WorldWideScience

Sample records for neural mems applications

  1. Parylene for MEMS applications

    Science.gov (United States)

    Yao, Tze-Jung

    The goal of this thesis is to utilize Parylene, a room-temperature chemical-vapor-deposited (CVD) polymer, for MicroElectroMechanical Systems (MEMS) applications. The identified unique properties of Parylene are used to fabricate various micromachining devices such as thermopneumatic microvalve, in-channel microflow restrictor, and electret microphones. First, the properties of Parylene as a MEMS material are reviewed. The electrical, thermal, surface, and mechanical properties are first compared with that of other materials and further studied specifically for MEMS applications. The high dielectric strength (determined as 250V/mum) of Parylene makes it suitable for use as an electrical insulation material. However, its high resistivity causes un-desired charging effects first described in polymer-based electrostatic devices. The undesired high pull-in voltage, "bounce-back," and "snap-down" effects caused by dielectric charging are studied. Second, to make Parylene as a surface-micromachined material, a process that overcomes the stiction problem has to be developed. Thus, a new technique that combines wet-acetone dissolution and dry BrF3 dry etching has developed to overcome the stiction problem, which prevents Parylene microstructures from freestanding. The devices of mm*mm size with high yield are demonstrated using this technology. A thermopneumatic microvalve with a corrugated silicone/Parylene composite membrane is designed, fabricated, and tested for gas flows of several slpm and inlet pressures of tens of psi. The lowest power consumption to turn off the gas flow is determined to be 73mW. A silicone-based microfluidic coupler, initially designed for microvalve packaging, is also demonstrated for its ability to connect the external macrofluidic world to microfluidic devices. The demonstrated "quick-connect" microfluidic coupler has low leakage, is reusable, and can maintain good seal up to 60 psi. An in-channel microflow restrictor is also demonstrated with

  2. MEMS for automotive and aerospace applications

    CERN Document Server

    Kraft, Michael

    2013-01-01

    MEMS for automotive and aerospace applications reviews the use of Micro-Electro-Mechanical-Systems (MEMS) in developing solutions to the unique challenges presented by the automotive and aerospace industries.Part one explores MEMS for a variety of automotive applications. The role of MEMS in passenger safety and comfort, sensors for automotive vehicle stability control applications and automotive tire pressure monitoring systems are considered, along with pressure and flow sensors for engine management, and RF MEMS for automotive radar sensors. Part two then goes on to explore MEMS for

  3. NeuroMEMS: Neural Probe Microtechnologies

    Directory of Open Access Journals (Sweden)

    Sam Musallam

    2008-10-01

    Full Text Available Neural probe technologies have already had a significant positive effect on our understanding of the brain by revealing the functioning of networks of biological neurons. Probes are implanted in different areas of the brain to record and/or stimulate specific sites in the brain. Neural probes are currently used in many clinical settings for diagnosis of brain diseases such as seizers, epilepsy, migraine, Alzheimer’s, and dementia. We find these devices assisting paralyzed patients by allowing them to operate computers or robots using their neural activity. In recent years, probe technologies were assisted by rapid advancements in microfabrication and microelectronic technologies and thus are enabling highly functional and robust neural probes which are opening new and exciting avenues in neural sciences and brain machine interfaces. With a wide variety of probes that have been designed, fabricated, and tested to date, this review aims to provide an overview of the advances and recent progress in the microfabrication techniques of neural probes. In addition, we aim to highlight the challenges faced in developing and implementing ultralong multi-site recording probes that are needed to monitor neural activity from deeper regions in the brain. Finally, we review techniques that can improve the biocompatibility of the neural probes to minimize the immune response and encourage neural growth around the electrodes for long term implantation studies.

  4. MEMS for medical technology applications

    Science.gov (United States)

    Frisk, Thomas; Roxhed, Niclas; Stemme, Göran

    2007-01-01

    This paper gives an in-depth description of two recent projects at the Royal Institute of Technology (KTH) which utilize MEMS and microsystem technology for realization of components intended for specific applications in medical technology and diagnostic instrumentation. By novel use of the DRIE fabrication technology we have developed side-opened out-of-plane silicon microneedles intended for use in transdermal drug delivery applications. The side opening reduces clogging probability during penetration into the skin and increases the up-take area of the liquid in the tissue. These microneedles offer about 200µm deep and pain-free skin penetration. We have been able to combine the microneedle chip with an electrically and heat controlled liquid actuator device where expandable microspheres are used to push doses of drug liquids into the skin. The entire unit is made of low cost materials in the form of a square one cm-sized patch. Finally, the design, fabrication and evaluation of an integrated miniaturized Quartz Crystal Microbalance (QCM) based "electronic nose" microsystem for detection of narcotics is described. The work integrates a novel environment-to-chip sample interface with the sensor element. The choice of multifunctional materials and the geometric features of a four-component microsystem allow a functional integration of a QCM crystal, electrical contacts, fluidic contacts and a sample interface in a single system with minimal assembly effort, a potential for low-cost manufacturing, and a few orders of magnitude reduced in system size (12*12*4 mm 3) and weight compared to commercially available instruments. The sensor chip was successfully used it for the detection of 200 ng of narcotics sample.

  5. Markets and applications for MEMS inertial sensors

    Science.gov (United States)

    Dixon, Richard H.; Bouchaud, Jérémie

    2006-01-01

    The ability to meet demanding specifications and stringent price points continues to drive market insertion for MEMS inertial sensors in cost-sensitive automotive applications and more recently, consumer markets. This paper examines major markets and drivers for gyroscopes and accelerometers, which will grow from a total of 835 million in 2004 to almost 1350 in 2009, a CAGR of over 10%.

  6. MEMS fundamental technology and applications

    CERN Document Server

    Choudhary, Vikas

    2013-01-01

    ""The book editors have managed to assemble a group of extraordinary authors to provide their expertise to this book. While giving an excellent overview of the history and the state of the art of MEMS technology, this book also focuses on current trends and topics such as gyroscopes that currently experience significant and increasing popularity in research and in industry. It is well written and the material is presented in a well-structured way making it easily accessible to any reader with a technical background.""-Boris Stoeber, The University of British Columbia, Vancouver, Canada<

  7. MEMS-Reconfigurable Metamaterials and Antenna Applications

    Directory of Open Access Journals (Sweden)

    Tomislav Debogovic

    2014-01-01

    Full Text Available This paper reviews some of our contributions to reconfigurable metamaterials, where dynamic control is enabled by microelectromechanical systems (MEMS technology. First, we show reconfigurable composite right-/left-handed transmission lines (CRLH-TLs having state of the art phase velocity variation and loss, thereby enabling efficient reconfigurable phase shifters and leaky-wave antennas (LWA. Second, we present very low loss metasurface designs with reconfigurable reflection properties, applicable in reflectarrays and partially reflective surface (PRS antennas. All the presented devices have been fabricated and experimentally validated. They operate in X- and Ku-bands.

  8. Application of RPF in MEMS gyro random drift filtering

    Science.gov (United States)

    Guowei, GAO; Yan, XIE

    2017-08-01

    With the development of micro-mechanical inertial technology, how to suppress the MEMS gyro’s random drift increasingly become a hot topic. In order to filter a certain type of MEMS gyro’s random drift, this paper introduces the regularized particle filter algorithm. The derivation of the algorithm and its application in MEMS gyro’s filtering process are described in detail in this paper: First, acquiring MEMS gyro’s static drift data and conducting data pre-treatment; then establishing the AR model by using time series analysis method, and transforming it into the corresponding state space model; finally, executing the estimation and compensation for MEMS gyro’s random drift with regular particle filter algorithm, and comparing it with other common methods in engineering. Tests and simulation results show that the regularized particle filter algorithm could achieve a good effect on the suppression of MEMS gyro’s random drift, it has a higher practical application value.

  9. Development and application of high-end aerospace MEMS

    Science.gov (United States)

    Yuan, Weizheng

    2017-12-01

    This paper introduces the design and manufacturing technology of aerospace microelectromechanical systems (MEMS) characterized by high performance, multi-variety, and small batch. Moreover, several kinds of special MEMS devices with high precision, high reliability, and environmental adaptability, as well as their typical applications in the fields of aeronautics and aerospace, are presented.

  10. Cryogenic MEMS Technology for Sensing Applications Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The development of cryogenic microwave components, such as focal plane polarization modulators, first requires an RF MEMS switching technology that operates...

  11. Adaptive Global Sliding Mode Control for MEMS Gyroscope Using RBF Neural Network

    Directory of Open Access Journals (Sweden)

    Yundi Chu

    2015-01-01

    Full Text Available An adaptive global sliding mode control (AGSMC using RBF neural network (RBFNN is proposed for the system identification and tracking control of micro-electro-mechanical system (MEMS gyroscope. Firstly, a new kind of adaptive identification method based on the global sliding mode controller is designed to update and estimate angular velocity and other system parameters of MEMS gyroscope online. Moreover, the output of adaptive neural network control is used to adjust the switch gain of sliding mode control dynamically to approach the upper bound of unknown disturbances. In this way, the switch item of sliding mode control can be converted to the output of continuous neural network which can weaken the chattering in the sliding mode control in contrast to the conventional fixed gain sliding mode control. Simulation results show that the designed control system can get satisfactory tracking performance and effective estimation of unknown parameters of MEMS gyroscope.

  12. Applications and requirements for MEMS scanner mirrors

    Science.gov (United States)

    Wolter, Alexander; Hsu, Shu-Ting; Schenk, Harald; Lakner, Hubert K.

    2005-01-01

    Micro scanning mirrors are quite versatile MEMS devices for the deflection of a laser beam or a shaped beam from another light source. The most exciting application is certainly in laser-scanned displays. Laser television, home cinema and data projectors will display the most brilliant colors exceeding even plasma, OLED and CRT. Devices for front and rear projection will have advantages in size, weight and price. These advantages will be even more important in near-eye virtual displays like head-mounted displays or viewfinders in digital cameras and potentially in UMTS handsets. Optical pattern generation by scanning a modulated beam over an area can be used also in a number of other applications: laser printers, direct writing of photo resist for printed circuit boards or laser marking and with higher laser power laser ablation or material processing. Scanning a continuous laser beam over a printed pattern and analyzing the scattered reflection is the principle of barcode reading in 1D and 2D. This principle works also for identification of signatures, coins, bank notes, vehicles and other objects. With a focused white-light or RGB beam even full color imaging with high resolution is possible from an amazingly small device. The form factor is also very interesting for the application in endoscopes. Further applications are light curtains for intrusion control and the generation of arbitrary line patterns for triangulation. Scanning a measurement beam extends point measurements to 1D or 2D scans. Automotive LIDAR (laser RADAR) or scanning confocal microscopy are just two examples. Last but not least there is the field of beam steering. E.g. for all-optical fiber switches or positioning of read-/write heads in optical storage devices. The variety of possible applications also brings a variety of specifications. This publication discusses various applications and their requirements.

  13. MEMS and MOEMS for national security applications

    Science.gov (United States)

    Scott, Marion W.

    2003-01-01

    Major opportunities for microsystem insertion into commercial applications, such as telecommunications and medical prosthesis, are well known. Less well known are applications that ensure the security of our nation, the protection of its armed forces, and the safety of its citizens. Microsystems enable entirely new possibilities to meet National Security needs, which can be classed along three lines: anticipating security needs and threats, deterring the efficacy of identified threats, and defending against the application of these threats. In each of these areas, specific products that are enabled by MEMS and MOEMS are discussed. In the area of anticipating needs and threats, sensored microsystems designed for chem/bio/nuclear threats, and sensors for border and asset protection can significantly secure our borders, ports, and transportation systems. Key features for these applications include adaptive optics and spectroscopic capabilities. Microsystems to monitor soil and water quality can be used to secure critical infrastructure, food safety can be improved by in-situ identification of pathogens, and sensored buildings can ensure the architectural safety of our homes and workplaces. A challenge to commercializing these opportunities, and thus making them available for National Security needs, is developing predictable markets and predictable technology roadmaps. The integrated circuit manufacturing industry provides an example of predictable technology maturation and market insertion, primarily due to the existence of a "unit cell" that allows volume manufacturing. It is not clear that microsystems can follow an analogous path. The possible paths to affordable low-volume production, as well as the prospects of a microsystems unit cell, are discussed.

  14. MEM application to IRAS CPC images

    Science.gov (United States)

    Marston, A. P.

    1994-01-01

    A method for applying the Maximum Entropy Method (MEM) to Chopped Photometric Channel (CPC) IRAS additional observations is illustrated. The original CPC data suffered from problems with repeatability which MEM is able to cope with by use of a noise image, produced from the results of separate data scans of objects. The process produces images of small areas of sky with circular Gaussian beams of approximately 30 in. full width half maximum resolution at 50 and 100 microns. Comparison is made to previous reconstructions made in the far-infrared as well as morphologies of objects at other wavelengths. Some projects with this dataset are discussed.

  15. Polycrystalline-Diamond MEMS Biosensors Including Neural Microelectrode-Arrays.

    Science.gov (United States)

    Varney, Michael W; Aslam, Dean M; Janoudi, Abed; Chan, Ho-Yin; Wang, Donna H

    2011-08-15

    Diamond is a material of interest due to its unique combination of properties, including its chemical inertness and biocompatibility. Polycrystalline diamond (poly-C) has been used in experimental biosensors that utilize electrochemical methods and antigen-antibody binding for the detection of biological molecules. Boron-doped poly-C electrodes have been found to be very advantageous for electrochemical applications due to their large potential window, low background current and noise, and low detection limits (as low as 500 fM). The biocompatibility of poly-C is found to be comparable, or superior to, other materials commonly used for implants, such as titanium and 316 stainless steel. We have developed a diamond-based, neural microelectrode-array (MEA), due to the desirability of poly-C as a biosensor. These diamond probes have been used for in vivo electrical recording and in vitro electrochemical detection. Poly-C electrodes have been used for electrical recording of neural activity. In vitro studies indicate that the diamond probe can detect norepinephrine at a 5 nM level. We propose a combination of diamond micro-machining and surface functionalization for manufacturing diamond pathogen-microsensors.

  16. Polycrystalline-Diamond MEMS Biosensors Including Neural Microelectrode-Arrays

    Directory of Open Access Journals (Sweden)

    Donna H. Wang

    2011-08-01

    Full Text Available Diamond is a material of interest due to its unique combination of properties, including its chemical inertness and biocompatibility. Polycrystalline diamond (poly-C has been used in experimental biosensors that utilize electrochemical methods and antigen-antibody binding for the detection of biological molecules. Boron-doped poly-C electrodes have been found to be very advantageous for electrochemical applications due to their large potential window, low background current and noise, and low detection limits (as low as 500 fM. The biocompatibility of poly-C is found to be comparable, or superior to, other materials commonly used for implants, such as titanium and 316 stainless steel. We have developed a diamond-based, neural microelectrode-array (MEA, due to the desirability of poly-C as a biosensor. These diamond probes have been used for in vivo electrical recording and in vitro electrochemical detection. Poly-C electrodes have been used for electrical recording of neural activity. In vitro studies indicate that the diamond probe can detect norepinephrine at a 5 nM level. We propose a combination of diamond micro-machining and surface functionalization for manufacturing diamond pathogen-microsensors.

  17. Adaptive Sliding Mode Control of MEMS Gyroscope Based on Neural Network Approximation

    Directory of Open Access Journals (Sweden)

    Yuzheng Yang

    2014-01-01

    Full Text Available An adaptive sliding controller using radial basis function (RBF network to approximate the unknown system dynamics microelectromechanical systems (MEMS gyroscope sensor is proposed. Neural controller is proposed to approximate the unknown system model and sliding controller is employed to eliminate the approximation error and attenuate the model uncertainties and external disturbances. Online neural network (NN weight tuning algorithms, including correction terms, are designed based on Lyapunov stability theory, which can guarantee bounded tracking errors as well as bounded NN weights. The tracking error bound can be made arbitrarily small by increasing a certain feedback gain. Numerical simulation for a MEMS angular velocity sensor is investigated to verify the effectiveness of the proposed adaptive neural control scheme and demonstrate the satisfactory tracking performance and robustness.

  18. Thermal energy harvesting for application at MEMS scale

    CERN Document Server

    Percy, Steven; McGarry, Scott; Post, Alex; Moore, Tim; Cavanagh, Kate

    2014-01-01

    This book discusses the history of thermal heat generators and focuses on the potential for these processes using micro-electrical mechanical systems (MEMS) technology for this application. The main focus is on the capture of waste thermal energy for example from industrial processes, transport systems or the human body to generate useable electrical power.  A wide range of technologies is discussed, including external combustion heat cycles at MEMS ( Brayton, Stirling and Rankine), Thermoacoustic, Shape Memory Alloys (SMAs), Multiferroics, Thermionics, Pyroelectric, Seebeck, Alkali Metal Thermal, Hydride Heat Engine, Johnson Thermo Electrochemical Converters, and the Johnson Electric Heat Pipe.

  19. Integrated MEMS-based IQ intelligent tire applications

    Science.gov (United States)

    Dunn, William F.

    1999-07-01

    The Goodyear Tire & Rubber Company is evaluating the use of integrated MEMS (MicroElectroMechanical Systems) for tire pressure sensing applications in automotive, bus, truck, aircraft and military tire lines. This paper deals with the reasons for this and the vision we have of how this will be implemented.

  20. Pulse Reversal PermAlloy Plating Process for MEMS Applications

    DEFF Research Database (Denmark)

    Smistrup, Kristian; Tang, Peter Torben; Møller, Per

    2007-01-01

    -stress deposits.We demonstrate selected MEMS applications of the electrolyte.The use of the strong complexing agent 5-sulfosalicylic acidallows for a photometric determination of the Fe3+-level in thebath and eliminate precipitates. This makes the electrolytesuitable as a Permalloy plating process used...

  1. MEMS-based tunable gratings and their applications

    Science.gov (United States)

    Yu, Yiting; Yuan, Weizheng; Qiao, Dayong

    2015-03-01

    The marriage of optics and MEMS has resulted in a new category of optical devices and systems that have unprecedented advantages compared with their traditional counterparts. As an important spatial light modulating technology, diffractive optical MEMS obtains a wide variety of successful commercial applications, e.g. projection displays, optical communication and spectral analysis, due to its features of highly compact, low-cost, IC-compatible, excellent performance, and providing possibilities for developing totally new, yet smart devices and systems. Three most successful MEMS diffraction gratings (GLVs, Polychromator and DMDs) are briefly introduced and their potential applications are analyzed. Then, three different MEMS tunable gratings developed by our group, named as micro programmable blazed gratings (μPBGs) and micro pitch-tunable gratings (μPTGs) working in either digital or analog mode, are demonstrated. The strategies to largely enhance the maximum blazed angle and grating period are described. Some preliminary application explorations based on the developed grating devices are also shown. For our ongoing research focus, we will further improve the device performance to meet the engineering application requirements.

  2. INVESTIGATION OF TITANIUM BONDED GRAPHITE FOAM COMPOSITES FOR MICRO ELECTRONIC MECHANICAL SYSTEMS (MEMS) APPLICATIONS

    Energy Technology Data Exchange (ETDEWEB)

    Menchhofer, Paul A [ORNL; Bozorgi, Payam [ORNL

    2016-04-01

    PiMEMS Inc. (Santa Barbara, CA) in collaboration with ORNL investigated the use of Titanium Bonded Graphite Foam Composites (TBGC) for thermal mitigation in Micro Electronic Mechanical Systems (MEMS) applications. Also considered were potentially new additive manufacturing routes to producing novel high surface area micro features and diverse shaped heat transfer components for numerous lightweight MEMs applications.

  3. Applications of MEMS technologies in tissue engineering.

    Science.gov (United States)

    Puleo, Christopher M; Yeh, Hsin-Chih; Wang, Tza-Huei

    2007-12-01

    The success of therapeutic strategies within the fields of regenerative medicine, including tissue engineering, biomaterials engineering, and cell and tissue transplantation science, relies on researchers' understanding of the complex cellular microenvironments that occur within functional tissue. Microfabricated biomedical platforms provide tools for researchers to study cellular response to various stimuli with micro- and nanoscale spatial control. Initial studies utilizing relatively passive means of microenvironmental control have provided the fundamental knowledge required to begin to design microculture platforms that closely mimic these biological systems. In this review, we discuss second-generation cell and tissue culture platforms that utilize active components, borrowed from work in the development of microelectromechanical systems (MEMS). These microsystems offer the unprecedented opportunity to fabricate culture platforms designed to match tissue-specific growth parameters. In addition, the adoption of MEMS components opens up the door for future integration with the burgeoning field of microanalytical systems, providing analytical platforms that retain the sensitivity and resolution required within low-volume, microfluidic culture technologies.

  4. Minimal-Learning-Parameter Technique Based Adaptive Neural Sliding Mode Control of MEMS Gyroscope

    Directory of Open Access Journals (Sweden)

    Bin Xu

    2017-01-01

    Full Text Available This paper investigates an adaptive neural sliding mode controller for MEMS gyroscopes with minimal-learning-parameter technique. Considering the system uncertainty in dynamics, neural network is employed for approximation. Minimal-learning-parameter technique is constructed to decrease the number of update parameters, and in this way the computation burden is greatly reduced. Sliding mode control is designed to cancel the effect of time-varying disturbance. The closed-loop stability analysis is established via Lyapunov approach. Simulation results are presented to demonstrate the effectiveness of the method.

  5. Neural network applications

    Science.gov (United States)

    Padgett, Mary L.; Desai, Utpal; Roppel, T.A.; White, Charles R.

    1993-01-01

    A design procedure is suggested for neural networks which accommodates the inclusion of such knowledge-based systems techniques as fuzzy logic and pairwise comparisons. The use of these procedures in the design of applications combines qualitative and quantitative factors with empirical data to yield a model with justifiable design and parameter selection procedures. The procedure is especially relevant to areas of back-propagation neural network design which are highly responsive to the use of precisely recorded expert knowledge.

  6. Neural Networks: Implementations and Applications

    NARCIS (Netherlands)

    Vonk, E.; Veelenturf, L.P.J.; Jain, L.C.

    1996-01-01

    Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in character recognition and other engineering areas

  7. Characterization of a MEMS Accelerometer for Inertial Navigating Applications

    Energy Technology Data Exchange (ETDEWEB)

    Kinney, R.D.

    1999-02-12

    Inertial MEMS sensors such as accelerometers and angular rotation sensing devices continue to improve in performance as advances in design and processing are made. Present state-of-the-art accelerometers have achieved performance levels in the laboratory that are consistent with requirements for successful application in tactical weapon navigation systems. However, sensor performance parameters that are of interest to the designer of inertial navigation systems are frequently not adequately addressed by the MEMS manufacturer. This paper addresses the testing and characterization of a MEMS accelerometer from an inertial navigation perspective. The paper discusses test objectives, data reduction techniques and presents results from the test of a three-axis MEMS accelerometer conducted at Sandia National Laboratories during 1997. The test was structured to achieve visibility and characterization of the accelerometer bias and scale factor stability overtime and temperature. Sandia is a multi-program laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the US Department of Energy under contract DE-AC04-94AL85000.

  8. New Trends on MEMS Sensor Technology for Harsh Environment Applications

    Directory of Open Access Journals (Sweden)

    Patricia M. NIEVA

    2007-10-01

    Full Text Available MEMS and NEMS sensor systems that can operate in the presence of high temperatures, corrosive media, and/or high radiation hold great promise for harsh environment applications. They would reduce weight, improve machine reliability and reduce cost in strategic market sectors such as automotive, avionics, oil well logging, and nuclear power. This paper presents a review of the recent advances in harsh-environment MEMS and NEMS sensors focusing on materials and devices. Special emphasis is put on high-temperature operation. Wide-bandgap semiconductor materials for high temperature applications are discussed from the device point of view. Micro-opto mechanical systems (MOEMS are presented as a new trend for high temperature applications. As an example of a harsh environment MOEMS sensor, a vibration sensor is presented.

  9. Capacitive MEMS accelerometer wide range modeling using artificial neural network

    OpenAIRE

    A. Baharodimehr; A. Abolfazl Suratgar; H. Sadeghi

    2009-01-01

    This paper presents a nonlinear model for a capacitive microelectromechanical accelerometer (MEMA). System parameters ofthe accelerometer are developed using the effect of cubic term of the folded‐flexure spring. To solve this equation, we use theFEA method. The neural network (NN) uses the Levenberg‐Marquardt (LM) method for training the system to have a moreaccurate response. The designed NN can identify and predict the displacement of the movable mass of accelerometer. Thesimulation result...

  10. Capacitive MEMS accelerometer wide range modeling using artificial neural network

    Directory of Open Access Journals (Sweden)

    A. Baharodimehr

    2009-08-01

    Full Text Available This paper presents a nonlinear model for a capacitive microelectromechanical accelerometer (MEMA. System parameters ofthe accelerometer are developed using the effect of cubic term of the folded‐flexure spring. To solve this equation, we use theFEA method. The neural network (NN uses the Levenberg‐Marquardt (LM method for training the system to have a moreaccurate response. The designed NN can identify and predict the displacement of the movable mass of accelerometer. Thesimulation results are very promising.

  11. Opportunities and challenges for MEMS technology in Army missile systems applications

    Science.gov (United States)

    Ruffin, Paul B.

    1999-07-01

    The military market drives the thrust for the development of robust, high performance MicroElectroMechanical Systems (MEMS) devices with applications such as: competent and smart munitions, aircraft and missile autopilots, tactical missile guidance, fire control systems, platform stabilization, smart structures with embedded inertial sensors, missile system health monitoring, aerodynamic flow control, and multiple intelligent small projectiles. Army missile applications will be a fertile market for MEMS products, such as MEMS-based inertial sensors. MEMS technology should significantly enhance performance and provide more robust mission capability in applications where arrays of MEMS devices are required. The Army Aviation and Missile Command Missile Research, Development, and Engineering Center is working diligently with other government agencies, academia, and industry to develop high performing MEMS devices to withstand shock, vibration, temperature, humidity, and long-term storage conditions often encountered by Army missile systems. The goals of the ongoing DARPA MEMS technology programs will meet a significant portion of the Army missile systems requirements. In lieu of presenting an all-inclusive review of Army MEMS applications, this paper addresses a number of opportunities and associated challenges for MEMS systems operating in military environments. Near term applications and the less mature, high-risk applications of MEMS devices are addressed.

  12. Role of MEMS in Biomedical Application: A Review

    Directory of Open Access Journals (Sweden)

    Himani SHARMA

    2010-04-01

    Full Text Available In this review, we have focused over MEMS (Micro Electro Mechanical System technology in the area of biomedical, which have played in important role-as diagnostic equipment in the diagnoses of different human body parts. The miniaturization of classical “bulky” measurement techniques has led to the realization of complex analytic systems, including such sensors as a Biochem Lab-On-Chip. This rapid progress in miniature devices and instrumentation development will significantly impact the practice of medical care as well as future advances in the biomedical field. Recently, MEMS along with modern IC also effected significantly on electrochemical, optical and acoustic wave transducer technologies, which have emerged as some of the most promising biomedical sensing technologies. Here, important features of these technologies, along with new developments and some of the applications, are presented.

  13. Intelligent MEMS spectral sensor for NIR applications (Conference Presentation)

    Science.gov (United States)

    Kantojärvi, Uula; Antila, Jarkko E.; Mäkynen, Jussi; Suhonen, Janne

    2017-05-01

    Near Infrared (NIR) spectrometers have been widely used in many material inspection applications, but mainly in central laboratories. The role of miniaturization, robustness of spectrometer and portability are really crucial when field inspection tools should be developed. We present an advanced spectral sensor based on a tunable Microelectromechanical (MEMS) Fabry-Perot Interferometer which will meet these requirements. We describe the wireless device design, operation principle and easy-to-use algorithms to adapt the sensor to number of applications. Multiple devices can be operated simultaneously and seamlessly through cloud connectivity. We also present some practical NIR applications carried out with truly portable NIR device.

  14. MEMS packaging

    CERN Document Server

    Hsu , Tai-Ran

    2004-01-01

    MEMS Packaging discusses the prevalent practices and enabling techniques in assembly, packaging and testing of microelectromechanical systems (MEMS). The entire spectrum of assembly, packaging and testing of MEMS and microsystems, from essential enabling technologies to applications in key industries of life sciences, telecommunications and aerospace engineering is covered. Other topics included are bonding and sealing of microcomponents, process flow of MEMS and microsystems packaging, automated microassembly, and testing and design for testing.The Institution of Engineering and Technology is

  15. Mems based valveless micropump for biomedical applications

    CSIR Research Space (South Africa)

    Van der Merwe, SW

    2010-01-01

    Full Text Available The valveless micropump holds great potential for the biomedical community in applications such as drug delivery systems, blood glucose monitoring, and many others. In this paper, the authors investigate the characteristics of a planar diffuser...

  16. MEMS temperature scanner: principles, advances, and applications

    Science.gov (United States)

    Otto, Thomas; Saupe, Ray; Stock, Volker; Gessner, Thomas

    2010-02-01

    Contactless measurement of temperatures has gained enormous significance in many application fields, ranging from climate protection over quality control to object recognition in public places or military objects. Thereby measurement of linear or spatially temperature distribution is often necessary. For this purposes mostly thermographic cameras or motor driven temperature scanners are used today. Both are relatively expensive and the motor drive devices are limited regarding to the scanning rate additionally. An economic alternative are temperature scanner devices based on micro mirrors. The micro mirror, attached in a simple optical setup, reflects the emitted radiation from the observed heat onto an adapted detector. A line scan of the target object is obtained by periodic deflection of the micro scanner. Planar temperature distribution will be achieved by perpendicularly moving the target object or the scanner device. Using Planck radiation law the temperature of the object is calculated. The device can be adapted to different temperature ranges and resolution by using different detectors - cooled or uncooled - and parameterized scanner parameters. With the basic configuration 40 spatially distributed measuring points can be determined with temperatures in a range from 350°C - 1000°C. The achieved miniaturization of such scanners permits the employment in complex plants with high building density or in direct proximity to the measuring point. The price advantage enables a lot of applications, especially new application in the low-price market segment This paper shows principle, setup and application of a temperature measurement system based on micro scanners working in the near infrared range. Packaging issues and measurement results will be discussed as well.

  17. Scanning Micromirror Platform Based on MEMS Technology for Medical Application

    Directory of Open Access Journals (Sweden)

    Eakkachai Pengwang

    2016-02-01

    Full Text Available This topical review discusses recent development and trends on scanning micromirrors for biomedical applications. This also includes a biomedical micro robot for precise manipulations in a limited volume. The characteristics of medical scanning micromirror are explained in general with the fundamental of microelectromechanical systems (MEMS for fabrication processes. Along with the explanations of mechanism and design, the principle of actuation are provided for general readers. In this review, several testing methodology and examples are described based on many types of actuators, such as, electrothermal actuators, electrostatic actuators, electromagnetic actuators, pneumatic actuators, and shape memory alloy. Moreover, this review provides description of the key fabrication processes and common materials in order to be a basic guideline for selecting micro-actuators. With recent developments on scanning micromirrors, performances of biomedical application are enhanced for higher resolution, high accuracy, and high dexterity. With further developments on integrations and control schemes, MEMS-based scanning micromirrors would be able to achieve a better performance for medical applications due to small size, ease in microfabrication, mass production, high scanning speed, low power consumption, mechanical stable, and integration compatibility.

  18. Micro Electromechanical Systems (MEMS Based Microfluidic Devices for Biomedical Applications

    Directory of Open Access Journals (Sweden)

    Nitin Afzulpurkar

    2011-06-01

    Full Text Available Micro Electromechanical Systems (MEMS based microfluidic devices have gained popularity in biomedicine field over the last few years. In this paper, a comprehensive overview of microfluidic devices such as micropumps and microneedles has been presented for biomedical applications. The aim of this paper is to present the major features and issues related to micropumps and microneedles, e.g., working principles, actuation methods, fabrication techniques, construction, performance parameters, failure analysis, testing, safety issues, applications, commercialization issues and future prospects. Based on the actuation mechanisms, the micropumps are classified into two main types, i.e., mechanical and non-mechanical micropumps. Microneedles can be categorized according to their structure, fabrication process, material, overall shape, tip shape, size, array density and application. The presented literature review on micropumps and microneedles will provide comprehensive information for researchers working on design and development of microfluidic devices for biomedical applications.

  19. MEMS Variable Stiffness Spring and Its Application in Fuze

    Directory of Open Access Journals (Sweden)

    Li Sui

    2014-04-01

    Full Text Available MEMS processing technology can manufacture any complex structures in a plane, using this point, a variable stiffness design idea for the planar micro-spring is proposed. That is, using one type of structure named contact pairs to achieve stiffness change during the micro-spring’s stretching process. Using contact pairs, three types of variable stiffness springs are designed: stiffness increase spring, stiffness decrease spring and stiffness hump spring. Finally, the variable stiffness springs’ application for fuze setback arming device is discussed. When the three types of springs are used in setback arming device, the stiffness decrease spring is better than the other two springs from security analysis. Kinematic analysis shows that, if the variable stiffness spring’s design is reasonable, the setback arming device not only can effectively solve the safety and reliability issues for rocket fuze, but also applies in small caliber grenade fuze’s working environment without changing the setback arming device’s size and structure. Analysis result indicate that the setback arming device based on MEMS variable stiffness spring is universal for rocket fuze and small caliber grenade fuze.

  20. Application of RF-MEMS-Based Split Ring Resonators (SRRs to the Implementation of Reconfigurable Stopband Filters: A Review

    Directory of Open Access Journals (Sweden)

    Ferran Martín

    2014-12-01

    Full Text Available In this review paper, several strategies for the implementation of reconfigurable split ring resonators (SRRs based on RF-MEMS switches are presented. Essentially three types of RF-MEMS combined with split rings are considered: (i bridge-type RF-MEMS on top of complementary split ring resonators CSRRs; (ii cantilever-type RF-MEMS on top of SRRs; and (iii cantilever-type RF-MEMS integrated with SRRs (or RF-MEMS SRRs. Advantages and limitations of these different configurations from the point of view of their potential applications for reconfigurable stopband filter design are discussed, and several prototype devices are presented.

  1. Application of RF-MEMS-based split ring resonators (SRRs) to the implementation of reconfigurable stopband filters: a review.

    Science.gov (United States)

    Martín, Ferran; Bonache, Jordi

    2014-12-02

    In this review paper, several strategies for the implementation of reconfigurable split ring resonators (SRRs) based on RF-MEMS switches are presented. Essentially three types of RF-MEMS combined with split rings are considered: (i) bridge-type RF-MEMS on top of complementary split ring resonators CSRRs; (ii) cantilever-type RF-MEMS on top of SRRs; and (iii) cantilever-type RF-MEMS integrated with SRRs (or RF-MEMS SRRs). Advantages and limitations of these different configurations from the point of view of their potential applications for reconfigurable stopband filter design are discussed, and several prototype devices are presented.

  2. Vibrations of Elastic Systems With Applications to MEMS and NEMS

    CERN Document Server

    Magrab, Edward B

    2012-01-01

    This work presents a unified approach to the vibrations of elastic systems as applied to MEMS devices, mechanical components, and civil structures. Applications include atomic force microscopes, energy harvesters, and carbon nanotubes and consider such complicating effects as squeeze film damping, viscous fluid loading, in-plane forces, and proof mass interactions with their elastic supports. These effects are analyzed as single degree-of-freedom models and as more realistic elastic structures. The governing equations and boundary conditions for beams, plates, and shells with interior and boundary attachments are derived by applying variational calculus to an expression describing the energy of the system. The advantages of this approach regarding the generation of orthogonal functions and the Rayleigh-Ritz method are demonstrated. A large number of graphs and tables are given to show the impact of various factors on the systems’ natural frequencies, mode shapes, and responses.

  3. MEMS Tunable Diffraction Grating for Spaceborne Imaging Spectroscopic Applications

    Directory of Open Access Journals (Sweden)

    Sanathanan S. Muttikulangara

    2017-10-01

    Full Text Available Diffraction gratings are among the most commonly used optical elements in applications ranging from spectroscopy and metrology to lasers. Numerous methods have been adopted for the fabrication of gratings, including microelectromechanical system (MEMS fabrication which is by now mature and presents opportunities for tunable gratings through inclusion of an actuation mechanism. We have designed, modeled, fabricated and tested a silicon based pitch tunable diffraction grating (PTG with relatively large resolving power that could be deployed in a spaceborne imaging spectrometer, for example in a picosatellite. We have carried out a detailed analytical modeling of PTG, based on a mass spring system. The device has an effective fill factor of 52% and resolving power of 84. Tuning provided by electrostatic actuation results in a displacement of 2.7 μ m at 40 V . Further, we have carried out vibration testing of the fabricated structure to evaluate its feasibility for spaceborne instruments.

  4. Long-term neural recordings using MEMS based moveable microelectrodes in the brain

    Directory of Open Access Journals (Sweden)

    Nathan Jackson

    2010-06-01

    Full Text Available One of the critical requirements of the emerging class of neural prosthetic devices is to maintain good quality neural recordings over long time periods. We report here a novel (Micro-ElectroMechanical Systems based technology that can move microelectrodes in the event of deterioration in neural signal to sample a new set of neurons. Microscale electro-thermal actuators are used to controllably move microelectrodes post-implantation in steps of approximately 9 µm. In this study, a total of 12 moveable microelectrode chips were individually implanted in adult rats. Two of the 12 moveable microelectrode chips were not moved over a period of 3 weeks and were treated as control experiments. During the first three weeks of implantation, moving the microelectrodes led to an improvement in the average SNR from 14.61 ± 5.21 dB before movement to 18.13 ± 4.99 dB after movement across all microelectrodes and all days. However, the average RMS values of noise amplitudes were similar at 2.98 ± 1.22 µV and 3.01 ± 1.16 µV before and after microelectrode movement. Beyond three weeks, the primary observed failure mode was biological rejection of the PMMA (dental cement based skull mount resulting in the device loosening and eventually falling from the skull. Additionally, the average SNR for functioning devices beyond three weeks was 11.88 ± 2.02 dB before microelectrode movement and was significantly different (p<0.01 from the average SNR of 13.34 ± 0.919 dB after movement. The results of this study demonstrate that MEMS based technologies can move microelectrodes in rodent brains in long-term experiments resulting in improvements in signal quality. Further improvements in packaging and surgical techniques will potentially enable movable microelectrodes to record cortical neuronal activity in chronic experiments.

  5. Neural Networks in Control Applications

    DEFF Research Database (Denmark)

    Sørensen, O.

    The intention of this report is to make a systematic examination of the possibilities of applying neural networks in those technical areas, which are familiar to a control engineer. In other words, the potential of neural networks in control applications is given higher priority than a detailed...... examined, and it appears that considering 'normal' neural network models with, say, 500 samples, the problem of over-fitting is neglible, and therefore it is not taken into consideration afterwards. Numerous model types, often met in control applications, are implemented as neural network models...... Kalmann filter) representing state space description. The potentials of neural networks for control of non-linear processes are also examined, focusing on three different groups of control concepts, all considered as generalizations of known linear control concepts to handle also non-linear processes...

  6. Titanium MEMS Technology Development for Drug Delivery and Microfluidic Applications

    Science.gov (United States)

    Khandan, Omid

    The use of microelectromechanical systems (MEMS) technology in medical and biological applications has increased dramatically in the past decade due to the potential for enhanced sensitivity, functionality, and performance associated with the miniaturization of devices, as well as the market potential for low-cost, personalized medicine. However, the utility of such devices in clinical medicine is ultimately limited due to factors associated with prevailing micromachined materials such as silicon, as it poses concerns of safety and reliability due to its intrinsically brittle properties, making it prone to catastrophic failure. Recent advances in titanium (Ti) micromachining provides an opportunity to create devices with enhanced safety and performance due to its proven biocompatibility and high fracture toughness, which causes it to fail by means of graceful, plasticity-based deformation. Motivated by this opportunity, we discuss our efforts to advance Ti MEMS technology in two ways: 1) Through the development of titanium-based microneedles (MNs) that seek to provide a safer, simpler, and more efficacious means of ocular drug delivery, and 2) Through the advancement of Ti anodic bonding for future realization of robust microfluidic devices for photocatalysis applications. As for the first of these thrusts, we show that MN devices with in-plane geometry and through-thickness fenestrations that serve as drug reservoirs for passive delivery via diffusive transport from fast-dissolving coatings can be fabricated utilizing Ti deep reactive ion etching (Ti DRIE). Our mechanical testing and finite element analysis (FEA) results suggest that these devices possess sufficient stiffness for reliable corneal insertion. Our MN coating studies show that, relative to solid MNs of identical shank dimension, fenestrated devices can increase drug carrying capacity by 5-fold. Furthermore, we demonstrate that through-etched fenestrations provide a protective cavity for delivering

  7. Neural fields theory and applications

    CERN Document Server

    Graben, Peter; Potthast, Roland; Wright, James

    2014-01-01

    With this book, the editors present the first comprehensive collection in neural field studies, authored by leading scientists in the field - among them are two of the founding-fathers of neural field theory. Up to now, research results in the field have been disseminated across a number of distinct journals from mathematics, computational neuroscience, biophysics, cognitive science and others. Starting with a tutorial for novices in neural field studies, the book comprises chapters on emergent patterns, their phase transitions and evolution, on stochastic approaches, cortical development, cognition, robotics and computation, large-scale numerical simulations, the coupling of neural fields to the electroencephalogram and phase transitions in anesthesia. The intended readership are students and scientists in applied mathematics, theoretical physics, theoretical biology, and computational neuroscience. Neural field theory and its applications have a long-standing tradition in the mathematical and computational ...

  8. MEMS Accelerometers Sensors: an Application in Virtual Reality

    Directory of Open Access Journals (Sweden)

    Daniel CORRÊA

    2010-09-01

    Full Text Available The measurement of a particular human body member position is extremely important in many applications. The human behavior understanding typically involves the body posture analysis or estimation, as well as the generated corresponding gestures. This behavior characterization allows analyzing, interpreting, and animating human actions and therefore enables us the use of experimental methodologies. Using the virtual reality devices to facilitate people’s lives, they can help to train and improve the actions of an Olympic athlete, for example and imitation of human actions by robotic systems. The systems development to monitor human body members’ movements is a growing interesting area, both in entertainment and in systems to help physically disabled people, as that developing assistive technology. To contribute to this area, this paper presents the experimental development of an instrumented glove prototype of low cost for the recognition of hand inclination movements, using a Micro-Electro-Mechanical Systems (MEMS accelerometer, by virtual reality concepts for demonstration in real time. We present the hardware that was developed, the calibration procedures, the achieved results with their statistical corresponding validation. The results allowed to state that the system is suitable for the inclination measurement in a 2D plan, thus allowing its use in entertainment systems and as an auxiliary device for assistive technology system.

  9. Predicting the random drift of MEMS gyroscope based on K-means clustering and OLS RBF Neural Network

    Science.gov (United States)

    Wang, Zhen-yu; Zhang, Li-jie

    2017-10-01

    Measure error of the sensor can be effectively compensated with prediction. Aiming at large random drift error of MEMS(Micro Electro Mechanical System))gyroscope, an improved learning algorithm of Radial Basis Function(RBF) Neural Network(NN) based on K-means clustering and Orthogonal Least-Squares (OLS) is proposed in this paper. The algorithm selects the typical samples as the initial cluster centers of RBF NN firstly, candidates centers with K-means algorithm secondly, and optimizes the candidate centers with OLS algorithm thirdly, which makes the network structure simpler and makes the prediction performance better. Experimental results show that the proposed K-means clustering OLS learning algorithm can predict the random drift of MEMS gyroscope effectively, the prediction error of which is 9.8019e-007°/s and the prediction time of which is 2.4169e-006s

  10. Neural Networks in Control Applications

    DEFF Research Database (Denmark)

    Sørensen, O.

    The intention of this report is to make a systematic examination of the possibilities of applying neural networks in those technical areas, which are familiar to a control engineer. In other words, the potential of neural networks in control applications is given higher priority than a detailed...... study of the networks themselves. With this end in view the following restrictions have been made: - Amongst numerous neural network structures, only the Multi Layer Perceptron (a feed-forward network) is applied. - Amongst numerous training algorithms, only four algorithms are examined, all...... in a recursive form (sample updating). The simplest is the Back Probagation Error Algorithm, and the most complex is the recursive Prediction Error Method using a Gauss-Newton search direction. - Over-fitting is often considered to be a serious problem when training neural networks. This problem is specifically...

  11. Neural Networks in Control Applications

    DEFF Research Database (Denmark)

    Sørensen, O.

    simulated process and compared. The closing chapter describes some practical experiments, where the different control concepts and training methods are tested on the same practical process operating in very noisy environments. All tests confirm that neural networks also have the potential to be trained......The intention of this report is to make a systematic examination of the possibilities of applying neural networks in those technical areas, which are familiar to a control engineer. In other words, the potential of neural networks in control applications is given higher priority than a detailed...... study of the networks themselves. With this end in view the following restrictions have been made: - Amongst numerous neural network structures, only the Multi Layer Perceptron (a feed-forward network) is applied. - Amongst numerous training algorithms, only four algorithms are examined, all...

  12. MEMS-Based Communications Systems for Space-Based Applications

    Science.gov (United States)

    DeLosSantos, Hector J.; Brunner, Robert A.; Lam, Juan F.; Hackett, Le Roy H.; Lohr, Ross F., Jr.; Larson, Lawrence E.; Loo, Robert Y.; Matloubian, Mehran; Tangonan, Gregory L.

    1995-01-01

    As user demand for higher capacity and flexibility in communications satellites increases, new ways to cope with the inherent limitations posed by the prohibitive mass and power consumption, needed to satisfy those requirements, are under investigation. Recent studies suggest that while new satellite architectures are necessary to enable multi-user, multi-data rate, multi-location satellite links, these new architectures will inevitably increase power consumption, and in turn, spacecraft mass, to such an extent that their successful implementation will demand novel lightweight/low power hardware approaches. In this paper, following a brief introduction to the fundamentals of communications satellites, we address the impact of micro-electro-mechanical systems (MEMS) technology, in particular micro-electro-mechanical (MEM) switches to mitigate the above mentioned problems and show that low-loss/wide bandwidth MEM switches will go a long way towards enabling higher capacity and flexibility space-based communications systems.

  13. APPLICATION OF MEMS TECHNOLOGY TO MICRO DIRECT METHANOL FUEL CELL

    OpenAIRE

    Liu, Xiaowei; Suo, Chunguang; Zhang, Yufeng; Zhang, Haifeng; Dhum, Ch.; Chen, Weiping; Lu, Xuebin

    2006-01-01

    Submitted on behalf of EDA Publishing Association (http://irevues.inist.fr/handle/2042/5920); International audience; In view of micro fuel cells, the silicon processes are employed for microfabrication of the micro direct methanol fuel cell (µDMFC). Using the MEMS technology we have successfully made single µDMFC as small as 10mm×8mm×3mm. The main reason for the use of MEMS processes is the prospective potential for miniaturization and economical mass production of small fuel cells. The doub...

  14. Sound Source Localization Through 8 MEMS Microphones Array Using a Sand-Scorpion-Inspired Spiking Neural Network

    Directory of Open Access Journals (Sweden)

    Christoph Beck

    2016-10-01

    Full Text Available Sand-scorpions and many other arachnids perceive their environment by using their feet to sense ground waves. They are able to determine amplitudes the size of an atom and locate the acoustic stimuli with an accuracy of within 13° based on their neuronal anatomy. We present here a prototype sound source localization system, inspired from this impressive performance. The system presented utilizes custom-built hardware with eight MEMS microphones, one for each foot, to acquire the acoustic scene, and a spiking neural model to localize the sound source. The current implementation shows smaller localization error than those observed in nature.

  15. Materials analysis of fluorocarbon films for MEMS applications

    NARCIS (Netherlands)

    Elders, J.; Jansen, Henricus V.; Elwenspoek, Michael Curt

    1994-01-01

    In this paper the results of the materials analysis of fluorocarbon (FC) films are presented. The properties of the fluorocarbon films are comparable to those of polytetrafluoroethylene (PTFE), better known under the trademarks such as teflon and fluon. The properties of PTFE are desirable for MEMS

  16. PECVD silicon carbide surface micromachining technology and selected MEMS applications

    NARCIS (Netherlands)

    Rajaraman, V.; Pakula, L.S.; Yang, H.; French, P.J.; Sarro, P.M.

    2011-01-01

    Attractive material properties of plasma enhanced chemical vapour deposited (PECVD) silicon carbide (SiC) when combined with CMOS-compatible low thermal budget processing provides an ideal technology platform for developing various microelectromechanical systems (MEMS) devices and merging them with

  17. A novel method of neural differentiation of PC12 cells by using Opti-MEM as a basic induction medium.

    Science.gov (United States)

    Hu, Rendong; Cao, Qiaoyu; Sun, Zhongqing; Chen, Jinying; Zheng, Qing; Xiao, Fei

    2017-10-19

    The PC12 cell line is a classical neuronal cell model due to its ability to acquire the sympathetic neurons features when deal with nerve growth factor (NGF). In the present study, the authors used a variety of different methods to induce PC12 cells, such as Opti-MEM medium containing different concentrations of fetal bovine serum (FBS) and horse serum compared with RPMI-1640 medium, and then observed the neurite length, differentiation, adhesion, cell proliferation and action potential, as well as the protein levels of axonal growth-associated protein 43 (GAP-43) and synaptic protein synapsin-1, among other differences. Compared with the conventional RPMI-1640 medium induction method, the new approach significantly improved the neurite length of induced cells (2.7 times longer), differentiation rate (30% increase), adhesion rate (21% increase) and expression of GAP-43 and synapsin-1 (three times), as well as reduced cell proliferation. The morphology of induced cells in Opti-MEM medium containing 0.5% FBS was more like that of neurons. Additionally, induced cells were also able to motivate the action potential after treatment for 6 days. Therefore, the research provided a novel, improved induction method of neural differentiation of PC12 cells using Opti-MEM medium containing 0.5% FBS, resulting in a better neuronal model cell line that can be widely used in neurobiology and neuropharmacology research.

  18. Neural networks and applications tutorial

    Science.gov (United States)

    Guyon, I.

    1991-09-01

    The importance of neural networks has grown dramatically during this decade. While only a few years ago they were primarily of academic interest, now dozens of companies and many universities are investigating the potential use of these systems and products are beginning to appear. The idea of building a machine whose architecture is inspired by that of the brain has roots which go far back in history. Nowadays, technological advances of computers and the availability of custom integrated circuits, permit simulations of hundreds or even thousands of neurons. In conjunction, the growing interest in learning machines, non-linear dynamics and parallel computation spurred renewed attention in artificial neural networks. Many tentative applications have been proposed, including decision systems (associative memories, classifiers, data compressors and optimizers), or parametric models for signal processing purposes (system identification, automatic control, noise canceling, etc.). While they do not always outperform standard methods, neural network approaches are already used in some real world applications for pattern recognition and signal processing tasks. The tutorial is divided into six lectures, that where presented at the Third Graduate Summer Course on Computational Physics (September 3-7, 1990) on Parallel Architectures and Applications, organized by the European Physical Society: (1) Introduction: machine learning and biological computation. (2) Adaptive artificial neurons (perceptron, ADALINE, sigmoid units, etc.): learning rules and implementations. (3) Neural network systems: architectures, learning algorithms. (4) Applications: pattern recognition, signal processing, etc. (5) Elements of learning theory: how to build networks which generalize. (6) A case study: a neural network for on-line recognition of handwritten alphanumeric characters.

  19. Conducting Polymers for Neural Prosthetic and Neural Interface Applications

    Science.gov (United States)

    2015-01-01

    Neural interfacing devices are an artificial mechanism for restoring or supplementing the function of the nervous system lost as a result of injury or disease. Conducting polymers (CPs) are gaining significant attention due to their capacity to meet the performance criteria of a number of neuronal therapies including recording and stimulating neural activity, the regeneration of neural tissue and the delivery of bioactive molecules for mediating device-tissue interactions. CPs form a flexible platform technology that enables the development of tailored materials for a range of neuronal diagnostic and treatment therapies. In this review the application of CPs for neural prostheses and other neural interfacing devices are discussed, with a specific focus on neural recording, neural stimulation, neural regeneration, and therapeutic drug delivery. PMID:26414302

  20. Neural Networks Methodology and Applications

    CERN Document Server

    Dreyfus, Gérard

    2005-01-01

    Neural networks represent a powerful data processing technique that has reached maturity and broad application. When clearly understood and appropriately used, they are a mandatory component in the toolbox of any engineer who wants make the best use of the available data, in order to build models, make predictions, mine data, recognize shapes or signals, etc. Ranging from theoretical foundations to real-life applications, this book is intended to provide engineers and researchers with clear methodologies for taking advantage of neural networks in industrial, financial or banking applications, many instances of which are presented in the book. For the benefit of readers wishing to gain deeper knowledge of the topics, the book features appendices that provide theoretical details for greater insight, and algorithmic details for efficient programming and implementation. The chapters have been written by experts ands seemlessly edited to present a coherent and comprehensive, yet not redundant, practically-oriented...

  1. BurstMem: A High-Performance Burst Buffer System for Scientific Applications

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Teng [Auburn University, Auburn, Alabama; Oral, H Sarp [ORNL; Wang, Yandong [Auburn University, Auburn, Alabama; Settlemyer, Bradley W [ORNL; Atchley, Scott [ORNL; Yu, Weikuan [Auburn University, Auburn, Alabama

    2014-01-01

    The growth of computing power on large-scale sys- tems requires commensurate high-bandwidth I/O system. Many parallel file systems are designed to provide fast sustainable I/O in response to applications soaring requirements. To meet this need, a novel system is imperative to temporarily buffer the bursty I/O and gradually flush datasets to long-term parallel file systems. In this paper, we introduce the design of BurstMem, a high- performance burst buffer system. BurstMem provides a storage framework with efficient storage and communication manage- ment strategies. Our experiments demonstrate that BurstMem is able to speed up the I/O performance of scientific applications by up to 8.5 on leadership computer systems.

  2. Optimization of the GaAs-on-Si Substrate for Microelectromechanical Systems (MEMS Sensor Application

    Directory of Open Access Journals (Sweden)

    Ying Yu

    2012-12-01

    Full Text Available Resonant Tunneling Diodes (RTD and High Electron Mobility Transistor (HEMT based on GaAs, as the piezoresistive sensing element, exhibit extremely high sensitivity in the MEMS sensors based on GaAs. To further expand their applications to the fields of MEMS sensors based on Si, we have studied the optimization of the GaAs epitaxy layers on Si wafers. Matching superlattice and strain superlattice were used, and the surface defect density can be improved by two orders of magnitude. Combing with the Raman spectrum, the residual stress was characterized, and it can be concluded from the experimental results that the residual stress can be reduced by 50%, in comparison with the original substrate. This method gives us a solution to optimize the epitaxy GaAs layers on Si substrate, which will also optimize our future process of integration RTD and HEMT based on GaAs on Si substrate for the MEMS sensor applications.

  3. NASA NDE Applications for Mobile MEMS Devices and Sensors

    Science.gov (United States)

    Wilson, William C.; Atkinson, Gary M.; Barclay, R. O.

    2008-01-01

    NASA would like new devices and sensors for performing nondestructive evaluation (NDE) of aerospace vehicles. These devices must be small in size/volume, mass, and power consumption. The devices must be autonomous and mobile so they can access the internal structures of aircraft and spacecraft and adequately monitor the structural health of these craft. The platforms must be mobile in order to transport NDE sensors for evaluating structural integrity and determining whether further investigations will be required. Microelectromechanical systems (MEMS) technology is crucial to the development of the mobile platforms and sensor systems. This paper presents NASA s needs for micro mobile platforms and MEMS sensors that will enable NDE to be performed on aerospace vehicles.

  4. Microelectromechanical Systems (MEMS)

    Indian Academy of Sciences (India)

    Once the fabrication processes got established and commercial MEMS foundries came into existence, the focus shifted to MEMS design and system development. After the launch of a few commercially successful MEMS devices, the research focus has shifted to exploration of vast areas of applications. Application areas ...

  5. A versatile multi-user polyimide surface micromachinning process for MEMS applications

    KAUST Repository

    Carreno, Armando Arpys Arevalo

    2015-04-01

    This paper reports a versatile multi-user micro-fabrication process for MEMS devices, the \\'Polyimide MEMS Multi-User Process\\' (PiMMPs). The reported process uses polyimide as the structural material and three separate metallization layers that can be interconnected depending on the desired application. This process enables for the first time the development of out-of-plane compliant mechanisms that can be designed using six different physical principles for actuation and sensing on a wafer from a single fabrication run. These principles are electrostatic motion, thermal bimorph actuation, capacitive sensing, magnetic sensing, thermocouple-based sensing and radio frequency transmission and reception. © 2015 IEEE.

  6. PLL application research of a broadband MEMS phase detector: Theory, measurement and modeling

    Science.gov (United States)

    Han, Juzheng; Liao, Xiaoping

    2017-06-01

    This paper evaluates the capability of a broadband MEMS phase detector in the application of phase locked loops (PLLs) through the aspect of theory, measurement and modeling. For the first time, it demonstrates how broadband property and optimized structure are realized through cascaded transmission lines and ANSYS simulations. The broadband MEMS phase detector shows potential in PLL application for its dc voltage output and large power handling ability which is important for munition applications. S-parameters of the power combiner in the MEMS phase detector are measured with S11 better than -15 dB and S23 better than -10 dB over the whole X-band. Compared to our previous works, developed phase detection measurements are performed and focused on signals at larger power levels up to 1 W. Cosine tendencies are revealed between the output voltage and the phase difference for both small and large signals. Simulation approach through equivalent circuit modeling is proposed to study the PLL application of the broadband MEMS phase detector. Synchronization and tracking properties are revealed.

  7. The black silicon method VI: high aspect ratio trench etching for MEMS applications

    NARCIS (Netherlands)

    Jansen, Henricus V.; de Boer, Meint J.; Elwenspoek, Michael Curt

    1996-01-01

    Etching high aspect ratio trenches (HART's) in silicon is becoming increasingly important for MEMS applications. Currently, the most important technique is dry reactive ion etching (RIE). This paper presents solutions for the most notorious problems during etching HART's: tilting and the aspect

  8. Design, fabrication and testing of a novel MEMS resonator for mass sensing applications

    DEFF Research Database (Denmark)

    Davis, Zachary James; Svendsen, Winnie Edith; Boisen, Anja

    2007-01-01

    Micro- and nanoelectromechanical systems (MEMS/NEMS) have a high potential for mass sensing application. By miniaturization of the dimensions, higher and higher sensitivities can be achieved. Here we are presenting finite element modelling and optimization of a free–free beam type mechanical...

  9. A MEMS vibration energy harvester for automotive applications

    Science.gov (United States)

    van Schaijk, R.; Elfrink, R.; Oudenhoven, J.; Pop, V.; Wang, Z.; Renaud, M.

    2013-05-01

    The objective of this work is to develop MEMS vibration energy harvesters for tire pressure monitoring systems (TPMS), they can be located on the rim or on the inner-liner of the car tire. Nowadays TPMS modules are powered by batteries with a limited lifetime. A large effort is ongoing to replace batteries with small and long lasting power sources like energy harvesters [1]. The operation principle of vibration harvesters is mechanical resonance of a seismic mass, where mechanical energy is converted into electrical energy. In general, vibration energy harvesters are of specific interest for machine environments where random noise or repetitive shock vibrations are present. In this work we present the results for MEMS based vibration energy harvesting for applying on the rim or inner-liner. The vibrations on the rim correspond to random noise. A vibration energy harvester can be described as an under damped mass-spring system acting like a mechanical band-pass filter, and will resonate at its natural frequency [2]. At 0.01 g2/Hz noise amplitude the average power can reach the level that is required to power a simple wireless sensor node, approximately 10 μW [3]. The dominant vibrations on the inner-liner consist mainly of repetitive high amplitude shocks. With a shock, the seismic mass is displaced, after which the mass will "ring-down" at its natural resonance frequency. During the ring-down period, part of the mechanical energy is harvested. On the inner-liner of the tire repetitive (one per rotation) high amplitude (few hundred g) shocks occur. The harvester enables an average power of a few tens of μW [4], sufficient to power a more sophisticated wireless sensor node that can measure additional tire-parameters besides pressure. In this work we characterized MEMS vibration energy harvesters for noise and shock excitation. We validated their potential for TPMS modules by measurements and simulation.

  10. MEMS Coupled Resonator for Filter Application in Air

    KAUST Repository

    Ilyas, Saad

    2017-11-03

    We present a mechanically coupled MEMS H resonator capable of performing simultaneous amplification and filter operation in air. The device comprises of two doubly clamped polyimide microbeams joined through the middle by a coupling beam of the same size. The resonator is fabricated via a multilayer surface micromachining process. A special fabrication process and device design is employed to enable the device\\'s operation in air and to achieve mechanical amplification of the output response. Moreover, mixed-frequency excitation is used to demonstrate a tunable wide band filter. The device design combined with the mixed-frequency excitation is used to demonstrate simultaneous amplification and filtering in air.

  11. Ex-vivo detection of neural events using THz BioMEMS

    CERN Document Server

    Abbas, Abdennour; Croix, Dominique; Salzet, Michel; Bocquet, Bertrand

    2009-01-01

    Background: Electromagnetic frequencies up to a few terahertz (THz) can yield real-time and noninvasive measurements on biological matter. Unfortunately, strong absorption in aqueous solutions and low spatial resolution return difficult free-space investigations. A new approach based on integrated THz circuits was used. The authors designed and fabricated a BioMEMS (Biological MicroElectro-Mechanical System) compatible with microfluidic circulation and electromagnetic propagation. It is dedicated to the ex vivo detection of nitric oxide synthase (NOS) activity, which is involved in neurodegenerative phenomena. Material/Methods: The biological model was a leech's central nervous system. After its injury, the production of NO was observed and measured in the far-THz spectral domain. The nerve cord was put inside a BioMEMS realized in polydimethylsiloxane (PDMS) sealed on a glass wafer. Glass is a good material for supporting high-frequency integrated waveguides such as coplanar waveguides (CPWs). Measurements w...

