Search results for: complex signal processing
1837 Two Concurrent Convolution Neural Networks TC*CNN Model for Face Recognition Using Edge
Authors: T. Alghamdi, G. Alaghband
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In this paper we develop a model that couples Two Concurrent Convolution Neural Network with different filters (TC*CNN) for face recognition and compare its performance to an existing sequential CNN (base model). We also test and compare the quality and performance of the models on three datasets with various levels of complexity (easy, moderate, and difficult) and show that for the most complex datasets, edges will produce the most accurate and efficient results. We further show that in such cases while Support Vector Machine (SVM) models are fast, they do not produce accurate results.
Keywords: Convolution neural network, edges, face recognition, support vector machine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7291836 Improved Automated Classification of Alcoholics and Non-alcoholics
Authors: Ramaswamy Palaniappan
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In this paper, several improvements are proposed to previous work of automated classification of alcoholics and nonalcoholics. In the previous paper, multiplayer-perceptron neural network classifying energy of gamma band Visual Evoked Potential (VEP) signals gave the best classification performance using 800 VEP signals from 10 alcoholics and 10 non-alcoholics. Here, the dataset is extended to include 3560 VEP signals from 102 subjects: 62 alcoholics and 40 non-alcoholics. Three modifications are introduced to improve the classification performance: i) increasing the gamma band spectral range by increasing the pass-band width of the used filter ii) the use of Multiple Signal Classification algorithm to obtain the power of the dominant frequency in gamma band VEP signals as features and iii) the use of the simple but effective knearest neighbour classifier. To validate that these two modifications do give improved performance, a 10-fold cross validation classification (CVC) scheme is used. Repeat experiments of the previously used methodology for the extended dataset are performed here and improvement from 94.49% to 98.71% in maximum averaged CVC accuracy is obtained using the modifications. This latest results show that VEP based classification of alcoholics is worth exploring further for system development.Keywords: Alcoholic, Multilayer-perceptron, Nearest neighbour, Gamma band, MUSIC, Visual evoked potential.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13781835 Optimising Business Rules in the Services Sector
Authors: Alan Dormer
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Business rules are widely used within the services sector. They provide consistency and allow relatively unskilled staff to process complex transactions correctly. But there are many examples where the rules themselves have an impact on the costs and profits of an organisation. Financial services, transport and human services are areas where the rules themselves can impact the bottom line in a predictable way. If this is the case, how can we find that set of rules that maximise profit, performance or customer service, or any other key performance indicators? The manufacturing, energy and process industries have embraced mathematical optimisation techniques to improve efficiency, increase production and so on. This paper explores several real world (but simplified) problems in the services sector and shows how business rules can be optimised. It also examines the similarities and differences between the service and other sectors, and how optimisation techniques could be used to deliver similar benefits.Keywords: Business rules, services, optimisation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16211834 Thematic Role Extraction Using Shallow Parsing
Authors: Mehrnoush Shamsfard, Maryam Sadr Mousavi
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Extracting thematic (semantic) roles is one of the major steps in representing text meaning. It refers to finding the semantic relations between a predicate and syntactic constituents in a sentence. In this paper we present a rule-based approach to extract semantic roles from Persian sentences. The system exploits a twophase architecture to (1) identify the arguments and (2) label them for each predicate. For the first phase we developed a rule based shallow parser to chunk Persian sentences and for the second phase we developed a knowledge-based system to assign 16 selected thematic roles to the chunks. The experimental results of testing each phase are shown at the end of the paper.Keywords: Natural Language Processing, Semantic RoleLabeling, Shallow parsing, Thematic Roles.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20271833 Efficient HAAR Wavelet Transform with Embedded Zerotrees of Wavelet Compression for Color Images
Authors: S. Piramu Kailasam
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This study is expected to compress true color image with compression algorithms in color spaces to provide high compression rates. The need of high compression ratio is to improve storage space. Alternative aim is to rank compression algorithms in a suitable color space. The dataset is sequence of true color images with size 128 x 128. HAAR Wavelet is one of the famous wavelet transforms, has great potential and maintains image quality of color images. HAAR wavelet Transform using Set Partitioning in Hierarchical Trees (SPIHT) algorithm with different color spaces framework is applied to compress sequence of images with angles. Embedded Zerotrees of Wavelet (EZW) is a powerful standard method to sequence data. Hence the proposed compression frame work of HAAR wavelet, xyz color space, morphological gradient and applied image with EZW compression, obtained improvement to other methods, in terms of Compression Ratio, Mean Square Error, Peak Signal Noise Ratio and Bits Per Pixel quality measures.
