Search results for: neural tube defects
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3015

Search results for: neural tube defects

2865 Producer’s Liability for Defective Medical Devices in Light of Council Directive 85/374/EEC

Authors: Vera Lúcia Raposo

Abstract:

Medical devices are products used for medical purposes and aimed to operate in the human body, sometimes even inside the human body. Therefore, they can become particularly risky products, and some of the injuries caused by medical devices can have serious effects on the person’s health or body, even leading to death. Because they fit in the category of 'products' as described in Article 2 of Council Directive 85/374/EEC of 25 July 1985, concerning liability for defective products, the liability of the manufacturer of medical devices follows the rules of strict liability as long as one of the defects covered by the directive is at stake. The directive is not concerned with the product’s efficiency, but instead with the product’s safety, although in what regards medical devices (the same being valid for drugs) the two concepts frequently go together, and a lack of efficiency can result in a lack of safety. In the particular case of medical devices, the most debatable defects are the ones related with erroneous or non-existing information and the so-called development defects. This paper analyses how directive 85/374/EEC applies to medical devices, which defects are covered by its regulation, and which criteria can be used to evaluate the product’s safety. Some issues are still to be clarified, even though the decisions from the European Court of Justice and from national courts are valuable tools to understand the scope of directive 85/374/EEC in what regards medical devices.

Keywords: medical devices, producer’s liability, product safety, strict liability

Procedia PDF Downloads 325
2864 Effect of Diamagnetic Additives on Defects Level of Soft LiTiZn Ferrite Ceramics

Authors: Andrey V. Malyshev, Anna B. Petrova, Anatoly P. Surzhikov

Abstract:

The article presents the results of the influence of diamagnetic additives on the defects level of ferrite ceramics. For this purpose, we use a previously developed method based on the mathematical analysis of experimental temperature dependences of the initial permeability. A phenomenological expression for the description of such dependence was suggested and an interpretation of its main parameters was given. It was shown, that the main criterion of the integral defects level of ferrite ceramics is the relation of two parameters correlating with elastic stress value in a material. Model samples containing a controlled number of intergranular phase inclusions served to prove the validity of the proposed method, as well as to assess its sensitivity in comparison with the traditional XRD (X-ray diffraction) analysis. The broadening data of diffraction reflexes of model samples have served for such comparison. The defects level data obtained by the proposed method are in good agreement with the X-ray data. The method showed high sensitivity. Therefore, the legitimacy of the selection relationship β/α parameters of phenomenological expression as a characteristic of the elastic state of the ferrite ceramics confirmed. In addition, the obtained data can be used in the detection of non-magnetic phases and testing the optimal sintering production technology of soft magnetic ferrites.

Keywords: cure point, initial permeability, integral defects level, homogeneity

Procedia PDF Downloads 134
2863 Ulnar Parametacarpal Flap for Coverage of Fifth Finger Defects: Propeller Flap Concept

Authors: Ahmed M. Gad, Ahmed S. Hweidi

Abstract:

Background: Defects of the little finger and adjacent areas are not uncommon. It could be a traumatic, post-burn, or after contracture release. Different options could be used for resurfacing these defect, including skin grafts, local or regional flaps. Ulnar para-metacarpal flap described by Bakhach in 1995 based on the distal division of the dorsal branch of the ulnar artery considered a good option for that. In this work, we applied the concept of propeller flap for better mobilization and in-setting of the ulnar para-metacarpal flap. Methods: The study included 15 cases with 4 females and 11 male patients. 10 of the patients had severe post-burn contractures of little finger, and 5 had post-traumatic little finger defects. Contractures were released and resulting soft tissue defects were reconstructed with propeller ulnar para-metacarpal artery flap. The flap based on two main perforators communicating with the palmar system, it was raised based on one of them depending on the extent of the defect and rotated 180 degrees after judicious dissection of the perforator. Results: 13 flaps survived completely, one of the cases developed partial skin loss, which healed by dressing, another flap was completely lost and covered later by a full-thickness skin graft. Conclusion: Ulnar para-metacarpal flap is a reliable option to resurface the little finger as well as adjacent areas. The application of the propeller flap concept based on whether the proximal or distal communicating branch makes the rotation and in-setting of the flap easier.

Keywords: little finger defects, propeller flap, regional hand defects, ulnar parametacarpal flap

Procedia PDF Downloads 198
2862 Designing Intelligent Adaptive Controller for Nonlinear Pendulum Dynamical System

Authors: R. Ghasemi, M. R. Rahimi Khoygani

Abstract:

This paper proposes the designing direct adaptive neural controller to apply for a class of a nonlinear pendulum dynamic system. The radial basis function (RBF) neural adaptive controller is robust in presence of external and internal uncertainties. Both the effectiveness of the controller and robustness against disturbances are importance of this paper. The simulation results show the promising performance of the proposed controller.

