Search results for: fault tree analysis (FTA) method

Authors: I.J. Kim, B.C. Kim, J.H. Kim, C.-Y. Yi

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Heat transfer in a graphite calorimeter is analyzed by using the finite elements method. The calorimeter is modeled in 3D geometry. Quasi-adiabatic mode operation is realized in the simulation and the temperature rise by different sources of the ionizing radiation and electric heaters is compared, directly. The temperature distribution caused by the electric power was much different from that by the ionizing radiation because of its point-like localized heating. However, the temperature rise which was finally read by sensing thermistors agreed well to each other within 0.02 %.

Keywords: graphite calorimeter, finite element analysis, heat transfer, quasi-adiabatic mode

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Authors: Rafat Alshorman, Fadi Awawdeh

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By employing a simplified bilinear method, a class of generalized fifth-order KdV (gfKdV) equations which arise in nonlinear lattice, plasma physics and ocean dynamics are investigated. With the aid of symbolic computation, both solitary wave solutions and multiple-soliton solutions are obtained. These new exact solutions will extend previous results and help us explain the properties of nonlinear solitary waves in many physical models in shallow water. Parametric analysis is carried out in order to illustrate that the soliton amplitude, width and velocity are affected by the coefficient parameters in the equation.

Keywords: multiple soliton solutions, fifth-order evolution equations, Cole-Hopf transformation, Hirota bilinear method

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Authors: Byung Ho Jung, Dong Hoon Lim

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Logistic regression is a statistical method for analyzing a dataset in which there are one or more independent variables that determine an outcome. Logistic regression is used extensively in numerous disciplines, including the medical and social science fields. In this paper, we address the problem of estimating parameters in the logistic regression based on MapReduce framework with RHadoop that integrates R and Hadoop environment applicable to large scale data. There exist three learning algorithms for logistic regression, namely Gradient descent method, Cost minimization method and Newton-Rhapson's method. The Newton-Rhapson's method does not require a learning rate, while gradient descent and cost minimization methods need to manually pick a learning rate. The experimental results demonstrated that our learning algorithms using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also compared the performance of our Newton-Rhapson's method with gradient descent and cost minimization methods. The results showed that our newton's method appeared to be the most robust to all data tested.

Keywords: big data, logistic regression, MapReduce, RHadoop

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Authors: Igor Miňo, Lenka Lešková

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Over the past 80 years, open-field method has evolved as a commonly used tool for the analysis of animal behaviour. The study was carried out using 50 kennel-reared purebred puppies of the German Shepherd dog breed. All dogs were tested in 5^th, 7^th, and 9^th week of age. For the purpose of behavioural analysis, an open-field evaluation report was designed prior to testing to ensure the most convenient, rapid, and suitable way to assess selected behavioural patterns in field conditions. Onset of vocalisation, intensity of vocalisation, level of physical activity, response to sound, and overall behaviour was monitored in the study. Correlations between measures of height, weight and chest circumference, and behavioural characteristics in the 5^th, 7^th, and 9^th week of age were not statistically significant. Onset of vocalisation, intensity of vocalisation, level of physical activity and response to sound differed on statistically significant level between 5^th, 7^th, and 9^th week of age. Results suggest that our practical assessment report may be used as an applicable method to evaluate the suitability of service dog puppies for future working roles.

Keywords: dog, behaviour, open-field, testing

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Authors: Bita Payami-Shabestari, Dariush Eslami

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The purpose of this paper is to develop a multi-product economic production quantity model under vendor management inventory policy and restrictions including limited warehouse space, budget, and number of orders, average shortage time and maximum permissible shortage. Since the “costs” cannot be predicted with certainty, it is assumed that data behave under uncertain environment. The problem is first formulated into the framework of a bi-objective of multi-product economic production quantity model. Then, the problem is solved with three multi-objective decision-making (MODM) methods. Then following this, three methods had been compared on information on the optimal value of the two objective functions and the central processing unit (CPU) time with the statistical analysis method and the multi-attribute decision-making (MADM). The results are compared with statistical analysis method and the MADM. The results of the study demonstrate that augmented-constraint in terms of optimal value of the two objective functions and the CPU time perform better than global criteria, and goal programming. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The contribution of this research is the use of random costs data in developing a multi-product economic production quantity model under vendor management inventory policy with several constraints.

