Search results for: computer modeling

Authors: Seok-In Sohn, Dae-Hwan Park, Yeon-Seung Lee, Il-Kwon Oh

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This paper presents an optimization of the hull separation, i.e. transverse clearance. The main objective is to identify the feasible speed ranges and find the optimum transverse clearance considering the minimum wave-making resistance. The dimensions and the weight of hardware systems installed in the catamaran structured fuel cell powered USV (Unmanned Surface Vehicle) were considered as constraints. As the CAE (Computer Aided Engineering) platform FRIENDSHIP-Framework was used. The hull surface modeling, DoE (Design of Experiment), Tangent search optimization, tool integration and the process automation were performed by FRIENDSHIP-Framework. The hydrodynamic result was evaluated by XPAN the potential solver of SHIPFLOW.

Keywords: Full parametric modeling, Hull Separation, Wave-making resistance, Design Of Experiment, Tangent search method

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Authors: Anwar H. Jarndal, Ahmed S. Elwakil

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In this paper, a fraction-order model for pad parasitic effect of GaN HEMT on Si substrate is developed and validated. Open de-embedding structure is used to characterize and de-embed substrate loading parasitic effects. Unbiased device measurements are implemented to extract parasitic inductances and resistances. The model shows very good simulation for S-parameter measurements under different bias conditions. It has been found that this approach can improve the simulation of intrinsic part of the transistor, which is very important for small- and large-signal modeling process.

Keywords: Fractional-order modeling, GaN HEMT, Si-substrate, open de-embedding structure.

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Authors: Ahmed Arara

Abstract:

Information sharing and exchange, rather than information processing, is what characterizes information technology in the 21st century. Ontologies, as shared common understanding, gain increasing attention, as they appear as the most promising solution to enable information sharing both at a semantic level and in a machine-processable way. Domain Ontology-based modeling has been exploited to provide shareability and information exchange among diversified, heterogeneous applications of enterprises. Contextual ontologies are “an explicit specification of contextual conceptualization". That is: ontology is characterized by concepts that have multiple representations and they may exist in several contexts. Hence, contextual ontologies are a set of concepts and relationships, which are seen from different perspectives. Contextualization is to allow for ontologies to be partitioned according to their contexts. The need for contextual ontologies in enterprise modeling has become crucial due to the nature of today's competitive market. Information resources in enterprise is distributed and diversified and is in need to be shared and communicated locally through the intranet and globally though the internet. This paper discusses the roles that ontologies play in an enterprise modeling, and how ontologies assist in building a conceptual model in order to provide communicative and interoperable information systems. The issue of enterprise modeling based on contextual domain ontology is also investigated, and a framework is proposed for an enterprise model that consists of various applications.

Keywords: Contextual ontologies, Enterprise model, domainontology.

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Authors: Huiming Peng, Jianguo Wen, Hongwei Li, Jeff Chang, Xiaobo Zhou

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NFκB activation plays a crucial role in anti-apoptotic responses in response to the apoptotic signaling during tumor necrosis factor (TNFa) stimulation in Multiple Myeloma (MM). Although several drugs have been found effective for the treatment of MM by mainly inhibiting NFκB pathway, there are no any quantitative or qualitative results of comparison assessment on inhibition effect between different single drugs or drug combinations. Computational modeling is becoming increasingly indispensable for applied biological research mainly because it can provide strong quantitative predicting power. In this study, a novel computational pathway modeling approach is employed to comparably assess the inhibition effects of specific single drugs and drug combinations on the NFκB pathway in MM, especially the prediction of synergistic drug combinations.

Keywords: Computational modeling, drug combination, inhibition effect, multiple myeloma, NFkB pathway.

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Authors: H. Mahboubi, B. Moshiri, A. Khaki Seddigh

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In the past decade, because of wide applications of hybrid systems, many researchers have considered modeling and control of these systems. Since switching systems constitute an important class of hybrid systems, in this paper a method for optimal control of linear switching systems is described. The method is also applied on the two-tank system which is a much appropriate system to analyze different modeling and control techniques of hybrid systems. Simulation results show that, in this method, the goals of control and also problem constraints can be satisfied by an appropriate selection of cost function.

