WorldWideScience

Sample records for artificial photosynthetic systems

  1. Challenges and Perspectives in Designing Artificial Photosynthetic Systems.

    Science.gov (United States)

    Zhou, Han; Yan, Runyu; Zhang, Di; Fan, Tongxiang

    2016-07-11

    The development of artificial photosynthetic systems for water splitting and CO2 reduction on a large scale for practical applications is the ultimate goal towards worldwide sustainability. This Concept highlights the state-of-the-art research trends of artificial photosynthesis concepts and designs from some new perspectives. Particularly, it is focused on five important aspects for the design of promising artificial photosynthetic systems: 1) catalyst development, 2) architecture design, 3) device buildup 4) mechanism exploration, and 5) theoretical investigations. Some typical progress and challenges, the most significant milestones achieved to date, as well as possible future directions are illustrated and discussed. This Concept article presents a selection of new developments to highlight new trends and possibilities, main barriers, or challenges; with this, we hope to inspire more advances in the field of artificial photosynthesis.

  2. 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.

  3. 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 systems are found in nature with the process of photosynthesis. Previous work has shown that photosynthetic light harvesting material can be incorporated into artificial vesicles called Pheroid. In this study researchers are characterising the level...

  4. 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

  5. Energy conversion at liquid/liquid interfaces: artificial photosynthetic systems

    Science.gov (United States)

    Volkov, A. G.; Gugeshashvili, M. I.; Deamer, D. W.

    1995-01-01

    This chapter focuses on multielectron reactions in organized assemblies of molecules at the liquid/liquid interface. We describe the thermodynamic and kinetic parameters of such reactions, including the structure of the reaction centers, charge movement along the electron transfer pathways, and the role of electric double layers in artificial photosynthesis. Some examples of artificial photosynthesis at the oil/water interface are considered, including water photooxidation to the molecular oxygen, oxygen photoreduction, photosynthesis of amphiphilic compounds and proton evolution by photochemical processes.

  6. Excitonic and vibrational coherence in artificial photosynthetic systems studied by negative-time ultrafast laser spectroscopy.

    Science.gov (United States)

    Han, Dongjia; Xue, Bing; Du, Juan; Kobayashi, Takayoshi; Miyatake, Tomohiro; Tamiaki, Hitoshi; Xing, Xin; Yuan, Wei; Li, Yanyan; Leng, Yuxin

    2016-09-21

    Quantum coherences between excitonic states are believed to have a substantial impact on excitation energy transfer in photosynthetic systems. Here, the excitonic and vibrational coherence relaxation dynamics of artificially synthetic chlorosomes are studied by a sub 7 fs negative-time-delay laser spectroscopy at room temperature. The results provide direct evidence for the quantum coherence of the excitonic dephasing time of 23 ± 1 fs at physiologically relevant temperatures, which is significant in the initial step of energy transfer in chlorosome or chlorosome-like photosynthetic systems. Meanwhile, coherent molecular vibrations in the excited state are also detected without the effect of wave-packet motion in the ground state, which shows that the excited state wave-packet motion contributes greatly to the vibrational modes of ∼150 and ∼1340 cm(-1) in artificial chlorosome systems.

  7. Studies of zeolite-based artificial photosynthetic systems

    Science.gov (United States)

    Zhang, Haoyu

    used as a model system. A MV2+-loaded zeolite was treated with disilazane reagents under ambient conditions and the grafting of siloxy functionality on the zeolite was confirmed by infrared, NMR spectroscopy and elemental analysis. Surface modification of MV2+-loaded zeolites encapsulated the guest molecules in the zeolite cages and release of MV2+ by ion-exchange with sodium ions was studied. The total amount of MV2+ released was dependent on the concentration of Na+ in solution, and was similar for the derivatized and underivatized samples. In the absence of surface modification, equilibration occurred within 20 minutes, whereas with surface modification, the equilibration time was extended to 7 days. These kinetics are reflected in the effective diffusion coefficients (D) of MV2+, with D = 1.2 x 10-15 cm 2 s-1 for derivatized zeolite Y and D = 0.2 -1.1 x 10-7 cm2 s-1 for the underivatized sample. (Abstract shortened by UMI.)

  8. Self-Assembly Strategies for Integrating Light Harvesting and Charge Separation in Artificial Photosynthetic Systems

    Energy Technology Data Exchange (ETDEWEB)

    Wasielewski, Michael R. (NWU)

    2017-02-15

    In natural photosynthesis, organisms optimize solar energy conversion through organized assemblies of photofunctional chromophores and catalysts within proteins that provide specifically tailored environments for chemical reactions. As with their natural counterparts, artificial photosynthetic systems for practical solar fuels production must collect light energy, separate charge, and transport charge to catalytic sites where multielectron redox processes will occur. While encouraging progress has been made on each aspect of this complex problem, researchers have not yet developed self-ordering and self-assembling components and the tailored environments necessary to realize a fully-functional artificial system. Previously researchers have used complex, covalent molecular systems comprised of chromophores, electron donors, and electron acceptors to mimic both the light-harvesting and the charge separation functions of photosynthetic proteins. These systems allow for study of the dependencies of electron transfer rate constants on donor?acceptor distance and orientation, electronic interaction, and the free energy of the reaction. The most useful and informative systems are those in which structural constraints control both the distance and the orientation between the electron donors and acceptors. Self-assembly provides a facile means for organizing large numbers of molecules into supramolecular structures that can bridge length scales from nanometers to macroscopic dimensions. The resulting structures must provide pathways for migration of light excitation energy among antenna chromophores, and from antennas to reaction centers. They also must incorporate charge conduits, that is, molecular 'wires' that can efficiently move electrons and holes between reaction centers and catalytic sites. The central scientific challenge is to develop small, functional building blocks with a minimum number of covalent linkages, which also have the appropriate molecular

  9. 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.

  10. 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

  11. Triplet excitons in natural photosynthetic and artificial light harvesting systems: Measurement and modeling

    Science.gov (United States)

    Hartzler, Daniel Allen

    Under full sunlight, unprotected (Bacterio)Chlorophyll ((B)Chl) molecules photodegrade in a matter of minutes. This is the result of the generation of highly reactive singlet oxygen (1O2) by energy transfer from the (B)Chl triplet state (3(B)Chl) to the oxygen ground state. Natural photosynthetic systems must protect themselves from 1O2, typically done by positioning carotenoids within a few angstroms of each (B)Chl molecule to quench 3(B)Chl states. Using phosphorescence spectroscopy and computational modeling, we investigated alternative, carotenoid independent, mechanisms which nature may employ to prevent 1O2 sensitization by lowering the energy of 3(B)Chl below that of 1O2. The two proposed triplet lowering mechanisms investigated were: triplet state lowering by strong pigment-pigment interactions (i.e. triplet exciton formation) and triplet state lowering by pigment-protein interactions. Possible natural examples employing these mechanisms are two structures found in green sulfur bacteria: the chlorosome (an antenna containing ~100000 coupled BChl c, d, or e molecules with unexpectedly high photostability) and the Fenna-Matthews-Olson (FMO) complex (an auxiliary antenna containing eight seemingly unprotected BChl a molecules). Measurements performed on linear aggregates of the dye perylene diimide (PDI) show that triplet exciton formation does reduce the triplet state energy. However, direct measurement of triplet state energies for the chlorosome and FMO complex proved experimentally difficult, thus an alternative approach was used to calculate these energies using empirical and excitonic models. Since the use of excitonic modeling requires knowledge of both the pigment site energies and the pigment-pigment interactions (i.e. couplings), work was performed to catalog the monomeric singlet and triplet state energies of all known natural (B)Chl pigments by direct measurement or computational modeling and to characterize the triplet-triplet (T-T) coupling in

  12. 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

    2013-04-01

    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.

  13. 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

  14. Artificial photosynthetic reaction centers coupled to light-harvesting antennas.

    Science.gov (United States)

    Ghosh, Pulak Kumar; Smirnov, Anatoly Yu; Nori, Franco

    2011-12-01

    We analyze a theoretical model for energy and electron transfer in an artificial photosynthetic system. The photosystem consists of a molecular triad (i.e., with a donor, a photosensitive unit, and an acceptor) coupled to four accessory light-harvesting-antenna pigments. The resonant energy transfer from the antennas to the artificial reaction center (the molecular triad) is described here by the Förster mechanism. We consider two different kinds of arrangements of the accessory light-harvesting pigments around the reaction center. The first arrangement allows direct excitation transfer to the reaction center from all the surrounding pigments. The second configuration transmits energy via a cascade mechanism along a chain of light-harvesting chromophores, where only one chromophore is connected to the reaction center. We show that the artificial photosynthetic system using the cascade energy transfer absorbs photons in a broader wavelength range and converts their energy into electricity with a higher efficiency than the system based on direct couplings between all the antenna chromophores and the reaction center.

  15. Studying the oxidation of water to molecular oxygen in photosynthetic and artificial systems by time-resolved membrane-inlet mass spectrometry

    Directory of Open Access Journals (Sweden)

    Dmitriy eShevela

    2013-11-01

    Full Text Available Monitoring isotopic compositions of gaseous products (e.g., H2, O2 and CO2 by time-resolved isotope-ratio membrane-inlet mass spectrometry (TR-IR-MIMS is widely used for kinetic and functional analyses in photosynthesis research. In particular, in combination with isotopic labelling, TR-MIMS became an essential and powerful research tool for the study of the mechanism of photosynthetic water-oxidation to molecular oxygen catalyzed by the water-oxidizing complex of photosystem II. Moreover, recently, the TR-MIMS and 18O-labeling approach was successfully applied for testing newly developed catalysts for artificial water-splitting and provided important insight about the mechanism and pathways of O2 formation. In this mini-review we summarize these results and provide a brief introduction into key aspects of the TR-MIMS technique and its perspectives for future studies of the enigmatic water-splitting chemistry.

  16. Hydrogen photoproduction by use of photosynthetic organisms and biomimetic systems.

    Science.gov (United States)

    Allakhverdiev, Suleyman I; Kreslavski, Vladimir D; Thavasi, Velmurugan; Zharmukhamedov, Sergei K; Klimov, Vyacheslav V; Nagata, Toshi; Nishihara, Hiroshi; Ramakrishna, Seeram

    2009-02-01

    Hydrogen can be important clean fuel for future. Among different technologies for hydrogen production, oxygenic natural and artificial photosyntheses using direct photochemistry in synthetic complexes have a great potential to produce hydrogen, since both use clean and cheap sources: water and solar energy. Artificial photosynthesis is one way to produce hydrogen from water using sunlight by employing biomimetic complexes. However, splitting of water into protons and oxygen is energetically demanding and chemically difficult. In oxygenic photosynthetic microorganisms such as algae and cyanobacteria, water is split into electrons and protons, which during primary photosynthetic process are redirected by photosynthetic electron transport chain, and ferredoxin, to the hydrogen-producing enzymes hydrogenase or nitrogenase. By these enzymes, e- and H+ recombine and form gaseous hydrogen. Biohydrogen activity of hydrogenase can be very high but it is extremely sensitive to photosynthetic O2. In contrast, nitrogenase is insensitive to O2, but has lower activity. At the moment, the efficiency of biohydrogen production is low. However, theoretical expectations suggest that the rates of photon conversion efficiency for H2 bioproduction can be high enough (>10%). Our review examines the main pathways of H2 photoproduction by using of photosynthetic organisms and biomimetic photosynthetic systems.

  17. Photosynthetic acclimation responses of maize seedlings grown under artificial laboratory light gradients mimicking natural canopy conditions

    Directory of Open Access Journals (Sweden)

    Matthias eHirth

    2013-09-01

    Full Text Available In this study we assessed the ability of the C4 plant maize to perform long-term photosynthetic acclimation in an artificial light quality system previously used for analysing short-term and long-term acclimation responses (LTR in C3 plants. We aimed to test if this light system could be used as a tool for analysing redox-regulated acclimation processes in maize seedlings. Photosynthetic parameters obtained from maize samples harvested in the field were used as control. The results indicated that field grown maize performed a pronounced LTR with significant differences between the top and the bottom levels of the plant stand corresponding to the strong light gradients occurring in it. We compared these data to results obtained from maize seedlings grown under artificial light sources preferentially exciting either photosystem II or photosystem I. In C3 plants, this light system induces redox signals within the photosynthetic electron transport chain which trigger state transitions and differential phosphorylation of light harvesting complexes of photosystem II (LHCII. The LTR to these redox signals induces changes in the accumulation of plastid psaA transcripts, in chlorophyll (Chl fluorescence values Fs/Fm, in Chl a/b ratios and in transient starch accumulation in C3 plants. Maize seedlings grown in this light system exhibited a pronounced ability to perform both short-term and long-term acclimation at the level of psaA transcripts, Chl fluorescence values Fs/Fm and Chl a/b ratios. Interestingly, maize seedlings did not exhibit redox-controlled variations of starch accumulation probably because of its specific differences in energy metabolism. In summary, the artificial laboratory light system was found to be well-suited to mimic field light conditions and provides a physiological tool for studying the molecular regulation of the LTR of maize in more detail.

  18. Photovoltaic concepts inspired by coherence effects in photosynthetic systems

    Science.gov (United States)

    Brédas, Jean-Luc; Sargent, Edward H.; Scholes, Gregory D.

    2017-01-01

    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.

  19. Systemic regulation of photosynthetic function in field-grown sorghum.

    Science.gov (United States)

    Li, Tao; Liu, Yujun; Shi, Lei; Jiang, Chuangdao

    2015-09-01

    The photosynthetic characteristics of developing leaves of plants grown under artificial conditions are, to some extent, regulated systemically by mature leaves; however, whether systemic regulation of photosynthesis occurs in field-grown crops is unclear. To explore this question, we investigated the effects of planting density on growth characteristics, gas exchange, leaf nitrogen concentration and chlorophyll a fluorescence in field-grown sorghum (Sorghum bicolor L.). Our results showed that close planting resulted in a marked decline in light intensity in lower canopy. Sorghum plants grown at a high planting density had lower net photosynthetic rate (Pn), stomatal conductance (Gs), and transpiration rate (E) than plants grown at a low planting density. Moreover, in the absence of mineral deficiency, close planting induced a slight increase in leaf nitrogen concentration. The decreased photosynthesis in leaves of the lower canopy at high planting density was caused mainly by the low light. However, newly developed leaves exposed to high light in the upper canopy of plants grown at high planting density also exhibited a distinct decline in photosynthesis relative to plants grown at low planting density. Based on these results, the photosynthetic function of the newly developed leaves in the upper canopy was not determined fully by their own high light environment. Accordingly, we suggest that the photosynthetic function of newly developed leaves in the upper canopy of field-grown sorghum plants is regulated systemically by the lower canopy leaves. The differences in systemic regulation of photosynthesis were also discussed between field conditions and artificial conditions.

  20. Designing artificial photosynthetic devices using hybrid organic-inorganic modules based on polyoxometalates.

    Science.gov (United States)

    Symes, Mark D; Cogdell, Richard J; Cronin, Leroy

    2013-08-13

    Artificial photosynthesis aims at capturing solar energy and using it to produce storable fuels. However, while there is reason to be optimistic that such approaches can deliver higher energy conversion efficiencies than natural photosynthetic systems, many serious challenges remain to be addressed. Perhaps chief among these is the issue of device stability. Almost all approaches to artificial photosynthesis employ easily oxidized organic molecules as light harvesters or in catalytic centres, frequently in solution with highly oxidizing species. The 'elephant in the room' in this regard is that oxidation of these organic moieties is likely to occur at least as rapidly as oxidation of water, meaning that current device performance is severely curtailed. Herein, we discuss one possible solution to this problem: using self-assembling organic-polyoxometalate hybrid structures to produce compartments inside which the individual component reactions of photosynthesis can occur without such a high incidence of deleterious side reactions.

  1. Artificial Photosynthetic Reaction Center Exhibiting Acid-Responsive Regulation of Photoinduced Charge Separation

    Energy Technology Data Exchange (ETDEWEB)

    Pahk, Ian [Arizona State Univ., Tempe, AZ (United States). School of Molecular Sciences; Kodis, Gerdenis [Arizona State Univ., Tempe, AZ (United States). School of Molecular Sciences; Fleming, Graham R. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Molecular Biophysics and Integrated Bioimaging Division; Univ. of California, Berkeley, CA (United States). Dept. of Chemistry and QB3 Inst.; Moore, Thomas A. [Arizona State Univ., Tempe, AZ (United States). School of Molecular Sciences; Moore, Ana L. [Arizona State Univ., Tempe, AZ (United States). School of Molecular Sciences; Gust, Devens [Arizona State Univ., Tempe, AZ (United States). School of Molecular Sciences

    2016-09-16

    Charge separation (CS) is the primary light-driven reaction in photosynthesis whereas onphotochemical quenching (NPQ) is a photoprotective regulatory mechanism employed by many photosynthetic organisms to dynamically modulate energy flow within the photosynthetic apparatus in response to fluctuating light conditions. Activated by decreases in lumen pH produced during periods of high photon flux, NPQ induces rapid thermal dissipation of excess excitation energy. As a result, the rate of CS decreases, thereby limiting the accumulation of potentially deleterious reactive intermediates and byproducts. In this article, a molecular triad that functionally mimics the effects of NPQ associated with an artificial photosynthetic reaction center is described. Steady-state absorption and emission, time-resolved fluorescence, and transient absorption spectroscopies have been used to demonstrate a 1 order of magnitude reduction in the CS quantum yield via reversible protonation of an excited-state-quenching molecular switch moiety. As in the natural system, the populations of unquenched and quenched states and therefore the overall yields of CS were found to be dependent on acid concentration.

  2. Hybrid system of semiconductor and photosynthetic protein.

    Science.gov (United States)

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

    2014-08-29

    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.

  3. 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.

  4. Photovoltaic concepts inspired by coherence effects in photosynthetic systems

    KAUST Repository

    Brédas, 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.

  5. Bimodal intramolecular excitation energy transfer in a multichromophore photosynthetic model system: hybrid fusion proteins comprising natural phycobilin- and artificial chlorophyll-binding domains.

