Search results for: Signal Processing
837 Highly Accurate Target Motion Compensation Using Entropy Function Minimization
Authors: Amin Aghatabar Roodbary, Mohammad Hassan Bastani
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One of the defects of stepped frequency radar systems is their sensitivity to target motion. In such systems, target motion causes range cell shift, false peaks, Signal to Noise Ratio (SNR) reduction and range profile spreading because of power spectrum interference of each range cell in adjacent range cells which induces distortion in High Resolution Range Profile (HRRP) and disrupt target recognition process. Thus Target Motion Parameters (TMPs) effects compensation should be employed. In this paper, such a method for estimating TMPs (velocity and acceleration) and consequently eliminating or suppressing the unwanted effects on HRRP based on entropy minimization has been proposed. This method is carried out in two major steps: in the first step, a discrete search method has been utilized over the whole acceleration-velocity lattice network, in a specific interval seeking to find a less-accurate minimum point of the entropy function. Then in the second step, a 1-D search over velocity is done in locus of the minimum for several constant acceleration lines, in order to enhance the accuracy of the minimum point found in the first step. The provided simulation results demonstrate the effectiveness of the proposed method.
Keywords: ATR, HRRP, motion compensation, SFW, TMP.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 657836 Design and Simulation of Heartbeat Measurement System Using Arduino Microcontroller in Proteus
Authors: Muhibul H. Bhuyan, Mafujul Hasan
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If a person can monitor his/her heart rate regularly then he/she can detect heart disease early and thus he/she can enjoy longer life span. Therefore, this disease should be taken seriously. Hence, many health care devices and monitoring systems are being designed to keep track of the heart disease. This work reports a design and simulation processes of an Arduino microcontroller based heart rate measurement and monitoring system in Proteus environment. Clipping sensors were utilized to sense the heart rate of an individual from the finger tips. It is a digital device and uses mainly infrared (IR) transmitter (mainly IR LED) and receiver (mainly IR photo-transistor or IR photo-detector). When the heart pumps the blood and circulates it among the blood vessels of the body, the changed blood pressure is detected by the transmitter and then reflected back to the receiver accordingly. The reflected signals are then processed inside the microcontroller through a software written assembly language and appropriate heart rate (HR) is determined by it in beats per minute (bpm) from the detected signal for a duration of 10 seconds and display the same in bpm on the LCD screen in digital format. The designed system was simulated on several persons with varying ages, for example, infants, adult persons and active athletes. Simulation results were found very satisfactory.
Keywords: Heart rate measurement, design, simulation, Proteus, Arduino Uno microcontroller.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1794835 Towards Growing Self-Organizing Neural Networks with Fixed Dimensionality
Authors: Guojian Cheng, Tianshi Liu, Jiaxin Han, Zheng Wang
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The competitive learning is an adaptive process in which the neurons in a neural network gradually become sensitive to different input pattern clusters. The basic idea behind the Kohonen-s Self-Organizing Feature Maps (SOFM) is competitive learning. SOFM can generate mappings from high-dimensional signal spaces to lower dimensional topological structures. The main features of this kind of mappings are topology preserving, feature mappings and probability distribution approximation of input patterns. To overcome some limitations of SOFM, e.g., a fixed number of neural units and a topology of fixed dimensionality, Growing Self-Organizing Neural Network (GSONN) can be used. GSONN can change its topological structure during learning. It grows by learning and shrinks by forgetting. To speed up the training and convergence, a new variant of GSONN, twin growing cell structures (TGCS) is presented here. This paper first gives an introduction to competitive learning, SOFM and its variants. Then, we discuss some GSONN with fixed dimensionality, which include growing cell structures, its variants and the author-s model: TGCS. It is ended with some testing results comparison and conclusions.Keywords: Artificial neural networks, Competitive learning, Growing cell structures, Self-organizing feature maps.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1542834 Food Safety Aspects of Pesticide Residues in Spice Paprika
Authors: Sz. Klátyik, B. Darvas, M. Mörtl, M. Ottucsák, E. Takács, H. Bánáti, L. Simon, G. Gyurcsó, A. Székács
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Environmental and health safety of condiments used for spicing food products in food processing or by culinary means receive relatively low attention, even though possible contamination of spices may affect food quality and safety. Contamination surveys mostly focus on microbial contaminants or their secondary metabolites, mycotoxins. Chemical contaminants, particularly pesticide residues, however, are clearly substantial factors in the case of given condiments in the Capsicum family including spice paprika and chilli. To assess food safety and support the quality of the Hungaricum product spice paprika, the pesticide residue status of spice paprika and chilli is assessed on the basis of reported pesticide contamination cases and non-compliances in the Rapid Alert System for Food and Feed of the European Union since 1998.
