Search results for: parameter extraction.
1237 Extracting Road Signs using the Color Information
Authors: Wen-Yen Wu, Tsung-Cheng Hsieh, Ching-Sung Lai
Abstract:
In this paper, we propose a method to extract the road signs. Firstly, the grabbed image is converted into the HSV color space to detect the road signs. Secondly, the morphological operations are used to reduce noise. Finally, extract the road sign using the geometric property. The feature extraction of road sign is done by using the color information. The proposed method has been tested for the real situations. From the experimental results, it is seen that the proposed method can extract the road sign features effectively.Keywords: Color information, image processing, road sign.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22411236 Iterative solutions to the linear matrix equation AXB + CXTD = E
Authors: Yongxin Yuan, Jiashang Jiang
Abstract:
In this paper the gradient based iterative algorithm is presented to solve the linear matrix equation AXB +CXTD = E, where X is unknown matrix, A,B,C,D,E are the given constant matrices. It is proved that if the equation has a solution, then the unique minimum norm solution can be obtained by choosing a special kind of initial matrices. Two numerical examples show that the introduced iterative algorithm is quite efficient.Keywords: matrix equation, iterative algorithm, parameter estimation, minimum norm solution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15551235 An Evaluation of Algorithms for Single-Echo Biosonar Target Classification
Authors: Turgay Temel, John Hallam
Abstract:
A recent neurospiking coding scheme for feature extraction from biosonar echoes of various plants is examined with avariety of stochastic classifiers. Feature vectors derived are employedin well-known stochastic classifiers, including nearest-neighborhood,single Gaussian and a Gaussian mixture with EM optimization.Classifiers' performances are evaluated by using cross-validation and bootstrapping techniques. It is shown that the various classifers perform equivalently and that the modified preprocessing configuration yields considerably improved results.
Keywords: Classification, neuro-spike coding, non-parametricmodel, parametric model, Gaussian mixture, EM algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16691234 Information Entropy of Isospectral Hydrogen Atom
Authors: Anil Kumar, C. Nagaraja Kumar
Abstract:
The position and momentum space information entropies of hydrogen atom are exactly evaluated. Using isospectral Hamiltonian approach, a family of isospectral potentials is constructed having same energy eigenvalues as that of the original potential. The information entropy content is obtained in position space as well as in momentum space. It is shown that the information entropy content in each level can be re-arranged as a function of deformation parameter.Keywords: Information Entropy, BBM inequality, Isospectral Potential.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21691233 Hybrid Color-Texture Space for Image Classification
Authors: Hassan El Maia, Ahmed Hammouch, Driss Aboutajdine
Abstract:
This work presents an approach for the construction of a hybrid color-texture space by using mutual information. Feature extraction is done by the Laws filter with SVM (Support Vectors Machine) as a classifier. The classification is applied on the VisTex database and a SPOT HRV (XS) image representing two forest areas in the region of Rabat in Morocco. The result of classification obtained in the hybrid space is compared with the one obtained in the RGB color space.
Keywords: Color, texture, laws filter, mutual information, SVM, hybrid space.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18261232 Indoor Mapping by using Smartphone Device
Authors: Shuib Rambat, Ruzsyahriman Jenal, John Elgy
Abstract:
This paper presented the potential of smart phone to provide support on mapping the indoor asset. The advantage of using the smart phone to generate the indoor map is that it has the ability to capture, store and reproduces still or video images; indeed most of us do have this powerful gadget. The captured images usually used by maintenance team to save a record for future reference. Here, these images are used to generate 3D models of an object precisely and accurately for efficient and effective solution in data gathering. Thus, it could be a resource for an informative database in asset management.Keywords: 3D modeling, Asset Management, Object Extraction, Smart Device
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27931231 Unified Method to Block Pornographic Images in Websites
Authors: Sakthi Priya Balaji R., Vijayendar G.
Abstract:
This paper proposes a technique to block adult images displayed in websites. The filter is designed so as to perform even in exceptional cases such as, where face detection is not possible or improper face visibility. This is achieved by using an alternative phase to extract the MFC (Most Frequent Color) from the Human Body regions estimated using a biometric of anthropometric distances between fixed rigidly connected body locations. The logical results generated can be protected from overriding by a firewall or intrusion, by encrypting the result in a SSH data packet.
