Search results for: equivalent model

Authors: Quy Dang Nguyen, Reza Nakhaie Jazar

Abstract:

The paper investigates vibration dynamics of tire-road separation for a quarter-car model; this separation model is developed to be close to the real situation considering the tire is able to separate from the ground plane. A set of piecewise linear mathematical models is developed and matches the in-contact and no-contact states to be considered as mother models for further investigations. The bound dynamics are numerically simulated in the time response and phase portraits. The separation analysis may determine which values of suspension parameters can delay and avoid the no-contact phenomenon, which results in improving ride comfort and eliminating the potentially dangerous oscillation. Finally, model verification is carried out in the MSC-ADAMS environment.

Keywords: quarter-car vibrations, tire-road separation, separation analysis, separation dynamics, ride comfort, ADAMS validation

Procedia PDF Downloads 86

Authors: Petra Buzkova, Milos Kopa

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Reliability of the credit default swap market had been questioned repeatedly during the EMU debt crisis. The article examines whether this development influenced sovereign EMU CDS prices in general. We regress the CDS market price on a model risk neutral CDS price obtained from an adopted reduced form valuation model in the 2009-2013 period. We look for a break point in the single-equation and multi-equation econometric models in order to show the changes in relations between CDS market and model prices. Our results differ according to the risk profile of a country. We find that in the case of riskier countries, the relationship between the market and model price changed when market participants started to question the ability of CDS contracts to protect their buyers. Specifically, it weakened after the change. In the case of less risky countries, the change happened earlier and the effect of a weakened relationship is not observed.

Keywords: chow stability test, credit default swap, debt crisis, reduced form valuation model, seemingly unrelated regression

Procedia PDF Downloads 259

Authors: César Garza

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In supervised binary classification and regression problems, it is well-known that learnability is equivalent to a uniform convergence of the hypothesis class, and if a problem is learnable, it is learnable by empirical risk minimization. For the general learning setting of unsupervised learning tasks, there are non-trivial learning problems where uniform convergence does not hold. We present here the task of learning centers of mass with an extra feature that “activates” some of the coordinates over the unit ball in a Hilbert space. We show that the learning problem is learnable under a stable RLM rule. We introduce a family of distributions over the domain space with some mild restrictions for which the sample complexity of uniform convergence for these problems must grow logarithmically with the dimension of the Hilbert space. If we take this dimension to infinity, we obtain a learnable problem for which the uniform convergence property fails for a vast family of distributions.

Keywords: statistical learning theory, learnability, uniform convergence, stability, regularized loss minimization

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Authors: Weiwen Li, Hao Huang, Chengmao You, Jianji Liao, Lei Wang, Lina An

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Zooplankton are a central issue in the ecology which makes a great contribution to maintaining the balance of an ecosystem. It is critical in promoting the material cycle and energy flow within the ecosystems. A generalized additive model (GAM) was applied to analyze the relationships between the density (individuals per m³) of zooplankton and other variables in West Daya Bay. All data used in this analysis (the survey month, survey station (longitude and latitude), the depth of the water column, the superficial concentration of chlorophyll a, the benthonic concentration of chlorophyll a, the number of zooplankton species and the number of zooplankton species) were collected through monthly scientific surveys during January to December 2016. GLM model (generalized linear model) was used to choose the significant variables’ impact on the density of zooplankton, and the GAM was employed to analyze the relationship between the density of zooplankton and the significant variables. The results showed that the density of zooplankton increased with an increase of the benthonic concentration of chlorophyll a, but decreased with a decrease in the depth of the water column. Both high numbers of zooplankton species and the overall total number of zooplankton individuals led to a higher density of zooplankton.

Keywords: density, generalized linear model, generalized additive model, the West Daya Bay, zooplankton