Keywords: Spice paprika, Capsicum, pesticide residues, RASFF.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2403833 Fast Wavelet Image Denoising Based on Local Variance and Edge Analysis
Authors: Gaoyong Luo
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The approach based on the wavelet transform has been widely used for image denoising due to its multi-resolution nature, its ability to produce high levels of noise reduction and the low level of distortion introduced. However, by removing noise, high frequency components belonging to edges are also removed, which leads to blurring the signal features. This paper proposes a new method of image noise reduction based on local variance and edge analysis. The analysis is performed by dividing an image into 32 x 32 pixel blocks, and transforming the data into wavelet domain. Fast lifting wavelet spatial-frequency decomposition and reconstruction is developed with the advantages of being computationally efficient and boundary effects minimized. The adaptive thresholding by local variance estimation and edge strength measurement can effectively reduce image noise while preserve the features of the original image corresponding to the boundaries of the objects. Experimental results demonstrate that the method performs well for images contaminated by natural and artificial noise, and is suitable to be adapted for different class of images and type of noises. The proposed algorithm provides a potential solution with parallel computation for real time or embedded system application.Keywords: Edge strength, Fast lifting wavelet, Image denoising, Local variance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2028832 Hardware Prototyping of an Efficient Encryption Engine
Authors: Muhammad I. Ibrahimy, Mamun B.I. Reaz, Khandaker Asaduzzaman, Sazzad Hussain
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An approach to develop the FPGA of a flexible key RSA encryption engine that can be used as a standard device in the secured communication system is presented. The VHDL modeling of this RSA encryption engine has the unique characteristics of supporting multiple key sizes, thus can easily be fit into the systems that require different levels of security. A simple nested loop addition and subtraction have been used in order to implement the RSA operation. This has made the processing time faster and used comparatively smaller amount of space in the FPGA. The hardware design is targeted on Altera STRATIX II device and determined that the flexible key RSA encryption engine can be best suited in the device named EP2S30F484C3. The RSA encryption implementation has made use of 13,779 units of logic elements and achieved a clock frequency of 17.77MHz. It has been verified that this RSA encryption engine can perform 32-bit, 256-bit and 1024-bit encryption operation in less than 41.585us, 531.515us and 790.61us respectively.Keywords: RSA, FPGA, Communication, Security, VHDL.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1451831 Efficient CT Image Volume Rendering for Diagnosis
Authors: HaeNa Lee, Sun K. Yoo
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Volume rendering is widely used in medical CT image visualization. Applying 3D image visualization to diagnosis application can require accurate volume rendering with high resolution. Interpolation is important in medical image processing applications such as image compression or volume resampling. However, it can distort the original image data because of edge blurring or blocking effects when image enhancement procedures were applied. In this paper, we proposed adaptive tension control method exploiting gradient information to achieve high resolution medical image enhancement in volume visualization, where restored images are similar to original images as much as possible. The experimental results show that the proposed method can improve image quality associated with the adaptive tension control efficacy.Keywords: Tension control, Interpolation, Ray-casting, Medical imaging analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2372830 Automatic Classification of Initial Categories of Alzheimer's Disease from Structural MRI Phase Images: A Comparison of PSVM, KNN and ANN Methods
Authors: Ahsan Bin Tufail, Ali Abidi, Adil Masood Siddiqui, Muhammad Shahzad Younis
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An early and accurate detection of Alzheimer's disease (AD) is an important stage in the treatment of individuals suffering from AD. We present an approach based on the use of structural magnetic resonance imaging (sMRI) phase images to distinguish between normal controls (NC), mild cognitive impairment (MCI) and AD patients with clinical dementia rating (CDR) of 1. Independent component analysis (ICA) technique is used for extracting useful features which form the inputs to the support vector machines (SVM), K nearest neighbour (kNN) and multilayer artificial neural network (ANN) classifiers to discriminate between the three classes. The obtained results are encouraging in terms of classification accuracy and effectively ascertain the usefulness of phase images for the classification of different stages of Alzheimer-s disease.