Keywords: Face detection, characteristics extraction andclassification, Component based shape analysis and classification, open source SSH V2 protocol
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13961230 Classification of Radio Communication Signals using Fuzzy Logic
Authors: Zuzana Dideková, Beata Mikovičová
Abstract:
Characterization of radio communication signals aims at automatic recognition of different characteristics of radio signals in order to detect their modulation type, the central frequency, and the level. Our purpose is to apply techniques used in image processing in order to extract pertinent characteristics. To the single analysis, we add several rules for checking the consistency of hypotheses using fuzzy logic. This allows taking into account ambiguity and uncertainty that may remain after the extraction of individual characteristics. The aim is to improve the process of radio communications characterization.Keywords: fuzzy classification, fuzzy inference system, radio communication signals, telecommunications
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19711229 Genetic Mining: Using Genetic Algorithm for Topic based on Concept Distribution
Authors: S. M. Khalessizadeh, R. Zaefarian, S.H. Nasseri, E. Ardil
Abstract:
Today, Genetic Algorithm has been used to solve wide range of optimization problems. Some researches conduct on applying Genetic Algorithm to text classification, summarization and information retrieval system in text mining process. This researches show a better performance due to the nature of Genetic Algorithm. In this paper a new algorithm for using Genetic Algorithm in concept weighting and topic identification, based on concept standard deviation will be explored.Keywords: Genetic Algorithm, Text Mining, Term Weighting, Concept Extraction, Concept Distribution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37151228 A Learning Agent for Knowledge Extraction from an Active Semantic Network
Authors: Simon Thiel, Stavros Dalakakis, Dieter Roller
Abstract:
This paper outlines the development of a learning retrieval agent. Task of this agent is to extract knowledge of the Active Semantic Network in respect to user-requests. Based on a reinforcement learning approach, the agent learns to interpret the user-s intention. Especially, the learning algorithm focuses on the retrieval of complex long distant relations. Increasing its learnt knowledge with every request-result-evaluation sequence, the agent enhances his capability in finding the intended information.
Keywords: Reinforcement learning, learning retrieval agent, search in semantic networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14941227 Face Recognition Using Eigen face Coefficients and Principal Component Analysis
Authors: Parvinder S. Sandhu, Iqbaldeep Kaur, Amit Verma, Samriti Jindal, Inderpreet Kaur, Shilpi Kumari
Abstract:
Face Recognition is a field of multidimensional applications. A lot of work has been done, extensively on the most of details related to face recognition. This idea of face recognition using PCA is one of them. In this paper the PCA features for Feature extraction are used and matching is done for the face under consideration with the test image using Eigen face coefficients. The crux of the work lies in optimizing Euclidean distance and paving the way to test the same algorithm using Matlab which is an efficient tool having powerful user interface along with simplicity in representing complex images.Keywords: Eigen Face, Multidimensional, Matching, PCA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28701226 Using Automatic Ontology Learning Methods in Human Plausible Reasoning Based Systems
Authors: A. R. Vazifedoost, M. Rahgozar, F. Oroumchian
Abstract:
Knowledge discovery from text and ontology learning are relatively new fields. However their usage is extended in many fields like Information Retrieval (IR) and its related domains. Human Plausible Reasoning based (HPR) IR systems for example need a knowledge base as their underlying system which is currently made by hand. In this paper we propose an architecture based on ontology learning methods to automatically generate the needed HPR knowledge base.Keywords: Ontology Learning, Human Plausible Reasoning, knowledge extraction, knowledge representation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16011225 Human Verification in a Video Surveillance System Using Statistical Features
Authors: Sanpachai Huvanandana
Abstract:
A human verification system is presented in this paper. The system consists of several steps: background subtraction, thresholding, line connection, region growing, morphlogy, star skelatonization, feature extraction, feature matching, and decision making. The proposed system combines an advantage of star skeletonization and simple statistic features. A correlation matching and probability voting have been used for verification, followed by a logical operation in a decision making stage. The proposed system uses small number of features and the system reliability is convincing.Keywords: Human verification, object recognition, videounderstanding, segmentation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15061224 Time-Derivative Estimation of Noisy Movie Data using Adaptive Control Theory
Authors: Soon-Hyun Park, Takami Matsuo
Abstract:
This paper presents an adaptive differentiator of sequential data based on the adaptive control theory. The algorithm is applied to detect moving objects by estimating a temporal gradient of sequential data at a specified pixel. We adopt two nonlinear intensity functions to reduce the influence of noises. The derivatives of the nonlinear intensity functions are estimated by an adaptive observer with σ-modification update law.Keywords: Adaptive estimation, parameter adjustmentlaw, motion detection, temporal gradient, differential filter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18731223 Semi-Automatic Approach for Semantic Annotation
Authors: Mohammad Yasrebi, Mehran Mohsenzadeh
Abstract:
The third phase of web means semantic web requires many web pages which are annotated with metadata. Thus, a crucial question is where to acquire these metadata. In this paper we propose our approach, a semi-automatic method to annotate the texts of documents and web pages and employs with a quite comprehensive knowledge base to categorize instances with regard to ontology. The approach is evaluated against the manual annotations and one of the most popular annotation tools which works the same as our tool. The approach is implemented in .net framework and uses the WordNet for knowledge base, an annotation tool for the Semantic Web.