Keywords: adaptive neural controller, nonlinear dynamical, neural network, RBF, driven pendulum, position control

Procedia PDF Downloads 482
2861 Modeling and Simulation for 3D Eddy Current Testing in Conducting Materials

Authors: S. Bennoud, M. Zergoug

Abstract:

The numerical simulation of electromagnetic interactions is still a challenging problem, especially in problems that result in fully three dimensional mathematical models. The goal of this work is to use mathematical modeling to characterize the reliability and capacity of eddy current technique to detect and characterize defects embedded in aeronautical in-service pieces. The finite element method is used for describing the eddy current technique in a mathematical model by the prediction of the eddy current interaction with defects. However, this model is an approximation of the full Maxwell equations. In this study, the analysis of the problem is based on a three dimensional finite element model that computes directly the electromagnetic field distortions due to defects.

Keywords: eddy current, finite element method, non destructive testing, numerical simulations

Procedia PDF Downloads 443
2860 Using Infrared Thermography, Photogrammetry and a Remotely Piloted Aircraft System to Create 3D Thermal Models

Authors: C. C. Kruger, P. Van Tonder

Abstract:

Concrete deteriorates over time and the deterioration can be escalated due to multiple factors. When deteriorations are beneath the concrete’s surface, they could be unknown, even more so when they are located at high elevations. Establishing the severity of such defects could prove difficult and therefore the need to find efficient, safe and economical methods to find these defects becomes ever more important. Current methods using thermography to find defects require equipment such as scaffolding to reach these higher elevations. This could become time- consuming and costly. The risks involved with personnel scaffold or abseil to such heights are high. Accordingly, by combining the technologies of a thermal camera and a Remotely Piloted Aerial System it could be used to find better diagnostic methods. The data could then be constructed into a 3D thermal model to easy representation of the results

Keywords: concrete, infrared thermography, 3D thermal models, diagnostic

Procedia PDF Downloads 172
2859 Classification Based on Deep Neural Cellular Automata Model

Authors: Yasser F. Hassan

Abstract:

Deep learning structure is a branch of machine learning science and greet achievement in research and applications. Cellular neural networks are regarded as array of nonlinear analog processors called cells connected in a way allowing parallel computations. The paper discusses how to use deep learning structure for representing neural cellular automata model. The proposed learning technique in cellular automata model will be examined from structure of deep learning. A deep automata neural cellular system modifies each neuron based on the behavior of the individual and its decision as a result of multi-level deep structure learning. The paper will present the architecture of the model and the results of simulation of approach are given. Results from the implementation enrich deep neural cellular automata system and shed a light on concept formulation of the model and the learning in it.

Keywords: cellular automata, neural cellular automata, deep learning, classification

Procedia PDF Downloads 198
2858 The Application of a Hybrid Neural Network for Recognition of a Handwritten Kazakh Text

Authors: Almagul Assainova , Dariya Abykenova, Liudmila Goncharenko, Sergey Sybachin, Saule Rakhimova, Abay Aman

Abstract:

The recognition of a handwritten Kazakh text is a relevant objective today for the digitization of materials. The study presents a model of a hybrid neural network for handwriting recognition, which includes a convolutional neural network and a multi-layer perceptron. Each network includes 1024 input neurons and 42 output neurons. The model is implemented in the program, written in the Python programming language using the EMNIST database, NumPy, Keras, and Tensorflow modules. The neural network training of such specific letters of the Kazakh alphabet as ә, ғ, қ, ң, ө, ұ, ү, h, і was conducted. The neural network model and the program created on its basis can be used in electronic document management systems to digitize the Kazakh text.

Keywords: handwriting recognition system, image recognition, Kazakh font, machine learning, neural networks

Procedia PDF Downloads 262
2857 Prediction of Wind Speed by Artificial Neural Networks for Energy Application

Authors: S. Adjiri-Bailiche, S. M. Boudia, H. Daaou, S. Hadouche, A. Benzaoui

Abstract:

In this work the study of changes in the wind speed depending on the altitude is calculated and described by the model of the neural networks, the use of measured data, the speed and direction of wind, temperature and the humidity at 10 m are used as input data and as data targets at 50m above sea level. Comparing predict wind speeds and extrapolated at 50 m above sea level is performed. The results show that the prediction by the method of artificial neural networks is very accurate.

