Search results for: time series modeling.

Authors: D. Zare, H. Naderi, A. A. Jafari

Abstract:

Drying characteristics of rough rice (variety of lenjan) with an initial moisture content of 25% dry basis (db) was studied in a hot air dryer assisted by infrared heating. Three arrival air temperatures (30, 40 and 500C) and four infrared radiation intensities (0, 0.2 , 0.4 and 0.6 W/cm2) and three arrival air speeds (0.1, 0.15 and 0.2 m.s-1) were studied. Bending strength of brown rice kernel, percentage of cracked kernels and time of drying were measured and evaluated. The results showed that increasing the drying arrival air temperature and radiation intensity of infrared resulted decrease in drying time. High bending strength and low percentage of cracked kernel was obtained when paddy was dried by hot air assisted infrared dryer. Between this factors and their interactive effect were a significant difference (p<0.01). An intensity level of 0.2 W/cm2 was found to be optimum for radiation drying. Furthermore, in the present study, the application of Artificial Neural Network (ANN) for predicting the moisture content during drying (output parameter for ANN modeling) was investigated. Infrared Radiation intensity, drying air temperature, arrival air speed and drying time were considered as input parameters for the model. An ANN model with two hidden layers with 8 and 14 neurons were selected for studying the influence of transfer functions and training algorithms. The results revealed that a network with the Tansig (hyperbolic tangent sigmoid) transfer function and trainlm (Levenberg-Marquardt) back propagation algorithm made the most accurate predictions for the paddy drying system. Mean square error (MSE) was calculated and found that the random errors were within and acceptable range of ±5% with coefficient of determination (R2) of 99%.

Keywords: Rough rice, Infrared-hot air, Artificial Neural Network

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Authors: Hamza Nejib, Okba Taouali

Abstract:

This paper presents two of the most knowing kernel adaptive filtering (KAF) approaches, the kernel least mean squares and the kernel recursive least squares, in order to predict a new output of nonlinear signal processing. Both of these methods implement a nonlinear transfer function using kernel methods in a particular space named reproducing kernel Hilbert space (RKHS) where the model is a linear combination of kernel functions applied to transform the observed data from the input space to a high dimensional feature space of vectors, this idea known as the kernel trick. Then KAF is the developing filters in RKHS. We use two nonlinear signal processing problems, Mackey Glass chaotic time series prediction and nonlinear channel equalization to figure the performance of the approaches presented and finally to result which of them is the adapted one.

Keywords: KLMS, online prediction, KAF, signal processing, RKHS, Kernel methods, KRLS, KLMS.

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Authors: Liu Ning, Zhong Chongquan, Teng Hongfei

Abstract:

EPA (Ethernet for Plant Automation) resolves the nondeterministic problem of standard Ethernet and accomplishes real-time communication by means of micro-segment topology and deterministic scheduling mechanism. This paper studies the real-time performance of EPA periodic data transmission from theoretical and experimental perspective. By analyzing information transmission characteristics and EPA deterministic scheduling mechanism, 5 indicators including delivery time, time synchronization accuracy, data-sending time offset accuracy, utilization percentage of configured timeslice and non-RTE bandwidth that can be used to specify the real-time performance of EPA periodic data transmission are presented and investigated. On this basis, the test principles and test methods of the indicators are respectively studied and some formulas for real-time performance of EPA system are derived. Furthermore, an experiment platform is developed to test the indicators of EPA periodic data transmission in a micro-segment. According to the analysis and the experiment, the methods to improve the real-time performance of EPA periodic data transmission including optimizing network structure, studying self-adaptive adjustment method of timeslice and providing data-sending time offset accuracy for configuration are proposed.

Keywords: EPA system, Industrial Ethernet, Periodic data, Real-time performance

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Authors: M. Rychlik, R. Roszak, M. Morzynski, M. Nowak, H. Hausa, K. Kotecki

Abstract:

Article presents the geometry and structure reconstruction procedure of the aircraft model for flatter research (based on the I22-IRYDA aircraft). For reconstruction the Reverse Engineering techniques and advanced surface modeling CAD tools are used. Authors discuss all stages of data acquisition process, computation and analysis of measured data. For acquisition the three dimensional structured light scanner was used. In the further sections, details of reconstruction process are present. Geometry reconstruction procedure transform measured input data (points cloud) into the three dimensional parametric computer model (NURBS solid model) which is compatible with CAD systems. Parallel to the geometry of the aircraft, the internal structure (structural model) are extracted and modeled. In last chapter the evaluation of obtained models are discussed.

