Search results for: variable separation method

Authors: Javid Iqbal, Zhu Shifan

Abstract:

The development in the construction of unconventional ships and the implementation of lightweight materials have shown a large impulse towards finite element (FE) method, making it a general tool for ship design. This paper briefly presents the modeling and analysis techniques of ship structures using FE method for complex boundary conditions which are difficult to analyze by existing Ship Classification Societies rules. During operation, all ships experience complex loading conditions. These loads are general categories into thermal loads, linear static, dynamic and non-linear loads. General strength of the ship structure is analyzed using static FE analysis. FE method is also suitable to consider the local loads generated by ballast tanks and cargo in addition to hydrostatic and hydrodynamic loads. Vibration analysis of a ship structure and its components can be performed using FE method which helps in obtaining the dynamic stability of the ship. FE method has developed better techniques for calculation of natural frequencies and different mode shapes of ship structure to avoid resonance both globally and locally. There is a lot of development towards the ideal design in ship industry over the past few years for solving complex engineering problems by employing the data stored in the FE model. This paper provides an overview of ship modeling methodology for FE analysis and its general application. Historical background, the basic concept of FE, advantages, and disadvantages of FE analysis are also reported along with examples related to hull strength and structural components.

Keywords: Dynamic analysis, finite element methods, ship structure, vibration analysis.

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Authors: Siliang Wang, Minghui Wang

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Many exist studies always use Markov decision processes (MDPs) in modeling optimal route choice in stochastic, time-varying networks. However, taking many variable traffic data and transforming them into optimal route decision is a computational challenge by employing MDPs in real transportation networks. In this paper we model finite horizon MDPs using directed hypergraphs. It is shown that the problem of route choice in stochastic, time-varying networks can be formulated as a minimum cost hyperpath problem, and it also can be solved in linear time. We finally demonstrate the significant computational advantages of the introduced methods.

Keywords: Markov decision processes (MDPs), stochastictime-varying networks, hypergraphs, route choice.

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Authors: Osea Zebua, Norikazu Ikoma, Hiroshi Maeda

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Estimation of voltage stability based on optimal filtering method is presented. PV curve is used as a tool for voltage stability analysis. Dynamic voltage stability estimation is done by using particle filter method. Optimum value (nose point) of PV curve can be estimated by estimating parameter of PV curve equation optimal value represents critical voltage and condition at specified point of measurement. Voltage stability is then estimated by analyzing loading margin condition c stimating equation. This maximum loading ecified dynamically.

Keywords: normalized PV curve, optimal filtering method particle filter, voltage stability.

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Authors: N. Aravantinos-Zafiris, M. M. Sigalas

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In this work we numerically examine structures which could confine light in nanometer areas. A system consisting of two silicon disks with in plane separation of a few tens of nanometers has been studied first. The normalized unitless effective mode volume, Veff, has been calculated for the two lowest whispering gallery mode resonances. The effective mode volume is reduced significantly as the gap between the disks decreases. In addition, the effect of the substrate is also studied. In that case, Veff of approximately the same value as the non-substrate case for a similar two disk system can be obtained by using disks almost twice as thick. We also numerically examine a structure consisting of a circular slot waveguide which is formed into a silicon disk resonator. We show that the proposed structure could have high Q resonances thus raising the belief that it is a very promising candidate for optical interconnects applications. The study includes several numerical calculations for all the geometric parameters of the structure. It also includes numerical simulations of the coupling between a waveguide and the proposed disk resonator leading to a very promising conclusion about its applicability.

Keywords: Disk resonators, field enhancement, optical interconnect, slot waveguides.

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Authors: Wajdi Ghezaiel, Amel Ben Slimane Rahmouni, Ezzedine Ben Braiek

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Many applications of speech communication and speaker identification suffer from the problem of co-channel speech. This paper deals with a multi-resolution dyadic wavelet transform method for usable segments of co-channel speech detection that could be processed by a speaker identification system. Evaluation of this method is performed on TIMIT database referring to the Target to Interferer Ratio measure. Co-channel speech is constructed by mixing all possible gender speakers. Results do not show much difference for different mixtures. For the overall mixtures 95.76% of usable speech is correctly detected with false alarms of 29.65%.

