Search results for: linear predictive coding (LPC)

Authors: N. Fusun Oyman Serteller

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In this paper, the techniques to solve time dependent electromagnetic wave propagation equations based on the Finite Difference Method (FDM) are proposed by comparing the results with Finite Element Method (FEM) in 2D while discussing some special simulation examples.  Here, 2D dynamical wave equations for lossy media, even with a constant source, are discussed for establishing symbolic manipulation of wave propagation problems. The main objective of this contribution is to introduce a comparative study of two suitable numerical methods and to show that both methods can be applied effectively and efficiently to all types of wave propagation problems, both linear and nonlinear cases, by using symbolic computation. However, the results show that the FDM is more appropriate for solving the nonlinear cases in the symbolic solution. Furthermore, some specific complex domain examples of the comparison of electromagnetic waves equations are considered. Calculations are performed through Mathematica software by making some useful contribution to the programme and leveraging symbolic evaluations of FEM and FDM.

Keywords: finite difference method, finite element method, linear-nonlinear PDEs, symbolic computation, wave propagation equations

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Authors: Abdullah Eqal Al Mazrooei

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In this paper, a nonlinear dynamical system is presented. This system is a bilinear class. The bilinear systems are very important kind of nonlinear systems because they have many applications in real life. They are used in biology, chemistry, manufacturing, engineering, and economics where linear models are ineffective or inadequate. They have also been recently used to analyze and forecast weather conditions. Bilinear systems have three advantages: First, they define many problems which have a great applied importance. Second, they give us approximations to nonlinear systems. Thirdly, they have a rich geometric and algebraic structures, which promises to be a fruitful field of research for scientists and applications. The type of nonlinearity that is treated and analyzed consists of bilinear interaction between the states vectors and the system input. By using some properties of the tensor product, these systems can be transformed to linear systems. But, here we discuss the nonlinearity when the state vector is multiplied by itself. So, this model will be able to handle evolutions according to the Lotka-Volterra models or the Lorenz weather models, thus enabling a wider and more flexible application of such models. Here we apply by using an estimator to estimate temperatures. The results prove the efficiency of the proposed system.

Keywords: Lorenz models, nonlinear systems, nonlinear estimator, state-space model

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Authors: Shamsul Chowdhury

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The objective of this paper is to present the detailed analysis of the turbulent wave boundary layer produced by progressive finite-amplitude waves theory. Most of the works have done for the mass transport in the turbulent boundary layer assuming the eddy viscosity is not time varying, where the sediment movement is induced by the mean velocity. Near the ocean bottom, the waves produce a thin turbulent boundary layer, where the flow is highly rotational, and shear stress associated with the fluid motion cannot be neglected. The magnitude and the predominant direction of the sediment transport near the bottom are known to be closely related to the flow in the wave induced boundary layer. The magnitude of water particle velocity at the Crest phase differs from the one of the Trough phases due to the non-linearity of the waves, which plays an important role to determine the sediment movement. The non-linearity of the waves become predominant in the surf zone area, where the sediment movement occurs vigorously. Therefore, in order to describe the flow near the bottom and relationship between the flow and the movement of the sediment, the analysis was done using the non-linear boundary layer equation and the finite amplitude wave theory was applied to represent the velocity fields in the turbulent wave boundary layer. At first, the calculation was done for turbulent wave boundary layer by two-dimensional model where throughout the calculation is non-linear. But Stokes second order wave profile is adopted at the upper boundary. The calculated profile was compared with the experimental data. Finally, the calculation is done based on various modes of the velocity and turbulent energy. The mean velocity is found to differ from condition of the relative depth and the roughness. It is also found that due to non-linearity, the absolute value for velocity and turbulent energy as well as Reynolds stress are asymmetric. The mean velocity of the laminar boundary layer is always positive but in the turbulent boundary layer plays a very complicated role.

Keywords: wave boundary, mass transport, mean velocity, shear stress

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Authors: Redvan Ghasemlounia, Elham Ansari, Hikmet Kerem Cigizoglu

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Hydrological modeling in arid and semi-arid regions is very important. Iran has many regions with these climate conditions such as Chaharmahal and Bakhtiari province that needs lots of attention with an appropriate management. Forecasting of hydrological parameters and estimation of hydrological events of catchments, provide important information that used for design, management and operation of water resources such as river systems, and dams, widely. Discharge in rivers is one of these parameters. This study presents the application and comparison of some estimation methods such as Feed-Forward Back Propagation Neural Network (FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) to predict the daily flow discharge of the Soolegan River, located at Chaharmahal and Bakhtiari province, in Iran. In this study, Soolegan, station was considered. This Station is located in Soolegan River at 51° 14՜ Latitude 31° 38՜ longitude at North Karoon basin. The Soolegan station is 2086 meters higher than sea level. The data used in this study are daily discharge and daily precipitation of Soolegan station. Feed Forward Back Propagation Neural Network(FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) models were developed using the same input parameters for Soolegan's daily discharge estimation. The results of estimation models were compared with observed discharge values to evaluate performance of the developed models. Results of all methods were compared and shown in tables and charts.

