Search results for: robust and damaged structure
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9412

Search results for: robust and damaged structure

9142 Robust and Transparent Spread Spectrum Audio Watermarking

Authors: Ali Akbar Attari, Ali Asghar Beheshti Shirazi

Abstract:

In this paper, we propose a blind and robust audio watermarking scheme based on spread spectrum in Discrete Wavelet Transform (DWT) domain. Watermarks are embedded in the low-frequency coefficients, which is less audible. The key idea is dividing the audio signal into small frames, and magnitude of the 6th level of DWT approximation coefficients is modifying based upon the Direct Sequence Spread Spectrum (DSSS) technique. Also, the psychoacoustic model for enhancing in imperceptibility, as well as Savitsky-Golay filter for increasing accuracy in extraction, is used. The experimental results illustrate high robustness against most common attacks, i.e. Gaussian noise addition, Low pass filter, Resampling, Requantizing, MP3 compression, without significant perceptual distortion (ODG is higher than -1). The proposed scheme has about 83 bps data payload.

Keywords: audio watermarking, spread spectrum, discrete wavelet transform, psychoacoustic, Savitsky-Golay filter

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9141 Robust Shrinkage Principal Component Parameter Estimator for Combating Multicollinearity and Outliers’ Problems in a Poisson Regression Model

Authors: Arum Kingsley Chinedu, Ugwuowo Fidelis Ifeanyi, Oranye Henrietta Ebele

Abstract:

The Poisson regression model (PRM) is a nonlinear model that belongs to the exponential family of distribution. PRM is suitable for studying count variables using appropriate covariates and sometimes experiences the problem of multicollinearity in the explanatory variables and outliers on the response variable. This study aims to address the problem of multicollinearity and outliers jointly in a Poisson regression model. We developed an estimator called the robust modified jackknife PCKL parameter estimator by combining the principal component estimator, modified jackknife KL and transformed M-estimator estimator to address both problems in a PRM. The superiority conditions for this estimator were established, and the properties of the estimator were also derived. The estimator inherits the characteristics of the combined estimators, thereby making it efficient in addressing both problems. And will also be of immediate interest to the research community and advance this study in terms of novelty compared to other studies undertaken in this area. The performance of the estimator (robust modified jackknife PCKL) with other existing estimators was compared using mean squared error (MSE) as a performance evaluation criterion through a Monte Carlo simulation study and the use of real-life data. The results of the analytical study show that the estimator outperformed other existing estimators compared with by having the smallest MSE across all sample sizes, different levels of correlation, percentages of outliers and different numbers of explanatory variables.

Keywords: jackknife modified KL, outliers, multicollinearity, principal component, transformed M-estimator.

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9140 Ice Load Measurements on Known Structures Using Image Processing Methods

Authors: Azam Fazelpour, Saeed R. Dehghani, Vlastimil Masek, Yuri S. Muzychka

Abstract:

This study employs a method based on image analyses and structure information to detect accumulated ice on known structures. The icing of marine vessels and offshore structures causes significant reductions in their efficiency and creates unsafe working conditions. Image processing methods are used to measure ice loads automatically. Most image processing methods are developed based on captured image analyses. In this method, ice loads on structures are calculated by defining structure coordinates and processing captured images. A pyramidal structure is designed with nine cylindrical bars as the known structure of experimental setup. Unsymmetrical ice accumulated on the structure in a cold room represents the actual case of experiments. Camera intrinsic and extrinsic parameters are used to define structure coordinates in the image coordinate system according to the camera location and angle. The thresholding method is applied to capture images and detect iced structures in a binary image. The ice thickness of each element is calculated by combining the information from the binary image and the structure coordinate. Averaging ice diameters from different camera views obtains ice thicknesses of structure elements. Comparison between ice load measurements using this method and the actual ice loads shows positive correlations with an acceptable range of error. The method can be applied to complex structures defining structure and camera coordinates.

Keywords: camera calibration, ice detection, ice load measurements, image processing

Procedia PDF Downloads 368
9139 The Market Structure Simulation of Heterogenous Firms

Authors: Arunas Burinskas, Manuela Tvaronavičienė

Abstract:

Although the new trade theories, unlike the theories of an industrial organisation, see the structure of the market and competition between enterprises through their heterogeneity according to various parameters, they do not pay any particular attention to the analysis of the market structure and its development. In this article, although we relied mainly on models developed by the scholars of new trade theory, we proposed a different approach. In our simulation model, we model market demand according to normal distribution function, while on the supply side (as it is in the new trade theory models), productivity is modeled with the Pareto distribution function. The results of the simulation show that companies with higher productivity (lower marginal costs) do not pass on all the benefits of such economies to buyers. However, even with higher marginal costs, firms can choose to offer higher value-added goods to stay in the market. In general, the structure of the market is formed quickly enough and depends on the skills available to firms.