Keywords: economic production quantity, random cost, supply chain management, vendor-managed inventory

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Authors: Luisa Müting, Wisnu Harto Adiwijoyo

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Agroforestry systems transform the agricultural landscapes in the Sahel region of Africa, providing food and farming products consumed for subsistence or sold for income. In the incrementally dry climate of the Sahel region, the spreading of agroforestry practices is integral for policymaker efforts to counteract land degradation and provide soil restoration in the region. Several measures on agroforestry practices have been implemented in the region by governmental and non-governmental institutions in recent years. However, despite the efforts, past research shows that awareness of how policies and interventions are being consumed and perceived by the public remains low. Therefore, interpreting public policy dilemmas by analyzing the public perception regarding agroforestry concepts and practices is necessary. Public perceptions and discourses can be an essential driver or constraint for the adoption of agroforestry practices in the region. Thus, understanding the public discourse behavior of crucial stakeholders could assist policymakers in developing inclusive and contextual policies that are relevant to the context of agroforestry adoption in Sahel region. To answer how information about agroforestry spreads and is perceived by the public. As internet usage increased drastically over the past decade, reaching a share of 33 percent of the population being connected to the internet, this research is based on online conversation data. Social media data from Facebook are gathered daily between April 2021 and April 2022 in Djibouti, Senegal, Mali, and Nigeria based on their share of active internet users compared to other countries in the Sahel region. A systematic methodology was applied to the extracted social media using discourse network analysis (DNA). This study then clustered the data by the types of agroforestry practices, sentiments, and country. Additionally, this research extracted the text data from online news media during the same period to pinpoint events related to the topic of agroforestry. The preliminary result indicates that tree management, crops, and livestock integration, diversifying species and genetic resources, and focusing on interactions and productivity across the agricultural system; are the most notable keywords in agroforestry-related conversations within the four countries in the Sahel region. Additionally, approximately 84 percent of the discussions were still dominated by big actors, such as NGO or government actors. Furthermore, as a subject of communication within agroforestry discourse, the Great Green Wall initiative generates almost 60 percent positive sentiment within the captured social media data, effectively having a more significant outreach than general agroforestry topics. This study provides an understanding for scholars and policymakers with a springboard for further research or policy design on agroforestry in the four countries of the Sahel region with systematically uncaptured novel data from the internet.

Keywords: sahel, djibouti, senegal, mali, nigeria, social networks analysis, public discourse analysis, sentiment analysis, content analysis, social media, online news, agroforestry, land restoration

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Authors: Evangelos G. Karvelas, Christos Liosis, Andreas Theodorakakos, Theodoros E. Karakasidis

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In the present work, a numerical method for the estimation of the appropriate gradient magnetic fields for optimum driving of the particles into the desired area inside the human body is presented. The proposed method combines Computational Fluid Dynamics (CFD), Discrete Element Method (DEM) and Covariance Matrix Adaptation (CMA) evolution strategy for the magnetic navigation of nanoparticles. It is based on an iteration procedure that intents to eliminate the deviation of the nanoparticles from a desired path. Hence, the gradient magnetic field is constantly adjusted in a suitable way so that the particles’ follow as close as possible to a desired trajectory. Using the proposed method, it is obvious that the diameter of particles is crucial parameter for an efficient navigation. In addition, increase of particles' diameter decreases their deviation from the desired path. Moreover, the navigation method can navigate nanoparticles into the desired areas with efficiency approximately 99%.

Keywords: computational fluid dynamics, CFD, covariance matrix adaptation evolution strategy, discrete element method, DEM, magnetic navigation, spherical particles

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Authors: Seyed Abolhasan Naeini, M. Mortezaee

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Various factors such as the method of installation, the pile type, the pile material and the pile shape, can affect the final bearing capacity of a pile executed in the soil; among them, the method of installation is of special importance. The physical modeling is among the best options in the laboratory study of the piles behavior. Therefore, the current paper first presents and reviews the frustum confining vesel (FCV) as a suitable tool for physical modeling of deep foundations. Then, by describing the loading tests of two open-ended and closed-end steel piles, each of which has been performed in two methods, “with displacement" and "without displacement", the effect of end conditions and installation method on the final bearing capacity of the pile is investigated. The soil used in the current paper is silty sand of Firoozkooh. The results of the experiments show that in general the without displacement installation method has a larger bearing capacity in both piles, and in a specific method of installation the closed ended pile shows a slightly higher bearing capacity.

