Search results for: octree compression techniques
2217 Anticipation of Bending Reinforcement Based on Iranian Concrete Code Using Meta-Heuristic Tools
Authors: Seyed Sadegh Naseralavi, Najmeh Bemani
Abstract:
In this paper, different concrete codes including America, New Zealand, Mexico, Italy, India, Canada, Hong Kong, Euro Code and Britain are compared with the Iranian concrete design code. First, by using Adaptive Neuro Fuzzy Inference System (ANFIS), the codes having the most correlation with the Iranian ninth issue of the national regulation are determined. Consequently, two anticipated methods are used for comparing the codes: Artificial Neural Network (ANN) and Multi-variable regression. The results show that ANN performs better. Predicting is done by using only tensile steel ratio and with ignoring the compression steel ratio.
Keywords: Concrete design code, anticipate method, artificial neural network, multi-variable regression, adaptive neuro fuzzy inference system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8072216 Multidimensional Performance Management
Authors: David Wiese
Abstract:
In order to maximize efficiency of an information management platform and to assist in decision making, the collection, storage and analysis of performance-relevant data has become of fundamental importance. This paper addresses the merits and drawbacks provided by the OLAP paradigm for efficiently navigating large volumes of performance measurement data hierarchically. The system managers or database administrators navigate through adequately (re)structured measurement data aiming to detect performance bottlenecks, identify causes for performance problems or assessing the impact of configuration changes on the system and its representative metrics. Of particular importance is finding the root cause of an imminent problem, threatening availability and performance of an information system. Leveraging OLAP techniques, in contrast to traditional static reporting, this is supposed to be accomplished within moderate amount of time and little processing complexity. It is shown how OLAP techniques can help improve understandability and manageability of measurement data and, hence, improve the whole Performance Analysis process.
Keywords: Data Warehousing, OLAP, Multidimensional Navigation, Performance Diagnosis, Performance Management, Performance Tuning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21192215 Comparison of ANN and Finite Element Model for the Prediction of Ultimate Load of Thin-Walled Steel Perforated Sections in Compression
Authors: Zhi-Jun Lu, Qi Lu, Meng Wu, Qian Xiang, Jun Gu
Abstract:
The analysis of perforated steel members is a 3D problem in nature, therefore the traditional analytical expressions for the ultimate load of thin-walled steel sections cannot be used for the perforated steel member design. In this study, finite element method (FEM) and artificial neural network (ANN) were used to simulate the process of stub column tests based on specific codes. Results show that compared with those of the FEM model, the ultimate load predictions obtained from ANN technique were much closer to those obtained from the physical experiments. The ANN model for the solving the hard problem of complex steel perforated sections is very promising.Keywords: Artificial neural network, finite element method, perforated sections, thin-walled steel, ultimate load.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10522214 Wood Species Recognition System
Authors: Bremananth R, Nithya B, Saipriya R
Abstract:
The proposed system identifies the species of the wood using the textural features present in its barks. Each species of a wood has its own unique patterns in its bark, which enabled the proposed system to identify it accurately. Automatic wood recognition system has not yet been well established mainly due to lack of research in this area and the difficulty in obtaining the wood database. In our work, a wood recognition system has been designed based on pre-processing techniques, feature extraction and by correlating the features of those wood species for their classification. Texture classification is a problem that has been studied and tested using different methods due to its valuable usage in various pattern recognition problems, such as wood recognition, rock classification. The most popular technique used for the textural classification is Gray-level Co-occurrence Matrices (GLCM). The features from the enhanced images are thus extracted using the GLCM is correlated, which determines the classification between the various wood species. The result thus obtained shows a high rate of recognition accuracy proving that the techniques used in suitable to be implemented for commercial purposes.Keywords: Correlation, Grey Level Co-Occurrence Matrix, ProbabilityDensity Function, Wood Recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24502213 An Enhanced Tool for Implementing Dialogue Forms in Conversational Applications
Authors: Ilias Spais, George Bafas
Abstract:
Natural Language Understanding Systems (NLU) will not be widely deployed unless they are technically mature and cost effective to develop. Cost effective development hinges on the availability of tools and techniques enabling the rapid production of NLU applications through minimal human resources. Further, these tools and techniques should allow quick development of applications in a user friendly way and should be easy to upgrade in order to continuously follow the evolving technologies and standards. This paper presents a visual tool for the structuring and editing of dialog forms, the key element of driving conversation in NLU applications based on IBM technology. The main focus is given on the basic component used to describe Human – Machine interactions of that kind, the Dialogue Manager. In essence, the description of a tool that enables the visual representation of the Dialogue Manager mainly during the implementation phase is illustrated.