Keywords: computer modeling, numerical simulation, Reverse Engineering, structural model

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Authors: S. M. Ghoreishi, R. Gholami Shahrestani, S. H. Ghaziaskar

Abstract:

Subcritical water extraction was investigated as a novel and alternative technology in the food and pharmaceutical industry for the separation of Mannitol from olive leaves and its results was compared with those of Soxhlet extraction. The effects of temperature, pressure, and flow rate of water and also momentum and mass transfer dimensionless variables such as Reynolds and Peclet Numbers on extraction yield and equilibrium partition coefficient were investigated. The 30-110 bars, 60-150°C, and flow rates of 0.2-2 mL/min were the water operating conditions. The results revealed that the highest Mannitol yield was obtained at 100°C and 50 bars. However, extraction of Mannitol was not influenced by the variations of flow rate. The mathematical modeling of experimental measurements was also investigated and the model is capable of predicting the experimental measurements very well. In addition, the results indicated higher extraction yield for the subcritical water extraction in contrast to Soxhlet method.

Keywords: Extraction, Mannitol, Modeling, Olive leaves, Soxhlet extraction, Subcritical water.

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Authors: Ghassan A. Abed, Mahamod Ismail, Kasmiran Jumari

Abstract:

Long Term Evolution (LTE) is a 4G wireless broadband technology developed by the Third Generation Partnership Project (3GPP) release 8, and it's represent the competitiveness of Universal Mobile Telecommunications System (UMTS) for the next 10 years and beyond. The concepts for LTE systems have been introduced in 3GPP release 8, with objective of high-data-rate, low-latency and packet-optimized radio access technology. In this paper, performance of different TCP variants during LTE network investigated. The performance of TCP over LTE is affected mostly by the links of the wired network and total bandwidth available at the serving base station. This paper describes an NS-2 based simulation analysis of TCP-Vegas, TCP-Tahoe, TCPReno, TCP-Newreno, TCP-SACK, and TCP-FACK, with full modeling of all traffics of LTE system. The Evaluation of the network performance with all TCP variants is mainly based on throughput, average delay and lost packet. The analysis of TCP performance over LTE ensures that all TCP's have a similar throughput and the best performance return to TCP-Vegas than other variants.

Keywords: LTE; EUTRAN; 3GPPP, SAE; TCP Variants; NS-2

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Authors: M. Yosofi, S. Ezeddini, A. Ollivier, V. Lavaste, C. Mayousse

Abstract:

Additive manufacturing processes have changed significantly in a wide range of industries and their application progressed from rapid prototyping to production of end-use products. However, their environmental impact is still a rather open question. In order to support the growth of this technology in the industrial sector, environmental aspects should be considered and predictive models may help monitor and reduce the environmental footprint of the processes. This work presents predictive models based on a previously developed methodology for the environmental impact evaluation combined with a technical and economical assessment. Here we applied the methodology to the Fused Deposition Modeling process. First, we present the predictive models relative to different types of machines. Then, we present a decision-making tool designed to identify the optimum manufacturing strategy regarding technical, economic, and environmental criteria.

Keywords: Additive manufacturing, decision-makings, environmental impact, predictive models.

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Authors: Azlina Abu Bakar, Abdul Fatah Wan Sidek

Abstract:

Well-being has been given special emphasis in quality of life. It involves living a meaningful, life satisfaction, stability and happiness in life. Well-being also concerns the satisfaction of physical, psychological, social needs and demands of an individual. The purpose of this study was to validate three-factor measurement model of well-being using structural equation modeling (SEM). The conceptions of well-being measured such dimensions as physical, psychological and social well-being. This study was done based on a total sample of 650 adolescents from east-coast of peninsular Malaysia. The Well-Being Scales which was adapted from [1] was used in this study. The items were hypothesized a priori to have nonzero loadings on all dimensions in the model. The findings of the SEM demonstrated that it is a good fitting model which the proposed model fits the driving theory; (x2df = 1.268; GFI = .994; CFI = .998; TLI= .996; p = .255; RMSEA = .021). Composite reliability (CR) was .93 and average variance extracted (AVE) was 58%. The model in this study fits with the sample of data and well-being is important to bring sustainable development to the mainstream.

Keywords: Adolescence, Structural Equation Modeling, Sustainable Development, Well-Being.

