Search results for: full-potential KKR-green’s function method
22013 A Numerical Computational Method of MRI Static Magnetic Field for an Ergonomic Facility Design Guidelines
Authors: Sherine Farrag
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Magnetic resonance imaging (MRI) presents safety hazards, with the general physical environment. The principal hazard of the MRI is the presence of static magnetic fields. Proper architectural design of MRI’s room ensure environment and health care staff safety. This research paper presents an easy approach for numerical computation of fringe static magnetic fields. Iso-gauss line of different MR intensities (0.3, 0.5, 1, 1.5 Tesla) was mapped and a polynomial function of the 7th degree was generated and tested. Matlab script was successfully applied for MRI SMF mapping. This method can be valid for any kind of commercial scanner because it requires only the knowledge of the MR scanner room map with iso-gauss lines. Results help to develop guidelines to guide healthcare architects to design of a safer Magnetic resonance imaging suite.Keywords: designing MRI suite, MRI safety, radiology occupational exposure, static magnetic fields
Procedia PDF Downloads 48522012 Deleterious SNP’s Detection Using Machine Learning
Authors: Hamza Zidoum
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This paper investigates the impact of human genetic variation on the function of human proteins using machine-learning algorithms. Single-Nucleotide Polymorphism represents the most common form of human genome variation. We focus on the single amino-acid polymorphism located in the coding region as they can affect the protein function leading to pathologic phenotypic change. We use several supervised Machine Learning methods to identify structural properties correlated with increased risk of the missense mutation being damaging. SVM associated with Principal Component Analysis give the best performance.Keywords: single-nucleotide polymorphism, machine learning, feature selection, SVM
Procedia PDF Downloads 37822011 Simple Procedure for Probability Calculation of Tensile Crack Occurring in Rigid Pavement: A Case Study
Authors: Aleš Florian, Lenka Ševelová, Jaroslav Žák
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Formation of tensile cracks in concrete slabs of rigid pavement can be (among others) the initiation point of the other, more serious failures which can ultimately lead to complete degradation of the concrete slab and thus the whole pavement. Two measures can be used for reliability assessment of this phenomenon - the probability of failure and/or the reliability index. Different methods can be used for their calculation. The simple ones are called moment methods and simulation techniques. Two methods - FOSM Method and Simple Random Sampling Method - are verified and their comparison is performed. The influence of information about the probability distribution and the statistical parameters of input variables as well as of the limit state function on the calculated reliability index and failure probability are studied in three points on the lower surface of concrete slabs of the older type of rigid pavement formerly used in the Czech Republic.Keywords: failure, pavement, probability, reliability index, simulation, tensile crack
Procedia PDF Downloads 54622010 Different Methods of Fe3O4 Nano Particles Synthesis
Authors: Arezoo Hakimi, Afshin Farahbakhsh
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Herein, we comparison synthesized Fe3O4 using, hydrothermal method, Mechanochemical processes and solvent thermal method. The Hydrothermal Technique has been the most popular one, gathering interest from scientists and technologists of different disciplines, particularly in the last fifteen years. In the hydrothermal method Fe3O4 microspheres, in which many nearly monodisperse spherical particles with diameters of about 400nm, in the mechanochemical method regular morphology indicates that the particles are well crystallized and in the solvent thermal method Fe3O4 nanoparticles have good properties of uniform size and good dispersion.Keywords: Fe3O4 nanoparticles, hydrothermal method, mechanochemical processes, solvent thermal method
Procedia PDF Downloads 35122009 A Comparison of Smoothing Spline Method and Penalized Spline Regression Method Based on Nonparametric Regression Model
Authors: Autcha Araveeporn
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This paper presents a study about a nonparametric regression model consisting of a smoothing spline method and a penalized spline regression method. We also compare the techniques used for estimation and prediction of nonparametric regression model. We tried both methods with crude oil prices in dollars per barrel and the Stock Exchange of Thailand (SET) index. According to the results, it is concluded that smoothing spline method performs better than that of penalized spline regression method.Keywords: nonparametric regression model, penalized spline regression method, smoothing spline method, Stock Exchange of Thailand (SET)
Procedia PDF Downloads 44022008 Forecasting Models for Steel Demand Uncertainty Using Bayesian Methods
Authors: Watcharin Sangma, Onsiri Chanmuang, Pitsanu Tongkhow
