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Sample records for method generates artificial

  1. A time-domain method to generate artificial time history from a given reference response spectrum

    Energy Technology Data Exchange (ETDEWEB)

    Shin, Gang Sik [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of); Song, Oh Seop [Dept. of Mechanical Engineering, Chungnam National University, Daejeon (Korea, Republic of)

    2016-06-15

    Seismic qualification by test is widely used as a way to show the integrity and functionality of equipment that is related to the overall safety of nuclear power plants. Another means of seismic qualification is by direct integration analysis. Both approaches require a series of time histories as an input. However, in most cases, the possibility of using real earthquake data is limited. Thus, artificial time histories are widely used instead. In many cases, however, response spectra are given. Thus, most of the artificial time histories are generated from the given response spectra. Obtaining the response spectrum from a given time history is straightforward. However, the procedure for generating artificial time histories from a given response spectrum is difficult and complex to understand. Thus, this paper presents a simple time-domain method for generating a time history from a given response spectrum; the method was shown to satisfy conditions derived from nuclear regulatory guidance.

  2. A time-domain method to generate artificial time history from a given reference response spectrum

    International Nuclear Information System (INIS)

    Shin, Gang Sik; Song, Oh Seop

    2016-01-01

    Seismic qualification by test is widely used as a way to show the integrity and functionality of equipment that is related to the overall safety of nuclear power plants. Another means of seismic qualification is by direct integration analysis. Both approaches require a series of time histories as an input. However, in most cases, the possibility of using real earthquake data is limited. Thus, artificial time histories are widely used instead. In many cases, however, response spectra are given. Thus, most of the artificial time histories are generated from the given response spectra. Obtaining the response spectrum from a given time history is straightforward. However, the procedure for generating artificial time histories from a given response spectrum is difficult and complex to understand. Thus, this paper presents a simple time-domain method for generating a time history from a given response spectrum; the method was shown to satisfy conditions derived from nuclear regulatory guidance

  3. Calculation of the energy provided by a PV generator. Comparative study: Conventional methods vs. artificial neural networks

    International Nuclear Information System (INIS)

    Almonacid, F.; Rus, C.; Perez-Higueras, P.; Hontoria, L.

    2011-01-01

    The use of photovoltaics for electricity generation purposes has recorded one of the largest increases in the field of renewable energies. The energy production of a grid-connected PV system depends on various factors. In a wide sense, it is considered that the annual energy provided by a generator is directly proportional to the annual radiation incident on the plane of the generator and to the installed nominal power. However, a range of factors is influencing the expected outcome by reducing the generation of energy. The aim of this study is to compare the results of four different methods for estimating the annual energy produced by a PV generator: three of them are classical methods and the fourth one is based on an artificial neural network developed by the R and D Group for Solar and Automatic Energy at the University of Jaen. The results obtained shown that the method based on an artificial neural network provides better results than the alternative classical methods in study, mainly due to the fact that this method takes also into account some second order effects, such as low irradiance, angular and spectral effects. -- Research highlights: → It is considered that the annual energy provided by a PV generator is directly proportional to the annual radiation incident on the plane of the generator and to the installed nominal power. → A range of factors are influencing the expected outcome by reducing the generation of energy (mismatch losses, dirt and dust, Ohmic losses,.). → The aim of this study is to compare the results of four different methods for estimating the annual energy produced by a PV generator: three of them are classical methods and the fourth one is based on an artificial neural network. → The results obtained shown that the method based on an artificial neural network provides better results than the alternative classical methods in study. While classical methods have only taken into account temperature losses, the method based in

  4. Artificial earthquake generation for nuclear power plant design

    International Nuclear Information System (INIS)

    King, A.C.Y.; Chen, C.

    1977-01-01

    The time history method has been one of the analytical tools applied in the seismic resistant design of nuclear power plants. The time histories used are required to be consistent with the specified design Spectra. Since the spectra of recorded strong motion earthquake or conventionally generated artificial time history have local peaks and valleys, iteration procedures must be applied to generate the artificial time history with desired spectra. The paper describes a detailed method for generating a time history which is consistent with a specified design spectra. There are several advantages of this method described herein. First of all, frequency content of the time history is well under control. Secondly, if one wishes to generate the three components of an earthquake at one site, the inherent nature of this method will make the correlations among these three components to simulate closely the actual recorded time histories. Thirdly, a single time history can be generated to match a spectra for different damping values. (auth.)

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

    Science.gov (United States)

    Wroblewski, David [Mentor, OH; Katrompas, Alexander M [Concord, OH; Parikh, Neel J [Richmond Heights, OH

    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.

  6. Gigantic balloon type artificial lightning generator

    Energy Technology Data Exchange (ETDEWEB)

    Horii; kenji

    1988-09-05

    This paper outlines a hot-air balloon type Van de Graaf 50-MV generator which can generate a 50,000,000 V, 0.2 to 0.3 coulomb artificial lightning comparable to natural lightning discharge and reports the results of investigation on discharging experiments conducted using this apparatus. The subjects covered are as follows: (1) Outline of the hot-air balloon type Van de Graaf 50-MV generator, (2) electric characteristics of the Van de Graaf 50-MV generator, (3) charge transfer with film and balloon charging, (4) the load of the balloon and buoyancy calculation, (5) leakage of charges, (6) study of charging experiments, and (7) evaluation of the apparatus and its method and problems to be solved. (4 figs, 4 tabs, 4 refs)

  7. Genetic algorithms in teaching artificial intelligence (automated generation of specific algebras)

    Science.gov (United States)

    Habiballa, Hashim; Jendryscik, Radek

    2017-11-01

    The problem of teaching essential Artificial Intelligence (AI) methods is an important task for an educator in the branch of soft-computing. The key focus is often given to proper understanding of the principle of AI methods in two essential points - why we use soft-computing methods at all and how we apply these methods to generate reasonable results in sensible time. We present one interesting problem solved in the non-educational research concerning automated generation of specific algebras in the huge search space. We emphasize above mentioned points as an educational case study of an interesting problem in automated generation of specific algebras.

  8. Generation of artificial FASTQ files to evaluate the performance of next-generation sequencing pipelines.

    Directory of Open Access Journals (Sweden)

    Matthew Frampton

    Full Text Available Pipelines for the analysis of Next-Generation Sequencing (NGS data are generally composed of a set of different publicly available software, configured together in order to map short reads of a genome and call variants. The fidelity of pipelines is variable. We have developed ArtificialFastqGenerator, which takes a reference genome sequence as input and outputs artificial paired-end FASTQ files containing Phred quality scores. Since these artificial FASTQs are derived from the reference genome, it provides a gold-standard for read-alignment and variant-calling, thereby enabling the performance of any NGS pipeline to be evaluated. The user can customise DNA template/read length, the modelling of coverage based on GC content, whether to use real Phred base quality scores taken from existing FASTQ files, and whether to simulate sequencing errors. Detailed coverage and error summary statistics are outputted. Here we describe ArtificialFastqGenerator and illustrate its implementation in evaluating a typical bespoke NGS analysis pipeline under different experimental conditions. ArtificialFastqGenerator was released in January 2012. Source code, example files and binaries are freely available under the terms of the GNU General Public License v3.0. from https://sourceforge.net/projects/artfastqgen/.

  9. Generation of artificial time-histories, rich in all frequencies, from given response spectra

    International Nuclear Information System (INIS)

    Levy, S.; Wilkinson, J.P.D.

    1975-01-01

    In order to apply the time-history method of seismic analysis, it is often desirable to generate a suitable artificial time-history from a given response spectrum. The method described allows the generation of such a time-history that is also rich in all frequencies in the spectrum. This richness is achieved by choosing a large number of closely-spaced frequency points such that the adjacent frequencies have their half-power points overlap. The adjacent frequencies satisfy the condition that the frequency interval Δf near a given frequency f is such that (Δf)/f<2c/csub(c) where c is the damping of the system and csub(c) is the critical damping. In developing an artificial time-history, it is desirable to specify the envelope and duration of the record, very often in such a manner as to reproduce the envelope property of a specific earthquake record, and such an option is available in the method described. Examples are given of the development of typical artificial time-histories from earthquake design response spectra and from floor response spectra

  10. Generation of artificial earthquakes for dynamic analysis of nuclear power plant

    International Nuclear Information System (INIS)

    Tsushima, Y.; Hiromatsu, T.; Abe, Y.; Tamaki, T.

    1979-01-01

    A procedure for generating artificial earthquakes for the purpose of the dynamic analysis of the nuclear power plant has been studied and relevant computer codes developed. This paper describes brieafly the generation procedure employed in the computer codes and also deals with the results of two artificial earthquakes generated as an example for input motions for the aseismic design of a BWR-type reactor building. Using one of the generated artificial earthquakes and two actually recorded earthquakes, non-linear responses of the reactor building were computed and the results were compared with each other. From this comparison, it has been concluded that the computer codes are practically usable and the generated artificial earthquakes are useful and powerful as input motions for dynamic analysis of a nuclear power plant. (author)

  11. Ortho Image and DTM Generation with Intelligent Methods

    Science.gov (United States)

    Bagheri, H.; Sadeghian, S.

    2013-10-01

    Nowadays the artificial intelligent algorithms has considered in GIS and remote sensing. Genetic algorithm and artificial neural network are two intelligent methods that are used for optimizing of image processing programs such as edge extraction and etc. these algorithms are very useful for solving of complex program. In this paper, the ability and application of genetic algorithm and artificial neural network in geospatial production process like geometric modelling of satellite images for ortho photo generation and height interpolation in raster Digital Terrain Model production process is discussed. In first, the geometric potential of Ikonos-2 and Worldview-2 with rational functions, 2D & 3D polynomials were tested. Also comprehensive experiments have been carried out to evaluate the viability of the genetic algorithm for optimization of rational function, 2D & 3D polynomials. Considering the quality of Ground Control Points, the accuracy (RMSE) with genetic algorithm and 3D polynomials method for Ikonos-2 Geo image was 0.508 pixel sizes and the accuracy (RMSE) with GA algorithm and rational function method for Worldview-2 image was 0.930 pixel sizes. For more another optimization artificial intelligent methods, neural networks were used. With the use of perceptron network in Worldview-2 image, a result of 0.84 pixel sizes with 4 neurons in middle layer was gained. The final conclusion was that with artificial intelligent algorithms it is possible to optimize the existing models and have better results than usual ones. Finally the artificial intelligence methods, like genetic algorithms as well as neural networks, were examined on sample data for optimizing interpolation and for generating Digital Terrain Models. The results then were compared with existing conventional methods and it appeared that these methods have a high capacity in heights interpolation and that using these networks for interpolating and optimizing the weighting methods based on inverse

  12. Generation of artificial time-histories, rich in all frequencies from given response spectra

    International Nuclear Information System (INIS)

    Levy, S.; Wilkinson, J.P.D.

    1975-01-01

    In order to apply the time-history method of seismic analysis, it is often desirable to generate a suitable artificial time-history from a given response spectrum. The method described in this paper allows the generation of such a time-history that is also rich in all frequencies in the spectrum. This richness is achieved by choosing a large number of closely-spaced frequency points such that the adjacent frequencies have their half-power points overlap. The adjacent frequencies satisfy the condition that the frequency interval Δf near a given frequency f is such that (Δf)/f<2c/csub(c) where c is the damping of the system and csub(c) is the critical damping. In developing an artificial time-history, it is desirable to specify the envelope and duration of the record, very often in such a manner as to reproduce the envelope property of a specific earthquake record, and such an option is available in the method described. Examples are given of the development of typical articifial time-histories from earthquake design response spectra and from floor response spectra. (Auth.)

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

    International Nuclear Information System (INIS)

    Yoshikawa, S.; Saiki, A.; Ugolini, D.; Ozawa, K.

    1996-01-01

    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 (NN ds ) 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)

  14. ORTHO IMAGE AND DTM GENERATION WITH INTELLIGENT METHODS

    Directory of Open Access Journals (Sweden)

    H. Bagheri

    2013-10-01

    Finally the artificial intelligence methods, like genetic algorithms as well as neural networks, were examined on sample data for optimizing interpolation and for generating Digital Terrain Models. The results then were compared with existing conventional methods and it appeared that these methods have a high capacity in heights interpolation and that using these networks for interpolating and optimizing the weighting methods based on inverse distance leads to a high accurate estimation of heights.

  15. A streamlined artificial variable free version of simplex method.

    Directory of Open Access Journals (Sweden)

    Syed Inayatullah

    Full Text Available This paper proposes a streamlined form of simplex method which provides some great benefits over traditional simplex method. For instance, it does not need any kind of artificial variables or artificial constraints; it could start with any feasible or infeasible basis of an LP. This method follows the same pivoting sequence as of simplex phase 1 without showing any explicit description of artificial variables which also makes it space efficient. Later in this paper, a dual version of the new method has also been presented which provides a way to easily implement the phase 1 of traditional dual simplex method. For a problem having an initial basis which is both primal and dual infeasible, our methods provide full freedom to the user, that whether to start with primal artificial free version or dual artificial free version without making any reformulation to the LP structure. Last but not the least, it provides a teaching aid for the teachers who want to teach feasibility achievement as a separate topic before teaching optimality achievement.

  16. A streamlined artificial variable free version of simplex method.

    Science.gov (United States)

    Inayatullah, Syed; Touheed, Nasir; Imtiaz, Muhammad

    2015-01-01

    This paper proposes a streamlined form of simplex method which provides some great benefits over traditional simplex method. For instance, it does not need any kind of artificial variables or artificial constraints; it could start with any feasible or infeasible basis of an LP. This method follows the same pivoting sequence as of simplex phase 1 without showing any explicit description of artificial variables which also makes it space efficient. Later in this paper, a dual version of the new method has also been presented which provides a way to easily implement the phase 1 of traditional dual simplex method. For a problem having an initial basis which is both primal and dual infeasible, our methods provide full freedom to the user, that whether to start with primal artificial free version or dual artificial free version without making any reformulation to the LP structure. Last but not the least, it provides a teaching aid for the teachers who want to teach feasibility achievement as a separate topic before teaching optimality achievement.

  17. Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation.

    Science.gov (United States)

    Du, Tingsong; Hu, Yang; Ke, Xianting

    2015-01-01

    An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA.

  18. Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation

    Directory of Open Access Journals (Sweden)

    Tingsong Du

    2015-01-01

    Full Text Available An improved quantum artificial fish swarm algorithm (IQAFSA for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA, the basic artificial fish swarm algorithm (BAFSA, and the global edition artificial fish swarm algorithm (GAFSA to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA.

  19. Resonant scattering of energetic electrons in the plasmasphere by monotonic whistler-mode waves artificially generated by ionospheric modification

    Directory of Open Access Journals (Sweden)

    S. S. Chang

    2014-05-01

    Full Text Available Modulated high-frequency (HF heating of the ionosphere provides a feasible means of artificially generating extremely low-frequency (ELF/very low-frequency (VLF whistler waves, which can leak into the inner magnetosphere and contribute to resonant interactions with high-energy electrons in the plasmasphere. By ray tracing the magnetospheric propagation of ELF/VLF emissions artificially generated at low-invariant latitudes, we evaluate the relativistic electron resonant energies along the ray paths and show that propagating artificial ELF/VLF waves can resonate with electrons from ~ 100 keV to ~ 10 MeV. We further implement test particle simulations to investigate the effects of resonant scattering of energetic electrons due to triggered monotonic/single-frequency ELF/VLF waves. The results indicate that within the period of a resonance timescale, changes in electron pitch angle and kinetic energy are stochastic, and the overall effect is cumulative, that is, the changes averaged over all test electrons increase monotonically with time. The localized rates of wave-induced pitch-angle scattering and momentum diffusion in the plasmasphere are analyzed in detail for artificially generated ELF/VLF whistlers with an observable in situ amplitude of ~ 10 pT. While the local momentum diffusion of relativistic electrons is small, with a rate of −7 s−1, the local pitch-angle scattering can be intense near the loss cone with a rate of ~ 10−4 s−1. Our investigation further supports the feasibility of artificial triggering of ELF/VLF whistler waves for removal of high-energy electrons at lower L shells within the plasmasphere. Moreover, our test particle simulation results show quantitatively good agreement with quasi-linear diffusion coefficients, confirming the applicability of both methods to evaluate the resonant diffusion effect of artificial generated ELF/VLF whistlers.

  20. A Streamlined Artificial Variable Free Version of Simplex Method

    OpenAIRE

    Inayatullah, Syed; Touheed, Nasir; Imtiaz, Muhammad

    2015-01-01

    This paper proposes a streamlined form of simplex method which provides some great benefits over traditional simplex method. For instance, it does not need any kind of artificial variables or artificial constraints; it could start with any feasible or infeasible basis of an LP. This method follows the same pivoting sequence as of simplex phase 1 without showing any explicit description of artificial variables which also makes it space efficient. Later in this paper, a dual version of the new ...

  1. Forecasting municipal solid waste generation using artificial intelligence modelling approaches.

    Science.gov (United States)

    Abbasi, Maryam; El Hanandeh, Ali

    2016-10-01

    Municipal solid waste (MSW) management is a major concern to local governments to protect human health, the environment and to preserve natural resources. The design and operation of an effective MSW management system requires accurate estimation of future waste generation quantities. The main objective of this study was to develop a model for accurate forecasting of MSW generation that helps waste related organizations to better design and operate effective MSW management systems. Four intelligent system algorithms including support vector machine (SVM), adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and k-nearest neighbours (kNN) were tested for their ability to predict monthly waste generation in the Logan City Council region in Queensland, Australia. Results showed artificial intelligence models have good prediction performance and could be successfully applied to establish municipal solid waste forecasting models. Using machine learning algorithms can reliably predict monthly MSW generation by training with waste generation time series. In addition, results suggest that ANFIS system produced the most accurate forecasts of the peaks while kNN was successful in predicting the monthly averages of waste quantities. Based on the results, the total annual MSW generated in Logan City will reach 9.4×10(7)kg by 2020 while the peak monthly waste will reach 9.37×10(6)kg. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Enhancement of contractile force generation of artificial skeletal muscle tissues by mild and transient heat treatment.

    Science.gov (United States)

    Sato, Masanori; Ikeda, Kazushi; Kanno, Shota; Ito, Akira; Kawabe, Yoshinori; Kamihira, Masamichi

    2014-01-01

    Artificial skeletal muscle tissues composed of cells are expected to be used for applications of regenerative medicine and drug screening. Generally, however, the physical forces generated by tissue-engineered skeletal muscle are lower than those of skeletal muscle tissues found in the body. Local hyperthermia is used for many diseases including muscle injuries. It was recently reported that mild heat treatment improved skeletal muscle functions. In this study, we investigated the effects of mild heat treatment on the tissue-engineered skeletal muscle tissues in vitro. We used magnetite cationic liposomes to label C2C12 myoblast cells magnetically, and constructed densely packed artificial skeletal muscle tissues by using magnetic force. Cell culture at 39°C promoted the differentiation of myoblast cells into myotubes. Moreover, the mild and transient heat treatment improved the contractile properties of artificial skeletal muscle tissue constructs. These findings indicate that the culture method using heat treatment is a useful approach to enhance functions of artificial skeletal muscle tissue.

  3. An artificial functional family filter in homolog searching in next-generation sequencing metagenomics.

    Directory of Open Access Journals (Sweden)

    Ruofei Du

    Full Text Available In functional metagenomics, BLAST homology search is a common method to classify metagenomic reads into protein/domain sequence families such as Clusters of Orthologous Groups of proteins (COGs in order to quantify the abundance of each COG in the community. The resulting functional profile of the community is then used in downstream analysis to correlate the change in abundance to environmental perturbation, clinical variation, and so on. However, the short read length coupled with next-generation sequencing technologies poses a barrier in this approach, essentially because similarity significance cannot be discerned by searching with short reads. Consequently, artificial functional families are produced, in which those with a large number of reads assigned decreases the accuracy of functional profile dramatically. There is no method available to address this problem. We intended to fill this gap in this paper. We revealed that BLAST similarity scores of homologues for short reads from COG protein members coding sequences are distributed differently from the scores of those derived elsewhere. We showed that, by choosing an appropriate score cut-off, we are able to filter out most artificial families and simultaneously to preserve sufficient information in order to build the functional profile. We also showed that, by incorporated application of BLAST and RPS-BLAST, some artificial families with large read counts can be further identified after the score cutoff filtration. Evaluated on three experimental metagenomic datasets with different coverages, we found that the proposed method is robust against read coverage and consistently outperforms the other E-value cutoff methods currently used in literatures.

  4. Generation of artificial accelerograms using neural networks for data of Iran

    International Nuclear Information System (INIS)

    Bargi, Kh.; Loux, C.; Rohani, H.

    2002-01-01

    A new method for generation of artificial earthquake accelerograms from response spectra is proposed by Ghaboussi and Lin in 1997 using neural networks. In this paper the methodology has been extended and enhanced for data of Iran. For this purpose, first 40 records of Iran acceleration is chosen, then an RBF neural network which called generalized regression neural network learn the inverse mapping directly from the response spectrum to the Discrete Cosine Transform of accelerograms. Discrete Cosine Transform has been used as an assisting device to extract the content of frequency domain. Learning of network is reasonable and a generalized regression neural network learns it in a few second. Outputs are presented to demonstrate the performance of this method and show its capabilities

  5. Generative Artificial Intelligence : Philosophy and Theory of Artificial Intelligence

    NARCIS (Netherlands)

    van der Zant, Tijn; Kouw, Matthijs; Schomaker, Lambertus; Mueller, Vincent C.

    2013-01-01

    The closed systems of contemporary Artificial Intelligence do not seem to lead to intelligent machines in the near future. What is needed are open-ended systems with non-linear properties in order to create interesting properties for the scaffolding of an artificial mind. Using post-structuralistic

  6. An Artificially Intelligent Technique to Generate Synthetic Geomechanical Well Logs for the Bakken Formation

    Directory of Open Access Journals (Sweden)

    George Parapuram

    2018-03-01

    Full Text Available Artificially intelligent and predictive modelling of geomechanical properties is performed by creating supervised machine learning data models utilizing artificial neural networks (ANN and will predict geomechanical properties from basic and commonly used conventional well logs such as gamma ray, and bulk density. The predictive models were created by following the approach on a large volume of data acquired from 112 wells containing the Bakken Formation in North Dakota. The studied wells cover a large surface area of the formation containing the five main producing counties in North Dakota: Burke, Mountrail, McKenzie, Dunn, and Williams. Thus, with a large surface area being analyzed in this research, there is confidence with a high degree of certainty that an extensive representation of the Bakken Formation is modelled, by training neural networks to work on varying properties from the different counties containing the Bakken Formation in North Dakota. Shear wave velocity of 112 wells is also analyzed by regression methods and neural networks, and a new correlation is proposed for the Bakken Formation. The final goal of the research is to achieve supervised artificial neural network models that predict geomechanical properties of future wells with an accuracy of at least 90% for the Upper and Middle Bakken Formation. Thus, obtaining these logs by generating it from statistical and artificially intelligent methods shows a potential for significant improvements in performance, efficiency, and profitability for oil and gas operators.

  7. The activL® Artificial Disc: a next-generation motion-preserving implant for chronic lumbar discogenic pain

    Science.gov (United States)

    Yue, James J; Garcia, Rolando; Miller, Larry E

    2016-01-01

    Degeneration of the lumbar intervertebral discs is a leading cause of chronic low back pain in adults. Treatment options for patients with chronic lumbar discogenic pain unresponsive to conservative management include total disc replacement (TDR) or lumbar fusion. Until recently, only two lumbar TDRs had been approved by the US Food and Drug Administration − the Charité Artificial Disc in 2004 and the ProDisc-L Total Disc Replacement in 2006. In June 2015, a next-generation lumbar TDR received Food and Drug Administration approval − the activL® Artificial Disc (Aesculap Implant Systems). Compared to previous-generation lumbar TDRs, the activL® Artificial Disc incorporates specific design enhancements that result in a more precise anatomical match and allow a range of motion that better mimics the healthy spine. The results of mechanical and clinical studies demonstrate that the activL® Artificial Disc results in improved mechanical and clinical outcomes versus earlier-generation artificial discs and compares favorably to lumbar fusion. The purpose of this report is to describe the activL® Artificial Disc including implant characteristics, intended use, surgical technique, postoperative care, mechanical testing, and clinical experience to date. PMID:27274317

  8. A new method of artificial latent fingerprint creation using artificial sweat and inkjet printer.

    Science.gov (United States)

    Hong, Sungwook; Hong, Ingi; Han, Aleum; Seo, Jin Yi; Namgung, Juyoung

    2015-12-01

    In order to study fingerprinting in the field of forensic science, it is very important to have two or more latent fingerprints with identical chemical composition and intensity. However, it is impossible to obtain identical fingerprints, in reality, because fingerprinting comes out slightly differently every time. A previous research study had proposed an artificial fingerprint creation method in which inkjet ink was replaced with amino acids and sodium chloride solution: the components of human sweat. But, this method had some drawbacks: divalent cations were not added while formulating the artificial sweat solution, and diluted solutions were used for creating weakly deposited latent fingerprint. In this study, a method was developed for overcoming the drawbacks of the methods used in the previous study. Several divalent cations were added in this study because the amino acid-ninhydrin (or some of its analogues) complex is known to react with divalent cations to produce a photoluminescent product; and, similarly, the amino acid-1,2-indanedione complex is known to be catalyzed by a small amount of zinc ions to produce a highly photoluminescent product. Also, in this study, a new technique was developed which enables to adjust the intensity when printing the latent fingerprint patterns. In this method, image processing software is used to control the intensity of the master fingerprint patterns, which adjusts the printing intensity of the latent fingerprints. This new method opened the way to produce a more realistic artificial fingerprint in various strengths with one artificial sweat working solution. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  9. Proposed Sandia frequency shift for anti-islanding detection method based on artificial immune system

    Directory of Open Access Journals (Sweden)

    A.Y. Hatata

    2018-03-01

    Full Text Available Sandia frequency shift (SFS is one of the active anti-islanding detection methods that depend on frequency drift to detect an islanding condition for inverter-based distributed generation. The non-detection zone (NDZ of the SFS method depends to a great extent on its parameters. Improper adjusting of these parameters may result in failure of the method. This paper presents a proposed artificial immune system (AIS-based technique to obtain optimal parameters of SFS anti-islanding detection method. The immune system is highly distributed, highly adaptive, and self-organizing in nature, maintains a memory of past encounters, and has the ability to continually learn about new encounters. The proposed method generates less total harmonic distortion (THD than the conventional SFS, which results in faster island detection and better non-detection zone. The performance of the proposed method is derived analytically and simulated using Matlab/Simulink. Two case studies are used to verify the proposed method. The first case includes a photovoltaic (PV connected to grid and the second includes a wind turbine connected to grid. The deduced optimized parameter setting helps to achieve the “non-islanding inverter” as well as least potential adverse impact on power quality. Keywords: Anti-islanding detection, Sandia frequency shift (SFS, Non-detection zone (NDZ, Total harmonic distortion (THD, Artificial immune system (AIS, Clonal selection algorithm

  10. The activL® Artificial Disc: a next-generation motion-preserving implant for chronic lumbar discogenic pain

    Directory of Open Access Journals (Sweden)

    Yue JJ

    2016-05-01

    Full Text Available James J Yue,1 Rolando Garcia Jr,2 Larry E Miller3 1Department of Orthopaedic Surgery, Yale School of Medicine, New Haven, CT, 2Orthopedic Care Center, Miami, FL, 3Miller Scientific Consulting, Inc., Asheville, NC, USA Abstract: Degeneration of the lumbar intervertebral discs is a leading cause of chronic low back pain in adults. Treatment options for patients with chronic lumbar discogenic pain unresponsive to conservative management include total disc replacement (TDR or lumbar fusion. Until recently, only two lumbar TDRs had been approved by the US Food and Drug Administration - the Charité Artificial Disc in 2004 and the ProDisc-L Total Disc Replacement in 2006. In June 2015, a next-generation lumbar TDR received Food and Drug Administration approval - the activL® Artificial Disc (Aesculap Implant Systems. Compared to previous-generation lumbar TDRs, the activL® Artificial Disc incorporates specific design enhancements that result in a more precise anatomical match and allow a range of motion that better mimics the healthy spine. The results of mechanical and clinical studies demonstrate that the activL® Artificial Disc results in improved mechanical and clinical outcomes versus earlier-generation artificial discs and compares favorably to lumbar fusion. The purpose of this report is to describe the activL® Artificial Disc including implant characteristics, intended use, surgical technique, postoperative care, mechanical testing, and clinical experience to date. Keywords: activL® Artificial Disc, artificial disc, degenerative disc disease, discogenic, implant, lumbar, motion preservation, pain

  11. Stator current harmonics evolution by neural network method based on CFE/SS algorithm for ACEC generator of Rey Power Plant

    International Nuclear Information System (INIS)

    Soleymani, S.; Ranjbar, A.M.; Mirabedini, H.

    2001-01-01

    One method for on-line fault diagnosis in synchronous generator is stator current harmonics analysis. Then artificial neural network is considered in this paper in order to evaluate stator current harmonics in different loads. Training set of artificial neural network is made ready by generator modeling, finite element method and state space model. Many points from generator capability curve are used in order to complete this set. Artificial neural network which is used in this paper is a percept ron network with a single hidden layer, Eight hidden neurons and back propagation algorithm. Results are indicated that the trained artificial neural network can identify stator current harmonics for arbitrary load from the capability curve. The error is less than 10% in comparison with values obtained directly from the CFE-SS algorithm. The rating parameters of modeled generator are 43950 (kV A), 11(KV), 3000 (rpm), 50 (H Z), (P F=0.8)

  12. A methodology based on dynamic artificial neural network for short-term forecasting of the power output of a PV generator

    International Nuclear Information System (INIS)

    Almonacid, F.; Pérez-Higueras, P.J.; Fernández, Eduardo F.; Hontoria, L.

    2014-01-01

    Highlights: • The output of the majority of renewables energies depends on the variability of the weather conditions. • The short-term forecast is going to be essential for effectively integrating solar energy sources. • A new method based on artificial neural network to predict the power output of a PV generator one hour ahead is proposed. • This new method is based on dynamic artificial neural network to predict global solar irradiance and the air temperature. • The methodology developed can be used to estimate the power output of a PV generator with a satisfactory margin of error. - Abstract: One of the problems of some renewables energies is that the output of these kinds of systems is non-dispatchable depending on variability of weather conditions that cannot be predicted and controlled. From this point of view, the short-term forecast is going to be essential for effectively integrating solar energy sources, being a very useful tool for the reliability and stability of the grid ensuring that an adequate supply is present. In this paper a new methodology for forecasting the output of a PV generator one hour ahead based on dynamic artificial neural network is presented. The results of this study show that the proposed methodology could be used to forecast the power output of PV systems one hour ahead with an acceptable degree of accuracy

  13. A review of football injuries on third and fourth generation artificial turfs compared with natural turf.

    Science.gov (United States)

    Williams, Sean; Hume, Patria A; Kara, Stephen

    2011-11-01

    Football codes (rugby union, soccer, American football) train and play matches on natural and artificial turfs. A review of injuries on different turfs was needed to inform practitioners and sporting bodies on turf-related injury mechanisms and risk factors. Therefore, the aim of this review was to compare the incidence, nature and mechanisms of injuries sustained on newer generation artificial turfs and natural turfs. Electronic databases were searched using the keywords 'artificial turf', 'natural turf', 'grass' and 'inj*'. Delimitation of 120 articles sourced to those addressing injuries in football codes and those using third and fourth generation artificial turfs or natural turfs resulted in 11 experimental papers. These 11 papers provided 20 cohorts that could be assessed using magnitude-based inferences for injury incidence rate ratio calculations pertaining to differences between surfaces. Analysis showed that 16 of the 20 cohorts showed trivial effects for overall incidence rate ratios between surfaces. There was increased risk of ankle injury playing on artificial turf in eight cohorts, with incidence rate ratios from 0.7 to 5.2. Evidence concerning risk of knee injuries on the two surfaces was inconsistent, with incidence rate ratios from 0.4 to 2.8. Two cohorts showed beneficial inferences over the 90% likelihood value for effects of artificial surface on muscle injuries for soccer players; however, there were also two harmful, four unclear and five trivial inferences across the three football codes. Inferences relating to injury severity were inconsistent, with the exception that artificial turf was very likely to have harmful effects for minor injuries in rugby union training and severe injuries in young female soccer players. No clear differences between surfaces were evident in relation to training versus match injuries. Potential mechanisms for differing injury patterns on artificial turf compared with natural turf include increased peak torque and

  14. Real power transfer allocation method with the application of artificial neural network

    Energy Technology Data Exchange (ETDEWEB)

    Mustafa, M.W.; Khalid, S.N.; Shareef, H.; Khairuddin, A. [Technological Univ. of Malaysia, Skudai, Johor Bahru (Malaysia). Dept. of Electrical Power Enginering

    2008-07-01

    This paper presented a newly modified nodal equations method for identifying the real power transfer between generators and load. The objective was to represent each load current as a function of the generator's current and load voltages. The modified admittance matrix of a circuit was used to decompose the load voltage dependent term into components of generator dependent terms. By using these two decompositions of current and voltage terms, the real power transfer between loads and generators was obtained. The robustness of the proposed method was demonstrated on the modified IEEE 30-bus system. An appropriate Artificial Neural Network (ANN) was also created to solve the same problem in a simpler and faster manner with very good accuracy. For this purpose, supervised learning paradigm and feedforward architecture were chosen for the proposed ANN power transfer allocation technique. The method could be adapted to other larger systems by modifying the neural network structure. This technique can be used to solve some of the difficult real power pricing and costing issues and to ensure fairness and transparency in the deregulated environment of power system operation. 22 refs., 5 tabs., 8 figs.

  15. Functional Identification of the Plasmodium Centromere and Generation of a Plasmodium Artificial Chromosome

    OpenAIRE

    Iwanaga, Shiroh; Khan, Shahid M.; Kaneko, Izumi; Christodoulou, Zoe; Newbold, Chris; Yuda, Masao; Janse, Chris J.; Waters, Andrew P.

    2010-01-01

    Summary The artificial chromosome represents a useful tool for gene transfer, both as cloning vectors and in chromosome biology research. To generate a Plasmodium artificial chromosome (PAC), we had to first functionally identify and characterize the parasite's centromere. A putative centromere (pbcen5) was cloned from chromosome 5 of the rodent parasite P. berghei based on a Plasmodium gene-synteny map. Plasmids containing pbcen5 were stably maintained in parasites during a blood-stage infec...

  16. An artificial vector model for generating abnormal electrocardiographic rhythms

    International Nuclear Information System (INIS)

    Clifford, Gari D; Nemati, Shamim; Sameni, Reza

    2010-01-01

    We present generalizations of our previously published artificial models for generating multi-channel ECG to provide simulations of abnormal cardiac rhythms. Using a three-dimensional vectorcardiogram (VCG) formulation, we generate the normal cardiac dipole for a patient using a sum of Gaussian kernels, fitted to real VCG recordings. Abnormal beats are specified either as perturbations to the normal dipole or as new dipole trajectories. Switching between normal and abnormal beat types is achieved using a first-order Markov chain. Probability transitions can be learned from real data or modeled by coupling to heart rate and sympathovagal balance. Natural morphology changes from beat-to-beat are incorporated by varying the angular frequency of the dipole as a function of the inter-beat (RR) interval. The RR interval time series is generated using our previously described model whereby time- and frequency-domain heart rate (HR) and heart rate variability characteristics can be specified. QT-HR hysteresis is simulated by coupling the Gaussian kernels associated with the T-wave in the model with a nonlinear factor related to the local HR (determined from the last n RR intervals). Morphology changes due to respiration are simulated by introducing a rotation matrix couple to the respiratory frequency. We demonstrate an example of the use of this model by simulating HR-dependent T-wave alternans (TWA) with and without phase-switching due to ectopy. Application of our model also reveals previously unreported effects of common TWA estimation methods

  17. Estimation of mechanical properties of nanomaterials using artificial intelligence methods

    Science.gov (United States)

    Vijayaraghavan, V.; Garg, A.; Wong, C. H.; Tai, K.

    2014-09-01

    Computational modeling tools such as molecular dynamics (MD), ab initio, finite element modeling or continuum mechanics models have been extensively applied to study the properties of carbon nanotubes (CNTs) based on given input variables such as temperature, geometry and defects. Artificial intelligence techniques can be used to further complement the application of numerical methods in characterizing the properties of CNTs. In this paper, we have introduced the application of multi-gene genetic programming (MGGP) and support vector regression to formulate the mathematical relationship between the compressive strength of CNTs and input variables such as temperature and diameter. The predictions of compressive strength of CNTs made by these models are compared to those generated using MD simulations. The results indicate that MGGP method can be deployed as a powerful method for predicting the compressive strength of the carbon nanotubes.

  18. Artificial urinary conduit construction using tissue engineering methods.

    Science.gov (United States)

    Kloskowski, Tomasz; Pokrywczyńska, Marta; Drewa, Tomasz

    2015-01-01

    Incontinent urinary diversion using an ileal conduit is the most popular method used by urologists after bladder cystectomy resulting from muscle invasive bladder cancer. The use of gastrointestinal tissue is related to a series of complications with the necessity of surgical procedure extension which increases the time of surgery. Regenerative medicine together with tissue engineering techniques gives hope for artificial urinary conduit construction de novo without affecting the ileum. In this review we analyzed history of urinary diversion together with current attempts in urinary conduit construction using tissue engineering methods. Based on literature and our own experience we presented future perspectives related to the artificial urinary conduit construction. A small number of papers in the field of tissue engineered urinary conduit construction indicates that this topic requires more attention. Three main factors can be distinguished to resolve this topic: proper scaffold construction along with proper regeneration of both the urothelium and smooth muscle layers. Artificial urinary conduit has a great chance to become the first commercially available product in urology constructed by regenerative medicine methods.

  19. Artificial intelligence methods for diagnostic

    International Nuclear Information System (INIS)

    Dourgnon-Hanoune, A.; Porcheron, M.; Ricard, B.

    1996-01-01

    To assist in diagnosis of its nuclear power plants, the Research and Development Division of Electricite de France has been developing skills in Artificial Intelligence for about a decade. Different diagnostic expert systems have been designed. Among them, SILEX for control rods cabinet troubleshooting, DIVA for turbine generator diagnosis, DIAPO for reactor coolant pump diagnosis. This know how in expert knowledge modeling and acquisition is direct result of experience gained during developments and of a more general reflection on knowledge based system development. We have been able to reuse this results for other developments such as a guide for auxiliary rotating machines diagnosis. (authors)

  20. Review of Artificial Abrasion Test Methods for PV Module Technology

    Energy Technology Data Exchange (ETDEWEB)

    Miller, David C. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Muller, Matt T. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Simpson, Lin J. [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2016-08-01

    This review is intended to identify the method or methods--and the basic details of those methods--that might be used to develop an artificial abrasion test. Methods used in the PV literature were compared with their closest implementation in existing standards. Also, meetings of the International PV Quality Assurance Task Force Task Group 12-3 (TG12-3, which is concerned with coated glass) were used to identify established test methods. Feedback from the group, which included many of the authors from the PV literature, included insights not explored within the literature itself. The combined experience and examples from the literature are intended to provide an assessment of the present industry practices and an informed path forward. Recommendations toward artificial abrasion test methods are then identified based on the experiences in the literature and feedback from the PV community. The review here is strictly focused on abrasion. Assessment methods, including optical performance (e.g., transmittance or reflectance), surface energy, and verification of chemical composition were not examined. Methods of artificially soiling PV modules or other specimens were not examined. The weathering of artificial or naturally soiled specimens (which may ultimately include combined temperature and humidity, thermal cycling and ultraviolet light) were also not examined. A sense of the purpose or application of an abrasion test method within the PV industry should, however, be evident from the literature.

  1. Artificial Intelligence Application in Power Generation Industry: Initial considerations

    Science.gov (United States)

    Ismail, Rahmat Izaizi B.; Ismail Alnaimi, Firas B.; AL-Qrimli, Haidar F.

    2016-03-01

    With increased competitiveness in power generation industries, more resources are directed in optimizing plant operation, including fault detection and diagnosis. One of the most powerful tools in faults detection and diagnosis is artificial intelligence (AI). Faults should be detected early so correct mitigation measures can be taken, whilst false alarms should be eschewed to avoid unnecessary interruption and downtime. For the last few decades there has been major interest towards intelligent condition monitoring system (ICMS) application in power plant especially with AI development particularly in artificial neural network (ANN). ANN is based on quite simple principles, but takes advantage of their mathematical nature, non-linear iteration to demonstrate powerful problem solving ability. With massive possibility and room for improvement in AI, the inspiration for researching them are apparent, and literally, hundreds of papers have been published, discussing the findings of hybrid AI for condition monitoring purposes. In this paper, the studies of ANN and genetic algorithm (GA) application will be presented.

  2. Artificial Neural Networks as an Architectural Design Tool-Generating New Detail Forms Based On the Roman Corinthian Order Capital

    Science.gov (United States)

    Radziszewski, Kacper

    2017-10-01

    The following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital. During the experiment, as an input training data set, five local geometry parameters combined has given the best results: Theta, Pi, Rho in spherical coordinate system based on the capital volume centroid, followed by Z value of the Cartesian coordinate system and a distance from vertical planes created based on the capital symmetry. Additionally during the experiment, artificial neural network hidden layers optimal count and structure was found, giving results of the error below 0.2% for the mentioned before input parameters. Once successfully trained artificial network, was able to mimic the details composition on any other geometry type given. Despite of calculating the transformed geometry locally and separately for each of the thousands of surface points, system could create visually attractive and diverse, complex patterns. Designed tool, based on the supervised learning method of machine learning, gives possibility of generating new architectural forms- free of the designer’s imagination bounds. Implementing the infinitely broad computational methods of machine learning, or Artificial Intelligence in general, not only could accelerate and simplify the design process, but give an opportunity to explore never seen before, unpredictable forms or everyday architectural practice solutions.

  3. Feasibility of gas-discharge and optical methods of creating artificial ozone layers of the earth

    International Nuclear Information System (INIS)

    Batanov, G.M.; Kossyi, I.A.; Matveev, A.A.; Silakov, V.P.

    1996-01-01

    Gas-discharge (microwave) and optical (laser) methods of generating large-scale artificial ozone layers in the stratosphere are analyzed. A kinetic model is developed to calculate the plasma-chemical consequences of discharges localized in the stratosphere. Computations and simple estimates indicate that, in order to implement gas-discharge and optical methods, the operating power of ozone-producing sources should be comparable to or even much higher than the present-day power production throughout the world. Consequently, from the engineering and economic standpoints, microwave and laser methods cannot be used to repair large-scale ozone 'holes'

  4. Estimates of hydroelectric generation using neural networks with the artificial bee colony algorithm for Turkey

    International Nuclear Information System (INIS)

    Uzlu, Ergun; Akpınar, Adem; Özturk, Hasan Tahsin; Nacar, Sinan; Kankal, Murat

    2014-01-01

    The primary objective of this study was to apply the ANN (artificial neural network) model with the ABC (artificial bee colony) algorithm to estimate annual hydraulic energy production of Turkey. GEED (gross electricity energy demand), population, AYT (average yearly temperature), and energy consumption were selected as independent variables in the model. The first part of the study compared ANN-ABC model performance with results of classical ANN models trained with the BP (back propagation) algorithm. Mean square and relative error were applied to evaluate model accuracy. The test set errors emphasized positive differences between the ANN-ABC and classical ANN models. After determining optimal configurations, three different scenarios were developed to predict future hydropower generation values for Turkey. Results showed the ANN-ABC method predicted hydroelectric generation better than the classical ANN trained with the BP algorithm. Furthermore, results indicated future hydroelectric generation in Turkey will range from 69.1 to 76.5 TWh in 2021, and the total annual electricity demand represented by hydropower supply rates will range from 14.8% to 18.0%. However, according to Vision 2023 agenda goals, the country plans to produce 30% of its electricity demand from renewable energy sources by 2023, and use 20% less energy than in 2010. This percentage renewable energy provision cannot be accomplished unless changes in energy policy and investments are not addressed and implemented. In order to achieve this goal, the Turkish government must reconsider and raise its own investments in hydropower, wind, solar, and geothermal energy, particularly hydropower. - Highlights: • This study is associated with predicting hydropower generation in Turkey. • Sensitivity analysis was performed to determine predictor variables. • GEED, population, energy consumption and AYT were used as predictor variables. • ANN-ABC predicted the hydropower generation more accurately

  5. Convergence of a residual based artificial viscosity finite element method

    KAUST Repository

    Nazarov, Murtazo

    2013-02-01

    We present a residual based artificial viscosity finite element method to solve conservation laws. The Galerkin approximation is stabilized by only residual based artificial viscosity, without any least-squares, SUPG, or streamline diffusion terms. We prove convergence of the method, applied to a scalar conservation law in two space dimensions, toward an unique entropy solution for implicit time stepping schemes. © 2012 Elsevier B.V. All rights reserved.

  6. Control Systems for Hyper-Redundant Robots Based on Artificial Potential Method

    Directory of Open Access Journals (Sweden)

    Mihaela Florescu

    2015-06-01

    Full Text Available This paper presents the control method of hyper-redundant robots based on the artificial potential approach. The principles of this method are shown and a suggestive example is offered. Then, the artificial potential method is applied to the case of a tentacle robot starting from the dynamic model of the robot. In addition, a series of results that are obtained through simulation is presented.

  7. Training algorithms evaluation for artificial neural network to temporal prediction of photovoltaic generation

    International Nuclear Information System (INIS)

    Arantes Monteiro, Raul Vitor; Caixeta Guimarães, Geraldo; Rocio Castillo, Madeleine; Matheus Moura, Fabrício Augusto; Tamashiro, Márcio Augusto

    2016-01-01

    Current energy policies are encouraging the connection of power generation based on low-polluting technologies, mainly those using renewable sources, to distribution networks. Hence, it becomes increasingly important to understand technical challenges, facing high penetration of PV systems at the grid, especially considering the effects of intermittence of this source on the power quality, reliability and stability of the electric distribution system. This fact can affect the distribution networks on which they are attached causing overvoltage, undervoltage and frequency oscillations. In order to predict these disturbs, artificial neural networks are used. This article aims to analyze 3 training algorithms used in artificial neural networks for temporal prediction of the generated active power thru photovoltaic panels. As a result it was concluded that the algorithm with the best performance among the 3 analyzed was the Levenberg-Marquadrt.

  8. Multi-Layer Artificial Neural Networks Based MPPT-Pitch Angle Control of a Tidal Stream Generator

    Directory of Open Access Journals (Sweden)

    Khaoula Ghefiri

    2018-04-01

    Full Text Available Artificial intelligence technologies are widely investigated as a promising technique for tackling complex and ill-defined problems. In this context, artificial neural networks methodology has been considered as an effective tool to handle renewable energy systems. Thereby, the use of Tidal Stream Generator (TSG systems aim to provide clean and reliable electrical power. However, the power captured from tidal currents is highly disturbed due to the swell effect and the periodicity of the tidal current phenomenon. In order to improve the quality of the generated power, this paper focuses on the power smoothing control. For this purpose, a novel Artificial Neural Network (ANN is investigated and implemented to provide the proper rotational speed reference and the blade pitch angle. The ANN supervisor adequately switches the system in variable speed and power limitation modes. In order to recover the maximum power from the tides, a rotational speed control is applied to the rotor side converter following the Maximum Power Point Tracking (MPPT generated from the ANN block. In case of strong tidal currents, a pitch angle control is set based on the ANN approach to keep the system operating within safe limits. Two study cases were performed to test the performance of the output power. Simulation results demonstrate that the implemented control strategies achieve a smoothed generated power in the case of swell disturbances.

  9. Alteration of blue pigment in artificial iris in ocular prosthesis: effect of paint, drying method and artificial aging.

    Science.gov (United States)

    Goiato, Marcelo Coelho; Fernandes, Aline Úrsula Rocha; dos Santos, Daniela Micheline; Hadadd, Marcela Filié; Moreno, Amália; Pesqueira, Aldiéris Alves

    2011-02-01

    The artificial iris is the structure responsible for the dissimulation and aesthetics of ocular prosthesis. The objective of the present study was to evaluate the color stability of artificial iris of microwaveable polymerized ocular prosthesis, as a function of paint type, drying method and accelerated aging. A total of 40 discs of microwaveable polymerized acrylic resin were fabricated, and divided according to the blue paint type (n = 5): hydrosoluble acrylic, nitrocellulose automotive, hydrosoluble gouache and oil paints. Paints where dried either at natural or at infrared light bulb method. Each specimen was constituted of one disc in colorless acrylic resin and another colored with a basic sclera pigment. Painting was performed in one surface of one of the discs. The specimens were submitted to an artificial aging chamber under ultraviolet light, during 1008 h. A reflective spectrophotometer was used to evaluate color changes. Data were evaluated by 3-way repeated-measures ANOVA and the Tukey HSD test (α = 0.05). All paints suffered color alteration. The oil paint presented the highest color resistance to artificial aging regardless of drying method. Copyright © 2010 British Contact Lens Association. Published by Elsevier Ltd. All rights reserved.

  10. An improved artificial physical optimization algorithm for dynamic dispatch of generators with valve-point effects and wind power

    International Nuclear Information System (INIS)

    Yuan, Xiaohui; Ji, Bin; Zhang, Shuangquan; Tian, Hao; Chen, Zhihuan

    2014-01-01

    Highlights: • Dynamic load economic dispatch with wind power (DLEDW) model is established. • Markov chains combined with scenario analysis method are used to predict wind power. • Chance constrained technique is used to simulate the impacts of wind forecast error. • Improved artificial physical optimization algorithm is proposed to solve DLEDW. • Heuristic search strategies are applied to handle the constraints of DLEDW. - Abstract: Wind power, a kind of promising renewable energy resource, has recently been getting more attractive because of various environmental and economic considerations. But the penetration of wind power with its fluctuation nature has made the operation of power system more intractable. To coordinate the reliability and operation cost, this paper established a stochastic model of dynamic load economic dispatch with wind integration (DLEDW). In this model, constraints such as ramping up/down capacity, prohibited operating zone are considered and effects of valve-point are taken into account. Markov chains combined with scenario analysis method is used to generate predictive values of wind power and chance constrained programming (CCP) is applied to simulate the impacts of wind power fluctuation on system operation. An improved artificial physical optimization algorithm is presented to solve the DLEDW problem. Heuristic strategies based on the priority list and stochastic simulation techniques are proposed to handle the constraints. In addition, a local chaotic mutation strategy is applied to overcome the disadvantage of premature convergence of artificial physical optimization algorithm. Two test systems with and without wind power integration are used to verify the feasibility and effectiveness of the proposed method and the results are compared with those of gravitational search algorithm, particle swarm optimization and standard artificial physical optimization. The simulation results demonstrate that the proposed method has a

  11. Artificial earthquake record generation using cascade neural network

    Directory of Open Access Journals (Sweden)

    Bani-Hani Khaldoon A.

    2017-01-01

    Full Text Available This paper presents the results of using artificial neural networks (ANN in an inverse mapping problem for earthquake accelerograms generation. This study comprises of two parts: 1-D site response analysis; performed for Dubai Emirate at UAE, where eight earthquakes records are selected and spectral matching are performed to match Dubai response spectrum using SeismoMatch software. Site classification of Dubai soil is being considered for two classes C and D based on shear wave velocity of soil profiles. Amplifications factors are estimated to quantify Dubai soil effect. Dubai’s design response spectra are developed for site classes C & D according to International Buildings Code (IBC -2012. In the second part, ANN is employed to solve inverse mapping problem to generate time history earthquake record. Thirty earthquakes records and their design response spectrum with 5% damping are used to train two cascade forward backward neural networks (ANN1, ANN2. ANN1 is trained to map the design response spectrum to time history and ANN2 is trained to map time history records to the design response spectrum. Generalized time history earthquake records are generated using ANN1 for Dubai’s site classes C and D, and ANN2 is used to evaluate the performance of ANN1.

  12. Artificial intelligence methods applied for quantitative analysis of natural radioactive sources

    International Nuclear Information System (INIS)

    Medhat, M.E.

    2012-01-01

    Highlights: ► Basic description of artificial neural networks. ► Natural gamma ray sources and problem of detections. ► Application of neural network for peak detection and activity determination. - Abstract: Artificial neural network (ANN) represents one of artificial intelligence methods in the field of modeling and uncertainty in different applications. The objective of the proposed work was focused to apply ANN to identify isotopes and to predict uncertainties of their activities of some natural radioactive sources. The method was tested for analyzing gamma-ray spectra emitted from natural radionuclides in soil samples detected by a high-resolution gamma-ray spectrometry based on HPGe (high purity germanium). The principle of the suggested method is described, including, relevant input parameters definition, input data scaling and networks training. It is clear that there is satisfactory agreement between obtained and predicted results using neural network.

  13. Development of a diagnostic expert system for eddy current data analysis using applied artificial intelligence methods

    International Nuclear Information System (INIS)

    Upadhyaya, B.R.; Yan, W.; Henry, G.

    1999-01-01

    A diagnostic expert system that integrates database management methods, artificial neural networks, and decision-making using fuzzy logic has been developed for the automation of steam generator eddy current test (ECT) data analysis. The new system, known as EDDYAI, considers the following key issues: (1) digital eddy current test data calibration, compression, and representation; (2) development of robust neural networks with low probability of misclassification for flaw depth estimation; (3) flaw detection using fuzzy logic; (4) development of an expert system for database management, compilation of a trained neural network library, and a decision module; and (5) evaluation of the integrated approach using eddy current data. The implementation to field test data includes the selection of proper feature vectors for ECT data analysis, development of a methodology for large eddy current database management, artificial neural networks for flaw depth estimation, and a fuzzy logic decision algorithm for flaw detection. A large eddy current inspection database from the Electric Power Research Institute NDE Center is being utilized in this research towards the development of an expert system for steam generator tube diagnosis. The integration of ECT data pre-processing as part of the data management, fuzzy logic flaw detection technique, and tube defect parameter estimation using artificial neural networks are the fundamental contributions of this research. (orig.)

  14. Development of a diagnostic expert system for eddy current data analysis using applied artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Upadhyaya, B.R.; Yan, W. [Tennessee Univ., Knoxville, TN (United States). Dept. of Nuclear Engineering; Behravesh, M.M. [Electric Power Research Institute, Palo Alto, CA (United States); Henry, G. [EPRI NDE Center, Charlotte, NC (United States)

    1999-09-01

    A diagnostic expert system that integrates database management methods, artificial neural networks, and decision-making using fuzzy logic has been developed for the automation of steam generator eddy current test (ECT) data analysis. The new system, known as EDDYAI, considers the following key issues: (1) digital eddy current test data calibration, compression, and representation; (2) development of robust neural networks with low probability of misclassification for flaw depth estimation; (3) flaw detection using fuzzy logic; (4) development of an expert system for database management, compilation of a trained neural network library, and a decision module; and (5) evaluation of the integrated approach using eddy current data. The implementation to field test data includes the selection of proper feature vectors for ECT data analysis, development of a methodology for large eddy current database management, artificial neural networks for flaw depth estimation, and a fuzzy logic decision algorithm for flaw detection. A large eddy current inspection database from the Electric Power Research Institute NDE Center is being utilized in this research towards the development of an expert system for steam generator tube diagnosis. The integration of ECT data pre-processing as part of the data management, fuzzy logic flaw detection technique, and tube defect parameter estimation using artificial neural networks are the fundamental contributions of this research. (orig.)

  15. ALOG user's manual: A Guide to using the spreadsheet-based artificial log generator

    Science.gov (United States)

    Matthew F. Winn; Philip A. Araman; Randolph H. Wynne

    2012-01-01

    Computer programs that simulate log sawing can be valuable training tools for sawyers, as well as a means oftesting different sawing patterns. Most available simulation programs rely on diagrammed-log databases, which canbe very costly and time consuming to develop. Artificial Log Generator (ALOG) is a user-friendly Microsoft® Excel®...

  16. Generation of artificial earthquake time histories for seismic design at Hanford, Washington

    International Nuclear Information System (INIS)

    Salmon, M.W.; Kuilanoff, G.

    1991-01-01

    The purpose of the development of artificial time-histories is to provide the designer with ground motion estimates which will meet the requirements of the design guidelines at the Hanford site. In particular, the artificial time histories presented in this paper were prepared to assist designers of the Hanford Waste Vitrification Plant (HWVP) with time histories that envelop the requirements for both a large magnitude earthquake (MI > 6.0) and a small magnitude, near-field earthquake (MI < 5. 0). A background of the requirements for both the large magnitude and small magnitude events is presented in this paper. The work done in generating time histories which produce response spectra matching those of the design seismic events is also presented. Finally, some preliminary results from studies performed using the small-magnitude near-filed earthquake time-history are presented

  17. Domestic and foreign trends in the prevalence of heart failure and the necessity of next-generation artificial hearts: a survey by the Working Group on Establishment of Assessment Guidelines for Next-Generation Artificial Heart Systems.

    Science.gov (United States)

    Tatsumi, Eisuke; Nakatani, Takeshi; Imachi, Kou; Umezu, Mitsuo; Kyo, Shun-Ei; Sase, Kazuhiro; Takatani, Setsuo; Matsuda, Hikaru

    2007-01-01

    A series of guidelines for development and assessment of next-generation medical devices has been drafted under an interagency collaborative project by the Ministry of Health, Labor and Welfare and the Ministry of Economy, Trade and Industry. The working group for assessment guidelines of next-generation artificial hearts reviewed the trend in the prevalence of heart failure and examined the potential usefulness of such devices in Japan and in other countries as a fundamental part of the process of establishing appropriate guidelines. At present, more than 23 million people suffer from heart failure in developed countries, including Japan. Although Japan currently has the lowest mortality from heart failure among those countries, the number of patients is gradually increasing as our lifestyle becomes more Westernized; the associated medical expenses are rapidly growing. The number of heart transplantations, however, is limited due to the overwhelming shortage of donor hearts, not only in Japan but worldwide. Meanwhile, clinical studies and surveys have revealed that the major causes of death in patients undergoing long-term use of ventricular assist devices (VADs) were infection, thrombosis, and mechanical failure, all of which are typical of VADs. It is therefore of urgent and universal necessity to develop next-generation artificial hearts that have excellent durability to provide at least 2 years of event-free operation with a superior quality of life and that can be used for destination therapy to save patients with irreversible heart failure. It is also very important to ensure that an environment that facilitates the development, testing, and approval evaluation processes of next-generation artificial hearts be established as soon as possible.

  18. Application of artificial intelligence methods for prediction of steel mechanical properties

    Directory of Open Access Journals (Sweden)

    Z. Jančíková

    2008-10-01

    Full Text Available The target of the contribution is to outline possibilities of applying artificial neural networks for the prediction of mechanical steel properties after heat treatment and to judge their perspective use in this field. The achieved models enable the prediction of final mechanical material properties on the basis of decisive parameters influencing these properties. By applying artificial intelligence methods in combination with mathematic-physical analysis methods it will be possible to create facilities for designing a system of the continuous rationalization of existing and also newly developing industrial technologies.

  19. Synthesis of artificial spectrum-compatible seismic accelerograms

    International Nuclear Information System (INIS)

    Vrochidou, E; Alvanitopoulos, P F; Andreadis, I; Mallousi, K; Elenas, A

    2014-01-01

    The Hilbert–Huang transform is used to generate artificial seismic signals compatible with the acceleration spectra of natural seismic records. Artificial spectrum-compatible accelerograms are utilized instead of natural earthquake records for the dynamic response analysis of many critical structures such as hospitals, bridges, and power plants. The realistic estimation of the seismic response of structures involves nonlinear dynamic analysis. Moreover, it requires seismic accelerograms representative of the actual ground acceleration time histories expected at the site of interest. Unfortunately, not many actual records of different seismic intensities are available for many regions. In addition, a large number of seismic accelerograms are required to perform a series of nonlinear dynamic analyses for a reliable statistical investigation of the structural behavior under earthquake excitation. These are the main motivations for generating artificial spectrum-compatible seismic accelerograms and could be useful in earthquake engineering for dynamic analysis and design of buildings. According to the proposed method, a single natural earthquake record is deconstructed into amplitude and frequency components using the Hilbert–Huang transform. The proposed method is illustrated by studying 20 natural seismic records with different characteristics such as different frequency content, amplitude, and duration. Experimental results reveal the efficiency of the proposed method in comparison with well-established and industrial methods in the literature. (paper)

  20. Image Signal Transfer Method in Artificial Retina using Laser

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, I.Y.; Lee, B.H.; Kim, S.J. [Seoul National University, Seoul (Korea)

    2002-05-01

    Recently, the research on artificial retina for the blind is active. In this paper a new optical link method for the retinal prosthesis is proposed. Laser diode system was chosen to transfer image into the eye in this project and the new optical system was designed and evaluated. The use of laser diode array in artificial retina system makes system simple for lack of signal processing part inside of the eyeball. Designed optical system is enough to focus laser diode array on photodiode array in 20X20 application. (author). 11 refs., 7 figs., 2 tabs.

  1. Artificial Association of Pre-stored Information to Generate a Qualitatively New Memory

    Directory of Open Access Journals (Sweden)

    Noriaki Ohkawa

    2015-04-01

    Full Text Available Memory is thought to be stored in the brain as an ensemble of cells activated during learning. Although optical stimulation of a cell ensemble triggers the retrieval of the corresponding memory, it is unclear how the association of information occurs at the cell ensemble level. Using optogenetic stimulation without any sensory input in mice, we found that an artificial association between stored, non-related contextual, and fear information was generated through the synchronous activation of distinct cell ensembles corresponding to the stored information. This artificial association shared characteristics with physiologically associated memories, such as N-methyl-D-aspartate receptor activity and protein synthesis dependence. These findings suggest that the association of information is achieved through the synchronous activity of distinct cell ensembles. This mechanism may underlie memory updating by incorporating novel information into pre-existing networks to form qualitatively new memories.

