Search results for: stochastic processes

Authors: Carlos Monge López, Patricia Gómez Hernández

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Educational innovation is a quality factor of teaching-learning processes and institutional accreditation. There is an increasing of these change processes, especially after 2000. However, the publications about this topic are more associated with ICTs in currently century. The main aim of the study was to determine the tendency of educational innovations around ICTs. The used method was mixed research design (content analysis, review of scientific literature and descriptive, comparative and correlation study) with 649 papers. In summary, the results indicated that, progressively, the educational innovation is associated with ICTs, in comparison with this type of change processes without ICTs. In conclusion, although this tendency, scientific literature must divulgate more kinds of pedagogical innovation with the aim of deepening in other new resources.

Keywords: descriptive study, knowledge society, pedagogical innovation, technologies

Procedia PDF Downloads 452

Authors: Rushiraj Heshi, Smriti Bhandari

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Master Data Management requires creation of Central repository, applying constraints on Repository and designing processes to manage data. Designing of Repository, constraints on repository and business processes is very tedious and time consuming task for large Enterprise. Hence Visual Repository, constraints and Process (Workflow) modeling is the most critical step in Master Data Management.In this paper, we realize a Visual Modeling tool for implementing Repositories, Constraints and Processes based on Eclipse Plugin using GMF/EMF which follows principles of Model Driven Engineering (MDE).

Keywords: EMF, GMF, GEF, repository, constraint, process

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Authors: Felicitas Pielsticker, Christoph Pielsticker, Ingo Witzke

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Neurological findings provide foundational results for many different disciplines. In this article we want to discuss these with a special focus on mathematics education. The intention is to make neuroscience research useful for the description of cognitive mathematical learning processes. A key issue of mathematics education is that students often behave as if their mathematical knowledge is constructed in isolated compartments with respect to the specific context of the original learning situation; supporting students to link these compartments to form a coherent mathematical society of mind is a fundamental task not only for mathematics teachers. This aspect goes hand in hand with the question if there is such a thing as abstract general mathematical knowledge detached from concrete reality. Educational Neuroscience may give answers to the question why students develop their mathematical knowledge in isolated subjective domains of experience and if it is generally possible to think in abstract terms. To address these questions, we will provide examples from different fields of mathematics education e.g. students’ development and understanding of the general concept of variables or the mathematical notion of universal proofs. We want to discuss these aspects in the reflection of functional studies which elucidate the role of specific brain regions in mathematical learning processes. In doing this the paper addresses concept formation processes of students in the mathematics classroom and how to support them adequately considering the results of (educational) neuroscience.

Keywords: brain regions, concept formation processes in mathematics education, proofs, teaching-learning processes

Procedia PDF Downloads 107

Authors: R. Berrached, H. Ait Mahamed, A. Iddou

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Water pollution is nowadays a serious problem, due to the increasing scarcity of water and thus to the impact induced by such pollution on the human health. Various techniques are made use of to deal with water pollution. Among the most used ones, some can be enumerated: the bacterian bed, the activated mud, the Lagunage as biological processes and coagulation-floculation as a physic-chemical process. These processes are very expensive and an treatment efficiency which decreases along with the increase of the initial pollutants’ concentration. This is the reason why research has been reoriented towards the use of a process by adsorption as an alternative solution instead of the other traditional processes. In our study, we have tempted to exploit the characteristics of two metallic hydroxides Al and Fe to purify contaminated water by two industrial dyes SBL blue and SRL-150 orange. Results have shown the efficiency of the two materials on the blue SBL dye.

Keywords: Metallic Hydroxydes, industrial dyes, purification, lagunage

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Authors: Jin-Qu Chen, Jie Liu, Yong Yin, Zi-Qi Ju, Yu-Yao Wu

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Increase in travel fare and station’s failure will have huge impact on passengers’ travel. The Urban Rail Transit (URT) station’s accessibility reliability under increasing travel fare and station failure are analyzed in this paper. Firstly, the passenger’s travel path is resumed based on stochastic user equilibrium and Automatic Fare Collection (AFC) data. Secondly, calculating station’s importance by combining LeaderRank algorithm and Ratio of Station Affected Passenger Volume (RSAPV), and then the station’s accessibility evaluation indicators are proposed based on the analysis of passenger’s travel characteristic. Thirdly, station’s accessibility under different scenarios are measured and rate of accessibility change is proposed as station’s accessibility reliability indicator. Finally, the accessibility of Hangzhou metro stations is analyzed by the formulated models. The result shows that Jinjiang station and Liangzhu station are the most important and convenient station in the Hangzhou metro, respectively. Station failure and increase in travel fare and station failure have huge impact on station’s accessibility, except for increase in travel fare. Stations in Hangzhou metro Line 1 have relatively worse accessibility reliability and Fengqi Road station’s accessibility reliability is weakest. For Hangzhou metro operational department, constructing new metro line around Line 1 and protecting Line 1’s station preferentially can effective improve the accessibility reliability of Hangzhou metro.

