Search results for: Fuzzy predictive model
1596 Energy Loss at Drops using Neuro Solutions
Authors: Farzin Salmasi
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Energy dissipation in drops has been investigated by physical models. After determination of effective parameters on the phenomenon, three drops with different heights have been constructed from Plexiglas. They have been installed in two existing flumes in the hydraulic laboratory. Several runs of physical models have been undertaken to measured required parameters for determination of the energy dissipation. Results showed that the energy dissipation in drops depend on the drop height and discharge. Predicted relative energy dissipations varied from 10.0% to 94.3%. This work has also indicated that the energy loss at drop is mainly due to the mixing of the jet with the pool behind the jet that causes air bubble entrainment in the flow. Statistical model has been developed to predict the energy dissipation in vertical drops denotes nonlinear correlation between effective parameters. Further an artificial neural networks (ANNs) approach was used in this paper to develop an explicit procedure for calculating energy loss at drops using NeuroSolutions. Trained network was able to predict the response with R2 and RMSE 0.977 and 0.0085 respectively. The performance of ANN was found effective when compared to regression equations in predicting the energy loss.Keywords: Air bubble, drop, energy loss, hydraulic jump, NeuroSolutions
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16321595 A Proposed Technique for Software Development Risks Identification by using FTA Model
Authors: Hatem A. Khater, A. Baith Mohamed, Sara M. Kamel
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Software Development Risks Identification (SDRI), using Fault Tree Analysis (FTA), is a proposed technique to identify not only the risk factors but also the causes of the appearance of the risk factors in software development life cycle. The method is based on analyzing the probable causes of software development failures before they become problems and adversely affect a project. It uses Fault tree analysis (FTA) to determine the probability of a particular system level failures that are defined by A Taxonomy for Sources of Software Development Risk to deduce failure analysis in which an undesired state of a system by using Boolean logic to combine a series of lower-level events. The major purpose of this paper is to use the probabilistic calculations of Fault Tree Analysis approach to determine all possible causes that lead to software development risk occurrenceKeywords: Software Development Risks Identification (SDRI), Fault Tree Analysis (FTA), Taxonomy for Software Development Risks (TSDR), Probabilistic Risk Assessment (PRA).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22011594 BIM Application Research Based on the Main Entrance and Garden Area Project of Shanghai Disneyland
Authors: Ying Yuken, Pengfei Wang, Zhang Qilin, Xiao Ben
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Based on the main entrance and garden area (ME&G) project of Shanghai Disneyland, this paper introduces the application of BIM technology in this kind of low-rise comprehensive building with complex facade system, electromechanical system and decoration system. BIM technology is applied to the whole process of design, construction and completion of the whole project. With the construction of BIM application framework of the whole project, the key points of BIM modeling methods of different systems and the integration and coordination of BIM models are elaborated in detail. The specific application methods of BIM technology in similar complex low-rise building projects are sorted out. Finally, the paper summarizes the benefits of BIM technology application, and puts forward some suggestions for BIM management mode and practical application of similar projects in the future.Keywords: BIM, complex low-rise building, BIM modeling, model integration and coordination, 3D scanning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10391593 Dynamic Measurement System Modeling with Machine Learning Algorithms
Authors: Changqiao Wu, Guoqing Ding, Xin Chen
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In this paper, ways of modeling dynamic measurement systems are discussed. Specially, for linear system with single-input single-output, it could be modeled with shallow neural network. Then, gradient based optimization algorithms are used for searching the proper coefficients. Besides, method with normal equation and second order gradient descent are proposed to accelerate the modeling process, and ways of better gradient estimation are discussed. It shows that the mathematical essence of the learning objective is maximum likelihood with noises under Gaussian distribution. For conventional gradient descent, the mini-batch learning and gradient with momentum contribute to faster convergence and enhance model ability. Lastly, experimental results proved the effectiveness of second order gradient descent algorithm, and indicated that optimization with normal equation was the most suitable for linear dynamic models.Keywords: Dynamic system modeling, neural network, normal equation, second order gradient descent.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7701592 Climate Change and Environmental Education: The Application of Concept Map for Representing the Knowledge Complexity of Climate Change
Authors: Hsueh-Chih, Chen, Yau-Ting, Sung, Tsai-Wen, Lin, Hung-Teng, Chou
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It has formed an essential issue that Climate Change, composed of highly knowledge complexity, reveals its significant impact on human existence. Therefore, specific national policies, some of which present the educational aspects, have been published for overcoming the imperative problem. Accordingly, the study aims to analyze as well as integrate the relationship between Climate Change and environmental education and apply the perspective of concept map to represent the knowledge contents and structures of Climate Change; by doing so, knowledge contents of Climate Change could be represented in an even more comprehensive way and manipulated as the tool for environmental education. The method adapted for this study is knowledge conversion model compounded of the platform for experts and teachers, who were the participants for this study, to cooperate and combine each participant-s standpoints into a complete knowledge framework that is the foundation for structuring the concept map. The result of this research contains the important concepts, the precise propositions and the entire concept map for representing the robust concepts of Climate Change.