  12. MEMS Based SINS/OD Filter for Land Vehicles’ Applications

    Directory of Open Access Journals (Sweden)

    Huisheng Liu

    2017-01-01

    Full Text Available A constrained low-cost SINS/OD filter aided with magnetometer is proposed in this paper. The filter is designed to provide a land vehicle navigation solution by fusing the measurements of the microelectromechanical systems based inertial measurement unit (MEMS IMU, the magnetometer (MAG, and the velocity measurement from odometer (OD. First, accelerometer and magnetometer integrated algorithm is studied to stabilize the attitude angle. Next, a SINS/OD/MAG integrated navigation system is designed and simulated, using an adaptive Kalman filter (AKF. It is shown that the accuracy of the integrated navigation system will be implemented to some extent. The field-test shows that the azimuth misalignment angle will diminish to less than 1°. Finally, an outliers detection algorithm is studied to estimate the velocity measurement bias of the odometer. The experimental results show the enhancement in restraining observation outliers that improves the precision of the integrated navigation system.

  13. Biomaterials for MEMS

    CERN Document Server

    Chiao, Mu

    2011-01-01

    This book serves as a guide for practicing engineers, researchers, and students interested in MEMS devices that use biomaterials and biomedical applications. It is also suitable for engineers and researchers interested in MEMS and its applications but who do not have the necessary background in biomaterials.Biomaterials for MEMS highlights important features and issues of biomaterials that have been used in MEMS and biomedical areas. Hence this book is an essential guide for MEMS engineers or researchers who are trained in engineering institutes that do not provide the background or knowledge

  14. Mechanical and electromechanical properties of graphene and their potential application in MEMS

    Science.gov (United States)

    Khan, Zulfiqar H.; Kermany, Atieh R.; Öchsner, Andreas; Iacopi, Francesca

    2017-02-01

    Graphene-based micro-electromechanical systems (MEMS) are very promising candidates for next generation miniaturized, lightweight, and ultra-sensitive devices. In this review, we review the progress to date of the assessment of the mechanical, electromechanical, and thermomechanical properties of graphene for application in graphene-based MEMS. Graphene possesses a plethora of outstanding properties—such as a 1 TPa Young’s modulus, exceptionally high 2D failure strength that stems from its sp2 hybridization, and strong sigma bonding between carbon atoms. Such exceptional mechanical properties can enable, for example, graphene-based sound sources capable of generating sound beyond the audible range. The recently engineered piezoelectric properties of atomic force microscope tip-pressed graphene membranes or supported graphene on SiO2 substrates, have paved the way in fabricating graphene-based nano-generators and actuators. On the other hand, graphene’s piezoresistive properties have enabled miniaturized pressure and strain sensors. 2D graphene nano-mechanical resonators can potentially measure ultralow forces, charges and potentially detect single atomic masses. The exceptional tribology of graphene can play a significant role in achieving superlubricity. In addition, the highest reported thermal conductivity of graphene is amenable for use in chips and providing better performing MEMS, as heat is efficiently dissipated. On top of that, graphene membranes could be nano-perforated to realize specialized applications like DNA translocation and desalination. Finally, to ensure stability and reliability of the graphene-based MEMS, adhesion is an important mechanical property that should be considered. In general, graphene could be used as a structural material in resonators, sensors, actuators and nano-generators with better performance and sensitivity than conventional MEMS.

  15. Development, characterization and application of compact spectrometers based on MEMS with in-plane capacitive drives

    Science.gov (United States)

    Kenda, A.; Kraft, M.; Tortschanoff, A.; Scherf, Werner; Sandner, T.; Schenk, Harald; Luettjohann, Stephan; Simon, A.

    2014-05-01

    With a trend towards the use of spectroscopic systems in various fields of science and industry, there is an increasing demand for compact spectrometers. For UV/VIS to the shortwave near-infrared spectral range, compact hand-held polychromator type devices are widely used and have replaced larger conventional instruments in many applications. Still, for longer wavelengths this type of compact spectrometers is lacking suitable and affordable detector arrays. In perennial development Carinthian Tech Research AG together with the Fraunhofer Institute for Photonic Microsystems endeavor to close this gap by developing spectrometer systems based on photonic MEMS. Here, we review on two different spectrometer developments, a scanning grating spectrometer working in the NIR and a FT-spectrometer accessing the mid-IR range up to 14 μm. Both systems are using photonic MEMS devices actuated by in-plane comb drive structures. This principle allows for high mechanical amplitudes at low driving voltages but results in gratings respectively mirrors oscillating harmonically. Both systems feature special MEMS structures as well as aspects in terms of system integration which shall tease out the best possible overall performance on the basis of this technology. However, the advantages of MEMS as enabling technology for high scanning speed, miniaturization, energy efficiency, etc. are pointed out. Whereas the scanning grating spectrometer has already evolved to a product for the point of sale analysis of traditional Chinese medicine products, the purpose of the FT-spectrometer as presented is to demonstrate what is achievable in terms of performance. Current developments topics address MEMS packaging issues towards long term stability, further miniaturization and usability.

  16. Electrostatic MEMS vibration energy harvester for HVAC applications

    Science.gov (United States)

    Oxaal, J.; Hella, M.; Borca-Tasciuc, D.-A.

    2015-12-01

    This paper reports on an electrostatic MEMS vibration energy harvester with gapclosing interdigitated electrodes, designed for and tested on HVAC air ducts. The device is fabricated on SOI wafers using a custom microfabrication process. A dual-level physical stopper system is implemented in order to control the minimum gap between the electrodes and maximize the power output. It utilizes cantilever beams to absorb a portion of the impact energy as the electrodes approach the impact point, and a film of parylene with nanometer thickness deposited on the electrode sidewalls, which defines the absolute minimum gap and provides electrical insulation. The fabricated device was first tested on a vibration shaker to characterize its resonant behavior. The device exhibits spring hardening behavior due to impacts with the stoppers and spring softening behavior with increasing voltage bias. Testing was carried out on HVAC air duct vibrating with an RMS acceleration of 155 mgRMS and a primary frequency of 60 Hz with a PSD of 7.15·10-2 g2/Hz. The peak power measured is 12nW (0.6 nW RMS) with a PSD of 6.9·10-11 W/Hz at 240 Hz (four times of the primary frequency of 60 Hz), which is the highest output reported for similar vibration conditions and biasing voltages.

  17. Love-Mode MEMS Devices for Sensing Applications in Liquids

    Directory of Open Access Journals (Sweden)

    Cinzia Caliendo

    2016-01-01

    Full Text Available Love-wave-based MEMS devices are theoretically investigated in their potential role as a promising technological platform for the development of acoustic-wave-based sensors for liquid environments. Both single- and bi-layered structures have been investigated and the velocity dispersion curves were calculated for different layer thicknesses, crystallographic orientations, material types and electrical boundary conditions. High velocity materials have been investigated too, enabling device miniaturization, power consumption reduction and integration with the conditioning electronic circuits. The electroacoustic coupling coefficient dispersion curves of the first four Love modes are calculated for four dispersive coupling configurations based on a c-axis tilted ZnO layer on wz-BN substrate. The gravimetric sensitivity of four Love modes travelling at a common velocity of 9318 m/s along different layer thicknesses, and of three Love modes travelling at different velocity along a fixed ZnO layer thickness, are calculated in order to design enhanced-performance sensors. The phase velocity shift and attenuation due to the presence of a viscous liquid contacting the device surface are calculated for different thicknesses of a c-axis inclined ZnO layer onto BN half-space.

  18. Recent Advances of MEMS Resonators for Lorentz Force Based Magnetic Field Sensors: Design, Applications and Challenges

    Directory of Open Access Journals (Sweden)

    Agustín Leobardo Herrera-May

    2016-08-01

    Full Text Available Microelectromechanical systems (MEMS resonators have allowed the development of magnetic field sensors with potential applications such as biomedicine, automotive industry, navigation systems, space satellites, telecommunications and non-destructive testing. We present a review of recent magnetic field sensors based on MEMS resonators, which operate with Lorentz force. These sensors have a compact structure, wide measurement range, low energy consumption, high sensitivity and suitable performance. The design methodology, simulation tools, damping sources, sensing techniques and future applications of magnetic field sensors are discussed. The design process is fundamental in achieving correct selection of the operation principle, sensing technique, materials, fabrication process and readout systems of the sensors. In addition, the description of the main sensing systems and challenges of the MEMS sensors are discussed. To develop the best devices, researches of their mechanical reliability, vacuum packaging, design optimization and temperature compensation circuits are needed. Future applications will require multifunctional sensors for monitoring several physical parameters (e.g., magnetic field, acceleration, angular ratio, humidity, temperature and gases.

  19. Development of a Multi-User Polyimide-MEMS Fabrication Process and its Application to MicroHotplates

    KAUST Repository

    Lizardo, Ernesto B.

    2013-05-08

    Micro-electro-mechanical systems (MEMS) became possible thanks to the silicon based technology used to fabricate integrated circuits. Originally, MEMS fabrication was limited to silicon based techniques and materials, but the expansion of MEMS applications brought the need of a wider catalog of materials, including polymers, now being used to fabricate MEMS. Polyimide is a very attractive polymer for MEMS fabrication due to its high temperature stability compared to other polymers, low coefficient of thermal expansion, low film stress and low cost. The goal of this thesis is to expand the Polyimide usage as structural material for MEMS by the development of a multi-user fabrication process for the integration of this polymer along with multiple metal layers on a silicon substrate. The process also integrates amorphous silicon as sacrificial layer to create free-standing structures. Dry etching is used to release the devices and avoid stiction phenomena. The developed process is used to fabricate platforms for micro-hotplate gas sensors. The fabrication steps for the platforms are described in detail, explaining the process specifics and capabilities. An initial testing of the micro-hotplate is presented. As the process was also used as educational tool, some designs made by students and fabricated with the Polyimide-MEMS process are also presented.

  20. Fuzzy neural network theory and application

    CERN Document Server

    Liu, Puyin

    2004-01-01

    This book systematically synthesizes research achievements in the field of fuzzy neural networks in recent years. It also provides a comprehensive presentation of the developments in fuzzy neural networks, with regard to theory as well as their application to system modeling and image restoration. Special emphasis is placed on the fundamental concepts and architecture analysis of fuzzy neural networks. The book is unique in treating all kinds of fuzzy neural networks and their learning algorithms and universal approximations, and employing simulation examples which are carefully designed to he

  1. Small Antenna Based on MEMS and Metamaterial Properties for Reconfigurable Applications

    Directory of Open Access Journals (Sweden)

    G. Rosas-Guevara

    2013-01-01

    Full Text Available This paper presents the design of a novel, small coplanar antenna using microelectromechanical systems (MEMS and metamaterial (MTM properties. The antenna is designed using coplanar waveguide (CPW technology, presenting lower dielectric losses and higher signal integrity. The design method for this MEMS-MTM antenna, herein presented, is based on a composite right/left hand (CRLH transmission Line (TL using a mixed approach; considering the circuit model and full-wave simulations. The fabrication process is based on high-resistivity silicon wafers. The radiator has dimensions of 0.017 λg × 0.033 λg and a thickness of 0.0116 λg, whereas the complete circuit, of 5 mm × 11 mm, is equivalent to 0.14 λg × 0.31 λg. The antenna is designed using MEMS parallel-plate capacitors as the radiator, which also allows for the reconfiguration of the central frequency by electrostatically varying the capacitance. The results presented here correspond to a central frequency of 8.4 GHz. Due to its small size, this antenna has a wide variety of applications in wireless circuits for different fields.

  2. A Capacitance-To-Digital Converter for MEMS Sensors for Smart Applications.

    Science.gov (United States)

    Pérez Sanjurjo, Javier; Prefasi, Enrique; Buffa, Cesare; Gaggl, Richard

    2017-06-07

    The use of MEMS sensors has been increasing in recent years. To cover all the applications, many different readout circuits are needed. To reduce the cost and time to market, a generic capacitance-to-digital converter (CDC) seems to be the logical next step. This work presents a configurable CDC designed for capacitive MEMS sensors. The sensor is built with a bridge of MEMS, where some of them function with pressure. Then, the capacitive to digital conversion is realized using two steps. First, a switched-capacitor (SC) preamplifier is used to make the capacitive to voltage (C-V) conversion. Second, a self-oscillated noise-shaping integrating dual-slope (DS) converter is used to digitize this magnitude. The proposed converter uses time instead of amplitude resolution to generate a multibit digital output stream. In addition it performs noise shaping of the quantization error to reduce measurement time. This article shows the effectiveness of this method by measurements performed on a prototype, designed and fabricated using standard 0.13 µm CMOS technology. Experimental measurements show that the CDC achieves a resolution of 17 bits, with an effective area of 0.317 mm², which means a pressure resolution of 1 Pa, while consuming 146 µA from a 1.5 V power supply.

  3. A Capacitance-To-Digital Converter for MEMS Sensors for Smart Applications

    Science.gov (United States)

    Pérez Sanjurjo, Javier; Prefasi, Enrique; Buffa, Cesare; Gaggl, Richard

    2017-01-01

    The use of MEMS sensors has been increasing in recent years. To cover all the applications, many different readout circuits are needed. To reduce the cost and time to market, a generic capacitance-to-digital converter (CDC) seems to be the logical next step. This work presents a configurable CDC designed for capacitive MEMS sensors. The sensor is built with a bridge of MEMS, where some of them function with pressure. Then, the capacitive to digital conversion is realized using two steps. First, a switched-capacitor (SC) preamplifier is used to make the capacitive to voltage (C-V) conversion. Second, a self-oscillated noise-shaping integrating dual-slope (DS) converter is used to digitize this magnitude. The proposed converter uses time instead of amplitude resolution to generate a multibit digital output stream. In addition it performs noise shaping of the quantization error to reduce measurement time. This article shows the effectiveness of this method by measurements performed on a prototype, designed and fabricated using standard 0.13 µm CMOS technology. Experimental measurements show that the CDC achieves a resolution of 17 bits, with an effective area of 0.317 mm2, which means a pressure resolution of 1 Pa, while consuming 146 µA from a 1.5 V power supply. PMID:28590425

  4. Design and Simulation of RF MEMS Switch for Wireless Communication Applications

    Directory of Open Access Journals (Sweden)

    Girija Sravani K.

    2015-12-01

    Full Text Available In this paper, we have reported the design and analysis of a novel bulk-silicon fabricated RF MEMS capacitive switch. This RF switch has a short response time, low power consumption, and an IC compatible design. To lower the driving voltage and insertion loss, multiple geometries for the movable beam, membrane, and air gap are investigated using Software tool Comsol Multiphysics. Potential thermal stresses and deflection of the cantilever due to the application of forces have been investigated. Performance of the device under the application of forces also studied using the software.

  5. Application of neural networks in coastal engineering

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.

    methods. That is why it is becoming popular in various fields including coastal engineering. Waves and tides will play important roles in coastal erosion or accretion. This paper briefly describes the back-propagation neural networks and its application...

  6. CMOS compatible fabrication process of MEMS resonator for timing reference and sensing application

    Science.gov (United States)

    Huynh, Duc H.; Nguyen, Phuong D.; Nguyen, Thanh C.; Skafidas, Stan; Evans, Robin

    2015-12-01

    Frequency reference and timing control devices are ubiquitous in electronic applications. There is at least one resonator required for each of this device. Currently electromechanical resonators such as crystal resonator, ceramic resonator are the ultimate choices. This tendency will probably keep going for many more years. However, current market demands for small size, low power consumption, cheap and reliable products, has divulged many limitations of this type of resonators. They cannot be integrated into standard CMOS (Complement metaloxide- semiconductor) IC (Integrated Circuit) due to material and fabrication process incompatibility. Currently, these devices are off-chip and they require external circuitries to interface with the ICs. This configuration significantly increases the overall size and cost of the entire electronic system. In addition, extra external connection, especially at high frequency, will potentially create negative impacts on the performance of the entire system due to signal degradation and parasitic effects. Furthermore, due to off-chip packaging nature, these devices are quite expensive, particularly for high frequency and high quality factor devices. To address these issues, researchers have been intensively studying on an alternative for type of resonator by utilizing the new emerging MEMS (Micro-electro-mechanical systems) technology. Recent progress in this field has demonstrated a MEMS resonator with resonant frequency of 2.97 GHz and quality factor (measured in vacuum) of 42900. Despite this great achievement, this prototype is still far from being fully integrated into CMOS system due to incompatibility in fabrication process and its high series motional impedance. On the other hand, fully integrated MEMS resonator had been demonstrated but at lower frequency and quality factor. We propose a design and fabrication process for a low cost, high frequency and a high quality MEMS resonator, which can be integrated into a standard

  7. Novel Designs for Application Specific MEMS Pressure Sensors

    Directory of Open Access Journals (Sweden)

    Erik V. Thomsen

    2010-10-01

    Full Text Available In the framework of developing innovative microfabricated pressure sensors, we present here three designs based on different readout principles, each one tailored for a specific application. A touch mode capacitive pressure sensor with high sensitivity (14 pF/bar, low temperature dependence and high capacitive output signal (more than 100 pF is depicted. An optical pressure sensor intrinsically immune to electromagnetic interference, with large pressure range (0–350 bar and a sensitivity of 1 pm/bar is presented. Finally, a resonating wireless pressure sensor power source free with a sensitivity of 650 KHz/mmHg is described. These sensors will be related with their applications in  harsh environment, distributed systems and medical environment, respectively. For many aspects, commercially available sensors, which in vast majority are piezoresistive, are not suited for the applications proposed.

  8. Novel Designs for Application Specific MEMS Pressure Sensors

    DEFF Research Database (Denmark)

    Fragiacomo, Giulio; Reck, Kasper; Lorenzen, Lasse Vestergaard

    2010-01-01

    In the framework of developing innovative microfabricated pressure sensors, we present here three designs based on different readout principles, each one tailored for a specific application. A touch mode capacitive pressure sensor with high sensitivity (14 pF/bar), low temperature dependence...... and high capacitive output signal (more than 100 pF) is depicted. An optical pressure sensor intrinsically immune to electromagnetic interference, with large pressure range (0-350 bar) and a sensitivity of 1 pm/bar is presented. Finally, a resonating wireless pressure sensor power source free...... with a sensitivity of 650 KHz/mmHg is described. These sensors will be related with their applications in harsh environment, distributed systems and medical environment, respectively. For many aspects, commercially available sensors, which in vast majority are piezoresistive, are not suited for the applications...

  9. Magnetic wires in MEMS and bio-medical applications

    Energy Technology Data Exchange (ETDEWEB)

    Barbic, Mladen E-mail: mladen@caltech.edu

    2002-08-01

    Magnetic wires of appropriate design have special features making them useful to micro-electromechanical systems and bio-medical applications. Several applications that exploit the properties of magnetic wires are reviewed including: (a) a magnetic micro-manipulation technique that utilizes integrated micro-coils and magnetic micro-wires for localized positioning of micron-sized magnetic objects, (b) integrated micro-coil/micro-wire system operating as a micro-fluidic micro-motor, (c) mechanical tweezers using magneto-static interaction between two magnetic micro-wires, and (d) ultra-high gradient magnetic separation system based on porous membranes partially filled with magnetic wires.

  10. Fracture Probability of MEMS Optical Devices for Space Flight Applications

    Science.gov (United States)

    Fettig, Rainer K.; Kuhn, Jonathan L.; Moseley, S. Harvey; Kutyrev, Alexander S.; Orloff, Jon

    1999-01-01

    A bending fracture test specimen design is presented for thin elements used in optical devices for space flight applications. The specimen design is insensitive to load position, avoids end effect complications, and can be used to measure strength of membranes less than 2 microns thick. The theoretical equations predicting stress at failure are presented, and a detailed finite element model is developed to validate the equations for this application. An experimental procedure using a focused ion beam machine is outlined, and results from preliminary tests of 1.9 microns thick single crystal silicon are presented. These tests are placed in the context of a methodology for the design and evaluation of mission critical devices comprised of large arrays of cells.

  11. Decentralized neural control application to robotics

    CERN Document Server

    Garcia-Hernandez, Ramon; Sanchez, Edgar N; Alanis, Alma y; Ruz-Hernandez, Jose A

    2017-01-01

    This book provides a decentralized approach for the identification and control of robotics systems. It also presents recent research in decentralized neural control and includes applications to robotics. Decentralized control is free from difficulties due to complexity in design, debugging, data gathering and storage requirements, making it preferable for interconnected systems. Furthermore, as opposed to the centralized approach, it can be implemented with parallel processors. This approach deals with four decentralized control schemes, which are able to identify the robot dynamics. The training of each neural network is performed on-line using an extended Kalman filter (EKF). The first indirect decentralized control scheme applies the discrete-time block control approach, to formulate a nonlinear sliding manifold. The second direct decentralized neural control scheme is based on the backstepping technique, approximated by a high order neural network. The third control scheme applies a decentralized neural i...

  12. Effects on Ferroelectric Thin-Film Stacks and Devices for Piezoelectric MEMS Applications at Varied Total Ionizing Dose (TID)

    Science.gov (United States)

    2017-03-01

    Effects on Ferroelectric Thin- Film Stacks and Devices for Piezoelectric MEMS Applications at Varied Total Ionizing Dose (TID) Manuel Rivas1...Atlanta, GA, USA, 30332 Abstract: Lead zirconate titanate (PZT) based thin films play a key role in a wide variety of applications due to its...strain; ferroelectric; dielectric; piezoelectric Introduction Ferroelectric thin films and devices are vital components for numerous

  13. Applications of Pulse-Coupled Neural Networks

    CERN Document Server

    Ma, Yide; Wang, Zhaobin

    2011-01-01

    "Applications of Pulse-Coupled Neural Networks" explores the fields of image processing, including image filtering, image segmentation, image fusion, image coding, image retrieval, and biometric recognition, and the role of pulse-coupled neural networks in these fields. This book is intended for researchers and graduate students in artificial intelligence, pattern recognition, electronic engineering, and computer science. Prof. Yide Ma conducts research on intelligent information processing, biomedical image processing, and embedded system development at the School of Information Sci

  14. Advanced Mechatronics and MEMS Devices

    CERN Document Server

    2013-01-01

    Advanced Mechatronics and MEMS Devicesdescribes state-of-the-art MEMS devices and introduces the latest technology in electrical and mechanical microsystems. The evolution of design in microfabrication, as well as emerging issues in nanomaterials, micromachining, micromanufacturing and microassembly are all discussed at length in this volume. Advanced Mechatronics also provides a reader with knowledge of MEMS sensors array, MEMS multidimensional accelerometer, artificial skin with imbedded tactile components, as well as other topics in MEMS sensors and transducers. The book also presents a number of topics in advanced robotics and an abundance of applications of MEMS in robotics, like reconfigurable modular snake robots, magnetic MEMS robots for drug delivery and flying robots with adjustable wings, to name a few. This book also: Covers the fundamentals of advanced mechatronics and MEMS devices while also presenting new state-of-the-art methodology and technology used in the application of these devices Prese...

  15. Neural networks advances and applications 2

    CERN Document Server

    Gelenbe, E

    1992-01-01

    The present volume is a natural follow-up to Neural Networks: Advances and Applications which appeared one year previously. As the title indicates, it combines the presentation of recent methodological results concerning computational models and results inspired by neural networks, and of well-documented applications which illustrate the use of such models in the solution of difficult problems. The volume is balanced with respect to these two orientations: it contains six papers concerning methodological developments and five papers concerning applications and examples illustrating the theoret

  16. Spray-coatable negative photoresist for high topography MEMS applications

    Science.gov (United States)

    Arnold, Markus; Voigt, Anja; Haas, Sven; Schwenzer, Falk; Schwenzer, Gunther; Reuter, Danny; Gruetzner, Gabi; Geßner, Thomas

    2017-03-01

    In microsystem technology, the lithographical processing of substrates with a topography is very important. Interconnecting lines, which are routed over sloped topography sidewalls from the top of the protecting wafer to the contact pads of the device wafer, are one example of patterning over a topography. For structuring such circuit paths, a photolithography process, and therefore a process for homogeneous photoresist coating, is required. The most flexible and advantageous way of depositing a homogeneous photoresist film over structures with high topography steps is spray-coating. As a pattern transfer process for circuit paths in cavities, the lift-off process is widely used. A negative resist, like ma-N (MRT) or AZnLOF (AZ) is favoured for lift-off processes due to the existing negative angle of the sidewalls. Only a few sprayable negative photoresists are commercially available. In this paper, the development of a novel negative resist spray-coating based on a commercially available single-layer lift-off resist for spin-coating, especially for the patterning of structures inside the cavity and on the cavity wall, is presented. A variety of parameters influences the spray-coating process, and therefore the patterning results. Besides the spray-coating tool and the parameters, the composition of the resist solution itself also influences the coating results. For homogeneous resist coverage over the topography of the substrate, different solvent combinations for diluting the resist solution, different chuck temperatures during the coating process, and also the softbake conditions, are all investigated. The solvent formulations and the process conditions are optimized with respect to the homogeneity of the resist coverage on the top edge of the cavities. Finally, the developed spray-coating process, the resist material and the process stability are demonstrated by the following applications: (i) lift-off, (ii) electroplating, (iii) the wet and (iv) the dry

  17. Experimental Study on the Effects of Alumina Abrasive Particle Behavior in MR Polishing for MEMS Applications

    Directory of Open Access Journals (Sweden)

    Young-Jae Shin

    2008-01-01

    Full Text Available Recently, the magnetorheological (MR polishing process has been examined asa new ultra-precision polishing technology for micro parts in MEMS applications. In theMR polishing process, the magnetic force plays a dominant role. This method uses MRfluids which contains micro abrasives as a polishing media. The objective of the presentresearch is to shed light onto the material removal mechanism under various slurryconditions for polishing and to investigate surface characteristics, including shape analysisand surface roughness measurement, of spots obtained from the MR polishing process usingalumina abrasives. A series of basic experiments were first performed to determine theoptimum polishing conditions for BK7 glass using prepared slurries by changing the processparameters, such as wheel rotating speed and electric current. Using the obtained results,groove polishing was then performed and the results are investigated. Outstanding surfaceroughness of Ra=3.8nm was obtained on the BK7 glass specimen. The present resultshighlight the possibility of applying this polishing method to ultra-precision micro partsproduction, especially in MEMS applications.

  18. MEMBRAIN NEURAL NETWORK FOR VISUAL PATTERN RECOGNITION

    Directory of Open Access Journals (Sweden)

    Artur Popko

    2013-06-01

    Full Text Available Recognition of visual patterns is one of significant applications of Artificial Neural Networks, which partially emulate human thinking in the domain of artificial intelligence. In the paper, a simplified neural approach to recognition of visual patterns is portrayed and discussed. This paper is dedicated for investigators in visual patterns recognition, Artificial Neural Networking and related disciplines. The document describes also MemBrain application environment as a powerful and easy to use neural networks’ editor and simulator supporting ANN.

  19. 5 V Compatible Two-Axis PZT Driven MEMS Scanning Mirror with Mechanical Leverage Structure for Miniature LiDAR Application.

    Science.gov (United States)

    Ye, Liangchen; Zhang, Gaofei; You, Zheng

    2017-03-05

    The MEMS (Micro-Electronical Mechanical System) scanning mirror is an optical MEMS device that can scan laser beams across one or two dimensions. MEMS scanning mirrors can be applied in a variety of applications, such as laser display, bio-medical imaging and Light Detection and Ranging (LiDAR). These commercial applications have recently created a great demand for low-driving-voltage and low-power MEMS mirrors. However, no reported two-axis MEMS scanning mirror is available for usage in a universal supplying voltage such as 5 V. In this paper, we present an ultra-low voltage driven two-axis MEMS scanning mirror which is 5 V compatible. In order to realize low voltage and low power, a two-axis MEMS scanning mirror with mechanical leverage driven by PZT (Lead zirconate titanate) ceramic is designed, modeled, fabricated and characterized. To further decrease the power of the MEMS scanning mirror, a new method of impedance matching for PZT ceramic driven by a two-frequency mixed signal is established. As experimental results show, this MEMS scanning mirror reaches a two-axis scanning angle of 41.9° × 40.3° at a total driving voltage of 4.2 Vpp and total power of 16 mW. The effective diameter of reflection of the mirror is 2 mm and the operating frequencies of two-axis scanning are 947.51 Hz and 1464.66 Hz, respectively.

  20. 5 V Compatible Two-Axis PZT Driven MEMS Scanning Mirror with Mechanical Leverage Structure for Miniature LiDAR Application

    Directory of Open Access Journals (Sweden)

    Liangchen Ye

    2017-03-01

    Full Text Available The MEMS (Micro-Electronical Mechanical System scanning mirror is an optical MEMS device that can scan laser beams across one or two dimensions. MEMS scanning mirrors can be applied in a variety of applications, such as laser display, bio-medical imaging and Light Detection and Ranging (LiDAR. These commercial applications have recently created a great demand for low-driving-voltage and low-power MEMS mirrors. However, no reported two-axis MEMS scanning mirror is available for usage in a universal supplying voltage such as 5 V. In this paper, we present an ultra-low voltage driven two-axis MEMS scanning mirror which is 5 V compatible. In order to realize low voltage and low power, a two-axis MEMS scanning mirror with mechanical leverage driven by PZT (Lead zirconate titanate ceramic is designed, modeled, fabricated and characterized. To further decrease the power of the MEMS scanning mirror, a new method of impedance matching for PZT ceramic driven by a two-frequency mixed signal is established. As experimental results show, this MEMS scanning mirror reaches a two-axis scanning angle of 41.9° × 40.3° at a total driving voltage of 4.2 Vpp and total power of 16 mW. The effective diameter of reflection of the mirror is 2 mm and the operating frequencies of two-axis scanning are 947.51 Hz and 1464.66 Hz, respectively.

  1. Development of a stimuli-responsive polymer nanocomposite toward biologically optimized, MEMS-based neural probes

    Science.gov (United States)

    Hess, A. E.; Capadona, J. R.; Shanmuganathan, K.; Hsu, L.; Rowan, S. J.; Weder, C.; Tyler, D. J.; Zorman, C. A.

    2011-05-01

    This paper reports the development of micromachining processes and mechanical evaluation of a stimuli-responsive, mechanically dynamic polymer nanocomposite for biomedical microsystems. This nanocomposite consists of a cellulose nanofiber network encased in a polyvinyl acetate matrix. Micromachined tensile testing structures fabricated from the nanocomposite displayed a reversible and switchable stiffness comparable to bulk samples, with a Young's modulus of 3420 MPa when dry, reducing to ~20 MPa when wet, and a stiff-to-flexible transition time of ~300 s. This mechanically dynamic behavior is particularly attractive for the development of adaptive intracortical probes that are sufficiently stiff to insert into the brain without buckling, but become highly compliant upon insertion. Along these lines, a micromachined neural probe incorporating parylene insulating/moisture barrier layers and Ti/Au electrodes was fabricated from the nanocomposite using a fabrication process designed specifically for this chemical- and temperature-sensitive material. It was found that the parylene layers only slightly increased the stiffness of the probe in the wet state in spite of its much higher Young's modulus. Furthermore, the Ti/Au electrodes exhibited impedance comparable to Au electrodes on conventional substrates. Swelling of the nanocomposite was highly anisotropic favoring the thickness dimension by a factor of 8 to 12, leading to excellent adhesion between the nanocomposite and parylene layers and no discernable deformation of the probes when deployed in deionized water.

  2. Low-cost compact MEMS scanning ladar system for robotic applications

    Science.gov (United States)

    Moss, Robert; Yuan, Ping; Bai, Xiaogang; Quesada, Emilio; Sudharsanan, Rengarajan; Stann, Barry L.; Dammann, John F.; Giza, Mark M.; Lawler, William B.

    2012-06-01

    Future robots and autonomous vehicles require compact low-cost Laser Detection and Ranging (LADAR) systems for autonomous navigation. Army Research Laboratory (ARL) had recently demonstrated a brass-board short-range eye-safe MEMS scanning LADAR system for robotic applications. Boeing Spectrolab is doing a tech-transfer (CRADA) of this system and has built a compact MEMS scanning LADAR system with additional improvements in receiver sensitivity, laser system, and data processing system. Improved system sensitivity, low-cost, miniaturization, and low power consumption are the main goals for the commercialization of this LADAR system. The receiver sensitivity has been improved by 2x using large-area InGaAs PIN detectors with low-noise amplifiers. The FPGA code has been updated to extend the range to 50 meters and detect up to 3 targets per pixel. Range accuracy has been improved through the implementation of an optical T-Zero input line. A compact commercially available erbium fiber laser operating at 1550 nm wavelength is used as a transmitter, thus reducing the size of the LADAR system considerably from the ARL brassboard system. The computer interface has been consolidated to allow image data and configuration data (configuration settings and system status) to pass through a single Ethernet port. In this presentation we will discuss the system architecture and future improvements to receiver sensitivity using avalanche photodiodes.

  3. A MEMS-based solid propellant microthruster array for space and military applications

    Science.gov (United States)

    Chaalane, A.; Chemam, R.; Houabes, M.; Yahiaoui, R.; Metatla, A.; Ouari, B.; Metatla, N.; Mahi, D.; Dkhissi, A.; Esteve, D.

    2015-12-01

    Since combustion is an easy way to achieve large quantities of energy from a small volume, we developed a MEMS based solid propellant microthruster array for small spacecraft and micro-air-vehicle applications. A thruster is composed of a fuel chamber layer, a top-side igniter with a micromachined nozzle in the same silicon layer. Layers are assembled by adhesive bonding to give final MEMS array. The thrust force is generated by the combustion of propellant stored in a few millimeter cube chamber. The micro-igniter is a polysilicon resistor deposited on a low stress SiO2/SiNx thin membrane to ensure a good heat transfer to the propellant and thus a low electric power consumption. A large range of thrust force is obtained simply by varying chamber and nozzle geometry parameters in one step of Deep Reactive Ion Etching (DRIE). Experimental tests of ignition and combustion employing home made (DB+x%BP) propellant composed of a DoubleBase and Black-Powder. A temperature of 250 °C, enough to propellant initiation, is reached for 40 mW of electric power. A combustion rate of about 3.4 mm/s is measured for DB+20%BP propellant and thrust ranges between 0.1 and 3,5 mN are obtained for BP ratio between 10% and 30% using a microthruster of 100 μm of throat wide.

  4. Nanotechnology: MEMS and NEMS and their applications to smart systems and devices

    Science.gov (United States)

    Varadan, Vijay K.

    2003-10-01

    civil strutures and food and medical industries. This unique combination of technologies also results in novel conformal sensors that can be remotely sensed by an antenna system with the advantage of no power requirements at the sensor site. This paper provides a brief review of MEMS and NEMS based smart systems for various applications mentioned above. Carbon Nano Tubes (CNT) with their unique structure, have already proven to be valuable in their application as tips for scanning probe microscopy, field emission devices, nanoelectronics, H2-storage, electromagnetic absorbers, ESD, EMI films and coatings and structural composites. For many of these applications, highly purified and functionalized CNT which are compatible with many host polymers are needed. A novel microwave CVD processing technique to meet these requirements has been developed at Penn State Center for the Engineering of Electronic and Acoustic Materials and Devices (CEEAMD). This method enables the production of highly purified carbon nano tubes with variable size (from 5 - 40 nm) at low cost (per gram) and high yield. Whereas, carbon nano tubes synthesized using the laser ablation or arc discharge evaporation method always include impurity due to catalyst or catalyst support. The Penn State research is based on the use of zeolites over other metal/metal oxides in the microwave field for a high production and uniformity of the product. An extended coventional purification method has been employed to purify our products in order to remove left over impurity. A novel composite structure can be tailored by functionalizing carbon nano tubes and chemically bonding them with the polymer matrix e.g. block or graft copolymer, or even cross-linked copolymer, to impart exceptional structural, electronic and surface properties. Bio- and Mechanical-MEMS devices derived from this hybrid composites will be presented.

  5. The Oral Fluid MEMS/NEMS Chip (OFMNC): diagnostic and translational applications.

    Science.gov (United States)

    Li, Y; Denny, P; Ho, C-M; Montemagno, C; Shi, W; Qi, F; Wu, B; Wolinsky, L; Wong, D T

    2005-06-01

    The ability to monitor health status, disease onset and progression, and treatment outcome through non-invasive means is a most desirable goal in health-care promotion and delivery. There are three prerequisites for this goal to be realized: specific biomarkers associated with a health or disease state, a non-invasive approach to detect and monitor the biomarkers, and the technologies to discriminate between and among the biomarkers. We present a roadmap to achieve these goals using oral fluids as the diagnostic medium to scrutinize the health and/or disease status of individuals. This is an ideal opportunity to bridge state-of-the-art micro-/nano-electromechanical system (MEMS/NEMS) sensors to oral fluid for diagnostic applications. As the "mirror of body", oral fluid is a perfect medium to be explored for health and disease surveillance. The translational applications and opportunities are enormous.

  6. EDITORIAL: International MEMS Conference 2006

    Science.gov (United States)

    Tay, Francis E. H.; Jianmin, Miao; Iliescu, Ciprian

    2006-04-01

    The International MEMS conference (iMEMS2006) organized by the Institute of Bioengineering and Nanotechnology and Nanyang Technological University aims to provide a platform for academicians, professionals and industrialists in various related fields from all over the world to share and learn from each other. Of great interest is the incorporation of the theme of life sciences application using MEMS. It is the desire of this conference to initiate collaboration and form network of cooperation. This has continued to be the objective of iMEMS since its inception in 1997. The technological advance of MEMS over the past few decades has been truly exciting in terms of development and applications. In order to participate in this rapid development, a conference involving delegates from within the MEMS community and outside the community is very meaningful and timely. With the receipt of over 200 articles, delegates related to MEMS field from all over the world will share their perspectives on topics such as MEMS/MST Design, MEMS Teaching and Education, MEMS/MST Packaging, MEMS/MST Fabrication, Microsystems Applications, System Integration, Wearable Devices, MEMSWear and BioMEMS. Invited speakers and delegates from outside the field have also been involved to provide challenges, especially in the life sciences field, for the MEMS community to potentially address. The proceedings of the conference will be published as an issue in the online Journal of Physics: Conference Series and this can reach a wider audience and will facilitate the reference and citation of the work presented in the conference. We wish to express our deep gratitude to the International Scientific Committee members and the organizing committee members for contributing to the success of this conference. We would like to thank all the delegates, speakers and sponsors from all over the world for presenting and sharing their perspectives on topics related to MEMS and the challenges that MEMS can

  7. Design and fabrication of non silicon substrate based MEMS energy harvester for arbitrary surface applications

    Energy Technology Data Exchange (ETDEWEB)

    Balpande, Suresh S., E-mail: balpandes@rknec.edu [Ph.D.. Scholar, Department of Electronics Engineering Shri Ramdeobaba College of Engineering & Management, Nagpur-13, (M.S.) (India); Pande, Rajesh S. [Professor, Department of Electronics Engineering Shri Ramdeobaba College of Engineering & Management, Nagpur-13, (M.S.) (India)

    2016-04-13

    Internet of Things (IoT) uses MEMS sensor nodes and actuators to sense and control objects through Internet. IOT deploys millions of chemical battery driven sensors at different locations which are not reliable many times because of frequent requirement of charging & battery replacement in case of underground laying, placement at harsh environmental conditions, huge count and difference between demand (24 % per year) and availability (energy density growing rate 8% per year). Energy harvester fabricated on silicon wafers have been widely used in manufacturing MEMS structures. These devices require complex fabrication processes, costly chemicals & clean room. In addition to this silicon wafer based devices are not suitable for curved surfaces like pipes, human bodies, organisms, or other arbitrary surface like clothes, structure surfaces which does not have flat and smooth surface always. Therefore, devices based on rigid silicon wafers are not suitable for these applications. Flexible structures are the key solution for this problems. Energy transduction mechanism generates power from free surrounding vibrations or impact. Sensor nodes application has been purposefully selected due to discrete power requirement at low duty cycle. Such nodes require an average power budget in the range of about 0.1 microwatt to 1 mW over a period of 3-5 seconds. Energy harvester is the best alternate source in contrast with battery for sensor node application. Novel design of Energy Harvester based on cheapest flexible non silicon substrate i.e. cellulose acetate substrate have been modeled, simulated and analyzed on COMSOL multiphysics and fabricated using sol-gel spin coating setup. Single cantilever based harvester generates 60-75 mV peak electric potential at 22Hz frequency and approximately 22 µW power at 1K-Ohm load. Cantilever array can be employed for generating higher voltage by replicating this structure. This work covers design, optimization, fabrication of

  8. Design Optimization of Cantilever Based MEMS Micro-accelerometer for High-g Applications

    Directory of Open Access Journals (Sweden)

    B. D. PANT

    2009-11-01

    Full Text Available Design optimization study of micro-cantilever based MEMS accelerometer is presented in this paper. The cantilever structure is dc biased with an ac signal to extract output voltage generated due to the change in capacitance. This signal modifies the behavior of the sensing element. The cantilever performance under a combined inertial and electrostatic force has been considered for estimating the dimensional dependence of cantilever sensitivity, non-linearity, off-set and critical acceleration and operating voltages. The cantilever performance has been verified using ANSYSTM Multiphysics software. Finally, a micro-accelerometer based on an array of 15 cantilevers has been designed and fabricated with a high sensitivity of 3 - 4 mV/g with a non-linearity of < 1 % for high-g (50 g applications.

  9. Digital signal processing by virtual instrumentation of a MEMS magnetic field sensor for biomedical applications.

    Science.gov (United States)

    Juárez-Aguirre, Raúl; Domínguez-Nicolás, Saúl M; Manjarrez, Elías; Tapia, Jesús A; Figueras, Eduard; Vázquez-Leal, Héctor; Aguilera-Cortés, Luz A; Herrera-May, Agustín L

    2013-11-05

    We present a signal processing system with virtual instrumentation of a MEMS sensor to detect magnetic flux density for biomedical applications. This system consists of a magnetic field sensor, electronic components implemented on a printed circuit board (PCB), a data acquisition (DAQ) card, and a virtual instrument. It allows the development of a semi-portable prototype with the capacity to filter small electromagnetic interference signals through digital signal processing. The virtual instrument includes an algorithm to implement different configurations of infinite impulse response (IIR) filters. The PCB contains a precision instrumentation amplifier, a demodulator, a low-pass filter (LPF) and a buffer with operational amplifier. The proposed prototype is used for real-time non-invasive monitoring of magnetic flux density in the thoracic cage of rats. The response of the rat respiratory magnetogram displays a similar behavior as the rat electromyogram (EMG).

  10. Digital Signal Processing by Virtual Instrumentation of a MEMS Magnetic Field Sensor for Biomedical Applications

    Science.gov (United States)

    Juárez-Aguirre, Raúl; Domínguez-Nicolás, Saúl M.; Manjarrez, Elías; Tapia, Jesús A.; Figueras, Eduard; Vázquez-Leal, Héctor; Aguilera-Cortés, Luz A.; Herrera-May, Agustín L.

    2013-01-01

    We present a signal processing system with virtual instrumentation of a MEMS sensor to detect magnetic flux density for biomedical applications. This system consists of a magnetic field sensor, electronic components implemented on a printed circuit board (PCB), a data acquisition (DAQ) card, and a virtual instrument. It allows the development of a semi-portable prototype with the capacity to filter small electromagnetic interference signals through digital signal processing. The virtual instrument includes an algorithm to implement different configurations of infinite impulse response (IIR) filters. The PCB contains a precision instrumentation amplifier, a demodulator, a low-pass filter (LPF) and a buffer with operational amplifier. The proposed prototype is used for real-time non-invasive monitoring of magnetic flux density in the thoracic cage of rats. The response of the rat respiratory magnetogram displays a similar behavior as the rat electromyogram (EMG). PMID:24196434

  11. MEMS reliability

    CERN Document Server

    Hartzell, Allyson L; Shea, Herbert R

    2010-01-01

    This book focuses on the reliability and manufacturability of MEMS at a fundamental level. It demonstrates how to design MEMs for reliability and provides detailed information on the different types of failure modes and how to avoid them.

  12. Application of radial basis neural network for state estimation of ...

    African Journals Online (AJOL)

    user

    An original application of radial basis function (RBF) neural network for power system state estimation is proposed in this paper. The property of massive parallelism of neural networks is employed for this. The application of RBF neural network for state estimation is investigated by testing its applicability on a IEEE 14 bus ...

  13. Characterization of low temperature deposited atomic layer deposition TiO2 for MEMS applications

    NARCIS (Netherlands)

    Huang, Y.; Pandraud, G.; Sarro, P.M.

    2012-01-01

    TiO2 is an interesting and promising material for micro-/nanoelectromechanical systems (MEMS/NEMS). For high performance and reliable MEMS/NEMS, optimization of the optical characteristics, mechanical stress, and especially surface smoothness of TiO2 is required. To overcome the roughness issue of

  14. Sub-nanometer stable precision MEMS clamping mechanism maintaining clamp force unpowered for TEM application

    NARCIS (Netherlands)

    Brouwer, Dannis Michel; de Jong, B.R.; Soemers, Herman; van Dijk, Johannes

    2006-01-01

    A design is presented for a relatively large force (0.5 mN) high-precision MEMS clamping mechanism. The clamp is a part of a MEMS transmission electron microscope (TEM) sample manipulator, which needs to be fixed unpowered once positioned. The elastic deformation of the clamp suspension has been

  15. Fast Configuration of MEMS-Based Storage Devices for Streaming Applications

    NARCIS (Netherlands)

    Khatib, M.G.; van Dijk, H.W.

    2009-01-01

    An exciting class of storage devices is emerging: the class of Micro-Electro-Mechanical storage Systems (MEMS). Properties of MEMS-based storage devices include high density, small form factor, and low power. The use of this type of devices in mobile infotainment systems, such as video cameras is

  16. PREFACE: 14th International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS 2014)

    Science.gov (United States)

    2014-11-01

    It is our great pleasure to welcome you to the 14th International Conference on Micro- and Nano-Technology for Power Generation and Energy Conversion Applications, or PowerMEMS 2014, in Awaji Island, Japan. The aim of PowerMEM is to present the latest research results in the field of miniature, micro- and nano-scale technologies for power generation and energy conversion. The conference will also- give us the opportunity to exchange informations and new ideas in the field of Power MEMS/NEMS. The current status of the field of PowerMEMS spans the full spectrum from basic research to practical applications. We will enjoy valuable discussions not only from the viewpoint of academia but from commercial and industrial perspectives. In the conference, three invited speakers lead the technical program. We received 172 abstracts and after a careful reviewing process by the Technical Program Committee a total of 133 papers were selected for presentation. These have been organized into 16 Oral sessions in two parallel streams and two poster sessions including some late-news papers. The oral and regular poster papers are published by the Institute of Physics (IOP). We have also organized a PowerMEMS School in Kobe-Sannomiya contiguous to the main conference. This two-day school will cover various topics of energy harvesting. World leading experts will give invited lectures on their main topics. This is a new experiment to broaden the technology remit of our conference by organizing mini symposiums that aim to gather the latest research on the following topics by the organizers: Microscale Combustion, Wideband Vibration Energy Harvesting, RF Energy Transfer and Industrial Application. We hope this, and other activities will make PowerMEMS2014 a memorable success. One of the important programs in an international conference is the social program, and we prepare the PowerMEMS2014 banquet in the banquet room at the Westin Awaji Island Hotel. This will provide an opportunity to

  17. Closed-loop control of gimbal-less MEMS mirrors for increased bandwidth in LiDAR applications

    Science.gov (United States)

    Milanović, Veljko; Kasturi, Abhishek; Yang, James; Hu, Frank

    2017-05-01

    In 2016, we presented a low SWaP wirelessly controlled MEMS mirror-based LiDAR prototype which utilized an OEM laser rangefinder for distance measurement [1]. The MEMS mirror was run in open loop based on its exceptionally fast design and high repeatability performance. However, to further extend the bandwidth and incorporate necessary eyesafety features, we recently focused on providing mirror position feedback and running the system in closed loop control. Multiple configurations of optical position sensors, mounted on both the front- and the back-side of the MEMS mirror, have been developed and will be presented. In all cases, they include a light source (LED or laser) and a 2D photosensor. The most compact version is mounted on the backside of the MEMS mirror ceramic package and can "view" the mirror's backside through openings in the mirror's PCB and its ceramic carrier. This version increases the overall size of the MEMS mirror submodule from 12mm x 12mm x 4mm to 15mm x 15mm x 7mm. The sensors also include optical and electronic filtering to reduce effects of any interference from the application laser illumination. With relatively simple FPGA-based PID control running at the sample rate of 100 kHz, we could configure the overall response of the system to fully utilize the MEMS mirror's native bandwidth which extends well beyond its first resonance. When compared to the simple open loop method of suppressing overshoot and ringing which significantly limits bandwidth utilization, running the mirrors in closed loop control increased the bandwidth to nearly 3.7 times. A 2.0mm diameter integrated MEMS mirror with a resonant frequency of 1300 Hz was limited to 500Hz bandwidth in open loop driving but was increased to 3kHz bandwidth with the closed loop controller. With that bandwidth it is capable of very sharply defined uniform-velocity scans (sawtooth or triangle waveforms) which are highly desired in scanned mirror LiDAR systems. A 2.4mm diameter mirror with

  18. EDITORIAL: The Fifth International Workshop on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS 2005)

    Science.gov (United States)

    Suzuki, Yuji

    2006-09-01

    This special issue of Journal of Micromechanics and Microengineering contains a selection of papers from the Fifth International Workshop on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS 2005). The meeting was held on 28-30 November 2005 in Tokyo, Japan, and was supported by the 21COE Program 'Mechanical Systems Innovation' at the University of Tokyo. Power MEMS is one of the newest categories of MEMS, encompassing microdevices and microsystems for power generation, energy conversion and propulsion. The series of PowerMEMS workshops started in 2000 in Sendai, Japan and then moved to Tsukuba, Makuhari, Kyoto and Tokyo. At the 2005 meeting there were four invited, 25 oral and 26 poster presentations from 14 different countries. From the 55 papers in the proceedings, 18 papers have been selected for this special issue. The papers were chosen on the basis of their quality, scientific impact and relevance to the scope of the journal. The authors of the selected papers were invited to expand their manuscripts beyond the workshop page limitation and to revise the papers to meet the criteria of archival journal publication. All papers have been subjected to the journal's standard peer review process. The papers included herein are ordered according to four areas: energy harvesting, micro combustors and fuel processors, micro fuel cells, and micro engines and generators. It is my pleasure to present these selected papers from PowerMEMS 2005, and I hope that this special issue provides a valuable overview of the latest research in micro and nanotechnology for power generation and energy conversion.

  19. Improved Extension Neural Network and Its Applications

    Directory of Open Access Journals (Sweden)

    Yu Zhou

    2014-01-01

    Full Text Available Extension neural network (ENN is a new neural network that is a combination of extension theory and artificial neural network (ANN. The learning algorithm of ENN is based on supervised learning algorithm. One of important issues in the field of classification and recognition of ENN is how to achieve the best possible classifier with a small number of labeled training data. Training data selection is an effective approach to solve this issue. In this work, in order to improve the supervised learning performance and expand the engineering application range of ENN, we use a novel data selection method based on shadowed sets to refine the training data set of ENN. Firstly, we use clustering algorithm to label the data and induce shadowed sets. Then, in the framework of shadowed sets, the samples located around each cluster centers (core data and the borders between clusters (boundary data are selected as training data. Lastly, we use selected data to train ENN. Compared with traditional ENN, the proposed improved ENN (IENN has a better performance. Moreover, IENN is independent of the supervised learning algorithms and initial labeled data. Experimental results verify the effectiveness and applicability of our proposed work.

  20. Some metal oxides and their applications for creation of Microsystems (MEMS) and Energy Harvesting Devices (EHD)

    Science.gov (United States)

    Denishev, K.

    2016-10-01

    This is a review of a part of the work of the Technological Design Group at Technical University of Sofia, Faculty of Electronic Engineering and Technologies, Department of Microelectronics. It is dealing with piezoelectric polymer materials and their application in different microsystems (MEMS) and Energy Harvesting Devices (EHD), some organic materials and their applications in organic (OLED) displays, some transparent conductive materials etc. The metal oxides Lead Zirconium Titanate (PZT) and Zinc Oxide (ZnO) are used as piezoelectric layers - driving part of different sensors, actuators and EHD. These materials are studied in term of their performance in dependence on the deposition conditions and parameters. They were deposited as thin films by using RF Sputtering System. As technological substrates, glass plates and Polyethylenetherephtalate (PET) foils were used. For characterization of the materials, a test structure, based on Surface Acoustic Waves (SAW), was designed and prepared. The layers were characterized by Fourier Transform Infrared spectroscopy (FTIR). The piezoelectric response was tested at variety of mechanical loads (tensile strain, stress) in static and dynamic (multiple bending) mode. The single-layered and double-layered structures were prepared for piezoelectric efficiency increase. A structure of piezoelectric energy transformer is proposed and investigated.

  1. High performance MEMS accelerometers for concrete SHM applications and comparison with COTS accelerometers

    Science.gov (United States)

    Kavitha, S.; Joseph Daniel, R.; Sumangala, K.

    2016-01-01

    Accelerometers used for civil and huge mechanical structural health monitoring intend to measure the shift in the natural frequency of the monitored structures (accelerometers is inversely proportional to the frequency squared. Commercial MEMS (Micro Electro-Mechanical System) accelerometers that are generally designed for large bandwidth (e.g 25 kHz in ADXL150) have poor sensor level sensitivity and therefore uses complex signal conditioning electronics to achieve large sensitivity and low noise floor which in turn results in higher cost. In this work, an attempt has been made to design MEMS capacitive and piezoresistive accelerometers for smaller bandwidth using IntelliSuite and CoventorWare MEMS tools respectively. The various performance metrics have been obtained using simulation experiments and the results show that these sensors have excellent voltage sensitivity, noise performance and high resolution at sensor level and are even superior to commercial MEMS accelerometers.

  2. SiC Thin Films on Insulating Substrates for Robust Microelectromechanical System (MEMS) Applications

    National Research Council Canada - National Science Library

    Cheng, Lin; Steckl, Andrew J

    2003-01-01

    An increasing demand for robust MEMS devices, such as micro-sensors, that can operate at temperatures well above 300 deg C and often in severe environments has stimulated the search for alternatives to Si. [1...

  3. The Effects of Mechanical Coupling on the Electrical Impedance of MEMS Resonators for UHF Filter Applications

    National Research Council Canada - National Science Library

    Hohreiter, Luke

    2004-01-01

    .... These Finite Element Analysis (FEA) simulations are performed using the ANSYS software and demonstrate the significance of mechanical coupling between MEMS longitudinal-mode bar (L-Bar) resonators...

  4. Artificial neural network applications in ionospheric studies

    Directory of Open Access Journals (Sweden)

    L. R. Cander

    1998-06-01

    Full Text Available The ionosphere of Earth exhibits considerable spatial changes and has large temporal variability of various timescales related to the mechanisms of creation, decay and transport of space ionospheric plasma. Many techniques for modelling electron density profiles through entire ionosphere have been developed in order to solve the "age-old problem" of ionospheric physics which has not yet been fully solved. A new way to address this problem is by applying artificial intelligence methodologies to current large amounts of solar-terrestrial and ionospheric data. It is the aim of this paper to show by the most recent examples that modern development of numerical models for ionospheric monthly median long-term prediction and daily hourly short-term forecasting may proceed successfully applying the artificial neural networks. The performance of these techniques is illustrated with different artificial neural networks developed to model and predict the temporal and spatial variations of ionospheric critical frequency, f0F2 and Total Electron Content (TEC. Comparisons between results obtained by the proposed approaches and measured f0F2 and TEC data provide prospects for future applications of the artificial neural networks in ionospheric studies.

  5. Humidity influence on the adhesion of SU-8 polymer from MEMS applications

    Directory of Open Access Journals (Sweden)

    Birleanu Corina

    2017-01-01

    Full Text Available In this paper, the adhesion behaviors of SU-8 polymer thin film from MEMS application were investigated as a function of relative humidity. The adhesion test between the AFM tip and SU-8 polymer have been extensively studied using the atomic force microscope (AFM, for a relative humidity (RH varying between 20 and 90%. The samples for tests are SU-8 polymers hard baked at different temperatures. The hard bake temperature changes the tribo-mechanical properties of polymers. The paper reports the measurements and the modeling of adhesion forces versus humidity in controlled ranges between 20 to 90%RH. To investigate the effect of relative humidity on adhesion for SU-8 polymer hard baked we used an analytical method which encompasses the effect of capillarity as well as the solid-to-solid interaction. While the capillary force expression is considered to be the sum of the superficial tension and the Laplace force for the solid-solid interaction is expressed by the Derjagin, Muller and Toropov (DMT model of solids adhesion. The analytical results obtained are in accordance with those obtained experimentally.

  6. Numerical Simulation of a Novel Electroosmotic Micropump for Bio-MEMS Applications

    Directory of Open Access Journals (Sweden)

    Alireza Alishahi

    2014-12-01

    Full Text Available High lamination in microchannel is one of the main challenges in Lab-On-a-Chip’s components like micro total analyzer systems and any miniaturization of fluid channels intensify the viscose effects. In chip-scale, the electroosmotic flow is more efficient. Therefore, this study presents a MEMS-based low-voltage micropump for low-conductive biological samples and solutions, where twelve narrow miniaturized microchannels designed in one unit to efficiently using the electroosmotic effects which generated near the walls. Four microelectrodes are mounted in lateral sides of the microchannel and excited by low-voltage potential to generate pumping process inside the channel. We sweep the voltage amplitude and a linear variation of fluid velocity achieved by Finite-Element-Method (FEM simulation. We obtain a net average velocity of 0.1 mm/s; by applying 2 V and -2 V to the electrodes. Therefore, the proposed low-voltage design is able to pumping the low-conductive biofluids for conventional lab-on-a-chip applications.

  7. Research on the Piezoelectric Properties of AlN Thin Films for MEMS Applications

    Directory of Open Access Journals (Sweden)

    Meng Zhang

    2015-09-01

    Full Text Available In this paper, the piezoelectric coefficient d33 of AlN thin films for MEMS applications was studied by the piezoresponse force microscopy (PFM measurement and finite element method (FEM simulation. Both the sample without a top electrode and another with a top electrode were measured by PFM to characterize the piezoelectric property effectively. To obtain the numerical solution, an equivalent model of the PFM measurement system was established based on theoretical analysis. The simulation results for two samples revealed the effective measurement value d33-test should be smaller than the intrinsic value d33 due to the clamping effect of the substrate and non-ideal electric field distribution. Their influences to the measurement results were studied systematically. By comparing the experimental results with the simulation results, an experimental model linking the actual piezoelectric coefficient d33 with the measurement results d33-test was given under this testing configuration. A novel and effective approach was presented to eliminate the influences of substrate clamping and non-ideal electric field distribution and extract the actual value d33 of AlN thin films.

  8. Aluminum Nitride Micro-Channels Grown via Metal Organic Vapor Phase Epitaxy for MEMs Applications

    Energy Technology Data Exchange (ETDEWEB)

    Rodak, L.E.; Kuchibhatla, S.; Famouri, P.; Ting, L.; Korakakis, D.

    2008-01-01

    Aluminum nitride (AlN) is a promising material for a number of applications due to its temperature and chemical stability. Furthermore, AlN maintains its piezoelectric properties at higher temperatures than more commonly used materials, such as Lead Zirconate Titanate (PZT) [1, 2], making AlN attractive for high temperature micro and nanoelectromechanical (MEMs and NEMs) applications including, but not limited to, high temperature sensors and actuators, micro-channels for fuel cell applications, and micromechanical resonators. This work presents a novel AlN micro-channel fabrication technique using Metal Organic Vapor Phase Epitaxy (MOVPE). AlN easily nucleates on dielectric surfaces due to the large sticking coefficient and short diffusion length of the aluminum species resulting in a high quality polycrystalline growth on typical mask materials, such as silicon dioxide and silicon nitride [3,4]. The fabrication process introduced involves partially masking a substrate with a silicon dioxide striped pattern and then growing AlN via MOVPE simultaneously on the dielectric mask and exposed substrate. A buffered oxide etch is then used to remove the underlying silicon dioxide and leave a free standing AlN micro-channel. The width of the channel has been varied from 5 ìm to 110 ìm and the height of the air gap from 130 nm to 800 nm indicating the stability of the structure. Furthermore, this versatile process has been performed on (111) silicon, c-plane sapphire, and gallium nitride epilayers on sapphire substrates. Reflection High Energy Electron Diffraction (RHEED), Atomic Force Microscopy (AFM), and Raman measurements have been taken on channels grown on each substrate and indicate that the substrate is influencing the growth of the AlN micro-channels on the SiO2 sacrificial layer.

  9. The 13th International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS 2013)

    Science.gov (United States)

    Mitcheson, Paul; Beeby, Steve

    2013-12-01

    It is a pleasure to welcome you to The Royal Society in London and the 13th International Conference on Micro- and Nano-Technology for Power Generation and Energy Conversion Applications, or PowerMEMS 2013. The objective of PowerMEMS 2013 is to catalyse innovation in miniature, micro- and nano-scale technologies for power generation and energy conversion. The conference aims to stimulate the exchange of insights and information, and the development of new ideas in the Power MEMS/NEMS field as well as at the meso-scale. It will allow the attendees to interact and network within our multidisciplinary community that includes professionals from many branches of science and engineering. The technical program is led by four invited speakers covering inductive power transfer, chip scale power sources, thermal energy harvesting and implantable biofuel cells. We received 177 abstracts and following a careful reviewing process by the Technical Program Committee a total of 137 papers were selected for presentation. These have been organised into 16 oral sessions in two parallel streams and two poster sessions that have been augmented by 10 late news papers. The oral and regular poster papers are, for the first time, being published by the Institute of Physics. We have made every effort to make PowerMEMS 2013 the busiest yet and have included for the first time the PowerMEMS School. This two-day school held at Imperial College London covered a wide range of power-MEMS topics including technologies for power generation, power transmission, energy storage, power electronics interfaces and metrology. Registrations for the School exceeded our expectations and it was full by early November. We hope this, and other activities such as the Discussion Panel and the inclusion of late news papers, will make PowerMEMS 2013 a memorable success. We have also reached out to new communities, such as those working in wireless power transfer and RF harvesting to broaden the technology remit of

  10. RF MEMS Phase Shifters and their Application in Phase Array Antennas

    Science.gov (United States)

    Scardelletti, Maximilian; Ponchak, George E.; Zaman, Afroz J.; Lee, Richard Q.

