Search results for: Riener muscle model
17092 Identification of Classes of Bilinear Time Series Models
Authors: Anthony Usoro
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In this paper, two classes of bilinear time series model are obtained under certain conditions from the general bilinear autoregressive moving average model. Bilinear Autoregressive (BAR) and Bilinear Moving Average (BMA) Models have been identified. From the general bilinear model, BAR and BMA models have been proved to exist for q = Q = 0, => j = 0, and p = P = 0, => i = 0 respectively. These models are found useful in modelling most of the economic and financial data.Keywords: autoregressive model, bilinear autoregressive model, bilinear moving average model, moving average model
Procedia PDF Downloads 40717091 A Nonlinear Visco-Hyper Elastic Constitutive Model for Modelling Behavior of Polyurea at Large Deformations
Authors: Shank Kulkarni, Alireza Tabarraei
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The fantastic properties of polyurea such as flexibility, durability, and chemical resistance have brought it a wide range of application in various industries. Effective prediction of the response of polyurea under different loading and environmental conditions necessitates the development of an accurate constitutive model. Similar to most polymers, the behavior of polyurea depends on both strain and strain rate. Therefore, the constitutive model should be able to capture both these effects on the response of polyurea. To achieve this objective, in this paper, a nonlinear hyper-viscoelastic constitutive model is developed by the superposition of a hyperelastic and a viscoelastic model. The proposed constitutive model can capture the behavior of polyurea under compressive loading conditions at various strain rates. Four parameter Ogden model and Mooney Rivlin model are used to modeling the hyperelastic behavior of polyurea. The viscoelastic behavior is modeled using both a three-parameter standard linear solid (SLS) model and a K-BKZ model. Comparison of the modeling results with experiments shows that Odgen and SLS model can more accurately predict the behavior of polyurea. The material parameters of the model are found by curve fitting of the proposed model to the uniaxial compression test data. The proposed model can closely reproduce the stress-strain behavior of polyurea for strain rates up to 6500 /s.Keywords: constitutive modelling, ogden model, polyurea, SLS model, uniaxial compression test
Procedia PDF Downloads 24317090 OmniDrive Model of a Holonomic Mobile Robot
Authors: Hussein Altartouri
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In this paper the kinematic and kinetic models of an omnidirectional holonomic mobile robot is presented. The kinematic and kinetic models form the OmniDrive model. Therefore, a mathematical model for the robot equipped with three- omnidirectional wheels is derived. This model which takes into consideration the kinematics and kinetics of the robot, is developed to state space representation. Relative analysis of the velocities and displacements is used for the kinematics of the robot. Lagrange’s approach is considered in this study for deriving the equation of motion. The drive train and the mechanical assembly only of the Festo Robotino® is considered in this model. Mainly the model is developed for motion control. Furthermore, the model can be used for simulation purposes in different virtual environments not only Robotino® View. Further use of the model is in the mechatronics research fields with the aim of teaching and learning the advanced control theories.Keywords: mobile robot, omni-direction wheel, mathematical model, holonomic mobile robot
Procedia PDF Downloads 60817089 Handwriting Velocity Modeling by Artificial Neural Networks
Authors: Mohamed Aymen Slim, Afef Abdelkrim, Mohamed Benrejeb
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The handwriting is a physical demonstration of a complex cognitive process learnt by man since his childhood. People with disabilities or suffering from various neurological diseases are facing so many difficulties resulting from problems located at the muscle stimuli (EMG) or signals from the brain (EEG) and which arise at the stage of writing. The handwriting velocity of the same writer or different writers varies according to different criteria: age, attitude, mood, writing surface, etc. Therefore, it is interesting to reconstruct an experimental basis records taking, as primary reference, the writing speed for different writers which would allow studying the global system during handwriting process. This paper deals with a new approach of the handwriting system modeling based on the velocity criterion through the concepts of artificial neural networks, precisely the Radial Basis Functions (RBF) neural networks. The obtained simulation results show a satisfactory agreement between responses of the developed neural model and the experimental data for various letters and forms then the efficiency of the proposed approaches.Keywords: Electro Myo Graphic (EMG) signals, experimental approach, handwriting process, Radial Basis Functions (RBF) neural networks, velocity modeling
Procedia PDF Downloads 44017088 A Constitutive Model for Time-Dependent Behavior of Clay
Authors: T. N. Mac, B. Shahbodaghkhan, N. Khalili
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A new elastic-viscoplastic (EVP) constitutive model is proposed for the analysis of time-dependent behavior of clay. The proposed model is based on the bounding surface plasticity and the concept of viscoplastic consistency framework to establish continuous transition from plasticity to rate dependent viscoplasticity. Unlike the overstress based models, this model will meet the consistency condition in formulating the constitutive equation for EVP model. The procedure of deriving the constitutive relationship is also presented. Simulation results and comparisons with experimental data are then presented to demonstrate the performance of the model.Keywords: bounding surface, consistency theory, constitutive model, viscosity