    Science.gov (United States)

    Zeng, Xiao-Li; Tang, Kun; Zhou, Nan; Zhou, Ming; Hou, Harvey J M; Scheer, Hugo; Zhao, Kai-Hong; Noy, Dror

    2013-09-11

    The phycobilisomes of cyanobacteria and red-algae are highly efficient peripheral light-harvesting complexes that capture and transfer light energy in a cascade of excitation energy transfer steps through multiple phycobilin chromophores to the chlorophylls of core photosystems. In this work, we focus on the last step of this process by constructing simple functional analogs of natural phycobilisome-photosystem complexes that are based on bichromophoric protein complexes comprising a phycobilin- and a chlorophyll- or porphyrin-binding domain. The former is based on ApcE(1-240), the N-terminal chromophore-binding domain of the phycobilisome's L(CM) core-membrane linker, and the latter on HP7, a de novo designed four-helix bundle protein that was originally planned as a high-affinity heme-binding protein, analogous to b-type cytochromes. We fused a modified HP7 protein sequence to ApcEΔ, a water-soluble fragment of ApcE(1-240) obtained by excising a putative hydrophobic loop sequence of residues 77-153. HP7 was fused either to the N- or the C-terminus of ApcEΔ or inserted between residues 76 and 78, thereby replacing the native hydrophobic loop domain. We describe the assembly, spectral characteristics, and intramolecular excitation energy transfer of two unique systems: in the first, the short-wavelength absorbing zinc-mesoporphyrin is bound to the HP7 domain and serves as an excitation-energy donor to the long-wavelength absorbing phycocyanobilin bound to the ApcE domain; in the second, the short-wavelength absorbing phycoerythrobilin is bound to the ApcE domain and serves as an excitation energy donor to the long-wavelength absorbing zinc-bacteriochlorophyllide bound to the HP7 domain. All the systems that were constructed and tested exhibited significant intramolecular fluorescence resonance energy transfer with yields ranging from 21% to 50%. This confirms that our modular, covalent approach for studying EET between the cyclic and open chain tetrapyrroles is

  6. Near infrared light-driven water oxidation in a molecule-based artificial photosynthetic device using an upconversion nano-photosensitizer

    NARCIS (Netherlands)

    Liu, X.; Chen, H.C.; Kong, X.; Zhang, Y.; Tu, L.; Chang, Y.; Wu, F.; Wang, T.; Reek, J.N.H.; Brouwer, A.M.; Zhang, H.

    2015-01-01

    We provide the first demonstration of a near infrared light driven water oxidation reaction in a molecule-based artificial photosynthetic device using an upconversion nano-photosensitizer. One very attractive advantage of this system is that using NIR light irradiation does not cause significant pho

  7. Photosynthetic system in Blastochloris viridis revisited.

    Science.gov (United States)

    Konorty, Marina; Brumfeld, Vlad; Vermeglio, Andre; Kahana, Nava; Medalia, Ohad; Minsky, Abraham

    2009-06-09

    The bacterium Blastochloris viridis carries one of the simplest photosynthetic systems, which includes a single light-harvesting complex that surrounds the reaction center, membrane soluble quinones, and a soluble periplasmic protein cytochrome c(2) that shuttle between the reaction center and the bc(1) complex and act as electron carriers, as well as the ATP synthase. The close arrangement of the photosynthetic membranes in Bl. viridis, along with the extremely tight arrangement of the photosystems within these membranes, raises a fundamental question about the diffusion of the electron carriers. To address this issue, we analyzed the structure and response of the Bl. viridis photosynthetic system to various light conditions, by using a combination of electron microscopy, whole-cell cryotomography, and spectroscopic methods. We demonstrate that in response to high light intensities, the ratio of both cytochrome c(2) and bc(1) complexes to the reaction centers is increased. The shorter membrane stacks, along with the notion that the bc(1) complex is located at the highly curved edges of these stacks, result in a smaller average distance between the reaction centers and the bc(1) complexes, leading to shorter pathways of cytochrome c(2) between the two complexes. Under anaerobic conditions, the slow diffusion rate is further mitigated by keeping most of the quinone pool reduced, resulting in a concentration gradient of quinols that allows for a constant supply of theses electron carriers to the bc(1) complex.

  8. 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.

  9. Novel conducting polymer-heteropoly acid hybrid material for artificial photosynthetic membranes.

    Science.gov (United States)

    McDonald, Michael B; Freund, Michael S

    2011-04-01

    Artificial photosynthetic (AP) approaches to convert and store solar energy will require membranes capable of conducting both ions and electrons while remaining relatively transparent and chemically stable. A new approach is applied herein involving previously described in situ chemical polymerization of electronically conducting poly(3,4-ethylenedioxythiophene) (PEDOT) in the presence of proton conducting heteropoly acid (HPA) phosphomolybdic acid (PMA). The electrochemical behaviour of the PEDOT/PMA hybrid material was investigated and it was found that the conducting polymer (CP) is susceptible to irreversible oxidative processes at potentials where water is oxidized. This will be problematic in AP devices should the process occur in very close proximity to a conducting polymer-based membrane. It was found that PEDOT grants the system good electrical performance in terms of conductivity and stability over a large pH window; however, the presence of PMA was not found to provide sufficient proton conductivity. This was addressed in an additional study by tuning the ionic (and in turn, electronic) conductivity in creating composites with the proton-permselective polymer Nafion. It was found that a material of this nature with near-equal conductivity for optimal chemical conversion efficiency will consist of roughly three parts Nafion and one part PEDOT/PMA.

  10. 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

  11. Multiscale Analysis and Optimisation of Photosynthetic Solar Energy Systems

    CERN Document Server

    Ringsmuth, Andrew K

    2014-01-01

    This work asks how light harvesting in photosynthetic systems can be optimised for economically scalable, sustainable energy production. Hierarchy theory is introduced as a system-analysis and optimisation tool better able to handle multiscale, multiprocess complexities in photosynthetic energetics compared with standard linear-process analysis. Within this framework, new insights are given into relationships between composition, structure and energetics at the scale of the thylakoid membrane, and also into how components at different scales cooperate under functional objectives of the whole photosynthetic system. Combining these reductionistic and holistic analyses creates a platform for modelling multiscale-optimal, idealised photosynthetic systems in silico.

  12. Artificial Immune Systems (2010)

    CERN Document Server

    Greensmith, Julie; Aickelin, Uwe

    2010-01-01

    The human immune system has numerous properties that make it ripe for exploitation in the computational domain, such as robustness and fault tolerance, and many different algorithms, collectively termed Artificial Immune Systems (AIS), have been inspired by it. Two generations of AIS are currently in use, with the first generation relying on simplified immune models and the second generation utilising interdisciplinary collaboration to develop a deeper understanding of the immune system and hence produce more complex models. Both generations of algorithms have been successfully applied to a variety of problems, including anomaly detection, pattern recognition, optimisation and robotics. In this chapter an overview of AIS is presented, its evolution is discussed, and it is shown that the diversification of the field is linked to the diversity of the immune system itself, leading to a number of algorithms as opposed to one archetypal system. Two case studies are also presented to help provide insight into the m...

  13. Photosynthetic machineries in nano-systems.

    Science.gov (United States)

    Nagy, László; Magyar, Melinda; Szabó, Tibor; Hajdu, Kata; Giotta, Livia; Dorogi, Márta; Milano, Francesco

    2014-01-01

    Photosynthetic reaction centres are membrane-spanning proteins, found in several classes of autotroph organisms, where a photoinduced charge separation and stabilization takes place with a quantum efficiency close to unity. The protein remains stable and fully functional also when extracted and purified in detergents thereby biotechnological applications are possible, for example, assembling it in nano-structures or in optoelectronic systems. Several types of bionanocomposite materials have been assembled by using reaction centres and different carrier matrices for different purposes in the field of light energy conversion (e.g., photovoltaics) or biosensing (e.g., for specific detection of pesticides). In this review we will summarize the current status of knowledge, the kinds of applications available and the difficulties to be overcome in the different applications. We will also show possible research directions for the close future in this specific field.

  14. Artificial Immune Systems Tutorial

    CERN Document Server

    Aickelin, Uwe

    2008-01-01

    The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body as self-cells or non-self cells. It does this with the help of a distributed task force that has the intelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years. A novel computational intelligence technique, inspired by immunology, has emerged, called Artificial Immune Systems. Several concepts from the immune have been extracted an...

  15. Artificial Immune Systems

    CERN Document Server

    Aickelin, Uwe

    2009-01-01

    The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body as self-cells or non-self cells. It does this with the help of a distributed task force that has the intelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years. A novel computational intelligence technique, inspired by immunology, has emerged, called Artificial Immune Systems. Several concepts from the immune have been extracted an...

  16. Phonon-assisted excitation energy transfer in photosynthetic systems

    Science.gov (United States)

    Chen, Hao; Wang, Xin; Fang, Ai-Ping; Li, Hong-Rong

    2016-09-01

    The phonon-assisted process of energy transfer aiming at exploring the newly emerging frontier between biology and physics is an issue of central interest. This article shows the important role of the intramolecular vibrational modes for excitation energy transfer in the photosynthetic systems. Based on a dimer system consisting of a donor and an acceptor modeled by two two-level systems, in which one of them is coupled to a high-energy vibrational mode, we derive an effective Hamiltonian describing the vibration-assisted coherent energy transfer process in the polaron frame. The effective Hamiltonian reveals in the case that the vibrational mode dynamically matches the energy detuning between the donor and the acceptor, the original detuned energy transfer becomes resonant energy transfer. In addition, the population dynamics and coherence dynamics of the dimer system with and without vibration-assistance are investigated numerically. It is found that, the energy transfer efficiency and the transfer time depend heavily on the interaction strength of the donor and the high-energy vibrational mode, as well as the vibrational frequency. The numerical results also indicate that the initial state and dissipation rate of the vibrational mode have little influence on the dynamics of the dimer system. Results obtained in this article are not only helpful to understand the natural photosynthesis, but also offer an optimal design principle for artificial photosynthesis. Project supported by the National Natural Science Foundation of China (Grant No. 11174233).

  17. Modeling light-driven proton pumps in artificial photosynthetic reaction centers.

    Science.gov (United States)

    Ghosh, Pulak Kumar; Smirnov, Anatoly Yu; Nori, Franco

    2009-07-21

    We study a model of a light-induced proton pump in artificial reaction centers. The model contains a molecular triad with four electron states (i.e., one donor state, two photosensitive group states, and one acceptor state) as well as a molecular shuttle having one electron and one proton-binding sites. The shuttle diffuses between the sides of the membrane and translocates protons energetically uphill: from the negative side to the positive side of the membrane, harnessing for this purpose the energy of the electron-charge separation produced by light. Using the methods of quantum transport theory we calculate the range of light intensity and transmembrane potentials that maximize both the light-induced proton current and the energy transduction efficiency. We also study the effect of temperature on proton pumping. The light-induced proton pump in our model gives a quantum yield of proton translocation of about 55%. Thus, our results explain previous experiments on these artificial photosynthetic reaction centers.

  18. Artificial Photosynthesis: Hybrid Systems.

    Science.gov (United States)

    Ni, Yan; Hollmann, Frank

    Oxidoreductases are promising catalysts for organic synthesis. To sustain their catalytic cycles they require efficient supply with redox equivalents. Today classical biomimetic approaches utilizing natural electron supply chains prevail but artificial regeneration approaches bear the promise of simpler and more robust reaction schemes. Utilizing visible light can accelerate such artificial electron transport chains and even enable thermodynamically unfeasible reactions such as the use of water as reductant.This contribution critically summarizes the current state of the art in photoredoxbiocatalysis (i.e. light-driven biocatalytic oxidation and reduction reactions).

  19. Artificial Neural Network Analysis System

    Science.gov (United States)

    2007-11-02

    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

  20. Photosynthetic responses of field-grown Pinus radiata trees to artificial and aphid-induced defoliation.

    Science.gov (United States)

    Eyles, Alieta; Smith, David; Pinkard, Elizabeth A; Smith, Ian; Corkrey, Ross; Elms, Stephen; Beadle, Chris; Mohammed, Caroline

    2011-06-01

    The phloem-feeding aphid Essigella californica represents a potential threat to the productivity of Pinus radiata plantations in south-eastern Australia. Five- and nine-year-old field trials were used to characterize the effects of artificial and natural aphid-induced (E. californica) defoliation, respectively, on shoot photosynthesis and growth. Photosynthetic capacity (A(max)) was significantly greater following a 25% (D25) (13.8 µmol m(-2) s(-1)) and a 50% (D50) (15.9 µmol m(-2) s(-1)) single-event upper-crown artificial defoliation, 3 weeks after defoliation than in undefoliated control trees (12.9 µmol m(-2) s(-1)). This response was consistently observed for up to 11 weeks after the defoliation event; by Week 16, there was no difference in A(max) between control and defoliated trees. In the D50 treatment, this increased A(max) was not sufficient to fully compensate for the foliage loss as evidenced by the reduced diameter increment (by 15%) in defoliated trees 36 weeks after defoliation. In contrast, diameter increment of trees in the D25 treatment was unaffected by defoliation. The A(max) of trees experiencing upper-crown defoliation by natural and repeated E. californica infestations varied, depending on host genotype. Despite clear differences in defoliation levels between resistant and susceptible genotypes (17 vs. 35% of tree crown defoliated, respectively), growth of susceptible genotypes was not significantly different from that of resistant genotypes. The observed increases in A(max) in the lower crown of the canopy following attack suggested that susceptible genotypes were able to partly compensate for the loss of foliage by compensatory photosynthesis. The capacity of P. radiata to regulate photosynthesis in response to natural aphid-induced defoliation provides evidence that the impact of E. californica attack on stem growth will be less than expected, at least for up to 35% defoliation.

  1. Light induced transmembrane proton gradient in artificial lipid vesicles reconstituted with photosynthetic reaction centers.

    Science.gov (United States)

    Milano, Francesco; Trotta, Massimo; Dorogi, Márta; Fischer, Béla; Giotta, Livia; Agostiano, Angela; Maróti, Péter; Kálmán, László; Nagy, László

    2012-06-01

    Photosynthetic reaction center (RC) is the minimal nanoscopic photoconverter in the photosynthetic membrane that catalyzes the conversion of solar light to energy readily usable for the metabolism of the living organisms. After electronic excitation the energy of light is converted into chemical potential by the generation of a charge separated state accompanied by intraprotein and ultimately transmembrane proton movements. We designed a system which fulfills the minimum structural and functional requirements to investigate the physico/chemical conditions of the processes: RCs were reconstituted in closed lipid vesicles made of selected lipids entrapping a pH sensitive indicator, and electron donors (cytochrome c₂ and K₄[Fe(CN)₆]) and acceptors (decylubiquinone) were added to sustain the photocycle. Thanks to the low proton permeability of our preparations, we could show the formation of a transmembrane proton gradient under illumination and low buffering conditions directly by measuring proton-related signals simultaneously inside and outside the vesicles. The effect of selected ionophores such as gramicidin, nigericin and valinomycin was used to gain more information on the transmembrane proton gradient driven by the RC photochemistry.

  2. 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.

  3. Beller Lecture: Artificial Ferroic Systems

    Science.gov (United States)

    Heyderman, Laura

    In artificial ferroic systems, novel functionality is engineered through the combination of structured ferroic materials and the control of the interactions between the different components. I will present two classes of these systems, beginning with hybrid mesoscopic structures incorporating two different ferromagnetic layers whose static and dynamic behaviour result from the mutual imprint of the magnetic domain configurations. Here we have demonstrated a new vortex core reversal mechanism, which occurs when it is displaced across domain boundaries with a magnetic field. I will then describe our progress on artificial spin ice, consisting of arrays of dipolar-coupled nanomagnets arranged in frustrated geometries. We have employed photoemission electron microscopy to observe the behaviour of emergent magnetic monopoles in an array of nanomagnets placed on the kagome lattice. We have also created artificial spin ice with fluctuating magnetic moments and observed the evolution of magnetic configurations with time. This has provided a means to study relaxation processes with a controlled route to the lowest-energy state. Recently, we have demonstrated with muon spin relaxation that these magnetic metamaterials can support thermodynamic phase transitions, and future directions include the incorporation of novel magnetic materials such as ultrathin magnetic films, the investigation of 3D structures, as well as the implementation of x-ray resonant magnetic scattering to study magnetic correlations in smaller nanomagnets and at faster timescales

  4. 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.

  5. Artificial kinesthetic systems for telerehabilitation.

    Science.gov (United States)

    De Rossi, D; Lorussi, F; Scilingo, E P; Carpi, F; Tognetti, A; Tesconi, M

    2004-01-01

    Artificial sensory motor systems are now under development in a truly wearable form using an innovative technology based on electroactive polymers. The integration of electroactive polymeric materials into wearable garments endorses them with strain sensing and mechanical actuation properties. The methodology underlying the design of haptic garments has necessarily to rely on knowledge of biological perceptual and motor processes which is, however, scattered and fragmented. Notwithstanding, the combined use of new polymeric electroactive materials in the form of fibers and fabrics with emerging concepts of biomimetic nature in sensor data analysis, pseudomuscular actuator control and biomechanical design may not only provide new avenues toward the realization of truly wearable kinesthetic and haptic interfaces, but also clues and instruments to better comprehend human manipulative and gestual functions. In this talk the conception, early stage implementation and preliminary testing of a fabric-based wearable interface endowed with spatially redundant strain sensing and distributed actuation are illustrated with reference to a wearable upper limb artificial kinesthesia system, intended to be used in telerehabilitation of post stroke patient.

  6. ARTIFICIAL LIVING SYSTEM AND ITS COMPLEXITY

    Institute of Scientific and Technical Information of China (English)

    ZHANG Yongguang

    2001-01-01

    In this paper the author shows some artificial living systems, whose basic life characteristics are explored, especially the differentiation in evolution from single cellular to multi-cellular organism. In addition, the author discusses diversity and evolvability also.The author gives a modified entropy function to measure the diversity. Finally, the author drops an open problem about the structure of "gene" of artificial living systems, so that we can measure the evolutionary order between the artificial living systems.

  7. Hourly photosynthetically active radiation estimation in Midwestern United States from artificial neural networks and conventional regressions models.