    2005-01-01

    Electronically scanned arrays are required for space based radars that are capable of tracking multiple robots, rovers, or other assets simultaneously and for beam-hopping communication systems between the various assets. ^Traditionally, these phased array antennas used GaAs Monolithic Microwave Integrated Circuit (MMIC) phase shifters, power amplifiers, and low noise amplifiers to amplify and steer the beam, but the development of RF MEMS switches over the past ten years has enabled system designers to consider replacing the GaAs MMIC phase shifters with RF Micro-Electro Mechanical System (MEMS) phase shifters. In this paper, the implication of replacing the relatively high loss GaAs MMICs with low loss MEMS phase shifters is investigated.

  11. Low Loss High Isolation NEMS/MEMS Switch for High Frequency RF Applications

    Directory of Open Access Journals (Sweden)

    Elangovan R.

    2015-03-01

    Full Text Available MEMS switches are advantageous in terms of low power consumption, switching times, high isolation, low insertion loss and many more. This paper proposes a MEMS switch with high isolation and low insertion loss. The model used is a CPW configuration with a cantilever series switch built on a silicon substrate. The switch parameters are optimized for the lowest insertion loss and return loss. An insertion loss values of -0.1305 dB in the down state with return loss of -38 dB and -75 dB of isolation have been observed in the high frequency range.

  12. Neural network models: Insights and prescriptions from practical applications

    Energy Technology Data Exchange (ETDEWEB)

    Samad, T. [Honeywell Technology Center, Minneapolis, MN (United States)

    1995-12-31

    Neural networks are no longer just a research topic; numerous applications are now testament to their practical utility. In the course of developing these applications, researchers and practitioners have been faced with a variety of issues. This paper briefly discusses several of these, noting in particular the rich connections between neural networks and other, more conventional technologies. A more comprehensive version of this paper is under preparation that will include illustrations on real examples. Neural networks are being applied in several different ways. Our focus here is on neural networks as modeling technology. However, much of the discussion is also relevant to other types of applications such as classification, control, and optimization.

  13. Fuzzy logic and neural networks basic concepts & application

    CERN Document Server

    Alavala, Chennakesava R

    2008-01-01

    About the Book: The primary purpose of this book is to provide the student with a comprehensive knowledge of basic concepts of fuzzy logic and neural networks. The hybridization of fuzzy logic and neural networks is also included. No previous knowledge of fuzzy logic and neural networks is required. Fuzzy logic and neural networks have been discussed in detail through illustrative examples, methods and generic applications. Extensive and carefully selected references is an invaluable resource for further study of fuzzy logic and neural networks. Each chapter is followed by a question bank

  14. MEMS-based wavelength and orbital angular momentum demultiplexer for on-chip applications

    DEFF Research Database (Denmark)

    Lyubopytov, Vladimir; Porfirev, Alexey P.; Gurbatov, Stanislav O.

    2017-01-01

    Summary form only given. We demonstrate a new tunable MEMS-based WDM&OAM Fabry-Pérot filter for simultaneous wavelength (WDM) and Orbital Angular Momentum (OAM) (de)multiplexing. The WDM&OAM filter is suitable for dense on-chip integration and dedicated for the next generation of optical...

  15. 3-D coupled electric mechanics for MEMS: Applications of COSOLVE-EM

    NARCIS (Netherlands)

    Gilbert, J.R.; Legtenberg, R.; Legtenberg, Rob; Senturia, S.D.

    1995-01-01

    Micro-electro-mechanical systems (MEMS) are often designed on scales at which electrostatic forces are capable of moving or deforming the parts of the system. In this regime accurate prediction of device behavior may require 3D coupled simulations between the electrostatic and mechanical domains. We

  16. Review of polymer MEMS micromachining

    Science.gov (United States)

    Kim, Brian J.; Meng, Ellis

    2016-01-01

    The development of polymer micromachining technologies that complement traditional silicon approaches has enabled the broadening of microelectromechanical systems (MEMS) applications. Polymeric materials feature a diverse set of properties not present in traditional microfabrication materials. The investigation and development of these materials have opened the door to alternative and potentially more cost effective manufacturing options to produce highly flexible structures and substrates with tailorable bulk and surface properties. As a broad review of the progress of polymers within MEMS, major and recent developments in polymer micromachining are presented here, including deposition, removal, and release techniques for three widely used MEMS polymer materials, namely SU-8, polyimide, and Parylene C. The application of these techniques to create devices having flexible substrates and novel polymer structural elements for biomedical MEMS (bioMEMS) is also reviewed.

  17. Fuzzy neural networks: theory and applications

    Science.gov (United States)

    Gupta, Madan M.

    1994-10-01

    During recent years, significant advances have been made in two distinct technological areas: fuzzy logic and computational neural networks. The theory of fuzzy logic provides a mathematical framework to capture the uncertainties associated with human cognitive processes, such as thinking and reasoning. It also provides a mathematical morphology to emulate certain perceptual and linguistic attributes associated with human cognition. On the other hand, the computational neural network paradigms have evolved in the process of understanding the incredible learning and adaptive features of neuronal mechanisms inherent in certain biological species. Computational neural networks replicate, on a small scale, some of the computational operations observed in biological learning and adaptation. The integration of these two fields, fuzzy logic and neural networks, have given birth to an emerging technological field -- fuzzy neural networks. Fuzzy neural networks, have the potential to capture the benefits of these two fascinating fields, fuzzy logic and neural networks, into a single framework. The intent of this tutorial paper is to describe the basic notions of biological and computational neuronal morphologies, and to describe the principles and architectures of fuzzy neural networks. Towards this goal, we develop a fuzzy neural architecture based upon the notion of T-norm and T-conorm connectives. An error-based learning scheme is described for this neural structure.

  18. Parylene as a new membrane material for BioMEMS applications

    Science.gov (United States)

    Lu, Bo

    The work in this thesis aims to use MEMS and microfabrication technologies to develop two types of parylene membrane devices for biomedical applications. The first device is the parylene membrane filter for cancer detection. The presence of circulating tumor cells (CTC) in patient blood is an important sign of cancer metastasis. However, currently there are two big challenges for CTC detection. First, CTCs are extremely rare, especially at the early stage of cancer metastasis. Secondly, CTCs are very fragile, and are very likely to be damaged during the capturing process. By using size-based membrane filtration through the specially designed parylene filters, together with a constant-pressure filtration system, we are able to capture the CTCs from patient blood with high capture efficiency, high viability, moderate enrichment, and high throughput. Both immunofluorescence enumeration and telomerase activity detection have been used to detect and differentiate the captured CTCs. The feasibility of further cell culture of the captured CTCs has also been demonstrated, which could be a useful way to increase the number of CTCs for future studies. Models of the time-dependent cell membrane damage are developed to predict and prevent CTC damage during this detection process. The results of clinical trials further demonstrate that the parylene membrane filter is a promising device for cancer detection. The second device is the parylene artificial Bruch's membrane for age-related macular degeneration (AMD). AMD is usually characterized by an impaired Bruch's membrane with much lowered permeability, which impedes the transportation of nutrients from choroid vessels to nourish the retinal pigment epithelial (RPE) cells and photoreceptors. Parylene is selected as a substitute material because of its good mechanical properties, transparency, biocompatibility, and machinability. More importantly, it is found that the permeability of submicron parylene is very similar to that of

  19. Power gating of VLSI circuits using MEMS switches in low power applications

    KAUST Repository

    Shobak, Hosam

    2011-12-01

    Power dissipation poses a great challenge for VLSI designers. With the intense down-scaling of technology, the total power consumption of the chip is made up primarily of leakage power dissipation. This paper proposes combining a custom-designed MEMS switch to power gate VLSI circuits, such that leakage power is efficiently reduced while accounting for performance and reliability. The designed MEMS switch is characterized by an 0.1876 ? ON resistance and requires 4.5 V to switch. As a result of implementing this novel power gating technique, a standby leakage power reduction of 99% and energy savings of 33.3% are achieved. Finally the possible effects of surge currents and ground bounce noise are studied. These findings allow longer operation times for battery-operated systems characterized by long standby periods. © 2011 IEEE.

  20. Synthesis and Characterization of LPCVD Polysilicon and Silicon Nitride Thin Films for MEMS Applications

    Directory of Open Access Journals (Sweden)

    N. Sharma

    2014-01-01

    Full Text Available Inherent residual stresses during material deposition can have profound effects on the functionality and reliability of fabricated MEMS devices. Residual stress often causes device failure due to curling, buckling, or fracture. Typically, the material properties of thin films used in surface micromachining are not very well controlled during deposition. The residual stress, for example, tends to vary significantly for different deposition conditions; experiments were carried out to study the polysilicon and silicon nitride deposited by Low Pressure Chemical Vapor Deposition (LPCVD method at wide range of process conditions. High temperature annealing effects on stress in case polysilicon are also reported. The reduced residual stress levels can significantly improve device performance, reliability, and yield as MEMS devices become smaller.

  1. Going Fabless with MEMS

    Directory of Open Access Journals (Sweden)

    Bhaskar CHOUBEY

    2011-04-01

    Full Text Available The Microelectromechanical sensors are finding increasing applications in everyday life. However, each MEMS sensor is generally fabricated on its own individual process. This leads to high cost per sensor. It has been suggested the MEMS should and would follow the path of integrated circuits industry, wherein fabless firms could concentrate on design leading pure-foundries to perfect the manufacturing process. With several designs being manufactured on the same process, the installation cost of fabrication would be evenly shared. Simultaneously, multiple project wafer runs are being offered for MEMS processes to encourage design activity in universities as well as startups. This paper reviews the present state of this transition through an experience of designing and manufacturing microelectromechanical resonators on different processes.

  2. X-ray diffraction characterization of suspended structures forMEMS applications

    Energy Technology Data Exchange (ETDEWEB)

    Goudeau, P.; Tamura, N.; Lavelle, B.; Rigo, S.; Masri, T.; Bosseboeuf, A.; Sarnet, T.; Petit, J.-A.; Desmarres, J.-M.

    2005-09-15

    Mechanical stress control is becoming one of the major challenges for the future of micro and nanotechnologies. Micro scanning X-ray diffraction is one of the promising techniques that allows stress characterization in such complex structures at sub micron scales. Two types of MEMS structure have been studied: a bilayer cantilever composed of a gold film deposited on poly-silicon and a boron doped silicon bridge. X-ray diffraction results are discussed in view of numerical simulation experiments.

  3. Application of MEMS Accelerometers and Gyroscopes in Fast Steering Mirror Control Systems

    Directory of Open Access Journals (Sweden)

    Jing Tian

    2016-03-01

    Full Text Available In a charge-coupled device (CCD-based fast steering mirror (FSM tracking control system, high control bandwidth is the most effective way to enhance the closed-loop performance. However, the control system usually suffers a great deal from mechanical resonances and time delays induced by the low sampling rate of CCDs. To meet the requirements of high precision and load restriction, fiber-optic gyroscopes (FOGs are usually used in traditional FSM tracking control systems. In recent years, the MEMS accelerometer and gyroscope are becoming smaller and lighter and their performance have improved gradually, so that they can be used in a fast steering mirror (FSM to realize the stabilization of the line-of-sight (LOS of the control system. Therefore, a tentative approach to implement a CCD-based FSM tracking control system, which uses MEMS accelerometers and gyroscopes as feedback components and contains an acceleration loop, a velocity loop and a position loop, is proposed. The disturbance suppression of the proposed method is the product of the error attenuation of the acceleration loop, the velocity loop and the position loop. Extensive experimental results show that the MEMS accelerometers and gyroscopes can act the similar role as the FOG with lower cost for stabilizing the LOS of the FSM tracking control system.

  4. Protein patterning on polycrystalline silicon-germanium via standard UV lithography for bioMEMS applications

    Energy Technology Data Exchange (ETDEWEB)

    Lenci, S., E-mail: silvia.lenci@gmail.com [Dipartimento di Ingegneria dell' Informazione, University of Pisa, Via G. Caruso 16, I-56122 Pisa (Italy); imec, Kapeldreef 75, Leuven B-3001 (Belgium); Tedeschi, L.; Domenici, C.; Lande, C. [Istituto di Fisiologia Clinica, CNR, via G. Moruzzi 1, Pisa I-56124 (Italy); Nannini, A.; Pennelli, G.; Pieri, F. [Dipartimento di Ingegneria dell' Informazione, University of Pisa, Via G. Caruso 16, I-56122 Pisa (Italy); Severi, S. [imec, Kapeldreef 75, Leuven B-3001 (Belgium)

    2010-10-12

    Polycrystalline silicon-germanium (poly-SiGe) is a promising structural material for the post-processing of micro electro-mechanical systems (MEMS) on top of complementary metal-oxide-semiconductor (CMOS) substrates. Combining MEMS and CMOS allows for the development of high-performance devices. We present for the first time selective protein immobilization on top of poly-SiGe surfaces, an enabling technique for the development of novel poly-SiGe based MEMS biosensors. Active regions made of 3-aminopropyl-triethoxysilane (APTES) were defined using silane deposition onto photoresist patterns followed by lift-off in organic solvents. Subsequently, proteins were covalently bound on the created APTES patterns. Fluorescein-labeled human serum albumin (HSA) was used to verify the immobilization procedure while the binding capability of the protein layer was tested by an antigen-labeled antibody pair. Inspection by fluorescence microscopy showed protein immobilization inside the desired bioactive areas and low non-specific adsorption outside the APTES pattern. Furthermore, the quality of the silane patches was investigated by treatment with 30 nm-diameter gold nanoparticles and scanning electron microscope observation. The developed technique is therefore a promising first step towards the realization of poly-SiGe based biosensors.

  5. Application of Neural Networks to House Pricing and Bond Rating

    NARCIS (Netherlands)

    Daniëls, H.A.M.; Kamp, B.; Verkooijen, W.J.H.

    1997-01-01

    Feed forward neural networks receive a growing attention as a data modelling tool in economic classification problems. It is well-known that controlling the design of a neural network can be cumbersome. Inaccuracies may lead to a manifold of problems in the application such as higher errors due to

  6. Hidden neural networks: application to speech recognition

    DEFF Research Database (Denmark)

    Riis, Søren Kamaric

    1998-01-01

    We evaluate the hidden neural network HMM/NN hybrid on two speech recognition benchmark tasks; (1) task independent isolated word recognition on the Phonebook database, and (2) recognition of broad phoneme classes in continuous speech from the TIMIT database. It is shown how hidden neural networks...

  7. Application of Neural Networks for Energy Reconstruction

    CERN Document Server

    Damgov, Jordan

    2002-01-01

    The possibility to use Neural Networks for reconstruction ofthe energy deposited in the calorimetry system of the CMS detector is investigated. It is shown that using feed-forward neural network, good linearity, Gaussian energy distribution and good energy resolution can be achieved. Significant improvement of the energy resolution and linearity is reached in comparison with other weighting methods for energy reconstruction.

  8. New Programmable CMOS Fuzzifier and C2V Circuits Applicable in FLC Chip for Signal Processing of MEMS Glucose Sensors

    Directory of Open Access Journals (Sweden)

    Ghader Yosefi

    2015-08-01

    Full Text Available This paper presents the design and simulation of improved circuits of Fuzzifier and capacitance to voltage (C2V converter. The Fuzzifier circuit is designed based on analog advantages such as low die area, high accuracy, and simplicity which are added to the fuzzy system advantages. For implementing this idea, a programmable Membership Function Generator (MFG including differential pair circuit as a Fuzzifier is proposed. The MFG generates arbitrary forms of Gaussian, Trapezoidal, and Triangular shapes. The shape types are achieved using control switches and different reference voltages. This structure is also general purpose in tuning the slope of Membership Functions (MFs using scaled transistors with different W/L ratios. With a specific purpose in mind, we used it here to generate fuzzy language terms from sensed classic data of a blood glucose microsensor. Thus we proposed a C2V circuit to convert capacitance variations (from MEMS glucose microsensor to voltage values as classic data. The proposed mentioned circuits can be applicable in design of Fuzzy Logic Controller (FLC chips to detect blood glucose, process its data in Fuzzy environment, and control insulin injection of diabetic patients by MEMS micropumps. The simulation results are achieved by MATLAB and Hspice software in 0.35 μm CMOS standard technology.

  9. MEMS Calculator

    Science.gov (United States)

    SRD 166 MEMS Calculator (Web, free access)   This MEMS Calculator determines the following thin film properties from data taken with an optical interferometer or comparable instrument: a) residual strain from fixed-fixed beams, b) strain gradient from cantilevers, c) step heights or thicknesses from step-height test structures, and d) in-plane lengths or deflections. Then, residual stress and stress gradient calculations can be made after an optical vibrometer or comparable instrument is used to obtain Young's modulus from resonating cantilevers or fixed-fixed beams. In addition, wafer bond strength is determined from micro-chevron test structures using a material test machine.

  10. Application of artificial neural networks (ANNs) in wine technology.

    Science.gov (United States)

    Baykal, Halil; Yildirim, Hatice Kalkan

    2013-01-01

    In recent years, neural networks have turned out as a powerful method for numerous practical applications in a wide variety of disciplines. In more practical terms neural networks are one of nonlinear statistical data modeling tools. They can be used to model complex relationships between inputs and outputs or to find patterns in data. In food technology artificial neural networks (ANNs) are useful for food safety and quality analyses, predicting chemical, functional and sensory properties of various food products during processing and distribution. In wine technology, ANNs have been used for classification and for predicting wine process conditions. This review discusses the basic ANNs technology and its possible applications in wine technology.

  11. MEMS-based LC tank with extended tuning range for multiband applications

    Science.gov (United States)

    Cazzorla, A.; Farinelli, P.; Urbani, L.; Sorrentino, R.; Margesin, B.

    2016-09-01

    This paper presents the modeling, simulations, and measurements of a compact multiband microelectromechanical (MEMS)-based LC tank resonator suitable for low phase noise voltage-controlled oscillators (VCOs). The resonator is based on a high-Q spiral inductor and high capacitance ratio varicap fully integrated in FBK-irst (Fondazione Bruno Kessler) MEMS manufacturing process. The design of the varicap is based on double-actuation mechanism with a mechanical central bond that inhibits the pull-in allowing for a theoretically infinite tuning ratio. The measurements have shown a total not continuous capacitance ratio (Cr) of 5.2 with a continuous variation of the capacitance values in the range 225 fF-600 fF which corresponds to a continuous capacitance ratio (Cr*) of 2.6. The performance repeatability, the power-handling capability, and the stability over time were tested on 10 samples showing a negligible variation of the capacitance values. The spiral inductor consists of a suspended gold membrane thick 5 µm in a circular shape which was modeled in order to optimize the quality factor (Q) in the frequency range 2-4 GHz. The measurement results show a Q of about 55 in the 2-4 GHz frequency band. The LC tank measurements show an overall tuning range better than of 45% in the 3.2-4.9 GHz frequency band, consisting of two continuous tuning ranges of 7.5% and 25%. The LC tank allowed the design of MEMS-based voltage-controlled oscillators (VCOs) with an overall tuning better than 60% in the frequency range 2.15 GHz-3.85 GHz and two separate regions of continuous tuning range. The VCO prototype will be fabricated on Surface Mount Technology on RO4350 laminate. The main figures of merit are presented in comparison with the state of the art.

  12. Resin-bonded permanent magnetic films with out-of-plane magnetization for MEMS applications

    Energy Technology Data Exchange (ETDEWEB)

    Rozenberg, Yu.I. [Department of Electrical Engineering-Physical Electronics, Tel-Aviv University, Tel-Aviv 69978 (Israel); Rosenberg, Yuri [Wolfson Applied Materials Research Center, Tel-Aviv University, Tel-Aviv 69978 (Israel)]. E-mail: yurir@post.tau.ac.il; Krylov, V. [Department of Solid Mechanics, Materials and Systems, Tel-Aviv University, Tel-Aviv 69978 (Israel); Belitsky, G. [Department of Electrical Engineering-Physical Electronics, Tel-Aviv University, Tel-Aviv 69978 (Israel); Department of Solid Mechanics, Materials and Systems, Tel-Aviv University, Tel-Aviv 69978 (Israel); Shacham-Diamand, Yosi [Department of Electrical Engineering-Physical Electronics, Tel-Aviv University, Tel-Aviv 69978 (Israel)

    2006-10-15

    Resin-bonded permanent magnets with out-of-plain direction of magnetization and improved magnetic properties for magnetic MEMS actuator have been created. The material investigated consists of magnetically anisotropic strontium ferrite particles embedded into epoxy resin matrix upto a volume loading of 80%. Intrinsic coercivity H {sub ci} of 6000 Oe (480 kA/m), residual magnetic flux density B {sub r} up to 4000 G (0.4 T) and maximum energy product (BH){sub max} of 3.0 MG Oe (23.6 kJ/m{sup 3}) have been attained due to magnetic-field-induced alignment of the ferrite particles during curing process.

  13. Application of SnO2 Nano-powder on MEMS Type Gas Sensors

    OpenAIRE

    E. Abbaspour-Sani; M. N. Azarmanesh; M. Nasseri; Kh. Farhadi

    2007-01-01

    This paper describes a cost effective and new method for preparing SnO2 sol-gel as the basic material for the Micro-Electro-Mechanical System (MEMS) type gas sensors. The SnO2 sol-gel was prepared by mixing SnCl4, propanol and isopropanol in a specified ratio. The produced sol-gel was exposed to two different decomposition temperatures of 600°C and 1200°C. Thermal treatment of the sol-gel resulted in formation of nano-crystalline single phase SnO2 powder having two different grain sizes. The ...

  14. Multi frequency excited MEMS cantilever beam resonator for Mixer-Filter applications

    KAUST Repository

    Chandran, Akhil A.

    2016-09-15

    Wireless communication uses Radio Frequency waves to transfer information from one point to another. The modern RF front end devices are implementing MEMS in their designs so as to exploit the inherent properties of MEMS devices, such as its low mass, low power consumption, and small size. Among the components in the RF transceivers, band pass filters and mixers play a vital role in achieving the optimum RF performance. And this paper aims at utilizing an electrostatically actuated micro cantilever beam resonator\\'s nonlinear frequency mixing property to realize a Mixer-Filter configuration through multi-frequency excitation. The paper studies about the statics and dynamics of the device. Simulations are carried out to study the added benefits of multi frequency excitation. The modelling of the cantilever beam has been done using a Reduced Order Model of the Euler-Bernoulli\\'s beam equation by implementing the Galerkin discretization. The device is shown to be able to down-convert signals from 960 MHz of frequency to an intermediate frequency around 50 MHz and 70 MHz in Phase 1 and 2, respectively. The simulation showed promising results to take the project to the next level. © 2016 IEEE.

  15. On using the dynamic snap-through motion of MEMS initially curved microbeams for filtering applications

    KAUST Repository

    Ouakad, Hassen M.

    2014-01-01

    Numerical and experimental investigations of the dynamics of micromachined shallow arches (initially curved microbeams) and the possibility of using their dynamic snap-through motion for filtering purposes are presented. The considered MEMS arches are actuated by a DC electrostatic load along with an AC harmonic load. Their dynamics is examined numerically using a Galerkin-based reduced-order model when excited near both their first and third natural frequencies. Several simulation results are presented demonstrating interesting jumps and dynamic snap-through behavior of the MEMS arches and their attractive features for uses as band-pass filters, such as their sharp roll-off from pass-bands to stop-bands and their flat response. Experimental work is conducted to test arches realized of curved polysilicon microbeams when excited by DC and AC loads. Experimental data of the micromachined curved beams are shown for the softening and hardening behavior near the first and third natural frequencies, respectively, as well as dynamic snap-through motion. © 2013 Elsevier Ltd.

  16. Nanotribological characterization of molecularly thick lubricant films for applications to MEMS/NEMS by AFM.

    Science.gov (United States)

    Liu, Huiwen; Bhushan, Bharat

    2003-01-01

    Molecularly thick perfluoropolyether (PFPE) films are considered to be good protective films for micro/nanoelectromechanical systems (MEMS/NEMS) to reduce stiction, friction, and improve their durability. Understanding the nanotribological performance and mechanisms of these films are quite important for efficient lubrication for MEMS/NEMS devices. These devices are used in various operating environments and their effect on friction, adhesion and durability needs to be clarified. For this purpose, mobile and chemically bonded PFPE films were deposited by dip coating technique. The friction and adhesion properties of these films were characterized by atomic force microscopy (AFM). The effect of rest time, velocity, relative humidity, and temperature on nanotribological properties of these films was studied. Durability of these films was also measured by repeated cycling tests. The adhesion, friction mechanisms of PFPE at molecular scale, and the mechanisms of the effect of operating environment and durability are subject of this paper. This study found that adsorption of water, formation of meniscus and its change during sliding, viscosity, and surface chemistry properties play a big role on the friction, adhesion, and durability of the lubricant films.

  17. Mechanical characterization of micro/nanoscale structures for MEMS/NEMS applications using nanoindentation techniques.

    Science.gov (United States)

    Li, Xiaodong; Bhushan, Bharat; Takashima, Kazuki; Baek, Chang-Wook; Kim, Yong-Kweon

    2003-01-01

    Mechanical properties of micro/nanoscale structures are needed to design reliable micro/nanoelectromechanical systems (MEMS/NEMS). Micro/nanomechanical characterization of bulk materials of undoped single-crystal silicon and thin films of undoped polysilicon, SiO(2), SiC, Ni-P, and Au have been carried out. Hardness, elastic modulus and scratch resistance of these materials were measured by nanoindentation and microscratching using a nanoindenter. Fracture toughness was measured by indentation using a Vickers indenter. Bending tests were performed on the nanoscale silicon beams, microscale Ni-P and Au beams using a depth-sensing nanoindenter. It is found that the SiC film exhibits higher hardness, elastic modulus and scratch resistance as compared to other materials. In the bending tests, the nanoscale Si beams failed in a brittle manner with a flat fracture surface. The notched Ni-P beam showed linear deformation behavior followed by abrupt failure. The Au beam showed elastic-plastic deformation behavior. FEM simulation can well predict the stress distribution in the beams studied. The nanoindentation, scratch and bending tests used in this study can be satisfactorily used to evaluate the mechanical properties of micro/nanoscale structures for use in MEMS/NEMS.

  18. Design and fabrication of insect-inspired composite wings for MAV application using MEMS technology

    Science.gov (United States)

    Bao, X. Q.; Bontemps, A.; Grondel, S.; Cattan, E.

    2011-12-01

    Insect wings consist of supporting veins and flexible membranes using fibrous composite material. This paper describes a method of wing design and fabrication based on composite, mimicking insect wings through advanced microelectromechanical system (MEMS) technology. SU-8 'fiber' reinforced polydimethylsiloxane (PDMS) membrane forms a fine structure, approaching real wings not only in material conception but also in mechanical performance. Based on a design in its initial stage, a new process was developed integrating all steps into a single procedure. We use a tailored AZ 4562 resist layer as the mold for PDMS wing membrane structuring. A 20 nm hydrophilic oxide layer was grown on the substrate to solve the final lift-off problems which become more severe when the wing membrane gets thinner. The vein thickness can be controlled with high precision by the spin-coating technique. The thickness of artificial membrane can be thinned down to a few microns, thus emulating those of some insects. Our process is compatible with common MEMS technology, and eligible to produce artificial wings of complex geometry and morphology mimicking natural insect wings. Our conclusion is that natural wings can be well mimicked in material conception, weight, venation, size, mass distribution and wing rigidity using hybrid materials. We also show that even using exceedingly compliant material as one composition, composite airfoils can be as light and stiff as insect wings, thereby highlighting the merit of smart material hybridization.

  19. A phononic crystal strip based on silicon for support tether applications in silicon-based MEMS resonators and effects of temperature and dopant on its band gap characteristics

    Directory of Open Access Journals (Sweden)

    Thi Dep Ha

    2016-04-01

    Full Text Available Phononic crystals (PnCs and n-type doped silicon technique have been widely employed in silicon-based MEMS resonators to obtain high quality factor (Q as well as temperature-induced frequency stability. For the PnCs, their band gaps play an important role in the acoustic wave propagation. Also, the temperature and dopant doped into silicon can cause the change in its material properties such as elastic constants, Young’s modulus. Therefore, in order to design the simultaneous high Q and frequency stability silicon-based MEMS resonators by two these techniques, a careful design should study effects of temperature and dopant on the band gap characteristics to examine the acoustic wave propagation in the PnC. Based on these, this paper presents (1 a proposed silicon-based PnC strip structure for support tether applications in low frequency silicon-based MEMS resonators, (2 influences of temperature and dopant on band gap characteristics of the PnC strips. The simulation results show that the largest band gap can achieve up to 33.56 at 57.59 MHz and increase 1280.13 % (also increase 131.89 % for ratio of the widest gaps compared with the counterpart without hole. The band gap properties of the PnC strips is insignificantly effected by temperature and electron doping concentration. Also, the quality factor of two designed length extensional mode MEMS resonators with proposed PnC strip based support tethers is up to 1084.59% and 43846.36% over the same resonators with PnC strip without hole and circled corners, respectively. This theoretical study uses the finite element analysis in COMSOL Multiphysics and MATLAB softwares as simulation tools. This findings provides a background in combination of PnC and dopant techniques for high performance silicon-based MEMS resonators as well as PnC-based MEMS devices.

  20. Sensitivity enhancement of a folded beam MEMS capacitive accelerometer-based microphone for fully implantable hearing application.

    Science.gov (United States)

    Dwivedi, Apoorva; Khanna, Gargi

    2017-10-31

    The present work attempts to enhance the sensitivity of a folded beam microelectromechanical systems (MEMS) capacitive accelerometer by optimising the device geometry. The accelerometer is intended to serve as a microphone in the fully implantable hearing application which can be surgically implanted in the middle ear bone structure. For the efficient design of the accelerometer as a fully implantable biomedical device, the design parameters such as size, weight and resonant frequency have been considered. The geometrical parameters are varied to obtain the optimum sensitivity considering the design constraints and the stability of the structure. The optimised design is simulated and verified using COMSOL MULTIPHYSICS 4.2. The stability of the device is ensured using eigenfrequency analysis. Optimised results of the device geometry are presented and discussed. The accelerometer has a sensing area of 1 mm2 and attains a nominal capacitance of 5.3 pF and an optimum sensitivity of 6.89 fF.

  1. Advances in Artificial Neural Networks – Methodological Development and Application

    Directory of Open Access Journals (Sweden)

    Yanbo Huang

    2009-08-01

    Full Text Available Artificial neural networks as a major soft-computing technology have been extensively studied and applied during the last three decades. Research on backpropagation training algorithms for multilayer perceptron networks has spurred development of other neural network training algorithms for other networks such as radial basis function, recurrent network, feedback network, and unsupervised Kohonen self-organizing network. These networks, especially the multilayer perceptron network with a backpropagation training algorithm, have gained recognition in research and applications in various scientific and engineering areas. In order to accelerate the training process and overcome data over-fitting, research has been conducted to improve the backpropagation algorithm. Further, artificial neural networks have been integrated with other advanced methods such as fuzzy logic and wavelet analysis, to enhance the ability of data interpretation and modeling and to avoid subjectivity in the operation of the training algorithm. In recent years, support vector machines have emerged as a set of high-performance supervised generalized linear classifiers in parallel with artificial neural networks. A review on development history of artificial neural networks is presented and the standard architectures and algorithms of artificial neural networks are described. Furthermore, advanced artificial neural networks will be introduced with support vector machines, and limitations of ANNs will be identified. The future of artificial neural network development in tandem with support vector machines will be discussed in conjunction with further applications to food science and engineering, soil and water relationship for crop management, and decision support for precision agriculture. Along with the network structures and training algorithms, the applications of artificial neural networks will be reviewed as well, especially in the fields of agricultural and biological

  2. Complex-valued neural networks advances and applications

    CERN Document Server

    Hirose, Akira

    2013-01-01

    Presents the latest advances in complex-valued neural networks by demonstrating the theory in a wide range of applications Complex-valued neural networks is a rapidly developing neural network framework that utilizes complex arithmetic, exhibiting specific characteristics in its learning, self-organizing, and processing dynamics. They are highly suitable for processing complex amplitude, composed of amplitude and phase, which is one of the core concepts in physical systems to deal with electromagnetic, light, sonic/ultrasonic waves as well as quantum waves, namely, electron and

  3. Hybrid digital signal processing and neural networks applications in PWRs

    Energy Technology Data Exchange (ETDEWEB)

    Eryurek, E.; Upadhyaya, B.R.; Kavaklioglu, K.

    1991-12-31

    Signal validation and plant subsystem tracking in power and process industries require the prediction of one or more state variables. Both heteroassociative and auotassociative neural networks were applied for characterizing relationships among sets of signals. A multi-layer neural network paradigm was applied for sensor and process monitoring in a Pressurized Water Reactor (PWR). This nonlinear interpolation technique was found to be very effective for these applications.

  4. Characterization of Polymer-Coated MEMS Humidity Sensors for Flight Applications

    Science.gov (United States)

    Shams, Qamar A.; Burkett, Cecil G., Jr.; Daniels, Taumi S.; Tsoucalas, George; Comeaux, Toby; Sealey, Bradley S.; Fox, Melanie L.

    2005-01-01

    Under NASA's Aviation Safety Program (AvSP), in addition to wind velocity and temperature, water vapor is considered one key factor in determining aviation weather, which is a substantial contributor to many general aviation (GA) accidents. The conventional and reliable humidity measuring methods such as radiation reflection or absorption have relatively high cost in addition to highly specialized operating and maintenance characteristics. This paper presents characterizations of inexpensive MEMS and capacitance type humidity sensors for their potential use on aircraft. If installed, these sensors are subjected to ambient environmental conditions as well as to different chemicals and deicing fluids used on aircraft. This paper reports the effect of different deicing fluids and chemicals on these inexpensive humidity sensors.

  5. Type-2 fuzzy neural networks and their applications

    CERN Document Server

    Aliev, Rafik Aziz

    2014-01-01

    This book deals with the theory, design principles, and application of hybrid intelligent systems using type-2 fuzzy sets in combination with other paradigms of Soft Computing technology such as Neuro-Computing and Evolutionary Computing. It provides a self-contained exposition of the foundation of type-2 fuzzy neural networks and presents a vast compendium of its applications to control, forecasting, decision making, system identification and other real problems. Type-2 Fuzzy Neural Networks and Their Applications is helpful for teachers and students of universities and colleges, for scientis

  6. Miniaturized GPS/MEMS IMU integrated board

    Science.gov (United States)

    Lin, Ching-Fang (Inventor)

    2012-01-01

    This invention documents the efforts on the research and development of a miniaturized GPS/MEMS IMU integrated navigation system. A miniaturized GPS/MEMS IMU integrated navigation system is presented; Laser Dynamic Range Imager (LDRI) based alignment algorithm for space applications is discussed. Two navigation cameras are also included to measure the range and range rate which can be integrated into the GPS/MEMS IMU system to enhance the navigation solution.

  7. MEMS-based Circuits and Systems for Wireless Communication

    CERN Document Server

    Kaiser, Andreas

    2013-01-01

    MEMS-based Circuits and Systems for Wireless Communication provides comprehensive coverage of RF-MEMS technology from device to system level. This edited volume places emphasis on how system performance for radio frequency applications can be leveraged by Micro-Electro-Mechanical Systems (MEMS). Coverage also extends to innovative MEMS-aware radio architectures that push the potential of MEMS technology further ahead.  This work presents a broad overview of the technology from MEMS devices (mainly BAW and Si MEMS resonators) to basic circuits, such as oscillators and filters, and finally complete systems such as ultra-low-power MEMS-based radios. Contributions from leading experts around the world are organized in three parts. Part I introduces RF-MEMS technology, devices and modeling and includes a prospective outlook on ongoing developments towards Nano-Electro-Mechanical Systems (NEMS) and phononic crystals. Device properties and models are presented in a circuit oriented perspective. Part II focusses on ...

  8. Neural networks: Application to medical imaging

    Science.gov (United States)

    Clarke, Laurence P.

    1994-01-01

    The research mission is the development of computer assisted diagnostic (CAD) methods for improved diagnosis of medical images including digital x-ray sensors and tomographic imaging modalities. The CAD algorithms include advanced methods for adaptive nonlinear filters for image noise suppression, hybrid wavelet methods for feature segmentation and enhancement, and high convergence neural networks for feature detection and VLSI implementation of neural networks for real time analysis. Other missions include (1) implementation of CAD methods on hospital based picture archiving computer systems (PACS) and information networks for central and remote diagnosis and (2) collaboration with defense and medical industry, NASA, and federal laboratories in the area of dual use technology conversion from defense or aerospace to medicine.

  9. In-flight performance analysis of MEMS GPS receiver and its application to precise orbit determination of APOD-A satellite

    Science.gov (United States)

    Gu, Defeng; Liu, Ye; Yi, Bin; Cao, Jianfeng; Li, Xie

    2017-12-01

    An experimental satellite mission termed atmospheric density detection and precise orbit determination (APOD) was developed by China and launched on 20 September 2015. The micro-electro-mechanical system (MEMS) GPS receiver provides the basis for precise orbit determination (POD) within the range of a few decimetres. The in-flight performance of the MEMS GPS receiver was assessed. The average number of tracked GPS satellites is 10.7. However, only 5.1 GPS satellites are available for dual-frequency navigation because of the loss of many L2 observations at low elevations. The variations in the multipath error for C1 and P2 were estimated, and the maximum multipath error could reach up to 0.8 m. The average code noises are 0.28 m (C1) and 0.69 m (P2). Using the MEMS GPS receiver, the orbit of the APOD nanosatellite (APOD-A) was precisely determined. Two types of orbit solutions are proposed: a dual-frequency solution and a single-frequency solution. The antenna phase center variations (PCVs) and code residual variations (CRVs) were estimated, and the maximum value of the PCVs is 4.0 cm. After correcting the antenna PCVs and CRVs, the final orbit precision for the dual-frequency and single-frequency solutions were 7.71 cm and 12.91 cm, respectively, validated using the satellite laser ranging (SLR) data, which were significantly improved by 3.35 cm and 25.25 cm. The average RMS of the 6-h overlap differences in the dual-frequency solution between two consecutive days in three dimensions (3D) is 4.59 cm. The MEMS GPS receiver is the Chinese indigenous onboard receiver, which was successfully used in the POD of a nanosatellite. This study has important reference value for improving the MEMS GPS receiver and its application in other low Earth orbit (LEO) nanosatellites.

  10. Evaluating the performance of MEMS based inertial navigation sensors for land mobile applications

    Science.gov (United States)

    Kealy, A.; Retscher, G.; Grejner-Brzezinska, D.; Gikas, V.; Roberts, G.

    2011-12-01

    In 2010 a collaborative working group was formed under the professional associations: International Association of Geodesy (IAG WG4.2.5) and International Federation of Surveys (FIG WG5.5). Entitled ubiquitous positioning, this working group aims to harness and develop existing research outputs available internationally in this research domain. Our goal over the next four years is to provide an online resource for academic and industry professionals, who can use these research outputs thereby reducing duplication and facilitating more rapid progress in the development of ubiquitous positioning systems. This paper presents a summary of the research activities and results of the working group to date. In particular, it presents the results of extensive testing to characterise the performance of a range of low-cost MEMS inertial sensors. The test scenarios, data acquisition software, processing tools and results obtained will be fully described and presented. The performance of these sensors in augmenting GNSS positioning is also presented using results obtained from a combination of loosely and tightly coupled Kalman filters. Finally, the future plans for the working group over the next four years and opportunities for wider collaboration will be discussed.

  11. Application of SnO2 Nano-powder on MEMS Type Gas Sensors

    Directory of Open Access Journals (Sweden)

    E. Abbaspour-Sani

    2007-04-01

    Full Text Available This paper describes a cost effective and new method for preparing SnO2 sol-gel as the basic material for the Micro-Electro-Mechanical System (MEMS type gas sensors. The SnO2 sol-gel was prepared by mixing SnCl4, propanol and isopropanol in a specified ratio. The produced sol-gel was exposed to two different decomposition temperatures of 600°C and 1200°C. Thermal treatment of the sol-gel resulted in formation of nano-crystalline single phase SnO2 powder having two different grain sizes. The grain size of the nano-powder calcinated at 600°C was about 10 nm and increased to about 80nm when the treatment temperature increased to 1200°C. The samples analyzed by XRD and TEM methods and both confirmed the grain size dependency on temperature. The prepared SnO2 sol-gels were applied on alumina substrates and the prepared samples were tested for sensitivity and selectivity using hydrogen, air and natural gas. The measurement results indicate a decrease in both selectivity and sensitivity of the gas sensor for increased nano-powder grain size.

  12. Single-layer silicon-on-insulator MEMS gyroscope for wide dynamic range and harsh environment applications

    Science.gov (United States)

    Kranz, Michael S.; Hudson, Tracy D.; Ashley, Paul R.; Ruffin, Paul B.; Burgett, Sherrie J.; Temmen, Mark; Tuck, Jerry

    2001-10-01

    The Army Aviation and Missile Command (AMCOM), Morgan Research Corporation, and Aegis Research Corporation are developing an SOI-based vibratory-rate z-axis MEMS gyroscope utilizing force-feedback control, and intended for wide dynamic range and harsh environment applications. Rate sensing in small diameter ballistic missile guidance units requires a rate resolution of less than 1 degree(s)/hr over a range of -3000 to +3000 degree(s)/sec, resulting in a dynamic range of 107. In addition, the devices must operate through military specifications on temperature (-55 degree(s)C to +125 degree(s)C) and vibration (1000 g at 5 - 15 kHz). This paper presents modeling, simulation, and fabrication efforts, as well as initial test data, for an SOI-based rate sensor intended for this application. The prototyped gyroscope is a single layer structure consisting of a proof mass placed in a three-fold mode-decoupled symmetric suspension. The device is fabricated in a cost-effective and highly-controllable Silicon-on-Insulator (SOI) process for in-plane inertial devices. The mechanical structure is integrated in a vacuum-sealed hermetic package with a separate CMOS readout ASIC. At the present time, the device has undergone two design iterations, with the most recent just completed.

  13. A review of vibration-based MEMS piezoelectric energy harvesters

    Energy Technology Data Exchange (ETDEWEB)

    Saadon, Salem; Sidek, Othman [Collaborative Microelectronic Design Excellence Center (CEDEC), School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Engineering Campus, 14300 Nibong Tebal, Seberang Perai Selatan, Pulau Pinang (Malaysia)

    2011-01-15

    The simplicity associated with the piezoelectric micro-generators makes it very attractive for MEMS applications, especially for remote systems. In this paper we reviewed the work carried out by researchers during the last three years. The improvements in experimental results obtained in the vibration-based MEMS piezoelectric energy harvesters show very good scope for MEMS piezoelectric harvesters in the field of power MEMS in the near future. (author)

  14. Listening to MEMS: An acoustic vibrometer

    NARCIS (Netherlands)

    Yntema, Doekle Reinder; Haneveld, J.; Engelen, Johannes Bernardus Charles; Brookhuis, Robert Anton; Sanders, Remco G.P.; Wiegerink, Remco J.; Elwenspoek, Michael Curt

    2010-01-01

    new way to characterize vibrating MEMS devices is presented. Using an acoustic particle velocity sensor the coupled sound field is measured, which is a measure for the movement of the MEMS device. We present several possible applications of this measurement method. It can be used as a read-out

  15. Listening to MEMS : An acoustic vibrometer

    NARCIS (Netherlands)

    Yntema, Doekle Reinder; Haneveld, J.; Engelen, Johannes Bernardus Charles; Brookhuis, Robert Anton; Sanders, Remco G.P.; Wiegerink, Remco J.; Elwenspoek, Michael Curt

    2010-01-01

    new way to characterize vibrating MEMS devices is presented. Using an acoustic particle velocity sensor the coupled sound field is measured, which is a measure for the movement of the MEMS device. We present several possible applications of this measurement method. It can be used as a read-out

  16. An SOI CMOS-Based Multi-Sensor MEMS Chip for Fluidic Applications.

    Science.gov (United States)

    Mansoor, Mohtashim; Haneef, Ibraheem; Akhtar, Suhail; Rafiq, Muhammad Aftab; De Luca, Andrea; Ali, Syed Zeeshan; Udrea, Florin

    2016-11-04

    An SOI CMOS multi-sensor MEMS chip, which can simultaneously measure temperature, pressure and flow rate, has been reported. The multi-sensor chip has been designed keeping in view the requirements of researchers interested in experimental fluid dynamics. The chip contains ten thermodiodes (temperature sensors), a piezoresistive-type pressure sensor and nine hot film-based flow rate sensors fabricated within the oxide layer of the SOI wafers. The silicon dioxide layers with embedded sensors are relieved from the substrate as membranes with the help of a single DRIE step after chip fabrication from a commercial CMOS foundry. Very dense sensor packing per unit area of the chip has been enabled by using technologies/processes like SOI, CMOS and DRIE. Independent apparatuses were used for the characterization of each sensor. With a drive current of 10 µA-0.1 µA, the thermodiodes exhibited sensitivities of 1.41 mV/°C-1.79 mV/°C in the range 20-300 °C. The sensitivity of the pressure sensor was 0.0686 mV/(Vexcit kPa) with a non-linearity of 0.25% between 0 and 69 kPa above ambient pressure. Packaged in a micro-channel, the flow rate sensor has a linearized sensitivity of 17.3 mV/(L/min)(-0.1) in the tested range of 0-4.7 L/min. The multi-sensor chip can be used for simultaneous measurement of fluid pressure, temperature and flow rate in fluidic experiments and aerospace/automotive/biomedical/process industries.

  17. Application of the minimum fuel neural network to music signals

    DEFF Research Database (Denmark)

    Harbo, Anders La-Cour

    2004-01-01

    Finding an optimal representation of a signal in an over-complete dictionary is often quite difficult. Since general results in this field are not very application friendly it truly helps to specify the framework as much as possible. We investigate the method Minimum Fuel Neural Network (MFNN...

  18. Artificial Neural Networks: A New Approach to Predicting Application Behavior.

    Science.gov (United States)

    Gonzalez, Julie M. Byers; DesJardins, Stephen L.

    2002-01-01

    Applied the technique of artificial neural networks to predict which students were likely to apply to one research university. Compared the results to the traditional analysis tool, logistic regression modeling. Found that the addition of artificial intelligence models was a useful new tool for predicting student application behavior. (EV)

  19. Challenges in the Packaging of MEMS

    Energy Technology Data Exchange (ETDEWEB)

    Malshe, A.P.; Singh, S.B.; Eaton, W.P.; O' Neal, C.; Brown, W.D.; Miller, W.M.

    1999-03-26

    The packaging of Micro-Electro-Mechanical Systems (MEMS) is a field of great importance to anyone using or manufacturing sensors, consumer products, or military applications. Currently much work has been done in the design and fabrication of MEMS devices but insufficient research and few publications have been completed on the packaging of these devices. This is despite the fact that packaging is a very large percentage of the total cost of MEMS devices. The main difference between IC packaging and MEMS packaging is that MEMS packaging is almost always application specific and greatly affected by its environment and packaging techniques such as die handling, die attach processes, and lid sealing. Many of these aspects are directly related to the materials used in the packaging processes. MEMS devices that are functional in wafer form can be rendered inoperable after packaging. MEMS dies must be handled only from the chip sides so features on the top surface are not damaged. This eliminates most current die pick-and-place fixtures. Die attach materials are key to MEMS packaging. Using hard die attach solders can create high stresses in the MEMS devices, which can affect their operation greatly. Low-stress epoxies can be high-outgassing, which can also affect device performance. Also, a low modulus die attach can allow the die to move during ultrasonic wirebonding resulting to low wirebond strength. Another source of residual stress is the lid sealing process. Most MEMS based sensors and devices require a hermetically sealed package. This can be done by parallel seam welding the package lid, but at the cost of further induced stress on the die. Another issue of MEMS packaging is the media compatibility of the packaged device. MEMS unlike ICS often interface with their environment, which could be high pressure or corrosive. The main conclusion we can draw about MEMS packaging is that the package affects the performance and reliability of the MEMS devices. There is a

  20. Non-linear feedback neural networks VLSI implementations and applications

    CERN Document Server

    Ansari, Mohd Samar

    2014-01-01

    This book aims to present a viable alternative to the Hopfield Neural Network (HNN) model for analog computation. It is well known that the standard HNN suffers from problems of convergence to local minima, and requirement of a large number of neurons and synaptic weights. Therefore, improved solutions are needed. The non-linear synapse neural network (NoSyNN) is one such possibility and is discussed in detail in this book. This book also discusses the applications in computationally intensive tasks like graph coloring, ranking, and linear as well as quadratic programming. The material in the book is useful to students, researchers and academician working in the area of analog computation.

  1. Real-time applications of neural nets

    Energy Technology Data Exchange (ETDEWEB)

    Spencer, J.E.

    1989-05-01

    Producing, accelerating and colliding very high power, low emittance beams for long periods is a formidable problem in real-time control. As energy has grown exponentially in time so has the complexity of the machines and their control systems. Similar growth rates have occurred in many areas, e.g., improved integrated circuits have been paid for with comparable increases in complexity. However, in this case, reliability, capability and cost have improved due to reduced size, high production and increased integration which allow various kinds of feedback. In contrast, most large complex systems (LCS) are perceived to lack such possibilities because only one copy is made. Neural nets, as a metaphor for LCS, suggest ways to circumvent such limitations. It is argued that they are logically equivalent to multi-loop feedback/forward control of faulty systems. While complimentary to AI, they mesh nicely with characteristics desired for real-time systems. Such issues are considered, examples given and possibilities discussed. 21 refs., 6 figs.

  2. Selected papers from the 12th International Workshop on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS 2012) (Atlanta, GA, USA, 2-5 December 2012)

    Science.gov (United States)

    Allen, Mark G.; Lang, Jeffrey

    2013-11-01

    Welcome to this special section of the Journal of Micromechanics and Microengineering (JMM). This section, co-edited by myself and by Professor Jeffrey Lang of the Massachusetts Institute of Technology, contains expanded versions of selected papers presented at the Power MEMS meeting held in Atlanta, GA, USA, in December of 2012. Professor Lang and I had the privilege of co-chairing Power MEMS 2012, the 12th International Workshop on Micro and Nanotechnology for Power Generation and Energy Conversion Applications. The scope of the PowerMEMS series of workshops ranges from basic principles, to materials and fabrication, to devices and systems, to applications. The many applications of power MEMS (microelectromehcanical systems) range from MEMS-enabled energy harvesting, storage, conversion and conditioning, to integrated systems that manage these processes. Why is the power MEMS field growing in importance? Smaller-scale power and power supplies (microwatts to tens of watts) are gaining in prominence due to many factors, including the ubiquity of low power portable electronic equipment and the proliferation of wireless sensor nodes that require extraction of energy from their embedding environment in order to function. MEMS manufacturing methods can be utilized to improve the performance of traditional power supply elements, such as allowing batteries to charge faster or shrinking the physical size of passive elements in small-scale power supplies. MEMS technologies can be used to fabricate energy harvesters that extract energy from an embedding environment to power wireless sensor nodes, in-body medical implants and other devices, in which the harvesters are on the small scales that are appropriately matched to the overall size of these microsystems. MEMS can enable the manufacturing of energy storage elements from nontraditional materials by bringing appropriate structure and surface morphology to these materials as well as fabricating the electrical interfaces

  3. The strength of polycrystalline silicon at the micro- and nano-scales with applications to MEMS

    Science.gov (United States)

    Chasiotis, Ioannis

    A new method for tensile testing of thin films by means of an improved apparatus has been developed to measure the elastic properties (Young's modulus, tensile strength) of surface micromachined polycrystalline silicon specimens. The newly designed tensile tester makes use of an Ultraviolet (UV) light curable adhesive to clamp micron-sized specimens. The properties determination utilizes surface topologies of deforming specimens, acquired with an Atomic Force Microscope (AFM), for determining strain fields by means of Digital Image Correlation (DIC). This full-field, direct and local measurements technique provides the capability of testing any type of thin film materials with nanometer resolution. A systematic study of small-scale size effects was thus performed by tensioning elliptically perforated specimens (minimum radius of curvature of 1 mum) so as to: (a) vary the stress concentration with constant radius of curvature, (b) increasing radius of curvature of micronotches relative to the grain size. The results demonstrate a strong influence of the size of the highly strained domain (decreasing notch radii) on the failure strength of MEMS scale specimens, while the effect of varying the stress concentration factor is rather insignificant. In addition, tests performed on unnotched tensile specimens of varying dimensions revealed a specimen size effect by which the values of strength scaled with the specimen length. The Young's modulus, however, is found to be rather insensitive to the specimen dimensions at the scale of microns. Contrary to the common belief that 49% HF wet release represents a safe post-process for manufacturing polycrystalline silicon, this study has clearly identified the release process as a key item in determining thin film failure properties. It is found that surface roughness as characterized by groove formation at the grain boundaries depends distinctly on the HF release time. In addition, while the actual failure mechanism in

  4. Electrostatic MEMS vibration energy harvester for HVAC applications with impact-based frequency up-conversion

    Science.gov (United States)

    Oxaal, J.; Hella, M.; Borca-Tasciuc, D.-A.

    2016-12-01

    This paper reports on electrostatic MEMS vibration energy harvesters with gap-closing interdigitated electrodes, designed for and tested on HVAC air ducts. The harvesters were fabricated on SOI wafers with 200 µm device layer using a custom microfabrication process. Designs with aspects ratio (electrodes’ gap versus depth) of 10 and 20 were implemented, while the overall footprint was approximately 1 cm  ×  1 cm in both cases. In order to enhance the power output, a dual-level physical stopper system was designed to control the minimum gap between the electrodes, which is a key parameter in the conversion process. The dual-level stopper utilizes cantilever beams to absorb a portion of the impact energy as the electrodes approach the impact point, and a film of parylene with nanometer thickness deposited on the electrode sidewalls. The parylene layer defines the absolute minimum gap and provides electrical insulation. The fabricated devices were first tested on a vibration shaker to characterize the resonant behavior. Devices with aspect ratio 10 were found to exhibit frequency up-conversion, which enhances the amount of converted power. Devices with both aspect ratios were found to exhibits spring hardening due to impact with the stoppers and spring softening behavior at increasing voltage bias. The highest power measured on shaker table for sinusoidal vibrations was 3.13 µW (includes enhancement due to frequency up-conversion driven by impact) for aspect ratio 10, and 0.166 µW for aspect ratio 20. The corresponding dimensional figure-of-merit, defined as the power output normalized to vibration acceleration and frequency, squared voltage and device mass, was in the range of 10 · 10-8 m V-2 for both devices, about an order of magnitude higher than state-of-the-art. Testing was carried out on HVAC air duct vibrating with an RMS acceleration of 155 mg RMS, a primary frequency of 60 Hz and a PSD of 7.15 · 10-2 g2 Hz-1. The peak power measured was

  5. Neural networks for process control and optimization: two industrial applications.

    Science.gov (United States)

    Bloch, Gérard; Denoeux, Thierry

    2003-01-01

    The two most widely used neural models, multilayer perceptron (MLP) and radial basis function network (RBFN), are presented in the framework of system identification and control. The main steps for building such nonlinear black box models are regressor choice, selection of internal architecture, and parameter estimation. The advantages of neural network models are summarized: universal approximation capabilities, flexibility, and parsimony. Two applications are described in steel industry and water treatment, respectively, the control of alloying process in a hot dipped galvanizing line and the control of a coagulation process in a drinking water treatment plant. These examples highlight the interest of neural techniques, when complex nonlinear phenomena are involved, but the empirical knowledge of control operators can be learned.

  6. SU-8-based microneedles for in vitro neural applications

    Science.gov (United States)

    Altuna, Ane; Gabriel, Gemma; Menéndez de la Prida, Liset; Tijero, María; Guimerá, Anton; Berganzo, Javier; Salido, Rafa; Villa, Rosa; Fernández, Luis J.

    2010-06-01

    This paper presents novel design, fabrication, packaging and the first in vitro neural activity recordings of SU-8-based microneedles. The polymer SU-8 was chosen because it provides excellent features for the fabrication of flexible and thin probes. A microprobe was designed in order to allow a clean insertion and to minimize the damage caused to neural tissue during in vitro applications. In addition, a tetrode is patterned at the tip of the needle to obtain fine-scale measurements of small neuronal populations within a radius of 100 µm. Impedance characterization of the electrodes has been carried out to demonstrate their viability for neural recording. Finally, probes are inserted into 400 µm thick hippocampal slices, and simultaneous action potentials with peak-to-peak amplitudes of 200-250 µV are detected.

  7. An artificial neural network controller for intelligent transportation systems applications

    Energy Technology Data Exchange (ETDEWEB)

    Vitela, J.E.; Hanebutte, U.R.; Reifman, J. [Argonne National Lab., IL (United States). Reactor Analysis Div.

    1996-04-01

    An Autonomous Intelligent Cruise Control (AICC) has been designed using a feedforward artificial neural network, as an example for utilizing artificial neural networks for nonlinear control problems arising in intelligent transportation systems applications. The AICC is based on a simple nonlinear model of the vehicle dynamics. A Neural Network Controller (NNC) code developed at Argonne National Laboratory to control discrete dynamical systems was used for this purpose. In order to test the NNC, an AICC-simulator containing graphical displays was developed for a system of two vehicles driving in a single lane. Two simulation cases are shown, one involving a lead vehicle with constant velocity and the other a lead vehicle with varying acceleration. More realistic vehicle dynamic models will be considered in future work.

  8. Double-tilt in situ TEM holder with multiple electrical contacts and its application in MEMS-based mechanical testing of nanomaterials

    Energy Technology Data Exchange (ETDEWEB)

    Bernal, Rodrigo A. [Department of Mechanical Engineering, Northwestern University, Evanston, IL 60208 (United States); Ramachandramoorthy, Rajaprakash [Department of Mechanical Engineering, Northwestern University, Evanston, IL 60208 (United States); Department of Theoretical and Applied Mechanics, Northwestern University, Evanston, IL 60208 (United States); Espinosa, Horacio D., E-mail: espinosa@northwestern.edu [Department of Mechanical Engineering, Northwestern University, Evanston, IL 60208 (United States); Department of Theoretical and Applied Mechanics, Northwestern University, Evanston, IL 60208 (United States); iNfinitesimal LLC, Skokie, IL 60077 (United States)

    2015-09-15

    MEMS and other lab-on-a-chip systems are emerging as attractive alternatives to carry out experiments in situ the electron microscope. However, several electrical connections are usually required for operating these setups. Such connectivity is challenging inside the limited space of the TEM side-entry holder. Here, we design, implement and demonstrate a double-tilt TEM holder with capabilities for up to 9 electrical connections, operating in a high-resolution TEM. We describe the operating principle of the tilting and connection mechanisms and the physical implementation of the holder. To demonstrate the holder capabilities, we calibrate the tilting action, which has limits of ±15°, and establish the insulation resistance of the electronics to be 36 GΩ, appropriate for measurements of currents down to the nano-amp (nA) regime. Furthermore, we demonstrate tensile testing of silver nanowires using a previously developed MEMS device for mechanical testing, using the implemented holder as the platform for electronic operation and sensing. The implemented holder can potentially have broad application to other areas where MEMS or electrically-actuated setups are used to carry out in situ TEM experiments. - Highlights: • We implement a double-tilt in-situ TEM holder with 9 electrical connections. • The holder can operate in a HRTEM with 2 mm pole-piece gap and has tilt up to ±15°. • Insulation resistance of 36 GΩ allows measurement of small currents. • The setup is showcased by testing silver nanowires using MEMS in-situ TEM. • Broad application to other electrically-actuated in-situ experiments is possible.

  9. Small-signal neural models and their applications.

    Science.gov (United States)

    Basu, Arindam

    2012-02-01

    This paper introduces the use of the concept of small-signal analysis, commonly used in circuit design, for understanding neural models. We show that neural models, varying in complexity from Hodgkin-Huxley to integrate and fire have similar small-signal models when their corresponding differential equations are close to the same bifurcation with respect to input current. Three applications of small-signal neural models are shown. First, some of the properties of cortical neurons described by Izhikevich are explained intuitively through small-signal analysis. Second, we use small-signal models for deriving parameters for a simple neural model (such as resonate and fire) from a more complicated but biophysically relevant one like Morris-Lecar. We show similarity in the subthreshold behavior of the simple and complicated model when they are close to a Hopf bifurcation and a saddle-node bifurcation. Hence, this is useful to correctly tune simple neural models for large-scale cortical simulations. Finaly, the biasing regime of a silicon ion channel is derived by comparing its small-signal model with a Hodgkin-Huxley-type model.

  10. PREFACE: The 15th International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS 2015)

    Science.gov (United States)

    Livermore, C.; Velásquez-García, L. F.