  2. An experimental investigation of artificial supercavitation generated by air injection behind disk-shaped cavitators

    Directory of Open Access Journals (Sweden)

    Byoung-Kwon Ahn

    2017-03-01

    Full Text Available In this paper, we investigated physical characteristics of an artificial supercavity generated behind an axisymmetric cavitator. Experiments for the same model were carried out at two different cavitation tunnels of the Chungnam National University and the University of Minnesota, and the results were compared and verified with each other. We measured pressures inside the cavity and observed the cavity formation by using a high-speed camera. Cavitation parameters were evaluated in considering blockage effects of the tunnel, and gravitational effects on supercavity dimensions were examined. Cavity dimensions corresponding to the unbounded cavitation number were compared. In addition, we investigated how artificial supercavitation develops according to the combination of injection positions and direction.

  3. In vivo generation of a mature and functional artificial skeletal muscle.

    Science.gov (United States)

    Fuoco, Claudia; Rizzi, Roberto; Biondo, Antonella; Longa, Emanuela; Mascaro, Anna; Shapira-Schweitzer, Keren; Kossovar, Olga; Benedetti, Sara; Salvatori, Maria L; Santoleri, Sabrina; Testa, Stefano; Bernardini, Sergio; Bottinelli, Roberto; Bearzi, Claudia; Cannata, Stefano M; Seliktar, Dror; Cossu, Giulio; Gargioli, Cesare

    2015-04-01

    Extensive loss of skeletal muscle tissue results in mutilations and severe loss of function. In vitro-generated artificial muscles undergo necrosis when transplanted in vivo before host angiogenesis may provide oxygen for fibre survival. Here, we report a novel strategy based upon the use of mouse or human mesoangioblasts encapsulated inside PEG-fibrinogen hydrogel. Once engineered to express placental-derived growth factor, mesoangioblasts attract host vessels and nerves, contributing to in vivo survival and maturation of newly formed myofibres. When the graft was implanted underneath the skin on the surface of the tibialis anterior, mature and aligned myofibres formed within several weeks as a complete and functional extra muscle. Moreover, replacing the ablated tibialis anterior with PEG-fibrinogen-embedded mesoangioblasts also resulted in an artificial muscle very similar to a normal tibialis anterior. This strategy opens the possibility for patient-specific muscle creation for a large number of pathological conditions involving muscle tissue wasting. © 2015 The Authors. Published under the terms of the CC BY 4.0 license.

  4. A study on measurement on artificial radiation dose rate using the response matrix method

    International Nuclear Information System (INIS)

    Kidachi, Hiroshi; Ishikawa, Yoichi; Konno, Tatsuya

    2004-01-01

    We examined accuracy and stability of estimated artificial dose contribution which is distinguished from natural background gamma-ray dose rate using Response Matrix method. Irradiation experiments using artificial gamma-ray sources indicated that there was a linear relationship between observed dose rate and estimated artificial dose contribution, when irradiated artificial gamma-ray dose rate was higher than about 2 nGy/h. Statistical and time-series analyses of long term data made it clear that estimated artificial contribution showed almost constant values under no artificial influence from the nuclear power plants. However, variations of estimated artificial dose contribution were infrequently observed due to of rainfall, detector maintenance operation and occurrence of calibration error. Some considerations on the factors to these variations were made. (author)

  5. A REVIEW OF VIBRATION MACHINE DIAGNOSTICS BY USING ARTIFICIAL INTELLIGENCE METHODS

    Directory of Open Access Journals (Sweden)

    Grover Zurita

    2016-09-01

    Full Text Available In the industry, gears and rolling bearings failures are one of the foremost causes of breakdown in rotating machines, reducing availability time of the production and resulting in costly systems downtime. Therefore, there are growing demands for vibration condition based monitoring of gears and bearings, and any method in order to improve the effectiveness, reliability, and accuracy of the bearing faults diagnosis ought to be evaluated. In order to perform machine diagnosis efficiently, researchers have extensively investigated different advanced digital signal processing techniques and artificial intelligence methods to accurately extract fault characteristics from vibration signals. The main goal of this article is to present the state-of-the-art development in vibration analysis for machine diagnosis based on artificial intelligence methods.

  6. Using artificial intelligence methods to design new conducting polymers

    Directory of Open Access Journals (Sweden)

    Ronaldo Giro

    2003-12-01

    Full Text Available In the last years the possibility of creating new conducting polymers exploring the concept of copolymerization (different structural monomeric units has attracted much attention from experimental and theoretical points of view. Due to the rich carbon reactivity an almost infinite number of new structures is possible and the procedure of trial and error has been the rule. In this work we have used a methodology able of generating new structures with pre-specified properties. It combines the use of negative factor counting (NFC technique with artificial intelligence methods (genetic algorithms - GAs. We present the results for a case study for poly(phenylenesulfide phenyleneamine (PPSA, a copolymer formed by combination of homopolymers: polyaniline (PANI and polyphenylenesulfide (PPS. The methodology was successfully applied to the problem of obtaining binary up to quinternary disordered polymeric alloys with a pre-specific gap value or exhibiting metallic properties. It is completely general and can be in principle adapted to the design of new classes of materials with pre-specified properties.

  7. Comparison between Two Methods for Diagnosis of Trichinellosis: Trichinoscopy and Artificial Digestion

    Directory of Open Access Journals (Sweden)

    María Laura Vignau

    1997-09-01

    Full Text Available Two direct methods for the diagnosis of trichinellosis were compared: trichinoscopy and artificial digestion. Muscles from 17 wistar rats, orally infected with 500 Trichinella spiralis encysted larvae were examined. From each of the following muscles: diaphragm, tongue, masseters, intercostals, triceps brachialis and cuadriceps femoralis, 648,440 larvae from 1 g samples were recovered. The linear correlation between trichinoscopy and artificial digestion was very high and significant (r=0.94, p< 0.0001, showing that both methods for the detection of muscular larvae did not differ significantly. In both methods, significant differences were found in the distribution of larvae per gramme of muscle

  8. Optimal design of permanent magnet flux switching generator for wind applications via artificial neural network and multi-objective particle swarm optimization hybrid approach

    International Nuclear Information System (INIS)

    Meo, Santolo; Zohoori, Alireza; Vahedi, Abolfazl

    2016-01-01

    Highlights: • A new optimal design of flux switching permanent magnet generator is developed. • A prototype is employed to validate numerical data used for optimization. • A novel hybrid multi-objective particle swarm optimization approach is proposed. • Optimization targets are weight, cost, voltage and its total harmonic distortion. • The hybrid approach preference is proved compared with other optimization methods. - Abstract: In this paper a new hybrid approach obtained combining a multi-objective particle swarm optimization and artificial neural network is proposed for the design optimization of a direct-drive permanent magnet flux switching generators for low power wind applications. The targets of the proposed multi-objective optimization are to reduce the costs and weight of the machine while maximizing the amplitude of the induced voltage as well as minimizing its total harmonic distortion. The permanent magnet width, the stator and rotor tooth width, the rotor teeth number and stator pole number of the machine define the search space for the optimization problem. Four supervised artificial neural networks are designed for modeling the complex relationships among the weight, the cost, the amplitude and the total harmonic distortion of the output voltage respect to the quantities of the search space. Finite element analysis is adopted to generate training dataset for the artificial neural networks. Finite element analysis based model is verified by experimental results with a 1.5 kW permanent magnet flux switching generator prototype suitable for renewable energy applications, having 6/19 stator poles/rotor teeth. Finally the effectiveness of the proposed hybrid procedure is compared with the results given by conventional multi-objective optimization algorithms. The obtained results show the soundness of the proposed multi objective optimization technique and its feasibility to be adopted as suitable methodology for optimal design of permanent

  9. Epigenetic Tracking, a Method to Generate Arbitrary Shapes By Using Evolutionary-Developmental Techniques

    OpenAIRE

    Fontana, Alessandro

    2008-01-01

    This paper describes an Artificial Embryology method (called ``Epigenetic Tracking'') to generate predefined arbitrarily shaped 2-dimensional arrays of cells by means of evolutionary techniques. It is based on a model of development, whose key features are: i) the distinction bewteen ``normal'' and ``driver'' cells, being the latter able to receive guidance from the genome, ii) the implementation of the proliferation/apoptosis events in such a way that many cells are created/deleted at once, ...

  10. Path-Wise Test Data Generation Based on Heuristic Look-Ahead Methods

    Directory of Open Access Journals (Sweden)

    Ying Xing

    2014-01-01

    Full Text Available Path-wise test data generation is generally considered an important problem in the automation of software testing. In essence, it is a constraint optimization problem, which is often solved by search methods such as backtracking algorithms. In this paper, the backtracking algorithm branch and bound and state space search in artificial intelligence are introduced to tackle the problem of path-wise test data generation. The former is utilized to explore the space of potential solutions and the latter is adopted to construct the search tree dynamically. Heuristics are employed in the look-ahead stage of the search. Dynamic variable ordering is presented with a heuristic rule to break ties, values of a variable are determined by the monotonicity analysis on branching conditions, and maintaining path consistency is achieved through analysis on the result of interval arithmetic. An optimization method is also proposed to reduce the search space. The results of empirical experiments show that the search is conducted in a basically backtrack-free manner, which ensures both test data generation with promising performance and its excellence over some currently existing static and dynamic methods in terms of coverage. The results also demonstrate that the proposed method is applicable in engineering.

  11. An Opening Chapter of the First Generation of Artificial Intelligence in Medicine: The First Rutgers AIM Workshop, June 1975

    Science.gov (United States)

    2015-01-01

    Summary The first generation of Artificial Intelligence (AI) in Medicine methods were developed in the early 1970’s drawing on insights about problem solving in AI. They developed new ways of representing structured expert knowledge about clinical and biomedical problems using causal, taxonomic, associational, rule, and frame-based models. By 1975, several prototype systems had been developed and clinically tested, and the Rutgers Research Resource on Computers in Biomedicine hosted the first in a series of workshops on AI in Medicine that helped researchers and clinicians share their ideas, demonstrate their models, and comment on the prospects for the field. These developments and the workshops themselves benefited considerably from Stanford’s SUMEX-AIM pioneering experiment in biomedical computer networking. This paper focuses on discussions about issues at the intersection of medicine and artificial intelligence that took place during the presentations and panels at the First Rutgers AIM Workshop in New Brunswick, New Jersey from June 14 to 17, 1975. PMID:26123911

  12. An Opening Chapter of the First Generation of Artificial Intelligence in Medicine: The First Rutgers AIM Workshop, June 1975.

    Science.gov (United States)

    Kulikowski, C A

    2015-08-13

    The first generation of Artificial Intelligence (AI) in Medicine methods were developed in the early 1970's drawing on insights about problem solving in AI. They developed new ways of representing structured expert knowledge about clinical and biomedical problems using causal, taxonomic, associational, rule, and frame-based models. By 1975, several prototype systems had been developed and clinically tested, and the Rutgers Research Resource on Computers in Biomedicine hosted the first in a series of workshops on AI in Medicine that helped researchers and clinicians share their ideas, demonstrate their models, and comment on the prospects for the field. These developments and the workshops themselves benefited considerably from Stanford's SUMEX-AIM pioneering experiment in biomedical computer networking. This paper focuses on discussions about issues at the intersection of medicine and artificial intelligence that took place during the presentations and panels at the First Rutgers AIM Workshop in New Brunswick, New Jersey from June 14 to 17, 1975.

  13. An example of the use of the DELPHI method: future prospects of artificial heart techniques in France

    International Nuclear Information System (INIS)

    Derian, Jean-Claude; Morize, Francoise; Vernejoul, Pierre de; Vial, Renee

    1971-01-01

    The artificial heart is still only a research project surrounded by numerous uncertainties which make it very difficult to estimate, at the moment, the possibilities for future development of this technique in France. A systematic analysis of the hazards which characterize this project has been undertaken in the following report: restricting these uncertainties has required a taking into account of opinions of specialists concerned with type of research or its upshot. We have achieved this by adapting an investigation technique which is still unusual in France, the DELPHI method. This adaptation has allowed the confrontation and statistical aggregation of the opinions given by a body of a hundred experts who were consulted through a program of sequential interrogations which studied in particular, the probable date of the research issue, the clinical cases which require the use of an artificial heart, as well as the probable future needs. After having taken into account the economic constraints, we can deduce from these results the probable amount of plutonium 238 needed in the hypothesis where isotopic generator would be retained for the energetics feeding of the artificial heart [fr

  14. FPGA controlled artificial vascular system

    Directory of Open Access Journals (Sweden)

    Laqua D.

    2015-09-01

    Full Text Available Monitoring the oxygen saturation of an unborn child is an invasive procedure, so far. Transabdominal fetal pulse oximetry is a promising method under research, used to estimate the oxygen saturation of a fetus noninvasively. Due to the nature of the method, the fetal information needs to be extracted from a mixed signal. To properly evaluate signal processing algorithms, a phantom modeling fetal and maternal blood circuits and tissue layers is necessary. This paper presents an improved hardware concept for an artificial vascular system, utilizing an FPGA based CompactRIO System from National Instruments. The experimental model to simulate the maternal and fetal blood pressure curve consists of two identical hydraulic circuits. Each of these circuits consists of a pre-pressure system and an artificial vascular system. Pulse curves are generated by proportional valves, separating these two systems. The dilation of the fetal and maternal artificial vessels in tissue substitutes is measured by transmissive and reflective photoplethysmography. The measurement results from the pressure sensors and the transmissive optical sensors are visualized to show the functionality of the pulse generating systems. The trigger frequency for the maternal valve was set to 1 per second, the fetal valve was actuated at 0.7 per second for validation. The reflective curve, capturing pulsations of the fetal and maternal circuit, was obtained with a high power LED (905 nm as light source. The results show that the system generates pulse curves, similar to its physiological equivalent. Further, the acquired reflective optical signal is modulated by the alternating diameter of the tubes of both circuits, allowing for tests of signal processing algorithms.

  15. Application of artificial intelligence to the management of urological cancer.

    Science.gov (United States)

    Abbod, Maysam F; Catto, James W F; Linkens, Derek A; Hamdy, Freddie C

    2007-10-01

    Artificial intelligence techniques, such as artificial neural networks, Bayesian belief networks and neuro-fuzzy modeling systems, are complex mathematical models based on the human neuronal structure and thinking. Such tools are capable of generating data driven models of biological systems without making assumptions based on statistical distributions. A large amount of study has been reported of the use of artificial intelligence in urology. We reviewed the basic concepts behind artificial intelligence techniques and explored the applications of this new dynamic technology in various aspects of urological cancer management. A detailed and systematic review of the literature was performed using the MEDLINE and Inspec databases to discover reports using artificial intelligence in urological cancer. The characteristics of machine learning and their implementation were described and reports of artificial intelligence use in urological cancer were reviewed. While most researchers in this field were found to focus on artificial neural networks to improve the diagnosis, staging and prognostic prediction of urological cancers, some groups are exploring other techniques, such as expert systems and neuro-fuzzy modeling systems. Compared to traditional regression statistics artificial intelligence methods appear to be accurate and more explorative for analyzing large data cohorts. Furthermore, they allow individualized prediction of disease behavior. Each artificial intelligence method has characteristics that make it suitable for different tasks. The lack of transparency of artificial neural networks hinders global scientific community acceptance of this method but this can be overcome by neuro-fuzzy modeling systems.

  16. An evaluation of an organically bound tritium measurement method in artificial and natural urine

    International Nuclear Information System (INIS)

    Trivedi, A.; Duong, T.

    1993-03-01

    The accurate measurement of tritium in urine in the form of tritiated water (HTO) as well as in organic forms (organically bound tritium (OBT)) is an essential step in assessing tritium exposures correctly. Exchange between HTO and OBT, arising intrinsically in the separation of HTO from urine samples, is a source of error in determining the concentration of OBT using the low-temperature distillation (LTD) bioassay method. The accuracy and precision of OBT measurements using the LTD method was investigated using spiked natural and artificial urine samples. The relative bias for most of the measurements was less than 25%. The choice of testing matrix, artificial urine versus human urine, made little difference: the precisions for each urine type were similar. The appropriateness of the use of artificial urine for testing purposes was judged using a ratio of performance indices. Based on this evaluation, the artificial urine is a suitable test matrix for intercomparisons of OBT in urine measurements. It is further concluded that the LTD method is reliable for measuring OBT in urine samples. (author). 7 refs., 6 tabs

  17. An evaluation of an organically bound tritium measurement method in artificial and natural urine

    Energy Technology Data Exchange (ETDEWEB)

    Trivedi, A; Duong, T

    1993-03-01

    The accurate measurement of tritium in urine in the form of tritiated water (HTO) as well as in organic forms (organically bound tritium (OBT)) is an essential step in assessing tritium exposures correctly. Exchange between HTO and OBT, arising intrinsically in the separation of HTO from urine samples, is a source of error in determining the concentration of OBT using the low-temperature distillation (LTD) bioassay method. The accuracy and precision of OBT measurements using the LTD method was investigated using spiked natural and artificial urine samples. The relative bias for most of the measurements was less than 25%. The choice of testing matrix, artificial urine versus human urine, made little difference: the precisions for each urine type were similar. The appropriateness of the use of artificial urine for testing purposes was judged using a ratio of performance indices. Based on this evaluation, the artificial urine is a suitable test matrix for intercomparisons of OBT in urine measurements. It is further concluded that the LTD method is reliable for measuring OBT in urine samples. (author). 7 refs., 6 tabs.

  18. Spatial capture-recapture: a promising method for analyzing data collected using artificial cover objects

    Science.gov (United States)

    Sutherland, Chris; Munoz, David; Miller, David A.W.; Grant, Evan H. Campbell

    2016-01-01

    Spatial capture–recapture (SCR) is a relatively recent development in ecological statistics that provides a spatial context for estimating abundance and space use patterns, and improves inference about absolute population density. SCR has been applied to individual encounter data collected noninvasively using methods such as camera traps, hair snares, and scat surveys. Despite the widespread use of capture-based surveys to monitor amphibians and reptiles, there are few applications of SCR in the herpetological literature. We demonstrate the utility of the application of SCR for studies of reptiles and amphibians by analyzing capture–recapture data from Red-Backed Salamanders, Plethodon cinereus, collected using artificial cover boards. Using SCR to analyze spatial encounter histories of marked individuals, we found evidence that density differed little among four sites within the same forest (on average, 1.59 salamanders/m2) and that salamander detection probability peaked in early October (Julian day 278) reflecting expected surface activity patterns of the species. The spatial scale of detectability, a measure of space use, indicates that the home range size for this population of Red-Backed Salamanders in autumn was 16.89 m2. Surveying reptiles and amphibians using artificial cover boards regularly generates spatial encounter history data of known individuals, which can readily be analyzed using SCR methods, providing estimates of absolute density and inference about the spatial scale of habitat use.

  19. Three-dimensional imaging of artificial fingerprint by optical coherence tomography

    Science.gov (United States)

    Larin, Kirill V.; Cheng, Yezeng

    2008-03-01

    Fingerprint recognition is one of the popular used methods of biometrics. However, due to the surface topography limitation, fingerprint recognition scanners are easily been spoofed, e.g. using artificial fingerprint dummies. Thus, biometric fingerprint identification devices need to be more accurate and secure to deal with different fraudulent methods including dummy fingerprints. Previously, we demonstrated that Optical Coherence Tomography (OCT) images revealed the presence of the artificial fingerprints (made from different household materials, such as cement and liquid silicone rubber) at all times, while the artificial fingerprints easily spoofed the commercial fingerprint reader. Also we demonstrated that an analysis of the autocorrelation of the OCT images could be used in automatic recognition systems. Here, we exploited the three-dimensional (3D) imaging of the artificial fingerprint by OCT to generate vivid 3D image for both the artificial fingerprint layer and the real fingerprint layer beneath. With the reconstructed 3D image, it could not only point out whether there exists an artificial material, which is intended to spoof the scanner, above the real finger, but also could provide the hacker's fingerprint. The results of these studies suggested that Optical Coherence Tomography could be a powerful real-time noninvasive method for accurate identification of artificial fingerprints real fingerprints as well.

  20. Generation of tactile maps for artificial skin.

    Directory of Open Access Journals (Sweden)

    Simon McGregor

    Full Text Available Prior research has shown that representations of retinal surfaces can be learned from the intrinsic structure of visual sensory data in neural simulations, in robots, as well as by animals. Furthermore, representations of cochlear (frequency surfaces can be learned from auditory data in neural simulations. Advances in hardware technology have allowed the development of artificial skin for robots, realising a new sensory modality which differs in important respects from vision and audition in its sensorimotor characteristics. This provides an opportunity to further investigate ordered sensory map formation using computational tools. We show that it is possible to learn representations of non-trivial tactile surfaces, which require topologically and geometrically involved three-dimensional embeddings. Our method automatically constructs a somatotopic map corresponding to the configuration of tactile sensors on a rigid body, using only intrinsic properties of the tactile data. The additional complexities involved in processing the tactile modality require the development of a novel multi-dimensional scaling algorithm. This algorithm, ANISOMAP, extends previous methods and outperforms them, producing high-quality reconstructions of tactile surfaces in both simulation and hardware tests. In addition, the reconstruction turns out to be robust to unanticipated hardware failure.

  1. Simulation of CO2 Solubility in Polystyrene-b-Polybutadieneb-Polystyrene (SEBS) by artificial intelligence network (ANN) method

    Science.gov (United States)

    Sharudin, R. W.; AbdulBari Ali, S.; Zulkarnain, M.; Shukri, M. A.

    2018-05-01

    This study reports on the integration of Artificial Neural Network (ANNs) with experimental data in predicting the solubility of carbon dioxide (CO2) blowing agent in SEBS by generating highest possible value for Regression coefficient (R2). Basically, foaming of thermoplastic elastomer with CO2 is highly affected by the CO2 solubility. The ability of ANN in predicting interpolated data of CO2 solubility was investigated by comparing training results via different method of network training. Regards to the final prediction result for CO2 solubility by ANN, the prediction trend (output generate) was corroborated with the experimental results. The obtained result of different method of training showed the trend of output generated by Gradient Descent with Momentum & Adaptive LR (traingdx) required longer training time and required more accurate input to produce better output with final Regression Value of 0.88. However, it goes vice versa with Levenberg-Marquardt (trainlm) technique as it produced better output in quick detention time with final Regression Value of 0.91.

  2. Humans can consciously generate random number sequences: a possible test for artificial intelligence.

    Science.gov (United States)

    Persaud, Navindra

    2005-01-01

    Computer algorithms can only produce seemingly random or pseudorandom numbers whereas certain natural phenomena, such as the decay of radioactive particles, can be utilized to produce truly random numbers. In this study, the ability of humans to generate random numbers was tested in healthy adults. Subjects were simply asked to generate and dictate random numbers. Generated numbers were tested for uniformity, independence and information density. The results suggest that humans can generate random numbers that are uniformly distributed, independent of one another and unpredictable. If humans can generate sequences of random numbers then neural networks or forms of artificial intelligence, which are purported to function in ways essentially the same as the human brain, should also be able to generate sequences of random numbers. Elucidating the precise mechanism by which humans generate random number sequences and the underlying neural substrates may have implications in the cognitive science of decision-making. It is possible that humans use their random-generating neural machinery to make difficult decisions in which all expected outcomes are similar. It is also possible that certain people, perhaps those with neurological or psychiatric impairments, are less able or unable to generate random numbers. If the random-generating neural machinery is employed in decision making its impairment would have profound implications in matters of agency and free will.

  3. Large artificially generated turbulent boundary layers for the study of atmospheric flows

    International Nuclear Information System (INIS)

    Guimaraes, Joao Henrique D.; Santos Junior, Sergio J.F. dos; Freire, Atila P. Silva; Jian, Su

    1999-01-01

    The present work discusses in detail the experimental conditions for the establishment of thick artificially generated turbulent boundary layer which can be classified as having the near characteristics of an atmospheric boundary layer. The paper describes the experimental arrangement, including the features of the designed wind tunnel and of the instrumentation. the boundary layer is made to develop over a surface fitted with wedge generators which are used to yield a very thick boundary layer. The flow conditions were validated against the following features: growth, structure, equilibrium and turbulent transport momentum. Results are presented for the following main flow variables: mean velocity, local skin-friction coefficient, boundary layer momentum thickness and the Clauser factor. The velocity boundary layer characteristics were shown to be in good agreement with the expected trend in view of the classical expressions found in literature. (author)

  4. A Model of Artificial Genotype and Norm of Reaction in a Robotic System

    OpenAIRE

    Durán Bosch, Ángel Juan; Pascual del Pobil Ferré, Ángel

    2016-01-01

    The genes of living organisms serve as large stores of information for replicating their behavior and morphology over generations. The evolutionary view of genetics that has inspired artificial systems with a Mendelian approach does not take into account the interaction between species and with the environment to generate a particular phenotype. In this paper, a genotype model is suggested to shape the relationship with the phenotype and the environment in an artificial system. A method to ob...

  5. Fluid-driven origami-inspired artificial muscles

    Science.gov (United States)

    Li, Shuguang; Vogt, Daniel M.; Rus, Daniela; Wood, Robert J.

    2017-12-01

    Artificial muscles hold promise for safe and powerful actuation for myriad common machines and robots. However, the design, fabrication, and implementation of artificial muscles are often limited by their material costs, operating principle, scalability, and single-degree-of-freedom contractile actuation motions. Here we propose an architecture for fluid-driven origami-inspired artificial muscles. This concept requires only a compressible skeleton, a flexible skin, and a fluid medium. A mechanical model is developed to explain the interaction of the three components. A fabrication method is introduced to rapidly manufacture low-cost artificial muscles using various materials and at multiple scales. The artificial muscles can be programed to achieve multiaxial motions including contraction, bending, and torsion. These motions can be aggregated into systems with multiple degrees of freedom, which are able to produce controllable motions at different rates. Our artificial muscles can be driven by fluids at negative pressures (relative to ambient). This feature makes actuation safer than most other fluidic artificial muscles that operate with positive pressures. Experiments reveal that these muscles can contract over 90% of their initial lengths, generate stresses of ˜600 kPa, and produce peak power densities over 2 kW/kg—all equal to, or in excess of, natural muscle. This architecture for artificial muscles opens the door to rapid design and low-cost fabrication of actuation systems for numerous applications at multiple scales, ranging from miniature medical devices to wearable robotic exoskeletons to large deployable structures for space exploration.

  6. An experimental investigation of artificial supercavitation generated by air injection behind disk-shaped cavitators

    OpenAIRE

    Ahn, Byoung-Kwon; Jeong, So-Won; Kim, Ji-Hye; Shao, Siyao; Hong, Jiarong; Arndt, Roger E.A.

    2017-01-01

    In this paper, we investigated physical characteristics of an artificial supercavity generated behind an axisymmetric cavitator. Experiments for the same model were carried out at two different cavitation tunnels of the Chungnam National University and the University of Minnesota, and the results were compared and verified with each other. We measured pressures inside the cavity and observed the cavity formation by using a high-speed camera. Cavitation parameters were evaluated in considering...

  7. Operation optimization of distributed generation using artificial intelligent techniques

    Directory of Open Access Journals (Sweden)

    Mahmoud H. Elkazaz

    2016-06-01

    Full Text Available Future smart grids will require an observable, controllable and flexible network architecture for reliable and efficient energy delivery. The use of artificial intelligence and advanced communication technologies is essential in building a fully automated system. This paper introduces a new technique for online optimal operation of distributed generation (DG resources, i.e. a hybrid fuel cell (FC and photovoltaic (PV system for residential applications. The proposed technique aims to minimize the total daily operating cost of a group of residential homes by managing the operation of embedded DG units remotely from a control centre. The target is formed as an objective function that is solved using genetic algorithm (GA optimization technique. The optimal settings of the DG units obtained from the optimization process are sent to each DG unit through a fully automated system. The results show that the proposed technique succeeded in defining the optimal operating points of the DGs that affect directly the total operating cost of the entire system.

  8. An artificial neural network model for periodic trajectory generation

    Science.gov (United States)

    Shankar, S.; Gander, R. E.; Wood, H. C.

    A neural network model based on biological systems was developed for potential robotic application. The model consists of three interconnected layers of artificial neurons or units: an input layer subdivided into state and plan units, an output layer, and a hidden layer between the two outer layers which serves to implement nonlinear mappings between the input and output activation vectors. Weighted connections are created between the three layers, and learning is effected by modifying these weights. Feedback connections between the output and the input state serve to make the network operate as a finite state machine. The activation vector of the plan units of the input layer emulates the supraspinal commands in biological central pattern generators in that different plan activation vectors correspond to different sequences or trajectories being recalled, even with different frequencies. Three trajectories were chosen for implementation, and learning was accomplished in 10,000 trials. The fault tolerant behavior, adaptiveness, and phase maintenance of the implemented network are discussed.

  9. Entropy generation and thermodynamic analysis of solar air heaters with artificial roughness on absorber plate

    Directory of Open Access Journals (Sweden)

    Prasad Radha K.

    2017-09-01

    Full Text Available This paper presents mathematical modelling and numerical analysis to evaluate entropy generation analysis (EGA by considering pressure drop and second law efficiency based on thermodynamics for forced convection heat transfer in rectangular duct of a solar air heater with wire as artificial roughness in the form of arc shape geometry on the absorber plate. The investigation includes evaluations of entropy generation, entropy generation number, Bejan number and irreversibilities of roughened as well as smooth absorber plate solar air heaters to compare the relative performances. Furthermore, effects of various roughness parameters and operating parameters on entropy generation have also been investigated. Entropy generation and irreversibilities (exergy destroyed has its minimum value at relative roughness height of 0.0422 and relative angle of attack of 0.33, which leads to the maximum exergetic efficiency. Entropy generation and exergy based analyses can be adopted for the evaluation of the overall performance of solar air heaters.

  10. Artificial Bee Colony Algorithm for Transient Performance Augmentation of Grid Connected Distributed Generation

    Science.gov (United States)

    Chatterjee, A.; Ghoshal, S. P.; Mukherjee, V.

    In this paper, a conventional thermal power system equipped with automatic voltage regulator, IEEE type dual input power system stabilizer (PSS) PSS3B and integral controlled automatic generation control loop is considered. A distributed generation (DG) system consisting of aqua electrolyzer, photovoltaic cells, diesel engine generator, and some other energy storage devices like flywheel energy storage system and battery energy storage system is modeled. This hybrid distributed system is connected to the grid. While integrating this DG with the onventional thermal power system, improved transient performance is noticed. Further improvement in the transient performance of this grid connected DG is observed with the usage of superconducting magnetic energy storage device. The different tunable parameters of the proposed hybrid power system model are optimized by artificial bee colony (ABC) algorithm. The optimal solutions offered by the ABC algorithm are compared with those offered by genetic algorithm (GA). It is also revealed that the optimizing performance of the ABC is better than the GA for this specific application.

  11. Automatic modulation format recognition for the next generation optical communication networks using artificial neural networks

    Science.gov (United States)

    Guesmi, Latifa; Hraghi, Abir; Menif, Mourad

    2015-03-01

    A new technique for Automatic Modulation Format Recognition (AMFR) in next generation optical communication networks is presented. This technique uses the Artificial Neural Network (ANN) in conjunction with the features of Linear Optical Sampling (LOS) of the detected signal at high bit rates using direct detection or coherent detection. The use of LOS method for this purpose mainly driven by the increase of bit rates which enables the measurement of eye diagrams. The efficiency of this technique is demonstrated under different transmission impairments such as chromatic dispersion (CD) in the range of -500 to 500 ps/nm, differential group delay (DGD) in the range of 0-15 ps and the optical signal tonoise ratio (OSNR) in the range of 10-30 dB. The results of numerical simulation for various modulation formats demonstrate successful recognition from a known bit rates with a higher estimation accuracy, which exceeds 99.8%.

  12. A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series

    Science.gov (United States)

    Wang, Wen-Chuan; Chau, Kwok-Wing; Cheng, Chun-Tian; Qiu, Lin

    2009-08-01

    SummaryDeveloping a hydrological forecasting model based on past records is crucial to effective hydropower reservoir management and scheduling. Traditionally, time series analysis and modeling is used for building mathematical models to generate hydrologic records in hydrology and water resources. Artificial intelligence (AI), as a branch of computer science, is capable of analyzing long-series and large-scale hydrological data. In recent years, it is one of front issues to apply AI technology to the hydrological forecasting modeling. In this paper, autoregressive moving-average (ARMA) models, artificial neural networks (ANNs) approaches, adaptive neural-based fuzzy inference system (ANFIS) techniques, genetic programming (GP) models and support vector machine (SVM) method are examined using the long-term observations of monthly river flow discharges. The four quantitative standard statistical performance evaluation measures, the coefficient of correlation ( R), Nash-Sutcliffe efficiency coefficient ( E), root mean squared error (RMSE), mean absolute percentage error (MAPE), are employed to evaluate the performances of various models developed. Two case study river sites are also provided to illustrate their respective performances. The results indicate that the best performance can be obtained by ANFIS, GP and SVM, in terms of different evaluation criteria during the training and validation phases.

  13. Dissolution and reactive oxygen species generation of inhaled cemented tungsten carbide particles in artificial human lung fluids

    International Nuclear Information System (INIS)

    Stefaniak, A B; Leonard, S S; Hoover, M D; Virji, M A; Day, G A

    2009-01-01

    Inhalation of both cobalt (Co) and tungsten carbide (WC) particles is associated with development of hard metal lung disease (HMD) via generation of reactive oxygen species (ROS), whereas Co alone is sufficient to cause asthma via solubilization and hapten formation. We characterized bulk and aerodynamically size-separated W, WC, Co, spray dryer (pre-sintered), and chamfer grinder (post-sintered) powders. ROS generation was measured in the murine RAW 264.7 cell line using electron spin resonance. When dose was normalized to surface area, hydroxyl radical generation was independent of particle size, which suggests that particle surface chemistry may be an important exposure factor. Chamfer grinder particles generated the highest levels of ROS, consistent with the hypothesis that intimate contact of metals is important for ROS generation. In artificial extracellular lung fluid, alkylbenzyldimethylammonium chloride (ABDC), added to prevent mold growth during experiments, did not influence dissolution of Co (44.0±5.2 vs. 48.3±6.4%); however, dissolution was higher (p<0.05) in the absence of phosphate (62.0±5.4 vs. 48.3±6.4%). In artificial macrophage phagolysosomal fluid, dissolution of Co (36.2±10.4%) does not appear to be influenced (p=0.30) by the absence of glycine (29.8±2.1%), phosphate (39.6±8.6%), or ABDC (44.0±10.5%). These results aid in assessing and understanding Co and W inhalation dosimetry.

  14. Artificial neural network intelligent method for prediction

    Science.gov (United States)

    Trifonov, Roumen; Yoshinov, Radoslav; Pavlova, Galya; Tsochev, Georgi

    2017-09-01

    Accounting and financial classification and prediction problems are high challenge and researchers use different methods to solve them. Methods and instruments for short time prediction of financial operations using artificial neural network are considered. The methods, used for prediction of financial data as well as the developed forecasting system with neural network are described in the paper. The architecture of a neural network used four different technical indicators, which are based on the raw data and the current day of the week is presented. The network developed is used for forecasting movement of stock prices one day ahead and consists of an input layer, one hidden layer and an output layer. The training method is algorithm with back propagation of the error. The main advantage of the developed system is self-determination of the optimal topology of neural network, due to which it becomes flexible and more precise The proposed system with neural network is universal and can be applied to various financial instruments using only basic technical indicators as input data.

  15. Fluid-driven origami-inspired artificial muscles.

    Science.gov (United States)

    Li, Shuguang; Vogt, Daniel M; Rus, Daniela; Wood, Robert J

    2017-12-12

    Artificial muscles hold promise for safe and powerful actuation for myriad common machines and robots. However, the design, fabrication, and implementation of artificial muscles are often limited by their material costs, operating principle, scalability, and single-degree-of-freedom contractile actuation motions. Here we propose an architecture for fluid-driven origami-inspired artificial muscles. This concept requires only a compressible skeleton, a flexible skin, and a fluid medium. A mechanical model is developed to explain the interaction of the three components. A fabrication method is introduced to rapidly manufacture low-cost artificial muscles using various materials and at multiple scales. The artificial muscles can be programed to achieve multiaxial motions including contraction, bending, and torsion. These motions can be aggregated into systems with multiple degrees of freedom, which are able to produce controllable motions at different rates. Our artificial muscles can be driven by fluids at negative pressures (relative to ambient). This feature makes actuation safer than most other fluidic artificial muscles that operate with positive pressures. Experiments reveal that these muscles can contract over 90% of their initial lengths, generate stresses of ∼600 kPa, and produce peak power densities over 2 kW/kg-all equal to, or in excess of, natural muscle. This architecture for artificial muscles opens the door to rapid design and low-cost fabrication of actuation systems for numerous applications at multiple scales, ranging from miniature medical devices to wearable robotic exoskeletons to large deployable structures for space exploration. Copyright © 2017 the Author(s). Published by PNAS.

  16. Handwritten Javanese Character Recognition Using Several Artificial Neural Network Methods

    Directory of Open Access Journals (Sweden)

    Gregorius Satia Budhi

    2015-07-01

    Full Text Available Javanese characters are traditional characters that are used to write the Javanese language. The Javanese language is a language used by many people on the island of Java, Indonesia. The use of Javanese characters is diminishing more and more because of the difficulty of studying the Javanese characters themselves. The Javanese character set consists of basic characters, numbers, complementary characters, and so on. In this research we have developed a system to recognize Javanese characters. Input for the system is a digital image containing several handwritten Javanese characters. Preprocessing and segmentation are performed on the input image to get each character. For each character, feature extraction is done using the ICZ-ZCZ method. The output from feature extraction will become input for an artificial neural network. We used several artificial neural networks, namely a bidirectional associative memory network, a counterpropagation network, an evolutionary network, a backpropagation network, and a backpropagation network combined with chi2. From the experimental results it can be seen that the combination of chi2 and backpropagation achieved better recognition accuracy than the other methods.

  17. 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.

  18. Proposed guidelines for synthetic accelerogram generation methods

    International Nuclear Information System (INIS)

    Shaw, D.E.; Rizzo, P.C.; Shukla, D.K.

    1975-01-01

    With the advent of high speed digital computation machines and discrete structural analysis techniques, it has become attractive to use synthetically generated accelerograms as input in the seismic design and analysis of structures. Several procedures are currently available which can generate accelerograms which match a given design response spectra while not paying significant attention to other properties of seismic accelerograms. This paper studies currently available artificial time history generation techniques from the standpoint of various properties of seismic time histories consisting of; 1. Response Spectra; 2. Peak Ground Acceleration; 3. Total Duration; 4. Time dependent enveloping functions defining the rise time to strong motion, duration of significant shaking and decay of the significant shaking portion of the seismic record; 5. Fourier Amplitude and Phase Spectra; 6. Ground Motion Parameters; 7. Apparent Frequency; with the aim of providing guidelines of the time history parameters based on historic strong motion seismic records. (Auth.)

  19. A study on the advanced methods for on-line signal processing by using artificial intelligence in nuclear power plants

    International Nuclear Information System (INIS)

    Kim, Wan Joo

    1993-02-01

    signals in a certain time interval for reducing the loads of the fusion part. The simulation results of LOCA in the simulator are demonstrated for the classification of the signal trend. The demonstration is performed for the transient states of a steam generator. Using the fuzzy memberships, the pre-processors classify the trend types in each time interval into three classes; increase, decrease, and steady that are fuzzy to classify. The result compared with the artificial neural network which has no pre-processor shows that the training time is reduced and the outputs are seldom influenced by noises. Because most knowledge of human operators include fuzzy concepts and words, the method like this is very helpful for computerizing the buman expert's knowledge

  20. A Rapid and Improved Method to Generate Recombinant Dengue Virus Vaccine Candidates.

    Science.gov (United States)

    Govindarajan, Dhanasekaran; Guan, Liming; Meschino, Steven; Fridman, Arthur; Bagchi, Ansu; Pak, Irene; ter Meulen, Jan; Casimiro, Danilo R; Bett, Andrew J

    2016-01-01

    Dengue is one of the most important mosquito-borne infections accounting for severe morbidity and mortality worldwide. Recently, the tetravalent chimeric live attenuated Dengue vaccine Dengvaxia® was approved for use in several dengue endemic countries. In general, live attenuated vaccines (LAV) are very efficacious and offer long-lasting immunity against virus-induced disease. Rationally designed LAVs can be generated through reverse genetics technology, a method of generating infectious recombinant viruses from full length cDNA contained in bacterial plasmids. In vitro transcribed (IVT) viral RNA from these infectious clones is transfected into susceptible cells to generate recombinant virus. However, the generation of full-length dengue virus cDNA clones can be difficult due to the genetic instability of viral sequences in bacterial plasmids. To circumvent the need for a single plasmid containing a full length cDNA, in vitro ligation of two or three cDNA fragments contained in separate plasmids can be used to generate a full-length dengue viral cDNA template. However, in vitro ligation of multiple fragments often yields low quality template for IVT reactions, resulting in inconsistent low yield RNA. These technical difficulties make recombinant virus recovery less efficient. In this study, we describe a simple, rapid and efficient method of using LONG-PCR to recover recombinant chimeric Yellow fever dengue (CYD) viruses as potential dengue vaccine candidates. Using this method, we were able to efficiently generate several viable recombinant viruses without introducing any artificial mutations into the viral genomes. We believe that the techniques reported here will enable rapid and efficient recovery of recombinant flaviviruses for evaluation as vaccine candidates and, be applicable to the recovery of other RNA viruses.

  1. Characterisation of PV CIS module by artificial neural networks. A comparative study with other methods

    International Nuclear Information System (INIS)

    Almonacid, F.; Rus, C.; Hontoria, L.; Munoz, F.J.

    2010-01-01

    The presence of PV modules made with new technologies and materials is increasing in PV market, in special Thin Film Solar Modules (TFSM). They are ready to make a substantial contribution to the world's electricity generation. Although Si wafer-based cells account for the most of increase, technologies of thin film have been those of the major growth in last three years. During 2007 they grew 133%. On the other hand, manufacturers provide ratings for PV modules for conditions referred to as Standard Test Conditions (STC). However, these conditions rarely occur outdoors, so the usefulness and applicability of the indoors characterisation in standard test conditions of PV modules is a controversial issue. Therefore, to carry out a correct photovoltaic engineering, a suitable characterisation of PV module electrical behaviour is necessary. The IDEA Research Group from Jaen University has developed a method based on artificial neural networks (ANNs) to electrical characterisation of PV modules. An ANN was able to generate V-I curves of si-crystalline PV modules for any irradiance and module cell temperature. The results show that the proposed ANN introduces a good accurate prediction for si-crystalline PV modules performance when compared with the measured values. Now, this method is going to be applied for electrical characterisation of PV CIS modules. Finally, a comparative study with other methods, of electrical characterisation, is done. (author)

  2. Optimal reactive power and voltage control in distribution networks with distributed generators by fuzzy adaptive hybrid particle swarm optimisation method

    DEFF Research Database (Denmark)

    Chen, Shuheng; Hu, Weihao; Su, Chi

    2015-01-01

    A new and efficient methodology for optimal reactive power and voltage control of distribution networks with distributed generators based on fuzzy adaptive hybrid PSO (FAHPSO) is proposed. The objective is to minimize comprehensive cost, consisting of power loss and operation cost of transformers...... that the proposed method can search a more promising control schedule of all transformers, all capacitors and all distributed generators with less time consumption, compared with other listed artificial intelligent methods....... algorithm is implemented in VC++ 6.0 program language and the corresponding numerical experiments are finished on the modified version of the IEEE 33-node distribution system with two newly installed distributed generators and eight newly installed capacitors banks. The numerical results prove...

  3. A Small-Satellite Demonstrator for Generating Artificial Gravity in Space via a Tethered System

    OpenAIRE

    Mazzoleni, Andre; Hoffman, John

    2002-01-01

    It is well-known that prolonged exposure in humans to a microgravity environment leads to significant loss of bone and muscle mass; this presents a formidable obstacle to human exploration of space, particularly for missions requiring travel times of several months or more, such as a 6 to 9mon th trip to Mars. Artificial gravity may be produced by spinning a spacecraft about its center of mass, but since the g– force generated by rotation is equal to “omega-squared times r” (where omega is it...

  4. Methods for Creation and Detection of Ultra-Strong Artificial Ionization in the Upper Atmosphere (Invited)

    Science.gov (United States)

    Bernhardt, P. A.; Siefring, C. L.; Briczinski, S. J.; Kendall, E. A.; Watkins, B. J.; Bristow, W. A.; Michell, R.

    2013-12-01

    The High Frequency Active Auroral Research Program (HAARP) transmitter in Alaska has been used to produce localized regions of artificial ionization at altitudes between 150 and 250 km. High power radio waves tuned near harmonics of the electron gyro frequency were discovered by Todd Pederson of the Air Force Research Laboratory to produce ionosonde traces that looked like artificial ionization layers below the natural F-region. The initial regions of artificial ionization (AI) were not stable but had moved down in altitude over a period of 15 minutes. Recently, artificial ionization has been produced by the 2nd, 3rd, 4th and 6th harmonics transmissions by the HAARP. In march 2013, the artificial ionization clouds were sustained for more the 5 hours using HAARP tuned to the 4 fce at the full power of 3.6 Mega-Watts with a twisted-beam antenna pattern. Frequency selection with narrow-band sweeps and antenna pattern shaping has been employed for optimal generation of AI. Recent research at HAARP has produced the longest lived and denser artificial ionization clouds using HF transmissions at the harmonics of the electron cyclotron frequency and ring-shaped radio beams tailored to prevent the descent of the clouds. Detection of artificial ionization employs (1) ionosonde echoes, (2) coherent backscatter from the Kodiak SuperDARN radar, (3) enhanced ion and plasma line echoes from the HAARP MUIR radar at 400 MHz, (4) high resolution optical image from ground sites, and (5) unique stimulated electromagnetic emissions, and (6) strong UHF and L-Band scintillation induced into trans-ionospheric signals from satellite radio beacons. Future HAARP experiments will determine the uses of long-sustained AI for enhanced HF communications.

  5. Dynamic cardiomyoplasty using artificial muscle.

    Science.gov (United States)

    Suzuki, Yasuyuki; Daitoku, Kazuyuki; Minakawa, Masahito; Fukui, Kozo; Fukuda, Ikuo

    2008-01-01

    Dynamic cardiomyoplasty using latissimus dorsi muscle was previously used to compensate for congestive heart failure. Now, however, this method is not acceptable because the long-term result was not as expected owing to fatigue of the skeletal muscle. BioMetal fiber developed by Toki Corporation is one of the artificial muscles activated by electric current. The behavior of this fiber is similar to that of organic muscle. We made an artificial muscle like the latissimus dorsi using BioMetal fiber and tested whether we could use this new muscle as a cardiac supporting device. Testing one Biometal fiber showed the following performance: practical use maximal generative force was 30 g, exercise variation was 50%, and the standard driving current was 220 mA. We created a 4 x 12-cm tabular artificial muscle using 8 BioMetal fibers as a cardiac support device. We also made a simulation circuit composed of a 6 x 8-cm soft bag with unidirectional valves, reservoir, and connecting tube. The simulation circuit was filled with water and the soft bag was wrapped with the artificial muscle device. After powering the device electrically at 9 V with a current of 220 mA for each fiber, we measured the inside pressure and observed the movement of the artificial device. The artificial muscle contracted in 0.5 s for peak time and squeezed the soft bag. The peak pressure inside the soft bag was measured as 10 mmHg. Although further work will be needed to enhance the speed of deformability and movement simulating contraction, we conclude that artificial muscle may be potentially useful as a cardiac assistance device that can be developed for dynamic cardiomyoplasty.

  6. Grid generation methods

    CERN Document Server

    Liseikin, Vladimir D

    2017-01-01

    This new edition provides a description of current developments relating to grid methods, grid codes, and their applications to actual problems. Grid generation methods are indispensable for the numerical solution of differential equations. Adaptive grid-mapping techniques, in particular, are the main focus and represent a promising tool to deal with systems with singularities. This 3rd edition includes three new chapters on numerical implementations (10), control of grid properties (11), and applications to mechanical, fluid, and plasma related problems (13). Also the other chapters have been updated including new topics, such as curvatures of discrete surfaces (3). Concise descriptions of hybrid mesh generation, drag and sweeping methods, parallel algorithms for mesh generation have been included too. This new edition addresses a broad range of readers: students, researchers, and practitioners in applied mathematics, mechanics, engineering, physics and other areas of applications.

  7. Novel method to load multiple genes onto a mammalian artificial chromosome.

    Directory of Open Access Journals (Sweden)

    Anna Tóth

    Full Text Available Mammalian artificial chromosomes are natural chromosome-based vectors that may carry a vast amount of genetic material in terms of both size and number. They are reasonably stable and segregate well in both mitosis and meiosis. A platform artificial chromosome expression system (ACEs was earlier described with multiple loading sites for a modified lambda-integrase enzyme. It has been shown that this ACEs is suitable for high-level industrial protein production and the treatment of a mouse model for a devastating human disorder, Krabbe's disease. ACEs-treated mutant mice carrying a therapeutic gene lived more than four times longer than untreated counterparts. This novel gene therapy method is called combined mammalian artificial chromosome-stem cell therapy. At present, this method suffers from the limitation that a new selection marker gene should be present for each therapeutic gene loaded onto the ACEs. Complex diseases require the cooperative action of several genes for treatment, but only a limited number of selection marker genes are available and there is also a risk of serious side-effects caused by the unwanted expression of these marker genes in mammalian cells, organs and organisms. We describe here a novel method to load multiple genes onto the ACEs by using only two selectable marker genes. These markers may be removed from the ACEs before therapeutic application. This novel technology could revolutionize gene therapeutic applications targeting the treatment of complex disorders and cancers. It could also speed up cell therapy by allowing researchers to engineer a chromosome with a predetermined set of genetic factors to differentiate adult stem cells, embryonic stem cells and induced pluripotent stem (iPS cells into cell types of therapeutic value. It is also a suitable tool for the investigation of complex biochemical pathways in basic science by producing an ACEs with several genes from a signal transduction pathway of interest.

  8. Novel method to load multiple genes onto a mammalian artificial chromosome.

    Science.gov (United States)

    Tóth, Anna; Fodor, Katalin; Praznovszky, Tünde; Tubak, Vilmos; Udvardy, Andor; Hadlaczky, Gyula; Katona, Robert L

    2014-01-01

    Mammalian artificial chromosomes are natural chromosome-based vectors that may carry a vast amount of genetic material in terms of both size and number. They are reasonably stable and segregate well in both mitosis and meiosis. A platform artificial chromosome expression system (ACEs) was earlier described with multiple loading sites for a modified lambda-integrase enzyme. It has been shown that this ACEs is suitable for high-level industrial protein production and the treatment of a mouse model for a devastating human disorder, Krabbe's disease. ACEs-treated mutant mice carrying a therapeutic gene lived more than four times longer than untreated counterparts. This novel gene therapy method is called combined mammalian artificial chromosome-stem cell therapy. At present, this method suffers from the limitation that a new selection marker gene should be present for each therapeutic gene loaded onto the ACEs. Complex diseases require the cooperative action of several genes for treatment, but only a limited number of selection marker genes are available and there is also a risk of serious side-effects caused by the unwanted expression of these marker genes in mammalian cells, organs and organisms. We describe here a novel method to load multiple genes onto the ACEs by using only two selectable marker genes. These markers may be removed from the ACEs before therapeutic application. This novel technology could revolutionize gene therapeutic applications targeting the treatment of complex disorders and cancers. It could also speed up cell therapy by allowing researchers to engineer a chromosome with a predetermined set of genetic factors to differentiate adult stem cells, embryonic stem cells and induced pluripotent stem (iPS) cells into cell types of therapeutic value. It is also a suitable tool for the investigation of complex biochemical pathways in basic science by producing an ACEs with several genes from a signal transduction pathway of interest.

  9. A Rapid and Improved Method to Generate Recombinant Dengue Virus Vaccine Candidates.

    Directory of Open Access Journals (Sweden)

    Dhanasekaran Govindarajan

    Full Text Available Dengue is one of the most important mosquito-borne infections accounting for severe morbidity and mortality worldwide. Recently, the tetravalent chimeric live attenuated Dengue vaccine Dengvaxia® was approved for use in several dengue endemic countries. In general, live attenuated vaccines (LAV are very efficacious and offer long-lasting immunity against virus-induced disease. Rationally designed LAVs can be generated through reverse genetics technology, a method of generating infectious recombinant viruses from full length cDNA contained in bacterial plasmids. In vitro transcribed (IVT viral RNA from these infectious clones is transfected into susceptible cells to generate recombinant virus. However, the generation of full-length dengue virus cDNA clones can be difficult due to the genetic instability of viral sequences in bacterial plasmids. To circumvent the need for a single plasmid containing a full length cDNA, in vitro ligation of two or three cDNA fragments contained in separate plasmids can be used to generate a full-length dengue viral cDNA template. However, in vitro ligation of multiple fragments often yields low quality template for IVT reactions, resulting in inconsistent low yield RNA. These technical difficulties make recombinant virus recovery less efficient. In this study, we describe a simple, rapid and efficient method of using LONG-PCR to recover recombinant chimeric Yellow fever dengue (CYD viruses as potential dengue vaccine candidates. Using this method, we were able to efficiently generate several viable recombinant viruses without introducing any artificial mutations into the viral genomes. We believe that the techniques reported here will enable rapid and efficient recovery of recombinant flaviviruses for evaluation as vaccine candidates and, be applicable to the recovery of other RNA viruses.

  10. Artificial neural networks versus conventional methods for boiling water reactor stability monitoring

    International Nuclear Information System (INIS)

    Hagen, T.H.J.J. van der

    1995-01-01

    The application of an artificial neural network (ANN) for boiling water reactor (BWR) stability monitoring was studied. A three-layer perceptron was trained on synthetic autocorrelation functions to estimate the decay ratio and the resonance frequency from measured neutron noise. Training of the ANN was improved by adding noise to the training patterns and by applying nonconventional error definitions in the generalized delta rule. The performance of the developed ANN was compared with those of conventional stability monitoring techniques. Explicit care was taken for generating unbiased test data. It is found that the trained ANN is capable of monitoring the stability of the Dodewaard BWR for four specific cases. By comparing properties such as the false alarm ratio, the alarm failure ratio, and the average time to alarm, it is shown that it performs worse than model-based methods in stability monitoring of exact second-order systems but that it is more robust (better resistant to corruptions of the input data and to deviations of the system at issue from an exact second-order system) than other methods. The latter explains its good performance on the Dodewaard BWR and is promising for the application of an ANN for stability monitoring of other reactors and for other operating conditions

  11. An active artificial cornea with the function of inducing new corneal tissue generation in vivo-a new approach to corneal tissue engineering

    International Nuclear Information System (INIS)

    Huang Yaoxiong; Li Qinhua

    2007-01-01

    An active artificial cornea which can perform the function of inducing new cornea generation in vivo but does not need culture cells in vitro and which has similar optical and mechanical properties to those of the human cornea was constructed. An animal keratoplasty experiment using the artificial cornea as the implant showed that the animals' corneas could keep smooth surface and clear stroma postoperatively, and that the repopulation of the host's keratocytes, the degradation of the implant and new corneal tissue generation were completed at 5-6 months after surgery. Such an artificial cornea has several advantages over other corneal equivalents constructed in the typical way of tissue engineering: in having similar mechanical and optical properties to those of the human cornea and with no exogenetic cells, it can be used universally in different implantation surgeries without immunoreaction; it is easy to prepare and process into different shapes and sizes on a large scale, and suitable for long-distance transportation and long-term storage. All these characteristics make it a new approach to cornea tissue engineering having potential in many clinical applications

  12. Generation of an artificial skin construct containing a non-degradable fiber mesh: a potential transcutaneous interface

    Energy Technology Data Exchange (ETDEWEB)

    Cahn, Frederick [Biomedical Strategies Inc., San Diego, CA (United States); Kyriakides, Themis R [Vascular Biology and Therapeutics, Yale University, New Haven, CT 06536-9812 (United States)], E-mail: themis.kyriakides@yale.edu

    2008-09-01

    Generation of a stable interface between soft tissues and biomaterials could improve the function of transcutaneous prostheses, primarily by minimizing chronic infections. We hypothesized that inclusion of non-biodegradable biomaterials in an artificial skin substrate would improve integration of the neodermis. In the present study, we compared the biocompatibility of an experimental substrate, consisting of collagen and glycosylaminoglycans, with commercially available artificial skin of similar composition. By utilizing a mouse excisional wound model, we found that the source of collagen (bovine tendon versus hide), extent of injury and wound contraction were critical determinants of inflammation and neodermis formation. Reducing the extent of injury to underlying muscle reduced inflammation and improved remodeling; the improved conditions allowed the detection of a pro-inflammatory effect of hide-derived collagen. To eliminate the complication of wound contraction, subsequent grafts were performed in guinea pigs and showed that inclusion of carbon fibers or non-degradable sutures resulted in increased foreign body response (FBR) and altered remodeling. On the other hand, inclusion of a polyester multi-stranded mesh induced a mild FBR and allowed normal neodermis formation. Taken together, our observations suggest that non-degradable biomaterials can be embedded in an artificial skin construct without compromising its ability to induce neodermis formation.

  13. Artificially lengthened and constricted vocal tract in vocal training methods.

    Science.gov (United States)

    Bele, Irene Velsvik

    2005-01-01

    It is common practice in vocal training to make use of vocal exercise techniques that involve partial occlusion of the vocal tract. Various techniques are used; some of them form an occlusion within the front part of the oral cavity or at the lips. Another vocal exercise technique involves lengthening the vocal tract; for example, the method of phonation into small tubes. This essay presents some studies made on the effects of various vocal training methods that involve an artificially lengthened and constricted vocal tract. The influence of sufficient acoustic impedance on vocal fold vibration and economical voice production is presented.

  14. Magnetohydrodynamic generation method

    International Nuclear Information System (INIS)

    Masai, Tadahisa; Ishibashi, Eiichi; Kojima, Akihiro.

    1967-01-01

    The present invention relates to a magneto-hydrodynamic generation method which increases the conductivity of active gas and the generated energy. In the conventional method of open-cycle magnetohydrodynamic generation, the working fluid does not possess a favorable electric conductivity since the collision cross section is large when the combustion is carried out in a condition of excess oxygen. Furthermore, combustion under a condition of oxygen shortage is uncapable of completely converting the generated energy. The air preheater or boiler is not sufficient to collect the waste gas resulting in damage and other economic disadvantages. In the present invention, the combustion gas caused by excess fuel in the combuster is supplied to the generator as the working gas, to which air or fully oxidized air is added to be reheated. While incomplete gas used for heat collection is not adequate, the unburned damage may be eliminated by combusting again and increasing the gas temperature and heat collection rate. Furthermore, a diffuser is mounted at the rear side of the generator to decrease the gas combustion rate. Thus, even when directly absorbing the preheated fully oxidized air or the ordinary air, the boiler is free from damage caused by combustion delay or impulsive force. (M. Ishida)

  15. Efficient Load Scheduling Method For Power Management

    Directory of Open Access Journals (Sweden)

    Vijo M Joy

    2015-08-01

    Full Text Available An efficient load scheduling method to meet varying power supply needs is presented in this paper. At peak load times the power generation system fails due to its instability. Traditionally we use load shedding process. In load shedding process disconnect the unnecessary and extra loads. The proposed method overcomes this problem by scheduling the load based on the requirement. Artificial neural networks are used for this optimal load scheduling process. For generate economic scheduling artificial neural network has been used because generation of power from each source is economically different. In this the total load required is the inputs of this network and the power generation from each source and power losses at the time of transmission are the output of the neural network. Training and programming of the artificial neural networks are done using MATLAB.

  16. Engineering applications of fpgas chaotic systems, artificial neural networks, random number generators, and secure communication systems

    CERN Document Server

    Tlelo-Cuautle, Esteban; de la Fraga, Luis Gerardo

    2016-01-01

    This book offers readers a clear guide to implementing engineering applications with FPGAs, from the mathematical description to the hardware synthesis, including discussion of VHDL programming and co-simulation issues. Coverage includes FPGA realizations such as: chaos generators that are described from their mathematical models; artificial neural networks (ANNs) to predict chaotic time series, for which a discussion of different ANN topologies is included, with different learning techniques and activation functions; random number generators (RNGs) that are realized using different chaos generators, and discussions of their maximum Lyapunov exponent values and entropies. Finally, optimized chaotic oscillators are synchronized and realized to implement a secure communication system that processes black and white and grey-scale images. In each application, readers will find VHDL programming guidelines and computer arithmetic issues, along with co-simulation examples with Active-HDL and Simulink. Readers will b...

  17. De Novo Design of Bioactive Small Molecules by Artificial Intelligence.

    Science.gov (United States)

    Merk, Daniel; Friedrich, Lukas; Grisoni, Francesca; Schneider, Gisbert

    2018-01-01

    Generative artificial intelligence offers a fresh view on molecular design. We present the first-time prospective application of a deep learning model for designing new druglike compounds with desired activities. For this purpose, we trained a recurrent neural network to capture the constitution of a large set of known bioactive compounds represented as SMILES strings. By transfer learning, this general model was fine-tuned on recognizing retinoid X and peroxisome proliferator-activated receptor agonists. We synthesized five top-ranking compounds designed by the generative model. Four of the compounds revealed nanomolar to low-micromolar receptor modulatory activity in cell-based assays. Apparently, the computational model intrinsically captured relevant chemical and biological knowledge without the need for explicit rules. The results of this study advocate generative artificial intelligence for prospective de novo molecular design, and demonstrate the potential of these methods for future medicinal chemistry. © 2018 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

  18. Hybrid Wing Body Shielding Studies Using an Ultrasonic Configurable Fan Artificial Noise Source Generating Simple Modes

    Science.gov (United States)

    Sutliff, Daniel, L.; Brown, Clifford, A.; Walker, Bruce, E.

    2012-01-01

    An Ultrasonic Configurable Fan Artificial Noise Source (UCFANS) was designed, built, and tested in support of the Langley Research Center s 14- by 22-Foot wind tunnel test of the Hybrid Wing Body (HWB) full three-dimensional 5.8 percent scale model. The UCFANS is a 5.8 percent rapid prototype scale model of a high-bypass turbofan engine that can generate the tonal signature of candidate engines using artificial sources (no flow). The purpose of the test was to provide an estimate of the acoustic shielding benefits possible from mounting the engine on the upper surface of an HWB aircraft and to provide a database for shielding code validation. A range of frequencies, and a parametric study of modes were generated from exhaust and inlet nacelle configurations. Radiated acoustic data were acquired from a traversing linear array of 13 microphones, spanning 36 in. Two planes perpendicular to the axis of the nacelle (in its 0 orientation) and three planes parallel were acquired from the array sweep. In each plane the linear array traversed five sweeps, for a total span of 160 in. acquired. The resolution of the sweep is variable, so that points closer to the model are taken at a higher resolution. Contour plots of Sound Pressure Level, and integrated Power Levels are presented in this paper; as well as the in-duct modal structure.