Procedia PDF Downloads 146

Authors: Tomohiko Utsuki

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Currently, brain resuscitation becomes increasingly important due to revising various clinical guidelines pertinent to emergency care. In brain resuscitation, the control of brain temperature (BT), intracranial pressure (ICP), and cerebral blood flow (CBF) is required for stabilizing physiological state of brain, and is described as the essential treatment points in many guidelines of disorder and/or disease such as brain injury, stroke, and encephalopathy. Thus, an integrated control system of BT, ICP, and CBF will greatly contribute to alleviating the burden on medical staff and improving treatment effect in brain resuscitation. In order to develop such a control system, models related to BT, ICP, and CBF are required for control simulation, because trial and error experiments using patients are not ethically allowed. A static model of cerebral blood circulation from intracranial arteries and vertebral artery to jugular veins has already constructed and verified. However, it is impossible to represent the pooling of blood in blood vessels, which is one cause of cerebral hypertension in this model. And, it is also impossible to represent the pulsing motion of blood vessels caused by blood pressure change which can have an affect on the change of cerebral tissue pressure. Thus, a dynamic model of cerebral blood circulation is constructed in consideration of the elasticity of the blood vessel and the inertia of the blood vessel wall. The constructed dynamic model was numerically analyzed using the normal data, in which each arterial blood flow in cerebral blood circulation, the distribution of blood pressure in the Circle of Willis, and the change of blood pressure along blood flow were calculated for verifying against physiological knowledge. As the result, because each calculated numerical value falling within the generally known normal range, this model has no problem in representing at least the normal physiological state of the brain. It is the next task to verify the accuracy of the present model in the case of disease or disorder. Currently, the construction of a migration model of extracellular fluid and a model of heat transfer in cerebral tissue are in progress for making them parts of an integrated model of brain physiological state, which is necessary for developing an future integrated control system of BT, ICP and CBF. The present model is applicable to constructing the integrated model representing at least the normal condition of brain physiological state by uniting with such models.

Keywords: dynamic model, cerebral blood circulation, brain resuscitation, automatic control

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Authors: Mostafa Sefidgar, Sohrab Zendehboudi, Hossein Bazmara, Madjid Soltani

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Based on findings from clinical applications, most drug treatments fail to eliminate malignant tumors completely even though drug delivery through systemic administration may inhibit their growth. Therefore, better understanding of tumor formation is crucial in developing more effective therapeutics. For this purpose, nowadays, solid tumor modeling and simulation results are used to predict how therapeutic drugs are transported to tumor cells by blood flow through capillaries and tissues. A solid tumor is investigated as a porous media for fluid flow simulation. Most of the studies use Darcy model for porous media. In Darcy model, the fluid friction is neglected and a few simplified assumptions are implemented. In this study, the effect of these assumptions is studied by considering Brinkman model. A multi scale mathematical method which calculates fluid flow to a solid tumor is used in this study to investigate how neglecting fluid friction affects the solid tumor simulation. In this work, the mathematical model in our previous studies is developed by considering two model of momentum equation for porous media: Darcy and Brinkman. The mathematical method involves processes such as fluid flow through solid tumor as porous media, extravasation of blood flow from vessels, blood flow through vessels and solute diffusion, convective transport in extracellular matrix. The sprouting angiogenesis model is used for generating capillary network and then fluid flow governing equations are implemented to calculate blood flow through the tumor-induced capillary network. Finally, the two models of porous media are used for modeling fluid flow in normal and tumor tissues in three different shapes of tumors. Simulations of interstitial fluid transport in a solid tumor demonstrate that the simplifications used in Darcy model affect the interstitial velocity and Brinkman model predicts a lower value for interstitial velocity than the values that Darcy model does.

Keywords: solid tumor, porous media, Darcy model, Brinkman model, drug delivery

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Authors: John Vergara, Giuseppe Palmese

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Fundamental studies aimed at elucidating the key contributions to corrosion performance are needed to make progress toward effective and environmentally compliant corrosion control. Epoxy/amine systems are typically employed as barrier coatings for corrosion control. However, the hardening agents used for coating applications can be very complex, making fundamental studies of water and oxygen permeability challenging to carry out. Creating model building blocks for epoxy/amine coatings is the first step in carrying out these studies. We will demonstrate the synthesis and characterization of model amine building blocks from saturated fatty acids and simple amines such as diethylenetriamine (DETA) and Bis(3-aminopropyl)amine. The structure-property relationship of thermosets made from these model amines and Diglycidyl ether of bisphenol A (DGBEA) will be discussed.