Keywords: Biomedical image processing, classification algorithms, feature extraction, statistical learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2765829 Adhesion Problematic for Novel Non-Crimp Fabric and Surface Modification of Carbon-Fibres Using Oxy-Fluorination
Authors: Iris Käppler, Paul Matthäi, Chokri Cherif
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In the scope of application of technical textiles, Non- Crimp Fabrics are increasingly used. In general, NCF exhibit excellent load bearing properties, but caused by the manufacturing process, there are some remaining disadvantages which have to be reduced. Regarding to this, a novel technique of processing NCF was developed substituting the binding-thread by an adhesive. This stitchfree method requires new manufacturing concept as well as new basic methods to prove adhesion of glue at fibres and textiles. To improve adhesion properties and the wettability of carbon-fibres by the adhesive, oxy-fluorination was used. The modification of carbonfibres by oxy-fluorination was investigated via scanning electron microscope, X-ray photoelectron spectroscopy and single fibre tensiometry. Special tensile tests were developed to determine the maximum force required for detachment.
Keywords: Non-Crimp Fabric, adhesive, stitch-free, high-performance fibre.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2036828 A New Image Psychovisual Coding Quality Measurement based Region of Interest
Authors: M. Nahid, A. Bajit, A. Tamtaoui, E. H. Bouyakhf
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To model the human visual system (HVS) in the region of interest, we propose a new objective metric evaluation adapted to wavelet foveation-based image compression quality measurement, which exploits a foveation setup filter implementation technique in the DWT domain, based especially on the point and region of fixation of the human eye. This model is then used to predict the visible divergences between an original and compressed image with respect to this region field and yields an adapted and local measure error by removing all peripheral errors. The technique, which we call foveation wavelet visible difference prediction (FWVDP), is demonstrated on a number of noisy images all of which have the same local peak signal to noise ratio (PSNR), but visibly different errors. We show that the FWVDP reliably predicts the fixation areas of interest where error is masked, due to high image contrast, and the areas where the error is visible, due to low image contrast. The paper also suggests ways in which the FWVDP can be used to determine a visually optimal quantization strategy for foveation-based wavelet coefficients and to produce a quantitative local measure of image quality.
Keywords: Human Visual System, Image Quality, ImageCompression, foveation wavelet, region of interest ROI.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1498827 QoS Improvement Using Intelligent Algorithm under Dynamic Tropical Weather for Earth-Space Satellite Applications
Authors: Joseph S. Ojo, Vincent A. Akpan, Oladayo G. Ajileye, Olalekan L, Ojo
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In this paper, the intelligent algorithm (IA) that is capable of adapting to dynamical tropical weather conditions is proposed based on fuzzy logic techniques. The IA effectively interacts with the quality of service (QoS) criteria irrespective of the dynamic tropical weather to achieve improvement in the satellite links. To achieve this, an adaptive network-based fuzzy inference system (ANFIS) has been adopted. The algorithm is capable of interacting with the weather fluctuation to generate appropriate improvement to the satellite QoS for efficient services to the customers. 5-year (2012-2016) rainfall rate of one-minute integration time series data has been used to derive fading based on ITU-R P. 618-12 propagation models. The data are obtained from the measurement undertaken by the Communication Research Group (CRG), Physics Department, Federal University of Technology, Akure, Nigeria. The rain attenuation and signal-to-noise ratio (SNR) were derived for frequency between Ku and V-band and propagation angle with respect to different transmitting power. The simulated results show a substantial reduction in SNR especially for application in the area of digital video broadcast-second generation coding modulation satellite networks.
