Search results for: Ascending Sort Index Vector

Authors: Mustafa M. Donma, Orkide Donma

Abstract:

Obesity is a clinical state associated with low-grade inflammation. It is also a major risk factor for insulin resistance (IR). In its advanced stages, metabolic syndrome (MetS), a much more complicated disease which may lead to life-threatening problems, may develop. Obesity-mediated IR seems to correlate with the inflammation. Human studies performed particularly on pediatric population are scarce. The aim of this study is to detect possible associations between inflammation and IR in terms of some related ratios. 549 children were grouped according to their age- and sex-based body mass index (BMI) percentile tables of WHO. MetS components were determined. Informed consent and approval from the Ethics Committee for Clinical Investigations were obtained. The principles of the Declaration of Helsinki were followed. The exclusion criteria were infection, inflammation, chronic diseases and those under drug treatment. Anthropometric measurements were obtained. Complete blood cell, fasting blood glucose, insulin, and C-reactive protein (CRP) analyses were performed. Homeostasis model assessment of insulin resistance (HOMA-IR), systemic immune inflammation (SII) index, tense index, alanine aminotransferase to aspartate aminotransferase ratio (ALT/AST), neutrophils to lymphocyte (NLR), platelet to lymphocyte, and lymphocyte to monocyte ratios were calculated. Data were evaluated by statistical analyses. The degree for statistical significance was 0.05. Statistically significant differences were found among the BMI values of the groups (p < 0.001). Strong correlations were detected between the BMI and waist circumference (WC) values in all groups. Tense index values were also correlated with both BMI and WC values in all groups except overweight (OW) children. SII index values of children with normal BMI were significantly different from the values obtained in OW, obese, morbid obese and MetS groups. Among all the other lymphocyte ratios, NLR exhibited a similar profile. Both HOMA-IR and ALT/AST values displayed an increasing profile from N towards MetS3 group. BMI and WC values were correlated with HOMA-IR and ALT/AST. Both in morbid obese and MetS groups, significant correlations between CRP versus SII index as well as HOMA-IR versus ALT/AST were found. ALT/AST and HOMA-IR values were correlated with NLR in morbid obese group and with SII index in MetS group, (p < 0.05), respectively. In conclusion, these findings showed that some parameters may exhibit informative differences between the early and late stages of obesity. Important associations among HOMA-IR, ALT/AST, NLR and SII index have come to light in the morbid obese and MetS groups. This study introduced the SII index and NLR as important inflammatory markers for the discrimination of normal and obese children. Interesting links were observed between inflammation and IR in morbid obese children and those with MetS, both being late stages of obesity.

Keywords: Children, inflammation, insulin resistance, metabolic syndrome, obesity.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 870

Authors: Chi Jung Kim, Mincheol Whang, Eui Chul Lee

Abstract:

In this paper, we propose a new method to distinguish between arousal and relaxation states by using multiple features acquired from a photoplethysmogram (PPG) and support vector machine (SVM). To induce arousal and relaxation states in subjects, 2 kinds of sound stimuli are used, and their corresponding biosignals are obtained using the PPG sensor. Two features–pulse to pulse interval (PPI) and pulse amplitude (PA)–are extracted from acquired PPG data, and a nonlinear classification between arousal and relaxation is performed using SVM. This methodology has several advantages when compared with previous similar studies. Firstly, we extracted 2 separate features from PPG, i.e., PPI and PA. Secondly, in order to improve the classification accuracy, SVM-based nonlinear classification was performed. Thirdly, to solve classification problems caused by generalized features of whole subjects, we defined each threshold according to individual features. Experimental results showed that the average classification accuracy was 74.67%. Also, the proposed method showed the better identification performance than the single feature based methods. From this result, we confirmed that arousal and relaxation can be classified using SVM and PPG features.

Keywords: Support Vector Machine, PPG, Emotion Recognition, Arousal, Relaxation

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2463

Authors: Mohini Polimetla, Rajat Mahapatra

Abstract:

There is need to explore emerging technologies based on carbon nanotube electronics as the MOS technology is approaching its limits. As MOS devices scale to the nano ranges, increased short channel effects and process variations considerably effect device and circuit designs. As a promising new transistor, the Carbon Nanotube Field Effect Transistor(CNTFET) avoids most of the fundamental limitations of the Traditional MOSFET devices. In this paper we present the analysis and comparision of a Carbon Nanotube FET(CNTFET) based 10(A current mirror with MOSFET for 32nm technology node. The comparision shows the superiority of the former in terms of 97% increase in output resistance,24% decrease in power dissipation and 40% decrease in minimum voltage required for constant saturation current. Furthermore the effect on performance of current mirror due to change in chirality vector of CNT has also been investigated. The circuit simulations are carried out using HSPICE model.