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Authors: W. Afef, A. Mohamed Ammar, G. Kamel, O. Ahmed

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In the present study, a numerical approach to describe the pyrolysis of a single solid particle of wood is used to study the influence of various conditions such as particle size, heat transfer coefficient, reactor temperature and heating rate. The influence of these parameters in the change of the duration of the pyrolysis cycle was studied. Mathematical modeling was employed to simulate the heat, mass transfer, and kinetic processes inside the reactor. The evolutions of the mass loss as well as the evolution of temperature inside the thick piece are investigated numerically. The elaborated model was also employed to study the effect of the reactor temperature and the rate of heating on the change of the temperature and the local loss of the mass inside the piece of wood. The obtained results are in good agreement with the experimental data available in the literature.

Keywords: Wood, Pyrolysis, Modeling, Convective heat transfer, Kinetic.

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Authors: José R. G. Braga, Joice B. Mendes, Guilherme H. Caponetto, Alexandre C. B. Ramos

Abstract:

With major technological advances and to reduce the cost of training apprentices for real-time critical systems, it was necessary the development of Intelligent Tutoring Systems for training apprentices in these systems. These systems, in general, have interactive features so that the learning is actually more efficient, making the learner more familiar with the mechanism in question. In the home stage of learning, tests are performed to obtain the student's income, a measure on their use. The aim of this paper is to present a framework to model an Intelligent Tutoring Systems using the UML language. The various steps of the analysis are considered the diagrams required to build a general model, whose purpose is to present the different perspectives of its development.

Keywords: Computer based training, Hypermedia, Software modeling.

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Authors: А. Pashayev, C. Ardil, D. Askerov, R. Sadiqov, A. Samedov

Abstract:

In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and quasistationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine first stage nozzle blade.

Keywords: Mathematical Modeling, Gas Turbine Blade Cooling, Neural Networks, BIEM and FDM.

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Authors: Farai Nyabadza

Abstract:

The functional response of an infective is the relationship between an infected individual-s infection rate and the abundance of the number of susceptibles that one can potentially be infected. In this paper, we consider defensive attitudes for HIV prevention (primary prevention) while at the same time emphasizing on offensive attitudes that reduce infection for those infected (secondary prevention). We look at how defenses can protect an uninfected individual in the case where high risk groups such as commercial sex workers and those who deliberately go out to look for partners. We propose an infection cycle that begins with a search, then an encounter, a proposal and contact. The infection cycle illustrates the various steps an infected individual goes through to successfully infect a susceptible. For heterogeneous transmission of HIV, there will be no infection unless there is contact. The ability to avoid an encounter, detection, proposal and contact constitute defense.

Keywords: Functional response, Infection cycle, Prevention, Defences, SSS equation.

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Authors: B. Fahimnia, L.H.S. Luong, B. Motevallian, R. M. Marian, M. M. Esmaeil

Abstract:

Product Lead Time (PLT) is the period of time from receiving a customer's order to delivering the final product. PLT is an indicator of the manufacturing controllability, efficiency and performance. Due to the explosion in the rate of technological innovations and the rapid changes in the nature of manufacturing processes, manufacturing firms can bring the new products to market quicker only if they can reduce their PLT and speed up the rate at which they can design, plan, control, and manufacture. Although there is a substantial body of research on manufacturing relating to cost and quality issues, there is no much specific research conducted in relation to the formulation of PLT, despite its significance and importance. This paper analyzes and formulates PLT which can be used as a guideline for achieving the shorter PLT. Further more this paper identifies the causes of delay and factors that contributes to the increased product lead-time.

Keywords: Manufacturing Control, Manufacturing Lead Time, Manufacturing Planning, Product Design, and Product Lead Time.

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Authors: R. Simutis, V. Galvanauskas, D. Levisauskas, J. Repsyte

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This paper proposes a bioprocess optimization procedure based on Relevance Vector Regression models and evolutionary programming technique. Relevance Vector Regression scheme allows developing a compact and stable data-based process model avoiding time-consuming modeling expenses. The model building and process optimization procedure could be done in a half-automated way and repeated after every new cultivation run. The proposed technique was tested in a simulated mammalian cell cultivation process. The obtained results are promising and could be attractive for optimization of industrial bioprocesses.

Keywords: Bioprocess optimization, Evolutionary programming, Relevance Vector Regression.

