Search results for: body identification.

Authors: Rumena D. Stancheva, Ilona I. Iatcheva

Abstract:

In working mode some unexpected changes could be arise in inner structure of electromagnetic device. They influence modification in electromagnetic field propagation map. The field values at an observed boundary are also changed. The development of the process has to be watched because the arising structural changes would provoke the device to be gone out later. The probabilistic assessment of the state is possible to be made. The numerical assessment points if the resulting changes have only accidental character or they are due to the essential inner structural disturbances. The presented application example is referring to the 200MW turbine-generator. A part of the stator core end teeth zone is simulated broken. Quasi three-dimensional electromagnetic and temperature field are solved applying FEM. The stator core state diagnosis is proposed to be solved as an identification problem on the basis of a statistical criterion.

Keywords: Identification, structural disturbance, statistical criterion.

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Authors: Ardhendu Behera, Denis Lalanne, Rolf Ingold

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This paper proposes a method, combining color and layout features, for identifying documents captured from low-resolution handheld devices. On one hand, the document image color density surface is estimated and represented with an equivalent ellipse and on the other hand, the document shallow layout structure is computed and hierarchically represented. Our identification method first uses the color information in the documents in order to focus the search space on documents having a similar color distribution, and finally selects the document having the most similar layout structure in the remaining of the search space.

Keywords: Document color modeling, document visualsignature, kernel density estimation, document identification.

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Authors: Yu-Ting Tsai, Yu-da Lee, Jin H. Huang

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The nonlinear damping behavior is usually ignored in the design of a miniature moving-coil loudspeaker. But when the loudspeaker operated in air, the damping parameter varies with the voice-coil displacement corresponding due to viscous air flow. The present paper presents an identification model as inverse problem to identify the nonlinear damping parameter in the lumped parameter model for the loudspeaker. Theoretical results for the nonlinear damping are verified by using laser displacement measurement scanner. These results indicate that the damping parameter has the greatly different nonlinearity between in air and vacuum. It is believed that the results of the present work can be applied in diagnosis and sound quality improvement of a miniature loudspeaker.

Keywords: Miniature loudspeaker, non-linear damping, system identification, Lumped parameter model.

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Authors: Cheng-Hsien Chang, Jyi-Tsong Lin, Po-Hsieh Lin, Hung-Pei Hsu, Chan-Hsiang Chang, Ming-Tsung Shih, Shih-Chuan Tseng, Min-Yan Lin

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In this paper, we have proposed a novel FinFET with extended body under the poly gate, which is called EB-FinFET, and its characteristic is demonstrated by using three-dimensional (3-D) numerical simulation. We have analyzed and compared it with conventional FinFET. The extended body height dependence on the drain induced barrier lowering (DIBL) and subthreshold swing (S.S) have been also investigated. According to the 3-D numerical simulation, the proposed structure has a firm structure, an acceptable short channel effect (SCE), a reduced series resistance, an increased on state drain current (I on) and a large normalized I DS. Furthermore, the structure can also improve corner effect and reduce self-heating effect due to the extended body. Our results show that the EBFinFET is excellent for nanoscale device.

Keywords: SOI, FinFET, tri-gate, self-heating effect.

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Authors: Nemat Abazari, Ilgin Sager

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In this paper smooth trajectories are computed in the Lie group SO(2, 1) as a motion planning problem by assigning a Frenet frame to the rigid body system to optimize the cost function of the elastic energy which is spent to track a timelike curve in Minkowski space. A method is proposed to solve a motion planning problem that minimizes the integral of the Lorentz inner product of Darboux vector of a timelike curve. This method uses the coordinate free Maximum Principle of Optimal control and results in the theory of integrable Hamiltonian systems. The presence of several conversed quantities inherent in these Hamiltonian systems aids in the explicit computation of the rigid body motions.

Keywords: Optimal control, Hamiltonian vector field, Darboux vector, maximum principle, lie group, rigid body motion, Lorentz metric.