Keywords: building block, amine, synthesis, characterization

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Authors: Aakansha Gupta, Neha Vadnere, Tapasvi Soni, M. Anbarsi

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Protein secondary structure prediction is one of the most important goals pursued by bioinformatics and theoretical chemistry; it is highly important in medicine and biotechnology. Some aspects of protein functions and genome analysis can be predicted by secondary structure prediction. This is used to help annotate sequences, classify proteins, identify domains, and recognize functional motifs. In this paper, we represent protein secondary structure as a mathematical model. To extract and predict the protein secondary structure from the primary structure, we require a set of parameters. Any constants appearing in the model are specified by these parameters, which also provide a mechanism for efficient and accurate use of data. To estimate these model parameters there are many algorithms out of which the most popular one is the EM algorithm or called the Expectation Maximization Algorithm. These model parameters are estimated with the use of protein datasets like RS126 by using the Bayesian Probabilistic method (data set being categorical). This paper can then be extended into comparing the efficiency of EM algorithm to the other algorithms for estimating the model parameters, which will in turn lead to an efficient component for the Protein Secondary Structure Prediction. Further this paper provides a scope to use these parameters for predicting secondary structure of proteins using machine learning techniques like neural networks and fuzzy logic. The ultimate objective will be to obtain greater accuracy better than the previously achieved.

Keywords: model parameters, expectation maximization algorithm, protein secondary structure prediction, bioinformatics

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Authors: Haidy S. Ghali, Engy Serag, A. Samer Ezeldin

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Copper is an essential raw material used in the construction industry. During the year 2021 and the first half of 2022, the global market suffered from a significant fluctuation in copper raw material prices due to the aftermath of both the COVID-19 pandemic and the Russia-Ukraine war, which exposed its consumers to an unexpected financial risk. Thereto, this paper aims to develop two ANN-LSTM price prediction models, using Python, that can forecast the average monthly copper prices traded in the London Metal Exchange; the first model is a multivariate model that forecasts the copper price of the next 1-month and the second is a univariate model that predicts the copper prices of the upcoming three months. Historical data of average monthly London Metal Exchange copper prices are collected from January 2009 till July 2022, and potential external factors are identified and employed in the multivariate model. These factors lie under three main categories: energy prices and economic indicators of the three major exporting countries of copper, depending on the data availability. Before developing the LSTM models, the collected external parameters are analyzed with respect to the copper prices using correlation and multicollinearity tests in R software; then, the parameters are further screened to select the parameters that influence the copper prices. Then, the two LSTM models are developed, and the dataset is divided into training, validation, and testing sets. The results show that the performance of the 3-Month prediction model is better than the 1-Month prediction model, but still, both models can act as predicting tools for diverse economic situations.

Keywords: copper prices, prediction model, neural network, time series forecasting

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Authors: Yalong Jiang, Zheru Chi

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In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, convolutional neural network, capsule network, capacity optimization, character recognition, data augmentation, semantic segmentation

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Authors: Sujeet Kumar Singh, Shiv Prasad Yadav

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This paper develops an approach for solving intuitionistic fuzzy linear fractional programming (IFLFP) problem where the cost of the objective function, the resources, and the technological coefficients are triangular intuitionistic fuzzy numbers. Here, the IFLFP problem is transformed into an equivalent crisp multi-objective linear fractional programming (MOLFP) problem. By using fuzzy mathematical programming approach the transformed MOLFP problem is reduced into a single objective linear programming (LP) problem. The proposed procedure is illustrated through a numerical example.

Keywords: triangular intuitionistic fuzzy number, linear programming problem, multi objective linear programming problem, fuzzy mathematical programming, membership function

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Authors: Xiuguo Zhao, He Li, Alireza Yazdani, Xiaoning Zheng, Xinxi Xu

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Wound infected poses a serious threat to the surgery on the patient during the process of surgery. Understanding the bacteria-carrying particles (BCPs) transportation and deposition in the open surgical wound model play essential role in protecting wound against being infected. Therefore BCPs transportation and deposition in the surgical wound model were investigated using force-coupling method (FCM) based computational fluid dynamics. The BCPs deposition in the wound was strongly associated with BCPs diameter and concentration. The results showed that the rise on the BCPs deposition was increasing not only with the increase of BCPs diameters but also with the increase of the BCPs concentration. BCPs deposition morphology was impacted by the combination of size distribution, airflow patterns and model geometry. The deposition morphology exhibited the characteristic with BCPs deposition on the sidewall in wound model and no BCPs deposition on the bottom of the wound model mainly because the airflow movement in one direction from up to down and then side created by laminar system constructing airflow patterns and then made BCPs hard deposit in the bottom of the wound model due to wound geometry limit. It was also observed that inertial impact becomes a main mechanism of the BCPs deposition. This work may contribute to next study in BCPs deposition limit, as well as wound infected estimation in surgical-site infections.