Keywords: Climate Change, knowledge complexity, concept map.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17231591 Planning a Supply Chain with Risk and Environmental Objectives
Authors: Ghanima Al-Sharrah, Haitham M. Lababidi, Yusuf I. Ali
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The main objective of the current work is to introduce sustainability factors in optimizing the supply chain model for process industries. The supply chain models are normally based on purely economic considerations related to costs and profits. To account for sustainability, two additional factors have been introduced; environment and risk. A supply chain for an entire petroleum organization has been considered for implementing and testing the proposed optimization models. The environmental and risk factors were introduced as indicators reflecting the anticipated impact of the optimal production scenarios on sustainability. The aggregation method used in extending the single objective function to multi-objective function is proven to be quite effective in balancing the contribution of each objective term. The results indicate that introducing sustainability factor would slightly reduce the economic benefit while improving the environmental and risk reduction performances of the process industries.Keywords: Supply chain, optimization, LP models, risk, environmental indicators, multi-objective.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14841590 Material Failure Process Simulation by Improve Finite Elements with Embedded Discontinuities
Authors: Juárez-Luna Gelacio, Ayala Gustavo, Retama-Velasco Jaime
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This paper shows the advantages of the material failure process simulation by improve finite elements with embedded discontinuities, using a new definition of traction vector, dependent on the discontinuity length and the angle. Particularly, two families of this kind of elements are compared: kinematically optimal symmetric and statically and kinematically optimal non-symmetric. The constitutive model to describe the behavior of the material in the symmetric formulation is a traction-displacement jump relationship equipped with softening after reaching the failure surface.
To show the validity of this symmetric formulation, representative numerical examples illustrating the performance of the proposed formulation are presented. It is shown that the non-symmetric family may over or underestimate the energy required to create a discontinuity, as this effect is related with the total length of the discontinuity, fact that is not noticed when the discontinuity path is a straight line.
Keywords: Variational formulation, strong discontinuity, embedded discontinuities, strain localization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17601589 Medical Image Segmentation Using Deformable Model and Local Fitting Binary: Thoracic Aorta
Authors: B. Bagheri Nakhjavanlo, T. S. Ellis, P.Raoofi, Sh.ziari
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This paper presents an application of level sets for the segmentation of abdominal and thoracic aortic aneurysms in CTA datasets. An important challenge in reliably detecting aortic is the need to overcome problems associated with intensity inhomogeneities. Level sets are part of an important class of methods that utilize partial differential equations (PDEs) and have been extensively applied in image segmentation. A kernel function in the level set formulation aids the suppression of noise in the extracted regions of interest and then guides the motion of the evolving contour for the detection of weak boundaries. The speed of curve evolution has been significantly improved with a resulting decrease in segmentation time compared with previous implementations of level sets, and are shown to be more effective than other approaches in coping with intensity inhomogeneities. We have applied the Courant Friedrichs Levy (CFL) condition as stability criterion for our algorithm.Keywords: Image segmentation, Level-sets, Local fitting binary, Thoracic aorta.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14451588 Effects of Photovoltaic System Introduction in Detached Houses with All-Electrified Residential Equipment in Japan
Authors: Qingrong Liu, Tetsuo Hayashi, Yuji Ryu
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In this paper, in order to investigate the effects of photovoltaic system introduction to detached houses in Japan, two kinds of works were done. Firstly, the hourly generation amount of a 4.2kW photovoltaic system were simulated in 46 cities to investigate the potential of the system in different regions in Japan using a simulation model of photovoltaic system. Secondly, based on the simulated electricity generation amount, the energy saving, the environmental and the economic effect of the photovoltaic system were examined from hourly to annual timescales, based upon calculations of typical electricity, heating, cooling and hot water supply load profiles for Japanese dwellings. The above analysis was carried out using a standard year-s hourly weather data for the different city provided by the Expanded AMeDAS Weather Data issued by AIJ (Architectural Institute of Japan).Keywords: Photovoltaic system, Energy saving, Environmental effect, Japanese dwelling, Detached house.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13571587 Sparse Unmixing of Hyperspectral Data by Exploiting Joint-Sparsity and Rank-Deficiency