Procedia PDF Downloads 49117087 The Effect of Relaxing Exercises in Water on Endorphin Hormone for the Beginner in Swimming
Authors: Yasmin Hussein Embaby
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Introduction: Athletic Training has its essentials, rules, and methods that help individual in reaching the maximum possible athletic level during the exercised physical activity, therefore; it is important for those working in athletic field to recognize and understand what is going on inside our bodies. This will show the close relationship between physiology and athletic training as the science that explains the various changes that happen to respond to the practice of physical activities. Swimming is one of the water sports that play a major role in influencing the full compatibility of body parts and its systems during the practice of different swimming methods, which uses aqueous to move. It is the initial nucleus in swimming learning and through which the beginner gain a sense of security, safety and the ability to move in aqueous by learning basic skills. Research Methodology: The researcher used the experimental methodology by using pre and post measurement on two equal groups (experimental – control) because it is appropriate for the research. Conclusions: Through the results and information found by the researcher, and in light of the related studies, theoretical readings and the statistical treatments of data; the researcher reached the following conclusions: 1. Muscle relaxation exercises have a positive effect on performance level in crawl swimming and on endorphin hormone as it helps in increasing its normal rater in body, the improvement percentage for experimental group in the relaxation ability, level of endorphin hormone exceeds those of control group. 2. The validity of muscle relaxation exercises proposed for the application, which achieved its objectives, namely increasing the level of endorphin hormone in the body; where research results showed a statistically significant difference in the level of endorphin hormone in favor of the experimental sample.Keywords: beginners, endorphin hormone, relaxing exercises, swimming
Procedia PDF Downloads 21217086 A Comparative Study of Dengue Fever in Taiwan and Singapore Based on Open Data
Authors: Wei Wen Yang, Emily Chia Yu Su
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Dengue fever is a mosquito-borne tropical infectious disease caused by the dengue virus. After infection, symptoms usually start from three to fourteen days. Dengue virus may cause a high fever and at least two of the following symptoms, severe headache, severe eye pain, joint pains, muscle or bone pain, vomiting, feature skin rash, and mild bleeding manifestation. In addition, recovery will take at least two to seven days. Dengue fever has rapidly spread in tropical and subtropical areas in recent years. Several phenomena around the world such as global warming, urbanization, and international travel are the main reasons in boosting the spread of dengue. In Taiwan, epidemics occur annually, especially during summer and fall seasons. On the other side, Singapore government also has announced the amounts number of dengue cases spreading in Singapore. As the serious epidemic of dengue fever outbreaks in Taiwan and Singapore, countries around the Asia-Pacific region are becoming high risks of susceptible to the outbreaks and local hub of spreading the virus. To improve public safety and public health issues, firstly, we are going to use Microsoft Excel and SAS EG to do data preprocessing. Secondly, using support vector machines and decision trees builds predict model, and analyzes the infectious cases between Taiwan and Singapore. By comparing different factors causing vector mosquito from model classification and regression, we can find similar spreading patterns where the disease occurred most frequently. The result can provide sufficient information to predict the future dengue infection outbreaks and control the diffusion of dengue fever among countries.Keywords: dengue fever, Taiwan, Singapore, Aedes aegypti
Procedia PDF Downloads 23417085 A Crop Growth Subroutine for Watershed Resources Management (WRM) Model
Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu
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Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studiesKeywords: crop yield, roughness coefficient, PAR, WRM model
Procedia PDF Downloads 40917084 Dietary Vitamin D Intake and the Bladder Cancer Risk: A Pooled Analysis of Prospective Cohort Studies
Authors: Iris W. A. Boot, Anke Wesselius, Maurice P. Zeegers
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Diet may play an essential role in the aetiology of bladder cancer (BC). Vitamin D is involved in various biological functions which have the potential to prevent BC development. Besides, vitamin D also influences the uptake of calcium and phosphorus , thereby possibly indirectly influencing the risk of BC. The aim of the present study was to investigate the relation between vitamin D intake and BC risk. Individual dietary data were pooled from three cohort studies. Food item intake was converted to daily intakes of vitamin D, calcium and phosphorus. Pooled multivariate hazard ratios (HRs), with corresponding 95% confidence intervals (CIs) were obtained using Cox-regression models. Analyses were adjusted for gender, age and smoking status (Model 1), and additionally for the food groups fruit, vegetables and meat (Model 2). Dose–response relationships (Model 1) were examined using a nonparametric test for trend. In total, 2,871 cases and 522,364 non-cases were included in the analyses. The present study showed an overall increased BC risk for high dietary vitamin D intake (HR: 1.14, 95% CI: 1.03-1.26). A similar increase BC risk with high vitamin D intake was observed among women and for the non-muscle invasive BC subtype, (HR: 1.41, 95% CI: 1.15-1.72, HR: 1.13, 95% CI: 1.01-1.27, respectively). High calcium intake decreased the BC risk among women (HR: 0.81, 95% CI: 0.67-0.97). A combined inverse effect on BC risk was observed for low vitamin D intake and high calcium intake (HR: 0.67, 95% CI: 0.48-0.93), while a positive effect was observed for high vitamin D intake in combination with low, moderate and high phosphorus (HR: 1.31, 95% CI: 1.09-1.59, HR: 1.17, 95% CI: 1.01-1.36, HR: 1.16, 95% CI: 1.03-1.31, respectively). Combining all nutrients showed a decreased BC risk for low vitamin D intake, high calcium and moderate phosphor intake (HR: 0.37, 95% CI: 0.18-0.75), and an increased BC risk for moderate intake of all the nutrients (HR: 1.18, 95% CI: 1.02-1.38), for high vitamin D and low calcium and phosphor intake (HR: 1.28, 95% CI: 1.01-1.62), and for moderate vitamin D and calcium and high phosphorus intake (HR: 1.27, 95% CI: 1.01-1.59). No significant dose-response analyses were observed. The findings of this study show an increased BC risk for high dietary vitamin D intake and a decreased risk for high calcium intake. Besides, the study highlights the importance of examining the effect of a nutrient in combination with complementary nutrients for risk assessment. Future research should focus on nutrients in a wider context and in nutritional patterns.Keywords: bladder cancer, nutritional oncology, pooled cohort analysis, vitamin D
Procedia PDF Downloads 8417083 Numerical Modeling of the Depth-Averaged Flow over a Hill
Authors: Anna Avramenko, Heikki Haario
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This paper reports the development and application of a 2D depth-averaged model. The main goal of this contribution is to apply the depth averaged equations to a wind park model in which the treatment of the geometry, introduced on the mathematical model by the mass and momentum source terms. The depth-averaged model will be used in future to find the optimal position of wind turbines in the wind park. K-E and 2D LES turbulence models were consider in this article. 2D CFD simulations for one hill was done to check the depth-averaged model in practise.Keywords: depth-averaged equations, numerical modeling, CFD, wind park model
Procedia PDF Downloads 60317082 Factors Associated with Acute Kidney Injury in Multiple Trauma Patients with Rhabdomyolysis
Authors: Yong Hwang, Kang Yeol Suh, Yundeok Jang, Tae Hoon Kim
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Introduction: Rhabdomyolysis is a syndrome characterized by muscle necrosis and the release of intracellular muscle constituents into the circulation. Acute kidney injury is a potential complication of severe rhabdomyolysis and the prognosis is substantially worse if renal failure develops. We try to identify the factors that were predictive of AKI in severe trauma patients with rhabdomyolysis. Methods: This retrospective study was conducted at the emergency department of a level Ⅰ trauma center. Patients enrolled that initial creatine phosphokinase (CPK) levels were higher than 1000 IU with acute multiple trauma, and more than 18 years older from Oct. 2012 to June 2016. We collected demographic data (age, gender, length of hospital day, and patients’ outcome), laboratory data (ABGA, lactate, hemoglobin. hematocrit, platelet, LDH, myoglobin, liver enzyme, and BUN/Cr), and clinical data (Injury Mechanism, RTS, ISS, AIS, and TRISS). The data were compared and analyzed between AKI and Non-AKI group. Statistical analyses were performed using IMB SPSS 20.0 statistics for Window. Results: Three hundred sixty-four patients were enrolled that AKI group were ninety-six and non-AKI group were two hundred sixty-eight. The base excess (HCO3), AST/ALT, LDH, and myoglobin in AKI group were significantly higher than non-AKI group from laboratory data (p ≤ 0.05). The injury severity score (ISS), revised Trauma Score (RTS), Abbreviated Injury Scale 3 and 4 (AIS 3 and 4) were showed significant results in clinical data. The patterns of CPK level were increased from first and second day, but slightly decreased from third day in both group. Seven patients had received hemodialysis treatment despite the bleeding risk and were survived in AKI group. Conclusion: We recommend that HCO3, CPK, LDH, and myoglobin should be checked and be concerned about ISS, RTS, AIS with injury mechanism at the early stage of treatment in the emergency department.Keywords: acute kidney injury, emergencies, multiple trauma, rhabdomyolysis
Procedia PDF Downloads 33917081 UBCSAND Model Calibration for Generic Liquefaction Triggering Curves
Authors: Jui-Ching Chou
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Numerical simulation is a popular method used to evaluate the effects of soil liquefaction on a structure or the effectiveness of a mitigation plan. Many constitutive models (UBCSAND model, PM4 model, SANISAND model, etc.) were presented to model the liquefaction phenomenon. In general, inputs of a constitutive model need to be calibrated against the soil cyclic resistance before being applied to the numerical simulation model. Then, simulation results can be compared with results from simplified liquefaction potential assessing methods. In this article, inputs of the UBCSAND model, a simple elastic-plastic stress-strain model, are calibrated against several popular generic liquefaction triggering curves of simplified liquefaction potential assessing methods via FLAC program. Calibrated inputs can provide engineers to perform a preliminary evaluation of an existing structure or a new design project.Keywords: calibration, liquefaction, numerical simulation, UBCSAND Model