    Science.gov (United States)

    Yu, Xiaolei; Guo, Xulin

    2016-08-01

    The relationship between hourly photosynthetically active radiation (PAR) and the global solar radiation (R s ) was analyzed from data gathered over 3 years at Bondville, IL, and Sioux Falls, SD, Midwestern USA. These data were used to determine temporal variability of the PAR fraction and its dependence on different sky conditions, which were defined by the clearness index. Meanwhile, models based on artificial neural networks (ANNs) were established for predicting hourly PAR. The performance of the proposed models was compared with four existing conventional regression models in terms of the normalized root mean square error (NRMSE), the coefficient of determination (r (2)), the mean percentage error (MPE), and the relative standard error (RSE). From the overall analysis, it shows that the ANN model can predict PAR accurately, especially for overcast sky and clear sky conditions. Meanwhile, the parameters related to water vapor do not improve the prediction result significantly.

  8. Hourly photosynthetically active radiation estimation in Midwestern United States from artificial neural networks and conventional regressions models

    Science.gov (United States)

    Yu, Xiaolei; Guo, Xulin

    2016-08-01

    The relationship between hourly photosynthetically active radiation (PAR) and the global solar radiation ( R s ) was analyzed from data gathered over 3 years at Bondville, IL, and Sioux Falls, SD, Midwestern USA. These data were used to determine temporal variability of the PAR fraction and its dependence on different sky conditions, which were defined by the clearness index. Meanwhile, models based on artificial neural networks (ANNs) were established for predicting hourly PAR. The performance of the proposed models was compared with four existing conventional regression models in terms of the normalized root mean square error (NRMSE), the coefficient of determination ( r 2), the mean percentage error (MPE), and the relative standard error (RSE). From the overall analysis, it shows that the ANN model can predict PAR accurately, especially for overcast sky and clear sky conditions. Meanwhile, the parameters related to water vapor do not improve the prediction result significantly.

  9. 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.

  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. Ultrafast transient absorption spectroscopy: principles and application to photosynthetic systems.

    Science.gov (United States)

    Berera, Rudi; van Grondelle, Rienk; Kennis, John T M

    2009-01-01

    The photophysical and photochemical reactions, after light absorption by a photosynthetic pigment-protein complex, are among the fastest events in biology, taking place on timescales ranging from tens of femtoseconds to a few nanoseconds. The advent of ultrafast laser systems that produce pulses with femtosecond duration opened up a new area of research and enabled investigation of these photophysical and photochemical reactions in real time. Here, we provide a basic description of the ultrafast transient absorption technique, the laser and wavelength-conversion equipment, the transient absorption setup, and the collection of transient absorption data. Recent applications of ultrafast transient absorption spectroscopy on systems with increasing degree of complexity, from biomimetic light-harvesting systems to natural light-harvesting antennas, are presented. In particular, we will discuss, in this educational review, how a molecular understanding of the light-harvesting and photoprotective functions of carotenoids in photosynthesis is accomplished through the application of ultrafast transient absorption spectroscopy.

  12. Synthesis and Photophysical Characterization of an Artificial Photosynthetic Reaction Center Exhibiting Acid-Responsive Regulation of Charge Separation

    Science.gov (United States)

    Pahk, Ian

    Non-photochemical quenching (NPQ) is a photoprotective regulatory mechanism essential to the robustness of the photosynthetic apparatus of green plants. Energy flow within the low-light adapted reaction centers is dynamically optimized to match the continuously fluctuating light conditions found in nature. Activated by compartmentalized decreases in pH resulting from photosynthetic activity during periods of elevated photon flux, NPQ induces rapid thermal dissipation of excess excitation energy that would otherwise overwhelm the apparatus's ability to consume it. Consequently, the frequency of charge separation decreases and the formation of potentially deleterious, high-energy intermediates slows, thereby reducing the threat of photodamage by disallowing their accumulation. Herein is described the synthesis and photophysical analysis of a molecular triad that mimics the effects of NPQ on charge separation within the photosynthetic reaction centers. Steady-state absorption and emission, time-resolved fluorescence, and transient absorption spectroscopies were used to demonstrate reversible quenching of the first singlet excited state affecting the quantum yield of charge separation by approximately one order of magnitude. As in the natural system, the populations of unquenched and quenched states and, therefore, the overall yields of charge separation were found to be dependent upon acid concentration.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. A DISTRIBUTED SMART HOME ARTIFICIAL INTELLIGENCE SYSTEM

    DEFF Research Database (Denmark)

    Lynggaard, Per

    2013-01-01

    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......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...... 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...

  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. Engineering analysis of potential photosynthetic bacterial hydrogen-production systems

    Science.gov (United States)

    Herlevich, A.; Karpuk, M. E.

    1982-06-01

    Photosynthetic bacteria (PSB) are capable of generating hydrogen from organics in effluents from food processing, pulp and paper, and chemical and pharmaceutical industries. Hydrogen evolution takes place under light in the absence of air. The rate of hydrogen production is expected to range between 300 to 600 scf of hydrogen per 1000 galloons of waste stream treated per hour. This hydrogen production system has been demonstrated at a bench-scale level and is ready for engineering development. A conceptual design for a PSB hydrogen production system is described. The system is expected to be sited adjacent to a waste stream source which will be pretreated by fermentation and pH adjustment, innoculated with bacteria, and then passed into the reactor. The reactor effluent can either be discharged into a rapid infiltration system, an irrigation ditch, and/or recycled back into the reactor. Several potential reactor designs have been developed, analyzed, and costed. A large covered pond appears to be the most economical design approach.

  20. 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

  1. Digital systems for artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Atlas, L.E. (Interactive Systems Design Lab., Univ. of Washington, WA (US)); Suzuki, Y. (NTT Human Interface Labs. (US))

    1989-11-01

    A tremendous flurry of research activity has developed around artificial neural systems. These systems have also been tested in many applications, often with positive results. Most of this work has taken place as digital simulations on general-purpose serial or parallel digital computers. Specialized neural network emulation systems have also been developed for more efficient learning and use. The authors discussed how dedicated digital VLSI integrated circuits offer the highest near-term future potential for this technology.

  2. An integrated multivariable artificial pancreas control system.

    Science.gov (United States)

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

    2014-05-01

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

  3. Tailoring superradiance to design artificial quantum systems

    Science.gov (United States)

    Longo, Paolo; Keitel, Christoph H.; Evers, Jörg

    2016-03-01

    Cooperative phenomena arising due to the coupling of individual atoms via the radiation field are a cornerstone of modern quantum and optical physics. Recent experiments on x-ray quantum optics added a new twist to this line of research by exploiting superradiance in order to construct artificial quantum systems. However, so far, systematic approaches to deliberately design superradiance properties are lacking, impeding the desired implementation of more advanced quantum optical schemes. Here, we develop an analytical framework for the engineering of single-photon superradiance in extended media applicable across the entire electromagnetic spectrum, and show how it can be used to tailor the properties of an artificial quantum system. This “reverse engineering” of superradiance not only provides an avenue towards non-linear and quantum mechanical phenomena at x-ray energies, but also leads to a unified view on and a better understanding of superradiance across different physical systems.

  4. Tailoring superradiance to design artificial quantum systems.

    Science.gov (United States)

    Longo, Paolo; Keitel, Christoph H; Evers, Jörg

    2016-03-24

    Cooperative phenomena arising due to the coupling of individual atoms via the radiation field are a cornerstone of modern quantum and optical physics. Recent experiments on x-ray quantum optics added a new twist to this line of research by exploiting superradiance in order to construct artificial quantum systems. However, so far, systematic approaches to deliberately design superradiance properties are lacking, impeding the desired implementation of more advanced quantum optical schemes. Here, we develop an analytical framework for the engineering of single-photon superradiance in extended media applicable across the entire electromagnetic spectrum, and show how it can be used to tailor the properties of an artificial quantum system. This "reverse engineering" of superradiance not only provides an avenue towards non-linear and quantum mechanical phenomena at x-ray energies, but also leads to a unified view on and a better understanding of superradiance across different physical systems.

  5. 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, ...

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

    Science.gov (United States)

    Rozzi, Carlo Andrea; Falke, Sarah Maria; Spallanzani, Nicola; Rubio, Angel; Molinari, Elisa; Brida, Daniele; Maiuri, Margherita; Cerullo, Giulio; Schramm, Heiko; Christoffers, Jens; Lienau, Christoph

    2013-01-01

    The efficient conversion of light into electricity or chemical fuels is a fundamental challenge. In artificial photosynthetic and photovoltaic devices, this conversion is generally thought to happen on ultrafast, femto-to-picosecond timescales and to involve an incoherent electron transfer process. In some biological systems, however, there is growing evidence that the coherent motion of electronic wavepackets is an essential primary step, raising questions about the role of quantum coherence in artificial devices. Here we investigate the primary charge-transfer process in a supramolecular triad, a prototypical artificial reaction centre. Combining high time-resolution femtosecond spectroscopy and time-dependent density functional theory, we provide compelling evidence that the driving mechanism of the photoinduced current generation cycle is a correlated wavelike motion of electrons and nuclei on a timescale of few tens of femtoseconds. We highlight the fundamental role of the interface between chromophore and charge acceptor in triggering the coherent wavelike electron-hole splitting.

  7. Agency in natural and artificial systems.

    Science.gov (United States)

    Moreno, Alvaro; Etxeberria, Arantza

    2005-01-01

    We analyze the conditions for agency in natural and artificial systems. In the case of basic (natural) autonomous systems, self-construction and activity in the environment are two aspects of the same organization, the distinction between which is entirely conceptual: their sensorimotor activities are metabolic, realized according to the same principles and through the same material transformations as those typical of internal processes (such as energy transduction). The two aspects begin to be distinguishable in a particular evolutionary trend, related to the size increase of some groups of organisms whose adaptive abilities depend on motility. Here a specialized system develops, which, in the sensorimotor aspect, is decoupled from the metabolic basis, although it remains dependent on it in the self-constructive aspect. This decoupling reveals a complexification of the organization. In the last section of the article this approach to natural agency is used to analyze artificial systems by posing two problems: whether it is possible to artificially build an organization similar to the natural, and whether this notion of agency can be grounded on different organizing principles.

  8. Artificial Hydrocarbon Networks Fuzzy Inference System

    Directory of Open Access Journals (Sweden)

    Hiram Ponce

    2013-01-01

    Full Text Available This paper presents a novel fuzzy inference model based on artificial hydrocarbon networks, a computational algorithm for modeling problems based on chemical hydrocarbon compounds. In particular, the proposed fuzzy-molecular inference model (FIM-model uses molecular units of information to partition the output space in the defuzzification step. Moreover, these molecules are linguistic units that can be partially understandable due to the organized structure of the topology and metadata parameters involved in artificial hydrocarbon networks. In addition, a position controller for a direct current (DC motor was implemented using the proposed FIM-model in type-1 and type-2 fuzzy inference systems. Experimental results demonstrate that the fuzzy-molecular inference model can be applied as an alternative of type-2 Mamdani’s fuzzy control systems because the set of molecular units can deal with dynamic uncertainties mostly present in real-world control applications.

  9. Dynamic artificial neural networks with affective systems.

    Science.gov (United States)

    Schuman, Catherine D; Birdwell, J Douglas

    2013-01-01

    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. Artificial Neural Network System for Thyroid Diagnosis

    Directory of Open Access Journals (Sweden)

    Mazin Abdulrasool Hameed

    2017-05-01

    Full Text Available Thyroid disease is one of major causes of severe medical problems for human beings. Therefore, proper diagnosis of thyroid disease is considered as an important issue to determine treatment for patients. This paper focuses on using Artificial Neural Network (ANN as a significant technique of artificial intelligence to diagnose thyroid diseases. The continuous values of three laboratory blood tests are used as input signals to the proposed system of ANN. All types of thyroid diseases that may occur in patients are taken into account in design of system, as well as the high accuracy of the detection and categorization of thyroid diseases are considered in the system. A multilayer feedforward architecture of ANN is adopted in the proposed design, and the back propagation is selected as learning algorithm to accomplish the training process. The result of this research shows that the proposed ANN system is able to precisely diagnose thyroid disease, and can be exploited in practical uses. The system is simulated via MATLAB software to evaluate its performance

  11. Development of artificial bionic baroreflex system.

    Science.gov (United States)

    Sunagawa, Kenji; Sugimachi, Masaru

    2010-01-01

    The baroreflex system is the fastest mechanism in the body to regulate arterial pressure. Because the neural system (i.e., autonomic nervous system) mediates the baroreflex and the system operates under the closed-loop condition, the quantitative dynamic characteristics of the baroreflex system remained unknown until recently despite the fact that a countless number of observational and qualitative studies had been conducted. In order to develop the artificial baroreflex system, i.e., the bionic baroreflex system, we first anatomically isolated the carotid sinuses to open the baroreflex loop and identified the open-loop transfer function of the baroreflex system using white noise pressure perturbations. We found that the baroreflex system is basically a lowpass filter and remarkably linear. As an actuator to implement the bionic baroreflex system, we then stimulated the sympathetic efferent nerves at various parts of the baroreflex loop and identified the transfer functions from the stimulation sites to systemic arterial pressure. We found that the actuator responses can be described remarkably well with linear transfer functions. Since transfer functions of the native baroreflex and of the actuator were identified, the controller that is required to reproduce the native baroreflex transfer function can be easily derived from those transfer functions. To examine the performance of bionic baroreflex system, we implemented it animal models of baroreflex failure. The bionic baroreflex system restored normal arterial pressure regulation against orthostatic stresses that is indistinguishable from the native baroreflex system.

  12. 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.

  13. Forster Energy Transfer Theory as Reflected in the Structures of Photosynthetic Light-Harvesting Systems

    Energy Technology Data Exchange (ETDEWEB)

    Sener, Melih [Univ. of Illinois, Urbana-Champaign, IL (United States); Strumpfer, Johan [Univ. of Illinois, Urbana-Champaign, IL (United States); Hsin, Jen [Univ. of Illinois, Urbana-Champaign, IL (United States); Chandler, Danielle [Univ. of Illinois, Urbana-Champaign, IL (United States); Scheuring, Simon [Institut National de la Sante Et Recherche Medicale, Paris (France); Hunter, C. Neil [Univ. of Sheffield (United Kingdom); Schulten, Klaus [Univ. of Illinois, Urbana-Champaign, IL (United States)

    2011-02-22

    Förster's theory of resonant energy transfer underlies a fundamental process in nature, namely the harvesting of sunlight by photosynthetic life forms. The theoretical framework developed by Förster and others describes how electronic excitation migrates in the photosynthetic apparatus of plants, algae, and bacteria from light absorbing pigments to reaction centers where light energy is utilized for the eventual conversion into chemical energy. The demand for highest possible efficiency of light harvesting appears to have shaped the evolution of photosynthetic species from bacteria to plants which, despite a great variation in architecture, display common structural themes founded on the quantum physics of energy transfer as described first by Förster. Herein, Förster’s theory of excitation transfer is summarized, including recent extensions, and the relevance of the theory to photosynthetic systems as evolved in purple bacteria, cyanobacteria, and plants is demonstrated. Förster's energy transfer formula, as used widely today in many fields of science, is also derived.

  14. Fault tolerant architecture for artificial olfactory system

    Science.gov (United States)

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

    2015-05-01

    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.

  15. 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).

  16. An Artificial Neural Network Control System for Spacecraft Attitude Stabilization

    Science.gov (United States)

    1990-06-01

    NAVAL POSTGRADUATE SCHOOL Monterey, California ’-DTIC 0 ELECT f NMARO 5 191 N S, U, THESIS B . AN ARTIFICIAL NEURAL NETWORK CONTROL SYSTEM FOR...NO. NO. NO ACCESSION NO 11. TITLE (Include Security Classification) AN ARTIFICIAL NEURAL NETWORK CONTROL SYSTEM FOR SPACECRAFT ATTITUDE STABILIZATION...obsolete a U.S. G v pi.. iim n P.. oiice! toog-eo.5s43 i Approved for public release; distribution is unlimited. AN ARTIFICIAL NEURAL NETWORK CONTROL

  17. 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....

  18. Multithreshold Segmentation Based on Artificial Immune Systems

    Directory of Open Access Journals (Sweden)

    Erik Cuevas

    2012-01-01

    Full Text Available Bio-inspired computing has lately demonstrated its usefulness with remarkable contributions to shape detection, optimization, and classification in pattern recognition. Similarly, multithreshold selection has become a critical step for image analysis and computer vision sparking considerable efforts to design an optimal multi-threshold estimator. This paper presents an algorithm for multi-threshold segmentation which is based on the artificial immune systems(AIS technique, also known as theclonal selection algorithm (CSA. It follows the clonal selection principle (CSP from the human immune system which basically generates a response according to the relationship between antigens (Ag, that is, patterns to be recognized and antibodies (Ab, that is, possible solutions. In our approach, the 1D histogram of one image is approximated through a Gaussian mixture model whose parameters are calculated through CSA. Each Gaussian function represents a pixel class and therefore a thresholding point. Unlike the expectation-maximization (EM algorithm, the CSA-based method shows a fast convergence and a low sensitivity to initial conditions. Remarkably, it also improves complex time-consuming computations commonly required by gradient-based methods. Experimental evidence demonstrates a successful automatic multi-threshold selection based on CSA, comparing its performance to the aforementioned well-known algorithms.

  19. [Membrane-based photochemical systems as models for photosynthetic cells

    Energy Technology Data Exchange (ETDEWEB)

    Hurst, J.K.

    1992-01-01

    The objectives of this research are to improve our conceptual view of the ways in which membranes and interfaces can be used to control chemical reactivity. We have focused on understanding three elementary processes that are central to developing membrane-based integrated chemical systems for water photolysis or related photoconversion/photostorage processes. Specifically, we have sought to identify: the influence of interfaces upon charge separation/recombination reactions, pathways for transmembrane charge separation across hydrocarbon bilayer membranes, and mechanisms of water oxidation catalyzed by transition metal coordination complexes. Historically, the chemical dynamics of each of these processes has been poorly understood, with numerous unresolved issues and conflicting viewpoints appearing in the literature. As described in this report our recent research has led to considerable clarification of the underlying reaction mechanisms.

  20. Artificial and bioartificial support systems for liver failure

    DEFF Research Database (Denmark)

    Liu, Jianping; Kjaergard, Lise Lotte; Als-Nielsen, Bodil;

    2002-01-01

    Liver support systems may bridge patients to liver transplantation or recovery from liver failure. This review is to evaluate the beneficial and harmful effects of artificial and bioartificial support systems for acute and acute-on-chronic liver failure.......Liver support systems may bridge patients to liver transplantation or recovery from liver failure. This review is to evaluate the beneficial and harmful effects of artificial and bioartificial support systems for acute and acute-on-chronic liver failure....