Keywords: Carbon Nanotube Field Effect Transistor, Chirality Vector, Current Mirror

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2993

Authors: Rachid Ahdid, Said Safi, Bouzid Manaut

Abstract:

In this paper, we present a comparative study of three methods of 2D face recognition system such as: Iso-Geodesic Curves (IGC), Geodesic Distance (GD) and Geodesic-Intensity Histogram (GIH). These approaches are based on computing of geodesic distance between points of facial surface and between facial curves. In this study we represented the image at gray level as a 2D surface in a 3D space, with the third coordinate proportional to the intensity values of pixels. In the classifying step, we use: Neural Networks (NN), K-Nearest Neighbor (KNN) and Support Vector Machines (SVM). The images used in our experiments are from two wellknown databases of face images ORL and YaleB. ORL data base was used to evaluate the performance of methods under conditions where the pose and sample size are varied, and the database YaleB was used to examine the performance of the systems when the facial expressions and lighting are varied.

Keywords: 2D face recognition, Geodesic distance, Iso-Geodesic Curves, Geodesic-Intensity Histogram, facial surface, Neural Networks, K-Nearest Neighbor, Support Vector Machines.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1802

Authors: D.O. Omondi, L.O.A. Othuon, G.M. Mbagaya

Abstract:

The purpose of this study was to determine the influence of physical activity and dietary fat intake on Body Mass Index (BMI) of lecturers within a higher learning institutionalized setting. The study adopted a Cross-sectional Correlational Design and included 120 lecturers selected proportionately by simple random sampling techniques from a population of 600 lecturers. Data was collected using questionnaires, which had sections including physical activity checklist adopted from the international physical activity questionnaire (IPAQ), 24-hour food recall, anthropometric measurements mainly weight and height. Analysis involved the use of bivariate correlations and linear regression. A significant inverse association was registered between BMI and duration (in minutes) spent doing moderate intense physical activity per day (r=-0.322, p<0.01). Physical activity also predicted BMI (r2=0.096, F=13.616, β=-3.22, t=-3.69, n=120, P<0.01). However, the association between Body Mass Index and dietary fat was not significant (r=0.038, p>0.05). Physical activity emerged as a more powerful determinant of BMI compared to dietary fat intake.

Keywords: Physical activity, dietary fat intake, Body MassIndex, Kenya.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1697

Authors: Mesbaholdin Salami, Farzad Movahedi Sobhani, Mohammad Sadegh Ghazizadeh

Abstract:

Evaluation of organizational performance is among the most important measures that help organizations and entities continuously improve their efficiency. Organizations can use the existing data and results from the comparison of units under investigation to obtain an estimation of their performance. The Malmquist Productivity Index (MPI) is an important index in the evaluation of overall productivity, which considers technological developments and technical efficiency at the same time. This article proposed a model based on the multistage MPI, considering limited data (Grey’s theory). This model can evaluate the performance of units using limited and uncertain data in a multistage process. It was applied by the electricity market manager to Iran’s electric power supply chain (EPSC), which contains uncertain data, to evaluate the performance of its actors. Results from solving the model showed an improvement in the accuracy of future performance of the units under investigation, using the Grey’s system theory. This model can be used in all case studies, in which MPI is used and there are limited or uncertain data.

Keywords: Malmquist Index, Grey's Theory, Charnes Cooper & Rhodes (CCR) Model, network data envelopment analysis, Iran electricity power chain.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 540

Authors: Jun Gil Ahn, Jong Kang Park, Jong Tae Kim

Abstract:

In this paper, we analyze major components of activity recognition (AR) in wearable device with 9-axis sensors and sensor fusion filters. 9-axis sensors commonly include 3-axis accelerometer, 3-axis gyroscope and 3-axis magnetometer. We chose sensor fusion filters as Kalman filter and Direction Cosine Matrix (DCM) filter. We also construct sensor fusion data from each activity sensor data and perform classification by accuracy of AR using Naïve Bayes and SVM. According to the classification results, we observed that the DCM filter and the specific combination of the sensing axes are more effective for AR in wearable devices while classifying walking, running, ascending and descending.

