Search results for: optimized closed polygonal segment method

Authors: Patricia M. B. Saint-Vincent, Anna Furches, Stephanie Galanie, Erica Teixeira Prates, Piet Jones, Nancy Engle, David Kainer, Wellington Muchero, Daniel Jacobson, Timothy J. Tschaplinski

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Uridine diphosphate-glycosyltransferases (UGTs) are enzymes that catalyze sugar transfer to a variety of plant metabolites. UGT substrates, which include plant secondary metabolites involved in lignification, demonstrate new activities and incorporation when glycosylated. Knowledge of UGT function, substrate specificity, and enzyme products is important for plant engineering efforts, especially related to increasing plant biomass through lignification. UGTs in Populus trichocarpa, a biofuel feedstock, and model woody plant, were selected from a pool of gene candidates using rapid prioritization strategies. A functional genomics workflow, consisting of a metabolite genome-wide association study (mGWAS), expression of synthetic codon-optimized genes, and high-throughput biochemical assays with mass spectrometry-based analysis, was developed for determining the substrates and products of previously-uncharacterized enzymes. A total of 40 UGTs from P. trichocarpa were profiled, and the biochemical assay results were compared to predicted mGWAS connections. Assay results confirmed seven of 11 leaf mGWAS associations and demonstrated varying levels of substrate specificity among candidate UGTs. P. trichocarpa UGT substrate processing confirms the role of these newly-characterized enzymes in lignan, flavonoid, and phytohormone metabolism, with potential implications for cell wall biosynthesis, nitrogen uptake, and biotic and abiotic stress responses.

Keywords: Populus, metabolite-gene associations, GWAS, bio feedstocks, glycosyltransferase

Procedia PDF Downloads 107

Authors: Nevena Jakovčević Stor, Ivan Slapničar

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Any polynomial can be expressed as a characteristic polynomial of a complex symmetric arrowhead matrix. This expression is not unique. If the polynomial is real with only real distinct roots, the matrix can be chosen as real. By using accurate forward stable algorithm for computing eigen values of real symmetric arrowhead matrices we derive a forward stable algorithm for computation of roots of such polynomials in O(n^2 ) operations. The algorithm computes each root to almost full accuracy. In some cases, the algorithm invokes extended precision routines, but only in the non-iterative part. Our examples include numerically difficult problems, like the well-known Wilkinson’s polynomials. Our algorithm compares favorably to other method for polynomial root-finding, like MPSolve or Newton’s method.

Keywords: roots of polynomials, eigenvalue decomposition, arrowhead matrix, high relative accuracy

Procedia PDF Downloads 409

Authors: Chih-Jer Lin, Jian-Hong Hou

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Industry 4.0 is a vision of integrated industry implemented by artificial intelligent computing, software, and Internet technologies. The main goal of industry 4.0 is to deal with the difficulty owing to competitive pressures in the marketplace. For today’s manufacturing factories, the type of production is changed from mass production (high quantity production with low product variety) to medium quantity-high variety production. To offer flexibility, better quality control, and improved productivity, robot manipulators are used to combine material processing, material handling, and part positioning systems into an integrated manufacturing system. To implement the automated system for sheet metal bending operations, motion planning of a 7-degrees of freedom (DOF) robot is studied in this paper. A virtual reality (VR) environment of a bending cell, which consists of the robot and a bending machine, is established using the virtual robot experimentation platform (V-REP) simulator. For sheet metal bending operations, the robot only needs six DOFs for the pick-and-place or tracking tasks. Therefore, this 7 DOF robot has more DOFs than the required to execute a specified task; it can be called a redundant robot. Therefore, this robot has kinematic redundancies to deal with the task-priority problems. For redundant robots, Pseudo-inverse of the Jacobian is the most popular motion planning method, but the pseudo-inverse methods usually lead to a kind of chaotic motion with unpredictable arm configurations as the Jacobian matrix lose ranks. To overcome the above problem, we proposed a method to formulate the motion planning problems as optimization problem. Moreover, a genetic algorithm (GA) based method is proposed to deal with motion planning of the redundant robot. Simulation results validate the proposed method feasible for motion planning of the redundant robot in an automated sheet-metal bending operations.

Keywords: redundant robot, motion planning, genetic algorithm, obstacle avoidance

Procedia PDF Downloads 142

Authors: Zulfikar Dinar Wahidayat Putra

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Water scarcity become a major challenge in an arid area. One of the arid areas is La Serena city in the Northern Chile which become a case study of this paper. Based on that, this paper tries to identify a sustainable water system by using urban harvest approach as a method to achieve water self-sufficiency for a neighborhood area in the La Serena city. By using the method, it is possible to create sustainable water system in the neighborhood area by reducing up to 38% of water demand and 94% of wastewater production even though water self-sufficient cannot be fully achieved, because of its dependency to the drinking water supply from water treatment plant of La Serena city.