Keywords: automatic fare collection data, AFC, station’s accessibility reliability, stochastic user equilibrium, urban rail transit, URT

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Authors: Ana Staneva, Vessela Stoimenova

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A parametric estimation of the MBP with Power Series offspring distribution family is considered in this paper. The MLE for the parameters is obtained in the case when the observable data are incomplete and consist only with the generation sizes of the family tree of MBP. The parameter estimation is calculated by using the Monte Carlo EM algorithm. The estimation for the posterior distribution and for the offspring distribution parameters are calculated by using the Bayesian approach and the Gibbs sampler. The article proposes various examples with bivariate branching processes together with computational results, simulation and an implementation using R.

Keywords: Bayesian, branching processes, EM algorithm, Gibbs sampler, Monte Carlo methods, statistical estimation

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Authors: N. R. Badurally Adam, S. R. Monebhurrun, M. Z. Dauhoo, A. Khoodaruth

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Transport energy demand is vital for the economic growth of any country. Globalisation and better standard of living plays an important role in transport energy demand. Recently, transport energy demand in Mauritius has increased significantly, thus leading to an abuse of natural resources and thereby contributing to global warming. Forecasting the transport energy demand is therefore important for controlling and managing the demand. In this paper, we develop a model to predict the transport energy demand. The model developed is based on a system of five stochastic differential equations (SDEs) consisting of five endogenous variables: fuel price, population, gross domestic product (GDP), number of vehicles and transport energy demand and three exogenous parameters: crude birth rate, crude death rate and labour force. An interval of seven years is used to avoid any falsification of result since Mauritius is a developing country. Data available for Mauritius from year 2003 up to 2009 are used to obtain the values of design variables by applying genetic algorithm. The model is verified and validated for 2010 to 2012 by substituting the values of coefficients obtained by GA in the model and using particle swarm optimisation (PSO) to predict the values of the exogenous parameters. This model will help to control the transport energy demand in Mauritius which will in turn foster Mauritius towards a pollution-free country and decrease our dependence on fossil fuels.

Keywords: genetic algorithm, modeling, particle swarm optimization, stochastic differential equations, transport energy demand

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Authors: Veena Nair, Srikanth Prakash, Mayuri Wijayasundara

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Globally, the textile industry is a key contributor to the generation of solid waste which gets landfilled. Textile waste generation generally occurs in three stages, namely: producer waste, pre-consumer waste, and post-consumer waste. However, the different processes adopted in textile material extraction, manufacturing, and use have their respective impact in terms of the quantity of waste being diverted to landfills. The study is focused on assessing the value chains of the two most common textile fibres: cotton and polyester, catering to a broad categories of apparel products. This study attempts to identify and evaluate the key processes adopted by the textile industry at each of the stages in their value chain in terms of waste generation. The different processes identified in each of the stages in the textile value chains are mapped to their respective contribution in generating fibre waste which eventually gets diverted to landfill. The results of the study are beneficial for the overall industry in terms of improving the traceability of waste in the value chains and the selection of processes and behaviours facilitating the reduction of environmental impacts associated with landfills.