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A forecasting model for steel demand uncertainty in Thailand is proposed. It consists of trend, autocorrelation, and outliers in a hierarchical Bayesian frame work. The proposed model uses a cumulative Weibull distribution function, latent first-order autocorrelation, and binary selection, to account for trend, time-varying autocorrelation, and outliers, respectively. The Gibbs sampling Markov Chain Monte Carlo (MCMC) is used for parameter estimation. The proposed model is applied to steel demand index data in Thailand. The root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) criteria are used for model comparison. The study reveals that the proposed model is more appropriate than the exponential smoothing method.Keywords: forecasting model, steel demand uncertainty, hierarchical Bayesian framework, exponential smoothing method
Procedia PDF Downloads 35022007 Improving Temporal Correlations in Empirical Orthogonal Function Expansions for Data Interpolating Empirical Orthogonal Function Algorithm
Authors: Ping Bo, Meng Yunshan
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Satellite-derived sea surface temperature (SST) is a key parameter for many operational and scientific applications. However, the disadvantage of SST data is a high percentage of missing data which is mainly caused by cloud coverage. Data Interpolating Empirical Orthogonal Function (DINEOF) algorithm is an EOF-based technique for reconstructing the missing data and has been widely used in oceanographic field. The reconstruction of SST images within a long time series using DINEOF can cause large discontinuities and one solution for this problem is to filter the temporal covariance matrix to reduce the spurious variability. Based on the previous researches, an algorithm is presented in this paper to improve the temporal correlations in EOF expansion. Similar with the previous researches, a filter, such as Laplacian filter, is implemented on the temporal covariance matrix, but the temporal relationship between two consecutive images which is used in the filter is considered in the presented algorithm, for example, two images in the same season are more likely correlated than those in the different seasons, hence the latter one is less weighted in the filter. The presented approach is tested for the monthly nighttime 4-km Advanced Very High Resolution Radiometer (AVHRR) Pathfinder SST for the long-term period spanning from 1989 to 2006. The results obtained from the presented algorithm are compared to those from the original DINEOF algorithm without filtering and from the DINEOF algorithm with filtering but without taking temporal relationship into account.Keywords: data interpolating empirical orthogonal function, image reconstruction, sea surface temperature, temporal filter
Procedia PDF Downloads 32422006 Structure Function and Violation of Scale Invariance in NCSM: Theory and Numerical Analysis
Authors: M. R. Bekli, N. Mebarki, I. Chadou
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In this study, we focus on the structure functions and violation of scale invariance in the context of non-commutative standard model (NCSM). We find that this violation appears in the first order of perturbation theory and a non-commutative version of the DGLAP evolution equation is deduced. Numerical analysis and comparison with experimental data imposes a new bound on the non-commutative parameter.Keywords: NCSM, structure function, DGLAP equation, standard model
Procedia PDF Downloads 61122005 Authority and Function of Administrative Organs According to the Constitution: A Construction of Democracy in the Administrative Law of Indonesia
Authors: Andhika Danesjvara, Nur Widyastanti
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The constitution regulates the forms, types, and powers of sState organs in a government. The powers of the organs are then regulated in more detail in the legislation. One of these organs is a government organ, headed by a president or by another name that serves as the main organizer of government. The laws and regulations will govern how the organs of government shall exercise their authority and functions. In a modern state, the function of enacting laws or called executive power does not exercise the functions of government alone, but there are other organs that help the government run the country. These organs are often called government agencies, government accelerating bodies, independent regulatory bodies, commissions, councils or other similar names. The legislation also limits the power of officials within the organs to keep from abusing its authority. The main question in this paper is whether organs are the implementation of a democratic country, or as a form of compromise with the power of stakeholders. It becomes important to see how the administrative organs perform their functions. The administrative organs that are bound by government procedures work in the public service; therefore the next question is how far the function of public service is appropriate and not contradictory to the constitution.Keywords: administrative organs, constitution, democracy, government
Procedia PDF Downloads 30322004 Degree of Approximation of Functions by Product Means
Authors: Hare Krishna Nigam
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In this paper, for the first time, (E,q)(C,2) product summability method is introduced and two quite new results on degree of approximation of the function f belonging to Lip (alpha,r)class and W(L(r), xi(t)) class by (E,q)(C,2) product means of Fourier series, has been obtained.Keywords: Degree of approximation, (E, q)(C, 2) means, Fourier series, Lebesgue integral, Lip (alpha, r)class, W(L(r), xi(t))class of functions