Keywords: BCPs deposition, computational fluid dynamics, force-coupling method (FCM), numerical simulation, open surgical wound model

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Authors: Maryam Gallab, Hafida Bouloiz, Youness Chater, Mohamed Tkiouat

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The aim of this paper is to present a model based on multi-agent systems in order to manage the maintenance activities and to ensure the reliability and availability of machines just with the required resources (operators, tools). The interest of the simulation is to solve the complexity of the system and to find results without cost or wasting time. An implementation of the model is carried out on the AnyLogic platform to display the defined performance indicators.

Keywords: maintenance, complexity, simulation, multi-agent systems, AnyLogic platform

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Authors: Assad Maalouf, Lunjin Lu, James Lynott

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We design and implement a precise model of string operations using finite state machine transformers and state transformers to approximate the values string variables can take throughout the execution of the program.We use our model to analyze Android program string variables. Our experimental results show that our string analysis is very efficient at detecting the contextual effect of string operations on the string variables. Our model proved to be very useful when it came to verifying statements about the string variables of the program.

Keywords: abstract interpretation, android, static analysis, string analysis

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Authors: Maryam Saeidi, Ehsan Motamedian, Seyed Abbas Shojaosadati

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Zymomonas mobilis is known as an example of the uncoupled growth phenomenon. This microorganism also has a unique metabolism that degrades glucose by the Entner–Doudoroff (ED) pathway. In this paper, a genome-scale metabolic model including 434 genes, 757 reactions and 691 metabolites was reconstructed to simulate uncoupled growth and study its effect on flux distribution in the central metabolism. The model properly predicted that ATPase was activated in experimental growth yields of Z. mobilis. Flux distribution obtained from model indicates that the major carbon flux passed through ED pathway that resulted in the production of ethanol. Small amounts of carbon source were entered into pentose phosphate pathway and TCA cycle to produce biomass precursors. Predicted flux distribution was in good agreement with experimental data. The model results also indicated that Z. mobilis metabolism is able to produce biomass with maximum growth yield of 123.7 g (mol glucose)-1 if ATP synthase is coupled with growth and produces 82 mmol ATP gDCW-1h-1. Coupling the growth and energy reduced ethanol secretion and changed the flux distribution to produce biomass precursors.

Keywords: genome-scale metabolic model, Zymomonas mobilis, uncoupled growth, flux distribution, ATP dissipation

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Authors: Yuliya E. Leshchenko, Tatyana S. Ostapenko

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Language variation is a widespread linguistic phenomenon which can affect different levels of a language system: phonological, morphological, lexical, syntactic, etc. It is obvious that the scope of possible standard alternations within a particular language is limited by a variety of its norms and regulations which set more or less clear boundaries for what is possible and what is not possible for the speakers. The possibility of lexical variation (alternate usage of lexical items within the same contexts) is based on the fact that the meanings of words are not clearly and rigidly defined in the consciousness of the speakers. Therefore, lexical variation is usually connected with unstable relationship between words and their referents: a case when a particular lexical item refers to different types of referents, or when a particular referent can be named by various lexical items. We assume that the scope of lexical variation in bilingual speech is generally wider than that observed in monolingual speech due to the fact that, besides ‘lexical item – referent’ relations it involves the possibility of cross-language variation of L1 and L2 lexical items. We use the term ‘cross-language variation’ to denote a case when two equivalent words of different languages are treated by a bilingual speaker as freely interchangeable within the common linguistic context. As distinct from code-switching which is traditionally defined as the conscious use of more than one language within one communicative act, in case of cross-language lexical variation the speaker does not perceive the alternate lexical items as belonging to different languages and, therefore, does not realize the change of language code. In the paper, the authors present research of lexical variation of adult Komi-Permyak – Russian bilingual speakers. The two languages co-exist on the territory of the Komi-Permyak District in Russia (Komi-Permyak as the ethnic language and Russian as the official state language), are usually acquired from birth in natural linguistic environment and, according to the data of sociolinguistic surveys, are both identified by the speakers as coordinate mother tongues. The experimental research demonstrated that alternation of Komi-Permyak and Russian words within one utterance/phrase is highly frequent both in speech perception and production. Moreover, our participants estimated cross-language word combinations like ‘маленькая /Russian/ нывка /Komi-Permyak/’ (‘a little girl’) or ‘мунны /Komi-Permyak/ домой /Russian/’ (‘go home’) as regular/habitual, containing no violation of any linguistic rules and being equally possible in speech as the equivalent intra-language word combinations (‘учöтик нывка’ /Komi-Permyak/ or ‘идти домой’ /Russian/). All the facts considered, we claim that constant concurrent use of the two languages results in the fact that a large number of their words tend to be intuitively interpreted by the speakers as lexical variants not only related to the same referent, but also referring to both languages or, more precisely, to none of them in particular. Consequently, we can suppose that bilingual mental lexicon includes an extensive ‘fused’ zone of lexical representations that provide the basis for cross-language variation in bilingual speech.