Keywords: textile waste, textile value chains, landfill waste, waste mapping

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Authors: Amer Ait Sidhoum

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Interest in sustainability has gained ground among practitioners, academics and policy-makers due to growing stakeholders’ awareness of environmental and social concerns. This is particularly true for agriculture. However, relatively little research has been conducted on the quantification of social sustainability and the contribution of social issues to the agricultural production efficiency. This research's main objective is to propose a method for evaluating prices of social outputs, more precisely shadow prices, by allowing for the stochastic nature of agricultural production that is to say for production uncertainty. In this article, the assessment of social outputs’ shadow prices is conducted within the methodological framework of nonparametric Data Envelopment Analysis (DEA). An output-oriented directional distance function (DDF) is implemented to represent the technology of a sample of Catalan arable crop farms and derive the efficiency scores the overall production technology of our sample is assumed to be the intersection of two different sub-technologies. The first sub-technology models the production of random desirable agricultural outputs, while the second sub-technology reflects the social outcomes from agricultural activities. Once a nonparametric production technology has been represented, the DDF primal approach can be used for efficiency measurement, while shadow prices are drawn from the dual representation of the DDF. Computing shadow prices is a method to assign an economic value to non-marketed social outcomes. Our research uses cross sectional, farm-level data collected in 2015 from a sample of 180 Catalan arable crop farms specialized in the production of cereals, oilseeds and protein (COP) crops. Our results suggest that our sample farms show high performance scores, from 85% for the bad state of nature to 88% for the normal and ideal crop growing conditions. This suggests that farm performance is increasing with an improvement in crop growth conditions. Results also show that average shadow prices of desirable state-contingent output and social outcomes for efficient and inefficient farms are positive, suggesting that the production of desirable marketable outputs and of non-marketable outputs makes a positive contribution to the farm production efficiency. Results also indicate that social outputs’ shadow prices are contingent upon the growing conditions. The shadow prices follow an upward trend as crop-growing conditions improve. This finding suggests that these efficient farms prefer to allocate more resources in the production of desirable outputs than of social outcomes. To our knowledge, this study represents the first attempt to compute shadow prices of social outcomes while accounting for the stochastic nature of the production technology. Our findings suggest that the decision-making process of the efficient farms in dealing with social issues are stochastic and strongly dependent on the growth conditions. This implies that policy-makers should adjust their instruments according to the stochastic environmental conditions. An optimal redistribution of rural development support, by increasing the public payment with the improvement in crop growth conditions, would likely enhance the effectiveness of public policies.

Keywords: data envelopment analysis, shadow prices, social sustainability, sustainable farming

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Authors: Said Al Saifi

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This paper proposes a conceptual model for understanding the impact of organisational culture on knowledge management processes and their link with organisational performance. It is suggested that organisational culture should be assessed as a multi-level construct comprising artifacts, espoused beliefs and values, and underlying assumptions. A holistic view of organisational culture and knowledge management processes, and their link with organisational performance, is presented. A comprehensive review of previous literature was undertaken in the development of the conceptual model. Taken together, the literature and the proposed model reveal possible relationships between organisational culture, knowledge management processes, and organisational performance. Potential implications of organisational culture levels for the creation, sharing, and application of knowledge are elaborated. In addition, the paper offers possible new insight into the impact of organisational culture on various knowledge management processes and their link with organisational performance. A number of possible relationships between organisational culture factors, knowledge management processes, and their link with organisational performance were employed to examine such relationships. The research model highlights the multi-level components of organisational culture. These are: the artifacts, the espoused beliefs and values, and the underlying assumptions. Through a conceptualisation of the relationships between organisational culture, knowledge management processes, and organisational performance, the study provides practical guidance for practitioners during the implementation of knowledge management processes. The focus of previous research on knowledge management has been on understanding organisational culture from the limited perspective of promoting knowledge creation and sharing. This paper proposes a more comprehensive approach to understanding organisational culture in that it draws on artifacts, espoused beliefs and values, and underlying assumptions, and reveals their impact on the creation, sharing, and application of knowledge which can affect overall organisational performance.

Keywords: knowledge application, knowledge creation, knowledge management, knowledge sharing, organisational culture, organisational performance

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Authors: Agarana Michael C., Akinlabi Esther T., Pule Kholopane

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Innovation in manufacturing process technologies and associated product design affects the prospects for manufacturing today and in near future. In this study some theoretical methods, useful as tools in advanced manufacturing, are considered. In particular, some basic Mathematical, Operational Research, Heuristic, and Statistical techniques are discussed. These techniques/methods are very handy in many areas of advanced manufacturing processes, including process planning optimization, modelling and analysis. Generally the production rate requires the application of Mathematical methods. The Emerging Trends Processes in Advanced Manufacturing can be enhanced by using Mathematical Modelling and Optimization techniques.