Authors: Fanqiang Kong, Chending Bian
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In this work, we exploit two assumed properties of the abundances of the observed signatures (endmembers) in order to reconstruct the abundances from hyperspectral data. Joint-sparsity is the first property of the abundances, which assumes the adjacent pixels can be expressed as different linear combinations of same materials. The second property is rank-deficiency where the number of endmembers participating in hyperspectral data is very small compared with the dimensionality of spectral library, which means that the abundances matrix of the endmembers is a low-rank matrix. These assumptions lead to an optimization problem for the sparse unmixing model that requires minimizing a combined l2,p-norm and nuclear norm. We propose a variable splitting and augmented Lagrangian algorithm to solve the optimization problem. Experimental evaluation carried out on synthetic and real hyperspectral data shows that the proposed method outperforms the state-of-the-art algorithms with a better spectral unmixing accuracy.Keywords: Hyperspectral unmixing, joint-sparse, low-rank representation, abundance estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7631586 Application of Post-Stack and Pre-Stack Seismic Inversion for Prediction of Hydrocarbon Reservoirs in a Persian Gulf Gas Field
Authors: Nastaran Moosavi, Mohammad Mokhtari
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Seismic inversion is a technique which has been in use for years and its main goal is to estimate and to model physical characteristics of rocks and fluids. Generally, it is a combination of seismic and well-log data. Seismic inversion can be carried out through different methods; we have conducted and compared post-stack and pre- stack seismic inversion methods on real data in one of the fields in the Persian Gulf. Pre-stack seismic inversion can transform seismic data to rock physics such as P-impedance, S-impedance and density. While post- stack seismic inversion can just estimate P-impedance. Then these parameters can be used in reservoir identification. Based on the results of inverting seismic data, a gas reservoir was detected in one of Hydrocarbon oil fields in south of Iran (Persian Gulf). By comparing post stack and pre-stack seismic inversion it can be concluded that the pre-stack seismic inversion provides a more reliable and detailed information for identification and prediction of hydrocarbon reservoirs.Keywords: Density, P-impedance, S-impedance, post-stack seismic inversion, pre-stack seismic inversion.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22121585 Tabu Search to Draw Evacuation Plans in Emergency Situations
Authors: S. Nasri, H. Bouziri
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Disasters are quite experienced in our days. They are caused by floods, landslides, and building fires that is the main objective of this study. To cope with these unexpected events, precautions must be taken to protect human lives. The emphasis on disposal work focuses on the resolution of the evacuation problem in case of no-notice disaster. The problem of evacuation is listed as a dynamic network flow problem. Particularly, we model the evacuation problem as an earliest arrival flow problem with load dependent transit time. This problem is classified as NP-Hard. Our challenge here is to propose a metaheuristic solution for solving the evacuation problem. We define our objective as the maximization of evacuees during earliest periods of a time horizon T. The objective provides the evacuation of persons as soon as possible. We performed an experimental study on emergency evacuation from the tunisian children’s hospital. This work prompts us to look for evacuation plans corresponding to several situations where the network dynamically changes.
Keywords: Dynamic network flow, Load dependent transit time, Evacuation strategy, Earliest arrival flow problem.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17891584 Cardiac Disorder Classification Based On Extreme Learning Machine
Authors: Chul Kwak, Oh-Wook Kwon
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In this paper, an extreme learning machine with an automatic segmentation algorithm is applied to heart disorder classification by heart sound signals. From continuous heart sound signals, the starting points of the first (S1) and the second heart pulses (S2) are extracted and corrected by utilizing an inter-pulse histogram. From the corrected pulse positions, a single period of heart sound signals is extracted and converted to a feature vector including the mel-scaled filter bank energy coefficients and the envelope coefficients of uniform-sized sub-segments. An extreme learning machine is used to classify the feature vector. In our cardiac disorder classification and detection experiments with 9 cardiac disorder categories, the proposed method shows significantly better performance than multi-layer perceptron, support vector machine, and hidden Markov model; it achieves the classification accuracy of 81.6% and the detection accuracy of 96.9%.