Keywords: market, structure, simulation, heterogenous firms

Procedia PDF Downloads 148
9138 Moderating Effects of Family Structure on College Achievement

Authors: Jennifer Knudsen

Abstract:

This study observes the moderating effects of family structure on College Achievement across cohorts. Over the past half-century, social stigmas surrounding non-traditional families have shifted, as they make up an increasing proportion of American families. Using the General Social Survey, this study employs a varying coefficient model to test if family structure moderates the effects of other background variables on respondents’ educational attainment. Initial analysis suggests that living in alternative family arrangements has an increasingly negative effect on college achievement, whereas living in an intact family with a mother and father has a positive effect on college achievement.

Keywords: education, family, college, family structure

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9137 Split-Share Structure Reform and Statutory Audit Fees in China

Authors: Hsiao-Wen Wang

Abstract:

The split-share structure reform in China represents one of the most significant milestones in the evolution of the capital market. With the goal of converting non-tradable shares into tradable shares, the reform laid the foundation and supported the development of full-scale privatization. This study explores China’s split-share structure reform and its impact on statutory audit fees. This study finds that auditors earn a significant statutory audit fee premium after the split-share structure reform. The Big 4 auditors who provide better audit quality receive higher statutory audit fee premium than non-Big 4 auditors after the share reform, which is attributable to their brand reputation, rather than the relative market dominance.

Keywords: chinese split-share structure reform, statutory audit fees, big-4 auditors, corporate governance

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9136 Non-Linear Numerical Modeling of the Interaction of Twin Tunnels-Structure

Authors: A. Bayoumi, M. Abdallah, F. Hage Chehade

Abstract:

Structures on the ground surface bear impact from the tunneling-induced settlement, especially when twin tunnels are constructed. The tunneling influence on the structure is considered as a critical issue based on the construction procedure and relative position of tunnels. Lebanon is suffering from a traffic phenomenon caused by the lack of transportation systems. After several traffic counts and geotechnical investigations in Beirut city, efforts aim for the construction of tunneling systems. In this paper, we present a non-linear numerical modeling of the effect of the twin tunnels constructions on the structures located at soil surface for a particular site in Beirut. A parametric study, which concerns the geometric configuration of tunnels, the distance between their centers, the construction order, and the position of the structure, is performed. The tunnel-soil-structure interaction is analyzed by using the non-linear finite element modeling software PLAXIS 2D. The results of the surface settlement and the bending moment of the structure reveal significant influence when the structure is moved away, especially in vertical aligned tunnels.

Keywords: bending moment, elastic modulus, horizontal twin tunnels, soil, structure location, surface settlement, vertical twin tunnels

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9135 DWT-SATS Based Detection of Image Region Cloning

Authors: Michael Zimba

Abstract:

A duplicated image region may be subjected to a number of attacks such as noise addition, compression, reflection, rotation, and scaling with the intention of either merely mating it to its targeted neighborhood or preventing its detection. In this paper, we present an effective and robust method of detecting duplicated regions inclusive of those affected by the various attacks. In order to reduce the dimension of the image, the proposed algorithm firstly performs discrete wavelet transform, DWT, of a suspicious image. However, unlike most existing copy move image forgery (CMIF) detection algorithms operating in the DWT domain which extract only the low frequency sub-band of the DWT of the suspicious image thereby leaving valuable information in the other three sub-bands, the proposed algorithm simultaneously extracts features from all the four sub-bands. The extracted features are not only more accurate representation of image regions but also robust to additive noise, JPEG compression, and affine transformation. Furthermore, principal component analysis-eigenvalue decomposition, PCA-EVD, is applied to reduce the dimension of the features. The extracted features are then sorted using the more computationally efficient Radix Sort algorithm. Finally, same affine transformation selection, SATS, a duplication verification method, is applied to detect duplicated regions. The proposed algorithm is not only fast but also more robust to attacks compared to the related CMIF detection algorithms. The experimental results show high detection rates.