Keywords: mathematical modelling, optimization, emerging trends, advanced manufacturing

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Authors: Alica Höpken, Hergen Pargmann

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The resource-efficient planning of the complex production planning processes in the meat industry and the reduction of food waste is a permanent challenge. The complexity of the production planning process occurs in every part of the supply chain, from agriculture to the end consumer. It arises from long and uncertain planning phases. Uncertainties such as stochastic yields, fluctuations in demand, and resource variability are part of this process. In the meat industry, waste mainly relates to incorrect storage, technical causes in production, or overproduction. The high amount of food waste along the complex supply chain in the meat industry could not be reduced by simple solutions until now. Therefore, resource-efficient production planning by conventional methods is currently only partially feasible. The realization of intelligent, automated production planning is basically possible through the application of machine learning algorithms, such as those of reinforcement learning. By applying the adapted design thinking method, machine learning methods (especially reinforcement learning algorithms) are used for the complex production planning process in the meat industry. This method represents a concretization to the application area. A resource-efficient production planning process is made available by adapting the design thinking method. In addition, the complex processes can be planned efficiently by using this method, since this standardized approach offers new possibilities in order to challenge the complexity and the high time consumption. It represents a tool to support the efficient production planning in the meat industry. This paper shows an elegant adaption of the design thinking method to apply the reinforcement learning method for a resource-efficient production planning process in the meat industry. Following, the steps that are necessary to introduce machine learning algorithms into the production planning of the food industry are determined. This is achieved based on a case study which is part of the research project ”REIF - Resource Efficient, Economic and Intelligent Food Chain” supported by the German Federal Ministry for Economic Affairs and Climate Action of Germany and the German Aerospace Center. Through this structured approach, significantly better planning results are achieved, which would be too complex or very time consuming using conventional methods.

Keywords: change management, design thinking method, machine learning, meat industry, reinforcement learning, resource-efficient production planning

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Authors: Theresa Steiner, Markus Pajones, Christian Haider

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Traffic is being induced by companies due to their economic behavior. Basically, two different types of traffic occur at company sites: freight traffic and commuting traffic. Due to the fact that these traffic types are connected to each other in different kinds, an integrated approach to manage them is useful. Mobility management is a proved method for companies, to handle the traffic processes caused by their business activities. According to recent trend analysis in Austria, the freight traffic as well as the individual traffic, as part of the commuting traffic, will continue to increase. More traffic jams, as well as negative environmental impacts, are expected impacts for the future. Mobility management is a tool to control the traffic behavior with the scope to reduce emissions and other negative effects which are caused by traffic. Until now, mobility management is mainly used for optimizing commuting traffic without taking the freight logistics processes into consideration. However, the method of mobility management can be used to improve the freight traffic area of a company as well. The focus of this paper will be particularly laid on analyzing to what extent companies are already using mobility management to influence not only the commuting traffic they produce but also their processes of freight logistics. A further objective is to acquire knowledge about the motivating factors which persuade companies to introduce and apply mobility management. Additionally, advantages and disadvantages of this tool will be defined as well as limitations and factors of success, with a special focus on freight logistics, will be depicted. The first step of this paper is to conduct a literature review on the issue of mobility management with a special focus on freight logistics processes. To compare the theoretical findings with the practice, interviews, following a structured interview guidline, with mobility managers of different companies in Upper Austria will be undertaken. A qualitative analysis of these surveys will in a first step show the motivation behind using mobility management to improve traffic processes and how far this approach is already being used to especially influence the freight traffic of the companies. An evaluation to what extent the method of mobility management is already being approached at Upper Austrian companies to regulate freight logistics processes will be one outcome of this publication. Furthermore, the results of the theoretical and practical analysis will reveal not only the possibilities but also the limitations of using mobility management to influence the processes of freight logistics.

Keywords: freight logistics processes, freight traffic, mobility management, passenger traffic

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Authors: Chi-Chung Marven Chick, Chu-Po Ho, Sau-Chuen Joe Au, Wing-Fai Sidney Wong, Chi-Wai Kan

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3D printing is now drawing attention to manufacturing process. In fashion and textile industry, many 3D printing applications had been developed for prototyping or even final product production because of its great flexibility in production. However, when compared with conventional manufacturing processes for fashion and textiles, the design aspects and requirements may not be same for using 3D printing process. Therefore, in this paper, we will compare the design aspects between conventional manufacturing processes and 3D printing processes. Also, the material requirements related to the design in 3D printing for fashion and textiles will be reviewed and discussed. This review paper may demonstrate a possible way to develop 3D printing method(s) for fashion and textiles.

Keywords: 3D printing, design, textile, applications

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Authors: M. N. Osman Zahid, K. Case, D. Watts

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This paper reports an advanced approach in the application of CNC machining for rapid manufacturing processes (CNC-RM). The aim of this study is to improve the quality of machined parts by introducing different cutting tools during finishing operations. As the cutting is performed in different directions, the surfaces presented on part can be classified into several categories. Therefore, suitable cutting tools are assigned to machine particular surfaces and to improve the quality. Experimental studies have been carried out by fabricating several parts based on the suggested approach. The results provide further support for implementing this approach in rapid machining processes.

