WorldWideScience

Sample records for artificial photosynthetic systems

  1. Energy transfer in real and artificial photosynthetic systems

    Energy Technology Data Exchange (ETDEWEB)

    Hindman, J.C.; Hunt, J.E.; Katz, J.J.

    1995-02-01

    Fluorescence emission from the photosynthetic organisms Tribonema aequale, Anacystis nidulau, and Chlorelia vulgais and from some chlorophyll model systems have been recorded as a function of excitation wavelength and temperature. Considerable similarity was observed in the effects of excitation wavelength and temperature on the fluorescence from intact photosynthetic organisms and the model systems. The parallelism in behavior suggest that self-assembly processes may occur in both the in vivo and in vitro systems that give rise to chlorophyll species at low temperature that may differ significantly from those present at ambient temperatures.

  2. Hybrid artificial photosynthetic systems comprising semiconductors as light harvesters and biomimetic complexes as molecular cocatalysts.

    Science.gov (United States)

    Wen, Fuyu; Li, Can

    2013-11-19

    Solar fuel production through artificial photosynthesis may be a key to generating abundant and clean energy, thus addressing the high energy needs of the world's expanding population. As the crucial components of photosynthesis, the artificial photosynthetic system should be composed of a light harvester (e.g., semiconductor or molecular dye), a reduction cocatalyst (e.g., hydrogenase mimic, noble metal), and an oxidation cocatalyst (e.g., photosystem II mimic for oxygen evolution from water oxidation). Solar fuel production catalyzed by an artificial photosynthetic system starts from the absorption of sunlight by the light harvester, where charge separation takes place, followed by a charge transfer to the reduction and oxidation cocatalysts, where redox reaction processes occur. One of the most challenging problems is to develop an artificial photosynthetic solar fuel production system that is both highly efficient and stable. The assembly of cocatalysts on the semiconductor (light harvester) not only can facilitate the charge separation, but also can lower the activation energy or overpotential for the reactions. An efficient light harvester loaded with suitable reduction and oxidation cocatalysts is the key for high efficiency of artificial photosynthetic systems. In this Account, we describe our strategy of hybrid photocatalysts using semiconductors as light harvesters with biomimetic complexes as molecular cocatalysts to construct efficient and stable artificial photosynthetic systems. We chose semiconductor nanoparticles as light harvesters because of their broad spectral absorption and relatively robust properties compared with a natural photosynthesis system. Using biomimetic complexes as cocatalysts can significantly facilitate charge separation via fast charge transfer from the semiconductor to the molecular cocatalysts and also catalyze the chemical reactions of solar fuel production. The hybrid photocatalysts supply us with a platform to study the

  3. Atmospheric CO2 capture for the artificial photosynthetic system

    Science.gov (United States)

    Nogalska, Adrianna; Zukowska, Adrianna; Garcia-Valls, Ricard

    2017-11-01

    The scope of these studies is to evaluate the ambient CO2 capture abilities of the membrane contactor system in the same conditions as leaves works during photosynthesis, such as ambient temperature, pressure and low CO2 concentration, where the only driving force is the concentration gradient. The polysulfone membrane was made by phase inversion process and characterized by ESEM micrographs which were used to determine the thickness, asymmetry and pore size. Besides, the porosity of the membrane was measured from the membrane and polysulfone density correlation and hydrophobicity was analyzed by contact angle measurements. Moreover, the compatibility of the membrane and absorbent solution was evaluated, in order to exclude wetting issues. The prepared membranes were introduced in a cross flow module and used as contactor between the CO2 and the potassium hydroxide solution, as absorbing media. The influence of the membrane thickness, absorbent stirring rate and absorption time, on CO2 capture were evaluated. The results show that the efficiency of our CO2 capture system is similar to stomatal carbon dioxide assimilation rate.

  4. Sustainable fuel, food, fertilizer and ecosystems through a global artificial photosynthetic system: overcoming anticompetitive barriers

    Science.gov (United States)

    Bruce, Alex; Faunce, Thomas

    2015-01-01

    This article discusses challenges that artificial photosynthetic (AP) systems will face when entering and competing in a global market characterized by established fossil fuel technology. It provides a perspective on the neoliberal principles underpinning much policy entrenching such environmentally destructive technology and outlines how competition law could aid overcoming these hurdles for AP development. In particular, it critiques the potential for competition law to promote a global AP initiative with greater emphasis on atmospheric carbon dioxide and nitrogen fixation (as well as solar-driven water splitting) to produce an equitable, globally distributed source of human food, fertilizer and biosphere sustainability, as well as hydrogen-based fuel. Some relevant strategies of competition law evaluated in this context include greater citizen–consumer involvement in shaping market values, legal requirements to factor services from the natural environment (i.e. provision of clean air, water, soil pollution degradation) into corporate costs, reform of corporate taxation and requirements to balance maximization of shareholder profit with contribution to a nominated public good, a global financial transactions tax, as well as prohibiting horizontal cartels, vertical agreements and unilateral misuse of market power. PMID:26052427

  5. Sustainable fuel, food, fertilizer and ecosystems through a global artificial photosynthetic system: overcoming anticompetitive barriers.

    Science.gov (United States)

    Bruce, Alex; Faunce, Thomas

    2015-06-06

    This article discusses challenges that artificial photosynthetic (AP) systems will face when entering and competing in a global market characterized by established fossil fuel technology. It provides a perspective on the neoliberal principles underpinning much policy entrenching such environmentally destructive technology and outlines how competition law could aid overcoming these hurdles for AP development. In particular, it critiques the potential for competition law to promote a global AP initiative with greater emphasis on atmospheric carbon dioxide and nitrogen fixation (as well as solar-driven water splitting) to produce an equitable, globally distributed source of human food, fertilizer and biosphere sustainability, as well as hydrogen-based fuel. Some relevant strategies of competition law evaluated in this context include greater citizen-consumer involvement in shaping market values, legal requirements to factor services from the natural environment (i.e. provision of clean air, water, soil pollution degradation) into corporate costs, reform of corporate taxation and requirements to balance maximization of shareholder profit with contribution to a nominated public good, a global financial transactions tax, as well as prohibiting horizontal cartels, vertical agreements and unilateral misuse of market power.

  6. Porphyrin and fullerene-based artificial photosynthetic materials for photovoltaics

    International Nuclear Information System (INIS)

    Imahori, Hiroshi; Kashiwagi, Yukiyasu; Hasobe, Taku; Kimura, Makoto; Hanada, Takeshi; Nishimura, Yoshinobu; Yamazaki, Iwao; Araki, Yasuyuki; Ito, Osamu; Fukuzumi, Shunichi

    2004-01-01

    We have developed artificial photosynthetic systems in which porphyrins and fullerenes are self-assembled as building blocks into nanostructured molecular light-harvesting materials and photovoltaic devices. Multistep electron transfer strategy has been combined with our finding that porphyrin and fullerene systems have small reorganization energies, which are suitable for the construction of light energy conversion systems as well as artificial photosynthetic models. Highly efficient photosynthetic electron transfer reactions have been realized at ITO electrodes modified with self-assembled monolayers of porphyrin oligomers as well as porphyrin-fullerene linked systems. Porphyrin-modified gold nanoclusters have been found to have potential as artificial photosynthetic materials. These results provide basic information for the development of nanostructured artificial photosynthetic systems

  7. Artificial vesicles with incorporated photosynthetic materials for potential solar energy conversion systems

    CSIR Research Space (South Africa)

    Smit, Jacoba E

    2009-07-01

    Full Text Available WITH INCORPORATED PHOTOSYNTHETIC MATERIALS FOR POTENTIAL SOLAR ENERGY CONVERSION SYSTEMS J E Smit1, A F Grobler2, A E Karsten1, R W Sparrow3 1 CSIR National Laser Centre, PO Box 395, Pretoria, 0001, South Africa 2 Unit for drug development and research, North...

  8. Leaf-architectured 3D Hierarchical Artificial Photosynthetic System of Perovskite Titanates Towards CO2 Photoreduction Into Hydrocarbon Fuels

    Science.gov (United States)

    Zhou, Han; Guo, Jianjun; Li, Peng; Fan, Tongxiang; Zhang, Di; Ye, Jinhua

    2013-01-01

    The development of an “artificial photosynthetic system” (APS) having both the analogous important structural elements and reaction features of photosynthesis to achieve solar-driven water splitting and CO2 reduction is highly challenging. Here, we demonstrate a design strategy for a promising 3D APS architecture as an efficient mass flow/light harvesting network relying on the morphological replacement of a concept prototype-leaf's 3D architecture into perovskite titanates for CO2 photoreduction into hydrocarbon fuels (CO and CH4). The process uses artificial sunlight as the energy source, water as an electron donor and CO2 as the carbon source, mimicking what real leaves do. To our knowledge this is the first example utilizing biological systems as “architecture-directing agents” for APS towards CO2 photoreduction, which hints at a more general principle for APS architectures with a great variety of optimized biological geometries. This research would have great significance for the potential realization of global carbon neutral cycle. PMID:23588925

  9. Carotenoid Photoprotection in Artificial Photosynthetic Antennas

    Energy Technology Data Exchange (ETDEWEB)

    Kloz, Miroslav [VU Univ., Amsterdam (Netherlands); Pillai, Smitha [Arizona State Univ., Tempe, AZ (United States); Kodis, Gerdenis [Arizona State Univ., Tempe, AZ (United States); Gust, Devens [Arizona State Univ., Tempe, AZ (United States); Moore, Thomas A. [Arizona State Univ., Tempe, AZ (United States); Moore, Ana L. [Arizona State Univ., Tempe, AZ (United States); van Grondelle, Rienk [VU Univ., Amsterdam (Netherlands); Kennis, John T. M. [VU Univ., Amsterdam (Netherlands)

    2011-04-14

    A series of phthalocyanine-carotenoid dyads in which a phenylamino group links a phthalocyanine to carotenoids having 8-11 backbone double bonds were examined by visible and near-infrared femtosecond pump-probe spectroscopy combined with global fitting analysis. The series of molecules has permitted investigation of the role of carotenoids in the quenching of excited states of cyclic tetrapyrroles. The transient behavior varied dramatically with the length of the carotenoid and the solvent environment. Clear spectroscopic signatures of radical species revealed photoinduced electron transfer as the main quenching mechanism for all dyads dissolved in a polar solvent (THF), and the quenching rate was almost independent of carotenoid length. However, in a nonpolar solvent (toluene), quenching rates displayed a strong dependence on the conjugation length of the carotenoid and the mechanism did not include charge separation. The lack of any rise time components of a carotenoid S1 signature in all experiments in toluene suggests that an excitonic coupling between the carotenoid S1 state and phthalocyanine Q state, rather than a conventional energy transfer process, is the major mechanism of quenching. A pronounced inhomogeneity of the system was observed and attributed to the presence of a phenyl-amino linker between phthalocyanine and carotenoids. On the basis of accumulated work on various caroteno-phthalocyanine dyads and triads, we have now identified three mechanisms of tetrapyrrole singlet excited state quenching by carotenoids in artificial systems: (i) Car-Pc electron transfer and recombination; (ii)1Pc to Car S1 energy transfer and fast internal conversion to the Car ground state; (iii) excitonic coupling between 1Pc and Car S1 and ensuing internal conversion to the ground state of the carotenoid. The dominant mechanism depends upon the exact molecular architecture and solvent environment

  10. 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.

  11. Hybrid system of semiconductor and photosynthetic protein

    International Nuclear Information System (INIS)

    Kim, Younghye; Shin, Seon Ae; Lee, Jaehun; Yang, Ki Dong; Nam, Ki Tae

    2014-01-01

    Photosynthetic protein has the potential to be a new attractive material for solar energy absorption and conversion. The development of semiconductor/photosynthetic protein hybrids is an example of recent progress toward efficient, clean and nanostructured photoelectric systems. In the review, two biohybrid systems interacting through different communicating methods are addressed: (1) a photosynthetic protein immobilized semiconductor electrode operating via electron transfer and (2) a hybrid of semiconductor quantum dots and photosynthetic protein operating via energy transfer. The proper selection of materials and functional and structural modification of the components and optimal conjugation between them are the main issues discussed in the review. In conclusion, we propose the direction of future biohybrid systems for solar energy conversion systems, optical biosensors and photoelectric devices. (topical reviews)

  12. Development of a novel artificial medium based on utilization of algal photosynthetic metabolites by symbiotic heterotrophs.

    Science.gov (United States)

    Watanabe, K; Imase, M; Aoyagi, H; Ohmura, N; Saiki, H; Tanaka, H

    2008-09-01

    (i) Quantitative and qualitative analyses of photosynthetic metabolites of Chlorella sorokiniana and elucidation of the mechanism of their utilization by algal symbionts. (ii) Development of artificial medium that imitates photoautotroph-heterotroph interaction and investigation of its suitability for isolation of novel microbes from the environment. Various components, including free dissolved carbohydrates, nitrogenous compounds and vitamin, were detected and together contributed 11.1% (as carbon content) of the total photosynthetic metabolites in the medium. Utilization of these photosynthetic metabolites in algal culture broth by algal symbionts was studied. Many symbionts showed specific utilization patterns. A novel artificial extracellular released organic carbon medium, which imitated the nutritional conditions surrounding algae, was developed based on the pattern of utilization of the algal metabolites by the symbiotic heterotrophs. About 42.9% of the isolates were closely related to photoautotrophic-dependent and oligotrophic bacteria. With the novel artificial medium, it was possible to selectively isolate some bacterial strains. Synthetic bacterial growth medium is an important and basic tool for bacterial isolation from environmental samples. The current study shows that preferential separation of typical bacterial subset can be achieved by using artificial medium that mimics photosynthetic metabolites.

  13. Photovoltaic concepts inspired by coherence effects in photosynthetic systems

    KAUST Repository

    Bredas, Jean-Luc

    2016-12-20

    The past decade has seen rapid advances in our understanding of how coherent and vibronic phenomena in biological photosynthetic systems aid in the efficient transport of energy from light-harvesting antennas to photosynthetic reaction centres. Such coherence effects suggest strategies to increase transport lengths even in the presence of structural disorder. Here we explore how these principles could be exploited in making improved solar cells. We investigate in depth the case of organic materials, systems in which energy and charge transport stand to be improved by overcoming challenges that arise from the effects of static and dynamic disorder-structural and energetic-and from inherently strong electron-vibration couplings. We discuss how solar-cell device architectures can evolve to use coherence-exploiting materials, and we speculate as to the prospects for a coherent energy conversion system. We conclude with a survey of the impacts of coherence and bioinspiration on diverse solar-energy harvesting solutions, including artificial photosynthetic systems.

  14. Ultrafast Energy Transfer in an Artificial Photosynthetic Antenna

    Directory of Open Access Journals (Sweden)

    van Grondelle R.

    2013-03-01

    Full Text Available We temporally resolved energy transfer kinetics in an artificial light-harvesting dyad composed of a phthalocyanine covalently linked to a carotenoid. Upon carotenoid photo-excitation, energy transfers within ≈100fs (≈52% efficiency to the phthalocyanine.

  15. Triplet–triplet energy transfer in artificial and natural photosynthetic antennas

    OpenAIRE

    Ho, Junming; Kish, Elizabeth; Méndez-Hernández, Dalvin D.; WongCarter, Katherine; Pillai, Smitha; Kodis, Gerdenis; Niklas, Jens; Poluektov, Oleg G.; Gust, Devens; Moore, Thomas A.; Moore, Ana L.; Batista, Victor S.; Robert, Bruno

    2017-01-01

    Rapid chlorophyll-to-carotenoid triplet–triplet energy transfer (T-TET) in photosynthetic organisms is crucial to photoprotection from singlet oxygen. Photosynthesis reengineered for increased efficiency will result in increased oxygen levels in the cells, and the need to ensure adequately rapid T-TET will arise. Using a combination of theoretical and experimental studies on artificial and natural carotenoid–chlorophyll complexes, we have identified spectroscopic markers indicative of specifi...

  16. Bio-Inspired Assembly of Artificial Photosynthetic Antenna Complexes for Development of Nanobiodevices

    Science.gov (United States)

    2011-06-24

    complexes involved in the primary reactions of bacterial photosynthesis . The structure of the reaction center (RC, the first membrane protein to have its...role in the primary process of purple bacterial photosynthesis that is, capturing light energy, transferring it to the RC where it is used in...immobilization LH2 LH1-RC AFM image of a bacterial photosynthetic membrane . Artificial domains of LH2 & LH1-RC with patterning substrate Modern

  17. Magnetic irone oxide nanoparticles in photosynthetic systems

    International Nuclear Information System (INIS)

    Khalilov, R.I.; Nasibova, A.N.; Khomutov, G.B.

    2014-01-01

    Full text : It was found and studied the effect of biogenic formation of magnetic inclusions in photosynthetic systems - in various higher plants under the influence of some external stress factors (radiation impact, moisture deficit) and in a model system - a suspension of chloroplasts. For registration and characterization of magnetic nanoparticles in the samples used EPR spectrometer because superparamagnetic and ferromagnetic nanoparticles have a chcracteristic signals of electron magnetic resonance. For direct visualization of magnetic nanoparticles it was used the method of transmission electron microscopy

  18. Artificial neural network model for photosynthetic pigments identification using multi wavelength chromatographic data

    Science.gov (United States)

    Prilianti, K. R.; Hariyanto, S.; Natali, F. D. D.; Indriatmoko, Adhiwibawa, M. A. S.; Limantara, L.; Brotosudarmo, T. H. P.

    2016-04-01

    The development of rapid and automatic pigment characterization method become an important issue due to the fact that there are only less than 1% of plant pigments in the earth have been explored. In this research, a mathematical model based on artificial intelligence approach was developed to simplify and accelerate pigment characterization process from HPLC (high-performance liquid chromatography) procedure. HPLC is a widely used technique to separate and identify pigments in a mixture. Input of the model is chromatographic data from HPLC device and output of the model is a list of pigments which is the spectrum pattern is discovered in it. This model provides two dimensional (retention time and wavelength) fingerprints for pigment characterization which is proven to be more accurate than one dimensional fingerprint (fixed wavelength). Moreover, by mimicking interconnection of the neuron in the nervous systems of the human brain, the model have learning ability that could be replacing expert judgement on evaluating spectrum pattern. In the preprocessing step, principal component analysis (PCA) was used to reduce the huge dimension of the chromatographic data. The aim of this step is to simplify the model and accelerate the identification process. Six photosynthetic pigments i.e. zeaxantin, pheophytin a, α-carotene, β-carotene, lycopene and lutein could be well identified by the model with accuracy up to 85.33% and processing time less than 1 second.

  19. PS2013 Satellite Workshop on Photosynthetic Light-Harvesting Systems

    Energy Technology Data Exchange (ETDEWEB)

    Niederman, Robert A. [Rutgers Univ., New Brunswick, NJ (United States); Blankenship, Robert E. [Washington Univ., St. Louis, MO (United States); Frank, Harry A. [Univ. of Connecticut, Storrs, CT (United States)

    2015-02-07

    These funds were used for partial support of the PS2013 Satellite Workshop on Photosynthetic Light-Harvesting Systems, that was held on 8-11 August, 2013, at Washington University, St. Louis, MO. This conference, held in conjunction with the 16th International Congress on Photosynthesis/St. Louis, continued a long tradition of light-harvesting satellite conferences that have been held prior to the previous six international photosynthesis congresses. In this Workshop, the basis was explored for the current interest in replacing fossil fuels with energy sources derived form direct solar radiation, coupled with light-driven electron transport in natural photosynthetic systems and how they offer a valuable blueprint for conversion of sunlight to useful energy forms. This was accomplished through sessions on the initial light-harvesting events in the biological conversion of solar energy to chemically stored energy forms, and how these natural photosynthetic processes serve as a guide to the development of robust bio-hybrid and artificial systems for solar energy conversion into both electricity or chemical fuels. Organized similar to a Gordon Research Conference, a lively, informal and collegial setting was established, highlighting the exchange of exciting new data and unpublished results from ongoing studies. A significant amount of time was set aside for open discussion and interactive poster sessions, with a special session devoted to oral presentations by talented students and postdoctoral fellows judged to have the best posters. This area of research has seen exceptionally rapid progress in recent years, with the availability of a number of antenna protein structures at atomic resolution, elucidation of the molecular surface architecture of native photosynthetic membranes by atomic force microscopy and the maturing of ultrafast spectroscopic and molecular biological techniques for the investigation and manipulation of photosynthetic systems. The conferees

  20. [Effects of low-light stress on photosynthetic characteristics of Paris polyphylla var. chinensis in artificial domestication cultivation].

    Science.gov (United States)

    Zheng, Shun-lin; Tian, Meng-liang; Liu, Jin-liang; Zhao, Ting-ting; Zhang, Zhong

    2014-09-01

    To decide on the optimum artificial domestication cultivation light environment for Paris polyphylla var. chinensis through investigating the effect of light intensity on leaf's gas exchange parameters, photosynthetic parameters, light saturation point and compensation point of Paris polyphylla var. chinensis. Different low-light stress gradients' effect on the growth of Paris polyphylla var. chinensis was compared with no low-light stress treatment through calculating leaf's gas exchange parameters, photosynthetic parameters, light saturation point and compensation point, and then all these parameters were statistically analyzed. Light intensity had significant influence on the photosynthetic characteristics of Paris polyphylla var. chinensis. With the strengthening of the low-light stress, chlorophyll content, gas exchange parameters, photosynthetic parameters P., AQY and light saturation point all gradually increased at first, and then decreased. However, both photosynthetic parameters Rd and light compensation point firstly decreased and then rose again. These results showed that too strong or too weak light intensity affected the optimization of photosynthetic parameters of Paris polyphylla var. chinensis. The optimal illuminance for each parameter was not completely same, but they could all reach a relative ideal state when the shading ranges between 40% and 60%. However, photosynthetic parameters deteriorated rapidly when the shading surpass 80%. For artificially cultivating Paris polyphylla var. chinensis in Baoxing,Sichuan or the similar ecological region, shading 40%-60% is the optimal light environment, which can enhance the photosynthesis of Paris polyphylla var. chinensis and promote the accumulation of photosynthetic products.

  1. Cyanobacteria as photosynthetic biocatalysts: a systems biology perspective.

    Science.gov (United States)

    Gudmundsson, Steinn; Nogales, Juan

    2015-01-01

    The increasing need to replace oil-based products and to address global climate change concerns has triggered considerable interest in photosynthetic microorganisms. Cyanobacteria, in particular, have great potential as biocatalysts for fuels and fine-chemicals. During the last few years the biotechnological applications of cyanobacteria have experienced an unprecedented increase and the use of these photosynthetic organisms for chemical production is becoming a tangible reality. However, the field is still immature and many concerns about the economic feasibility of the biotechnological potential of cyanobacteria remain. In this review we describe recent successes in biofuel and fine-chemical production using cyanobacteria. We discuss the role of the photosynthetic metabolism and highlight the need for systems-level metabolic optimization in order to achieve the true potential of cyanobacterial biocatalysts.

  2. PHOTOINDUCED TRANSFER OF OXYGEN FROM WATER: AN ARTIFICAL PHOTOSYNTHETIC SYSTEM

    Energy Technology Data Exchange (ETDEWEB)

    Willner, Itamar; Otvos, John W.; Ford, William E.; Mettee, Howard; Calvin, Melvin

    1979-11-01

    The photoinduced splitting of water into hydrogen and oxygen has evoked great interest in recent years as a means for energy storag eand fuel production. Photoinduced reduction of water to hydrogen, using visible light, has been described using heterogeneous or homogeneous catalysts. However, the complementary part involving the oxidation of water to oxygen is required in order to create a cyclic artificial 'photosynthetic' fuel system. The major difficulty assocaited with the photooxidation of water involves the requirement for a four electron transfer to produce oxygen. A stepwise one-electron oxidation of water is unfavorable due to the implied formation of active hydroxyl radicals. Very recently, it has been reported that RuO{sub 2} can serve as a heterogeneous charge storage catalyst for oxygen production. On the basis of the limited knowledge about natural photosynthesis, in which manganese ions play an important role in oxygen evolution, synthetic manganese complexes, and in particular dimeric complexes, have been proposed as potential catalysts for oxygen production. So far, efforts directed toward this goal have been unsuccessful. Consequently, using a manganese complex, they attempted to perform a photoinduced oxidation of water whereby the active oxygen is transferred to a trapping substrate. In such a way, the requirement for a dimerization process to evolve molecular oxygen is avoided. They wish to report a photoinduced redox cycle sensitized by a manganese porphyrin, 5-(4{prime}-hexadecylpyridium)-10, 15, 20-tri (4{prime}-pyridyl)-porphinatomanganese(III) (abbreciated to Pn-Mn{sup III}) in which the resultant reaction is the oxidation of water and trapping of the single oxygen atom by a substrate (triphenylphosphine).

  3. Coherent memory functions for finite systems: hexagonal photosynthetic unit

    International Nuclear Information System (INIS)

    Barvik, I.; Herman, P.

    1990-10-01

    Coherent memory functions entering the Generalized Master Equation are presented for an hexagonal model of a photosynthetic unit. Influence of an energy heterogeneity on an exciton transfer is an antenna system as well as to a reaction center is investigated. (author). 9 refs, 3 figs

  4. Biological optimization systems for enhancing photosynthetic efficiency and methods of use

    Science.gov (United States)

    Hunt, Ryan W.; Chinnasamy, Senthil; Das, Keshav C.; de Mattos, Erico Rolim

    2012-11-06

    Biological optimization systems for enhancing photosynthetic efficiency and methods of use. Specifically, methods for enhancing photosynthetic efficiency including applying pulsed light to a photosynthetic organism, using a chlorophyll fluorescence feedback control system to determine one or more photosynthetic efficiency parameters, and adjusting one or more of the photosynthetic efficiency parameters to drive the photosynthesis by the delivery of an amount of light to optimize light absorption of the photosynthetic organism while providing enough dark time between light pulses to prevent oversaturation of the chlorophyll reaction centers are disclosed.

  5. Artificial Neural Network Analysis System

    Science.gov (United States)

    2001-02-27

    Contract No. DASG60-00-M-0201 Purchase request no.: Foot in the Door-01 Title Name: Artificial Neural Network Analysis System Company: Atlantic... Artificial Neural Network Analysis System 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Powell, Bruce C 5d. PROJECT NUMBER 5e. TASK NUMBER...34) 27-02-2001 Report Type N/A Dates Covered (from... to) ("DD MON YYYY") 28-10-2000 27-02-2001 Title and Subtitle Artificial Neural Network Analysis

  6. Building Explainable Artificial Intelligence Systems

    National Research Council Canada - National Science Library

    Core, Mark G; Lane, H. Chad; van Lent, Michael; Gomboc, Dave; Solomon, Steve; Rosenberg, Milton

    2006-01-01

    As artificial intelligence (AI) systems and behavior models in military simulations become increasingly complex, it has been difficult for users to understand the activities of computer-controlled entities...

  7. Artificial Intelligence and Expert Systems.

    Science.gov (United States)

    Wilson, Harold O.; Burford, Anna Marie

    1990-01-01

    Delineates artificial intelligence/expert systems (AI/ES) concepts; provides an exposition of some business application areas; relates progress; and creates an awareness of the benefits, limitations, and reservations of AI/ES. (Author)

  8. Photoelectrochemical cells based on photosynthetic systems: a review

    Directory of Open Access Journals (Sweden)

    Roman A. Voloshin

    2015-06-01

    Full Text Available Photosynthesis is a process which converts light energy into energy contained in the chemical bonds of organic compounds by photosynthetic pigments such as chlorophyll (Chl a, b, c, d, f or bacteriochlorophyll. It occurs in phototrophic organisms, which include higher plants and many types of photosynthetic bacteria, including cyanobacteria. In the case of the oxygenic photosynthesis, water is a donor of both electrons and protons, and solar radiation serves as inexhaustible source of energy. Efficiency of energy conversion in the primary processes of photosynthesis is close to 100%. Therefore, for many years photosynthesis has attracted the attention of researchers and designers looking for alternative energy systems as one of the most efficient and eco-friendly pathways of energy conversion. The latest advances in the design of optimal solar cells include the creation of converters based on thylakoid membranes, photosystems, and whole cells of cyanobacteria immobilized on nanostructured electrode (gold nanoparticles, carbon nanotubes, nanoparticles of ZnO and TiO2. The mode of solar energy conversion in photosynthesis has a great potential as a source of renewable energy while it is sustainable and environmentally safety as well. Application of pigments such as Chl f and Chl d (unlike Chl a and Chl b, by absorbing the far red and near infrared region of the spectrum (in the range 700-750 nm, will allow to increase the efficiency of such light transforming systems. This review article presents the last achievements in the field of energy photoconverters based on photosynthetic systems.

  9. Photosynthetic antennae systems: energy transport and optical absorption

    International Nuclear Information System (INIS)

    Reineker, P.; Supritz, Ch.; Warns, Ch.; Barvik, I.

    2004-01-01

    The energy transport and the optical line shape of molecular aggregates, modeling bacteria photosynthetic light-harvesting systems (chlorosomes in the case of Chlorobium tepidum or Chloroflexus aurantiacus and LH2 in the case of Rhodopseudomonas acidophila) is investigated theoretically. The molecular units are described by two-level systems with an average excitation energy ε and interacting with each other through nearest-neighbor interactions. For LH2 an elliptical deformation of the ring is also allowed. Furthermore, dynamic and in the case of LH2 also quasi-static fluctuations of the local excitation energies are taken into account, simulating fast molecular vibrations and slow motions of the protein backbone, respectively. The fluctuations are described by Gaussian Markov processes in the case of the chlorosomes and by colored dichotomic Markov processes, with exponentially decaying correlation functions, with small (λ s ) and large (λ) decay constants, in the case of LH2

  10. Extension of Light-Harvesting Ability of Photosynthetic Light-Harvesting Complex 2 (LH2) through Ultrafast Energy Transfer from Covalently Attached Artificial Chromophores.

    Science.gov (United States)

    Yoneda, Yusuke; Noji, Tomoyasu; Katayama, Tetsuro; Mizutani, Naoto; Komori, Daisuke; Nango, Mamoru; Miyasaka, Hiroshi; Itoh, Shigeru; Nagasawa, Yutaka; Dewa, Takehisa

    2015-10-14

    Introducing appropriate artificial components into natural biological systems could enrich the original functionality. To expand the available wavelength range of photosynthetic bacterial light-harvesting complex 2 (LH2 from Rhodopseudomonas acidophila 10050), artificial fluorescent dye (Alexa Fluor 647: A647) was covalently attached to N- and C-terminal Lys residues in LH2 α-polypeptides with a molar ratio of A647/LH2 ≃ 9/1. Fluorescence and transient absorption spectroscopies revealed that intracomplex energy transfer from A647 to intrinsic chromophores of LH2 (B850) occurs in a multiexponential manner, with time constants varying from 440 fs to 23 ps through direct and B800-mediated indirect pathways. Kinetic analyses suggested that B800 chromophores mediate faster energy transfer, and the mechanism was interpretable in terms of Förster theory. This study demonstrates that a simple attachment of external chromophores with a flexible linkage can enhance the light harvesting activity of LH2 without affecting inherent functions of energy transfer, and can achieve energy transfer in the subpicosecond range. Addition of external chromophores, thus, represents a useful methodology for construction of advanced hybrid light-harvesting systems that afford solar energy in the broad spectrum.

  11. 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.

  12. Removal of triazine herbicides from freshwater systems using photosynthetic microorganisms

    International Nuclear Information System (INIS)

    Gonzalez-Barreiro, O.; Rioboo, C.; Herrero, C.; Cid, A.

    2006-01-01

    The uptake of the triazine herbicides, atrazine and terbutryn, was determined for two freshwater photosynthetic microorganisms, the green microalga Chlorella vulgaris and the cyanobacterium Synechococcus elongatus. An extremely rapid uptake of both pesticides was recorded, although uptake rate was lower for the cyanobacterium, mainly for atrazine. Other parameters related to the herbicide bioconcentration capacity of these microorganisms were also studied. Growth rate, biomass, and cell viability in cultures containing herbicide were clearly affected by herbicide uptake. Herbicide toxicity and microalgae sensitivity were used to determine the effectiveness of the bioconcentration process and the stability of herbicide removal. C. vulgaris showed higher bioconcentration capability for these two triazine herbicides than S. elongatus, especially with regard to terbutryn. This study supports the usefulness of such microorganisms, as a bioremediation technique in freshwater systems polluted with triazine herbicides

  13. Removal of triazine herbicides from freshwater systems using photosynthetic microorganisms

    Energy Technology Data Exchange (ETDEWEB)

    Gonzalez-Barreiro, O. [Laboratorio de Microbiologia, Facultad de Ciencias, Universidad de A Coruna, Campus da Zapateira s/n. 15071 A Coruna (Spain); Rioboo, C. [Laboratorio de Microbiologia, Facultad de Ciencias, Universidad de A Coruna, Campus da Zapateira s/n. 15071 A Coruna (Spain); Herrero, C. [Laboratorio de Microbiologia, Facultad de Ciencias, Universidad de A Coruna, Campus da Zapateira s/n. 15071 A Coruna (Spain); Cid, A. [Laboratorio de Microbiologia, Facultad de Ciencias, Universidad de A Coruna, Campus da Zapateira s/n. 15071 A Coruna (Spain)]. E-mail: cid@udc.es

    2006-11-15

    The uptake of the triazine herbicides, atrazine and terbutryn, was determined for two freshwater photosynthetic microorganisms, the green microalga Chlorella vulgaris and the cyanobacterium Synechococcus elongatus. An extremely rapid uptake of both pesticides was recorded, although uptake rate was lower for the cyanobacterium, mainly for atrazine. Other parameters related to the herbicide bioconcentration capacity of these microorganisms were also studied. Growth rate, biomass, and cell viability in cultures containing herbicide were clearly affected by herbicide uptake. Herbicide toxicity and microalgae sensitivity were used to determine the effectiveness of the bioconcentration process and the stability of herbicide removal. C. vulgaris showed higher bioconcentration capability for these two triazine herbicides than S. elongatus, especially with regard to terbutryn. This study supports the usefulness of such microorganisms, as a bioremediation technique in freshwater systems polluted with triazine herbicides.

  14. 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.

  15. Artificial Intelligence and Spacecraft Power Systems

    Science.gov (United States)

    Dugel-Whitehead, Norma R.

    1997-01-01

    This talk will present the work which has been done at NASA Marshall Space Flight Center involving the use of Artificial Intelligence to control the power system in a spacecraft. The presentation will include a brief history of power system automation, and some basic definitions of the types of artificial intelligence which have been investigated at MSFC for power system automation. A video tape of one of our autonomous power systems using co-operating expert systems, and advanced hardware will be presented.

  16. Learning in Artificial Neural Systems

    Science.gov (United States)

    Matheus, Christopher J.; Hohensee, William E.

    1987-01-01

    This paper presents an overview and analysis of learning in Artificial Neural Systems (ANS's). It begins with a general introduction to neural networks and connectionist approaches to information processing. The basis for learning in ANS's is then described, and compared with classical Machine learning. While similar in some ways, ANS learning deviates from tradition in its dependence on the modification of individual weights to bring about changes in a knowledge representation distributed across connections in a network. This unique form of learning is analyzed from two aspects: the selection of an appropriate network architecture for representing the problem, and the choice of a suitable learning rule capable of reproducing the desired function within the given network. The various network architectures are classified, and then identified with explicit restrictions on the types of functions they are capable of representing. The learning rules, i.e., algorithms that specify how the network weights are modified, are similarly taxonomized, and where possible, the limitations inherent to specific classes of rules are outlined.

  17. Artificial intelligence in power system optimization

    CERN Document Server

    Ongsakul, Weerakorn

    2013-01-01

    With the considerable increase of AI applications, AI is being increasingly used to solve optimization problems in engineering. In the past two decades, the applications of artificial intelligence in power systems have attracted much research. This book covers the current level of applications of artificial intelligence to the optimization problems in power systems. This book serves as a textbook for graduate students in electric power system management and is also be useful for those who are interested in using artificial intelligence in power system optimization.

  18. A DISTRIBUTED SMART HOME ARTIFICIAL INTELLIGENCE SYSTEM

    DEFF Research Database (Denmark)

    Lynggaard, Per

    2013-01-01

    A majority of the research performed today explore artificial intelligence in smart homes by using a centralized approach where a smart home server performs the necessary calculations. This approach has some disadvantages that can be overcome by shifting focus to a distributed approach where...... the artificial intelligence system is implemented as distributed as agents running parts of the artificial intelligence system. This paper presents a distributed smart home architecture that distributes artificial intelligence in smart homes and discusses the pros and cons of such a concept. The presented...... distributed model is a layered model. Each layer offers a different complexity level of the embedded distributed artificial intelligence. At the lowest layer smart objects exists, they are small cheap embedded microcontroller based smart devices that are powered by batteries. The next layer contains a more...

  19. Abstraction in artificial intelligence and complex systems

    CERN Document Server

    Saitta, Lorenza

    2013-01-01

    Abstraction is a fundamental mechanism underlying both human and artificial perception, representation of knowledge, reasoning and learning. This mechanism plays a crucial role in many disciplines, notably Computer Programming, Natural and Artificial Vision, Complex Systems, Artificial Intelligence and Machine Learning, Art, and Cognitive Sciences. This book first provides the reader with an overview of the notions of abstraction proposed in various disciplines by comparing both commonalities and differences.  After discussing the characterizing properties of abstraction, a formal model, the K

  20. Artificial intelligence techniques in power systems

    Energy Technology Data Exchange (ETDEWEB)

    Laughton, M.A.

    1997-12-31

    Since the early to mid 1980s much of the effort in power systems analysis has turned away from the methodology of formal mathematical modelling which came from the fields of operations research, control theory and numerical analysis to the less rigorous techniques of artificial intelligence (AI). Today the main AI techniques found in power systems applications are those utilising the logic and knowledge representations of expert systems, fuzzy systems, artificial neural networks (ANN) and, more recently, evolutionary computing. These techniques will be outlined in this chapter and the power system applications indicated. (Author)

  1. Diel tuning of photosynthetic systems in ice algae at Saroma-ko Lagoon, Hokkaido, Japan

    Science.gov (United States)

    Aikawa, Shimpei; Hattori, Hiroshi; Gomi, Yasushi; Watanabe, Kentaro; Kudoh, Sakae; Kashino, Yasuhiro; Satoh, Kazuhiko

    Ice algae are the major primary producers in seasonally ice-covered oceans during the cold season. Diurnal change in solar radiation is inevitable for ice algae, even beneath seasonal sea ice in lower-latitude regions. In this work, we focused on the photosynthetic response of ice algae under diurnally changing irradiance in Saroma-ko Lagoon, Japan. Photosynthetic properties were assessed by pulse-amplitude modulation (PAM) fluorometry. The species composition remained almost the same throughout the investigation. The maximum electron transport rate ( rETRmax), which indicates the capacity of photosynthetic electron transport, increased from sunrise until around noon and decreased toward sunset, with no sign of the afternoon depression commonly observed in other photosynthetic organisms. The level of non-photochemical quenching, which indicates photoprotection activity by dissipating excess light energy via thermal processes, changed with diurnal variations in irradiance. The pigment composition appeared constant, except for xanthophyll cycle pigments, which changed irrespective of irradiance. These results indicate that ice algae tune their photosynthetic system harmonically to achieve efficient photosynthesis under diurnally changing irradiance, while avoiding damage to photosystems. This regulation system may be essential for productive photosynthesis in ice algae.

  2. Counseling, Artificial Intelligence, and Expert Systems.

    Science.gov (United States)

    Illovsky, Michael E.

    1994-01-01

    Considers the use of artificial intelligence and expert systems in counseling. Limitations are explored; candidates for counseling versus those for expert systems are discussed; programming considerations are reviewed; and techniques for dealing with rational, nonrational, and irrational thoughts and feelings are described. (Contains 46…

  3. What Is an Artificial Muscle? A Systemic Approach.

    OpenAIRE

    Bertrand Tondu

    2015-01-01

    Artificial muscles define a large category of actuators we propose to analyze in a systemic framework by considering any artificial muscle as an open-loop stable system for any output which represents an artificial muscle dimension resulting from its “contraction”, understood in a broad meaning. This approach makes it possible to distinguish the artificial muscle from other actuators and to specify an original model for a linear artificial muscle, according to the theory of linear systems. Su...

  4. Missileborne Artificial Vision System (MAVIS)

    Science.gov (United States)

    Andes, David K.; Witham, James C.; Miles, Michael D.

    1994-01-01

    Several years ago when INTEL and China Lake designed the ETANN chip, analog VLSI appeared to be the only way to do high density neural computing. In the last five years, however, digital parallel processing chips capable of performing neural computation functions have evolved to the point of rough equality with analog chips in system level computational density. The Naval Air Warfare Center, China Lake, has developed a real time, hardware and software system designed to implement and evaluate biologically inspired retinal and cortical models. The hardware is based on the Adaptive Solutions Inc. massively parallel CNAPS system COHO boards. Each COHO board is a standard size 6U VME card featuring 256 fixed point, RISC processors running at 20 MHz in a SIMD configuration. Each COHO board has a companion board built to support a real time VSB interface to an imaging seeker, a NTSC camera, and to other COHO boards. The system is designed to have multiple SIMD machines each performing different corticomorphic functions. The system level software has been developed which allows a high level description of corticomorphic structures to be translated into the native microcode of the CNAPS chips. Corticomorphic structures are those neural structures with a form similar to that of the retina, the lateral geniculate nucleus, or the visual cortex. This real time hardware system is designed to be shrunk into a volume compatible with air launched tactical missiles. Initial versions of the software and hardware have been completed and are in the early stages of integration with a missile seeker.

  5. 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.

  6. Nuclear-powered artificial heart system

    International Nuclear Information System (INIS)

    Pouchot, W.D.; Lehrfeld, D.

    1976-01-01

    As reported to the 9th IECEC, a bench model version of a nuclear-powered artificial heart system to be used as a replacement for the natural heart was constructed and tested as part of a broader U.S. ERDA program. A report is given of the system design and integration, bench testing, and field support equipment of an implantable and advanced version of the bench model incorporating some of the component developments reported to the 10th IECEC. The basic elements of the system are a 32-watt Pu-238 heat source, a Stirling engine thermal converter, a coupling mechanism, and a mechanical blood pump drive actuating, alternatively, two artificial ventricles of polymeric material. As tested on the bench using a mock circulation, the system provides approximately 9 liters/minute at 120/80 mm Hg aortic pressure. At 190/145 mm Hg aortic pressure, the maximum flow decreases to about 7 liters/minute

  7. Artificial immune system applications in computer security

    CERN Document Server

    Tan, Ying

    2016-01-01

    This book provides state-of-the-art information on the use, design, and development of the Artificial Immune System (AIS) and AIS-based solutions to computer security issues. Artificial Immune System: Applications in Computer Security focuses on the technologies and applications of AIS in malware detection proposed in recent years by the Computational Intelligence Laboratory of Peking University (CIL@PKU). It offers a theoretical perspective as well as practical solutions for readers interested in AIS, machine learning, pattern recognition and computer security. The book begins by introducing the basic concepts, typical algorithms, important features, and some applications of AIS. The second chapter introduces malware and its detection methods, especially for immune-based malware detection approaches. Successive chapters present a variety of advanced detection approaches for malware, including Virus Detection System, K-Nearest Neighbour (KNN), RBF networ s, and Support Vector Machines (SVM), Danger theory, ...

  8. 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.

  9. Dynamic artificial neural networks with affective systems.

    Directory of Open Access Journals (Sweden)

    Catherine D Schuman

    Full Text Available Artificial neural networks (ANNs are processors that are trained to perform particular tasks. We couple a computational ANN with a simulated affective system in order to explore the interaction between the two. In particular, we design a simple affective system that adjusts the threshold values in the neurons of our ANN. The aim of this paper is to demonstrate that this simple affective system can control the firing rate of the ensemble of neurons in the ANN, as well as to explore the coupling between the affective system and the processes of long term potentiation (LTP and long term depression (LTD, and the effect of the parameters of the affective system on its performance. We apply our networks with affective systems to a simple pole balancing example and briefly discuss the effect of affective systems on network performance.

  10. An Artificial Neural Network Controller for Intelligent Transportation Systems Applications

    Science.gov (United States)

    1996-01-01

    An Autonomous Intelligent Cruise Control (AICC) has been designed using a feedforward artificial neural network, as an example for utilizing artificial neural networks for nonlinear control problems arising in intelligent transportation systems appli...

  11. Vibration behavior of the artificial barrier system

    International Nuclear Information System (INIS)

    Mikoshiba, Tadashi; Ogawa, Nobuyuki; Nakamura, Izuru

    2000-01-01

    This study aims at production of a mimic specimen of artificial barrier, experimental elucidation of influence of seismic motion due to a vibration experiment on the artificial barrier system, and establishment of an evaluating method on its long-term behavior. The study has been carried out under a cooperative study of the National Research Institute for Earth Science and Disaster Prevention and the Japan Nuclear Cycle Development Institute. In 1998 fiscal year, an artificial barrier specimen initiated by crosscut road was produced, and their random wave and actual seismic wave vibrations were carried out to acquire their fundamental data. As a result of the both vibrations, it was found that in a Case 2 specimen of which buffer material was swelled by poured water, the material was integrated with a mimic over-pack to vibrate under judgement of eigen-frequency, maximum acceleration ratio, and so forth on the test results. And, in a Case 1 specimen, it was thought that the mimic over-pack showed an extreme non-linear performance (soft spring) because of reducing eigen-frequency with increase of its vibration level. (G.K.)

  12. 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

  13. Vibration behavior of the artificial barrier system

    Energy Technology Data Exchange (ETDEWEB)

    Mikoshiba, Tadashi; Ogawa, Nobuyuki; Nakamura, Izuru [National Research Inst. for Earth sceince and Disaster Prevention (Japan)

    2000-02-01

    This study aims at production of a mimic specimen of artificial barrier, experimental elucidation of influence of seismic motion due to a vibration experiment on the artificial barrier system, and establishment of an evaluating method on its long-term behavior. The study has been carried out under a cooperative study of the National Research Institute for Earth Science and Disaster Prevention and the Japan Nuclear Cycle Development Institute. In 1998 fiscal year, an artificial barrier specimen initiated by crosscut road was produced, and their random wave and actual seismic wave vibrations were carried out to acquire their fundamental data. As a result of the both vibrations, it was found that in a Case 2 specimen of which buffer material was swelled by poured water, the material was integrated with a mimic over-pack to vibrate under judgement of eigen-frequency, maximum acceleration ratio, and so forth on the test results. And, in a Case 1 specimen, it was thought that the mimic over-pack showed an extreme non-linear performance (soft spring) because of reducing eigen-frequency with increase of its vibration level. (G.K.)

  14. Proactive learning for artificial cognitive systems

    Science.gov (United States)

    Lee, Soo-Young

    2010-04-01

    The Artificial Cognitive Systems (ACS) will be developed for human-like functions such as vision, auditory, inference, and behavior. Especially, computational models and artificial HW/SW systems will be devised for Proactive Learning (PL) and Self-Identity (SI). The PL model provides bilateral interactions between robot and unknown environment (people, other robots, cyberspace). For the situation awareness in unknown environment it is required to receive audiovisual signals and to accumulate knowledge. If the knowledge is not enough, the PL should improve by itself though internet and others. For human-oriented decision making it is also required for the robot to have self-identify and emotion. Finally, the developed models and system will be mounted on a robot for the human-robot co-existing society. The developed ACS will be tested against the new Turing Test for the situation awareness. The Test problems will consist of several video clips, and the performance of the ACSs will be compared against those of human with several levels of cognitive ability.

  15. 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.

  16. A photocatalyst-enzyme coupled artificial photosynthesis system for solar energy in production of formic acid from CO2.

    Science.gov (United States)

    Yadav, Rajesh K; Baeg, Jin-Ook; Oh, Gyu Hwan; Park, No-Joong; Kong, Ki-jeong; Kim, Jinheung; Hwang, Dong Won; Biswas, Soumya K

    2012-07-18

    The photocatalyst-enzyme coupled system for artificial photosynthesis process is one of the most promising methods of solar energy conversion for the synthesis of organic chemicals or fuel. Here we report the synthesis of a novel graphene-based visible light active photocatalyst which covalently bonded the chromophore, such as multianthraquinone substituted porphyrin with the chemically converted graphene as a photocatalyst of the artificial photosynthesis system for an efficient photosynthetic production of formic acid from CO(2). The results not only show a benchmark example of the graphene-based material used as a photocatalyst in general artificial photosynthesis but also the benchmark example of the selective production system of solar chemicals/solar fuel directly from CO(2).

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

    International Nuclear Information System (INIS)

    Plander, I.

    1987-01-01

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

  18. Artificial heart system thermal insulation component development

    International Nuclear Information System (INIS)

    Svedberg, R.C.; Buckman, R.W. Jr.

    1975-01-01

    A concentric cup vacuum multifoil insulation system has been selected by virtue of its size, weight, and thermal performance to insulate the hot radioisotope portion of the thermal converter of an artificial implantable heart system. A factor of 2 improvement in thermal performance, based on the heat loss per number of foil layers (minimum system weight and volume) has been realized over conventional spiral wrapped multifoil vacuum insulation. This improvement is the result of the concentric cup construction to maintain a uniform interfoil spacing and the elimination of corner heat losses. Based on external insulation system dimensions (surface area in contact with host body), heat losses of 0.019 W/ cm 2 at 1140 0 K (1600 0 F) and 0.006 W/cm 2 at 920 0 K (1200 0 F) have been achieved. Factors which influence thermal performance of the nickel foil concentric cup insulation system include the number of cups, configuration and method of application of zirconia (ZrO 2 ) spacer material, system pressure, emittance of the cups, and operating temperature

  19. Distributed Computations Environment Protection Using Artificial Immune Systems

    Directory of Open Access Journals (Sweden)

    A. V. Moiseev

    2011-12-01

    Full Text Available In this article the authors describe possibility of artificial immune systems applying for distributed computations environment protection from definite types of malicious impacts.

  20. Plasmon-enhanced absorption in a metal nanoparticles and photosynthetic molecules hybrid system

    Science.gov (United States)

    Fan, Zhiyuan; Govorov, Alexander

    2010-03-01

    Photosystem I from cyanobacteria is one of nature's most efficient light harvesting complexes, converting light energy into electronic energy with a quantum yield of 100% and an energy yield about 58%. It is very attractive to the nanotechnology community because of its nanoscale dimensions and excellent optoelectronic properties. This protein has the potential to be utilized in devices such as solar cells, electric switches, photo-detectors, etc. However, there is one limiting factor for potential applications of a single monolayer of these photosynthetic proteins. One monolayer absorbs less than 1% of sunlight's energy, despite their excellent optoelectronic properties. Recently, experiments [1] have been conducted to enhance light absorption with the assistance of metal nanoparticles as artificial antenna for the photosystem I. Here, we present a theoretical description of the strong plasmon-assisted interactions between the metal nanoparticles and the optical dipoles of the reaction centers observed in the experiments. The resonance and off-resonance plasmon effects enhance the electromagnetic fields around the photosystem-I molecules and, in this way, lead to enhanced absorption. [4pt] [1] I. Carmeli, I. Lieberman, L. Kraversky, Zhiyuan Fan, A. O. Govorov, G. Markovich, and S. Richter, submitted.

  1. Fault tolerant architecture for artificial olfactory system

    International Nuclear Information System (INIS)

    Lotfivand, Nasser; Hamidon, Mohd Nizar; Abdolzadeh, Vida

    2015-01-01

    In this paper, to cover and mask the faults that occur in the sensing unit of an artificial olfactory system, a novel architecture is offered. The proposed architecture is able to tolerate failures in the sensors of the array and the faults that occur are masked. The proposed architecture for extracting the correct results from the output of the sensors can provide the quality of service for generated data from the sensor array. The results of various evaluations and analysis proved that the proposed architecture has acceptable performance in comparison with the classic form of the sensor array in gas identification. According to the results, achieving a high odor discrimination based on the suggested architecture is possible. (paper)

  2. [Review of wireless energy transmission system for total artificial heart].

    Science.gov (United States)

    Zhang, Chi; Yang, Ming

    2009-11-01

    This paper sums up the fundamental structure of wireless energy transmission system for total artificial heart, and compares the key parameters and performance of some representative systems. After that, it is discussed that the future development trend of wireless energy transmission system for total artificial heart.

  3. 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.

  4. [Artificial intelligence] AI for protection systems

    Energy Technology Data Exchange (ETDEWEB)

    Aggarwal, R.; Johns, A.

    1997-12-31

    The reliable operation of large power systems with small stability margins is highly dependent on control systems and protection devices. Progress in the field of microprocessor systems and demanding requirements in respect of the performance of protective relays are the reasons for digital device applications to power system protection. The superiority of numeric protection over its analogue alternatives is attributed to such factors as accurate extraction of the fundamental voltage and current components through filtering, functional benefits resulting from multi-processor design and extensive self-monitoring, etc. However, all these reasons have not led to a major impact on speed, sensitivity and selectivity of primary protective relays, and the gains are only marginal; this is so because conventional digital relays still rely on deterministic signal models and a heuristic approach for decision making, so that only a fraction of the information contained within voltage and current signals as well as knowledge about the plant to be protected is used. The performance of digital relays may be substantially improved if the decision making is based on elements of artificial intelligence (AI). (Author)

  5. Artificial and bioartificial support systems for liver failure

    DEFF Research Database (Denmark)

    Liu, J P; Gluud, L L; Als-Nielsen, B

    2004-01-01

    Artificial and bioartificial liver support systems may 'bridge' patients with acute or acute-on-chronic liver failure to liver transplantation or recovery.......Artificial and bioartificial liver support systems may 'bridge' patients with acute or acute-on-chronic liver failure to liver transplantation or recovery....

  6. 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...

  7. DEVELOPING A HUMAN CONTROLLED MODEL FOR SAFE ARTIFICIAL INTELLIGENCE SYSTEMS

    OpenAIRE

    KÖSE, Utku

    2018-01-01

    Artificial Intelligence is known as one of the most effective research field of nowadays and the future. But rapid rise of Artificial Intelligence and its potential to solve all real world problems autonomously, it has caused also several anxieties. Some scientists think that intelligent systems can reach to a level, which is dangerous for the humankind so because of that some precautions should be taken. So, many sub-research fields like Machine Ethics or Artificial Intelligence Safety have ...

  8. A Characterization of the Utility of Using Artificial Intelligence to Test Two Artificial Intelligence Systems

    OpenAIRE

    Straub, Jeremy; Huber, Justin

    2013-01-01

    An artificial intelligence system, designed for operations in a real-world environment faces a nearly infinite set of possible performance scenarios. Designers and developers, thus, face the challenge of validating proper performance across both foreseen and unforeseen conditions, particularly when the artificial intelligence is controlling a robot that will be operating in close proximity, or may represent a danger, to humans. While the manual creation of test cases allows limited testing (p...

  9. Applications of artificial intelligence, including expert systems

    International Nuclear Information System (INIS)

    Abbott, M.B.

    1989-01-01

    When Artificial Intelligence is applied to a complex physical system like a nuclear plant it is useful to distinguish between two rather distinct and different intelligent views of such a plant. The first view may be characterised as ''the designer's view''. This is the view of the plant as it was originally conceived and designed; it is essentially a once-and-for-all static view, corresponding to the implicit assumption of an ''ageless plant'', or at most a plant which ages in a preconceived, preset manner. The second view, which may be characterised as ''the operators view'', has to do more with a real-world, ageing plant. It is a more dynamic view, which sees the ageing process as one in which unforeseen, and possibly unforeseeable events may occur at equally unforeseen, and possibly unforeseeable times. The first view is predominantly a way of thinking about the plant, while the second is very often more a way of feeling about it. It should be emphasized that both ways are ways of intelligence. (author)

  10. An Artificial Intelligence-Based Environment Quality Analysis System

    OpenAIRE

    Oprea , Mihaela; Iliadis , Lazaros

    2011-01-01

    Part 20: Informatics and Intelligent Systems Applications for Quality of Life information Services (ISQLIS) Workshop; International audience; The paper describes an environment quality analysis system based on a combination of some artificial intelligence techniques, artificial neural networks and rule-based expert systems. Two case studies of the system use are discussed: air pollution analysis and flood forecasting with their impact on the environment and on the population health. The syste...

  11. Evolution and Adaptation of Phytoplankton Photosynthetic Pathways to perturbations of the geological carbon system

    Science.gov (United States)

    Rickaby, R. E.; Young, J. N.; Hermoso, M.; Heureux, A.; McCLelland, H.; Lee, R.; Eason Hubbard, M.