    2015-12-01

    Greetings, and welcome to Boston, MA and PowerMEMS 2015 - the 15th International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications! The objective of PowerMEMS 2015 is to catalyze innovation in micro- and nano-scale technologies for the energy domain. The scope of the meeting ranges from basic principles, to materials and fabrication, to devices and systems, to applications. The many applications of Power MEMS range from the harvesting, storage, conversion and conditioning of energy, to integrated systems that manage these processes, to actuation, pumping, and propulsion. Our Conference aims to stimulate the exchange of insights and information, as well as the development of new ideas, in the Power MEMS field. Our goal is to allow the attendees to interact and network within our multidisciplinary community that includes professionals from many branches of science and engineering, as well as energy, policy, and entrepreneurial specialists interested in the commercialization of Power MEMS technologies. Since the first PowerMEMS in Sendai, Japan in 2000, the Conference has grown in size, reputation, impact, and technical breadth. This continuing growth is evident in this year's technical program, which includes an increasing number of papers on nanomaterials, additive manufacturing for energy systems, actuators, energy storage, harvesting strategies and integrated energy harvesting systems, for example. This year's technical program is highlighted by six plenary talks from prominent experts on piezoelectrics, robotic insects, thermoelectrics, photovoltaics, nanocomposite cathodes, and thermal energy conversion systems. The contributed program received a large number of abstract submissions this year, 169 in total. After careful review by the 34-member Technical Program Committee, a total of 135 papers were selected for presentation. The 60 contributed oral presentations are arranged in two parallel sessions. The 75 posters

  11. Analysis of RF MEMS Capacitive Switches by Using Switch EM ANN Models

    Directory of Open Access Journals (Sweden)

    Z. Marinković

    2015-11-01

    Full Text Available Artificial neural networks (ANNs have appeared to be an alternative to the conventional models of RF MEMS switches. In this paper, neural models of an RF MEMS capacitive switch are developed and used for the electrical design of the switch. Namely, an ANN model relating the switch resonant frequency and the bridge dimensions is used to analyze efficiently the switch behavior with changes of bridge dimensions. Furthermore, it is illustrated how the developed model can be used for the determination of bridge dimensions in order to achieve the desired switch resonant frequency. In addition, application of a switch inverse ANN model for the determination of bridge dimensions is analyzed as well.

  12. Hollow MEMS

    DEFF Research Database (Denmark)

    Larsen, Peter Emil

    a hollow MEMS sensor has been designed, fabricated and tested. Combined density, viscosity, buoyant mass spectrometry and IR absorption spectroscopy are possible on liquid samples and micron sized suspended particles (e.g. single cells). Measurements are based on changes in the resonant behavior...... of these sensors. Optimization of the microfabrication process has led to a process yield of almost 100% .This is achieved despite the fact, that the process still offers a high degree of flexibility. By simple modifications the Sensor shape can be optimized for different size ranges and sensitivities...... technologies and pre-concentration approaches. A thorough theoretical analysis of the expected sensor responsivity and sensitivity is performed. Predictions made are confirmed by finite element simulations. Using these tools the sensor geometry is optimized for ideal performance in both mass density and IR...

  13. EDITORIAL: The 6th International Workshop on Micro and Nanotechnologies for Power Generation and Energy Conversion Applications (PowerMEMS 2006)

    Science.gov (United States)

    Fréchette, Luc G.

    2007-09-01

    Energy is a sector of paramount importance over the coming decades if we are to ensure sustainable development that respects our environment. The research and development of novel approaches to convert available energy into usable forms using micro and nanotechnologies can contribute towards this goal and meet the growing need for power in small scale portable applications. The dominant power sources for handheld and other portable electronics are currently primary and rechargeable batteries. Their limited energy density and adverse effects on the environment upon disposal suggest that alternative approaches need to be explored. This special issue will showcase some of the leading work in this area, initially presented at PowerMEMS 2006, the 6th International Workshop on Micro and Nanotechnologies for Power Generation and Energy Conversion Applications. Power MEMS are defined as microsystems for electrical power generation and other energy conversion applications, including propulsion and cooling. The range of power MEMS technologies includes micro thermodynamic machines, such as microturbines, miniature internal combustion engines and micro-coolers; solid-state direct energy conversion, such as thermoelectric and photovoltaic microstructures; micro electrochemical devices, such as micro fuel cells and nanostructure batteries; vibration energy harvesting devices, such as piezoelectric, magnetic or electrostatic micro generators, as well as micro thrusters and rocket engines for propulsion. These can either be driven by scavenging thermal, mechanical or solar energy from the environment, or from a stored energy source, such as chemical fuel or radioactive material. The unique scope leads to unique challenges in the development of power MEMS, ranging from the integration of novel materials to the efficient small scale implementation of energy conversion principles. In this special issue, Mitcheson et al provide a comparative assessment of three inertial vibration

  14. Of light, of MEMS: Optical MEMS in telecommunications and beyond

    Indian Academy of Sciences (India)

    The burst of the Internet bubble in 2000 has severely quenched the pace of development in the optical MEMS field. However, it is now clear that this field is again set to move forward as not only telecommunication but many other industries are benefiting from its application. We describe in this paper some of our latest ...

  15. Two-layer radio frequency MEMS fractal capacitors in PolyMUMPS for S-band applications

    KAUST Repository

    Elshurafa, Amro M.

    2012-07-23

    In this Letter, the authors fabricate for the first time MEMS fractal capacitors possessing two layers and compare their performance characteristics with the conventional parallel-plate capacitor and previously reported state-of-the-art single-layer MEMS fractal capacitors. Explicitly, a capacitor with a woven structure and another with an interleaved configuration were fabricated in the standard PolyMUMPS surface micromachining process and tested at S-band frequencies. The self-resonant frequencies of the fabricated capacitors were close to 10GHz, which is better than that of the parallel-plate capacitor, which measured only 5.5GHz. Further, the presented capacitors provided a higher capacitance when compared with the state-of-the-art-reported MEMS fractal capacitors created using a single layer at the expense of a lower quality factor. © 2012 The Institution of Engineering and Technology.

  16. Towards a SFP+ module for WDM applications using an ultra-widely-tunable high-speed MEMS-VCSEL

    Science.gov (United States)

    Paul, Sujoy; Cesar, Julijan; Malekizandi, Mohammadreza; Haidar, Mohammad T.; Heermeier, Niels; Ortsiefer, Markus; Neumeyr, Christian; Gréus, Christoph; Eiselt, Michael H.; Ibrahim, Irfan; Schmidt, Henning; Schmidt, Jörg; Küppers, Franko

    2017-02-01

    In this work, we have used a tunable VCSEL for high-speed optical data transmission. To obtain wide tunability, a MEMS-DBR is surface micromachined onto a short-cavity high-speed VCSEL operating at 1550 nm. Ultra-wide continuous tuning is realized with electro-thermal actuation of the MEMS with built-in stress gradient within SiOx/SiNy dielectric layers. The MEMS-VCSEL operates in single-mode with SMSR > 40 dB across the entire tuning range. Quasi-error-free transmission of direct-modulation at record 15 Gbps is reported for 20 nm tuning, showing the potential towards the standard requirements for the SFP+ modules in the tail-ends of the WDM transmission system.

  17. Workshop on environmental and energy applications of neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Hashem, S.

    1995-03-01

    This report consists of the abstracts for the papers given at the conference. Applications of neural networks in the environmental, energy and biomedical fields are discussed. Some of the topics covered are: predicting atmospheric pollutant concentrations due to fossil-fired electric power generation; hazardous waste characterization; nondestructive TRU (transuranic) waste assay; risk analysis; load forecasting for electric utilities; design of a wind power storage and generation system; nuclear fuel management; etc.

  18. Neuronmaster: an integrated tool for applications in neural networks

    Science.gov (United States)

    Rivas-Echeverria, Francklin; Colina-Morles, Eliezer; Sole, Solazver; Perez-Mendez, Anna; Bravo-Bravo, Cesar; Bravo-Bravo, Victor

    2001-03-01

    This work presents the design of an integral environment for the suitable development of neural networks applications. The integrated environment contemplates the following features: A data processing module which encompasses statistical data analysis techniques for variables selection reduction, a variety of learning algorithms, code generator for different computer languages to enable network implementation, a learning sessions planning module and database connectivity facilities via ODBC, RPC, and API.

  19. Artificial Neural Networks Application in Modal Analysis of Tires

    Science.gov (United States)

    Koštial, P.; Jančíková, Z.; Bakošová, D.; Valíček, J.; Harničárová, M.; Špička, I.

    2013-10-01

    The paper deals with the application of artificial neural networks (ANN) to tires' own frequency (OF) prediction depending on a tire construction. Experimental data of OF were obtained by electronic speckle pattern interferometry (ESPI). A very good conformity of both experimental and predicted data sets is presented here. The presented ANN method applied to ESPI experimental data can effectively help designers to optimize dimensions of tires from the point of view of their noise.

  20. Approaches and Challenges of Engineering Implantable Microelectromechanical Systems (MEMS Drug Delivery Systems for in Vitro and in Vivo Applications

    Directory of Open Access Journals (Sweden)

    Ken-Tye Yong

    2012-11-01

    Full Text Available Despite the advancements made in drug delivery systems over the years, many challenges remain in drug delivery systems for treating chronic diseases at the personalized medicine level. The current urgent need is to develop novel strategies for targeted therapy of chronic diseases. Due to their unique properties, microelectromechanical systems (MEMS technology has been recently engineered as implantable drug delivery systems for disease therapy. This review examines the challenges faced in implementing implantable MEMS drug delivery systems in vivo and the solutions available to overcome these challenges.

  1. Review On Applications Of Neural Network To Computer Vision

    Science.gov (United States)

    Li, Wei; Nasrabadi, Nasser M.

    1989-03-01

    Neural network models have many potential applications to computer vision due to their parallel structures, learnability, implicit representation of domain knowledge, fault tolerance, and ability of handling statistical data. This paper demonstrates the basic principles, typical models and their applications in this field. Variety of neural models, such as associative memory, multilayer back-propagation perceptron, self-stabilized adaptive resonance network, hierarchical structured neocognitron, high order correlator, network with gating control and other models, can be applied to visual signal recognition, reinforcement, recall, stereo vision, motion, object tracking and other vision processes. Most of the algorithms have been simulated on com-puters. Some have been implemented with special hardware. Some systems use features, such as edges and profiles, of images as the data form for input. Other systems use raw data as input signals to the networks. We will present some novel ideas contained in these approaches and provide a comparison of these methods. Some unsolved problems are mentioned, such as extracting the intrinsic properties of the input information, integrating those low level functions to a high-level cognitive system, achieving invariances and other problems. Perspectives of applications of some human vision models and neural network models are analyzed.

  2. Application of neural networks to waste site screening

    Energy Technology Data Exchange (ETDEWEB)

    Dabiri, A.E.; Garrett, M.; Kraft, T.; Hilton, J.; VanHammersveld, M.

    1993-02-01

    Waste site screening requires knowledge of the actual concentrations of hazardous materials and rates of flow around and below the site with time. The present approach consists primarily of drilling boreholes near contaminated sites and chemically analyzing the extracted physical samples and processing the data. This is expensive and time consuming. The feasibility of using neural network techniques to reduce the cost of waste site screening was investigated. Two neural network techniques, gradient descent back propagation and fully recurrent back propagation were utilized. The networks were trained with data received from Westinghouse Hanford Corporation. The results indicate that the network trained with the fully recurrent technique shows satisfactory generalization capability. The predicted results are close to the results obtained from a mathematical flow prediction model. It is possible to develop a new tool to predict the waste plume, thus substantially reducing the number of the bore sites and samplings. There are a variety of applications for this technique in environmental site screening and remediation. One of the obvious applications would be for optimum well siting. A neural network trained from the existing sampling data could be utilized to decide where would be the best position for the next bore site. Other applications are discussed in the report.

  3. Magnetron sputtered Cu3N/NiTiCu shape memory thin film heterostructures for MEMS applications

    Science.gov (United States)

    Kaur, Navjot; Choudhary, Nitin; Goyal, Rajendra N.; Viladkar, S.; Matai, I.; Gopinath, P.; Chockalingam, S.; Kaur, Davinder

    2013-03-01

    In the present study, for the first time, Cu3N/NiTiCu/Si heterostructures were successfully grown using magnetron sputtering technique. Nanocrystalline copper nitride (Cu3N with thickness 200 nm) thin films and copper nanodots were subsequently deposited on the surface of 2-μm-thick NiTiCu shape memory thin films in order to improve the surface corrosion and nickel release properties of NiTiCu thin films. Interestingly, the phase transformation from martensite phase to austenite phase has been observed in Cu3N/NiTiCu heterostructures with corresponding change in texture and surface morphology of top Cu3N films. Field emission scanning electron microscopy and atomic force microscope images of the heterostructures reveals the formation of 20-nm-sized copper nanodots on NiTiCu surface at higher deposition temperature (450 °C) of Cu3N. Cu3N passivated NiTiCu films possess low corrosion current density with higher corrosion potential and, therefore, better corrosion resistance as compared to pure NiTiCu films. The concentration of Ni released from the Cu3N/NiTiCu samples was observed to be much less than that of pure NiTiCu film. It can be reduced to the factor of about one-ninth after the surface passivation resulting in smooth, homogeneous and highly corrosion resistant surface. The antibacterial and cytotoxicity of pure and Cu3N coated NiTiCu thin films were investigated through green fluorescent protein expressing E. coli bacteria and human embryonic kidney cells. The results show the strong antibacterial property and non cytotoxicity of Cu3N/NiTiCu heterostructure. This work is of immense technological importance due to variety of BioMEMS applications.

  4. MEMS monocrystalline-silicon based thermal devices for chemical and microfluidic applications

    NARCIS (Netherlands)

    Mihailovic, M.

    2011-01-01

    This thesis explores the employment of monocrystalline silicon in microsystems as an active material for different thermal functions, such as heat generation and heat transfer by conduction. In chapter 1 applications that need thermal micro devices, micro heaters and micro heat exchangers, are

  5. RF-MEMS for future mobile applications: experimental verification of a reconfigurable 8-bit power attenuator up to 110 GHz

    Science.gov (United States)

    Iannacci, J.; Tschoban, C.

    2017-04-01

    RF-MEMS technology is proposed as a key enabling solution for realising the high-performance and highly reconfigurable passive components that future communication standards will demand. In this work, we present, test and discuss a novel design concept for an 8-bit reconfigurable power attenuator, manufactured using the RF-MEMS technology available at the CMM-FBK, in Italy. The device features electrostatically controlled MEMS ohmic switches in order to select/deselect the resistive loads (both in series and shunt configuration) that attenuate the RF signal, and comprises eight cascaded stages (i.e. 8-bit), thus implementing 256 different network configurations. The fabricated samples are measured (S-parameters) from 10 MHz to 110 GHz in a wide range of different configurations, and modelled/simulated with Ansys HFSS. The device exhibits attenuation levels (S21) in the range from  -10 dB to  -60 dB, up to 110 GHz. In particular, S21 shows flatness from 15 dB down to 3-5 dB and from 10 MHz to 50 GHz, as well as fewer linear traces up to 110 GHz. A comprehensive discussion is developed regarding the voltage standing wave ratio, which is employed as a quality indicator for the attenuation levels. The margins of improvement at design level which are needed to overcome the limitations of the presented RF-MEMS device are also discussed.

  6. Experimental methods of actuation, characterization and prototyping of hydrogels for bioMEMS/NEMS applications.

    Science.gov (United States)

    Khaleque, T; Abu-Salih, S; Saunders, J R; Moussa, W

    2011-03-01

    As a member of the smart polymer material group, stimuli responsive hydrogels have achieved a wide range of applications in microfluidic devices, micro/nano bio and environmental sensors, biomechanics and drug delivery systems. To optimize the utilization of a hydrogel in various micro and nano applications it is essential to have a better understanding of its mechanical and electrical properties. This paper presents a review of the different techniques used to determine a hydrogel's mechanical properties, including tensile strength, compressive strength and shear modulus and the electrical properties including electrical conductivity and dielectric permittivity. Also explored the effect of various prototyping factors and the mechanisms by which these factors are used to alter the mechanical and electrical properties of a hydrogel. Finally, this review discusses a wide range of hydrogel fabrication techniques and methods used, to date, to actuate this family of smart polymer material.

  7. MEMS monocrystalline-silicon based thermal devices for chemical and microfluidic applications

    OpenAIRE

    Mihailovic, M.

    2011-01-01

    This thesis explores the employment of monocrystalline silicon in microsystems as an active material for different thermal functions, such as heat generation and heat transfer by conduction. In chapter 1 applications that need thermal micro devices, micro heaters and micro heat exchangers, are briefly introduced. The shortcomings of commonly used materials are listed, and monocrystalline silicon is identified as an appropriate choice for several thermal micro devices. Chapter 2 briefly presen...

  8. EDITORIAL: Selected papers from the 11th International Workshop on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS 2011) Selected papers from the 11th International Workshop on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS 2011)

    Science.gov (United States)

    Cho, Young-Ho

    2012-09-01

    This special section of Journal of Micromechanics and Microengineering features papers selected from the 11th International Workshop on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS 2011), held at Sejong Hotel in Seoul, Korea during 15-18 November 2011. Since the first PowerMEMS workshop held in Sendai, Japan in 2000, the workshop has developed as the premier forum for reporting research results in micro and nanotechnology for power generation, energy conversion, harvesting and processing applications, including in-depth technical issues on nanostructures and materials for small-scale high-density energy and thermal management. Potential PowerMEMS applications cover not only portable power devices for consumer electronics and remote sensors, but also micro engines, impulsive thrusters and fuel cells for systems ranging from the nanometer to the millimeter scale. The 2011 technical program consists of 1 plenary talk, 4 invited talks and 118 contributed presentations. The 48 oral and 70 poster presentations, selected by 27 Technical Program Committee Members from 131 submitted abstracts, have stimulated lively discussion maximizing the interaction between participants. Among them, this special section includes 9 papers covering micro-scale power generators, energy converters, harvesters, thrusters and thermal coolers. Finally, we are grateful to the members of the International Steering Committee, the Technical Program Committee, and the Local Organizing Committee for their efforts and contributions to PowerMEMS 2011. We also thank the two companies Samsung Electro-Mechanics and LG Elite for technical tour arrangements. Special thanks go to Dr Ian Forbes, the editorial staff of the Journal of Micromechanics and Microengineering, as well as to the staff of IOP Publishing for making this special section possible.

  9. The Investigation of a Shape Memory Alloy Micro-Damper for MEMS Applications

    Directory of Open Access Journals (Sweden)

    Chongdu Cho

    2007-09-01

    Full Text Available Some shape memory alloys like NiTi show noticeable high damping property inpseudoelastic range. Due to its unique characteristics, a NiTi alloy is commonly used forpassive damping applications, in which the energy may be dissipated by the conversion frommechanical to thermal energy. This study presents a shape memory alloy based micro-damper, which exploits the pseudoelasticity of NiTi wires for energy dissipation. Themechanical model and functional principle of the micro-damper are explained in detail.Moreover, the mechanical behavior of NiTi wires subjected to various temperatures, strainrates and strain amplitudes is observed. Resulting from those experimental results, thedamping properties of the micro-damper involving secant stiffness, energy dissipation andloss factor are analyzed. The result indicates the proposed NiTi based micro-damper exhibitsgood energy dissipation ability, compared with conventional materials damper.

  10. The Investigation of a Shape Memory Alloy Micro-Damper for MEMS Applications.

    Science.gov (United States)

    Pan, Qiang; Cho, Chongdu

    2007-09-11

    Some shape memory alloys like NiTi show noticeable high damping property inpseudoelastic range. Due to its unique characteristics, a NiTi alloy is commonly used forpassive damping applications, in which the energy may be dissipated by the conversion frommechanical to thermal energy. This study presents a shape memory alloy based micro-damper, which exploits the pseudoelasticity of NiTi wires for energy dissipation. Themechanical model and functional principle of the micro-damper are explained in detail.Moreover, the mechanical behavior of NiTi wires subjected to various temperatures, strainrates and strain amplitudes is observed. Resulting from those experimental results, thedamping properties of the micro-damper involving secant stiffness, energy dissipation andloss factor are analyzed. The result indicates the proposed NiTi based micro-damper exhibitsgood energy dissipation ability, compared with conventional materials damper.

  11. High aspect ratio MEMS capacitor for high frequency impedance matching applications

    DEFF Research Database (Denmark)

    Yalcinkaya, Arda Deniz; Jensen, Søren; Hansen, Ole

    2003-01-01

    We present a microelectromechanical tunable capacitor with a low control voltage, a wide tuning range and adequate electrical quality factor. The device is fabricated in a single-crystalline silicon layer using deep reactive ion etching (DRIE) for obtaining high-aspect ratio (> 20) parallel comb......-drive structures with vertical sidewalls. The process sequence for fabrication of the devices uses only one lithographic masking step and can be completed in a short time. The fabricated device was characterized with respect to electrical quality factor, tuning range, self-resonance frequency and transient...... response and it was found that the device is a suitable passive component to be used in impedance matching applications, band-pass filtering or voltage controlled oscillators in the Very High Frequency (VHF) and Ultra High Frequency (UHF) bands....

  12. Application of a MEMS-Based TRNG in a Chaotic Stream Cipher

    Directory of Open Access Journals (Sweden)

    Miguel Garcia-Bosque

    2017-03-01

    Full Text Available In this work, we used a sensor-based True Random Number Generator in order to generate keys for a stream cipher based on a recently published hybrid algorithm mixing Skew Tent Map and a Linear Feedback Shift Register. The stream cipher was implemented and tested in a Field Programmable Gate Array (FPGA and was able to generate 8-bit width data streams at a clock frequency of 134 MHz, which is fast enough for Gigabit Ethernet applications. An exhaustive cryptanalysis was completed, allowing us to conclude that the system is secure. The stream cipher was compared with other chaotic stream ciphers implemented on similar platforms in terms of area, power consumption, and throughput.

  13. Application of a MEMS-Based TRNG in a Chaotic Stream Cipher.

    Science.gov (United States)

    Garcia-Bosque, Miguel; Pérez, Adrián; Sánchez-Azqueta, Carlos; Celma, Santiago

    2017-03-21

    In this work, we used a sensor-based True Random Number Generator in order to generate keys for a stream cipher based on a recently published hybrid algorithm mixing Skew Tent Map and a Linear Feedback Shift Register. The stream cipher was implemented and tested in a Field Programmable Gate Array (FPGA) and was able to generate 8-bit width data streams at a clock frequency of 134 MHz, which is fast enough for Gigabit Ethernet applications. An exhaustive cryptanalysis was completed, allowing us to conclude that the system is secure. The stream cipher was compared with other chaotic stream ciphers implemented on similar platforms in terms of area, power consumption, and throughput.

  14. Sandia Agile MEMS Prototyping, Layout Tools, Education and Services Program

    Energy Technology Data Exchange (ETDEWEB)

    Schriner, H.; Davies, B.; Sniegowski, J.; Rodgers, M.S.; Allen, J.; Shepard, C.

    1998-05-01

    Research and development in the design and manufacture of Microelectromechanical Systems (MEMS) is growing at an enormous rate. Advances in MEMS design tools and fabrication processes at Sandia National Laboratories` Microelectronics Development Laboratory (MDL) have broadened the scope of MEMS applications that can be designed and manufactured for both military and commercial use. As improvements in micromachining fabrication technologies continue to be made, MEMS designs can become more complex, thus opening the door to an even broader set of MEMS applications. In an effort to further research and development in MEMS design, fabrication, and application, Sandia National Laboratories has launched the Sandia Agile MEMS Prototyping, Layout Tools, Education and Services Program or SAMPLES program. The SAMPLES program offers potential partners interested in MEMS the opportunity to prototype an idea and produce hardware that can be used to sell a concept. The SAMPLES program provides education and training on Sandia`s design tools, analysis tools and fabrication process. New designers can participate in the SAMPLES program and design MEMS devices using Sandia`s design and analysis tools. As part of the SAMPLES program, participants` designs are fabricated using Sandia`s 4 level polycrystalline silicon surface micromachine technology fabrication process known as SUMMiT (Sandia Ultra-planar, Multi-level MEMS Technology). Furthermore, SAMPLES participants can also opt to obtain state of the art, post-fabrication services provided at Sandia such as release, packaging, reliability characterization, and failure analysis. This paper discusses the components of the SAMPLES program.

  15. Evolutionary Computation and Its Applications in Neural and Fuzzy Systems

    Directory of Open Access Journals (Sweden)

    Biaobiao Zhang

    2011-01-01

    Full Text Available Neural networks and fuzzy systems are two soft-computing paradigms for system modelling. Adapting a neural or fuzzy system requires to solve two optimization problems: structural optimization and parametric optimization. Structural optimization is a discrete optimization problem which is very hard to solve using conventional optimization techniques. Parametric optimization can be solved using conventional optimization techniques, but the solution may be easily trapped at a bad local optimum. Evolutionary computation is a general-purpose stochastic global optimization approach under the universally accepted neo-Darwinian paradigm, which is a combination of the classical Darwinian evolutionary theory, the selectionism of Weismann, and the genetics of Mendel. Evolutionary algorithms are a major approach to adaptation and optimization. In this paper, we first introduce evolutionary algorithms with emphasis on genetic algorithms and evolutionary strategies. Other evolutionary algorithms such as genetic programming, evolutionary programming, particle swarm optimization, immune algorithm, and ant colony optimization are also described. Some topics pertaining to evolutionary algorithms are also discussed, and a comparison between evolutionary algorithms and simulated annealing is made. Finally, the application of EAs to the learning of neural networks as well as to the structural and parametric adaptations of fuzzy systems is also detailed.

  16. Pulsed laser deposition of SmCo thin films for MEMS applications

    Directory of Open Access Journals (Sweden)

    Mirza Khurram Baig

    2016-10-01

    Full Text Available Thin films and coatings of permanent magnetic materials have found extensive applications in a wide range of technological domains. SmCo thin films show tremendous potential for use as permanent magnetic films on account of their high anisotropy fields, moderately high saturation magnetization and high curie temperature. In the present research, SmCo thin films have been deposited on single crystal Si(1 0 0 substrates using pulsed laser deposition technique. The films were deposited at a fixed substrate temperature of 400 °C by varying the number of pulses, in order to get thin films of different thicknesses. Effect of laser pulses on the crystal structure evolution, composition of the deposited material, film thicknesses and hence the magnetic properties have been investigated. X-ray diffraction analysis was performed in order to determine the crystal structure of the deposited films. The compositional analysis was performed by using energy dispersive X-ray spectroscopy. A slight variation in the Sm and Co contents was observed in the thin films grown by varying the laser shots. The microstructural information of the thin films was obtained by using a scanning electron microscope. The magnetic and electrical parameters were investigated by using vibrating sample magnetometer and two point probe respectively. The results show hard magnetic and conducting nature of all deposited thin films except sample 1 due to poor crystallinity.

  17. Artificial neural nets application in the cotton yarn industry

    Directory of Open Access Journals (Sweden)

    Gilberto Clóvis Antoneli

    2016-06-01

    Full Text Available The competitiveness in the yarn production sector has led companies to search for solutions to attain quality yarn at a low cost. Today, the difference between them, and thus the sector, is in the raw material, meaning processed cotton and its characteristics. There are many types of cotton with different characteristics due to its production region, harvest, storage and transportation. Yarn industries work with cotton mixtures, which makes it difficult to determine the quality of the yarn produced from the characteristics of the processed fibers. This study uses data from a conventional spinning, from a raw material made of 100% cotton, and presents a solution with artificial neural nets that determine the thread quality information, using the fibers’ characteristics values and settings of some process adjustments. In this solution a neural net of the type MultiLayer Perceptron with 11 entry neurons (8 characteristics of the fiber and 3 process adjustments, 7 output neurons (yarn quality and two types of training, Back propagation and Conjugate gradient descent. The selection and organization of the production data of the yarn industry of the cocamar® indústria de fios company are described, to apply the artificial neural nets developed. In the application of neural nets to determine yarn quality, one concludes that, although the ideal precision of absolute values is lacking, the presented solution represents an excellent tool to define yarn quality variations when modifying the raw material composition. The developed system enables a simulation to define the raw material percentage mixture to be processed in the plant using the information from the stocked cotton packs, thus obtaining a mixture that maintains the stability of the entire productive process.

  18. Neural computation and particle accelerators research, technology and applications

    CERN Document Server

    D'Arras, Horace

    2010-01-01

    This book discusses neural computation, a network or circuit of biological neurons and relatedly, particle accelerators, a scientific instrument which accelerates charged particles such as protons, electrons and deuterons. Accelerators have a very broad range of applications in many industrial fields, from high energy physics to medical isotope production. Nuclear technology is one of the fields discussed in this book. The development that has been reached by particle accelerators in energy and particle intensity has opened the possibility to a wide number of new applications in nuclear technology. This book reviews the applications in the nuclear energy field and the design features of high power neutron sources are explained. Surface treatments of niobium flat samples and superconducting radio frequency cavities by a new technique called gas cluster ion beam are also studied in detail, as well as the process of electropolishing. Furthermore, magnetic devises such as solenoids, dipoles and undulators, which ...

  19. Micro electromechanical systems (MEMS) for mechanical engineers

    Energy Technology Data Exchange (ETDEWEB)

    Lee, A. P., LLNL

    1996-11-18

    The ongoing advances in Microelectromechanical Systems (MEMS) are providing man-kind the freedom to travel to dimensional spaces never before conceivable. Advances include new fabrication processes, new materials, tailored modeling tools, new fabrication machines, systems integration, and more detailed studies of physics and surface chemistry as applied to the micro scale. In the ten years since its inauguration, MEMS technology is penetrating industries of automobile, healthcare, biotechnology, sports/entertainment, measurement systems, data storage, photonics/optics, computer, aerospace, precision instruments/robotics, and environment monitoring. It is projected that by the turn of the century, MEMS will impact every individual in the industrial world, totaling sales up to $14 billion (source: System Planning Corp.). MEMS programs in major universities have spawned up all over the United States, preparing the brain-power and expertise for the next wave of MEMS breakthroughs. It should be pointed out that although MEMS has been initiated by electrical engineering researchers through the involvement of IC fabrication techniques, today it has evolved such that it requires a totally multi-disciplinary team to develop useful devices. Mechanical engineers are especially crucial to the success of MEMS development, since 90% of the physical realm involved is mechanical. Mechanical engineers are needed for the design of MEMS, the analysis of the mechanical system, the design of testing apparatus, the implementation of analytical tools, and the packaging process. Every single aspect of mechanical engineering is being utilized in the MEMS field today, however, the impact could be more substantial if more mechanical engineers are involved in the systems level designing. In this paper, an attempt is made to create the pathways for a mechanical engineer to enter in the MEMS field. Examples of application in optics and medical devices will be used to illustrate how mechanical

  20. Advanced mechatronics and MEMS devices II

    CERN Document Server

    Wei, Bin

    2017-01-01

    This book introduces the state-of-the-art technologies in mechatronics, robotics, and MEMS devices in order to improve their methodologies. It provides a follow-up to "Advanced Mechatronics and MEMS Devices" (2013) with an exploration of the most up-to-date technologies and their applications, shown through examples that give readers insights and lessons learned from actual projects. Researchers on mechatronics, robotics, and MEMS as well as graduate students in mechanical engineering will find chapters on: Fundamental design and working principles on MEMS accelerometers Innovative mobile technologies Force/tactile sensors development Control schemes for reconfigurable robotic systems Inertial microfluidics Piezoelectric force sensors and dynamic calibration techniques ...And more. Authors explore applications in the areas of agriculture, biomedicine, advanced manufacturing, and space. Micro-assembly for current and future industries is also considered, as well as the design and development of micro and intel...

  1. Optical MEMS and MOEMS for telecommunications

    Science.gov (United States)

    Mounier, Eric

    2003-03-01

    This article will present the technologies and markets trends, as well as the latest R&D developments, in MEMS and MOEMS for optical telecom. Today, the MEMS technology has found the optical telecommunication market as a new "killer applications" (following the IT, automotive and medical markets). This overview will describe the current state-of-the-art in MEMS manufacturing for optical functions in optical networks. Switching is a crucial function in the future all-optical networks and MEMS and MOEMS are ideal candidates for this. After an over-estimation of the needs in optical switching in 2000, components manufacturers are today targeting market where low and medium size switches are needed. In this article, a specific focus on switching will be made with comparison between the MEMS technology and others switching technologies (thermo-optical, LC, holography...). The current industrial offer for MEMS (3D, 2D and 1D) will be described. The presentation will also give market figures and forecast for MEMS and MOEMS in optical telecom.

  2. Optical inspection of hidden MEMS structures

    Science.gov (United States)

    Krauter, Johann; Gronle, Marc; Osten, Wolfgang

    2017-06-01

    Micro-electro-mechanical system's (MEMS) applications have greatly expanded over the recent years, and the MEMS industry has grown almost exponentially. One of the strongest drivers are the automotive and consumer markets. A 100% test is necessary especially in the production of automotive MEMS sensors since they are subject to safety relevant functions. This inspection should be carried out before dicing and packaging since more than 90% of the production costs are incurred during these steps. An electrical test is currently being carried out with each MEMS component. In the case of a malfunction, the defect can not be located on the wafer because the MEMS are no longer optically accessible due to the encapsulation. This paper presents a low coherence interferometer for the topography measurement of MEMS structures located within the wafer stack. Here, a high axial and lateral resolution is necessary to identify defects such as stuck or bent MEMS fingers. First, the boundary conditions for an optical inspection system will be discussed. The setup is then shown with some exemplary measurements.

  3. Nano-tribology and materials in MEMS

    CERN Document Server

    Satyanarayana, N; Lim, Seh

    2013-01-01

    This book brings together recent developments in the areas of MEMS tribology, novel lubricants and coatings for nanotechnological applications, biomimetics in tribology and fundamentals of micro/nano-tribology. Tribology plays important roles in the functioning and durability of machines at small length scales because of the problems associated with strong surface adhesion, friction, wear etc. Recently, a number of studies have been conducted to understand tribological phenomena at nano/micro scales and many new tribological solutions for MEMS have been proposed.

  4. Digital holography for MEMS and microsystem metrology

    CERN Document Server

    Asundi, Anand

    2011-01-01

    Approaching the topic of digital holography from the practical perspective of industrial inspection, Digital Holography for MEMS and Microsystem Metrology describes the process of digital holography and its growing applications for MEMS characterization, residual stress measurement, design and evaluation, and device testing and inspection. Asundi also provides a thorough theoretical grounding that enables the reader to understand basic concepts and thus identify areas where this technique can be adopted. This combination of both practical and theoretical approach will ensure the

  5. Methodology of Neural Design: Applications in Microwave Engineering

    OpenAIRE

    Z. Raida; P. Pomenka

    2006-01-01

    In the paper, an original methodology for the automatic creation of neural models of microwave structures is proposed and verified. Following the methodology, neural models of the prescribed accuracy are built within the minimum CPU time. Validity of the proposed methodology is verified by developing neural models of selected microwave structures. Functionality of neural models is verified in a design - a neural model is joined with a genetic algorithm to find a global minimum of a formulat...

  6. Three applications of pulse-coupled neural networks

    Science.gov (United States)

    Ranganath, Heggere S.; Banish, Michele R.; Karpinsky, John R.; Clark, Rodney L.; Germany, Glynn A.; Richards, Philip G.

    1999-03-01

    Image segmentation is one of the major application areas for Pulsed Coupled Neural Networks (PCNN). Previous research has shown that the ability of PCNN to ignore minor variations in intensity and small spatial discontinuities in images is beneficial to image segmentation as well as image smoothing. This paper describes research and development projects in progress in which PCNN is used for the segmentation of three different types of digital images. The software for the diagnosis of Pulmonary Embolism from VQ lung scans uses PCNN in single burst mode for segmenting perfusion and ventilation images. The second project is attempting to detect ischemia by comparing 3D SPECT (Single Photon Emission Computed Tomography) images of heart obtained during stress and rest conditions, respectively. The third application is a space science project which deals with the study of global auroral images obtained from Ultraviolet Imager. The paper also describes an hardware implementation of PCNN as an electro-optical chip.

  7. Self-organization in neural networks - Applications in structural optimization

    Science.gov (United States)

    Hajela, Prabhat; Fu, B.; Berke, Laszlo

    1993-01-01

    The present paper discusses the applicability of ART (Adaptive Resonance Theory) networks, and the Hopfield and Elastic networks, in problems of structural analysis and design. A characteristic of these network architectures is the ability to classify patterns presented as inputs into specific categories. The categories may themselves represent distinct procedural solution strategies. The paper shows how this property can be adapted in the structural analysis and design problem. A second application is the use of Hopfield and Elastic networks in optimization problems. Of particular interest are problems characterized by the presence of discrete and integer design variables. The parallel computing architecture that is typical of neural networks is shown to be effective in such problems. Results of preliminary implementations in structural design problems are also included in the paper.

  8. Lubricated MEMS: effect of boundary slippage and texturing

    NARCIS (Netherlands)

    Tauviqirrahman, Mohammad

    2013-01-01

    Many types of micro-electro-mechanical-system (MEMS) based products are currently employed in a variety of applications. Recently, there has been an increase in the demand for higher reliability of MEMS which incorporate moving parts for each intended application. This is because the reliability of

  9. Stacked Integration of MEMS on LSI

    Directory of Open Access Journals (Sweden)

    Masayoshi Esashi

    2016-08-01

    Full Text Available Two stacked integration methods have been developed to enable advanced microsystems of microelectromechanical systems (MEMS on large scale integration (LSI. One is a wafer level transfer of MEMS fabricated on a carrier wafer to a LSI wafer. The other is the use of electrical interconnections using through-Si vias from the structure of a MEMS wafer on a LSI wafer. The wafer level transfer methods are categorized to film transfer, device transfer connectivity last, and immediate connectivity at device transfer. Applications of these transfer methods are film bulk acoustic resonator (FBAR on LSI, lead zirconate titanate (Pb(Zr,TiO3 (PZT MEMS switch on LSI, and surface acoustic wave (SAW resonators on LSI using respective methods. A selective transfer process was developed for multiple SAW filters on LSI. Tactile sensors and active matrix electron emitters for massive parallel electron beam lithography were developed using the through-Si vias.

  10. Recurrent Neural Network Applications for Astronomical Time Series

    Science.gov (United States)

    Protopapas, Pavlos

    2017-06-01

    The benefits of good predictive models in astronomy lie in early event prediction systems and effective resource allocation. Current time series methods applicable to regular time series have not evolved to generalize for irregular time series. In this talk, I will describe two Recurrent Neural Network methods, Long Short-Term Memory (LSTM) and Echo State Networks (ESNs) for predicting irregular time series. Feature engineering along with a non-linear modeling proved to be an effective predictor. For noisy time series, the prediction is improved by training the network on error realizations using the error estimates from astronomical light curves. In addition to this, we propose a new neural network architecture to remove correlation from the residuals in order to improve prediction and compensate for the noisy data. Finally, I show how to set hyperparameters for a stable and performant solution correctly. In this work, we circumvent this obstacle by optimizing ESN hyperparameters using Bayesian optimization with Gaussian Process priors. This automates the tuning procedure, enabling users to employ the power of RNN without needing an in-depth understanding of the tuning procedure.

  11. Advantages of PZT thick film for MEMS sensors

    DEFF Research Database (Denmark)

    Hindrichsen, Christian Carstensen; Lou-Moller, R.; Hansen, K.

    2010-01-01

    For all MEMS devices a high coupling between the mechanical and electrical domain is desired. Figures of merit describing the coupling are important for comparing different piezoelectric materials. The existing figures of merit are discussed and a new figure of merit is introduced for a fair...... comparison of piezoelectric thin and thick films based MEMS devices, as cantilevers, beams, bridges and membranes. Simple analytical modeling is used to define the new figure of merit. The relevant figure of merits is compared for the piezoelectric material of interest for MEMS applications: ZnO, AIN, PZT...... thin film and PZT thick film. It is shown that MEMS sensors with the PZT thick film TF2100 from InSensor A/S have potential for significant higher voltage sensitivities compared to PZT thin film base MEMS sensors when the total thickness of the MEMS cantilever, beam, bridge or membrane is high...

  12. APPLICATION OF NEURAL NETWORK ALGORITHMS FOR BPM LINEARIZATION

    Energy Technology Data Exchange (ETDEWEB)

    Musson, John C. [JLAB; Seaton, Chad [JLAB; Spata, Mike F. [JLAB; Yan, Jianxun [JLAB

    2012-11-01

    Stripline BPM sensors contain inherent non-linearities, as a result of field distortions from the pickup elements. Many methods have been devised to facilitate corrections, often employing polynomial fitting. The cost of computation makes real-time correction difficult, particulalry when integer math is utilized. The application of neural-network technology, particularly the multi-layer perceptron algorithm, is proposed as an efficient alternative for electrode linearization. A process of supervised learning is initially used to determine the weighting coefficients, which are subsequently applied to the incoming electrode data. A non-linear layer, known as an activation layer, is responsible for the removal of saturation effects. Implementation of a perceptron in an FPGA-based software-defined radio (SDR) is presented, along with performance comparisons. In addition, efficient calculation of the sigmoidal activation function via the CORDIC algorithm is presented.

  13. Practical application of artificial neural networks in the neurosciences

    Science.gov (United States)

    Pinti, Antonio

    1995-04-01

    This article presents a practical application of artificial multi-layer perceptron (MLP) neural networks in neurosciences. The data that are processed are labeled data from the visual analysis of electrical signals of human sleep. The objective of this work is to automatically classify into sleep stages the electrophysiological signals recorded from electrodes placed on a sleeping patient. Two large data bases were designed by experts in order to realize this study. One data base was used to train the network and the other to test its generalization capacity. The classification results obtained with the MLP network were compared to a type K nearest neighbor Knn non-parametric classification method. The MLP network gave a better result in terms of classification than the Knn method. Both classification techniques were implemented on a transputer system. With both networks in their final configuration, the MLP network was 160 times faster than the Knn model in classifying a sleep period.

  14. A Method for Testing the Dynamic Accuracy of Micro-Electro-Mechanical Systems (MEMS) Magnetic, Angular Rate, and Gravity (MARG) Sensors for Inertial Navigation Systems (INS) and Human Motion Tracking Applications

    Science.gov (United States)

    2010-06-01

    civilian first responder, and commercial consumer applications are all discussed. The types of dynamic tests that were desired are introduced in Chapter...the new location. Pedometers, wheel counters, stars, sextants , compasses, and precise clocks have all been used as tools for determining position [7...existing and potential future applications of MEMS MARG sensor packages are introduced. Emphasis is given to military and first responder applications

  15. A Nuclear Microbattery for MEMS Devices

    Energy Technology Data Exchange (ETDEWEB)

    Blanchard, James; Henderson, Douglass; Lal, Amit

    2002-08-20

    This project was designed to demonstrate the feasibility of producing on-board power for MEMS devices using radioisotopes. MEMS is a fast growing field, with hopes for producing a wide variety of revolutionary applications, including ''labs on a chip,'' micromachined scanning tunneling microscopes, microscopic detectors for biological agents, microsystems for DNA identification, etc. Currently, these applications are limited by the lack of an on-board power source. Research is ongoing to study approaches such as fuel cells, fossil fuels, and chemical batteries, but all these concepts have limitations. For long-lived, high energy density applications, on-board radioisotope power offers the best choice. We have succeeded in producing such devices using a variety of isotopes, incorporation methods, and device geometries. These experiments have demonstrated the feasibility of using radioisotope power and that there are a variety of options available for MEMS designers. As an example of an integrated, self-powered application, we have created an oscillating cantilever beam that is capable of consistent, periodic oscillations over very long time periods without the need for refueling. Ongoing work will demonstrate that this cantilever is capable of radio frequency transmission, allowing MEMS devices to communicate with one another wirelessly. Thus, this will be the first self-powered wireless transmitter available for use in MEMS devices, permitting such applications as sensors embedded in buildings for continuous monitoring of the building performance and integrity.

  16. Thermoelastic dissipation in MEMS/NEMS flexural mode resonators.

    Science.gov (United States)

    Yan, Jize; Seshia, Ashwin A

    2009-02-01

    Understanding the energy dissipation mechanisms in single-crystal silicon MEMS/NEMS resonators are particularly important to maximizing an important figure of merit relevant for miniature sensor and signal processing applications: the Quality factor (Q) of resonance. This paper discusses thermoelastic dissipation (TED) as the dominant internal-friction mechanism in flexural mode MEMS/NEMS resonators. Criteria for optimizing the geometrical design of flexural mode MEMS/NEMS resonators are theoretically established with a view towards minimizing the TED for single-crystal silicon MEMS/NEMS flexural mode resonators.

  17. Laser Interferometry for Harsh Environment MEMS Sensors

    Science.gov (United States)

    Nieva, Patricia

    2008-03-01

    Silicon-based MEMS technology has enabled the fabrication of a broad range of sensor and actuator systems that are having a great impact in areas that benefit from miniaturization and increased functionality. The main advantage of Si-based MEMS technologies is their possibility of integration with microelectronics thus allowing the economical production of smart microsystems. In the automotive industry for example, there is a need for inexpensive smart MEMS sensors for engine control applications. For instance, smart MEMS sensors capable of operating ``in cylinder'', where temperatures are around 400 C, could continuously monitor the combustion quality of the cylinders of automotive engines thus leading to reduced emissions and improved fuel economy. However, when the environment temperature is too high (>180 C), conventional Si-based microelectronics suffer from severe performance degradation, thus making smart Si-based MEMS impractical. Hence, further development, in terms of new MEMS materials and/or new technologies, is needed especially where high temperature capability is crucial to realizing improved electronic control. Remote sensing through optical signal detection has major advantages for safe signal transmission in harsh environments. It is highly resistant to electromagnetic interference (EMI) and radio frequency interference (RFI) and at the same time, it eliminates the necessity of on-board electronics, which has been one of the main obstacles in the development of smart MEMS sensors for high temperature applications. An economical way to deal with higher temperatures and other aggressive environmental conditions is to build MEMS sensors out of robust materials (e.g. Silicon nitride, SiC) and integrate them with optical signal detection techniques to form MOEMS. In this paper, we review recent trends for the use of laser interferometry for MEMS sensors in the context of using them for high temperature applications. Technological challenges faced in

  18. Close Up - Mem Fox.

    Science.gov (United States)

    Moss, Barbara

    2003-01-01

    Presents an interview with Mem Fox, a teacher educator and children's book author well known throughout the world. Discusses writing books for children, and the mistakes she made early in her career as a writer. Notes that Mem is a tireless advocate for meaningful literacy instruction, and her "Radical Reflections: Passionate Opinions on Teaching,…

  19. Integrated design of MEMS

    DEFF Research Database (Denmark)

    De Grave, Arnaud; Brissaud, Daniel

    2007-01-01

    . Manufacturing is mainly coming from the silicon industry. Our interest is to highlight the differences between designing MEMS and designing classical ICs or mechanical devices, to propose new methods and aided-tools supporting the design process. Our methodology is based on an ethnographic approach through...... industrial immersion to propose a socio-technological description of the design process and MEMS design tools....

  20. Applications of artificial neural networks for microbial water quality modeling

    Energy Technology Data Exchange (ETDEWEB)

    Brion, G.M.; Lingireddy, S. [Univ. of Kentucky, Dept. of Civil Engineering, Lexington, Kentucky (United States)]. E-mail: gbrion@engr.uky.edu

    2002-06-15

    There has been a significant shift in the recent past towards protecting chemical and microbial quality of source waters rather than developing advanced methods to treat heavily polluted water. The key to successful best management practices in protecting the source waters is to identify sources of non-point pollution and their collective impact on the quality of water at the intake. This article presents a few successful applications where artificial neural networks (ANN) have proven to be the useful mathematical tools in correlating the nonlinear relationships between routinely measured parameters (such as rainfall, turbidity, fecal coliforms etc.) and quality of source waters and/or nature of fecal sources. These applications include, prediction of peak concentrations of Giardia and Cryptosporidium, sorting of fecal sources (e.g. agricultural animals vs. urban animals), predicting relative ages of the runoff sources, identifying the potential for sewage contamination. The ability of ANNs to work with complex, inter-related multiparameter databases, and provide superior predictive power in non-linear relationships has been the key for their successful application to microbial water quality studies. (author)

  1. Challenges in the Packaging of MEMS

    Energy Technology Data Exchange (ETDEWEB)

    BROWN, WILLIAM D.; EATON, WILLIAM P.; MALSHE, AJAY P.; MILLER, WILLIAM M.; O' NEAL, CHAD; SINGH, SUSHILA B.

    1999-09-24

    Microelectromechanical Systems (MEMS) packaging is much different from conventional integrated circuit (IC) packaging. Many MEMS devices must interface to the environment in order to perform their intended function, and the package must be able to facilitate access with the environment while protecting the device. The package must also not interfere with or impede the operation of the MEMS device. The die attachment material should be low stress, and low outgassing, while also minimizing stress relaxation overtime which can lead to scale factor shifts in sensor devices. The fabrication processes used in creating the devices must be compatible with each other, and not result in damage to the devices. Many devices are application specific requiring custom packages that are not commercially available. Devices may also need media compatible packages that can protect the devices from harsh environments in which the MEMS device may operate. Techniques are being developed to handle, process, and package the devices such that high yields of functional packaged parts will result. Currently, many of the processing steps are potentially harmful to MEMS devices and negatively affect yield. It is the objective of this paper to review and discuss packaging challenges that exist for MEMS systems and to expose these issues to new audiences from the integrated circuit packaging community.

  2. From MEMS to NEMS with carbon.

    Science.gov (United States)

    Wang, Chunlei; Madou, Marc

    2005-04-15

    Our work in carbon-microelectromechanical systems (C-MEMS) suggests that C-MEMS might provide a very interesting material and microfabrication approach to battery miniaturization, active DNA arrays and a wide variety of chemical and biological sensors. In C-MEMS, photoresist is patterned by photolithography and subsequently pyrolyzed at high-temperatures in an oxygen-free environment. We established that it is possible to use C-MEMS to create very high-aspect ratio carbon structures (e.g. posts with an aspect ratio >10), suspended carbon plates and suspended carbon nanowires (C-NEMS). By changing the lithography conditions, soft and hard baking times and temperatures, additives to the resist, pyrolysis time, temperature and environment, C-MEMS permits a wide variety of interesting new MEMS and NEMS applications that employ structures having a wide variety of shapes, resistivities and mechanical properties. We also demonstrate that arrays of high-aspect ratio carbon posts can be charged/discharged with Li and this enables the fabrication of a smart switchable array of batteries.

  3. Shutdown Policies for MEMS-Based Storage Devices -- Analytical Models

    NARCIS (Netherlands)

    Khatib, M.G.; Engelen, Johannes Bernardus Charles; Hartel, Pieter H.

    MEMS-based storage devices should be energy ecient for deployment in mobile systems. Since MEMS-based storage devices have a moving me- dia sled, they should be shut down during periods of inactivity. However, shutdown costs energy, limiting the applicability of aggressive shutdown decisions. The

  4. Buffering Implications for the Design Space of Streaming MEMS Storage

    NARCIS (Netherlands)

    Khatib, M.G.; Abelmann, Leon; Preas, Kathy

    2011-01-01

    Emerging nanotechnology-based systems encounter new non-functional requirements. This work addresses MEMS storage, an emerging technology that promises ultrahigh density and energy-efficient storage devices. We study the buffering requirement of MEMS storage in streaming applications. We show that

  5. Methodology of Neural Design: Applications in Microwave Engineering

    Directory of Open Access Journals (Sweden)

    Z. Raida

    2006-06-01

    Full Text Available In the paper, an original methodology for the automatic creation of neural models of microwave structures is proposed and verified. Following the methodology, neural models of the prescribed accuracy are built within the minimum CPU time. Validity of the proposed methodology is verified by developing neural models of selected microwave structures. Functionality of neural models is verified in a design - a neural model is joined with a genetic algorithm to find a global minimum of a formulated objective function. The objective function is minimized using different versions of genetic algorithms, and their mutual combinations. The verified methodology of the automated creation of accurate neural models of microwave structures, and their association with global optimization routines are the most important original features of the paper.

  6. A new application of neural network technique to sensorless speed identification of induction motor

    OpenAIRE

    Mostefai, Mohamed; Miloud, Yahia; Abdullah MILOUDI

    2016-01-01

    A new application of neural network technique to sensorless speed identification of scalar-controlled induction motor is implemented in this paper. The neural network estimates the rotor speed through stator measurements and nominal settings of the motor. By changing the motor parameters, the neural network can estimate the speed of another motor. We evaluated our approach based on the speed response and load disturbance effects on two different motors. The test results demonstrate the feasib...

  7. A new application of neural network technique to sensorless speed identification of induction motor

    Directory of Open Access Journals (Sweden)

    Mohamed MOSTEFAI

    2016-12-01

    Full Text Available A new application of neural network technique to sensorless speed identification of scalar-controlled induction motor is implemented in this paper. The neural network estimates the rotor speed through stator measurements and nominal settings of the motor. By changing the motor parameters, the neural network can estimate the speed of another motor. We evaluated our approach based on the speed response and load disturbance effects on two different motors. The test results demonstrate the feasibility of the method.

  8. Application of a Shallow Neural Network to Short-Term Stock Trading

    OpenAIRE

    Madahar, Abhinav; Ma, Yuze; Patel, Kunal

    2017-01-01

    Machine learning is increasingly prevalent in stock market trading. Though neural networks have seen success in computer vision and natural language processing, they have not been as useful in stock market trading. To demonstrate the applicability of a neural network in stock trading, we made a single-layer neural network that recommends buying or selling shares of a stock by comparing the highest high of 10 consecutive days with that of the next 10 days, a process repeated for the stock's ye...

  9. Neural network and its application to CT imaging

    Energy Technology Data Exchange (ETDEWEB)

    Nikravesh, M.; Kovscek, A.R.; Patzek, T.W. [Lawrence Berkeley National Lab., CA (United States)] [and others

    1997-02-01

    We present an integrated approach to imaging the progress of air displacement by spontaneous imbibition of oil into sandstone. We combine Computerized Tomography (CT) scanning and neural network image processing. The main aspects of our approach are (I) visualization of the distribution of oil and air saturation by CT, (II) interpretation of CT scans using neural networks, and (III) reconstruction of 3-D images of oil saturation from the CT scans with a neural network model. Excellent agreement between the actual images and the neural network predictions is found.

  10. Neural networks supporting switching, hypothesis testing, and rule application.

    Science.gov (United States)

    Liu, Zhiya; Braunlich, Kurt; Wehe, Hillary S; Seger, Carol A

    2015-10-01

    We identified dynamic changes in recruitment of neural connectivity networks across three phases of a flexible rule learning and set-shifting task similar to the Wisconsin Card Sort Task: switching, rule learning via hypothesis testing, and rule application. During fMRI scanning, subjects viewed pairs of stimuli that differed across four dimensions (letter, color, size, screen location), chose one stimulus, and received feedback. Subjects were informed that the correct choice was determined by a simple unidimensional rule, for example "choose the blue letter". Once each rule had been learned and correctly applied for 4-7 trials, subjects were cued via either negative feedback or visual cues to switch to learning a new rule. Task performance was divided into three phases: Switching (first trial after receiving the switch cue), hypothesis testing (subsequent trials through the last error trial), and rule application (correct responding after the rule was learned). We used both univariate analysis to characterize activity occurring within specific regions of the brain, and a multivariate method, constrained principal component analysis for fMRI (fMRI-CPCA), to investigate how distributed regions coordinate to subserve different processes. As hypothesized, switching was subserved by a limbic network including the ventral striatum, thalamus, and parahippocampal gyrus, in conjunction with cortical salience network regions including the anterior cingulate and frontoinsular cortex. Activity in the ventral striatum was associated with switching regardless of how switching was cued; visually cued shifts were associated with additional visual cortical activity. After switching, as subjects moved into the hypothesis testing phase, a broad fronto-parietal-striatal network (associated with the cognitive control, dorsal attention, and salience networks) increased in activity. This network was sensitive to rule learning speed, with greater extended activity for the slowest

  11. Advances in Artificial Neural Networks - Methodological Development and Application

    Science.gov (United States)

    Artificial neural networks as a major soft-computing technology have been extensively studied and applied during the last three decades. Research on backpropagation training algorithms for multilayer perceptron networks has spurred development of other neural network training algorithms for other ne...

  12. Application of a neural network for reflectance spectrum classification

    Science.gov (United States)

    Yang, Gefei; Gartley, Michael

    2017-05-01

    Traditional reflectance spectrum classification algorithms are based on comparing spectrum across the electromagnetic spectrum anywhere from the ultra-violet to the thermal infrared regions. These methods analyze reflectance on a pixel by pixel basis. Inspired by high performance that Convolution Neural Networks (CNN) have demonstrated in image classification, we applied a neural network to analyze directional reflectance pattern images. By using the bidirectional reflectance distribution function (BRDF) data, we can reformulate the 4-dimensional into 2 dimensions, namely incident direction × reflected direction × channels. Meanwhile, RIT's micro-DIRSIG model is utilized to simulate additional training samples for improving the robustness of the neural networks training. Unlike traditional classification by using hand-designed feature extraction with a trainable classifier, neural networks create several layers to learn a feature hierarchy from pixels to classifier and all layers are trained jointly. Hence, the our approach of utilizing the angular features are different to traditional methods utilizing spatial features. Although training processing typically has a large computational cost, simple classifiers work well when subsequently using neural network generated features. Currently, most popular neural networks such as VGG, GoogLeNet and AlexNet are trained based on RGB spatial image data. Our approach aims to build a directional reflectance spectrum based neural network to help us to understand from another perspective. At the end of this paper, we compare the difference among several classifiers and analyze the trade-off among neural networks parameters.

  13. Neural network based adaptive output feedback control: Applications and improvements

    Science.gov (United States)

    Kutay, Ali Turker

    Application of recently developed neural network based adaptive output feedback controllers to a diverse range of problems both in simulations and experiments is investigated in this thesis. The purpose is to evaluate the theory behind the development of these controllers numerically and experimentally, identify the needs for further development in practical applications, and to conduct further research in directions that are identified to ultimately enhance applicability of adaptive controllers to real world problems. We mainly focus our attention on adaptive controllers that augment existing fixed gain controllers. A recently developed approach holds great potential for successful implementations on real world applications due to its applicability to systems with minimal information concerning the plant model and the existing controller. In this thesis the formulation is extended to the multi-input multi-output case for distributed control of interconnected systems and successfully tested on a formation flight wind tunnel experiment. The command hedging method is formulated for the approach to further broaden the class of systems it can address by including systems with input nonlinearities. Also a formulation is adopted that allows the approach to be applied to non-minimum phase systems for which non-minimum phase characteristics are modeled with sufficient accuracy and treated properly in the design of the existing controller. It is shown that the approach can also be applied to augment nonlinear controllers under certain conditions and an example is presented where the nonlinear guidance law of a spinning projectile is augmented. Simulation results on a high fidelity 6 degrees-of-freedom nonlinear simulation code are presented. The thesis also presents a preliminary adaptive controller design for closed loop flight control with active flow actuators. Behavior of such actuators in dynamic flight conditions is not known. To test the adaptive controller design in

  14. Research on the Application of Artificial Neural Networks in Tender Offer for Construction Projects

    Science.gov (United States)

    Minli, Zhang; Shanshan, Qiao

    The BP model in artificial neural network is used in this paper. Various factors that affect the tender offer is identified and these factors as the input nodes of network to conduct iterated operation in the network is applied in this paper. Through taking advantage of the self-learning function of network, this paper constantly modifies the weight matrix to achieve the objective error of the network error to achieve the function of predicting offer. As a software support tool, MATLAB is used in artificial neural network, the neural network toolbox helps to reduce the workload of writing code greatly and make the application of neural network more widely.

  15. Applications of neural networks in environmental and energy sciences and engineering. Proceedings of the 1995 workshop on environmental and energy applications of neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Hashem, S.; Keller, P.E.; Kouzes, R.T.; Kangas, L.J.

    1995-12-31

    These proceedings contain edited versions of the technical presentations of the Workshop on Environmental and Energy Applications of Neural Networks, held on March 30--31, 1995, in Richland, Washington. The purpose of the workshop was to provide a forum for discussing environmental, energy, and biomedical applications of neural networks. Panels were held to discuss various research and development issues relating to real-world applications in each of the three areas. The applications covered in the workshop were: Environmental applications -- modeling and predicting soil, air and water pollution, environmental sensing, spectroscopy, hazardous waste handling and cleanup; Energy applications -- process monitoring and optimization of power systems, modeling and control of power plants, environmental monitoring for power systems, power load forecasting, fault location and diagnosis of power systems; and Biomedical applications -- medical image and signal analysis, medical diagnosis, analysis of environmental health effects, and modeling biological systems. Selected papers are indexed separately for inclusion in the Energy Science and Technology Database.

  16. Polypyrrole-coated electrospun PLGA nanofibers for neural tissue applications.

    Science.gov (United States)

    Lee, Jae Y; Bashur, Chris A; Goldstein, Aaron S; Schmidt, Christine E

    2009-09-01

    Electrospinning is a promising approach to create nanofiber structures that are capable of supporting adhesion and guiding extension of neurons for nerve regeneration. Concurrently, electrical stimulation of neurons in the absence of topographical features also has been shown to guide axonal extension. Therefore, the goal of this study was to form electrically conductive nanofiber structures and to examine the combined effect of nanofiber structures and electrical stimulation. Conductive meshes were produced by growing polypyrrole (PPy) on random and aligned electrospun poly(lactic-co-glycolic acid) (PLGA) nanofibers, as confirmed by scanning electron micrographs and X-ray photon spectroscopy. PPy-PLGA electrospun meshes supported the growth and differentiation of rat pheochromocytoma 12 (PC12) cells and hippocampal neurons comparable to non-coated PLGA control meshes, suggesting that PPy-PLGA may be suitable as conductive nanofibers for neuronal tissue scaffolds. Electrical stimulation studies showed that PC12 cells, stimulated with a potential of 10 mV/cm on PPy-PLGA scaffolds, exhibited 40-50% longer neurites and 40-90% more neurite formation compared to unstimulated cells on the same scaffolds. In addition, stimulation of the cells on aligned PPy-PLGA fibers resulted in longer neurites and more neurite-bearing cells than stimulation on random PPy-PLGA fibers, suggesting a combined effect of electrical stimulation and topographical guidance and the potential use of these scaffolds for neural tissue applications.