Keywords: Conversational Applications, Forms Dialogue Manager (FDM), Natural Language Processing, Natural Language Understanding.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14372212 Design Analysis of a Slotted Microstrip Antenna for Wireless Communication
Authors: Norbahiah Misran, Mohammed N. Shakib, Mohammad T. Islam, Baharudin Yatim
Abstract:
In this paper, a new design technique for enhancing bandwidth that improves the performance of a conventional microstrip patch antenna is proposed. This paper presents a novel wideband probe fed inverted slotted microstrip patch antenna. The design adopts contemporary techniques; coaxial probe feeding, inverted patch structure and slotted patch. The composite effect of integrating these techniques and by introducing the proposed patch, offer a low profile, broadband, high gain, and low cross-polarization level. The results for the VSWR, gain and co-and cross-polarization patterns are presented. The antenna operating the band of 1.80-2.36 GHz shows an impedance bandwidth (2:1 VSWR) of 27% and a gain of 10.18 dBi with a gain variation of 1.12 dBi. Good radiation characteristics, including a cross-polarization level in xz-plane less than -42 dB, have been obtained.Keywords: Slotted antenna, microstrip patch antenna, wideband, coaxial probe fed.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28842211 Vr-GIS and Ar-GIS In Education: A Case Study
Authors: Ilario Gabriele Gerloni, Vincenza Carchiolo, Alessandro Longheu, Ugo Becciani, Eva Sciacca, Fabio Vitello
Abstract:
ICT tools and platforms endorse more and more educational process. Many models and techniques for people to be educated and trained about specific topics and skills do exist, as classroom lectures with textbooks, computers, handheld devices and others. The choice to what extent ICT is applied within learning contexts is related to personal access to technologies as well as to the infrastructure surrounding environment. Among recent techniques, the adoption of Virtual Reality (VR) and Augmented Reality (AR) provides significant impulse in fully engaging users senses. In this paper, an application of AR/VR within Geographic Information Systems (GIS) context is presented. It aims to provide immersive environment experiences for educational and training purposes (e.g. for civil protection personnel), useful especially for situations where real scenarios are not easily accessible by humans. First acknowledgments are promising for building an effective tool that helps civil protection personnel training with risk reduction.Keywords: Education, virtual reality, augmented reality, civil protection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9002210 Fake Account Detection in Twitter Based on Minimum Weighted Feature set
Authors: Ahmed El Azab, Amira M. Idrees, Mahmoud A. Mahmoud, Hesham Hefny
Abstract:
Social networking sites such as Twitter and Facebook attracts over 500 million users across the world, for those users, their social life, even their practical life, has become interrelated. Their interaction with social networking has affected their life forever. Accordingly, social networking sites have become among the main channels that are responsible for vast dissemination of different kinds of information during real time events. This popularity in Social networking has led to different problems including the possibility of exposing incorrect information to their users through fake accounts which results to the spread of malicious content during life events. This situation can result to a huge damage in the real world to the society in general including citizens, business entities, and others. In this paper, we present a classification method for detecting the fake accounts on Twitter. The study determines the minimized set of the main factors that influence the detection of the fake accounts on Twitter, and then the determined factors are applied using different classification techniques. A comparison of the results of these techniques has been performed and the most accurate algorithm is selected according to the accuracy of the results. The study has been compared with different recent researches in the same area; this comparison has proved the accuracy of the proposed study. We claim that this study can be continuously applied on Twitter social network to automatically detect the fake accounts; moreover, the study can be applied on different social network sites such as Facebook with minor changes according to the nature of the social network which are discussed in this paper.Keywords: Fake accounts detection, classification algorithms, twitter accounts analysis, features based techniques.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 58182209 Detecting and Measuring Fabric Pills Using Digital Image Analysis
Authors: Dariush Semnani, Hossein Ghayoor
Abstract:
In this paper a novel method was presented for evaluating the fabric pills using digital image processing techniques. This work provides a novel technique for detecting pills and also measuring their heights, surfaces and volumes. Surely, measuring the intensity of defects by human vision is an inaccurate method for quality control; as a result, this problem became a motivation for employing digital image processing techniques for detection of defects of fabric surface. In the former works, the systems were just limited to measuring of the surface of defects, but in the presented method the height and the volume of defects were also measured, which leads to a more accurate quality control. An algorithm was developed to first, find pills and then measure their average intensity by using three criteria of height, surface and volume. The results showed a meaningful relation between the number of rotations and the quality of pilled fabrics.Keywords: 3D analysis, computer vision, fabric, pile, surface evaluation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26082208 Audio Watermarking Using Spectral Modifications
Authors: Jyotsna Singh, Parul Garg, Alok Nath De
Abstract:
In this paper, we present a non-blind technique of adding the watermark to the Fourier spectral components of audio signal in a way such that the modified amplitude does not exceed the maximum amplitude spread (MAS). This MAS is due to individual Discrete fourier transform (DFT) coefficients in that particular frame, which is derived from the Energy Spreading function given by Schroeder. Using this technique one can store double the information within a given frame length i.e. overriding the watermark on the host of equal length with least perceptual distortion. The watermark is uniformly floating on the DFT components of original signal. This helps in detecting any intentional manipulations done on the watermarked audio. Also, the scheme is found robust to various signal processing attacks like presence of multiple watermarks, Additive white gaussian noise (AWGN) and mp3 compression.Keywords: Discrete Fourier Transform, Spreading Function, Watermark, Pseudo Noise Sequence, Spectral Masking Effect
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16912207 A Heuristics Approach for Fast Detecting Suspicious Money Laundering Cases in an Investment Bank
Authors: Nhien-An Le-Khac, Sammer Markos, M-Tahar Kechadi
Abstract:
Today, money laundering (ML) poses a serious threat not only to financial institutions but also to the nation. This criminal activity is becoming more and more sophisticated and seems to have moved from the cliché of drug trafficking to financing terrorism and surely not forgetting personal gain. Most international financial institutions have been implementing anti-money laundering solutions (AML) to fight investment fraud. However, traditional investigative techniques consume numerous man-hours. Recently, data mining approaches have been developed and are considered as well-suited techniques for detecting ML activities. Within the scope of a collaboration project for the purpose of developing a new solution for the AML Units in an international investment bank, we proposed a data mining-based solution for AML. In this paper, we present a heuristics approach to improve the performance for this solution. We also show some preliminary results associated with this method on analysing transaction datasets.Keywords: data mining, anti money laundering, clustering, heuristics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35692206 Techniques of Construction Management in Civil Engineering
Authors: Mamoon M. Atout
Abstract:
The Middle East Gulf region has witnessed rapid growth and development in many areas over the last two decades. The development of the real-estate sector, construction industry and infrastructure projects are a major share of the development that has participated in the civilization of the countries of the Gulf. Construction industry projects were planned and managed by different types of experts, who came from all over the world having different types of experiences in construction management and industry. Some of these projects were completed on time, while many were not, due to many accumulating factors. Many accumulated factors are considered as the principle reason for the problem experienced at the project construction stage, which reflected negatively on the project success. Specific causes of delay have been identified by construction managers to avoid any unexpected delays through proper analysis and considerations to some implications such as risk assessment and analysis for many potential problems to ensure that projects will be delivered on time. Construction management implications were adopted and considered by project managers who have experience and knowledge in applying the techniques of the system of engineering construction management. The aim of this research is to determine the benefits of the implications of construction management by the construction team and level of considerations of the techniques and processes during the project development and construction phases to avoid any delay in the projects. It also aims to determine the factors that participate to project completion delays in case project managers are not well committed to their roles and responsibilities. The results of the analysis will determine the necessity of the applications required by the project team to avoid the causes of delays that help them deliver projects on time, e.g. verifying tender documents, quantities and preparing the construction method of the project.