    2012-12-01

    The ocean and atmosphere carbon system has varied greatly over geological history both in response to initial evolutionary innovation, and as a driver of adaptive change. Here we establish that positive selection in Rubisco, the most abundant enzyme on the Earth responsible for all photosynthetic carbon fixation, occurred early in Earth's history, and basal to the radiation of the modern marine algal groups. Our signals of positive selection appear to be triggered by changing intracellular concentrations of carbon dioxide (CO2) due to the emergence of carbon concentrating mechanisms between 1.56 and 0.41 Ba in response to declining atmospheric CO2 . We contend that, at least in terms of carbon, phytoplankton generally were well poised to manage subsequent abrupt carbon cycle perturbations. The physiological pathways for optimising carbon acquisition across a wide range of ambient carbon dioxide concentrations had already been established and were genetically widespread across open ocean phytoplankton groups. We will further investigate some case studies from the Mesozoic and Cenozoic abrupt carbon cycle excursions using isotopic tools to probe the community photosynthetic response and demonstrate the flexibility of phytoplankton photosynthesis in the face of major perturbations. In particular, an unprecedented resolution record across the Toarcian (Early Jurassic) carbon isotope excursion in the Paris Basin reveals a selection and evolution towards a community reliant solely on diffusive carbon dioxide supply for photosynthesis at the height of the excursion at 1500-2500 ppm CO2. The continued flourishing of the phytoplankton biological pump throughout this excursion was able to remove the excess carbon injected into the water column in less than 45 kyrs.

  12. Analyze of the Measuring Performance for Artificially Business Intelligent Systems

    OpenAIRE

    Vatuiu, Teodora

    2007-01-01

    This paper analyzes the measuring performance of artificially business intelligent systems. Thousands of persons-years have been devoted to the research and development in the vari¬ous aspects of artificially intelligent systems. Much progress has been attained. However, there has been no means of evaluating the progress of the field. How can we assess the cur¬rent state of the science? Most of business intelligent systems are beginning to be deployed commercially. How can a commercial buyer ...

  13. Building Artificial Vision Systems with Machine Learning

    Energy Technology Data Exchange (ETDEWEB)

    LeCun, Yann [New York University

    2011-02-23

    Three questions pose the next challenge for Artificial Intelligence (AI), robotics, and neuroscience. How do we learn perception (e.g. vision)? How do we learn representations of the perceptual world? How do we learn visual categories from just a few examples?

  14. Stereoselective phytotoxicity of HCH mediated by photosynthetic and antioxidant defense systems in Arabidopsis thaliana.

    Science.gov (United States)

    Zhang, Qiong; Zhou, Cong; Zhang, Quan; Qian, Haifeng; Liu, Weiping; Zhao, Meirong

    2013-01-01

    Hexachlorocyclohexane (HCH) has been used for plant protection and sanitation world-widely, and its isomers have been detected in water, soil, and air as well as in vegetation. As a sink for lipophilic pollutants, vegetation is very important for the degradation and fate of organic contamination; however, little was known about their phytotoxicity and mechanisms of toxic effect. In this study, the stereoselective phototoxicity of four isomers (α, β, γ, and δ) of HCHs mediated by independent as well as interconnecting systems of photosynthesis and enzymatic antioxidant defense system in Arabidopsis thaliana were assessed. Our results revealed that all the HCHs not only stimulated the activities of catalase (CAT) and peroxidase (POD), but also inhibited the activity of superoxide dismutase (SOD). In photosynthesis system, the photosynthetic efficiency of PSI and PSII were all down regulated. Meanwhile, results from both systems showed that δ-HCH was the most toxic one, while α-HCH the least in Arabidopsis thaliana. For the first time, stereoselective effects of different isomers of HCH in plant were demonstrated. And the results suggest that it requires further research to fully elucidate the environmental toxicity and their mechanisms.

  15. Stereoselective phytotoxicity of HCH mediated by photosynthetic and antioxidant defense systems in Arabidopsis thaliana.

    Directory of Open Access Journals (Sweden)

    Qiong Zhang

    Full Text Available BACKGROUND: Hexachlorocyclohexane (HCH has been used for plant protection and sanitation world-widely, and its isomers have been detected in water, soil, and air as well as in vegetation. As a sink for lipophilic pollutants, vegetation is very important for the degradation and fate of organic contamination; however, little was known about their phytotoxicity and mechanisms of toxic effect. In this study, the stereoselective phototoxicity of four isomers (α, β, γ, and δ of HCHs mediated by independent as well as interconnecting systems of photosynthesis and enzymatic antioxidant defense system in Arabidopsis thaliana were assessed. PRINCIPAL FINDINGS: Our results revealed that all the HCHs not only stimulated the activities of catalase (CAT and peroxidase (POD, but also inhibited the activity of superoxide dismutase (SOD. In photosynthesis system, the photosynthetic efficiency of PSI and PSII were all down regulated. Meanwhile, results from both systems showed that δ-HCH was the most toxic one, while α-HCH the least in Arabidopsis thaliana. CONCLUSIONS: For the first time, stereoselective effects of different isomers of HCH in plant were demonstrated. And the results suggest that it requires further research to fully elucidate the environmental toxicity and their mechanisms.

  16. Chlorophyll fluorescence analysis revealed essential roles of FtsH 11 protease in regulation of the adaptive responses of photosynthetic systems to high temperature

    Science.gov (United States)

    Background: Photosynthetic systems are known to be sensitive to high temperature stress. To maintain a relatively “normal” level of photosynthetic activities, plants employ a variety of adaptive mechanisms in response to environmental temperature fluctuations. Previously, we reported that the chloro...

  17. Credit Risk Evaluation System For Nigerian Banks Using Artificial Ne

    African Journals Online (AJOL)

    MANKABS

    CREDIT RISK EVALUATION SYSTEM: AN ARTIFICIAL NEURAL NETWORK APPROACH of their own experiential .... limitations concern the high computational ... Number of existing credits at this bank. 7. Personal status and sex. 14. Job. 17.

  18. A Characterization of the Utility of Using Artificial Intelligence to Test Two Artificial Intelligence Systems

    Directory of Open Access Journals (Sweden)

    Jeremy Straub

    2013-05-01

    Full Text Available An artificial intelligence system, designed for operations in a real-world environment faces a nearly infinite set of possible performance scenarios. Designers and developers, thus, face the challenge of validating proper performance across both foreseen and unforeseen conditions, particularly when the artificial intelligence is controlling a robot that will be operating in close proximity, or may represent a danger, to humans. While the manual creation of test cases allows limited testing (perhaps ensuring that a set of foreseeable conditions trigger an appropriate response, this may be insufficient to fully characterize and validate safe system performance. An approach to validating the performance of an artificial intelligence system using a simple artificial intelligence test case producer (AITCP is presented. The AITCP allows the creation and simulation of prospective operating scenarios at a rate far exceeding that possible by human testers. Four scenarios for testing an autonomous navigation control system are presented: single actor in two-dimensional space, multiple actors in two-dimensional space, single actor in three-dimensional space, and multiple actors in three-dimensional space. The utility of using the AITCP is compared to that of human testers in each of these scenarios.

  19. Systems with artificial intelligence in nuclear power plant operation

    International Nuclear Information System (INIS)

    Bastl, W.; Felkel, L.

    1989-01-01

    The authors first summarize some developments made by GRS teams which can be regarded as the precursors of systems with artificial intelligence, and explain the basic characteristics of artificial intelligence, referring in particular to possible applications in nuclear engineering. The systems described are arranged in four groups according to applicability as follows: plant diagnosis and failure analysis, information systems and operating systems, control systems, assessment and decision aids. The working principle of the systems is explained by some examples giving details of the database and the interference processes. (orig./DG) [de

  20. Cotton growth potassium deficiency stress is influenced by photosynthetic apparatus and root system

    International Nuclear Information System (INIS)

    Hussain, Z.U.; Arshad, M.

    2010-01-01

    Due to rapid depletion of soil potassium (K) and increasing cost of K fertilizers in Pakistan, the K-use efficient crop genotypes become very important for agricultural sustain ability. However, limited research has been done on this important issue particularly in cotton, an important fibre crop. We studied the growth and biomass production of three cotton genotypes (CIM-506, NIAB- 78 and NIBGE-2) different in K-use efficiency in a K-deficient solution culture. Genotypes differed significantly for biomass production, absolute growth rates (shoot, root, leaf, total), leaf area, mean leaf area and relative growth rate of leaf under K deficiency stress, besides specific leaf area. The relative growth rate (shoot, root, total) did not differ significantly, except for leaf. For all these characters, NIBGE-2 was the best performer followed by NIAB-78 and CIM-506. Shoot dry weight was significantly related with (in decreasing order of significance): mean leaf area, leaf dry weight, leaf area, root dry weight, absolute growth rate of shoot, absolute growth rate of root, absolute growth rate total, absolute growth rate root, relative growth rate leaf, relative growth rate total and relative growth rate shoot. Hence, the enhanced biomass accumulation of cotton genotypes under K deficiency stress is related to their efficient photosynthetic apparatus and root system, appeared to be the most important morphological markers while breeding for K-use efficient cotton genotypes.(author)

  1. Knowledge in Artificial Intelligence Systems: Searching the Strategies for Application

    OpenAIRE

    Kornienko, Alla A.; Kornienko, Anatoly V.; Fofanov, Oleg B.; Chubik, Maxim P.

    2015-01-01

    The studies based on auto-epistemic logic are pointed out as an advanced direction for development of artificial intelligence (AI). Artificial intelligence is taken as a system that imitates the solution of complicated problems by human during the course of life. The structure of symbols and operations, by which intellectual solution is performed, as well as searching the strategic reference points for those solutions, which are caused by certain structures of symbols and operations, – are co...

  2. SOME PARADIGMS OF ARTIFICIAL INTELLIGENCE IN FINANCIAL COMPUTER SYSTEMS

    Directory of Open Access Journals (Sweden)

    Jerzy Balicki

    2015-12-01

    Full Text Available The article discusses some paradigms of artificial intelligence in the context of their applications in computer financial systems. The proposed approach has a significant po-tential to increase the competitiveness of enterprises, including financial institutions. However, it requires the effective use of supercomputers, grids and cloud computing. A reference is made to the computing environment for Bitcoin. In addition, we characterized genetic programming and artificial neural networks to prepare investment strategies on the stock exchange market.

  3. SOME PARADIGMS OF ARTIFICIAL INTELLIGENCE IN FINANCIAL COMPUTER SYSTEMS

    OpenAIRE

    Jerzy Balicki

    2015-01-01

    The article discusses some paradigms of artificial intelligence in the context of their applications in computer financial systems. The proposed approach has a significant po-tential to increase the competitiveness of enterprises, including financial institutions. However, it requires the effective use of supercomputers, grids and cloud computing. A reference is made to the computing environment for Bitcoin. In addition, we characterized genetic programming and artificial neural networks to p...

  4. An artificial odor recognition system is developed for discriminating odors

    Directory of Open Access Journals (Sweden)

    Wisnu Jatmiko

    2002-12-01

    Full Text Available This artificial system consisted of 16 quartz resonator crystals as the sensor array, a frequency modulator and a frequency counter for each sensor that are connected directly to a microcomputer. We have already shown that the artificial odor recognition system with 4 sensors is high enough to discriminate simple odor correctly, however, when it was used to discriminate compound odors, the recognition capability of this system is dropped significantly to be about 40%. Results of experiments show that the developed artificial system with 16 sensors could discriminate compound aroma based on 6 gradient of alcohol concentrations with high recognition rate of 89.9% for non batch processing system, and 82.4% for batch processing of the classes of odors.

  5. Role-based Rights in Artificial Social Systems

    NARCIS (Netherlands)

    G. Boella (Guido); L.W.N. van der Torre (Leon)

    2005-01-01

    htmlabstract In this paper we use normative systems to introduce roles and rights in the game-theoretic artificial social systems developed by Shoham and Tennenholtz. We model normative systems as socially constructed agents whose behavior is determined by a set of role playing agents. Roles are

  6. Artificial light and quantum order in systems of screened dipoles

    International Nuclear Information System (INIS)

    Wen Xiaogang

    2003-01-01

    The origin of light is an unsolved mystery in nature. Recently, it was suggested that light may originate from a new kind of order, quantum order. To test this idea in experiments, we study systems of screened magnetic/electric dipoles in two-dimensional (2D) and 3D lattices. We show that our models contain an artificial light-a photonlike collective excitation. We discuss how to design realistic devices that realize our models. We show that the 'speed of light' and the 'fine-structure constant' of the artificial light can be tuned in our models. The properties of artificial atoms (bound states of pairs of artificial charges) are also discussed. The existence of artificial light (as well as artificial electron) in condensed-matter systems suggests that elementary particles, such as light and electron, may not be elementary. They may be collective excitations of quantum order in our vacuum. In our model, light is realized as a fluctuation of string-nets and charges as the ends of open strings (or nodes of string nets)

  7. Advanced solutions in power systems HVDC, facts, and artificial intelligence

    CERN Document Server

    Liu, Chen-Ching; Edris, Abdel-Aty

    2016-01-01

    Provides insight on both classical means and new trends in the application of power electronic and artificial intelligence techniques in power system operation and control This book presents advanced solutions for power system controllability improvement, transmission capability enhancement and operation planning. The book is organized into three parts. The first part describes the CSC-HVDC and VSC-HVDC technologies, the second part presents the FACTS devices, and the third part refers to the artificial intelligence techniques. All technologies and tools approached in this book are essential for power system development to comply with the smart grid requirements.

  8. 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.

  9. Response of the photosynthetic system to altered protein composition and changes in environmental conditions

    NARCIS (Netherlands)

    Tóth, T.

    2014-01-01

    The photosynthetic thylakoid membrane has a hierarchically ordered structure containing pigment-protein complexes that capture solar radiation and convert it into chemical energy. Its highly dynamic structure is capable to continuously respond to the altered environmental conditions, e.g., light

  10. System to determine leaf photosynthetic activity by means of 14CO2

    International Nuclear Information System (INIS)

    Fernandez Gonzalez, J.

    1977-01-01

    A method to determine leaf photosynthetic activity is described. 14 CO 2 labeled air is produced from 14 CO 3 Ba and stored in a poliethylene balloon and supplied by means of an automatic dispenser to a perspex chamber inside of which is the leaf. (author) [es

  11. Systems in Science: Modeling Using Three Artificial Intelligence Concepts.

    Science.gov (United States)

    Sunal, Cynthia Szymanski; Karr, Charles L.; Smith, Coralee; Sunal, Dennis W.

    2003-01-01

    Describes an interdisciplinary course focusing on modeling scientific systems. Investigates elementary education majors' applications of three artificial intelligence concepts used in modeling scientific systems before and after the course. Reveals a great increase in understanding of concepts presented but inconsistent application. (Author/KHR)

  12. VAR control in distribution systems by using artificial intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Golkar, M.A. [Curtin Univ. of Technology, Sarawak (Malaysia). School of Engineering and Science

    2005-07-01

    This paper reviewed artificial intelligence techniques used in VAR control systems. Reactive power controls in distribution systems were also reviewed. While artificial intelligence methods are widely used in power control systems, the techniques require extensive human knowledge bases and experiences in order to operate correctly. Expert systems use knowledge and interface procedures to solve problems that often require human expertise. Expert systems often cause knowledge bottlenecks as they are unable to learn or adopt to new situations. While neural networks possess learning ability, they are computationally expensive. However, test results in recent neural network studies have demonstrated that they work well in a variety of loading conditions. Fuzzy logic techniques are used to accurately represent the operational constraints of power systems. Fuzzy logic has an advantage over other artificial intelligence techniques as it is able to remedy uncertainties in data. Evolutionary computing algorithms use probabilistic transition rules which can search complicated data to determine optimal constraints and parameters. Over 95 per cent of all papers published on power systems use genetic algorithms. It was concluded that hybrid systems using various artificial intelligence techniques are now being used by researchers. 69 refs.

  13. Stability of Bifurcating Stationary Solutions of the Artificial Compressible System

    Science.gov (United States)

    Teramoto, Yuka

    2018-02-01

    The artificial compressible system gives a compressible approximation of the incompressible Navier-Stokes system. The latter system is obtained from the former one in the zero limit of the artificial Mach number ɛ which is a singular limit. The sets of stationary solutions of both systems coincide with each other. It is known that if a stationary solution of the incompressible system is asymptotically stable and the velocity field of the stationary solution satisfies an energy-type stability criterion, then it is also stable as a solution of the artificial compressible one for sufficiently small ɛ . In general, the range of ɛ shrinks when the spectrum of the linearized operator for the incompressible system approaches to the imaginary axis. This can happen when a stationary bifurcation occurs. It is proved that when a stationary bifurcation from a simple eigenvalue occurs, the range of ɛ can be taken uniformly near the bifurcation point to conclude the stability of the bifurcating solution as a solution of the artificial compressible system.

  14. Carbon dioxide fixation by artificial photosynthesis

    Energy Technology Data Exchange (ETDEWEB)

    Ibusuki, Takashi; Koike, Kazuhide; Ishitani, Osamu [National Inst. for Resources and Environment, AIST, MITI, Tsukuba, Ibaraki (Japan)

    1993-12-31

    Green plants can absorb atmospheric CO{sub 2} and transform it to sugars, carbohydrates through their photosynthetic systems, but they become the source of CO{sub 2} when they are dead. This is the reason why artificial leaves which can be alive forever should be developed to meet with global warming due to the increase of CO{sub 2} concentration. The goal of artificial photosynthesis is not to construct the same system as the photosynthetic one, but to mimic the ability of green plants to utilize solar energy to make high energy chemicals. Needless to say, the artificial photosynthetic system is desired to be as simple as possible and to be as efficient as possible. From the knowledge on photosynthesis and the results of previous investigations, the critical components of artificial photosynthetic system are understood as follows: (1) light harvesting chromophore, (2) a center for electron transfer and charge separation, (3) catalytic sites for converting small molecules like water and CO{sub 2} (mutilelectron reactions) which are schematically described.

  15. Glucose Synthesis in a Protein-Based Artificial Photosynthesis System.

    Science.gov (United States)

    Lu, Hao; Yuan, Wenqiao; Zhou, Jack; Chong, Parkson Lee-Gau

    2015-09-01

    The objective of this study was to understand glucose synthesis of a protein-based artificial photosynthesis system affected by operating conditions, including the concentrations of reactants, reaction temperature, and illumination. Results from non-vesicle-based glyceraldehyde-3-phosphate (GAP) and glucose synthesis showed that the initial concentrations of ribulose-1,5-bisphosphate (RuBP) and adenosine triphosphate (ATP), lighting source, and temperature significantly affected glucose synthesis. Higher initial concentrations of RuBP and ATP significantly enhanced GAP synthesis, which was linearly correlated to glucose synthesis, confirming the proper functions of all catalyzing enzymes in the system. White fluorescent light inhibited artificial photosynthesis and reduced glucose synthesis by 79.2 % compared to in the dark. The reaction temperature of 40 °C was optimum, whereas lower or higher temperature reduced glucose synthesis. Glucose synthesis in the vesicle-based artificial photosynthesis system reconstituted with bacteriorhodopsin, F 0 F 1 ATP synthase, and polydimethylsiloxane-methyloxazoline-polydimethylsiloxane triblock copolymer was successfully demonstrated. This system efficiently utilized light-induced ATP to drive glucose synthesis, and 5.2 μg ml(-1) glucose was synthesized in 0.78-ml reaction buffer in 7 h. Light-dependent reactions were found to be the bottleneck of the studied artificial photosynthesis system.

  16. Thermocompressor powered artificial heart assist system

    International Nuclear Information System (INIS)

    Moise, J.C.; Rudnicki, M.I.; Faeser, R.J.

    1975-01-01

    The development of a fully implantable, left ventricular assist system is described. The system utilizes a radioisotope-powered Stirling cycle thermocompressor and an all-pneumatic actuation and control system to drive a pusher-plate type blood pump. This basic approach has been shown to be efficient and workable by implantation experiments on calves. The recent effort has been directed toward the fabrication and development of a fourth-generation system, designed to reduce weight, volume and isotope inventory. Extensive endurance and accelerated-life testing has been undertaken. The improved design concepts utilized in the system and pertinent test results are discussed

  17. Evaluating neural networks and artificial intelligence systems

    Science.gov (United States)

    Alberts, David S.

    1994-02-01

    Systems have no intrinsic value in and of themselves, but rather derive value from the contributions they make to the missions, decisions, and tasks they are intended to support. The estimation of the cost-effectiveness of systems is a prerequisite for rational planning, budgeting, and investment documents. Neural network and expert system applications, although similar in their incorporation of a significant amount of decision-making capability, differ from each other in ways that affect the manner in which they can be evaluated. Both these types of systems are, by definition, evolutionary systems, which also impacts their evaluation. This paper discusses key aspects of neural network and expert system applications and their impact on the evaluation process. A practical approach or methodology for evaluating a certain class of expert systems that are particularly difficult to measure using traditional evaluation approaches is presented.

  18. Artificial intelligence system for technical diagnostics of photomasks

    OpenAIRE

    Kozin A. A.; Kozina Yu. Yu.

    2012-01-01

    The developed artificial intelligence system has a high level of noise immunity, so its inclusion in the hardware and software for technical diagnostics of photomasks will reduce the hardware requirements for its execution, and thereby reduce the cost of the complex. As a result it will allow to make a small-scale production profitable.

  19. Artificial intelligence system for technical diagnostics of photomasks

    Directory of Open Access Journals (Sweden)

    Kozin A. A.

    2012-02-01

    Full Text Available The developed artificial intelligence system has a high level of noise immunity, so its inclusion in the hardware and software for technical diagnostics of photomasks will reduce the hardware requirements for its execution, and thereby reduce the cost of the complex. As a result it will allow to make a small-scale production profitable.

  20. An Artificial Intelligence-Based Distance Education System: Artimat

    Science.gov (United States)

    Nabiyev, Vasif; Karal, Hasan; Arslan, Selahattin; Erumit, Ali Kursat; Cebi, Ayca

    2013-01-01

    The purpose of this study is to evaluate the artificial intelligence-based distance education system called ARTIMAT, which has been prepared in order to improve mathematical problem solving skills of the students, in terms of conceptual proficiency and ease of use with the opinions of teachers and students. The implementation has been performed…

  1. Nucleocytoplasmic Transport: A Paradigm for Molecular Logistics in Artificial Systems.

    Science.gov (United States)

    Vujica, Suncica; Zelmer, Christina; Panatala, Radhakrishnan; Lim, Roderick Y H

    2016-01-01

    Artificial organelles, molecular factories and nanoreactors are membrane-bound systems envisaged to exhibit cell-like functionality. These constitute liposomes, polymersomes or hybrid lipo-polymersomes that display different membrane-spanning channels and/or enclose molecular modules. To achieve more complex functionality, an artificial organelle should ideally sustain a continuous influx of essential macromolecular modules (i.e. cargoes) and metabolites against an outflow of reaction products. This would benefit from the incorporation of selective nanopores as well as specific trafficking factors that facilitate cargo selectivity, translocation efficiency, and directionality. Towards this goal, we describe how proteinaceous cargoes are transported between the nucleus and cytoplasm by nuclear pore complexes and the biological trafficking machinery in living cells (i.e. nucleocytoplasmic transport). On this basis, we discuss how biomimetic control may be implemented to selectively import, compartmentalize and accumulate diverse macromolecular modules against concentration gradients in artificial organelles.

  2. Emergent Properties in Natural and Artificial Dynamical Systems

    CERN Document Server

    Aziz-Alaoui, M.A

    2006-01-01

    An important part of the science of complexity is the study of emergent properties arising through dynamical processes in various types of natural and artificial systems. This is the aim of this book, which is the outcome of a discussion meeting within the first European conference on complex systems. It presents multidisciplinary approaches for getting representations of complex systems and using different methods to extract emergent structures. This carefully edited book studies emergent features such as self organization, synchronization, opening on stability and robustness properties. Invariant techniques are presented which can express global emergent properties in dynamical and in temporal evolution systems. This book demonstrates how artificial systems such as a distributed platform can be used for simulation used to search emergent placement during simulation execution.

  3. Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

    Science.gov (United States)

    Huntsberger, Terry

    2011-01-01

    The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

  4. An artificial intelligence system for reliability studies

    International Nuclear Information System (INIS)

    Llory, M.; Ancelin, C.; Bannelier, M.; Bouhadana, H.; Bouissou, M.; Lucas, J.Y.; Magne, L.; Villate, N.

    1990-01-01

    The EDF (French Electricity Company) software developed for computer aided reliability studies is considered. Such software tools were applied in the study of the safety requirements of the Paluel nuclear power plant. The reliability models, based on IF-THEN type rules, and the generation of models by the expert system are described. The models are then processed applying algorithm structures [fr

  5. Educational Game Systems in Artificial Intelligence Course

    Science.gov (United States)

    Chubarkova, Elena V.; Sadchikov, Ilya A.; Suslova, Irina A.; Tsaregorodtsev, Andrey ?.; Milova, Larisa N.

    2016-01-01

    Article actuality based on fact that existing knowledge system aimed at future professional life of students: a skillful use game activity in educational process will teach students to look for alternative ways solving of real problems. The purpose of article lies in theoretical substantiation, development and testing of criteria, which must be…

  6. Control system for an artificial heart

    Science.gov (United States)

    Gebben, V. D.; Webb, J. A., Jr.

    1970-01-01

    Inexpensive industrial pneumatic components are combined to produce control system to drive sac-type heart-assistance blood pump with controlled pulsatile pressure that makes pump rate of flow sensitive to venous /atrial/ pressure, while stroke is centered about set operating point and pump is synchronized with natural heart.

  7. Computer Vision for Artificially Intelligent Robotic Systems

    Science.gov (United States)

    Ma, Chialo; Ma, Yung-Lung

    1987-04-01

    In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts -- position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed bye the main control unit. In Pulse-Echo Signal Process Unit, we ultilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by u law coding method, and this data together with delay time T, angle information OH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main

  8. Artificial Intelligence at Advanced Information and Decision Systems

    OpenAIRE

    McCune, Brian P.

    1981-01-01

    Advanced Information and Decision Systems (AI-DS) is a relatively new, employee-owned company that does basic and applied research, product development, and consulting in the fields of artificial intelligence, computer science, decision analysis, operations research, control theory, estimation theory, and signal processing. AI&DS performs studies, analyses, systems design and evaluation, and software development for a variety of industrial clients and government agencies, including the Depart...

  9. Contrasting Responses of Marine and Freshwater Photosynthetic Organisms to UVB Radiation: A Meta-Analysis

    KAUST Repository

    Jin, Peng; Duarte, Carlos M.; Agusti, Susana

    2017-01-01

    artificial lamps. We found that marine photosynthetic organisms tend to be more sensitive than freshwater photosynthetic organisms to UVB radiation; responses to either decreased or increased UVB radiation vary among taxa; the mortality rate is the most

  10. On the photosynthetic and devlopmental responses of leaves to the spectral composition of light

    NARCIS (Netherlands)

    Hogewoning, S.W.

    2010-01-01

    Key words: action spectrum, artificial solar spectrum, blue light, Cucumis sativus, gas-exchange, light-emitting diodes (LEDs), light interception, light quality, non-photosynthetic pigments, photo-synthetic capacity, photomorphogenesis, photosystem excitation balance, quantum yield, red light.

  11. ARTIFICIAL NEURAL NETWORKS BASED GEARS MATERIAL SELECTION HYBRID INTELLIGENT SYSTEM

    Institute of Scientific and Technical Information of China (English)

    X.C. Li; W.X. Zhu; G. Chen; D.S. Mei; J. Zhang; K.M. Chen

    2003-01-01

    An artificial neural networks(ANNs) based gear material selection hybrid intelligent system is established by analyzing the individual advantages and weakness of expert system (ES) and ANNs and the applications in material select of them. The system mainly consists of tow parts: ES and ANNs. By being trained with much data samples,the back propagation (BP) ANN gets the knowledge of gear materials selection, and is able to inference according to user input. The system realizes the complementing of ANNs and ES. Using this system, engineers without materials selection experience can conveniently deal with gear materials selection.

  12. Using Artificial Intelligence Techniques to Implement a Multifactor Authentication System

    Directory of Open Access Journals (Sweden)

    Jackson Phiri

    2011-08-01

    Full Text Available The recent years have seen a rise in the number of cases of cyber-crime committed through identity theft and fraud. To address this problem, this paper uses adaptive neural-fuzzy inference system, fuzzy logic and artificial neural network to implement a multifactor authentication system through a technique of information fusion. To begin with, the identity attributes are mined using the three corpora from three major sources namely the social networks, a set of questionnaires and application forms from the various services offered both in the real and cyberspace. The statistical information generated by the corpora is then used to compose an identity attribute metric model. The composed identity attributes metrics values classified as biometrics, device metrics and pseudo metrics are then fused at the score level through a technique of information fusion in a multifactor authentication system by using each of the above artificial intelligence technologies and the results compared.

  13. Applications Of Artificial Intelligence In Control System Analysis And Design

    Science.gov (United States)

    Birdwell, J. D.

    1987-10-01

    To date, applications of artificial intelligence in control system analysis and design are primarily associated with the design process. These applications take the form of knowledge bases incorporating expertise on a design method, such as multivariable linear controller design, or on a field such as identification. My experience has demonstrated that, while such expert systems are useful, perhaps a greater benefit will come from applications in the maintenance of technical databases, as are found in real-time data acquisition systems, and of modeling and design databases, which represent the status of a computer-aided design process for a human user. This reflects the observation that computers are best at maintaining relations about large sets of objects, whereas humans are best at maintaining knowledge of depth, as occurs when a design option involving a sequence of steps is explored. This paper will discuss some of these issues, and will provide some examples which illustrate the potential of artificial intelligence.

  14. Effects of artificial gravity on the cardiovascular system: Computational approach

    Science.gov (United States)

    Diaz Artiles, Ana; Heldt, Thomas; Young, Laurence R.

    2016-09-01

    Artificial gravity has been suggested as a multisystem countermeasure against the negative effects of weightlessness. However, many questions regarding the appropriate configuration are still unanswered, including optimal g-level, angular velocity, gravity gradient, and exercise protocol. Mathematical models can provide unique insight into these questions, particularly when experimental data is very expensive or difficult to obtain. In this research effort, a cardiovascular lumped-parameter model is developed to simulate the short-term transient hemodynamic response to artificial gravity exposure combined with ergometer exercise, using a bicycle mounted on a short-radius centrifuge. The model is thoroughly described and preliminary simulations are conducted to show the model capabilities and potential applications. The model consists of 21 compartments (including systemic circulation, pulmonary circulation, and a cardiac model), and it also includes the rapid cardiovascular control systems (arterial baroreflex and cardiopulmonary reflex). In addition, the pressure gradient resulting from short-radius centrifugation is captured in the model using hydrostatic pressure sources located at each compartment. The model also includes the cardiovascular effects resulting from exercise such as the muscle pump effect. An initial set of artificial gravity simulations were implemented using the Massachusetts Institute of Technology (MIT) Compact-Radius Centrifuge (CRC) configuration. Three centripetal acceleration (artificial gravity) levels were chosen: 1 g, 1.2 g, and 1.4 g, referenced to the subject's feet. Each simulation lasted 15.5 minutes and included a baseline period, the spin-up process, the ergometer exercise period (5 minutes of ergometer exercise at 30 W with a simulated pedal cadence of 60 RPM), and the spin-down process. Results showed that the cardiovascular model is able to predict the cardiovascular dynamics during gravity changes, as well as the expected

  15. Melatonin immunoreactivity in the photosynthetic prokaryote Rhodospirillum rubrum: implications for an ancient antioxidant system.

    Science.gov (United States)

    Manchester, L C; Poeggeler, B; Alvares, F L; Ogden, G B; Reiter, R J

    1995-01-01

    Rhodospirillum rubrum is a spiral anoxygenic photosynthetic bacterium that can exist under either aerobic or anaerobic conditions. The organism thrives in the presence of light or complete darkness and represents one of the oldest species of living organisms, possibly 2-3.5 billion years old. The success of this prokaryotic species may be attributed to the evolution of certain indole compounds that offer protection against life-threatening oxygen radicals produced by an evolutionary harsh environment. Melatonin, N-acetyl-5-methoxytryptamine, is an indolic highly conserved molecule that exists in protists, plants, and animals. This study was undertaken to determine the presence of an immunoreactive melatonin in the kingdom Monera and particularly in the photosynthetic bacterium, R. rubrum, under conditions of prolonged darkness or prolonged light. Immunoreactive melatonin was measured during both the extended day and extended night. Significantly more melatonin was observed during the scotophase than the photophase. This study marks the first demonstration of melatonin in a bacterium. The high level of melatonin observed in bacteria may provide on-site protection of bacterial DNA against free radical attack.

  16. Optimal approximation of linear systems by artificial immune response

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    This paper puts forward a novel artificial immune response algorithm for optimal approximation of linear systems. A quaternion model of artificial immune response is proposed for engineering computing. The model abstracts four elements, namely, antigen, antibody, reaction rules among antibodies, and driving algorithm describing how the rules are applied to antibodies, to simulate the process of immune response. Some reaction rules including clonal selection rules, immunological memory rules and immune regulation rules are introduced. Using the theorem of Markov chain, it is proofed that the new model is convergent. The experimental study on the optimal approximation of a stable linear system and an unstable one show that the approximate models searched by the new model have better performance indices than those obtained by some existing algorithms including the differential evolution algorithm and the multi-agent genetic algorithm.

  17. Artificial intelligence, expert systems, computer vision, and natural language processing

    Science.gov (United States)

    Gevarter, W. B.

    1984-01-01

    An overview of artificial intelligence (AI), its core ingredients, and its applications is presented. The knowledge representation, logic, problem solving approaches, languages, and computers pertaining to AI are examined, and the state of the art in AI is reviewed. The use of AI in expert systems, computer vision, natural language processing, speech recognition and understanding, speech synthesis, problem solving, and planning is examined. Basic AI topics, including automation, search-oriented problem solving, knowledge representation, and computational logic, are discussed.

  18. Artificial intelligence and dynamic systems for geophysical applications

    CERN Document Server

    Gvishiani, Alexei

    2002-01-01

    The book presents new clustering schemes, dynamical systems and pattern recognition algorithms in geophysical, geodynamical and natural hazard applications. The original mathematical technique is based on both classical and fuzzy sets models. Geophysical and natural hazard applications are mostly original. However, the artificial intelligence technique described in the book can be applied far beyond the limits of Earth science applications. The book is intended for research scientists, tutors, graduate students, scientists in geophysics and engineers

  19. Artefact: the division of artificial intelligence, robotics and expert systems

    Energy Technology Data Exchange (ETDEWEB)

    Ferber, J

    1983-06-01

    The history of artificial intelligence is traced from its beginnings in 1956 to its current coverage of the areas of problem-solving, expert systems and games, natural-language processing, robotics, picture and speech recognition, automatic programming, and computer-aided design and instruction. Each area is reviewed in turn, programming languages and techniques are discussed, and both apocalyptic forecasts and underestimates of future developments are criticised.

  20. Should fully autonomous artificial intelligence systems be granted legal capacity?

    OpenAIRE

    Naučius, Mindaugas

    2018-01-01

    The aim of this article is to address the issue of granting legal capacity to artificial inteligence systems. In order to approach the solution to the problem addressed, the article includes several aspects, relevant in order to achieve it. To begin with, the general concept of legal capacity is introduced. Following this aspect, the main features of both natural and juridical persons are addressed, in order to become familiar with the content of legal capacity, or in other words, to be aware...

  1. Solving Complex Logistics Problems with Multi-Artificial Intelligent System

    Directory of Open Access Journals (Sweden)

    Y.K. Tse

    2009-10-01

    Full Text Available The economy, which has become more information intensive, more global and more technologically dependent, is undergoing dramatic changes. The role of logistics is also becoming more and more important. In logistics, the objective of service providers is to fulfill all customers? demands while adapting to the dynamic changes of logistics networks so as to achieve a higher degree of customer satisfaction and therefore a higher return on investment. In order to provide high quality service, knowledge and information sharing among departments becomes a must in this fast changing market environment. In particular, artificial intelligence (AI technologies have achieved significant attention for enhancing the agility of supply chain management, as well as logistics operations. In this research, a multi-artificial intelligence system, named Integrated Intelligent Logistics System (IILS is proposed. The objective of IILS is to provide quality logistics solutions to achieve high levels of service performance in the logistics industry. The new feature of this agile intelligence system is characterized by the incorporation of intelligence modules through the capabilities of the case-based reasoning, multi-agent, fuzzy logic and artificial neural networks, achieving the optimization of the performance of organizations.

  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. Validation of artificial skin equivalents as in vitro testing systems

    Science.gov (United States)

    Schmitt, Robert; Marx, Ulrich; Walles, Heike; Schober, Lena

    2011-03-01

    With the increasing complexity of the chemical composition of pharmaceuticals, cosmetics and everyday substances, the awareness of potential health issues and long term damages for humanoid organs is shifting into focus. Artificial in vitro testing systems play an important role in providing reliable test conditions and replacing precarious animal testing. Especially artificial skin equivalents ASEs are used for a broad spectrum of studies like penetration, irritation and corrosion of substances. One major challenge in tissue engineering is the qualification of each individual ASE as in vitro testing system. Due to biological fluctuations, the stratum corneum hornified layer of some ASEs may not fully develop or other defects might occur. For monitoring these effects we developed an fully automated Optical Coherence Tomography device. Here, we present different methods to characterize and evaluate the quality of the ASEs based on image and data processing of OCT B-scans. By analysing the surface structure, defects, like cuts or tears, are detectable. A further indicator for the quality of the ASE is the morphology of the tissue. This allows to determine if the skin model has reached the final growth state. We found, that OCT is a well suited technology for automatically characterizing artificial skin equivalents and validating the application as testing system.

  4. Multisensor system and artificial intelligence in housing for the elderly.

    Science.gov (United States)

    Chan, M; Bocquet, H; Campo, E; Val, T; Estève, D; Pous, J

    1998-01-01

    To improve the safety of a growing proportion of elderly and disabled people in the developed countries, a multisensor system based on Artificial Intelligence (AI), Advanced Telecommunications (AT) and Information Technology (IT) has been devised and fabricated. Thus, the habits and behaviours of these populations will be recorded without disturbing their daily activities. AI will diagnose any abnormal behavior or change and the system will warn the professionals. Gerontology issues are presented together with the multisensor system, the AI-based learning and diagnosis methodology and the main functionalities.

  5. 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.

  6. Theory and applications of artificial endocrine system-an overview

    Institute of Scientific and Technical Information of China (English)

    CUI Wei; QIANG Sheng; GAO X Z

    2006-01-01

    Inspired by the biological endocrine system, the Artificial Endocrine System (AES) has been proposed and investigated during the past decade. As a novel branch of computational intelligence methods, it has its unique and distinguishing features. This paper intends to give an overview of the current research work in the AES. The preliminary theory of the AES, which is based on the simplified mathematic models of natural endocrine system, is first introduced here. Some typical AES algorithms and their applications are also briefly discussed. Finally, a few remarks and conclusions are made.

  7. Learning modalities in artificial intelligence systems: a framework and review

    Energy Technology Data Exchange (ETDEWEB)

    Araya, A A

    1982-01-01

    Intelligent systems should possess two fundamental capabilities: problem solving and learning. Problem solving capabilities allow an intelligent system to cope with problems in a given domain. Learning capabilities make possible for an intelligent system to improve the solution to the problems within its current reach or to cope with new problems. This paper examines research in artificial intelligence from the perspective of learning with the purpose of: 1) developing and understanding of the problem of learning from the AI point of view, and II) characterizing the current state of the art on learning in AI. 35 references.

  8. Artificial ferroic systems: novel functionality from structure, interactions and dynamics

    International Nuclear Information System (INIS)

    Heyderman, L J; Stamps, R L

    2013-01-01

    Lithographic processing and film growth technologies are continuing to advance, so that it is now possible to create patterned ferroic materials consisting of arrays of sub-1 μm elements with high definition. Some of the most fascinating behaviour of these arrays can be realised by exploiting interactions between the individual elements to create new functionality. The properties of these artificial ferroic systems differ strikingly from those of their constituent components, with novel emergent behaviour arising from the collective dynamics of the interacting elements, which are arranged in specific designs and can be activated by applying magnetic or electric fields. We first focus on artificial spin systems consisting of arrays of dipolar-coupled nanomagnets and, in particular, review the field of artificial spin ice, which demonstrates a wide range of fascinating phenomena arising from the frustration inherent in particular arrangements of nanomagnets, including emergent magnetic monopoles, domains of ordered macrospins, and novel avalanche behaviour. We outline how demagnetisation protocols have been employed as an effective thermal anneal in an attempt to reach the ground state, comment on phenomena that arise in thermally activated systems and discuss strategies for selectively generating specific configurations using applied magnetic fields. We then move on from slow field and temperature driven dynamics to high frequency phenomena, discussing spinwave excitations in the context of magnonic crystals constructed from arrays of patterned magnetic elements. At high frequencies, these arrays are studied in terms of potential applications including magnetic logic, linear and non-linear microwave optics, and fast, efficient switching, and we consider the possibility to create tunable magnonic crystals with artificial spin ice. Finally, we discuss how functional ferroic composites can be incorporated to realise magnetoelectric effects. Specifically, we discuss

  9. Artificial ferroic systems: novel functionality from structure, interactions and dynamics.

    Science.gov (United States)

    Heyderman, L J; Stamps, R L

    2013-09-11

    Lithographic processing and film growth technologies are continuing to advance, so that it is now possible to create patterned ferroic materials consisting of arrays of sub-1 μm elements with high definition. Some of the most fascinating behaviour of these arrays can be realised by exploiting interactions between the individual elements to create new functionality. The properties of these artificial ferroic systems differ strikingly from those of their constituent components, with novel emergent behaviour arising from the collective dynamics of the interacting elements, which are arranged in specific designs and can be activated by applying magnetic or electric fields. We first focus on artificial spin systems consisting of arrays of dipolar-coupled nanomagnets and, in particular, review the field of artificial spin ice, which demonstrates a wide range of fascinating phenomena arising from the frustration inherent in particular arrangements of nanomagnets, including emergent magnetic monopoles, domains of ordered macrospins, and novel avalanche behaviour. We outline how demagnetisation protocols have been employed as an effective thermal anneal in an attempt to reach the ground state, comment on phenomena that arise in thermally activated systems and discuss strategies for selectively generating specific configurations using applied magnetic fields. We then move on from slow field and temperature driven dynamics to high frequency phenomena, discussing spinwave excitations in the context of magnonic crystals constructed from arrays of patterned magnetic elements. At high frequencies, these arrays are studied in terms of potential applications including magnetic logic, linear and non-linear microwave optics, and fast, efficient switching, and we consider the possibility to create tunable magnonic crystals with artificial spin ice. Finally, we discuss how functional ferroic composites can be incorporated to realise magnetoelectric effects. Specifically, we discuss

  10. Simulation of Artificial Intelligence for Automotive Air-conditioning System

    Institute of Scientific and Technical Information of China (English)

    YUAN Xiao-mei; CHEN You-hua; CHEN Zhi-jiu

    2002-01-01

    The artificial intelligence is applied to the simulation of the automotive air-conditioning system ( AACS )According to the system's characteristics a model of AACS, based on neural network, is developed. Different control methods of AACS are discussed through simulation based on this model. The result shows that the neural- fuzzy control is the best one compared with the on-off control and conventional fuzzy control method.It can make the compartment's temperature descend rapidly to the designed temperature and the fluctuation is small.

  11. PRONET: Basic concepts of a system of Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    S. Lasai

    1999-12-01

    Full Text Available In the work are expounded the principles and basic elements of a system of artificial intelligence. Knowledge representation develops according to the method settled for processing. A thing, a phenomenon can be determined or established by more modules subject to their state as well as the links and relations between them. The system creates a set of blocks (modules for which the concurrent work is pre- established. The volume of knowledge can be also increased without increasing the number of blocks.

  12. Artificial Intelligence in the service of system administrators

    CERN Multimedia

    CERN. Geneva

    2012-01-01

    Research has been performed to try to automatize (some) system administration tasks, starting in 2001 when IBM defined the so-called “self objectives” supposed to lead to “autonomic computing”. In this context, we present a framework that makes use of artificial intelligence and machine learning to monitor and diagnose at a low level and in a non intrusive way  Linux-based systems and their interaction with software. Moreover, the multi agent approach we use, coupled with a "object oriented paradigm" architecture should increase a lot our learning speed, and highlight relations between probl...

  13. Artificial intelligence and expert systems in-flight software testing

    Science.gov (United States)

    Demasie, M. P.; Muratore, J. F.

    1991-01-01

    The authors discuss the introduction of advanced information systems technologies such as artificial intelligence, expert systems, and advanced human-computer interfaces directly into Space Shuttle software engineering. The reconfiguration automation project (RAP) was initiated to coordinate this move towards 1990s software technology. The idea behind RAP is to automate several phases of the flight software testing procedure and to introduce AI and ES into space shuttle flight software testing. In the first phase of RAP, conventional tools to automate regression testing have already been developed or acquired. There are currently three tools in use.

  14. An 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

  15. Photosynthetic Response of Soybean to Microclimate in 26-Year-Old Tree-Based Intercropping Systems in Southern Ontario, Canada.

    Science.gov (United States)

    Peng, Xiaobang; Thevathasan, Naresh V; Gordon, Andrew M; Mohammed, Idris; Gao, Pengxiang

    2015-01-01

    In order to study the effect of light competition and microclimatic modifications on the net assimilation (NA), growth and yield of soybean (Glycine max L.) as an understory crop, three 26-year-old soybean-tree (Acer saccharinum Marsh., Populus deltoides X nigra, Juglans nigra L.) intercropping systems were examined. Tree competition reduced photosynthetically active radiation (PAR) incident on soybeans and reduced net assimilation, growth and yield of soybean. Soil moisture of 20 cm depth close (tree rows was also reduced. Correlation analysis showed that NA and soil water content were highly correlated with growth and yield of soybean. When compared with the monoculture soybean system, the relative humidity (RH) of the poplar-soybean, silver maple-soybean, and black walnut-soybean intercropped systems was increased by 7.1%, 8.0% and 5.9%, soil water content was reduced by 37.8%, 26.3% and 30.9%, ambient temperature was reduced by 1.3°C, 1.4°C and 1.0°C, PAR was reduced by 53.6%, 57.9% and 39.9%, and air CO2 concentration was reduced by 3.7μmol·mol(-1), 4.2μmol·mol(-1) and 2.8μmol·mol(-1), respectively. Compared to the monoculture, the average NA of soybean in poplar, maple and walnut treatments was also reduced by 53.1%, 67.5% and 46.5%, respectively. Multivariate stepwise regression analysis showed that PAR, ambient temperature and CO2 concentration were the dominant factors influencing net photosynthetic rate.

  16. Evolving a photosynthetic organelle

    Directory of Open Access Journals (Sweden)

    Nakayama Takuro

    2012-04-01

    Full Text Available Abstract The evolution of plastids from cyanobacteria is believed to represent a singularity in the history of life. The enigmatic amoeba Paulinella and its 'recently' acquired photosynthetic inclusions provide a fascinating system through which to gain fresh insight into how endosymbionts become organelles. The plastids, or chloroplasts, of algae and plants evolved from cyanobacteria by endosymbiosis. This landmark event conferred on eukaryotes the benefits of photosynthesis - the conversion of solar energy into chemical energy - and in so doing had a huge impact on the course of evolution and the climate of Earth 1. From the present state of plastids, however, it is difficult to trace the evolutionary steps involved in this momentous development, because all modern-day plastids have fully integrated into their hosts. Paulinella chromatophora is a unicellular eukaryote that bears photosynthetic entities called chromatophores that are derived from cyanobacteria and has thus received much attention as a possible example of an organism in the early stages of organellogenesis. Recent studies have unlocked the genomic secrets of its chromatophore 23 and provided concrete evidence that the Paulinella chromatophore is a bona fide photosynthetic organelle 4. The question is how Paulinella can help us to understand the process by which an endosymbiont is converted into an organelle.

  17. Evolving a photosynthetic organelle.

    Science.gov (United States)

    Nakayama, Takuro; Archibald, John M

    2012-04-24

    The evolution of plastids from cyanobacteria is believed to represent a singularity in the history of life. The enigmatic amoeba Paulinella and its 'recently' acquired photosynthetic inclusions provide a fascinating system through which to gain fresh insight into how endosymbionts become organelles.The plastids, or chloroplasts, of algae and plants evolved from cyanobacteria by endosymbiosis. This landmark event conferred on eukaryotes the benefits of photosynthesis--the conversion of solar energy into chemical energy--and in so doing had a huge impact on the course of evolution and the climate of Earth 1. From the present state of plastids, however, it is difficult to trace the evolutionary steps involved in this momentous development, because all modern-day plastids have fully integrated into their hosts. Paulinella chromatophora is a unicellular eukaryote that bears photosynthetic entities called chromatophores that are derived from cyanobacteria and has thus received much attention as a possible example of an organism in the early stages of organellogenesis. Recent studies have unlocked the genomic secrets of its chromatophore 23 and provided concrete evidence that the Paulinella chromatophore is a bona fide photosynthetic organelle 4. The question is how Paulinella can help us to understand the process by which an endosymbiont is converted into an organelle.

  18. AN ARTIFICIAL INTELLIGENCE-BASED DISTANCE EDUCATION SYSTEM: Artimat

    Directory of Open Access Journals (Sweden)

    Vasif NABIYEV

    2013-04-01

    Full Text Available The purpose of this study is to evaluate the artificial intelligence-based distance education system called as ARTIMAT, which has been prepared in order to improve mathematical problem solving skills of the students, in terms of conceptual proficiency and ease of use with the opinions of teachers and students. The implementation has been performed with 4 teachers and 59 students in 10th grade in an Anatolian High School in Trabzon. Many institutions and organizations in the world approach seriously to distance education besides traditional education. It is inevitable to use the distance education in teaching the problem solving skills in this different dimension of the education. In the studies in Turkey and abroad in the field of mathematics teaching, problem solving skills are generally stated not to be at the desired level and often expressed to have difficulty in teaching. For this reason, difficulties of the students in problem solving have initially been evaluated and the system has been prepared utilizing artificial intelligence algorithms according to the obtained results. In the evaluation of the findings obtained from the application, it has been concluded that the system is responsive to the needs of the students and is successful in general, but that conceptual changes should be made in order that students adapt to the system quickly.

  19. Artificial vision support system (AVS(2)) for improved prosthetic vision.

    Science.gov (United States)

    Fink, Wolfgang; Tarbell, Mark A

    2014-11-01

    State-of-the-art and upcoming camera-driven, implanted artificial vision systems provide only tens to hundreds of electrodes, affording only limited visual perception for blind subjects. Therefore, real time image processing is crucial to enhance and optimize this limited perception. Since tens or hundreds of pixels/electrodes allow only for a very crude approximation of the typically megapixel optical resolution of the external camera image feed, the preservation and enhancement of contrast differences and transitions, such as edges, are especially important compared to picture details such as object texture. An Artificial Vision Support System (AVS(2)) is devised that displays the captured video stream in a pixelation conforming to the dimension of the epi-retinal implant electrode array. AVS(2), using efficient image processing modules, modifies the captured video stream in real time, enhancing 'present but hidden' objects to overcome inadequacies or extremes in the camera imagery. As a result, visual prosthesis carriers may now be able to discern such objects in their 'field-of-view', thus enabling mobility in environments that would otherwise be too hazardous to navigate. The image processing modules can be engaged repeatedly in a user-defined order, which is a unique capability. AVS(2) is directly applicable to any artificial vision system that is based on an imaging modality (video, infrared, sound, ultrasound, microwave, radar, etc.) as the first step in the stimulation/processing cascade, such as: retinal implants (i.e. epi-retinal, sub-retinal, suprachoroidal), optic nerve implants, cortical implants, electric tongue stimulators, or tactile stimulators.

  20. Artificial immune system for effective properties optimization of magnetoelectric composites

    Science.gov (United States)

    Poteralski, Arkadiusz; Dziatkiewicz, Grzegorz

    2018-01-01

    The optimization problem of the effective properties for magnetoelectric composites is considered. The effective properties are determined by the semi-analytical Mori-Tanaka approach. The generalized Eshelby tensor components are calculated numerically by using the Gauss quadrature method for the integral representation of the inclusion problem. The linear magnetoelectric constitutive equation is used. The effect of orientation of the electromagnetic materials components is taken into account. The optimization problem of the design is formulated and the artificial immune system is applied to solve it.

  1. Multicriteria vehicle routing problem solved by artificial immune system

    Directory of Open Access Journals (Sweden)

    Bogna MRÓWCZYŃSKA

    2015-09-01

    Full Text Available Vehicles route planning in large transportation companies, where drivers are workers, usually takes place on the basis of experience or intuition of the employees. Because of the cost and environmental protection, it is important to save fuel, thus planning routes in an optimal way. In this article an example of the problem is presented solving delivery vans route planning taking into account the distance and travel time within the constraints of vehicle capacities, restrictions on working time of drivers and having varying degrees of movement. An artificial immune system was used for the calculations.

  2. The Effects O Artificial Intelligence And Robotic Systems On Librarianship

    OpenAIRE

    Müslüm Yıldız; Banu Fulya Yıldırım

    2018-01-01

    With Industry 4.0, smart robots will be involved in all areas of our lives, and systems using technology control instead of work force will dominate. In this way, there will be a more qualified workforce with a high level of education, rather than workers with low-skilled jobs. According to recent studies, librarianship has been identified as one of the professions that could disappear in the near future due to this rapidly advancing technology. In this study, the possible effects of artifici...

  3. The application of artificial intelligence technology to aeronautical system design

    Science.gov (United States)

    Bouchard, E. E.; Kidwell, G. H.; Rogan, J. E.

    1988-01-01

    This paper describes the automation of one class of aeronautical design activity using artificial intelligence and advanced software techniques. Its purpose is to suggest concepts, terminology, and approaches that may be useful in enhancing design automation. By understanding the basic concepts and tasks in design, and the technologies that are available, it will be possible to produce, in the future, systems whose capabilities far exceed those of today's methods. Some of the tasks that will be discussed have already been automated and are in production use, resulting in significant productivity benefits. The concepts and techniques discussed are applicable to all design activity, though aeronautical applications are specifically presented.

  4. The implementation of artificial intelligence in control systems

    International Nuclear Information System (INIS)

    Koul, R.; Weygand, D.P.

    1987-01-01

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

  5. Control of an automated mobile manipulator using artificial immune system

    Science.gov (United States)

    Deepak, B. B. V. L.; Parhi, Dayal R.

    2016-03-01

    This paper addresses the coordination and control of a wheeled mobile manipulator (WMM) using artificial immune system. The aim of the developed methodology is to navigate the system autonomously and transport jobs and tools in manufacturing environments. This study integrates the kinematic structures of a four-axis manipulator and a differential wheeled mobile platform. The motion of the developed WMM is controlled by the complete system of parametric equation in terms of joint velocities and makes the robot to follow desired trajectories by the manipulator and platform within its workspace. The developed robot system performs its action intelligently according to the sensed environmental criteria within its search space. To verify the effectiveness of the proposed immune-based motion planner for WMM, simulations as well as experimental results are presented in various unknown environments.

  6. Evaluation of articulation simulation system using artificial maxillectomy models.

    Science.gov (United States)

    Elbashti, M E; Hattori, M; Sumita, Y I; Taniguchi, H

    2015-09-01

    Acoustic evaluation is valuable for guiding the treatment of maxillofacial defects and determining the effectiveness of rehabilitation with an obturator prosthesis. Model simulations are important in terms of pre-surgical planning and pre- and post-operative speech function. This study aimed to evaluate the acoustic characteristics of voice generated by an articulation simulation system using a vocal tract model with or without artificial maxillectomy defects. More specifically, we aimed to establish a speech simulation system for maxillectomy defect models that both surgeons and maxillofacial prosthodontists can use in guiding treatment planning. Artificially simulated maxillectomy defects were prepared according to Aramany's classification (Classes I-VI) in a three-dimensional vocal tract plaster model of a subject uttering the vowel /a/. Formant and nasalance acoustic data were analysed using Computerized Speech Lab and the Nasometer, respectively. Formants and nasalance of simulated /a/ sounds were successfully detected and analysed. Values of Formants 1 and 2 for the non-defect model were 675.43 and 976.64 Hz, respectively. Median values of Formants 1 and 2 for the defect models were 634.36 and 1026.84 Hz, respectively. Nasalance was 11% in the non-defect model, whereas median nasalance was 28% in the defect models. The results suggest that an articulation simulation system can be used to help surgeons and maxillofacial prosthodontists to plan post-surgical defects that will be facilitate maxillofacial rehabilitation. © 2015 John Wiley & Sons Ltd.

  7. Classification system for rain fed wheat grain cultivars using artificial ...

    African Journals Online (AJOL)

    Artificial neural network (ANN) models have found wide applications, including ... of grains is essential for various applications as wheat grain industry and cultivation. In order to classify the rain fed wheat cultivars using artificial neural network ...