Keywords: Co-channel speech, usable speech, multi-resolutionanalysis, speaker identification

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Authors: Emad Alenany, M. Adel El-Baz

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In this paper, the flow of different classes of patients into a hospital is modelled and analyzed by using the queueing network analyzer (QNA) algorithm and discrete event simulation. Input data for QNA are the rate and variability parameters of the arrival and service times in addition to the number of servers in each facility. Patient flows mostly match real flow for a hospital in Egypt. Based on the analysis of the waiting times, two approaches are suggested for improving performance: Separating patients into service groups, and adopting different service policies for sequencing patients through hospital units. The separation of a specific group of patients, with higher performance target, to be served separately from the rest of patients requiring lower performance target, requires the same capacity while improves performance for the selected group of patients with higher target. Besides, it is shown that adopting the shortest processing time and shortest remaining processing time service policies among other tested policies would results in, respectively, 11.47% and 13.75% reduction in average waiting time relative to first come first served policy.

Keywords: Queueing network, discrete-event simulation, health applications, SPT.

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Authors: Ahmed Badawi

Abstract:

This paper proposes a method for speckle reduction in medical ultrasound imaging while preserving the edges with the added advantages of adaptive noise filtering and speed. A nonlinear image diffusion method that incorporates local image parameter, namely, scatterer density in addition to gradient, to weight the nonlinear diffusion process, is proposed. The method was tested for the isotropic case with a contrast detail phantom and varieties of clinical ultrasound images, and then compared to linear and some other diffusion enhancement methods. Different diffusion parameters were tested and tuned to best reduce speckle noise and preserve edges. The method showed superior performance measured both quantitatively and qualitatively when incorporating scatterer density into the diffusivity function. The proposed filter can be used as a preprocessing step for ultrasound image enhancement before applying automatic segmentation, automatic volumetric calculations, or 3D ultrasound volume rendering.

Keywords: Ultrasound imaging, Nonlinear isotropic diffusion, Speckle noise, Scattering.

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Authors: Marina Velikova, Hennie Daniels, Ad Feelders

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In many applications, it is a priori known that the target function should satisfy certain constraints imposed by, for example, economic theory or a human-decision maker. Here we consider partially monotone problems, where the target variable depends monotonically on some of the predictor variables but not all. We propose an approach to build partially monotone models based on the convolution of monotone neural networks and kernel functions. The results from simulations and a real case study on house pricing show that our approach has significantly better performance than partially monotone linear models. Furthermore, the incorporation of partial monotonicity constraints not only leads to models that are in accordance with the decision maker's expertise, but also reduces considerably the model variance in comparison to standard neural networks with weight decay.

Keywords: Mixture models, monotone neural networks, partially monotone models, partially monotone problems.

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Authors: Michal Cerny

Abstract:

We consider linear regression models where both input data (the values of independent variables) and output data (the observations of the dependent variable) are interval-censored. We introduce a possibilistic generalization of the least squares estimator, so called OLS-set for the interval model. This set captures the impact of the loss of information on the OLS estimator caused by interval censoring and provides a tool for quantification of this effect. We study complexity-theoretic properties of the OLS-set. We also deal with restricted versions of the general interval linear regression model, in particular the crisp input – interval output model. We give an argument that natural descriptions of the OLS-set in the crisp input – interval output cannot be computed in polynomial time. Then we derive easily computable approximations for the OLS-set which can be used instead of the exact description. We illustrate the approach by an example.

Keywords: Linear regression, interval-censored data, computational complexity.

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Authors: M. Elkhoury

Abstract:

A recently developed one-equation turbulence model has been successfully applied to simulate turbulent flows with various complexities. The model, which is based on the transformation of the k-ε closure, is wall-distance free and equipped with lagging destruction/dissipation terms. Test cases included shockboundary- layer interaction flows over the NACA 0012 airfoil, an axisymmetric bump, and the ONERA M6 wing. The capability of the model to operate in a Scale Resolved Simulation (SRS) mode is demonstrated through the simulation of a massive flow separation over a circular cylinder at Re= 1.2 x106. An assessment of the results against available experiments Menter (k-ε)1Eq and the Spalart- Allmaras model that belongs to the single equation closure family is made.

Keywords: Turbulence modeling, complex flow simulation, scale adaptive simulation, one-equation turbulence model.

