Search results for: linear motor motion stage
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8565

Search results for: linear motor motion stage

7545 Stochastic Model Predictive Control for Linear Discrete-Time Systems with Random Dither Quantization

Authors: Tomoaki Hashimoto

Abstract:

Recently, feedback control systems using random dither quantizers have been proposed for linear discrete-time systems. However, the constraints imposed on state and control variables have not yet been taken into account for the design of feedback control systems with random dither quantization. Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial and terminal time. An important advantage of model predictive control is its ability to handle constraints imposed on state and control variables. Based on the model predictive control approach, the objective of this paper is to present a control method that satisfies probabilistic state constraints for linear discrete-time feedback control systems with random dither quantization. In other words, this paper provides a method for solving the optimal control problems subject to probabilistic state constraints for linear discrete-time feedback control systems with random dither quantization.

Keywords: optimal control, stochastic systems, random dither, quantization

Procedia PDF Downloads 445
7544 Retrieving Similar Segmented Objects Using Motion Descriptors

Authors: Konstantinos C. Kartsakalis, Angeliki Skoura, Vasileios Megalooikonomou

Abstract:

The fuzzy composition of objects depicted in images acquired through MR imaging or the use of bio-scanners has often been a point of controversy for field experts attempting to effectively delineate between the visualized objects. Modern approaches in medical image segmentation tend to consider fuzziness as a characteristic and inherent feature of the depicted object, instead of an undesirable trait. In this paper, a novel technique for efficient image retrieval in the context of images in which segmented objects are either crisp or fuzzily bounded is presented. Moreover, the proposed method is applied in the case of multiple, even conflicting, segmentations from field experts. Experimental results demonstrate the efficiency of the suggested method in retrieving similar objects from the aforementioned categories while taking into account the fuzzy nature of the depicted data.

Keywords: fuzzy object, fuzzy image segmentation, motion descriptors, MRI imaging, object-based image retrieval

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7543 Data Augmentation for Early-Stage Lung Nodules Using Deep Image Prior and Pix2pix

Authors: Qasim Munye, Juned Islam, Haseeb Qureshi, Syed Jung

Abstract:

Lung nodules are commonly identified in computed tomography (CT) scans by experienced radiologists at a relatively late stage. Early diagnosis can greatly increase survival. We propose using a pix2pix conditional generative adversarial network to generate realistic images simulating early-stage lung nodule growth. We have applied deep images prior to 2341 slices from 895 computed tomography (CT) scans from the Lung Image Database Consortium (LIDC) dataset to generate pseudo-healthy medical images. From these images, 819 were chosen to train a pix2pix network. We observed that for most of the images, the pix2pix network was able to generate images where the nodule increased in size and intensity across epochs. To evaluate the images, 400 generated images were chosen at random and shown to a medical student beside their corresponding original image. Of these 400 generated images, 384 were defined as satisfactory - meaning they resembled a nodule and were visually similar to the corresponding image. We believe that this generated dataset could be used as training data for neural networks to detect lung nodules at an early stage or to improve the accuracy of such networks. This is particularly significant as datasets containing the growth of early-stage nodules are scarce. This project shows that the combination of deep image prior and generative models could potentially open the door to creating larger datasets than currently possible and has the potential to increase the accuracy of medical classification tasks.

Keywords: medical technology, artificial intelligence, radiology, lung cancer

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7542 Constant Order Predictor Corrector Method for the Solution of Modeled Problems of First Order IVPs of ODEs

Authors: A. A. James, A. O. Adesanya, M. R. Odekunle, D. G. Yakubu

Abstract:

This paper examines the development of one step, five hybrid point method for the solution of first order initial value problems. We adopted the method of collocation and interpolation of power series approximate solution to generate a continuous linear multistep method. The continuous linear multistep method was evaluated at selected grid points to give the discrete linear multistep method. The method was implemented using a constant order predictor of order seven over an overlapping interval. The basic properties of the derived corrector was investigated and found to be zero stable, consistent and convergent. The region of absolute stability was also investigated. The method was tested on some numerical experiments and found to compete favorably with the existing methods.

Keywords: interpolation, approximate solution, collocation, differential system, half step, converges, block method, efficiency

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7541 Obtaining the Analytic Dependence for Estimating the Ore Mill Operation Modes

Authors: Baghdasaryan Marinka

Abstract:

The particular significance of comprehensive estimation of the increase in the operation efficiency of the mill motor electromechanical system, providing the main technological process for obtaining a metallic concentrate, as well as the technical state of the system are substantiated. The works carried out in the sphere of investigating, creating, and improving the operation modes of electric drive motors and ore-grinding mills have been studied. Analytic dependences for estimating the operation modes of the ore-grinding mills aimed at improving the ore-crashing process maintenance and technical service efficiencies have been obtained. The obtained analytic dependencies establish a link between the technological and power parameters of the electromechanical system, and allow to estimate the state of the system and reveal the controlled parameters required for the efficient management in case of changing the technological parameters. It has been substantiated that the changes in the technological factors affecting the consumption power of the drive motor do not cause an instability in the electromechanical system.

