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Biogeography-Based Optimization Combined with Predator-Prey Approach Applied to Economic Load Dispatch

Biogeography-Based Optimization Combined with Predator-Prey ...

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Brazilian Symposium on Neural Networks

作者： Marsil de Athayde Costa e Silva Leandro dos Santos Coelho Undergraduate Course in Mechatronics Engineering Pontifical Catholic University of Paraná (PUCPR) Curitiba Paraná Brazil Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Paraná (PUCPR) Curitiba Paraná Brazil

Economic Load Dispatch (ELD) problems are nonlinear constrained problems which occupy an important role in the economic operation of power system. Recently, as an alternative to the conventional mathematical approaches, evolutionary algorithms have been given much attention by researchers due to their ability to find good solutions in ELD problems. In this paper, a biogeography based-optimization approach is validated. Biogeography is the study of the geographical distribution of biological organisms. Furthermore, a new approach of the biogeography based-optimization methodology combined with predator-prey approach were proposed and validated for two test systems consisting of 15 and 20 generation units (thermal generators), respectively. Simulation results are compared with those of other studies reported in the literature.

关键词： Optimization Biogeography Mathematical model Generators Economics Convergence Equations

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Micromachined ultrasonic transducer using piezoelectric PVDF film to measure the mechanical properties of bio cells

Micromachined ultrasonic transducer using piezoelectric PVDF...

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IEEE SENSORS

作者： Minhyun Jung Man Geun Kim Jong-Hyun Lee School of Information and Mechatronics Gwangju Institute of Science and Technology Gwangju South Korea Graduate-program of Medical System Engineering Gwangju Institute of Science and Technology Gwangju South Korea

We proposed a new method to measure the frequency-dependent attenuation of bio cells using piezoelectric ultrasonic transducer. The polyvinylidene fluoride (PVDF) polymer was employed as piezoelectric material to take an advantage of its low acoustic impedance (2.7 Mrayl) so that the transmission of acoustic power will be improved by impedance matching with that of liquid medium. The thickness of PVDF film is 110 ¿m and the resonance frequency of the 1 st thickness mode is 8.7 MHz. In order to characterize the fabricated ultrasonic transducer, a transducer and an acoustic wave reflector were positioned face to face. The output voltage for reflected transmitted ultrasonic wave was measured with impulse method and was transformed into the Round Trip Insertion Loss (RTIL) where the dominant frequency ranges from 5 MHz to 9 MHz.

关键词： Ultrasonic transducers Piezoelectric films Mechanical variables measurement Ultrasonic variables measurement Mechanical factors Acoustic measurements Frequency measurement Attenuation measurement Polymers Piezoelectric materials

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Virtual testing of buckling-restrained braces via nonlinear autoregressive exogenous neural networks

Virtual testing of buckling-restrained braces via nonlinear ...

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作者： Alhamaydeh, Mohammad Choudhary, Ibrahim Assaleh, Khaled Dept. of Civil Engineering American Univ. of Sharjah P.O. Box 26666 Sharjah United Arab Emirates Mechatronics Graduate Program American Univ. of Sharjah P.O. Box 26666 Sharjah United Arab Emirates Dept. of Electrical Engineering American Univ. of Sharjah P.O. Box 26666 Sharjah United Arab Emirates