Keywords: physical modeling, frustum confining vessel, pile, bearing capacity, installation method

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Authors: Merve Yünlü, Nihat Kandemir, Aylin Ersoy

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Temperature sensors are used in home appliances not only to monitor the basic functions of the machine but also to minimize energy consumption and ensure safe operation. In parallel with the development of smart home applications and IoT algorithms, these sensors produce important data such as the frequency of use of the machine, user preferences, and the compilation of critical data in terms of diagnostic processes for fault detection throughout an appliance's operational lifespan. Commercially available thin-film resistive temperature sensors have a well-established manufacturing procedure that allows them to operate over a wide temperature range. However, these sensors are over-designed for white goods applications. The operating temperature range of these sensors is between -70°C and 850°C, while the temperature range requirement in home appliance applications is between 23°C and 500°C. To ensure the operation of commercial sensors in this wide temperature range, usually, a platinum coating of approximately 1-micron thickness is applied to the wafer. However, the use of platinum in coating and the high coating thickness extends the sensor production process time and therefore increases sensor costs. In this study, an attempt was made to develop a low-cost temperature sensor design and production method that meets the technical requirements of white goods applications. For this purpose, a custom design was made, and design parameters (length, width, trim points, and thin film deposition thickness) were optimized by using statistical methods to achieve the desired resistivity value. To develop thin film resistive temperature sensors, one side polished sapphire wafer was used. To enhance adhesion and insulation 100 nm silicon dioxide was coated by inductively coupled plasma chemical vapor deposition technique. The lithography process was performed by a direct laser writer. The lift-off process was performed after the e-beam evaporation of 10 nm titanium and 280 nm platinum layers. Standard four-point probe sheet resistance measurements were done at room temperature. The annealing process was performed. Resistivity measurements were done with a probe station before and after annealing at 600°C by using a rapid thermal processing machine. Temperature dependence between 25-300 °C was also tested. As a result of this study, a temperature sensor has been developed that has a lower coating thickness than commercial sensors but can produce reliable data in the white goods application temperature range. A relatively simplified but optimized production method has also been developed to produce this sensor.

Keywords: thin film resistive sensor, temperature sensor, household appliance, sustainability, energy efficiency

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Authors: Sergey A. Burikov, Tatiana A. Dolenko, Kirill A. Gushchin, Sergey A. Dolenko

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The paper presents the results of clusterization by Kohonen self-organizing maps (SOM) applied for analysis of array of Raman spectra of multi-component solutions of inorganic salts, for determination of types of salts present in the solution. It is demonstrated that use of SOM is a promising method for solution of clusterization and classification problems in spectroscopy of multi-component objects, as attributing a pattern to some cluster may be used for recognition of component composition of the object.

Keywords: Kohonen self-organizing maps, clusterization, multi-component solutions, Raman spectroscopy

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Authors: Yanping Liao, Congcong He, Ruigang Zhao

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The application of magnetocardiography signals to detect cardiac electrical function is a new technology developed in recent years. The magnetocardiography signal is detected with Superconducting Quantum Interference Devices (SQUID) and has considerable advantages over electrocardiography (ECG). It is difficult to extract Magnetocardiography (MCG) signal which is buried in the noise, which is a critical issue to be resolved in cardiac monitoring system and MCG applications. In order to remove the severe background noise, the Total Variation (TV) regularization method is proposed to denoise MCG signal. The approach transforms the denoising problem into a minimization optimization problem and the Majorization-minimization algorithm is applied to iteratively solve the minimization problem. However, traditional TV regularization method tends to cause step effect and lacks constraint adaptability. In this paper, an improved TV regularization method for denoising MCG signal is proposed to improve the denoising precision. The improvement of this method is mainly divided into three parts. First, high-order TV is applied to reduce the step effect, and the corresponding second derivative matrix is used to substitute the first order. Then, the positions of the non-zero elements in the second order derivative matrix are determined based on the peak positions that are detected by the detection window. Finally, adaptive constraint parameters are defined to eliminate noises and preserve signal peak characteristics. Theoretical analysis and experimental results show that this algorithm can effectively improve the output signal-to-noise ratio and has superior performance.