Keywords: Color Spaces, HAAR Wavelet, Morphological Gradient, Embedded Zerotrees Wavelet Compression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5191832 Constrained Particle Swarm Optimization of Supply Chains
Authors: András Király, Tamás Varga, János Abonyi
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Since supply chains highly impact the financial performance of companies, it is important to optimize and analyze their Key Performance Indicators (KPI). The synergistic combination of Particle Swarm Optimization (PSO) and Monte Carlo simulation is applied to determine the optimal reorder point of warehouses in supply chains. The goal of the optimization is the minimization of the objective function calculated as the linear combination of holding and order costs. The required values of service levels of the warehouses represent non-linear constraints in the PSO. The results illustrate that the developed stochastic simulator and optimization tool is flexible enough to handle complex situations.Keywords: stochastic processes, empirical distributions, Monte Carlo simulation, PSO, supply chain management
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20751831 Gas Sweetening Process Simulation: Investigation on Recovering Waste Hydraulic Energy
Authors: Meisam Moghadasi, Hassan Ali Ozgoli, Foad Farhani
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In this research, firstly, a commercial gas sweetening unit with methyl-di-ethanol-amine (MDEA) solution is simulated and comprised in an integrated model in accordance with Aspen HYSYS software. For evaluation purposes, in the second step, the results of the simulation are compared with operating data gathered from South Pars Gas Complex (SPGC). According to the simulation results, the considerable energy potential contributed to the pressure difference between absorber and regenerator columns causes this energy driving force to be applied in power recovery turbine (PRT). In the last step, the amount of waste hydraulic energy is calculated, and its recovery methods are investigated.
Keywords: Gas sweetening unit, simulation, MDEA, power recovery turbine, waste-to-energy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10771830 Straight Line Defect Detection with Feed Forward Neural Network
Authors: S. Liangwongsan, A. Oonsivilai
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Nowadays, hard disk is one of the most popular storage components. In hard disk industry, the hard disk drive must pass various complex processes and tested systems. In each step, there are some failures. To reduce waste from these failures, we must find the root cause of those failures. Conventionall data analysis method is not effective enough to analyze the large capacity of data. In this paper, we proposed the Hough method for straight line detection that helps to detect straight line defect patterns that occurs in hard disk drive. The proposed method will help to increase more speed and accuracy in failure analysis.