An artificial intelligence model utilizing feedforward back-propagation (FFBP) and nonlinear autoregressive exogenous (NARX) artificial neural networks (ANNs) is presented to model the nonlinear behavior of buckling-restrained braces (BRBs). The NARX ANN is developed using normalized time-delayed inputs and outputs to predict normalized brace forces during load reversals. The values of brace forces are denormalized via an auxiliary FFBP ANN. The training and testing of the proposed model (i.e., the NARX and FFBP ANNs) are performed using experimental data from BRB specimens tested at the Pacific Earthquake engineering Research (PEER) Center. Experimental data from one specimen is used in the model developing (training) stage. In addition, three sets of data are used to test the model's learning and generalizing abilities. Brace deformations are used as the network input to estimate the resulting brace forces. The network performance with different parameters is evaluated to arrive at an optimized architecture that best models the phenomenon. The nonlinear hysteretic behavior predicted by the ANN model shows excellent agreement with the experimental results for the training sample. The generalization and prediction capability of the proposed model is further demonstrated by predicting the hysteretic behavior of the testing samples with noticeable accuracy. The presented model is a powerful tool for virtually testing BRB specimens. Such a tool supplements the traditionally available experimental tools for BRB performance investigation. The developed modeling technique facilitates the BRB design and performance investigation processes by minimizing the need for, and extent of, experimental testing. © 2013 American Society of Civil Engineers.

关键词： Hysteresis

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A Multi Soft-sensor Approach for the Development of Emergencies Detection Units on the Edge

A Multi Soft-sensor Approach for the Development of Emergenc...

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Workshop on Metrology for Industry 4.0 and IoT

作者： Franklin Oliveira Daniel G. Costa Flávio Assis Ivanovitch Silva Graduate Program in Mechatronics Federal University of Bahia Salvador Brazil INEGI Faculty of Engineering University of Porto Porto Portugal Department of Computer Engineering and Automation Federal University of Rio Grande do Norte Natal Brazil

The adoption of multi-sensor hardware units to detect different types of emergencies in complex scenarios such as Industry 4.0 and Smart Cities is a recent development trend, which have demanded research efforts to optimize the way these units are assembled, configured, and deployed. However, although their expected advantages, usual multi-sensors emergency-oriented approaches may be constrained by the tight association between physical sensor devices and the emergency detection process. Therefore, this paper proposes an innovative approach to concurrently detect multiple emergencies exploiting the concept of soft-sensor modules, which are implemented on Emergency Detection Units (EDUs) as concurrent tasks along with a high-priority emergency alerting task. The soft-sensor concept defines physical sensors as ordinary input data streams, which will be processed according to the defined algorithms by each particular soft-sensor, allowing detection decisions to be performed on the edge. In order to support the practical exploitation of this concept, a formal specification based on Petri Nets is defined, modeling the concurrent operation of the tasks within an EDU. A proof of concept is also designed based on the affordable Raspberry Pi Pico microcontroller, demonstrating how the proposed approach would behave when two soft-sensors are implemented in a typical detection unit.

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Development of bionic invasion membrane for the study of multiple sclerosis

Development of bionic invasion membrane for the study of mul...

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IEEE International Conference on Nano/Micro Engineered and Molecular Systems (NEMS)

作者： Chia-Yi Lee Kin Fong Lei Cheng-Lung Ku Chia-Hao Huang Ph.D. Program in Biomedical Engineering Chang Gung University Taiwan Department of Mechanical Engineering Chang Gung University Taiwan Graduate Institute of Clinical Medical Science Chang Gung University Taiwan Graduate Institute of Medical Mechatronics Chang Gung University Taiwan

ISBN: (纸本)9781509019489

Multiple sclerosis (MS) is an autoimmune disease and leads to many inflammations. Cause of this disease is autoreactive T cells invade the blood-brain-barrier and attack the myelin sheath. Because MS infringes upon young human and has gradual loss of bodily functions, the disease has a burden on society and economy. Traditional treatment is to use immune-suppressant, but it has many side effects. Currently, the most effective treatment of MS is to use Natalizumab. Target molecule of this agent is α4-integrin of T cells. The mechanism is to prevent invasion of activated lymphocytes across the blood-brain-barrier. However, this agent affects the overall immune response and easily generates side effects of progressive multifocal leukoencephalopathy (PML). Transwall systems are often used to investigate cell invasion, but there is no specific protein immobilizing on the isolation membrane of these systems. In this work, we have successfully developed a bionic invasion membrane for the study of MS. Different chemokines were applied to the system for the demonstration of drug screening application. The bionic invasion membrane was a PP/PTEE membrane coated with VCAM-1 protein. Jurkat T cell was used to evaluate the feasibility of using the membrane for the study of MS. Results indicated that the invasion ability of T cells was reduced by VCAM-1 protein. The current work provides bionic invasion membrane for the study of MS in vitro.

