Search results for: data structure
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30015

Search results for: data structure

29955 Synthesis, Structure and Properties of NZP/NASICON Structured Materials

Authors: E. A. Asabina, V. I. Pet'kov, P. A. Mayorov, A. V. Markin, N. N. Smirnova, A. M. Kovalskii, A. A. Usenko

Abstract:

The purpose of this work was to synthesize and investigate phase formation, structure and thermophysical properties of the phosphates M0.5+xM'xZr2–x(PO4)3 (M – Cd, Sr, Pb; M' – Mg, Co, Mn). The compounds were synthesized by sol-gel method. The results showed formation of limited solid solutions of NZP/NASICON type. The crystal structures of triple phosphates of the compositions MMg0.5Zr1.5(PO4)3 were refined by the Rietveld method using XRD data. Heat capacity (8–660 K) of the phosphates Pb0.5+xMgxZr2-x(PO4)3 (x = 0, 0.5) was measured, and reversible polymorphic transitions were found at temperatures, close to the room temperature. The results of Rietveld structure refinement showed the polymorphism caused by disordering of lead cations in the cavities of NZP/NASICON structure. Thermal expansion (298−1073 K) of the phosphates MMg0.5Zr1.5(PO4)3 was studied by XRD method, and the compounds were found to belong to middle and low-expanding materials. Thermal diffusivity (298–573 K) of the ceramic samples of phosphates slightly decreased with temperature increasing. As was demonstrated, the studied phosphates are characterized by the better thermophysical characteristics than widespread fire-resistant materials, such as zirconia and etc.

Keywords: NASICON, NZP, phosphate, structure, synthesis, thermophysical properties

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29954 Analysis Of Magnetic Anomaly Data For Identification Subsurface Structure Geothermal Manifestations Area Candi Umbul, Grabag, Magelang, Central Java Province, Indonesia

Authors: Ikawati Wulandari

Abstract:

Acquisition of geomagnetic field has been done at Geothermal manifestation Candi Umbul, Grabag, Magelang, Central Java Province on 10-12 May 2013. The purpose of this research to study sub-surface structure condition and the structure which control the hot springs manifestation. The research area have size of 1,5 km x 2 km and measurement spacing of 150 m. Total magnetic field data, the position, and the north pole direction have acquired by Proton Precession Magnetometer (PPM), Global Positioning System (GPS), and of geology compass, respectively. The raw data has been processed and performed using IGRF (International Geomagnetics Reference Field) correction to obtain total field magnetic anomaly. Upward continuation was performed at 100 meters height using software Magpick. Analysis conclude horizontal position of the body causing anomaly which is located at hot springs manifestation, and it stretch along Northeast - Southwest, which later interpreted as normal fault. This hotsprings manifestation was controlled by the downward fault which becomes a weak zone where hot water from underground the geothermal reservoir leakage

Keywords: PPM, Geothermal, Fault, Grabag

Procedia PDF Downloads 423
29953 Introduction of the Fluid-Structure Coupling into the Force Analysis Technique

Authors: Océane Grosset, Charles Pézerat, Jean-Hugh Thomas, Frédéric Ablitzer

Abstract:

This paper presents a method to take into account the fluid-structure coupling into an inverse method, the Force Analysis Technique (FAT). The FAT method, also called RIFF method (Filtered Windowed Inverse Resolution), allows to identify the force distribution from local vibration field. In order to only identify the external force applied on a structure, it is necessary to quantify the fluid-structure coupling, especially in naval application, where the fluid is heavy. This method can be decomposed in two parts, the first one consists in identifying the fluid-structure coupling and the second one to introduced it in the FAT method to reconstruct the external force. Results of simulations on a plate coupled with a cavity filled with water are presented.

