performance (experience factor). The 45 tasks were graded according to five proficiency levels. Our results helped us to create a core guideline that may assist companies in two ways: first, in helping determine which tasks employees with a certain English proficiency should be able to satisfactorily carry out, and secondly, to quickly prioritize which business-related English skills they would need in future English language programs.

Keywords: Business settings, Can-do statements, English language training programs, Self-assessment, Task experience.

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Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

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Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: Deep neural models, natural language inference, recognizing textual entailment, sentence-to-sentence relation.

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Authors: M. Tahani, G. Karimi

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In this paper after reviewing some previous studies, in order to optimize the above knee prosthesis, beside the inertial properties a new controlling parameter is informed. This controlling parameter makes the prosthesis able to act as a multi behavior system when the amputee is opposing to different environments. This active prosthesis with the new controlling parameter can simplify the control of prosthesis and reduce the rate of energy consumption in comparison to recently presented similar prosthesis “Agonistantagonist active knee prosthesis". In this paper three models are generated, a passive, an active, and an optimized active prosthesis. Second order Taylor series is the numerical method in solution of the models equations and the optimization procedure is genetic algorithm. Modeling the prosthesis which comprises this new controlling parameter (SEP) during the swing phase represents acceptable results in comparison to natural behavior of shank. Reported results in this paper represent 3.3 degrees as the maximum deviation of models shank angle from the natural pattern. The natural gait pattern belongs to walking at the speed of 81 m/min.

Keywords: Above knee prosthesis, active controlling parameter, ballistic motion, swing phase.

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Authors: Benedek Kovacs, Janos Toth

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Solutions are proposed for the central problem of estimating the reaction rate coefficients in homogeneous kinetics. The first is based upon the fact that the right hand side of a kinetic differential equation is linear in the rate constants, whereas the second one uses the technique of neural networks. This second one is discussed deeply and its advantages, disadvantages and conditions of applicability are analyzed in the mirror of the first one. Numerical analysis carried out on practical models using simulated data, and our programs written in Mathematica.

Keywords: Neural networks, parameter estimation, linear regression, kinetic models, reaction rate coefficients.

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Authors: Masaru Furukawa, Shigeki Hirobayashi, Tadanobu Misawa

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Nowadays, IT/Business strategy alignment is still a key topic of concern among managers worldwide. Change has always being considered the primary challenge affecting the strategy alignment. Planning for alignment in uncertain and dynamic changing environments is burdened with risk as organizations seek to understand how much flexibility to build in their management information system so as to maintain high levels of alignment. The literature review showed that there is a tight relationship between IT infrastructure flexibility and the strategy alignment with strategic information systems (SIS) planning serving as a moderator of this relationship, and that emphasized the needs for organizations to use SIS planning consistently and to monitor the relationship between IS flexibility and the alignment. This paper presents the procedure of SIS planning with IS flexibility renovation via future oriented analysis of POC (penalty of change) as a function of cost and time. Using this SIS planning and monitoring IS flexibility and the alignment during periods of increased change in dynamic and uncertain environments reduces the risk that could transform IT into an inhibitor rather than an enabler of change.

Keywords: IT/Business strategy alignment, strategic information systems (SIS) planning, IS flexibility, penalty of change (POC).

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Authors: Elhameh Narimani, Mikhail Sorin, Philippe Micheau, Hakim Nesreddine

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Numerical models of the heat exchangers in ejector refrigeration system (ERS) were developed and validated with the experimental data. The models were based on the switched heat exchangers model using the moving boundary method, which were capable of estimating the zones’ lengths, the outlet temperatures of both sides and the heat loads at various experimental points. The developed models were utilized to investigate the influence of the primary flow pressure on the performance of an R245fa ERS based on its coefficient of performance (COP) and exergy efficiency. It was illustrated numerically and proved experimentally that increasing the primary flow pressure slightly reduces the COP while the exergy efficiency goes through a maximum before decreasing.

Keywords: Coefficient of performance, ejector refrigeration system, exergy efficiency, heat exchangers modeling, moving boundary method.