  17. Polypyrrole-Coated Electrospun PLGA Nanofibers for Neural Tissue Applications

    Science.gov (United States)

    Lee, Jae Young; Bashur, Chris A.; Goldstein, Aaron S.; Schmidt, Christine E.

    2009-01-01

    Electrospinning is a promising approach to create nanofiber structures that are capable of supporting adhesion and guiding extension of neurons for nerve regeneration. Concurrently, electrical stimulation of neurons in the absence of topographical features also has been shown to guide axonal extension. Therefore, the goal of this study was to form electrically conductive nanofiber structures and to examine the combined effect of nanofiber structures and electrical stimulation. Conductive meshes were produced by growing polypyrrole (PPy) on random and aligned electrospun poly(lactic-co-glycolic acid) (PLGA) nanofibers, as confirmed by scanning electron micrographs and X-ray photon spectroscopy. PPy-PLGA electrospun meshes supported the growth and differentiation of rat pheochromocytoma 12 (PC12) cells and hippocampal neurons comparable to non-coated PLGA control meshes, suggesting that PPy-PLGA may be suitable as conductive nanofibers for neuronal tissue scaffolds. Electrical stimulation studies showed that PC12 cells, stimulated with a potential of 10 mV/cm on PPy-PLGA scaffolds, exhibited 40–50% longer neurites and 40–90% more neurite formation compared to unstimulated cells on the same scaffolds. In addition, stimulation of the cells on aligned PPy-PLGA fibers resulted in longer neurites and more neurite-bearing cells than stimulation on random PPy-PLGA fibers, suggesting a combined effect of electrical stimulation and topographical guidance and the potential use of these scaffolds for neural tissue applications. PMID:19501901

  18. EDITORIAL: Selected papers from the 10th International Workshop on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS 2010) Selected papers from the 10th International Workshop on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS 2010)

    Science.gov (United States)

    Reynaerts, Dominiek; Vullers, Ruud

    2011-10-01

    This special section of Journal of Micromechanics and Microengineering features papers selected from the 10th International Workshop on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS 2010). The workshop was organized in Leuven, Belgium from 30 November to 3 December 2010 by Katholieke Universiteit Leuven and the imec/Holst Centre. This was a special PowerMEMS Workshop, for several reasons. First of all, we celebrated the 10th anniversary of the workshop: the first PowerMEMS meeting was organized in Sendai, Japan in 2000. None of the organizers or participants of this first meeting could have predicted the impact of the workshop over the next decade. The second reason was that, for the first time, the conference organization spanned two countries: Belgium and the Netherlands. Thanks to the advances in information technology, teams from Katholieke Universiteit Leuven (Belgium) and the imec/Holst Centre in Eindhoven (the Netherlands) have been able to work together seamlessly as one team. The objective of the PowerMEMS Workshop is to stimulate innovation in micro and nanotechnology for power generation and energy conversion applications. Its scope ranges from integrated microelectromechanical systems (MEMS) for power generation, dissipation, harvesting, and management, to novel nanostructures and materials for energy-related applications. True to the objective of the PowerMEMSWorkshop, the 2010 technical program covered a broad range of energy related research, ranging from the nanometer to the millimeter scale, discussed in 5 invited and 52 oral presentations, and 112 posters. This special section includes 14 papers covering vibration energy harvesters, thermal applications and micro power systems. Finally, we wish to express sincere appreciation to the members of the International Steering Committee, the Technical Program Committee and last but not least the Local Organizing Committee. This special issue was edited in

  19. EDITORIAL: Selected papers from the 9th International Workshop on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS 2009) Selected papers from the 9th International Workshop on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS 2009)

    Science.gov (United States)

    Ghodssi, Reza; Livermore, Carol; Arnold, David

    2010-10-01

    This special section of the Journal of Micromechanics and Microengineering presents papers selected from the 9th International Workshop on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS 2009), which was held in Washington DC, USA from 1-4 December 2009. Since it was first held in Sendai, Japan in 2000, the PowerMEMS workshop has focused on small-scale systems that process, convert, or generate macroscopically significant amounts of power, typically with high power density or high energy density. In the workshop's early years, much of the research presented was on small-scale fueled systems, such as micro heat engines and micro fuel cells. The past nine years have seen a dramatic expansion in the range of technologies that are brought to bear on the challenge of high-power, small-scale systems, as well as an increase in the applications for such technologies. At this year's workshop, 158 contributed papers were presented, along with invited and plenary presentations. The papers focused on applications from micro heat engines and fuel cells, to energy harvesting and its enabling electronics, to thermal management and propulsion. Also presented were the technologies that enable these applications, such as the structuring of microscale, nanoscale and biological systems for power applications, as well as combustion and catalysis at small scales. This special section includes a selection of 12 expanded papers representing energy harvesting, chemical and fueled systems, and elastic energy storage at small scales. We would like to express our appreciation to the members of the International Steering Committee, the Technical Program Committee, the Local Organizing Committee, and to the workshop's financial supporters. We are grateful to the referees for their contributions to the review process. Finally, we would like to thank Dr Ian Forbes, the editorial staff of the Journal of Micromechanics and Microengineering, and the staff

  20. MEMS in microfluidic channels.

    Energy Technology Data Exchange (ETDEWEB)

    Ashby, Carol Iris Hill; Okandan, Murat; Michalske, Terry A.; Sounart, Thomas L.; Matzke, Carolyn M.

    2004-03-01

    Microelectromechanical systems (MEMS) comprise a new class of devices that include various forms of sensors and actuators. Recent studies have shown that microscale cantilever structures are able to detect a wide range of chemicals, biomolecules or even single bacterial cells. In this approach, cantilever deflection replaces optical fluorescence detection thereby eliminating complex chemical tagging steps that are difficult to achieve with chip-based architectures. A key challenge to utilizing this new detection scheme is the incorporation of functionalized MEMS structures within complex microfluidic channel architectures. The ability to accomplish this integration is currently limited by the processing approaches used to seal lids on pre-etched microfluidic channels. This report describes Sandia's first construction of MEMS instrumented microfluidic chips, which were fabricated by combining our leading capabilities in MEMS processing with our low-temperature photolithographic method for fabricating microfluidic channels. We have explored in-situ cantilevers and other similar passive MEMS devices as a new approach to directly sense fluid transport, and have successfully monitored local flow rates and viscosities within microfluidic channels. Actuated MEMS structures have also been incorporated into microfluidic channels, and the electrical requirements for actuation in liquids have been quantified with an elegant theory. Electrostatic actuation in water has been accomplished, and a novel technique for monitoring local electrical conductivities has been invented.

  1. Chaotic Hopfield Neural Network Swarm Optimization and Its Application

    Directory of Open Access Journals (Sweden)

    Yanxia Sun

    2013-01-01

    Full Text Available A new neural network based optimization algorithm is proposed. The presented model is a discrete-time, continuous-state Hopfield neural network and the states of the model are updated synchronously. The proposed algorithm combines the advantages of traditional PSO, chaos and Hopfield neural networks: particles learn from their own experience and the experiences of surrounding particles, their search behavior is ergodic, and convergence of the swarm is guaranteed. The effectiveness of the proposed approach is demonstrated using simulations and typical optimization problems.

  2. FPGA platform for prototyping and evaluation of neural network automotive applications

    Science.gov (United States)

    Aranki, N.; Tawel, R.

    2002-01-01

    In this paper we present an FPGA based reconfigurable computing platform for prototyping and evaluation of advanced neural network based applications for control and diagnostics in an automotive sub-systems.

  3. Application of neural networks in coastal engineering - An overview

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.; Patil, S.G.; Manjunatha, Y.R.; Hegde, A.V.

    . International conference on COPEDEC VII, Dubai (UAE), paper no- 27, 1-11. Mandal, S. 2001. Tides prediction using back propagation neural networks, Proc. International Conference in Ocean Engineering, ICOE, IIT Madras, 499-504. Mandal, S. and Prabhaharan, N...

  4. Testing reliability of MEMS materials in liquids

    Science.gov (United States)

    Kuehn, Thomas P.; Ali, S. Mubassar; Mantell, Susan C.; Longmire, Ellen K.

    2007-01-01

    MEMS are increasingly being considered for applications that involve immersion in liquids. However, there are very little reliability data for MEMS structures in liquids environments. In this study, an apparatus was developed which enables the investigation of fatigue failure of MEMS in liquids. MEMS cantilever beams were mounted on a PZT piezoelectric actuator and immersed in a liquid. A laser is reflected off the tip of the vibrating cantilever and onto a position-sensing photo-diode device (PSD) to obtain position data. From this data resonance frequency can be extracted for long-term monitoring. Cantilevers are resonated for at least 10 8 cycles. This apparatus allows for the testing of many combinations of materials and environments. For this study, the fatigue performance in liquid of silicon nitride cantilever beams was evaluated and compared to single crystal silicon cantilever beams. Tests were conducted in deionized water and a saline solution. Silicon nitride exhibited no long-term degradation of resonance frequency within measurement limits in air, DI water, and saline environments. Silicon exhibited a steady decrease in resonance. Results showed that this method could be extended to conduct reliability studies on other MEMS materials.

  5. Neural Networks and Their Application to Air Force Personnel Modeling

    Science.gov (United States)

    1991-11-01

    breadth of techniques provides fertile ground against which to compare the results obtained with neural networks. ", Most of the models in reenlistment or...Specialties (MOSs) receiving SRBs were taken from the 1980 and 1981 Enlisted Master Files ( EMFs ). These 98 MOSs were then aggregated into 15 Career Management... mechanisms , and architectures. Neural Networks, 1(1), 17-62. Hagiwara, M. (1990). Accelerated backpropagation using unlearning based on a Hebb rule

  6. A Fast C++ Implementation of Neural Network Backpropagation Training Algorithm: Application to Bayesian Optimal Image Demosaicing

    Directory of Open Access Journals (Sweden)

    Yi-Qing Wang

    2015-09-01

    Full Text Available Recent years have seen a surge of interest in multilayer neural networks fueled by their successful applications in numerous image processing and computer vision tasks. In this article, we describe a C++ implementation of the stochastic gradient descent to train a multilayer neural network, where a fast and accurate acceleration of tanh(· is achieved with linear interpolation. As an example of application, we present a neural network able to deliver state-of-the-art performance in image demosaicing.

  7. Neural Network Methodology for Earthquake Early Warning - first applications

    Science.gov (United States)

    Wenzel, F.; Koehler, N.; Cua, G.; Boese, M.

    2007-12-01

    PreSEIS is a method for earthquake early warning for finite faults (Böse, 2006) that is based on Artificial Neural Networks (ANN's), which are used for the mapping of seismic observations onto likely source parameters, including the moment magnitude and the location of an earthquake. PreSEIS integrates all available information on ground shaking at different sensors in a seismic network and up-dates the estimates of seismic source parameters regularly with proceeding time. PreSEIS has been developed and tested with synthetic waveform data using the example of Istanbul, Turkey (Böse, 2006). We will present first results of the application of PreSEIS to real data from Southern California, recorded at stations from the Southern California Seismic Network. The dataset consists of 69 shallow local earthquakes with moment magnitudes ranging between 1.96 and 7.1. The data come from broadband (20 or 40 Hz) or high broadband (80 or 100 Hz), high gain channels (3-component). The Southern California dataset will allow a comparison of our results to those of the Virtual Seismologist (Cua, 2004). We used the envelopes of the waveforms defined by Cua (2004) as input for the ANN's. The envelopes were obtained by taking the maximum absolute amplitude value of the recorded ground motion time history over a 1-second time window. Due to the fact that not all of the considered stations have recorded each earthquake, the missing records were replaced by synthetic envelopes, calculated by envelope attenuation relationships developed by Cua (2004).

  8. RF MEMS theory, design, and technology

    CERN Document Server

    Rebeiz, Gabriel M

    2003-01-01

    Ultrasmall Radio Frequency and Micro-wave Microelectromechanical systems (RF MEMs), such as switches, varactors, and phase shifters, exhibit nearly zero power consumption or loss. For this reason, they are being developed intensively by corporations worldwide for use in telecommunications equipment. This book acquaints readers with the basics of RF MEMs and describes how to design practical circuits and devices with them. The author, an acknowledged expert in the field, presents a range of real-world applications and shares many valuable tricks of the trade.

  9. Examples of Current and Future Uses of Neural-Net Image Processing for Aerospace Applications

    Science.gov (United States)

    Decker, Arthur J.

    2004-01-01

    Feed forward artificial neural networks are very convenient for performing correlated interpolation of pairs of complex noisy data sets as well as detecting small changes in image data. Image-to-image, image-to-variable and image-to-index applications have been tested at Glenn. Early demonstration applications are summarized including image-directed alignment of optics, tomography, flow-visualization control of wind-tunnel operations and structural-model-trained neural networks. A practical application is reviewed that employs neural-net detection of structural damage from interference fringe patterns. Both sensor-based and optics-only calibration procedures are available for this technique. These accomplishments have generated the knowledge necessary to suggest some other applications for NASA and Government programs. A tomography application is discussed to support Glenn's Icing Research tomography effort. The self-regularizing capability of a neural net is shown to predict the expected performance of the tomography geometry and to augment fast data processing. Other potential applications involve the quantum technologies. It may be possible to use a neural net as an image-to-image controller of an optical tweezers being used for diagnostics of isolated nano structures. The image-to-image transformation properties also offer the potential for simulating quantum computing. Computer resources are detailed for implementing the black box calibration features of the neural nets.

  10. MEMS tunable grating micro-spectrometer

    Science.gov (United States)

    Tormen, Maurizio; Lockhart, R.; Niedermann, P.; Overstolz, T.; Hoogerwerf, A.; Mayor, J.-M.; Pierer, J.; Bosshard, C.; Ischer, R.; Voirin, G.; Stanley, R. P.

    2017-11-01

    The interest in MEMS based Micro-Spectrometers is increasing due to their potential in terms of flexibility as well as cost, low mass, small volume and power savings. This interest, especially in the Near-Infrared and Mid- Infrared, ranges from planetary exploration missions to astronomy, e.g. the search for extra solar planets, as well as to many other terrestrial fields of application such as, industrial quality and surface control, chemical analysis of soil and water, detection of chemical pollutants, exhausted gas analysis, food quality control, process control in pharmaceuticals, to name a few. A compact MEMS-based Spectrometer for Near- Infrared and Mid-InfraRed operation have been conceived, designed and demonstrated. The design based on tunable MEMS blazed grating, developed in the past at CSEM [1], achieves state of the art results in terms of spectral resolution, operational wavelength range, light throughput, overall dimensions, and power consumption.

  11. Development of Unified Fabrication Process and Testing of MEMS Based Comb and Crab Type Capacitive Accelerometers for Navigational Applications

    Directory of Open Access Journals (Sweden)

    R. K. Bhan

    2016-08-01

    Full Text Available MEMS based accelerometers have already penetrated defense programs including navigation control in addition to their usual deployment in automotive, consumer and industrial markets because of their improved reliability, accuracy and excellent price performance. This paper discussed about the fabrication and testing of single axis capacitive accelerometer structures based on change in area (comb-type and change in gap (Crab type sensing principles. The accelerometers are designed for ±30 g acceleration range. A common fabrication process flow is designed for the fabrication of both types of accelerometers that are fabricated by using a three mask dissolved wafer process (DWP. Both the accelerometers showed a scale factor sensitivity of >60 mV/g at ±1 g flip test. Vibration and sensitivity testing at higher frequency was conducted on shaker table using a half sine wave shock (HSWS of 2 ms. Using HSWS test, a sensitivity in the range of ~60 mV/g was obtained for both comb or crab type structures in the 0-30 g range. It can be further tuned upto 100 mV/g by increasing the gain of the capacitance Read Out Integrated Circuit (ROIC. However, performance of the comb type of accelerometers gets affected in – 30 g to – 0 g range due to deep boron diffusion induced residual stress. The crab accelerometers showed almost linear (nonlinearity:<3 % FS behavior in the whole ±30 g range. Other tests like bias stability, bandwidth, bias temperature coefficient etc. indicate that devices are fully functional. All these observations validate our design and unified process.

  12. The MEM/Rietveld method with nano-applications - accurate charge-density studies of nano-structured materials by synchrotron-radiation powder diffraction.

    Science.gov (United States)

    Takata, Masaki

    2008-01-01

    Structural studies of materials with nano-sized spaces, called nano-structured materials, have been carried out by high-resolution powder diffraction. Our developed analytical method, which is the combination of the maximum-entropy method (MEM) and Rietveld refinement, the so-called MEM/Rietveld method, has been successfully applied to the analysis of synchrotron-radiation (SR) powder diffraction data measured at SPring-8, a third-generation SR light source. In this article, structural studies of nano-porous coordination polymers and endohedral metallofullerenes are presented with the advanced technique of SR powder experiment. The structure of the adsorbed guest molecule in the coordination polymer and encapsulated atoms in the fullerene cage are clearly revealed by the MEM charge density. The methodology of MEM/Rietveld analysis is also presented.

  13. Review on the Modeling of Electrostatic MEMS

    Science.gov (United States)

    Chuang, Wan-Chun; Lee, Hsin-Li; Chang, Pei-Zen; Hu, Yuh-Chung

    2010-01-01

    Electrostatic-driven microelectromechanical systems devices, in most cases, consist of couplings of such energy domains as electromechanics, optical electricity, thermoelectricity, and electromagnetism. Their nonlinear working state makes their analysis complex and complicated. This article introduces the physical model of pull-in voltage, dynamic characteristic analysis, air damping effect, reliability, numerical modeling method, and application of electrostatic-driven MEMS devices. PMID:22219707

  14. Characterization of dielectric charging in RF MEMS

    NARCIS (Netherlands)

    Herfst, R.W.; Huizing, H.G.A.; Steeneken, P.G.; Schmitz, Jurriaan

    Capacitive RF MEMS switches show great promise for use in wireless communication devices such as mobile phones, but the successful application of these switches is hindered by the reliability of the devices: charge injection in the dielectric layer (SiN) can cause irreversible stiction of the moving

  15. 3D heterostructures and systems for novel MEMS/NEMS.

    Science.gov (United States)

    Yakovlevich Prinz, Victor; Alexandrovich Seleznev, Vladimir; Victorovich Prinz, Alexander; Vladimirovich Kopylov, Alexander

    2009-06-01

    In this review, we consider the application of solid micro- and nanostructures of various shapes as building blocks for micro-electro-mechanical or nano-electro-mechanical systems (MEMS/NEMS). We provide examples of practical applications of structures created by MEMS/NEMS fabrication. Novel devices are briefly described, such as a high-power electrostatic nanoactuator, a fast-response tubular anemometer for measuring gas and liquid flows, a nanoprinter, a nanosyringe and optical MEMS/NEMS. The prospects are described for achieving NEMS with tunable quantum properties.

  16. 3D heterostructures and systems for novel MEMS/NEMS

    Directory of Open Access Journals (Sweden)

    Victor Yakovlevich Prinz, Vladimir Alexandrovich Seleznev, Alexander Victorovich Prinz and Alexander Vladimirovich Kopylov

    2009-01-01

    Full Text Available In this review, we consider the application of solid micro- and nanostructures of various shapes as building blocks for micro-electro-mechanical or nano-electro-mechanical systems (MEMS/NEMS. We provide examples of practical applications of structures created by MEMS/NEMS fabrication. Novel devices are briefly described, such as a high-power electrostatic nanoactuator, a fast-response tubular anemometer for measuring gas and liquid flows, a nanoprinter, a nanosyringe and optical MEMS/NEMS. The prospects are described for achieving NEMS with tunable quantum properties.

  17. Extreme-Precision MEMS Segmented Deformable Mirror Project

    Data.gov (United States)

    National Aeronautics and Space Administration — In Phase I research, Iris AO developed enhanced electromechanical models and calibration techniques for MEMS-based segmented deformable mirrors (DMs) applicable to a...

  18. A MEMS-based, wireless, biometric-like security system

    Science.gov (United States)

    Cross, Joshua D.; Schneiter, John L.; Leiby, Grant A.; McCarter, Steven; Smith, Jeremiah; Budka, Thomas P.

    2010-04-01

    We present a system for secure identification applications that is based upon biometric-like MEMS chips. The MEMS chips have unique frequency signatures resulting from fabrication process variations. The MEMS chips possess something analogous to a "voiceprint". The chips are vacuum encapsulated, rugged, and suitable for low-cost, highvolume mass production. Furthermore, the fabrication process is fully integrated with standard CMOS fabrication methods. One is able to operate the MEMS-based identification system similarly to a conventional RFID system: the reader (essentially a custom network analyzer) detects the power reflected across a frequency spectrum from a MEMS chip in its vicinity. We demonstrate prototype "tags" - MEMS chips placed on a credit card-like substrate - to show how the system could be used in standard identification or authentication applications. We have integrated power scavenging to provide DC bias for the MEMS chips through the use of a 915 MHz source in the reader and a RF-DC conversion circuit on the tag. The system enables a high level of protection against typical RFID hacking attacks. There is no need for signal encryption, so back-end infrastructure is minimal. We believe this system would make a viable low-cost, high-security system for a variety of identification and authentication applications.

  19. A novel neural dynamical approach to convex quadratic program and its efficient applications.

    Science.gov (United States)

    Xia, Youshen; Sun, Changyin

    2009-12-01

    This paper proposes a novel neural dynamical approach to a class of convex quadratic programming problems where the number of variables is larger than the number of equality constraints. The proposed continuous-time and proposed discrete-time neural dynamical approach are guaranteed to be globally convergent to an optimal solution. Moreover, the number of its neurons is equal to the number of equality constraints. In contrast, the number of neurons in existing neural dynamical methods is at least the number of the variables. Therefore, the proposed neural dynamical approach has a low computational complexity. Compared with conventional numerical optimization methods, the proposed discrete-time neural dynamical approach reduces multiplication operation per iteration and has a large computational step length. Computational examples and two efficient applications to signal processing and robot control further confirm the good performance of the proposed approach.

  20. Statistical modelling of neural networks in {gamma}-spectrometry applications

    Energy Technology Data Exchange (ETDEWEB)

    Vigneron, V.; Martinez, J.M. [CEA Centre d`Etudes de Saclay, 91 - Gif-sur-Yvette (France). Dept. de Mecanique et de Technologie; Morel, J.; Lepy, M.C. [CEA Centre d`Etudes de Saclay, 91 - Gif-sur-Yvette (France). Dept. des Applications et de la Metrologie des Rayonnements Ionisants

    1995-12-31

    Layered Neural Networks, which are a class of models based on neural computation, are applied to the measurement of uranium enrichment, i.e. the isotope ratio {sup 235} U/({sup 235} U + {sup 236} U + {sup 238} U). The usual method consider a limited number of {Gamma}-ray and X-ray peaks, and require previously calibrated instrumentation for each sample. But, in practice, the source-detector ensemble geometry conditions are critically different, thus a means of improving the above convention methods is to reduce the region of interest: this is possible by focusing on the K{sub {alpha}} X region where the three elementary components are present. Real data are used to study the performance of neural networks. Training is done with a Maximum Likelihood method to measure uranium {sup 235} U and {sup 238} U quantities in infinitely thick samples. (authors). 18 refs., 6 figs., 3 tabs.

  1. MEMS sensor technologies for human centred applications in healthcare, physical activities, safety and environmental sensing: a review on research activities in Italy.

    Science.gov (United States)

    Ciuti, Gastone; Ricotti, Leonardo; Menciassi, Arianna; Dario, Paolo

    2015-03-17

    Over the past few decades the increased level of public awareness concerning healthcare, physical activities, safety and environmental sensing has created an emerging need for smart sensor technologies and monitoring devices able to sense, classify, and provide feedbacks to users' health status and physical activities, as well as to evaluate environmental and safety conditions in a pervasive, accurate and reliable fashion. Monitoring and precisely quantifying users' physical activity with inertial measurement unit-based devices, for instance, has also proven to be important in health management of patients affected by chronic diseases, e.g., Parkinson's disease, many of which are becoming highly prevalent in Italy and in the Western world. This review paper will focus on MEMS sensor technologies developed in Italy in the last three years describing research achievements for healthcare and physical activity, safety and environmental sensing, in addition to smart systems integration. Innovative and smart integrated solutions for sensing devices, pursued and implemented in Italian research centres, will be highlighted, together with specific applications of such technologies. Finally, the paper will depict the future perspective of sensor technologies and corresponding exploitation opportunities, again with a specific focus on Italy.

  2. MEMS Sensor Technologies for Human Centred Applications in Healthcare, Physical Activities, Safety and Environmental Sensing: A Review on Research Activities in Italy

    Science.gov (United States)

    Ciuti, Gastone; Ricotti, Leonardo; Menciassi, Arianna; Dario, Paolo

    2015-01-01

    Over the past few decades the increased level of public awareness concerning healthcare, physical activities, safety and environmental sensing has created an emerging need for smart sensor technologies and monitoring devices able to sense, classify, and provide feedbacks to users’ health status and physical activities, as well as to evaluate environmental and safety conditions in a pervasive, accurate and reliable fashion. Monitoring and precisely quantifying users’ physical activity with inertial measurement unit-based devices, for instance, has also proven to be important in health management of patients affected by chronic diseases, e.g., Parkinson’s disease, many of which are becoming highly prevalent in Italy and in the Western world. This review paper will focus on MEMS sensor technologies developed in Italy in the last three years describing research achievements for healthcare and physical activity, safety and environmental sensing, in addition to smart systems integration. Innovative and smart integrated solutions for sensing devices, pursued and implemented in Italian research centres, will be highlighted, together with specific applications of such technologies. Finally, the paper will depict the future perspective of sensor technologies and corresponding exploitation opportunities, again with a specific focus on Italy. PMID:25808763

  3. Piezoelectric MEMS resonators

    CERN Document Server

    Piazza, Gianluca

    2017-01-01

    This book introduces piezoelectric microelectromechanical (pMEMS) resonators to a broad audience by reviewing design techniques including use of finite element modeling, testing and qualification of resonators, and fabrication and large scale manufacturing techniques to help inspire future research and entrepreneurial activities in pMEMS. The authors discuss the most exciting developments in the area of materials and devices for the making of piezoelectric MEMS resonators, and offer direct examples of the technical challenges that need to be overcome in order to commercialize these types of devices. Some of the topics covered include: Widely-used piezoelectric materials, as well as materials in which there is emerging interest Principle of operation and design approaches for the making of flexural, contour-mode, thickness-mode, and shear-mode piezoelectric resonators, and examples of practical implementation of these devices Large scale manufacturing approaches, with a focus on the practical aspects associate...

  4. Optical MEMS for Earth observation

    Science.gov (United States)

    Liotard, Arnaud; Viard, Thierry; Noell, Wilfried; Zamkotsian, Frédéric; Freire, Marco; Guldimann, Benedikt; Kraft, Stefan

    2017-11-01

    Due to the relatively large number of optical Earth Observation missions at ESA, this area is interesting for new space technology developments. In addition to their compactness, scalability and specific task customization, optical MEMS could generate new functions not available with current technologies and are thus candidates for the design of future space instruments. Most mature components for space applications are the digital mirror arrays, the micro-deformable mirrors, the programmable micro diffraction gratings and tiltable micromirrors. A first selection of market-pull and techno-push concepts is done. In addition, some concepts are coming from outside Earth Observation. Finally two concepts are more deeply analyzed. The first concept is a programmable slit for straylight control for space spectro-imagers. This instrument is a push-broom spectroimager for which some images cannot be exploited because of bright sources in the field-of-view. The proposed concept consists in replacing the current entrance spectrometer slit by an active row of micro-mirrors. The MEMS will permit to dynamically remove the bright sources and then to obtain a field-of-view with an optically enhanced signal-to-noise ratio. The second concept is a push-broom imager for which the acquired spectrum can be tuned by optical MEMS. This system is composed of two diffractive elements and a digital mirror array. The first diffractive element spreads the spectrum. A micromirror array is set at the location of the spectral focal plane. By putting the micro-mirrors ON or OFF, we can select parts of field-of-view or spectrum. The second diffractive element then recombines the light on a push-broom detector. Dichroics filters, strip filter, band-pass filter could be replaced by a unique instrument.

  5. Application of design of experiments and artificial neural networks ...

    African Journals Online (AJOL)

    user

    Abstract. This paper discusses the use of Distance based optimal designs in the design of experiments (DOE) and artificial neural networks (ANN) in optimizing the stacking sequence for simply supported laminated composite plate under uniformly distributed load (UDL) for minimizing the deflections and stresses. A number ...

  6. Applicability of tooth derived stem cells in neural regeneration

    Directory of Open Access Journals (Sweden)

    Ludovica Parisi

    2016-01-01

    Full Text Available Within the nervous system, regeneration is limited, and this is due to the small amount of neural stem cells, the inhibitory origin of the stem cell niche and often to the development of a scar which constitutes a mechanical barrier for the regeneration. Regarding these aspects, many efforts have been done in the research of a cell component that combined with scaffolds and growth factors could be suitable for nervous regeneration in regenerative medicine approaches. Autologous mesenchymal stem cells represent nowadays the ideal candidate for this aim, thank to their multipotency and to their amount inside adult tissues. However, issues in their harvesting, through the use of invasive techniques, and problems involved in their ageing, require the research of new autologous sources. To this purpose, the recent discovery of a stem cells component in teeth, and which derive from neural crest cells, has came to the light the possibility of using dental stem cells in nervous system regeneration. In this work, in order to give guidelines on the use of dental stem cells for neural regeneration, we briefly introduce the concepts of regeneration and regenerative medicine, we then focus the attention on odontogenesis, which involves the formation and the presence of a stem component in different parts of teeth, and finally we describe some experimental approaches which are exploiting dental stem cells for neural studies.

  7. Application of design of experiments and artificial neural networks ...

    African Journals Online (AJOL)

    This paper discusses the use of Distance based optimal designs in the design of experiments (DOE) and artificial neural networks (ANN) in optimizing the stacking sequence for simply supported laminated composite plate under uniformly distributed load (UDL) for minimizing the deflections and stresses. A number of finite ...

  8. Image Filtering with Neural Networks: applications and performance evaluation

    NARCIS (Netherlands)

    Spreeuwers, Lieuwe Jan

    1992-01-01

    A simple and elegant method to design image filters with neural networks is proposed: using small networks that scan the image and perform position invariant filtering. In the theses examples of image filtering with error backpropagation networks for edge detection, image deblurring and noise

  9. Applicability of tooth derived stem cells in neural regeneration.

    Science.gov (United States)

    Parisi, Ludovica; Manfredi, Edoardo

    2016-11-01

    Within the nervous system, regeneration is limited, and this is due to the small amount of neural stem cells, the inhibitory origin of the stem cell niche and often to the development of a scar which constitutes a mechanical barrier for the regeneration. Regarding these aspects, many efforts have been done in the research of a cell component that combined with scaffolds and growth factors could be suitable for nervous regeneration in regenerative medicine approaches. Autologous mesenchymal stem cells represent nowadays the ideal candidate for this aim, thank to their multipotency and to their amount inside adult tissues. However, issues in their harvesting, through the use of invasive techniques, and problems involved in their ageing, require the research of new autologous sources. To this purpose, the recent discovery of a stem cells component in teeth, and which derive from neural crest cells, has came to the light the possibility of using dental stem cells in nervous system regeneration. In this work, in order to give guidelines on the use of dental stem cells for neural regeneration, we briefly introduce the concepts of regeneration and regenerative medicine, we then focus the attention on odontogenesis, which involves the formation and the presence of a stem component in different parts of teeth, and finally we describe some experimental approaches which are exploiting dental stem cells for neural studies.

  10. The Development of the Differential MEMS Vector Hydrophone

    Directory of Open Access Journals (Sweden)

    Guojun Zhang

    2017-06-01

    Full Text Available To solve the problem that MEMS vector hydrophones are greatly interfered with by the vibration of the platform and flow noise in applications, this paper describes a differential MEMS vector hydrophone that could simultaneously receive acoustic signals and reject acceleration signals. Theoretical and simulation analyses have been carried out. Lastly, a prototype of the differential MEMS vector hydrophone has been created and tested using a standing wave tube and a vibration platform. The results of the test show that this hydrophone has a high sensitivity, Mv = −185 dB (@ 500 Hz, 0 dB reference 1 V/μPa, which is almost the same as the previous MEMS vector hydrophones, and has a low acceleration sensitivity, Mv = −58 dB (0 dB reference 1 V/g, which has decreased by 17 dB compared with the previous MEMS vector hydrophone. The differential MEMS vector hydrophone basically meets the requirements of acoustic vector detection when it is rigidly fixed to a working platform, which lays the foundation for engineering applications of MEMS vector hydrophones.

  11. The Development of the Differential MEMS Vector Hydrophone.

    Science.gov (United States)

    Zhang, Guojun; Liu, Mengran; Shen, Nixin; Wang, Xubo; Zhang, Wendong

    2017-06-08

    To solve the problem that MEMS vector hydrophones are greatly interfered with by the vibration of the platform and flow noise in applications, this paper describes a differential MEMS vector hydrophone that could simultaneously receive acoustic signals and reject acceleration signals. Theoretical and simulation analyses have been carried out. Lastly, a prototype of the differential MEMS vector hydrophone has been created and tested using a standing wave tube and a vibration platform. The results of the test show that this hydrophone has a high sensitivity, Mv = -185 dB (@ 500 Hz, 0 dB reference 1 V/μPa), which is almost the same as the previous MEMS vector hydrophones, and has a low acceleration sensitivity, Mv = -58 dB (0 dB reference 1 V/g), which has decreased by 17 dB compared with the previous MEMS vector hydrophone. The differential MEMS vector hydrophone basically meets the requirements of acoustic vector detection when it is rigidly fixed to a working platform, which lays the foundation for engineering applications of MEMS vector hydrophones.

  12. Application of Neural Network and Simulation Modeling to Evaluate Russian Banks’ Performance

    OpenAIRE

    Sharma, Satish; Shebalkov, Mikhail

    2013-01-01

    This paper presents an application of neural network and simulation modeling to analyze and predict the performance of 883 Russian Banks over the period 2000-2010. Correlation analysis was performed to obtain key financial indicators which reflect the leverage, liquidity, profitability and size of Banks. Neural network was trained over the entire dataset, and then simulation modeling was performed generating values which are distributed with Largest Extreme Value and Loglogistic distributions...

  13. Comparison of Simulation Algorithms for the Hopfield Neural Network: An Application of Economic Dispatch

    OpenAIRE

    Altun, Tankut Yalçınöz and Halis

    2014-01-01

    This paper is mainly concerned with an investigation of the suitability of Hopfield neural network structures in solving the power economic dispatch problem. For Hopfield neural network applications to this problem three important questions have been answered: what the size of the power system is; how efficient the computational method; and how to handle constraints. A new mapping process is formulated and a computational method for obtaining the weights and biases is described. A few simulat...

  14. A critical review on the applications of artificial neural networks in winemaking technology.

    Science.gov (United States)

    Moldes, O A; Mejuto, J C; Rial-Otero, R; Simal-Gandara, J

    2017-09-02

    Since their development in 1943, artificial neural networks were extended into applications in many fields. Last twenty years have brought their introduction into winery, where they were applied following four basic purposes: authenticity assurance systems, electronic sensory devices, production optimization methods, and artificial vision in image treatment tools, with successful and promising results. This work reviews the most significant approaches for neural networks in winemaking technologies with the aim of producing a clear and useful review document.

  15. Synthesize, optimize, analyze, repeat (SOAR): Application of neural network tools to ECG patient monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Watrous, R.; Towell, G.; Glassman, M.S. [Siemens Corporate Research, Princeton, NJ (United States)

    1995-12-31

    Results are reported from the application of tools for synthesizing, optimizing and analyzing neural networks to an ECG Patient Monitoring task. A neural network was synthesized from a rule-based classifier and optimized over a set of normal and abnormal heartbeats. The classification error rate on a separate and larger test set was reduced by a factor of 2. When the network was analyzed and reduced in size by a factor of 40%, the same level of performance was maintained.

  16. [Artificial neural networks and their application in drug addiction medicine].

    Science.gov (United States)

    Buscema, P M

    2000-01-01

    This article presents the use of a new processing technology: artificial neural networks (ANN) modeling. We introduce the reader, in an easy way, to types of problems for which researchers can use this technology. ANN represents a powerful way for understanding, predicting, and simulating complex and chaotic dynamics. We believe that social fields, human psychology, and behaviors, which are nonlinear in their essence, need an adequate methodology such as ANN in order to best investigate and comprehend them.

  17. Artificial neural networks application for solid fuel slagging intensity predictions

    Directory of Open Access Journals (Sweden)

    Kakietek Sławomir

    2017-01-01

    Full Text Available Slagging issues present in pulverized steam boilers very often lead to heat transfer problems, corrosion and not planned outages of boilers which increase the cost of energy production and decrease the efficiency of energy production. Slagging especially occurs in regions with reductive atmospheres which nowadays are very common due to very strict limitations in NOx emissions. Moreover alternative fuels like biomass which are also used in combustion systems from two decades in order to decrease CO2 emissions also usually increase the risk of slagging. Thus the prediction of slagging properties of fuels is not the minor issue which can be neglected before purchasing or mixing of fuels. This however is rather difficult to estimate and even commonly known standard laboratory methods like fusion temperature determination or special indexers calculated on the basis of proximate and ultimate analyses, very often have no reasonable correlation to real boiler fuel behaviour. In this paper the method of determination of slagging properties of solid fuels based on laboratory investigation and artificial neural networks were presented. A fuel data base with over 40 fuels was created. Neural networks simulations were carried out in order to predict the beginning temperature and intensity of slagging. Reasonable results were obtained for some of tested neural networks, especially for hybrid feedforward networks with PCA technique. Consequently neural network model will be used in Common Intelligent Boiler Operation Platform (CIBOP being elaborated within CERUBIS research project for two BP-1150 and BB-1150 steam boilers. The model among others enables proper fuel selection in order to minimize slagging risk.

  18. Application of Artificial Neural Networks for Predicting Generated Wind Power

    OpenAIRE

    Vijendra Singh

    2016-01-01

    This paper addresses design and development of an artificial neural network based system for prediction of wind energy produced by wind turbines. Now in the last decade, renewable energy emerged as an additional alternative source for electrical power generation. We need to assess wind power generation capacity by wind turbines because of its non-exhaustible nature. The power generation by electric wind turbines depends on the speed of wind, flow direction, fluctuations, density of air, gener...

  19. Application of neural networks to waste site screening

    Energy Technology Data Exchange (ETDEWEB)

    Dabiri, A.E.; Kraft, T.; Hilton, J.M. [Science Applications International Corp., San Diego, CA (United States)

    1993-03-01

    Waste site screening requires knowledge of the actual concentrations of hazardous materials and rates of flow around and below the site with time. The present approach to site screening consists primarily of drilling, boreholes near contaminated site and chemically analyzing the extracted physical samples and processing the data. In addition, hydraulic and geochemical soil properties are obtained so that numerical simulation models can be used to interpret and extrapolate the field data. The objective of this work is to investigate the feasibility of using neural network techniques to reduce the cost of waste site screening. A successful technique may lead to an ability to reduce the number of boreholes and the number of samples analyzed from each borehole to properly screen the waste site. The analytic tool development described here is inexpensive because it makes use of neural network techniques that can interpolate rapidly and which can learn how to analyze data rather than having to be explicitly programmed. In the following sections, data collection and data analyses will be described, followed by a section on different neural network techniques used. The results will be presented and compared with mathematical model. Finally, the last section will summarize the research work performed and make several recommendations for future work.

  20. Computing with Biologically Inspired Neural Oscillators: Application to Colour Image Segmentation

    Directory of Open Access Journals (Sweden)

    Ammar Belatreche

    2010-01-01

    Full Text Available This paper investigates the computing capabilities and potential applications of neural oscillators, a biologically inspired neural model, to grey scale and colour image segmentation, an important task in image understanding and object recognition. A proposed neural system that exploits the synergy between neural oscillators and Kohonen self-organising maps (SOMs is presented. It consists of a two-dimensional grid of neural oscillators which are locally connected through excitatory connections and globally connected to a common inhibitor. Each neuron is mapped to a pixel of the input image and existing objects, represented by homogenous areas, are temporally segmented through synchronisation of the activity of neural oscillators that are mapped to pixels of the same object. Self-organising maps form the basis of a colour reduction system whose output is fed to a 2D grid of neural oscillators for temporal correlation-based object segmentation. Both chromatic and local spatial features are used. The system is simulated in Matlab and its demonstration on real world colour images shows promising results and the emergence of a new bioinspired approach for colour image segmentation. The paper concludes with a discussion of the performance of the proposed system and its comparison with traditional image segmentation approaches.

  1. Shifting the Inertial Navigation Paradigm with MEMS Technology

    Science.gov (United States)

    Crain, Timothy; Brady, Tye; Bishop, Robert H.

    2010-01-01

    Why don t you use MEMS? is one of the most common questions posed to navigation systems engineers designing inertial navigation solutions in the modern era. The question stems from a general understanding that great strides have been made in terrestrial MEMS accelerometers and attitude rate sensors in terms of accuracy, mass, and power. Yet, when compared on a unit-to-unit basis, MEMS devices do not provide comparable performance (accuracy) to navigation grade sensors. This paper will propose a paradigm shift where the comparison in performance is between multiple MEMS devices and a single navigation grade sensor. The concept is that systematically, a sufficient number of MEMS sensors may mathematically provide comparable performance to a single navigation grade device and be competitive in terms power and mass allocations when viewed on a systems level. The implication is that both inertial navigation system design and fault detection, identification, and recovery could benefit from a system of MEMS devices in the same way that swarm sensing has benefited Earth observation and astronomy. A survey of the state of the art in inertial sensor accuracy scaled by mass and power will be provided to show the specific error in MEMS and navigation graded devices, a mathematical comparison of multi-unit to single-unit sensor errors will be developed, and preliminary applications to Constellation vehicles will be explored.

  2. Shifting the Intertial Navigation Paradigm with the MEMS Technology

    Science.gov (United States)

    Crain, Timothy P., II; Bishop, Robert H.; Brady, Tye

    2010-01-01

    "Why don't you use MEMS?" is of the most common questions posed to navigation systems engineers designing inertial navigation solutions in the modern era. The question stems from a general understanding that great strides have been made in terrestrial MEMS accelerometers and attitude rate sensors in terms of accuracy, mass, and power. Yet, when compared on a unit-to-unit basis, MEMS devices do not provide comparable performance (accuracy) to navigation grade sensors in several key metrics. This paper will propose a paradigm shift where the comparison in performance is between multiple MEMS devices and a single navigation grade sensor. The concept is that systematically, a sufficient number of MEMS sensors may mathematically provide comparable performance to a single navigation grade device and be competitive in terms power and mass allocations when viewed on a systems level. The implication is that both inertial navigation system design and fault detection, identification, and recovery could benefit from a system of MEMS devices in the same way that swarm sensing has benefited Earth observation and astronomy. A survey of the state of the art in inertial sensor accuracy scaled by mass and power will be provided to show the scaled error in MEMS and navigation graded devices, a mathematical comparison of multi-unit to single-unit sensor errors will be developed, and preliminary application to an Orion lunar skip atmospheric entry trajectory will be explored.

  3. Carbon microelectromechanical systems (C-MEMS) based microsupercapacitors

    KAUST Repository

    Agrawal, Richa

    2015-05-18

    The rapid development in miniaturized electronic devices has led to an ever increasing demand for high-performance rechargeable micropower scources. Microsupercapacitors in particular have gained much attention in recent years owing to their ability to provide high pulse power while maintaining long cycle lives. Carbon microelectromechanical systems (C-MEMS) is a powerful approach to fabricate high aspect ratio carbon microelectrode arrays, which has been proved to hold great promise as a platform for energy storage. C-MEMS is a versatile technique to create carbon structures by pyrolyzing a patterned photoresist. Furthermore, different active materials can be loaded onto these microelectrode platforms for further enhancement of the electrochemical performance of the C-MEMS platform. In this article, different techniques and methods in order to enhance C-MEMS based various electrochemical capacitor systems have been discussed, including electrochemical activation of C-MEMS structures for miniaturized supercapacitor applications, integration of carbon nanostructures like carbon nanotubes onto C-MEMS structures and also integration of pseudocapacitive materials such as polypyrrole onto C-MEMS structures. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

  4. Carbon microelectromechanical systems (C-MEMS) based microsupercapacitors

    Science.gov (United States)

    Agrawal, Richa; Beidaghi, Majid; Chen, Wei; Wang, Chunlei

    2015-05-01

    The rapid development in miniaturized electronic devices has led to an ever increasing demand for high-performance rechargeable micropower scources. Microsupercapacitors in particular have gained much attention in recent years owing to their ability to provide high pulse power while maintaining long cycle lives. Carbon microelectromechanical systems (C-MEMS) is a powerful approach to fabricate high aspect ratio carbon microelectrode arrays, which has been proved to hold great promise as a platform for energy storage. C-MEMS is a versatile technique to create carbon structures by pyrolyzing a patterned photoresist. Furthermore, different active materials can be loaded onto these microelectrode platforms for further enhancement of the electrochemical performance of the C-MEMS platform. In this article, different techniques and methods in order to enhance C-MEMS based various electrochemical capacitor systems have been discussed, including electrochemical activation of C-MEMS structures for miniaturized supercapacitor applications, integration of carbon nanostructures like carbon nanotubes onto C-MEMS structures and also integration of pseudocapacitive materials such as polypyrrole onto C-MEMS structures.

  5. Printing systems for MEMS packaging

    Science.gov (United States)

    Hayes, Donald J.; Cox, Weldon R.; Wallace, David B.

    2001-10-01

    Ink-jet printing technology is, in many ways, ideally suited for addressing a number of these MEMS device packaging challenges. The general advantages of this form of microdispensing derive from the incorporation of data-driven, non-contact processes which enable precise, picoliter-level volumes of material to be deposited with high accuracy and speed at target sites, even on non-planar surfaces. Being data-driven, microjet printing is a highly flexible and automated process which may readily be incorporated into manufacturing lines. It does not require application-specific tooling such as photomasks or screens, and, as an additive process with no chemical waste, it is environmentally friendly. In short, the advantages obtainable with incorporation of micro-jet printing technology in many fabrication applications range from increased process capability, integration and automation to reduced manufacturing costs.

  6. Application of Neural Network to Determine the Source Location in Acoustic Emission

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Sang Eun [Sambo Engineering Co, Seoul (Korea, Republic of)

    2005-12-15

    The iterative calculation by least square method was used to determine the source location of acoustic emission in rock, as so called 'traditional method'. The results were compared with source coordinates inferred from the application of neural network system for new input data, as so called 'new method'. Input data of the neural network were based on the time differences of longitudinal waves arrived from acoustic emission events at each transducer, the variation of longitudinal velocities at each stress level, and the coordinates of transducer as in the traditional method. The momentum back propagation neural network system adopted to determine source location, which consists of three layers, and has twenty-seven input processing elements. Applicability of the new method were identified, since the results of source location by the application of two methods were similarly concordant

  7. Practical Application of Neural Networks in State Space Control

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon

    theoretic notions followed by a detailed description of the topology, neuron functions and learning rules of the two types of neural networks treated in the thesis, the multilayer perceptron and the neurofuzzy networks. In both cases, a Least Squares second-order gradient method is used to train....... Then the controller is shown to work on a simulation example. We also address the potential problem of too rapidly fluctuating parameters by including regularization in the learning rule. Next we develop a direct adaptive certainty-equivalence controller based on neurofuzzy models. The control loop is proven...

  8. Artificial neural network applications in the calibration of spark-ignition engines: An overview

    Directory of Open Access Journals (Sweden)

    Richard Fiifi Turkson

    2016-09-01

    Full Text Available Emission legislation has become progressively tighter, making the development of new internal combustion engines very challenging. New engine technologies for complying with these regulations introduce an exponential dependency between the number of test combinations required for obtaining optimum results and the time and cost outlays. This makes the calibration task very expensive and virtually impossible to carry out. The potential use of trained neural networks in combination with Design of Experiments (DoE methods for engine calibration has been a subject of research activities in recent times. This is because artificial neural networks, compared with other data-driven modeling techniques, perform better in satisfying a majority of the modeling requirements for engine calibration including the curse of dimensionality; the use of DoE for obtaining few measurements as practicable, with the aim of reducing engine calibration costs; the required flexibility that allows model parameters to be optimized to avoid overfitting; and the facilitation of automated online optimization during the engine calibration process that eliminates the need for user intervention. The purpose of this review is to give an overview of the various applications of neural networks in the calibration of spark-ignition engines. The identified and discussed applications include system identification for rapid prototyping, virtual sensing, use of neural networks as look-up table surrogates, emerging control strategies and On-Board Diagnostic (OBD applications. The demerits of neural networks, future possibilities and alternatives were also discussed.

  9. Color segmentation using neural networks: an application to dermatology

    Science.gov (United States)

    Yova, Dido M.; Delibasis, Athanasios K.; Papaodysseus, Constantinos N.

    1999-02-01

    In the incidence of malignant melanoma, which is the most lethal skin cancer, has risen around the world more than 15 times over the last 50 years and continues to increase. Diagnosis of skin tumors can be automated based on the introduction of digital imaging in dermatology. Automated diagnosis is based on certain physical features and color information that are characteristic of benign, dysplastic or malignant tissue. In this paper, the research is addressed towards the problem of segmentation of digital images based on color information and specifically was a selected feature called variegated coloring. Neural networks - Kohonen model - were used for the automatic identification of variegated coloring and self organizing maps (SOMs) were applied to the segmentation of color images of skin cancer. A set of 12 images was used and the results were compared with the segmentation procedure of a clinical expert. The results have shown that the Kohonen model of neural networks can utilize the chromatic information of color skin images to successfully segment skin cancers from the surrounding skin.

  10. Multifunctional nanowire scaffolds for neural tissue engineering applications

    Science.gov (United States)

    Bechara, Samuel Leo

    Unlike other regions of the body, the nervous system is extremely vulnerable to damage and injury because it has a limited ability to self-repair. Over 250,000 people in the United States have spinal cord injuries and due to the complicated pathophysiology of such injuries, there are few options available for functional regeneration of the spinal column. Furthermore, peripheral nerve damage is troublingly common in the United States, with an estimated 200,000 patients treated surgically each year. The current gold standard in treatment for peripheral nerve damage is a nerve autograft. This technique was pioneered over 45 years ago, but suffers from a major drawback. By transecting a nerve from another part of the body, function is regained at the expense of destroying a nerve connection elsewhere. Because of these issues, the investigation of different materials for regenerating nervous tissue is necessary. This work examines multi-functional nanowire scaffolds to provide physical and chemical guidance cues to neural stem cells to enhance cellular activity from a biomedical engineering perspective. These multi-functional scaffolds include a unique nanowire nano-topography to provide physical cues to guide cellular adhesion. The nanowires were then coated with an electrically conductive polymer to further enhance cellular activity. Finally, nerve growth factor was conjugated to the surface of the scaffolds to provide chemical cues for the neural stem cells. The results in this work suggest that these multifunctional nanowire scaffolds could be used in vivo to repair nervous system tissue.

  11. Image Finder Mobile Application Based on Neural Networks

    Directory of Open Access Journals (Sweden)

    Nabil M. Hewahi

    2017-04-01

    Full Text Available Nowadays taking photos via mobile phone has become a very important part of everyone’s life. Almost each and every person who has a smart phone also has thousands of photos in their mobile device. At times it becomes very difficult to find a particular photo from thousands of photos, and it takes time. This research was done to come up with an innovative solution that could solve this problem. The solution will allow the user to find the required photo by simply drawing a sketch on the objects in the required picture, for example a tree or car, etc. Two types of supervised Artificial Neural Networks are used for this purpose; one is trained to identify the handmade sketches and other is trained to identify the images. The proposed approach introduces a mechanism to relate the sketches with the images by matching them after training. The experimentation results for testing the trained neural networks reached 100% for the sketches, and 84% for the images of two objects as a case study.

  12. Application of Artificial Neural Networks for Catalysis: A Review

    National Research Council Canada - National Science Library

    Hao Li; Zhien Zhang; Zhijian Liu

    2017-01-01

    .... However, their applications for catalysis were not well-studied until recent decades. In this review, we aim to summarize the applications of ANNs for catalysis research reported in the literature...

  13. SU-8 Based MEMS Process with Two Metal Layers using α-Si as a Sacrificial Material

    KAUST Repository

    Ramadan, Khaled S.

    2012-04-01

    Polymer based microelectromechanical systems (MEMS) micromachining is finding more interest in research and applications. This is due to its low cost and less time processing compared with silicon MEMS. SU-8 is a photo-patternable polymer that is used as a structural layer for MEMS and microfluidic devices. In addition to being processed with low cost, it is a biocompatible material with good mechanical properties. Also, amorphous silicon (α-Si) has found use as a sacrificial layer in silicon MEMS applications. α-Si can be deposited at large thicknesses for MEMS applications and also can be released in a dry method using XeF2 which can solve stiction problems related to MEMS applications. In this thesis, an SU-8 MEMS process is developed using amorphous silicon (α-Si) as a sacrificial layer. Electrostatic actuation and sensing is used in many MEMS applications. SU-8 is a dielectric material which limits its direct use in electrostatic actuation. This thesis provides a MEMS process with two conductive metal electrodes that can be used for out-of-plane electrostatic applications like MEMS switches and variable capacitors. The process provides the fabrication of dimples that can be conductive or non-conductive to facilitate more flexibility for MEMS designers. This SU-8 process can fabricate SU-8 MEMS structures of a single layer of two different thicknesses. Process parameters were tuned for two sets of thicknesses which are thin (5-10μm) and thick (130μm). Chevron bent-beam structures and different suspended beams (cantilevers and bridges) were fabricated to characterize the SU-8 process through extracting the density, Young’s Modulus and the Coefficient of Thermal Expansion (CTE) of SU-8. Also, the process was tested and used as an educational tool through which different MEMS structures were fabricated including MEMS switches, variable capacitors and thermal actuators.

  14. Nanotwinned metal MEMS films with unprecedented strength and stability.

    Science.gov (United States)

    Sim, Gi-Dong; Krogstad, Jessica A; Reddy, K Madhav; Xie, Kelvin Y; Valentino, Gianna M; Weihs, Timothy P; Hemker, Kevin J

    2017-06-01

    Silicon-based microelectromechanical systems (MEMS) sensors have become ubiquitous in consumer-based products, but realization of an interconnected network of MEMS devices that allows components to be remotely monitored and controlled, a concept often described as the "Internet of Things," will require a suite of MEMS materials and properties that are not currently available. We report on the synthesis of metallic nickel-molybdenum-tungsten films with direct current sputter deposition, which results in fully dense crystallographically textured films that are filled with nanotwins. These films exhibit linear elastic mechanical behavior and tensile strengths exceeding 3 GPa, which is unprecedented for materials that are compatible with wafer-level device fabrication processes. The ultrahigh strength is attributed to a combination of solid solution strengthening and the presence of dense nanotwins. These films also have excellent thermal and mechanical stability, high density, and electrical properties that are attractive for next-generation metal MEMS applications.

  15. Application of artificial neural networks in computer-aided diagnosis.

    Science.gov (United States)

    Liu, Bei

    2015-01-01

    Computer-aided diagnosis is a diagnostic procedure in which a radiologist uses the outputs of computer analysis of medical images as a second opinion in the interpretation of medical images, either to help with lesion detection or to help determine if the lesion is benign or malignant. Artificial neural networks (ANNs) are usually employed to formulate the statistical models for computer analysis. Receiver operating characteristic curves are used to evaluate the performance of the ANN alone, as well as the diagnostic performance of radiologists who take into account the ANN output as a second opinion. In this chapter, we use mammograms to illustrate how an ANN model is trained, tested, and evaluated, and how a radiologist should use the ANN output as a second opinion in CAD.

  16. Image Registration for Stability Testing of MEMS

    Science.gov (United States)

    Memarsadeghi, Nargess; LeMoigne, Jacqueline; Blake, Peter N.; Morey, Peter A.; Landsman, Wayne B.; Chambers, Victor J.; Moseley, Samuel H.

    2011-01-01

    Image registration, or alignment of two or more images covering the same scenes or objects, is of great interest in many disciplines such as remote sensing, medical imaging. astronomy, and computer vision. In this paper, we introduce a new application of image registration algorithms. We demonstrate how through a wavelet based image registration algorithm, engineers can evaluate stability of Micro-Electro-Mechanical Systems (MEMS). In particular, we applied image registration algorithms to assess alignment stability of the MicroShutters Subsystem (MSS) of the Near Infrared Spectrograph (NIRSpec) instrument of the James Webb Space Telescope (JWST). This work introduces a new methodology for evaluating stability of MEMS devices to engineers as well as a new application of image registration algorithms to computer scientists.

  17. Cell Culture on MEMS Platforms: A Review

    Science.gov (United States)

    Ni, Ming; Tong, Wen Hao; Choudhury, Deepak; Rahim, Nur Aida Abdul; Iliescu, Ciprian; Yu, Hanry

    2009-01-01

    Microfabricated systems provide an excellent platform for the culture of cells, and are an extremely useful tool for the investigation of cellular responses to various stimuli. Advantages offered over traditional methods include cost-effectiveness, controllability, low volume, high resolution, and sensitivity. Both biocompatible and bio-incompatible materials have been developed for use in these applications. Biocompatible materials such as PMMA or PLGA can be used directly for cell culture. However, for bio-incompatible materials such as silicon or PDMS, additional steps need to be taken to render these materials more suitable for cell adhesion and maintenance. This review describes multiple surface modification strategies to improve the biocompatibility of MEMS materials. Basic concepts of cell-biomaterial interactions, such as protein adsorption and cell adhesion are covered. Finally, the applications of these MEMS materials in Tissue Engineering are presented. PMID:20054478

  18. Architecture and biological applications of artificial neural networks: a tuberculosis perspective.

    Science.gov (United States)

    Darsey, Jerry A; Griffin, William O; Joginipelli, Sravanthi; Melapu, Venkata Kiran

    2015-01-01

    Advancement of science and technology has prompted researchers to develop new intelligent systems that can solve a variety of problems such as pattern recognition, prediction, and optimization. The ability of the human brain to learn in a fashion that tolerates noise and error has attracted many researchers and provided the starting point for the development of artificial neural networks: the intelligent systems. Intelligent systems can acclimatize to the environment or data and can maximize the chances of success or improve the efficiency of a search. Due to massive parallelism with large numbers of interconnected processers and their ability to learn from the data, neural networks can solve a variety of challenging computational problems. Neural networks have the ability to derive meaning from complicated and imprecise data; they are used in detecting patterns, and trends that are too complex for humans, or other computer systems. Solutions to the toughest problems will not be found through one narrow specialization; therefore we need to combine interdisciplinary approaches to discover the solutions to a variety of problems. Many researchers in different disciplines such as medicine, bioinformatics, molecular biology, and pharmacology have successfully applied artificial neural networks. This chapter helps the reader in understanding the basics of artificial neural networks, their applications, and methodology; it also outlines the network learning process and architecture. We present a brief outline of the application of neural networks to medical diagnosis, drug discovery, gene identification, and protein structure prediction. We conclude with a summary of the results from our study on tuberculosis data using neural networks, in diagnosing active tuberculosis, and predicting chronic vs. infiltrative forms of tuberculosis.

  19. Absolute stability of nonlinear systems with time delays and applications to neural networks

    Directory of Open Access Journals (Sweden)

    Xinzhi Liu

    2001-01-01

    Full Text Available In this paper, absolute stability of nonlinear systems with time delays is investigated. Sufficient conditions on absolute stability are derived by using the comparison principle and differential inequalities. These conditions are simple and easy to check. In addition, exponential stability conditions for some special cases of nonlinear delay systems are discussed. Applications of those results to cellular neural networks are presented.

  20. Artificial Neural Networks: A New Approach for Predicting Application Behavior. AIR 2001 Annual Forum Paper.

    Science.gov (United States)

    Gonzalez, Julie M. Byers; DesJardins, Stephen L.

    This paper examines how predictive modeling can be used to study application behavior. A relatively new technique, artificial neural networks (ANNs), was applied to help predict which students were likely to get into a large Research I university. Data were obtained from a university in Iowa. Two cohorts were used, each containing approximately…

  1. Image Registration for Stability Testing of MEMS

    OpenAIRE

    Memarsadeghi, Nargess; Moigne, Jacqueline Le; Blake, Peter N.; Morey, Peter A.; Landsman, Wayne B.; Chambers, Victor J.; Moseley, Samuel H.

    2013-01-01

    Image registration, or alignment of two or more images covering the same scenes or objects, is of great interest in many disciplines such as remote sensing, medical imaging, astronomy, and computer vision. In this paper, we introduce a new application of image registration algorithms. We demonstrate how through a wavelet based image registration algorithm, engineers can evaluate stability of Micro-Electro-Mechanical Systems (MEMS). In particular, we applied image registration algorithms to as...

  2. EDITORIAL: The 7th International Workshop on Micro and Nanotechnologies for Power Generation and Energy Conversion Applications (PowerMEMS 2007)

    Science.gov (United States)

    Hebling, C.; Woias, P.