Keywords: constraint parameters, derivative matrix, magnetocardiography, regular term, total variation

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Authors: Hamid Nikzad, Shinta Yoshitomi

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In this paper, nonlinear static pushover analysis is performed on 15 storied RC building structure with a shear wall to evaluate the seismic performance of the building. Section sizes of the members are obtained based on structural optimization method utilizing MATLAB frame optimizer, then the structure is simulated and designed in ETABS program conforming ACI 318-14 design code. The pushover curve has been generated by pushing the top node of the structure to the limited target displacement. Members failure due to the formation of plastic hinges, considering shear wall-frame structure was observed and the result of this study is presented based on current regulation of FEMA356, ASCE7-10, and ACI 318-14 design criteria

Keywords: structural optimization, linear static analysis, ETABS, MATLAB, RC moment frame, RC shear wall structures

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Authors: A. Khernane, N. Khelil, L. Djerou

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The aim of this work is to study the numerical implementation of the Hilbert uniqueness method for the exact boundary controllability of Euler-Bernoulli beam equation. This study may be difficult. This will depend on the problem under consideration (geometry, control, and dimension) and the numerical method used. Knowledge of the asymptotic behaviour of the control governing the system at time T may be useful for its calculation. This idea will be developed in this study. We have characterized as a first step the solution by a minimization principle and proposed secondly a method for its resolution to approximate the control steering the considered system to rest at time T.

Keywords: boundary control, exact controllability, finite difference methods, functional optimization

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Authors: Han Xiao, Zhang Lei, Huang Hai, Lv Shizeng

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Space environment simulator is a device for spacecraft test. KM8 large space environment simulator built in Tianjing Space City is the largest as well as the most advanced space environment simulator in China. Large deviation of spacecraft level will lead to abnormally work of the thermal control device in spacecraft during the thermal vacuum test. In order to avoid thermal vacuum test failure, level adjusting mechanism system is developed in the KM8 large space environment simulator as one of the most important subsystems. According to the level adjusting requirements of spacecraft’s thermal vacuum tests, the four fulcrums adjusting model is established. By means of collecting level instruments and displacement sensors data, stepping motors controlled by PLC drive four supporting legs simultaneous movement. In addition, a PID algorithm is used to control the temperature of supporting legs and level instruments which long time work under the vacuum cold and black environment in KM8 large space environment simulator during thermal vacuum tests. Based on the above methods, the data acquisition and processing, the analysis and calculation, real time adjustment and fault alarming of the level adjusting mechanism system are implemented. The level adjusting accuracy reaches 1mm/m, and carrying capacity is 20 tons. Debugging showed that the level adjusting mechanism system of KM8 large space environment simulator can meet the thermal vacuum test requirement of the new generation spacecraft. The performance and technical indicators of the level adjusting mechanism system which provides important support for the development of spacecraft in China have been ahead of similar equipment in the world.

Keywords: space environment simulator, thermal vacuum test, level adjusting, spacecraft, parallel mechanism

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Authors: Cheng Zhang, James Marco, Walid Allafi, Truong Q. Dinh, W. D. Widanage

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Equivalent circuit models (ECMs) are widely used in battery management systems in electric vehicles and other battery energy storage systems. The battery dynamics and the model parameters vary under different working conditions, such as different temperature and state of charge (SOC) levels, and therefore online parameter identification can improve the modelling accuracy. This paper presents a way of online ECM parameter identification using a continuous time (CT) estimation method. The CT estimation method has several advantages over discrete time (DT) estimation methods for ECM parameter identification due to the widely separated battery dynamic modes and fast sampling. The presented method can be used for online SOC estimation. Test data are collected using a lithium ion cell, and the experimental results show that the presented CT method achieves better modelling accuracy compared with the conventional DT recursive least square method. The effectiveness of the presented method for online SOC estimation is also verified on test data.

Keywords: electric circuit model, continuous time domain estimation, linear integral filter method, parameter and SOC estimation, recursive least square

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Authors: Ming-Hsiang Shih, Wen-Pei Sung, Shih-Heng Tung