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Authors: S. Niksarlioglu, F. Kulahci

Abstract:

Earthquakes are natural phenomena that occur with influence of a lot of parameters such as seismic activity, changing in the ground waters' motion, changing in the water-s temperature, etc. On the other hand, the radon gas concentrations in soil vary as nonlinear generally with earthquakes. Continuous measurement of the soil radon gas is very important for determination of characteristic of the seismic activity. The radon gas changes as continuous with strain occurring within the Earth-s surface during an earthquake and effects from the physical and the chemical processes such as soil structure, soil permeability, soil temperature, the barometric pressure, etc. Therefore, at the modeling researches are notsufficient to knowthe concentration ofradon gas. In this research, we determined relationships between radon emissions based on the environmental parameters and earthquakes occurring along the East Anatolian Fault Zone (EAFZ), Turkiye and predicted magnitudes of some earthquakes with the artificial neural network (ANN) model.

Keywords: Earthquake, Modeling, Prediction, Radon.

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Authors: M. Schulze, P. Crespo Del Granado

Abstract:

This paper considers the influence of promotion instruments for renewable energy sources (RES) on a multi-energy modeling framework. In Europe, so called Feed-in Tariffs are successfully used as incentive structures to increase the amount of energy produced by RES. Because of the stochastic nature of large scale integration of distributed generation, many problems have occurred regarding the quality and stability of supply. Hence, a macroscopic model was developed in order to optimize the power supply of the local energy infrastructure, which includes electricity, natural gas, fuel oil and district heating as energy carriers. Unique features of the model are the integration of RES and the adoption of Feed-in Tariffs into one optimization stage. Sensitivity studies are carried out to examine the system behavior under changing profits for the feed-in of RES. With a setup of three energy exchanging regions and a multi-period optimization, the impact of costs and profits are determined.

Keywords: Distributed generation, optimization methods, power system modeling, renewable energy.

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Authors: Lijiang Xiang, Shouming Zhong, Yucai Ding

Abstract:

The problems of globally exponential stability and dissipativity analysis for static neural networks (NNs) with time delay is investigated in this paper. Some delay-dependent stability criteria are established for static NNs with time delay using the delay partitioning technique. In terms of this criteria, the delay-dependent sufficient condition is given to guarantee the dissipativity of static NNs with time delay. All the given results in this paper are not only dependent upon the time delay but also upon the number of delay partitions. Two numerical examples are used to show the effectiveness of the proposed methods.

Keywords: Globally exponential stability, Dissipativity, Static neural networks, Time delay.

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Authors: Ju H. Park, S.M. Lee

Abstract:

In this paper, we propose a robust controller design method for discrete-time systems with sector-bounded nonlinearities and time-varying delay. Based on the Lyapunov theory, delaydependent stabilization criteria are obtained in terms of linear matrix inequalities (LMIs) by constructing the new Lyapunov-Krasovskii functional and using some inequalities. A robust state feedback controller is designed by LMI framework and a reciprocally convex combination technique. The effectiveness of the proposed method is verified throughout a numerical example.

Keywords: Lur'e systems, Time-delay, Stabilization, LMIs.

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Authors: Zarita Zainuddin, Ong Pauline, C. Ardil

Abstract:

Diabetes Mellitus is a chronic metabolic disorder, where the improper management of the blood glucose level in the diabetic patients will lead to the risk of heart attack, kidney disease and renal failure. This paper attempts to enhance the diagnostic accuracy of the advancing blood glucose levels of the diabetic patients, by combining principal component analysis and wavelet neural network. The proposed system makes separate blood glucose prediction in the morning, afternoon, evening and night intervals, using dataset from one patient covering a period of 77 days. Comparisons of the diagnostic accuracy with other neural network models, which use the same dataset are made. The comparison results showed overall improved accuracy, which indicates the effectiveness of this proposed system.

Keywords: Diabetes Mellitus, principal component analysis, time-series, wavelet neural network.

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Authors: Paola Gattinoni, Vincenzo Francani

Abstract:

The paper deals with the analysis of triggering conditions and evolution processes of piping phenomena, in relation to both mechanical and hydraulic aspects. In particular, the aim of the study is to predict slope instabilities triggered by piping, analysing the conditions necessary for a flow failure to occur. Really, the mechanical effect involved in the loads redistribution around the pipe is coupled to the drainage process arising from higher permeability of the pipe. If after the pipe formation, the drainage goes prevented for pipe clogging, the porewater pressure increase can lead to the failure or even the liquefaction, with a subsequent flow slide. To simulate the piping evolution and to verify relevant stability conditions, a iterative coupled modelling approach has been pointed out. As example, the proposed tool has been applied to the Stava Valley disaster (July, 1985), demonstrating that piping might be one of triggering phenomena of the tailings dams collapse.