  8. ANUBIS: artificial neuromodulation using a Bayesian inference system.

    Science.gov (United States)

    Smith, Benjamin J H; Saaj, Chakravarthini M; Allouis, Elie

    2013-01-01

    Gain tuning is a crucial part of controller design and depends not only on an accurate understanding of the system in question, but also on the designer's ability to predict what disturbances and other perturbations the system will encounter throughout its operation. This letter presents ANUBIS (artificial neuromodulation using a Bayesian inference system), a novel biologically inspired technique for automatically tuning controller parameters in real time. ANUBIS is based on the Bayesian brain concept and modifies it by incorporating a model of the neuromodulatory system comprising four artificial neuromodulators. It has been applied to the controller of EchinoBot, a prototype walking rover for Martian exploration. ANUBIS has been implemented at three levels of the controller; gait generation, foot trajectory planning using Bézier curves, and foot trajectory tracking using a terminal sliding mode controller. We compare the results to a similar system that has been tuned using a multilayer perceptron. The use of Bayesian inference means that the system retains mathematical interpretability, unlike other intelligent tuning techniques, which use neural networks, fuzzy logic, or evolutionary algorithms. The simulation results show that ANUBIS provides significant improvements in efficiency and adaptability of the three controller components; it allows the robot to react to obstacles and uncertainties faster than the system tuned with the MLP, while maintaining stability and accuracy. As well as advancing rover autonomy, ANUBIS could also be applied to other situations where operating conditions are likely to change or cannot be accurately modeled in advance, such as process control. In addition, it demonstrates one way in which neuromodulation could fit into the Bayesian brain framework.

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

    Science.gov (United States)

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

    2016-09-01

    The incidence of diabetes is increasing at an unprecedented pace and has become a serious health concern worldwide during the last two decades. Despite this, adequate glycemic control using an artificial pancreas has not been established, although the 21st century has seen rapid developments in this area. Herein, we review current topics in glycemic control for both the wearable artificial pancreas for type 1 and type 2 diabetic patients and the bedside artificial pancreas for surgical diabetic patients. In type 1 diabetic patients, nocturnal hypoglycemia associated with insulin therapy remains a serious problem that could be addressed by the recent development of a wearable artificial pancreas. This smart phone-like device, comprising a real-time, continuous glucose monitoring system and insulin pump system, could potentially significantly reduce nocturnal hypoglycemia compared with conventional glycemic control. Of particular interest in this space are the recent inventions of a low-glucose suspend feature in the portable systems that automatically stops insulin delivery 2 h following a glucose sensor value <70 mg/dL and a bio-hormonal pump system consisting of insulin and glucagon pumps. Perioperative tight glycemic control using a bedside artificial pancreas with the closed-loop system has also proved safe and effective for not only avoiding hypoglycemia, but also for reducing blood glucose level variability resulting in good surgical outcomes. We hope that a more sophisticated artificial pancreas with closed-loop system will now be taken up for routine use worldwide, providing enormous relief for patients suffering from uncontrolled hyperglycemia, hypoglycemia, and/or variability in blood glucose concentrations.

  10. Ultrathin Alvarez lens system actuated by artificial muscles.

    Science.gov (United States)

    Petsch, S; Grewe, A; Köbele, L; Sinzinger, S; Zappe, H

    2016-04-01

    A key feature of Alvarez lenses is that they may be tuned in focal length using lateral rather than axial translation, thus reducing the overall length of a focus-tunable optical system. Nevertheless the bulk of classical microsystems actuators limits further miniaturization. We present here a new, ultrathin focus-tunable Alvarez lens fabricated using molding techniques and actuated using liquid crystal elastomer (LCE) artificial muscle actuators. The large deformation generated by the LCE actuators permits the integration of the actuators in-plane with the mechanical and optical system and thus reduces the device thickness to only 1.6 mm. Movement of the Alvarez lens pair of 178 μm results in a focal length change of 3.3 mm, based on an initial focal length of 28.4 mm. This design is of considerable interest for realization of ultraflat focus-tunable and zoom systems.

  11. Artificial neural network analysis of triple effect absorption refrigeration systems

    Energy Technology Data Exchange (ETDEWEB)

    Hajizadeh Aghdam, A. [Department of Mechanical Engineering, Islamic Azad University (Iran, Islamic Republic of)], email: a.hajizadeh@iaukashan.ac.ir; Nazmara, H.; Farzaneh, B. [Department of Mechanical Engineering, University of Tabriz (Iran, Islamic Republic of)], email: h.nazmara@nioec.org, email: b_farzaneh_ms@yahoo.com

    2011-07-01

    In this study, artificial neural networks are utilized to predict the performance of triple effect series and parallel flow absorption refrigeration systems, with lithium bromide/water as the working fluid. Important parameters such as high generator and evaporator temperatures were varied and their effects on the performance characteristics of the refrigeration unit were observed. Absorption refrigeration systems make energy savings possible because they can use heat energy to produce cooling, in place of the electricity used for conventional vapour compression chillers. In addition, non-conventional sources of energy (such as solar, waste heat, and geothermal) can be utilized as their primary energy input. Moreover, absorption units use environmentally friendly working fluid pairs instead of CFCs and HCFCs, which affect the ozone layer. Triple effect absorption cycles were analysed. Results apply for both series and parallel flow systems. A relative preference for parallel-flow over series-flow is also shown.

  12. Using isotopes for design and monitoring of artificial recharge systems

    Science.gov (United States)

    Contributors: Hendriksson, N.; Kulongoski, J.T.; Massmann, G.; Newman, B.

    2013-01-01

    Over the past years, the IAEA has provided support to a number of Member States engaged in the implementation of hydrological projects dealing with the design and monitoring of artificial recharge ( A R ) systems, primarily situated in arid and semiarid regions. AR is defined as any engineered system designed to introduce water to, and store water in, underlying aquifers. Aquifer storage and recovery (ASR) is a specific type of AR used with the purpose of increasing groundwater resources. Different water management strategies have been tested under various geographical, hydrological and climatic regimes. However, the success of such schemes cannot easily be predicted, since many variables need to be taken into account in the early stages of every AR project.

  13. The Effects O Artificial Intelligence And Robotic Systems On Librarianship

    Directory of Open Access Journals (Sweden)

    Müslüm Yıldız

    2018-03-01

    Full Text Available With Industry 4.0, smart robots will be involved in all areas of our lives, and systems using technology control instead of work force will dominate. In this way, there will be a more qualified workforce with a high level of education, rather than workers with low-skilled jobs. According to recent studies, librarianship has been identified as one of the professions that could disappear in the near future due to this rapidly advancing technology. In this study, the possible effects of artificial intelligence and robotic systems on the profession of librarianship/information and document management were evaluated considering the findings of research conducted at Oxford University in 2017 and it was emphasized that in the near future, the only way to continue in this profession would be to keep the professional knowledge up to date as well as to follow the technological developments in areas such as computers, communication, and the internet.

  14. Artificial intelligence techniques for sizing photovoltaic systems. A review

    Energy Technology Data Exchange (ETDEWEB)

    Mellit, A. [Department of Electronics, Faculty of Science Engineering, LAMEL Laboratory, Jijel University, P.O. Box 98, Oulad Aissa, Jijel 18000 (Algeria); Kalogirou, S.A. [Department of Mechanical Engineering and Materials Science and Engineering, Cyprus University of Technology, P.O. Box 50329, Limassol 3603 (Cyprus); Hontoria, L. [Grupo Investigacion y Desarrollo en Energia Solar y Automatica, Dpto. de Electronica, E.P.S. Jaen, Universidad de Jaen, Avda., Madrid, 35, 23071 Jaen (Spain); Shaari, S. [Faculty of Applied Sciences, Universiti Teknologi MARA 40450 Shah Alam, Selangor (Malaysia)

    2009-02-15

    Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques or as components of integrated systems. They have been used to solve complicated practical problems in various areas and are becoming more and more popular nowadays. AI-techniques have the following features: can learn from examples; are fault tolerant in the sense that they are able to handle noisy and incomplete data; are able to deal with non-linear problems; and once trained can perform prediction and generalization at high speed. AI-based systems are being developed and deployed worldwide in a myriad of applications, mainly because of their symbolic reasoning, flexibility and explanation capabilities. AI have been used and applied in different sectors, such as engineering, economics, medicine, military, marine, etc. They have also been applied for modeling, identification, optimization, prediction, forecasting, and control of complex systems. The main objective of this paper is to present an overview of the AI-techniques for sizing photovoltaic (PV) systems: stand-alone PVs, grid-connected PV systems, PV-wind hybrid systems, etc. Published literature presented in this paper show the potential of AI as a design tool for the optimal sizing of PV systems. Additionally, the advantage of using an AI-based sizing of PV systems is that it provides good optimization, especially in isolated areas, where the weather data are not always available. (author)

  15. Artificial Neural Network-Based System for PET Volume Segmentation

    Directory of Open Access Journals (Sweden)

    Mhd Saeed Sharif

    2010-01-01

    Full Text Available Tumour detection, classification, and quantification in positron emission tomography (PET imaging at early stage of disease are important issues for clinical diagnosis, assessment of response to treatment, and radiotherapy planning. Many techniques have been proposed for segmenting medical imaging data; however, some of the approaches have poor performance, large inaccuracy, and require substantial computation time for analysing large medical volumes. Artificial intelligence (AI approaches can provide improved accuracy and save decent amount of time. Artificial neural networks (ANNs, as one of the best AI techniques, have the capability to classify and quantify precisely lesions and model the clinical evaluation for a specific problem. This paper presents a novel application of ANNs in the wavelet domain for PET volume segmentation. ANN performance evaluation using different training algorithms in both spatial and wavelet domains with a different number of neurons in the hidden layer is also presented. The best number of neurons in the hidden layer is determined according to the experimental results, which is also stated Levenberg-Marquardt backpropagation training algorithm as the best training approach for the proposed application. The proposed intelligent system results are compared with those obtained using conventional techniques including thresholding and clustering based approaches. Experimental and Monte Carlo simulated PET phantom data sets and clinical PET volumes of nonsmall cell lung cancer patients were utilised to validate the proposed algorithm which has demonstrated promising results.

  16. 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.

  17. 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.

  18. 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.

  19. Use of in vivo chlorophyll fluorescence to estimate photosynthetic activity and biomass productivity in microalgae grown in different culture systems

    Directory of Open Access Journals (Sweden)

    Félix L Figueroa

    2013-11-01

    Full Text Available In vivo chlorophyll fluorescence associated to Photosystem II is being used to evaluate photosynthetic activity of microalgae grown in different types of photobioreactors; however, controversy on methodology is usual. Several recommendations on the use of chlorophyll fluorescence to estimate electron transport rate and productivity of microalgae grown in thin-layer cascade cultivators and methacrylate cylindrical vessels are included. Different methodologies related to the measure of photosynthetic activity in microalgae are discussed: (1 measurement of light absorption, (2 determination of electron transport rates versus irradiance and (3 use of simplified devices based on pulse amplitude modulated (PAM fluorescence as Junior PAM or Pocket PAM with optical fiber and optical head as measuring units, respectively. Data comparisons of in vivo chlorophyll fluorescence by using these devices and other PAM fluorometers as Water-PAM in the microalga Chlorella sp. (Chlorophyta are presented. Estimations of carbon production and productivity by transforming electron transport rate to gross photosynthetic rate (as oxygen evolution using reported oxygen produced per photons absorbed values and carbon photosynthetic yield based on reported oxygen/carbon ratio are also shown. The limitation of ETR as estimator of photosynthetic and biomass productivity is discussed. Low cost:quality PAMs can promote monitoring of chlorophyll fluorescence in algal biotechnology to estimate the photosynthetic activity and biomass productivity.

  20. VWPS: A Ventilator Weaning Prediction System with Artificial Intelligence

    Science.gov (United States)

    Chen, Austin H.; Chen, Guan-Ting

    How to wean patients efficiently off mechanical ventilation continues to be a challenge for medical professionals. In this paper we have described a novel approach to the study of a ventilator weaning prediction system (VWPS). Firstly, we have developed and written three Artificial Neural Network (ANN) algorithms to predict a weaning successful rate based on the clinical data. Secondly, we have implemented two user-friendly weaning success rate prediction systems; the VWPS system and the BWAP system. Both systems could be used to help doctors objectively and effectively predict whether weaning is appropriate for patients based on the patients' clinical data. Our system utilizes the powerful processing abilities of MatLab. Thirdly, we have calculated the performance through measures such as sensitivity and accuracy for these three algorithms. The results show a very high sensitivity (around 80%) and accuracy (around 70%). To our knowledge, this is the first design approach of its kind to be used in the study of ventilator weaning success rate prediction.

  1. Development of a linear induction motor based artificial muscle system.

    Science.gov (United States)

    Gruber, A; Arguello, E; Silva, R

    2013-01-01

    We present the design of a linear induction motor based on electromagnetic interactions. The engine is capable of producing a linear movement from electricity. The design consists of stators arranged in parallel, which produce a magnetic field sufficient to displace a plunger along its axial axis. Furthermore, the winding has a shell and cap of ferromagnetic material that amplifies the magnetic field. This produces a force along the length of the motor that is similar to that of skeletal muscle. In principle, the objective is to use the engine in the development of an artificial muscle system for prosthetic applications, but it could have multiple applications, not only in the medical field, but in other industries.

  2. Artificial Neural Network for Location Estimation in Wireless Communication Systems

    Directory of Open Access Journals (Sweden)

    Chien-Sheng Chen

    2012-03-01

    Full Text Available In a wireless communication system, wireless location is the technique used to estimate the location of a mobile station (MS. To enhance the accuracy of MS location prediction, we propose a novel algorithm that utilizes time of arrival (TOA measurements and the angle of arrival (AOA information to locate MS when three base stations (BSs are available. Artificial neural networks (ANN are widely used techniques in various areas to overcome the problem of exclusive and nonlinear relationships. When the MS is heard by only three BSs, the proposed algorithm utilizes the intersections of three TOA circles (and the AOA line, based on various neural networks, to estimate the MS location in non-line-of-sight (NLOS environments. Simulations were conducted to evaluate the performance of the algorithm for different NLOS error distributions. The numerical analysis and simulation results show that the proposed algorithms can obtain more precise location estimation under different NLOS environments.

  3. Artificial neural network for location estimation in wireless communication systems.

    Science.gov (United States)

    Chen, Chien-Sheng

    2012-01-01

    In a wireless communication system, wireless location is the technique used to estimate the location of a mobile station (MS). To enhance the accuracy of MS location prediction, we propose a novel algorithm that utilizes time of arrival (TOA) measurements and the angle of arrival (AOA) information to locate MS when three base stations (BSs) are available. Artificial neural networks (ANN) are widely used techniques in various areas to overcome the problem of exclusive and nonlinear relationships. When the MS is heard by only three BSs, the proposed algorithm utilizes the intersections of three TOA circles (and the AOA line), based on various neural networks, to estimate the MS location in non-line-of-sight (NLOS) environments. Simulations were conducted to evaluate the performance of the algorithm for different NLOS error distributions. The numerical analysis and simulation results show that the proposed algorithms can obtain more precise location estimation under different NLOS environments.

  4. Artificially Expanded Genetic Information Systems for New Aptamer Technologies

    Directory of Open Access Journals (Sweden)

    Elisa Biondi

    2018-05-01

    Full Text Available Directed evolution was first applied to diverse libraries of DNA and RNA molecules a quarter century ago in the hope of gaining technology that would allow the creation of receptors, ligands, and catalysts on demand. Despite isolated successes, the outputs of this technology have been somewhat disappointing, perhaps because the four building blocks of standard DNA and RNA have too little functionality to have versatile binding properties, and offer too little information density to fold unambiguously. This review covers the recent literature that seeks to create an improved platform to support laboratory Darwinism, one based on an artificially expanded genetic information system (AEGIS that adds independently replicating nucleotide “letters” to the evolving “alphabet”.

  5. Automatic Emboli Detection System for the Artificial Heart

    Science.gov (United States)

    Steifer, T.; Lewandowski, M.; Karwat, P.; Gawlikowski, M.

    In spite of the progress in material engineering and ventricular assist devices construction, thromboembolism remains the most crucial problem in mechanical heart supporting systems. Therefore, the ability to monitor the patient's blood for clot formation should be considered an important factor in development of heart supporting systems. The well-known methods for automatic embolus detection are based on the monitoring of the ultrasound Doppler signal. A working system utilizing ultrasound Doppler is being developed for the purpose of flow estimation and emboli detection in the clinical artificial heart ReligaHeart EXT. Thesystem will be based on the existing dual channel multi-gate Doppler device with RF digital processing. A specially developed clamp-on cannula probe, equipped with 2 - 4 MHz piezoceramic transducers, enables easy system setup. We present the issuesrelated to the development of automatic emboli detection via Doppler measurements. We consider several algorithms for the flow estimation and emboli detection. We discuss their efficiency and confront them with the requirements of our experimental setup. Theoretical considerations are then met with preliminary experimental findings from a) flow studies with blood mimicking fluid and b) in-vitro flow studies with animal blood. Finally, we discuss some more methodological issues - we consider several possible approaches to the problem of verification of the accuracy of the detection system.

  6. Artificial intelligence in the service of system administrators

    Science.gov (United States)

    Haen, C.; Barra, V.; Bonaccorsi, E.; Neufeld, N.

    2012-12-01

    The LHCb online system relies on a large and heterogeneous IT infrastructure made from thousands of servers on which many different applications are running. They run a great variety of tasks: critical ones such as data taking and secondary ones like web servers. The administration of such a system and making sure it is working properly represents a very important workload for the small expert-operator team. Research has been performed to try to automatize (some) system administration tasks, starting in 2001 when IBM defined the so-called “self objectives” supposed to lead to “autonomic computing”. In this context, we present a framework that makes use of artificial intelligence and machine learning to monitor and diagnose at a low level and in a non intrusive way Linux-based systems and their interaction with software. Moreover, the multi agent approach we use, coupled with an “object oriented paradigm” architecture should increase our learning speed a lot and highlight relations between problems.

  7. Artificial intelligence in the service of system administrators

    International Nuclear Information System (INIS)

    Haen, C; Barra, V; Bonaccorsi, E; Neufeld, N

    2012-01-01

    The LHCb online system relies on a large and heterogeneous IT infrastructure made from thousands of servers on which many different applications are running. They run a great variety of tasks: critical ones such as data taking and secondary ones like web servers. The administration of such a system and making sure it is working properly represents a very important workload for the small expert-operator team. Research has been performed to try to automatize (some) system administration tasks, starting in 2001 when IBM defined the so-called “self objectives” supposed to lead to “autonomic computing”. In this context, we present a framework that makes use of artificial intelligence and machine learning to monitor and diagnose at a low level and in a non intrusive way Linux-based systems and their interaction with software. Moreover, the multi agent approach we use, coupled with an “object oriented paradigm” architecture should increase our learning speed a lot and highlight relations between problems.

  8. Symptom based diagnostic system using artificial neural networks

    International Nuclear Information System (INIS)

    Santosh; Vinod, Gopika; Saraf, R.K.

    2003-01-01

    Nuclear power plant experiences a number of transients during its operations. In case of such an undesired plant condition generally known as an initiating event, the operator has to carry out diagnostic and corrective actions. The operator's response may be too late to mitigate or minimize the negative consequences in such scenarios. The objective of this work is to develop an operator support system based on artificial neural networks that will assist the operator to identify the initiating events at the earliest stages of their developments. A symptom based diagnostic system has been developed to investigate the initiating events. Neutral networks are utilized for carrying out the event identification by continuously monitoring process parameters. Whenever an event is detected, the system will display the necessary operator actions along with the initiating event. The system will also show the graphical trend of process parameters that are relevant to the event. This paper describes the features of the software that is used to monitor the reactor. (author)

  9. Production and photosynthetic activity of Mimosa Verde and Mimosa Roxa lettuce in two farming systems

    Directory of Open Access Journals (Sweden)

    Aline Mabel Rosa

    2014-08-01

    Full Text Available Lettuce (Lactuca sativa L. is the most commonly consumed leaf vegetable in the Brazilian diet, and it is a good source of vitamins and minerals. It is widely grown in the conventional farming system. However, the hydroponic farming system has been gaining importance in the market, wining confidence from consumers, who are becoming increasingly more demanding on food quality. The objective of this study was to evaluate the performance of two lettuce cultivars on hydroponic and conventional farming systems for the production of fresh mass (FM and dry mass (DM, photosynthesis, contents of chlorophyll and anthocyanin. The following two experiments were carried out: hydroponics farming (HF and conventional farming (CF, performed in protect and unprotect environments, respectively, in Florianópolis, SC. Mimosa Verde cultivar (MV showed greater fresh mass than Mimosa Roxa (MR, in both farming systems and the two cultivars presented better performance in the hydroponic system (287.7 g MV and 139.1 g MR than the conventional system (129.7 g MV and 111.8 g MR. Mimosa Verde cultivar presented lower average contents of total chlorophyll (7.7 mg g-¹ FM than Mimosa Roxa (11.8 mg g-¹FM, and both cultivars displayed higher means for this variable in the hydroponic farming system. Mimosa Roxa presented higher contents of anthocyanin in the conventional system (88.24 mg g-¹ FM than the ones in the hydroponic system (36.89 mg g-¹ FM. The best results for CO2 net assimilation rate regarded to photosyntheticaly active photon flux density were found in the hydroponic system, for both lettuce cultivars. Variation in the contents of chlorophyll were also found. Those variations were higher in the protected system than in the hydroponic system and contents of anthocyanin were higher in the conventional system.

  10. Artificial Systems and Models for Risk Covering Operations

    Directory of Open Access Journals (Sweden)

    Laurenţiu Mihai Treapăt

    2017-04-01

    Full Text Available Mainly, this paper focuses on the roles of artificial intelligence based systems and especially on risk-covering operations. In this context, the paper comes with theoretical explanations on real-life based examples and applications. From a general perspective, the paper enriches its value with a wide discussion on the related subject. The paper aims to revise the volatilities’ estimation models and the correlations between the various time series and also by presenting the Risk Metrics methodology, as explained is a case study. The advantages that the VaR estimation offers, consist of its ability to quantitatively and numerically express the risk level of a portfolio, at a certain moment in time and also the risk of on open position (in titles, in FX, commodities or granted loans, belonging to an economic agent or even individual; hence, its role in a more efficient capital allocation, in the assumed risk delimitation, and also as a performance measurement instrument. In this paper and the study case that completes our work, we aim to prove how we can prevent considerable losses and even bankruptcies if VaR is known and applied accordingly. For this reason, the universities inRomaniashould include or increase their curricula with the study of the VaR model as an artificial intelligence tool. The simplicity of the presented case study, most probably, is the strongest argument of the current work because it can be understood also by the readers that are not necessarily very experienced in the risk management field.

  11. An introduction to artificial intelligence and its potential use in space systems.

    OpenAIRE

    McDonald, Gary Wayne

    1986-01-01

    Approved for public release; distribution is unlimited This thesis provides an introduction to Artificial Intelligence and Space Systems, with comments regarding their integration. The survey of Artificial Intelligence (AI) is based upon a review of its history, its philosophical development, and subcategories of its current technologies. These subcategories are Expert Systems (ES), Natural Language Processing (NLP), Computer Vision and Pattern Recognition, and Robotic...

  12. Plant Pest Detection Using an Artificial Nose System: A Review

    Directory of Open Access Journals (Sweden)

    Shaoqing Cui

    2018-01-01

    Full Text Available This paper reviews artificial intelligent noses (or electronic noses as a fast and noninvasive approach for the diagnosis of insects and diseases that attack vegetables and fruit trees. The particular focus is on bacterial, fungal, and viral infections, and insect damage. Volatile organic compounds (VOCs emitted from plants, which provide functional information about the plant’s growth, defense, and health status, allow for the possibility of using noninvasive detection to monitor plants status. Electronic noses are comprised of a sensor array, signal conditioning circuit, and pattern recognition algorithms. Compared with traditional gas chromatography–mass spectrometry (GC-MS techniques, electronic noses are noninvasive and can be a rapid, cost-effective option for several applications. However, using electronic noses for plant pest diagnosis is still in its early stages, and there are challenges regarding sensor performance, sampling and detection in open areas, and scaling up measurements. This review paper introduces each element of electronic nose systems, especially commonly used sensors and pattern recognition methods, along with their advantages and limitations. It includes a comprehensive comparison and summary of applications, possible challenges, and potential improvements of electronic nose systems for different plant pest diagnoses.

  13. Plant Pest Detection Using an Artificial Nose System: A Review.

    Science.gov (United States)

    Cui, Shaoqing; Ling, Peter; Zhu, Heping; Keener, Harold M

    2018-01-28

    This paper reviews artificial intelligent noses (or electronic noses) as a fast and noninvasive approach for the diagnosis of insects and diseases that attack vegetables and fruit trees. The particular focus is on bacterial, fungal, and viral infections, and insect damage. Volatile organic compounds (VOCs) emitted from plants, which provide functional information about the plant's growth, defense, and health status, allow for the possibility of using noninvasive detection to monitor plants status. Electronic noses are comprised of a sensor array, signal conditioning circuit, and pattern recognition algorithms. Compared with traditional gas chromatography-mass spectrometry (GC-MS) techniques, electronic noses are noninvasive and can be a rapid, cost-effective option for several applications. However, using electronic noses for plant pest diagnosis is still in its early stages, and there are challenges regarding sensor performance, sampling and detection in open areas, and scaling up measurements. This review paper introduces each element of electronic nose systems, especially commonly used sensors and pattern recognition methods, along with their advantages and limitations. It includes a comprehensive comparison and summary of applications, possible challenges, and potential improvements of electronic nose systems for different plant pest diagnoses.

  14. An alternative respiratory sounds classification system utilizing artificial neural networks

    Directory of Open Access Journals (Sweden)

    Rami J Oweis

    2015-04-01

    Full Text Available Background: Computerized lung sound analysis involves recording lung sound via an electronic device, followed by computer analysis and classification based on specific signal characteristics as non-linearity and nonstationarity caused by air turbulence. An automatic analysis is necessary to avoid dependence on expert skills. Methods: This work revolves around exploiting autocorrelation in the feature extraction stage. All process stages were implemented in MATLAB. The classification process was performed comparatively using both artificial neural networks (ANNs and adaptive neuro-fuzzy inference systems (ANFIS toolboxes. The methods have been applied to 10 different respiratory sounds for classification. Results: The ANN was superior to the ANFIS system and returned superior performance parameters. Its accuracy, specificity, and sensitivity were 98.6%, 100%, and 97.8%, respectively. The obtained parameters showed superiority to many recent approaches. Conclusions: The promising proposed method is an efficient fast tool for the intended purpose as manifested in the performance parameters, specifically, accuracy, specificity, and sensitivity. Furthermore, it may be added that utilizing the autocorrelation function in the feature extraction in such applications results in enhanced performance and avoids undesired computation complexities compared to other techniques.

  15. Paul Henry Latimer (1925-2011): discoverer of selective scattering in photosynthetic systems.

    Science.gov (United States)

    Latimer, Margaret Gwyn; Bannister, Thomas T; Govindjee

    2017-10-01

    We provide here a brief tribute to Paul Henry Latimer (November 25, 1925 to October 1, 2011), a dedicated biological physicist, discoverer of selective scattering in biological systems, a wonderful teacher, husband, and father. We provide here a glimpse of his personal and professional life, including reminiscences from F. Dudley Bryant, Dan A. Cross, Bobby E. Pyle, Bryan L. Seiber, and Bruce A. Seiber.

  16. Using Isotopes for Design and Monitoring of Artificial Recharge Systems

    International Nuclear Information System (INIS)

    2013-11-01

    Over the past years, the IAEA has provided support to a number of Member States engaged in the implementation of hydrological projects dealing with the design and monitoring of artificial recharge (AR) systems, primarily situated in arid and semiarid regions. AR is defined as any engineered system designed to introduce water to, and store water in, underlying aquifers. Aquifer storage and recovery (ASR) is a specific type of AR used with the purpose of increasing groundwater resources. Different water management strategies have been tested under various geographical, hydrological and climatic regimes. However, the success of such schemes cannot easily be predicted, since many variables need to be taken into account in the early stages of every AR project. As often occurs in the case of the assessment and management of groundwater and aquifers, information on hydrological behaviour and response to human-made actions is difficult to obtain and often very costly, especially if only conventional hydrological methods are used. Classical methods in AR and ASR are meant to provide information on changes in the volume and quality of the artificially introduced water to ensure its sustainability. Although the use of isotopes and geochemical tracers to plan and monitor AR and ASR has been limited, there is a growing number of publications reporting the successful application of tracers in the different phases of AR and ASR schemes. This publication discusses several theoretical aspects important to the understanding, planning and monitoring of AR and ASR schemes and presents a selected number of examples illustrating the usefulness of isotopes and other tracers. One section presents the list of available isotope tracers, indicating the type of information that can be obtained from each. The case studies presented in this publication illustrate the use of these tools in the different stages of AR and ASR schemes. The publication is expected to be of interest to hydrologists

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

    Directory of Open Access Journals (Sweden)

    A. R Tahavvor

    2016-09-01

    Full Text Available Introduction Automation of agricultural and machinery construction has generally been enhanced by intelligent control systems due to utility and efficiency rising, ease of use, profitability and upgrading according to market demand. A broad variety of industrial merchandise are now supplied with computerized control systems of earth moving processes to be performed by construction and agriculture field vehicle such as grader, backhoe, tractor and scraper machines. A height control machine which is used in measuring base thickness is consisted of two mechanical and electronic parts. The mechanical part is consisted of conveyor belt, main body, electrical engine and invertors while the electronic part is consisted of ultrasonic, wave transmitter and receiver sensor, electronic board, control set, and microcontroller. The main job of these controlling devices consists of the topographic surveying, cutting and filling of elevated and spotted low area, and these actions fundamentally dependent onthe machine's ability in elevation and thickness measurement and control. In this study, machine was first tested and then some experiments were conducted for data collection. Study of system modeling in artificial neural networks (ANN was done for measuring, controlling the height for bases by input variable input vectors such as sampling time, probe speed, conveyer speed, sound wave speed and speed sensor are finally the maximum and minimum probe output vector on various conditions. The result reveals the capability of this procedure for experimental recognition of sensors' behavior and improvement of field machine control systems. Inspection, calibration and response, diagnosis of the elevation control system in combination with machine function can also be evaluated by some extra development of this system. Materials and Methods Designing and manufacture of the planned apparatus classified in three dissimilar, mechanical and electronic module, courses of

  18. Quantum dot systems: artificial atoms with tunable properties

    International Nuclear Information System (INIS)

    Weis, J.

    2005-01-01

    Full text: Quantum dots - also called zero-dimensional electron systems or artificial atoms - are physical objects where the constituent electrons are confined in a small spatial region, leading to discrete eigenvalues for the energies of the confined electrons. Large quantum dots offer a dense energy spectrum comparable to that of metallic grains, whereas small quantum dots more closely resemble atoms in their electronic properties. Quantum dots can be linked to leads by tunnel barriers, hence permitting electrical transport measurements: Coulomb blockade and single-electron charging effects are observed due to the repulsive electron electron interaction on the quantum dot site. Usually fabricated by conventional semiconductor growth and processing technology, the advantage is that both simple and also more complex quantum dot systems can be designed to purpose, acting as model systems with in-situ tunable parameters such as the number of confined electrons in the quantum dot and the strength of the tunnel coupling to the leads, electrostatically controlled by the applied voltages to gate electrodes. With increasing the tunnel coupling to the leads, the virtual occupation of the quantum dot from the leads becomes more and more important -- the simple description of electrical transport by single-electron tunneling events breaks down. The basic physics is described by the Kondo physics based on the Anderson impurity model. A system consisting of strongly electrostatically coupled quantum dots with separate leads to each quantum dot represent another realization of the Anderson impurity model. Experiments to verify the analogy are presented. The experimental data embedded within this tutorial have been obtained with Alexander Huebel, Matthias Keller, Joerg Schmid, David Quirion, Armin Welker, Ulf Wilhelm, and Klaus von Klitzing. (author)

  19. Artificial sweetener sucralose in U.S. drinking water systems.

    Science.gov (United States)

    Mawhinney, Douglas B; Young, Robert B; Vanderford, Brett J; Borch, Thomas; Snyder, Shane A

    2011-10-15

    The artificial sweetener sucralose has recently been shown to be a widespread of contaminant of wastewater, surface water, and groundwater. In order to understand its occurrence in drinking water systems, water samples from 19 United States (U.S.) drinking water treatment plants (DWTPs) serving more than 28 million people were analyzed for sucralose using liquid chromatography tandem mass spectrometry (LC-MS/MS). Sucralose was found to be present in source water of 15 out of 19 DWTPs (47-2900 ng/L), finished water of 13 out of 17 DWTPs (49-2400 ng/L) and distribution system water of 8 out of the 12 DWTPs (48-2400 ng/L) tested. Sucralose was only found to be present in source waters with known wastewater influence and/or recreational usage, and displayed low removal (12% average) in the DWTPs where finished water was sampled. Further, in the subset of DWTPs with distribution system water sampled, the compound was found to persist regardless of the presence of residual chlorine or chloramines. In order to understand intra-DWTP consistency, sucralose was monitored at one drinking water treatment plant over an 11 month period from March 2010 through January 2011, and averaged 440 ng/L in the source water and 350 ng/L in the finished water. The results of this study confirm that sucralose will function well as an indicator compound for anthropogenic influence on source, finished drinking and distribution system (i.e., tap) water, as well as an indicator compound for the presence of other recalcitrant compounds in finished drinking water in the U.S.

  20. Biomimetic Polymeric Semiconductor Based Hybrid Nanosystems for Artificial Photosynthesis towards Solar Fuels Generation via CO2 reduction

    OpenAIRE

    Zhou, H.; Li, P.; Liu, J.; Chen, Z.; Liu, L.; Dontsova, D.; Yan, R.; Fan, T.; Zhang, D.; Ye, J.

    2016-01-01

    In photosynthesis, an intricate polymeric system is constructed by connecting a light-harvesting antenna network, a molecular water oxidation center, and \\CO2\\} or proton-reduction machinery in a nanolayered architecture as a basic photosynthetic unit for solar-to-fuels conversion. Herein, we present a prototype basic artificial photosynthetic unit by connecting a typical CO2/proton reduction catalyst, a cocatalyst and an electron mediator as well as \\{CO2\\} activator into a polymer based nan...

  1. Current state of total artificial heart therapy and introduction of the most important total artificial heart systems.

    Science.gov (United States)

    Spiliopoulos, Sotirios; Hergesell, Vera; Wasler, Andrae; Dapunt, Otto

    2018-06-14

    Due to the declining instances of organ donation, total artificial heart (TAH) therapy is of increasing importance for the management of end-stage biventricular heart failure. We introduce the currently most important established and novel TAH systems (SynCardia, CARMAT, ReinHeart, BiVACOR), report clinical outcomes and discuss technical requirements for the successful implementation of TAH therapy as an alternative to cardiac transplantation.

  2. New genome sequence data and molecular tools promote the use of photosynthetic and edible cyanobacteria in bioregenerative systems to support human space exploration.

    Science.gov (United States)

    Leys, Natalie; Morin, Nicolas; Janssen, Paul; Mergeay, Max

    Cyanobacteria are daily used as nutritional supplements (e.g. Spirulina) and are considered for promising applications beyond Earth, in space, where they can play a crucial role in closed miniaturised biological waste recycling systems that are currently developed to support future long-term space missions. Cyanobacteria can be cultured with artificial light in controllable photobioreactors, and used for the efficient removal of CO2 from and production of O2 in the at-mosphere of the confined spacecraft, for removal of nitrate from waste water that is recycled to potable water, and as complementary food source. In this context, the filamentous cyanobac-terium Arthrospira sp. PCC 8005 was selected as part of the bio-regenerative life-support system MELiSSA from the European Space Agency. For bioprocess control and optimisation, the access to its genetic information and the development of molecular tools is crucial. Here we report on our efforts to determine the full genome of the cyanobacterium Arthrospira sp. PCC 8005. The obtained sequence data were analysed in detail to gain a better insight in the photosynthetic, nutritive, or potential toxic potential of this strain. In addition, the sensitivity of PCC 8005 to ionizing radiation was investigated because prolonged exposure of PCC 8005 to cosmic radiation in space might have a deleterious effect on its metabolism and oxygenic properties. To our knowledge, of the 6 different research groups across the globe trying to sequence Arthrospira strains, none of them, including us, were yet able to obtain a complete genome sequence. For Arthrospira sp. strain PCC 8005, we obtained 119 contigs (assembled in 16 scaffolds), representing 6,3 Mb, with 5,856 predicted protein-coding sequences (CDSs) and 176 genes encoding RNA. The PCC 8005 genome displays an unusual high number of large repeated sequences, covering around 8% of the genome, which likely hampered the sequenc-ing. The PCC 8005 genome is also ridden by mobile

  3. A new evolutionary system for evolving artificial neural networks.

    Science.gov (United States)

    Yao, X; Liu, Y

    1997-01-01

    This paper presents a new evolutionary system, i.e., EPNet, for evolving artificial neural networks (ANNs). The evolutionary algorithm used in EPNet is based on Fogel's evolutionary programming (EP). Unlike most previous studies on evolving ANN's, this paper puts its emphasis on evolving ANN's behaviors. Five mutation operators proposed in EPNet reflect such an emphasis on evolving behaviors. Close behavioral links between parents and their offspring are maintained by various mutations, such as partial training and node splitting. EPNet evolves ANN's architectures and connection weights (including biases) simultaneously in order to reduce the noise in fitness evaluation. The parsimony of evolved ANN's is encouraged by preferring node/connection deletion to addition. EPNet has been tested on a number of benchmark problems in machine learning and ANNs, such as the parity problem, the medical diagnosis problems, the Australian credit card assessment problem, and the Mackey-Glass time series prediction problem. The experimental results show that EPNet can produce very compact ANNs with good generalization ability in comparison with other algorithms.

  4. Direct process estimation from tomographic data using artificial neural systems

    Science.gov (United States)

    Mohamad-Saleh, Junita; Hoyle, Brian S.; Podd, Frank J.; Spink, D. M.

    2001-07-01

    The paper deals with the goal of component fraction estimation in multicomponent flows, a critical measurement in many processes. Electrical capacitance tomography (ECT) is a well-researched sensing technique for this task, due to its low-cost, non-intrusion, and fast response. However, typical systems, which include practicable real-time reconstruction algorithms, give inaccurate results, and existing approaches to direct component fraction measurement are flow-regime dependent. In the investigation described, an artificial neural network approach is used to directly estimate the component fractions in gas-oil, gas-water, and gas-oil-water flows from ECT measurements. A 2D finite- element electric field model of a 12-electrode ECT sensor is used to simulate ECT measurements of various flow conditions. The raw measurements are reduced to a mutually independent set using principal components analysis and used with their corresponding component fractions to train multilayer feed-forward neural networks (MLFFNNs). The trained MLFFNNs are tested with patterns consisting of unlearned ECT simulated and plant measurements. Results included in the paper have a mean absolute error of less than 1% for the estimation of various multicomponent fractions of the permittivity distribution. They are also shown to give improved component fraction estimation compared to a well known direct ECT method.

  5. Embodied artificial evolution: Artificial evolutionary systems in the 21st Century.

    Science.gov (United States)

    Eiben, A E; Kernbach, S; Haasdijk, Evert

    2012-12-01

    Evolution is one of the major omnipresent powers in the universe that has been studied for about two centuries. Recent scientific and technical developments make it possible to make the transition from passively understanding to actively using evolutionary processes. Today this is possible in Evolutionary Computing, where human experimenters can design and manipulate all components of evolutionary processes in digital spaces. We argue that in the near future it will be possible to implement artificial evolutionary processes outside such imaginary spaces and make them physically embodied. In other words, we envision the "Evolution of Things", rather than just the evolution of digital objects, leading to a new field of Embodied Artificial Evolution (EAE). The main objective of this paper is to present a unifying vision in order to aid the development of this high potential research area. To this end, we introduce the notion of EAE, discuss a few examples and applications, and elaborate on the expected benefits as well as the grand challenges this developing field will have to address.

  6. Effects of system-bath coupling on a photosynthetic heat engine: A polaron master-equation approach

    Science.gov (United States)

    Qin, M.; Shen, H. Z.; Zhao, X. L.; Yi, X. X.

    2017-07-01

    Stimulated by suggestions of quantum effects in energy transport in photosynthesis, the fundamental principles responsible for the near-unit efficiency of the conversion of solar to chemical energy became active again in recent years. Under natural conditions, the formation of stable charge-separation states in bacteria and plant reaction centers is strongly affected by the coupling of electronic degrees of freedom to a wide range of vibrational motions. These inspire and motivate us to explore the effects of the environment on the operation of such complexes. In this paper, we apply the polaron master equation, which offers the possibilities to interpolate between weak and strong system-bath coupling, to study how system-bath couplings affect the exciton-transfer processes in the Photosystem II reaction center described by a quantum heat engine (QHE) model over a wide parameter range. The effects of bath correlation and temperature, together with the combined effects of these factors are also discussed in detail. We interpret these results in terms of noise-assisted transport effect and dynamical localization, which correspond to two mechanisms underpinning the transfer process in photosynthetic complexes: One is resonance energy transfer and the other is the dynamical localization effect captured by the polaron master equation. The effects of system-bath coupling and bath correlation are incorporated in the effective system-bath coupling strength determining whether noise-assisted transport effect or dynamical localization dominates the dynamics and temperature modulates the balance of the two mechanisms. Furthermore, these two mechanisms can be attributed to one physical origin: bath-induced fluctuations. The two mechanisms are manifestations of the dual role played by bath-induced fluctuations depending on the range of parameters. The origin and role of coherence are also discussed. It is the constructive interplay between noise and coherent dynamics, rather

  7. Photosynthetic water splitting

    Energy Technology Data Exchange (ETDEWEB)

    Greenbaum, E.

    1981-01-01

    The photosynthetic unit of hydrogen evolution, the turnover time of photosynthetic hydrogen production, and hydrogenic photosynthesis are discussed in the section on previous work. Recent results are given on simultaneous photoproduction of hydrogen and oxygen, kinetic studies, microscopic marine algae-seaweeds, and oxygen profiles.

  8. A Modular Artificial Intelligence Inference Engine System (MAIS) for support of on orbit experiments

    Science.gov (United States)

    Hancock, Thomas M., III

    1994-01-01

    This paper describes a Modular Artificial Intelligence Inference Engine System (MAIS) support tool that would provide health and status monitoring, cognitive replanning, analysis and support of on-orbit Space Station, Spacelab experiments and systems.

  9. Application of artificial intelligence (AI) methods for designing and analysis of reconfigurable cellular manufacturing system (RCMS)

    CSIR Research Space (South Africa)

    Xing, B

    2009-12-01

    Full Text Available This work focuses on the design and control of a novel hybrid manufacturing system: Reconfigurable Cellular Manufacturing System (RCMS) by using Artificial Intelligence (AI) approach. It is hybrid as it combines the advantages of Cellular...

  10. Computer-aided N. M. R. spectra interpretation. I. An artificial intelligence system

    Energy Technology Data Exchange (ETDEWEB)

    Vida, M [Central N.M.R. Laboratory, Slovak Technical University, Bratislava (Czechoslovakia)

    1980-03-01

    Some desirable hardware and software features of an artificial intelligence system tailored to the needs of a modern computerized n.m.r. laboratory are discussed. A system corresponding to this idea is described.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-11-15

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

  12. Products of an Artificially Induced Hydrothermal System at Yucca Mountain

    International Nuclear Information System (INIS)

    Levy, S.

    2000-01-01

    Studies of mineral deposition in the recent geologic past at Yucca Mountain, Nevada, address competing hypotheses of hydrothermal alteration and deposition from percolating groundwater. The secondary minerals being studied are calcite-opal deposits in fractures and lithophysal cavities of ash-flow tuffs exposed in the Exploratory Studies Facility (ESF), a 7.7-km tunnel excavated by the Yucca Mountain Site Characterization Project within Yucca Mountain. An underground field test in the ESF provided information about the minerals deposited by a short-lived artificial hydrothermal system and an opportunity for comparison of test products with the natural secondary minerals. The heating phase lasted nine months, followed by a nine-month cooling period. Natural pore fluids were the only source of water during the thermal test. Condensation and reflux of water driven away from the heater produced fluid flow in certain fractures and intersecting boreholes. The mineralogic products of the thermal test are calcite-gypsum aggregates of less than 4-micrometer crystals and amorphous silica as glassy scale less than 0.2 mm thick and as mounds of tubules with diameters less than 0.7 micrometers. The minute crystal sizes of calcite and gypsum from the field test are very different from the predominantly coarser calcite crystals (up to cm scale) in natural secondary-mineral deposits at the site. The complex micrometer-scale textures of the amorphous silica differ from the simple forms of opal spherules and coatings in the natural deposits, even though some natural spherules are as small as 1 micrometer. These differences suggest that the natural minerals, especially if they were of hydrothermal origin, may have developed coarser or simpler forms during subsequent episodes of dissolution and redeposition. The presence of gypsum among the test products and its absence from the natural secondary-mineral assemblage may indicate a higher degree of evaporation during the test than

  13. Artificial immune system for diabetes meal plans optimization

    Science.gov (United States)

    Prilianti, K. R.; Callista, P. B.; Setiawan, H.

    2017-03-01

    Type 2 diabetes mellitus is a disease that occurs because the body lacks of insulin or the insulin produced by the pancreas cannot work effectively such that the glucose level in the blood cannot well controlled. One of the most common causes of diabetes mellitus type 2 is obesity, therefore this disease can be controlled with the appropriate diet regarding to the daily calorie requirement. Hence, the level of blood glucose is maintained. Unfortunately, because the lack of proper diet education and facility, many people cannot work on proper daily healthy diet by their own. In this research Artificial Immune System algorithm was applied to build a model that help diabetes mellitus patient arrange their meal plans. The model can calculate the amount of daily calorie needed and arrange the appropriate daily meal plans based on it. The meal plans vary according to the patient calorie needs. The required input data are age, gender, weight, height, and type of patient daily main activity. The experiments show that this model has a good result. The result is already approaching the patients' daily calorie need, i.e. 97.6% (actual need is not less than 80% and not greater than 100%). Carbohydrate of the meal plan is 55-57% (actual need is not less than 45% and not greater than 60%) whereas the protein approximate 15-18% (actual need is not less than 15% and not greater than 20%) and fat of approximate 22-24% (actual need is not less than 20% and not greater than 25%).

  14. SWANN: The Snow Water Artificial Neural Network Modelling System

    Science.gov (United States)

    Broxton, P. D.; van Leeuwen, W.; Biederman, J. A.

    2017-12-01

    Snowmelt from mountain forests is important for water supply and ecosystem health. Along Arizona's Mogollon Rim, snowmelt contributes to rivers and streams that provide a significant water supply for hydro-electric power generation, agriculture, and human consumption in central Arizona. In this project, we are building a snow monitoring system for the Salt River Project (SRP), which supplies water and power to millions of customers in the Phoenix metropolitan area. We are using process-based hydrological models and artificial neural networks (ANNs) to generate information about both snow water equivalent (SWE) and snow cover. The snow-cover data is generated with ANNs that are applied to Landsat and MODIS satellite reflectance data. The SWE data is generated using a combination of gridded SWE estimates generated by process-based snow models and ANNs that account for variations in topography, forest cover, and solar radiation. The models are trained and evaluated with snow data from SNOTEL stations as well as from aerial LiDAR and field data that we collected this past winter in northern Arizona, as well as with similar data from other sites in the Southwest US. These snow data are produced in near-real time, and we have built a prototype decision support tool to deliver them to SRP. This tool is designed to provide daily-to annual operational monitoring of spatial and temporal changes in SWE and snow cover conditions over the entire Salt River Watershed (covering 17,000 km2), and features advanced web mapping capabilities and watershed analytics displayed as graphical data.

  15. An artificial neural network for modeling reliability, availability and maintainability of a repairable system

    International Nuclear Information System (INIS)

    Rajpal, P.S.; Shishodia, K.S.; Sekhon, G.S.

    2006-01-01

    The paper explores the application of artificial neural networks to model the behaviour of a complex, repairable system. A composite measure of reliability, availability and maintainability parameters has been proposed for measuring the system performance. The artificial neural network has been trained using past data of a helicopter transportation facility. It is used to simulate behaviour of the facility under various constraints. The insights obtained from results of simulation are useful in formulating strategies for optimal operation of the system

  16. 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

  17. Physiological targets of artificial gravity: the sensory-motor system

    NARCIS (Netherlands)

    Groen, E.L.; Clarke, A.; Bles, W.; Wuyts, F.; Paloski, W.; Clément, G.

    2007-01-01

    This chapter describes the pros and cons of artificial gravity applications in relation to human sensory-motor functioning in space. Spaceflight creates a challenge for sensory-motor functions that depend on gravity, which include postural balance, locomotion, eye-hand coordination, and spatial

  18. Classification system for rain fed wheat grain cultivars using artificial ...

    African Journals Online (AJOL)

    Jane

    2011-08-03

    Aug 3, 2011 ... Artificial neural network (ANN) models have found wide applications, including prediction, ... number of hidden layers, this study was done in Islamic Azad University, Shahr-e-Rey Branch, during ... External features describe the boundary information. ... based on Bayes decision theory to classify rice variety.

  19. Express: the reliability of complex systems and artificial intelligence techniques

    International Nuclear Information System (INIS)

    Ancelin, C.; Le, P.; Saint-Quentin, S. de

    1987-01-01

    The probabilistic safety study for the Paluel nuclear power station, commissioned by EDF in 1986, involved development of data processing methods and equipment which was to be given an entirely new impetus by the use of artificial intelligence techniques. The authors describe the salient features of the approach which was adopted and the lessons learnt from the way it was applied in practice [fr

  20. Removal of organic micropollutants in an artificial recharge system

    Science.gov (United States)

    Valhondo, C.; Nödler, K.; Köck-Schulmeyer, M.; Hernandez, M.; Licha, T.; Ayora, C.; Carrera, J.

    2012-04-01

    Emerging contaminants including pharmaceutically active compounds (PhACs), personal care products (PCPs) and pesticides are increasingly being identified in the environment. Emerging pollutants and their transformation products show low concentration in the environment (ng/L), but the effects of the mixtures and lifelong exposure to humans are currently unknown. Many of these contaminants are removed under aerobic conditions in water treatment plants. However, several pharmaceuticals and metabolites present in wastewater are not eliminated by conventional treatment processes. Several lab studies, however, show that the behaviour of many of these micropollutants is affected by the dominant redox conditions. However, data from field experiments are limited and sometimes contradictory. Artificial recharge is a widespread technology to increase the groundwater resources. In this study we propose a design to enhance the natural remediation potential of the aquifer with the installation of a reactive layer at the bottom of the infiltration pond. This layer is a mixture of compost, aquifer material, clay and iron oxide. This layer is intended to provide an extra amount of DOC to the recharge water and to promote biodegradation by means of the development of different redox zones along the travel path through the unsaturated zone and within the aquifer. Moreover, compost, clay and iron oxide of the layer are assumed to increase sorption surfaces for neutral, cationic and anionic compounds, respectively. The infiltration system is sited in Sant Vicenç dels Horts (Barcelona, Spain). It consists of a decantation pond, receiving raw water from the Llobregat River (highly affected from treatment plant effluents), and an infiltration pond (5600 m2). The infiltration rate is around 1 m3/m2/day. The system is equipped with a network of piezometers, suction cups and tensiometers. Infiltration periods have been performed before and after the installation of the reactive layer

  1. The role of artificial intelligence and expert systems in increasing STS operations productivity

    Science.gov (United States)

    Culbert, C.

    1985-01-01

    Artificial Intelligence (AI) is discussed. A number of the computer technologies pioneered in the AI world can make significant contributions to increasing STS operations productivity. Application of expert systems, natural language, speech recognition, and other key technologies can reduce manpower while raising productivity. Many aspects of STS support lend themselves to this type of automation. The artificial intelligence section of the mission planning and analysis division has developed a number of functioning prototype systems which demonstrate the potential gains of applying AI technology.

  2. 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...

  3. Research on artificial intelligence systems for nuclear installations

    International Nuclear Information System (INIS)

    Sakuma, Minoru

    1992-01-01

    The development and utilization of atomic energy in Japan has be advanced in conformity with the long term plan of atomic energy development and utilization decided in 1987. As one of the basic targets, the upbringing of creative and innovative science and technology is put up. Artificial intelligence technology has been positioned as one of the important basic technologies for promoting future atomic energy development. The research and development of artificial intelligence technology have been advanced aiming at making nuclear power stations autonomous, by the guidance of Science and Technology Agency and the cooperation of several research institutes. The upbringing of creative science and technology, the preponderant development of basic technology, the concept of developing the basic technology for atomic energy, the concept of autonomous plants, the standard for autonomy, the approach to autonomous plants, the present state of the researches in respective research institutes on autonomous operation and autonomous maintenance are described. (K.I.)

  4. A quick overview of artificial intelligence and expert systems

    International Nuclear Information System (INIS)

    Engelmore, R.S.

    1989-01-01

    Artificial intelligence (AI) is almost a household word these days. There have been several conferences held in this country over the last two years on artificial intelligence and its applications. The international AI conference at Snowbird, Utah, in 1987 centered on AI applications in the nuclear industry. This paper serves as an introductory overview of the subject of AI for this state-of-the-art review of AI applications in the nuclear industry. We introduce the subject in a way that will be relevant to many people in the nuclear industry who have heard of AI but are not familiar with it and are looking for answers to several simple questions. We attempt to answer those simple questions here and prepare the reader so that he or she can appreciate the following sections on AI applications in the nuclear field. (orig./GL)

  5. Ecological-photosynthetic system for the treatment of swine wastewater in farm; Proceso ecologico-fotosintetico para la depuracion de purines en grajas

    Energy Technology Data Exchange (ETDEWEB)

    Duran Barrantes, M. M.; Alvarez Mateos, P.; Carta Escobar, F.; Romero guzman, F. [Universidad de Sevilla (Spain); Fiestas Ros de Ursinos, J. A. [Instituto de la Grasa. Sevilla (Spain)

    2000-07-01

    The Ecological-Photosynthetic System (Paten n. 8901368, C.S.I.C.) is a low cost process of operational simplicity; his only energetic source is solar radiation. It is based on the ecological development of different communities of microorganisms in order to avoid negative interactions between them, immobilized on clayey support. The present work went in pursuit of the study of an integral biological plant in a piggery farm, from October of 1993 to June of 1995. Its high purification performance and nil running costs make it ideal for treating waste water from small farms. (Author) 13 refs.

  6. Closed-Loop Artificial Pancreas Systems: Engineering the Algorithms

    OpenAIRE

    Doyle, Francis J.; Huyett, Lauren M.; Lee, Joon Bok; Zisser, Howard C.; Dassau, Eyal

    2014-01-01

    In this two-part Bench to Clinic narrative, recent advances in both the preclinical and clinical aspects of artificial pancreas (AP) development are described. In the preceding Bench narrative, Kudva and colleagues provide an in-depth understanding of the modified glucoregulatory physiology of type 1 diabetes that will help refine future AP algorithms. In the Clinic narrative presented here, we compare and evaluate AP technology to gain further momentum toward outpatient trials and eventual a...

  7. Artificial intelligence (AI) systems for interpreting complex medical datasets.

    Science.gov (United States)

    Altman, R B

    2017-05-01

    Advances in machine intelligence have created powerful capabilities in algorithms that find hidden patterns in data, classify objects based on their measured characteristics, and associate similar patients/diseases/drugs based on common features. However, artificial intelligence (AI) applications in medical data have several technical challenges: complex and heterogeneous datasets, noisy medical datasets, and explaining their output to users. There are also social challenges related to intellectual property, data provenance, regulatory issues, economics, and liability. © 2017 ASCPT.

  8. Skin friction related behaviour of artificial turf systems.

    Science.gov (United States)

    Tay, Sock Peng; Fleming, Paul; Hu, Xiao; Forrester, Steph

    2017-08-01

    The occurrence of skin friction related injuries is an issue for artificial turf sports pitches and remains a barrier to their acceptance. The purpose of this study was to evaluate the current industry standard Securisport® Sports Surface Tester that measures skin surface related frictional behaviour of artificial turf. Little research has been published about the device and its efficacy, despite its widespread use as a standard FIFA test instrument. To achieve a range of frictional behaviours, several "third generation" (3G) carpet and infill combinations were investigated; friction time profiles throughout the Securisport rotations were assessed in combination with independent measurements of skin roughness before and after friction testing via 3D surface scanning. The results indicated that carpets without infill had greatest friction (coefficients of friction 0.97-1.20) while those completely filled with sand or rubber had similar and lower values independent of carpet type (coefficient of friction (COF) ≈0.57). Surface roughness of a silicone skin (s-skin) decreased after friction testing, with the largest change on sand infilled surfaces, indicating an "abrasive" polishing effect. The combined data show that the s-skin is damaged in a surface-specific manner, thus the Securisport COF values appear to be a poor measure of the potential for skin abrasion. It is proposed that the change in s-skin roughness improves assessment of the potential for skin damage when players slide on artificial turf.