Keywords: Hybrid systems, optimal control, switched systems, two-tank system

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Authors: M. R. Mustafa, M. H. Isa, R. B. Rezaur

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The use of artificial neural network (ANN) modeling for prediction and forecasting variables in water resources engineering are being increasing rapidly. Infrastructural applications of ANN in terms of selection of inputs, architecture of networks, training algorithms, and selection of training parameters in different types of neural networks used in water resources engineering have been reported. ANN modeling conducted for water resources engineering variables (river sediment and discharge) published in high impact journals since 2002 to 2011 have been examined and presented in this review. ANN is a vigorous technique to develop immense relationship between the input and output variables, and able to extract complex behavior between the water resources variables such as river sediment and discharge. It can produce robust prediction results for many of the water resources engineering problems by appropriate learning from a set of examples. It is important to have a good understanding of the input and output variables from a statistical analysis of the data before network modeling, which can facilitate to design an efficient network. An appropriate training based ANN model is able to adopt the physical understanding between the variables and may generate more effective results than conventional prediction techniques.

Keywords: ANN, discharge, modeling, prediction, sediment,

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Authors: Christhu Raj, Rajeev Sukumaran

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In this research article of modeling Underwater Wireless Sensor Network Simulators, we provide a comprehensive overview of the various currently available simulators used in UWSN modeling. In this work, we compare their working environment, software platform, simulation language, key features, limitations and corresponding applications. Based on extensive experimentation and performance analysis, we provide their efficiency for specific applications. We have also provided guidelines for developing protocols in different layers of the protocol stack, and finally these parameters are also compared and tabulated. This analysis is significant for researchers and designers to find the right simulator for their research activities.

Keywords: Underwater Wireless Sensor networks (UWSN), SUNSET, NS2, OPNET, WOSS, DESERT, RECORDS, Aqua- Sim, Aqua- Net Mate.

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Authors: W. Louhichi, M.Berrima, N. Ben Rajeb Robbana

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Elasticity is the essential property of cloud computing. As the name suggests, it constitutes the ability of a cloud system to adjust resource provisioning in relation to fluctuating workloads. There are two types of elasticity operations, vertical and horizontal. In this work, we are interested in horizontal scaling, which is ensured by two mechanisms; scaling in and scaling out. Following the sizing of the system, we can adopt scaling in the event of over-supply and scaling out in the event of under-supply. In this paper, we propose a formal model, based on temporized and colored Petri nets (TdCPNs), for the modeling of the duplication and the removal of a virtual machine from a server. This model is based on formal Petri Nets (PNs) modeling language. The proposed models are edited, verified, and simulated with two examples implemented in colored Petri nets (CPNs)tools, which is a modeling tool for colored and timed PNs.

Keywords: Cloud computing, elasticity, elasticity controller, petri nets, scaling in, scaling out.

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Authors: M. Goodarzi, P. Lashgari

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A major part of the flow field involves no complicated turbulent behavior in many turbulent flows. In this research work, in order to reduce required memory and CPU time, the flow field was decomposed into several blocks, each block including its special turbulence. A two dimensional backward facing step was considered here. Four combinations of the Prandtl mixing length and standard k- E models were implemented as well. Computer memory and CPU time consumption in addition to numerical convergence and accuracy of the obtained results were mainly investigated. Observations showed that, a suitable combination of turbulence models in different blocks led to the results with the same accuracy as the high order turbulence model for all of the blocks, in addition to the reductions in memory and CPU time consumption.

Keywords: Computer memory, CPU time, Multi-block method, Turbulence modeling.

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Authors: Nyein Nyein Soe, Thet Thet Han Yee, Soe Sandar Aung

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This paper is proposed the dynamic simulation of small power induction motor based on Mathematical modeling. The dynamic simulation is one of the key steps in the validation of the design process of the motor drive systems and it is needed for eliminating inadvertent design mistakes and the resulting error in the prototype construction and testing. This paper demonstrates the simulation of steady-state performance of induction motor by MATLAB Program Three phase 3 hp induction motor is modeled and simulated with SIMULINK model.

Keywords: Squirrel cage induction motor, modeling andsimulation, MATLAB software, torque, speed.