Keywords: aeroacoustics, fluid-structure coupling, inverse methods, naval, turbulent flow

Procedia PDF Downloads 488
29952 Identification of Bayesian Network with Convolutional Neural Network

Authors: Mohamed Raouf Benmakrelouf, Wafa Karouche, Joseph Rynkiewicz

Abstract:

In this paper, we propose an alternative method to construct a Bayesian Network (BN). This method relies on a convolutional neural network (CNN classifier), which determinates the edges of the network skeleton. We train a CNN on a normalized empirical probability density distribution (NEPDF) for predicting causal interactions and relationships. We have to find the optimal Bayesian network structure for causal inference. Indeed, we are undertaking a search for pair-wise causality, depending on considered causal assumptions. In order to avoid unreasonable causal structure, we consider a blacklist and a whitelist of causality senses. We tested the method on real data to assess the influence of education on the voting intention for the extreme right-wing party. We show that, with this method, we get a safer causal structure of variables (Bayesian Network) and make to identify a variable that satisfies the backdoor criterion.

Keywords: Bayesian network, structure learning, optimal search, convolutional neural network, causal inference

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29951 The Effect of Environmental, Social, and Governance (ESG) Disclosure on Firms’ Credit Rating and Capital Structure

Authors: Heba Abdelmotaal

Abstract:

This paper explores the impact of the extent of a company's environmental, social, and governance (ESG) disclosure on credit rating and capital structure. The analysis is based on a sample of 202 firms from the 350 FTSE firms over the period of 2008-2013. ESG disclosure score is measured using Proprietary Bloomberg score based on the extent of a company's Environmental, Social, and Governance (ESG) disclosure. The credit rating is measured by The QuiScore, which is a measure of the likelihood that a company will become bankrupt in the twelve months following the date of calculation. The Capital Structure is measured by long term debt ratio. Two hypotheses are test using panel data regression. The results suggested that the higher degree of ESG disclosure leads to better credit rating. There is significant negative relationship between ESG disclosure and the long term debit percentage. The paper includes implications for the transparency which is resulting of the ESG disclosure could support the Monitoring Function. The monitoring role of disclosure is the increasing in the transparency of the credit rating agencies, also it could affect on managers’ actions. This study provides empirical evidence on the material of ESG disclosure on credit ratings changes and the firms’ capital decision making.

Keywords: capital structure, credit rating agencies, ESG disclosure, panel data regression

Procedia PDF Downloads 336
29950 Assessment of the Two-Way Relationship between Capital Structure and Operation Performance of Listed Companies on Vietnam’s Stock

Authors: Uyen Tran Tu

Abstract:

The decision on capital structure is one of the most important and sophisticated decisions in financial management in order to improve firm performance. This article would study the two-way impact between capital structure and firm performance. The study use EVIEWS 6.0 software to determine a two-way relationship between the capital structure and firm performance based on two-stage regression (2SLS - Two-Stage Least Squares). The findings are: capital structure has the opposite effect on the business efficiency and vice versa, factors that effect on business efficiency include Size and Opportunities. Factors effects on the capital structure are size; liquidity. These factors also affect the ratio of capital structure (total debt/ total asset) of companies. In particular, liquidity has the opposite effect; and the size of the business has the same impact. The results of the study are in line with the theory and empirical studies presented, and the results of the study are unchanged for all three years 2015-2017.

Keywords: capital structure, firm performance, factors, two-way relationship

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29949 Vibration Control of Building Using Multiple Tuned Mass Dampers Considering Real Earthquake Time History

Authors: Rama Debbarma, Debanjan Das

Abstract:

The performance of multiple tuned mass dampers to mitigate the seismic vibration of structures considering real time history data is investigated in this paper. Three different real earthquake time history data like Kobe, Imperial Valley and Mammoth Lake are taken in the present study. The multiple tuned mass dampers (MTMD) are distributed at each storey. For comparative study, single tuned mass damper (STMD) is installed at top of the similar structure. This study is conducted for a fixed mass ratio (5%) and fixed damping ratio (5%) of structures. Numerical study is performed to evaluate the effectiveness of MTMDs and overall system performance. The displacement, acceleration, base shear and storey drift are obtained for both combined system (structure with MTMD and structure with STMD) for all earthquakes. The same responses are also obtained for structure without damper system. From obtained results, it is investigated that the MTMD configuration is more effective for controlling the seismic response of the primary system with compare to STMD configuration.