Keywords: affine transformation, discrete wavelet transform, radix sort, SATS

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9134 Robust Heart Rate Estimation from Multiple Cardiovascular and Non-Cardiovascular Physiological Signals Using Signal Quality Indices and Kalman Filter

Authors: Shalini Rankawat, Mansi Rankawat, Rahul Dubey, Mazad Zaveri

Abstract:

Physiological signals such as electrocardiogram (ECG) and arterial blood pressure (ABP) in the intensive care unit (ICU) are often seriously corrupted by noise, artifacts, and missing data, which lead to errors in the estimation of heart rate (HR) and incidences of false alarm from ICU monitors. Clinical support in ICU requires most reliable heart rate estimation. Cardiac activity, because of its relatively high electrical energy, may introduce artifacts in Electroencephalogram (EEG), Electrooculogram (EOG), and Electromyogram (EMG) recordings. This paper presents a robust heart rate estimation method by detection of R-peaks of ECG artifacts in EEG, EMG & EOG signals, using energy-based function and a novel Signal Quality Index (SQI) assessment technique. SQIs of physiological signals (EEG, EMG, & EOG) were obtained by correlation of nonlinear energy operator (teager energy) of these signals with either ECG or ABP signal. HR is estimated from ECG, ABP, EEG, EMG, and EOG signals from separate Kalman filter based upon individual SQIs. Data fusion of each HR estimate was then performed by weighing each estimate by the Kalman filters’ SQI modified innovations. The fused signal HR estimate is more accurate and robust than any of the individual HR estimate. This method was evaluated on MIMIC II data base of PhysioNet from bedside monitors of ICU patients. The method provides an accurate HR estimate even in the presence of noise and artifacts.

Keywords: ECG, ABP, EEG, EMG, EOG, ECG artifacts, Teager-Kaiser energy, heart rate, signal quality index, Kalman filter, data fusion

Procedia PDF Downloads 696
9133 Further Analysis of Global Robust Stability of Neural Networks with Multiple Time Delays

Authors: Sabri Arik

Abstract:

In this paper, we study the global asymptotic robust stability of delayed neural networks with norm-bounded uncertainties. By employing the Lyapunov stability theory and Homeomorphic mapping theorem, we derive some new types of sufficient conditions ensuring the existence, uniqueness and global asymptotic stability of the equilibrium point for the class of neural networks with discrete time delays under parameter uncertainties and with respect to continuous and slopebounded activation functions. An important aspect of our results is their low computational complexity as the reported results can be verified by checking some properties symmetric matrices associated with the uncertainty sets of network parameters. The obtained results are shown to be generalization of some of the previously published corresponding results. Some comparative numerical examples are also constructed to compare our results with some closely related existing literature results.

Keywords: neural networks, delayed systems, lyapunov functionals, stability analysis

Procedia PDF Downloads 527
9132 Translating Discourse Organization Structures Used in Chinese and English Scientific and Engineering Writings

Authors: Ming Qian, Davis Qian

Abstract:

This study compares the different organization structures of Chinese and English writing discourses in the engineering and scientific fields, and recommends approaches for translators to convert the organization structures properly. Based on existing intercultural communication literature, English authors tend to deductively give their main points at the beginning, following with detailed explanations or arguments afterwards while the Chinese authors tend to place their main points inductively towards the end. In this study, this hypothesis has been verified by the authors’ Chinese-to-English translation experiences in the fields of science and engineering (e.g. journal papers, conference papers and monographs). The basic methodology used is the comparison of writings by Chinese authors with writings of the same or similar topic written by English authors in terms of organization structures. Translators should be aware of this nuance, so that instead of limiting themselves to translating the contents of an article in its original structure, they can convert the structures to fill the cross-culture gap. This approach can be controversial because if a translator changes the structure organization of a paragraph (e.g. from a 'because-therefore' inductive structure by a Chinese author to a deductive structure in English), this change of sentence order could be questioned by the original authors. For this reason, translators need to properly inform the original authors on the intercultural differences of English and Chinese writing (e.g. inductive structure versus deductive structure), and work with the original authors to maintain accuracy while converting from one structure used in a source language to another structure in the target language. The authors have incorporated these methodologies into their translation practices and work closely with the authors on the inter-cultural organization structure mapping. Translating discourse organization structure should become a standard practice in the translation process.

Keywords: discourse structure, information structure, intercultural communication, translation practice

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9131 Ownership Structure and Portfolio Performance: Pre- and Post-Crisis Evidence from the Amman Stock Exchange

Authors: Mohammad Q. M. Momani

Abstract:

The objective of this study is to examine whether the value relevance of ownership structure changed as the Amman Stock Exchange market conditions changed. Using data from 2005 to 2014, the study finds that the performance of portfolios that contain firms with concentrated ownership structure declines significantly during the post-crisis period. These portfolios exhibit poor performance relative to portfolios that contain firms with dispersed ownership structure during the post-crisis period. The results argue that uninspired performance of the Amman Stock Exchange during the post-crisis period, increased the incentives for controlling shareholders to expropriate. Investors recognized these incentives and discounted firms that were more likely to expropriate.