Keywords: bilingualism, bilingual mental lexicon, code-switching, lexical variation

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Authors: Mohd Yusri Ibrahim

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Although it is known that interpersonal skills are essential for personal development, the debate however continues as to how to measure those skills, especially in youths. This study was conducted to develop a measurement model of interpersonal skills by suggesting three construct namely personal, skills and relationship; six function namely self, perception, listening, conversation, emotion and conflict management; and 30 behaviours as indicators. This cross-sectional survey by questionnaires was applied in east side of peninsula of Malaysia for 150 respondents, and analyzed by structural equation modelling (SEM) by AMOS. The suggested constructs, functions and indicators were consider accepted as measurement elements by observing on regression weight for standard loading, average variance extracted (AVE) for convergent validity, square root of AVE for discriminant validity, composite reliability (CR), and at least three fit indexes for model fitness. Finally, a measurement model of interpersonal skill for youth was successfully developed.

Keywords: interpersonal communication, interpersonal skill, youth, communication skill

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Authors: Mohd Asrul Affedi, Nyi Nyi Naing

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Overdispersion is present in count data, and basically when a phenomenon happened, a Negative Binomial (NB) is commonly used to replace a standard Poisson model. Analysis of count data event, such as mortality cases basically Poisson regression model is appropriate. Hence, the model is not appropriate when existing a zero values. The zero-inflated negative binomial model is appropriate. In this article, we modelled the mortality cases as a dependent variable by age categorical. The objective of this study to determine existing overdispersion in mortality data of AIDS co-infection patients in Kelantan.

Keywords: negative binomial death rate, overdispersion, zero-inflation negative binomial death rate, AIDS

Procedia PDF Downloads 459

Authors: Hari Pulapaka

Abstract:

This paper defines and develops the notion of a traceability index for food and may be used by any consumer (restaurant, distributor, average consumer etc.). The concept is then extended to a region's food system as a way to measure how well a regional food system utilizes its own bounty or at least, is connected to its food sources. With increasing emphases on the sustainability of aspects of regional and ultimately, the global food system, it is reasonable to accept that if we know how close (in relative terms) an end-user of a set of ingredients (as they traverse through the maze of supply chains) is from the sources, we may be better equipped to evaluate the quality of the set as measured by any number of qualitative and quantitative criteria. We propose a mathematical model which may be adapted to a number of contexts and sizes. Two hypothetical cases of different scope are presented which highlight how the model works as an evaluator of steps between an end-user and the source(s) of the ingredients they consume. The variables in the model are flexible enough to be adapted to other applications beyond food systems.

Keywords: food, traceability, supply chain, mathematical model

Procedia PDF Downloads 270

Authors: L. Ramirez, E. Guillén, J. Sánchez

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Some of the main goals about telecare such as monitoring, treatment, telediagnostic are deployed with the integration of applications with specific appliances. In order to achieve a coherent model to integrate software, hardware, and healthcare systems, different telehealth models with Internet of Things (IoT), cloud computing, artificial intelligence, etc. have been implemented, and their advantages are still under analysis. In this paper, we propose an integrated model based on IoT architecture and cloud computing telehealth center. Analytics module is presented as a solution to control an ideal diagnostic about some diseases. Specific features are then compared with the recently deployed conventional models in telemedicine. The main advantage of this model is the availability of controlling the security and privacy about patient information and the optimization on processing and acquiring clinical parameters according to technical characteristics.