Keywords: electromechanical system, estimation, operation mode, productivity, technological process, the mill filling degree

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7540 A Mathematical Model for 3-DOF Rotary Accuracy Measurement Method Based on a Ball Lens

Authors: Hau-Wei Lee, Yu-Chi Liu, Chien-Hung Liu

Abstract:

A mathematical model is presented for a system that measures rotational errors in a shaft using a ball lens. The geometric optical characteristics of the ball lens mounted on the shaft allows the measurement of rotation axis errors in both the radial and axial directions. The equipment used includes two quadrant detectors (QD), two laser diodes and a ball lens that is mounted on the rotating shaft to be evaluated. Rotational errors in the shaft cause changes in the optical geometry of the ball lens. The resulting deflection of the laser beams is detected by the QDs and their output signals are used to determine rotational errors. The radial and the axial rotational errors can be calculated as explained by the mathematical model. Results from system calibration show that the measurement error is within ±1 m and resolution is about 20 nm. Using a direct drive motor (DD motor) as an example, experimental results show a rotational error of less than 20 m. The most important features of this system are that it does not require the use of expensive optical components, it is small, very easy to set up, and measurements are highly accurate.

Keywords: ball lens, quadrant detector, axial error, radial error

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7539 Decentralized Control of Interconnected Systems with Non-Linear Unknown Interconnections

Authors: Haci Mehmet Guzey, Levent Acar

Abstract:

In this paper, a novel decentralized controller is developed for linear systems with nonlinear unknown interconnections. A model linear decoupled system is assigned for each system. By using the difference actual and model state dynamics, the problem is formulated as inverse problem. Then, the interconnected dynamics are approximated by using Galerkin’s expansion method for inverse problems. Two different sets of orthogonal basis functions are utilized to approximate the interconnected dynamics. Approximated interconnections are utilized in the controller to cancel the interconnections and decouple the systems. Subsequently, the interconnected systems behave as a collection of decoupled systems.

Keywords: decentralized control, inverse problems, large scale systems, nonlinear interconnections, basis functions, system identification

Procedia PDF Downloads 532
7538 Response of Chickpea (Cicer arietinum L.) Genotypes to Drought Stress at Different Growth Stages

Authors: Ali. Marjani, M. Farsi, M. Rahimizadeh

Abstract:

Chickpea (Cicer arietinum L.) is one of the important grain legume crops in the world. However, drought stress is a serious threat to chickpea production, and development of drought-resistant varieties is a necessity. Field experiments were conducted to evaluate the response of 8 chickpea genotypes (MCC* 696, 537, 80, 283, 392, 361, 252, 397) and drought stress (S1: non-stress, S2: stress at vegetative growth stage, S3: stress at early bloom, S4: stress at early pod visible) at different growth stages. Experiment was arranged in split plot design with four replications. Difference among the drought stress time was found to be significant for investigated traits except biological yield. Differences were observed for genotypes in flowering time, pod information time, physiological maturation time and yield. Plant height reduced due to drought stress in vegetative growth stage. Stem dry weight reduced due to drought stress in pod visibly. Flowering time, maturation time, pod number, number of seed per plant and yield cause of drought stress in flowering was also reduced. The correlation between yield and number of seed per plant and biological yield was positive. The MCC283 and MCC696 were the high-tolerance genotypes. These results demonstrated that drought stress delayed phonological growth in chickpea and that flowering stage is sensitive.

Keywords: chickpea, drought stress, growth stage, tolerance

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7537 Development of a Systematic Approach to Assess the Applicability of Silver Coated Conductive Yarn

Authors: Y. T. Chui, W. M. Au, L. Li

Abstract:

Recently, wearable electronic textiles have been emerging in today’s market and were developed rapidly since, beside the needs for the clothing uses for leisure, fashion wear and personal protection, there also exist a high demand for the clothing to be capable for function in this electronic age, such as interactive interfaces, sensual being and tangible touch, social fabric, material witness and so on. With the requirements of wearable electronic textiles to be more comfortable, adorable, and easy caring, conductive yarn becomes one of the most important fundamental elements within the wearable electronic textile for interconnection between different functional units or creating a functional unit. The properties of conductive yarns from different companies can vary to a large extent. There are vitally important criteria for selecting the conductive yarns, which may directly affect its optimization, prospect, applicability and performance of the final garment. However, according to the literature review, few researches on conductive yarns on shelf focus on the assessment methods of conductive yarns for the scientific selection of material by a systematic way under different conditions. Therefore, in this study, direction of selecting high-quality conductive yarns is given. It is to test the stability and reliability of the conductive yarns according the problems industrialists would experience with the yarns during the every manufacturing process, in which, this assessment system can be classified into four stage. That is 1) Yarn stage, 2) Fabric stage, 3) Apparel stage and 4) End user stage. Several tests with clear experiment procedures and parameters are suggested to be carried out in each stage. This assessment method suggested that the optimal conducting yarns should be stable in property and resistant to various corrosions at every production stage or during using them. It is expected that this demonstration of assessment method can serve as a pilot study that assesses the stability of Ag/nylon yarns systematically at various conditions, i.e. during mass production with textile industry procedures, and from the consumer perspective. It aims to assist industrialists to understand the qualities and properties of conductive yarns and suggesting a few important parameters that they should be reminded of for the case of higher level of suitability, precision and controllability.