Keywords: Fuzzy logic, intelligent algorithm, Nigeria, QoS, satellite applications, tropical weather.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 818826 An Optimization of Machine Parameters for Modified Horizontal Boring Tool Using Taguchi Method
Authors: Thirasak Panyaphirawat, Pairoj Sapsmarnwong, Teeratas Pornyungyuen
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This paper presents the findings of an experimental investigation of important machining parameters for the horizontal boring tool modified to mouth with a horizontal lathe machine to bore an overlength workpiece. In order to verify a usability of a modified tool, design of experiment based on Taguchi method is performed. The parameters investigated are spindle speed, feed rate, depth of cut and length of workpiece. Taguchi L9 orthogonal array is selected for four factors three level parameters in order to minimize surface roughness (Ra and Rz) of S45C steel tubes. Signal to noise ratio analysis and analysis of variance (ANOVA) is performed to study an effect of said parameters and to optimize the machine setting for best surface finish. The controlled factors with most effect are depth of cut, spindle speed, length of workpiece, and feed rate in order. The confirmation test is performed to test the optimal setting obtained from Taguchi method and the result is satisfactory.
Keywords: Design of Experiment, Taguchi Design, Optimization, Analysis of Variance, Machining Parameters, Horizontal Boring Tool.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2706825 Optimization of Process Parameters of Pressure Die Casting using Taguchi Methodology
Authors: Satish Kumar, Arun Kumar Gupta, Pankaj Chandna
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The present work analyses different parameters of pressure die casting to minimize the casting defects. Pressure diecasting is usually applied for casting of aluminium alloys. Good surface finish with required tolerances and dimensional accuracy can be achieved by optimization of controllable process parameters such as solidification time, molten temperature, filling time, injection pressure and plunger velocity. Moreover, by selection of optimum process parameters the pressure die casting defects such as porosity, insufficient spread of molten material, flash etc. are also minimized. Therefore, a pressure die casting component, carburetor housing of aluminium alloy (Al2Si2O5) has been considered. The effects of selected process parameters on casting defects and subsequent setting of parameters with the levels have been accomplished by Taguchi-s parameter design approach. The experiments have been performed as per the combination of levels of different process parameters suggested by L18 orthogonal array. Analyses of variance have been performed for mean and signal-to-noise ratio to estimate the percent contribution of different process parameters. Confidence interval has also been estimated for 95% consistency level and three conformational experiments have been performed to validate the optimum level of different parameters. Overall 2.352% reduction in defects has been observed with the help of suggested optimum process parameters.
Keywords: Aluminium Casting, Pressure Die Casting, Taguchi Methodology, Design of Experiments
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7335824 MJPEG Real-Time Transmission in Industrial Environments Using a CBR Channel
Authors: J. Silvestre, L. Almeida, R. Marau, P. Pedreiras
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Currently, there are many local area industrial networks that can give guaranteed bandwidth to synchronous traffic, particularly providing CBR channels (Constant Bit Rate), which allow improved bandwidth management. Some of such networks operate over Ethernet, delivering channels with enough capacity, specially with compressors, to integrate multimedia traffic in industrial monitoring and image processing applications with many sources. In these industrial environments where a low latency is an essential requirement, JPEG is an adequate compressing technique but it generates VBR traffic (Variable Bit Rate). Transmitting VBR traffic in CBR channels is inefficient and current solutions to this problem significantly increase the latency or further degrade the quality. In this paper an R(q) model is used which allows on-line calculation of the JPEG quantification factor. We obtained increased quality, a lower requirement for the CBR channel with reduced number of discarded frames along with better use of the channel bandwidth.Keywords: Industrial Networks, Multimedia.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1594823 An Improved Scheduling Strategy in Cloud Using Trust Based Mechanism
Authors: D. Sumathi, P. Poongodi