Procedia PDF Downloads 51822003 Non-Differentiable Mond-Weir Type Symmetric Duality under Generalized Invexity
Authors: Jai Prakash Verma, Khushboo Verma
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In the present paper, a pair of Mond-Weir type non-differentiable multiobjective second-order programming problems, involving two kernel functions, where each of the objective functions contains support function, is formulated. We prove weak, strong and converse duality theorem for the second-order symmetric dual programs under η-pseudoinvexity conditions.Keywords: non-differentiable multiobjective programming, second-order symmetric duality, efficiency, support function, eta-pseudoinvexity
Procedia PDF Downloads 24922002 Algorithm Research on Traffic Sign Detection Based on Improved EfficientDet
Authors: Ma Lei-Lei, Zhou You
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Aiming at the problems of low detection accuracy of deep learning algorithm in traffic sign detection, this paper proposes improved EfficientDet based traffic sign detection algorithm. Multi-head self-attention is introduced in the minimum resolution layer of the backbone of EfficientDet to achieve effective aggregation of local and global depth information, and this study proposes an improved feature fusion pyramid with increased vertical cross-layer connections, which improves the performance of the model while introducing a small amount of complexity, the Balanced L1 Loss is introduced to replace the original regression loss function Smooth L1 Loss, which solves the problem of balance in the loss function. Experimental results show, the algorithm proposed in this study is suitable for the task of traffic sign detection. Compared with other models, the improved EfficientDet has the best detection accuracy. Although the test speed is not completely dominant, it still meets the real-time requirement.Keywords: convolutional neural network, transformer, feature pyramid networks, loss function
Procedia PDF Downloads 9822001 The Investigation of Oil Price Shocks by Using a Dynamic Stochastic General Equilibrium: The Case of Iran
Authors: Bahram Fathi, Karim Alizadeh, Azam Mohammadbagheri
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The aim of this paper is to investigate the role of oil price shocks in explaining business cycles in Iran using a dynamic stochastic general equilibrium approach. This model incorporates both productivity and oil revenue shocks. The results indicate that productivity shocks are relatively more important to business cycles than oil shocks. The model with two shocks produces different values for volatility, but these values have the same ranking as that of the actual data for most variables. In addition, the actual data are close to the ratio of standard deviations to the output obtained from the model with two shocks. The results indicate that productivity shocks are relatively more important to business cycles than the oil shocks. The model with only a productivity shock produces the most similar figures in term of volatility magnitude to that of the actual data. Next, we use the Impulse Response Functions (IRF) to evaluate the capability of the model. The IRF shows no effect of an oil shock on the capital stocks and on labor hours, which is a feature of the model. When the log-linearized system of equations is solved numerically, investment and labor hours were not found to be functions of the oil shock. This research recommends using different techniques to compare the model’s robustness. One method by which to do this is to have all decision variables as a function of the oil shock by inducing the stationary to the model differently. Another method is to impose a bond adjustment cost. This study intends to fill that gap. To achieve this objective, we derive a DSGE model that allows for the world oil price and productivity shocks. Second, we calibrate the model to the Iran economy. Next, we compare the moments from the theoretical model with both single and multiple shocks with that obtained from the actual data to see the extent to which business cycles in Iran can be explained by total oil revenue shock. Then, we use an impulse response function to evaluate the role of world oil price shocks. Finally, I present implications of the findings and interpretations in accordance with economic theory.Keywords: oil price, shocks, dynamic stochastic general equilibrium, Iran
Procedia PDF Downloads 43822000 RBF Neural Network Based Adaptive Robust Control for Bounded Position/Force Control of Bilateral Teleoperation Arms
Authors: Henni Mansour Abdelwaheb
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This study discusses the design of a bounded position/force feedback controller developed to ensure position and force tracking for bilateral teleoperation arms operating with variable delay, and actuator saturation. Also, an adaptive robust Radial Basis Function (RBF) neural network is used to estimate the environment torque. The parameters of the environment torque are then sent from the slave site to the master site as a non-power signal to avoid passivity problems. Moreover, a nonlinear function is applied to each controller term as a smooth saturation function, providing a bounded control signal and preserving the system’s actuators. Lastly, the Lyapunov approach demonstrates the global stability of the controlled system, and numerical experiment results further confirm the validity of the presented strategy.Keywords: teleoperation manipulators system, time-varying delay, actuator saturation, adaptive robust rbf neural network approximation, uncertainties