  1. 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?

  2. Indoor Positioning System Using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Hamid Mehmood

    2010-01-01

    Full Text Available Problem statement: Location knowledge in indoor environment using Indoor Positioning Systems (IPS has become very useful and popular in recent years. A number of Location Based Services (LBS have been developed, which are based on IPS, these LBS include asset tracking, inventory management and security based applications. Many next-generation LBS applications such as social networking, local search, advertising and geo-tagging are expected to be used in urban and indoor environments where GNSS either underperforms in terms of fix times or accuracy, or fails altogether. To develop an IPS based on Wi-Fi Received Signal Strength (RSS using Artificial Neural Networks (ANN, which should use already available Wi-Fi infrastructure in a heterogeneous environment. Approach: This study discussed the use of ANN for IPS using RSS in an indoor wireless facility which has varying human activity, material of walls and type of Wireless Access Points (WAP, hence simulating a heterogeneous environment. The proposed system used backpropogation method with 4 input neurons, 2 output neurons and 4 hidden layers. The model was trained with three different types of training data. The accuracy assessment for each training data was performed by computing the distance error and average distance error. Results: The results of the experiments showed that using ANN with the proposed method of collecting training data, maximum accuracy of 0.7 m can be achieved, with 30% of the distance error less than 1 m and 60% of the distance error within the range of 1-2 m. Whereas maximum accuracy of 1.01 can be achieved with the commonly used method of collecting training data. The proposed model also showed 67% more accuracy as compared to a probabilistic model. Conclusion: The results indicated that ANN based IPS can provide accuracy and precision which is quite adequate for the development of indoor LBS while using the already available Wi-Fi infrastructure, also the proposed method

  3. Artificial olfaction systems: principles and applications to food analysis

    National Research Council Canada - National Science Library

    Antonella Macagnano; Roberto Paolesse; Arnaldo D’Amico; Corrado Di Natale

    2001-01-01

    .... On the other hands, since human senses are strongly involved in the interaction with foods the analysis of food provides an excellent field to compare the performances of natural and artificial olfaction systems...

  4. Quantum non-equilibrium approach for fast electron transport in open systems: photosynthetic reaction centers

    CERN Document Server

    Pudlak, M; Nazmitdinov, R G; Pincak, R

    2011-01-01

    Creation of electron or exciton by external fields in a system with initially statistically independent unrelaxed vibrational modes leads to an initial condition term. The contribution of this term in the time convolution generalized master equation approach is studied in second order of the perturbation theory for electron-phonon coupling in the parth integral formalism. The developed approach, applied for analysis of dynamics in the photosynthetic reaction center, exhibits the key role of the initial condition term at the primary stage of electron transfer.

  5. 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.

  6. 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.

  7. Artificial Pheromone System Using RFID for Navigation of Autonomous Robots

    Institute of Scientific and Technical Information of China (English)

    Herianto; Toshiki Sakakibara; Daisuke Kurabayashi

    2007-01-01

    Navigation system based on the animal behavior has received a growing attention in the past few years. The navigation systems using artificial pheromone are still few so far. For this reason, this paper presents our research that aim to implement autonomous navigation with artificial pheromone system. By introducing artificial pheromone system composed of data carriers and autonomous robots, the robotic system creates a potential field to navigate their group. We have developed a pheromone density model to realize the function of pheromones with the help of data carriers. We intend to show the effectiveness of the proposed system by performing simulations and realization using modified mobile robot. The pheromone potential field system can be used for navigation of autonomous robots.

  8. Effects of system-bath coupling on Photosynthetic heat engine: A polaron master equation approach

    CERN Document Server

    Qin, M; Zhao, X L; Yi, X X

    2016-01-01

    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 charge transfer processes in Photosystem II reaction center (PSII RC) inspired quantum heat engine (QHE) model in a wide parameter range. The effects of bath correlation and temperature, together with the combined effects of these factors are also discussed in details. The results show a variety of dynamical behaviours. 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 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...

  9. 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.

  10. Artificial Intelligence Systems in New Media Art and Design

    OpenAIRE

    DiPaola, Steve

    2006-01-01

    Science and art are merging and with artificial intelligence system like neural networks, genetic programs and rule based systems, artists or designers are using smart systems that allow them to better immerse themselves in the creative process. Artist/Scientist Steve DiPaola uses AI techniques in his self created programs and artwork.

  11. Structural colors: from natural to artificial systems.

    Science.gov (United States)

    Fu, Yulan; Tippets, Cary A; Donev, Eugenii U; Lopez, Rene

    2016-09-01

    Structural coloration has attracted great interest from scientists and engineers in recent years, owing to fascination with various brilliant examples displayed in nature as well as to promising applications of bio-inspired functional photonic structures and materials. Much research has been done to reveal and emulate the physical mechanisms that underlie the structural colors found in nature. In this article, we review the fundamental physics of many natural structural colors displayed by living organisms as well as their bio-inspired artificial counterparts, with emphasis on their connections, tunability strategies, and proposed applications, which aim to maximize the technological benefits one could derive from these photonic nanostructures. WIREs Nanomed Nanobiotechnol 2016, 8:758-775. doi: 10.1002/wnan.1396 For further resources related to this article, please visit the WIREs website.

  12. SANA - Security Analysis in Internet Traffic through Artificial Immune Systems

    CERN Document Server

    Hilker, Michael

    2008-01-01

    The Attacks done by Viruses, Worms, Hackers, etc. are a Network Security-Problem in many Organisations. Current Intrusion Detection Systems have significant Disadvantages, e.g. the need of plenty of Computational Power or the Local Installation. Therefore, we introduce a novel Framework for Network Security which is called SANA. SANA contains an artificial Immune System with artificial Cells which perform certain Tasks in order to to support existing systems to better secure the Network against Intrusions. The Advantages of SANA are that it is efficient, adaptive, autonomous, and massively-distributed. In this Article, we describe the Architecture of the artificial Immune System and the Functionality of the Components. We explain briefly the Implementation and discuss Results.

  13. 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.

  14. 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.

  15. Imitation of Life: Advanced system for native Artificial Evolution

    CERN Document Server

    Sperl, Thomas

    2011-01-01

    A model for artificial evolution in native x86 Windows systems has been developed at the end of 2010. In this text, further improvements and additional analogies to natural microbiologic processes are presented. Several experiments indicate the capability of the system - and raise the question of possible countermeasures.

  16. Quantum simulator of an open quantum system using superconducting qubits: exciton transport in photosynthetic complexes

    CERN Document Server

    Mostame, Sarah; Tsomokos, Dimitris I; Aspuru-Guzik, Alán

    2011-01-01

    In the initial stage of photosynthesis, light-harvested energy is transferred with remarkably high efficiency to a reaction center, with the vibrational environment assisting the transport mechanism. It is of great interest to mimic this process with present-day technologies. Here we propose an analog quantum simulator of open system dynamics, where noise engineering of the environment has a central role. In particular, we propose the use of superconducting qubits for the simulation of exciton transport in the Fenna-Matthew-Olson protein, a prototypical photosynthetic complex. Our method allows for a single-molecule implementation and the investigation of energy transfer pathways as well as non-Markovian and spatiotemporal noise-correlation effects.

  17. Quantum simulator of an open quantum system using superconducting qubits: exciton transport in photosynthetic complexes

    Science.gov (United States)

    Mostame, Sarah; Rebentrost, Patrick; Eisfeld, Alexander; Kerman, Andrew J.; Tsomokos, Dimitris I.; Aspuru-Guzik, Alan

    2012-02-01

    In the initial stage of photosynthesis, light-harvested energy is transferred with remarkably high efficiency to a reaction center, with the vibrational environment assisting the transport mechanism. It is of great interest to mimic this process with present-day technologies. Here we propose an analog quantum simulator of open system dynamics, where noise engineering of the environment has a central role. In particular, we propose the use of superconducting qubits for the simulation of exciton transport in the Fenna-Matthew-Olson protein, a prototypical photosynthetic complex. Our method allows for a single-molecule implementation and the investigation of energy transfer pathways as well as non-Markovian and spatiotemporal noise-correlation effects.

  18. The fundamental role of localised vibrations in excitation dynamics in photosynthetic light-harvesting systems

    CERN Document Server

    Kolli, Avinash; Scholes, Gregory D; Olaya-Castro, Alexandra

    2012-01-01

    The importance of fast vibrations in enhancing and controlling energy transfer and conversion in biomolecules is an issue of current debate. In this article we show that coupling between localised high-frequency vibrations and electronic degrees of freedom is fundamental for efficient excitation transport in photosynthetic light-harvesting systems with high degree of disorder. We consider the cryptophyte antennae protein phycoerythrin 545 and discuss how the balance between electronic interactions and coupling to fast vibronic modes supports the biological function of these antennae by generating a non-cascaded transport that leads to a rapid, directed and wider spatial distribution of excitation energy across the complex. Furthermore, we illustrate signatures of vibronic influence in the beating of excitonic coherences and show that mechanisms supporting coherent evolution of excitons also assist coupling to selected modes that enhance energy transfer to preferential sites in the complex. We therefore argue ...

  19. Solving Systems of Equations with Techniques from Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Irina Maria Terfaloaga

    2015-07-01

    Full Text Available A frequent problem in numerical analysis is solving the systems of equations. That problem has generated in time a great interest among mathematicians and computer scientists, as evidenced by the large number of numerical methods developed. Besides the classical numerical methods, in the last years were proposed methods inspired by techniques from artificial intelligence. Hybrid methods have been also proposed along the time [15, 19]. The goal of this study is to make a survey of methods inspired from artificial intelligence for solving systems of equations

  20. Fuels from solar energy: photosynthetic systems--state of the art and potential for energy production

    Energy Technology Data Exchange (ETDEWEB)

    Goldman, J.C.

    1978-07-01

    Research on the mass culturing of microalgae has been carried out over the past 30 years in many parts of the world. Today there are numerous potential applications for algal mass cultures including protein production, wastewater treatment, water renovation, closed life-support systems, production of commercial chemicals, aquaculture, and bioconversion of energy. Photosynthetic yields over 30 gr dry wt m/sup -2/ day/sup -1/ have been attained on occasion in many locations for short periods and yields between 15 to 25 gr dry wt m/sup -2/ day/sup -1/ for longer periods are now common. This apparent upper limit in productivity is not coincidental. Under outdoor conditions peak yields are possible only under conditions of light limitation. Photosynthetic algae absorb light energy and convert it to stored chemical energy under rigid adherence to the laws of thermodynamics. By examining the basic physics of photosynthesis, it is possible to clearly demonstrate that under conditions of full sunlight in the most ideal locations maximum yields of 30 to 40 gr m/sup -2/ day/sup -1/ can be expected. For long-term operation of large-scale outdoor cultures, many bioengineering factors are involved and realistic yields considerably less than the maximum potential can be anticipated. Manipulation of the two independent variables, flow rate and depth, is the key to maximizing yields for varying outdoor sunlight intensities. Future applications for algal mass cultures will probably be restricted to small well-managed systems for solving specific environmental problems in individual communities and not on the grand scale envisaged in the past.

  1. Atomic force microscopy of bacterial photosynthetic systems: a new model for native membrane organization

    NARCIS (Netherlands)

    Bahatyrova, Svetlana

    2005-01-01

    The main goal of this thesis was to investigate the supramolecular architecture of a photosynthetic membrane from Rhodobacter sphaeroides purple bacteria cells. This is extremely timely, since we now know all of the structures of photosynthetic pigment-protein LH and RC complexes, ATP-synthase and b

  2. Modeling of higher order systems using artificial bee colony algorithm

    Directory of Open Access Journals (Sweden)

    Aytekin Bağış

    2016-05-01

    Full Text Available In this work, modeling of the higher order systems based on the use of the artificial bee colony (ABC algorithm were examined. Proposed model parameters for the sample systems in the literature were obtained by using the algorithm, and its performance was presented comparatively with the other methods. Simulation results show that the ABC algorithm based system modeling approach can be used as an efficient and powerful method for higher order systems.

  3. 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.

  4. Pegylated polystyrene particles as a model system for artificial cells

    NARCIS (Netherlands)

    Meng, Fenghua; Engbers, Gerard H.M.; Gessner, Andrea; Müller, Reiner H.; Feijen, Jan

    2004-01-01

    Pegylated polystyrene particles (PS-PEG) were prepared as a model system for artificial cells, by modification of carboxyl polystyrene particles (PS-COOH) with homo- and hetero-bifunctional polyethylene glycols (PEG, MW 1500, 3400, and 5000) containing an amino end group for immobilization and an am

  5. Integrated Photobioelectrochemical Systems: A Paradigm Shift in Artificial Photosynthesis.

    Science.gov (United States)

    Majumdar, Pavel; Pant, Deepak; Patra, Snehangshu

    2017-04-01

    Recent breakthroughs have reinvigorated the century-old research domain of artificial photosynthesis. Here, we highlight CO2-reducing and O2-liberating integrated photobioelectrochemical systems that contain novel enzymatic cathodes and photoanodes. These devices, which are completely self-driven by solar energy with unprecedented efficiency and stability, have important implications for biotechnological research communities.

  6. Qualitative reasoning about physical systems: an artificial intelligence perspective

    NARCIS (Netherlands)

    Top, J.L.; Akkermans, J.M.; Breedveld, P.C.

    1991-01-01

    Some interdisciplinary issues concerning artificial intelligence (AI) are explored in relation to modelling in physics and engineering. A short survey is given of automated qualitative reasoning about physical systems, which in recent years has become an active research area in AI, and has been part

  7. 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…

  8. 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.

  9. A Native Intelligence Metric for Artificial Systems

    Science.gov (United States)

    2002-08-01

    models of intelligence that will readily yield a NIM. Why not use linear systems theory as a model for a NIM? The successes of traditional linear...intelligence would be easily perceived by all. 1.5 The nature of a NIM Perhaps the solution is not in an analogy to linear systems theory , as has

  10. Artificial Intelligence Theory and Reconfigurable Control Systems.

    Science.gov (United States)

    1984-06-30

    IEEE Transactions on Automatic Control , Vol...AC-iS, No. 1, Feb 1970. 5. Sklansky, J., "Learning Systems for Automatic Control", IEEE = Transactions on Automatic Control , Vol...34A Gerfcale itellihoode Raio ,-. ~Aproc tohemesecio and Ca Suis nwEtimat eeion" (: Jump in-Linea & -,"Ŗ. Systems", IEEE Transactions on Automatic Control ,

  11. 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.

  12. 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.

  13. 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.

  14. Creativity and constraint in artificial systems

    NARCIS (Netherlands)

    Leijnen, S.

    2014-01-01

    Since the advent of computers and internet in everyday life, we are more than ever surrounded by systems that exhibit intelligent behavior. However, intelligent behavior doesn’t necessarily imply creativity: computers are often programmed to achieve specific results. When the results are not explici

  15. 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…

  16. 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.

  17. Evolutionary learning in the 2D artificial life system "avida"

    CERN Document Server

    Adami, C; Chris Adami

    1994-01-01

    We present a new tierra-inspired artificial life system with local interactions and two-dimensional geometry, based on an update mechanism akin to that of 2D cellular automata. We find that the spatial geometry is conducive to the development of diversity and thus improves adaptive capabilities. We also demonstrate the adaptive strength of the system by breeding cells with simple computational abilities, and study the dependence of this adaptability on mutation rate and population size.

  18. Quantum coherence in photosynthetic complexes

    Energy Technology Data Exchange (ETDEWEB)

    Calhoun, Tessa R.; Fleming, Graham R. [Department of Chemistry, University of California, Berkeley, CA 94720 (United States); Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States)

    2011-04-15

    The initial steps of photosynthesis require the absorption and subsequent transfer of energy through an intricate network of pigment-protein complexes. Held within the protein scaffold of these complexes, chromophore molecules are densely packed and fixed in specific geometries relative to one another resulting in Coulombic coupling. Excitation energy transfer through these systems can be accomplished with near unity quantum efficiency [Wraight and Clayton, Biochim. Biophys. Acta 333, 246 (1974)]. While replication of this feat is desirable for artificial photosynthesis, the mechanism by which nature achieves this efficiency is unknown. Recent experiments have revealed the presence of long-lived quantum coherences in photosynthetic pigment-protein complexes spanning bacterial and plant species with a variety of functions and compositions. Its ubiquitous presence and wavelike energy transfer implicate quantum coherence as key to the high efficiency achieved by photosynthesis. (Copyright copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

  19. Förster energy transfer theory as reflected in the structures of photosynthetic light-harvesting systems.

    Science.gov (United States)

    Şener, Melih; Strümpfer, Johan; Hsin, Jen; Chandler, Danielle; Scheuring, Simon; Hunter, C Neil; Schulten, Klaus

    2011-02-25

    Förster’s theory of resonant energy transfer underlies a fundamental process in nature, namely the harvesting of sunlight by photosynthetic life forms. The theoretical framework developed by Förster and others describes how electronic excitation migrates in the photosynthetic apparatus of plants, algae, and bacteria from light absorbing pigments to reaction centers where light energy is utilized for the eventual conversion into chemical energy. The demand for highest possible efficiency of light harvesting appears to have shaped the evolution of photosynthetic species from bacteria to plants which, despite a great variation in architecture, display common structural themes founded on the quantum physics of energy transfer as described first by Förster. Herein, Förster’s theory of excitation transfer is summarized, including recent extensions, and the relevance of the theory to photosynthetic systems as evolved in purple bacteria, cyanobacteria, and plants is demonstrated. Förster’s energy transfer formula, as used widely today in many fields of science, is also derived.