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Cloud Computing refers to applications delivered as services over the internet, and the datacenters that provide those services with hardware and systems software. These were earlier referred to as Software as a Service (SaaS). Scheduling is justified by job components (called tasks), lack of information. In fact, in a large fraction of jobs from machine learning, bio-computing, and image processing domains, it is possible to estimate the maximum time required for a task in the job. This study focuses on Trust based scheduling to improve cloud security by modifying Heterogeneous Earliest Finish Time (HEFT) algorithm. It also proposes TR-HEFT (Trust Reputation HEFT) which is then compared to Dynamic Load Scheduling.Keywords: Software as a Service (SaaS), Trust, Heterogeneous Earliest Finish Time (HEFT) algorithm, Dynamic Load Scheduling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2196822 Power System Stability Improvement by Simultaneous Tuning of PSS and SVC Based Damping Controllers Employing Differential Evolution Algorithm
Authors: Sangram Keshori Mohapatra, Sidhartha Panda, Prasant Kumar Satpathy
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Power-system stability improvement by simultaneous tuning of power system stabilizer (PSS) and a Static Var Compensator (SVC) based damping controller is thoroughly investigated in this paper. Both local and remote signals with associated time delays are considered in the present study. The design problem of the proposed controller is formulated as an optimization problem, and differential evolution (DE) algorithm is employed to search for the optimal controller parameters. The performances of the proposed controllers are evaluated under different disturbances for both single-machine infinite bus power system and multi-machine power system. The performance of the proposed controllers with variations in the signal transmission delays has also been investigated. The proposed stabilizers are tested on a weakly connected power system subjected to different disturbances. Nonlinear simulation results are presented to show the effectiveness and robustness of the proposed control schemes over a wide range of loading conditions and disturbances. Further, the proposed design approach is found to be robust and improves stability effectively even under small disturbance conditions.
Keywords: Differential Evolution Algorithm, Power System Stability, Power System Stabilizer, Static Var Compensator
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2339821 An Enhanced Slicing Algorithm Using Nearest Distance Analysis for Layer Manufacturing
Authors: M. Vatani, A. R. Rahimi, F. Brazandeh, A. Sanati nezhad
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Although the STL (stereo lithography) file format is widely used as a de facto industry standard in the rapid prototyping industry due to its simplicity and ability to tessellation of almost all surfaces, but there are always some defects and shortcoming in their usage, which many of them are difficult to correct manually. In processing the complex models, size of the file and its defects grow extremely, therefore, correcting STL files become difficult. In this paper through optimizing the exiting algorithms, size of the files and memory usage of computers to process them will be reduced. In spite of type and extent of the errors in STL files, the tail-to-head searching method and analysis of the nearest distance between tails and heads techniques were used. As a result STL models sliced rapidly, and fully closed contours produced effectively and errorless.Keywords: Layer manufacturing, STL files, slicing algorithm, nearest distance analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4158820 Energy Detection Based Sensing and Primary User Traffic Classification for Cognitive Radio
Authors: Urvee B. Trivedi, U. D. Dalal
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As wireless communication services grow quickly; the seriousness of spectrum utilization has been on the rise gradually. An emerging technology, cognitive radio has come out to solve today’s spectrum scarcity problem. To support the spectrum reuse functionality, secondary users are required to sense the radio frequency environment, and once the primary users are found to be active, the secondary users are required to vacate the channel within a certain amount of time. Therefore, spectrum sensing is of significant importance. Once sensing is done, different prediction rules apply to classify the traffic pattern of primary user. Primary user follows two types of traffic patterns: periodic and stochastic ON-OFF patterns. A cognitive radio can learn the patterns in different channels over time. Two types of classification methods are discussed in this paper, by considering edge detection and by using autocorrelation function. Edge detection method has a high accuracy but it cannot tolerate sensing errors. Autocorrelation-based classification is applicable in the real environment as it can tolerate some amount of sensing errors.Keywords: Cognitive radio (CR), probability of detection (PD), probability of false alarm (PF), primary User (PU), secondary user (SU), Fast Fourier transform (FFT), signal to noise ratio (SNR).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1470819 Subjective Evaluation of Spectral and Time Domain Cascading Algorithm for Speech Enhancement for Mobile Communication