Keywords: Accelerometer, activity recognition, directional cosine matrix filter, gyroscope, Kalman filter, magnetometer.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1655

Authors: K. Sakthivel, R. Nallusamy, C. Kavitha

Abstract:

The goal of image segmentation is to cluster pixels into salient image regions. Segmentation could be used for object recognition, occlusion boundary estimation within motion or stereo systems, image compression, image editing, or image database lookup. In this paper, we present a color image segmentation using support vector machine (SVM) pixel classification. Firstly, the pixel level color and texture features of the image are extracted and they are used as input to the SVM classifier. These features are extracted using the homogeneity model and Gabor Filter. With the extracted pixel level features, the SVM Classifier is trained by using FCM (Fuzzy C-Means).The image segmentation takes the advantage of both the pixel level information of the image and also the ability of the SVM Classifier. The Experiments show that the proposed method has a very good segmentation result and a better efficiency, increases the quality of the image segmentation compared with the other segmentation methods proposed in the literature.

Keywords: Image Segmentation, Support Vector Machine, Fuzzy C–Means, Pixel Feature, Texture Feature, Homogeneity model, Gabor Filter.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6722

Authors: Sanghoon Kim, Sun-Tae Chung, Souhwan Jung, Seongwon Cho

Abstract:

Robust face recognition under various illumination environments is very difficult and needs to be accomplished for successful commercialization. In this paper, we propose an improved illumination normalization method for face recognition. Illumination normalization algorithm based on anisotropic smoothing is well known to be effective among illumination normalization methods but deteriorates the intensity contrast of the original image, and incurs less sharp edges. The proposed method in this paper improves the previous anisotropic smoothing-based illumination normalization method so that it increases the intensity contrast and enhances the edges while diminishing the effect of illumination variations. Due to the result of these improvements, face images preprocessed by the proposed illumination normalization method becomes to have more distinctive feature vectors (Gabor feature vectors) for face recognition. Through experiments of face recognition based on Gabor feature vector similarity, the effectiveness of the proposed illumination normalization method is verified.

Keywords: Illumination Normalization, Face Recognition, Anisotropic smoothing, Gabor feature vector.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1529

Authors: Ali A. Ahmed, Mohammed I. Hussein

Abstract:

The amounts of radioactivity in the igneous rocks have been investigated; samples were collected from the total of eight basalt rock types in the northeastern of Kurdistan region/Iraq. The activity concentration of 226Ra (238U) series, 228Ac (232Th) series, 40K and 137Cs were measured using Planar HPGe and NaI(Tl) detectors. Along the study area the radium equivalent activities Raeq in Bq/Kg of samples under investigation were found in the range of 22.16 to 77.31 Bq/Kg with an average value of 44.8 Bq/Kg, this value is much below the internationally accepted value of 370 Bq/Kg. To estimate the health effects of this natural radioactive composition, the average values of absorbed gamma dose rate D (55 nGyh-1), Indoor and outdoor annual effective dose rates Eied (0.11 mSvy-1) . and Eoed (0.03 mSvy-1), External hazard index Hex (0.138) and internal hazard index Hin(0.154), and representative level index Iγr (0.386) have been calculated and found to be lower than the worldwide average values.

Keywords: Absorbed dose, activity concentration, igneousrocks, HPGe, NaI(TI), Natural Radioactivity.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2315

Authors: Pushkar Umaranikar, Chris Pollett

Abstract:

An online advertisement system and its implementation for the Yioop open source search engine are presented. This system supports both selling advertisements and displaying them within search results. The selling of advertisements is done using a system to auction off daily impressions for keyword searches. This is an open, ascending price auction system in which all accepted bids will receive a fraction of the auctioned day’s impressions. New bids in our system are required to be at least one half of the sum of all previous bids ensuring the number of accepted bids is logarithmic in the total ad spend on a keyword for a day. The mechanics of creating an advertisement, attaching keywords to it, and adding it to an advertisement inventory are described. The algorithm used to go from accepted bids for a keyword to which ads are displayed at search time is also presented. We discuss properties of our system and compare it to existing auction systems and systems for selling online advertisements.

Keywords: Online markets, online ad system, online auctions, search engines.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1347

Authors: S. Qaedi, S. Seyedtabaii

Abstract:

Non-Destructive evaluation of in-service power transformer condition is necessary for avoiding catastrophic failures. Dissolved Gas Analysis (DGA) is one of the important methods. Traditional, statistical and intelligent DGA approaches have been adopted for accurate classification of incipient fault sources. Unfortunately, there are not often enough faulty patterns required for sufficient training of intelligent systems. By bootstrapping the shortcoming is expected to be alleviated and algorithms with better classification success rates to be obtained. In this paper the performance of an artificial neural network, K-Nearest Neighbour and support vector machine methods using bootstrapped data are detailed and shown that while the success rate of the ANN algorithms improves remarkably, the outcome of the others do not benefit so much from the provided enlarged data space. For assessment, two databases are employed: IEC TC10 and a dataset collected from reported data in papers. High average test success rate well exhibits the remarkable outcome.