Keywords: analytics, telemedicine, internet of things, cloud computing

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Authors: Gamze Ozel, Selen Cakmakyapan

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We introduce a new model called the Marshall-Olkin Rayleigh distribution which extends the Rayleigh distribution using Marshall-Olkin transformation and has increasing and decreasing shapes for the hazard rate function. Various structural properties of the new distribution are derived including explicit expressions for the moments, generating and quantile function, some entropy measures, and order statistics are presented. The model parameters are estimated by the method of maximum likelihood and the observed information matrix is determined. The potentiality of the new model is illustrated by means of real life data set.

Keywords: Marshall-Olkin distribution, Rayleigh distribution, estimation, maximum likelihood

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Authors: Hossein Arzani, Masoud Jafari Shalamzari, Z. Arzani

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This paper follows FAO model of suitability analysis. Influential factors affecting extensive grazing were determined and converted into a model. Taleghan rangelands were examined for common types of grazing animals as an example. Advantages and limitations were elicited. All range ecosystems’ components affect range suitability but due to the time and money restrictions, the most important and feasible elements were investigated. From which three sub-models including water accessibility, forage production and erosion sensitivity were considered. Suitable areas in four levels of suitability were calculated using GIS. This suitability modeling approach was adopted due to its simplicity and the minimal time that is required for transforming and analyzing the data sets. Managers could be benefited from the model to devise the measures more wisely to cope with the limitations and enhance the rangelands health and condition.

Keywords: range suitability, land-use, extensive grazing, modeling, land evaluation

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Authors: H. Shokouhmand, H. Sobhani, B. Sajadi, M. Degheh

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In recent years, experimental and numerical investigation of water UV reactors has increased significantly. The main drawback of experimental methods is confined and expensive survey of UV reactors features. In this study, a CFD model utilizing the eulerian-lagrangian framework is applied to analysis the disinfection performance of a closed conduit reactor which contains four UV lamps perpendicular to the flow. A discrete ordinates (DO) model was employed to evaluate the UV irradiance field. To investigate the importance of each of lamps on the inactivation performance, in addition to the reference model (with 4 bright lamps), several models with one or two bright lamps in various arrangements were considered. All results were reported in three inactivation kinetics. The results showed that the log inactivation of the two central bright lamps model was between 88-99 percent, close to the reference model results. Also, whatever the lamps are closer to the main flow region, they have more effect on microbial inactivation. The effect of some operational parameters such as water flow rate, inlet water temperature, and lamps power were also studied.

Keywords: Eulerian-Lagrangian framework, inactivation kinetics, log inactivation, water UV reactor

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Authors: Hong-Ming Chen

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This work considers the resolution of the Hull and White interest rate model with the jump process. A deterministic process is adopted to model the random behavior of interest rate variation as deterministic perturbations, which is depending on the time t. The Brownian motion and jumps uncertainty are denoted as the integral functions piecewise constant function w(t) and point function θ(t). It shows that the interest rate function and the yield function of the Hull and White interest rate model with jump process can be obtained by solving a nonlinear semi-infinite programming problem. A relaxed cutting plane algorithm is then proposed for solving the resulting optimization problem. The method is calibrated for the U.S. treasury securities at 3-month data and is used to analyze several effects on interest rate prices, including interest rate variability, and the negative correlation between stock returns and interest rates. The numerical results illustrate that our approach essentially generates the yield functions with minimal fitting errors and small oscillation.

Keywords: optimization, interest rate model, jump process, deterministic

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Authors: Zhaoxin Luo, Michael Zhu

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In natural languages, there are always complex semantic hierarchies. Obtaining the feature representation based on these complex semantic hierarchies becomes the key to the success of the model. Several RNN models have recently been proposed to use latent indicators to obtain the hierarchical structure of documents. However, the model that only uses a single-layer latent indicator cannot achieve the true hierarchical structure of the language, especially a complex language like Chinese. In this paper, we propose a deep layered model that stacks arbitrarily many RNN layers equipped with latent indicators. After using EM and training it hierarchically, our model solves the computational problem of stacking RNN layers and makes it possible to stack arbitrarily many RNN layers. Our deep hierarchical model not only achieves comparable results to large pre-trained models on the Chinese short text classification problem but also achieves state of art results on the Chinese long text classification problem.