Authors: Harish Chander, Balwinder Singh, Ravinder Khanna
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In this paper, we present the comparative subjective analysis of Improved Minima Controlled Recursive Averaging (IMCRA) Algorithm, the Kalman filter and the cascading of IMCRA and Kalman filter algorithms. Performance of speech enhancement algorithms can be predicted in two different ways. One is the objective method of evaluation in which the speech quality parameters are predicted computationally. The second is a subjective listening test in which the processed speech signal is subjected to the listeners who judge the quality of speech on certain parameters. The comparative objective evaluation of these algorithms was analyzed in terms of Global SNR, Segmental SNR and Perceptual Evaluation of Speech Quality (PESQ) by the authors and it was reported that with cascaded algorithms there is a substantial increase in objective parameters. Since subjective evaluation is the real test to judge the quality of speech enhancement algorithms, the authenticity of superiority of cascaded algorithms over individual IMCRA and Kalman algorithms is tested through subjective analysis in this paper. The results of subjective listening tests have confirmed that the cascaded algorithms perform better under all types of noise conditions.
Keywords: Speech enhancement, spectral domain, time domain, PESQ, subjective analysis, objective analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1231818 A Novel Fuzzy Technique for Image Noise Reduction
Authors: Hamed Vahdat Nejad, Hameed Reza Pourreza, Hasan Ebrahimi
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A new fuzzy filter is presented for noise reduction of images corrupted with additive noise. The filter consists of two stages. In the first stage, all the pixels of image are processed for determining noisy pixels. For this, a fuzzy rule based system associates a degree to each pixel. The degree of a pixel is a real number in the range [0,1], which denotes a probability that the pixel is not considered as a noisy pixel. In the second stage, another fuzzy rule based system is employed. It uses the output of the previous fuzzy system to perform fuzzy smoothing by weighting the contributions of neighboring pixel values. Experimental results are obtained to show the feasibility of the proposed filter. These results are also compared to other filters by numerical measure and visual inspection.Keywords: Additive noise, Fuzzy logic, Image processing, Noise reduction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2112817 Variance Based Component Analysis for Texture Segmentation
Authors: Zeinab Ghasemi, S. Amirhassan Monadjemi, Abbas Vafaei
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This paper presents a comparative analysis of a new unsupervised PCA-based technique for steel plates texture segmentation towards defect detection. The proposed scheme called Variance Based Component Analysis or VBCA employs PCA for feature extraction, applies a feature reduction algorithm based on variance of eigenpictures and classifies the pixels as defective and normal. While the classic PCA uses a clusterer like Kmeans for pixel clustering, VBCA employs thresholding and some post processing operations to label pixels as defective and normal. The experimental results show that proposed algorithm called VBCA is 12.46% more accurate and 78.85% faster than the classic PCA. Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1973816 Performance Analysis of MT Evaluation Measures and Test Suites
Authors: Yao Jian-Min, Lv Qiang, Zhang Jing
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Many measures have been proposed for machine translation evaluation (MTE) while little research has been done on the performance of MTE methods. This paper is an effort for MTE performance analysis. A general frame is proposed for the description of the MTE measure and the test suite, including whether the automatic measure is consistent with human evaluation, whether different results from various measures or test suites are consistent, whether the content of the test suite is suitable for performance evaluation, the degree of difficulty of the test suite and its influence on the MTE, the relationship of MTE result significance and the size of the test suite, etc. For a better clarification of the frame, several experiment results are analyzed relating human evaluation, BLEU evaluation, and typological MTE. A visualization method is introduced for better presentation of the results. The study aims for aid in construction of test suite and method selection in MTE practice.Keywords: Machine translation, natural language processing, visualization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1706815 Rule-Based Expert System for Headache Diagnosis and Medication Recommendation