Keywords: Earthquake, multiple tuned mass dampers, single tuned mass damper, Time history.

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29948 Real-Time Visualization Using GPU-Accelerated Filtering of LiDAR Data

Authors: Sašo Pečnik, Borut Žalik

Abstract:

This paper presents a real-time visualization technique and filtering of classified LiDAR point clouds. The visualization is capable of displaying filtered information organized in layers by the classification attribute saved within LiDAR data sets. We explain the used data structure and data management, which enables real-time presentation of layered LiDAR data. Real-time visualization is achieved with LOD optimization based on the distance from the observer without loss of quality. The filtering process is done in two steps and is entirely executed on the GPU and implemented using programmable shaders.

Keywords: filtering, graphics, level-of-details, LiDAR, real-time visualization

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29947 Missing Link Data Estimation with Recurrent Neural Network: An Application Using Speed Data of Daegu Metropolitan Area

Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

Abstract:

In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.

Keywords: data estimation, link data, machine learning, road network

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29946 Combining Diffusion Maps and Diffusion Models for Enhanced Data Analysis

Authors: Meng Su

Abstract:

High-dimensional data analysis often presents challenges in capturing the complex, nonlinear relationships and manifold structures inherent to the data. This article presents a novel approach that leverages the strengths of two powerful techniques, Diffusion Maps and Diffusion Probabilistic Models (DPMs), to address these challenges. By integrating the dimensionality reduction capability of Diffusion Maps with the data modeling ability of DPMs, the proposed method aims to provide a comprehensive solution for analyzing and generating high-dimensional data. The Diffusion Map technique preserves the nonlinear relationships and manifold structure of the data by mapping it to a lower-dimensional space using the eigenvectors of the graph Laplacian matrix. Meanwhile, DPMs capture the dependencies within the data, enabling effective modeling and generation of new data points in the low-dimensional space. The generated data points can then be mapped back to the original high-dimensional space, ensuring consistency with the underlying manifold structure. Through a detailed example implementation, the article demonstrates the potential of the proposed hybrid approach to achieve more accurate and effective modeling and generation of complex, high-dimensional data. Furthermore, it discusses possible applications in various domains, such as image synthesis, time-series forecasting, and anomaly detection, and outlines future research directions for enhancing the scalability, performance, and integration with other machine learning techniques. By combining the strengths of Diffusion Maps and DPMs, this work paves the way for more advanced and robust data analysis methods.

Keywords: diffusion maps, diffusion probabilistic models (DPMs), manifold learning, high-dimensional data analysis

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29945 One Dimensional Magneto-Plasmonic Structure Based On Metallic Nano-Grating

Authors: S. M. Hamidi, M. Zamani

Abstract:

Magneto-plasmonic (MP) structures have turned into essential tools for the amplification of magneto-optical (MO) responses via the combination of MO activity and surface Plasmon resonance (SPR). Both the plasmonic and the MO properties of the resulting MP structure become interrelated because the SPR of the metallic medium. This interconnection can be modified the wave vector of surface plasmon polariton (SPP) in MP multilayer [1] or enhanced the MO activity [2- 3] and also modified the sensor responses [4]. There are several types of MP structures which are studied to enhance MO response in miniaturized configuration. In this paper, we propose a new MP structure based on the nano-metal grating and we investigate the MO and optical properties of this new structure. Our new MP structure fabricate by DC magnetron sputtering method and our home made MO experimental setup use for characterization of the structure.