Procedia PDF Downloads 17317080 Awareness about Work-Related Hazards Causing Musculoskeletal Disorders
Authors: Bintou Jobe
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Musculo-skeletal disorders (MSDs) are injuries or disorders of the spine disc, muscle strains, and low back injuries. It remains a major cause of occupational illness. Findings: Due to poor grips during handling, it is possible for neck, shoulder, arm, knees, ankle, fingers, waist, lower back injuries, and other muscle joints to be affected. Pregnant women are more prone to physical and hormonal changes, which lead to the relaxation of supporting ligaments. MSD continues to pose a global concern due to its impact on workers worldwide. The prevalence of the disorder is high, according to research into the workforce in Europe and developing countries. The causes are characterized by long working hours, insufficient rest breaks, poor posture, repetitive motion, poor manual handling techniques, psychological stress, and poor nutrition. To prevent MSD, the design mainly involves avoiding and assessing the risk. However, clinical solutions, policy governance, and minimizing manual labour are also an alternative. In addition, eating a balanced diet and teamwork force are key to elements in minimising the risk. This review aims to raise awareness and promote cost effectiveness prevention and understanding of MSD through research and identify proposed solutions to recognise the underlying causes of MSDs in the construction sectors. The methodology involves a literature review approach, engaging with the policy landscape of MSD, synthesising publications on MSD and a wider range of academic publications. In conclusion, training on effective manual handling techniques should be considered, and Personal Protective Equipment should be a last resort. The implementation of training guidelines has yielded significant benefits.Keywords: musculoskeletal disorder work related, MSD, manual handling, work hazards
Procedia PDF Downloads 6017079 A Crop Growth Subroutine for Watershed Resources Management (WRM) Model 1: Description
Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu
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Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies.Keywords: runoff, roughness coefficient, PAR, WRM model
Procedia PDF Downloads 37817078 Comparison of Two Transcranial Magnetic Stimulation Protocols on Spasticity in Multiple Sclerosis - Pilot Study of a Randomized and Blind Cross-over Clinical Trial
Authors: Amanda Cristina da Silva Reis, Bruno Paulino Venâncio, Cristina Theada Ferreira, Andrea Fialho do Prado, Lucimara Guedes dos Santos, Aline de Souza Gravatá, Larissa Lima Gonçalves, Isabella Aparecida Ferreira Moretto, João Carlos Ferrari Corrêa, Fernanda Ishida Corrêa
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Objective: To compare two protocols of Transcranial Magnetic Stimulation (TMS) on quadriceps muscle spasticity in individuals diagnosed with Multiple Sclerosis (MS). Method: Clinical, crossover study, in which six adult individuals diagnosed with MS and spasticity in the lower limbs were randomized to receive one session of high-frequency (≥5Hz) and low-frequency (≤ 1Hz) TMS on motor cortex (M1) hotspot for quadriceps muscle, with a one-week interval between the sessions. To assess the spasticity was applied the Ashworth scale and were analyzed the latency time (ms) of the motor evoked potential (MEP) and the central motor conduction time (CMCT) of the bilateral quadriceps muscle. Assessments were performed before and after each intervention. The difference between groups was analyzed using the Friedman test, with a significance level of 0.05 adopted. Results: All statistical analyzes were performed using the SPSS Statistic version 26 programs, with a significance level established for the analyzes at p<0.05. Shapiro Wilk normality test. Parametric data were represented as mean and standard deviation for non-parametric variables, median and interquartile range, and frequency and percentage for categorical variables. There was no clinical change in quadriceps spasticity assessed using the Ashworth scale for the 1 Hz (p=0.813) and 5 Hz (p= 0.232) protocols for both limbs. Motor Evoked Potential latency time: in the 5hz protocol, there was no significant change for the contralateral side from pre to post-treatment (p>0.05), and for the ipsilateral side, there was a decrease in latency time of 0.07 seconds (p<0.05 ); for the 1Hz protocol there was an increase of 0.04 seconds in the latency time (p<0.05) for the contralateral side to the stimulus, and for the ipsilateral side there was a decrease in the latency time of 0.04 seconds (p=<0.05), with a significant difference between the contralateral (p=0.007) and ipsilateral (p=0.014) groups. Central motor conduction time in the 1Hz protocol, there was no change for the contralateral side (p>0.05) and for the ipsilateral side (p>0.05). In the 5Hz protocol for the contralateral side, there was a small decrease in latency time (p<0.05) and for the ipsilateral side, there was a decrease of 0.6 seconds in the latency time (p<0.05) with a significant difference between groups (p=0.019). Conclusion: A high or low-frequency session does not change spasticity, but it is observed that when the low-frequency protocol was performed, there was an increase in latency time on the stimulated side, and a decrease in latency time on the non-stimulated side, considering then that inhibiting the motor cortex increases cortical excitability on the opposite side.Keywords: multiple sclerosis, spasticity, motor evoked potential, transcranial magnetic stimulation