  9. The Artificial Hamiltonian, First Integrals, and Closed-Form Solutions of Dynamical Systems for Epidemics

    Science.gov (United States)

    Naz, Rehana; Naeem, Imran

    2018-03-01

    The non-standard Hamiltonian system, also referred to as a partial Hamiltonian system in the literature, of the form {\\dot q^i} = {partial H}/{partial {p_i}},\\dot p^i = - {partial H}/{partial {q_i}} + {Γ ^i}(t,{q^i},{p_i}) appears widely in economics, physics, mechanics, and other fields. The non-standard (partial) Hamiltonian systems arise from physical Hamiltonian structures as well as from artificial Hamiltonian structures. We introduce the term `artificial Hamiltonian' for the Hamiltonian of a model having no physical structure. We provide here explicitly the notion of an artificial Hamiltonian for dynamical systems of ordinary differential equations (ODEs). Also, we show that every system of second-order ODEs can be expressed as a non-standard (partial) Hamiltonian system of first-order ODEs by introducing an artificial Hamiltonian. This notion of an artificial Hamiltonian gives a new way to solve dynamical systems of first-order ODEs and systems of second-order ODEs that can be expressed as a non-standard (partial) Hamiltonian system by using the known techniques applicable to the non-standard Hamiltonian systems. We employ the proposed notion to solve dynamical systems of first-order ODEs arising in epidemics.

  10. Multilayer models of photosynthetic membranes. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Brocklehurst, J R; Flanagan, M T

    1982-01-01

    The primary aim of this project has been to build an artificial membrane in which is incorporated, in a functional state, the protein bacteriorhodopsin responsible for generating an electrical potential difference across the membrane of the photosynthetic bacterium, halobacterium halobium, and to investigate the use of this artificial system as the basis of a solar cell. the bacteriorhodopsin has been incorporated into Langmuir-Blodgett multilayers. If ths supporting filter is then illuminated, a potential difference is generated between the two compartments. The lipid in the filter appears to act as a charge carrier for protons, the charge species that forms the electrochemical gradient generated by the bacteriorhodopsin when this molecule absorbs light. The internal resistances of such solar cells were determined and found to be so high that the cells could not be seriously considered as competitors with classical semiconductor cells. Multilayerswere deposited onto filters in which ion carriers that make the filters permeable to sodium ions had been dissolved in the paraffin. The photovoltage obtained indicated that protons transferred from one side of the filter to the other by the action of the bacteriorhodopsin were bing exchanged for sodium ions. A secondary aim of the project has been to examine the possibility of depositing mixed multilayers of a dye and a long chain quinone onto a semiconductor surface. A sensitizing multilayer has been prepared and the mobility of long chain quinones within the layers is high enough to warrant further research. However, it was found that, with the dyes and quinones used, quenched complexes were formed which would not act as sensitizers.

  11. A Framework for Intelligent Instructional Systems: An Artificial Intelligence Machine Learning Approach.

    Science.gov (United States)

    Becker, Lee A.

    1987-01-01

    Presents and develops a general model of the nature of a learning system and a classification for learning systems. Highlights include the relationship between artificial intelligence and cognitive psychology; computer-based instructional systems; intelligent instructional systems; and the role of the learner's knowledge base in an intelligent…

  12. A Novel Artificial Intelligence System for Endotracheal Intubation.

    Science.gov (United States)

    Carlson, Jestin N; Das, Samarjit; De la Torre, Fernando; Frisch, Adam; Guyette, Francis X; Hodgins, Jessica K; Yealy, Donald M

    2016-01-01

    Adequate visualization of the glottic opening is a key factor to successful endotracheal intubation (ETI); however, few objective tools exist to help guide providers' ETI attempts toward the glottic opening in real-time. Machine learning/artificial intelligence has helped to automate the detection of other visual structures but its utility with ETI is unknown. We sought to test the accuracy of various computer algorithms in identifying the glottic opening, creating a tool that could aid successful intubation. We collected a convenience sample of providers who each performed ETI 10 times on a mannequin using a video laryngoscope (C-MAC, Karl Storz Corp, Tuttlingen, Germany). We recorded each attempt and reviewed one-second time intervals for the presence or absence of the glottic opening. Four different machine learning/artificial intelligence algorithms analyzed each attempt and time point: k-nearest neighbor (KNN), support vector machine (SVM), decision trees, and neural networks (NN). We used half of the videos to train the algorithms and the second half to test the accuracy, sensitivity, and specificity of each algorithm. We enrolled seven providers, three Emergency Medicine attendings, and four paramedic students. From the 70 total recorded laryngoscopic video attempts, we created 2,465 time intervals. The algorithms had the following sensitivity and specificity for detecting the glottic opening: KNN (70%, 90%), SVM (70%, 90%), decision trees (68%, 80%), and NN (72%, 78%). Initial efforts at computer algorithms using artificial intelligence are able to identify the glottic opening with over 80% accuracy. With further refinements, video laryngoscopy has the potential to provide real-time, direction feedback to the provider to help guide successful ETI.

  13. PHILOSOPHICAL AND ANTHROPOLOGICAL IMPORTANCE OF DEVELOPMENT OF ARTIFICIALLY CREATED INTELLIGENT SYSTEMS

    Directory of Open Access Journals (Sweden)

    Yu. D. Gensitskiy

    2015-12-01

    Full Text Available Purpose. Understanding the philosophical and anthropological importance of the development the artificial intelligence systems requires the analysis of the socio and anthropological content of intercomputer problems of interaction in the context of media philosophical praxis, anthropological maintenance of intellect nature, considering the specifics of the concept of artificial intelligence systems in the environment of M2M development of socio-cognitive practices of intercomputer interaction of social and humanitarian potential. Methodology. The implementation target is seen in the use of scientific and theoretical basis of the media philosophical, philosophical anthropology, the media philosophical approach to understanding society, science and technology, the use of publications on selected topics of research. Scientific novelty. The concept of artificial intelligence systems in the aspect of social and humanitarian potential of their formation and development in the environment of M2M was considered. The problems of machine learning as technology transformation M2M were analysed. The anthropological threats to the development of artificially created intelligent systems were defined. Conclusions. From the global risks point of view, one of the most critical circumstances due to the artificial intelligent system can strengthen its intelligence very quickly. The obvious reason for suspecting such an opportunity – a recursive self-improvement. Such system becomes smarter, including the intelligent writing of internal cognitive function, that the ability to rewrite their existing cognitive function to make it work better. This will make such systems more intelligent, and smarter in terms of the processing itself. The success of artificial intelligence may be the beginning of the end of the human race. Almost any technology falling into malicious hands reveals the potential for harm, but when it comes to artificial intelligent system, there is a

  14. Challenges facing the distribution of an artificial-intelligence-based system for nursing.

    Science.gov (United States)

    Evans, S

    1985-04-01

    The marketing and successful distribution of artificial-intelligence-based decision-support systems for nursing face special barriers and challenges. Issues that must be confronted arise particularly from the present culture of the nursing profession as well as the typical organizational structures in which nurses predominantly work. Generalizations in the literature based on the limited experience of physician-oriented artificial intelligence applications (predominantly in diagnosis and pharmacologic treatment) must be modified for applicability to other health professions.

  15. Systems-Wide Analysis of Acclimation Responses to Long-Term Heat Stress and Recovery in the Photosynthetic Model Organism Chlamydomonas reinhardtii[W][OPEN

    Science.gov (United States)

    Hemme, Dorothea; Veyel, Daniel; Mühlhaus, Timo; Sommer, Frederik; Jüppner, Jessica; Unger, Ann-Katrin; Sandmann, Michael; Fehrle, Ines; Schönfelder, Stephanie; Steup, Martin; Geimer, Stefan; Kopka, Joachim; Giavalisco, Patrick; Schroda, Michael

    2014-01-01

    We applied a top-down systems biology approach to understand how Chlamydomonas reinhardtii acclimates to long-term heat stress (HS) and recovers from it. For this, we shifted cells from 25 to 42°C for 24 h and back to 25°C for ≥8 h and monitored abundances of 1856 proteins/protein groups, 99 polar and 185 lipophilic metabolites, and cytological and photosynthesis parameters. Our data indicate that acclimation of Chlamydomonas to long-term HS consists of a temporally ordered, orchestrated implementation of response elements at various system levels. These comprise (1) cell cycle arrest; (2) catabolism of larger molecules to generate compounds with roles in stress protection; (3) accumulation of molecular chaperones to restore protein homeostasis together with compatible solutes; (4) redirection of photosynthetic energy and reducing power from the Calvin cycle to the de novo synthesis of saturated fatty acids to replace polyunsaturated ones in membrane lipids, which are deposited in lipid bodies; and (5) when sinks for photosynthetic energy and reducing power are depleted, resumption of Calvin cycle activity associated with increased photorespiration, accumulation of reactive oxygen species scavengers, and throttling of linear electron flow by antenna uncoupling. During recovery from HS, cells appear to focus on processes allowing rapid resumption of growth rather than restoring pre-HS conditions. PMID:25415976

  16. Artificial Intelligence, Expert Systems, Natural Language Interfaces, Knowledge Engineering and the Librarian.

    Science.gov (United States)

    Davies, Jim

    This paper begins by examining concepts of artificial intelligence (AI) and discusses various definitions of the concept that have been suggested in the literature. The nesting relationship of expert systems within the broader framework of AI is described, and expert systems are characterized as knowledge-based systems (KBS) which attempt to solve…

  17. Artificial Intelligence and Expert Systems Research and Their Possible Impact on Information Science.

    Science.gov (United States)

    Borko, Harold

    1985-01-01

    Defines artificial intelligence (AI) and expert systems; describes library applications utilizing AI to automate creation of document representations, request formulations, and design and modify search strategies for information retrieval systems; discusses expert system development for information services; and reviews impact of these…

  18. Design of an artificial intelligence system for safety function maintenance

    International Nuclear Information System (INIS)

    Sharma, D.D.; Miller, D.W.; Chandrasekaran, B.

    1985-01-01

    The safety function (SF) maintenance concept provides a systematic approach to mitigate the consequences of an unforeseen event. Safety functions are a set of actions for mitigating or limiting consequences of a safety threatening event. The current approach to SF maintenance of selecting a success path (SP) from a library of predefined SPs is inadequate because it includes only anticipated modes of challenging an SF. To cover all possible modes of challenging an SF, the library of success paths would be extremely large and difficult to implement on any existing computer. In this paper the authors describe a method based on artificial intelligence (AI) theory of planning to synthesize an SP using available resources to satisfy a hierarchy of safety goals. The method has been applied to SF maintenance of a boiling water reactor (BWR) using data from the Perry nuclear power plant

  19. Testbeam results of the first real-time embedded tracking system with artificial retina

    Energy Technology Data Exchange (ETDEWEB)

    Neri, N., E-mail: nicola.neri@mi.infn.it; Abba, A.; Caponio, F.; Citterio, M.; Coelli, S.; Fu, J.; Merli, A.; Monti, M.; Petruzzo, M.

    2017-02-11

    We present the testbeam results of the first real-time embedded tracking system based on artificial retina algorithm. The tracking system prototype is capable of fast track reconstruction with a latency of the response below 1 μs and track parameter resolutions that are comparable with the offline results. The artificial retina algorithm was implemented in hardware in a custom data acquisition board based on commercial FPGA. The system was tested successfully using a 180 GeV/c proton beam at the CERN SPS with a maximum track rate of about 280 kHz. Online track parameters were found in good agreement with offline results and with the simulated response. - Highlights: • First real-time tracking system based on artificial retina algorithm tested on beam. • Fast track reconstruction within one microsecond latency and offline like quality. • Fast tracking algorithm implemented in commercial FPGAs.

  20. Design and performance of heart assist or artificial heart control systems

    Science.gov (United States)

    Webb, J. A., Jr.; Gebben, V. D.

    1978-01-01

    The factors leading to the design of a controlled driving system for either a heart assist pump or artificial heart are discussed. The system provides square pressure waveform to drive a pneumatic-type blood pump. For assist usage the system uses an R-wave detector circuit that can detect the R-wave of the electrocardiogram in the presence of electrical disturbances. This circuit provides a signal useful for synchronizing an assist pump with the natural heart. It synchronizes a square wave circuit, the output of which is converted into square waveforms of pneumatic pressure suitable for driving both assist device and artificial heart. The pressure levels of the driving waveforms are controlled by means of feedback channels to maintain physiological regulation of the artificial heart's output flow. A more compact system that could achieve similar regulatory characteristics is also discussed.

  1. Artificial intelligence system for the monitoring of natural gas production systems; Intelligente Ueberwachung von Erdgasfoerderanlagen

    Energy Technology Data Exchange (ETDEWEB)

    Tschaetsch, H.U.

    2001-02-01

    The article explains a novel, artificial intelligence-based system called HISS (Human Interface Supervision System) which has been installed as a prototype for the monitoring of a natural gas production site at Thoense near Hannover/Germany. The system is capable to perform audio-visual and smelling functions, analogous to the human sensory perception. (orig./CB) [German] Die Aufrechterhaltung eines einwandfreien Betriebszustandes von technischen Anlagen durch staendige Kontrollen und regelmaessige Wartungsarbeiten ist haeufig eine aufwendige und kostspielige Angelegenheit. Gleichwohl ist sie - sowohl was die Frage der Sicherheit als auch des Umweltschutzes anbelangt - unentbehrlich. Die Erdgasfoerderanlage Thoense bei Hannover wird von einem intelligenten Ueberwachungssystem, HISS - Human Interface Supervision System, kontrolliert, das die menschlichen Eigenschaften sehen, hoeren und riechen beherrscht. (orig.)

  2. Effect of space mutation on photosynthetic characteristics of soybean varieties

    International Nuclear Information System (INIS)

    Liu Xinlei; Ma Yansong; Luan Xiaoyan; Man Weiqun; Xu Dechun; Meng Lifen; Fu Lixin; Zhao Xiaonan; Liu Qi

    2011-01-01

    In order to elucidate the response of the photosynthetic traits of soybean to space mutation, three soybean varieties (lines) of Heinong 48, Heinong 44 and Ha 2291-Y were carried by artificial satellite in 2006 and the net photosynthetic rate (Pn), stomatal conductance (Cond), intercellular CO 2 concentration (Ci) and stomatal resistance (Rs) from SP 1 to SP 4 generation were determined. The results showed that space mutation affected photosynthesis traits of soybean. The photosynthetic rate of soybean varieties by space mutation occurred different levels of genetic variation and the positive mutation rate were higher. Coefficient of variation among generations were SP 2 > SP 3 > SP 4 > CK. Results suggest that space mutation can effectively create soybean materials with higher photosynthetic rate. (authors)

  3. The application of an artificial immune system for solving the identification problem

    Directory of Open Access Journals (Sweden)

    Astachova Irina

    2017-01-01

    Full Text Available Ecological prognosis sets the identification task, which is to find the capacity of pollution sources based on the available experimental data. This problem is an inverse problem, for the solution of which the method of symbolic regression is considered. The distributed artificial immune system is used as an algorithm for the problem solving. The artificial immune system (AIS is a model that allows solving various problems of identification, its concept was borrowed from biology. The solution is sought using a distributed version of the artificial immune system, which is implemented through a network. This distributed network can operate in any heterogeneous environment, which is achieved through the use of cross-platform Python programming language. AIS demonstrates the ability to restore the original function in the problem of identification. The obtained solution for the test data is represented by the graph.

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

    Directory of Open Access Journals (Sweden)

    Karin S. Komati

    2003-01-01

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

  5. A Game Based e-Learning System to Teach Artificial Intelligence in the Computer Sciences Degree

    Science.gov (United States)

    de Castro-Santos, Amable; Fajardo, Waldo; Molina-Solana, Miguel

    2017-01-01

    Our students taking the Artificial Intelligence and Knowledge Engineering courses often encounter a large number of problems to solve which are not directly related to the subject to be learned. To solve this problem, we have developed a game based e-learning system. The elected game, that has been implemented as an e-learning system, allows to…

  6. Artificial intelligence guides system's best practices, cutting costs and improving services.

    Science.gov (United States)

    1999-06-01

    One for the history books. Clinical care improvement initiatives guided by a sophisticated artificial intelligence program have helped a major Virginia integrated health system make dramatic improvements in the cost and quality of its health care services. Find out how the technological innovation has earned Sentara Health System a place in the permanent collection of the Smithsonian's National Museum of American History.

  7. The application of artificial intelligence chemistry diagnostic system to nuclear power plants

    International Nuclear Information System (INIS)

    Chen Meizhen

    1996-01-01

    By processing water chemistry data to diagnose sensor and equipment malfunctions in realtime, artificial intelligence chemistry diagnostic system helps to reduce the plant downtime due to steam generator tubing failures and other accidents. A typical processing system of water chemistry data is presented

  8. [Design of an artificial sphincter system with bio-feedback function based on MSP430].

    Science.gov (United States)

    Wang, Yong-kan; Yan, De-tian

    2005-11-01

    In this paper, we advance a new treating method for rectectomy postoperative anus incontinence, which is called "artificial sphincter system with biofeedback-function". The system simulates the function of human's sphincter and has entered into a stage of simulation experiments on animals.

  9. International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems

    CERN Document Server

    Dash, Subhransu; Panigrahi, Bijaya

    2015-01-01

      The book is a collection of high-quality peer-reviewed research papers presented in Proceedings of International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems (ICAEES 2014) held at Noorul Islam Centre for Higher Education, Kumaracoil, India. These research papers provide the latest developments in the broad area of use of artificial intelligence and evolutionary algorithms in engineering systems. The book discusses wide variety of industrial, engineering and scientific applications of the emerging techniques. It presents invited papers from the inventors/originators of new applications and advanced technologies.

  10. Nanoporous biomaterials for uremic toxin adsorption in artificial kidney systems: A review.

    Science.gov (United States)

    Cheah, Wee-Keat; Ishikawa, Kunio; Othman, Radzali; Yeoh, Fei-Yee

    2017-07-01

    Hemodialysis, one of the earliest artificial kidney systems, removes uremic toxins via diffusion through a semipermeable porous membrane into the dialysate fluid. Miniaturization of the present hemodialysis system into a portable and wearable device to maintain continuous removal of uremic toxins would require that the amount of dialysate used within a closed-system is greatly reduced. Diffused uremic toxins within a closed-system dialysate need to be removed to maintain the optimum concentration gradient for continuous uremic toxin removal by the dialyzer. In this dialysate regenerative system, adsorption of uremic toxins by nanoporous biomaterials is essential. Throughout the years of artificial kidney development, activated carbon has been identified as a potential adsorbent for uremic toxins. Adsorption of uremic toxins necessitates nanoporous biomaterials, especially activated carbon. Nanoporous biomaterials are also utilized in hemoperfusion for uremic toxin removal. Further miniaturization of artificial kidney system and improvements on uremic toxin adsorption capacity would require high performance nanoporous biomaterials which possess not only higher surface area, controlled pore size, but also designed architecture or structure and surface functional groups. This article reviews on various nanoporous biomaterials used in current artificial kidney systems and several emerging nanoporous biomaterials. © 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 105B: 1232-1240, 2017. © 2016 Wiley Periodicals, Inc.

  11. Artificial intelligence enhancements to safety parameter display systems

    International Nuclear Information System (INIS)

    Hajek, B.K.; Hashemi, S.; Sharma, D.; Chandrasekaran, B.; Miller, D.W.

    1986-01-01

    Two prototype knowledge based systems have been developed at The Ohio State University to be the basis of an operator aid that can be attached to an existing nuclear power plant Safety Parameter Display System. The first system uses improved sensor validation techniques to provide input to a fault diagnosis process. The second system would use the diagnostic system output to synthesize corrective procedures to aid the control room licensed operator in plant recovery

  12. A Multiuser Detector Based on Artificial Bee Colony Algorithm for DS-UWB Systems

    Directory of Open Access Journals (Sweden)

    Zhendong Yin

    2013-01-01

    Full Text Available Artificial Bee Colony (ABC algorithm is an optimization algorithm based on the intelligent behavior of honey bee swarm. The ABC algorithm was developed to solve optimizing numerical problems and revealed premising results in processing time and solution quality. In ABC, a colony of artificial bees search for rich artificial food sources; the optimizing numerical problems are converted to the problem of finding the best parameter which minimizes an objective function. Then, the artificial bees randomly discover a population of initial solutions and then iteratively improve them by employing the behavior: moving towards better solutions by means of a neighbor search mechanism while abandoning poor solutions. In this paper, an efficient multiuser detector based on a suboptimal code mapping multiuser detector and artificial bee colony algorithm (SCM-ABC-MUD is proposed and implemented in direct-sequence ultra-wideband (DS-UWB systems under the additive white Gaussian noise (AWGN channel. The simulation results demonstrate that the BER and the near-far effect resistance performances of this proposed algorithm are quite close to those of the optimum multiuser detector (OMD while its computational complexity is much lower than that of OMD. Furthermore, the BER performance of SCM-ABC-MUD is not sensitive to the number of active users and can obtain a large system capacity.

  13. Biotechnological Approaches to Enhance Halotolerance and Photosynthetic Efficacy in the Cyanobacterium, Fremyella diplosiphon

    Science.gov (United States)

    Tabatabai, Ben

    Growing concerns over dwindling energy supplies linked to nonrenewable fossil fuels have driven profound interest in biofuels as a clean and sustainable alternative. Cyanobacteria are a promising source of third-generation biofuel due to their fast generation time and high net biomass conversion. In this study, the effect of salinity stress on Fremyella diplosiphon, a model organism for studying photosynthetic pathways, was investigated and nanobiotechnological approaches undertaken to enhance its halotolerance and photosynthetic efficacy. Heat-induced mutagenesis resulted in a mutant strain that could survive in 20 g L-1 sodium chloride (NaCl) with no loss in pigmentation. To further enhance F. diplosiphon halotolerance, expression plasmids harboring the hlyB and mdh genes were overexpressed in the wild type resulting in two transformants that thrived in 35 g L-1 NaCl, the average salinity of sea water. In addition, no significant reduction in photosynthetic efficacy was detected in the halotolerant strains relative to the wild type. Total lipid content and fatty acid methyl ester composition of wild type and halotolerant strains were assessed for their potential as a production-scale biofuel agent. Methyl palmitate, the methyl ester of hexodeconoate (C16:0), was found to be most abundant in the wild type and transformants accounting for 60-70% of total FAMEs produced. Efforts to enhance the photosynthetic efficiency of the strains revealed that gold nanoparticle-derived surface plasmon resonance augmented culture growth and pigment accumulation. Cell-nanoparticles interactions were visualized using scanning and transmission electron microscopy. Our findings address two key challenges that cyanobacterial biofuel agents need to overcome: enhanced halotolerance and photosynthetic efficacy to minimize freshwater input and artificial light supply. These innovations have paved the way for an efficient cyanobacterial cultivation system for large-scale production of

  14. Vein matching using artificial neural network in vein authentication systems

    Science.gov (United States)

    Noori Hoshyar, Azadeh; Sulaiman, Riza

    2011-10-01

    Personal identification technology as security systems is developing rapidly. Traditional authentication modes like key; password; card are not safe enough because they could be stolen or easily forgotten. Biometric as developed technology has been applied to a wide range of systems. According to different researchers, vein biometric is a good candidate among other biometric traits such as fingerprint, hand geometry, voice, DNA and etc for authentication systems. Vein authentication systems can be designed by different methodologies. All the methodologies consist of matching stage which is too important for final verification of the system. Neural Network is an effective methodology for matching and recognizing individuals in authentication systems. Therefore, this paper explains and implements the Neural Network methodology for finger vein authentication system. Neural Network is trained in Matlab to match the vein features of authentication system. The Network simulation shows the quality of matching as 95% which is a good performance for authentication system matching.

  15. Simulation of excitonic optical line shapes of cyclic oligomers - models for basic units of photosynthetic antenna systems: Transfer integral versus local energy fluctuations with dichotomic coloured noise

    International Nuclear Information System (INIS)

    Barvik, I.; Reineker, P.; Warns, C.; Neidlinger, T.

    1995-08-01

    For Frenkel excitons moving on cyclic and linear molecular chains modeling in part photosynthetic antenna systems we investigate the influence of dynamic and static disorder on their optical line shapes. The dynamic disorder describes the influence of vibrational degrees of freedom and is taken into account by fluctuations of the transfer matrix element between neighbouring molecules. The fluctuations are represented by dichotomic Markov processes with coloured noise. We obtain a closed set of equations of motion for the correlation functions determining the optical line shape which is solved exactly. The line shapes are discussed for various sets of the model parameters and arrangements of molecules and their dipole moments. (author). 63 refs, 10 figs

  16. [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.

  17. Artificial intelligence and medical imaging. Expert systems and image analysis

    International Nuclear Information System (INIS)

    Wackenheim, A.; Zoellner, G.; Horviller, S.; Jacqmain, T.

    1987-01-01

    This paper gives an overview on the existing systems for automated image analysis and interpretation in medical imaging, especially in radiology. The example of ORFEVRE, the system for the analysis of CAT-scan images of the cervical triplet (c3-c5) by image analysis and subsequent expert-system is given and discussed in detail. Possible extensions are described [fr

  18. Utilization of artificial intelligence techniques for the Space Station power system

    Science.gov (United States)

    Evatt, Thomas C.; Gholdston, Edward W.

    1988-01-01

    Due to the complexity of the Space Station Electrical Power System (EPS) as currently envisioned, artificial intelligence/expert system techniques are being investigated to automate operations, maintenance, and diagnostic functions. A study was conducted to investigate this technology as it applies to failure detection, isolation, and reconfiguration (FDIR) and health monitoring of power system components and of the total system. Control system utilization of expert systems for load scheduling and shedding operations was also researched. A discussion of the utilization of artificial intelligence/expert systems for Initial Operating Capability (IOC) for the Space Station effort is presented along with future plans at Rocketdyne for the utilization of this technology for enhanced Space Station power capability.

  19. Cognitive Connected Vehicle Information System Design Requirement for Safety: Role of Bayesian Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Ata Khan

    2013-04-01

    Full Text Available Intelligent transportation systems (ITS are gaining acceptance around the world and the connected vehicle component of ITS is recognized as a high priority research and development area in many technologically advanced countries. Connected vehicles are expected to have the capability of safe, efficient and eco-driving operations whether these are under human control or in the adaptive machine control mode of operations. The race is on to design the capability to operate in connected traffic environment. The operational requirements can be met with cognitive vehicle design features made possible by advances in artificial intelligence-supported methodology, improved understanding of human factors, and advances in communication technology. This paper describes cognitive features and their information system requirements. The architecture of an information system is presented that supports the features of the cognitive connected vehicle. For better focus, information processing capabilities are specified and the role of Bayesian artificial intelligence is defined for data fusion. Example applications illustrate the role of information systems in integrating intelligent technology, Bayesian artificial intelligence, and abstracted human factors. Concluding remarks highlight the role of the information system and Bayesian artificial intelligence in the design of a new generation of cognitive connected vehicle.

  20. Diagnosis - Using automatic test equipment and artificial intelligence expert systems

    Science.gov (United States)

    Ramsey, J. E., Jr.

    Three expert systems (ATEOPS, ATEFEXPERS, and ATEFATLAS), which were created to direct automatic test equipment (ATE), are reviewed. The purpose of the project was to develop an expert system to troubleshoot the converter-programmer power supply card for the F-15 aircraft and have that expert system direct the automatic test equipment. Each expert system uses a different knowledge base or inference engine, basing the testing on the circuit schematic, test requirements document, or ATLAS code. Implementing generalized modules allows the expert systems to be used for any different unit under test. Using converted ATLAS to LISP code allows the expert system to direct any ATE using ATLAS. The constraint propagated frame system allows for the expansion of control by creating the ATLAS code, checking the code for good software engineering techniques, directing the ATE, and changing the test sequence as needed (planning).

  1. Artificial intelligence costs, benefits, and risks for selected spacecraft ground system automation scenarios

    Science.gov (United States)

    Truszkowski, Walter F.; Silverman, Barry G.; Kahn, Martha; Hexmoor, Henry

    1988-01-01

    In response to a number of high-level strategy studies in the early 1980s, expert systems and artificial intelligence (AI/ES) efforts for spacecraft ground systems have proliferated in the past several years primarily as individual small to medium scale applications. It is useful to stop and assess the impact of this technology in view of lessons learned to date, and hopefully, to determine if the overall strategies of some of the earlier studies both are being followed and still seem relevant. To achieve that end four idealized ground system automation scenarios and their attendant AI architecture are postulated and benefits, risks, and lessons learned are examined and compared. These architectures encompass: (1) no AI (baseline); (2) standalone expert systems; (3) standardized, reusable knowledge base management systems (KBMS); and (4) a futuristic unattended automation scenario. The resulting artificial intelligence lessons learned, benefits, and risks for spacecraft ground system automation scenarios are described.

  2. Artificial intelligence costs, benefits, risks for selected spacecraft ground system automation scenarios

    Science.gov (United States)

    Truszkowski, Walter F.; Silverman, Barry G.; Kahn, Martha; Hexmoor, Henry

    1988-01-01

    In response to a number of high-level strategy studies in the early 1980s, expert systems and artificial intelligence (AI/ES) efforts for spacecraft ground systems have proliferated in the past several years primarily as individual small to medium scale applications. It is useful to stop and assess the impact of this technology in view of lessons learned to date, and hopefully, to determine if the overall strategies of some of the earlier studies both are being followed and still seem relevant. To achieve that end four idealized ground system automation scenarios and their attendant AI architecture are postulated and benefits, risks, and lessons learned are examined and compared. These architectures encompass: (1) no AI (baseline), (2) standalone expert systems, (3) standardized, reusable knowledge base management systems (KBMS), and (4) a futuristic unattended automation scenario. The resulting artificial intelligence lessons learned, benefits, and risks for spacecraft ground system automation scenarios are described.

  3. Photosynthetic Pigments in Diatoms

    OpenAIRE

    Kuczynska, Paulina; Jemiola-Rzeminska, Malgorzata; Strzalka, Kazimierz

    2015-01-01

    Photosynthetic pigments are bioactive compounds of great importance for the food, cosmetic, and pharmaceutical industries. They are not only responsible for capturing solar energy to carry out photosynthesis, but also play a role in photoprotective processes and display antioxidant activity, all of which contribute to effective biomass and oxygen production. Diatoms are organisms of a distinct pigment composition, substantially different from that present in plants. Apart from light-harvestin...

  4. Artificial lateral-line system for imaging dipole sources using Beamforming techniques

    NARCIS (Netherlands)

    Dagamseh, A.M.K.; Wiegerink, Remco J.; Lammerink, Theodorus S.J.; Krijnen, Gijsbertus J.M.

    In nature, fish have the ability to localize prey, school, navigate, etc. using the lateral-line organ [1]. Here we present the use of biomimetic artificial hair-based flow-sensors arranged as lateral-line system in combination with beamforming techniques for dipole source localization in air.

  5. Applications of artificial intelligence systems in the analysis of epidemiological data.

    Science.gov (United States)

    Flouris, Andreas D; Duffy, Jack

    2006-01-01

    A brief review of the germane literature suggests that the use of artificial intelligence (AI) statistical algorithms in epidemiology has been limited. We discuss the advantages and disadvantages of using AI systems in large-scale sets of epidemiological data to extract inherent, formerly unidentified, and potentially valuable patterns that human-driven deductive models may miss.

  6. Intelligent Tutoring System: A Tool for Testing the Research Curiosities of Artificial Intelligence Researchers

    Science.gov (United States)

    Yaratan, Huseyin

    2003-01-01

    An ITS (Intelligent Tutoring System) is a teaching-learning medium that uses artificial intelligence (AI) technology for instruction. Roberts and Park (1983) defines AI as the attempt to get computers to perform tasks that if performed by a human-being, intelligence would be required to perform the task. The design of an ITS comprises two distinct…

  7. Artificial neural network decision support systems for new product development project selection

    NARCIS (Netherlands)

    Thieme, R.J.; Song, Michael; Calantone, R.J.

    2000-01-01

    The authors extend and develop an artificial neural network decision support system and demonstrate how it can guide managers when they make complex new product development decisions. The authors use data from 612 projects to compare this new method with traditional methods for predicting various

  8. Optimal routes scheduling for municipal waste disposal garbage trucks using evolutionary algorithm and artificial immune system

    Directory of Open Access Journals (Sweden)

    Bogna MRÓWCZYŃSKA

    2011-01-01

    Full Text Available This paper describes an application of an evolutionary algorithm and an artificial immune systems to solve a problem of scheduling an optimal route for waste disposal garbage trucks in its daily operation. Problem of an optimisation is formulated and solved using both methods. The results are presented for an area in one of the Polish cities.

  9. An open and configurable embedded system for EMG pattern recognition implementation for artificial arms.

    Science.gov (United States)

    Jun Liu; Fan Zhang; Huang, He Helen

    2014-01-01

    Pattern recognition (PR) based on electromyographic (EMG) signals has been developed for multifunctional artificial arms for decades. However, assessment of EMG PR control for daily prosthesis use is still limited. One of the major barriers is the lack of a portable and configurable embedded system to implement the EMG PR control. This paper aimed to design an open and configurable embedded system for EMG PR implementation so that researchers can easily modify and optimize the control algorithms upon our designed platform and test the EMG PR control outside of the lab environments. The open platform was built on an open source embedded Linux Operating System running a high-performance Gumstix board. Both the hardware and software system framework were openly designed. The system was highly flexible in terms of number of inputs/outputs and calibration interfaces used. Such flexibility enabled easy integration of our embedded system with different types of commercialized or prototypic artificial arms. Thus far, our system was portable for take-home use. Additionally, compared with previously reported embedded systems for EMG PR implementation, our system demonstrated improved processing efficiency and high system precision. Our long-term goals are (1) to develop a wearable and practical EMG PR-based control for multifunctional artificial arms, and (2) to quantify the benefits of EMG PR-based control over conventional myoelectric prosthesis control in a home setting.

  10. Diagnosis aids with artificial intelligence in the PSAD system

    International Nuclear Information System (INIS)

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

    1996-01-01

    To improve monitoring and diagnosis capabilities in nuclear power plants, Electricite de France (EDF) has designed an integrated monitoring and diagnosis assistance system: PSAD - Poste de Surveillance et d'Aide au Diagnostic. The development of this sophisticated monitoring and data processing system requires the addition of analysis and diagnosis assistance capabilities. Diagnostic knowledge based systems have thus been added to the functions monitored in PSAD: DIVA for turbine generators, and DIAPO for reactor coolant pumps. These systems rely on a representation of the diagnostic reasoning process of experts and of supporting knowledge. Diagnosis in both systems is performed through an abductive reasoning process applied to component fault models and observations derived from their actual behavior, as provided by the monitoring functions. The basic theoretical elements of this diagnostic model are summarized in a first part of this paper. In a second part, DIVA and DIAPO specific elements are described. (authors)

  11. A Fault Diagnosis Approach for the Hydraulic System by Artificial Neural Networks

    OpenAIRE

    Xiangyu He; Shanghong He

    2014-01-01

    Based on artificial neural networks, a fault diagnosis approach for the hydraulic system was proposed in this paper. Normal state samples were used as the training data to develop a dynamic general regression neural network (DGRNN) model. The trained DGRNN model then served as the fault determinant to diagnose test faults and the work condition of the hydraulic system was identified. Several typical faults of the hydraulic system were used to verify the fault diagnosis approach. Experiment re...

  12. Applications of artificial intelligence and expert systems in ANGRA-I emergency preparedness - The Brazilian case

    International Nuclear Information System (INIS)

    Alvarenga, M.A.B.; Guimaraes, A.C.F.

    1991-01-01

    This study describes a system to follow a nuclear accident and points the areas where the presence of artificial intelligence could be necessary: diagnostics systems, emergency classification, accident management strategies and protective actions. Logical rules could be combined with deterministic equations to provide an expert system prototype to manage a nuclear emergency preparedness for nuclear reactors (fast or thermal) in the Brazilian Nuclear Energy National Commission. (CNEN). (author)

  13. Special Issue: New trends and applications on hybrid artificial intelligence systems

    OpenAIRE

    Corchado Rodríguez, Emilio; Graña Romay, Manuel; Woźniak, MichaŁ

    2017-01-01

    This Special Issue is an outgrowth of the HAIS'10, the 5th International Conference on Hybrid Artificial Intelligence Systems, which was held in San Sebastián, Spain, 23–25 June 2010. The HAIS conference series is devoted to the presentation of innovative techniques involving the hybridization of emerging and active topics in data mining and decision support systems, information fusion, evolutionary computation, visualization techniques, ensemble models, intelligent agent-based systems (compl...

  14. 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...

  15. The twenty first century informatization and artificial intelligence system

    International Nuclear Information System (INIS)

    Noh, Jung Ho

    1999-12-01

    The contents of this book are competition of mental weakness and visually handicapped people, barbarian about the knowledge of commodity, we are living in notion of time of the agricultural age, parade of informatization of fool. Is there a successful case of informatization when it is done as others do?, what is technology of informatization?, there is mistake in traditional information technology from a system of thought, information system, and analysis of improvement of industrial structure case of development for program case of system installation, and a thief free society.

  16. The twenty first century informatization and artificial intelligence system

    Energy Technology Data Exchange (ETDEWEB)

    Noh, Jung Ho

    1999-12-15

    The contents of this book are competition of mental weakness and visually handicapped people, barbarian about the knowledge of commodity, we are living in notion of time of the agricultural age, parade of informatization of fool. Is there a successful case of informatization when it is done as others do?, what is technology of informatization?, there is mistake in traditional information technology from a system of thought, information system, and analysis of improvement of industrial structure case of development for program case of system installation, and a thief free society.

  17. Effect of Artificial Gravity: Central Nervous System Neurochemical Studies

    Science.gov (United States)

    Fox, Robert A.; D'Amelio, Fernando; Eng, Lawrence F.

    1997-01-01

    The major objective of this project was to assess chemical and morphological modifications occurring in muscle receptors and the central nervous system of animals subjected to altered gravity (2 x Earth gravity produced by centrifugation and simulated micro gravity produced by hindlimb suspension). The underlying hypothesis for the studies was that afferent (sensory) information sent to the central nervous system by muscle receptors would be changed in conditions of altered gravity and that these changes, in turn, would instigate a process of adaptation involving altered chemical activity of neurons and glial cells of the projection areas of the cerebral cortex that are related to inputs from those muscle receptors (e.g., cells in the limb projection areas). The central objective of this research was to expand understanding of how chronic exposure to altered gravity, through effects on the vestibular system, influences neuromuscular systems that control posture and gait. The project used an approach in which molecular changes in the neuromuscular system were related to the development of effective motor control by characterizing neurochemical changes in sensory and motor systems and relating those changes to motor behavior as animals adapted to altered gravity. Thus, the objective was to identify changes in central and peripheral neuromuscular mechanisms that are associated with the re-establishment of motor control which is disrupted by chronic exposure to altered gravity.

  18. A Red-Light Running Prevention System Based on Artificial Neural Network and Vehicle Trajectory Data

    Directory of Open Access Journals (Sweden)

    Pengfei Li

    2014-01-01

    Full Text Available The high frequency of red-light running and complex driving behaviors at the yellow onset at intersections cannot be explained solely by the dilemma zone and vehicle kinematics. In this paper, the author presented a red-light running prevention system which was based on artificial neural networks (ANNs to approximate the complex driver behaviors during yellow and all-red clearance and serve as the basis of an innovative red-light running prevention system. The artificial neural network and vehicle trajectory are applied to identify the potential red-light runners. The ANN training time was also acceptable and its predicting accurate rate was over 80%. Lastly, a prototype red-light running prevention system with the trained ANN model was described. This new system can be directly retrofitted into the existing traffic signal systems.

  19. A red-light running prevention system based on artificial neural network and vehicle trajectory data.

    Science.gov (United States)

    Li, Pengfei; Li, Yan; Guo, Xiucheng

    2014-01-01

    The high frequency of red-light running and complex driving behaviors at the yellow onset at intersections cannot be explained solely by the dilemma zone and vehicle kinematics. In this paper, the author presented a red-light running prevention system which was based on artificial neural networks (ANNs) to approximate the complex driver behaviors during yellow and all-red clearance and serve as the basis of an innovative red-light running prevention system. The artificial neural network and vehicle trajectory are applied to identify the potential red-light runners. The ANN training time was also acceptable and its predicting accurate rate was over 80%. Lastly, a prototype red-light running prevention system with the trained ANN model was described. This new system can be directly retrofitted into the existing traffic signal systems.

  20. A Red-Light Running Prevention System Based on Artificial Neural Network and Vehicle Trajectory Data

    Science.gov (United States)

    Li, Pengfei; Li, Yan; Guo, Xiucheng

    2014-01-01

    The high frequency of red-light running and complex driving behaviors at the yellow onset at intersections cannot be explained solely by the dilemma zone and vehicle kinematics. In this paper, the author presented a red-light running prevention system which was based on artificial neural networks (ANNs) to approximate the complex driver behaviors during yellow and all-red clearance and serve as the basis of an innovative red-light running prevention system. The artificial neural network and vehicle trajectory are applied to identify the potential red-light runners. The ANN training time was also acceptable and its predicting accurate rate was over 80%. Lastly, a prototype red-light running prevention system with the trained ANN model was described. This new system can be directly retrofitted into the existing traffic signal systems. PMID:25435870

  1. Artificial activation of toxin-antitoxin systems as an antibacterial strategy.

    Science.gov (United States)

    Williams, Julia J; Hergenrother, Paul J

    2012-06-01

    Toxin-antitoxin (TA) systems are unique modules that effect plasmid stabilization via post-segregational killing of the bacterial host. The genes encoding TA systems also exist on bacterial chromosomes, and it has been speculated that these are involved in a variety of cellular processes. Interest in TA systems has increased dramatically over the past 5 years as the ubiquitous nature of TA genes on bacterial genomes has been revealed. The exploitation of TA systems as an antibacterial strategy via artificial activation of the toxin has been proposed and has considerable potential; however, efforts in this area remain in the early stages and several major questions remain. This review investigates the tractability of targeting TA systems to kill bacteria, including fundamental requirements for success, recent advances, and challenges associated with artificial toxin activation. Copyright © 2012 Elsevier Ltd. All rights reserved.

  2. Overload control of artificial gravity facility using spinning tether system for high eccentricity transfer orbits

    Science.gov (United States)

    Gou, Xing-wang; Li, Ai-jun; Tian, Hao-chang; Wang, Chang-qing; Lu, Hong-shi

    2018-06-01

    As the major part of space life supporting systems, artificial gravity requires further study before it becomes mature. Spinning tether system is a good alternative solution to provide artificial gravity for the whole spacecraft other than additional devices, and its longer tether length could significantly reduce spinning velocity and thus enhance comfortability. An approximated overload-based feedback method is proposed to provide estimated spinning velocity signals for controller, so that gravity level could be accurately controlled without complicated GPS modules. System behavior in high eccentricity transfer orbits is also studied to give a complete knowledge of the spinning stabilities. The application range of the proposed method is studied in various orbit cases and spinning velocities, indicating that it is accurate and reliable for most of the mission phases especially for the final constant gravity level phase. In order to provide stable gravity level for transfer orbit missions, a sliding mode controller based on estimated angular signals is designed for closed-loop control. Numerical results indicate that the combination of overload-based feedback and sliding mode controller could satisfy most of the long-term artificial gravity missions. It is capable of forming flexible gravity environment in relatively good accuracy even in the lowest possible orbital radiuses and high eccentricity orbits of crewed space missions. The proposed scheme provides an effective tether solution for the artificial gravity construction in interstellar travel.

  3. A theoretical approach to artificial intelligence systems in medicine.

    Science.gov (United States)

    Spyropoulos, B; Papagounos, G

    1995-10-01

    The various theoretical models of disease, the nosology which is accepted by the medical community and the prevalent logic of diagnosis determine both the medical approach as well as the development of the relevant technology including the structure and function of the A.I. systems involved. A.I. systems in medicine, in addition to the specific parameters which enable them to reach a diagnostic and/or therapeutic proposal, entail implicitly theoretical assumptions and socio-cultural attitudes which prejudice the orientation and the final outcome of the procedure. The various models -causal, probabilistic, case-based etc. -are critically examined and their ethical and methodological limitations are brought to light. The lack of a self-consistent theoretical framework in medicine, the multi-faceted character of the human organism as well as the non-explicit nature of the theoretical assumptions involved in A.I. systems restrict them to the role of decision supporting "instruments" rather than regarding them as decision making "devices". This supporting role and, especially, the important function which A.I. systems should have in the structure, the methods and the content of medical education underscore the need of further research in the theoretical aspects and the actual development of such systems.

  4. A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence

    CERN Document Server

    Vlassis, Nikos

    2007-01-01

    Multiagent systems is an expanding field that blends classical fields like game theory and decentralized control with modern fields like computer science and machine learning. This monograph provides a concise introduction to the subject, covering the theoretical foundations as well as more recent developments in a coherent and readable manner. The text is centered on the concept of an agent as decision maker. Chapter 1 is a short introduction to the field of multiagent systems. Chapter 2 covers the basic theory of singleagent decision making under uncertainty. Chapter 3 is a brief introductio

  5. Discrete simulation system based on artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Futo, I; Szeredi, J

    1982-01-01

    A discrete event simulation system based on the AI language Prolog is presented. The system called t-Prolog extends the traditional possibilities of simulation languages toward automatic problem solving by using backtrack in time and automatic model modification depending on logical deductions. As t-Prolog is an interactive tool, the user has the possibility to interrupt the simulation run to modify the model or to force it to return to a previous state for trying possible alternatives. It admits the construction of goal-oriented or goal-seeking models with variable structure. Models are defined in a restricted version of the first order predicate calculus using Horn clauses. 21 references.

  6. A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms

    Directory of Open Access Journals (Sweden)

    Gys Albertus Marthinus Meiring

    2015-12-01

    Full Text Available In this paper the various driving style analysis solutions are investigated. An in-depth investigation is performed to identify the relevant machine learning and artificial intelligence algorithms utilised in current driver behaviour and driving style analysis systems. This review therefore serves as a trove of information, and will inform the specialist and the student regarding the current state of the art in driver style analysis systems, the application of these systems and the underlying artificial intelligence algorithms applied to these applications. The aim of the investigation is to evaluate the possibilities for unique driver identification utilizing the approaches identified in other driver behaviour studies. It was found that Fuzzy Logic inference systems, Hidden Markov Models and Support Vector Machines consist of promising capabilities to address unique driver identification algorithms if model complexity can be reduced.

  7. A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms.

    Science.gov (United States)

    Meiring, Gys Albertus Marthinus; Myburgh, Hermanus Carel

    2015-12-04

    In this paper the various driving style analysis solutions are investigated. An in-depth investigation is performed to identify the relevant machine learning and artificial intelligence algorithms utilised in current driver behaviour and driving style analysis systems. This review therefore serves as a trove of information, and will inform the specialist and the student regarding the current state of the art in driver style analysis systems, the application of these systems and the underlying artificial intelligence algorithms applied to these applications. The aim of the investigation is to evaluate the possibilities for unique driver identification utilizing the approaches identified in other driver behaviour studies. It was found that Fuzzy Logic inference systems, Hidden Markov Models and Support Vector Machines consist of promising capabilities to address unique driver identification algorithms if model complexity can be reduced.

  8. Towards Realization of Intelligent Medical Treatment at Nanoscale by Artificial Microscopic Swarm Control Systems

    Directory of Open Access Journals (Sweden)

    Alireza Rowhanimanesh

    2017-07-01

    Full Text Available Background: In this paper, the novel concept of artificial microscopic swarm control systems is proposed as a promising approach towards realization of intelligent medical treatment at nanoscale. In this new paradigm, treatment is done autonomously at nanoscale within the patient’s body by the proposed swarm control systems.Methods: From control engineering perspective, medical treatment can be considered as a control problem, in which the ultimate goal is to find the best feasible way to change the state of diseased tissue from unhealthy to healthy in presence of uncertainty. Although a living tissue is a huge swarm of microscopic cells, nearly all of the common treatment methods are based on macroscopic centralized control paradigm. Inspired by natural microscopic swarm control systems such as nervous, endocrine and immune systems that work based on swarm control paradigm, medical treatment needs a paradigm shift from macroscopic centralized control to microscopic swarm control. An artificial microscopic swarm control system consists of a huge number of very simple autonomous microscopic agents that exploit swarm intelligence to realize sense, control (computing and actuation at nanoscale in local, distributed and decentralized manner. This control system can be designed based on mathematical analysis and computer simulation.Results: The proposed approach is used for treatment of atherosclerosis and cancer based on mathematical analysis and in-silico study.Conclusion: The notion of artificial microscopic swarm control systems opens new doors towards realization of autonomous and intelligent medical treatment at nanoscale within the patient’s body.

  9. Artificial Intelligence Systems as Prognostic and Predictive Tools in Ovarian Cancer.

    Science.gov (United States)

    Enshaei, A; Robson, C N; Edmondson, R J

    2015-11-01

    The ability to provide accurate prognostic and predictive information to patients is becoming increasingly important as clinicians enter an era of personalized medicine. For a disease as heterogeneous as epithelial ovarian cancer, conventional algorithms become too complex for routine clinical use. This study therefore investigated the potential for an artificial intelligence model to provide this information and compared it with conventional statistical approaches. The authors created a database comprising 668 cases of epithelial ovarian cancer during a 10-year period and collected data routinely available in a clinical environment. They also collected survival data for all the patients, then constructed an artificial intelligence model capable of comparing a variety of algorithms and classifiers alongside conventional statistical approaches such as logistic regression. The model was used to predict overall survival and demonstrated that an artificial neural network (ANN) algorithm was capable of predicting survival with high accuracy (93 %) and an area under the curve (AUC) of 0.74 and that this outperformed logistic regression. The model also was used to predict the outcome of surgery and again showed that ANN could predict outcome (complete/optimal cytoreduction vs. suboptimal cytoreduction) with 77 % accuracy and an AUC of 0.73. These data are encouraging and demonstrate that artificial intelligence systems may have a role in providing prognostic and predictive data for patients. The performance of these systems likely will improve with increasing data set size, and this needs further investigation.

  10. Artificial intelligence in conceptual design of intelligent manufacturing systems: A state of the art review

    OpenAIRE

    Petrović, Milica M.; Miljković, Zoran Đ.; Babić, Bojan R.

    2013-01-01

    Intelligent manufacturing systems (IMS), as the highest class of flexible manufacturing systems, are able to adapt to market changes applying methods of artificial intelligence. This paper presents a detailed review of the following IMS functions: (i) process planning optimization, (ii) scheduling optimization, (iii) integrated process planning and scheduling, and (iv) mobile robot scheduling for internal material transport tasks. The research presented in this paper shows that improved perfo...

  11. Artificial intelligence and tutoring systems computational and cognitive approaches to the communication of knowledge

    CERN Document Server

    Wenger, Etienne

    2014-01-01

    Artificial Intelligence and Tutoring Systems: Computational and Cognitive Approaches to the Communication of Knowledge focuses on the cognitive approaches, methodologies, principles, and concepts involved in the communication of knowledge. The publication first elaborates on knowledge communication systems, basic issues, and tutorial dialogues. Concerns cover natural reasoning and tutorial dialogues, shift from local strategies to multiple mental models, domain knowledge, pedagogical knowledge, implicit versus explicit encoding of knowledge, knowledge communication, and practical and theoretic

  12. 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.

  13. Procedure for Selection of Suitable Resources in Interactions in Complex Dynamic Systems Using Artificial Immunity

    Directory of Open Access Journals (Sweden)

    Naors Y. anadalsaleem

    2017-03-01

    Full Text Available The dynamic optimization procedure for -dimensional vector function of a system, the state of which is interpreted as adaptable immune cell, is considered Using the results of the theory of artificial immune systems. The procedures for estimate of monitoring results are discussed. The procedure for assessing the entropy is recommended as a general recursive estimation algorithm. The results are focused on solving the optimization problems of cognitive selection of suitable physical resources, what expands the scope of Electromagnetic compatibility.

  14. An on-line gas control system using an artificial intelligence language: PROLOG II

    International Nuclear Information System (INIS)

    Lai, C.

    1990-01-01

    An application of Artificial Intelligence to a real physics experiment is presented. This allows comparison with classical programming techniques. The PROLOG language appears as a convenient on-line language, easily interfaced to the low level service routines, for which algorithmic languages can still be used. Steering modules have been written for a gas acquisition and analysis program, and for a control system with graphic human interface. This system includes safety rules and automatic action sequences

  15. Illumination properties and energy savings of a solar fiber optic lighting system balanced by artificial lights

    OpenAIRE

    Lingfors, David

    2013-01-01

    A solar fiber optic lighting system, SP3 from the Swedish company Parans Solar Lighting AB, has been installed in a study area/corridor test site. A collector is tracking the sun during daytime, focusing the direct sun irradiance via Fresnel lenses into optical fibers, which guide the solar light into the building. The illumination properties of the system have been characterized. The energy saving due to reduced need of artificial lighting have been calculated and methods for balancing the a...

  16. Neutron spectrometry and dosimetry by means of Bonner spheres system and artificial neural networks applying robust design of artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Martinez B, M.R.; Ortiz R, J.M.; Vega C, H.R. [UAZ, Av. Ramon Lopez Velarde No. 801, 98000 Zacatecas (Mexico)

    2006-07-01

    An Artificial Neural Network has been designed, trained and tested to unfold neutron spectra and simultaneously to calculate equivalent doses. A set of 187 neutron spectra compiled by the International Atomic Energy Agency and 13 equivalent doses were used in the artificial neural network designed, trained and tested. In order to design the neural network was used the robust design of artificial neural networks methodology, which assures that the quality of the neural networks takes into account from the design stage. Unless previous works, here, for first time a group of neural networks were designed and trained to unfold 187 neutron spectra and at the same time to calculate 13 equivalent doses, starting from the count rates coming from the Bonner spheres system by using a systematic and experimental strategy. (Author)

  17. Neutron spectrometry and dosimetry by means of Bonner spheres system and artificial neural networks applying robust design of artificial neural networks

    International Nuclear Information System (INIS)

    Martinez B, M.R.; Ortiz R, J.M.; Vega C, H.R.

    2006-01-01

    An Artificial Neural Network has been designed, trained and tested to unfold neutron spectra and simultaneously to calculate equivalent doses. A set of 187 neutron spectra compiled by the International Atomic Energy Agency and 13 equivalent doses were used in the artificial neural network designed, trained and tested. In order to design the neural network was used the robust design of artificial neural networks methodology, which assures that the quality of the neural networks takes into account from the design stage. Unless previous works, here, for first time a group of neural networks were designed and trained to unfold 187 neutron spectra and at the same time to calculate 13 equivalent doses, starting from the count rates coming from the Bonner spheres system by using a systematic and experimental strategy. (Author)

  18. Artificial photosynthesis combines biology with technology for sustainable energy transformation

    Science.gov (United States)

    Moore, Thomas A.; Moore, Ana L.; Gust, Devens

    2013-03-01

    Photosynthesis supports the biosphere. Currently, human activity appropriates about one fourth of terrestrial photosynthetic net primary production (NPP) to support our GDP and nutrition. The cost to Earth systems of "our cut" of NPP is thought to be rapidly driving several Earth systems outside of bounds that were established on the geological time scale. Even with a fundamental realignment of human priorities, changing the unsustainable trajectory of the anthropocene will require reengineering photosynthesis to more efficiently meet human needs. Artificial photosynthetic systems are envisioned that can both supply renewable fuels and serve as platforms for exploring redesign strategies for photosynthesis. These strategies can be used in the nascent field of synthetic biology to make vast, much needed improvements in the biomass production efficiency of photosynthesis.

  19. Artificial Immune System Approach for Airborne Vehicle Maneuvering

    Science.gov (United States)

    Kaneshige, John T. (Inventor); Krishnakumar, Kalmanje S. (Inventor)

    2014-01-01

    A method and system for control of a first aircraft relative to a second aircraft. A desired location and desired orientation are estimated for the first aircraft, relative to the second aircraft, at a subsequent time, t=t2, subsequent to the present time, t=t1, where the second aircraft continues its present velocity during a subsequent time interval, t1.ltoreq.t.ltoreq.t2, or takes evasive action. Action command sequences are examined, and an optimal sequence is chosen to bring the first aircraft to the desired location and desired orientation relative to the second aircraft at time t=t2. The method applies to control of combat aircraft and/or of aircraft in a congested airspace.