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Authors: N. Ebrahimi, J. Rashidinia

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In this paper, numerical solution of system of Fredholm and Volterra integral equations by means of the Spline collocation method is considered. This approximation reduces the system of integral equations to an explicit system of algebraic equations. The solution is collocated by cubic B-spline and the integrand is approximated by the Newton-Cotes formula. The error analysis of proposed numerical method is studied theoretically. The results are compared with the results obtained by other methods to illustrate the accuracy and the implementation of our method.

Keywords: Convergence analysis, Cubic B-spline, Newton- Cotes formula, System of Fredholm and Volterra integral equations.

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Authors: Yan Liu, Weidong Shen, Dekang Mao, Baolin Tian

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The MFCAV Riemann solver is practically used in many Lagrangian or ALE methods due to its merit of sharp shock profiles and rarefaction corners, though very often with numerical oscillations. By viewing it as a modification of the WWAM Riemann solver, we apply the MFCAV Riemann solver to the Lagrangian method recently developed by Maire. P. H et. al.. The numerical experiments show that the application is successful in that the shock profiles and rarefaction corners are sharpened compared with results obtained using other Riemann solvers. Though there are still numerical oscillations, they are within the range of the MFCAV applied in onther Lagrangian methods.

Keywords: Cell-centered Lagrangian method, approximated Riemann solver, HLLC Riemann solver

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Authors: Wookuen Shin, Gregory R. Miller, Pedro Arduino, Peter Mackenzie-Helnwein

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This paper presents strategies for dynamically creating, managing and removing mesh cells during computations in the context of the Material Point Method (MPM). The dynamic meshing approach has been developed to help address problems involving motion of a finite size body in unbounded domains in which the extent of material travel and deformation is unknown a priori, such as in the case of landslides and debris flows. The key idea is to efficiently instantiate and search only cells that contain material points, thereby avoiding unneeded storage and computation. Mechanisms for doing this efficiently are presented, and example problems are used to demonstrate the effectiveness of dynamic mesh management relative to alternative approaches.

Keywords: Numerical Analysis, Material Point Method, Large Deformations, Moving Boundaries.

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Authors: Atheel Hassan Alwash, Ahmad Zuhairi Abdullah, Norli Ismail

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Characteristics and sonocatalytic activity of zeolite Y catalysts loaded with TiO2 using impregnation and ion exchange methods for the degradation of amaranth dye were investigated. The Ion-exchange method was used to encapsulate the TiO2 into the internal pores of the zeolite while the incorporation of TiO2 mostly on the external surface of zeolite was carried out using the impregnation method. Different characterization techniques were used to elucidate the physicochemical properties of the produced catalysts. The framework of zeolite Y remained virtually unchanged after the encapsulation of TiO2 while the crystallinity of zeolite decreased significantly after the incorporation of 15 wt% of TiO2. The sonocatalytic activity was enhanced by TiO2 incorporation with maximum degradation efficiencies of 50% and 68% for the encapsulated titanium and titanium loaded onto the zeolite, respectively after 120min of reaction. Catalysts characteristics and sonocatalytic behaviors were significantly affected by the preparation method and the location of TiO2 introduced with zeolite structure. Behaviors in the sonocatalytic process were successfully correlated with the characteristics of the catalysts used.

Keywords: Sonocatalytic degradation, TiO2 loaded, ionexchange, impregnation, amaranth dye, process behavior.

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Authors: Moghiman Mohammad, Amiri Maryam, Amiri Amirhosein

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The present paper develops and validates a numerical procedure for the calculation of turbulent combustive flow in converging and diverging ducts and throuh simulation of the heat transfer processes, the amount of production and spread of Nox pollutant has been measured. A marching integration solution procedure employing the TDMA is used to solve the discretized equations. The turbulence model is the Prandtl Mixing Length method. Modeling the combustion process is done by the use of Arrhenius and Eddy Dissipation method. Thermal mechanism has been utilized for modeling the process of forming the nitrogen oxides. Finite difference method and Genmix numerical code are used for numerical solution of equations. Our results indicate the important influence of the limiting diverging angle of diffuser on the coefficient of recovering of pressure. Moreover, due to the intense dependence of Nox pollutant to the maximum temperature in the domain with this feature, the Nox pollutant amount is also in maximum level.

