WorldWideScience

Sample records for artificial techniques controlling

  1. Under-Actuated Robot Manipulator Positioning Control Using Artificial Neural Network Inversion Technique

    Directory of Open Access Journals (Sweden)

    Ali T. Hasan

    2012-01-01

    Full Text Available This paper is devoted to solve the positioning control problem of underactuated robot manipulator. Artificial Neural Networks Inversion technique was used where a network represents the forward dynamics of the system trained to learn the position of the passive joint over the working space of a 2R underactuated robot. The obtained weights from the learning process were fixed, and the network was inverted to represent the inverse dynamics of the system and then used in the estimation phase to estimate the position of the passive joint for a new set of data the network was not previously trained for. Data used in this research are recorded experimentally from sensors fixed on the robot joints in order to overcome whichever uncertainties presence in the real world such as ill-defined linkage parameters, links flexibility, and backlashes in gear trains. Results were verified experimentally to show the success of the proposed control strategy.

  2. Leading research on artificial techniques controlling cellular function; Saibo zoshoku seigyo gijutsu no sendo kenkyu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-03-01

    Advanced research and its applicability were surveyed to apply the advanced functional cells to industry. The basic target was set to develop, produce, control and utilize the functional cells, such as intelligent materials and self-regulation bioreactors. The regulation factors regarding apotosis, which is a process of cell suicide programmed within the cell itself of multicellular organisms, cell cycle and aging/ageless were investigated. Furthermore, the function of regulatory factors was investigated at the protein level. Injection of factors regulating cellular function and tissue engineering required for the regulation of cell proliferation were investigated. Tissue engineering is considered to be the intracellular regulation by gene transduction and the extracellular regulation by culture methods, such as coculture. Analysis methods for cell proliferation and function of living cells were investigated using the probes recognizing molecular structure. Novel biomaterials, artificial organ systems, cellular therapy and useful materials were investigated for utilizing the regulation techniques of cell proliferation. 425 refs., 85 figs., 9 tabs.

  3. Combining Artificial Intelligence and Advanced Techniques in Fault-Tolerant Control

    Directory of Open Access Journals (Sweden)

    A. Vargas-Martínez

    2011-08-01

    Full Text Available We present the integration of artificial intelligence, robust, nonlinear and model reference adaptive control (MRACmethods for fault-tolerant control (FTC. We combine MRAC schemes with classical PID controllers, artificial neuralnetworks (ANNs, genetic algorithms (GAs, H∞ controls and sliding mode controls. Six different schemas areproposed: the first one is an MRAC with an artificial neural network and a PID controller whose parameters weretuned by a GA using Pattern Search Optimization. The second scheme is an MRAC controller with an H∞ control(H∞. The third scheme is an MRAC controller with a sliding mode controller (SMC. The fourth scheme is an MRACcontroller with an ANN. The fifth scheme is an MRAC controller with a PID controller optimized by a GA. Finally, thelast scheme is an MRAC classical control system. The objective of this research is to generate more powerful FTCmethods and compare the performance of above schemes under different fault conditions in sensors and actuators.An industrial heat exchanger process was the test bed for these approaches. Simulation results showed that the useof Pattern Search Optimization and ANNs improved the performance of the FTC scheme because it makes the controlsystem more robust against sensor and actuator faults.

  4. Artificial intelligence techniques in Prolog

    CERN Document Server

    Shoham, Yoav

    1993-01-01

    Artificial Intelligence Techniques in Prolog introduces the reader to the use of well-established algorithmic techniques in the field of artificial intelligence (AI), with Prolog as the implementation language. The techniques considered cover general areas such as search, rule-based systems, and truth maintenance, as well as constraint satisfaction and uncertainty management. Specific application domains such as temporal reasoning, machine learning, and natural language are also discussed.Comprised of 10 chapters, this book begins with an overview of Prolog, paying particular attention to Prol

  5. Application of Artificial Intelligence Techniques for the Control of the Asynchronous Machine

    Directory of Open Access Journals (Sweden)

    F. Khammar

    2016-01-01

    Full Text Available The induction machine is experiencing a growing success for two decades by gradually replacing the DC machines and synchronous in many industrial applications. This paper is devoted to the study of advanced methods applied to the command of the asynchronous machine in order to obtain a system of control of high performance. While the criteria for response time, overtaking, and static error can be assured by the techniques of conventional control, the criterion of robustness remains a challenge for researchers. This criterion can be satisfied only by applying advanced techniques of command. After mathematical modeling of the asynchronous machine, it defines the control strategies based on the orientation of the rotor flux. The results of the different simulation tests highlight the properties of robustness of algorithms proposed and suggested to compare the different control strategies.

  6. Diagnostics and Control of Natural Gas-Fired furnaces via Flame Image Analysis using Machine Vision & Artificial Intelligence Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Shahla Keyvan

    2005-12-01

    A new approach for the detection of real-time properties of flames is used in this project to develop improved diagnostics and controls for natural gas fired furnaces. The system utilizes video images along with advanced image analysis and artificial intelligence techniques to provide virtual sensors in a stand-alone expert shell environment. One of the sensors is a flame sensor encompassing a flame detector and a flame analyzer to provide combustion status. The flame detector can identify any burner that has not fired in a multi-burner furnace. Another sensor is a 3-D temperature profiler. One important aspect of combustion control is product quality. The 3-D temperature profiler of this on-line system is intended to provide a tool for a better temperature control in a furnace to improve product quality. In summary, this on-line diagnostic and control system offers great potential for improving furnace thermal efficiency, lowering NOx and carbon monoxide emissions, and improving product quality. The system is applicable in natural gas-fired furnaces in the glass industry and reheating furnaces used in steel and forging industries.

  7. Artificial intelligence techniques for rational decision making

    CERN Document Server

    Marwala, Tshilidzi

    2014-01-01

    Develops insights into solving complex problems in engineering, biomedical sciences, social science and economics based on artificial intelligence. Some of the problems studied are in interstate conflict, credit scoring, breast cancer diagnosis, condition monitoring, wine testing, image processing and optical character recognition. The author discusses and applies the concept of flexibly-bounded rationality which prescribes that the bounds in Nobel Laureate Herbert Simon's bounded rationality theory are flexible due to advanced signal processing techniques, Moore's Law and artificial intellig

  8. Artificial locomotion control

    DEFF Research Database (Denmark)

    Azevedo, Christine; Poignet, Philippe; Espiau, Bernard

    2004-01-01

    walking from descriptive (biomechanics) as well as explicative (neuroscience and physiology) points of view, the objective being to stress the relevant elements for the approach of robot control. The adopted principles are then: no joint trajectory tracking; explicit distinction and integration...... of postural and walking control; use of evolutive optimization objectives; on-line event handling and environment adaptation and anticipation. This leads to the synthesis of an original control scheme based on non-linear model predictive control: Trajectory Free NMPC. The movement is specified implicitly...... through coherent physical inequality constraints. Dynamic model and internal limitations of the system are part of the problem constraints. This work is validated by simulation results obtained for the Bip and Rabbit biped robots in various walking and standing situations and compared to human data...

  9. Artificial Intelligence Techniques for Steam Generator Modelling

    CERN Document Server

    Wright, Sarah

    2008-01-01

    This paper investigates the use of different Artificial Intelligence methods to predict the values of several continuous variables from a Steam Generator. The objective was to determine how the different artificial intelligence methods performed in making predictions on the given dataset. The artificial intelligence methods evaluated were Neural Networks, Support Vector Machines, and Adaptive Neuro-Fuzzy Inference Systems. The types of neural networks investigated were Multi-Layer Perceptions, and Radial Basis Function. Bayesian and committee techniques were applied to these neural networks. Each of the AI methods considered was simulated in Matlab. The results of the simulations showed that all the AI methods were capable of predicting the Steam Generator data reasonably accurately. However, the Adaptive Neuro-Fuzzy Inference system out performed the other methods in terms of accuracy and ease of implementation, while still achieving a fast execution time as well as a reasonable training time.

  10. Artificial intelligence approach to accelerator control systems

    International Nuclear Information System (INIS)

    An experiment was recently started at LAMPF to evaluate the power and limitations of using artificial intelligence techniques to solve problems in accelerator control and operation. A knowledge base was developed to describe the characteristics and the relationships of the first 30 devices in the LAMPF H+ beam line. Each device was categorized and pertinent attributes for each category defined. Specific values were assigned in the knowledge base to represent each actual device. Relationships between devices are modeled using the artificial intelligence techniques of rules, active values, and object-oriented methods. This symbolic model, built using the Knowledge Engineering Environment (KEE) system, provides a framework for analyzing faults, tutoring trainee operators, and offering suggestions to assist in beam tuning. Based on information provided by the domain expert responsible for tuning this portion of the beam line, additional rules were written to describe how he tunes, how he analyzes what is actually happening, and how he deals with failures. Initial results have shown that artificial intelligence techniques can be a useful adjunct to traditional methods of numerical simulation. Successful and efficient operation of future accelerators may depend on the proper merging of symbolic reasoning and conventional numerical control algorithms

  11. Air Quality Forecasting through Different Statistical and Artificial Intelligence Techniques

    Science.gov (United States)

    Mishra, D.; Goyal, P.

    2014-12-01

    Urban air pollution forecasting has emerged as an acute problem in recent years because there are sever environmental degradation due to increase in harmful air pollutants in the ambient atmosphere. In this study, there are different types of statistical as well as artificial intelligence techniques are used for forecasting and analysis of air pollution over Delhi urban area. These techniques are principle component analysis (PCA), multiple linear regression (MLR) and artificial neural network (ANN) and the forecasting are observed in good agreement with the observed concentrations through Central Pollution Control Board (CPCB) at different locations in Delhi. But such methods suffers from disadvantages like they provide limited accuracy as they are unable to predict the extreme points i.e. the pollution maximum and minimum cut-offs cannot be determined using such approach. Also, such methods are inefficient approach for better output forecasting. But with the advancement in technology and research, an alternative to the above traditional methods has been proposed i.e. the coupling of statistical techniques with artificial Intelligence (AI) can be used for forecasting purposes. The coupling of PCA, ANN and fuzzy logic is used for forecasting of air pollutant over Delhi urban area. The statistical measures e.g., correlation coefficient (R), normalized mean square error (NMSE), fractional bias (FB) and index of agreement (IOA) of the proposed model are observed in better agreement with the all other models. Hence, the coupling of statistical and artificial intelligence can be use for the forecasting of air pollutant over urban area.

  12. Artificial Intrusion Detection Techniques: A Survey

    Directory of Open Access Journals (Sweden)

    Ashutosh Gupta

    2014-08-01

    Full Text Available Networking has become the most integral part of our cyber society. Everyone wants to connect themselves with each other. With the advancement of network technology, we find this most vulnerable to breach and take information and once information reaches to the wrong hands it can do terrible things. During recent years, number of attacks on networks have been increased which drew the attention of many researchers on this field. There have been many researches on intrusion detection lately. Many methods have been devised which are really very useful but they can only detect the attacks which already took place. These methods will always fail whenever there is a foreign attack which is not famous or which is new to the networking world. In order to detect new intrusions in the network, researchers have devised artificial intelligence technique for Intrusion detection prevention system. In this paper we are going to cover what types evolutionary techniques have been devised and their significance and modification.

  13. Application of Artificial Intelligence Techniques in Unmanned Aerial Vehicle Flight

    Science.gov (United States)

    Bauer, Frank H. (Technical Monitor); Dufrene, Warren R., Jr.

    2003-01-01

    This paper describes the development of an application of Artificial Intelligence for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in Artificial Intelligence (AI) at Nova southeastern University and as an adjunct to a project at NASA Goddard Space Flight Center's Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an AI method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed. A low cost approach was taken using freeware, gnu, software, and demo programs. The focus of this research has been to outline some of the AI techniques used for UAV flight control and discuss some of the tools used to apply AI techniques. The intent is to succeed with the implementation of applying AI techniques to actually control different aspects of the flight of an UAV.

  14. Artificial Intelligence techniques for mission planning for mobile robots

    International Nuclear Information System (INIS)

    This work focuses on Spatial Modelization Techniques and on Control Software Architectures, in order to deal efficiently with the Navigation and Perception problems encountered in Mobile Autonomous Robotics. After a brief survey of the current various approaches for these techniques, we expose ongoing simulation works for a specific mission in robotics. Studies in progress used for Spatial Reasoning are based on new approaches combining Artificial Intelligence and Geometrical techniques. These methods deal with the problem of environment modelization using three types of models: geometrical topological and semantic models at different levels. The decision making processes of control are presented as the result of cooperation between a group of decentralized agents that communicate by sending messages. (author)

  15. [Research progress on techniques for artificial propagation of corals].

    Science.gov (United States)

    Wang, Shu-hong; Hong, Wen-ting; Chen, Ji-xin; Chen, Yun; Wang, Yi-lei; Zhang, Zi-ping; Weng, Zhao-hong; Xie, Yang-jie

    2015-09-01

    The natural coral reef resources degrade rapidly because of climate change, environmental pollution and exploitation of aquarium species. Artificial propagation is an effective way to facilitate the reduction of wild harvesting, reef restoration, preservation of biodiversity. This paper reviewed the technique and research progresses focused on coral artificial propagation. We compared the advantages and disadvantages of sexual reproduction and asexual reproduction as well as in situ and ex situ propagation. Moreover, we summarized the important roles of irradiation, flow rate, nutrients, feed and other factors in coral propagation within recirculating aquaculture system (RAS). Irradiation is the key to successful ex situ coral culture and different species show different needs of radiation intensity and light spectrum. Therefore, artificial lighting in RAS, as well as. power and maintenance costs, are very important for ex situ coral aquaculture. In addition, corals are very sensitive to NH4+, NO3-, NO2- as well as phosphate in RAS, and many physical, chemical and biological methods are acquired to maintain low nutrients condition. Although RAS has progressed a lot in terms of irradiation, flow rate and nutrient control, future studies also should focus on sexual reproduction, genetic modification and disease control. PMID:26785577

  16. Artificial Breeding Techniques of Whitmania pigra

    Institute of Scientific and Technical Information of China (English)

    Zhao; Nan; Xu; Ziliang

    2014-01-01

    The artificial breeding technology for juvenile of Whitmania pigra was introduced in the paper,including selection of sites and water quality,construction of spawning pool,hatching pool and escape proof facilities,key technology of leech selection,feeding,cocoon hatching,juvenile feeding and management.

  17. Simulation Techniques and Prosthetic Approach Towards Biologically Efficient Artificial Sense Organs- An Overview

    CERN Document Server

    Neogi, Biswarup; Mukherjee, Soumyajit; Das, Achintya; Tibarewala, D N

    2011-01-01

    An overview of the applications of control theory to prosthetic sense organs including the senses of vision, taste and odor is being presented in this paper. Simulation aspect nowadays has been the centre of research in the field of prosthesis. There have been various successful applications of prosthetic organs, in case of natural biological organs dis-functioning patients. Simulation aspects and control modeling are indispensible for knowing system performance, and to generate an original approach of artificial organs. This overview focuses mainly on control techniques, by far a theoretical overview and fusion of artificial sense organs trying to mimic the efficacies of biologically active sensory organs. Keywords: virtual reality, prosthetic vision, artificial

  18. Chromatic changes to artificial irises produced using different techniques

    Science.gov (United States)

    Bannwart, Lisiane Cristina; Goiato, Marcelo Coelho; dos Santos, Daniela Micheline; Moreno, Amália; Pesqueira, Aldiéris Alves; Haddad, Marcela Filié; Andreotti, Agda Marobo; de Medeiros, Rodrigo Antonio

    2013-05-01

    Ocular prostheses are important determinants of their users' aesthetic recovery and self-esteem. Because of use, ocular prostheses longevity is strongly affected by instability of the iris color due to polymerization. The goal of this study is to examine how the color of the artificial iris button is affected by different techniques of artificial wear and by the application of varnish following polymerization of the colorless acrylic resin that covers the colored paint. We produce 60 samples (n=10) according to the wear technique applied: conventional technique without varnish (PE); conventional technique with varnish (PEV); technique involving a prefabricated cap without varnish (CA); technique involving a prefabricated cap with varnish (CAV); technique involving inverted painting without varnish (PI); and technique involving inverted painting with varnish (PIV). Color readings using a spectrophotometer are taken before and after polymerization. We submitted the data obtained to analyses of variance and Tukey's test (Pimprove color stability.

  19. APPLYING ARTIFICIAL INTELLIGENCE TECHNIQUES TO HUMAN-COMPUTER INTERFACES

    DEFF Research Database (Denmark)

    Sonnenwald, Diane H.

    1988-01-01

    A description is given of UIMS (User Interface Management System), a system using a variety of artificial intelligence techniques to build knowledge-based user interfaces combining functionality and information from a variety of computer systems that maintain, test, and configure customer telephone...... and data networks. Three artificial intelligence (AI) techniques used in UIMS are discussed, namely, frame representation, object-oriented programming languages, and rule-based systems. The UIMS architecture is presented, and the structure of the UIMS is explained in terms of the AI techniques....

  20. Contamination Control Techniques

    Energy Technology Data Exchange (ETDEWEB)

    EBY, J.L.

    2000-05-16

    Welcome to a workshop on contamination Control techniques. This work shop is designed for about two hours. Attendee participation is encouraged during the workshop. We will address different topics within contamination control techniques; present processes, products and equipment used here at Hanford and then open the floor to you, the attendees for your input on the topics.

  1. Contamination Control Techniques

    International Nuclear Information System (INIS)

    Welcome to a workshop on contamination Control techniques. This work shop is designed for about two hours. Attendee participation is encouraged during the workshop. We will address different topics within contamination control techniques; present processes, products and equipment used here at Hanford and then open the floor to you, the attendees for your input on the topics

  2. Electronic artificial hand controlled by reconstructed digit

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Objecive: To treat the loss of part of the forearm with a multi-dimension-freedom electronic artificial hand,which is controlled by a reconstructed finger transplanted from the second toe to the forearm stump.Methods: The female patient was 19 years old, whose right hand and wrist were crushed into pieces by machine at work and her forearm was amputated at the level of 8 cm proximal to the wrist. The second toe of her left foot was transplanted to reconstruct the digit onto the stump of her forearm. Two months after the transplantation, the patient was transferred to the rehabilitation center for further rehabilitation training, which consisted of: training for adaptation to weight bearing, testing and training of sensibility to weight. testing and training for stability of the hand, and testing and training for the controlling function of the reconstructed digit. Results: The transplanted toe survived well. After rehabilitation the reconstructed digit functioned well. In testing the performance under control mandate, the accuracy rate of the electronic artificial hand was 100%.Conclusions: A 100% accuracy rate of the electronic artificial hand can be achieved by transplantation of the toe onto the stump of the forearm. It provides a useful pathway and an example for improvement of control accuracy of a multiple-freedom electronic artificial hand and reduction of false action.

  3. Artificial Intelligence based technique for BTS placement

    Science.gov (United States)

    Alenoghena, C. O.; Emagbetere, J. O.; Aibinu, A. M.

    2013-12-01

    The increase of the base transceiver station (BTS) in most urban areas can be traced to the drive by network providers to meet demand for coverage and capacity. In traditional network planning, the final decision of BTS placement is taken by a team of radio planners, this decision is not fool proof against regulatory requirements. In this paper, an intelligent based algorithm for optimal BTS site placement has been proposed. The proposed technique takes into consideration neighbour and regulation considerations objectively while determining cell site. The application will lead to a quantitatively unbiased evaluated decision making process in BTS placement. An experimental data of a 2km by 3km territory was simulated for testing the new algorithm, results obtained show a 100% performance of the neighbour constrained algorithm in BTS placement optimization. Results on the application of GA with neighbourhood constraint indicate that the choices of location can be unbiased and optimization of facility placement for network design can be carried out.

  4. Artificial Intelligence based technique for BTS placement

    International Nuclear Information System (INIS)

    The increase of the base transceiver station (BTS) in most urban areas can be traced to the drive by network providers to meet demand for coverage and capacity. In traditional network planning, the final decision of BTS placement is taken by a team of radio planners, this decision is not fool proof against regulatory requirements. In this paper, an intelligent based algorithm for optimal BTS site placement has been proposed. The proposed technique takes into consideration neighbour and regulation considerations objectively while determining cell site. The application will lead to a quantitatively unbiased evaluated decision making process in BTS placement. An experimental data of a 2km by 3km territory was simulated for testing the new algorithm, results obtained show a 100% performance of the neighbour constrained algorithm in BTS placement optimization. Results on the application of GA with neighbourhood constraint indicate that the choices of location can be unbiased and optimization of facility placement for network design can be carried out

  5. Application of Artificial Intelligence Techniques in Uninhabited Aerial Vehicle Flight

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2004-01-01

    This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA Southeastearn University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

  6. Application of Artificial Intelligence Techniques in Uninhabitated Aerial Vehicle Flight

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2003-01-01

    This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA southeastern University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

  7. Performance of artificial neural networks and genetical evolved artificial neural networks unfolding techniques

    International Nuclear Information System (INIS)

    With the Bonner spheres spectrometer neutron spectrum is obtained through an unfolding procedure. Monte Carlo methods, Regularization, Parametrization, Least-squares, and Maximum Entropy are some of the techniques utilized for unfolding. In the last decade methods based on Artificial Intelligence Technology have been used. Approaches based on Genetic Algorithms and Artificial Neural Networks (Ann) have been developed in order to overcome the drawbacks of previous techniques. Nevertheless the advantages of Ann still it has some drawbacks mainly in the design process of the network, vg the optimum selection of the architectural and learning Ann parameters. In recent years the use of hybrid technologies, combining Ann and genetic algorithms, has been utilized to. In this work, several Ann topologies were trained and tested using Ann and Genetically Evolved Artificial Neural Networks in the aim to unfold neutron spectra using the count rates of a Bonner sphere spectrometer. Here, a comparative study of both procedures has been carried out. (Author)

  8. Performance of artificial neural networks and genetical evolved artificial neural networks unfolding techniques

    Energy Technology Data Exchange (ETDEWEB)

    Ortiz R, J. M. [Escuela Politecnica Superior, Departamento de Electrotecnia y Electronica, Avda. Menendez Pidal s/n, Cordoba (Spain); Martinez B, M. R.; Vega C, H. R. [Universidad Autonoma de Zacatecas, Unidad Academica de Estudios Nucleares, Calle Cipres No. 10, Fracc. La Penuela, 98068 Zacatecas (Mexico); Gallego D, E.; Lorente F, A. [Universidad Politecnica de Madrid, Departamento de Ingenieria Nuclear, ETSI Industriales, C. Jose Gutierrez Abascal 2, 28006 Madrid (Spain); Mendez V, R.; Los Arcos M, J. M.; Guerrero A, J. E., E-mail: morvymm@yahoo.com.m [CIEMAT, Laboratorio de Metrologia de Radiaciones Ionizantes, Avda. Complutense 22, 28040 Madrid (Spain)

    2011-02-15

    With the Bonner spheres spectrometer neutron spectrum is obtained through an unfolding procedure. Monte Carlo methods, Regularization, Parametrization, Least-squares, and Maximum Entropy are some of the techniques utilized for unfolding. In the last decade methods based on Artificial Intelligence Technology have been used. Approaches based on Genetic Algorithms and Artificial Neural Networks (Ann) have been developed in order to overcome the drawbacks of previous techniques. Nevertheless the advantages of Ann still it has some drawbacks mainly in the design process of the network, vg the optimum selection of the architectural and learning Ann parameters. In recent years the use of hybrid technologies, combining Ann and genetic algorithms, has been utilized to. In this work, several Ann topologies were trained and tested using Ann and Genetically Evolved Artificial Neural Networks in the aim to unfold neutron spectra using the count rates of a Bonner sphere spectrometer. Here, a comparative study of both procedures has been carried out. (Author)

  9. Artificial Intelligence for Controlling Robotic Aircraft

    Science.gov (United States)

    Krishnakumar, Kalmanje

    2005-01-01

    A document consisting mostly of lecture slides presents overviews of artificial-intelligence-based control methods now under development for application to robotic aircraft [called Unmanned Aerial Vehicles (UAVs) in the paper] and spacecraft and to the next generation of flight controllers for piloted aircraft. Following brief introductory remarks, the paper presents background information on intelligent control, including basic characteristics defining intelligent systems and intelligent control and the concept of levels of intelligent control. Next, the paper addresses several concepts in intelligent flight control. The document ends with some concluding remarks, including statements to the effect that (1) intelligent control architectures can guarantee stability of inner control loops and (2) for UAVs, intelligent control provides a robust way to accommodate an outer-loop control architecture for planning and/or related purposes.

  10. Artificial intelligence techniques for industrial applications in job shop scheduling.

    OpenAIRE

    Townsend, Wade Benton

    1983-01-01

    The application of AI (artificial intelligence) techniques to the scheduling of industrial production operations offers a promising new approach to a scheduling problem of great magnitude and complexity. Foremost among these techniques is a powerful knowledge representation language that is capable of modeling the production environment at all levels of detail. The capturing of such complexity in the data base enables the computer to generate feasible schedules from a very large solution spac...

  11. Application of artificial intelligence techniques to TRR operation

    International Nuclear Information System (INIS)

    It has been over ten years since TRR had its initial critical. To collect the experiences of shift operators and technique staffs and transfer these experts' knowledge to a computer and build an expert system is a typical application of artificial intelligence techniques to nuclear business. The system can provide the correct information of TRR operation for shift personnel, new staffs and other technical people

  12. The role of artificial intelligence techniques in scheduling systems

    Science.gov (United States)

    Geoffroy, Amy L.; Britt, Daniel L.; Gohring, John R.

    1990-01-01

    Artificial Intelligence (AI) techniques provide good solutions for many of the problems which are characteristic of scheduling applications. However, scheduling is a large, complex heterogeneous problem. Different applications will require different solutions. Any individual application will require the use of a variety of techniques, including both AI and conventional software methods. The operational context of the scheduling system will also play a large role in design considerations. The key is to identify those places where a specific AI technique is in fact the preferable solution, and to integrate that technique into the overall architecture.

  13. An integrated multivariable artificial pancreas control system.

    Science.gov (United States)

    Turksoy, Kamuran; Quinn, Lauretta T; Littlejohn, Elizabeth; Cinar, Ali

    2014-05-01

    The objective was to develop a closed-loop (CL) artificial pancreas (AP) control system that uses continuous measurements of glucose concentration and physiological variables, integrated with a hypoglycemia early alarm module to regulate glucose concentration and prevent hypoglycemia. Eleven open-loop (OL) and 9 CL experiments were performed. A multivariable adaptive artificial pancreas (MAAP) system was used for the first 6 CL experiments. An integrated multivariable adaptive artificial pancreas (IMAAP) system consisting of MAAP augmented with a hypoglycemia early alarm system was used during the last 3 CL experiments. Glucose values and physical activity information were measured and transferred to the controller every 10 minutes and insulin suggestions were entered to the pump manually. All experiments were designed to be close to real-life conditions. Severe hypoglycemic episodes were seen several times during the OL experiments. With the MAAP system, the occurrence of severe hypoglycemia was decreased significantly (P < .01). No hypoglycemia was seen with the IMAAP system. There was also a significant difference (P < .01) between OL and CL experiments with regard to percentage of glucose concentration (54% vs 58%) that remained within target range (70-180 mg/dl). Integration of an adaptive control and hypoglycemia early alarm system was able to keep glucose concentration values in target range in patients with type 1 diabetes. Postprandial hypoglycemia and exercise-induced hypoglycemia did not occur when this system was used. Physical activity information improved estimation of the blood glucose concentration and effectiveness of the control system.

  14. A quality by design approach using artificial intelligence techniques to control the critical quality attributes of ramipril tablets manufactured by wet granulation.

    Science.gov (United States)

    Aksu, Buket; Paradkar, Anant; de Matas, Marcel; Özer, Özgen; Güneri, Tamer; York, Peter

    2013-02-01

    Quality by design (QbD) is an essential part of the modern approach to pharmaceutical quality. This study was conducted in the framework of a QbD project involving ramipril tablets. Preliminary work included identification of the critical quality attributes (CQAs) and critical process parameters (CPPs) based on the quality target product profiles (QTPPs) using the historical data and risk assessment method failure mode and effect analysis (FMEA). Compendial and in-house specifications were selected as QTPPs for ramipril tablets. CPPs that affected the product and process were used to establish an experimental design. The results thus obtained can be used to facilitate definition of the design space using tools such as design of experiments (DoE), the response surface method (RSM) and artificial neural networks (ANNs). The project was aimed at discovering hidden knowledge associated with the manufacture of ramipril tablets using a range of artificial intelligence-based software, with the intention of establishing a multi-dimensional design space that ensures consistent product quality. At the end of the study, a design space was developed based on the study data and specifications, and a new formulation was optimized. On the basis of this formulation, a new laboratory batch formulation was prepared and tested. It was confirmed that the explored formulation was within the design space.

  15. Analysis of dynamic conflicts by techniques of artificial intelligence

    OpenAIRE

    Shinar, Josef

    1989-01-01

    Dynamic conflicts exhibit differentiel game characteristics and their analysis by any method which disregards this feature may be, by definition, futile. Unfortunately, realistic conflicts may have an intricate information structure and a complex hierarchy which don't fit in the classical differential game formulation. Moreover, in many cases even well formulated differential games are not solvable. In the recent years great progress has been made in artificial intelligence techniques, put in...

  16. An application of artificial intelligence theory to reconfigurable flight control

    Science.gov (United States)

    Handelman, David A.

    1987-01-01

    Artificial intelligence techniques were used along with statistical hpyothesis testing and modern control theory, to help the pilot cope with the issues of information, knowledge, and capability in the event of a failure. An intelligent flight control system is being developed which utilizes knowledge of cause and effect relationships between all aircraft components. It will screen the information available to the pilots, supplement his knowledge, and most importantly, utilize the remaining flight capability of the aircraft following a failure. The list of failure types the control system will accommodate includes sensor failures, actuator failures, and structural failures.

  17. Inspection of an artificial heart by the neutron radiography technique

    CERN Document Server

    Pugliesi, R; Andrade, M L G; Menezes, M O; Pereira, M A S; Maizato, M J S

    1999-01-01

    The neutron radiography technique was employed to inspect an artificial heart prototype which is being developed to provide blood circulation for patients expecting heart transplant surgery. The radiographs have been obtained by the direct method with a gadolinium converter screen along with the double coated Kodak-AA emulsion film. The artificial heart consists of a flexible plastic membrane located inside a welded metallic cavity, which is employed for blood pumping purposes. The main objective of the present inspection was to identify possible damages in this plastic membrane, produced during the welding process of the metallic cavity. The obtained radiographs were digitized as well as analysed in a PC and the improved images clearly identify several damages in the plastic membrane, suggesting changes in the welding process.

  18. Artificial proprioceptive feedback for myoelectric control.

    Science.gov (United States)

    Pistohl, Tobias; Joshi, Deepak; Ganesh, Gowrishankar; Jackson, Andrew; Nazarpour, Kianoush

    2015-05-01

    The typical control of myoelectric interfaces, whether in laboratory settings or real-life prosthetic applications, largely relies on visual feedback because proprioceptive signals from the controlling muscles are either not available or very noisy. We conducted a set of experiments to test whether artificial proprioceptive feedback, delivered noninvasively to another limb, can improve control of a two-dimensional myoelectrically-controlled computer interface. In these experiments, participants were required to reach a target with a visual cursor that was controlled by electromyogram signals recorded from muscles of the left hand, while they were provided with an additional proprioceptive feedback on their right arm by moving it with a robotic manipulandum. Provision of additional artificial proprioceptive feedback improved the angular accuracy of their movements when compared to using visual feedback alone but did not increase the overall accuracy quantified with the average distance between the cursor and the target. The advantages conferred by proprioception were present only when the proprioceptive feedback had similar orientation to the visual feedback in the task space and not when it was mirrored, demonstrating the importance of congruency in feedback modalities for multi-sensory integration. Our results reveal the ability of the human motor system to learn new inter-limb sensory-motor associations; the motor system can utilize task-related sensory feedback, even when it is available on a limb distinct from the one being actuated. In addition, the proposed task structure provides a flexible test paradigm by which the effectiveness of various sensory feedback and multi-sensory integration for myoelectric prosthesis control can be evaluated.

  19. Implementation and Validation of Artificial Intelligence Techniques for Robotic Surgery

    Directory of Open Access Journals (Sweden)

    Aarshay Jain

    2014-03-01

    Full Text Available The primary focus of this study is implementation of Artificial Intelligence (AI technique for developing an inverse kinematics solution for the Raven-IITM surgical research robot [1]. First, the kinematic model of the Raven-IITM robot was analysed along with the proposed analytical solution [2] for inverse kinematics problem. Next, The Artificial Neural Network (ANN techniques was implemented. The training data for the same was careful selected by keeping manipulability constraints in mind. Finally, the results were verified using elliptical trajectories. The originally proposed analytical solution was found to be computationally inefficient, gave multiple solutions and its existence necessitates the use of the Standard Raven-IITM Tool [2]. The solution devised using ANN technique gave a single solution which was thirteen times faster than the original solution. Moreover, it is generic in nature and can be used for any type of tool. Thus, a novel solution for solving the inverse kinematics problem of the Raven-II surgical robot was formulated and confirmed.

  20. Artificial intelligence techniques for scheduling Space Shuttle missions

    Science.gov (United States)

    Henke, Andrea L.; Stottler, Richard H.

    1994-01-01

    Planning and scheduling of NASA Space Shuttle missions is a complex, labor-intensive process requiring the expertise of experienced mission planners. We have developed a planning and scheduling system using combinations of artificial intelligence knowledge representations and planning techniques to capture mission planning knowledge and automate the multi-mission planning process. Our integrated object oriented and rule-based approach reduces planning time by orders of magnitude and provides planners with the flexibility to easily modify planning knowledge and constraints without requiring programming expertise.

  1. Development of a Car Racing Simulator Game Using Artificial Intelligence Techniques

    Directory of Open Access Journals (Sweden)

    Marvin T. Chan

    2015-01-01

    Full Text Available This paper presents a car racing simulator game called Racer, in which the human player races a car against three game-controlled cars in a three-dimensional environment. The objective of the game is not to defeat the human player, but to provide the player with a challenging and enjoyable experience. To ensure that this objective can be accomplished, the game incorporates artificial intelligence (AI techniques, which enable the cars to be controlled in a manner that mimics natural driving. The paper provides a brief history of AI techniques in games, presents the use of AI techniques in contemporary video games, and discusses the AI techniques that were implemented in the development of Racer. A comparison of the AI techniques implemented in the Unity platform with traditional AI search techniques is also included in the discussion.

  2. Training Software in Artificial-Intelligence Computing Techniques

    Science.gov (United States)

    Howard, Ayanna; Rogstad, Eric; Chalfant, Eugene

    2005-01-01

    The Artificial Intelligence (AI) Toolkit is a computer program for training scientists, engineers, and university students in three soft-computing techniques (fuzzy logic, neural networks, and genetic algorithms) used in artificial-intelligence applications. The program promotes an easily understandable tutorial interface, including an interactive graphical component through which the user can gain hands-on experience in soft-computing techniques applied to realistic example problems. The tutorial provides step-by-step instructions on the workings of soft-computing technology, whereas the hands-on examples allow interaction and reinforcement of the techniques explained throughout the tutorial. In the fuzzy-logic example, a user can interact with a robot and an obstacle course to verify how fuzzy logic is used to command a rover traverse from an arbitrary start to the goal location. For the genetic algorithm example, the problem is to determine the minimum-length path for visiting a user-chosen set of planets in the solar system. For the neural-network example, the problem is to decide, on the basis of input data on physical characteristics, whether a person is a man, woman, or child. The AI Toolkit is compatible with the Windows 95,98, ME, NT 4.0, 2000, and XP operating systems. A computer having a processor speed of at least 300 MHz, and random-access memory of at least 56MB is recommended for optimal performance. The program can be run on a slower computer having less memory, but some functions may not be executed properly.

  3. Optimal control learning with artificial neural networks

    International Nuclear Information System (INIS)

    This paper shows neural networks capabilities in optimal control applications of non linear dynamic systems. Our method is issued of a classical method concerning the direct research of the optimal control using gradient techniques. We show that neural approach and backpropagation paradigm are able to solve efficiently equations relative to necessary conditions for an optimizing solution. We have taken into account the known capabilities of multi layered networks in approximation functions. And for dynamic systems, we have generalized the indirect learning of inverse model adaptive architecture that is capable to define an optimal control in relation to a temporal criterion. (orig.)

  4. Intrusion Detection Systems Based on Artificial Intelligence Techniques in Wireless Sensor Networks

    OpenAIRE

    Nabil Ali Alrajeh; Lloret, J

    2013-01-01

    Intrusion detection system (IDS) is regarded as the second line of defense against network anomalies and threats. IDS plays an important role in network security. There are many techniques which are used to design IDSs for specific scenario and applications. Artificial intelligence techniques are widely used for threats detection. This paper presents a critical study on genetic algorithm, artificial immune, and artificial neural network (ANN) based IDSs techniques used in wireless sensor netw...

  5. Generating Artificial Event Logs with Sufficient Discriminatory Power to Compare Process Discovery Techniques

    OpenAIRE

    Jouck, Toon; Depaire, Benoit

    2014-01-01

    Past research revealed issues with artificial event data used for comparative analysis of process mining algorithms. The aim of this research is to design, implement and validate a framework for producing artificial event logs which should increase discriminatory power of artificial event logs when evaluating process discovery techniques.

  6. Artificial intelligence and information-control systems of robots - 87

    International Nuclear Information System (INIS)

    Independent research areas of artificial intelligence represent the following problems: automatic problem solving and new knowledge discovering, automatic program synthesis, natural language, picture and scene recognition and understanding, intelligent control systems of robots equipped with sensoric subsystems, dialogue of two knowledge systems, as well as studying and modelling higher artificial intelligence attributes, such as emotionality and personality. The 4th Conference draws on the problems treated at the preceding Conferences, and presents the most recent knowledge on the following topics: theoretical problems of artificial intelligence, knowledge-based systems, expert systems, perception and pattern recognition, robotics, intelligent computer-aided design, special-purpose computer systems for artificial intelligence and robotics

  7. Macrocell path loss prediction using artificial intelligence techniques

    Science.gov (United States)

    Usman, Abraham U.; Okereke, Okpo U.; Omizegba, Elijah E.

    2014-04-01

    The prediction of propagation loss is a practical non-linear function approximation problem which linear regression or auto-regression models are limited in their ability to handle. However, some computational Intelligence techniques such as artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFISs) have been shown to have great ability to handle non-linear function approximation and prediction problems. In this study, the multiple layer perceptron neural network (MLP-NN), radial basis function neural network (RBF-NN) and an ANFIS network were trained using actual signal strength measurement taken at certain suburban areas of Bauchi metropolis, Nigeria. The trained networks were then used to predict propagation losses at the stated areas under differing conditions. The predictions were compared with the prediction accuracy of the popular Hata model. It was observed that ANFIS model gave a better fit in all cases having higher R2 values in each case and on average is more robust than MLP and RBF models as it generalises better to a different data.

  8. Parameter tuning of PVD process based on artificial intelligence technique

    Science.gov (United States)

    Norlina, M. S.; Diyana, M. S. Nor; Mazidah, P.; Rusop, M.

    2016-07-01

    In this study, an artificial intelligence technique is proposed to be implemented in the parameter tuning of a PVD process. Due to its previous adaptation in similar optimization problems, genetic algorithm (GA) is selected to optimize the parameter tuning of the RF magnetron sputtering process. The most optimized parameter combination obtained from GA's optimization result is expected to produce the desirable zinc oxide (ZnO) thin film from the sputtering process. The parameters involved in this study were RF power, deposition time and substrate temperature. The algorithm was tested to optimize the 25 datasets of parameter combinations. The results from the computational experiment were then compared with the actual result from the laboratory experiment. Based on the comparison, GA had shown that the algorithm was reliable to optimize the parameter combination before the parameter tuning could be done to the RF magnetron sputtering machine. In order to verify the result of GA, the algorithm was also been compared to other well known optimization algorithms, which were, particle swarm optimization (PSO) and gravitational search algorithm (GSA). The results had shown that GA was reliable in solving this RF magnetron sputtering process parameter tuning problem. GA had shown better accuracy in the optimization based on the fitness evaluation.

  9. Crack identification based on synthetic artificial intelligent technique

    Energy Technology Data Exchange (ETDEWEB)

    Shim, Mun Bo; Suh, Myung Won [Sungkyunkwan Univ., Suwon (Korea, Republic of)

    2001-07-01

    It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a Continuous Evolutionary Algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising.

  10. Alpha efficiency under TL and OSL - A subtraction technique using OSL and TL to detect artificial irradiation

    International Nuclear Information System (INIS)

    With the development of thermoluminescence (TL) and optically stimulated luminescence (OSL) to determine the authenticity of old ceramics, forgers use artificial irradiation by gamma ray to age modern productions. Besides fraudulent action, objects can be exposed to various sources of X-rays (e.g. radiography, security control at airports). For all these reasons, the determination of artificial irradiation is an important topic for dating art objects. The main technique to identify artificial irradiations is the subtraction technique. It is based on the fact that alpha efficiency varies according to the luminescence technique (fine grain, coarse grains, predose, OSL). Having observed a rather significant difference of alpha efficiency for TL and OSL, we propose a new subtraction technique using OSL and TL of fine grains.

  11. Alpha efficiency under TL and OSL - A subtraction technique using OSL and TL to detect artificial irradiation

    Energy Technology Data Exchange (ETDEWEB)

    Zink, A.J.C., E-mail: antoine.zink@culture.gouv.f [Laboratoire du Centre de Recherche et de Restauration des Musees de France, C2RMF, MCC, CNRS, Palais du Louvre, Porte des lions, 14 quai F. Mitterrand, 75001 Paris (France); Dabis, S.; Porto, E.; Castaing, J. [Laboratoire du Centre de Recherche et de Restauration des Musees de France, C2RMF, MCC, CNRS, Palais du Louvre, Porte des lions, 14 quai F. Mitterrand, 75001 Paris (France)

    2010-03-15

    With the development of thermoluminescence (TL) and optically stimulated luminescence (OSL) to determine the authenticity of old ceramics, forgers use artificial irradiation by gamma ray to age modern productions. Besides fraudulent action, objects can be exposed to various sources of X-rays (e.g. radiography, security control at airports). For all these reasons, the determination of artificial irradiation is an important topic for dating art objects. The main technique to identify artificial irradiations is the subtraction technique. It is based on the fact that alpha efficiency varies according to the luminescence technique (fine grain, coarse grains, predose, OSL). Having observed a rather significant difference of alpha efficiency for TL and OSL, we propose a new subtraction technique using OSL and TL of fine grains.

  12. Advanced Wavefront Control Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Olivier, S S; Brase, J M; Avicola, K; Thompson, C A; Kartz, M W; Winters, S; Hartley, R; Wihelmsen, J; Dowla, F V; Carrano, C J; Bauman, B J; Pennington, D M; Lande, D; Sawvel, R M; Silva, D A; Cooke, J B; Brown, C G

    2001-02-21

    Programs at LLNL that involve large laser systems--ranging from the National Ignition Facility to new tactical laser weapons--depend on the maintenance of laser beam quality through precise control of the optical wavefront. This can be accomplished using adaptive optics, which compensate for time-varying aberrations that are often caused by heating in a high-power laser system. Over the past two decades, LLNL has developed a broad capability in adaptive optics technology for both laser beam control and high-resolution imaging. This adaptive optics capability has been based on thin deformable glass mirrors with individual ceramic actuators bonded to the back. In the case of high-power lasers, these adaptive optics systems have successfully improved beam quality. However, as we continue to extend our applications requirements, the existing technology base for wavefront control cannot satisfy them. To address this issue, this project studied improved modeling tools to increase our detailed understanding of the performance of these systems, and evaluated novel approaches to low-order wavefront control that offer the possibility of reduced cost and complexity. We also investigated improved beam control technology for high-resolution wavefront control. Many high-power laser systems suffer from high-spatial-frequency aberrations that require control of hundreds or thousands of phase points to provide adequate correction. However, the cost and size of current deformable mirrors can become prohibitive for applications requiring more than a few tens of phase control points. New phase control technologies are becoming available which offer control of many phase points with small low-cost devices. The goal of this project was to expand our wavefront control capabilities with improved modeling tools, new devices that reduce system cost and complexity, and extensions to high spatial and temporal frequencies using new adaptive optics technologies. In FY 99, the second year of

  13. Artificial Intelligence Techniques in Real-Time Strategy Games - Architecture and Combat Behavior

    OpenAIRE

    Stene, Sindre Berg

    2006-01-01

    The general purpose of this research is to investigate the possibilities offered for the use of Artificial Intelligence theory and methods in advanced game environments. The real-time strategy (RTS) game genre is investigated in detail, and an architecture and solutions to some common issues are presented. An RTS AI controlled opponent named KAI is implemented for the TA Spring game engine in order to advance the state of the art in usin AI techniques in games and to gain some insight int...

  14. Development and Physical Control Research on Prototype Artificial Leg

    OpenAIRE

    Fei Li; Fuming Zhang; Hualong Xie

    2016-01-01

    To provide an ideal platform for research on intelligent bionic leg (IBL), this paper proposes a model of a biped robot with heterogeneous legs (BRHL). A prototype of an artificial leg is developed based on biological structure and motion principle analysis of human lower extremities. With regard to the driving sources, servomotors are chosen for the hip joint and ankle joint, while pneumatic muscle actuators (PMAs) are chosen for the knee joint. The control system of the bionic artificial le...

  15. Application of Artificial Intelligence and Data Mining Techniques to Financial Markets

    OpenAIRE

    Katarína Hilovska; Peter Koncz

    2012-01-01

    The aim of artificial intelligence is to discover mechanisms of adaptation in a changing environment with utilisation of intelligence, for instance in the ability to exclude unlikely solutions. Artificial intelligence methods have extensive application in different fields such as medicine, games, transportation, or heavy industry. This paper deals with interdisciplinary issues – interconnection of artificial intelligence and finance. The paper briefly describes techniques of data mining, expe...

  16. The application of neural networks with artificial intelligence technique in the modeling of industrial processes

    International Nuclear Information System (INIS)

    Neural networks are a relatively new artificial intelligence technique that emulates the behavior of biological neural systems in digital software or hardware. These networks can 'learn', automatically, complex relationships among data. This feature makes the technique very useful in modeling processes for which mathematical modeling is difficult or impossible. The work described here outlines some examples of the application of neural networks with artificial intelligence technique in the modeling of industrial processes.

  17. Optimal fuel loading pattern design using artificial intelligence techniques

    International Nuclear Information System (INIS)

    The Optimal Fuel Shuffling System (OFSS) is developed for optimal design of PWR fuel loading pattern. OFSS is a hybrid system that a rule based system, a fuzzy logic, and an artificial neural network are connected each other. The rule based system classifies loading patterns into two classes using several heuristic rules and a fuzzy rule. A fuzzy rule is introduced to achieve more effective and fast searching. Its membership function is automatically updated in accordance with the prediction results. The artificial neural network predicts core parameters for the patterns generated from the rule based system. The back-propagation network is used for fast prediction of core parameters. The artificial neural network and the fuzzy logic can be used as the tool for improvement of existing algorithm's capabilities. OFSS was demonstrated and validated for cycle 1 of Kori unit 1 PWR. (Author)

  18. Artificial Neural Networks Based Modeling and Control of Continuous Stirred Tank Reactor

    Directory of Open Access Journals (Sweden)

    R. S.M.N. Malar

    2009-01-01

    Full Text Available Continuous Stirred Tank Reactor (CSTR is one of the common reactors in chemical plant. Problem statement: Developing a model incorporating the nonlinear dynamics of the system warrants lot of computation. An efficient control of the product concentration can be achieved only through accurate model. Approach: In this study, attempts were made to alleviate the above mentioned problem using “Artificial Intelligence” (AI techniques. One of the AI techniques namely Artificial Neural Networks (ANN was used to model the CSTR incorporating its non-linear characteristics. Two nonlinear models based control strategies namely internal model control and direct inverse control were designed using the neural networks and applied to the control of isothermal CSTR. Results: The simulation results for the above control schemes with set point tracking were presented. Conclusion: Results indicated that neural networks can learn accurate models and give good non-linear control when model equations are not known.

  19. An Efficient Technique to Implement Similarity Measures in Text Document Clustering using Artificial Neural Networks Algorithm

    Directory of Open Access Journals (Sweden)

    K. Selvi

    2014-12-01

    Full Text Available Pattern recognition, envisaging supervised and unsupervised method, optimization, associative memory and control process are some of the diversified troubles that can be resolved by artificial neural networks. Problem identified: Of late, discovering the required information in massive quantity of data is the challenging tasks. The model of similarity evaluation is the central element in accomplishing a perceptive of variables and perception that encourage behavior and mediate concern. This study proposes Artificial Neural Networks algorithms to resolve similarity measures. In order to apply singular value decomposition the frequency of word pair is established in the given document. (1 Tokenization: The splitting up of a stream of text into words, phrases, signs, or other significant parts is called tokenization. (2 Stop words: Preceding or succeeding to processing natural language data, the words that are segregated is called stop words. (3 Porter stemming: The main utilization of this algorithm is as part of a phrase normalization development that is characteristically completed while setting up in rank recovery technique. (4 WordNet: The compilation of lexical data base for the English language is called as WordNet Based on Artificial Neural Networks, the core part of this study work extends n-gram proposed algorithm. All the phonemes, syllables, letters, words or base pair corresponds in accordance to the application. Future work extends the application of this same similarity measures in various other neural network algorithms to accomplish improved results.

  20. Modeling of the height control system using artificial neural networks

    Directory of Open Access Journals (Sweden)

    A. R Tahavvor

    2016-09-01

    action. The mechanical parts were computer-generated by engineering software in assembled, exploded and standard two-dimensional drawing required for the manufacturing process. Carrier and framework of control unit and actuator mainly designed to have the capability to support and hold the hardware and sensor assembly in an easy mountable fashion. This arrangement performed feasibility of the movement and allocating of control unit along the travel length of belt above the conveyor unit. In this work a multilayer perceptron network with different training algorithm was used and it is found that the backpropagation algorithm with Levenberge-Marquardt learning rule was the best choice for this analysis because of the accurate and faster training procedure. The Levenberg-Marquardt algorithm was an iterative technique that locates the minimum of a multivariate function that was expressed as the sum of squares of nonlinear real-valued functions. It has become a standard technique for non-linear least-squares problems, widely adopted in a broad spectrum of disciplines. LM can be thought of as a combination of steepest descent and the Gauss-Newton method. When the current solution was far from the correct one, the algorithm behaves like a steepest descent method: slow, but guaranteed to converge. When the current solution is close to the correct solution, it becomes a Gauss-Newton method. The Levenberg algorithm is: 1. Do an update as directed by the rule above. 2. Evaluate the error at the new parameter vector. 3. If the error has increased as a result the update, then retract the step (i.e. reset the weights to their previous values and increase l by a factor of 10 or some such significant factor, then goes to (1 and try an update again. 4. If the error has decreased as a result of the update, then accept the step (i.e. keep the weights at their new values and decrease l by a factor of 10 or so. Results and Discussion The study of multi artificial neural network learning

  1. Study on optimization control method based on artificial neural network

    Institute of Scientific and Technical Information of China (English)

    FU Hua; SUN Shao-guang; XU Zhen-Iiang

    2005-01-01

    In the goal optimization and control optimization process the problems with common artificial neural network algorithm are unsure convergence, insufficient post-training network precision, and slow training speed, in which partial minimum value question tends to occur. This paper conducted an in-depth study on the causes of the limitations of the algorithm, presented a rapid artificial neural network algorithm, which is characterized by integrating multiple algorithms and by using their complementary advantages. The salient feature of the method is self-organization, which can effectively prevent the optimized results from tending to be partial minimum values. Overall optimization can be achieved with this method, goal function can be searched for in overall scope. With optimization control of coal mine ventilator as a practical application, the paper proves that by integrating multiple artificial neural network algorithms, best control optimization and goal optimized can be achieved.

  2. Myoelectric Control of Artificial Limb by Quantum Information Processing

    CERN Document Server

    Siomau, Michael

    2013-01-01

    Precise and elegant coordination of a prosthesis across many degrees of freedom is highly desired for rehabilitation of people with limb deficiency. Processing the electrical neural signals, collected from the surface of the remnant muscles of the stump, is a common way to activate certain function of the artificial limb. Based on the assumption that there are distinguishable and repeatable signal patterns among different types of muscular activation, the problem of the prosthesis control reduces to the pattern recognition. Widely accepted classical methods for pattern recognition, however, can not provide simultaneous and proportional control of the artificial limb. Here we show that quantum information processing of the neural signals allows us to overcome above difficulties suggesting a very simple scheme for myoelectric control of artificial limb with advanced functionalities.

  3. Techniques of Image Processing Based on Artificial Neural Networks

    Institute of Scientific and Technical Information of China (English)

    LI Wei-qing; WANG Qun; WANG Cheng-biao

    2006-01-01

    This paper presented an online quality inspection system based on artificial neural networks. Chromatism classification and edge detection are two difficult problems in glass steel surface quality inspection. Two artificial neural networks were made and the two problems were solved. The one solved chromatism classification. Hue,saturation and their probability of three colors, whose appearing probabilities were maximum in color histogram,were selected as input parameters, and the number of output node could be adjusted with the change of requirement. The other solved edge detection. In this neutral network, edge detection of gray scale image was able to be tested with trained neural networks for a binary image. It prevent the difficulty that the number of needed training samples was too large if gray scale images were directly regarded as training samples. This system is able to be applied to not only glass steel fault inspection but also other product online quality inspection and classification.

  4. Control system for solar tracking based on artificial vision; Sistema de control para seguimiento solar basado en vision artificial

    Energy Technology Data Exchange (ETDEWEB)

    Pacheco Ramirez, Jesus Horacio; Anaya Perez, Maria Elena; Benitez Baltazar, Victor Hugo [Universidad de onora, Hermosillo, Sonora (Mexico)]. E-mail: jpacheco@industrial.uson.mx; meanaya@industrial.uson.mx; vbenitez@industrial.uson.mx

    2010-11-15

    This work shows how artificial vision feedback can be applied to control systems. The control is applied to a solar panel in order to track the sun position. The algorithms to calculate the position of the sun and the image processing are developed in LabView. The responses obtained from the control show that it is possible to use vision for a control scheme in closed loop. [Spanish] El presente trabajo muestra la manera en la cual un sistema de control puede ser retroalimentado mediante vision artificial. El control es aplicado en un panel solar para realizar el seguimiento del sol a lo largo del dia. Los algoritmos para calcular la posicion del sol y para el tratamiento de la imagen fueron desarrollados en LabView. Las respuestas obtenidas del control muestran que es posible utilizar vision para un esquema de control en lazo cerrado.

  5. Artificial moment method for swarm robot formation control

    Institute of Scientific and Technical Information of China (English)

    XU WangBao; CHEN XueBo

    2008-01-01

    The purpose of this paper is to develop a general control method for swarm robot formation control.Firstly,an attraction-segment leader-follower formation graph is presented for formation representations.The model of swarm robot systems is described.According to the results and two kinds of artificial momenta defined as leader-attraction moment and follower-attraction moment,a novel artificial moment method is proposed for swarm robot formation control.The principle of the method is introduced and the motion controller of robots is designed.Finally,the stability of the formation control system is proved.The simulations show that both the formation representation graph and the formation control method are valid and feasible.

  6. Control approach development for variable recruitment artificial muscles

    Science.gov (United States)

    Jenkins, Tyler E.; Chapman, Edward M.; Bryant, Matthew

    2016-04-01

    This study characterizes hybrid control approaches for the variable recruitment of fluidic artificial muscles with double acting (antagonistic) actuation. Fluidic artificial muscle actuators have been explored by researchers due to their natural compliance, high force-to-weight ratio, and low cost of fabrication. Previous studies have attempted to improve system efficiency of the actuators through variable recruitment, i.e. using discrete changes in the number of active actuators. While current variable recruitment research utilizes manual valve switching, this paper details the current development of an online variable recruitment control scheme. By continuously controlling applied pressure and discretely controlling the number of active actuators, operation in the lowest possible recruitment state is ensured and working fluid consumption is minimized. Results provide insight into switching control scheme effects on working fluids, fabrication material choices, actuator modeling, and controller development decisions.

  7. Voice-Controlled Artificial Handspeak System

    Directory of Open Access Journals (Sweden)

    Carlo Fonda

    2014-01-01

    Full Text Available A man-machine interaction project is described which aims to establish an automated voice to sign language translator for communication with the deaf using integrated open technologies. The first prototype consists of a robotic hand designed with OpenSCAD and manufactured with a low-cost 3D printer ─which smoothly reproduces the alphabet of the sign language controlled by voice only. The core automation comprises an Arduino UNO controller used to activate a set of servo motors that follow instructions from a Raspberry Pi mini-computer having installed the open source speech recognition engine Julius. We discuss its features, limitations and possible future developments.

  8. ARTIFICIAL INTELLIGENCE PLANNING TECHNIQUES FOR ADAPTIVE VIRTUAL COURSE CONSTRUCTION

    Directory of Open Access Journals (Sweden)

    NÉSTOR DARÍO DUQUE

    2011-01-01

    Full Text Available El artículo tiene como objetivo proponer un modelo de planificación para la adaptación de cursos virtuales, basado en técnicas de inteligencia artificial, en particular usando el enfoque de sistema multi-agente (SMA y métodos de planificación en inteligencia artificial. El diseño y la implementación por medio de un SMA pedagógico y la definición de un framework para especificar la estrategia de adaptación permiten incorporar diversos enfoques pedagógicos y tecnológicos, de acuerdo a los puntos de vista del equipo de trabajo, lo cual resulta en una implementación e instalación concreta. Se incorpora un novedoso pre-planificador que permite la transparencia y la neutralidad en el modelo propuesto y también ofrece soporte para traducir los elementos del curso a las especificaciones de un problema de planificación. La última sección muestra la plataforma experimental SICAD + (Sistema Inteligente de Cursos ADaptativos, a través de un enfoque multiagente, que valida el modelo propuesto.

  9. Artificial Intelligence Techniques for Automatic Screening of Amblyogenic Factors

    Science.gov (United States)

    Van Eenwyk, Jonathan; Agah, Arvin; Giangiacomo, Joseph; Cibis, Gerhard

    2008-01-01

    Purpose To develop a low-cost automated video system to effectively screen children aged 6 months to 6 years for amblyogenic factors. Methods In 1994 one of the authors (G.C.) described video vision development assessment, a digitizable analog video-based system combining Brückner pupil red reflex imaging and eccentric photorefraction to screen young children for amblyogenic factors. The images were analyzed manually with this system. We automated the capture of digital video frames and pupil images and applied computer vision and artificial intelligence to analyze and interpret results. The artificial intelligence systems were evaluated by a tenfold testing method. Results The best system was the decision tree learning approach, which had an accuracy of 77%, compared to the “gold standard” specialist examination with a “refer/do not refer” decision. Criteria for referral were strabismus, including microtropia, and refractive errors and anisometropia considered to be amblyogenic. Eighty-two percent of strabismic individuals were correctly identified. High refractive errors were also correctly identified and referred 90% of the time, as well as significant anisometropia. The program was less correct in identifying more moderate refractive errors, below +5 and less than −7. Conclusions Although we are pursuing a variety of avenues to improve the accuracy of the automated analysis, the program in its present form provides acceptable cost benefits for detecting ambylogenic factors in children aged 6 months to 6 years. PMID:19277222

  10. Power system stabilizers based on modern control techniques

    Energy Technology Data Exchange (ETDEWEB)

    Malik, O.P.; Chen, G.P.; Zhang, Y.; El-Metwally, K. [Calgary Univ., AB (Canada). Dept. of Electrical and Computer Engineering

    1994-12-31

    Developments in digital technology have made it feasible to develop and implement improved controllers based on sophisticated control techniques. Power system stabilizers based on adaptive control, fuzzy logic and artificial networks are being developed. Each of these control techniques possesses unique features and strengths. In this paper, the relative performance of power systems stabilizers based on adaptive control, fuzzy logic and neural network, both in simulation studies and real time tests on a physical model of a power system, is presented and compared to that of a fixed parameter conventional power system stabilizer. (author) 16 refs., 45 figs., 3 tabs.

  11. Optimal haptic feedback control of artificial muscles

    Science.gov (United States)

    Chen, Daniel; Besier, Thor; Anderson, Iain; McKay, Thomas

    2014-03-01

    As our population ages, and trends in obesity continue to grow, joint degenerative diseases like osteoarthritis (OA) are becoming increasingly prevalent. With no cure currently in sight, the only effective treatments for OA are orthopaedic surgery and prolonged rehabilitation, neither of which is guaranteed to succeed. Gait retraining has tremendous potential to alter the contact forces in the joints due to walking, reducing the risk of one developing hip and knee OA. Dielectric Elastomer Actuators (DEAs) are being explored as a potential way of applying intuitive haptic feedback to alter a patient's walking gait. The main challenge with the use of DEAs in this application is producing large enough forces and strains to induce sensation when coupled to a patient's skin. A novel controller has been proposed to solve this issue. The controller uses simultaneous capacitive self-sensing and actuation which will optimally apply a haptic sensation to the patient's skin independent of variability in DEAs and patient geometries.