Keywords: arid area, sustainable water system, urban harvest approach, self-sufficiency

Procedia PDF Downloads 256

Authors: Gerald Gwamba, Bo Zhou, Yajun Song, Dong Changyin

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The challenges that sand production presents to the oil and gas industry, particularly while working in poorly consolidated reservoirs, cannot be overstated. From restricting production to blocking production tubing, sand production increases the costs associated with production as it elevates the cost of servicing production equipment over time. Production in reservoirs that present with high viscosities, flow rate, cementation, clay content as well as fine sand contents is even more complex and challenging. As opposed to the one-factor at a-time testing, investigating the interactive effects arising from a combination of several factors offers increased reliability of results as well as representation of actual field conditions. It is thus paramount to investigate the conditions leading to the onset of sanding during production to ensure the future sustainability of hydrocarbon production operations under viscous conditions. We adopt the Design of Experiments (DOE) to analyse, using Taguchi factorial designs, the most significant interactive effects of sanding. We propose an optimized regression model to predict the drawdown time at sand production. The results obtained underscore that reservoirs characterized by varying (high and low) levels of viscosity, flow rate, cementation, clay, and fine sand content have a resulting impact on sand production. The only significant interactive effect recorded arises from the interaction between BD (fine sand content and flow rate), while the main effects included fluid viscosity and cementation, with percentage significances recorded as 31.3%, 37.76%, and 30.94%, respectively. The drawdown time model presented could be useful for predicting the time to reach the maximum drawdown pressure under viscous conditions during the onset of sand production.

Keywords: factorial designs, DOE optimization, sand production prediction, drawdown time, regression model

Procedia PDF Downloads 144

Authors: Le Hieu Giang, Truong Nguyen Luan Vu, Le Linh

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In this paper, the analytical tuning rules of IMC-PID controller are presented for the multivariable Smith predictor that involved the ideal decoupling. Accordingly, the decoupler is first introduced into the multivariable Smith predictor control system by a well-known approach of ideal decoupling, which is compactly extended for general nxn multivariable processes and the multivariable Smith predictor controller is then obtained in terms of the multiple single-loop Smith predictor controllers. The tuning rules of PID controller in series with filter are found by using Maclaurin approximation. Many multivariable industrial processes are employed to demonstrate the simplicity and effectiveness of the presented method. The simulation results show the superior performances of presented method in compared with the other methods.

Keywords: ideal decoupler, IMC-PID controller, multivariable smith predictor, Padé approximation

Procedia PDF Downloads 408

Authors: R. Devicharan

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In a short span 3D Printing is expected to play a vital role in our life. The possibility of creativity and speed in manufacturing through various 3D printing processes is infinite. This study is performed on the FDM (Fused Deposition Modelling) method of 3D printing, which is one of the pre-dominant methods of 3D printing technologies. This study focuses on physical properties of the objects produced by 3D printing which determine the applications of the 3D printed objects. This paper specifically aims at the study of the tensile strength and the folding endurance of the 3D printed objects through the FDM (Fused Deposition Modelling) method using the ABS (Acronitirile Butadiene Styrene) and PLA (Poly Lactic Acid) plastic materials. The study is performed on a controlled environment and the specific machine settings. Appropriate tables, graphs are plotted and research analysis techniques will be utilized to analyse, verify and validate the experiment results.

Keywords: FDM process, 3D printing, ABS for 3D printing, PLA for 3D printing, rapid prototyping

Procedia PDF Downloads 592

Authors: Raghvendra Singh Yadav, Ivo Kuřitka, Jaromir Havlica, Zuzana Kozakova, Jiri Masilko, Lukas Kalina, Miroslava Hajdúchová, Vojtěch Enev, Jaromir Wasserbauer

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In this work, we investigated the structural and magnetic properties of CoFe2O4:Nd3+/Dy3+/Pr3+/Gd3+ nanoparticles synthesized by starch-assisted sol-gel combustion method. X-ray diffraction pattern confirmed the formation of cubic spinel structure of rare-earth ions (Nd3+, Dy3+, Pr3+, Gd3+) doped CoFe2O4 spinel ferrite nanoparticles. Raman and Fourier Transform Infrared spectroscopy study also confirmed cubic spinel structure of rare-earth ions (Nd3+, Dy3+, Pr3+, Gd3+) substituted CoFe2O4 nanoparticles. The field emission scanning electron microscopy study revealed the effect of annealing temperature on size of rare-earth ions (Nd3+, Dy3+, Pr3+, Gd3+) substituted CoFe2O4 nanoparticles and particles were in the range of 10-100 nm. The magnetic properties of rare-earth ions (Nd3+, Dy3+, Pr3+, Gd3+) substituted CoFe2O4 nanoparticles were investigated by using vibrating sample magnetometer. The variation in saturation magnetization, coercivity and remanent magnetization with annealing temperature/ particle size of rare-earth ions (Nd3+, Dy3+, Pr3+, Gd3+) substituted CoFe2O4 nanoparticles was observed. Acknowledgment: This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic – Program NPU I (LO1504).