Keywords: Dissolved gas analysis, Transformer incipient fault, Artificial Neural Network, Support Vector Machine (SVM), KNearest Neighbor (KNN)

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2720

Authors: Paitoon Kraipornsak

Abstract:

Government spending is categorized into consumption spending and capital spending. Three categories of private consumption are used: food consumption, nonfood consumption, and services consumption. The estimated model indicates substitution effects of government consumption spending on budget shares of private nonfood consumption and of government capital spending on budget share of private food consumption. However, the results do not indicate whether the negative effects of changes in the budget shares of the nonfood and the food consumption equates to reduce total private consumption. The concept of aggregate demand comprising consumption, investment, government spending (consumption spending and capital spending), export, and import are used to estimate their relationship by using the Vector Error Correction Mechanism. The study found no effect of government capital spending on either the private consumption or the growth of GDP while the government consumption spending has negative effect on the growth of GDP.

Keywords: Complementary effect, government capital spending, government consumption spending, private consumption on food, nonfood, and services, substitution effect, vector error correction mechanism.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2180

Authors: Ramya Dorai, M. Rajaram

Abstract:

A Mobile Adhoc Network (MANET) is a collection of mobile nodes that communicate with each other with wireless links and without pre-existing communication infrastructure. Routing is an important issue which impacts network performance. As MANETs lack central administration and prior organization, their security concerns are different from those of conventional networks. Wireless links make MANETs susceptible to attacks. This study proposes a new trust mechanism to mitigate wormhole attack in MANETs. Different optimization techniques find available optimal path from source to destination. This study extends trust and reputation to an improved link quality and channel utilization based Adhoc Ondemand Multipath Distance Vector (AOMDV). Differential Evolution (DE) is used for optimization.

Keywords: Mobile Adhoc Network (MANET), Adhoc Ondemand Multi-Path Distance Vector (AOMDV), Trust and Reputation, Differential Evolution (DE), Link Quality, Channel Utilization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1640

Authors: Magdi M. E. Zumrawi, Mohamed Awad

Abstract:

Determination of Resilient Modulus (M_R) is quite important for characterizing materials in pavement design and evaluation. The main focus of this study is to develop a correlation that predict the resilient modulus of subgrade soils from simple and easy measured soil index properties. To achieve this objective, three subgrade soils representing typical Khartoum soils were selected and tested in the laboratory for measuring resilient modulus. Other basic laboratory tests were conducted on the soils to determine their physical properties. Several soil samples were prepared and compacted at different moisture contents and dry densities and then tested using resilient modulus testing machine. Based on experimental results, linear relationship of M_R with the consistency factor ‘F_c’ which is a combination of dry density, void ratio and consistency index had been developed. The results revealed that very good linear relationship found between the M_R and the consistency factor with a coefficient of linearity (R²) more than 0.9. The consistency factor could be used for the prediction of the M_R of compacted subgrade soils with precise and reliable results.

Keywords: Consistency factor, resilient modulus, subgrade soil, properties.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1872

Authors: Mokhtar Ghobadi , Mohammad-Eghbal Ghobadi, Danial Kahrizi, Alireza Zebarjadi, Mahdi Geravandi

Abstract:

Post-anthesis drought stress is the most important problem affecting wheat production in dryland fields, specially in Mediterranean regions. The main objective of this research was to evaluate drought tolerance indices in dryland wheat genotypes under post-anthesis drought stress. The research was including two different experiments. In each experiment, twenty dryland bread wheat genotypes were sown in a randomized complete blocks design (RCBD) with three replications. One of experiments belonged to rain-fed conditions (post-anthesis drought stress) and other experiment was under non-stress conditions (with supplemental irrigation). Different drought tolerance indices include Stress Tolerance (Tol), Mean Productivity (MP), Geometric Mean Productivity (GMP), Stress Susceptibility Index (SSI), Stress Tolerance Index (STI), Harmonic Mean (HAM), Yield Index (YI) and Yield Stability Index (YSI) were evaluate based on grain yield under rain-fed (Ys) and supplemental irrigation (Yp) environments. G10 and G12 were the most tolerant genotypes based on TOL and SSI. But, based on MP, GMP, STI, HAM and YI indices, G1 and G2 were selected. STI, GMP and MP indices had high correlation with grain yield under rain-fed and supplementary irrigation conditions and were recognized as appropriate indices to identify genotypes with high grain yield and low sensitivity to drought stress environments.