Keywords: Converging and Diverging Duct, Combustion, Diffuser, Diverging Angle, Nox

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Authors: Zainur Rahman

Abstract:

Meaningful work is the topic that will be discussed in this article, especially in changing period. It has an important role because by reaching meaningful work, it will drive to be positive in the workplace. Therefore, task performance will be increased and cynicism about organizational change (CAOC) will be reduced. Moreover, it is influenced by situational factor, which is transformational leadership. In this conceptual paper, the author discusses how the construct of meaningful work influenced by transformational leadership that will have impact on the follower’ work outcomes in the organizational change. It is proposed that the construct of meaningful work are susceptible with situational variable. Transformational leaders who are respectful on the process of humanizing the followers affect task performance and reduce CAOC in organizational change.

Keywords: Meaningful work, organizational change, task performance, and work outcomes.

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Authors: Zhanli Zhang, Wei Chen, Xin Jiang, Lili Ma, Shaoting Tang, Zhiming Zheng

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A new class of percolation model in complex networks, in which nodes are characterized by hidden variables reflecting the properties of nodes and the occupied probability of each link is determined by the hidden variables of the end nodes, is studied in this paper. By the mean field theory, the analytical expressions for the phase of percolation transition is deduced. It is determined by the distribution of the hidden variables for the nodes and the occupied probability between pairs of them. Moreover, the analytical expressions obtained are checked by means of numerical simulations on a particular model. Besides, the general model can be applied to describe and control practical diffusion models, such as disease diffusion model, scientists cooperation networks, and so on.

Keywords: complex networks, percolation transition, hidden variable, occupied probability.

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Authors: Yutaka Kisakibaru, AsepBayu Dani Nandiyanto, Ratna Balgis, Takashi Ogi, Kikuo Okuyama

Abstract:

spherical porous carbon particles with controllable porosity with a mean size of 2.5m have been prepared using a spray drying method with organic particle colloidal template. As a precursor, a mixing solution of carbon nanopowder and polystyrene (PS) particles as a template was used. The result showed that the particles with a good porous structure could be obtained. The pore size and shape (spherical) were identical to the initial template, giving a potential way for further developments. The control of particle porosity was also possible and reported in this paper, in which this control could be achieved by means of PS concentration.

Keywords: Porous structure particle; Carbon nanoparticles; Catalyst; Spray-drying method.

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Authors: Aziah Khamis, H. Shareef

Abstract:

The purpose of planned islanding is to construct a power island during system disturbances which are commonly formed for maintenance purpose. However, in most of the cases island mode operation is not allowed. Therefore distributed generators (DGs) must sense the unplanned disconnection from the main grid. Passive technique is the most commonly used method for this purpose. However, it needs improvement in order to identify the islanding condition. In this paper an effective method for identification of islanding condition based on phase space and neural network techniques has been developed. The captured voltage waveforms at the coupling points of DGs are processed to extract the required features. For this purposed a method known as the phase space techniques is used. Based on extracted features, two neural network configuration namely radial basis function and probabilistic neural networks are trained to recognize the waveform class. According to the test result, the investigated technique can provide satisfactory identification of the islanding condition in the distribution system.

Keywords: Classification, Islanding detection, Neural network, Phase space.

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Authors: N. Dizadji, P. Entezar, A. Shabani

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This study presents energy saving in general-purpose pumps widely used in industrial applications. Such pumps are normally driven by a constant-speed electrical motor which in most applications must support varying load conditions. This is equivalent to saying the loading conditions mismatch the designed optimal energy consumption requirements of the intended application thus resulting in substantial energy losses. In the held experiments it was indicated that combination of mechanical and electrical speed drives can contribute to lower energy consumption in the pump without negatively distorting the required performance indices of a typical centrifugal pump at substantially lower energy consumption. The registered energy savings were recorded to be within the 15-40% margin. It was also indicated that although VSDs are installed at a cost, the financial burden is balanced against the earnings resulting from the associated energy savings.

Keywords: Industrial motors, Pumps, Energy consumption, Energy savings, Variable speed drive.

