Search results for: output excitation factor
2186 Enabling Factors towards Safety Improvement for Industrialised Building System (IBS)
Authors: Nasyairi Mat Nasir, Zulhabri Ismail, Faridah Ismail, Sharifah Nur Aina Syed Alwee, Masnizan Che Mat
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The utilisation of Industrial Building System (IBS) in construction industry will lead to a safe site condition since minimum numbers of workers are required to be on-site, timely material delivery, systematic component storage, reduction of construction material and waste. These matters are being promoted in the Construction Industry Master Plan (CIMP 2006-2015). However, the enabling factors of IBS that will foster a safer working environment are indefinite; on that basis a research has been conducted. The purpose of this paper is to discuss and identify the relevant factors towards safety improvement for IBS. A quantitative research by way of questionnaire surveys have been conducted to 314 construction companies. The target group was Grade 5 to Grade 7 contractors registered with Construction Industry Development Board (CIDB) which specialise in IBS. The findings disclosed seven factors linked to the safety improvement of IBS construction site in Malaysia. The factors were historical, economic, psychological, technical, procedural, organisational and the environmental factors. From the findings, a psychological factor ranked as the highest and most crucial factor contributing to safer IBS construction site. The psychological factor included the self-awareness and influences from workmates behaviour. Followed by organisational factors, where project management style will encourage the safety efforts. From the procedural factors, it was also found that training was one of the significant factors to improve safety culture of IBS construction site. Another important finding that formed as a part of the environmental factor was storage of IBS components, in which proper planning of the layout would able to contribute to a safer site condition. To conclude, in order to improve safety of IBS construction site, a welltrained and skilled workers are required for IBS projects, thus proper training is permissible and should be emphasised.
Keywords: Enabling Factors, Industrialised Building System, Safety Improvement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29382185 The Development of a Teachers- Self-Efficacy Instrument for High School Physical Education Teacher
Authors: Yi-Hsiang Pan
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The purpose of this study was to develop a “teachers’ self-efficacy scale for high school physical education teachers (TSES-HSPET)” in Taiwan. This scale is based on the self-efficacy theory of Bandura [1], [2]. This study used exploratory and confirmatory factor analyses to test the reliability and validity. The participants were high school physical education teachers in Taiwan. Both stratified random sampling and cluster sampling were used to sample participants for the study. 350 teachers were sampled in the first stage and 234 valid scales (male 133, female 101) returned. During the second stage, 350 teachers were sampled and 257 valid scales (male 143, female 110, 4 did not indicate gender) returned. The exploratory factor analysis was used in the first stage, and it got 60.77% of total variance for construct validity. The Cronbach’s alpha coefficient of internal consistency was 0.91 for sumscale, and subscales were 0.84 and 0.90. In the second stage, confirmatory factor analysis was used to test construct validity. The result showed that the fit index could be accepted (χ2 (75) =167.94, p <.05, RMSEA =0.07, SRMR=0.05, GFI=0.92, NNFI=0.97, CFI=0.98, PNFI=0.79). Average variance extracted of latent variables were 0.43 and 0.53, which composite reliability are 0.78 and 0.90. It is concluded that the TSES-HSPET is a well-considered measurement instrument with acceptable validity and reliability. It may be used to estimate teachers’ self-efficacy for high school physical education teachers.Keywords: teaching in physical education, teacher's self-efficacy, teacher's belief
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31812184 A FE-Based Scheme for Computing Wave Interaction with Nonlinear Damage and Generation of Harmonics in Layered Composite Structures
Authors: R. K. Apalowo, D. Chronopoulos
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A Finite Element (FE) based scheme is presented for quantifying guided wave interaction with Localised Nonlinear Structural Damage (LNSD) within structures of arbitrary layering and geometric complexity. The through-thickness mode-shape of the structure is obtained through a wave and finite element method. This is applied in a time domain FE simulation in order to generate time harmonic excitation for a specific wave mode. Interaction of the wave with LNSD within the system is computed through an element activation and deactivation iteration. The scheme is validated against experimental measurements and a WFE-FE methodology for calculating wave interaction with damage. Case studies for guided wave interaction with crack and delamination are presented to verify the robustness of the proposed method in classifying and identifying damage.Keywords: Layered Structures, nonlinear ultrasound, wave interaction with nonlinear damage, wave finite element, finite element.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5482183 A Three-Dimensional TLM Simulation Method for Thermal Effect in PV-Solar Cells
Authors: R. Hocine, A. Boudjemai, A. Amrani, K. Belkacemi
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Temperature rising is a negative factor in almost all systems. It could cause by self heating or ambient temperature. In solar photovoltaic cells this temperature rising affects on the behavior of cells. The ability of a PV module to withstand the effects of periodic hot-spot heating that occurs when cells are operated under reverse biased conditions is closely related to the properties of the cell semi-conductor material.