Keywords: Dryland wheat, Supplemental irrigation, Tolerance indices

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2035

Authors: R. Gunabalan, V. Subbiah

Abstract:

This paper describes the speed sensorless vector control method of the parallel connected induction motor drive fed by a single inverter. Speed and rotor fluxes of the induction motor are estimated by natural observer with load torque adaptation and adaptive rotor flux observer. The performance parameters speed and rotor fluxes are estimated from the measured terminal voltages and currents. Fourth order induction motor model is used and speed is considered as a parameter. The performance of the natural observer is similar to the conventional observer. The speed of an induction motor is estimated by MATLAB simulation under different speed and load conditions. Estimated values along with other measured states are used for closed loop control. The simulation results show that the natural observer is also effective for parallel connected induction motor drive.

Keywords: natural observer, adaptive observer, sensorless control

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2512

Authors: Kasra Majbouri Yazdi, Adel Majbouri Yazdi, Saeid Khodayi, Jingyu Hou, Wanlei Zhou, Saeed Saedy

Abstract:

Fake news and false information are big challenges of all types of media, especially social media. There is a lot of false information, fake likes, views and duplicated accounts as big social networks such as Facebook and Twitter admitted. Most information appearing on social media is doubtful and in some cases misleading. They need to be detected as soon as possible to avoid a negative impact on society. The dimensions of the fake news datasets are growing rapidly, so to obtain a better result of detecting false information with less computation time and complexity, the dimensions need to be reduced. One of the best techniques of reducing data size is using feature selection method. The aim of this technique is to choose a feature subset from the original set to improve the classification performance. In this paper, a feature selection method is proposed with the integration of K-means clustering and Support Vector Machine (SVM) approaches which work in four steps. First, the similarities between all features are calculated. Then, features are divided into several clusters. Next, the final feature set is selected from all clusters, and finally, fake news is classified based on the final feature subset using the SVM method. The proposed method was evaluated by comparing its performance with other state-of-the-art methods on several specific benchmark datasets and the outcome showed a better classification of false information for our work. The detection performance was improved in two aspects. On the one hand, the detection runtime process decreased, and on the other hand, the classification accuracy increased because of the elimination of redundant features and the reduction of datasets dimensions.

Keywords: Fake news detection, feature selection, support vector machine, K-means clustering, machine learning, social media.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4468

Authors: Shaoying Guo, Yanyun Xu, Meng Zhang, Weiqing Huang

Abstract:

The wireless communication network is developing rapidly, thus the wireless security becomes more and more important. Specific emitter identification (SEI) is an vital part of wireless communication security as a technique to identify the unique transmitters. In this paper, a SEI method based on multiscale dispersion entropy (MDE) and refined composite multiscale dispersion entropy (RCMDE) is proposed. The algorithms of MDE and RCMDE are used to extract features for identification of five wireless devices and cross-validation support vector machine (CV-SVM) is used as the classifier. The experimental results show that the total identification accuracy is 99.3%, even at low signal-to-noise ratio(SNR) of 5dB, which proves that MDE and RCMDE can describe the communication signal series well. In addition, compared with other methods, the proposed method is effective and provides better accuracy and stability for SEI.

Keywords: Cross-validation support vector machine, refined composite multiscale dispersion entropy, specific emitter identification, transient signal, wireless communication device.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 834

Authors: R. J. Kuo, W. C. Cheng, W. C. Lien, T. J. Yang

Abstract:

Taiwan is a hyper endemic area for the Hepatitis B virus (HBV). The estimated total number of HBsAg carriers in the general population who are more than 20 years old is more than 3 million. Therefore, a case record review is conducted from January 2003 to June 2007 for all patients with a diagnosis of acute hepatitis who were admitted to the Emergency Department (ED) of a well-known teaching hospital. The cost for the use of medical resources is defined as the total medical fee. In this study, principal component analysis (PCA) is firstly employed to reduce the number of dimensions. Support vector regression (SVR) and artificial neural network (ANN) are then used to develop the forecasting model. A total of 117 patients meet the inclusion criteria. 61% patients involved in this study are hepatitis B related. The computational result shows that the proposed PCA-SVR model has superior performance than other compared algorithms. In conclusion, the Child-Pugh score and echogram can both be used to predict the cost of medical resources for patients with acute hepatitis in the ED.

Keywords: Acute hepatitis, Medical resource cost, Artificial neural network, Support vector regression.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1906

Authors: Amir Hajian, Sepehr Damavandinejadmonfared

Abstract:

In this paper the issue of dimensionality reduction is investigated in finger vein recognition systems using kernel Principal Component Analysis (KPCA). One aspect of KPCA is to find the most appropriate kernel function on finger vein recognition as there are several kernel functions which can be used within PCA-based algorithms. In this paper, however, another side of PCA-based algorithms -particularly KPCA- is investigated. The aspect of dimension of feature vector in PCA-based algorithms is of importance especially when it comes to the real-world applications and usage of such algorithms. It means that a fixed dimension of feature vector has to be set to reduce the dimension of the input and output data and extract the features from them. Then a classifier is performed to classify the data and make the final decision. We analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in this paper and investigate the optimal feature extraction dimension in finger vein recognition using KPCA.