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Authors: Albertus G. Joubert, Roelien Goede

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Benefits to the organisation are just as important as technical ability when it comes to software success. The challenge is to provide industry with professionals who understand this. In other words: How to teach computer engineering students to look beyond technology, and at the benefits of software to organizations? This paper reports on the conceptual design of a section of the computer networks module aimed to sensitize the students to the organisational context. Checkland focuses on different worldviews represented by various role players in the organisation. He developed the Soft Systems Methodology that guides purposeful action in organisations, while incorporating different worldviews in the modeling process. If we can sensitize students to these methods, they are likely to appreciate the wider context of application of system software. This paper will provide literature on these concepts as well as detail on how the students will be guided to adopt these concepts.

Keywords: Checkland, Soft Systems Methodology, Systems Approach, System Software.

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Authors: Werner Sandmann, Verena Wolf

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Stochastic models of biological networks are well established in systems biology, where the computational treatment of such models is often focused on the solution of the so-called chemical master equation via stochastic simulation algorithms. In contrast to this, the development of storage-efficient model representations that are directly suitable for computer implementation has received significantly less attention. Instead, a model is usually described in terms of a stochastic process or a "higher-level paradigm" with graphical representation such as e.g. a stochastic Petri net. A serious problem then arises due to the exponential growth of the model-s state space which is in fact a main reason for the popularity of stochastic simulation since simulation suffers less from the state space explosion than non-simulative numerical solution techniques. In this paper we present transition class models for the representation of biological network models, a compact mathematical formalism that circumvents state space explosion. Transition class models can also serve as an interface between different higher level modeling paradigms, stochastic processes and the implementation coded in a programming language. Besides, the compact model representation provides the opportunity to apply non-simulative solution techniques thereby preserving the possible use of stochastic simulation. Illustrative examples of transition class representations are given for an enzyme-catalyzed substrate conversion and a part of the bacteriophage λ lysis/lysogeny pathway.

Keywords: Computational Modeling, Biological Networks, Stochastic Models, Markov Chains, Transition Class Models.

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Authors: Ali Haroonabadi, Mohammad Teshnehlab

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None of the processing models in the software development has explained the software systems performance evaluation and modeling; likewise, there exist uncertainty in the information systems because of the natural essence of requirements, and this may cause other challenges in the processing of software development. By definition an extended version of UML (Fuzzy- UML), the functional requirements of the software defined uncertainly would be supported. In this study, the behavioral description of uncertain information systems by the aid of fuzzy-state diagram is crucial; moreover, the introduction of behavioral diagrams role in F-UML is investigated in software performance modeling process. To get the aim, a fuzzy sub-profile is used.

Keywords: Fuzzy System, Software Development Model, Software Performance Evaluation, UML

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Authors: Hala Abdel hameed, Hazem M. El-Bakry, Torky Sultan

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There are many issues that affect modeling and designing real-time databases. One of those issues is maintaining consistency between the actual state of the real-time object of the external environment and its images as reflected by all its replicas distributed over multiple nodes. The need to improve the scalability is another important issue. In this paper, we present a general framework to design a replicated real-time database for small to medium scale systems and maintain all timing constrains. In order to extend the idea for modeling a large scale database, we present a general outline that consider improving the scalability by using an existing static segmentation algorithm applied on the whole database, with the intent to lower the degree of replication, enables segments to have individual degrees of replication with the purpose of avoiding excessive resource usage, which all together contribute in solving the scalability problem for DRTDBS.

Keywords: Database modeling, Distributed database, Real time databases, Replication

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Authors: Hacene Benkhoula, Mohamed Badreddine Benabdella, Hamid Bouzeboudja, Abderrahmane Asraoui

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The wind is a random variable difficult to master, for this, we developed a mathematical and statistical methods enable to modeling and forecast wind power. Gaussian Processes (GP) is one of the most widely used families of stochastic processes for modeling dependent data observed over time, or space or time and space. GP is an underlying process formed by unrecognized operator’s uses to solve a problem. The purpose of this paper is to present how to forecast wind power by using the GP. The Gaussian process method for forecasting are presented. To validate the presented approach, a simulation under the MATLAB environment has been given.

Keywords: Forecasting, Gaussian process, modeling, wind power.