  19. Artificial life and Piaget.

    Science.gov (United States)

    Mueller, Ulrich; Grobman, K H.

    2003-04-01

    Artificial life provides important theoretical and methodological tools for the investigation of Piaget's developmental theory. This new method uses artificial neural networks to simulate living phenomena in a computer. A recent study by Parisi and Schlesinger suggests that artificial life might reinvigorate the Piagetian framework. We contrast artificial life with traditional cognitivist approaches, discuss the role of innateness in development, and examine the relation between physiological and psychological explanations of intelligent behaviour.

  20. SOLVING TRANSPORT LOGISTICS PROBLEMS IN A VIRTUAL ENTERPRISE THROUGH ARTIFICIAL INTELLIGENCE METHODS

    OpenAIRE

    PAVLENKO, Vitaliy; PAVLENKO, Tetiana; MOROZOVA, Olga; KUZNETSOVA, Anna; VOROPAI, Olena

    2017-01-01

    The paper offers a solution to the problem of material flow allocation within a virtual enterprise by using artificial intelligence methods. The research is based on the use of fuzzy relations when planning for optimal transportation modes to deliver components for manufactured products. The Fuzzy Logic Toolbox is used to determine the optimal route for transportation of components for manufactured products. The methods offered have been exemplified in the present research. The authors have b...

  1. Nanomaterials with enzyme-like characteristics (nanozymes): next-generation artificial enzymes.

    Science.gov (United States)

    Wei, Hui; Wang, Erkang

    2013-07-21

    Over the past few decades, researchers have established artificial enzymes as highly stable and low-cost alternatives to natural enzymes in a wide range of applications. A variety of materials including cyclodextrins, metal complexes, porphyrins, polymers, dendrimers and biomolecules have been extensively explored to mimic the structures and functions of naturally occurring enzymes. Recently, some nanomaterials have been found to exhibit unexpected enzyme-like activities, and great advances have been made in this area due to the tremendous progress in nano-research and the unique characteristics of nanomaterials. To highlight the progress in the field of nanomaterial-based artificial enzymes (nanozymes), this review discusses various nanomaterials that have been explored to mimic different kinds of enzymes. We cover their kinetics, mechanisms and applications in numerous fields, from biosensing and immunoassays, to stem cell growth and pollutant removal. We also summarize several approaches to tune the activities of nanozymes. Finally, we make comparisons between nanozymes and other catalytic materials (other artificial enzymes, natural enzymes, organic catalysts and nanomaterial-based catalysts) and address the current challenges and future directions (302 references).

  2. Autonomously Generating Operations Sequences for a Mars Rover Using Artificial Intelligence-Based Planning

    Science.gov (United States)

    Sherwood, R.; Mutz, D.; Estlin, T.; Chien, S.; Backes, P.; Norris, J.; Tran, D.; Cooper, B.; Rabideau, G.; Mishkin, A.; Maxwell, S.

    2001-07-01

    This article discusses a proof-of-concept prototype for ground-based automatic generation of validated rover command sequences from high-level science and engineering activities. This prototype is based on ASPEN, the Automated Scheduling and Planning Environment. This artificial intelligence (AI)-based planning and scheduling system will automatically generate a command sequence that will execute within resource constraints and satisfy flight rules. An automated planning and scheduling system encodes rover design knowledge and uses search and reasoning techniques to automatically generate low-level command sequences while respecting rover operability constraints, science and engineering preferences, environmental predictions, and also adhering to hard temporal constraints. This prototype planning system has been field-tested using the Rocky 7 rover at JPL and will be field-tested on more complex rovers to prove its effectiveness before transferring the technology to flight operations for an upcoming NASA mission. Enabling goal-driven commanding of planetary rovers greatly reduces the requirements for highly skilled rover engineering personnel. This in turn greatly reduces mission operations costs. In addition, goal-driven commanding permits a faster response to changes in rover state (e.g., faults) or science discoveries by removing the time-consuming manual sequence validation process, allowing rapid "what-if" analyses, and thus reducing overall cycle times.

  3. Evaluation and scoring of radiotherapy treatment plans using an artificial neural network

    International Nuclear Information System (INIS)

    Willoughby, Twyla R.; Starkschall, George; Janjan, Nora A.; Rosen, Isaac I.

    1996-01-01

    Purpose: The objective of this work was to demonstrate the feasibility of using an artificial neural network to predict the clinical evaluation of radiotherapy treatment plans. Methods and Materials: Approximately 150 treatment plans were developed for 16 patients who received external-beam radiotherapy for soft-tissue sarcomas of the lower extremity. Plans were assigned a figure of merit by a radiation oncologist using a five-point rating scale. Plan scoring was performed by a single physician to ensure consistency in rating. Dose-volume information extracted from a training set of 511 treatment plans on 14 patients was correlated to the physician-generated figure of merit using an artificial neural network. The neural network was tested with a test set of 19 treatment plans on two patients whose plans were not used in the training of the neural net. Results: Physician scoring of treatment plans was consistent to within one point on the rating scale 88% of the time. The neural net reproduced the physician scores in the training set to within one point approximately 90% of the time. It reproduced the physician scores in the test set to within one point approximately 83% of the time. Conclusions: An artificial neural network can be trained to generate a score for a treatment plan that can be correlated to a clinically-based figure of merit. The accuracy of the neural net in scoring plans compares well with the reproducibility of the clinical scoring. The system of radiotherapy treatment plan evaluation using an artificial neural network demonstrates promise as a method for generating a clinically relevant figure of merit

  4. An artificial intelligence (AI) NOx/heat rate optimization system for Ontario Hydro`s fossil generating stations

    Energy Technology Data Exchange (ETDEWEB)

    Luk, J.; Frank, A.; Bodach, P. [Ontario Hydro, Toronto, ON (Canada); Warriner, G. [Radian International, Tucker, GA (United States); Noblett, J. [Radian International, Austin, TX (United States); Slatsky, M. [Southern Company, Birmingham, AL (United States)

    1999-08-01

    Artificial intelligence (AI)-based software packages which can optimize power plant operations that improves heat rate and also reduces nitrogen oxide emissions are now commonly available for commercial use. This paper discusses the implementation of the AI-based NOx and Heat Rate Optimization System at Ontario Hydro`s generation stations, emphasizing the current AI Optimization Project at Units 5 and 6 of the Lakeview Generating Station. These demonstration programs are showing promising results in NOx reduction and plant performance improvement. The availability of the plant Digital Control System (DCS) in implementing AI optimization in a closed-loop system was shown to be an important criterion for success. Implementation of AI technology at other Ontario Hydro fossil generating units as part of the overall NOx emission reduction system is envisaged to coincide with the retrofit of the original plant control system with the latest DCS systems. 14 refs., 3 figs.

  5. Determination of feature generation methods for PTZ camera object tracking

    Science.gov (United States)

    Doyle, Daniel D.; Black, Jonathan T.

    2012-06-01

    Object detection and tracking using computer vision (CV) techniques have been widely applied to sensor fusion applications. Many papers continue to be written that speed up performance and increase learning of artificially intelligent systems through improved algorithms, workload distribution, and information fusion. Military application of real-time tracking systems is becoming more and more complex with an ever increasing need of fusion and CV techniques to actively track and control dynamic systems. Examples include the use of metrology systems for tracking and measuring micro air vehicles (MAVs) and autonomous navigation systems for controlling MAVs. This paper seeks to contribute to the determination of select tracking algorithms that best track a moving object using a pan/tilt/zoom (PTZ) camera applicable to both of the examples presented. The select feature generation algorithms compared in this paper are the trained Scale-Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF), the Mixture of Gaussians (MoG) background subtraction method, the Lucas- Kanade optical flow method (2000) and the Farneback optical flow method (2003). The matching algorithm used in this paper for the trained feature generation algorithms is the Fast Library for Approximate Nearest Neighbors (FLANN). The BSD licensed OpenCV library is used extensively to demonstrate the viability of each algorithm and its performance. Initial testing is performed on a sequence of images using a stationary camera. Further testing is performed on a sequence of images such that the PTZ camera is moving in order to capture the moving object. Comparisons are made based upon accuracy, speed and memory.

  6. Grid generation methods

    CERN Document Server

    Liseikin, Vladimir D

    2010-01-01

    This book is an introduction to structured and unstructured grid methods in scientific computing, addressing graduate students, scientists as well as practitioners. Basic local and integral grid quality measures are formulated and new approaches to mesh generation are reviewed. In addition to the content of the successful first edition, a more detailed and practice oriented description of monitor metrics in Beltrami and diffusion equations is given for generating adaptive numerical grids. Also, new techniques developed by the author are presented, in particular a technique based on the inverted form of Beltrami’s partial differential equations with respect to control metrics. This technique allows the generation of adaptive grids for a wide variety of computational physics problems, including grid clustering to given function values and gradients, grid alignment with given vector fields, and combinations thereof. Applications of geometric methods to the analysis of numerical grid behavior as well as grid ge...

  7. De novo formed satellite DNA-based mammalian artificial chromosomes and their possible applications.

    Science.gov (United States)

    Katona, Robert L

    2015-02-01

    Mammalian artificial chromosomes (MACs) are non-integrating, autonomously replicating natural chromosome-based vectors that may carry a vast amount of genetic material, which in turn enable potentially prolonged, safe, and regulated therapeutic transgene expression and render MACs as attractive genetic vectors for "gene replacement" or for controlling differentiation pathways in target cells. Satellite-DNA-based artificial chromosomes (SATACs) can be made by induced de novo chromosome formation in cells of different mammalian and plant species. These artificially generated accessory chromosomes are composed of predictable DNA sequences, and they contain defined genetic information. SATACs have already passed a number of obstacles crucial to their further development as gene therapy vectors, including large-scale purification, transfer of purified artificial chromosomes into different cells and embryos, generation of transgenic animals and germline transmission with purified SATACs, and the tissue-specific expression of a therapeutic gene from an artificial chromosome in the milk of transgenic animals. SATACs could be used in cell therapy protocols. For these methods, the most versatile target cell would be one that was pluripotent and self-renewing to address multiple disease target cell types, thus making multilineage stem cells, such as adult derived early progenitor cells and embryonic stem cells, as attractive universal host cells.

  8. ARTIFICIAL NEURAL NETWORK AND WAVELET DECOMPOSITION IN THE FORECAST OF GLOBAL HORIZONTAL SOLAR RADIATION

    Directory of Open Access Journals (Sweden)

    Luiz Albino Teixeira Júnior

    2015-04-01

    Full Text Available This paper proposes a method (denoted by WD-ANN that combines the Artificial Neural Networks (ANN and the Wavelet Decomposition (WD to generate short-term global horizontal solar radiation forecasting, which is an essential information for evaluating the electrical power generated from the conversion of solar energy into electrical energy. The WD-ANN method consists of two basic steps: firstly, it is performed the decomposition of level p of the time series of interest, generating p + 1 wavelet orthonormal components; secondly, the p + 1 wavelet orthonormal components (generated in the step 1 are inserted simultaneously into an ANN in order to generate short-term forecasting. The results showed that the proposed method (WD-ANN improved substantially the performance over the (traditional ANN method.

  9. Estimating Penetration Resistance in Agricultural Soils of Ardabil Plain Using Artificial Neural Network and Regression Methods

    Directory of Open Access Journals (Sweden)

    Gholam Reza Sheykhzadeh

    2017-02-01

    Full Text Available Introduction: Penetration resistance is one of the criteria for evaluating soil compaction. It correlates with several soil properties such as vehicle trafficability, resistance to root penetration, seedling emergence, and soil compaction by farm machinery. Direct measurement of penetration resistance is time consuming and difficult because of high temporal and spatial variability. Therefore, many different regressions and artificial neural network pedotransfer functions have been proposed to estimate penetration resistance from readily available soil variables such as particle size distribution, bulk density (Db and gravimetric water content (θm. The lands of Ardabil Province are one of the main production regions of potato in Iran, thus, obtaining the soil penetration resistance in these regions help with the management of potato production. The objective of this research was to derive pedotransfer functions by using regression and artificial neural network to predict penetration resistance from some soil variations in the agricultural soils of Ardabil plain and to compare the performance of artificial neural network with regression models. Materials and methods: Disturbed and undisturbed soil samples (n= 105 were systematically taken from 0-10 cm soil depth with nearly 3000 m distance in the agricultural lands of the Ardabil plain ((lat 38°15' to 38°40' N, long 48°16' to 48°61' E. The contents of sand, silt and clay (hydrometer method, CaCO3 (titration method, bulk density (cylinder method, particle density (Dp (pychnometer method, organic carbon (wet oxidation method, total porosity(calculating from Db and Dp, saturated (θs and field soil water (θf using the gravimetric method were measured in the laboratory. Mean geometric diameter (dg and standard deviation (σg of soil particles were computed using the percentages of sand, silt and clay. Penetration resistance was measured in situ using cone penetrometer (analog model at 10

  10. Unidirectional Expiratory Valve Method to Assess Maximal Inspiratory Pressure in Individuals without Artificial Airway.

    Directory of Open Access Journals (Sweden)

    Samantha Torres Grams

    Full Text Available Maximal Inspiratory Pressure (MIP is considered an effective method to estimate strength of inspiratory muscles, but still leads to false positive diagnosis. Although MIP assessment with unidirectional expiratory valve method has been used in patients undergoing mechanical ventilation, no previous studies investigated the application of this method in subjects without artificial airway.This study aimed to compare the MIP values assessed by standard method (MIPsta and by unidirectional expiratory valve method (MIPuni in subjects with spontaneous breathing without artificial airway. MIPuni reproducibility was also evaluated.This was a crossover design study, and 31 subjects performed MIPsta and MIPuni in a random order. MIPsta measured MIP maintaining negative pressure for at least one second after forceful expiration. MIPuni evaluated MIP using a unidirectional expiratory valve attached to a face mask and was conducted by two evaluators (A and B at two moments (Tests 1 and 2 to determine interobserver and intraobserver reproducibility of MIP values. Intraclass correlation coefficient (ICC[2,1] was used to determine intraobserver and interobserver reproducibility.The mean values for MIPuni were 14.3% higher (-117.3 ± 24.8 cmH2O than the mean values for MIPsta (-102.5 ± 23.9 cmH2O (p<0.001. Interobserver reproducibility assessment showed very high correlation for Test 1 (ICC[2,1] = 0.91, and high correlation for Test 2 (ICC[2,1] = 0.88. The assessment of the intraobserver reproducibility showed high correlation for evaluator A (ICC[2,1] = 0.86 and evaluator B (ICC[2,1] = 0.77.MIPuni presented higher values when compared with MIPsta and proved to be reproducible in subjects with spontaneous breathing without artificial airway.

  11. Comparison of three artificial digestion methods for detection of non-encapsulated Trichinella pseudospiralis larvae in pork

    DEFF Research Database (Denmark)

    Nockler, K.; Reckinger, S.; Szabo, I.

    2009-01-01

    In a ring trial involving five laboratories (A, B, C, D, and E), three different methods of artificial digestion were compared for the detection of non-encapsulated Trichinella pseudospiralis larvae in minced meat. Each sample panel consisted often 1 g minced pork samples. All samples in each panel...... were derived from a bulk meat preparation with a nominal value of either 7 or 17 larvae per g (Ipg). Samples were tested for the number of muscle larvae using the magnetic stirrer method (labs A, B, and E), stomacher method (lab B), and Trichomatic 35 (R) (labs C and D). T. pseudospiralis larvae were...... by using the magnetic stirrer method (22%), followed by the stomacher method (25%), and Trichomatic 35 (R) (30%). Results revealed that T. pseudospiralis larvae in samples with a nominal value of 7 and 17 Ipg can be detected by all three methods of artificial digestion....

  12. Investigation of reliability of EC method for inspection of VVER steam generator tubes

    International Nuclear Information System (INIS)

    Corak, Z.

    2004-01-01

    Complete and accurate non-destructive examinations (NDE) data provides the basis for performing mitigating actions and corrective repairs. It is important that detection and characterization of flaws are done properly at an early stage. EPRI Document PWR Steam Generator Examination Guidelines recommends an approach that is intended to provide the following: Ensure accurate assessment of steam generator tube integrity; Extend the reliable, cost effective, operating life of the steam generators, and Maximize the availability of the unit. Steam Generator Eddy Current Data Analysis Performance Demonstration represents the culmination of the intense two-year industry effort in the development of a performance demonstration program for eddy current testing (ECT) of steam generator tubing. It is referred to as the Industry Database (IDB) and provides a capability for individual organizations to implement SG ECT performance demonstration programs in accordance with the requirements specified in Appendices G and H of the ISI Guidelines. The Appendix G of EPRI Document PWR Steam Generator Examination Guidelines specifies personnel training and qualification requirements for NDE personnel who analyze NDE data for PWR steam generator tubing. Its purpose is to insure a continuing uniform knowledge base and skill level for data analysis. The European methodology document is intended to provide a general framework for development of qualifications for the inspection of specific components to ensure they are developed in a consistent way throughout Europe while still allowing qualification to be tailored in detail to meet different nation requirements. In the European methodology document one will not find a detailed description of how the inspection of a specific component should be qualified. A recommended practice is a document produced by ENIQ to support the production of detailed qualification procedures by individual countries. VVER SG tubes are inspected by EC method but a

  13. Inflow Turbulence Generation Methods

    Science.gov (United States)

    Wu, Xiaohua

    2017-01-01

    Research activities on inflow turbulence generation methods have been vigorous over the past quarter century, accompanying advances in eddy-resolving computations of spatially developing turbulent flows with direct numerical simulation, large-eddy simulation (LES), and hybrid Reynolds-averaged Navier-Stokes-LES. The weak recycling method, rooted in scaling arguments on the canonical incompressible boundary layer, has been applied to supersonic boundary layer, rough surface boundary layer, and microscale urban canopy LES coupled with mesoscale numerical weather forecasting. Synthetic methods, originating from analytical approximation to homogeneous isotropic turbulence, have branched out into several robust methods, including the synthetic random Fourier method, synthetic digital filtering method, synthetic coherent eddy method, and synthetic volume forcing method. This article reviews major progress in inflow turbulence generation methods with an emphasis on fundamental ideas, key milestones, representative applications, and critical issues. Directions for future research in the field are also highlighted.

  14. Monitoring of operation with artificial intelligence methods; Betriebsueberwachung mit Verfahren der Kuenstlichen Intelligenz

    Energy Technology Data Exchange (ETDEWEB)

    Bruenninghaus, H. [DMT-Gesellschaft fuer Forschung und Pruefung mbH, Essen (Germany). Geschaeftsbereich Systemtechnik

    1999-03-11

    Taking the applications `early detection of fires` and `reduction of burst of messages` as an example, the usability of artificial intelligence (AI) methods in the monitoring of operation was checked in a R and D project. The contribution describes the concept, development and evaluation of solutions to the specified problems. A platform, which made it possible to investigate different AI methods (in particular artificial neuronal networks), had to be creaated as a basis for the project. At the same time ventilation data had to be acquired and processed by the networks for the classification. (orig.) [Deutsch] Am Beispiel der Anwendungsfaelle `Brandfrueherkennung` und `Meldungsschauerreduzierung` wurde im Rahmen eines F+E-Vorhabens die Einsetzbarkeit von Kuenstliche-Intelligenz-Methoden (KI) in der Betriebsueberwachung geprueft. Der Beitrag stellt Konzeption, Entwicklung und Bewertung von Loesungsansaetzen fuer die genannten Aufgabenstellungen vor. Als Grundlage fuer das Vorhaben wurden anhand KI-Methoden (speziell: Kuenstliche Neuronale Netze -KNN) auf der Grundlage gewonnener und aufbereiteter Wetterdaten die Beziehungen zwischen den Wettermessstellen im Laufe des Wetterwegs klassifiziert. (orig.)

  15. Brown's TRANSPORT up to third order aberration by artificial intelligence

    International Nuclear Information System (INIS)

    Xia Jiawen; Xie Xi; Qiao Qingwen

    1991-01-01

    Brown's TRANSPORT is a first and second order matrix multiplication computer program intended for the design of accelerator beam transport systems, neglecting the third order aberration. Recently a new method was developed to derive analytically any order aberration coefficients of general charged particle optic system, applicable to any practical systems, such as accelerators, electron microscopes, lithographs, etc., including those unknown systems yet to be invented. An artificial intelligence program in Turbo Prolog was implemented on IBM-PC 286 or 386 machine to generate automatically the analytical expression of any order aberration coefficients of general charged particle optic system. Based on this new method and technique, Brown's TRANSPORT is extended beyond the second order aberration effects by artificial intelligence, outputing automatically all the analytical expressions up to the third order aberration coefficients

  16. Brown's transport up to third order aberration by artificial intelligence

    International Nuclear Information System (INIS)

    Xia Jiawen; Xie Xi; Qiao Qingwen

    1992-01-01

    Brown's TRANSPORT is a first and second order matrix multiplication computer program intended for the design of accelerator beam transport systems, neglecting the third order aberration. Recently a new method was developed to derive analytically any order aberration coefficients of general charged particle optic system, applicable to any practical systems, such as accelerators, electron microscopes, lithographs, including those unknown systems yet to be invented. An artificial intelligence program in Turbo Prolog was implemented on IBM-PC 286 or 386 machine to generate automatically the analytical expression of any order aberration coefficients of general charged particle optic system. Based on this new method and technique, Brown's TRANSPORT is extended beyond the second order aberration effect by artificial intelligence, outputting automatically all the analytical expressions up to the third order aberration coefficients

  17. An artificial nonlinear diffusivity method for supersonic reacting flows with shocks

    Science.gov (United States)

    Fiorina, B.; Lele, S. K.

    2007-03-01

    A computational approach for modeling interactions between shocks waves, contact discontinuities and reactions zones with a high-order compact scheme is investigated. To prevent the formation of spurious oscillations around shocks, artificial nonlinear viscosity [A.W. Cook, W.H. Cabot, A high-wavenumber viscosity for high resolution numerical method, J. Comput. Phys. 195 (2004) 594-601] based on high-order derivative of the strain rate tensor is used. To capture temperature and species discontinuities a nonlinear diffusivity based on the entropy gradient is added. It is shown that the damping of 'wiggles' is controlled by the model constants and is largely independent of the mesh size and the shock strength. The same holds for the numerical shock thickness and allows a determination of the L2 error. In the shock tube problem, with fluids of different initial entropy separated by the diaphragm, an artificial diffusivity is required to accurately capture the contact surface. Finally, the method is applied to a shock wave propagating into a medium with non-uniform density/entropy and to a CJ detonation wave. Multi-dimensional formulation of the model is presented and is illustrated by a 2D oblique wave reflection from an inviscid wall, by a 2D supersonic blunt body flow and by a Mach reflection problem.

  18. Runoff generation and routing on artificial slopes in a Mediterranean-continental environment: the Teruel coalfield, Spain

    Energy Technology Data Exchange (ETDEWEB)

    Nicolau, J.M. [Universidad de Alcala de Henares, Alcala de Henares (Spain)

    2002-07-01

    The aim of the study was to identify the mechanisms of runoff generation and routing and their controlling factors at the hillslope scale, on artificial slopes derived from surface coal mining reclamation in a Mediterranean-continental area. Rainfall and runoff at interrill and microcatchment scales were recorded for a year on two slopes with different substrata: topsoil cover and overburden cover. Runoff coefficient and runoff routing from interrill areas to microcatchment outlets were higher in the overburden substratum than in topsoil, and greater in the most developed rill network. Rainfall volume is the major parameter responsible for runoff response on overburden, suggesting that this substratum is very impermeable - at least during the main rainfall periods of the year (late spring and autumn) when the soil surface is sealed. In such conditions, most rainfall input is converted into runoff, regardless of its intensity. Results from artificial rainfall experiments, conducted 3 and 7 years after seeding, confirm the low infiltration capacity of overburden when sealed. The hydrological response shows great seasonal variability on the overburden slope in accordance with soil surface changes over the year. Rainfall volume and intensities explain runoff at the inter-rill scale on the topsoil slope, where rainfall experiments demonstrated a typical Hortonian infiltration curve. However, no correlation was found at the microcatchment level, probably because of the loss of functionality of the only rill as ecological succession proceeded. The runoff generation mechanism on the topsoil slope is more homogeneous throughout the year. The dense rill networks of the overburden slope guarantee very effective runoff drainage, regardless of rainfall magnitude. Runoff generation and routing on topsoil slopes are controlled by grass cover and soil moisture content, whereas on overburden slopes rill network density and soil moisture content are the main controlling factors.

  19. Web Intelligence and Artificial Intelligence in Education

    Science.gov (United States)

    Devedzic, Vladan

    2004-01-01

    This paper surveys important aspects of Web Intelligence (WI) in the context of Artificial Intelligence in Education (AIED) research. WI explores the fundamental roles as well as practical impacts of Artificial Intelligence (AI) and advanced Information Technology (IT) on the next generation of Web-related products, systems, services, and…

  20. Bioengineering of Artificial Lymphoid Organs.

    Science.gov (United States)

    Nosenko, M A; Drutskaya, M S; Moisenovich, M M; Nedospasov, S A

    2016-01-01

    This review addresses the issue of bioengineering of artificial lymphoid organs.Progress in this field may help to better understand the nature of the structure-function relations that exist in immune organs. Artifical lymphoid organs may also be advantageous in the therapy or correction of immunodefficiencies, autoimmune diseases, and cancer. The structural organization, development, and function of lymphoid tissue are analyzed with a focus on the role of intercellular contacts and on the cytokine signaling pathways regulating these processes. We describe various polymeric materials, as scaffolds, for artificial tissue engineering. Finally, published studies in which artificial lymphoid organs were generated are reviewed and possible future directions in the field are discussed.

  1. Artificial Evolution for the Detection of Group Identities in Complex Artificial Societies

    DEFF Research Database (Denmark)

    Grappiolo, Corrado; Togelius, Julian; Yannakakis, Georgios N.

    2013-01-01

    This paper aims at detecting the presence of group structures in complex artificial societies by solely observing and analysing the interactions occurring among the artificial agents. Our approach combines: (1) an unsupervised method for clustering interactions into two possible classes, namely in...

  2. Lexicon generation methods, lexicon generation devices, and lexicon generation articles of manufacture

    Science.gov (United States)

    Carter, Richard J [Richland, WA; McCall, Jonathon D [West Richland, WA; Whitney, Paul D [Richland, WA; Gregory, Michelle L [Richland, WA; Turner, Alan E [Kennewick, WA; Hetzler, Elizabeth G [Kennewick, WA; White, Amanda M [Kennewick, WA; Posse, Christian [Seattle, WA; Nakamura, Grant C [Kennewick, WA

    2010-10-26

    Lexicon generation methods, computer implemented lexicon editing methods, lexicon generation devices, lexicon editors, and articles of manufacture are described according to some aspects. In one aspect, a lexicon generation method includes providing a seed vector indicative of occurrences of a plurality of seed terms within a plurality of text items, providing a plurality of content vectors indicative of occurrences of respective ones of a plurality of content terms within the text items, comparing individual ones of the content vectors with respect to the seed vector, and responsive to the comparing, selecting at least one of the content terms as a term of a lexicon usable in sentiment analysis of text.

  3. Reasoning methods in medical consultation systems: artificial intelligence approaches.

    Science.gov (United States)

    Shortliffe, E H

    1984-01-01

    It has been argued that the problem of medical diagnosis is fundamentally ill-structured, particularly during the early stages when the number of possible explanations for presenting complaints can be immense. This paper discusses the process of clinical hypothesis evocation, contrasts it with the structured decision making approaches used in traditional computer-based diagnostic systems, and briefly surveys the more open-ended reasoning methods that have been used in medical artificial intelligence (AI) programs. The additional complexity introduced when an advice system is designed to suggest management instead of (or in addition to) diagnosis is also emphasized. Example systems are discussed to illustrate the key concepts.

  4. Three-dimensional hysteresis compensation enhances accuracy of robotic artificial muscles

    Science.gov (United States)

    Zhang, Jun; Simeonov, Anthony; Yip, Michael C.

    2018-03-01

    Robotic artificial muscles are compliant and can generate straight contractions. They are increasingly popular as driving mechanisms for robotic systems. However, their strain and tension force often vary simultaneously under varying loads and inputs, resulting in three-dimensional hysteretic relationships. The three-dimensional hysteresis in robotic artificial muscles poses difficulties in estimating how they work and how to make them perform designed motions. This study proposes an approach to driving robotic artificial muscles to generate designed motions and forces by modeling and compensating for their three-dimensional hysteresis. The proposed scheme captures the nonlinearity by embedding two hysteresis models. The effectiveness of the model is confirmed by testing three popular robotic artificial muscles. Inverting the proposed model allows us to compensate for the hysteresis among temperature surrogate, contraction length, and tension force of a shape memory alloy (SMA) actuator. Feedforward control of an SMA-actuated robotic bicep is demonstrated. This study can be generalized to other robotic artificial muscles, thus enabling muscle-powered machines to generate desired motions.

  5. Impact of adding artificially generated alert sound to hybrid electric vehicles on their detectability by pedestrians who are blind.

    Science.gov (United States)

    Kim, Dae Shik; Emerson, Robert Wall; Naghshineh, Koorosh; Pliskow, Jay; Myers, Kyle

    2012-01-01

    A repeated-measures design with block randomization was used for the study, in which 14 adults with visual impairments attempted to detect three different vehicles: a hybrid electric vehicle (HEV) with an artificially generated sound (Vehicle Sound for Pedestrians [VSP]), an HEV without the VSP, and a comparable internal combustion engine (ICE) vehicle. The VSP vehicle (mean +/- standard deviation [SD] = 38.3 +/- 14.8 m) was detected at a significantly farther distance than the HEV (mean +/- SD = 27.5 +/- 11.5 m), t = 4.823, p vehicles (mean +/- SD = 34.5 +/- 14.3 m), t = 1.787, p = 0.10. Despite the overall sound level difference between the two test sites (parking lot = 48.7 dBA, roadway = 55.1 dBA), no significant difference in detection distance between the test sites was observed, F(1, 13) = 0.025, p = 0.88. No significant interaction was found between the vehicle type and test site, F(1.31, 16.98) = 0.272, p = 0.67. The findings of the study may help us understand how adding an artificially generated sound to an HEV could affect some of the orientation and mobility tasks performed by blind pedestrians.

  6. Heat and electricity generating methods

    International Nuclear Information System (INIS)

    Buter, J.

    1977-01-01

    A short synopsis on the actual methods of heating of lodgings and of industrial heat generation is given. Electricity can be generated in steam cycles heated by burning of fossil fuels or by nuclear energy. A valuable contribution to the electricity economy is produced in the hydroelectric power plants. Besides these classical methods, also the different procedures of direct electricity generation are treated: thermoelectric, thermionic, magnetohydrodynamic power sources, solar and fuel cells. (orig.) [de

  7. Comparison of steam generator methods in PISC

    International Nuclear Information System (INIS)

    Lahdenperae, K.; Kankare, M.

    1996-01-01

    The main objective of the study (PISC III, action 5) was the experimental evaluation of the performance of methods used in in-service inspection of steam generator tubes used in nuclear power plants. The study was organized by the Joint Research Center of the European Community (JRC). The round robin test with blind boxes started in 1991. During the study training boxes and blind boxes were circulated in 29 laboratories in Europe, Japan and the USA. The boxes contained steam generator tubes with artificial and natural (chemically induced) flaws. The material was inconell. The blind boxes contained 66 tubes and 95 flaws. All flaws were introduced into different discontinuities, under support plates, above the tube sheet and into U-bends. The flaws included volumetric flaws (wastage, pitting, wear), axial and circumferential notches and chemically induced SCC cracks and IGA. After the round robin test the reference laboratory performed the destructive examination of reported flaws. The flaw detection probability (FDP) for all flaws and for teams inspecting all tubes was 60-85%. The detection of flaws deeper than 40% of the wall thickness was good. Flaws with a depth of less than 20% were not detected. When all flaws were considered, depth sizing was found to have a wide dispersion. Similarly, measured lengths did not as a rule correlate with true lengths. The classification of flaws in cracks and of volumetric flaws was not very successful, the correct classification probability being only about 70%. Evaluation of the flaws showed some shortcomings. The correct rejection probability was at best 83% for teams inspecting all boxes. (3 refs.)

  8. Assessing artificial neural networks and statistical methods for infilling missing soil moisture records

    Science.gov (United States)

    Dumedah, Gift; Walker, Jeffrey P.; Chik, Li

    2014-07-01

    Soil moisture information is critically important for water management operations including flood forecasting, drought monitoring, and groundwater recharge estimation. While an accurate and continuous record of soil moisture is required for these applications, the available soil moisture data, in practice, is typically fraught with missing values. There are a wide range of methods available to infilling hydrologic variables, but a thorough inter-comparison between statistical methods and artificial neural networks has not been made. This study examines 5 statistical methods including monthly averages, weighted Pearson correlation coefficient, a method based on temporal stability of soil moisture, and a weighted merging of the three methods, together with a method based on the concept of rough sets. Additionally, 9 artificial neural networks are examined, broadly categorized into feedforward, dynamic, and radial basis networks. These 14 infilling methods were used to estimate missing soil moisture records and subsequently validated against known values for 13 soil moisture monitoring stations for three different soil layer depths in the Yanco region in southeast Australia. The evaluation results show that the top three highest performing methods are the nonlinear autoregressive neural network, rough sets method, and monthly replacement. A high estimation accuracy (root mean square error (RMSE) of about 0.03 m/m) was found in the nonlinear autoregressive network, due to its regression based dynamic network which allows feedback connections through discrete-time estimation. An equally high accuracy (0.05 m/m RMSE) in the rough sets procedure illustrates the important role of temporal persistence of soil moisture, with the capability to account for different soil moisture conditions.

  9. Influence of the Mechanical Properties of Third-Generation Artificial Turf Systems on Soccer Players’ Physiological and Physical Performance and Their Perceptions

    Science.gov (United States)

    Sánchez-Sánchez, Javier; García-Unanue, Jorge; Jiménez-Reyes, Pedro; Gallardo, Ana; Burillo, Pablo; Felipe, José Luis; Gallardo, Leonor

    2014-01-01

    The aim of this research was to evaluate the influence of the mechanical properties of artificial turf systems on soccer players’ performance. A battery of perceptive physiological and physical tests were developed on four different structural systems of artificial turf (System 1: Compacted gravel sub-base without elastic layer; System 2: Compacted gravel sub-base with elastic layer; System 3: Asphalt sub-base without elastic layer; System 4: Asphalt sub-base with elastic layer). The sample was composed of 18 soccer players (22.44±1.72 years) who typically train and compete on artificial turf. The artificial turf system with less rotational traction (S3) showed higher total time in the Repeated Sprint Ability test in comparison to the systems with intermediate values (49.46±1.75 s vs 47.55±1.82 s (S1) and 47.85±1.59 s (S2); pperformance in jumping tests (countermovement jump and squat jump) and ball kicking to goal decreased after the RSA test in all surfaces assessed (pperformance deterioration (p>0.05). The physiological load was similar in all four artificial turf systems. However, players felt more comfortable on the harder and more rigid system (S4; visual analogue scale = 70.83±14.28) than on the softer artificial turf system (S2; visual analogue scale = 54.24±19.63). The lineal regression analysis revealed a significant influence of the mechanical properties of the surface of 16.5%, 15.8% and 7.1% on the mean time of the sprint, the best sprint time and the maximum mean speed in the RSA test respectively. Results suggest a mechanical heterogeneity between the systems of artificial turf which generate differences in the physical performance and in the soccer players’ perceptions. PMID:25354188

  10. A Method Based on Artificial Intelligence To Fully Automatize The Evaluation of Bovine Blastocyst Images.

    Science.gov (United States)

    Rocha, José Celso; Passalia, Felipe José; Matos, Felipe Delestro; Takahashi, Maria Beatriz; Ciniciato, Diego de Souza; Maserati, Marc Peter; Alves, Mayra Fernanda; de Almeida, Tamie Guibu; Cardoso, Bruna Lopes; Basso, Andrea Cristina; Nogueira, Marcelo Fábio Gouveia

    2017-08-09

    Morphological analysis is the standard method of assessing embryo quality; however, its inherent subjectivity tends to generate discrepancies among evaluators. Using genetic algorithms and artificial neural networks (ANNs), we developed a new method for embryo analysis that is more robust and reliable than standard methods. Bovine blastocysts produced in vitro were classified as grade 1 (excellent or good), 2 (fair), or 3 (poor) by three experienced embryologists according to the International Embryo Technology Society (IETS) standard. The images (n = 482) were subjected to automatic feature extraction, and the results were used as input for a supervised learning process. One part of the dataset (15%) was used for a blind test posterior to the fitting, for which the system had an accuracy of 76.4%. Interestingly, when the same embryologists evaluated a sub-sample (10%) of the dataset, there was only 54.0% agreement with the standard (mode for grades). However, when using the ANN to assess this sub-sample, there was 87.5% agreement with the modal values obtained by the evaluators. The presented methodology is covered by National Institute of Industrial Property (INPI) and World Intellectual Property Organization (WIPO) patents and is currently undergoing a commercial evaluation of its feasibility.

  11. Automation of gender determination in human canines using artificial intelligence

    Directory of Open Access Journals (Sweden)

    F. Fidya

    2017-09-01

    Full Text Available Background: Gender determination is an important aspect of the identification process. The tooth represents a part of the human body that indicates the nature of sexual dimorphism. Artificial intelligence enables computers to perform to the same standard the same tasks as those carried out by humans. Several methods of classification exist within an artificial intelligence approach to identifying sexual dimorphism in canines. Purpose: This study aimed to quantify the respective accuracy of the Naive Bayes, decision tree, and multi-layer perceptron (MLP methods in identifying sexual dimorphism in canines. Methods: A sample of results derived from 100 measurements of the diameter of mesiodistal, buccolingual, and diagonal upper and lower canine jaw models of both genders were entered into an application computer program that implements the algorithm (MLP. The analytical process was conducted by the program to obtain a classification model with testing being subsequently carried out in order to obtain 50 new measurement results, 25 each for males and females. A comparative analysis was conducted on the program-generated information. Results: The accuracy rate of the Naive Bayes method was 82%, while that of the decision tree and MLP amounted to 84%. The MLP method had an absolute error value lower than that of its decision tree counterpart. Conclusion: The use of artificial intelligence methods produced a highly accurate identification process relating to the gender determination of canine teeth. The most appropriate method was the MLP with an accuracy rate of 84%.

  12. A method of generating moving objects on the constrained network

    Science.gov (United States)

    Zhang, Jie; Ma, Linbing

    2008-10-01

    Moving objects databases have become an important research issue in recent years. In case large real data sets acquired by GPS, PDA or other mobile devices are not available, benchmarking requires the generation of artificial data sets following the real-world behavior of spatial objects that change their locations over time. In the field of spatiotemporal databases, a number of publications about the generation of test data are restricted to few papers. However, most of the existing moving-object generators assume a fixed and often unrealistic mobility model and do not consider several important characteristics of the network. In this paper, a new generator is presented to solve these problems. First of all, the network is realistic transportation network of Guangzhou. Second, the observation records of vehicle flow are available. Third, in order to simplify the whole simulation process and to help us visualize the process, this framework is built under .Net development platform of Microsoft and ArcEngine9 environment.

  13. Probabilistic Wind Power Forecasting with Hybrid Artificial Neural Networks

    DEFF Research Database (Denmark)

    Wan, Can; Song, Yonghua; Xu, Zhao

    2016-01-01

    probabilities of prediction errors provide an alternative yet effective solution. This article proposes a hybrid artificial neural network approach to generate prediction intervals of wind power. An extreme learning machine is applied to conduct point prediction of wind power and estimate model uncertainties...... via a bootstrap technique. Subsequently, the maximum likelihood estimation method is employed to construct a distinct neural network to estimate the noise variance of forecasting results. The proposed approach has been tested on multi-step forecasting of high-resolution (10-min) wind power using...... actual wind power data from Denmark. The numerical results demonstrate that the proposed hybrid artificial neural network approach is effective and efficient for probabilistic forecasting of wind power and has high potential in practical applications....

  14. Multilevel method for modeling large-scale networks.

    Energy Technology Data Exchange (ETDEWEB)

    Safro, I. M. (Mathematics and Computer Science)

    2012-02-24

    Understanding the behavior of real complex networks is of great theoretical and practical significance. It includes developing accurate artificial models whose topological properties are similar to the real networks, generating the artificial networks at different scales under special conditions, investigating a network dynamics, reconstructing missing data, predicting network response, detecting anomalies and other tasks. Network generation, reconstruction, and prediction of its future topology are central issues of this field. In this project, we address the questions related to the understanding of the network modeling, investigating its structure and properties, and generating artificial networks. Most of the modern network generation methods are based either on various random graph models (reinforced by a set of properties such as power law distribution of node degrees, graph diameter, and number of triangles) or on the principle of replicating an existing model with elements of randomization such as R-MAT generator and Kronecker product modeling. Hierarchical models operate at different levels of network hierarchy but with the same finest elements of the network. However, in many cases the methods that include randomization and replication elements on the finest relationships between network nodes and modeling that addresses the problem of preserving a set of simplified properties do not fit accurately enough the real networks. Among the unsatisfactory features are numerically inadequate results, non-stability of algorithms on real (artificial) data, that have been tested on artificial (real) data, and incorrect behavior at different scales. One reason is that randomization and replication of existing structures can create conflicts between fine and coarse scales of the real network geometry. Moreover, the randomization and satisfying of some attribute at the same time can abolish those topological attributes that have been undefined or hidden from

  15. Reinforcement Learning Based Artificial Immune Classifier

    Directory of Open Access Journals (Sweden)

    Mehmet Karakose

    2013-01-01

    Full Text Available One of the widely used methods for classification that is a decision-making process is artificial immune systems. Artificial immune systems based on natural immunity system can be successfully applied for classification, optimization, recognition, and learning in real-world problems. In this study, a reinforcement learning based artificial immune classifier is proposed as a new approach. This approach uses reinforcement learning to find better antibody with immune operators. The proposed new approach has many contributions according to other methods in the literature such as effectiveness, less memory cell, high accuracy, speed, and data adaptability. The performance of the proposed approach is demonstrated by simulation and experimental results using real data in Matlab and FPGA. Some benchmark data and remote image data are used for experimental results. The comparative results with supervised/unsupervised based artificial immune system, negative selection classifier, and resource limited artificial immune classifier are given to demonstrate the effectiveness of the proposed new method.

  16. Satellite DNA-based artificial chromosomes for use in gene therapy.

    Science.gov (United States)

    Hadlaczky, G

    2001-04-01

    Satellite DNA-based artificial chromosomes (SATACs) can be made by induced de novo chromosome formation in cells of different mammalian species. These artificially generated accessory chromosomes are composed of predictable DNA sequences and they contain defined genetic information. Prototype human SATACs have been successfully constructed in different cell types from 'neutral' endogenous DNA sequences from the short arm of the human chromosome 15. SATACs have already passed a number of hurdles crucial to their further development as gene therapy vectors, including: large-scale purification; transfer of purified artificial chromosomes into different cells and embryos; generation of transgenic animals and germline transmission with purified SATACs; and the tissue-specific expression of a therapeutic gene from an artificial chromosome in the milk of transgenic animals.

  17. An Object-Based Image Analysis Method for Monitoring Land Conversion by Artificial Sprawl Use of RapidEye and IRS Data

    Directory of Open Access Journals (Sweden)

    Maud Balestrat

    2012-02-01

    Full Text Available In France, in the peri-urban context, urban sprawl dynamics are particularly strong with huge population growth as well as a land crisis. The increase and spreading of built-up areas from the city centre towards the periphery takes place to the detriment of natural and agricultural spaces. The conversion of land with agricultural potential is all the more worrying as it is usually irreversible. The French Ministry of Agriculture therefore needs reliable and repeatable spatial-temporal methods to locate and quantify loss of land at both local and national scales. The main objective of this study was to design a repeatable method to monitor land conversion characterized by artificial sprawl: (i We used an object-based image analysis to extract artificial areas from satellite images; (ii We built an artificial patch that consists of aggregating all the peripheral areas that characterize artificial areas. The “artificialized” patch concept is an innovative extension of the urban patch concept, but differs in the nature of its components and in the continuity distance applied; (iii The diachronic analysis of artificial patch maps enables characterization of artificial sprawl. The method was applied at the scale of four departments (similar to provinces along the coast of Languedoc-Roussillon, in the South of France, based on two satellite datasets, one acquired in 1996–1997 (Indian Remote Sensing and the other in 2009 (RapidEye. In the four departments, we measured an increase in artificial areas of from 113,000 ha in 1997 to 133,000 ha in 2009, i.e., an 18% increase in 12 years. The package comes in the form of a 1/15,000 valid cartography, usable at the scale of a commune (the smallest territorial division used for administrative purposes in France that can be adapted to departmental and regional scales. The method is reproducible in homogenous spatial-temporal terms, so that it could be used periodically to assess changes in land conversion

  18. A MITE-based genotyping method to reveal hundreds of DNA polymorphisms in an animal genome after a few generations of artificial selection

    Directory of Open Access Journals (Sweden)

    Tetreau Guillaume

    2008-10-01

    Full Text Available Abstract Background For most organisms, developing hundreds of genetic markers spanning the whole genome still requires excessive if not unrealistic efforts. In this context, there is an obvious need for methodologies allowing the low-cost, fast and high-throughput genotyping of virtually any species, such as the Diversity Arrays Technology (DArT. One of the crucial steps of the DArT technique is the genome complexity reduction, which allows obtaining a genomic representation characteristic of the studied DNA sample and necessary for subsequent genotyping. In this article, using the mosquito Aedes aegypti as a study model, we describe a new genome complexity reduction method taking advantage of the abundance of miniature inverted repeat transposable elements (MITEs in the genome of this species. Results Ae. aegypti genomic representations were produced following a two-step procedure: (1 restriction digestion of the genomic DNA and simultaneous ligation of a specific adaptor to compatible ends, and (2 amplification of restriction fragments containing a particular MITE element called Pony using two primers, one annealing to the adaptor sequence and one annealing to a conserved sequence motif of the Pony element. Using this protocol, we constructed a library comprising more than 6,000 DArT clones, of which at least 5.70% were highly reliable polymorphic markers for two closely related mosquito strains separated by only a few generations of artificial selection. Within this dataset, linkage disequilibrium was low, and marker redundancy was evaluated at 2.86% only. Most of the detected genetic variability was observed between the two studied mosquito strains, but individuals of the same strain could still be clearly distinguished. Conclusion The new complexity reduction method was particularly efficient to reveal genetic polymorphisms in Ae. egypti. Overall, our results testify of the flexibility of the DArT genotyping technique and open new

  19. Color matching of fabric blends: hybrid Kubelka-Munk + artificial neural network based method

    Science.gov (United States)

    Furferi, Rocco; Governi, Lapo; Volpe, Yary

    2016-11-01

    Color matching of fabric blends is a key issue for the textile industry, mainly due to the rising need to create high-quality products for the fashion market. The process of mixing together differently colored fibers to match a desired color is usually performed by using some historical recipes, skillfully managed by company colorists. More often than desired, the first attempt in creating a blend is not satisfactory, thus requiring the experts to spend efforts in changing the recipe with a trial-and-error process. To confront this issue, a number of computer-based methods have been proposed in the last decades, roughly classified into theoretical and artificial neural network (ANN)-based approaches. Inspired by the above literature, the present paper provides a method for accurate estimation of spectrophotometric response of a textile blend composed of differently colored fibers made of different materials. In particular, the performance of the Kubelka-Munk (K-M) theory is enhanced by introducing an artificial intelligence approach to determine a more consistent value of the nonlinear function relationship between the blend and its components. Therefore, a hybrid K-M+ANN-based method capable of modeling the color mixing mechanism is devised to predict the reflectance values of a blend.

  20. Artificial Intelligence in Civil Engineering

    Directory of Open Access Journals (Sweden)

    Pengzhen Lu

    2012-01-01

    Full Text Available Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives for efficiently solving problems in the civil engineering. This paper summarizes recently developed methods and theories in the developing direction for applications of artificial intelligence in civil engineering, including evolutionary computation, neural networks, fuzzy systems, expert system, reasoning, classification, and learning, as well as others like chaos theory, cuckoo search, firefly algorithm, knowledge-based engineering, and simulated annealing. The main research trends are also pointed out in the end. The paper provides an overview of the advances of artificial intelligence applied in civil engineering.

  1. Continuous surveillance of transformers using artificial intelligence methods; Surveillance continue des transformateurs: application des methodes d'intelligence artificielle

    Energy Technology Data Exchange (ETDEWEB)

    Schenk, A.; Germond, A. [Ecole Polytechnique Federale de Lausanne, Lausanne (Switzerland); Boss, P.; Lorin, P. [ABB Secheron SA, Geneve (Switzerland)

    2000-07-01

    The article describes a new method for the continuous surveillance of power transformers based on the application of artificial intelligence (AI) techniques. An experimental pilot project on a specially equipped, strategically important power transformer is described. Traditional surveillance methods and the use of mathematical models for the prediction of faults are described. The article describes the monitoring equipment used in the pilot project and the AI principles such as self-organising maps that are applied. The results obtained from the pilot project and methods for their graphical representation are discussed.

  2. A comparative study of laser induced breakdown spectroscopy analysis for element concentrations in aluminum alloy using artificial neural networks and calibration methods

    International Nuclear Information System (INIS)

    Inakollu, Prasanthi; Philip, Thomas; Rai, Awadhesh K.; Yueh Fangyu; Singh, Jagdish P.

    2009-01-01

    A comparative study of analysis methods (traditional calibration method and artificial neural networks (ANN) prediction method) for laser induced breakdown spectroscopy (LIBS) data of different Al alloy samples was performed. In the calibration method, the intensity of the analyte lines obtained from different samples are plotted against their concentration to form calibration curves for different elements from which the concentrations of unknown elements were deduced by comparing its LIBS signal with the calibration curves. Using ANN, an artificial neural network model is trained with a set of input data of known composition samples. The trained neural network is then used to predict the elemental concentration from the test spectra. The present results reveal that artificial neural networks are capable of predicting values better than traditional method in most cases

  3. Prediction of shear wave velocity using empirical correlations and artificial intelligence methods

    Science.gov (United States)

    Maleki, Shahoo; Moradzadeh, Ali; Riabi, Reza Ghavami; Gholami, Raoof; Sadeghzadeh, Farhad

    2014-06-01

    Good understanding of mechanical properties of rock formations is essential during the development and production phases of a hydrocarbon reservoir. Conventionally, these properties are estimated from the petrophysical logs with compression and shear sonic data being the main input to the correlations. This is while in many cases the shear sonic data are not acquired during well logging, which may be for cost saving purposes. In this case, shear wave velocity is estimated using available empirical correlations or artificial intelligent methods proposed during the last few decades. In this paper, petrophysical logs corresponding to a well drilled in southern part of Iran were used to estimate the shear wave velocity using empirical correlations as well as two robust artificial intelligence methods knows as Support Vector Regression (SVR) and Back-Propagation Neural Network (BPNN). Although the results obtained by SVR seem to be reliable, the estimated values are not very precise and considering the importance of shear sonic data as the input into different models, this study suggests acquiring shear sonic data during well logging. It is important to note that the benefits of having reliable shear sonic data for estimation of rock formation mechanical properties will compensate the possible additional costs for acquiring a shear log.

  4. Prediction of shear wave velocity using empirical correlations and artificial intelligence methods

    Directory of Open Access Journals (Sweden)

    Shahoo Maleki

    2014-06-01

    Full Text Available Good understanding of mechanical properties of rock formations is essential during the development and production phases of a hydrocarbon reservoir. Conventionally, these properties are estimated from the petrophysical logs with compression and shear sonic data being the main input to the correlations. This is while in many cases the shear sonic data are not acquired during well logging, which may be for cost saving purposes. In this case, shear wave velocity is estimated using available empirical correlations or artificial intelligent methods proposed during the last few decades. In this paper, petrophysical logs corresponding to a well drilled in southern part of Iran were used to estimate the shear wave velocity using empirical correlations as well as two robust artificial intelligence methods knows as Support Vector Regression (SVR and Back-Propagation Neural Network (BPNN. Although the results obtained by SVR seem to be reliable, the estimated values are not very precise and considering the importance of shear sonic data as the input into different models, this study suggests acquiring shear sonic data during well logging. It is important to note that the benefits of having reliable shear sonic data for estimation of rock formation mechanical properties will compensate the possible additional costs for acquiring a shear log.

  5. SOLVING TRANSPORT LOGISTICS PROBLEMS IN A VIRTUAL ENTERPRISE THROUGH ARTIFICIAL INTELLIGENCE METHODS

    Directory of Open Access Journals (Sweden)

    Vitaliy PAVLENKO

    2017-06-01

    Full Text Available The paper offers a solution to the problem of material flow allocation within a virtual enterprise by using artificial intelligence methods. The research is based on the use of fuzzy relations when planning for optimal transportation modes to deliver components for manufactured products. The Fuzzy Logic Toolbox is used to determine the optimal route for transportation of components for manufactured products. The methods offered have been exemplified in the present research. The authors have built a simulation model for component transportation and delivery for manufactured products using the Simulink graphical environment for building models.

  6. Spin wave absorber generated by artificial surface anisotropy for spin wave device network

    Directory of Open Access Journals (Sweden)

    Naoki Kanazawa

    2016-09-01

    Full Text Available Spin waves (SWs have the potential to reduce the electric energy loss in signal processing networks. The SWs called magnetostatic forward volume waves (MSFVWs are advantageous for networking due to their isotropic dispersion in the plane of a device. To control the MSFVW flow in a processing network based on yttrium iron garnet, we developed a SW absorber using artificial structures. The mechanical surface polishing method presented in this work can well control extrinsic damping without changing the SW dispersion of the host material. Furthermore, enhancement of the ferromagnetic resonance linewidth over 3 Oe was demonstrated.

  7. Comparison of two solution ways of district heating control: Using analysis methods, using artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Balate, J.; Sysala, T. [Technical Univ., Zlin (Czech Republic). Dept. of Automation and Control Technology

    1997-12-31

    The District Heating Systems - DHS (Centralized Heat Supply Systems - CHSS) are being developed in large cities in accordance with their growth. The systems are formed by enlarging networks of heat distribution to consumers and at the same time they interconnect the heat sources gradually built. The heat is distributed to the consumers through the circular networks, that are supplied by several cooperating heat sources, that means by power and heating plants and heating plants. The complicated process of heat production technology and supply requires the system approach when solving the concept of automatized control. The paper deals with comparison of the solution way using the analysis methods and using the artificial intelligence methods. (orig.)

  8. Apparatuses and methods for generating electric fields

    Science.gov (United States)

    Scott, Jill R; McJunkin, Timothy R; Tremblay, Paul L

    2013-08-06

    Apparatuses and methods relating to generating an electric field are disclosed. An electric field generator may include a semiconductive material configured in a physical shape substantially different from a shape of an electric field to be generated thereby. The electric field is generated when a voltage drop exists across the semiconductive material. A method for generating an electric field may include applying a voltage to a shaped semiconductive material to generate a complex, substantially nonlinear electric field. The shape of the complex, substantially nonlinear electric field may be configured for directing charged particles to a desired location. Other apparatuses and methods are disclosed.

  9. Rapid generation of markerless recombinant MVA vaccines by en passant recombineering of a self-excising bacterial artificial chromosome.

    Science.gov (United States)

    Cottingham, Matthew G; Gilbert, Sarah C

    2010-09-01

    The non-replicating poxviral vector modified vaccinia virus Ankara (MVA) is currently a leading candidate for development of novel recombinant vaccines against globally important diseases. The 1980s technology for making recombinant MVA (and other poxviruses) is powerful and robust, but relies on rare recombination events in poxviral-infected cells. In the 21st century, it has become possible to apply bacterial artificial chromosome (BAC) technology to poxviruses, as first demonstrated by B. Moss' lab in 2002 for vaccinia virus. A similar BAC clone of MVA was subsequently derived, but while recombination-mediated genetic engineering for rapid production was used of deletion mutants, an alternative method was required for efficient insertion of transgenes. Furthermore "markerless" viruses, which carry no trace of the selectable marker used for their isolation, are increasingly required for clinical trials, and the viruses derived via the new method contained the BAC sequence in their genomic DNA. Two methods are adapted to MVA-BAC to provide more rapid generation of markerless recombinants in weeks rather than months. "En passant" recombineering is applied to the insertion of a transgene expression cassette and the removal of the selectable marker in bacteria; and a self-excising variant of MVA-BAC is constructed, in which the BAC cassette region is rapidly and efficiently lost from the viral genome following rescue of the BAC into infectious virus. These methods greatly facilitate and accelerate production of recombinant MVA, including markerless constructs. Copyright 2010 Elsevier B.V. All rights reserved.

  10. Improved artificial bee colony algorithm based gravity matching navigation method.

    Science.gov (United States)

    Gao, Wei; Zhao, Bo; Zhou, Guang Tao; Wang, Qiu Ying; Yu, Chun Yang

    2014-07-18

    Gravity matching navigation algorithm is one of the key technologies for gravity aided inertial navigation systems. With the development of intelligent algorithms, the powerful search ability of the Artificial Bee Colony (ABC) algorithm makes it possible to be applied to the gravity matching navigation field. However, existing search mechanisms of basic ABC algorithms cannot meet the need for high accuracy in gravity aided navigation. Firstly, proper modifications are proposed to improve the performance of the basic ABC algorithm. Secondly, a new search mechanism is presented in this paper which is based on an improved ABC algorithm using external speed information. At last, modified Hausdorff distance is introduced to screen the possible matching results. Both simulations and ocean experiments verify the feasibility of the method, and results show that the matching rate of the method is high enough to obtain a precise matching position.

  11. From Unnatural Amino Acid Incorporation to Artificial Metalloenzymes

    KAUST Repository

    Makki, Arwa A.

    2016-12-04

    Studies and development of artificial metalloenzymes have developed into vibrant areas of research. It is expected that artificial metalloenzymes will be able to combine the best of enzymatic and homogenous catalysis, that is, a broad catalytic scope, high selectivity and activity under mild, aqueous conditions. Artificial metalloenzyme consist of a host protein and a newly introduced artificial metal center. The host protein merely functions as ligand controlling selectivity and augmenting reactivity, while the metal center determines the reactivity. Potential applications range from catalytic production of fine chemicals and feedstock to electron transfer utilization (e.g. fuel cells, water splitting) and medical research (e.g. metabolic screening). Particularly modern asymmetric synthesis is expected to benefit from a successful combination of the power of biocatalysis (substrate conversion via multi-step or cascade reactions, potentially immortal catalyst, unparalleled selectivity and optimization by evolutionary methods) with the versatility and mechanism based optimization methods of homogeneous catalysis. However, so far systems are either limited in structural diversity (biotin-avidin technology) or fail to deliver the selectivities expected (covalent approaches). This thesis explores a novel strategy based on the site-selective incorporation of unnatural, metal binding amino acids into a host protein. The unnatural amino acids can either serve directly as metal binding centers can be used as anchoring points for artificial metallo-cofactors. The identification expression, purification and modification of a suitable protein scaffolds is fundamental to successfully develop this field. Chapter 2 and 3 detail a rational approach leading to a highly engineered host protein. Starting with fluorescent proteins, which combine high thermal and pH stability, high expression yields, and fluorescence for ease of quantification and monitoring an efficient and fast

  12. Recent development in artificial photosynthetic model; Jinko kogosei no moderu ka kenkyu saikin no shinpo

    Energy Technology Data Exchange (ETDEWEB)

    Kaneko, M [Ibaraki Univ., Ibaraki (Japan). Faculty of Engineering

    1996-03-01

    In the conversion from solar energy into chemical energy (fuels) by photochemical conversion, an electron donor is necessary since all the fuels are reductive compounds. From the viewpoint of economic profit, water is the only one candidate as a cheap compound and existing impartially. In this paper, photosynthesis as well as the realization of its artificial model, and the relevant basic research executed recently aiming at the construction of an artificial photosynthetic system are explained. The main reaction of photosynthesis is the generation of carbohydrates by the reduction reaction of carbon dioxide with water as an electron donor and solar visual light as an energy resource. As a special example thereof, the UV photolysis of water due to the photocatalysis of a micro-particle system is introduced. The method of using a semiconductor and the method of using sensitizes are described as the photo excitation system when designing the artificial model. Additionally, as the research with respect to the construction of an artificial photosynthetic system, a photo-exciting charge transfer system is introduced. 27 refs., 1 fig.

  13. Generation of daily solar irradiation by means of artificial neural net works

    Energy Technology Data Exchange (ETDEWEB)

    Siqueira, Adalberto N.; Tiba, Chigueru; Fraidenraich, Naum [Departamento de Energia Nuclear, da Universidade Federal de Pernambuco, Av. Prof. Luiz Freire, 1000 - CDU, CEP 50.740-540 Recife, Pernambuco (Brazil)

    2010-11-15

    The present study proposes the utilization of Artificial Neural Networks (ANN) as an alternative for generating synthetic series of daily solar irradiation. The sequences were generated from the use of daily temporal series of a group of meteorological variables that were measured simultaneously. The data used were measured between the years of 1998 and 2006 in two temperate climate localities of Brazil, Ilha Solteira (Sao Paulo) and Pelotas (Rio Grande do Sul). The estimates were taken for the months of January, April, July and October, through two models which are distinguished regarding the use or nonuse of measured bright sunshine hours as an input variable. An evaluation of the performance of the 56 months of solar irradiation generated by way of ANN showed that by using the measured bright sunshine hours as an input variable (model 1), the RMSE obtained were less or equal to 23.2% being that of those, although 43 of those months presented RMSE less or equal to 12.3%. In the case of the model that did not use the measured bright sunshine hours but used a daylight length (model 2), RMSE were obtained that varied from 8.5% to 37.5%, although 38 of those months presented RMSE less or equal to 20.0%. A comparison of the monthly series for all of the years, achieved by means of the Kolmogorov-Smirnov test (to a confidence level of 99%), demonstrated that of the 16 series generated by ANN model only two, obtained by model 2 for the months of April and July in Pelotas, presented significant difference in relation to the distributions of the measured series and that all mean deviations obtained were inferior to 0.39 MJ/m{sup 2}. It was also verified that the two ANN models were able to reproduce the principal statistical characteristics of the frequency distributions of the measured series such as: mean, mode, asymmetry and Kurtosis. (author)

  14. Artificial Intelligence in Civil Engineering

    OpenAIRE

    Lu, Pengzhen; Chen, Shengyong; Zheng, Yujun

    2012-01-01

    Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives for efficiently solving problems in the civil engineering. This paper summarizes recently developed methods and theories in the developing direction for applicati...