Keywords: MATLAB, neural network, power low, vertical extrapolation, wind energy, wind speed

Procedia PDF Downloads 692
2856 Risk Factors and Outcome of Free Tissue Transfer at a Tertiary Care Referral Center

Authors: Majid Khan

Abstract:

Introduction: In this era of microsurgery, free flap holds a remarkable spot in reconstructive surgery. A free flap is well suited for composite defects as it provides sufficient and well-vascularized tissue for coverage. We report our experience with the use of the free flaps for the reconstruction of composite defects. Methods: This is a retrospective case series (chart review) of patients who underwent reconstruction of composite defects with a free flap at Aga Khan University Hospital, Karachi (Pakistan) from January 01, 2015, to December 31, 2019. Data were collected for patient demographics, size of the defect, size of flap, recipient vessels, postoperative complications, and outcome of the free flap. Results: Over this period, 532 free flaps are included in this study. The overall success rate is 95.5%. The mean age of the patient was 44.86 years. In 532 procedures, there were 448 defects from tumor ablation of head and neck cancer. The most frequent free flap was the anterolateral thigh flap in 232 procedures. In this study, the risk factor hypertension (p=0.004) was found significant for wound dehiscence, preop radiation/chemotherapy (p=0.003), and malnutrition (p=0.005) were found significant for fistula formation. Malnutrition (p=0.02) and use of vein grafts (p=0.025) were significant factors for flap failure. Conclusion: Free tissue transfer is a reliable option for the reconstruction of large and composite defects. Hypertension, malnutrition, and preoperative radiotherapy can cause significant morbidity.

Keywords: free flap, free flap failure, risk factors for flap failure, free flap outcome

Procedia PDF Downloads 113
2855 Development of a CFD Model for PCM Based Energy Storage in a Vertical Triplex Tube Heat Exchanger

Authors: Pratibha Biswal, Suyash Morchhale, Anshuman Singh Yadav, Shubham Sanjay Chobe

Abstract:

Energy demands are increasing whereas energy sources, especially non-renewable sources are limited. Due to the intermittent nature of renewable energy sources, it has become the need of the hour to find new ways to store energy. Out of various energy storage methods, latent heat thermal storage devices are becoming popular due to their high energy density per unit mass and volume at nearly constant temperature. This work presents a computational fluid dynamics (CFD) model using ANSYS FLUENT 19.0 for energy storage characteristics of a phase change material (PCM) filled in a vertical triplex tube thermal energy storage system. A vertical triplex tube heat exchanger, just like its name consists of three concentric tubes (pipe sections) for parting the device into three fluid domains. The PCM is filled in the middle domain with heat transfer fluids flowing in the outer and innermost domains. To enhance the heat transfer inside the PCM, eight fins have been incorporated between the internal and external tubes. These fins run radially outwards from the outer-wall of innermost tube to the inner-wall of the middle tube dividing the middle domain (between innermost and middle tube) into eight sections. These eight sections are then filled with a PCM. The validation is carried with earlier work and a grid independence test is also presented. Further studies on freezing and melting process were carried out. The results are presented in terms of pictorial representation of isotherms and liquid fraction

Keywords: heat exchanger, thermal energy storage, phase change material, CFD, latent heat

Procedia PDF Downloads 153
2854 Prediction of Endotracheal Tube Size in Children by Predicting Subglottic Diameter Using Ultrasonographic Measurement versus Traditional Formulas

Authors: Parul Jindal, Shubhi Singh, Priya Ramakrishnan, Shailender Raghuvanshi

Abstract:

Background: Knowledge of the influence of the age of the child on laryngeal dimensions is essential for all practitioners who are dealing with paediatric airway. Choosing the correct endotracheal tube (ETT) size is a crucial step in pediatric patients because a large-sized tube may cause complications like post-extubation stridor and subglottic stenosis. On the other hand with a smaller tube, there will be increased gas flow resistance, aspiration risk, poor ventilation, inaccurate monitoring of end-tidal gases and reintubation may also be required with a different size of the tracheal tube. Recent advancement in ultrasonography (USG) techniques should now allow for accurate and descriptive evaluation of pediatric airway. Aims and objectives: This study was planned to determine the accuracy of Ultrasonography (USG) to assess the appropriate ETT size and compare it with physical indices based formulae. Methods: After obtaining approval from Institute’s Ethical and Research committee, and parental written and informed consent, the study was conducted on 100 subjects of either sex between 12-60 months of age, undergoing various elective surgeries under general anesthesia requiring endotracheal intubation. The same experienced radiologist performed ultrasonography. The transverse diameter was measured at the level of cricoids cartilage by USG. After USG, general anesthesia was administered using standard techniques followed by the institute. An experienced anesthesiologist performed the endotracheal intubations with uncuffed endotracheal tube (Portex Tracheal Tube Smiths Medical India Pvt. Ltd.) with Murphy’s eye. He was unaware of the finding of the ultrasonography. The tracheal tube was considered best fit if air leak was satisfactory at 15-20 cm H₂O of airway pressure. The obtained values were compared with the values of endotracheal tube size calculated by ultrasonography, various age, height, weight-based formulas and diameter of right and left little finger. The correlation of the size of the endotracheal tube by different modalities was done and Pearson's correlation coefficient was obtained. The comparison of the mean size of the endotracheal tube by ultrasonography and by traditional formula was done by the Friedman’s test and Wilcoxon sign-rank test. Results: The predicted tube size was equal to best fit and best determined by ultrasonography (100%) followed by comparison to left little finger (98%) and right little finger (97%) and age-based formula (95%) followed by multivariate formula (83%) and body length (81%) formula. According to Pearson`s correlation, there was a moderate correlation of best fit endotracheal tube with endotracheal tube size by age-based formula (r=0.743), body length based formula (r=0.683), right little finger based formula (r=0.587), left little finger based formula (r=0.587) and multivariate formula (r=0.741). There was a strong correlation with ultrasonography (r=0.943). Ultrasonography was the most sensitive (100%) method of prediction followed by comparison to left (98%) and right (97%) little finger and age-based formula (95%), the multivariate formula had an even lesser sensitivity (83%) whereas body length based formula was least sensitive with a sensitivity of 78%. Conclusion: USG is a reliable method of estimation of subglottic diameter and for prediction of ETT size in children.

Keywords: endotracheal intubation, pediatric airway, subglottic diameter, traditional formulas, ultrasonography

Procedia PDF Downloads 240
2853 Optimization of Structures Subjected to Earthquake

Authors: Alireza Lavaei, Alireza Lohrasbi, Mohammadali M. Shahlaei

Abstract:

To reduce the overall time of structural optimization for earthquake loads two strategies are adopted. In the first strategy, a neural system consisting self-organizing map and radial basis function neural networks, is utilized to predict the time history responses. In this case, the input space is classified by employing a self-organizing map neural network. Then a distinct RBF neural network is trained in each class. In the second strategy, an improved genetic algorithm is employed to find the optimum design. A 72-bar space truss is designed for optimal weight using exact and approximate analysis for the El Centro (S-E 1940) earthquake loading. The numerical results demonstrate the computational advantages and effectiveness of the proposed method.

Keywords: optimization, genetic algorithm, neural networks, self-organizing map

Procedia PDF Downloads 311
2852 Classic Training of a Neural Observer for Estimation Purposes

Authors: R. Loukil, M. Chtourou, T. Damak

Abstract:

This paper investigates the training of multilayer neural network using the classic approach. Then, for estimation purposes, we suggest the use of a specific neural observer that we study its training algorithm which is the back-propagation one in the case of the disponibility of the state and in the case of an unmeasurable state. A MATLAB simulation example will be studied to highlight the usefulness of this kind of observer.

Keywords: training, estimation purposes, neural observer, back-propagation, unmeasurable state

Procedia PDF Downloads 574
2851 Modeling Studies on the Elevated Temperatures Formability of Tube Ends Using RSM

Authors: M. J. Davidson, N. Selvaraj, L. Venugopal

Abstract:

The elevated temperature forming studies on the expansion of thin walled tubes have been studied in the present work. The influence of process parameters namely the die angle, the die ratio and the operating temperatures on the expansion of tube ends at elevated temperatures is carried out. The range of operating parameters have been identified by perfoming extensive simulation studies. The hot forming parameters have been evaluated for AA2014 alloy for performing the simulation studies. Experimental matrix has been developed from the feasible range got from the simulation results. The design of experiments is used for the optimization of process parameters. Response Surface Method’s (RSM) and Box-Behenken design (BBD) is used for developing the mathematical model for expansion. Analysis of variance (ANOVA) is used to analyze the influence of process parameters on the expansion of tube ends. The effect of various process combinations of expansion are analyzed through graphical representations. The developed model is found to be appropriate as the coefficient of determination value is very high and is equal to 0.9726. The predicted values are found to coincide well with the experimental results, within acceptable error limits.