Keywords: starch, sol-gel combustion method, rare-earth ions, spinel ferrite nanoparticles, magnetic properties

Procedia PDF Downloads 345

Authors: N. K. Chougule, G. V. Parishwad

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The pin fin heat sink is a novel heat transfer device to transfer large amount of heat through with very small temperature differences and it also possesses large uniform cooling characteristics. Pin fins are widely used as elements that provide increased cooling for electronic devices. Increasing demands regarding the performance of such devices can be observed due to the increasing heat production density of electronic components. For this reason, extensive work is being carried out to select and optimize pin fin elements for increased heat transfer. In this paper, the effects of design parameters and the optimum design parameters for a Pin-Fin heat sink (PFHS) under multi-jet impingement case with thermal performance characteristics have been investigated by using Taguchi methodology based on the L9 orthogonal arrays. Various design parameters, such as pin-fin array size, gap between nozzle exit to impingement target surface (Z/d) and air velocity are explored by numerical experiment. The average convective heat transfer coefficient is considered as the thermal performance characteristics. The analysis of variance (ANOVA) is applied to find the effect of each design parameter on the thermal performance characteristics. Then the results of confirmation test with the optimal level constitution of design parameters have obviously shown that this logic approach can effective in optimizing the PFHS with the thermal performance characteristics. The analysis of the Taguchi method reveals that, all the parameters mentioned above have equal contributions in the performance of heat sink efficiency. Experimental results are provided to validate the suitability of the proposed approach.

Keywords: Pin Fin Heat Sink (PFHS), Taguchi method, CFD, thermal performance

Procedia PDF Downloads 245

Authors: Gonzalez Carlos, Martinez Fransisco

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The creation of a seismic prediction model that considers all the regional variations and perfectly adjusts its results to the response spectra is very complicated. To achieve statistically acceptable results, it is necessary to process a sufficiently robust data set, and even if high efficiencies are achieved, this model will only work properly in this region. However, when using it in other regions, differences are found due to different parameters that have not been calibrated to other regions, such as the site effect. The fact that impedance contrasts, as well as other factors belonging to the site, have a great influence on the local response is well known, which is why this work, using the residual method, is intended to establish a regional calibration of the corresponding parameters site effect for the Spain region in the global GMPM BSSA 14.

Keywords: GMPM, seismic prediction equations, residual method, response spectra, impedance contrast

Procedia PDF Downloads 79

Authors: Saad M. Darwish, Mohamed A. El-Iskandarani, Guitar M. Shawkat

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Nowadays, the amount of available multimedia data is continuously on the rise. The need to find a required image for an ordinary user is a challenging task. Content based image retrieval (CBIR) computes relevance based on the visual similarity of low-level image features such as color, textures, etc. However, there is a gap between low-level visual features and semantic meanings required by applications. The typical method of bridging the semantic gap is through the automatic image annotation (AIA) that extracts semantic features using machine learning techniques. In this paper, a multi-label image annotation system guided by Firefly and Bayesian method is proposed. Firstly, images are segmented using the maximum variance intra cluster and Firefly algorithm, which is a swarm-based approach with high convergence speed, less computation rate and search for the optimal multiple threshold. Feature extraction techniques based on color features and region properties are applied to obtain the representative features. After that, the images are annotated using translation model based on the Net Bayes system, which is efficient for multi-label learning with high precision and less complexity. Experiments are performed using Corel Database. The results show that the proposed system is better than traditional ones for automatic image annotation and retrieval.

Keywords: feature extraction, feature selection, image annotation, classification

Procedia PDF Downloads 579

Authors: Zhenqiu Liu

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Visualizing the heterogeneity within cell-populations for single-cell RNA-seq data is crucial for studying the functional diversity of a cell. However, because of the high level of noises, outlier, and dropouts, it is very challenging to measure the cell-to-cell similarity (distance), visualize and cluster the data in a low-dimension. Minimum volume embedding (MVE) projects the data into a lower-dimensional space and is a promising tool for data visualization. However, it is computationally inefficient to solve a semi-definite programming (SDP) when the sample size is large. Therefore, it is not applicable to single-cell RNA-seq data with thousands of samples. In this paper, we develop an efficient algorithm with an accelerated proximal gradient method and visualize the single-cell RNA-seq data efficiently. We demonstrate that the proposed approach separates known subpopulations more accurately in single-cell data sets than other existing dimension reduction methods.