  15. Based on Short Motion Paths and Artificial Intelligence Method for Chinese Chess Game

    Directory of Open Access Journals (Sweden)

    Chien-Ming Hung

    2017-08-01

    Full Text Available The article develops the decision rules to win each set of the Chinese chess game using evaluation algorithm and artificial intelligence method, and uses the mobile robot to be instead of the chess, and presents the movement scenarios using the shortest motion paths for mobile robots. Player can play the Chinese chess game according to the game rules with the supervised computer. The supervised computer decides the optimal motion path to win the set using artificial intelligence method, and controls mobile robots according to the programmed motion paths of the assigned chesses moving on the platform via wireless RF interface. We uses enhance A* searching algorithm to solve the shortest path problem of the assigned chess, and solve the collision problems of the motion paths for two mobile robots moving on the platform simultaneously. We implement a famous set to be called lwild horses run in farmr using the proposed method. First we use simulation method to display the motion paths of the assigned chesses for the player and the supervised computer. Then the supervised computer implements the simulation results on the chessboard platform using mobile robots. Mobile robots move on the chessboard platform according to the programmed motion paths and is guided to move on the centre line of the corridor, and avoid the obstacles (chesses, and detect the cross point of the platform using three reflective IR modules.

  16. Artificial Intelligence in Cardiology.

    Science.gov (United States)

    Johnson, Kipp W; Torres Soto, Jessica; Glicksberg, Benjamin S; Shameer, Khader; Miotto, Riccardo; Ali, Mohsin; Ashley, Euan; Dudley, Joel T

    2018-06-12

    Artificial intelligence and machine learning are poised to influence nearly every aspect of the human condition, and cardiology is not an exception to this trend. This paper provides a guide for clinicians on relevant aspects of artificial intelligence and machine learning, reviews selected applications of these methods in cardiology to date, and identifies how cardiovascular medicine could incorporate artificial intelligence in the future. In particular, the paper first reviews predictive modeling concepts relevant to cardiology such as feature selection and frequent pitfalls such as improper dichotomization. Second, it discusses common algorithms used in supervised learning and reviews selected applications in cardiology and related disciplines. Third, it describes the advent of deep learning and related methods collectively called unsupervised learning, provides contextual examples both in general medicine and in cardiovascular medicine, and then explains how these methods could be applied to enable precision cardiology and improve patient outcomes. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  17. Hybrid Wing Body Shielding Studies Using an Ultrasonic Configurable Fan Artificial Noise Source Generating Typical Turbofan Modes

    Science.gov (United States)

    Sutliff, Daniel l.; Brown, Clifford A.; Walker, Bruce E.

    2014-01-01

    An Ultrasonic Configurable Fan Artificial Noise Source (UCFANS) was designed, built, and tested in support of the NASA Langley Research Center's 14- by 22-ft wind tunnel test of the Hybrid Wing Body (HWB) full 3-D 5.8 percent scale model. The UCFANS is a 5.8 percent rapid prototype scale model of a high-bypass turbofan engine that can generate the tonal signature of proposed engines using artificial sources (no flow). The purpose of the test was to provide an estimate of the acoustic shielding benefits possible from mounting the engine on the upper surface of an HWB aircraft using the projected signature of the engine currently proposed for the HWB. The modal structures at the rating points were generated from inlet and exhaust nacelle configurations--a flat plate model was used as the shielding surface and vertical control surfaces with correct plan form shapes were also tested to determine their additional impact on shielding. Radiated acoustic data were acquired from a traversing linear array of 13 microphones, spanning 36 in. Two planes perpendicular, and two planes parallel, to the axis of the nacelle were acquired from the array sweep. In each plane the linear array traversed four sweeps, for a total span of 168 in. acquired. The resolution of the sweep is variable, so that points closer to the model are taken at a higher resolution. Contour plots of Sound Pressure Levels, and integrated Power Levels, from nacelle alone and shielded configurations are presented in this paper; as well as the in-duct mode power levels

  18. Hybrid Wing Body Shielding Studies Using an Ultrasonic Configurable Fan Artificial Noise Source Generating Typical Turbofan Modes

    Science.gov (United States)

    Sutliff, Daniel L.; Brown, Cliff; Walker, Bruce E.

    2014-01-01

    An Ultrasonic Configurable Fan Artificial Noise Source (UCFANS) was designed, built, and tested in support of the NASA Langley Research Center's 14x22 wind tunnel test of the Hybrid Wing Body (HWB) full 3-D 5.8% scale model. The UCFANS is a 5.8% rapid prototype scale model of a high-bypass turbofan engine that can generate the tonal signature of proposed engines using artificial sources (no flow). The purpose of the test was to provide an estimate of the acoustic shielding benefits possible from mounting the engine on the upper surface of an HWB aircraft using the projected signature of the engine currently proposed for the HWB. The modal structures at the rating points were generated from inlet and exhaust nacelle configurations - a flat plate model was used as the shielding surface and vertical control surfaces with correct plan form shapes were also tested to determine their additional impact on shielding. Radiated acoustic data were acquired from a traversing linear array of 13 microphones, spanning 36 inches. Two planes perpendicular, and two planes parallel, to the axis of the nacelle were acquired from the array sweep. In each plane the linear array traversed 4 sweeps, for a total span of 168 inches acquired. The resolution of the sweep is variable, so that points closer to the model are taken at a higher resolution. Contour plots of Sound Pressure Levels, and integrated Power Levels, from nacelle alone and shielded configurations are presented in this paper; as well as the in-duct mode power levels.

  19. Artificial Life - Why Should Musicians Bother?

    DEFF Research Database (Denmark)

    Berry, Rodney; Dahlstedt, Palle

    2003-01-01

    for artistic expression. Artists serve to prepare society for the invisible changes going on within it by producing artworks in response to the mechanisms of change. This paper discusses the authors' approaches to using concepts from artificial life in their musical works, which are basically of two kinds...... - artificial worlds producing music as an output, and interactive compositional tools using evolutionary algorithms to generate music and sound. It also provides a brief cultural context for these works....

  20. Great landslide events in Italian artificial reservoirs

    Directory of Open Access Journals (Sweden)

    A. Panizzo

    2005-01-01

    Full Text Available The empirical formulations to forecast landslide generated water waves, recently defined in the framework of a research program funded by the Italian National Dam Office RID (Registro Italiano Dighe, are here used to study three real cases of subaerial landslides which fell down italian artificial reservoirs. It is well known that impulse water waves generated by landslides constitute a very dangerous menace for human communities living in the shoreline of the artificial basin or downstream the dam. In 1963, the menace became tragedy, when a 270 millions m3 landslide fell down the Vajont reservoir (Italy, generated an impulse wave which destroyed the city of Longarone, and killed 2000 people. The paper is aimed at presenting the very satisfactorily reproduction of the events at hand by using forecasting formulations.  

  1. Great landslide events in Italian artificial reservoirs

    Science.gov (United States)

    Panizzo, A.; de Girolamo, P.; di Risio, M.; Maistri, A.; Petaccia, A.

    2005-09-01

    The empirical formulations to forecast landslide generated water waves, recently defined in the framework of a research program funded by the Italian National Dam Office RID (Registro Italiano Dighe), are here used to study three real cases of subaerial landslides which fell down italian artificial reservoirs. It is well known that impulse water waves generated by landslides constitute a very dangerous menace for human communities living in the shoreline of the artificial basin or downstream the dam. In 1963, the menace became tragedy, when a 270 millions m3 landslide fell down the Vajont reservoir (Italy), generated an impulse wave which destroyed the city of Longarone, and killed 2000 people. The paper is aimed at presenting the very satisfactorily reproduction of the events at hand by using forecasting formulations.

  2. [Evaluation of artificial digestion method on inspection of meat for Trichinella spiralis contamination and influence of the method on muscle larvae recovery].

    Science.gov (United States)

    Wang, Guo-Ying; Du, Jing-Fang; Dun, Guo-Qing; Sun, Wei-Li; Wang, Jin-Xi

    2011-04-01

    To evaluate the effect of artificial digestion method on inspection of meat for Trichinella spiralis contamination and its influence on activity and infectivity of muscle larvae. The mice were inoculated orally with 100 muscle larvae of T. spiralis and sacrificed on the 30th day following the infection. The muscle larvae of T. spiralis were recovered by three different test protocols employing variations of the artificial digestion method, i.e. the first test protocol evaluating digestion for 2 hours (magnetic stirrer method), the second test protocol evaluating digestion for 12 hours, and the third test protocol evaluating digestion for 20 hours. Each test group included ten samples, and each of which included 300 encapsulated larvae. Meanwhile, the activity of the recovered muscle larvae was also assessed. Forty mice were randomly divided into a control group and three digestion groups, so 4 groups (with 10 mice per group) in total. In the control group, each mouse was orally inoculated with 100 encapsulated larvae of T. spiralis. In all of the digestion test groups, each mouse was orally inoculated with 100 muscle larvae of T. spiralis. The larvae were then recovered from the different three test groups by the artificial digestion protocol variations. All the infected mice were sacrificed on the 30th day following the infection, and the muscle larvae of T. spiralis were examined respectively by the diaphragm compression method and the magnetic stirrer method. The muscle larvae detection rates were 78.47%, 76.73%, and 68.63%, the death rates were 0.59%, 4.60%, and 7.43%, and the reduction rates were 60.56%, 61.94%, and 73.07%, in the Test Group One (2-hour digestion), Test Group Two (12-hour digestion) and Test Group Three (20-hour digestion), respectively. The magnetic stirrer method (2-hour digestion method) is superior to both 12-hour digestion and 20-hour digestion methods when assessed by the detection rate, activity and infectivity of muscle larvae.

  3. Transport modeling: An artificial immune system approach

    Directory of Open Access Journals (Sweden)

    Teodorović Dušan

    2006-01-01

    Full Text Available This paper describes an artificial immune system approach (AIS to modeling time-dependent (dynamic, real time transportation phenomenon characterized by uncertainty. The basic idea behind this research is to develop the Artificial Immune System, which generates a set of antibodies (decisions, control actions that altogether can successfully cover a wide range of potential situations. The proposed artificial immune system develops antibodies (the best control strategies for different antigens (different traffic "scenarios". This task is performed using some of the optimization or heuristics techniques. Then a set of antibodies is combined to create Artificial Immune System. The developed Artificial Immune transportation systems are able to generalize, adapt, and learn based on new knowledge and new information. Applications of the systems are considered for airline yield management, the stochastic vehicle routing, and real-time traffic control at the isolated intersection. The preliminary research results are very promising.

  4. Comparison of artificial intelligence methods and empirical equations to estimate daily solar radiation

    Science.gov (United States)

    Mehdizadeh, Saeid; Behmanesh, Javad; Khalili, Keivan

    2016-08-01

    In the present research, three artificial intelligence methods including Gene Expression Programming (GEP), Artificial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) as well as, 48 empirical equations (10, 12 and 26 equations were temperature-based, sunshine-based and meteorological parameters-based, respectively) were used to estimate daily solar radiation in Kerman, Iran in the period of 1992-2009. To develop the GEP, ANN and ANFIS models, depending on the used empirical equations, various combinations of minimum air temperature, maximum air temperature, mean air temperature, extraterrestrial radiation, actual sunshine duration, maximum possible sunshine duration, sunshine duration ratio, relative humidity and precipitation were considered as inputs in the mentioned intelligent methods. To compare the accuracy of empirical equations and intelligent models, root mean square error (RMSE), mean absolute error (MAE), mean absolute relative error (MARE) and determination coefficient (R2) indices were used. The results showed that in general, sunshine-based and meteorological parameters-based scenarios in ANN and ANFIS models presented high accuracy than mentioned empirical equations. Moreover, the most accurate method in the studied region was ANN11 scenario with five inputs. The values of RMSE, MAE, MARE and R2 indices for the mentioned model were 1.850 MJ m-2 day-1, 1.184 MJ m-2 day-1, 9.58% and 0.935, respectively.

  5. Risk assessment for pipelines with active defects based on artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Anghel, Calin I. [Department of Chemical Engineering, Faculty of Chemistry and Chemical Engineering, University ' Babes-Bolyai' , Cluj-Napoca (Romania)], E-mail: canghel@chem.ubbcluj.ro

    2009-07-15

    The paper provides another insight into the pipeline risk assessment for in-service pressure piping containing defects. Beside of the traditional analytical approximation methods or sampling-based methods safety index and failure probability of pressure piping containing defects will be obtained based on a novel type of support vector machine developed in a minimax manner. The safety index or failure probability is carried out based on a binary classification approach. The procedure named classification reliability procedure, involving a link between artificial intelligence and reliability methods was developed as a user-friendly computer program in MATLAB language. To reveal the capacity of the proposed procedure two comparative numerical examples replicating a previous related work and predicting the failure probabilities of pressured pipeline with defects were presented.

  6. Risk assessment for pipelines with active defects based on artificial intelligence methods

    International Nuclear Information System (INIS)

    Anghel, Calin I.

    2009-01-01

    The paper provides another insight into the pipeline risk assessment for in-service pressure piping containing defects. Beside of the traditional analytical approximation methods or sampling-based methods safety index and failure probability of pressure piping containing defects will be obtained based on a novel type of support vector machine developed in a minimax manner. The safety index or failure probability is carried out based on a binary classification approach. The procedure named classification reliability procedure, involving a link between artificial intelligence and reliability methods was developed as a user-friendly computer program in MATLAB language. To reveal the capacity of the proposed procedure two comparative numerical examples replicating a previous related work and predicting the failure probabilities of pressured pipeline with defects were presented.

  7. Shielding Characteristics Using an Ultrasonic Configurable Fan Artificial Noise Source to Generate Modes - Experimental Measurements and Analytical Predictions

    Science.gov (United States)

    Sutliff, Daniel L.; Walker, Bruce E.

    2014-01-01

    An Ultrasonic Configurable Fan Artificial Noise Source (UCFANS) was designed, built, and tested in support of the NASA Langley Research Center's 14x22 wind tunnel test of the Hybrid Wing Body (HWB) full 3-D 5.8% scale model. The UCFANS is a 5.8% rapid prototype scale model of a high-bypass turbofan engine that can generate the tonal signature of proposed engines using artificial sources (no flow). The purpose of the program was to provide an estimate of the acoustic shielding benefits possible from mounting an engine on the upper surface of a wing; a flat plate model was used as the shielding surface. Simple analytical simulations were used to preview the radiation patterns - Fresnel knife-edge diffraction was coupled with a dense phased array of point sources to compute shielded and unshielded sound pressure distributions for potential test geometries and excitation modes. Contour plots of sound pressure levels, and integrated power levels, from nacelle alone and shielded configurations for both the experimental measurements and the analytical predictions are presented in this paper.

  8. Algorithms and architectures of artificial intelligence

    CERN Document Server

    Tyugu, E

    2007-01-01

    This book gives an overview of methods developed in artificial intelligence for search, learning, problem solving and decision-making. It gives an overview of algorithms and architectures of artificial intelligence that have reached the degree of maturity when a method can be presented as an algorithm, or when a well-defined architecture is known, e.g. in neural nets and intelligent agents. It can be used as a handbook for a wide audience of application developers who are interested in using artificial intelligence methods in their software products. Parts of the text are rather independent, so that one can look into the index and go directly to a description of a method presented in the form of an abstract algorithm or an architectural solution. The book can be used also as a textbook for a course in applied artificial intelligence. Exercises on the subject are added at the end of each chapter. Neither programming skills nor specific knowledge in computer science are expected from the reader. However, some p...

  9. High Performance Artificial Muscles Using Nanofiber and Hybrid Yarns

    Science.gov (United States)

    2015-07-14

    2. Above advance led to “Artificial Muscles From Fishing Line and Sewing Thread”, which was patent filed and then published in Science in 2014...consuming significant energy. The publication of Artificial Muscles From Fishing Line and Sewing Thread (Science, 2014) generated TV, radio, and other...gn f cant energy. The pub cat on of “Art f c a Musc es From F sh ng L ne and Sew ng Thread” (Sc ence, 2014) generated TV, rad o, and other wor d-w de

  10. Natural and artificial atoms for quantum computation

    Energy Technology Data Exchange (ETDEWEB)

    Buluta, Iulia; Ashhab, Sahel; Nori, Franco, E-mail: fnori@riken.jp [Advanced Science Institute, RIKEN, Wako-shi, Saitama, 351-0198 (Japan)

    2011-10-15

    Remarkable progress towards realizing quantum computation has been achieved using natural and artificial atoms as qubits. This paper presents a brief overview of the current status of different types of qubits. On the one hand, natural atoms (such as neutral atoms and ions) have long coherence times, and could be stored in large arrays, providing ideal 'quantum memories'. On the other hand, artificial atoms (such as superconducting circuits or semiconductor quantum dots) have the advantage of custom-designed features and could be used as 'quantum processing units'. Natural and artificial atoms can be coupled with each other and can also be interfaced with photons for long-distance communications. Hybrid devices made of natural/artificial atoms and photons may provide the next-generation design for quantum computers.

  11. Parameter estimation of brain tumors using intraoperative thermal imaging based on artificial tactile sensing in conjunction with artificial neural network

    International Nuclear Information System (INIS)

    Sadeghi-Goughari, M; Mojra, A; Sadeghi, S

    2016-01-01

    Intraoperative Thermal Imaging (ITI) is a new minimally invasive diagnosis technique that can potentially locate margins of brain tumor in order to achieve maximum tumor resection with least morbidity. This study introduces a new approach to ITI based on artificial tactile sensing (ATS) technology in conjunction with artificial neural networks (ANN) and feasibility and applicability of this method in diagnosis and localization of brain tumors is investigated. In order to analyze validity and reliability of the proposed method, two simulations were performed. (i) An in vitro experimental setup was designed and fabricated using a resistance heater embedded in agar tissue phantom in order to simulate heat generation by a tumor in the brain tissue; and (ii) A case report patient with parafalcine meningioma was presented to simulate ITI in the neurosurgical procedure. In the case report, both brain and tumor geometries were constructed from MRI data and tumor temperature and depth of location were estimated. For experimental tests, a novel assisted surgery robot was developed to palpate the tissue phantom surface to measure temperature variations and ANN was trained to estimate the simulated tumor’s power and depth. Results affirm that ITI based ATS is a non-invasive method which can be useful to detect, localize and characterize brain tumors. (paper)

  12. Estimation of Entropy Generation for Ag-MgO/Water Hybrid Nanofluid Flow through Rectangular Minichannel by Using Artificial Neural Network

    OpenAIRE

    Uysal, Cuneyt; Korkmaz, Mehmet Erdi

    2018-01-01

    The convective heat transfer andentropy generation characteristics of Ag-MgO/water hybrid nanofluid flowthrough rectangular minichannel were numerically investigated. The Reynoldsnumber was in the range of 200 to 2000 and different nanoparticle volume fractionswere varied between = 0.005 and 0.02. In addition, ArtificialNeural Network was used to create a model for estimating of entropy generationof Ag-MgO/water hybrid nanofluid flow. As a result, it was found th...

  13. Implanted artificial heart with radioisotope power source

    Energy Technology Data Exchange (ETDEWEB)

    Shumakov, V I; Griaznov, G M; Zhemchuzhnikov, G N; Kiselev, I M; Osipov, A P

    1983-02-01

    An atomic artificial heart for orthotopic implantation was developed with the following characteristics: volume, 1.2 L; weight, 1.5 kg; radioisotope power, 45 W; operating life, up to 5 years; hemodynamics, similar to natural hemodynamics. The artificial heart includes a thermal drive with systems for regulating power, feeding steam into the cylinders, return of the condensate to the steam generator, and delivery of power to the ventricles and heat container. The artificial heart is placed in an artificial pericardium partially filled with physiologic solution. It uses a steam engine with two operating cylinders that separately drive the left and right ventricles. There is no electronic control system in the proposed design. The operation of the heat engine is controlled, with preservation of autoregulation by the vascular system of the body. The separate drives for the ventricles is of primary importance as it provides for operation of the artificial heart through control of cardiac activity by venous return. Experimental testing on a hydromechanical bench demonstrated effective autoregulation.

  14. [Artificial Intelligence in Drug Discovery].

    Science.gov (United States)

    Fujiwara, Takeshi; Kamada, Mayumi; Okuno, Yasushi

    2018-04-01

    According to the increase of data generated from analytical instruments, application of artificial intelligence(AI)technology in medical field is indispensable. In particular, practical application of AI technology is strongly required in "genomic medicine" and "genomic drug discovery" that conduct medical practice and novel drug development based on individual genomic information. In our laboratory, we have been developing a database to integrate genome data and clinical information obtained by clinical genome analysis and a computational support system for clinical interpretation of variants using AI. In addition, with the aim of creating new therapeutic targets in genomic drug discovery, we have been also working on the development of a binding affinity prediction system for mutated proteins and drugs by molecular dynamics simulation using supercomputer "Kei". We also have tackled for problems in a drug virtual screening. Our developed AI technology has successfully generated virtual compound library, and deep learning method has enabled us to predict interaction between compound and target protein.

  15. Prediction of Disease Causing Non-Synonymous SNPs by the Artificial Neural Network Predictor NetDiseaseSNP

    DEFF Research Database (Denmark)

    Johansen, Morten Bo; Gonzalez-Izarzugaza, Jose Maria; Brunak, Søren

    2013-01-01

    We have developed a sequence conservation-based artificial neural network predictor called NetDiseaseSNP which classifies nsSNPs as disease-causing or neutral. Our method uses the excellent alignment generation algorithm of SIFT to identify related sequences and a combination of 31 features...

  16. PC graphics generation and management tool for real-time applications

    Science.gov (United States)

    Truong, Long V.

    1992-01-01

    A graphics tool was designed and developed for easy generation and management of personal computer graphics. It also provides methods and 'run-time' software for many common artificial intelligence (AI) or expert system (ES) applications.

  17. Kinetic parametric estimation in animal PET molecular imaging based on artificial immune network

    International Nuclear Information System (INIS)

    Chen Yuting; Ding Hong; Lu Rui; Huang Hongbo; Liu Li

    2011-01-01

    Objective: To develop an accurate,reliable method without the need of initialization in animal PET modeling for estimation of the tracer kinetic parameters based on the artificial immune network. Methods: The hepatic and left ventricular time activity curves (TACs) were obtained by drawing ROIs of liver tissue and left ventricle on dynamic 18 F-FDG PET imaging of small mice. Meanwhile, the blood TAC was analyzed by sampling the tail vein blood at different time points after injection. The artificial immune network for parametric optimization of pharmacokinetics (PKAIN) was adapted to estimate the model parameters and the metabolic rate of glucose (K i ) was calculated. Results: TACs of liver,left ventricle and tail vein blood were obtained.Based on the artificial immune network, K i in 3 mice was estimated as 0.0024, 0.0417 and 0.0047, respectively. The average weighted residual sum of squares of the output model generated by PKAIN was less than 0.0745 with a maximum standard deviation of 0.0084, which indicated that the proposed PKAIN method can provide accurate and reliable parametric estimation. Conclusion: The PKAIN method could provide accurate and reliable tracer kinetic modeling in animal PET imaging without the need of initialization of model parameters. (authors)

  18. EU copyright protection of works created by artificial intelligence systems

    OpenAIRE

    Bøhler, Helene Margrethe

    2017-01-01

    This thesis is concerned with copyright regulation of works created by artificial intelligence systems. The rapid advances in artificial intelligence are calling into question some of the fundamental assumptions upon which intellectual property law rests. Currently, the European framework of copyright law does not take non-human innovation into account. Meanwhile, advances in artificial intelligence are quickly making machine-generation of creative works a reality. Institutions of the Europea...

  19. Physical and Mechanical Characterization of Artificial Stone with Marble Calcite Waste and Epoxy Resin

    OpenAIRE

    Silva, Fernanda Souza; Ribeiro, Carlos Eduardo Gomes; Rodriguez, Rubén Jesus Sánchez

    2017-01-01

    The incorporation of calcite marble waste in epoxy resin for the production of artificial stone can represent a technical-economical method and environmentally viable, reducing the amount of discarded residue in the environment, and adding economic value to marble waste and enabling the generation of jobs. The production of natural stone in Brazil recorded an exorbitant amount of waste generated in marble processing. Only 75% of marble taken from the deposits it becomes the finished product t...

  20. Generation of New Genotypic and Phenotypic Features in Artificial and Natural Yeast Hybrids

    Directory of Open Access Journals (Sweden)

    Walter P. Pfliegler

    2014-01-01

    Full Text Available Evolution and genome stabilization have mostly been studied on the Saccharomyces hybrids isolated from natural and alcoholic fermentation environments. Genetic and phenotypic properties have usually been compared to the laboratory and reference strains, as the true ancestors of the natural hybrid yeasts are unknown. In this way the exact impact of different parental fractions on the genome organization or metabolic activity of the hybrid yeasts is difficult to resolve completely. In the present work the evolution of geno- and phenotypic properties is studied in the interspecies hybrids created by the cross-breeding of S. cerevisiae with S. uvarum or S. kudriavzevii auxotrophic mutants. We hypothesized that the extent of genomic alterations in S. cerevisiae × S. uvarum and S. cerevisiae × S. kudriavzevii should affect the physiology of their F1 offspring in different ways. Our results, obtained by amplified fragment length polymorphism (AFLP genotyping and karyotyping analyses, showed that both subgenomes of the S. cerevisiae x S. uvarum and of S. cerevisiae × S. kudriavzevii hybrids experienced various modifications. However, the S. cerevisiae × S. kudriavzevii F1 hybrids underwent more severe genomic alterations than the S. cerevisiae × S. uvarum ones. Generation of the new genotypes also influenced the physiological performances of the hybrids and the occurrence of novel phenotypes. Significant differences in carbohydrate utilization and distinct growth dynamics at increasing concentrations of sodium chloride, urea and miconazole were observed within and between the S. cerevisiae × S. uvarum and S. cerevisiae × S. kudriavzevii hybrids. Parental strains also demonstrated different contributions to the final metabolic outcomes of the hybrid yeasts. A comparison of the genotypic properties of the artificial hybrids with several hybrid isolates from the wine-related environments and wastewater demonstrated a greater genetic variability of

  1. A stereo remote sensing feature selection method based on artificial bee colony algorithm

    Science.gov (United States)

    Yan, Yiming; Liu, Pigang; Zhang, Ye; Su, Nan; Tian, Shu; Gao, Fengjiao; Shen, Yi

    2014-05-01

    To improve the efficiency of stereo information for remote sensing classification, a stereo remote sensing feature selection method is proposed in this paper presents, which is based on artificial bee colony algorithm. Remote sensing stereo information could be described by digital surface model (DSM) and optical image, which contain information of the three-dimensional structure and optical characteristics, respectively. Firstly, three-dimensional structure characteristic could be analyzed by 3D-Zernike descriptors (3DZD). However, different parameters of 3DZD could descript different complexity of three-dimensional structure, and it needs to be better optimized selected for various objects on the ground. Secondly, features for representing optical characteristic also need to be optimized. If not properly handled, when a stereo feature vector composed of 3DZD and image features, that would be a lot of redundant information, and the redundant information may not improve the classification accuracy, even cause adverse effects. To reduce information redundancy while maintaining or improving the classification accuracy, an optimized frame for this stereo feature selection problem is created, and artificial bee colony algorithm is introduced for solving this optimization problem. Experimental results show that the proposed method can effectively improve the computational efficiency, improve the classification accuracy.

  2. Dynalight Next Generation

    DEFF Research Database (Denmark)

    Jørgensen, Bo Nørregaard; Ottosen, Carl-Otto; Dam-Hansen, Carsten

    2016-01-01

    The project aims to develop the next generation of energy cost-efficient artificial lighting control that enables greenhouse growers to adapt their use of artificial lighting dynamically to fluctuations in the price of electricity. This is a necessity as fluctuations in the price of electricity c...

  3. Survey of artificial intelligence methods for detection and identification of component faults in nuclear power plants

    International Nuclear Information System (INIS)

    Reifman, J.

    1997-01-01

    A comprehensive survey of computer-based systems that apply artificial intelligence methods to detect and identify component faults in nuclear power plants is presented. Classification criteria are established that categorize artificial intelligence diagnostic systems according to the types of computing approaches used (e.g., computing tools, computer languages, and shell and simulation programs), the types of methodologies employed (e.g., types of knowledge, reasoning and inference mechanisms, and diagnostic approach), and the scope of the system. The major issues of process diagnostics and computer-based diagnostic systems are identified and cross-correlated with the various categories used for classification. Ninety-five publications are reviewed

  4. Method for protecting an electric generator

    Science.gov (United States)

    Kuehnle, Barry W.; Roberts, Jeffrey B.; Folkers, Ralph W.

    2008-11-18

    A method for protecting an electrical generator which includes providing an electrical generator which is normally synchronously operated with an electrical power grid; providing a synchronizing signal from the electrical generator; establishing a reference signal; and electrically isolating the electrical generator from the electrical power grid if the synchronizing signal is not in phase with the reference signal.

  5. Prediction of enthalpy of fusion of pure compounds using an Artificial Neural Network-Group Contribution method

    International Nuclear Information System (INIS)

    Gharagheizi, Farhad; Salehi, Gholam Reza

    2011-01-01

    Highlights: → An Artificial Neural Network-Group Contribution method is presented for prediction of enthalpy of fusion of pure compounds at their normal melting point. → Validity of the model is confirmed using a large evaluated data set containing 4157 pure compounds. → The average percent error of the model is equal to 2.65% in comparison with the experimental data. - Abstract: In this work, the Artificial Neural Network-Group Contribution (ANN-GC) method is applied to estimate the enthalpy of fusion of pure chemical compounds at their normal melting point. 4157 pure compounds from various chemical families are investigated to propose a comprehensive and predictive model. The obtained results show the Squared Correlation Coefficient (R 2 ) of 0.999, Root Mean Square Error of 0.82 kJ/mol, and average absolute deviation lower than 2.65% for the estimated properties from existing experimental values.

  6. Improved FPGA controlled artificial vascular system for plethysmographic measurements

    Directory of Open Access Journals (Sweden)

    Laqua Daniel

    2016-09-01

    Full Text Available The fetal oxygen saturation is an important parameter to determine the health status of a fetus, which is until now mostly acquired invasively. The transabdominal, fetal pulse oximetry is a promising approach to measure this non-invasively and continuously. The fetal pulse curve has to be extracted from the mixed signal of mother and fetus to determine its oxygen saturation. For this purpose efficient algorithms are necessary, which have to be evaluated under constant and reproducable test conditions. This paper presents the improved version of a phantom which can generate artificial pulse waves in a synthetic tissue phantom. The tissue phantom consists of several layers that mimic the different optical properties of the fetal and maternal tissue layers. Additionally an artificial vascular system and a dome, which mimics the bending of the belly of a pregnant woman, are incorporated. To obtain data on the pulse waves, several measurement methods are included, to help understand the behavior of the signals gained from the pulse waves. Besides pressure sensors and a transmissive method we integrated a capacitive approach, that makes use of the so called “Pin Oscillator” method. Apart from the enhancements in the tissue phantom and the measurements, we also improved the used blood substitute, which reproduces the different absorption characteristics of fetal and maternal blood. The results show that the phantom can generate pulse waves similar to the natural ones. Furthermore, the phantom represents a reference that can be used to evaluate the algorithms for transabdominal, fetal pulse oximetry.

  7. Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare

    Science.gov (United States)

    Mamoshina, Polina; Ojomoko, Lucy; Yanovich, Yury; Ostrovski, Alex; Botezatu, Alex; Prikhodko, Pavel; Izumchenko, Eugene; Aliper, Alexander; Romantsov, Konstantin; Zhebrak, Alexander; Ogu, Iraneus Obioma; Zhavoronkov, Alex

    2018-01-01

    The increased availability of data and recent advancements in artificial intelligence present the unprecedented opportunities in healthcare and major challenges for the patients, developers, providers and regulators. The novel deep learning and transfer learning techniques are turning any data about the person into medical data transforming simple facial pictures and videos into powerful sources of data for predictive analytics. Presently, the patients do not have control over the access privileges to their medical records and remain unaware of the true value of the data they have. In this paper, we provide an overview of the next-generation artificial intelligence and blockchain technologies and present innovative solutions that may be used to accelerate the biomedical research and enable patients with new tools to control and profit from their personal data as well with the incentives to undergo constant health monitoring. We introduce new concepts to appraise and evaluate personal records, including the combination-, time- and relationship-value of the data. We also present a roadmap for a blockchain-enabled decentralized personal health data ecosystem to enable novel approaches for drug discovery, biomarker development, and preventative healthcare. A secure and transparent distributed personal data marketplace utilizing blockchain and deep learning technologies may be able to resolve the challenges faced by the regulators and return the control over personal data including medical records back to the individuals. PMID:29464026

  8. Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare.

    Science.gov (United States)

    Mamoshina, Polina; Ojomoko, Lucy; Yanovich, Yury; Ostrovski, Alex; Botezatu, Alex; Prikhodko, Pavel; Izumchenko, Eugene; Aliper, Alexander; Romantsov, Konstantin; Zhebrak, Alexander; Ogu, Iraneus Obioma; Zhavoronkov, Alex

    2018-01-19

    The increased availability of data and recent advancements in artificial intelligence present the unprecedented opportunities in healthcare and major challenges for the patients, developers, providers and regulators. The novel deep learning and transfer learning techniques are turning any data about the person into medical data transforming simple facial pictures and videos into powerful sources of data for predictive analytics. Presently, the patients do not have control over the access privileges to their medical records and remain unaware of the true value of the data they have. In this paper, we provide an overview of the next-generation artificial intelligence and blockchain technologies and present innovative solutions that may be used to accelerate the biomedical research and enable patients with new tools to control and profit from their personal data as well with the incentives to undergo constant health monitoring. We introduce new concepts to appraise and evaluate personal records, including the combination-, time- and relationship-value of the data. We also present a roadmap for a blockchain-enabled decentralized personal health data ecosystem to enable novel approaches for drug discovery, biomarker development, and preventative healthcare. A secure and transparent distributed personal data marketplace utilizing blockchain and deep learning technologies may be able to resolve the challenges faced by the regulators and return the control over personal data including medical records back to the individuals.

  9. The Rack-Gear Tool Generation Modelling. Non-Analytical Method Developed in CATIA, Using the Relative Generating Trajectories Method

    Science.gov (United States)

    Teodor, V. G.; Baroiu, N.; Susac, F.; Oancea, N.

    2016-11-01

    The modelling of a curl of surfaces associated with a pair of rolling centrodes, when it is known the profile of the rack-gear's teeth profile, by direct measuring, as a coordinate matrix, has as goal the determining of the generating quality for an imposed kinematics of the relative motion of tool regarding the blank. In this way, it is possible to determine the generating geometrical error, as a base of the total error. The generation modelling allows highlighting the potential errors of the generating tool, in order to correct its profile, previously to use the tool in machining process. A method developed in CATIA is proposed, based on a new method, namely the method of “relative generating trajectories”. They are presented the analytical foundation, as so as some application for knows models of rack-gear type tools used on Maag teething machines.

  10. Development and validation of a sensitive LC-MS-MS method for the simultaneous determination of multicomponent contents in artificial Calculus Bovis.

    Science.gov (United States)

    Peng, Can; Tian, Jixin; Lv, Mengying; Huang, Yin; Tian, Yuan; Zhang, Zunjian

    2014-02-01

    Artificial Calculus Bovis is a major substitute in clinical treatment for Niuhuang, a widely used, efficacious but rare traditional Chinese medicine. However, its chemical structures and the physicochemical properties of its components are complicated, which causes difficulty in establishing a set of effective and comprehensive methods for its identification and quality control. In this study, a simple, sensitive and reliable liquid chromatography-tandem mass spectrometry method was successfully developed and validated for the simultaneous determination of bilirubin, taurine and major bile acids (including six unconjugated bile acids, two glycine-conjugated bile acids and three taurine-conjugated bile acids) in artificial Calculus Bovis using a Zorbax SB-C18 column with a gradient elution of methanol and 10 mmol/L ammonium acetate in aqueous solution (adjusted to pH 3.0 with formic acid). The mass spectra were obtained in the negative ion mode using dehydrocholic acid as the internal standard. The content of each analyte in artificial Calculus Bovis was determined by monitoring specific ion pairs in the selected reaction monitoring mode. All analytes demonstrated perfect linearity (r(2) > 0.994) in a wide dynamic range, and 10 batches of samples from different sources were further analyzed. This study provided a comprehensive method for the quality control of artificial Calculus Bovis.

  11. Artificial intelligence in medicine.

    OpenAIRE

    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 ...

  12. Comparison of three artificial digestion methods for detection of non-encapsulated Trichinella pseudospiralis larvae in pork.

    Science.gov (United States)

    Nöckler, K; Reckinger, S; Szabó, I; Maddox-Hyttel, C; Pozio, E; van der Giessen, J; Vallée, I; Boireau, P

    2009-02-23

    In a ring trial involving five laboratories (A, B, C, D, and E), three different methods of artificial digestion were compared for the detection of non-encapsulated Trichinella pseudospiralis larvae in minced meat. Each sample panel consisted of ten 1g minced pork samples. All samples in each panel were derived from a bulk meat preparation with a nominal value of either 7 or 17 larvae per g (lpg). Samples were tested for the number of muscle larvae using the magnetic stirrer method (labs A, B, and E), stomacher method (lab B), and Trichomatic 35 (labs C and D). T. pseudospiralis larvae were found in all 120 samples tested. For samples with 7 lpg, larval recoveries were significantly higher using the stomacher method versus the magnetic stirrer method, but there were no significant differences for samples with 17 lpg. In comparing laboratory results irrespective of the method used, lab B detected a significantly higher number of larvae than lab E for samples with 7 lpg, and lab E detected significantly less larvae than labs A, B, and D in samples with 17 lpg. The lowest overall variation for quantitative results (i.e. larval recoveries which were outside the tolerance range) was achieved by using the magnetic stirrer method (22%), followed by the stomacher method (25%), and Trichomatic 35 (30%). Results revealed that T. pseudospiralis larvae in samples with a nominal value of 7 and 17 lpg can be detected by all three methods of artificial digestion.

  13. In Defense of Artificial Replacement.

    Science.gov (United States)

    Shiller, Derek

    2017-06-01

    If it is within our power to provide a significantly better world for future generations at a comparatively small cost to ourselves, we have a strong moral reason to do so. One way of providing a significantly better world may involve replacing our species with something better. It is plausible that in the not-too-distant future, we will be able to create artificially intelligent creatures with whatever physical and psychological traits we choose. Granted this assumption, it is argued that we should engineer our extinction so that our planet's resources can be devoted to making artificial creatures with better lives. © 2017 John Wiley & Sons Ltd.

  14. Artificial Consciousness or Artificial Intelligence

    OpenAIRE

    Spanache Florin

    2017-01-01

    Artificial intelligence is a tool designed by people for the gratification of their own creative ego, so we can not confuse conscience with intelligence and not even intelligence in its human representation with conscience. They are all different concepts and they have different uses. Philosophically, there are differences between autonomous people and automatic artificial intelligence. This is the difference between intelligence and artificial intelligence, autonomous versus a...

  15. Soft computing in artificial intelligence

    CERN Document Server

    Matson, Eric

    2014-01-01

    This book explores the concept of artificial intelligence based on knowledge-based algorithms. Given the current hardware and software technologies and artificial intelligence theories, we can think of how efficient to provide a solution, how best to implement a model and how successful to achieve it. This edition provides readers with the most recent progress and novel solutions in artificial intelligence. This book aims at presenting the research results and solutions of applications in relevance with artificial intelligence technologies. We propose to researchers and practitioners some methods to advance the intelligent systems and apply artificial intelligence to specific or general purpose. This book consists of 13 contributions that feature fuzzy (r, s)-minimal pre- and β-open sets, handling big coocurrence matrices, Xie-Beni-type fuzzy cluster validation, fuzzy c-regression models, combination of genetic algorithm and ant colony optimization, building expert system, fuzzy logic and neural network, ind...

  16. Devices and methods for generating an aerosol

    KAUST Repository

    Bisetti, Fabrizio

    2016-03-03

    Aerosol generators and methods of generating aerosols are provided. The aerosol can be generated at a stagnation interface between a hot, wet stream and a cold, dry stream. The aerosol has the benefit that the properties of the aerosol can be precisely controlled. The stagnation interface can be generated, for example, by the opposed flow of the hot stream and the cold stream. The aerosol generator and the aerosol generation methods are capable of producing aerosols with precise particle sizes and a narrow size distribution. The properties of the aerosol can be controlled by controlling one or more of the stream temperatures, the saturation level of the hot stream, and the flow times of the streams.

  17. Artificial heartbeat: design and fabrication of a biologically inspired pump

    International Nuclear Information System (INIS)

    Walters, Peter; Stephenson, Robert; Lewis, Amy; Stinchcombe, Andrew; Ieropoulos, Ioannis

    2013-01-01

    We present a biologically inspired actuator exhibiting a novel pumping action. The design of the ‘artificial heartbeat’ actuator is inspired by physical principles derived from the structure and function of the human heart. The actuator employs NiTi artificial muscles and is powered by electrical energy generated by microbial fuel cells (MFCs). We describe the design and fabrication of the actuator and report the results of tests conducted to characterize its performance. This is the first artificial muscle-driven pump to be powered by MFCs fed on human urine. Results are presented in terms of the peak pumping pressure generated by the actuator, as well as for the volume of fluid transferred, when the actuator was powered by energy stored in a capacitor bank, which was charged by 24 MFCs fed on urine. The results demonstrate the potential for the artificial heartbeat actuator to be employed as a fluid circulation pump in future generations of MFC-powered robots (‘EcoBots’) that extract energy from organic waste. We also envisage that the actuator could in the future form part of a bio-robotic artwork or ‘bio-automaton’ that could help increase public awareness of research in robotics, bio-energy and biologically inspired design. (paper)

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

    International Nuclear Information System (INIS)

    Ortiz R, J. M.; Martinez B, M. R.; Vega C, H. R.; Gallego D, E.; Lorente F, A.; Mendez V, R.; Los Arcos M, J. M.; Guerrero A, J. E.

    2011-01-01

    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)

  19. Artificial neural networks for automation of Rutherford backscattering spectroscopy experiments and data analysis

    International Nuclear Information System (INIS)

    Barradas, N.P.; Vieira, A.; Patricio, R.

    2002-01-01

    We present an algorithm based on artificial neural networks able to determine optimized experimental conditions for Rutherford backscattering measurements of Ge-implanted Si. The algorithm can be implemented for any other element implanted into a lighter substrate. It is foreseeable that the method developed in this work can be applied to still many other systems. The algorithm presented is a push-button black box, and does not require any human intervention. It is thus suited for automated control of an experimental setup, given an interface to the relevant hardware. Once the experimental conditions are optimized, the algorithm analyzes the final data obtained, and determines the desired parameters. The method is thus also suited for automated analysis of the data. The algorithm presented can be easily extended to other ion beam analysis techniques. Finally, it is suggested how the artificial neural networks required for automated control and analysis of experiments could be automatically generated. This would be suited for automated generation of the required computer code. Thus could RBS be done without experimentalists, data analysts, or programmers, with only technicians to keep the machines running

  20. Comparison of classical statistical methods and artificial neural network in traffic noise prediction

    International Nuclear Information System (INIS)

    Nedic, Vladimir; Despotovic, Danijela; Cvetanovic, Slobodan; Despotovic, Milan; Babic, Sasa

    2014-01-01

    Traffic is the main source of noise in urban environments and significantly affects human mental and physical health and labor productivity. Therefore it is very important to model the noise produced by various vehicles. Techniques for traffic noise prediction are mainly based on regression analysis, which generally is not good enough to describe the trends of noise. In this paper the application of artificial neural networks (ANNs) for the prediction of traffic noise is presented. As input variables of the neural network, the proposed structure of the traffic flow and the average speed of the traffic flow are chosen. The output variable of the network is the equivalent noise level in the given time period L eq . Based on these parameters, the network is modeled, trained and tested through a comparative analysis of the calculated values and measured levels of traffic noise using the originally developed user friendly software package. It is shown that the artificial neural networks can be a useful tool for the prediction of noise with sufficient accuracy. In addition, the measured values were also used to calculate equivalent noise level by means of classical methods, and comparative analysis is given. The results clearly show that ANN approach is superior in traffic noise level prediction to any other statistical method. - Highlights: • We proposed an ANN model for prediction of traffic noise. • We developed originally designed user friendly software package. • The results are compared with classical statistical methods. • The results are much better predictive capabilities of ANN model

  1. Comparison of classical statistical methods and artificial neural network in traffic noise prediction

    Energy Technology Data Exchange (ETDEWEB)

    Nedic, Vladimir, E-mail: vnedic@kg.ac.rs [Faculty of Philology and Arts, University of Kragujevac, Jovana Cvijića bb, 34000 Kragujevac (Serbia); Despotovic, Danijela, E-mail: ddespotovic@kg.ac.rs [Faculty of Economics, University of Kragujevac, Djure Pucara Starog 3, 34000 Kragujevac (Serbia); Cvetanovic, Slobodan, E-mail: slobodan.cvetanovic@eknfak.ni.ac.rs [Faculty of Economics, University of Niš, Trg kralja Aleksandra Ujedinitelja, 18000 Niš (Serbia); Despotovic, Milan, E-mail: mdespotovic@kg.ac.rs [Faculty of Engineering, University of Kragujevac, Sestre Janjic 6, 34000 Kragujevac (Serbia); Babic, Sasa, E-mail: babicsf@yahoo.com [College of Applied Mechanical Engineering, Trstenik (Serbia)

    2014-11-15

    Traffic is the main source of noise in urban environments and significantly affects human mental and physical health and labor productivity. Therefore it is very important to model the noise produced by various vehicles. Techniques for traffic noise prediction are mainly based on regression analysis, which generally is not good enough to describe the trends of noise. In this paper the application of artificial neural networks (ANNs) for the prediction of traffic noise is presented. As input variables of the neural network, the proposed structure of the traffic flow and the average speed of the traffic flow are chosen. The output variable of the network is the equivalent noise level in the given time period L{sub eq}. Based on these parameters, the network is modeled, trained and tested through a comparative analysis of the calculated values and measured levels of traffic noise using the originally developed user friendly software package. It is shown that the artificial neural networks can be a useful tool for the prediction of noise with sufficient accuracy. In addition, the measured values were also used to calculate equivalent noise level by means of classical methods, and comparative analysis is given. The results clearly show that ANN approach is superior in traffic noise level prediction to any other statistical method. - Highlights: • We proposed an ANN model for prediction of traffic noise. • We developed originally designed user friendly software package. • The results are compared with classical statistical methods. • The results are much better predictive capabilities of ANN model.

  2. Long-time stability effects of quadrature and artificial viscosity on nodal discontinuous Galerkin methods for gas dynamics

    Science.gov (United States)

    Durant, Bradford; Hackl, Jason; Balachandar, Sivaramakrishnan

    2017-11-01

    Nodal discontinuous Galerkin schemes present an attractive approach to robust high-order solution of the equations of fluid mechanics, but remain accompanied by subtle challenges in their consistent stabilization. The effect of quadrature choices (full mass matrix vs spectral elements), over-integration to manage aliasing errors, and explicit artificial viscosity on the numerical solution of a steady homentropic vortex are assessed over a wide range of resolutions and polynomial orders using quadrilateral elements. In both stagnant and advected vortices in periodic and non-periodic domains the need arises for explicit stabilization beyond the numerical surface fluxes of discontinuous Galerkin spectral elements. Artificial viscosity via the entropy viscosity method is assessed as a stabilizing mechanism. It is shown that the regularity of the artificial viscosity field is essential to its use for long-time stabilization of small-scale features in nodal discontinuous Galerkin solutions of the Euler equations of gas dynamics. Supported by the Department of Energy Predictive Science Academic Alliance Program Contract DE-NA0002378.

  3. Artificial gametes: a systematic review of biological progress towards clinical application

    NARCIS (Netherlands)

    Hendriks, Saskia; Dancet, Eline A. F.; van Pelt, Ans M. M.; Hamer, Geert; Repping, Sjoerd

    2015-01-01

    Recent progress in the formation of artificial gametes, i.e. gametes generated by manipulation of their progenitors or of somatic cells, has led to scientific and societal discussion about their use in medically assisted reproduction (MAR). Artificial gametes could potentially help infertile men and

  4. Space Environment Modelling with the Use of Artificial Intelligence Methods

    Science.gov (United States)

    Lundstedt, H.; Wintoft, P.; Wu, J.-G.; Gleisner, H.; Dovheden, V.

    1996-12-01

    Space based technological systems are affected by the space weather in many ways. Several severe failures of satellites have been reported at times of space storms. Our society also increasingly depends on satellites for communication, navigation, exploration, and research. Predictions of the conditions in the satellite environment have therefore become very important. We will here present predictions made with the use of artificial intelligence (AI) techniques, such as artificial neural networks (ANN) and hybrids of AT methods. We are developing a space weather model based on intelligence hybrid systems (IHS). The model consists of different forecast modules, each module predicts the space weather on a specific time-scale. The time-scales range from minutes to months with the fundamental time-scale of 1-5 minutes, 1-3 hours, 1-3 days, and 27 days. Solar and solar wind data are used as input data. From solar magnetic field measurements, either made on the ground at Wilcox Solar Observatory (WSO) at Stanford, or made from space by the satellite SOHO, solar wind parameters can be predicted and modelled with ANN and MHD models. Magnetograms from WSO are available on a daily basis. However, from SOHO magnetograms will be available every 90 minutes. SOHO magnetograms as input to ANNs will therefore make it possible to even predict solar transient events. Geomagnetic storm activity can today be predicted with very high accuracy by means of ANN methods using solar wind input data. However, at present real-time solar wind data are only available during part of the day from the satellite WIND. With the launch of ACE in 1997, solar wind data will on the other hand be available during 24 hours per day. The conditions of the satellite environment are not only disturbed at times of geomagnetic storms but also at times of intense solar radiation and highly energetic particles. These events are associated with increased solar activity. Predictions of these events are therefore

  5. Artificial neural network for violation analysis

    International Nuclear Information System (INIS)

    Zhang, Z.; Polet, P.; Vanderhaegen, F.; Millot, P.

    2004-01-01

    Barrier removal (BR) is a safety-related violation, and it can be analyzed in terms of benefits, costs, and potential deficits. In order to allow designers to integrate BR into the risk analysis during the initial design phase or during re-design work, we propose a connectionist method integrating self-organizing maps (SOM). The basic SOM is an artificial neural network that, on the basis of the information contained in a multi-dimensional space, generates a space of lesser dimensions. Three algorithms--Unsupervised SOM, Supervised SOM, and Hierarchical SOM--have been developed to permit BR classification and prediction in terms of the different criteria. The proposed method can be used, on the one hand, to foresee/predict the possibility level of a new/changed barrier (prospective analysis), and on the other hand, to synthetically regroup/rearrange the BR of a given human-machine system (retrospective analysis). We applied this method to the BR analysis of an experimental railway simulator, and our preliminary results are presented here

  6. Beyond AI: Artificial Dreams Conference

    CERN Document Server

    Zackova, Eva; Kelemen, Jozef; Beyond Artificial Intelligence : The Disappearing Human-Machine Divide

    2015-01-01

    This book is an edited collection of chapters based on the papers presented at the conference “Beyond AI: Artificial Dreams” held in Pilsen in November 2012. The aim of the conference was to question deep-rooted ideas of artificial intelligence and cast critical reflection on methods standing at its foundations.  Artificial Dreams epitomize our controversial quest for non-biological intelligence, and therefore the contributors of this book tried to fully exploit such a controversy in their respective chapters, which resulted in an interdisciplinary dialogue between experts from engineering, natural sciences and humanities.   While pursuing the Artificial Dreams, it has become clear that it is still more and more difficult to draw a clear divide between human and machine. And therefore this book tries to portrait such an image of what lies beyond artificial intelligence: we can see the disappearing human-machine divide, a very important phenomenon of nowadays technological society, the phenomenon which i...

  7. Method of operating a thermoelectric generator

    Science.gov (United States)

    Reynolds, Michael G; Cowgill, Joshua D

    2013-11-05

    A method for operating a thermoelectric generator supplying a variable-load component includes commanding the variable-load component to operate at a first output and determining a first load current and a first load voltage to the variable-load component while operating at the commanded first output. The method also includes commanding the variable-load component to operate at a second output and determining a second load current and a second load voltage to the variable-load component while operating at the commanded second output. The method includes calculating a maximum power output of the thermoelectric generator from the determined first load current and voltage and the determined second load current and voltage, and commanding the variable-load component to operate at a third output. The commanded third output is configured to draw the calculated maximum power output from the thermoelectric generator.

  8. Artificial Satellites Observations Using the Complex of Telescopes of RI "MAO"

    Science.gov (United States)

    Sybiryakova, Ye. S.; Shulga, O. V.; Vovk, V. S.; Kaliuzny, M. P.; Bushuev, F. I.; Kulichenko, M. O.; Haloley, M. I.; Chernozub, V. M.

    2017-02-01

    Special methods, means and software for cosmic objects' observation and processing of obtained results were developed. Combined method, which consists in separated accumulation of images of reference stars and artificial objects, is the main method used in observations of artificial cosmic objects. It is used for observations of artificial objects at all types of orbits.

  9. Natural - synthetic - artificial!

    DEFF Research Database (Denmark)

    Nielsen, Peter E

    2010-01-01

    The terms "natural," "synthetic" and "artificial" are discussed in relation to synthetic and artificial chromosomes and genomes, synthetic and artificial cells and artificial life.......The terms "natural," "synthetic" and "artificial" are discussed in relation to synthetic and artificial chromosomes and genomes, synthetic and artificial cells and artificial life....

  10. Structure–function relationship of skeletal muscle provides inspiration for design of new artificial muscle

    International Nuclear Information System (INIS)

    Gao, Yingxin; Zhang, Chi

    2015-01-01

    A variety of actuator technologies have been developed to mimic biological skeletal muscle that generates force in a controlled manner. Force generation process of skeletal muscle involves complicated biophysical and biochemical mechanisms; therefore, it is impossible to replace biological muscle. In biological skeletal muscle tissue, the force generation of a muscle depends not only on the force generation capacity of the muscle fiber, but also on many other important factors, including muscle fiber type, motor unit recruitment, architecture, structure and morphology of skeletal muscle, all of which have significant impact on the force generation of the whole muscle or force transmission from muscle fibers to the tendon. Such factors have often been overlooked, but can be incorporated in artificial muscle design, especially with the discovery of new smart materials and the development of innovative fabrication and manufacturing technologies. A better understanding of the physiology and structure–function relationship of skeletal muscle will therefore benefit the artificial muscle design. In this paper, factors that affect muscle force generation are reviewed. Mathematical models used to model the structure–function relationship of skeletal muscle are reviewed and discussed. We hope the review will provide inspiration for the design of a new generation of artificial muscle by incorporating the structure–function relationship of skeletal muscle into the design of artificial muscle. (topical review)

  11. Structure-function relationship of skeletal muscle provides inspiration for design of new artificial muscle

    Science.gov (United States)

    Gao, Yingxin; Zhang, Chi

    2015-03-01

    A variety of actuator technologies have been developed to mimic biological skeletal muscle that generates force in a controlled manner. Force generation process of skeletal muscle involves complicated biophysical and biochemical mechanisms; therefore, it is impossible to replace biological muscle. In biological skeletal muscle tissue, the force generation of a muscle depends not only on the force generation capacity of the muscle fiber, but also on many other important factors, including muscle fiber type, motor unit recruitment, architecture, structure and morphology of skeletal muscle, all of which have significant impact on the force generation of the whole muscle or force transmission from muscle fibers to the tendon. Such factors have often been overlooked, but can be incorporated in artificial muscle design, especially with the discovery of new smart materials and the development of innovative fabrication and manufacturing technologies. A better understanding of the physiology and structure-function relationship of skeletal muscle will therefore benefit the artificial muscle design. In this paper, factors that affect muscle force generation are reviewed. Mathematical models used to model the structure-function relationship of skeletal muscle are reviewed and discussed. We hope the review will provide inspiration for the design of a new generation of artificial muscle by incorporating the structure-function relationship of skeletal muscle into the design of artificial muscle.

  12. Coupling artificial intelligence and numerical computation for engineering design (Invited paper)

    Science.gov (United States)

    Tong, S. S.

    1986-01-01

    The possibility of combining artificial intelligence (AI) systems and numerical computation methods for engineering designs is considered. Attention is given to three possible areas of application involving fan design, controlled vortex design of turbine stage blade angles, and preliminary design of turbine cascade profiles. Among the AI techniques discussed are: knowledge-based systems; intelligent search; and pattern recognition systems. The potential cost and performance advantages of an AI-based design-generation system are discussed in detail.

  13. Time evolution of artificial plasma cloud in atmospheric environment

    International Nuclear Information System (INIS)

    Lu Qiming; Yang Weihong; Liu Wandong

    2004-01-01

    By analyzing the time evolution of artificial plasma cloud in the high altitude of atmospheric environment, the authors found that there are two zones, an exponential attenuation zone and a linearly attenuating zone, existing in the spatial distribution of electron density of the artificial plasma clouds. The plasma generator's particle flux density only contributes to the exponential attenuation zone, and has no effect on the linear attenuation zone. The average electron density in the linear attenuation zone is about 10 -5 of neutral particle density, and can diffuse over a wider area. The conclusion will supply some valuable references to the research of electromagnetic wave and artificial plasma interaction, the plasma invisibleness research of missile and special aerocraft, and the design of artificial plasma source. (authors)

  14. Handling the decline of ground water using artificial recharge areas

    Science.gov (United States)

    Hidayatullah, Muhammad Shofi; Yoga, Kuncaraningrat Edi; Muslim, Dicky

    2017-11-01

    Jatinagor, a region with rapid growth cause increasing in water demand. The ground water surface in the observation area shows a decrease based on its potential. This deflation is mainly caused by the inequality between inputs and outputs of the ground water itself. The decrease of this ground water surface is also caused by the number of catchment areas that keeps decreasing. According to the data analysis of geology and hydrology, the condition of ground water in Jatinangor on 2015 had indicated a decrease compared to 2010. Nowadays, the longlivity of clean water can be ensure by the hydrogeology engineering, which is to construct an artificial recharge for ground water in use. The numerical method is aims to determine the number of ground water supply in Jatinangor. According to the research, the most suitable artificial recharge is in the form of a small dam located in the internment river. With the area of 209.000 m2, this dam will be able to contain 525 m3 runoff water with the intensity of maximum rainfall effectively 59,44 mm/hour. The increase of water volume generate by this artificial recharge, fulfilled the demand of clean water.

  15. Artificial sweetener; Jinko kanmiryo

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1999-08-01

    The patents related to the artificial sweetener that it is introduced to the public in 3 years from 1996 until 1998 are 115 cases. The sugar quality which makes an oligosaccharide and sugar alcohol the subject is greatly over 28 cases of the non-sugar quality in the one by the kind as a general tendency of these patents at 73 cases in such cases as the Aspartame. The method of manufacture patent, which included new material around other peptides, the oligosaccharide and sugar alcohol isn`t inferior to 56 cases of the formation thing patent at 43 cases, and pays attention to the thing, which is many by the method of manufacture, formation. There is most improvement of the quality of sweetness with 31 cases in badness of the aftertaste which is characteristic of the artificial sweetener and so on, and much stability including the improvement in the flavor of food by the artificial sweetener, a long time and dissolution, fluid nature and productivity and improvement of the economy such as a cost are seen with effect on a purpose. (NEDO)

  16. Advanced Applications of Neural Networks and Artificial Intelligence: A Review

    OpenAIRE

    Koushal Kumar; Gour Sundar Mitra Thakur

    2012-01-01

    Artificial Neural Network is a branch of Artificial intelligence and has been accepted as a new computing technology in computer science fields. This paper reviews the field of Artificial intelligence and focusing on recent applications which uses Artificial Neural Networks (ANN’s) and Artificial Intelligence (AI). It also considers the integration of neural networks with other computing methods Such as fuzzy logic to enhance the interpretation ability of data. Artificial Neural Networks is c...

  17. Design of alluvial Egyptian irrigation canals using artificial neural networks method

    Directory of Open Access Journals (Sweden)

    Hassan Ibrahim Mohamed

    2013-06-01

    Full Text Available In the present study, artificial neural networks method (ANNs is used to estimate the main parameters which used in design of stable alluvial channels. The capability of ANN models to predict the stable alluvial channels dimensions is investigated, where the flow rate and sediment mean grain size were considered as input variables and wetted perimeter, hydraulic radius, and water surface slope were considered as output variables. The used ANN models are based on a back propagation algorithm to train a multi-layer feed-forward network (Levenberg Marquardt algorithm. The proposed models were verified using 311 data sets of field data collected from 61 manmade canals and drains. Several statistical measures and graphical representation are used to check the accuracy of the models in comparison with previous empirical equations. The results of the developed ANN model proved that this technique is reliable in such field compared with previously developed methods.