Keywords: Heart sound classification, extreme learning machine
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19211583 Effect of Blade Number on a Straight-Bladed Vertical-Axis Darreius Wind Turbine
Authors: Marco Raciti Castelli, Stefano De Betta, Ernesto Benini
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This paper presents a mean for reducing the torque variation during the revolution of a vertical-axis wind turbine (VAWT) by increasing the blade number. For this purpose, twodimensional CDF analysis have been performed on a straight-bladed Darreius-type rotor. After describing the computational model, a complete campaign of simulations based on full RANS unsteady calculations is proposed for a three, four and five-bladed rotor architecture characterized by a NACA 0025 airfoil. For each proposed rotor configuration, flow field characteristics are investigated at several values of tip speed ratio, allowing a quantification of the influence of blade number on flow geometric features and dynamic quantities, such as rotor torque and power. Finally, torque and power curves are compared for the analyzed architectures, achieving a quantification of the effect of blade number on overall rotor performance.Keywords: CFD, VAWT, NACA 0021, blade number
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 53181582 Modeling of Radiofrequency Nerve Lesioning in Inhomogeneous Media
Authors: Nour Ismail, Sahar El Kardawy, Bassant Badwy
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Radiofrequency (RF) lesioning of nerves have been commonly used to alleviate chronic pain, where RF current preventing transmission of pain signals through the nerve by heating the nerve causing the pain. There are some factors that affect the temperature distribution and the nerve lesion size, one of these factors is the inhomogeneities in the tissue medium. Our objective is to calculate the temperature distribution and the nerve lesion size in an inhomogeneous medium surrounding the RF electrode. A two 3-D finite element models are used to compare the temperature distribution in the homogeneous and inhomogeneous medium. Also the effect of temperature-dependent electric conductivity on maximum temperature and lesion size is observed. Results show that the presence of an inhomogeneous medium around the RF electrode has a valuable effect on the temperature distribution and lesion size. The dependency of electric conductivity on tissue temperature increased lesion size.
Keywords: Finite element model, nerve lesioning, pain relief, radiofrequency lesion.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19621581 Numerical Investigation of Thermally Triggered Release Kinetics of Double Emulsion for Drug Delivery Using Phase Change Material
Authors: Yong Ren, Yaping Zhang
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A numerical model has been developed to investigate the thermally triggered release kinetics for drug delivery using phase change material as shell of microcapsules. Biocompatible material n-Eicosane is used as demonstration. PCM shell of microcapsule will remain in solid form after the drug is taken, so the drug will be encapsulated by the shell, and will not be released until the target body part of lesion is exposed to external heat source, which will thermally trigger the release kinetics, leading to solid-to-liquid phase change. The findings can lead to better understanding on the key effects influencing the phase change process for drug delivery applications. The facile approach to release drug from core/shell structure of microcapsule can be well integrated with organic solvent free fabrication of microcapsules, using double emulsion as template in microfluidic aqueous two phase system.
Keywords: Phase change material, drug release kinetics, double emulsion, microfluidics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24001580 Deployment of a Biocompatible International Space Station into Geostationary Orbit
Authors: Tim Falk, Chris Chatwin
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This study explores the possibility of a space station that will occupy a geostationary equatorial orbit (GEO) and create artificial gravity using centripetal acceleration. The concept of the station is to create a habitable, safe environment that can increase the possibility of space tourism by reducing the wide variation of hazards associated with space exploration. The ability to control the intensity of artificial gravity through Hall-effect thrusters will allow experiments to be carried out at different levels of artificial gravity. A feasible prototype model was built to convey the concept and to enable cost estimation. The SpaceX Falcon Heavy rocket with a 26,700 kg payload to GEO was selected to take the 675 tonne spacecraft into orbit; space station construction will require up to 30 launches, this would be reduced to 5 launches when the SpaceX BFR becomes available. The estimated total cost of implementing the Sussex Biocompatible International Space Station (BISS) is approximately $47.039 billion, which is very attractive when compared to the cost of the International Space Station, which cost $150 billion.