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Authors: M. J. Cunha

Abstract:

The aim of this paper is to understand how peers can influence adolescent girls- dieting behaviour and their body image. Departing from imitation and social learning theories, we study whether adolescent girls tend to model their peer group dieting behaviours, thus influencing their body image construction. Our study was conducted through an enquiry applied to a cluster sample of 466 adolescent high school girls in Lisbon city public schools. Our main findings point to an association between girls- and peers- dieting behaviours, thus reinforcing the modelling hypothesis.

Keywords: Modelling, Diet, Body image, Adolescent girls, Peer group.

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Authors: Javad Khazaei, Rick S. Blum

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Distributed control is an efficient and flexible approach for coordination of multi-agent systems. One of the main challenges in designing a distributed controller is identifying the governing dynamics of the dynamical systems. Data-driven system identification is currently undergoing a revolution. With the availability of high-fidelity measurements and historical data, model-free identification of dynamical systems can facilitate the control design without tedious modeling of high-dimensional and/or nonlinear systems. This paper develops a distributed control design using consensus theory for linear and nonlinear dynamical systems using sparse identification of system dynamics. Compared with existing consensus designs that heavily rely on knowing the detailed system dynamics, the proposed model-free design can accurately capture the dynamics of the system with available measurements and input data and provide guaranteed performance in consensus and tracking problems. Heterogeneous damped oscillators are chosen as examples of dynamical system for validation purposes.

Keywords: Consensus tracking, distributed control, model-free control, sparse identification of dynamical systems.

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Authors: Yu-Xiang Zhao, Chien-Hsing Chou, Mu-Chun Su, Yi-Zeng Hsieh

Abstract:

The purpose of this study is to design a portable virtual piano. By utilizing optical fiber gloves and the virtual piano software designed by this study, the user can play the piano anywhere at any time. This virtual piano consists of three major parts: finger tapping identification, hand movement and positioning identification, and MIDI software sound effect simulation. To play the virtual piano, the user wears optical fiber gloves and simulates piano key tapping motions. The finger bending information detected by the optical fiber gloves can tell when piano key tapping motions are made. Images captured by a video camera are analyzed, hand locations and moving directions are positioned, and the corresponding scales are found. The system integrates finger tapping identification with information about hand placement in relation to corresponding piano key positions, and generates MIDI piano sound effects based on this data. This experiment shows that the proposed method achieves an accuracy rate of 95% for determining when a piano key is tapped.

Keywords: virtual piano, portable, identification, optical fibergloves.

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Authors: A. Bumbová, M. Čáslavský, F. Božek, J. Dvořák, E. Bakoš

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The paper presents the case study of hazard identification and sensitivity of potential resource of emergency water supply as part of the application of methodology classifying the resources of drinking water for emergency supply of population. The case study has been carried out on a selected resource of emergency water supply in one region of the Czech Republic. The hazard identification and sensitivity of potential resource of emergency water supply is based on a unique procedure and developed general registers of selected types of hazards and sensitivities. The registers have been developed with the help of the “Fault Tree Analysis” method in combination with the “What if method”. The identified hazards for the assessed resource include hailstorms and torrential rains, drought, soil erosion, accidents of farm machinery, and agricultural production. The developed registers of hazards and vulnerabilities and a semi-quantitative assessment of hazards for individual parts of hydrological structure and technological elements of presented drilled wells are the basis for a semi-quantitative risk assessment of potential resource of emergency supply of population and the subsequent classification of such resource within the system of crisis planning.

Keywords: Hazard identification, register of hazards, sensitivity identification, register of sensitivity, emergency water supply, state of crisis, resource of emergency water supply, ground water.