Keywords: ANN, multi linear regression, Bayesian network, forecasting, discharge, gene expression programming

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Authors: Watcharapan Sukkerd, Teeradej Wuttipornpun

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This paper aims to present non-population search algorithms called tabu search (TS), simulated annealing (SA) and variable neighborhood search (VNS) to minimize the total cost of capacitated MRP problem in multi-stage assembly flow shop with two alternative machines. There are three main steps for the algorithm. Firstly, an initial sequence of orders is constructed by a simple due date-based dispatching rule. Secondly, the sequence of orders is repeatedly improved to reduce the total cost by applying TS, SA and VNS separately. Finally, the total cost is further reduced by optimizing the start time of each operation using the linear programming (LP) model. Parameters of the algorithm are tuned by using real data from automotive companies. The result shows that VNS significantly outperforms TS, SA and the existing algorithm.

Keywords: capacitated MRP, tabu search, simulated annealing, variable neighborhood search, linear programming, assembly flow shop, application in industry

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Authors: Sedat Yayla, Azhin Abdullah

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In the process of constructing hydroelectric power plants, the Pelton turbine, which is characterized by its simple manufacturing and construction, is performed in high head and low water flow. Parameters of the turbine have to be comprised in the designing process for obtaining hydraulic turbine with the highest efficiency during different operating conditions. The present investigation applied three-dimensional computational fluid dynamics (CFD). In addition, the bucket of Pelton turbine models with different splitter angle and inlet velocity values were examined for determining the force and visualizing the flow pattern on the bucket. The study utilized two diverse bucket models at various inlet velocities (20, 25, 30,35and 40m/s) and four different splitter angles (55, 75,90and 115 degree) for finding out the impacts of every single parameter on the effective force on the bucket. The acquired outcomes revealed that there is a linear relationship between force and inlet velocity on the bucket. Furthermore, the results also uncovered that the relationship between splitter angle and force on the bucket is linear until 90 degree.

Keywords: bucket design, computational fluid dynamics (CFD), free surface flow, two-phase flow, volume of fluid (VOF)

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Authors: Potaliya Pushpa, Kataria Sushma, D. S. Chowdhary, Dadhich Abhilasha

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Introduction: Stress is a nonspecific response of the body to a stressor or triggering stimulus. Chronic stress exposure contributes to various remarkable alterations o growth and development. Collective effects of stressors lead to several changes which are physical, physiological and behavioral in nature. Objective: To understand on an animal model how various chronic stress affect the somatic body growth as it can be useful for effective stress treatment and prevention of stress related illnesses. Material and Method: By selective fostering only male pup colonies were made and 102 male albino rats were studied. They were divided two groups as Control and Stressed. The experimental groups were exposed to four major types of stress as maternal deprivation, Restraint stress, electric foot shock and noise stress for affecting emotional, physical and physiological activities. Exposure was from birth to 17 week of life. Roentgenographs were taken in two planes as Dorso-ventral and Lateral and then measured for each rat. Various parameters were observed at specific intervals. Parameters recorded were Body weight and for linear growth it was summation of Cranial length, Head rump length and tail length. Behavior changes were also observed. Result: Multiple chronic stresses resulted in loss of approx. 25% of mean body weight. Maximal difference was found on 119th day (i.e. 87.81 gm) between the control and stressed group. Linear growth showed retardation which was found to be significant in stressed group on statistical analysis. Cranial Length and Head-rump Length showed maximum difference after maternal deprivation stress. After maternal deprivation (Day 21) and electric foot shock (Day 101) maximum difference i.e. 0.39 cm and 0.47 cm were found in cranial length of two groups. Electric foot shock had considerable impact on tail length. Noise Stress affected moreover behavior as compact to physical growth. Conclusion: Collective study showed that chronic stress not only resulted in reduced body weight in albino rats but also total linear size of rat thus affecting whole growth and development.

Keywords: stress, microscopic anatomy, macroscopic anatomy, chronic multiple stress, birth

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Authors: Shanti Swaroop Gupta, Bibekananda Mohapatra, S. K. Chaturvedi, Anand Bohra

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For sustainable development in India, there is an urgent need to follow the principles of industrial symbiosis in the industrial processes, under which the scraps, wastes, or by‐products of one industry can become the raw materials for another. This will not only help in reducing the dependence on natural resources but also help in gaining economic advantage to the industry. Gypsum is one such area in India, where the linear economy model of by-product gypsum utilization has resulted in unutilized legacy phosphogypsum stock of 64.65 million tonnes (mt) at phosphoric acid plants in 2020-21. In the future, this unutilized gypsum stock will increase further due to the expected generation of Flue Gas Desulphurization (FGD) gypsum in huge quantities from thermal power plants. Therefore, it is essential to transit from the linear to circular economy in Gypsum in India, which will result in huge environmental as well as ecological benefits. Gypsum is required in many sectors like Construction (Cement industry, gypsum boards, glass fiber reinforced gypsum panels, gypsum plaster, fly ash lime bricks, floor screeds, road construction), agriculture, in the manufacture of Plaster of Paris, pottery, ceramic industry, water treatment processes, manufacture of ammonium sulphate, paints, textiles, etc. The challenges faced in areas of quality, policy, logistics, lack of infrastructure, promotion, etc., for complete utilization of by-product gypsum have been discussed. The untapped potential of by-product gypsum utilization in various sectors like the use of gypsum in agriculture for sodic soil reclamation, utilization of legacy stock in cement industry on mission mode, improvement in quality of by-product gypsum by standardization and usage in building materials industry has been identified. Based on the measures required to tackle the various challenges and utilization of the untapped potential of gypsum, a comprehensive action plan for the transition from linear to the circular economy in gypsum in India has been formulated. The strategies and policy measures required to implement the action plan to achieve a circular economy in Gypsum have been recommended for various government departments. It is estimated that the focused implementation of the proposed action plan would result in a significant decrease in unutilized gypsum legacy stock in the next five years and it would cease to exist by 2027-28 if the proposed action plan is effectively implemented.