Procedia PDF Downloads 7621999 Transfer Learning for Protein Structure Classification at Low Resolution
Authors: Alexander Hudson, Shaogang Gong
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Structure determination is key to understanding protein function at a molecular level. Whilst significant advances have been made in predicting structure and function from amino acid sequence, researchers must still rely on expensive, time-consuming analytical methods to visualise detailed protein conformation. In this study, we demonstrate that it is possible to make accurate (≥80%) predictions of protein class and architecture from structures determined at low (>3A) resolution, using a deep convolutional neural network trained on high-resolution (≤3A) structures represented as 2D matrices. Thus, we provide proof of concept for high-speed, low-cost protein structure classification at low resolution, and a basis for extension to prediction of function. We investigate the impact of the input representation on classification performance, showing that side-chain information may not be necessary for fine-grained structure predictions. Finally, we confirm that high resolution, low-resolution and NMR-determined structures inhabit a common feature space, and thus provide a theoretical foundation for boosting with single-image super-resolution.Keywords: transfer learning, protein distance maps, protein structure classification, neural networks
Procedia PDF Downloads 13621998 Reduction of the Number of Traffic Accidents by Function of Driver's Anger Detection
Authors: Masahiro Miyaji
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When a driver happens to be involved in some traffic congestion or after traffic incidents, the driver may fall in a state of anger. State of anger may encounter decisive risk resulting in severer traffic accidents. Preventive safety function using driver’s psychosomatic state with regard to anger may be one of solutions which would avoid that kind of risks. Identifying driver’s anger state is important to create countermeasures to prevent the risk of traffic accidents. As a first step, this research figured out root cause of traffic incidents by means of using Internet survey. From statistical analysis of the survey, dominant psychosomatic states immediately before traffic incidents were haste, distraction, drowsiness and anger. Then, we replicated anger state of a driver while driving, and then, replicated it by means of using driving simulator on bench test basis. Six types of facial expressions including anger were introduced as alternative characteristics. Kohonen neural network was adopted to classify anger state. Then, we created a methodology to detect anger state of a driver in high accuracy. We presented a driving support safety function. The function adapts driver’s anger state in cooperation with an autonomous driving unit to reduce the number of traffic accidents. Consequently, e evaluated reduction rate of driver’s anger in the traffic accident. To validate the estimation results, we referred the reduction rate of Advanced Safety Vehicle (ASV) as well as Intelligent Transportation Systems (ITS).Keywords: Kohonen neural network, driver’s anger state, reduction of traffic accidents, driver’s state adaptive driving support safety
Procedia PDF Downloads 35921997 Comparative Analysis of Sigmoidal Feedforward Artificial Neural Networks and Radial Basis Function Networks Approach for Localization in Wireless Sensor Networks
Authors: Ashish Payal, C. S. Rai, B. V. R. Reddy
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With the increasing use and application of Wireless Sensor Networks (WSN), need has arisen to explore them in more effective and efficient manner. An important area which can bring efficiency to WSNs is the localization process, which refers to the estimation of the position of wireless sensor nodes in an ad hoc network setting, in reference to a coordinate system that may be internal or external to the network. In this paper, we have done comparison and analysed Sigmoidal Feedforward Artificial Neural Networks (SFFANNs) and Radial Basis Function (RBF) networks for developing localization framework in WSNs. The presented work utilizes the Received Signal Strength Indicator (RSSI), measured by static node on 100 x 100 m2 grid from three anchor nodes. The comprehensive evaluation of these approaches is done using MATLAB software. The simulation results effectively demonstrate that FFANNs based sensor motes will show better localization accuracy as compared to RBF.Keywords: localization, wireless sensor networks, artificial neural network, radial basis function, multi-layer perceptron, backpropagation, RSSI, GPS
Procedia PDF Downloads 33921996 Overall Function and Symptom Impact of Self-Applied Myofascial Release in Adult Patients With Fibromyalgia. A Seven-Week Pilot Study
Authors: Domenica Tambasco, Riina Bray, Sophia Jaworski, Gillian Grant, Celeste Corkery