Keywords: Hough Transform, Failure Analysis, Media, Hard Disk Drive
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20941829 Axisymmetric Vibration of Pyrocomposite Hollow Cylinder
Authors: V. K. Nelson, S. Karthikeyan
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Axisymmetric vibration of an infinite Pyrocomposite circular hollow cylinder made of inner and outer pyroelectric layer of 6mm-class bonded together by a Linear Elastic Material with Voids (LEMV) layer is studied. The exact frequency equation is obtained for the traction free surfaces with continuity condition at the interfaces. Numerical results in the form of data and dispersion curves for the first and second mode of the axisymmetric vibration of the cylinder BaTio3 / Adhesive / BaTio3 by taking the Adhesive layer as an existing Carbon Fibre Reinforced Polymer (CFRP) are compared with a hypothetical LEMV layer with and without voids and as well with a pyroelectric hollow cylinder. The damping is analyzed through the imaginary parts of the complex frequencies.Keywords: Axisymmetric vibration, CFRP, hollow cylinders, LEMV, pyrocomposite
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15031828 Knowledge Sharing based on Semantic Nets and Mereology to Avoid Risks in Manufacturing
Authors: Ulrich Berger, Yuliya Lebedynska, Veronica Vargas
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The right information at the right time influences the enterprise and technical success. Sharing knowledge among members of a big organization may be a complex activity. And as long as the knowledge is not shared, can not be exploited by the organization. There are some mechanisms which can originate knowledge sharing. It is intended, in this paper, to trigger these mechanisms by using semantic nets. Moreover, the intersection and overlapping of terms and sub-terms, as well as their relationships will be described through the mereology science for the whole knowledge sharing system. It is proposed a knowledge system to supply to operators with the right information about a specific process and possible risks, e.g. at the assembly process, at the right time in an automated manufacturing environment, such as at the automotive industry.Keywords: Automated manufacturing, knowledge sharing, mereology, risk management, semantic net.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14841827 Wireless Sensor Network: Characteristics and Architectures
Authors: Muhammad R Ahmed, Xu Huang, Dharmandra Sharma, Hongyan Cui
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An information procuring and processing emerging technology wireless sensor network (WSN) Consists of autonomous nodes with versatile devices underpinned by applications. Nodes are equipped with different capabilities such as sensing, computing, actuation and wireless communications etc. based on application requirements. A WSN application ranges from military implementation in the battlefield, environmental monitoring, health sector as well as emergency response of surveillance. The nodes are deployed independently to cooperatively monitor the physical and environmental conditions. The architecture of WSN differs based on the application requirements and focus on low cost, flexibility, fault tolerance capability, deployment process as well as conserve energy. In this paper we have present the characteristics, architecture design objective and architecture of WSNKeywords: wireless sensor network, characteristics, architecture
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 78091826 Devising a Paradigm for the Assessment of Guilt across Species
Authors: Trisha S. Malhotra
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While there exist frameworks to study the induction, manifestation, duration and general nature of emotions like shame, guilt, embarrassment and pride in humans, the same cannot be said for other species. This is because such 'complex' emotions have situational inductions and manifestations that supposedly vary due to differences between and within different species' ethology. This paper looks at the socio-adaptive functions of guilt to posit why this emotion might be observed across varying species. Primarily, the experimental paradigm of guilt-assessment in domesticated dogs is critiqued for lack of ethological consideration in its measurement and analysis. It is argued that a paradigm for guilt-assessment should measure the species-specific prosocial approach behavior instead of the immediate feedback of the 'guilty'. Finally, it is asserted that the origin of guilt is subjective and if it must be studied across a plethora of species, its definition must be tailored to fit accordingly.Keywords: Guilt, assessment, dogs, prosocial approach behavior, empathy, species, ethology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9031825 3D Mesh Coarsening via Uniform Clustering
Authors: Shuhua Lai, Kairui Chen
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In this paper, we present a fast and efficient mesh coarsening algorithm for 3D triangular meshes. Theis approach can be applied to very complex 3D meshes of arbitrary topology and with millions of vertices. The algorithm is based on the clustering of the input mesh elements, which divides the faces of an input mesh into a given number of clusters for clustering purpose by approximating the Centroidal Voronoi Tessellation of the input mesh. Once a clustering is achieved, it provides us an efficient way to construct uniform tessellations, and therefore leads to good coarsening of polygonal meshes. With proliferation of 3D scanners, this coarsening algorithm is particularly useful for reverse engineering applications of 3D models, which in many cases are dense, non-uniform, irregular and arbitrary topology. Examples demonstrating effectiveness of the new algorithm are also included in the paper.Keywords: Coarsening, mesh clustering, shape approximation, mesh simplification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14051824 GSM Based Smart Patient Monitoring System
Authors: Ayman M. Mansour
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In this paper, we propose an intelligent system that is used for monitoring the health conditions of patients. Monitoring the health condition of patients is a complex problem that involves different medical units and requires continuous monitoring especially in rural areas because of inadequate number of available specialized physicians. The proposed system will improve patient care and drive costs down comparing to the existing system in Jordan. The proposed system will be the start point to faster and improve the communication between different units in the health system in Jordan. Connecting patients and their physicians beyond hospital doors regarding their geographical area is an important issue in developing the health system in Jordan. The ability of making medical decisions, the quality of medical is expected to be improved.