    2008-10-01

    This special issue of Journal of Micromechanics and Microengineering (JMM) contains a selection of papers from the 7th International Workshop on Micro and Nanotechnologies for Power Generation and Energy Conversion (PowerMEMS 2007). The workshop was held in Freiburg, Germany on 27-29 November 2007 under the joint organization of the Fraunhofer Institute for Solar Energy Systems (FhG-ISE), Freiburg and the Department of Microsystems Engineering (IMTEK) of the Albert-Ludwig-University of Freiburg. PowerMEMS 2007 continues a series of workshops initiated in 2000 in Japan to create an annual discussion forum in the emerging field of micro energy technology. With a single exception in 2001, the workshop has continued as an annual meeting ever since, with a continuous increase in the number of presentations and participants. The program of PowerMEMS 2007 was composed of 2 invited talks, 25 oral talks and 61 poster presentations. From these 88 presentations 16 have been selected for this special issue. It was at the end of 1959 when the Caltech physicist Richard Feynman gave his famous lecture entitled 'There Is Plenty of Room at the Bottom' in which he discussed the possibilities of miniaturization for both storage capacity ('Encyclopaedia Britannica on the head of a pin') as well as micro machining ('rearranging the atoms'), although there were absolutely no technological possibilities in sight for an adequate realization of such ideas. Now, nearly 50 years later, we not only have incredible knowledge about the nanoworld, but even more we are now able to generate microelectromechanical devices which, next to their electronic properties, can integrate physical and analytical functions. Today, Feynman might easily have added a second lecture entitled 'There is Plenty of Energy at the Bottom'. Micro energy technology has seen a tremendous rise in MEMS and material sciences and is regarded today as one of their hot topics. Also, there are more and more companies in this

  3. Abstracts for the symposium on the Application of neural networks to the earth sciences

    Science.gov (United States)

    Singer, Donald A.

    2002-01-01

    Artificial neural networks are a group of mathematical methods that attempt to mimic some of the processes in the human mind. Although the foundations for these ideas were laid as early as 1943 (McCulloch and Pitts, 1943), it wasn't until 1986 (Rumelhart and McClelland, 1986; Masters, 1995) that applications to practical problems became possible. It is the acknowledged superiority of the human mind at recognizing patterns that the artificial neural networks are trying to imitate with their interconnected neurons. Interconnections used in the methods that have been developed allow robust learning. Capabilities of neural networks fall into three kinds of applications: (1) function fitting or prediction, (2) noise reduction or pattern recognition, and (3) classification or placing into types. Because of these capabilities and the powerful abilities of artificial neural networks, there have been increasing applications of these methods in the earth sciences. The abstracts in this document represent excellent samples of the range of applications. Talks associated with the abstracts were presented at the Symposium on the Application of Neural Networks to the Earth Sciences: Seventh International Symposium on Mineral Exploration (ISME–02), held August 20–21, 2002, at NASA Moffett Field, Mountain View, California. This symposium was sponsored by the Mining and Materials Processing Institute of Japan (MMIJ), the U.S. Geological Survey, the Circum-Pacific Council, and NASA. The ISME symposia have been held every two years in order to bring together scientists actively working on diverse quantitative methods applied to the earth sciences. Although the title, International Symposium on Mineral Exploration, suggests exclusive focus on mineral exploration, interests and presentations have always been wide-ranging—abstracts presented here are no exception.

  4. Development and Evaluation of Micro-Electrocorticography Arrays for Neural Interfacing Applications

    Science.gov (United States)

    Schendel, Amelia Ann

    Neural interfaces have great promise for both electrophysiological research and therapeutic applications. Whether for the study of neural circuitry or for neural prosthetic or other therapeutic applications, micro-electrocorticography (micro-ECoG) arrays have proven extremely useful as neural interfacing devices. These devices strike a balance between invasiveness and signal resolution, an important step towards eventual human application. The objective of this research was to make design improvements to micro-ECoG devices to enhance both biocompatibility and device functionality. To best evaluate the effectiveness of these improvements, a cranial window imaging method for in vivo monitoring of the longitudinal tissue response post device implant was developed. Employment of this method provided valuable insight into the way tissue grows around micro-ECoG arrays after epidural implantation, spurring a study of the effects of substrate geometry on the meningeal tissue response. The results of the substrate footprint comparison suggest that a more open substrate geometry provides an easy path for the tissue to grow around to the top side of the device, whereas a solid device substrate encourages the tissue to thicken beneath the device, between the electrode sites and the brain. The formation of thick scar tissue between the recording electrode sites and the neural tissue is disadvantageous for long-term recorded signal quality, and thus future micro-ECoG device designs should incorporate open-architecture substrates for enhanced longitudinal in vivo function. In addition to investigating improvements for long-term device reliability, it was also desired to enhance the functionality of micro-ECoG devices for neural electrophysiology research applications. To achieve this goal, a completely transparent graphene-based device was fabricated for use with the cranial window imaging method and optogenetic techniques. The use of graphene as the conductive material provided

  5. Direct integration of MEMS, dielectric pumping and cell manipulation with reversibly bonded gecko adhesive microfluidics

    Science.gov (United States)

    Warnat, S.; King, H.; Wasay, A.; Sameoto, D.; Hubbard, T.

    2016-09-01

    We present an approach to form a microfluidic environment on top of MEMS dies using reversibly bonded microfluidics. The reversible polymeric microfluidics moulds bond to the MEMS die using a gecko-inspired gasket architecture. In this study the formed microchannels are demonstrated in conjunction with a MEMS mechanical single cell testing environment for BioMEMS applications. A reversible microfluidics placement technique with an x-y and rotational accuracy of  ±2 µm and 1° respectively on a MEMS die was developed. No leaks were observed during pneumatic pumping of common cell media (PBS, sorbitol, water, seawater) through the fluidic channels. Thermal chevron actuators were successful operated inside this fluidic environment and a performance deviation of ~15% was measured compared to an open MEMS configuration. Latex micro-spheres were pumped using traveling wave di-electrophoresis and compared to an open (no-microfluidics) configuration with velocities of 24 µm s-1 and 20 µm s-1.

  6. Small-Size Eight-Band Frequency Reconfigurable Antenna Loading a MEMS Switch for Mobile Handset Applications

    Directory of Open Access Journals (Sweden)

    Xin Meng

    2014-01-01

    Full Text Available A planar small-size eight-band frequency reconfigurable antenna for LTE/WWAN mobile handset applications is proposed. The proposed antenna consists of a feeding strip and a coupled strip, with a total dimension of 10 × 29.5 mm2. Reconfigurability is realized by incorporating a one-pole four-throw RF switch, which is embedded in the coupled strip and changes the resonant modes for the lower band. By combining four different working modes, the proposed antenna successfully realize the eight-band operation, covering the operating bands of 700~787 MHz, 824~960 MHz, and 1710~2690 MHz. In addition, the simple DC bias circuit of the RF switch has little effect on the antenna performances, with no significant reduction in antenna efficiency and variations in the radiation patterns. The measured antenna efficiencies are 40%~50% and over 60% for the lower band and the upper band, respectively. Prototypes of the proposed frequency reconfigurable antenna incorporating the one-pole four-throw switch are fabricated and measured. The measured results including return losses and radiation characteristics are presented.

  7. Application of recurrent neural networks for drought projections in California

    Science.gov (United States)

    Le, J. A.; El-Askary, H. M.; Allali, M.; Struppa, D. C.

    2017-05-01

    We use recurrent neural networks (RNNs) to investigate the complex interactions between the long-term trend in dryness and a projected, short but intense, period of wetness due to the 2015-2016 El Niño. Although it was forecasted that this El Niño season would bring significant rainfall to the region, our long-term projections of the Palmer Z Index (PZI) showed a continuing drought trend, contrasting with the 1998-1999 El Niño event. RNN training considered PZI data during 1896-2006 that was validated against the 2006-2015 period to evaluate the potential of extreme precipitation forecast. We achieved a statistically significant correlation of 0.610 between forecasted and observed PZI on the validation set for a lead time of 1 month. This gives strong confidence to the forecasted precipitation indicator. The 2015-2016 El Niño season proved to be relatively weak as compared with the 1997-1998, with a peak PZI anomaly of 0.242 standard deviations below historical averages, continuing drought conditions.

  8. AN APPLICATION OF SPEAKER RECOGNITION USING ARTIFICIAL NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Murat CANER

    2006-02-01

    Full Text Available In this study an artificial neural network (ANN is implemented, which has been used frequently as an implementation model in recent years, to recognize speaker identification. Generally, recognition is consist of three stages that, processing of signal, obtaining attributes and comparing them. Speech samples are transformed into digital data according to voice card of PC. In the analysis of voice stage, recurrent periods and white noise of voice data are trimmed by hamming window method and voice attribute part of the digital data is obtained. For obtaining attribute of voice data LPC (linear predictive coding and DFT (discrete fourier transform methods are used. Of those 28 coefficents, that is used for speaker recognition, 16 were obtained by the analysis of DFT and 12 were obtained by the analysis of LPC. The parameters that represent speaker voice, is used for training and test of ANN. Multilayer perceptron model is used as an architecture of ANN and backpropagation algorithm is used for training method. Voices of "a" is taken from 7 different person and their attributes are found. ANN is trained with these features to find the speaker who is the owner of the sample voice. And then using the test data that is not used for training part, recognition achievement of ANN is tested. As a result, good results were obtained with low failure rate.

  9. Application of artificial neural network in medical geochemistry.

    Science.gov (United States)

    Fajčíková, K; Stehlíková, B; Cvečková, V; Rapant, S

    2017-12-01

    For the evaluation of various adverse health effects of chemical elements occurring in the environment on humans, the comparison and linking of geochemical data (chemical composition of groundwater, soils, and dusts) with data on health status of population (so-called health indicators) play a key role. Geochemical and health data are predominantly nonlinear, and the use of standard statistical methods can lead to wrong conclusions. For linking such data, we find appropriate the use method of artificial neural networks (ANNs) which enable to eliminate data inhomogeneity and also potential data errors. Through method of ANNs, we are able to determine the order of influence of chemical elements on health indicators as well as to define limit values for the influential elements at which the health status of population is the most favourable (i.e. the lowest mortality, the highest life expectancy). For determination of dependence between the groundwater contents of chemical elements and health indicators, we recommend to create 200 ANNs. In further calculations performed for identification of order of influence of chemical elements as well as definition of limit values, we propose to work with median or mean values from calculated 200 ANNs. The ANN represents an appropriate method to be used for environmental and health data analysis in medical geochemistry.

  10. An Application Specific Instruction Set Processor (ASIP) for Adaptive Filters in Neural Prosthetics.

    Science.gov (United States)

    Xin, Yao; Li, Will X Y; Zhang, Zhaorui; Cheung, Ray C C; Song, Dong; Berger, Theodore W

    2015-01-01

    Neural coding is an essential process for neuroprosthetic design, in which adaptive filters have been widely utilized. In a practical application, it is needed to switch between different filters, which could be based on continuous observations or point process, when the neuron models, conditions, or system requirements have changed. As candidates of coding chip for neural prostheses, low-power general purpose processors are not computationally efficient especially for large scale neural population coding. Application specific integrated circuits (ASICs) do not have flexibility to switch between different adaptive filters while the cost for design and fabrication is formidable. In this research work, we explore an application specific instruction set processor (ASIP) for adaptive filters in neural decoding activity. The proposed architecture focuses on efficient computation for the most time-consuming matrix/vector operations among commonly used adaptive filters, being able to provide both flexibility and throughput. Evaluation and implementation results are provided to demonstrate that the proposed ASIP design is area-efficient while being competitive to commercial CPUs in computational performance.

  11. Electromagnetic actuation in MEMS switches

    DEFF Research Database (Denmark)

    Oliveira Hansen, Roana Melina de; Mátéfi-Tempfli, Mária; Chemnitz, Steffen

    . Electromagnetic actuation is a very promising approach to operate such MEMS and Power MEMS devices, due to the long range, reproducible and strong forces generated by this method, among other advantages. However, the use of electromagnetic actuation in such devices requires the use of thick magnetic films, which...

  12. Application of Artificial Neural Network to Predict the use of Runway at Juanda International Airport

    Science.gov (United States)

    Putra, J. C. P.; Safrilah

    2017-06-01

    Artificial neural network approaches are useful to solve many complicated problems. It solves a number of problems in various areas such as engineering, medicine, business, manufacturing, etc. This paper presents an application of artificial neural network to predict a runway capacity at Juanda International Airport. An artificial neural network model of backpropagation and multi-layer perceptron is adopted to this research to learning process of runway capacity at Juanda International Airport. The results indicate that the training data is successfully recognizing the certain pattern of runway use at Juanda International Airport. Whereas, testing data indicate vice versa. Finally, it can be concluded that the approach of uniformity data and network architecture is the critical part to determine the accuracy of prediction results.

  13. ER fluid applications to vibration control devices and an adaptive neural-net controller

    Science.gov (United States)

    Morishita, Shin; Ura, Tamaki

    1993-07-01

    Four applications of electrorheological (ER) fluid to vibration control actuators and an adaptive neural-net control system suitable for the controller of ER actuators are described: a shock absorber system for automobiles, a squeeze film damper bearing for rotational machines, a dynamic damper for multidegree-of-freedom structures, and a vibration isolator. An adaptive neural-net control system composed of a forward model network for structural identification and a controller network is introduced for the control system of these ER actuators. As an example study of intelligent vibration control systems, an experiment was performed in which the ER dynamic damper was attached to a beam structure and controlled by the present neural-net controller so that the vibration in several modes of the beam was reduced with a single dynamic damper.

  14. Application of clustering analysis in the prediction of photovoltaic power generation based on neural network

    Science.gov (United States)

    Cheng, K.; Guo, L. M.; Wang, Y. K.; Zafar, M. T.

    2017-11-01

    In order to select effective samples in the large number of data of PV power generation years and improve the accuracy of PV power generation forecasting model, this paper studies the application of clustering analysis in this field and establishes forecasting model based on neural network. Based on three different types of weather on sunny, cloudy and rainy days, this research screens samples of historical data by the clustering analysis method. After screening, it establishes BP neural network prediction models using screened data as training data. Then, compare the six types of photovoltaic power generation prediction models before and after the data screening. Results show that the prediction model combining with clustering analysis and BP neural networks is an effective method to improve the precision of photovoltaic power generation.

  15. Evolvable Block-Based Neural Network Design for Applications in Dynamic Environments

    Directory of Open Access Journals (Sweden)

    Saumil G. Merchant

    2010-01-01

    Full Text Available Dedicated hardware implementations of artificial neural networks promise to provide faster, lower-power operation when compared to software implementations executing on microprocessors, but rarely do these implementations have the flexibility to adapt and train online under dynamic conditions. A typical design process for artificial neural networks involves offline training using software simulations and synthesis and hardware implementation of the obtained network offline. This paper presents a design of block-based neural networks (BbNNs on FPGAs capable of dynamic adaptation and online training. Specifically the network structure and the internal parameters, the two pieces of the multiparametric evolution of the BbNNs, can be adapted intrinsically, in-field under the control of the training algorithm. This ability enables deployment of the platform in dynamic environments, thereby significantly expanding the range of target applications, deployment lifetimes, and system reliability. The potential and functionality of the platform are demonstrated using several case studies.

  16. Modeling of a Piezoelectric MEMS Micropump Dedicated to Insulin Delivery and Experimental Validation Using Integrated Pressure Sensors: Application to Partial Occlusion Management

    Directory of Open Access Journals (Sweden)

    S. Fournier

    2017-01-01

    Full Text Available A numerical model based on equivalent electrical networks has been built to simulate the dynamic behavior of a positive-displacement MEMS micropump dedicated to insulin delivery. This device comprises a reservoir in direct communication with the inlet check valve, a pumping membrane actuated by a piezo actuator, two integrated piezoresistive pressure sensors, an anti-free-flow check valve at the outlet, and finally a fluidic pathway up to the patient cannula. The pressure profiles delivered by the sensors are continuously analyzed during the therapy in order to detect failures like occlusion. The numerical modeling is a reliable way to better understand the behavior of the micropump in case of failure. The experimental pressure profiles measured during the actuation phase have been used to validate the numerical modeling. The effect of partial occlusion on the pressure profiles has been also simulated. Based on this analysis, a new management of partial occlusion for MEMS micropump is finally proposed.

  17. MEMS IMU Error Mitigation Using Rotation Modulation Technique.

    Science.gov (United States)

    Du, Shuang; Sun, Wei; Gao, Yang

    2016-11-29

    Micro-electro-mechanical-systems (MEMS) inertial measurement unit (IMU) outputs are corrupted by significant sensor errors. The navigation errors of a MEMS-based inertial navigation system will therefore accumulate very quickly over time. This requires aiding from other sensors such as Global Navigation Satellite Systems (GNSS). However, it will still remain a significant challenge in the presence of GNSS outages, which are typically in urban canopies. This paper proposed a rotary inertial navigation system (INS) to mitigate navigation errors caused by MEMS inertial sensor errors when external aiding information is not available. A rotary INS is an inertial navigator in which the IMU is installed on a rotation platform. Application of proper rotation schemes can effectively cancel and reduce sensor errors. A rotary INS has the potential to significantly increase the time period that INS can bridge GNSS outages and make MEMS IMU possible to maintain longer autonomous navigation performance when there is no external aiding. In this research, several IMU rotation schemes (rotation about X-, Y- and Z-axes) are analyzed to mitigate the navigation errors caused by MEMS IMU sensor errors. As the IMU rotation induces additional sensor errors, a calibration process is proposed to remove the induced errors. Tests are further conducted with two MEMS IMUs installed on a tri-axial rotation table to verify the error mitigation by IMU rotations.

  18. Development of the micro pixel chamber based on MEMS technology

    Directory of Open Access Journals (Sweden)

    Takemura T.

    2018-01-01

    Full Text Available Micro pixel chambers (μ-PIC are gaseous two-dimensional imaging detectors originally manufactured using printed circuit board (PCB technology. They are used in MeV gamma-ray astronomy, medicalimaging, neutron imaging, the search for dark matter, and dose monitoring. The position resolution of the present μ-PIC is approximately 120 μm (RMS, however some applications require a fine position resolution of less than 100 μm. To this end, we have started to develop a μ-PIC based on micro electro mechanical system (MEMS technology, which provides better manufacturing accuracy than PCB technology. Our simulation predicted the gains of MEMS μ-PICs to be twice those of PCB μ-PICs at the same anode voltage. We manufactured two MEMS μ-PICs and tested them to study their behavior. In these experiments, we successfully operated the fabricatedMEMS μ-PICs and we achieved a maximum gain of approximately 7×103 and collected their energy spectra under irradiation of X-rays from 55Fe. However, the measured gains of the MEMS μ-PICs were less than half of the values predicted in the simulations. We postulated that the gains of the MEMS μ-PICs are diminished by the effect of the silicon used as a semiconducting substrate.

  19. MEMS Reliability: Infrastructure, Test Structures, Experiments, and Failure Modes

    Energy Technology Data Exchange (ETDEWEB)

    TANNER,DANELLE M.; SMITH,NORMAN F.; IRWIN,LLOYD W.; EATON,WILLIAM P.; HELGESEN,KAREN SUE; CLEMENT,J. JOSEPH; MILLER,WILLIAM M.; MILLER,SAMUEL L.; DUGGER,MICHAEL T.; WALRAVEN,JEREMY A.; PETERSON,KENNETH A.

    2000-01-01

    The burgeoning new technology of Micro-Electro-Mechanical Systems (MEMS) shows great promise in the weapons arena. We can now conceive of micro-gyros, micro-surety systems, and micro-navigators that are extremely small and inexpensive. Do we want to use this new technology in critical applications such as nuclear weapons? This question drove us to understand the reliability and failure mechanisms of silicon surface-micromachined MEMS. Development of a testing infrastructure was a crucial step to perform reliability experiments on MEMS devices and will be reported here. In addition, reliability test structures have been designed and characterized. Many experiments were performed to investigate failure modes and specifically those in different environments (humidity, temperature, shock, vibration, and storage). A predictive reliability model for wear of rubbing surfaces in microengines was developed. The root causes of failure for operating and non-operating MEMS are discussed. The major failure mechanism for operating MEMS was wear of the polysilicon rubbing surfaces. Reliability design rules for future MEMS devices are established.

  20. MEMS IMU Error Mitigation Using Rotation Modulation Technique

    Directory of Open Access Journals (Sweden)

    Shuang Du

    2016-11-01

    Full Text Available Micro-electro-mechanical-systems (MEMS inertial measurement unit (IMU outputs are corrupted by significant sensor errors. The navigation errors of a MEMS-based inertial navigation system will therefore accumulate very quickly over time. This requires aiding from other sensors such as Global Navigation Satellite Systems (GNSS. However, it will still remain a significant challenge in the presence of GNSS outages, which are typically in urban canopies. This paper proposed a rotary inertial navigation system (INS to mitigate navigation errors caused by MEMS inertial sensor errors when external aiding information is not available. A rotary INS is an inertial navigator in which the IMU is installed on a rotation platform. Application of proper rotation schemes can effectively cancel and reduce sensor errors. A rotary INS has the potential to significantly increase the time period that INS can bridge GNSS outages and make MEMS IMU possible to maintain longer autonomous navigation performance when there is no external aiding. In this research, several IMU rotation schemes (rotation about X-, Y- and Z-axes are analyzed to mitigate the navigation errors caused by MEMS IMU sensor errors. As the IMU rotation induces additional sensor errors, a calibration process is proposed to remove the induced errors. Tests are further conducted with two MEMS IMUs installed on a tri-axial rotation table to verify the error mitigation by IMU rotations.

  1. Application of neural models as controllers in mobile robot velocity control loop

    Science.gov (United States)

    Cerkala, Jakub; Jadlovska, Anna

    2017-01-01

    This paper presents the application of an inverse neural models used as controllers in comparison to classical PI controllers for velocity tracking control task used in two-wheel, differentially driven mobile robot. The PI controller synthesis is based on linear approximation of actuators with equivalent load. In order to obtain relevant datasets for training of feed-forward multi-layer perceptron based neural network used as neural model, the mathematical model of mobile robot, that combines its kinematic and dynamic properties such as chassis dimensions, center of gravity offset, friction and actuator parameters is used. Neural models are trained off-line to act as an inverse dynamics of DC motors with particular load using data collected in simulation experiment for motor input voltage step changes within bounded operating area. The performances of PI controllers versus inverse neural models in mobile robot internal velocity control loops are demonstrated and compared in simulation experiment of navigation control task for line segment motion in plane.

  2. Modeling of a Piezoelectric MEMS Micropump Dedicated to Insulin Delivery and Experimental Validation Using Integrated Pressure Sensors: Application to Partial Occlusion Management

    OpenAIRE

    Fournier, S; Chappel, E.

    2017-01-01

    A numerical model based on equivalent electrical networks has been built to simulate the dynamic behavior of a positive-displacement MEMS micropump dedicated to insulin delivery. This device comprises a reservoir in direct communication with the inlet check valve, a pumping membrane actuated by a piezo actuator, two integrated piezoresistive pressure sensors, an anti-free-flow check valve at the outlet, and finally a fluidic pathway up to the patient cannula. The pressure profiles delivered b...

  3. Active mems microbeam device for gas detection

    KAUST Repository

    Bouchaala, Adam M.

    2017-10-05

    Sensors and active switches for applications in gas detection and other fields are described. The devices are based on the softening and hardening nonlinear response behaviors of microelectromechanical systems (MEMS) clamped-clamped microbeams. In that context, embodiments of gas-triggered MEMS microbeam sensors and switches are described. The microbeam devices can be coated with a Metal-Organic Framework to achieve high sensitivity. For gas sensing, an amplitude-based tracking algorithm can be used to quantify an amount of gas captured by the devices according to frequency shift. Noise analysis is also conducted according to the embodiments, which shows that the microbeam devices have high stability against thermal noise. The microbeam devices are also suitable for the generation of binary sensing information for alarming, for example.

  4. Electrical and mechanical performance difference on piezoelectric segmentation in a passive MEMS DC current sensor applicable to two-wire DC appliances

    Science.gov (United States)

    Yang, Xu; Fu, Yupeng; Wang, Dong F.

    2017-01-01

    As society develops in intelligence, DC is being widely used in all kinds of field in modern life, which means that a sensitive and convenient DC sensor is necessary to monitor it. Compared with other kinds of current sensor, the proposed passive MEMS DC current sensor has several significant features: power-free passive sensing, small size and low cost. In this work, the performance difference of a cantilever-based bending MEMS DC current sensor among three segmentation PZT plates was first experimentally discovered. The distribution difference of X-dir (X-direction) stress along the Y axis is confirmed through FEM analysis. An optimized structure with two slots at the root of the cantilever has been proposed to minimize the difference of average X-dir stress on an area attached to three PZT plates. A nearly linear relationship between the output voltage V output and the AC current has been obtained through both theoretical calculation and experimental verification. The sensitivity of the developed MEMS DC current sensor is 40-25 mV A-1 in the current range of 0-400 mA. It is found that there is a good consistency among the calculation, experiment and simulation results.

  5. Application of radial basis neural network for state estimation of ...

    African Journals Online (AJOL)

    user

    MultiCraft. International Journal of Engineering, Science and Technology. Vol. 2, No. 3, 2010, pp. 19-28. INTERNATIONAL. JOURNAL OF. ENGINEERING,. SCIENCE AND. TECHNOLOGY ... state estimation is investigated by testing its applicability on a IEEE 14 bus system. The proposed estimator is compared with.

  6. MEMS-gyromatriser

    OpenAIRE

    Sandmo, Tomas

    2011-01-01

    Denne masteroppgaven tar for seg bruk av gyromatriser for å forbedre nøyaktigheten til MEMS-gyroer. Det er utviklet en matematisk modell av vinkelhastighetsmålinger fra et enkelt gyroskop, og det er gjort forsøk på å få en høyere nøyaktighet ved å kombinere målinger fra flere gyroer. I gyromatrisene er støybidragene fra gyroene samlet og kombinert, og det er benyttet Kalmanfilter som filtrerer bort store deler av støyen. Flere scenarioer er simulert, blant annet med forskjellige antall gyroer...

  7. Movable MEMS Devices on Flexible Silicon

    KAUST Repository

    Ahmed, Sally

    2013-05-05

    Flexible electronics have gained great attention recently. Applications such as flexible displays, artificial skin and health monitoring devices are a few examples of this technology. Looking closely at the components of these devices, although MEMS actuators and sensors can play critical role to extend the application areas of flexible electronics, fabricating movable MEMS devices on flexible substrates is highly challenging. Therefore, this thesis reports a process for fabricating free standing and movable MEMS devices on flexible silicon substrates; MEMS flexure thermal actuators have been fabricated to illustrate the viability of the process. Flexure thermal actuators consist of two arms: a thin hot arm and a wide cold arm separated by a small air gap; the arms are anchored to the substrate from one end and connected to each other from the other end. The actuator design has been modified by adding etch holes in the anchors to suit the process of releasing a thin layer of silicon from the bulk silicon substrate. Selecting materials that are compatible with the release process was challenging. Moreover, difficulties were faced in the fabrication process development; for example, the structural layer of the devices was partially etched during silicon release although it was protected by aluminum oxide which is not attacked by the releasing gas . Furthermore, the thin arm of the thermal actuator was thinned during the fabrication process but optimizing the patterning and etching steps of the structural layer successfully solved this problem. Simulation was carried out to compare the performance of the original and the modified designs for the thermal actuators and to study stress and temperature distribution across a device. A fabricated thermal actuator with a 250 μm long hot arm and a 225 μm long cold arm separated by a 3 μm gap produced a deflection of 3 μm before silicon release, however, the fabrication process must be optimized to obtain fully functioning

  8. A Monte Carlo EM approach for partially observable diffusion processes: theory and applications to neural networks.

    Science.gov (United States)

    Movellan, Javier R; Mineiro, Paul; Williams, R J

    2002-07-01

    We present a Monte Carlo approach for training partially observable diffusion processes. We apply the approach to diffusion networks, a stochastic version of continuous recurrent neural networks. The approach is aimed at learning probability distributions of continuous paths, not just expected values. Interestingly, the relevant activation statistics used by the learning rule presented here are inner products in the Hilbert space of square integrable functions. These inner products can be computed using Hebbian operations and do not require backpropagation of error signals. Moreover, standard kernel methods could potentially be applied to compute such inner products. We propose that the main reason that recurrent neural networks have not worked well in engineering applications (e.g., speech recognition) is that they implicitly rely on a very simplistic likelihood model. The diffusion network approach proposed here is much richer and may open new avenues for applications of recurrent neural networks. We present some analysis and simulations to support this view. Very encouraging results were obtained on a visual speech recognition task in which neural networks outperformed hidden Markov models.

  9. Performance Evaluation of Three Architectural Variants for Multi-sled MEMS Storage

    NARCIS (Netherlands)

    Khatib, M.G.

    2011-01-01

    MEMS storage technology promises appealing features, such as ultrahigh density and low cost. To stay competitive, however, its performance must improve to fulfil the increasing I/O requirements in first-tier applications. Further, it must be energy-efficient. The maturity of MEMS techniques invites

  10. Load support Improvement on Superhydropobic Surface in Lubracated -MEMS using Numerical Investigation

    NARCIS (Netherlands)

    Muchammad, Muchammad; Tauviqirrahman, Mohammad; Jamari, Jamari; Schipper, Dirk J.

    2015-01-01

    The development of micro-electro-mechanical systems (MEMS) faces a great challenge in commercial application with respect to lubrication issue recently. Short life time of lubricated MEMS is primarily caused by the failure of the lubrication. In this study, the use of superhydrophobic material

  11. Robust sliding-mode control of a MEMS optical switch

    Energy Technology Data Exchange (ETDEWEB)

    Ebrahimi, Behrouz; Bahrami, Mohsen [Mechanical Engineering Department, Amirkabir University of Technology, 434 Hafez Ave., Tehran 15, Iran Aerospace Research Institute, Tehran (Iran, Islamic Republic of)

    2006-04-01

    Over the last few years interests have emerged for application of MEMS in telecommunications. The use of MEMS for optical switching has turned to be the most attractive since this application could revolutionize fiber optic telecommunications. In this paper a robust control strategy based on sliding-mode control theory is developed for a MEMS optical switch, considering electrical, mechanical, and optical models. Sliding-mode control enables compact realization of a robust controller tolerant of device characteristics variation, non-linearties, and types of inherent instabilities. Robustness of proposed control scheme against disturbances is proved by Lyapunov second method and demonstrated through simulations. In addition, the presented control scheme is simple to implement in practical application.

  12. Image processing using pulse-coupled neural networks applications in Python

    CERN Document Server

    Lindblad, Thomas

    2013-01-01

    Image processing algorithms based on the mammalian visual cortex are powerful tools for extraction information and manipulating images. This book reviews the neural theory and translates them into digital models. Applications are given in areas of image recognition, foveation, image fusion and information extraction. The third edition reflects renewed international interest in pulse image processing with updated sections presenting several newly developed applications. This edition also introduces a suite of Python scripts that assist readers in replicating results presented in the text and to further develop their own applications.

  13. Gamma-ray irradiation of ohmic MEMS switches

    Science.gov (United States)

    Maciel, John J.; Lampen, James L.; Taylor, Edward W.

    2012-10-01

    Radio Frequency (RF) Microelectromechanical System (MEMS) switches are becoming important building blocks for a variety of military and commercial applications including switch matrices, phase shifters, electronically scanned antennas, switched filters, Automatic Test Equipment, instrumentation, cell phones and smart antennas. Low power consumption, large ratio of off-impedance to on-impedance, extreme linearity, low mass, small volume and the ability to be integrated with other electronics makes MEMS switches an attractive alternative to other mechanical and solid-state switches for a variety of space applications. Radant MEMS, Inc. has developed an electrostatically actuated broadband ohmic microswitch that has applications from DC through the microwave region. Despite the extensive earth based testing, little is known about the performance and reliability of these devices in space environments. To help fill this void, we have irradiated our commercial-off-the-shelf SPST, DC to 40 GHz MEMS switches with gamma-rays as an initial step to assessing static impact on RF performance. Results of Co-60 gamma-ray irradiation of the MEMS switches at photon energies ≥ 1.0 MeV to a total dose of ~ 118 krad(Si) did not show a statistically significant post-irradiation change in measured broadband, RF insertion loss, insertion phase, return loss and isolation.

  14. Application of artificial neural network model combined with four biomarkers in auxiliary diagnosis of lung cancer.

    Science.gov (United States)

    Duan, Xiaoran; Yang, Yongli; Tan, Shanjuan; Wang, Sihua; Feng, Xiaolei; Cui, Liuxin; Feng, Feifei; Yu, Songcheng; Wang, Wei; Wu, Yongjun

    2017-08-01

    The purpose of the study was to explore the application of artificial neural network model in the auxiliary diagnosis of lung cancer and compare the effects of back-propagation (BP) neural network with Fisher discrimination model for lung cancer screening by the combined detections of four biomarkers of p16, RASSF1A and FHIT gene promoter methylation levels and the relative telomere length. Real-time quantitative methylation-specific PCR was used to detect the levels of three-gene promoter methylation, and real-time PCR method was applied to determine the relative telomere length. BP neural network and Fisher discrimination analysis were used to establish the discrimination diagnosis model. The levels of three-gene promoter methylation in patients with lung cancer were significantly higher than those of the normal controls. The values of Z(P) in two groups were 2.641 (0.008), 2.075 (0.038) and 3.044 (0.002), respectively. The relative telomere lengths of patients with lung cancer (0.93 ± 0.32) were significantly lower than those of the normal controls (1.16 ± 0.57), t = 4.072, P neural network were 0.670 (0.569-0.761) and 0.760 (0.664-0.840). The AUC of BP neural network was higher than that of Fisher discrimination analysis, and Z(P) was 0.76. Four biomarkers are associated with lung cancer. BP neural network model for the prediction of lung cancer is better than Fisher discrimination analysis, and it can provide an excellent and intelligent diagnosis tool for lung cancer.

  15. NEURAL NETWORKS, FUZZY LOGIC AND GENETIC ALGORITHMS: APPLICATIONS AND POSSIBILITIES IN FINANCE AND ACCOUNTING

    Directory of Open Access Journals (Sweden)

    José Alonso Borba

    2010-04-01

    Full Text Available There are problems in Finance and Accounting that can not be easily solved by means of traditional techniques (e.g. bankruptcy prediction and strategies for investing in common stock. In these situations, it is possible to use methods of Artificial Intelligence. This paper analyzes empirical works published in international journals between 2000 and 2007 that present studies about the application of Neural Networks, Fuzzy Logic and Genetic Algorithms to problems in Finance and Accounting. The objective is to identify and quantify the relationships established between the available techniques and the problems studied by the researchers. Analyzing 258 papers, it was noticed that the most used technique is the Artificial Neural Network. The most researched applications are from the field of Finance, especially those related to stock exchanges (forecasting of common stock and indices prices.

  16. Design of a novel MEMS gyroscope array.

    Science.gov (United States)

    Wang, Wei; Lv, Xiaoyong; Sun, Feng

    2013-01-28

    This paper reports a novel four degree-of-freedom (DOF) MEMS vibratory gyroscope. A MEMS gyroscope array is then presented using the novel gyroscope unit. In the design of the proposed 4-DOF MEMS vibratory gyroscope, the elements of the drive-mode are set inside the whole gyroscope architecture, and the elements of sense-mode are set around the drive-mode, which thus makes it possible to combine several gyroscope units into a gyroscope array through sense-modes of all the units. The complete 2-DOF vibratory structure is utilized in both the drive-mode and sense-mode of the gyroscope unit, thereby providing the desired bandwidth and inherent robustness. The gyroscope array combines several gyroscope units by using the unique detection mass, which will increase the gain of sense-mode and improve the sensitivity of the system. The simulation results demonstrate that, compared to a single gyroscope unit, the gain of gyroscope array (n = 6) is increased by about 8 dB; a 3 dB bandwidth of 100 Hz in sense-mode and 190 Hz in drive-mode are also provided. The bandwidths of both modes are highly matched with each other, providing a bandwidth of 100 Hz for the entire system, thus illustrating that it could satisfy the requirements in practical applications.

  17. Solid polymer MEMS-based fuel cells

    Science.gov (United States)

    Jankowski, Alan F [Livermore, CA; Morse, Jeffrey D [Pleasant Hill, CA

    2008-04-22

    A micro-electro-mechanical systems (MEMS) based thin-film fuel cells for electrical power applications. The MEMS-based fuel cell may be of a solid oxide type (SOFC), a solid polymer type (SPFC), or a proton exchange membrane type (PEMFC), and each fuel cell basically consists of an anode and a cathode separated by an electrolyte layer. The electrolyte layer can consist of either a solid oxide or solid polymer material, or proton exchange membrane electrolyte materials may be used. Additionally catalyst layers can also separate the electrodes (cathode and anode) from the electrolyte. Gas manifolds are utilized to transport the fuel and oxidant to each cell and provide a path for exhaust gases. The electrical current generated from each cell is drawn away with an interconnect and support structure integrated with the gas manifold. The fuel cells utilize integrated resistive heaters for efficient heating of the materials. By combining MEMS technology with thin-film deposition technology, thin-film fuel cells having microflow channels and full-integrated circuitry can be produced that will lower the operating temperature an will yield an order of magnitude greater power density than the currently known fuel cells.

  18. Heterogeneous MEMS device assembly and integration

    Science.gov (United States)

    Topart, Patrice; Picard, Francis; Ilias, Samir; Alain, Christine; Chevalier, Claude; Fisette, Bruno; Paultre, Jacques E.; Généreux, Francis; Legros, Mathieu; Lepage, Jean-François; Laverdière, Christian; Ngo Phong, Linh; Caron, Jean-Sol; Desroches, Yan

    2014-03-01

    In recent years, smart phone applications have both raised the pressure for cost and time to market reduction, and the need for high performance MEMS devices. This trend has led the MEMS community to develop multi-die packaging of different functionalities or multi-technology (i.e. wafer) approaches to fabricate and assemble devices respectively. This paper reports on the fabrication, assembly and packaging at INO of various MEMS devices using heterogeneous assembly at chip and package-level. First, the performance of a giant (e.g. about 3 mm in diameter), electrostatically actuated beam steering mirror is presented. It can be rotated about two perpendicular axes to steer an optical beam within an angular cone of up to 60° in vector scan mode with an angular resolution of 1 mrad and a response time of 300 ms. To achieve such angular performance relative to mirror size, the microassembly was performed from sub-components fabricated from 4 different wafers. To combine infrared detection with inertial sensing, an electroplated proof mass was flip-chipped onto a 256×1 pixel uncooled bolometric FPA and released using laser ablation. In addition to the microassembly technology, performance results of packaged devices are presented. Finally, to simulate a 3072×3 pixel uncooled detector for cloud and fire imaging in mid and long-wave IR, the staggered assembly of six 512×3 pixel FPAs with a less than 50 micron pixel co-registration is reported.

  19. Improved methods in neural network-based adaptive output feedback control, with applications to flight control

    Science.gov (United States)

    Kim, Nakwan

    Utilizing the universal approximation property of neural networks, we develop several novel approaches to neural network-based adaptive output feedback control of nonlinear systems, and illustrate these approaches for several flight control applications. In particular, we address the problem of non-affine systems and eliminate the fixed point assumption present in earlier work. All of the stability proofs are carried out in a form that eliminates an algebraic loop in the neural network implementation. An approximate input/output feedback linearizing controller is augmented with a neural network using input/output sequences of the uncertain system. These approaches permit adaptation to both parametric uncertainty and unmodeled dynamics. All physical systems also have control position and rate limits, which may either deteriorate performance or cause instability for a sufficiently high control bandwidth. Here we apply a method for protecting an adaptive process from the effects of input saturation and time delays, known as "pseudo control hedging". This method was originally developed for the state feedback case, and we provide a stability analysis that extends its domain of applicability to the case of output feedback. The approach is illustrated by the design of a pitch-attitude flight control system for a linearized model of an R-50 experimental helicopter, and by the design of a pitch-rate control system for a 58-state model of a flexible aircraft consisting of rigid body dynamics coupled with actuator and flexible modes. A new approach to augmentation of an existing linear controller is introduced. It is especially useful when there is limited information concerning the plant model, and the existing controller. The approach is applied to the design of an adaptive autopilot for a guided munition. Design of a neural network adaptive control that ensures asymptotically stable tracking performance is also addressed.

  20. Wavelet neural networks with applications in financial engineering, chaos, and classification

    CERN Document Server

    Alexandridis, Antonios K

    2014-01-01

    Through extensive examples and case studies, Wavelet Neural Networks provides a step-by-step introduction to modeling, training, and forecasting using wavelet networks. The acclaimed authors present a statistical model identification framework to successfully apply wavelet networks in various applications, specifically, providing the mathematical and statistical framework needed for model selection, variable selection, wavelet network construction, initialization, training, forecasting and prediction, confidence intervals, prediction intervals, and model adequacy testing. The text is ideal for

  1. Ultra-compact MEMS FTIR spectrometer

    Science.gov (United States)

    Sabry, Yasser M.; Hassan, Khaled; Anwar, Momen; Alharon, Mohamed H.; Medhat, Mostafa; Adib, George A.; Dumont, Rich; Saadany, Bassam; Khalil, Diaa

    2017-05-01

    Portable and handheld spectrometers are being developed and commercialized in the late few years leveraging the rapidly-progressing technology and triggering new markets in the field of on-site spectroscopic analysis. Although handheld devices were commercialized for the near-infrared spectroscopy (NIRS), their size and cost stand as an obstacle against the deployment of the spectrometer as spectral sensing components needed for the smart phone industry and the IoT applications. In this work we report a chip-sized microelectromechanical system (MEMS)-based FTIR spectrometer. The core optical engine of the solution is built using a passive-alignment integration technique for a selfaligned MEMS chip; self-aligned microoptics and a single detector in a tiny package sized about 1 cm3. The MEMS chip is a monolithic, high-throughput scanning Michelson interferometer fabricated using deep reactive ion etching technology of silicon-on-insulator substrate. The micro-optical part is used for conditioning the input/output light to/from the MEMS and for further light direction to the detector. Thanks to the all-reflective design of the conditioning microoptics, the performance is free of chromatic aberration. Complemented by the excellent transmission properties of the silicon in the infrared region, the integrated solution allows very wide spectral range of operation. The reported sensor's spectral resolution is about 33 cm-1 and working in the range of 1270 nm to 2700 nm; upper limited by the extended InGaAs detector. The presented solution provides a low cost, low power, tiny size, wide wavelength range NIR spectral sensor that can be manufactured with extremely high volumes. All these features promise the compatibility of this technology with the forthcoming demand of smart portable and IoT devices.

  2. Critical dimension: MEMS road map

    Science.gov (United States)

    Poulingue, Marc; Knutrud, Paul

    2007-03-01

    The use of Micro-Electro-Mechanical Systems (MEMS) technology in mechanical, biotechnology, optical, communications, and ink jet is growing. Critical dimensions in MEMS devices are getting smaller and processes are constantly facing new metrology challenges. This paper will examine some critical dimension metrology needs and challenges for MEMS using resist-on-silicon structures. It is shown that the use of automated optical CD metrology can meet emerging measurement requirements while bringing the advantages of a non-destructive, high throughput and precise methodology.

  3. Topology optimized RF MEMS switches

    DEFF Research Database (Denmark)

    Philippine, M. A.; Zareie, H.; Sigmund, Ole

    2013-01-01

    optimization for an RF MEM capacitive switch. Extensive experimental data confirms that the switches perform as designed by the optimizations, and that our simulation models are accurate. A subset of measurements are presented here. Broader results have been submitted in full journal format.......Topology optimization is a rigorous and powerful method that should become a standard MEMS design tool - it can produce unique and non-intuitive designs that meet complex objectives and can dramatically improve the performance and reliability of MEMS devices. We present successful uses of topology...

  4. NONLINEAR SYSTEM MODELING USING SINGLE NEURON CASCADED NEURAL NETWORK FOR REAL-TIME APPLICATIONS

    Directory of Open Access Journals (Sweden)

    S. Himavathi

    2012-04-01

    Full Text Available Neural Networks (NN have proved its efficacy for nonlinear system modeling. NN based controllers and estimators for nonlinear systems provide promising alternatives to the conventional counterpart. However, NN models have to meet the stringent requirements on execution time for its effective use in real time applications. This requires the NN model to be structurally compact and computationally less complex. In this paper a parametric method of analysis is adopted to determine the compact and faster NN model among various neural network architectures. This work proves through analysis and examples that the Single Neuron Cascaded (SNC architecture is distinct in providing compact and simpler models requiring lower execution time. The unique structural growth of SNC architecture enables automation in design. The SNC Network is shown to combine the advantages of both single and multilayer neural network architectures. Extensive analysis on selected architectures and their models for four benchmark nonlinear theoretical plants and a practical application are tested. A performance comparison of the NN models is presented to demonstrate the superiority of the single neuron cascaded architecture for online real time applications.

  5. Basic concepts of artificial neural network (ANN) modeling and its application in pharmaceutical research.

    Science.gov (United States)

    Agatonovic-Kustrin, S; Beresford, R

    2000-06-01

    Artificial neural networks (ANNs) are biologically inspired computer programs designed to simulate the way in which the human brain processes information. ANNs gather their knowledge by detecting the patterns and relationships in data and learn (or are trained) through experience, not from programming. An ANN is formed from hundreds of single units, artificial neurons or processing elements (PE), connected with coefficients (weights), which constitute the neural structure and are organised in layers. The power of neural computations comes from connecting neurons in a network. Each PE has weighted inputs, transfer function and one output. The behavior of a neural network is determined by the transfer functions of its neurons, by the learning rule, and by the architecture itself. The weights are the adjustable parameters and, in that sense, a neural network is a parameterized system. The weighed sum of the inputs constitutes the activation of the neuron. The activation signal is passed through transfer function to produce a single output of the neuron. Transfer function introduces non-linearity to the network. During training, the inter-unit connections are optimized until the error in predictions is minimized and the network reaches the specified level of accuracy. Once the network is trained and tested it can be given new input information to predict the output. Many types of neural networks have been designed already and new ones are invented every week but all can be described by the transfer functions of their neurons, by the learning rule, and by the connection formula. ANN represents a promising modeling technique, especially for data sets having non-linear relationships which are frequently encountered in pharmaceutical processes. In terms of model specification, artificial neural networks require no knowledge of the data source but, since they often contain many weights that must be estimated, they require large training sets. In addition, ANNs can combine

  6. Applications of Mesenchymal Stem Cells and Neural Crest Cells in Craniofacial Skeletal Research

    Directory of Open Access Journals (Sweden)

    Satoru Morikawa

    2016-01-01

    Full Text Available Craniofacial skeletal tissues are composed of tooth and bone, together with nerves and blood vessels. This composite material is mainly derived from neural crest cells (NCCs. The neural crest is transient embryonic tissue present during neural tube formation whose cells have high potential for migration and differentiation. Thus, NCCs are promising candidates for craniofacial tissue regeneration; however, the clinical application of NCCs is hindered by their limited accessibility. In contrast, mesenchymal stem cells (MSCs are easily accessible in adults, have similar potential for self-renewal, and can differentiate into skeletal tissues, including bones and cartilage. Therefore, MSCs may represent good sources of stem cells for clinical use. MSCs are classically identified under adherent culture conditions, leading to contamination with other cell lineages. Previous studies have identified mouse- and human-specific MSC subsets using cell surface markers. Additionally, some studies have shown that a subset of MSCs is closely related to neural crest derivatives and endothelial cells. These MSCs may be promising candidates for regeneration of craniofacial tissues from the perspective of developmental fate. Here, we review the fundamental biology of MSCs in craniofacial research.

  7. Tympanic-ossicular prostheses and MEMS technology: whats and whys.

    Science.gov (United States)

    Urquiza, Rafael; López, Javier; Gonzalez-Herrera, Antonio; Povedano, Valerio; Ciges, Miguel

    2009-04-01

    Microelectromechanical systems (MEMS) technology fulfils the requirements of implantable middle ear devices and consequently it becomes an excellent option to design and develop the related transducers. To present a summarized overview of the fundamentals of mechanical technologies in relation to middle ear implants research. Analysis of the possibilities, limitations and practical applications of MEMS as regards the research, development, transference and fabrication processes. MEMS is a new technology with the potential to develop small integrated mechanical and electronic systems that share many processes of integrated circuits technology and its wide application potential. Middle ear prostheses are essentially special implantable transducers that mimic the properties of the tympano-ossicular system: electromechanical systems that deliver low energy pulses safely and efficiently into the labyrinth fluids. They primarily require: active mechanisms to preclude potential damage levels; minimum energy consumption; adequate dimensions for the middle ear; and biotolerable materials. Additionally, development and translational aspects of the selected technology are of utmost importance in this field.

  8. Cryogenic MEMS Pressure Sensor Project

    Data.gov (United States)

    National Aeronautics and Space Administration — A directly immersible cryogenic MEMS pressure sensor will be developed. Each silicon die will contain a vacuum-reference and a tent-like membrane. Offsetting thermal...

  9. Ovenized microelectromechanical system (MEMS) resonator

    Energy Technology Data Exchange (ETDEWEB)

    Olsson, Roy H; Wojciechowski, Kenneth; Kim, Bongsang

    2014-03-11

    An ovenized micro-electro-mechanical system (MEMS) resonator including: a substantially thermally isolated mechanical resonator cavity; a mechanical oscillator coupled to the mechanical resonator cavity; and a heating element formed on the mechanical resonator cavity.

  10. Long Life MEM Switch Technology

    National Research Council Canada - National Science Library

    Rebeiz, Gabriel M

    2006-01-01

    Report developed under contract FA8718-04-C-0029. Microelectromechanical (MEM) switches have already been developed that demonstrate exceptional RF performance but have been plagued by poor reliability...

  11. Optically transduced MEMS magnetometer

    Science.gov (United States)

    Nielson, Gregory N; Langlois, Eric

    2014-03-18

    MEMS magnetometers with optically transduced resonator displacement are described herein. Improved sensitivity, crosstalk reduction, and extended dynamic range may be achieved with devices including a deflectable resonator suspended from the support, a first grating extending from the support and disposed over the resonator, a pair of drive electrodes to drive an alternating current through the resonator, and a second grating in the resonator overlapping the first grating to form a multi-layer grating having apertures that vary dimensionally in response to deflection occurring as the resonator mechanically resonates in a plane parallel to the first grating in the presence of a magnetic field as a function of the Lorentz force resulting from the alternating current. A plurality of such multi-layer gratings may be disposed across a length of the resonator to provide greater dynamic range and/or accommodate fabrication tolerances.

  12. MEMS glaucoma monitoring device

    Science.gov (United States)

    Shankar, Smitha; Austin, Michael

    2007-04-01

    Glaucoma is a serious disease, affecting millions of people worldwide requiring continuous monitoring of Intra Ocular Pressure (IOP) to avoid the risk of blindness. Current laboratory measurements are infrequent, intrusive and do not indicate the progression of the disease. The paper reports on the development of an implantable Glaucoma monitoring system that can monitor IOP in the eye to indicate any elevation in risk to the patient. A mathematical model of the anterior chamber of the eye was used to analyze the complex fluid flow and pressure balance in the eye. This was done in order to determine the performance requirements of the actuator, sensor and transmission electronics that could be integrated on a single microchip using microelectromechanical systems (MEMS) technology, to carry out the testing internally. The accuracy of the system was theoretically tested against results from external medical tests. The results were found to be comparable.

  13. MEMS digital parametric loudspeaker

    KAUST Repository

    Carreno, Armando Arpys Arevalo

    2016-03-23

    This paper reports on the design and fabrication of MEMS actuator arrays suitable for Digital Sound reconstruction and Parametric Directional Loudspeakers. Two distinct versions of the device were fabricated: one using the electrostatic principle actuation and the other one, the piezoelectric principle. Both versions used similar membrane dimensions, with a diameter of 500 μm. These devices are the smallest Micro-Machined Ultrasound Transducer (MUT) arrays that can be operated for both modes: Digital Sound Reconstruction and Parametric Loudspeaker. The chips consist of an array with 256 transducers, in a footprint of 12 mm by 12 mm. The total single chip size is: 2.3 cm by 2.3 cm, including the contact pads. © 2016 IEEE.

  14. An Examination of Application of Artificial Neural Network in Cognitive Radios

    Science.gov (United States)

    Bello Salau, H.; Onwuka, E. N.; Aibinu, A. M.

    2013-12-01

    Recent advancement in software radio technology has led to the development of smart device known as cognitive radio. This type of radio fuses powerful techniques taken from artificial intelligence, game theory, wideband/multiple antenna techniques, information theory and statistical signal processing to create an outstanding dynamic behavior. This cognitive radio is utilized in achieving diverse set of applications such as spectrum sensing, radio parameter adaptation and signal classification. This paper contributes by reviewing different cognitive radio implementation that uses artificial intelligence such as the hidden markov models, metaheuristic algorithm and artificial neural networks (ANNs). Furthermore, different areas of application of ANNs and their performance metrics based approach are also examined.

  15. Neural Network Based Recognition of Signal Patterns in Application to Automatic Testing of Rails

    Directory of Open Access Journals (Sweden)

    Tomasz Ciszewski

    2006-01-01

    Full Text Available The paper describes the application of neural network for recognition of signal patterns in measuring data gathered by the railroad ultrasound testing car. Digital conversion of the measuring signal allows to store and process large quantities of data. The elaboration of smart, effective and automatic procedures recognizing the obtained patterns on the basisof measured signal amplitude has been presented. The test shows only two classes of pattern recognition. In authors’ opinion if we deliver big enough quantity of training data, presented method is applicable to a system that recognizes many classes.

  16. MEMS (Micro-Electro-Mechanical Systems) for Automotive and Consumer Electronics

    Science.gov (United States)

    Marek, Jiri; Gómez, Udo-Martin

    MEMS sensors gained over the last two decades an impressive width of applications: (a) ESP: A car is skidding and stabilizes itself without driver intervention (b) Free-fall detection: A laptop falls to the floor and protects the hard drive by parking the read/write drive head automatically before impact. (c) Airbag: An airbag fires before the driver/occupant involved in an impending automotive crash impacts the steering wheel, thereby significantly reducing physical injury risk. MEMS sensors are sensing the environmental conditions and are giving input to electronic control systems. These crucial MEMS sensors are making system reactions to human needs more intelligent, precise, and at much faster reaction rates than humanly possible. Important prerequisites for the success of sensors are their size, functionality, power consumption, and costs. This technical progress in sensor development is realized by micro-machining. The development of these processes was the breakthrough to industrial mass-production for micro-electro-mechanical systems (MEMS). Besides leading-edge micromechanical processes, innovative and robust ASIC designs, thorough simulations of the electrical and mechanical behaviour, a deep understanding of the interactions (mainly over temperature and lifetime) of the package and the mechanical structures are needed. This was achieved over the last 20 years by intense and successful development activities combined with the experience of volume production of billions of sensors. This chapter gives an overview of current MEMS technology, its applications and the market share. The MEMS processes are described, and the challenges of MEMS, compared to standard IC fabrication, are discussed. The evolution of MEMS requirements is presented, and a short survey of MEMS applications is shown. Concepts of newest inertial sensors for ESP-systems are given with an emphasis on the design concepts of the sensing element and the evaluation circuit for achieving

  17. Micro-electro-mechanical systems (MEMS: Technology for the 21st century

    Directory of Open Access Journals (Sweden)

    Đakov Tatjana A.

    2014-01-01

    Full Text Available Micro-electro-mechanical systems (MEMS are miniturized devices that can sense the environment, process and analyze information, and respond with a variety of mechanical and electrical actuators. MEMS consists of mechanical elements, sensors, actuators, electrical and electronics devices on a common silicon substrate. Micro-electro-mechanical systems are becoming a vital technology for modern society. Some of the advantages of MEMS devices are: very small size, very low power consumption, low cost, easy to integrate into systems or modify, small thermal constant, high resistance to vibration, shock and radiation, batch fabricated in large arrays, improved thermal expansion tolerance. MEMS technology is increasingly penetrating into our lives and improving quality of life, similar to what we experienced in the microelectronics revolution. Commercial opportunities for MEMS are rapidly growing in broad application areas, including biomedical, telecommunication, security, entertainment, aerospace, and more in both the consumer and industrial sectors on a global scale. As a breakthrough technology, MEMS is building synergy between previously unrelated fields such as biology and microelectronics. Many new MEMS and nanotechnology applications will emerge, expanding beyond that which is currently identified or known. MEMS are definitely technology for 21st century.

  18. Effects of Radiation on MEMS

    OpenAIRE

    Shea, Herbert

    2011-01-01

    The sensitivity of MEMS devices to radiation is reviewed, with an emphasis on radiation levels representative of space missions. While silicon and metals generally do not show mechanical degradation at the radiation levels encountered in most missions, MEMS devices have been reported to fail at doses of as few krad, corresponding to less than one year in most orbits. Radiation sensitivity is linked primarily to the impact on device operation of radiation-induced trapped charge in dielectrics...

  19. "Geo-statistics methods and neural networks in geophysical applications: A case study"

    Science.gov (United States)

    Rodriguez Sandoval, R.; Urrutia Fucugauchi, J.; Ramirez Cruz, L. C.

    2008-12-01

    The study is focus in the Ebano-Panuco basin of northeastern Mexico, which is being explored for hydrocarbon reservoirs. These reservoirs are in limestones and there is interest in determining porosity and permeability in the carbonate sequences. The porosity maps presented in this study are estimated from application of multiattribute and neural networks techniques, which combine geophysics logs and 3-D seismic data by means of statistical relationships. The multiattribute analysis is a process to predict a volume of any underground petrophysical measurement from well-log and seismic data. The data consist of a series of target logs from wells which tie a 3-D seismic volume. The target logs are neutron porosity logs. From the 3-D seismic volume a series of sample attributes is calculated. The objective of this study is to derive a set of attributes and the target log values. The selected set is determined by a process of forward stepwise regression. The analysis can be linear or nonlinear. In the linear mode the method consists of a series of weights derived by least-square minimization. In the nonlinear mode, a neural network is trained using the select attributes as inputs. In this case we used a probabilistic neural network PNN. The method is applied to a real data set from PEMEX. For better reservoir characterization the porosity distribution was estimated using both techniques. The case shown a continues improvement in the prediction of the porosity from the multiattribute to the neural network analysis. The improvement is in the training and the validation, which are important indicators of the reliability of the results. The neural network showed an improvement in resolution over the multiattribute analysis. The final maps provide more realistic results of the porosity distribution.

  20. Shock-Resistibility of MEMS-Based Inertial Microswitch under Reverse Directional Ultra-High g Acceleration for IoT Applications

    Science.gov (United States)

    Xu, Qiu; Yang, Zhuoqing; Sun, Yunna; Lai, Liyan; Jin, Zhiyu; Ding, Guifu; Zhao, Xiaolin; Yao, Jinyuan; Wang, Jing

    2017-03-01

    This paper presents a novel MEMS-based inertial microswitch design with multi-directional compact constraint structures for improving the shock-resistibility. Its shock-resistibility in the reverse-sensitive direction to ultra-high g acceleration (~hunderds of thousands) is simulated and analyzed. The dynamic response process indicates that in the designed inertial microswitch the proof mass weight G, the whole system’s stiffness k and the gap x2 between the proof mass and reverse constraint blocks have significant effect on the shock-resistibility. The MEMS inertial microswitch micro-fabricated by surface micromachining has been evaluated using the drop hammer test. The maximum allowable reverse acceleration, which does not cause the spurious trigger, is defined as the reverse acceleration threshold (athr). Test results show that athr increases with the decrease of the gap x2, and the proposed microswitch tends to have a better shock-resistibility under smaller gap. The measured responses of the microswitches with and without constraint structure indicates that the device without constraint structure is prone to spurious trigger, while the designed constraint structures can effectively improve the shock-resistibility. In this paper, the method for improving the shock-resistibility and reducing the spurious trigger has been discussed.

  1. Shock-Resistibility of MEMS-Based Inertial Microswitch under Reverse Directional Ultra-High g Acceleration for IoT Applications.

    Science.gov (United States)

    Xu, Qiu; Yang, Zhuoqing; Sun, Yunna; Lai, Liyan; Jin, Zhiyu; Ding, Guifu; Zhao, Xiaolin; Yao, Jinyuan; Wang, Jing

    2017-03-31

    This paper presents a novel MEMS-based inertial microswitch design with multi-directional compact constraint structures for improving the shock-resistibility. Its shock-resistibility in the reverse-sensitive direction to ultra-high g acceleration (~hunderds of thousands) is simulated and analyzed. The dynamic response process indicates that in the designed inertial microswitch the proof mass weight G, the whole system's stiffness k and the gap x2 between the proof mass and reverse constraint blocks have significant effect on the shock-resistibility. The MEMS inertial microswitch micro-fabricated by surface micromachining has been evaluated using the drop hammer test. The maximum allowable reverse acceleration, which does not cause the spurious trigger, is defined as the reverse acceleration threshold (athr). Test results show that athr increases with the decrease of the gap x2, and the proposed microswitch tends to have a better shock-resistibility under smaller gap. The measured responses of the microswitches with and without constraint structure indicates that the device without constraint structure is prone to spurious trigger, while the designed constraint structures can effectively improve the shock-resistibility. In this paper, the method for improving the shock-resistibility and reducing the spurious trigger has been discussed.

  2. Learning from a carbon dioxide capture system dataset: Application of the piecewise neural network algorithm

    Directory of Open Access Journals (Sweden)

    Veronica Chan

    2017-03-01

    Full Text Available This paper presents the application of a neural network rule extraction algorithm, called the piece-wise linear artificial neural network or PWL-ANN algorithm, on a carbon capture process system dataset. The objective of the application is to enhance understanding of the intricate relationships among the key process parameters. The algorithm extracts rules in the form of multiple linear regression equations by approximating the sigmoid activation functions of the hidden neurons in an artificial neural network (ANN. The PWL-ANN algorithm overcomes the weaknesses of the statistical regression approach, in which accuracies of the generated predictive models are often not satisfactory, and the opaqueness of the ANN models. The results show that the generated PWL-ANN models have accuracies that are as high as the originally trained ANN models of the four datasets of the carbon capture process system. An analysis of the extracted rules and the magnitude of the coefficients in the equations revealed that the three most significant parameters of the CO2 production rate are the steam flow rate through reboiler, reboiler pressure, and the CO2 concentration in the flue gas.