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Fibromyalgia is a chronic condition characterized by widespread musculoskeletal pain, fatigue, and reduced function. Management of symptoms include medications, physical treatments and mindfulness therapies. Myofascial Release is a modality that has been successfully applied in var-ious musculoskeletal conditions. However, to the author’s best knowledge, it is not yet recog-nized as a self-management therapy option in Fibromyalgia. In this study, we investigated whether Self-applied Myofascial Release (SMR) is associated with overall improved function and symptoms in Fibromyalgia. Methods: Eligible adult patients with a confirmed diagnosis of Fibromyalgia at Women’s College Hospital were recruited to SMR. Sessions ran for 1 hour once a week for 7 weeks, led by the same two Physiotherapists knowledgeable in this physical treat-ment modality. The main outcome measure was an overall impact score for function and symp-toms based on the validated assessment tool for Fibromyalgia, the Revised Fibromyalgia Impact Questionnaire (FIQR), measured pre and post-intervention. Both descriptive and analytical methods were applied and reported. Results: We analyzed results using a paired t-test to deter-mine if there was a statistically significant difference in mean FIQR scores between initial (pre-intervention) and final (post-intervention) scores. A clinically significant difference in FIQR was defined as a reduction in score by 10 or more points. Conclusions: Our pilot study showed that SMR appeared to be a safe and effective intervention for our Fibromyalgia participants and the overall impact on function and symptoms occurred in only 7 weeks. Further studies with larger sample sizes comparing SMR to other physical treatment modalities (such as stretching) in an RCT are recommended.Keywords: fibromyalgia, myofascial release, physical therapy, FIQR
Procedia PDF Downloads 7621995 Soil Parameters Identification around PMT Test by Inverse Analysis
Authors: I. Toumi, Y. Abed, A. Bouafia
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This paper presents a methodology for identifying the cohesive soil parameters that takes into account different constitutive equations. The procedure, applied to identify the parameters of generalized Prager model associated to the Drucker & Prager failure criterion from a pressuremeter expansion curve, is based on an inverse analysis approach, which consists of minimizing the function representing the difference between the experimental curve and the simulated curve using a simplex algorithm. The model response on pressuremeter path and its identification from experimental data lead to the determination of the friction angle, the cohesion and the Young modulus. Some parameters effects on the simulated curves and stresses path around pressuremeter probe are presented. Comparisons between the parameters determined with the proposed method and those obtained by other means are also presented.Keywords: cohesive soils, cavity expansion, pressuremeter test, finite element method, optimization procedure, simplex algorithm
Procedia PDF Downloads 29421994 A Distinct Method Based on Mamba-Unet for Brain Tumor Image Segmentation
Authors: Djallel Bouamama, Yasser R. Haddadi
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Accurate brain tumor segmentation is crucial for diagnosis and treatment planning, yet it remains a challenging task due to the variability in tumor shapes and intensities. This paper introduces a distinct approach to brain tumor image segmentation by leveraging an advanced architecture known as Mamba-Unet. Building on the well-established U-Net framework, Mamba-Unet incorporates distinct design enhancements to improve segmentation performance. Our proposed method integrates a multi-scale attention mechanism and a hybrid loss function to effectively capture fine-grained details and contextual information in brain MRI scans. We demonstrate that Mamba-Unet significantly enhances segmentation accuracy compared to conventional U-Net models by utilizing a comprehensive dataset of annotated brain MRI scans. Quantitative evaluations reveal that Mamba-Unet surpasses traditional U-Net architectures and other contemporary segmentation models regarding Dice coefficient, sensitivity, and specificity. The improvements are attributed to the method's ability to manage class imbalance better and resolve complex tumor boundaries. This work advances the state-of-the-art in brain tumor segmentation and holds promise for improving clinical workflows and patient outcomes through more precise and reliable tumor detection.Keywords: brain tumor classification, image segmentation, CNN, U-NET
Procedia PDF Downloads 3421993 The Response of 4-Hydroxybenzoic Acid on Kv1.4 Potassium Channel Subunit Expressed in Xenopus laevis Oocytes
Authors: Fatin H. Mohamad, Jia H. Wong, Muhammad Bilal, Abdul A. Mohamed Yusoff, Jafri M. Abdullah, Jingli Zhang