Keywords: Magneto-plasmonic structures, magneto-optical effect, nano-garting

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29944 The Features of Formation of Russian Agriculture’s Sectoral Structure

Authors: Natalya G. Filimonova, Mariya G. Ozerova, Irina N. Ermakova

Abstract:

The long-term strategy of the economic development of Russia up to 2030 is based on the concept of sustainable growth. The determining factor of such development is complex changes in the economic system which may be achieved by making progressive changes in its structure. The structural changes determine the character and the direction of economic development, as well as they include all elements of this system without exception, and their regulated character ensures the most rapid aim achievement. This article has discussed the industrial structure of the agriculture in Russia. With the use of the system of indexes, the article has determined the directions, intensity, and speed of structural shifts. The influence of structural changes on agricultural production development has been found out. It is noticed that the changes in the industrial structure are synchronized with the changes in the organisation and economic structure. Efficiency assessment of structural changes allowed to trace the efficiency of structural changes and elaborate the main directions for agricultural policy improvement.

Keywords: Russian agricultural sectors, sectoral structure, organizational and economic structure, structural changes

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29943 Comparison of Different Artificial Intelligence-Based Protein Secondary Structure Prediction Methods

Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

Abstract:

The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

Procedia PDF Downloads 584
29942 Board Structure, Composition, and Firm Performance: A Theoretical and Empirical Review

Authors: Suleiman Ahmed Badayi

Abstract:

Corporate governance literature is very wide and involves several empirical studies conducted on the relationship between board structure, composition and firm performance. The separation of ownership and control in organizations were aimed at reducing the losses suffered by the investors in the event of financial scandals. This paper reviewed the theoretical and empirical literature on the relationship between board composition and its impact on firm performance. The findings from the studies provide different results while some are of the view that board structure is related to firm performance, many empirical studies indicates no relationship. However, others found a U-shape relationship between firm performance and board structure. Therefore, this study argued that board structure is not much significant to determine the financial performance of a firm.

Keywords: board structure, composition, firm performance, corporate governance

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29941 Comparative Analysis of Effect of Capital Structure to Profitability in Manufacturing Sector in Indonesia and Malaysia in 2009 - 2014

Authors: Hatane Semuel, Hartmann H. Ngono, Sautma R. Basana

Abstract:

The effect of capital structure on profitability is often debated by many financial investigators. The application of the trade-off theory and pecking order theory to analyze this relationship may generate different views. Each company has its own strategies to achieve its objectives and the external environment, such as state policy has a broad impact on the relationship with the capital structure of the company's profitability. Malaysia is the country closest to Indonesia that had a similar growth rate of GDP and industrial production with Indonesia, but Malaysia has lower inflation rate than Indonesia. This study was conducted to compare the performance of manufacturing sector between two countries when entering the era of the ASEAN Economic Community (AEC). The samples for this study were 69 companies in Indonesia and 242 companies in Malaysia that engaged in manufacturing sector. The study uses panel data analysis. The study found that the capital structure have positive effect on profitability of manufacturing company in Indonesia, and it turns to negative effect on manufacturing companies in Malaysia. The results also showed that there are significant differences in short-term debt towards profitability of manufacturing companies in the two countries Indonesia and Malaysia.

Keywords: capital structure, Indonesia, Malaysia, manufacturing, profitability

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29940 Exploring Corporate Governance Structure in Gulf Cooperation Council Countries

Authors: Zahra A. Al Nasser, Domenico Campa

Abstract:

This paper investigates board of directors and firms’ ownership structure on non-financial companies listed in Gulf Cooperation council (GCC) countries using data from 2009 to 2013. The overall result of the study is that board size and board meeting have increased over years. Additionally, all combined committee variables have improved as well as audit committee size, audit committee meeting and audit committee experience have improved over the years. Furthermore, Oman is the only country that has not shown any statistically significant change in value of its associated variables.