Keywords: value relevance, ownership structure, portfolio performance, Jordan, ASE

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9130 Prediction of All-Beta Protein Secondary Structure Using Garnier-Osguthorpe-Robson Method

Authors: K. Tejasri, K. Suvarna Vani, S. Prathyusha, S. Ramya

Abstract:

Proteins are chained sequences of amino acids which are brought together by the peptide bonds. Many varying formations of the chains are possible due to multiple combinations of amino acids and rotation in numerous positions along the chain. Protein structure prediction is one of the crucial goals worked towards by the members of bioinformatics and theoretical chemistry backgrounds. Among the four different structure levels in proteins, we emphasize mainly the secondary level structure. Generally, the secondary protein basically comprises alpha-helix and beta-sheets. Multi-class classification problem of data with disparity is truly a challenge to overcome and has to be addressed for the beta strands. Imbalanced data distribution constitutes a couple of the classes of data having very limited training samples collated with other classes. The secondary structure data is extracted from the protein primary sequence, and the beta-strands are predicted using suitable machine learning algorithms.

Keywords: proteins, secondary structure elements, beta-sheets, beta-strands, alpha-helices, machine learning algorithms

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9129 Optimal Sensing Technique for Estimating Stress Distribution of 2-D Steel Frame Structure Using Genetic Algorithm

Authors: Jun Su Park, Byung Kwan Oh, Jin Woo Hwang, Yousok Kim, Hyo Seon Park

Abstract:

For the structural safety, the maximum stress calculated from the stress distribution of a structure is widely used. The stress distribution can be estimated by deformed shape of the structure obtained from measurement. Although the estimation of stress is strongly affected by the location and number of sensing points, most studies have conducted the stress estimation without reasonable basis on sensing plan such as the location and number of sensors. In this paper, an optimal sensing technique for estimating the stress distribution is proposed. This technique proposes the optimal location and number of sensing points for a 2-D frame structure while minimizing the error of stress distribution between analytical model and estimation by cubic smoothing splines using genetic algorithm. To verify the proposed method, the optimal sensor measurement technique is applied to simulation tests on 2-D steel frame structure. The simulation tests are performed under various loading scenarios. Through those tests, the optimal sensing plan for the structure is suggested and verified.

Keywords: genetic algorithm, optimal sensing, optimizing sensor placements, steel frame structure

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9128 Angiogenic and Immunomodulatory Properties and Phenotype of Mesenchymal Stromal Cells Can Be Regulated by Cytokine Treatment

Authors: Ekaterina Zubkova, Irina Beloglazova, Iurii Stafeev, Konsyantin Dergilev, Yelena Parfyonova, Mikhail Menshikov

Abstract:

Mesenchymal stromal cells from adipose tissue (MSC) currently are widely used in regenerative medicine to restore the function of damaged tissues, but that is significantly hampered by their heterogeneity. One of the modern approaches to overcoming this obstacle is the polarization of cell subpopulations into a specific phenotype under the influence of cytokines and other factors that activate receptors and signal transmission to cells. We polarized MSC with factors affecting the inflammatory signaling and functional properties of cells, followed by verification of their expression profile and ability to affect the polarization of macrophages. RT-PCR evaluation showed that cells treated with LPS, interleukin-17, tumor necrosis factor α (TNF α), primarily express pro-inflammatory factors and cytokines, and after treatment with polyninosin polycytidic acid and interleukin-4 (IL4) anti-inflammatory factors and some proinflammatory factors. MSC polarized with pro-inflammatory cytokines showed a more robust pro-angiogenic effect in fibrin gel bead 3D angiogenesis assay. Further, we evaluated the possibility of paracrine effects of MSCs on the polarization of intact macrophages. Polarization efficiency was assesed by expression of M1/M2 phenotype markers CD80 and CD206. We showed that conditioned media from MSC preincubated in the presence of IL-4 cause an increase in CD206 expression similar to that observed in M2 macrophages. Conditioned media from MSC polarized in the presence of LPS or TNF-α increased the expression of CD80 antigen in macrophages, similar to that observed in M1 macrophages. In other cases, a pronounced paracrine effect of MSC on the polarization of macrophages was not detected. Thus, our study showed that the polarization of MSC along the pro-inflammatory or anti-inflammatory pathway allows us to obtain cell subpopulations that have a multidirectional modulating effect on the polarization of macrophages. (RFBR grants 20-015-00405 and 18-015-00398.)