  12. Uniaxial aerodynamic attitude control of artificial satellites

    Science.gov (United States)

    Sazonov, V. V.

    1983-01-01

    Within the context of a simple mechanical model the paper examines the movement of a satellite with respect to the center of masses under conditions of uniaxial aerodynamic attitude control. The equations of motion of the satellite take account of the gravitational and restorative aerodynamic moments. It is presumed that the aerodynamic moment is much larger than the gravitational, and the motion equations contain a large parameter. A two-parameter integrated surface of these equations is constructed in the form of formal series in terms of negative powers of the large parameter, describing the oscillations and rotations of the satellite about its lengthwise axis, approximately oriented along the orbital tangent. It is proposed to treat such movements as nominal undisturbed motions of the satellite under conditions of aerodynamic attitude control. A numerical investigation is made for the above integrated surface.

  13. Voice-Controlled Artificial Handspeak System

    Directory of Open Access Journals (Sweden)

    Jonathan Gatti

    2014-04-01

    Full Text Available A man-machine interaction project is described whic h aims to establish an automated voice to sign language translator for communication with the deaf using integrated open technologies. The first prototype consists of a robotic hand designed with OpenSCAD and manufactured with a low-cost 3D printer which smoothly reproduces the alphabet of the sign language controlled by voice only. The core automation comprises an Arduino UNO controller used to activate a set of servo motors that follow instructions from a Raspberry Pi mini-computer havi ng installed the open source speech recognition eng ine Julius. We discuss its features, limitations and po ssible future developmen

  14. Use of nuclear techniques in biological control

    International Nuclear Information System (INIS)

    As pointed out by Benbrook (1996), pest management is at a crossroads, and there is a great need for new, biointensive pest management strategies. Among these approaches, biological control is a keystone. However, because of increasing concerns about the introduction of exotic natural enemies of insect pests and weeds (Howarth 1991, Delfosse 1997), the overall thrust of biological control has moved toward augmentative biological control, involving releases of established natural enemy species (Knipling 1992). This in turn has created a need to develop more cost-effective mass rearing technologies for beneficial insects. Nuclear techniques could play an especially important role in augmentative biological control, not only in facilitating mass rearing, but in several other ways, as indicated below. Recognising the potential value for use of nuclear techniques in biological control, the Insect and Pest Control Section of the Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture, International Atomic Energy Agency, sponsored a Consultants' Group Meeting on this subject in April 1997. The Group produced a document entitled Use of Nuclear Techniques in Biological Control: Managing Pests, Facilitating Trade and Protecting the Environment. The consultants included the authors of this paper as well as Ernest Delfosse (at that time, with the USDA-APHIS National Biological Control Institute), Garry Hill (Intl. Institute for Biological Control), Sinthya Penn (Beneficial Insectary), and Felipe Jeronimo (USDA-APHIS PPQ, Guatemala). The remarks presented in this paper reflect the thoughts presented by these consultants and other participants at the IAEA-sponsored meeting. Several potential uses for nuclear techniques were identified by the Consultants' Group, including: 1) improvements in rearing media (either artificial diets or natural hosts/prey), 2) provision of sterilised natural prey to be used as food during shipment, to ameliorate concerns relating to the

  15. Improved Space Surveillance Network (SSN) Scheduling using Artificial Intelligence Techniques

    Science.gov (United States)

    Stottler, D.

    There are close to 20,000 cataloged manmade objects in space, the large majority of which are not active, functioning satellites. These are tracked by phased array and mechanical radars and ground and space-based optical telescopes, collectively known as the Space Surveillance Network (SSN). A better SSN schedule of observations could, using exactly the same legacy sensor resources, improve space catalog accuracy through more complementary tracking, provide better responsiveness to real-time changes, better track small debris in low earth orbit (LEO) through efficient use of applicable sensors, efficiently track deep space (DS) frequent revisit objects, handle increased numbers of objects and new types of sensors, and take advantage of future improved communication and control to globally optimize the SSN schedule. We have developed a scheduling algorithm that takes as input the space catalog and the associated covariance matrices and produces a globally optimized schedule for each sensor site as to what objects to observe and when. This algorithm is able to schedule more observations with the same sensor resources and have those observations be more complementary, in terms of the precision with which each orbit metric is known, to produce a satellite observation schedule that, when executed, minimizes the covariances across the entire space object catalog. If used operationally, the results would be significantly increased accuracy of the space catalog with fewer lost objects with the same set of sensor resources. This approach inherently can also trade-off fewer high priority tasks against more lower-priority tasks, when there is benefit in doing so. Currently the project has completed a prototyping and feasibility study, using open source data on the SSN's sensors, that showed significant reduction in orbit metric covariances. The algorithm techniques and results will be discussed along with future directions for the research.

  16. Vibroacoustic Modeling of Mechanically Coupled Structures: Artificial Spring Technique Applied to Light and Heavy Mediums

    Directory of Open Access Journals (Sweden)

    L. Cheng

    1996-01-01

    Full Text Available This article deals with the modeling of vibrating structures immersed in both light and heavy fluids, and possible applications to noise control problems and industrial vessels containing fluids. A theoretical approach, using artificial spring systems to characterize the mechanical coupling between substructures, is extended to include fluid loading. A structure consisting of a plate-ended cylindrical shell and its enclosed acoustic cavity is analyzed. After a brief description of the proposed technique, a number of numerical results are presented. The analysis addresses the following specific issues: the coupling between the plate and the shell; the coupling between the structure and the enclosure; the possibilities and difficulties regarding internal soundproofing through modifications of the joint connections; and the effects of fluid loading on the vibration of the structure.

  17. Development and Physical Control Research on Prototype Artificial Leg

    Directory of Open Access Journals (Sweden)

    Fei Li

    2016-03-01

    Full Text Available To provide an ideal platform for research on intelligent bionic leg (IBL, this paper proposes a model of a biped robot with heterogeneous legs (BRHL. A prototype of an artificial leg is developed based on biological structure and motion principle analysis of human lower extremities. With regard to the driving sources, servomotors are chosen for the hip joint and ankle joint, while pneumatic muscle actuators (PMAs are chosen for the knee joint. The control system of the bionic artificial leg is designed and a physical experimental platform is established. The physical control experiments are done based on proportional-integral-derivative (PID control strategy. The experimental results show that such a system can realize the expected goals.

  18. Application of Isotope Techniques for the Estimation of Artificial Recharge

    International Nuclear Information System (INIS)

    Geochemical studies on the alluvial aquifer system near the Nakdong River were carried out for the basic investigation of the estimation of artificial recharge for the river bank filtration. In-situ data do not show any distinct difference between the pumping well and river. Most of waters belong Ca-HCO3 and Ca-SO4 types and show high Mn concentration. In the borehole installed with Multi-packer (MP) system, Na, Ca, Mg, HCO3 contents of the groundwater are increased with depth increasing. Cl and SO4 contents of the groundwater show the lowest values at the bottom level (18m depth) and Mn content is very high at the middle level (13.5m depth) of MP system. There is no distinct difference in the δ18O and D values and tritium content between MP, borehole and surface water samples. The sulfur isotope data indicate that the possible sulfur source is dissolution of sulfate mineral from sedimentary rock. Strontium isotope ratio shows a little differences between the pumping well and observation borehole samples. Nitrogen isotope data indicate that the nitrogen of water samples is originated from fertilizer or organic materials

  19. DIRECT TORQUE CONTROL FOR INDUCTION MOTOR USING INTELLIGENT TECHNIQUES

    Directory of Open Access Journals (Sweden)

    R.Toufouti

    2007-09-01

    Full Text Available In this paper, we propose two approach intelligent techniques of improvement of Direct Torque Control (DTC of Induction motor such as fuzzy logic (FL and artificial neural network (ANN, applied in switching select voltage vector .The comparison with conventional direct torque control (DTC, show that the use of the DTC_FL and DTC_ANN, reduced the torque, stator flux, and current ripples. The validity of the proposed methods is confirmed by the simulative results.

  20. Globally controlled artificial semiconducting molecules as quantum computers

    OpenAIRE

    Tribollet, Jerome

    2005-01-01

    Quantum computers are expected to be considerably more efficient than classical computers for the execution of some specific tasks. The difficulty in the practical implementation of thoose computers is to build a microscopic quantum system that can be controlled at a larger mesoscopic scale. Here I show that vertical lines of donor atoms embedded in an appropriate Zinc Oxide semiconductor structure can constitute artificial molecules that are as many copy of the same quantum computer. In this...

  1. Design Optimization Utilizing Dynamic Substructuring and Artificial Intelligence Techniques

    OpenAIRE

    Akcay Perdahcioglu, D.; Ellenbroek, M.H.M.; Hoogt, van der, P.J.M.; Boer

    2008-01-01

    In mechanical and structural systems, resonance may cause large strains and stresses which can lead to the failure of the system. Since it is often not possible to change the frequency content of the external load excitation, the phenomenon can only be avoided by updating the design of the structure. In this paper, a design optimization strategy based on the integration of the Component Mode Synthesis (CMS) method with numerical optimization techniques is presented. For reasons of numerical e...

  2. Application of artificial intelligence techniques in the engineering design process

    International Nuclear Information System (INIS)

    The proposed paper gives a proof of concept of the fact that, currently available techniques for handling non-algorithmic problems by computers can be successfully applied to partially automate the decision making processes in the engineering design synthesis. Several small expert systems have been developed for helping a novice engineer to perform finite-element analyses of various structural elements. The expert systems guide the novice through such processes as setting the boundary conditions, choice of materials and suggest changes in initial design to achieve the desired product. (author)

  3. Design And Analysis Of Artificial Neural Network Based Controller For Speed Control Of Induction Motor Using D T C

    Directory of Open Access Journals (Sweden)

    Kusuma Gottapu

    2014-04-01

    Full Text Available This paper presents an improved version of direct torque control (DTC based on Artificial Neural Network technique used for flux position estimation and sector selection. This controller mainly reduces the torque and flux ripples. Direct torque control of induction motor drive has quick torque response without complex orientation transformation and inner loop current control. The major problem associated with DTC drive is the high torque ripples. The important point in ANN based DTC is the right selection of voltage vector. This project presents simple structured neural network for flux position estimation and sector selection for induction motor. The Levenberg-Marquardt back propagation technique has been used to train the neural networks. The simple structure network facilitates a short training and processing times. The neural network based controller is found to be a very useful technique to obtain high performance speed control.

  4. Artificial cervical disc replacement: Principles, types and techniques

    Directory of Open Access Journals (Sweden)

    Sekhon L

    2005-01-01

    Full Text Available Cervical arthroplasty after anterior decompression with insertion of a prosthetic total disc replacement has been suggested as an alternate to anterior cervical fusion. Currently there are four cervical arthroplasty devices available on the market whose results in clinical use have been reported. Each device varies in terms of materials, range of motion, insertion technique and constraint. It is not known which device is ideal. Early studies suggest that in the short term, the complication rate and efficacy is no worse than fusion surgery. Long-term results have not yet been reported. This review examines the current prostheses available on the market as well as discussing issues regarding indications and technique. Pitfalls are discussed and early experiences reviewed. In time, it is hoped that a refinement of cervical arthroplasty occurs in terms of both materials and design as well as in terms of indications and clinical outcomes as spinal surgeons enter a new era of the management of cervical spine disease.

  5. Technique of nuclear reactors controls

    International Nuclear Information System (INIS)

    This report deal about 'Techniques of control of the nuclear reactors' in the goal to achieve the control of natural uranium reactors and especially the one of Saclay. This work is mainly about the measurement into nuclear parameters and go further in the measurement of thermodynamic variables,etc... putting in relief the new features required on behalf of the detectors because of their use in the thermal neutrons flux. In the domain of nuclear measurement, we indicate the realizations and the results obtained with thermal neutron detectors and for the measurement of ionizations currents. We also treat the technical problem of the start-up of a reactor and of the reactivity measurement. We give the necessary details for the comprehension of all essential diagrams and plans put on, in particular, for the reactor of Saclay. (author)

  6. Semen controlled-release capsules allow a single artificial insemination in sows.

    Science.gov (United States)

    Vigo, D; Faustini, M; Villani, S; Orsini, F; Bucco, M; Chlapanidas, T; Conte, U; Ellis, K; Torre, M L

    2009-09-01

    Controlled-release capsules containing boar spermatozoa were developed to extend the preservation time of spermatozoa and maximize the efficiency of a single artificial insemination. A large trial (4245 sows) was performed with these capsules using double/triple conventional artificial insemination as a control. The effect of treatment on pregnancy diagnosis, delivery, and born piglets was investigated, with allowance being made for considering season, spermatozoa amount, and the weaning-to-estrus interval as confounding variables. The same pregnancy rate and prolificacy were obtained by two insemination techniques, and a higher parturition frequency was reached with capsules. The reproductive performance in pigs has therefore been optimized by a single instrumental insemination with controlled-release capsules. PMID:19505716

  7. Validating a UAV artificial intelligence control system using an autonomous test case generator

    Science.gov (United States)

    Straub, Jeremy; Huber, Justin

    2013-05-01

    The validation of safety-critical applications, such as autonomous UAV operations in an environment which may include human actors, is an ill posed problem. To confidence in the autonomous control technology, numerous scenarios must be considered. This paper expands upon previous work, related to autonomous testing of robotic control algorithms in a two dimensional plane, to evaluate the suitability of similar techniques for validating artificial intelligence control in three dimensions, where a minimum level of airspeed must be maintained. The results of human-conducted testing are compared to this automated testing, in terms of error detection, speed and testing cost.

  8. Design techniques for mutlivariable flight control systems

    Science.gov (United States)

    1981-01-01

    Techniques which address the multi-input closely coupled nature of advanced flight control applications and digital implementation issues are described and illustrated through flight control examples. The techniques described seek to exploit the advantages of traditional techniques in treating conventional feedback control design specifications and the simplicity of modern approaches for multivariable control system design.

  9. RESEARCH AREA -- ARTIFICIAL INTELLIGENCE CONTROL (AIR POLLUTION TECHNOLOGY BRANCH, AIR POLLUTION PREVENTION AND CONTROL DIVISION, NRMRL)

    Science.gov (United States)

    The Air Pollution Technology Branch (APTB) of NRMRL's Air Pollution Prevention and Control Division in Research Triangle Park, NC, has conducted several research projects for evaluating the use of artificial intelligence (AI) to improve the control of pollution control systems an...

  10. Formation Control of Robotic Swarm Using Bounded Artificial Forces

    Directory of Open Access Journals (Sweden)

    Long Qin

    2013-01-01

    Full Text Available Formation control of multirobot systems has drawn significant attention in the recent years. This paper presents a potential field control algorithm, navigating a swarm of robots into a predefined 2D shape while avoiding intermember collisions. The algorithm applies in both stationary and moving targets formation. We define the bounded artificial forces in the form of exponential functions, so that the behavior of the swarm drove by the forces can be adjusted via selecting proper control parameters. The theoretical analysis of the swarm behavior proves the stability and convergence properties of the algorithm. We further make certain modifications upon the forces to improve the robustness of the swarm behavior in the presence of realistic implementation considerations. The considerations include obstacle avoidance, local minima, and deformation of the shape. Finally, detailed simulation results validate the efficiency of the proposed algorithm, and the direction of possible futrue work is discussed in the conclusions.

  11. Artificial Intelligent Control for a Novel Advanced Microwave Biodiesel Reactor

    Science.gov (United States)

    Wali, W. A.; Hassan, K. H.; Cullen, J. D.; Al-Shamma'a, A. I.; Shaw, A.; Wylie, S. R.

    2011-08-01

    Biodiesel, an alternative diesel fuel made from a renewable source, is produced by the transesterification of vegetable oil or fat with methanol or ethanol. In order to control and monitor the progress of this chemical reaction with complex and highly nonlinear dynamics, the controller must be able to overcome the challenges due to the difficulty in obtaining a mathematical model, as there are many uncertain factors and disturbances during the actual operation of biodiesel reactors. Classical controllers show significant difficulties when trying to control the system automatically. In this paper we propose a comparison of artificial intelligent controllers, Fuzzy logic and Adaptive Neuro-Fuzzy Inference System(ANFIS) for real time control of a novel advanced biodiesel microwave reactor for biodiesel production from waste cooking oil. Fuzzy logic can incorporate expert human judgment to define the system variables and their relationships which cannot be defined by mathematical relationships. The Neuro-fuzzy system consists of components of a fuzzy system except that computations at each stage are performed by a layer of hidden neurons and the neural network's learning capability is provided to enhance the system knowledge. The controllers are used to automatically and continuously adjust the applied power supplied to the microwave reactor under different perturbations. A Labview based software tool will be presented that is used for measurement and control of the full system, with real time monitoring.

  12. Artificial Intelligent Control for a Novel Advanced Microwave Biodiesel Reactor

    International Nuclear Information System (INIS)

    Biodiesel, an alternative diesel fuel made from a renewable source, is produced by the transesterification of vegetable oil or fat with methanol or ethanol. In order to control and monitor the progress of this chemical reaction with complex and highly nonlinear dynamics, the controller must be able to overcome the challenges due to the difficulty in obtaining a mathematical model, as there are many uncertain factors and disturbances during the actual operation of biodiesel reactors. Classical controllers show significant difficulties when trying to control the system automatically. In this paper we propose a comparison of artificial intelligent controllers, Fuzzy logic and Adaptive Neuro-Fuzzy Inference System(ANFIS) for real time control of a novel advanced biodiesel microwave reactor for biodiesel production from waste cooking oil. Fuzzy logic can incorporate expert human judgment to define the system variables and their relationships which cannot be defined by mathematical relationships. The Neuro-fuzzy system consists of components of a fuzzy system except that computations at each stage are performed by a layer of hidden neurons and the neural network's learning capability is provided to enhance the system knowledge. The controllers are used to automatically and continuously adjust the applied power supplied to the microwave reactor under different perturbations. A Labview based software tool will be presented that is used for measurement and control of the full system, with real time monitoring.

  13. Artificial Intelligent Control for a Novel Advanced Microwave Biodiesel Reactor

    Energy Technology Data Exchange (ETDEWEB)

    Wali, W A; Hassan, K H; Cullen, J D; Al-Shamma' a, A I; Shaw, A; Wylie, S R, E-mail: w.wali@2009.ljmu.ac.uk [Built Environment and Sustainable Technologies Institute (BEST), School of the Built Environment, Faculty of Technology and Environment Liverpool John Moores University, Byrom Street, Liverpool L3 3AF (United Kingdom)

    2011-08-17

    Biodiesel, an alternative diesel fuel made from a renewable source, is produced by the transesterification of vegetable oil or fat with methanol or ethanol. In order to control and monitor the progress of this chemical reaction with complex and highly nonlinear dynamics, the controller must be able to overcome the challenges due to the difficulty in obtaining a mathematical model, as there are many uncertain factors and disturbances during the actual operation of biodiesel reactors. Classical controllers show significant difficulties when trying to control the system automatically. In this paper we propose a comparison of artificial intelligent controllers, Fuzzy logic and Adaptive Neuro-Fuzzy Inference System(ANFIS) for real time control of a novel advanced biodiesel microwave reactor for biodiesel production from waste cooking oil. Fuzzy logic can incorporate expert human judgment to define the system variables and their relationships which cannot be defined by mathematical relationships. The Neuro-fuzzy system consists of components of a fuzzy system except that computations at each stage are performed by a layer of hidden neurons and the neural network's learning capability is provided to enhance the system knowledge. The controllers are used to automatically and continuously adjust the applied power supplied to the microwave reactor under different perturbations. A Labview based software tool will be presented that is used for measurement and control of the full system, with real time monitoring.

  14. Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands.

    Science.gov (United States)

    Santello, Marco; Bianchi, Matteo; Gabiccini, Marco; Ricciardi, Emiliano; Salvietti, Gionata; Prattichizzo, Domenico; Ernst, Marc; Moscatelli, Alessandro; Jörntell, Henrik; Kappers, Astrid M L; Kyriakopoulos, Kostas; Albu-Schäffer, Alin; Castellini, Claudio; Bicchi, Antonio

    2016-07-01

    The term 'synergy' - from the Greek synergia - means 'working together'. The concept of multiple elements working together towards a common goal has been extensively used in neuroscience to develop theoretical frameworks, experimental approaches, and analytical techniques to understand neural control of movement, and for applications for neuro-rehabilitation. In the past decade, roboticists have successfully applied the framework of synergies to create novel design and control concepts for artificial hands, i.e., robotic hands and prostheses. At the same time, robotic research on the sensorimotor integration underlying the control and sensing of artificial hands has inspired new research approaches in neuroscience, and has provided useful instruments for novel experiments. The ambitious goal of integrating expertise and research approaches in robotics and neuroscience to study the properties and applications of the concept of synergies is generating a number of multidisciplinary cooperative projects, among which the recently finished 4-year European project "The Hand Embodied" (THE). This paper reviews the main insights provided by this framework. Specifically, we provide an overview of neuroscientific bases of hand synergies and introduce how robotics has leveraged the insights from neuroscience for innovative design in hardware and controllers for biomedical engineering applications, including myoelectric hand prostheses, devices for haptics research, and wearable sensing of human hand kinematics. The review also emphasizes how this multidisciplinary collaboration has generated new ways to conceptualize a synergy-based approach for robotics, and provides guidelines and principles for analyzing human behavior and synthesizing artificial robotic systems based on a theory of synergies.

  15. Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands

    Science.gov (United States)

    Santello, Marco; Bianchi, Matteo; Gabiccini, Marco; Ricciardi, Emiliano; Salvietti, Gionata; Prattichizzo, Domenico; Ernst, Marc; Moscatelli, Alessandro; Jörntell, Henrik; Kappers, Astrid M. L.; Kyriakopoulos, Kostas; Albu-Schäffer, Alin; Castellini, Claudio; Bicchi, Antonio

    2016-07-01

    The term 'synergy' - from the Greek synergia - means 'working together'. The concept of multiple elements working together towards a common goal has been extensively used in neuroscience to develop theoretical frameworks, experimental approaches, and analytical techniques to understand neural control of movement, and for applications for neuro-rehabilitation. In the past decade, roboticists have successfully applied the framework of synergies to create novel design and control concepts for artificial hands, i.e., robotic hands and prostheses. At the same time, robotic research on the sensorimotor integration underlying the control and sensing of artificial hands has inspired new research approaches in neuroscience, and has provided useful instruments for novel experiments. The ambitious goal of integrating expertise and research approaches in robotics and neuroscience to study the properties and applications of the concept of synergies is generating a number of multidisciplinary cooperative projects, among which the recently finished 4-year European project "The Hand Embodied" (THE). This paper reviews the main insights provided by this framework. Specifically, we provide an overview of neuroscientific bases of hand synergies and introduce how robotics has leveraged the insights from neuroscience for innovative design in hardware and controllers for biomedical engineering applications, including myoelectric hand prostheses, devices for haptics research, and wearable sensing of human hand kinematics. The review also emphasizes how this multidisciplinary collaboration has generated new ways to conceptualize a synergy-based approach for robotics, and provides guidelines and principles for analyzing human behavior and synthesizing artificial robotic systems based on a theory of synergies.

  16. Current topics in glycemic control by wearable artificial pancreas or bedside artificial pancreas with closed-loop system.

    Science.gov (United States)

    Hanazaki, Kazuhiro; Munekage, Masaya; Kitagawa, Hiroyuki; Yatabe, Tomoaki; Munekage, Eri; Shiga, Mai; Maeda, Hiromichi; Namikawa, Tsutomu

    2016-09-01

    The incidence of diabetes is increasing at an unprecedented pace and has become a serious health concern worldwide during the last two decades. Despite this, adequate glycemic control using an artificial pancreas has not been established, although the 21st century has seen rapid developments in this area. Herein, we review current topics in glycemic control for both the wearable artificial pancreas for type 1 and type 2 diabetic patients and the bedside artificial pancreas for surgical diabetic patients. In type 1 diabetic patients, nocturnal hypoglycemia associated with insulin therapy remains a serious problem that could be addressed by the recent development of a wearable artificial pancreas. This smart phone-like device, comprising a real-time, continuous glucose monitoring system and insulin pump system, could potentially significantly reduce nocturnal hypoglycemia compared with conventional glycemic control. Of particular interest in this space are the recent inventions of a low-glucose suspend feature in the portable systems that automatically stops insulin delivery 2 h following a glucose sensor value artificial pancreas with the closed-loop system has also proved safe and effective for not only avoiding hypoglycemia, but also for reducing blood glucose level variability resulting in good surgical outcomes. We hope that a more sophisticated artificial pancreas with closed-loop system will now be taken up for routine use worldwide, providing enormous relief for patients suffering from uncontrolled hyperglycemia, hypoglycemia, and/or variability in blood glucose concentrations.

  17. GDO Artificial Intelligence-Based Switching PID Baseline Feedback Linearization Method: Controlled PUMA Workspace

    Directory of Open Access Journals (Sweden)

    Farzin Piltan

    2012-10-01

    Full Text Available Congetive method is used in this research to create portfilo of movement robot manipulator. Gradient descent (GD artificial intelligence based switching feedback linearization controller was used and robot’s postures and trajectory were expected in MATLAB/SIMULINK environment. Feedback linearization controller (CTC is an influential nonlinear controller to certain systems which it is based on feedback linearization and computes the required torques using the nonlinear feedback control law in certain systems. Practically a large amount of systems have uncertainties accordingly this method has a challenge. Switching feedback linearization controller is a significant combination nonlinear stable-robust controller under condition of partly uncertain dynamic parameters of system. This technique is used to control of highly nonlinear systems especially in nonlinear time varient nonlinear dynamic system. To increase the stability and robustness with regards to improve the robustness switching methodology is applied to feedback linearization controller. Lyapunov stability is proved in proposed controller based on switching function. To compensate for the dependence on switching parameters baseline methodology is used.The nonlinear model dynamic formulation problem in uncertain system can be solved by using artificial intelligence theorem. Fuzzy logic theory is used to estimate the system dynamic. Forward kinematics implemented the manipulator's movements. Results validated the robot's range of possible postures and trajectories.

  18. Production of genetically and developmentally modified seaweeds: Exploiting the potential of artificial selection techniques

    Directory of Open Access Journals (Sweden)

    Bénédicte eCharrier

    2015-03-01

    Full Text Available Plant feedstock with specific, modified developmental features has been a quest for centuries. Since the development and spread of agriculture, there has been a desire for plants producing disproportionate — or more abundant and more nutritional — biomass that meet human needs better than their native counterparts. Seaweed aquaculture, targeted for human consumption and the production of various raw materials, is a rapidly expanding field and its stakeholders have increasing vested interest for cost-effective and lucrative seaweed cultivation processes. Thus, scientific research on seaweed development is particularly timely: the potential for expansion of seaweed cultivation depends on the sector’s capacity to produce seaweeds with modified morphological features (e.g. thicker blades, higher growth rates or delayed (or even no fertility. Here, we review the various technical approaches used to modify development in macroalgae, which have attracted little attention from developmental biologists to date. Because seaweed (or marine macroalgae anatomy is much less complex than that of land plants and because seaweeds belong to three different eukaryotic phyla, the mechanisms controlling their morphogenesis are key to understanding their development. Here, we present efficient sources of developmentally and genetically modified seaweeds — somatic variants, artificial hybrids and mutants — as well as the future potential of these techniques.

  19. The implementation of artificial intelligence in control systems

    Energy Technology Data Exchange (ETDEWEB)

    Koul, R.; Weygand, D.P.

    1987-01-01

    Some concepts of artificial intelligence are reviewed, particularly as they apply to control systems of accelerators. Logical representation and formal reasoning are discussed briefly, as well as production systems, which describe various systems based on the idea of condition-action pairs (productions). Procedural knowledge, which deals with routine activities that rarely require change, is described. Frames are defined, which provide a convenient structure for representing knowledge. Frames consist of information about objects. For a given frame there are various slots, and for each slot there are various facets, each containing various data. Direct analogical representation is defined as a class of representation which represents knowledge in a natural analog manner, allowing observation of facts in many cases to be achieved quickly and easily compared to deduction. Architecture of systems applied to accelerator control is then described. (LEW)

  20. The implementation of artificial intelligence in control systems

    International Nuclear Information System (INIS)

    Some concepts of artificial intelligence are reviewed, particularly as they apply to control systems of accelerators. Logical representation and formal reasoning are discussed briefly, as well as production systems, which describe various systems based on the idea of condition-action pairs (productions). Procedural knowledge, which deals with routine activities that rarely require change, is described. Frames are defined, which provide a convenient structure for representing knowledge. Frames consist of information about objects. For a given frame there are various slots, and for each slot there are various facets, each containing various data. Direct analogical representation is defined as a class of representation which represents knowledge in a natural analog manner, allowing observation of facts in many cases to be achieved quickly and easily compared to deduction. Architecture of systems applied to accelerator control is then described

  1. Fault diagnosis in nuclear power plants using an artificial neural network technique

    International Nuclear Information System (INIS)

    Application of artificial intelligence (AI) computational techniques, such as expert systems, fuzzy logic, and neural networks in diverse areas has taken place extensively. In the nuclear industry, the intended goal for these AI techniques is to improve power plant operational safety and reliability. As a computerized operator support tool, the artificial neural network (ANN) approach is an emerging technology that currently attracts a large amount of interest. The ability of ANNs to extract the input/output relation of a complicated process and the superior execution speed of a trained ANN motivated this study. The goal was to develop neural networks for sensor and process faults diagnosis with the potential of implementing as a component of a real-time operator support system LYDIA, early sensor and process fault detection and diagnosis

  2. Artificial Intelligence SVC Based Control of Two Machine Transmission System

    Directory of Open Access Journals (Sweden)

    Reza Bayat

    2013-07-01

    Full Text Available The main target in this paper is to present, design fuzzy logic controller (FLC applied to static var compensator (SVC on two machine transmission system to improve transient stability and rapid damping oscillations of synchronous generators, when power generators sudden changes occur.stability that also played important role in power systems. static var compensator with fuzzy logic controller (SVCFLC is a new control strategy can help improve transient stability.The effect of three phase fault causes instability on power system. By and large, it is very difficult to control machine speeds ,rotor angle and voltage during three-phase fault.SVCFLC is a voltage stablizer using three static var compensator which are controlled by SVC with fuzzy logic controller(FLC.The FLC is an effective device for transient stability of two-mashine transmission system. The nonlinear model dynamic formulation problem in unstable system can be solved by using artificial intelligence theorem. Fuzzy logic theory is used to improve the system stability . simulation results of three-phase fault in power system show that SVCFLC caused to increase the stability and damp out the oscillation of machine, compared with effective of SVC in the presence of power system stabilizer(PSS.

  3. Making smart cities smarter using artificial intelligence techniques for smarter mobility

    OpenAIRE

    Vázquez Salceda, Javier; Álvarez Napagao, Sergio; Tejeda Gómez, José Arturo; Oliva Felipe, Luis Javier; Garcia Gasulla, Dario; Gómez Sebastià, Ignasi; Codina Busquet, Víctor

    2014-01-01

    The term Smart City is tipically applied to urban and metropolitan areas where Information and Communication Technologies provide ways to enable social, cultural and urban development, improving social and political capacities and/or efficiency. In this paper we will show the potential of Artificial Intelligence techniques for augmenting ICT solutions to both increase the cities competiveness but also the active participation of citizens in those processes, making Smart Cities smarter. As exa...

  4. Method and apparatus for optimizing operation of a power generating plant using artificial intelligence techniques

    Science.gov (United States)

    Wroblewski, David; Katrompas, Alexander M.; Parikh, Neel J.

    2009-09-01

    A method and apparatus for optimizing the operation of a power generating plant using artificial intelligence techniques. One or more decisions D are determined for at least one consecutive time increment, where at least one of the decisions D is associated with a discrete variable for the operation of a power plant device in the power generating plant. In an illustrated embodiment, the power plant device is a soot cleaning device associated with a boiler.

  5. The use of artificial intelligence techniques to improve the multiple payload integration process

    Science.gov (United States)

    Cutts, Dannie E.; Widgren, Brian K.

    1992-01-01

    A maximum return of science and products with a minimum expenditure of time and resources is a major goal of mission payload integration. A critical component then, in successful mission payload integration is the acquisition and analysis of experiment requirements from the principal investigator and payload element developer teams. One effort to use artificial intelligence techniques to improve the acquisition and analysis of experiment requirements within the payload integration process is described.

  6. Back stepping-Based-PID-Controller Designed for an Artificial Pancreas model

    Directory of Open Access Journals (Sweden)

    ShaimaMahmou Mahdi

    2011-01-01

    Full Text Available Artificial pancreas is simulated to handle Type I diabetic patients under intensive care by automatically controlling the insulin infusion rate. A Backstepping technique is used to apply the effect of PID controller to blood glucose level since there is no direct relation between insulin infusion (the manipulated variable and glucose level in Bergman’s system model subjected to an oral glucose tolerance test by applying a meal translated into a disturbance. Backstepping technique is usually recommended to stabilize and control the states of Bergman's class of nonlinear systems. The results showed a very satisfactory behavior of glucose deviation to a sudden rise represented by the meal that increase the blood glucose

  7. A NOVEL ARTIFICIAL HYDROCARBON NETWORKS BASED SPACE VECTOR PULSE WIDTH MODULATION CONTROLLER FOR INDUCTION MOTORS

    Directory of Open Access Journals (Sweden)

    Hiram Ponce

    2014-01-01

    Full Text Available Most of machine-operated industrial processes implement electric machinery as their work sources, implying the necessary improvement of control techniques and power electronics drivers. Many years have passed since the control conflicts related to induction motors have been overcome through torque-flux control techniques so their advantages over direct current motors have made them to be the most common electric actuator found behind industrial automation. In fact, induction motors can be easily operated using a Direct Torque Control (DTC. Since, it is based on a hysteresis control of the torque and flux errors, its performance is characterized by a quick reaching of the set point, but also a high ripple on both torque and flux. In order to enhance that technique, this study introduces a novel hybrid fuzzy controller with artificial hydrocarbon networks (FMC that is used in a Space Vector Pulse Width Modulation (SVPWM technique, so-called FMC-SVPWM-DTC. In fact, this study describes the proposal and its design method. Experimental results over a velocity-torque cascade topology proved that the proposed FMC-SVPWM-DTC responses highly effective almost suppressing rippling in torque and flux. It also performed a faster speed response than in a conventional DTC. In that sense, the proposed FMC-SVPWM-DTC can be used an alternative approach for controlling induction motors.

  8. Control strategies for afterload reduction with an artificial vasculature device.

    Science.gov (United States)

    Giridharan, Guruprasad A; Cheng, Rolando Chip; Glower, Jacob S; Ewert, Daniel L; Sobieski, Michael A; Slaughter, Mark S; Koenig, Steven C

    2012-01-01

    Ventricular assist devices (VADs) have been used successfully as a bridge to transplant in heart failure patients by unloading ventricular volume and restoring the circulation. An artificial vasculature device (AVD) is being developed that may better facilitate myocardial recovery than VAD by controlling the afterload experienced by the native heart and controlling the pulsatile energy entering into the arterial system from the device, potentially reconditioning the arterial system properties. The AVD is a valveless, 80 ml blood chamber with a servo-controlled pusher plate connected to the ascending aorta by a vascular graft. Control algorithms for the AVD were developed to maintain any user-defined systemic input impedance (IM) including resistance, elastance, and inertial components. Computer simulation and mock circulation models of the cardiovascular system were used to test the efficacy of two control strategies for the AVD: 1) average impedance position control (AIPC)-to maintain an average value of resistance during left ventricular (LV) systole and 2) instantaneous impedance force feedback (IIFF) and position control (IIPC)-to maintain a desired value or profile of resistance and compliance. Computer simulations and mock loop tests were performed to predict resulting cardiovascular pressures, volumes, flows, and the resistance and compliance experienced by the native LV during ejection for simulated normal, failing, and recovering LV. These results indicate that the LV volume and pressure decreased, and the LV stroke volume increased with decreasing IM, resulting in an increased ejection fraction. Although the AIPC algorithm is more stable and can tolerate higher levels of sensor errors and noise, the IIFF and IIPC control algorithms are better suited to maintain any instantaneous IM or an IM profile. The developed AVD impedance control algorithms may be implemented with current VADs to promote myocardial recovery and facilitate weaning.

  9. Control strategies for afterload reduction with an artificial vasculature device.

    Science.gov (United States)

    Giridharan, Guruprasad A; Cheng, Rolando Chip; Glower, Jacob S; Ewert, Daniel L; Sobieski, Michael A; Slaughter, Mark S; Koenig, Steven C

    2012-01-01

    Ventricular assist devices (VADs) have been used successfully as a bridge to transplant in heart failure patients by unloading ventricular volume and restoring the circulation. An artificial vasculature device (AVD) is being developed that may better facilitate myocardial recovery than VAD by controlling the afterload experienced by the native heart and controlling the pulsatile energy entering into the arterial system from the device, potentially reconditioning the arterial system properties. The AVD is a valveless, 80 ml blood chamber with a servo-controlled pusher plate connected to the ascending aorta by a vascular graft. Control algorithms for the AVD were developed to maintain any user-defined systemic input impedance (IM) including resistance, elastance, and inertial components. Computer simulation and mock circulation models of the cardiovascular system were used to test the efficacy of two control strategies for the AVD: 1) average impedance position control (AIPC)-to maintain an average value of resistance during left ventricular (LV) systole and 2) instantaneous impedance force feedback (IIFF) and position control (IIPC)-to maintain a desired value or profile of resistance and compliance. Computer simulations and mock loop tests were performed to predict resulting cardiovascular pressures, volumes, flows, and the resistance and compliance experienced by the native LV during ejection for simulated normal, failing, and recovering LV. These results indicate that the LV volume and pressure decreased, and the LV stroke volume increased with decreasing IM, resulting in an increased ejection fraction. Although the AIPC algorithm is more stable and can tolerate higher levels of sensor errors and noise, the IIFF and IIPC control algorithms are better suited to maintain any instantaneous IM or an IM profile. The developed AVD impedance control algorithms may be implemented with current VADs to promote myocardial recovery and facilitate weaning. PMID:22635010

  10. A NEW RULE-BASED APPROACH FOR COMPUTER CHESS PROGRAMMING USING GP-ARTIFICIAL TECHNIQUES : PECP

    OpenAIRE

    HANEDAN, Y.Güney; SERTBAŞ, Ahmet

    2012-01-01

    In this paper, we use a brand new chess engine programming technique which we name PECP (Positional Evolutionary Chess Programming), that brings the Artificial Intelligence and Genetic Programming approaches together, to construct a chess endgame analyzing engine. Throughout the paper, the technique and the algorithm are discussed in detail. Also,  using PECP, an  example program (RETI V1.0)  aimed to prove the correctness and performance of the rule-based theory and algorithm is written in P...

  11. Detection of drugs and explosives using neutron computerized tomography and artificial intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Ferreira, F.J.O. [Instituto de Engenharia Nuclear, Cidade Universitaria, Rio de Janeiro, CEP 21945-970, Caixa Postal 68550 (Brazil)], E-mail: fferreira@ien.gov.br; Crispim, V.R.; Silva, A.X. [DNC/Poli, PEN COPPE CT, UFRJ Universidade Federal do Rio de Janeiro, CEP 21941-972, Caixa Postal 68509, Rio de Janeiro (Brazil)

    2010-06-15

    In this study the development of a methodology to detect illicit drugs and plastic explosives is described with the objective of being applied in the realm of public security. For this end, non-destructive assay with neutrons was used and the technique applied was the real time neutron radiography together with computerized tomography. The system is endowed with automatic responses based upon the application of an artificial intelligence technique. In previous tests using real samples, the system proved capable of identifying 97% of the inspected materials.

  12. Detection of drugs and explosives using neutron computerized tomography and artificial intelligence techniques

    International Nuclear Information System (INIS)

    In this study the development of a methodology to detect illicit drugs and plastic explosives is described with the objective of being applied in the realm of public security. For this end, non-destructive assay with neutrons was used and the technique applied was the real time neutron radiography together with computerized tomography. The system is endowed with automatic responses based upon the application of an artificial intelligence technique. In previous tests using real samples, the system proved capable of identifying 97% of the inspected materials.

  13. Controlled Magnetic Reversal and Frustration in Artificial Quasicrystals

    Science.gov (United States)

    Bhat, Vinayak

    2014-03-01

    Recent studies of ferromagnetic (FM) antidot arrays have been restricted to simple periodic lattices (square, triangular, etc.). We have fabricated artificial FM quasicrystals (AFQ), which are aperiodic antidot lattices that are self-similar, retain definite rotational symmetry, and consist of a multiply-connected network of permalloy film segments. We focus on Penrose P2 tilings (P2T) constructed from film segments of two lengths (d1 = 810 nm -1618 nm, d2 = 500 nm - 1 μ m), width W ~ 100 nm, and thickness t = 25 nm. Static and dynamic magnetizations were studied using DC magnetometry, broadband (BB) FMR, and micromagnetic simulations (MS). Reproducible ``knee'' anomalies observed in the hysteretic, low-field DC magnetization M(H,T) signal a series of abrupt transitions between ordered magnetization textures, concluding in a smooth evolution into a saturated state. Numerous FMR mode signatures quantitatively reproduce in opposite DC field sweeps in the near-saturated regime, which suggests pinning of the magnetization parallel to the AD edges and confinement of domain walls at P2T vertices control segment polarization and reversal. Novel ``asymmetric'' modes, defined by their presence on only one side of the field origin in a given sweep, are observed only in the reversal regime, and accompany knee anomalies in M(H,T). MS agree with experimental DC hysteresis loops and FMR spectra, and indicate that systematic control of magnetic reversal and domain wall motion can be achieved via tiling design, offering a new paradigm of magnonic quasicrystals. AFQ also behave as novel artificial spin ice systems that exhibit non-stochastic switching due to their aperiodicity and inequivalent pattern vertices. MS indicate pinned Dirac monopoles and confined magnetic avalanches exist in AFQ. Research supported by U.S. DoE Grant DE-FG02-97ER45653 and NSF Grant EPS-0814194.

  14. Ripple reduction control of the undulation pump total artificial heart.

    Science.gov (United States)

    Saito, Itsuro; Chinzei, Tsuneo; Mochizuki, Shuichi; Abe, Yusuke; Isoyama, Takashi; Iwasaki, Kiyotaka; Suzuki, Takafumi; Karita, Tatsuro; Ono, Toshiya; Kouno, Akimasa; Ishimaru, Mitsuhiko; Baba, Atsushi; Ozeki, Toshinaga; Tohyama, Takahiro; Kobayashi Si, Shin-ichi; Imachi, Kou

    2002-01-01

    An undulation pump total artificial heart (UPTAH) in which the revolutions of the motor are converted to undulation motion of a disk has been developed. In an experiment, a goat using the UPTAH survived for 54 days. However, a large ripple was observed in the device's output pressure and flow waveform. In calculating the spectrum of the ripple, we found that the ripple mainly comprised 2 frequency sine waves: 1 having the same frequency as and 1 having double the frequency of the motor revolutions. To reduce the ripple, 2 sine waves, 1 having the same frequency as and 1 having double the frequency of the motor revolutions, were provided to the motor current to modulate the pulse width of the pulse width modulation controlling the motor revolutions. This ripple control method reduced the pressure ripple by 90% in a mock circulation and by 70% in animal experiments. These results revealed that the ripple generated in the UPTAH could be controlled through the use of motor control software.

  15. An artificial pancreas for automated blood glucose control in patients with Type 1 diabetes

    DEFF Research Database (Denmark)

    Schmidt, Signe; Boiroux, Dimitri; Ranjan, Ajenthen;

    2015-01-01

    Automated glucose control in patients with Type 1 diabetes is much-coveted by patients, relatives and healthcare professionals. It is the expectation that a system for automated control, also know as an artificial pancreas, will improve glucose control, reduce the risk of diabetes complications...... and markedly improve patient quality of life. An artificial pancreas consists of portable devices for glucose sensing and insulin delivery which are controlled by an algorithm residing on a computer. The technology is still under development and currently no artificial pancreas is commercially available....... This review gives an introduction to recent progress, challenges and future prospects within the field of artificial pancreas research....

  16. Smart Collections: Can Artificial Intelligence Tools and Techniques Assist with Discovering, Evaluating and Tagging Digital Learning Resources?

    Science.gov (United States)

    Leibbrandt, Richard; Yang, Dongqiang; Pfitzner, Darius; Powers, David; Mitchell, Pru; Hayman, Sarah; Eddy, Helen

    2010-01-01

    This paper reports on a joint proof of concept project undertaken by researchers from the Flinders University Artificial Intelligence Laboratory in partnership with information managers from the Education Network Australia (edna) team at Education Services Australia to address the question of whether artificial intelligence techniques could be…

  17. Structural investigation and simulation of acoustic properties of some tellurite glasses using artificial intelligence technique

    International Nuclear Information System (INIS)

    Research highlights: → Simulation the acoustic properties of some tellurite glasses using one of the artificial intelligence techniques (artificial neural network). → The glass network is strengthened by enhancing the linkage of Te-O chains. The tellurite network will also come to homogenization, because of uniform distribution of Nb5+ ions among the Te-O chains, though some of the tellurium-oxide polyhedra still link each other in edge sharing. → Excellent agreements between the measured values and the predicted values were obtained for over 50 different tellurite glass compositions. → The model we designed gives a better agreement as compared with Makishima and Machenzie model. - Abstract: The developments in the field of industry raise the need for simulating the acoustic properties of glass materials before melting raw material oxides. In this paper, we are trying to simulate the acoustic properties of some tellurite glasses using one of the artificial intelligence techniques (artificial neural network). The artificial neural network (ANN) technique is introduced in the current study to simulate and predict important parameters such as density, longitudinal and shear ultrasonic velocities and elastic moduli (longitudinal and shear moduli). The ANN results were found to be in successful good agreement with those experimentally measured parameters. Then the presented ANN model is used to predict the acoustic properties of some new tellurite glasses. For this purpose, four glass systems xNb2O5-(1 - x)TeO2, 0.1PbO-xNb2O5-(0.9 - x)TeO2, 0.2PbO-xNb2O5-(0.8 - x)TeO2 and 0.05Bi2O3-xNb2O5-(0.95 - x)TeO2 were prepared using melt quenching technique. The results of ultrasonic velocities and elastic moduli showed that the addition of Nb2O5 as a network modifier provides oxygen ions to change [TeO4] tbps into [TeO3] tps.

  18. Consistently Trained Artificial Neural Network for Automatic Ship Berthing Control

    Directory of Open Access Journals (Sweden)

    Y.A. Ahmed

    2015-09-01

    Full Text Available In this paper, consistently trained Artificial Neural Network controller for automatic ship berthing is discussed. Minimum time course changing manoeuvre is utilised to ensure such consistency and a new concept named ‘virtual window’ is introduced. Such consistent teaching data are then used to train two separate multi-layered feed forward neural networks for command rudder and propeller revolution output. After proper training, several known and unknown conditions are tested to judge the effectiveness of the proposed controller using Monte Carlo simulations. After getting acceptable percentages of success, the trained networks are implemented for the free running experiment system to judge the network’s real time response for Esso Osaka 3-m model ship. The network’s behaviour during such experiments is also investigated for possible effect of initial conditions as well as wind disturbances. Moreover, since the final goal point of the proposed controller is set at some distance from the actual pier to ensure safety, therefore a study on automatic tug assistance is also discussed for the final alignment of the ship with actual pier.

  19. Nuclear power plant monitoring and fault diagnosis methods based on the artificial intelligence technique

    International Nuclear Information System (INIS)

    The main objective of this paper is to develop an advanced diagnosis system based on the artificial intelligence technique to monitor the operation and to improve the operational safety of nuclear power plants. Three different methods have been elaborated in this study: an artificial neural network local diagnosis (NNds) scheme that acting at the component level discriminates between normal and abnormal transients, a model-based diagnostic reasoning mechanism that combines a physical causal network model-based knowledge compiler (KC) that generates applicable diagnostic rules from widely accepted physical knowledge compiler (KC) that generates applicable diagnostic rules from widely accepted physical knowledge. Although the three methods have been developed and verified independently, they are highly correlated and, when connected together, form a effective and robust diagnosis and monitoring tool. (authors)

  20. A scenario for a genetically controlled fission of artificial vesicles

    DEFF Research Database (Denmark)

    Bönzli, Eva; Hadorn, Maik; Jørgensen, Mikkel Girke;

    2011-01-01

    Artificial vesicles have been used for decades as model systems of biological cells to investigate scientific questions in simulacra. In recent years, the significance of artificial vesicles further increased because they represent ideal candidates to become the building block of a de novo...... construction of a cell in a bottom-up manner. Numerous efforts to build an artificial cell that bridge the living and non-living world will most presumably represent one of the main goals of science in the 21st century. It was shown that artificial genetic programs and the required cellular machinery can...

  1. 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.

  2. Atmospheric controls on Puerto Rico precipitation using artificial neural networks

    Science.gov (United States)

    Ramseyer, Craig A.; Mote, Thomas L.

    2016-01-01

    The growing need for local climate change scenarios has given rise to a wide range of empirical climate downscaling techniques. One of the most critical decisions in these methodologies is the selection of appropriate predictor variables for the downscaled surface predictand. A systematic approach to selecting predictor variables should be employed to ensure that the most important variables are utilized for the study site where the climate change scenarios are being developed. Tropical study areas have been far less examined than mid- and high-latitudes in the climate downscaling literature. As a result, studies analyzing optimal predictor variables for tropics are limited. The objectives of this study include developing artificial neural networks for six sites around Puerto Rico to develop nonlinear functions between 37 atmospheric predictor variables and local rainfall. The relative importance of each predictor is analyzed to determine the most important inputs in the network. Randomized ANNs are produced to determine the statistical significance of the relative importance of each predictor variable. Lower tropospheric moisture and winds are shown to be the most important variables at all sites. Results show inter-site variability in u- and v-wind importance depending on the unique geographic situation of the site. Lower tropospheric moisture and winds are physically linked to variability in sea surface temperatures (SSTs) and the strength and position of the North Atlantic High Pressure cell (NAHP). The changes forced by anthropogenic climate change in regional SSTs and the NAHP will impact rainfall variability in Puerto Rico.

  3. Atmospheric controls on Puerto Rico precipitation using artificial neural networks

    Science.gov (United States)

    Ramseyer, Craig A.; Mote, Thomas L.

    2016-10-01

    The growing need for local climate change scenarios has given rise to a wide range of empirical climate downscaling techniques. One of the most critical decisions in these methodologies is the selection of appropriate predictor variables for the downscaled surface predictand. A systematic approach to selecting predictor variables should be employed to ensure that the most important variables are utilized for the study site where the climate change scenarios are being developed. Tropical study areas have been far less examined than mid- and high-latitudes in the climate downscaling literature. As a result, studies analyzing optimal predictor variables for tropics are limited. The objectives of this study include developing artificial neural networks for six sites around Puerto Rico to develop nonlinear functions between 37 atmospheric predictor variables and local rainfall. The relative importance of each predictor is analyzed to determine the most important inputs in the network. Randomized ANNs are produced to determine the statistical significance of the relative importance of each predictor variable. Lower tropospheric moisture and winds are shown to be the most important variables at all sites. Results show inter-site variability in u- and v-wind importance depending on the unique geographic situation of the site. Lower tropospheric moisture and winds are physically linked to variability in sea surface temperatures (SSTs) and the strength and position of the North Atlantic High Pressure cell (NAHP). The changes forced by anthropogenic climate change in regional SSTs and the NAHP will impact rainfall variability in Puerto Rico.

  4. Temperature Control System Using Fuzzy Logic Technique

    Directory of Open Access Journals (Sweden)

    Isizoh A N

    2012-06-01

    Full Text Available Fuzzy logic technique is an innovative technology used in designing solutions for multi-parameter and non-linear control models for the definition of a control strategy. As a result, it delivers solutions faster than the conventional control design techniques. This paper thus presents a fuzzy logic based-temperature control system, which consists of a microcontroller, temperature sensor, and operational amplifier, Analogue to Digital Converter, display interface circuit and output interface circuit. It contains a design approach that uses fuzzy logic technique to achieve a controlled temperature output function.

  5. Artificial Intelligence Techniques for the Estimation of Direct Methanol Fuel Cell Performance

    Science.gov (United States)

    Hasiloglu, Abdulsamet; Aras, Ömür; Bayramoglu, Mahmut

    2016-04-01

    Artificial neural networks and neuro-fuzzy inference systems are well known artificial intelligence techniques used for black-box modelling of complex systems. In this study, Feed-forward artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are used for modelling the performance of direct methanol fuel cell (DMFC). Current density (I), fuel cell temperature (T), methanol concentration (C), liquid flow-rate (q) and air flow-rate (Q) are selected as input variables to predict the cell voltage. Polarization curves are obtained for 35 different operating conditions according to a statistically designed experimental plan. In modelling study, various subsets of input variables and various types of membership function are considered. A feed -forward architecture with one hidden layer is used in ANN modelling. The optimum performance is obtained with the input set (I, T, C, q) using twelve hidden neurons and sigmoidal activation function. On the other hand, first order Sugeno inference system is applied in ANFIS modelling and the optimum performance is obtained with the input set (I, T, C, q) using sixteen fuzzy rules and triangular membership function. The test results show that ANN model estimates the polarization curve of DMFC more accurately than ANFIS model.

  6. Simulation and prediction for energy dissipaters and stilling basins design using artificial intelligence technique

    Directory of Open Access Journals (Sweden)

    Mostafa Ahmed Moawad Abdeen

    2015-12-01

    Full Text Available Water with large velocities can cause considerable damage to channels whose beds are composed of natural earth materials. Several stilling basins and energy dissipating devices have been designed in conjunction with spillways and outlet works to avoid damages in canals’ structures. In addition, lots of experimental and traditional mathematical numerical works have been performed to profoundly investigate the accurate design of these stilling basins and energy dissipaters. The current study is aimed toward introducing the artificial intelligence technique as new modeling tool in the prediction of the accurate design of stilling basins. Specifically, artificial neural networks (ANNs are utilized in the current study in conjunction with experimental data to predict the length of the hydraulic jumps occurred in spillways and consequently the stilling basin dimensions can be designed for adequate energy dissipation. The current study showed, in a detailed fashion, the development process of different ANN models to accurately predict the hydraulic jump lengths acquired from different experimental studies. The results obtained from implementing these models showed that ANN technique was very successful in simulating the hydraulic jump characteristics occurred in stilling basins. Therefore, it can be safely utilized in the design of these basins as ANN involves minimum computational and financial efforts and requirements compared with experimental work and traditional numerical techniques such as finite difference or finite elements.

  7. OFO experimental techniques and preliminary conclusions - Is artificial gravity needed during prolonged weightlessness.

    Science.gov (United States)

    Gualtierotti, T.; Bracchi, F.

    1972-01-01

    The technique of single unit recording from body systems generating electrical pulses coherent with their basic function (CNS, muscles, sense organs) has been proved feasible during the OFO A orbital flight, an automatic physiological experiment. The results of recording 155 hours of orbital flight of pulses from the nerve fibres of four vestibular gravity sensors in two bull frogs indicate that the vestibular organ adjusts to zero g. As all the other biological changes observed during orbit are due to lack of exercise, it is concluded that artificial gravity might not be necessary during prolonged space missions or on low gravity celestial bodies.

  8. Implementation of Artificial Intelligence Techniques for Steady State Security Assessment in Pool Market

    Directory of Open Access Journals (Sweden)

    I. S. Saeh

    2009-03-01

    Full Text Available Various techniques have been implemented to include steady state securityassessment in the analysis of trading in deregulated power system, howevermost of these techniques lack requirements of fast computational time withacceptable accuracy. The problem is compounded further by the requirements toconsider bus voltages and thermal line limits. This work addresses the problemby presenting the analysis and management of power transaction between powerproducers and customers in the deregulated system using the application ofArtificial Intelligence (AI techniques such as Neural Network (ANN, DecisionTree (DT techniques and Adaptive Network based Fuzzy Inference System(ANFIS. Data obtained from Newton Raphson load flow analysis method areused for the training and testing purposes of the proposed techniques and alsoas comparison in term of accuracy against the proposed techniques. The inputvariables to the AI systems are loadings of the lines and the voltage magnitudesof the load buses. The algorithms are initially tested on the 5 bus system andfurther verified on the IEEE 30 57 and 118 bus test system configured as pooltrading models. By comparing the results, it can be concluded that ANNtechnique is more accurate and better in term of computational time takencompared to the other two techniques. However, ANFIS and DT’s can be moreeasily implemented for practical applications. The newly developed techniquescan further improve security aspects related to the planning and operation ofpool-type deregulated system.

  9. Global Control of the Furuta Pendulum Using Artificial Neural Networks and Feedback of State Variables

    Directory of Open Access Journals (Sweden)

    Luisa F. Escobar-Dávila

    2013-06-01

    Full Text Available This paper presents the mathematical modeling of the Furuta Pendu-lum by power functions, taking into account the non linear own dynamics of the physical systems and considering the existing couplings between the electric and mechanic devices. A control process based on feedback of state variables (FSV for the equilibrium point is developed and two topics for the non linear zone are addressed. First of all, functions are implemented to represent the energetic states of the plant in a global way and the operation regions are established (“Swing up” zone, and later Artificial Neural Networks (ANN are employed to simulate the behavior of the energy functions. Finally, it is presented the combination between the control techniques, considering the own constrains of the actuators and sensors used, besides of this, a study is done in a simulated environment of the physical phenomena that may disturb system behavior, and the capacity, sensitivity and robustness of the controller is verified.

  10. NONLINEAR MODELING AND CONTROLLING OF ARTIFICIAL MUSCLE SYSTEM USING NEURAL NETWORKS

    Institute of Scientific and Technical Information of China (English)

    Tian Sheping; Ding Guoqing; Yan Detian; Lin Liangming

    2004-01-01

    The pneumatic artificial muscles are widely used in the fields of medical robots,etc.Neural networks are applied to modeling and controlling of artificial muscle system.A single-joint artificial muscle test system is designed.The recursive prediction error (RPE) algorithm which yields faster convergence than back propagation (BP) algorithm is applied to train the neural networks.The realization of RPE algorithm is given.The difference of modeling of artificial muscles using neural networks with different input nodes and different hidden layer nodes is discussed.On this basis the nonlinear control scheme using neural networks for artificial muscle system has been introduced.The experimental results show that the nonlinear control scheme yields faster response and higher control accuracy than the traditional linear control scheme.

  11. Genetically Controlled Fusion, Exocytosis and Fission of Artificial Vesicles

    DEFF Research Database (Denmark)

    Bönzli, Eva; Hadorn, Maik; De Lucrezia, Davide;

    Artificial vesicles represent ideal candidates as a model for artificial cells. It was shown that artificial genetic programs and the required cellular machinery (cell-free expression systems) can be incorporated into vesicles and allow the synthesis of proteins. Vesicles were shown to fuse...... vesicles in the presence of peptides. This project may present a step towards personalized drug delivery. Specific drugs or prodrugs enclosed into vesicles may be released upon an external signal related to a disease, e.g. a tumor, to activate gene expression and synthesis of fusion peptides to induce...

  12. Artificial intelligence-based control system for the analysis of metal casting properties

    Directory of Open Access Journals (Sweden)

    E. Mares

    2010-06-01

    Full Text Available Purpose: The metal casting process requires testing equipment that along with customized computer software properly supports the analysis of casting component characteristic properties. Due to the fact that this evaluation process involves the control of complex and multi-variable melting, casting and solidification factors, it is necessary to develop dedicated software.Design/methodology/approach: The integration of Statistical Process Control methods and Artificial Intelligence techniques (Case-Based Reasoning into Thermal Analysis Data Acquisition Software (NI LabView was developed to analyze casting component properties. The thermal data was tested in terms of accuracy, reliability and timeliness in order to secure metal casting process effectiveness.Findings: Quantitative values were defined as “Low”, “Medium” and “High” to assess the level of improvement in the metal casting analysis by means of the Artificial Intelligence-Based Control System (AIBCS. The traditional process was used as a reference to measure such improvement. As a result, the accuracy, reliability and timeliness were significantly increased to the “High” level.Research limitations/implications: Presently, the AIBCS predicts a limited number of casting properties. Due to its flexible design more properties could be added.Practical implications: The AIBCS has been successfully used at the Ford/Nemak Windsor Aluminum Plant (WAP to analyze Al casting properties of the engine blocks.Originality/value: The metal casting research community has immensely benefited from these developed information technologies that support the metal casting process.