Keywords: circular economy, FGD gypsum, India, phosphogypsum

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Authors: Ebrahim Asadi-Gangraj

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Hybrid flow shop scheduling problem (HFS) contains sequencing in a flow shop where, at any stage, there exist one or more related or unrelated parallel machines. This production system is a common manufacturing environment in many real industries, such as the steel manufacturing, ceramic tile manufacturing, and car assembly industries. In this research, a mixed integer linear programming (MILP) model is presented for the hybrid flow shop scheduling problem, in which, the objective consists of minimizing the maximum completion time (makespan). For this purpose, a Benders Decomposition (BD) method is developed to solve the research problem. The proposed approach is tested on some test problems, small to moderate scale. The experimental results show that the Benders decomposition approach can solve the hybrid flow shop scheduling problem in a reasonable time, especially for small and moderate-size test problems.

Keywords: hybrid flow shop, mixed integer linear programming, Benders decomposition, makespan

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Authors: Mohammed Al-Zubaidi, Katherine Ong, Pravin Viswambaram, Steve McCombie, Oliver Oey, Jeremy Ong, Richard Gauci, Ronny Low, Dickon Hayne

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Objective: Lymph node involvement along with distant metastasis in a patient with invasive bladder cancer determines the disease survival, therefeor, it is an essential determinant of the therapeutic management and outcome. This retrospective study aims to determine the accuracy of FDG PET scan in detecting lymphatic involvement and distant metastatic urothelial cancer compared to conventional CT staging. Method: A retrospective review of 76 patients with UC or BC who underwent surgery or confirmatory biopsy that was staged with both CT and 18F-FDG-PET (up to 8 weeks apart) between 2015 and 2020. Fifty-sevenpatients (75%) had formal pelvic LN dissection or biopsy of suspicious metastasis. 18F-FDG-PET reports for positive sites were qualitative depending on SUV Max. On the other hand, enlarged LN by RECIST criteria 1.1 (>10 mm) and other qualitative findings suggesting metastasis were considered positive in CT scan. Histopathological findings from surgical specimens or image-guided biopsies were considered the gold standard in comparison to imaging reports. 18F-FDG-avid or enlarged pelvic LNs with surgically proven nodal metastasis were considered true positives. Performance characteristics of 18F-FDG-PET and CT, including sensitivity, specificity, positive predictive value (PPV), and negative predictive value (PPV), were calculated. Results: Pelvic LN involvement was confirmed histologically in 10/57 (17.5%) patients. Sensitivity, specificity, PPV and NPV of CT for detecting pelvic LN metastases were 41.17% (95% CI:18-67%), 100% (95% CI:90-100%) 100% (95% CI:59-100%) and 78.26% (95% CI:64-89%) respectively. Sensitivity, specificity, PPV and NPV of 18F-FDG-PET for detecting pelvic LN metastases were 62.5% (95% CI:35-85%), 83.78% (95% CI:68-94%), 62.5% (95% CI:35-85%), and 83.78% (95% CI:68-94%) respectively. Pre-operative staging with 18F-FDG-PET identified the distant metastatic disease in 9/76 (11.8%) patients who were occult on CT. This retrospective study suggested that 18F-FDG-PET may be more sensitive than CT for detecting pelvic LN metastases. 7/76 (9.2%) patients avoided cystectomy due to 18F-FDG-PET diagnosed metastases that were not reported on CT. Conclusion: 18F-FDG-PET is more sensitive than CT for pelvic LN metastases, which can be used as the standard modality of bladder cancer staging, as it may change the treatment by detecting lymph node metastasis that was occult in CT. Further research involving randomised controlled trials comparing the diagnostic yield of 18F-FDG-PET and CT in detecting nodal and distant metastasis in UC or BC is warranted to confirm our findings.