Keywords: CNC machining, end mill tool, finishing operation, rapid manufacturing

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Authors: Iulia E. Falcan

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The transition of the European power sector towards a clean, renewable energy (RE) system faces the challenge of meeting power demand in times of low wind speed and low solar radiation, at a reasonable cost. This is likely to be achieved through a combination of 1) energy storage technologies, 2) development of the cross-border power grid, 3) installed overcapacity of RE and 4) dispatchable power sources – such as biomass. This paper uses NASA; derived hourly data on weather patterns of sixteen European countries for the past twenty-five years, and load data from the European Network of Transmission System Operators-Electricity (ENTSO-E), to develop a stochastic optimization model. This model aims to understand the synergies between the four classes of technologies mentioned above and to determine the optimal configuration of the energy technologies portfolio. While this issue has been addressed before, it was done so using deterministic models that extrapolated historic data on weather patterns and power demand, as well as ignoring the risk of an unbalanced grid-risk stemming from both the supply and the demand side. This paper aims to explicitly account for the inherent uncertainty in the energy system transition. It articulates two levels of uncertainty: a) the inherent uncertainty in future weather patterns and b) the uncertainty of fully meeting power demand. The first level of uncertainty is addressed by developing probability distributions for future weather data and thus expected power output from RE technologies, rather than known future power output. The latter level of uncertainty is operationalized by introducing a Conditional Value at Risk (CVaR) constraint in the portfolio optimization problem. By setting the risk threshold at different levels – 1%, 5% and 10%, important insights are revealed regarding the synergies of the different energy technologies, i.e., the circumstances under which they behave as either complements or substitutes to each other. The paper concludes that allowing for uncertainty in expected power output - rather than extrapolating historic data - paints a more realistic picture and reveals important departures from results of deterministic models. In addition, explicitly acknowledging the risk of an unbalanced grid - and assigning it different thresholds - reveals non-linearity in the cost functions of different technology portfolio configurations. This finding has significant implications for the design of the European energy mix.

Keywords: cross-border grid extension, energy storage technologies, energy system transition, stochastic portfolio optimization

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Authors: T. Rajamäki

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In clean room environment molecular contamination in very small concentrations can cause significant harm for the components and processes. This is commonly referred as airborne molecular contamination (AMC). There is a shortage of high sensitivity continuous measurement data for existence and behavior of several of these contaminants. Accordingly, in most cases correlation between concentration of harmful molecules and their effect on processes is not known. In addition, the formation and distribution of contaminating molecules are unclear. In this work sensitive optical techniques are applied in clean room facilities for investigation of concentrations, forming mechanisms and effects of contaminating molecules. Special emphasis is on reactive acid and base gases ammonia (NH3) and hydrogen fluoride (HF). They are the key chemicals in several operations taking place in clean room processes.

Keywords: AMC, clean room, concentration, reactive gas

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Authors: Maxat Bokambayev, Bella Tussupova, Aisha Mamyrova, Erlan Izbasarov

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Optimization of business processes in trading companies is reviewed in the report. There is the presentation of the “Wholesale Customer Order Handling Process” business process model applicable for small and medium businesses. It is proposed to apply the algorithm for automation of the customer order processing which will significantly reduce labor costs and time expenditures and increase the profitability of companies. An optimized business process is an element of the information system of accounting of spare parts trading network activity. The considered algorithm may find application in the trading industry as well.

Keywords: business processes, discrete-event simulation, management, trading industry

Procedia PDF Downloads 314

Authors: Adrian Rettig, Silvan Schneider, Reto Tamburini, Mirko Kleingries, Ulf Christian Muller

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Industrial adsorption processes are, mainly due to si-multaneous heat and mass transfer, characterized by a high level of complexity. The conception of such processes often does not take place systematically; instead scale-up/down respectively number-up/down methods based on existing systems are used. This paper shows how Modelica® can be used to develop a transient model enabling a more systematic design of such ad- and desorption components and processes. The core of this model is a lumped-element submodel of a single adsorbent grain, where the thermodynamic equilibria and the kinetics of the ad- and desorption processes are implemented and solved on the basis of mass-, momentum and energy balances. For validation of this submodel, a fixed bed adsorber, whose characteristics are described in detail in the literature, was modeled and simulated. The simulation results are in good agreement with the experimental results from the literature. Therefore, the model development will be continued, and the extended model will be applied to further adsorber types like rotor adsorbers and moving bed adsorbers.