  13. Integrating Nanostructured Artificial Receptors with Whispering Gallery Mode Optical Microresonators via Inorganic Molecular Imprinting Techniques

    Directory of Open Access Journals (Sweden)

    G. Denise Hammond

    2016-06-01

    Full Text Available The creation of label-free biosensors capable of accurately detecting trace contaminants, particularly small organic molecules, is of significant interest for applications in environmental monitoring. This is achieved by pairing a high-sensitivity signal transducer with a biorecognition element that imparts selectivity towards the compound of interest. However, many environmental pollutants do not have corresponding biorecognition elements. Fortunately, biomimetic chemistries, such as molecular imprinting, allow for the design of artificial receptors with very high selectivity for the target. Here, we perform a proof-of-concept study to show how artificial receptors may be created from inorganic silanes using the molecular imprinting technique and paired with high-sensitivity transducers without loss of device performance. Silica microsphere Whispering Gallery Mode optical microresonators are coated with a silica thin film templated by a small fluorescent dye, fluorescein isothiocyanate, which serves as our model target. Oxygen plasma degradation and solvent extraction of the template are compared. Extracted optical devices are interacted with the template molecule to confirm successful sorption of the template. Surface characterization is accomplished via fluorescence and optical microscopy, ellipsometry, optical profilometry, and contact angle measurements. The quality factors of the devices are measured to evaluate the impact of the coating on device sensitivity. The resulting devices show uniform surface coating with no microstructural damage with Q factors above 106. This is the first report demonstrating the integration of these devices with molecular imprinting techniques, and could lead to new routes to biosensor creation for environmental monitoring.

  14. Integrating Nanostructured Artificial Receptors with Whispering Gallery Mode Optical Microresonators via Inorganic Molecular Imprinting Techniques.

    Science.gov (United States)

    Hammond, G Denise; Vojta, Adam L; Grant, Sheila A; Hunt, Heather K

    2016-01-01

    The creation of label-free biosensors capable of accurately detecting trace contaminants, particularly small organic molecules, is of significant interest for applications in environmental monitoring. This is achieved by pairing a high-sensitivity signal transducer with a biorecognition element that imparts selectivity towards the compound of interest. However, many environmental pollutants do not have corresponding biorecognition elements. Fortunately, biomimetic chemistries, such as molecular imprinting, allow for the design of artificial receptors with very high selectivity for the target. Here, we perform a proof-of-concept study to show how artificial receptors may be created from inorganic silanes using the molecular imprinting technique and paired with high-sensitivity transducers without loss of device performance. Silica microsphere Whispering Gallery Mode optical microresonators are coated with a silica thin film templated by a small fluorescent dye, fluorescein isothiocyanate, which serves as our model target. Oxygen plasma degradation and solvent extraction of the template are compared. Extracted optical devices are interacted with the template molecule to confirm successful sorption of the template. Surface characterization is accomplished via fluorescence and optical microscopy, ellipsometry, optical profilometry, and contact angle measurements. The quality factors of the devices are measured to evaluate the impact of the coating on device sensitivity. The resulting devices show uniform surface coating with no microstructural damage with Q factors above 10⁶. This is the first report demonstrating the integration of these devices with molecular imprinting techniques, and could lead to new routes to biosensor creation for environmental monitoring. PMID:27314397

  15. Soft Computing Techniques for Process Control Applications

    Directory of Open Access Journals (Sweden)

    Rahul Malhotra

    2011-09-01

    Full Text Available Technological innovations in soft computing techniques have brought automation capabilities to new levelsof applications. Process control is an important application of any industry for controlling the complexsystem parameters, which can greatly benefit from such advancements. Conventional control theory isbased on mathematical models that describe the dynamic behaviour of process control systems. Due to lackin comprehensibility, conventional controllers are often inferior to the intelligent controllers. Softcomputing techniques provide an ability to make decisions and learning from the reliable data or expert’sexperience. Moreover, soft computing techniques can cope up with a variety of environmental and stabilityrelated uncertainties. This paper explores the different areas of soft computing techniques viz. Fuzzy logic,genetic algorithms and hybridization of two and abridged the results of different process control casestudies. It is inferred from the results that the soft computing controllers provide better control on errorsthan conventional controllers. Further, hybrid fuzzy genetic algorithm controllers have successfullyoptimized the errors than standalone soft computing and conventional techniques.

  16. The Changeless Technique Researches for City Flood Control and Reduced the Disaster

    Institute of Scientific and Technical Information of China (English)

    Chen Gangyi; OuYang Bolin; Xia Fan

    2006-01-01

    The make use of the stir kinetic energy conservation law, the theories and chaogeless technique build up for city flood control. Pass the system energy conversion or deliver with contain of second circulation, carry out city flood control and reduced the disaster that develops the artificial lake. It is advantageous to the improvement city ecosystem environment and resources of water that is missing.

  17. APPLICATIONS OF ARTIFICIAL INTELLIGENCE TECHNIQUES TO COMBATING CYBER CRIMES: A REVIEW

    Directory of Open Access Journals (Sweden)

    Selma Dilek

    2015-01-01

    Full Text Available With the advances in information technology (IT criminals are using cyberspace to commit numerous cyber crimes. Cyber infrastructures are highly vulnerable to intrusions and other threats. Physical devices and human intervention are not sufficient for monitoring and protection of these infrastructures; hence, there is a need for more sophisticated cyber defense systems that need to be flexible, adaptable and robust, and able to detect a wide variety of threats and make intelligent real-time decisions. Numerous bio-inspired computing methods of Artificial Intelligence have been increasingly playing an important role in cyber crime detection and prevention. The purpose of this study is to present advances made so far in the field of applying AI techniques for combating cyber crimes, to demonstrate how these techniques can be a

  18. Artificial intelligence techniques used in respiratory sound analysis--a systematic review.

    Science.gov (United States)

    Palaniappan, Rajkumar; Sundaraj, Kenneth; Sundaraj, Sebastian

    2014-02-01

    Artificial intelligence (AI) has recently been established as an alternative method to many conventional methods. The implementation of AI techniques for respiratory sound analysis can assist medical professionals in the diagnosis of lung pathologies. This article highlights the importance of AI techniques in the implementation of computer-based respiratory sound analysis. Articles on computer-based respiratory sound analysis using AI techniques were identified by searches conducted on various electronic resources, such as the IEEE, Springer, Elsevier, PubMed, and ACM digital library databases. Brief descriptions of the types of respiratory sounds and their respective characteristics are provided. We then analyzed each of the previous studies to determine the specific respiratory sounds/pathology analyzed, the number of subjects, the signal processing method used, the AI techniques used, and the performance of the AI technique used in the analysis of respiratory sounds. A detailed description of each of these studies is provided. In conclusion, this article provides recommendations for further advancements in respiratory sound analysis.

  19. Insect control by using sterile male technique

    International Nuclear Information System (INIS)

    The sterile male technique used in insect control is presented as an alternative for chemical control of pest insect. Description and effects of sterile male technique on morphology and physiology of different classes of pest insects are given. Prerequisite conditions necessary to work out SMT are presented. As an example of the application of this technique: control of Ephestia Cartella is studied. Gamma radiation effects on deformation, sterilization and longevity of the male insect as well as fecondity and fertility with respects of gamma irradiation are presented. 11 refs. 3 tabs

  20. ARTIFICIAL NEURAL NETWORK AND FUZZY LOGIC CONTROLLER FOR GTAW MODELING AND CONTROL

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    An artificial neural network(ANN) and a self-adjusting fuzzy logic controller(FLC) for modeling and control of gas tungsten arc welding(GTAW) process are presented. The discussion is mainly focused on the modeling and control of the weld pool depth with ANN and the intelligent control for weld seam tracking with FLC. The proposed neural network can produce highly complex nonlinear multi-variable model of the GTAW process that offers the accurate prediction of welding penetration depth. A self-adjusting fuzzy controller used for seam tracking adjusts the control parameters on-line automatically according to the tracking errors so that the torch position can be controlled accurately.

  1. A new technique based on Artificial Bee Colony Algorithm for optimal sizing of stand-alone photovoltaic system

    Directory of Open Access Journals (Sweden)

    Ahmed F. Mohamed

    2014-05-01

    Full Text Available One of the most recent optimization techniques applied to the optimal design of photovoltaic system to supply an isolated load demand is the Artificial Bee Colony Algorithm (ABC. The proposed methodology is applied to optimize the cost of the PV system including photovoltaic, a battery bank, a battery charger controller, and inverter. Two objective functions are proposed: the first one is the PV module output power which is to be maximized and the second one is the life cycle cost (LCC which is to be minimized. The analysis is performed based on measured solar radiation and ambient temperature measured at Helwan city, Egypt. A comparison between ABC algorithm and Genetic Algorithm (GA optimal results is done. Another location is selected which is Zagazig city to check the validity of ABC algorithm in any location. The ABC is more optimal than GA. The results encouraged the use of the PV systems to electrify the rural sites of Egypt.

  2. A new technique based on Artificial Bee Colony Algorithm for optimal sizing of stand-alone photovoltaic system.

    Science.gov (United States)

    Mohamed, Ahmed F; Elarini, Mahdi M; Othman, Ahmed M

    2014-05-01

    One of the most recent optimization techniques applied to the optimal design of photovoltaic system to supply an isolated load demand is the Artificial Bee Colony Algorithm (ABC). The proposed methodology is applied to optimize the cost of the PV system including photovoltaic, a battery bank, a battery charger controller, and inverter. Two objective functions are proposed: the first one is the PV module output power which is to be maximized and the second one is the life cycle cost (LCC) which is to be minimized. The analysis is performed based on measured solar radiation and ambient temperature measured at Helwan city, Egypt. A comparison between ABC algorithm and Genetic Algorithm (GA) optimal results is done. Another location is selected which is Zagazig city to check the validity of ABC algorithm in any location. The ABC is more optimal than GA. The results encouraged the use of the PV systems to electrify the rural sites of Egypt.

  3. Artificial Intelligence Techniques to Optimize the EDC/NHS-Mediated Immobilization of Cellulase on Eudragit L-100

    OpenAIRE

    Min-Chao He; Yun-Yun Liu,; Wei Qi; Zhen-Hong Yuan; Jing-Liang Xu,; Yu Zhang

    2012-01-01

    Two artificial intelligence techniques, namely artificial neural network (ANN) and genetic algorithm (GA) were combined to be used as a tool for optimizing the covalent immobilization of cellulase on a smart polymer, Eudragit L-100. 1-Ethyl-3-(3-dimethyllaminopropyl) carbodiimide (EDC) concentration, N-hydroxysuccinimide (NHS) concentration and coupling time were taken as independent variables, and immobilization efficiency was taken as the response. The data of the centr...

  4. Evolving Spiking Neural Networks for Control of Artificial Creatures

    Directory of Open Access Journals (Sweden)

    Arash Ahmadi

    2013-10-01

    Full Text Available To understand and analysis behavior of complicated and intelligent organisms, scientists apply bio-inspired concepts including evolution and learning to mathematical models and analyses. Researchers utilize these perceptions in different applications, searching for improved methods andapproaches for modern computational systems. This paper presents a genetic algorithm based evolution framework in which Spiking Neural Network (SNN of artificial creatures are evolved for higher chance of survival in a virtual environment. The artificial creatures are composed ofrandomly connected Izhikevich spiking reservoir neural networks using population activity rate coding. Inspired by biological neurons, the neuronal connections are considered with different axonal conduction delays. Simulations results prove that the evolutionary algorithm has thecapability to find or synthesis artificial creatures which can survive in the environment successfully.

  5. Artificial neural networks application in duplex/triplex elevator group control system:

    OpenAIRE

    Imrak, C. Erdem

    2008-01-01

    Artificial neural networks can offer the better solution to the passenger call distribution problem when compared to the conventional elevator control systems. Therefore, the application of neural networks in elevator group control system is discussed. The significance of introducing artificial neural networks is presented. Elevator group control systems with neural networks can predict the next stopping floors to stop by considering what has been learnt by processing the changes in passenger...

  6. Automatic Level Control for Video Cameras towards HDR Techniques

    Directory of Open Access Journals (Sweden)

    de With PeterHN

    2010-01-01

    Full Text Available We give a comprehensive overview of the complete exposure processing chain for video cameras. For each step of the automatic exposure algorithm we discuss some classical solutions and propose their improvements or give new alternatives. We start by explaining exposure metering methods, describing types of signals that are used as the scene content descriptors as well as means to utilize these descriptors. We also discuss different exposure control types used for the control of lens, integration time of the sensor, and gain control, such as a PID control, precalculated control based on the camera response function, and propose a new recursive control type that matches the underlying image formation model. Then, a description of commonly used serial control strategy for lens, sensor exposure time, and gain is presented, followed by a proposal of a new parallel control solution that integrates well with tone mapping and enhancement part of the image pipeline. Parallel control strategy enables faster and smoother control and facilitates optimally filling the dynamic range of the sensor to improve the SNR and an image contrast, while avoiding signal clipping. This is archived by the proposed special control modes used for better display and correct exposure of both low-dynamic range and high-dynamic range images. To overcome the inherited problems of limited dynamic range of capturing devices we discuss a paradigm of multiple exposure techniques. Using these techniques we can enable a correct rendering of difficult class of high-dynamic range input scenes. However, multiple exposure techniques bring several challenges, especially in the presence of motion and artificial light sources such as fluorescent lights. In particular, false colors and light-flickering problems are described. After briefly discussing some known possible solutions for the motion problem, we focus on solving the fluorescence-light problem. Thereby, we propose an algorithm for

  7. A COMPARATIVE ANALYSIS OF OPTIMIZATION TECHNIQUES FOR ARTIFICIAL NEURAL NETWORK IN BIO MEDICAL APPLICATIONS

    Directory of Open Access Journals (Sweden)

    V. Saishanmuga Raja

    2014-01-01

    Full Text Available In this study we compare the performance of three evolutionary algorithms such as Genetic Algorithm (GA Particle Swarm Optimization (PSO and Ant-Colony Optimization (ACO which are used to optimize the Artificial Neural Network (ANN. Optimization of Neural Networks improves speed of recall and may also improve the efficiency of training. Here we have used the Ant colony optimization, Particle Swarm Optimization and Genetic Algorithm to optimize the artificial neural networks for applications in medical image processing (extraction and compression. The aim of developing such algorithms is to arrive at near-optimum solutions to large-scale optimization problems, for which traditional mathematical techniques may fail. This study compares the efficiency and results of the three evolutionary algorithms. We have compared these algorithms based on processing time, accuracy and time taken to train Neural Networks. The results show that the Genetic Algorithm outperformed the other two algorithms. This study helps researchers to get an idea of selecting an optimization algorithm for configuring a neural network.

  8. Evaluation of artificial neural network techniques for flow forecasting in the River Yangtze, China

    Directory of Open Access Journals (Sweden)

    C. W. Dawson

    2002-01-01

    Full Text Available While engineers have been quantifying rainfall-runoff processes since the mid-19th century, it is only in the last decade that artificial neural network models have been applied to the same task. This paper evaluates two neural networks in this context: the popular multilayer perceptron (MLP, and the radial basis function network (RBF. Using six-hourly rainfall-runoff data for the River Yangtze at Yichang (upstream of the Three Gorges Dam for the period 1991 to 1993, it is shown that both neural network types can simulate river flows beyond the range of the training set. In addition, an evaluation of alternative RBF transfer functions demonstrates that the popular Gaussian function, often used in RBF networks, is not necessarily the ‘best’ function to use for river flow forecasting. Comparisons are also made between these neural networks and conventional statistical techniques; stepwise multiple linear regression, auto regressive moving average models and a zero order forecasting approach. Keywords: Artificial neural network, multilayer perception, radial basis function, flood forecasting

  9. Use of artificial intelligence techniques for visual inspection systems prototyping. Application to magnetoscopy

    International Nuclear Information System (INIS)

    The automation of visual inspection is a complex task that requires collaboration between experts, for example inspection specialist, vision specialist. on-line operators. Solving such problems through prototyping promotes this collaboration: the use of a non specific programming environment allows rapid, concrete checking of method validity, thus leading incrementally to the final system. In this context, artificial intelligence techniques permit easy, extensible, and modular design of the prototype, together with heuristic solution building. We define and achieve the SPOR prototyping environment, based on object-oriented programming and rules-basis managing. The feasibility and the validity of an heuristic method for automated visual inspection in fluoroscopy have been proved through prototyping in SPOR. (author)

  10. Artificial intelligence search techniques for optimization of the cold source geometry

    International Nuclear Information System (INIS)

    Most optimization studies of cold neutron sources have concentrated on the numerical prediction or experimental measurement of the cold moderator optimum thickness which produces the largest cold neutron leakage for a given thermal neutron source. Optimizing the geometrical shape of the cold source, however, is a more difficult problem because the optimized quantity, the cold neutron leakage, is an implicit function of the shape which is the unknown in such a study. We draw an analogy between this problem and a state space search, then we use a simple Artificial Intelligence (AI) search technique to determine the optimum cold source shape based on a two-group, r-z diffusion model. We implemented this AI design concept in the computer program AID which consists of two modules, a physical model module and a search module, which can be independently modified, improved, or made more sophisticated. 7 refs., 1 fig

  11. An alarm processing system for a nuclear power plant using artificial intelligence techniques

    International Nuclear Information System (INIS)

    This paper reports on an alarm processing system (APS) developed that uses artificial intelligence techniques to help operators to make decisions. Alarms in nuclear power plants are classified into generalized and special alarms. Generalized alarms are further classified into global and local alarms. For each type of alarm, the specific processing rules are applied to filter and suppress unnecessary and potentially misleading alarms. The processing for the generalized alarms is based on model-based reasoning. The special alarms are processed by the cause-consequence check rules. The priorities of alarms are determined according to both the plant state and the consistencies among the alarms. This APS is built on a workstation using the Prolog language

  12. Pursing Contamination Detection on Aircraft CFRP Surfaces By Artificial Olfaction Techniques

    Science.gov (United States)

    De Vito, Saverio; Massera, Ettore; Fattoruso, Grazia; Miglietta, Maria Lucia; Di Francia, Girolamo

    2011-09-01

    Carbon Fiber Reinforced Polymer (CFRP) structures can be easily bonded via adhesive assembly procedures but their cleanliness is of fundamental importance to ensure the strength of the adhesive bonding. Actually, surface contamination by several aeronautics fluids eventually results in weak or kissing bonds. The goal of our research work is to investigate solid state chemical sensors and artificial olfaction techniques (AO) for the detection of CFRP surface contamination by aeronautic fluids. This result will allow the implementation of an instrumental NDT procedure for CFRP surface cleanliness assessment prior to bonding. Herein, results of our first experimental setup, based on the use of an array of polymer sensors for the detection of aeronautic fluids contamination, are presented.

  13. Assisted Reproductive Techniques in Farm Animal - From Artificial Insemination to Nanobiotechnology

    Directory of Open Access Journals (Sweden)

    O P Verma

    2012-10-01

    Full Text Available It has become evident that advances in farm animal reproduction have become increasingly dependent on advance scientific research in addition to an understanding of the physiological processes involved in reproduction. The use of assisted reproductive techniques (ART has helped owners to produce offspring from valuable farm animals that were considered infertile using standard breeding techniques. This chapter constitutes an update of recent developments in the field of assisted reproduction includes Artificial insemination, Embryo transfer, in vitro fertilization, embryo cryopreservation, Sexing of semen and embryos, cloning, transgenesis, stem cell technology, embryo genomics, micro and nanotechnology has been included. Recently in some of these fields remarkable progress has been made. None the less, imperfections are remaining and sustained efforts will be required to optimize existing and invent new technologies. Before referring an animal for an ART, the practitioner should be able to identify the underlying cause of subfertility of that animal. Knowing the complexity as well as the risks of these techniques, enables practitioners to refer a sub-fertile animal to the least complex and most appropriate and successful ART that can overcome specific causes of infertility. [Vet. World 2012; 5(5.000: 301-310

  14. Transformer Incipient Fault Prediction Using Combined Artificial Neural Network and Various Particle Swarm Optimisation Techniques.

    Science.gov (United States)

    Illias, Hazlee Azil; Chai, Xin Rui; Abu Bakar, Ab Halim; Mokhlis, Hazlie

    2015-01-01

    It is important to predict the incipient fault in transformer oil accurately so that the maintenance of transformer oil can be performed correctly, reducing the cost of maintenance and minimise the error. Dissolved gas analysis (DGA) has been widely used to predict the incipient fault in power transformers. However, sometimes the existing DGA methods yield inaccurate prediction of the incipient fault in transformer oil because each method is only suitable for certain conditions. Many previous works have reported on the use of intelligence methods to predict the transformer faults. However, it is believed that the accuracy of the previously proposed methods can still be improved. Since artificial neural network (ANN) and particle swarm optimisation (PSO) techniques have never been used in the previously reported work, this work proposes a combination of ANN and various PSO techniques to predict the transformer incipient fault. The advantages of PSO are simplicity and easy implementation. The effectiveness of various PSO techniques in combination with ANN is validated by comparison with the results from the actual fault diagnosis, an existing diagnosis method and ANN alone. Comparison of the results from the proposed methods with the previously reported work was also performed to show the improvement of the proposed methods. It was found that the proposed ANN-Evolutionary PSO method yields the highest percentage of correct identification for transformer fault type than the existing diagnosis method and previously reported works.

  15. Active load control techniques for wind turbines.

    Energy Technology Data Exchange (ETDEWEB)

    van Dam, C.P. (University of California, Davis, CA); Berg, Dale E.; Johnson, Scott J. (University of California, Davis, CA)

    2008-07-01

    This report provides an overview on the current state of wind turbine control and introduces a number of active techniques that could be potentially used for control of wind turbine blades. The focus is on research regarding active flow control (AFC) as it applies to wind turbine performance and loads. The techniques and concepts described here are often described as 'smart structures' or 'smart rotor control'. This field is rapidly growing and there are numerous concepts currently being investigated around the world; some concepts already are focused on the wind energy industry and others are intended for use in other fields, but have the potential for wind turbine control. An AFC system can be broken into three categories: controls and sensors, actuators and devices, and the flow phenomena. This report focuses on the research involved with the actuators and devices and the generated flow phenomena caused by each device.

  16. Evolving Spiking Neural Networks for Control of Artificial Creatures

    OpenAIRE

    Arash Ahmadi

    2013-01-01

    To understand and analysis behavior of complicated and intelligent organisms, scientists apply bio-inspired concepts including evolution and learning to mathematical models and analyses. Researchers utilize these perceptions in different applications, searching for improved methods andapproaches for modern computational systems. This paper presents a genetic algorithm based evolution framework in which Spiking Neural Network (SNN) of artificial creatures are evolved for higher chance of survi...

  17. Sensorless Direct Power Control of Induction Motor Drive Using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Abolfazl Halvaei Niasar

    2015-01-01

    Full Text Available This paper proposes the design of sensorless induction motor drive based on direct power control (DPC technique. It is shown that DPC technique enjoys all advantages of pervious methods such as fast dynamic and ease of implementation, without having their problems. To reduce the cost of drive and enhance the reliability, an effective sensorless strategy based on artificial neural network (ANN is developed to estimate rotor’s position and speed of induction motor. Developed sensorless scheme is a new model reference adaptive system (MRAS speed observer for direct power control induction motor drives. The proposed MRAS speed observer uses the current model as an adaptive model. The neural network has been then designed and trained online by employing a back propagation network (BPN algorithm. The estimator was designed and simulated in Simulink. Some simulations are carried out for the closed-loop speed control systems under various load conditions to verify the proposed methods. Simulation results confirm the performance of ANN based sensorless DPC induction motor drive in various conditions.

  18. Active Vibration Control of the Smart Plate Using Artificial Neural Network Controller

    Directory of Open Access Journals (Sweden)

    Mohit

    2015-01-01

    Full Text Available The active vibration control (AVC of a rectangular plate with single input and single output approach is investigated using artificial neural network. The cantilever plate of finite length, breadth, and thickness having piezoelectric patches as sensors/actuators fixed at the upper and lower surface of the metal plate is considered for examination. The finite element model of the cantilever plate is utilized to formulate the whole strategy. The compact RIO and MATLAB simulation software are exercised to get the appropriate results. The cantilever plate is subjected to impulse input and uniform white noise disturbance. The neural network is trained offline and tuned with LQR controller. The various training algorithms to tune the neural network are exercised. The best efficient algorithm is finally considered to tune the neural network controller designed for active vibration control of the smart plate.

  19. Multirobot Lunar Excavation and ISRU Using Artificial-Neural-Tissue Controllers

    International Nuclear Information System (INIS)

    Automation of site preparation and resource utilization on the Moon with teams of autonomous robots holds considerable promise for establishing a lunar base. Such multirobot autonomous systems would require limited human support infrastructure, complement necessary manned operations and reduce overall mission risk. We present an Artificial Neural Tissue (ANT) architecture as a control system for autonomous multirobot excavation tasks. An ANT approach requires much less human supervision and pre-programmed human expertise than previous techniques. Only a single global fitness function and a set of allowable basis behaviors need be specified. An evolutionary (Darwinian) selection process is used to 'breed' controllers for the task at hand in simulation and the fittest controllers are transferred onto hardware for further validation and testing. ANT facilitates 'machine creativity', with the emergence of novel functionality through a process of self-organized task decomposition of mission goals. ANT based controllers are shown to exhibit self-organization, employ stigmergy (communication mediated through the environment) and make use of templates (unlabeled environmental cues). With lunar in-situ resource utilization (ISRU) efforts in mind, ANT controllers have been tested on a multirobot excavation task in which teams of robots with no explicit supervision can successfully avoid obstacles, interpret excavation blueprints, perform layered digging, avoid burying or trapping other robots and clear/maintain digging routes

  20. Active Noise Control Using a Functional Link Artificial Neural Network with the Simultaneous Perturbation Learning Rule

    Directory of Open Access Journals (Sweden)

    Ya-li Zhou

    2009-01-01

    Full Text Available In practical active noise control (ANC systems, the primary path and the secondary path may be nonlinear and time-varying. It has been reported that the linear techniques used to control such ANC systems exhibit degradation in performance. In addition, the actuators of an ANC system very often have nonminimum-phase response. A linear controller under such situations yields poor performance. A novel functional link artificial neural network (FLANN-based simultaneous perturbation stochastic approximation (SPSA algorithm, which functions as a nonlinear mode-free (MF controller, is proposed in this paper. Computer simulations have been carried out to demonstrate that the proposed algorithm outperforms the standard filtered-x least mean square (FXLMS algorithm, and performs better than the recently proposed filtered-s least mean square (FSLMS algorithm when the secondary path is time-varying. This observation implies that the SPSA-based MF controller can eliminate the need of the modeling of the secondary path for the ANC system.

  1. Measure of pore size in micro filtration polymeric membrane using ultrasonic technique and artificial neural networks

    International Nuclear Information System (INIS)

    This work presents a study of the pore size in micro filtration polymeric membranes, used in the nuclear area for the filtration of radioactive liquid effluent, in the residual water treatment of the petrochemical industry, in the electronic industry for the ultrapure water production for the manufacture of conductors and laundering of microcircuits and in many other processes of separation. Diverse processes for measures of pores sizes in membranes exist, amongst these, electronic microscopy, of bubble point and mercury intrusion porosimetry, however the majority of these uses destructive techniques, of high cost or great time of analysis. The proposal of this work is to measure so great of pore being used ultrasonic technique in the time domain of the frequency and artificial neural networks. A receiving/generator of ultrasonic pulses, a immersion transducer of 25 MHz was used, a tank of immersion and microporous membranes of pores sizes of 0,2 μm, 0,4 μm, 0,6 μm, 8 μm, 10 μm and 12 μm. The ultrasonic signals after to cover the membrane, come back to the transducer (emitting/receiving) bringing information of the interaction of the signal with the membranes. These signals had been used for the training of neural networks, and these had supplied the necessary precision the distinction of the same ones. Soon after, technique with the one of electronic microscopy of sweepings was made the comparison of this. The experiment showed very resulted next to the results gotten with the MEV, what it indicated that the studied technique is ideal for measure of pore size in membranes for being not destructive and of this form to be able to be used also on-line of production. (author)

  2. Teaching artificial neural systems to drive: Manual training techniques for autonomous systems

    Science.gov (United States)

    Shepanski, J. F.; Macy, S. A.

    1987-01-01

    A methodology was developed for manually training autonomous control systems based on artificial neural systems (ANS). In applications where the rule set governing an expert's decisions is difficult to formulate, ANS can be used to extract rules by associating the information an expert receives with the actions taken. Properly constructed networks imitate rules of behavior that permits them to function autonomously when they are trained on the spanning set of possible situations. This training can be provided manually, either under the direct supervision of a system trainer, or indirectly using a background mode where the networks assimilates training data as the expert performs its day-to-day tasks. To demonstrate these methods, an ANS network was trained to drive a vehicle through simulated freeway traffic.

  3. Volume fraction prediction in biphasic flow using nuclear technique and artificial neural network

    Energy Technology Data Exchange (ETDEWEB)

    Salgado, Cesar M.; Brandao, Luis E.B., E-mail: otero@ien.gov.br, E-mail: brandao@ien.gov.br [Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil)

    2015-07-01

    The volume fraction is one of the most important parameters used to characterize air-liquid two-phase flows. It is a physical value to determine other parameters, such as the phase's densities and to determine the flow rate of each phase. These parameters are important to predict the flow pattern and to determine a mathematical model for the system. To study, for example, heat transfer and pressure drop. This work presents a methodology for volume fractions prediction in water-gas stratified flow regime using the nuclear technique and artificial intelligence. The volume fractions calculate in biphasic flow systems is complex and the analysis by means of analytical equations becomes very difficult. The approach is based on gamma-ray pulse height distributions pattern recognition by means of the artificial neural network. The detection system uses appropriate broad beam geometry, comprised of a ({sup 137}Cs) energy gamma-ray source and a NaI(Tl) scintillation detector in order measure transmitted beam whose the counts rates are influenced by the phases composition. These distributions are directly used by the network without any parameterization of the measured signal. The ideal and static theoretical models for stratified regime have been developed using MCNP-X code, which was used to provide training, test and validation data for the network. The detector also was modeled with this code and the results were compared to experimental photopeak efficiency measurements of radiation sources. The proposed network could obtain with satisfactory prediction of the volume fraction in water-gas system, demonstrating to be a promising approach for this purpose. (author)

  4. Artificial tektites: an experimental technique for capturing the shapes of spinning drops

    Science.gov (United States)

    Baldwin, Kyle A.; Butler, Samuel L.; Hill, Richard J. A.

    2015-01-01

    Determining the shapes of a rotating liquid droplet bound by surface tension is an archetypal problem in the study of the equilibrium shapes of a spinning and charged droplet, a problem that unites models of the stability of the atomic nucleus with the shapes of astronomical-scale, gravitationally-bound masses. The shapes of highly deformed droplets and their stability must be calculated numerically. Although the accuracy of such models has increased with the use of progressively more sophisticated computational techniques and increases in computing power, direct experimental verification is still lacking. Here we present an experimental technique for making wax models of these shapes using diamagnetic levitation. The wax models resemble splash-form tektites, glassy stones formed from molten rock ejected from asteroid impacts. Many tektites have elongated or `dumb-bell' shapes due to their rotation mid-flight before solidification, just as we observe here. Measurements of the dimensions of our wax `artificial tektites' show good agreement with equilibrium shapes calculated by our numerical model, and with previous models. These wax models provide the first direct experimental validation for numerical models of the equilibrium shapes of spinning droplets, of importance to fundamental physics and also to studies of tektite formation.

  5. Artificial intelligent techniques for optimizing water allocation in a reservoir watershed

    Science.gov (United States)

    Chang, Fi-John; Chang, Li-Chiu; Wang, Yu-Chung

    2014-05-01

    This study proposes a systematical water allocation scheme that integrates system analysis with artificial intelligence techniques for reservoir operation in consideration of the great uncertainty upon hydrometeorology for mitigating droughts impacts on public and irrigation sectors. The AI techniques mainly include a genetic algorithm and adaptive-network based fuzzy inference system (ANFIS). We first derive evaluation diagrams through systematic interactive evaluations on long-term hydrological data to provide a clear simulation perspective of all possible drought conditions tagged with their corresponding water shortages; then search the optimal reservoir operating histogram using genetic algorithm (GA) based on given demands and hydrological conditions that can be recognized as the optimal base of input-output training patterns for modelling; and finally build a suitable water allocation scheme through constructing an adaptive neuro-fuzzy inference system (ANFIS) model with a learning of the mechanism between designed inputs (water discount rates and hydrological conditions) and outputs (two scenarios: simulated and optimized water deficiency levels). The effectiveness of the proposed approach is tested on the operation of the Shihmen Reservoir in northern Taiwan for the first paddy crop in the study area to assess the water allocation mechanism during drought periods. We demonstrate that the proposed water allocation scheme significantly and substantially avails water managers of reliably determining a suitable discount rate on water supply for both irrigation and public sectors, and thus can reduce the drought risk and the compensation amount induced by making restrictions on agricultural use water.

  6. Evaluation of biological control agents for mosquitoes control in artificial breeding places

    Institute of Scientific and Technical Information of China (English)

    Salim Abadi Yaser; Vatandoost Hassan; Rassi Yavar; Abai Mohammad Reza; Sanei Dehkordi Ali Reza; Paksa Azim

    2010-01-01

    Objective:To evaluate the entomological impact of chlorpyrifos-methyl,Bacillus thuringiensis, andGambusia affinis on mosquitoes control in artificial breeding places.Methods:A Latin square design with 4 replicates was performed in order to evaluate the efficacy of chlorpyrifos-methyl,Bacillus thuringiensis, andGambusia affinis on larva. The larvicide was applied at the dosage of 100 mg a.h/ha,Bacillus thuringiensis at the recommended dosage and 10 fishes per m2 were applied at 1í1 m2 artificial breeding sites. The larval densities for both anopheline and culicine were counted according to larvae /10 dippers prior and 24 h after application.Results:All three control agents are effective for mosquito density reduction, and the difference between the three agents and the control is significant (P<0.05). There is also significant difference among chlorpyrifos-methyl,Bacillus thuringiensis andGambusia affinis.Bacillus thuringiensisexhibited more reduction on mosquito larval density than fish and larvicide (P<0.05).Conclusions:Bacillus thuringiensis in comparison with two other agents is the appropriate method for larviciding in the breeding places. Although long term assessing for biological activities as well as monitoring and mapping of resistance is required.

  7. Ultrasonic techniques for process monitoring and control.

    Energy Technology Data Exchange (ETDEWEB)

    Chien, H.-T.

    1999-03-24

    Ultrasonic techniques have been applied successfully to process monitoring and control for many industries, such as energy, medical, textile, oil, and material. It helps those industries in quality control, energy efficiency improving, waste reducing, and cost saving. This paper presents four ultrasonic systems, ultrasonic viscometer, on-loom, real-time ultrasonic imaging system, ultrasonic leak detection system, and ultrasonic solid concentration monitoring system, developed at Argonne National Laboratory in the past five years for various applications.

  8. Using artificial intelligence to control fluid flow computations

    Science.gov (United States)

    Gelsey, Andrew

    1992-01-01

    Computational simulation is an essential tool for the prediction of fluid flow. Many powerful simulation programs exist today. However, using these programs to reliably analyze fluid flow and other physical situations requires considerable human effort and expertise to set up a simulation, determine whether the output makes sense, and repeatedly run the simulation with different inputs until a satisfactory result is achieved. Automating this process is not only of considerable practical importance but will also significantly advance basic artificial intelligence (AI) research in reasoning about the physical world.

  9. Control Power Optimization using Artificial Intelligence for Hybrid Wing Body Aircraft

    OpenAIRE

    Chhabra, Rupanshi

    2015-01-01

    Traditional methods of control allocation optimization have shown difficulties in exploiting the full potential of controlling a large array of control surfaces. This research investigates the potential of employing artificial intelligence methods like neurocomputing to the control allocation optimization problem of Hybrid Wing Body (HWB) aircraft concepts for minimizing control power, hinge moments, and actuator forces, while keeping the system weights within acceptable limits. The main obje...

  10. Artificial Leg Design and Control Research of a Biped Robot with Heterogeneous Legs Based on PID Control Algorithm

    Directory of Open Access Journals (Sweden)

    Hualong Xie

    2015-04-01

    Full Text Available A biped robot with heterogeneous legs (BRHL is proposed to provide an ideal test-bed for intelligent bionic legs (IBL. To make artificial leg gait better suited to a human, a four-bar mechanism is used as its knee joint, and a pneumatic artificial muscle (PAM is used as its driving source. The static mathematical model of PAM is established and the mechanical model of a single degree of freedom of a knee joint driven by PAM is analyzed. A control simulation of an artificial leg based on PID control algorithm is carried out and the simulation results indicate that the artificial leg can simulate precisely a normal human walking gait.

  11. Estimation of Sub Hourly Glacier Albedo Values Using Artificial Intelligence Techniques

    Science.gov (United States)

    Moya Quiroga, Vladimir; Mano, Akira; Asaoka, Yoshihiro; Udo, Keiko; Kure, Shuichi; Mendoza, Javier

    2013-04-01

    Glaciers are the most important fresh water reservoirs storing about 67% of total fresh water. Unfortunately, they are retreating and some small glaciers have already disappeared. Thus, snow glacier melt (SGM) estimation plays an important role in water resources management. Whether SGM is estimated by complete energy balance or a simplified method, albedo is an important data present in most of the methods. However, this is a variable value depending on the ground surface and local conditions. The present research presents a new approach for estimating sub hourly albedo values using different artificial intelligence techniques such as artificial neural networks and decision trees along with measured and easy to obtain data. . The models were developed using measured data from the Zongo-Ore station located in the Bolivian tropical glacier Zongo (68°10' W, 16°15' S). This station automatically records every 30 minutes several meteorological parameters such as incoming short wave radiation, outgoing short wave radiation, temperature or relative humidity. The ANN model used was the Multi Layer Perceptron, while the decision tree used was the M5 model. Both models were trained using the WEKA software and validated using the cross validation method. After analysing the model performances, it was concluded that the decision tree models have a better performance. The model with the best performance was then validated with measured data from the Equatorian tropical glacier Antizana (78°09'W, 0°28'S). The model predicts the sub hourly albedo with an overall mean absolute error of 0.103. The highest errors occur for albedo measured values higher than 0.9. Considering that this is an extreme value coincident with low measured values of incoming short wave radiation, it is reasonable to assume that such values include errors due to censored data. Assuming a maximum albedo of 0.9 improved the accuracy of the model reducing the MAE to less than 0.1. Considering that the

  12. Adaptive Artificial Intelligence Based Model Base Controller: Applied to Surgical Endoscopy Telemanipulator

    Directory of Open Access Journals (Sweden)

    Farzin Piltan

    2013-08-01

    Full Text Available This research involved developing a surgical robot assistant using an articulated PUMA robot running on a linear or nonlinear axis. The research concentrated on studying the artificial intelligence based switching computed torque controller to localization of an endoscopic tool. Results show that the switching artificial nonlinear control algorithm is capable to design a stable controller. For this system, error was used as the performance metric. Positioning of the endoscopic manipulator relative to the world coordinate frame was possible to within 0.05 inch. Error in maintaining a constant point in space is evident during repositioning however this was caused by limitations in the robot arm.

  13. Optimum Design of Fractional Order PID Controller for an AVR System Using an Improved Artificial Bee Colony Algorithm

    Institute of Scientific and Technical Information of China (English)

    ZHANG Dong-Li; TANG Ying-Gan; GUAN Xin-Ping

    2014-01-01

    Fractional order proportional-integral-derivative (FOPID) controller generalizes the standard PID controller. Compared to PID controller, FOPID controller has more pa-rameters and the tuning of parameters is more complex. In this paper, an improved artificial bee colony algorithm, which com-bines cyclic exchange neighborhood with chaos (CNC-ABC), is proposed for the sake of tuning the parameters of FOPID con-troller. The characteristic of the proposed CNC-ABC exists in two folds: one is that it enlarges the search scope of the solution by utilizing cyclic exchange neighborhood techniques, speeds up the convergence of artificial bee colony algorithm (ABC). The other is that it has potential to get out of local optima by exploit-ing the ergodicity of chaos. The proposed CNC-ABC algorithm is used to optimize the parameters of the FOPID controller for an automatic voltage regulator (AVR) system. Numerical sim-ulations show that the CNC-ABC FOPID controller has better performance than other FOPID and PID controllers.

  14. Modern insect control: Nuclear techniques and biotechnology

    International Nuclear Information System (INIS)

    The Symposium dealt primarily with genetic methods of insect control, including sterile insect technique (SIT), F1 sterility, compound chromosomes, translocations and conditional lethals. Research and development activities on various aspects of these control technologies were reported by participants during the Symposium. Of particular interest was development of F1 sterility as a practical method of controlling pest Lepidoptera. Genetic methods of insect control are applicable only on an area wide basis. They are species specific and thus do not reduce populations of beneficial insects or cause other environmental problems. Other papers presented reported on the potential use of radiation as a quarantine treatment for commodities in international trade and the use of radioisotopes as ''tags'' in studying insects

  15. Admission Control Techniques for UMTS System

    Directory of Open Access Journals (Sweden)

    P. Kejik

    2010-09-01

    Full Text Available Universal mobile telecommunications system (UMTS is one of the 3rd generation (3G cell phone technologies. The capacity of UMTS is interference limited. Radio resources management (RRM functions are therefore used. They are responsible for supplying optimum coverage, ensuring efficient use of physical resources, and providing the maximum planned capacity. This paper deals with admission control techniques for UMTS. An own UMTS simulation program and several versions of proposed admission control algorithms are presented in this paper. These algorithms are based on fuzzy logic and genetic algorithms. The performance of algorithms is verified via simulations.

  16. Control techniques for invasive alien plants

    OpenAIRE

    Michele de Sá Dechoum; Sílvia Renate Ziller

    2013-01-01

    Invasive alien species are recognized as a major threat to the conservation of biodiversity. These species should be managed based on local and regional environmental conditions. Control techniques were tested for ten invasive species in Santa Catarina State: the trees Casuarina equisetifolia, Hovenia dulcis, Psidium guajava, Syzygium cumini, and Terminalia catappa, and shrubs and herbs Rubus fruticosus, Furcraea foetida, Hedychium coronarium, Impatiens walleriana, and Tradescantia zebrina. T...

  17. Artificial intelligence in process control: Knowledge base for the shuttle ECS model

    Science.gov (United States)

    Stiffler, A. Kent

    1989-01-01

    The general operation of KATE, an artificial intelligence controller, is outlined. A shuttle environmental control system (ECS) demonstration system for KATE is explained. The knowledge base model for this system is derived. An experimental test procedure is given to verify parameters in the model.

  18. Application of Artificial Neural Network in Active Vibration Control of Diesel Engine

    Institute of Scientific and Technical Information of China (English)

    SUN Cheng-shun; ZHANG Jian-wu

    2005-01-01

    Artificial Neural Network (ANN) is applied to diesel twostage vibration isolating system and an AVC (Active Vibration Control) system is developed. Both identifier and controller are constructed by three-layer BP neural network. Besides computer simulation, experiment research is carried out on both analog bench and diesel bench. The results of simulation and experiment show a diminished response of vibration.

  19. Artificial Intelligence SVC Based Control of Two Machine Transmission System

    OpenAIRE

    Reza Bayat; Hamed ahmadi

    2013-01-01

    The main target in this paper is to present, design fuzzy logic controller (FLC) applied to static var compensator (SVC) on two machine transmission system to improve transient stability and rapid damping oscillations of synchronous generators, when power generators sudden changes occur.stability that also played important role in power systems. static var compensator with fuzzy logic controller (SVCFLC) is a new control strategy can help improve transient stability.The effect of three phase...

  20. OOP techniques for control systems software design

    International Nuclear Information System (INIS)

    The process of software design for nuclear power plants has several stages that must be fulfilled for a successful application. The first deals with the suitability of the concepts being applied to control the process itself, i.e. the control theory approach used, rationale for imposed limits, etc., that could be termed the formal specification generation. The second encompasses the processes of insuring the correctness of the software according to its formal specification. There are several approaches to dealing with these issues being developed worldwide, from the purely analytical to exhaustive testing methods. The purpose of our research effort is to explore and develop new tools for designing and testing control algorithms based in object-oriented programming (OOP) techniques and iconic interfaces. These two technologies will empower the designer by providing powerful yet simple means to introduce faults, investigate their effects and introduce configuration changes. Software development approaches that both encourage and force modularity with explicit interfacing definition could be of great help towards automatic software verification techniques. It is in this context that OOP techniques could play an important role, since they could be thought of as independent units interacting through allowed communication channels. Object classes implementing most common algorithms have been developed and used in our research laboratory computing environment with good results. It is feasible, in principle at least, to design a topology advisor/verifier that parses the control algorithm to detect anomalous configurations. Future research topics include the development of a prototype topology parser to explore its potential applicability in software design. (Author) 6 refs., 2 figs

  1. PERFORMANCE OF PID CONTROLLER OF NONLINEAR SYSTEM USING SWARM INTELLIGENCE TECHNIQUES

    Directory of Open Access Journals (Sweden)

    Neeraj Jain

    2016-07-01

    Full Text Available In this paper swarm intelligence based PID controller tuning is proposed for a nonlinear ball and hoop system. Particle swarm optimization (PSO, Artificial bee colony (ABC, Bacterial foraging optimization (BFO is some example of swarm intelligence techniques which are focused for PID controller tuning. These algorithms are also tested on perturbed ball and hoop model. Integral square error (ISE based performance index is used for finding the best possible value of controller parameters. Matlab software is used for designing the ball and hoop model. It is found that these swarm intelligence techniques have easy implementation & lesser settling & rise time compare to conventional methods.

  2. Research review: Indoor air quality control techniques

    International Nuclear Information System (INIS)

    Techniques for controlling the concentration of radon, formaldehyde, and combustion products in the indoor air are reviewed. The most effective techniques, which are generally based on limiting or reducing indoor pollutant source strengths, can decrease indoor pollutant concentrations by a factor of 3 to 10. Unless the initial ventilation rate is unusually low, it is difficult to reduce indoor pollutant concentrations more than approximately 50% by increasing the ventilation rate of an entire building. However, the efficiency of indoor pollutant control by ventilation can be enhanced through the use of local exhaust ventilation near concentrated sources of pollutants, by minimizing short circuiting of air from supply to exhaust when pollutant sources are dispersed and, in some situations, by promoting a displacement flow of air and pollutants toward the exhaust. Active air cleaning is also examined briefly. Filtration and electrostatic air cleaning for removal of particles from the indoor air are the most practical and effective currently available techniques of air cleaning. 49 refs., 7 figs

  3. Artificial Intelligence Approach to Support Statistical Quality Control Teaching

    Science.gov (United States)

    Reis, Marcelo Menezes; Paladini, Edson Pacheco; Khator, Suresh; Sommer, Willy Arno

    2006-01-01

    Statistical quality control--SQC (consisting of Statistical Process Control, Process Capability Studies, Acceptance Sampling and Design of Experiments) is a very important tool to obtain, maintain and improve the Quality level of goods and services produced by an organization. Despite its importance, and the fact that it is taught in technical and…

  4. Using Weightless Neural Networks for Vergence Control in an Artificial Vision System

    Directory of Open Access Journals (Sweden)

    Karin S. Komati

    2003-01-01

    Full Text Available This paper presents a methodology we have developed and used to implement an artificial binocular vision system capable of emulating the vergence of eye movements. This methodology involves using weightless neural networks (WNNs as building blocks of artificial vision systems. Using the proposed methodology, we have designed several architectures of WNN-based artificial vision systems, in which images captured by virtual cameras are used for controlling the position of the ‘foveae’ of these cameras (high-resolution region of the images captured. Our best architecture is able to control the foveae vergence movements with average error of only 3.58 image pixels, which is equivalent to an angular error of approximately 0.629°.

  5. Application of Meta-Heuristic Hybrid Artificial Intelligence Techniques for Modeling of Bonding Strength of Plywood Panels

    OpenAIRE

    Demirkır, Cenk; Kahraman, Hamdi Tolga; ÇOLAKOĞLU*, Gürsel

    2014-01-01

    Plywood, which is one of the most important wood based panels, has many usage areas changing from traffic signs to building constructions in many countries. It is known that the high quality plywood panel manufacturing has been achieved with a good bonding under the optimum pressure conditions depending on adhesive type. This is a study of determining the using possibilities of modern meta-heuristic hybrid artificial intelligence techniques such as IKE and AANN methods for prediction of bondi...

  6. Development of a Rain Down Technique to Artificially Infest Hemlocks with the Hemlock Woolly Adelgid, Adelges tsugae

    OpenAIRE

    Jetton, Robert M.; Mayfield, Albert E.; Zaidee L. Powers

    2014-01-01

    The hemlock woolly adelgid Adelges tsugae Annand (Hemiptera: Adelgidae), is a non-native invasive pest that has caused widespread decline and mortality of eastern hemlock (Tsuga canadensis (L.) Carr. (Pinales: Pinaceae)) and Carolina hemlock (T. caroliniana Engelm.) in the eastern United States. Our preliminary experiments evaluated the utility of a rain-down technique to induce artificial infestations of A. tsugae on hemlock seedlings en masse. Experiments were conducted in PVC (1 m3) cages ...

  7. Sterile insect technique for tsetse control and eradication

    International Nuclear Information System (INIS)

    The current publication contains the contributions made by scientists who participated in the fourth Co-ordinated Research Programme. A range of topics, covering both field and laboratory activities, was addressed: Eradication of Glossina palpalis palpalis (Robineau-Desvoidy) (Diptera: Glossinidae) from agropastoral land in Central Nigeria by means of the sterile insect technique; Research and development in the IAEA Laboratory at Seibersdorf in support of BICOT for the eradication of Glossina palpalis palpalis; Tsetse fly eradication in Burkina Faso and evaluation of traps and targets; Ecology of Glossina species inhabiting peridomestic agroecosystems in relation to options for tsetse fly control; Population dynamics of Glossina fuscipes fuscipes on Buvuma Island, Lake Victoria, Uganda; Population estimation from mark-recapture data: Equations for a pooled mark system and for pooled data, with applications to a study on island populations of tsetse flies in Zimbabwe; Surveillance of tsetse fly and cattle populations for trypanosomes in the BICOT area during the sterile insect technique control programme; Freeze dried blood and development of an artificial diet for blood feeding anthropods; Effects of the nutritional quality of locally obtained blood diets on the performance of Glossina palpalis palpalis fed in vitro; Mycetomes and symbionts of tsetse flies maintained on a membrane feeding system and the agents interfering with natural reproduction; Virus particles infection in laboratory reared Glossina pallidipes Austen (Diptera: Glossinidae); Influence of different nutritional sources on haemolymph composition and vitellogenesis in haematophagous arthropods; Effect of rearing diet on the injection rate in flies released for the control of tsetse populations by sterile males; Use of juvenile hormone mimics in the sterilization of tsetse flies; Studies of Glossina pallidipes and G. morsitans subspecies related to the genetic control of tsetse flies

  8. Novel USDA Mosquito Control Techniques for the US Military

    Science.gov (United States)

    Novel techniques that we developed at the USDA to protect deployed military troops from the threat of vector-borne diseases are described. Some of the methods developed included (1) novel military personal protection methods, (2) barrier treatments of artificial materials and natural vegetation, and...

  9. Mosquito Control Techniques Developed for the US Military

    Science.gov (United States)

    The USDA developed and field tested new techniques to reduce the risk to deployed military troops from vector-borne diseases. Some of the methods developed included (1) novel military personal protection methods, (2) barrier treatments of artificial materials and natural vegetation, and (3) ground a...

  10. Concurrency Control Technique in RFID Implementation

    Directory of Open Access Journals (Sweden)

    Ajaegbu C

    2014-03-01

    Full Text Available Database techniques have been used to proffer solution to some challenging situations that has to do with management of data in industries. This idea can also be valuable and implemented in managing the operation mode of some devices during t he design level stage. The proposition of Radio Frequency Identification Detection technology as a convenient and automatic instrument of identification and detection has shown value in usage in the society. However, it has been identified with some challenges such as collision despite its prospects. The need to mitigate collision between a reader and multiple tags is of importance for effective deployment of the technology. The paper aimed at integrating one of the concepts of database management technique of concurrency control known as Time-Stamp (TS in order to offer solution to the problem of collision in RFID implementation. This paper adopted a small scale business scenario which was used to illustrate the benefit this stands to offer in the real-life implementation. The paper concluded by arguing that this technique can be adopted and implemented and by such doing, will enhance further the performance of RFID technology.

  11. CONCURRENCY CONTROL TECHNIQUE IN RFID IMPLEMENTATION

    Directory of Open Access Journals (Sweden)

    Ajaegbu C

    2015-11-01

    Full Text Available Database techniques have been used to proffer solution to some challenging situations that has to do with management of data in industries. This idea can also be valuable and implemented in managing the operation mode of some devices during the design level stage. The proposition of Radio Frequency Identification Detection technology as a convenient and automatic instrument of identification and detection has shown value in usage in the society. However, it has been identified with some challenges such as collision despite its prospects. The need to mitigate collision between a reader and multiple tags is of importance for effective deployment of the technology. The paper aimed at integrating one of the concepts of database management technique of concurrency control known as Time-Stamp (TS in order to offer solution to the problem of collision in RFID implementation. This paper adopted a small scale business scenario which was used to illustrate the benefit this stands to offer in the real-life implementation. The paper concluded by arguing that this technique can be adopted and implemented and by such doing, will enhance further the performance of RFID technology.

  12. Fuzzy Controller Design Using Evolutionary Techniques for Twin Rotor MIMO System: A Comparative Study

    Directory of Open Access Journals (Sweden)

    H. A. Hashim

    2015-01-01

    Full Text Available This paper presents a comparative study of fuzzy controller design for the twin rotor multi-input multioutput (MIMO system (TRMS considering most promising evolutionary techniques. These are gravitational search algorithm (GSA, particle swarm optimization (PSO, artificial bee colony (ABC, and differential evolution (DE. In this study, the gains of four fuzzy proportional derivative (PD controllers for TRMS have been optimized using the considered techniques. The optimization techniques are developed to identify the optimal control parameters for system stability enhancement, to cancel high nonlinearities in the model, to reduce the coupling effect, and to drive TRMS pitch and yaw angles into the desired tracking trajectory efficiently and accurately. The most effective technique in terms of system response due to different disturbances has been investigated. In this work, it is observed that GSA is the most effective technique in terms of solution quality and convergence speed.

  13. Fuzzy Controller Design Using Evolutionary Techniques for Twin Rotor MIMO System: A Comparative Study.

    Science.gov (United States)

    Hashim, H A; Abido, M A

    2015-01-01

    This paper presents a comparative study of fuzzy controller design for the twin rotor multi-input multioutput (MIMO) system (TRMS) considering most promising evolutionary techniques. These are gravitational search algorithm (GSA), particle swarm optimization (PSO), artificial bee colony (ABC), and differential evolution (DE). In this study, the gains of four fuzzy proportional derivative (PD) controllers for TRMS have been optimized using the considered techniques. The optimization techniques are developed to identify the optimal control parameters for system stability enhancement, to cancel high nonlinearities in the model, to reduce the coupling effect, and to drive TRMS pitch and yaw angles into the desired tracking trajectory efficiently and accurately. The most effective technique in terms of system response due to different disturbances has been investigated. In this work, it is observed that GSA is the most effective technique in terms of solution quality and convergence speed. PMID:25960738

  14. Biologically Inspired Robotic Arm Control Using an Artificial Neural Oscillator

    Directory of Open Access Journals (Sweden)

    Woosung Yang

    2010-01-01

    Full Text Available We address a neural-oscillator-based control scheme to achieve biologically inspired motion generation. In general, it is known that humans or animals exhibit novel adaptive behaviors regardless of their kinematic configurations against unexpected disturbances or environment changes. This is caused by the entrainment property of the neural oscillator which plays a key role to adapt their nervous system to the natural frequency of the interacted environments. Thus we focus on a self-adapting robot arm control to attain natural adaptive motions as a controller employing neural oscillators. To demonstrate the excellence of entrainment, we implement the proposed control scheme to a single pendulum coupled with the neural oscillator in simulation and experiment. Then this work shows the performance of the robot arm coupled to neural oscillators through various tasks that the arm traces a trajectory. With these, the real-time closed-loop system allowing sensory feedback of the neural oscillator for the entrainment property is proposed. In particular, we verify an impressive capability of biologically inspired self-adaptation behaviors that enables the robot arm to make adaptive motions corresponding to an unexpected environmental variety.

  15. Closed-Loop Control and Advisory Mode Evaluation of an Artificial Pancreatic β Cell: Use of Proportional–Integral–Derivative Equivalent Model-Based Controllers

    Science.gov (United States)

    Percival, Matthew W.; Zisser, Howard; Jovanovič, Lois; Doyle, Francis J.

    2008-01-01

    Background Using currently available technology, it is possible to apply modern control theory to produce a closed-loop artificial β cell. Novel use of established control techniques would improve glycemic control, thereby reducing the complications of diabetes. Two popular controller structures, proportional–integral–derivative (PID) and model predictive control (MPC), are compared first in a theoretical sense and then in two applications. Methods The Bergman model is transformed for use in a PID equivalent model-based controller. The internal model control (IMC) structure, which makes explicit use of the model, is compared with the PID controller structure in the transfer function domain. An MPC controller is then developed as an optimization problem with restrictions on its tuning parameters and is shown to be equivalent to an IMC controller. The controllers are tuned for equivalent performance and evaluated in a simulation study as a closed-loop controller and in an advisory mode scenario on retrospective clinical data. Results Theoretical development shows conditions under which PID and MPC controllers produce equivalent output via IMC. The simulation study showed that the single tuning parameter for the equivalent controllers relates directly to the closed-loop speed of response and robustness, an important result considering system uncertainty. The risk metric allowed easy identification of instances of inadequate control. Results of the advisory mode simulation showed that suitable tuning produces consistently appropriate delivery recommendations. Conclusion The conditions under which PID and MPC are equivalent have been derived. The MPC framework is more suitable given the extensions necessary for a fully closed-loop artificial β cell, such as consideration of controller constraints. Formulation of the control problem in risk space is attractive, as it explicitly addresses the asymmetry of the problem; this is done easily with MPC. PMID:19885240

  16. Artificial control of muscle by endoneural multi electrode stimulation and sensing

    NARCIS (Netherlands)

    Rutten, W.L.C.; Bouwman, R.L.M.

    1991-01-01

    Artificial electrical stimulation of motor nerves for muscle control can be made selective by using intrafascicular micro electrode arrays which contact many individual or small groups of nerve fibres. If at the same time te electrode arrays could record afferent information from the stimulated musc

  17. Artificial Neural Network Based Rotor Capacitive Reactance Control for Energy Efficient Wound Rotor Induction Motor

    Directory of Open Access Journals (Sweden)

    K. Siva Kumar

    2012-01-01

    Full Text Available Problem statement: The Rotor reactance control by inclusion of external capacitance in the rotor circuit has been in recent research for improving the performances of Wound Rotor Induction Motor (WRIM. The rotor capacitive reactance is adjusted such that for any desired load torque the efficiency of the WRIM is maximized. The rotor external capacitance can be controlled using a dynamic capacitor in which the duty ratio is varied for emulating the capacitance value. This study presents a novel technique for tracking maximum efficiency point in the entire operating range of WRIM using Artificial Neural Network (ANN. The data for ANN training were obtained on a three phase WRIM with dynamic capacitor control and rotor short circuit at different speed and load torque values. Approach: A novel neural network model based on the back-propagation algorithm has been developed and trained in determining the maximum efficiency of the motor with no prior knowledge of the machine parameters. The input variables to the ANN are stator current (Is, Speed (N and Torque (Tm and the output variable is the duty ratio (D. Results: The target is pre-set and the accuracy of the ANN model is measured using Mean Square Error (MSE and R2 parameters. The result of R2 value of the proposed ANN model is found to be 0.99980. Conclusion: The optimal duty ratio and corresponding optimal rotor capacitance for improving the performances of the motor are predicted for low, medium and full loads by using proposed ANN model.

  18. Genetic diversity analysis of mitochondrial DNA control region in artificially propagated Chinese sucker Myxocyprinus asiaticus.

    Science.gov (United States)

    Wan, Yuan; Zhou, Chun-Hua; Ouyang, Shan; Huang, Xiao-Chen; Zhan, Yang; Zhou, Ping; Rong, Jun; Wu, Xiao-Ping

    2015-08-01

    The genetic diversity of the three major artificially propagated populations of Chinese sucker, an endangered freshwater fish species, was investigated using the sequences of mitochondrial DNA (mtDNA) control regions. Among the 89 individuals tested, 66 variable sites (7.26%) and 10 haplotypes were detected (Haplotype diversity Hd = 0.805, Nucleotide diversity π = 0.0287). In general, genetic diversity was lower in artificially propagated populations than in wild populations. This reduction in genetic diversity may be due to population bottlenecks, genetic drift and human selection. A stepping-stone pattern of gene flow was detected in the populations studied, showing much higher gene flow between neighbouring populations. To increase the genetic diversity, wild lineages should be introduced, and more lineages should be shared among artificially propagated populations.