Authors: Noura Al-Ajmi, Mohammed A. Almulla
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With the increased utilization of technology devices around the world, healthcare and medical diagnosis are critical issues that people worry about these days. Doctors are doing their best to avoid any medical errors while diagnosing diseases and prescribing the wrong medication. Subsequently, artificial intelligence applications that can be installed on mobile devices such as rule-based expert systems facilitate the task of assisting doctors in several ways. Due to their many advantages, the usage of expert systems has increased recently in health sciences. This work presents a backward rule-based expert system that can be used for a headache diagnosis and medication recommendation system. The structure of the system consists of three main modules, namely the input unit, the processing unit, and the output unit.Keywords: Headache diagnosis system, treatment recommender system, rule-based expert system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 746814 Effect of Scanning Speed on Material Efficiency of Laser Metal Deposited Ti6Al4V
Authors: Esther T. Akinlabi, Rasheedat M. Mahamood, Mukul Shukla, Sisa. Pityana
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The study of effect of laser scanning speed on material efficiency in Ti6Al4V application is very important because unspent powder is not reusable because of high temperature oxygen pick-up and contamination. This study carried out an extensive study on the effect of scanning speed on material efficiency by varying the speed between 0.01 to 0.1m/sec. The samples are wire brushed and cleaned with acetone after each deposition to remove un-melted particles from the surface of the deposit. The substrate is weighed before and after deposition. A formula was developed to calculate the material efficiency and the scanning speed was compared with the powder efficiency obtained. The results are presented and discussed. The study revealed that the optimum scanning speed exists for this study at 0.01m/sec, above and below which the powder efficiency will dropKeywords: Additive Manufacturing, Laser Metal Deposition Process, Material efficiency, Processing Parameter, Titanium alloy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2348813 Microwave Pretreatment of Seeds to Extract High Quality Vegetable Oil
Authors: S. Azadmard-Damirchi, K. Alirezalu, B. Fathi Achachlouei
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Microwave energy is a superior alternative to several other thermal treatments. Extraction techniques are widely employed for the isolation of bioactive compounds and vegetable oils from oil seeds. Among the different and new available techniques, microwave pretreatment of seeds is a simple and desirable method for production of high quality vegetable oils. Microwave pretreatment for oil extraction has many advantages as follow: improving oil extraction yield and quality, direct extraction capability, lower energy consumption, faster processing time and reduced solvent levels compared with conventional methods. It allows also for better retention and availability of desirable nutraceuticals, such as phytosterols and tocopherols, canolol and phenolic compounds in the extracted oil such as rapeseed oil. This can be a new step to produce nutritional vegetable oils with improved shelf life because of high antioxidant content.
Keywords: Microwave pretreatment, vegetable oil extraction, nutraceuticals, oil quality
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4907812 1G2A IMU\GPS Integration Algorithm for Land Vehicle Navigation
Authors: O. Maklouf, Ahmed Abdulla
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A general decline in the cost, size, and power requirements of electronics is accelerating the adoption of integrated GPS/INS technologies in consumer applications such Land Vehicle Navigation. Researchers have looking for ways to eliminate additional components from product designs. One possibility is to drop one or more of the relatively expensive gyroscopes from microelectromechanical system (MEMS) versions of inertial measurement units (IMUs). For land vehicular use, the most important gyroscope is the vertical gyro that senses the heading of the vehicle and two horizontal accelerometers for determining the velocity of the vehicle. This paper presents a simplified integration algorithm for strap down (ParIMU)\GPS combination, with data post processing for the determination of 2-D components of position (trajectory), velocity and heading. In the present approach we have neglected earth rotation and gravity variations, because of the poor gyroscope sensitivities of the low-cost IMU and because of the relatively small area of the trajectory.