Keywords: applicability, assessment method, conductive yarn, wearable electronics

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7536 Using Machine Learning to Build a Real-Time COVID-19 Mask Safety Monitor

Authors: Yash Jain

Abstract:

The US Center for Disease Control has recommended wearing masks to slow the spread of the virus. The research uses a video feed from a camera to conduct real-time classifications of whether or not a human is correctly wearing a mask, incorrectly wearing a mask, or not wearing a mask at all. Utilizing two distinct datasets from the open-source website Kaggle, a mask detection network had been trained. The first dataset that was used to train the model was titled 'Face Mask Detection' on Kaggle, where the dataset was retrieved from and the second dataset was titled 'Face Mask Dataset, which provided the data in a (YOLO Format)' so that the TinyYoloV3 model could be trained. Based on the data from Kaggle, two machine learning models were implemented and trained: a Tiny YoloV3 Real-time model and a two-stage neural network classifier. The two-stage neural network classifier had a first step of identifying distinct faces within the image, and the second step was a classifier to detect the state of the mask on the face and whether it was worn correctly, incorrectly, or no mask at all. The TinyYoloV3 was used for the live feed as well as for a comparison standpoint against the previous two-stage classifier and was trained using the darknet neural network framework. The two-stage classifier attained a mean average precision (MAP) of 80%, while the model trained using TinyYoloV3 real-time detection had a mean average precision (MAP) of 59%. Overall, both models were able to correctly classify stages/scenarios of no mask, mask, and incorrectly worn masks.

Keywords: datasets, classifier, mask-detection, real-time, TinyYoloV3, two-stage neural network classifier

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7535 Optimal Placement of Phasor Measurement Units Using Gravitational Search Method

Authors: Satyendra Pratap Singh, S. P. Singh

Abstract:

This paper presents a methodology using Gravitational Search Algorithm for optimal placement of Phasor Measurement Units (PMUs) in order to achieve complete observability of the power system. The objective of proposed algorithm is to minimize the total number of PMUs at the power system buses, which in turn minimize installation cost of the PMUs. In this algorithm, the searcher agents are collection of masses which interact with each other using Newton’s laws of gravity and motion. This new Gravitational Search Algorithm based method has been applied to the IEEE 14-bus, IEEE 30-bus and IEEE 118-bus test systems. Case studies reveal optimal number of PMUs with better observability by proposed method.

Keywords: gravitational search algorithm (GSA), law of motion, law of gravity, observability, phasor measurement unit

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7534 Overlaps and Intersections: An Alternative Look at Choreography

Authors: Ashlie Latiolais

Abstract:

Architecture, as a discipline, is on a trajectory of extension beyond the boundaries of buildings and, more increasingly, is coupled with research that connects to alternative and typically disjointed disciplines. A “both/and” approach and (expanded) definition of architecture, as depicted here, expands the margins that contain the profession. Figuratively, architecture is a series of edges, events, and occurrences that establishes a choreography or stage by which humanity exists. The way in which architecture controls and suggests the movement through these spaces, being within a landscape, city, or building, can be viewed as a datum by which the “dance” of everyday life occurs. This submission views the realm of architecture through the lens of movement and dance as a cross-fertilizer of collaboration, tectonic, and spatial geometry investigations. “Designing on digital programs puts architects at a distance from the spaces they imagine. While this has obvious advantages, it also means that they lose the lived, embodied experience of feeling what is needed in space—meaning that some design ideas that work in theory ultimately fail in practice.” By studying the body in motion through real-time performance, a more holistic understanding of architectural space surfaces and new prospects for theoretical teaching pedagogies emerge. The atypical intersection rethinks how architecture is considered, created, and tested, similar to how “dance artists often do this by thinking through the body, opening pathways and possibilities that might not otherwise be accessible” –this is the essence of this poster submission as explained through unFOLDED, a creative performance work. A new languageismaterialized through unFOLDED, a dynamic occupiable installation by which architecture is investigated through dance, movement, and body analysis. The entry unfolds a collaboration of an architect, dance choreographer, musicians, video artist, and lighting designers to re-create one of the first documented avant-garde performing arts collaborations (Matisse, Satie, Massine, Picasso) from the Ballet Russes in 1917, entitled Parade. Architecturally, this interdisciplinary project orients and suggests motion through structure, tectonic, lightness, darkness, and shadow as it questions the navigation of the dark space (stage) surrounding the installation. Artificial light via theatrical lighting and video graphics brought the blank canvas to life – where the sensitive mix of musicality coordinated with the structure’s movement sequencing was certainly a challenge. The upstage light from the video projections created both flickered contextual imagery and shadowed figures. When the dancers were either upstage or downstage of the structure, both silhouetted figures and revealed bodies are experienced as dancer-controlled installation manipulations occurred throughout the performance. The experimental performance, through structure, prompted moving (dancing) bodies in space, where the architecture served as a key component to the choreography itself. The tectonic of the delicate steel structure allowed for the dancers to interact with the installation, which created a variety of spatial conditions – the contained box of three-dimensional space, to a wall, and various abstracted geometries in between. The development of this research unveils the new role of an Architect as a Choreographer of the built environment.

Keywords: dance, architecture, choreography, installation, architect, choreographer, space

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7533 Novel Hole-Bar Standard Design and Inter-Comparison for Geometric Errors Identification on Machine-Tool

Authors: F. Viprey, H. Nouira, S. Lavernhe, C. Tournier

Abstract:

Manufacturing of freeform parts may be achieved on 5-axis machine tools currently considered as a common means of production. In particular, the geometrical quality of the freeform parts depends on the accuracy of the multi-axis structural loop, which is composed of several component assemblies maintaining the relative positioning between the tool and the workpiece. Therefore, to reach high quality of the geometries of the freeform parts the geometric errors of the 5 axis machine should be evaluated and compensated, which leads one to master the deviations between the tool and the workpiece (volumetric accuracy). In this study, a novel hole-bar design was developed and used for the characterization of the geometric errors of a RRTTT 5-axis machine tool. The hole-bar standard design is made of Invar material, selected since it is less sensitive to thermal drift. The proposed design allows once to extract 3 intrinsic parameters: one linear positioning and two straightnesses. These parameters can be obtained by measuring the cylindricity of 12 holes (bores) and 11 cylinders located on a perpendicular plane. By mathematical analysis, twelve 3D points coordinates can be identified and correspond to the intersection of each hole axis with the least square plane passing through two perpendicular neighbour cylinders axes. The hole-bar was calibrated using a precision CMM at LNE traceable the SI meter definition. The reversal technique was applied in order to separate the error forms of the hole bar from the motion errors of the mechanical guiding systems. An inter-comparison was additionally conducted between four NMIs (National Metrology Institutes) within the EMRP IND62: JRP-TIM project. Afterwards, the hole-bar was integrated in RRTTT 5-axis machine tool to identify its volumetric errors. Measurements were carried out in real time and combine raw data acquired by the Renishaw RMP600 touch probe and the linear and rotary encoders. The geometric errors of the 5 axis machine were also evaluated by an accurate laser tracer interferometer system. The results were compared to those obtained with the hole bar.

Keywords: volumetric errors, CMM, 3D hole-bar, inter-comparison

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7532 Non-Linear Free Vibration Analysis of Laminated Composite Beams Resting on Non-Linear Pasternak Elastic Foundation: A Homogenization Procedure

Authors: Merrimi El Bekkaye, El Bikri Khalid, Benamar Rhali

Abstract:

In the present paper, the problem of geometrically non-linear free vibration of symmetrically and asymmetrically laminated composite beams (LCB) resting on nonlinear Pasternak elastic Foundation with immovable ends is studied. A homogenization procedure has been performed to reduce the problem under consideration to that of the isotropic homogeneous beams with effective bending stiffness and axial stiffness parameters. This simple formulation is developed using the governing axial equation of the beam in which the axial inertia and damping are ignored. The theoretical model is based on Hamilton’s principle and spectral analysis. Iterative form solutions are presented to calculate the fundamental nonlinear frequency parameters which are found to be in a good agreement with the published results. On the other hand, the influence of the foundation parameters on the nonlinear frequency to the linear frequency ratio of the LCB has been studied. The non-dimensional curvatures associated to the fundamental mode are also given in the case of clamped-clamped symmetrically and asymmetrically laminated composite beams.

Keywords: large vibration amplitudes, laminated composite beam, Pasternak foundation, composite beams

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7531 Design and Control of a Brake-by-Wire System Using a Permanent Magnet Synchronous Motor

Authors: Daniel S. Gamba, Marc Sánchez, Javier Pérez, Juan J. Castillo, Juan A. Cabrera

Abstract:

The conventional hydraulic braking system operates through the activation of a master cylinder and solenoid valves that distribute and regulate brake fluid flow, adjusting the pressure at each wheel to prevent locking during sudden braking. However, in recent years, there has been a significant increase in the integration of electronic units into various vehicle control systems. In this context, one of the technologies most recently researched is the Brake-by-wire system, which combines electronic, hydraulic, and mechanical technologies to manage braking. This proposal introduces the design and control of a Brake-by-wire system, which will be part of a fully electric and teleoperated vehicle. This vehicle will have independent four-wheel drive, braking, and steering systems. The vehicle will be operated by embedded controllers programmed into a Speedgoat test system, which allows programming through Simulink and real-time capabilities. The braking system comprises all mechanical and electrical components, a vehicle control unit (VCU), and an electronic control unit (ECU). The mechanical and electrical components include a permanent magnet synchronous motor from Odrive and its inverter, the mechanical transmission system responsible for converting torque into pressure, and the hydraulic system that transmits this pressure to the brake caliper. The VCU is responsible for controlling the pressure and communicates with the other components through the CAN protocol, minimizing response times. The ECU, in turn, transmits the information obtained by a sensor installed in the caliper to the central computer, enabling the control loop to continuously regulate pressure by controlling the motor's speed and current. To achieve this, tree controllers are used, operating in a nested configuration for effective control. Since the computer allows programming in Simulink, a digital model of the braking system has been developed in Simscape, which makes it possible to reproduce different operating conditions, faithfully simulate the performance of alternative brake control systems, and compare the results with data obtained in various real tests. These tests involve evaluating the system's response to sinusoidal and square wave inputs at different frequencies, with the results compared to those obtained from conventional braking systems.

Keywords: braking, CAN protocol, permanent magnet motor, pressure control

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7530 Development of a Decision-Making Method by Using Machine Learning Algorithms in the Early Stage of School Building Design

Authors: Pegah Eshraghi, Zahra Sadat Zomorodian, Mohammad Tahsildoost

Abstract:

Over the past decade, energy consumption in educational buildings has steadily increased. The purpose of this research is to provide a method to quickly predict the energy consumption of buildings using separate evaluation of zones and decomposing the building to eliminate the complexity of geometry at the early design stage. To produce this framework, machine learning algorithms such as Support vector regression (SVR) and Artificial neural network (ANN) are used to predict energy consumption and thermal comfort metrics in a school as a case. The database consists of more than 55000 samples in three climates of Iran. Cross-validation evaluation and unseen data have been used for validation. In a specific label, cooling energy, it can be said the accuracy of prediction is at least 84% and 89% in SVR and ANN, respectively. The results show that the SVR performed much better than the ANN.