Keywords: single-cell RNA-seq, minimum volume embedding, visualization, accelerated proximal gradient method

Procedia PDF Downloads 222

Authors: Jen-Yuan Wang, Min-Chuan Wang, Der-Jun Jan

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Polymer electrolytes can be classified into four major categories, solid polymer electrolytes (SPEs), gel polymer electrolytes (GPEs), polyelectrolytes and composite polymer electrolytes. SPEs suffer from low ionic conductivity at room temperature. The main problems for GPEs are the poor thermal stability and mechanical properties. In this study, a GPE containing PMMA and succinonitrile is prepared to solve the problems mentioned above, and applied to the assembly of a quasi-solid-state electrochromic device (ECD). In the polymer electrolyte, poly(methyl methacrylate) (PMMA) is the polymer matrix and propylene carbonate (PC) is used as the plasticizer. To enhance the mechanical properties of this GPE, succinonitrile (SN) is introduced as the additive. For the electrochromic materials, tungsten oxide (WO3) is used as the cathodic coloring film, which is fabricated by pulsed dc magnetron reactive sputtering. For the anodic coloring material, Prussian blue nanoparticles (PBNPs) are synthesized and coated on the transparent Sn-doped indium oxide (ITO) glass. The thickness of ITO, WO3 and PB film is 110, 170 and 200 nm, respectively. The size of the ECD is 5×5 cm2. The effect of the introduction of SN into the GPEs is discussed by observing the electrochromic behaviors of the WO3-PB ECD. Besides, the composition ratio of PC to SN is also investigated by measuring the ionic conductivity. The optimized ratio of PC to SN is 4:1, and the ionic conductivity under this condition is 6.34x10-5 S∙cm-1, which is higher than that of PMMA/PC (1.35x10-6 S∙cm-1) and PMMA/EC/PC (4.52x10-6 S∙cm-1). This quasi-solid-state ECD fabricated with the PMMA/SN based GPE shows an optical contrast of ca. 53% at 690 nm. The optical transmittance of the ECD can be reversibly modulated from 72% (bleached) to 19% (darkened), by applying potentials of 1.5 and -2.2 V, respectively. During the durability test, the optical contrast of this ECD remains 44.5% after 2400 cycles, which is 83% of the original one.

Keywords: electrochromism, tungsten oxide, prussian blue, poly(methyl methacrylate), succinonitrile

Procedia PDF Downloads 288

Authors: Jong-Jy Shyu, Soo-Chang Pei, Yun-Da Huang

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In this paper, design of wide-range variable fractional-delay (WR-VFD) finite impulse response (FIR) digital filters is proposed. With respect to the conventional VFD filter which is designed such that its delay is adjustable within one unit, the proposed VFD FIR filter is designed such that its delay can be tunable within a wider range. By the traces of coefficients of the fractional-delay FIR filter, it is found that the conventional method of polynomial substitution for filter coefficients no longer satisfies the design demand, and the circuits perform the sinc function (sinc converter) are added to overcome this problem. In this paper, least-squares method is adopted to design WR-VFD FIR filter. Throughout this paper, several examples will be proposed to demonstrate the effectiveness of the presented methods.

Keywords: digital filter, FIR filter, variable fractional-delay (VFD) filter, least-squares approximation

Procedia PDF Downloads 487

Authors: Safia Rabaaoui, Héla Hachicha, Ezzeddine Zagrouba

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Nowadays, cloud computing is becoming the more popular technology to various companies and consumers, which benefit from its increased efficiency, cost optimization, data security, unlimited storage capacity, etc. One of the biggest challenges of cloud computing is resource allocation. Its efficiency directly influences the performance of the whole cloud environment. Finding an effective method to address these critical issues and increase cloud performance was necessary. This paper proposes a mobile agents-based framework for dynamic resource allocation in cloud computing to minimize both the cost of using virtual machines and the makespan. Furthermore, its impact on the best response time and power consumption has been studied. The simulation showed that our method gave better results than here.

Keywords: cloud computing, multi-agent system, mobile agent, dynamic resource allocation, cost, makespan

Procedia PDF Downloads 92

Authors: Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Kensuke Nakamura, Dongeun Choi, Byung-Woo Hong