  18. Devices and methods for generating an aerosol

    KAUST Repository

    Bisetti, Fabrizio; Scribano, Gianfranco

    2016-01-01

    Aerosol generators and methods of generating aerosols are provided. The aerosol can be generated at a stagnation interface between a hot, wet stream and a cold, dry stream. The aerosol has the benefit that the properties of the aerosol can

  19. Prediction of U-Mo dispersion nuclear fuels with Al-Si alloy using artificial neural network

    International Nuclear Information System (INIS)

    Susmikanti, Mike; Sulistyo, Jos

    2014-01-01

    Dispersion nuclear fuels, consisting of U-Mo particles dispersed in an Al-Si matrix, are being developed as fuel for research reactors. The equilibrium relationship for a mixture component can be expressed in the phase diagram. It is important to analyze whether a mixture component is in equilibrium phase or another phase. The purpose of this research it is needed to built the model of the phase diagram, so the mixture component is in the stable or melting condition. Artificial neural network (ANN) is a modeling tool for processes involving multivariable non-linear relationships. The objective of the present work is to develop code based on artificial neural network models of system equilibrium relationship of U-Mo in Al-Si matrix. This model can be used for prediction of type of resulting mixture, and whether the point is on the equilibrium phase or in another phase region. The equilibrium model data for prediction and modeling generated from experimentally data. The artificial neural network with resilient backpropagation method was chosen to predict the dispersion of nuclear fuels U-Mo in Al-Si matrix. This developed code was built with some function in MATLAB. For simulations using ANN, the Levenberg-Marquardt method was also used for optimization. The artificial neural network is able to predict the equilibrium phase or in the phase region. The develop code based on artificial neural network models was built, for analyze equilibrium relationship of U-Mo in Al-Si matrix

  20. Log-Linear Model Based Behavior Selection Method for Artificial Fish Swarm Algorithm

    Directory of Open Access Journals (Sweden)

    Zhehuang Huang

    2015-01-01

    Full Text Available Artificial fish swarm algorithm (AFSA is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishes are an important task. To solve these problems, an improved artificial fish swarm algorithm based on log-linear model is proposed and implemented in this paper. There are three main works. Firstly, we proposed a new behavior selection algorithm based on log-linear model which can enhance decision making ability of behavior selection. Secondly, adaptive movement behavior based on adaptive weight is presented, which can dynamically adjust according to the diversity of fishes. Finally, some new behaviors are defined and introduced into artificial fish swarm algorithm at the first time to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and reasonable convergence speed compared with the standard artificial fish swarm algorithm.

  1. Log-linear model based behavior selection method for artificial fish swarm algorithm.

    Science.gov (United States)

    Huang, Zhehuang; Chen, Yidong

    2015-01-01

    Artificial fish swarm algorithm (AFSA) is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishes are an important task. To solve these problems, an improved artificial fish swarm algorithm based on log-linear model is proposed and implemented in this paper. There are three main works. Firstly, we proposed a new behavior selection algorithm based on log-linear model which can enhance decision making ability of behavior selection. Secondly, adaptive movement behavior based on adaptive weight is presented, which can dynamically adjust according to the diversity of fishes. Finally, some new behaviors are defined and introduced into artificial fish swarm algorithm at the first time to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and reasonable convergence speed compared with the standard artificial fish swarm algorithm.

  2. Magnetic artificial cilia for microfluidic propulsion

    NARCIS (Netherlands)

    Khaderi, S.N.; den Toonder, J.M.J.; Onck, P.R.

    2015-01-01

    Cilia are tiny hair-like structures that cover the surfaces of biological cells. One of their functions is to generate flow. Artificial cilia are mechanical actuators that are designed to mimic the motion of natural cilia in order to create fluid transport in microchannels. These fluid propulsion

  3. Magnetic Artificial Cilia for Microfluidic Propulsion

    NARCIS (Netherlands)

    Khaderi, Syed N.; den Toonder, Jaap M. J.; Onck, Patrick R.; Bordas, Stéphane P.A.; Balint, Daniel S.

    2015-01-01

    Cilia are tiny hair-like structures that cover the surfaces of biological cells. One of their functions is to generate flow. Artificial cilia are mechanical actuators that are designed to mimic the motion of natural cilia in order to create fluid transport in microchannels. These fluid propulsion

  4. Review of Data Preprocessing Methods for Sign Language Recognition Systems based on Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Zorins Aleksejs

    2016-12-01

    Full Text Available The article presents an introductory analysis of relevant research topic for Latvian deaf society, which is the development of the Latvian Sign Language Recognition System. More specifically the data preprocessing methods are discussed in the paper and several approaches are shown with a focus on systems based on artificial neural networks, which are one of the most successful solutions for sign language recognition task.

  5. Folding pathways explored with artificial potential functions

    International Nuclear Information System (INIS)

    Ulutaş, B; Bozma, I; Haliloglu, T

    2009-01-01

    This paper considers the generation of trajectories to a given protein conformation and presents a novel approach based on artificial potential functions—originally proposed for multi-robot navigation. The artificial potential function corresponds to a simplified energy model, but with the novelty that—motivated by work on robotic navigation—a nonlinear compositional scheme of constructing the energy model is adapted instead of an additive formulation. The artificial potential naturally gives rise to a dynamic system for the protein structure that ensures collision-free motion to an equilibrium point. In cases where the equilibrium point is the native conformation, the motion trajectory corresponds to the folding pathway. This framework is used to investigate folding in a variety of protein structures, and the results are compared with those of other approaches including experimental studies

  6. Vapor generation methods for explosives detection research

    Energy Technology Data Exchange (ETDEWEB)

    Grate, Jay W.; Ewing, Robert G.; Atkinson, David A.

    2012-12-01

    The generation of calibrated vapor samples of explosives compounds remains a challenge due to the low vapor pressures of the explosives, adsorption of explosives on container and tubing walls, and the requirement to manage (typically) multiple temperature zones as the vapor is generated, diluted, and delivered. Methods that have been described to generate vapors can be classified as continuous or pulsed flow vapor generators. Vapor sources for continuous flow generators are typically explosives compounds supported on a solid support, or compounds contained in a permeation or diffusion device. Sources are held at elevated isothermal temperatures. Similar sources can be used for pulsed vapor generators; however, pulsed systems may also use injection of solutions onto heated surfaces with generation of both solvent and explosives vapors, transient peaks from a gas chromatograph, or vapors generated by s programmed thermal desorption. This article reviews vapor generator approaches with emphasis on the method of generating the vapors and on practical aspects of vapor dilution and handling. In addition, a gas chromatographic system with two ovens that is configurable with up to four heating ropes is proposed that could serve as a single integrated platform for explosives vapor generation and device testing. Issues related to standards, calibration, and safety are also discussed.

  7. Multidirectional Artificial Muscles from Nylon.

    Science.gov (United States)

    Mirvakili, Seyed M; Hunter, Ian W

    2017-01-01

    Multidirectional artificial muscles are made from highly oriented nylon filaments. Thanks to the low thermal conductivity of nylon and its anisotropic thermal expansion, bending occurs when a nylon beam is differentially heated. This heat can be generated via a Joule heating mechanism or high power laser pulses. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. The deconvolution of complex spectra by artificial immune system

    Science.gov (United States)

    Galiakhmetova, D. I.; Sibgatullin, M. E.; Galimullin, D. Z.; Kamalova, D. I.

    2017-11-01

    An application of the artificial immune system method for decomposition of complex spectra is presented. The results of decomposition of the model contour consisting of three components, Gaussian contours, are demonstrated. The method of artificial immune system is an optimization method, which is based on the behaviour of the immune system and refers to modern methods of search for the engine optimization.

  9. Hybrid Modeling and Optimization of Manufacturing Combining Artificial Intelligence and Finite Element Method

    CERN Document Server

    Quiza, Ramón; Davim, J Paulo

    2012-01-01

    Artificial intelligence (AI) techniques and the finite element method (FEM) are both powerful computing tools, which are extensively used for modeling and optimizing manufacturing processes. The combination of these tools has resulted in a new flexible and robust approach as several recent studies have shown. This book aims to review the work already done in this field as well as to expose the new possibilities and foreseen trends. The book is expected to be useful for postgraduate students and researchers, working in the area of modeling and optimization of manufacturing processes.

  10. Assessment of cavitation in artificial approximal dental lesions with near-IR imaging

    Science.gov (United States)

    Simon, Jacob C.; Darling, Cynthia L.; Fried, Daniel

    2017-02-01

    Bitewing radiography is still considered state-of-the-art diagnostic technology for assessing cavitation within approximal carious dental lesions, even though radiographs cannot resolve cavitated surfaces but instead are used to measure lesion depth in order to predict cavitation. Clinicians need new technologies capable of determining whether approximal carious lesions have become cavitated because not all lesions progress to cavitation. Assessing lesion cavitation from near-infrared (NIR) imaging methods holds great potential due to the high transparency of enamel in the NIR region from λ=1300-1700-nm, which allows direct visualization and quantified measurements of enamel demineralization. The objective of this study was to measure the change in lesion appearance between non-cavitated and cavitated lesions in artificially generated lesions using NIR imaging modalities (two-dimensional) at λ=1300-nm and λ=1450-nm and cross-polarization optical coherence tomography (CP-OCT) (thee-dimensional) λ=1300-nm. Extracted human posterior teeth with sound proximal surfaces were chosen for this study and imaged before and after artificial lesions were made. A high speed dental hand piece was used to create artificial cavitated proximal lesions in sound samples and imaged. The cavitated artificial lesions were then filled with hydroxyapatite powder to simulate non-cavitated proximal lesions.

  11. Artificial Intelligence Techniques and Methodology

    OpenAIRE

    Carbonell, Jaime G.; Sleeman, Derek

    1982-01-01

    Two closely related aspects of artificial intelligence that have received comparatively little attention in the recent literature are research methodology, and the analysis of computational techniques that span multiple application areas. We believe both issues to be increasingly significant as Artificial Intelligence matures into a science and spins off major application efforts. It is imperative to analyze the repertoire of AI methods with respect to past experience, utility in new domains,...

  12. Artificial vision in nuclear fuel fabrication

    International Nuclear Information System (INIS)

    Dorado, P.

    2007-01-01

    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)

  13. Demand Forecasting Methods in Accommodation Establishments: A Research with Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Ebru ULUCAN

    2018-05-01

    Full Text Available As it being seen in every sector, demand forecasting in tourism is been conducted with various qualitative and quantitative methods. In recent years, artificial neural network models, which have been developed as an alternative to these forecasting methods, give the nearest values in forecasting with the smallest failure percentage. This study aims to reveal that accomodation establishments can use the neural network models as an alternative while forecasting their demand. With this aim, neural network models have been tested by using the sold room values between the period of 2013-2016 of a five star hotel in Istanbul and it is found that the results acquired from the testing models are the nearest values comparing the realized figures. In the light of these results, tourism demand of the hotel for 2017 and 2018 has been forecasted.

  14. 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)

  15. Analysis of some meteorological parameters using artificial neural ...

    African Journals Online (AJOL)

    Analysis of some meteorological parameters using artificial neural network method for ... The mean daily data for sunshine hours, maximum temperature, cloud cover and ... The study used artificial neural networks (ANN) for the estimation.

  16. Ethico-epistemological implications of artificial intelligence for ...

    African Journals Online (AJOL)

    We argued for a re-direction of AI. research and suggested a humanization of Artificial Intelligence that cloaks technoscientific innovations with humanistic life jackets for man‟s preservation. The textual analysis method is adopted for this research. Key words: Ethics, Epistemology, Artificial Intelligence, Humanity.

  17. 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.

  18. 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

  19. Generating quantitative models describing the sequence specificity of biological processes with the stabilized matrix method

    Directory of Open Access Journals (Sweden)

    Sette Alessandro

    2005-05-01

    Full Text Available Abstract Background Many processes in molecular biology involve the recognition of short sequences of nucleic-or amino acids, such as the binding of immunogenic peptides to major histocompatibility complex (MHC molecules. From experimental data, a model of the sequence specificity of these processes can be constructed, such as a sequence motif, a scoring matrix or an artificial neural network. The purpose of these models is two-fold. First, they can provide a summary of experimental results, allowing for a deeper understanding of the mechanisms involved in sequence recognition. Second, such models can be used to predict the experimental outcome for yet untested sequences. In the past we reported the development of a method to generate such models called the Stabilized Matrix Method (SMM. This method has been successfully applied to predicting peptide binding to MHC molecules, peptide transport by the transporter associated with antigen presentation (TAP and proteasomal cleavage of protein sequences. Results Herein we report the implementation of the SMM algorithm as a publicly available software package. Specific features determining the type of problems the method is most appropriate for are discussed. Advantageous features of the package are: (1 the output generated is easy to interpret, (2 input and output are both quantitative, (3 specific computational strategies to handle experimental noise are built in, (4 the algorithm is designed to effectively handle bounded experimental data, (5 experimental data from randomized peptide libraries and conventional peptides can easily be combined, and (6 it is possible to incorporate pair interactions between positions of a sequence. Conclusion Making the SMM method publicly available enables bioinformaticians and experimental biologists to easily access it, to compare its performance to other prediction methods, and to extend it to other applications.

  20. An artificial neural network ensemble method for fault diagnosis of proton exchange membrane fuel cell system

    International Nuclear Information System (INIS)

    Shao, Meng; Zhu, Xin-Jian; Cao, Hong-Fei; Shen, Hai-Feng

    2014-01-01

    The commercial viability of PEMFC (proton exchange membrane fuel cell) systems depends on using effective fault diagnosis technologies in PEMFC systems. However, many researchers have experimentally studied PEMFC (proton exchange membrane fuel cell) systems without considering certain fault conditions. In this paper, an ANN (artificial neural network) ensemble method is presented that improves the stability and reliability of the PEMFC systems. In the first part, a transient model giving it flexibility in application to some exceptional conditions is built. The PEMFC dynamic model is built and simulated using MATLAB. In the second, using this model and experiments, the mechanisms of four different faults in PEMFC systems are analyzed in detail. Third, the ANN ensemble for the fault diagnosis is built and modeled. This model is trained and tested by the data. The test result shows that, compared with the previous method for fault diagnosis of PEMFC systems, the proposed fault diagnosis method has higher diagnostic rate and generalization ability. Moreover, the partial structure of this method can be altered easily, along with the change of the PEMFC systems. In general, this method for diagnosis of PEMFC has value for certain applications. - Highlights: • We analyze the principles and mechanisms of the four faults in PEMFC (proton exchange membrane fuel cell) system. • We design and model an ANN (artificial neural network) ensemble method for the fault diagnosis of PEMFC system. • This method has high diagnostic rate and strong generalization ability

  1. An Artificial Emotion Model For Visualizing Emotion of Characters

    OpenAIRE

    Junseok Ham; Chansun Jung; Junhyung Park; Jihye Ryeo; Ilju Ko

    2009-01-01

    It is hard to express emotion through only speech when we watch a character in a movie or a play because we cannot estimate the size, kind, and quantity of emotion. So this paper proposes an artificial emotion model for visualizing current emotion with color and location in emotion model. The artificial emotion model is designed considering causality of generated emotion, difference of personality, difference of continual emotional stimulus, and co-relation of various emo...

  2. Development of classification and prediction methods of critical heat flux using fuzzy theory and artificial neural networks

    International Nuclear Information System (INIS)

    Moon, Sang Ki

    1995-02-01

    This thesis applies new information techniques, artificial neural networks, (ANNs) and fuzzy theory, to the investigation of the critical heat flux (CHF) phenomenon for water flow in vertical round tubes. The work performed are (a) classification and prediction of CHF based on fuzzy clustering and ANN, (b) prediction and parametric trends analysis of CHF using ANN with the introduction of dimensionless parameters, and (c) detection of CHF occurrence using fuzzy rule and spatiotemporal neural network (STN). Fuzzy clustering and ANN are used for classification and prediction of the CHF using primary system parameters. The fuzzy clustering classifies the experimental CHF data into a few data clusters (data groups) according to the data characteristics. After classification of the experimental data, the characteristics of the resulted clusters are discussed with emphasis on the distribution of the experimental conditions and physical mechanisms. The CHF data in each group are trained in an artificial neural network to predict the CHF. The artificial neural network adjusts the weight so as to minimize the prediction error within the corresponding cluster. Application of the proposed method to the KAIST CHF data bank shows good prediction capability of the CHF, better than other existing methods. Parametric trends of the CHF are analyzed by applying artificial neural networks to a CHF data base for water flow in uniformly heated vertical round tubes. The analyses are performed from three viewpoints, i.e., for fixed inlet conditions, for fixed exit conditions, and based on local conditions hypothesis. In order to remove the necessity of data classification, Katto and Groeneveld et al.'s dimensionless parameters are introduced in training the ANNs with the experimental CHF data. The trained ANNs predict the CHF better than any other conventional correlations, showing RMS error of 8.9%, 13.1%, and 19.3% for fixed inlet conditions, for fixed exit conditions, and for local

  3. Spatially Resolved Artificial Chemistry

    DEFF Research Database (Denmark)

    Fellermann, Harold

    2009-01-01

    Although spatial structures can play a crucial role in chemical systems and can drastically alter the outcome of reactions, the traditional framework of artificial chemistry is a well-stirred tank reactor with no spatial representation in mind. Advanced method development in physical chemistry has...... made a class of models accessible to the realms of artificial chemistry that represent reacting molecules in a coarse-grained fashion in continuous space. This chapter introduces the mathematical models of Brownian dynamics (BD) and dissipative particle dynamics (DPD) for molecular motion and reaction...

  4. Spatially Resolved Artificial Chemistry

    DEFF Research Database (Denmark)

    Fellermann, Harold

    2009-01-01

    made a class of models accessible to the realms of artificial chemistry that represent reacting molecules in a coarse-grained fashion in continuous space. This chapter introduces the mathematical models of Brownian dynamics (BD) and dissipative particle dynamics (DPD) for molecular motion and reaction......Although spatial structures can play a crucial role in chemical systems and can drastically alter the outcome of reactions, the traditional framework of artificial chemistry is a well-stirred tank reactor with no spatial representation in mind. Advanced method development in physical chemistry has...

  5. C code generation applied to nonlinear model predictive control for an artificial pancreas

    DEFF Research Database (Denmark)

    Boiroux, Dimitri; Jørgensen, John Bagterp

    2017-01-01

    This paper presents a method to generate C code from MATLAB code applied to a nonlinear model predictive control (NMPC) algorithm. The C code generation uses the MATLAB Coder Toolbox. It can drastically reduce the time required for development compared to a manual porting of code from MATLAB to C...

  6. Artificial Consciousness or Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Spanache Florin

    2017-05-01

    Full Text Available Artificial intelligence is a tool designed by people for the gratification of their own creative ego, so we can not confuse conscience with intelligence and not even intelligence in its human representation with conscience. They are all different concepts and they have different uses. Philosophically, there are differences between autonomous people and automatic artificial intelligence. This is the difference between intelligence and artificial intelligence, autonomous versus automatic. But conscience is above these differences because it is neither conditioned by the self-preservation of autonomy, because a conscience is something that you use to help your neighbor, nor automatic, because one’s conscience is tested by situations which are not similar or subject to routine. So, artificial intelligence is only in science-fiction literature similar to an autonomous conscience-endowed being. In real life, religion with its notions of redemption, sin, expiation, confession and communion will not have any meaning for a machine which cannot make a mistake on its own.

  7. An Examination of a Music Appreciation Method Incorporating Tactile Sensations from Artificial Vibrations

    Science.gov (United States)

    Ideguchi, Tsuyoshi; Yoshida, Ryujyu; Ooshima, Keita

    We examined how test subject impressions of music changed when artificial vibrations were incorporated as constituent elements of a musical composition. In this study, test subjects listened to several music samples in which different types of artificial vibration had been incorporated and then subjectively evaluated any resulting changes to their impressions of the music. The following results were obtained: i) Even if rhythm vibration is added to a silent component of a musical composition, it can effectively enhance musical fitness. This could be readily accomplished when actual sounds that had been synchronized with the vibration components were provided beforehand. ii) The music could be listened to more comfortably by adding not only a natural vibration extracted from percussion instruments but also artificial vibration as tactile stimulation according to intentional timing. Furthermore, it was found that the test subjects' impression of the music was affected by a characteristic of the artificial vibration. iii) Adding vibration to high-frequency areas can offer an effective and practical way of enhancing the appeal of a musical composition. iv) The movement sensations of sound and vibration could be experienced when the strength of the sound and vibration are modified in turn. These results suggest that the intentional application of artificial vibration could result in a sensitivity amplification factor on the part of a listener.

  8. Wains: a pattern-seeking artificial life species.

    Science.gov (United States)

    de Buitléir, Amy; Russell, Michael; Daly, Mark

    2012-01-01

    We describe the initial phase of a research project to develop an artificial life framework designed to extract knowledge from large data sets with minimal preparation or ramp-up time. In this phase, we evolved an artificial life population with a new brain architecture. The agents have sufficient intelligence to discover patterns in data and to make survival decisions based on those patterns. The species uses diploid reproduction, Hebbian learning, and Kohonen self-organizing maps, in combination with novel techniques such as using pattern-rich data as the environment and framing the data analysis as a survival problem for artificial life. The first generation of agents mastered the pattern discovery task well enough to thrive. Evolution further adapted the agents to their environment by making them a little more pessimistic, and also by making their brains more efficient.

  9. Cognitive Artificial Intelligence Method for Interpreting Transformer Condition Based on Maintenance Data

    Directory of Open Access Journals (Sweden)

    Karel Octavianus Bachri

    2017-07-01

    Full Text Available A3S(Arwin-Adang-Aciek-Sembiring is a method of information fusion at a single observation and OMA3S(Observation Multi-time A3S is a method of information fusion for time-series data. This paper proposes OMA3S-based Cognitive Artificial-Intelligence method for interpreting Transformer Condition, which is calculated based on maintenance data from Indonesia National Electric Company (PLN. First, the proposed method is tested using the previously published data, and then followed by implementation on maintenance data. Maintenance data are fused to obtain part condition, and part conditions are fused to obtain transformer condition. Result shows proposed method is valid for DGA fault identification with the average accuracy of 91.1%. The proposed method not only can interpret the major fault, it can also identify the minor fault occurring along with the major fault, allowing early warning feature. Result also shows part conditions can be interpreted using information fusion on maintenance data, and the transformer condition can be interpreted using information fusion on part conditions. The future works on this research is to gather more data, to elaborate more factors to be fused, and to design a cognitive processor that can be used to implement this concept of intelligent instrumentation.

  10. Traceable calibration of impedance heads and artificial mastoids

    International Nuclear Information System (INIS)

    Scott, D A; Dickinson, L P; Bell, T J

    2015-01-01

    Artificial mastoids are devices which simulate the mechanical characteristics of the human head, and in particular of the bony structure behind the ear. They are an essential tool in the calibration of bone-conduction hearing aids and audiometers. With the emergence of different types of artificial mastoids in the market, and the realisation that the visco-elastic part of these instruments changes over time, the development of a method of traceable calibration of these devices without relying on commercial software has become important for national metrology institutes. This paper describes commercially available calibration methods, and the development of a traceable calibration method including the traceable calibration of the impedance head used to measure the mechanical impedance of the artificial mastoid. (paper)

  11. A Modified Artificial Bee Colony Algorithm Application for Economic Environmental Dispatch

    Science.gov (United States)

    Tarafdar Hagh, M.; Baghban Orandi, Omid

    2018-03-01

    In conventional fossil-fuel power systems, the economic environmental dispatch (EED) problem is a major problem that optimally determines the output power of generating units in a way that cost of total production and emission level be minimized simultaneously, and at the same time all the constraints of units and system are satisfied properly. To solve EED problem which is a non-convex optimization problem, a modified artificial bee colony (MABC) algorithm is proposed in this paper. This algorithm by implementing weighted sum method is applied on two test systems, and eventually, obtained results are compared with other reported results. Comparison of results confirms superiority and efficiency of proposed method clearly.

  12. Characterization of marble waste for manufacture of artificial stone; Caracterizacao de residuo de marmore para fabricacao de rocha artificial

    Energy Technology Data Exchange (ETDEWEB)

    Aguiar, M.C.; Silva, A.G.P., E-mail: maricostalonga2@gmail.com [Universidade Estadual do Norte Fluminense (UENF/LAMAV), Campos dos Goytacazes, RJ (Brazil). Laboratorio de Materiais Avancados; Gadioli, M.C.B. [Centro de Tecnologia Mineral (CETEM/NR-ES), Cachoeiro de Itapemirim, ES (Brazil)

    2016-07-01

    This work aims to study the characterization of marble waste for the manufacture of artificial stone. The characterization of the waste was performed through X-ray fluorescence, X-ray diffraction, particle size distribution, scanning electron microscopy and confocal microscopy. The results indicated that the marble waste presents typical composition of a dolomite, calcite marble, and their minerals are: Calcite (CaCO{sub 3}) and dolomite (MgCa (CO{sub 3}){sub 2}. The waste presented predominance of particles below 200 mesh screen. This may be interesting for the production of artificial stone better visual appearance, such as marmoglass, for example. The results indicate that the use of marble waste for production of artificial stone is feasible and environmentally friendly alternative to give a destination for this waste generated in the order of millions of tons representing serious environmental problem. (author)

  13. Steam Generator Inspection Planning Expert System

    International Nuclear Information System (INIS)

    Rzasa, P.

    1987-01-01

    Applying Artificial Intelligence technology to steam generator non-destructive examination (NDE) can help identify high risk locations in steam generators and can aid in preparing technical specification compliant eddy current test (ECT) programs. A steam Generator Inspection Planning Expert System has been developed which can assist NDE or utility personnel in planning ECT programs. This system represents and processes its information using an object oriented declarative knowledge base, heuristic rules, and symbolic information processing, three artificial intelligence based techniques incorporated in the design. The output of the system is an automated generation of ECT programs. Used in an outage inspection, this system significantly reduced planning time

  14. Design of flat pneumatic artificial muscles

    Science.gov (United States)

    Wirekoh, Jackson; Park, Yong-Lae

    2017-03-01

    Pneumatic artificial muscles (PAMs) have gained wide use in the field of robotics due to their ability to generate linear forces and motions with a simple mechanism, while remaining lightweight and compact. However, PAMs are limited by their traditional cylindrical form factors, which must increase radially to improve contraction force generation. Additionally, this form factor results in overly complicated fabrication processes when embedded fibers and sensor elements are required to provide efficient actuation and control of the PAMs while minimizing the bulkiness of the overall robotic system. In order to overcome these limitations, a flat two-dimensional PAM capable of being fabricated using a simple layered manufacturing process was created. Furthermore, a theoretical model was developed using Von Karman’s formulation for large deformations and the energy methods. Experimental characterizations of two different types of PAMs, a single-cell unit and a multi-cell unit, were performed to measure the maximum contraction lengths and forces at input pressures ranging from 0 to 150 kPa. Experimental data were then used to verify the fidelity of the theoretical model.

  15. Biomaterials for artificial organs

    CERN Document Server

    Lysaght, Michael J

    2010-01-01

    The worldwide demand for organ transplants far exceeds available donor organs. Consequently some patients die whilst waiting for a transplant. Synthetic alternatives are therefore imperative to improve the quality of, and in some cases, save people's lives. Advances in biomaterials have generated a range of materials and devices for use either outside the body or through implantation to replace or assist functions which may have been lost through disease or injury. Biomaterials for artificial organs reviews the latest developments in biomaterials and investigates how they can be used to improve the quality and efficiency of artificial organs. Part one discusses commodity biomaterials including membranes for oxygenators and plasmafilters, titanium and cobalt chromium alloys for hips and knees, polymeric joint-bearing surfaces for total joint replacements, biomaterials for pacemakers, defibrillators and neurostimulators and mechanical and bioprosthetic heart valves. Part two goes on to investigate advanced and ...

  16. Fluvial facies reservoir productivity prediction method based on principal component analysis and artificial neural network

    Directory of Open Access Journals (Sweden)

    Pengyu Gao

    2016-03-01

    Full Text Available It is difficult to forecast the well productivity because of the complexity of vertical and horizontal developments in fluvial facies reservoir. This paper proposes a method based on Principal Component Analysis and Artificial Neural Network to predict well productivity of fluvial facies reservoir. The method summarizes the statistical reservoir factors and engineering factors that affect the well productivity, extracts information by applying the principal component analysis method and approximates arbitrary functions of the neural network to realize an accurate and efficient prediction on the fluvial facies reservoir well productivity. This method provides an effective way for forecasting the productivity of fluvial facies reservoir which is affected by multi-factors and complex mechanism. The study result shows that this method is a practical, effective, accurate and indirect productivity forecast method and is suitable for field application.

  17. 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.

  18. Introducing micrometer-sized artificial objects into live cells: a method for cell-giant unilamellar vesicle electrofusion.

    Directory of Open Access Journals (Sweden)

    Akira C Saito

    Full Text Available Here, we report a method for introducing large objects of up to a micrometer in diameter into cultured mammalian cells by electrofusion of giant unilamellar vesicles. We prepared GUVs containing various artificial objects using a water-in-oil (w/o emulsion centrifugation method. GUVs and dispersed HeLa cells were exposed to an alternating current (AC field to induce a linear cell-GUV alignment, and then a direct current (DC pulse was applied to facilitate transient electrofusion. With uniformly sized fluorescent beads as size indexes, we successfully and efficiently introduced beads of 1 µm in diameter into living cells along with a plasmid mammalian expression vector. Our electrofusion did not affect cell viability. After the electrofusion, cells proliferated normally until confluence was reached, and the introduced fluorescent beads were inherited during cell division. Analysis by both confocal microscopy and flow cytometry supported these findings. As an alternative approach, we also introduced a designed nanostructure (DNA origami into live cells. The results we report here represent a milestone for designing artificial symbiosis of functionally active objects (such as micro-machines in living cells. Moreover, our technique can be used for drug delivery, tissue engineering, and cell manipulation.

  19. Analysis Resilient Algorithm on Artificial Neural Network Backpropagation

    Science.gov (United States)

    Saputra, Widodo; Tulus; Zarlis, Muhammad; Widia Sembiring, Rahmat; Hartama, Dedy

    2017-12-01

    Prediction required by decision makers to anticipate future planning. Artificial Neural Network (ANN) Backpropagation is one of method. This method however still has weakness, for long training time. This is a reason to improve a method to accelerate the training. One of Artificial Neural Network (ANN) Backpropagation method is a resilient method. Resilient method of changing weights and bias network with direct adaptation process of weighting based on local gradient information from every learning iteration. Predicting data result of Istanbul Stock Exchange training getting better. Mean Square Error (MSE) value is getting smaller and increasing accuracy.

  20. Use of artificial tracers in hydrology

    International Nuclear Information System (INIS)

    1991-05-01

    The IAEA has convened an Advisory Group Meeting with the following objectives: To define the role of artificial radioactive tracers for water tracing in comparison with other non-radioactive tracers. To evaluate the real needs of artificial radioactive tracers in hydrology. To identify the fields for which artificial radioactive tracers are useful as well as those in which they can be substituted by other tracers. To discuss the strategy to be adopted to overcome the difficulties derived from the restrictions on the use of radioactive tracers in hydrology. The meeting was held at IAEA Headquarters from 19 to 22 March 1990, and was attended by 30 participants from 15 Member States. The conclusions and recommendations are that the use of artificial radioactive tracers should be restricted to cases where other tracers cannot be used or do not provide the same quality of information. Tritium, iodine-131, bromine-82, chromium-51 in the form of Cr-EDTA, technetium-99m obtained from 99 Mo-generators and gold-198 as an adsorbable tracer are, practically, the only radionuclides used for water tracing. The use of other radionuclides for this purpose does not appear to be necessary, possible and/or convenient. Refs, figs and tabs

  1. EXPRESS METHOD OF BARCODE GENERATION FROM FACIAL IMAGES

    Directory of Open Access Journals (Sweden)

    G. A. Kukharev

    2014-03-01

    Full Text Available In the paper a method of generating of standard type linear barcodes from facial images is proposed. The method is based on use of the histogram of facial image brightness, averaging the histogram on a limited number of intervals, quantization of results in a range of decimal numbers from 0 to 9 and table conversion into the final barcode. The proposed solution is computationally low-cost and not requires the use of specialized software on image processing that allows generating of facial barcodes in mobile systems, and thus the proposed method can be interpreted as an express method. Results of tests on the Face94 and CUHK Face Sketch FERET Databases showed that the proposed method is a new solution for use in the real-world practice and ensures the stability of generated barcodes in changes of scale, pose and mirroring of a facial image, and also changes of a facial expression and shadows on faces from local lighting. The proposed method is based on generating of a standard barcode directly from the facial image, and thus contains the subjective information about a person's face.

  2. Entropy method combined with extreme learning machine method for the short-term photovoltaic power generation forecasting

    International Nuclear Information System (INIS)

    Tang, Pingzhou; Chen, Di; Hou, Yushuo

    2016-01-01

    As the world’s energy problem becomes more severe day by day, photovoltaic power generation has opened a new door for us with no doubt. It will provide an effective solution for this severe energy problem and meet human’s needs for energy if we can apply photovoltaic power generation in real life, Similar to wind power generation, photovoltaic power generation is uncertain. Therefore, the forecast of photovoltaic power generation is very crucial. In this paper, entropy method and extreme learning machine (ELM) method were combined to forecast a short-term photovoltaic power generation. First, entropy method is used to process initial data, train the network through the data after unification, and then forecast electricity generation. Finally, the data results obtained through the entropy method with ELM were compared with that generated through generalized regression neural network (GRNN) and radial basis function neural network (RBF) method. We found that entropy method combining with ELM method possesses higher accuracy and the calculation is faster.

  3. Neural network based control of Doubly Fed Induction Generator in wind power generation

    Science.gov (United States)

    Barbade, Swati A.; Kasliwal, Prabha

    2012-07-01

    To complement the other types of pollution-free generation wind energy is a viable option. Previously wind turbines were operated at constant speed. The evolution of technology related to wind systems industry leaded to the development of a generation of variable speed wind turbines that present many advantages compared to the fixed speed wind turbines. In this paper the phasor model of DFIG is used. This paper presents a study of a doubly fed induction generator driven by a wind turbine connected to the grid, and controlled by artificial neural network ANN controller. The behaviour of the system is shown with PI control, and then as controlled by ANN. The effectiveness of the artificial neural network controller is compared to that of a PI controller. The SIMULINK/MATLAB simulation for Doubly Fed Induction Generator and corresponding results and waveforms are displayed.

  4. Structural Reliability: An Assessment Using a New and Efficient Two-Phase Method Based on Artificial Neural Network and a Harmony Search Algorithm

    Directory of Open Access Journals (Sweden)

    Naser Kazemi Elaki

    2016-06-01

    Full Text Available In this research, a two-phase algorithm based on the artificial neural network (ANN and a harmony search (HS algorithm has been developed with the aim of assessing the reliability of structures with implicit limit state functions. The proposed method involves the generation of datasets to be used specifically for training by Finite Element analysis, to establish an ANN model using a proven ANN model in the reliability assessment process as an analyzer for structures, and finally estimate the reliability index and failure probability by using the HS algorithm, without any requirements for the explicit form of limit state function. The proposed algorithm is investigated here, and its accuracy and efficiency are demonstrated by using several numerical examples. The results obtained show that the proposed algorithm gives an appropriate estimate for the assessment of reliability of structures.

  5. Non-linear M -sequences Generation Method

    Directory of Open Access Journals (Sweden)

    Z. R. Garifullina

    2011-06-01

    Full Text Available The article deals with a new method for modeling a pseudorandom number generator based on R-blocks. The gist of the method is the replacement of a multi digit XOR element by a stochastic adder in a parallel binary linear feedback shift register scheme.

  6. Artificial neural network and classical least-squares methods for neurotransmitter mixture analysis.

    Science.gov (United States)

    Schulze, H G; Greek, L S; Gorzalka, B B; Bree, A V; Blades, M W; Turner, R F

    1995-02-01

    Identification of individual components in biological mixtures can be a difficult problem regardless of the analytical method employed. In this work, Raman spectroscopy was chosen as a prototype analytical method due to its inherent versatility and applicability to aqueous media, making it useful for the study of biological samples. Artificial neural networks (ANNs) and the classical least-squares (CLS) method were used to identify and quantify the Raman spectra of the small-molecule neurotransmitters and mixtures of such molecules. The transfer functions used by a network, as well as the architecture of a network, played an important role in the ability of the network to identify the Raman spectra of individual neurotransmitters and the Raman spectra of neurotransmitter mixtures. Specifically, networks using sigmoid and hyperbolic tangent transfer functions generalized better from the mixtures in the training data set to those in the testing data sets than networks using sine functions. Networks with connections that permit the local processing of inputs generally performed better than other networks on all the testing data sets. and better than the CLS method of curve fitting, on novel spectra of some neurotransmitters. The CLS method was found to perform well on noisy, shifted, and difference spectra.

  7. Herbert: A Second Generation Mobile Robot.

    Science.gov (United States)

    1988-01-01

    PROJECT. TASK S Artificial Inteligence Laboratory AREA A WORK UNIT NUMBERS ’ ~ 545 Technology Square Cambridge, MA 02139 11. CONTROLLING OFFICE NAME...AD-AI93 632 WMRT: A SECOND GENERTION MOBILE ROWT(U) / MASSACHUSETTS IMST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB R BROOKS ET AL .JAN l8 Al-M...MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A. I. Memo 1016 January, 1988 HERBERT: A SECOND GENERATION MOBILE ROBOT Rodney A

  8. [A method of recognizing biology surface spectrum using cascade-connection artificial neural nets].

    Science.gov (United States)

    Shi, Wei-Jie; Yao, Yong; Zhang, Tie-Qiang; Meng, Xian-Jiang

    2008-05-01

    A method of recognizing the visible spectrum of micro-areas on the biological surface with cascade-connection artificial neural nets is presented in the present paper. The visible spectra of spots on apples' pericarp, ranging from 500 to 730 nm, were obtained with a fiber-probe spectrometer, and a new spectrum recognition system consisting of three-level cascade-connection neural nets was set up. The experiments show that the spectra of rotten, scar and bumped spot on an apple's pericarp can be recognized by the spectrum recognition system, and the recognition accuracy is higher than 85% even when noise level is 15%. The new recognition system overcomes the disadvantages of poor accuracy and poor anti-noise with the traditional system based on single cascade neural nets. Finally, a new method of expression of recognition results was proved. The method is based on the conception of degree of membership in fuzzing mathematics, and through it the recognition results can be expressed exactly and objectively.

  9. Artificial intelligence applications in information and communication technologies

    CERN Document Server

    Bouguila, Nizar

    2015-01-01

    This book presents various recent applications of Artificial Intelligence in Information and Communication Technologies such as Search and Optimization methods, Machine Learning, Data Representation and Ontologies, and Multi-agent Systems. The main aim of this book is to help Information and Communication Technologies (ICT) practitioners in managing efficiently their platforms using AI tools and methods and to provide them with sufficient Artificial Intelligence background to deal with real-life problems.  .

  10. Improved Artificial Fish Algorithm for Parameters Optimization of PID Neural Network

    OpenAIRE

    Jing Wang; Yourui Huang

    2013-01-01

    In order to solve problems such as initial weights are difficult to be determined, training results are easy to trap in local minima in optimization process of PID neural network parameters by traditional BP algorithm, this paper proposed a new method based on improved artificial fish algorithm for parameters optimization of PID neural network. This improved artificial fish algorithm uses a composite adaptive artificial fish algorithm based on optimal artificial fish and nearest artificial fi...

  11. Development of a hybrid system of artificial neural networks and ...

    African Journals Online (AJOL)

    Development of a hybrid system of artificial neural networks and artificial bee colony algorithm for prediction and modeling of customer choice in the market. ... attempted to present a new method for the modeling and prediction of customer choice in the market using the combination of artificial intelligence and data mining.

  12. A recursive economic dispatch algorithm for assessing the cost of thermal generator schedules

    International Nuclear Information System (INIS)

    Wong, K.P.; Doan, K.

    1992-01-01

    This paper develops an efficient, recursive algorithm for determining the economic power dispatch of thermal generators within the unit commitment environment. A method for incorporating the operation limits of all on-line generators and limits due to ramping generators is developed in the paper. The developed algorithm is amenable for computer implementation using the artificial intelligence programming language, Prolog. The performance of the developed algorithm is demonstrated through its application to evaluate the costs of dispatching 13 thermal generators within a generator schedule in a 24-hour schedule horizon

  13. Larvas output and influence of human factor in reliability of meat inspection by the method of artificial digestion

    OpenAIRE

    Đorđević Vesna; Savić Marko; Vasilev Saša; Đorđević Milovan

    2013-01-01

    On the basis of the performed analyses of the factors that contributed the infected meat reach food chain, we have found out that the infection occurred after consuming the meat inspected by the method of collective samples artificial digestion by using a magnetic stirrer (MM). In this work there are presented assay results which show how modifications of the method, on the level of final sedimentation, influence the reliability of Trichinella larvas detect...

  14. A comparison of methods for demonstrating artificial bone lesions; conventional versus computer tomography

    International Nuclear Information System (INIS)

    Heller, M.; Wenk, M.; Jend, H.H.

    1984-01-01

    Conventional tomography (T) and computer tomography (CT) were used for examining 97 artificial bone lesions at various sites. The purpose of the study was to determine how far CT can replace T in the diagnosis of skeletal abnormalities. The results have shown that modern CT, particularly in its high resolution form, equals T and provides additional information (substrate of a lesion, its relationship to neighbouring tissues, simultaneous demonstration of soft tissue etc.). These cannot be shown successfully by T. It follows that CT is indicated as the primary method of examination for lesions of the facial skeleton, skull base, spine, pelvis and, to some extent, extremities. (orig.) [de

  15. Status and headway of the clinical application of artificial ligaments

    Directory of Open Access Journals (Sweden)

    Tianwu Chen

    2015-01-01

    Full Text Available The authors first reviewed the history of clinical application of artificial ligaments. Then, the status of clinical application of artificial ligaments was detailed. Some artificial ligaments possessed comparable efficacy to, and fewer postoperative complications than, allografts and autografts in ligament reconstruction, especially for the anterior cruciate ligament. At the end, the authors focused on the development of two types of artificial ligaments: polyethylene glycol terephthalate artificial ligaments and tissue-engineered ligaments. In conclusion, owing to the advancements in surgical techniques, materials processing, and weaving methods, clinical application of some artificial ligaments so far has demonstrated good outcomes and will become a trend in the future.

  16. Artificial E-region field-aligned plasma irregularities generated at pump frequencies near the second electron gyroharmonic

    Directory of Open Access Journals (Sweden)

    D. L. Hysell

    2009-07-01

    Full Text Available E region ionospheric modification experiments have been performed at HAARP using pump frequencies about 50 kHz above and below the second electron gyroharmonic frequency. Artificial E region field-aligned plasma density irregularities (FAIs were created and observed using the imaging coherent scatter radar near Homer, Alaska. Echoes from FAIs generated with pump frequencies above and below 2Ωe did not appear to differ significantly in experiments conducted on summer afternoons in 2008, and the resonance instability seemed to be at work in either case. We argue that upper hybrid wave trapping and resonance instability at pump frequencies below the second electron gyroharmonic frequency are permitted theoretically when the effects of finite parallel wavenumbers are considered. Echoes from a sporadic E layer were observed to be somewhat weaker when the pump frequency was 50 kHz below the second electron gyroharmonic frequency. This may indicate that finite parallel wavenumbers are inconsistent with wave trapping in thin sporadic E ionization layers.

  17. Artificial senses for characterization of food quality

    Institute of Scientific and Technical Information of China (English)

    HUANG Yan-bo; LAN Yu-bin; R.E. Lacey

    2004-01-01

    Food quality is of primary concern in the food industry and to the consumer. Systems that mimic human senses have been developed and applied to the characterization of food quality. The five primary senses are: vision, hearing, smell, taste and touch.In the characterization of food quality, people assess the samples sensorially and differentiate "good" from "bad" on a continuum.However, the human sensory system is subjective, with mental and physical inconsistencies, and needs time to work. Artificial senses such as machine vision, the electronic ear, electronic nose, electronic tongue, artificial mouth and even artificial the head have been developed that mimic the human senses. These artificial senses are coordinated individually or collectively by a pattern recognition technique, typically artificial neural networks, which have been developed based on studies of the mechanism of the human brain. Such a structure has been used to formulate methods for rapid characterization of food quality. This research presents and discusses individual artificial sensing systems. With the concept of multi-sensor data fusion these sensor systems can work collectively in some way. Two such fused systems, artificial mouth and artificial head, are described and discussed. It indicates that each of the individual systems has their own artificially sensing ability to differentiate food samples. It further indicates that with a more complete mimic of human intelligence the fused systems are more powerful than the individual systems in differentiation of food samples.

  18. Automated Scheduling Via Artificial Intelligence

    Science.gov (United States)

    Biefeld, Eric W.; Cooper, Lynne P.

    1991-01-01

    Artificial-intelligence software that automates scheduling developed in Operations Mission Planner (OMP) research project. Software used in both generation of new schedules and modification of existing schedules in view of changes in tasks and/or available resources. Approach based on iterative refinement. Although project focused upon scheduling of operations of scientific instruments and other equipment aboard spacecraft, also applicable to such terrestrial problems as scheduling production in factory.

  19. Specificity control for read alignments using an artificial reference genome-guided false discovery rate.

    Science.gov (United States)

    Giese, Sven H; Zickmann, Franziska; Renard, Bernhard Y

    2014-01-01

    Accurate estimation, comparison and evaluation of read mapping error rates is a crucial step in the processing of next-generation sequencing data, as further analysis steps and interpretation assume the correctness of the mapping results. Current approaches are either focused on sensitivity estimation and thereby disregard specificity or are based on read simulations. Although continuously improving, read simulations are still prone to introduce a bias into the mapping error quantitation and cannot capture all characteristics of an individual dataset. We introduce ARDEN (artificial reference driven estimation of false positives in next-generation sequencing data), a novel benchmark method that estimates error rates of read mappers based on real experimental reads, using an additionally generated artificial reference genome. It allows a dataset-specific computation of error rates and the construction of a receiver operating characteristic curve. Thereby, it can be used for optimization of parameters for read mappers, selection of read mappers for a specific problem or for filtering alignments based on quality estimation. The use of ARDEN is demonstrated in a general read mapper comparison, a parameter optimization for one read mapper and an application example in single-nucleotide polymorphism discovery with a significant reduction in the number of false positive identifications. The ARDEN source code is freely available at http://sourceforge.net/projects/arden/.

  20. Accretion rate in mangroves sediment at Sungai Miang, Pahang, Malaysia: 230Thexcess versus artificial horizon marker method

    International Nuclear Information System (INIS)

    Kamaruzzaman Yunus; Jamil Tajam; Hasrizal Shaari; Noor Azhar Mohd Shazili; Misbahul Mohd Amin

    2008-01-01

    Mangroves have enormous ecological value and one of their important role is to act as an efficient sediment trappers which dominantly supplied by rivers and the atmosphere to the oceans. Applying the 230 Th excess method, an average accretion rate of 0.54 cm yr -1 was obtained. this is comparable to that of an artificial horizon marker method giving an average of 0.54 cm yr -1 . The 230 Th excess method provides a rapid and simple method of evaluating 230 Th excess accumulation histories in sediment cores. Sample preparation is also significantly simplified, thus providing a relatively quick and easy method for the determination of the accretion rate in mangrove area. (author)

  1. Whispering galleries and the control of artificial atoms.

    Science.gov (United States)

    Forrester, Derek Michael; Kusmartsev, Feodor V

    2016-04-28

    Quantum computation using artificial-atoms, such as novel superconducting circuits, can be sensitively controlled by external electromagnetic fields. These fields and the self-fields attributable to the coupled artificial-atoms influence the amount of quantum correlation in the system. However, control elements that can operate without complete destruction of the entanglement of the quantum-bits are difficult to engineer. Here we investigate the possibility of using closely-spaced-linear arrays of metallic-elliptical discs as whispering gallery waveguides to control artificial-atoms. The discs confine and guide radiation through the array with small notches etched into their sides that act as scatterers. We focus on π-ring artificial-atoms, which can generate their own spontaneous fluxes. We find that the micro-discs of the waveguides can be excited by terahertz frequency fields to exhibit whispering-modes and that a quantum-phase-gate composed of π-rings can be operated under their influence. Furthermore, we gauge the level of entanglement through the concurrence measure and show that under certain magnetic conditions a series of entanglement sudden-deaths and revivals occur between the two qubits. This is important for understanding the stability and life-time of qubit operations using, for example, a phase gate in a hybrid of quantum technologies composed of control elements and artificial-atoms.

  2. Artificial skin and patient simulator comprising the artificial skin

    NARCIS (Netherlands)

    2011-01-01

    The invention relates to an artificial skin (10, 12, 14), and relates to a patient simulator (100) comprising the artificial skin. The artificial skin is a layered structure comprising a translucent cover layer (20) configured for imitating human or animal skin, and comprising a light emitting layer

  3. Generational differences of baccalaureate nursing students' preferred teaching methods and faculty use of teaching methods

    Science.gov (United States)

    Delahoyde, Theresa

    Nursing education is experiencing a generational phenomenon with student enrollment spanning three generations. Classrooms of the 21st century include the occasional Baby Boomer and a large number of Generation X and Generation Y students. Each of these generations has its own unique set of characteristics that have been shaped by values, trends, behaviors, and events in society. These generational characteristics create vast opportunities to learn, as well as challenges. One such challenge is the use of teaching methods that are congruent with nursing student preferences. Although there is a wide range of studies conducted on student learning styles within the nursing education field, there is little research on the preferred teaching methods of nursing students. The purpose of this quantitative, descriptive study was to compare the preferred teaching methods of multi-generational baccalaureate nursing students with faculty use of teaching methods. The research study included 367 participants; 38 nursing faculty and 329 nursing students from five different colleges within the Midwest region. The results of the two-tailed t-test found four statistically significant findings between Generation X and Y students and their preferred teaching methods including; lecture, listening to the professor lecture versus working in groups; actively participating in group discussion; and the importance of participating in group assignments. The results of the Analysis of Variance (ANOVA) found seventeen statistically significant findings between levels of students (freshmen/sophomores, juniors, & seniors) and their preferred teaching methods. Lecture was found to be the most frequently used teaching method by faculty as well as the most preferred teaching method by students. Overall, the support for a variety of teaching methods was also found in the analysis of data.

  4. Study on Fault Diagnostics of a Turboprop Engine Using Inverse Performance Model and Artificial Intelligent Methods

    Science.gov (United States)

    Kong, Changduk; Lim, Semyeong

    2011-12-01

    Recently, the health monitoring system of major gas path components of gas turbine uses mostly the model based method like the Gas Path Analysis (GPA). This method is to find quantity changes of component performance characteristic parameters such as isentropic efficiency and mass flow parameter by comparing between measured engine performance parameters such as temperatures, pressures, rotational speeds, fuel consumption, etc. and clean engine performance parameters without any engine faults which are calculated by the base engine performance model. Currently, the expert engine diagnostic systems using the artificial intelligent methods such as Neural Networks (NNs), Fuzzy Logic and Genetic Algorithms (GAs) have been studied to improve the model based method. Among them the NNs are mostly used to the engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base if there are large amount of learning data. In addition, it has a very complex structure for finding effectively single type faults or multiple type faults of gas path components. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measured performance data, and proposes a fault diagnostic system using the base engine performance model and the artificial intelligent methods such as Fuzzy logic and Neural Network. The proposed diagnostic system isolates firstly the faulted components using Fuzzy Logic, then quantifies faults of the identified components using the NN leaned by fault learning data base, which are obtained from the developed base performance model. In leaning the NN, the Feed Forward Back Propagation (FFBP) method is used. Finally, it is verified through several test examples that the component faults implanted arbitrarily in the engine are well isolated and quantified by the proposed diagnostic system.

  5. Recognition of faults patterns in electric generators using artificial neurons networks; Reconocimiento de patrones de fallas en generadores electricos empleando redes neuronales artificiales

    Energy Technology Data Exchange (ETDEWEB)

    Rocha Sanchez, Martha Alicia

    1999-03-01

    This work present the development of a reprocessing method to reduce the information of the original data and to maintain the essential information of the data that enter the reduction process. The obtaining of these data is performed with the aid of the ICM ++ (ICMsystems), from which vectors or n-uplos of elements are obtained. This investigation allowed to analyze an evaluation of the paradigms of artificial neural networks, with the intention of detecting which of these paradigms would evolve better with the problem of fault diagnosis in electric generators. From this a prototype system was developed called diagnosis of faults in electrical generators, which automatically will recognize faults in electrical generators by means of the interpretation of the recording of partial discharges. [Spanish] El presente trabajo presenta el desarrollo de un metodo de reprocesamiento para reducir informacion de los datos originales y mantener la informacion esencial de los datos que entran al proceso de reduccion. La obtencion de estos datos se realiza con la ayuda del ICM ++ (ICMsystems), de los cuales se obtienen vectores o n-uplos de elementos. Esta investigacion permitio analizar una evaluacion de los paradigmas de redes neuronales artificiales, con el objeto de detectar cual de estos paradigmas se desempenaria mejor con el problema de diagnostico de fallas en generadores electricos. A partir de esto se desarrollo un sistema prototipo llamado diagnostico de fallas en generadores electricos, el cual automaticamente reconocera fallas en los generadores electricos mediante la interpretacion de registro de descargas parciales.

  6. Optical effects of different colors of artificial gingiva on ceramic crowns.

    Science.gov (United States)

    Wang, Jian; Lin, Jin; Gil, Mindy; Da Silva, John D; Wright, Robert; Ishikawa-Nagai, Shigemi

    2013-08-01

    The interaction between gingival color and the shade of ceramic restorations has never been fully studied. The purpose of this study is to investigate the optical effects of altering artificial gingival color on the ceramic crown shade in the cervical area. Thirty-one all-ceramic crowns of different shades were used in this study with six different artificial gingival colors. Using a spectrophotometer (Crystaleye(®) Olympus, Japan), we measured the shade of crowns in cervical areas with each of six different artificial gingiva. The crown color measured in the presence of pink artificial gingiva (control) was compared with the crown color with five other artificial gingiva. color difference values ΔE* were calculated and compared between the control group and test groups and the correlation of the artificial gingival color with the crown color was also assessed. Significant differences were found in the mean L* and a* values of all-ceramic crowns at the cervical regions in all six gingival color groups (pcolors of artificial gingiva generated clinically detectable shade differences in the cervical region of ceramic crowns. Copyright © 2013. Published by Elsevier Ltd.

  7. Artificial ground motion compatible with specified peak ground displacement and target multi-damping response spectra

    International Nuclear Information System (INIS)

    Zhang Yushan; Zhao Fengxin

    2010-01-01

    With respect to the design ground motion of nuclear power plant (NPP), the Regular Guide 1.60 of the US not only defined the standard multi-damping response spectra, i.e. the RG1.60 spectra, but also definitely prescribed the peak ground displacement (PGD) value corresponding to the standard spectra. However, in the engineering practice of generating multi-damping-spectra-compatible artificial ground motion for the seismic design of NPP, the PGD value had been neglected. Addressing this issue, this paper proposed a synthesizing method which generates the artificial ground motion compatible with not only the target multi-damping response spectra but also the specified PGD value. Firstly, by the transfer formula between the power spectrum and the response spectrum, an initial uniformly modulated acceleration time history is synthesized by multiplying the stationary Gaussian process with the prescribed intensity envelope to simulate the amplitude-non-stationarity of earthquake ground motion. And then by superimposing a series of narrow-band time histories in the time domain, the initial time history is modified in the iterative manner to match the target PGD as well as the target multi-damping spectra with the pre-specified matching precisions. Numerical examples are provided to demonstrate the matching precisions of the proposed method to the target values.

  8. The Artificial Neural Networks Based on Scalarization Method for a Class of Bilevel Biobjective Programming Problem

    Science.gov (United States)

    Chen, Zhong; Liu, June; Li, Xiong

    2017-01-01

    A two-stage artificial neural network (ANN) based on scalarization method is proposed for bilevel biobjective programming problem (BLBOP). The induced set of the BLBOP is firstly expressed as the set of minimal solutions of a biobjective optimization problem by using scalar approach, and then the whole efficient set of the BLBOP is derived by the proposed two-stage ANN for exploring the induced set. In order to illustrate the proposed method, seven numerical examples are tested and compared with results in the classical literature. Finally, a practical problem is solved by the proposed algorithm. PMID:29312446

  9. Artificial Intelligence.

    Science.gov (United States)

    Information Technology Quarterly, 1985

    1985-01-01

    This issue of "Information Technology Quarterly" is devoted to the theme of "Artificial Intelligence." It contains two major articles: (1) Artificial Intelligence and Law" (D. Peter O'Neill and George D. Wood); (2) "Artificial Intelligence: A Long and Winding Road" (John J. Simon, Jr.). In addition, it contains two sidebars: (1) "Calculating and…

  10. Artificial Lipid Membranes: Past, Present, and Future.

    Science.gov (United States)

    Siontorou, Christina G; Nikoleli, Georgia-Paraskevi; Nikolelis, Dimitrios P; Karapetis, Stefanos K

    2017-07-26

    The multifaceted role of biological membranes prompted early the development of artificial lipid-based models with a primary view of reconstituting the natural functions in vitro so as to study and exploit chemoreception for sensor engineering. Over the years, a fair amount of knowledge on the artificial lipid membranes, as both, suspended or supported lipid films and liposomes, has been disseminated and has helped to diversify and expand initial scopes. Artificial lipid membranes can be constructed by several methods, stabilized by various means, functionalized in a variety of ways, experimented upon intensively, and broadly utilized in sensor development, drug testing, drug discovery or as molecular tools and research probes for elucidating the mechanics and the mechanisms of biological membranes. This paper reviews the state-of-the-art, discusses the diversity of applications, and presents future perspectives. The newly-introduced field of artificial cells further broadens the applicability of artificial membranes in studying the evolution of life.

  11. Transplantation of artificial gelatin-co-bletillastriata gelatin/Salvia ...

    African Journals Online (AJOL)

    Tropical Journal of Pharmaceutical Research April 2016; 15 (4): 735-741 ... Methods: The composite artificial corium was constructed by culturing fibroblast cells in gelatin-co- ... Conclusion: The composite artificial corium has some clinical prospects for use in the treatment of ... burns, and treatment of large areas of skin.

  12. Artificial organs: recent progress in artificial hearing and vision.

    Science.gov (United States)

    Ifukube, Tohru

    2009-01-01

    Artificial sensory organs are a prosthetic means of sending visual or auditory information to the brain by electrical stimulation of the optic or auditory nerves to assist visually impaired or hearing-impaired people. However, clinical application of artificial sensory organs, except for cochlear implants, is still a trial-and-error process. This is because how and where the information transmitted to the brain is processed is still unknown, and also because changes in brain function (plasticity) remain unknown, even though brain plasticity plays an important role in meaningful interpretation of new sensory stimuli. This article discusses some basic unresolved issues and potential solutions in the development of artificial sensory organs such as cochlear implants, brainstem implants, artificial vision, and artificial retinas.

  13. Sentence Processing in an Artificial Language: Learning and Using Combinatorial Constraints

    Science.gov (United States)

    Amato, Michael S.; MacDonald, Maryellen C.

    2010-01-01

    A study combining artificial grammar and sentence comprehension methods investigated the learning and online use of probabilistic, nonadjacent combinatorial constraints. Participants learned a small artificial language describing cartoon monsters acting on objects. Self-paced reading of sentences in the artificial language revealed comprehenders'…

  14. A new comparison method for dew-point generators

    Science.gov (United States)

    Heinonen, Martti

    1999-12-01

    A new method for comparing dew-point generators was developed at the Centre for Metrology and Accreditation. In this method, the generators participating in a comparison are compared with a transportable saturator unit using a dew-point comparator. The method was tested by constructing a test apparatus and by comparing it with the MIKES primary dew-point generator several times in the dew-point temperature range from -40 to +75 °C. The expanded uncertainty (k = 2) of the apparatus was estimated to be between 0.05 and 0.07 °C and the difference between the comparator system and the generator is well within these limits. In particular, all of the results obtained in the range below 0 °C are within ±0.03 °C. It is concluded that a new type of a transfer standard with characteristics most suitable for dew-point comparisons can be developed on the basis of the principles presented in this paper.

  15. Artificial intelligence utilization in power generation units control systems; Utilizacao de inteligencia artificial em sistemas de controle de unidades geradoras

    Energy Technology Data Exchange (ETDEWEB)

    Souza, G N [CEPEL, Rio de Janeiro, RJ (Brazil); Mendes, S B [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia

    1992-12-31

    To the implementation of the logics of control in a hydroelectric power plant artificial languages or complexes formalisms are used which cause error introduction in the description process of such logic. This work suggests the use of an intelligent and interactive system with interface in natural language to the control description as a solution to this problem. 28 refs., 3 figs.

  16. Artificial intelligence utilization in power generation units control systems; Utilizacao de inteligencia artificial em sistemas de controle de unidades geradoras

    Energy Technology Data Exchange (ETDEWEB)

    Souza, G.N. [CEPEL, Rio de Janeiro, RJ (Brazil); Mendes, S.B. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia

    1991-12-31

    To the implementation of the logics of control in a hydroelectric power plant artificial languages or complexes formalisms are used which cause error introduction in the description process of such logic. This work suggests the use of an intelligent and interactive system with interface in natural language to the control description as a solution to this problem. 28 refs., 3 figs.

  17. Artificial heart for humanoid robot

    Science.gov (United States)

    Potnuru, Akshay; Wu, Lianjun; Tadesse, Yonas

    2014-03-01

    A soft robotic device inspired by the pumping action of a biological heart is presented in this study. Developing artificial heart to a humanoid robot enables us to make a better biomedical device for ultimate use in humans. As technology continues to become more advanced, the methods in which we implement high performance and biomimetic artificial organs is getting nearer each day. In this paper, we present the design and development of a soft artificial heart that can be used in a humanoid robot and simulate the functions of a human heart using shape memory alloy technology. The robotic heart is designed to pump a blood-like fluid to parts of the robot such as the face to simulate someone blushing or when someone is angry by the use of elastomeric substrates and certain features for the transport of fluids.

  18. Artificial intelligence in the diagnosis of low back pain.

    Science.gov (United States)

    Mann, N H; Brown, M D

    1991-04-01

    Computerized methods are used to recognize the characteristics of patient pain drawings. Artificial neural network (ANN) models are compared with expert predictions and traditional statistical classification methods when placing the pain drawings of low back pain patients into one of five clinically significant categories. A discussion is undertaken outlining the differences in these classifiers and the potential benefits of the ANN model as an artificial intelligence technique.

  19. Decision based on big data research for non-small cell lung cancer in medical artificial system in developing country.