Procedia PDF Downloads 8917077 Stock Market Prediction by Regression Model with Social Moods
Authors: Masahiro Ohmura, Koh Kakusho, Takeshi Okadome
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This paper presents a regression model with autocorrelated errors in which the inputs are social moods obtained by analyzing the adjectives in Twitter posts using a document topic model. The regression model predicts Dow Jones Industrial Average (DJIA) more precisely than autoregressive moving-average models.Keywords: stock market prediction, social moods, regression model, DJIA
Procedia PDF Downloads 54817076 Implementation of Active Recovery at Immediate, 12 and 24 Hours Post-Training in Young Soccer Players
Authors: C. Villamizar, M. Serrato
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In the pursuit of athletic performance, the role of physical training which is determined by a number of charges or taxes on physiological stress and musculoskeletal systems of the human body generated by the intensity and duration is fundamental. Given the physical demands of these activities both training and competitive must take into account the optimal relationship with a straining process recovery post favoring the process of overcompensation which aims to facilitate the return and rising energy potential and protein synthesis also of different tissues. Allowing muscle function returns to baseline or pre-exercise states. If this recovery process is not performed or is not allowed in a proper way, will result in an increased state of fatigue. Active recovery, is one of the strategies implemented in the sport for a return to pre-exercise physiological states. However, there are some adverse assumptions regarding the negative effects, as is the possibility of increasing the degradation of muscle glycogen and thus delaying the synthesis thereof. For them, it is necessary to investigate what would be the effects generated application made at different times after the effort. The aim of this study was to determine the effects of active recovery post effort made at three different times: immediately, at 12 and 24 hours on biochemical markers creatine kinase in youth soccer player’s categories. A randomized controlled trial with allocation to three groups was performed: A. active recovery immediately after the effort; B. active recovery performed at 12 hours after the effort; C. active recovery made at 24 hours after the effort. This study included 27 subjects belonging to a Colombian soccer team of the second division. Vital signs, weight, height, BMI, the percentage of muscle mass, fat mass percentage, personal medical history, and family were valued. The velocity, explosive force and Creatin Kinase (CK) in blood were tested before and after interventions. SAFT 90 protocol (Soccer Field specific Aerobic Test) was applied to participants for generating fatigue. CK samples were taken one hour before the application of the fatigue test, one hour after the fatigue protocol and 48 of the initial CK sample. Mean age was 18.5 ± 1.1 years old. Improvements in jumping and speed recovery the 3 groups (p < 0.05), but no statistically significant differences between groups was observed after recuperation. In all participants, there was a significant increment of CK when applied SAFT 90 in all the groups (median 103.1-111.1). The CK measurement after 48 hours reflects a recovery in all groups, however the group C, a decline below baseline levels of -55.5 (-96.3 /-20.4) which is a significant find. Other research has shown that CK does not return quickly to their baseline, but our study shows that active recovery favors the clearance of CK and also to perform recovery 24 hours after the effort generates higher clearance of this biomarker.Keywords: active recuperation, creatine phosphokinase, post training, young soccer players
Procedia PDF Downloads 16017075 The Three-Dimensional Kinematics of the Sprint Start in Young Elite Sprinters
Authors: Saeed Ilbeigi, Bart Van Gheluwe
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The purpose of this study was to identify the three-dimensional kinematics of the sprint start during the start phase of the sprint. The purpose of this study was to identify the three-dimensional kinematics of the sprint start during the start phase of the sprint. Moreover, the effect of anthropometrical factors such as skeletal muscle mass, thigh girth, and calf girth also were considered on the kinematics of the sprint start. Among all young sprinters involved in the national Belgium league, sixty sprinters (boys: 14.7 ± 1.8 years and girls: 14.8±1.5 years) were randomly selected. The kinematics data of the sprint start were collected with a Vicon® 620 motion analysis system equipped with 12 infrared cameras running at 250 Hz and running the Vicon Data Station software. For statistical analysis, T-tests and ANOVA׳s with Scheffé post hoc test were used and the significant level was set as p≤0.05. The results showed that the angular positions of the lower joints of the young sprinters in the set position were comparable with adult figures from literature, however, with a greater range of joint extension. The most significant difference between boys and girls was found in the set position, where the boys presented a more dorsiflexed ankle. No further gender effect was observed during the leaving the blocks and contact phase. The sprinters with a higher age, skeletal muscle mass, thigh girth, and calf girth displayed a better angular position of the lower joints (e.g. ankle, knee, hip) in the set position, a more optimal angular position for the foot and knee for absorbing impact forces at foot contact and finally a higher range of flexion/extension motion to produce force and power when leaving the blocks.Keywords: anthropometry, kinematics, sprint start, young elite sprinters