Keywords: Artificial gravity, biocompatible, geostationary orbit, space station.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5521579 A Study on the Circumstances Affecting Elementary School Students in Their Familyand School Lives and Their Consequential Emotions
Authors: Osman Samancı, Ramazan Kaya
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The purpose of this study is to determine the circumstances affecting elementary school students in their family and school lives and what kind of emotions children may feel because of these circumstances. The study was carried out according to the survey model. Four Turkish elementary schools provided 123 fourth grade students for participation in the study. The study-s data were collected by using worksheets for the activity titled “Important Days in Our Lives", which was part of the Elementary School Social Sciences Course 4th Grade Education Program. Data analysis was carried out according to the content analysis technique used in qualitative research. The study detected that circumstances of their family and school lives caused children to feel emotions such as happiness, sadness, anger, fear and jealousy. The circumstances and the emotions caused by these circumstances were analyzed according to gender and interpreted by presenting them with their frequencies.Keywords: Elementary school students, emotional development, family and school, social development.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13751578 Experiments on Element and Document Statistics for XML Retrieval
Authors: Mohamed Ben Aouicha, Mohamed Tmar, Mohand Boughanem, Mohamed Abid
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This paper presents an information retrieval model on XML documents based on tree matching. Queries and documents are represented by extended trees. An extended tree is built starting from the original tree, with additional weighted virtual links between each node and its indirect descendants allowing to directly reach each descendant. Therefore only one level separates between each node and its indirect descendants. This allows to compare the user query and the document with flexibility and with respect to the structural constraints of the query. The content of each node is very important to decide weither a document element is relevant or not, thus the content should be taken into account in the retrieval process. We separate between the structure-based and the content-based retrieval processes. The content-based score of each node is commonly based on the well-known Tf × Idf criteria. In this paper, we compare between this criteria and another one we call Tf × Ief. The comparison is based on some experiments into a dataset provided by INEX1 to show the effectiveness of our approach on one hand and those of both weighting functions on the other.Keywords: XML retrieval, INEX, Tf × Idf, Tf × Ief
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13221577 Non-Population Search Algorithms for Capacitated Material Requirement Planning in Multi-Stage Assembly Flow Shop with Alternative Machines
Authors: Watcharapan Sukkerd, Teeradej Wuttipornpun
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This paper aims to present non-population search algorithms called tabu search (TS), simulated annealing (SA) and variable neighborhood search (VNS) to minimize the total cost of capacitated MRP problem in multi-stage assembly flow shop with two alternative machines. There are three main steps for the algorithm. Firstly, an initial sequence of orders is constructed by a simple due date-based dispatching rule. Secondly, the sequence of orders is repeatedly improved to reduce the total cost by applying TS, SA and VNS separately. Finally, the total cost is further reduced by optimizing the start time of each operation using the linear programming (LP) model. Parameters of the algorithm are tuned by using real data from automotive companies. The result shows that VNS significantly outperforms TS, SA and the existing algorithm.
Keywords: Capacitated MRP, non-population search algorithms, linear programming, assembly flow shop.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9461576 A Conceptual Framework on Review of E-Service Quality in Banking Industry
Authors: Vivek Agrawal, Vikas Tripathi, Nitin Seth
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E-service quality plays a significant role to achieve success or failure in any organization, offering services online. It will increase the competition among the organizations, to attract the customers on the basis of the quality of service provided by the organization. Better e-service quality will enhance the relationship with customers and their satisfaction. So the measurement of eservice quality is very important but it is a complex process due to the complex nature of services. Literature predicts that there is a lack of universal definition of e-service quality. The e-service quality measures in banking have great importance in achieving high customer base. This paper proposes a conceptual model for measuring e-service quality in Indian Banking Industry. Nine dimensions reliability, ease of use, personalization, security and trust, website aesthetic, responsiveness, contact and fulfillment had been identified. The results of this paper may help to develop a proper scale to measure the e-service quality in Indian Banking Industry, which may assist to maintain and improve the performance and effectiveness of e-service quality to retain customers.