    Science.gov (United States)

    Wu, Jia; Tan, Yanlin; Chen, Zhigang; Zhao, Ming

    2018-06-01

    Non-small cell lung cancer (NSCLC) is a high risk cancer and is usually scanned by PET-CT for testing, predicting and then give the treatment methods. However, in the actual hospital system, at least 640 images must be generated for each patient through PET-CT scanning. Especially in developing countries, a huge number of patients in NSCLC are attended by doctors. Artificial system can predict and make decision rapidly. According to explore and research artificial medical system, the selection of artificial observations also can result in low work efficiency for doctors. In this study, data information of 2,789,675 patients in three hospitals in China are collected, compiled, and used as the research basis; these data are obtained through image acquisition and diagnostic parameter machine decision-making method on the basis of the machine diagnosis and medical system design model of adjuvant therapy. By combining image and diagnostic parameters, the machine decision diagnosis auxiliary algorithm is established. Experimental result shows that the accuracy has reached 77% in NSCLC. Copyright © 2018 Elsevier B.V. All rights reserved.

  20. Detection of Artificially Generated Seismic Signals using Balloon-borne Infrasound Sensors

    OpenAIRE

    Krishnamoorthy, Siddharth; Komjathy, Attila; Pauken, Michael T.; Cutts, James A.; Garcia, Raphael F.; Mimoun, David; Cadu, Alexandre; Sournac, Anthony; Jackson, Jennifer M.; Lai, Voon Hui; Bowman, Daniel C.

    2018-01-01

    We conducted an experiment in Pahrump, Nevada, in June 2017, where artificial seismic signals were created using a seismic hammer, and the possibility of detecting them from their acoustic signature was examined. In this work, we analyze the pressure signals recorded by highly sensitive barometers deployed on the ground and on tethers suspended from balloons. Our signal processing results show that wind noise experienced by a barometer on a free‐flying balloon is lower compared to one on a mo...

  1. Artificial neural networks for decision-making in urologic oncology.

    Science.gov (United States)

    Anagnostou, Theodore; Remzi, Mesut; Lykourinas, Michael; Djavan, Bob

    2003-06-01

    The authors are presenting a thorough introduction in Artificial Neural Networks (ANNs) and their contribution to modern Urologic Oncology. The article covers a description of Artificial Neural Network methodology and points out the differences of Artificial Intelligence to traditional statistic models in terms of serving patients and clinicians, in a different way than current statistical analysis. Since Artificial Intelligence is not yet fully understood by many practicing clinicians, the authors have reviewed a careful selection of articles in order to explore the clinical benefit of Artificial Intelligence applications in modern Urology questions and decision-making. The data are from real patients and reflect attempts to achieve more accurate diagnosis and prognosis, especially in prostate cancer that stands as a good example of difficult decision-making in everyday practice. Experience from current use of Artificial Intelligence is also being discussed, and the authors address future developments as well as potential problems such as medical record quality, precautions in using ANNs or resistance to system use, in an attempt to point out future demands and the need for common standards. The authors conclude that both methods should continue to be used in a complementary manner. ANNs still do not prove always better as to replace standard statistical analysis as the method of choice in interpreting medical data.

  2. Production and properties of artificial antimicrobial marble; Jushikei zinzo dairiseki no kokin kako

    Energy Technology Data Exchange (ETDEWEB)

    Amano, Ryozo; Miyamoto, Hiroyuki [INAX Corp., Aichi (Japan)

    1999-11-01

    There are many cases in which they are suitable for the growth of the microorganism on bathrooms and lavatories, kitchens, etc., which are the place where the artificial marble product is installed. Therefore, the generation of the fouling of the microorganism by the aberrant growth is also abounding. Then, it developed the antimicrobe artificial marble for the purpose of suppressing growth of bacteria in the surface of the product. Here, this paper describes the gist in doing antimicrobial treatment in the resin systems artificial marble product. (NEDO)

  3. Terahertz wave manipulation based on multi-bit coding artificial electromagnetic surfaces

    Science.gov (United States)

    Li, Jiu-Sheng; Zhao, Ze-Jiang; Yao, Jian-Quan

    2018-05-01

    A polarization insensitive multi-bit coding artificial electromagnetic surface is proposed for terahertz wave manipulation. The coding artificial electromagnetic surfaces composed of four-arrow-shaped particles with certain coding sequences can generate multi-bit coding in the terahertz frequencies and manipulate the reflected terahertz waves to the numerous directions by using of different coding distributions. Furthermore, we demonstrate that our coding artificial electromagnetic surfaces have strong abilities to reduce the radar cross section with polarization insensitive for TE and TM incident terahertz waves as well as linear-polarized and circular-polarized terahertz waves. This work offers an effectively strategy to realize more powerful manipulation of terahertz wave.

  4. Modular Extended-Stay HyperGravity Facility Design Concept: An Artificial-Gravity Space-Settlement Ground Analogue

    Science.gov (United States)

    Dorais, Gregory A.

    2015-01-01

    This document defines the design concept for a ground-based, extended-stay hypergravity facility as a precursor for space-based artificial-gravity facilities that extend the permanent presence of both human and non-human life beyond Earth in artificial-gravity settlements. Since the Earth's current human population is stressing the environment and the resources off-Earth are relatively unlimited, by as soon as 2040 more than one thousand people could be living in Earthorbiting artificial-gravity habitats. Eventually, the majority of humanity may live in artificialgravity habitats throughout this solar system as well as others, but little is known about the longterm (multi-generational) effects of artificial-gravity habitats on people, animals, and plants. In order to extend life permanently beyond Earth, it would be useful to create an orbiting space facility that generates 1g as well as other gravity levels to rigorously address the numerous challenges of such an endeavor. Before doing so, developing a ground-based artificial-gravity facility is a reasonable next step. Just as the International Space Station is a microgravity research facility, at a small fraction of the cost and risk a ground-based artificial-gravity facility can begin to address a wide-variety of the artificial-gravity life-science questions and engineering challenges requiring long-term research to enable people, animals, and plants to live off-Earth indefinitely.

  5. A Concurrent Distributed System for Aircraft Tactical Decision Generation

    Science.gov (United States)

    McManus, John W.

    1990-01-01

    A research program investigating the use of artificial intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within Visual Range (WVR) air combat engagements is discussed. The application of AI programming and problem solving methods in the development and implementation of a concurrent version of the Computerized Logic For Air-to-Air Warfare Simulations (CLAWS) program, a second generation TDG, is presented. Concurrent computing environments and programming approaches are discussed and the design and performance of a prototype concurrent TDG system are presented.

  6. Colonization of Lutzomyia shannoni (Diptera: Psychodidae) utilizing an artificial blood feeding technique.

    Science.gov (United States)

    Mann, Rajinder S; Kaufman, Phillip E

    2010-12-01

    Laboratory colonization of hematophagous insects must include an efficient method of blood feeding, preferably by artificial means. Strict rules for obtaining animal use permits, extensive animal maintenance costs, and indirect anesthesia effects on animal health warrant the development of an artificial membrane feeding technique for sand fly colonization in laboratories. An attempt was made to colonize Lutzomyia shannoni using an artificial blood feeding membrane to replace the use of live animals commonly used for sand fly blood-feeding purposes. Lutzomyia shannoni readily fed through a pig intestine membrane exposed at an angle of 45°. However, it did not feed through a chicken skin membrane. Olfactory attractants were unable to improve blood-feeding efficiency. Plaster of Paris was the most suitable oviposition substrate. Female L. shannoni adults laid no eggs on moist sand substrate. Sand fly adults held in groups of ten or more laid higher numbers of eggs than did individually maintained sand flies. Inclusion of the L. longipalpis oviposition hormone dodecanoic acid or the presence of previously laid eggs did not stimulate L. shannoni oviposition. The average L. shannoni egg, larval, and pupal duration were 9.3, 36.7, and 17.8 days, respectively. The addition of a 20% sugar solution improved adult female longevity. Females survived longer (14.8 days) than males (11.9 days). Lutzomyia shannoni was successfully colonized in the laboratory for up to four generations using this artificial membrane technique. © 2010 The Society for Vector Ecology.

  7. Methods for estimating residential building energy consumption by application of artificial intelligence; Methode d'estimation energetique des batiments d'habitation basee sur l'application de l'intelligence artificielle

    Energy Technology Data Exchange (ETDEWEB)

    Kajl, S.; Roberge, M-A. [Quebec Univ., Ecole de technologie superieure, Montreal, PQ (Canada)

    1999-02-01

    A method for estimating energy requirements in buildings five to twenty-five stories in height using artificial intelligence techniques is proposed. In developing this technique, the pre-requisites specified were rapid execution, the ability to generate a wide range of results, including total energy consumption, power demands, heating and cooling consumption, and accuracy comparable to that of a detailed building energy simulation software. The method proposed encompasses (1) the creation of various databases such as classification of the parameters used in the energy simulation, modelling using the Department of Energy (DOE)-2 software and validation of the DOE-2 models; (2) application of the neural networks inclusive of teaching the neural network and validation of the neural network's learning; (3) designing an energy estimate assessment (EEA) system for residential buildings; and (4) validation of the EEA system. The system has been developed in the MATLAB software environment, specifically for the climate in the Ottawa region. For use under different climatic conditions appropriate adjustments need to be made for the heating and cooling consumption. 12 refs., tabs., figs., 2 appendices.

  8. Application of artificial seeds in rapid multiplication of ...

    African Journals Online (AJOL)

    ajl user 3

    2011-11-09

    Nov 9, 2011 ... In this study, a method which produces artificial seeds of Pseudostellaria heterophylla was presented. The micro-tubers ... traditional herb used for hundreds of years in China to .... One of the advantages of artificial seed production is that it is not ... neration system, relative cost of a specific application for.

  9. Advanced methodology for generation expansion planning including interconnected systems

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, M; Yokoyama, R; Yasuda, K [Tokyo Metropolitan Univ. (Japan); Sasaki, H [Hiroshima Univ. (Japan); Ogimoto, K [Electric Power Development Co. Ltd., Tokyo (Japan)

    1994-12-31

    This paper reviews advanced methodology for generation expansion planning including interconnected systems developed in Japan, putting focus on flexibility and efficiency in a practical application. First, criteria for evaluating flexibility of generation planning considering uncertainties are introduced. Secondly, the flexible generation mix problem is formulated as a multi-objective optimization with more than two objective functions. The multi-objective optimization problem is then transformed into a single objective problem by using the weighting method, to obtain the Pareto optimal solution, and solved by a dynamics programming technique. Thirdly, a new approach for electric generation expansion planning of interconnected systems is presented, based on the Benders Decomposition technique. That is, large scale generation problem constituted by the general economic load dispatch problem, and several sub problems which are composed of smaller scale isolated system generation expansion plans. Finally, the generation expansion plan solved by an artificial neural network is presented. In conclusion, the advantages and disadvantages of this method from the viewpoint of flexibility and applicability to practical generation expansion planning are presented. (author) 29 refs., 10 figs., 4 tabs.

  10. Double evolutsional artificial bee colony algorithm for multiple traveling salesman problem

    Directory of Open Access Journals (Sweden)

    Xue Ming Hao

    2016-01-01

    Full Text Available The double evolutional artificial bee colony algorithm (DEABC is proposed for solving the single depot multiple traveling salesman problem (MTSP. The proposed DEABC algorithm, which takes advantage of the strength of the upgraded operators, is characterized by its guidance in exploitation search and diversity in exploration search. The double evolutional process for exploitation search is composed of two phases of half stochastic optimal search, and the diversity generating operator for exploration search is used for solutions which cannot be improved after limited times. The computational results demonstrated the superiority of our algorithm over previous state-of-the-art methods.

  11. Artificial Neural Networks for Nonlinear Dynamic Response Simulation in Mechanical Systems

    DEFF Research Database (Denmark)

    Christiansen, Niels Hørbye; Høgsberg, Jan Becker; Winther, Ole

    2011-01-01

    It is shown how artificial neural networks can be trained to predict dynamic response of a simple nonlinear structure. Data generated using a nonlinear finite element model of a simplified wind turbine is used to train a one layer artificial neural network. When trained properly the network is ab...... to perform accurate response prediction much faster than the corresponding finite element model. Initial result indicate a reduction in cpu time by two orders of magnitude....

  12. Metal-conjugated affinity labels: A new concept to create enantioselective artificial metalloenzymes

    KAUST Repository

    Reiner, Thomas

    2013-02-20

    How to train a protein: Metal-conjugated affinity labels were used to selectively position catalytically active metal centers in the binding pocket of proteases. The resulting artificial metalloenzymes achieve up to 82% e.r. in the hydrogenation of ketones. The modular setup enables a rapid generation of artificial metalloenzyme libraries, which can be adapted to a broad range of catalytic conditions. 2013 The Authors.

  13. Metal-conjugated affinity labels: A new concept to create enantioselective artificial metalloenzymes

    KAUST Repository

    Reiner, Thomas; Jantke, Dominik; Marziale, Alexander N.; Raba, Andreas; Eppinger, Jö rg

    2013-01-01

    How to train a protein: Metal-conjugated affinity labels were used to selectively position catalytically active metal centers in the binding pocket of proteases. The resulting artificial metalloenzymes achieve up to 82% e.r. in the hydrogenation of ketones. The modular setup enables a rapid generation of artificial metalloenzyme libraries, which can be adapted to a broad range of catalytic conditions. 2013 The Authors.

  14. Collective intelligence of the artificial life community on its own successes, failures, and future.

    Science.gov (United States)

    Rasmussen, Steen; Raven, Michael J; Keating, Gordon N; Bedau, Mark A

    2003-01-01

    We describe a novel Internet-based method for building consensus and clarifying conflicts in large stakeholder groups facing complex issues, and we use the method to survey and map the scientific and organizational perspectives of the artificial life community during the Seventh International Conference on Artificial Life (summer 2000). The issues addressed in this survey included artificial life's main successes, main failures, main open scientific questions, and main strategies for the future, as well as the benefits and pitfalls of creating a professional society for artificial life. By illuminating the artificial life community's collective perspective on these issues, this survey illustrates the value of such methods of harnessing the collective intelligence of large stakeholder groups.

  15. Engineering a Light-Attenuating Artificial Iris

    Science.gov (United States)

    Shareef, Farah J.; Sun, Shan; Kotecha, Mrignayani; Kassem, Iris; Azar, Dimitri; Cho, Michael

    2016-01-01

    Purpose Discomfort from light exposure leads to photophobia, glare, and poor vision in patients with congenital or trauma-induced iris damage. Commercial artificial iris lenses are static in nature to provide aesthetics without restoring the natural iris's dynamic response to light. A new photo-responsive artificial iris was therefore developed using a photochromic material with self-adaptive light transmission properties and encased in a transparent biocompatible polymer matrix. Methods The implantable artificial iris was designed and engineered using Photopia, a class of photo-responsive materials (termed naphthopyrans) embedded in polyethylene. Photopia was reshaped into annular disks that were spin-coated with polydimethylsiloxane (PDMS) to form our artificial iris lens of controlled thickness. Results Activated by UV and blue light in approximately 5 seconds with complete reversal in less than 1 minute, the artificial iris demonstrates graded attenuation of up to 40% of visible and 60% of UV light. There optical characteristics are suitable to reversibly regulate the incident light intensity. In vitro cell culture experiments showed up to 60% cell death within 10 days of exposure to Photopia, but no significant cell death observed when cultured with the artificial iris with protective encapsulation. Nuclear magnetic resonance spectroscopy confirmed these results as there was no apparent leakage of potentially toxic photochromic material from the ophthalmic device. Conclusions Our artificial iris lens mimics the functionality of the natural iris by attenuating light intensity entering the eye with its rapid reversible change in opacity and thus potentially providing an improved treatment option for patients with iris damage. PMID:27116547

  16. Analysis of multicriteria models application for selection of an optimal artificial lift method in oil production

    Directory of Open Access Journals (Sweden)

    Crnogorac Miroslav P.

    2016-01-01

    Full Text Available In the world today for the exploitation of oil reservoirs by artificial lift methods are applied different types of deep pumps (piston, centrifugal, screw, hydraulic, water jet pumps and gas lift (continuous, intermittent and plunger. Maximum values of oil production achieved by these exploitation methods are significantly different. In order to select the optimal exploitation method of oil well, the multicriteria analysis models are used. In this paper is presented an analysis of the multicriteria model's application known as VIKOR, TOPSIS, ELECTRE, AHP and PROMETHEE for selection of optimal exploitation method for typical oil well at Serbian exploration area. Ranking results of applicability of the deep piston pumps, hydraulic pumps, screw pumps, gas lift method and electric submersible centrifugal pumps, indicated that in the all above multicriteria models except in PROMETHEE, the optimal method of exploitation are deep piston pumps and gas lift.

  17. Designing the next generation (fifth generation computers)

    International Nuclear Information System (INIS)

    Wallich, P.

    1983-01-01

    A description is given of the designs necessary to develop fifth generation computers. An analysis is offered of problems and developments in parallelism, VLSI, artificial intelligence, knowledge engineering and natural language processing. Software developments are outlined including logic programming, object-oriented programming and exploratory programming. Computer architecture is detailed including concurrent computer architecture

  18. Orbit Determination from Tracking Data of Artificial Satellite Using the Method of Differential Correction

    Directory of Open Access Journals (Sweden)

    Byoung-Sun Lee

    1988-06-01

    Full Text Available The differential correction process determining osculating orbital elements as correct as possible at a given instant of time from tracking data of artificial satellite was accomplished. Preliminary orbital elements were used as an initial value of the differential correction procedure and iterated until the residual of real observation(O and computed observation(C was minimized. Tracking satellite was NOAA-9 or TIROS-N series. Two types of tracking data were prediction data precomputed from mean orbital elements of TBUS and real data obtained from tracking 1.707GHz HRPT signal of NOAA-9 using 5 meter auto-track antenna in Radio Research Laboratory. According to tracking data either Gauss method or Herrick-Gibbs method was applied to preliminary orbit determination. In the differential correction stage we used both of the Escobal(1975's analytical method and numerical ones are nearly consistent. And the differentially corrected orbit converged to the same value in spite of the differences between preliminary orbits of each time span.

  19. Comparative toxicity of pentachlorophenol to three earthworm species in artificial soil

    Energy Technology Data Exchange (ETDEWEB)

    Fitzgerald, D.; Lanno, R.P.; Farwell, A.; Dixon, D.G. [Univ. of Waterloo, Ontario (Canada). Dept. of Biology

    1994-12-31

    Although methods for standardized toxicity tests with earthworms exist, many of the test parameters and conditions have not been validated in actual tests and with different species of worms. This study evaluated the toxicity of pentachlorophenol (PCP) to three species of earthworms, Lumbricus terrestris, Eisenia fetida, and Eudrilus eugeniae using various methods of data analysis and body residues. Tests were conducted in artificial soil for a period of 28 days or until an Acute Lethality Threshold (ALT) was reached. An intensive temporal sampling regime was applied to generate sufficient data for the accurate estimation of ALTs using both LC50/time and time-to-death/soil concentration methods of data analysis. L. terrestris was tested at 15 C, E. eugeniae at 24 C, and E. fetida at both temperatures. Total body residues of PCP were measured by GC following cryogenic separation of the lipid fraction of the worm. ALTs were significantly different between E. fetida and the two larger species of worms. No effect of temperature on the ALT for E. fetida was observed, although the time taken to reach the ALT increased at the lower temperature. The relationship of PCP residues at mortality will be discussed in terms of the effects of species, body size and temperature. Limitations of the artificial soil based upon growth curves of worms will also be examined.

  20. An application of artificial intelligence for rainfall–runoff modeling

    Indian Academy of Sciences (India)

    This study proposes an application of two techniques of artificial intelligence (AI) for rainfall–runoff modeling: the artificial neural networks (ANN) and the evolutionary computation (EC). Two diff- erent ANN techniques, the feed forward back propagation (FFBP) and generalized regression neural network (GRNN) methods ...

  1. Growth and Reproduction of Artificially Fed Cnaphalocrocis medinalis

    Directory of Open Access Journals (Sweden)

    Jian XU

    2012-09-01

    Full Text Available The growth and reproduction of rice leaffolder, Cnaphalocrocis medinalis, fed on an artificial diet were studied. The results showed that the larvae were able to grow and pupate on the artificial diet. The durations of larvae and pupas of C. medinalis on the artificial diet were 28.1 d and 10.1 d, postponed 4.9 d and 1.7 d respectively, compared with those reared with rice leaves. The number of ovipositions was 41.6 per female, 26.2% higher than that fed on rice leaves. Survival rate curve of larvae was a descent function of mortality-age, with no significant differences from the curve of larvae fed on rice leaves. The net reproductive rate (Ro, intrinsic rate of increase (rm and finite rate of increase (λ of the population fed on diet were 17.6928, 0.0884 and 1.0924, respectively, and the mean generation time (T and double time (td were prolonged 4.9 d and 1.3 d in comparison with the treatment of rice leaves. Population trend index (I was 3.26, indicating a growing number of the population of C. medinalis fed on artificial diet.

  2. Collective motion and the generator coordinate method

    International Nuclear Information System (INIS)

    Passos, E.J.V. de

    1981-01-01

    The generator coordinate method is used to construct a collective subspace of the many-body Hylbert space. The construction is based on the analysis of the properties of the overlaps of the generator states. Some well-known misbehaviours of the generator coordinate weight functions are clearly identified as of kinematical origin. A standard orthonormal representation in the collective subspace is introduced which eliminates them. It is also indicated how appropriate collective dynamical variables can be defined a posteriori. To illustrate the properties of the collective subspaces applications are made to a) translational invariant overlap kernels b) to one and two-conjugate parameter families of generator states. (Author) [pt

  3. The importance of the keyword-generation method in keyword mnemonics.

    Science.gov (United States)

    Campos, Alfredo; Amor, Angeles; González, María Angeles

    2004-01-01

    Keyword mnemonics is under certain conditions an effective approach for learning foreign-language vocabulary. It appears to be effective for words with high image vividness but not for words with low image vividness. In this study, two experiments were performed to assess the efficacy of a new keyword-generation procedure (peer generation). In Experiment 1, a sample of 363 high-school students was randomly into four groups. The subjects were required to learn L1 equivalents of a list of 16 Latin words (8 with high image vividness, 8 with low image vividness), using a) the rote method, or the keyword method with b) keywords and images generated and supplied by the experimenter, c) keywords and images generated by themselves, or d) keywords and images previously generated by peers (i.e., subjects with similar sociodemographic characteristics). Recall was tested immediately and one week later. For high-vivideness words, recall was significantly better in the keyword groups than the rote method group. For low-vividness words, learning method had no significant effect. Experiment 2 was basically identical, except that the word lists comprised 32 words (16 high-vividness, 16 low-vividness). In this experiment, the peer-generated-keyword group showed significantly better recall of high-vividness words than the rote method groups and the subject generated keyword group; again, however, learning method had no significant effect on recall of low-vividness words.

  4. Determination of Electron Optical Properties for Aperture Zoom Lenses Using an Artificial Neural Network Method.

    Science.gov (United States)

    Isik, Nimet

    2016-04-01

    Multi-element electrostatic aperture lens systems are widely used to control electron or charged particle beams in many scientific instruments. By means of applied voltages, these lens systems can be operated for different purposes. In this context, numerous methods have been performed to calculate focal properties of these lenses. In this study, an artificial neural network (ANN) classification method is utilized to determine the focused/unfocused charged particle beam in the image point as a function of lens voltages for multi-element electrostatic aperture lenses. A data set for training and testing of ANN is taken from the SIMION 8.1 simulation program, which is a well known and proven accuracy program in charged particle optics. Mean squared error results of this study indicate that the ANN classification method provides notable performance characteristics for electrostatic aperture zoom lenses.

  5. Artificial organs 2011: a year in review.

    Science.gov (United States)

    Malchesky, Paul S

    2012-03-01

    In this Editor's Review, articles published in 2011 are organized by category and briefly summarized. As the official journal of The International Federation for Artificial Organs, The International Faculty for Artificial Organs, and the International Society for Rotary Blood Pumps, Artificial Organs continues in the original mission of its founders "to foster communications in the field of artificial organs on an international level."Artificial Organs continues to publish developments and clinical applications of artificial organ technologies in this broad and expanding field of organ replacement, recovery, and regeneration from all over the world. We take this time also to express our gratitude to our authors for offering their work to this journal. We offer our very special thanks to our reviewers who give so generously of time and expertise to review, critique, and especially provide meaningful suggestions to the author's work whether eventually accepted or rejected. Without these excellent and dedicated reviewers, the quality expected from such a journal would not be possible. We also express our special thanks to our Publisher, Wiley-Blackwell, for their expert attention and support in the production and marketing of Artificial Organs. In this Editor's Review, that historically has been widely well-received by our readership, we aim to provide a brief reflection of the currently available worldwide knowledge that is intended to advance and better human life while providing insight for continued application of technologies and methods of organ replacement, recovery, and regeneration. We look forward to recording further advances in the coming years. © 2012, Copyright the Author. Artificial Organs © 2012, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

  6. Artificial Organs 2012: a year in review.

    Science.gov (United States)

    Malchesky, Paul S

    2013-03-01

    In this editor's review, articles published in 2012 are organized by category and briefly summarized. We aim to provide a brief reflection of the currently available worldwide knowledge that is intended to advance and better human life while providing insight for continued application of technologies and methods of organ replacement, recovery, and regeneration. As the official journal of the International Federation for Artificial Organs, the International Faculty for Artificial Organs, and the International Society for Rotary Blood Pumps, Artificial Organs continues in the original mission of its founders "to foster communications in the field of artificial organs on an international level." Artificial Organs continues to publish developments and clinical applications of artificial organ technologies in this broad and expanding field of organ replacement, recovery, and regeneration from all over the world. We take this time also to express our gratitude to our authors for offering their work to this journal. We offer our very special thanks to our reviewers who give so generously of time and expertise to review, critique, and especially provide such meaningful suggestions to the author's work whether eventually accepted or rejected, and especially to those whose native tongue is not English. Without these excellent and dedicated reviewers, the quality expected from such a journal could not be possible. We also express our special thanks to our publisher, Wiley Periodicals, for their expert attention and support in the production and marketing of Artificial Organs. We look forward to recording further advances in the coming years. © 2013, Copyright the Author. Artificial Organs © 2013, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

  7. Radionuclide power source for artificial heart autonomic apparatus

    Energy Technology Data Exchange (ETDEWEB)

    Lazarenko, Yu V; Gusev, V V; Pustovalov, A A

    1988-02-01

    Works on creating autonomous artificial heart devices with radionuclide heat source are described. Calculated and experimental parameters of /sup 238/Pu base radionuclide thermoelectric RITEG generators designed for supplying perspective blood pump electric drives are presented. RITEG structure is described and the prospects of increasing its efficiency are shown.

  8. The use of artificial intelligence methods for visual analysis of properties of surface layers

    Directory of Open Access Journals (Sweden)

    Tomasz Wójcicki

    2014-12-01

    Full Text Available [b]Abstract[/b]. The article presents a selected area of research on the possibility of automatic prediction of material properties based on the analysis of digital images. Original, holistic model of forecasting properties of surface layers based on a multi-step process that includes the selected methods of processing and analysis of images, inference with the use of a priori knowledge bases and multi-valued fuzzy logic, and simulation with the use of finite element methods is presented. Surface layers characteristics and core technologies of their production processes such as mechanical, thermal, thermo-mechanical, thermo-chemical, electrochemical, physical are discussed. Developed methods used in the model for the classification of images of the surface layers are shown. The objectives of the use of selected methods of processing and analysis of digital images, including techniques for improving the quality of images, segmentation, morphological transformation, pattern recognition and simulation of physical phenomena in the structures of materials are described.[b]Keywords[/b]: image analysis, surface layer, artificial intelligence, fuzzy logic

  9. Differences of Streptococcus mutans adhesion between artificial mouth systems: a dinamic and static methods

    Directory of Open Access Journals (Sweden)

    Aryan Morita

    2016-06-01

    Full Text Available Background: Various materials have been used for treating dental caries. Dental caries is a disease that attacks hard tissues of the teeth. The initial phase of caries is a formation of bacterial biofilm, called as dental plaque. Dental restorative materials are expected for preventing secondary caries formation initiated by dental plaque. Initial bacterial adhesion is assumed to be an important stage of dental plaque formation. Bacteria that recognize the receptor for binding to the pellicle on tooth surface are known as initial bacterial colonies. One of the bacteria that plays a role in the early stage of dental plaque formation is Streptococcus mutans (S. mutans. Artificial mouth system (AMS used in bacterial biofilm research on the oral cavity provides the real condition of oral cavity and continous and intermittent supply of nutrients for bacteria. Purpose: This study aimed to compare the profile of S. mutans bacterial adhesion as the primary etiologic agent for dental caries between using static method and using artificial mouth system, a dinamic. method (AMS. Method: The study was conducted at Faculty of Dentistry and Integrated Research and testing laboratory (LPPT in Universitas Gadjah Mada from April to August 2015. Composite resin was used as the subject of this research. Twelve composite resins with a diameter of 5 mm and a width of 2 mm were divided into two groups, namely group using static method and group using dynamic method. Static method was performed by submerging the samples into a 100µl suspension of 1.5 x 108 CFU/ml S. mutans and 200µl BHI broth. Meanwhile AMS method was carried out by placing the samples at the AMS tube drained with 20 drops/minute of bacterial suspension and sterile aquadest. After 72 hours, five samples from each group were calculated for their biofilm mass using 1% crystal violet and read by a spectrofotometer with a wavelength of 570 nm. Meanwhile, one sample from each group was taken for its

  10. Engineering an artificial amoeba propelled by nanoparticle-triggered actin polymerization

    Energy Technology Data Exchange (ETDEWEB)

    Yi Jinsoo; Schmidt, Jacob; Chien Aichi; Montemagno, Carlo D [Department of Bioengineering, University of California Los Angeles, 420 Westwood Plaza, 7523 Boelter Hall, Los Angeles, CA 90095-1600 (United States)], E-mail: montemcd@ucmail.uc.edu

    2009-02-25

    We have engineered an amoeba system combining nanofabricated inorganic materials with biological components, capable of propelling itself via actin polymerization. The nanofabricated materials have a mechanism similar to the locomotion of the Listeria monocytogenes, food poisoning bacteria. The propulsive force generation utilizes nanoparticles made from nickel and gold functionalized with the Listeria monocytogenes transmembrane protein, ActA. These Listeria-mimic nanoparticles were in concert with actin, actin binding proteins, ATP (adenosine triphosphate) and encapsulated within a lipid vesicle. This system is an artificial cell, such as a vesicle, where artificial nanobacteria and actin polymerization machinery are used in driving force generators inside the cell. The assembled structure was observed to crawl on a glass surface analogously to an amoeba, with the speed of the movement dependent on the amount of actin monomers and ATP present.

  11. Procedural Personas for Player Decision Modeling and Procedural Content Generation

    DEFF Research Database (Denmark)

    Holmgård, Christoffer

    2016-01-01

    ." These methods for constructing procedural personas are then integrated with existing procedural content generation systems, acting as critics that shape the output of these systems, optimizing generated content for different personas and by extension, different kinds of players and their decision making styles......How can player models and artificially intelligent (AI) agents be useful in early-stage iterative game and simulation design? One answer may be as ways of generating synthetic play-test data, before a game or level has ever seen a player, or when the sampled amount of play test data is very low....... This thesis explores methods for creating low-complexity, easily interpretable, generative AI agents for use in game and simulation design. Based on insights from decision theory and behavioral economics, the thesis investigates how player decision making styles may be defined, operationalised, and measured...

  12. [Artificial organs].

    Science.gov (United States)

    Raguin, Thibaut; Dupret-Bories, Agnès; Debry, Christian

    2017-01-01

    Research has been fighting against organ failure and shortage of donations by supplying artificial organs for many years. With the raise of new technologies, tissue engineering and regenerative medicine, many organs can benefit of an artificial equivalent: thanks to retinal implants some blind people can visualize stimuli, an artificial heart can be proposed in case of cardiac failure while awaiting for a heart transplant, artificial larynx enables laryngectomy patients to an almost normal life, while the diabetic can get a glycemic self-regulation controlled by smartphones with an artificial device. Dialysis devices become portable, as well as the oxygenation systems for terminal respiratory failure. Bright prospects are being explored or might emerge in a near future. However, the retrospective assessment of putative side effects is not yet sufficient. Finally, the cost of these new devices is significant even if the advent of three dimensional printers may reduce it. © 2017 médecine/sciences – Inserm.

  13. Structural refinement of artificial superlattices by the X-ray diffraction method

    CERN Document Server

    Ishibashi, Y; Tsurumi, T

    1999-01-01

    This paper reports a structural refinement of BaTiO sub 3 (BTO)/SrTiO sub 3 (STO) artificially superstructured thin films. The refinement was achieved by taking into account the effect of interdiffusion between BTO and STO. The samples were prepared by a molecular-beam epitaxy method on SrTiO sub 3 (001) substrate at 600 .deg. C. The phonon model was employed to simulate the X-ray diffraction (XRD) profiles. A discrepancy was observed in the intensities of the satellite peaks when the effect of the interdiffusion between BTO and STO was not incorporated in the simulation. In successive simulations, the concentration profile due to the interdiffusion was first calculated according to Fick's second law, and then the coefficients of the Fourier series describing the lattice distortion and the modulation of the structure factor were determined. The XRD profiles thus simulated almost completely agreed with those observed. This indicates that XRD analysis with the calculation process proposed in this study will ena...

  14. A Method of Effective Quarry Water Purifying Using Artificial Filtering Arrays

    Science.gov (United States)

    Tyulenev, M.; Garina, E.; Khoreshok, A.; Litvin, O.; Litvin, Y.; Maliukhina, E.

    2017-01-01

    The development of open pit mining in the large coal basins of Russia and other countries increases their negative impact on the environment. Along with the damage of land and air pollution by dust and combustion gases of blasting, coal pits have a significant negative impact on water resources. Polluted quarry water worsens the ecological situation on a much larger area than covered by air pollution and land damage. This significantly worsens the conditions of people living in cities and towns located near the coal pits, and complicates the subsequent restoration of the environment, irreversibly destroying the nature. Therefore, the research of quarry wastewater purifying is becoming an important mater for scholars of technical colleges and universities in the regions with developing open-pit mining. This paper describes the method of determining the basic parameters of the artificial filtering arrays formed on coal pits of Kuzbass (Western Siberia, Russia), and gives recommendations on its application.

  15. A Machine Learning Approach to Test Data Generation

    DEFF Research Database (Denmark)

    Christiansen, Henning; Dahmcke, Christina Mackeprang

    2007-01-01

    been tested, and a more thorough statistical foundation is required. We propose to use logic-statistical modelling methods for machine-learning for analyzing existing and manually marked up data, integrated with the generation of new, artificial data. More specifically, we suggest to use the PRISM...... system developed by Sato and Kameya. Based on logic programming extended with random variables and parameter learning, PRISM appears as a powerful modelling environment, which subsumes HMMs and a wide range of other methods, all embedded in a declarative language. We illustrate these principles here...

  16. Trajectory Generation Method with Convolution Operation on Velocity Profile

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Geon [Hanyang Univ., Seoul (Korea, Republic of); Kim, Doik [Korea Institute of Science and Technology, Daejeon (Korea, Republic of)

    2014-03-15

    The use of robots is no longer limited to the field of industrial robots and is now expanding into the fields of service and medical robots. In this light, a trajectory generation method that can respond instantaneously to the external environment is strongly required. Toward this end, this study proposes a method that enables a robot to change its trajectory in real-time using a convolution operation. The proposed method generates a trajectory in real time and satisfies the physical limits of the robot system such as acceleration and velocity limit. Moreover, a new way to improve the previous method, which generates inefficient trajectories in some cases owing to the characteristics of the trapezoidal shape of trajectories, is proposed by introducing a triangle shape. The validity and effectiveness of the proposed method is shown through a numerical simulation and a comparison with the previous convolution method.

  17. WE-AB-204-06: Pseudo-CT Generation Using Undersampled, Single-Acquisition UTE-MDixon and Direct-Mapping Artificial Neural Networks for MR-Based Attenuation Correction and Radiation Therapy Planning

    Energy Technology Data Exchange (ETDEWEB)

    Su, K; Kuo, J [Case Center for Imaging Research, Case Western Reserve University, Cleveland, Ohio (United States); Department of Radiology, University Hospitals Case Medical Center, Case Western Reserve University, Cleveland, Ohio (United States); Hu, L; Traughber, M [Philips Healthcare, Cleveland, Ohio (United States); Pereira, G; Traughber, B [Department of Radiation Oncology, University Hospitals Seidman Cancer Center, Case Western Reserve University, Cleveland, Ohio (United States); Herrmann, K [Department of Radiology, University Hospitals Case Medical Center, Case Western Reserve University, Cleveland, Ohio (United States); Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, Ohio (United States); Muzic, R [Case Center for Imaging Research, Case Western Reserve University, Cleveland, Ohio (United States); Department of Radiology, University Hospitals Case Medical Center, Case Western Reserve University, Cleveland, Ohio (United States); Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH (United States)

    2015-06-15

    Purpose: Emerging technologies such as dedicated PET/MRI and MR-therapy systems require robust and clinically practical methods for determining photon attenuation. Herein, we propose using novel MR acquisition methods and processing for the generation of pseudo-CTs. Methods: A single acquisition, 190-second UTE-mDixon sequence with 25% (angular) sampling density and 3D radial readout was performed on nine volunteers. Three water-filled tubes were placed in the FOV for trajectory-delay correction. The MR data were reconstructed to generate three primitive images acquired at TEs of 0.1, 1.5 and 2.8 ms. In addition, three derived MR images were generated, i.e. two-point Dixon water/fat separation and R2* (1/T2*) map. Furthermore, two spatial features, i.e. local binary pattern (S-1) and relative spatial coordinates (S-2), were incorporated. A direct-mapping operator was generated using Artificial Neural Networks (ANNs) for transforming the MR features to a pseudo-CT. CT images served as the training data and, using a leave-one-out method, for performance evaluation using mean prediction deviation (MPD), mean absolute prediction deviation (MAPD), and correlation coefficient (R). Results: The errors between measured CT and pseudo-CT declined dramatically when the spatial features, i.e. S-1 and S-2, were included. The MPD, MAPD, and R were, respectively, 5±57 HU, 141±41 HU, and 0.815±0.066 for results generated by the ANN trained without the spatial features and were 32±26 HU, 115±18 HU, and 0.869±0.035 with the spatial features. The estimation errors of the pseudo-CT were smaller when both the S-1 and S-2 were used together than when either the S-1 or the S-2 was used. Pseudo-CT generation (256×256×256 voxels) by ANN took < 0.5 s using a computer having an Intel i7 3.4GHz CPU and 16 GB RAM. Conclusion: The proposed direct-mapping ANN approach is a technically accurate, clinically practical method for pseudo-CT generation and can potentially help improve the

  18. WE-AB-204-06: Pseudo-CT Generation Using Undersampled, Single-Acquisition UTE-MDixon and Direct-Mapping Artificial Neural Networks for MR-Based Attenuation Correction and Radiation Therapy Planning

    International Nuclear Information System (INIS)

    Su, K; Kuo, J; Hu, L; Traughber, M; Pereira, G; Traughber, B; Herrmann, K; Muzic, R

    2015-01-01

    Purpose: Emerging technologies such as dedicated PET/MRI and MR-therapy systems require robust and clinically practical methods for determining photon attenuation. Herein, we propose using novel MR acquisition methods and processing for the generation of pseudo-CTs. Methods: A single acquisition, 190-second UTE-mDixon sequence with 25% (angular) sampling density and 3D radial readout was performed on nine volunteers. Three water-filled tubes were placed in the FOV for trajectory-delay correction. The MR data were reconstructed to generate three primitive images acquired at TEs of 0.1, 1.5 and 2.8 ms. In addition, three derived MR images were generated, i.e. two-point Dixon water/fat separation and R2* (1/T2*) map. Furthermore, two spatial features, i.e. local binary pattern (S-1) and relative spatial coordinates (S-2), were incorporated. A direct-mapping operator was generated using Artificial Neural Networks (ANNs) for transforming the MR features to a pseudo-CT. CT images served as the training data and, using a leave-one-out method, for performance evaluation using mean prediction deviation (MPD), mean absolute prediction deviation (MAPD), and correlation coefficient (R). Results: The errors between measured CT and pseudo-CT declined dramatically when the spatial features, i.e. S-1 and S-2, were included. The MPD, MAPD, and R were, respectively, 5±57 HU, 141±41 HU, and 0.815±0.066 for results generated by the ANN trained without the spatial features and were 32±26 HU, 115±18 HU, and 0.869±0.035 with the spatial features. The estimation errors of the pseudo-CT were smaller when both the S-1 and S-2 were used together than when either the S-1 or the S-2 was used. Pseudo-CT generation (256×256×256 voxels) by ANN took < 0.5 s using a computer having an Intel i7 3.4GHz CPU and 16 GB RAM. Conclusion: The proposed direct-mapping ANN approach is a technically accurate, clinically practical method for pseudo-CT generation and can potentially help improve the

  19. Daily Reservoir Runoff Forecasting Method Using Artificial Neural Network Based on Quantum-behaved Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Chun-tian Cheng

    2015-07-01

    Full Text Available Accurate daily runoff forecasting is of great significance for the operation control of hydropower station and power grid. Conventional methods including rainfall-runoff models and statistical techniques usually rely on a number of assumptions, leading to some deviation from the exact results. Artificial neural network (ANN has the advantages of high fault-tolerance, strong nonlinear mapping and learning ability, which provides an effective method for the daily runoff forecasting. However, its training has certain drawbacks such as time-consuming, slow learning speed and easily falling into local optimum, which cannot be ignored in the real world application. In order to overcome the disadvantages of ANN model, the artificial neural network model based on quantum-behaved particle swarm optimization (QPSO, ANN-QPSO for short, is presented for the daily runoff forecasting in this paper, where QPSO was employed to select the synaptic weights and thresholds of ANN, while ANN was used for the prediction. The proposed model can combine the advantages of both QPSO and ANN to enhance the generalization performance of the forecasting model. The methodology is assessed by using the daily runoff data of Hongjiadu reservoir in southeast Guizhou province of China from 2006 to 2014. The results demonstrate that the proposed approach achieves much better forecast accuracy than the basic ANN model, and the QPSO algorithm is an alternative training technique for the ANN parameters selection.

  20. Dispersion Differences and Consistency of Artificial Periodic Structures.

    Science.gov (United States)

    Cheng, Zhi-Bao; Lin, Wen-Kai; Shi, Zhi-Fei

    2017-10-01

    Dispersion differences and consistency of artificial periodic structures, including phononic crystals, elastic metamaterials, as well as periodic structures composited of phononic crystals and elastic metamaterials, are investigated in this paper. By developing a K(ω) method, complex dispersion relations and group/phase velocity curves of both the single-mechanism periodic structures and the mixing-mechanism periodic structures are calculated at first, from which dispersion differences of artificial periodic structures are discussed. Then, based on a unified formulation, dispersion consistency of artificial periodic structures is investigated. Through a comprehensive comparison study, the correctness for the unified formulation is verified. Mathematical derivations of the unified formulation for different artificial periodic structures are presented. Furthermore, physical meanings of the unified formulation are discussed in the energy-state space.

  1. Database in Artificial Intelligence.

    Science.gov (United States)

    Wilkinson, Julia

    1986-01-01

    Describes a specialist bibliographic database of literature in the field of artificial intelligence created by the Turing Institute (Glasgow, Scotland) using the BRS/Search information retrieval software. The subscription method for end-users--i.e., annual fee entitles user to unlimited access to database, document provision, and printed awareness…

  2. The application of hybrid artificial intelligence systems for forecasting

    Science.gov (United States)

    Lees, Brian; Corchado, Juan

    1999-03-01

    The results to date are presented from an ongoing investigation, in which the aim is to combine the strengths of different artificial intelligence methods into a single problem solving system. The premise underlying this research is that a system which embodies several cooperating problem solving methods will be capable of achieving better performance than if only a single method were employed. The work has so far concentrated on the combination of case-based reasoning and artificial neural networks. The relative merits of artificial neural networks and case-based reasoning problem solving paradigms, and their combination are discussed. The integration of these two AI problem solving methods in a hybrid systems architecture, such that the neural network provides support for learning from past experience in the case-based reasoning cycle, is then presented. The approach has been applied to the task of forecasting the variation of physical parameters of the ocean. Results obtained so far from tests carried out in the dynamic oceanic environment are presented.

  3. An artificial intelligence heat rate/NOx optimization system for Ontario Hydro`s Lambton Generating Station

    Energy Technology Data Exchange (ETDEWEB)

    Luk, J.; Bachalo, K.; Henrikson, J. [Ontario Hydro, Toronto, ON (Canada); Roland, W.; Booth, R.C.; Parikh, N.; Radl, B. [Pegasus Technologies Ltd., Painesville, OH (United States)

    1998-12-01

    The utilization of artificial Intelligence (AI)-based software programs to optimize power plant operations by simultaneously improving heat rate performance and reducing NOx emissions was discussed. While many AI programs were initially used for demonstration purposes, they are now available for commercial use due to their promising results. In 1996, the Fossil Business Unit of Ontario Hydro initiated a study to evaluate AI technology as a tool for optimizing heat rate and NOx reduction in coal fired stations. Tests were conducted at Units 3 and 4 of the Lambton Generation Station, located just south of Sarnia, Ontario. The tests were conducted to examine three desirable options: (1) achieve at least 0.5 per cent improvement in heat rate concurrently with a NOx reduction of at least 5 per cent, (2) optimize on `heat rate` only with minimum improvement of 2 per cent, and optimize `minimal NOx` only with reduction target of 20 per cent or more, and (3) reach a collaborative agreement with a supplier to further explore and develop AI optimization applications for other advanced and more complex plant processes. Results indicated that NOx reduction and heat rate improvement are not contradictory goals. 15 refs., 1 fig.

  4. Generating pulsatility by pump speed modulation with continuous-flow total artificial heart in awake calves.

    Science.gov (United States)

    Fukamachi, Kiyotaka; Karimov, Jamshid H; Sunagawa, Gengo; Horvath, David J; Byram, Nicole; Kuban, Barry D; Dessoffy, Raymond; Sale, Shiva; Golding, Leonard A R; Moazami, Nader

    2017-12-01

    The purpose of this study was to evaluate the effects of sinusoidal pump speed modulation of the Cleveland Clinic continuous-flow total artificial heart (CFTAH) on hemodynamics and pump flow in an awake chronic calf model. The sinusoidal pump speed modulations, performed on the day of elective sacrifice, were set at ±15 and ± 25% of mean pump speed at 80 bpm in four awake calves with a CFTAH. The systemic and pulmonary arterial pulse pressures increased to 12.0 and 12.3 mmHg (±15% modulation) and to 15.9 and 15.7 mmHg (±25% modulation), respectively. The pulsatility index and surplus hemodynamic energy significantly increased, respectively, to 1.05 and 1346 ergs/cm at ±15% speed modulation and to 1.51 and 3381 ergs/cm at ±25% speed modulation. This study showed that it is feasible to generate pressure pulsatility with pump speed modulation; the platform is suitable for evaluating the physiologic impact of pulsatility and allows determination of the best speed modulations in terms of magnitude, frequency, and profiles.

  5. Characterization of marble waste for manufacture of artificial stone

    International Nuclear Information System (INIS)

    Aguiar, M.C.; Silva, A.G.P.

    2016-01-01

    This work aims to study the characterization of marble waste for the manufacture of artificial stone. The characterization of the waste was performed through X-ray fluorescence, X-ray diffraction, particle size distribution, scanning electron microscopy and confocal microscopy. The results indicated that the marble waste presents typical composition of a dolomite, calcite marble, and their minerals are: Calcite (CaCO_3) and dolomite (MgCa (CO_3)_2. The waste presented predominance of particles below 200 mesh screen. This may be interesting for the production of artificial stone better visual appearance, such as marmoglass, for example. The results indicate that the use of marble waste for production of artificial stone is feasible and environmentally friendly alternative to give a destination for this waste generated in the order of millions of tons representing serious environmental problem. (author)

  6. Optimal fuel loading pattern design using artificial intelligence techniques

    International Nuclear Information System (INIS)

    Kim, Han Gon; Chang, Soon Heung; Lee, Byung Ho

    1993-01-01

    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)

  7. Artificial intelligence approaches in statistics

    International Nuclear Information System (INIS)

    Phelps, R.I.; Musgrove, P.B.

    1986-01-01

    The role of pattern recognition and knowledge representation methods from Artificial Intelligence within statistics is considered. Two areas of potential use are identified and one, data exploration, is used to illustrate the possibilities. A method is presented to identify and separate overlapping groups within cluster analysis, using an AI approach. The potential of such ''intelligent'' approaches is stressed

  8. A method for generating hydrogen from water

    International Nuclear Information System (INIS)

    Godin, Paul; Mascarello, Jean; Millet, Jacques.

    1974-01-01

    Description is given of a method and an installation for generating hydrogen from water, through an endothermic cycle of several successive chemical reactions involving intermediate substances regenerated during said cycle, said reactions occuring at different temperatures. The reaction which takes place at the highest temperature is carried out electrochemically. This can be applied to power-generating units comprising a nuclear reactor [fr

  9. Online Optimization Method for Operation of Generators in a Micro Grid

    Science.gov (United States)

    Hayashi, Yasuhiro; Miyamoto, Hideki; Matsuki, Junya; Iizuka, Toshio; Azuma, Hitoshi

    Recently a lot of studies and developments about distributed generator such as photovoltaic generation system, wind turbine generation system and fuel cell have been performed under the background of the global environment issues and deregulation of the electricity market, and the technique of these distributed generators have progressed. Especially, micro grid which consists of several distributed generators, loads and storage battery is expected as one of the new operation system of distributed generator. However, since precipitous load fluctuation occurs in micro grid for the reason of its smaller capacity compared with conventional power system, high-accuracy load forecasting and control scheme to balance of supply and demand are needed. Namely, it is necessary to improve the precision of operation in micro grid by observing load fluctuation and correcting start-stop schedule and output of generators online. But it is not easy to determine the operation schedule of each generator in short time, because the problem to determine start-up, shut-down and output of each generator in micro grid is a mixed integer programming problem. In this paper, the authors propose an online optimization method for the optimal operation schedule of generators in micro grid. The proposed method is based on enumeration method and particle swarm optimization (PSO). In the proposed method, after picking up all unit commitment patterns of each generators satisfied with minimum up time and minimum down time constraint by using enumeration method, optimal schedule and output of generators are determined under the other operational constraints by using PSO. Numerical simulation is carried out for a micro grid model with five generators and photovoltaic generation system in order to examine the validity of the proposed method.

  10. Temporal anomaly detection: an artificial immune approach based on T cell activation, clonal size regulation and homeostasis.

    Science.gov (United States)

    Antunes, Mário J; Correia, Manuel E

    2010-01-01

    This paper presents an artificial immune system (AIS) based on Grossman's tunable activation threshold (TAT) for temporal anomaly detection. We describe the generic AIS framework and the TAT model adopted for simulating T Cells behaviour, emphasizing two novel important features: the temporal dynamic adjustment of T Cells clonal size and its associated homeostasis mechanism. We also present some promising results obtained with artificially generated data sets, aiming to test the appropriateness of using TAT in dynamic changing environments, to distinguish new unseen patterns as part of what should be detected as normal or as anomalous. We conclude by discussing results obtained thus far with artificially generated data sets.

  11. An intelligent artificial throat with sound-sensing ability based on laser induced graphene

    Science.gov (United States)

    Tao, Lu-Qi; Tian, He; Liu, Ying; Ju, Zhen-Yi; Pang, Yu; Chen, Yuan-Quan; Wang, Dan-Yang; Tian, Xiang-Guang; Yan, Jun-Chao; Deng, Ning-Qin; Yang, Yi; Ren, Tian-Ling

    2017-02-01

    Traditional sound sources and sound detectors are usually independent and discrete in the human hearing range. To minimize the device size and integrate it with wearable electronics, there is an urgent requirement of realizing the functional integration of generating and detecting sound in a single device. Here we show an intelligent laser-induced graphene artificial throat, which can not only generate sound but also detect sound in a single device. More importantly, the intelligent artificial throat will significantly assist for the disabled, because the simple throat vibrations such as hum, cough and scream with different intensity or frequency from a mute person can be detected and converted into controllable sounds. Furthermore, the laser-induced graphene artificial throat has the advantage of one-step fabrication, high efficiency, excellent flexibility and low cost, and it will open practical applications in voice control, wearable electronics and many other areas.

  12. Construction of membrane-bound artificial cells using microfluidics: a new frontier in bottom-up synthetic biology.

    Science.gov (United States)

    Elani, Yuval

    2016-06-15

    The quest to construct artificial cells from the bottom-up using simple building blocks has received much attention over recent decades and is one of the grand challenges in synthetic biology. Cell mimics that are encapsulated by lipid membranes are a particularly powerful class of artificial cells due to their biocompatibility and the ability to reconstitute biological machinery within them. One of the key obstacles in the field centres on the following: how can membrane-based artificial cells be generated in a controlled way and in high-throughput? In particular, how can they be constructed to have precisely defined parameters including size, biomolecular composition and spatial organization? Microfluidic generation strategies have proved instrumental in addressing these questions. This article will outline some of the major principles underpinning membrane-based artificial cells and their construction using microfluidics, and will detail some recent landmarks that have been achieved. © 2016 The Author(s).

  13. Artificial E-region field-aligned plasma irregularities generated at pump frequencies near the second electron gyroharmonic

    Directory of Open Access Journals (Sweden)

    D. L. Hysell

    2009-07-01

    Full Text Available E region ionospheric modification experiments have been performed at HAARP using pump frequencies about 50 kHz above and below the second electron gyroharmonic frequency. Artificial E region field-aligned plasma density irregularities (FAIs were created and observed using the imaging coherent scatter radar near Homer, Alaska. Echoes from FAIs generated with pump frequencies above and below 2Ωe did not appear to differ significantly in experiments conducted on summer afternoons in 2008, and the resonance instability seemed to be at work in either case. We argue that upper hybrid wave trapping and resonance instability at pump frequencies below the second electron gyroharmonic frequency are permitted theoretically when the effects of finite parallel wavenumbers are considered. Echoes from a sporadic E layer were observed to be somewhat weaker when the pump frequency was 50 kHz below the second electron gyroharmonic frequency. This may indicate that finite parallel wavenumbers are inconsistent with wave trapping in thin sporadic E ionization layers.

  14. Method of mobile robot indoor navigation by artificial landmarks with use of computer vision

    Science.gov (United States)

    Glibin, E. S.; Shevtsov, A. A.; Enik, O. A.

    2018-05-01

    The article describes an algorithm of the mobile robot indoor navigation based on the use of visual odometry. The results of the experiment identifying calculation errors in the distance traveled on a slip are presented. It is shown that the use of computer vision allows one to correct erroneous coordinates of the robot with the help of artificial landmarks. The control system utilizing the proposed method has been realized on the basis of Arduino Mego 2560 controller and a single-board computer Raspberry Pi 3. The results of the experiment on the mobile robot navigation with the use of this control system are presented.

  15. Determination of penetration depth at high velocity impact using finite element method and artificial neural network tools

    Directory of Open Access Journals (Sweden)

    Namık KılıÇ

    2015-06-01

    Full Text Available Determination of ballistic performance of an armor solution is a complicated task and evolved significantly with the application of finite element methods (FEM in this research field. The traditional armor design studies performed with FEM requires sophisticated procedures and intensive computational effort, therefore simpler and accurate numerical approaches are always worthwhile to decrease armor development time. This study aims to apply a hybrid method using FEM simulation and artificial neural network (ANN analysis to approximate ballistic limit thickness for armor steels. To achieve this objective, a predictive model based on the artificial neural networks is developed to determine ballistic resistance of high hardness armor steels against 7.62 mm armor piercing ammunition. In this methodology, the FEM simulations are used to create training cases for Multilayer Perceptron (MLP three layer networks. In order to validate FE simulation methodology, ballistic shot tests on 20 mm thickness target were performed according to standard Stanag 4569. Afterwards, the successfully trained ANN(s is used to predict the ballistic limit thickness of 500 HB high hardness steel armor. Results show that even with limited number of data, FEM-ANN approach can be used to predict ballistic penetration depth with adequate accuracy.

  16. Research of the method of pseudo-random number generation based on asynchronous cellular automata with several active cells

    Directory of Open Access Journals (Sweden)

    Bilan Stepan

    2017-01-01

    Full Text Available To date, there are many tasks that are aimed at studying the dynamic changes in physical processes. These tasks do not give advance known result. The solution of such problems is based on the construction of a dynamic model of the object. Successful structural and functional implementation of the object model can give a positive result in time. This approach uses the task of constructing artificial biological objects. To solve such problems, pseudo-random number generators are used, which also find wide application for information protection tasks. Such generators should have good statistical properties and give a long repetition period of the generated pseudo-random bit sequence. This work is aimed at improving these characteristics. The paper considers the method of forming pseudo-random sequences of numbers on the basis of aperiodic cellular automata with two active cells. A pseudo-random number generator is proposed that generates three bit sequences. The first two bit sequences are formed by the corresponding two active cells in the cellular automaton. The third bit sequence is the result of executing the XOR function over the bits of the first two sequences and it has better characteristics compared to them. The use of cellular automata with two active cells allowed to improve the statistical properties of the formed bit sequence, as well as its repetition period. This is proved by using graphical tests for generators built based on cellular automata using the neighborhoods of von Neumann and Moore. The tests showed high efficiency of the generator based on an asynchronous cellular automaton with the neighborhood of Moore. The proposed pseudo-random number generators have good statistical properties, which makes it possible to use them in information security systems, as well as for simulation tasks of various dynamic processes.

  17. Study of artificial intelligence algorithms applied to the generation of non-playable characters in arcade games

    OpenAIRE

    Garduño Hernández, Daniel

    2017-01-01

    En la actualidad, el auge de la Inteligencia Artificial en diversos campos está llevando a un aumento en la investigación que se lleva a cabo en ella. Uno de estos campos es el de los videojuegos. Desde el inicio de los videojuegos, ha primado la experiencia del usuario en términos de jugabilidad y gráficos, sobre todo, prestando menor atención a la Inteligencia Artificial. Ahora, debido a que cada vez se dispone de mejores máquinas que pueden realizar acciones computacionalmen...

  18. Method of generating a computer readable model

    DEFF Research Database (Denmark)

    2008-01-01

    A method of generating a computer readable model of a geometrical object constructed from a plurality of interconnectable construction elements, wherein each construction element has a number of connection elements for connecting the construction element with another construction element. The met......A method of generating a computer readable model of a geometrical object constructed from a plurality of interconnectable construction elements, wherein each construction element has a number of connection elements for connecting the construction element with another construction element....... The method comprises encoding a first and a second one of the construction elements as corresponding data structures, each representing the connection elements of the corresponding construction element, and each of the connection elements having associated with it a predetermined connection type. The method...... further comprises determining a first connection element of the first construction element and a second connection element of the second construction element located in a predetermined proximity of each other; and retrieving connectivity information of the corresponding connection types of the first...

  19. Fertility response of artificial insemination methods in sheep with fresh and frozen-thawed semen.

    Science.gov (United States)

    Masoudi, Reza; Zare Shahneh, Ahmad; Towhidi, Armin; Kohram, Hamid; Akbarisharif, Abbas; Sharafi, Mohsen

    2017-02-01

    The aim of this study was to evaluate the fertility response of artificial insemination (AI) methods with fresh and frozen sperm in sheep. In experiment 1, one hundred and fifty fat tailed Zandi ewes were assigned into 3 equal groups and inseminated with three AI methods consisting of vaginal, laparoscopic and trans-cervical AI with fresh semen. In experiment 2, a factorial study (3 AI methods × 2 extenders) was used to analyze the effects of three AI methods and two freezing extenders containing soybean lecithin (SL) or Egg yolk (EY) on reproductive performance of 300 fat tailed Zandi ewes. Also, total motility, progressive motility, viability and lipid peroxidation of semen were evaluated after freeze-thawing in two extenders. In result, there was no significant difference among three AI methods when fresh semen was used. In experiment 2, the highest percentage of pregnancy rate, parturition rate and lambing rate were obtained in laparoscopic AI group (P semen, trans-cervical AI was more efficient than vaginal method when frozen-thawed semen was used, but its efficiency was not as high as laparoscopic method. Also, SL extender can be an efficient alternative extender to preserve ram sperm during cryopreservation procedure without adverse effects of EY. Copyright © 2016. Published by Elsevier Inc.

  20. Artificial fingerprint recognition by using optical coherence tomography with autocorrelation analysis

    Science.gov (United States)

    Cheng, Yezeng; Larin, Kirill V.

    2006-12-01

    Fingerprint recognition is one of the most widely used methods of biometrics. This method relies on the surface topography of a finger and, thus, is potentially vulnerable for spoofing by artificial dummies with embedded fingerprints. In this study, we applied the optical coherence tomography (OCT) technique to distinguish artificial materials commonly used for spoofing fingerprint scanning systems from the real skin. Several artificial fingerprint dummies made from household cement and liquid silicone rubber were prepared and tested using a commercial fingerprint reader and an OCT system. While the artificial fingerprints easily spoofed the commercial fingerprint reader, OCT images revealed the presence of them at all times. We also demonstrated that an autocorrelation analysis of the OCT images could be potentially used in automatic recognition systems.

  1. The use of artificial neural networks and multiple linear regression to predict rate of medical waste generation

    International Nuclear Information System (INIS)

    Jahandideh, Sepideh; Jahandideh, Samad; Asadabadi, Ebrahim Barzegari; Askarian, Mehrdad; Movahedi, Mohammad Mehdi; Hosseini, Somayyeh; Jahandideh, Mina

    2009-01-01

    Prediction of the amount of hospital waste production will be helpful in the storage, transportation and disposal of hospital waste management. Based on this fact, two predictor models including artificial neural networks (ANNs) and multiple linear regression (MLR) were applied to predict the rate of medical waste generation totally and in different types of sharp, infectious and general. In this study, a 5-fold cross-validation procedure on a database containing total of 50 hospitals of Fars province (Iran) were used to verify the performance of the models. Three performance measures including MAR, RMSE and R 2 were used to evaluate performance of models. The MLR as a conventional model obtained poor prediction performance measure values. However, MLR distinguished hospital capacity and bed occupancy as more significant parameters. On the other hand, ANNs as a more powerful model, which has not been introduced in predicting rate of medical waste generation, showed high performance measure values, especially 0.99 value of R 2 confirming the good fit of the data. Such satisfactory results could be attributed to the non-linear nature of ANNs in problem solving which provides the opportunity for relating independent variables to dependent ones non-linearly. In conclusion, the obtained results showed that our ANN-based model approach is very promising and may play a useful role in developing a better cost-effective strategy for waste management in future.