  19. Controllable rectification of the axial expansion in the thermally driven artificial muscle

    Science.gov (United States)

    Yue, Donghua; Zhang, Xingyi; Yong, Huadong; Zhou, Jun; Zhou, You-He

    2015-09-01

    At present, the concept of artificial muscle twisted by polymers or fibers has become a hot issue in the field of intelligent material research according to its distinguishing advantages, e.g., high energy density, large-stroke, non-hysteresis, and inexpensive. The axial thermal expansion coefficient is an important parameter which can affect its demanding applications. In this letter, a device with high accuracy capacitive sensor is constructed to measure the axial thermal expansion coefficient of the twisted carbon fibers and yarns of Kevlar, and a theoretical model based on the thermal elasticity and the geometrical features of the twisted structure are also presented to predict the axial expansion coefficient. It is found that the calculated results take good agreements with the experimental data. According to the present experiment and analyses, a method to control the axial thermal expansion coefficient of artificial muscle is proposed. Moreover, the mechanism of this kind of thermally driven artificial muscle is discussed.

  20. Genetic diversity analysis of mitochondrial DNA control region in artificially propagated Chinese sucker Myxocyprinus asiaticus.

    Science.gov (United States)

    Wan, Yuan; Zhou, Chun-Hua; Ouyang, Shan; Huang, Xiao-Chen; Zhan, Yang; Zhou, Ping; Rong, Jun; Wu, Xiao-Ping

    2015-08-01

    The genetic diversity of the three major artificially propagated populations of Chinese sucker, an endangered freshwater fish species, was investigated using the sequences of mitochondrial DNA (mtDNA) control regions. Among the 89 individuals tested, 66 variable sites (7.26%) and 10 haplotypes were detected (Haplotype diversity Hd = 0.805, Nucleotide diversity π = 0.0287). In general, genetic diversity was lower in artificially propagated populations than in wild populations. This reduction in genetic diversity may be due to population bottlenecks, genetic drift and human selection. A stepping-stone pattern of gene flow was detected in the populations studied, showing much higher gene flow between neighbouring populations. To increase the genetic diversity, wild lineages should be introduced, and more lineages should be shared among artificially propagated populations. PMID:24409897

  1. Genetic Fuzzy Logic Control Technique for a Mobile Robot Tracking a Moving Target

    Directory of Open Access Journals (Sweden)

    Karim Benbouabdallah

    2013-01-01

    Full Text Available Target tracking is a crucial function for an autonomous mobile robot navigating in unknown environments. This paper presents a mobile robot target tracking approach based on artificial intelligence techniques. The proposed controller calculates both the mobile robot linear and angular velocities from the distance and angle that separate it to the moving target. The controller was designed using fuzzy logics theory and then, a genetic algorithm was applied to optimize the scaling factors of the fuzzy logic controller for better accuracy and smoothness of the robot trajectory. Simulation results illustrate that the proposed controller leads to good performances in terms of computational time and tracking errors convergence.

  2. The First Workshop on Artificial Intelligence Techniques for Ambient Intelligence (AITAmI '06)

    OpenAIRE

    Augusto, Juan Carlos; Shapiro, Daniel

    2007-01-01

    The first annual workshop on the role of AI in ambient intelligence was held in Riva de Garda, Italy, on August 29, 2006. The workshop was colocated with the European Conference on Artificial Intelligence (ECAI 2006). It provided an opportunity for researchers in a variety of AI subfields together with representatives of commercial interests to explore ambient intelligence technology and applications.

  3. Scientific approaches and techniques for negotiation : a game theoretic and artificial intelligence perspective

    NARCIS (Netherlands)

    Gerding, E.H.; Bragt, D.D.B. van; La Poutré, J.A.

    2000-01-01

    Due to the rapid growth of electronic environments (such as the Internet) much research is currently being performed on autonomous trading mechanisms. This report contains an overview of the current literature on negotiations in the fields of game theory and artificial intelligence (AI). Game theori

  4. Artificial intelligence techniques to optimize the EDC/NHS-mediated immobilization of cellulase on Eudragit L-100.

    Science.gov (United States)

    Zhang, Yu; Xu, Jing-Liang; Yuan, Zhen-Hong; Qi, Wei; Liu, Yun-Yun; He, Min-Chao

    2012-01-01

    Two artificial intelligence techniques, namely artificial neural network (ANN) and genetic algorithm (GA) were combined to be used as a tool for optimizing the covalent immobilization of cellulase on a smart polymer, Eudragit L-100. 1-Ethyl-3-(3-dimethyllaminopropyl) carbodiimide (EDC) concentration, N-hydroxysuccinimide (NHS) concentration and coupling time were taken as independent variables, and immobilization efficiency was taken as the response. The data of the central composite design were used to train ANN by back-propagation algorithm, and the result showed that the trained ANN fitted the data accurately (correlation coefficient R(2) = 0.99). Then a maximum immobilization efficiency of 88.76% was searched by genetic algorithm at a EDC concentration of 0.44%, NHS concentration of 0.37% and a coupling time of 2.22 h, where the experimental value was 87.97 ± 6.45%. The application of ANN based optimization by GA is quite successful. PMID:22942683

  5. Artificial Intelligence Techniques to Optimize the EDC/NHS-Mediated Immobilization of Cellulase on Eudragit L-100

    Science.gov (United States)

    Zhang, Yu; Xu, Jing-Liang; Yuan, Zhen-Hong; Qi, Wei; Liu, Yun-Yun; He, Min-Chao

    2012-01-01

    Two artificial intelligence techniques, namely artificial neural network (ANN) and genetic algorithm (GA) were combined to be used as a tool for optimizing the covalent immobilization of cellulase on a smart polymer, Eudragit L-100. 1-Ethyl-3-(3-dimethyllaminopropyl) carbodiimide (EDC) concentration, N-hydroxysuccinimide (NHS) concentration and coupling time were taken as independent variables, and immobilization efficiency was taken as the response. The data of the central composite design were used to train ANN by back-propagation algorithm, and the result showed that the trained ANN fitted the data accurately (correlation coefficient R2 = 0.99). Then a maximum immobilization efficiency of 88.76% was searched by genetic algorithm at a EDC concentration of 0.44%, NHS concentration of 0.37% and a coupling time of 2.22 h, where the experimental value was 87.97 ± 6.45%. The application of ANN based optimization by GA is quite successful. PMID:22942683

  6. Resfriamento artificial para o controle de Coleoptera em arroz armazenado em silo metálico

    Directory of Open Access Journals (Sweden)

    Sonia Maria Noemberg Lazzari

    2006-06-01

    Full Text Available Resfriamento artificial para o controle de Coleoptera em arroz armazenado em silo metálico. O objetivo desta pesquisa foi avaliar o efeito do resfriamento artificial de grãos de arroz para o controle de coleópteros-praga. O ar frio foi insuflado pelo sistema de aeração em um silo metálico com arroz-em-casca. A avaliação do tratamento foi feita quinzenalmente usando armadilhas caladores. As espécies de Coleoptera capturadas foram: Oryzaephilus surinamensis (60%; Cryptolestes ferrugineus (9%; Rhyzopertha dominica (16,5% e Sitophilus spp. (0,5%. Aos 28 dias, a temperatura média da massa de grãos era de 15ºC, e o número médio de insetos havia diminuído 76,8%. A aplicação de ar frio manteve as populações sob controle por aproximadamente 60 dias. Os resultados do monitoramento dos insetos e da temperatura indicaram que um novo ciclo de ar frio deveria ser aplicado nesse período para manter as populações sob controle. Também o manejo adequado da massa de grãos faz-se necessário para garantir resultados satisfatórios do resfriamento artificial.Artificial chilling to control Coleoptera in paddy rice stored in metallic silo. The objective of this research was to evaluate the effect of artificial chilling for the control of coleopterans in stored paddy rice. The cold air was insufflated through the aeration system of a metallic silo with paddy rice. Evaluation of insect number was made every 15 days using probe traps. The species of Coleoptera captured were: Oryzaephilus surinamensis (60%; Cryptolestes ferrugineus (9%; Rhyzopertha dominica (16.5% and Sitophilus spp. (0.5%. By the 28th day the average temperature of the grain mass was 15ºC, and the mean number of insects decreased 76.8%. The cold air application kept the insect populations under control for approximately 60 days. The results of temperature and insect monitoring indicated that a new cycle of cold air should be applied by that time to keep the populations under

  7. IDENTIFICATION OF MARKS ON TIRES USING ARTIFICIAL VISION FOR QUALITY CONTROL

    Directory of Open Access Journals (Sweden)

    André P. Dias

    2015-03-01

    Full Text Available Tire inspection is presently done by workers who have as their main problems, besides identifying the defects, the time available for defect identification and the inherent costs. Companies can become more sustainable by adopting automated methods to perform such type of processes, such as artificial vision, with advantages both in the processing time and in the incurred costs. This paper addresses the development of an artificial vision system that aims to be an asset in the field of tyre inspection, having as main characteristics its execution speed and its reliability. The conjugation of these criteria is a prerequisite for this system to be able to be integrated in inspection machines. The paper focusses on the study of three image processing methods to be used in the identification of marks (red dots on tires. In this work was used the free Open Computer Vision artificial vision library to process the images acquired by a Basler matrix camera. Two different techniques, namely Background Subtraction and Hough Transform, were tested to implement the solution. After developing the artificial vision inspection application, tests were made to measure the performance of both methods and the results were promising: processing time was low and, simultaneous, the achieved accuracy is high.

  8. Decade Review (1999-2009): Artificial Intelligence Techniques in Student Modeling

    Science.gov (United States)

    Drigas, Athanasios S.; Argyri, Katerina; Vrettaros, John

    Artificial Intelligence applications in educational field are getting more and more popular during the last decade (1999-2009) and that is why much relevant research has been conducted. In this paper, we present the most interesting attempts to apply artificial intelligence methods such as fuzzy logic, neural networks, genetic programming and hybrid approaches such as neuro - fuzzy systems and genetic programming neural networks (GPNN) in student modeling. This latest research trend is a part of every Intelligent Tutoring System and aims at generating and updating a student model in order to modify learning content to fit individual needs or to provide reliable assessment and feedback to student's answers. In this paper, we make a brief presentation of methods used to point out their qualities and then we attempt a navigation to the most representative studies sought in the decade of our interest after classifying them according to the principal aim they attempted to serve.

  9. Daily water level forecasting using wavelet decomposition and artificial intelligence techniques

    Science.gov (United States)

    Seo, Youngmin; Kim, Sungwon; Kisi, Ozgur; Singh, Vijay P.

    2015-01-01

    Reliable water level forecasting for reservoir inflow is essential for reservoir operation. The objective of this paper is to develop and apply two hybrid models for daily water level forecasting and investigate their accuracy. These two hybrid models are wavelet-based artificial neural network (WANN) and wavelet-based adaptive neuro-fuzzy inference system (WANFIS). Wavelet decomposition is employed to decompose an input time series into approximation and detail components. The decomposed time series are used as inputs to artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) for WANN and WANFIS models, respectively. Based on statistical performance indexes, the WANN and WANFIS models are found to produce better efficiency than the ANN and ANFIS models. WANFIS7-sym10 yields the best performance among all other models. It is found that wavelet decomposition improves the accuracy of ANN and ANFIS. This study evaluates the accuracy of the WANN and WANFIS models for different mother wavelets, including Daubechies, Symmlet and Coiflet wavelets. It is found that the model performance is dependent on input sets and mother wavelets, and the wavelet decomposition using mother wavelet, db10, can further improve the efficiency of ANN and ANFIS models. Results obtained from this study indicate that the conjunction of wavelet decomposition and artificial intelligence models can be a useful tool for accurate forecasting daily water level and can yield better efficiency than the conventional forecasting models.

  10. Terapias hormonales utilizadas en el control artificial de la madurez sexual en peces de cultivo: una revisión Hormone therapy for the artificial control of sexual maturity in fish culture: a review

    Directory of Open Access Journals (Sweden)

    I Valdebenito

    2008-01-01

    Full Text Available En la presente revisión bibliográfica se analiza el estado actual del control artificial de la madurez sexual en peces de cultivo utilizando terapias hormonales, analizando en forma crítica las ventajas y desventajas de las diferentes estrategias tecnológicas existentes para un cultivador. Se discute desde los primeros intentos exitosos realizados por Houssay (1930 en Argentina, hasta las últimas y cada vez más exitosas técnicas de liberación lenta y el uso cada vez mayor de inhibidores de la dopamina. Además, se discute el uso de metodologías no traumáticas que a la fecha no han resultado del todo exitosas.The present literature review analyzes the current state of artificial control of sexual maturity in fish culture using hormone therapy, evaluating the advantages and disadvantages of different technological strategies available. The discussion covers from the first successful attempt conducted by Houssay (1930, Argentina, up to the most recent and more effective techniques of slow release and the use of dopamine inhibitors. In addition, the evaluation of the use of non traumatic methodologies that up until now have not been entirely effective is covered.

  11. Control techniques for invasive alien plants

    Directory of Open Access Journals (Sweden)

    Michele de Sá Dechoum

    2013-03-01

    Full Text Available Invasive alien species are recognized as a major threat to the conservation of biodiversity. These species should be managed based on local and regional environmental conditions. Control techniques were tested for ten invasive species in Santa Catarina State: the trees Casuarina equisetifolia, Hovenia dulcis, Psidium guajava, Syzygium cumini, and Terminalia catappa, and shrubs and herbs Rubus fruticosus, Furcraea foetida, Hedychium coronarium, Impatiens walleriana, and Tradescantia zebrina. Treatments applied for trees were cut stump, frill and girdling or ring-barking followed by herbicide application, while the other species were treated with foliar spray, application of herbicide on the root system, cut stump and herbicide injection. The active ingredients tested were Triclopyr, Glyphosate, and the combination of Triclopyr + Fluroxipyr in concentrations from 2 to 6%, according to the species. The cut stump method was efficient for all of the woody species, while ring-barking and frilling followed by herbicide application and basal bark application resulted in different levels of efficiency for the species tested. The most efficient method for herbs and shrubs was foliar spray, and the least efficient methods were cut stump and herbicide injection.

  12. Control of a Heavy-Lift Robotic Manipulator with Pneumatic Artificial Muscles

    Directory of Open Access Journals (Sweden)

    Ryan M. Robinson

    2014-04-01

    Full Text Available Lightweight, compliant actuators are particularly desirable in robotic systems intended for interaction with humans. Pneumatic artificial muscles (PAMs exhibit these characteristics and are capable of higher specific work than comparably-sized hydraulic actuators and electric motors. The objective of this work is to develop a control algorithm that can smoothly and accurately track the desired motions of a manipulator actuated by pneumatic artificial muscles. The manipulator is intended for lifting humans in nursing assistance or casualty extraction scenarios; hence, the control strategy must be capable of responding to large variations in payload over a large range of motion. The present work first investigates the feasibility of two output feedback controllers (proportional-integral-derivative and fuzzy logic, but due to the limitations of pure output feedback control, a model-based feedforward controller is developed and combined with output feedback to achieve improved closed-loop performance. The model upon which the controller is based incorporates the internal airflow dynamics, the physical parameters of the pneumatic muscles and the manipulator dynamics. Simulations were performed in order to validate the control algorithms, guide controller design and predict optimal gains. Using real-time interface software and hardware, the controllers were implemented and experimentally tested on the manipulator, demonstrating the improved capability.

  13. Artificial biomembrane based on DPPC--Investigation into phase transition and thermal behavior through ellipsometric techniques.

    Science.gov (United States)

    González, Carmen M; Pizarro-Guerra, Guadalupe; Droguett, Felipe; Sarabia, Mauricio

    2015-10-01

    Organic thin film deposition presents a multiplicity of challenges. Most notably, layer thickness control, homogeneity and subsequent characterization have been not cleared yet. Phospholipid bilayers are frequently used to model cell membranes. Bilayers can be disrupted by changes in mechanical stress, pH and temperature. The strategy presented in this article is based on thermal study of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) through analysis of slight changes in material thickness. The sample was prepared by depositing X- or Y-type DPPC bilayers using Langmuir-Blodgett technique over silicon wafer. Thus, molecular inclination degree, mobility and stability of phases and their respective phase transitions were observed and analyzed through ellipsometric techniques during heating cycles and corroborated by Grazing Incidence X-ray Diffraction and Atomic Force Microcopy measurements. DPPC functional group vibrations were detected by Raman spectra analysis. Scanning Electron Microscope with Field Emission gun (FE-SEM) and conventional SEM micrographs were also used to characterize sample morphology, demonstrating that homogenous bilayer formations coexist with some vesicles or micelles at surface level. Contact angle measurements corroborate DPPC surface wettability, which is mainly related to surface treatment methods of silicon wafer used to create either hydrophilic or hydrophobic nature regarding the substrate surface. Also, shifting and intensity changes of certain functional groups into Raman spectra confirm water presence between DPPC layers. Signal analysis detects certain interdigitation between aliphatic chains. These studies correspond to the base of future biosensors based on proteins or antimicrobial peptides stabilized into phospholipid bilayers over thin hydrogel films as moist scaffold. PMID:26150275

  14. Optimal Fuzzy PID Controller with Adjustable Factors and Its Application to Intelligent Artificial Legs

    Institute of Scientific and Technical Information of China (English)

    Tan Guanzheng(谭冠政); Xiao Hongfeng; Wang Yuechao

    2004-01-01

    A new kind of optimal fuzzy PID controller is proposed, which contains two parts. One is an on-line fuzzy inference mechanism and another is a conventional PID controller. In the fuzzy inference mechanism, three adjustable factors xp, xi, and xd are introduced. Their function is to further modify and optimize the result of the fuzzy inference to make the controller have the optimal control effect on a given object. The optimal values of these factors are determined based on the ITAE criterion and the flexible polyhedron search algorithm of Nelder and Mead. This PID controller has been used to control a D.C. motor of the intelligent artificial leg designed by the authors. The result of computer simulation indicates that the design of this controller is very effective and can be widely used to control different kinds of objects and processes.

  15. Economic power dispatch of power systems with pollution control using artificial bee colony optimization

    OpenAIRE

    Linda SLIMANI; BOUKTIR, Tarek

    2013-01-01

    This paper presents a solution for the emission-controlled economic dispatch (ECED) problem of medium-sized power systems via an artificial bee colony algorithm. The ECED problem, which accounts for the minimization of both the fuel cost and the emission, is a multiple objective function problem. The objective is to minimize the total fuel cost of the generation and environmental pollution caused by fossil-based thermal generating units and to also maintain an acceptable system performa...

  16. Control of a hybrid compensator in a power network by an artificial neural network

    Directory of Open Access Journals (Sweden)

    I. S. Shaw

    1998-07-01

    Full Text Available Increased interest in the elimination of distortion in electrical power networks has led to the development of various compensator topologies. The increasing cost of electrical energy necessitates the cost-effective operation of any of these topologies. This paper considers the development of an artificial neural network based controller, trained by means of the backpropagation method, that ensures the cost-effective operation of the hybrid compensator consisting of various converters and filters.

  17. Approximate Matching as a Key Technique in Organization of Natural and Artificial Intelligence

    Science.gov (United States)

    Mack, Marilyn; Lapir, Gennadi M.; Berkovich, Simon

    2000-01-01

    The basic property of an intelligent system, natural or artificial, is "understanding". We consider the following formalization of the idea of "understanding" among information systems. When system I issues a request to system 2, it expects a certain kind of desirable reaction. If such a reaction occurs, system I assumes that its request was "understood". In application to simple, "push-button" systems the situation is trivial because in a small system the required relationship between input requests and desired outputs could be specified exactly. As systems grow, the situation becomes more complex and matching between requests and actions becomes approximate.

  18. Modeling of biodistribution of 90 Y-DOTA-hR3 by using artificial intelligence techniques

    International Nuclear Information System (INIS)

    In this work the biodistribution of radioimmunoconjugate 90Y-DOTA-hR3 was modeled by using an artificial neural network. In vivo stability of 90Y-DOTA-hR3 was determined in healthy male Wistar rats at 4, 24 and 48 hours, in different organs. A model describing the relationship between, by one hand, the incorporated dose and, by the other hand, organ and time was developed by using a multilayer perceptron neural network. Adjusted model was analyzed by several statistical tests. Outcomes shown that proposed neural model describes the relationship between the studied variables in a proper way. (Author)

  19. Artificial Intelligence Based Control Power Optimization on Tailless Aircraft. [ARMD Seedling Fund Phase I

    Science.gov (United States)

    Gern, Frank; Vicroy, Dan D.; Mulani, Sameer B.; Chhabra, Rupanshi; Kapania, Rakesh K.; Schetz, Joseph A.; Brown, Derrell; Princen, Norman H.

    2014-01-01

    Traditional methods of control allocation optimization have shown difficulties in exploiting the full potential of controlling large arrays of control devices on innovative air vehicles. Artificial neutral networks are inspired by biological nervous systems and neurocomputing has successfully been applied to a variety of complex optimization problems. This project investigates the potential of applying neurocomputing to the control allocation optimization problem of Hybrid Wing Body (HWB) aircraft concepts to minimize control power, hinge moments, and actuator forces, while keeping system weights within acceptable limits. The main objective of this project is to develop a proof-of-concept process suitable to demonstrate the potential of using neurocomputing for optimizing actuation power for aircraft featuring multiple independently actuated control surfaces. A Nastran aeroservoelastic finite element model is used to generate a learning database of hinge moment and actuation power characteristics for an array of flight conditions and control surface deflections. An artificial neural network incorporating a genetic algorithm then uses this training data to perform control allocation optimization for the investigated aircraft configuration. The phase I project showed that optimization results for the sum of required hinge moments are improved by more than 12% over the best Nastran solution by using the neural network optimization process.

  20. Artificial feel system using magneto-rheological fluid on aircraft control stick

    Science.gov (United States)

    Manoharan, Vignesh; Kim, Daewon

    2016-04-01

    The conventional feel system in aircraft occupies large space in the cockpit and has complicated designs. The primary objective of this research is to develop an artificial feel force system that can overcome some drawbacks of the current system. A novel feel system using magneto-rheological (MR) fluid is constructed to precisely control the shear stress under the magnetic field. To validate the functionality of the MR artificial feel system, the final system is fabricated and multiple tests are performed to acquire force-velocity characteristics that are compared to the mathematical model derived. In addition, the PID closed loop control algorithm is developed to simulate the dynamic system model. Both experimental and simulation results are compared to validate the derived system model. The system response time and sampling rates are evaluated and compared to the conventional system at the end. It is concluded that the developed artificial feel system can precisely control and acts as a fail proof system when incorporated with a modern fly-by-wire aircraft system.

  1. Sterile insect technique in codling moth control

    International Nuclear Information System (INIS)

    Exposure of mature pupae or adult codling moths, Cydia pomonella (L.), to 30-40 krad of gamma radiation induces a high level of sterility in the male and complete sterility in the female without seriously affecting behaviour except for sperm competitiveness which is drastically reduced. Substerilizing doses (below about 25 krad) have very little adverse effect and induces higher level of sterility in the F1 male than in the irradiated male parent. The most satisfactory method of measuring the population density of native moths is by examining fruit for larval exit holes. Population increase per generation depends largely on evening temperatures during the moth's reproductive period. The codling moth is a sedentary species, and its distribution is very uneven in commercial orchards. Neglected host trees must be sprayed or destroyed to avoid reinfestation of sterile insect release orchards with immigrant moths. Laboratory-reared moths may be marked externally with fluorescent powders or internally with calco oil red without adverse effects. Mass rearing is still unreliable and expensive, and prolonged colonization affects the insects' behaviour. Successful codling moth suppression was achieved in North America and/or Europe by release of sterile males, sterile females or sterile mixed sexes; by substerile males; and by F1 male progeny (released as diapausing larvae) of substerile males X untreated females. Arthropod predators and parasites held aphids and spider mites at noninjurious levels in most insect release orchards, but leafrollers eventually built up to damaging numbers. The sterile insect technique for commercial control of the codling moth is not feasible at this time because of high costs. (author)

  2. Position control of fishing line artificial muscles (coiled polymer actuators) from nylon thread

    Science.gov (United States)

    Arakawa, Takeshi; Takagi, Kentaro; Tahara, Kenji; Asaka, Kinji

    2016-04-01

    Recently, fishing line artificial muscle has been developed and is paid much attention due to the properties such as large contraction, light weight and extremely low cost. Typical fishing line artificial muscle is made from Nylon thread and made by just twisting the polymer. In this paper, because of the structure of the actuator, such actuators may be named as coiled polymer actuators (CPAs). In this paper, a CPA is fabricated from commercial Nylon fishing line and Ni-Cr alloy (Nichrome) wire is wound around it. The CPA contracts by the Joule heat generated by applied voltage to the Nichrome wire. For designing the control system, a simple model is proposed. According to the physical principle of the actuator, two first-order transfer functions are introduced to represent the actuator model. One is a system from the input power to the temperature and the other is a system from the temperature to the deformation. From the system identification result, it is shown that the dominant dynamics is the system from the input power to the temperature. Using the developed model, position control of the voltage-driven CPA is discussed. Firstly, the static nonlinearity from the voltage to the power is eliminated. Then, a 2-DOF PID controller which includes an inversion-based feed forward controller and a PID controller are designed. In order to demonstrate the proposed controller, experimental verification is shown.

  3. Artificial Intelligence Techniques for the Berth Allocation and Container Stacking Problems in Container Terminals

    Science.gov (United States)

    Salido, Miguel A.; Rodriguez-Molins, Mario; Barber, Federico

    The Container Stacking Problem and the Berth Allocation Problem are two important problems in maritime container terminal's management which are clearly related. Terminal operators normally demand all containers to be loaded into an incoming vessel should be ready and easily accessible in the terminal before vessel's arrival. Similarly, customers (i.e., vessel owners) expect prompt berthing of their vessels upon arrival. In this paper, we present an artificial intelligence based-integrated system to relate these problems. Firstly, we develop a metaheuristic algorithm for berth allocation which generates an optimized order of vessel to be served according to existing berth constraints. Secondly, we develop a domain-oriented heuristic planner for calculating the number of reshuffles needed to allocate containers in the appropriate place for a given berth ordering of vessels. By combining these optimized solutions, terminal operators can be assisted to decide the most appropriated solution in each particular case.

  4. Artificial Intelligence Techniques for river flow forecasting in the Seyhan River Catchment, Turkey

    Directory of Open Access Journals (Sweden)

    M. Firat

    2007-06-01

    Full Text Available The use of Artificial Intelligence methods is becoming increasingly common in the modeling and forecasting of hydrological and water resource processes. In this study, applicability of Adaptive Neuro Fuzzy Inference System (ANFIS and Artificial Neural Network (ANN methods, Generalized Regression Neural Networks (GRNN and Feed Forward Neural Networks (FFNN, for forecasting of daily river flow is investigated and the Seyhan catchment, located in the south of Turkey, is chosen as a case study. Totally, 5114 daily river flow data are obtained from river flow gauges station of Üçtepe (1818 on Seyhan River between the years 1986 and 2000. The data set are divided into three subgroups, training, testing and verification. The training and testing data set include totally 5114 daily river flow data and the number of verification data points is 731. The river flow forecasting models having various input structures are trained and tested to investigate the applicability of ANFIS and ANN methods. The results of ANFIS, GRNN and FFNN models for both training and testing are evaluated and the best fit forecasting model structure and method is determined according to criteria of performance evaluation. The best fit model is also trained and tested by traditional statistical methods and the performances of all models are compared in order to get more effective evaluation. Moreover ANFIS, GRNN and FFNN models are also verified by verification data set including 731 daily river flow data at the time period 1998–2000 and the results of models are compared. The results demonstrate that ANFIS model is superior to the GRNN and FFNN forecasting models, and ANFIS can be successfully applied and provide high accuracy and reliability for daily River flow forecasting.

  5. Development of a technique for level measurement in pressure vessels using thermal probes and artificial neural networks

    International Nuclear Information System (INIS)

    A technique for level measurement in pressure vessels was developed using thermal probes with internal cooling and artificial neural networks (ANN's). This new concept of thermal probes was experimentally tested in an experimental facility (BETSNI) with two test sections, ST1 and ST2. Two different thermal probes were designed and constructed: concentric tubes probe and U tube probe. A data acquisition system (DAS) was assembled to record the experimental data during the tests. Steady state and transient level tests were carried out and the experimental data obtained were used as learning and recall data sets in the ANN's program RETRO-05 that simulate a multilayer perceptron with backpropagation. The results of the analysis show that the technique can be applied for level measurements in pressure vessel. The technique is applied for a less input temperature data than the initially designed to the probes. The technique is robust and can be used in case of lack of some temperature data. Experimental data available in literature from electrically heated thermal probe were also used in the ANN's analysis producing good results. The results of the ANN's analysis show that the technique can be improved and applied to level measurements in pressure vessels. (author)

  6. Improvement of controlled pollination techniques of poplar

    Institute of Scientific and Technical Information of China (English)

    ZHOU Zhong-cheng; LIU Zong-you; HOU Kai-ju; SUN Xian-meng; ZHANG Ji-he; SHEN Bao-xian

    2008-01-01

    Over a number of years, in order to find substitutes for two traditional poplar pollination techniques: outdoor bridging trees and indoor cutting with water culture, research into two new pollination methods of uprooted outdoor seed trees and outdoor cutting branches was carried out. The advantages of two new and improved techniques were of efficiency, economy, safety and ease of operation. The methods can be applied in hybridization and breeding of poplar and other easy-to-root trees.

  7. Two applications of airtightness control techniques on big assemblies

    CERN Document Server

    Devallan, C; Marcellin, J

    1973-01-01

    Deals with two airtightness control techniques respectively applied on intersecting storage rings (ISR) at CERN in Geneva and on a liquid methane storage tank. These two big assemblies called for two different control techniques which use helium and ammonia respectively as tracer gas. Existing practical leakage detection techniques to meet industrial needs are discussed at the end of the article. (2 refs).

  8. The relationship between strategic control and conscious structural knowledge in artificial grammar learning.

    Science.gov (United States)

    Norman, Elisabeth; Scott, Ryan B; Price, Mark C; Dienes, Zoltan

    2016-05-01

    We address Jacoby's (1991) proposal that strategic control over knowledge requires conscious awareness of that knowledge. In a two-grammar artificial grammar learning experiment all participants were trained on two grammars, consisting of a regularity in letter sequences, while two other dimensions (colours and fonts) varied randomly. Strategic control was measured as the ability to selectively apply the grammars during classification. For each classification, participants also made a combined judgement of (a) decision strategy and (b) relevant stimulus dimension. Strategic control was found for all types of decision strategy, including trials where participants claimed to lack conscious structural knowledge. However, strong evidence of strategic control only occurred when participants knew or guessed that the letter dimension was relevant, suggesting that strategic control might be associated with - or even causally requires - global awareness of the nature of the rules even though it does not require detailed knowledge of their content. PMID:27055066

  9. Cascading effects of artificial light at night: resource-mediated control of herbivores in a grassland ecosystem

    OpenAIRE

    Bennie, Jonathan; Davies, Thomas W; Cruse, David; Inger, Richard; Gaston, Kevin J

    2015-01-01

    Artificial light at night has a wide range of biological effects on both plants and animals. Here, we review mechanisms by which artificial light at night may restructure ecological communities by modifying the interactions between species. Such mechanisms may be top-down (predator, parasite or grazer controlled), bottom-up (resource-controlled) or involve non-trophic processes, such as pollination, seed dispersal or competition. We present results from an experiment investigating both top-do...

  10. Assisted Reproductive Techniques in Farm Animal - From Artificial Insemination to Nanobiotechnology

    OpenAIRE

    O P Verma; Kumar, R.; Kumar, A.(State University of New York at Buffalo, Buffalo, USA); Chand, S

    2012-01-01

    It has become evident that advances in farm animal reproduction have become increasingly dependent on advance scientific research in addition to an understanding of the physiological processes involved in reproduction. The use of assisted reproductive techniques (ART) has helped owners to produce offspring from valuable farm animals that were considered infertile using standard breeding techniques. This chapter constitutes an update of recent developments in the field of assisted reproduction...

  11. Magnetic Levitation Technique for Active Vibration Control

    OpenAIRE

    Hoque, Emdadul; Mizuno, Takeshi

    2010-01-01

    A zero-power controlled magnetic levitation system has been presented in this chapter. The unique characteristic of the zero-power control system is that it can generate negative stiffness with zero control current in the steady-state which is realized in this chapter. The detail characteristics of the levitation system are investigated. Moreover, two major contributions, the stiffness adjustment and nonlinear compensation of the suspension system have been introduced elaborately. Often, ther...

  12. An artificial vision-based control system for automatic heliostat positioning offset correction in a central receiver solar power plant

    Energy Technology Data Exchange (ETDEWEB)

    Berenguel, M. [Universidad de Almeria, Dept. de Lenguajes y Computacion, La Canada Almeria (Spain); Rubio, F.R.; Lara, P.J.; Arahal, M.R.; Camacho, E.F.; Lopez, M. [Universidad de Sevilla, Dept. de Ingenieria de Sistemas y Automatica, Sevilla (Spain); Valverde, A. [Plataforma Solar de Almeria (PSA-CIEMAT), Tabernas (Almeria) (Spain)

    2004-07-01

    This paper presents the development of a simplified and automatic heliostat positioning offset correction control system using artificial vision techniques and common CCD devices. The heliostats of a solar power plant reflect solar radiation onto a receiver (in this case, a volumetric receiver) placed at the top of a tower in order to provide a desired energy flux distribution correlated with the coolant flow (in this case air mass flow) through the receiver, usually in an open loop control configuration. There exist error sources that increase the complexity of the control system, some of which are systematic ones, mainly due to tolerances, wrong mirror facets alignment (optical errors), errors due to the approximations made when calculating the solar position, etc., that produce errors (offsets) in the heliostat orientation (aiming point). The approximation adopted in this paper is based on the use of a B/W CCD camera to correct these deviations in an automatic way imitating the same procedure followed by the operators. The obtained images are used to estimate the distance between the sunbeam centroid projected by the heliostats and a target placed on the tower, this distance thus is used for low accuracy offset correction purposes. Basic threshold-based image processing techniques are used for automatic correction. (Author)

  13. An artificial neural network technique for downscaling GCM outputs to RCM spatial scale

    Directory of Open Access Journals (Sweden)

    R. Chadwick

    2011-12-01

    Full Text Available An Artificial Neural Network (ANN approach is used to downscale ECHAM5 GCM temperature (T and rainfall (R fields to RegCM3 regional model scale over Europe. The main inputs to the neural network were the ECHAM5 fields and topography, and RegCM3 topography. An ANN trained for the period 1960–1980 was able to recreate the RegCM3 1981–2000 mean T and R fields with reasonable accuracy. The ANN showed an improvement over a simple lapse-rate correction method for T, although the ANN R field did not capture all the fine-scale detail of the RCM field. An ANN trained over a smaller area of Southern Europe was able to capture this detail with more precision. The ANN was unable to accurately recreate the RCM climate change (CC signal between 1981–2000 and 2081–2100, and it is suggested that this is because the relationship between the GCM fields, RCM fields and topography is not constant with time and changing climate. An ANN trained with three ten-year "time-slices" was able to better reproduce the RCM CC signal, particularly for the full European domain. This approach shows encouraging results but will need further refinement before becoming a viable supplement to dynamical regional climate modelling of temperature and rainfall.

  14. Tactile on-chip pre-processing with techniques from artificial retinas

    Science.gov (United States)

    Maldonado-Lopez, R.; Vidal-Verdu, F.; Linan, G.; Roca, E.; Rodriguez-Vazquez, A.

    2005-06-01

    The interest in tactile sensors is increasing as their use in complex unstructured environments is demanded, like in telepresence, minimal invasive surgery, robotics etc. The matrix of pressure data these devices provide can be managed with many image processing algorithms to extract the required information. However, as in the case of vision chips or artificial retinas, problems arise when the array size and the computation complexity increase. Having a look to the skin, the information collected by every mechanoreceptor is not carried to the brain for its processing, but some complex pre-processing is performed to fit the limited throughput of the nervous system. This is specially important for high bandwidth demanding tasks. Experimental works report that neural response of skin mechanoreceptors encodes the change in local shape from an offset level rather than the absolute force or pressure distributions. This is also the behavior of the retina, which implements a spatio-temporal averaging. We propose the same strategy in tactile preprocessing, and we show preliminary results when it faces the detection of the slip, which involves fast real-time processing.

  15. Comparison of artificial intelligence techniques for prediction of soil temperatures in Turkey

    Science.gov (United States)

    Citakoglu, Hatice

    2016-08-01

    Soil temperature is a meteorological data directly affecting the formation and development of plants of all kinds. Soil temperatures are usually estimated with various models including the artificial neural networks (ANNs), adaptive neuro-fuzzy inference system (ANFIS), and multiple linear regression (MLR) models. Soil temperatures along with other climate data are recorded by the Turkish State Meteorological Service (MGM) at specific locations all over Turkey. Soil temperatures are commonly measured at 5-, 10-, 20-, 50-, and 100-cm depths below the soil surface. In this study, the soil temperature data in monthly units measured at 261 stations in Turkey having records of at least 20 years were used to develop relevant models. Different input combinations were tested in the ANN and ANFIS models to estimate soil temperatures, and the best combination of significant explanatory variables turns out to be monthly minimum and maximum air temperatures, calendar month number, depth of soil, and monthly precipitation. Next, three standard error terms (mean absolute error (MAE, °C), root mean squared error (RMSE, °C), and determination coefficient (R 2 )) were employed to check the reliability of the test data results obtained through the ANN, ANFIS, and MLR models. ANFIS (RMSE 1.99; MAE 1.09; R 2 0.98) is found to outperform both ANN and MLR (RMSE 5.80, 8.89; MAE 1.89, 2.36; R 2 0.93, 0.91) in estimating soil temperature in Turkey.

  16. Development of sediment load estimation models by using artificial neural networking techniques.

    Science.gov (United States)

    Hassan, Muhammad; Ali Shamim, M; Sikandar, Ali; Mehmood, Imran; Ahmed, Imtiaz; Ashiq, Syed Zishan; Khitab, Anwar

    2015-11-01

    This study aims at the development of an artificial neural network-based model for the estimation of weekly sediment load at a catchment located in northern part of Pakistan. The adopted methodology has been based upon antecedent sediment conditions, discharge, and temperature information. Model input and data length selection was carried out using a novel mathematical tool, Gamma test. Model training was carried out by using three popular algorithms namely Broyden-Fletcher-Goldfarb-Shanno (BFGS), back propagation (BP), and local linear regression (LLR) using forward selection of input variables. Evaluation of the best model was carried out on the basis of basic statistical parameters namely R-square, root mean squared error (RMSE), and mean biased error (MBE). Results indicated that BFGS-based ANN model outperformed all other models with significantly low values of RMSE and MBE. A strong correlation was also found between the observed and estimated sediment load values for the same model as the value of Nash-Sutcliffe model efficiency coefficient (R-square) was found to be quite high as well. PMID:26463089

  17. Artificial Intelligence Techniques to Optimize the EDC/NHS-Mediated Immobilization of Cellulase on Eudragit L-100

    Directory of Open Access Journals (Sweden)

    Min-Chao He

    2012-06-01

    Full Text Available Two artificial intelligence techniques, namely artificial neural network (ANN and genetic algorithm (GA were combined to be used as a tool for optimizing the covalent immobilization of cellulase on a smart polymer, Eudragit L-100. 1-Ethyl-3-(3-dimethyllaminopropyl carbodiimide (EDC concentration, N-hydroxysuccinimide (NHS concentration and coupling time were taken as independent variables, and immobilization efficiency was taken as the response. The data of the central composite design were used to train ANN by back-propagation algorithm, and the result showed that the trained ANN fitted the data accurately (correlation coefficient R2 = 0.99. Then a maximum immobilization efficiency of 88.76% was searched by genetic algorithm at a EDC concentration of 0.44%, NHS concentration of 0.37% and a coupling time of 2.22 h, where the experimental value was 87.97 ± 6.45%. The application of ANN based optimization by GA is quite successful.

  18. Artificial Reefs

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — An artificial reef is a human-made underwater structure, typically built to promote marine life in areas with a generally featureless bottom, control erosion, block...

  19. Comparison of Conventional and Modern Load Forecasting Techniques Based on Artificial Intelligence and Expert Systems

    Directory of Open Access Journals (Sweden)

    Badar ul Islam

    2011-09-01

    Full Text Available This paper picturesquely depicts the comparison of different methodologies adopted for predicting the load demand and highlights the changing trend and values under new circumstances using latest non analytical soft computing techniques employed in the field of electrical load forecasting. A very clear advocacy about the changing trends from conventional and obsolete to the modern techniques is explained in very simple way. Load forecast has been a central and an integral process in the planning and operation of electric utilities. Many techniques and approaches have been investigated to tackle this problem in the last two decades. These are often different in nature and apply different engineering considerations and economic analysis. Further a clear comparison is also presented between the past standard practices with the current methodology of electrical load demand forecasting. Besides all this, different important points are highlighted which need special attention while doing load forecasting when the environment is competitive and deregulated one.

  20. Determination of Complex-Valued Parametric Model Coefficients Using Artificial Neural Network Technique

    Directory of Open Access Journals (Sweden)

    A. M. Aibinu

    2010-01-01

    Full Text Available A new approach for determining the coefficients of a complex-valued autoregressive (CAR and complex-valued autoregressive moving average (CARMA model coefficients using complex-valued neural network (CVNN technique is discussed in this paper. The CAR and complex-valued moving average (CMA coefficients which constitute a CARMA model are computed simultaneously from the adaptive weights and coefficients of the linear activation functions in a two-layered CVNN. The performance of the proposed technique has been evaluated using simulated complex-valued data (CVD with three different types of activation functions. The results show that the proposed method can accurately determine the model coefficients provided that the network is properly trained. Furthermore, application of the developed CVNN-based technique for MRI K-space reconstruction results in images with improve resolution.

  1. Contribution of artificial intelligence to operation

    International Nuclear Information System (INIS)

    Artificial Intelligence techniques are already used in nuclear plants for assistance to operation: synthesis from numerous information sources may be then derived, based on expert knowledge. Artificial intelligence may be used also for quality and reliability assessment of software-based control-command systems. Various expert systems developed by CEA, EDF and Framatome are presented

  2. Integrated control of the cooling system and surface openings using the artificial neural networks

    International Nuclear Information System (INIS)

    This study aimed at suggesting an indoor temperature control method that can provide a comfortable thermal environment through the integrated control of the cooling system and the surface openings. Four control logic were developed, employing different application levels of rules and artificial neural network models. Rule-based control methods represented the conventional approach while ANN-based methods were applied for the predictive and adaptive controls. Comparative performance tests for the conventional- and ANN-based methods were numerically conducted for the double-skin-facade building, using the MATLAB (Matrix Laboratory) and TRNSYS (Transient Systems Simulation) software, after proving the validity by comparing the simulation and field measurement results. Analysis revealed that the ANN-based controls of the cooling system and surface openings improved the indoor temperature conditions with increased comfortable temperature periods and decreased standard deviation of the indoor temperature from the center of the comfortable range. In addition, the proposed ANN-based logic effectively reduced the number of operating condition changes of the cooling system and surface openings, which can prevent system failure. The ANN-based logic, however, did not show superiority in energy efficiency over the conventional logic. Instead, they have increased the amount of heat removal by the cooling system. From the analysis, it can be concluded that the ANN-based temperature control logic was able to keep the indoor temperature more comfortably and stably within the comfortable range due to its predictive and adaptive features. - Highlights: • Integrated rule-based and artificial neural network based logics were developed. • A cooling device and surface openings were controlled in an integrated manner. • Computer simulation method was employed for comparative performance tests. • ANN-based logics showed the advanced features of thermal environment. • Rule

  3. Use of nuclear techniques for evaluation of first service conception rate in dairy herds with artificial insemination in Chile

    International Nuclear Information System (INIS)

    The objective of this study was to identify causes of inefficiency in Artificial Insemination (AI) services in 12 dairy farms located in southern Chile. Milk progesterone concentration was determined on the day of breeding and then 10-12 and 21-22 days after AI. Data for semen and cow inseminated, including physical signs of oestrus, were recorded in a computer database (AIDA). Information from 713 cows with first services was analysed. The mean interval from calving to first service was 88.7 days and the mean interval from calving to conception was 107.9 days. The conception rate at first service was 61.9%. Incidence of incorrect AI, most likely due to erroneous heat detection, was 8.9%. Herd related problems affected efficiency of AI in 15.2%. The results show that important factors affecting reproductive performance include nutritional management, oestrus detection and AI technique. (author)

  4. From bioseparation to artificial micro-organs: microfluidic chip based particle manipulation techniques

    Science.gov (United States)

    Stelzle, Martin

    2010-02-01

    Microfluidic device technology provides unique physical phenomena which are not available in the macroscopic world. These may be exploited towards a diverse array of applications in biotechnology and biomedicine ranging from bioseparation of particulate samples to the assembly of cells into structures that resemble the smallest functional unit of an organ. In this paper a general overview of chip-based particle manipulation and separation is given. In the state of the art electric, magnetic, optical and gravitational field effects are utilized. Also, mechanical obstacles often in combination with force fields and laminar flow are employed to achieve separation of particles or molecules. In addition, three applications based on dielectrophoretic forces for particle manipulation in microfluidic systems are discussed in more detail. Firstly, a virus assay is demonstrated. There, antibody-loaded microbeads are used to bind virus particles from a sample and subsequently are accumulated to form a pico-liter sized aggregate located at a predefined position in the chip thus enabling highly sensitive fluorescence detection. Secondly, subcellular fractionation of mitochondria from cell homogenate yields pure samples as was demonstrated by Western Blot and 2D PAGE analysis. Robust long-term operation with complex cell homogenate samples while avoiding electrode fouling is achieved by a set of dedicated technical means. Finally, a chip intended for the dielectrophoretic assembly of hepatocytes and endothelial cells into a structure resembling a liver sinusoid is presented. Such "artificial micro organs" are envisioned as substance screening test systems providing significantly higher predictability with respect to the in vivo response towards a substance under test.

  5. Application of artificial neural network technique to uranium logging data interpretation

    International Nuclear Information System (INIS)

    The author describes the application of B-P technique to pertinent questions in uranium logging data interpretation. Adopting the improved B-P algorithm to establish network structure and thoroughly investigating the process, and the method constructing learning sample has been improved. Good results have been achieved through applying the B-P model to recognize lithologies and forecast porosity

  6. Inverse simulation system for manual-controlled rendezvous and docking based on artificial neural network

    Science.gov (United States)

    Zhou, Wanmeng; Wang, Hua; Tang, Guojin; Guo, Shuai

    2016-09-01

    The time-consuming experimental method for handling qualities assessment cannot meet the increasing fast design requirements for the manned space flight. As a tool for the aircraft handling qualities research, the model-predictive-control structured inverse simulation (MPC-IS) has potential applications in the aerospace field to guide the astronauts' operations and evaluate the handling qualities more effectively. Therefore, this paper establishes MPC-IS for the manual-controlled rendezvous and docking (RVD) and proposes a novel artificial neural network inverse simulation system (ANN-IS) to further decrease the computational cost. The novel system was obtained by replacing the inverse model of MPC-IS with the artificial neural network. The optimal neural network was trained by the genetic Levenberg-Marquardt algorithm, and finally determined by the Levenberg-Marquardt algorithm. In order to validate MPC-IS and ANN-IS, the manual-controlled RVD experiments on the simulator were carried out. The comparisons between simulation results and experimental data demonstrated the validity of two systems and the high computational efficiency of ANN-IS.

  7. Microsoft Kinect-Based Artificial Perception System for Control of Functional Electrical Stimulation Assisted Grasping

    Directory of Open Access Journals (Sweden)

    Matija Štrbac

    2014-01-01

    Full Text Available We present a computer vision algorithm that incorporates a heuristic model which mimics a biological control system for the estimation of control signals used in functional electrical stimulation (FES assisted grasping. The developed processing software acquires the data from Microsoft Kinect camera and implements real-time hand tracking and object analysis. This information can be used to identify temporal synchrony and spatial synergies modalities for FES control. Therefore, the algorithm acts as artificial perception which mimics human visual perception by identifying the position and shape of the object with respect to the position of the hand in real time during the planning phase of the grasp. This artificial perception used within the heuristically developed model allows selection of the appropriate grasp and prehension. The experiments demonstrate that correct grasp modality was selected in more than 90% of tested scenarios/objects. The system is portable, and the components are low in cost and robust; hence, it can be used for the FES in clinical or even home environment. The main application of the system is envisioned for functional electrical therapy, that is, intensive exercise assisted with FES.

  8. Artificial intelligence techniques applied to the development of a decision–support system for diagnosing celiac disease

    Science.gov (United States)

    Tenório, Josceli Maria; Hummel, Anderson Diniz; Cohrs, Frederico Molina; Sdepanian, Vera Lucia; Pisa, Ivan Torres; de Fátima Marin, Heimar

    2013-01-01

    Background Celiac disease (CD) is a difficult-to-diagnose condition because of its multiple clinical presentations and symptoms shared with other diseases. Gold-standard diagnostic confirmation of suspected CD is achieved by biopsying the small intestine. Objective To develop a clinical decision–support system (CDSS) integrated with an automated classifier to recognize CD cases, by selecting from experimental models developed using intelligence artificial techniques. Methods A web-based system was designed for constructing a retrospective database that included 178 clinical cases for training. Tests were run on 270 automated classifiers available in Weka 3.6.1 using five artificial intelligence techniques, namely decision trees, Bayesian inference, k-nearest neighbor algorithm, support vector machines and artificial neural networks. The parameters evaluated were accuracy, sensitivity, specificity and area under the ROC curve (AUC). AUC was used as a criterion for selecting the CDSS algorithm. A testing database was constructed including 38 clinical CD cases for CDSS evaluation. The diagnoses suggested by CDSS were compared with those made by physicians during patient consultations. Results The most accurate method during the training phase was the averaged one-dependence estimator (AODE) algorithm (a Bayesian classifier), which showed accuracy 80.0%, sensitivity 0.78, specificity 0.80 and AUC 0.84. This classifier was integrated into the web-based decision–support system. The gold-standard validation of CDSS achieved accuracy of 84.2% and k = 0.68 (p < 0.0001) with good agreement. The same accuracy was achieved in the comparison between the physician’s diagnostic impression and the gold standard k = 0. 64 (p < 0.0001). There was moderate agreement between the physician’s diagnostic impression and CDSS k = 0.46 (p = 0.0008). Conclusions The study results suggest that CDSS could be used to help in diagnosing CD, since the algorithm tested achieved excellent

  9. DETECTION OF MENDELIAN AND GENOTYPE FREQUENCY OF GROWTH HORMONE GENE IN ONGOLE CROSSBRED CATTLE MATED BY THE ARTIFICIAL INSEMINATION TECHNIQUE

    Directory of Open Access Journals (Sweden)

    U. Paputungan

    2012-06-01

    Full Text Available The objectives of this study were to detect the Mendelian mode inheritance of growth hormone (GH and to establish genotype frequency of GH gene in Ongole-crossbred cattle mated by the artificial insemination (AI technique. Total of 76 blood samples were collected from Ongole-crossbred cows and bulls (G0, and their progenies (G1 at the Tumaratas AI service center in North Sulawesi province, Indonesia. All blood samples were screened for the presence of GH locus using a PCR-RFLP method involving restricted enzyme Msp1 on 1.2 % of agarose gel. Data were analyzed using statistical program function in Excel XP. The results showed that GH locus using alleles of Msp1+ and Msp1- enzyme restriction in Ongole-crossbred cows and bulls was inherited to their Ongole-crossbred progenies following the Mendelian mode inheritance. This Mendelian inheritance generated by AI technique was not under genetic equilibrium for the Msp1 genotype frequencies in groups of G0 and G1. The breeding program using genotypes of bulls and cows (G0 for generating the genotype of GH Msp1 enzyme restriction by AI technique should be maintained to increase these various allele dispersion rates for breeding under genetic equilibrium of the Ongole-crossbred cattle population.

  10. Intraoperative glycemic control procedures and the use of an artificial pancreas

    Institute of Scientific and Technical Information of China (English)

    Koichi Yamashita; Tomoaki Yatabe

    2009-01-01

    Strict intraoperative glycemic control can significantly decrease the incidence of postoperative infection;however, anesthesiologists must carefully control blood glucose levels as well as properly manage the respiratory and cardiovascular systems. However,standard blood glucose measurement systems and insulin dosing algorithms, which are necessary for achieving strict glycemic control, have not yet been developed. An artificial pancreas (STG-22TM;Nikkiso Co., Tokyo, Japan) is considered a highly accurate blood glucose monitoring system capable of closedloopcontrol of blood glucose. The device has, however,many problems to be addressed since it is a large and expensive system with little versatility, and it requires a large amount of blood to be collected. Therefore,the development of less invasive and inexpensive systems with future technological progress is greatly anticipated.

  11. An optimized control of ventilation in coal mines based on artificial neural network

    Institute of Scientific and Technical Information of China (English)

    付华; 邵良杉

    2002-01-01

    According to the nonlinear and time-dependent features of the ventilation systems for coal mines, a neural network method is applied to control the ventilator for coal mines in real time. The technical processes of coal mine ventilation system are introduced, and the principle of controlling a ventilation fan is also explained in detail. The artificial neutral network method is used to calculate the wind quantity needed by work spots in coal mine on the basis of the data collected by the system, including ventilation conditions, environmental temperatures, humidity, coal dust and the contents of all kinds of poisonous and harmful gases. Then the speed of ventilation fan is controlled according to the required wind which is determined by an overall integration of data. A neural network method is presented for overall optimized solution or the genetic algorithm of simulated annealing.

  12. Photons and (artificial) atoms: an overview of optical spectroscopy techniques on quantum dots

    Science.gov (United States)

    Vamivakas, A. N.; Atatüre, M.

    2010-01-01

    In most branches within experimental physics technical prowess lies at the heart of many seminal works. From the observation of the photoelectric effect and the ultraviolet catastrophe that led to the development of quantum mechanics to the first transistor that shaped the modern age of electronics, significant physical insight has been achieved on the shoulders of technical advances and progress. Research on self-assembled quantum dots may be a drop in the sea of physics, but it still is no exception to this trend, and more physical insight continues to be revealed as the tools of the trade get increasingly more complex and advanced. This article is written primarily for senior undergraduate students and first year graduate students of experimental physics involving optically active quantum dots. More often than not, we have seen students shuffling through journal articles trying to relate the reported physics to the used experimental techniques. What we want to cover here is not in any way the history or the recent progress in quantum dot research - there are an ample number of topical books and review articles for that - but rather to highlight a selection of optics-based measurement techniques that have led to significant progress in our understanding of quantum dot physics as well as their applications in the last two decades. We hope a basic survey of the relevant optical spectroscopy techniques will help the newcomers in connecting the dots between measurements and physics.

  13. Advanced Control Techniques for WEC Wave Dragon

    DEFF Research Database (Denmark)

    Tedd, James; Kofoed, Jens Peter; Jasinski, M.;

    2007-01-01

    This paper presents the ongoing work on control of the Wave Dragon wave energy converter. Research is being conducted in and between several centers across Europe. This is building upon the knowledge gained in the prototype project, and will enable much better performance of the future deployment...... of the full scale Wave Dragon....

  14. Advanced Control Techniques for WEC Wave Dragon

    OpenAIRE

    Tedd, James; Kofoed, Jens Peter; Jasinski, M; Morris, A.; Friis-Madsen, E.; Wisniewski, Rafal; Bendtsen, Jan Dimon

    2007-01-01

      This paper presents the ongoing work on control of the Wave Dragon wave energy converter. Research is being conducted in and between several centers across Europe. This is building upon the knowledge gained in the prototype project, and will enable much better performance of the future deployment of the full scale Wave Dragon.

  15. Simulation Techniques and Prosthetic Approach Towards Biologically Efficient Artificial Sense Organs- An Overview

    OpenAIRE

    Neogi, Biswarup; Ghosal, Soumya; Mukherjee, Soumyajit; Das, Achintya; D N TIBAREWALA

    2011-01-01

    An overview of the applications of control theory to prosthetic sense organs including the senses of vision, taste and odor is being presented in this paper. Simulation aspect nowadays has been the centre of research in the field of prosthesis. There have been various successful applications of prosthetic organs, in case of natural biological organs dis-functioning patients. Simulation aspects and control modeling are indispensible for knowing system performance, and to generate an original a...

  16. Autonomous self-configuration of artificial neural networks for data classification or system control

    Science.gov (United States)

    Fink, Wolfgang

    2009-05-01

    Artificial neural networks (ANNs) are powerful methods for the classification of multi-dimensional data as well as for the control of dynamic systems. In general terms, ANNs consist of neurons that are, e.g., arranged in layers and interconnected by real-valued or binary neural couplings or weights. ANNs try mimicking the processing taking place in biological brains. The classification and generalization capabilities of ANNs are given by the interconnection architecture and the coupling strengths. To perform a certain classification or control task with a particular ANN architecture (i.e., number of neurons, number of layers, etc.), the inter-neuron couplings and their accordant coupling strengths must be determined (1) either by a priori design (i.e., manually) or (2) using training algorithms such as error back-propagation. The more complex the classification or control task, the less obvious it is how to determine an a priori design of an ANN, and, as a consequence, the architecture choice becomes somewhat arbitrary. Furthermore, rather than being able to determine for a given architecture directly the corresponding coupling strengths necessary to perform the classification or control task, these have to be obtained/learned through training of the ANN on test data. We report on the use of a Stochastic Optimization Framework (SOF; Fink, SPIE 2008) for the autonomous self-configuration of Artificial Neural Networks (i.e., the determination of number of hidden layers, number of neurons per hidden layer, interconnections between neurons, and respective coupling strengths) for performing classification or control tasks. This may provide an approach towards cognizant and self-adapting computing architectures and systems.

  17. Benchmark of experimental techniques for measuring and controlling suction

    OpenAIRE

    Muñoz, Juan Jorge; Tarantino, A.; Gallipoli, Domenico; Augarde, C.E.; V. Gennaro; Gómez, R.; Laloui, L.; Mancuso, C.; El Mountassir, G.; Wheeler, S. J.; Tombolato, S.; Toll, D.G.; Rojas Arias, Juan Carlos; Raveendiraraj, A.; Romero Morales, Enrique Edgar

    2011-01-01

    The paper presents a benchmarking study carried out within the ‘Mechanics of Unsaturated Soils for Engineering’ (MUSE) network aimed at comparing different techniques for measurement and control of suction. Techniques tested by the eight ‘Mechanics of Unsaturated Soils for Engineering’ research teams include axis-translation (pressure plate and suction-controlled oedometer), highcapacity tensiometer and osmotic technique. The soil used in the exercise was a mixture of uniform sand, sodium ...

  18. Technique for Controlling Spread of Limnotic Oncomelania

    Institute of Scientific and Technical Information of China (English)

    Li Damei(李大美); WANG Xiangsan(王祥三); LAI Yonggen

    2003-01-01

    Schistosomiasis is a parasitic disease mostly found in areas along the Changjiang River of China. The disease is spread solely through an intermediary named oncomelania, so its spread of schistosomiasis can be controlled by properly designing water intakes which prevent oncomelania from entering fanning land or residential areas. This paper reports a successful design process and a new oncomelania-free intake device. The design of the new intake is based on a sound research program in which extensive experimental studies were carried out to gain knowledge of oncomelania eco-hydraulic behavior and detailed flow field information through CFD simulation.