Keywords: Banking, Service Quality, e-service quality, Dimensions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 54781575 Methods for Distinction of Cattle Using Supervised Learning
Authors: Radoslav Židek, Veronika Šidlová, Radovan Kasarda, Birgit Fuerst-Waltl
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Machine learning represents a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. The data can present identification patterns which are used to classify into groups. The result of the analysis is the pattern which can be used for identification of data set without the need to obtain input data used for creation of this pattern. An important requirement in this process is careful data preparation validation of model used and its suitable interpretation. For breeders, it is important to know the origin of animals from the point of the genetic diversity. In case of missing pedigree information, other methods can be used for traceability of animal´s origin. Genetic diversity written in genetic data is holding relatively useful information to identify animals originated from individual countries. We can conclude that the application of data mining for molecular genetic data using supervised learning is an appropriate tool for hypothesis testing and identifying an individual.
Keywords: Genetic data, Pinzgau cattle, supervised learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23071574 Modeling of Single Bay Precast Residential House Using Ruaumoko 2D Program
Authors: N. H. Hamid, N. M. Mohamed, S. A. Anuar
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Precast residential houses are normally constructed in Malaysia using precast shear-key wall panel and this panel is designed using BS8110 where there is no provision for earthquake. However, the safety of this house under moderate and strong earthquake is still questionable. Consequently, the full-scale of residential house are designed, constructed, tested and analyzed under in-plane lateral quasi-static cyclic loading. Hysteresis loops are plotted based on the experimental work and compared with modeling of hysteresis loops using HYSTERES in RUAUMOKO 2D program. Modified Takeda hysteresis model is chosen to behave a similar pattern with experimental work. This program will display the earthquake excitations, spectral displacements, pseudo spectral acceleration, mode shape and deformation of the structure. It can be concluded that this building is suffering severe cracks and damage under moderate and severe earthquake.
Keywords: Deformation shape, hysteresis loops, precast shear-key, spectral displacement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20491573 Comparative Analysis of Geographical Routing Protocol in Wireless Sensor Networks
Authors: Rahul Malhotra
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The field of wireless sensor networks (WSN) engages a lot of associates in the research community as an interdisciplinary field of interest. This type of network is inexpensive, multifunctionally attributable to advances in micro-electromechanical systems and conjointly the explosion and expansion of wireless communications. A mobile ad hoc network is a wireless network without fastened infrastructure or federal management. Due to the infrastructure-less mode of operation, mobile ad-hoc networks are gaining quality. During this work, we have performed an efficient performance study of the two major routing protocols: Ad hoc On-Demand Distance Vector Routing (AODV) and Dynamic Source Routing (DSR) protocols. We have used an accurate simulation model supported NS2 for this purpose. Our simulation results showed that AODV mitigates the drawbacks of the DSDV and provides better performance as compared to DSDV.
Keywords: Routing protocols, mobility, Mobile Ad-hoc Networks, Ad-hoc On-demand Distance Vector, Dynamic Source Routing, Destination Sequence Distance Vector, Quality of Service.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6991572 A Robust Eyelashes and Eyelid Detection in Transformation Invariant Iris Recognition: In Application with LRC Security System
Authors: R. Bremananth
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Biometric authentication is an essential task for any kind of real-life applications. In this paper, we contribute two primary paradigms to Iris recognition such as Robust Eyelash Detection (RED) using pathway kernels and hair curve fitting synthesized model. Based on these two paradigms, rotation invariant iris recognition is enhanced. In addition, the presented framework is tested with real-life iris data to provide the authentication for LRC (Learning Resource Center) users. Recognition performance is significantly improved based on the contributed schemes by evaluating real-life irises. Furthermore, the framework has been implemented using Java programming language. Experiments are performed based on 1250 diverse subjects in different angles of variations on the authentication process. The results revealed that the methodology can deploy in the process on LRC management system and other security required applications.Keywords: Authentication, biometric, eye lashes detection, iris scanning, LRC security, secure access.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10281571 Real-Time Visual Simulation and Interactive Animation of Shadow Play Puppets Using OpenGL
Authors: Tan Kian Lam, Abdullah Zawawi bin Haji Talib, Mohd. Azam Osman