Keywords: early stage of design, energy, thermal comfort, validation, machine learning

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7529 A Statistical Approach to Predict and Classify the Commercial Hatchability of Chickens Using Extrinsic Parameters of Breeders and Eggs

Authors: M. S. Wickramarachchi, L. S. Nawarathna, C. M. B. Dematawewa

Abstract:

Hatchery performance is critical for the profitability of poultry breeder operations. Some extrinsic parameters of eggs and breeders cause to increase or decrease the hatchability. This study aims to identify the affecting extrinsic parameters on the commercial hatchability of local chicken's eggs and determine the most efficient classification model with a hatchability rate greater than 90%. In this study, seven extrinsic parameters were considered: egg weight, moisture loss, breeders age, number of fertilised eggs, shell width, shell length, and shell thickness. Multiple linear regression was performed to determine the most influencing variable on hatchability. First, the correlation between each parameter and hatchability were checked. Then a multiple regression model was developed, and the accuracy of the fitted model was evaluated. Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), k-Nearest Neighbors (kNN), Support Vector Machines (SVM) with a linear kernel, and Random Forest (RF) algorithms were applied to classify the hatchability. This grouping process was conducted using binary classification techniques. Hatchability was negatively correlated with egg weight, breeders' age, shell width, shell length, and positive correlations were identified with moisture loss, number of fertilised eggs, and shell thickness. Multiple linear regression models were more accurate than single linear models regarding the highest coefficient of determination (R²) with 94% and minimum AIC and BIC values. According to the classification results, RF, CART, and kNN had performed the highest accuracy values 0.99, 0.975, and 0.972, respectively, for the commercial hatchery process. Therefore, the RF is the most appropriate machine learning algorithm for classifying the breeder outcomes, which are economically profitable or not, in a commercial hatchery.

Keywords: classification models, egg weight, fertilised eggs, multiple linear regression

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7528 Nonlinear Vibration of FGM Plates Subjected to Acoustic Load in Thermal Environment Using Finite Element Modal Reduction Method

Authors: Hassan Parandvar, Mehrdad Farid

Abstract:

In this paper, a finite element modeling is presented for large amplitude vibration of functionally graded material (FGM) plates subjected to combined random pressure and thermal load. The material properties of the plates are assumed to vary continuously in the thickness direction by a simple power law distribution in terms of the volume fractions of the constituents. The material properties depend on the temperature whose distribution along the thickness can be expressed explicitly. The von Karman large deflection strain displacement and extended Hamilton's principle are used to obtain the governing system of equations of motion in structural node degrees of freedom (DOF) using finite element method. Three-node triangular Mindlin plate element with shear correction factor is used. The nonlinear equations of motion in structural degrees of freedom are reduced by using modal reduction method. The reduced equations of motion are solved numerically by 4th order Runge-Kutta scheme. In this study, the random pressure is generated using Monte Carlo method. The modeling is verified and the nonlinear dynamic response of FGM plates is studied for various values of volume fraction and sound pressure level under different thermal loads. Snap-through type behavior of FGM plates is studied too.

Keywords: nonlinear vibration, finite element method, functionally graded material (FGM) plates, snap-through, random vibration, thermal effect

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7527 A Study on the Coefficient of Transforming Relative Lateral Displacement under Linear Analysis of Structure to Its Real Relative Lateral Displacement

Authors: Abtin Farokhipanah

Abstract:

In recent years, analysis of structures is based on ductility design in contradictory to strength design in surveying earthquake effects on structures. ASCE07-10 code offers to intensify relative drifts calculated from a linear analysis with Cd which is called (Deflection Amplification Factor) to obtain the real relative drifts which can be calculated using nonlinear analysis. This lateral drift should be limited to the code boundaries. Calculation of this amplification factor for different structures, comparing with ASCE07-10 code and offering the best coefficient are the purposes of this research. Following our target, short and tall building steel structures with various earthquake resistant systems in linear and nonlinear analysis should be surveyed, so these questions will be answered: 1. Does the Response Modification Coefficient (R) have a meaningful relation to Deflection Amplification Factor? 2. Does structure height, seismic zone, response spectrum and similar parameters have an effect on the conversion coefficient of linear analysis to real drift of structure? The procedure has used to conduct this research includes: (a) Study on earthquake resistant systems, (b) Selection of systems and modeling, (c) Analyzing modeled systems using linear and nonlinear methods, (d) Calculating conversion coefficient for each system and (e) Comparing conversion coefficients with the code offered ones and concluding results.

Keywords: ASCE07-10 code, deflection amplification factor, earthquake engineering, lateral displacement of structures, response modification coefficient

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7526 Detection and Classification Strabismus Using Convolutional Neural Network and Spatial Image Processing

Authors: Anoop T. R., Otman Basir, Robert F. Hess, Eileen E. Birch, Brooke A. Koritala, Reed M. Jost, Becky Luu, David Stager, Ben Thompson

Abstract:

Strabismus refers to a misalignment of the eyes. Early detection and treatment of strabismus in childhood can prevent the development of permanent vision loss due to abnormal development of visual brain areas. We developed a two-stage method for strabismus detection and classification based on photographs of the face. The first stage detects the presence or absence of strabismus, and the second stage classifies the type of strabismus. The first stage comprises face detection using Haar cascade, facial landmark estimation, face alignment, aligned face landmark detection, segmentation of the eye region, and detection of strabismus using VGG 16 convolution neural networks. Face alignment transforms the face to a canonical pose to ensure consistency in subsequent analysis. Using facial landmarks, the eye region is segmented from the aligned face and fed into a VGG 16 CNN model, which has been trained to classify strabismus. The CNN determines whether strabismus is present and classifies the type of strabismus (exotropia, esotropia, and vertical deviation). If stage 1 detects strabismus, the eye region image is fed into stage 2, which starts with the estimation of pupil center coordinates using mask R-CNN deep neural networks. Then, the distance between the pupil coordinates and eye landmarks is calculated along with the angle that the pupil coordinates make with the horizontal and vertical axis. The distance and angle information is used to characterize the degree and direction of the strabismic eye misalignment. This model was tested on 100 clinically labeled images of children with (n = 50) and without (n = 50) strabismus. The True Positive Rate (TPR) and False Positive Rate (FPR) of the first stage were 94% and 6% respectively. The classification stage has produced a TPR of 94.73%, 94.44%, and 100% for esotropia, exotropia, and vertical deviations, respectively. This method also had an FPR of 5.26%, 5.55%, and 0% for esotropia, exotropia, and vertical deviation, respectively. The addition of one more feature related to the location of corneal light reflections may reduce the FPR, which was primarily due to children with pseudo-strabismus (the appearance of strabismus due to a wide nasal bridge or skin folds on the nasal side of the eyes).