Keywords: corporate governance, GCC countries, board of directors, ownership structure

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29939 Effect of Composition and Cooling Rate on the Solidification Structure of Al-Er Alloy

Authors: Jing Ning, Kunyuan Gao

Abstract:

The microstructure and phase structure of Al-Er alloys with Er content of 10, 20, 30wt% at cooling rate of 60, 40 and 5℃/h were analyzed using scanning electron microscope (SEM) and X-ray diffraction (XRD). Experimental results showed that for solidification of the hypereutectic Al-Er alloys at different conditions, a halo of α-Al appeared around the primary Al₃Er phase. Analysis of the solidification process indicated that after the primary Al₃Er phase formed, the composition of supercooled liquid phase located outside the coupled zone of eutectic growth below the eutectic line, which leaded to the formation of Al halo. With the increase of Er content, the blocky primary Al₃Er phase expanded from 200μm to 1mm in size. With the decrease of cooling rate, the morphology and phase structure of alloy were different. At the cooling rate of 60℃/h, it was obtained the primary Al3Er phase with L1₂ structure, whose profile was straight. Meanwhile, the eutectic structure was flocculent. At the quite slow cooling rate of 5℃/h, it was obtained the primary Al₃Er phase with hR20 structure with irregular jagged profile, and the eutectic structure was approximately strip-shaped. These characteristics were closely related to the cooling rate of solidification. The XRD analysis showed that for Al₃Er phase, the lattice constant a of L1₂ structure was 4.2158Å, and a, c of hR20 structure were 6.0321Å and 35.6290Å, respectively.

Keywords: Al-Er alloy, composition, cooling rate, microstructure

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29938 Band Structure Computation of GaMnAs Using the Multiband k.p Theory

Authors: Khadijah B. Alziyadi, Khawlh A. Alzubaidi, Amor M. Alsayari

Abstract:

Recently, GaMnAs diluted magnetic semiconductors(DMSs) have received considerable attention because they combine semiconductor and magnetic properties. GaMnAs has been used as a model DMS and as a test bed for many concepts and functionalities of spintronic devices. In this paper, a theoretical study on the band structure ofGaMnAswill be presented. The model that we used in this study is the 8-band k.p methodwherespin-orbit interaction, spin splitting, and strain are considered. The band structure of GaMnAs will be calculated in different directions in the reciprocal space. The effect of manganese content on the GaMnAs band structure will be discussed. Also, the influence of strain, which varied continuously from tensile to compressive, on the different bands will be studied.

Keywords: band structure, diluted magnetic semiconductor, k.p method, strain

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29937 An ANN Approach for Detection and Localization of Fatigue Damage in Aircraft Structures

Authors: Reza Rezaeipour Honarmandzad

Abstract:

In this paper we propose an ANN for detection and localization of fatigue damage in aircraft structures. We used network of piezoelectric transducers for Lamb-wave measurements in order to calculate damage indices. Data gathered by the sensors was given to neural network classifier. A set of neural network electors of different architecture cooperates to achieve consensus concerning the state of each monitored path. Sensed signal variations in the ROI, detected by the networks at each path, were used to assess the state of the structure as well as to localize detected damage and to filter out ambient changes. The classifier has been extensively tested on large data sets acquired in the tests of specimens with artificially introduced notches as well as the results of numerous fatigue experiments. Effect of the classifier structure and test data used for training on the results was evaluated.

Keywords: ANN, fatigue damage, aircraft structures, piezoelectric transducers, lamb-wave measurements

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29936 Numerical Simulation of Fluid Structure Interaction Using Two-Way Method

Authors: Samira Laidaoui, Mohammed Djermane, Nazihe Terfaya

Abstract:

The fluid-structure coupling is a natural phenomenon which reflects the effects of two continuums: fluid and structure of different types in the reciprocal action on each other, involving knowledge of elasticity and fluid mechanics. The solution for such problems is based on the relations of continuum mechanics and is mostly solved with numerical methods. It is a computational challenge to solve such problems because of the complex geometries, intricate physics of fluids, and complicated fluid-structure interactions. The way in which the interaction between fluid and solid is described gives the largest opportunity for reducing the computational effort. In this paper, a problem of fluid structure interaction is investigated with two-way coupling method. The formulation Arbitrary Lagrangian-Eulerian (ALE) was used, by considering a dynamic grid, where the solid is described by a Lagrangian formulation and the fluid by a Eulerian formulation. The simulation was made on the ANSYS software.