关键词： Biomembranes Proteins Multiple sclerosis Immune system Microfluidics Color

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Motion Detection Method of Electrostatic MEMS Resonators Operating in Aqueous Media

Motion Detection Method of Electrostatic MEMS Resonators Ope...

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International Youth Conference on Radio Electronics, Electrical and Power engineering (REEPE)

作者： Mohamed Hemid Basil Alattar Mehdi Ghommem Alaaeldin Ahmed Eihab Abdel-Rahman Rana Sabouni Mechatronics Graduate Program American University of Sharjah Sharjah UAE Mechanical Engineering Department American University of Sharjah Sharjah UAE Systems Design Engineering University of Waterloo Ontario Canada Chemical Engineering Department American University of Sharjah Sharjah UAE

This paper introduces an experimental method to detect the motion of an electrostatic Micro-Electro-Mechanical Systems (MEMS) resonator in aqueous media. The resonator comprises a micro cantilever beam subject to electrostatic actuation through a side electrode. A Finite Element Method (FEM) model of the resonator is developed to determine the in-plane mode shapes and their natural frequencies in order to facilitate the experimental study. The motion of the resonator lead to variations in its capacitance and induce a current. The developed experiments demonstrate that motion-induced current can be measured and analyzed to detect the motion of the resonator's higher-order modes and can be used in chemical sensing.

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Design, implementation and control of dual axis self balancing inverted pendulum using reaction wheels

Design, implementation and control of dual axis self balanci...

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International Conference on Electrical and Electronics engineering, ELECO

作者： Abdullah Türkmen M. Yusuf Korkut Mustafa Erdem Ömer Gönül Volkan Sezer Mechatronics Graduate Program Istanbul Technical University Istanbul TURKEY Energy Institute Istanbul Technical University Istanbul TURKEY Dept. of Control and Automation Engineering Istanbul Technical University Istanbul TURKEY

Inverted pendulum systems have an important place in practice for control problems due to their nonlinear structures. It is a very difficult task to control the orientation and speed of objects and robots which are free in three dimensions. These systems constitute the substructure of many advanced systems. Conventional actuators may not be used in such applications due to various limitations. Under these circumstances usage of reaction wheels come into prominence. Reaction wheel based systems are used for orienting, coordinating and balancing of spacecraft, transport systems, and other such systems. In this study, dual axis self-balancing reaction wheel based inverted pendulum system which is a basis for many complex systems has been designed, manufactured and controlled.

关键词： Wheels Mathematical model DC motors Gravity State feedback Torque Aluminum

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Motion Measurement Methods for Nonlinear Analysis of Electrostatic MEMS Resonators

Motion Measurement Methods for Nonlinear Analysis of Electro...

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Eurocon

作者： Mehdi Ghommem Basil Alattar Michael Lherbette Alaaeldin Elhady Eihab Abdel-Rahman Department of Mechanical Engineering American University of Sharjah Sharjah UAE Mechatronics Graduate Program American University of Sharjah Sharjah UAE SmarAct Metrology Rohdenweg Oldenburg Germany Systems Design Engineering University of Waterloo Waterloo Ontario Canada

In this paper, we compare two measurement techniques to analyze the dynamic response of a MEMS resonator, made of a microcantilever beam, that is electrostatically actuated via a side electrode. The first method is based on a combination of Michelson interferometry, knife-edge analysis, and stroboscopic imaging, and is used to dissect the in-plane and out-of-plane motions of the resonator. The second approach follows the motion-induced current method and is based on a transduction mechanism that converts the movement of the resonator to a current signal. The third harmonic of said current is directly related to the in-plane motion of the resonator. Motion-induced current measurements enable the detection of the nonlinear dynamics associated with the motion of the resonator when actuated with high excitation voltages. The optical and electrical measurements show similar nonlinear features in terms of the location of the cyclic-fold bifurcation in the parameter space and the hysteretic region associated with it. These dynamic features can be exploited for sensing purposes.