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Authors: K. Jahani, J. Razavi

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Nowadays, to decrease the number of downtimes in the industries such as metal mining, petroleum and chemical industries, predictive maintenance is crucial. In order to have efficient predictive maintenance, knowing the performance of critical equipment of production line such as pumps and hydro-cyclones under variable operating parameters, selecting best indicators of this equipment health situations, best locations for instrumentation, and also measuring of these indicators are very important. In this paper, computer aided engineering (CAE) tools are implemented to study some important elements of copper process line, namely slurry pumps and cyclone to predict the performance of these components under different working conditions. These modeling and simulations can be used in predicting, for example, the damage tolerance of the main shaft of the slurry pump or wear rate and location of cyclone wall or pump case and impeller. Also, the simulations can suggest best-measuring parameters, measuring intervals, and their locations.

Keywords: Computer aided engineering, predictive maintenance, fault detection, mining process line, slurry pump, hydrocyclone.

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Authors: Omar Boutkhoum, Mohamed Hanine, Tarik Agouti, Abdessadek Tikniouine

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This paper discusses the intake of combining multi-criteria decision analysis (MCDA) with OLAP systems, to generate an integrated analysis process dealing with complex multi-criteria decision-making situations. In this context, a multi-agent modeling is presented for decision support systems by combining multi-criteria decision analysis (MCDA) with OLAP systems. The proposed modeling which consists in performing the multi-agent system (MAS) architecture, procedure and protocol of the negotiation model is elaborated as a decision support tool for complex decision-making environments. Our objective is to take advantage from the multi-agent system which distributes resources and computational capabilities across interconnected agents, and provide a problem modeling in terms of autonomous interacting component-agents. Thus, the identification and evaluation of criteria as well as the evaluation and ranking of alternatives in a decision support situation will be performed by organizing tasks and user preferences between different agents in order to reach the right decision. At the end, an illustrative example is conducted to demonstrate the function and effectiveness of our MAS modeling.

Keywords: Multidimensional Analysis, OLAP Analysis, Multi-criteria Decision Analysis, Multi-Agent System, Decision Support System.

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Authors: Suhas K, Sripadaraja K

Abstract:

This paper details few mechanical modeling and design issues of RF MEMS switches. We concentrate on an electrostatically actuated broad side series switch; surface micromachined with a crab leg membrane. The same results are extended to any complex structure. With available experimental data and fabrication results, we present the variation in dynamic performance and compliance of the switch with reference to few design issues, which we find are critical in deciding the dynamic behavior of the switch, without compromise on the RF characteristics. The optimization of pull in voltage, transient time and resonant frequency with regard to these critical design parameters are also presented.

Keywords: Microelectromechanical Systems (MEMS), RadioFrequency MEMS, Modeling, Actuators

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Authors: Mehdi Salami-Kalajahi, Pejman Ganjeh-Anzabi, Vahid Haddadi-Asl, Mohammad Najafi

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In the following text, we show that by introducing universal kinetic scheme, the origin of rate retardation and inhibition period which observed in dithiobenzoate-mediated RAFT polymerization can be described properly. We develop our model by utilizing the method of moments, then we apply our model to different monomer/RAFT agent systems, both homo- and copolymerization. The modeling results are in an excellent agreement with experiments and imply the validity of universal kinetic scheme, not only for dithiobenzoate-mediated systems, but also for different types of monomer/RAFT agent ones.

Keywords: RAFT Polymerization, Mechanism, Kinetics, Moment Equations, Modeling.

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Authors: Moeiz Miraoui, Chakib Tadj, Chokri ben Amar

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Devices in a pervasive computing system (PCS) are characterized by their context-awareness. It permits them to provide proactively adapted services to the user and applications. To do so, context must be well understood and modeled in an appropriate form which enhance its sharing between devices and provide a high level of abstraction. The most interesting methods for modeling context are those based on ontology however the majority of the proposed methods fail in proposing a generic ontology for context which limit their usability and keep them specific to a particular domain. The adaptation task must be done automatically and without an explicit intervention of the user. Devices of a PCS must acquire some intelligence which permits them to sense the current context and trigger the appropriate service or provide a service in a better suitable form. In this paper we will propose a generic service ontology for context modeling and a context-aware service adaptation based on a service oriented definition of context.

Keywords: Pervasive computing system, context, contextawareness, service, context modeling, ontology, adaptation, machine learning.