In addition, the thermal effect also influences the estimation of the maximum power point (MPP) and electrical parameters for the PV modules, such as maximum output power, maximum conversion efficiency, internal efficiency, reliability, and lifetime. The cells junction temperature is a critical parameter that significantly affects the electrical characteristics of PV modules. For practical applications of PV modules, it is very important to accurately estimate the junction temperature of PV modules and analyze the thermal characteristics of the PV modules. Once the temperature variation is taken into account, we can then acquire a more accurate MPP for the PV modules, and the maximum utilization efficiency of the PV modules can also be further achieved.
In this paper, the three-Dimensional Transmission Line Matrix (3D-TLM) method was used to map the surface temperature distribution of solar cells while in the reverse bias mode. It was observed that some cells exhibited an inhomogeneity of the surface temperature resulting in localized heating (hot-spot). This hot-spot heating causes irreversible destruction of the solar cell structure. Hot spots can have a deleterious impact on the total solar modules if individual solar cells are heated. So, the results show clearly that the solar cells are capable of self-generating considerable amounts of heat that should be dissipated very quickly to increase PV module's lifetime.
Keywords: Thermal effect, Conduction, Heat dissipation, Thermal conductivity, Solar cell, PV module, Nodes, 3D-TLM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23482182 A Neurofuzzy Learning and its Application to Control System
Authors: Seema Chopra, R. Mitra, Vijay Kumar
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A neurofuzzy approach for a given set of input-output training data is proposed in two phases. Firstly, the data set is partitioned automatically into a set of clusters. Then a fuzzy if-then rule is extracted from each cluster to form a fuzzy rule base. Secondly, a fuzzy neural network is constructed accordingly and parameters are tuned to increase the precision of the fuzzy rule base. This network is able to learn and optimize the rule base of a Sugeno like Fuzzy inference system using Hybrid learning algorithm, which combines gradient descent, and least mean square algorithm. This proposed neurofuzzy system has the advantage of determining the number of rules automatically and also reduce the number of rules, decrease computational time, learns faster and consumes less memory. The authors also investigate that how neurofuzzy techniques can be applied in the area of control theory to design a fuzzy controller for linear and nonlinear dynamic systems modelling from a set of input/output data. The simulation analysis on a wide range of processes, to identify nonlinear components on-linely in a control system and a benchmark problem involving the prediction of a chaotic time series is carried out. Furthermore, the well-known examples of linear and nonlinear systems are also simulated under the Matlab/Simulink environment. The above combination is also illustrated in modeling the relationship between automobile trips and demographic factors.
Keywords: Fuzzy control, neuro-fuzzy techniques, fuzzy subtractive clustering, extraction of rules, and optimization of membership functions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25962181 Design of QFT-Based Self-Tuning Deadbeat Controller
Authors: H. Mansor, S. B. Mohd Noor
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This paper presents a design method of self-tuning Quantitative Feedback Theory (QFT) by using improved deadbeat control algorithm. QFT is a technique to achieve robust control with pre-defined specifications whereas deadbeat is an algorithm that could bring the output to steady state with minimum step size. Nevertheless, usually there are large peaks in the deadbeat response. By integrating QFT specifications into deadbeat algorithm, the large peaks could be tolerated. On the other hand, emerging QFT with adaptive element will produce a robust controller with wider coverage of uncertainty. By combining QFT-based deadbeat algorithm and adaptive element, superior controller that is called selftuning QFT-based deadbeat controller could be achieved. The output response that is fast, robust and adaptive is expected. Using a grain dryer plant model as a pilot case-study, the performance of the proposed method has been evaluated and analyzed. Grain drying process is very complex with highly nonlinear behaviour, long delay, affected by environmental changes and affected by disturbances. Performance comparisons have been performed between the proposed self-tuning QFT-based deadbeat, standard QFT and standard dead-beat controllers. The efficiency of the self-tuning QFTbased dead-beat controller has been proven from the tests results in terms of controller’s parameters are updated online, less percentage of overshoot and settling time especially when there are variations in the plant.