Keywords: ALE, coupling, FEM, fluid-structure, interaction, one-way method, two-way method

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29935 Design and Production of Thin-Walled UHPFRC Footbridge

Authors: P. Tej, P. Kněž, M. Blank

Abstract:

The paper presents design and production of thin-walled U-profile footbridge made of UHPFRC. The main structure of the bridge is one prefabricated shell structure made of UHPFRC with dispersed steel fibers without any conventional reinforcement. The span of the bridge structure is 10 m and the clear width of 1.5 m. The thickness of the UHPFRC shell structure oscillated in an interval of 30-45 mm. Several calculations were made during the bridge design and compared with the experiments. For the purpose of verifying the calculations, a segment of 1.5 m was first produced, followed by the whole footbridge for testing. After the load tests were done, the design was optimized to cast the final footbridge.

Keywords: footbridge, non-linear analysis, shell structure, UHPFRC, Ultra-High Performance Fibre Reinforced Concrete

Procedia PDF Downloads 199
29934 Population Structure Analysis of Pakistani Indigenous Cattle Population by Using High Density SNP Array

Authors: Hamid Mustafa, Huson J. Heather, Kim Eiusoo, McClure Matt, Khalid Javed, Talat Nasser Pasha, Afzal Ali1, Adeela Ajmal, Tad Sonstegard

Abstract:

Genetic differences associated with speciation, breed formation or local adaptation can help to preserve and effective utilization of animals in selection programs. Analyses of population structure and breed diversity have provided insight into the origin and evolution of cattle. In this study, we used a high-density panel of SNP markers to examine population structure and diversity among ten Pakistani indigenous cattle breeds. In total, 25 individuals from three cattle populations, including Achi (n=08), Bhagnari (n=04) and Cholistani (n=13) were genotyped for 777, 962 single nucleotide polymorphism (SNP) markers. Population structure was examined using the linkage model in the program STRUCTURE. After characterizing SNP polymorphism in the different populations, we performed a detailed analysis of genetic structure at both the individual and population levels. The whole-genome SNP panel identified several levels of population substructure in the set of examined cattle breeds. We further searched for spatial patterns of genetic diversity among these breeds under the recently developed spatial principal component analysis framework. Overall, such high throughput genotyping data confirmed a clear partitioning of the cattle genetic diversity into distinct breeds. The resulting complex historical origins associated with both natural and artificial selection have led to the differentiation of numerous different cattle breeds displaying a broad phenotypic variety over a short period of time.

Keywords: Pakistan, cattle, genetic diversity, population structure

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29933 Improved Whale Algorithm Based on Information Entropy and Its Application in Truss Structure Optimization Design

Authors: Serges Mendomo Meye, Li Guowei, Shen Zhenzhong, Gan Lei, Xu Liqun

Abstract:

Given the limitations of the original whale optimization algorithm (WAO) in local optimum and low convergence accuracy in truss structure optimization problems, based on the fundamental whale algorithm, an improved whale optimization algorithm (SWAO) based on information entropy is proposed. The information entropy itself is an uncertain measure. It is used to control the range of whale searches in path selection. It can overcome the shortcomings of the basic whale optimization algorithm (WAO) and can improve the global convergence speed of the algorithm. Taking truss structure as the optimization research object, the mathematical model of truss structure optimization is established; the cross-sectional area of truss is taken as the design variable; the objective function is the weight of truss structure; and an improved whale optimization algorithm (SWAO) is used for optimization design, which provides a new idea and means for its application in large and complex engineering structure optimization design.