Keywords: Biometrics, finger vein recognition, Principal Component Analysis (PCA), Kernel Principal Component Analysis (KPCA).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1945

Authors: C. A. Cortes-Quiroz, A. Azarbadegan, E. Moeendarbary

Abstract:

A new design of a planar passive T-micromixer with fin-shaped baffles in the mixing channel is presented. The mixing efficiency and the level of pressure loss in the channel have been investigated by numerical simulations in the range of Reynolds number (Re) 1 to 50. A Mixing index (Mi) has been defined to quantify the mixing efficiency, which results over 85% at both ends of the Re range, what demonstrates the micromixer can enhance mixing using the mechanisms of diffusion (lower Re) and convection (higher Re). Three geometric dimensions: radius of baffle, baffles pitch and height of the channel define the design parameters, and the mixing index and pressure loss are the performance parameters used to optimize the micromixer geometry with a multi-criteria optimization method. The Pareto front of designs with the optimum trade-offs, maximum mixing index with minimum pressure loss, is obtained. Experiments for qualitative and quantitative validation have been implemented.

Keywords: Computational fluids dynamics, fin-shaped baffle, mixing strategies, multi-objective optimization, passive micromixer.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1962

Authors: Dongfang Qiu, Yilin Lu

Abstract:

The measurement of enterprise-university-research cooperative efficiency has important meanings in improving the cooperative efficiency, strengthening the effective integration of regional resource, enhancing the ability of regional innovation and promoting the development of regional economy. The paper constructs the DEA method and DEA-Malmquist productivity index method to research the cooperation efficiency of Hubei by making comparisons with other provinces in China. The study found out the index of technology efficiency is 0.52 and the enterprise-universityresearch cooperative efficiency is Non-DEA efficient. To realize the DEA efficiency of Hubei province, the amount of 1652.596 R&D employees and 638.368 R&D employees’ full time equivalence should be reduced or 137.89 billion yuan of new products’ sales income be increased. Finally, it puts forward policy recommendations on existing problems to strengthen the standings of the cooperation, realize the effective application of the research results, and improve the level of management of enterprise-university-research cooperation efficiency.

Keywords: Cooperation Ability, DEA Method, Enterprise-university-research Cooperation, Malmquist Efficiency Index.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1672

Authors: Mustafa M. Donma, Orkide Donma

Abstract:

A growing list of cancers might be influenced by obesity. Obesity is associated with an increased risk for the occurrence and development of some cancers. Inflammation can lead to cancer. It is one of the characteristic features of cancer and plays a critical role in cancer development. C-reactive protein (CRP) is under evaluation related to the new and simple prognostic factors in patients with metastatic renal cell cancer. Obesity can predict and promote systemic inflammation in healthy adults. BMI is correlated with hs-CRP. In this study, SII index and CRP values were evaluated in children with normal BMI and those within the range of different obesity grades to detect the tendency towards cancer in pediatric obesity. A total of one hundred and ninety-four children; thirty-five children with normal BMI, twenty overweight (OW), forty-seven obese (OB) and ninety-two morbid obese (MO) participated in the study. Age- and sex-matched groups were constituted using BMI-for age percentiles. Informed consent was obtained. Ethical Committee approval was taken. Weight, height, waist circumference (C), hip C, head C and neck C of the children were measured. The complete blood count test was performed. C-reactive protein analysis was performed. Statistical analyses were performed using SPSS. The degree for statistical significance was p≤0.05. SII index values were progressively increasing starting from normal weight (NW) to MO children. There is a statistically significant difference between NW and OB as well as MO children. No significant difference was observed between NW and OW children, however, a correlation was observed between NW and OW children. MO constitutes the only group, which exhibited a statistically significant correlation between SII index and CRP. Obesity-related bladder, kidney, cervical, liver, colorectal, endometrial cancers are still being investigated. Obesity, characterized as a chronic low-grade inflammation, is a crucial risk factor for colon cancer. Elevated childhood BMI values may be indicative of processes leading to cancer, initiated early in life. Prevention of childhood adiposity may decrease the cancer incidence in adults. To authors’ best knowledge, this study is the first to introduce SII index values during obesity of varying degrees of severity. It is suggested that this index seems to affect all stages of obesity with an increasing tendency and may point out the concomitant status of obesity and cancer starting from very early periods of life.