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Low Complexity Broadband Array Processing in Dynamic Scenarios with Jamming

Low Complexity Broadband Array Processing in Dynamic Scenari...

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IEEE Conference on Vehicular Technology (VTC)

作者： Daniel V. De Lima João Paulo J. Da Costa Ricardo K. Miranda Antonio Arlis S. Da Silva Giovanni A. Santos José Alfredo R. Vargas Auzuir R. De Alexandria Postgraduate Program in Telecommunications Engineering (PPGET) IFCE Fortaleza Brazil Hamm-Lippstadt University of Applied Sciences (HSHL) Lippstadt Germany Graduate School for Applied Research in North Rhine-Westphalia (PKNRW) Bochum Germany Karlsruhe Institute of Technology (KIT) Karlsruhe Germany Graduate Program in Computing (PPGC) UFRGS Porto Alegre Brazil Postgraduate Program in Mechatronics Engineering (PPMEC) UnB Brasilia Brazil

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

Vehicle-to-Everything (V2X) networks require low-latency communications utilizing a broad spectrum while operating under jamming. In this sense, low complexity antenna array-based broadband jamming mitigation schemes are crucial in order to allow low latency communication and low-cost hardware. In this paper we propose low-complexity algorithms for signal recovery in broadband processing scenario applied to V2X. Numerical simulation of a jamming scenario demonstrate the proposed algorithm achieving the same performance in terms of signal-to-interference plus noise ratio (SINR) as the state-of-the-art while taking signiflcantly less time to compute.

关键词： Heuristic algorithms Prevention and mitigation Interference Numerical simulation Broadband communication Broadband antennas Jamming

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A Cascade Deep Neural Network Approach for Oil Spills Classification and Detection

A Cascade Deep Neural Network Approach for Oil Spills Classi...

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International Conference on Electric Power and Energy Conversion Systems (EPECS)

作者： Mohammad Rashwan Mohammed Alhadi Mohammad A. Jaradat Mohammad I. Daoud Mechatronics Graduate Program American University of Sharjah Sharjah United Arab Emirates Mechanical Engineering Department American University of Sharjah Sharjah United Arab Emirates Computer Science and Engineering Department American University of Sharjah Sharjah United Arab Emirates

ISBN: (数字)9798331516963

ISBN: (纸本)9798331516970

Oil spills represent a growing environmental challenge that poses a significant threat to living organisms. Moreover, the treatment of oil spills, especially in severe cases, has serious economic repercussions and requires substantial labor and time. Therefore, the effective detection of oil spills has become an important research problem. Traditional methods for detecting oil spills, such as manual patrolling and dynamic sensors, are often limited in accuracy and coverage. As a result, the automation of oil spills detection has emerged as a critical global imperative in scientific research. The aim of this paper is to employ deep learning technology to achieve effective detection of oil spills based on aerial images. Our approach is composed of two phases. In the first phase, a Deep Convolutional Neural Network (DCNN), namely ResNet50, is trained on a large dataset containing images showing oil spills at a seaport. The trained DCNN is used to classify the input image as "Oil Spill" or "No Oil Spill". In the second phase, the images classified as "Oil Spill" are analyzed using a deep learning detection model, namely You-Only-Look-Once (YOLOv4), to localize the oil spills. The results indicate the capability of the proposed method to achieve effective oil spill detection. In particular, the classification accuracy obtained by the ResNet50 model is equal to 98%. Moreover, the YOLOv4 model was able to obtain effective localization of the oil spills with mean-average precision of 62%.

关键词： Deep learning Accuracy Oils Manuals Seaports Organisms Sensors Power systems Convolutional neural networks Residual neural networks

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