Keywords: information entropy, structural optimization, truss structure, whale algorithm

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29932 A Study on Golden Ratio (ф) and Its Implications on Seismic Design Using ETABS

Authors: Vishal A. S. Salelkar, Sumitra S. Kandolkar

Abstract:

Golden ratio (ф) or Golden mean or Golden section, as it is often referred to, is a proportion or a mean, which is often used by architects while conceiving the aesthetics of a structure. Golden Ratio (ф) is an irrational number that can be roughly rounded to 1.618 and is derived out of quadratic equation x2-x-1=0. The use of Golden Ratio (ф) can be observed throughout history, as far as ancient Egyptians, which later peaked during the Greek golden age. The use of this design technique is very much prevalent. At present, architects around the world prefer this as one of the primary techniques to decide aesthetics. In this study, an analysis has been performed to investigate whether the use of the golden ratio while planning a structure has any effects on the seismic behavior of the structure. The structure is modeled and analyzed on ETABS (by Computers and Structures, Inc.) for Seismic requirements equivalent to Zone III (Region: Goa-India) as per Indian Standard Code IS-1893. The results were compared to that of an identical structure modeled along the lines of normal design philosophy, not using the Golden Ratio tools. The results were then compared for Story Shear, Story Drift, and Story Displacement Readings. Improvement in performance, although slight, but was observed. Similar improvements were also observed in subsequent iterations, performed using time-acceleration data of previous major earthquakes matched to Zone III as per IS-1893.

Keywords: ETABS, golden ratio, seismic design, structural behavior

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29931 Clustering of Extremes in Financial Returns: A Comparison between Developed and Emerging Markets

Authors: Sara Ali Alokley, Mansour Saleh Albarrak

Abstract:

This paper investigates the dependency or clustering of extremes in the financial returns data by estimating the extremal index value θ∈[0,1]. The smaller the value of θ the more clustering we have. Here we apply the method of Ferro and Segers (2003) to estimate the extremal index for a range of threshold values. We compare the dependency structure of extremes in the developed and emerging markets. We use the financial returns of the stock market index in the developed markets of US, UK, France, Germany and Japan and the emerging markets of Brazil, Russia, India, China and Saudi Arabia. We expect that more clustering occurs in the emerging markets. This study will help to understand the dependency structure of the financial returns data.

Keywords: clustring, extremes, returns, dependency, extermal index

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29930 Glycoside Hydrolase Clan GH-A-like Structure Complete Evaluation

Authors: Narin Salehiyan

Abstract:

The three iodothyronine selenodeiodinases catalyze the start and end of thyroid hormone impacts in vertebrates. Auxiliary examinations of these proteins have been prevented by their indispensably film nature and the wasteful eukaryotic-specific pathway for selenoprotein blend. Hydrophobic cluster examination utilized in combination with Position-specific Iterated Impact uncovers that their extramembrane parcel has a place to the thioredoxin-fold superfamily for which test structure data exists. Besides, a expansive deiodinase locale imbedded within the thioredoxin overlay offers solid similitudes with the dynamic location of iduronidase, a part of the clan GH-A-fold of glycoside hydrolases. This show can clarify a number of comes about from past mutagenesis examinations and grants unused irrefutable experiences into the auxiliary and utilitarian properties of these proteins.

Keywords: glycoside, hydrolase, GH-A-like structure, catalyze

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29929 Cloud Computing in Data Mining: A Technical Survey

Authors: Ghaemi Reza, Abdollahi Hamid, Dashti Elham

Abstract:

Cloud computing poses a diversity of challenges in data mining operation arising out of the dynamic structure of data distribution as against the use of typical database scenarios in conventional architecture. Due to immense number of users seeking data on daily basis, there is a serious security concerns to cloud providers as well as data providers who put their data on the cloud computing environment. Big data analytics use compute intensive data mining algorithms (Hidden markov, MapReduce parallel programming, Mahot Project, Hadoop distributed file system, K-Means and KMediod, Apriori) that require efficient high performance processors to produce timely results. Data mining algorithms to solve or optimize the model parameters. The challenges that operation has to encounter is the successful transactions to be established with the existing virtual machine environment and the databases to be kept under the control. Several factors have led to the distributed data mining from normal or centralized mining. The approach is as a SaaS which uses multi-agent systems for implementing the different tasks of system. There are still some problems of data mining based on cloud computing, including design and selection of data mining algorithms.