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Artefacts are commonly encountered in the imaging process of clinical computed tomography (CT) where the artefact refers to any systematic discrepancy between the reconstructed observation and the true attenuation coefficient of the object. It is known that CT images are inherently more prone to artefacts due to its image formation process where a large number of independent detectors are involved, and they are assumed to yield consistent measurements. There are a number of different artefact types including noise, beam hardening, scatter, pseudo-enhancement, motion, helical, ring, and metal artefacts, which cause serious difficulties in reading images. Thus, it is desired to remove nuisance factors from the degraded image leaving the fundamental intrinsic information that can provide better interpretation of the anatomical and pathological characteristics. However, it is considered as a difficult task due to the high dimensionality and variability of data to be recovered, which naturally motivates the use of machine learning techniques. We propose an image restoration algorithm based on the deep neural network framework where the denoising auto-encoders are stacked building multiple layers. The denoising auto-encoder is a variant of a classical auto-encoder that takes an input data and maps it to a hidden representation through a deterministic mapping using a non-linear activation function. The latent representation is then mapped back into a reconstruction the size of which is the same as the size of the input data. The reconstruction error can be measured by the traditional squared error assuming the residual follows a normal distribution. In addition to the designed loss function, an effective regularization scheme using residual-driven dropout determined based on the gradient at each layer. The optimal weights are computed by the classical stochastic gradient descent algorithm combined with the back-propagation algorithm. In our algorithm, we initially decompose an input image into its intrinsic representation and the nuisance factors including artefacts based on the classical Total Variation problem that can be efficiently optimized by the convex optimization algorithm such as primal-dual method. The intrinsic forms of the input images are provided to the deep denosing auto-encoders with their original forms in the training phase. In the testing phase, a given image is first decomposed into the intrinsic form and then provided to the trained network to obtain its reconstruction. We apply our algorithm to the restoration of the corrupted CT images by the artefacts. It is shown that our algorithm improves the readability and enhances the anatomical and pathological properties of the object. The quantitative evaluation is performed in terms of the PSNR, and the qualitative evaluation provides significant improvement in reading images despite degrading artefacts. The experimental results indicate the potential of our algorithm as a prior solution to the image interpretation tasks in a variety of medical imaging applications. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: auto-encoder neural network, CT image artefact, deep learning, intrinsic image representation, noise reduction, total variation

Procedia PDF Downloads 186

Authors: Alia Alghosoun, Nabil El Moçayd, Mohammed Seaid

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Modeling dam-break flows over non-flat beds requires an accurate representation of the topography which is the main source of uncertainty in the model. Therefore, developing robust and accurate techniques for reconstructing topography in this class of problems would reduce the uncertainty in the flow system. In many hydraulic applications, experimental techniques have been widely used to measure the bed topography. In practice, experimental work in hydraulics may be very demanding in both time and cost. Meanwhile, computational hydraulics have served as an alternative for laboratory and field experiments. Unlike the forward problem, the inverse problem is used to identify the bed parameters from the given experimental data. In this case, the shallow water equations used for modeling the hydraulics need to be rearranged in a way that the model parameters can be evaluated from measured data. However, this approach is not always possible and it suffers from stability restrictions. In the present work, we propose an adaptive optimal control technique to numerically identify the underlying bed topography from a given set of free-surface observation data. In this approach, a minimization function is defined to iteratively determine the model parameters. The proposed technique can be interpreted as a fractional-stage scheme. In the first stage, the forward problem is solved to determine the measurable parameters from known data. In the second stage, the adaptive control Ensemble Kalman Filter is implemented to combine the optimality of observation data in order to obtain the accurate estimation of the topography. The main features of this method are on one hand, the ability to solve for different complex geometries with no need for any rearrangements in the original model to rewrite it in an explicit form. On the other hand, its achievement of strong stability for simulations of flows in different regimes containing shocks or discontinuities over any geometry. Numerical results are presented for a dam-break flow problem over non-flat bed using different solvers for the shallow water equations. The robustness of the proposed method is investigated using different numbers of loops, sensitivity parameters, initial samples and location of observations. The obtained results demonstrate high reliability and accuracy of the proposed techniques.

Keywords: erodible beds, finite element method, finite volume method, nonlinear elasticity, shallow water equations, stresses in soil

Procedia PDF Downloads 126

Authors: Hayder H. Kareem

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Groundwater recharge is a crucial parameter for any groundwater management system. The variability of the recharge rates and the difficulty in estimating this factor in many processes by direct observation leads to the complexity of estimating the recharge value. Various methods are existing to estimate the groundwater recharge, with some limitations for each method to be able for application. This paper focuses particularly on a real study area, Al-Najaf City, Iraq. In this city, there are few groundwater aquifers, but the aquifer which is considered in this study is the closest one to the ground surface, the Dibdibba aquifer. According to the Aridity Index, which is estimated in the paper, Al-Najaf City is classified as a region located in an arid climate, and this identified that the most appropriate method to estimate the groundwater recharge is Thornthwaite's formula or Thornthwaite's method. From the calculations, the estimated average groundwater recharge over the period 1980-2014 for Al-Najaf City is 40.32 mm/year. Groundwater recharge is completely affected the groundwater table level (groundwater head). Therefore, to make sure that this value of recharge is true, the MODFLOW program has been used to apply this value through finding the relationship between the calculated and observed heads where a groundwater model for the Al-Najaf City study area has been built by MODFLOW to simulate this area for different purposes, one of these purposes is to simulate the groundwater recharge. MODFLOW results show that this value of groundwater recharge is extremely high and needs to be reduced. Therefore, a further sensitivity test has been carried out for the Al-Najaf City study area by the MODFLOW program through changing the recharge value and found that the best estimation of groundwater recharge value for this city is 16.5 mm/year where this value gives the best fitting between the calculated and observed heads with minimum values of RMSE % (13.175) and RSS m² (1454).