Keywords: Children, c- reactive protein, systemic immune-inflammation index, obesity.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 828

Authors: Orkide Donma, Mustafa M. Donma, Muhammet Demirkol, Murat Aydin, Tuba Gokkus, Burcin Nalbantoglu, Aysin Nalbantoglu, Birol Topcu

Abstract:

Obesity in childhood establishes a ground for adulthood obesity. Especially morbid obesity is an important problem for the children because of the associated diseases such as diabetes mellitus, cancer and cardiovascular diseases. In this study, body mass index (BMI), body fat ratios, anthropometric measurements and ratios were evaluated together with different laboratory indices upon evaluation of obesity in morbidly obese (MO) children. Children with nutritional problems participated in the study. Written informed consent was obtained from the parents. Study protocol was approved by the Ethics Committee. Sixty-two MO girls aged 129.5±35.8 months and 75 MO boys aged 120.1±26.6 months were included into the scope of the study. WHO-BMI percentiles for age-and-sex were used to assess the children with those higher than 99^th as morbid obesity. Anthropometric measurements of the children were recorded after their physical examination. Bio-electrical impedance analysis was performed to measure fat distribution. Anthropometric ratios, body fat ratios, Index-I and Index-II as well as insulin sensitivity indices (ISIs) were calculated. Girls as well as boys were binary grouped according to homeostasis model assessment-insulin resistance (HOMA-IR) index of <2.5 and >2.5, fasting glucose to insulin ratio (FGIR) of <6 and >6 and quantitative insulin sensitivity check index (QUICKI) of <0.33 and >0.33 as the frequently used cut-off points. They were evaluated based upon their BMIs, arms, legs, trunk, whole body fat percentages, body fat ratios such as fat mass index (FMI), trunk-to-appendicular fat ratio (TAFR), whole body fat ratio (WBFR), anthropometric measures and ratios [waist-to-hip, head-to-neck, thigh-to-arm, thigh-to-ankle, height/2-to-waist, height/2-to-hip circumference (C)]. SPSS/PASW 18 program was used for statistical analyses. p≤0.05 was accepted as statistically significance level. All of the fat percentages showed differences between below and above the specified cut-off points in girls when evaluated with HOMA-IR and QUICKI. Differences were observed only in arms fat percent for HOMA-IR and legs fat percent for QUICKI in boys (p≤ 0.05). FGIR was unable to detect any differences for the fat percentages of boys. Head-to-neck C was the only anthropometric ratio recommended to be used for all ISIs (p≤0.001 for both girls and boys in HOMA-IR, p≤0.001 for girls and p≤0.05 for boys in FGIR and QUICKI). Indices which are recommended for use in both genders were Index-I, Index-II, HOMA/BMI and log HOMA (p≤0.001). FMI was also a valuable index when evaluated with HOMA-IR and QUICKI (p≤0.001). The important point was the detection of the severe significance for HOMA/BMI and log HOMA while they were evaluated also with the other indices, FGIR and QUICKI (p≤0.001). These parameters along with Index-I were unique at this level of significance for all children. In conclusion, well-accepted ratios or indices may not be valid for the evaluation of both genders. This study has emphasized the limiting properties for boys. This is particularly important for the selection process of some ratios and/or indices during the clinical studies. Gender difference should be taken into consideration for the evaluation of the ratios or indices, which will be recommended to be used particularly within the scope of obesity studies.

Keywords: Anthropometry, childhood obesity, gender, insulin sensitivity index.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1446

Authors: Monica Dudian , Raluca Andreea Popa

Abstract:

This article analyses the relationship between sovereign credit risk rating and gross domestic product for Central and Eastern European Countries for the period 1996 – 2010. In order to study the metioned relationship, we have used a numerical transformation of the risk qualification, thus: we marked 0 the lowest risk; then, we went on ascending, with a pace of 5, up to the score of 355 corresponding to the maximum risk. The used method of analysis is that of econometric modelling with EViews 7.0. programme. This software allows the analysis of data into a pannel type system, involving a mix of periods of time and series of data for different entities. The main conclusion of the work is the one confirming the negative relationship between the sovereign credit risk and the gross domestic product for the Central European and Eastern countries during the reviewed period.