  20. Vehicle Signal Analysis Using Artificial Neural Networks for a Bridge Weigh-in-Motion System

    Directory of Open Access Journals (Sweden)

    Min-Seok Park

    2009-10-01

    Full Text Available This paper describes the procedures for development of signal analysis algorithms using artificial neural networks for Bridge Weigh-in-Motion (B-WIM systems. Through the analysis procedure, the extraction of information concerning heavy traffic vehicles such as weight, speed, and number of axles from the time domain strain data of the B-WIM system was attempted. As one of the several possible pattern recognition techniques, an Artificial Neural Network (ANN was employed since it could effectively include dynamic effects and bridge-vehicle interactions. A number of vehicle traveling experiments with sufficient load cases were executed on two different types of bridges, a simply supported pre-stressed concrete girder bridge and a cable-stayed bridge. Different types of WIM systems such as high-speed WIM or low-speed WIM were also utilized during the experiments for cross-checking and to validate the performance of the developed algorithms.

  1. Vehicle Signal Analysis Using Artificial Neural Networks for a Bridge Weigh-in-Motion System.

    Science.gov (United States)

    Kim, Sungkon; Lee, Jungwhee; Park, Min-Seok; Jo, Byung-Wan

    2009-01-01

    This paper describes the procedures for development of signal analysis algorithms using artificial neural networks for Bridge Weigh-in-Motion (B-WIM) systems. Through the analysis procedure, the extraction of information concerning heavy traffic vehicles such as weight, speed, and number of axles from the time domain strain data of the B-WIM system was attempted. As one of the several possible pattern recognition techniques, an Artificial Neural Network (ANN) was employed since it could effectively include dynamic effects and bridge-vehicle interactions. A number of vehicle traveling experiments with sufficient load cases were executed on two different types of bridges, a simply supported pre-stressed concrete girder bridge and a cable-stayed bridge. Different types of WIM systems such as high-speed WIM or low-speed WIM were also utilized during the experiments for cross-checking and to validate the performance of the developed algorithms.

  2. Design of a portable artificial heart drive system based on efficiency analysis.

    Science.gov (United States)

    Kitamura, T

    1986-11-01

    This paper discusses a computer simulation of a pneumatic portable piston-type artificial heart drive system with a linear d-c-motor. The purpose of the design is to obtain an artificial heart drive system with high efficiency and small dimensions to enhance portability. The design employs two factors contributing the total efficiency of the drive system. First, the dimensions of the pneumatic actuator were optimized under a cost function of the total efficiency. Second, the motor performance was studied in terms of efficiency. More than 50 percent of the input energy of the actuator with practical loads is consumed in the armature circuit in all linear d-c-motors with brushes. An optimal design is: the piston cross-sectional area of 10.5 cm2 cylinder longitudinal length of 10 cm. The total efficiency could be up to 25 percent by improving the gasket to reduce the frictional force.

  3. Creating a two-layered augmented artificial immune system for application to computer network intrusion detection

    Science.gov (United States)

    Judge, Matthew G.; Lamont, Gary B.

    2009-05-01

    Computer network security has become a very serious concern of commercial, industrial, and military organizations due to the increasing number of network threats such as outsider intrusions and insider covert activities. An important security element of course is network intrusion detection which is a difficult real world problem that has been addressed through many different solution attempts. Using an artificial immune system has been shown to be one of the most promising results. By enhancing jREMISA, a multi-objective evolutionary algorithm inspired artificial immune system, with a secondary defense layer; we produce improved accuracy of intrusion classification and a flexibility in responsiveness. This responsiveness can be leveraged to provide a much more powerful and accurate system, through the use of increased processing time and dedicated hardware which has the flexibility of being located out of band.

  4. Counting viruses and bacteria in photosynthetic microbial mats

    NARCIS (Netherlands)

    Carreira, C; Staal, M.; Middelboe, M.; Brussaard, C.P.D.

    2015-01-01

    Viral abundances in benthic environments are the highest found in aquatic systems. Photosynthetic microbial mats represent benthic environments with high microbial activity and possibly high viral densities, yet viral abundances have not been examined in such systems. Existing extraction procedures

  5. Artificial frame filling using adaptive neural fuzzy inference system for particle image velocimetry dataset

    Science.gov (United States)

    Akdemir, Bayram; Doǧan, Sercan; Aksoy, Muharrem H.; Canli, Eyüp; Özgören, Muammer

    2015-03-01

    Liquid behaviors are very important for many areas especially for Mechanical Engineering. Fast camera is a way to observe and search the liquid behaviors. Camera traces the dust or colored markers travelling in the liquid and takes many pictures in a second as possible as. Every image has large data structure due to resolution. For fast liquid velocity, there is not easy to evaluate or make a fluent frame after the taken images. Artificial intelligence has much popularity in science to solve the nonlinear problems. Adaptive neural fuzzy inference system is a common artificial intelligence in literature. Any particle velocity in a liquid has two dimension speed and its derivatives. Adaptive Neural Fuzzy Inference System has been used to create an artificial frame between previous and post frames as offline. Adaptive neural fuzzy inference system uses velocities and vorticities to create a crossing point vector between previous and post points. In this study, Adaptive Neural Fuzzy Inference System has been used to fill virtual frames among the real frames in order to improve image continuity. So this evaluation makes the images much understandable at chaotic or vorticity points. After executed adaptive neural fuzzy inference system, the image dataset increase two times and has a sequence as virtual and real, respectively. The obtained success is evaluated using R2 testing and mean squared error. R2 testing has a statistical importance about similarity and 0.82, 0.81, 0.85 and 0.8 were obtained for velocities and derivatives, respectively.

  6. A status report on artificial lift systems and challenges in North Dakota horizontal completions

    Energy Technology Data Exchange (ETDEWEB)

    Fangmeier, K. [Amerada Hess Corp., ND (United States)

    2005-07-01

    Partially pressure depleted reservoirs and unfavorable horizontal flow geometries can impact artificial lift designs and diagnostics. In addition, terrain slugging, drilling fines, high gas volume fractions, H{sub 2}S gas and high bottom hole temperatures also pose challenges. This paper provides an overview of various systems utilized by Amerada Hess, a company which examines methods of reducing gas lift gas volumes to achieve maximum flow. A description of naturally fractured reservoirs and limited natural fractures was provided. A comparison was presented between the original conditions at Beaver Lodge Madison and existing conditions with horizontal development. Various artificial lift challenges were examined. It was suggested that high volume lift utilizing gas lift was the preferred artificial lift system for high volume wells. It was noted that downhole sensors can be used as an indicator of potential run life. However, reliability is limited by downhole operating temperatures and electrical ground faults. A comparison of friendly and unfriendly flow systems was presented, as well as a gas lift pressure chart. A summary of average gas volume systems was provided as well as an example of a response to increase drawdown. Examples of downhole Electric Submersible Pump (ESP) sensors were provided, as well as possible flowing pressure profiles in horizontal completion because of the constraints of lift capacity. It was concluded that a single point injection and proven gas lift system is the next step in high volume lift strategy. 2 tabs, 16 figs.

  7. Combination of artificial intelligence and procedural language programs in a computer application system supporting nuclear reactor operations

    International Nuclear Information System (INIS)

    Town, G.G.; Stratton, R.C.

    1985-01-01

    A computer application system is described which provides nuclear reactor power plant operators with an improved decision support system. This system combines traditional computer applications such as graphics display with artificial intelligence methodologies such as reasoning and diagnosis so as to improve plant operability. This paper discusses the issues, and a solution, involved with the system integration of applications developed using traditional and artificial intelligence languages

  8. Photosynthetic Pigments in Diatoms.

    Science.gov (United States)

    Kuczynska, Paulina; Jemiola-Rzeminska, Malgorzata; Strzalka, Kazimierz

    2015-09-16

    Photosynthetic pigments are bioactive compounds of great importance for the food, cosmetic, and pharmaceutical industries. They are not only responsible for capturing solar energy to carry out photosynthesis, but also play a role in photoprotective processes and display antioxidant activity, all of which contribute to effective biomass and oxygen production. Diatoms are organisms of a distinct pigment composition, substantially different from that present in plants. Apart from light-harvesting pigments such as chlorophyll a, chlorophyll c, and fucoxanthin, there is a group of photoprotective carotenoids which includes β-carotene and the xanthophylls, diatoxanthin, diadinoxanthin, violaxanthin, antheraxanthin, and zeaxanthin, which are engaged in the xanthophyll cycle. Additionally, some intermediate products of biosynthetic pathways have been identified in diatoms as well as unusual pigments, e.g., marennine. Marine algae have become widely recognized as a source of unique bioactive compounds for potential industrial, pharmaceutical, and medical applications. In this review, we summarize current knowledge on diatom photosynthetic pigments complemented by some new insights regarding their physico-chemical properties, biological role, and biosynthetic pathways, as well as the regulation of pigment level in the cell, methods of purification, and significance in industries.

  9. Photosynthetic Pigments in Diatoms

    Directory of Open Access Journals (Sweden)

    Paulina Kuczynska

    2015-09-01

    Full Text Available Photosynthetic pigments are bioactive compounds of great importance for the food, cosmetic, and pharmaceutical industries. They are not only responsible for capturing solar energy to carry out photosynthesis, but also play a role in photoprotective processes and display antioxidant activity, all of which contribute to effective biomass and oxygen production. Diatoms are organisms of a distinct pigment composition, substantially different from that present in plants. Apart from light-harvesting pigments such as chlorophyll a, chlorophyll c, and fucoxanthin, there is a group of photoprotective carotenoids which includes β-carotene and the xanthophylls, diatoxanthin, diadinoxanthin, violaxanthin, antheraxanthin, and zeaxanthin, which are engaged in the xanthophyll cycle. Additionally, some intermediate products of biosynthetic pathways have been identified in diatoms as well as unusual pigments, e.g., marennine. Marine algae have become widely recognized as a source of unique bioactive compounds for potential industrial, pharmaceutical, and medical applications. In this review, we summarize current knowledge on diatom photosynthetic pigments complemented by some new insights regarding their physico-chemical properties, biological role, and biosynthetic pathways, as well as the regulation of pigment level in the cell, methods of purification, and significance in industries.

  10. [Energy and memory efficient calculation of the accommodation demand in the artificial accommodation system].

    Science.gov (United States)

    Nagel, J A; Beck, C; Harms, H; Stiller, P; Guth, H; Stachs, O; Bretthauer, G

    2010-12-01

    Presbyopia and cataract are gaining more and more importance in the ageing society. Both age-related complaints are accompanied with a loss of the eye's ability to accommodate. A new approach to restore accommodation is the Artificial Accommodation System, an autonomous micro system, which will be implanted into the capsular bag instead of a rigid intraocular lens. The Artificial Accommodation System will, depending on the actual demand for accommodation, autonomously adapt the refractive power of its integrated optical element. One possibility to measure the demand for accommodation non-intrusively is to analyse eye movements. We present an efficient algorithm, based on the CORDIC technique, to calculate the demand for accommodation from magnetic field sensor data. It can be shown that specialised algorithms significantly shorten calculation time without violating precision requirements. Additionally, a communication strategy for the wireless exchange of sensor data between the implants of the left and right eye is introduced. The strategy allows for a one-sided calculation of the demand for accommodation, resulting in an overall reduction of calculation time by 50 %. The presented methods enable autonomous microsystems, such as the Artificial Accommodation System, to save significant amounts of energy, leading to extended autonomous run-times. © Georg Thieme Verlag KG Stuttgart · New York.

  11. 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.)

  12. 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.)

  13. Excitons in intact cells of photosynthetic bacteria.

    Science.gov (United States)

    Freiberg, Arvi; Pajusalu, Mihkel; Rätsep, Margus

    2013-09-26

    Live cells and regular crystals seem fundamentally incompatible. Still, effects characteristic to ideal crystals, such as coherent sharing of excitation, have been recently used in many studies to explain the behavior of several photosynthetic complexes, especially the inner workings of the light-harvesting apparatus of the oldest known photosynthetic organisms, the purple bacteria. To this date, there has been no concrete evidence that the same effects are instrumental in real living cells, leaving a possibility that this is an artifact of unnatural study conditions, not a real effect relevant to the biological operation of bacteria. Hereby, we demonstrate survival of collective coherent excitations (excitons) in intact cells of photosynthetic purple bacteria. This is done by using excitation anisotropy spectroscopy for tracking the temperature-dependent evolution of exciton bands in light-harvesting systems of increasing structural complexity. The temperature was gradually raised from 4.5 K to ambient temperature, and the complexity of the systems ranged from detergent-isolated complexes to complete bacterial cells. The results provide conclusive evidence that excitons are indeed one of the key elements contributing to the energetic and dynamic properties of photosynthetic organisms.

  14. Predicting IVF Outcome: A Proposed Web-based System Using Artificial Intelligence.

    Science.gov (United States)

    Siristatidis, Charalampos; Vogiatzi, Paraskevi; Pouliakis, Abraham; Trivella, Marialenna; Papantoniou, Nikolaos; Bettocchi, Stefano

    2016-01-01

    To propose a functional in vitro fertilization (IVF) prediction model to assist clinicians in tailoring personalized treatment of subfertile couples and improve assisted reproduction outcome. Construction and evaluation of an enhanced web-based system with a novel Artificial Neural Network (ANN) architecture and conformed input and output parameters according to the clinical and bibliographical standards, driven by a complete data set and "trained" by a network expert in an IVF setting. The system is capable to act as a routine information technology platform for the IVF unit and is capable of recalling and evaluating a vast amount of information in a rapid and automated manner to provide an objective indication on the outcome of an artificial reproductive cycle. ANNs are an exceptional candidate in providing the fertility specialist with numerical estimates to promote personalization of healthcare and adaptation of the course of treatment according to the indications. Copyright © 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

  15. Artificial intelligence tools decision support systems in condition monitoring and diagnosis

    CERN Document Server

    Galar Pascual, Diego

    2015-01-01

    Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box approaches to fault diagnosis in condition monitoring (CM). This indispensable resource: Addresses nearest-neighbor-based, clustering-based, statistical, and information theory-based techniques Considers the merits of each technique as well as the issues associated with real-life application Covers classification methods, from neural networks to Bayesian and support vector machines Proposes fuzzy logic to explain the uncertainties associated with diagnostic processes Provides data sets, sample signals, and MATLAB® code for algorithm testing Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis delivers a thorough evaluation of the latest AI tools for CM, describing the most common fault diagnosis techniques used and the data acquired when these techniques are applied.

  16. Effect of space mutation of photosynthetic characteristics of soybean varieties

    International Nuclear Information System (INIS)

    Liu Xinlei; Ma Yansong; Luan Xiaoyan; Man Weiqun; Xu Dechun; Meng Lifen; Fu Lixin; Zhao Xiao'nan; Liu Qi

    2012-01-01

    In order to elucidate the response of the photosynthetic traits of soybean to space mutation, three soybean varieties (lines) of Heinong 48, Heinong 44 and Ha 2291-Y were carried by artificial satellite in 2006 and the net photo synthetic rate (Pn), stomatal conductance (Cond), intercellular CO 2 concentration (Ci) and stomatal resistance (Rs) from SP 1 to SP 4 generation were determined. The results showed that space mutation affected photosynthesis traits of soy bean. The photosynthetic rate of soybean varieties by space mutation occurred different levels of genetic variation and the positive mutation rate were higher. Coefficient of variation among generations were SP 2 >SP 3 >SP 4 >CK. Results suggest that space mutation can effectively create soybean materials with higher photosynthetic rate. (authors)

  17. The topologic information processing by the artificial intellingence systems for the logic tasks' solving

    Directory of Open Access Journals (Sweden)

    Demyokhin V. V.

    2008-04-01

    Full Text Available The new method of parallel logic gates realization is described. The implementation of the parallel logic for a binary patterns considered on the basis of the topological information processing, used also in recognizing of visual images of single-layer systems of artificial intelligence. The estimates of the main parameters of TIP devices indicate that their performance can reach 1016 operations / sec and the amount of the structural elements is much less than in the known opto-logic devices.

  18. An Artificial Intelligence System to Predict Quality of Service in Banking Organizations

    OpenAIRE

    Castelli, Mauro; Manzoni, Luca; Popovi?, Ale?

    2016-01-01

    Quality of service, that is, the waiting time that customers must endure in order to receive a service, is a critical performance aspect in private and public service organizations. Providing good service quality is particularly important in highly competitive sectors where similar services exist. In this paper, focusing on banking sector, we propose an artificial intelligence system for building a model for the prediction of service quality. While the traditional approach used for building a...

  19. Chemical analysis of multicomponent aqueous solutions using a system of nonselective sensor and artificial neural networks

    International Nuclear Information System (INIS)

    Vlasov, Yu.G.; Legin, A.V.; Rudnitskaya, A.M.; Amiko, A.D.; Natale, K.D.

    1997-01-01

    With the aim of creating a multisensor system for determining heavy-metal cations (Cu 2+ , Pb 2+ , Cd 2+ , and Zn 2+ ) and inorganic anions (Cl - , F - , and SO 4 2- ), measurements in mixed solutions were carried out with the use of an array of sensors based on chalcogenide glass electrodes, and the possibility of using various methods of mathematical processing of the resulting intricate signals was studied. Three methods of data processing were used: multilinear regression, partial least squares, and artificial neural networks. It was found that the multisensor system proposed were suitable for determining all of the analytes with an accuracy of 1-10%. Because the responses of sensors in solutions of complex composition deviated from linearity, the lowest determination errors were obtained with the use of an artificial neural network. As to the method of data securing (nonselective response of a sensor array) and processing (artificial neural network), the multisensor system developed may be considered a prototype of a device of the electronic tongue type

  20. Primary photosynthetic processes: from supercomplex to leaf

    NARCIS (Netherlands)

    Broess, K.

    2009-01-01

    This thesis describes fluorescence spectroscopy experiments on photosynthetic complexes that cover the primary photosynthetic processes, from the absorption of light by photosynthetic pigments to a charge separation (CS) in the reaction center (RC). Fluorescence spectroscopy is a useful tool in

  1. Cold priming drives the sub-cellular antioxidant systems to protect photosynthetic electron transport against subsequent low temperature stress in winter wheat

    DEFF Research Database (Denmark)

    Li, Xiangnan; Cai, Jian; Liu, Fulai

    2014-01-01

    Low temperature seriously depresses the growth of wheat through inhibition of photosynthesis, while earlier cold priming may enhance the tolerance of plants to subsequent low temperature stress. Here, winter wheat plants were firstly cold primed (5.2°C lower temperature than the ambient temperatu......-cellular antioxidant systems, depressing the oxidative burst in photosynthetic apparatus, hereby enhanced the tolerance to subsequent low temperature stress in winter wheat plants.......Low temperature seriously depresses the growth of wheat through inhibition of photosynthesis, while earlier cold priming may enhance the tolerance of plants to subsequent low temperature stress. Here, winter wheat plants were firstly cold primed (5.2°C lower temperature than the ambient temperature......, viz., 10.0°C) at the Zadoks growth stage 28 (i.e.re-greening stage, starting on 20th of March) for 7d, and after 14d of recovery the plants were subsequently subjected to a 5d low temperature stress (8.4°C lower than the ambient temperature, viz., 14.1°C) at the Zadoks growth stage 31 (i...

  2. Application of algorithms and artificial-intelligence approach for locating multiple harmonics in distribution systems

    Energy Technology Data Exchange (ETDEWEB)

    Hong, Y.-Y.; Chen, Y.-C. [Chung Yuan University (China). Dept. of Electrical Engineering

    1999-05-01

    A new method is proposed for locating multiple harmonic sources in distribution systems. The proposed method first determines the proper locations for metering measurement using fuzzy clustering. Next, an artificial neural network based on the back-propagation approach is used to identify the most likely location for multiple harmonic sources. A set of systematic algorithmic steps is developed until all harmonic locations are identified. The simulation results for an 18-busbar system show that the proposed method is very efficient in locating the multiple harmonics in a distribution system. (author)

  3. SHARP: A multi-mission artificial intelligence system for spacecraft telemetry monitoring and diagnosis

    Science.gov (United States)

    Lawson, Denise L.; James, Mark L.

    1989-01-01

    The Spacecraft Health Automated Reasoning Prototype (SHARP) is a system designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. Telecommunications link analysis of the Voyager 2 spacecraft is the initial focus for the SHARP system demonstration which will occur during Voyager's encounter with the planet Neptune in August, 1989, in parallel with real time Voyager operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. A brief introduction is given to the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory. The current method of operation for monitoring the Voyager Telecommunications subsystem is described, and the difficulties associated with the existing technology are highlighted. The approach taken in the SHARP system to overcome the current limitations is also described, as well as both the conventional and artificial intelligence solutions developed in SHARP.

  4. An Investigation on the Role of Spike Latency in an Artificial Olfactory System

    Directory of Open Access Journals (Sweden)

    Corrado eDi Natale

    2011-12-01

    Full Text Available Experimental studies have shown that the reactions to external stimuli may appear only few hundreds of milliseconds after the physical interaction of the stimulus with the proper receptor. This behavior suggests that neurons transmit the largest meaningful part of their signal in the first spikes, and than that the spike latency is a good descriptor of the information content in biological neural networks. In this paper this property has been investigated in an artificial sensorial system where a single layer of spiking neurons is trained with the data generated by an artificial olfactory platform based on a large array of chemical sensors. The capability to discriminate between distinct chemicals and mixtures of them was studied with spiking neural networks endowed with and without lateral inhibitions and considering as output feature of the network both the spikes latency and the average firing rate. Results show that the average firing rate of the output spikes sequences shows the best separation among the experienced vapors, however the latency code is able in a shorter time to correctly discriminate all the tested volatile compounds. This behavior is qualitatively similar to those recently found in natural olfaction, and noteworthy it provides practical suggestions to tail the measurement conditions of artificial olfactory systems defining for each specific case a proper measurement time.

  5. Estimating the behavior of RC beams strengthened with NSM system using artificial neural networks

    Directory of Open Access Journals (Sweden)

    Seyed Rohollah Hosseini Vaez

    2017-12-01

    Full Text Available In the last decade, conventional materials such as steel and concrete are being replaced by fiber reinforced polymer (FRP materials for the strengthening of concrete structures. Among the strengthening techniques based on Fiber Reinforced Polymer composites, the use of near-surface mounted (NSM FRP rods is emerging as a promising technology for increasing flexural and shear strength of deficient concrete, masonry and timber members. An artificial neural network is an information processing tool that is inspired by the way biological nervous systems (such as the brain process the information. The key element of this tool is the novel structure of the information processing system. In engineering applications, a neural network can be a vector mapper which maps an input vector to an output one. In the present study, a new approach is developed to predict the behavior of strengthened concrete beam using a large number of experimental data by applying artificial neural networks. Having parameters used as input nodes in ANN modeling such as elastic modulus of the FRP reinforcement, the ratio of the steel longitudinal reinforcement, dimensions of the beam section, the ratio of the NSM-FRP reinforcement and characteristics of concrete, the output node was the flexural strength of beams. The idealized neural network was employed to generate empirical charts and equations to be used in design. The aim of this study is to investigate the behavior of strengthened RC beam using artificial neural networks.

  6. Electromagnetic effects on the biological tissue surrounding a transcutaneous transformer for an artificial anal sphincter system*

    Science.gov (United States)

    Zan, Peng; Yang, Bang-hua; Shao, Yong; Yan, Guo-zheng; Liu, Hua

    2010-01-01

    This paper reports on the electromagnetic effects on the biological tissue surrounding a transcutaneous transformer for an artificial anal sphincter. The coupling coils and human tissues, including the skin, fat, muscle, liver, and blood, were considered. Specific absorption rate (SAR) and current density were analyzed by a finite-length solenoid model. First, SAR and current density as a function of frequency (10–107 Hz) for an emission current of 1.5 A were calculated under different tissue thickness. Then relations between SAR, current density, and five types of tissues under each frequency were deduced. As a result, both the SAR and current density were below the basic restrictions of the International Commission on Non-Ionizing Radiation Protection (ICNIRP). The results show that the analysis of these data is very important for developing the artificial anal sphincter system. PMID:21121071

  7. Pressure distribution-based texture sensing by using a simple artificial mastication system.

    Science.gov (United States)

    Yamamoto, Takeshi; Higashimori, Mitsuru; Nakauma, Makoto; Nakao, Satomi; Ikegami, Akira; Ishihara, Sayaka

    2014-01-01

    This paper proposes a novel texture sensing method for nursing-care gel by using an artificial mastication system, in which not only mechanical characteristics but also geometrical ones are objectively and quantitatively evaluated. When human masticates gel food, she or he perceives the changes of the shape and contact force simultaneously. Based on the impressions, they evaluate the texture. For reproducing such a procedure, the pressure distribution of gel is measured in the simple artificial mastication, and the information associated to both the geometrical and mechanical characteristics is simultaneously acquired. The relationship between the value of sensory evaluation (i.e. impression human perceives), and the pressure distribution data is numerically modeled by applying the image texture analysis. Experimental results show that the proposed method succeeds in estimating the values of sensory evaluation of nine kinds of gel with the coefficient of determination greater than 0.93.

  8. Chaotic Artificial Bee Colony Algorithm for System Identification of a Small-Scale Unmanned Helicopter

    Directory of Open Access Journals (Sweden)

    Li Ding

    2015-01-01

    Full Text Available The purpose of this paper is devoted to developing a chaotic artificial bee colony algorithm (CABC for the system identification of a small-scale unmanned helicopter state-space model in hover condition. In order to avoid the premature of traditional artificial bee colony algorithm (ABC, which is stuck in local optimum and can not reach the global optimum, a novel chaotic operator with the characteristics of ergodicity and irregularity was introduced to enhance its performance. With input-output data collected from actual flight experiments, the identification results showed the superiority of CABC over the ABC and the genetic algorithm (GA. Simulations are presented to demonstrate the effectiveness of our proposed algorithm and the accuracy of the identified helicopter model.

  9. An Artificial Immune System with Feedback Mechanisms for Effective Handling of Population Size

    Science.gov (United States)

    Gao, Shangce; Wang, Rong-Long; Ishii, Masahiro; Tang, Zheng

    This paper represents a feedback artificial immune system (FAIS). Inspired by the feedback mechanisms in the biological immune system, the proposed algorithm effectively manipulates the population size by increasing and decreasing B cells according to the diversity of the current population. Two kinds of assessments are used to evaluate the diversity aiming to capture the characteristics of the problem on hand. Furthermore, the processing of adding and declining the number of population is designed. The validity of the proposed algorithm is tested for several traveling salesman benchmark problems. Simulation results demonstrate the efficiency of the proposed algorithm when compared with the traditional genetic algorithm and an improved clonal selection algorithm.

  10. 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...

  11. Functional integration of automated system databases by means of artificial intelligence

    Science.gov (United States)

    Dubovoi, Volodymyr M.; Nikitenko, Olena D.; Kalimoldayev, Maksat; Kotyra, Andrzej; Gromaszek, Konrad; Iskakova, Aigul

    2017-08-01

    The paper presents approaches for functional integration of automated system databases by means of artificial intelligence. The peculiarities of turning to account the database in the systems with the usage of a fuzzy implementation of functions were analyzed. Requirements for the normalization of such databases were defined. The question of data equivalence in conditions of uncertainty and collisions in the presence of the databases functional integration is considered and the model to reveal their possible occurrence is devised. The paper also presents evaluation method of standardization of integrated database normalization.

  12. Diagnosis of Diabetes Diseases Using an Artificial Immune Recognition System2 (AIRS2) with Fuzzy K-nearest Neighbor

    OpenAIRE

    CHIKH, Mohamed Amine; SAIDI, Meryem; SETTOUTI, Nesma

    2012-01-01

    The use of expert systems and artificial intelligence techniques in disease diagnosis has been increasing gradually. Artificial Immune Recognition System (AIRS) is one of the methods used in medical classification problems. AIRS2 is a more efficient version of the AIRS algorithm. In this paper, we used a modified AIRS2 called MAIRS2 where we replace the K- nearest neighbors algorithm with the fuzzy K-nearest neighbors to improve the diagnostic accuracy of diabetes diseases. The diabetes disea...

  13. Identification of mathematical model of human breathing in systemArtificial lungs – self-contained breathing apparatus”

    Science.gov (United States)

    Onevsky, P. M.; Onevsky, M. P.; Pogonin, V. A.

    2018-03-01

    The structure and mathematical models of the main subsystems of the control system of the “Artificial Lungs” are presented. This structure implements the process of imitation of human external respiration in the systemArtificial lungs - self-contained breathing apparatus”. A presented algorithm for parametric identification of the model is based on spectral operators, which allows using it in real time.

  14. Artificial neural network-aided image analysis system for cell counting.

    Science.gov (United States)

    Sjöström, P J; Frydel, B R; Wahlberg, L U

    1999-05-01

    In histological preparations containing debris and synthetic materials, it is difficult to automate cell counting using standard image analysis tools, i.e., systems that rely on boundary contours, histogram thresholding, etc. In an attempt to mimic manual cell recognition, an automated cell counter was constructed using a combination of artificial intelligence and standard image analysis methods. Artificial neural network (ANN) methods were applied on digitized microscopy fields without pre-ANN feature extraction. A three-layer feed-forward network with extensive weight sharing in the first hidden layer was employed and trained on 1,830 examples using the error back-propagation algorithm on a Power Macintosh 7300/180 desktop computer. The optimal number of hidden neurons was determined and the trained system was validated by comparison with blinded human counts. System performance at 50x and lO0x magnification was evaluated. The correlation index at 100x magnification neared person-to-person variability, while 50x magnification was not useful. The system was approximately six times faster than an experienced human. ANN-based automated cell counting in noisy histological preparations is feasible. Consistent histology and computer power are crucial for system performance. The system provides several benefits, such as speed of analysis and consistency, and frees up personnel for other tasks.

  15. Prodiag--a hybrid artificial intelligence based reactor diagnostic system for process faults

    International Nuclear Information System (INIS)

    Reifman, J.; Wei, T.Y.C.; Vitela, J.E.; Applequist, C. A.; Chasensky, T.M.

    1996-01-01

    Commonwealth Research Corporation (CRC) and Argonne National Laboratory (ANL) are collaborating on a DOE-sponsored Cooperative Research and Development Agreement (CRADA), project to perform feasibility studies on a novel approach to Artificial Intelligence (Al) based diagnostics for component faults in nuclear power plants. Investigations are being performed in the construction of a first-principles physics-based plant level process diagnostic expert system (ES) and the identification of component-level fault patterns through operating component characteristics using artificial neural networks (ANNs). The purpose of the proof-of-concept project is to develop a computer-based system using this Al approach to assist process plant operators during off-normal plant conditions. The proposed computer-based system will use thermal hydraulic (T-H) signals complemented by other non-T-H signals available in the data stream to provide the process operator with the component which most likely caused the observed process disturbance.To demonstrate the scale-up feasibility of the proposed diagnostic system it is being developed for use with the Chemical Volume Control System (CVCS) of a nuclear power plant. A full-scope operator training simulator representing the Commonwealth Edison Braidwood nuclear power plant is being used both as the source of development data and as the means to evaluate the advantages of the proposed diagnostic system. This is an ongoing multi-year project and this paper presents the results to date of the CRADA phase

  16. On the photosynthetic and devlopmental responses of leaves to the spectral composition of light

    OpenAIRE

    Hogewoning, S.W.

    2010-01-01

    Key words: action spectrum, artificial solar spectrum, blue light, Cucumis sativus, gas-exchange, light-emitting diodes (LEDs), light interception, light quality, non-photosynthetic pigments, photo-synthetic capacity, photomorphogenesis, photosystem excitation balance, quantum yield, red light. A wide range of plant properties respond to the spectral composition of irradiance, such as photosynthesis, photomorphogenesis, phototropism and photonastic movements. These responses affect plant pr...

  17. Distribution of natural and artificial radionuclides in chernozem soil/crop system from stationary experiments.

    Science.gov (United States)

    Sarap, Nataša B; Rajačić, Milica M; Đalović, Ivica G; Šeremešić, Srđan I; Đorđević, Aleksandar R; Janković, Marija M; Daković, Marko Z

    2016-09-01

    The present paper focuses on the determination of radiological characteristics of cultivated chernozem soil and crops from long-term field experiments, taking into account the importance of distribution and transfer of radionuclides in the soil-plant system, especially in agricultural cropland. The investigation was performed on the experimental fields where maize, winter wheat, and rapeseed were cultivated. Analysis of radioactivity included determination of the gross alpha and beta activity as a screening method, as well as the activities of the following radionuclides: natural ((210)Pb, (235)U, (238)U, (226)Ra, (232)Th, (40)K, (7)Be) and artificial ((90)Sr and (137)Cs). The activities of natural and artificial ((137)Cs) radionuclides were determined by gamma spectrometry, while the artificial radionuclide (90)Sr was determined by a radiochemical analytical method. Based on the obtained results for the specific activity of (40)K, (137)Cs, and (90)Sr, accumulation factors for these radionuclides were calculated in order to estimate transfer of radionuclides from soil to crops. The results of performed analyses showed that there is no increase of radioactivity that could endanger the food production through the grown crops.

  18. A neural network based artificial vision system for licence plate recognition.

    Science.gov (United States)

    Draghici, S

    1997-02-01

    This paper presents a neural network based artificial vision system able to analyze the image of a car given by a camera, locate the registration plate and recognize the registration number of the car. The paper describes in detail various practical problems encountered in implementing this particular application and the solutions used to solve them. The main features of the system presented are: controlled stability-plasticity behavior, controlled reliability threshold, both off-line and on-line learning, self assessment of the output reliability and high reliability based on high level multiple feedback. The system has been designed using a modular approach. Sub-modules can be upgraded and/or substituted independently, thus making the system potentially suitable in a large variety of vision applications. The OCR engine was designed as an interchangeable plug-in module. This allows the user to choose an OCR engine which is suited to the particular application and to upgrade it easily in the future. At present, there are several versions of this OCR engine. One of them is based on a fully connected feedforward artificial neural network with sigmoidal activation functions. This network can be trained with various training algorithms such as error backpropagation. An alternative OCR engine is based on the constraint based decomposition (CBD) training architecture. The system has showed the following performances (on average) on real-world data: successful plate location and segmentation about 99%, successful character recognition about 98% and successful recognition of complete registration plates about 80%.

  19. System overview of the fully implantable destination therapy--ReinHeart-total artificial heart.

    Science.gov (United States)

    Pelletier, Benedikt; Spiliopoulos, Sotirios; Finocchiaro, Thomas; Graef, Felix; Kuipers, Kristin; Laumen, Marco; Guersoy, Dilek; Steinseifer, Ulrich; Koerfer, Reiner; Tenderich, Gero

    2015-01-01

    Owing to the lack of suitable allografts, the demand for long-term mechanical circulatory support in patients with biventricular end-stage heart failure is rising. Currently available Total Artificial Heart (TAH) systems consist of pump units with only limited durability, percutaneous tubes and bulky external equipment that limit the quality of life. Therefore we are focusing on the development of a fully implantable, highly durable destination therapy total artificial heart. The ReinHeart-TAH system consists of a passively filling pump unit driven by a low-wear linear drive between two artificial ventricles, an implantable control unit and a compliance chamber. The TAH is powered by a transcutaneous energy transmission system. The flow distribution inside the ventricles was analysed by fluid structure interaction simulation and particle image velocimetry measurements. Along with durability tests, the hydrodynamic performance and flow balance capability were evaluated in a mock circulation loop. Animal trials are ongoing. Based on fluid structure interaction simulation and particle image velocimetry, blood stagnation areas have been significantly reduced. In the mock circulation loop the ReinHeart-TAH generated a cardiac output of 5 l/min at an operating frequency of 120 bpm and an aortic pressure of 120/80 mmHg. The highly effective preload sensitivity of the passively filling ventricles allowed the sensorless integration of the Frank Starling mechanism. The ReinHeart-TAH effectively replaced the native heart's function in animals for up to 2 days. In vitro and in vivo testing showed a safe and effective function of the ReinHeart-TAH system. This has the potential to become an alternative to transplantation. However, before a first-in-man implant, chronic animal trials still have to be completed. © The Author 2014. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

  20. Artificial intelligence

    International Nuclear Information System (INIS)

    Perret-Galix, D.

    1992-01-01

    A vivid example of the growing need for frontier physics experiments to make use of frontier technology is in the field of artificial intelligence and related themes. This was reflected in the second international workshop on 'Software Engineering, Artificial Intelligence and Expert Systems in High Energy and Nuclear Physics' which took place from 13-18 January at France Telecom's Agelonde site at La Londe des Maures, Provence. It was the second in a series, the first having been held at Lyon in 1990

  1. Artificial Intelligence.

    Science.gov (United States)

    Wash, Darrel Patrick

    1989-01-01

    Making a machine seem intelligent is not easy. As a consequence, demand has been rising for computer professionals skilled in artificial intelligence and is likely to continue to go up. These workers develop expert systems and solve the mysteries of machine vision, natural language processing, and neural networks. (Editor)

  2. Artificial Immune Systems as a Modern Tool for Solving Multi-Purpose Optimization Tasks in the Field of Logistics

    Directory of Open Access Journals (Sweden)

    Skitsko Volodymyr I.

    2017-03-01

    Full Text Available The article investigates various aspects of the functioning of artificial immune systems and their using to solve different tasks. The analysis of the studied literature showed that nowadays there exist combinations of artificial immune systems, in particular with genetic algorithms, the particle swarm optimization method, artificial neural networks, etc., to solve different tasks. However, the solving of economic tasks is paid little attention. The article presents the basic terminology of artificial immune systems; the steps of the clonal selection algorithm are described, as well as a brief description of the negative selection algorithm, the immune network algorithm and the dendritic algorithm is given; conceptual aspects of the use of an artificial immune system for solving multi-purpose optimization problems are formulated, and an example of solving a problem in the field of logistics is described. Artificial immune systems as a means of solving various weakly structured, multi-criteria and multi-purpose economic tasks, in particular in the sphere of logistics, are a promising tool that requires further research. Therefore, it is advisable in the future to focus on the use of various existing immune algorithms for solving various economic problems.

  3. Promise of a low power mobile CPU based embedded system in artificial leg control.

    Science.gov (United States)

    Hernandez, Robert; Zhang, Fan; Zhang, Xiaorong; Huang, He; Yang, Qing

    2012-01-01

    This paper presents the design and implementation of a low power embedded system using mobile processor technology (Intel Atom™ Z530 Processor) specifically tailored for a neural-machine interface (NMI) for artificial limbs. This embedded system effectively performs our previously developed NMI algorithm based on neuromuscular-mechanical fusion and phase-dependent pattern classification. The analysis shows that NMI embedded system can meet real-time constraints with high accuracies for recognizing the user's locomotion mode. Our implementation utilizes the mobile processor efficiently to allow a power consumption of 2.2 watts and low CPU utilization (less than 4.3%) while executing the complex NMI algorithm. Our experiments have shown that the highly optimized C program implementation on the embedded system has superb advantages over existing PC implementations on MATLAB. The study results suggest that mobile-CPU-based embedded system is promising for implementing advanced control for powered lower limb prostheses.

  4. Integration of artificial intelligence systems for nuclear power plants surveillance and diagnostics

    International Nuclear Information System (INIS)

    Chetry, Moon K.

    2012-01-01

    The objective of this program is to design, construct operate, test, and evaluate a prototype integrated monitoring and diagnostic system for a nuclear power plant. It is anticipated that this technology will have wide application to other complex systems (e.g., fossil power plants, chemical processing plants, and possibly air traffic control systems). Over the past decade, the University of Tennessee (UT) and others have carried out many projects utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems and genetic algorithms) to enhance the performance (safety, efficiency, reliability, and availability) of nuclear power plants. Investigations and studies have included a) instrumentation surveillance and calibration validation, b) inferential sensing to calibration of feed water venture flow during fouling, c) thermodynamic performance modeling with iterative improvement of plant heat rate, d) diagnosis of nuclear power plant transients

  5. Stellar Image Interpretation System using Artificial Neural Networks: Unipolar Function Case

    Directory of Open Access Journals (Sweden)

    F. I. Younis

    2001-01-01

    Full Text Available An artificial neural network based system for interpreting astronomical images has been developed. The system is based on feed-forward Artificial Neural Networks (ANNs with error back-propagation learning. Knowledge about images of stars, cosmic ray events and noise found in images is used to prepare two sets of input patterns to train and test our approach. The system has been developed and implemented to scan astronomical digital images in order to segregate stellar images from other entities. It has been coded in C language for users of personal computers. An astronomical image of a star cluster from other objects is undertaken as a test case. The obtained results are found to be in very good agreement with those derived from the DAOPHOTII package, which is widely used in the astronomical community. It is proved that our system is simpler, much faster and more reliable. Moreover, no prior knowledge, or initial data from the frame to be analysed is required.

  6. A Physical Heart Failure Simulation System Utilizing the Total Artificial Heart and Modified Donovan Mock Circulation.

    Science.gov (United States)

    Crosby, Jessica R; DeCook, Katrina J; Tran, Phat L; Betterton, Edward; Smith, Richard G; Larson, Douglas F; Khalpey, Zain I; Burkhoff, Daniel; Slepian, Marvin J

    2017-07-01

    With the growth and diversity of mechanical circulatory support (MCS) systems entering clinical use, a need exists for a robust mock circulation system capable of reliably emulating and reproducing physiologic as well as pathophysiologic states for use in MCS training and inter-device comparison. We report on the development of such a platform utilizing the SynCardia Total Artificial Heart and a modified Donovan Mock Circulation System, capable of being driven at normal and reduced output. With this platform, clinically relevant heart failure hemodynamics could be reliably reproduced as evidenced by elevated left atrial pressure (+112%), reduced aortic flow (-12.6%), blunted Starling-like behavior, and increased afterload sensitivity when compared with normal function. Similarly, pressure-volume relationships demonstrated enhanced sensitivity to afterload and decreased Starling-like behavior in the heart failure model. Lastly, the platform was configured to allow the easy addition of a left ventricular assist device (HeartMate II at 9600 RPM), which upon insertion resulted in improvement of hemodynamics. The present configuration has the potential to serve as a viable system for training and research, aimed at fostering safe and effective MCS device use. © 2016 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

  7. A Review of Hydrogen Production by Photosynthetic Organisms Using Whole-Cell and Cell-Free Systems.

    Science.gov (United States)

    Martin, Baker A; Frymier, Paul D

    2017-10-01

    Molecular hydrogen is a promising currency in the future energy economy due to the uncertain availability of finite fossil fuel resources and environmental effects from their combustion. It also has important uses in the production of fertilizers and platform chemicals as well as in upgrading conventional fuels. Conventional methods for producing molecular hydrogen from natural gas produce carbon dioxide and use a finite resource as feedstock. However, these issues can be overcome by using light energy from the Sun combined with microorganisms and their molecular machinery capable of photosynthesis. In the presence of light, the proteins involved in photosynthesis coupled with appropriate catalysts in higher plants, algae, and cyanobacteria can produce molecular hydrogen, and optimization via genetic modifications and biomolecular engineering further improves production rates. In this review, we will discuss techniques that have been utilized to improve rates of hydrogen production in biological systems based on the protein machinery of photosynthesis coupled with appropriate catalysts. We will also suggest areas for improvement and future directions for work in the field.

  8. Photosynthetic fuel for heterologous enzymes

    DEFF Research Database (Denmark)

    Mellor, Silas Busck; Vavitsas, Konstantinos; Nielsen, Agnieszka Janina Zygadlo

    2017-01-01

    of reducing power. Recent work on the metabolic engineering of photosynthetic organisms has shown that the electron carriers such as ferredoxin and flavodoxin can be used to couple heterologous enzymes to photosynthetic reducing power. Because these proteins have a plethora of interaction partners and rely...... on electrostatically steered complex formation, they form productive electron transfer complexes with non-native enzymes. A handful of examples demonstrate channeling of photosynthetic electrons to drive the activity of heterologous enzymes, and these focus mainly on hydrogenases and cytochrome P450s. However......, competition from native pathways and inefficient electron transfer rates present major obstacles, which limit the productivity of heterologous reactions coupled to photosynthesis. We discuss specific approaches to address these bottlenecks and ensure high productivity of such enzymes in a photosynthetic...

  9. Automated system for load flow prediction in power substations using artificial neural networks

    Directory of Open Access Journals (Sweden)

    Arlys Michel Lastre Aleaga

    2015-09-01

    Full Text Available The load flow is of great importance in assisting the process of decision making and planning of generation, distribution and transmission of electricity. Ignorance of the values in this indicator, as well as their inappropriate prediction, difficult decision making and efficiency of the electricity service, and can cause undesirable situations such as; the on demand, overheating of the components that make up a substation, and incorrect planning processes electricity generation and distribution. Given the need for prediction of flow of electric charge of the substations in Ecuador this research proposes the concept for the development of an automated prediction system employing the use of Artificial Neural Networks.

  10. International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems

    CERN Document Server

    Vijayakumar, K; Panigrahi, Bijaya; Das, Swagatam

    2017-01-01

    The volume is a collection of high-quality peer-reviewed research papers presented in the International Conference on Artificial Intelligence and Evolutionary Computation in Engineering Systems (ICAIECES 2016) held at SRM University, Chennai, Tamilnadu, India. This conference is an international forum for industry professionals and researchers to deliberate and state their research findings, discuss the latest advancements and explore the future directions in the emerging areas of engineering and technology. The book presents original work and novel ideas, information, techniques and applications in the field of communication, computing and power technologies.

  11. International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems

    CERN Document Server

    Bhaskar, M; Panigrahi, Bijaya; Das, Swagatam

    2016-01-01

    The book is a collection of high-quality peer-reviewed research papers presented in the first International Conference on International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems (ICAIECES -2015) held at Velammal Engineering College (VEC), Chennai, India during 22 – 23 April 2015. The book discusses wide variety of industrial, engineering and scientific applications of the emerging techniques. Researchers from academic and industry present their original work and exchange ideas, information, techniques and applications in the field of Communication, Computing and Power Technologies.

  12. Protection of the female reproductive system from natural and artificial insults

    Science.gov (United States)

    Tilly, Jonathan L.; Kolesnick, Richard N.

    2010-12-14

    Described are methods for protecting the female reproductive system against natural and artificial insults by administering to women a composition comprising an agent that antagonizes one or more acid sphingomyelinase (ASMase) gene products. Specifically, methods disclosed herein serve to protect women's germline from damage resulting from cancer therapy regimens including chemotherapy or radiotherapy. In one aspect, the method preserves, enhances, or revives ovarian function in women, by administering to women a composition containing sphingosine-1-phosphate, or an analog thereof. Also disclosed are methods to prevent or ameliorate menopausal syndromes and to improve in vitro fertilization techniques.

  13. A novel algorithm of artificial immune system for high-dimensional function numerical optimization

    Institute of Scientific and Technical Information of China (English)

    DU Haifeng; GONG Maoguo; JIAO Licheng; LIU Ruochen

    2005-01-01

    Based on the clonal selection theory and immune memory theory, a novel artificial immune system algorithm, immune memory clonal programming algorithm (IMCPA), is put forward. Using the theorem of Markov chain, it is proved that IMCPA is convergent. Compared with some other evolutionary programming algorithms (like Breeder genetic algorithm), IMCPA is shown to be an evolutionary strategy capable of solving complex machine learning tasks, like high-dimensional function optimization, which maintains the diversity of the population and avoids prematurity to some extent, and has a higher convergence speed.

  14. Porphyrin nanorods characterisation for an artificial light harvesting and energy transfer system

    CSIR Research Space (South Africa)

    Mongwaketsi, N

    2010-01-01

    Full Text Available s 1 0 h r s 1 3 h r s 1 5 h r s 1 8 h r s Porphyrin Nanorods Characterization for an Artificial Light Harvesting and Energy Transfer System Nametso Mongwaketsi1,2,3, Raymond Sparrow2, Bert Klumperman3, Malik Maaza1 1 NanoSciences Lab..., Materials Research Dept, iThemba LABS, PO Box 722, Somerset West, 7129, South Africa 2 CSIR Biosciences, PO Box 395, Pretoria, 0001, South Africa 3 Stellenbosch University, Department of Chemistry and Polymer Science, Private Bag X 1, Matieland, 7602...

  15. Artificial neural net system for interactive tissue classification with MR imaging and image segmentation

    International Nuclear Information System (INIS)

    Clarke, L.P.; Silbiger, M.; Naylor, C.; Brown, K.

    1990-01-01

    This paper reports on the development of interactive methods for MR tissue classification that permit mathematically rigorous methods for three-dimensional image segmentation and automatic organ/tumor contouring, as required for surgical and RTP planning. The authors investigate a number of image-intensity based tissue- classification methods that make no implicit assumptions on the MR parameters and hence are not limited by image data set. Similarly, we have trained artificial neural net (ANN) systems for both supervised and unsupervised tissue classification

  16. Artificial immune system and sheep flock algorithms for two-stage fixed-charge transportation problem

    DEFF Research Database (Denmark)

    Kannan, Devika; Govindan, Kannan; Soleimani, Hamed

    2014-01-01

    In this paper, we cope with a two-stage distribution planning problem of supply chain regarding fixed charges. The focus of the paper is on developing efficient solution methodologies of the selected NP-hard problem. Based on computational limitations, common exact and approximation solution...... approaches are unable to solve real-world instances of such NP-hard problems in a reasonable time. These approaches involve cumbersome computational steps in real-size cases. In order to solve the mixed integer linear programming model, we develop an artificial immune system and a sheep flock algorithm...

  17. Propulsion System with Pneumatic Artificial Muscles for Powering Ankle-Foot Orthosis

    Science.gov (United States)

    Veneva, Ivanka; Vanderborght, Bram; Lefeber, Dirk; Cherelle, Pierre

    2013-12-01

    The aim of this paper is to present the design of device for control of new propulsion system with pneumatic artificial muscles. The propulsion system can be used for ankle joint articulation, for assisting and rehabilitation in cases of injured ankle-foot complex, stroke patients or elderly with functional weakness. Proposed device for control is composed by microcontroller, generator for muscles contractions and sensor system. The microcontroller receives the control signals from sensors and modulates ankle joint flex- ion and extension during human motion. The local joint control with a PID (Proportional-Integral Derivative) position feedback directly calculates desired pressure levels and dictates the necessary contractions. The main goal is to achieve an adaptation of the system and provide the necessary joint torque using position control with feedback.

  18. A development framework for artificial intelligence based distributed operations support systems

    Science.gov (United States)

    Adler, Richard M.; Cottman, Bruce H.

    1990-01-01

    Advanced automation is required to reduce costly human operations support requirements for complex space-based and ground control systems. Existing knowledge based technologies have been used successfully to automate individual operations tasks. Considerably less progress has been made in integrating and coordinating multiple operations applications for unified intelligent support systems. To fill this gap, SOCIAL, a tool set for developing Distributed Artificial Intelligence (DAI) systems is being constructed. SOCIAL consists of three primary language based components defining: models of interprocess communication across heterogeneous platforms; models for interprocess coordination, concurrency control, and fault management; and for accessing heterogeneous information resources. DAI applications subsystems, either new or existing, will access these distributed services non-intrusively, via high-level message-based protocols. SOCIAL will reduce the complexity of distributed communications, control, and integration, enabling developers to concentrate on the design and functionality of the target DAI system itself.

  19. Use of a parallel artificial membrane system to evaluate passive absorption and elimination in small fish.

    Science.gov (United States)

    Kwon, Jung-Hwan; Katz, Lynn E; Liljestrand, Howard M

    2006-12-01

    A parallel artificial lipid membrane system was developed to mimic passive mass transfer of hydrophobic organic chemicals in fish. In this physical model system, a membrane filter-supported lipid bilayer separates two aqueous phases that represent the external and internal aqueous environments of fish. To predict bioconcentration kinetics in small fish with this system, literature absorption and elimination rates were analyzed with an allometric diffusion model to quantify the mass transfer resistances in the aqueous and lipid phases of fish. The effect of the aqueous phase mass transfer resistance was controlled by adjusting stirring intensity to mimic bioconcentration rates in small fish. Twenty-three simple aromatic hydrocarbons were chosen as model compounds for purposes of evaluation. For most of the selected chemicals, literature absorption/elimination rates fall into the range predicted from measured membrane permeabilities and elimination rates of the selected chemicals determined by the diffusion model system.

  20. Brain potentials predict learning, transmission and modification of an artificial symbolic system

    DEFF Research Database (Denmark)

    Lumaca, Massimo; Baggio, G.

    2016-01-01

    capacity account for aspects of ‘variation’ observed in symbolic behavior and symbolic systems. We addressed this issue in the domain of auditory processing.We conducted a combined behavioral and EEG study on 2 successive days. On day 1, participants listened to standard and deviant five-tone sequences......: as in previous oddball studies, an mismatch negativity (MMN) was elicited by deviant tones. On day 2, participants learned an artificial signaling system from a trained confederate of the experimenters in a coordination game in which five-tone sequences were associated to affective meanings (emotion......-laden pictures of human faces). In a subsequent game with identical structure, participants transmitted and occasionally changed the signaling system learned during the first game. TheMMNlatency from day 1 predicted learning, transmission and structural modification of signaling systems on day 2. Our study...

  1. Apparatus and method for measuring single cell and sub-cellular photosynthetic efficiency

    Science.gov (United States)

    Davis, Ryan Wesley; Singh, Seema; Wu, Huawen

    2013-07-09

    Devices for measuring single cell changes in photosynthetic efficiency in algal aquaculture are disclosed that include a combination of modulated LED trans-illumination of different intensities with synchronized through objective laser illumination and confocal detection. Synchronization and intensity modulation of a dual illumination scheme were provided using a custom microcontroller for a laser beam block and constant current LED driver. Therefore, single whole cell photosynthetic efficiency, and subcellular (diffraction limited) photosynthetic efficiency measurement modes are permitted. Wide field rapid light scanning actinic illumination is provided for both by an intensity modulated 470 nm LED. For the whole cell photosynthetic efficiency measurement, the same LED provides saturating pulses for generating photosynthetic induction curves. For the subcellular photosynthetic efficiency measurement, a switched through objective 488 nm laser provides saturating pulses for generating photosynthetic induction curves. A second near IR LED is employed to generate dark adapted states in the system under study.

  2. Proposal of a framework for solving human factors of artificial systems and its application to maintenance work

    International Nuclear Information System (INIS)

    Nagamatsu, Takashi; Otsuji, Tomoo; Yoshikawa, Hidekazu; Shiba, Shigenari

    2004-01-01

    A framework for solving human factors of artificial systems is proposed in this study, where a whole system of machines and the human organization that involves in the operation and management of machines is defined as an 'artificial system'. Five aspects of human factors in the artificial system are first discussed, and the types of artificial system with respect to the human factors are divided into three levels from a viewpoint of complexity. A framework that can treat artificial systems by unified methodology has been proposed for treating both the complexity level and the different kinds of human factors. As a concrete example of this framework application, a prototype system has been developed for advanced plant maintenance support by using ES-HMD (Eye Sensing-Head Mounted Display). This is a remote communication system of cooperative maintenance work between the expert in a remote support center and the maintenance worker at a certain machine in the plant site to conduct a complicated task without committing human error. It was confirmed by laboratory experiment that the expert would instruct the worker so that he or she could perform the task successfully, by observing the worker's eye gazing point and by pointing the right place of action on the transferred display of the worker's eyesight through the ES-MHD. (author)

  3. Geometric Distribution-Based Readers Scheduling Optimization Algorithm Using Artificial Immune System

    Directory of Open Access Journals (Sweden)

    Litian Duan

    2016-11-01

    Full Text Available In the multiple-reader environment (MRE of radio frequency identification (RFID system, multiple readers are often scheduled to interrogate the randomized tags via operating at different time slots or frequency channels to decrease the signal interferences. Based on this, a Geometric Distribution-based Multiple-reader Scheduling Optimization Algorithm using Artificial Immune System (GD-MRSOA-AIS is proposed to fairly and optimally schedule the readers operating from the viewpoint of resource allocations. GD-MRSOA-AIS is composed of two parts, where a geometric distribution function combined with the fairness consideration is first introduced to generate the feasible scheduling schemes for reader operation. After that, artificial immune system (including immune clone, immune mutation and immune suppression quickly optimize these feasible ones as the optimal scheduling scheme to ensure that readers are fairly operating with larger effective interrogation range and lower interferences. Compared with the state-of-the-art algorithm, the simulation results indicate that GD-MRSOA-AIS could efficiently schedules the multiple readers operating with a fairer resource allocation scheme, performing in larger effective interrogation range.

  4. 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

  5. Microsoft kinect-based artificial perception system for control of functional electrical stimulation assisted grasping.