Keywords: strabismus, deep neural networks, face detection, facial landmarks, face alignment, segmentation, VGG 16, mask R-CNN, pupil coordinates, angle deviation, horizontal and vertical deviation

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7525 The Hyundai Model: A Self-Sufficient State like Entity Masquerading as a Company

Authors: Nikita Koradia

Abstract:

Hyundai Motor Company, which started off as a small fish in a big sea, paved its way out successfully and established itself as an independent group from the conglomerate. Hyundai, with its officious power across the globe and particularly in South Korea in the automobile industry, has one the most complex yet fascinating governance structure. Being the second largest contributor to the Gross Domestic Product of South Korea after Samsung and having a market share of 51.3% domestically in automobile industry, Hyundai has faced its part of criticism owing to its anti-labor union approach and owing to its internalization of supply chain management. The censure has been coming from across jurisdictions like China, India, Canada, the EU, etc. The paper focuses on the growth of Hyundai and its inward and outward investment structure. The paper questions the ability of Hyundai to become a mini-state in itself by focusing on its governance structure. The paper further elaborates on its compliance and disclosure regime in the field of Corporate social responsibility and explores how far the business structure adopted by Hyundai works in its favor to become one of the leading automobile contenders in the market.

Keywords: compliance regime, disclosure regime, Hyundai motor company, supply-chain management

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7524 Axle Load Estimation of Moving Vehicles Using BWIM Technique

Authors: Changgil Lee, Seunghee Park

Abstract:

Although vehicle driving test for the development of BWIM system is necessary, but it needs much cost and time in addition application of various driving condition. Thus, we need the numerical-simulation method resolving the cost and time problems of vehicle driving test and the way of measuring response of bridge according to the various driving condition. Using the precision analysis model reflecting the dynamic characteristic is contributed to increase accuracy in numerical simulation. In this paper, we conduct a numerical simulation to apply precision analysis model, which reflects the dynamic characteristic of bridge using Bridge Weigh-in-Motion technique and suggest overload vehicle enforcement technology using precision analysis model.

Keywords: bridge weigh-in-motion(BWIM) system, precision analysis model, dynamic characteristic of bridge, numerical simulation

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7523 Effect of Measured and Calculated Static Torque on Instantaneous Torque Profile of Switched Reluctance Motor

Authors: Ali Asghar Memon

Abstract:

The simulation modeling of switched reluctance (SR) machine often relies and uses the three data tables identified as static torque characteristics that include flux linkage characteristics, co energy characteristics and static torque characteristics separately. It has been noticed from the literature that the data of static torque used in the simulation model is often calculated so far the literature is concerned. This paper presents the simulation model that include the data of measured and calculated static torque separately to see its effect on instantaneous torque profile of the machine. This is probably for the first time so far the literature review is concerned that static torque from co energy information, and measured static torque directly from experiments are separately used in the model. This research is helpful for accurate modeling of switched reluctance drive.

Keywords: static characteristics, current chopping, flux linkage characteristics, switched reluctance motor

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7522 Anaerobic Co-digestion in Two-Phase TPAD System of Sewage Sludge and Fish Waste

Authors: Rocio López, Miriam Tena, Montserrat Pérez, Rosario Solera

Abstract:

Biotransformation of organic waste into biogas is considered an interesting alternative for the production of clean energy from renewable sources by reducing the volume and organic content of waste Anaerobic digestion is considered one of the most efficient technologies to transform waste into fertilizer and biogas in order to obtain electrical energy or biofuel within the concept of the circular economy. Currently, three types of anaerobic processes have been developed on a commercial scale: (1) single-stage process where sludge bioconversion is completed in a single chamber, (2) two-stage process where the acidogenic and methanogenic stages are separated into two chambers and, finally, (3) temperature-phase sequencing (TPAD) process that combines a thermophilic pretreatment unit prior to mesophilic anaerobic digestion. Two-stage processes can provide hydrogen and methane with easier control of the first and second stage conditions producing higher total energy recovery and substrate degradation than single-stage processes. On the other hand, co-digestion is the simultaneous anaerobic digestion of a mixture of two or more substrates. The technology is similar to anaerobic digestion but is a more attractive option as it produces increased methane yields due to the positive synergism of the mixtures in the digestion medium thus increasing the economic viability of biogas plants. The present study focuses on the energy recovery by anaerobic co-digestion of sewage sludge and waste from the aquaculture-fishing sector. The valorization is approached through the application of a temperature sequential phase process or TPAD technology (Temperature - Phased Anaerobic Digestion). Moreover, two-phase of microorganisms is considered. Thus, the selected process allows the development of a thermophilic acidogenic phase followed by a mesophilic methanogenic phase to obtain hydrogen (H₂) in the first stage and methane (CH₄) in the second stage. The combination of these technologies makes it possible to unify all the advantages of these anaerobic digestion processes individually. To achieve these objectives, a sequential study has been carried out in which the biochemical potential of hydrogen (BHP) is tested followed by a BMP test, which will allow checking the feasibility of the two-stage process. The best results obtained were high total and soluble COD yields (59.8% and 82.67%, respectively) as well as H₂ production rates of 12LH₂/kg SVadded and methane of 28.76 L CH₄/kg SVadded for TPAD.