Keywords: FDG PET, CT scan, urothelial cancer, bladder cancer

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Authors: Elham Kiyani

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In this paper, we first introduce the concept of Q-efficient solutions in a real linear space not necessarily endowed with a topology, where Q is some nonempty (not necessarily convex) set. We also used the scalarization technique including the Gerstewitz function generated by a nonconvex set to characterize these Q-efficient solutions. The algebraic concepts of interior and closure are useful to study optimization problems without topology. Studying nonconvex vector optimization is valuable since topological interior is equal to algebraic interior for a convex cone. So, we use the algebraic concepts of interior and closure to define Q-weak efficient solutions and Q-Henig proper efficient solutions of set-valued optimization problems, where Q is not a convex cone. Optimization problems with set-valued maps have a wide range of applications, so it is expected that there will be a useful analytical tool in optimization theory for set-valued maps. These kind of optimization problems are closely related to stochastic programming, control theory, and economic theory. The paper focus on nonconvex problems, the results are obtained by assuming generalized non-convexity assumptions on the data of the problem. In convex problems, main mathematical tools are convex separation theorems, alternative theorems, and algebraic counterparts of some usual topological concepts, while in nonconvex problems, we need a nonconvex separation function. Thus, we consider the Gerstewitz function generated by a general set in a real linear space and re-examine its properties in the more general setting. A useful approach for solving a vector problem is to reduce it to a scalar problem. In general, scalarization means the replacement of a vector optimization problem by a suitable scalar problem which tends to be an optimization problem with a real valued objective function. The Gerstewitz function is well known and widely used in optimization as the basis of the scalarization. The essential properties of the Gerstewitz function, which are well known in the topological framework, are studied by using algebraic counterparts rather than the topological concepts of interior and closure. Therefore, properties of the Gerstewitz function, when it takes values just in a real linear space are studied, and we use it to characterize Q-efficient solutions of vector problems whose image space is not endowed with any particular topology. Therefore, we deal with a constrained vector optimization problem in a real linear space without assuming any topology, and also Q-weak efficient and Q-proper efficient solutions in the senses of Henig are defined. Moreover, by means of the Gerstewitz function, we provide some necessary and sufficient optimality conditions for set-valued vector optimization problems.

Keywords: algebraic interior, Gerstewitz function, vector closure, vector optimization

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Authors: S. Fominow, C. Dobert

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The present article describes the research that deals with the development of equivalent geometric imperfections for the stability design of steel members considering lateral-torsional buckling. The application of these equivalent imperfections takes into account the stiffness-reducing effects due to inelasticity and residual stresses, which lead to a reduction of the load carrying capacity of slender members and structures. This allows the application of a simplified design method, that is performed in three steps. Application of equivalent geometric imperfections, determination of internal forces using geometrical non-linear analysis (GNIA) and verification of the cross-section resistance at the most unfavourable location. All three verification steps are closely related and influence the results. The derivation of the equivalent imperfections was carried out in several steps. First, reference lateral-torsional buckling resistances for various rolled I-sections, slenderness grades, load shapes and steel grades were determined. This was done either with geometric and material non-linear analysis with geometrical imperfections and residual stresses (GMNIA) or for standard cases based on the equivalent member method. With the aim of obtaining identical lateral-torsional buckling resistances as the reference resistances from the application of the design method, the required sizes for equivalent imperfections were derived. For this purpose, a program based on the FEM method has been developed. Based on these results, several proposals for the specification of equivalent geometric imperfections have been developed. These differ in the shape of the applied equivalent geometric imperfection, the model of the cross-sectional resistance and the steel grade. The proposed design methods allow a wide range of applications and a reliable calculation of the lateral-torsional buckling resistances, as comparisons between the calculated resistances and the reference resistances have shown.

Keywords: equivalent geometric imperfections, GMNIA, lateral-torsional buckling, non-linear finite element analysis

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Authors: Jaan-Willem Simon, Bertram Stier, Brett Bednarcyk, Evan Pineda, Stefanie Reese

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Textile composites, in which the reinforcing fibers are woven or braided, have become very popular in numerous applications in aerospace, automotive, and maritime industry. These textile composites are advantageous due to their ease of manufacture, damage tolerance, and relatively low cost. However, physics-based modeling of the mechanical behavior of textile composites is challenging. Compared to their unidirectional counterparts, textile composites introduce additional geometric complexities, which cause significant local stress and strain concentrations. Since these internal concentrations are primary drivers of nonlinearity, damage, and failure within textile composites, they must be taken into account in order for the models to be predictive. The macro-scale approach to modeling textile-reinforced composites treats the whole composite as an effective, homogenized material. This approach is very computationally efficient, but it cannot be considered predictive beyond the elastic regime because the complex microstructural geometry is not considered. Further, this approach can, at best, offer a phenomenological treatment of nonlinear deformation and failure. In contrast, the mesoscale approach to modeling textile composites explicitly considers the internal geometry of the reinforcing tows, and thus, their interaction, and the effects of their curved paths can be modeled. The tows are treated as effective (homogenized) materials, requiring the use of anisotropic material models to capture their behavior. Finally, the micro-scale approach goes one level lower, modeling the individual filaments that constitute the tows. This paper will compare meso- and micro-scale approaches to modeling the deformation, damage, and failure of textile-reinforced polymer matrix composites. For the mesoscale approach, the woven composite architecture will be modeled using the finite element method, and an anisotropic damage model for the tows will be employed to capture the local nonlinear behavior. For the micro-scale, two different models will be used, the one being based on the finite element method, whereas the other one makes use of an embedded semi-analytical approach. The goal will be the comparison and evaluation of these approaches to modeling textile-reinforced composites in terms of accuracy, efficiency, and utility.