Keywords: GSM, SMS, Patient, Monitoring system, Fuzzy Logic, Multi-agent system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30041823 Investigations Into the Turning Parameters Effect on the Surface Roughness of Flame Hardened Medium Carbon Steel with TiN-Al2O3-TiCN Coated Inserts based on Taguchi Techniques
Authors: Samir Khrais, Adel Mahammod Hassan , Amro Gazawi
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The aim of this research is to evaluate surface roughness and develop a multiple regression model for surface roughness as a function of cutting parameters during the turning of flame hardened medium carbon steel with TiN-Al2O3-TiCN coated inserts. An experimental plan of work and signal-to-noise ratio (S/N) were used to relate the influence of turning parameters to the workpiece surface finish utilizing Taguchi methodology. The effects of turning parameters were studied by using the analysis of variance (ANOVA) method. Evaluated parameters were feed, cutting speed, and depth of cut. It was found that the most significant interaction among the considered turning parameters was between depth of cut and feed. The average surface roughness (Ra) resulted by TiN-Al2O3- TiCN coated inserts was about 2.44 μm and minimum value was 0.74 μm. In addition, the regression model was able to predict values for surface roughness in comparison with experimental values within reasonable limit.Keywords: Medium carbon steel, Prediction, Surface roughness, Taguchi method
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17711822 A Comparison of Adaline and MLP Neural Network based Predictors in SIR Estimation in Mobile DS/CDMA Systems
Authors: Nahid Ardalani, Ahmadreza Khoogar, H. Roohi
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In this paper we compare the response of linear and nonlinear neural network-based prediction schemes in prediction of received Signal-to-Interference Power Ratio (SIR) in Direct Sequence Code Division Multiple Access (DS/CDMA) systems. The nonlinear predictor is Multilayer Perceptron MLP and the linear predictor is an Adaptive Linear (Adaline) predictor. We solve the problem of complexity by using the Minimum Mean Squared Error (MMSE) principle to select the optimal predictors. The optimized Adaline predictor is compared to optimized MLP by employing noisy Rayleigh fading signals with 1.8 GHZ carrier frequency in an urban environment. The results show that the Adaline predictor can estimates SIR with the same error as MLP when the user has the velocity of 5 km/h and 60 km/h but by increasing the velocity up-to 120 km/h the mean squared error of MLP is two times more than Adaline predictor. This makes the Adaline predictor (with lower complexity) more suitable than MLP for closed-loop power control where efficient and accurate identification of the time-varying inverse dynamics of the multi path fading channel is required.Keywords: Power control, neural networks, DS/CDMA mobilecommunication systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25151821 Strategies of Education and Training Practice of Small and Medium Sized Enterprises
Authors: A. Bencsik, - A. Sólyom
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The role of knowledge is a determinative factor in the life of economy and society. To determine knowledge is not an easy task yet the real task is to determine the right knowledge. From this view knowledge is a sum of experience, ideas and cognitions which can help companies to remain in markets and to realize a maximum profit. At the same time changes of circumstances project in advance that contents and demands of the right knowledge are changing. In this paper we will analyse a special segment on the basis of an empirical survey. We investigated the behaviour and strategies of small and medium sized enterprises (SMEs) in the area of knowledge-handling. This survey was realized by questionnaires and wide range statistical methods were used during processing. As a result we will show how these companies are prepared to operate in a knowledge-based economy and in which areas they have prominent deficiencies.Keywords: education, knowledge, knowledgemanagement, strategy, SME
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15131820 An Automatic Gridding and Contour Based Segmentation Approach Applied to DNA Microarray Image Analysis
Authors: Alexandra Oliveros, Miguel Sotaquirá