  20. Optimizing Mining Association Rules for Artificial Immune System based Classification

    Directory of Open Access Journals (Sweden)

    SAMEER DIXIT

    2011-08-01

    Full Text Available The primary function of a biological immune system is to protect the body from foreign molecules known as antigens. It has great pattern recognition capability that may be used to distinguish between foreigncells entering the body (non-self or antigen and the body cells (self. Immune systems have many characteristics such as uniqueness, autonomous, recognition of foreigners, distributed detection, and noise tolerance . Inspired by biological immune systems, Artificial Immune Systems have emerged during the last decade. They are incited by many researchers to design and build immune-based models for a variety of application domains. Artificial immune systems can be defined as a computational paradigm that is inspired by theoretical immunology, observed immune functions, principles and mechanisms. Association rule mining is one of the most important and well researched techniques of data mining. The goal of association rules is to extract interesting correlations, frequent patterns, associations or casual structures among sets of items in thetransaction databases or other data repositories. Association rules are widely used in various areas such as inventory control, telecommunication networks, intelligent decision making, market analysis and risk management etc. Apriori is the most widely used algorithm for mining the association rules. Other popular association rule mining algorithms are frequent pattern (FP growth, Eclat, dynamic itemset counting (DIC etc. Associative classification uses association rule mining in the rule discovery process to predict the class labels of the data. This technique has shown great promise over many other classification techniques. Associative classification also integrates the process of rule discovery and classification to build the classifier for the purpose of prediction. The main problem with the associative classification approach is the discovery of highquality association rules in a very large space of

  1. 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.

  2. Artificial and bioartificial support systems for acute and acute-on-chronic liver failure

    DEFF Research Database (Denmark)

    Kjaergard, Lise L; Liu, Jianping; Als-Nielsen, Bodil;

    2003-01-01

    Artificial and bioartificial support systems may provide a "bridge" for patients with severe liver disease to recovery or transplantation.......Artificial and bioartificial support systems may provide a "bridge" for patients with severe liver disease to recovery or transplantation....

  3. 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

  4. The Research on Artificial Olfaction System-Electronic Nose

    Energy Technology Data Exchange (ETDEWEB)

    Li, C W [Institute of Biomedical Engineering, Yanshan University, Qinhuangdao (China); Wang, G D [Institute of Biomedical Engineering, Yanshan University, Qinhuangdao (China)

    2006-10-15

    This paper has presented an artificial olfactory system, based on the structure and mechanism of biological olfactory system. The main goal of our study was to expound the principle of olfaction system of human body. It has complex structure model and of which structure and mechanism still under exploration. We built the model of sensory system mechanism, depicted the olfactory mechanism of the olfactory, and compared the different methods of pattern recognition. The result will show that the SOM method of pattern recognition accord by and large with human mode, and is better than the BP neural network.

  5. Entropy and biological systems: Experimentally-investigated entropy-driven stacking of plant photosynthetic membranes

    Science.gov (United States)

    Jia, Husen; Liggins, John R.; Chow, Wah Soon

    2014-01-01

    According to the Second Law of Thermodynamics, an overall increase of entropy contributes to the driving force for any physicochemical process, but entropy has seldom been investigated in biological systems. Here, for the first time, we apply Isothermal Titration Calorimetry (ITC) to investigate the Mg2+-induced spontaneous stacking of photosynthetic membranes isolated from spinach leaves. After subtracting a large endothermic interaction of MgCl2 with membranes, unrelated to stacking, we demonstrate that the enthalpy change (heat change at constant pressure) is zero or marginally positive or negative. This first direct experimental evidence strongly suggests that an entropy increase significantly drives membrane stacking in this ordered biological structure. Possible mechanisms for the entropy increase include: (i) the attraction between discrete oppositely-charged areas, releasing counterions; (ii) the release of loosely-bound water molecules from the inter-membrane gap; (iii) the increased orientational freedom of previously-aligned water dipoles; and (iv) the lateral rearrangement of membrane components. PMID:24561561

  6. 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.

  7. Application of Artificial Immune System Approach in MRI Classification

    Directory of Open Access Journals (Sweden)

    Gia-Hao Chang

    2008-05-01

    Full Text Available Numerous scholars have submitted the theory and research of artificial immune systems (AISs in recent years. Although AIS has been used in various fields, applying the AIS to medical images is very rare. The purpose of this study is using the clonal selection algorithm (CSA of artificial immune systems for classifying the brain MRI, and displaying a single organism image which can finally offer faster organism reference information to a doctor; hence reducing the time to ascertain large number of images, so that the doctor can diagnose the nidus more efficiently and accurately. In order to verify the feasibility and efficiency of this method, we adopt statistical theory for manifold assessment and compare with the perceptron network of double layers, FCM method. The result proves that the method of this study is both feasible and useful.

  8. 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

  9. 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.

  10. 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.

  11. Interactional Motivation in Artificial Systems: Between Extrinsic and Intrinsic Motivation

    OpenAIRE

    Georgeon, Olivier; Marshall, James; Gay, Simon

    2012-01-01

    International audience; This paper introduces Interactional Motivation (IM) as a way to implement self-motivation in artificial systems. An interactionally motivated agent selects behaviors for the sake of enacting the behavior itself rather than for the value of the behavior’s outcome. IM contrasts with extrinsic motivation by the fact that it defines the agent’s motivation independently from the environment’s state. Because IM does not refer to the environment’s states, we argue that IM is ...

  12. 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.

  13. 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.

  14. 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.

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

    Science.gov (United States)

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

    2016-09-01

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

  16. 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.

  17. 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.

  18. Artificial Intelligence in the service of system administrators

    CERN Document Server

    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...

  19. 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.

  20. 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.

  1. Artificial endocrine controller for power management in robotic systems.

    Science.gov (United States)

    Sauzé, Colin; Neal, Mark

    2013-12-01

    The robots that operate autonomously for extended periods in remote environments are often limited to gather only small amounts of power through photovoltaic solar panels. Such limited power budgets make power management critical to the success of the robot's mission. Artificial endocrine controllers, inspired by the mammalian endocrine system, have shown potential as a method for managing competing demands, gradually switching between behaviors, synchronizing behavior with external events, and maintaining a stable internal state of the robot. This paper reports the results obtained using these methods to manage power in an autonomous sailing robot. Artificial neural networks are used for sail and rudder control, while an artificial endocrine controller modulates the magnitude of actuator movements in response to battery or sunlight levels. Experiments are performed both in simulation and using a real robot. In simulation a 13-fold reduction in median power consumption is achieved; in the robot this is reduced to a twofold reduction because of the limitations of the simulation model. Additional simulations of a long term mission demonstrate the controller's ability to make gradual behavioral transitions and to synchronize behaviors with diurnal and seasonal changes in sunlight levels.

  2. Characterization of nonlinear dynamic systems using artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Urbina, A. [Univ. of Texas, El Paso, TX (United States); Hunter, N.F. [Los Alamos National Lab., NM (United States). Engineering Science and Analysis Div.; Paez, T.L. [Sandia National Labs., Albuquerque, NM (United States). Experimental Structural Dynamics Dept.

    1998-12-01

    The efficient characterization of nonlinear systems is an important goal of vibration and model testing. The authors build a nonlinear system model based on the acceleration time series response of a single input, multiple output system. A series of local linear models are used as a template to train artificial neutral networks (ANNs). The trained ANNs map measured time series responses into states of a nonlinear system. Another NN propagates response states in time, and a third ANN inverts the original map, transforming states into acceleration predictions in the measurement domain. The technique is illustrated using a nonlinear oscillator, in which quadratic and cubic stiffness terms play a major part in the system`s response. Reasonable maps are obtained for the states, and accurate, long-term response predictions are made for data outside the training data set.

  3. 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

  4. Triplet state dynamics of chlorophylls in photosynthetic reaction centers and model systems.

    NARCIS (Netherlands)

    Wijk, van F.G.H.

    1987-01-01

    In this work the temperature dependence of the lineshape, and more specifically, the electron spin polarization pattern of the Δm = ±1 triplet EPR (Electron Paramagnetic Resonance) spectra from several photosynthetic purple bacteria has been investigated.In Chapter I a general introduction is presen

  5. 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 qua

  6. Photosynthetic characteristics of Lycoris aurea and monthly ...

    African Journals Online (AJOL)

    AJL

    2012-02-21

    Feb 21, 2012 ... Full Length Research Paper ... photosynthetic measurement system, high performance liquid chromatography and SPSS13.0 software. ... net photosynthetic rate and lycorine and galantamine contents. .... Pigment analysis.

  7. A Preliminary Research Plan for Development of a Photosynthetic Link in a Closed Ecological Life Support System

    Science.gov (United States)

    Morgan, P. W.

    1979-01-01

    The use of higher plants in a closed ecological life support system for long duration space missions involving large numbers of people is considered. The approach to planning and developing both the habitat for a long term space mission and closed ecological life support systems are discussed with emphasis on environmental compatibility and integrated systems design. The requirements of photosynthetic processes are summarized and evaluated in terms of their availability within a closed ecological life support environment. Specific references are recommended as a data base for future research on this topic.

  8. Detecting Anomalous Process Behaviour using Second Generation Artificial Immune Systems

    CERN Document Server

    Twycross, Jamie; Whitbrook, Amanda

    2010-01-01

    Artificial Immune Systems have been successfully applied to a number of problem domains including fault tolerance and data mining, but have been shown to scale poorly when applied to computer intrusion detec- tion despite the fact that the biological immune system is a very effective anomaly detector. This may be because AIS algorithms have previously been based on the adaptive immune system and biologically-naive mod- els. This paper focuses on describing and testing a more complex and biologically-authentic AIS model, inspired by the interactions between the innate and adaptive immune systems. Its performance on a realistic process anomaly detection problem is shown to be better than standard AIS methods (negative-selection), policy-based anomaly detection methods (systrace), and an alternative innate AIS approach (the DCA). In addition, it is shown that runtime information can be used in combination with system call information to enhance detection capability.

  9. A Recommender System based on Idiotypic Artificial Immune Networks

    CERN Document Server

    Cayzer, Steve

    2008-01-01

    The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an Artificial Immune System (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by Collaborative Filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen-antibody interaction for matching and idiotypic antibody-antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques.

  10. 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.

  11. 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.

  12. Obesity Heuristic, New Way on Artificial Immune Systems

    Directory of Open Access Journals (Sweden)

    M. A. El-Dosuky

    2012-12-01

    Full Text Available There is a need for new metaphors from immunology to flourish the application areas of ArtificialImmune Systems. A metaheuristic called Obesity Heuristic derived from advances in obesity treatment isproposed. The main forces of the algorithm are the generation omega-6 and omega-3 fatty acids. Thealgorithm works with Just-In-Time philosophy; by starting only when desired. A case study of datacleaning is provided. With experiments conducted on standard tables, results show that Obesity Heuristicoutperforms other algorithms, with 100% recall. This is a great improvement over other algorithms

  13. Surname Inherited Algorithm Research Based on Artificial Immune System

    Directory of Open Access Journals (Sweden)

    Jing Xie

    2013-06-01

    Full Text Available To keep the diversity of antibodies in artificial immune system evolution process, this paper puts forward a kind of increase simulation surname inheritance algorithm based on the clonal selection algorithm, and identification and forecast the Vibration Data about CA6140 horizontal  lathe machining slender shaft workpiece prone . The results show that the algorithm has the characteristics of flexible application, strong adaptability, an effective approach to improve efficiency of the algorithm, a good performance of global searching and broad application prospect.

  14. 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.

  15. 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.

  16. Improved hydrogen production by coupled systems of hydrogenase negative photosynthetic bacteria and fermentative bacteria in reverse micelles

    Energy Technology Data Exchange (ETDEWEB)

    Singh, Anita [Centre for Biotechnology, University of Allahabad, Allahabad 211002 (India); Misra, Krishna [Indo-Russian Center for Bioinformatics, Indian Institute of Information Technology, Allahabad 211011 (India)

    2008-11-15

    Significant improvement in biological hydrogen production is achieved by the use of coupled bacterial cells in reverse micellar systems. Two coupled systems (a) Rhodopseudomonas palustris CGA009/Citrobacter Y19, and (b) Rhodobacter sphaeroides 2.4.1/Citrobacter Y19 bacteria have been immobilized separately in aqueous pool of the reverse micelles fabricated by various surfactants (AOT, CBAC and SDS) and apolar organic solvents (benzene and isooctane). The gene for uptake hydrogenase enzyme has been manipulated further for hydrogen generation. Mutants deficient in uptake hydrogenase (Hup{sup -}) were obtained from R. palustris CGA009 and R. sphaeroides 2.4.1, and entrapped with Citrobacter Y19 in the reverse micellar systems. More than two fold increase in hydrogen production was obtained by the use of Hup{sup -} mutants instead of wild-type photosynthetic bacteria together with Citrobacter Y19. Addition of sodium dithionite, a reducing agent to AOT/H{sub 2}O/isooctane reverse micellar system with the coupled systems of wild-type photosynthetic bacteria and fermentative bacterium Y19 effected similar increase in hydrogen production rate as it is obtained by the use of mutants. CBAC/H{sub 2}O/isooctane reverse micellar system is used for the first time for hydrogen production and is as promising as AOT/H{sub 2}O/isooctane reverse micellar system. All reverse micellar systems of coupled bacterial cultures gave encouraging hydrogen production (rate as well as yield) compared to uncoupled bacterial culture. (author)

  17. Artificial intelligence in the service of system administrators

    CERN Document Server

    Haen, Christophe; 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.

  18. Monitoring induced denitrification in an artificial aquifer recharge system.

    Science.gov (United States)

    Grau-Martinez, Alba; Torrentó, Clara; Folch, Albert; Domènech, Cristina; Otero, Neus; Soler, Albert

    2014-05-01

    literature ɛN values of -4o and -22o respectively (Aravena and Robertson, 1998; Pauwels et al., 2000). Ongoing denitrification batch experiments will allow us to determine the specific nitrogen and oxygen isotopic fractionation induced by the organic reactive layer, in order to estimate more precisely the extent of denitrification during artificial aquifer recharge. These results confirmed that the reactive layer induces denitrification in the recharge ponds area, proving the usefulness of an isotopic approach to characterize water quality improvement occurring during artificial aquifer recharge. References 1. Aravena, R., Robertson, W.D., 1998. Use of multiple isotope tracers to evaluate denitrification in ground water: Study of nitrate from a large-flux septic system plume. Ground Water, 36(6): 975-982. 2. Pauwels, H., J.C., Kloppmann, W., 2000. Denitrification and mixing in a schist aquifer: Influence on water chemistry and isotopes. Chemical Geology, 168(3-4): 307-324. Acknowledgment This study was supported by the projects CGL2011-29975-C04-01 from the Spanish Government, 2009SGR-00103 from the Catalan Government and ENPI/2011/280-008 from the European Commission. Please fill in your abstract text.

  19. 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.

  20. Incomplete fuzzy data processing systems using artificial neural network

    Science.gov (United States)

    Patyra, Marek J.

    1992-01-01

    In this paper, the implementation of a fuzzy data processing system using an artificial neural network (ANN) is discussed. The binary representation of fuzzy data is assumed, where the universe of discourse is decartelized into n equal intervals. The value of a membership function is represented by a binary number. It is proposed that incomplete fuzzy data processing be performed in two stages. The first stage performs the 'retrieval' of incomplete fuzzy data, and the second stage performs the desired operation on the retrieval data. The method of incomplete fuzzy data retrieval is proposed based on the linear approximation of missing values of the membership function. The ANN implementation of the proposed system is presented. The system was computationally verified and showed a relatively small total error.

  1. 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.

  2. Light-induced systemic regulation of photosynthesis in primary and trifoliate leaves of Phaseolus vulgaris: effects of photosynthetic photon flux density (PPFD) versus spectrum.

    Science.gov (United States)

    Murakami, K; Matsuda, R; Fujiwara, K

    2014-01-01

    The objectives of this work using Phaseolus vulgaris were to examine whether the light spectrum incident on mature primary leaves (PLs) is related to leaf-to-leaf systemic regulation of developing trifoliate leaves (TLs) in photosynthetic characteristics, and to investigate the relative importance of spectrum and photosynthetic photon flux density (PPFD) in light-induced systemic regulation. Systemic regulation was induced by altering PPFD and the spectrum of light incident on PLs using a shading treatment and lighting treatments including either white, blue, green or red light-emitting diodes (LEDs). Photosynthetic characteristics were evaluated by measuring the light-limited and light-saturated net photosynthetic rates and the amounts of nitrogen (N), chlorophyll (Chl) and ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco; EC 4.1.1.39). Shading treatment on PLs decreased the amounts of N, Chl and Rubisco of TLs and tended to decrease the photosynthetic rates. However, we observed no systemic effects induced by the light spectrum on PLs in this study, except that a higher amount of Rubisco of TLs was observed when the PLs were irradiated with blue LEDs. Our results imply that photoreceptors in mature leaves have little influence on photosynthetic rates and amounts of N and Chl of developing leaves through systemic regulation, although the possibility of the action of blue light irradiation on the amount of Rubisco cannot be ruled out. Based on these results, we concluded that the light spectrum incident on mature leaves has little systemic effect on developing leaves in terms of photosynthetic characteristics and that the light-induced systemic regulation was largely accounted for by PPFD.

  3. 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.

  4. A Survey of Artificial Immune System Based Intrusion Detection

    Directory of Open Access Journals (Sweden)

    Hua Yang

    2014-01-01

    Full Text Available In the area of computer security, Intrusion Detection (ID is a mechanism that attempts to discover abnormal access to computers by analyzing various interactions. There is a lot of literature about ID, but this study only surveys the approaches based on Artificial Immune System (AIS. The use of AIS in ID is an appealing concept in current techniques. This paper summarizes AIS based ID methods from a new view point; moreover, a framework is proposed for the design of AIS based ID Systems (IDSs. This framework is analyzed and discussed based on three core aspects: antibody/antigen encoding, generation algorithm, and evolution mode. Then we collate the commonly used algorithms, their implementation characteristics, and the development of IDSs into this framework. Finally, some of the future challenges in this area are also highlighted.

  5. AISMOTIF-An Artificial Immune System for DNA Motif Discovery

    CERN Document Server

    Seeja, K R

    2011-01-01

    Discovery of transcription factor binding sites is a much explored and still exploring area of research in functional genomics. Many computational tools have been developed for finding motifs and each of them has their own advantages as well as disadvantages. Most of these algorithms need prior knowledge about the data to construct background models. However there is not a single technique that can be considered as best for finding regulatory motifs. This paper proposes an artificial immune system based algorithm for finding the transcription factor binding sites or motifs and two new weighted scores for motif evaluation. The algorithm is enumerative, but sufficient pruning of the pattern search space has been incorporated using immune system concepts. The performance of AISMOTIF has been evaluated by comparing it with eight state of art composite motif discovery algorithms and found that AISMOTIF predicts known motifs as well as new motifs from the benchmark dataset without any prior knowledge about the data...