Keywords: Deadbeat control, quantitative feedback theory (QFT), robust control, self-tuning control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23352180 Electron Density Discrepancy Analysis of Energy Metabolism Coenzymes
Authors: Alan Luo, Hunter N. B. Moseley
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Many macromolecular structure entries in the Protein Data Bank (PDB) have a range of regional (localized) quality issues, be it derived from X-ray crystallography, Nuclear Magnetic Resonance (NMR) spectroscopy, or other experimental approaches. However, most PDB entries are judged by global quality metrics like R-factor, R-free, and resolution for X-ray crystallography or backbone phi-psi distribution statistics and average restraint violations for NMR. Regional quality is often ignored when PDB entries are re-used for a variety of structurally based analyses. The binding of ligands, especially ligands involved in energy metabolism, is of particular interest in many structurally focused protein studies. Using a regional quality metric that provides chemically interpretable information from electron density maps, a significant number of outliers in regional structural quality was detected across X-ray crystallographic PDB entries for proteins bound to biochemically critical ligands. In this study, a series of analyses was performed to evaluate both specific and general potential factors that could promote these outliers. In particular, these potential factors were the minimum distance to a metal ion, the minimum distance to a crystal contact, and the isotropic atomic b-factor. To evaluate these potential factors, Fisher’s exact tests were performed, using regional quality criteria of outlier (top 1%, 2.5%, 5%, or 10%) versus non-outlier compared to a potential factor metric above versus below a certain outlier cutoff. The results revealed a consistent general effect from region-specific normalized b-factors but no specific effect from metal ion contact distances and only a very weak effect from crystal contact distance as compared to the b-factor results. These findings indicate that no single specific potential factor explains a majority of the outlier ligand-bound regions, implying that human error is likely as important as these other factors. Thus, all factors, including human error, should be considered when regions of low structural quality are detected. Also, the downstream re-use of protein structures for studying ligand-bound conformations should screen the regional quality of the binding sites. Doing so prevents misinterpretation due to the presence of structural uncertainty or flaws in regions of interest.
Keywords: Biomacromolecular structure, coenzyme, electron density discrepancy analysis, X-ray crystallography.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2582179 Ductility, Rμ, and Overstrength Factors for V Braced Reinforced Concrete Buildings
Authors: Birendra Kumar Bohara
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Steel bracings are used to improve the seismic behaviors of the structures. In this study, 8, 12 and 16 story reinforced concrete (RC) buildings with steel bracings are used in three base shear contributions (25%, 50% and 75%) in the columns. With the help of pushover analysis and capacity curves, the overstrength factors, ductility factors and ductility reduction factors are investigated for braced RC buildings. It is observed that when the base shear contribution in the columns increases the ductility reduction factor also increases. The results show that when the time period of the structures increases, the ductility reduction factors of the structures decrease.
Keywords: Steel bracing, overstrength factor, ductility, ductility reduction factors, base shear contributions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3892178 Characteristic Study on Conventional and Soliton Based Transmission System
Authors: Bhupeshwaran Mani, S. Radha, A. Jawahar, A. Sivasubramanian
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Here, we study the characteristic feature of conventional (ON-OFF keying) and soliton based transmission system. We consider 20Gbps transmission system implemented with Conventional Single Mode Fiber (C-SMF) to examine the role of Gaussian pulse which is the characteristic of conventional propagation and Hyperbolic-secant pulse which is the characteristic of soliton propagation in it. We note the influence of these pulses with respect to different dispersion lengths and soliton period in conventional and soliton system respectively and evaluate the system performance in terms of Quality factor. From the analysis, we could prove that the soliton pulse has the consistent performance even for long distance without dispersion compensation than the conventional system as it is robust to dispersion. For the length of transmission of 200Km, soliton system yielded Q of 33.958 while the conventional system totally exhausted with Q=0.Keywords: Soliton, dispersion length, Soliton period, Return-tozero (RZ), Q-factor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16402177 Estimation of Structural Parameters in Time Domain Using One Dimensional Piezo Zirconium Titanium Patch Model
Authors: N. Jinesh, K. Shankar
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This article presents a method of using the one dimensional piezo-electric patch on beam model for structural identification. A hybrid element constituted of one dimensional beam element and a PZT sensor is used with reduced material properties. This model is convenient and simple for identification of beams. Accuracy of this element is first verified against a corresponding 3D finite element model (FEM). The structural identification is carried out as an inverse problem whereby parameters are identified by minimizing the deviation between the predicted and measured voltage response of the patch, when subjected to excitation. A non-classical optimization algorithm Particle Swarm Optimization is used to minimize this objective function. The signals are polluted with 5% Gaussian noise to simulate experimental noise. The proposed method is applied on beam structure and identified parameters are stiffness and damping. The model is also validated experimentally.