Keywords: multiscale modeling, continuum damage model, damage interaction, textile composites

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Authors: Sajjad Baghernezhad, Saeideh Baghernezhad

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Nowadays considering human involved in increasing data development some methods such as data mining to extract science are unavoidable. One of the discussions of data mining is inherent distribution of the data usually the bases creating or receiving such data belong to corporate or non-corporate persons and do not give their information freely to others. Yet there is no guarantee to enable someone to mine special data without entering in the owner’s privacy. Sending data and then gathering them by each vertical or horizontal software depends on the type of their preserving type and also executed to improve data privacy. In this study it was attempted to compare comprehensively preserving data methods; also general methods such as random data, coding and strong and weak points of each one are examined.

Keywords: data mining, distributed data mining, privacy protection, privacy preserving

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Authors: Revant Nayar

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In this work, we recast the equations describing large scale structure, and by extension all nonlinear fluids, in the path integral formalism. We first calculate the well known two and three point functions using Schwinger Keldysh formalism used commonly to perturbatively solve path integrals in non- equilibrium systems. Then we include EFT corrections due to pressure, viscosity, and noise as effects on the time-dependent propagator. We are able to express results for arbitrary two and three point correlation functions in LSS in terms of differential operators acting on a triple K master intergral. We also, for the first time, get analytical results for more general initial conditions deviating from the usual power law P∝kⁿ by introducing a mass scale in the initial conditions. This robust field theoretic formalism empowers us with tools from strongly coupled QFT to study the strongly non-linear regime of LSS and turbulent fluid dynamics such as OPE and holographic duals. These could be used to capture fully the strongly non-linear dynamics of fluids and move towards solving the open problem of classical turbulence.

Keywords: quantum field theory, cosmology, effective field theory, renormallisation

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Authors: Mengna Hu

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This paper examines the impact of an anti-speculation tax policy on the trading activities and home price movements in the housing market in Hong Kong. The study focuses on the secondary residential property market where transactions dominate. The policy intervention substantially raised the transaction cost to speculators as well as genuine homeowners who dispose their homes within a certain period. Through the demonstration of structural breaks, our empirical results show that the rise in transaction cost effectively reduced speculative trading activities. However, it accelerated price increase in the small-sized segment by vastly demotivating existing homeowners from trading up to better homes, causing congestion in the lower-end market where the demand from first-time buyers is still strong. Apart from that, by employing regime switching approach, we further show that the unintended consequences are likely to be persistent due to this policy together with other strengthened cooling measures.

Keywords: transaction costs, housing market, structural breaks, regime switching

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Authors: Fatemeh Valizadeh Gamchi, Edward L. Boone

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This research focuses on Lyme disease, a widespread infectious condition in the United States caused by the bacterium Borrelia burgdorferi sensu stricto. It is critical to identify environmental and economic elements that are contributing to the spread of the disease. This study examined data from Virginia to identify a subset of explanatory variables significant for Lyme disease case numbers. To identify relevant variables and avoid overfitting, linear poisson, and regularization regression methods such as a ridge, lasso, and elastic net penalty were employed. Cross-validation was performed to acquire tuning parameters. The methods proposed can automatically identify relevant disease count covariates. The efficacy of the techniques was assessed using four criteria on three simulated datasets. Finally, using the Virginia Department of Health’s Lyme disease data set, the study successfully identified key factors, and the results were consistent with previous studies.

Keywords: lyme disease, Poisson generalized linear model, ridge regression, lasso regression, elastic net regression

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Authors: Kai Liu

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Remote sensing-derived land surface temperature (LST) can provide an indication of the temporal and spatial patterns of surface evapotranspiration (ET). However, the spatial resolution achieved by existing commonly satellite products is ~1 km, which remains too coarse for ET estimations. This paper proposed a model that can disaggregate coarse resolution MODIS LST at 1 km scale to fine spatial resolutions at the scale of 250 m. Our approach attempted to weaken the impacts of soil moisture and growing statues on LST variations. The proposed model spatially disaggregates the coarse thermal data by using a non-linear model involving Bowen ratio, normalized difference vegetation index (NDVI) and photochemical reflectance index (PRI). This LST disaggregation model was tested on two heterogeneous landscapes in central Iowa, USA and Heihe River, China, during the growing seasons. Statistical results demonstrated that our model achieved better than the two classical methods (DisTrad and TsHARP). Furthermore, using the surface energy balance model, it was observed that the estimated ETs using the disaggregated LST from our model were more accurate than those using the disaggregated LST from DisTrad and TsHARP.

Keywords: Bowen ration, downscaling, evapotranspiration, land surface temperature

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Authors: Nur Aidya Hanum Aizam, Vikneswary Uvaraja

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The agenda of showing the scheduled time for performing certain tasks is known as timetabling. It widely used in many departments such as transportation, education, and production. Some difficulties arise to ensure all tasks happen in the time and place allocated. Therefore, many researchers invented various programming model to solve the scheduling problems from several fields. However, the studies in developing the general integer programming model for many timetabling problems are still questionable. Meanwhile, this thesis describe about creating a general model which solve different types of timetabling problems by considering the basic constraints. Initially, the common basic constraints from five different fields are selected and analyzed. A general basic integer programming model was created and then verified by using the medium set of data obtained randomly which is much similar to realistic data. The mathematical software, AIMMS with CPLEX as a solver has been used to solve the model. The model obtained is significant in solving many timetabling problems easily since it is modifiable to all types of scheduling problems which have same basic constraints.