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Authors: Mohd Faridz Ahmad, Amirul Hakim Hasbullah

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Electrical Muscle Stimulation (EMS) has been introduced and globally gained increasing attention on its usefulness. Continuous application of EMS may lead to the increment of muscle mass and indirectly will increase the strength. This study can be used as an alternative to help people especially those living a sedentary lifestyle to improve their muscle activity without having to go through a heavy workout session. Therefore, this study intended to investigate the effectiveness of EMS training program in 5 weeks interventions towards male body composition. It was a quasiexperimental design, held at the Impulse Studio Bangsar, which examined the effects of EMS training towards skeletal muscle mass among the subjects. Fifteen subjects (n = 15) were selected to assist in this study. The demographic data showed that, the average age of the subjects was 43.07 years old ± 9.90, height (173.4 cm ± 9.09) and weight was (85.79 kg ± 18.07). Results showed that there was a significant difference on the skeletal muscle mass (p = 0.01 < 0.05), upper body (p = 0.01 < 0.05) and lower body (p = 0.00 < 0.05). Therefore, the null hypothesis has been rejected in this study. As a conclusion, the application of EMS towards body composition can increase the muscle size and strength. This method has been proven to be able to improve athlete strength and thus, may be implemented in the sports science area of knowledge.

Keywords: Body composition, EMS, skeletal muscle mass, strength.

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Authors: K. Elleuch, A. Chaari

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This paper deals with modeling and parameter identification of nonlinear systems described by Hammerstein model having Piecewise nonlinear characteristics such as Dead-zone nonlinearity characteristic. The simultaneous use of both an easy decomposition technique and the triangular basis functions leads to a particular form of Hammerstein model. The approximation by using Triangular basis functions for the description of the static nonlinear block conducts to a linear regressor model, so that least squares techniques can be used for the parameter estimation. Singular Values Decomposition (SVD) technique has been applied to separate the coupled parameters. The proposed approach has been efficiently tested on academic examples of simulation.

Keywords: Identification, Hammerstein model, Piecewisenonlinear characteristic, Dead-zone nonlinearity, Triangular basisfunctions, Singular Values Decomposition

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Authors: Hsuan-Chia Yang, Yan-Jhih Haung, Yu-Chuan Li

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Researchers of drug-drug interaction alert systems have often suggested that there were high overridden rate for alerts and also too false alerts. However, research about decreasing false alerts is scant. Therefore, the aim of this article attempts to proactive identification of false alert for drug-drug interaction and provide solution to decrease false alerts. This research involved retrospective analysis prescribing database and calculated false alert rate by using MYSQL and JAVA. Results of this study showed 17% of false alerts and the false alert rate in the hospitals (37%) was more than in the clinics. To conclude, this study described the importance that drug-drug interaction alert system should not only detect drug name but also detect frequency or route, as well as in providing solution to decrease false alerts.

Keywords: drug-drug interaction, proactive identification, false alert

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Authors: T. Atan, T. Ayyıldız, P. Akyol

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The purpose of this study was to examine and compare physical fitness values of students engaged in different team sport branches Totally 60 female, and 60 male athletes, that 20 athletes in each branch which are volleyball, basketball and football participated the study as a volunteer. The mean ages of female and male athletes were 21.20 ±1.87 and 21.61 ± 1.61 respectively. Age, height, body weight, body mass index, flexibility, body fat percentage, 30m sprint, maximum oxygen consumption capacity (MaxVO2) and drop jump values were measured. As a result of measurements, significant differences were found in height, weight, MaxVO2, shuttle run speed between different sports branches in female athletes. In male athletes, height, body weight, flexibility, 30m split speed and drop jump values were found significantly different between sports branches. As a conclusion and as a literature, it can be said that structure of body has to be appropriate with the engaged sports branch. Physical fitness values that required the sports branches can be expressed clearly by increasing the number of subjects.

Keywords: Volleyball, basketball, football, athletes, physical fitness.

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Authors: Omar B. Yaakob, Yasser M. Ahmed, Ahmad F. Said

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There is an essential need for obtaining the mathematical representation of fish body undulations, which can be used for designing and building new innovative types of marine propulsion systems with less environmental impact. This research work presents a case study to derive the mathematical model for fish body movement. Observation and capturing image methods were used in this study in order to obtain a mathematical representation of Clariasbatrachus fish (catfish). An experiment was conducted by using an aquarium with dimension 0.609 m x 0.304 m x 0.304 m, and a 0.5 m ruler was attached at the base of the aquarium. Progressive Scan Monochrome Camera was positioned at 1.8 m above the base of the aquarium to provide swimming sequences. Seven points were marked on the fish body using white marker to indicate the fish movement and measuring the amplitude of undulation. Images from video recordings (20 frames/s) were analyzed frame by frame using local coordinate system, with time interval 0.05 s. The amplitudes of undulations were obtained for image analysis from each point that has been marked on fish body. A graph of amplitude of undulations versus time was plotted by using computer to derive a mathematical fit. The function for the graph is polynomial with nine orders.