Keywords: Structural identification, PZT patches, inverse problem, particle swarm optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9312176 Conventional and PSO Based Approaches for Model Reduction of SISO Discrete Systems
Authors: S. K. Tomar, R. Prasad, S. Panda, C. Ardil
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Reduction of Single Input Single Output (SISO) discrete systems into lower order model, using a conventional and an evolutionary technique is presented in this paper. In the conventional technique, the mixed advantages of Modified Cauer Form (MCF) and differentiation are used. In this method the original discrete system is, first, converted into equivalent continuous system by applying bilinear transformation. The denominator of the equivalent continuous system and its reciprocal are differentiated successively, the reduced denominator of the desired order is obtained by combining the differentiated polynomials. The numerator is obtained by matching the quotients of MCF. The reduced continuous system is converted back into discrete system using inverse bilinear transformation. In the evolutionary technique method, Particle Swarm Optimization (PSO) is employed to reduce the higher order model. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example.
Keywords: Discrete System, Single Input Single Output (SISO), Bilinear Transformation, Reduced Order Model, Modified CauerForm, Polynomial Differentiation, Particle Swarm Optimization, Integral Squared Error.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19452175 A Numerical Investigation of Lamb Wave Damage Diagnosis for Composite Delamination Using Instantaneous Phase
Authors: Haode Huo, Jingjing He, Rui Kang, Xuefei Guan
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This paper presents a study of Lamb wave damage diagnosis of composite delamination using instantaneous phase data. Numerical experiments are performed using the finite element method. Different sizes of delamination damages are modeled using finite element package ABAQUS. Lamb wave excitation and responses data are obtained using a pitch-catch configuration. Empirical mode decomposition is employed to extract the intrinsic mode functions (IMF). Hilbert–Huang Transform is applied to each of the resulting IMFs to obtain the instantaneous phase information. The baseline data for healthy plates are also generated using the same procedure. The size of delamination is correlated with the instantaneous phase change for damage diagnosis. It is observed that the unwrapped instantaneous phase of shows a consistent behavior with the increasing delamination size.Keywords: Delamination, lamb wave, finite element method, EMD, instantaneous phase.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7282174 Soil Resistivity Structure and Its Implication on the Pole Grid Resistance for Transmission Lines
Authors: M. Nassereddine, J. Rizk, G. Nasserddine
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High Voltage (HV) transmission lines are widely spread around residential places. They take all forms of shapes: concrete, steel, and timber poles. Earth grid always form part of the HV transmission structure, whereat soil resistivity value is one of the main inputs when it comes to determining the earth grid requirements. In this paper, the soil structure and its implication on the electrode resistance of HV transmission poles will be explored. In Addition, this paper will present simulation for various soil structures using IEEE and Australian standards to verify the computation with CDEGS software. Furthermore, the split factor behavior under different soil resistivity structure will be presented using CDEGS simulations.Keywords: Earth Grid, EPR, High Voltage, Soil Resistivity Structure, Split Factor, Step Voltage, Touch Voltage.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32872173 Bi-axial Stress Effects on Barkhausen-Noise
Authors: G. Balogh, I. A. Szabó, P. Z. Kovács
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Mechanical stress has a strong effect on the magnitude of the Barkhausen-noise in structural steels. Because the measurements are performed at the surface of the material, for a sample sheet, the full effect can be described by a biaxial stress field. The measured Barkhausen-noise is dependent on the orientation of the exciting magnetic field relative to the axis of the stress tensor. The sample inhomogenities including the residual stress also modifies the angular dependence of the measured Barkhausen-noise. We have developed a laboratory device with a cross like specimen for bi-axial bending. The measuring head allowed performing excitations in two orthogonal directions. We could excite the two directions independently or simultaneously with different amplitudes. The simultaneous excitation of the two coils could be performed in phase or with a 90 degree phase shift. In principle this allows to measure the Barkhausen-noise at an arbitrary direction without moving the head, or to measure the Barkhausen-noise induced by a rotating magnetic field if a linear superposition of the two fields can be assumed.