Keywords: Al-Najaf City, groundwater modelling, recharge estimation, visual MODFLOW

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Authors: Anastasia K. Eleftheriadou, Athanasios Sfetsos, Nikolaos Gounaris

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The present work examines the suitability of a seasonal forecasting model downscaled with a very high spatial resolution in order to assess the energy performance and requirements of buildings. The application of the developed model is applied on Greece for a period and with a forecast horizon of 5 months in the future. Greece, as a country in the middle of a financial crisis and facing serious societal challenges, is also very sensitive to climate changes. The commonly used method for the correlation of climate change with the buildings energy consumption is the concept of Degree Days (DD). This method can be applied to heating and cooling systems for a better management of environmental, economic and energy crisis, and can be used as medium (3-6 months) planning tools in order to predict the building needs and country’s requirements for residential energy use.

Keywords: downscaled seasonal models, degree days, energy performance

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Authors: R. Harman Dwi, Ryan Avirsa, P. Abraham Ivan

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Understanding of temperatures in the past, present, and future temperatures can be possible to do by analysis abundance of fossil foraminifera. This research was conducted in Sambipitu Formation, Ngalang River, Nglipar, Gunung Kidul Regency. The research method is divided into 3 stages: 1) study of literature, research based on previous researchers, 2) spatial, observation and sampling every 5-10 meters, 3) descriptive, analyzing samples consisting of a 10-gram sample weight, washing sample using 30% peroxide, biostratigraphy analysis, paleotemperature analysis using abundance of fossil, diversity analysis using Simpson diversity index method, and comparing current temperature data. There are two phases based on the appearance of Globorotalia menardii and Pulleniatina obliqueculata pointed to Phase Tropical Area, and the appearance of fossil Globigerinoides ruber and Orbulina universa fossil shows the phase of Subtropical Area. Paleotemperatur based on the appearance of Globorotalia menardii, Globigerinoides trilobus, Globigerinoides ruber, Orbulina universa, and Pulleniatina obliqueculata pointed to Warm Water Area and Warm Water Area (average surface water approximate 25°C).

Keywords: abundance, biostratigraphy, Simpson diversity index method, paleotemperature

Procedia PDF Downloads 167

Authors: Hamed Seddighi Khavidak

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Voluntary work has a lot of economic and social benefits for a country, but the economic value is ignored because it is voluntary. The aim of this study is reviewing Monetary Value of Voluntary Work methods and comparing opportunity cost method and replacement cost method both in theory and in practice. Beside monetary value, in this study, we discuss cost-benefit analysis of health and safety plan in the New Year that conducted by young volunteers of Red Crescent society of Iran. Method: We discussed eight methods for monetary value of voluntary work including: Alternative-Employment Wage Approach, Leisure-Adjusted OCA, Volunteer Judgment OCA, Replacement Wage Approach, Volunteer Judgment RWA, Supervisor Judgment RWA, Cost of Counterpart Goods and Services and Beneficiary Judgment. Also, for cost benefit analysis we drew on 'value audit and volunteer investment' (VIVA) technique that is used widely in voluntary organizations like international federation of Red Cross and Red Crescent societies. Findings: In this study, using replacement cost approach, voluntary work by 1034 youth volunteers was valued 938000000 Riyals and using Replacement Wage Approach it was valued 2268713232 Riyals. Moreover, Yazd Red Crescent Society spent 212800000 Riyals on food and other costs for these volunteers. Discussion and conclusion: In this study, using cost benefit analysis method that is Volunteer Investment and Value Audit (VIVA), VIVA rate showed that for every Riyal that the Red Crescent Society invested in the health and safety of New Year's travelers in its volunteer project, four Riyals returned, and using the wage replacement approach, 11 Riyals returned. Therefore, New Year's travelers health and safety project were successful and economically, it was worthwhile for the Red Crescent Society because the output was much bigger than the input costs.

Keywords: voluntary work, monetary value, youth, red crescent society

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Authors: P. Ahuja, K. S. S. Sai Krishna

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There is a concern over the energy shortage in the modern societies as it is one of the primary necessities. Renewable energy, mainly biomass, is found to be one feasible solution as it is inexhaustible and clean energy source all over the world. Out of various methods, thermo chemical conversion is considered to be the most common and convenient method to extract energy from biomass. The thermo-chemical methods that are employed are gasification, liquefaction and combustion. On gasification biomass yields biogas, on liquefaction biomass yields bio-oil and on combustion biomass yields bio-char. Any attempt to biomass gasification, liquefaction or combustion calls for a good understanding of biomass pyrolysis. So, Irrespective of the method used the first step towards the thermo-chemical treatment of biomass is pyrolysis. Pyrolysis mainly converts the solid mass into liquid with gas and residual char as the byproducts. Liquid is used for the production of heat, power and many other chemicals whereas the gas and char can be used as fuels to generate heat.