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Authors: Zongyou He, Bashu Tsai, Chinhung Ko, Tainchi Lu

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A procedural-animation-based approach which rapidly synthesize the adaptive locomotion for quadruped characters that they can walk or run in any directions on an uneven terrain within a dynamic environment was proposed. We devise practical motion models of the quadruped animals for adapting to a varied terrain in a real-time manner. While synthesizing locomotion, we choose the corresponding motion models by means of the footstep prediction of the current state in the dynamic environment, adjust the key-frames of the motion models relying on the terrain-s attributes, calculate the collision-free legs- trajectories, and interpolate the key-frames according to the legs- trajectories. Finally, we apply dynamic time warping to each part of motion for seamlessly concatenating all desired transition motions to complete the whole locomotion. We reduce the time cost of producing the locomotion and takes virtual characters to fit in with dynamic environments no matter when the environments are changed by users.

Keywords: Dynamic environment, motion synthesis, procedural animation, quadruped locomotion

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Authors: Adel Aloraini

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Financial forecasting using machine learning techniques has received great efforts in the last decide . In this ongoing work, we show how machine learning of graphical models will be able to infer a visualized causal interactions between different banks in the Saudi equities market. One important discovery from such learned causal graphs is how companies influence each other and to what extend. In this work, a set of graphical models named Gaussian graphical models with developed ensemble penalized feature selection methods that combine ; filtering method, wrapper method and a regularizer will be shown. A comparison between these different developed ensemble combinations will also be shown. The best ensemble method will be used to infer the causal relationships between banks in Saudi equities market.

Keywords: Causal interactions , banks, feature selection, regularizere,

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Authors: Vineet Kansal

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Enterprise Wide Information Systems (EWIS) implementation involves the entire business and will require changes throughout the firm. Because of the scope, complexity and continuous nature of ERP, the project-based approach to managing the implementation process resulted in failure rates of between 60% and 80%. In recent years ERP systems have received much attention. The organizational relevance and risk of ERP projects make it important for organizations to focus on ways to make ERP implementation successful. Once these systems are in place, however, their performance depends on the identified macro variables viz. 'Business Process', 'Decision Making' and 'Individual / Group working'. The questionnaire was designed and administered. The responses from 92 organizations were compiled. The relationship of these variables with EWIS performance is analyzed using inferential statistical measurements. The study helps to understand the performance of model presented. The study suggested in keeping away from the calamities and thereby giving the necessary competitive edge. Whenever some discrepancy is identified during the process of performance appraisal care has to be taken to draft necessary preventive measures. If all these measures are taken care off then the EWIS performance will definitely deliver the results.

Keywords: Enterprise Systems, performance, technology

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Authors: Miroslav Byrtus

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Large rotating systems, especially gear drives and gearboxes, occur as parts of many mechanical devices transmitting the torque with relatively small loss of power. With the increased demand for high speed machinery, mathematical modeling and dynamic analysis of gear drives gained importance. Mathematical description of such mechanical systems is a complex task evolving for several decades. In gear drive dynamic models, which include flexible shafts, bearings and gearing and use the finite elements, nonlinear effects due to gear mesh and bearings are usually ignored, for such models have large number of degrees of freedom (DOF) and it is computationally expensive to analyze nonlinear systems with large number of DOF. Therefore, these models are not suitable for simulation of nonlinear behavior with amplitude jumps in frequency response. The contribution uses a methodology of nonlinear large rotating system modeling which is based on degrees of freedom (DOF) number reduction using modal synthesis method (MSM). The MSM enables significant DOF number reduction while keeping the nonlinear behavior of the system in a specific frequency range. Further, the MSM with DOF number reduction is suitable for including detail models of nonlinear couplings (mainly gear and bearing couplings) into the complete gear drive models. Since each subsystem is modeled separately using different FEM systems, it is advantageous to parameterize models of subsystems and to use the parameterization for optimization of chosen design parameters. Final complex model of gear drive is assembled in MATLAB and MATLAB tools are used for dynamical analysis of the nonlinear system. The contribution is further focused on developing of a methodology for investigation of behavior of the system by Nonlinear Normal Modes with combination of the MSM using numerical continuation method. The proposed methodology will be tested using a two-stage gearbox including its housing.