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This paper describes a method of modeling to model shadow play puppet using sophisticated computer graphics techniques available in OpenGL in order to allow interactive play in real-time environment as well as producing realistic animation. This paper proposes a novel real-time method is proposed for modeling of puppet and its shadow image that allows interactive play of virtual shadow play using texture mapping and blending techniques. Special effects such as lighting and blurring effects for virtual shadow play environment are also developed. Moreover, the use of geometric transformations and hierarchical modeling facilitates interaction among the different parts of the puppet during animation. Based on the experiments and the survey that were carried out, the respondents involved are very satisfied with the outcomes of these techniques.Keywords: Animation, blending, hierarchical modeling, interactive play, real-time, shadow play, visual simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24941570 Hybrid Feature and Adaptive Particle Filter for Robust Object Tracking
Authors: Xinyue Zhao, Yutaka Satoh, Hidenori Takauji, Shun'ichi Kaneko
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A hybrid feature based adaptive particle filter algorithm is presented for object tracking in real scenarios with static camera. The hybrid feature is combined by two effective features: the Grayscale Arranging Pairs (GAP) feature and the color histogram feature. The GAP feature has high discriminative ability even under conditions of severe illumination variation and dynamic background elements, while the color histogram feature has high reliability to identify the detected objects. The combination of two features covers the shortage of single feature. Furthermore, we adopt an updating target model so that some external problems such as visual angles can be overcame well. An automatic initialization algorithm is introduced which provides precise initial positions of objects. The experimental results show the good performance of the proposed method.Keywords: Hybrid feature, adaptive Particle Filter, robust Object Tracking, Grayscale Arranging Pairs (GAP) feature.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15201569 The Effect of User Comments on Traffic Application Usage
Authors: I. Gokasar, G. Bakioglu
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With the unprecedented rates of technological improvements, people start to solve their problems with the help of technological tools. According to application stores and websites in which people evaluate and comment on the traffic apps, there are more than 100 traffic applications which have different features with respect to their purpose of usage ranging from the features of traffic apps for public transit modes to the features of traffic apps for private cars. This study focuses on the top 30 traffic applications which were chosen with respect to their download counts. All data about the traffic applications were obtained from related websites. The purpose of this study is to analyze traffic applications in terms of their categorical attributes with the help of developing a regression model. The analysis results suggest that negative interpretations (e.g., being deficient) does not lead to lower star ratings of the applications. However, those negative interpretations result in a smaller increase in star rate. In addition, women use higher star rates than men for the evaluation of traffic applications.
Keywords: Traffic App, real–time information, traffic congestion, regression analysis, dummy variables.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11701568 Performance Investigation of Solid-Rocket Motor with Nozzle Throat Erosion
Authors: Suwicha Chankapoe, Nattawat Winya, Narupon Pittayaprasertkul
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In order to determine the performance and key design parameters of rocket, the erosion of nozzle throat during solid rocket motor burning have to be calculated. This study aims to predict the nozzle throat erosion in solid rocket motors according to the thrust profile of motor in operating conditions and develop a model for optimum performance of rocket. We investigate the throat radius change in the static test programs. The standard method and thrust coefficient are used for adjusting into the ideal performance for conical nozzles. Pressure and thrust data acquired from the tests are analyzed to determine the instantaneous nozzle throat diameter variation throughout the test duration. The result shows good agreement of calculated correlation comparing with measured erosion rate data showing agreement within 1.6 mm/s. Nozzle thrust coefficient loss is found approximately 24% form nozzle throat erosion during burning.
Keywords: Erosion, nozzle throat, thrust coefficient.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 50241567 Artificial Neural Network Approach for Inventory Management Problem
Authors: Govind Shay Sharma, Randhir Singh Baghel
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The stock management of raw materials and finished goods is a significant issue for industries in fulfilling customer demand. Optimization of inventory strategies is crucial to enhancing customer service, reducing lead times and costs, and meeting market demand. This paper suggests finding an approach to predict the optimum stock level by utilizing past stocks and forecasting the required quantities. In this paper, we utilized Artificial Neural Network (ANN) to determine the optimal value. The objective of this paper is to discuss the optimized ANN that can find the best solution for the inventory model. In the context of the paper, we mentioned that the k-means algorithm is employed to create homogeneous groups of items. These groups likely exhibit similar characteristics or attributes that make them suitable for being managed using uniform inventory control policies. The paper proposes a method that uses the neural fit algorithm to control the cost of inventory.
Keywords: Artificial Neural Network, inventory management, optimization, distributor center.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 146