Keywords: angiogenesis, cytokines, mesenchymal, polarization, inflammation

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9127 Characterization and Analysis of Airless Tire in Mountain Cycle

Authors: Sadia Rafiq, Md. Ashab Siddique Zaki, Ananya Roy

Abstract:

Mountain cycling is a type of off-road bicycle racing that typically takes place on rocky, arid, or other challenging terrains on specially-made mountain cycles. Professional cyclists race while attempting to stay on their bikes in a variety of locales across the world. For safety measures in mountain cycling, as there we have a high chance of injury in case of tire puncture, it’s a preferable way to use an airless tire instead of a pneumatic tire. As airless tire does not tend to go flat, it needs to be replaced less frequently. The airless tire replaces the pneumatic tire, wheel, and tire system with a single unit. It consists of a stiff hub connected to a shear band by flexible, pliable spokes, which is made of poly-composite and a tread band, all of which work together as a single unit to replace all of the components of a normal radial tire. In this paper, an analysis of airless tires in the mountain cycle is shown along with structure and material study. We will be taking the Honeycomb and Diamond Structure of spokes to compare the deformation in both cases and choose our preferable structure. As we know, the tread and spokes deform with the surface roughness and impact. So, the tire tread thickness and the design of spokes can control how much the tire can distort. Through the simulation, we can come to the conclusion that the diamond structure deforms less than the honeycomb structure. So, the diamond structure is more preferable.

Keywords: airless tire, diamond structure, honeycomb structure, deformation

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9126 Data-Driven Dynamic Overbooking Model for Tour Operators

Authors: Kannapha Amaruchkul

Abstract:

We formulate a dynamic overbooking model for a tour operator, in which most reservations contain at least two people. The cancellation rate and the timing of the cancellation may depend on the group size. We propose two overbooking policies, namely economic- and service-based. In an economic-based policy, we want to minimize the expected oversold and underused cost, whereas, in a service-based policy, we ensure that the probability of an oversold situation does not exceed the pre-specified threshold. To illustrate the applicability of our approach, we use tour package data in 2016-2018 from a tour operator in Thailand to build a data-driven robust optimization model, and we tested the proposed overbooking policy in 2019. We also compare the data-driven approach to the conventional approach of fitting data into a probability distribution.

Keywords: applied stochastic model, data-driven robust optimization, overbooking, revenue management, tour operator

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9125 Competition between Verb-Based Implicit Causality and Theme Structure's Influence on Anaphora Bias in Mandarin Chinese Sentences: Evidence from Corpus

Authors: Linnan Zhang

Abstract:

Linguists, as well as psychologists, have shown great interests in implicit causality in reference processing. However, most frequently-used approaches to this issue are psychological experiments (such as eye tracking or self-paced reading, etc.). This research is a corpus-based one and is assisted with statistical tool – software R. The main focus of the present study is about the competition between verb-based implicit causality and theme structure’s influence on anaphora bias in Mandarin Chinese sentences. In Accessibility Theory, it is believed that salience, which is also known as accessibility, and relevance are two important factors in reference processing. Theme structure, which is a special syntactic structure in Chinese, determines the salience of an antecedent on the syntactic level while verb-based implicit causality is a key factor to the relevance between antecedent and anaphora. Therefore, it is a study about anaphora, combining psychology with linguistics. With analysis of the sentences from corpus as well as the statistical analysis of Multinomial Logistic Regression, major findings of the present study are as follows: 1. When the sentence is stated in a ‘cause-effect’ structure, the theme structure will always be the antecedent no matter forward biased verbs or backward biased verbs co-occur; in non-theme structure, the anaphora bias will tend to be the opposite of the verb bias; 2. When the sentence is stated in a ‘effect-cause’ structure, theme structure will not always be the antecedent and the influence of verb-based implicit causality will outweigh that of theme structure; moreover, the anaphora bias will be the same with the bias of verbs. All the results indicate that implicit causality functions conditionally and the noun in theme structure will not be the high-salience antecedent under any circumstances.