  19. Cerebellar-inspired algorithm for adaptive control of nonlinear dielectric elastomer-based artificial muscle

    Science.gov (United States)

    Assaf, Tareq; Rossiter, Jonathan M.; Porrill, John

    2016-01-01

    Electroactive polymer actuators are important for soft robotics, but can be difficult to control because of compliance, creep and nonlinearities. Because biological control mechanisms have evolved to deal with such problems, we investigated whether a control scheme based on the cerebellum would be useful for controlling a nonlinear dielectric elastomer actuator, a class of artificial muscle. The cerebellum was represented by the adaptive filter model, and acted in parallel with a brainstem, an approximate inverse plant model. The recurrent connections between the two allowed for direct use of sensory error to adjust motor commands. Accurate tracking of a displacement command in the actuator's nonlinear range was achieved by either semi-linear basis functions in the cerebellar model or semi-linear functions in the brainstem corresponding to recruitment in biological muscle. In addition, allowing transfer of training between cerebellum and brainstem as has been observed in the vestibulo-ocular reflex prevented the steady increase in cerebellar output otherwise required to deal with creep. The extensibility and relative simplicity of the cerebellar-based adaptive-inverse control scheme suggests that it is a plausible candidate for controlling this type of actuator. Moreover, its performance highlights important features of biological control, particularly nonlinear basis functions, recruitment and transfer of training. PMID:27655667

  20. Optimizing an Industrial Scale Naphtha Catalytic Reforming Plant Using a Hybrid Artificial Neural Network and Genetic Algorithm Technique

    Directory of Open Access Journals (Sweden)

    Sepehr Sadighi

    2015-07-01

    Full Text Available In this paper, a hybrid model for estimating the activity of a commercial Pt-Re/Al2O3 catalyst in an industrial scale heavy naphtha catalytic-reforming unit (CRU is presented. This model is also capable of predicting research octane number (RON and yield of gasoline. In the proposed model, called DANN, the decay function of heterogeneous catalysts is combined with a recurrent-layer artificial neural network. During a life cycle (919 days, fifty-eight points are selected for building and training the DANN (60%, nineteen data points for testing (20%, and the remained ones for validating steps. Results show that DANN can acceptably estimate the activity of catalyst during its life in consideration of all process variables. Moreover, it is confirmed that the proposed model is capable of predicting RON and yield of gasoline for unseen (validating data with AAD% (average absolute deviation of 0.272% and 0.755%, respectively. After validating the model, the octane barrel level (OCB of the plant is maximized by manipulating the inlet temperature of reactors, and hydrogen to hydrocarbon molar ratio whilst all process limitations are taken into account. During a complete life cycle results show that the decision variables, generated by the optimization program, can increase the RON, process yield and OCB of CRU to about 1.15%, 3.21%, and 4.56%, respectively. © 2015 BCREC UNDIP. All rights reserved.Received: 27th July 2014; Revised: 31st May 2015; Accepted: 31th May 2015 How to Cite: Sadighi, S., Mohaddecy, R.S., Norouzian, A. (2015. Optimizing an Industrial Scale Naphtha Catalytic Reforming Plant Using a Hybrid Artificial Neural Network and Genetic Algorithm Technique. Bulletin of Chemical Reaction Engineering & Catalysis, 10(2: 210-220. (doi:10.9767/bcrec.10.2.7171.210-220 Permalink/DOI: http://dx.doi.org/10.9767/bcrec.10.2.7171.210-220  

  1. Models of signal validation using artificial intelligence techniques applied to a nuclear reactor

    International Nuclear Information System (INIS)

    This work presents two models of signal validation in which the analytical redundancy of the monitored signals from a nuclear plant is made by neural networks. In one model the analytical redundancy is made by only one neural network while in the other it is done by several neural networks, each one working in a specific part of the entire operation region of the plant. Four cluster techniques were tested to separate the entire operation region in several specific regions. An additional information of systems' reliability is supplied by a fuzzy inference system. The models were implemented in C language and tested with signals acquired from Angra I nuclear power plant, from its start to 100% of power. (author)

  2. Recent advances in knowledge-based paradigms and applications enhanced applications using hybrid artificial intelligence techniques

    CERN Document Server

    Jain, Lakhmi

    2014-01-01

    This book presents carefully selected contributions devoted to the modern perspective of AI research and innovation. This collection covers several areas of applications and motivates new research directions. The theme across all chapters combines several domains of AI research , Computational Intelligence and Machine Intelligence including an introduction to  the recent research and models. Each of the subsequent chapters reveals leading edge research and innovative solution that employ AI techniques with an applied perspective. The problems include classification of spatial images, early smoke detection in outdoor space from video images, emergent segmentation from image analysis, intensity modification in images, multi-agent modeling and analysis of stress. They all are novel pieces of work and demonstrate how AI research contributes to solutions for difficult real world problems that benefit the research community, industry and society.

  3. Position and Speed Control of Brushless DC Motors Using Sensorless Techniques and Application Trends

    Directory of Open Access Journals (Sweden)

    Jaime Gómez-Gil

    2010-07-01

    Full Text Available This paper provides a technical review of position and speed sensorless methods for controlling Brushless Direct Current (BLDC motor drives, including the background analysis using sensors, limitations and advances. The performance and reliability of BLDC motor drivers have been improved because the conventional control and sensing techniques have been improved through sensorless technology. Then, in this paper sensorless advances are reviewed and recent developments in this area are introduced with their inherent advantages and drawbacks, including the analysis of practical implementation issues and applications. The study includes a deep overview of state-of-the-art back-EMF sensing methods, which includes Terminal Voltage Sensing, Third Harmonic Voltage Integration, Terminal Current Sensing, Back-EMF Integration and PWM strategies. Also, the most relevant techniques based on estimation and models are briefly analysed, such as Sliding-mode Observer, Extended Kalman Filter, Model Reference Adaptive System, Adaptive observers (Full-order and Pseudoreduced-order and Artificial Neural Networks.

  4. Establishing structure-property correlations and classification of base oils using statistical techniques and artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Kapur, G.S.; Sastry, M.I.S.; Jaiswal, A.K.; Sarpal, A.S

    2004-03-17

    The present paper describes various classification techniques like cluster analysis, principal component (PC)/factor analysis to classify different types of base stocks. The API classification of base oils (Group I-III) has been compared to a more detailed NMR derived chemical compositional and molecular structural parameters based classification in order to point out the similarities of the base oils in the same group and the differences between the oils placed in different groups. The detailed compositional parameters have been generated using {sup 1}H and {sup 13}C nuclear magnetic resonance (NMR) spectroscopic methods. Further, oxidation stability, measured in terms of rotating bomb oxidation test (RBOT) life, of non-conventional base stocks and their blends with conventional base stocks, has been quantitatively correlated with their {sup 1}H NMR and elemental (sulphur and nitrogen) data with the help of multiple linear regression (MLR) and artificial neural networks (ANN) techniques. The MLR based model developed using NMR and elemental data showed a high correlation between the 'measured' and 'estimated' RBOT values for both training (R=0.859) and validation (R=0.880) data sets. The ANN based model, developed using fewer number of input variables (only {sup 1}H NMR data) also showed high correlation between the 'measured' and 'estimated' RBOT values for training (R=0.881), validation (R=0.860) and test (R=0.955) data sets.

  5. Active structural control with stable fuzzy PID techniques

    CERN Document Server

    Yu, Wen

    2016-01-01

    This book presents a detailed discussion of intelligent techniques to measure the displacement of buildings when they are subjected to vibration. It shows how these techniques are used to control active devices that can reduce vibration 60–80% more effectively than widely used passive anti-seismic systems. After introducing various structural control devices and building-modeling and active structural control methods, the authors propose offset cancellation and high-pass filtering techniques to solve some common problems of building-displacement measurement using accelerometers. The most popular control algorithms in industrial settings, PD/PID controllers, are then analyzed and then combined with fuzzy compensation. The stability of this combination is proven with standard weight-training algorithms. These conditions provide explicit methods for selecting PD/PID controllers. Finally, fuzzy-logic and sliding-mode control are applied to the control of wind-induced vibration. The methods described are support...

  6. Landfill pollution control with isotope techniques

    International Nuclear Information System (INIS)

    Groundwater and surface water contamination by sanitary landfills is being monitored since 1989 in Italy by using isotope techniques combined with chemical analyses. The results obtained are considered mostly satisfactory for identifying sources of contaminants and predicting their behaviour. We present in this work the results of chemical and isotopic measurements performed on rainwater, surface water and groundwater samples, with the aim of investigating the fate of contaminants released from some landfills located near Ancona, Central Italy. The isotope determinations included δ18O, δ2H and tritium (3H). The first objective of these investigations is establishing the background values of the main environmental parameters related to contamination, and obtaining indication about source and residence time (age) of groundwater in the landfill proximity. In particular, the methods used for detecting groundwater and/or surface waters contamination derived from the landfill, are based on the occurrence of tritium activity anomalies and chemical concentration changes. In order to estimate the regional background of environmental tritium in shallow groundwater, we measured the tritium content of monthly rainwater samples collected in stations on the Apennines in proximity of Ancona. The tritium concentration ranged from 3 to 6 TU in winter months (October to April), and reached the maximum values (up to 14 TU) in summer months. The investigations of groundwater and surface water contamination were undertaken on landfills dismissed from 1986 to 1998. The isotopic and chemical monitoring was started one year ago and was carried out on leachates, surface waters and groundwater (the last sampled in several downstream wells). The tritium concentration in leachates can be very high, due to a still active tritium release from the landfill. Tritium values in wells outside of the landfill area, lower than in leachate but higher than the regional background of environmental

  7. Fuzzy-GA PID controller with incomplete derivation and its application to intelligent bionic artificial leg

    Institute of Scientific and Technical Information of China (English)

    谭冠政; 李安平

    2003-01-01

    An optimal PID controller with incomplete derivation is proposed based on fuzzy inference and the geneticalgorithm, which is called the fuzzy-GA PID controller with incomplete derivation. It consists of the off-line part andthe on-line part. In the off-line part, by taking the overshoot, rise time, and settling time of system unit step re-sponse as the performance indexes and by using the genetic algorithm, a group of optimal PID parameters K*p , Ti* ,and Tj are obtained, which are used as the initial values for the on-line tuning of PID parameters. In the on-linepart, based on K; , Ti* , and T*d and according to the current system error e and its time derivative, a dedicatedprogram is written, which is used to optimize and adjust the PID parameters on line through a fuzzy inference mech-anism to ensure that the system response has optimal dynamic and steady-state performance. The controller has beenused to control the D. C. motor of the intelligent bionic artificial leg designed by the authors. The result of computersimulation shows that this kind of optimal PID controller has excellent control performance and robust performance.

  8. An efficient artificial bee colony algorithm with application to nonlinear predictive control

    Science.gov (United States)

    Ait Sahed, Oussama; Kara, Kamel; Benyoucef, Abousoufyane; Laid Hadjili, Mohamed

    2016-05-01

    In this paper a constrained nonlinear predictive control algorithm, that uses the artificial bee colony (ABC) algorithm to solve the optimization problem, is proposed. The main objective is to derive a simple and efficient control algorithm that can solve the nonlinear constrained optimization problem with minimal computational time. Indeed, a modified version, enhancing the exploring and the exploitation capabilities, of the ABC algorithm is proposed and used to design a nonlinear constrained predictive controller. This version allows addressing the premature and the slow convergence drawbacks of the standard ABC algorithm, using a modified search equation, a well-known organized distribution mechanism for the initial population and a new equation for the limit parameter. A convergence statistical analysis of the proposed algorithm, using some well-known benchmark functions is presented and compared with several other variants of the ABC algorithm. To demonstrate the efficiency of the proposed algorithm in solving engineering problems, the constrained nonlinear predictive control of the model of a Multi-Input Multi-Output industrial boiler is considered. The control performances of the proposed ABC algorithm-based controller are also compared to those obtained using some variants of the ABC algorithms.

  9. The application of artificial intelligent techniques to accelerator operations at McMaster University

    International Nuclear Information System (INIS)

    In an era of downsizing and a limited pool of skilled accelerator personnel from which to draw replacements for an aging workforce, the impetus to integrate intelligent computer automation into the accelerator operator's repertoire is strong. However, successful deployment of an 'Operator's Companion' is not trivial. Both graphical and human factors need to be recognized as critical areas that require extra care when formulating the Companion. They include interactive graphical user's interface that mimics, for the operator, familiar accelerator controls; knowledge of acquisition phases during development must acknowledge the expert's mental model of machine operation; and automated operations must be seen as improvements to the operator's environment rather than threats of ultimate replacement. Experiences with the PACES Accelerator Operator Companion developed at two sites over the past three years are related and graphical examples are given. The scale of the work involves multi-computer control of various start-up/shutdown and tuning procedures for Model FN and KN Van de Graaff accelerators. The response from licensing agencies has been encouraging. (orig.)

  10. A case of perioperative glucose control by using an artificial pancreas in a patient with glycogen storage disease.

    Science.gov (United States)

    Yatabe, Tomoaki; Nakamura, Ryu; Kitagawa, Hiroyuki; Munekage, Masaya; Hanazaki, Kazuhiro

    2016-03-01

    A 57-year-old woman was diagnosed with type I glycogen storage disease in her twenties. She had undergone hepatectomy under general anesthesia with epidural anesthesia. Fifty minutes after the induction of anesthesia, a 20-gauge venous catheter was inserted in the patient's right hand, and an artificial pancreas (STG-55, Nikkiso Co., Tokyo, Japan) was connected for continuous glucose monitoring and automatic glucose control. Insulin was infused when the blood glucose level reached 120 mg/dL or higher, and glucose was infused when the level fell to 100 mg/dL or lower. After the Pringle maneuver, the blood glucose level increased, and insulin was administered automatically via an artificial pancreas. Hypoglycemia did not occur during the operation. After total parenteral nutrition was started in the intensive care unit (ICU), the blood glucose level increased, and the artificial pancreas controlled the blood glucose level through automatic insulin administration. Thirty-four hours after admission to the ICU, the artificial pancreas was removed because the blood sampling failed. After the removal of the artificial pancreas, blood glucose level was measured every 2 h until extubation. During the ICU stay, hypoglycemia never occurred, with the average blood glucose level being 144 mg/dL. In conclusion, the use of an artificial pancreas for perioperative blood glucose management in a patient with glycogen storage disease had the beneficial effect of enabling the management of blood glucose levels without hypoglycemia.

  11. An Intensive Insulinotherapy Mobile Phone Application Built on Artificial Intelligence Techniques

    Science.gov (United States)

    Curran, Kevin; Nichols, Eric; Xie, Ermai; Harper, Roy

    2010-01-01

    Background Software to help control diabetes is currently an embryonic market with the main activity to date focused mainly on the development of noncomputerized solutions, such as cardboard calculators or computerized solutions that use “flat” computer models, which are applied to each person without taking into account their individual lifestyles. The development of true, mobile device-driven health applications has been hindered by the lack of tools available in the past and the sheer lack of mobile devices on the market. This has now changed, however, with the availability of pocket personal computer handsets. Method This article describes a solution in the form of an intelligent neural network running on mobile devices, allowing people with diabetes access to it regardless of their location. Utilizing an easy to learn and use multipanel user interface, people with diabetes can run the software in real time via an easy to use graphical user interface. The neural network consists of four neurons. The first is glucose. If the user's current glucose level is within the target range, the glucose weight is then multiplied by zero. If the glucose level is high, then there will be a positive value multiplied to the weight, resulting in a positive amount of insulin to be injected. If the user's glucose level is low, then the weights will be multiplied by a negative value, resulting in a decrease in the overall insulin dose. Results A minifeasibility trial was carried out at a local hospital under a consultant endocrinologist in Belfast. The short study ran for 2 weeks with six patients. The main objectives were to investigate the user interface, test the remote sending of data over a 3G network to a centralized server at the university, and record patient data for further proofing of the neural network. We also received useful feedback regarding the user interface and the feasibility of handing real-world patients a new mobile phone. Results of this short trial

  12. Giant Controllable Magnetization Changes Induced by Structural Phase Transitions in a Metamagnetic Artificial Multiferroic.

    Science.gov (United States)

    Bennett, S P; Wong, A T; Glavic, A; Herklotz, A; Urban, C; Valmianski, I; Biegalski, M D; Christen, H M; Ward, T Z; Lauter, V

    2016-01-01

    The realization of a controllable metamagnetic transition from AFM to FM ordering would open the door to a plethora of new spintronics based devices that, rather than reorienting spins in a ferromagnet, harness direct control of a materials intrinsic magnetic ordering. In this study FeRh films with drastically reduced transition temperatures and a large magneto-thermal hysteresis were produced for magnetocaloric and spintronics applications. Remarkably, giant controllable magnetization changes (measured to be as high has ~25%) are realized by manipulating the strain transfer from the external lattice when subjected to two structural phase transitions of BaTiO3 (001) single crystal substrate. These magnetization changes are the largest seen to date to be controllably induced in the FeRh system. Using polarized neutron reflectometry we reveal how just a slight in plane surface strain change at ~290C results in a massive magnetic transformation in the bottom half of the film clearly demonstrating a strong lattice-spin coupling in FeRh. By means of these substrate induced strain changes we show a way to reproducibly explore the effects of temperature and strain on the relative stabilities of the FM and AFM phases in multi-domain metamagnetic systems. This study also demonstrates for the first time the depth dependent nature of a controllable magnetic order using strain in an artificial multiferroic heterostructure. PMID:26940159

  13. Giant Controllable Magnetization Changes Induced by Structural Phase Transitions in a Metamagnetic Artificial Multiferroic

    Science.gov (United States)

    Bennett, S. P.; Wong, A. T.; Glavic, A.; Herklotz, A.; Urban, C.; Valmianski, I.; Biegalski, M. D.; Christen, H. M.; Ward, T. Z.; Lauter, V.

    2016-03-01

    The realization of a controllable metamagnetic transition from AFM to FM ordering would open the door to a plethora of new spintronics based devices that, rather than reorienting spins in a ferromagnet, harness direct control of a materials intrinsic magnetic ordering. In this study FeRh films with drastically reduced transition temperatures and a large magneto-thermal hysteresis were produced for magnetocaloric and spintronics applications. Remarkably, giant controllable magnetization changes (measured to be as high has ~25%) are realized by manipulating the strain transfer from the external lattice when subjected to two structural phase transitions of BaTiO3 (001) single crystal substrate. These magnetization changes are the largest seen to date to be controllably induced in the FeRh system. Using polarized neutron reflectometry we reveal how just a slight in plane surface strain change at ~290C results in a massive magnetic transformation in the bottom half of the film clearly demonstrating a strong lattice-spin coupling in FeRh. By means of these substrate induced strain changes we show a way to reproducibly explore the effects of temperature and strain on the relative stabilities of the FM and AFM phases in multi-domain metamagnetic systems. This study also demonstrates for the first time the depth dependent nature of a controllable magnetic order using strain in an artificial multiferroic heterostructure.

  14. Fuzzy Self-Tuning PID Control of Hydrogen-Driven Pneumatic Artificial Muscle Actuator

    Institute of Scientific and Technical Information of China (English)

    Thanana Nuchkrua; Thananchai Leephakpreeda

    2013-01-01

    In this paper,a fuzzy self-tuning Proportional-Integral-Derivative (PID) control of hydrogen-driven Pneumatic Artificial Muscle (PAM) actuator is presented.With a conventional PID control,non-linear thermodynamics of the hydrogen-driven PAM actuator still highly affects the mechanical actuations itself,causing deyiation of desired tasks.The fuzzy self-tuning PID controller is systematically developed so as to achieve dynamic performance targets of the hydrogen-driven PAM actuator.The fuzzy rules based on desired characteristics of closed-loop control are designed to finely tune the PID gains of the controller under different operating conditions.The empirical models and properties of the hydrogen-driven PAM actuator are used as a genuine representation of mechanical actuations.A mass-spring-damper system is applied to the hydrogen-driven PAM actuator as a typical mechanical load during actuations.The results of the implementation show that the viability of the proposed method in actuating the hydrogen-driven PAM under mechanical loads is close to desired performance.

  15. Hybrid control using evolutionary tuned fuzzy controller techniques - a study

    OpenAIRE

    Stirrup, R.; Chipperfield, A.; Tang, K.S.; Man, K.F.

    2002-01-01

    Many real world systems exist that have operating regions or regimes that exhibit varying degrees of non-lineararity. An example of this are the significant variations in the dynamic characteristics of a distributed collector field within a solar power plant. Her a gain schedule controller using pole placement with feedforward was chosen to control the more linear operating regimes of the plant. Then a study was carried out to find the best suited and most efficient evolutionary-tuned fuzz...

  16. Research Considering Embryonic Development of Pikeperch (Stizostedion lucioperca under Artificial-Controlled Spawning Conditions

    Directory of Open Access Journals (Sweden)

    Daniel Tiberiu Oprea

    2014-05-01

    Full Text Available The experiments made in order to study the embryonic development of pikeperch were take place at the Fish Culture Research and Development Station Nucet, within 02.04 – 17.04.2012. For artificial-controlled spawning of pikeperch were used 4 years old breeders reared in ponds, at Nucet Station in policulture with older cyprinids. The experiment was accomplished in two experimental variants, wherein the fertilized eggs have been hatched at two different intervals of temperatures. The technological parameters of incubation were as follow, variant V1: fertilized rate 92 %, embryo rate 76 % and hatching rate 65 %; variant V2: fertilized rate 93 %, embryo rate 82 % and hatching rate 71 %. The Nucet type incubators seem to offer good conditions for embryonic development of pikeperch.

  17. Hybrid optical fiber sensor and artificial neural network system for bioethanol quality control and productivity enhancement

    Science.gov (United States)

    Gusken, Edmilton; Salgado, Ricardo M.; Rossell, Carlos E. V.; Ohishi, Takaaki; Suzuki, Carlos K.

    2008-04-01

    Bioethanol is produced by bio-chemical process that converts sugar or biomass feedstock into ethanol. After bio-chemical process, the solution is distilled under controlled conditions of pressure and temperature, in order to obtain an ethanol-water solution. However, the ethanol concentration analysis is generally performed off-line and, sometimes, a re-distillation process becomes necessary. In this research, an optical apparatus based on Fresnel reflection has been used in combination with artificial neural networks for determination of bioethanol concentration in hydro-alcoholic solution at any temperature. The volumetric concentration and temperature effect was investigated. This intelligent system can effectively detect and update in real-time the correction of distillation parameters to reduce losses of bioethanol and also to improve the quality in a production plant.

  18. Controlling dispersion forces between small particles with artificially created random light fields

    CERN Document Server

    Bruegger, Georges; Scheffold, Frank; Saenz, Juan Jose

    2015-01-01

    Appropriate combinations of laser beams can be used to trap and manipulate small particles with "optical tweezers" as well as to induce significant "optical binding" forces between particles. These interaction forces are usually strongly anisotropic depending on the interference landscape of the external fields. This is in contrast with the familiar isotropic, translationally invariant, van der Waals and, in general, Casimir-Lifshitz interactions between neutral bodies arising from random electromagnetic waves generated by equilibrium quantum and thermal fluctuations. Here we show, both theoretically and experimentally, that dispersion forces between small colloidal particles can also be induced and controlled using artificially created fluctuating light fields. Using optical tweezers as gauge, we present experimental evidence for the predicted isotropic attractive interactions between dielectric microspheres induced by laser-generated, random light fields. These light induced interactions open a path towards...

  19. The Virtual UNICOS Process Expert: integration of Artificial Intelligence tools in Control Systems

    CERN Multimedia

    Vilches Calvo, I; Barillere, R

    2009-01-01

    UNICOS is a CERN framework to produce control applications. It provides operators with ways to interact with all process items from the most simple (e.g. I/O channels) to the most abstract objects (e.g. a part of the plant). This possibility of fine grain operation is particularly useful to recover from abnormal situations if operators have the required knowledge. The Virtual UNICOS Process Expert project aims at providing operators with means to handle difficult operation cases for which the intervention of process experts is usually requested. The main idea of project is to use the openness of the UNICOS-based applications to integrate tools (e.g. Artificial Intelligence tools) which will act as Process Experts to analyze complex situations, to propose and to execute smooth recovery procedures.

  20. Synergistic control of forearm based on accelerometer data and artificial neural networks

    Directory of Open Access Journals (Sweden)

    B. Mijovic

    2008-05-01

    Full Text Available In the present study, we modeled a reaching task as a two-link mechanism. The upper arm and forearm motion trajectories during vertical arm movements were estimated from the measured angular accelerations with dual-axis accelerometers. A data set of reaching synergies from able-bodied individuals was used to train a radial basis function artificial neural network with upper arm/forearm tangential angular accelerations. The trained radial basis function artificial neural network for the specific movements predicted forearm motion from new upper arm trajectories with high correlation (mean, 0.9149-0.941. For all other movements, prediction was low (range, 0.0316-0.8302. Results suggest that the proposed algorithm is successful in generalization over similar motions and subjects. Such networks may be used as a high-level controller that could predict forearm kinematics from voluntary movements of the upper arm. This methodology is suitable for restoring the upper limb functions of individuals with motor disabilities of the forearm, but not of the upper arm. The developed control paradigm is applicable to upper-limb orthotic systems employing functional electrical stimulation. The proposed approach is of great significance particularly for humans with spinal cord injuries in a free-living environment. The implication of a measurement system with dual-axis accelerometers, developed for this study, is further seen in the evaluation of movement during the course of rehabilitation. For this purpose, training-related changes in synergies apparent from movement kinematics during rehabilitation would characterize the extent and the course of recovery. As such, a simple system using this methodology is of particular importance for stroke patients. The results underlie the important issue of upper-limb coordination.

  1. A Multi-form Multiple Choice Editor Exam Tool Based on HTML Website and Artificial Intelligence Techniques

    Directory of Open Access Journals (Sweden)

    A. Rjoub

    2009-01-01

    Full Text Available Problem statement: The educators argue that in the post modern world changes in the nature of work, globalization, the information revaluation and today's social challenges will all impact on educational priorities and thus will require a new mode of assessment. Approach: The objectives of this study were to: (1 Present a novel software package tool to create multiple choice and true/false exam forms. (2 Provide exams key solutions automatically (3 Meet special instructors' needs by allowing to easily incorporating multimedia elements into the exam questions, as well as the word processor editing functions and (4 Save both instructors time and money. Results: The multiform exam can be created randomly from question database or manually with shuffled answers for each question. The tool was built based on website and HTML interface using the multimedia applications, two different languages English/Arabic inserted to be used on the same time, efficient Artificial Intelligence techniques and Algorithms are used. The tool had been designed, implemented and tested by experienced instructors, with the result that efficiency, accountability and saving time improved. Conclusion/Recommendations: The transform from paper to electronic resulted in greatly enhanced user satisfaction. Editor exam tool can be used via internet without the need to download and install it to users machine, it’s a time saving system when multiple versions of random exams are required. This should highly motivated, instructors and teachers to utilize technology and IT to enhance exams and performance.

  2. Adhesion control by inflation: implications from biology to artificial attachment device

    Science.gov (United States)

    Dening, Kirstin; Heepe, Lars; Afferrante, Luciano; Carbone, Giuseppe; Gorb, Stanislav N.

    2014-08-01

    There is an increasing demand for materials that incorporate advanced adhesion properties, such as an ability to adhere in a reversible and controllable manner. In biological systems, these features are known from adhesive pads of the tree frog, Litoria caerulea, and the bush-cricket, Tettigonia viridissima. These species have convergently developed soft, hemispherically shaped pads that might be able to control their adhesion through active changing the curvature of the pad. Inspired by these biological systems, an artificial model system is developed here. It consists of an inflatable membrane clamped to the metallic cylinder and filled with air. Pull-off force measurements of the membrane surface were conducted in contact with the membrane at five different radii of curvature r c with (1) a smooth polyvinylsiloxane membrane and (2) mushroom-shaped adhesive microstructured membrane made of the same polymer. The hypothesis that an increased internal pressure, acting on the membrane, reduces the radius of the membrane curvature, resulting in turn in a lower pull-off force, is verified. Such an active control of adhesion, inspired by biological models, will lead to the development of industrial pick-and-drop devices with controllable adhesive properties.

  3. Incorporating Artificial Neural Networks in the dynamic thermal-hydraulic model of a controlled cryogenic circuit

    Science.gov (United States)

    Carli, S.; Bonifetto, R.; Savoldi, L.; Zanino, R.

    2015-09-01

    A model based on Artificial Neural Networks (ANNs) is developed for the heated line portion of a cryogenic circuit, where supercritical helium (SHe) flows and that also includes a cold circulator, valves, pipes/cryolines and heat exchangers between the main loop and a saturated liquid helium (LHe) bath. The heated line mimics the heat load coming from the superconducting magnets to their cryogenic cooling circuits during the operation of a tokamak fusion reactor. An ANN is trained, using the output from simulations of the circuit performed with the 4C thermal-hydraulic (TH) code, to reproduce the dynamic behavior of the heated line, including for the first time also scenarios where different types of controls act on the circuit. The ANN is then implemented in the 4C circuit model as a new component, which substitutes the original 4C heated line model. For different operational scenarios and control strategies, a good agreement is shown between the simplified ANN model results and the original 4C results, as well as with experimental data from the HELIOS facility confirming the suitability of this new approach which, extended to an entire magnet systems, can lead to real-time control of the cooling loops and fast assessment of control strategies for heat load smoothing to the cryoplant.

  4. Reducing risk of closed loop control of blood glucose in artificial pancreas using fractional calculus.

    Science.gov (United States)

    Ghorbani, Mahboobeh; Bogdan, Paul

    2014-01-01

    Healthcare costs in the US are among the highest in the world. Chronic diseases such as diabetes significantly contribute to these extensive costs. Despite technological advances to improve sensing and actuation devices, we still lack a coherent theory that facilitates the design and optimization of efficient and robust medical cyber-physical systems for managing chronic diseases. In this paper, we propose a mathematical model for capturing the complex dynamics of blood glucose time series (e.g., time dependent and fractal behavior) observed in real world measurements via fractional calculus concepts. Building upon our time dependent fractal model, we propose a novel model predictive controller for an artificial pancreas that regulates insulin injection. We verify the accuracy of our controller by comparing it to conventional non-fractal models using real world measurements and show how the nonlinear optimal controller based on fractal calculus concepts is superior to non-fractal controllers in terms of average risk index and prediction accuracy. PMID:25571075

  5. Active Force with Fuzzy Logic Control of a Two-Link Arm Driven by Pneumatic Artificial Muscles

    Institute of Scientific and Technical Information of China (English)

    H. Jahanabadi; M. Mailah; M. Z. Md Zain; H. M. Hooi

    2011-01-01

    In this paper,the practicality and feasibility of Active Force Control (AFC) integrated with Fuzzy Logic(AFCAFL) appliedto a two link planar arm actuated by a pair of Pneumatic Artificial Muscle (PAM) is investigated.The study emphasizes on the application and control of PAM actuators which may be considered as the new generation of actuators comprising fluidic muscle that has high-tension force,high power to weight ratio and high strength in spite of its drawbacks in the form of high nonlinearity behaviour,high hysteresis and time varying parameters.Fuzzy Logic (FL) is used as a technique to estimate the best value of the inertia matrix of robot arm essential for the AFC mechanism that is complemented with a conventional Proportional-Integral-Derivative (PID) control at the outermost loop.A simulation study was first performed followed by an experimental investigation for validation.The experimental study was based on the independent joint tracking control and coordinated motion control of the arm in Cartesian or task space.In the former,the PAM actuated arm is commanded to track the prescribed trajectories due to harmonic excitations at the joints for a given frequency,whereas for the latter,two sets of trajectories with different loadings were considered.A practical rig utilizing a Hardware-In-The-Loop Simulation (H1LS) configuration was developed and a number of experiments were carried out.The results of the experiment and the simulation works were in good agreement,which verified the effectiveness and robustness of the proposed AFCAFL scheme actuated by PAM.

  6. Artificial neural network model with the parameter tuning assisted by a differential evolution technique: the study of the hold up of the slurry flow in a pipeline

    Directory of Open Access Journals (Sweden)

    S. K. Lahiri

    2009-05-01

    Full Text Available This paper describes a robust hybrid artificial neural network (ANN methodology which can offer a superior performance for the important process engineering problems. The method incorporates a hybrid artificial neural network and differential evolution technique (ANN-DE for the efficient tuning of ANN meta parameters. The algorithm has been applied for the prediction of the hold up of the solid liquid slurry flow. A comparison with selected correlations in the literature showed that the developed ANN correlation noticeably improved the prediction of hold up over a wide range of operating conditions, physical properties, and pipe diameters.

  7. Model-free control techniques for Stop & Go systems

    OpenAIRE

    Villagra, Jorge; Milanés, Vicente; Pérez Rastelli, Joshué; González, Carlos

    2010-01-01

    International audience; This paper presents a comparison of Stop & Go control algorithms, which deal with car following scenarios in urban environments. Since many vehicle/road interaction factors (road slope, aerodynamic forces) and actuator dynamics are very poorly known, two robust control strategies are proposed: an intelligent PID controller and a fuzzy controller. Both model-free techniques will be implemented and compared in simulation to show their suitability for demanding scenarios.

  8. Control and driving of pneumatic total artificial hearts TNS-BRNO-II and -III in long-term experiments.

    Science.gov (United States)

    Vasků, J; Urbánek, P; Vasků, J; Cerný, J; Smutný, M; Urbánek, E; Suchánek, J; Gregor, Z; Dostál, M; Guba, P

    1986-04-01

    Hemodynamic analysis was carried out during long-term experiments with the pneumatic total artificial hearts TNS-BRNO-II and TNS-BRNO-III to determine standard methods of starting artificial hearts and criteria for their long-term operation in vivo. In long-term experiments, regulatory mechanisms automatically regulating the systole length and diastolic aspiration pressure have also been verified. Comparison of hemodynamic variables obtained from invasive measurements with pneumatic pressure curves permitted the control and monitoring of the experiment in its entirety by noninvasive methods only. The control of the artificial heart using the Chirasist TN 3 and Chirasist TN 4 was adapted to specific properties of the pumps, above all to the functions of the atypical inlet valves. The terminal stages of the experiments have shown that a 100-ml pump can ensure survival of experimental calves up to 210 kg body weight.

  9. A program for assisting automatic generation control of the ELETRONORTE using artificial neural network; Um programa para assistencia ao controle automatico de geracao da Eletronorte usando rede neuronal artificial

    Energy Technology Data Exchange (ETDEWEB)

    Brito Filho, Pedro Rodrigues de; Nascimento Garcez, Jurandyr do [Para Univ., Belem, PA (Brazil). Centro Tecnologico; Charone Junior, Wady [Centrais Eletricas do Nordeste do Brasil S.A. (ELETRONORTE), Belem, PA (Brazil)

    1994-12-31

    This work presents an application of artificial neural network as a support to decision making in the automatic generation control (AGC) of the ELETRONORTE. It uses a software to auxiliary in the decisions in real time of the AGC. (author) 2 refs., 6 figs., 1 tab.

  10. UAV path planning using artificial potential field method updated by optimal control theory

    Science.gov (United States)

    Chen, Yong-bo; Luo, Guan-chen; Mei, Yue-song; Yu, Jian-qiao; Su, Xiao-long

    2016-04-01

    The unmanned aerial vehicle (UAV) path planning problem is an important assignment in the UAV mission planning. Based on the artificial potential field (APF) UAV path planning method, it is reconstructed into the constrained optimisation problem by introducing an additional control force. The constrained optimisation problem is translated into the unconstrained optimisation problem with the help of slack variables in this paper. The functional optimisation method is applied to reform this problem into an optimal control problem. The whole transformation process is deduced in detail, based on a discrete UAV dynamic model. Then, the path planning problem is solved with the help of the optimal control method. The path following process based on the six degrees of freedom simulation model of the quadrotor helicopters is introduced to verify the practicability of this method. Finally, the simulation results show that the improved method is more effective in planning path. In the planning space, the length of the calculated path is shorter and smoother than that using traditional APF method. In addition, the improved method can solve the dead point problem effectively.

  11. Controlling the Twin Wire Arc Spray Process Using Artificial Neural Networks (ANN)

    Science.gov (United States)

    Hartz-Behrend, K.; Schaup, J.; Zierhut, J.; Schein, J.

    2016-01-01

    One approach for controlling the twin wire arc spray process is to use optical properties of the particle beam as input parameters for a process control. The idea is that changes in the process like eroded contact nozzles or variations of current, voltage, and/or atomizing gas pressure may be detected through observation of the particle beam. It can be assumed that if these properties deviate significantly from those obtained from a beam recorded for an optimal coating process, the spray particle and thus the coating properties change significantly. The goal is to detect these deviations and compensate the occurring errors by adjusting appropriate process parameters for the wire arc spray unit. One method for monitoring optical properties is to apply the diagnostic system particle flux imaging (PFI): PFI fits an ellipse to an image of a particle beam thereby defining easy to analyze characteristical parameters by relating optical beam properties to ellipse parameters. Using artificial neural networks (ANN), mathematical relations between ellipse and process parameters can be defined. It will be shown that in the case of a process disturbance through the use of an ANN-based control new process parameters can be computed to compensate particle beam deviations.

  12. Fault detection and diagnosis using statistical control charts and artificial neural networks

    International Nuclear Information System (INIS)

    In order to operate a successful plant or process, continuous improvement must be made in the areas of safety, quality and reliability. Central to this continuous improvement is the early or proactive detection and correct diagnosis of process faults. This research examines the feasibility of using Cumulative Summation (CUSUM) Control Charts and artificial neural networks together for fault detection and diagnosis (FDD). The proposed FDD strategy was tested on a model of the heat transport system of a CANDU nuclear reactor. The results of the investigation indicate that a FDD system using CUSUM Control Charts and a Radial Basis Function (RBF) neural network is not only feasible but also of promising potential. The control charts and neural network are linked together by using a characteristic fault signature pattern for each fault which is to be detected and diagnosed. When tested, the system was able to eliminate all false alarms at steady state, promptly detect 6 fault conditions and correctly diagnose 5 out of the 6 faults. The diagnosis for the sixth fault was inconclusive. (author). 9 refs., 6 tabs., 7 figs

  13. Continental Land Mass Air Traffic Control (COLM ATC). [using three artificial satellite configurations

    Science.gov (United States)

    Pecar, J. A.; Henrich, J. E.

    1973-01-01

    The application of various satellite systems and techniques relative to providing air traffic control services for the continental United States was studied. Three satellite configurations were reviewed. The characteristics and capabilities of the satellites are described. The study includes consideration for the various ranging waveforms, multiple access alternatives, and the power and bandwidth required as a function of the number of users.

  14. Automatic diameter control system applied to the laser heated pedestal growth technique

    Directory of Open Access Journals (Sweden)

    Andreeta M.R.B.

    2003-01-01

    Full Text Available We described an automatic diameter control system (ADC, for the laser heated pedestal growth technique, that reduces the diameter fluctuations in oxide fibers grown from unreacted and non-sinterized pedestals, to less than 2% of the average fiber diameter, and diminishes the average diameter fluctuation, over the entire length of the fiber, to less than 1%. The ADC apparatus is based on an artificial vision system that controls the pulling speed and the height of the molten zone within a precision of 30 mum. We also show that this system can be used for periodic in situ axial doping the fiber. Pure and Cr3+ doped LaAlO3 and pure LiNbO3 were usedas model materials.

  15. Active vibration control techniques for flexible space structures

    Science.gov (United States)

    Parlos, Alexander G.; Jayasuriya, Suhada

    1990-01-01

    Two proposed control system design techniques for active vibration control in flexible space structures are detailed. Control issues relevant only to flexible-body dynamics are addressed, whereas no attempt was made to integrate the flexible and rigid-body spacecraft dynamics. Both of the proposed approaches revealed encouraging results; however, further investigation of the interaction of the flexible and rigid-body dynamics is warranted.

  16. Engine control techniques to account for fuel effects

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Shankar; Frazier, Timothy R.; Stanton, Donald W.; Xu, Yi; Bunting, Bruce G.; Wolf, Leslie R.

    2014-08-26

    A technique for engine control to account for fuel effects including providing an internal combustion engine and a controller to regulate operation thereof, the engine being operable to combust a fuel to produce an exhaust gas; establishing a plurality of fuel property inputs; establishing a plurality of engine performance inputs; generating engine control information as a function of the fuel property inputs and the engine performance inputs; and accessing the engine control information with the controller to regulate at least one engine operating parameter.

  17. Nonlinear control techniques for an atomic force microscope system

    Institute of Scientific and Technical Information of China (English)

    Yongchun FANG; Matthew FEEMSTER; Darren DAWSON; Nader M.JALILI

    2005-01-01

    Two nonlinear control techniques are proposed for an atomic force microscope system.Initially,a learning-based control algorithm is developed for the microcantilever-sample system that achieves asymptotic cantilever tip tracking for periodic trajectories.Specifically,the control approach utilizes a learning-based feedforward term to compensate for periodic dynamics and high-gain terms to account for non-periodic dynamics.An adaptive control algorithm is then developed to achieve asymptotic cantilever tip tracking for bounded tip trajectories despite uncertainty throughout the system parameters.Simulation results are provided to illustrate the efficacy and performance of the control strategies.

  18. Sliding mode control of switching power converters techniques and implementation

    CERN Document Server

    Tan, Siew-Chong; Tse, Chi-Kong

    2011-01-01

    Sliding Mode Control of Switching Power Converters: Techniques and Implementation is perhaps the first in-depth account of how sliding mode controllers can be practically engineered to optimize control of power converters. A complete understanding of this process is timely and necessary, as the electronics industry moves toward the use of renewable energy sources and widely varying loads that can be adequately supported only by power converters using nonlinear controllers.Of the various advanced control methods used to handle the complex requirements of power conversion systems, sliding mode c

  19. Pig Artificial Insemination Techniques and Factors Discussed%猪人工授精技术和影响因素讨论

    Institute of Scientific and Technical Information of China (English)

    黄汉良

    2014-01-01

    As technology becomes more sophisticated modern pig insemination, to work in this field technicians put forward higher requirements, requiring mastery of the relevant technology to control the factors that affect the success rate of fertilization. In this regard, elaborated pig semen quality detection technology, breeding sows, semen preservation and insemination techniques, so that the number of swine artificial insemination conception rate and production to reach the expected level in order to provide a reference for future work.%随着现代猪人工授精技术越来越精湛,对从事这方面工作的技术人员提出了更高的要求,要求其熟悉掌握相关技术,能够控制影响授精成功率的因素。对此,阐述了猪精液的质量检测技术、母猪的饲养、精液保存和输精技术等,使猪人工授精的受胎率和生产数达到预期水平,以期为今后工作提供借鉴。

  20. New control strategies for neuroprosthetic systems

    NARCIS (Netherlands)

    Crago, Patrick E.; Lan, Ning; Veltink, Peter H.; Abbas, James J.; Kantor, Carole

    1996-01-01

    The availability of techniques to artificially excite paralyzed muscles opens enormous potential for restoring both upper and lower extremity movements with neuroprostheses. Neuroprostheses must stimulate muscle, and control and regulate the artificial movements produced. Control methods to accompli

  1. Active vibration control of flexible cantilever plates using piezoelectric materials and artificial neural networks

    Science.gov (United States)

    Abdeljaber, Osama; Avci, Onur; Inman, Daniel J.

    2016-02-01

    The study presented in this paper introduces a new intelligent methodology to mitigate the vibration response of flexible cantilever plates. The use of the piezoelectric sensor/actuator pairs for active control of plates is discussed. An intelligent neural network based controller is designed to control the optimal voltage applied on the piezoelectric patches. The control technique utilizes a neurocontroller along with a Kalman Filter to compute the appropriate actuator command. The neurocontroller is trained based on an algorithm that incorporates a set of emulator neural networks which are also trained to predict the future response of the cantilever plate. Then, the neurocontroller is evaluated by comparing the uncontrolled and controlled responses under several types of dynamic excitations. It is observed that the neurocontroller reduced the vibration response of the flexible cantilever plate significantly; the results demonstrated the success and robustness of the neurocontroller independent of the type and distribution of the excitation force.

  2. Evolutionary biology and genetic techniques for insect control

    OpenAIRE

    Leftwich, Philip; Bolton, Michael; Chapman, Tracey

    2016-01-01

    Abstract The requirement to develop new techniques for insect control that minimize negative environmental impacts has never been more pressing. Here we discuss population suppression and population replacement technologies. These include sterile insect technique, genetic elimination methods such as the release of insects carrying a dominant lethal (RIDL), and gene driving mechanisms offered by intracellular bacteria and homing endonucleases. We also review the potential of newer or underutil...

  3. Establishment of an artificial β-cell line expressing insulin under the control of doxycycline

    Institute of Scientific and Technical Information of China (English)

    Xin-Yu Qin; Kun-Tang Shen; Xin Zhang; Zhi-Hong Cheng; Xiang-Ru Xu; Ze-Guang Han

    2002-01-01

    AIM: Artificial β-cell lines may offer an abundant source of calls for the treatment of type Ⅰ diabetes, but insulin secretion in β-cells is tightly regulwted in physiological conditions The Tet-On system is a "gene switch" system,which can induce gene expression by administration of tetracycline (Tet) derivatives such as doxcycline (D ox).Using this system, we established 293 cells to an artificial cell line secreting insulin in response to stimulation by Dox.METHODS: The mutated proinsulin cDNA was obtained fromplasmid pcDNA3.1/C-mlNS by the polymerase chain reaction(PCR), and was inserted downstream from the promoter onthe expression vector pTRE2, to construct a recombinedexpression vector pTRE2mlNS. The promoter on pTRE2consists of the tetracycline-response element and the CMVminimal promoter and is thus activated by the reversetetracycline-controlled transactivator (rtTA) when Dox isadministrated. pTRE2mlNS and plasmid pTK-Hyg encodinghygromycin were co-transfected in the tet293 cells, whichexpress rtTA stably. Following hygromycin screening, thesurvived cells expressing insulin were selected andenriched. Dox was used to control the expression of insulinin these cells. At the levels of mRNA and protein, theregulating effect of Dox in culture medium on the expressionof proinsulin gene was estimated respectively with Northernblot, RT-PCR, and radioimmunoassay.RESULTS: From the 28 hygromycin-resistant cell strains, weselected one cell strain (tet293/Ins6) secreting insulin notonly automatically, but in response to stimulation by Dox.The amount on insulin secretion was dependent on the Doxdose (0,10,100,200,400,800 and 1000 μg@ L-1 ), the level ofinsulin secreted by the cells treated with Dox ( 1000μg. L-1 )wes 241.0 pU@d1 @cell-1 , which was 25-fold that of 9.7 pU@d1@ cell-1 without Dox treatment. Northern blot analyses andRT-PCR further confinned that the transcription of insulingene had already been up-regulated after exposing tet293/Ins6 cells to Dox for

  4. vitisFlower®: Development and Testing of a Novel Android-Smartphone Application for Assessing the Number of Grapevine Flowers per Inflorescence Using Artificial Vision Techniques

    OpenAIRE

    Arturo Aquino; Borja Millan; Daniel Gaston; María-Paz Diago; Javier Tardaguila

    2015-01-01

    Grapevine flowering and fruit set greatly determine crop yield. This paper presents a new smartphone application for automatically counting, non-invasively and directly in the vineyard, the flower number in grapevine inflorescence photos by implementing artificial vision techniques. The application, called vitisFlower®, firstly guides the user to appropriately take an inflorescence photo using the smartphone’s camera. Then, by means of image analysis, the flowers in the image are detected and...

  5. Comparison of Suspended Branch and Direct Infestation Techniques for Artificially Infesting Hemlock Seedlings with the Hemlock Woolly Adelgid for Resistance Screening

    OpenAIRE

    Zaidee L. Powers; Mayfield, Albert E.; John Frampton; Jetton, Robert M.

    2015-01-01

    The hemlock woolly adelgid (Adelges tsugae Annand) is an invasive forest pest in eastern North America that has caused significant decline and mortality in populations of eastern hemlock (Tsuga canadensis (L.) Carr.) and Carolina hemlock (T. caroliniana Engelm.). The breeding of adelgid-resistant genotypes for reforestation activities is still in the early development phases, and most resistance screening programs have depended on labor-intensive direct artificial infestation techniques for...

  6. Artificial perches as a nucleation technique for restoration of a riparian environment: characterization of the seed rain and of natural regeneration

    OpenAIRE

    Aline Luiza Tomazi; Carlos Eduardo Zimmermann; Rudi Ricardo Laps

    2010-01-01

    Riparian habitats are important to the maintenance of ecological processes and environmental services. However, a significant portion of the riparian vegetation in the Brazilian Atlantic forest has been removed in response to increasing human pressure. Therefore, the application of restoration techniques in these habitats becomes essential. In this context, a nucleation model with 18 artificial perches was evaluated for the restoration of a degraded riparian area in Gaspar, Santa Catarina, Br...

  7. Metamodeling Techniques Applied to the Design of Reconfigurable Control Applications

    Directory of Open Access Journals (Sweden)

    Fogliazza Giuseppe

    2008-01-01

    Full Text Available Abstract In order to realize autonomous manufacturing systems in environments characterized by high dynamics and high complexity of task, it is necessary to improve the control system modelling and performance. This requires the use of better and reusable abstractions. In this paper, we explore the metamodel techniques as a foundation to the solution of this problem. The increasing popularity of model-driven approaches and a new generation of tools to support metamodel techniques are changing software engineering landscape, boosting the adoption of new methodologies for control application development.

  8. Metamodeling Techniques Applied to the Design of Reconfigurable Control Applications

    Directory of Open Access Journals (Sweden)

    Luca Ferrarini

    2008-02-01

    Full Text Available In order to realize autonomous manufacturing systems in environments characterized by high dynamics and high complexity of task, it is necessary to improve the control system modelling and performance. This requires the use of better and reusable abstractions. In this paper, we explore the metamodel techniques as a foundation to the solution of this problem. The increasing popularity of model-driven approaches and a new generation of tools to support metamodel techniques are changing software engineering landscape, boosting the adoption of new methodologies for control application development.

  9. A time-delay suppression technique for DPWM control circuit

    OpenAIRE

    Ishizuka, Yoichi; Hirose, Fumitoshi; Yamada, Yusuke; Matsuo, Hirofumi

    2009-01-01

    A proposed design of a low-cost digital pulse width modulation (DPWM) control circuit for non-isolated DC-DC converter without A/D converter is described. Also, propsed real-time PID control technique for DPWM is described. Some experimental results and simulation results are revealed the proposed circuit and scheme. The purpose of this research is striking a balance between minimizing cost increase by digitalizing of the control circuit of DC-DC converter and speeding up the control circuit.

  10. ARTIFICIAL NEURAL NETWORK CONTROLLER BASED DISTRIBUTION STATIC COMPENSATOR FOR VOLTAGE SAG MITIGATION

    Directory of Open Access Journals (Sweden)

    D. Rajasekaran

    2013-01-01

    Full Text Available Switching of loads, capacitors, along with the proliferation of power electronics equipment, non-linear loads in industrial, commercial and domestic applications have lead to power quality issues in the distribution system. Power quality issues such as voltage sag, voltage swell and harmonics, which are certainly major concerning issues in the present era. These issues can lead to failure or malfunction of the many sensitive loads connected to the distribution system, thus incurring a high cost for end users. Power quality problems are solved by advanced custom power devices. This study presents how the custom power device Distribution Static Compensator (D-STATCOM is used to mitigate voltage sag and voltage harmonics in distribution system. Artificial Neural Network (ANN controller based D-STATCOM is simulated in MATLAB-SIMULINK environment. Prototype model for single phase D-STATCOM is developed to verify the results. The simulation and hardware results show clearly the performance of the D-STATCOM in mitigating voltage sag and voltage harmonics in distribution system.

  11. SINGLE - PHASE INVERTER CONTROL TECHNIQUES FOR INTERFACING RENEWABLE ENERGY SOURCES

    OpenAIRE

    C.Nallasivam

    2015-01-01

    A novel current control technique is proposed to control power flow from a renewable energy source feeding a microgrid system through a three - phase parallel - connected inverter. The parallel - connected inverter ensures that the power flow from the grid with low - current total harmonic distortion even in the presence of nonlinear load. The renewable energy sources ar e paralleled, and the average of this constant sup...

  12. Abstraction and control techniques for non-stationary scheduling problems

    CERN Document Server

    Innocenti, Giacomo

    2009-01-01

    The paper faces the problem of scheduling from a new perspective, trying to bridge the gap between classical heuristic approaches and system identification and control strategies. To this aim, a complete mathematical formulation of a general scheduling process is derived, beginning from very broad assumptions. This allows a greater freedom of manipulation and guarantee the resolution of the identification (and control) techniques. Both an adaptive and a switching strategies are presented in relation to the performances of a simple Round Robin algorithm.

  13. Development of irradiation technique on controlling food contamination residue

    International Nuclear Information System (INIS)

    The current state of the researches of irradiation technology on controlling food mycotoxin, pesticide, veterinary drugs and fishery drugs residue was summarized. And the degradation rate, mechanism, products and toxicities of food contamination were expatiated. The free radical from irradiation attack the site of weaker bond, and the less or more toxic substances were produced, which lead to the degradation of the food contamination. The limitations and future application of irradiation technique on controlling food contamination were also analyzed. (authors)

  14. Sterile insect technique and radiation in insect control

    International Nuclear Information System (INIS)

    Out of 39 papers and 6 summaries of the poster presentations published in this proceeding series, 23 respectively fall within the INIS subject scope. Four main topics were covered: a review of the sterile insect technique against various insect pests; its application to tsetse flies in eradication programmes; quality control of mass-reared insects for release; and the development of genetic approaches to insect mass rearing and control. Other topics emphasized integrated pest management, computer models and radioisotope labelling

  15. Tsetse control, diagnosis and chemotherapy using nuclear techniques

    International Nuclear Information System (INIS)

    The focus of the seminar was on recent advances in the use of nuclear techniques in the diagnosis and control of tsetse-transmitted trypanosomiasis. The proceedings contain the full text of sixteen selected papers addressing the disease and its diagnosis, chemotherapy, vector biology, ecology and control. Synopses of the other papers presented are also included. The individual contributions are indexed separately. Refs, figs and tabs

  16. Power electronic converters PWM strategies and current control techniques

    CERN Document Server

    Monmasson, Eric

    2013-01-01

    A voltage converter changes the voltage of an electrical power source and is usually combined with other components to create a power supply. This title is devoted to the control of static converters, which deals with pulse-width modulation (PWM) techniques, and also discusses methods for current control. Various application cases are treated. The book is ideal for professionals in power engineering, power electronics, and electric drives industries, as well as practicing engineers, university professors, postdoctoral fellows, and graduate students.

  17. A Novel Application of Artificial Neural Network for the Solution of Inverse Kinematics Controls of Robotic Manipulators

    Directory of Open Access Journals (Sweden)

    Santosh Kumar Nanda

    2012-08-01

    Full Text Available In robotic applications and research, inverse kinematics is one of the most important problems in terms of robot kinematics and control. Consequently, finding the solution of Inverse Kinematics in now days is considered as one of the most important problems in robot kinematics and control. As the intricacy of robot manipulator increases, obtaining the mathematical, statistical solutions of inverse kinematics are difficult and computationally expensive. For that reason, now soft-computing based highly intelligent based model applications should be adopted to getting appropriate solution for inverse kinematics. In this paper, a novel application of artificial neural network is used for controlling a robotic manipulator. The proposed methods are based on the establishments of the non-linear mapping between Cartesian and joint coordinates using multi layer perceptron and functional link artificial neural network.

  18. Application of Agent Technique in Traffic Control%Agent技术在交通控制中的应用

    Institute of Scientific and Technical Information of China (English)

    孙静

    2011-01-01

    The Agent originates the artificial intelligence,the artificial intelligence technique combines distributing type calculation techniques together in the middle of 80's in 20 centuries,appearing the distributing type artificial intelligence.At the same time,the Agent is mentioned more and more,the Agent technical research direction and applications contain more extensive development space,this text mainly introduced the Agent concept,characteristic,type,with many techniques of Agent in application of traffic control system.%Agent技术来源于分布式人工智能DAI领域。也有人将其翻译为智能主体或智能体,Agent技术在90年代成为热门话题,Agent一词越来越多地被提到,Agent技术的研究方向和应用就有了更加广泛的发展空间。主要介绍了Agent的概念、特性、类型,与多Agent技术在交通控制系统中的应用这两大方面的内容。

  19. The sterile insect technique for control of tsetse flies in Africa

    International Nuclear Information System (INIS)

    The tsetse fly is the major vector of trypanosomiasis in Africa. At various places in Africa, tsetse control and eradication studies are under way, mostly relying on insecticides. However, two sterile insect programmes are in an executionary phase as field research projects. A third project, in Nigeria, will be carried out by the Joint FAO/IAEA Division, in close collaboration with the Nigerian Government. The Seibersdorf Entomology Laboratory (Austria) is studying several basic aspects of the fly's biology. Research is now being conducted on mass-rearing techniques. An artificial membrane has been developed to replace living hosts and has proved effective, stretched over a pool of blood. Sterilization of flies by 12-17 rad of gamma radiation from a cobalt-60 source without enfeebling their mating behaviour in the field is also investigated at Seibersdorf. Training facilities are available for scientists from developing countries

  20. 白木通人工繁育技术研究%Research on Artificial Propagation Techniques of Caulis Akebiae

    Institute of Scientific and Technical Information of China (English)

    雷可

    2011-01-01

    为探讨白木通人工繁育技术,以出苗率和成活率为指标,研究了播种季节、播种方式对有性繁殖的影响,以及扦插种条前处理、扦插用种条的采集时间、扦插用种条的质量、扦插时间4因素对扦插效果的影响。结果表明,播种季节以农历冬至前后播种效果最好;播种方式为种子直播到塑料大棚的营养钵中,并加盖1~2 cm厚的营养土;扦插繁殖中,激素处理对扦插效果影响较大,其中ABT(2号)处理成活率最高;冬季采集种条置湿沙贮藏成活率明显高于其它采集时间所采集的种条;扦插种条的质量直接影响扦插成活率,其中以直接5~8 mm的种条成活率最高;扦插时间对扦插种条的成活起关键作用,其中以3月份扦插效果最好。通过本研究,初步拟定了白木通有性繁殖与无性繁殖技术。%To study the technique of artificial propagation of Akebia trifoliate. The effects of sexual reproduction in different planting season and with different planting methods were studied according to seed germination rate and survival rate. The effects of cuttage with different pre-treatment, in different cutting acquisition time,with different cutting qualifies, and in different outrage time were studies according to the survival rate. The best planting season was about lunar winter solstice. The best planting method was to plant seeds diretly in nutrition bowl in greenhouse and cover with 1 - 2 cm thick nutrient soil. In cuttage propagation, the highest survival rate was obtained from ABT ( NO. 2) treatment. The survival rate of cutting collected in winter was higher than that of collected in other seasons. The survival rate of cutting with 5 - 8 mm in length was higher than other length, and the cuttage time was very important to the survival rate, the best cuttage effect was obtained from March. Through this study, the technique of sexual reproduction and asexual propagation of Akebia trifoliate were

  1. Control Techniques in Heating, Ventilating and Air Conditioning Systems

    Directory of Open Access Journals (Sweden)

    H. Mirinejad

    2008-01-01

    Full Text Available Problem statement: Heating, Ventilating and Air Conditioning (HVAC systems are among the main installations in residential, commercial and industrial buildings. The purpose of the HVAC systems is normally to provide a comfortable environment in terms of temperature, humidity and other environmental parameters for the occupants as well as to save energy. Achieving these objectives requires a suitable control system design. Approach: In this overview, thermal comfort level and ISO comfort field is introduced, followed by a review and comparison of the main existing control techniques used in HVAC systems to date. Results: The present overview shows that intelligent controllers which are based on the human sensation of thermal comfort have a better performance in providing thermal comfort as well as energy saving than the traditional controllers and those based on a model of the HVAC system. Conclusion: Such an overview provides an insight into current control methods in HVAC systems and can help scholars and HVAC learners to have the comprehensive information about a variety of control techniques in the field of HVAC and therefore to better design a proper controller for their work

  2. Rewritable artificial magnetic charge ice

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Y. -L.; Xiao, Z. -L.; Snezhko, A.; Xu, J.; Ocola, L. E.; Divan, R.; Pearson, J. E.; Crabtree, G. W.; Kwok, W. -K.

    2016-05-19

    Artificial ices enable the study of geometrical frustration by design and through direct observation. However, it has proven difficult to achieve tailored long-range ordering of their diverse configurations, limiting both fundamental and applied research directions. We designed an artificial spin structure that produces a magnetic charge ice with tunable long-range ordering of eight different configurations. We also developed a technique to precisely manipulate the local magnetic charge states and demonstrate write-read-erase multifunctionality at room temperature. This globally reconfigurable and locally writable magnetic charge ice could provide a setting for designing magnetic monopole defects, tailoring magnonics, and controlling the properties of other two-dimensional materials.

  3. Artificial Error Tuning Based on Design a Novel SISO Fuzzy Backstepping Adaptive Variable Structure Control

    Directory of Open Access Journals (Sweden)

    Samaneh Zahmatkesh

    2013-10-01

    Full Text Available This paper examines single input single output (SISO chattering free variable structure control (VSC which controller coefficient is on-line tuned by fuzzy backstepping algorithm to control of continuum robot manipulator. Variable structure methodology is selected as a framework to construct the control law and address the stability and robustness of the close loop system based on Lyapunove formulation. The main goal is to guarantee acceptable error result and adjust the trajectory following. The proposed approach effectively combines the design technique from variable structure controller is based on Lyapunov and modified Proportional plus Derivative (P+D fuzzy estimator to estimate the nonlinearity of undefined system dynamic in backstepping controller. The input represents the function between variable structure function, error and the modified rate of error. The outputs represent joint torque, respectively. The fuzzy backstepping methodology is on-line tune the variable structure function based on adaptive methodology. The performance of the SISO VSC based on-line tuned by fuzzy backstepping algorithm (FBSAVSC is validated through comparison with VSC. Simulation results signify good performance of trajectory in presence of uncertainty joint torque load.