Keywords: Barkhausen-noise, Bi-axial stress, Stress dependency, Stress measuring.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21872172 Linear Prediction System in Measuring Glucose Level in Blood
Authors: Intan Maisarah Abd Rahim, Herlina Abdul Rahim, Rashidah Ghazali
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Diabetes is a medical condition that can lead to various diseases such as stroke, heart disease, blindness and obesity. In clinical practice, the concern of the diabetic patients towards the blood glucose examination is rather alarming as some of the individual describing it as something painful with pinprick and pinch. As for some patient with high level of glucose level, pricking the fingers multiple times a day with the conventional glucose meter for close monitoring can be tiresome, time consuming and painful. With these concerns, several non-invasive techniques were used by researchers in measuring the glucose level in blood, including ultrasonic sensor implementation, multisensory systems, absorbance of transmittance, bio-impedance, voltage intensity, and thermography. This paper is discussing the application of the near-infrared (NIR) spectroscopy as a non-invasive method in measuring the glucose level and the implementation of the linear system identification model in predicting the output data for the NIR measurement. In this study, the wavelengths considered are at the 1450 nm and 1950 nm. Both of these wavelengths showed the most reliable information on the glucose presence in blood. Then, the linear Autoregressive Moving Average Exogenous model (ARMAX) model with both un-regularized and regularized methods was implemented in predicting the output result for the NIR measurement in order to investigate the practicality of the linear system in this study. However, the result showed only 50.11% accuracy obtained from the system which is far from the satisfying results that should be obtained.
Keywords: Diabetes, glucose level, linear, near-infrared (NIR), non-invasive, prediction system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8752171 Critical Factors Affecting the Implementation of Total Quality Management in the Construction Industry in U.A.E
Authors: Firas Mohamad Al-Sabek
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The purpose of the paper is to examine the most critical and important factor which will affect the implementation of Total Quality Management (TQM) in the construction industry in the United Arab Emirates. It also examines the most effected Project outcome from implementing TQM. A framework was also proposed depending on the literature studies. The method used in this paper is a quantitative study. A survey with a sample of 60 respondents was created and distributed in a construction company in Abu Dhabi, which includes 15 questions to examine the most critical factor that will affect the implementation of TQM in addition to the most effected project outcome from implementing TQM. The survey showed that management commitment is the most important factor in implementing TQM in a construction company. Also it showed that Project cost is most effected outcome from the implementation of TQM. Management commitment is very important for implementing TQM in any company. If the management loose interest in quality then everyone in the organization will do so. The success of TQM will depend mostly on the top of the pyramid. Also cost is reduced and money is saved when the project team implement TQM. While if no quality measures are present within the team, the project will suffer a commercial failure. Based on literature, more factors can be examined and added to the model. In addition, more construction companies could be surveyed in order to obtain more accurate results. Also this study could be conducted outside the United Arab Emirates for further enchantment.Keywords: Construction project, total quality management, management commitment, cost, theoretical framework.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 40702170 Enhanced Photocatalytic Hydrogen Production on TiO2 by Using Carbon Materials
Authors: Bashir Ahmmad, Kensaku Kanomata, Fumihiko Hirose
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The effect of carbon materials on TiO2 for the photocatalytic hydrogen gas production from water / alcohol mixtures was investigated. Single walled carbon nanotubes (SWNTs), multi walled carbon nanotubes (MWNTs), carbon nanofiber (CNF), fullerene (FLN), graphite (GP), and graphite silica (GS) were used as co-catalysts by directly mixing with TiO2. Drastic synergy effects were found with increase in the amount of hydrogen gas by a factor of ca. 150 and 100 for SWNTs and GS with TiO2, respectively. Moreover, the increment factor of hydrogen production reached to 180, when the mixture of SWNTs and TiO2 were smashed in an agate mortar before photocatalytic reactions. The order of H2 gas production for these carbon materials was SWNTs > GS >> MWNTs > FLN > CNF > GP. To maximize the hydrogen production from SWNTs/TiO2, various parameters of experimental condition were changed. Also, a comparison between Pt/TiO2, SWNTs/TiO2 and GS/TiO2 was made for the amount of H2 gas production. Finally, the recyclability of SWNTs/TiO2or GS/TiO2 was tested.