Keywords: expansion, optimization, Response Surface Method (RSM), ANOVA, bbd, residuals, regression, tube

Procedia PDF Downloads 509
2850 Facial Emotion Recognition with Convolutional Neural Network Based Architecture

Authors: Koray U. Erbas

Abstract:

Neural networks are appealing for many applications since they are able to learn complex non-linear relationships between input and output data. As the number of neurons and layers in a neural network increase, it is possible to represent more complex relationships with automatically extracted features. Nowadays Deep Neural Networks (DNNs) are widely used in Computer Vision problems such as; classification, object detection, segmentation image editing etc. In this work, Facial Emotion Recognition task is performed by proposed Convolutional Neural Network (CNN)-based DNN architecture using FER2013 Dataset. Moreover, the effects of different hyperparameters (activation function, kernel size, initializer, batch size and network size) are investigated and ablation study results for Pooling Layer, Dropout and Batch Normalization are presented.

Keywords: convolutional neural network, deep learning, deep learning based FER, facial emotion recognition

Procedia PDF Downloads 274
2849 Contributing Factors to Building Failures and Defects in the Nigerian Construction Industry

Authors: Ndibarafinia Tobin

Abstract:

Building defect and failure are common phenomena in the Nigerian construction industry. The activities of the inexperienced labor force in the Nigerian construction industry have tarnished the image of practicing construction professionals in recent past. Defects and collapse can cause unnecessary expenditure, delays, loss of lives, property and left many people injured. They are also generating controversies among parties involved. Also, if this situation is left unanswered and untreated, it will lead to more serious problems in the future upcoming construction projects in Nigeria. Quite a number of factors are responsible for collapse of high-rise, reinforced concrete buildings in Nigeria. Government, professional bodies and stakeholders are asking countless questions as to who should be responsible and how solutions could be proffered. Therefore this study is aimed to identify the contributing factors to high-rise buildings defects and failures in Nigeria, which frequently occur in construction project in order to minimize time and cost and also the roles of professionals and other participants play in the industry in terms of the use of building materials, placement and curing of concrete, modification in the use of a building, collapse of building induced by fire and other causes. The data is collected from questionnaire from various players in construction industry in Nigeria. This study is succeeds in identifying the causes of building failure and also suggesting possible measures to be taken by government and other regulatory bodies in the building industry to avert this and also improve the effectiveness of managing appraisal process of failures and defects in the future.

Keywords: building defects, building failures, Nigerian construction industry, professionals

Procedia PDF Downloads 297
2848 Parametric Study of 3D Micro-Fin Tubes on Heat Transfer and Friction Factor

Authors: Shima Soleimani, Steven Eckels

Abstract:

One area of special importance for surface-level study of heat exchangers is tubes with internal micro-fins (< 0.5 mm tall). Micro-finned surfaces are a kind of extended solid surface in which energy is exchanged with water that acts as the source or sink of energy. Significant performance gains are possible for either shell, tube, or double pipe heat exchangers if the best surfaces are identified. The parametric studies of micro-finned tubes that have appeared in the literature left some key parameters unexplored. Specifically, they ignored three-dimensional (3D) micro-fin configurations, conduction heat transfer in the fins, and conduction in the solid surface below the micro-fins. Thus, this study aimed at implementing a parametric study of 3D micro-finned tubes that considered micro-fin height and discontinuity features. A 3D conductive and convective heat-transfer simulation through coupled solid and periodic fluid domains is applied in a commercial package, ANSYS Fluent 19.1. The simulation is steady-state with turbulent water flow cooling inner wall of a tube with micro-fins. The simulation utilizes a constant and uniform temperature on the tube outer wall. Performance is mapped for 18 different simulation cases, including a smooth tube using a realizable k-ε turbulence model at a Reynolds number of 48,928. Results compared the performance of 3D tubes with results for the similar two-dimensional (2D) one. Results showed that the micro-fin height has greater impact on performance factor than discontinuity features in 3D micro-fin tubes. A transformed 3D micro-fin tube can enhance heat transfer and pressure drop up to 21% and 56% compared to a 2D one, respectfully.

Keywords: three-dimensional micro-finned tube, heat transfer, friction factor, heat exchanger

Procedia PDF Downloads 115
2847 Simulation and Optimization of an Annular Methanol Reformer

Authors: Shu-Bo Yang, Wei Wu, Yuan-Heng Liu

Abstract:

This research aims to design a heat-exchanger type of methanol reformer coupled with a preheating design in gPROMS® environment. The endothermic methanol steam reforming reaction (MSR) and the exothermic preferential oxidation reaction (PROX) occur in the inner tube and the outer tube of the reformer, respectively. The effective heat transfer manner between the inner and outer tubes is investigated. It is verified that the countercurrent-flow type reformer provides the higher hydrogen yield than the cocurrent-flow type. Since the hot spot temperature appears in the outer tube, an improved scheme is proposed to suppress the hot spot temperature by splitting the excess air flowing into two sites. Finally, an optimization algorithm for maximizing the hydrogen yield is employed to determine optimal operating conditions.