  4. Reinforcement learning output feedback NN control using deterministic learning technique.

    Science.gov (United States)

    Xu, Bin; Yang, Chenguang; Shi, Zhongke

    2014-03-01

    In this brief, a novel adaptive-critic-based neural network (NN) controller is investigated for nonlinear pure-feedback systems. The controller design is based on the transformed predictor form, and the actor-critic NN control architecture includes two NNs, whereas the critic NN is used to approximate the strategic utility function, and the action NN is employed to minimize both the strategic utility function and the tracking error. A deterministic learning technique has been employed to guarantee that the partial persistent excitation condition of internal states is satisfied during tracking control to a periodic reference orbit. The uniformly ultimate boundedness of closed-loop signals is shown via Lyapunov stability analysis. Simulation results are presented to demonstrate the effectiveness of the proposed control. PMID:24807456

  5. H(sub infinity) techniques for spacecraft control

    Science.gov (United States)

    Frapard, B.; Leballois, S.; Champetier, C.

    1993-09-01

    The high performance Attitude and Orbit Control Systems (AOCS) and high accuracy Instrument Pointing Systems design require more and more control bandwidth: dynamic couplings can be no more neglected and control laws tend to be highly sensitive to the unmodeled dynamics. Multivariable systems analysis and optimal control synthesis tools, with robustness bounds/robustness constraints with respect to the unmodeled dynamics, are a major area of research for space applications. Among others, the large field of techniques provided by H(sub infinity) theory appears to be very promising. Two typical applications are presented in this paper, one concerning high accuracy pointing for observation satellites, with a particular interest in the SPOT Mark II platform, the other addressing the Drag Free Control problem for missions such as Aristoteles, STEP and Gravity Probe B.

  6. The Development of Radiation hardened tele-robot system - Development of artificial force reflection control for teleoperated mobile robots

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Ju Jang; Hong, Sun Gi; Kang, Young Hoon; Kim, Min Soeng [Korea Advanced Institute of Science and Technology, Taejon (Korea)

    1999-04-01

    One of the most important issues in teleoperation is to provide the sense of telepresence so as to conduct the task more reliably. In particular, teleoperated mobile robots are needed to have some kinds of backup system when the operator is blind for remote situation owing to the failure of vision system. In the first year, the idea of artificial force reflection was researched to enhance the reliability of operation when the mobile robot travels on the plain ground. In the second year, we extend previous results to help the teleoperator even when the robot climbs stairs. Finally, we apply the developed control algorithms to real experiments. The artificial force reflection method has two modes; traveling on the plain ground and climbing stairs. When traveling on the plain ground, the force information is artificially generated by using the range data from the environment while generating the impulse force when climbing stairs. To verify the validity of our algorithm, we develop the simulator which consists of the joystick and the visual display system. Through some experiments using this system, we confirm the validity and effectiveness of our new idea of artificial force reflection in the teleoperated mobile robot. 11 refs., 30 figs. (Author)

  7. Insect population control by the sterile-male technique

    International Nuclear Information System (INIS)

    The successful use of the sterile male technique to eradicate the screw worm fly from the Southeastern part of the United States showed that a new biological method using radiation-sterilized insects could not only control but also eradicate harmful insect pests. A panel of experts met at the IAEA in Vienna in October 1962 to discuss the various aspects and applications of this new technique and to assess its usefulness and limitations. This report summarizes the panel proceedings. 42 refs, 18 figs, 1 tab

  8. Artificial Culture and Breeding Technique of Shizothorax grahami%昆明裂腹鱼人工驯养繁殖技术

    Institute of Scientific and Technical Information of China (English)

    胡思玉; 詹会祥; 赵海涛; 陈永祥

    2012-01-01

    昆明裂腹鱼(Shizothorax grahami)是长江上游特有的较大型经济鱼类之一,为更好地保护这一珍稀鱼类资源,对其生物学特性、人工驯养及人工繁殖技术进行了综述,为昆明裂腹鱼的人工驯养及繁殖提供一定的理论依据.%Shizothorax grahami is a kind of economic fish which is unique in the upper Yangtze River. To protect this rarefish, the biological characteristics, artificial domestication and artificial reproduction techniques of Shizothorax grahami were investigated, and it have large theoretical significance.

  9. Robust and Accurate Closed-Loop Control of McKibben Artificial Muscle Contraction with a Linear Single Integral Action

    Directory of Open Access Journals (Sweden)

    Bertrand Tondu

    2014-06-01

    Full Text Available We analyze the possibility of taking advantage of artificial muscle’s own stiffness and damping, and substituting it for a classic proportional-integral-derivative controller (PID controller an I controller. The advantages are that there would only be one parameter to tune and no need for a dynamic model. A stability analysis is proposed from a simple phenomenological artificial muscle model. Step and sinus-wave tracking responses performed with pneumatic McKibben muscles are reported showing the practical efficiency of the method to combine accuracy and load robustness. In the particular case of the McKibben artificial muscle technology, we suggest that the dynamic performances in stability and load robustness would result from the textile nature of its braided sleeve and its internal friction which do not obey Coulomb’s third law, as verified by preliminary reported original friction experiments. Comparisons are reported between three kinds of braided sleeves made of rayon yarns, plastic, and thin metal wires, whose similar closed-loop dynamic performances are highlighted. It is also experimentally shown that a sleeve braided with thin metal wires can give high accuracy performance, in step as in tracking response. This would be due to a low static friction coefficient combined with a kinetic friction exponentially increasing with speed in accordance with hydrodynamic lubrication theory applied to textile physics.

  10. Models of signal validation using artificial intelligence techniques applied to a nuclear reactor; Modelos de validacao de sinal utilizando tecnicas de inteligencia artificial aplicados a um reator nuclear

    Energy Technology Data Exchange (ETDEWEB)

    Oliveira, Mauro V. [Instituto de Engenharia Nuclear (IEN), Rio de Janeiro, RJ (Brazil); Schirru, Roberto [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia

    2000-07-01

    This work presents two models of signal validation in which the analytical redundancy of the monitored signals from a nuclear plant is made by neural networks. In one model the analytical redundancy is made by only one neural network while in the other it is done by several neural networks, each one working in a specific part of the entire operation region of the plant. Four cluster techniques were tested to separate the entire operation region in several specific regions. An additional information of systems' reliability is supplied by a fuzzy inference system. The models were implemented in C language and tested with signals acquired from Angra I nuclear power plant, from its start to 100% of power. (author)

  11. Key techniques of automatic gauge control and profile control for aluminium strip and foil

    Institute of Scientific and Technical Information of China (English)

    LI Mou-wei; LIU Hong-fei; WANG Xiang-li; TONG Chao-nan; YIN Feng-fu; BIAN Xin-xiao; ZHANG Lei

    2006-01-01

    Such characteristics of aluminium strip and foil as soft and thin gauge make tension control one of the key techniques for automation gauge control(AGC). To avoid the disadvantage of traditional mathematical control method which is unfitful for nonlinear hysteresis, the technique for tension AGC fuzzy control was developed and thickness deviation more than 3% of product thickness was achieved consequently in 1 350 mm cold rolling mill of aluminium strip and foil. Additionally, because the gauge of aluminium strip and foil is thin, stage-cooling roll method becomes a key technique for profile control. So stage-cooling roll intelligent control method is developed and pre-coated aluminum foil with good profile less than 10 I (the relative differences in elongation of 0.01% ) is produced using the profile control system in 1 400 mm cold rolling mill of aluminium strip and foil.

  12. New approaches in intelligent control techniques, methodologies and applications

    CERN Document Server

    Kountchev, Roumen

    2016-01-01

    This volume introduces new approaches in intelligent control area from both the viewpoints of theory and application. It consists of eleven contributions by prominent authors from all over the world and an introductory chapter. This volume is strongly connected to another volume entitled "New Approaches in Intelligent Image Analysis" (Eds. Roumen Kountchev and Kazumi Nakamatsu). The chapters of this volume are self-contained and include summary, conclusion and future works. Some of the chapters introduce specific case studies of various intelligent control systems and others focus on intelligent theory based control techniques with applications. A remarkable specificity of this volume is that three chapters are dealing with intelligent control based on paraconsistent logics.

  13. Robust Fault-Tolerant Control for Satellite Attitude Stabilization Based on Active Disturbance Rejection Approach with Artificial Bee Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Fei Song

    2014-01-01

    Full Text Available This paper proposed a robust fault-tolerant control algorithm for satellite stabilization based on active disturbance rejection approach with artificial bee colony algorithm. The actuating mechanism of attitude control system consists of three working reaction flywheels and one spare reaction flywheel. The speed measurement of reaction flywheel is adopted for fault detection. If any reaction flywheel fault is detected, the corresponding fault flywheel is isolated and the spare reaction flywheel is activated to counteract the fault effect and ensure that the satellite is working safely and reliably. The active disturbance rejection approach is employed to design the controller, which handles input information with tracking differentiator, estimates system uncertainties with extended state observer, and generates control variables by state feedback and compensation. The designed active disturbance rejection controller is robust to both internal dynamics and external disturbances. The bandwidth parameter of extended state observer is optimized by the artificial bee colony algorithm so as to improve the performance of attitude control system. A series of simulation experiment results demonstrate the performance superiorities of the proposed robust fault-tolerant control algorithm.

  14. Non-Destructive Testing Techniques for Research and Process Control

    International Nuclear Information System (INIS)

    Non-destructive test methods have been used primarily for the detection of defects and the rejection of faulty materials. The Oak Ridge National Laboratory has found it valuable to employ special non-destructive testing techniques as aids in materials research, component development, and process control. This paper gives three recent examples of the evolution of non-destructive testing techniques from research to process control. A current fuel-element design contains fuel pins filled with vibratorily compacted uranium and thorium oxide powder. A gamma-attenuation technique was developed to allow the homogeneity of fuel loading to be measured and was used to aid the development of fabrication techniques and equipment. Later an inspection device was built to operate remotely in a hermetically sealed and shielded facility and used for production process control. Another fuel element required fuel plates containing a uranium oxide-aluminium dispersion core with a programmed variation in the fuel loading across the width. A continuous scanning, X-ray attenuation technique was developed and used to measure fuel inhomogeneities and conformity to design contour. The technique assisted the development for both core pressing and plate-rolling practices. A system was constructed for rapid automatic evaluation of production fuel plates. These fuel plates were pressed into involute shape and assembled with alternate cooling channels. Stringent heat-transfer requirements imposed a tight tolerance on the channel dimensions. A unique eddy-current device using the ''lift-off'' characteristic was invented to insert in the very narrow channel and allow recording of dimensions both during fabrication development and actual manufacture. Another approach to fuel elements is the use of minute fuel-bearing particles coated with pyrolytic carbon to retain the fission products. Of concern are the core diameter, coating thickness and integrity, and presence of fuel in the coating

  15. 家蚕人工授精关键技术的研究%Study on Key Technique of Artificial Insemination for Silkworm, Bombyx mori

    Institute of Scientific and Technical Information of China (English)

    张业顺; 张国政; 韦亚东; 夏定国

    2009-01-01

    [Objective] The aim of this study was to investigate the efficient technique of artificial insemination for silkworm. [Method] Sperms were extracted from bursa copulatrix of female moths mated for 30 min through extruding and centrifugal method, and then the semen was injected into other virgin moths with trypsinase. [Result] A high-effective collection technology of spermatids from silkworm was established successfully, 50 μl semen could be collected by only one person in each hour. The survival rate of spermatids was over 80% in vito after collected from bursa copulatrix, while the obtained semen was quite pure and the average fertilization rate of silkworm was 76.5%. [Conclusion] The establishment of high-effective semen extraction technique of silkworm provides the technical basis for studies on other related techniques for silkworm sperm.

  16. Quantum coherence controls the charge separation in a prototypical artificial light harvesting system

    Directory of Open Access Journals (Sweden)

    Schramm H.

    2013-03-01

    Full Text Available Ultrafast spectroscopy and quantum-dynamics simulations of an artificial supramolecular light-harvesting system — a supramolecular triad - provide strong evidence that the quantum-correlated wavelike motion of electrons and nuclei on a timescale of few tens of femtoseconds governs the ultrafast electronic charge transfer.

  17. Algorithms for a Single Hormone Closed-Loop Artificial Pancreas: Challenges Pertinent to Chemical Process Operations and Control

    Directory of Open Access Journals (Sweden)

    B. Wayne Bequette

    2016-10-01

    Full Text Available The development of a closed-loop artificial pancreas to regulate the blood glucose concentration of individuals with type 1 diabetes has been a focused area of research for over 50 years, with rapid progress during the past decade. The daily control challenges faced by someone with type 1 diabetes include asymmetric objectives and risks, and one-sided manipulated input action with frequent relatively fast disturbances. The major automation steps toward a closed-loop artificial pancreas include (i monitoring and overnight alarms for hypoglycemia (low blood glucose; (ii overnight low glucose suspend (LGS systems to prevent hypoglycemia; and (iii fully closed-loop systems that adjust insulin (and perhaps glucagon to maintain desired blood glucose levels day and night. We focus on the steps that we used to develop and test a probabilistic, risk-based, model predictive control strategy for a fully closed-loop artificial pancreas. We complete the paper by discussing ramifications of lessons learned for chemical process systems applications.

  18. Multi-level overlay techniques for improving DPL overlay control

    Science.gov (United States)

    Chen, Charlie; Pai, Y. C.; Yu, Dennis; Pang, Peter; Yu, Chun Chi; Wu, Robert (Hsing-Chien); Huang, Eros (Chien Jen); Chen, Marson (Chiun-Chieh); Tien, David; Choi, Dongsub

    2012-03-01

    Overlay continues to be one of the key challenges for lithography in semiconductor manufacturing, especially in light of the accelerated pace of device node shrinks. This reality will be especially evident at 20nm node where DPL and multi-layer overlay will require 4nm or less in overlay control across many critical layers in order to meet device yield entitlements. The motivation for this paper is based on improving DPL overlay control in face of the high complexity involved with multi-layer overlay requirements. For example, the DPL-2nd-litho layer will need to achieve tight registration with the DPL-1st-litho layer, and at the same time, it will need to achieve tight overlay to the reference-litho layer, which in some cases can also be a DPL layer. Of course, multi-level overlay measurements are not new, but the combination of increased complexity of multi-DPL layers and extremely challenging overlay specifications for 20nm node together will necessitate a better understanding of multi-level overlay control, specifically in terms of root cause analysis of multi-layer related overlay errors and appropriate techniques for improvement In this paper, we start with the identification of specific overlay errors caused by multi-layer DPL processing on full film stack product wafers. After validation of these findings with inter-lot and intra-lot controlled experiments, we investigate different advanced control techniques to determine how to optimize overlay control and minimize both intra-lot and inter-lot sources of error. A new approach to overlay data analysis will also be introduced that combines empirical data with target image quality data to more accurately determine and better explain the root cause error mechanism as well as provide effective strategies for improved overlay control.

  19. Biosolar cells: global artificial photosynthesis needs responsive matrices with quantum coherent kinetic control for high yield.

    Science.gov (United States)

    Purchase, R L; de Groot, H J M

    2015-06-01

    This contribution discusses why we should consider developing artificial photosynthesis with the tandem approach followed by the Dutch BioSolar Cells consortium, a current operational paradigm for a global artificial photosynthesis project. We weigh the advantages and disadvantages of a tandem converter against other approaches, including biomass. Owing to the low density of solar energy per unit area, artificial photosynthetic systems must operate at high efficiency to minimize the land (or sea) area required. In particular, tandem converters are a much better option than biomass for densely populated countries and use two photons per electron extracted from water as the raw material into chemical conversion to hydrogen, or carbon-based fuel when CO2 is also used. For the average total light sum of 40 mol m(-2) d(-1) for The Netherlands, the upper limits are many tons of hydrogen or carbon-based fuel per hectare per year. A principal challenge is to forge materials for quantitative conversion of photons to chemical products within the physical limitation of an internal potential of ca 2.9 V. When going from electric charge in the tandem to hydrogen and back to electricity, only the energy equivalent to 1.23 V can be stored in the fuel and regained. A critical step is then to learn from nature how to use the remaining difference of ca 1.7 V effectively by triple use of one overpotential for preventing recombination, kinetic stabilization of catalytic intermediates and finally generating targeted heat for the release of oxygen. Probably the only way to achieve this is by using bioinspired responsive matrices that have quantum-classical pathways for a coherent conversion of photons to fuels, similar to what has been achieved by natural selection in evolution. In appendix A for the expert, we derive a propagator that describes how catalytic reactions can proceed coherently by a convergence of time scales of quantum electron dynamics and classical nuclear dynamics. We

  20. Artificial Inductance Concept to Compensate Nonlinear Inductance Effects in the Back EMF-Based Sensorless Control Method for PMSM

    DEFF Research Database (Denmark)

    Lu, Kaiyuan; Lei, Xiao; Blaabjerg, Frede

    2013-01-01

    The back EMF-based sensorless control method is very popular for permanent magnet synchronous machines (PMSMs) in the medium- to high-speed operation range due to its simple structure. In this speed range, the accuracy of the estimated position is mainly affected by the inductance, which varies...... at different loading conditions due to saturation effects. In this paper, a new concept of using a constant artificial inductance to replace the actual varying machine inductance for position estimation is introduced. This facilitates greatly the analysis of the influence of inductance variation...... on the estimated position error, and gives a deep insight into this problem. It also provides a simple approach to achieve a globally minimized position error. A proper choice of the artificial machine inductance may reduce the maximum position error by 50% without considering the actual inductance variation...

  1. Multi-time-step ahead daily and hourly intermittent reservoir inflow prediction by artificial intelligent techniques using lumped and distributed data

    Science.gov (United States)

    Jothiprakash, V.; Magar, R. B.

    2012-07-01

    SummaryIn this study, artificial intelligent (AI) techniques such as artificial neural network (ANN), Adaptive neuro-fuzzy inference system (ANFIS) and Linear genetic programming (LGP) are used to predict daily and hourly multi-time-step ahead intermittent reservoir inflow. To illustrate the applicability of AI techniques, intermittent Koyna river watershed in Maharashtra, India is chosen as a case study. Based on the observed daily and hourly rainfall and reservoir inflow various types of time-series, cause-effect and combined models are developed with lumped and distributed input data. Further, the model performance was evaluated using various performance criteria. From the results, it is found that the performances of LGP models are found to be superior to ANN and ANFIS models especially in predicting the peak inflows for both daily and hourly time-step. A detailed comparison of the overall performance indicated that the combined input model (combination of rainfall and inflow) performed better in both lumped and distributed input data modelling. It was observed that the lumped input data models performed slightly better because; apart from reducing the noise in the data, the better techniques and their training approach, appropriate selection of network architecture, required inputs, and also training-testing ratios of the data set. The slight poor performance of distributed data is due to large variations and lesser number of observed values.

  2. Artificial Intelligence based Tuning of SVC Controller FOR CO-generated Power System

    Directory of Open Access Journals (Sweden)

    Vinod Kumar

    2007-06-01

    Full Text Available The gain of SVC depends upon the type of reactive power load for optimum performance. As the load and input wind power conditions are variable, the gain setting of SVC needs to be adjusted or tuned. In this paper, an ANN based approach has been used to tune the gain parameters of the SVC controller over a wide range of load characteristics. The multi-layer feed-forward ANN tool with the error back-propagation training method is employed. Loads have been taken as the function of voltage. Analytical techniques have mostly been based on impedance load reduced network models, which suffer from several disadvantages, including inadequate load representation and lack of structural integrity. The ability of ANNs to spontaneously learn from examples, reason over inexact and fuzzy data and provide adequate and quick responses to new information not previously stored in memory has generated high performance dynamical system with unprecedented robustness. ANNs models have been developed for different hybrid power system configurations for tuning the proportional-integral controller for SVC. Transient responses of different autonomous configurations show that SVC controller with its gained tuned by the ANNs provide optimum system performance for a variety of loads.

  3. Integrated controlling technique of ecological environment in Shendong Mining Area

    Institute of Scientific and Technical Information of China (English)

    ZHANG Dong-sheng; LIU Yu-de; WANG An; WANG Yi

    2007-01-01

    To enclose the interactive relation between the underground mining with suitable protection for surface ecological environments and surface prevention of ecological environments adapting to mining disturbing was researched and developed core of this technique. There are three aspects of controlling ecological environments, to dispose and renew before exploitation, to protect surface ecological environments in the exploitative process and to repair and build up after exploitation. Based on the moving law of overburden strata in shallow seam, the surface subsidence law and the growth law of vegetation in subsidence mine area, the integrated controlling technique has been developed synthetically by methods of theoretic analysis, laboratory simulation, numerical calculation,commercial test etc.. It includes the key techniques of aquifer-protective mining, filtering and purging of mine water through goaf, preventing and extinguishing fire in shallow seam,no-rock roadway layout and waste disposal in underground, frame-building ecological functional sphere before exploitation, frame-building the ecological cycle using system after mining and so on.

  4. A New Mathematical Modeling Technique for Pull Production Control Systems

    Directory of Open Access Journals (Sweden)

    O. Srikanth

    2013-12-01

    Full Text Available The Kanban Control System widely used to control the release of parts of multistage manufacturing system operating under a pull production control system. Most of the work on Kanban Control System deals with multi-product manufacturing system. In this paper, we are proposing a regression modeling technique in a multistage manufacturing system is to be coordinates the release of parts into each stage of the system with the arrival of customer demands for final products. And also comparing two variants stages of the Kanban Control System model and combines with mathematical and Simulink model for the production coordination of parts in an assembly manufacturing systems. In both variants, the production of a new subassembly is authorized only when an assembly Kanban is available. Assembly kanbans become available when finished product is consumed. A simulation environment for the product line system has to generate with the proposed model and the mathematical model have to give implementation against the simulation model in the working platform of MATLAB. Both the simulation and model outputs have provided an in depth analysis of each of the resulting control system for offering model of a product line system.

  5. Reinforcement learning techniques for controlling resources in power networks

    Science.gov (United States)

    Kowli, Anupama Sunil

    As power grids transition towards increased reliance on renewable generation, energy storage and demand response resources, an effective control architecture is required to harness the full functionalities of these resources. There is a critical need for control techniques that recognize the unique characteristics of the different resources and exploit the flexibility afforded by them to provide ancillary services to the grid. The work presented in this dissertation addresses these needs. Specifically, new algorithms are proposed, which allow control synthesis in settings wherein the precise distribution of the uncertainty and its temporal statistics are not known. These algorithms are based on recent developments in Markov decision theory, approximate dynamic programming and reinforcement learning. They impose minimal assumptions on the system model and allow the control to be "learned" based on the actual dynamics of the system. Furthermore, they can accommodate complex constraints such as capacity and ramping limits on generation resources, state-of-charge constraints on storage resources, comfort-related limitations on demand response resources and power flow limits on transmission lines. Numerical studies demonstrating applications of these algorithms to practical control problems in power systems are discussed. Results demonstrate how the proposed control algorithms can be used to improve the performance and reduce the computational complexity of the economic dispatch mechanism in a power network. We argue that the proposed algorithms are eminently suitable to develop operational decision-making tools for large power grids with many resources and many sources of uncertainty.

  6. Direct in vivo study of flowing blood-artificial surface interactions - an original application of dynamic isotopic techniques

    International Nuclear Information System (INIS)

    A Ge(Li) detector, associated with a data acquisition and storage unit, and a data analysis facility, was used to record sequentially the activity, related to several radioisotopes, inside an extracorporeal shunt, settled between the femoral artery and the colateral vein of an anaesthetized dog. The shunt was made of a material, the haemocompatibility of which needed to be evaluated. Before the blood was allowed to flow through the shunt, the circulation of the dog was fed with technetium- or indium-labelled biological species thought to be concerned with blood-artificial surface interactions. The method described here offers the possibility of computing kinetic parameters for these interactions. (author)

  7. The Use of Management Control Systems and Operations Management Techniques

    Directory of Open Access Journals (Sweden)

    Edelcio Koitiro Nisiyama

    2016-01-01

    Full Text Available It is well known that both management control systems (MCSs and operations management (OM are related to firm performance; however, an integrated st udy that involves MCS and OM within the context of firm performance is still lacking. This research aimed to examine the relationships among the use of MCSs and OM techniques and firm performance in the Brazilian auto parts industry. Simons’ levers of cont rol framework was used to characterise the uses of MCSs, and OM techniques, such as total quality management (TQM and continuous improvement programmes, were adopted. The results obtained through the structural equation modelling indicated that the diagno stic use of MCSs is positively associated with the goals of cost reduction. In addition, the interactive use of MCSs is positively associated with the objectives of introducing new products, which is consistent with previous research. Additionally, OM tech niques are positively related to cost reduction but have no direct relationship with the introduction of new products.

  8. Artificial vision.

    Science.gov (United States)

    Zarbin, M; Montemagno, C; Leary, J; Ritch, R

    2011-09-01

    A number treatment options are emerging for patients with retinal degenerative disease, including gene therapy, trophic factor therapy, visual cycle inhibitors (e.g., for patients with Stargardt disease and allied conditions), and cell transplantation. A radically different approach, which will augment but not replace these options, is termed neural prosthetics ("artificial vision"). Although rewiring of inner retinal circuits and inner retinal neuronal degeneration occur in association with photoreceptor degeneration in retinitis pigmentosa (RP), it is possible to create visually useful percepts by stimulating retinal ganglion cells electrically. This fact has lead to the development of techniques to induce photosensitivity in cells that are not light sensitive normally as well as to the development of the bionic retina. Advances in artificial vision continue at a robust pace. These advances are based on the use of molecular engineering and nanotechnology to render cells light-sensitive, to target ion channels to the appropriate cell type (e.g., bipolar cell) and/or cell region (e.g., dendritic tree vs. soma), and on sophisticated image processing algorithms that take advantage of our knowledge of signal processing in the retina. Combined with advances in gene therapy, pathway-based therapy, and cell-based therapy, "artificial vision" technologies create a powerful armamentarium with which ophthalmologists will be able to treat blindness in patients who have a variety of degenerative retinal diseases.

  9. Distributed flow estimation and closed-loop control of an underwater vehicle with a multi-modal artificial lateral line.

    Science.gov (United States)

    DeVries, Levi; Lagor, Francis D; Lei, Hong; Tan, Xiaobo; Paley, Derek A

    2015-04-01

    Bio-inspired sensing modalities enhance the ability of autonomous vehicles to characterize and respond to their environment. This paper concerns the lateral line of cartilaginous and bony fish, which is sensitive to fluid motion and allows fish to sense oncoming flow and the presence of walls or obstacles. The lateral line consists of two types of sensing modalities: canal neuromasts measure approximate pressure gradients, whereas superficial neuromasts measure local flow velocities. By employing an artificial lateral line, the performance of underwater sensing and navigation strategies is improved in dark, cluttered, or murky environments where traditional sensing modalities may be hindered. This paper presents estimation and control strategies enabling an airfoil-shaped unmanned underwater vehicle to assimilate measurements from a bio-inspired, multi-modal artificial lateral line and estimate flow properties for feedback control. We utilize potential flow theory to model the fluid flow past a foil in a uniform flow and in the presence of an upstream obstacle. We derive theoretically justified nonlinear estimation strategies to estimate the free stream flowspeed, angle of attack, and the relative position of an upstream obstacle. The feedback control strategy uses the estimated flow properties to execute bio-inspired behaviors including rheotaxis (the tendency of fish to orient upstream) and station-holding (the tendency of fish to position behind an upstream obstacle). A robotic prototype outfitted with a multi-modal artificial lateral line composed of ionic polymer metal composite and embedded pressure sensors experimentally demonstrates the distributed flow sensing and closed-loop control strategies. PMID:25807584

  10. Application of Active Flow Control Technique for Gust Load Alleviation

    Institute of Scientific and Technical Information of China (English)

    XU Xiaoping; ZHU Xiaoping; ZHOU Zhou; FAN Ruijun

    2011-01-01

    A new gust load alleviation technique is presented in this paper based on active flow control.Numerical studies are conducted to investigate the beneficial effects on the aerodynamic characteristics of the quasi “Global Hawk” airfoil using arrays of jets during the gust process.Based on unsteady Navier-Stokes equations,the grid-velocity method is introduced to simulate the gust influence,and dynamic response in vertical gust flow perturbation is investigated for the airfoil as well.An unsteady surface transpiration boundary condition is enforced over a user specified portion of the airfoil's surface to emulate the time dependent velocity boundary conditions.Firstly,after applying this method to simulate typical NACA0006 airfoil gust response to a step change in the angle of attack,it shows that the indicial responses of the airfoil make good agreement with the exact theoretical values and the calculated values in references.Furthermore,gust response characteristic for the quasi “Global Hawk” airfoil is analyzed.Five kinds of flow control techniques are introduced as steady blowing,steady suction,unsteady blowing,unsteady suction and synthetic jets.The physical analysis of the influence on the effects of gust load alleviation is proposed to provide some guidelines for practice.Numerical results have indicated that active flow control technique,as a new technology of gust load alleviation,can affect and suppress the fluid disturbances caused by gust so as to achieve the purpose of gust load alleviation.

  11. Nuclear and related techniques in the control of communicable diseases

    International Nuclear Information System (INIS)

    The IAEA has a programme component entitled ''Nuclear Techniques in Communicable Diseases'', the aims of which are to encourage research in the development of new methods of controlling communicable diseases and to transfer the technology to institutes in endemic regions. Implementation of the programme component includes information exchange through publications, symposiums and seminars. The two most recent seminars were held in Bombay in November 1988 and Belo Horizonte in November 1989, and a selection of the papers presented have been published in this Technical Document. Refs, figs and tabs

  12. An artificial-vision responsive to patient motions during computer controlled radiation therapy

    International Nuclear Information System (INIS)

    Purpose/Objectives: Automated precision radiotherapy using multiple conformal and modulated beams, requires monitoring of patient movements during irradiation. Immobilizers relying on patient cooperating in cradles have somewhat reduced positional uncertainties, but others including breathing are largely unknown. We built an artificial vision (AV) device for real-time vision of patient movements, their tracking and quantification. Method and Materials: The Artificial Vision System's 'acuity' and 'reflex' were evaluated in terms of imaged skin spatial resolutions and temporal dispersions measured using a mannequin and a fiduciated harmonic oscillator placed at 100cm isocenter. The device traced skin motion even in poorly lighted rooms without use of explicit skin fiduciation, or using standard radiotherapy skin tattoos. Results: The AV system tracked human skin at vision rates approaching 30Hz and sensitivity of 2mm. It successfully identified and tracked independent skin marks, either natural tattoos or artificial fiducials. Three alert levels triggered when patient movement exceeded preset displacements (2mm/30Hz), motion velocities (5m/sec) or acceleration (2m/sec2). Conclusion: The AV system trigger should suit for patient ventilatory gating and safety interlocking of treatment accelerators, in order to modulate, interrupt, or abort radiation during dynamic therapy

  13. Artificial perches as a nucleation technique for restoration of a riparian environment: characterization of the seed rain and of natural regeneration

    Directory of Open Access Journals (Sweden)

    Aline Luiza Tomazi

    2010-09-01

    Full Text Available Riparian habitats are important to the maintenance of ecological processes and environmental services. However, a significant portion of the riparian vegetation in the Brazilian Atlantic forest has been removed in response to increasing human pressure. Therefore, the application of restoration techniques in these habitats becomes essential. In this context, a nucleation model with 18 artificial perches was evaluated for the restoration of a degraded riparian area in Gaspar, Santa Catarina, Brazil, by the characterization of the seed rain and natural regeneration. In two years we collected 21,864 seeds of 51 morphospecies, and recorded 42 colonizing species. Zoochoric seeds belonging to 15 plant families comprised 17% of the seed rain and 19.05% of the spontaneously regenerating plant species. Asteraceae and Poaceae were the most represented families. The artificial perches performed the nucleating function through the increase of zoochoric seed rain. However, possibly due to different barriers that were not evaluated in this study, part of these seeds was not recruited. We recommend the application of this technique for the attraction of dispersers in degraded areas similar to the study site.

  14. Demand Management Based on Model Predictive Control Techniques

    Directory of Open Access Journals (Sweden)

    Yasser A. Davizón

    2014-01-01

    Full Text Available Demand management (DM is the process that helps companies to sell the right product to the right customer, at the right time, and for the right price. Therefore the challenge for any company is to determine how much to sell, at what price, and to which market segment while maximizing its profits. DM also helps managers efficiently allocate undifferentiated units of capacity to the available demand with the goal of maximizing revenue. This paper introduces control system approach to demand management with dynamic pricing (DP using the model predictive control (MPC technique. In addition, we present a proper dynamical system analogy based on active suspension and a stability analysis is provided via the Lyapunov direct method.

  15. Control techniques for an automated mixed traffic vehicle

    Science.gov (United States)

    Meisenholder, G. W.; Johnston, A. R.

    1977-01-01

    The paper describes an automated mixed traffic vehicle (AMTV), a driverless low-speed tram designed to operate in mixed pedestrian and vehicular traffic. The vehicle is a six-passenger electric tram equipped with sensing and control which permit it to function on existing streets in an automatic mode. The design includes established wire-following techniques for steering and near-IR headway sensors. A 7-mph cruise speed is reduced to 2 mph or a complete stop in response to sensor (or passenger) inputs. The AMTV performance is evaluated by operation on a loop route and by simulation. Some necessary improvements involving sensors, sensor pattern, use of an audible signal, and control lag are discussed. It is suggested that appropriate modifications will eliminate collision incidents.

  16. Fish recognition based on the combination between robust feature selection, image segmentation and geometrical parameter techniques using Artificial Neural Network and Decision Tree

    CERN Document Server

    Alsmadi, Mutasem Khalil Sari; Noah, Shahrul Azman; Almarashdah, Ibrahim

    2009-01-01

    We presents in this paper a novel fish classification methodology based on a combination between robust feature selection, image segmentation and geometrical parameter techniques using Artificial Neural Network and Decision Tree. Unlike existing works for fish classification, which propose descriptors and do not analyze their individual impacts in the whole classification task and do not make the combination between the feature selection, image segmentation and geometrical parameter, we propose a general set of features extraction using robust feature selection, image segmentation and geometrical parameter and their correspondent weights that should be used as a priori information by the classifier. In this sense, instead of studying techniques for improving the classifiers structure itself, we consider it as a black box and focus our research in the determination of which input information must bring a robust fish discrimination.The main contribution of this paper is enhancement recognize and classify fishes...

  17. Evolutionary biology and genetic techniques for insect control.

    Science.gov (United States)

    Leftwich, Philip T; Bolton, Michael; Chapman, Tracey

    2016-01-01

    The requirement to develop new techniques for insect control that minimize negative environmental impacts has never been more pressing. Here we discuss population suppression and population replacement technologies. These include sterile insect technique, genetic elimination methods such as the release of insects carrying a dominant lethal (RIDL), and gene driving mechanisms offered by intracellular bacteria and homing endonucleases. We also review the potential of newer or underutilized methods such as reproductive interference, CRISPR technology, RNA interference (RNAi), and genetic underdominance. We focus on understanding principles and potential effectiveness from the perspective of evolutionary biology. This offers useful insights into mechanisms through which potential problems may be minimized, in much the same way that an understanding of how resistance evolves is key to slowing the spread of antibiotic and insecticide resistance. We conclude that there is much to gain from applying principles from the study of resistance in these other scenarios - specifically, the adoption of combinatorial approaches to minimize the spread of resistance evolution. We conclude by discussing the focused use of GM for insect pest control in the context of modern conservation planning under land-sparing scenarios. PMID:27087849

  18. Intention recognition, commitment and their roles in the evolution of cooperation from artificial intelligence techniques to evolutionary game theory models

    CERN Document Server

    Han, The Anh

    2013-01-01

    This original and timely monograph describes a unique self-contained excursion that reveals to the readers the roles of two basic cognitive abilities, i.e. intention recognition and arranging commitments, in the evolution of cooperative behavior. This book analyses intention recognition, an important ability that helps agents predict others’ behavior, in its artificial intelligence and evolutionary computational modeling aspects, and proposes a novel intention recognition method. Furthermore, the book presents a new framework for intention-based decision making and illustrates several ways in which an ability to recognize intentions of others can enhance a decision making process. By employing the new intention recognition method and the tools of evolutionary game theory, this book introduces computational models demonstrating that intention recognition promotes the emergence of cooperation within populations of self-regarding agents. Finally, the book describes how commitment provides a pathway to the evol...

  19. Power Control Technique for Efficient Call Admission Control in Advanced Wirless Networks

    Directory of Open Access Journals (Sweden)

    Ch. Sreenivasa Rao

    2012-06-01

    Full Text Available In 4G networks, call admission control techniques have been proposed to provide Quality of Service (QoS in a network by restricting the access to network resources. Power control is essential in call admission control in order to provide fair access to all users, improve battery lifetime and system performance. But the existing call admission control algorithms rarely consider the power controlling techniques in the handoff process for different traffic classes. In this paper, we propose to develop a power controlled call admission control scheme for handoff in the advanced wireless networks. The incoming call measures the initial interference on it and then the base station starts transmitting the packets to the new call. The new call is rejected when the interference reaches a threshold value.Whenever an existing call meets the power constraint, the transmit power is decremented based on thetraffic class and incoming call obtains this information by monitoring the interference received on it. Theconvergence of the power control algorithm is checked and the power levels of all incoming calls areadjusted. From our simulation results we prove that this power control technique provides efficienthandoff in the 4G networks by increasing the throughput and reducing the delay of the existing users.

  20. Hybrid Position Tracking Control of a Pneumatic Artificial Muscle%基于气动人工肌肉的混合位置跟踪控制

    Institute of Scientific and Technical Information of China (English)

    沈伟; 施光林

    2012-01-01

    A single degree freedom pneumatic artificial muscle spring mass system was built.The pneumatic artificial muscle is controlled by high speed on/off valve in PWM technique.A hybrid controller is setup to tracking control the pneumatic artificial muscle system which is composed of an adaptive fuzzy CMAC(cerebellar model articulation controller) and discrete sliding mode reaching low strategy.In hybrid controller discrete sliding mode strategy produces the control output;the adaptive fuzzy CMAC is used to approximate the uncertainty of the pneumatic artificial muscle control system.The on-line self adjustment ability guarantees the approximation ability of the adaptive fuzzy CMAC.Finally,the comparative study of control performance between discrete anti saturation PID(DASPID) and hybrid controller(HybridC) was carried out.The experimental results suggest that the hybridC is better than DASPID.While the desired reference input is sinusoidal,the biggest tracking error of PID is ±1.5 mm;however the biggest tracking error of the hybridC is only ±0.7 mm;the average tracking error is about ±0.2 mm.Furthermore as the main drawback of discrete sliding mode strategy,the chatter phenomenon is greatly reduced.%针对一种气动人工肌肉驱动的弹簧质量位置控制系统,设计了一个带有自适应模糊小脑模型(Cerebellar Model Articulation Controller,CMAC)在线逼近的离散趋近律滑模混合控制器.该混合控制器中离散趋近律滑模策略产生控制器的输出;自适应模糊CMAC用以逼近气动人工肌肉系统中的不确定项.CMAC网络权值的在线学习调整保证了自适应模糊CMAC的逼近性能.对离散抗饱和PID控制器(DASPID)与自适应模糊CMAC离散滑模混合控制器(HybridC)的位置跟踪控制性能进行了对比实验.实验结果表明,HybridC较之DASPID有更好的位置跟踪控制性能.当期望参考输入为正弦信号时,DASPID的最大位置跟踪误差为±1.5 mm;

  1. Artificial intelligence in medicine.

    Science.gov (United States)

    Ramesh, A. N.; Kambhampati, C.; Monson, J. R. T.; Drew, P. J.

    2004-01-01

    INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. METHODS: Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of different artificial intelligent techniques is presented in this paper along with the review of important clinical applications. RESULTS: The proficiency of artificial intelligent techniques has been explored in almost every field of medicine. Artificial neural network was the most commonly used analytical tool whilst other artificial intelligent techniques such as fuzzy expert systems, evolutionary computation and hybrid intelligent systems have all been used in different clinical settings. DISCUSSION: Artificial intelligence techniques have the potential to be applied in almost every field of medicine. There is need for further clinical trials which are appropriately designed before these emergent techniques find application in the real clinical setting. PMID:15333167

  2. The application of nuclear technique for practical controlling of Ectomyelois Ceratoniae zeller (Lepidoptera: Pyralidae)

    International Nuclear Information System (INIS)

    Iran ranks the first producer and exporter of pomegranate in the world. Carob moth Ectomyelois ceratiniae(Lepidoptera: Pyralidae) has also been recognized as an important pest of pomegranate in the country. Due to biology of the pest, the application of pesticide has not been considered practical and the losses to this product are more than 30 percent of the yield. The application of Sterile Insect Technique is a method that is used on a few insects with the specific characters. This research was accomplished for evaluation of the practical control of this pest upon application of nuclear methods on pomegranate. Larval and pupal stages were collected from Saveh, transferred to Agricultural, Medical and Industrial Research School and reared on artificial diet at 28±2degreeC, 60±5% Rh, 14:10 light: dark photo period. The produced pupae (young and old) were irradiated by gamma radiation and were reared with 0:0:1:1-9:9:1:1 (Irradiated male: Irradiated female: Natural male: Natural female) ratios on pomegranate fruits in the cages. The results show that the application of sterile doses (120 and 160 Gy) on pupae (Young 1,2 days and old 3-4 days old) and releasing ratios 7:7:1:1 to 9:9:1:1 in comparison with the controlled treatment by the releasing ratio of 0:0:1:1 that prevents damage of E. ceratiniae on the pomegranate.

  3. Time-Based Dithering Algorithm and Frame Rate Control Technique for STN LCD Controller

    Institute of Scientific and Technical Information of China (English)

    LEIJianming; ZOUXuechen

    2004-01-01

    Time-based dithering algorithm and Frame rate control (FRC) technique applied to the STN liquid crystal display controller are presented. The dithering unit performs time-based dithering algorithm on pixel data to advantageously increase smoothness of an image displayed. The frame rate control unit is responsive to the dithering unit and performs frame rate controlling to generate more gray-shades, which may reduce flicker and visual artifacts. Results show that the gray shades displayed on images can be up to 256 for monochrome STN LCD panels or 2563 colors for color STN LCD panels respectively by using timebased dithering algorithm and frame rate control technique if each encoded pixel data is 8 bits. The images displayed on the STN liquid crystal display can get desirable grayshades and very little flicker and visual artifacts.

  4. Semen preparation techniques in intrauterine insemination: A comparison of non-temperature and temperature controlled centrifugation in cases of unexplained infertility

    OpenAIRE

    Priya Selvaraj; Kamala Selvaraj; Kalaichelvi, S.; R.Mahalakshmi

    2013-01-01

    AIM: The aim of the following study is to compare pregnancy rates between the use of non-temperature and temperature controlled centrifugation on semen preparation technique in intrauterine insemination. MATERIALS AND METHODS: The retrospective study was conducted on 671 patients of idiopathic infertility who underwent homologous artificial insemination at Fertility Research Center from the period of January 2007 to September 2012. The couples were randomized into two groups namely, Group A-p...

  5. Artificial intelligence

    CERN Document Server

    Hunt, Earl B

    1975-01-01

    Artificial Intelligence provides information pertinent to the fundamental aspects of artificial intelligence. This book presents the basic mathematical and computational approaches to problems in the artificial intelligence field.Organized into four parts encompassing 16 chapters, this book begins with an overview of the various fields of artificial intelligence. This text then attempts to connect artificial intelligence problems to some of the notions of computability and abstract computing devices. Other chapters consider the general notion of computability, with focus on the interaction bet

  6. Application Of Nuclear Techniques In Environmental Studies And Pollution Control

    International Nuclear Information System (INIS)

    Environmental pollution has become a world wide concern. One of the main sources of such pollution is sewage wastewater and sludge. Their utilization without proper treatment can pollute the ecosystem (plant, soil, surface and ground water). Sewage wastewater and sludge contains several pollutants such as: pathogens, toxic organic compounds, heavy metals, high level of BOD and COD, seed weed. The reuse of sewage water and sludge in agriculture can lead to the transfer of some of these pollutants into the food chain causing health hazard. In addition, most of these contaminants are not biodegradable, becoming dangerous to plant and human health. Nuclear techniques has recently been used to control environmental pollution. Ionizing radiation provide a fast and reliable means of sewage water and sludge treatment than the conventional methods. Gamma radiation ( 60Co) and electron beam (accelerator) has been successfully used for alleviation of environmental pollution. Such alleviation includes: disinfection of harmful pathogens, degradation of toxic organic pollutants, destruction of seed weed and reduction of soluble heavy metals, odor and BOD and COD. The use of radioactive and stable isotopes are a useful tools to investigate the contribution of sludge nutrients to plant nutrition. Nitrogen, using 15N-ammonium sulfate, uptake and translocation by plant from soil amended with sewage sludge was studied under field condition. The contribution of sludge to phosphorus nutrition of plants was quantified using 32p as tracer. In both cases the principal of isotopic dilution technique was applied. The information generated from these experiments could help preserve the environment. It could help optimize the application rate of sludge to meet plant requirements while avoiding the accumulation of N and P in the soil or leaching to the aquifer. Isotope exchange kinetic technique is used to evaluate nutrients availability from sludge. Neutron moisture meter is used to measure

  7. Active control technique of fractional-order chaotic complex systems

    Science.gov (United States)

    Mahmoud, Gamal M.; Ahmed, Mansour E.; Abed-Elhameed, Tarek M.

    2016-06-01

    Several kinds of synchronization of fractional-order chaotic complex systems are challenging research topics of current interest since they appear in many applications in applied sciences. Our main goal in this paper is to introduce the definition of modified projective combination-combination synchronization (MPCCS) of some fractional-order chaotic complex systems. We show that our systems are chaotic by calculating their Lyapunov exponents. The fractional Lyapunov dimension of the chaotic solutions of these systems is computed. A scheme is introduced to calculate MPCCS of four different (or identical) chaotic complex systems using the active control technique. Special cases of this type, which are projective and anti C-C synchronization, are discussed. Some figures are plotted to show that MPCCS is achieved and its errors approach zero.

  8. Nondestructive techniques for the control of conditioned radioactive wastes

    International Nuclear Information System (INIS)

    The final product of the radwaste conditioning process must satisfy certain requirments and physico-chemical properties in order to assure its safe long-term behaviour. Of course, the foreseen quality assurance and quality control should be conducted by means of non-destructive techniques. This work presents an over-view of various applicable non-destructive methods of analysis, showing their fields of investigation in testing waste packages, together with some arising practical problems. The most promising methods, such as eddy current testing, ultrasonic testing, γ-scanning, γ-spectroscopy, neutron counting and computerized tomography, are treated more deeply and some applications are presented. Particular attention is devoted to the development of a device based on computerized tomography; its essential components are reported and some design problems are also discussed

  9. Una Técnica de Inteligencia Artificial para el Ajuste de uno de los Elementos que Definen una B-Spline Racional No Uniforme (NURBS A Technique of Artificial Intelligence to Fit one of the Elements that Define a Non-Uniform Rational B-Spline (NURBS

    Directory of Open Access Journals (Sweden)

    Sandra P Mateus

    2010-01-01

    Full Text Available Dentro de las técnicas existentes de Inteligencia Artificial, se escogieron y adaptaron dos Redes Neuronales Artificiales (RNA para realizar el ajuste de uno de los elementos que definen una B-Spline Racional No Uniforme (NURBS y con ello obtener un modelado adecuado de la NURBS. Los elementos escogidos fueron los puntos de control. Las RNA utilizadas son las de Función de Base Radial y las de Kohonen o Mapas Auto-organizativos. Con base en el análisis de resultados y la caracterización de las RNA, la Función de Base Radial tuvo un desempeño más adecuado y óptimo para un número elevado de datos, lo cual es una desventaja de los Mapas Auto-organizativos. En este modelo se tiene que realizar procesos extras para determinar la neurona ganadora y realizar el reajuste de los pesos.In the existing techniques of Artificial Intelligence, two Artificial Neural Networks (ANN were selected and adapted to fit one of the elements that define a Non-Uniform Rational B-Spline (NURBS and thus obtaining an appropriate modeling of the NURBS. The selected elements were the checkpoints. The ANN used were the Radial Basis Function and the Kohonen model or Self-Organizing Maps. Based on the analysis of the results and characterization of the ANN the Radial Basis Function had a more appropriate and optimum performance for a large number of data, which is a disadvantage of the Self-Organizing Maps. In this model, additional processes must be done to determine the winning neuron and the weights must be refitted.

  10. Intelligent PID controller based on ant system algorithm and fuzzy inference and its application to bionic artificial leg

    Institute of Scientific and Technical Information of China (English)

    谭冠政; 曾庆冬; 李文斌

    2004-01-01

    A designing method of intelligent proportional-integral-derivative(PID) controllers was proposed based on the ant system algorithm and fuzzy inference. This kind of controller is called Fuzzy-ant system PID controller. It consists of an off-line part and an on-line part. In the off-line part, for a given control system with a PID controller,by taking the overshoot, setting time and steady-state error of the system unit step response as the performance indexes and by using the ant system algorithm, a group of optimal PID parameters K*p , Ti* and T*d can be obtained, which are used as the initial values for the on-line tuning of PID parameters. In the on-line part, based on Kp* , Ti*and Td* and according to the current system error e and its time derivative, a specific program is written, which is used to optimize and adjust the PID parameters on-line through a fuzzy inference mechanism to ensure that the system response has optimal transient and steady-state performance. This kind of intelligent PID controller can be used to control the motor of the intelligent bionic artificial leg designed by the authors. The result of computer simulation experiment shows that the controller has less overshoot and shorter setting time.

  11. Advanced terahertz techniques for quality control and counterfeit detection

    Science.gov (United States)

    Ahi, Kiarash; Anwar, Mehdi

    2016-04-01

    This paper reports our invented methods for detection of counterfeit electronic. These versatile techniques are also handy in quality control applications. Terahertz pulsed laser systems are capable of giving the material characteristics and thus make it possible to distinguish between the materials used in authentic components and their counterfeit clones. Components with material defects can also be distinguished in section in this manner. In this work different refractive indices and absorption coefficients were observed for counterfeit components compared to their authentic counterparts. Existence of unexpected ingredient materials was detected in counterfeit components by Fourier Transform analysis of the transmitted terahertz pulse. Thicknesses of different layers are obtainable by analyzing the reflected terahertz pulse. Existence of unexpected layers is also detectable in this manner. Recycled, sanded and blacktopped counterfeit electronic components were detected as a result of these analyses. Counterfeit ICs with die dislocations were detected by depicting the terahertz raster scanning data in a coordinate plane which gives terahertz images. In the same manner, raster scanning of the reflected pulse gives terahertz images of the surfaces of the components which were used to investigate contaminant materials and sanded points on the surfaces. The results of the later technique, reveals the recycled counterfeit components.

  12. Comparison of Suspended Branch and Direct Infestation Techniques for Artificially Infesting Hemlock Seedlings with the Hemlock Woolly Adelgid for Resistance Screening

    Directory of Open Access Journals (Sweden)

    Zaidee L. Powers

    2015-06-01

    Full Text Available The hemlock woolly adelgid (Adelges tsugae Annand is an invasive forest pest in eastern North America that has caused significant decline and mortality in populations of eastern hemlock (Tsuga canadensis (L. Carr. and Carolina hemlock (T. caroliniana Engelm.. The breeding of adelgid-resistant genotypes for reforestation activities is still in the early development phases, and most resistance screening programs have depended on labor-intensive direct artificial infestation techniques for introducing adelgids to target seedlings. We investigated the timing and effectiveness of a potentially less labor-intense suspended branch infestation technique compared to two levels of a direct infestation method. Results indicated that peak crawler emergence from adelgid infested hemlock branches occurred within a 10 to 14 day period and that crawler emergence was higher from non-hydrated compared to hydrated branches. Greater infestation pressure was achieved when using progrediens crawlers compared to sistens crawlers. In 2013, when the infestation attempts were most successful, the suspended branch technique induced the same or higher adelgid densities on target seedlings as the direct infestation techniques. Assuming an initial investment in infrastructure, the suspended branch approach could be a more time and cost effective method for inducing adelgid infestations for resistance screening of large numbers of candidate trees.

  13. Operant Conditioning: A Minimal Components Requirement in Artificial Spiking Neurons Designed for Bio-Inspired Robot’s Controller

    Directory of Open Access Journals (Sweden)

    André eCyr

    2014-07-01

    Full Text Available We demonstrate the operant conditioning (OC learning process within a basic bio-inspired robot controller paradigm, using an artificial spiking neural network (ASNN with minimal component count as artificial brain. In biological agents, OC results in behavioral changes that are learned from the consequences of previous actions, using progressive prediction adjustment triggered by reinforcers. In a robotics context, virtual and physical robots may benefit from a similar learning skill when facing unknown environments with no supervision. In this work, we demonstrate that a simple ASNN can efficiently realise many OC scenarios. The elementary learning kernel that we describe relies on a few critical neurons, synaptic links and the integration of habituation and spike-timing dependent plasticity (STDP as learning rules. Using four tasks of incremental complexity, our experimental results show that such minimal neural component set may be sufficient to implement many OC procedures. Hence, with the described bio-inspired module, OC can be implemented in a wide range of robot controllers, including those with limited computational resources.

  14. Microscope-controlled glass bead blasting: a new technique

    Directory of Open Access Journals (Sweden)

    Peter Kotschy

    2011-01-01

    Full Text Available Peter Kotschy1, Sascha Virnik2, Doris Christ3, Alexander Gaggl21Private Practice, Vienna, Austria; 2Department of Oral and Maxillofacial Surgery, Central Hospital, Klagenfurt, Austria; 3Klagenfurt, AustriaObjective: The aim of periodontal therapy is the healing of periodontal inflammation; the protection of the attachment and the alveolar bone; and the regeneration of the periodontal structures. In the therapy of periodontitis, supra- and subgingival scaling and root planing plays a main role. The procedure described combines perfect root cleaning without scaling and root planing and minimal invasive periodontal surgery without a scalpel.Material and methods: Glass beads of 90 µm were used with the kinetic preparation unit PrepStart® under a pressure of 0.5–5 bar. This technique was practised only under visual control using the OPMI® PRO Magis microscope. Seven examinations were carried out at baseline after 3, 6, 12, 18, 24, and 36 months.Results: Time shows a statistically significant influence on all of the considered target variables (P < 0.0001 for all. As the according estimate is negative, probing depth decreases over time. The major decrease seems to be during the first 6 months. Considering probing depth, plaque on the main effect root shows significant influence (again, P < 0.0001 for all. Observations with high probing depth at the beginning were faster than those with low probing depth. The same characteristic appears by attachment level. Patients with more loss of attachment show more gain.Conclusions: Using microscope-controlled glass bead blasting results in a perfectly clean root surface using visual control (magnification 20×. Microscope-controlled glass bead blasting is therefore a good alternative to periodontal surgery.Keywords: periodontal therapy, microscope, periodontitis

  15. Heat transfer optimization of two phase modeling of nanofluid in a sinusoidal wavy channel using Artificial Bee Colony technique

    Directory of Open Access Journals (Sweden)

    P. Valinataj-Bahnemiri

    2015-12-01

    Full Text Available The present study represents the heat transfer optimization of two-dimensional incompressible laminar flow of Al2O3-water nanofluids in a duct with uniform temperature corrugated walls. A two phase model is applied to investigate different governing parameters, namely: Reynolds number (100 ≤ Re ≤ 1000, nonofluids volume fraction (0% ≤ ϕ ≤ 5% and amplitude of the wavy wall (0 ≤ α ≤ 0.04 m. For optimization process, a recent spot-lighted method, called Artificial Bee Colony (ABC algorithm, is applied, and the results are shown to be in a good accuracy in comparison with another well-known heuristic method, i.e. particle swarm optimization (PSO. The results indicate that the effect of utilizing nanoparticles and increasing Reynolds number is more intensified on growing the average Nusselt number than variations of the amplitude of the wavy wall. To prevent the worst possible heat transfer, the specific amplitude which leads to a minimum average Nusselt number is detected. The effect of using nanoparticles on thermal-hydraulic performance factor (j/f is presented which considers both heat transfer and hydrodynamics aspects. The results showed that volume fraction has a direct and the wavy wall's amplitude has a converse effect on the thermal-hydraulic performance factor. Furthermore, an optimum value for Reynolds number is found to maximize the thermal-hydraulic performance factor.

  16. Prediction of Heavy Metal Removal by Different Liner Materials from Landfill Leachate: Modeling of Experimental Results Using Artificial Intelligence Technique

    Science.gov (United States)

    Turan, Nurdan Gamze; Gümüşel, Emine Beril; Ozgonenel, Okan

    2013-01-01

    An intensive study has been made to see the performance of the different liner materials with bentonite on the removal efficiency of Cu(II) and Zn(II) from industrial leachate. An artificial neural network (ANN) was used to display the significant levels of the analyzed liner materials on the removal efficiency. The statistical analysis proves that the effect of natural zeolite was significant by a cubic spline model with a 99.93% removal efficiency. Optimization of liner materials was achieved by minimizing bentonite mixtures, which were costly, and maximizing Cu(II) and Zn(II) removal efficiency. The removal efficiencies were calculated as 45.07% and 48.19% for Cu(II) and Zn(II), respectively, when only bentonite was used as liner material. However, 60% of natural zeolite with 40% of bentonite combination was found to be the best for Cu(II) removal (95%), and 80% of vermiculite and pumice with 20% of bentonite combination was found to be the best for Zn(II) removal (61.24% and 65.09%). Similarly, 60% of natural zeolite with 40% of bentonite combination was found to be the best for Zn(II) removal (89.19%), and 80% of vermiculite and pumice with 20% of bentonite combination was found to be the best for Zn(II) removal (82.76% and 74.89%). PMID:23844384

  17. The virtual microphone technique in active sound field control systems

    Science.gov (United States)

    Lampropoulos, Iraklis E.; Shimizu, Yasushi

    2003-04-01

    Active Sound Field Control (AFC) has been proven very useful in reverberation enhancement applications in large rooms. However, feedback control is required in order to eliminate peaks in the frequency response of the system. The present research closely follows the studies of Shimizu in AFC, in which smoothing of the rooms transfer function is achieved by averaging the impulse responses of multiple microphones. ``The virtual or rotating microphone technique'' reduces the number of microphones in the aforementioned AFC technology, while still achieving the same acoustical effects in the room. After the impulse responses at previously specified pairs of microphone positions are measured, the ratio of transfer functions for every pair is calculated, thus yielding a constant K. Next, microphones are removed and their impulse responses are reproduced by processing the incoming signal of each pair through a convolver, where the computed K constants have been previously stored. Band limiting, windowing and time variance effects are critical factors, in order to reduce incoherence effects and yield reliable approximations of inverse filters and consequently calculations of K. The project is implemented in a church lacking low frequency reverberation for music and makes use of 2 physical and 2 virtual microphones.

  18. Using an Artificial Neural Bypass to Restore Cortical Control of Rhythmic Movements in a Human with Quadriplegia

    Science.gov (United States)

    Sharma, Gaurav; Friedenberg, David A.; Annetta, Nicholas; Glenn, Bradley; Bockbrader, Marcie; Majstorovic, Connor; Domas, Stephanie; Mysiw, W. Jerry; Rezai, Ali; Bouton, Chad

    2016-09-01

    Neuroprosthetic technology has been used to restore cortical control of discrete (non-rhythmic) hand movements in a paralyzed person. However, cortical control of rhythmic movements which originate in the brain but are coordinated by Central Pattern Generator (CPG) neural networks in the spinal cord has not been demonstrated previously. Here we show a demonstration of an artificial neural bypass technology that decodes cortical activity and emulates spinal cord CPG function allowing volitional rhythmic hand movement. The technology uses a combination of signals recorded from the brain, machine-learning algorithms to decode the signals, a numerical model of CPG network, and a neuromuscular electrical stimulation system to evoke rhythmic movements. Using the neural bypass, a quadriplegic participant was able to initiate, sustain, and switch between rhythmic and discrete finger movements, using his thoughts alone. These results have implications in advancing neuroprosthetic technology to restore complex movements in people living with paralysis.

  19. Modern control techniques in active flutter suppression using a control moment gyro

    Science.gov (United States)

    Buchek, P. M.

    1974-01-01

    Development of organized synthesis techniques, using concepts of modern control theory was studied for the design of active flutter suppression systems for two and three-dimensional lifting surfaces, utilizing a control moment gyro (CMG) to generate the required control torques. Incompressible flow theory is assumed, with the unsteady aerodynamic forces and moments for arbitrary airfoil motion obtained by using the convolution integral based on Wagner's indicial lift function. Linear optimal control theory is applied to find particular optimal sets of gain values which minimize a quadratic performance function. The closed loop system's response to impulsive gust disturbances and the resulting control power requirements are investigated, and the system eigenvalues necessary to minimize the maximum value of control power are determined.