Keywords: Flow failure, liquefaction, modeling, piping, porewater pressure.

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Authors: Marko A. Rodriguez

Abstract:

There exists an injective, information-preserving function that maps a semantic network (i.e a directed labeled network) to a directed network (i.e. a directed unlabeled network). The edge label in the semantic network is represented as a topological feature of the directed network. Also, there exists an injective function that maps a directed network to an undirected network (i.e. an undirected unlabeled network). The edge directionality in the directed network is represented as a topological feature of the undirected network. Through function composition, there exists an injective function that maps a semantic network to an undirected network. Thus, aside from space constraints, the semantic network construct does not have any modeling functionality that is not possible with either a directed or undirected network representation. Two proofs of this idea will be presented. The first is a proof of the aforementioned function composition concept. The second is a simpler proof involving an undirected binary encoding of a semantic network.

Keywords: general-modeling, multi-relational networks, semantic networks

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Authors: Monica Dudian , Raluca Andreea Popa

Abstract:

This article analyses the relationship between sovereign credit risk rating and gross domestic product for Central and Eastern European Countries for the period 1996 – 2010. In order to study the metioned relationship, we have used a numerical transformation of the risk qualification, thus: we marked 0 the lowest risk; then, we went on ascending, with a pace of 5, up to the score of 355 corresponding to the maximum risk. The used method of analysis is that of econometric modelling with EViews 7.0. programme. This software allows the analysis of data into a pannel type system, involving a mix of periods of time and series of data for different entities. The main conclusion of the work is the one confirming the negative relationship between the sovereign credit risk and the gross domestic product for the Central European and Eastern countries during the reviewed period.

Keywords: credit rating agencies, economic growth, gross domestic product, sovereign credit risk rating.

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Authors: Makhlouf Mourad, Medkour Mihoub, Bouchher Omar, Messabih Sidi Mohamed, Benrachedi Khaled

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This work is the modeling and simulation of fluid flow (liquid) through porous media. This type of flow occurs in many situations of interest in applied sciences and engineering, fluid (oil) consists of several individual substances in pure, single-phase flow is incompressible and isothermal. The porous medium is isotropic, homogeneous optionally, with the rectangular format and the flow is two-dimensional. Modeling of hydrodynamic phenomena incorporates Darcy's law and the equation of mass conservation. Correlations are used to model the density and viscosity of the fluid. A finite volume code is used in the discretization of differential equations. The nonlinearity is treated by Newton's method with relaxation coefficient. The results of the simulation of the pressure and the mobility of liquid flowing through porous media are presented, analyzed, and illustrated.

Keywords: Darcy equation, middle porous, continuity equation, Peng Robinson equation, mobility.

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Authors: S. A. Naeini, A. Khalili

Abstract:

Nowadays, tunnels with different applications are developed, and most of them are related to subway tunnels. The excavation of shallow tunnels that pass under municipal utilities is very important, and the surface settlement control is an important factor in the design. The study sought to analyze the settlement and also to find an appropriate model in order to predict the behavior of the tunnel in Tehran subway line-3. The displacement in these sections is also determined by using numerical analyses and numerical modeling. In addition, the Adaptive Neuro-Fuzzy Inference System (ANFIS) method is utilized by Hybrid training algorithm. The database pertinent to the optimum network was obtained from 46 subway tunnels in Iran and Turkey which have been constructed by the new Austrian tunneling method (NATM) with similar parameters based on type of their soil. The surface settlement was measured, and the acquired results were compared to the predicted values. The results disclosed that computing intelligence is a good substitute for numerical modeling.

Keywords: Settlement, subway line, FLAC3D, ANFIS method.

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Authors: Jihad S. Daba (Jean-Pierre Dubois), Philip Jreije

Abstract:

Speckled images arise when coherent microwave, optical, and acoustic imaging techniques are used to image an object, surface or scene. Examples of coherent imaging systems include synthetic aperture radar, laser imaging systems, imaging sonar systems, and medical ultrasound systems. Speckle noise is a form of object or target induced noise that results when the surface of the object is Rayleigh rough compared to the wavelength of the illuminating radiation. Detection and estimation in images corrupted by speckle noise is complicated by the nature of the noise and is not as straightforward as detection and estimation in additive noise. In this work, we derive stochastic models for speckle noise, with an emphasis on speckle as it arises in medical ultrasound images. The motivation for this work is the problem of segmentation and tissue classification using ultrasound imaging. Modeling of speckle in this context involves partially developed speckle model where an underlying Poisson point process modulates a Gram-Charlier series of Laguerre weighted exponential functions, resulting in a doubly stochastic filtered Poisson point process. The statistical distribution of partially developed speckle is derived in a closed canonical form. It is observed that as the mean number of scatterers in a resolution cell is increased, the probability density function approaches an exponential distribution. This is consistent with fully developed speckle noise as demonstrated by the Central Limit theorem.