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Kv1.4 is a Shaker-related member of voltage-gated potassium channel which can be associated with cardiac action potential but can also be found in Schaffer collateral and dentate gyrus. It has two inactivation mechanisms; the fast N-type and slow C-type. Kv1.4 produces rapid current inactivation. This A type potential of Kv1.4 makes it as a target in antiepileptic drugs (AEDs) selection. In this study, 4-hydroxybenzoic acid, which can be naturally found in bamboo shoots, were tested on its enhancement effect on potassium current of Kv1.4 channel expressed in Xenopus laevis oocytes using the two-microelectrode voltage clamp method. Current obtained were recorded and analyzed with pClamp software whereas statistical analysis were done by student t-test. The ratio of final / peak amplitude is an index of the activity of the Kv1.4 channel. The less the ratio, the greater the function of Kv1.4. The decrease of ratio of which by 1µM 4-hydroxybenzoic acid (n= 7), compared with 0.1% DMSO (vehicle), was mean= 47.62%, SE= 13.76%, P= 0.026 (statistically significant). It indicated more opening of Kv1.4 channels under 4-hydroxybenzoic acid. In conclusion, 4-hydroxybenzoic acid can enhance the function of Kv1.4 potassium channels, which is regarded as one of the mechanisms of antiepileptic treatment.Keywords: antiepileptic, Kv1.4 potassium channel, two-microelectrode voltage clamp, Xenopus laevis oocytes, 4-hydroxybenzoic acid
Procedia PDF Downloads 36221992 Evaluation of Spatial Correlation Length and Karhunen-Loeve Expansion Terms for Predicting Reliability Level of Long-Term Settlement in Soft Soils
Authors: Mehrnaz Alibeikloo, Hadi Khabbaz, Behzad Fatahi
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The spectral random field method is one of the widely used methods to obtain more reliable and accurate results in geotechnical problems involving material variability. Karhunen-Loeve (K-L) expansion method was applied to perform random field discretization of cross-correlated creep parameters. Karhunen-Loeve expansion method is based on eigenfunctions and eigenvalues of covariance function adopting Kernel integral solution. In this paper, the accuracy of Karhunen-Loeve expansion was investigated to predict long-term settlement of soft soils adopting elastic visco-plastic creep model. For this purpose, a parametric study was carried to evaluate the effect of K-L expansion terms and spatial correlation length on the reliability of results. The results indicate that small values of spatial correlation length require more K-L expansion terms. Moreover, by increasing spatial correlation length, the coefficient of variation (COV) of creep settlement increases, confirming more conservative and safer prediction.Keywords: Karhunen-Loeve expansion, long-term settlement, reliability analysis, spatial correlation length
Procedia PDF Downloads 15921991 Optimization of the Measure of Compromise as a Version of Sorites Paradox
Authors: Aleksandar Hatzivelkos
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The term ”compromise” is mostly used casually within the social choice theory. It is usually used as a mere result of the social choice function, and this omits its deeper meaning and ramifications. This paper is based on a mathematical model for the description of a compromise as a version of the Sorites paradox. It introduces a formal definition of d-measure of divergence from a compromise and models a notion of compromise that is often used only colloquially. Such a model for vagueness phenomenon, which lies at the core of the notion of compromise enables the introduction of new mathematical structures. In order to maximize compromise, different methods can be used. In this paper, we explore properties of a social welfare function TdM (from Total d-Measure), which is defined as a function which minimizes the total sum of d-measures of divergence over all possible linear orderings. We prove that TdM satisfy strict Pareto principle and behaves well asymptotically. Furthermore, we show that for certain domain restrictions, TdM satisfy positive responsiveness and IIIA (intense independence of irrelevant alternatives) thus being equivalent to Borda count on such domain restriction. This result gives new opportunities in social choice, especially when there is an emphasis on compromise in the decision-making process.Keywords: borda count, compromise, measure of divergence, minimization
Procedia PDF Downloads 13321990 Ergonomic Assessment of Workplace Environment of Flour Mill Workers
Authors: Jayshree P. Zend, Ashatai B. Pawar
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The study was carried out in Parbhani district of Maharashtra state, India with the objectives to study environmental problems faced by flour mill workers, prevalence of work-related health hazards and the physiological cost of workers while performing work in flour mill in traditional method as well as improved method. The use of flour presser, dust controlling bag and noise and dust controlling mask developed by AICRP College of Home Science, VNMKV, Parbhani was considered as an improved method. This investigation consisted survey and experiment which was conducted in the respective locations of flour mills. Healthy, non-smoking 30 flour mill workers ranged between the age group of 20-50 yrs comprising 16 female and 14 male working at flour mill for 4-8 hrs/ day and 6 days/ week and had minimum five years experience of work in flour mill were selected for the study. Pulmonary function test of flour mill workers was carried out by trained technician at Dr. ShankarraoChavan Government Medical College, Nanded by using Electronic Spirometer. The data regarding heart rate (resting, working and recovery), energy expenditure, musculoskeletal problems and occupational health hazards and accidents were recorded by using pretested questionnaire. Scientific equipment used in the experiment were polar sport test heart rate