Keywords: Construction management, control process, cost control, planning and scheduling, roles and responsibilities.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14062205 Application of a New Hybrid Optimization Algorithm on Cluster Analysis
Authors: T. Niknam, M. Nayeripour, B.Bahmani Firouzi
Abstract:
Clustering techniques have received attention in many areas including engineering, medicine, biology and data mining. The purpose of clustering is to group together data points, which are close to one another. The K-means algorithm is one of the most widely used techniques for clustering. However, K-means has two shortcomings: dependency on the initial state and convergence to local optima and global solutions of large problems cannot found with reasonable amount of computation effort. In order to overcome local optima problem lots of studies done in clustering. This paper is presented an efficient hybrid evolutionary optimization algorithm based on combining Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO), called PSO-ACO, for optimally clustering N object into K clusters. The new PSO-ACO algorithm is tested on several data sets, and its performance is compared with those of ACO, PSO and K-means clustering. The simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for handing data clustering.
Keywords: Ant Colony Optimization (ACO), Data clustering, Hybrid evolutionary optimization algorithm, K-means clustering, Particle Swarm Optimization (PSO).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21862204 A Novel Multiresolution based Optimization Scheme for Robust Affine Parameter Estimation
Authors: J.Dinesh Peter
Abstract:
This paper describes a new method for affine parameter estimation between image sequences. Usually, the parameter estimation techniques can be done by least squares in a quadratic way. However, this technique can be sensitive to the presence of outliers. Therefore, parameter estimation techniques for various image processing applications are robust enough to withstand the influence of outliers. Progressively, some robust estimation functions demanding non-quadratic and perhaps non-convex potentials adopted from statistics literature have been used for solving these. Addressing the optimization of the error function in a factual framework for finding a global optimal solution, the minimization can begin with the convex estimator at the coarser level and gradually introduce nonconvexity i.e., from soft to hard redescending non-convex estimators when the iteration reaches finer level of multiresolution pyramid. Comparison has been made to find the performance of the results of proposed method with the results found individually using two different estimators.Keywords: Image Processing, Affine parameter estimation, Outliers, Robust Statistics, Robust M-estimators
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14462203 Establishing Pairwise Keys Using Key Predistribution Schemes for Sensor Networks
Authors: Y. Harold Robinson, M. Rajaram
Abstract:
Designing cost-efficient, secure network protocols for Wireless Sensor Networks (WSNs) is a challenging problem because sensors are resource-limited wireless devices. Security services such as authentication and improved pairwise key establishment are critical to high efficient networks with sensor nodes. For sensor nodes to correspond securely with each other efficiently, usage of cryptographic techniques is necessary. In this paper, two key predistribution schemes that enable a mobile sink to establish a secure data-communication link, on the fly, with any sensor nodes. The intermediate nodes along the path to the sink are able to verify the authenticity and integrity of the incoming packets using a predicted value of the key generated by the sender’s essential power. The proposed schemes are based on the pairwise key with the mobile sink, our analytical results clearly show that our schemes perform better in terms of network resilience to node capture than existing schemes if used in wireless sensor networks with mobile sinks.Keywords: Wireless Sensor Networks, predistribution scheme, cryptographic techniques.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15772202 The Effect of Program Type on Mutation Testing: Comparative Study
Authors: B. Falah, N. E. Abakouy
Abstract:
Due to its high computational cost, mutation testing has been neglected by researchers. Recently, many cost and mutants’ reduction techniques have been developed, improved, and experimented, but few of them has relied the possibility of reducing the cost of mutation testing on the program type of the application under test. This paper is a comparative study between four operators’ selection techniques (mutants sampling, class level operators, method level operators, and all operators’ selection) based on the program code type of each application under test. It aims at finding an alternative approach to reveal the effect of code type on mutation testing score. The result of our experiment shows that the program code type can affect the mutation score and that the programs using polymorphism are best suited to be tested with mutation testing.Keywords: Equivalent mutant, killed mutant, mutation score, mutation testing, program code type.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14042201 Robust Image Registration Based on an Adaptive Normalized Mutual Information Metric
Authors: Huda Algharib, Amal Algharib, Hanan Algharib, Ali Mohammad Alqudah
Abstract:
Image registration is an important topic for many imaging systems and computer vision applications. The standard image registration techniques such as Mutual information/ Normalized mutual information -based methods have a limited performance because they do not consider the spatial information or the relationships between the neighbouring pixels or voxels. In addition, the amount of image noise may significantly affect the registration accuracy. Therefore, this paper proposes an efficient method that explicitly considers the relationships between the adjacent pixels, where the gradient information of the reference and scene images is extracted first, and then the cosine similarity of the extracted gradient information is computed and used to improve the accuracy of the standard normalized mutual information measure. Our experimental results on different data types (i.e. CT, MRI and thermal images) show that the proposed method outperforms a number of image registration techniques in terms of the accuracy.