Keywords: adsorption, desorption, linear driving force, dynamic model, Modelica®, integral equation approach

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Authors: Riadh Zorgati, Thomas Triboulet

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In quite diverse application areas such as astronomy, medical imaging, geophysics or nondestructive evaluation, many problems related to calibration, fitting or estimation of a large number of input parameters of a model from a small amount of output noisy data, can be cast as inverse problems. Due to noisy data corruption, insufficient data and model errors, most inverse problems are ill-posed in a Hadamard sense, i.e. existence, uniqueness and stability of the solution are not guaranteed. A wide class of inverse problems in physics relates to the Fredholm equation of the first kind. The ill-posedness of such inverse problem results, after discretization, in a very ill-conditioned linear system of equations, the condition number of the associated matrix can typically range from 109 to 1018. This condition number plays the role of an amplifier of uncertainties on data during inversion and then, renders the inverse problem difficult to handle numerically. Similar problems appear in other areas such as numerical optimization when using interior points algorithms for solving linear programs leads to face ill-conditioned systems of linear equations. Devising efficient solution approaches for such system of equations is therefore of great practical interest. Efficient iterative algorithms are proposed for solving a system of linear equations. The approach is based on a preconditioning of the initial matrix of the system with an approximation of a generalized inverse leading to a stochastic preconditioned matrix. This approach, valid for non-negative matrices, is first extended to hermitian, semi-definite positive matrices and then generalized to any complex rectangular matrices. The main results obtained are as follows: 1) We are able to build a generalized inverse of any complex rectangular matrix which satisfies the convergence condition requested in iterative algorithms for solving a system of linear equations. This completes the (short) list of generalized inverse having this property, after Kaczmarz and Cimmino matrices. Theoretical results on both the characterization of the type of generalized inverse obtained and the convergence are derived. 2) Thanks to its properties, this matrix can be efficiently used in different solving schemes as Richardson-Tanabe or preconditioned conjugate gradients. 3) By using Lp norms, we propose generalized Kaczmarz’s type matrices. We also show how Cimmino's matrix can be considered as a particular case consisting in choosing the Euclidian norm in an asymmetrical structure. 4) Regarding numerical results obtained on some pathological well-known test-cases (Hilbert, Nakasaka, …), some of the proposed algorithms are empirically shown to be more efficient on ill-conditioned problems and more robust to error propagation than the known classical techniques we have tested (Gauss, Moore-Penrose inverse, minimum residue, conjugate gradients, Kaczmarz, Cimmino). We end on a very early prospective application of our approach based on stochastic matrices aiming at computing some parameters (such as the extreme values, the mean, the variance, …) of the solution of a linear system prior to its resolution. Such an approach, if it were to be efficient, would be a source of information on the solution of a system of linear equations.

Keywords: conditioning, generalized inverse, linear system, norms, stochastic matrix

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Authors: Timir Baran Roy, Luis Guerreiro, Ashutosh Bagchi

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Dynamic study is important in order to design, repair and rehabilitation of structures. It has played an important role in the behavior characterization of structures; such as bridges, dams, high-rise buildings etc. There had been a substantial development in this area over the last few decades, especially in the field of dynamic identification techniques of structural systems. Frequency Domain Decomposition (FDD) and Time Domain Decomposition are most commonly used methods to identify modal parameters; such as natural frequency, modal damping, and mode shape. The focus of the present research is to study the dynamic characteristics of typical timber masonry walls commonly used in Portugal. For that purpose, a multi-storey structural prototypes of such walls have been tested on a seismic shake table at the National Laboratory for Civil Engineering, Portugal (LNEC). Signal processing has been performed of the output response, which is collected from the shaking table experiment of the prototype using accelerometers. In the present work signal processing of the output response, based on the input response has been done in two ways: FDD and Stochastic Subspace Identification (SSI). In order to estimate the values of the modal parameters, algorithms for FDD are formulated, and parametric functions for the SSI are computed. Finally, estimated values from both the methods are compared to measure the accuracy of both the techniques.