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DNA microarray technology is widely used by geneticists to diagnose or treat diseases through gene expression. This technology is based on the hybridization of a tissue-s DNA sequence into a substrate and the further analysis of the image formed by the thousands of genes in the DNA as green, red or yellow spots. The process of DNA microarray image analysis involves finding the location of the spots and the quantification of the expression level of these. In this paper, a tool to perform DNA microarray image analysis is presented, including a spot addressing method based on the image projections, the spot segmentation through contour based segmentation and the extraction of relevant information due to gene expression.Keywords: Contour segmentation, DNA microarrays, edge detection, image processing, segmentation, spot addressing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13901819 Characteristics of the Severe Rollover Crashes in the UAE Using In-Depth Crash Investigation Data
Authors: Yaser E. Hawas, Md. Didarul Alam
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Rollover crashes are complex events entailing interactions of driver, road, vehicle, and environmental factors. The primary objective of this paper is to present an empirical approach that can be used to characterise the rollover crashes and to identify some of the important factors that may lead to rollovers. Among the studied factors are the vehicle types and the rollover occurrence rate after hitting various barrier types. The carried analysis indicated that 71% of the rollover crashes occurred after impact and the type of rollover initiation is “trip/turn over” (nearly 50%). It was also found that light trucks (LTVs) vehicles are more likely to rollover than the sedan vehicles. Barrier impacts are associated with increased incidence of rollover.
Keywords: Empirical, hitting barrier, in-depth crash investigation, rollover, severe crash.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7891818 Application of Pearson Parametric Distribution Model in Fatigue Life Reliability Evaluation
Authors: E. A. Azrulhisham, Y. M. Asri, A. W. Dzuraidah, A. H. Hairul Fahmi
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The aim of this paper is to introduce a parametric distribution model in fatigue life reliability analysis dealing with variation in material properties. Service loads in terms of responsetime history signal of Belgian pave were replicated on a multi-axial spindle coupled road simulator and stress-life method was used to estimate the fatigue life of automotive stub axle. A PSN curve was obtained by monotonic tension test and two-parameter Weibull distribution function was used to acquire the mean life of the component. A Pearson system was developed to evaluate the fatigue life reliability by considering stress range intercept and slope of the PSN curve as random variables. Considering normal distribution of fatigue strength, it is found that the fatigue life of the stub axle to have the highest reliability between 10000 – 15000 cycles. Taking into account the variation of material properties associated with the size effect, machining and manufacturing conditions, the method described in this study can be effectively applied in determination of probability of failure of mass-produced parts.Keywords: Stub axle, Fatigue life reliability, Stress-life, PSN curve, Weibull distribution, Pearson system
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21411817 Application of Scanning Electron Microscopy and X-Ray Evaluation of the Main Digestion Methods for Determination of Macroelements in Plant Tissue
Authors: Krasimir I. Ivanov, Penka S. Zapryanova, Stefan V. Krustev, Violina R. Angelova
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Three commonly used digestion methods (dry ashing, acid digestion, and microwave digestion) in different variants were compared for digestion of tobacco leaves. Three main macroelements (K, Ca and Mg) were analysed using AAS Spectrometer Spectra АА 220, Varian, Australia. The accuracy and precision of the measurements were evaluated by using Polish reference material CTR-VTL-2 (Virginia tobacco leaves). To elucidate the problems with elemental recovery X-Ray and SEM–EDS analysis of all residues after digestion were performed. The X-ray investigation showed a formation of KClO4 when HClO4 was used as a part of the acids mixture. The use of HF at Ca and Mg determination led to the formation of CaF2 and MgF2. The results were confirmed by energy dispersive X-ray microanalysis. SPSS program for Windows was used for statistical data processing.