Keywords: Semantic Annotation, Metadata, Information Extraction, Semantic Web, knowledge base.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18671222 Parallelization and Optimization of SIFT Feature Extraction on Cluster System
Authors: Mingling Zheng, Zhenlong Song, Ke Xu, Hengzhu Liu
Abstract:
Scale Invariant Feature Transform (SIFT) has been widely applied, but extracting SIFT feature is complicated and time-consuming. In this paper, to meet the demand of the real-time applications, SIFT is parallelized and optimized on cluster system, which is named pSIFT. Redundancy storage and communication are used for boundary data to improve the performance, and before representation of feature descriptor, data reallocation is adopted to keep load balance in pSIFT. Experimental results show that pSIFT achieves good speedup and scalability.Keywords: cluster, image matching, parallelization and optimization, SIFT.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18631221 Analysis of Combined Use of NN and MFCC for Speech Recognition
Authors: Safdar Tanweer, Abdul Mobin, Afshar Alam
Abstract:
The performance and analysis of speech recognition system is illustrated in this paper. An approach to recognize the English word corresponding to digit (0-9) spoken by 2 different speakers is captured in noise free environment. For feature extraction, speech Mel frequency cepstral coefficients (MFCC) has been used which gives a set of feature vectors from recorded speech samples. Neural network model is used to enhance the recognition performance. Feed forward neural network with back propagation algorithm model is used. However other speech recognition techniques such as HMM, DTW exist. All experiments are carried out on Matlab.
Keywords: Speech Recognition, MFCC, Neural Network, classifier.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32681220 Hybrid Knowledge Approach for Determining Health Care Provider Specialty from Patient Diagnoses
Authors: Erin Lynne Plettenberg, Jeremy Vickery
Abstract:
In an access-control situation, the role of a user determines whether a data request is appropriate. This paper combines vetted web mining and logic modeling to build a lightweight system for determining the role of a health care provider based only on their prior authorized requests. The model identifies provider roles with 100% recall from very little data. This shows the value of vetted web mining in AI systems, and suggests the impact of the ICD classification on medical practice.
Keywords: Ontology, logic modeling, electronic medical records, information extraction, vetted web mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9361219 Identifying an Unknown Source in the Poisson Equation by a Modified Tikhonov Regularization Method
Authors: Ou Xie, Zhenyu Zhao
Abstract:
In this paper, we consider the problem for identifying the unknown source in the Poisson equation. A modified Tikhonov regularization method is presented to deal with illposedness of the problem and error estimates are obtained with an a priori strategy and an a posteriori choice rule to find the regularization parameter. Numerical examples show that the proposed method is effective and stable.
Keywords: Ill-posed problem, Unknown source, Poisson equation, Tikhonov regularization method, Discrepancy principle
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14501218 Estimating Reaction Rate Constants with Neural Networks
Authors: Benedek Kovacs, Janos Toth
Abstract:
Solutions are proposed for the central problem of estimating the reaction rate coefficients in homogeneous kinetics. The first is based upon the fact that the right hand side of a kinetic differential equation is linear in the rate constants, whereas the second one uses the technique of neural networks. This second one is discussed deeply and its advantages, disadvantages and conditions of applicability are analyzed in the mirror of the first one. Numerical analysis carried out on practical models using simulated data, and our programs written in Mathematica.
Keywords: Neural networks, parameter estimation, linear regression, kinetic models, reaction rate coefficients.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19971217 Study of a Crude Oil Desalting Plant of the National Iranian South Oil Company in Gachsaran by Using Artificial Neural Networks
Authors: H. Kiani, S. Moradi, B. Soltani Soulgani, S. Mousavian
Abstract:
Desalting/dehydration plants (DDP) are often installed in crude oil production units in order to remove water-soluble salts from an oil stream. In order to optimize this process, desalting unit should be modeled. In this research, artificial neural network is used to model efficiency of desalting unit as a function of input parameter. The result of this research shows that the mentioned model has good agreement with experimental data.