Procedia PDF Downloads 22817074 Structural Equation Modeling Semiparametric Truncated Spline Using Simulation Data
Authors: Adji Achmad Rinaldo Fernandes
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SEM analysis is a complex multivariate analysis because it involves a number of exogenous and endogenous variables that are interconnected to form a model. The measurement model is divided into two, namely, the reflective model (reflecting) and the formative model (forming). Before carrying out further tests on SEM, there are assumptions that must be met, namely the linearity assumption, to determine the form of the relationship. There are three modeling approaches to path analysis, including parametric, nonparametric and semiparametric approaches. The aim of this research is to develop semiparametric SEM and obtain the best model. The data used in the research is secondary data as the basis for the process of obtaining simulation data. Simulation data was generated with various sample sizes of 100, 300, and 500. In the semiparametric SEM analysis, the form of the relationship studied was determined, namely linear and quadratic and determined one and two knot points with various levels of error variance (EV=0.5; 1; 5). There are three levels of closeness of relationship for the analysis process in the measurement model consisting of low (0.1-0.3), medium (0.4-0.6) and high (0.7-0.9) levels of closeness. The best model lies in the form of the relationship X1Y1 linear, and. In the measurement model, a characteristic of the reflective model is obtained, namely that the higher the closeness of the relationship, the better the model obtained. The originality of this research is the development of semiparametric SEM, which has not been widely studied by researchers.Keywords: semiparametric SEM, measurement model, structural model, reflective model, formative model
Procedia PDF Downloads 4017073 Applying Biosensors’ Electromyography Signals through an Artificial Neural Network to Control a Small Unmanned Aerial Vehicle
Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores
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This work introduces the use of EMGs (electromyography) from muscle sensors to develop an Artificial Neural Network (ANN) for pattern recognition to control a small unmanned aerial vehicle. The objective of this endeavor exhibits interfacing drone applications beyond manual control directly. MyoWare Muscle sensor contains three EMG electrodes (dual and single type) used to collect signals from the posterior (extensor) and anterior (flexor) forearm and the bicep. Collection of raw voltages from each sensor were connected to an Arduino Uno and a data processing algorithm was developed with the purpose of interpreting the voltage signals given when performing flexing, resting, and motion of the arm. Each sensor collected eight values over a two-second period for the duration of one minute, per assessment. During each two-second interval, the movements were alternating between a resting reference class and an active motion class, resulting in controlling the motion of the drone with left and right movements. This paper further investigated adding up to three sensors to differentiate between hand gestures to control the principal motions of the drone (left, right, up, and land). The hand gestures chosen to execute these movements were: a resting position, a thumbs up, a hand swipe right motion, and a flexing position. The MATLAB software was utilized to collect, process, and analyze the signals from the sensors. The protocol (machine learning tool) was used to classify the hand gestures. To generate the input vector to the ANN, the mean, root means squared, and standard deviation was processed for every two-second interval of the hand gestures. The neuromuscular information was then trained using an artificial neural network with one hidden layer of 10 neurons to categorize the four targets, one for each hand gesture. Once the machine learning training was completed, the resulting network interpreted the processed inputs and returned the probabilities of each class. Based on the resultant probability of the application process, once an output was greater or equal to 80% of matching a specific target class, the drone would perform the motion expected. Afterward, each movement was sent from the computer to the drone through a Wi-Fi network connection. These procedures have been successfully tested and integrated into trial flights, where the drone has responded successfully in real-time to predefined command inputs with the machine learning algorithm through the MyoWare sensor interface. The full paper will describe in detail the database of the hand gestures, the details of the ANN architecture, and confusion matrices results.Keywords: artificial neural network, biosensors, electromyography, machine learning, MyoWare muscle sensors, Arduino
Procedia PDF Downloads 17417072 Comparison of Anthropometric Measurements Between Handball and Basketball Female Players
Authors: Jasmina Pluncevic Gligoroska, Sanja Manchevska, Vaska Antevska, Lidija Todorovska, Beti Dejanova, Sunchica Petrovska, Ivanka Karagjozova, Elizabeta Sivevska