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The purposes of hydraulic gate are to maintain the functions of storing and draining water. It bears long-term hydraulic pressure and earthquake force and is very important for reservoir and waterpower plant. The high tensile strength of steel plate is used as constructional material of hydraulic gate. The cracks and rusts, induced by the defects of material, bad construction and seismic excitation and under water respectively, thus, the mechanics phenomena of gate with crack are probing into the cause of stress concentration, induced high crack increase rate, affect the safety and usage of hydroelectric power plant. Stress distribution analysis is a very important and essential surveying technique to analyze bi-material and singular point problems. The finite difference infinitely small element method has been demonstrated, suitable for analyzing the buckling phenomena of welding seam and steel plate with crack. Especially, this method can easily analyze the singularity of kink crack. Nevertheless, the construction form and deformation shape of some gates are three-dimensional system. Therefore, the three-dimensional Digital Image Correlation (DIC) has been developed and applied to analyze the strain variation of steel plate with crack at weld joint. The proposed Digital image correlation (DIC) technique is an only non-contact method for measuring the variation of test object. According to rapid development of digital camera, the cost of this digital image correlation technique has been reduced. Otherwise, this DIC method provides with the advantages of widely practical application of indoor test and field test without the restriction on the size of test object. Thus, the research purpose of this research is to develop and apply this technique to monitor mechanics crack variations of weld steel hydraulic gate and its conformation under action of loading. The imagines can be picked from real time monitoring process to analyze the strain change of each loading stage. The proposed 3-Dimensional digital image correlation method, developed in the study, is applied to analyze the post-buckling phenomenon and buckling tendency of welded steel plate with crack. Then, the stress intensity of 3-dimensional analysis of different materials and enhanced materials in steel plate has been analyzed in this paper. The test results show that this proposed three-dimensional DIC method can precisely detect the crack variation of welded steel plate under different loading stages. Especially, this proposed DIC method can detect and identify the crack position and the other flaws of the welded steel plate that the traditional test methods hardly detect these kind phenomena. Therefore, this proposed three-dimensional DIC method can apply to observe the mechanics phenomena of composite materials subjected to loading and operating.

Keywords: welded steel plate, crack variation, three-dimensional digital image correlation (DIC), crack stel plate

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Authors: Hyun-Kyu Cho, Jun-Su Kim, Choon-Geun Huh, Geon Lee Young-Chul Park

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In this study, the relationship between flow properties and fluid projection distance look into connection for shape variations of foam monitor. A numerical analysis technique for fluid analysis of a foam monitor was developed for the prediction. Shape of foam monitor the flow path of fluid flow according to the shape, The fluid losses were calculated from flow analysis result.. The modified model used the length increase model of the flow path, and straight line of the model. Inlet pressure was 7 [bar] and external was atmosphere codition. am. The results showed that the length increase model of the flow path and straight line of the model was improved in the nozzle projection distance.

Keywords: injection performance, finite element method, foam monitor, Projection distance

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Authors: Seyed Abolhasan Naeini, Saeideh Mohammadi

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Time dependent settlement due to loading on soft saturated soils produces many problems such as high consolidation settlements and low consolidation rates. Also, long term consolidation settlement of soft soil underlying the embankment leads to unpredicted settlements and cracks on soil surface. Preloading method is an effective improvement method to solve this problem. Using vertical drains in preloading method is an effective method for improving soft soils. Applying deep soil mixing method on soft soils is another effective method for improving soft soils. There are little studies on using two methods of preloading and deep soil mixing simultaneously. In this paper, the concurrent effect of preloading with deep soil mixing by vertical drains is investigated through a finite element code, Plaxis2D. The influence of parameters such as deep soil mixing columns spacing, existence of vertical drains and distance between them, on settlement and stability factor of safety of embankment embedded on soft soil is investigated in this research.

Keywords: preloading, soft soil, vertical drains, deep soil mixing, consolidation settlement

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Authors: S. Mamoucha, J. Rahul, N. Christodoulakis

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Introduction: Nature has been the source of medicinal agents since the dawn of the human existence on Earth. Currently, millions of people, in the developing world, rely on medicinal plants for primary health care, income generation and lifespan improvement. In Greece, more than 5500 plant taxa are reported while about 250 of them are considered to be of great pharmaceutical importance. Among the plants used for medical purposes, Vitex agnus-castus L. (Verbenaceae) is known since ancient times. It is a small tree or shrub, widely distributed in the Mediterranean basin up to the Central Asia. It is also known as chaste tree or monks pepper. Theophrastus mentioned the shrub several times, as ‘agnos’ in his ‘Enquiry into Plants’. Dioscorides mentioned the use of V. agnus-castus for the stimulation of lactation in nursing mothers and the treatment of several female disorders. The plant has important medicinal properties and a long tradition in folk medicine as an antimicrobial, diuretic, digestive and insecticidal agent. Materials and methods: Leaves were cleaned, detached, fixed, sectioned and investigated with light and Scanning Electron Microscopy (SEM). Histochemical tests were executed as well. Specific histochemical reagents (osmium tetroxide, H2SO4, vanillin/HCl, antimony trichloride, Wagner’ s reagent, Dittmar’ s reagent, potassium bichromate, nitroso reaction, ferric chloride and di methoxy benzaldehyde) were used for the sub cellular localization of secondary metabolites. Results: Light microscopical investigations of the elongated leaves of V. agnus-castus revealed three layers of palisade parenchyma, just below the single layered adaxial epidermis. The spongy parenchyma is rather loose. Adaxial epidermal cells are larger in magnitude, compared to those of the abaxial epidermis. Four different types of capitate, secreting trichomes, were localized among the abaxial epidermal cells. Stomata were observed at the abaxial epidermis as well. SEM revealed the interesting arrangement of trichomes. Histochemical treatment on fresh and plastic embedded tissue sections revealed the nature and the sites of secondary metabolites accumulation (flavonoids, steroids, terpenes). Acknowledgment: This work was supported by IKY - State Scholarship Foundation, Athens, Greece.