Keywords: Photocatalysis, carbon materials, alcohol reforming, hydrogen production, titanium oxide.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 39882169 On the Parameter Optimization of Fuzzy Inference Systems
Authors: Erika Martinez Ramirez, Rene V. Mayorga
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Nowadays, more engineering systems are using some kind of Artificial Intelligence (AI) for the development of their processes. Some well-known AI techniques include artificial neural nets, fuzzy inference systems, and neuro-fuzzy inference systems among others. Furthermore, many decision-making applications base their intelligent processes on Fuzzy Logic; due to the Fuzzy Inference Systems (FIS) capability to deal with problems that are based on user knowledge and experience. Also, knowing that users have a wide variety of distinctiveness, and generally, provide uncertain data, this information can be used and properly processed by a FIS. To properly consider uncertainty and inexact system input values, FIS normally use Membership Functions (MF) that represent a degree of user satisfaction on certain conditions and/or constraints. In order to define the parameters of the MFs, the knowledge from experts in the field is very important. This knowledge defines the MF shape to process the user inputs and through fuzzy reasoning and inference mechanisms, the FIS can provide an “appropriate" output. However an important issue immediately arises: How can it be assured that the obtained output is the optimum solution? How can it be guaranteed that each MF has an optimum shape? A viable solution to these questions is through the MFs parameter optimization. In this Paper a novel parameter optimization process is presented. The process for FIS parameter optimization consists of the five simple steps that can be easily realized off-line. Here the proposed process of FIS parameter optimization it is demonstrated by its implementation on an Intelligent Interface section dealing with the on-line customization / personalization of internet portals applied to E-commerce.Keywords: Artificial Intelligence, Fuzzy Logic, Fuzzy InferenceSystems, Nonlinear Optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19842168 Government Initiatives: The Missing Key for E-commerce Growth in KSA
Authors: R. AlGhamdi, S. Drew, S. Alkhalaf
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This paper explores the issues that influence online retailing in Saudi Arabia. Retailers in Saudi Arabia have been reserved in their adoption of electronically delivered aspects of their business. Despite the fact that Saudi Arabia has the largest and fastest growth of ICT marketplaces in the Arab region, e-commerce activities are not progressing at the same speed. Only very few Saudi companies, mostly medium and large companies from the manufacturing sector, are involved in e-commerce implementation. Based on qualitative data collected by conducting interviews with 16 retailers and 16 potential customers in Saudi Arabia, several factors influencing online retailing diffusion in Saudi Arabia are identified. However, government support comes the highest and most influencing factor for online retailing growth as identified by both parties; retailers and potential customers in Saudi Arabia.
Keywords: government support, key factor, online retailing growth, Saudi Arabia
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18522167 Modern Vibration Signal Processing Techniques for Vehicle Gearbox Fault Diagnosis
Authors: Mohamed El Morsy, Gabriela Achtenová
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This paper presents modern vibration signalprocessing techniques for vehicle gearbox fault diagnosis, via the wavelet analysis and the Squared Envelope (SE) technique. The wavelet analysis is regarded as a powerful tool for the detection of sudden changes in non-stationary signals. The Squared Envelope (SE) technique has been extensively used for rolling bearing diagnostics. In the present work a scheme of using the Squared Envelope technique for early detection of gear tooth pit. The pitting defect is manufactured on the tooth side of a fifth speed gear on the intermediate shaft of a vehicle gearbox. The objective is to supplement the current techniques of gearbox fault diagnosis based on using the raw vibration and ordered signals. The test stand is equipped with three dynamometers; the input dynamometer serves as the internal combustion engine, the output dynamometers introduce the load on the flanges of output joint shafts. The gearbox used for experimental measurements is the type most commonly used in modern small to mid-sized passenger cars with transversely mounted powertrain and front wheel drive; a five-speed gearbox with final drive gear and front wheel differential. The results show that the approaches methods are effective for detecting and diagnosing localized gear faults in early stage under different operation conditions, and are more sensitive and robust than current gear diagnostic techniques.
Keywords: Wavelet analysis, Squared Envelope, gear faults.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25782166 Silver Nanoparticles-Enhanced Luminescence Spectra of Silicon Nanocrystals
Authors: Khamael M. Abualnaja, Lidija Šiller, Benjamin R. Horrocks
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Metal-enhanced Luminescence of silicon nanocrystals (SiNCs) was determined using two different particle sizes of silver nanoparticles (AgNPs). SiNCs have been characterized by scanning electron microscopy (SEM), high resolution transmission electron microscopy (HRTEM), Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS). It is found that the SiNCs are crystalline with an average diameter of 65 nm and FCC lattice. AgNPs were synthesized using photochemical reduction of AgNO3 with sodium dodecyl sulphate (SDS). The enhanced luminescence of SiNCs by AgNPs was evaluated by confocal Raman microspectroscopy. Enhancement up to x9 and x3 times were observed for SiNCs that mixed with AgNPs which have an average particle size of 100 nm and 30 nm, respectively. Silver NPs-enhanced luminescence of SiNCs occurs as a result of the coupling between the excitation laser light and the plasmon bands of AgNPs; thus this intense field at AgNPs surface couples strongly to SiNCs.