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Authors: Ek Ngoy, A F Mulaba-Bafubiandi

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Cobalt was acid nitric leached from a mixed cobaltcopper oxide with variable acid concentration. Resulting experimental data were used to analyze effects of increase in acid concentration, based on a shrinking core model of the process. The mathematical simulation demonstrated that the time rate of the dissolution mechanism is an increasing function of acid concentration. It was also shown that the magnitude of the acid concentration effect is time dependent and the increase in acid concentration is more effective at earlier stage of the dissolution than at later stage. The remaining process parameters are comprehensively affected by acid concentration and their interaction is synergetic.

Keywords: Acid effect, Cobalt, Cobalt-copper oxide, Leaching, Simulation

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Authors: Ryu Watanabe, Yutaka Miyake

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Reducing the risk of information leaks is one of the most important functions of identity management systems. To achieve this purpose, Dey et al. have already proposed an account management method for a federated login system using a blind signature scheme. In order to ensure account anonymity for the authentication provider, referred to as an IDP (identity provider), a blind signature scheme is utilized to generate an authentication token on an authentication service and the token is sent to an IDP. However, there is a problem with the proposed system. Malicious users can establish multiple accounts on an IDP by requesting such accounts. As a measure to solve this problem, in this paper, the authors propose an account checking method that is performed before account generation.

Keywords: identity management, blind signature, privacy protection

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Authors: Khaddouja Boujenfa, Nadia Essoussi, Mohamed Limam

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Multiple sequence alignment is a fundamental part in many bioinformatics applications such as phylogenetic analysis. Many alignment methods have been proposed. Each method gives a different result for the same data set, and consequently generates a different phylogenetic tree. Hence, the chosen alignment method affects the resulting tree. However in the literature, there is no evaluation of multiple alignment methods based on the comparison of their phylogenetic trees. This work evaluates the following eight aligners: ClustalX, T-Coffee, SAGA, MUSCLE, MAFFT, DIALIGN, ProbCons and Align-m, based on their phylogenetic trees (test trees) produced on a given data set. The Neighbor-Joining method is used to estimate trees. Three criteria, namely, the dNNI, the dRF and the Id_Tree are established to test the ability of different alignment methods to produce closer test tree compared to the reference one (true tree). Results show that the method which produces the most accurate alignment gives the nearest test tree to the reference tree. MUSCLE outperforms all aligners with respect to the three criteria and for all datasets, performing particularly better when sequence identities are within 10-20%. It is followed by T-Coffee at lower sequence identity (<10%), Align-m at 20-30% identity, and ClustalX and ProbCons at 30-50% identity. Also, it is noticed that when sequence identities are higher (>30%), trees scores of all methods become similar.

Keywords: Multiple alignment methods, phylogenetic trees, Neighbor-Joining method, Robinson-Foulds distance.

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Authors: C. Ardil

Abstract:

The decision to select an unmanned combat aircraft is complicated since several options and conflicting criteria must be considered at simultaneously. When making multiple criteria decision, it is important to consider the selected evaluation criteria, including priceability, payloadability, stealthability, speedability , and survivability. The fundamental goal of the study is to select the best unmanned combat aircraft by taking these evaluation criteria into account. The optimal aircraft was chosen using the fuzzy proximity measure method, which enables decision-makers to designate preferences as standard fuzzy set numbers during the multiple criteria decision-making process. To assess the applicability of the proposed approach, a numerical example is provided. Finally, by comparing determined unmanned combat aircraft, the proposed method produced a successful application, and the best aircraft was selected.

Keywords: standard fuzzy sets (SFS), unmanned combat aircraft selection, multiple criteria decision making (MCDM), multiple criteria group decision making (MCGDM), proximity measure method (PMM)

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Authors: Desmond Adair, Kairat Ismailov, Martin Jaeger

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Modelling of Timoshenko beams on elastic foundations has been widely used in the analysis of buildings, geotechnical problems, and, railway and aerospace structures. For the elastic foundation, the most widely used models are one-parameter mechanical models or two-parameter models to include continuity and cohesion of typical foundations, with the two-parameter usually considered the better of the two. Knowledge of free vibration characteristics of beams on an elastic foundation is considered necessary for optimal design solutions in many engineering applications, and in this work, the efficient and accurate variational iteration method is developed and used to calculate natural frequencies of a Timoshenko beam on a two-parameter foundation. The variational iteration method is a technique capable of dealing with some linear and non-linear problems in an easy and efficient way. The calculations are compared with those using a finite-element method and other analytical solutions, and it is shown that the results are accurate and are obtained efficiently. It is found that the effect of the presence of the two-parameter foundation is to increase the beam’s natural frequencies and this is thought to be because of the shear-layer stiffness, which has an effect on the elastic stiffness. By setting the two-parameter model’s stiffness parameter to zero, it is possible to obtain a one-parameter foundation model, and so, comparison between the two foundation models is also made.