  2. Artificial light pollution increases nocturnal vigilance in peahens.

    Science.gov (United States)

    Yorzinski, Jessica L; Chisholm, Sarah; Byerley, Sydney D; Coy, Jeanee R; Aziz, Aisyah; Wolf, Jamie A; Gnerlich, Amanda C

    2015-01-01

    Artificial light pollution is drastically changing the sensory environments of animals. Even though many animals are now living in these changed environments, the effect light pollution has on animal behavior is poorly understood. We investigated the effect of light pollution on nocturnal vigilance in peahens (Pavo cristatus). Captive peahens were exposed to either artificial lighting or natural lighting at night. We employed a novel method to record their vigilance behavior by attaching accelerometers to their heads and continuously monitoring their large head movements. We found that light pollution significantly increases nocturnal vigilance in peahens. Furthermore, the birds faced a trade-off between vigilance and sleep at night: peahens that were more vigilant spent less time sleeping. Given the choice, peahens preferred to roost away from high levels of artificial lighting but showed no preference for roosting without artificial lighting or with low levels of artificial lighting. Our study demonstrates that light pollution can have a substantial impact on animal behavior that can potentially result in fitness consequences.

  3. Degradation of ticarcillin by subcritial water oxidation method: Application of response surface methodology and artificial neural network modeling.

    Science.gov (United States)

    Yabalak, Erdal

    2018-05-18

    This study was performed to investigate the mineralization of ticarcillin in the artificially prepared aqueous solution presenting ticarcillin contaminated waters, which constitute a serious problem for human health. 81.99% of total organic carbon removal, 79.65% of chemical oxygen demand removal, and 94.35% of ticarcillin removal were achieved by using eco-friendly, time-saving, powerful and easy-applying, subcritical water oxidation method in the presence of a safe-to-use oxidizing agent, hydrogen peroxide. Central composite design, which belongs to the response surface methodology, was applied to design the degradation experiments, to optimize the methods, to evaluate the effects of the system variables, namely, temperature, hydrogen peroxide concentration, and treatment time, on the responses. In addition, theoretical equations were proposed in each removal processes. ANOVA tests were utilized to evaluate the reliability of the performed models. F values of 245.79, 88.74, and 48.22 were found for total organic carbon removal, chemical oxygen demand removal, and ticarcillin removal, respectively. Moreover, artificial neural network modeling was applied to estimate the response in each case and its prediction and optimizing performance was statistically examined and compared to the performance of central composite design.

  4. Comparison of sensorless dimming control based on building modeling and solar power generation

    International Nuclear Information System (INIS)

    Lee, Naeun; Kim, Jonghun; Jang, Cheolyong; Sung, Yoondong; Jeong, Hakgeun

    2015-01-01

    Artificial lighting in office buildings accounts for about 30% of the total building energy consumption. Lighting energy is important to reduce building energy consumption since artificial lighting typically has a relatively large energy conversion factor. Therefore, previous studies have proposed a dimming control using daylight. When applied dimming control, method based on building modeling does not need illuminance sensors. Thus, it can be applied to existing buildings that do not have illuminance sensors. However, this method does not accurately reflect real-time weather conditions. On the other hand, solar power generation from a PV (photovoltaic) panel reflects real-time weather conditions. The PV panel as the sensor improves the accuracy of dimming control by reflecting disturbance. Therefore, we compared and analyzed two types of sensorless dimming controls: those based on the building modeling and those that based on solar power generation using PV panels. In terms of energy savings, we found that a dimming control based on building modeling is more effective than that based on solar power generation by about 6%. However, dimming control based on solar power generation minimizes the inconvenience to occupants and can also react to changes in solar radiation entering the building caused by dirty window. - Highlights: • We conducted sensorless dimming control based on solar power generation. • Dimming controls using building modeling and solar power generation were compared. • The real time weather conditions can be considered by using solar power generation. • Dimming control using solar power generation minimizes inconvenience to occupants

  5. Hall et al., 2016 Artificial Turf Surrogate Surface Methods Paper Data File

    Data.gov (United States)

    U.S. Environmental Protection Agency — Mercury dry deposition data quantified via static water surrogate surface (SWSS) and artificial turf surrogate surface (ATSS) collectors. This dataset is associated...

  6. Incremental artificial bee colony with local search to economic dispatch problem with ramp rate limits and prohibited operating zones

    International Nuclear Information System (INIS)

    Özyön, Serdar; Aydin, Doğan

    2013-01-01

    Highlights: ► Prohibited operating zone economic dispatch problem has been solved by IABC-LS. ► The losses used in the solution of the problem have been computed by B-loss matrix. ► IABC-LS method has been applied to three test systems in literature. ► The values obtained by IABC and IABC-LS are better than the results in literature. - Abstract: In this study, prohibited operating zone economic power dispatch problem which considers ramp rate limit, has been solved by incremental artificial bee colony algorithm (IABC) and incremental artificial bee colony algorithm with local search (IABC-LS) methods. The transmission line losses used in the solution of the problem have been computed by B-loss matrix. IABC, IABC-LS methods have been applied to three different test systems in literature which consist of 6, 15 and 40 generators. The attained optimum solution values have been compared with the optimum results in literature and have been discussed.

  7. Artificial organs 2010: a year in review.

    Science.gov (United States)

    Malchesky, Paul S

    2011-03-01

    In this Editor's Review, articles published in 2010 are organized by category and briefly summarized. As the official journal of The International Federation for Artificial Organs, The International Faculty for Artificial Organs, and the International Society for Rotary Blood Pumps, Artificial Organs continues in the original mission of its founders "to foster communications in the field of artificial organs on an international level."Artificial Organs continues to publish developments and clinical applications of artificial organ technologies in this broad and expanding field of organ Replacement, Recovery, and Regeneration from all over the world. We take this time also to express our gratitude to our authors for offering their work to this journal. We offer our very special thanks to our reviewers who give so generously of time and expertise to review, critique, and especially provide such meaningful suggestions to the author's work whether eventually accepted or rejected and especially to those whose native tongue is not English. Without these excellent and dedicated reviewers the quality expected from such a journal could not be possible. We also express our special thanks to our Publisher, Wiley-Blackwell, for their expert attention and support in the production and marketing of Artificial Organs. In this Editor's Review, that historically has been widely received by our readership, we aim to provide a brief reflection of the currently available worldwide knowledge that is intended to advance and better human life while providing insight for continued application of technologies and methods of organ Replacement, Recovery, and Regeneration. We look forward to recording further advances in the coming years. © 2011, Copyright the Author. Artificial Organs © 2011, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

  8. Application of Artificial Bee Colony in Model Parameter Identification of Solar Cells

    Directory of Open Access Journals (Sweden)

    Rongjie Wang

    2015-07-01

    Full Text Available The identification of values of solar cell parameters is of great interest for evaluating solar cell performances. The algorithm of an artificial bee colony was used to extract model parameters of solar cells from current-voltage characteristics. Firstly, the best-so-for mechanism was introduced to the original artificial bee colony. Then, a method was proposed to identify parameters for a single diode model and double diode model using this improved artificial bee colony. Experimental results clearly demonstrate the effectiveness of the proposed method and its superior performance compared to other competing methods.

  9. Artificial intelligence in robot control systems

    Science.gov (United States)

    Korikov, A.

    2018-05-01

    This paper analyzes modern concepts of artificial intelligence and known definitions of the term "level of intelligence". In robotics artificial intelligence system is defined as a system that works intelligently and optimally. The author proposes to use optimization methods for the design of intelligent robot control systems. The article provides the formalization of problems of robotic control system design, as a class of extremum problems with constraints. Solving these problems is rather complicated due to the high dimensionality, polymodality and a priori uncertainty. Decomposition of the extremum problems according to the method, suggested by the author, allows reducing them into a sequence of simpler problems, that can be successfully solved by modern computing technology. Several possible approaches to solving such problems are considered in the article.

  10. Generation of artificial time-histories, rich in all frequencies, from given response spectra

    International Nuclear Information System (INIS)

    Levy, S.; Wilkinson, J.P.D.

    1976-01-01

    In the design of nuclear power plants, it has been found desirable in certain instances to use the time-history method of dynamic analysis to determine the plant response to seismic input. In the implementation of this method, it is necessary to determine an adequate representation of the excitation as a function of time. Because many design criteria are specified in terms of design response spectra one is faced with the problem of generating a time-history whose own response spectrum approximates as far as possible to the originally specified design response spectrum. One objective of this paper is to present a method of synthesizing such time-histories from a given design response spectrum. The design response spectra may be descriptive of floor responses at a particular location in a plant, or they may be descriptive of seismic ground motions at a plant site. The method described in this paper allows the generation of time histories that are rich in all frequencies in the spectrum. This richness is achieved by choosing a large number of closely-spaced frequency points such that the half-power points of adjacent frequencies overlap. Examples are given concerning seismic design response spectra, and a number of points are discussed concerning the effect of frequency spacing on convergence. (Auth.)

  11. Forecast for Artificial Muscle Tremor Behavior Based on Dynamic Additional Grey Catastrophe Prediction

    Directory of Open Access Journals (Sweden)

    Yu Fu

    2018-02-01

    Full Text Available Recently, bio-inspired artificial muscles based on ionic polymers have shown a bright perspective in engineering and medical research, but the inherent tremor behavior can cause instability of output response. In this paper, dynamic additional grey catastrophe prediction (DAGCP is proposed to forecast the occurrence time of tremor behavior, providing adequate preparation time for the suppression of the chitosan-based artificial muscles. DAGCP constructs various dimensions of time subsequence models under different starting points based on the threshold of tremor occurrence times and peak-to-peak values in unit time. Next, the appropriate subsequence is selected according to grey correlation degree and prediction accuracy, then it is updated with the newly generated values to achieve a real-time forecast of forthcoming tremor time. Compared with conventional grey catastrophe prediction (GCP, the proposed method has the following advantages: (1 the degradation of prediction accuracy caused by the immobilization of original parameters is prevented; (2 the dynamic input, real-time update and gradual forecast of time sequence are incorporated into the model. The experiment results show that the novel DAGCP can predict forthcoming tremor time earlier and more accurately than the conventional GCP. The generation mechanism of tremor behavior is illustrated as well.

  12. Control of non-linear actuator of artificial muscles for the use in low-cost robotics prosthetics limbs

    Science.gov (United States)

    Anis Atikah, Nurul; Yeng Weng, Leong; Anuar, Adzly; Chien Fat, Chau; Sahari, Khairul Salleh Mohamed; Zainal Abidin, Izham

    2017-10-01

    Currently, the methods of actuating robotic-based prosthetic limbs are moving away from bulky actuators to more fluid materials such as artificial muscles. The main disadvantages of these artificial muscles are their high cost of manufacturing, low-force generation, cumbersome and complex controls. A recent discovery into using super coiled polymer (SCP) proved to have low manufacturing costs, high force generation, compact and simple controls. Nevertheless, the non-linear controls still exists due to the nature of heat-based actuation, which is hysteresis. This makes position control difficult. Using electrically conductive devices allows for very quick heating, but not quick cooling. This research tries to solve the problem by using peltier devices, which can effectively heat and cool the SCP, hence giving way to a more precise control. The peltier device does not actively introduce more energy to a volume of space, which the coiled heating does; instead, it acts as a heat pump. Experiments were conducted to test the feasibility of using peltier as an actuating method on different diameters of nylon fishing strings. Based on these experiments, the performance characteristics of the strings were plotted, which could be used to control the actuation of the string efficiently in the future.

  13. Primitive polynomials selection method for pseudo-random number generator

    Science.gov (United States)

    Anikin, I. V.; Alnajjar, Kh

    2018-01-01

    In this paper we suggested the method for primitive polynomials selection of special type. This kind of polynomials can be efficiently used as a characteristic polynomials for linear feedback shift registers in pseudo-random number generators. The proposed method consists of two basic steps: finding minimum-cost irreducible polynomials of the desired degree and applying primitivity tests to get the primitive ones. Finally two primitive polynomials, which was found by the proposed method, used in pseudorandom number generator based on fuzzy logic (FRNG) which had been suggested before by the authors. The sequences generated by new version of FRNG have low correlation magnitude, high linear complexity, less power consumption, is more balanced and have better statistical properties.

  14. [Artificial intelligence in psychiatry-an overview].

    Science.gov (United States)

    Meyer-Lindenberg, A

    2018-06-18

    Artificial intelligence and the underlying methods of machine learning and neuronal networks (NN) have made dramatic progress in recent years and have allowed computers to reach superhuman performance in domains that used to be thought of as uniquely human. In this overview, the underlying methodological developments that made this possible are briefly delineated and then the applications to psychiatry in three domains are discussed: precision medicine and biomarkers, natural language processing and artificial intelligence-based psychotherapeutic interventions. In conclusion, some of the risks of this new technology are mentioned.

  15. Summary of the benchmark test on artificial noise data

    Energy Technology Data Exchange (ETDEWEB)

    Hoogenboom, J.E.; Ciftcioglu, O.; Dam, H. van

    1988-01-01

    A survey is given of the SMORN-V artificial noise benchmark test for checking autoregressive modelling of noise and testing anomaly detection methods. A detailed description of the system used to generate the signals is given. Contributions from 7 participants have been received. Not all participants executed both the tests on the stationary data and the anomaly data. Comparison of plots of transfer functions, noise contribution ratios and the spectrum of a noise source obtained from AR-analysis partly shows satisfactory agreement (except for normalization), partly distinct disagreement. This was also the case for the several parameters to be determined numerically. The covariance matrices of the intrinsic noise sources showed considerable differences. Participants dealing with the anomaly data used very different methods for anomaly detection. Two of them detected both anomalies present in the signals. One participant the first anomaly and the other participant the second anomaly only.

  16. Summary of the benchmark test on artificial noise data

    International Nuclear Information System (INIS)

    Hoogenboom, J.E.; Ciftcioglu, O.; Dam, H. van

    1988-01-01

    A survey is given of the SMORN-V artificial noise benchmark test for checking autoregressive modelling of noise and testing anomaly detection methods. A detailed description of the system used to generate the signals is given. Contributions from 7 participants have been received. Not all participants executed both the tests on the stationary data and the anomaly data. Comparison of plots of transfer functions, noise contribution ratios and the spectrum of a noise source obtained from AR-analysis partly shows satisfactory agreement (except for normalization), partly distinct disagreement. This was also the case for the several parameters to be determined numerically. The covariance matrices of the intrinsic noise sources showed considerable differences. Participants dealing with the anomaly data used very different methods for anomaly detection. Two of them detected both anomalies present in the signals. One participant the first anomaly and the other participant the second anomaly only. (author)

  17. A new generation in computing

    International Nuclear Information System (INIS)

    Kahn, R.E.

    1983-01-01

    Fifth generation of computers is described. The three disciplines involved in bringing such a new generation to reality are: microelectronics; artificial intelligence and, computer systems and architecture. Applications in industry, offices, aerospace, education, health care and retailing are outlined. An analysis is given of research efforts in the US, Japan, U.K., and Europe. Fifth generation programming languages are detailed

  18. Artificial Organs 2015: A Year in Review.

    Science.gov (United States)

    Malchesky, Paul S

    2016-03-01

    In this Editor's Review, articles published in 2015 are organized by category and briefly summarized. We aim to provide a brief reflection of the currently available worldwide knowledge that is intended to advance and better human life while providing insight for continued application of technologies and methods of organ Replacement, Recovery, and Regeneration. As the official journal of The International Federation for Artificial Organs, The International Faculty for Artificial Organs, the International Society for Rotary Blood Pumps, the International Society for Pediatric Mechanical Cardiopulmonary Support, and the Vienna International Workshop on Functional Electrical Stimulation, Artificial Organs continues in the original mission of its founders "to foster communications in the field of artificial organs on an international level." Artificial Organs continues to publish developments and clinical applications of artificial organ technologies in this broad and expanding field of organ Replacement, Recovery, and Regeneration from all over the world. We take this time also to express our gratitude to our authors for providing their work to this journal. We offer our very special thanks to our reviewers who give so generously of their time and expertise to review, critique, and especially provide meaningful suggestions to the author's work whether eventually accepted or rejected. Without these excellent and dedicated reviewers, the quality expected from such a journal could not be possible. We also express our special thanks to our Publisher, John Wiley & Sons for their expert attention and support in the production and marketing of Artificial Organs. We look forward to reporting further advances in the coming years. Copyright © 2016 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

  19. Artificial Organs 2013: a year in review.

    Science.gov (United States)

    Malchesky, Paul S

    2014-03-01

    In this Editor's Review, articles published in 2013 are organized by category and briefly summarized. We aim to provide a brief reflection of the currently available worldwide knowledge that is intended to advance and better human life while providing insight for continued application of technologies and methods of organ Replacement, Recovery, and Regeneration. As the official journal of The International Federation for Artificial Organs, The International Faculty for Artificial Organs, the International Society for Rotary Blood Pumps, the International Society for Pediatric Mechanical Cardiopulmonary Support, and the Vienna International Workshop on Functional Electrical Stimulation, Artificial Organs continues in the original mission of its founders "to foster communications in the field of artificial organs on an international level". Artificial Organs continues to publish developments and clinical applications of artificial organ technologies in this broad and expanding field of organ Replacement, Recovery, and Regeneration from all over the world. We take this time also to express our gratitude to our authors for offering their work to this journal. We offer our very special thanks to our reviewers who give so generously of time and expertise to review, critique, and especially provide so meaningful suggestions to the author's work whether eventually accepted or rejected and especially to those whose native tongue is not English. Without these excellent and dedicated reviewers the quality expected from such a journal could not be possible. We also express our special thanks to our Publisher, Wiley Periodicals, for their expert attention and support in the production and marketing of Artificial Organs. We look forward to recording further advances in the coming years. © 2014 Wiley Periodicals, Inc. and International Center for Artificial Organs and Transplantation.

  20. Stability monitoring for BWR based on singular value decomposition method using artificial neural network

    International Nuclear Information System (INIS)

    Tsuji, Masashi; Shimazu, Yoichiro; Michishita, Hiroshi

    2005-01-01

    A new method for evaluating the decay ratios in a boiling water reactor (BWR) using the singular value decomposition (SVD) method had been proposed. In this method, a signal component closely related to the BWR stability can be extracted from independent components of the neutron noise signal decomposed by the SVD method. However, real-time stability monitoring by the SVD method requires an efficient procedure for screening such components. For efficient screening, an artificial neural network (ANN) with three layers was adopted. The trained ANN was actually applied to decomposed components of local power range monitor (LPRM) signals that were measured in stability experiments conducted in the Ringhals-1 BWR. In each LPRM signal, multiple candidates were screened from the decomposed components. However, decay ratios could be estimated by introducing appropriate criterions for selecting the most suitable component among the candidates. The estimated decay ratios are almost identical to those evaluated by visual screening in a previous study. The selected components commonly have the largest singular value, the largest decay ratio and the least squared fitting error among the candidates. By virtue of excellent screening performance of the trained ANN, the real-time stability monitoring by the SVD method can be applied in practice. (author)

  1. Intelligent Evaluation Method of Tank Bottom Corrosion Status Based on Improved BP Artificial Neural Network

    Science.gov (United States)

    Qiu, Feng; Dai, Guang; Zhang, Ying

    According to the acoustic emission information and the appearance inspection information of tank bottom online testing, the external factors associated with tank bottom corrosion status are confirmed. Applying artificial neural network intelligent evaluation method, three tank bottom corrosion status evaluation models based on appearance inspection information, acoustic emission information, and online testing information are established. Comparing with the result of acoustic emission online testing through the evaluation of test sample, the accuracy of the evaluation model based on online testing information is 94 %. The evaluation model can evaluate tank bottom corrosion accurately and realize acoustic emission online testing intelligent evaluation of tank bottom.

  2. Residential building energy estimation method based on the application of artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Marshall, S.; Kajl, S.

    1999-07-01

    The energy requirements of a residential building five to twenty-five stories high can be measured using a newly proposed analytical method based on artificial intelligence. The method is fast and provides a wide range of results such as total energy consumption values, power surges, and heating or cooling consumption values. A series of database were created to take into account the particularities which influence the energy consumption of a building. In this study, DOE-2 software was created for use in 8 apartment models. A total of 27 neural networks were used, 3 for the estimation of energy consumption in the corridor, and 24 for inside the apartments. Three user interfaces were created to facilitate the estimation of energy consumption. These were named the Energy Estimation Assistance System (EEAS) interfaces and are only accessible using MATLAB software. The input parameters for EEAS are: climatic region, exterior wall resistance, roofing resistance, type of windows, infiltration, number of storeys, and corridor ventilation system operating schedule. By changing the parameters, the EEAS can determine annual heating, cooling and basic energy consumption levels for apartments and corridors. 2 tabs., 2 figs.

  3. A Universal Method for Species Identification of Mammals Utilizing Next Generation Sequencing for the Analysis of DNA Mixtures

    Science.gov (United States)

    Tillmar, Andreas O.; Dell'Amico, Barbara; Welander, Jenny; Holmlund, Gunilla

    2013-01-01

    Species identification can be interesting in a wide range of areas, for example, in forensic applications, food monitoring and in archeology. The vast majority of existing DNA typing methods developed for species determination, mainly focuses on a single species source. There are, however, many instances where all species from mixed sources need to be determined, even when the species in minority constitutes less than 1 % of the sample. The introduction of next generation sequencing opens new possibilities for such challenging samples. In this study we present a universal deep sequencing method using 454 GS Junior sequencing of a target on the mitochondrial gene 16S rRNA. The method was designed through phylogenetic analyses of DNA reference sequences from more than 300 mammal species. Experiments were performed on artificial species-species mixture samples in order to verify the method’s robustness and its ability to detect all species within a mixture. The method was also tested on samples from authentic forensic casework. The results showed to be promising, discriminating over 99.9 % of mammal species and the ability to detect multiple donors within a mixture and also to detect minor components as low as 1 % of a mixed sample. PMID:24358309

  4. Semantic Network and Frame Knowledge Representation Formalisms in Artificial Intelligence

    OpenAIRE

    Rashid, Pshtiwan Qader

    2015-01-01

    ABSTRACT: Choosing a suitable method to represent the knowledge concerning the real world is one of the major issues involved in Artificial Intelligence. The purpose of this research is to consider the important beneficial roles of semantic network and frame formalisms for knowledge representation in Artificial Intelligence. The basic properties of the above methods for appropriate structuring and arranging the knowledge are presented. Some types of relationships, the conceptual graph...

  5. Biologically inspired technologies using artificial muscles

    Science.gov (United States)

    Bar-Cohen, Yoseph

    2005-01-01

    After billions of years of evolution, nature developed inventions that work, which are appropriate for the intended tasks and that last. The evolution of nature led to the introduction of highly effective and power efficient biological mechanisms that are scalable from micron to many meters in size. Imitating these mechanisms offers enormous potentials for the improvement of our life and the tools we use. Humans have always made efforts to imitate nature and we are increasingly reaching levels of advancement where it becomes significantly easier to imitate, copy, and adapt biological methods, processes and systems. Some of the biomimetic technologies that have emerged include artificial muscles, artificial intelligence, and artificial vision to which significant advances in materials science, mechanics, electronics, and computer science have contributed greatly. One of the newest fields of biomimetics is the electroactive polymers (EAP) that are also known as artificial muscles. To take advantage of these materials, efforts are made worldwide to establish a strong infrastructure addressing the need for comprehensive analytical modeling of their operation mechanism and develop effective processing and characterization techniques. The field is still in its emerging state and robust materials are not readily available however in recent years significant progress has been made and commercial products have already started to appear. This paper covers the state-of-the-art and challenges to making artificial muscles and their potential biomimetic applications.

  6. Method of generating ploynucleotides encoding enhanced folding variants

    Energy Technology Data Exchange (ETDEWEB)

    Bradbury, Andrew M.; Kiss, Csaba; Waldo, Geoffrey S.

    2017-05-02

    The invention provides directed evolution methods for improving the folding, solubility and stability (including thermostability) characteristics of polypeptides. In one aspect, the invention provides a method for generating folding and stability-enhanced variants of proteins, including but not limited to fluorescent proteins, chromophoric proteins and enzymes. In another aspect, the invention provides methods for generating thermostable variants of a target protein or polypeptide via an internal destabilization baiting strategy. Internally destabilization a protein of interest is achieved by inserting a heterologous, folding-destabilizing sequence (folding interference domain) within DNA encoding the protein of interest, evolving the protein sequences adjacent to the heterologous insertion to overcome the destabilization (using any number of mutagenesis methods), thereby creating a library of variants. The variants in the library are expressed, and those with enhanced folding characteristics selected.

  7. Intelligible Artificial Intelligence

    OpenAIRE

    Weld, Daniel S.; Bansal, Gagan

    2018-01-01

    Since Artificial Intelligence (AI) software uses techniques like deep lookahead search and stochastic optimization of huge neural networks to fit mammoth datasets, it often results in complex behavior that is difficult for people to understand. Yet organizations are deploying AI algorithms in many mission-critical settings. In order to trust their behavior, we must make it intelligible --- either by using inherently interpretable models or by developing methods for explaining otherwise overwh...

  8. Application of artificial neural networks to identify equilibration in computer simulations

    Science.gov (United States)

    Leibowitz, Mitchell H.; Miller, Evan D.; Henry, Michael M.; Jankowski, Eric

    2017-11-01

    Determining which microstates generated by a thermodynamic simulation are representative of the ensemble for which sampling is desired is a ubiquitous, underspecified problem. Artificial neural networks are one type of machine learning algorithm that can provide a reproducible way to apply pattern recognition heuristics to underspecified problems. Here we use the open-source TensorFlow machine learning library and apply it to the problem of identifying which hypothetical observation sequences from a computer simulation are “equilibrated” and which are not. We generate training populations and test populations of observation sequences with embedded linear and exponential correlations. We train a two-neuron artificial network to distinguish the correlated and uncorrelated sequences. We find that this simple network is good enough for > 98% accuracy in identifying exponentially-decaying energy trajectories from molecular simulations.

  9. 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...

  10. 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

  11. The Researches on Cycle-Changeable Generation Settlement Method

    Science.gov (United States)

    XU, Jun; LONG, Suyan; LV, Jianhu

    2018-03-01

    Through the analysis of the business characteristics and problems of price adjustment, a cycle-changeable generation settlement method is proposed to support any time cycle settlement, and put forward a complete set of solutions, including the creation of settlement tasks, time power dismantle, generating fixed cycle of electricity, net energy split. At the same time, the overall design flow of cycle-changeable settlement is given. This method supports multiple price adjustments during the month, and also is an effective solution to the cost reduction of month-after price adjustment.

  12. Estimation of effective connectivity using multi-layer perceptron artificial neural network.

    Science.gov (United States)

    Talebi, Nasibeh; Nasrabadi, Ali Motie; Mohammad-Rezazadeh, Iman

    2018-02-01

    Studies on interactions between brain regions estimate effective connectivity, (usually) based on the causality inferences made on the basis of temporal precedence. In this study, the causal relationship is modeled by a multi-layer perceptron feed-forward artificial neural network, because of the ANN's ability to generate appropriate input-output mapping and to learn from training examples without the need of detailed knowledge of the underlying system. At any time instant, the past samples of data are placed in the network input, and the subsequent values are predicted at its output. To estimate the strength of interactions, the measure of " Causality coefficient " is defined based on the network structure, the connecting weights and the parameters of hidden layer activation function. Simulation analysis demonstrates that the method, called "CREANN" (Causal Relationship Estimation by Artificial Neural Network), can estimate time-invariant and time-varying effective connectivity in terms of MVAR coefficients. The method shows robustness with respect to noise level of data. Furthermore, the estimations are not significantly influenced by the model order (considered time-lag), and the different initial conditions (initial random weights and parameters of the network). CREANN is also applied to EEG data collected during a memory recognition task. The results implicate that it can show changes in the information flow between brain regions, involving in the episodic memory retrieval process. These convincing results emphasize that CREANN can be used as an appropriate method to estimate the causal relationship among brain signals.

  13. Effectiveness of Context-Aware Character Input Method for Mobile Phone Based on Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Masafumi Matsuhara

    2012-01-01

    Full Text Available Opportunities and needs are increasing to input Japanese sentences on mobile phones since performance of mobile phones is improving. Applications like E-mail, Web search, and so on are widely used on mobile phones now. We need to input Japanese sentences using only 12 keys on mobile phones. We have proposed a method to input Japanese sentences on mobile phones quickly and easily. We call this method number-Kanji translation method. The number string inputted by a user is translated into Kanji-Kana mixed sentence in our proposed method. Number string to Kana string is a one-to-many mapping. Therefore, it is difficult to translate a number string into the correct sentence intended by the user. The proposed context-aware mapping method is able to disambiguate a number string by artificial neural network (ANN. The system is able to translate number segments into the intended words because the system becomes aware of the correspondence of number segments with Japanese words through learning by ANN. The system does not need a dictionary. We also show the effectiveness of our proposed method for practical use by the result of the evaluation experiment in Twitter data.

  14. Application of artificial neural networks in analysis of CHF experimental data in round tubes

    International Nuclear Information System (INIS)

    Huang Yanping; Chen Bingde; Lang Xuemei; Wang Xiaojun; Shan Jianqiang; Jia Dounan

    2004-01-01

    Artificial neural networks (ANNs) are applied successfully to analyze the critical heat flux (CHF) experimental data from some round tubes in this paper. A set of software adopting artificial neural network method for predicting CHF in round tube and a set of CHF database are gotten. Comparing with common CHF correlations and CHF look-up table, ANN method has stronger ability of allow-wrong and nice robustness. The CHF predicting software adopting artificial neural network technology can improve the predicting accuracy in a wider parameter range, and is easier to update and to use. The artificial neural network method used in this paper can be applied to some similar physical problems. (authors)

  15. A Novel Method for Generating Encryption Keys

    Directory of Open Access Journals (Sweden)

    Dascalescu Ana Cristina

    2009-12-01

    Full Text Available The development of the informational society, which has led to an impressive growth of the information volume circulating in the computer networks, has accelerated the evolution and especially the use of modern cryptography instruments. Today, the commercial products use standard cryptographic libraries that implement certified and tested cryptographic algorithms. Instead, the fragility ofencryption algorithms is given by compositional operations like key handling or key generation. In this sense, the article proposes an innovative method to generate pseudorandom numbers which can be used for the construction of secure stream encryption keys. The proposed method is based on the mathematical complements based on the algebra of the finite fields and uses a particularized structure of the linear feedback shift registers.

  16. Planning Training Loads for the 400 M Hurdles in Three-Month Mesocycles using Artificial Neural Networks.

    Science.gov (United States)

    Przednowek, Krzysztof; Iskra, Janusz; Wiktorowicz, Krzysztof; Krzeszowski, Tomasz; Maszczyk, Adam

    2017-12-01

    This paper presents a novel approach to planning training loads in hurdling using artificial neural networks. The neural models performed the task of generating loads for athletes' training for the 400 meters hurdles. All the models were calculated based on the training data of 21 Polish National Team hurdlers, aged 22.25 ± 1.96, competing between 1989 and 2012. The analysis included 144 training plans that represented different stages in the annual training cycle. The main contribution of this paper is to develop neural models for planning training loads for the entire career of a typical hurdler. In the models, 29 variables were used, where four characterized the runner and 25 described the training process. Two artificial neural networks were used: a multi-layer perceptron and a network with radial basis functions. To assess the quality of the models, the leave-one-out cross-validation method was used in which the Normalized Root Mean Squared Error was calculated. The analysis shows that the method generating the smallest error was the radial basis function network with nine neurons in the hidden layer. Most of the calculated training loads demonstrated a non-linear relationship across the entire competitive period. The resulting model can be used as a tool to assist a coach in planning training loads during a selected training period.

  17. Planning Training Loads for The 400 M Hurdles in Three-Month Mesocycles Using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Przednowek Krzysztof

    2017-12-01

    Full Text Available This paper presents a novel approach to planning training loads in hurdling using artificial neural networks. The neural models performed the task of generating loads for athletes’ training for the 400 meters hurdles. All the models were calculated based on the training data of 21 Polish National Team hurdlers, aged 22.25 ± 1.96, competing between 1989 and 2012. The analysis included 144 training plans that represented different stages in the annual training cycle. The main contribution of this paper is to develop neural models for planning training loads for the entire career of a typical hurdler. In the models, 29 variables were used, where four characterized the runner and 25 described the training process. Two artificial neural networks were used: a multi-layer perceptron and a network with radial basis functions. To assess the quality of the models, the leave-one-out cross-validation method was used in which the Normalized Root Mean Squared Error was calculated. The analysis shows that the method generating the smallest error was the radial basis function network with nine neurons in the hidden layer. Most of the calculated training loads demonstrated a non-linear relationship across the entire competitive period. The resulting model can be used as a tool to assist a coach in planning training loads during a selected training period.

  18. A new collaborative recommendation approach based on users clustering using artificial bee colony algorithm.

    Science.gov (United States)

    Ju, Chunhua; Xu, Chonghuan

    2013-01-01

    Although there are many good collaborative recommendation methods, it is still a challenge to increase the accuracy and diversity of these methods to fulfill users' preferences. In this paper, we propose a novel collaborative filtering recommendation approach based on K-means clustering algorithm. In the process of clustering, we use artificial bee colony (ABC) algorithm to overcome the local optimal problem caused by K-means. After that we adopt the modified cosine similarity to compute the similarity between users in the same clusters. Finally, we generate recommendation results for the corresponding target users. Detailed numerical analysis on a benchmark dataset MovieLens and a real-world dataset indicates that our new collaborative filtering approach based on users clustering algorithm outperforms many other recommendation methods.

  19. A New Collaborative Recommendation Approach Based on Users Clustering Using Artificial Bee Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Chunhua Ju

    2013-01-01

    Full Text Available Although there are many good collaborative recommendation methods, it is still a challenge to increase the accuracy and diversity of these methods to fulfill users’ preferences. In this paper, we propose a novel collaborative filtering recommendation approach based on K-means clustering algorithm. In the process of clustering, we use artificial bee colony (ABC algorithm to overcome the local optimal problem caused by K-means. After that we adopt the modified cosine similarity to compute the similarity between users in the same clusters. Finally, we generate recommendation results for the corresponding target users. Detailed numerical analysis on a benchmark dataset MovieLens and a real-world dataset indicates that our new collaborative filtering approach based on users clustering algorithm outperforms many other recommendation methods.

  20. Artificial light pollution increases nocturnal vigilance in peahens

    Directory of Open Access Journals (Sweden)

    Jessica L. Yorzinski

    2015-08-01

    Full Text Available Artificial light pollution is drastically changing the sensory environments of animals. Even though many animals are now living in these changed environments, the effect light pollution has on animal behavior is poorly understood. We investigated the effect of light pollution on nocturnal vigilance in peahens (Pavo cristatus. Captive peahens were exposed to either artificial lighting or natural lighting at night. We employed a novel method to record their vigilance behavior by attaching accelerometers to their heads and continuously monitoring their large head movements. We found that light pollution significantly increases nocturnal vigilance in peahens. Furthermore, the birds faced a trade-off between vigilance and sleep at night: peahens that were more vigilant spent less time sleeping. Given the choice, peahens preferred to roost away from high levels of artificial lighting but showed no preference for roosting without artificial lighting or with low levels of artificial lighting. Our study demonstrates that light pollution can have a substantial impact on animal behavior that can potentially result in fitness consequences.

  1. Optimal dynamic economic dispatch of generation: A review

    International Nuclear Information System (INIS)

    Xia, X.; Elaiw, A.M.

    2010-01-01

    This paper presents a review of the research of the optimal power dynamic dispatch problem. The dynamic dispatch problem differs from the static economic dispatch problem by incorporating generator ramp rate constraints. There are two different formulations of this problem in the literature. The first formulation is the optimal control dynamic dispatch (OCDD) where the power system generation has been modeled as a control system and optimization is done in the optimal control setting with respect to the ramp rates as input variables. The second one is a later formulation known as the dynamic economic dispatch (DED) where optimization is done with respect to the dispatchable powers of the committed generation units. In this paper we first outline the two formulations, then present an overview on the mathematical optimization methods, Artificial Intelligence (AI) techniques and hybrid methods used to solve the problem incorporating extended and complex objective functions or constraints. The DED problem in deregulated electricity markets is also reported. (author)

  2. Evaluation of the Application of Artificial Neural Networks and Adaptive Neuro-Fuzzy Inference Systems for Rainfall-Runoff Modelling in Zayandeh_rood Dam Basin

    Directory of Open Access Journals (Sweden)

    Mohammad Taghi Dastorani

    2012-01-01

    Full Text Available During recent few decades, due to the importance of the availability of water, and therefore the necesity of predicting run off resulted from rain fall there has been an increase in developing and implementation of new suitable method for prediction of run off using precipitation data. One of these approaches that have been developed in several areas of sciences including water related fields, is soft computing techniques such as artificial neural networks and fuzzy logic systems. This research was designed to evaluate the applicability of artificial neural network and adaptive neuro –fuzzy inference system to model rainfall-runoff process in Zayandeh_rood dam basin. It must be mentioned that, data have been analysed using Wingamma software, to select appropriate type and number of training input data before they can be used in the models. Then, it has been tried to evaluated applicability of artificial neural networks and neuro-fuzzy techniques to predict runoff generated from daily rainfall. Finally, the accuracy of the results produced by these methods has been compared using statistical criterion. Results taken from this research show that artificial neural networks and neuro-fuzzy technique presented different outputs in different conditions in terms of type and number of inputs variables, but both method have been able to produce acceptable results when suitable input variables and network structures are used.

  3. Artificial Organs 2017: A Year in Review.

    Science.gov (United States)

    Malchesky, Paul S

    2018-03-01

    In this Editor's Review, articles published in 2017 are organized by category and summarized. We provide a brief reflection of the research and progress in artificial organs intended to advance and better human life while providing insight for continued application of these technologies and methods. Artificial Organs continues in the original mission of its founders "to foster communications in the field of artificial organs on an international level." Artificial Organs continues to publish developments and clinical applications of artificial organ technologies in this broad and expanding field of organ Replacement, Recovery, and Regeneration from all over the world. Peer-reviewed Special Issues this year included contributions from the 12th International Conference on Pediatric Mechanical Circulatory Support Systems and Pediatric Cardiopulmonary Perfusion edited by Dr. Akif Undar, Artificial Oxygen Carriers edited by Drs. Akira Kawaguchi and Jan Simoni, the 24th Congress of the International Society for Mechanical Circulatory Support edited by Dr. Toru Masuzawa, Challenges in the Field of Biomedical Devices: A Multidisciplinary Perspective edited by Dr. Vincenzo Piemonte and colleagues and Functional Electrical Stimulation edited by Dr. Winfried Mayr and colleagues. We take this time also to express our gratitude to our authors for offering their work to this journal. We offer our very special thanks to our reviewers who give so generously of time and expertise to review, critique, and especially provide meaningful suggestions to the author's work whether eventually accepted or rejected. Without these excellent and dedicated reviewers the quality expected from such a journal could not be possible. We also express our special thanks to our Publisher, John Wiley & Sons for their expert attention and support in the production and marketing of Artificial Organs. We look forward to reporting further advances in the coming years. © 2018 International Center for

  4. Three-Dimensional Human iPSC-Derived Artificial Skeletal Muscles Model Muscular Dystrophies and Enable Multilineage Tissue Engineering

    Directory of Open Access Journals (Sweden)

    Sara Martina Maffioletti

    2018-04-01

    Full Text Available Summary: Generating human skeletal muscle models is instrumental for investigating muscle pathology and therapy. Here, we report the generation of three-dimensional (3D artificial skeletal muscle tissue from human pluripotent stem cells, including induced pluripotent stem cells (iPSCs from patients with Duchenne, limb-girdle, and congenital muscular dystrophies. 3D skeletal myogenic differentiation of pluripotent cells was induced within hydrogels under tension to provide myofiber alignment. Artificial muscles recapitulated characteristics of human skeletal muscle tissue and could be implanted into immunodeficient mice. Pathological cellular hallmarks of incurable forms of severe muscular dystrophy could be modeled with high fidelity using this 3D platform. Finally, we show generation of fully human iPSC-derived, complex, multilineage muscle models containing key isogenic cellular constituents of skeletal muscle, including vascular endothelial cells, pericytes, and motor neurons. These results lay the foundation for a human skeletal muscle organoid-like platform for disease modeling, regenerative medicine, and therapy development. : Maffioletti et al. generate human 3D artificial skeletal muscles from healthy donors and patient-specific pluripotent stem cells. These human artificial muscles accurately model severe genetic muscle diseases. They can be engineered to include other cell types present in skeletal muscle, such as vascular cells and motor neurons. Keywords: skeletal muscle, pluripotent stem cells, iPS cells, myogenic differentiation, tissue engineering, disease modeling, muscular dystrophy, organoids

  5. A simple method for generating exactly solvable quantum mechanical potentials

    CERN Document Server

    Williams, B W

    1993-01-01

    A simple transformation method permitting the generation of exactly solvable quantum mechanical potentials from special functions solving second-order differential equations is reviewed. This method is applied to Gegenbauer polynomials to generate an attractive radial potential. The relationship of this method to the determination of supersymmetric quantum mechanical superpotentials is discussed, and the superpotential for the radial potential is also derived. (author)

  6. Modelling and Prediction of Photovoltaic Power Output Using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Aminmohammad Saberian

    2014-01-01

    Full Text Available This paper presents a solar power modelling method using artificial neural networks (ANNs. Two neural network structures, namely, general regression neural network (GRNN feedforward back propagation (FFBP, have been used to model a photovoltaic panel output power and approximate the generated power. Both neural networks have four inputs and one output. The inputs are maximum temperature, minimum temperature, mean temperature, and irradiance; the output is the power. The data used in this paper started from January 1, 2006, until December 31, 2010. The five years of data were split into two parts: 2006–2008 and 2009-2010; the first part was used for training and the second part was used for testing the neural networks. A mathematical equation is used to estimate the generated power. At the end, both of these networks have shown good modelling performance; however, FFBP has shown a better performance comparing with GRNN.

  7. Artificial Intelligence In Computational Fluid Dynamics

    Science.gov (United States)

    Vogel, Alison Andrews

    1991-01-01

    Paper compares four first-generation artificial-intelligence (Al) software systems for computational fluid dynamics. Includes: Expert Cooling Fan Design System (EXFAN), PAN AIR Knowledge System (PAKS), grid-adaptation program MITOSIS, and Expert Zonal Grid Generation (EZGrid). Focuses on knowledge-based ("expert") software systems. Analyzes intended tasks, kinds of knowledge possessed, magnitude of effort required to codify knowledge, how quickly constructed, performances, and return on investment. On basis of comparison, concludes Al most successful when applied to well-formulated problems solved by classifying or selecting preenumerated solutions. In contrast, application of Al to poorly understood or poorly formulated problems generally results in long development time and large investment of effort, with no guarantee of success.

  8. Generalized Artificial Life Structure for Time-dependent Problems

    Institute of Scientific and Technical Information of China (English)

    TSAU Minhe; KAO Weiwen; CHANG Albert

    2009-01-01

    In recent years, more attention has been paid on artificial life researches. Artificial life(AL) is a research on regulating gene parameters of digital organisms under complicated problematic environments through natural selections and evolutions to achieve the final emergence of intelligence. Most recent studies focused on solving certain real problems by artificial life methods, yet without much address on the AL life basic mechanism. The real problems are often very complicated, and the proposed methods sometimes seem too simple to handle those problems. This study proposed a new approach in AL research, named "generalized artificial life structure(GALS)", in which the traditional "gene bits" in genetic algorithms is first replaced by "gene parameters", which could appear anywhere in GALS. A modeling procedure is taken to normalize the input data, and AL "tissue" is innovated to make AL more complex. GALS is anticipated to contribute significantly to the fitness of AL evolution. The formation of"tissue" begins with some different AL basic cells, and then tissue is produced by the casual selections of one or several of these cells. As a result, the gene parameters, represented by "tissues", could become highly diversified. This diversification should have obvious effects on improving gene fitness. This study took the innovative method of GALS in a stock forecasting problem under a carefully designed manipulating platform. And the researching results verify that the GALS is successful in improving the gene evolution fitness.

  9. An example of the use of the DELPHI method: future prospects of artificial heart techniques in France; Un exemple d'utilisation de la methode DELPHI: perspectives de developpement en France des techniques de coeur artificiel

    Energy Technology Data Exchange (ETDEWEB)

    Derian, Jean-Claude [Commissariat a l' energie atomique et aux energies alternatives - CEA, Centre d' Etudes Nucleaires de Fontenay-aux-Roses, Departement des Programmes, Section des Etudes Economiques Generales (France); Morize, Francoise [Commissariat a l' energie atomique et aux energies alternatives - CEA, Centre d' Etudes Nucleaires de Saclay, Institut National des Sciences et Techniques Nucleaires (France); Vernejoul, Pierre de [Faculte de Medecine Necker - Enfants Malades (France); Service Hospitalier Frederic Joliot (France); Vial, Renee [Direction de Protection et Surete Radiologiques (France)

    1971-07-01

    The artificial heart is still only a research project surrounded by numerous uncertainties which make it very difficult to estimate, at the moment, the possibilities for future development of this technique in France. A systematic analysis of the hazards which characterize this project has been undertaken in the following report: restricting these uncertainties has required a taking into account of opinions of specialists concerned with type of research or its upshot. We have achieved this by adapting an investigation technique which is still unusual in France, the DELPHI method. This adaptation has allowed the confrontation and statistical aggregation of the opinions given by a body of a hundred experts who were consulted through a program of sequential interrogations which studied in particular, the probable date of the research issue, the clinical cases which require the use of an artificial heart, as well as the probable future needs. After having taken into account the economic constraints, we can deduce from these results the probable amount of plutonium 238 needed in the hypothesis where isotopic generator would be retained for the energetics feeding of the artificial heart [French] Le coeur artificiel n'est encore actuellement qu'un projet de recherche auquel sont attachees de nombreuses incertitudes qui rendent difficile l'appreciation des possibilites de developpement futures de cette technique en France. Une analyse systematique des aleas qui caracterisent ce projet est entreprise dans l'etude ci-apres: circonscrire ces aleas necessite la prise en compte d'opinions emanant des specialistes concernes par cette recherche ou par son issue: c'est ce qui a ete realise en adaptant une methodologie non classique en France, la methode DELPHI. Cette adaptation a permis la confrontation et l'agregation statistique des opinions fournies par un college d'une centaine d'experts consultes par un programme d'interrogations sequentielles, envisageant en particulier les

  10. An Efficient Method for Generation of Transgenic Rats Avoiding Embryo Manipulation

    Directory of Open Access Journals (Sweden)

    Bhola Shankar Pradhan

    2016-01-01

    Full Text Available Although rats are preferred over mice as an animal model, transgenic animals are generated predominantly using mouse embryos. There are limitations in the generation of transgenic rat by embryo manipulation. Unlike mouse embryos, most of the rat embryos do not survive after male pronuclear DNA injection which reduces the efficiency of generation of transgenic rat by this method. More importantly, this method requires hundreds of eggs collected by killing several females for insertion of transgene to generate transgenic rat. To this end, we developed a noninvasive and deathless technique for generation of transgenic rats by integrating transgene into the genome of the spermatogonial cells by testicular injection of DNA followed by electroporation. After standardization of this technique using EGFP as a transgene, a transgenic disease model displaying alpha thalassemia was successfully generated using rats. This efficient method will ease the generation of transgenic rats without killing the lives of rats while simultaneously reducing the number of rats used for generation of transgenic animal.

  11. Classification of intelligence quotient via brainwave sub-band power ratio features and artificial neural network.

    Science.gov (United States)

    Jahidin, A H; Megat Ali, M S A; Taib, M N; Tahir, N Md; Yassin, I M; Lias, S

    2014-04-01

    This paper elaborates on the novel intelligence assessment method using the brainwave sub-band power ratio features. The study focuses only on the left hemisphere brainwave in its relaxed state. Distinct intelligence quotient groups have been established earlier from the score of the Raven Progressive Matrices. Sub-band power ratios are calculated from energy spectral density of theta, alpha and beta frequency bands. Synthetic data have been generated to increase dataset from 50 to 120. The features are used as input to the artificial neural network. Subsequently, the brain behaviour model has been developed using an artificial neural network that is trained with optimized learning rate, momentum constant and hidden nodes. Findings indicate that the distinct intelligence quotient groups can be classified from the brainwave sub-band power ratios with 100% training and 88.89% testing accuracies. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  12. Using Drawings and Collages as Data Generation Methods With Children

    Directory of Open Access Journals (Sweden)

    Nokhanyo Nomakhwezi Mayaba

    2015-12-01

    Full Text Available Appropriate data generation methods are key to a successful research project to attain rich and relevant data. When doing research with children, the methods selected should be age appropriate and enable them to contribute their ideas in the research process. However, data generation with children is not “child’s play”—it is a challenging task that requires careful design on the part of the researcher. We conducted a study in South Africa with children between the ages of 9 and 14 who were orphaned and rendered vulnerable by HIV and AIDS in order to explore if, and how, the use of participatory visual methods might enhance resilience. In this article, we provide a reflective account of the research process and discuss lessons learnt from our experiences of using drawings and collage as data generation methods when doing research with children. This article contributes to the literature on the use of participatory visual methods as data generation strategies with children highlighting some caveats and offering insight into how challenges could be circumvented.

  13. The spatial prediction of landslide susceptibility applying artificial neural network and logistic regression models: A case study of Inje, Korea

    Science.gov (United States)

    Saro, Lee; Woo, Jeon Seong; Kwan-Young, Oh; Moung-Jin, Lee

    2016-02-01

    The aim of this study is to predict landslide susceptibility caused using the spatial analysis by the application of a statistical methodology based on the GIS. Logistic regression models along with artificial neutral network were applied and validated to analyze landslide susceptibility in Inje, Korea. Landslide occurrence area in the study were identified based on interpretations of optical remote sensing data (Aerial photographs) followed by field surveys. A spatial database considering forest, geophysical, soil and topographic data, was built on the study area using the Geographical Information System (GIS). These factors were analysed using artificial neural network (ANN) and logistic regression models to generate a landslide susceptibility map. The study validates the landslide susceptibility map by comparing them with landslide occurrence areas. The locations of landslide occurrence were divided randomly into a training set (50%) and a test set (50%). A training set analyse the landslide susceptibility map using the artificial network along with logistic regression models, and a test set was retained to validate the prediction map. The validation results revealed that the artificial neural network model (with an accuracy of 80.10%) was better at predicting landslides than the logistic regression model (with an accuracy of 77.05%). Of the weights used in the artificial neural network model, `slope' yielded the highest weight value (1.330), and `aspect' yielded the lowest value (1.000). This research applied two statistical analysis methods in a GIS and compared their results. Based on the findings, we were able to derive a more effective method for analyzing landslide susceptibility.

  14. The spatial prediction of landslide susceptibility applying artificial neural network and logistic regression models: A case study of Inje, Korea

    Directory of Open Access Journals (Sweden)

    Saro Lee

    2016-02-01

    Full Text Available The aim of this study is to predict landslide susceptibility caused using the spatial analysis by the application of a statistical methodology based on the GIS. Logistic regression models along with artificial neutral network were applied and validated to analyze landslide susceptibility in Inje, Korea. Landslide occurrence area in the study were identified based on interpretations of optical remote sensing data (Aerial photographs followed by field surveys. A spatial database considering forest, geophysical, soil and topographic data, was built on the study area using the Geographical Information System (GIS. These factors were analysed using artificial neural network (ANN and logistic regression models to generate a landslide susceptibility map. The study validates the landslide susceptibility map by comparing them with landslide occurrence areas. The locations of landslide occurrence were divided randomly into a training set (50% and a test set (50%. A training set analyse the landslide susceptibility map using the artificial network along with logistic regression models, and a test set was retained to validate the prediction map. The validation results revealed that the artificial neural network model (with an accuracy of 80.10% was better at predicting landslides than the logistic regression model (with an accuracy of 77.05%. Of the weights used in the artificial neural network model, ‘slope’ yielded the highest weight value (1.330, and ‘aspect’ yielded the lowest value (1.000. This research applied two statistical analysis methods in a GIS and compared their results. Based on the findings, we were able to derive a more effective method for analyzing landslide susceptibility.

  15. Prediction of the Thermal Conductivity of Refrigerants by Computational Methods and Artificial Neural Network.

    Science.gov (United States)

    Ghaderi, Forouzan; Ghaderi, Amir H; Ghaderi, Noushin; Najafi, Bijan

    2017-01-01

    Background: The thermal conductivity of fluids can be calculated by several computational methods. However, these methods are reliable only at the confined levels of density, and there is no specific computational method for calculating thermal conductivity in the wide ranges of density. Methods: In this paper, two methods, an Artificial Neural Network (ANN) approach and a computational method established upon the Rainwater-Friend theory, were used to predict the value of thermal conductivity in all ranges of density. The thermal conductivity of six refrigerants, R12, R14, R32, R115, R143, and R152 was predicted by these methods and the effectiveness of models was specified and compared. Results: The results show that the computational method is a usable method for predicting thermal conductivity at low levels of density. However, the efficiency of this model is considerably reduced in the mid-range of density. It means that this model cannot be used at density levels which are higher than 6. On the other hand, the ANN approach is a reliable method for thermal conductivity prediction in all ranges of density. The best accuracy of ANN is achieved when the number of units is increased in the hidden layer. Conclusion: The results of the computational method indicate that the regular dependence between thermal conductivity and density at higher densities is eliminated. It can develop a nonlinear problem. Therefore, analytical approaches are not able to predict thermal conductivity in wide ranges of density. Instead, a nonlinear approach such as, ANN is a valuable method for this purpose.

  16. Preconditioned characteristic boundary conditions based on artificial compressibility method for solution of incompressible flows

    Science.gov (United States)

    Hejranfar, Kazem; Parseh, Kaveh

    2017-09-01

    The preconditioned characteristic boundary conditions based on the artificial compressibility (AC) method are implemented at artificial boundaries for the solution of two- and three-dimensional incompressible viscous flows in the generalized curvilinear coordinates. The compatibility equations and the corresponding characteristic variables (or the Riemann invariants) are mathematically derived and then applied as suitable boundary conditions in a high-order accurate incompressible flow solver. The spatial discretization of the resulting system of equations is carried out by the fourth-order compact finite-difference (FD) scheme. In the preconditioning applied here, the value of AC parameter in the flow field and also at the far-field boundary is automatically calculated based on the local flow conditions to enhance the robustness and performance of the solution algorithm. The code is fully parallelized using the Concurrency Runtime standard and Parallel Patterns Library (PPL) and its performance on a multi-core CPU is analyzed. The incompressible viscous flows around a 2-D circular cylinder, a 2-D NACA0012 airfoil and also a 3-D wavy cylinder are simulated and the accuracy and performance of the preconditioned characteristic boundary conditions applied at the far-field boundaries are evaluated in comparison to the simplified boundary conditions and the non-preconditioned characteristic boundary conditions. It is indicated that the preconditioned characteristic boundary conditions considerably improve the convergence rate of the solution of incompressible flows compared to the other boundary conditions and the computational costs are significantly decreased.

  17. Liquefaction Microzonation of Babol City Using Artificial Neural Network

    DEFF Research Database (Denmark)

    Farrokhzad, F.; Choobbasti, A.J.; Barari, Amin

    2012-01-01

    that will be less susceptible to damage during earthquakes. The scope of present study is to prepare the liquefaction microzonation map for the Babol city based on Seed and Idriss (1983) method using artificial neural network. Artificial neural network (ANN) is one of the artificial intelligence (AI) approaches...... microzonation map is produced for research area. Based on the obtained results, it can be stated that the trained neural network is capable in prediction of liquefaction potential with an acceptable level of confidence. At the end, zoning of the city is carried out based on the prediction of liquefaction...... that can be classified as machine learning. Simplified methods have been practiced by researchers to assess nonlinear liquefaction potential of soil. In order to address the collective knowledge built-up in conventional liquefaction engineering, an alternative general regression neural network model...

  18. Artificial Leaf Based on Artificial Photosynthesis for Solar Fuel Production

    Science.gov (United States)

    2017-06-30

    collect light energy and separate charge for developing new types of nanobiodevices to construct ”artificial leaf” from solar to fuel. or Concept of...AFRL-AFOSR-JP-TR-2017-0054 Artificial Leaf Based on Artificial Photosynthesis for Solar Fuel Production Mamoru Nango NAGOYA INSTITUTE OF TECHNOLOGY...display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ORGANIZATION. 1. REPORT DATE (DD-MM-YYYY)      30-06-2017 2

  19. Improved methodology for generation of axial flux shapes in digital core protection systems

    International Nuclear Information System (INIS)

    Lee, G.-C.; Baek, W.-P.; Chang, S.H.

    2002-01-01

    An improved method of axial flux shape (AFS) generation for digital core protection systems of pressurized water reactors is presented in this paper using an artificial neural network (ANN) technique - a feedforward network trained by backpropagation. It generates 20-node axial power shapes based on the information from three ex-core detectors. In developing the method, a total of 7173 axial flux shapes are generated from ROCS code simulation for training and testing of the ANN. The ANN trained 200 data predicts the remaining data with the average root mean square error of about 3%. The developed method is also tested with the real plant data measured during normal operation of Yonggwang Unit 4. The RMS errors in the range of 0.9∼2.1% are about twice as accurate as the cubic spline approximation method currently used in the plant. The developed method would contribute to solve the drawback of the current method as it shows reasonable accuracy over wide range of core conditions

  20. Adaptive integration of daylight and artificial lighting

    DEFF Research Database (Denmark)

    Petersen, Kjell Yngve

    2016-01-01

    Daylight is dynamic and dependent upon weather conditions; unfolding with both subtle and dramatic variations in qualities of light. Through a building’s apertures, daylight creates a connection between the space inside and the world outside. The aperture or window itself constitutes the frame...... with the world. In contrast to fluctuating daylight, a specific distinctive feature of artificial light has been – until very recently – its constancy in colour and intensity. However, by virtue of the technological convertibility of LEDs in concert with digital control systems, LEDs are capable of dynamically...... producing variations in colour and intensity in ways that correspond to our experiences of the daylight. Daylight and artificial lighting are thus positioned in a new relationship to one another. Metaphorically, one can think of the adaptive software as ‘digital weather’ – as a self-generating and shifting...

  1. Artificial Intelligence for Diabetes Management and Decision Support: Literature Review.

    Science.gov (United States)

    Contreras, Ivan; Vehi, Josep

    2018-05-30

    Artificial intelligence methods in combination with the latest technologies, including medical devices, mobile computing, and sensor technologies, have the potential to enable the creation and delivery of better management services to deal with chronic diseases. One of the most lethal and prevalent chronic diseases is diabetes mellitus, which is characterized by dysfunction of glucose homeostasis. The objective of this paper is to review recent efforts to use artificial intelligence techniques to assist in the management of diabetes, along with the associated challenges. A review of the literature was conducted using PubMed and related bibliographic resources. Analyses of the literature from 2010 to 2018 yielded 1849 pertinent articles, of which we selected 141 for detailed review. We propose a functional taxonomy for diabetes management and artificial intelligence. Additionally, a detailed analysis of each subject category was performed using related key outcomes. This approach revealed that the experiments and studies reviewed yielded encouraging results. We obtained evidence of an acceleration of research activity aimed at developing artificial intelligence-powered tools for prediction and prevention of complications associated with diabetes. Our results indicate that artificial intelligence methods are being progressively established as suitable for use in clinical daily practice, as well as for the self-management of diabetes. Consequently, these methods provide powerful tools for improving patients' quality of life. ©Ivan Contreras, Josep Vehi. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 30.05.2018.

  2. Model-Based Fault Diagnosis in Electric Drive Inverters Using Artificial Neural Network

    National Research Council Canada - National Science Library

    Masrur, Abul; Chen, ZhiHang; Zhang, Baifang; Jia, Hongbin; Murphey, Yi-Lu

    2006-01-01

    .... A normal model and various faulted models of the inverter-motor combination were developed, and voltages and current signals were generated from those models to train an artificial neural network for fault diagnosis...

  3. [Experimental study on novel hybrid artificial trachea transplantation].

    Science.gov (United States)

    Liu, Wenliang; Xiao, Peng; Liang, Hengxing; An, Ran; Cheng, Gang; Yu, Fenglei

    2014-04-01

    We developed and designed a new type of artificial trachea. The basic structure of the artificial trachea was polytetrafluoroethylene vascular prosthesis linked with titanium rings on both sides. Dualmesh was sutured on titanium rings. This experimentation follows the replacement of trachea in dogs with a combined artificial trachea to investigate the feasibility of this type of prosthesis. Sixteen dogs were implanted with the combined artificial trachea after resection of 5 cm of cervical trachea. The 5 cm-long trachea of dogs on the necks were resected and the reconstruction of the defect of the trachea was performed with trachea prosthesis. According to the method of trachea reconstruction, the models were divided into 2 groups, artificial trachea implantation group (the control group, n = 8) and group of artificial trachea implantation with growth factor (the experimental group, n = 8). Then computer tomography scan (CT), bronchoscope and pathologic examination were conducted periodically to observe the healing state of the hybrid artificial trachea. None of the dogs died during operation of cervical segmental trachea construction. But four dogs in the control group died of apnea in succession because artificial trachea was displaced and the lumen was obstructed, while 2 dogs died in the experimental group. In the first month there was granulation around anastomosis with slight stenosis. The rest of dogs were well alive until they were sacrificed 14 months later. The mean survival time of the experimental group was longer than that of the control group. The rate of infection, anastomotic dehiscence, severe stenosis and accidental death in the experimental group were lower than the control group (P anastomosis effectively but infections and split or displacement of the artificial trachea are still major problems affecting long-term survival of the animals. Application of growth factors to a certain extent promotes tissue healing by changing the local environment.