  6. Hybrid Heuristic-Based Artificial Immune System for Task Scheduling

    CERN Document Server

    sanei, Masoomeh

    2011-01-01

    Task scheduling problem in heterogeneous systems is the process of allocating tasks of an application to heterogeneous processors interconnected by high-speed networks, so that minimizing the finishing time of application as much as possible. Tasks are processing units of application and have precedenceconstrained, communication and also, are presented by Directed Acyclic Graphs (DAGs). Evolutionary algorithms are well suited for solving task scheduling problem in heterogeneous environment. In this paper, we propose a hybrid heuristic-based Artificial Immune System (AIS) algorithm for solving the scheduling problem. In this regard, AIS with some heuristics and Single Neighbourhood Search (SNS) technique are hybridized. Clonning and immune-remove operators of AIS provide diversity, while heuristics and SNS provide convergence of algorithm into good solutions, that is balancing between exploration and exploitation. We have compared our method with some state-of-the art algorithms. The results of the experiments...

  7. 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.

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

    Science.gov (United States)

    Sharif, Mhd Saeed; Abbod, Maysam; Amira, Abbes; Zaidi, Habib

    2010-01-01

    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.

  9. Artificial intelligence methods in deregulated power systems operations

    Science.gov (United States)

    Ilic, Jovan

    With the introduction of the power systems deregulation, many classical power transmission and distribution optimization tools became inadequate. Optimal Power Flow and Unit Commitment are common computer programs used in the regulated power industry. This work is addressing the Optimal Power Flow and Unit Commitment in the new deregulated environment. Optimal Power Flow is a high dimensional, non-linear, and non-convex optimization problem. As such, it is even now, after forty years since its introduction, a research topic without a widely accepted solution able to encompass all areas of interest. Unit Commitment is a high dimensional, combinatorial problem which should ideally include the Optimal Power Flow in its solution. The dimensionality of a typical Unit Commitment problem is so great that even the enumeration of all the combinations would take too much time for any practical purposes. This dissertation attacks the Optimal Power Flow problem using non-traditional tools from the Artificial Intelligence arena. Artificial Intelligence optimization methods are based on stochastic principles. Usually, stochastic optimization methods are successful where all other classical approaches fail. We will use Genetic Programming optimization for both Optimal Power Flow and Unit Commitment. Long processing times will also be addressed through supervised machine learning.

  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. A

  11. 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. A

  12. 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.

  13. Transport, hysteresis and avalanches in artificial spin ice systems

    Energy Technology Data Exchange (ETDEWEB)

    Reichhardt, Charles [Los Alamos National Laboratory; Reichhardt, Cynthia J [Los Alamos National Laboratory; Libal, A [BABES-BOLYAI UNIV.

    2010-01-01

    We examine the hopping dynamics of an artificial spin ice system constructed from colloids on a kagome optical trap array where each trap has two possible states. By applying an external drive from an electric field which is analogous to a biasing applied magnetic field for real spin systems, we can create polarized states that obey the spin-ice rules of two spins in and one spin out at each vertex. We demonstrate that when we sweep the external drive and measure the fraction of the system that has been polarized, we can generate a hysteresis loop analogous to the hysteretic magnetization versus external magnetic field curves for real spin systems. The disorder in our system can be readily controlled by changing the barrier that must be overcome before a colloid can hop from one side of a trap to the other. For systems with no disorder, the effective spins all flip simultaneously as the biasing field is changed, while for strong disorder the hysteresis curves show a series of discontinuous jumps or avalanches similar to Barkhausen noise.

  14. 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.

  15. Visual system based on artificial retina for motion detection.

    Science.gov (United States)

    Barranco, Francisco; Díaz, Javier; Ros, Eduardo; del Pino, Begoña

    2009-06-01

    We present a bioinspired model for detecting spatiotemporal features based on artificial retina response models. Event-driven processing is implemented using four kinds of cells encoding image contrast and temporal information. We have evaluated how the accuracy of motion processing depends on local contrast by using a multiscale and rank-order coding scheme to select the most important cues from retinal inputs. We have also developed some alternatives by integrating temporal feature results and obtained a new improved bioinspired matching algorithm with high stability, low error and low cost. Finally, we define a dynamic and versatile multimodal attention operator with which the system is driven to focus on different target features such as motion, colors, and textures.

  16. 24-epibrassinolide mitigates the adverse effects of manganese induced toxicity through improved antioxidant system and photosynthetic attributes in Brassica juncea.

    Science.gov (United States)

    Fariduddin, Qazi; Ahmed, Mumtaz; Mir, Bilal A; Yusuf, Mohammad; Khan, Tanveer A

    2015-08-01

    The objective of this study was to establish relationship between manganese-induced toxicity and antioxidant system response in Brassica juncea plants and also to investigate whether brassinosteroids activate antioxidant system to confer tolerance to the plants affected with manganese induced oxidative stress. Brassica juncea plants were administered with 3, 6, or 9 mM manganese at 10-day stage for 3 days. At 31-day stage, the seedlings were sprayed with deionized water (control) or 10(-8) M of 24-epibrassinolide, and plants were harvested at 45-day stage to assess growth, leaf gas-exchange traits, and biochemical parameters. The manganese treatments diminished growth along with photosynthetic attributes and carbonic anhydrase activity in the concentration-dependent manner, whereas it enhanced lipid peroxidation, electrolyte leakage, accumulation of H2O2 as well as proline, and various antioxidant enzymes in the leaves of Brassica juncea which were more pronounced at higher concentrations of manganese. However, the follow-up application of 24-epibrassinolide to the manganese stressed plants improved growth, water relations, and photosynthesis and further enhanced the various antioxidant enzymes viz. catalase, peroxidase, and superoxide dismutase and content of proline. The elevated level of antioxidant enzymes as well as proline could have conferred tolerance to the manganese-stressed plants resulting in improved growth and photosynthetic attributes.

  17. 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.

  18. Effects of 24-epibrassinolide on the photosynthetic characteristics, antioxidant system, and chloroplast ultrastructure in Cucumis sativus L. under Ca(NO(3))(2) stress.

    Science.gov (United States)

    Yuan, Lingyun; Shu, Sheng; Sun, Jin; Guo, Shirong; Tezuka, Takafumi

    2012-09-01

    The effects of 0.1 μM 24-epibrassinolide (EBL) on plant growth (plant height, leaf area, fresh weight, and dry weight), chlorophyll content, photosynthetic characteristics, antioxidant enzymes, and chloroplast ultrastructure were investigated using cucumber seedlings (Cucumis sativus L. cv. Jinyou No. 4) with 80 mM Ca(NO(3))(2) to induce stress. The presence of Ca(NO(3))(2) caused significant reductions in net photosynthetic rate (P(N)), stomatal conductance (Gs), intercellular CO(2) concentration (Ci), and transpiration rate (Tr) of leaves. In addition, Ca(NO(3))(2) markedly reduced the chlorophyll content and inhibited photochemical activity, including the actual photochemical efficiency (ΦPSII). In contrast, EBL increased the chlorophyll content, especially chlorophyll b, and minimized the harmful effects on photosynthesis caused by the Ca(NO(3))(2). The application of EBL to the plants subjected to Ca(NO(3))(2)-enhanced photochemical activity. EBL protected the photosynthetic membrane system from oxidative damage due to up-regulating the capacity of the antioxidant systems. Microscopic analyses revealed that Ca(NO(3))(2) affected the structure of the photosynthetic apparatus and membrane system and induced damage of granal thylakoid layers, while EBL recovered the typical shape of chloroplasts and promoted the formation of grana. Taken together, EBL compensated for damage/losses by Ca(NO(3))(2) due to the regulation of photosynthetic characteristics and the antioxidant system.

  19. 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.

  20. Adaptive Control of Artificial Pancreas Systems - A Review

    Directory of Open Access Journals (Sweden)

    Kamuran Turksoy

    2014-01-01

    Full Text Available Artificial pancreas (AP systems offer an important improvement in regulating blood glucose concentration for patients with type 1 diabetes, compared to current approaches. AP consists of sensors, control algorithms and an insulin pump. Different AP control algorithms such as proportional-integral-derivative, model-predictive control, adaptive control, and fuzzy logic control have been investigated in simulation and clinical studies in the past three decades. The variability over time and complexity of the dynamics of blood glucose concentration, unsteady disturbances such as meals, time-varying delays on measurements and insulin infusion, and noisy data from sensors create a challenging system to AP. Adaptive control is a powerful control technique that can deal with such challenges. In this paper, a review of adaptive control techniques for blood glucose regulation with an AP system is presented. The investigations and advances in technology produced impressive results, but there is still a need for a reliable AP system that is both commercially viable and appealing to patients with type 1 diabetes.

  1. VISART: Artificial vision for industrial use. A comprehensive system

    Science.gov (United States)

    Debritoalves, Sdnei

    1992-02-01

    A thorough description of a Computer Vision System applied to inspection activities is presented, all of the life-cycle stages of this system being dealt with in detail. It was conceived, designed, and implemented within the scope of an applied research, entitled (VISART) Artificial Vision for Industrial Use: A Comprehensive System. During the effort employed in the development of this work, significant contributions were incorporated to the state-of-the-art in processing of binary images. The VISART system includes resources, concepts, and inovations not yet seen in similar systems. A new terminology with technical terms nearer to those used by engineers and technicians, in industrial environments, is proposed and it might contribute for acceptance and dissemination of Vision Systems in these environments. Concepts of Group Technology have been associated to Vision Systems and they might contribute for a greater integration of the industrial process automation. A special data structure was conceived for image data storage, allowing to reduce the processing time of algorithms of industrial part features-extraction. A library with a considerable number of feature extraction algorithms, used for recognition, acceptance or rejection of industrial products under inspection, was conceived and implemented. New algorithms can be appended to this library by the user, without the necessity of reprogramming the modules of the VISART system. Within this respect lies one of the main comprisement features of VISART. It has a graphic editor which makes possible to use it in activities such as teaching and formation of skilled personnel in the area of vision. At first, this facility exempts the use of sensors, making it more economic for use in these activities. All in all, this research work is a pioneer in Brazil, and its divulgation must contribute significantly for the dissemination and growth of the computer vision area applied to inspection, in the country.

  2. 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.

  3. SMS Spam Filtering Technique Based on Artificial Immune System

    Directory of Open Access Journals (Sweden)

    Tarek M Mahmoud

    2012-03-01

    Full Text Available The Short Message Service (SMS have an important economic impact for end users and service providers. Spam is a serious universal problem that causes problems for almost all users. Several studies have been presented, including implementations of spam filters that prevent spam from reaching their destination. Nave Bayesian algorithm is one of the most effective approaches used in filtering techniques. The computational power of smart phones are increasing, making increasingly possible to perform spam filtering at these devices as a mobile agent application, leading to better personalization and effectiveness. The challenge of filtering SMS spam is that the short messages often consist of few words composed of abbreviations and idioms. In this paper, we propose an anti-spam technique based on Artificial Immune System (AIS for filtering SMS spam messages. The proposed technique utilizes a set of some features that can be used as inputs to spam detection model. The idea is to classify message using trained dataset that contains Phone Numbers, Spam Words, and Detectors. Our proposed technique utilizes a double collection of bulk SMS messages Spam and Ham in the training process. We state a set of stages that help us to build dataset such as tokenizer, stop word filter, and training process. Experimental results presented in this paper are based on iPhone Operating System (iOS. The results applied to the testing messages show that the proposed system can classify the SMS spam and ham with accurate compared with Nave Bayesian algorithm.

  4. Integrated real time bowel sound detector for artificial pancreas systems

    Directory of Open Access Journals (Sweden)

    Khandaker A. Al Mamun

    2016-03-01

    Full Text Available This paper reports an ultra-low power real time bowel sound detector with integrated feature extractor for physiologic measure of meal instances in artificial pancreas devices. The system can aid in improving long term diabetic patient care and consists of a front end detector and signal processing unit. The front end detector transduces the initial bowel sound recorded from a piezoelectric sensor into a voltage signal. The signal processor uses a feature extractor to determine whether a bowel sound is detected. The feature extractor consists of a low noise, low power signal front-end, peak and trough locator, signal slope and width detector, digitizer, and bowel pulse locator. The system was fabricated in a standard 0.18 μm CMOS process, and the bowel sound detection system was characterized and verified with experimentally recorded bowel sounds. The integrated instrument consumes 53 μW of power from a 1 V supply in a 0.96 mm2 area, and is suitable for integration with portable devices.

  5. The Thoratec system implanted as a modified total artificial heart: the Bad Oeynhausen technique.

    Science.gov (United States)

    Arusoglu, Latif; Reiss, Nils; Morshuis, Michiel; Schoenbrodt, Michael; Hakim-Meibodi, Kavous; Gummert, Jan

    2010-12-01

    The CardioWest™ total artificial heart (SynCardia Systems, Tuscon, AZ, USA) is the only FDA-approved total artificial heart determined as a bridge to human heart transplantation for patients dying of biventricular heart failure. Implantation provides immediate hemodynamic restoration and clinical stabilization, leading to end-organ recovery and thus eventually allowing cardiac transplantation. Occasionally, implantation of a total artificial heart is not feasible for anatomical reasons. For this patient group, we have developed an alternative technique using the paracorporeal Thoratec biventricular support system (Thoratec, Pleasanton, CA, USA) as a modified total artificial heart. A detailed description of the implantation technique is presented.

  6. Environmentally Conscious Polishing System Based on Robotics and Artificial Vision

    Directory of Open Access Journals (Sweden)

    J. A. Dieste

    2015-02-01

    Full Text Available Polishing process is one of the manufacturing issues that are essential in the production flow, but it generates the major amount of defects on parts. Finishing tasks in which polishing is included are performed in the final steps of the manufacturing sequence. Any defect in these steps impliesrejection of the part, generating a big amount of scrap and generating a huge amount of energy consumption, emission, and time to manufacture and replace the rejected part. Traditionally polishing process has not evolved during the last 30 years, while other manufacturing processes have been automated and technologically improved. Finishing processes (grinding and polishing, are still manually performed, especially in freeform surface parts, but to be sustainable some development and automation have to be introduced. This research proposes a novel polishing system based on robotics and artificial vision. The application of this novel system has allowed reducing the failed parts due to finishing process down to zero percent from 28% of rejected parts with manual polishing process. The reduction in process time consumption, and amount of scrapped parts, has reduced the energy consumption up to 30% in finishing process and 20% in whole manufacturing process for an injection moulded aluminium part for automotive industry with high production volumes.

  7. 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.

  8. Phosphorus fate, management, and modeling in artificially drained systems.

    Science.gov (United States)

    Kleinman, Peter J A; Smith, Douglas R; Bolster, Carl H; Easton, Zachary M

    2015-03-01

    Phosphorus (P) losses in agricultural drainage waters, both surface and subsurface, are among the most difficult form of nonpoint source pollution to mitigate. This special collection of papers on P in drainage waters documents the range of field conditions leading to P loss in drainage water, the potential for drainage and nutrient management practices to control drainage losses of P, and the ability of models to represent P loss to drainage systems. A review of P in tile drainage and case studies from North America, Europe, and New Zealand highlight the potential for artificial drainage to exacerbate watershed loads of dissolved and particulate P via rapid, bypass flow and shorter flow path distances. Trade-offs are identified in association with drainage intensification, tillage, cover crops, and manure management. While P in drainage waters tends to be tied to surface sources of P (soil, amendments or vegetation) that are in highest concentration, legacy sources of P may occur at deeper depths or other points along drainage flow paths. Most startling, none of the major fate-and-transport models used to predict management impacts on watershed P losses simulate the dominant processes of P loss to drainage waters. Because P losses to drainage waters can be so difficult to manage and to model, major investment are needed (i) in systems that can provide necessary drainage for agronomic production while detaining peak flows and promoting P retention and (ii) in models that can adequately describe P loss to drainage waters.

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

    OpenAIRE

    2013-01-01

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

  10. 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

  11. Network modeling of membrane-based artificial cellular systems

    Science.gov (United States)

    Freeman, Eric C.; Philen, Michael K.; Leo, Donald J.

    2013-04-01

    Computational models are derived for predicting the behavior of artificial cellular networks for engineering applications. The systems simulated involve the use of a biomolecular unit cell, a multiphase material that incorporates a lipid bilayer between two hydrophilic compartments. These unit cells may be considered building blocks that enable the fabrication of complex electrochemical networks. These networks can incorporate a variety of stimuli-responsive biomolecules to enable a diverse range of multifunctional behavior. Through the collective properties of these biomolecules, the system demonstrates abilities that recreate natural cellular phenomena such as mechanotransduction, optoelectronic response, and response to chemical gradients. A crucial step to increase the utility of these biomolecular networks is to develop mathematical models of their stimuli-responsive behavior. While models have been constructed deriving from the classical Hodgkin-Huxley model focusing on describing the system as a combination of traditional electrical components (capacitors and resistors), these electrical elements do not sufficiently describe the phenomena seen in experiment as they are not linked to the molecular scale processes. From this realization an advanced model is proposed that links the traditional unit cell parameters such as conductance and capacitance to the molecular structure of the system. Rather than approaching the membrane as an isolated parallel plate capacitor, the model seeks to link the electrical properties to the underlying chemical characteristics. This model is then applied towards experimental cases in order that a more complete picture of the underlying phenomena responsible for the desired sensing mechanisms may be constructed. In this way the stimuli-responsive characteristics may be understood and optimized.

  12. 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.

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

    Directory of Open Access Journals (Sweden)

    Xiaobang Peng

    Full Text Available 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 (< 3 m to the 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.

  14. [The application and development of artificial intelligence in medical diagnosis systems].

    Science.gov (United States)

    Chen, Zhencheng; Jiang, Yong; Xu, Mingyu; Wang, Hongyan; Jiang, Dazong

    2002-09-01

    This paper has reviewed the development of artificial intelligence in medical practice and medical diagnostic expert systems, and has summarized the application of artificial neural network. It explains that a source of difficulty in medical diagnostic system is the co-existence of multiple diseases--the potentially inter-related diseases. However, the difficulty of image expert systems is inherent in high-level vision. And it increases the complexity of expert system in medical image. At last, the prospect for the development of artificial intelligence in medical image expert systems is made.