Keywords: frequency domain decomposition (fdd), modal parameters, signal processing, stochastic subspace identification (ssi), time domain decomposition

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Authors: G. Shahzadi, A. Soulaimani

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This research work aims to identify the physical parameters of the constitutive soil model in the design of a rockfill dam by inverse analysis. The best parameters of the constitutive soil model, are those that minimize the objective function, defined as the difference between the measured and numerical results. The Finite Element code (Plaxis) has been utilized for numerical simulation. Polynomial and neural network-based response surfaces have been generated to analyze the relationship between soil parameters and displacements. The performance of surrogate models has been analyzed and compared by evaluating the root mean square error. A comparative study has been done based on objective functions and optimization techniques. Objective functions are categorized by considering measured data with and without uncertainty in instruments, defined by the least square method, which estimates the norm between the predicted displacements and the measured values. Hydro Quebec provided data sets for the measured values of the Romaine-2 dam. Stochastic optimization, an approach that can overcome local minima, and solve non-convex and non-differentiable problems with ease, is used to obtain an optimum value. Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) are compared for the minimization problem, although all these techniques take time to converge to an optimum value; however, PSO provided the better convergence and best soil parameters. Overall, parameter identification analysis could be effectively used for the rockfill dam application and has the potential to become a valuable tool for geotechnical engineers for assessing dam performance and dam safety.

Keywords: Rockfill dam, parameter identification, stochastic analysis, regression, PLAXIS

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Authors: Alireza Nikravanshallmani, Jamshid Dehmeshki, Mojtaba Ahmadi

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Modeling of business processes, based on BPMN (Business Process Modeling Notation), helps analysts and managers to understand business processes, and, identify their shortages. These models provide a context to make rational decision of organizing business processes activities in an understandable manner. The purpose of this paper is to provide a framework for better understanding of business processes and their problems by reducing the cognitive load of displayed information for their audience at different managerial levels while keeping the essential information which are needed by them. For this reason, we integrate business process diagrams across the different managerial levels to develop a framework to improve the performance of business process management (BPM) projects. The proposed framework is entitled ‘Business process improvement framework based on managerial levels (BPIML)’. This framework, determine a certain type of business process diagrams (BPD) based on BPMN with respect to the objectives and tasks of the various managerial levels of organizations and their roles in BPM projects. This framework will make us able to provide the necessary support for making decisions about business processes. The framework is evaluated with a case study in a real business process improvement project, to demonstrate its superiority over the conventional method. A questionnaire consisted of 10 questions using Likert scale was designed and given to the participants (managers of Bank Refah Kargaran three managerial levels). By examining the results of the questionnaire, it can be said that the proposed framework provide support for correct and timely decisions by increasing the clarity and transparency of the business processes which led to success in BPM projects.

Keywords: business process management (BPM), business process modeling, business process reengineering (BPR), business process optimizing, BPMN

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Authors: Kassem Saleh

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An alarming number of software projects fail to deliver the required functionalities within the provided budget and timeframe and with the required qualities. Some of the main reasons for this problem include bad stakeholder management, poor communications and informal change management. Informal processes to identify, engage and control stakeholders lead to these reasons. Recently, to emphasize its importance, the Project Management Institute (PMI) updated the Project Management Body of Knowledge (PMBoK) to explicitly include the stakeholder management knowledge area. This knowledge area consists of four processes to identify stakeholders, plan stakeholder management, and manage and control stakeholder engagement. The use of appropriate techniques for stakeholder management in software projects will definitely lead to higher quality and successful software. In this paper, we describe some of the proven techniques that can be used during the execution of the four processes for stakeholder management. Development of collaboration tools for automating these processes are recommended and need to be integrated in available software project management tools.

Keywords: project management, stakeholder management, software development, project management body of knowledge

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Authors: Issa M. Shehabat, Huda F. Y. Nimri

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This paper aims to study the relationship between knowledge management in its processes, including knowledge creation, knowledge sharing, knowledge organization, and knowledge application, and business intelligence tools, including OLAP, data mining, and data warehouse, and their impact on the decision-making process in the banking sector in Jordan. A total of 200 questionnaires were distributed to the sample of the study. The study hypotheses were tested using the statistical package SPSS. Study findings suggest that decision-making processes were positively related to knowledge management processes. Additionally, the components of business intelligence had a positive impact on decision-making. The study recommended conducting studies similar to this study in other sectors such as the industrial, telecommunications, and service sectors to contribute to enhancing understanding of the role of the knowledge management processes and business intelligence tools.