  20. [Population dynamics and control techniques of aphids on honeysuckle].

    Science.gov (United States)

    Sun, Ying; Xue, Ming; Zhang, Xiao; Zhao, Hai-Peng; Li, Zhao-Xia

    2013-11-01

    The objective of this study is to define the population dynamics of Semiaphis heraclei in the main-producing district of Lonicera japonica in Shandong, and screen for highly efficient, safety control technique. Through fixed field investigation, we tested the toxicity of eight kinds of insecticides by using dipping methods, and carried out the field experiment. The results showed that the aphids' emergence peak appeared in May. The aphids on the Sijihua variety of L. japonica was more susceptible and the peak was also seven days earlier than Damao variety of L. japonica. The aphid populations on Sijihua were 1 fold than those on the Daomao in happened peak. Comparing the eight kinds of insecticides, the LC50 of lambda-cyhaothrin, abamectin, imidacloprid and pyrethrin to wingless aphids were 1.494, 1.690, 2.840, 2.861 mg x L(-1), respectively, whose toxicity were higher, the toxicity of matrine, pymetrozine and azadirachtin were also high. The field efficacy trials indicated that during the period of aphids occurred, 25% imidacloprid wettable powder, 1.8% abamectin missible oil, 2.5% lambda-cyhaothrin missible oil, 25% pymetrozine wettable powder, 5% pyrethrin missible oil, 1% matrine water aqua were sprayed at concentrations of 20,000, 2,000, 2,500, 5,000, 500 and 50 times, respectively,the control effect achieved 91.69%, 98.90%, 96.18%, 95.06%, 99.24%, 90.10%, respectively, after 5 days. During the growing period of L. japonica in spring, application of thiamethoxam, thiacloprid, pymetrozine and imidacloprid, all of the control effect against aphids achieved above 98.88% after 50 days. The result indicated that May was the S. heraclei Takahashi's emergence peak in Pingyi, Shandong. The efficient safety and environmentally friendly insecticides by spraying and systemic insecticide of pymetrozine and imidacloprid by root application were all efficient controlled aphids. These insecticides were long for controlling S. heraclei Takahashi and worthy of being widely

  1. Computer automation and artificial intelligence

    International Nuclear Information System (INIS)

    Rapid advances in computing, resulting from micro chip revolution has increased its application manifold particularly for computer automation. Yet the level of automation available, has limited its application to more complex and dynamic systems which require an intelligent computer control. In this paper a review of Artificial intelligence techniques used to augment automation is presented. The current sequential processing approach usually adopted in artificial intelligence has succeeded in emulating the symbolic processing part of intelligence, but the processing power required to get more elusive aspects of intelligence leads towards parallel processing. An overview of parallel processing with emphasis on transputer is also provided. A Fuzzy knowledge based controller for amination drug delivery in muscle relaxant anesthesia on transputer is described. 4 figs. (author)

  2. Improvement of Power System Stability using Artificial Neural Network based HVDC Controls

    OpenAIRE

    Nagu Bhookya

    2013-01-01

    In this paper, investigation is carried out for the improvement of power system stability by utilizing auxiliary controls for controlling HVDC power flow. The current controller model and the line dynamics are considered in the stability analysis. Transient stability analysis is done on a multi-machine system, where, a neural network controller is developed to improve the stability of the power system and to improve the response time of the controller to the changing conditions in power syste...

  3. Radioimmunoassay and related techniques to improve artificial insemination programmes for cattle reared under tropical and sub-tropical conditions. Proceedings of a final research co-ordination meeting

    International Nuclear Information System (INIS)

    Artificial insemination (AI) is widely used for improvement of cattle production in developed countries. Its use in developing countries is less widespread and the results obtained are far from satisfactory. Under tropical small-farm conditions, a number of socio-economic, organizational, biological and technical factors make the service more difficult to provide and also less efficient. If the major constraints can be identified and overcome, this technology would become more widely adopted and contribute to an increased production of milk and meat, leading to better food security and poverty alleviation. The Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture therefore convened a consultants meeting in May 1994 to advise on the applicability of radioimmunoassay (RIA) for measuring progesterone in milk of dairy cattle to identify the major causes of conception failure and reproductive wastage when AI is used under the conditions prevailing in developing countries. The consultants recommended the initiation of a co-ordinated research project (CRP) on this topic, and developed a comprehensive technical document including the sampling protocol and the range of information that needs to be recorded in order to obtain conclusive results. A five year CRP on the ''Use of RIA and Related Techniques to Identify Ways of Improving Artificial Insemination Programmes for Cattle Reared Under Tropical and Sub-Tropical Conditions'' was initiated in early 1995. The CRP resulted in the development and standardization of methodologies and protocols, including the computer software program termed AIDA (Artificial Insemination Database Application), to determine current status and identify constraints. These methodologies and protocols are now being applied on a wider scale in Member States through regional TC projects in Asia and Africa and country TC projects in Latin America. Contributing to the wider application of progesterone RIA for field level problem solving

  4. Speed Control of a DC Motor for the Orientation of a Heliostat in a Solar Tower Power Plant using Artificial Intelligence Systems (FLC and NC

    Directory of Open Access Journals (Sweden)

    Abdelfettah Zeghoudi

    2015-06-01

    Full Text Available Recent research in the field of motor controls is becoming more interesting especially with the developments of new control methods. This study shows a comparative study between two artificial intelligence methods namely neural networks and fuzzy logic for the speed control of a DC motor for the orientation of a heliostat in a solar tower power plant. The speed controller of DC motor is performed using two Fuzzy Logic Configuration (FLC1 and FLC2 and neural controller in MATLAB environment. The simulation results are used to make sure the real possibility of using artificial intelligence systems to identify and control this type of installation. The performance of the Fuzzy Logic Controller and Neural control are compared using different errors metrics. The results show that Fuzzy logic method is more efficient compared with neural controller method.

  5. 工程降水中人工回灌综合技术%Integrated technique of artificial recharge in engineering dewatering

    Institute of Scientific and Technical Information of China (English)

    冶雪艳; 耿冬青; 杜新强; 王福刚; 曹东军

    2011-01-01

    建筑工程降水往往伴生水资源浪费和地面变形等环境问题,人工回灌是解决这些问题的有效手段之一.影响工程降水中人工回灌的条件有回灌场地水文地质条件、回灌水源水质和水量及回灌方案的经济可行性等因素.就工程降水中出现的问题,提出资源补充型回灌和应力稳定型回灌方法,并给出了适用条件;根据工程降水水质特点及现有的地下水人工回灌相关水质标准,提出工程降水回灌水质的控制指标主要为悬浮物、浊度、一般污染性指标、微生物指标及重金属等.针对目前人工回灌在工程中存在的可回灌性低的问题,进行了影响入渗速率因素研究,为今后开展促渗关键技术提供理论支持.%The waste of water resources, ground deformation and other environmental issues are often associated with construction industry dewatering. Artificial recharge is an effective mean to solve these problems. Influential factors of artificial recharge in engineering dewatering are hydrogeological conditions of recharge site, water quality and quantity of recharge and the economic feasibility of recharge program. For the problems in the engineering dewatering, the authors propose two kinds of recharge methods including water resources supplement recharge and stress stable recharge, and propose the applicable conditions. According to the features of construction dewatering and the artificial recharge standards of native grounduater, it was suggested that the water quality control indicators of engineering dewatering are suspended solids, turbidity, general pollution indexes, microbial indexes and heavy metals. Aiming at the problem of low recharge in artificial recharge of construction, the factors that affect the infiltration rate is studied to give theoretical support of the key technology of promotion infiltration in future.

  6. Improvement of Power System Stability using Artificial Neural Network based HVDC Controls

    Directory of Open Access Journals (Sweden)

    Nagu Bhookya

    2013-06-01

    Full Text Available In this paper, investigation is carried out for the improvement of power system stability by utilizing auxiliary controls for controlling HVDC power flow. The current controller model and the line dynamics are considered in the stability analysis. Transient stability analysis is done on a multi-machine system, where, a neural network controller is developed to improve the stability of the power system and to improve the response time of the controller to the changing conditions in power system. The results show the application of the neural network controller in AC-DC power systems.

  7. Estimation of global solar radiation using an artificial neural network based on an interpolation technique in southeast China

    Science.gov (United States)

    Zou, Ling; Wang, Lunche; Lin, Aiwen; Zhu, Hongji; Peng, Yuling; Zhao, Zhenzhen

    2016-08-01

    Solar radiation plays important roles in energy application, vegetation growth and climate change. Empirical relations and machine-learning methods have been widely used to estimate global solar radiation (GSR) in recent years. An artificial neural network (ANN) based on spatial interpolation is developed to estimate GSR in southeast China. The improved Bristow-Campbell (IBC) model and the improved Ångström-Prescott (IA-P) model are compared with the ANN model to explore the best model in solar radiation modeling. Daily meteorological parameters, such as sunshine duration hours, mean temperature, maximum temperature, minimum temperature, relative humidity, precipitation, air pressure, water vapor pressure, and wind speed, along with station-measured GSR and a daily surface GSR dataset over China obtained from the Data Assimilation and Modeling Center for Tibetan Multi-spheres (DAM), are used to predict GSR and to validate the models in this work. The ANN model with the network of 9-17-1 provides better accuracy than the two improved empirical models in GSR estimation. The root-mean-square error (RMSE), mean bias error (MBE), and determination coefficient (R2) are 2.65 MJ m-2, -0.94 MJ m-2, and 0.68 in the IA-P model; 2.19 MJ m-2, 1.11 MJ m-2, and 0.83 in the IBC model; 1.34 MJ m-2, -0.11 MJ m-2, and 0.91 in the ANN model, respectively. The regional monthly mean GSR in the measured dataset, DAM dataset, and ANN model is analyzed. The RMSE (RMSE %) is 1.07 MJ m-2 (8.91%) and the MBE (MBE %) is -0.62 MJ m-2 (-5.21%) between the measured and ANN-estimated GSR. The statistical errors of RMSE (RMSE %) are 0.91 MJ m-2 (7.28%) and those of MBE (MBE %) are -0.15 MJ m-2 (-1.20%) between DAM and ANN-modeled GSR. The correlation coefficients and R2 are larger than 0.95. The regional mean GSR is 12.58 MJ m-2. The lowest GSR is observed in the northwest area, and it increases from northwest to southeast. The annual mean GSR decreases by 0.02 MJ m-2 decade-1 over the entire

  8. Artificial Limbs

    Science.gov (United States)

    ... you are missing an arm or leg, an artificial limb can sometimes replace it. The device, which ... activities such as walking, eating, or dressing. Some artificial limbs let you function nearly as well as ...

  9. An Artificial Neural Network Compensated Output Feedback Power-Level Control for Modular High Temperature Gas-Cooled Reactors

    Directory of Open Access Journals (Sweden)

    Zhe Dong

    2014-02-01

    Full Text Available Small modular reactors (SMRs could be beneficial in providing electricity power safely and also be viable for applications such as seawater desalination and heat production. Due to its inherent safety features, the modular high temperature gas-cooled reactor (MHTGR has been seen as one of the best candidates for building SMR-based nuclear power plants. Since the MHTGR dynamics display high nonlinearity and parameter uncertainty, it is necessary to develop a nonlinear adaptive power-level control law which is not only beneficial to the safe, stable, efficient and autonomous operation of the MHTGR, but also easy to implement practically. In this paper, based on the concept of shifted-ectropy and the physically-based control design approach, it is proved theoretically that the simple proportional-differential (PD output-feedback power-level control can provide asymptotic closed-loop stability. Then, based on the strong approximation capability of the multi-layer perceptron (MLP artificial neural network (ANN, a compensator is established to suppress the negative influence caused by system parameter uncertainty. It is also proved that the MLP-compensated PD power-level control law constituted by an experientially-tuned PD regulator and this MLP-based compensator can guarantee bounded closed-loop stability. Numerical simulation results not only verify the theoretical results, but also illustrate the high performance of this MLP-compensated PD power-level controller in suppressing the oscillation of process variables caused by system parameter uncertainty.

  10. Start of reproduction and allozyme heterozygosity in Pinus sibirica under different techniques of artificial forest stand establishment

    Directory of Open Access Journals (Sweden)

    S.N. Velisevich

    2013-12-01

    Full Text Available Siberian stone pine (Pinus sibirica Du Tour is one of the main forest-forming tree species in boreal forests of Eurasia. Large edibleseeds of this species have an important resource value because of their high nutritious properties. Development of approaches toestablishment of early cone producing Siberian stone pine stands including utilization of corresponding genetic background is one of the priorities of forest resource management. The goal of our study was to evaluate the effect of stand density on the differentiation of trees bythe age of first reproduction and the relationship of allozyme heterozygosity and morphological traits variability in Siberian stone pine.Morphological and allozyme variability in artificial Pinus sibirica stands with high and low density was investigated. In the high-densitystand the distance between trees was 0.7 and 3 meters (4080 trees per ha while in the lowdensity stand it was 8 and 8 meters (144 treesper ha. Age of formation of first male and female cones was evaluated by retrospective method based on analysis of tracks of cones ona shoot bark. Tree height, diameter and number of male, female and vegetative shoots in a crown of model trees were measured.Genotypes of the trees were determined by 29 isozyme loci coding for 16 enzymes (ADH, FDH, FEST, GDH, GOT, IDH, LAP, MDH, MNR, PEPCA, 6-PGD, PGI, PGM, SDH, SKDH, SOD. In the low-density stand, the portion of generative trees was higher and differentiation of trees by age of reproduction starting was lower in spite of the smaller age of trees as compared to the high-density stand. Inboth samples, the age of formation of first generative organs was related negatively with stem height, stem diameter and number offemale shoots. In the high-density stand, positive relation of age of first reproduction with total number of shoots and number ofmale shoots was found. In both samples nonreproductive trees were less heterozygous at

  11. Speed Control of Induction Motor Using New Sliding Mode Control Technique

    Directory of Open Access Journals (Sweden)

    Aamir Hashim Obeid Ahmed

    2010-06-01

    Full Text Available Induction Motors have been used as the workhorse in the industry for a long time due to its easy build, high robustness, and generally satisfactory efficiency. However, they are significantly more difficult to control than DC motors. One of the problems which might cause unsuccessful attempts for designing a proper controller would be the time varying nature of parameters and variables which might be changed while working with the motion systems. One of the best suggested solutions to solve this problem would be the use of Sliding Mode Control (SMC. This paper presents the design of a new controller for a vector control induction motor drive that employs an outer loop speed controller using SMC. Several tests were performed to evaluate the performance of the new controller method, and two other sliding mode controller techniques. From the comparative simulation results, one can conclude that the new controller law provides high performance dynamic characteristics and is robust with regard to plant parameter variations.

  12. Verification of the helioseismology travel-time measurement technique and the inversion procedure for sound speed using artificial data

    International Nuclear Information System (INIS)

    We performed three-dimensional numerical simulations of the solar surface acoustic wave field for the quiet Sun and for three models with different localized sound-speed perturbations in the interior with deep, shallow, and two-layer structures. We used the simulated data generated by two solar acoustics codes that employ the same standard solar model as a background model, but utilize different integration techniques and different models of stochastic wave excitation. Acoustic travel times were measured using a time-distance helioseismology technique, and compared with predictions from ray theory frequently used for helioseismic travel-time inversions. It is found that the measured travel-time shifts agree well with the helioseismic theory for sound-speed perturbations, and for the measurement procedure with and without phase-speed filtering of the oscillation signals. This testing verifies the whole measuring-filtering-inversion procedure for static sound-speed anomalies with small amplitude inside the Sun outside regions of strong magnetic field. It is shown that the phase-speed filtering, frequently used to extract specific wave packets and improve the signal-to-noise ratio, does not introduce significant systematic errors. Results of the sound-speed inversion procedure show good agreement with the perturbation models in all cases. Due to its smoothing nature, the inversion procedure may overestimate sound-speed variations in regions with sharp gradients of the sound-speed profile.

  13. Verification of the Travel Time Measurement Technique and the Helioseismic Inversion Procedure for Sound Speed Using Artificial Data

    CERN Document Server

    Parchevsky, Konstantin V; Hartlep, Thomas; Kosovichev, Alexander G

    2012-01-01

    We performed 3D numerical simulations of the solar surface wave field for the quiet Sun and for three models with different localized sound-speed variations in the interior with: (i) deep, (ii) shallow, and (iii) two-layer structures. We used simulated data generated by two different codes which use the same standard solar model as a background model, but utilize two different integration techniques and use different models of stochastic wave excitation. Acoustic travel times were measured from all data sets using the time-distance helioseismology technique and compared with the ray theory predictions, frequently used for helioseismic travel-time inversions. It is found that the measured travel-time shifts agree well with the ray theory in both cases with and without phase-speed filtering for the shallow and deep perturbations. This testing verifies the whole measuring-filtering-inversion procedure for sound-speed anomalies inside the Sun. It is shown, that the phase-speed filtering, frequently used to improv...

  14. Microsoft Kinect-Based Artificial Perception System for Control of Functional Electrical Stimulation Assisted Grasping

    OpenAIRE

    Matija Štrbac; Slobodan Kočović; Marko Marković; Popović, Dejan B.

    2014-01-01

    We present a computer vision algorithm that incorporates a heuristic model which mimics a biological control system for the estimation of control signals used in functional electrical stimulation (FES) assisted grasping. The developed processing software acquires the data from Microsoft Kinect camera and implements real-time hand tracking and object analysis. This information can be used to identify temporal synchrony and spatial synergies modalities for FES control. Therefore, the algorithm ...

  15. Giant Controllable Magnetization Changes Induced by Structural Phase Transitions in a Metamagnetic Artificial Multiferroic

    OpenAIRE

    Bennett, S. P.; A. T. Wong; Glavic, A.; Herklotz, A.; Urban, C; Valmianski, I.; Biegalski, M. D.; Christen, H. M.; Ward, T. Z.; Lauter, V.

    2016-01-01

    The realization of a controllable metamagnetic transition from AFM to FM ordering would open the door to a plethora of new spintronics based devices that, rather than reorienting spins in a ferromagnet, harness direct control of a materials intrinsic magnetic ordering. In this study FeRh films with drastically reduced transition temperatures and a large magneto-thermal hysteresis were produced for magnetocaloric and spintronics applications. Remarkably, giant controllable magnetization change...

  16. A Real-Time and Closed-Loop Control Algorithm for Cascaded Multilevel Inverter Based on Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Libing Wang

    2014-01-01

    Full Text Available In order to control the cascaded H-bridges (CHB converter with staircase modulation strategy in a real-time manner, a real-time and closed-loop control algorithm based on artificial neural network (ANN for three-phase CHB converter is proposed in this paper. It costs little computation time and memory. It has two steps. In the first step, hierarchical particle swarm optimizer with time-varying acceleration coefficient (HPSO-TVAC algorithm is employed to minimize the total harmonic distortion (THD and generate the optimal switching angles offline. In the second step, part of optimal switching angles are used to train an ANN and the well-designed ANN can generate optimal switching angles in a real-time manner. Compared with previous real-time algorithm, the proposed algorithm is suitable for a wider range of modulation index and results in a smaller THD and a lower calculation time. Furthermore, the well-designed ANN is embedded into a closed-loop control algorithm for CHB converter with variable direct voltage (DC sources. Simulation results demonstrate that the proposed closed-loop control algorithm is able to quickly stabilize load voltage and minimize the line current’s THD (<5% when subjecting the DC sources disturbance or load disturbance. In real design stage, a switching angle pulse generation scheme is proposed and experiment results verify its correctness.

  17. Tight glycemic control using an artificial endocrine pancreas may play an important role in preventing infection after pancreatic resection

    Institute of Scientific and Technical Information of China (English)

    Kazuhiro Hanazaki

    2012-01-01

    It is well known that perioperative hyperglycemia is the main cause of infectious complications after surgery.To improve perioperative glycemic control,we wish to highlight and comment on an interesting paper published recently by the Annals of Surgery entitled:"Early postoperative hyperglycemia is associated with postoperative complications after pancreatoduodenectomy (PD)" by Eshuis et al.The authors concluded that early postoperative glucose levels more than 140mg/dL was significantly associated with complications after PD.Since we recommend that perioperative tight glycemic control (TGC) is an effective method to prevent postoperative complications including surgical site infection after distal,proximal,and total pancreatic resection,we support strongly this conclusion drawn in this article.However,if early postoperative glucose control in patients undergoing PD was administrated by conventional method such as sliding scale approach as described in this article,it is difficult to maintain TGC.Therefore,we introduce a novel perioperative glycemic control using an artificial endocrine pancreas against pancreatogenic diabetes after pancreatic resection including PD.

  18. A GIS based hydrogeomorphic approach for identification of site-specific artificial-recharge techniques in the Deccan Volcanic Province

    Indian Academy of Sciences (India)

    M N Ravi Shankar; G Mohan

    2005-10-01

    The Deccan Volcanic Province (DVP)of India,as a whole,faces a severe shortage of water despite receiving a high annual rainfall,this is primarily due to excess runoff and lack of water conservation practices.In this study,an attempt is made to identify zones favourable for the application and adaptation of site-specific artificial-recharge techniques for augmentation of groundwater through a Geographical Information System (GIS)based hydrogeomorphic approach in the Bhatsa and Kalu river basins of Thane district,in western DVP.The criteria adopted for the GIS analysis were based on the hydrogeomorphological characteristics of both basins extracted from the IRS- 1C LISS-III data supported by information on drainage pattern,DEM derived slope,lineament density,drainage density,and groundwater condition.The integrated study helps design a suitable groundwater management plan for a basaltic terrain.

  19. Performance Enhancement of PID Controllers by Modern Optimization Techniques for Speed Control of PMBL DC Motor

    Directory of Open Access Journals (Sweden)

    M. Antony Freeda Rani

    2015-08-01

    Full Text Available Permanent Magnet Brushless DC motor (PMBL DC is used in a large number of industrial and automotive applications because of their high efficiency, compactness and excellent reliability. However to design an efficient PMBL DC motor, it is necessary to provide an effective controller that has to reduce the overshoot, settling and rise time. In this study, an improved PID controller has been designed by optimizing the parameters of PID controller based on two advanced optimization techniques ANFIS and Cuckoo Search optimization for speed control of a PMBL DC motor. The proposed approach has superior features, including easy implementation, stable convergence characteristic and good computational efficiency. The PMBL DC motor is modeled in SIMULINK implementing the algorithms in MATLAB and the performance evaluation has been studied.

  20. Development of a novel optimization tool for electron linacs inspired by artificial intelligence techniques in video games

    Energy Technology Data Exchange (ETDEWEB)

    Meier, E., E-mail: evelyne.meier@synchrotron.org.a [School of Physics, Monash University, Wellington Rd, Clayton VIC 3800 (Australia) and Australian Synchrotron, 800 Blackburn Rd, Clayton VIC 3168 (Australia) and FERMI-Elettra, Sincrotrone Trieste, S.S. 14 km 163.5 in AREA Science Park, 34012 Basovizza, Trieste (Italy); Biedron, S.G., E-mail: biedron@anl.go [Department of Defense Project Office, Argonne National Laboratory, IL 60439 (United States); FERMI-Elettra, Sincrotrone Trieste, S.S. 14 km 163.5 in AREA Science Park, 34012 Basovizza, Trieste (Italy); LeBlanc, G., E-mail: greg.leblanc@synchrotron.org.a [Australian Synchrotron, 800 Blackburn Rd, Clayton VIC 3168 (Australia); Morgan, M.J., E-mail: Michael.J.Morgan@monash.ed [School of Physics, Monash University, Wellington Rd, Clayton VIC 3800 (Australia)

    2011-03-11

    This paper reports the results of an advanced algorithm for the optimization of electron beam parameters in Free Electron Laser (FEL) Linacs. In the novel approach presented in this paper, the system uses state of the art developments in video games to mimic an operator's decisions to perform an optimization task when no prior knowledge, other than constraints on the actuators is available. The system was tested for the simultaneous optimization of the energy spread and the transmission of the Australian Synchrotron Linac. The proposed system successfully increased the transmission of the machine from 90% to 97% and decreased the energy spread of the beam from 1.04% to 0.91%. Results of a control experiment performed at the new FERMI-Elettra FEL is also reported, suggesting the adaptability of the scheme for beam-based control.

  1. Development of a novel optimization tool for electron linacs inspired by artificial intelligence techniques in video games

    International Nuclear Information System (INIS)

    This paper reports the results of an advanced algorithm for the optimization of electron beam parameters in Free Electron Laser (FEL) Linacs. In the novel approach presented in this paper, the system uses state of the art developments in video games to mimic an operator's decisions to perform an optimization task when no prior knowledge, other than constraints on the actuators is available. The system was tested for the simultaneous optimization of the energy spread and the transmission of the Australian Synchrotron Linac. The proposed system successfully increased the transmission of the machine from 90% to 97% and decreased the energy spread of the beam from 1.04% to 0.91%. Results of a control experiment performed at the new FERMI-Elettra FEL is also reported, suggesting the adaptability of the scheme for beam-based control.

  2. Development of a novel optimization tool for electron linacs inspired by artificial intelligence techniques in video games

    Science.gov (United States)

    Meier, E.; Biedron, S. G.; LeBlanc, G.; Morgan, M. J.

    2011-03-01

    This paper reports the results of an advanced algorithm for the optimization of electron beam parameters in Free Electron Laser (FEL) Linacs. In the novel approach presented in this paper, the system uses state of the art developments in video games to mimic an operator's decisions to perform an optimization task when no prior knowledge, other than constraints on the actuators is available. The system was tested for the simultaneous optimization of the energy spread and the transmission of the Australian Synchrotron Linac. The proposed system successfully increased the transmission of the machine from 90% to 97% and decreased the energy spread of the beam from 1.04% to 0.91%. Results of a control experiment performed at the new FERMI@Elettra FEL is also reported, suggesting the adaptability of the scheme for beam-based control.

  3. Knowledge-Based Aircraft Automation: Managers Guide on the use of Artificial Intelligence for Aircraft Automation and Verification and Validation Approach for a Neural-Based Flight Controller

    Science.gov (United States)

    Broderick, Ron

    1997-01-01

    The ultimate goal of this report was to integrate the powerful tools of artificial intelligence into the traditional process of software development. To maintain the US aerospace competitive advantage, traditional aerospace and software engineers need to more easily incorporate the technology of artificial intelligence into the advanced aerospace systems being designed today. The future goal was to transition artificial intelligence from an emerging technology to a standard technology that is considered early in the life cycle process to develop state-of-the-art aircraft automation systems. This report addressed the future goal in two ways. First, it provided a matrix that identified typical aircraft automation applications conducive to various artificial intelligence methods. The purpose of this matrix was to provide top-level guidance to managers contemplating the possible use of artificial intelligence in the development of aircraft automation. Second, the report provided a methodology to formally evaluate neural networks as part of the traditional process of software development. The matrix was developed by organizing the discipline of artificial intelligence into the following six methods: logical, object representation-based, distributed, uncertainty management, temporal and neurocomputing. Next, a study of existing aircraft automation applications that have been conducive to artificial intelligence implementation resulted in the following five categories: pilot-vehicle interface, system status and diagnosis, situation assessment, automatic flight planning, and aircraft flight control. The resulting matrix provided management guidance to understand artificial intelligence as it applied to aircraft automation. The approach taken to develop a methodology to formally evaluate neural networks as part of the software engineering life cycle was to start with the existing software quality assurance standards and to change these standards to include neural network

  4. A Fast Adaptive Artificial Neural Network Controller for Flexible Link Manipulators

    Directory of Open Access Journals (Sweden)

    Amin Riad Maouche

    2016-01-01

    Full Text Available This paper describes a hybrid approach to the problem of controlling flexible link manipulators in the dynamic phase of the trajectory. A flexible beam/arm is an appealing option for civil and military applications, such as space-based robot manipulators. However, flexibility brings with it unwanted oscillations and severe chattering which may even lead to an unstable system. To tackle these challenges, a novel control architecture scheme is presented. First, a neural network controller based on the robot’s dynamic equation of motion is elaborated. Its aim is to produce a fast and stable control of the joint position and velocity and damp the vibration of each arm. Then, an adaptive Cerebellar Model Articulation Controller (CMAC is implemented to balance unmodeled dynamics, enhancing the precision of the control. Efficiency of the new controller obtained is tested on a two-link flexible manipulator. Simulation results on a dynamic trajectory with a sinusoidal form show the effectiveness of the proposed control strategy.

  5. Integrated control of sun shades, daylight and artificial light; Integreret regulering af solafskaermning, dagslys og kunstlys

    Energy Technology Data Exchange (ETDEWEB)

    Johnsen, K.; Christoffersen, J.; Soerensen, Henrik; Jessen, G.

    2011-07-01

    The project established a basis of calculation and a practical basis for optimum choice of solar shading and integrated control strategies for both new buildings and for office, commercial and institutional buildings to be renovated with new calculation models for controlling solar shading integrated in the BSim program. A complete and applicable model for optimum, integrated solar shading control was established, focusing on thermal and visual comfort criteria towards energy consumption for heating, cooling and lighting. A prototype was tested in the daylight laboratory at Danish Building Research Institute-Aalborg University and at University of Southern Denmark. (LN)

  6. Tuning fractional PID controllers for a Steward platform based on frequency domain and artificial intelligence methods

    Science.gov (United States)

    Copot, Cosmin; Zhong, Yu; Ionescu, Clara; Keyser, Robin

    2013-06-01

    In this paper, two methods to tune a fractional-order PI λ D μ controller for a mechatronic system are presented. The first method is based on a genetic algorithm to obtain the parameter values for the fractionalorder PI λ D μ controller by global optimization. The second method used to design the fractional-order PI λ D μ controller relies on an auto-tuning approach by meeting some specifications in the frequency domain. The real-time experiments are conducted using a Steward platform which consists of a table tilted by six servo-motors with a ball on the top of the table. The considered system is a 6 degrees of freedom (d.o.f.) motion platform. The feedback on the position of the ball is obtained from images acquired by a visual sensor mounted above the platform. The fractional-order controllers were implemented and the performances of the steward platform are analyzed.

  7. Towards an Irritable Bowel Syndrome Control System Based on Artificial Neural Networks

    Science.gov (United States)

    Podolski, Ina; Rettberg, Achim

    To solve health problems with medical applications that use complex algorithms is a trend nowadays. It could also be a chance to help patients with critical problems caused from nerve irritations to overcome them and provide a better living situation. In this paper a system for monitoring and controlling the nerves from the intestine is described on a theoretical basis. The presented system could be applied to the irritable bowel syndrome. For control a neural network is used. The advantages for using a neural network for the control of irritable bowel syndrome are the adaptation and learning. These two aspects are important because the syndrome behavior varies from patient to patient and have also concerning the time a lot of variations with respect to each patient. The developed neural network is implemented and can be simulated. Therefore, it can be shown how the network monitor and control the nerves for individual input parameters.

  8. Visual reliance for balance control in older adults persists when visual information is disrupted by artificial feedback delays.

    Directory of Open Access Journals (Sweden)

    Ting Ting Yeh

    Full Text Available Sensory information from our eyes, skin and muscles helps guide and correct balance. Less appreciated, however, is that delays in the transmission of sensory information between our eyes, limbs and central nervous system can exceed several 10s of milliseconds. Investigating how these time-delayed sensory signals influence balance control is central to understanding the postural system. Here, we investigate how delayed visual feedback and cognitive performance influence postural control in healthy young and older adults. The task required that participants position their center of pressure (COP in a fixed target as accurately as possible without visual feedback about their COP location (eyes-open balance, or with artificial time delays imposed on visual COP feedback. On selected trials, the participants also performed a silent arithmetic task (cognitive dual task. We separated COP time series into distinct frequency components using low and high-pass filtering routines. Visual feedback delays affected low frequency postural corrections in young and older adults, with larger increases in postural sway noted for the group of older adults. In comparison, cognitive performance reduced the variability of rapid center of pressure displacements in young adults, but did not alter postural sway in the group of older adults. Our results demonstrate that older adults prioritize vision to control posture. This visual reliance persists even when feedback about the task is delayed by several hundreds of milliseconds.

  9. Artificial Neural Network based control for PV/T panel to track optimum thermal and electrical power

    International Nuclear Information System (INIS)

    Highlights: ► We establish a state model of PV/T panel. ► We study the effect of mass flow rate on PV/T efficiency. ► A real time PV/T control algorithm is proposed. ► A model based optimal thermal and electrical power operation point is tracked. - Abstract: As solar energy is intermittent, many algorithms and electronics have been developed to track the maximum power generation from photovoltaic and thermal panels. Following technological advances, these panels are gathered into one unit: PV/T system. PV/T delivers simultaneously two kinds of power: electrical power and thermal power. Nevertheless, no control systems have been developed in order to track maximum power generation from PV/T system. This paper suggests a PV/T control algorithm based on Artificial Neural Network (ANN) to detect the optimal power operating point (OPOP) by considering PV/T model behavior. The OPOP computes the optimum mass flow rate of PV/T for a considered irradiation and ambient temperature. Simulation results demonstrate great concordance between OPOP model based calculation and ANN outputs.

  10. Integrating sampling techniques and inverse virtual screening: toward the discovery of artificial peptide-based receptors for ligands.

    Science.gov (United States)

    Pérez, Germán M; Salomón, Luis A; Montero-Cabrera, Luis A; de la Vega, José M García; Mascini, Marcello

    2016-05-01

    A novel heuristic using an iterative select-and-purge strategy is proposed. It combines statistical techniques for sampling and classification by rigid molecular docking through an inverse virtual screening scheme. This approach aims to the de novo discovery of short peptides that may act as docking receptors for small target molecules when there are no data available about known association complexes between them. The algorithm performs an unbiased stochastic exploration of the sample space, acting as a binary classifier when analyzing the entire peptides population. It uses a novel and effective criterion for weighting the likelihood of a given peptide to form an association complex with a particular ligand molecule based on amino acid sequences. The exploratory analysis relies on chemical information of peptides composition, sequence patterns, and association free energies (docking scores) in order to converge to those peptides forming the association complexes with higher affinities. Statistical estimations support these results providing an association probability by improving predictions accuracy even in cases where only a fraction of all possible combinations are sampled. False positives/false negatives ratio was also improved with this method. A simple rigid-body docking approach together with the proper information about amino acid sequences was used. The methodology was applied in a retrospective docking study to all 8000 possible tripeptide combinations using the 20 natural amino acids, screened against a training set of 77 different ligands with diverse functional groups. Afterward, all tripeptides were screened against a test set of 82 ligands, also containing different functional groups. Results show that our integrated methodology is capable of finding a representative group of the top-scoring tripeptides. The associated probability of identifying the best receptor or a group of the top-ranked receptors is more than double and about 10 times higher

  11. Volcanic Monitoring Techniques Applied to Controlled Fragmentation Experiments

    Science.gov (United States)

    Kueppers, U.; Alatorre-Ibarguengoitia, M. A.; Hort, M. K.; Kremers, S.; Meier, K.; Scharff, L.; Scheu, B.; Taddeucci, J.; Dingwell, D. B.

    2010-12-01

    Volcanic eruptions are an inevitable natural threat. The range of eruptive styles is large and short term fluctuations of explosivity or vent position pose a large risk that is not necessarily confined to the immediate vicinity of a volcano. Explosive eruptions rather may also affect aviation, infrastructure and climate, regionally as well as globally. Multiparameter monitoring networks are deployed on many active volcanoes to record signs of magmatic processes and help elucidate the secrets of volcanic phenomena. However, our mechanistic understanding of many processes hiding in recorded signals is still poor. As a direct consequence, a solid interpretation of the state of a volcano is still a challenge. In an attempt to bridge this gap, we combined volcanic monitoring and experimental volcanology. We performed 15 well-monitored, field-based, experiments and fragmented natural rock samples from Colima volcano (Mexico) by rapid decompression. We used cylindrical samples of 60 mm height and 25 mm and 60 mm diameter, respectively, and 25 and 35 vol.% open porosity. The applied pressure range was from 4 to 18 MPa. Using different experimental set-ups, the pressurised volume above the samples ranged from 60 - 170 cm3. The experiments were performed at ambient conditions and at controlled sample porosity and size, confinement geometry, and applied pressure. The experiments have been thoroughly monitored with 1) Doppler Radar (DR), 2) high-speed and high-definition cameras, 3) acoustic and infrasound sensors, 4) pressure transducers, and 5) electrically conducting wires. Our aim was to check for common results achieved by the different approaches and, if so, calibrate state-of-the-art monitoring tools. We present how the velocity of the ejected pyroclasts was measured by and evaluated for the different approaches and how it was affected by the experimental conditions and sample characteristics. We show that all deployed instruments successfully measured the pyroclast

  12. Object-Oriented Control System Design Using On-Line Training of Artificial Neural Networks

    Science.gov (United States)

    Rubaai, Ahmed

    1997-01-01

    This report deals with the object-oriented model development of a neuro-controller design for permanent magnet (PM) dc motor drives. The system under study is described as a collection of interacting objects. Each object module describes the object behaviors, called methods. The characteristics of the object are included in its variables. The knowledge of the object exists within its variables, and the performance is determined by its methods. This structure maps well to the real world objects that comprise the system being modeled. A dynamic learning architecture that possesses the capabilities of simultaneous on-line identification and control is incorporated to enforce constraints on connections and control the dynamics of the motor. The control action is implemented "on-line", in "real time" in such a way that the predicted trajectory follows a specified reference model. A design example of controlling a PM dc motor drive on-line shows the effectiveness of the design tool. This will therefore be very useful in aerospace applications. It is expected to provide an innovative and noval software model for the rocket engine numerical simulator executive.

  13. Predictive Techniques for Spacecraft Cabin Air Quality Control

    Science.gov (United States)

    Perry, J. L.; Cromes, Scott D. (Technical Monitor)

    2001-01-01

    As assembly of the International Space Station (ISS) proceeds, predictive techniques are used to determine the best approach for handling a variety of cabin air quality challenges. These techniques use equipment offgassing data collected from each ISS module before flight to characterize the trace chemical contaminant load. Combined with crew metabolic loads, these data serve as input to a predictive model for assessing the capability of the onboard atmosphere revitalization systems to handle the overall trace contaminant load as station assembly progresses. The techniques for predicting in-flight air quality are summarized along with results from early ISS mission analyses. Results from groundbased analyses of in-flight air quality samples are compared to the predictions to demonstrate the technique's relative conservatism.

  14. Adaptive control in an artificial pancreas for people with type 1 diabetes

    DEFF Research Database (Denmark)

    Boiroux, Dimitri; Duun-Henriksen, Anne Katrine; Schmidt, Signe;

    2016-01-01

    In this paper, we discuss overnight blood glucose stabilization in patients with type 1 diabetes using a Model Predictive Controller (MPC). We compute the model parameters in the MPC using a simple and systematic method based on a priori available patient information. We describe and compare 3...... control strategies using a virtual clinic of 100 randomly generated patients with a representative inter-subject variability. This virtual clinic is based on the Hovorka model. We consider the case where only half of the meal bolus is administered at mealtime, and the case where the insulin sensitivity...

  15. The need for artificial intelligence as an aid in controlling a manufacturing operation

    Science.gov (United States)

    Weyand, J.

    AI applications to industrial production and planning are discussed and illustrated with diagrams and drawings. Applications examined include flexible automation of manufacturing processes (robots with open manual control, robots programmable to meet product specifications, self-regulated robots, and robots capable of learning), flexible fault detection and diagnostics, production control, and overall planning and management (product strategies, marketing, determination of development capacity, site selection, project organization, and technology investment strategies). For the case of robots, problems in the design and operation of a state-of-the-art machine-tool cell (for hole boring, milling, and joining) are analyzed in detail.

  16. Effect of Control Techniques on the Performance of Semiactive Dampers

    OpenAIRE

    Masi, John William

    2001-01-01

    A computer simulation is used to examine the effects that various control methods have on the performance of semiactive dampers in controlling the dynamics of a single suspension (quarter car) model. The level of dynamic control of this model has a direct bearing on the ride comfort and vehicle handling, when the single suspension is interpreted as a partial model of a vehicle. The dynamic results obtained when using two alternative semiactive control methods are compared to the results obt...

  17. Genetically controlled fusion, exocytosis and fission of artificial vesicles-a roadmap

    DEFF Research Database (Denmark)

    Bönzli, Eva; Hadorn, Maik; de Lucrezia, Davide;

    2011-01-01

    mechanisms are available, e.g. addition of transcription factors (Kelley et al. 2010). Changes in the pH are reported to control the activity of the fusion peptides (Nomura et al. 2004). So far, we successfully enclosed a commercially available cell-free system and expressed eGFP in vesicles as a proof...

  18. Signal sampling techniques for data acquisition in process control

    NARCIS (Netherlands)

    Laan, Marten Derk van der

    1995-01-01

    In computing sytems employed for data acquisition and process control, communication with the controlled processes is mainly taking place via analog signal lines. In this situation, the quality of data acquired by A/D-converters and the generation of analog control signals by D/A-converters is of ma

  19. Developing an Intelligent Reservoir Flood Control Decision Support System through Integrating Artificial Neural Networks

    Science.gov (United States)

    Chang, L. C.; Kao, I. F.; Tsai, F. H.; Hsu, H. C.; Yang, S. N.; Shen, H. Y.; Chang, F. J.

    2015-12-01

    Typhoons and storms hit Taiwan several times every year and cause serious flood disasters. Because the mountainous terrain and steep landform rapidly accelerate the speed of flood flow, rivers cannot be a stable source of water supply. Reservoirs become one of the most important and effective floodwater storage facilities. However, real-time operation for reservoir flood control is a continuous and instant decision-making process based on rules, laws, meteorological nowcast, in addition to the immediate rainfall and hydrological data. The achievement of reservoir flood control can effectively mitigate flood disasters and store floodwaters for future uses. In this study, we construct an intelligent decision support system for reservoir flood control through integrating different types of neural networks and the above information to solve this problem. This intelligent reservoir flood control decision support system includes three parts: typhoon track classification, flood forecast and adaptive water release models. This study used the self-organizing map (SOM) for typhoon track clustering, nonlinear autoregressive with exogenous inputs (NARX) for multi-step-ahead reservoir inflow prediction, and adaptive neuro-fuzzy inference system (ANFIS) for reservoir flood control. Before typhoons landfall, we can estimate the entire flood hydrogragh of reservoir inflow by using SOM and make a pre-release strategy and real-time reservoir flood operating by using ANFIS. In the meanwhile, NARX can be constantly used real-time five-hour-ahead inflow prediction for providing the newest flood information. The system has been successfully implemented Typhoons Trami (2013), Fitow (2013) and Matmo (2014) in Shihmen Reservoir.

  20. Herion Servo techniques with electronic control systems in hydraulic systems

    Energy Technology Data Exchange (ETDEWEB)

    Ehrath, M.

    1981-01-01

    A description of an electro-hydraulic control circuit for the fuel pump and the injection valve of a large diesel engine is presented. Pressures of 500-1000 bar must be controlled in diesel engines. The newly-developed electronically controlled injection system uses quick-action control valves, a further developed version of the high-response valves. Electronically controlled ignition systems offer the following advantages: improved fuel-air ratio and better combustion; improved injection parameters within the total load range of the engine, better adaption to changing operational and environmental conditions and to changing fuel quality, fewer and less complicated components, and increased operational safety.

  1. AC electric motors control advanced design techniques and applications

    CERN Document Server

    Giri, Fouad

    2013-01-01

    The complexity of AC motor control lies in the multivariable and nonlinear nature of AC machine dynamics. Recent advancements in control theory now make it possible to deal with long-standing problems in AC motors control. This text expertly draws on these developments to apply a wide range of model-based control designmethods to a variety of AC motors. Contributions from over thirty top researchers explain how modern control design methods can be used to achieve tight speed regulation, optimal energetic efficiency, and operation reliability and safety, by considering online state var

  2. Analysis of Dual Rotating Rake Data from the NASA Glenn Advanced Noise Control Fan Duct with Artificial Sources

    Science.gov (United States)

    Dahl, Milo D.; Sutliff, Daniel L.

    2014-01-01

    The Rotating Rake mode measurement system was designed to measure acoustic duct modes generated by a fan stage. Initially, the mode amplitudes and phases were quantified from a single rake measurement at one axial location. To directly measure the modes propagating in both directions within a duct, a second rake was mounted to the rotating system with an offset in both the axial and the azimuthal directions. The rotating rake data analysis technique was then extended to include the data measured by the second rake. The analysis resulted in a set of circumferential mode levels at each of the two rake microphone locations. Radial basis functions were then least-squares fit to this data to obtain the radial mode amplitudes for the modes propagating in both directions within the duct. Validation experiments have been conducted using artificial acoustic sources. Results are shown for the measurement of the standing waves in the duct from sound generated by one and two acoustic sources that are separated into the component modes propagating in both directions within the duct. Measured reflection coefficients from the open end of the duct are compared to analytical predictions.

  3. Controlling vortex chirality in hexagonal building blocks of artificial spin ice

    Science.gov (United States)

    Chopdekar, R. V.; Duff, G.; Hügli, R. V.; Mengotti, E.; Zanin, D. A.; Heyderman, L. J.; Braun, H. B.

    2013-12-01

    We exploit dipolar coupling to control the magnetic states in assemblies of single-domain magnetic nanoislands, arranged in one, two and three adjacent hexagonal rings. On tailoring the shape anisotropy of specific islands, and thus their switching fields, we achieve particular target states with near perfect reliability, and are able to control the chirality of the vortex target states. The magnetic states are observed during magnetization reversal with x-ray photoemission electron microscopy and our results are generally in excellent agreement with a numerical model based on point dipoles and realistic values of disorder. We conclude with a quantitative discussion of how our results depend on disorder and the chosen bias in shape anisotropy.

  4. vitisFlower®: Development and Testing of a Novel Android-Smartphone Application for Assessing the Number of Grapevine Flowers per Inflorescence Using Artificial Vision Techniques

    Directory of Open Access Journals (Sweden)

    Arturo Aquino

    2015-08-01

    Full Text Available Grapevine flowering and fruit set greatly determine crop yield. This paper presents a new smartphone application for automatically counting, non-invasively and directly in the vineyard, the flower number in grapevine inflorescence photos by implementing artificial vision techniques. The application, called vitisFlower®, firstly guides the user to appropriately take an inflorescence photo using the smartphone’s camera. Then, by means of image analysis, the flowers in the image are detected and counted. vitisFlower® has been developed for Android devices and uses the OpenCV libraries to maximize computational efficiency. The application was tested on 140 inflorescence images of 11 grapevine varieties taken with two different devices. On average, more than 84% of flowers in the captures were found, with a precision exceeding 94%. Additionally, the application’s efficiency on four different devices covering a wide range of the market’s spectrum was also studied. The results of this benchmarking study showed significant differences among devices, although indicating that the application is efficiently usable even with low-range devices. vitisFlower is one of the first applications for viticulture that is currently freely available on Google Play.

  5. vitisFlower®: Development and Testing of a Novel Android-Smartphone Application for Assessing the Number of Grapevine Flowers per Inflorescence Using Artificial Vision Techniques.

    Science.gov (United States)

    Aquino, Arturo; Millan, Borja; Gaston, Daniel; Diago, María-Paz; Tardaguila, Javier

    2015-08-28

    Grapevine flowering and fruit set greatly determine crop yield. This paper presents a new smartphone application for automatically counting, non-invasively and directly in the vineyard, the flower number in grapevine inflorescence photos by implementing artificial vision techniques. The application, called vitisFlower(®), firstly guides the user to appropriately take an inflorescence photo using the smartphone's camera. Then, by means of image analysis, the flowers in the image are detected and counted. vitisFlower(®) has been developed for Android devices and uses the OpenCV libraries to maximize computational efficiency. The application was tested on 140 inflorescence images of 11 grapevine varieties taken with two different devices. On average, more than 84% of flowers in the captures were found, with a precision exceeding 94%. Additionally, the application's efficiency on four different devices covering a wide range of the market's spectrum was also studied. The results of this benchmarking study showed significant differences among devices, although indicating that the application is efficiently usable even with low-range devices. vitisFlower is one of the first applications for viticulture that is currently freely available on Google Play.

  6. Artificial neural network assisted kinetic spectrophotometric technique for simultaneous determination of paracetamol and p-aminophenol in pharmaceutical samples using localized surface plasmon resonance band of silver nanoparticles

    Science.gov (United States)

    Khodaveisi, Javad; Dadfarnia, Shayessteh; Haji Shabani, Ali Mohammad; Rohani Moghadam, Masoud; Hormozi-Nezhad, Mohammad Reza

    2015-03-01

    Spectrophotometric analysis method based on the combination of the principal component analysis (PCA) with the feed-forward neural network (FFNN) and the radial basis function network (RBFN) was proposed for the simultaneous determination of paracetamol (PAC) and p-aminophenol (PAP). This technique relies on the difference between the kinetic rates of the reactions between analytes and silver nitrate as the oxidizing agent in the presence of polyvinylpyrrolidone (PVP) which is the stabilizer. The reactions are monitored at the analytical wavelength of 420 nm of the localized surface plasmon resonance (LSPR) band of the formed silver nanoparticles (Ag-NPs). Under the optimized conditions, the linear calibration graphs were obtained in the concentration range of 0.122-2.425 μg mL-1 for PAC and 0.021-5.245 μg mL-1 for PAP. The limit of detection in terms of standard approach (LODSA) and upper limit approach (LODULA) were calculated to be 0.027 and 0.032 μg mL-1 for PAC and 0.006 and 0.009 μg mL-1 for PAP. The important parameters were optimized for the artificial neural network (ANN) models. Statistical parameters indicated that the ability of the both methods is comparable. The proposed method was successfully applied to the simultaneous determination of PAC and PAP in pharmaceutical preparations.

  7. vitisFlower®: Development and Testing of a Novel Android-Smartphone Application for Assessing the Number of Grapevine Flowers per Inflorescence Using Artificial Vision Techniques.

    Science.gov (United States)

    Aquino, Arturo; Millan, Borja; Gaston, Daniel; Diago, María-Paz; Tardaguila, Javier

    2015-01-01

    Grapevine flowering and fruit set greatly determine crop yield. This paper presents a new smartphone application for automatically counting, non-invasively and directly in the vineyard, the flower number in grapevine inflorescence photos by implementing artificial vision techniques. The application, called vitisFlower(®), firstly guides the user to appropriately take an inflorescence photo using the smartphone's camera. Then, by means of image analysis, the flowers in the image are detected and counted. vitisFlower(®) has been developed for Android devices and uses the OpenCV libraries to maximize computational efficiency. The application was tested on 140 inflorescence images of 11 grapevine varieties taken with two different devices. On average, more than 84% of flowers in the captures were found, with a precision exceeding 94%. Additionally, the application's efficiency on four different devices covering a wide range of the market's spectrum was also studied. The results of this benchmarking study showed significant differences among devices, although indicating that the application is efficiently usable even with low-range devices. vitisFlower is one of the first applications for viticulture that is currently freely available on Google Play. PMID:26343664

  8. Characterization of calcareous deposits in artificial seawater by impedance techniques 3--Deposit of CaCO{sub 3} in the presence of Mg(II)

    Energy Technology Data Exchange (ETDEWEB)

    Barchiche, Ch.; Deslouis, C.; Festy, D.; Gil, O.; Refait, Ph.; Touzain, S.; Tribollet, B

    2003-05-30

    Calcareous deposits were formed on steel under cathodic protection conditions in artificial seawater at various potentials from -0.9 to -1.4 V/SCE. The deposition kinetics was analysed by chronoamperometry measurements and the calcareous layers were characterized by electrochemical and electrohydrodynamical impedance spectroscopies, scanning electron microscopy observations and X-ray diffraction analyses. At 20 deg. C, the deposits were composed of aragonite CaCO{sub 3} when formed at potentials E comprised between -0.9 and -1.1 V/SCE, of brucite Mg(OH){sub 2} and aragonite when formed at -1.2 V/SCE, and only of brucite when formed at potentials E{<=}-1.3 V/SCE. However, the in situ impedance techniques demonstrated the presence of a Mg(II)-containing porous layer along with the aragonite deposit at E{>=}-1.1 V/SCE. In seawater enriched with Mg{sup 2+}, the deposition of aragonite was almost totally inhibited, and the behavior of the film containing Mg(II) could be described.

  9. Characterization of calcareous deposits in artificial seawater by impedance techniques 3--Deposit of CaCO3 in the presence of Mg(II)

    International Nuclear Information System (INIS)

    Calcareous deposits were formed on steel under cathodic protection conditions in artificial seawater at various potentials from -0.9 to -1.4 V/SCE. The deposition kinetics was analysed by chronoamperometry measurements and the calcareous layers were characterized by electrochemical and electrohydrodynamical impedance spectroscopies, scanning electron microscopy observations and X-ray diffraction analyses. At 20 deg. C, the deposits were composed of aragonite CaCO3 when formed at potentials E comprised between -0.9 and -1.1 V/SCE, of brucite Mg(OH)2 and aragonite when formed at -1.2 V/SCE, and only of brucite when formed at potentials E≤-1.3 V/SCE. However, the in situ impedance techniques demonstrated the presence of a Mg(II)-containing porous layer along with the aragonite deposit at E≥-1.1 V/SCE. In seawater enriched with Mg2+, the deposition of aragonite was almost totally inhibited, and the behavior of the film containing Mg(II) could be described

  10. Effects of Artificial Gravity and Bed Rest on Spatial Orientation and Balance Control

    Science.gov (United States)

    Paloski, William H.; Moore, S. T.; Feiveson, A. H.; Taylor, L. C.

    2007-01-01

    While the vestibular system should be well-adapted to bed rest (a condition it experiences approximately 8/24 hrs each day), questions remain regarding the degree to which repeated exposures to the unusual gravito-inertial force environment of a short-radius centrifuge might affect central processing of vestibular information used in spatial orientation and balance control. Should these functions be impaired by intermittent AG, its feasibility as a counter-measure would be diminished. We, therefore, examined the effects of AG on spatial orientation and balance control in 15 male volunteers before and after 21 days of 6 HDT bed rest (BR). Eight of the subjects were treated with daily 1hr AG exposures (2.5g at the feet; 1.0g at the heart) aboard a short radius (3m) centrifuge, while the other seven served as controls (C). Spatial orientation was assessed by measures of ocular counter-rolling (OCR; rotation of the eye about the line of sight, an otolith-mediated reflex) and subjective visual vertical (SVV; perception of the spatial upright). Both OCR and SVV measurements were made with the subject upright, lying on their left sides, and lying on their right sides. OCR was measured from binocular eye orientation recordings made while the subjects fixated for 10s on a point target directly in front of the face at a distance of 1 m. SVV was assessed by asking subjects (in the dark) to adjust to upright (using a handheld controller) the orientation of a luminous bar randomly perturbed (15) to either side of the vertical meridian. Balance control performance was assessed using a computerized dynamic posturography (CDP) protocol similar to that currently required for all returning crew members. During each session, the subjects completed a combination of trials of sensory organization test (SOT) 2 (eyes closed, fixed platform) and SOT 5 (eyes closed, sway-referenced platform) with and without static and dynamic pitch plane head movements (plus or minus 20 deg., dynamic

  11. The Sterile Insect Technique as a method of pest control

    International Nuclear Information System (INIS)

    In the Valencia community is doing one of the most ambitious project in the field of plant protection at European level: the fight against fruit fly, one of the most damaging pests of citrus and fruit; by Insect Technique Sterile. This technique consists of laboratory breeding and release into the fields of huge quantities of insects of the pest species that have previously been sterilized. Sterile insect looking for wild individuals of the same species to mate with them and the result is a clutch of viable eggs, causing a decrease in pest populations. After three years of application of the technique on an area of 150,000 hectares, the pest populations have been reduced by 90%. Other benefits have been the reduced used of insecticides and improved the quality of exported fruit. (Author)

  12. Higher-order techniques for some problems of nonlinear control

    Directory of Open Access Journals (Sweden)

    Sarychev Andrey V.

    2002-01-01

    Full Text Available A natural first step when dealing with a nonlinear problem is an application of some version of linearization principle. This includes the well known linearization principles for controllability, observability and stability and also first-order optimality conditions such as Lagrange multipliers rule or Pontryagin's maximum principle. In many interesting and important problems of nonlinear control the linearization principle fails to provide a solution. In the present paper we provide some examples of how higher-order methods of differential geometric control theory can be used for the study nonlinear control systems in such cases. The presentation includes: nonlinear systems with impulsive and distribution-like inputs; second-order optimality conditions for bang–bang extremals of optimal control problems; methods of high-order averaging for studying stability and stabilization of time-variant control systems.

  13. Quality assurance and quality control of nuclear analytical techniques

    International Nuclear Information System (INIS)

    Test and analytical laboratories in East and Central European countries need to prove the reliability and credibility of their economic, environmental, medical and legal decisions and their capacity of issuing reliable, verifiable reports. These demands imposed by the European Union aimed at avoiding a possible barrier to trade for the developing countries. In June 1999, in order to help Member States to develop according to EU objectives and the overall situation of the European market, IAEA launched a new co-operation programme designed to help the nuclear analytical laboratories in nuclear institutions and universities of Member States by training in the use of some Nuclear Analytical Techniques (NAT) that include: alpha, beta and gamma-ray spectrometry, radiochemical and neutron activation analysis, total reflection X-ray fluorescence. The Regional IAEA Project, named 'Quality Assurance/Quality Control of Nuclear Analytical Techniques' (NAT) aims at implementing the QA principles via a system of defined consecutive steps leading to a level on which the QA system is self-sustainable for formal accreditation or certification and satisfies the EU technical performance criteria; the requirements are in accordance with the new ISO/IEC 17025 Standard/Dec.1999 'General requirements for the competence of testing and calibration laboratories' - First edition. The Horia Hulubei National Institute for Nuclear Physics and Engineering, IFIN-HH, was admitted for participation in the IAEA Project in June 1999 account taken of its experience in the QA and metrology fields and its performance in the fields of beta and gamma-ray spectrometry, and radiochemical and neutron activation analysis, employed in both basic research and applications for external clients. Two working groups of specialists with the QA and Standardization and Metrology Departments and six analytical groups with the departments of Nuclear Applied Physics, Life Physics and Ionising Radiation Metrology are

  14. Application of adaptive neuro-fuzzy inference system techniques and artificial neural networks to predict solid oxide fuel cell performance in residential microgeneration installation

    Energy Technology Data Exchange (ETDEWEB)

    Entchev, Evgueniy; Yang, Libing [Integrated Energy Systems Laboratory, CANMET Energy Technology Centre, 1 Haanel Dr., Ottawa, Ontario (Canada)

    2007-06-30

    This study applies adaptive neuro-fuzzy inference system (ANFIS) techniques and artificial neural network (ANN) to predict solid oxide fuel cell (SOFC) performance while supplying both heat and power to a residence. A microgeneration 5 kW{sub el} SOFC system was installed at the Canadian Centre for Housing Technology (CCHT), integrated with existing mechanical systems and connected in parallel to the grid. SOFC performance data were collected during the winter heating season and used for training of both ANN and ANFIS models. The ANN model was built on back propagation algorithm as for ANFIS model a combination of least squares method and back propagation gradient decent method were developed and applied. Both models were trained with experimental data and used to predict selective SOFC performance parameters such as fuel cell stack current, stack voltage, etc. The study revealed that both ANN and ANFIS models' predictions agreed well with variety of experimental data sets representing steady-state, start-up and shut-down operations of the SOFC system. The initial data set was subjected to detailed sensitivity analysis and statistically insignificant parameters were excluded from the training set. As a result, significant reduction of computational time was achieved without affecting models' accuracy. The study showed that adaptive models can be applied with confidence during the design process and for performance optimization of existing and newly developed solid oxide fuel cell systems. It demonstrated that by using ANN and ANFIS techniques SOFC microgeneration system's performance could be modelled with minimum time demand and with a high degree of accuracy. (author)

  15. Applying artificial intelligence to the control of space telescopes (extended abstract)

    Science.gov (United States)

    Drummond, Mark; Swanson, Keith; Bresina, John; Philips, Andrew; Levinson, Rich

    1992-01-01

    The field of astronomy has recently benefited from the availability of space telescopes. The Hubble Space Telescope (HST), for instance, despite its problems, provides a unique and valuable view of the universe. However, unlike HST, a telescope need not be in low Earth orbit to escape our thickening atmosphere: it is currently technologically feasible to put a telescope on the moon, and there are excellent reasons for doing this. Either in low Earth orbit or on the moon, a space telescope represents an expensive and sought-after resource. Thus, the planning, scheduling, and control of these telescopes is an important problem that must be seriously studied.