Keywords: Vibro-impact system, rotating system, gear drive, modal synthesis method, numerical continuation method, periodic solution.

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Authors: Alireza Behvandi, Somayeh Tourani

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High pressure adsorption of carbon dioxide on zeolite 13X was investigated in the pressure range (0 to 4) Mpa and temperatures 298, 308 and 323K. The data fitting is accomplished with the Toth, UNILAN, Dubinin-Astakhov and virial adsorption models which are generally used for micro porous adsorbents such as zeolites. Comparison with experimental data from the literature indicated that the virial model would best determine results. These results may be partly attributed to the flexibility of the virial model which can accommodate as many constants as the data warrants.

Keywords: adsorption models, zeolite, carbon dioxide

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Authors: Pradip Peter Dey, Bhaskar Raj Sinha, Mohammad Amin, Hassan Badkoobehi

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Mathematical, graphical and intuitive models are often constructed in the development process of computational systems. The Unified Modeling Language (UML) is one of the most popular modeling languages used by practicing software engineers. This paper critically examines UML models and suggests an augmented use case view with the addition of new constructs for modeling software. It also shows how a use case diagram can be enhanced. The improved modeling constructs are presented with examples for clarifying important design and implementation issues.

Keywords: Software architecture, software design, Unified Modeling Language (UML), user interface.

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Authors: Z. Saleh, E. J. Avital, T. Korakianitis

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The effect of the blade tip geometry of a high pressure gas turbine is studied experimentally and computationally for high speed leakage flows. For this purpose two simplified models are constructed, one models a flat tip of the blade and the second models a cavity tip of the blade. Experimental results are obtained from a transonic wind tunnel to show the static pressure distribution along the tip wall and provide flow visualization. RANS computations were carried to provide further insight into the mean flow behavior and to calculate the discharge coefficient which is a measure of the flow leaking over the tip. It is shown that in both geometries of tip the flow separates over the tip to form a separation bubble. The bubble is higher for the cavity tip while a complete shock wave system of oblique waves ending with a normal wave can be seen for the flat tip. The discharge coefficient for the flat tip shows less dependence on the pressure ratio over the blade tip than the cavity tip. However, the discharge coefficient for the cavity tip is lower than that of the flat tip, showing a better ability to reduce the leakage flow and thus increase the turbine efficiency.

Keywords: Gas turbine, blade tip leakage flow, transonic flow.

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Authors: David E. Culler, Noah D. Anderson

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Integrated systems for product design, manufacturing, and lifecycle management are difficult to implement and customize. Commercial software vendors, including CAD/CAM and third party PDM/PLM developers, create user interfaces and functionality that allow their products to be applied across many industries. The result is that systems become overloaded with functionality, difficult to navigate, and use terminology that is unfamiliar to engineers and production personnel. For example, manufacturers of automotive, aeronautical, electronics, and household products use similar but distinct methods and processes. Furthermore, each company tends to have their own preferred tools and programs for controlling work and information flow and that connect design, planning, and manufacturing processes to business applications. This paper presents a methodology and a case study that addresses these issues and suggests that in the future more companies will develop personalized applications that fit to the natural way that their business operates. A functioning system has been implemented at a highly competitive U.S. aerospace tooling and component supplier that works with many prominent airline manufacturers around the world including The Boeing Company, Airbus, Embraer, and Bombardier Aerospace. During the last three years, the program has produced significant benefits such as the automatic creation and management of component and assembly designs (parametric models and drawings), the extensive use of lightweight 3D data, and changes to the way projects are executed from beginning to end. CATIA (CAD/CAE/CAM) and a variety of programs developed in C#, VB.Net, HTML, and SQL make up the current system. The web-based platform is facilitating collaborative work across multiple sites around the world and improving communications with customers and suppliers. This work demonstrates that the creative use of Application Programming Interface (API) utilities, libraries, and methods is a key to automating many time-consuming tasks and linking applications together.