Keywords: AIMMS mathematical software, integer linear programming, scheduling problems, timetabling

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Authors: Li Feng, Cheng Zhang, Chuanzhou Yuang

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Understanding the macromolecular structure of low-rank coal is very important for its gasification and liquefaction. The pyrolysis is one of the methods of analyzing the macromolecular structure of coal. The gaseous products decomposed directly by the raw lignite at 500 °C and indirectly by tar products from raw lignite pyrolysis at 500 °C were investigated and compared by thermogravimetry, gas chromatography and mass spectrum coupled instrument system (TG/GC/MS) in this paper. The results show that 52 kinds of products were found from the raw lignite and 70 kinds of products from the tar. The pyrolysis products directly from the lignite appear more monocyclic aromatic hydrocarbons and less substituent groups or branch chain, compared with the products from the tar. There is less linear chain and double bonds structure in the tar, which can be speculated that linear chain and double bonds structure took part in the generation of condensed rings and other reactions. There are more kinds of phenol and furan in the tar, which indicate that these products may be generated from the secondary reaction. The formation process of phenol, phenol naphthalene, naphthene and furan are discussed.

Keywords: composition and structure, lignite, pyrolysis of coal, tar, TG/GC/MS

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Authors: Recep Keşli, Hayriye Tokay, Cengiz Demir, İsmail Ceyhan

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Objective: In many countries, tuberculosis (TB) is still one of the most important diseases. Tuberculosis is among top 10 causes of death worldwide. The early diagnosis of active tuberculosis still depends on the presence of acid resistant bacilli (ARB) in stained smears. In this study, we aimed to investigate the diagnostic performances of Erlich Ziehl Neelsen (EZN), Kinyoun and two different fluorescent stains. Methods: The specimens were obtained from the patients who applied to Chest Diseases Departments of Ankara Atatürk Chest Diseases and Thoracic Surgery Training and Research Hospital, and Afyon Kocatepe University, ANS Research and Practice Hospital. The study was carried out in the Medical Microbiology Laboratory, School of Medicine, Afyon Kocatepe University. All the non-sterile specimens were homogenized and decontaminated according to the EUCAST instructions. Samples were inoculated onto the Löwenstein-Jensen agars (bio-Merieux Marcy l'Etoile, France) and then incubated at 37˚C, for 40 days. Four smears were prepared from each specimen. Slides were stained with commercial EZN (BD, Sparks, USA), Kinyoun (SALUBRIS Istanbul, Turkey), Auramine (SALUBRIS Istanbul, Turkey) and Rhodamine (SALUBRIS Istanbul, Turkey) kit. While EZN and Kinyoun stainings were examined by light microscope, Auramine and Rhodamine slides were examined by fluorescence microscopy. Results: A total of 158 respiratory system samples (sputum, broncho alveolar lavage fluid…etc) were enrolled into the study. A hundred and two of the samples that processed were found as culture positive. The sensitivity, specificity, positive predictive, and negative predictive values were detected as 100%, 67.5%, 73.5%, and 100% for EZN, 100%, 70.9%, 77.4%, and 100% for Kinyoun, 100%,77.8%, 84.3%, 100% for Auramine, and 100%, 80% , 86.3%, and 100% for Rhodamine respectively. Conclusions: According to our study auramine and rhodamine staining methods showed the best diagnostic performance among the four investigated staining methods. In conclusion, the fluorochrome staining method may be accepted as the most reliable, rapid and useful method for diagnosis of the mycobacterial infections truly.

Keywords: acid resistant bacilli (ARB), auramine, Ehrlich-Ziehl-Neelsen (EZN), Kinyoun, Rhodamine

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Authors: Nada Slimane, Foued Theljani, Faouzi Bouani

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The paper addresses the problem of fault diagnosis for systems operating in several modes (normal or faulty) based on states assessment. We use, for this purpose, a methodology consisting of three main processes: 1) sequential data clustering, 2) linear model regression and 3) state filtering. Typically, Kalman Filter (KF) is an algorithm that provides estimation of unknown states using a sequence of I/O measurements. Inevitably, although it is an efficient technique for state estimation, it presents two main weaknesses. First, it merely predicts states without being able to isolate/classify them according to their different operating modes, whether normal or faulty modes. To deal with this dilemma, the KF is endowed with an extra clustering step based fully on sequential version of the k-means algorithm. Second, to provide state estimation, KF requires state space models, which can be unknown. A linear regularized regression is used to identify the required models. To prove its effectiveness, the proposed approach is assessed on a simulated benchmark.

Keywords: clustering, diagnosis, Kalman Filtering, k-means, regularized regression

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Authors: Kourosh Nazarian

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Many of the engineering materials, such as behavioral metals, have at least a certain level of linear behavior. It means that if the stresses are doubled, the deformations would be also doubled. In fact, these materials have linear elastic properties. Soils do not follow this law, for example, when compressed, soils become gradually tighter. On the surface of the ground, the sand can be easily deformed with a finger, but in high compressive stresses, they gain considerable hardness and strength. This is mainly due to the increase in the forces among the separate particles. Creeps also deform the soils under a constant load over time. Clay and peat soils have creep behavior. As a result of this phenomenon, structures constructed on such soils will continue their collapse over time. In this paper, the researchers analyzed and modeled the stresses and creeps in the southern plains of Kerman province in Iran through library-documentary, quantitative and software techniques, and field survey. The results of the modeling showed that these plains experienced severe stresses and had a collapse of about 26 cm in the last 15 years and also creep evidence was discovered in an area with a gradient of 3-6 degrees.