Keywords: Desalting unit, Crude oil, Neural Networks, Simulation, Recovery, Separation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 42501216 A Supervised Text-Independent Speaker Recognition Approach
Authors: Tudor Barbu
Abstract:
We provide a supervised speech-independent voice recognition technique in this paper. In the feature extraction stage we propose a mel-cepstral based approach. Our feature vector classification method uses a special nonlinear metric, derived from the Hausdorff distance for sets, and a minimum mean distance classifier.
Keywords: Text-independent speaker recognition, mel cepstral analysis, speech feature vector, Hausdorff-based metric, supervised classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18291215 Current Drainage Attack Correction via Adjusting the Attacking Saw Function Asymmetry
Authors: Yuri Boiko, Iluju Kiringa, Tet Yeap
Abstract:
Current drainage attack suggested previously is further studied in regular settings of closed-loop controlled Brushless DC (BLDC) motor with Kalman filter in the feedback loop. Modeling and simulation experiments are conducted in a MATLAB environment, implementing the closed-loop control model of BLDC motor operation in position sensorless mode under Kalman filter drive. The current increase in the motor windings is caused by the controller (p-controller in our case) affected by false data injection of substitution of the angular velocity estimates with distorted values. Operation of multiplication to distortion coefficient, values of which are taken from the distortion function synchronized in its periodicity with the rotor’s position change. A saw function with a triangular tooth shape is studied herewith for the purpose of carrying out the bias injection with current drainage consequences. The specific focus here is on how the asymmetry of the tooth in the saw function affects the flow of current drainage. The purpose is two-fold: (i) to produce and collect the signature of an asymmetric saw in the attack for further pattern recognition process, and (ii) to determine conditions of improving stealthiness of such attack via regulating asymmetry in saw function used. It is found that modification of the symmetry in the saw tooth affects the periodicity of current drainage modulation. Specifically, the modulation frequency of the drained current for a fully asymmetric tooth shape coincides with the saw function modulation frequency itself. Increasing the symmetry parameter for the triangle tooth shape leads to an increase in the modulation frequency for the drained current. Moreover, such frequency reaches the switching frequency of the motor windings for fully symmetric triangular shapes, thus becoming undetectable and improving the stealthiness of the attack. Therefore, the collected signatures of the attack can serve for attack parameter identification via the pattern recognition route.
Keywords: Bias injection attack, Kalman filter, BLDC motor, control system, closed loop, P-controller, PID-controller, current drainage, saw-function, asymmetry.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1551214 End Point Detection for Wavelet Based Speech Compression
Authors: Jalal Karam
Abstract:
In real-field applications, the correct determination of voice segments highly improves the overall system accuracy and minimises the total computation time. This paper presents reliable measures of speech compression by detcting the end points of the speech signals prior to compressing them. The two different compession schemes used are the Global threshold and the Level- Dependent threshold techniques. The performance of the proposed method is tested wirh the Signal to Noise Ratios, Peak Signal to Noise Ratios and Normalized Root Mean Square Error parameter measures.
Keywords: Wavelets, End-points Detection, Compression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13781213 Extraction of Graphene-Titanium Contact Resistances using Transfer Length Measurement and a Curve-Fit Method
Authors: Johanna Anteroinen, Wonjae Kim, Kari Stadius, Juha Riikonen, Harri Lipsanen, Jussi Ryynanen
Abstract:
Graphene-metal contact resistance limits the performance of graphene-based electrical devices. In this work, we have fabricated both graphene field-effect transistors (GFET) and transfer length measurement (TLM) test devices with titanium contacts. The purpose of this work is to compare the contact resistances that can be numerically extracted from the GFETs and measured from the TLM structures. We also provide a brief review of the work done in the field to solve the contact resistance problem.
Keywords: Contact resistance, graphene, TLM
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37541212 Generalized Chaplygin Gas and Varying Bulk Viscosity in Lyra Geometry
Authors: A. K. Sethi, R. N. Patra, B. Nayak
Abstract:
In this paper, we have considered Friedmann-Robertson-Walker (FRW) metric with generalized Chaplygin gas which has viscosity in the context of Lyra geometry. The viscosity is considered in two different ways (i.e. zero viscosity, non-constant r (rho)-dependent bulk viscosity) using constant deceleration parameter which concluded that, for a special case, the viscous generalized Chaplygin gas reduces to modified Chaplygin gas. The represented model indicates on the presence of Chaplygin gas in the Universe. Observational constraints are applied and discussed on the physical and geometrical nature of the Universe.