Keywords: Fish locomotion, body undulation, steady and unsteady swimming modes.

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Authors: Gelareh Mohammadi, Parisa Shoushtari, Behnam Molaee Ardekani, Mohammad B. Shamsollahi

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A direct connection between ElectroEncephaloGram (EEG) and the genetic information of individuals has been investigated by neurophysiologists and psychiatrists since 1960-s; and it opens a new research area in the science. This paper focuses on the person identification based on feature extracted from the EEG which can show a direct connection between EEG and the genetic information of subjects. In this work the full EO EEG signal of healthy individuals are estimated by an autoregressive (AR) model and the AR parameters are extracted as features. Here for feature vector constitution, two methods have been proposed; in the first method the extracted parameters of each channel are used as a feature vector in the classification step which employs a competitive neural network and in the second method a combination of different channel parameters are used as a feature vector. Correct classification scores at the range of 80% to 100% reveal the potential of our approach for person classification/identification and are in agreement to the previous researches showing evidence that the EEG signal carries genetic information. The novelty of this work is in the combination of AR parameters and the network type (competitive network) that we have used. A comparison between the first and the second approach imply preference of the second one.

Keywords: Person Identification, Autoregressive Model, EEG, Neural Network

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Authors: Tomohiro Hachino, Kengo Nagatomo, Hitoshi Takata

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This paper deals with an on-line identification method of continuous-time Hammerstein systems by using the radial basis function (RBF) networks and immune algorithm (IA). An unknown nonlinear static part to be estimated is approximately represented by the RBF network. The IA is efficiently combined with the recursive least-squares (RLS) method. The objective function for the identification is regarded as the antigen. The candidates of the RBF parameters such as the centers and widths are coded into binary bit strings as the antibodies and searched by the IA. On the other hand, the candidates of both the weighting parameters of the RBF network and the system parameters of the linear dynamic part are updated by the RLS method. Simulation results are shown to illustrate the proposed method.

Keywords: Continuous-time System, Hammerstein System, OnlineIdentification, Immune Algorithm, RBF network.

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Authors: Fuad M. Alkoot

Abstract:

DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: Biometrics, identity verification, genetic data, k-nearest neighbor.

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Authors: K. Sekulová, M. Šimon

Abstract:

The article demonstrates on a case study how it is possible to identify MSD risk. It is based on a dissertation Risk identification model of occupational diseases formation in relation to the work activity that determines what risk can endanger workers who are exposed to the specific risk factors. It is evaluated based on statistical calculations. These risk factors are main cause of upperextremities musculoskeletal disorders.

Keywords: Case study, upper-extremity musculoskeletal disorders, ergonomics.

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Authors: Mohammed Boutalline, Imad Badi, Belaid Bouikhalene, Said Safi

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In this paper we describe the Levenvberg-Marquardt (LM) algorithm for identification and equalization of CDMA signals received by an antenna array in communication channels. The synthesis explains the digital separation and equalization of signals after propagation through multipath generating intersymbol interference (ISI). Exploiting discrete data transmitted and three diversities induced at the reception, the problem can be composed by the Block Component Decomposition (BCD) of a tensor of order 3 which is a new tensor decomposition generalizing the PARAFAC decomposition. We optimize the BCD decomposition by Levenvberg-Marquardt method gives encouraging results compared to classical alternating least squares algorithm (ALS). In the equalization part, we use the Minimum Mean Square Error (MMSE) to perform the presented method. The simulation results using the LM algorithm are important.