Keywords: Stress, creep, faryab, surface runoff

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Authors: Zellagui Redouane, Bellaouar Ahmed, Lachi Mohammed

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The railway axles are the essential parts in the bogie of train, and its failure creates a big problem in the railway transport; during the work of this parts we noticed a premature deterioration. The aim has been presented a predictive model allowing the identification of the probable causes that are the cause of these premature deterioration. The results are employed for predicting fatigue crack growth in the railway axle, Also we want to present the variation value of stress intensity factor in different positions of elliptical crack tip. The modeling of axle in performed by the SOLID WORKS software and imported into ANSYS.

Keywords: crack growth, static load, railway axle, lifetime

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Authors: Iliya Bitrus Abaje

Abstract:

This study examines the evidence of climate change scenario in Kaduna State from the analysis of temperature and rainfall data (1976-2015) from three meteorological stations along a geographic transect from the southern part to the northern part of the State. Different statistical methods were used in determining the changes in both the temperature and rainfall series. The result of the linear trend lines revealed a mean increase in average temperature of 0.73oC for the 40 years period of study in the State. The plotted standard deviation for the temperature anomalies generally revealed that years of temperatures above the mean standard deviation (hotter than the normal conditions) in the last two decades (1996-2005 and 2006-2015) were more than those below (colder than the normal condition). The Cramer’s test and student’s t-test generally revealed an increasing temperature trend in the recent decades. The increased in temperature is an evidence that the earth’s atmosphere is getting warmer in recent years. The linear trend line equation of the annual rainfall for the period of study showed a mean increase of 316.25 mm for the State. Findings also revealed that the plotted standard deviation for the rainfall anomalies, and the 10-year non-overlapping and 30-year overlapping sub-periods analysis in all the three stations generally showed an increasing trend from the beginning of the data to the recent years. This is an evidence that the study area is now experiencing wetter conditions in recent years and hence climate change. The study recommends diversification of the economic base of the populace with emphasis on moving away from activities that are sensitive to temperature and rainfall extremes Also, appropriate strategies to ameliorate the scourge of climate change at all levels/sectors should always take into account the recent changes in temperature and rainfall amount in the area.

Keywords: anomalies, linear trend, rainfall, temperature

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Authors: David Alejandro Lazo-Vasquez, Jorge Luis Balino

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In the petroleum industry, multiphase flow occurs when oil, gas, and water are transported in the same pipe through large pipeline systems. The flow can take different patterns depending on parameters like fluid velocities, pipe diameter, pipe inclination, and fluid properties. Mainly, intermittent flow is produced by the natural propagation of short and long waves, according to the Kelvin-Helmholtz Stability Theory. To model stratified flow and the onset of intermittent flow, it is crucial to have knowledge of short and long waves behavior. The two-fluid model, frequently employed for characterizing multiphase systems, becomes ill-posed for high liquid and gas velocities and large inclination angles, for short waves can develop infinite growth rates. We are interested in focusing attention on long-wave instability, which leads to the production of roll waves that may grow and result in the transition from stratified flow to intermittent flow. In this study, global and local linear stability analyses for dynamic and kinematic stability criteria predict the regions of stability of the flow for different pipe inclinations and fluid velocities in regularized and non-regularized systems, concurrently. It was possible to distinguish when: wave growth rates are absolutely bounded (stable stratified smooth flow), waves have finite growth rates (unstable stratified wavy flow), and when the equation system becomes elliptic and hyperbolization is needed. In order to bound short wave growth rates and regularize the equation system, we incorporated some lower and higher-order terms like interfacial drag and surface tension, respectively.

Keywords: linear stability analysis, multiphase flow, onset of slugging, two-fluid model regularization

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Authors: H. Namazi, H. T. N. Kuan

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Brain activity can be measured by acquiring and analyzing EEG signals from an individual. In fact, the human brain response to external and internal stimuli is mapped in his EEG signals. During years some methods such as Fourier transform, wavelet transform, empirical mode decomposition, etc. have been used to analyze the EEG signals in order to find the effect of stimuli, especially external stimuli. But each of these methods has some weak points in analysis of EEG signals. For instance, Fourier transform and wavelet transform methods are linear signal analysis methods which are not good to be used for analysis of EEG signals as nonlinear signals. In this research we analyze the brain response to visual stimuli by extracting information in the form of various measures from EEG signals using a software developed by our research group. The used measures are Jeffrey’s measure, Fractal dimension and Hurst exponent. The results of these analyses are useful not only for fundamental understanding of brain response to visual stimuli but provide us with very good recommendations for clinical purposes.