Keywords: biomass, fluidisation, pyrolysis, simulation

Procedia PDF Downloads 334

Authors: Shreya Thusoo, Karan Modi, Ankit Kumar Jha, Rajesh Kumar

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Since the evolution of computational tools and simulation software, there has been considerable increase in research on Soil Structure Interaction (SSI) to decrease the computational time and increase accuracy in the results. To aid the designer with a proper understanding of the response of structure in different soil types, the presented paper compares the deformation, shear stress, acceleration and other parameters of multi-storey building for a specific input ground motion using Response-spectrum Analysis (RSA) method. The response of all the models of different heights have been compared in different soil types. Finite Element Simulation software, ANSYS, has been used for all the computational purposes. Overall, higher response is observed with SSI, while it increases with decreasing stiffness of soil.

Keywords: soil-structure interaction, response spectrum, analysis, finite element method, multi-storey buildings

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Authors: Soheir Mohamed Hegazy

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Culture sustainability, which reflects a deep respect for people and history, is a cause of concern in contemporary architecture. Adopting ultramodern architecture styles was initiated in the 20th century by a plurality of states worldwide. Only a few countries, including Oman, realized that fashionable architectural designs ignore cultural values, identity, the context of its environment, economic perspective, and social performance. Stirring the Sultanate of Oman from being a listless and closed community to a modern country started in the year 1970. Despite unprecedented development in all aspects of Omani people's life, the leadership and the public had the capability to adjust to the changing global challenges without compromising social values and identity. This research provides a close analysis of one of the recent examples of contemporary vernacular architecture in the Sultanate of Oman, as a case study, Oman International Airport. The said airport gained an international appreciation for its Omani-themed architecture, distinguished traveler experience, and advanced technology. Accordingly, it was selected by the World Travel Awards as the Best Tourism Development Project in the Middle East only four weeks afterward after starting its operation. This paper aims to transfer this successful design approach of integrating the latest trends in technology, systems, eco-friendly aspects, and materials with the traditional Omani architectural features, which reflects symbiotic harmony of the community, individuals, and environment to other countries, designers, researchers, and students. In addition, the paper aims to encourage architects and teachers to take responsibility for valorizing built heritage as a source of inspiration for modern architecture, which could be considered as an added value. The work depends on reviewing the relevant literature, a case study, interviews with two architects who were involved in the project’s site work, and one current high-ranking employee in the airport besides data analysis and conclusion.

Keywords: contemporary vernacular architecture, culture sustainability, Oman international airport, current Omani architecture type

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Authors: Shrikrishna Mishra, Badri Yadav

Abstract:

In this complex society of today where experiences are innumerable and varied, it is not at all possible to present every situation in its original colors hence the opportunities for learning by actual experiences always are not at all possible. It is only through the use of proper audio visual aids that the life situation can be trough in the class room by an enlightened teacher in their simplest form and representing the original to the highest point of similarity which is totally absent in the verbal or lecture method. In the presence of audio aids, the attention is attracted interest roused and suitable atmosphere for proper understanding is automatically created, but in the existing traditional method greater efforts are to be made in order to achieve the aforesaid essential requisite. Inspire of the best and sincere efforts on the side of the teacher the net effect as regards understanding or learning in general is quite negligible.

Keywords: Audio-Visual Aids, the secondary school teaching, complex society, audio

Procedia PDF Downloads 476

Authors: Oumaima Khlifati, Khadija Baba

Abstract:

Pavement distress is the main factor responsible for the deterioration of road structure durability, damage vehicles, and driver comfort. Transportation agencies spend a high proportion of their funds on pavement monitoring and maintenance. The auscultation of pavement distress was based on the manual survey, which was extremely time consuming, labor intensive, and required domain expertise. Therefore, the automatic distress detection is needed to reduce the cost of manual inspection and avoid more serious damage by implementing the appropriate remediation actions at the right time. Inspired by recent deep learning applications, this paper proposes an algorithm for automatic road distress detection and classification using on the Deep Convolutional Neural Network (DCNN). In this study, the types of pavement distress are classified as transverse or longitudinal cracking, alligator, pothole, and intact pavement. The dataset used in this work is composed of public asphalt pavement images. In order to learn the structure of the different type of distress, the DCNN models are trained and tested as a multi-label classification task. In addition, to get the highest accuracy for our model, we adjust the structural optimization hyper parameters such as the number of convolutions and max pooling, filers, size of filters, loss functions, activation functions, and optimizer and fine-tuning hyper parameters that conclude batch size and learning rate. The optimization of the model is executed by checking all feasible combinations and selecting the best performing one. The model, after being optimized, performance metrics is calculated, which describe the training and validation accuracies, precision, recall, and F1 score.