Keywords: Identification and equalization, communication channel, Levenvberg-Marquardt, tensor decomposition

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Authors: M. Chňapek, M. Tomka, R. Peroutková, Z. Gálová

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Processes of plant breeding, testing and licensing of new varieties, patent protection in seed production, relations in trade and protection of copyright are dependent on identification, differentiation and characterization of plant genotypes. Therefore, we focused our research on utilization of wheat storage proteins as genetic markers suitable not only for differentiation of individual genotypes, but also for identification and characterization of their considerable properties. We analyzed a collection of 102 genotypes of bread wheat (Triticum aestivum L.), 41 genotypes of spelt wheat (Triticum spelta L.), and 35 genotypes of durum wheat (Triticum durum Desf.), in this study. Our results show, that genotypes of bread wheat and durum wheat were homogenous and single line, but spelt wheat genotypes were heterogenous. We observed variability of HMW-GS composition according to environmental factors and level of breeding and predict technological quality on the basis of Glu-score calculation.

Keywords: Genotype identification, HMW-GS, wheat quality.

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Authors: Slimane Ouhmad, Abdellah Halimi

Abstract:

In this work, neural networks methods MLP type were applied to a database from an array of six sensors for the detection of three toxic gases. The choice of the number of hidden layers and the weight values are influential on the convergence of the learning algorithm. We proposed, in this article, a mathematical formula to determine the optimal number of hidden layers and good weight values based on the method of back propagation of errors. The results of this modeling have improved discrimination of these gases and optimized the computation time. The model presented here has proven to be an effective application for the fast identification of toxic gases.

Keywords: Back-propagation, Computing time, Fast identification, MLP neural network, Number of neurons in the hidden layer.

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Authors: Suman Senapati, Goutam Saha

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Real world Speaker Identification (SI) application differs from ideal or laboratory conditions causing perturbations that leads to a mismatch between the training and testing environment and degrade the performance drastically. Many strategies have been adopted to cope with acoustical degradation; wavelet based Bayesian marginal model is one of them. But Bayesian marginal models cannot model the inter-scale statistical dependencies of different wavelet scales. Simple nonlinear estimators for wavelet based denoising assume that the wavelet coefficients in different scales are independent in nature. However wavelet coefficients have significant inter-scale dependency. This paper enhances this inter-scale dependency property by a Circularly Symmetric Probability Density Function (CS-PDF) related to the family of Spherically Invariant Random Processes (SIRPs) in Log Gabor Wavelet (LGW) domain and corresponding joint shrinkage estimator is derived by Maximum a Posteriori (MAP) estimator. A framework is proposed based on these to denoise speech signal for automatic speaker identification problems. The robustness of the proposed framework is tested for Text Independent Speaker Identification application on 100 speakers of POLYCOST and 100 speakers of YOHO speech database in three different noise environments. Experimental results show that the proposed estimator yields a higher improvement in identification accuracy compared to other estimators on popular Gaussian Mixture Model (GMM) based speaker model and Mel-Frequency Cepstral Coefficient (MFCC) features.

Keywords: Speaker Identification, Log Gabor Wavelet, Bayesian Bivariate Estimator, Circularly Symmetric Probability Density Function, SIRP.

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Authors: Sumalee B., Sirinapa L., Jenjira T., Jr., Setasak S.