Keywords: visual stimuli, brain response, EEG signal, fractal dimension, hurst exponent, Jeffrey’s measure

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Authors: Ali Soroush, Mehdi Mirzaei Alavijeh, Touraj Ahmadi Jouybari, Fazel Zinat-Motlagh, Abbas Aghaei, Mari Ataee

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Diabetes is a disease with long cardiovascular, renal, ophthalmic and neural complications. It is prevalent all around the world including Iran, and its prevalence is increasing. The aim of this study was to determine the factors related to self-care behavior based on health belief model among sample of Iranian diabetic patients. This cross-sectional study was conducted among 301 type 2 diabetic patients in Gachsaran, Iran. Data collection was based on an interview and the data were analyzed by SPSS version 20 using ANOVA, t-tests, Pearson correlation, and linear regression statistical tests at 95% significant level. Linear regression analyses showed the health belief model variables accounted for 29% of the variation in self-care behavior; and perceived severity and perceived self-efficacy are more influential predictors on self-care behavior among diabetic patients.

Keywords: diabetes, patients, self-care behaviors, health belief model

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Authors: Tanida Julvanichpong

Abstract:

Exercise has been regarded as a necessary and important aspect to enhance physical performance and psychology health. Body weight statistics of students in junior high school students in Chonburi Province beyond a standard risk of obesity. Promoting exercise among Junior high school students in Chonburi Province, essential knowledge concerning factors influencing exercise is needed. Therefore, this study aims to (1) determine the levels of perceived exercise behavior, exercise behavior in the past, perceived barriers to exercise, perceived benefits of exercise, perceived self-efficacy to exercise, feelings associated with exercise behavior, influence of the family to exercise, influence of friends to exercise, and the perceived influence of the environment on exercise. (2) examine the predicting ability of each of the above factors while including personal factors (sex, educational level) for exercise behavior. Pender’s Health Promotion Model was used as a guide for the study. Sample included 652 students in junior high schools, Chonburi Provience. The samples were selected by Multi-Stage Random Sampling. Data Collection has been done by using self-administered questionnaires. Data were analyzed using descriptive statistics, Pearson’s product moment correlation coefficient, Eta, and stepwise multiple regression analysis. The research results showed that: 1. Perceived benefits of exercise, influence of teacher, influence of environmental, feelings associated with exercise behavior were at a high level. Influence of the family to exercise, exercise behavior, exercise behavior in the past, perceived self-efficacy to exercise and influence of friends were at a moderate level. Perceived barriers to exercise were at a low level. 2. Exercise behavior was positively significant related to perceived benefits of exercise, influence of the family to exercise, exercise behavior in the past, perceived self-efficacy to exercise, influence of friends, influence of teacher, influence of environmental and feelings associated with exercise behavior (p < .01, respectively) and was negatively significant related to educational level and perceived barriers to exercise (p < .01, respectively). Exercise behavior was significant related to sex (Eta = 0.243, p=.000). 3. Exercise behavior in the past, influence of the family to exercise significantly contributed 60.10 percent of the variance to the prediction of exercise behavior in male students (p < .01). Exercise behavior in the past, perceived self-efficacy to exercise, perceived barriers to exercise, and educational level significantly contributed 52.60 percent of the variance to the prediction of exercise behavior in female students (p < .01).

Keywords: predictive factors, exercise behaviors, Junior high school, Chonburi Province

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Authors: X. Li, Y. Liu, H. Wong, B. Pardoen, A. Fabbri, F. McGregor, E. Liu

Abstract:

The target of this paper is to investigate how saturated poroelastic soils subject to freezing temperatures behave and how different boundary conditions can intervene and affect the thermo-hydro-mechanical (THM) responses, based on a particular but classical configuration of a finite homogeneous soil layer studied by Terzaghi. The essential relations on the constitutive behavior of a freezing soil are firstly recalled: ice crystal - liquid water thermodynamic equilibrium, hydromechanical constitutive equations, momentum balance, water mass balance, and the thermal diffusion equation, in general, non-linear case where material parameters are state-dependent. The system of equations is firstly linearized, assuming all material parameters to be constants, particularly the permeability of liquid water, which should depend on the ice content. Two analytical solutions solved by the classic Laplace transform are then developed, accounting for two different sets of boundary conditions. Afterward, the general non-linear equations with state-dependent parameters are solved using a commercial code COMSOL based on finite elements method to obtain numerical results. The validity of this numerical modeling is partially verified using the analytical solution in the limiting case of state-independent parameters. Comparison between the results given by the linearized analytical solutions and the non-linear numerical model reveals that the above-mentioned linear computation will always underestimate the liquid pore pressure and displacement, whatever the hydraulic boundary conditions are. In the nonlinear model, the faster growth of ice crystals, accompanying the subsequent reduction of permeability of freezing soil layer, makes a longer duration for the depressurization of water liquid and slower settlement in the case where the ground surface is swiftly covered by a thin layer of ice, as well as a bigger global liquid pressure and swelling in the case of the impermeable ground surface. Nonetheless, the analytical solutions based on linearized equations give a correct order-of-magnitude estimate, especially at moderate temperature variations, and remain a useful tool for preliminary design checks.

Keywords: chemical potential, cryosuction, Laplace transform, multiphysics coupling, phase transformation, thermodynamic equilibrium

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