Keywords: cloud computing, data mining, computing models, cloud services

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29928 Electronic Structure Calculation of AsSiTeB/SiAsBTe Nanostructures Using Density Functional Theory

Authors: Ankit Kargeti, Ravikant Shrivastav, Tabish Rasheed

Abstract:

The electronic structure calculation for the nanoclusters of AsSiTeB/SiAsBTe quaternary semiconductor alloy belonging to the III-V Group elements was performed. Motivation for this research work was to look for accurate electronic and geometric data of small nanoclusters of AsSiTeB/SiAsBTe in the gaseous form. The two clusters, one in the linear form and the other in the bent form, were studied under the framework of Density Functional Theory (DFT) using the B3LYP functional and LANL2DZ basis set with the software packaged Gaussian 16. We have discussed the Optimized Energy, Frontier Orbital Energy Gap in terms of HOMO-LUMO, Dipole Moment, Ionization Potential, Electron Affinity, Binding Energy, Embedding Energy, Density of States (DoS) spectrum for both structures. The important findings of the predicted nanostructures are that these structures have wide band gap energy, where linear structure has band gap energy (Eg) value is 2.375 eV and bent structure (Eg) value is 2.778 eV. Therefore, these structures can be utilized as wide band gap semiconductors. These structures have high electron affinity value of 4.259 eV for the linear structure and electron affinity value of 3.387 eV for the bent structure form. It shows that electron acceptor capability is high for both forms. The widely known application of these compounds is in the light emitting diodes due to their wide band gap nature.

Keywords: density functional theory, DFT, density functional theory, nanostructures, HOMO-LUMO, density of states

Procedia PDF Downloads 92
29927 Nano-Texturing of Single Crystalline Silicon via Cu-Catalyzed Chemical Etching

Authors: A. A. Abaker Omer, H. B. Mohamed Balh, W. Liu, A. Abas, J. Yu, S. Li, W. Ma, W. El Kolaly, Y. Y. Ahmed Abuker

Abstract:

We have discovered an important technical solution that could make new approaches in the processing of wet silicon etching, especially in the production of photovoltaic cells. During its inferior light-trapping and structural properties, the inverted pyramid structure outperforms the conventional pyramid textures and black silicone. The traditional pyramid textures and black silicon can only be accomplished with more advanced lithography, laser processing, etc. Importantly, our data demonstrate the feasibility of an inverted pyramidal structure of silicon via one-step Cu-catalyzed chemical etching (CCCE) in Cu (NO3)2/HF/H2O2/H2O solutions. The effects of etching time and reaction temperature on surface geometry and light trapping were systematically investigated. The conclusion shows that the inverted pyramid structure has ultra-low reflectivity of ~4.2% in the wavelength of 300~1000 nm; introduce of Cu particles can significantly accelerate the dissolution of the silicon wafer. The etching and the inverted pyramid structure formation mechanism are discussed. Inverted pyramid structure with outstanding anti-reflectivity includes useful applications throughout the manufacture of semi-conductive industry-compatible solar cells, and can have significant impacts on industry colleagues and populations.

Keywords: Cu-catalyzed chemical etching, inverted pyramid nanostructured, reflection, solar cells

Procedia PDF Downloads 133
29926 Efficient Bargaining versus Right to Manage in the Era of Liberalization

Authors: Panagiota Koliousi, Natasha Miaouli

Abstract:

We compare product and labour market liberalization under the two trade union bargaining models: the Right-to-Manage (RTM) model and the Efficient Bargaining (EB) model. The vehicle is a dynamic general equilibrium (DGE) model that incorporates two types of agents (capitalists and workers), imperfectly competitive product and labour markets. The model is solved numerically employing common parameter values and data from the euro area. A key message is that product market deregulation is favourable under any labour market structure while opting for labour market deregulation one should provide special attention to the structure of the labour market such as the bargaining system of unions. If the prevailing way of bargaining is the RTM model then restructuring both markets is beneficial for all agents.

Keywords: market structure, structural reforms, trade unions, unemployment

Procedia PDF Downloads 180