Keywords: Digestion methods, determination of macroelements, plant tissue.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9401816 WiPoD Wireless Positioning System based on 802.11 WLAN Infrastructure
Authors: Haluk Gümüskaya, Hüseyin Hakkoymaz
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This paper describes WiPoD (Wireless Position Detector) which is a pure software based location determination and tracking (positioning) system. It uses empirical signal strength measurements from different wireless access points for mobile user positioning. It is designed to determine the location of users having 802.11 enabled mobile devices in an 802.11 WLAN infrastructure and track them in real time. WiPoD is the first main module in our LBS (Location Based Services) framework. We tested K-Nearest Neighbor and Triangulation algorithms to estimate the position of a mobile user. We also give the analysis results of these algorithms for real time operations. In this paper, we propose a supportable, i.e. understandable, maintainable, scalable and portable wireless positioning system architecture for an LBS framework. The WiPoD software has a multithreaded structure and was designed and implemented with paying attention to supportability features and real-time constraints and using object oriented design principles. We also describe the real-time software design issues of a wireless positioning system which will be part of an LBS framework.Keywords: Indoor location determination and tracking, positioning in Wireless LAN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19941815 Localization for Indoor Service Robot Using Natural Landmark on the Ceiling
Authors: Seung-Hun Kim, Changwoo Park
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In this paper, we present a localization of a mobile robot with localization modules which have two ceiling-view cameras in indoor environments. We propose two kinds of localization method. The one is the localization in the local space; we use the line feature and the corner feature between the ceiling and wall. The other is the localization in the large space; we use the natural features such as bulbs, structures on the ceiling. These methods are installed on the embedded module able to mount on the robot. The embedded module has two cameras to be able to localize in both the local space and the large spaces. The experiment is practiced in our indoor test-bed and a government office. The proposed method is proved by the experimental results.
Keywords: Robot, Localization, Indoor, Ceiling vision, Local space, Large space, Complex space.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21771814 Designing a Robust Controller for a 6 Linkage Robot
Authors: G. Khamooshian
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One of the main points of application of the mechanisms of the series and parallel is the subject of managing them. The control of this mechanism and similar mechanisms is one that has always been the intention of the scholars. On the other hand, modeling the behavior of the system is difficult due to the large number of its parameters, and it leads to complex equations that are difficult to solve and eventually difficult to control. In this paper, a six-linkage robot has been presented that could be used in different areas such as medical robots. Using these robots needs a robust control. In this paper, the system equations are first found, and then the system conversion function is written. A new controller has been designed for this robot which could be used in other parallel robots and could be very useful. Parallel robots are so important in robotics because of their stability, so methods for control of them are important and the robust controller, especially in parallel robots, makes a sense.
Keywords: 3-RRS, 6 linkage, parallel robot, control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6691813 3D Dynamic Representation System for the Human Head
Authors: Laurenţiu Militeanu, Cristina Gena Dascâlu, D. Cristea
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The human head representations usually are based on the morphological – structural components of a real model. Over the time became more and more necessary to achieve full virtual models that comply very rigorous with the specifications of the human anatomy. Still, making and using a model perfectly fitted with the real anatomy is a difficult task, because it requires large hardware resources and significant times for processing. That is why it is necessary to choose the best compromise solution, which keeps the right balance between the details perfection and the resources consumption, in order to obtain facial animations with real-time rendering. We will present here the way in which we achieved such a 3D system that we intend to use as a base point in order to create facial animations with real-time rendering, used in medicine to find and to identify different types of pathologies.Keywords: 3D models, virtual reality.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14561812 Finding an Optimized Discriminate Function for Internet Application Recognition
Authors: E. Khorram, S.M. Mirzababaei
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Everyday the usages of the Internet increase and simply a world of the data become accessible. Network providers do not want to let the provided services to be used in harmful or terrorist affairs, so they used a variety of methods to protect the special regions from the harmful data. One of the most important methods is supposed to be the firewall. Firewall stops the transfer of such packets through several ways, but in some cases they do not use firewall because of its blind packet stopping, high process power needed and expensive prices. Here we have proposed a method to find a discriminate function to distinguish between usual packets and harmful ones by the statistical processing on the network router logs. So an administrator can alarm to the user. This method is very fast and can be used simply in adjacent with the Internet routers.