Keywords: distress pavement, hyperparameters, automatic classification, deep learning

Procedia PDF Downloads 81

Authors: H. Elgubbi, A. Mlitan, A. Alzridy

Abstract:

Ninhydrin is the most well known spray reagent for identification of amino acids. Spring with Ninhydrin as a non-specific reagent is well-known and widely used for its remarkable high sensitivity. Using Ninhydrin reagent alone to detect amino acid on thin layer chromatography (TLA) paper is not advisable due to its lower sensitivity. A new spray reagent, Stannus chloride solution (Sn CL2) has been used to detect amino acids on filtter paper (witman 14) and TLC paper, silica Gel, 60 F254 TLC Aluminium Sheet 20x20cm Merck- Germany. Also, modified TLC pre-staining method was used, which only consisted of 3 steps: spotting, separating and color. The improved method was rapid and inexpensive and the results obtained were clear and reliable. In addition, it is suitable for screening different amino acid.

Keywords: amino acid, ninhydrin, modified ninhydrin reagent, stannus chloride reagent, thin-layer chromatography (TLC), TLC pre-staining

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Authors: Nuo Duan, Yi Pik Cheng

Abstract:

This paper presents the data of a series of two-dimensional Discrete Element Method (DEM) simulations of a large-diameter rigid monopile subjected to cyclic loading under a high gravitational force. At present, monopile foundations are widely used to support the tall and heavy wind turbines, which are also subjected to significant from wind and wave actions. A safe design must address issues such as rotations and changes in soil stiffness subject to these loadings conditions. Design guidance on the issue is limited, so are the availability of laboratory and field test data. The interpretation of these results in sand, such as the relation between loading and displacement, relies mainly on empirical correlations to pile properties. Regarding numerical models, most data from Finite Element Method (FEM) can be found. They are not comprehensive, and most of the FEM results are sensitive to input parameters. The micro scale behaviour could change the mechanism of the soil-structure interaction. A DEM model was used in this paper to study the cyclic lateral loads behaviour. A non-dimensional framework is presented and applied to interpret the simulation results. The DEM data compares well with various set of published experimental centrifuge model test data in terms of lateral deflection. The accumulated permanent pile lateral displacements induced by the cyclic lateral loads were found to be dependent on the characteristics of the applied cyclic load, such as the extent of the loading magnitudes and directions.

Keywords: cyclic loading, DEM, numerical modelling, sands

Procedia PDF Downloads 316

Authors: Abderrahmane Kechich, Othmane Abdelkhalek

Abstract:

Static converters behave as nonlinear loads that inject harmonic currents into the grid and increase the consumption of the inactive power. On the other hand, the increased use of sensitive equipment requires the application of sinusoidal voltages. As a result, the electrical power quality control has become a major concern in the field of power electronics. In this context, the active power conditioner (UPQC) was developed. It combines both serial and parallel structures; the series filter can protect sensitive loads and compensate for voltage disturbances such as voltage harmonics, voltage dips or flicker when the shunt filter compensates for current disturbances such as current harmonics, reactive currents and imbalance. This double feature is that it is one of the most appropriate devices. Calculating parameters is an important step and in the same time it’s not easy for that reason several researchers based on trial and error method for calculating parameters but this method is not easy for beginners researchers especially what about the controller’s parameters, for that reason this paper gives a mathematical way to calculate of almost all of UPQC parameters away from trial and error method. This paper gives also a new approach for calculating of PI regulators parameters for purpose to have a stable UPQC able to compensate for disturbances acting on the waveform of line voltage and load current in order to improve the electrical power quality.

Keywords: UPQC, Shunt active filer, series active filer, PI controller, PWM control, dual-loop control

Procedia PDF Downloads 395

Authors: Chia-Hau Liu, Tai-Yue Wang

Abstract:

Traditional multivariate control charts assume that measurement from manufacturing processes follows a multivariate normal distribution. However, this assumption may not hold or may be difficult to verify because not all the measurement from manufacturing processes are normal distributed in practice. This study develops a new multivariate control chart for monitoring the processes with non-normal data. We propose a mechanism based on integrating the one-class classification method and the adaptive technique. The adaptive technique is used to improve the sensitivity to small shift on one-class classification in statistical process control. In addition, this design provides an easy way to allocate the value of type I error so it is easier to be implemented. Finally, the simulation study and the real data from industry are used to demonstrate the effectiveness of the propose control charts.

Keywords: multivariate control chart, statistical process control, one-class classification method, non-normal data

Procedia PDF Downloads 417