monitor, Hygrometer, Goniometer, Dialed Thermometer, Sound Level Meter, Lux Meter, Ambient Air Sampler and Air Quality Monitor. The collected data were subjected to appropriate statistical analysis such as 't' test and correlation coefficient test. Results indicated that improved method i.e. use of noise and dust controlling mask, flour presser and dust controlling bag were effective in reducing physiological cost of work of flour mill workers. Lung function test of flour mill workers showed decreased values of all parameters, hence the results of present study support paying attention to use of personal protective noise and dust controlling mask by flour mill workers and also to the working conditions in flour mill especially ventilation and illumination level needs to be enhanced in flour mill. The study also emphasizes the need to develop some mechanism for lifting load of grains and unloading in the hopper. It is also suggested that the flour mill workers should use flour presser suitable to their height to avoid frequent bending and should use dust controlling bag to flour outlet of machine to reduce inhalable flour dust level in the flour mill.Keywords: physiological cost, energy expenditure, musculoskeletal problems
Procedia PDF Downloads 40121989 Welfare Estimation in a General Equilibrium Model with Cities
Authors: Oded Hochman
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We first show that current measures of welfare changes in the whole economy do not apply to an economy with cities. In addition, since such measures are defined over a partial equilibrium, they capture only partially the effect of a welfare change. We then define a unique and additive measure that we term the modified economic surplus (mES) which fully captures the welfare effects caused by a change in the price of a nationally traded good. We show that the price change causes, on the one hand a change of land rents in the economy and, on the other hand, an equal change of mES that can be estimated by measuring areas in the price-quantity national demand and supply plane. We construct for each city a cost function from which we derive a city’s and, after aggregation, an economy-wide demand and supply functions of nationwide prices and of either the unearned incomes (Marshalian functions) or the utility levels (compensated functions).Keywords: city cost function, welfare measures, modified compensated variation, modified economic surplus, unearned income function, differential land rents, city size
Procedia PDF Downloads 32021988 Influence of Optimization Method on Parameters Identification of Hyperelastic Models
Authors: Bale Baidi Blaise, Gilles Marckmann, Liman Kaoye, Talaka Dya, Moustapha Bachirou, Gambo Betchewe, Tibi Beda
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This work highlights the capabilities of particles swarm optimization (PSO) method to identify parameters of hyperelastic models. The study compares this method with Genetic Algorithm (GA) method, Least Squares (LS) method, Pattern Search Algorithm (PSA) method, Beda-Chevalier (BC) method and the Levenberg-Marquardt (LM) method. Four classic hyperelastic models are used to test the different methods through parameters identification. Then, the study compares the ability of these models to reproduce experimental Treloar data in simple tension, biaxial tension and pure shear.Keywords: particle swarm optimization, identification, hyperelastic, model
Procedia PDF Downloads 17121987 Design and Analysis of Universal Multifunctional Leaf Spring Main Landing Gear for Light Aircraft
Authors: Meiyuan Zheng, Jingwu He, Yuexi Xiong
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A universal multi-function leaf spring main landing gear was designed for light aircraft. The main landing gear combined with the leaf spring, skidding, and wheels enables it to have a good takeoff and landing performance on various grounds such as the hard, snow, grass and sand grounds. Firstly, the characteristics of different landing sites were studied in this paper in order to analyze the load of the main landing gear on different types of grounds. Based on this analysis, the structural design optimization along with the strength and stiffness characteristics of the main landing gear has been done, which enables it to have good takeoff and landing performance on different types of grounds given the relevant regulations and standards. Additionally, the impact of the skidding on the aircraft during the flight was also taken into consideration. Finally, a universal multi-function leaf spring type of the main landing gear suitable for light aircraft has been developed.Keywords: landing gear, multi-function, leaf spring, skidding
Procedia PDF Downloads 26821986 Influence of Strengthening of Hip Abductors and External Rotators in Treatment of Patellofemoral Pain Syndrome
Authors: Karima Abdel Aty Hassan Mohamed, Manal Mohamed Ismail, Mona Hassan Gamal Eldein, Ahmed Hassan Hussein, Abdel Aziz Mohamed Elsingerg