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Introduction: Anthropometric measurements are integral part of regular medical examinations of athletes. In addition to the quantification of the size of the body, these measurements indicate the quality of the physical status, because of its association with sports performance. The purpose of this study was to examine whether there are differences in anthropometric parameters and body mass components in female athletes who participate in two different types of sports. Methods: A total of 27 athletes, 15 handball players and 12 basketball players, at the average age of 22.7 years (age span from 17 to 30 years) entered the study. Anthropometric method by Matiegka was used for determination of body components. Sixteen anthropometric measures were taken: height, weight, four diameters of joints, four circumferences of limbs and six skin folds. Results: Handball players were 169.6±6.7 cm tall and 63,75±7.5 kg heavy. Their average relative muscle mass (absolute mass in kg) was 51% (32.5kg), while bone component was 16.8% (10.7kg) and fat component was 14.3% (7.74kg). The basketball players were 177.4±8.2cm tall and 70.37±12.1kg heavy. Their average relative muscle mass (absolute mass in kg) was 51.9 % (36.6kg), bone component was 16.37% (11.5kg) and fat component was 15.36% (9.4kg). The comparison of anthropometric values showed that basketball players were statistically significantly higher and heavier than handball players (p<0.05). Statistically significant difference (p<0.05) was observed in the range of upper leg circumference (higher in basketball players) and the forearm skin fold (higher in the basketball players). Conclusion: Handball players and basketball players significantly differed in basic anthropometric measures (height and weight), but the body components had almost identical values. The anthropometric measurements that have been taken did not show significant difference between handball and basketball female players despite the different physical demands of the games.Keywords: anthropometry, body components, basketball, handball female players
Procedia PDF Downloads 46317071 Metabolic Predictive Model for PMV Control Based on Deep Learning
Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon
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In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.Keywords: deep learning, indoor quality, metabolism, predictive model
Procedia PDF Downloads 25717070 Model Averaging in a Multiplicative Heteroscedastic Model
Authors: Alan Wan
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In recent years, the body of literature on frequentist model averaging in statistics has grown significantly. Most of this work focuses on models with different mean structures but leaves out the variance consideration. In this paper, we consider a regression model with multiplicative heteroscedasticity and develop a model averaging method that combines maximum likelihood estimators of unknown parameters in both the mean and variance functions of the model. Our weight choice criterion is based on a minimisation of a plug-in estimator of the model average estimator's squared prediction risk. We prove that the new estimator possesses an asymptotic optimality property. Our investigation of finite-sample performance by simulations demonstrates that the new estimator frequently exhibits very favourable properties compared to some existing heteroscedasticity-robust model average estimators. The model averaging method hedges against the selection of very bad models and serves as a remedy to variance function misspecification, which often discourages practitioners from modeling heteroscedasticity altogether. The proposed model average estimator is applied to the analysis of two real data sets.Keywords: heteroscedasticity-robust, model averaging, multiplicative heteroscedasticity, plug-in, squared prediction risk
Procedia PDF Downloads 38417069 Reliability Prediction of Tires Using Linear Mixed-Effects Model
Authors: Myung Hwan Na, Ho- Chun Song, EunHee Hong
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We widely use normal linear mixed-effects model to analysis data in repeated measurement. In case of detecting heteroscedasticity and the non-normality of the population distribution at the same time, normal linear mixed-effects model can give improper result of analysis. To achieve more robust estimation, we use heavy tailed linear mixed-effects model which gives more exact and reliable analysis conclusion than standard normal linear mixed-effects model.Keywords: reliability, tires, field data, linear mixed-effects model
Procedia PDF Downloads 56317068 Assessment of Influence of Short-Lasting Whole-Body Vibration on Joint Position Sense and Body Balance–A Randomised Masked Study
Authors: Anna Slupik, Anna Mosiolek, Sebastian Wojtowicz, Dariusz Bialoszewski
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Introduction: Whole-body vibration (WBV) uses high frequency mechanical stimuli generated by a vibration plate and transmitted through bone, muscle and connective tissues to the whole body. Research has shown that long-term vibration-plate training improves neuromuscular facilitation, especially in afferent neural pathways, responsible for the conduction of vibration and proprioceptive stimuli, muscle function, balance and proprioception. Some researchers suggest that the vibration stimulus briefly inhibits the conduction of afferent signals from proprioceptors and can interfere with the maintenance of body balance. The aim of this study was to evaluate the influence of a single set of exercises associated with whole-body vibration on the joint position sense and body balance. Material and methods: The study enrolled 55 people aged 19-24 years. These individuals were randomly divided into a test group (30 persons) and a control group (25 persons). Both groups performed the same set of exercises on a vibration plate. The following vibration parameters: frequency of 20Hz and amplitude of 3mm, were used in the test group. The control group performed exercises on the vibration plate while it was off. All participants were instructed to perform six dynamic exercises lasting 30 seconds each with a 60-second period of rest between them. The exercises involved large muscle groups of the trunk, pelvis and lower limbs. Measurements were carried out before and immediately after exercise. Joint