Keywords: accessibility theory, anaphora, theme strcture, verb-based implicit causality

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9124 Investigating the Role of Combined Length Scale Effect on the Mechanical Properties of Ni/Cu Multilayer Structures

Authors: Naresh Radaliyagoda, Nigel M. Jennett, Rong Lan, David Parfitt

Abstract:

A series of length scale engineered multilayer material with temperature robust mechanical properties has been suggested. A range of polycrystalline copper sub-layers with the thickness varying from 1 to 25μm and buried in between two nickel layers was produced using electrodeposition dual bath technique. The structure of the multilayers was characterized using Electron Backscatter Diffraction and Scanning Electron Microscope. The interface effect on the hardness and elastic modulus was tested using Nano-indentation. Results of the grain size and layer thickness measurements, and indentation hardness have been compared. It is found that there is a combined length scale effect that improves mechanical properties in Ni/Cu multilayer structures.

Keywords: nano-indentation, size effect, multilayers, electrodeposition

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9123 A Case Study of Assessment of Fire Affected Concrete Structure by NDT

Authors: Nikhil Gopalkrishnan, Praveen Bhaskaran, Aditya Bhargava, Gyandeep Bhumarkar

Abstract:

The present paper is an attempt to perform various Non-Destructive Tests on concrete structure as NDT is gaining a wide importance in the branch of civil engineering these days. Various tests that are performed under NDT not only enable us to determine the strength of concrete structure, but also provide us in-hand information regarding the durability, in-situ properties of the concrete structure. Keeping these points in our mind, we have focused our views on performing a case study to show the comparison between the NDT test results performed on a particular concrete structure and another structure at the same site which is subjected to a continuous fire of say 48-72 hours. The mix design and concrete grade of both the structures were same before the one was affected by fire. The variations in the compressive strength, concrete quality and in-situ properties of the two structures have been discussed in this paper. NDT tests namely Ultrasonic Pulse Velocity Test, Rebound Hammer Test, Core-Cutter Test was performed at both the sites. The main objective of this research is to analyze the variations in the strength and quality of the concrete structure which is subjected to a high temperature fire and the one which isn’t exposed to it.

Keywords: core-cutter test, non-destructive test, rebound hammer test, ultrasonic pulse velocity test

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9122 Transfer Learning for Protein Structure Classification at Low Resolution

Authors: Alexander Hudson, Shaogang Gong

Abstract:

Structure determination is key to understanding protein function at a molecular level. Whilst significant advances have been made in predicting structure and function from amino acid sequence, researchers must still rely on expensive, time-consuming analytical methods to visualise detailed protein conformation. In this study, we demonstrate that it is possible to make accurate (≥80%) predictions of protein class and architecture from structures determined at low (>3A) resolution, using a deep convolutional neural network trained on high-resolution (≤3A) structures represented as 2D matrices. Thus, we provide proof of concept for high-speed, low-cost protein structure classification at low resolution, and a basis for extension to prediction of function. We investigate the impact of the input representation on classification performance, showing that side-chain information may not be necessary for fine-grained structure predictions. Finally, we confirm that high resolution, low-resolution and NMR-determined structures inhabit a common feature space, and thus provide a theoretical foundation for boosting with single-image super-resolution.

Keywords: transfer learning, protein distance maps, protein structure classification, neural networks

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9121 Multi-Point Dieless Forming Product Defect Reduction Using Reliability-Based Robust Process Optimization

Authors: Misganaw Abebe Baye, Ji-Woo Park, Beom-Soo Kang

Abstract:

The product quality of multi-point dieless forming (MDF) is identified to be dependent on the process parameters. Moreover, a certain variation of friction and material properties may have a substantially worse influence on the final product quality. This study proposed on how to compensate the MDF product defects by minimizing the sensitivity of noise parameter variations. This can be attained by reliability-based robust optimization (RRO) technique to obtain the optimal process setting of the controllable parameters. Initially two MDF Finite Element (FE) simulations of AA3003-H14 saddle shape showed a substantial amount of dimpling, wrinkling, and shape error. FE analyses are consequently applied on ABAQUS commercial software to obtain the correlation between the control process setting and noise variation with regard to the product defects. The best prediction models are chosen from the family of metamodels to swap the computational expensive FE simulation. Genetic algorithm (GA) is applied to determine the optimal process settings of the control parameters. Monte Carlo Analysis (MCA) is executed to determine how the noise parameter variation affects the final product quality. Finally, the RRO FE simulation and the experimental result show that the amendment of the control parameters in the final forming process leads to a considerably better-quality product.