  3. Study of functional viability of SU-8-based microneedles for neural applications

    Science.gov (United States)

    Fernández, Luis J.; Altuna, Ane; Tijero, Maria; Gabriel, Gemma; Villa, Rosa; Rodríguez, Manuel J.; Batlle, Montse; Vilares, Roman; Berganzo, Javier; Blanco, F. J.

    2009-02-01

    This paper presents the design, fabrication, packaging and first test results of SU-8-based microneedles for neural applications. By the use of photolithography, sputtering and bonding techniques, polymer needles with integrated microchannels and electrodes have been successfully fabricated. The use of photolithography for the patterning of the fluidic channel integrated in the needle allows the design of multiple outlet ports at the needle tip, minimizing the possibility of being blocked by the tissue. Furthermore, the flexibility of the polymer reduces the risk of fracture and tissue damage once the needle is inserted, while it is still rigid enough to allow a perfect insertion into the neural tissue. Fluidic and electric characterization of the microneedles has shown their viability for drug delivery and monitoring in neural applications. First drug delivery tests in ex vivo tissue demonstrated the functional viability of the needle to deliver drugs to precise points. Furthermore, in vivo experiments have demonstrated lower associated damages during insertion than those by stereotaxic standard needles.

  4. Application of neural network in market segmentation: A review on recent trends

    Directory of Open Access Journals (Sweden)

    Manojit Chattopadhyay

    2012-04-01

    Full Text Available Despite the significance of Artificial Neural Network (ANN algorithm to market segmentation, there is a need of a comprehensive literature review and a classification system for it towards identification of future trend of market segmentation research. The present work is the first identifiable academic literature review of the application of neural network based techniques to segmentation. Our study has provided an academic database of literature between the periods of 2000–2010 and proposed a classification scheme for the articles. One thousands (1000 articles have been identified, and around 100 relevant selected articles have been subsequently reviewed and classified based on the major focus of each paper. Findings of this study indicated that the research area of ANN based applications are receiving most research attention and self organizing map based applications are second in position to be used in segmentation. The commonly used models for market segmentation are data mining, intelligent system etc. Our analysis furnishes a roadmap to guide future research and aid knowledge accretion and establishment pertaining to the application of ANN based techniques in market segmentation. Thus the present work will significantly contribute to both the industry and academic research in business and marketing as a sustainable valuable knowledge source of market segmentation with the future trend of ANN application in segmentation.

  5. Multiple Linear Regression Model Based on Neural Network and Its Application in the MBR Simulation

    Directory of Open Access Journals (Sweden)

    Chunqing Li

    2012-01-01

    Full Text Available The computer simulation of the membrane bioreactor MBR has become the research focus of the MBR simulation. In order to compensate for the defects, for example, long test period, high cost, invisible equipment seal, and so forth, on the basis of conducting in-depth study of the mathematical model of the MBR, combining with neural network theory, this paper proposed a three-dimensional simulation system for MBR wastewater treatment, with fast speed, high efficiency, and good visualization. The system is researched and developed with the hybrid programming of VC++ programming language and OpenGL, with a multifactor linear regression model of affecting MBR membrane fluxes based on neural network, applying modeling method of integer instead of float and quad tree recursion. The experiments show that the three-dimensional simulation system, using the above models and methods, has the inspiration and reference for the future research and application of the MBR simulation technology.

  6. Parzen neural networks: Fundamentals, properties, and an application to forensic anthropology.

    Science.gov (United States)

    Trentin, Edmondo; Lusnig, Luca; Cavalli, Fabio

    2017-10-18

    A novel, unsupervised nonparametric model of multivariate probability density functions (pdf) is introduced, namely the Parzen neural network (PNN). The PNN is intended to overcome the major limitations of traditional (either statistical or neural) pdf estimation techniques. Besides being profitably simple, the PNN turns out to have nice properties in terms of unbiased modeling capability, asymptotic convergence, and efficiency at test time. Several matters pertaining the practical application of the PNN are faced in the paper, too. Experiments are reported, involving (i) synthetic datasets, and (ii) a challenging sex determination task from 1400 scout-view CT-scan images of human crania. Incidentally, the empirical evidence entails also some conclusions of high anthropological relevance. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. New Endoscopic Imaging Technology Based on MEMS Sensors and Actuators

    Directory of Open Access Journals (Sweden)

    Zhen Qiu

    2017-07-01

    Full Text Available Over the last decade, optical fiber-based forms of microscopy and endoscopy have extended the realm of applicability for many imaging modalities. Optical fiber-based imaging modalities permit the use of remote illumination sources and enable flexible forms supporting the creation of portable and hand-held imaging instrumentations to interrogate within hollow tissue cavities. A common challenge in the development of such devices is the design and integration of miniaturized optical and mechanical components. Until recently, microelectromechanical systems (MEMS sensors and actuators have been playing a key role in shaping the miniaturization of these components. This is due to the precision mechanics of MEMS, microfabrication techniques, and optical functionality enabling a wide variety of movable and tunable mirrors, lenses, filters, and other optical structures. Many promising results from MEMS based optical fiber endoscopy have demonstrated great potentials for clinical translation. In this article, reviews of MEMS sensors and actuators for various fiber-optical endoscopy such as fluorescence, optical coherence tomography, confocal, photo-acoustic, and two-photon imaging modalities will be discussed. This advanced MEMS based optical fiber endoscopy can provide cellular and molecular features with deep tissue penetration enabling guided resections and early cancer assessment to better treatment outcomes.

  8. Shock reliability enhancement for MEMS vibration energy harvesters with nonlinear air damping as a soft stopper

    Science.gov (United States)

    Chen, Shao-Tuan; Du, Sijun; Arroyo, Emmanuelle; Jia, Yu; Seshia, Ashwin

    2017-10-01

    This paper presents a novel application of utilising nonlinear air damping as a soft mechanical stopper to increase the shock reliability for microelectromechanical systems (MEMS) vibration energy harvesters. The theoretical framework for nonlinear air damping is constructed for MEMS vibration energy harvesters operating in different air pressure levels, and characterisation experiments are conducted to establish the relationship between air pressure and nonlinear air damping coefficient for rectangular cantilever MEMS micro cantilevers with different proof masses. Design guidelines on choosing the optimal air pressure level for different MEMS vibration energy harvesters based on the trade-off between harvestable energy and the device robustness are presented, and random excitation experiments are performed to verify the robustness of MEMS vibration energy harvesters with nonlinear air damping as soft stoppers to limit the maximum deflection distance and increase the shock reliability of the device.

  9. Integrated Magnetic MEMS Relays: Status of the Technology

    Directory of Open Access Journals (Sweden)

    Giuseppe Schiavone

    2014-08-01

    Full Text Available The development and application of magnetic technologies employing microfabricated magnetic structures for the production of switching components has generated enormous interest in the scientific and industrial communities over the last decade. Magnetic actuation offers many benefits when compared to other schemes for microelectromechanical systems (MEMS, including the generation of forces that have higher magnitude and longer range. Magnetic actuation can be achieved using different excitation sources, which create challenges related to the integration with other technologies, such as CMOS (Complementary Metal Oxide Semiconductor, and the requirement to reduce power consumption. Novel designs and technologies are therefore sought to enable the use of magnetic switching architectures in integrated MEMS devices, without incurring excessive energy consumption. This article reviews the status of magnetic MEMS technology and presents devices recently developed by various research groups, with key focuses on integrability and effective power management, in addition to the ability to integrate the technology with other microelectronic fabrication processes.

  10. Neural networks for learning and prediction with applications to remote sensing and speech perception

    Science.gov (United States)

    Gjaja, Marin N.

    1997-11-01

    Neural networks for supervised and unsupervised learning are developed and applied to problems in remote sensing, continuous map learning, and speech perception. Adaptive Resonance Theory (ART) models are real-time neural networks for category learning, pattern recognition, and prediction. Unsupervised fuzzy ART networks synthesize fuzzy logic and neural networks, and supervised ARTMAP networks incorporate ART modules for prediction and classification. New ART and ARTMAP methods resulting from analyses of data structure, parameter specification, and category selection are developed. Architectural modifications providing flexibility for a variety of applications are also introduced and explored. A new methodology for automatic mapping from Landsat Thematic Mapper (TM) and terrain data, based on fuzzy ARTMAP, is developed. System capabilities are tested on a challenging remote sensing problem, prediction of vegetation classes in the Cleveland National Forest from spectral and terrain features. After training at the pixel level, performance is tested at the stand level, using sites not seen during training. Results are compared to those of maximum likelihood classifiers, back propagation neural networks, and K-nearest neighbor algorithms. Best performance is obtained using a hybrid system based on a convex combination of fuzzy ARTMAP and maximum likelihood predictions. This work forms the foundation for additional studies exploring fuzzy ARTMAP's capability to estimate class mixture composition for non-homogeneous sites. Exploratory simulations apply ARTMAP to the problem of learning continuous multidimensional mappings. A novel system architecture retains basic ARTMAP properties of incremental and fast learning in an on-line setting while adding components to solve this class of problems. The perceptual magnet effect is a language-specific phenomenon arising early in infant speech development that is characterized by a warping of speech sound perception. An

  11. Application of Surface Protective Coating to Enhance Environment-Withstanding Property of the MEMS 2D Wind Direction and Wind Speed Sensor.

    Science.gov (United States)

    Shin, Kyu-Sik; Lee, Dae-Sung; Song, Sang-Woo; Jung, Jae Pil

    2017-09-19

    In this study, a microelectromechanical system (MEMS) two-dimensional (2D) wind direction and wind speed sensor consisting of a square heating source and four thermopiles was manufactured using the heat detection method. The heating source and thermopiles of the manufactured sensor must be exposed to air to detect wind speed and wind direction. Therefore, there are concerns that the sensor could be contaminated by deposition or adhesion of dust, sandy dust, snow, rain, and so forth, in the air, and that the membrane may be damaged by physical shock. Hence, there was a need to protect the heating source, thermopiles, and the membrane from environmental and physical shock. The upper protective coating to protect both the heating source and thermopiles and the lower protective coating to protect the membrane were formed by using high-molecular substances such as SU-8, Teflon and polyimide (PI). The sensor characteristics with the applied protective coatings were evaluated.

  12. A Two-Step Global Maximum Error Controller-Based TPWL MOR with POD Basis Vectors and Its Applications to MEMS

    Directory of Open Access Journals (Sweden)

    Ying Liu

    2017-01-01

    Full Text Available In our previous study, we have proposed a linearization point (LP selection method based on a global maximum error controller for the trajectory piecewise-linear (TPWL method. It has been demonstrated that this method has many advantages over other existing methods. In this paper, a more efficient version of this method is presented, which introduces a preliminary LP selection procedure and constructs projection matrix by the proper orthogonal decomposition (POD method. Compared with the original method, the improved method takes much less time for extracting a reduced-order model (ROM of similar quality and gets some other benefits (such as being easier to implement, having lower memory requirement, and enhanced flexibility. The effectiveness of the new method is fully demonstrated by a diode transmission line RLC circuit. And then, the method is applied to three more complicated microelectromechanical systems (MEMS devices, which are a micromachined switch, an electrostatic micropump diaphragm, and a thermomechanical in-plane microactuator.

  13. Characterization of dielectric charging in RF MEMS capacitive switches

    NARCIS (Netherlands)

    Herfst, R.W.; Huizing, H.G.A.; Steeneken, P.G.; Schmitz, Jurriaan

    2006-01-01

    RF MEMS capacitive switches show great promise for use in wireless communication devices such as mobile phones, but the successful application of these switches is hindered by reliability concerns: charge injection in the dielectric layer (SiN) can cause irreversible stiction of the moving part of

  14. CMOS MEMS Fabrication Technologies and Devices

    Directory of Open Access Journals (Sweden)

    Hongwei Qu

    2016-01-01

    Full Text Available This paper reviews CMOS (complementary metal-oxide-semiconductor MEMS (micro-electro-mechanical systems fabrication technologies and enabled micro devices of various sensors and actuators. The technologies are classified based on the sequence of the fabrication of CMOS circuitry and MEMS elements, while SOI (silicon-on-insulator CMOS MEMS are introduced separately. Introduction of associated devices follows the description of the respective CMOS MEMS technologies. Due to the vast array of CMOS MEMS devices, this review focuses only on the most typical MEMS sensors and actuators including pressure sensors, inertial sensors, frequency reference devices and actuators utilizing different physics effects and the fabrication processes introduced. Moreover, the incorporation of MEMS and CMOS is limited to monolithic integration, meaning wafer-bonding-based stacking and other integration approaches, despite their advantages, are excluded from the discussion. Both competitive industrial products and state-of-the-art research results on CMOS MEMS are covered.

  15. Artificial Neural Networks for Processing Graphs with Application to Image Understanding: A Survey

    Science.gov (United States)

    Bianchini, Monica; Scarselli, Franco

    In graphical pattern recognition, each data is represented as an arrangement of elements, that encodes both the properties of each element and the relations among them. Hence, patterns are modelled as labelled graphs where, in general, labels can be attached to both nodes and edges. Artificial neural networks able to process graphs are a powerful tool for addressing a great variety of real-world problems, where the information is naturally organized in entities and relationships among entities and, in fact, they have been widely used in computer vision, f.i. in logo recognition, in similarity retrieval, and for object detection. In this chapter, we propose a survey of neural network models able to process structured information, with a particular focus on those architectures tailored to address image understanding applications. Starting from the original recursive model (RNNs), we subsequently present different ways to represent images - by trees, forests of trees, multiresolution trees, directed acyclic graphs with labelled edges, general graphs - and, correspondingly, neural network architectures appropriate to process such structures.

  16. Uncertainties in Parameters Estimated with Neural Networks: Application to Strong Gravitational Lensing

    Science.gov (United States)

    Perreault Levasseur, Laurence; Hezaveh, Yashar D.; Wechsler, Risa H.

    2017-11-01

    In Hezaveh et al. we showed that deep learning can be used for model parameter estimation and trained convolutional neural networks to determine the parameters of strong gravitational-lensing systems. Here we demonstrate a method for obtaining the uncertainties of these parameters. We review the framework of variational inference to obtain approximate posteriors of Bayesian neural networks and apply it to a network trained to estimate the parameters of the Singular Isothermal Ellipsoid plus external shear and total flux magnification. We show that the method can capture the uncertainties due to different levels of noise in the input data, as well as training and architecture-related errors made by the network. To evaluate the accuracy of the resulting uncertainties, we calculate the coverage probabilities of marginalized distributions for each lensing parameter. By tuning a single variational parameter, the dropout rate, we obtain coverage probabilities approximately equal to the confidence levels for which they were calculated, resulting in accurate and precise uncertainty estimates. Our results suggest that the application of approximate Bayesian neural networks to astrophysical modeling problems can be a fast alternative to Monte Carlo Markov Chains, allowing orders of magnitude improvement in speed.

  17. Gait Phases Recognition from Accelerations and Ground Reaction Forces: Application of Neural Networks

    Directory of Open Access Journals (Sweden)

    S. Rafajlović

    2009-06-01

    Full Text Available The goal of this study was to test the applicability of accelerometer as the sensor for assessment of the walking. We present here the comparison of gait phases detected from the data recorded by force sensing resistors mounted in the shoe insoles, non-processed acceleration and processed acceleration perpendicular to the direction of the foot. The gait phases in all three cases were detected by means of a neural network. The output from the neural network was the gait phase, while the inputs were data from the sensors. The results show that the errors were in the ranges: 30 ms (2.7% – force sensors; 150 ms (13.6% – nonprocessed acceleration, and 120 ms (11% – processed acceleration data. This result suggests that it is possible to use the accelerometer as the gait phase detector, however, with the knowledge that the gait phases are time shifted for about 100 ms with respect the neural network predicted times.

  18. Modeling Markov switching ARMA-GARCH neural networks models and an application to forecasting stock returns.

    Science.gov (United States)

    Bildirici, Melike; Ersin, Özgür

    2014-01-01

    The study has two aims. The first aim is to propose a family of nonlinear GARCH models that incorporate fractional integration and asymmetric power properties to MS-GARCH processes. The second purpose of the study is to augment the MS-GARCH type models with artificial neural networks to benefit from the universal approximation properties to achieve improved forecasting accuracy. Therefore, the proposed Markov-switching MS-ARMA-FIGARCH, APGARCH, and FIAPGARCH processes are further augmented with MLP, Recurrent NN, and Hybrid NN type neural networks. The MS-ARMA-GARCH family and MS-ARMA-GARCH-NN family are utilized for modeling the daily stock returns in an emerging market, the Istanbul Stock Index (ISE100). Forecast accuracy is evaluated in terms of MAE, MSE, and RMSE error criteria and Diebold-Mariano equal forecast accuracy tests. The results suggest that the fractionally integrated and asymmetric power counterparts of Gray's MS-GARCH model provided promising results, while the best results are obtained for their neural network based counterparts. Further, among the models analyzed, the models based on the Hybrid-MLP and Recurrent-NN, the MS-ARMA-FIAPGARCH-HybridMLP, and MS-ARMA-FIAPGARCH-RNN provided the best forecast performances over the baseline single regime GARCH models and further, over the Gray's MS-GARCH model. Therefore, the models are promising for various economic applications.

  19. Modeling Markov Switching ARMA-GARCH Neural Networks Models and an Application to Forecasting Stock Returns

    Directory of Open Access Journals (Sweden)

    Melike Bildirici

    2014-01-01

    Full Text Available The study has two aims. The first aim is to propose a family of nonlinear GARCH models that incorporate fractional integration and asymmetric power properties to MS-GARCH processes. The second purpose of the study is to augment the MS-GARCH type models with artificial neural networks to benefit from the universal approximation properties to achieve improved forecasting accuracy. Therefore, the proposed Markov-switching MS-ARMA-FIGARCH, APGARCH, and FIAPGARCH processes are further augmented with MLP, Recurrent NN, and Hybrid NN type neural networks. The MS-ARMA-GARCH family and MS-ARMA-GARCH-NN family are utilized for modeling the daily stock returns in an emerging market, the Istanbul Stock Index (ISE100. Forecast accuracy is evaluated in terms of MAE, MSE, and RMSE error criteria and Diebold-Mariano equal forecast accuracy tests. The results suggest that the fractionally integrated and asymmetric power counterparts of Gray’s MS-GARCH model provided promising results, while the best results are obtained for their neural network based counterparts. Further, among the models analyzed, the models based on the Hybrid-MLP and Recurrent-NN, the MS-ARMA-FIAPGARCH-HybridMLP, and MS-ARMA-FIAPGARCH-RNN provided the best forecast performances over the baseline single regime GARCH models and further, over the Gray’s MS-GARCH model. Therefore, the models are promising for various economic applications.

  20. Porosity Estimation By Artificial Neural Networks Inversion . Application to Algerian South Field

    Science.gov (United States)

    Eladj, Said; Aliouane, Leila; Ouadfeul, Sid-Ali

    2017-04-01

    One of the main geophysicist's current challenge is the discovery and the study of stratigraphic traps, this last is a difficult task and requires a very fine analysis of the seismic data. The seismic data inversion allows obtaining lithological and stratigraphic information for the reservoir characterization . However, when solving the inverse problem we encounter difficult problems such as: Non-existence and non-uniqueness of the solution add to this the instability of the processing algorithm. Therefore, uncertainties in the data and the non-linearity of the relationship between the data and the parameters must be taken seriously. In this case, the artificial intelligence techniques such as Artificial Neural Networks(ANN) is used to resolve this ambiguity, this can be done by integrating different physical properties data which requires a supervised learning methods. In this work, we invert the acoustic impedance 3D seismic cube using the colored inversion method, then, the introduction of the acoustic impedance volume resulting from the first step as an input of based model inversion method allows to calculate the Porosity volume using the Multilayer Perceptron Artificial Neural Network. Application to an Algerian South hydrocarbon field clearly demonstrate the power of the proposed processing technique to predict the porosity for seismic data, obtained results can be used for reserves estimation, permeability prediction, recovery factor and reservoir monitoring. Keywords: Artificial Neural Networks, inversion, non-uniqueness , nonlinear, 3D porosity volume, reservoir characterization .

  1. Three applications of pulse-coupled neural networks and an optoelectronic hardware implementation

    Science.gov (United States)

    Banish, Michele R.; Ranganath, Heggere S.; Karpinsky, John R.; Clark, Rodney L.; Germany, Glynn A.; Richards, Philip G.

    1999-03-01

    Pulse Coupled Neural Networks have been extended and modified to suit image segmentation applications. Previous research demonstrated the ability of a PCNN to ignore noisy variations in intensity and small spatial discontinuities in images that prove beneficial to image segmentation and image smoothing. This paper describes four research and development projects that relate to PCNN segmentation - three different signal processing applications and a CMOS integrated circuit implementation. The software for the diagnosis of Pulmonary Embolism from VQ lung scans uses PCNN in single burst mode for segmenting perfusion and ventilation images. The second project is attempting to detect ischemia by comparing 3D SPECT images of the heart obtained during stress and rest conditions, respectively. The third application is a space science project which deals with the study of global aurora images obtained from UV Imager. The paper also describes the hardware implementation of PCNN algorithm as an electro-optical chip.

  2. Recent Advances and Future Challenges for Artificial Neural Systems in Geotechnical Engineering Applications

    Directory of Open Access Journals (Sweden)

    Mohamed A. Shahin

    2009-01-01

    Full Text Available Artificial neural networks (ANNs are a form of artificial intelligence that has proved to provide a high level of competency in solving many complex engineering problems that are beyond the computational capability of classical mathematics and traditional procedures. In particular, ANNs have been applied successfully to almost all aspects of geotechnical engineering problems. Despite the increasing number and diversity of ANN applications in geotechnical engineering, the contents of reported applications indicate that the progress in ANN development and procedures is marginal and not moving forward since the mid-1990s. This paper presents a brief overview of ANN applications in geotechnical engineering, briefly provides an overview of the operation of ANN modeling, investigates the current research directions of ANNs in geotechnical engineering, and discusses some ANN modeling issues that need further attention in the future, including model robustness; transparency and knowledge extraction; extrapolation; uncertainty.

  3. Neural Mechanisms Underlying Musical Pitch Perception and Clinical Applications Including Developmental Dyslexia.

    Science.gov (United States)

    Yuskaitis, Christopher J; Parviz, Mahsa; Loui, Psyche; Wan, Catherine Y; Pearl, Phillip L

    2015-08-01

    Music production and perception invoke a complex set of cognitive functions that rely on the integration of sensorimotor, cognitive, and emotional pathways. Pitch is a fundamental perceptual attribute of sound and a building block for both music and speech. Although the cerebral processing of pitch is not completely understood, recent advances in imaging and electrophysiology have provided insight into the functional and anatomical pathways of pitch processing. This review examines the current understanding of pitch processing and behavioral and neural variations that give rise to difficulties in pitch processing, and potential applications of music education for language processing disorders such as dyslexia.

  4. Neural Mechanisms Underlying Musical Pitch Perception and Clinical Applications including Developmental Dyselxia

    Science.gov (United States)

    Yuskaitis, Christopher J.; Parviz, Mahsa; Loui, Psyche; Wan, Catherine Y.; Pearl, Phillip L.

    2017-01-01

    Music production and perception invoke a complex set of cognitive functions that rely on the integration of sensory-motor, cognitive, and emotional pathways. Pitch is a fundamental perceptual attribute of sound and a building block for both music and speech. Although the cerebral processing of pitch is not completely understood, recent advances in imaging and electrophysiology have provided insight into the functional and anatomical pathways of pitch processing. This review examines the current understanding of pitch processing, behavioral and neural variations that give rise to difficulties in pitch processing, and potential applications of music education for language processing disorders such as dyslexia. PMID:26092314

  5. Radial basis function neural networks with sequential learning MRAN and its applications

    CERN Document Server

    Sundararajan, N; Wei Lu Ying

    1999-01-01

    This book presents in detail the newly developed sequential learning algorithm for radial basis function neural networks, which realizes a minimal network. This algorithm, created by the authors, is referred to as Minimal Resource Allocation Networks (MRAN). The book describes the application of MRAN in different areas, including pattern recognition, time series prediction, system identification, control, communication and signal processing. Benchmark problems from these areas have been studied, and MRAN is compared with other algorithms. In order to make the book self-contained, a review of t

  6. Application of artificial neural network with extreme learning machine for economic growth estimation

    Science.gov (United States)

    Milačić, Ljubiša; Jović, Srđan; Vujović, Tanja; Miljković, Jovica

    2017-01-01

    The purpose of this research is to develop and apply the artificial neural network (ANN) with extreme learning machine (ELM) to forecast gross domestic product (GDP) growth rate. The economic growth forecasting was analyzed based on agriculture, manufacturing, industry and services value added in GDP. The results were compared with ANN with back propagation (BP) learning approach since BP could be considered as conventional learning methodology. The reliability of the computational models was accessed based on simulation results and using several statistical indicators. Based on results, it was shown that ANN with ELM learning methodology can be applied effectively in applications of GDP forecasting.

  7. RF-MEMS for high-performance and widely reconfigurable passive components – A review with focus on future telecommunications, Internet of Things (IoT and 5G applications

    Directory of Open Access Journals (Sweden)

    Jacopo Iannacci

    2017-10-01

    This work frames the current state of RF-MEMS market exploitation, analysing the main reasons impairing in past years the proper employment of Microsystem technology based RF passive components. Moreover, highlights on further expansion of RF-MEMS solutions in mobile and telecommunication systems will be briefly provided and discussed.

  8. Microelectromechanical (MEM) thermal actuator

    Science.gov (United States)

    Garcia, Ernest J [Albuquerque, NM; Fulcher, Clay W. G. [Sandia Park, NM

    2012-07-31

    Microelectromechanical (MEM) buckling beam thermal actuators are disclosed wherein the buckling direction of a beam is constrained to a desired direction of actuation, which can be in-plane or out-of-plane with respect to a support substrate. The actuators comprise as-fabricated, linear beams of uniform cross section supported above the substrate by supports which rigidly attach a beam to the substrate. The beams can be heated by methods including the passage of an electrical current through them. The buckling direction of an initially straight beam upon heating and expansion is controlled by incorporating one or more directional constraints attached to the substrate and proximal to the mid-point of the beam. In the event that the beam initially buckles in an undesired direction, deformation of the beam induced by contact with a directional constraint generates an opposing force to re-direct the buckling beam into the desired direction. The displacement and force generated by the movement of the buckling beam can be harnessed to perform useful work, such as closing contacts in an electrical switch.

  9. Modeling nonlinearities in MEMS oscillators.

    Science.gov (United States)

    Agrawal, Deepak K; Woodhouse, Jim; Seshia, Ashwin A

    2013-08-01

    We present a mathematical model of a microelectromechanical system (MEMS) oscillator that integrates the nonlinearities of the MEMS resonator and the oscillator circuitry in a single numerical modeling environment. This is achieved by transforming the conventional nonlinear mechanical model into the electrical domain while simultaneously considering the prominent nonlinearities of the resonator. The proposed nonlinear electrical model is validated by comparing the simulated amplitude-frequency response with measurements on an open-loop electrically addressed flexural silicon MEMS resonator driven to large motional amplitudes. Next, the essential nonlinearities in the oscillator circuit are investigated and a mathematical model of a MEMS oscillator is proposed that integrates the nonlinearities of the resonator. The concept is illustrated for MEMS transimpedance-amplifier- based square-wave and sine-wave oscillators. Closed-form expressions of steady-state output power and output frequency are derived for both oscillator models and compared with experimental and simulation results, with a good match in the predicted trends in all three cases.

  10. Electrostatic MEMS devices with high reliability

    Science.gov (United States)

    Goldsmith, Charles L; Auciello, Orlando H; Sumant, Anirudha V; Mancini, Derrick C; Gudeman, Chris; Sampath, Suresh; Carlilse, John A; Carpick, Robert W; Hwang, James

    2015-02-24

    The present invention provides for an electrostatic microelectromechanical (MEMS) device comprising a dielectric layer separating a first conductor and a second conductor. The first conductor is moveable towards the second conductor, when a voltage is applied to the MEMS device. The dielectric layer recovers from dielectric charging failure almost immediately upon removal of the voltage from the MEMS device.

  11. Structured synthesis of MEMS using evolutionary approaches

    DEFF Research Database (Denmark)

    Fan, Zhun; Wang, Jiachuan; Achiche, Sofiane

    2008-01-01

    In this paper, we discuss the hierarchy that is involved in a typical MEMS design and how evolutionary approaches can be used to automate the hierarchical synthesis process for MEMS. The paper first introduces the flow of a structured MEMS design process and emphasizes that system-level lumped-pa...

  12. Neural networks, fuzzy logic and genetic algorithms: applications and possibilities in finance and accounting/ Redes neurais, logica nebulosa e algoritmos geneticos: aplicacoes e possibilidades em financas e contabilidade

    National Research Council Canada - National Science Library

    Wuerges, Artur Filipe Ewald; Borba, Jose Alonso

    2010-01-01

    .... This paper analyzes empirical works published in international journals between 2000 and 2007 that present studies about the application of Neural Networks, Fuzzy Logic and Genetic Algorithms to...

  13. Bayesian neural networks for bivariate binary data: an application to prostate cancer study.

    Science.gov (United States)

    Chakraborty, Sounak; Ghosh, Malay; Maiti, Tapabrata; Tewari, Ashutosh

    2005-12-15

    Prostate cancer is one of the most common cancers in American men. The cancer could either be locally confined, or it could spread outside the organ. When locally confined, there are several options for treating and curing this disease. Otherwise, surgery is the only option, and in extreme cases of outside spread, it could very easily recur within a short time even after surgery and subsequent radiation therapy. Hence, it is important to know, based on pre-surgery biopsy results how likely the cancer is organ-confined or not. The paper considers a hierarchical Bayesian neural network approach for posterior prediction probabilities of certain features indicative of non-organ confined prostate cancer. In particular, we find such probabilities for margin positivity (MP) and seminal vesicle (SV) positivity jointly. The available training set consists of bivariate binary outcomes indicating the presence or absence of the two. In addition, we have certain covariates such as prostate specific antigen (PSA), gleason score and the indicator for the cancer to be unilateral or bilateral (i.e. spread on one or both sides) in one data set and gene expression microarrays in another data set. We take a hierarchical Bayesian neural network approach to find the posterior prediction probabilities for a test and validation set, and compare these with the actual outcomes for the first data set. In case of the microarray data we use leave one out cross-validation to access the accuracy of our method. We also demonstrate the superiority of our method to the other competing methods through a simulation study. The Bayesian procedure is implemented by an application of the Markov chain Monte Carlo numerical integration technique. For the problem at hand, our Bayesian bivariate neural network procedure is shown to be superior to the classical neural network, Radford Neal's Bayesian neural network as well as bivariate logistic models to predict jointly the MP and SV in a patient in both the

  14. Human-Derived Neurons and Neural Progenitor Cells in High Content Imaging Applications.

    Science.gov (United States)

    Harrill, Joshua A

    2018-01-01

    Due to advances in the fields of stem cell biology and cellular engineering, a variety of commercially available human-derived neurons and neural progenitor cells (NPCs) are now available for use in research applications, including small molecule efficacy or toxicity screening. The use of human-derived neural cells is anticipated to address some of the uncertainties associated with the use of nonhuman culture models or transformed cell lines derived from human tissues. Many of the human-derived neurons and NPCs currently available from commercial sources recapitulate critical process of nervous system development including NPC proliferation, neurite outgrowth, synaptogenesis, and calcium signaling, each of which can be evaluated using high content image analysis (HCA). Human-derived neurons and NPCs are also amenable to culture in multiwell plate formats and thus may be adapted for use in HCA-based screening applications. This article reviews various types of HCA-based assays that have been used in conjunction with human-derived neurons and NPC cultures. This article also highlights instances where lower throughput analysis of neurodevelopmental processes has been performed and which demonstrate a potential for adaptation to higher-throughout imaging methods. Finally, a generic protocol for evaluating neurite outgrowth in human-derived neurons using a combination of immunocytochemistry and HCA is presented. The information provided in this article is intended to serve as a resource for cell model and assay selection for those interested in evaluating neurodevelopmental processes in human-derived cells.

  15. Neural prostheses in clinical applications--trends from precision mechanics towards biomedical microsystems in neurological rehabilitation.

    Science.gov (United States)

    Stieglitz, T; Schuettler, M; Koch, K P

    2004-04-01

    Neural prostheses partially restore body functions by technical nerve excitation after trauma or neurological diseases. External devices and implants have been developed since the early 1960s for many applications. Several systems have reached nowadays clinical practice: Cochlea implants help the deaf to hear, micturition is induced by bladder stimulators in paralyzed persons and deep brain stimulation helps patients with Parkinson's disease to participate in daily life again. So far, clinical neural prostheses are fabricated with means of precision mechanics. Since microsystem technology opens the opportunity to design and develop complex systems with a high number of electrodes to interface with the nervous systems, the opportunity for selective stimulation and complex implant scenarios seems to be feasible in the near future. The potentials and limitations with regard to biomedical microdevices are introduced and discussed in this paper. Target specifications are derived from existing implants and are discussed on selected applications that has been investigated in experimental research: a micromachined implant to interface a nerve stump with a sieve electrode, cuff electrodes with integrated electronics, and an epiretinal vision prosthesis.

  16. A hybrid neural network structure for application to nondestructive TRU waste assay

    Energy Technology Data Exchange (ETDEWEB)

    Becker, G. [Idaho National Engineering Lab., Idaho Falls, ID (United States)

    1995-12-31

    The determination of transuranic (TRU) and associated radioactive material quantities entrained in waste forms is a necessary component. of waste characterization. Measurement performance requirements are specified in the National TRU Waste Characterization Program quality assurance plan for which compliance must be demonstrated prior to the transportation and disposition of wastes. With respect to this criterion, the existing TRU nondestructive waste assay (NDA) capability is inadequate for a significant fraction of the US Department of Energy (DOE) complex waste inventory. This is a result of the general application of safeguard-type measurement and calibration schemes to waste form configurations. Incompatibilities between such measurement methods and actual waste form configurations complicate regulation compliance demonstration processes and illustrate the need for an alternate measurement interpretation paradigm. Hence, it appears necessary to supplement or perhaps restructure the perceived solution and approach to the waste NDA problem. The first step is to understand the magnitude of the waste matrix/source attribute space associated with those waste form configurations in inventory and how this creates complexities and unknowns with respect to existing NDA methods. Once defined and/or bounded, a conceptual method must be developed that specifies the necessary tools and the framework in which the tools are used. A promising framework is a hybridized neural network structure. Discussed are some typical complications associated with conventional waste NDA techniques and how improvements can be obtained through the application of neural networks.

  17. Surface engineering for MEMS reliability

    Science.gov (United States)

    Ashurst, William Robert

    The integration of miniaturized mechanical components with microelectronic components has spawned a new technology known as microelectromechanical systems (MEMS). This technology extends the benefits of microelectronic fabrication to sensing and actuating functions. Examples of MEMS devices that have been commercially produced include relatively simple mechanisms such as accelerometers, pressure sensors and digital mirror projectors. Despite recent progress in micromachining capability, the realization of more complex commercial and specialized use of MEMS is challenged due to plaguing reliability issues. Barriers to the widespread commercialization and development of MEMS technologies are steep and require engineering at the molecular level. Reliability issues which commonly limit MEMS to the research level include (but are not limited to) adhesion (also referred to as "stiction") and wear. The goal of this work is to improve MEMS reliability by developing new processes and techniques that allow the study of adhesion and wear, that are industrially favorable and that are process compatible with MEMS fabrication schemes. A "tribology chip" has been developed which employs a variety of standard micromechanical test instruments as well as new devices. Also, a liquid based anti-adhesion coating process for MEMS which utilizes non-chlorosilane chemistry is developed. This octadecene based coating process is simpler than the standard chlorosilane processes, and circumvents a number of limitations imposed by chlorosilane chemistry. In order to provide a manufacturable anti-adhesion process, a new vapor phase coating method has been developed. This method is based on chlorosilane chemistry, specifically dichlorodimethylsilane, and has been shown to be effective at reducing adhesion in fully packaged devices at the wafer scale. To address the issue of wear, novel methods of producing films of silicon carbide as coatings for existing polysilicon micromachines have been

  18. Prospects of application of artificial neural networks for forecasting of cargo transportation volume in transport systems

    Directory of Open Access Journals (Sweden)

    D. T. Yakupov

    2017-01-01

    Full Text Available The purpose of research – to identify the prospects for the use of neural network approach in relation to the tasks of economic forecasting of logistics performance, in particular of volume freight traffic in the transport system promiscuous regional freight traffic, as well as to substantiate the effectiveness of the use of artificial neural networks (ANN, as compared with the efficiency of traditional extrapolative methods of forecasting. The authors consider the possibility of forecasting to use ANN for these economic indicators not as an alternative to the traditional methods of statistical forecasting, but as one of the available simple means for solving complex problems.Materials and methods. When predicting the ANN, three methods of learning were used: 1 the Levenberg-Marquardt algorithm-network training stops when the generalization ceases to improve, which is shown by the increase in the mean square error of the output value; 2 Bayes regularization method - network training is stopped in accordance with the minimization of adaptive weights; 3 the method of scaled conjugate gradients, which is used to find the local extremum of a function on the basis of information about its values and gradient. The Neural Network Toolbox package is used for forecasting. The neural network model consists of a hidden layer of neurons with a sigmoidal activation function and an output neuron with a linear activation function, the input values of the dynamic time series, and the predicted value is removed from the output. For a more objective assessment of the prospects of the ANN application, the results of the forecast are presented in comparison with the results obtained in predicting the method of exponential smoothing.Results. When predicting the volumes of freight transportation by rail, satisfactory indicators of the verification of forecasting by both the method of exponential smoothing and ANN had been obtained, although the neural network

  19. MEMS linear and nonlinear statics and dynamics

    CERN Document Server

    Younis, Mohammad I

    2011-01-01

    MEMS Linear and Nonlinear Statics and Dynamics presents the necessary analytical and computational tools for MEMS designers to model and simulate most known MEMS devices, structures, and phenomena. This book also provides an in-depth analysis and treatment of the most common static and dynamic phenomena in MEMS that are encountered by engineers. Coverage also includes nonlinear modeling approaches to modeling various MEMS phenomena of a nonlinear nature, such as those due to electrostatic forces, squeeze-film damping, and large deflection of structures. The book also: Includes examples of nume

  20. Engineering applications of fpgas chaotic systems, artificial neural networks, random number generators, and secure communication systems

    CERN Document Server

    Tlelo-Cuautle, Esteban; de la Fraga, Luis Gerardo

    2016-01-01

    This book offers readers a clear guide to implementing engineering applications with FPGAs, from the mathematical description to the hardware synthesis, including discussion of VHDL programming and co-simulation issues. Coverage includes FPGA realizations such as: chaos generators that are described from their mathematical models; artificial neural networks (ANNs) to predict chaotic time series, for which a discussion of different ANN topologies is included, with different learning techniques and activation functions; random number generators (RNGs) that are realized using different chaos generators, and discussions of their maximum Lyapunov exponent values and entropies. Finally, optimized chaotic oscillators are synchronized and realized to implement a secure communication system that processes black and white and grey-scale images. In each application, readers will find VHDL programming guidelines and computer arithmetic issues, along with co-simulation examples with Active-HDL and Simulink. Readers will b...

  1. Application of Electrospun Nanofibrous PHBV Scaffold in Neural Graft and Regeneration: A Mini-Review

    Directory of Open Access Journals (Sweden)

    Ali Gheibi

    2016-10-01

    Full Text Available Among the synthetic polymers, poly (3-hydroxybutyrate-co-3-hydroxyvalerate (PHBV microbial polyester is one of the biocompatible and biodegradable copolymers in the nanomedicine scope. PHBV has key points and suitable properties to support cellular adhesion, proliferation and differentiation of nanofibers. Nanofibers are noticeably employed in order to enhance the performance of biomaterials, and could be effectively considered in this scope. Electrospinning is one of the well-known and practical methods that extremely employed in the construction of nanofibrous scaffolds for biomedical application and recently PHBV has exploited in nerve graft and regenerative medicine. PHBV composites nanofibrous scaffolds are able to be applied as promising materials in many fields, such as; wound healing and dressing, tissue engineering, targeted drug delivery systems, functional carries, biosensors or nano-biosensors and so on. In this mini-review, we attempt to provide a more detailed overview of the recent advances of PHBV electrospun nanofibers application in neural graft and regeneration.

  2. "Mem's the Word": Examining the Writing of Mem Fox.

    Science.gov (United States)

    Gilles, Carol

    2000-01-01

    Focuses on the work of Mem Fox. Explores Fox's life in order to better understand her work; examines books she has written for teachers and for parents; and reviews her children's books, emphasizing children's and teachers comments. Looks at best-loved books, bedtime books, predictable books for early readers, books that play with language, and…

  3. Of light, of MEMS: Optical MEMS in telecommunications and beyond

    Indian Academy of Sciences (India)

    The burst of the Internet bubble in 2000 has severely quenched the pace of development in the optical MEMS ... products and services resulted in the burst of what was called the Internet bubble. Many com- ... The use of external cavity laser for precise displacement measurement has a long history. (Mileset al1983; Lang ...

  4. Development of an SU-8 MEMS process with two metal electrodes using amorphous silicon as a sacrificial material

    KAUST Repository

    Ramadan, Khaled S.

    2013-02-08

    This work presents an SU-8 surface micromachining process using amorphous silicon as a sacrificial material, which also incorporates two metal layers for electrical excitation. SU-8 is a photo-patternable polymer that is used as a structural layer for MEMS and microfluidic applications due to its mechanical properties, biocompatibility and low cost. Amorphous silicon is used as a sacrificial layer in MEMS applications because it can be deposited in large thicknesses, and can be released in a dry method using XeF2, which alleviates release-based stiction problems related to MEMS applications. In this work, an SU-8 MEMS process was developed using ;-Si as a sacrificial layer. Two conductive metal electrodes were integrated in this process to allow out-of-plane electrostatic actuation for applications like MEMS switches and variable capacitors. In order to facilitate more flexibility for MEMS designers, the process can fabricate dimples that can be conductive or nonconductive. Additionally, this SU-8 process can fabricate SU-8 MEMS structures of a single layer of two different thicknesses. Process parameters were optimized for two sets of thicknesses: thin (5-10 m) and thick (130 m). The process was tested fabricating MEMS switches, capacitors and thermal actuators. © 2013 IOP Publishing Ltd.

  5. Compact MEMS-driven pyramidal polygon reflector for circumferential scanned endoscopic imaging probe.

    Science.gov (United States)

    Mu, Xiaojing; Zhou, Guangya; Yu, Hongbin; Du, Yu; Feng, Hanhua; Tsai, Julius Ming Lin; Chau, Fook Siong

    2012-03-12

    A novel prototype of an electrothermal chevron-beam actuator based microelectromechanical systems (MEMS) platform has been successfully developed for circumferential scan. Microassembly technology is utilized to construct this platform, which consists of a MEMS chevron-beam type microactuator and a micro-reflector. The proposed electrothermal microactuators with a two-stage electrothermal cascaded chevron-beam driving mechanism provide displacement amplification, thus enabling a highly reflective micro-pyramidal polygon reflector to rotate a large angle for light beam scanning. This MEMS platform is ultra-compact, supports circumferential imaging capability and is suitable for endoscopic optical coherence tomography (EOCT) applications, for example, for intravascular cancer detection.

  6. Additive direct-write microfabrication for MEMS: A review

    Science.gov (United States)

    Teh, Kwok Siong

    2017-12-01

    manufacturing technologies, it is possible to fabricate unsophisticated micrometer scale structures at adequate resolutions and precisions using materials that range from polymers, metals, ceramics, to composites. In both academia and industry, direct-write additive manufacturing offers extraordinary promises to revolutionize research and development in microfabrication and MEMS technologies. Importantly, direct-write additive manufacturing could appreciably augment current MEMS fabrication technologies, enable faster design-to-product cycle, empower new paradigms in MEMS designs, and critically, encourage wider participation in MEMS research at institutions or for individuals with limited or no access to cleanroom facilities. This article aims to provide a limited review of the current landscape of direct-write additive manufacturing techniques that are potentially applicable for MEMS microfabrication.

  7. Additive direct-write microfabrication for MEMS: A review

    Science.gov (United States)

    Teh, Kwok Siong

    2017-10-01

    manufacturing technologies, it is possible to fabricate unsophisticated micrometer scale structures at adequate resolutions and precisions using materials that range from polymers, metals, ceramics, to composites. In both academia and industry, direct-write additive manufacturing offers extraordinary promises to revolutionize research and development in microfabrication and MEMS technologies. Importantly, direct-write additive manufacturing could appreciably augment current MEMS fabrication technologies, enable faster design-to-product cycle, empower new paradigms in MEMS designs, and critically, encourage wider participation in MEMS research at institutions or for individuals with limited or no access to cleanroom facilities. This article aims to provide a limited review of the current landscape of direct-write additive manufacturing techniques that are potentially applicable for MEMS microfabrication.

  8. Miniaturized Rotary Actuators Using Shape Memory Alloy for Insect-Type MEMS Microrobot

    Directory of Open Access Journals (Sweden)

    Ken Saito

    2016-03-01

    Full Text Available Although several types of locomotive microrobots have been developed, most of them have difficulty locomoting on uneven surfaces. Thus, we have been focused on microrobots that can locomote using step patterns. We are studying insect-type microrobot systems. The locomotion of the microrobot is generated by rotational movements of the shape memory alloy-type rotary actuator. In addition, we have constructed artificial neural networks by using analog integrated circuit (IC technology. The artificial neural networks can output the driving waveform without using software programs. The shape memory alloy-type rotary actuator and the artificial neural networks are constructed with silicon wafers; they can be integrated by using micro-electromechanical system (MEMS technology. As a result, the MEMS microrobot system can locomote using step patterns. The insect-type MEMS microrobot system is 0.079 g in weight and less than 5.0 mm in size, and its locomotion speed is 2 mm/min. The locomotion speed is slow because the heat of the shape memory alloy conducts to the mechanical parts of the MEMS microrobot. In this paper, we discuss a new rotary actuator compared with the previous model and show the continuous rotation of the proposed rotary actuator.

  9. Refining mass formulas for astrophysical applications: A Bayesian neural network approach

    Science.gov (United States)

    Utama, R.; Piekarewicz, J.

    2017-10-01

    Background: Exotic nuclei, particularly those near the drip lines, are at the core of one of the fundamental questions driving nuclear structure and astrophysics today: What are the limits of nuclear binding? Exotic nuclei play a critical role in both informing theoretical models as well as in our understanding of the origin of the heavy elements. Purpose: Our aim is to refine existing mass models through the training of an artificial neural network that will mitigate the large model discrepancies far away from stability. Methods: The basic paradigm of our two-pronged approach is an existing mass model that captures as much as possible of the underlying physics followed by the implementation of a Bayesian neural network (BNN) refinement to account for the missing physics. Bayesian inference is employed to determine the parameters of the neural network so that model predictions may be accompanied by theoretical uncertainties. Results: Despite the undeniable quality of the mass models adopted in this work, we observe a significant improvement (of about 40%) after the BNN refinement is implemented. Indeed, in the specific case of the Duflo-Zuker mass formula, we find that the rms deviation relative to experiment is reduced from σrms=0.503 MeV to σrms=0.286 MeV. These newly refined mass tables are used to map the neutron drip lines (or rather "drip bands") and to study a few critical r -process nuclei. Conclusions: The BNN approach is highly successful in refining the predictions of existing mass models. In particular, the large discrepancy displayed by the original "bare" models in regions where experimental data are unavailable is considerably quenched after the BNN refinement. This lends credence to our approach and has motivated us to publish refined mass tables that we trust will be helpful for future astrophysical applications.

  10. MEMS AO for Planet Finding

    Science.gov (United States)

    Rao, Shanti; Wallace, J. Kent; Shao, Mike; Schmidtlin, Edouard; Levine, B. Martin; Samuele, Rocco; Lane, Benjamin; Chakrabarti, Supriya; Cook, Timothy; Hicks, Brian; hide

    2008-01-01

    This slide presentation reviews a method for planet finding using microelectromechanical systems (MEMS) Adaptive Optics (AO). The use of a deformable mirror (DM) is described as a part of the instrument that was designed with a nulling interferometer. The strategy that is used is described in detail.

  11. Photonic MEMS for NIR in-situ

    Energy Technology Data Exchange (ETDEWEB)

    Bond, T C; Cole, G D; Goddard, L L; Behymer, E

    2007-07-03

    We report on a novel sensing technique combining photonics and microelectromechanical systems (MEMS) for the detection and monitoring of gas emissions for critical environmental, medical, and industrial applications. We discuss how MEMS-tunable vertical-cavity surface-emitting lasers (VCSELs) can be exploited for in-situ detection and NIR spectroscopy of several gases, such as O{sub 2}, N{sub 2}O, CO{sub x}, CH{sub 4}, HF, HCl, etc., with estimated sensitivities between 0.1 and 20 ppm on footprints {approx}10{sup -3} mm{sup 3}. The VCSELs can be electrostatically tuned with a continuous wavelength shift up to 20 nm, allowing for unambiguous NIR signature determination. Selective concentration analysis in heterogeneous gas compositions is enabled, thus paving the way to an integrated optical platform for multiplexed gas identification by bandgap and device engineering. We will discuss here, in particular, our efforts on the development of a 760 nm AlGaAs based tunable VCSEL for O{sub 2} detection.

  12. Piezoelectric Zinc Oxide Based MEMS Acoustic Sensor

    Directory of Open Access Journals (Sweden)

    Aarti Arora

    2008-04-01

    Full Text Available An acoustic sensors exhibiting good sensitivity was fabricated using MEMS technology having piezoelectric zinc oxide as a dielectric between two plates of capacitor. Thin film zinc oxide has structural, piezoelectric and optical properties for surface acoustic wave (SAW and bulk acoustic wave (BAW devices. Oxygen effficient films are transparent and insulating having wide applications for sensors and transducers. A rf sputtered piezoelectric ZnO layer transforms the mechanical deflection of a thin etched silicon diaphragm into a piezoelectric charge. For 25-micron thin diaphragm Si was etched in tetramethylammonium hydroxide solution using bulk micromachining. This was followed by deposition of sandwiched structure composed of bottom aluminum electrode, sputtered 3 micron ZnO film and top aluminum electrode. A glass having 1 mm diameter hole was bonded on backside of device to compensate sound pressure in side the cavity. The measured value of central capacitance and dissipation factor of the fabricated MEMS acoustic sensor was found to be 82.4pF and 0.115 respectively, where as the value of ~176 pF was obtained for the rim capacitance with a dissipation factor of 0.138. The response of the acoustic sensors was reproducible for the devices prepared under similar processing conditions under different batches. The acoustic sensor was found to be working from 30Hz to 8KHz with a sensitivity of 139µV/Pa under varying acoustic pressure.

  13. Application of Levenberg-Marquardt Optimization Algorithm Based Multilayer Neural Networks for Hydrological Time Series Modeling

    Directory of Open Access Journals (Sweden)

    Umut Okkan

    2011-07-01

    Full Text Available Recently, Artificial Neural Networks (ANN, which is mathematical modelingtools inspired by the properties of the biological neural system, has been typically used inthe studies of hydrological time series modeling. These modeling studies generally includethe standart feed forward backpropagation (FFBP algorithms such as gradient-descent,gradient-descent with momentum rate and, conjugate gradient etc. As the standart FFBPalgorithms have some disadvantages relating to the time requirement and slowconvergency in training, Newton and Levenberg-Marquardt algorithms, which arealternative approaches to standart FFBP algorithms, were improved and also used in theapplications. In this study, an application of Levenberg-Marquardt algorithm based ANN(LM-ANN for the modeling of monthly inflows of Demirkopru Dam, which is located inthe Gediz basin, was presented. The LM-ANN results were also compared with gradientdescentwith momentum rate algorithm based FFBP model (GDM-ANN. When thestatistics of the long-term and also seasonal-term outputs are compared, it can be seen thatthe LM-ANN model that has been developed, is more sensitive for prediction of theinflows. In addition, LM-ANN approach can be used for modeling of other hydrologicalcomponents in terms of a rapid assessment and its robustness.

  14. An Inverse Neural Controller Based on the Applicability Domain of RBF Network Models

    Directory of Open Access Journals (Sweden)

    Alex Alexandridis

    2018-01-01

    Full Text Available This paper presents a novel methodology of generic nature for controlling nonlinear systems, using inverse radial basis function neural network models, which may combine diverse data originating from various sources. The algorithm starts by applying the particle swarm optimization-based non-symmetric variant of the fuzzy means (PSO-NSFM algorithm so that an approximation of the inverse system dynamics is obtained. PSO-NSFM offers models of high accuracy combined with small network structures. Next, the applicability domain concept is suitably tailored and embedded into the proposed control structure in order to ensure that extrapolation is avoided in the controller predictions. Finally, an error correction term, estimating the error produced by the unmodeled dynamics and/or unmeasured external disturbances, is included to the control scheme to increase robustness. The resulting controller guarantees bounded input-bounded state (BIBS stability for the closed loop system when the open loop system is BIBS stable. The proposed methodology is evaluated on two different control problems, namely, the control of an experimental armature-controlled direct current (DC motor and the stabilization of a highly nonlinear simulated inverted pendulum. For each one of these problems, appropriate case studies are tested, in which a conventional neural controller employing inverse models and a PID controller are also applied. The results reveal the ability of the proposed control scheme to handle and manipulate diverse data through a data fusion approach and illustrate the superiority of the method in terms of faster and less oscillatory responses.

  15. A Novel Chaotic Neural Network Using Memristive Synapse with Applications in Associative Memory

    Directory of Open Access Journals (Sweden)

    Xiaofang Hu

    2012-01-01

    Full Text Available Chaotic Neural Network, also denoted by the acronym CNN, has rich dynamical behaviors that can be harnessed in promising engineering applications. However, due to its complex synapse learning rules and network structure, it is difficult to update its synaptic weights quickly and implement its large scale physical circuit. This paper addresses an implementation scheme of a novel CNN with memristive neural synapses that may provide a feasible solution for further development of CNN. Memristor, widely known as the fourth fundamental circuit element, was theoretically predicted by Chua in 1971 and has been developed in 2008 by the researchers in Hewlett-Packard Laboratory. Memristor based hybrid nanoscale CMOS technology is expected to revolutionize the digital and neuromorphic computation. The proposed memristive CNN has four significant features: (1 nanoscale memristors can simplify the synaptic circuit greatly and enable the synaptic weights update easily; (2 it can separate stored patterns from superimposed input; (3 it can deal with one-to-many associative memory; (4 it can deal with many-to-many associative memory. Simulation results are provided to illustrate the effectiveness of the proposed scheme.

  16. Efficient Simulation of Wing Modal Response: Application of 2nd Order Shape Sensitivities and Neural Networks

    Science.gov (United States)

    Kapania, Rakesh K.; Liu, Youhua

    2000-01-01

    At the preliminary design stage of a wing structure, an efficient simulation, one needing little computation but yielding adequately accurate results for various response quantities, is essential in the search of optimal design in a vast design space. In the present paper, methods of using sensitivities up to 2nd order, and direct application of neural networks are explored. The example problem is how to decide the natural frequencies of a wing given the shape variables of the structure. It is shown that when sensitivities cannot be obtained analytically, the finite difference approach is usually more reliable than a semi-analytical approach provided an appropriate step size is used. The use of second order sensitivities is proved of being able to yield much better results than the case where only the first order sensitivities are used. When neural networks are trained to relate the wing natural frequencies to the shape variables, a negligible computation effort is needed to accurately determine the natural frequencies of a new design.

  17. Artificial neural networks: Principle and application to model based control of drying systems -- A review

    Energy Technology Data Exchange (ETDEWEB)

    Thyagarajan, T.; Ponnavaikko, M. [Crescent Engineering Coll., Madras (India); Shanmugam, J. [Madras Inst. of Tech. (India); Panda, R.C.; Rao, P.G. [Central Leather Research Inst., Madras (India)

    1998-07-01

    This paper reviews the developments in the model based control of drying systems using Artificial Neural Networks (ANNs). Survey of current research works reveals the growing interest in the application of ANN in modeling and control of non-linear, dynamic and time-variant systems. Over 115 articles published in this area are reviewed. All landmark papers are systematically classified in chronological order, in three distinct categories; namely, conventional feedback controllers, model based controllers using conventional methods and model based controllers using ANN for drying process. The principles of ANN are presented in detail. The problems and issues of the drying system and the features of various ANN models are dealt with up-to-date. ANN based controllers lead to smoother controller outputs, which would increase actuator life. The paper concludes with suggestions for improving the existing modeling techniques as applied to predicting the performance characteristics of dryers. The hybridization techniques, namely, neural with fuzzy logic and genetic algorithms, presented, provide, directions for pursuing further research for the implementation of appropriate control strategies. The authors opine that the information presented here would be highly beneficial for pursuing research in modeling and control of drying process using ANN. 118 refs.

  18. Extruded Bread Classification on the Basis of Acoustic Emission Signal With Application of Artificial Neural Networks

    Science.gov (United States)

    Świetlicka, Izabela; Muszyński, Siemowit; Marzec, Agata

    2015-04-01

    The presented work covers the problem of developing a method of extruded bread classification with the application of artificial neural networks. Extruded flat graham, corn, and rye breads differening in water activity were used. The breads were subjected to the compression test with simultaneous registration of acoustic signal. The amplitude-time records were analyzed both in time and frequency domains. Acoustic emission signal parameters: single energy, counts, amplitude, and duration acoustic emission were determined for the breads in four water activities: initial (0.362 for rye, 0.377 for corn, and 0.371 for graham bread), 0.432, 0.529, and 0.648. For classification and the clustering process, radial basis function, and self-organizing maps (Kohonen network) were used. Artificial neural networks were examined with respect to their ability to classify or to cluster samples according to the bread type, water activity value, and both of them. The best examination results were achieved by the radial basis function network in classification according to water activity (88%), while the self-organizing maps network yielded 81% during bread type clustering.

  19. Applications of Artificial Neural Networks in Structural Engineering with Emphasis on Continuum Models

    Science.gov (United States)

    Kapania, Rakesh K.; Liu, Youhua

    1998-01-01

    The use of continuum models for the analysis of discrete built-up complex aerospace structures is an attractive idea especially at the conceptual and preliminary design stages. But the diversity of available continuum models and hard-to-use qualities of these models have prevented them from finding wide applications. In this regard, Artificial Neural Networks (ANN or NN) may have a great potential as these networks are universal approximators that can realize any continuous mapping, and can provide general mechanisms for building models from data whose input-output relationship can be highly nonlinear. The ultimate aim of the present work is to be able to build high fidelity continuum models for complex aerospace structures using the ANN. As a first step, the concepts and features of ANN are familiarized through the MATLAB NN Toolbox by simulating some representative mapping examples, including some problems in structural engineering. Then some further aspects and lessons learned about the NN training are discussed, including the performances of Feed-Forward and Radial Basis Function NN when dealing with noise-polluted data and the technique of cross-validation. Finally, as an example of using NN in continuum models, a lattice structure with repeating cells is represented by a continuum beam whose properties are provided by neural networks.

  20. Quality-on-Demand Compression of EEG Signals for Telemedicine Applications Using Neural Network Predictors

    Directory of Open Access Journals (Sweden)

    N. Sriraam

    2011-01-01

    Full Text Available A telemedicine system using communication and information technology to deliver medical signals such as ECG, EEG for long distance medical services has become reality. In either the urgent treatment or ordinary healthcare, it is necessary to compress these signals for the efficient use of bandwidth. This paper discusses a quality on demand compression of EEG signals using neural network predictors for telemedicine applications. The objective is to obtain a greater compression gains at a low bit rate while preserving the clinical information content. A two-stage compression scheme with a predictor and an entropy encoder is used. The residue signals obtained after prediction is first thresholded using various levels of thresholds and are further quantized and then encoded using an arithmetic encoder. Three neural network models, single-layer and multi-layer perceptrons and Elman network are used and the results are compared with linear predictors such as FIR filters and AR modeling. The fidelity of the reconstructed EEG signal is assessed quantitatively using parameters such as PRD, SNR, cross correlation and power spectral density. It is found from the results that the quality of the reconstructed signal is preserved at a low PRD thereby yielding better compression results compared to results obtained using lossless scheme.

  1. Quality-on-Demand Compression of EEG Signals for Telemedicine Applications Using Neural Network Predictors.

    Science.gov (United States)

    Sriraam, N

    2011-01-01

    A telemedicine system using communication and information technology to deliver medical signals such as ECG, EEG for long distance medical services has become reality. In either the urgent treatment or ordinary healthcare, it is necessary to compress these signals for the efficient use of bandwidth. This paper discusses a quality on demand compression of EEG signals using neural network predictors for telemedicine applications. The objective is to obtain a greater compression gains at a low bit rate while preserving the clinical information content. A two-stage compression scheme with a predictor and an entropy encoder is used. The residue signals obtained after prediction is first thresholded using various levels of thresholds and are further quantized and then encoded using an arithmetic encoder. Three neural network models, single-layer and multi-layer perceptrons and Elman network are used and the results are compared with linear predictors such as FIR filters and AR modeling. The fidelity of the reconstructed EEG signal is assessed quantitatively using parameters such as PRD, SNR, cross correlation and power spectral density. It is found from the results that the quality of the reconstructed signal is preserved at a low PRD thereby yielding better compression results compared to results obtained using lossless scheme.

  2. Optogenetic stimulation of multiwell MEA plates for neural and cardiac applications

    Science.gov (United States)

    Clements, Isaac P.; Millard, Daniel C.; Nicolini, Anthony M.; Preyer, Amanda J.; Grier, Robert; Heckerling, Andrew; Blum, Richard A.; Tyler, Phillip; McSweeney, K. M.; Lu, Yi-Fan; Hall, Diana; Ross, James D.