Keywords: anaerobic co-digestion, TPAD, two-phase, BHP, BMP, sewage sludge, fish waste

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7521 Tele-Rehabilitation for Multiple Sclerosis: A Case Study

Authors: Sharon Harel, Rachel Kizony, Yoram Feldman, Gabi Zeilig, Mordechai Shani

Abstract:

Multiple Sclerosis (MS) is a neurological disease that may cause restriction in participation in daily activities of young adults. Main symptoms include fatigue, weakness and cognitive decline. The appearance of symptoms, their severity and deterioration rate, change between patients. The challenge of health services is to provide long-term rehabilitation services to people with MS. The objective of this presentation is to describe a course of tele-rehabilitation service of a woman with MS. Methods; R is a 48 years-old woman, diagnosed with MS when she was 22. She started to suffer from weakness of her non-dominant left upper extremity about ten years after the diagnosis. She was referred to the tele-rehabilitation service by her rehabilitation team, 16 years after diagnosis. Her goals were to improve ability to use her affected upper extremity in daily activities. On admission her score in the Mini-Mental State Exam was 30/30. Her Fugl-Meyer Assessment (FMA) score of the left upper extremity was 48/60, indicating mild weakness and she had a limitation of her shoulder abduction (90 degrees). In addition, she reported little use of her arm in daily activities as shown in her responses to the Motor Activity Log (MAL) that were equal to 1.25/5 in amount and 1.37 in quality of use. R. received two 30 minutes on-line sessions per week in the tele-rehabilitation service, with the CogniMotion system. These were complemented by self-practice with the system. The CogniMotion system provides a hybrid (synchronous-asynchronous), the home-based tele-rehabilitation program to improve the motor, cognitive and functional status of people with neurological deficits. The system consists of a computer, large monitor, and the Microsoft’s Kinect 3D sensor. This equipment is located in the client’s home and connected to a clinician’s computer setup in a remote clinic via WiFi. The client sits in front of the monitor and uses his body movements to interact with games and tasks presented on the monitor. The system provides feedback in the form of ‘knowledge of results’ (e.g., the success of a game) and ‘knowledge of performance’ (e.g., alerts for compensatory movements) to enhance motor learning. The games and tasks were adapted for R. motor abilities and level of difficulty was gradually increased according to her abilities. The results of her second assessment (after 35 on-line sessions) showed improvement in her FMA score to 52 and shoulder abduction to 140 degrees. Moreover, her responses to the MAL indicated an increased amount (2.4) and quality (2.2) of use of her left upper extremity in daily activities. She reported high level of enjoyment from the treatments (5/5), specifically the combination of cognitive challenges while moving her body. In addition, she found the system easy to use as reflected by her responses to the System Usability Scale (85/100). To-date, R. continues to receive treatments in the tele-rehabilitation service. To conclude, this case report shows the potential of using tele-rehabilitation for people with MS to provide strategies to enhance the use of the upper extremity in daily activities as well as for maintaining motor function.

Keywords: motor function, multiple-sclerosis, tele-rehabilitation, daily activities

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7520 Feasibility Study on Hybrid Multi-Stage Direct-Drive Generator for Large-Scale Wind Turbine

Authors: Jin Uk Han, Hye Won Han, Hyo Lim Kang, Tae An Kim, Seung Ho Han

Abstract:

Direct-drive generators for large-scale wind turbine, which are divided into AFPM(Axial Flux Permanent Magnet) and RFPM(Radial Flux Permanent Magnet) type machine, have attracted interest because of a higher energy density in comparison with gear train type generators. Each type of the machines provides distinguishable geometrical features such as narrow width with a large diameter for the AFPM-type machine and wide width with a certain diameter for the RFPM-type machine. When the AFPM-type machine is applied, an increase of electric power production through a multi-stage arrangement in axial direction is easily achieved. On the other hand, the RFPM-type machine can be applied by using its geometric feature of wide width. In this study, a hybrid two-stage direct-drive generator for 6.2MW class wind turbine was proposed, in which the two-stage AFPM-type machine for 5 MW was composed of two models arranged in axial direction with a hollow shape topology of the rotor with annular disc, the stator and the main shaft mounted on coupled slew bearings. In addition, the RFPM-type machine for 1.2MW was installed at the empty space of the rotor. Analytic results obtained from an electro-magnetic and structural interaction analysis showed that the structural weight of the proposed hybrid two-stage direct-drive generator can be achieved as 155tonf in a condition satisfying the requirements of structural behaviors such as allowable air-gap clearance and strength. Therefore, it was sure that the 6.2MW hybrid two-stage direct-drive generator is competitive than conventional generators. (NRF grant funded by the Korea government MEST, No. 2017R1A2B4005405).