Keywords: Image registration, mutual information, image gradients, Image transformations.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8812200 Frame Texture Classification Method (FTCM) Applied on Mammograms for Detection of Abnormalities
Authors: Kjersti Engan, Karl Skretting, Jostein Herredsvela, Thor Ole Gulsrud
Abstract:
Texture classification is an important image processing task with a broad application range. Many different techniques for texture classification have been explored. Using sparse approximation as a feature extraction method for texture classification is a relatively new approach, and Skretting et al. recently presented the Frame Texture Classification Method (FTCM), showing very good results on classical texture images. As an extension of that work the FTCM is here tested on a real world application as detection of abnormalities in mammograms. Some extensions to the original FTCM that are useful in some applications are implemented; two different smoothing techniques and a vector augmentation technique. Both detection of microcalcifications (as a primary detection technique and as a last stage of a detection scheme), and soft tissue lesions in mammograms are explored. All the results are interesting, and especially the results using FTCM on regions of interest as the last stage in a detection scheme for microcalcifications are promising.Keywords: detection, mammogram, texture classification, dictionary learning, FTCM
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13752199 The Costume Design by the Inspiration of The Figurehead of Thai Royal Barges
Authors: Taechit Cheuypoung
Abstract:
The purpose of this research was to design costume by the inspiration from the configurations, colors and decorations of Thai Royal Barges. The researcher investigated the bibliographies and the important of the Thai Royal Water-Course Procession, configurations and decoration techniques of four Royal Barges history. Furthermore, the researcher combined the contemporary architecture which became part of the four costumes with four patterns in this research. The four costumes designed by applied the physical configuration of the Royal Barge with the fold techniques which create the geometry pattern that are part of the Royal Barge-s decoration and contemporary architecture. Therefore, the researcher united each identity color of the barges with each costume composed with the original patterns by adjusted new layout and resized. Lastly, the new attractive patterns appeared. Nevertheless, the beauty of Thai traditional still remain by using Thai painting figure with black and white color which are the prevalent colors for the contemporary architectures.
Keywords: Costume Design, Figurehead, Thai Royal Barges.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14072198 Modeling of Reinforcement in Concrete Beams Using Machine Learning Tools
Authors: Yogesh Aggarwal
Abstract:
The paper discusses the results obtained to predict reinforcement in singly reinforced beam using Neural Net (NN), Support Vector Machines (SVM-s) and Tree Based Models. Major advantage of SVM-s over NN is of minimizing a bound on the generalization error of model rather than minimizing a bound on mean square error over the data set as done in NN. Tree Based approach divides the problem into a small number of sub problems to reach at a conclusion. Number of data was created for different parameters of beam to calculate the reinforcement using limit state method for creation of models and validation. The results from this study suggest a remarkably good performance of tree based and SVM-s models. Further, this study found that these two techniques work well and even better than Neural Network methods. A comparison of predicted values with actual values suggests a very good correlation coefficient with all four techniques.Keywords: Linear Regression, M5 Model Tree, Neural Network, Support Vector Machines.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20192197 Using Machine Learning Techniques for Autism Spectrum Disorder Analysis and Detection in Children
Authors: Norah Alshahrani, Abdulaziz Almaleh
Abstract:
Autism Spectrum Disorder (ASD) is a condition related to issues with brain development that affects how a person recognises and communicates with others which results in difficulties with interaction and communication socially and it is constantly growing. Early recognition of ASD allows children to lead safe and healthy lives and helps doctors with accurate diagnoses and management of conditions. Therefore, it is crucial to develop a method that will achieve good results and with high accuracy for the measurement of ASD in children. In this paper, ASD datasets of toddlers and children have been analyzed. We employed the following machine learning techniques to attempt to explore ASD: Random Forest (RF), Decision Tree (DT), Na¨ıve Bayes (NB) and Support Vector Machine (SVM). Then feature selection was used to provide fewer attributes from ASD datasets while preserving model performance. As a result, we found that the best result has been provided by SVM, achieving 0.98% in the toddler dataset and 0.99% in the children dataset.