    Science.gov (United States)

    Strbac, Matija; Kočović, Slobodan; Marković, Marko; Popović, Dejan B

    2014-01-01

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

  6. Artificial neural network to support thermohydraulic design optimization for an advanced nuclear heat removal system

    International Nuclear Information System (INIS)

    Ridluan, Artit; Tokuhiro, Akira; Linda, Ondrej; Manic, Milos

    2009-01-01

    The U.S. Department of Energy (DOE) is leading a number of initiatives, including one known as the Next Generation Nuclear Plant (NGNP) project. One of the NGNP nuclear system concepts is the Very High Temperature (gas-cooled) Reactor (VHTR) that may be coupled to a hydrogen generating plant to support the anticipated hydrogen economy. For the NGNP, an efficient power conversion system using an Intermediate Heat Exchanger (IHX) is key to electricity and/or process heat generation (hydrogen production). Ideally, it's desirable for the IHX to be compact and thermally efficient. However, traditional heat exchanger design practices do not assure that the design parameters are optimized. As part of NGNP heat exchanger design and optimization project, this research paper thus proposes developing a recurrent-type Artificial Neural Network (ANN), the Hopfield Network (HN) model, in which the activation function is modified, as a design optimization approach to support a NGNP thermal system candidate, the Printed Circuit Heat Exchanger (PCHE). Four quadratic functions, available in literature, were used to test the presented methodology. The results computed by an artificially intelligent approach were compared to another approach, the Genetic Algorithm (GA). The results show that the HN results are close to GA in optimization of multi-variable second-order equations. (author)

  7. A non-contact shape measuring system using an artificial neural network

    International Nuclear Information System (INIS)

    Jeon, Woo Tae; Lee, Myung Chan; Koh, Duck Joon; Cho, Hyung Suck

    1996-01-01

    We developed a non-contact shape measuring device using computer image processing technology. We present a method of calibrating a CCD video camera and a laser range finder which is the most important step toward making an accurate shape measuring system. An artificial neural network is used for the calibration. Our measurement system is composed of a semiconductor laser, a CCD video camera, a personal computer, and a linear motion table. We think that the developed system could be used for measuring the change in shape of the spent nuclear fuel rod before and after irradiation which is one of the most important tasks for developing a better nuclear fuel. A radiation shield is suggested for the possible utilization of the range finder in radioactive environment

  8. Monitoring and operational support on nuclear power plants using an artificial intelligence system

    International Nuclear Information System (INIS)

    Bianchi, P.H.; Baptista Filho, B.D.

    2009-01-01

    The monitoring task in nuclear power plants is of crucial importance with respect to safety and efficient operation. The operators have a wide range of variables to observe and analyze; the quantity of variables and their behavior determine the time they have to take correct decisions. The complexity of such aspects in a nuclear power plant influences both, the plant operational efficiency and the general safety issues. This paper describes an experimental system developed by the authors which aims to assist the operators of nuclear power plants to take quick and safe decisions. The system maps the status of plant and helps the operators to make quick judgments by using artificial intelligence methods. The method makes use of a small set of monitored variables and presents a map of the plant status in a friendly manner. This system uses an architecture that has multiple self-organizing maps to perform these tasks. (author)

  9. Application of artificial neural network to predict the optimal start time for heating system in building

    International Nuclear Information System (INIS)

    Yang, In-Ho; Yeo, Myoung-Souk; Kim, Kwang-Woo

    2003-01-01

    The artificial neural network (ANN) approach is a generic technique for mapping non-linear relationships between inputs and outputs without knowing the details of these relationships. This paper presents an application of the ANN in a building control system. The objective of this study is to develop an optimized ANN model to determine the optimal start time for a heating system in a building. For this, programs for predicting the room air temperature and the learning of the ANN model based on back propagation learning were developed, and learning data for various building conditions were collected through program simulation for predicting the room air temperature using systems of experimental design. Then, the optimized ANN model was presented through learning of the ANN, and its performance to determine the optimal start time was evaluated

  10. Artificial intelligence technology assessment for the US Army Depot System Command

    Energy Technology Data Exchange (ETDEWEB)

    Pennock, K A

    1991-07-01

    This assessment of artificial intelligence (AI) has been prepared for the US Army's Depot System Command (DESCOM) by Pacific Northwest Laboratory. The report describes several of the more promising AI technologies, focusing primarily on knowledge-based systems because they have been more successful in commercial applications than any other AI technique. The report also identifies potential Depot applications in the areas of procedural support, scheduling and planning, automated inspection, training, diagnostics, and robotic systems. One of the principal objectives of the report is to help decisionmakers within DESCOM to evaluate AI as a possible tool for solving individual depot problems. The report identifies a number of factors that should be considered in such evaluations. 22 refs.

  11. Monitoring and operational support on nuclear power plants using an artificial intelligence system

    Energy Technology Data Exchange (ETDEWEB)

    Bianchi, Paulo H.; Baptista Filho, Benedito D., E-mail: phbianchi@gmail.co, E-mail: bdbfilho@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

    2009-07-01

    The monitoring task in nuclear power plants is of crucial importance with respect to safety and efficient operation. The operators have a wide range of variables to observe and analyze; the quantity of variables and their behavior determine the time they have to take correct decisions. The complexity of such aspects in a nuclear power plant influences both, the plant operational efficiency and the general safety issues. This paper describes an experimental system developed by the authors which aims to assist the operators of nuclear power plants to take quick and safe decisions. The system maps the status of plant and helps the operators to make quick judgments by using artificial intelligence methods. The method makes use of a small set of monitored variables and presents a map of the plant status in a friendly manner. This system uses an architecture that has multiple self-organizing maps to perform these tasks. (author)

  12. Artificial Neural Network-Based Clutter Reduction Systems for Ship Size Estimation in Maritime Radars

    Directory of Open Access Journals (Sweden)

    M. P. Jarabo-Amores

    2010-01-01

    Full Text Available The existence of clutter in maritime radars deteriorates the estimation of some physical parameters of the objects detected over the sea surface. For that reason, maritime radars should incorporate efficient clutter reduction techniques. Due to the intrinsic nonlinear dynamic of sea clutter, nonlinear signal processing is needed, what can be achieved by artificial neural networks (ANNs. In this paper, an estimation of the ship size using an ANN-based clutter reduction system followed by a fixed threshold is proposed. High clutter reduction rates are achieved using 1-dimensional (horizontal or vertical integration modes, although inaccurate ship width estimations are achieved. These estimations are improved using a 2-dimensional (rhombus integration mode. The proposed system is compared with a CA-CFAR system, denoting a great performance improvement and a great robustness against changes in sea clutter conditions and ship parameters, independently of the direction of movement of the ocean waves and ships.

  13. Integration of artificial intelligence and numerical optimization techniques for the design of complex aerospace systems

    International Nuclear Information System (INIS)

    Tong, S.S.; Powell, D.; Goel, S.

    1992-02-01

    A new software system called Engineous combines artificial intelligence and numerical methods for the design and optimization of complex aerospace systems. Engineous combines the advanced computational techniques of genetic algorithms, expert systems, and object-oriented programming with the conventional methods of numerical optimization and simulated annealing to create a design optimization environment that can be applied to computational models in various disciplines. Engineous has produced designs with higher predicted performance gains that current manual design processes - on average a 10-to-1 reduction of turnaround time - and has yielded new insights into product design. It has been applied to the aerodynamic preliminary design of an aircraft engine turbine, concurrent aerodynamic and mechanical preliminary design of an aircraft engine turbine blade and disk, a space superconductor generator, a satellite power converter, and a nuclear-powered satellite reactor and shield. 23 refs

  14. [Elaboration of Pseudo-natural Products Using Artificial In Vitro Biosynthesis Systems].

    Science.gov (United States)

    Goto, Yuki

    2018-01-01

     Peptidic natural products often consist of not only proteinogenic building blocks but also unique non-proteinogenic structures such as macrocyclic scaffolds and N-methylated backbones. Since such non-proteinogenic structures are important structural motifs that contribute to diverse bioactivity, we have proposed that peptides with non-proteinogenic structures should be attractive candidates as artificial bioactive peptides mimicking natural products, or so-called pseudo-natural products. We previously devised an engineered translation system for pseudo-natural peptides, referred to as the flexible in vitro translation (FIT) system. This system enabled "one-pot" synthesis of highly diverse pseudo-natural peptide libraries, which can be rapidly screened by mRNA display technology for the discovery of pseudo-natural peptides with diverse bioactivities.

  15. Development of a microcontroller-based automatic control system for the electrohydraulic total artificial heart.

    Science.gov (United States)

    Kim, H C; Khanwilkar, P S; Bearnson, G B; Olsen, D B

    1997-01-01

    An automatic physiological control system for the actively filled, alternately pumped ventricles of the volumetrically coupled, electrohydraulic total artificial heart (EHTAH) was developed for long-term use. The automatic control system must ensure that the device: 1) maintains a physiological response of cardiac output, 2) compensates for an nonphysiological condition, and 3) is stable, reliable, and operates at a high power efficiency. The developed automatic control system met these requirements both in vitro, in week-long continuous mock circulation tests, and in vivo, in acute open-chested animals (calves). Satisfactory results were also obtained in a series of chronic animal experiments, including 21 days of continuous operation of the fully automatic control mode, and 138 days of operation in a manual mode, in a 159-day calf implant.

  16. Analysis of Boiler Operational Variables Prior to Tube Leakage Fault by Artificial Intelligent System

    Directory of Open Access Journals (Sweden)

    Al-Kayiem Hussain H.

    2014-07-01

    Full Text Available Steam boilers are considered as a core of any steam power plant. Boilers are subjected to various types of trips leading to shut down of the entire plant. The tube leakage is the worse among the common boiler faults, where the shutdown period lasts for around four to five days. This paper describes the rules of the Artificial Intelligent Systems to diagnosis the boiler variables prior to tube leakage occurrence. An Intelligent system based on Artificial Neural Network was designed and coded in MATLAB environment. The ANN was trained and validated using real site data acquired from coal fired power plant in Malaysia. Ninety three boiler operational variables were identified for the present investigation based on the plant operator experience. Various neural networks topology combinations were investigated. The results showed that the NN with two hidden layers performed better than one hidden layer using Levenberg-Maquardt training algorithm. Moreover, it was noticed that hyperbolic tangent function for input and output nodes performed better than other activation function types.

  17. AITSO: A Tool for Spatial Optimization Based on Artificial Immune Systems

    Science.gov (United States)

    Zhao, Xiang; Liu, Yaolin; Liu, Dianfeng; Ma, Xiaoya

    2015-01-01

    A great challenge facing geocomputation and spatial analysis is spatial optimization, given that it involves various high-dimensional, nonlinear, and complicated relationships. Many efforts have been made with regard to this specific issue, and the strong ability of artificial immune system algorithms has been proven in previous studies. However, user-friendly professional software is still unavailable, which is a great impediment to the popularity of artificial immune systems. This paper describes a free, universal tool, named AITSO, which is capable of solving various optimization problems. It provides a series of standard application programming interfaces (APIs) which can (1) assist researchers in the development of their own problem-specific application plugins to solve practical problems and (2) allow the implementation of some advanced immune operators into the platform to improve the performance of an algorithm. As an integrated, flexible, and convenient tool, AITSO contributes to knowledge sharing and practical problem solving. It is therefore believed that it will advance the development and popularity of spatial optimization in geocomputation and spatial analysis. PMID:25678911

  18. AITSO: A Tool for Spatial Optimization Based on Artificial Immune Systems

    Directory of Open Access Journals (Sweden)

    Xiang Zhao

    2015-01-01

    Full Text Available A great challenge facing geocomputation and spatial analysis is spatial optimization, given that it involves various high-dimensional, nonlinear, and complicated relationships. Many efforts have been made with regard to this specific issue, and the strong ability of artificial immune system algorithms has been proven in previous studies. However, user-friendly professional software is still unavailable, which is a great impediment to the popularity of artificial immune systems. This paper describes a free, universal tool, named AITSO, which is capable of solving various optimization problems. It provides a series of standard application programming interfaces (APIs which can (1 assist researchers in the development of their own problem-specific application plugins to solve practical problems and (2 allow the implementation of some advanced immune operators into the platform to improve the performance of an algorithm. As an integrated, flexible, and convenient tool, AITSO contributes to knowledge sharing and practical problem solving. It is therefore believed that it will advance the development and popularity of spatial optimization in geocomputation and spatial analysis.

  19. A 2-transistor/1-resistor artificial synapse capable of communication and stochastic learning in neuromorphic systems.

    Science.gov (United States)

    Wang, Zhongqiang; Ambrogio, Stefano; Balatti, Simone; Ielmini, Daniele

    2014-01-01

    Resistive (or memristive) switching devices based on metal oxides find applications in memory, logic and neuromorphic computing systems. Their small area, low power operation, and high functionality meet the challenges of brain-inspired computing aiming at achieving a huge density of active connections (synapses) with low operation power. This work presents a new artificial synapse scheme, consisting of a memristive switch connected to 2 transistors responsible for gating the communication and learning operations. Spike timing dependent plasticity (STDP) is achieved through appropriate shaping of the pre-synaptic and the post synaptic spikes. Experiments with integrated artificial synapses demonstrate STDP with stochastic behavior due to (i) the natural variability of set/reset processes in the nanoscale switch, and (ii) the different response of the switch to a given stimulus depending on the initial state. Experimental results are confirmed by model-based simulations of the memristive switching. Finally, system-level simulations of a 2-layer neural network and a simplified STDP model show random learning and recognition of patterns.

  20. An artificial neural network system to identify alleles in reference electropherograms.

    Science.gov (United States)

    Taylor, Duncan; Harrison, Ash; Powers, David

    2017-09-01

    Electropherograms are produced in great numbers in forensic DNA laboratories as part of everyday criminal casework. Before the results of these electropherograms can be used they must be scrutinised by analysts to determine what the identified data tells them about the underlying DNA sequences and what is purely an artefact of the DNA profiling process. This process of interpreting the electropherograms can be time consuming and is prone to subjective differences between analysts. Recently it was demonstrated that artificial neural networks could be used to classify information within an electropherogram as allelic (i.e. representative of a DNA fragment present in the DNA extract) or as one of several different categories of artefactual fluorescence that arise as a result of generating an electropherogram. We extend that work here to demonstrate a series of algorithms and artificial neural networks that can be used to identify peaks on an electropherogram and classify them. We demonstrate the functioning of the system on several profiles and compare the results to a leading commercial DNA profile reading system. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Physiological characterization of the SynCardia total artificial heart in a mock circulation system.

    Science.gov (United States)

    Crosby, Jessica R; DeCook, Katrina J; Tran, Phat L; Smith, Richard G; Larson, Douglas F; Khalpey, Zain I; Burkhoff, Daniel; Slepian, Marvin J

    2015-01-01

    The SynCardia total artificial heart (TAH) has emerged as an effective, life-saving biventricular replacement system for a wide variety of patients with end-stage heart failure. Although the clinical performance of the TAH is established, modern physiological characterization, in terms of elastance behavior and pressure-volume (PV) characterization has not been defined. Herein, we examine the TAH in terms of elastance using a nonejecting left ventricle, and then characterize the PV relation of the TAH by varying preload and afterload parameters using a Donovan Mock Circulatory System. We demonstrate that the TAH does not operate with time-varying elastance, differing from the human heart. Furthermore, we show that the TAH has a PV relation behavior that also differs from that of the human heart. The TAH does exhibit Starling-like behavior, with output increasing via preload-dependent mechanisms, without reliance on an alteration of inotropic state within the operating window of the TAH. Within our testing range, the TAH is insensitive to variations in afterload; however, this insensitivity has a limit, the limit being the maximum driving pressure of the pneumatic driver. Understanding the physiology of the TAH affords insight into the functional parameters that govern artificial heart behavior providing perspective on differences compared with the human heart.

  2. A Game Theoretic Framework for Incentive-Based Models of Intrinsic Motivation in Artificial Systems

    Directory of Open Access Journals (Sweden)

    Kathryn Elizabeth Merrick

    2013-10-01

    Full Text Available An emerging body of research is focusing on understanding and building artificial systems that can achieve open-ended development influenced by intrinsic motivations. In particular, research in robotics and machine learning is yielding systems and algorithms with increasing capacity for self-directed learning and autonomy. Traditional software architectures and algorithms are being augmented with intrinsic motivations to drive cumulative acquisition of knowledge and skills. Intrinsic motivations have recently been considered in reinforcement learning, active learning and supervised learning settings among others. This paper considers game theory as a novel setting for intrinsic motivation. A game theoretic framework for intrinsic motivation is formulated by introducing the concept of optimally motivating incentive as a lens through which players perceive a game. Transformations of four well-known mixed-motive games are presented to demonstrate the perceived games when players’ optimally motivating incentive falls in three cases corresponding to strong power, affiliation and achievement motivation. We use agent-based simulations to demonstrate that players with different optimally motivating incentive act differently as a result of their altered perception of the game. We discuss the implications of these results both for modeling human behavior and for designing artificial agents or robots.

  3. A game theoretic framework for incentive-based models of intrinsic motivation in artificial systems.

    Science.gov (United States)

    Merrick, Kathryn E; Shafi, Kamran

    2013-01-01

    An emerging body of research is focusing on understanding and building artificial systems that can achieve open-ended development influenced by intrinsic motivations. In particular, research in robotics and machine learning is yielding systems and algorithms with increasing capacity for self-directed learning and autonomy. Traditional software architectures and algorithms are being augmented with intrinsic motivations to drive cumulative acquisition of knowledge and skills. Intrinsic motivations have recently been considered in reinforcement learning, active learning and supervised learning settings among others. This paper considers game theory as a novel setting for intrinsic motivation. A game theoretic framework for intrinsic motivation is formulated by introducing the concept of optimally motivating incentive as a lens through which players perceive a game. Transformations of four well-known mixed-motive games are presented to demonstrate the perceived games when players' optimally motivating incentive falls in three cases corresponding to strong power, affiliation and achievement motivation. We use agent-based simulations to demonstrate that players with different optimally motivating incentive act differently as a result of their altered perception of the game. We discuss the implications of these results both for modeling human behavior and for designing artificial agents or robots.

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

    International Nuclear Information System (INIS)

    Moon, Jin Woo

    2015-01-01

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

  5. Optimization of an artificial-recharge-pumping system for water supply in the Maghaway Valley, Cebu, Philippines

    Science.gov (United States)

    Kawo, Nafyad Serre; Zhou, Yangxiao; Magalso, Ronnell; Salvacion, Lasaro

    2018-05-01

    A coupled simulation-optimization approach to optimize an artificial-recharge-pumping system for the water supply in the Maghaway Valley, Cebu, Philippines, is presented. The objective is to maximize the total pumping rate through a system of artificial recharge and pumping while meeting constraints such as groundwater-level drawdown and bounds on pumping rates at each well. The simulation models were coupled with groundwater management optimization to maximize production rates. Under steady-state natural conditions, the significant inflow to the aquifer comes from river leakage, whereas the natural discharge is mainly the subsurface outflow to the downstream area. Results from the steady artificial-recharge-pumping simulation model show that artificial recharge is about 20,587 m3/day and accounts for 77% of total inflow. Under transient artificial-recharge-pumping conditions, artificial recharge varies between 14,000 and 20,000 m3/day depending on the wet and dry seasons, respectively. The steady-state optimisation results show that the total optimal abstraction rate is 37,545 m3/day and artificial recharge is increased to 29,313 m3/day. The transient optimization results show that the average total optimal pumping rate is 36,969 m3/day for the current weir height. The transient optimization results for an increase in weir height by 1 and 2 m show that the average total optimal pumping rates are increased to 38,768 and 40,463 m3/day, respectively. It is concluded that the increase in the height of the weir can significantly increase the artificial recharge rate and production rate in Maghaway Valley.

  6. Robustness, efficiency, and optimality in the Fenna-Matthews-Olson photosynthetic pigment-protein complex

    Energy Technology Data Exchange (ETDEWEB)

    Baker, Lewis A.; Habershon, Scott, E-mail: S.Habershon@warwick.ac.uk [Department of Chemistry and Centre for Scientific Computing, University of Warwick, Coventry CV4 7AL (United Kingdom)

    2015-09-14

    Pigment-protein complexes (PPCs) play a central role in facilitating excitation energy transfer (EET) from light-harvesting antenna complexes to reaction centres in photosynthetic systems; understanding molecular organisation in these biological networks is key to developing better artificial light-harvesting systems. In this article, we combine quantum-mechanical simulations and a network-based picture of transport to investigate how chromophore organization and protein environment in PPCs impacts on EET efficiency and robustness. In a prototypical PPC model, the Fenna-Matthews-Olson (FMO) complex, we consider the impact on EET efficiency of both disrupting the chromophore network and changing the influence of (local and global) environmental dephasing. Surprisingly, we find a large degree of resilience to changes in both chromophore network and protein environmental dephasing, the extent of which is greater than previously observed; for example, FMO maintains EET when 50% of the constituent chromophores are removed, or when environmental dephasing fluctuations vary over two orders-of-magnitude relative to the in vivo system. We also highlight the fact that the influence of local dephasing can be strongly dependent on the characteristics of the EET network and the initial excitation; for example, initial excitations resulting in rapid coherent decay are generally insensitive to the environment, whereas the incoherent population decay observed following excitation at weakly coupled chromophores demonstrates a more pronounced dependence on dephasing rate as a result of the greater possibility of local exciton trapping. Finally, we show that the FMO electronic Hamiltonian is not particularly optimised for EET; instead, it is just one of many possible chromophore organisations which demonstrate a good level of EET transport efficiency following excitation at different chromophores. Overall, these robustness and efficiency characteristics are attributed to the highly

  7. Robustness, efficiency, and optimality in the Fenna-Matthews-Olson photosynthetic pigment-protein complex

    International Nuclear Information System (INIS)

    Baker, Lewis A.; Habershon, Scott

    2015-01-01

    Pigment-protein complexes (PPCs) play a central role in facilitating excitation energy transfer (EET) from light-harvesting antenna complexes to reaction centres in photosynthetic systems; understanding molecular organisation in these biological networks is key to developing better artificial light-harvesting systems. In this article, we combine quantum-mechanical simulations and a network-based picture of transport to investigate how chromophore organization and protein environment in PPCs impacts on EET efficiency and robustness. In a prototypical PPC model, the Fenna-Matthews-Olson (FMO) complex, we consider the impact on EET efficiency of both disrupting the chromophore network and changing the influence of (local and global) environmental dephasing. Surprisingly, we find a large degree of resilience to changes in both chromophore network and protein environmental dephasing, the extent of which is greater than previously observed; for example, FMO maintains EET when 50% of the constituent chromophores are removed, or when environmental dephasing fluctuations vary over two orders-of-magnitude relative to the in vivo system. We also highlight the fact that the influence of local dephasing can be strongly dependent on the characteristics of the EET network and the initial excitation; for example, initial excitations resulting in rapid coherent decay are generally insensitive to the environment, whereas the incoherent population decay observed following excitation at weakly coupled chromophores demonstrates a more pronounced dependence on dephasing rate as a result of the greater possibility of local exciton trapping. Finally, we show that the FMO electronic Hamiltonian is not particularly optimised for EET; instead, it is just one of many possible chromophore organisations which demonstrate a good level of EET transport efficiency following excitation at different chromophores. Overall, these robustness and efficiency characteristics are attributed to the highly

  8. System responses to equal doses of photosynthetically usable radiation of blue, green, and red light in the marine diatom Phaeodactylum tricornutum.

    Directory of Open Access Journals (Sweden)

    Kristin Collier Valle

    Full Text Available Due to the selective attenuation of solar light and the absorption properties of seawater and seawater constituents, free-floating photosynthetic organisms have to cope with rapid and unpredictable changes in both intensity and spectral quality. We have studied the transcriptional, metabolic and photo-physiological responses to light of different spectral quality in the marine diatom Phaeodactylum tricornutum through time-series studies of cultures exposed to equal doses of photosynthetically usable radiation of blue, green and red light. The experiments showed that short-term differences in gene expression and profiles are mainly light quality-dependent. Transcription of photosynthesis-associated nuclear genes was activated mainly through a light quality-independent mechanism likely to rely on chloroplast-to-nucleus signaling. In contrast, genes encoding proteins important for photoprotection and PSII repair were highly dependent on a blue light receptor-mediated signal. Changes in energy transfer efficiency by light-harvesting pigments were spectrally dependent; furthermore, a declining trend in photosynthetic efficiency was observed in red light. The combined results suggest that diatoms possess a light quality-dependent ability to activate photoprotection and efficient repair of photodamaged PSII. In spite of approximately equal numbers of PSII-absorbed quanta in blue, green and red light, the spectral quality of light is important for diatom responses to ambient light conditions.

  9. Phase equilibrium of binary system carbon dioxide - methanol at high pressure using artificial neural network

    International Nuclear Information System (INIS)

    Nasri, F.; Hatami, T.

    2012-01-01

    Interest in supercritical fluids extraction (SFE ) is increasing throughout many scientific and industrial fields. The common solvent for use in SFE is carbon dioxide. However, pure carbon dioxide frequently fails to efficiently extract the essential oil from a sample matrix, and modifier fluids such as methanol should be used to enhance extraction yield. A more efficient use of SFE requires quantitative prediction of phase equilibrium of this binary system, carbon dioxide - methanol. The purpose of the current research is modeling carbon dioxide - methanol system using artificial neural network (ANN). Results of ANN modeling has been compared with experimental data as well as thermodynamic equations of state. The comparison shows that the ANN modeling has a higher accuracy than thermodynamic models. (author)

  10. Natural gas demand forecast system based on the application of artificial neural networks

    International Nuclear Information System (INIS)

    Sanfeliu, J.M.; Doumanian, J.E.

    1997-01-01

    Gas Natural BAN, as a distribution gas company since 1993 in the north and west area of Buenos Aires Argentina, with 1,000,000 customers, had to develop a gas demand forecast system which should comply with the following basic requirements: Be able to do reliable forecasts with short historical information (2 years); Distinguish demands in areas of different characteristics, i.e. mainly residential, mainly industrial; Self-learning capability. To accomplish above goals, Gas Natural BAN chose in view of its own necessities, an artificial intelligence application (neural networks). 'SANDRA', the gas demand forecast system for gas distribution used by Gas Natural BAN, has the following features: Daily gas demand forecast, Hourly gas demand forecast and Breakdown of both forecast for each of the 3 basic zones in which the distribution area of Gas Natural BAN is divided. (au)

  11. Fault tolerance of artificial neural networks with applications in critical systems

    Science.gov (United States)

    Protzel, Peter W.; Palumbo, Daniel L.; Arras, Michael K.

    1992-01-01

    This paper investigates the fault tolerance characteristics of time continuous recurrent artificial neural networks (ANN) that can be used to solve optimization problems. The principle of operations and performance of these networks are first illustrated by using well-known model problems like the traveling salesman problem and the assignment problem. The ANNs are then subjected to 13 simultaneous 'stuck at 1' or 'stuck at 0' faults for network sizes of up to 900 'neurons'. The effects of these faults is demonstrated and the cause for the observed fault tolerance is discussed. An application is presented in which a network performs a critical task for a real-time distributed processing system by generating new task allocations during the reconfiguration of the system. The performance degradation of the ANN under the presence of faults is investigated by large-scale simulations, and the potential benefits of delegating a critical task to a fault tolerant network are discussed.

  12. Based on Artificial Neural Network to Realize K-Parameter Analysis of Vehicle Air Spring System

    Science.gov (United States)

    Hung, San-Shan; Hsu, Chia-Ning; Hwang, Chang-Chou; Chen, Wen-Jan

    2017-10-01

    In recent years, because of the air-spring control technique is more mature, that air- spring suspension systems already can be used to replace the classical vehicle suspension system. Depend on internal pressure variation of the air-spring, thestiffnessand the damping factor can be adjusted. Because of air-spring has highly nonlinear characteristic, therefore it isn’t easy to construct the classical controller to control the air-spring effectively. The paper based on Artificial Neural Network to propose a feasible control strategy. By using offline way for the neural network design and learning to the air-spring in different initial pressures and different loads, offline method through, predict air-spring stiffness parameter to establish a model. Finally, through adjusting air-spring internal pressure to change the K-parameter of the air-spring, realize the well dynamic control performance of air-spring suspension.

  13. Uncertain multiobjective redundancy allocation problem of repairable systems based on artificial bee colony algorithm

    Institute of Scientific and Technical Information of China (English)

    Guo Jiansheng; Wang Zutong; Zheng Mingfa; Wang Ying

    2014-01-01

    Based on the uncertainty theory, this paper is devoted to the redundancy allocation problem in repairable parallel-series systems with uncertain factors, where the failure rate, repair rate and other relative coefficients involved are considered as uncertain variables. The availability of the system and the corresponding designing cost are considered as two optimization objectives. A crisp multiobjective optimization formulation is presented on the basis of uncertainty theory to solve this resultant problem. For solving this problem efficiently, a new multiobjective artificial bee colony algorithm is proposed to search the Pareto efficient set, which introduces rank value and crowding distance in the greedy selection strategy, applies fast non-dominated sort procedure in the exploitation search and inserts tournament selection in the onlooker bee phase. It shows that the proposed algorithm outperforms NSGA-II greatly and can solve multiobjective redundancy allocation problem efficiently. Finally, a numerical example is provided to illustrate this approach.

  14. Powered Upper Limb Orthosis Actuation System Based on Pneumatic Artificial Muscles

    Science.gov (United States)

    Chakarov, Dimitar; Veneva, Ivanka; Tsveov, Mihail; Venev, Pavel

    2018-03-01

    The actuation system of a powered upper limb orthosis is studied in the work. To create natural safety in the mutual "man-robot" interaction, an actuation system based on pneumatic artificial muscles (PAM) is selected. Experimentally obtained force/contraction diagrams for bundles, consisting of different number of muscles are shown in the paper. The pooling force and the stiffness of the pneumatic actuators is assessed as a function of the number of muscles in the bundle and the supply pressure. Joint motion and torque is achieved by antagonistic actions through pulleys, driven by bundles of pneumatic muscles. Joint stiffness and joint torques are determined on condition of a power balance, as a function of the joint position, pressure, number of muscles and muscles

  15. DECISION WITH ARTIFICIAL NEURAL NETWORKS IN DISCRETE EVENT SIMULATION MODELS ON A TRAFFIC SYSTEM

    Directory of Open Access Journals (Sweden)

    Marília Gonçalves Dutra da Silva

    2016-04-01

    Full Text Available ABSTRACT This work aims to demonstrate the use of a mechanism to be applied in the development of the discrete-event simulation models that perform decision operations through the implementation of an artificial neural network. Actions that involve complex operations performed by a human agent in a process, for example, are often modeled in simplified form with the usual mechanisms of simulation software. Therefore, it was chosen a traffic system controlled by a traffic officer with a flow of vehicles and pedestrians to demonstrate the proposed solution. From a module built in simulation software itself, it was possible to connect the algorithm for intelligent decision to the simulation model. The results showed that the model elaborated responded as expected when it was submitted to actions, which required different decisions to maintain the operation of the system with changes in the flow of people and vehicles.

  16. Coral bleaching independent of photosynthetic activity.

    Science.gov (United States)

    Tolleter, Dimitri; Seneca, François O; DeNofrio, Jan C; Krediet, Cory J; Palumbi, Stephen R; Pringle, John R; Grossman, Arthur R

    2013-09-23

    The global decline of reef-building corals is due in part to the loss of algal symbionts, or "bleaching," during the increasingly frequent periods of high seawater temperatures. During bleaching, endosymbiotic dinoflagellate algae (Symbiodinium spp.) either are lost from the animal tissue or lose their photosynthetic pigments, resulting in host mortality if the Symbiodinium populations fail to recover. The >1,000 studies of the causes of heat-induced bleaching have focused overwhelmingly on the consequences of damage to algal photosynthetic processes, and the prevailing model for bleaching invokes a light-dependent generation of toxic reactive oxygen species (ROS) by heat-damaged chloroplasts as the primary trigger. However, the precise mechanisms of bleaching remain unknown, and there is evidence for involvement of multiple cellular processes. In this study, we asked the simple question of whether bleaching can be triggered by heat in the dark, in the absence of photosynthetically derived ROS. We used both the sea anemone model system Aiptasia and several species of reef-building corals to demonstrate that symbiont loss can occur rapidly during heat stress in complete darkness. Furthermore, we observed damage to the photosynthetic apparatus under these conditions in both Aiptasia endosymbionts and cultured Symbiodinium. These results do not directly contradict the view that light-stimulated ROS production is important in bleaching, but they do show that there must be another pathway leading to bleaching. Elucidation of this pathway should help to clarify bleaching mechanisms under the more usual conditions of heat stress in the light. Copyright © 2013 Elsevier Ltd. All rights reserved.

  17. Nitrogen control of photosynthetic protein synthesis

    Energy Technology Data Exchange (ETDEWEB)

    Schmidt, G.W.

    1986-09-01

    Plant growth is severely affected by impaired photosynthesis resulting from nitrogen deficiency. The molecular aspects of this effect are being studied in the green alga Chlamydomonas grown in continuous culture systems. Photosynthetic membranes of nitrogen-limited cells are dramatically depleted in chlorophylls, xanthophylls and proteins of the light-harvesting complexes. In contrast, enzymes of the reductive pentose phosphate cycle and electron transport chain complexes are reduced only 40 to 65% on a per cell basis comparison with nitrogen-sufficient cultures. From analyses of mRNA levels by in vitro translation and hybridization analyses with cloned DNA sequences for photosynthetic proteins, we have found there are rather minor effects of nitrogen deficiency on nuclear or chloroplast gene transcription. Maturation of a transcript of the nuclear-encoded small subunit of ribulose 1,5-bisphosphate carboxylase is inhibited in nitrogen-deficient cells and causes accumulation of large amounts of mRNA precursors. Most of the effects of nitrogen deficiency on photosynthetic proteins appear to result from posttranscriptional regulatory processes: light-harvesting protein synthesis may be sustained but their import into chloroplasts or translocation to photosynthetic membranes is impaired. Nitrogen-deficient cells lack violaxanthin, a pigment that is essential for the structure, function and biogenesis of the major antenna complexes. The absence of this pigment may be a causative factor for the deficiency of light harvesting complexes. Finally, the accumulation of massive amounts of starch and triglycerides in nitrogen-limited cells indicate there are some genes whose maximal expression is dependent upon nitrogen-limiting conditions. 10 refs.

  18. Use of artificial intelligence in analytical systems for the clinical laboratory.

    Science.gov (United States)

    Place, J F; Truchaud, A; Ozawa, K; Pardue, H; Schnipelsky, P

    1995-01-01

    The incorporation of information-processing technology into analytical systems in the form of standard computing software has recently been advanced by the introduction of artificial intelligence (AI), both as expert systems and as neural networks.This paper considers the role of software in system operation, control and automation, and attempts to define intelligence. AI is characterized by its ability to deal with incomplete and imprecise information and to accumulate knowledge. Expert systems, building on standard computing techniques, depend heavily on the domain experts and knowledge engineers that have programmed them to represent the real world. Neural networks are intended to emulate the pattern-recognition and parallel processing capabilities of the human brain and are taught rather than programmed. The future may lie in a combination of the recognition ability of the neural network and the rationalization capability of the expert system.In the second part of the paper, examples are given of applications of AI in stand-alone systems for knowledge engineering and medical diagnosis and in embedded systems for failure detection, image analysis, user interfacing, natural language processing, robotics and machine learning, as related to clinical laboratories.It is concluded that AI constitutes a collective form of intellectual propery, and that there is a need for better documentation, evaluation and regulation of the systems already being used in clinical laboratories.

  19. [Application prospect of human-artificial intelligence system in future manned space flight].

    Science.gov (United States)

    Wei, Jin-he

    2003-01-01

    To make the manned space flight more efficient and safer, a concept of human-artificial (AI) system is proposed in the present paper. The task of future manned space flight and the technique requirement with respect to the human-AI system development were analyzed. The main points are as follows: 1)Astronaut and AI are complementary to each other functionally; 2) Both symbol AI and connectionist AI should be included in the human-AI system, but expert system and Soar-like system are used mainly inside the cabin, the COG-like robots are mainly assigned for EVA either in LEO flight or on the surface of Moon or Mars; 3) The human-AI system is hierarchical in nature with astronaut at the top level; 4) The complex interfaces between astronaut and AI are the key points for running the system reliably and efficiently. As the importance of human-AI system in future manned space flight and the complexity of related technology, it is suggested that the R/D should be planned as early as possible.

  20. Artificial intelligence/expert (AI/EX) systems for steelworks pollution control

    Energy Technology Data Exchange (ETDEWEB)

    Schofield, N.; Le Louer, P.; Mirabile, D.; Hubner, R. [Corus UK Ltd., Rotherham (United Kingdom)

    2002-07-01

    The objectives of this project have been to develop and apply artificial intelligence and expert system (AI/EX) methods to improve the control and operational performance of steelworks' pollution control equipment and to assess the viability and benefits of using such systems in dynamic process plant applications. Four distinct sub-projects were carried out: an expert system incorporating knowledge-based rules and neural network simulations has been developed by Corus which provides plant personnel with a real-time condition monitoring tool for the plant. Abnormalities with plant operation are now instantly recognised and alarmed, allowing prioritised maintenance to increase plant availability. The LECES project focused on studies concerning three different sites in order to evaluate predictive emission monitoring systems using neural networks to replace conventional instrumental and controls in steelworks' combustion systems. VAI developed a software template for pollution control expert systems to demonstrate the transferability of AI/EX technology. This has been done through the development of a validated process database containing data from the Corus sub-project and the subsequent integration of this data with dynamic emission models to produce rules for input to an evaluation database. CSM developed a fuzzy logic controlled process management system applied to the biological treatment of coke-oven waste water. A pilot plant has been installed and results on simulations performed using the fuzzy logic system linked to a neural network simulator show that it is possible to obtain great advantages in the biological pilot plant performance.

  1. Prediction of pork loin quality using online computer vision system and artificial intelligence model.

    Science.gov (United States)

    Sun, Xin; Young, Jennifer; Liu, Jeng-Hung; Newman, David

    2018-06-01

    The objective of this project was to develop a computer vision system (CVS) for objective measurement of pork loin under industry speed requirement. Color images of pork loin samples were acquired using a CVS. Subjective color and marbling scores were determined according to the National Pork Board standards by a trained evaluator. Instrument color measurement and crude fat percentage were used as control measurements. Image features (18 color features; 1 marbling feature; 88 texture features) were extracted from whole pork loin color images. Artificial intelligence prediction model (support vector machine) was established for pork color and marbling quality grades. The results showed that CVS with support vector machine modeling reached the highest prediction accuracy of 92.5% for measured pork color score and 75.0% for measured pork marbling score. This research shows that the proposed artificial intelligence prediction model with CVS can provide an effective tool for predicting color and marbling in the pork industry at online speeds. Copyright © 2018 Elsevier Ltd. All rights reserved.

  2. Implementing artificial neural networks in nuclear power plants diagnostic systems: issues and challenges

    International Nuclear Information System (INIS)

    Boger, Z.

    1998-01-01

    A recent review of artificial intelligence applications in nuclear power plants (NPP) diagnostics and fault detection finds that mostly expert systems (ES) and artificial neural networks (ANN) techniques were researched and proposed, but the number of actual implementations in NPP diagnostics systems is very small. It lists the perceived obstacles to the ANN-based system acceptance and implementation. This paper analyses this list. Some of ANN limitations relate to 'quantitative' difficulties of designing and training large-scale ANNs. The availability of an efficient large-scale ANN training algorithm may alleviate most of these concerns. Other perceived drawbacks refer to the 'qualitative' aspects of ANN acceptance - how and when can we rely on the quality of the advice given by the ANN model. Several techniques are available that help to brighten the 'black box' image of the ANN. Analysis of the trained ANN can identify the significant inputs. Calculation of the Causal Indices may reveal the magnitude and sign of the influence of each input on each output. Both these techniques increase the confidence of the users when they conform to known knowledge, or point to plausible relationships. Analysis of the behavior of the neurons in the hidden layer can identify false ANN classification when presented with noisy or corrupt data. Auto-associative NN can identify faulty sensors or data. Two examples of the ANN capabilities as possible diagnostic tools are given, using NPP data, one classifying internal reactor disturbances by neutron noise spectra analysis, the other identifying the faults causes of several transients. To use these techniques the ANN developers need large amount of training data of as many transients as possible. Such data is routinely generated in NPP simulators during the periodic qualification of NPP operators. The IAEA can help by encouraging the saving and distributing the transient data to developers of ANN diagnostic system, to serve as

  3. A bio-inspired real-time capable artificial lateral line system for freestream flow measurements.

    Science.gov (United States)

    Abels, C; Qualtieri, A; De Vittorio, M; Megill, W M; Rizzi, F

    2016-06-03

    To enhance today's artificial flow sensing capabilities in aerial and underwater robotics, future robots could be equipped with a large number of miniaturized sensors distributed over the surface to provide high resolution measurement of the surrounding fluid flow. In this work we show a linear array of closely separated bio-inspired micro-electro-mechanical flow sensors whose sensing mechanism is based on a piezoresistive strain-gauge along a stress-driven cantilever beam, mimicking the biological superficial neuromasts found in the lateral line organ of fishes. Aiming to improve state-of-the-art flow sensing capability in autonomously flying and swimming robots, our artificial lateral line system was designed and developed to feature multi-parameter freestream flow measurements which provide information about (1) local flow velocities as measured by the signal amplitudes from the individual cantilevers as well as (2) propagation velocity, (3) linear forward/backward direction along the cantilever beam orientation and (4) periodicity of pulses or pulse trains determined by cross-correlating sensor signals. A real-time capable cross-correlation procedure was developed which makes it possible to extract freestream flow direction and velocity information from flow fluctuations. The computed flow velocities deviate from a commercial system by 0.09 m s(-1) at 0.5 m s(-1) and 0.15 m s(-1) at 1.0 m s(-1) flow velocity for a sampling rate of 240 Hz and a sensor distance of 38 mm. Although experiments were performed in air, the presented flow sensing system can be applied to underwater vehicles as well, once the sensors are embedded in a waterproof micro-electro-mechanical systems package.

  4. Artificial heart system thermal converter and blood pump component research and development

    International Nuclear Information System (INIS)

    Pouchot, W.D.; Bifano, N.J.; Hanson, J.P.

    1975-01-01

    A bench model version of a nuclear-powered artificial heart system to be used as a replacement for the natural heart was constructed and tested as a part of a broader U. S. ERDA program. The objective of the broader program has been to develop a prototype of a fully implantable nuclear-powered total artificial heart system powered by the thermal energy of plutonium-238 and having minimum weight and volume and a minimum life of ten years. As a forward step in this broader program, component research and development has been carried out directed towards a fully implantable and advanced version of the bench model (IVBM). Some of the results of the component research and development effort on a Stirling engine, blood pump drive mechanisms, and coupling mechanisms are presented. The Stirling-mechanical system under development is shown. There are three major subassemblies: the thermal converter, the coupling mechanism, and the blood pump drive mechanism. The thermal converter uses a Stirling cycle to convert the heat of the plutonium-238 fueled heat source to a rotary shaft power output. The coupling mechanism changes the orientation of the output shaft by 90 degrees and transmits the pumping power by wire-wound core flexible shafting to the pumping mechanism. The coupling mechanism also provides routing of the coolant lines which carry the cycle waste heat from the thermal converter to the blood pump. The change in orientation of the thermal converter output shaft is for convenience in implanting in a calf. This orientation of thermal converter to blood pump seemed to give the best overall system fit in a calf based on fit trials with wooden models in a calf cadaver

  5. DEVELOPMENT OF A COMPUTER SYSTEM FOR IDENTITY AUTHENTICATION USING ARTIFICIAL NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Timur Kartbayev

    2017-03-01

    Full Text Available The aim of the study is to increase the effectiveness of automated face recognition to authenticate identity, considering features of change of the face parameters over time. The improvement of the recognition accuracy, as well as consideration of the features of temporal changes in a human face can be based on the methodology of artificial neural networks. Hybrid neural networks, combining the advantages of classical neural networks and fuzzy logic systems, allow using the network learnability along with the explanation of the findings. The structural scheme of intelligent system for identification based on artificial neural networks is proposed in this work. It realizes the principles of digital information processing and identity recognition taking into account the forecast of key characteristics’ changes over time (e.g., due to aging. The structural scheme has a three-tier architecture and implements preliminary processing, recognition and identification of images obtained as a result of monitoring. On the basis of expert knowledge, the fuzzy base of products is designed. It allows assessing possible changes in key characteristics, used to authenticate identity based on the image. To take this possibility into consideration, a neuro-fuzzy network of ANFIS type was used, which implements the algorithm of Tagaki-Sugeno. The conducted experiments showed high efficiency of the developed neural network and a low value of learning errors, which allows recommending this approach for practical implementation. Application of the developed system of fuzzy production rules that allow predicting changes in individuals over time, will improve the recognition accuracy, reduce the number of authentication failures and improve the efficiency of information processing and decision-making in applications, such as authentication of bank customers, users of mobile applications, or in video monitoring systems of sensitive sites.

  6. Production of bioplastics and hydrogen gas by photosynthetic microorganisms

    Science.gov (United States)

    Yasuo, Asada; Masato, Miyake; Jun, Miyake

    1998-03-01

    Our efforts have been aimed at the technological basis of photosynthetic-microbial production of materials and an energy carrier. We report here accumulation of poly-(3-hydroxybutyrate) (PHB), a raw material of biodegradable plastics and for production of hydrogen gas, and a renewable energy carrier by photosynthetic microorganisms (tentatively defined as cyanobacteria plus photosynthetic bateria, in this report). A thermophilic cyanobacterium, Synechococcus sp. MA19 that accumulates PHB at more than 20% of cell dry wt under nitrogen-starved conditions was isolated and microbiologically identified. The mechanism of PHB accumulation was studied. A mesophilic Synechococcus PCC7942 was transformed with the genes encoding PHB-synthesizing enzymes from Alcaligenes eutrophus. The transformant accumulated PHB under nitrogen-starved conditions. The optimal conditions for PHB accumulation by a photosynthetic bacterium grown on acetate were studied. Hydrogen production by photosynthetic microorganisms was studied. Cyanobacteria can produce hydrogen gas by nitrogenase or hydrogenase. Hydrogen production mediated by native hydrogenase in cyanobacteria was revealed to be in the dark anaerobic degradation of intracellular glycogen. A new system for light-dependent hydrogen production was targeted. In vitro and in vivo coupling of cyanobacterial ferredoxin with a heterologous hydrogenase was shown to produce hydrogen under light conditions. A trial for genetic trasformation of Synechococcus PCC7942 with the hydrogenase gene from Clostridium pasteurianum is going on. The strong hydrogen producers among photosynthetic bacteria were isolated and characterized. Co-culture of Rhodobacter and Clostriumdium was applied to produce hydrogen from glucose. Conversely in the case of cyanobacteria, genetic regulation of photosynthetic proteins was intended to improve conversion efficiency in hydrogen production by the photosynthetic bacterium, Rhodobacter sphaeroides RV. A mutant acquired by

  7. Integration of artificial intelligence systems for nuclear power plant surveillance and diagnostics

    International Nuclear Information System (INIS)

    Uhrig, R.E.; Hines, J.W.; Nelson, W.R.

    1998-01-01

    The objective of this program is to design, construct, operate, test, and evaluate a prototype integrated monitoring and diagnostic system for a nuclear power plant. It is anticipated that this technology will have wide application to other complex systems (e.g., fossil power plants, chemical processing plants, and possibly air traffic control systems). Over the past decade, the University of Tennessee (UT) and others have carried out many projects utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems, and genetic algorithms) to enhance the performance (safety, efficiency, reliability, and availability) of nuclear power plants. Investigations and studies have included a) instrumentation surveillance and calibration validation, b) inferential sensing to calibration of feedwater venturi flow during fouling, c) thermodynamic performance modeling with iterative improvement of plant beat rate, d) diagnosis of nuclear power plant transients, and e) increase in thermal power through monitoring of DNBR (Departure from Nucleate Boiling Regime). To increase the likelihood of these individual systems being used in a nuclear power plant, they must be integrated into a single system that operates virtually autonomously, collecting, interpreting, and providing information to the operators in a simple and understandable format. (author)

  8. Integration of artificial intelligence systems for nuclear power plant surveillance and diagnostics

    Energy Technology Data Exchange (ETDEWEB)

    Uhrig, R.E.; Hines, J.W.; Nelson, W.R.

    1998-07-01

    The objective of this program is to design, construct, operate, test, and evaluate a prototype integrated monitoring and diagnostic system for a nuclear power plant. It is anticipated that this technology will have wide application to other complex systems (e.g., fossil power plants, chemical processing plants, and possibly air traffic control systems). Over the past decade, the University of Tennessee (UT) and others have carried out many projects utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems, and genetic algorithms) to enhance the performance (safety, efficiency, reliability, and availability) of nuclear power plants. Investigations and studies have included a) instrumentation surveillance and calibration validation, b) inferential sensing to calibration of feedwater venturi flow during fouling, c) thermodynamic performance modeling with iterative improvement of plant beat rate, d) diagnosis of nuclear power plant transients, and e) increase in thermal power through monitoring of DNBR (Departure from Nucleate Boiling Regime). To increase the likelihood of these individual systems being used in a nuclear power plant, they must be integrated into a single system that operates virtually autonomously, collecting, interpreting, and providing information to the operators in a simple and understandable format. (author)

  9. Blood glucose monitoring during aerobic and anaerobic physical exercise using a new artificial pancreas system.

    Science.gov (United States)

    Quirós, Carmen; Bertachi, Arthur; Giménez, Marga; Biagi, Lyvia; Viaplana, Judith; Viñals, Clara; Vehí, Josep; Conget, Ignacio; Bondia, Jorge

    To assess an artificial pancreas system during aerobic (AeE) and anaerobic exercise (AnE). A pilot clinical trial on five subjects with type 1 diabetes (4 males) aged 37±10.9 years, diabetes diagnosed 21.2±12.2 years before, insulin pump users, and with a mean HbA 1c level of 7.8±0.5%. Every subject did three AeE and three AnE sessions. Blood glucose levels were monitored by the artificial pancreas system during exercise and up to four hours later. Before the start of exercise, 23g of carbohydrates were administered orally. The mean glucose level was 124.0±25.1mg/dL in the AeE studies and 152.1±34.1mg/dL in the AnE studies. Percent times in the different glucose ranges of 70-180, >180 and 18.6% and 75.9±27.6%; 7.7±18.4% and 23.2±28.0%; and 2.5±6.3% and 1.0±3.6% during the AeE and AnE sessions, respectively. Only six rescues with carbohydrates (15g) were required during the studies (4 in AeE and 2 in AnE). Total insulin dose during the five hours of the study was 3.1±1.0IU in the AeE studies and 3.5±1.3IU in the AnE studies. Blood glucose response to AeE and AnE exercise is different. The evaluated artificial pancreas system appeared to achieve effective and safe blood glucose control during exercise and up to four hours later. However, new control strategies that minimize patient intervention should be designed. Copyright © 2018 SEEN y SED. Publicado por Elsevier España, S.L.U. All rights reserved.

  10. Automatic learning algorithm for the MD-logic artificial pancreas system.

    Science.gov (United States)

    Miller, Shahar; Nimri, Revital; Atlas, Eran; Grunberg, Eli A; Phillip, Moshe

    2011-10-01

    Applying real-time learning into an artificial pancreas system could effectively track the unpredictable behavior of glucose-insulin dynamics and adjust insulin treatment accordingly. We describe a novel learning algorithm and its performance when integrated into the MD-Logic Artificial Pancreas (MDLAP) system developed by the Diabetes Technology Center, Schneider Children's Medical Center of Israel, Petah Tikva, Israel. The algorithm was designed to establish an initial patient profile using open-loop data (Initial Learning Algorithm component) and then make periodic adjustments during closed-loop operation (Runtime Learning Algorithm component). The MDLAP system, integrated with the learning algorithm, was tested in seven different experiments using the University of Virginia/Padova simulator, comprising adults, adolescents, and children. The experiments included simulations using the open-loop and closed-loop control strategy under nominal and varying insulin sensitivity conditions. The learning algorithm was automatically activated at the end of the open-loop segment and after every day of the closed-loop operation. Metabolic control parameters achieved at selected time points were compared. The percentage of time glucose levels were maintained within 70-180 mg/dL for children and adolescents significantly improved when open-loop was compared with day 6 of closed-loop control (Psignificantly reduced by approximately sevenfold (Psignificant reduction in the Low Blood Glucose Index (P<0.001). The new algorithm was effective in characterizing the patient profiles from open-loop data and in adjusting treatment to provide better glycemic control during closed-loop control in both conditions. These findings warrant corroboratory clinical trials.

  11. Use of Wearable Sensors and Biometric Variables in an Artificial Pancreas System

    Science.gov (United States)

    Turksoy, Kamuran; Monforti, Colleen; Park, Minsun; Griffith, Garett; Quinn, Laurie; Cinar, Ali

    2017-01-01

    An artificial pancreas (AP) computes the optimal insulin dose to be infused through an insulin pump in people with Type 1 Diabetes (T1D) based on information received from a continuous glucose monitoring (CGM) sensor. It has been recognized that exercise is a major challenge in the development of an AP system. The use of biometric physiological variables in an AP system may be beneficial for prevention of exercise-induced challenges and better glucose regulation. The goal of the present study is to find a correlation between biometric variables such as heart rate (HR), heat flux (HF), skin temperature (ST), near-body temperature (NBT), galvanic skin response (GSR), and energy expenditure (EE), 2D acceleration-mean of absolute difference (MAD) and changes in glucose concentrations during exercise via partial least squares (PLS) regression and variable importance in projection (VIP) in order to determine which variables would be most useful to include in a future artificial pancreas. PLS and VIP analyses were performed on data sets that included seven different types of exercises. Data were collected from 26 clinical experiments. Clinical results indicate ST to be the most consistently important (important for six out of seven tested exercises) variable over all different exercises tested. EE and HR are also found to be important variables over several types of exercise. We also found that the importance of GSR and NBT observed in our experiments might be related to stress and the effect of changes in environmental temperature on glucose concentrations. The use of the biometric measurements in an AP system may provide better control of glucose concentration. PMID:28272368

  12. International Conference on Artificial Immune Systems (1st) ICARIS 2002, held on 9, 10, and 11 September 2002

    Science.gov (United States)

    2002-03-07

    now become the dominating theme for a number of new proteomics technologies. Based on this principle, two main systems are currently used for analysis...bactaerium, fungus or other parasite. For an artificial immune system a complete data item represents a pathogen. ii) Antigen: a real antigen is a

  13. Artificial Pancreas Device Systems for the Closed-Loop Control of Type 1 Diabetes

    Science.gov (United States)

    Trevitt, Sara; Simpson, Sue; Wood, Annette

    2015-01-01

    Background: Closed-loop artificial pancreas device (APD) systems are externally worn medical devices that are being developed to enable people with type 1 diabetes to regulate their blood glucose levels in a more automated way. The innovative concept of this emerging technology is that hands-free, continuous, glycemic control can be achieved by using digital communication technology and advanced computer algorithms. Methods: A horizon scanning review of this field was conducted using online sources of intelligence to identify systems in development. The systems were classified into subtypes according to their level of automation, the hormonal and glycemic control approaches used, and their research setting. Results: Eighteen closed-loop APD systems were identified. All were being tested in clinical trials prior to potential commercialization. Six were being studied in the home setting, 5 in outpatient settings, and 7 in inpatient settings. It is estimated that 2 systems may become commercially available in the EU by the end of 2016, 1 during 2017, and 2 more in 2018. Conclusions: There are around 18 closed-loop APD systems progressing through early stages of clinical development. Only a few of these are currently in phase 3 trials and in settings that replicate real life. PMID:26589628

  14. Artificial neural network analysis of a refrigeration system with an evaporative condenser

    Energy Technology Data Exchange (ETDEWEB)

    Ertunc, H.M. [Department of Mechatronics Engineering, Kocaeli University, 41040 Kocaeli (Turkey); Hosoz, M. [Department of Mechanical Education, Kocaeli University, 41380 Kocaeli (Turkey)

    2006-04-01

    This paper describes an application of artificial neural networks (ANNs) to predict the performance of a refrigeration system with an evaporative condenser. In order to gather data for training and testing the proposed ANN, an experimental refrigeration system with an evaporative condenser was set up. Then, steady-state test runs were conducted varying the evaporator load, air and water flow rates passing through the condenser and both dry and wet bulb temperatures of the air stream entering the condenser. Utilizing some of the experimental data, an ANN model for the system based on standard backpropagation algorithm was developed. The ANN was used for predicting various performance parameters of the system, namely the condenser heat rejection rate, refrigerant mass flow rate, compressor power, electric power input to the compressor motor and the coefficient of performance. The ANN predictions usually agree well with the experimental values with correlation coefficients in the range of 0.933-1.000, mean relative errors in the range of 1.90-4.18% and very low root mean square errors. Results show that refrigeration systems, even complex ones involving concurrent heat and mass transfer such as systems with an evaporative condenser, can alternatively be modelled using ANNs within a high degree of accuracy. [Author].