Keywords: AFPM-type machine, direct-drive generator, electro-magnetic analysis, large-scale wind turbine, RFPM-type machine

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7519 Effect of Deficit Irrigation on Photosynthesis Pigments, Proline Accumulation and Oil Quantity of Sweet Basil (Ocimum basilicum L.) in Flowering and Seed Formation Stages

Authors: Batoul Mohamed Abdullatif, Nouf Ali Asiri

Abstract:

O. basilicum plant was subjected to deficit irrigation using four treatments viz. control, irrigated with 70% of soil water capacity (SWC), Treatment 1, irrigated with 50% SWC, Treatment 2, irrigated with 30% SWC and Treatment 3, irrigated with 10 % SWC. Photosynthesis pigments viz. chlorophyll a, b, and the carotenoids, proline accumulation, and oil quantity were investigated under these irrigation treatments. The results indicate that photosynthesis pigments and oil content of deficit irrigation treatments did not significantly reduced than that of the full irrigation control. Photosynthesis pigments were affected by the stage of growth and not by irrigation treatments. They were high during flowering stage and low during seed formation stage for all treatments. The lowest irrigation plants (10 % SWC) achieved, during flowering stage, 0.72 mg\g\fresh weight of chlorophyll a, compared to 0.43 mg\g\fresh weight in control plant, 0.40 mg\g\fresh weight of chlorophyll b, compared to 0.19 mg\g\fresh weight in control plants and 0.29 mg\g\fresh weight of carotenoids, compared to 0.21 mg\g\fresh weight in control plants. It has been shown that reduced irrigation rates tend to enhance O. basilicum to have high oil quantity reaching a value of 63.37 % in a very low irrigation rate (10 % SWC) compared to 45.38 of control in seeds. Proline was shown to be accumulated in roots to almost double the amount in shoot during flowering stage in treatment 3. This accumulation seems to have a pronounce effect on O. basilicum acclimation to deficit irrigation.

Keywords: deficit irrigation, photosynthesis pigments, proline accumulation, oil quantity, sweet basil flowering formation, seed formation

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7518 Robotic Exoskeleton Response During Infant Physiological Knee Kinematics

Authors: Breanna Macumber, Victor A. Huayamave, Emir A. Vela, Wangdo Kim, Tamara T. Chamber, Esteban Centeno

Abstract:

Spina bifida is a type of neural tube defect that affects the nervous system and can lead to problems such as total leg paralysis. Treatment requires physical therapy and rehabilitation. Robotic exoskeletons have been used for rehabilitation to train muscle movement and assist in injury recovery; however, current models focus on the adult populations and not on the infant population. The proposed framework aims to couple a musculoskeletal infant model with a robotic exoskeleton using vacuum-powered artificial muscles to provide rehabilitation to infants affected by spina bifida. The study that drove the input values for the robotic exoskeleton used motion capture technology to collect data from the spontaneous kicking movement of a 2.4-month-old infant lying supine. OpenSim was used to develop the musculoskeletal model, and Inverse kinematics was used to estimate hip joint angles. A total of 4 kicks (A, B, C, D) were selected, and the selection was based on range, transient response, and stable response. Kicks had at least 5° of range of motion with a smooth transient response and a stable period. The robotic exoskeleton used a Vacuum-Powered Artificial Muscle (VPAM) the structure comprised of cells that were clipped in a collapsed state and unclipped when desired to simulate infant’s age. The artificial muscle works with vacuum pressure. When air is removed, the muscle contracts and when air is added, the muscle relaxes. Bench testing was performed using a 6-month-old infant mannequin. The previously developed exoskeleton worked really well with controlled ranges of motion and frequencies, which are typical of rehabilitation protocols for infants suffering with spina bifida. However, the random kicking motion in this study contained high frequency kicks and was not able to accurately replicate all the investigated kicks. Kick 'A' had a greater error when compared to the other kicks. This study has the potential to advance the infant rehabilitation field.

Keywords: musculoskeletal modeling, soft robotics, rehabilitation, pediatrics

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7517 A Mixed Integer Linear Programming Model for Flexible Job Shop Scheduling Problem

Authors: Mohsen Ziaee

Abstract:

In this paper, a mixed integer linear programming (MILP) model is presented to solve the flexible job shop scheduling problem (FJSP). This problem is one of the hardest combinatorial problems. The objective considered is the minimization of the makespan. The computational results of the proposed MILP model were compared with those of the best known mathematical model in the literature in terms of the computational time. The results show that our model has better performance with respect to all the considered performance measures including relative percentage deviation (RPD) value, number of constraints, and total number of variables. By this improved mathematical model, larger FJS problems can be optimally solved in reasonable time, and therefore, the model would be a better tool for the performance evaluation of the approximation algorithms developed for the problem.

Keywords: scheduling, flexible job shop, makespan, mixed integer linear programming

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7516 Modelling and Detecting the Demagnetization Fault in the Permanent Magnet Synchronous Machine Using the Current Signature Analysis

Authors: Yassa Nacera, Badji Abderrezak, Saidoune Abdelmalek, Houassine Hamza

Abstract:

Several kinds of faults can occur in a permanent magnet synchronous machine (PMSM) systems: bearing faults, electrically short/open faults, eccentricity faults, and demagnetization faults. Demagnetization fault means that the strengths of permanent magnets (PM) in PMSM decrease, and it causes low output torque, which is undesirable for EVs. The fault is caused by physical damage, high-temperature stress, inverse magnetic field, and aging. Motor current signature analysis (MCSA) is a conventional motor fault detection method based on the extraction of signal features from stator current. a simulation model of the PMSM under partial demagnetization and uniform demagnetization fault was established, and different degrees of demagnetization fault were simulated. The harmonic analyses using the Fast Fourier Transform (FFT) show that the fault diagnosis method based on the harmonic wave analysis is only suitable for partial demagnetization fault of the PMSM and does not apply to uniform demagnetization fault of the PMSM.

Keywords: permanent magnet, diagnosis, demagnetization, modelling

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