Keywords: credit rating agencies, economic growth, gross domestic product, sovereign credit risk rating.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2418

Authors: Rameswar Debnath, Haruhisa Takahashi

Abstract:

An evolutionary method whose selection and recombination operations are based on generalization error-bounds of support vector machine (SVM) can select a subset of potentially informative genes for SVM classifier very efficiently [7]. In this paper, we will use the derivative of error-bound (first-order criteria) to select and recombine gene features in the evolutionary process, and compare the performance of the derivative of error-bound with the error-bound itself (zero-order) in the evolutionary process. We also investigate several error-bounds and their derivatives to compare the performance, and find the best criteria for gene selection and classification. We use 7 cancer-related human gene expression datasets to evaluate the performance of the zero-order and first-order criteria of error-bounds. Though both criteria have the same strategy in theoretically, experimental results demonstrate the best criterion for microarray gene expression data.

Keywords: support vector machine, generalization error-bound, feature selection, evolutionary algorithm, microarray data

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1521

Authors: N. Talisa, K. Rungsarid, P. Chakrit

Abstract:

The objectives of the research are to study the existing agricultural patterns, and to evaluate the sustainability of agricultural on economic, social and environmental aspects. The samplings were the representatives of the agriculturist group from Ban Paew district, Samut Sakorn province by purposive sampling method of 30 households. The tools being used were interview forms together with the Rapid Rural Appraisal (RRA) and the Participation Rural Appraisal (PRA). The information collected was analyzed with the principle of Content Analysis andusing Descriptive Statistics. After that all the information gotten was analyze the sustainability on the household level and village level. The research result can be concluded as follows: The agricultural Patterns: For most of the cultivation main crop was fruit trees planted and the supplement crop was around the patch or added other plants in the trenches. There were trenches for the cultivating water. The product distribution was by selling (97.5%) and the selling to middle man was the highest number (62.5%). Evaluating the sustainability of the agricultural by the indicators which were appropriate to the area: For the agricultural sustainability on the household level it was found that only one household had sustainable, others household had conditioned sustainable. For on the village level it was found that the sustainability on the issue of agricultural knowledge training had the lowest level (Sustainability index = 31.67%). Secondary was the acknowledging about soil information (Sustainability index = 35.0), and the household labors on agriculture, net return over cash cost (Sustainability index = 55.0%) respectively. Performance percentage is 48.81 %. It was brought to the conclusion that this area did not have the agricultural sustainability.

Keywords: Sustainability of agricultural, sustainability indicators, sustainability index.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1634

Authors: Leila Ramezani, Mohammad Saeid Mossadegh

Abstract:

Different uses of land by humans alter the physico chemical characteristics of the soil and affect the soil microhabitat. The objective of this study was to evaluate the influence of tillage in three different human land uses on microarthropods biodiversity in Khuzestan province, southwest of Iran. Three microhabitats including a permanent grassland with old Date-Palms around and no till system, and two wheat fields, one with conservative agricultural practices and low till system and the other with conventional agricultural practices (deep tillage), were compared for the biodiversity of the two main groups of soil microarthropods (Oribatida and Collembola). Soil samples were collected from the top to a depth of 15 cm bimonthly during a period of two years. Significant differences in the biodiversity index of microarthropods were observed between the different tillage systems (F = 36.748, P =0.000). Indeed, analysis of species diversity showed that the diversity index at the conservative field with low till (2.58 ± 0.01) was higher (p < 0.05) than the conventional tilled field (2.45 ± 0.08) and the diversity of natural grassland was the highest (2.79 ± 0.19, p < 0.05). Indeed, the index of biodiversity and population abundance differed significantly in different seasons (p < 0.00).

Keywords: Biodiversity, collembola, microarthropods, oribatida.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 958

Authors: C. S. Saini

Abstract:

The composite flour blend consisting of corn, pearl millet, black gram and wheat bran in the ratio of 80:5:10:5 was taken to prepare the extruded product and their effect on physical properties of extrudate was studied. The extrusion process was conducted in laboratory by using twin screw extruder. The physical characteristics evaluated include lateral expansion, bulk density, water absorption index, water solubility index, and rehydration ratio and moisture retention. The Central Composite Rotatable Design (CCRD) was used to decide the level of processing variables i.e. feed moisture content (%), screw speed (rpm), and barrel temperature (oC) for the experiment. The data obtained after extrusion process were analyzed by using response surface methodology. A second order polynomial model for the dependent variables was established to fit the experimental data. The numerical optimization studies resulted in 127°C of barrel temperature, 246 rpm of screw speed, and 14.5% of feed moisture as optimum variables to produce acceptable extruded product. The responses predicted by the software for the optimum process condition resulted in lateral expansion 126%, bulk density 0.28 g/cm3, water absorption index 4.10 g/g, water solubility index 39.90%, rehydration ratio 544% and moisture retention 11.90% with 75% desirability.

Keywords: Black gram, corn flour, extrusion, physical characteristics.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3290