  15. Real-time operation guide system for sintering process with artificial intelligence

    Institute of Scientific and Technical Information of China (English)

    FAN Xiao-hui; CHEN Xu-ling; JIANG Tao; LI Tao

    2005-01-01

    In order to optimize the sintering process, a real-time operation guide system with artificial intelligence was developed, mainly including the data acquisition online subsystem, the sinter chemical composition controller, the sintering process state controller, and the abnormal conditions diagnosis subsystem. Knowledge base of the sintering process controlling was constructed, and inference engine of the system was established. Sinter chemical compositions were controlled by the strategies of self-adaptive prediction, internal optimization and center on basicity. And the state of sintering was stabilized centering on permeability. In order to meet the needs of process change and make the system clear, the system has learning ability and explanation function. The software of the system was developed in Visual C++ programming language. The application of the system shows that the hitting accuracy of sinter compositions and burning through point prediction are more than 85%; the first-grade rate of sinter chemical composition, stability rate of burning through point and stability rate of sintering process are increased by 3%, 9% and 4%, respectively.

  16. Artificial Intelligence in Public Health Prevention of Legionelosis in Drinking Water Systems

    Directory of Open Access Journals (Sweden)

    Peter Sinčak

    2014-08-01

    Full Text Available Good quality water supplies and safe sanitation in urban areas are a big challenge for governments throughout the world. Providing adequate water quality is a basic requirement for our lives. The colony forming units of the bacterium Legionella pneumophila in potable water represent a big problem which cannot be overlooked for health protection reasons. We analysed several methods to program a virtual hot water tank with AI (artificial intelligence tools including neuro-fuzzy systems as a precaution against legionelosis. The main goal of this paper is to present research which simulates the temperature profile in the water tank. This research presents a tool for a water management system to simulate conditions which are able to prevent legionelosis outbreaks in a water system. The challenge is to create a virtual water tank simulator including the water environment which can simulate a situation which is common in building water distribution systems. The key feature of the presented system is its adaptation to any hot water tank. While respecting the basic parameters of hot water, a water supplier and building maintainer are required to ensure the predefined quality and water temperature at each sampling site and avoid the growth of Legionella. The presented system is one small contribution how to overcome a situation when legionelosis could find good conditions to spread and jeopardize human lives.

  17. Artificial neural networks and adaptive neuro-fuzzy assessments for ground-coupled heat pump system

    Energy Technology Data Exchange (ETDEWEB)

    Esen, Hikmet; Esen, Mehmet [Department of Mechanical Education, Faculty of Technical Education, Firat University, 23119 Elazig (Turkey); Inalli, Mustafa [Department of Mechanical Engineering, Faculty of Engineering, Firat University, 23279 Elazig (Turkey); Sengur, Abdulkadir [Department of Electronic and Computer Science, Faculty of Technical Education, Firat University, 23119 Elazig (Turkey)

    2008-07-01

    This article present a comparison of artificial neural network (ANN) and adaptive neuro-fuzzy inference systems (ANFIS) applied for modelling a ground-coupled heat pump system (GCHP). The aim of this study is predicting system performance related to ground and air (condenser inlet and outlet) temperatures by using desired models. Performance forecasting is the precondition for the optimal design and energy-saving operation of air-conditioning systems. So obtained models will help the system designer to realize this precondition. The most suitable algorithm and neuron number in the hidden layer are found as Levenberg-Marquardt (LM) with seven neurons for ANN model whereas the most suitable membership function and number of membership functions are found as Gauss and two, respectively, for ANFIS model. The root-mean squared (RMS) value and the coefficient of variation in percent (cov) value are 0.0047 and 0.1363, respectively. The absolute fraction of variance (R{sup 2}) is 0.9999 which can be considered as very promising. This paper shows the appropriateness of ANFIS for the quantitative modeling of GCHP systems. (author)

  18. Artificial intelligence in public health prevention of legionelosis in drinking water systems.

    Science.gov (United States)

    Sinčak, Peter; Ondo, Jaroslav; Kaposztasova, Daniela; Virčikova, Maria; Vranayova, Zuzana; Sabol, Jakub

    2014-08-21

    Good quality water supplies and safe sanitation in urban areas are a big challenge for governments throughout the world. Providing adequate water quality is a basic requirement for our lives. The colony forming units of the bacterium Legionella pneumophila in potable water represent a big problem which cannot be overlooked for health protection reasons. We analysed several methods to program a virtual hot water tank with AI (artificial intelligence) tools including neuro-fuzzy systems as a precaution against legionelosis. The main goal of this paper is to present research which simulates the temperature profile in the water tank. This research presents a tool for a water management system to simulate conditions which are able to prevent legionelosis outbreaks in a water system. The challenge is to create a virtual water tank simulator including the water environment which can simulate a situation which is common in building water distribution systems. The key feature of the presented system is its adaptation to any hot water tank. While respecting the basic parameters of hot water, a water supplier and building maintainer are required to ensure the predefined quality and water temperature at each sampling site and avoid the growth of Legionella. The presented system is one small contribution how to overcome a situation when legionelosis could find good conditions to spread and jeopardize human lives.

  19. Artificial Intelligence in Public Health Prevention of Legionelosis in Drinking Water Systems

    Science.gov (United States)

    Sinčak, Peter; Ondo, Jaroslav; Kaposztasova, Daniela; Virčikova, Maria; Vranayova, Zuzana; Sabol, Jakub

    2014-01-01

    Good quality water supplies and safe sanitation in urban areas are a big challenge for governments throughout the world. Providing adequate water quality is a basic requirement for our lives. The colony forming units of the bacterium Legionella pneumophila in potable water represent a big problem which cannot be overlooked for health protection reasons. We analysed several methods to program a virtual hot water tank with AI (artificial intelligence) tools including neuro-fuzzy systems as a precaution against legionelosis. The main goal of this paper is to present research which simulates the temperature profile in the water tank. This research presents a tool for a water management system to simulate conditions which are able to prevent legionelosis outbreaks in a water system. The challenge is to create a virtual water tank simulator including the water environment which can simulate a situation which is common in building water distribution systems. The key feature of the presented system is its adaptation to any hot water tank. While respecting the basic parameters of hot water, a water supplier and building maintainer are required to ensure the predefined quality and water temperature at each sampling site and avoid the growth of Legionella. The presented system is one small contribution how to overcome a situation when legionelosis could find good conditions to spread and jeopardize human lives. PMID:25153475

  20. Toward a multipoint optical fibre sensor system for use in process water systems based on artificial neural network pattern recognition

    International Nuclear Information System (INIS)

    King, D; Lyons, W B; Flanagan, C; Lewis, E

    2005-01-01

    An optical fibre sensor capable of detecting various concentrations of ethanol in water supplies is reported. The sensor is based on a U-bend sensor configuration and is incorporated into a 170-metre length of silica cladding silica core optical fibre. The sensor is interrogated using Optical Time Domain Reflectometry (OTDR) and it is proposed to apply artificial neural network (ANN) pattern recognition techniques to the resulting OTDR signals to accurately classify the sensor test conditions. It is also proposed that additional U-bend configuration sensors will be added to the fibre measurement length, in order to implement a multipoint optical fibre sensor system

  1. Artificial liver support with the molecular adsorbent recirculating system: activation of coagulation and bleeding complications.

    Science.gov (United States)

    Bachli, Esther B; Schuepbach, Reto A; Maggiorini, Marco; Stocker, Reto; Müllhaupt, Beat; Renner, Eberhard L

    2007-05-01

    Numerous, mostly uncontrolled, observations suggest that artificial liver support with the Molecular Adsorbent Recirculating System (MARS) improves pathophysiologic sequelae and outcome of acute and acute-on-chronic liver failure. MARS is felt to be safe, but extracorporeal circuits may activate coagulation. To assess the frequency of and risk factors for activation of coagulation during MARS treatment. Retrospective analysis of coagulopathy/bleeding complications observed during 83 consecutive MARS sessions in 21 patients (11 men; median age 46 years; median three sessions per patient; median duration of session 8 h). Nine clinically relevant episodes of coagulopathy/bleeding were observed in eight patients, forced to premature cessation of MARS in seven and ended lethal in four. Four complications occurred during the first, five during later (third to seventh) MARS sessions and two bleeders tolerated further sessions without complications. Coagulation parameters worsened significantly also during MARS sessions not associated with bleeding (PMARS therapy, potentially leading to bleeding complications and mortality.

  2. Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS): A conceptual framework

    Science.gov (United States)

    Parnell, Gregory S.; Rowell, William F.; Valusek, John R.

    1987-01-01

    In recent years there has been increasing interest in applying the computer based problem solving techniques of Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS) to analyze extremely complex problems. A conceptual framework is developed for successfully integrating these three techniques. First, the fields of AI, OR, and DSS are defined and the relationships among the three fields are explored. Next, a comprehensive adaptive design methodology for AI and OR modeling within the context of a DSS is described. These observations are made: (1) the solution of extremely complex knowledge problems with ill-defined, changing requirements can benefit greatly from the use of the adaptive design process, (2) the field of DSS provides the focus on the decision making process essential for tailoring solutions to these complex problems, (3) the characteristics of AI, OR, and DSS tools appears to be converging rapidly, and (4) there is a growing need for an interdisciplinary AI/OR/DSS education.

  3. Research on Flow Field Perception Based on Artificial Lateral Line Sensor System

    Directory of Open Access Journals (Sweden)

    Guijie Liu

    2018-03-01

    Full Text Available In nature, the lateral line of fish is a peculiar and important organ for sensing the surrounding hydrodynamic environment, preying, escaping from predators and schooling. In this paper, by imitating the mechanism of fish lateral canal neuromasts, we developed an artificial lateral line system composed of micro-pressure sensors. Through hydrodynamic simulations, an optimized sensor structure was obtained and the pressure distribution models of the lateral surface were established in uniform flow and turbulent flow. Carrying out the corresponding underwater experiment, the validity of the numerical simulation method is verified by the comparison between the experimental data and the simulation results. In addition, a variety of effective research methods are proposed and validated for the flow velocity estimation and attitude perception in turbulent flow, respectively and the shape recognition of obstacles is realized by the neural network algorithm.

  4. A survey on the design of multiprocessing systems for artificial intelligence applications

    Science.gov (United States)

    Wah, Benjamin W.; Li, Guo Jie

    1989-01-01

    Some issues in designing computers for artificial intelligence (AI) processing are discussed. These issues are divided into three levels: the representation level, the control level, and the processor level. The representation level deals with the knowledge and methods used to solve the problem and the means to represent it. The control level is concerned with the detection of dependencies and parallelism in the algorithmic and program representations of the problem, and with the synchronization and sheduling of concurrent tasks. The processor level addresses the hardware and architectural components needed to evaluate the algorithmic and program representations. Solutions for the problems of each level are illustrated by a number of representative systems. Design decisions in existing projects on AI computers are classed into top-down, bottom-up, and middle-out approaches.

  5. Hemostasis system in patients with pulmonary cancer during multimodality treatment with the use of artificial hyperglycemia

    International Nuclear Information System (INIS)

    Demidchik, Yu.E.; Zharkov, V.V.; Antipova, L.I.; Kurchin, V.P.; Moiseev, P.I.

    1990-01-01

    The main hemostasis indices at all stages of combined treatment of 105 patients with pulmonary cancer, involving radiotherapy artificial hyperglycemia and surgical intervention, are estimated. The functional status of the hemostasis system was estimated on the basis of a complex of hemocoagulation tests. All patients were subjected to preoperative remote large-fractioned irradiation with 20 Gy total absorbed dose in 5 fractions of 4 Gy in a week. It is established that at the irradiation stage of combined treatment hyperglycemia leads to hyper coagulation and increases the risk of thromboembolic complications. For prophylaxis of the complications it is reasonable to combine low doses of heparin and preparations, improving blood rheology either before or after surgical intervention. 7 refs.; 2 tabs

  6. Gapped sequence alignment using artificial neural networks: application to the MHC class I system

    DEFF Research Database (Denmark)

    Andreatta, Massimo; Nielsen, Morten

    2016-01-01

    . On this relatively simple system, we developed a sequence alignment method based on artificial neural networks that allows insertions and deletions in the alignment. Results: We show that prediction methods based on alignments that include insertions and deletions have significantly higher performance than methods...... trained on peptides of single lengths. Also, we illustrate how the location of deletions can aid the interpretation of the modes of binding of the peptide-MHC, as in the case of long peptides bulging out of the MHC groove or protruding at either terminus. Finally, we demonstrate that the method can learn...... the length profile of different MHC molecules, and quantified the reduction of the experimental effort required to identify potential epitopes using our prediction algorithm. Availability and implementation: The NetMHC-4.0 method for the prediction of peptide-MHC class I binding affinity using gapped...

  7. Beyond AI: Multi-Intelligence (MI Combining Natural and Artificial Intelligences in Hybrid Beings and Systems

    Directory of Open Access Journals (Sweden)

    Stephen Fox

    2017-06-01

    Full Text Available Framing strongly influences actions among technology proponents and end-users. Underlying much debate about artificial intelligence (AI are several fundamental shortcomings in its framing. First, discussion of AI is atheoretical, and therefore has limited potential for addressing the complexity of causation. Second, intelligence is considered from an anthropocentric perspective that sees human intelligence, and intelligence developed by humans, as superior to all other intelligences. Thus, the extensive post-anthropocentric research into intelligence is not given sufficient consideration. Third, AI is discussed often in reductionist mechanistic terms. Rather than in organicist emergentist terms as a contributor to multi-intelligence (MI hybrid beings and/or systems. Thus, current framing of AI can be a self-validating reduction within which AI development is focused upon AI becoming the single-variable mechanism causing future effects. In this paper, AI is reframed as a contributor to MI.

  8. A New Artificial Immune System Algorithm for Multiobjective Fuzzy Flow Shop Problems

    Directory of Open Access Journals (Sweden)

    Cengiz Kahraman

    2009-12-01

    Full Text Available In this paper a new artificial immune system (AIS algorithm is proposed to solve multi objective fuzzy flow shop scheduling problems. A new mutation operator is also described for this AIS. Fuzzy sets are used to model processing times and due dates. The objectives are to minimize the average tardiness and the number of tardy jobs. The developed new AIS algorithm is tested on real world data collected at an engine cylinder liner manufacturing process. The feasibility and effectiveness of the proposed AIS is demonstrated by comparing it with genetic algorithms. Computational results demonstrate that the proposed AIS algorithm is more effective meta-heuristic for multi objective flow shop scheduling problems with fuzzy processing time and due date.

  9. Fault detection and classification in electrical power transmission system using artificial neural network.

    Science.gov (United States)

    Jamil, Majid; Sharma, Sanjeev Kumar; Singh, Rajveer

    2015-01-01

    This paper focuses on the detection and classification of the faults on electrical power transmission line using artificial neural networks. The three phase currents and voltages of one end are taken as inputs in the proposed scheme. The feed forward neural network along with back propagation algorithm has been employed for detection and classification of the fault for analysis of each of the three phases involved in the process. A detailed analysis with varying number of hidden layers has been performed to validate the choice of the neural network. The simulation results concluded that the present method based on the neural network is efficient in detecting and classifying the faults on transmission lines with satisfactory performances. The different faults are simulated with different parameters to check the versatility of the method. The proposed method can be extended to the Distribution network of the Power System. The various simulations and analysis of signals is done in the MATLAB(®) environment.

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

    International Nuclear Information System (INIS)

    Pallas, Christophe

    1987-01-01

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

  11. ANALYSIS OF THE HARMONIC LOSSES WITH ARTIFICIAL NEURAL NETWORKS IN UNBALANCED SYSTEM LOSSES USING BALANCED ELECTRIC POWER SYSTEM DATA

    Directory of Open Access Journals (Sweden)

    Aslan İNAN

    2005-01-01

    Full Text Available The losses in the power systems should be low as possible as. Saving energy instead of loses (kWh in power utilities can supply much more energy to the consumers. The lower losses the more energy is saved and thus the power system becomes more economical. In recent years, the increasing number of applications and power ratings of the devices which have nonlinear voltage-current characteristics cause voltage waveform distortion and additional losses. While evaluating losses considering harmonics will provide more contribution to obtain more accurate results. In this study, Artificial Neural Networks (ANN method has been presented to predict the harmonic losses in unbalanced power systems by using the data from balanced power system with nonlinear loads.

  12. How well do growing season dynamics of photosynthetic capacity correlate with leaf biochemistry and climate fluctuations?

    Science.gov (United States)

    Way, Danielle A; Stinziano, Joseph R; Berghoff, Henry; Oren, Ram

    2017-07-01

    Accurate values of photosynthetic capacity are needed in Earth System Models to predict gross primary productivity. Seasonal changes in photosynthetic capacity in these models are primarily driven by temperature, but recent work has suggested that photoperiod may be a better predictor of seasonal photosynthetic capacity. Using field-grown kudzu (Pueraria lobata (Willd.) Ohwi), a nitrogen-fixing vine species, we took weekly measurements of photosynthetic capacity, leaf nitrogen, and pigment and photosynthetic protein concentrations and correlated these with temperature, irradiance and photoperiod over the growing season. Photosynthetic capacity was more strongly correlated with photoperiod than with temperature or daily irradiance, while the growing season pattern in photosynthetic capacity was uncoupled from changes in leaf nitrogen, chlorophyll and Rubisco. Daily estimates of the maximum carboxylation rate of Rubisco (Vcmax) based on either photoperiod or temperature were correlated in a non-linear manner, but Vcmax estimates from both approaches that also accounted for diurnal temperature fluctuations were similar, indicating that differences between these models depend on the relevant time step. We advocate for considering photoperiod, and not just temperature, when estimating photosynthetic capacity across the year, particularly as climate change alters temperatures but not photoperiod. We also caution that the use of leaf biochemical traits as proxies for estimating photosynthetic capacity may be unreliable when the underlying relationships between proxy leaf traits and photosynthetic capacity are established outside of a seasonal framework. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  13. Establishment of extracorporeal circulation of artificial liver support system in high altitude region

    Directory of Open Access Journals (Sweden)

    Ming-sen ZHANG

    2011-01-01

    Full Text Available Objective To establish extracorporeal circulation in big animal suitable for the research on artificial liver support system in high altitude region.Methods Under the anesthesia of ketamine hydrochloride/diazepam IV,cannulation of common carotid artery/external jugular vein(n=3 and inferior vena cava via the left external jugular vein/right external jugular vein(n=3,was respectively performed on six healthy Chang-Bai piglets adapted to native environment(altitude 3700m.One day after that,the extracorporeal circulation was performed at a progressively elevated blood current velocity,and the general condition of the animals,blood pressure,HR,bleeding tendoncy of the experimental pigs and coagulation in the cannulae were observed.Results On the premise that the hemodynamics was not influenced,the highest blood current velocity was 133.33±28.87ml/min,the lowest heparin maintaining speed amounted to 138.67±12.22mg/h,and the bleeding tendency and blood coagulation in the cannula was significant in the group of common carotid artery/external jugular vein intubation.While the highest blood current velocity was 400ml/min,the lowest heparin maintaining speed was 26.67±9.24mg/h,no bleeding tendency or obvious cannular blood coagulation were observed in the group of cannulation of inferior vena cava via the left external jugular vein/right external jugular vein.These untoward results were significantly less or slight than that of the former group(P < 0.01.Conclusion It is suitable to perform research of artificial liver support system on piglets in high altitude region by establishing extracorporeal circulation by the way of inferior vena cava with cannulation passing through the left external jugular vein/right external jugular vein with the blood current velocity of 400ml/min.

  14. Hybrid intelligence systems and artificial neural network (ANN approach for modeling of surface roughness in drilling

    Directory of Open Access Journals (Sweden)

    Ch. Sanjay

    2014-12-01

    Full Text Available In machining processes, drilling operation is material removal process that has been widely used in manufacturing since industrial revolution. The useful life of cutting tool and its operating conditions largely controls the economics of machining operations. Drilling is most frequently performed material removing process and is used as a preliminary step for many operations, such as reaming, tapping, and boring. Drill wear has a bad effect on the surface finish and dimensional accuracy of the work piece. The surface finish of a machined part is one of the most important quality characteristics in manufacturing industries. The primary objective of this research is the prediction of suitable parameters for surface roughness in drilling. Cutting speed, cutting force, and machining time were given as inputs to the adaptive fuzzy neural network and neuro-fuzzy analysis for estimating the values of surface roughness by using 2, 3, 4, and 5 membership functions. The best structures were selected based on minimum of summation of square with the actual values with the estimated values by artificial neural fuzzy inference system (ANFIS and neuro-fuzzy systems. For artificial neural network (ANN analysis, the number of neurons was selected from 1, 2, 3, … , 20. The learning rate was selected as .5 and .5 smoothing factor was used. The inputs were selected as cutting speed, feed, machining time, and thrust force. The best structures of neural networks were selected based on the criteria as the minimum of summation of square with the actual value of surface roughness. Drilling experiments with 10 mm size were performed at two cutting speeds and feeds. Comparative analysis has been done between the actual values and the estimated values obtained by ANFIS, neuro-fuzzy, and ANN analysis.

  15. Rescuing ethanol photosynthetic production of cyanobacteria in non-sterilized outdoor cultivations with a bicarbonate-based pH-rising strategy.

    Science.gov (United States)

    Zhu, Zhi; Luan, Guodong; Tan, Xiaoming; Zhang, Haocui; Lu, Xuefeng

    2017-01-01

    Ethanol photosynthetic production based on cyanobacteria cell factories utilizing CO 2 and solar energy provides an attractive solution for sustainable production of green fuels. However, the scaling up processes of cyanobacteria cell factories were usually threatened or even devastated by biocontaminations, which restricted biomass or products accumulations of cyanobacteria cells. Thus it is of great significance to develop reliable biocontamination-controlling strategies for promoting ethanol photosynthetic production in large scales. The scaling up process of a previously developed Synechocystis strain Syn-HZ24 for ethanol synthesis was severely inhibited and devastated by a specific contaminant, Pannonibacter phragmitetus , which overcame the growths of cyanobacteria cells and completely consumed the ethanol accumulation in the cultivation systems. Physiological analysis revealed that growths and ethanol-consuming activities of the contaminant were sensitive to alkaline conditions, while ethanol-synthesizing cyanobacteria strain Syn-HZ24 could tolerate alkaline pH conditions as high as 11.0, indicating that pH-increasing strategy might be a feasible approach for rescuing ethanol photosynthetic production in outdoor cultivation systems. Thus, we designed and evaluated a Bicarbonate-based Integrated Carbon Capture System (BICCS) derived pH-rising strategy to rescue the ethanol photosynthetic production in non-sterilized conditions. In lab scale artificially simulated systems, pH values of BG11 culture medium were maintained around 11.0 by 180 mM NaHCO 3 and air steam, under which the infection of Pannonibacter phragmitetus was significantly restricted, recovering ethanol production of Syn-HZ24 by about 80%. As for outdoor cultivations, ethanol photosynthetic production of Syn-HZ24 was also successfully rescued by the BICCS-derived pH-rising strategy, obtaining a final ethanol concentration of 0.9 g/L after 10 days cultivation. In this work, a novel product

  16. Drug release control and system understanding of sucrose esters matrix tablets by artificial neural networks.

    Science.gov (United States)

    Chansanroj, Krisanin; Petrović, Jelena; Ibrić, Svetlana; Betz, Gabriele

    2011-10-09

    Artificial neural networks (ANNs) were applied for system understanding and prediction of drug release properties from direct compacted matrix tablets using sucrose esters (SEs) as matrix-forming agents for controlled release of a highly water soluble drug, metoprolol tartrate. Complexity of the system was presented through the effects of SE concentration and tablet porosity at various hydrophilic-lipophilic balance (HLB) values of SEs ranging from 0 to 16. Both effects contributed to release behaviors especially in the system containing hydrophilic SEs where swelling phenomena occurred. A self-organizing map neural network (SOM) was applied for visualizing interrelation among the variables and multilayer perceptron neural networks (MLPs) were employed to generalize the system and predict the drug release properties based on HLB value and concentration of SEs and tablet properties, i.e., tablet porosity, volume and tensile strength. Accurate prediction was obtained after systematically optimizing network performance based on learning algorithm of MLP. Drug release was mainly attributed to the effects of SEs, tablet volume and tensile strength in multi-dimensional interrelation whereas tablet porosity gave a small impact. Ability of system generalization and accurate prediction of the drug release properties proves the validity of SOM and MLPs for the formulation modeling of direct compacted matrix tablets containing controlled release agents of different material properties. Copyright © 2011 Elsevier B.V. All rights reserved.

  17. Artificial heart development program. Volume I. System development. Phase III summary report

    Energy Technology Data Exchange (ETDEWEB)

    1977-01-01

    The report documents efforts and results in the development of the power system portions of a calf implantable model of nuclear-powered artificial heart. The primary objective in developing the implantable model was to solve the packaging problems for total system implantation. The power systems portion is physically that portion of the implantable model between the Pu-238 heat sources and the blood pump ventricles. The work performed had two parallel themes. The first of these was the development of an integrated implantable model for bench and animal experiments plus design effort on a more advanced model. The second was research and development on components of the system done in conjunction with the development of the implantable model and to provide technology for incorporation into advanced models plus support to implantations, at the University of Utah, of the systems blood pumping elements when driven by electric motor. The efforts and results of implantable model development are covered, mainly, in the text of the report. The research and development efforts and results are reported, primarily, in the appendices (Vol. 2).

  18. Artificial heart development program. Volume I. System development. Phase III summary report

    International Nuclear Information System (INIS)

    1977-01-01

    The report documents efforts and results in the development of the power system portions of a calf implantable model of nuclear-powered artificial heart. The primary objective in developing the implantable model was to solve the packaging problems for total system implantation. The power systems portion is physically that portion of the implantable model between the Pu-238 heat sources and the blood pump ventricles. The work performed had two parallel themes. The first of these was the development of an integrated implantable model for bench and animal experiments plus design effort on a more advanced model. The second was research and development on components of the system done in conjunction with the development of the implantable model and to provide technology for incorporation into advanced models plus support to implantations, at the University of Utah, of the systems blood pumping elements when driven by electric motor. The efforts and results of implantable model development are covered, mainly, in the text of the report. The research and development efforts and results are reported, primarily, in the appendices

  19. Propagating gene expression fronts in a one-dimensional coupled system of artificial cells

    Science.gov (United States)

    Tayar, Alexandra M.; Karzbrun, Eyal; Noireaux, Vincent; Bar-Ziv, Roy H.

    2015-12-01

    Living systems employ front propagation and spatiotemporal patterns encoded in biochemical reactions for communication, self-organization and computation. Emulating such dynamics in minimal systems is important for understanding physical principles in living cells and in vitro. Here, we report a one-dimensional array of DNA compartments in a silicon chip as a coupled system of artificial cells, offering the means to implement reaction-diffusion dynamics by integrated genetic circuits and chip geometry. Using a bistable circuit we programmed a front of protein synthesis propagating in the array as a cascade of signal amplification and short-range diffusion. The front velocity is maximal at a saddle-node bifurcation from a bistable regime with travelling fronts to a monostable regime that is spatially homogeneous. Near the bifurcation the system exhibits large variability between compartments, providing a possible mechanism for population diversity. This demonstrates that on-chip integrated gene circuits are dynamical systems driving spatiotemporal patterns, cellular variability and symmetry breaking.

  20. Dynamic route guidance algorithm based algorithm based on artificial immune system

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    To improve the performance of the K-shortest paths search in intelligent traffic guidance systems,this paper proposes an optimal search algorithm based on the intelligent optimization search theory and the memphor mechanism of vertebrate immune systems.This algorithm,applied to the urban traffic network model established by the node-expanding method,can expediently realize K-shortest paths search in the urban traffic guidance systems.Because of the immune memory and global parallel search ability from artificial immune systems,K shortest paths can be found without any repeat,which indicates evidently the superiority of the algorithm to the conventional ones.Not only does it perform a better parallelism,the algorithm also prevents premature phenomenon that often occurs in genetic algorithms.Thus,it is especially suitable for real-time requirement of the traffic guidance system and other engineering optimal applications.A case study verifies the efficiency and the practicability of the algorithm aforementioned.

  1. Systematically In Silico Comparison of Unihormonal and Bihormonal Artificial Pancreas Systems

    Directory of Open Access Journals (Sweden)

    Xiaoteng Gao

    2013-01-01

    Full Text Available Automated closed-loop control of blood glucose concentration is a daily challenge for type 1 diabetes mellitus, where insulin and glucagon are two critical hormones for glucose regulation. According to whether glucagon is included, all artificial pancreas (AP systems can be divided into two types: unihormonal AP (infuse only insulin and bihormonal AP (infuse both insulin and glucagon. Even though the bihormonal AP is widely considered a promising direction, related studies are very scarce due to this system’s short research history. More importantly, there are few studies to compare these two kinds of AP systems fairly and systematically. In this paper, two switching rules, P-type and PD-type, were proposed to design the logic of orchestrates switching between insulin and glucagon subsystems, where the delivery rates of both insulin and glucagon were designed by using IMC-PID method. These proposed algorithms have been compared with an optimal unihormonal system on virtual type 1 diabetic subjects. The in silico results demonstrate that the proposed bihormonal AP systems have outstanding superiorities in reducing the risk of hypoglycemia, smoothing the glucose level, and robustness with respect to insulin/glucagon sensitivity variations, compared with the optimal unihormonal AP system.

  2. Statistical uncertainty of response characteristic of building-appendage system for spectrum-compatible artificial earthquake motion

    International Nuclear Information System (INIS)

    Kurosaki, A.; Kozeki, M.

    1981-01-01

    Spectrum-compatible artificial time histories of ground motions are frequently used for the seismic design of nuclear power plant structures and components. However, statistical uncertainty of the responses of building structures and mechanical components mounted on the building (building-appendage systems) are anticipated, since an artificial time history is no more than one sample from a population of such time histories that match a specified design response spectrum. This uncertainty may spoil the reliability of the seismic design and therefore the extent of the uncertainty of the response characteristic is a matter of great concern. In this paper, above-mentioned uncertainty of the dynamic response characteristics of the building-appendage system to the spectrum-compatible artificial earthquake is investigated. (orig./RW)

  3. Evaluation of the safety and efficacy of Glycyrrhiza uralensis root extracts produced using artificial hydroponic and artificial hydroponic-field hybrid cultivation systems.

    Science.gov (United States)

    Akiyama, H; Nose, M; Ohtsuki, N; Hisaka, S; Takiguchi, H; Tada, A; Sugimoto, N; Fuchino, H; Inui, T; Kawano, N; Hayashi, S; Hishida, A; Kudo, T; Sugiyama, K; Abe, Y; Mutsuga, M; Kawahara, N; Yoshimatsu, K

    2017-01-01

    Glycyrrhiza uralensis roots used in this study were produced using novel cultivation systems, including artificial hydroponics and artificial hydroponic-field hybrid cultivation. The equivalency between G. uralensis root extracts produced by hydroponics and/or hybrid cultivation and a commercial Glycyrrhiza crude drug were evaluated for both safety and efficacy, and there were no significant differences in terms of mutagenicity on the Ames tests. The levels of cadmium and mercury in both hydroponic roots and crude drugs were less than the limit of quantitation. Arsenic levels were lower in all hydroponic roots than in the crude drug, whereas mean lead levels in the crude drug were not significantly different from those in the hydroponically cultivated G. uralensis roots. Both hydroponic and hybrid-cultivated root extracts showed antiallergic activities against contact hypersensitivity that were similar to those of the crude drug extracts. These study results suggest that hydroponic and hybrid-cultivated roots are equivalent in safety and efficacy to those of commercial crude drugs. Further studies are necessary before the roots are applicable as replacements for the currently available commercial crude drugs produced from wild plant resources.

  4. Combination of artificial intelligence and procedural language programs in a computer application system supporting nuclear reactor operations

    International Nuclear Information System (INIS)

    Stratton, R.C.; Town, G.G.

    1985-01-01

    A computer application system is described which provides nuclear reactor power plant operators with an improved decision support system. This system combines traditional computer applications such as graphics display with artifical intelligence methodologies such as reasoning and diagnosis so as to improve plant operability. This paper discusses the issues, and a solution, involved with the system integration of applications developed using traditional and artificial intelligence languages

  5. Artificial groundwater recharge as integral part of a water resources system in a humid environment

    Science.gov (United States)

    Kupfersberger, Hans; Stadler, Hermann

    2010-05-01

    In Graz, Austria, artificial groundwater recharge has been operated as an integral part of the drinking water supply system for more than thirty years. About 180 l/s of high quality water from pristine creeks (i.e. no pre-treatment necessary) are infiltrated via sand and lawn basins and infiltration trenches into two phreatic aquifers to sustain the extraction of approximately 400 l/s. The remaining third of drinking water for roughly 300.000 people is provided by a remote supply line from the East alpine karst region Hochschwab. By this threefold model the water supply system is less vulnerable to external conditions. In the early 1980's the infiltration devices were also designed as a hydraulic barrier against riverbank infiltration from the river Mur, which at that time showed seriously impaired water quality due to upstream paper mills. This resulted into high iron and manganese groundwater concentrations which lead to clogging of the pumping wells. These problems have been eliminated in the meantime due to the onsite purification of paper mill effluents and the construction of many waste water treatment plants. The recharge system has recently been thoroughly examined to optimize the operation of groundwater recharge and to provide a basis for further extension. The investigations included (i) field experiments and laboratory analyses to improve the trade off between infiltration rate and elimination capacities of the sand filter basins' top layer, (ii) numerical groundwater modelling to compute the recovery rate of the recharged water, the composition of the origin of the pumped water, emergency scenarios due to the failure of system parts, the transient capture zones of the withdrawal wells and the coordination of recharge and withdrawal and (iii) development of an online monitoring setup combined with a decision support system to guarantee reliable functioning of the entire structure. Additionally, the depreciation, maintenance and operation costs of the

  6. Special issue of photosynthetic research

    NARCIS (Netherlands)

    Okamura, M.; Wraight, C.A.; van Grondelle, R.

    2014-01-01

    This Special Issue of Photosynthesis Research honors Louis M. N. Duysens, Roderick K. Clayton, and George Feher, three pioneering researchers whose work on bacterial photosynthesis laid much of the groundwork for our understanding of the role of the reaction center in photosynthetic light energy

  7. Dynamics of a pneumatic artificial muscle actuation system driving a trailing edge flap

    Science.gov (United States)

    Woods, Benjamin K. S.; Kothera, Curt S.; Wang, Gang; Wereley, Norman M.

    2014-09-01

    This study presents a time domain dynamic model of an antagonistic pneumatic artificial muscle (PAM) driven trailing edge flap (TEF) system for next generation active helicopter rotors. Active rotor concepts are currently being widely researched in the rotorcraft community as a means to provide a significant leap forward in performance through primary aircraft control, vibration mitigation and noise reduction. Recent work has shown PAMs to be a promising candidate for active rotor actuation due to their combination of high force, large stroke, light weight, and suitable bandwidth. When arranged into biologically inspired agonist/antagonist muscle pairs they can produce bidirectional torques for effectively driving a TEF. However, there are no analytical dynamic models in the literature that can accurately capture the behavior of such systems across the broad range of frequencies required for this demanding application. This work combines mechanical, pneumatic, and aerodynamic component models into a global flap system model developed for the Bell 407 rotor system. This model can accurately predict pressure, force, and flap angle response to pneumatic control valve inputs over a range of operating frequencies from 7 to 35 Hz (1/rev to 5/rev for the Bell 407) and operating pressures from 30 to 90 psi.

  8. Dynamics of a pneumatic artificial muscle actuation system driving a trailing edge flap

    International Nuclear Information System (INIS)

    Woods, Benjamin K S; Kothera, Curt S; Wang, Gang; Wereley, Norman M

    2014-01-01

    This study presents a time domain dynamic model of an antagonistic pneumatic artificial muscle (PAM) driven trailing edge flap (TEF) system for next generation active helicopter rotors. Active rotor concepts are currently being widely researched in the rotorcraft community as a means to provide a significant leap forward in performance through primary aircraft control, vibration mitigation and noise reduction. Recent work has shown PAMs to be a promising candidate for active rotor actuation due to their combination of high force, large stroke, light weight, and suitable bandwidth. When arranged into biologically inspired agonist/antagonist muscle pairs they can produce bidirectional torques for effectively driving a TEF. However, there are no analytical dynamic models in the literature that can accurately capture the behavior of such systems across the broad range of frequencies required for this demanding application. This work combines mechanical, pneumatic, and aerodynamic component models into a global flap system model developed for the Bell 407 rotor system. This model can accurately predict pressure, force, and flap angle response to pneumatic control valve inputs over a range of operating frequencies from 7 to 35 Hz (1/rev to 5/rev for the Bell 407) and operating pressures from 30 to 90 psi. (paper)

  9. Artificial intelligent methods for thermodynamic evaluation of ammonia-water refrigeration systems

    International Nuclear Information System (INIS)

    Sencan, Arzu

    2006-01-01

    In this paper, Linear Regression and M5'Rules models within Data Mining Process and Artificial Neural Network (ANN) model for thermodynamic evaluation of ammonia-water absorption refrigeration systems was carried out. A new formulation based on ANN model is presented for the analysis of ammonia-water absorption refrigeration systems (AWRS) because the optimal result was obtained by using ANN Model. Thermodynamic analysis of the AWRS is very complex because of analytic functions used for calculating the properties of fluid couples and simulation programs. Therefore, it is extremely difficult to perform analysis of this system. COP and f are estimated depending on the temperatures of system component and concentration values. Using the weights obtained from the trained network a new formulation is presented for the calculation of the COP and f; the use of ANN is proliferating with high speed in simulation. The R 2 -values obtained when unknown data were used to the networks was 0.9996 and 0.9873 for the circulation ratio and COP respectively which is very satisfactory. The use of this new formulation, which can be employed with any programming language or spreadsheet program for the estimation of the circulation ratio and COP of AWRS, as described in this paper, may make the use of dedicated ANN software unnecessary

  10. Artificial neural networks and neuro-fuzzy inference systems as virtual sensors for hydrogen safety prediction

    Energy Technology Data Exchange (ETDEWEB)

    Karri, Vishy; Ho, Tien [School of Engineering, University of Tasmania, GPO Box 252-65, Hobart, Tasmania 7001 (Australia); Madsen, Ole [Department of Production, Aalborg University, Fibigerstraede 16, DK-9220 Aalborg (Denmark)

    2008-06-15

    Hydrogen is increasingly investigated as an alternative fuel to petroleum products in running internal combustion engines and as powering remote area power systems using generators. The safety issues related to hydrogen gas are further exasperated by expensive instrumentation required to measure the percentage of explosive limits, flow rates and production pressure. This paper investigates the use of model based virtual sensors (rather than expensive physical sensors) in connection with hydrogen production with a Hogen 20 electrolyzer system. The virtual sensors are used to predict relevant hydrogen safety parameters, such as the percentage of lower explosive limit, hydrogen pressure and hydrogen flow rate as a function of different input conditions of power supplied (voltage and current), the feed of de-ionized water and Hogen 20 electrolyzer system parameters. The virtual sensors are developed by means of the application of various Artificial Intelligent techniques. To train and appraise the neural network models as virtual sensors, the Hogen 20 electrolyzer is instrumented with necessary sensors to gather experimental data which together with MATLAB neural networks toolbox and tailor made adaptive neuro-fuzzy inference systems (ANFIS) were used as predictive tools to estimate hydrogen safety parameters. It was shown that using the neural networks hydrogen safety parameters were predicted to less than 3% of percentage average root mean square error. The most accurate prediction was achieved by using ANFIS. (author)

  11. Nonlinear estimation-based dipole source localization for artificial lateral line systems

    International Nuclear Information System (INIS)

    Abdulsadda, Ahmad T; Tan Xiaobo

    2013-01-01

    As a flow-sensing organ, the lateral line system plays an important role in various behaviors of fish. An engineering equivalent of a biological lateral line is of great interest to the navigation and control of underwater robots and vehicles. A vibrating sphere, also known as a dipole source, can emulate the rhythmic movement of fins and body appendages, and has been widely used as a stimulus in the study of biological lateral lines. Dipole source localization has also become a benchmark problem in the development of artificial lateral lines. In this paper we present two novel iterative schemes, referred to as Gauss–Newton (GN) and Newton–Raphson (NR) algorithms, for simultaneously localizing a dipole source and estimating its vibration amplitude and orientation, based on the analytical model for a dipole-generated flow field. The performance of the GN and NR methods is first confirmed with simulation results and the Cramer–Rao bound (CRB) analysis. Experiments are further conducted on an artificial lateral line prototype, consisting of six millimeter-scale ionic polymer–metal composite sensors with intra-sensor spacing optimized with CRB analysis. Consistent with simulation results, the experimental results show that both GN and NR schemes are able to simultaneously estimate the source location, vibration amplitude and orientation with comparable precision. Specifically, the maximum localization error is less than 5% of the body length (BL) when the source is within the distance of one BL. Experimental results have also shown that the proposed schemes are superior to the beamforming method, one of the most competitive approaches reported in literature, in terms of accuracy and computational efficiency. (paper)

  12. Photosynthetic characteristics of Lycoris aurea and monthly ...

    African Journals Online (AJOL)

    The leaf photosynthetic characteristics of Lycoris aurea, the monthly dynamics in lycorine and galantamine contents in its bulb and the correlation among the photosynthetic characteristics and the lycorine and galantamine during the annual growth period were studied by using LI-6400 portable photosynthetic measurement ...

  13. Improving the Effectiveness of a Nutrient Removal System Composed of Microalgae and Daphnia by an Artificial Illumination

    Directory of Open Access Journals (Sweden)

    In-Ho Chang

    2014-03-01

    Full Text Available For determining the effect of illumination on nutrient removal in an artificial food web (AFW system, we launched a pilot continuous-flow system. The system consisted of a storage basin, a phytoplankton growth chamber, and a zooplankton growth chamber. A 25,000 Lux AFW-light emitting diode (LED on system and an AFW-LED off system were separately operated for 10 days. In the AFW-LED on system, the maximum chlorophyll-a concentration of the phytoplankton chamber was four times higher than that of the AFW-LED off system. With artificial nighttime illumination, the microalgae became both smaller and more nutritious; the microalgae became high quality food for the zooplankton, Daphnia magna. Consequently, this zooplankton became more efficient at extracting nutrients and grew more densely than in the AFW-LED off system condition. In the LED-on condition, the amounts of total nitrogen (TN and total phosphorus (TP flowing into the system for 10 days were 84.7 g and 20.4 g, and the amounts flowing out were 19.5 g (23% and 4.0 g (20%, respectively. In contrast, in the LED-off condition, 83.8 g and 20.6 g of TN and TP flowed into the system while 38.8 g (46% and 6.8 g (33% flowed out, respectively. Artificial illumination significantly improves the removal rate of nutrients in an AFW system.

  14. 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

  15. Power management of a hybrid renewable system for artificial islands: A case study

    International Nuclear Information System (INIS)

    Cozzolino, R.; Tribioli, L.; Bella, G.

    2016-01-01

    In this paper, a hybrid wind/solar/fuel cell power plant is designed and a possible power management strategy is proposed. In particular, wind and solar energy sources are used as primary power suppliers, while a pure-hydrogen-fueled fuel cell – with hydrogen produced by means of an electrolyzer recovering excess power – and a battery pack are employed to fulfill the power demand, when the power supplied by the renewable sources is not sufficient. The analysis is applied to a particular case study, i.e. the TUNeIT [TUNisia and ITaly] Project, that involves the realization of four artificial islands to connect Bon (Tunisia) and Pizzolato (Sicily), provided with electrical-power-demanding facilities for tourists. Components sizing has been performed with HOMER, where a load profile has been assumed in order to reproduce the possible power demand of one of these artificial islands, while Matlab/Simulink"® is used for simulations and power management strategy design. The obtained results demonstrate the possibility of realizing an almost self-sustaining renewable power plant, able to realize a good integration of different energy sources and power converters, with no negative effects on end-user satisfaction. The system would consist of a wind turbine of 1 MW and a photovoltaic array of 1.1 MW, acting as primary power sources and several backup systems, such as a 72-kWh battery, a 300-kW fuel cell and a 300-kW diesel engine to cope with power demand unmatches and/or failures. In order to verify the system performance under different situations, simulation studies have been carried out using practical load demand profiles and real weather data. Typical winter and summer day loads have been kept for simulations of a four-season scenario and results are provided to show the effectiveness of the proposed system. The major drawback encountered during the analysis is the low value of the utilization factors of both wind turbine and photovoltaic array, which are 10

  16. AN INTRODUCTION TO KNOWLEDGE-GROWING SYSTEM: A NOVEL FIELD IN ARTIFICIAL INTELLIGENCE

    Directory of Open Access Journals (Sweden)

    Arwin Datumaya Wahyudi Sumari

    2010-07-01

    Full Text Available The essential matter of Artificial Intelligence (AI is how to build an entity that mimics human intelligence in the way of learning of a phenomenon in a real life to gain knowledge of it and uses the knowledge to solve problems related to it. Based on the findings of intelligenct characteristic displayed by the human brain in growing and generating new knowledge by fusing information perceived by sensory organs, we develop brain-inspired Knowledge-Growing System (KGS that is, a system that is capable of growing its knowledge along with the accretion of information as the time passes. The essential matter of KGS is knowledge-growing method which is based on a new algorithm called Observation Multi-time A3S (OMA3S information-inferencing fusion method. In this paper we deliver the development of KGS along with some examples of KGS application to a real-life problem. Based on the state-of-the-art of AI and approaches to construct OMA3S method as KG method as well as validations to assess the system performance, we state that brain-inspired KGS is a novel field in AI.

  17. Dispersion compensation of fiber optic communication system with direct detection using artificial neural networks (ANNs)

    Science.gov (United States)

    Maghrabi, Mahmoud M. T.; Kumar, Shiva; Bakr, Mohamed H.

    2018-02-01

    This work introduces a powerful digital nonlinear feed-forward equalizer (NFFE), exploiting multilayer artificial neural network (ANN). It mitigates impairments of optical communication systems arising due to the nonlinearity introduced by direct photo-detection. In a direct detection system, the detection process is nonlinear due to the fact that the photo-current is proportional to the absolute square of the electric field intensity. The proposed equalizer provides the most efficient computational cost with high equalization performance. Its performance is comparable to the benchmark compensation performance achieved by maximum-likelihood sequence estimator. The equalizer trains an ANN to act as a nonlinear filter whose impulse response removes the intersymbol interference (ISI) distortions of the optical channel. Owing to the proposed extensive training of the equalizer, it achieves the ultimate performance limit of any feed-forward equalizer (FFE). The performance and efficiency of the equalizer is investigated by applying it to various practical short-reach fiber optic communication system scenarios. These scenarios are extracted from practical metro/media access networks and data center applications. The obtained results show that the ANN-NFFE compensates for the received BER degradation and significantly increases the tolerance to the chromatic dispersion distortion.

  18. Matching between the light spots and lenslets of an artificial compound eye system

    Science.gov (United States)

    He, Jianzheng; Jian, Huijie; Zhu, Qitao; Ma, Mengchao; Wang, Keyi

    2017-10-01

    As the visual organ of many arthropods, the compound eye has attracted a lot of attention with the advantage of wide field-of-view, multi-channel imaging ability and high agility. Extended from this concept, a new kind of artificial compound eye device is developed. There are 141 lenslets which share one image sensor distributed evenly on a curved surface, thus it is difficult to distinguish the lenslets which the light spot belongs to during calibration and positioning process. Therefore, the matching algorithm is proposed based on the device structure and the principle of calibration and positioning. Region partition of lenslet array is performed at first. Each lenslet and its adjacent lenslets are defined as cluster eyes and constructed into an index table. In the calibration process, a polar coordinate system is established, and the matching can be accomplished by comparing the rotary table position in the polar coordinate system and the central light spot angle in the image. In the positioning process, the spot is paired to the correct region according to the spots distribution firstly, and the final results is determined by the dispersion of the distance from the target point to the incident ray in the region traversal matching. Finally, the experiment results show that the presented algorithms provide a feasible and efficient way to match the spot to the lenslet, and perfectly meet the needs in the practical application of the compound eye system.

  19. Measuring an artificial intelligence system's performance on a Verbal IQ test for young children

    Science.gov (United States)

    Ohlsson, Stellan; Sloan, Robert H.; Turán, György; Urasky, Aaron

    2017-07-01

    We administered the Verbal IQ (VIQ) part of the Wechsler Preschool and Primary Scale of Intelligence (WPPSI-III) to the ConceptNet 4 artificial intelligence (AI) system. The test questions (e.g. "Why do we shake hands?") were translated into ConceptNet 4 inputs using a combination of the simple natural language processing tools that come with ConceptNet together with short Python programs that we wrote. The question answering used a version of ConceptNet based on spectral methods. The ConceptNet system scored a WPPSI-III VIQ that is average for a four-year-old child, but below average for 5-7 year olds. Large variations among subtests indicate potential areas of improvement. In particular, results were strongest for the Vocabulary and Similarities subtests, intermediate for the Information subtest and lowest for the Comprehension and Word Reasoning subtests. Comprehension is the subtest most strongly associated with common sense. The large variations among subtests and ordinary common sense strongly suggest that the WPPSI-III VIQ results do not show that "ConceptNet has the verbal abilities of a four-year-old". Rather, children's IQ tests offer one objective metric for the evaluation and comparison of AI systems. Also, this work continues previous research on psychometric AI.

  20. Classification of Physical Activity: Information to Artificial Pancreas Control Systems in Real Time.

    Science.gov (United States)

    Turksoy, Kamuran; Paulino, Thiago Marques Luz; Zaharieva, Dessi P; Yavelberg, Loren; Jamnik, Veronica; Riddell, Michael C; Cinar, Ali

    2015-10-06

    Physical activity has a wide range of effects on glucose concentrations in type 1 diabetes (T1D) depending on the type (ie, aerobic, anaerobic, mixed) and duration of activity performed. This variability in glucose responses to physical activity makes the development of artificial pancreas (AP) systems challenging. Automatic detection of exercise type and intensity, and its classification as aerobic or anaerobic would provide valuable information to AP control algorithms. This can be achieved by using a multivariable AP approach where biometric variables are measured and reported to the AP at high frequency. We developed a classification system that identifies, in real time, the exercise intensity and its reliance on aerobic or anaerobic metabolism and tested this approach using clinical data collected from 5 persons with T1D and 3 individuals without T1D in a controlled laboratory setting using a variety of common types of physical activity. The classifier had an average sensitivity of 98.7% for physiological data collected over a range of exercise modalities and intensities in these subjects. The classifier will be added as a new module to the integrated multivariable adaptive AP system to enable the detection of aerobic and anaerobic exercise for enhancing the accuracy of insulin infusion strategies during and after exercise. © 2015 Diabetes Technology Society.

  1. Evaluation of design parameters in soil-structure systems through artificial intelligence

    International Nuclear Information System (INIS)

    Cremonini, M.G.; Vardanega, C.; Parvis, E.

    1989-01-01

    This study refers to development of an artificial intelligence tool to evaluate design parameters for a soil-structure system as the foundations of Class 1 buildings of a nuclear power plant (NPP). This is based on an expert analysis of a large amount of information, collected during a comprehensive program of site investigations and laboratory tests and stored on a computer data-bank. The methodology comprises the following steps: organization of the available information on the site characteristics in a data-base; implementation and extensive use of a specific knowledge based expert system (KBES) devoted to both the analysis, interpretation and check of the information in the data-base, and to the evaluation of the design parameters; determination of effective access criteria to the data-base, for purposes of reordering the information and extracting design properties from a large number of experimental data; development of design profiles for both index properties and strength/strain parameters; and final evaluation of the design parameters. Results are obtained in the form of: local and general site stratigraphy; summarized soil index properties, detailing the site setting; static and dynamic stress-strain parameters, G/G max behavior and damping factors; condolidation parameters and OCR ratio; spatial distribution of parameters on site area; identification of specific local conditions; and cross correlation of parameters, thus covering the whole range of design parameters for NPP soil-structure systems

  2. Artificial neural network controller for automatic ship berthing using head-up coordinate system

    Directory of Open Access Journals (Sweden)

    Nam-Kyun Im

    2018-05-01

    Full Text Available The Artificial Neural Network (ANN model has been known as one of the most effective theories for automatic ship berthing, as it has learning ability and mimics the actions of the human brain when performing the stages of ship berthing. However, existing ANN controllers can only bring a ship into a berth in a certain port, where the inputs of the ANN are the same as those of the teaching data. This means that those ANN controllers must be retrained when the ship arrives to a new port, which is time-consuming and costly. In this research, by using the head-up coordinate system, which includes the relative bearing and distance from the ship to the berth, a novel ANN controller is proposed to automatically control the ship into the berth in different ports without retraining the ANN structure. Numerical simulations were performed to verify the effectiveness of the proposed controller. First, teaching data were created in the original port to train the neural network; then, the controller was tested for automatic berthing in other ports, where the initial conditions of the inputs in the head-up coordinate system were similar to those of the teaching data in the original port. The results showed that the proposed controller has good performance for ship berthing in ports. Keywords: Automatic ship berthing, ANN controller, Head-up coordinate system, Low speed, Relative bearing

  3. Biological model of vision for an artificial system that learns to perceive its environment

    Energy Technology Data Exchange (ETDEWEB)

    Blackburn, M.R.; Nguyen, H.G.

    1989-06-01

    The objective is to design an artificial vision system for use in robotics applications. Because the desired performance is equivalent to that achieved by nature, the authors anticipate that the objective will be accomplished most efficiently through modeling aspects of the neuroanatomy and neurophysiology of the biological visual system. Information enters the biological visual system through the retina and is passed to the lateral geniculate and optic tectum. The lateral geniculate nucleus (LGN) also receives information from the cerebral cortex and the result of these two inflows is returned to the cortex. The optic tectum likewise receives the retinal information in a context of other converging signals and organizes motor responses. A computer algorithm is described which implements models of the biological visual mechanisms of the retina, thalamic lateral geniculate and perigeniculate nuclei, and primary visual cortex. Motion and pattern analyses are performed in parallel and interact in the cortex to construct perceptions. We hypothesize that motion reflexes serve as unconditioned pathways for the learning and recall of pattern information. The algorithm demonstrates this conditioning through a learning function approximating heterosynaptic facilitation.

  4. Imaging dipole flow sources using an artificial lateral-line system made of biomimetic hair flow sensors

    NARCIS (Netherlands)

    Dagamseh, A.M.K.; Wiegerink, Remco J.; Lammerink, Theodorus S.J.; Krijnen, Gijsbertus J.M.

    2013-01-01

    In Nature, fish have the ability to localize prey, school, navigate, etc., using the lateral-line organ. Artificial hair flow sensors arranged in a linear array shape (inspired by the lateral-line system (LSS) in fish) have been applied to measure airflow patterns at the sensor positions. Here, we

  5. Carbon dot-Au(i)Ag(0) assembly for the construction of an artificial light harvesting system.

    Science.gov (United States)

    Jana, Jayasmita; Aditya, Teresa; Pal, Tarasankar

    2018-03-06

    Artificial light harvesting systems (LHS) with inorganic counterparts are considered to be robust as well as mechanistically simple, where the system follows the donor-acceptor principle with an unchanged structural pattern. Plasmonic gold or silver nanoparticles are mostly chosen as inorganic counterparts to design artificial LHS. To capitalize on its electron accepting capability, Au(i) has been considered in this work for the synergistic stabilization of a system with intriguingly fluorescing silver(0) clusters produced in situ. Thus a stable fluorescent Au(i)Ag(0) assembly is generated with electron accepting capabilities. On the other hand, carbon dots have evolved as new fluorescent probes due to their unique physicochemical properties. Utilizing the simple electronic behavior of carbon dots, an electronic interaction between the fluorescent Au(i)Ag(0) and a carbon dot has been investigated for the construction of a new artificial light harvesting system. This coinage metal assembly allows surface energy transfer where it acts as an acceptor, while the carbon dot behaves as a good donor. The energy transfer efficiency has been calculated experimentally to be significant (81.3%) and the Au(i)Ag(0)-carbon dot assembly paves the way for efficient artificial LHS.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1999-04-01

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

  7. BRAIN. Broad Research in Artificial Intelligence and Neuroscience-Review of Recent Trends in Measuring the Computing Systems Intelligence

    OpenAIRE

    Laszlo Barna Iantovics; Adrian Gligor; Muaz A. Niazi; Anna Iuliana Biro; Sandor Miklos Szilagyi; Daniel Tokody

    2018-01-01

    Many difficult problems, from the philosophy of computation point of view, could require computing systems that have some kind of intelligence in order to be solved. Recently, we have seen a large number of artificial intelligent systems used in a number of scientific, technical and social domains. Usage of such an approach often has a focus on healthcare. These systems can provide solutions to a very large set of problems such as, but not limited to: elder patient care; medica...

  8. Energy efficient security in MANETs: a comparison of cryptographic and artificial immune systems

    International Nuclear Information System (INIS)

    Mazhar, N.