Keywords: dimpling, multi-point dieless forming, reliability-based robust optimization, shape error, variation, wrinkling

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9120 Non-Linear Static Pushover Analysis of 15 Storied Reinforced Concrete Building Structure with Shear Wall

Authors: Hamid Nikzad, Shinta Yoshitomi

Abstract:

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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9119 Technical Non-Destructive Evaluation of Burnt Bridge at CH. 57+450 Along Abuja-Abaji-Lokoja Road, Nigeria

Authors: Abraham O. Olaniyi, Oluyemi Oke, Atilade Otunla

Abstract:

The structural performance of bridges decreases progressively throughout their service life due to many contributing factors (fatigue, carbonation, fire incidents etc.). Around the world, numerous bridges have attained their estimated service life and many have approached this limit. The structural integrity assessment of the burnt composite bridge located at CH57+450, Koita village along Abuja-Abaji-Lokoja road, Nigeria, is presented as a case study and shall be forthwith referred to as the 'Koita bridge' in this paper. From the technical evaluation, the residual compressive strength of the concrete piers was found to be below 16.0 N/mm2. This value is very low compared to the expected design value of 30.0 N/mm2. The pier capping beam at pier location 1 has a very low residual compressive strength. The cover to the reinforcement of certain capping beams has an outline of reinforcement which signifies poor concrete cover and the mean compressive strength is also less than 20.0 N/mm2. The steel girder indicated black colouration as a result of the fire incident without any significant structural defect like buckling or warping of the steel section. This paper reviews the structural integrity assessment and repair methodology of the Koita bridge; a composite bridge damaged by fire, highlighting the various challenges of limited obtainable guidance documents about the bridge. The objectives are to increase the understanding of processes and versatile equipment required to test and assess a fire-damaged bridge in order to improve the quality of structural appraisal and rehabilitation; thus, eliminating the prejudice associated with current visual inspection techniques.

Keywords: assessment, bridge, rehabilitation, sustainability

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9118 Hotel and Service Industry in USA: Is It Leveraged? Case Study of Seven Important Hotel Chains

Authors: Azadeh Shahbazi

Abstract:

This study tries to find out the determinants of capital structure in hotel industry in 7 important hotel chains in USA within the period of 12 years of 2000 to 2012. The study is used a panel pooled regression to realize the relation among different variables. Results show that the variables which could make changes in the capital structure of firms are Non-Debt Tax Shield and Tangibility.

Keywords: capital structure, service industry, hospitality, finance

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9117 The Relationship between Creative Imagination and Curriculum

Authors: Faride Hashemiannejad, Shima Oloomi

Abstract:

Imagination is one of the important elements of creative thinking which as a skill needs attention by the educational system. Although most students learn reading, writing, and arithmetic skills well, they lack high level thinking skills like creative thinking. Therefore, in the information age and in the beginning of entry to knowledge-based society, the educational system needs to think over its goals and mission, and concentrate on creativity-based curriculum. From among curriculum elements-goals, content, method and evaluation “method” is a major domain whose reform can pave the way for fostering imagination and creativity. The purpose of this study was examining the relationship between creativity development and curriculum. Research questions were: (1) is there a relationship between the cognitive-emotional structure of the classroom and creativity development? (2) Is there a relationship between the environmental-social structure of the classroom and creativity development? (3) Is there a relationship between the thinking structure of the classroom and creativity development? (4) Is there a relationship between the physical structure of the classroom and creativity development? (5) Is there a relationship between the instructional structure of the classroom and creativity development? Method: This research is a applied research and the research method is Correlational research. Participants: The total number of participants in this study included 894 students from High school through 11th grade from seven schools of seven zones in Mashad city. Sampling Plan: Sampling was selected based on Random Multi State. Measurement: The dependent measure in this study was: (a) the Test of Creative Thinking, (b) The researcher-made questionnaire includes five fragments, cognitive, emotional structure, environmental social structure, thinking structure, physical structure, and instructional structure. The Results Show: There was significant relationship between the cognitive-emotional structure of the classroom and student’s creativity development (sig=0.139). There was significant relationship between the environmental-social structure of the classroom and student’s creativity development (sig=0.006). There was significant relationship between the thinking structure of the classroom and student’s creativity development (sig=0.004). There was not significant relationship between the physical structure of the classroom and student’s creativity development (sig=0.215). There was significant relationship between the instructional structure of the classroom and student’s creativity development (sig=0.003). These findings denote if students feel secure, calm and confident, they can experience creative learning. Also the quality of coping with students’ questions, imaginations and risks can influence on their creativity development.

Keywords: imagination, creativity, curriculum, bioinformatics, biomedicine

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9116 Single-Element Simulations of Wood Material in LS-DYNA

Authors: Ren Zuo Wang

Abstract:

In this paper, in order to investigate the behavior of the wood structure, the non-linearity of wood material model in LS-DYNA is adopted. It is difficult and less efficient to conduct the experiment of the ancient wood structure, hence LS-DYNA software can be used to simulate nonlinear responses of ancient wood structure. In LS-DYNA software, there is material model called *MAT_WOOD or *MAT_143. This model is to simulate a single-element response of the wood subjected to tension and compression under the parallel and the perpendicular material directions. Comparing with the exact solution and numerical simulations results using LS-DYNA, it demonstrates the accuracy and the efficiency of the proposed simulation method.