Keywords: Autism Spectrum Disorder, ASD, Machine Learning, ML, Feature Selection, Support Vector Machine, SVM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5552196 Optical Switching Based On Bragg Solitons in A Nonuniform Fiber Bragg Grating
Authors: Abdulatif Abdusalam, Mohamed Shaban
Abstract:
In this paper, we consider the nonlinear pulse propagation through a nonuniform birefringent fiber Bragg grating (FBG) whose index modulation depth varies along the propagation direction. Here, the pulse propagation is governed by the nonlinear birefringent coupled mode (NLBCM) equations. To form the Bragg soliton outside the photonic bandgap (PBG), the NLBCM equations are reduced to the well known NLS type equation by multiple scale analysis. As we consider the pulse propagation in a nonuniform FBG, the pulse propagation outside the PBG is governed by inhomogeneous NLS (INLS) rather than NLS. We then discuss the formation of soliton in the FBG known as Bragg soliton whose central frequency lies outside but close to the PBG of the grating structure. Further, we discuss Bragg soliton compression due to a delicate balance between the SPM and the varying grating induced dispersion. In addition, Bragg soliton collision, Bragg soliton switching and possible logic gates have also been discussed.
Keywords: Bragg grating, Nonuniform fiber, Nonlinear pulse.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18882195 Genetic Programming Approach for Multi-Category Pattern Classification Appliedto Network Intrusions Detection
Authors: K.M. Faraoun, A. Boukelif
Abstract:
This paper describes a new approach of classification using genetic programming. The proposed technique consists of genetically coevolving a population of non-linear transformations on the input data to be classified, and map them to a new space with a reduced dimension, in order to get a maximum inter-classes discrimination. The classification of new samples is then performed on the transformed data, and so become much easier. Contrary to the existing GP-classification techniques, the proposed one use a dynamic repartition of the transformed data in separated intervals, the efficacy of a given intervals repartition is handled by the fitness criterion, with a maximum classes discrimination. Experiments were first performed using the Fisher-s Iris dataset, and then, the KDD-99 Cup dataset was used to study the intrusion detection and classification problem. Obtained results demonstrate that the proposed genetic approach outperform the existing GP-classification methods [1],[2] and [3], and give a very accepted results compared to other existing techniques proposed in [4],[5],[6],[7] and [8].Keywords: Genetic programming, patterns classification, intrusion detection
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16982194 Multilayer Neural Network and Fuzzy Logic Based Software Quality Prediction
Authors: Sadaf Sahar, Usman Qamar, Sadaf Ayaz
Abstract:
In the software development lifecycle, the quality prediction techniques hold a prime importance in order to minimize future design errors and expensive maintenance. There are many techniques proposed by various researchers, but with the increasing complexity of the software lifecycle model, it is crucial to develop a flexible system which can cater for the factors which in result have an impact on the quality of the end product. These factors include properties of the software development process and the product along with its operation conditions. In this paper, a neural network (perceptron) based software quality prediction technique is proposed. Using this technique, the stakeholders can predict the quality of the resulting software during the early phases of the lifecycle saving time and resources on future elimination of design errors and costly maintenance. This technique can be brought into practical use using successful training.Keywords: Software quality, fuzzy logic, perceptron, prediction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11582193 The Visual Inspection of Surgical Tasks Using Machine Vision: Applications to Robotic Surgery
Authors: M. Ovinis, D. Kerr, K. Bouazza-Marouf, M. Vloeberghs
Abstract:
In this paper, the feasibility of using machine vision to assess task completion in a surgical intervention is investigated, with the aim of incorporating vision based inspection in robotic surgery systems. The visually rich operative field presents a good environment for the development of automated visual inspection techniques in these systems, for a more comprehensive approach when performing a surgical task. As a proof of concept, machine vision techniques were used to distinguish the two possible outcomes i.e. satisfactory or unsatisfactory, of three primary surgical tasks involved in creating a burr hole in the skull, namely incision, retraction, and drilling. Encouraging results were obtained for the three tasks under consideration, which has been demonstrated by experiments on cadaveric pig heads. These findings are suggestive for the potential use of machine vision to validate successful task completion in robotic surgery systems. Finally, the potential of using machine vision in the operating theatre, and the challenges that must be addressed, are identified and discussed.