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The paper describes ergonomics problems trend of student at B5101 classroom building 2, Suranaree University of Technology. The objective to survey ergonomics problems and effect from use chairs for sitting in class room. The result from survey method 100 student they use lecture chair for sitting in classroom more than 2 hours/ day by RULA[1]. and Body discomfort survey[2]. The result from Body discomfort survey contribute fatigue problems at neck, lower back, upper back and right shoulder 2.93, 2.91, 2.33, 1.75 respectively and result from RULA contribute fatigue problems at neck, body and right upper arm 4.00, 3.75 and 3.00 respectively are consistent. After that the researcher provide improvement plan for design new chair support student fatigue reduction by prepare data of sample anthropometry and design ergonomics chair prototype 3 unit. Then sample 100 student trial to use new chair and evaluate again by RULA, Body discomfort and satisfaction. The result from trial new chair after improvement by RULA present fatigue reduction average of head and neck from 4.00 to 2.25 , body and trunk from 3.75 to 2.00 and arm force from 1.00 to 0.25 respectively. The result from trial new chair after improvement by Body discomfort present fatigue reduction average of lower back from 2.91 to 0.87, neck from 2.93 to 1.24, upper back 2.33 to 0.84 and right upper arm from 1.75 to 0.74. That statistical of RULA and Body discomfort survey present fatigue reduction after improvement significance with a confidence level of 95% (p-value 0.05). When analyzing the relationship of fatigue as part of the body by Chi – square test during RULA and Body discomfort that before and after improvements were consistent with the significant level of confidence 95% (p-value 0.05) . Moreover the students satisfaction result from trial with a new chair for 30 minutes [3]. 72 percent very satisfied of the folding of the secondary writing simple 66% the width of the writing plate, 64% the suitability of the writing plate, 62% of soft seat cushion and 61% easy to seat the chair.

Keywords: Ergonomics, Work station design, ErgonomicsChair, Student, Fatigue

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Authors: Gabriella Tjondro, Julita Dortua Laurentina Nainggolan

Abstract:

Introduction: There are several things affecting menstrual cycle, namely, nutritional status, diet, financial status of one’s household and exercises. The most commonly used parameter to calculate the fat in a human body is body mass index. Therefore, it is necessary to do research to prevent complications caused by menstrual disorder in the future. Design Study: This research is an observational analytical study with the cross-sectional-case control approach. Participants (n = 124; median age = 19.5 years ± SD 3.5) were classified into 2 groups: normal, NM (n = 62; BMI = 18-23 kg/m²) and obese, OB (n = 62; BMI = > 25 kg/m²). BMI was calculated from the equation; BMI = weight, kg/height, m². Results: There were 79.10% from obese group who experienced menstrual cycle disorders (n=53, 79.10%; p value 0.00; OR 5.25) and 20.90% from normal BMI group with menstrual cycle disorders. There were several factors in this research that also influence the menstrual cycle disorders such as stress (44.78%; p value 0.00; OR 1.85), sleep disorders (25.37%; p value 0.00; OR 1.01), physical activities (25.37%; p value 0.00; OR 1.24) and diet (10.45%; p value 0.00; OR 1.07). Conclusion: There is a significant relation between body mass index (obese) and menstrual cycle disorders. However, BMI is not the only factor that affects the menstrual cycle disorders. There are several factors that also can affect menstrual cycle disorders, in this study we use stress, sleep disorders, physical activities and diet, in which none of them are dominant.

Keywords: Menstrual disorders, menstrual cycle, obesity, body mass index, stress, sleep disorders, physical activities, diet.

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Authors: Michael Netzer, Michael Seger, Mahesh Visvanathan, Bernhard Pfeifer, Gerald H. Lushington, Christian Baumgartner

Abstract:

Lung cancer accounts for the most cancer related deaths for men as well as for women. The identification of cancer associated genes and the related pathways are essential to provide an important possibility in the prevention of many types of cancer. In this work two filter approaches, namely the information gain and the biomarker identifier (BMI) are used for the identification of different types of small-cell and non-small-cell lung cancer. A new method to determine the BMI thresholds is proposed to prioritize genes (i.e., primary, secondary and tertiary) using a k-means clustering approach. Sets of key genes were identified that can be found in several pathways. It turned out that the modified BMI is well suited for microarray data and therefore BMI is proposed as a powerful tool for the search for new and so far undiscovered genes related to cancer.

Keywords: lung cancer, micro arrays, data mining, feature selection.

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Authors: Megha Gupta, Nupur Prakash

Abstract:

Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

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Authors: C. Pislaru, A. Shebani

Abstract:

This paper uses the radial basis function neural network (RBFNN) for system identification of nonlinear systems. Five nonlinear systems are used to examine the activity of RBFNN in system modeling of nonlinear systems; the five nonlinear systems are dual tank system, single tank system, DC motor system, and two academic models. The feed forward method is considered in this work for modelling the non-linear dynamic models, where the KMeans clustering algorithm used in this paper to select the centers of radial basis function network, because it is reliable, offers fast convergence and can handle large data sets. The least mean square method is used to adjust the weights to the output layer, and Euclidean distance method used to measure the width of the Gaussian function.