Keywords: Vitex agnus-castus, leaf anatomy, histochemical reagents, secondary metabolites

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Authors: Melissa Ramirez, Mohammad Awal

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The Inflow Performance Relationship (IPR) of a well is a relation between the oil production rate and flowing bottom-hole pressure. This relationship is an important tool for petroleum engineers to understand and predict the well performance. In the petroleum industry, IPR correlations are used to design and evaluate well completion, optimizing well production, and designing artificial lift. The most commonly used IPR correlations models are Vogel and Wiggins, these models are applicable to homogeneous and isotropic reservoir data. In this work, a new IPR model is developed to determine inflow performance relationship of oil wells in a naturally fracture reservoir. A 3D black-oil reservoir simulator is used to develop the oil mobility function for the studied reservoir. Based on simulation runs, four flow rates are run to record the oil saturation and calculate the relative permeability for a naturally fractured reservoir. The new method uses the result of a well test analysis along with permeability and pressure-volume-temperature data in the fluid flow equations to obtain the oil mobility function. Comparisons between the new method and two popular correlations for non-fractured reservoirs indicate the necessity for developing and using an IPR correlation specifically developed for a fractured reservoir.

Keywords: inflow performance relationship, mobility function, naturally fractured reservoir, well test analysis

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Authors: Charles Lee

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The Principal Orthogonal Decomposition (POD) technique has been used as a model reduction tool for many applications in engineering and science. In principle, one begins with an ensemble of data, called snapshots, collected from an experiment or laboratory results. The beauty of the POD technique is that when applied, the entire data set can be represented by the smallest number of orthogonal basis elements. It is the such capability that allows us to reduce the complexity and dimensions of many physical applications. Mathematical formulations and numerical schemes for the POD method will be discussed along with applications in NASA’s Deep Space Large Antenna Arrays, Satellite Image Reconstruction, Cancer Detection with DNA Microarray Data, Maximizing Stock Return, and Medical Imaging.

Keywords: reduced-order methods, principal component analysis, cancer detection, image reconstruction, stock portfolios

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Authors: Abdolreza Memari

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In this article in order to estimate the viscosity of crude oil,a numerical method has been used. We use this method to measure the crude oil's viscosity for 3 states: Saturated oil's viscosity, viscosity above the bubble point and viscosity under the saturation pressure. Then the crude oil's viscosity is estimated by using KHAN model and roller ball method. After that using these data that include efficient conditions in measuring viscosity, the estimated viscosity by the presented method, a radial based neural method, is taught. This network is a kind of two layered artificial neural network that its stimulation function of hidden layer is Gaussian function and teaching algorithms are used to teach them. After teaching radial based neural network, results of experimental method and artificial intelligence are compared all together. Teaching this network, we are able to estimate crude oil's viscosity without using KHAN model and experimental conditions and under any other condition with acceptable accuracy. Results show that radial neural network has high capability of estimating crude oil saving in time and cost is another advantage of this investigation.

Keywords: viscosity, Iranian crude oil, radial based, neural network, roller ball method, KHAN model

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Authors: K. Passbakhsh

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Determination of reinforcement forces is one of the most important and main discussions in designing retaining walls. By determining these forces we refrain from conservative planning. By numerically modeling the reinforced soil retaining walls under dynamic loading reinforcement forces can be calculated. In this study we try to approach the gained forces by pseudo-static method according to FHWA code and gained forces from numerical modeling by finite element method, by selecting seismic horizontal coefficient for different wall height. PLAXIS software was used for numerical analysis. Then the effect of reinforcement stiffness and soil type on reinforcement forces is examined.