Keywords: Luminescence, Silicon Nanocrystals, Silver Nanoparticles, Surface Enhanced Raman Spectroscopy (SERS).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28202165 Vehicle Gearbox Fault Diagnosis Based On Cepstrum Analysis
Authors: Mohamed El Morsy, Gabriela Achtenová
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Research on damage of gears and gear pairs using vibration signals remains very attractive, because vibration signals from a gear pair are complex in nature and not easy to interpret. Predicting gear pair defects by analyzing changes in vibration signal of gears pairs in operation is a very reliable method. Therefore, a suitable vibration signal processing technique is necessary to extract defect information generally obscured by the noise from dynamic factors of other gear pairs.This article presents the value of cepstrum analysis in vehicle gearbox fault diagnosis. Cepstrum represents the overall power content of a whole family of harmonics and sidebands when more than one family of sidebands is present at the same time. The concept for the measurement and analysis involved in using the technique are briefly outlined. Cepstrum analysis is used for detection of an artificial pitting defect in a vehicle gearbox loaded with different speeds and torques. The test stand is equipped with three dynamometers; the input dynamometer serves asthe internal combustion engine, the output dynamometers introduce the load on the flanges of the output joint shafts. The pitting defect is manufactured on the tooth side of a gear of the fifth speed on the secondary shaft. Also, a method for fault diagnosis of gear faults is presented based on order Cepstrum. The procedure is illustrated with the experimental vibration data of the vehicle gearbox. The results show the effectiveness of Cepstrum analysis in detection and diagnosis of the gear condition.
Keywords: Cepstrum analysis, fault diagnosis, gearbox.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33112164 Quadrotor Black-Box System Identification
Authors: Ionel Stanculeanu, Theodor Borangiu
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This paper presents a new approach in the identification of the quadrotor dynamic model using a black-box system for identification. Also the paper considers the problems which appear during the identification in the closed-loop and offers a technical solution for overcoming the correlation between the input noise present in the output
Keywords: System identification, UAV, prediction error method, quadrotor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34612163 Contrast-Enhanced Multispectal Upconversion Fluorescence Analysis for High-Resolution in-vivo Deep Tissue Imaging
Authors: Lijiang Wang, Wei Wang, Yuhong Xu
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Lanthanide-doped upconversion nanoparticles which can convert near-infrared lights to visible lights have attracted growing interest because of their great potentials in fluorescence imaging. Upconversion fluorescence imaging technique with excitation in the near-infrared (NIR) region has been used for imaging of biological cells and tissues. However, improving the detection sensitivity and decreasing the absorption and scattering in biological tissues are as yet unresolved problems. In this present study, a novel NIR-reflected multispectral imaging system was developed for upconversion fluorescent imaging in small animals. Based on this system, we have obtained the high contrast images without the autofluorescence when biocompatible UCPs were injected near the body surface or deeply into the tissue. Furthermore, we have extracted respective spectra of the upconversion fluorescence and relatively quantify the fluorescence intensity with the multispectral analysis. To our knowledge, this is the first time to analyze and quantify the upconversion fluorescence in the small animal imaging.
Keywords: Multispectral imaging, near-infrared, upconversion fluorescence imaging, upconversion nanoparticles.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17162162 Clustering of Variables Based On a Probabilistic Approach Defined on the Hypersphere
Authors: Paulo Gomes, Adelaide Figueiredo
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We consider n individuals described by p standardized variables, represented by points of the surface of the unit hypersphere Sn-1. For a previous choice of n individuals we suppose that the set of observables variables comes from a mixture of bipolar Watson distribution defined on the hypersphere. EM and Dynamic Clusters algorithms are used for identification of such mixture. We obtain estimates of parameters for each Watson component and then a partition of the set of variables into homogeneous groups of variables. Additionally we will present a factor analysis model where unobservable factors are just the maximum likelihood estimators of Watson directional parameters, exactly the first principal component of data matrix associated to each group previously identified. Such alternative model it will yield us to directly interpretable solutions (simple structure), avoiding factors rotations.