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Background: Patellofemoral pain (PFP) is a common musculoskeletal pain condition, especially in females. Decreased hip muscle strength has been implicated as a contributing factor, yet the relationships between pain, hip muscle strength and function are not known. Objective: The purpose of this study is to investigate the effects of strengthening hip abductors and lateral rotators on pain intensity, function and hip abductor and hip lateral rotator eccentric and concentric torques in patients with PFPS. Methods: Thirty patients had participated in this study; they were assigned into two experimental groups. With age ranged for eighty to thirty five years. Group A consisted of 15 patients (11females and 4 males) with mean age 20.8 (±2.73) years, received closed kinetic chain exercises program, stretching exercises for tight lower extremity soft tissues, and hip strengthening exercises .Group B consisted of 15 patients (12 females and 3 males) with mean age 21.2(±3.27) years, received closed kinetic chain exercises program and stretching exercises for tight lower extremity soft tissues. Treatment was given 2-3times/week, for 6 weeks. Patients were evaluated pre and post treatment for their pain severity, function of knee joint, hip abductors and external rotators concentric/eccentric peak torque. Result: the results revealed that there were significant differences in pain and function between both groups, while there was improvement for all values for both group. Conclusion: Six weeks rehabilitation program focusing on knee strengthening exercises either supplemented by hip strengthening exercises or not effective in improving function, reducing pain and improving hip muscles torque in patients with PFPS. However, adding hip abduction and lateral rotation strengthening exercises seem to reduce pain and improve function more efficiently.Keywords: patellofemoral pain syndrome, hip muscles, rehabilitation, isokinetic
Procedia PDF Downloads 44721985 Virtual Test Model for Qualification of Knee Prosthesis
Authors: K. Zehouani, I. Oldal
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Purpose: In the human knee joint, degenerative joint disease may happen with time. The standard treatment of this disease is the total knee replacement through prosthesis implanting. The reason lies in the fact that this phenomenon causes different material abrasion as compare to pure sliding or rolling alone. This study focuses on developing a knee prosthesis geometry, which fulfills the mechanical and kinematical requirements. Method: The MSC ADAMS program is used to describe the rotation of the human knee joint as a function of flexion, and to investigate how the flexion and rotation movement changes between the condyles of a multi-body model of the knee prosthesis as a function of flexion angle (in the functional arc of the knee (20-120º)). Moreover, the multi-body model with identical boundary conditions is constituted, and the numerical simulations are carried out using the MSC ADAMS program system. Results: It is concluded that the use of the multi-body model reduces time and cost since it does not need to manufacture the tibia and the femur as it requires for the knee prosthesis of the test machine. Moreover, without measuring or by dispensing with a test machine for the knee prosthesis geometry, approximation of the results of our model to a human knee is carried out directly. Conclusion: The pattern obtained by the multi-body model provides an insight for future experimental tests related to the rotation and flexion of the knee joint concerning the actual average and friction load.Keywords: biomechanics, knee joint, rotation, flexion, kinematics, MSC ADAMS
Procedia PDF Downloads 14421984 Similarity Solutions of Nonlinear Stretched Biomagnetic Flow and Heat Transfer with Signum Function and Temperature Power Law Geometries
Authors: M. G. Murtaza, E. E. Tzirtzilakis, M. Ferdows
Abstract:
Biomagnetic fluid dynamics is an interdisciplinary field comprising engineering, medicine, and biology. Bio fluid dynamics is directed towards finding and developing the solutions to some of the human body related diseases and disorders. This article describes the flow and heat transfer of two dimensional, steady, laminar, viscous and incompressible biomagnetic fluid over a non-linear stretching sheet in the presence of magnetic dipole. Our model is consistent with blood fluid namely biomagnetic fluid dynamics (BFD). This model based on the principles of ferrohydrodynamic (FHD). The temperature at the stretching surface is assumed to follow a power law variation, and stretching velocity is assumed to have a nonlinear form with signum function or sign function. The governing boundary layer equations with boundary conditions are simplified to couple higher order equations using usual transformations. Numerical solutions for the governing momentum and energy equations are obtained by efficient numerical techniques based on the common finite difference method with central differencing, on a tridiagonal matrix manipulation and on an iterative procedure. Computations are performed for a wide range of the governing parameters such as magnetic field parameter, power law exponent temperature parameter, and other involved parameters and the effect of these parameters on the velocity and temperature field is presented. It is observed that for different values of the magnetic parameter, the velocity distribution decreases while temperature distribution increases. Besides, the finite difference solutions results for skin-friction coefficient and rate of heat transfer are discussed. This study will have an important bearing on a high targeting efficiency, a high magnetic field is required in the targeted body compartment.Keywords: biomagnetic fluid, FHD, MHD, nonlinear stretching sheet
Procedia PDF Downloads 161