position sense (JPS) was measured in the knee joint for the starting position at 45° in an open kinematic chain. JPS error was measured using a digital inclinometer. Balance was assessed in a standing position with both feet on the ground with the eyes open and closed (each test lasting 30 sec). Balance was assessed using Matscan with FootMat 7.0 SAM software. The surface of the ellipse of confidence and front-back as well as right-left swing were measured to assess balance. Statistical analysis was performed using Statistica 10.0 PL software. Results: There were no significant differences between the groups, both before and after the exercise (p> 0.05). JPS did not change in both the test (10.7° vs. 8.4°) and control groups (9.0° vs. 8.4°). No significant differences were shown in any of the test parameters during balance tests with the eyes open or closed in both the test and control groups (p> 0.05). Conclusions. 1. Deterioration in proprioception or balance was not observed immediately after the vibration stimulus. This suggests that vibration-induced blockage of proprioceptive stimuli conduction can have only a short-lasting effect that occurs only as long as a vibration stimulus is present. 2. Short-term use of vibration in treatment does not impair proprioception and seems to be safe for patients with proprioceptive impairment. 3. These results need to be supplemented with an assessment of proprioception during the application of vibration stimuli. Additionally, the impact of vibration parameters used in the exercises should be evaluated.Keywords: balance, joint position sense, proprioception, whole body vibration
Procedia PDF Downloads 32817067 Towards a Measurement-Based E-Government Portals Maturity Model
Authors: Abdoullah Fath-Allah, Laila Cheikhi, Rafa E. Al-Qutaish, Ali Idri
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The e-government emerging concept transforms the way in which the citizens are dealing with their governments. Thus, the citizens can execute the intended services online anytime and anywhere. This results in great benefits for both the governments (reduces the number of officers) and the citizens (more flexibility and time saving). Therefore, building a maturity model to assess the e-government portals becomes desired to help in the improvement process of such portals. This paper aims at proposing an e-government maturity model based on the measurement of the best practices’ presence. The main benefit of such maturity model is to provide a way to rank an e-government portal based on the used best practices, and also giving a set of recommendations to go to the higher stage in the maturity model.Keywords: best practices, e-government portal, maturity model, quality model
Procedia PDF Downloads 33817066 CFD Simulation of a Large Scale Unconfined Hydrogen Deflagration
Authors: I. C. Tolias, A. G. Venetsanos, N. Markatos
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In the present work, CFD simulations of a large scale open deflagration experiment are performed. Stoichiometric hydrogen-air mixture occupies a 20 m hemisphere. Two combustion models are compared and are evaluated against the experiment. The Eddy Dissipation Model and a Multi-physics combustion model which is based on Yakhot’s equation for the turbulent flame speed. The values of models’ critical parameters are investigated. The effect of the turbulence model is also examined. k-ε model and LES approach were tested.Keywords: CFD, deflagration, hydrogen, combustion model
Procedia PDF Downloads 50217065 A Framework for Consumer Selection on Travel Destinations
Authors: J. Rhodes, V. Cheng, P. Lok
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The aim of this study is to develop a parsimonious model that explains the effect of different stimulus on a tourist’s intention to visit a new destination. The model consists of destination trust and interest as the mediating variables. The model was tested using two different types of stimulus; both studies empirically supported the proposed model. Furthermore, the first study revealed that advertising has a stronger effect than positive online reviews. The second study found that the peripheral route of the elaboration likelihood model has a stronger influence power than the central route in this context.Keywords: advertising, electronic word-of-mouth, elaboration likelihood model, intention to visit, trust
Procedia PDF Downloads 45817064 A Combined AHP-GP Model for Selecting Knowledge Management Tool
Authors: Ahmad Sarfaraz, Raiyad Herwies
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In this paper, a multi-criteria decision making analysis is used to help any organization selects the best KM tool that fits and serves its needs. The AHP model is used based on a previous study to highlight and identify the main criteria and sub-criteria that are incorporated in the selection process. Different KM tools alternatives with different criteria are compared and weighted accurately to be incorporated in the GP model. The main goal is to combine the GP model with the AHP model to ensure that selecting the KM tool considers the resource constraints. Two important issues are discussed in this paper: how different factors could be taken into consideration in forming the AHP model, and how to incorporate the AHP results into the GP model for better results.Keywords: knowledge management, analytical hierarchy process, goal programming, multi-criteria decision making
Procedia PDF Downloads 38517063 Long Short-Time Memory Neural Networks for Human Driving Behavior Modelling
Authors: Lu Zhao, Nadir Farhi, Yeltsin Valero, Zoi Christoforou, Nadia Haddadou
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In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change
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