Keywords: Doubly stochastic filtered process, Poisson point process, segmentation, speckle, ultrasound

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Authors: Emin Özyılmaz

Abstract:

In this work, position vector of a time-like dual curve according to standard frame of D31 is investigated. First, it is proven that position vector of a time-like dual curve satisfies a dual vector differential equation of fourth order. The general solution of this dual vector differential equation has not yet been found. Due to this, in terms of special solutions, position vectors of some special time-like dual curves with respect to standard frame of D31 are presented.

Keywords: Classical Differential Geometry, Dual Numbers, DualFrenet Equations, Time-like Dual Curve, Position Vector, DualLorentzian Space.

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Authors: Kwok Tak Kit

Abstract:

With the growing trend of adoption of advanced technologies like, building information modeling, artificial intelligence, wireless network, the collaboration and integration of these technologies into digital twin become more prominent in architecture, engineering and construction (AEC) industry in view of the nature and scale of AEC industry which efficiently adopted the digital twin. Digital twin is provided to be effective for AEC professions for design and project management. The digital concept is continuously developing and it is vital for AEC professionals and other stakeholders to understand the digital twin concept and the adoption of various advanced building technologies related to the AEC industry. This paper is to review the application of digital twins application in project management in AEC industry and highlight the challenge of AEC partitioners faced by the revolution of technologies including digital twins and building information modelling (BIM) for further research and future study.

Keywords: Digital Twin, AEC, building information modeling, project management, internet of things.

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Authors: Neila Mezghani, Philippe Phan, Hubert Labelle, Carl Eric Aubin, Jacques de Guise

Abstract:

The identification and classification of the spine deformity play an important role when considering surgical planning for adolescent patients with idiopathic scoliosis. The subject of this article is the Lenke classification of scoliotic spines using Cobb angle measurements. The purpose is two-fold: (1) design a rulebased diagram to assist clinicians in the classification process and (2) investigate a computer classifier which improves the classification time and accuracy. The rule-based diagram efficiency was evaluated in a series of scoliotic classifications by 10 clinicians. The computer classifier was tested on a radiographic measurement database of 603 patients. Classification accuracy was 93% using the rule-based diagram and 99% for the computer classifier. Both the computer classifier and the rule based diagram can efficiently assist clinicians in their Lenke classification of spine scoliosis.

Keywords: Scoliosis, Lenke model, decision-rules, computer aided classifier.

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Authors: Sarra Roubi, Mohammed Erramdani, Samir Mbarki

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This paper presents an approach for the model-driven generating of Rich Internet Application (RIA) focusing on the graphical aspect. We used well known Model-Driven Engineering (MDE) frameworks and technologies, such as Eclipse Modeling Framework (EMF), Graphical Modeling Framework (GMF), Query View Transformation (QVTo) and Acceleo to enable the design and the code automatic generation of the RIA. During the development of the approach, we focused on the graphical aspect of the application in terms of interfaces while opting for the Model View Presenter pattern that is designed for graphics interfaces. The paper describes the process followed to define the approach, the supporting tool and presents the results from a case study.

Keywords: Code generation, Design Pattern, metamodel, Model Driven Engineering, MVP, Rich Internet Application, transformation, User Interface.

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Authors: S. Sfarni, E. Bellenger, J. Fortin, M. Guessasma

Abstract:

The use of the mechanical simulation (in particular the finite element analysis) requires the management of assumptions in order to analyse a real complex system. In finite element analysis (FEA), two modeling steps require assumptions to be able to carry out the computations and to obtain some results: the building of the physical model and the building of the simulation model. The simplification assumptions made on the analysed system in these two steps can generate two kinds of errors: the physical modeling errors (mathematical model, domain simplifications, materials properties, boundary conditions and loads) and the mesh discretization errors. This paper proposes a mesh adaptive method based on the use of an h-adaptive scheme in combination with an error estimator in order to choose the mesh of the simulation model. This method allows us to choose the mesh of the simulation model in order to control the cost and the quality of the finite element analysis.

Keywords: Finite element, discretization errors, adaptivity.

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