Keywords: Bulk viscosity, Lyra geometry, generalized Chaplygin gas, cosmology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7971211 Flow and Heat Transfer over a Shrinking Sheet: A Stability Analysis
Authors: Anuar Ishak
Abstract:
The characteristics of fluid flow and heat transfer over a permeable shrinking sheet is studied. The governing partial differential equations are transformed into a set of ordinary differential equations, which are then solved numerically using MATLAB routine boundary value problem solver bvp4c. Numerical results show that dual solutions are possible for a certain range of the suction parameter. A stability analysis is performed to determine which solution is linearly stable and physically realizable.
Keywords: Dual solutions, heat transfer, shrinking sheet, stability analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20171210 The Relative Efficiency of Parameter Estimation in Linear Weighted Regression
Authors: Baoguang Tian, Nan Chen
Abstract:
A new relative efficiency in linear model in reference is instructed into the linear weighted regression, and its upper and lower bound are proposed. In the linear weighted regression model, for the best linear unbiased estimation of mean matrix respect to the least-squares estimation, two new relative efficiencies are given, and their upper and lower bounds are also studied.
Keywords: Linear weighted regression, Relative efficiency, Mean matrix, Trace.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24731209 Physical Parameters for Reliability Evaluation
Abstract:
This paper presents ageing experiments controlled by the evolution of junction parameters. The deterioration of the device is related to high injection effects which modified the transport mechanisms in the space charge region of the junction. Physical phenomena linked to the degradation of junction parameters that affect the devices reliability are reported and discussed. We have used the method based on numerical analysis of experimental current-voltage characteristic of the junction, in order to extract the electrical parameters. The simultaneous follow-up of the evolutions of the series resistance and of the transition voltage allow us to introduce a new parameter for reliability evaluation.
Keywords: High injection, junction, parameters, reliability
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13811208 The Evaluation of Complete Blood Cell Count-Based Inflammatory Markers in Pediatric Obesity and Metabolic Syndrome
Authors: Mustafa M. Donma, Orkide Donma
Abstract:
Obesity is defined as a severe chronic disease characterized by a low-grade inflammatory state. Therefore, inflammatory markers gained utmost importance during the evaluation of obesity and metabolic syndrome (MetS), a disease characterized by central obesity, elevated blood pressure, increased fasting blood glucose and elevated triglycerides or reduced high density lipoprotein cholesterol (HDL-C) values. Some inflammatory markers based upon complete blood cell count (CBC) are available. In this study, it was questioned which inflammatory marker was the best to evaluate the differences between various obesity groups. 514 pediatric individuals were recruited. 132 children with MetS, 155 morbid obese (MO), 90 obese (OB), 38 overweight (OW) and 99 children with normal BMI (N-BMI) were included into the scope of this study. Obesity groups were constituted using age- and sex-dependent body mass index (BMI) percentiles tabulated by World Health Organization. MetS components were determined to be able to specify children with MetS. CBC were determined using automated hematology analyzer. HDL-C analysis was performed. Using CBC parameters and HDL-C values, ratio markers of inflammation, which cover neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (dNLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), monocyte-to-HDL-C ratio (MHR) were calculated. Statistical analyses were performed. The statistical significance degree was considered as p < 0.05. There was no statistically significant difference among the groups in terms of platelet count, neutrophil count, lymphocyte count, monocyte count, and NLR. PLR differed significantly between OW and N-BMI as well as MetS. Monocyte-to HDL-C value exhibited statistical significance between MetS and N-BMI, OB, and MO groups. HDL-C value differed between MetS and N-BMI, OW, OB, MO groups. MHR was the ratio, which exhibits the best performance among the other CBC-based inflammatory markers. On the other hand, when MHR was compared to HDL-C only, it was suggested that HDL-C has given much more valuable information. Therefore, this parameter still keeps its value from the diagnostic point of view. Our results suggest that MHR can be an inflammatory marker during the evaluation of pediatric MetS, but the predictive value of this parameter was not superior to HDL-C during the evaluation of obesity.
Keywords: Children, complete blood cell count, high density lipoprotein cholesterol, metabolic syndrome, obesity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 851