Keywords: methanol reformer, methanol steam reforming, optimization, simulation

Procedia PDF Downloads 332
2846 Neural Style Transfer Using Deep Learning

Authors: Shaik Jilani Basha, Inavolu Avinash, Alla Venu Sai Reddy, Bitragunta Taraka Ramu

Abstract:

We can use the neural style transfer technique to build a picture with the same "content" as the beginning image but the "style" of the picture we've chosen. Neural style transfer is a technique for merging the style of one image into another while retaining its original information. The only change is how the image is formatted to give it an additional artistic sense. The content image depicts the plan or drawing, as well as the colors of the drawing or paintings used to portray the style. It is a computer vision programme that learns and processes images through deep convolutional neural networks. To implement software, we used to train deep learning models with the train data, and whenever a user takes an image and a styled image, the output will be as the style gets transferred to the original image, and it will be shown as the output.

Keywords: neural networks, computer vision, deep learning, convolutional neural networks

Procedia PDF Downloads 95
2845 Nonlinear Defects and Discombinations in Anisotropic Solids

Authors: Ashkan Golgoon, Arash Yavari

Abstract:

In this paper, we present some analytical solutions for the stress fields of nonlinear anisotropic solids with line and point defects distributions. In particular, we determine the induced stress fields of a parallel cylindrically-symmetric distribution of screw dislocations in infinite orthotropic and monoclinic media as well as a cylindrically-symmetric distribution of parallel wedge disclinations in an infinite orthotropic medium. For a given distribution of edge dislocations, the material manifold is constructed using Cartan's moving frames and the stress field is obtained assuming that the medium is orthotropic. Also, we consider a spherically-symmetric distribution of point defects in a transversely isotropic spherical ball. We show that for an arbitrary incompressible transversely isotropic ball with the radial material preferred direction, a uniform point defect distribution results in a uniform hydrostatic stress field inside the spherical region the distribution is supported in. Finally, we find the stresses induced by a discombination in an orthotropic medium.

Keywords: defects, disclinations, dislocations, monoclinic solids, nonlinear elasticity, orthotropic solids, transversely isotropic solids

Procedia PDF Downloads 254
2844 A Polyimide Based Split-Ring Neural Interface Electrode for Neural Signal Recording

Authors: Ning Xue, Srinivas Merugu, Ignacio Delgado Martinez, Tao Sun, John Tsang, Shih-Cheng Yen

Abstract:

We have developed a polyimide based neural interface electrode to record nerve signals from the sciatic nerve of a rat. The neural interface electrode has a split-ring shape, with four protruding gold electrodes for recording, and two reference gold electrodes around the split-ring. The split-ring electrode can be opened up to encircle the sciatic nerve. The four electrodes can be bent to sit on top of the nerve and hold the device in position, while the split-ring frame remains flat. In comparison, while traditional cuff electrodes can only fit certain sizes of the nerve, the developed device can fit a variety of rat sciatic nerve dimensions from 0.6 mm to 1.0 mm, and adapt to the chronic changes in the nerve as the electrode tips are bendable. The electrochemical impedance spectroscopy measurement was conducted. The gold electrode impedance is on the order of 10 kΩ, showing excellent charge injection capacity to record neural signals.

Keywords: impedance, neural interface, split-ring electrode, neural signal recording

Procedia PDF Downloads 376
2843 Neural Networks with Different Initialization Methods for Depression Detection

Authors: Tianle Yang

Abstract:

As a common mental disorder, depression is a leading cause of various diseases worldwide. Early detection and treatment of depression can dramatically promote remission and prevent relapse. However, conventional ways of depression diagnosis require considerable human effort and cause economic burden, while still being prone to misdiagnosis. On the other hand, recent studies report that physical characteristics are major contributors to the diagnosis of depression, which inspires us to mine the internal relationship by neural networks instead of relying on clinical experiences. In this paper, neural networks are constructed to predict depression from physical characteristics. Two initialization methods are examined - Xaiver and Kaiming initialization. Experimental results show that a 3-layers neural network with Kaiming initialization achieves 83% accuracy.