Keywords: nature language processing, recurrent neural network, hierarchical structure, document classification, Chinese

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Authors: Paul Dallyn, Ashraf El-Hamalawi, Alessandro Palmeri, Bob Knight

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In order to better understand the long term implications of the grout wear failure mode in large-diameter plain-sided grouted connections, a numerical model has been developed and calibrated that can take advantage of existing operational plant data to predict the wear accumulation for the actual load conditions experienced over a given period, thus limiting the need for expensive monitoring systems. This model has been derived and calibrated based on site structural condition monitoring (SCM) data and supervisory control and data acquisition systems (SCADA) data for two operational wind turbine generator substructures afflicted with this challenge, along with experimentally derived wear rates.

Keywords: grouted connection, numerical model, offshore structure, wear, wind energy

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Authors: Nafiseh Ebrahimi, Gautham Muthukumaran, Amir Jafari

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Human walking gait is considered to be the most efficient biped walking gait. There are various types of gait human follows during locomotion and arm swing is one of the most important factors which controls and differentiates human gaits. Earlier studies declared a 7% reduction in the metabolic cost due to the arm swing. In this research, we compared different types of arm swings in terms of metabolic cost reduction and then suggested, designed, fabricated and tested a quasi-passive upper body exoskeleton to study the metabolic cost reduction in the folded arm walking gate scenarios. Our experimental results validate a 10% reduction in the metabolic cost of walking aided by the application of the proposed exoskeleton.

Keywords: arm swing, MET (metabolic equivalent of a task), calorimeter, oxygen consumption, upper body quasi-passive exoskeleton

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Authors: D. Maneetham, L. Sivhour

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Robotic arm manipulators are widely used to accomplish many kinds of tasks. SCORBOT-ER 4u is a 5-degree of freedom (DOF) vertical articulated educational robotic arm, and all joints are revolute. It is specifically designed to perform pick and place task with its gripper. The pick and place task consists of consideration of the end effector coordinate of the robotic arm and the desired position coordinate in its workspace. This paper describes about forward kinematics modeling and analysis of the robotic end effector motion through joint space. The kinematics problems are defined by the transformation from the Cartesian space to the joint space. Denavit-Hartenberg (D-H) model is used in order to model the robotic links and joints with 4x4 homogeneous matrix. The forward kinematics model is also developed and simulated in MATLAB. The mathematical model is validated by using robotic toolbox in MATLAB. By using this method, it may be applicable to get the end effector coordinate of this robotic arm and other similar types to this arm. The software development of SCORBOT-ER 4u is also described here. PC-and EtherCAT based control technology from BECKHOFF is used to control the arm to express the pick and place task.

Keywords: forward kinematics, D-H model, robotic toolbox, PC- and EtherCAT-based control

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Authors: Ritu Raj, Hrishikesh Dubey

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This paper presents the results of the experimental investigations carried out on two intricate plan shaped buildings to evaluate aerodynamic performance of the building. The purpose is to study the associated environment arising due to wind forces in isolated and interference conditions on a model of scale 1:300 with a prototype having 180m height. Experimental tests were carried out at the boundary layer wind tunnel considering isolated conditions with 0° to 180° isolated wind directions and four interference conditions of twin building (separately for both the models). The research has been undertaken in Terrain Category-II, which is the most widely available terrain in India. A comparative assessment of the two models is performed out in an attempt to comprehend the various consequences of diverse conditions that may emerge in real-life situations, as well as the discrepancies amongst them. Experimental results of wind pressure coefficients of Model-1 and Model-2 shows good agreement with various wind incidence conditions with minute difference in the magnitudes of mean Cp. On the basis of wind tunnel studies, it is distinguished that the performance of Model-2 is better than Model-1in both isolated as well as interference conditions for all wind incidences and orientations respectively.

Keywords: interference factor, tall buildings, wind direction, mean pressure-coefficients

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Authors: Langa Hendrick Musawenkosi, Twala Bhekisipho

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The success or failure of students is a concern for every academic institution, college, university, governments and students themselves. Several approaches have been researched to address this concern. In this paper, a view is held that when a student enters a university or college or an academic institution, he or she enters an academic environment. The academic environment is unique concept used to develop the solution for making predictions effectively. This paper presents a model to determine the propensity of a student to succeed or fail in the French South African Schneider Electric Education Center (FSASEC) at the Vaal University of Technology (VUT). The Decision Tree algorithm is used to implement the model at FSASEC.

Keywords: FSASEC, academic environment model, decision trees, k-nearest neighbor, machine learning, popularity index, support vector machine

Procedia PDF Downloads 197