Keywords: GPS, ParIMU, INS, Kalman Filter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2866811 Parallel Text Processing: Alignment of Indonesian to Javanese Language
Authors: Aji P. Wibawa, Andrew Nafalski, Neil Murray, Wayan F. Mahmudy
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Parallel text alignment is proposed as a way of aligning bahasa Indonesia to words in Javanese. Since the one-to-one word translator does not have the facility to translate pragmatic aspects of Javanese, the parallel text alignment model described uses a phrase pair combination. The algorithm aligns the parallel text automatically from the beginning to the end of each sentence. Even though the results of the phrase pair combination outperform the previous algorithm, it is still inefficient. Recording all possible combinations consume more space in the database and time consuming. The original algorithm is modified by applying the edit distance coefficient to improve the data-storage efficiency. As a result, the data-storage consumption is 90% reduced as well as its learning period (42s).
Keywords: Parallel text alignment, phrase pair combination, edit distance coefficient, Javanese-Indonesian language.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2482810 Intelligent Temperature Controller for Water-Bath System
Authors: Om Prakash Verma, Rajesh Singla, Rajesh Kumar
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Conventional controller’s usually required a prior knowledge of mathematical modelling of the process. The inaccuracy of mathematical modelling degrades the performance of the process, especially for non-linear and complex control problem. The process used is Water-Bath system, which is most widely used and nonlinear to some extent. For Water-Bath system, it is necessary to attain desired temperature within a specified period of time to avoid the overshoot and absolute error, with better temperature tracking capability, else the process is disturbed.
To overcome above difficulties intelligent controllers, Fuzzy Logic (FL) and Adaptive Neuro-Fuzzy Inference System (ANFIS), are proposed in this paper. The Fuzzy controller is designed to work with knowledge in the form of linguistic control rules. But the translation of these linguistic rules into the framework of fuzzy set theory depends on the choice of certain parameters, for which no formal method is known. To design ANFIS, Fuzzy-Inference-System is combined with learning capability of Neural-Network.
It is analyzed that ANFIS is best suitable for adaptive temperature control of above system. As compared to PID and FLC, ANFIS produces a stable control signal. It has much better temperature tracking capability with almost zero overshoot and minimum absolute error.
Keywords: PID Controller, FLC, ANFIS, Non-Linear Control System, Water-Bath System, MATLAB-7.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5548809 An Efficient Watermarking Method for MP3 Audio Files
Authors: Dimitrios Koukopoulos, Yiannis Stamatiou
Abstract:
In this work, we present for the first time in our perception an efficient digital watermarking scheme for mpeg audio layer 3 files that operates directly in the compressed data domain, while manipulating the time and subband/channel domain. In addition, it does not need the original signal to detect the watermark. Our scheme was implemented taking special care for the efficient usage of the two limited resources of computer systems: time and space. It offers to the industrial user the capability of watermark embedding and detection in time immediately comparable to the real music time of the original audio file that depends on the mpeg compression, while the end user/audience does not face any artifacts or delays hearing the watermarked audio file. Furthermore, it overcomes the disadvantage of algorithms operating in the PCMData domain to be vulnerable to compression/recompression attacks, as it places the watermark in the scale factors domain and not in the digitized sound audio data. The strength of our scheme, that allows it to be used with success in both authentication and copyright protection, relies on the fact that it gives to the users the enhanced capability their ownership of the audio file not to be accomplished simply by detecting the bit pattern that comprises the watermark itself, but by showing that the legal owner knows a hard to compute property of the watermark.
Keywords: Audio watermarking, mpeg audio layer 3, hard instance generation, NP-completeness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1834808 Neural Network Based Approach for Face Detection cum Face Recognition
Authors: Kesari Verma, Aniruddha S. Thoke, Pritam Singh
Abstract:
Automatic face detection is a complex problem in image processing. Many methods exist to solve this problem such as template matching, Fisher Linear Discriminate, Neural Networks, SVM, and MRC. Success has been achieved with each method to varying degrees and complexities. In proposed algorithm we used upright, frontal faces for single gray scale images with decent resolution and under good lighting condition. In the field of face recognition technique the single face is matched with single face from the training dataset. The author proposed a neural network based face detection algorithm from the photographs as well as if any test data appears it check from the online scanned training dataset. Experimental result shows that the algorithm detected up to 95% accuracy for any image.Keywords: Face Detection, Face Recognition, NN Approach, PCA Algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2301