  15. Spatial coherence of thermal photons favors photosynthetic life

    CERN Document Server

    Manrique, Pedro; Caycedo-Soler, Felipe; Rodríguez, Ferney; Quiroga, Luis; Johnson, Neil

    2015-01-01

    Harvesting of sunlight underpins Life on Earth as well as driving novel energy device design. Though several experiments suggest that excitation energy transport and charge separation within a photosynthetic membrane may benefit from the quantum nature of their dynamics, the effects of spatial coherences in the incident light have been largely ignored. Here we show that spatial correlations in the incident light likely play an important role in trapping light and adding robustness, as well as providing a driving mechanism for an organism's adaptation toward more ordered structures. Our theory is grounded by empirical inputs, while its output is validated against testable predictions. Our results suggest that spatiotemporal correlations between photons, a fundamental property of the quantum world, should play a key role in our understanding of early Life and in improving the design of artificial photosynthetic systems.

  16. Artificial intelligence approach for spot application project system design

    Science.gov (United States)

    Lefevre, M. J.; Fisse, G.; Martin, E.; de Boissezon, H.; Galaup, M.

    1993-11-01

    Over the past four years, CNES has been engaged in a major programme focusing on the development of SPOT Operational Application Projects. With a total of sixty projects now complete, we can draw a number of meaningful conclusions and identify a number of objectives to be satisfied by advanced remote sensing methodology. One of the main conclusions points to the importance of human vision in studies on natural complex space imagery. This being so, visual recognition must be one of the main phases of the ``Pilot Project for the Application of Remote Sensing to Agricultural Statistics'': only human experts have the ability to make a meaningful analysis of Spot TM imagery. Non-expert operators will not be able to manage the subsequent rational production phase alone. The first part of this paper describes an approach to the formalization and modelling of expert know-how based on the use of artificial intelligence. The second part puts forward a cooperative operator/computer system based on a cognitive structure. Our proposal comprises 1) a specific knowledge base, 2) an ergonomic interface associated with functional software that is based on automatic image enhancement coupled with perception support functions.

  17. EXPLORATION OF STYLIZED FACTS IN THE ARTIFICIAL LIFE SYSTEM AVIDA

    Directory of Open Access Journals (Sweden)

    Shinta Koyano

    2016-09-01

    Full Text Available Population dynamics in the evolution, extinction, and re-evolution of various logic-function performing organisms is studied in the artificial life system, Avida. Following the work of Yedid (2009, we design an experiment involving two extinction regimes, pulse-extinction (corresponding to a random-kill event and press-extinction (corresponding to a prolonged episode of rare resources. In addition, we study the effect of environmental topology (toroidal grid and clique graph. In the study of population dynamics, logarithmic returns are generally applied. The resulting distributions display a fat tail form of the power law: the more complex the logic function (in terms of NAND components, the broader the full width at half a maximum of the histogram. The power law exponents were in sound agreement with those of “real-life” populations and distributions. The distributions of evolutionary times, as well as post-extinction recovery periods, were very broad, and presumably had no standard deviations. Using 100 runs of 200,000 updates for each of the four cases (about 1 month of central processing unit time, we established the dynamics of the average population, with the effect of world topology.

  18. [Cashmere goat bacterial artificial chromosome recombination and cell transfection system].

    Science.gov (United States)

    Huang, Tian; Cao, Zhongyang; Yang, Yaohui; Cao, Gengsheng

    2016-03-01

    The Cashmere goat is mainly used to produce cashmere, which is very popular for its delicate fiber, luscious softness and natural excellent warm property. Keratin associated protein (KAP) and bone morphogenetic protein (BMP) of the Cashmere goat play an important role in the proliferation and development of cashmere fiber follicle cells. Bacterial artificial chromosome containing kap6.3, kap8.1 and bmp4 genes were used to increase the production and quality of Cashmere. First, we constructed bacterial artificial chromosomes by homology recombination. Then Tol2 transposon was inserted into bacterial artificial chromosomes that were then transfected into Cashmere goat fibroblasts by Amaxa Nucleofector technology according to the manufacture's instructions. We successfully constructed the BAC-Tol2 vectors containing target genes. Each vector contained egfp report gene with UBC promoter, Neomycin resistant gene for cell screening and two loxp elements for resistance removing after transfected into cells. The bacterial artificial chromosome-Tol2 vectors showed a high efficiency of transfection that can reach 1% to 6% with a highest efficiency of 10%. We also obtained Cashmere goat fibroblasts integrated exogenous genes (kap6.3, kap8.1 and bmp4) preparing for the clone of Cashmere goat in the future. Our research demonstrates that the insertion of Tol2 transposons into bacterial artificial chromosomes improves the transfection efficiency and accuracy of bacterial artificial chromosome error-free recombination.

  19. Optimal secondary coil design for inductive powering of the Artificial Accommodation System.

    Science.gov (United States)

    Nagel, J A; Krug, M; Gengenbach, U; Guth, H; Bretthauer, G; Guthoff, R F

    2011-01-01

    Age-related ailments like presbyopia and cataract are increasing concerns in the aging society. Both go along with a loss of ability to accommodate. A new approach to restore the patients' ability to accommodate is the Artificial Accommodation System. This micro mechatronic system will be implanted into the capsular bag to replace the human crystalline lens. Depending on the patients' actual need for accommodation, the Artificial Accommodation System autonomously adapts the refractive power of its integrated optical element in a way that the projection on the patients' retina results in a sharp image. As the Artificial Accommodation System is an active implant, its subsystems have to be supplied with electrical energy. Evolving technologies, like energy harvesting, which can potentially be used to power an implant like the Artificial Accommodation System are at the current state of art not sufficient to power the Artificial Accommodation System autonomously [1]. In the near future, therefore an inductive power supply system will be developed which includes an energy storage to power the Artificial Accommodation System autonomously over a period of 24 h and can be recharged wirelessly. This Paper describes a new possibility to optimize the secondary coil design in a solely analytical way, based on a new figure of merit. Within this paper the developed figure of merit is applied to optimize the secondary coil design for the Artificial Accommodation System.

  20. Homologous Comparisons of Photosynthetic System 1 Genes among Cyanobacteria and Chloroplasts

    Institute of Scientific and Technical Information of China (English)

    Jie Yu; Pei-Jun Ma; Ding-Ji Shi; Shi-Ming Li; Chang-Lu Wang

    2008-01-01

    It has now believed that chloroplasts arose from cyanobacteria,however,during endosymbiosis,the photosynthetic genes in chloroplasts have been reduced.How these changes occurred during plant evolution was the focus of the present study.Beginning with photosystem Ⅰ (PSI) genes,a homologous comparison of amino acid sequences of 18 subunits of PSI from 10 species of cyanobacteria,chloroplasts in 12 species of eucaryotic algae,and 28 species of plants (including bryophytes,pteridophytes,gymnospermae,dicotyledon and monocotyledon) was undertaken.The data showed that 18 genes of PSIcan be divided into two groups: Part Ⅰ including seven genes (psaA,psaB,psaC,psaI,psaJ,yct3 and ycf4) shared both by cyanobacteria and plant chloroplasts;Part Ⅱ containing another 11 genes (psaD,psaE,psaF,psaK,psaL,psaM,btpA,ycf37,psaG,psaH and psaN) appeared to have diversified in different plant groups.Among Part I genes,psaC,psaA and psaB had higher homology in all species of cyanobacteria and chloroplasts.Among Part II genes,only psaG,psaH and psaN emerged in seed plants.

  1. 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...

  2. Multifunctional astronomical self-organizing system of autonomous navigation and orientation for artificial Earth satellites

    Science.gov (United States)

    Kuznetsov, V. I.; Danilova, T. V.

    2017-03-01

    We describe the methods and algorithms of a multifunctional astronomical system of the autonomous navigation and orientation for artificial Earth satellites based on the automatization of the system approach to the design and programming problems of the subject area.

  3. 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.

  4. Promising synergies of simulation model management, software engineering, artificial intelligence, and general system theories

    Energy Technology Data Exchange (ETDEWEB)

    Oren, T.I.

    1982-01-01

    Simulation is viewed within the model management paradigm. Major components of simulation systems as well as elements of model management are outlined. Possible synergies of simulation model management, software engineering, artificial intelligence, and general system theories are systematized. 21 references.

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

    Institute of Scientific and Technical Information of China (English)

    Tian Sheping; Ding Guoqing; Yan Detian; Lin Liangming

    2004-01-01

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

  6. Blood feeding of Ornithodoros turicata larvae using an artificial membrane system

    Science.gov (United States)

    An artificial membrane system was adapted to feed Ornithodoros turicata larvae from a laboratory colony using defibrinated swine blood. Aspects related to larval feeding and molting to the 1st nymphal instar were evaluated. Fifty-five percent of all larvae exposed to the artificial membrane in two e...

  7. Implications of Human Pattern Processing for the Design of Artificial Knowledge Systems.

    Science.gov (United States)

    Hayes-Roth, Barbara

    This paper presents evidence that four design principles commonly embodied in artificial knowledge systems are inconsistent with human cognitive capabilities. Because these principles are widely accepted as characteristics of human knowledge processing, common theoretical properties related to cognitive psychology and artificial intelligence which…

  8. 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.

  9. Next Challenges in Bringing Artificial Immune Systems to Production in Network Security

    OpenAIRE

    Hilker, Michael

    2008-01-01

    The human immune system protects the human body against various pathogens like e.g. biological viruses and bacteria. Artificial immune systems reuse the architecture, organization, and workflows of the human immune system for various problems in computer science. In the network security, the artificial immune system is used to secure a network and its nodes against intrusions like viruses, worms, and trojans. However, these approaches are far away from production where they are academic proof...

  10. 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.

  11. A novel artificial anal sphincter system based on transcutaneous energy transmission

    Institute of Scientific and Technical Information of China (English)

    Zan Peng; Yan Guozheng; Liu Hua

    2008-01-01

    For controlling anal incontinence, a new artificial anal sphincter system (AASS) with sensor feedback based on transcutaneous energy transmission is developed. The device mainly comprises an artificial anal sphincter (AAS), a wireless power supply subsystem, and a communication subsystem. The artificial anal sphincter comprises a front cuff and a sensor cuff placed around the rectum, a reservoir sited in abdominal cavity and a micropump controlling inflation and deflation of the front cuff. There are two pressure sensors in the artificial anal sphincter. One can measure the pressure in the front cuff to clamp the rectum, the other in the sensor cuff can measure the pressure of the rectum. Wireless power supply subsystem includes a resonance transmit coil to transmit an alternating magnetic field and a secondary coil to receive the power. Wireless communication subsystem can transmit the pressure information of the artificial anal sphincter to the monitor, or send the control commands to the artificial anal sphincter. A prototype is designed and the basic function of the artificial anal sphincter system has been tested through experiments. The results demonstrate that the artificial anal sphincter system can control anal incontinence effectively.

  12. Next Challenges in Bringing Artificial Immune Systems to Production in Network Security

    CERN Document Server

    Hilker, Michael

    2008-01-01

    The human immune system protects the human body against various pathogens like e.g. biological viruses and bacteria. Artificial immune systems reuse the architecture, organization, and workflows of the human immune system for various problems in computer science. In the network security, the artificial immune system is used to secure a network and its nodes against intrusions like viruses, worms, and trojans. However, these approaches are far away from production where they are academic proof-of-concept implementations or use only a small part to protect against a certain intrusion. This article discusses the required steps to bring artificial immune systems into production in the network security domain. It furthermore figures out the challenges and provides the description and results of the prototype of an artificial immune system, which is SANA called.

  13. In vitro selection with artificial expanded genetic information systems.

    Science.gov (United States)

    Sefah, Kwame; Yang, Zunyi; Bradley, Kevin M; Hoshika, Shuichi; Jiménez, Elizabeth; Zhang, Liqin; Zhu, Guizhi; Shanker, Savita; Yu, Fahong; Turek, Diane; Tan, Weihong; Benner, Steven A

    2014-01-28

    Artificially expanded genetic information systems (AEGISs) are unnatural forms of DNA that increase the number of independently replicating nucleotide building blocks. To do this, AEGIS pairs are joined by different arrangements of hydrogen bond donor and acceptor groups, all while retaining their Watson-Crick geometries. We report here a unique case where AEGIS DNA has been used to execute a systematic evolution of ligands by exponential enrichment (SELEX) experiment. This AEGIS-SELEX was designed to create AEGIS oligonucleotides that bind to a line of breast cancer cells. AEGIS-SELEX delivered an AEGIS aptamer (ZAP-2012) built from six different kinds of nucleotides (the standard G, A, C, and T, and the AEGIS nonstandard P and Z nucleotides, the last having a nitro functionality not found in standard DNA). ZAP-2012 has a dissociation constant of 30 nM against these cells. The affinity is diminished or lost when Z or P (or both) is replaced by standard nucleotides and compares well with affinities of standard GACT aptamers selected against cell lines using standard SELEX. The success of AEGIS-SELEX relies on various innovations, including (i) the ability to synthesize GACTZP libraries, (ii) polymerases that PCR amplify GACTZP DNA with little loss of the AEGIS nonstandard nucleotides, and (iii) technologies to deep sequence GACTZP DNA survivors. These results take the next step toward expanding the power and utility of SELEX and offer an AEGIS-SELEX that could possibly generate receptors, ligands, and catalysts having sequence diversities nearer to that displayed by proteins.

  14. 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%).

  15. Research on architecture of intelligent design platform for artificial neural network expert system

    Science.gov (United States)

    Gu, Honghong

    2017-09-01

    Based on the review of the development and current situation of CAD technology, the necessity of combination of artificial neural network and expert system, and then present an intelligent design system based on artificial neural network. Moreover, it discussed the feasibility of realization of a design-oriented expert system development tools on the basis of above combination. In addition, knowledge representation strategy and method and the solving process are given in this paper.

  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. Rapid transfer of photosynthetic carbon through the plant-soil system in differently managed grasslands

    Directory of Open Access Journals (Sweden)

    G. B. De Deyn

    2011-02-01

    Full Text Available Plant-soil interactions are central to short-term carbon (C cycling through the rapid transfer of recently assimilated C from plant roots to soil biota. In grassland ecosystems, changes in C cycling are likely to be influenced by land use and management that changes vegetation and the associated soil microbial communities. Here we tested whether changes in grassland vegetation composition resulting from management for plant diversity influences short-term rates of C assimilation, retention and transfer from plants to soil microbes. To do this, we used an in situ 13C-CO2 pulse-labeling approach to measure differential C uptake among different plant species and the transfer of the plant-derived 13C to key groups of soil microbiota across selected treatments of a long-term plant diversity grassland restoration experiment. Results showed that plant taxa differed markedly in the rate of 13C assimilation and retention: uptake was greatest and retention lowest in Ranunculus repens, and assimilation was least and retained longest in mosses. Incorporation of recent plant-derived 13C was maximal in all microbial phosopholipid fatty acid (PLFA markers at 24 h after labeling. The greatest incorporation of 13C was in the PLFA 16:1ω5, a marker for arbuscular mycorrhizal fungi (AMF, while after one week most 13C was retained in the PLFA 18:2ω6,9 which is indicative of assimilation of plant-derived 13C by saprophytic fungi. Our results of 13C assimilation, transfer and retention within plant species and soil microbes were consistent across management treatments. Overall, our findings suggest that changes in vegetation and soil microbial composition resulting from differences in long-term grassland management will affect short-term cycling of photosynthetic C, but that restoration management does not alter the short-term C uptake and transfer within plant

  18. 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 orie

  19. 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

  20. An Efficient Quantum Jump Method for Coherent Energy Transfer Dynamics in Photosynthetic Systems under the Influence of Laser Fields

    CERN Document Server

    Ai, Qing; Jin, Bih-Yaw; Cheng, Yuan-Chung

    2014-01-01

    We present a non-Markovian quantum jump approach for simulating coherent energy transfer dynamics in molecular systems in the presence of laser fields. By combining a coherent modified Redfield theory (CMRT) and a non-Markovian quantum jump (NMQJ) method, this new approach inherits the broad-range validity from the CMRT and highly efficient propagation from the NMQJ. To implement NMQJ propagation of CMRT, we show that the CMRT master equation can be casted into a generalized Lindblad form. Moreover, we extend the NMQJ approach to treat time-dependent Hamiltonian, enabling the description of excitonic systems under coherent laser fields. As a benchmark of the validity of this new method, we show that the CMRT-NMQJ method accurately describes the energy transfer dynamics in a prototypical photosynthetic complex. Finally, we apply this new approach to simulate the quantum dynamics of a dimer system coherently excited to coupled single-excitation states under the influence of laser fields, which allows us to inve...

  1. 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.

  2. 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.

  3. A REVIEW ON ARTIFICIAL INTELLIGENT SYSTEM FOR BEARING CONDITION MONITORING

    Directory of Open Access Journals (Sweden)

    PIYUSH M. PATEL,

    2011-02-01

    Full Text Available Artificial Intelligence (AI is an emerging technology. Research in AI is focused on developing computational approaches to intelligent behavior. The computer programs with which AI could be associated are primarily processes associated with complexity, ambiguity, ndecisiveness, and uncertainty. This present paper surveys the development of a condition monitoring procedure for different types ofbearings, which involves an artificial intelligence method as well as reviewed in order to examine the capability of AI methods and techniques to effectively address various hard-to-solve design tasks and issues relating different types of bearing fault. Although this review cannot be collectively exhaustive, it may be considered as a valuable guide for researchers who are interested in the domain of AI and wish to explore the opportunities offered by fuzzy logic, artificial neural networks and genetic algorithms for further improvement of conditioning monitoring for different types of bearing under different operating conditioning. Recent trends in research on conditioning monitoring using AI for different bearing have also been included.

  4. 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.

  5. Photosynthetic Characterization of Plant Functional Types from Coastal Tundra to Improve Representation of the Arctic in Earth System Models

    Science.gov (United States)

    Rogers, A.; Xu, C.; McDowell, N. G.; Sloan, V. L.; Norby, R. J.