Keywords: business intelligence, knowledge management, decision making, Jordan, banking sector

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Authors: Fuad H. Veliev

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Negative pressure phenomenon appears in many thermodynamic, geophysical and biophysical processes in the Nature and technological systems. For more than 100 years of the laboratory researches beginning from F. M. Donny’s tests, the great values of negative pressure have been achieved. But this phenomenon has not been practically applied, being only a nice lab toy due to the special demands for the purity and homogeneity of the liquids for its appearance. The possibility of creation of direct wave of negative pressure in real heterogeneous liquid systems was confirmed experimentally under the certain kinetic and hydraulic conditions. The negative pressure can be considered as the factor of both useful and destroying energies. The new approach to generation of the negative pressure waves in impure, unclean fluids has allowed the creation of principally new energy saving technologies and installations to increase the effectiveness and efficiency of different production processes. It was proved that the negative pressure is one of the main factors causing hard troubles in some technological and natural processes. Received results emphasize the necessity to take into account the role of the negative pressure as an energy factor in evaluation of many transient thermohydrodynamic processes in the Nature and production systems.

Keywords: liquid systems, negative pressure, temperature, wave, metastable state

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Authors: Oscar F. Toro, Alexia Pardo Figueroa, Brigitte M. Larico

Abstract:

The development of new processes in the textile industry entails designing methodologies to select adequate supplies that fit these new processes requirements. This paper presents a methodology to select chemicals that fulfill a new process technical specifications. The proposed methodology involves three major phases: (1) Data collection of chemical products, (2) Qualitative pre-selection and (3) Laboratory tests. We have applied this methodology to the selection of a binder which will form a protective film above the textile fibers and bond them. Our findings were that, there exist five possible products that can be used in our new process: Arkofil, Elvanol, Size plus A, Size plus AC and Starch. This new methodology has both qualitative and experimental variables, and can be used to select supplies for new textile processes.

Keywords: binder, chemical products, selection methodology, textile supplies, textile fiber

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Authors: Qiaoyun Yang

Abstract:

Organizational scholars have paid enormous attention on how local governments manage their knowledge during the past two decades. Government knowledge management (KM) research recognizes that the management of knowledge flows and networks is critical to reforms on government service efficiency and the effect of administration. When dealing with complex affairs, all the limitations resulting from a lack of KM concept, processes and technologies among all the involved organizations begin to be exposed and further compound the processing difficulty of the affair. As a result, the challenges for individual or group knowledge sharing, knowledge digging and organizations’ collaboration in government's activities are diverse and immense. This analysis presents recent situation of government KM in China drawing from a total of more than 300 questionnaires and highlights important challenges that remain. The causes of the lapses in KM processes within and across the government agencies are discussed.

Keywords: KM processes, KM technologies, government, KM situation

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Authors: Bahman Ghaderi, Hedayat Hosseini, Parviz Kafche

Abstract:

The role of knowledge management processes in achieving the strategic goals of organizations is crucial. To this end, understanding the relationship between knowledge management processes and different aspects of strategic thinking (followed by long-term organizational planning) should be considered. This research examines the relationship between each of the five knowledge management processes (creation, storage, transfer, audit, and deployment) with each dimension of strategic thinking (vision, creativity, thinking, communication and analysis) in one of the major sectors of the food industry in Iran. In this research, knowledge management and its dimensions (knowledge acquisition, knowledge storage, knowledge transfer, knowledge auditing, and finally knowledge utilization) as independent variables and strategic thinking and its dimensions (creativity, systematic thinking, vision, strategic analysis, and strategic communication) are considered as the dependent variable. The statistical population of this study consisted of 245 managers and employees of Minoo Food Industrial Group in Tehran. In this study, a simple random sampling method was used, and data were collected by a questionnaire designed by the research team. Data were analyzed using SPSS 21 software. LISERL software is also used for calculating and drawing models and graphs. Among the factors investigated in the present study, knowledge storage with 0.78 had the most effect, and knowledge transfer with 0.62 had the least effect on knowledge management and thus on strategic thinking.

Keywords: knowledge management, strategic thinking, knowledge management processes, food industry

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Authors: Ainura Kairanbayeva

Abstract:

Currently, the issue of maintaining the operational condition of highways at the required level is acute in Kazakhstan. The impact of landslides on the state of the road industry in Kazakhstan has been poorly studied. This article presents the classification of natural hazards and examines the influence of atmospheric natural processes on the operational condition of the sections of the highway "Ayusai–Kosmostantsia" passing along the mountain slopes of the Trans-Ili Alatau. According to the results of field studies, multi-turn reflected cracks have been identified, this is also due to the fact that the base of the road is made of a sand-gravel mixture and is not treated with reinforcing additives and the actual density of the asphalt concrete pavement is below regulatory requirements.

Keywords: building materials and products, construction of highways and engineering structures, construction processes, displacements of the earth's surface, geodynamic processes

Procedia PDF Downloads 43