  4. Plane-wave diffraction by periodic structures with artificial anisotropic dielectrics

    International Nuclear Information System (INIS)

    Kazerooni, Azadeh Semsar; Shahabadi, Mahmoud

    2010-01-01

    Periodic structures with artificial anisotropic dielectrics are studied. The artificial anisotropic dielectric material in this work is made of two alternating isotropic dielectric layers. By a proper choice of the dielectric constant of the layers, we can realize a uniaxial anisotropic medium with controllable anisotropy. The artificial anisotropic dielectric is then used in periodic structures. For these structures, the optical axis of the artificial dielectric is assumed to be parallel or perpendicular to the period of the structure. Diffraction of plane waves by these structures is analyzed by a fully vectorial rigorous matrix method based on a generalized transmission line (TL) formulation. The propagation constants and field distributions are computed and diffraction properties of such structures are studied to show that, by a proper choice of structural parameters, these periodic structures with artificial anisotropic dielectrics can be used as polarizers or polarizing mirrors

  5. Upwind methods for the Baer–Nunziato equations and higher-order reconstruction using artificial viscosity

    International Nuclear Information System (INIS)

    Fraysse, F.; Redondo, C.; Rubio, G.; Valero, E.

    2016-01-01

    This article is devoted to the numerical discretisation of the hyperbolic two-phase flow model of Baer and Nunziato. A special attention is paid on the discretisation of intercell flux functions in the framework of Finite Volume and Discontinuous Galerkin approaches, where care has to be taken to efficiently approximate the non-conservative products inherent to the model equations. Various upwind approximate Riemann solvers have been tested on a bench of discontinuous test cases. New discretisation schemes are proposed in a Discontinuous Galerkin framework following the criterion of Abgrall and the path-conservative formalism. A stabilisation technique based on artificial viscosity is applied to the high-order Discontinuous Galerkin method and compared against classical TVD-MUSCL Finite Volume flux reconstruction.

  6. Upwind methods for the Baer–Nunziato equations and higher-order reconstruction using artificial viscosity

    Energy Technology Data Exchange (ETDEWEB)

    Fraysse, F., E-mail: francois.fraysse@rs2n.eu [RS2N, St. Zacharie (France); E. T. S. de Ingeniería Aeronáutica y del Espacio, Universidad Politécnica de Madrid, Madrid (Spain); Redondo, C.; Rubio, G.; Valero, E. [E. T. S. de Ingeniería Aeronáutica y del Espacio, Universidad Politécnica de Madrid, Madrid (Spain)

    2016-12-01

    This article is devoted to the numerical discretisation of the hyperbolic two-phase flow model of Baer and Nunziato. A special attention is paid on the discretisation of intercell flux functions in the framework of Finite Volume and Discontinuous Galerkin approaches, where care has to be taken to efficiently approximate the non-conservative products inherent to the model equations. Various upwind approximate Riemann solvers have been tested on a bench of discontinuous test cases. New discretisation schemes are proposed in a Discontinuous Galerkin framework following the criterion of Abgrall and the path-conservative formalism. A stabilisation technique based on artificial viscosity is applied to the high-order Discontinuous Galerkin method and compared against classical TVD-MUSCL Finite Volume flux reconstruction.

  7. Application of artificial neural networks for response surface modelling in HPLC method development

    Directory of Open Access Journals (Sweden)

    Mohamed A. Korany

    2012-01-01

    Full Text Available This paper discusses the usefulness of artificial neural networks (ANNs for response surface modelling in HPLC method development. In this study, the combined effect of pH and mobile phase composition on the reversed-phase liquid chromatographic behaviour of a mixture of salbutamol (SAL and guaiphenesin (GUA, combination I, and a mixture of ascorbic acid (ASC, paracetamol (PAR and guaiphenesin (GUA, combination II, was investigated. The results were compared with those produced using multiple regression (REG analysis. To examine the respective predictive power of the regression model and the neural network model, experimental and predicted response factor values, mean of squares error (MSE, average error percentage (Er%, and coefficients of correlation (r were compared. It was clear that the best networks were able to predict the experimental responses more accurately than the multiple regression analysis.

  8. Distinguishing of artificial irradiation by α dose: a method of discriminating imitations of ancient pottery

    International Nuclear Information System (INIS)

    Wang Weida; Xia Junding; Zhou Zhixin; Leung, P.L.

    2003-01-01

    If a modern pottery is artificially irradiated by γ-rays of 60 Co source, the modern will become ancient when the pottery is dated by the thermoluminescence technique. For distinguishing artificial irradiation a study was made. Meanwhile the 'fine-grain' and 'pre-dose' techniques were used respectively for measurement of the paleodose in a fine-grain sample from the same pottery. If the paleodose measured by the fine-grain technique is greater than that by the pre-dose techniques, we can affirm that the difference between two paleodoses is due to α dose and this paleodose containing α component results from natural radiation, the pottery therefore is ancient. If two paleodoses are equal approximately, i.e. α dose is not included in the paleodose, the paleodose comes from artificial γ irradiation and the pottery is an imitation

  9. Comparison of Boolean analysis and standard phylogenetic methods using artificially evolved and natural mt-tRNA sequences from great apes.

    Science.gov (United States)

    Ari, Eszter; Ittzés, Péter; Podani, János; Thi, Quynh Chi Le; Jakó, Eena

    2012-04-01

    Boolean analysis (or BOOL-AN; Jakó et al., 2009. BOOL-AN: A method for comparative sequence analysis and phylogenetic reconstruction. Mol. Phylogenet. Evol. 52, 887-97.), a recently developed method for sequence comparison uses the Iterative Canonical Form of Boolean functions. It considers sequence information in a way entirely different from standard phylogenetic methods (i.e. Maximum Parsimony, Maximum-Likelihood, Neighbor-Joining, and Bayesian analysis). The performance and reliability of Boolean analysis were tested and compared with the standard phylogenetic methods, using artificially evolved - simulated - nucleotide sequences and the 22 mitochondrial tRNA genes of the great apes. At the outset, we assumed that the phylogeny of Hominidae is generally well established, and the guide tree of artificial sequence evolution can also be used as a benchmark. These offer a possibility to compare and test the performance of different phylogenetic methods. Trees were reconstructed by each method from 2500 simulated sequences and 22 mitochondrial tRNA sequences. We also introduced a special re-sampling method for Boolean analysis on permuted sequence sites, the P-BOOL-AN procedure. Considering the reliability values (branch support values of consensus trees and Robinson-Foulds distances) we used for simulated sequence trees produced by different phylogenetic methods, BOOL-AN appeared as the most reliable method. Although the mitochondrial tRNA sequences of great apes are relatively short (59-75 bases long) and the ratio of their constant characters is about 75%, BOOL-AN, P-BOOL-AN and the Bayesian approach produced the same tree-topology as the established phylogeny, while the outcomes of Maximum Parsimony, Maximum-Likelihood and Neighbor-Joining methods were equivocal. We conclude that Boolean analysis is a promising alternative to existing methods of sequence comparison for phylogenetic reconstruction and congruence analysis. Copyright © 2012 Elsevier Inc. All

  10. Generating and testing methods for consumer-oriented product development

    International Nuclear Information System (INIS)

    2001-10-01

    In order to obtain a good insight into various design methods that can be used by product developers to enable them to develop and test useful domotics products (domotics: intelligent systems for the home), an inventory has been made of the methods used in the Netherlands. The inventory is directed at two categories of methods: (1) Methods of getting better acquainted with the user and/or the problem, and of generating novel solutions: generative methods; and (2) Methods of assessing solutions (through various phases of the designing process): testing methods. The first category of methods concentrates on the designing process. In other words: how can the designer realise as much as possible of the workability of (domotics) products during the designing process? The second category aims at testing a design (in whatever shape: drawing, prototype, functional computer animation, etc.) through its users. These are methods of assessing a design at various stages of the designing process [nl

  11. On the relationships between generative encodings, regularity, and learning abilities when evolving plastic artificial neural networks.

    Directory of Open Access Journals (Sweden)

    Paul Tonelli

    Full Text Available A major goal of bio-inspired artificial intelligence is to design artificial neural networks with abilities that resemble those of animal nervous systems. It is commonly believed that two keys for evolving nature-like artificial neural networks are (1 the developmental process that links genes to nervous systems, which enables the evolution of large, regular neural networks, and (2 synaptic plasticity, which allows neural networks to change during their lifetime. So far, these two topics have been mainly studied separately. The present paper shows that they are actually deeply connected. Using a simple operant conditioning task and a classic evolutionary algorithm, we compare three ways to encode plastic neural networks: a direct encoding, a developmental encoding inspired by computational neuroscience models, and a developmental encoding inspired by morphogen gradients (similar to HyperNEAT. Our results suggest that using a developmental encoding could improve the learning abilities of evolved, plastic neural networks. Complementary experiments reveal that this result is likely the consequence of the bias of developmental encodings towards regular structures: (1 in our experimental setup, encodings that tend to produce more regular networks yield networks with better general learning abilities; (2 whatever the encoding is, networks that are the more regular are statistically those that have the best learning abilities.

  12. Multisensor system for toxic gases detection generated on indoor environments

    Science.gov (United States)

    Durán, C. M.; Monsalve, P. A. G.; Mosquera, C. J.

    2016-11-01

    This work describes a wireless multisensory system for different toxic gases detection generated on indoor environments (i.e., Underground coal mines, etc.). The artificial multisensory system proposed in this study was developed through a set of six chemical gas sensors (MQ) of low cost with overlapping sensitivities to detect hazardous gases in the air. A statistical parameter was implemented to the data set and two pattern recognition methods such as Principal Component Analysis (PCA) and Discriminant Function Analysis (DFA) were used for feature selection. The toxic gases categories were classified with a Probabilistic Neural Network (PNN) in order to validate the results previously obtained. The tests were carried out to verify feasibility of the application through a wireless communication model which allowed to monitor and store the information of the sensor signals for the appropriate analysis. The success rate in the measures discrimination was 100%, using an artificial neural network where leave-one-out was used as cross validation method.

  13. An Improved Artificial Bee Colony Algorithm and Its Application to Multi-Objective Optimal Power Flow

    Directory of Open Access Journals (Sweden)

    Xuanhu He

    2015-03-01

    Full Text Available Optimal power flow (OPF objective functions involve minimization of the total fuel costs of generating units, minimization of atmospheric pollutant emissions, minimization of active power losses and minimization of voltage deviations. In this paper, a fuzzy multi-objective OPF model is established by the fuzzy membership functions and the fuzzy satisfaction-maximizing method. The improved artificial bee colony (IABC algorithm is applied to solve the model. In the IABC algorithm, the mutation and crossover operations of a differential evolution algorithm are utilized to generate new solutions to improve exploitation capacity; tent chaos mapping is utilized to generate initial swarms, reference mutation solutions and the reference dimensions of crossover operations to improve swarm diversity. The proposed method is applied to multi-objective OPF problems in IEEE 30-bus, IEEE 57-bus and IEEE 300-bus test systems. The results are compared with those obtained by other algorithms, which demonstrates the effectiveness and superiority of the IABC algorithm, and how the optimal scheme obtained by the proposed model can make systems more economical and stable.

  14. Bidding strategy based on artificial intelligence for a competitive electric market

    International Nuclear Information System (INIS)

    Hong, Y.-Y.; Tsai, S.-W.; Weng, M.-T.

    2001-01-01

    A bidding strategy using a fuzzy-c-mean (FCM) algorithm and the artificial neural network (ANN) was developed for competitive electric markets. The nodal price information was assumed to be released into the market. The FCM was used, first, to classify the daily load pattern into peak, medium-peak and off-peak levels and, secondly, to classify the competitive generation companies (gencos) into less-menacing, possible-menacing and menacing gencos. The back-propagation ANN was used for determining the bidding price for a genco. The FCM results aided in lessening the training data and reducing the ANN input nodes. The IEEE 30-busbar system was used for illustrating the applicability of the proposed method. (Author)

  15. Bidding strategy based on artificial intelligence for a competitive electric market

    Energy Technology Data Exchange (ETDEWEB)

    Hong, Y.-Y.; Tsai, S.-W.; Weng, M.-T. [Chung Yuan Univ., Dept. of Electrical Engineering, Chung Li (China)

    2001-03-01

    A bidding strategy using a fuzzy-c-mean (FCM) algorithm and the artificial neural network (ANN) was developed for competitive electric markets. The nodal price information was assumed to be released into the market. The FCM was used, first, to classify the daily load pattern into peak, medium-peak and off-peak levels and, secondly, to classify the competitive generation companies (gencos) into less-menacing, possible-menacing and menacing gencos. The back-propagation ANN was used for determining the bidding price for a genco. The FCM results aided in lessening the training data and reducing the ANN input nodes. The IEEE 30-busbar system was used for illustrating the applicability of the proposed method. (Author)

  16. The Third Age of Artificial Intelligence

    OpenAIRE

    Miailhe, Nicolas; Hodes, Cyrus

    2018-01-01

    If the definitional boundaries of Artificial Intelligence (AI) remains contested, experts agree that we are witnessing a revolution. “Is this time different?” is the question that they worryingly argue over when they analyze the socio-economic impact of the AI revolution as compared with the other industrial revolutions of the 19th and 20th centuries. This Schumpeterian wave may prove to be a creative destruction raising incomes, enhancing quality of life for all and generating previously uni...

  17. Generation of Fullspan Leading-Edge 3D Ice Shapes for Swept-Wing Aerodynamic Testing

    Science.gov (United States)

    Camello, Stephanie C.; Lee, Sam; Lum, Christopher; Bragg, Michael B.

    2016-01-01

    The deleterious effect of ice accretion on aircraft is often assessed through dry-air flight and wind tunnel testing with artificial ice shapes. This paper describes a method to create fullspan swept-wing artificial ice shapes from partial span ice segments acquired in the NASA Glenn Icing Reserch Tunnel for aerodynamic wind-tunnel testing. Full-scale ice accretion segments were laser scanned from the Inboard, Midspan, and Outboard wing station models of the 65% scale Common Research Model (CRM65) aircraft configuration. These were interpolated and extrapolated using a weighted averaging method to generate fullspan ice shapes from the root to the tip of the CRM65 wing. The results showed that this interpolation method was able to preserve many of the highly three dimensional features typically found on swept-wing ice accretions. The interpolated fullspan ice shapes were then scaled to fit the leading edge of a 8.9% scale version of the CRM65 wing for aerodynamic wind-tunnel testing. Reduced fidelity versions of the fullspan ice shapes were also created where most of the local three-dimensional features were removed. The fullspan artificial ice shapes and the reduced fidelity versions were manufactured using stereolithography.

  18. Medical applications of membranes: Drug delivery, artificial organs and tissue engineering

    NARCIS (Netherlands)

    Stamatialis, Dimitrios; Papenburg, B.J.; Girones nogue, Miriam; Saiful, S.; Bettahalli Narasimha, M.S.; Schmitmeier, Stephanie; Wessling, Matthias

    2008-01-01

    This paper covers the main medical applications of artificial membranes. Specific attention is given to drug delivery systems, artificial organs and tissue engineering which seem to dominate the interest of the membrane community this period. In all cases, the materials, methods and the current

  19. A method for generating subgroup parameters from resonance tables

    International Nuclear Information System (INIS)

    Devan, K.; Mohanakrishnan, P.

    1993-01-01

    A method for generating subgroup or band parameters from resonance tables is described. A computer code SPART was written using this method. This code generates the subgroup parameters for any number of bands within the specified broad groups at different temperatures by reading the required input data from the binary cross section library in the Cadarache format. The results obtained with SPART code for two bands were compared with that obtained from GROUPIE code and a good agreement was obtained. Results of the generation of subgroup parameters in four bands for sample case of 239 Pu from resonance tables of Cadarache Ver.2 library is also presented. (author). 8 refs., 2 tabs

  20. Artificial immune system algorithm in VLSI circuit configuration

    Science.gov (United States)

    Mansor, Mohd. Asyraf; Sathasivam, Saratha; Kasihmuddin, Mohd Shareduwan Mohd

    2017-08-01

    In artificial intelligence, the artificial immune system is a robust bio-inspired heuristic method, extensively used in solving many constraint optimization problems, anomaly detection, and pattern recognition. This paper discusses the implementation and performance of artificial immune system (AIS) algorithm integrated with Hopfield neural networks for VLSI circuit configuration based on 3-Satisfiability problems. Specifically, we emphasized on the clonal selection technique in our binary artificial immune system algorithm. We restrict our logic construction to 3-Satisfiability (3-SAT) clauses in order to outfit with the transistor configuration in VLSI circuit. The core impetus of this research is to find an ideal hybrid model to assist in the VLSI circuit configuration. In this paper, we compared the artificial immune system (AIS) algorithm (HNN-3SATAIS) with the brute force algorithm incorporated with Hopfield neural network (HNN-3SATBF). Microsoft Visual C++ 2013 was used as a platform for training, simulating and validating the performances of the proposed network. The results depict that the HNN-3SATAIS outperformed HNN-3SATBF in terms of circuit accuracy and CPU time. Thus, HNN-3SATAIS can be used to detect an early error in the VLSI circuit design.

  1. Glytube: a conical tube and parafilm M-based method as a simplified device to artificially blood-feed the dengue vector mosquito, Aedes aegypti.

    Directory of Open Access Journals (Sweden)

    André Luis Costa-da-Silva

    Full Text Available Aedes aegypti, the main vector of dengue virus, requires a blood meal to produce eggs. Although live animals are still the main blood source for laboratory colonies, many artificial feeders are available. These feeders are also the best method for experimental oral infection of Ae. aegypti with Dengue viruses. However, most of them are expensive or laborious to construct. Based on principle of Rutledge-type feeder, a conventional conical tube, glycerol and Parafilm-M were used to develop a simple in-house feeder device. The blood feeding efficiency of this apparatus was compared to a live blood source, mice, and no significant differences (p = 0.1189 were observed between artificial-fed (51.3% of engorgement and mice-fed groups (40.6%. Thus, an easy to assemble and cost-effective artificial feeder, designated "Glytube" was developed in this report. This simple and efficient feeding device can be built with common laboratory materials for research on Ae. aegypti.

  2. Artificial neural Network-Based modeling and monitoring of photovoltaic generator

    Directory of Open Access Journals (Sweden)

    H. MEKKI

    2015-03-01

    Full Text Available In this paper, an artificial neural network based-model (ANNBM is introduced for partial shading detection losses in photovoltaic (PV panel. A Multilayer Perceptron (MLP is used to estimate the electrical outputs (current and voltage of the photovoltaic module using the external meteorological data: solar irradiation G (W/m2 and the module temperature T (°C. Firstly, a database of the BP150SX photovoltaic module operating without any defect has been used to train the considered MLP. Subsequently, in the first case of this study, the developed model is used to estimate the output current and voltage of the PV module considering the partial shading effect. Results confirm the good ability of the ANNBM to detect the partial shading effect in the photovoltaic module with logical accuracy. The proposed strategy could also be used for the online monitoring and supervision of PV modules.

  3. Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data.

    Science.gov (United States)

    Ching, Travers; Zhu, Xun; Garmire, Lana X

    2018-04-01

    Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been applied to biomedical fields such as imaging analysis and diagnosis. We have developed a new ANN framework called Cox-nnet to predict patient prognosis from high throughput transcriptomics data. In 10 TCGA RNA-Seq data sets, Cox-nnet achieves the same or better predictive accuracy compared to other methods, including Cox-proportional hazards regression (with LASSO, ridge, and mimimax concave penalty), Random Forests Survival and CoxBoost. Cox-nnet also reveals richer biological information, at both the pathway and gene levels. The outputs from the hidden layer node provide an alternative approach for survival-sensitive dimension reduction. In summary, we have developed a new method for accurate and efficient prognosis prediction on high throughput data, with functional biological insights. The source code is freely available at https://github.com/lanagarmire/cox-nnet.

  4. Artificial intelligence approach to accelerator control systems

    International Nuclear Information System (INIS)

    Schultz, D.E.; Hurd, J.W.; Brown, S.K.

    1987-01-01

    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

  5. FY1995 new technology of artificial organ materials which can induce host biocompatibility; 1995 nendo jinko zokiyo seitai kino fukatsukagata sozai no kaihatsu gijutsu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-12-01

    The aim of this project is to produce a highly biocompatible materials for next generation's artificial organs using the following methods: 1, Micromodification of polymer materials. 2, Biocompatible treatment for biological materials. 3, Application of bioabsorbable materials. 4, Bioactive substance immobilization. and 5, Use of autologous tissue as artificial organ materials. As a synthetic polymer material, microporous polyurethane was used for a small diameter vascular prosthesis. The graft with this technology was successfully implanted in rat abdomical aortic position. The graft of 1.5 mm in internal diameter and 10cm in length showed excellent patency with nice endothelialisation. As a biological material, microfibers of collagen was used for a sealing substance of vascular prothesis. The microfibers absorbed a large amount of water, which could prevent blood leakage from the graft wall. The graft showed non-thrombogenic property and excellent host cell affinity, resulted in rapid neointima formation. As to autologous tissue, bone marrow was used, since marrow cells can differentiate into any mesenchimal cells with synthesis of growth factors. Marrow cell transplanted vascular prothesis showed rapid capillary ingrowth. These results indicated that the newly designed materials had suitable properties for materials of next generation's artificial organs. (NEDO)

  6. FY1995 new technology of artificial organ materials which can induce host biocompatibility; 1995 nendo jinko zokiyo seitai kino fukatsukagata sozai no kaihatsu gijutsu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-05-01

    The aim of this project is to produce a highly biocompatible materials for next generation's artificial organs using the following methods: 1, Micromodification of polymer materials. 2, Biocompatible treatment for biological materials. 3, Application of bioabsorbable materials. 4, Bioactive substance immobilization. and 5, Use of autologous tissue as artificial organ materials. As a synthetic polymer material, microporous polyurethane was used for a small diameter vascular prosthesis. The graft with this technology was successfully implanted in rat abdomical aortic position. The graft of 1.5 mm in internal diameter and 10 cm in length showed excellent patency with nice endothelialisation. As a biological material, microfibers of collagen was used for a sealing substance of vascular prothesis. The microfibers absorbed a large amount of water, which could prevent blood leakage from the graft wall. The graft showed non-thrombogenic property and excellent host cell affinity, resulted in rapid neointima formation. As to autologous tissue, bone marrow was used, since marrow cells can differentiate into any mesenchimal cells with synthesis of growth factors. Marrow cell transplanted vascular prothesis showed rapid capillary ingrowth. These results indicated that the newly designed materials had suitable properties for materials of next generation's artificial organs. (NEDO)

  7. A Simple and Efficient Artificial Bee Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Yunfeng Xu

    2013-01-01

    Full Text Available Artificial bee colony (ABC is a new population-based stochastic algorithm which has shown good search abilities on many optimization problems. However, the original ABC shows slow convergence speed during the search process. In order to enhance the performance of ABC, this paper proposes a new artificial bee colony (NABC algorithm, which modifies the search pattern of both employed and onlooker bees. A solution pool is constructed by storing some best solutions of the current swarm. New candidate solutions are generated by searching the neighborhood of solutions randomly chosen from the solution pool. Experiments are conducted on a set of twelve benchmark functions. Simulation results show that our approach is significantly better or at least comparable to the original ABC and seven other stochastic algorithms.

  8. New model for prediction binary mixture of antihistamine decongestant using artificial neural networks and least squares support vector machine by spectrophotometry method

    Science.gov (United States)

    Mofavvaz, Shirin; Sohrabi, Mahmoud Reza; Nezamzadeh-Ejhieh, Alireza

    2017-07-01

    In the present study, artificial neural networks (ANNs) and least squares support vector machines (LS-SVM) as intelligent methods based on absorption spectra in the range of 230-300 nm have been used for determination of antihistamine decongestant contents. In the first step, one type of network (feed-forward back-propagation) from the artificial neural network with two different training algorithms, Levenberg-Marquardt (LM) and gradient descent with momentum and adaptive learning rate back-propagation (GDX) algorithm, were employed and their performance was evaluated. The performance of the LM algorithm was better than the GDX algorithm. In the second one, the radial basis network was utilized and results compared with the previous network. In the last one, the other intelligent method named least squares support vector machine was proposed to construct the antihistamine decongestant prediction model and the results were compared with two of the aforementioned networks. The values of the statistical parameters mean square error (MSE), Regression coefficient (R2), correlation coefficient (r) and also mean recovery (%), relative standard deviation (RSD) used for selecting the best model between these methods. Moreover, the proposed methods were compared to the high- performance liquid chromatography (HPLC) as a reference method. One way analysis of variance (ANOVA) test at the 95% confidence level applied to the comparison results of suggested and reference methods that there were no significant differences between them.

  9. Application of artificial tactile sensing approach in kidney-stone-removal laparoscopy.

    Science.gov (United States)

    Afshari, Elnaz; Najarian, Siamak; Simforoosh, Nasser

    2010-01-01

    Artificial tactile sensing is a novel method for obtaining different characteristics of a hard object embedded in a soft tissue. In this regard, artificial palpation is one of the most valuable achievements of artificial tactile sensing that can be used in various fields of medicine and more specifically in surgery. In this study, considering the present problems and limitations in kidney-stone-removal laparoscopy, a new application will be presented for artificial tactile sensing approach. Having imitated surgeon's palpation during open surgery and modeled it conceptually, indications of stone existence that appear on the surface of kidney (due to exerting mechanical load) were determined. A number of different cases were created and solved by the software. Using stress distribution contours and stress graphs, it is illustrated that the created stress patterns on the surface of kidney not only show the existence of stone inside, but also its exact location. In fact, the reliability and accuracy of artificial tactile sensing method in detection of kidney stone during laparoscopy is demonstrated by means of finite element analysis. Also, in this paper, the functional principles of tactile system capable of determining the exact location of stone during laparoscopy will be presented.

  10. Artificial sweeteners

    DEFF Research Database (Denmark)

    Raben, Anne Birgitte; Richelsen, Bjørn

    2012-01-01

    Artificial sweeteners can be a helpful tool to reduce energy intake and body weight and thereby risk for diabetes and cardiovascular diseases (CVD). Considering the prevailing diabesity (obesity and diabetes) epidemic, this can, therefore, be an important alternative to natural, calorie-containin......Artificial sweeteners can be a helpful tool to reduce energy intake and body weight and thereby risk for diabetes and cardiovascular diseases (CVD). Considering the prevailing diabesity (obesity and diabetes) epidemic, this can, therefore, be an important alternative to natural, calorie......-containing sweeteners. The purpose of this review is to summarize the current evidence on the effect of artificial sweeteners on body weight, appetite, and risk markers for diabetes and CVD in humans....

  11. Application of artificial neural network for heat transfer in porous cone

    Science.gov (United States)

    Athani, Abdulgaphur; Ahamad, N. Ameer; Badruddin, Irfan Anjum

    2018-05-01

    Heat transfer in porous medium is one of the classical areas of research that has been active for many decades. The heat transfer in porous medium is generally studied by using numerical methods such as finite element method; finite difference method etc. that solves coupled partial differential equations by converting them into simpler forms. The current work utilizes an alternate method known as artificial neural network that mimics the learning characteristics of neurons. The heat transfer in porous medium fixed in a cone is predicted using backpropagation neural network. The artificial neural network is able to predict this behavior quite accurately.

  12. Westinghouse use of artificial intelligence in signal interpretation

    International Nuclear Information System (INIS)

    Mark, R.H.

    1984-01-01

    This paper discusses Westinghouse's use of artificial intelligence to assist inspectors who routinely monitor the thousands of tubes in nuclear steam generators. Using the AI technology has made the inspection process easier to learn and to apply. The system uses pattern recognition to identify off-normal conditions. As part of the in-service inspection program for nuclear power reactors, utilities make a practice of inspecting the condition of the large heat exchangers that produce the steam that turns the electric turbine generator. The same data are presented for inspection using form, motion, and color to call attention to off-normal signal patterns

  13. QUESTION ANSWERING SYSTEM BERBASIS ARTIFICIAL INTELLIGENCE MARKUP LANGUAGE SEBAGAI MEDIA INFORMASI

    Directory of Open Access Journals (Sweden)

    Fajrin Azwary

    2016-04-01

    Full Text Available Artificial intelligence technology nowadays, can be processed with a variety of forms, such as chatbot, and the various methods, one of them using Artificial Intelligence Markup Language (AIML. AIML using template matching, by comparing the specific patterns in the database. AIML template design process begins with determining the necessary information, then formed into questions, these questions adapted to AIML pattern. From the results of the study, can be known that the Question-Answering System in the chatbot using Artificial Intelligence Markup Language are able to communicate and deliver information. Keywords: Artificial Intelligence, Template Matching, Artificial Intelligence Markup Language, AIML Teknologi kecerdasan buatan saat ini dapat diolah dengan berbagai macam bentuk, seperti ChatBot, dan berbagai macam metode, salah satunya menggunakan Artificial Intelligence Markup Language (AIML. AIML menggunakan metode template matching yaitu dengan membandingkan pola-pola tertentu pada database. Proses perancangan template AIML diawali dengan menentukan informasi yang diperlukan, kemudian dibentuk menjadi pertanyaan, pertanyaan tersebut disesuaikan dengan bentuk pattern AIML. Hasil penelitian dapat diperoleh bahwa Question-Answering System dalam bentuk ChatBot menggunakan Artificial Intelligence Markup Language dapat berkomunikasi dan menyampaikan informasi. Kata kunci : Kecerdasan Buatan, Pencocokan Pola, Artificial Intelligence Markup Language, AIML

  14. Applying artificial intelligence technology to support decision-making in nursing: A case study in Taiwan.

    Science.gov (United States)

    Liao, Pei-Hung; Hsu, Pei-Ti; Chu, William; Chu, Woei-Chyn

    2015-06-01

    This study applied artificial intelligence to help nurses address problems and receive instructions through information technology. Nurses make diagnoses according to professional knowledge, clinical experience, and even instinct. Without comprehensive knowledge and thinking, diagnostic accuracy can be compromised and decisions may be delayed. We used a back-propagation neural network and other tools for data mining and statistical analysis. We further compared the prediction accuracy of the previous methods with an adaptive-network-based fuzzy inference system and the back-propagation neural network, identifying differences in the questions and in nurse satisfaction levels before and after using the nursing information system. This study investigated the use of artificial intelligence to generate nursing diagnoses. The percentage of agreement between diagnoses suggested by the information system and those made by nurses was as much as 87 percent. When patients are hospitalized, we can calculate the probability of various nursing diagnoses based on certain characteristics. © The Author(s) 2013.

  15. Bio-accessibility and Risk of Exposure to Metals and SVOCs in Artificial Turf Field Fill Materials and Fibers

    Science.gov (United States)

    Pavilonis, Brian T.; Weisel, Clifford P.; Buckley, Brian; Lioy, Paul J.

    2014-01-01

    To reduce maintenance costs, municipalities and schools are starting to replace natural grass fields with a new generation synthetic turf. Unlike Astro-Turf, which was first introduced in the 1960’s, synthetic field turf provides more cushioning to athletes. Part of this cushioning comes from materials like crumb rubber infill, which is manufactured from recycled tires and may contain a variety of chemicals. The goal of this study was to evaluate potential exposures from playing on artificial turf fields and associated risks to trace metals, semivolatile organic compounds (SVOCs), and polycyclic aromatic hydrocarbons (PAHs) by examining typical artificial turf fibers (n=8), different types of infill (n=8), and samples from actual fields (n=7). Three artificial biofluids were prepared which included: lung, sweat, and digestive fluids. Artificial biofluids were hypothesized to yield a more representative estimation of dose than the levels obtained from total extraction methods. PAHs were routinely below the limit of detection across all three biofluids precluding completion of a meaningful risk assessment. No SVOCs were identified at quantifiable levels in any extracts based on a match of their mass spectrum to compounds that are regulated in soil. The metals were measurable but at concentrations for which human health risk was estimated to be low. The study demonstrated that for the products and fields we tested, exposure to infill and artificial turf was generally considered de minimus, with the possible exception of lead for some fields and materials. PMID:23758133

  16. Artificial cognition architectures

    CERN Document Server

    Crowder, James A; Friess, Shelli A

    2013-01-01

    The goal of this book is to establish the foundation, principles, theory, and concepts that are the backbone of real, autonomous Artificial Intelligence. Presented here are some basic human intelligence concepts framed for Artificial Intelligence systems. These include concepts like Metacognition and Metamemory, along with architectural constructs for Artificial Intelligence versions of human brain functions like the prefrontal cortex. Also presented are possible hardware and software architectures that lend themselves to learning, reasoning, and self-evolution

  17. Laser Doppler Vibrometer Based Examination of the Efficiency of Introducing Artificial Delaminations into Composite Shells

    Directory of Open Access Journals (Sweden)

    Kustroń Kamila

    2015-09-01

    Full Text Available During its operation, the laminate shell of the watercraft hull can be exposed to local stability losses caused by the appearance and development of delaminations. The sources of these delaminations are discontinuities, created both in the production process and as a result of bumps of foreign bodies into the hull in operation. In the environment of fatigue loads acting on the hull, the delaminations propagate and lead to the loss of load capacity of the hull structure. There is a need to improve diagnostic systems used in Structural Health Monitoring (SHM of laminate hull elements to detect and monitor the development of the delaminations. Effective diagnostic systems used for delamination assessment base on expert systems. Along with other tools, the expert diagnostic advisory systems make use of the non-destructive examination method which consists in generating elastic waves in the hull shell structure and observing their changes by comparing the recorded signal with damage patterns collected in the expert system database. This system requires introducing certain patterns to its knowledge base, based on the results of experimental examinations performed on specimens with implemented artificial delaminations. The article presents the results of the examination oriented on assessing the delaminations artificially generated in the structure of glass- and carbon-epoxy laminates by introducing local non-adhesive layers with the aid of thin polyethylene film, teflon insert, or thin layer of polyvinyl alcohol. The efficiency of each method was assessed using laser vibrometry. The effect of the depth of delamination position in the laminate on the efficiency of the applied method is documented as well.

  18. Pressurized liquid extraction-gas chromatography-mass spectrometry for confirming the photo-induced generation of dioxin-like derivatives and other cosmetic preservative photoproducts on artificial skin.

    Science.gov (United States)

    Alvarez-Rivera, Gerardo; Llompart, Maria; Garcia-Jares, Carmen; Lores, Marta

    2016-04-01

    The stability and photochemical transformations of cosmetic preservatives in topical applications exposed to UV-light is a serious but poorly understood problem. In this study, a high throughput extraction and selective method based on pressurized liquid extraction (PLE) coupled to gas chromatography-mass spectrometry (GC-MS) was validated and applied to investigate the photochemical transformation of the antioxidant butylated hydroxytoluene (BHT), as well as the antimicrobials triclosan (TCS) and phenyl benzoate (PhBz) in an artificial skin model. Two sets of photodegradation experiments were performed: (i) UV-Irradiation (8W, 254nm) of artificial skin directly spiked with the target preservatives, and (ii) UV-irradiation of artificial skin after the application of a cosmetic cream fortified with the target compounds. After irradiation, PLE was used to isolate the target preservatives and their transformation products. The follow-up of the photodegradation kinetics of the parent preservatives, the identification of the arising by-products, and the monitorization of their kinetic profiles was performed by GC-MS. The photochemical transformation of triclosan into 2,8-dichloro-dibenzo-p-dioxin (2,8-DCDD) and other dioxin-like photoproducts has been confirmed in this work. Furthermore, seven BHT photoproducts, and three benzophenones as PhBz by-products, have been also identified. These findings reveal the first evidences of cosmetic ingredients phototransformation into unwanted photoproducts on an artificial skin model. Copyright © 2016 Elsevier B.V. All rights reserved.

  19. The method in γ spectrum analysis with artificial neural network based on MATLAB

    International Nuclear Information System (INIS)

    Bai Lixin; Zhang Yiyun; Xu Jiayun; Wu Liping

    2003-01-01

    Analyzing γ spectrum with artificial neural network have the advantage of using the information of whole spectrum and having high analyzing precision. A convenient realization based on MATLAB was present in this

  20. Artificial Enzymes, "Chemzymes"

    DEFF Research Database (Denmark)

    Bjerre, Jeannette; Rousseau, Cyril Andre Raphaël; Pedersen, Lavinia Georgeta M

    2008-01-01

    Enzymes have fascinated scientists since their discovery and, over some decades, one aim in organic chemistry has been the creation of molecules that mimic the active sites of enzymes and promote catalysis. Nevertheless, even today, there are relatively few examples of enzyme models that successf......Enzymes have fascinated scientists since their discovery and, over some decades, one aim in organic chemistry has been the creation of molecules that mimic the active sites of enzymes and promote catalysis. Nevertheless, even today, there are relatively few examples of enzyme models...... that successfully perform Michaelis-Menten catalysis under enzymatic conditions (i.e., aqueous medium, neutral pH, ambient temperature) and for those that do, very high rate accelerations are seldomly seen. This review will provide a brief summary of the recent developments in artificial enzymes, so called...... "Chemzymes", based on cyclodextrins and other molecules. Only the chemzymes that have shown enzyme-like activity that has been quantified by different methods will be mentioned. This review will summarize the work done in the field of artificial glycosidases, oxidases, epoxidases, and esterases, as well...

  1. Evaluation of methods used for the direct generation of response spectra

    International Nuclear Information System (INIS)

    Mayers, R.L.; Muraki, T.; Jones, L.R.; Donikian, R.

    1983-01-01

    The paper presents an alternate methodology by which seismic in-structure response spectra may be generated directly from either ground or floor excitation spectra. The method is based upon stochastic concepts and utilizes the modal superposition solution. The philosophy of the method is based upon the notion that the evaluation of 'peak' response in uncertain excitation environments is only meaningful in a probabilistic sense. This interpretation of response spectra facilitates the generation of in-structure spectra for any non-exceedance probability (NEP). The method is validated by comparisons with a set of deterministic time-history analyses with three example models: an eleven-story building model, a containment structure stick model, and a floor mounted control panel, subjected to ten input spectrum compatible acceleration time-histories. A significant finding resulting from these examples is that the time-history method portrayed substantial variation in the resulting in-structure spectra, and therefore is unreliable for the generation of spectra. It is shown that the average of the time-history generated spectra can be estimated by the direct generation procedure, and reliable spectra may be generated for 85 NEP levels. The methodology presented herein is shown to be valid for both primary and secondary systems. Also included in the paper, is a review of the stochastic methods proposed by Singh and Der Kiureghian et. al., and the Fourier transform method proposed by Scanlan et al. (orig./HP)

  2. A critical review and analysis of ethical issues associated with the artificial pancreas.

    Science.gov (United States)

    Quintal, A; Messier, V; Rabasa-Lhoret, R; Racine, E

    2018-04-25

    The artificial pancreas combines a hormone infusion pump with a continuous glucose monitoring device, supported by a dosing algorithm currently installed on the pump. It allows for dynamic infusions of insulin (and possibly other hormones such as glucagon) tailored to patient needs. For patients with type 1 diabetes the artificial pancreas has been shown to prevent more effectively hypoglycaemic events and hyperglycaemia than insulin pump therapy and has the potential to simplify care. However, the potential ethical issues associated with the upcoming integration of the artificial pancreas into clinical practice have not yet been discussed. Our objective was to identify and articulate ethical issues associated with artificial pancreas use for patients, healthcare professionals, industry and policymakers. We performed a literature review to identify clinical, psychosocial and technical issues raised by the artificial pancreas and subsequently analysed them through a common bioethics framework. We identified five sensitive domains of ethical issues. Patient confidentiality and safety can be jeopardized by the artificial pancreas' vulnerability to security breaches or unauthorized data sharing. Public and private coverage of the artificial pancreas could be cost-effective and warranted. Patient selection criteria need to ensure equitable access and sensitivity to patient-reported outcomes. Patient coaching and support by healthcare professionals or industry representatives could help foster realistic expectations in patients. Finally, the artificial pancreas increases the visibility of diabetes and could generate issues related to personal identity and patient agency. The timely consideration of these issues will optimize the technological development and clinical uptake of the artificial pancreas. Copyright © 2018. Published by Elsevier Masson SAS.

  3. Generating Artificial Plant Morphologies for Function and Aesthetics through Evolving L-Systems

    DEFF Research Database (Denmark)

    Veenstra, Frank; Faina, Andres; Støy, Kasper

    2016-01-01

    Due to the replacement of natural flora and fauna with ur- ban environments, a significant part of the earth’s organisms that function as primary consumers have been dispelled. To compensate for the reduction in the amount of primary con- sumers, robotic systems that mimic plant-like organisms...... are interesting to mimic for their potential functional and aes- thetic value in urban environments. To investigate how to utilize plant developmental strategies in order to engender ur- ban artificial plants, we built a simple evolutionary model that applies an L-System based grammar as an abstraction of plant...

  4. Method to implement the CCD timing generator based on FPGA

    Science.gov (United States)

    Li, Binhua; Song, Qian; He, Chun; Jin, Jianhui; He, Lin

    2010-07-01

    With the advance of the PFPA technology, the design methodology of digital systems is changing. In recent years we develop a method to implement the CCD timing generator based on FPGA and VHDL. This paper presents the principles and implementation skills of the method. Taking a developed camera as an example, we introduce the structure, input and output clocks/signals of a timing generator implemented in the camera. The generator is composed of a top module and a bottom module. The bottom one is made up of 4 sub-modules which correspond to 4 different operation modes. The modules are implemented by 5 VHDL programs. Frame charts of the architecture of these programs are shown in the paper. We also describe implementation steps of the timing generator in Quartus II, and the interconnections between the generator and a Nios soft core processor which is the controller of this generator. Some test results are presented in the end.

  5. Spatial interpolation and radiological mapping of ambient gamma dose rate by using artificial neural networks and fuzzy logic methods.

    Science.gov (United States)

    Yeşilkanat, Cafer Mert; Kobya, Yaşar; Taşkın, Halim; Çevik, Uğur

    2017-09-01

    The aim of this study was to determine spatial risk dispersion of ambient gamma dose rate (AGDR) by using both artificial neural network (ANN) and fuzzy logic (FL) methods, compare the performances of methods, make dose estimations for intermediate stations with no previous measurements and create dose rate risk maps of the study area. In order to determine the dose distribution by using artificial neural networks, two main networks and five different network structures were used; feed forward ANN; Multi-layer perceptron (MLP), Radial basis functional neural network (RBFNN), Quantile regression neural network (QRNN) and recurrent ANN; Jordan networks (JN), Elman networks (EN). In the evaluation of estimation performance obtained for the test data, all models appear to give similar results. According to the cross-validation results obtained for explaining AGDR distribution, Pearson's r coefficients were calculated as 0.94, 0.91, 0.89, 0.91, 0.91 and 0.92 and RMSE values were calculated as 34.78, 43.28, 63.92, 44.86, 46.77 and 37.92 for MLP, RBFNN, QRNN, JN, EN and FL, respectively. In addition, spatial risk maps showing distributions of AGDR of the study area were created by all models and results were compared with geological, topological and soil structure. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Cognitive logical systems with artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Liss, E

    1983-09-01

    The simulation of cognitive processes for the purpose of the technical development of learning systems with intelligent behavior is a basic object of the young interdisciplinary cognition science which is based upon artificial intelligence, cognitive psychology, computer science, linguistics and pedagogics. Cognitive systems may be described as knowledge-based logical systems. Based on structural and functional principles of intelligent automata and elementary information processing systems with structural learning capability the future process, machine and robot controls, advising units and fifth generation computers may be developed.

  7. Automated bony region identification using artificial neural networks: reliability and validation measurements

    International Nuclear Information System (INIS)

    Gassman, Esther E.; Kallemeyn, Nicole A.; DeVries, Nicole A.; Shivanna, Kiran H.; Powell, Stephanie M.; Magnotta, Vincent A.; Ramme, Austin J.; Adams, Brian D.; Grosland, Nicole M.

    2008-01-01

    The objective was to develop tools for automating the identification of bony structures, to assess the reliability of this technique against manual raters, and to validate the resulting regions of interest against physical surface scans obtained from the same specimen. Artificial intelligence-based algorithms have been used for image segmentation, specifically artificial neural networks (ANNs). For this study, an ANN was created and trained to identify the phalanges of the human hand. The relative overlap between the ANN and a manual tracer was 0.87, 0.82, and 0.76, for the proximal, middle, and distal index phalanx bones respectively. Compared with the physical surface scans, the ANN-generated surface representations differed on average by 0.35 mm, 0.29 mm, and 0.40 mm for the proximal, middle, and distal phalanges respectively. Furthermore, the ANN proved to segment the structures in less than one-tenth of the time required by a manual rater. The ANN has proven to be a reliable and valid means of segmenting the phalanx bones from CT images. Employing automated methods such as the ANN for segmentation, eliminates the likelihood of rater drift and inter-rater variability. Automated methods also decrease the amount of time and manual effort required to extract the data of interest, thereby making the feasibility of patient-specific modeling a reality. (orig.)

  8. Automated bony region identification using artificial neural networks: reliability and validation measurements

    Energy Technology Data Exchange (ETDEWEB)

    Gassman, Esther E.; Kallemeyn, Nicole A.; DeVries, Nicole A.; Shivanna, Kiran H. [The University of Iowa, Department of Biomedical Engineering, Seamans Center for the Engineering Arts and Sciences, Iowa City, IA (United States); The University of Iowa, Center for Computer-Aided Design, Iowa City, IA (United States); Powell, Stephanie M. [The University of Iowa, Department of Biomedical Engineering, Seamans Center for the Engineering Arts and Sciences, Iowa City, IA (United States); University of Iowa Hospitals and Clinics, The University of Iowa, Department of Radiology, Iowa City, IA (United States); Magnotta, Vincent A. [The University of Iowa, Department of Biomedical Engineering, Seamans Center for the Engineering Arts and Sciences, Iowa City, IA (United States); The University of Iowa, Center for Computer-Aided Design, Iowa City, IA (United States); University of Iowa Hospitals and Clinics, The University of Iowa, Department of Radiology, Iowa City, IA (United States); Ramme, Austin J. [University of Iowa Hospitals and Clinics, The University of Iowa, Department of Radiology, Iowa City, IA (United States); Adams, Brian D. [The University of Iowa, Department of Biomedical Engineering, Seamans Center for the Engineering Arts and Sciences, Iowa City, IA (United States); University of Iowa Hospitals and Clinics, The University of Iowa, Department of Orthopaedics and Rehabilitation, Iowa City, IA (United States); Grosland, Nicole M. [The University of Iowa, Department of Biomedical Engineering, Seamans Center for the Engineering Arts and Sciences, Iowa City, IA (United States); University of Iowa Hospitals and Clinics, The University of Iowa, Department of Orthopaedics and Rehabilitation, Iowa City, IA (United States); The University of Iowa, Center for Computer-Aided Design, Iowa City, IA (United States)

    2008-04-15

    The objective was to develop tools for automating the identification of bony structures, to assess the reliability of this technique against manual raters, and to validate the resulting regions of interest against physical surface scans obtained from the same specimen. Artificial intelligence-based algorithms have been used for image segmentation, specifically artificial neural networks (ANNs). For this study, an ANN was created and trained to identify the phalanges of the human hand. The relative overlap between the ANN and a manual tracer was 0.87, 0.82, and 0.76, for the proximal, middle, and distal index phalanx bones respectively. Compared with the physical surface scans, the ANN-generated surface representations differed on average by 0.35 mm, 0.29 mm, and 0.40 mm for the proximal, middle, and distal phalanges respectively. Furthermore, the ANN proved to segment the structures in less than one-tenth of the time required by a manual rater. The ANN has proven to be a reliable and valid means of segmenting the phalanx bones from CT images. Employing automated methods such as the ANN for segmentation, eliminates the likelihood of rater drift and inter-rater variability. Automated methods also decrease the amount of time and manual effort required to extract the data of interest, thereby making the feasibility of patient-specific modeling a reality. (orig.)

  9. Personalizes lung motion simulation fore external radiotherapy using an artificial neural network

    International Nuclear Information System (INIS)

    Laurent, R.

    2011-01-01

    The development of new techniques in the field of external radiotherapy opens new ways of gaining accuracy in dose distribution, in particular through the knowledge of individual lung motion. The numeric simulation NEMOSIS (Neural Network Motion Simulation System) we describe is based on artificial neural networks (ANN) and allows, in addition to determining motion in a personalized way, to reduce the necessary initial doses to determine it. In the first part, we will present current treatment options, lung motion as well as existing simulation or estimation methods. The second part describes the artificial neural network used and the steps for defining its parameters. An accurate evaluation of our approach was carried out on original patient data. The obtained results are compared with an existing motion estimated method. The extremely short computing time, in the range of milliseconds for the generation of one respiratory phase, would allow its use in clinical routine. Modifications to NEMOSIS in order to meet the requirements for its use in external radiotherapy are described, and a study of the motion of tumor outlines is carried out. This work lays the basis for lung motion simulation with ANNs and validates our approach. Its real time implementation coupled to its predication accuracy makes NEMOSIS promising tool for the simulation of motion synchronized with breathing. (author)

  10. Induction of genomic instability and activation of autophagy in artificial human aneuploid cells

    Energy Technology Data Exchange (ETDEWEB)

    Ariyoshi, Kentaro [Hirosaki University, Institute of Radiation Emergency Medicine, 66-1 Hon-cho, Hirosaki 036-8564 (Japan); Miura, Tomisato; Kasai, Kosuke; Fujishima, Yohei [Department of Biomedical Sciences, Hirosaki University Graduate School of Health Sciences, 66-1 Hon-cho, Hirosaki 036-8564 (Japan); Oshimura, Mitsuo [Chromosome Engineering Research Center (CERC), Tottori University, Nishicho 86, Yonago, Tottori 683-8503 (Japan); Yoshida, Mitsuaki A., E-mail: ariyoshi@hirosaki-u.ac.jp [Hirosaki University, Institute of Radiation Emergency Medicine, 66-1 Hon-cho, Hirosaki 036-8564 (Japan)

    2016-08-15

    Highlights: • Clones with artificial aneuploidy of chromosome 8 or chromosome 22 both show inhibited proliferation and genomic instability. • Increased autophagy was observed in the artificially aneuploid clones. • Inhibition of autophagy resulted in increased genomic instability and DNA damage. • Intracellular levels of reactive oxygen species were up-regulated in the artificially aneuploid clones. - Abstract: Chromosome missegregation can lead to a change in chromosome number known as aneuploidy. Although aneuploidy is a known hallmark of cancer cells, the various mechanisms by which altered gene and/or DNA copy number facilitate tumorigenesis remain unclear. To understand the effect of aneuploidy occurring in non-tumorigenic human breast epithelial cells, we generated clones harboring artificial aneuploidy using microcell-mediated chromosome transfer. Our results demonstrate that clones with artificial aneuploidy of chromosome 8 or chromosome 22 both show inhibited proliferation and genomic instability. Also, the increased autophagy was observed in the artificially aneuploidy clones, and inhibition of autophagy resulted in increased genomic instability and DNA damage. In addition, the intracellular levels of reactive oxygen species were up-regulated in the artificially aneuploid clones, and inhibition of autophagy further increased the production of reactive oxygen species. Together, these results suggest that even a single extraneous chromosome can induce genomic instability, and that autophagy triggered by aneuploidy-induced stress is a mechanism to protect cells bearing abnormal chromosome number.

  11. Induction of genomic instability and activation of autophagy in artificial human aneuploid cells

    International Nuclear Information System (INIS)

    Ariyoshi, Kentaro; Miura, Tomisato; Kasai, Kosuke; Fujishima, Yohei; Oshimura, Mitsuo; Yoshida, Mitsuaki A.

    2016-01-01

    Highlights: • Clones with artificial aneuploidy of chromosome 8 or chromosome 22 both show inhibited proliferation and genomic instability. • Increased autophagy was observed in the artificially aneuploid clones. • Inhibition of autophagy resulted in increased genomic instability and DNA damage. • Intracellular levels of reactive oxygen species were up-regulated in the artificially aneuploid clones. - Abstract: Chromosome missegregation can lead to a change in chromosome number known as aneuploidy. Although aneuploidy is a known hallmark of cancer cells, the various mechanisms by which altered gene and/or DNA copy number facilitate tumorigenesis remain unclear. To understand the effect of aneuploidy occurring in non-tumorigenic human breast epithelial cells, we generated clones harboring artificial aneuploidy using microcell-mediated chromosome transfer. Our results demonstrate that clones with artificial aneuploidy of chromosome 8 or chromosome 22 both show inhibited proliferation and genomic instability. Also, the increased autophagy was observed in the artificially aneuploidy clones, and inhibition of autophagy resulted in increased genomic instability and DNA damage. In addition, the intracellular levels of reactive oxygen species were up-regulated in the artificially aneuploid clones, and inhibition of autophagy further increased the production of reactive oxygen species. Together, these results suggest that even a single extraneous chromosome can induce genomic instability, and that autophagy triggered by aneuploidy-induced stress is a mechanism to protect cells bearing abnormal chromosome number.

  12. Artificial Disc Replacement

    Science.gov (United States)

    ... Spondylolisthesis BLOG FIND A SPECIALIST Treatments Artificial Disc Replacement (ADR) Patient Education Committee Jamie Baisden The disc ... Disc An artificial disc (also called a disc replacement, disc prosthesis or spine arthroplasty device) is a ...

  13. [Artificial intelligence applied to radiation oncology].

    Science.gov (United States)

    Bibault, J-E; Burgun, A; Giraud, P

    2017-05-01

    Performing randomised comparative clinical trials in radiation oncology remains a challenge when new treatment modalities become available. One of the most recent examples is the lack of phase III trials demonstrating the superiority of intensity-modulated radiation therapy in most of its current indications. A new paradigm is developing that consists in the mining of large databases to answer clinical or translational issues. Beyond national databases (such as SEER or NCDB), that often lack the necessary level of details on the population studied or the treatments performed, electronic health records can be used to create detailed phenotypic profiles of any patients. In parallel, the Record-and-Verify Systems used in radiation oncology precisely document the planned and performed treatments. Artificial Intelligence and machine learning algorithms can be used to incrementally analyse these data in order to generate hypothesis to better personalize treatments. This review discusses how these methods have already been used in previous studies. Copyright © 2017 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

  14. Octopus-like suction cups: from natural to artificial solutions.

    Science.gov (United States)

    Tramacere, F; Follador, M; Pugno, N M; Mazzolai, B

    2015-05-13

    Octopus suckers are able to attach to all nonporous surfaces and generate a very strong attachment force. The well-known attachment features of this animal result from the softness of the sucker tissues and the surface morphology of the portion of the sucker that is in contact with objects or substrates. Unlike artificial suction cups, octopus suckers are characterized by a series of radial grooves that increase the area subjected to pressure reduction during attachment. In this study, we constructed artificial suction cups with different surface geometries and tested their attachment performances using a pull-off setup. First, smooth suction cups were obtained for casting; then, sucker surfaces were engraved with a laser cutter. As expected, for all the tested cases, the engraving treatment enhanced the attachment performance of the elastomeric suction cups compared with that of the smooth versions. Moreover, the results indicated that the surface geometry with the best attachment performance was the geometry most similar to octopus sucker morphology. The results obtained in this work can be utilized to design artificial suction cups with higher wet attachment performance.

  15. Use of artificial neural networks (computer analysis) in the diagnosis of microcalcifications on mammography

    International Nuclear Information System (INIS)

    Markopoulos, Christos; Kouskos, Efstratios; Koufopoulos, Konstantinos; Kyriakou, Vasiliki; Gogas, John

    2001-01-01

    Introduction/objective: the purpose of this study was to evaluate a computer based method for differentiating malignant from benign clustered microcalcifications, comparing it with the performance of three physicians. Methods and material: materials for the study are 240 suspicious microcalcifications on mammograms from 220 female patients who underwent breast biopsy, following hook wire localization under mammographic guidance. The histologic findings were malignant in 108 cases (45%) and benign in 132 cases (55%). Those clusters were analyzed by a computer program and eight features of the calcifications (density, number, area, brightness, diameter average, distance average, proximity average, perimeter compacity average) were quantitatively estimated by a specific artificial neural network. Human input was limited to initial identification of the calcifications. Three physicians-observers were also evaluated for the malignant or benign nature of the clustered microcalcifications. Results: the performance of the artificial network was evaluated by receiver operating characteristics (ROC) curves. ROC curves were also generated for the performance of each observer and for the three observers as a group. The ROC curves for the computer and for the physicians were compared and the results are:area under the curve (AUC) value for computer is 0.937, for physician-1 is 0.746, for physician-2 is 0.785, for physician-3 is 0.835 and for physicians as a group is 0.810. The results of the Student's t-test for paired data showed statistically significant difference between the artificial neural network and the physicians' performance, independently and as a group. Discussion and conclusion: our study showed that computer analysis achieves statistically significantly better performance than that of physicians in the classification of malignant and benign calcifications. This method, after further evaluation and improvement, may help radiologists and breast surgeons in better

  16. An Exploration into Integrating Daylight and Artificial Light via an Observational Instrument

    DEFF Research Database (Denmark)

    Petersen, Kjell Yngve; Søndergaard, Karin

    2015-01-01

    An Exploration into Integrating Daylight and Artificial Light via an Observational Instrument Daylight is dynamic and dependent upon weather conditions; unfolding with both subtle and dramatic variations in qualities of light. Through a building’s apertures, daylight creates a connection between...... abstract and blurred phenomena, these diffused luminous reflections rouse us into interactions with the world. In this book we are interested in identifying the qualitative parameters involved in the integration of dynamic artificial lighting and daylight; the latter being already highly dynamic by nature...... that examine how the dynamic artificial lighting in the observational instrument unfolds during the changing of the daylight situations that are generated by the weather outside. This research employs the concept of coupling between interior and exterior, in order to identify a spectrum of design parameters...

  17. Forecasting electricity market pricing using artificial neural networks

    International Nuclear Information System (INIS)

    Pao, Hsiao-Tien

    2007-01-01

    Electricity price forecasting is extremely important for all market players, in particular for generating companies: in the short term, they must set up bids for the spot market; in the medium term, they have to define contract policies; and in the long term, they must define their expansion plans. For forecasting long-term electricity market pricing, in order to avoid excessive round-off and prediction errors, this paper proposes a new artificial neural network (ANN) with single output node structure by using direct forecasting approach. The potentials of ANNs are investigated by employing a rolling cross validation scheme. Out of sample performance evaluated with three criteria across five forecasting horizons shows that the proposed ANNs are a more robust multi-step ahead forecasting method than autoregressive error models. Moreover, ANN predictions are quite accurate even when the length of the forecast horizon is relatively short or long

  18. Electrically controllable artificial PAN muscles

    Science.gov (United States)

    Salehpoor, Karim; Shahinpoor, Mohsen; Mojarrad, Mehran

    1996-02-01

    Artificial muscles made with polyacrylonitrile (PAN) fibers are traditionally activated in electrolytic solution by changing the pH of the solution by the addition of acids and/or bases. This usually consumes a considerable amount of weak acids or bases. Furthermore, the synthetic muscle (PAN) itself has to be impregnated with an acid or a base and must have an appropriate enclosure or provision for waste collection after actuation. This work introduces a method by which the PAN muscle may be elongated or contracted in an electric field. We believe this is the first time that this has been achieved with PAN fibers as artificial muscles. In this new development the PAN muscle is first put in close contact with one of the two platinum wires (electrodes) immersed in an aqueous solution of sodium chloride. Applying an electric voltage between the two wires changes the local acidity of the solution in the regions close to the platinum wires. This is because of the ionization of sodium chloride molecules and the accumulation of Na+ and Cl- ions at the negative and positive electrode sites, respectively. This ion accumulation, in turn, is accompanied by a sharp increase and decrease of the local acidity in regions close to either of the platinum wires, respectively. An artificial muscle, in close contact with the platinum wire, because of the change in the local acidity will contract or expand depending on the polarity of the electric field. This scheme allows the experimenter to use a fixed flexible container of an electrolytic solution whose local pH can be modulated by an imposed electric field while the produced ions are basically trapped to stay in the neighborhood of a given electrode. This method of artificial muscle activation has several advantages. First, the need to use a large quantity of acidic or alkaline solutions is eliminated. Second, the use of a compact PAN muscular system is facilitated for applications in active musculoskeletal structures. Third, the

  19. Application of a hybrid method combining grey model and back propagation artificial neural networks to forecast hepatitis B in china.

    Science.gov (United States)

    Gan, Ruijing; Chen, Xiaojun; Yan, Yu; Huang, Daizheng

    2015-01-01

    Accurate incidence forecasting of infectious disease provides potentially valuable insights in its own right. It is critical for early prevention and may contribute to health services management and syndrome surveillance. This study investigates the use of a hybrid algorithm combining grey model (GM) and back propagation artificial neural networks (BP-ANN) to forecast hepatitis B in China based on the yearly numbers of hepatitis B and to evaluate the method's feasibility. The results showed that the proposal method has advantages over GM (1, 1) and GM (2, 1) in all the evaluation indexes.

  20. Bioaccessibility and Risk of Exposure to Metals and SVOCs in Artificial Turf Field Fill Materials and Fibers.

    Science.gov (United States)

    Pavilonis, Brian T; Weisel, Clifford P; Buckley, Brian; Lioy, Paul J

    2014-01-01

    To reduce maintenance costs, municipalities and schools are starting to replace natural grass fields with a new generation synthetic turf. Unlike Astro-Turf, which was first introduced in the 1960s, synthetic field turf provides more cushioning to athletes. Part of this cushioning comes from materials like crumb rubber infill, which is manufactured from recycled tires and may contain a variety of chemicals. The goal of this study was to evaluate potential exposures from playing on artificial turf fields and associated risks to trace metals, semi-volatile organic compounds (SVOCs), and polycyclic aromatic hydrocarbons (PAHs) by examining typical artificial turf fibers (n = 8), different types of infill (n = 8), and samples from actual fields (n = 7). Three artificial biofluids were prepared, which included: lung, sweat, and digestive fluids. Artificial biofluids were hypothesized to yield a more representative estimation of dose than the levels obtained from total extraction methods. PAHs were routinely below the limit of detection across all three biofluids, precluding completion of a meaningful risk assessment. No SVOCs were identified at quantifiable levels in any extracts based on a match of their mass spectrum to compounds that are regulated in soil. The metals were measurable but at concentrations for which human health risk was estimated to be low. The study demonstrated that for the products and fields we tested, exposure to infill and artificial turf was generally considered de minimus, with the possible exception of lead for some fields and materials. © 2013 Society for Risk Analysis.