Keywords: Data Mining, Firewall, Optimization, Packetclassification, Statistical Pattern Recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14081811 Basket Option Pricing under Jump Diffusion Models
Authors: Ali Safdari-Vaighani
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Pricing financial contracts on several underlying assets received more and more interest as a demand for complex derivatives. The option pricing under asset price involving jump diffusion processes leads to the partial integral differential equation (PIDEs), which is an extension of the Black-Scholes PDE with a new integral term. The aim of this paper is to show how basket option prices in the jump diffusion models, mainly on the Merton model, can be computed using RBF based approximation methods. For a test problem, the RBF-PU method is applied for numerical solution of partial integral differential equation arising from the two-asset European vanilla put options. The numerical result shows the accuracy and efficiency of the presented method.Keywords: Radial basis function, basket option, jump diffusion, RBF-PUM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12081810 Model-Driven and Data-Driven Approaches for Crop Yield Prediction: Analysis and Comparison
Authors: Xiangtuo Chen, Paul-Henry Cournéde
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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.Keywords: Crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11761809 Statistics over Lyapunov Exponents for Feature Extraction: Electroencephalographic Changes Detection Case
Authors: Elif Derya UBEYLI, Inan GULER
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A new approach based on the consideration that electroencephalogram (EEG) signals are chaotic signals was presented for automated diagnosis of electroencephalographic changes. This consideration was tested successfully using the nonlinear dynamics tools, like the computation of Lyapunov exponents. This paper presented the usage of statistics over the set of the Lyapunov exponents in order to reduce the dimensionality of the extracted feature vectors. Since classification is more accurate when the pattern is simplified through representation by important features, feature extraction and selection play an important role in classifying systems such as neural networks. Multilayer perceptron neural network (MLPNN) architectures were formulated and used as basis for detection of electroencephalographic changes. Three types of EEG signals (EEG signals recorded from healthy volunteers with eyes open, epilepsy patients in the epileptogenic zone during a seizure-free interval, and epilepsy patients during epileptic seizures) were classified. The selected Lyapunov exponents of the EEG signals were used as inputs of the MLPNN trained with Levenberg- Marquardt algorithm. The classification results confirmed that the proposed MLPNN has potential in detecting the electroencephalographic changes.
Keywords: Chaotic signal, Electroencephalogram (EEG) signals, Feature extraction/selection, Lyapunov exponents
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25101808 Environmentally Adaptive Acoustic Echo Suppression for Barge-in Speech Recognition
Authors: Jong Han Joo, Jeong Hun Lee, Young Sun Kim, Jae Young Kang, Seung Ho Choi
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In this study, we propose a novel technique for acoustic echo suppression (AES) during speech recognition under barge-in conditions. Conventional AES methods based on spectral subtraction apply fixed weights to the estimated echo path transfer function (EPTF) at the current signal segment and to the EPTF estimated until the previous time interval. However, the effects of echo path changes should be considered for eliminating the undesired echoes. We describe a new approach that adaptively updates weight parameters in response to abrupt changes in the acoustic environment due to background noises or double-talk. Furthermore, we devised a voice activity detector and an initial time-delay estimator for barge-in speech recognition in communication networks. The initial time delay is estimated using log-spectral distance measure, as well as cross-correlation coefficients. The experimental results show that the developed techniques can be successfully applied in barge-in speech recognition systems.
Keywords: Acoustic echo suppression, barge-in, speech recognition, echo path transfer function, initial delay estimator, voice activity detector.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2317