    2010-01-01

    MANET is characterized by a set of mobile nodes in an inherently insecure environment, having limited battery capacities. Provisioning of energy efficient security in MANETs is, therefore, an open problem for which a number of solutions have been proposed. In this paper, we present an overview and comparison of the MANET security at routing layer by using the cryptographic and Artificial Immune System (AIS) approaches. The BeeAdHoc protocol, which is a Bio-inspired MANET routing protocol based on the foraging principles of honey bee colony, is taken as case study. We carry out an analysis of the three security frameworks that we have proposed earlier for securing BeeAdHoc protocol; one based on asymmetric key encryption, i.e BeeSec, and the other two using the AIS approach, i.e BeeAIS based on self non-self discrimination from adaptive immune system and BeeAIS-DC based on Dendritic Cell (DC) behavior from innate immune system. We extensively evaluate the performance of the three protocols through network simulations in ns-2 and compare with BeeAdHoc, the base protocol, as well as with state-of-the-art MANET routing protocols DSR and AODV. Our results clearly indicate that AIS based systems provide security at much lower cost to energy as compared with the cryptographic systems. Moreover, the use of dendritic cells and danger signals instead of the classical self non-self discrimination allows to detect the non-self antigens with greater accuracy. Based on the results of this investigation, we also propose a composite AIS model for BeeAdHoc security by combining the concepts from both the adaptive and the innate immune systems by modelling the attributes and behavior of the B-cells and DCs. (author)

  9. Cooperative research and development for artificial intelligence based reactor diagnostic system

    International Nuclear Information System (INIS)

    Reifman, J.; Wei, T.Y.C.; Abboud, R.G.; Chasensky, T.M.

    1994-01-01

    Artificial Intelligence (AI) techniques in the form of knowledge-based Expert Systems (ESs) have been proposed to provide on-line decision-making support for plant operators during both normal and emergency conditions. However, in spite of the great interest in these advanced techniques, their application in the diagnosis of large-scale processes has not yet reached its full potential because of limitations of the knowledge base. These limitations include problems with knowledge acquisition and the use of an event-oriented approach for process diagnosis. To investigate the capabilities of this two-level hierarchical knowledge structure, Commonwealth Research Corporation (CRC) and Argonne National Laboratory (ANL)are collaborating on a DOE-sponsored Cooperative Research and Development Agreement (CRADA) project to perform feasibility studies on the proposed diagnostic system. Investigations are being performed in the construction of a physics-based plant level process diagnostic ES and the characterization of component-level fault project is to develop a computer-based system using this Al approach to assist process plant operators during off-normal plant conditions. The proposed computer-based system will use T-H signals complemented by other non-T-H signals available in the data stream to provide the process operator with the component which most likely caused the observed process disturbance. To demonstrate the scale-up feasibility of the proposed diagnostic system it is being developed for use with the Chemical Volume Control System (CVCS) of a nuclear power plant. This is an ongoing multi-year project and the remainder of this paper presents a mid-term status report

  10. An artificial arm/hand system with a haptic sensory function using electric stimulation of peripheral sensory nerve fibers.

    Science.gov (United States)

    Mabuchi, Kunihiko

    2013-01-01

    We are currently developing an artificial arm/hand system which is capable of sensing stimuli and then transferring these stimuli to users as somatic sensations. Presently, we are evoking the virtual somatic sensations by electrically stimulating a sensory nerve fiber which innervates a single mechanoreceptor unit at the target area; this is done using a tungsten microelectrode that was percutaneously inserted into the use's peripheral nerve (a microstimulation method). The artificial arm/hand system is composed of a robot hand equipped with a pressure sensor system on its fingers. The sensor system detects mechanical stimuli, which are transferred to the user by means of the microstimulation method so that the user experiences the stimuli as the corresponding somatic sensations. In trials, the system worked satisfactorily and there was a good correlation between the pressure applied to the pressure sensors on the robot fingers and the subjective intensities of the evoked pressure sensations.

  11. Extrusion and erosion of bentonite buffer material in a flow-through, horizontal, artificial fracture system

    International Nuclear Information System (INIS)

    Schatz, Timothy; Kanerva, Noora; Martikainen, Jari

    2012-01-01

    Document available in extended abstract form only. One scenario of interest for the long-term safety assessment of a spent nuclear fuel repository involves the loss of bentonite buffer material through contact with dilute groundwater at a transmissive fracture interface [SKB 2011, Posiva 2012]. In order to simulate the potential extrusion/erosion behaviour of bentonite buffer material in such an environment, a series of small-scale, flow-through, artificial fracture experiments were performed in which swelling clay material could extrude/erode into a well defined, system (see Figure 1). The fracture dimensions were 24 cm (length) x 24 cm (width) x 1 mm (aperture) and the compacted sample dimensions were 2 cm (height) x 2 cm (diameter). Extrusion/erosion effects were analysed against solution chemistry (salt concentration and composition), material composition (sodium montmorillonite and admixtures with calcium montmorillonite), and flow velocity. No erosion was observed for sodium montmorillonite against solution compositions from 10 to 0.5 g/L NaCl. Comparatively, most reports in the literature indicate that a concentration of 0.5 g/L NaCl (8.6 mM) is below, in some cases well below, the (experimentally observed) critical coagulation concentration (CCC) for the colloidal sodium montmorillonite/sodium chloride system [Garcia-Garcia et al. 2007]. It was also the case that no erosion was observed for 50/50 calcium/sodium montmorillonite against 0.5 g/L NaCl. Overall, the results of the flow-through, artificial fracture tests, indicate stability to erosion down to a dilute concentration range between 8 to 4 mM NaCl for both sodium and 50/50 calcium/sodium montmorillonite. These limits compare favorably to the erosion stability limits observed by Birgersson et al. [2009] in the case of the latter material but less so for the former. A number of tests were conducted for which measurable erosion was observed. The calculated mass loss rates for these tests, expressed in

  12. Development of automatic radiographic inspection system using digital image processing and artificial intelligence

    International Nuclear Information System (INIS)

    Itoga, Kouyu; Sugimoto, Koji; Michiba, Koji; Kato, Yuhei; Sugita, Yuji; Onda, Katsuhiro.

    1991-01-01

    The application of computers to welding inspection is expanding rapidly. The classification of the application is the collection, analysis and processing of data, the graphic display of results, the distinction of the kinds of defects and the evaluation of the harmufulness of defects and the judgement of acceptance or rejection. The application of computer techniques to the automation of data collection was realized at the relatively early stage. Data processing and the graphic display of results are the techniques in progress now, and the application of artificial intelligence to the distinction of the kinds of defects and the evaluation of harmfulness is expected to expand rapidly. In order to computerize radiographic inspection, the abilities of image processing technology and knowledge engineering must be given to computers. The object of this system is the butt joints by arc welding of the steel materials of up to 30 mm thickness. The digitizing transformation of radiographs, the distinction and evaluation of transmissivity and gradation by image processing, and only as for those, of which the picture quality satisfies the standard, the extraction of defect images, their display, the distinction of the kinds and the final judgement are carried out. The techniques of image processing, the knowledge for distinguishing the kinds of defects and the concept of the practical system are reported. (K.I.)

  13. Prediction of Breeding Values for Dairy Cattle Using Artificial Neural Networks and Neuro-Fuzzy Systems

    Directory of Open Access Journals (Sweden)

    Saleh Shahinfar

    2012-01-01

    Full Text Available Developing machine learning and soft computing techniques has provided many opportunities for researchers to establish new analytical methods in different areas of science. The objective of this study is to investigate the potential of two types of intelligent learning methods, artificial neural networks and neuro-fuzzy systems, in order to estimate breeding values (EBV of Iranian dairy cattle. Initially, the breeding values of lactating Holstein cows for milk and fat yield were estimated using conventional best linear unbiased prediction (BLUP with an animal model. Once that was established, a multilayer perceptron was used to build ANN to predict breeding values from the performance data of selection candidates. Subsequently, fuzzy logic was used to form an NFS, a hybrid intelligent system that was implemented via a local linear model tree algorithm. For milk yield the correlations between EBV and EBV predicted by the ANN and NFS were 0.92 and 0.93, respectively. Corresponding correlations for fat yield were 0.93 and 0.93, respectively. Correlations between multitrait predictions of EBVs for milk and fat yield when predicted simultaneously by ANN were 0.93 and 0.93, respectively, whereas corresponding correlations with reference EBV for multitrait NFS were 0.94 and 0.95, respectively, for milk and fat production.

  14. The application of artificial intelligence in the optimal design of mechanical systems

    Science.gov (United States)

    Poteralski, A.; Szczepanik, M.

    2016-11-01

    The paper is devoted to new computational techniques in mechanical optimization where one tries to study, model, analyze and optimize very complex phenomena, for which more precise scientific tools of the past were incapable of giving low cost and complete solution. Soft computing methods differ from conventional (hard) computing in that, unlike hard computing, they are tolerant of imprecision, uncertainty, partial truth and approximation. The paper deals with an application of the bio-inspired methods, like the evolutionary algorithms (EA), the artificial immune systems (AIS) and the particle swarm optimizers (PSO) to optimization problems. Structures considered in this work are analyzed by the finite element method (FEM), the boundary element method (BEM) and by the method of fundamental solutions (MFS). The bio-inspired methods are applied to optimize shape, topology and material properties of 2D, 3D and coupled 2D/3D structures, to optimize the termomechanical structures, to optimize parameters of composites structures modeled by the FEM, to optimize the elastic vibrating systems to identify the material constants for piezoelectric materials modeled by the BEM and to identify parameters in acoustics problem modeled by the MFS.

  15. A prototype system for perinatal knowledge engineering using an artificial intelligence tool.

    Science.gov (United States)

    Sokol, R J; Chik, L

    1988-01-01

    Though several perinatal expert systems are extant, the use of artificial intelligence has, as yet, had minimal impact in medical computing. In this evaluation of the potential of AI techniques in the development of a computer based "Perinatal Consultant," a "top down" approach to the development of a perinatal knowledge base was taken, using as a source for such a knowledge base a 30-page manuscript of a chapter concerning high risk pregnancy. The UNIX utility "style" was used to parse sentences and obtain key words and phrases, both as part of a natural language interface and to identify key perinatal concepts. Compared with the "gold standard" of sentences containing key facts as chosen by the experts, a semiautomated method using a nonmedical speller to identify key words and phrases in context functioned with a sensitivity of 79%, i.e., approximately 8 in 10 key sentences were detected as the basis for PROLOG, rules and facts for the knowledge base. These encouraging results suggest that functional perinatal expert systems may well be expedited by using programming utilities in conjunction with AI tools and published literature.

  16. An Artificial Intelligence System to Predict Quality of Service in Banking Organizations

    Science.gov (United States)

    Popovič, Aleš

    2016-01-01

    Quality of service, that is, the waiting time that customers must endure in order to receive a service, is a critical performance aspect in private and public service organizations. Providing good service quality is particularly important in highly competitive sectors where similar services exist. In this paper, focusing on banking sector, we propose an artificial intelligence system for building a model for the prediction of service quality. While the traditional approach used for building analytical models relies on theories and assumptions about the problem at hand, we propose a novel approach for learning models from actual data. Thus, the proposed approach is not biased by the knowledge that experts may have about the problem, but it is completely based on the available data. The system is based on a recently defined variant of genetic programming that allows practitioners to include the concept of semantics in the search process. This will have beneficial effects on the search process and will produce analytical models that are based only on the data and not on domain-dependent knowledge. PMID:27313604

  17. Estimation of Leakage Ratio Using Principal Component Analysis and Artificial Neural Network in Water Distribution Systems

    Directory of Open Access Journals (Sweden)

    Dongwoo Jang

    2018-03-01

    Full Text Available Leaks in a water distribution network (WDS constitute losses of water supply caused by pipeline failure, operational loss, and physical factors. This has raised the need for studies on the factors affecting the leakage ratio and estimation of leakage volume in a water supply system. In this study, principal component analysis (PCA and artificial neural network (ANN were used to estimate the volume of water leakage in a WDS. For the study, six main effective parameters were selected and standardized data obtained through the Z-score method. The PCA-ANN model was devised and the leakage ratio was estimated. An accuracy assessment was performed to compare the measured leakage ratio to that of the simulated model. The results showed that the PCA-ANN method was more accurate for estimating the leakage ratio than a single ANN simulation. In addition, the estimation results differed according to the number of neurons in the ANN model’s hidden layers. In this study, an ANN with multiple hidden layers was found to be the best method for estimating the leakage ratio with 12–12 neurons. This suggested approaches to improve the accuracy of leakage ratio estimation, as well as a scientific approach toward the sustainable management of water distribution systems.

  18. An Artificial Intelligence System to Predict Quality of Service in Banking Organizations.

    Science.gov (United States)

    Castelli, Mauro; Manzoni, Luca; Popovič, Aleš

    2016-01-01

    Quality of service, that is, the waiting time that customers must endure in order to receive a service, is a critical performance aspect in private and public service organizations. Providing good service quality is particularly important in highly competitive sectors where similar services exist. In this paper, focusing on banking sector, we propose an artificial intelligence system for building a model for the prediction of service quality. While the traditional approach used for building analytical models relies on theories and assumptions about the problem at hand, we propose a novel approach for learning models from actual data. Thus, the proposed approach is not biased by the knowledge that experts may have about the problem, but it is completely based on the available data. The system is based on a recently defined variant of genetic programming that allows practitioners to include the concept of semantics in the search process. This will have beneficial effects on the search process and will produce analytical models that are based only on the data and not on domain-dependent knowledge.

  19. An Artificial Intelligence System to Predict Quality of Service in Banking Organizations

    Directory of Open Access Journals (Sweden)

    Mauro Castelli

    2016-01-01

    Full Text Available Quality of service, that is, the waiting time that customers must endure in order to receive a service, is a critical performance aspect in private and public service organizations. Providing good service quality is particularly important in highly competitive sectors where similar services exist. In this paper, focusing on banking sector, we propose an artificial intelligence system for building a model for the prediction of service quality. While the traditional approach used for building analytical models relies on theories and assumptions about the problem at hand, we propose a novel approach for learning models from actual data. Thus, the proposed approach is not biased by the knowledge that experts may have about the problem, but it is completely based on the available data. The system is based on a recently defined variant of genetic programming that allows practitioners to include the concept of semantics in the search process. This will have beneficial effects on the search process and will produce analytical models that are based only on the data and not on domain-dependent knowledge.

  20. An Artificial Flexible Visual Memory System Based on an UV-Motivated Memristor.

    Science.gov (United States)

    Chen, Shuai; Lou, Zheng; Chen, Di; Shen, Guozhen

    2018-02-01

    For the mimicry of human visual memory, a prominent challenge is how to detect and store the image information by electronic devices, which demands a multifunctional integration to sense light like eyes and to memorize image information like the brain by transforming optical signals to electrical signals that can be recognized by electronic devices. Although current image sensors can perceive simple images in real time, the image information fades away when the external image stimuli are removed. The deficiency between the state-of-the-art image sensors and visual memory system inspires the logical integration of image sensors and memory devices to realize the sensing and memory process toward light information for the bionic design of human visual memory. Hence, a facile architecture is designed to construct artificial flexible visual memory system by employing an UV-motivated memristor. The visual memory arrays can realize the detection and memory process of UV light distribution with a patterned image for a long-term retention and the stored image information can be reset by a negative voltage sweep and reprogrammed to the same or an other image distribution, which proves the effective reusability. These results provide new opportunities for the mimicry of human visual memory and enable the flexible visual memory device to be applied in future wearable electronics, electronic eyes, multifunctional robotics, and auxiliary equipment for visual handicapped. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Improvement in the determination of elemental concentrations in PIXE analyses using artificial neural system

    International Nuclear Information System (INIS)

    Correa, R.; Dinator, M.I.; Morales, J.R.; Miranda, P.A.; Cancino, S.A.; Vila, I.; Requena, I.

    2008-01-01

    An Artificial Neural System, ANS, has been designed to operate in the analysis of spectra obtained from a PIXE (Proton Induced X-ray Emissions) application. The special designed ANS was used in the calculation of the concentrations of the major elements in the samples. Neural systems using several feed-forward ANN of similar topology working in parallel were trained with error back propagation algorithm using sets of spectra of known elemental concentrations. Following the training phase of the neural networks, other PIXE spectra were analyzed with this methodology providing unknown elemental concentrations. ANS results were compared with results obtained by traditional computer codes like AXIL and GUPIX, obtaining correlations factors close to one. The rather short time required to process each spectrum, of the order of microseconds, allows fast analysis of a large number of samples. Here we present applications of ANS in the PIXE analyses of samples of organic nature like liver, gills and muscle from fishes. ANS results were compared with elemental concentrations obtained in a previous application where a single ANN was used for each analyzed element. PIXE analyses were performed at the Nuclear Physics Laboratory of the University of Chile, using 2.2 MeV proton beams provided by a Van de Graaff accelerator. (author)

  2. Development of data communication system with ultra high frequency radio wave for implantable artificial hearts.

    Science.gov (United States)

    Tsujimura, Shinichi; Yamagishi, Hiroto; Sankai, Yoshiyuki

    2009-01-01

    In order to minimize infection risks of patients with artificial hearts, wireless data transmission methods with electromagnetic induction or light have been developed. However, these methods tend to become difficult to transmit data if the external data transmission unit moves from its proper position. To resolve this serious problem, the purpose of this study is to develop a prototype wireless data communication system with ultra high frequency radio wave and confirm its performance. Due to its high-speed communication rate, low power consumption, high tolerance to electromagnetic disturbances, and secure wireless communication, we adopted Bluetooth radio wave technology for our system. The system consists of an internal data transmission unit and an external data transmission unit (53 by 64 by 16 mm, each), and each has a Bluetooth module (radio field intensity: 4 dBm, receiver sensitivity: -80 dBm). The internal unit also has a micro controller with an 8-channel 10-bit A/D converter, and the external unit also has a RS-232C converter. We experimented with the internal unit implanted into pig meat, and carried out data transmission tests to evaluate the performance of this system in tissue thickness of up to 3 mm. As a result, data transfer speeds of about 20 kbps were achieved within the communication distance of 10 m. In conclusion, we confirmed that the system can wirelessly transmit the data from the inside of the body to the outside, and it promises to resolve unstable data transmission due to accidental movements of an external data transmission unit.

  3. 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

  4. Production traits of artificially and naturally hatched geese in intensive and free-range systems: I. Growth traits.

    Science.gov (United States)

    Boz, M A; Sarica, M; Yamak, U S

    2017-04-01

    1. This study investigated the effect of incubation type and production system on geese growth traits. 2. A total of 216 geese were either naturally (114) or artificially (102) hatched and reared in intensive or free-range production systems (4 replicates each) until 18 weeks of age. 3. Weights of naturally hatched goslings (NHG) were significantly higher than artificially hatched goslings (AHG) at 2 weeks (644 vs. 536 g); however, weights of AHG were significantly higher than NHG at both 6 weeks (3245 vs. 3010 g) and 18 weeks (5212 vs. 4353 g). 4. AHG had better feed conversion ratios (FCRs) than NHG (6.21 vs. 6.46 at 18 weeks). Feed consumption of naturally hatched geese was found higher in first 4 weeks when compared to artificially hatched geese and artificially hatched geese consumed more feed than naturally hatched geese after 8 weeks. 5. Production system had insignificant effects on feed consumption, FCRs, viability and mutilation rates. 6. Slipped wings were more frequent in NHG than AHG (8.32% vs. 1.68% at 6 weeks; 23.84% vs. 5.12% between 7 and 18 weeks) and in free-range production when compared to intensive production (17.88% vs. 11.08% over the course of the production period). 7. The study results indicate that both artificially and NHG can be reared in free-range production systems without any loss in performance and in deference to animal welfare.

  5. 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

  6. Artificial Intelligence in Astronomy

    Science.gov (United States)

    Devinney, E. J.; Prša, A.; Guinan, E. F.; Degeorge, M.

    2010-12-01

    From the perspective (and bias) as Eclipsing Binary researchers, we give a brief overview of the development of Artificial Intelligence (AI) applications, describe major application areas of AI in astronomy, and illustrate the power of an AI approach in an application developed under the EBAI (Eclipsing Binaries via Artificial Intelligence) project, which employs Artificial Neural Network technology for estimating light curve solution parameters of eclipsing binary systems.

  7. Inteligencia artificial en vehiculo

    OpenAIRE

    Amador Díaz, Pedro

    2012-01-01

    Desarrollo de un robot seguidor de líneas, en el que se implementan diversas soluciones de las áreas de sistemas embebidos e inteligencia artificial. Desenvolupament d'un robot seguidor de línies, en el qual s'implementen diverses solucions de les àrees de sistemes encastats i intel·ligència artificial. Follower robot development of lines, in which various solutions are implemented in the areas of artificial intelligence embedded systems.

  8. Stability of free and encapsulated Lactobacillus acidophilus ATCC 4356 in yogurt and in an artificial human gastric digestion system.

    Science.gov (United States)

    Ortakci, F; Sert, S

    2012-12-01

    The objective of this study was to determine the effect of encapsulation on survival of probiotic Lactobacillus acidophilus ATCC 4356 (ATCC 4356) in yogurt and during artificial gastric digestion. Strain ATCC 4356 was added to yogurt either encapsulated in calcium alginate or in free form (unencapsulated) at levels of 8.26 and 9.47 log cfu/g, respectively, and the influence of alginate capsules (1.5 to 2.5mm) on the sensorial characteristics of yogurts was investigated. The ATCC 4356 strain was introduced into an artificial gastric solution consisting of 0.08 N HCl (pH 1.5) containing 0.2% NaCl or into artificial bile juice consisting of 1.2% bile salts in de Man, Rogosa, and Sharpe broth to determine the stability of the probiotic bacteria. When incubated for 2h in artificial gastric juice, the free ATCC 4356 did not survive (reduction of >7 log cfu/g). We observed, however, greater survival of encapsulated ATCC 4356, with a reduction of only 3 log cfu/g. Incubation in artificial bile juice (6 h) did not significantly affect the viability of free or encapsulated ATCC 4356. Moreover, statistically significant reductions (~1 log cfu/g) of both free and encapsulated ATCC 4356 were observed during 4-wk refrigerated storage of yogurts. The addition of probiotic cultures in free or alginate-encapsulated form did not significantly affect appearance/color or flavor/odor of the yogurts. However, significant deficiencies were found in body/texture of yogurts containing encapsulated ATCC 4356. We concluded that incorporation of free and encapsulated probiotic bacteria did not substantially change the overall sensory properties of yogurts, and encapsulation in alginate using the extrusion method greatly enhanced the survival of probiotic bacteria against an artificial human gastric digestive system. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  9. The spatial decision-supporting system combination of RBR & CBR based on artificial neural network and association rules

    Science.gov (United States)

    Tian, Yangge; Bian, Fuling

    2007-06-01

    The technology of artificial intelligence should be imported on the basis of the geographic information system to bring up the spatial decision-supporting system (SDSS). The paper discusses the structure of SDSS, after comparing the characteristics of RBR and CBR, the paper brings up the frame of a spatial decisional system that combines RBR and CBR, which has combined the advantages of them both. And the paper discusses the CBR in agriculture spatial decisions, the application of ANN (Artificial Neural Network) in CBR, and enriching the inference rule base based on association rules, etc. And the paper tests and verifies the design of this system with the examples of the evaluation of the crops' adaptability.

  10. Phytochromes in photosynthetically competent plants

    Energy Technology Data Exchange (ETDEWEB)

    Pratt, L.H.

    1990-07-01

    Plants utilize light as a source of information in photomorphogenesis and of free energy in photosynthesis, two processes that are interrelated in that the former serves to increase the efficiency with which plants can perform the latter. Only one pigment involved in photomorphogenesis has been identified unequivocally, namely phytochrome. The thrust of this proposal is to investigate this pigment and its mode(s) of action in photosynthetically competent plants. Our long term objective is to characterize phytochrome and its functions in photosynthetically competent plants from molecular, biochemical and cellular perspectives. It is anticipated that others will continue to contribute indirectly to these efforts at the physiological level. The ultimate goal will be to develop this information from a comparative perspective in order to learn whether the different phytochromes have significantly different physicochemical properties, whether they fulfill independent functions and if so what these different functions are, and how each of the different phytochromes acts at primary molecular and cellular levels.

  11. Artificial neural network application for space station power system fault diagnosis

    Science.gov (United States)

    Momoh, James A.; Oliver, Walter E.; Dias, Lakshman G.

    1995-01-01

    This study presents a methodology for fault diagnosis using a Two-Stage Artificial Neural Network Clustering Algorithm. Previously, SPICE models of a 5-bus DC power distribution system with assumed constant output power during contingencies from the DDCU were used to evaluate the ANN's fault diagnosis capabilities. This on-going study uses EMTP models of the components (distribution lines, SPDU, TPDU, loads) and power sources (DDCU) of Space Station Alpha's electrical Power Distribution System as a basis for the ANN fault diagnostic tool. The results from the two studies are contrasted. In the event of a major fault, ground controllers need the ability to identify the type of fault, isolate the fault to the orbital replaceable unit level and provide the necessary information for the power management expert system to optimally determine a degraded-mode load schedule. To accomplish these goals, the electrical power distribution system's architecture can be subdivided into three major classes: DC-DC converter to loads, DC Switching Unit (DCSU) to Main bus Switching Unit (MBSU), and Power Sources to DCSU. Each class which has its own electrical characteristics and operations, requires a unique fault analysis philosophy. This study identifies these philosophies as Riddles 1, 2 and 3 respectively. The results of the on-going study addresses Riddle-1. It is concluded in this study that the combination of the EMTP models of the DDCU, distribution cables and electrical loads yields a more accurate model of the behavior and in addition yielded more accurate fault diagnosis using ANN versus the results obtained with the SPICE models.

  12. Totally implantable total artificial heart and ventricular assist device with multipurpose miniature electromechanical energy system.

    Science.gov (United States)

    Takatani, S; Orime, Y; Tasai, K; Ohara, Y; Naito, K; Mizuguchi, K; Makinouchi, K; Damm, G; Glueck, J; Ling, J

    1994-01-01

    A multipurpose miniature electromechanical energy system has been developed to yield a compact, efficient, durable, and biocompatible total artificial heart (TAH) and ventricular assist device (VAD). Associated controller-driver electronics were recently miniaturized and converted into hybrid circuits. The hybrid controller consists of a microprocessor and controller, motor driver, Hall sensor, and commutation circuit hybrids. The sizing study demonstrated that all these components can be incorporated in the pumping unit of the TAH and VAD, particularly in the centerpiece of the TAH and the motor housing of the VAD. Both TAH and VAD pumping units will start when their power line is connected to either the internal power pack or the external battery unit. As a redundant driving and diagnostic port, an emergency port was newly added and will be placed in subcutaneous location. In case of system failure, the skin will be cut down, and an external motor drive or a pneumatic driver will be connected to this port to run the TAH. This will minimize the circulatory arrest time. Overall efficiency of the TAH without the transcutaneous energy transmission system was 14-18% to deliver pump outputs of 4-9 L/min against the right and left afterload pressures of 25 and 100 mm Hg. The internal power requirement ranged from 6 to 13 W. The rechargeable batteries such as NiCd or NiMH with 1 AH capacity can run the TAH for 30-45 min. The external power requirement, when TETS efficiency of 75% was assumed, ranged from 8 to 18 W. The accelerated endurance test in the 42 degrees C saline bath demonstrated stable performance over 4 months. Long-term endurance and chronic animal studies will continue toward a system with 5 years durability by the year 2000.

  13. Artificial Pancreas Device Systems for the Closed-Loop Control of Type 1 Diabetes: What Systems Are in Development?

    Science.gov (United States)

    Trevitt, Sara; Simpson, Sue; Wood, Annette

    2016-05-01

    Closed-loop artificial pancreas device (APD) systems are externally worn medical devices that are being developed to enable people with type 1 diabetes to regulate their blood glucose levels in a more automated way. The innovative concept of this emerging technology is that hands-free, continuous, glycemic control can be achieved by using digital communication technology and advanced computer algorithms. A horizon scanning review of this field was conducted using online sources of intelligence to identify systems in development. The systems were classified into subtypes according to their level of automation, the hormonal and glycemic control approaches used, and their research setting. Eighteen closed-loop APD systems were identified. All were being tested in clinical trials prior to potential commercialization. Six were being studied in the home setting, 5 in outpatient settings, and 7 in inpatient settings. It is estimated that 2 systems may become commercially available in the EU by the end of 2016, 1 during 2017, and 2 more in 2018. There are around 18 closed-loop APD systems progressing through early stages of clinical development. Only a few of these are currently in phase 3 trials and in settings that replicate real life. © 2015 Diabetes Technology Society.

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

    OpenAIRE

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

    2013-01-01

    One of the most recent optimization techniques applied to the optimal design of photovoltaic system to supply an isolated load demand is the Artificial Bee Colony Algorithm (ABC). The proposed methodology is applied to optimize the cost of the PV system including photovoltaic, a battery bank, a battery charger controller, and inverter. Two objective functions are proposed: the first one is the PV module output power which is to be maximized and the second one is the life cycle cost (LCC) whic...

  15. ANALYSIS DATA SETS USING HYBRID TECHNIQUES APPLIED ARTIFICIAL INTELLIGENCE BASED PRODUCTION SYSTEMS INTEGRATED DESIGN

    OpenAIRE

    Daniel-Petru GHENCEA; Miron ZAPCIU; Claudiu-Florinel BISU; Elena-Iuliana BOTEANU; Elena-Luminiţa OLTEANU

    2017-01-01

    The paper proposes a prediction model of behavior spindle from the point of view of the thermal deformations and the level of the vibrations by highlighting and processing the characteristic equations. This is a model analysis for the shaft with similar electro-mechanical characteristics can be achieved using a hybrid analysis based on artificial intelligence (genetic algorithms - artificial neural networks - fuzzy logic). The paper presents a prediction mode obtaining valid range of values f...

  16. 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.

  17. QUESTION ANSWERING SYSTEM BERBASIS ARTIFICIAL INTELLIGENCE MARKUP LANGUAGE SEBAGAI MEDIA INFORMASI

    OpenAIRE

    Fajrin Azwary; Fatma Indriani; Dodon T. Nugrahadi

    2016-01-01

    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...

  18. 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....

  19. Wavelet based artificial neural network applied for energy efficiency enhancement of decoupled HVAC system

    International Nuclear Information System (INIS)

    Jahedi, G.; Ardehali, M.M.

    2012-01-01

    Highlights: ► In HVAC systems, temperature and relative humidity are coupled and dynamic mathematical models are non-linear. ► A wavelet-based ANN is used in series with an infinite impulse response filter for self tuning of PD controller. ► Energy consumption is evaluated for a decoupled bi-linear HVAC system with variable air volume and variable water flow. ► Substantial enhancement in energy efficiency is realized, when the gain coefficients of PD controllers are tuned adaptively. - Abstract: Control methodologies could lower energy demand and consumption of heating, ventilating and air conditioning (HVAC) systems and, simultaneously, achieve better comfort conditions. However, the application of classical controllers is unsatisfactory as HVAC systems are non-linear and the control variables such as temperature and relative humidity (RH) inside the thermal zone are coupled. The objective of this study is to develop and simulate a wavelet-based artificial neural network (WNN) for self tuning of a proportional-derivative (PD) controller for a decoupled bi-linear HVAC system with variable air volume and variable water flow responsible for controlling temperature and RH of a thermal zone, where thermal comfort and energy consumption of the system are evaluated. To achieve the objective, a WNN is used in series with an infinite impulse response (IIR) filter for faster and more accurate identification of system dynamics, as needed for on-line use and off-line batch mode training. The WNN-IIR algorithm is used for self-tuning of two PD controllers for temperature and RH. The simulation results show that the WNN-IIR controller performance is superior, as compared with classical PD controller. The enhancement in efficiency of the HVAC system is accomplished due to substantially lower consumption of energy during the transient operation, when the gain coefficients of PD controllers are tuned in an adaptive manner, as the steady state setpoints for temperature and

  20. Artificial neural networks applied to DNBR calculation in digital core protection systems

    International Nuclear Information System (INIS)

    Lee, H. C.; Chang, S. H.

    2003-01-01

    The nuclear power plant has to be operated with sufficient margin from the specified DNBR limit for assuring its safety. The digital core protection system calculates on-line real-time DNBR by using a complex subchannel analysis program, and triggers a reliable reactor shutdown if the calculated DNBR approaches the specified limit. However, it takes relatively long calculation time even for a steady state condition, which may have an adverse effect on the operation flexibility. To overcome the drawback, a method using artificial neural networks is studied in this paper. Nonparametric training approach is utilized, which shows dramatic reduction of the training time, no tedious heuristic process for optimizing parameters, and no local minima problem during the training. The test results show that the predicted DNBR is within about ±2% deviation from the target DNBR for the fixed axial flux shape case. For the variable axial flux case including severely skewed shapes appeared during accidents, the deviation is about ±10∼15%. The suggested method could be the alternative that can calculate DNBR very quickly while increasing the plant availability

  1. Evolution of Collective Behaviour in an Artificial World Using Linguistic Fuzzy Rule-Based Systems.

    Directory of Open Access Journals (Sweden)

    Jure Demšar

    Full Text Available Collective behaviour is a fascinating and easily observable phenomenon, attractive to a wide range of researchers. In biology, computational models have been extensively used to investigate various properties of collective behaviour, such as: transfer of information across the group, benefits of grouping (defence against predation, foraging, group decision-making process, and group behaviour types. The question 'why,' however remains largely unanswered. Here the interest goes into which pressures led to the evolution of such behaviour, and evolutionary computational models have already been used to test various biological hypotheses. Most of these models use genetic algorithms to tune the parameters of previously presented non-evolutionary models, but very few attempt to evolve collective behaviour from scratch. Of these last, the successful attempts display clumping or swarming behaviour. Empirical evidence suggests that in fish schools there exist three classes of behaviour; swarming, milling and polarized. In this paper we present a novel, artificial life-like evolutionary model, where individual agents are governed by linguistic fuzzy rule-based systems, which is capable of evolving all three classes of behaviour.

  2. Nanostructured complex oxides as a route towards thermal behavior in artificial spin ice systems

    Science.gov (United States)

    Chopdekar, R. V.; Li, B.; Wynn, T. A.; Lee, M. S.; Jia, Y.; Liu, Z. Q.; Biegalski, M. D.; Retterer, S. T.; Young, A. T.; Scholl, A.; Takamura, Y.

    2017-07-01

    We have used soft x-ray photoemission electron microscopy to image the magnetization of single-domain L a0.7S r0.3Mn O3 nanoislands arranged in geometrically frustrated configurations such as square ice and kagome ice geometries. Upon thermal randomization, ensembles of nanoislands with strong interisland magnetic coupling relax towards low-energy configurations. Statistical analysis shows that the likelihood of ensembles falling into low-energy configurations depends strongly on the annealing temperature. Annealing to just below the Curie temperature of the ferromagnetic film (TC=338 K ) allows for a much greater probability of achieving low-energy configurations as compared to annealing above the Curie temperature. At this thermally active temperature of 325 K, the ensemble of ferromagnetic nanoislands explore their energy landscape over time and eventually transition to lower energy states as compared to the frozen-in configurations obtained upon cooling from above the Curie temperature. Thus, this materials system allows for a facile method to systematically study thermal evolution of artificial spin ice arrays of nanoislands at temperatures modestly above room temperature.

  3. Abstract computation in schizophrenia detection through artificial neural network based systems.

    Science.gov (United States)

    Cardoso, L; Marins, F; Magalhães, R; Marins, N; Oliveira, T; Vicente, H; Abelha, A; Machado, J; Neves, J

    2015-01-01

    Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

  4. Identification of time-varying structural dynamic systems - An artificial intelligence approach

    Science.gov (United States)

    Glass, B. J.; Hanagud, S.

    1992-01-01

    An application of the artificial intelligence-derived methodologies of heuristic search and object-oriented programming to the problem of identifying the form of the model and the associated parameters of a time-varying structural dynamic system is presented in this paper. Possible model variations due to changes in boundary conditions or configurations of a structure are organized into a taxonomy of models, and a variant of best-first search is used to identify the model whose simulated response best matches that of the current physical structure. Simulated model responses are verified experimentally. An output-error approach is used in a discontinuous model space, and an equation-error approach is used in the parameter space. The advantages of the AI methods used, compared with conventional programming techniques for implementing knowledge structuring and inheritance, are discussed. Convergence conditions and example problems have been discussed. In the example problem, both the time-varying model and its new parameters have been identified when changes occur.

  5. Treatment of hyperthyroidism complicated with severe hepatitis by 131I and artificial liver support system

    International Nuclear Information System (INIS)

    Hu Hui; Deng Haoyu; Li Xinhui; Liang Changhua; Zhang Yangde

    2006-01-01

    Objective: To assess the clinical application of 131 I and artificial liver support system (ALSS) in the treatment of hyperthyroidism complicated with severe hepatitis. Methods: Forty-three hyperthyroidism patients complicated with severe hepatitis were divided into two groups: 18 cases treated with anti-thyroid drugs (ATD) as group A, and 25 cases with 131 I therapy as group B, the group B was further divided into: 12 cases were treated without ALSS as group B1, while 13 cases with ALSS as in group B2. The cure and improved rates were compared between group A and B, and the cure rates were compared between group B1 and B2, respectively. Moreover, the changes of serum level of thyroid and liver function indexes before and 1 week after each ALSS therapy were observed. Results: The cure and improved rate of group B (96.0%) was significantly higher than that of group A (61.1%), and the cure rate of group B2 (84.6%) was significantly higher than that of group B1 (33.3%, P 3 , FT 4 , total bilirubin (TBIL), direct bilirubin (DBIL), aspartate aminotransferase (AST) and alanine aminotransferase (ALT) improved obviously after ALSS therapy (P 131 I is more effective. Besides, ALSS is safe, and it can improve cure rate. (authors)

  6. Optimum Assembly Sequence Planning System Using Discrete Artificial Bee Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Özkan Özmen

    2018-01-01

    Full Text Available Assembly refers both to the process of combining parts to create a structure and to the product resulting therefrom. The complexity of this process increases with the number of pieces in the assembly. This paper presents the assembly planning system design (APSD program, a computer program developed based on a matrix-based approach and the discrete artificial bee colony (DABC algorithm, which determines the optimum assembly sequence among numerous feasible assembly sequences (FAS. Specifically, the assembly sequences of three-dimensional (3D parts prepared in the computer-aided design (CAD software AutoCAD are first coded using the matrix-based methodology and the resulting FAS are assessed and the optimum assembly sequence is selected according to the assembly time optimisation criterion using DABC. The results of comparison of the performance of the proposed method with other methods proposed in the literature verify its superiority in finding the sequence with the lowest overall time. Further, examination of the results of application of APSD to assemblies consisting of parts in different numbers and shapes shows that it can select the optimum sequence from among hundreds of FAS.

  7. Prediction of Groundwater Arsenic Contamination using Geographic Information System and Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Md. Moqbul Hossain

    2013-01-01

    Full Text Available Ground water arsenic contamination is a well known health and environmental problem in Bangladesh. Sources of this heavy metal are known to be geogenic, however, the processes of its release into groundwater are poorly understood phenomena. In quest of mitigation of the problem it is necessary to predict probable contamination before it causes any damage to human health. Hence our research has been carried out to find the factor relations of arsenic contamination and develop an arsenic contamination prediction model. Researchers have generally agreed that the elevated concentration of arsenic is affected by several factors such as soil reaction (pH, organic matter content, geology, iron content, etc. However, the variability of concentration within short lateral and vertical intervals, and the inter-relationships of variables among themselves, make the statistical analyses highly non-linear and difficult to converge with a meaningful relationship. Artificial Neural Networks (ANN comes in handy for such a black box type problem. This research uses Back propagation Neural Networks (BPNN to train and validate the data derived from Geographic Information System (GIS spatial distribution grids. The neural network architecture with (6-20-1 pattern was able to predict the arsenic concentration with reasonable accuracy.

  8. An Artificial Neural Network for Analyzing Overall Uniformity in Outdoor Lighting Systems

    Directory of Open Access Journals (Sweden)

    Antonio del Corte-Valiente

    2017-02-01

    Full Text Available Street lighting installations are an essential service for modern life due to their capability of creating a welcoming feeling at nighttime. Nevertheless, several studies have highlighted that it is possible to improve the quality of the light significantly improving the uniformity of the illuminance. The main difficulty arises when trying to improve some of the installation’s characteristics based only on statistical analysis of the light distribution. This paper presents a new algorithm that is able to obtain the overall illuminance uniformity in order to improve this sort of installations. To develop this algorithm it was necessary to perform a detailed study of all the elements which are part of street lighting installations. Because classification is one of the most important tasks in the application areas of artificial neural networks, we compared the performances of six types of training algorithms in a feed forward neural network for analyzing the overall uniformity in outdoor lighting systems. We found that the best algorithm that minimizes the error is “Levenberg-Marquardt back-propagation”, which approximates the desired output of the training pattern. By means of this kind of algorithm, it is possible to help to lighting professionals optimize the quality of street lighting installations.

  9. Abstract Computation in Schizophrenia Detection through Artificial Neural Network Based Systems

    Directory of Open Access Journals (Sweden)

    L. Cardoso

    2015-01-01

    Full Text Available Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason of defective information.

  10. Diagnosing tuberculosis with a novel support vector machine-based artificial immune recognition system.

    Science.gov (United States)

    Saybani, Mahmoud Reza; Shamshirband, Shahaboddin; Golzari Hormozi, Shahram; Wah, Teh Ying; Aghabozorgi, Saeed; Pourhoseingholi, Mohamad Amin; Olariu, Teodora

    2015-04-01

    Tuberculosis (TB) is a major global health problem, which has been ranked as the second leading cause of death from an infectious disease worldwide. Diagnosis based on cultured specimens is the reference standard, however results take weeks to process. Scientists are looking for early detection strategies, which remain the cornerstone of tuberculosis control. Consequently there is a need to develop an expert system that helps medical professionals to accurately and quickly diagnose the disease. Artificial Immune Recognition System (AIRS) has been used successfully for diagnosing various diseases. However, little effort has been undertaken to improve its classification accuracy. In order to increase the classification accuracy of AIRS, this study introduces a new hybrid system that incorporates a support vector machine into AIRS for diagnosing tuberculosis. Patient epacris reports obtained from the Pasteur laboratory of Iran were used as the benchmark data set, with the sample size of 175 (114 positive samples for TB and 60 samples in the negative group). The strategy of this study was to ensure representativeness, thus it was important to have an adequate number of instances for both TB and non-TB cases. The classification performance was measured through 10-fold cross-validation, Root Mean Squared Error (RMSE), sensitivity and specificity, Youden's Index, and Area Under the Curve (AUC). Statistical analysis was done using the Waikato Environment for Knowledge Analysis (WEKA), a machine learning program for windows. With an accuracy of 100%, sensitivity of 100%, specificity of 100%, Youden's Index of 1, Area Under the Curve of 1, and RMSE of 0, the proposed method was able to successfully classify tuberculosis patients. There have been many researches that aimed at diagnosing tuberculosis faster and more accurately. Our results described a model for diagnosing tuberculosis with 100% sensitivity and 100% specificity. This model can be used as an additional tool for

  11. Thermodynamic Optimization of a Geothermal- Based Organic Rankine Cycle System Using an Artificial Bee Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Osman Özkaraca

    2017-10-01

    Full Text Available Geothermal energy is a renewable form of energy, however due to misuse, processing and management issues, it is necessary to use the resource more efficiently. To increase energy efficiency, energy systems engineers carry out careful energy control studies and offer alternative solutions. With this aim, this study was conducted to improve the performance of a real operating air-cooled organic Rankine cycle binary geothermal power plant (GPP and its components in the aspects of thermodynamic modeling, exergy analysis and optimization processes. In-depth information is obtained about the exergy (maximum work a system can make, exergy losses and destruction at the power plant and its components. Thus the performance of the power plant may be predicted with reasonable accuracy and better understanding is gained for the physical process to be used in improving the performance of the power plant. The results of the exergy analysis show that total exergy production rate and exergy efficiency of the GPP are 21 MW and 14.52%, respectively, after removing parasitic loads. The highest amount of exergy destruction occurs, respectively, in condenser 2, vaporizer HH2, condenser 1, pumps 1 and 2 as components requiring priority performance improvement. To maximize the system exergy efficiency, the artificial bee colony (ABC is applied to the model that simulates the actual GPP. Under all the optimization conditions, the maximum exergy efficiency for the GPP and its components is obtained. Two of these conditions such as Case 4 related to the turbine and Case 12 related to the condenser have the best performance. As a result, the ABC optimization method provides better quality information than exergy analysis. Based on the guidance of this study, the performance of power plants based on geothermal energy and other energy resources may be improved.

  12. Excitation energy transfer in natural photosynthetic complexes and chlorophyll trefoils: hole-burning and single complex/trefoil spectroscopic studies

    Energy Technology Data Exchange (ETDEWEB)

    Ryszard Jankowiak, Kansas State University, Department of Chemistry, CBC Bldg., Manhattan KS, 66505; Phone: (785) 532-6785

    2012-09-12

    In this project we studied both natural photosynthetic antenna complexes and various artificial systems (e.g. chlorophyll (Chl) trefoils) using high resolution hole-burning (HB) spectroscopy and excitonic calculations. Results obtained provided more insight into the electronic (excitonic) structure, inhomogeneity, electron-phonon coupling strength, vibrational frequencies, and excitation energy (or electron) transfer (EET) processes in several antennas and reaction centers. For example, our recent work provided important constraints and parameters for more advanced excitonic calculations of CP43, CP47, and PSII core complexes. Improved theoretical description of HB spectra for various model systems offers new insight into the excitonic structure and composition of low-energy absorption traps in very several antenna protein complexes and reaction centers. We anticipate that better understanding of HB spectra obtained for various photosynthetic complexes and their simultaneous fits with other optical spectra (i.e. absorption, emission, and circular dichroism spectra) provides more insight into the underlying electronic structures of these important biological systems. Our recent progress provides a necessary framework for probing the electronic structure of these systems via Hole Burning Spectroscopy. For example, we have shown that the theoretical description of non-resonant holes is more restrictive (in terms of possible site energies) than those of absorption and emission spectra. We have demonstrated that simultaneous description of linear optical spectra along with HB spectra provides more realistic site energies. We have also developed new algorithms to describe both nonresonant and resonant hole-burn spectra using more advanced Redfield theory. Simultaneous description of various optical spectra for complex biological system, e.g. artificial antenna systems, FMO protein complexes, water soluble protein complexes, and various mutants of reaction centers

  13. Artificial Neural Network System to Predict the Postoperative Outcome of Percutaneous Nephrolithotomy.

    Science.gov (United States)

    Aminsharifi, Alireza; Irani, Dariush; Pooyesh, Shima; Parvin, Hamid; Dehghani, Sakineh; Yousofi, Khalilolah; Fazel, Ebrahim; Zibaie, Fatemeh

    2017-05-01

    To construct, train, and apply an artificial neural network (ANN) system for prediction of different outcome variables of percutaneous nephrolithotomy (PCNL). We calculated predictive accuracy, sensitivity, and precision for each outcome variable. During the study period, all adult patients who underwent PCNL at our institute were enrolled in the study. Preoperative and postoperative variables were recorded, and stone-free status was assessed perioperatively with computed tomography scans. MATLAB software was used to design and train the network in a feed forward back-propagation error adjustment scheme. Preoperative and postoperative data from 200 patients (training set) were used to analyze the effect and relative relevance of preoperative values on postoperative parameters. The validated adequately trained ANN was used to predict postoperative outcomes in the subsequent 254 adult patients (test set) whose preoperative values were serially fed into the system. To evaluate system accuracy in predicting each postoperative variable, predicted values were compared with actual outcomes. Two hundred fifty-four patients (155 [61%] males) were considered the test set. Mean stone burden was 6702.86 ± 381.6 mm 3 . Overall stone-free rate was 76.4%. Fifty-four out of 254 patients (21.3%) required ancillary procedures (shockwave lithotripsy 5.9%, transureteral lithotripsy 10.6%, and repeat PCNL 4.7%). The accuracy and sensitivity of the system in predicting different postoperative variables ranged from 81.0% to 98.2%. As a complex nonlinear mathematical model, our ANN system is an interconnected data mining tool, which prospectively analyzes and "learns" the relationships between variables. The accuracy and sensitivity of the system for predicting the stone-free rate, the need for blood transfusion, and post-PCNL ancillary procedures ranged from 81.0% to 98.2%.The stone burden and the stone morphometry were among the most significant preoperative characteristics that

  14. 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…

  15. Artificial fish skin of self-powered micro-electromechanical systems hair cells for sensing hydrodynamic flow phenomena.

    Science.gov (United States)

    Asadnia, Mohsen; Kottapalli, Ajay Giri Prakash; Miao, Jianmin; Warkiani, Majid Ebrahimi; Triantafyllou, Michael S

    2015-10-06

    Using biological sensors, aquatic animals like fishes are capable of performing impressive behaviours such as super-manoeuvrability, hydrodynamic flow 'vision' and object localization with a success unmatched by human-engineered technologies. Inspired by the multiple functionalities of the ubiquitous lateral-line sensors of fishes, we developed flexible and surface-mountable arrays of micro-electromechanical systems (MEMS) artificial hair cell flow sensors. This paper reports the development of the MEMS artificial versions of superficial and canal neuromasts and experimental characterization of their unique flow-sensing roles. Our MEMS flow sensors feature a stereolithographically fabricated polymer hair cell mounted on Pb(Zr(0.52)Ti(0.48))O3 micro-diaphragm with floating bottom electrode. Canal-inspired versions are developed by mounting a polymer canal with pores that guide external flows to the hair cells embedded in the canal. Experimental results conducted employing our MEMS artificial superficial neuromasts (SNs) demonstrated a high sensitivity and very low threshold detection limit of 22 mV/(mm s(-1)) and 8.2 µm s(-1), respectively, for an oscillating dipole stimulus vibrating at 35 Hz. Flexible arrays of such superficial sensors were demonstrated to localize an underwater dipole stimulus. Comparative experimental studies revealed a high-pass filtering nature of the canal encapsulated sensors with a cut-off frequency of 10 Hz and a flat frequency response of artificial SNs. Flexible arrays of self-powered, miniaturized, light-weight, low-cost and robust artificial lateral-line systems could enhance the capabilities of underwater vehicles. © 2015 The Author(s).

  16. Bibliography: Artificial Intelligence.

    Science.gov (United States)

    Smith, Richard L.

    1986-01-01

    Annotates reference material on artificial intelligence, mostly at an introductory level, with applications to education and learning. Topics include: (1) programing languages; (2) expert systems; (3) language instruction; (4) tutoring systems; and (5) problem solving and reasoning. (JM)

  17. Evaluation of an artificial intelligence guided inverse planning system: Clinical case study

    International Nuclear Information System (INIS)

    Yan Hui; Yin Fangfang; Willett, Christopher

    2007-01-01

    Purpose: An artificial intelligence (AI) guided method for parameter adjustment of inverse planning was implemented on a commercial inverse treatment planning system. For evaluation purpose, four typical clinical cases were tested and the results from both plans achieved by automated and manual methods were compared. Methods and materials: The procedure of parameter adjustment mainly consists of three major loops. Each loop is in charge of modifying parameters of one category, which is carried out by a specially customized fuzzy inference system. A physician prescribed multiple constraints for a selected volume were adopted to account for the tradeoff between prescription dose to the PTV and dose-volume constraints for critical organs. The searching process for an optimal parameter combination began with the first constraint, and proceeds to the next until a plan with acceptable dose was achieved. The initial setup of the plan parameters was the same for each case and was adjusted independently by both manual and automated methods. After the parameters of one category were updated, the intensity maps of all fields were re-optimized and the plan dose was subsequently re-calculated. When final plan arrived, the dose statistics were calculated from both plans and compared. Results: For planned target volume (PTV), the dose for 95% volume is up to 10% higher in plans using the automated method than those using the manual method. For critical organs, an average decrease of the plan dose was achieved. However, the automated method cannot improve the plan dose for some critical organs due to limitations of the inference rules currently employed. For normal tissue, there was no significant difference between plan doses achieved by either automated or manual method. Conclusion: With the application of AI-guided method, the basic parameter adjustment task can be accomplished automatically and a comparable plan dose was achieved in comparison with that achieved by the manual

  18. Cooperative research and development for artificial intelligence based reactor diagnostic system

    International Nuclear Information System (INIS)

    Reifman, J.; Wei, T.Y.C.; Abboud, R.G.; Chasensky, T.M.

    1994-01-01

    Artificial Intelligence (AI) techniques in the form of knowledge-based Expert Systems (ESs) have been proposed to provide on-line decision-making support for plant operators during both normal and emergency conditions. However, in spite of the great interest in these advanced techniques, their application in the diagnosis of large-scale processes has not yet reached its full potential because of limitations of the knowledge base. These limitations include problems with knowledge acquisition and the use of an event-oriented approach for process diagnosis. The knowledge base of process diagnosis ESs is generally acquired in a heuristic fashion through empirical associations between plant symptoms and component malfunctions with no reliance on fundamental physical principles. This nonsystematic construction of the knowledge base causes, among other problems, the encoded information to be biased and limited towards the developer's own experience and judgmental knowledge. The use of an event-oriented approach for process diagnosis requires the developer of the knowledge base to anticipate and formulate rules to cover every conceivable plant situation. In addition to yielding a large knowledge base, an undesirable characteristic for an on-line real-time advisory system, an event-oriented approach for diagnosis of large and complex thermal-hydraulic (T-H) based processes cannot guarantee functional completeness and is likely to fail under unanticipated circumstances. Hence, these limitations preclude an effective verification and validation of the knowledge base which is required in industrial applications. In contrast to the heuristic construction of a rigid knowledge base that uses an event-oriented approach for process diagnosis, the authors propose a different approach that involves the systematic construction of a hierarchical knowledge base with two levels

  19. Artificial neural systems using memristive synapses and nano-crystalline silicon thin-film transistors

    Science.gov (United States)

    Cantley, Kurtis D.

    Future computer systems will not rely solely on digital processing of inputs from well-defined data sets. They will also be required to perform various computational tasks using large sets of ill-defined information from the complex environment around them. The most efficient processor of this type of information known today is the human brain. Using a large number of primitive elements (˜1010 neurons in the neocortex) with high parallel connectivity (each neuron has ˜104 synapses), brains have the remarkable ability to recognize and classify patterns, predict outcomes, and learn from and adapt to incredibly diverse sets of problems. A reasonable goal in the push to increase processing power of electronic systems would thus be to implement artificial neural networks in hardware that are compatible with today's digital processors. This work focuses on the feasibility of utilizing non-crystalline silicon devices in neuromorphic electronics. Hydrogenated amorphous silicon (a-Si:H) nanowire transistors with Schottky barrier source/drain junctions, as well as a-Si:H/Ag resistive switches are fabricated and characterized. In the transistors, it is found that the on-current scales linearly with the effective width W eff of the channel nanowire array down to at least 20 nm. The solid-state electrolyte resistive switches (memristors) are shown to exhibit the proper current-voltage hysteresis. SPICE models of similar devices are subsequently developed to investigate their performance in neural circuits. The resulting SPICE simulations demonstrate spiking properties and synaptic learning rules that are incredibly similar to those in biology. Specifically, the neuron circuits can be designed to mimic the firing characteristics of real neurons, and Hebbian learning rules are investigated. Finally, some applications are presented, including associative learning analogous to the classical conditioning experiments originally performed by Pavlov, and frequency and pattern

  20. Evaluation of an artificial intelligence guided inverse planning system: clinical case study.

    Science.gov (United States)

    Yan, Hui; Yin, Fang-Fang; Willett, Christopher

    2007-04-01

    An artificial intelligence (AI) guided method for parameter adjustment of inverse planning was implemented on a commercial inverse treatment planning system. For evaluation purpose, four typical clinical cases were tested and the results from both plans achieved by automated and manual methods were compared. The procedure of parameter adjustment mainly consists of three major loops. Each loop is in charge of modifying parameters of one category, which is carried out by a specially customized fuzzy inference system. A physician prescribed multiple constraints for a selected volume were adopted to account for the tradeoff between prescription dose to the PTV and dose-volume constraints for critical organs. The searching process for an optimal parameter combination began with the first constraint, and proceeds to the next until a plan with acceptable dose was achieved. The initial setup of the plan parameters was the same for each case and was adjusted independently by both manual and automated methods. After the parameters of one category were updated, the intensity maps of all fields were re-optimized and the plan dose was subsequently re-calculated. When final plan arrived, the dose statistics were calculated from both plans and compared. For planned target volume (PTV), the dose for 95% volume is up to 10% higher in plans using the automated method than those using the manual method. For critical organs, an average decrease of the plan dose was achieved. However, the automated method cannot improve the plan dose for some critical organs due to limitations of the inference rules currently employed. For normal tissue, there was no significant difference between plan doses achieved by either automated or manual method. With the application of AI-guided method, the basic parameter adjustment task can be accomplished automatically and a comparable plan dose was achieved in comparison with that achieved by the manual method. Future improvements to incorporate case