Keywords: System identification, Nonlinear system, Neural networks, RBF neural network.

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Authors: Masamitsu Chikaraishi, Mutsuto Kawahara

Abstract:

This paper focuses on a technique for identifying the geological boundary of the ground strata in front of a tunnel excavation site using the first order adjoint method based on the optimal control theory. The geological boundary is defined as the boundary which is different layers of elastic modulus. At tunnel excavations, it is important to presume the ground situation ahead of the cutting face beforehand. Excavating into weak strata or fault fracture zones may cause extension of the construction work and human suffering. A theory for determining the geological boundary of the ground in a numerical manner is investigated, employing excavating blasts and its vibration waves as the observation references. According to the optimal control theory, the performance function described by the square sum of the residuals between computed and observed velocities is minimized. The boundary layer is determined by minimizing the performance function. The elastic analysis governed by the Navier equation is carried out, assuming the ground as an elastic body with linear viscous damping. To identify the boundary, the gradient of the performance function with respect to the geological boundary can be calculated using the adjoint equation. The weighed gradient method is effectively applied to the minimization algorithm. To solve the governing and adjoint equations, the Galerkin finite element method and the average acceleration method are employed for the spatial and temporal discretizations, respectively. Based on the method presented in this paper, the different boundary of three strata can be identified. For the numerical studies, the Suemune tunnel excavation site is employed. At first, the blasting force is identified in order to perform the accuracy improvement of analysis. We identify the geological boundary after the estimation of blasting force. With this identification procedure, the numerical analysis results which almost correspond with the observation data were provided.

Keywords: Parameter identification, finite element method, average acceleration method, first order adjoint equation method, weighted gradient method, geological boundary, navier equation, optimal control theory.

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Authors: V.Manikandan, N.Devarajan

Abstract:

The main objective of this work is to provide a fault detection and isolation based on Markov parameters for residual generation and a neural network for fault classification. The diagnostic approach is accomplished in two steps: In step 1, the system is identified using a series of input / output variables through an identification algorithm. In step 2, the fault is diagnosed comparing the Markov parameters of faulty and non faulty systems. The Artificial Neural Network is trained using predetermined faulty conditions serves to classify the unknown fault. In step 1, the identification is done by first formulating a Hankel matrix out of Input/ output variables and then decomposing the matrix via singular value decomposition technique. For identifying the system online sliding window approach is adopted wherein an open slit slides over a subset of 'n' input/output variables. The faults are introduced at arbitrary instances and the identification is carried out in online. Fault residues are extracted making a comparison of the first five Markov parameters of faulty and non faulty systems. The proposed diagnostic approach is illustrated on benchmark problems with encouraging results.

Keywords: Artificial neural network, Fault Diagnosis, Identification, Markov parameters.

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Authors: Fidel Lòpez Saca, Carlos Avilés-Cruz, Miguel Magos-Rivera, José Antonio Lara-Chávez

Abstract:

Automated object recognition and identification systems are widely used throughout the world, particularly in assembly lines, where they perform quality control and automatic part selection tasks. This article presents the design and implementation of an object recognition system in an assembly line. The proposed shapes-color recognition system is based on deep learning theory in a specially designed convolutional network architecture. The used methodology involve stages such as: image capturing, color filtering, location of object mass centers, horizontal and vertical object boundaries, and object clipping. Once the objects are cut out, they are sent to a convolutional neural network, which automatically identifies the type of figure. The identification system works in real-time. The implementation was done on a Raspberry Pi 3 system and on a Jetson-Nano device. The proposal is used in an assembly course of bachelor’s degree in industrial engineering. The results presented include studying the efficiency of the recognition and processing time.

Keywords: Deep-learning, image classification, image identification, industrial engineering.

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