Keywords: Machine vision, robotic surgery, visual inspection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16422192 Automatic Text Summarization
Authors: Mohamed Abdel Fattah, Fuji Ren
Abstract:
This work proposes an approach to address automatic text summarization. This approach is a trainable summarizer, which takes into account several features, including sentence position, positive keyword, negative keyword, sentence centrality, sentence resemblance to the title, sentence inclusion of name entity, sentence inclusion of numerical data, sentence relative length, Bushy path of the sentence and aggregated similarity for each sentence to generate summaries. First we investigate the effect of each sentence feature on the summarization task. Then we use all features score function to train genetic algorithm (GA) and mathematical regression (MR) models to obtain a suitable combination of feature weights. The proposed approach performance is measured at several compression rates on a data corpus composed of 100 English religious articles. The results of the proposed approach are promising.Keywords: Automatic Summarization, Genetic Algorithm, Mathematical Regression, Text Features.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23162191 Dynamic Analysis of Viscoelastic Plates with Variable Thickness
Authors: Gülçin Tekin, Fethi Kadıoğlu
Abstract:
In this study, the dynamic analysis of viscoelastic plates with variable thickness is examined. The solutions of dynamic response of viscoelastic thin plates with variable thickness have been obtained by using the functional analysis method in the conjunction with the Gâteaux differential. The four-node serendipity element with four degrees of freedom such as deflection, bending, and twisting moments at each node is used. Additionally, boundary condition terms are included in the functional by using a systematic way. In viscoelastic modeling, Three-parameter Kelvin solid model is employed. The solutions obtained in the Laplace-Carson domain are transformed to the real time domain by using MDOP, Dubner & Abate, and Durbin inverse transform techniques. To test the performance of the proposed mixed finite element formulation, numerical examples are treated.
Keywords: Dynamic analysis, inverse Laplace transform techniques, mixed finite element formulation, viscoelastic plate with variable thickness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20192190 Buckling Resistance of Basalt Fiber Reinforced Polymer Infill Panel Subjected to Elevated Temperatures
Authors: Viriyavudh Sim, Woo Young Jung
Abstract:
Performance of Basalt Fiber Reinforced Polymer (BFRP) sandwich infill panel system under diagonal compression was studied by means of numerical analysis. Furthermore, the variation of temperature was considered to affect the mechanical properties of BFRP, since their composition was based on polymeric material. Moreover, commercial finite element analysis platform ABAQUS was used to model and analyze this infill panel system. Consequently, results of the analyses show that the overall performance of BFRP panel had a 15% increase compared to that of GFRP infill panel system. However, the variation of buckling load in terms of temperature for the BFRP system showed a more sensitive nature compared to those of GFRP system.
Keywords: Basalt Fiber Reinforced Polymer, Buckling performance, numerical simulation, temperature dependent materials.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11332189 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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8342188 An Intelligent Baby Care System Based on IoT and Deep Learning Techniques
Authors: Chinlun Lai, Lunjyh Jiang
Abstract:
Due to the heavy burden and pressure of caring for infants, an integrated automatic baby watching system based on IoT smart sensing and deep learning machine vision techniques is proposed in this paper. By monitoring infant body conditions such as heartbeat, breathing, body temperature, sleeping posture, as well as the surrounding conditions such as dangerous/sharp objects, light, noise, humidity and temperature, the proposed system can analyze and predict the obvious/potential dangerous conditions according to observed data and then adopt suitable actions in real time to protect the infant from harm. Thus, reducing the burden of the caregiver and improving safety efficiency of the caring work. The experimental results show that the proposed system works successfully for the infant care work and thus can be implemented in various life fields practically.Keywords: Baby care system, internet of things, deep learning, machine vision.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1876