Keywords: LS-DYNA, wood structure, single-element simulations, MAT_143

Procedia PDF Downloads 653
9115 Fast and Robust Long-term Tracking with Effective Searching Model

Authors: Thang V. Kieu, Long P. Nguyen

Abstract:

Kernelized Correlation Filter (KCF) based trackers have gained a lot of attention recently because of their accuracy and fast calculation speed. However, this algorithm is not robust in cases where the object is lost by a sudden change of direction, being obscured or going out of view. In order to improve KCF performance in long-term tracking, this paper proposes an anomaly detection method for target loss warning by analyzing the response map of each frame, and a classification algorithm for reliable target re-locating mechanism by using Random fern. Being tested with Visual Tracker Benchmark and Visual Object Tracking datasets, the experimental results indicated that the precision and success rate of the proposed algorithm were 2.92 and 2.61 times higher than that of the original KCF algorithm, respectively. Moreover, the proposed tracker handles occlusion better than many state-of-the-art long-term tracking methods while running at 60 frames per second.

Keywords: correlation filter, long-term tracking, random fern, real-time tracking

Procedia PDF Downloads 138
9114 Easymodel: Web-based Bioinformatics Software for Protein Modeling Based on Modeller

Authors: Alireza Dantism

Abstract:

Presently, describing the function of a protein sequence is one of the most common problems in biology. Usually, this problem can be facilitated by studying the three-dimensional structure of proteins. In the absence of a protein structure, comparative modeling often provides a useful three-dimensional model of the protein that is dependent on at least one known protein structure. Comparative modeling predicts the three-dimensional structure of a given protein sequence (target) mainly based on its alignment with one or more proteins of known structure (templates). Comparative modeling consists of four main steps 1. Similarity between the target sequence and at least one known template structure 2. Alignment of target sequence and template(s) 3. Build a model based on alignment with the selected template(s). 4. Prediction of model errors 5. Optimization of the built model There are many computer programs and web servers that automate the comparative modeling process. One of the most important advantages of these servers is that it makes comparative modeling available to both experts and non-experts, and they can easily do their own modeling without the need for programming knowledge, but some other experts prefer using programming knowledge and do their modeling manually because by doing this they can maximize the accuracy of their modeling. In this study, a web-based tool has been designed to predict the tertiary structure of proteins using PHP and Python programming languages. This tool is called EasyModel. EasyModel can receive, according to the user's inputs, the desired unknown sequence (which we know as the target) in this study, the protein sequence file (template), etc., which also has a percentage of similarity with the primary sequence, and its third structure Predict the unknown sequence and present the results in the form of graphs and constructed protein files.

Keywords: structural bioinformatics, protein tertiary structure prediction, modeling, comparative modeling, modeller

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9113 Using Cyclic Structure to Improve Inference on Network Community Structure

Authors: Behnaz Moradijamei, Michael Higgins

Abstract:

Identifying community structure is a critical task in analyzing social media data sets often modeled by networks. Statistical models such as the stochastic block model have proven to explain the structure of communities in real-world network data. In this work, we develop a goodness-of-fit test to examine community structure's existence by using a distinguishing property in networks: cyclic structures are more prevalent within communities than across them. To better understand how communities are shaped by the cyclic structure of the network rather than just the number of edges, we introduce a novel method for deciding on the existence of communities. We utilize these structures by using renewal non-backtracking random walk (RNBRW) to the existing goodness-of-fit test. RNBRW is an important variant of random walk in which the walk is prohibited from returning back to a node in exactly two steps and terminates and restarts once it completes a cycle. We investigate the use of RNBRW to improve the performance of existing goodness-of-fit tests for community detection algorithms based on the spectral properties of the adjacency matrix. Our proposed test on community structure is based on the probability distribution of eigenvalues of the normalized retracing probability matrix derived by RNBRW. We attempt to make the best use of asymptotic results on such a distribution when there is no community structure, i.e., asymptotic distribution under the null hypothesis. Moreover, we provide a theoretical foundation for our statistic by obtaining the true mean and a tight lower bound for RNBRW edge weights variance.

Keywords: hypothesis testing, RNBRW, network inference, community structure

Procedia PDF Downloads 150