  16. Glucose-responsive artificial promoter-mediated insulin gene transfer improves glucose control in diabetic mice

    Institute of Scientific and Technical Information of China (English)

    Jaeseok Han; Eung-Hwi Kim; Woohyuk Choi; Hee-Sook Jun

    2012-01-01

    AIM:To investigate the effect of insulin gene therapy using a glucose-responsive synthetic promoter in type 2 diabetic obese mice.METHODS:We employed a recently developed novel insulin gene therapy strategy using a synthetic promoter that regulates insulin gene expression in the liver in response to blood glucose level changes.We intravenously administered a recombinant adenovirus expressing furin-cleavable rat insulin under the control of the synthetic promoter (rAd-SP-rINSfur) into diabetic Leprdb/db mice.A recombinant adenovirus expressing β-galactosidase under the cytomegalovirus promoter was used as a control (rAd-CMV-βgal).Blood glucose levels and body weights were monitored for 50 d.Glucose and insulin tolerance tests were performed.Immunohistochemical staining was performed to investigate islet morphology and insulin content.RESULTS:Administration of rAd-SP-rINSfur lowered blood glucose levels and normoglycemia was maintained for 50 d,whereas the rAd-CMV-βgal control virus-injected mice remained hyperglycemic.Glucose tolerance tests showed that rAd-SP-rINSfur-treated mice cleared exogenous glucose from the blood more efficiently than control virus-injected mice at 4 wk [area under the curve (AUC):21 508.80 ± 2248.18 vs 62 640.00 ± 5014.28,P < 0.01] and at 6 wk (AUC:29 956.60 ± 1757.33 vs 60 016.60 ± 3794.47,P < 0.01).In addition,insulin sensitivity was also significantly improved in mice treated with rAd-SP-rINSfur compared with rAd-CMV-βgal-treated mice (AUC:9150.17±1007.78 vs 11 994.20 ± 474.40,P < 0.05).The islets from rAd-SP-rINSfur-injected mice appeared to be smaller and to contain a higher concentration of insulin than those from rAd-CMV-βgal-injected mice.CONCLUSION:Based on these results,we suggest that insulin gene therapy might be one therapeutic option for remission of type 2 diabetes.

  17. Techniques of artificial intelligence applied to the electric power expansion distribution system planning problem; Tecnicas de inteligencia artificial aplicadas ao problema de planejamento da expansao do sistema de distribuicao de energia eletrica

    Energy Technology Data Exchange (ETDEWEB)

    Froes, Salete Maria

    1996-07-01

    A tool named Constrained Decision Problem (CDP), which is based on Artificial Intelligence and a specific application to Distribution System Planning is described. The CDP allows multiple objective optimization that does not, necessarily, result in a single optimal solution. First, a literature review covers published works related to Artificial Intelligence applications to Electric Power Distribution Systems, emphasizing feeder restoration and reconfiguration. Some concepts related to Artificial Intelligence are described, with particular attention to Planning and to Constrained Decision Problems. Following, an Electric Power System planning model is addressed by using the CDP tool. Some case studies illustrate the Distribution Planning model, which are compared with standard optimization models. Concluding, some comments establishing the possibilities of CDP applications are followed by a view on future developments. (author)

  18. Neuro-prosthetic interplay. Comment on "Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands" by M. Santello et al.

    Science.gov (United States)

    Schieber, Marc H.

    2016-07-01

    Control of the human hand has been both difficult to understand scientifically and difficult to emulate technologically. The article by Santello and colleagues in the current issue of Physics of Life Reviews[1] highlights the accelerating pace of interaction between the neuroscience of controlling body movement and the engineering of robotic hands that can be used either autonomously or as part of a motor neuroprosthesis, an artificial body part that moves under control from a human subject's own nervous system. Motor neuroprostheses typically involve a brain-computer interface (BCI) that takes signals from the subject's nervous system or muscles, interprets those signals through a decoding algorithm, and then applies the resulting output to control the artificial device.

  19. Principal Component Analysis Coupled with Artificial Neural Networks—A Combined Technique Classifying Small Molecular Structures Using a Concatenated Spectral Database

    Directory of Open Access Journals (Sweden)

    Mihail Lucian Birsa

    2011-10-01

    Full Text Available In this paper we present several expert systems that predict the class identity of the modeled compounds, based on a preprocessed spectral database. The expert systems were built using Artificial Neural Networks (ANN and are designed to predict if an unknown compound has the toxicological activity of amphetamines (stimulant and hallucinogen, or whether it is a nonamphetamine. In attempts to circumvent the laws controlling drugs of abuse, new chemical structures are very frequently introduced on the black market. They are obtained by slightly modifying the controlled molecular structures by adding or changing substituents at various positions on the banned molecules. As a result, no substance similar to those forming a prohibited class may be used nowadays, even if it has not been specifically listed. Therefore, reliable, fast and accessible systems capable of modeling and then identifying similarities at molecular level, are highly needed for epidemiological, clinical, and forensic purposes. In order to obtain the expert systems, we have preprocessed a concatenated spectral database, representing the GC-FTIR (gas chromatography-Fourier transform infrared spectrometry and GC-MS (gas chromatography-mass spectrometry spectra of 103 forensic compounds. The database was used as input for a Principal Component Analysis (PCA. The scores of the forensic compounds on the main principal components (PCs were then used as inputs for the ANN systems. We have built eight PC-ANN systems (principal component analysis coupled with artificial neural network with a different number of input variables: 15 PCs, 16 PCs, 17 PCs, 18 PCs, 19 PCs, 20 PCs, 21 PCs and 22 PCs. The best expert system was found to be the ANN network built with 18 PCs, which accounts for an explained variance of 77%. This expert system has the best sensitivity (a rate of classification C = 100% and a rate of true positives TP = 100%, as well as a good selectivity (a rate of true negatives TN

  20. Design and Comparison Direct Torque Control Techniques for Induction Motors

    DEFF Research Database (Denmark)

    Blaabjerg, Frede; Kazmierkowski, Marian P.; Zelechowski, Marcin;

    2005-01-01

    In this paper a comparison of two significant control methods of induction motor are presented. The first one is a classical Direct Torque and Flux Control (DTC) and is compared with a scheme, which uses Space Vector Modulator (DTC-SVM). A comparison in respect to dynamic and steady state...

  1. Analytical techniques and quality control in biomedical trace element research

    DEFF Research Database (Denmark)

    Heydorn, K.

    1994-01-01

    The small number of analytical results in trace element research calls for special methods of quality control. It is shown that when the analytical methods are in statistical control, only small numbers of duplicate or replicate results are needed to ascertain the absence of systematic errors cau...

  2. Linear Control Technique for Anti-Lock Braking System

    Directory of Open Access Journals (Sweden)

    Chankit Jain

    2014-08-01

    Full Text Available Antilock braking systems are used in modern cars to prevent the wheels from locking after brakes are applied. The dynamics of the controller needed for antilock braking system depends on various factors. The vehicle model often is in nonlinear form. Controller needs to provide a controlled torque necessary to maintain optimum value of the wheel slip ratio. The slip ratio is represented in terms of vehicle speed and wheel rotation. In present work first of all system dynamic equations are explained and a slip ratio is expressed in terms of system variables namely vehicle linear velocity and angular velocity of the wheel. By applying a bias braking force system, response is obtained using Simulink models. Using the linear control strategies like PI-type the effectiveness of maintaining desired slip ratio is tested. It is always observed that a steady state error of 10% occurring in all the control system models.

  3. Software factory techniques applied to Process Control at CERN

    CERN Multimedia

    Dutour, MD

    2007-01-01

    The CERN Large Hadron Collider (LHC) requires constant monitoring and control of quantities of parameters to guarantee operational conditions. For this purpose, a methodology called UNICOS (UNIfied Industrial COntrols Systems) has been implemented to standardize the design of process control applications. To further accelerate the development of these applications, we migrated our existing UNICOS tooling suite toward a software factory in charge of assembling project, domain and technical information seamlessly into deployable PLC (Programmable logic Controller) – SCADA (Supervisory Control And Data Acquisition) systems. This software factory delivers consistently high quality by reducing human error and repetitive tasks, and adapts to user specifications in a cost-efficient way. Hence, this production tool is designed to encapsulate and hide the PLC and SCADA target platforms, enabling the experts to focus on the business model rather than specific syntaxes and grammars. Based on industry standard software...

  4. An Artificial Neural Network Modeling for Force Control System of a Robotic Pruning Machine

    Directory of Open Access Journals (Sweden)

    Ali Hashemi

    2014-06-01

    Full Text Available Nowadays, there has been an increasing application of pruning robots for planted forests due to the growing concern on the efficiency and safety issues. Power consumption and working time of agricultural machines have become important issues due to the high value of energy in modern world. In this study, different multi-layer back-propagation networks were utilized for mapping the complex and highly interactive of pruning process parameters and to predict power consumption and cutting time of a force control equipped robotic pruning machine by knowing input parameters such as: rotation speed, stalk diameter, and sensitivity coefficient. Results showed significant effects of all input parameters on output parameters except rotational speed on cutting time. Therefore, for reducing the wear of cutting system, a less rotational speed in every sensitivity coefficient should be selected.

  5. Welfare aspects of vertebrate pest control and culling: ranking control techniques for humaneness.

    Science.gov (United States)

    Littin, K; Fisher, P; Beausoleil, N J; Sharp, T

    2014-04-01

    The management of vertebrate pests depends on the use of traps, pesticides, repellents and other methods, each of which can cause varying levels of pain and other negative experiences to animals. Vertebrate pest control is essential for managing the impacts of unwanted or over-abundant animals on human and animal health, ecological balance and economic interests. As the need for this management is unlikely to diminish over time, a framework has been developed for assessing the humaneness of each technique by considering their negative impacts on animal welfare so that these can be included in decision-making about the selection of techniques for a specific control operation. This information can also support evidence-based regulations directed at managing such animal welfare impacts. In this paper, the authors discuss this assessment framework, briefly review two assessments conducted using the framework and discuss ways in which Competent Authorities and others can use it and other means to improve animal welfare in vertebrate pest management.

  6. Bayesian artificial intelligence

    CERN Document Server

    Korb, Kevin B

    2003-01-01

    As the power of Bayesian techniques has become more fully realized, the field of artificial intelligence has embraced Bayesian methodology and integrated it to the point where an introduction to Bayesian techniques is now a core course in many computer science programs. Unlike other books on the subject, Bayesian Artificial Intelligence keeps mathematical detail to a minimum and covers a broad range of topics. The authors integrate all of Bayesian net technology and learning Bayesian net technology and apply them both to knowledge engineering. They emphasize understanding and intuition but also provide the algorithms and technical background needed for applications. Software, exercises, and solutions are available on the authors' website.

  7. A 21st century technique for food control: Electronic noses

    Energy Technology Data Exchange (ETDEWEB)

    Peris, Miguel, E-mail: mperist@qim.upv.es [Departamento de Quimica, Universidad Politecnica de Valencia, 46071 Valencia (Spain); Escuder-Gilabert, Laura [Departamento de Quimica Analitica, Universitat de Valencia, C/Vicente Andres Estelles s/n, E-46100 Burjasot, Valencia (Spain)

    2009-04-06

    This work examines the main features of modern electronic noses (e-noses) and their most important applications in food control in this new century. The three components of an electronic nose (sample handling system, detection system, and data processing system) are described. Special attention is devoted to the promising mass spectrometry based e-noses, due to their advantages over the more classical gas sensors. Applications described include process monitoring, shelf-life investigation, freshness evaluation, authenticity assessment, as well as other general aspects of the utilization of electronic noses in food control. Finally, some interesting remarks concerning the strengths and weaknesses of electronic noses in food control are also mentioned.

  8. Techniques for increasing the reliability of accelerator control system electronics

    International Nuclear Information System (INIS)

    As the physical size of modern accelerators becomes larger and larger, the number of required control system circuit boards increases, and the probability of one of those circuit boards failing while in service also increases. In order to do physics, the experimenters need the accelerator to provide beam reliably with as little down time as possible. With the advent of colliding beams physics, reliability becomes even more important due to the fact that a control system failure can cause the loss of painstakingly produced antiprotons. These facts prove the importance of keeping reliability in mind when designing and maintaining accelerator control system electronics

  9. A 21st century technique for food control: Electronic noses

    International Nuclear Information System (INIS)

    This work examines the main features of modern electronic noses (e-noses) and their most important applications in food control in this new century. The three components of an electronic nose (sample handling system, detection system, and data processing system) are described. Special attention is devoted to the promising mass spectrometry based e-noses, due to their advantages over the more classical gas sensors. Applications described include process monitoring, shelf-life investigation, freshness evaluation, authenticity assessment, as well as other general aspects of the utilization of electronic noses in food control. Finally, some interesting remarks concerning the strengths and weaknesses of electronic noses in food control are also mentioned.

  10. Control of the energetic proton flux in the inner radiation belt by artificial means

    Science.gov (United States)

    Shao, X.; Papadopoulos, K.; Sharma, A. S.

    2009-07-01

    that such reduction requires injection of less than 10 kW of SAW power. Increasing the power will result in the further decrease of the trapped flux. The paper concludes with a brief discussion of techniques that can inject such waves using ground-based transmitters.

  11. Use of Nuclear Techniques in Food, Agriculture and Pest Control

    International Nuclear Information System (INIS)

    The so-called Nuclear Techniques used in agriculture are of two distinct types but both based on the special characteristics of radio-isotopes which give off radiation or on isotopes which are heavier than the normal element. One type of application uses the radiation given off by isotopes to enable the detection of individual atoms in infinitely small amounts of matter. With this technique we can e.g. follow the travels of fertilizer elements in the soil, into and throughout the crop plant or the travels of animal nutrient atoms throughout the animal and their deposition in milk and meat. This has resulted in enormous advances in crop and livestock research. Very minute traces of pesticides and their residues can be detected in food, in plants and animals and in the environment enabling the development of measures to reduce harmful effects

  12. Use of Nuclear Techniques in Biological Control: Managing Pests, Facilitating Trade and Protecting the Environment. Report of a Consultants Group Meeting. Working Material

    International Nuclear Information System (INIS)

    High-priority opportunities are proposed for use of nuclear techniques to effect improved production and shipping of augmentative biological control agents. Proposed subprojects include use of ionizing radiation to improve the production of insect natural enemies on natural hosts/prey or on artificial diets. Other subprojects pertain to improving the ability to move beneficial organisms in international trade, and in using them in the field. Additional high priority activities were identified proposing use of nuclear techniques to produce sterile and/or substerile F-1 weed biological control agents to help evaluate potential impact on non-target species in the pre-release phase, integration of augmentative releases and F-1 sterility in IPM and area-wide pest management programmes, and utilization of by-products from SIT mass-rearing facilities in augmentative biological control programmes. (author)

  13. Artificial blood

    Directory of Open Access Journals (Sweden)

    Sarkar Suman

    2008-01-01

    Full Text Available Artificial blood is a product made to act as a substitute for red blood cells. While true blood serves many different functions, artificial blood is designed for the sole purpose of transporting oxygen and carbon dioxide throughout the body. Depending on the type of artificial blood, it can be produced in different ways using synthetic production, chemical isolation, or recombinant biochemical technology. Development of the first blood substitutes dates back to the early 1600s, and the search for the ideal blood substitute continues. Various manufacturers have products in clinical trials; however, no truly safe and effective artificial blood product is currently marketed. It is anticipated that when an artificial blood product is available, it will have annual sales of over $7.6 billion in the United States alone.

  14. Operant conditioning: a minimal components requirement in artificial spiking neurons designed for bio-inspired robot's controller.

    Science.gov (United States)

    Cyr, André; Boukadoum, Mounir; Thériault, Frédéric

    2014-01-01

    In this paper, we investigate the operant conditioning (OC) learning process within a bio-inspired paradigm, using artificial spiking neural networks (ASNN) to act as robot brain controllers. In biological agents, OC results in behavioral changes learned from the consequences of previous actions, based on progressive prediction adjustment from rewarding or punishing signals. In a neurorobotics context, virtual and physical autonomous robots may benefit from a similar learning skill when facing unknown and unsupervised environments. In this work, we demonstrate that a simple invariant micro-circuit can sustain OC in multiple learning scenarios. The motivation for this new OC implementation model stems from the relatively complex alternatives that have been described in the computational literature and recent advances in neurobiology. Our elementary kernel includes only a few crucial neurons, synaptic links and originally from the integration of habituation and spike-timing dependent plasticity as learning rules. Using several tasks of incremental complexity, our results show that a minimal neural component set is sufficient to realize many OC procedures. Hence, with the proposed OC module, designing learning tasks with an ASNN and a bio-inspired robot context leads to simpler neural architectures for achieving complex behaviors. PMID:25120464

  15. TiO2 as a photocatalyst for control of the aquatic invasive alga, Cladophora, under natural and artificial light

    Science.gov (United States)

    Peller, J.R.; Whitman, R.L.; Griffith, S.; Harris, P.; Peller, C.; Scalzitti, J.

    2007-01-01

    Cladophora, a nuisance and invasive, filamentous algae (Chlorophyta), massively accumulates along the shores of the lower Great Lakes each summer causing great economic damage and compromising recreational opportunity and perhaps public health. In vitro experiments showed that Cladophora samples were physically and biologically degraded when subjected to TiO2-mediated photocatalysis. For the most successful photocatalytic process, TiO2 was immobilized on a glass surface and used in combination with either sunlight or artificial UV light. The loss of vital algal pigments was monitored using UV–vis spectrophotometry, and cell structural changes were determined by microscopic observation. Cladophora, in the presence of TiO2-covered glass beads, experienced a loss of chloroplast pigments after 2 h of UV lamp light irradiation. In a separate experiment, sunlight exposure over 4 days (∼24 h) resulted in the complete oxidative degradation of the green chloroplast pigments, verified by the UV spectra of the algal extracts. These results suggest that TiO2, mobilized on sunlit silicates may be useful in controlling growth and survival of this alga in the Great Lakes, thus mitigating many of the economic, aesthetic ecological impacts of this invasive alga.

  16. New techniques to control salinity-wastewater reuse interactions in golf courses of the Mediterranean regions

    Science.gov (United States)

    Beltrao, J.; Costa, M.; Rosado, V.; Gamito, P.; Santos, R.; Khaydarova, V.

    2003-04-01

    or artificial leaching remained; 3) Enhanced fertilization increases turfgrass tolerance to salinity, but the contamination will be increased by other hazardous chemicals such as nitrate; 4) Use of salt tolerant turfgrass species this technique will be very useful to the plants, but does not solve the problem os soil or groundwater contamination. When reusing treated wastewater in the Mediterranean areas, the only way to control the salination process and to maintain the sustainability of golf courses is to combat the salination problems by environmentally safe and clean techniques. These new clean techniques include: 1) Use of salt removing turfgrass species; 2) Use of drought tolerant turfgrass species - reduction of salt application by deficit irrigation; 3) Reuse of minimal levels of wastewater enough to obtain a good visual appearance GVA of the turfgrass. Regarding these new clean techniques, experiments were carried out in golf courses of Algarve, Portugal, the most southwest part of Europe. It was shown: 1) Use of salt removing turfgrass species - 3 sprinkle irrigated cultivars were studied (Agrostis solonífera L.; Cynodon dactylon, L. and Penninsetum clandestinum Hochst ex Chiov). 2) Use of drought tolerant turfgrass species -responses to several levels of sprinkle irrigation wastewater and potable water (with and without fertilization). An experimental design, known as sprinkle point source was specially used to simulate the several levels of water application, expressed by the crop coefficient kc and by the crop evapotranspiration rate ETc. Turfgrass yield was enhanced linearly with the increased application of treated wastewater. 3) Reuse of minimal levels of wastewater enough to obtain a good visual appearance GVA of the turfgrass - The minimal crop coefficient kc for a good visual appearance GVA of the turfgrass was around 1.0 to potable water irrigated mixed cultivars (with 30 kg nitrogen ha-1 month-1) and 1.2 to wastewater irrigated Bermuda grass

  17. Control of cabbage diamondback moth by integrating the sterile insect technique and parasitoids in Myanmar

    International Nuclear Information System (INIS)

    Full text: Mass rearing of DBM was carried out on cauliflower, cabbage, mustard and artificial diet. Pupae collection on aluminum foil was tested. Storage of pupae and larvae was carried out in 16 deg. C incubator and 5-10 deg. C refrigerator. Different doses of gamma radiation: 10Kr, 15Kr and 20Kr were tested to established the effective gamma radiation dose. Each one hundred cabbage plants were selected and marked for regular observations of DBM populations in control plots to assess the frequency distribution of DBM adult population in cabbage fields. DBM larvae were collected in control plots to assess the rate of DBM larvae with the parasitoid - Cotesia plutellae in fields. Mass rearing of DBM on cauliflower was better than rearing on cabbage, mustard and artificial diet. Pupae collection on cauliflower was better than those of cabbage, mustard and artificial diet. Pupae could be stored successfully for 2 weeks in 16 deg. C incubator and 5-10 deg. C refrigerator. DBM larvae reared on cauliflower could be stored for 7 days at 5-10 deg. c refrigerator. Radiation doses of 10Kr gave better results than 15 Kr and 20 Kr. 1-5 DBM adults were found in most of the plants during the season. Percentage of DBM larvae parasitised by the parasitoid - Cotesia plutellae was 30-40% in the field. (author)

  18. Modeling and Analysis of Mechanical Properties of Aluminium Alloy (A413 Processed through Squeeze Casting Route Using Artificial Neural Network Model and Statistical Technique

    Directory of Open Access Journals (Sweden)

    R. Soundararajan

    2015-01-01

    Full Text Available Artificial Neural Network (ANN approach was used for predicting and analyzing the mechanical properties of A413 aluminum alloy produced by squeeze casting route. The experiments are carried out with different controlled input variables such as squeeze pressure, die preheating temperature, and melt temperature as per Full Factorial Design (FFD. The accounted absolute process variables produce a casting with pore-free and ideal fine grain dendritic structure resulting in good mechanical properties such as hardness, ultimate tensile strength, and yield strength. As a primary objective, a feed forward back propagation ANN model has been developed with different architectures for ensuring the definiteness of the values. The developed model along with its predicted data was in good agreement with the experimental data, inferring the valuable performance of the optimal model. From the work it was ascertained that, for castings produced by squeeze casting route, the ANN is an alternative method for predicting the mechanical properties and appropriate results can be estimated rather than measured, thereby reducing the testing time and cost. As a secondary objective, quantitative and statistical analysis was performed in order to evaluate the effect of process parameters on the mechanical properties of the castings.

  19. Evaluation of six techniques for control of the western drywood termite (Isoptera: Kalotermitidae) in structures

    International Nuclear Information System (INIS)

    Chemical and nonchemical methods for control of western drywood termites, Incisitermes minor (Hager), were evaluated under conditions that simulated infestations in structures. The efficacy of excessive heat or cold, electrocution, microwaves, and 2 fumigants was evaluated. Termite mortality in artificially infested boards was 100% at 3 d after treatment for both fumigant gases. Heating the whole-structure or spot-applications using microwaves resulted in 96 and 90% mortality, respectively, 3 d after treatment. Mortality levels 4 wk after treatment increased to 98% for heat and 92% for microwaves. Spot-applications of liquid nitrogen at 381.8 kg/m3 achieved 100% mortality 3 d after treatment. However, for 122.7 and 57.3 kg/m3, mortality levels 4 wk after treatment were 99 and 87%, respectively. Mortality by spot-applications of electricity was 44% 3 d after treatment in the 1st test. Four weeks after treatment drywood termite mortality increased to 81%. In a 2nd electrocution test, using spot-application techniques infrequently used in structures, mortality levels increased to 93% at 3 d and 99% at 4 wk after treatment. The distribution of termite survivors within the test building and test boards varied for some treatment techniques. For naturally infested boards, both fumigants exceeded 99% mortality. Use of heat and microwaves resulted in 100 and 99% mortality levels, respectively, 4 wk after treatment. Applications of liquid nitrogen resulted in mortality greater than or equal to 99.8% at 381.8 and 122.7 kg/m3; however, mortality for 57.3 kg/m3 was significantly lower (74%). Mortality levels from electrocution were 89 and 95% 4 wk after treatment respectively in the 2 tests. Damage to test boards and the test building did occur. Six test boards were scorched during microwave treatment, 80% of test boards were damaged during electrocution, and visible signs of damage to the test building were noted for whole-structure heating. (author)

  20. Artificial vision in nuclear fuel fabrication

    International Nuclear Information System (INIS)

    The development of artificial vision techniques opens a door to the optimization of industrial processes which the nuclear industry cannot miss out on. Backing these techniques represents a revolution in security and reliability in the manufacturing of a highly technological products as in nuclear fuel. Enusa Industrias Avanzadas S. A. has successfully developed and implemented the first automatic inspection equipment for pellets by artificial vision in the European nuclear industry which is nowadays qualified and is already developing the second generation of this machine. There are many possible applications for the techniques of artificial vision in the fuel manufacturing processes. Among the practices developed by Enusa Industrias Avanzadas are, besides the pellets inspection, the rod sealing drills detection and positioning in the BWR products and the sealing drills inspection in the PWR fuel. The use of artificial vision in the arduous and precise processes of full inspection will allow the absence of human error, the increase of control in the mentioned procedures, the reduction of doses received by the personnel, a higher reliability of the whole of the operations and an improvement in manufacturing costs. (Author)

  1. Study on modeling of vehicle dynamic stability and control technique

    Institute of Scientific and Technical Information of China (English)

    GAO Yun-ting; LI Pan-feng

    2012-01-01

    In order to solve the problem of enhancing the vehicle driving stability and safety,which has been the hot question researched by scientific and engineering in the vehicle industry,the new control method was investigated.After the analysis of tire moving characteristics and the vehicle stress analysis,the tire model based on the extension pacejka magic formula which combined longitudinal motion and lateral motion was developed and a nonlinear vehicle dynamical stability model with seven freedoms was made.A new model reference adaptive control project which made the slip angle and yaw rate of vehicle body as the output and feedback variable in adjusting the torque of vehicle body to control the vehicle stability was designed.A simulation model was also built in Matlab/Simulink to evaluate this control project.It was made up of many mathematical subsystem models mainly including the tire model module,the yaw moment calculation module,the center of mass parameter calculation module,tire parameter calculation module of multiple and so forth.The severe lane change simulation result shows that this vehicle model and the model reference adaptive control method have an excellent performance.

  2. GPU-Based Optimal Control Techniques for Resistive Wall Mode Control on DIII-D

    Science.gov (United States)

    Clement, M.; Navratil, G. A.; Hanson, J. M.; Strait, E. J.

    2014-10-01

    The DIII-D tokamak can excite strong, locked or nearly locked kink modes whose rotation frequencies do not evolve quickly and are slow compared to their growth rates. To control such modes, DIII-D plans to implement a Graphical Processing Unit (GPU) based feedback control system in a low-latency architecture based on system developed on the HBT-EP tokamak. Up to 128 local magnetic sensors will be used to extrapolate the state of the rotating kink mode, which will be used by the feedback algorithm to calculate the required currents for the internal and/or external control coils. Offline techniques for resolving the mode structure of the resistive wall mode (RWM) will be presented and compared along with the proposed GPU implementation scheme and potential real-time estimation algorithms for RWM feedback. Work supported by the US Department of Energy under DE-FG02-07ER54917, DE-FG02-04ER54761, and DE-FC02-04ER54698.

  3. Respiratory protective device design using control system techniques

    Science.gov (United States)

    Burgess, W. A.; Yankovich, D.

    1972-01-01

    The feasibility of a control system analysis approach to provide a design base for respiratory protective devices is considered. A system design approach requires that all functions and components of the system be mathematically identified in a model of the RPD. The mathematical notations describe the operation of the components as closely as possible. The individual component mathematical descriptions are then combined to describe the complete RPD. Finally, analysis of the mathematical notation by control system theory is used to derive compensating component values that force the system to operate in a stable and predictable manner.

  4. The technique of sand control with expandable screens

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, P. [Petrochina, Liaohe (China). Liaohe Oilfield Co.

    2009-07-01

    Sand production in heavy oil reservoirs can limit the normal production of oil wells. In this study, expandable screens were used as a sand control mechanism by filtering the sand as it entered the wellbore. The screen systems consists of an expandable outer housing, an expandable base pipe and a filtering layer. The screen expands radially through an expandable cone and presses into the casing well. Axial tension is used to shrink the screens radially through a fishing anchor in order to remove them from the well. The lack of a sand ring between the screen and the casing increases the flow area of the oil and reduces flow resistance caused by fine silt blockages. A series of laboratory experiments were conducted to study the expansion and shrinkage properties of the screens. A field test conducted at a well located in the Liaohe oilfield in China demonstrated that good sand control results can be obtained without the need for pump checking. It was concluded that the sand control method is easy to use and provides good sand control results in large open flow areas. 2 refs., 2 tabs., 3 figs.

  5. Design of a Fractional Order PID Controller Using Particle Swarm Optimization Technique

    CERN Document Server

    Maiti, Deepyaman; Konar, Amit

    2008-01-01

    Particle Swarm Optimization technique offers optimal or suboptimal solution to multidimensional rough objective functions. In this paper, this optimization technique is used for designing fractional order PID controllers that give better performance than their integer order counterparts. Controller synthesis is based on required peak overshoot and rise time specifications. The characteristic equation is minimized to obtain an optimum set of controller parameters. Results show that this design method can effectively tune the parameters of the fractional order controller.

  6. Control and switching synchronization of fractional order chaotic systems using active control technique

    KAUST Repository

    Radwan, A.G.

    2013-03-13

    This paper discusses the continuous effect of the fractional order parameter of the Lü system where the system response starts stable, passing by chaotic behavior then reaching periodic response as the fractional-order increases. In addition, this paper presents the concept of synchronization of different fractional order chaotic systems using active control technique. Four different synchronization cases are introduced based on the switching parameters. Also, the static and dynamic synchronizations can be obtained when the switching parameters are functions of time. The nonstandard finite difference method is used for the numerical solution of the fractional order master and slave systems. Many numeric simulations are presented to validate the concept for different fractional order parameters.

  7. Control and switching synchronization of fractional order chaotic systems using active control technique

    Directory of Open Access Journals (Sweden)

    A.G. Radwan

    2014-01-01

    Full Text Available This paper discusses the continuous effect of the fractional order parameter of the Lü system where the system response starts stable, passing by chaotic behavior then reaching periodic response as the fractional-order increases. In addition, this paper presents the concept of synchronization of different fractional order chaotic systems using active control technique. Four different synchronization cases are introduced based on the switching parameters. Also, the static and dynamic synchronizations can be obtained when the switching parameters are functions of time. The nonstandard finite difference method is used for the numerical solution of the fractional order master and slave systems. Many numeric simulations are presented to validate the concept for different fractional order parameters.

  8. Artificial urushi.

    Science.gov (United States)

    Kobayashi, S; Uyama, H; Ikeda, R

    2001-11-19

    A new concept for the design and laccase-catalyzed preparation of "artificial urushi" from new urushiol analogues is described. The curing proceeded under mild reaction conditions to produce the very hard cross-linked film (artificial urushi) with a high gloss surface. A new cross-linkable polyphenol was synthesized by oxidative polymerization of cardanol, a phenol derivative from cashew-nut-shell liquid, by enzyme-related catalysts. The polyphenol was readily cured to produce the film (also artificial urushi) showing excellent dynamic viscoelasticity. PMID:11763444

  9. Artificial intelligence

    CERN Document Server

    Ennals, J R

    1987-01-01

    Artificial Intelligence: State of the Art Report is a two-part report consisting of the invited papers and the analysis. The editor first gives an introduction to the invited papers before presenting each paper and the analysis, and then concludes with the list of references related to the study. The invited papers explore the various aspects of artificial intelligence. The analysis part assesses the major advances in artificial intelligence and provides a balanced analysis of the state of the art in this field. The Bibliography compiles the most important published material on the subject of

  10. Feasibility of Applying Controllable Lubrication Techniques to Reciprocating Machines

    DEFF Research Database (Denmark)

    Pulido, Edgar Estupinan

    conventional lubrication conditions, a mathematical model of a reciprocating mechanism connected to a rigid / flexible rotor via thin fluid films was developed. The mathematical model involves the use of multibody dynamics theory for the modelling of the reciprocating mechanism (rigid bodies), finite elements...... modified hydrostatic lubrication. In this case, the hydrostatic lubrication is modified by injecting oil at controllable pressures, through orifices circumferentially located around the bearing surface. In order to study the performance of journal bearings of reciprocating machines, operating under...... method for the modelling of the flexible rotor (crankshaft) and hydrodynamic fluid film theory for describing the dynamics of the thin fluid films. When active lubrication is introduced to modify conventional hydrodynamic lubrication, by means of aplying radial oil injection at controllable oil pressures...

  11. Development of mercury control techniques for utility boilers

    Energy Technology Data Exchange (ETDEWEB)

    Livengood, C.D.; Mendelsohn, M.H.; Huang, H.S.; Wu, J.M.

    1995-06-01

    This paper gives an overview of research being conducted at Argonne National Laboratory on the capture of mercury in flue gas by both dry sorbents and wet scrubbers. The emphasis in the research is on development of a better understanding of the key factors that control the capture of mercury. Future work is expected to utilize that information for the development of new or modified process concepts featuring enhanced mercury capture capabilities.

  12. Contribution of semen trait selection, artificial insemination technique, and semen dose to the profitability of pig production systems: A simulation study.

    Science.gov (United States)

    Gonzalez-Pena, Dianelys; Knox, Robert V; Rodriguez-Zas, Sandra L

    2016-01-15

    The economic impact of selection for semen traits on pig production systems and potential interaction with artificial insemination (AI) technique and semen dose remains partially understood. The objectives of this study were to compare the financial indicators (gross return, net profit, cost) in a three-tier pig production system under one of two selection strategies: a traditional strategy including nine paternal and maternal traits (S9) and an advanced strategy that adds four semen traits (S13). Maternal traits included the number of pigs born alive, litter birth weight, adjusted 21-day litter weight, and the number of pigs at 21 days, and paternal traits included days to 113.5 kg, back fat, average daily gain, feed efficiency, and carcass lean percentage. The four semen traits included volume, concentration, progressive motility of spermatozoa, and abnormal spermatozoa. Simultaneously, the impact of two AI techniques and a range of fresh refrigerated semen doses including cervical AI with 3 × 10(9) (CAI3) and 2 × 10(9) (CAI2) sperm cells/dose, and intrauterine AI with 1.5 × 10(9) (IUI1.5), 0.75 × 10(9) (IUI0.75), and 0.5 × 10(9) (IUI0.5) sperm cells/dose were evaluated. These factors were also evaluated using a range of farrowing rates (60%-90%), litter sizes (8-14 live-born pigs), and a selected semen collection frequency. The financial impact of the factors was assessed through simulation of a three-way crossbreeding system (maternal nucleus lines A and B and paternal nucleus line C) using ZPLAN. The highest return on investment (profit/cost) of boars was observed at 2.33 collections/wk (three periods of 24 hours between collections). Under this schedule, a significant (P profit. The highest gross return was obtained under S13 with IUI0.75 and IUI0.5. The net profit of S13 was 34.37% higher than the traditional S9 (P profit favored IUI0.5 with relative differences of 4.13%, 2.41%, 1.72%, and 0.43% compared to CAI3, CAI2, IUI1.5, and IUI0

  13. Contribution of semen trait selection, artificial insemination technique, and semen dose to the profitability of pig production systems: A simulation study.

    Science.gov (United States)

    Gonzalez-Pena, Dianelys; Knox, Robert V; Rodriguez-Zas, Sandra L

    2016-01-15

    The economic impact of selection for semen traits on pig production systems and potential interaction with artificial insemination (AI) technique and semen dose remains partially understood. The objectives of this study were to compare the financial indicators (gross return, net profit, cost) in a three-tier pig production system under one of two selection strategies: a traditional strategy including nine paternal and maternal traits (S9) and an advanced strategy that adds four semen traits (S13). Maternal traits included the number of pigs born alive, litter birth weight, adjusted 21-day litter weight, and the number of pigs at 21 days, and paternal traits included days to 113.5 kg, back fat, average daily gain, feed efficiency, and carcass lean percentage. The four semen traits included volume, concentration, progressive motility of spermatozoa, and abnormal spermatozoa. Simultaneously, the impact of two AI techniques and a range of fresh refrigerated semen doses including cervical AI with 3 × 10(9) (CAI3) and 2 × 10(9) (CAI2) sperm cells/dose, and intrauterine AI with 1.5 × 10(9) (IUI1.5), 0.75 × 10(9) (IUI0.75), and 0.5 × 10(9) (IUI0.5) sperm cells/dose were evaluated. These factors were also evaluated using a range of farrowing rates (60%-90%), litter sizes (8-14 live-born pigs), and a selected semen collection frequency. The financial impact of the factors was assessed through simulation of a three-way crossbreeding system (maternal nucleus lines A and B and paternal nucleus line C) using ZPLAN. The highest return on investment (profit/cost) of boars was observed at 2.33 collections/wk (three periods of 24 hours between collections). Under this schedule, a significant (P profit. The highest gross return was obtained under S13 with IUI0.75 and IUI0.5. The net profit of S13 was 34.37% higher than the traditional S9 (P profit favored IUI0.5 with relative differences of 4.13%, 2.41%, 1.72%, and 0.43% compared to CAI3, CAI2, IUI1.5, and IUI0

  14. Cells, Agents, and Support Vectors in Interaction - Modeling Urban Sprawl based on Machine Learning and Artificial Intelligence Techniques in a Post-Industrial Region

    Science.gov (United States)

    Rienow, A.; Menz, G.

    2015-12-01

    Since the beginning of the millennium, artificial intelligence techniques as cellular automata (CA) and multi-agent systems (MAS) have been incorporated into land-system simulations to address the complex challenges of transitions in urban areas as open, dynamic systems. The study presents a hybrid modeling approach for modeling the two antagonistic processes of urban sprawl and urban decline at once. The simulation power of support vector machines (SVM), cellular automata (CA) and multi-agent systems (MAS) are integrated into one modeling framework and applied to the largest agglomeration of Central Europe: the Ruhr. A modified version of SLEUTH (short for Slope, Land-use, Exclusion, Urban, Transport, and Hillshade) functions as the CA component. SLEUTH makes use of historic urban land-use data sets and growth coefficients for the purpose of modeling physical urban expansion. The machine learning algorithm of SVM is applied in order to enhance SLEUTH. Thus, the stochastic variability of the CA is reduced and information about the human and ecological forces driving the local suitability of urban sprawl is incorporated. Subsequently, the supported CA is coupled with the MAS ReHoSh (Residential Mobility and the Housing Market of Shrinking City Systems). The MAS models population patterns, housing prices, and housing demand in shrinking regions based on interactions between household and city agents. Semi-explicit urban weights are introduced as a possibility of modeling from and to the pixel simultaneously. Three scenarios of changing housing preferences reveal the urban development of the region in terms of quantity and location. They reflect the dissemination of sustainable thinking among stakeholders versus the steady dream of owning a house in sub- and exurban areas. Additionally, the outcomes are transferred into a digital petri dish reflecting a synthetic environment with perfect conditions of growth. Hence, the generic growth elements affecting the future

  15. Wind Erosion Processes and Control Techniques in the Sahelian Zone of Niger

    NARCIS (Netherlands)

    Sterk, G.; Stroosnijder, L.; Raats, P.A.C.

    1999-01-01

    Wind Erosion Processes and Control Techniques in the Sahelian Zone of Niger G. Sterk, L. Stroosnijder, and P.A.C. Raats Abstract The objective of this paper is to present the main results and conclusions from three years of field research on wind erosion processes and control techniques in the Sahel

  16. Observations of artificial satellites

    Directory of Open Access Journals (Sweden)

    A. MAMMANO

    1964-06-01

    Full Text Available The following publication gives the results of photographic
    observations of artificial satellites made at Asiago during the second
    and third year of this programme. The fixed camera technique and that
    with moving film (the latter still in its experimental stage have been used.

  17. Closed-loop glycaemic control using an implantable artificial pancreas in diabetic domestic pig (Sus scrofa domesticus).

    Science.gov (United States)

    Taylor, M J; Gregory, R; Tomlins, P; Jacob, D; Hubble, J; Sahota, T S

    2016-03-16

    The performance of a completely implantable peritoneal artificial pancreas (AP) has been demonstrated in principle in a live diabetic domestic pig. The device consists of a smart glucose-sensitive gel that forms a gateway to an insulin reservoir and is designed to both sense glucose and deliver insulin in the peritoneal cavity. It can be refilled with insulin via subcutaneous ports and surgery was developed to insert the AP. Diabetes was induced with streptozotocin (STZ), the device filled with insulin (Humulin(®) R U-500) in situ and the animal observed for several weeks, during which time there was normal access to food and water and several oral glucose challenges. Blood glucose (BG) levels were brought down from >30 mmol/L (540 mg/dL) to non-fasted values between 7 and 13 mmol/L (126-234 mg/dL) about five days after filling the device. Glucose challenge responses improved ultimately so that, starting at 10 mmol/L (180 mg/dL), the BG peak was 18 mmol/L (324 mg/dL) and fell to 7 mmol/L (126 mg/dL) after 30 min, contrasting with intravenous attempts. The reservoir solution was removed after 8 days of blood glucose levels during which they had been increasingly better controlled. A rapid return to diabetic BG levels (30 mmol/L) occurred only after a further 24 days implying some insulin had remained in the device after removal of the reservoir solution. Thus, the closed loop system appeared to have particular influence on the basal and bolus needs for the 8 days in which the reservoir solution was in place and substantial impact for a further 3 weeks. No additional insulin manual adjustment was given during this period. PMID:26691655

  18. Beaconless adaptive-optics technique for HEL beam control

    Science.gov (United States)

    Khizhnyak, Anatoliy; Markov, Vladimir

    2016-05-01

    Effective performance of forthcoming laser systems capable of power delivery on a distant target requires an adaptive optics system to correct atmospheric perturbations on the laser beam. The turbulence-induced effects are responsible for beam wobbling, wandering, and intensity scintillation, resulting in degradation of the beam quality and power density on the target. Adaptive optics methods are used to compensate for these negative effects. In its turn, operation of the AOS system requires a reference wave that can be generated by the beacon on the target. This report discusses a beaconless approach for wavefront correction with its performance based on the detection of the target-scattered light. Postprocessing of the beacon-generated light field enables retrieval and detailed characterization of the turbulence-perturbed wavefront -data that is essential to control the adaptive optics module of a high-power laser system.

  19. Fine tuning of cascaded d-q axis controller for AC-DC-AC converter without DC link capacitor using artificial neural network

    OpenAIRE

    Padmanaban Sanjeevikumar; Balakrishnan GeethaLakshmi; Perumal Danajayan

    2008-01-01

    This paper presents an artificial neural network (ANN) based approach to tune the parameters of the cascaded d-q axis controller for an AC-DC-AC converter without dc link capacitor. The proposed converter uses the cascaded d-q axis controller on the rectifier side and space vector pulse width modulation on the inverter side. The feed-forward ANN with the error back-propagation training is employed to tune the parameters of the cascaded d-q axis controller. The converter topology provides simp...

  20. 人工内分泌系统调节人工神经网络的控制模型%A dynamic control model for modulating using artificial neural networks using the artificial endocrine system

    Institute of Scientific and Technical Information of China (English)

    林广栋; 王煦法

    2012-01-01

    人体的内分泌系统是一个复杂的控制系统,与神经系统、免疫系统一起维持机体的内平衡.受内分泌系统与神经系统的相互作用机制启发,提出一种内分泌系统调节神经网络系统的EMNCS(endocrine modulated neural control system)控制模型.EMNCS模型中,内分泌系统可以根据环境变化动态调节神经网络系统,达到动态控制的目的.把该模型应用于动态环境下的机器人控制系统,实验表明,EMNCS模型能有效提高机器人在动态环境下的适应能力.%The endocrine system in the human body is a complex control system and cooperates with the neural and immune systems to maintain homeostasis. Inspired by the mechanism by which the endocrine system interacts with neural system, an EMNCS (endocrine modulated neural control system) model was proposed in which the artificial endocrine system modulated and artificial neural system. In EMNCS, the endocrine system could modulate the parameters and structures of the neural system in order to achieve dynamic control. The algorithm was applied in the robot system and experimental results show that EMNCS model can improve performance and enhance its adaptability.

  1. HPLC-MS technique for radiopharmaceuticals research and control

    International Nuclear Information System (INIS)

    A liquid chromatography/refractive index detector/radiometric detector/ mass spectrometric detector combination (Agilent 1100 HPLC/RAD/DAD/RID/MSD system) is used as a complex technique for quality assessment of radiopharmaceuticals such as 2-deoxy-2-[18F]fluoro-D-glucose (FDG). Optimisation of HPLC/MS analysis was performed investigating the electrospray ionisation (ESI) analytical signal of the mass spectrometer as a function of solvent composition. The anion-exchange eluents applied as specified by the pharmacopoeia are not suitable for ESI detection due to high ion concentrations. Therefore, solutions of glucose in methanol/water and acetonitrile/water solutions of various semi-volatile electrolytes (ammonium chloride, formic acid, ammonium formate) were analysed by flow injection analysis (FIA) and chromatographically. The best analytical response was obtained with acetonitrile : 0.25% ammonium formate = 80:20 solutions. The most intense MSD signals of FDG in ammonium formate were obtained for the following complex ions: (i) positive ions: fdg.NH4+, fdg.Na+ and (fdg2-CH3O).Na+ (m/z = 200, 205 and 344); (ii) negative ions: fdg.Cl- and fdg.HCOO- (m/z= 217 and 227). The HPLC-MS analysis with Zorbax C-18 and Asahipak-NH2P50 columns gave evidence of admixtures and radiolytic formation of deoxyglucose, deoxychloro-glucose, erythrose, erythritol, gluconic acid, lactose, raffinose, saccharic acid, sorbitol/[19F]FDG, sorbitol/[19F]FDG, xylitol, and other compounds. However, radiometric analysis of expired samples of [18F]FDG gave evidence of a very high radiation stability of its water-ethanol solutions at the point of output of radioactive products. Remarkable is the exceedingly high complexity of the mass spectra of FDG as compared to glucose. Therefore, further research concerns the influence of sodium chloride, linearity of signal response, impurities (mannitol, mannose etc.) interference, and robustness of the MS analysis, with special attention to the ratio of

  2. Recent developments in the techniques of controlling and measuring suction in unsaturated soils

    OpenAIRE

    Delage, Pierre; Romero, Enrique; Tarantino, Alessandro

    2008-01-01

    The difficulty of measuring and controlling suction in unsaturated soils is one of the reasons why the development of the mechanics of unsaturated soils has not been as advanced as that of saturated soils. However, significant developments have been carried out in the last decade in this regard. In this paper, a re-view of some developments carried out in the techniques of controlling suction by using the axis translation, the osmotic method and the vapour control technique is presented. The ...

  3. HPLC-MS technique for radiopharmaceuticals analysis and quality control

    Science.gov (United States)

    Macášek, F.; Búriová, E.; Brúder, P.; Vera-Ruiz, H.

    2003-01-01

    Potentialities of liquid chromatography with mass spectrometric detector (MSD) were investigated with the objective of quality control of radiopharmaceuticals; 2-deoxy-2-[18F]fluoro-D-glucose (FDG) being an example. Screening of suitable MSD analytical lines is presented. Mass-spectrometric monitoring of acetonitrile— aqueous ammonium formate eluant by negatively charged FDG.HCO2 - ions enables isotope analysis (specific activity) of the radiopharmaceutical at m/z 227 and 226. Kryptofix® 222 provides an intense MSD signal of the positive ion associated with NH4 + at m/z 394. Expired FDG injection samples contain decomposition products from which at least one labelled by 18F and characterised by signal of negative ions at m/z 207 does not correspond to FDG fragments but to C5 decomposition products. A glucose chromatographic peak, characterised by m/z 225 negative ion is accompanied by a tail of a component giving a signal of m/z 227, which can belong to [18O]glucose; isobaric sorbitol signals were excluded but FDG-glucose association occurs in the co-elution of separation of model mixtures. The latter can actually lead to a convoluted chromatographic peak, but the absence of 18F makes this inconsistent. Quantification and validation of the FDG component analysis is under way.

  4. Speed control of PMSM system using improved reaching law based sliding mode control and disturbance observer technique

    Directory of Open Access Journals (Sweden)

    Shital M.Wasu

    2013-12-01

    Full Text Available In this paper, improvement of transient response of the permanent-magnet synchronous motor (PMSM subjected to different level of load disturbances and parametric uncertainties and unmodeled dynamics are studied using improved reaching law sliding mode control (IRLSMC and disturbance observer techniques. Proposed scheme is tested under different load conditions and parametric uncertainties. The results of proposed reaching law are compared with other techniques to prove the effectiveness of proposed scheme. Simulation results show the efficacy of proposed control approach.

  5. Artificial Ant Species on Solving Optimization Problems

    OpenAIRE

    Pintea, Camelia-M.

    2013-01-01

    During the last years several ant-based techniques were involved to solve hard and complex optimization problems. The current paper is a short study about the influence of artificial ant species in solving optimization problems. There are studied the artificial Pharaoh Ants, Lasius Niger and also artificial ants with no special specificity used commonly in Ant Colony Optimization.

  6. Speed Control of DC Motor using AC/AC/DC Converter Based on Intelligent Techniques

    Directory of Open Access Journals (Sweden)

    Rakan Kh Antar

    2013-05-01

    Full Text Available    This paper describes the application of ac/ac/dc and ac/dc converters to control the speed of a separately excited DC motor. Artificial neural network and PI controller are trained to select the desired values of firing angles for triggering thyristors of the ac/ac/dc and ac/dc bridge converters in order to control the speed of the dc motor at a desired value with constant and different load torques in order to obtain the best speed response. Simulation results show that the rising time for ac/dc and ac/ac/dc converters at 250rpm are reduced about 79% and 89% respectively, while delay time it reduced about 69% and 64% respectively. Therefore, speed response of the dc motor is more efficient for closed loop system compared with open loop also the response of ac/ac/dc converter is better than ac/dc converter.

  7. Use of artificial intelligence in nuclear power plants

    International Nuclear Information System (INIS)

    The application of artificial intelligence, in the form of expert systems and neural networks, to the control room activities in a nuclear power plant has the potential to reduce operator error and increase plant safety, reliability, and efficiency. Furthermore, there are a large number of non-operating activities (testing, routine maintenance, outage planning, equipment diagnostics, and fuel management) in which artificial intelligence can increase the efficiency and effectiveness of overall plant and corporate operations. This paper reviews the state-of-the-art of artificial intelligence techniques, specifically, expert systems and neural networks, to nuclear power plants. This paper has reviewed the state-of-the-art of artificial intelligence, specifically expert systems and neural networks that are applied to problems in nuclear power plants

  8. Studies of human dynamic space orientation using techniques of control theory

    Science.gov (United States)

    Young, L. R.

    1974-01-01

    Studies of human orientation and manual control in high order systems are summarized. Data cover techniques for measuring and altering orientation perception, role of non-visual motion sensors, particularly the vestibular and tactile sensors, use of motion cues in closed loop control of simple stable and unstable systems, and advanced computer controlled display systems.

  9. Cell-level battery charge/discharge protection system. [electronic control techniques

    Science.gov (United States)

    Donovan, R. L.; Imamura, M. S.

    1977-01-01

    The paper describes three design approaches to individual cell monitoring and control for sealed secondary battery cells. One technique involves a modular strap-on single cell protector which contains all the electronics required for monitoring cell voltage, responding to external commands, and forming a bypass circuit for the cell. A second technique, the multiplexed cell protector, uses common circuitry to monitor and control each cell in a battery pack. The third technique, the computerized cell protector, by replacing the hard-wired logic of the multiplexed cell protector with a microprocessor, achieves greatest control flexibility and inherent computational capability with a minimum parts count implementation.

  10. A randomized controlled, non-inferiority trial of modified natural versus artificial cycle for cryo-thawed embryo transfer

    NARCIS (Netherlands)

    Groenewoud, E. R.; Cohlen, B. J.; Al-Oraiby, A.; Brinkhuis, E. A.; Broekmans, F. J M; De Bruin, J. P.; Van Den Dool, G.; Fleisher, K.; Friederich, J.; Goddijn, M.; Hoek, A.; Hoozemans, D. A.; Kaaijk, E. M.; Koks, C. A M; Laven, J. S E; Van Der Linden, P. J Q; Manger, A. P.; Slappendel, E.; Spinder, T.; Kollen, B. J.; Macklon, N. S.

    2016-01-01

    studyquestion: Are live birth rates (LBRs) after artificial cycle frozen-thawed embryo transfer (AC-FET) non-inferior to LBRs after modified natural cycle frozen-thawed embryo transfer (mNC-FET)? summaryanswer: AC-FET is non-inferior to mNC-FET with regard to LBRs, clinical and ongoing pregnancy rat

  11. Artificial intelligence methods applied in the controlled synthesis of polydimethilsiloxane - poly (methacrylic acid) copolymer networks with imposed properties

    Science.gov (United States)

    Rusu, Teodora; Gogan, Oana Marilena

    2016-05-01

    This paper describes the use of artificial intelligence method in copolymer networks design. In the present study, we pursue a hybrid algorithm composed from two research themes in the genetic design framework: a Kohonen neural network (KNN), path (forward problem) combined with a genetic algorithm path (backward problem). The Tabu Search Method is used to improve the performance of the genetic algorithm path.

  12. 电磁式人工肌肉控制系统的研究与设计初探%Research and Design on Electromagnetic Artificial Muscle Control System

    Institute of Scientific and Technical Information of China (English)

    李靖; 彭宏业; 秦现生

    2012-01-01

    Based on the analysis of the skeletal muscle structure and function of animal neural control system, the micro control system of bionic artificial muscle drive was designed preliminarily. The control system software was planed and analyzed by getting the inspiration from the animal neural control system. The central computer was used to substitute the central nervous system, and the peripheral nervous system was used to substitute of the DSP & FPGA. The R-C force and position mixed control was used for artificial sarcomere actuator to achieve the purpose of the correct control the robot motion.%在分析哺乳动物骨骼肌结构和神经控制机理的基础上,仿生哺乳动物神经系统,使用中央计算机代替中枢神经系统,DSP结合FPGA代替周围神经系统,各种传感器代替感应器,初步设计了微观仿生的人工肌肉驱动器控制系统,并对该控制系统的软件进行了设计规划和任务剖面分解.对单个肌小节驱动器采用R-C力和位置混合控制,使得该控制系统性能更加真实地逼近动物肌肉运动.

  13. An Evaluation on the Criticality Control Ability of a Neutron Absorber based on Artificial Rare Earth Compounds in PLUS7 and WH17x17 Spent Fuel Storage

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jae Hyun; Yim, Che Wook; Shin, Chang Ho; Kim, Song Hyun [Hanyang Univ., Seoul (Korea, Republic of); Choe, Jung Hun; Cho, In Hak; Kim, Jong Kyung; Park, Hwan Seo [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Park, Hyun Seo; Kim, Jung Ho; Kim, Yoon Ho [Korea Research Institute of Standards and Science, Daejeon (Korea, Republic of)

    2014-10-15

    Storages have been designed to minimize space due to increasing storage efficiency. Therefore, the neutron absorbers are generally used for the design of dense spent fuel storages. In a previous study, a neutron absorber based on artificial rare earth compounds with a conceptual design was proposed for efficient and economic disposal of spent nuclear fuel. In this study, the design criteria of the neutron absorber are established by performance evaluations of the neutron absorber. In this study, a design criterion of the neutron absorber based on the artificial rare earth compound was established by the sensitivity analysis of the design parameters. The sensitivity estimations were pursued as the material composition, geometrical feature, heterogeneous conditions, and the arrangement of the absorber. The results show that the neutron absorber has an enough margin of the criticality control when the absorber is manufactured by the minimum requirements.

  14. Myoelectric control of a computer animated hand: a new concept based on the combined use of a tree-structured artificial neural network and a data glove.

    Science.gov (United States)

    Sebelius, F; Eriksson, L; Balkenius, C; Laurell, T

    2006-01-01

    This paper proposes a new learning set-up in the field of control systems for multifunctional hand prostheses. Two male subjects with a traumatic one-hand amputation performed simultaneous symmetric movements with the healthy and the phantom hand. A data glove on the healthy hand was used as a reference to train the system to perform natural movements. Instead of a physical prosthesis with limited degrees of freedom, a virtual (computer-animated) hand was used as the target tool. Both subjects successfully performed seven different motoric actions with the fingers and wrist. To reduce the training time for the system, a tree-structured, self-organizing, artificial neural network was designed. The training time never exceeded 30 seconds for any of the configurations used, which is three to four times faster than most currently used artificial neural network (ANN) architectures.

  15. High-speed reference-beam-angle control technique for holographic memory drive

    Science.gov (United States)

    Yamada, Ken-ichiro; Ogata, Takeshi; Hosaka, Makoto; Fujita, Koji; Okuyama, Atsushi

    2016-09-01

    We developed a holographic memory drive for next-generation optical memory. In this study, we present the key technology for achieving a high-speed transfer rate for reproduction, that is, a high-speed control technique for the reference beam angle. In reproduction in a holographic memory drive, there is the issue that the optimum reference beam angle during reproduction varies owing to distortion of the medium. The distortion is caused by, for example, temperature variation, beam irradiation, and moisture absorption. Therefore, a reference-beam-angle control technique to position the reference beam at the optimum angle is crucial. We developed a new optical system that generates an angle-error-signal to detect the optimum reference beam angle. To achieve the high-speed control technique using the new optical system, we developed a new control technique called adaptive final-state control (AFSC) that adds a second control input to the first one derived from conventional final-state control (FSC) at the time of angle-error-signal detection. We established an actual experimental system employing AFSC to achieve moving control between each page (Page Seek) within 300 µs. In sequential multiple Page Seeks, we were able to realize positioning to the optimum angles of the reference beam that maximize the diffracted beam intensity. We expect that applying the new control technique to the holographic memory drive will enable a giga-bit/s-class transfer rate.

  16. Investigation of proportional integral based technique for controlling PWR pressurizer water level

    International Nuclear Information System (INIS)

    The control system in the pressurizer water level is necessary for the safety of the operation of pressurizer water reactors (PWRs). It will compensate t the primary loop volume changes while keeping the existing pressure of the primary loop at a certain set point. Some researchers have proposed both an intelligent system of neural network and a fuzzy logic to improve the capability of the common conventional control systems used in PWR, i.e. Proportional-Integral (PI) or Proportional-Integral-Derivative (PID). However, those studies did not comprehensively assess the potential of the conventional control systems. It has been confirmed that if the parameters of the Pi based control system are determined more carefully, its results will be equivalent to the results of other control systems or even better. This study aims to address this challenging topic by examining and testing control parameters more closely to obtain the best configuration of the PI-based control system. Compared to the results of the artificial neural network-based control system, the PI results of this study provide an increase of rise time around 280 times, better settling time for approximately 293 times, a decrease of overshoot about 1.1 times, and a reduction of the peak around 0.2%. The configuration has also been validated to be stable and able to overcome disturbances for about 10 seconds with a maximum peak level of 0.005%. Moreover, it can track the set point changes very well. (author)

  17. Artificial intelligence

    International Nuclear Information System (INIS)

    A vivid example of the growing need for frontier physics experiments to make use of frontier technology is in the field of artificial intelligence and related themes. This was reflected in the second international workshop on 'Software Engineering, Artificial Intelligence and Expert Systems in High Energy and Nuclear Physics' which took place from 13-18 January at France Telecom's Agelonde site at La Londe des Maures, Provence. It was the second in a series, the first having been held at Lyon in 1990

  18. Artificial Intelligence

    CERN Document Server

    Warwick, Kevin

    2011-01-01

    if AI is outside your field, or you know something of the subject and would like to know more then Artificial Intelligence: The Basics is a brilliant primer.' - Nick Smith, Engineering and Technology Magazine November 2011 Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include: how intelligence can be defined whether machines can 'think' sensory

  19. Self-controllable Voltage Level Technique to reduce leakage current in DRAM 4×4

    OpenAIRE

    Radha K; M. Sowmyasri

    2016-01-01

    As the technology improved to support very large chip sizes, system designers were faced with power consumption problem and leakage current problem. CMOS technology has increased in level of importance to the point where it now clearly holds center stage as the dominant VLSI technology The present work shows the implementation of a DRAM 4×4 (dynamic random access memory) with self controllable voltage level (SVL) technique. SVL technique is leakage current reduction technique. Sim...

  20. Technical management techniques for identification and control of industrial safety and pollution hazards

    Science.gov (United States)

    Campbell, R.; Dyer, M. K.; Hoard, E. G.; Little, D. G.; Taylor, A. C.

    1972-01-01

    Constructive recommendations are suggested for pollution problems from offshore energy resources industries on outer continental shelf. Technical management techniques for pollution identification and control offer possible applications to space engineering and management.