    2016-03-01

    Microelectrode array (MEA) technology enables advanced drug screening and "disease-in-a-dish" modeling by measuring the electrical activity of cultured networks of neural or cardiac cells. Recent developments in human stem cell technologies, advancements in genetic models, and regulatory initiatives for drug screening have increased the demand for MEA-based assays. In response, Axion Biosystems previously developed a multiwell MEA platform, providing up to 96 MEA culture wells arrayed into a standard microplate format. Multiwell MEA-based assays would be further enhanced by optogenetic stimulation, which enables selective excitation and inhibition of targeted cell types. This capability for selective control over cell culture states would allow finer pacing and probing of cell networks for more reliable and complete characterization of complex network dynamics. Here we describe a system for independent optogenetic stimulation of each well of a 48-well MEA plate. The system enables finely graded control of light delivery during simultaneous recording of network activity in each well. Using human induced pluripotent stem cell (hiPSC) derived cardiomyocytes and rodent primary neuronal cultures, we demonstrate high channel-count light-based excitation and suppression in several proof-of-concept experimental models. Our findings demonstrate advantages of combining multiwell optical stimulation and MEA recording for applications including cardiac safety screening, neural toxicity assessment, and advanced characterization of complex neuronal diseases.

  3. Feasibility of Frequency-Modulated Wireless Transmission for a Multi-Purpose MEMS-Based Accelerometer

    Directory of Open Access Journals (Sweden)

    Alessandro Sabato

    2014-09-01

    Full Text Available Recent advances in the Micro Electro-Mechanical System (MEMS technology have made wireless MEMS accelerometers an attractive tool for Structural Health Monitoring (SHM of civil engineering structures. To date, sensors’ low sensitivity and accuracy—especially at very low frequencies—have imposed serious limitations for their application in monitoring large-sized structures. Conventionally, the MEMS sensor’s analog signals are converted to digital signals before radio-frequency (RF wireless transmission. The conversion can cause a low sensitivity to the important low-frequency and low-amplitude signals. To overcome this difficulty, the authors have developed a MEMS accelerometer system, which converts the sensor output voltage to a frequency-modulated signal before RF transmission. This is achieved by using a Voltage to Frequency Conversion (V/F instead of the conventional Analog to Digital Conversion (ADC. In this paper, a prototype MEMS accelerometer system is presented, which consists of a transmitter and receiver circuit boards. The former is equipped with a MEMS accelerometer, a V/F converter and a wireless RF transmitter, while the latter contains an RF receiver and a F/V converter for demodulating the signal. The efficacy of the MEMS accelerometer system in measuring low-frequency and low-amplitude dynamic responses is demonstrated through extensive laboratory tests and experiments on a flow-loop pipeline.

  4. Feasibility of frequency-modulated wireless transmission for a multi-purpose MEMS-based accelerometer.

    Science.gov (United States)

    Sabato, Alessandro; Feng, Maria Q

    2014-09-05

    Recent advances in the Micro Electro-Mechanical System (MEMS) technology have made wireless MEMS accelerometers an attractive tool for Structural Health Monitoring (SHM) of civil engineering structures. To date, sensors' low sensitivity and accuracy--especially at very low frequencies--have imposed serious limitations for their application in monitoring large-sized structures. Conventionally, the MEMS sensor's analog signals are converted to digital signals before radio-frequency (RF) wireless transmission. The conversion can cause a low sensitivity to the important low-frequency and low-amplitude signals. To overcome this difficulty, the authors have developed a MEMS accelerometer system, which converts the sensor output voltage to a frequency-modulated signal before RF transmission. This is achieved by using a Voltage to Frequency Conversion (V/F) instead of the conventional Analog to Digital Conversion (ADC). In this paper, a prototype MEMS accelerometer system is presented, which consists of a transmitter and receiver circuit boards. The former is equipped with a MEMS accelerometer, a V/F converter and a wireless RF transmitter, while the latter contains an RF receiver and a F/V converter for demodulating the signal. The efficacy of the MEMS accelerometer system in measuring low-frequency and low-amplitude dynamic responses is demonstrated through extensive laboratory tests and experiments on a flow-loop pipeline.

  5. Feasibility of Frequency-Modulated Wireless Transmission for a Multi-Purpose MEMS-Based Accelerometer

    Science.gov (United States)

    Sabato, Alessandro; Feng, Maria Q.

    2014-01-01

    Recent advances in the Micro Electro-Mechanical System (MEMS) technology have made wireless MEMS accelerometers an attractive tool for Structural Health Monitoring (SHM) of civil engineering structures. To date, sensors' low sensitivity and accuracy—especially at very low frequencies—have imposed serious limitations for their application in monitoring large-sized structures. Conventionally, the MEMS sensor's analog signals are converted to digital signals before radio-frequency (RF) wireless transmission. The conversion can cause a low sensitivity to the important low-frequency and low-amplitude signals. To overcome this difficulty, the authors have developed a MEMS accelerometer system, which converts the sensor output voltage to a frequency-modulated signal before RF transmission. This is achieved by using a Voltage to Frequency Conversion (V/F) instead of the conventional Analog to Digital Conversion (ADC). In this paper, a prototype MEMS accelerometer system is presented, which consists of a transmitter and receiver circuit boards. The former is equipped with a MEMS accelerometer, a V/F converter and a wireless RF transmitter, while the latter contains an RF receiver and a F/V converter for demodulating the signal. The efficacy of the MEMS accelerometer system in measuring low-frequency and low-amplitude dynamic responses is demonstrated through extensive laboratory tests and experiments on a flow-loop pipeline. PMID:25198003

  6. Synthesis of KCa₂Nb₃O₁₀ Crystals with Varying Grain Sizes and Their Nanosheet Monolayer Films As Seed Layers for PiezoMEMS Applications.

    Science.gov (United States)

    Yuan, Huiyu; Nguyen, Minh; Hammer, Tom; Koster, Gertjan; Rijnders, Guus; ten Elshof, Johan E

    2015-12-16

    The layered perovskite-type niobate KCa2Nb3O10 and its derivatives show advantages in several fields, such as templated film growth and (photo)catalysis. Conventional synthesis routes generally yield crystal size smaller than 2 μm. We report a flux synthesis method to obtain KCa2Nb3O10 crystals with significantly larger sizes. By using different flux materials (K2SO4 and K2MoO4), crystals with average sizes of 8 and 20 μm, respectively, were obtained. The KCa2Nb3O10 crystals from K2SO4 and K2MoO4 assisted synthesis were protonated and exfoliated into monolayer nanosheets, and the optimal exfoliation conditions were determined. Using pulsed laser deposition, highly (001)-oriented piezoelectric stacks (SrRuO3/PbZr0.52Ti0.48O3/SrRuO3, SRO/PZT/SRO) were deposited onto Langmuir-Blodgett films of Ca2Nb3O10(-) (CNO) nanosheets with varying lateral nanosheet sizes on Si substrates. The resulting PZT thin films showed high crystallinity irrespective of nanosheet size. The small sized nanosheets yielded a high longitudinal piezoelectric coefficient d33 of 100 pm/V, while the larger sized sheets had a d33 of 72 pm/V. An enhanced transverse piezoelectric coefficient d31 of -107 pm/V, an important input parameter for the actuation of active structures in microelectromechanical systems (MEMS) devices, was obtained for PZT films grown on CNO nanosheets with large lateral size, while the corresponding value on small sized sheets was -96 pm/V.

  7. Noise Reduction for a MEMS-Gyroscope-Based Head Mouse.

    Science.gov (United States)

    Du, Jiaying; Gerdtman, Christer; Lindén, Maria

    2015-01-01

    In this paper, four different signal processing algorithms which can be applied to reduce the noise from a MEMS-gyroscope-based computer head mouse are presented. MEMS-gyroscopes are small, light, cheap and widely used in many electrical products. MultiPos, a MEMS-gyroscope-based computer head mouse system was designed for persons with movement disorders. Noise such as physiological tremor and electrical noise is a common problem for the MultiPos system. In this study four different signal processing algorithms were applied and evaluated by simulation in MATLAB and implementation in a dsPIC, with aim to minimize the noise in MultiPos. The algorithms were low-pass filter, Least Mean Square (LMS) algorithm, Kalman filter and Weighted Fourier Linear Combiner (WFLC) algorithm. Comparisons and system tests show that these signal processing algorithms can be used to improve the MultiPos system. The WFLC algorithm was found the best method for noise reduction in the application of a MEMS-gyroscope-based head mouse.

  8. An Integrated MEMS Gyroscope Array with Higher Accuracy Output

    Science.gov (United States)

    Chang, Honglong; Xue, Liang; Qin, Wei; Yuan, Guangmin; Yuan, Weizheng

    2008-01-01

    In this paper, an integrated MEMS gyroscope array method composed of two levels of optimal filtering was designed to improve the accuracy of gyroscopes. In the first-level filtering, several identical gyroscopes were combined through Kalman filtering into a single effective device, whose performance could surpass that of any individual sensor. The key of the performance improving lies in the optimal estimation of the random noise sources such as rate random walk and angular random walk for compensating the measurement values. Especially, the cross correlation between the noises from different gyroscopes of the same type was used to establish the system noise covariance matrix and the measurement noise covariance matrix for Kalman filtering to improve the performance further. Secondly, an integrated Kalman filter with six states was designed to further improve the accuracy with the aid of external sensors such as magnetometers and accelerometers in attitude determination. Experiments showed that three gyroscopes with a bias drift of 35 degree per hour could be combined into a virtual gyroscope with a drift of 1.07 degree per hour through the first-level filter, and the bias drift was reduced to 0.53 degree per hour after the second-level filtering. It proved that the proposed integrated MEMS gyroscope array is capable of improving the accuracy of the MEMS gyroscopes, which provides the possibility of using these low cost MEMS sensors in high-accuracy application areas. PMID:27879855

  9. Fast tunable blazed MEMS grating for external cavity lasers

    Science.gov (United States)

    Tormen, Maurizio; Niedermann, Philippe; Hoogerwerf, Arno; Shea, Herbert; Stanley, Ross

    2017-11-01

    Diffractive MEMS are interesting for a wide range of applications, including displays, scanners or switching elements. Their advantages are compactness, potentially high actuation speed and in the ability to deflect light at large angles. We have designed and fabricated deformable diffractive MEMS grating to be used as tuning elements for external cavity lasers. The resulting device is compact, has wide tunability and a high operating speed. The initial design is a planar grating where the beams are free-standing and attached to each other using leaf springs. Actuation is achieved through two electrostatic comb drives at either end of the grating. To prevent deformation of the free-standing grating, the device is 10 μm thick made from a Silicon on Insulator (SOI) wafer in a single mask process. At 100V a periodicity tuning of 3% has been measured. The first resonant mode of the grating is measured at 13.8 kHz, allowing high speed actuation. This combination of wide tunability and high operating speed represents state of the art in the domain of tunable MEMS filters. In order to improve diffraction efficiency and to expand the usable wavelength range, a blazed version of the deformable MEMS grating has been designed. A key issue is maintaining the mechanical properties of the original device while providing optically smooth blazed beams. Using a process based on anisotropic KOH etching, blazed gratings have been obtained and preliminary characterization is promising.

  10. Neural Network for Principal Component Analysis with Applications in Image Compression

    Directory of Open Access Journals (Sweden)

    Luminita State

    2007-04-01

    Full Text Available Classical feature extraction and data projection methods have been extensively investigated in the pattern recognition and exploratory data analysis literature. Feature extraction and multivariate data projection allow avoiding the "curse of dimensionality", improve the generalization ability of classifiers and significantly reduce the computational requirements of pattern classifiers. During the past decade a large number of artificial neural networks and learning algorithms have been proposed for solving feature extraction problems, most of them being adaptive in nature and well-suited for many real environments where adaptive approach is required. Principal Component Analysis, also called Karhunen-Loeve transform is a well-known statistical method for feature extraction, data compression and multivariate data projection and so far it has been broadly used in a large series of signal and image processing, pattern recognition and data analysis applications.

  11. Application of Artificial Neural Network into the Water Level Modeling and Forecast

    Directory of Open Access Journals (Sweden)

    Marzenna Sztobryn

    2013-06-01

    Full Text Available The dangerous sea and river water level increase does not only destroy the human lives, but also generate the severe flooding in coastal areas. The rapidly changes in the direction and velocity of wind and associated with them sea level changes could be the severe threat for navigation, especially on the fairways of small fishery harbors located in the river mouth. There is the area of activity of two external forcing: storm surges and flood wave. The aim of the work was the description of an application of Artificial Neural Network (ANN methodology into the water level forecast in the case study field in Swibno harbor located is located at 938.7 km of the Wisla River and at a distance of about 3 km up the mouth (Gulf of Gdansk - Baltic Sea.

  12. Technical note: An R package for fitting Bayesian regularized neural networks with applications in animal breeding.

    Science.gov (United States)

    Pérez-Rodríguez, P; Gianola, D; Weigel, K A; Rosa, G J M; Crossa, J

    2013-08-01

    In recent years, several statistical models have been developed for predicting genetic values for complex traits using information on dense molecular markers, pedigrees, or both. These models include, among others, the Bayesian regularized neural networks (BRNN) that have been widely used in prediction problems in other fields of application and, more recently, for genome-enabled prediction. The R package described here (brnn) implements BRNN models and extends these to include both additive and dominance effects. The implementation takes advantage of multicore architectures via a parallel computing approach using openMP (Open Multiprocessing) for the computations. This note briefly describes the classes of models that can be fitted using the brnn package, and it also illustrates its use through several real examples.

  13. Neural control of fast nonlinear systems--application to a turbocharged SI engine with VCT.

    Science.gov (United States)

    Colin, Guillaume; Chamaillard, Yann; Bloch, Gérard; Corde, Gilles

    2007-07-01

    Today, (engine) downsizing using turbocharging appears as a major way in reducing fuel consumption and pollutant emissions of spark ignition (SI) engines. In this context, an efficient control of the air actuators [throttle, turbo wastegate, and variable camshaft timing (VCT)] is needed for engine torque control. This paper proposes a nonlinear model-based control scheme which combines separate, but coordinated, control modules. Theses modules are based on different control strategies: internal model control (IMC), model predictive control (MPC), and optimal control. It is shown how neural models can be used at different levels and included in the control modules to replace physical models, which are too complex to be online embedded, or to estimate nonmeasured variables. The results obtained from two different test benches show the real-time applicability and good control performance of the proposed methods.

  14. Synchronization of Switched Interval Networks and Applications to Chaotic Neural Networks

    Directory of Open Access Journals (Sweden)

    Jinde Cao

    2013-01-01

    Full Text Available This paper investigates synchronization problem of switched delay networks with interval parameters uncertainty, based on the theories of the switched systems and drive-response technique, a mathematical model of the switched interval drive-response error system is established. Without constructing Lyapunov-Krasovskii functions, introducing matrix measure method for the first time to switched time-varying delay networks, combining Halanay inequality technique, synchronization criteria are derived for switched interval networks under the arbitrary switching rule, which are easy to verify in practice. Moreover, as an application, the proposed scheme is then applied to chaotic neural networks. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results.

  15. Fast Convolutional Neural Network Training Using Selective Data Sampling: Application to Hemorrhage Detection in Color Fundus Images

    NARCIS (Netherlands)

    Grinsven, M.J.J.P. van; Ginneken, B. van; Hoyng, C.B.; Theelen, T.; Sanchez, C.I.

    2016-01-01

    Convolutional neural networks (CNNs) are deep learning network architectures that have pushed forward the state-of-the-art in a range of computer vision applications and are increasingly popular in medical image analysis. However, training of CNNs is time-consuming and challenging. In medical image

  16. Integration of a MEMS Inertial Measuring Unit with a MEMS Magnetometer for 3D Orientation Estimation

    DEFF Research Database (Denmark)

    Cai, Junping; Malureanu, Christian; Andersen, Niels Lervad

    2011-01-01

    This paper presents an algorithm for combining the measurements of a MEMS Inertial Measurement Unit (IMU) and a MEMS magnetometer. The measurements are done using a special designed and customized miniature detecting system for 3D orientation estimation, and position tracking......This paper presents an algorithm for combining the measurements of a MEMS Inertial Measurement Unit (IMU) and a MEMS magnetometer. The measurements are done using a special designed and customized miniature detecting system for 3D orientation estimation, and position tracking...

  17. Improving Stability and Convergence for Adaptive Radial Basis Function Neural Networks Algorithm. (On-Line Harmonics Estimation Application

    Directory of Open Access Journals (Sweden)

    Eyad K Almaita

    2017-03-01

    Keywords: Energy efficiency, Power quality, Radial basis function, neural networks, adaptive, harmonic. Article History: Received Dec 15, 2016; Received in revised form Feb 2nd 2017; Accepted 13rd 2017; Available online How to Cite This Article: Almaita, E.K and Shawawreh J.Al (2017 Improving Stability and Convergence for Adaptive Radial Basis Function Neural Networks Algorithm (On-Line Harmonics Estimation Application.  International Journal of Renewable Energy Develeopment, 6(1, 9-17. http://dx.doi.org/10.14710/ijred.6.1.9-17

  18. Application of viral vectors to the study of neural connectivities and neural circuits in the marmoset brain.

    Science.gov (United States)

    Watakabe, Akiya; Sadakane, Osamu; Hata, Katsusuke; Ohtsuka, Masanari; Takaji, Masafumi; Yamamori, Tetsuo

    2017-03-01

    It is important to study the neural connectivities and functions in primates. For this purpose, it is critical to be able to transfer genes to certain neurons in the primate brain so that we can image the neuronal signals and analyze the function of the transferred gene. Toward this end, our team has been developing gene transfer systems using viral vectors. In this review, we summarize our current achievements as follows. 1) We compared the features of gene transfer using five different AAV serotypes in combination with three different promoters, namely, CMV, mouse CaMKII (CaMKII), and human synapsin 1 (hSyn1), in the marmoset cortex with those in the mouse and macaque cortices. 2) We used target-specific double-infection techniques in combination with TET-ON and TET-OFF using lentiviral retrograde vectors for enhanced visualization of neural connections. 3) We used an AAV-mediated gene transfer method to study the transcriptional control for amplifying fluorescent signals using the TET/TRE system in the primate neocortex. We also established systems for shRNA mediated gene targeting in a neocortical region where a gene is significantly expressed and for expressing the gene using the CMV promoter for an unexpressed neocortical area in the primate cortex using AAV vectors to understand the regulation of downstream genes. Our findings have demonstrated the feasibility of using viral vector mediated gene transfer systems for the study of primate cortical circuits using the marmoset as an animal model. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 77: 354-372, 2017. © 2016 The Authors. Developmental Neurobiology Published by Wiley Periodicals, Inc.

  19. Advances in piezoelectric PZT-based RF MEMS components and systems

    Science.gov (United States)

    Benoit, R. R.; Rudy, R. Q.; Pulskamp, J. S.; Polcawich, R. G.; Bedair, S. S.

    2017-08-01

    There is continuing interest in radio frequency (RF) microelectromechanical system (MEMS) devices due to their ability to offer exceptional RF performance, high linearity and low power consumption. To date, there is an impressive amount of RF MEMS components such as; switches, resonators, varactors, and tunable inductors that have enabled smaller, cheaper and more efficient RF systems. RF MEMS devices contain micromachined components that have the ability to move so that a change in the mechanical state of a device will result in a change to the device’s RF properties. There are many common modes of actuation, including, but not limited to: electrostatic, magnetostatic, piezoelectric, and electrothermal actuation. Although there are attractive aspects and drawbacks to each of these technologies, this paper will focus on advances in the application of piezoelectric actuation, and in particular the use of lead zirconium titanate (PZT), for RF MEMS.

  20. Surface chemistry and tribology of MEMS.

    Science.gov (United States)

    Maboudian, Roya; Carraro, Carlo

    2004-01-01

    The microscopic length scale and high surface-to-volume ratio, characteristic of microelectro-mechanical systems (MEMS), dictate that surface properties are of paramount importance. This review deals with the effects of surface chemical treatments on tribological properties (adhesion, friction, and wear) of MEMS devices. After a brief review of materials and processes that are utilized in MEMS technology, the relevant tribological and chemical issues are discussed. Various MEMS microinstruments are discussed, which are commonly employed to perform adhesion, friction, and wear measurements. The effects of different surface treatments on the reported tribological properties are discussed.

  1. MEMS Bragg grating force sensor

    DEFF Research Database (Denmark)

    Reck, Kasper; Thomsen, Erik Vilain; Hansen, Ole

    2011-01-01

    We present modeling, design, fabrication and characterization of a new type of all-optical frequency modulated MEMS force sensor based on a mechanically amplified double clamped waveguide beam structure with integrated Bragg grating. The sensor is ideally suited for force measurements in harsh...... environments and for remote and distributed sensing and has a measured sensitivity of -14 nm/N, which is several times higher than what is obtained in conventional fiber Bragg grating force sensors. © 2011 Optical Society of America....

  2. Neural Learning Control of Flexible Joint Manipulator with Predefined Tracking Performance and Application to Baxter Robot

    Directory of Open Access Journals (Sweden)

    Min Wang

    2017-01-01

    Full Text Available This paper focuses on neural learning from adaptive neural control (ANC for a class of flexible joint manipulator under the output tracking constraint. To facilitate the design, a new transformed function is introduced to convert the constrained tracking error into unconstrained error variable. Then, a novel adaptive neural dynamic surface control scheme is proposed by combining the neural universal approximation. The proposed control scheme not only decreases the dimension of neural inputs but also reduces the number of neural approximators. Moreover, it can be verified that all the closed-loop signals are uniformly ultimately bounded and the constrained tracking error converges to a small neighborhood around zero in a finite time. Particularly, the reduction of the number of neural input variables simplifies the verification of persistent excitation (PE condition for neural networks (NNs. Subsequently, the proposed ANC scheme is verified recursively to be capable of acquiring and storing knowledge of unknown system dynamics in constant neural weights. By reusing the stored knowledge, a neural learning controller is developed for better control performance. Simulation results on a single-link flexible joint manipulator and experiment results on Baxter robot are given to illustrate the effectiveness of the proposed scheme.

  3. Feedback Control of MEMS to Atoms

    CERN Document Server

    Shapiro, Benjamin

    2012-01-01

    Feedback Control of MEMS to Atoms illustrates the use of control and control systems as an essential part of functioning integrated miniaturized systems. The book is organized according to the dimensional scale of the problem, starting with microscale systems and ending with atomic-scale systems. Similar to macroscale machines and processes, control systems can play a major role in improving the performance of micro- and nanoscale systems and in enabling new capabilities that would otherwise not be possible. The majority of problems at these scales present many new challenges that go beyond the current state-of-the-art in control theory and engineering. This is a result of the multidisciplinary nature of micro/nanotechnology, which requires the merging of control engineering with physics, biology and chemistry. This book: Shows how the utilization of feedback control in nanotechnology instrumentation can yield results far better than passive systems can Discusses the application of control systems to problems...

  4. Interface Circuit Design for Frequency-Time Domain MEMS Sensors

    Energy Technology Data Exchange (ETDEWEB)

    Yurish, Sergey Y [Information Systems and Networks, National University Lviv Polytechnic, Bandera str., 12 Lviv, 79013 (Ukraine); Kirianaki, Nikolay V [International Frequency Sensor Association (IFSA), Bandera str., 12 Lviv, 79013 (Ukraine)

    2006-04-01

    The focus of this paper is to describe emerging techniques and methods for interface circuit design for frequency, period, duty-cycle or PWM output MEMS sensors. The designed module is intended for frequency-time parameters - to - digital conversion and communication functions and can be embedded into a SoC. The developed interface circuit provides technologies that both reduce the cost and time of SoC development and improve sensor system performance. Its revolutionary suite of technical products facilitates, for the first time, low-cost, time-efficient production of MEMS sensor applications. On the other hand the proposed design approach reduces the development time, risk and cost of sensor applications by to ten times.

  5. Microelectromechanical (MEMS) manipulators for control of nanoparticle coupling interactions

    Science.gov (United States)

    Lopez, Daniel; Wiederrecht, Gary; Gosztola, David J.; Mancini, Derrick C.

    2017-01-17

    A nanopositioning system for producing a coupling interaction between a first nanoparticle and a second nanoparticle. A first MEMS positioning assembly includes an electrostatic comb drive actuator configured to selectively displace a first nanoparticle in a first dimension and an electrode configured to selectively displace the first nanoparticle in a second dimensions. Accordingly, the first nanoparticle may be selectively positioned in two dimensions to modulate the distance between the first nanoparticle and a second nanoparticle that may be coupled to a second MEMS positioning assembly. Modulating the distance between the first and second nanoparticles obtains a coupling interaction between the nanoparticles that alters at least one material property of the nanoparticles applicable to a variety of sensing and control applications.

  6. Combined application of mixture experimental design and artificial neural networks in the solid dispersion development.

    Science.gov (United States)

    Medarević, Djordje P; Kleinebudde, Peter; Djuriš, Jelena; Djurić, Zorica; Ibrić, Svetlana

    2016-01-01

    This study for the first time demonstrates combined application of mixture experimental design and artificial neural networks (ANNs) in the solid dispersions (SDs) development. Ternary carbamazepine-Soluplus®-poloxamer 188 SDs were prepared by solvent casting method to improve carbamazepine dissolution rate. The influence of the composition of prepared SDs on carbamazepine dissolution rate was evaluated using d-optimal mixture experimental design and multilayer perceptron ANNs. Physicochemical characterization proved the presence of the most stable carbamazepine polymorph III within the SD matrix. Ternary carbamazepine-Soluplus®-poloxamer 188 SDs significantly improved carbamazepine dissolution rate compared to pure drug. Models developed by ANNs and mixture experimental design well described the relationship between proportions of SD components and percentage of carbamazepine released after 10 (Q10) and 20 (Q20) min, wherein ANN model exhibit better predictability on test data set. Proportions of carbamazepine and poloxamer 188 exhibited the highest influence on carbamazepine release rate. The highest carbamazepine release rate was observed for SDs with the lowest proportions of carbamazepine and the highest proportions of poloxamer 188. ANNs and mixture experimental design can be used as powerful data modeling tools in the systematic development of SDs. Taking into account advantages and disadvantages of both techniques, their combined application should be encouraged.

  7. A Real Valued Neural Network Based Autoregressive Energy Detector for Cognitive Radio Application.

    Science.gov (United States)

    Onumanyi, A J; Onwuka, E N; Aibinu, A M; Ugweje, O C; Salami, M J E

    2014-01-01

    A real valued neural network (RVNN) based energy detector (ED) is proposed and analyzed for cognitive radio (CR) application. This was developed using a known two-layered RVNN model to estimate the model coefficients of an autoregressive (AR) system. By using appropriate modules and a well-designed detector, the power spectral density (PSD) of the AR system transfer function was estimated and subsequent receiver operating characteristic (ROC) curves of the detector generated and analyzed. A high detection performance with low false alarm rate was observed for varying signal to noise ratio (SNR), sample number, and model order conditions. The proposed RVNN based ED was then compared to the simple periodogram (SP), Welch periodogram (WP), multitaper (MT), Yule-Walker (YW), Burg (BG), and covariance (CV) based ED techniques. The proposed detector showed better performance than the SP, WP, and MT while providing better false alarm performance than the YW, BG, and CV. Data provided here support the effectiveness of the proposed RVNN based ED for CR application.

  8. Programmable differential capacitance-to-voltage converter for MEMS accelerometers

    Science.gov (United States)

    Royo, G.; Sánchez-Azqueta, C.; Gimeno, C.; Aldea, C.; Celma, S.

    2017-05-01

    Capacitive MEMS sensors exhibit an excellent noise performance, high sensitivity and low power consumption. They offer a huge range of applications, being the accelerometer one of its main uses. In this work, we present the design of a capacitance-to-voltage converter in CMOS technology to measure the acceleration from the capacitance variations. It is based on a low-power, fully-differential transimpedance amplifier with low input impedance and a very low input noise.

  9. Applications of Wavelet Neural Network Model to Building Settlement Prediction: A Case Study

    Directory of Open Access Journals (Sweden)

    Qulin TAN

    2014-04-01

    Full Text Available Deformation monitoring is a significant work for engineering safety, which is performed throughout the entire process of engineering design, construction and operation. Based on the theoretic analysis of wavelet and neural network, we applied the improved BP neural network model, auxiliary wavelet neural network model and embedded wavelet neural network model to the settlement prediction in one practical engineering monitoring project with MATLAB software programming. The cumulative and the interval settlement was predicted and compared with measured data. The overall performances of the three models were analyzed and compared. The results show that the accuracies of two kinds of wavelet neural network models are roughly the same, which prediction errors of monitoring points are less than 1mm, obviously superior to the single BP neural network model.

  10. A neural networks application for the study of the influence of transport conditions on the working performance

    Science.gov (United States)

    Anghel, D.-C.; Ene, A.; Ştirbu, C.; Sicoe, G.

    2017-10-01

    This paper presents a study about the factors that influence the working performances of workers in the automotive industry. These factors regard mainly the transportations conditions, taking into account the fact that a large number of workers live in places that are far away of the enterprise. The quantitative data obtained from this study will be generalized by using a neural network, software simulated. The neural network is able to estimate the performance of workers even for the combinations of input factors that had been not recorded by the study. The experimental data obtained from the study will be divided in two classes. The first class that contains approximately 80% of data will be used by the Java software for the training of the neural network. The weights resulted from the training process will be saved in a text file. The other class that contains the rest of the 20% of experimental data will be used to validate the neural network. The training and the validation of the networks are performed in a Java software (TrainAndValidate java class). We designed another java class, Test.java that will be used with new input data, for new situations. The experimental data collected from the study. The software that simulated the neural network. The software that estimates the working performance, when new situations are met. This application is useful for human resources department of an enterprise. The output results are not quantitative. They are qualitative (from low performance to high performance, divided in five classes).

  11. Strong Motion Seismograph Based On MEMS Accelerometer

    Science.gov (United States)

    Teng, Y.; Hu, X.

    2013-12-01

    The MEMS strong motion seismograph we developed used the modularization method to design its software and hardware.It can fit various needs in different application situation.The hardware of the instrument is composed of a MEMS accelerometer,a control processor system,a data-storage system,a wired real-time data transmission system by IP network,a wireless data transmission module by 3G broadband,a GPS calibration module and power supply system with a large-volumn lithium battery in it. Among it,the seismograph's sensor adopted a three-axis with 14-bit high resolution and digital output MEMS accelerometer.Its noise level just reach about 99μg/√Hz and ×2g to ×8g dynamically selectable full-scale.Its output data rates from 1.56Hz to 800Hz. Its maximum current consumption is merely 165μA,and the device is so small that it is available in a 3mm×3mm×1mm QFN package. Furthermore,there is access to both low pass filtered data as well as high pass filtered data,which minimizes the data analysis required for earthquake signal detection. So,the data post-processing can be simplified. Controlling process system adopts a 32-bit low power consumption embedded ARM9 processor-S3C2440 and is based on the Linux operation system.The processor's operating clock at 400MHz.The controlling system's main memory is a 64MB SDRAM with a 256MB flash-memory.Besides,an external high-capacity SD card data memory can be easily added.So the system can meet the requirements for data acquisition,data processing,data transmission,data storage,and so on. Both wired and wireless network can satisfy remote real-time monitoring, data transmission,system maintenance,status monitoring or updating software.Linux was embedded and multi-layer designed conception was used.The code, including sensor hardware driver,the data acquisition,earthquake setting out and so on,was written on medium layer.The hardware driver consist of IIC-Bus interface driver, IO driver and asynchronous notification driver. The

  12. Application of Artificial Neural Networks in the Heart Electrical Axis Position Conclusion Modeling

    Science.gov (United States)

    Bakanovskaya, L. N.

    2016-08-01

    The article touches upon building of a heart electrical axis position conclusion model using an artificial neural network. The input signals of the neural network are the values of deflections Q, R and S; and the output signal is the value of the heart electrical axis position. Training of the network is carried out by the error propagation method. The test results allow concluding that the created neural network makes a conclusion with a high degree of accuracy.

  13. An interpretation of neural networks as inference engines with application to transformer failure diagnosis

    Energy Technology Data Exchange (ETDEWEB)

    Castro, Adriana R. Garcez; Miranda, Vladimiro [Instituto de Engenharia de Sistemas e Computadores do Porto, INESC Porto (Portugal)

    2005-12-01

    An artificial neural network concept has been developed for transformer fault diagnosis using dissolved gas-in-oil analysis (DGA). A new methodology for mapping the neural network into a rule-based inference system is described. This mapping makes explicit the knowledge implicitly captured by the neural network during the learning stage, by transforming it into a Fuzzy Inference System. Some studies are reported, illustrating the good results obtained. (author)

  14. Design and evaluation of neural classifiers application to skin lesion classification

    DEFF Research Database (Denmark)

    Hintz-Madsen, Mads; Hansen, Lars Kai; Larsen, Jan

    1995-01-01

    Addresses design and evaluation of neural classifiers for the problem of skin lesion classification. By using Gauss Newton optimization for the entropic cost function in conjunction with pruning by Optimal Brain Damage and a new test error estimate, the authors show that this scheme is capable...... of optimizing the architecture of neural classifiers. Furthermore, error-reject tradeoff theory indicates, that the resulting neural classifiers for the skin lesion classification problem are near-optimal...

  15. Engineering Applications of Neural Computing: A State-of-the-Art Survey

    Science.gov (United States)

    1991-05-01

    Papachristou. C. A., "Training of a Neural Network for Pattern Classifi- cation Based on Entropy Measure," Proceedings of 1988 IEEE International Conference...diction and System Modeling," Technical Report LA-UR-87-2662, Los Alamos National Lab- oratoiy, 1987. 10. Levy, W. B., "Maximum Entropy Prediction in Neural...Lawrence Erlbaum, Hillsdale, NJ, 1990. 53. MacGregor, R. J., Neural and Brain Modeling, The Academic Press, New York, 1987. 54. Marr , D., Vision, San

  16. Introduction to neural networks

    CERN Document Server

    James, Frederick E

    1994-02-02

    1. Introduction and overview of Artificial Neural Networks. 2,3. The Feed-forward Network as an inverse Problem, and results on the computational complexity of network training. 4.Physics applications of neural networks.

  17. How much power does neural signal propagation need?Presented at the SPIE Conf. on BioMEMS and Smart Nanostructures (Adelaide., 2001); the conference version was published in its proceedings.

    Science.gov (United States)

    Bezrukov, Sergey M.; Kish, Laszlo B.

    2002-10-01

    Two well known, biologically inspired non-dynamical models of stochastic resonance, the threshold-crossing model and the fluctuating rate model, are analyzed in terms of channel information capacity and dissipation of energy necessary for small-signal transduction. Using analogies to spike propagation in neurons we postulate the average output pulse rate as a measure of dissipation. The dissipation increases monotonically with the input noise. We find that for small dissipation both models give a close to linear dependence of the channel information capacity on dissipation. In both models the channel information capacity, as a function of dissipation, has a maximum at input noise amplitude that is different from that in the standard signal-to-noise ratio versus input noise plot. Though a direct comparison is not straightforward, for small signals the threshold model gives appreciably higher density of information per dissipation than the exponential fluctuating rate model. We show that a formal introduction of cooperativity in the rate fluctuating model permits us to imitate the response function of the threshold model and to enhance performance. This finding may have direct relevance to real neural spike generation where, due to a strong positive feedback, the ion channel currents add up in a synchronized way.

  18. An introduction to artificial neural networks in bioinformatics--application to complex microarray and mass spectrometry datasets in cancer studies.

    Science.gov (United States)

    Lancashire, Lee J; Lemetre, Christophe; Ball, Graham R

    2009-05-01

    Applications of genomic and proteomic technologies have seen a major increase, resulting in an explosion in the amount of highly dimensional and complex data being generated. Subsequently this has increased the effort by the bioinformatics community to develop novel computational approaches that allow for meaningful information to be extracted. This information must be of biological relevance and thus correlate to disease phenotypes of interest. Artificial neural networks are a form of machine learning from the field of artificial intelligence with proven pattern recognition capabilities and have been utilized in many areas of bioinformatics. This is due to their ability to cope with highly dimensional complex datasets such as those developed by protein mass spectrometry and DNA microarray experiments. As such, neural networks have been applied to problems such as disease classification and identification of biomarkers. This review introduces and describes the concepts related to neural networks, the advantages and caveats to their use, examples of their applications in mass spectrometry and microarray research (with a particular focus on cancer studies), and illustrations from recent literature showing where neural networks have performed well in comparison to other machine learning methods. This should form the necessary background knowledge and information enabling researchers with an interest in these methodologies, but not necessarily from a machine learning background, to apply the concepts to their own datasets, thus maximizing the information gain from these complex biological systems.

  19. Measurement of the Earth tides with a MEMS gravimeter.

    Science.gov (United States)

    Middlemiss, R P; Samarelli, A; Paul, D J; Hough, J; Rowan, S; Hammond, G D

    2016-03-31

    The ability to measure tiny variations in the local gravitational acceleration allows, besides other applications, the detection of hidden hydrocarbon reserves, magma build-up before volcanic eruptions, and subterranean tunnels. Several technologies are available that achieve the sensitivities required for such applications (tens of microgal per hertz(1/2)): free-fall gravimeters, spring-based gravimeters, superconducting gravimeters, and atom interferometers. All of these devices can observe the Earth tides: the elastic deformation of the Earth's crust as a result of tidal forces. This is a universally predictable gravitational signal that requires both high sensitivity and high stability over timescales of several days to measure. All present gravimeters, however, have limitations of high cost (more than 100,000 US dollars) and high mass (more than 8 kilograms). Here we present a microelectromechanical system (MEMS) device with a sensitivity of 40 microgal per hertz(1/2) only a few cubic centimetres in size. We use it to measure the Earth tides, revealing the long-term stability of our instrument compared to any other MEMS device. MEMS accelerometers--found in most smart phones--can be mass-produced remarkably cheaply, but none are stable enough to be called a gravimeter. Our device has thus made the transition from accelerometer to gravimeter. The small size and low cost of this MEMS gravimeter suggests many applications in gravity mapping. For example, it could be mounted on a drone instead of low-flying aircraft for distributed land surveying and exploration, deployed to monitor volcanoes, or built into multi-pixel density-contrast imaging arrays.

  20. Measurement of the Earth tides with a MEMS gravimeter

    Science.gov (United States)

    Middlemiss, R. P.; Samarelli, A.; Paul, D. J.; Hough, J.; Rowan, S.; Hammond, G. D.

    2016-03-01

    The ability to measure tiny variations in the local gravitational acceleration allows, besides other applications, the detection of hidden hydrocarbon reserves, magma build-up before volcanic eruptions, and subterranean tunnels. Several technologies are available that achieve the sensitivities required for such applications (tens of microgal per hertz1/2): free-fall gravimeters, spring-based gravimeters, superconducting gravimeters, and atom interferometers. All of these devices can observe the Earth tides: the elastic deformation of the Earth’s crust as a result of tidal forces. This is a universally predictable gravitational signal that requires both high sensitivity and high stability over timescales of several days to measure. All present gravimeters, however, have limitations of high cost (more than 100,000 US dollars) and high mass (more than 8 kilograms). Here we present a microelectromechanical system (MEMS) device with a sensitivity of 40 microgal per hertz1/2 only a few cubic centimetres in size. We use it to measure the Earth tides, revealing the long-term stability of our instrument compared to any other MEMS device. MEMS accelerometers—found in most smart phones—can be mass-produced remarkably cheaply, but none are stable enough to be called a gravimeter. Our device has thus made the transition from accelerometer to gravimeter. The small size and low cost of this MEMS gravimeter suggests many applications in gravity mapping. For example, it could be mounted on a drone instead of low-flying aircraft for distributed land surveying and exploration, deployed to monitor volcanoes, or built into multi-pixel density-contrast imaging arrays.

  1. An application of neural networks in microeconomics: input-output mapping in a power generation subsector of the US electricity industry

    NARCIS (Netherlands)

    Erbas, B.C.; Stefanou, S.E.

    2009-01-01

    The use of the artificial neural networks in economics and business goes back to 1950s, while the major bulk of the applications have been developed in more recent years. Reviewing this literature indicates that the field of business benefits from the neural networks in a wide spectrum from

  2. Full C-band Tunable MEMS-VCSEL for Next Generation G.metro Mobile Front- and Backhauling

    DEFF Research Database (Denmark)

    Wagner, Christoph; Zou, Shihuan Jim; Ortsiefer, Markus

    2017-01-01

    We report full C-band tunable, 10 Gbit/s capability, directly modulated MEMS-VCSEL for next generation converged mobile fronthaul and backhaul applications. Bit error rates below 10(-9) were achieved over up to 40 km SSMF.......We report full C-band tunable, 10 Gbit/s capability, directly modulated MEMS-VCSEL for next generation converged mobile fronthaul and backhaul applications. Bit error rates below 10(-9) were achieved over up to 40 km SSMF....

  3. Integration of optoelectronics and MEMS by free-space micro-optics

    Energy Technology Data Exchange (ETDEWEB)

    WARREN,MIAL E.; SPAHN,OLGA B.; SWEATT,WILLIAM C.; SHUL,RANDY J.; WENDT,JOEL R.; VAWTER,GREGORY A.; KRYGOWSKI,TOM W.; REYES,DAVID NMN; RODGERS,M. STEVEN; SNIEGOWSKI,JEFFRY J.

    2000-06-01

    This report represents the completion of a three-year Laboratory-Directed Research and Development (LDRD) program to investigate combining microelectromechanical systems (MEMS) with optoelectronic components as a means of realizing compact optomechanical subsystems. Some examples of possible applications are laser beam scanning, switching and routing and active focusing, spectral filtering or shattering of optical sources. The two technologies use dissimilar materials with significant compatibility problems for a common process line. This project emphasized a hybrid approach to integrating optoelectronics and MEMS. Significant progress was made in developing processing capabilities for adding optical function to MEMS components, such as metal mirror coatings and through-vias in the substrate. These processes were used to demonstrate two integration examples, a MEMS discriminator driven by laser illuminated photovoltaic cells and a MEMS shutter or chopper. Another major difficulty with direct integration is providing the optical path for the MEMS components to interact with the light. The authors explored using folded optical paths in a transparent substrate to provide the interconnection route between the components of the system. The components can be surface-mounted by flip-chip bonding to the substrate. Micro-optics can be fabricated into the substrate to reflect and refocus the light so that it can propagate from one device to another and them be directed out of the substrate into free space. The MEMS components do not require the development of transparent optics and can be completely compatible with the current 5-level polysilicon process. They report progress on a MEMS-based laser scanner using these concepts.

  4. System Modeling of a MEMS Vibratory Gyroscope and Integration to Circuit Simulation.

    Science.gov (United States)

    Kwon, Hyukjin J; Seok, Seyeong; Lim, Geunbae

    2017-11-18

    Recently, consumer applications have dramatically created the demand for low-cost and compact gyroscopes. Therefore, on the basis of microelectromechanical systems (MEMS) technology, many gyroscopes have been developed and successfully commercialized. A MEMS gyroscope consists of a MEMS device and an electrical circuit for self-oscillation and angular-rate detection. Since the MEMS device and circuit are interactively related, the entire system should be analyzed together to design or test the gyroscope. In this study, a MEMS vibratory gyroscope is analyzed based on the system dynamic modeling; thus, it can be mathematically expressed and integrated into a circuit simulator. A behavioral simulation of the entire system was conducted to prove the self-oscillation and angular-rate detection and to determine the circuit parameters to be optimized. From the simulation, the operating characteristic according to the vacuum pressure and scale factor was obtained, which indicated similar trends compared with those of the experimental results. The simulation method presented in this paper can be generalized to a wide range of MEMS devices.

  5. System Modeling of a MEMS Vibratory Gyroscope and Integration to Circuit Simulation

    Directory of Open Access Journals (Sweden)

    Hyukjin J. Kwon

    2017-11-01

    Full Text Available Recently, consumer applications have dramatically created the demand for low-cost and compact gyroscopes. Therefore, on the basis of microelectromechanical systems (MEMS technology, many gyroscopes have been developed and successfully commercialized. A MEMS gyroscope consists of a MEMS device and an electrical circuit for self-oscillation and angular-rate detection. Since the MEMS device and circuit are interactively related, the entire system should be analyzed together to design or test the gyroscope. In this study, a MEMS vibratory gyroscope is analyzed based on the system dynamic modeling; thus, it can be mathematically expressed and integrated into a circuit simulator. A behavioral simulation of the entire system was conducted to prove the self-oscillation and angular-rate detection and to determine the circuit parameters to be optimized. From the simulation, the operating characteristic according to the vacuum pressure and scale factor was obtained, which indicated similar trends compared with those of the experimental results. The simulation method presented in this paper can be generalized to a wide range of MEMS devices.

  6. A non-resonant fiber scanner based on an electrothermally-actuated MEMS stage.

    Science.gov (United States)

    Zhang, Xiaoyang; Duan, Can; Liu, Lin; Li, Xingde; Xie, Huikai

    2015-09-01

    Scanning fiber tips provides the most convenient way for forward-viewing fiber-optic microendoscopy. In this paper, a distal fiber scanning method based on a large-displacement MEMS actuator is presented. A single-mode fiber is glued on the micro-platform of an electrothermal MEMS stage to realize large range non-resonantscanning. The micro-platform has a large piston scan range of up to 800 µm at only 6V. The tip deflection of the fiber can be further amplified by placing the MEMS stage at a proper location along the fiber. A quasi-static model of the fiber-MEMS assembly has been developed and validated experimentally. The frequency response has also been studied and measured. A fiber tip deflection of up to 1650 µm for the 45 mm-long movable fiber portion has been achieved when the MEMS electrothermal stage was placed 25 mm away from the free end. The electrothermally-actuated MEMS stage shows a great potential for forward viewing fiber scanning and optical applications.

  7. A Review on Key Issues and Challenges in Devices Level MEMS Testing

    Directory of Open Access Journals (Sweden)

    Muhammad Shoaib

    2016-01-01

    Full Text Available The present review provides information relevant to issues and challenges in MEMS testing techniques that are implemented to analyze the microelectromechanical systems (MEMS behavior for specific application and operating conditions. MEMS devices are more complex and extremely diverse due to the immersion of multidomains. Their failure modes are distinctive under different circumstances. Therefore, testing of these systems at device level as well as at mass production level, that is, parallel testing, is becoming very challenging as compared to the IC test, because MEMS respond to electrical, physical, chemical, and optical stimuli. Currently, test systems developed for MEMS devices have to be customized due to their nondeterministic behavior and complexity. The accurate measurement of test systems for MEMS is difficult to quantify in the production phase. The complexity of the device to be tested required maturity in the test technique which increases the cost of test development; this practice is directly imposed on the device cost. This factor causes a delay in time-to-market.

  8. Comparison between MEM and Nott dynamic retinoscopy.

    Science.gov (United States)

    del Pilar Cacho, M; García-Muñoz, A; García-Bernabeu, J R; López, A

    1999-09-01

    The aim of this study was to compare MEM dynamic retinoscopy with the Nott method, to discover whether there were different results in the accommodative response and whether a relation exists between the two techniques. We performed MEM and Nott dynamic retinoscopy in 50 visually normal university students. Both methods were performed first on the basis of static retinoscopy and second with the result of the subjective refractive exam (binocular balancing). A statistically significant difference existed between the methods. Nott retinoscopy assessed on basis of the subjective refractive exam was the method that obtained the lowest amounts of accommodative lag (+0.42 D), whereas MEM method performed through the static retinoscopy result showed the highest accommodative lag (+0.94 D). Furthermore, correlation analysis showed that a linear relation existed between both methods, so that the Nott value was about one-half the value of the MEM retinoscopy. MEM dynamic retinoscopy showed greater lag than Nott retinoscopy.

  9. Application of Convolutional Neural Network in Classification of High Resolution Agricultural Remote Sensing Images

    Science.gov (United States)

    Yao, C.; Zhang, Y.; Zhang, Y.; Liu, H.

    2017-09-01

    With the rapid development of Precision Agriculture (PA) promoted by high-resolution remote sensing, it makes significant sense in management and estimation of agriculture through crop classification of high-resolution remote sensing image. Due to the complex and fragmentation of the features and the surroundings in the circumstance of high-resolution, the accuracy of the traditional classification methods has not been able to meet the standard of agricultural problems. In this case, this paper proposed a classification method for high-resolution agricultural remote sensing images based on convolution neural networks(CNN). For training, a large number of training samples were produced by panchromatic images of GF-1 high-resolution satellite of China. In the experiment, through training and testing on the CNN under the toolbox of deep learning by MATLAB, the crop classification finally got the correct rate of 99.66 % after the gradual optimization of adjusting parameter during training. Through improving the accuracy of image classification and image recognition, the applications of CNN provide a reference value for the field of remote sensing in PA.

  10. Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications

    Science.gov (United States)

    Pastur-Romay, Lucas Antón; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana Belén

    2016-01-01

    Over the past decade, Deep Artificial Neural Networks (DNNs) have become the state-of-the-art algorithms in Machine Learning (ML), speech recognition, computer vision, natural language processing and many other tasks. This was made possible by the advancement in Big Data, Deep Learning (DL) and drastically increased chip processing abilities, especially general-purpose graphical processing units (GPGPUs). All this has created a growing interest in making the most of the potential offered by DNNs in almost every field. An overview of the main architectures of DNNs, and their usefulness in Pharmacology and Bioinformatics are presented in this work. The featured applications are: drug design, virtual screening (VS), Quantitative Structure–Activity Relationship (QSAR) research, protein structure prediction and genomics (and other omics) data mining. The future need of neuromorphic hardware for DNNs is also discussed, and the two most advanced chips are reviewed: IBM TrueNorth and SpiNNaker. In addition, this review points out the importance of considering not only neurons, as DNNs and neuromorphic chips should also include glial cells, given the proven importance of astrocytes, a type of glial cell which contributes to information processing in the brain. The Deep Artificial Neuron–Astrocyte Networks (DANAN) could overcome the difficulties in architecture design, learning process and scalability of the current ML methods. PMID:27529225

  11. Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications

    Directory of Open Access Journals (Sweden)

    Lucas Antón Pastur-Romay

    2016-08-01

    Full Text Available Over the past decade, Deep Artificial Neural Networks (DNNs have become the state-of-the-art algorithms in Machine Learning (ML, speech recognition, computer vision, natural language processing and many other tasks. This was made possible by the advancement in Big Data, Deep Learning (DL and drastically increased chip processing abilities, especially general-purpose graphical processing units (GPGPUs. All this has created a growing interest in making the most of the potential offered by DNNs in almost every field. An overview of the main architectures of DNNs, and their usefulness in Pharmacology and Bioinformatics are presented in this work. The featured applications are: drug design, virtual screening (VS, Quantitative Structure–Activity Relationship (QSAR research, protein structure prediction and genomics (and other omics data mining. The future need of neuromorphic hardware for DNNs is also discussed, and the two most advanced chips are reviewed: IBM TrueNorth and SpiNNaker. In addition, this review points out the importance of considering not only neurons, as DNNs and neuromorphic chips should also include glial cells, given the proven importance of astrocytes, a type of glial cell which contributes to information processing in the brain. The Deep Artificial Neuron–Astrocyte Networks (DANAN could overcome the difficulties in architecture design, learning process and scalability of the current ML methods.

  12. Application of neural networks and other machine learning algorithms to DNA sequence analysis

    Energy Technology Data Exchange (ETDEWEB)

    Lapedes, A.; Barnes, C.; Burks, C.; Farber, R.; Sirotkin, K.

    1988-01-01

    In this article we report initial, quantitative results on application of simple neutral networks, and simple machine learning methods, to two problems in DNA sequence analysis. The two problems we consider are: (1) determination of whether procaryotic and eucaryotic DNA sequences segments are translated to protein. An accuracy of 99.4% is reported for procaryotic DNA (E. coli) and 98.4% for eucaryotic DNA (H. Sapiens genes known to be expressed in liver); (2) determination of whether eucaryotic DNA sequence segments containing the dinucleotides ''AG'' or ''GT'' are transcribed to RNA splice junctions. Accuracy of 91.2% was achieved on intron/exon splice junctions (acceptor sites) and 92.8% on exon/intron splice junctions (donor sites). The solution of these two problems, by use of information processing algorithms operating on unannotated base sequences and without recourse to biological laboratory work, is relevant to the Human Genome Project. A variety of neural network, machine learning, and information theoretic algorithms are used. The accuracies obtained exceed those of previous investigations for which quantitative results are available in the literature. They result from an ongoing program of research that applies machine learning algorithms to the problem of determining biological function of DNA sequences. Some predictions of possible new genes using these methods are listed -- although a complete survey of the H. sapiens and E. coli sections of GenBank will be given elsewhere. 36 refs., 6 figs., 6 tabs.

  13. APPLICATION OF CONVOLUTIONAL NEURAL NETWORK IN CLASSIFICATION OF HIGH RESOLUTION AGRICULTURAL REMOTE SENSING IMAGES

    Directory of Open Access Journals (Sweden)

    C. Yao

    2017-09-01

    Full Text Available With the rapid development of Precision Agriculture (PA promoted by high-resolution remote sensing, it makes significant sense in management and estimation of agriculture through crop classification of high-resolution remote sensing image. Due to the complex and fragmentation of the features and the surroundings in the circumstance of high-resolution, the accuracy of the traditional classification methods has not been able to meet the standard of agricultural problems. In this case, this paper proposed a classification method for high-resolution agricultural remote sensing images based on convolution neural networks(CNN. For training, a large number of training samples were produced by panchromatic images of GF-1 high-resolution satellite of China. In the experiment, through training and testing on the CNN under the toolbox of deep learning by MATLAB, the crop classification finally got the correct rate of 99.66 % after the gradual optimization of adjusting parameter during training. Through improving the accuracy of image classification and image recognition, the applications of CNN provide a reference value for the field of remote sensing in PA.

  14. Artificial neural networks in gynaecological diseases: current and potential future applications.

    Science.gov (United States)

    Siristatidis, Charalampos S; Chrelias, Charalampos; Pouliakis, Abraham; Katsimanis, Evangelos; Kassanos, Dimitrios

    2010-10-01

    Current (and probably future) practice of medicine is mostly associated with prediction and accurate diagnosis. Especially in clinical practice, there is an increasing interest in constructing and using valid models of diagnosis and prediction. Artificial neural networks (ANNs) are mathematical systems being used as a prospective tool for reliable, flexible and quick assessment. They demonstrate high power in evaluating multifactorial data, assimilating information from multiple sources and detecting subtle and complex patterns. Their capability and difference from other statistical techniques lies in performing nonlinear statistical modelling. They represent a new alternative to logistic regression, which is the most commonly used method for developing predictive models for outcomes resulting from partitioning in medicine. In combination with the other non-algorithmic artificial intelligence techniques, they provide useful software engineering tools for the development of systems in quantitative medicine. Our paper first presents a brief introduction to ANNs, then, using what we consider the best available evidence through paradigms, we evaluate the ability of these networks to serve as first-line detection and prediction techniques in some of the most crucial fields in gynaecology. Finally, through the analysis of their current application, we explore their dynamics for future use.

  15. Application of a Deep Neural Network to Metabolomics Studies and Its Performance in Determining Important Variables.

    Science.gov (United States)

    Date, Yasuhiro; Kikuchi, Jun

    2018-02-06

    Deep neural networks (DNNs), which are kinds of the machine learning approaches, are powerful tools for analyzing big sets of data derived from biological and environmental systems. However, DNNs are not applicable to metabolomics studies because they have difficulty in identifying contribution factors, e.g., biomarkers, in constructed classification and regression models. In this paper, we describe an improved DNN-based analytical approach that incorporates an importance estimation for each variable using a mean decrease accuracy (MDA) calculation, which is based on a permutation algorithm; this approach is called DNN-MDA. The performance of the DNN-MDA approach was evaluated using a data set of metabolic profiles derived from yellowfin goby that lived in various rivers throughout Japan. Its performance was compared with that of conventional multivariate and machine learning methods, and the DNN-MDA approach was found to have the best classification accuracy (97.8%) among the examined methods. In addition to this, the DNN-MDA approach facilitated the identification of important variables such as trimethylamine N-oxide, inosinic acid, and glycine, which were characteristic metabolites that contributed to the discrimination of the geographical differences between fish caught in the Kanto region and those caught in other regions. As a result, the DNN-MDA approach is a useful and powerful tool for determining the geographical origins of specimens and identifying their biomarkers in metabolomics studies that are conducted in biological and environmental systems.

  16. Prospect of Human Pluripotent Stem Cell-Derived Neural Crest Stem Cells in Clinical Application

    Directory of Open Access Journals (Sweden)

    Qian Zhu

    2016-01-01

    Full Text Available Neural crest stem cells (NCSCs represent a transient and multipotent cell population that contributes to numerous anatomical structures such as peripheral nervous system, teeth, and cornea. NCSC maldevelopment is related to various human diseases including pigmentation abnormalities, disorders affecting autonomic nervous system, and malformations of teeth, eyes, and hearts. As human pluripotent stem cells including human embryonic stem cells (hESCs and human induced pluripotent stem cells (hiPSCs can serve as an unlimited cell source to generate NCSCs, hESC/hiPSC-derived NCSCs can be a valuable tool to study the underlying mechanisms of NCSC-associated diseases, which paves the way for future therapies for these abnormalities. In addition, hESC/hiPSC-derived NCSCs with the capability of differentiating to various cell types are highly promising for clinical organ repair and regeneration. In this review, we first discuss NCSC generation methods from human pluripotent stem cells and differentiation mechanism of NCSCs. Then we focus on the clinical application potential of hESC/hiPSC-derived NCSCs on peripheral nerve injuries, corneal blindness, tooth regeneration, pathological melanogenesis, Hirschsprung disease, and cardiac repair and regeneration.

  17. Expandable and Rapidly Differentiating Human Induced Neural Stem Cell Lines for Multiple Tissue Engineering Applications

    Directory of Open Access Journals (Sweden)

    Dana M. Cairns

    2016-09-01

    Full Text Available Limited availability of human neurons poses a significant barrier to progress in biological and preclinical studies of the human nervous system. Current stem cell-based approaches of neuron generation are still hindered by prolonged culture requirements, protocol complexity, and variability in neuronal differentiation. Here we establish stable human induced neural stem cell (hiNSC lines through the direct reprogramming of neonatal fibroblasts and adult adipose-derived stem cells. These hiNSCs can be passaged indefinitely and cryopreserved as colonies. Independently of media composition, hiNSCs robustly differentiate into TUJ1-positive neurons within 4 days, making them ideal for innervated co-cultures. In vivo, hiNSCs migrate, engraft, and contribute to both central and peripheral nervous systems. Lastly, we demonstrate utility of hiNSCs in a 3D human brain model. This method provides a valuable interdisciplinary tool that could be used to develop drug screening applications as well as patient-specific disease models related to disorders of innervation and the brain.

  18. Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications.

    Science.gov (United States)

    Pastur-Romay, Lucas Antón; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana Belén

    2016-08-11

    Over the past decade, Deep Artificial Neural Networks (DNNs) have become the state-of-the-art algorithms in Machine Learning (ML), speech recognition, computer vision, natural language processing and many other tasks. This was made possible by the advancement in Big Data, Deep Learning (DL) and drastically increased chip processing abilities, especially general-purpose graphical processing units (GPGPUs). All this has created a growing interest in making the most of the potential offered by DNNs in almost every field. An overview of the main architectures of DNNs, and their usefulness in Pharmacology and Bioinformatics are presented in this work. The featured applications are: drug design, virtual screening (VS), Quantitative Structure-Activity Relationship (QSAR) research, protein structure prediction and genomics (and other omics) data mining. The future need of neuromorphic hardware for DNNs is also discussed, and the two most advanced chips are reviewed: IBM TrueNorth and SpiNNaker. In addition, this review points out the importance of considering not only neurons, as DNNs and neuromorphic chips should also include glial cells, given the proven importance of astrocytes, a type of glial cell which contributes to information processing in the brain. The Deep Artificial Neuron-Astrocyte Networks (DANAN) could overcome the difficulties in architecture design, learning process and scalability of the current ML methods.

  19. Fabrication and characterization of PZT string based MEMS devices

    Directory of Open Access Journals (Sweden)

    D.T. Huong Giang

    2016-06-01

    Full Text Available String based MEMS devices recently attract world technology development thanks to their advantages over cantilever ones. Approaching to this direction, the paper reports on the micro-fabrication and characterization of free-standing doubly clamped piezoelectric beams based on heterostructures of Pd/FeNi/Pd/PZT/LSMO/STO/Si. The displacement of strings is investigated in both static and dynamic mode. The static response exhibits a bending displacement as large as 1.2 μm, whereas the dynamic response shows a strong resonance with a high quality factor of around 35 depending on the resonant mode at atmospheric pressure. These findings are comparable with those observed in large dimension membrane and cantilever based MEMS devices, which exhibit high potentials in variety of sensor and resonant actuator applications.

  20. MEMS based stencil lithography for mechanically tunable metasurfaces

    Science.gov (United States)

    Reeves, Jeremy; Stark, Thomas; Jayne, Rachael; Barrett, Lawrence; Lally, Richard; Bishop, David

    We present a scalable technique for nanoscale patterning on soft microstructured substrates. Polymer substrates are 3D-printed onto a microelectromechanical systems (MEMS) device which enables the precise alignment of a MEMS stencil relative to the substrate. With this technique, we fabricate optical metamaterials on two dimensional substrates with lattice geometries that allow for the deformation of the lattice unit cells by the application of mechanical strain. Unit cells can be designed to stretch or rotate, giving the substrate auxetic properties. Physical vapor deposition is used to apply metallic metamaterial patterns, defined on the stencil, to the polymer substrates. The fabricated surfaces demonstrate tunable infrared responses, enabled by the elongation or rotation of the substrate lattice unit cells. We discuss our fabrication technique, the potential for use with other types of substrates, and explore its scalability. The project is funded through the DARPA A2P program.