Keywords: CAD/CAM, CAPP, PDM, PLM, Scalable Systems.

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Authors: Dalia Suša Vugec

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Business process management (BPM) is widely used approach focused on designing, mapping, changing, managing and analyzing business processes of an organization, which eventually leads to better performance and derives many other benefits. Since every organization strives to improve its performance in order to be sustainable and to remain competitive on the market in long-term period, numerous organizations are nowadays adopting and implementing BPM. However, not all organizations are equally successful in that. One of the ways of measuring BPM success is by measuring its maturity by calculating Process Performance Index (PPI) using ten BPM success factors. Still, although BPM is a holistic concept, organizational culture is not taken into consideration in calculating PPI. Hence, aim of this paper is twofold; first, it aims to explore and analyze the current state of BPM success factors within the big organizations from Slovenia, Croatia, and Austria and second, it aims to analyze the structure of organizational culture within the observed companies, focusing on the link with BPM success factors as well. The presented study is based on the results of the questionnaire conducted as the part of the PROSPER project (IP-2014-09-3729) and financed by Croatian Science Foundation. The results of the questionnaire reveal differences in the achieved levels of BPM success factors and therefore BPM maturity in total between the three observed countries. Moreover, the structure of organizational culture across three countries also differs. This paper discusses the revealed differences between countries as well as the link between organizational culture and BPM success factors.

Keywords: Business process management, BPM maturity, BPM success factors, organizational culture, process performance index.

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Authors: Mohd Aftar Abu Bakar, Noratiqah Mohd Ariff, Abdul Aziz Jemain

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Storm Event Analysis (SEA) provides a method to define rainfalls events as storms where each storm has its own amount and duration. By modelling daily probability of different types of storms, the onset, offset and cycle of rainfall seasons can be determined and investigated. Furthermore, researchers from the field of meteorology will be able to study the dynamical characteristics of rainfalls and make predictions for future reference. In this study, four categories of storms; short, intermediate, long and very long storms; are introduced based on the length of storm duration. Daily probability models of storms are built for these four categories of storms in Peninsular Malaysia. The models are constructed by using Bernoulli distribution and by applying linear regression on the first Fourier harmonic equation. From the models obtained, it is found that daily probability of storms at the Eastern part of Peninsular Malaysia shows a unimodal pattern with high probability of rain beginning at the end of the year and lasting until early the next year. This is very likely due to the Northeast monsoon season which occurs from November to March every year. Meanwhile, short and intermediate storms at other regions of Peninsular Malaysia experience a bimodal cycle due to the two inter-monsoon seasons. Overall, these models indicate that Peninsular Malaysia can be divided into four distinct regions based on the daily pattern for the probability of various storm events.

Keywords: Daily probability model, monsoon seasons, regions, storm events.

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Authors: Ngoc Dang Khoa Nguyen, Imran Ali

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The cloud customer relationship management (CRM) has emerged as an innovative tool to augment the customer satisfaction and performance of banking systems. Cloud CRM allows to collect, analyze and utilize customer-associated information and update the systems, thereby offer superior customer service. Cloud technologies have invaluable potential to ensure innovative customer experiences, successful collaboration, enhanced speed to marketplace and IT effectiveness. As such, many leading banks have been attracted towards adoption of such innovative and customer-driver solutions to revolutionize their existing business models. Chief Information Officers (CIOs) are already implemented or in the process of implementation of cloud CRM. However, many organizations are still reluctant to take such initiative due to the lack of information on the factors influencing its implementation. This paper, therefore, aims to delve into the strategies, benefits and challenges intertwined in the implementation of cloud CRM in banking sector and provide reliable solutions.

Keywords: Banking sector, cloud computing, cloud CRM, strategy.