Keywords: depression, neural network, Xavier initialization, Kaiming initialization

Procedia PDF Downloads 128
2842 Parametric Study of 3D Micro-Fin Tubes on Heat Transfer and Friction Factor

Authors: Shima Soleimani, Steven Eckels

Abstract:

One area of special importance for the surface-level study of heat exchangers is tubes with internal micro-fins (< 0.5 mm tall). Micro-finned surfaces are a kind of extended solid surface in which energy is exchanged with water that acts as the source or sink of energy. Significant performance gains are possible for either shell, tube, or double pipe heat exchangers if the best surfaces are identified. The parametric studies of micro-finned tubes that have appeared in the literature left some key parameters unexplored. Specifically, they ignored three-dimensional (3D) micro-fin configurations, conduction heat transfer in the fins, and conduction in the solid surface below the micro-fins. Thus, this study aimed at implementing a parametric study of 3D micro-finned tubes that considered micro-fine height and discontinuity features. A 3D conductive and convective heat-transfer simulation through coupled solid and periodic fluid domains is applied in a commercial package, ANSYS Fluent 19.1. The simulation is steady-state with turbulent water flow cooling the inner wall of a tube with micro-fins. The simulation utilizes a constant and uniform temperature on the tube outer wall. Performance is mapped for 18 different simulation cases, including a smooth tube using a realizable k-ε turbulence model at a Reynolds number of 48,928. Results compared the performance of 3D tubes with results for the similar two-dimensional (2D) one. Results showed that the micro-fine height has a greater impact on performance factors than discontinuity features in 3D micro-fin tubes. A transformed 3D micro-fin tube can enhance heat transfer, and pressure drops up to 21% and 56% compared to a 2D one, respectfully.

Keywords: three-dimensional micro-fin tube, heat transfer, friction factor, heat exchanger

Procedia PDF Downloads 118
2841 Parametrical Simulation of Sheet Metal Forming Process to Control the Localized Thinning

Authors: Hatem Mrad, Alban Notin, Mohamed Bouazara

Abstract:

Sheet metal forming process has a multiple successive steps starting from sheets fixation to sheets evacuation. Often after forming operation, the sheet has defects requiring additional corrections steps. For example, in the drawing process, the formed sheet may have several defects such as springback, localized thinning and bends. All these defects are directly dependent on process, geometric and material parameters. The prediction and elimination of these defects requires the control of most sensitive parameters. The present study is concerned with a reliable parametric study of deep forming process in order to control the localized thinning. The proposed approach will be based on stochastic finite element method. Especially, the polynomial Chaos development will be used to establish a reliable relationship between input (process, geometric and material parameters) and output variables (sheet thickness). The commercial software Abaqus is used to conduct numerical finite elements simulations. The automatized parametrical modification is provided by coupling a FORTRAN routine, a PYTHON script and input Abaqus files.

Keywords: sheet metal forming, reliability, localized thinning, parametric simulation

Procedia PDF Downloads 423
2840 Fault Diagnosis of Squirrel-Cage Induction Motor by a Neural Network Multi-Models

Authors: Yahia. Kourd, N. Guersi D. Lefebvre

Abstract:

In this paper we propose to study the faults diagnosis in squirrel-cage induction motor using MLP neural networks. We use neural healthy and faulty models of the behavior in order to detect and isolate some faults in machine. In the first part of this work, we have created a neural model for the healthy state using Matlab and a motor located in LGEB by acquirins data inputs and outputs of this engine. Then we detected the faults in the machine by residual generation. These residuals are not sufficient to isolate the existing faults. For this reason, we proposed additive neural networks to represent the faulty behaviors. From the analysis of these residuals and the choice of a threshold we propose a method capable of performing the detection and diagnosis of some faults in asynchronous machines with squirrel cage rotor.

Keywords: faults diagnosis, neural networks, multi-models, squirrel-cage induction motor

Procedia PDF Downloads 636
2839 A Two-Step Framework for Unsupervised Speaker Segmentation Using BIC and Artificial Neural Network

Authors: Ahmad Alwosheel, Ahmed Alqaraawi

Abstract:

This work proposes a new speaker segmentation approach for two speakers. It is an online approach that does not require a prior information about speaker models. It has two phases, a conventional approach such as unsupervised BIC-based is utilized in the first phase to detect speaker changes and train a Neural Network, while in the second phase, the output trained parameters from the Neural Network are used to predict next incoming audio stream. Using this approach, a comparable accuracy to similar BIC-based approaches is achieved with a significant improvement in terms of computation time.