Keywords: Timoshenko beam, variational iteration method, two-parameter elastic foundation model.

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Authors: Mohammed Farag, Mina Attari, S. Andrew Gadsden, Saeid R. Habibi

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Battery state of charge (SOC) estimation is an important parameter as it measures the total amount of electrical energy stored at a current time. The SOC percentage acts as a fuel gauge if it is compared with a conventional vehicle. Estimating the SOC is, therefore, essential for monitoring the amount of useful life remaining in the battery system. This paper looks at the implementation of three nonlinear estimation strategies for Li-Ion battery SOC estimation. One of the most common behavioral battery models is the one state hysteresis (OSH) model. The extended Kalman filter (EKF), the smooth variable structure filter (SVSF), and the time-varying smoothing boundary layer SVSF are applied on this model, and the results are compared.

Keywords: State of charge estimation, battery modeling, one-state hysteresis, filtering and estimation.

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Authors: Nai-Chieh Wei, I-Ming Chao, Chin-Jung Liuand, Hong Long Chen

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This paper combines the branch-and-bound method and the petri net to solve the two-sided assembly line balancing problem, thus facilitating effective branching and pruning of tasks. By integrating features of the petri net, such as reachability graph and incidence matrix, the propose method can support the branch-and-bound to effectively reduce poor branches with systematic graphs. Test results suggest that using petri net in the branching process can effectively guide the system trigger process, and thus, lead to consistent results.

 

Keywords: Branch-and-Bound Method, Petri Net, Two-Sided Assembly Line Balancing Problem.

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Authors: Nadine Ali Hassan, Ngoc Son Nguyen, Didier Marot, Fateh Bendahmane

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This paper aims at presenting a study of the effect of scalping methods on the mechanical properties of coarse soils by resorting to numerical simulations based on the discrete element method (DEM) and experimental triaxial tests. Two reconstitution methods are used, designated as scalping method and substitution method. Triaxial compression tests are first simulated on a granular materials with a grap graded particle size distribution by using the DEM. We study the effect of these reconstitution methods on the stress-strain behavior of coarse soils with different fine contents and with different ways to control the densities of the scalped and substituted materials. Experimental triaxial tests are performed on original mixtures of sands and gravels with different fine contents and on their corresponding scalped and substituted samples. Numerical results are qualitatively compared to experimental ones. Agreements and discrepancies between these results are also discussed.

Keywords: Coarse soils, scalping, substitution, discrete element method, triaxial test.

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Authors: Süha Yılmaz, Melih Turgut

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In this paper, a method to calculate Frenet Apparatus of the curves in five dimensional Euclidean space is presented.

Keywords: Classical Differential Geometry, Euclidean-5 space, Frenet Apparatus.

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Authors: Chang-Uk Kwak, Sun-Joong Kim, Seong-Bae Park, Sang-Jo Lee

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This paper proposes a method of learning topics for broadcasting contents. There are two kinds of texts related to broadcasting contents. One is a broadcasting script, which is a series of texts including directions and dialogues. The other is blogposts, which possesses relatively abstracted contents, stories, and diverse information of broadcasting contents. Although two texts range over similar broadcasting contents, words in blogposts and broadcasting script are different. When unseen words appear, it needs a method to reflect to existing topic. In this paper, we introduce a semantic vocabulary expansion method to reflect unseen words. We expand topics of the broadcasting script by incorporating the words in blogposts. Each word in blogposts is added to the most semantically correlated topics. We use word2vec to get the semantic correlation between words in blogposts and topics of scripts. The vocabularies of topics are updated and then posterior inference is performed to rearrange the topics. In experiments, we verified that the proposed method can discover more salient topics for broadcasting contents.

Keywords: Broadcasting script analysis, topic expansion, semantic correlation analysis, word2vec.

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