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Authors: M. Hassani, Y. Hassani, N. Ajudanioskooei, N. N. Benvid

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Laser Forming process as a non-contact thermal forming process is widely used to forming and bending of metallic and non-metallic sheets. In this process, according to laser irradiation along a specific path, sheet is bent. One of the most important output parameters in laser forming is bending angle that depends on process parameters such as physical and mechanical properties of materials, laser power, laser travel speed and the number of scan passes. In this paper, Artificial Neural Network and Fuzzy Logic System were used to predict of bending angle in laser forming process. Inputs to these models were laser travel speed and laser power. The comparison between artificial neural network and fuzzy logic models with experimental results has been shown both of these models have high ability to prediction of bending angles with minimum errors.

Keywords: Artificial neural network, bending angle, fuzzy logic, laser forming.

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Authors: Theodosios Tsiakis, George Stephanides, George Pekos

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The growth of open networks created the interest to commercialise it. The establishment of an electronic business mechanism must be accompanied by a digital-electronic payment system to transfer the value of transactions. Financial organizations are requested to offer a secure e-payment synthesis with equivalent levels of trust and security served in conventional paper-based payment transactions. The paper addresses the challenge of the first trade problem in e-commerce, provides a brief literature review on electronic payment and attempts to explain the underlying concept and method of trust in relevance to electronic payment.

Keywords: Electronic payment, security, trust, electronic business mechanism.

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Authors: Javier Sedano-Cibrián, Julio Manuel de Luis-Ruiz, Rubén Pérez-Álvarez, Raúl Pereda-García, Beatriz Malagón-Picón

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Structural inspection activities are necessary to ensure the correct functioning of infrastructures. UAV techniques have become more popular than traditional techniques. Specifically, UAV Photogrammetry allows time and cost savings. The development of this technology has permitted the use of low-cost thermal sensors in UAVs. The representation of 3D thermal models with this type of equipment is in continuous evolution. The direct processing of thermal images usually leads to errors and inaccurate results. In this paper, a methodology is proposed for the generation of 3D thermal models using dual sensors, which involves the application of RGB and thermal images in parallel. Hence, the RGB images are used as the basis for the generation of the model geometry, and the thermal images are the source of the surface temperature information that is projected onto the model. Mining/industrial facilities representations that are obtained can be used for inspection activities.

Keywords: Aerial thermography, data processing, drone, low-cost, point cloud.

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Authors: M. Pepe, S. Ackermann, L. Fregonese, C. Achille

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3D models obtained with advanced survey techniques such as close-range photogrammetry and laser scanner are nowadays particularly appreciated in Cultural Heritage and Archaeology fields. In order to produce high quality models representing archaeological evidences and anthropological artifacts, the appearance of the model (i.e. color) beyond the geometric accuracy, is not a negligible aspect. The integration of the close-range photogrammetry survey techniques with the laser scanner is still a topic of study and research. By combining point cloud data sets of the same object generated with both technologies, or with the same technology but registered in different moment and/or natural light condition, could construct a final point cloud with accentuated color dissimilarities. In this paper, a methodology to uniform the different data sets, to improve the chromatic quality and to highlight further details by balancing the point color will be presented.

Keywords: Color models, cultural heritage, laser scanner, photogrammetry, point cloud color.

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Authors: Elmamy Ahmedsalem

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The world has witnessed the collapse of many corporate giants as a result of unethical behavior in recent decades. This has induced a series of questions by the global community on why such occurrences could happen, even with corporate governance in place. This paper attempts to propose a philosophical approach from an Islamic perspective to be consolidated with current corporate governance in order to confront contemporary dilemmas. In this paper, ethical theories are presented as a discussion followed by their applications to modern cases of financial collapses. Virtue ethics by Aristotle, justice and fairness by John Rawls, deontology by Immanuel Kant, and utilitarianism by John Stuart Mill, are the four theories which can then be contrasted with the paradigm of Muslim scholars. Despite the differences between the fundamental principles of Islamic and Western worldviews, their ethical theories are aimed at making right decisions and solving ethical dilemmas based on what is good for society. Therefore, Islamic principles should be synthesized with Western philosophy to form a more coherent framework. The integration of Islamic and western ethical theories into business is important for sound corporate governance.

Keywords: Business ethics, Islamic philosophy, western philosophy, Western and Islamic Worldview of Ethics.

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