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Authors: Lo Kar Yin, Law Ka Mei

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Architectural, engineering, construction and operations (AECO) industry practitioners have been well adapting to the dynamic construction market from the fundamental training of its disciplines. As further triggered by the pandemic since 2019, great steps are taken in virtual environment and the best collaboration is strived with project teams without boundaries. With adoption of Building Information Modeling-based approach and qualitative analysis, this paper is to review quantity take-off (QTO) and cost estimation process through modeling techniques in liaison with suppliers, fabricators, subcontractors, contractors, designers, consultants and services providers in the construction industry value chain for automatic project cost budgeting, project cost control and cost evaluation on design options of in-situ reinforced-concrete construction and Modular Integrated Construction (MiC) at design stage, variation of works and cash flow/spending analysis at construction stage as far as practicable, with a view to sharing the findings for enhancing mutual trust and co-operation among AECO industry practitioners. It is to foster development through a common prototype of design and build project delivery method in NEC4 Engineering and Construction Contract (ECC) Options A and C.

Keywords: Building Information Modeling, cost estimation, quantity take-off, modeling techniques.

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Authors: Adel Smeda, Adel Alti, Mourad Oussalah, Abdallah Boukerram

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A key aspect of the design of any software system is its architecture. An architecture description provides a formal model of the architecture in terms of components and connectors and how they are composed together. COSA (Component-Object based Software Structures), is based on object-oriented modeling and component-based modeling. The model improves the reusability by increasing extensibility, evolvability, and compositionality of the software systems. This paper presents the COSA modelling tool which help architects the possibility to verify the structural coherence of a given system and to validate its semantics with COSA approach.

Keywords: Software Architecture, Architecture Description Languages, UML, Components, Connectors.

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Authors: Changqiao Wu, Guoqing Ding, Xin Chen

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In this paper, ways of modeling dynamic measurement systems are discussed. Specially, for linear system with single-input single-output, it could be modeled with shallow neural network. Then, gradient based optimization algorithms are used for searching the proper coefficients. Besides, method with normal equation and second order gradient descent are proposed to accelerate the modeling process, and ways of better gradient estimation are discussed. It shows that the mathematical essence of the learning objective is maximum likelihood with noises under Gaussian distribution. For conventional gradient descent, the mini-batch learning and gradient with momentum contribute to faster convergence and enhance model ability. Lastly, experimental results proved the effectiveness of second order gradient descent algorithm, and indicated that optimization with normal equation was the most suitable for linear dynamic models.

Keywords: Dynamic system modeling, neural network, normal equation, second order gradient descent.

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Authors: Amin Eslami, Jafar Bolouri Bazaz

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Under active stress conditions, a rigid cantilever retaining wall tends to rotate about a pivot point located within the embedded depth of the wall. For purely granular and cohesive soils, a methodology was previously reported called minimization of moment ratio to determine the location of the pivot point of rotation. The usage of this new methodology is to estimate the rotational stability safety factor. Moreover, the degree of improvement required in a backfill to get a desired safety factor can be estimated by the concept of the shear strength demand. In this article, the accuracy of this method for another type of cantilever walls called Contiguous Bored Pile (CBP) retaining wall is evaluated by using physical modeling technique. Based on observations, the results of moment ratio minimization method are in good agreement with the results of the carried out physical modeling.

Keywords: Cantilever Retaining Wall, Physical Modeling, Minimization of Moment Ratio Method, Pivot Point.

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Authors: Z. Hormozi Moghaddam, M. Mokhtari-Dizaji, M. Movahedin, M. E. Ravari

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Mechanical index (MI) is used for quantifying acoustic cavitation and the relationship between acoustic pressure and the frequency. In this study, modeling of the MI was applied to provide treatment protocol and to understand the effective physical processes on reproducibility of stem cells. The acoustic pressure and MI equations are modeled and solved to estimate optimal MI for 28, 40, 150 kHz and 1 MHz frequencies. Radial and axial acoustic pressure distribution was extracted. To validate the results of the modeling, the acoustic pressure in the water and near field depth was measured by a piston hydrophone. Results of modeling and experiments show that the model is consistent well to experimental results with 0.91 and 0.90 correlation of coefficient (p<0.05) for 1 MHz and 40 kHz. Low intensity ultrasound with 0.40 MI is more effective on the proliferation rate of the spermatogonial stem cells during the seven days of culture, in contrast, high MI has a harmful effect on the spermatogonial stem cells. This model provides proper treatment planning in vitro and in vivo by estimating the cavitation phenomenon.

Keywords: Ultrasound, mechanical index, modeling, stem cell.