Keywords: reinforced soil, PLAXIS, reinforcement forces, retaining walls

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Authors: L. I. Izhar, T. Stathaki, K. Howell

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Analyzing and interpreting of thermograms have been increasingly employed in the diagnosis and monitoring of diseases thanks to its non-invasive, non-harmful nature and low cost. In this paper, a novel system is proposed to improve diagnosis and monitoring of morphoea skin disorder based on integration with the published lines of Blaschko. In the proposed system, image registration based on global and local registration methods are found inevitable. This paper presents a modified normalized gradient cross-correlation (NGC) method to reduce large geometrical differences between two multimodal images that are represented by smooth gray edge maps is proposed for the global registration approach. This method is improved further by incorporating an iterative-based normalized cross-correlation coefficient (NCC) method. It is found that by replacing the final registration part of the NGC method where translational differences are solved in the spatial Fourier domain with the NCC method performed in the spatial domain, the performance and robustness of the NGC method can be greatly improved. It is shown in this paper that the hybrid NGC method not only outperforms phase correlation (PC) method but also improved misregistration due to translation, suffered by the modified NGC method alone for thermograms with ill-defined jawline. This also demonstrates that by using the gradients of the gray edge maps and a hybrid technique, the performance of the PC based image registration method can be greatly improved.

Keywords: Blaschko’s lines, image registration, morphoea, thermal imaging

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Authors: Shantosa Yudha Siswanto, Rachmat Harryanto

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The aim of the research was to investigate the effect of land use and slope steepness on soil erodibility index. The research was conducted from September to December 2013 in Mekarwangi catchment area, sub watershed of Cikapundung Hulu, Indonesia. The study was carried out using descriptive method. Physiographic free survey method was used as survey method, it was a survey based on land physiographic appearance. Soil sampling was carried out into transect on the similarity of slope without calculating the range between points of observation. Soil samples were carried onto three classes of land use such as: forest, plantation and dry cultivation area. Each land use consists of three slope classes such as: 8-15%, 16-25%, and 26-40% class. Five samples of soil were taken from each of them, resulting 45 points of observation. The result of the research showed that type of land use and slope classes gave different effect on soil erodibility. The highest C-organic and permeability was found on forest with slope 16-25%. Slope of 8-15% with forest land use give the lowest effect on soil erodibility.

Keywords: land use, slope, erodibility, erosion

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Authors: J. J. Vargas, N. Prieto, L. A. Toro

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Control charts are commonly used to monitor processes involving either variable or attribute of quality characteristics and determining the control limits as a critical task for quality engineers to improve the processes. Nonetheless, in some applications it is necessary to include an estimation of efficiency. In this paper, the ability to define the efficiency of an industrial process was added to a control chart by means of incorporating a data envelopment analysis (DEA) approach. In depth, a Bayesian estimation was performed to calculate the posterior probability distribution of parameters as means and variance and covariance matrix. This technique allows to analyse the data set without the need of using the hypothetical large sample implied in the problem and to be treated as an approximation to the finite sample distribution. A rejection simulation method was carried out to generate random variables from the parameter functions. Each resulting vector was used by stochastic DEA model during several cycles for establishing the distribution of each efficiency measures for each DMU (decision making units). A control limit was calculated with model obtained and if a condition of a low level efficiency of DMU is presented, system efficiency is out of control. In the efficiency calculated a global optimum was reached, which ensures model reliability.

Keywords: data envelopment analysis, DEA, Multivariate control chart, rejection simulation method

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Authors: Emmanuel Iyamuremye, Jean François Maniriho, Irenee Ndayambaje

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Mathematics is the foundational enabling discipline that underpins science, technology, and engineering disciplines. Science, technology, engineering, and mathematics (STEM) subjects are foreseen as the engine for socio-economic transformation. Rwanda has done reforms in education aiming at empowering and preparing students for the real world job by providing career pathways in science, technology, engineering, and mathematics related fields. While that considered so, the performance in mathematics has remained deplorable in both formative and national examinations. Therefore, this paper aims at exploring the extent to which the engage, explore, explain, elaborate and evaluate (5Es) instructional model contributing towards students’ achievement in mathematics. The present study adopted the pre-test, post-test non-equivalent control group quasi-experimental design. The 5Es instructional model was applied to the experimental group while the control group received instruction with the conventional teaching method for eight weeks. One research-made instrument, mathematics achievement test (MAT), was used for data collection. A pre-test was given to students before the intervention to make sure that both groups have equivalent characteristics. At the end of the experimental period, the two groups have undergone a post-test to ascertain the contribution of the 5Es instructional model. Descriptive statistics and analysis of covariance (ANCOVA) were used for the analysis of the study. For determining the improvement in mathematics, Hakes methods of calculating gain were used to analyze the pre-test and post-test scores. Results showed that students exposed to 5Es instructional model achieved significantly better performance in mathematics than students instructed using the conventional teaching method. It was also found that 5Es instructional model made lessons more interesting, easy and created friendship among students. Thus, 5Es instructional model was recommended to be adopted as a close substitute to the conventional teaching method in teaching mathematics in lower secondary schools in Rwanda.