Keywords: artificial neural network, diarization, speaker indexing, speaker segmentation

Procedia PDF Downloads 502
2838 Spontaneous Reformation of Dehiscent Frontal Sinus Wall after Endoscopic Removal of Mucocele

Authors: Tan Dexian Arthur, James Wei Ming Kwek, Ian Loh, Lee Tee Sin

Abstract:

Statement of the Problem: Mucoceles most commonly affect the frontal sinus, which results from chronic obstruction of the sinus ostium or cystic dilatation of mucous glands with ductal obstruction. They are known to cause bony erosion of the sinus walls, which can lead to large defects. These defects were typically managed by obliteration or cranialization of the frontal sinus. Although short term outcomes of conservative management of significant posterior table defects from fractures are promising, there have been no studies on the long-term outcomes of large dehiscences in the posterior wall of the frontal sinus. Methodology & Findings : Computed Tomography (CT) Paranasal Sinuses images were analyzed and found complete spontaneous osteogenesis of a large dehiscent frontal sinus posterior wall, secondary to a large mucocele, 9 years from functional endoscopic sinus surgery with the defect managed conservatively. Conclusion & Significance: The dura is well known for its osteogenic properties. Prior studies have showed that dura could induce osteogenesis in cutaneous tissue in the absence of other central nervous system structures. It was also demonstrated that osteogenesis and chondrogenesis were possible in zygomatic fractures by transplanting neonatal dura grafts to the bony defects in rats. Extrapolating from these studies, the authors postulate that the presence of dura beneath the bony deformity of the posterior frontal sinus wall had likely initiated the osteogenesis and restored the bony defect in the patient. In our literature review, we did not find any reports of spontaneous osteogenesis of large frontal sinus defects. While our experience is incidental, it reinforces the osteogenetic potential of an intact dura and further highlights that selected large defects of the posterior wall of the frontal sinus can be conservatively managed.

Keywords: paranasal sinus mucocele, mucocele, osteogenesis, dehiscence

Procedia PDF Downloads 64
2837 Study of 'Rolled in Scale' and 'Rolled in Scum' in Automotive Grade Cold-Rolled Annealed Steel Sheet

Authors: Soumendu Monia, Vaibhav Jain, Hrishikesh Jugade, Manashi Adhikary, Goutam Mukhopadhyay

Abstract:

'Rolled in scale' (RIS) and 'Rolled in Scum' (RISc) are two superficial surface defects on cold rolled and annealed steel sheets which affect the aesthetics of surface and thereby that of the end-product. Both the defects are believed to be originating from distinctly different sources having different mechanisms of formation. However, due to their similar physical appearance, RIS and RISc are generally confused with each other and hence attaining the exact root cause for elimination of the defect becomes difficult. RIS appears irregular in shape, sometimes scattered, and always oriented in rolling direction. RISc is generally oval shaped, having identifiable pointed edges and mostly oriented in rolling direction. Visually, RIS appears to be greyish in colour whereas RISc is whitish in colour. Both the defects have quite random occurrence and do not leave any imprints on the reverse-side of the sheet. In the current study, an attempt has been made to differentiate these two similar looking surface defects using various metallographic and characterization techniques. Systematic experiments have been carried out to identify possible mechanisms of formation of these defects. Detailed characterization revealed basic differences between RIS and RISc with respect to their surface morphology. To summarize, RIS was observed as a residue of an otherwise under-pickled scale patch on surface, after it has been subjected to cold rolling and annealing in a batch/continuous furnace. Whereas RISc was found to be a localized rubbing of the surface, at the time of cold rolling itself, resulting in a rough surface texture.

Keywords: annealing, rolled in scale, rolled in scum, skin panel

Procedia PDF Downloads 187
2836 Feedforward Neural Network with Backpropagation for Epilepsy Seizure Detection

Authors: Natalia Espinosa, Arthur Amorim, Rudolf Huebner

Abstract:

Epilepsy is a chronic neural disease and around 50 million people in the world suffer from this disease, however, in many cases, the individual acquires resistance to the medication, which is known as drug-resistant epilepsy, where a detection system is necessary. This paper showed the development of an automatic system for seizure detection based on artificial neural networks (ANN), which are common techniques of machine learning. Discrete Wavelet Transform (DWT) is used for decomposing electroencephalogram (EEG) signal into main brain waves, with these frequency bands is extracted features for training a feedforward neural network with backpropagation, finally made a pattern classification, seizure or non-seizure. Obtaining 95% accuracy in epileptic EEG and 100% in normal EEG.

Keywords: Artificial Neural Network (ANN), Discrete Wavelet Transform (DWT), Epilepsy Detection , Seizure.

Procedia PDF Downloads 223