Keywords: Dynamic Clusters algorithm, EM algorithm, Factor analysis model, Hierarchical Clustering, Watson distribution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16252161 Topical Delivery of Thymidine Dinucleotide to Induce p53 Generation in the Skin by Elastic Liposome
Authors: Yi-Ping Fang, Yi-Ting Wong
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Transcription factor p53 has a powerful tumor suppressing function that is associated with many cancers. However, p53 of the molecular weight was higher make the limitation across to skin or cell membrane. Thymidine dinucleotide (pTT), an oligonucleotide, can activate the p53 transcription factor. pTT is a hydrophilic and negative charge oligonucleotide, which delivery in to cell membrane need an appropriate carrier. The aim of this study was to improve the bioavailability of the nucleotide fragment, thymidine dinucleotide (pTT), using elasic liposome carriers to deliver the drug into the skin. The study demonstrate that dioleoylphosphocholine (DOPC) incorporated with sodium cholate at molar ratio 1:1 can archived the particle size about 220 nm. This elastic liposome could penetration through skin from stratum corneum to whole epidermis by confocal laser scanning microscopy (CLSM). Moreover, we observed the the slight increase in generation of p53 by western blot.Keywords: Elastic liposome, Tymidine dinucleotide, p53, Topical delivery
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18382160 Energy-Level Structure of a Confined Electron-Positron Pair in Nanostructure
Authors: Tokuei Sako, Paul-Antoine Hervieux
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The energy-level structure of a pair of electron and positron confined in a quasi-one-dimensional nano-scale potential well has been investigated focusing on its trend in the small limit of confinement strength ω, namely, the Wigner molecular regime. An anisotropic Gaussian-type basis functions supplemented by high angular momentum functions as large as l = 19 has been used to obtain reliable full configuration interaction (FCI) wave functions. The resultant energy spectrum shows a band structure characterized by ω for the large ω regime whereas for the small ω regime it shows an energy-level pattern dominated by excitation into the in-phase motion of the two particles. The observed trend has been rationalized on the basis of the nodal patterns of the FCI wave functions.
Keywords: Confined systems, positron, wave function, Wigner molecule, quantum dots.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18552159 An Adaptive Mammographic Image Enhancement in Orthogonal Polynomials Domain
Authors: R. Krishnamoorthy, N. Amudhavalli, M.K. Sivakkolunthu
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X-ray mammography is the most effective method for the early detection of breast diseases. However, the typical diagnostic signs such as microcalcifications and masses are difficult to detect because mammograms are of low-contrast and noisy. In this paper, a new algorithm for image denoising and enhancement in Orthogonal Polynomials Transformation (OPT) is proposed for radiologists to screen mammograms. In this method, a set of OPT edge coefficients are scaled to a new set by a scale factor called OPT scale factor. The new set of coefficients is then inverse transformed resulting in contrast improved image. Applications of the proposed method to mammograms with subtle lesions are shown. To validate the effectiveness of the proposed method, we compare the results to those obtained by the Histogram Equalization (HE) and the Unsharp Masking (UM) methods. Our preliminary results strongly suggest that the proposed method offers considerably improved enhancement capability over the HE and UM methods.Keywords: mammograms, image enhancement, orthogonalpolynomials, contrast improvement
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20122158 Resource Efficiency within Current Production
Authors: Sarah Majid Ansari, Serjosha Wulf, Matthias Görke
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In times of global warming and the increasing shortage of resources, sustainable production is becoming more and more inevitable. Companies cannot only heighten their competitiveness but also contribute positively to environmental protection through efficient energy and resource consumption. Regarding this, technical solutions are often preferred during production, although organizational and process-related approaches also offer great potential. This project focuses on reducing resource usage, with a special emphasis on the human factor. It is the aspiration to develop a methodology that systematically implements and embeds suitable and individual measures and methods regarding resource efficiency throughout the entire production. The measures and methods established help employees handle resources and energy more sensitively. With this in mind, this paper also deals with the difficulties that can occur during the sensitization of employees and the implementation of these measures and methods. In addition, recommendations are given on how to avoid such difficulties.
Keywords: Implementation, human factor, production plant, resource efficiency.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19752157 Dynamic Threshold Adjustment Approach For Neural Networks
Authors: Hamza A. Ali, Waleed A. J. Rasheed
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The use of neural networks for recognition application is generally constrained by their inherent parameters inflexibility after the training phase. This means no adaptation is accommodated for input variations that have any influence on the network parameters. Attempts were made in this work to design a neural network that includes an additional mechanism that adjusts the threshold values according to the input pattern variations. The new approach is based on splitting the whole network into two subnets; main traditional net and a supportive net. The first deals with the required output of trained patterns with predefined settings, while the second tolerates output generation dynamically with tuning capability for any newly applied input. This tuning comes in the form of an adjustment to the threshold values. Two levels of supportive net were studied; one implements an extended additional layer with adjustable neuronal threshold setting mechanism, while the second implements an auxiliary net with traditional architecture performs dynamic adjustment to the threshold value of the main net that is constructed in dual-layer architecture. Experiment results and analysis of the proposed designs have given quite satisfactory conducts. The supportive layer approach achieved over 90% recognition rate, while the multiple network technique shows more effective and acceptable level of recognition. However, this is achieved at the price of network complexity and computation time. Recognition generalization may be also improved by accommodating capabilities involving all the innate structures in conjugation with Intelligence abilities with the needs of further advanced learning phases.
Keywords: Classification, Recognition, Neural Networks, Pattern Recognition, Generalization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1630