Keywords: 5Es instructional model, achievement, conventional teaching method, mathematics

Procedia PDF Downloads 90

Authors: Yezli-Touiker Samira, Amrani-Kirane Leila, Soltani Mazouni Nadia

Abstract:

Due to secondary effects of conventional insecticides on the environment, the agrochemical research has resulted in the discovery of novel molecules. That research work will help in the development of a new group of pesticides that may be cheaper and less hazardous to the environment and non-target organisms which is the main desired outcome of the present work. Angiotensin-converting enzyme as a target for the development of novel insect growth regulators. Captopril is an inhibitor of angiotensin converting enzyme (ACE) it was tested in vivo by topical application on reproduction of Ephestia kuehniella Zeller (Lepidoptera: Pyralidae). The compound is diluted in acetone and applied topically to newly emerged pupae (10µg/ 2µl). The effects of this molecule was studied,on the biochemistry of ovary (on amounts nucleic acid, proteins, the qualitative analysis of the ovarian proteins and the reproductive potential (duration of the pre-oviposition, duration of the oviposition, number of eggs laid and hatching percentage). Captopril reduces significantly quantity of ovarian proteins and nucleic acid. The electrophoresis profile reveals the absence of tree bands at the treated series. This molecule reduced the duration of the oviposition period, the fecundity and the eggviability.

Keywords: environment, ephestia kuehniella, captopril, reproduction, the agrochemical research

Procedia PDF Downloads 264

Authors: Donggun Lee, Q-Han Park

Abstract:

Due to its coarse grid, the Pseudo-Spectral Time Domain (PSTD) method has advantages against the Finite Difference Time Domain (FDTD) method in terms of memory requirement and operation time. However, since the efficiency of parallelization is much lower than that of FDTD, PSTD is not a useful method for a large-scale electromagnetic simulation in a parallel platform. In this paper, we propose the parallelization technique of the hybrid PSTD-FDTD (HPF) method which simultaneously possesses the efficient parallelizability of FDTD and the quick speed and low memory requirement of PSTD. Parallelization cost of the HPF method is exactly the same as the parallel FDTD, but still, it occupies much less memory space and has faster operation speed than the parallel FDTD. Experiments in distributed memory systems have shown that the parallel HPF method saves up to 96% of the operation time and reduces 84% of the memory requirement. Also, by combining the OpenMP library to the MPI library, we further reduced the operation time of the parallel HPF method by 50%.

Keywords: FDTD, hybrid, MPI, OpenMP, PSTD, parallelization

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Authors: Joon-Hyung Kim, Him-Chan Lee, Jin-Hyuk Kim, Yong-Kab Lee, Young-Seok Choi

Abstract:

The crude oil in an oil well exists in various phases such as gas, seawater, and sand, as well as oil. Therefore, a phase separator is needed at the front of a single-phase pump for pressurization and transfer. On the other hand, the application of a multiphase pump can provide such advantages as simplification of the equipment structure and cost savings, because there is no need for a phase separation process. Therefore, the crude oil transfer method using a multiphase pump is being applied to recently developed oil wells. Due to this increase in demand, technical demands for the development of multiphase pumps are sharply increasing, but the progress of research into related technologies is insufficient, due to the nature of multiphase pumps that require high levels of skills. This study was conducted to verify the reliability of pump performance evaluation using numerical analysis, which is the basis of the development of a multiphase pump. For this study, a model was designed by selecting the specifications of the pump under study. The performance of the designed model was evaluated through numerical analysis and experiment, and the results of the performance evaluation were compared to verify the reliability of the result using numerical analysis.

Keywords: multiphase pump, numerical analysis, experiment, performance evaluation, reliability verification

Procedia PDF Downloads 410