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Authors: Abbas Khoshhal, Masoud Rahimi, Sayed Reza Shabanian, Ammar Abdulaziz Alsairafi

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In the present study, the rate of NOx emission in a combustion chamber working in conventional combustion and High Temperature Air Combustion (HiTAC) system are examined using CFD modeling. The effect of peak temperature, combustion air temperature and oxygen concentration on NOx emission rate was undertaken. Results show that in a fixed oxygen concentration, increasing the preheated air temperature will increase the peak temperature and NOx emission rate. In addition, it was observed that the reduction of the oxygen concentration in the fixed preheated air temperature decreases the peak temperature and NOx emission rate. On the other hand, the results show that increase of preheated air temperature at various oxygen concentrations increases the NOx emission rate. However, the rate of increase in HiTAC conditions is quite lower than the conventional combustion. The modeling results show that the NOx emission rate in HiTAC combustion is 133% less than that of the conventional combustion.

Keywords: CFD Modeling, HiTAC, NOx, Combustion.

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Authors: Sahba Sadir, M. R. A. Kadir, A. Öchsner, M. N. Harun

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Scaffolds play a key role in tissue engineering and can be produced in many different ways depending on the applications and the materials used. Most researchers used an experimental trialand- error approach into new biomaterials but computer simulation applied to tissue engineering can offer a more exhaustive approach to test and screen out biomaterials. This paper develops the model of scaffolds and Computational Fluid Dynamics that show the value of computer simulations in determining the influence of the geometrical scaffold parameter porosity, pore size and shape on the permeability of scaffolds, magnitude of velocity, drop pressure, shear stress distribution and level and the proper design of the geometry of the scaffold. This creates a need for more advanced studies that include aspects of dynamic conditions of a micro fluid passing through the scaffold were characterized for tissue engineering applications and differentiation of tissues within scaffolds.

Keywords: Scaffold engineering, Tissue engineering, Cellularstructure, Biomaterial, Computational fluid dynamics.

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Authors: Bothinah Altaf, Gary Montague, Elaine B. Martin

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This study involves the modeling and monitoring of an ammonia synthesis fixed-bed reactor using partial least squares (PLS) and its variants. The process exhibits complex dynamic behavior due to the presence of heat recycling and feed quench. One limitation of static PLS model in this situation is that it does not take account of the process dynamics and hence dynamic PLS was used. Although it showed, superior performance to static PLS in terms of prediction, the monitoring scheme was inappropriate hence adaptive PLS was considered. A limitation of adaptive PLS is that non-conforming observations also contribute to the model, therefore, a new adaptive approach was developed, robust adaptive dynamic PLS. This approach updates a dynamic PLS model and is robust to non-representative data. The developed methodology showed a clear improvement over existing approaches in terms of the modeling of the reactor and the detection of faults.

Keywords: Ammonia synthesis fixed-bed reactor, dynamic partial least squares modeling, recursive partial least squares, robust modeling.

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Authors: Yousef Abu Nahleh, Arun Kumar, Fugen Daver, Reham Al-Hindawi

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Despite the availability of natural disaster related time series data for last 110 years, there is no forecasting tool available to humanitarian relief organizations to determine forecasts for emergency logistics planning. This study develops a forecasting tool based on identifying probability of disaster for each country in the world by using decision tree modeling. Further, the determination of aggregate forecasts leads to efficient pre-disaster planning. Based on the research findings, the relief agencies can optimize the various resources allocation in emergency logistics planning.

Keywords: Decision tree modeling, Forecasting, Humanitarian relief, emergency supply chain.

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Authors: Robest Flasza, Milan Rippel, Jan Solc

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The main aim of this paper is to develop and calibrate an econometric model for modeling prices of long term electricity futures contracts. The calibration of our model is performed on data from EEX AG allowing us to capture the specific features of German electricity market. The data sample contains several structural breaks which have to be taken into account for modeling. We model the data with an ARIMAX model which reveals high correlation between the price of electricity futures contracts and prices of LT futures contracts of fuels (namely coal, natural gas and crude oil). Besides this, also a share price index of representative electricity companies traded on Xetra, spread between 10Y and 1Y German bonds and exchange rate between EUR and USD appeared to have significant explanatory power over these futures contracts on EEX.

Keywords: electricity futures, EEX, ARIMAX, emissionallowances

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