    2012-12-01

    The primary goal of Earth System Models (ESMs) is to improve understanding and projection of future global change. In order to do this they must accurately represent the carbon fluxes associated with the terrestrial carbon cycle. Photosynthetic CO2 uptake is well described by the Farquhar, von Caemmerer and Berry model of photosynthesis, and most ESMs use a derivation of this model. One of the key parameters required by the Farquhar, von Caemmerer and Berry model is an estimate of the maximum rate of carboxylation by the enzyme Rubisco (Vc,max). In ESMs the parameter Vc,max is usually fixed for a given plant functional type (PFT) and often estimated from the empirical relationship between leaf N content and Vc,max. However, uncertainty in the estimation of Vc,max has been shown to account for significant variation in model estimation of gross primary production, particularly in the Arctic. As part of a new multidisciplinary project to improve the representation of the Arctic in ESMs (Next Generation Ecosystem Experiments - Arctic) we have begun to characterize photosynthetic parameters and N acquisition in the key Arctic PFTs. We measured the response of photosynthesis (A) to internal CO2 concentration (ci) in situ in two sedges (Carex aquatilis, Eriophorum angustifolium), a grass (Dupontia fisheri) and a forb (Petasites frigidus) growing on the Barrow Environmental Observatory, Barrow, AK. The values of Vc,max (normalized to 25oC) currently used to represent Arctic PFTs in ESMs are approximately half of the values we measured in these species in July, 2012, on the coastal tundra in Barrow. We hypothesize that these plants have a greater fraction of leaf N invested in Rubisco (FLNR) than is assumed by the models. The parameter Vc,max is used directly as a driver for respiration in some ESMs, and in other ESMs Vc,max is linked to leaf N content and N acquisition through FLNR. Therefore, these results have implications for ESMs beyond photosynthesis, and suggest that

  6. 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.

  7. A Hybrid Approach Towards Intrusion Detection Based on Artificial Immune System and Soft Computing

    CERN Document Server

    Sanyal, Sugata

    2012-01-01

    A number of works in the field of intrusion detection have been based on Artificial Immune System and Soft Computing. Artificial Immune System based approaches attempt to leverage the adaptability, error tolerance, self- monitoring and distributed nature of Human Immune Systems. Whereas Soft Computing based approaches are instrumental in developing fuzzy rule based systems for detecting intrusions. They are computationally intensive and apply machine learning (both supervised and unsupervised) techniques to detect intrusions in a given system. A combination of these two approaches could provide significant advantages for intrusion detection. In this paper we attempt to leverage the adaptability of Artificial Immune System and the computation intensive nature of Soft Computing to develop a system that can effectively detect intrusions in a given network.

  8. 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…

  9. 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

  10. The Artificial Reverberation Real-time Processing System Based On DSP

    Institute of Scientific and Technical Information of China (English)

    WEN Chuan-xue; ZHENG Sheng-lin; ZHANG Cheng-yun

    2008-01-01

    A real-time process system of artificial reverberation based on fixed-point DSP is presented in this paper. This paper dis- cusses the hardware interface and software between TMS320VC5509 DSP chip and TLV320AIC23 cedee chip. Based on this, it intro- duces the design and working of the artificial reverberation algorithm. At last, the paper discusses the sticking point in realization of real-time process.

  11. MINUTIAE EXTRACTION BASED ON ARTIFICIAL NEURAL NETWORKS FOR AUTOMATIC FINGERPRINT RECOGNITION SYSTEMS

    Directory of Open Access Journals (Sweden)

    Necla ÖZKAYA

    2007-01-01

    Full Text Available Automatic fingerprint recognition systems are utilised for personal identification with the use of comparisons of local ridge characteristics and their relationships. Critical stages in personal identification are to extract features automatically, fast and reliably from the input fingerprint images. In this study, a new approach based on artificial neural networks to extract minutiae from fingerprint images is developed and introduced. The results have shown that artificial neural networks achieve the minutiae extraction from fingerprint images with high accuracy.

  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. Solar fuels via artificial photosynthesis.

    Science.gov (United States)

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

    2009-12-21

    Because sunlight is diffuse and intermittent, substantial use of solar energy to meet humanity's needs will probably require energy storage in dense, transportable media via chemical bonds. Practical, cost effective technologies for conversion of sunlight directly into useful fuels do not currently exist, and will require new basic science. Photosynthesis provides a blueprint for solar energy storage in fuels. Indeed, all of the fossil-fuel-based energy consumed today derives from sunlight harvested by photosynthetic organisms. Artificial photosynthesis research applies the fundamental scientific principles of the natural process to the design of solar energy conversion systems. These constructs use different materials, and researchers tune them to produce energy efficiently and in forms useful to humans. Fuel production via natural or artificial photosynthesis requires three main components. First, antenna/reaction center complexes absorb sunlight and convert the excitation energy to electrochemical energy (redox equivalents). Then, a water oxidation complex uses this redox potential to catalyze conversion of water to hydrogen ions, electrons stored as reducing equivalents, and oxygen. A second catalytic system uses the reducing equivalents to make fuels such as carbohydrates, lipids, or hydrogen gas. In this Account, we review a few general approaches to artificial photosynthetic fuel production that may be useful for eventually overcoming the energy problem. A variety of research groups have prepared artificial reaction center molecules. These systems contain a chromophore, such as a porphyrin, covalently linked to one or more electron acceptors, such as fullerenes or quinones, and secondary electron donors. Following the excitation of the chromophore, photoinduced electron transfer generates a primary charge-separated state. Electron transfer chains spatially separate the redox equivalents and reduce electronic coupling, slowing recombination of the charge

  14. The Photosynthetic Cycle

    Science.gov (United States)

    Calvin, Melvin

    1955-03-21

    A cyclic sequence of transformations, including the carboxylation of RuDP (ribulose diphosphate) and its re-formation, has been deduced as the route for the creation of reduced carbon compounds in photosynthetic organisms. With the demonstration of RuDP as substrate for the carboxylation in a cell-free system, each of the reactions has now been carried out independently in vitro. Further purification of this last enzyme system has confirmed the deduction that the carboxylation of RuDP leads directly to the two molecules of PGA (phosphoglyceric acid) involving an internal dismutation and suggesting the name "carboxydismutase" for the enzyme. As a consequence of this knowledge of each of the steps in the photosynthetic CO{sub 2} reduction cycle, it is possible to define the reagent requirements to maintain it. The net requirement for the reduction of one molecule of CO{sub 2} is four equivalents of [H]and three molecules of ATP (adenine triphosphate). These must ultimately be supplied by the photochemical reaction. Some possible ways in which this may be accomplished are discussed.

  15. New Trends in Computing Anticipatory Systems : Emergence of Artificial Conscious Intelligence with Machine Learning Natural Language

    Science.gov (United States)

    Dubois, Daniel M.

    2008-10-01

    This paper deals with the challenge to create an Artificial Intelligence System with an Artificial Consciousness. For that, an introduction to computing anticipatory systems is presented, with the definitions of strong and weak anticipation. The quasi-anticipatory systems of Robert Rosen are linked to open-loop controllers. Then, some properties of the natural brain are presented in relation to the triune brain theory of Paul D. MacLean, and the mind time of Benjamin Libet, with his veto of the free will. The theory of the hyperincursive discrete anticipatory systems is recalled in view to introduce the concept of hyperincursive free will, which gives a similar veto mechanism: free will as unpredictable hyperincursive anticipation The concepts of endo-anticipation and exo-anticipation are then defined. Finally, some ideas about artificial conscious intelligence with natural language are presented, in relation to the Turing Machine, Formal Language, Intelligent Agents and Mutli-Agent System.

  16. 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

  17. Effects of artificial lighting on the detection of plant stress with spectral reflectance remote sensing in bioregenerative life support systems

    Science.gov (United States)

    Schuerger, Andrew C.; Richards, Jeffrey T.

    2006-09-01

    Plant-based life support systems that utilize bioregenerative technologies have been proposed for long-term human missions to both the Moon and Mars. Bioregenerative life support systems will utilize higher plants to regenerate oxygen, water, and edible biomass for crews, and are likely to significantly lower the ‘equivalent system mass’ of crewed vehicles. As part of an ongoing effort to begin the development of an automatic remote sensing system to monitor plant health in bioregenerative life support modules, we tested the efficacy of seven artificial illumination sources on the remote detection of plant stresses. A cohort of pepper plants (Capsicum annuum L.) were grown 42 days at 25 °C, 70% relative humidity, and 300 μmol m-2 s-1 of photosynthetically active radiation (PAR; from 400 to 700 nm). Plants were grown under nutritional stresses induced by irrigating subsets of the plants with 100, 50, 25, or 10% of a standard nutrient solution. Reflectance spectra of the healthy and stressed plants were collected under seven artificial lamps including two tungsten halogen lamps, plus high pressure sodium, metal halide, fluorescent, microwave, and red/blue light emitting diode (LED) sources. Results indicated that several common algorithms used to estimate biomass and leaf chlorophyll content were effective in predicting plant stress under all seven illumination sources. However, the two types of tungsten halogen lamps and the microwave illumination source yielded linear models with the highest residuals and thus the highest predictive capabilities of all lamps tested. The illumination sources with the least predictive capabilities were the red/blue LEDs and fluorescent lamps. Although the red/blue LEDs yielded the lowest residuals for linear models derived from the remote sensing data, the LED arrays used in these experiments were optimized for plant productivity and not the collection of remote sensing data. Thus, we propose that if adjusted to optimize the

  18. An excitation-dependent four-level model for quantum entanglement in photosynthetic systems

    CERN Document Server

    Chang, Chi-Han; Scholes, Gregory D; James, Daniel F V

    2012-01-01

    We model energy transfer between two coupled four-level chromophores with arbitrarily spaced energy levels. Our analysis takes into account the crucial---yet often ignored---process of initial excitation by light that is incident on the chromophores. We show that the amount of entanglement generated between the chromophores is strongly dependent on the degree of initial excitation as well as the inclusion of higher energy levels. We apply our model to the specific example of chlorophyll. Our results suggest that an excitation-dependent approach should be employed for entanglement studies on multi-level light-harvesting systems even when a two-level approximation is valid.

  19. 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.

  20. A comparative study of artificial intelligent-based maximum power point tracking for photovoltaic systems

    Science.gov (United States)

    Hussain Mutlag, Ammar; Mohamed, Azah; Shareef, Hussain

    2016-03-01

    Maximum power point tracking (MPPT) is normally required to improve the performance of photovoltaic (PV) systems. This paper presents artificial intelligent-based maximum power point tracking (AI-MPPT) by considering three artificial intelligent techniques, namely, artificial neural network (ANN), adaptive neuro fuzzy inference system with seven triangular fuzzy sets (7-tri), and adaptive neuro fuzzy inference system with seven gbell fuzzy sets. The AI-MPPT is designed for the 25 SolarTIFSTF-120P6 PV panels, with the capacity of 3 kW peak. A complete PV system is modelled using 300,000 data samples and simulated in the MATLAB/SIMULINK. The AI-MPPT has been tested under real environmental conditions for two days from 8 am to 18 pm. The results showed that the ANN based MPPT gives the most accurate performance and then followed by the 7-tri-based MPPT.

  1. Comparison of Scale in a Photosynthetic Reactor System for Algal Remediation of Wastewater.

    Science.gov (United States)

    Sniffen, Kaitlyn D; Sales, Christopher M; Olson, Mira S

    2017-03-06

    An experimental methodology is presented to compare the performance of two different sized reactors designed for wastewater treatment. In this study, ammonia removal, nitrogen removal and algal growth are compared over an 8-week period in paired sets of small (100 L) and large (1,000 L) reactors designed for algal remediation of landfill wastewater. Contents of the small and large scale reactors were mixed before the beginning of each weekly testing interval to maintain equivalent initial conditions across the two scales. System characteristics, including surface area to volume ratio, retention time, biomass density, and wastewater feed concentrations, can be adjusted to better equalize conditions occurring at both scales. During the short 8-week representative time period, starting ammonia and total nitrogen concentrations ranged from 3.1-14 mg NH3-N/L, and 8.1-20.1 mg N/L, respectively. The performance of the treatment system was evaluated based on its ability to remove ammonia and total nitrogen and to produce algal biomass. Mean ± standard deviation of ammonia removal, total nitrogen removal and biomass growth rates were 0.95±0.3 mg NH3-N/L/day, 0.89±0.3 mg N/L/day, and 0.02±0.03 g biomass/L/day, respectively. All vessels showed a positive relationship between the initial ammonia concentration and ammonia removal rate (R(2)=0.76). Comparison of process efficiencies and production values measured in reactors of different scale may be useful in determining if lab-scale experimental data is appropriate for prediction of commercial-scale production values.

  2. Elucidating the toxicity targets of {beta}-ionone on photosynthetic system of Microcystis aeruginosa NIES-843 (Cyanobacteria)

    Energy Technology Data Exchange (ETDEWEB)

    Shao Jihai, E-mail: shaojihai@yahoo.com.cn [Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072 (China); College of Resources and Environment, Hunan Agricultural University, Changsha, 410128 (China); Xu Yao [Department of Environmental Science and Engineering, College of Geography Science, Nanjing Normal University, Nanjing, 210046 (China); Wang Zhongjie; Jiang Yongguang [Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072 (China); Graduate University of Chinese Academy of Sciences, Beijing, 100039 (China); Yu Gongliang; Peng Xin [Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072 (China); Li Renhui, E-mail: reli@ihb.ac.cn [Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072 (China)

    2011-07-15

    In order to explore the potential targets of toxicity of {beta}-ionone on the photosynthetic system of Microcystis aeruginosa, the polyphasic rise in chlorophyll a (Chl a) fluorescence transient and transcript expression for key genes in photosystem II (PSII) of M. aeruginosa NIES-843 were studied. The EC{sub 50} value of {beta}-ionone on M. aeruginosa NIES-843 was found to be 21.23 {+-} 1.87 mg/L. It was shown that {beta}-Ionone stress can lead to a decrease in pigment content of M. aeruginosa NIES-843 cells, and that carotenoids were more sensitive to {beta}-ionone stress than Chl a. The normalized Chl a fluorescence transients were slightly decreased at 6.67 and 10 mg/L {beta}-ionone, but significantly increased at 15, 22.5 and 33.75 mg/L. There was no significant variation on transcript expression of psbA and psbO at a concentration of 6.67 mg/L {beta}-ionone, but they were down-regulated at 22.5 mg/L. Ultrastructural examination by transmission electron microscopy indicated that the thylakoids were distorted, and the thylakoid membrane stacks began to collapse when M. aeruginosa NIES-843 was exposed to {beta}-ionone at a concentration of 22.5 and 33.75 mg/L. Our results indicate that the reaction centre of PS II and the electron transport at the acceptor side of PS II are the targets responsible for the toxicity of {beta}-ionone on the PS II of M. aeruginosa NIES-843.

  3. Influence of environment induced correlated fluctuations in electronic coupling on coherent excitation energy transfer dynamics in model photosynthetic systems.

    Science.gov (United States)

    Huo, Pengfei; Coker, David F

    2012-03-21

    Two-dimensional photon-echo experiments indicate that excitation energy transfer between chromophores near the reaction center of the photosynthetic purple bacterium Rhodobacter sphaeroides occurs coherently with decoherence times of hundreds of femtoseconds, comparable to the energy transfer time scale in these systems. The original explanation of this observation suggested that correlated fluctuations in chromophore excitation energies, driven by large scale protein motions could result in long lived coherent energy transfer dynamics. However, no significant site energy correlation has been found in recent molecular dynamics simulations of several model light harvesting systems. Instead, there is evidence of correlated fluctuations in site energy-electronic coupling and electronic coupling-electronic coupling. The roles of these different types of correlations in excitation energy transfer dynamics are not yet thoroughly understood, though the effects of site energy correlations have been well studied. In this paper, we introduce several general models that can realistically describe the effects of various types of correlated fluctuations in chromophore properties and systematically study the behavior of these models using general methods for treating dissipative quantum dynamics in complex multi-chromophore systems. The effects of correlation between site energy and inter-site electronic couplings are explored in a two state model of excitation energy transfer between the accessory bacteriochlorophyll and bacteriopheophytin in a reaction center system and we find that these types of correlated fluctuations can enhance or suppress coherence and transfer rate simultaneously. In contrast, models for correlated fluctuations in chromophore excitation energies show enhanced coherent dynamics but necessarily show decrease in excitation energy transfer rate accompanying such coherence enhancement. Finally, for a three state model of the Fenna-Matthews-Olsen light

  4. 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

  5. Evolutionary Competition Between Primitive Photosynthetic Systems: Existence of an early purple Earth?

    Science.gov (United States)

    Sparks, William B.; DasSarma, S.; Reid, I. N.

    2006-12-01

    The onset of photosynthesis in primitive cyanobacteria is thought to have profoundly altered the Earth’s atmosphere by producing an oxygen-rich atmosphere some 2 billion years ago. However, the pigments used by chlorophyll-based photosynthesis absorb at a variety of wavelengths, curiously except those centered around the peak of the Solar spectrum, 550nm. By contrast, simpler retinal-based light harvesting systems such as the haloarchaeal purple membrane bacteriorhodopsin and halorhodopsin show a strong well-defined peak of absorbance centered at 550nm. The spectroscopic complementarity for retinal pigments with chlorophyll-based pigments suggests an intriguing possibility of their co-evolution. This hypothesis argues that simpler retinal-based phototrophic capability may have evolved earlier, in microorganisms that dominated during the anaerobic and purple phase of the planet. Later, the more complex chlorophyll-based photosystem pigments could have evolved to harvest light in regions of the spectrum not absorbed by preexisting species. This would have led to the greening and oxidation of our planet and displacement of most of the retinal-based microorganisms. Not surprisingly, evidence for retinal chromoproteins have recently turned up in a variety of planktonic microorganisms. Although speculative, such a scenario would indicate that retinal-based phototrophy may be one of the oldest metabolic capabilities on Earth. Moreover, if the chlorophyll absorption spectrum is simply a product of adaptation, then its utility as a potential biomarker is likely to be limited.

  6. Design of a hydraulic analog of the circulatory system for evaluating artificial hearts.

    Science.gov (United States)

    Donovan, F M

    1975-01-01

    A major problem in improving artificial heart designs is the absence of methods for accurate in vitro testing of artificial heart systems. A mock circulatory system has been constructed which hydraulically simulates the systemic and pulmonary circulations of the normal human. The device is constructed of 1/2 in. acrylic sheet and has overall dimensions of 24 in. wide, 16 in. tall, and 8 in. deep. The artificial heart to be tested is attached to the front of the device, and pumps fluid from the systemic venous chamber into the pulmonary arterial chamber and from the pulmonary venous chamber into the systemic arterial chamber. Each of the four chambers is hermetically sealed. The compliance of each chamber is determined by the volume of air trapped above the fluid in that chamber. The pulmonary and systemic resistances are set automatically by bellows-operated valves to simulate the barroreceptor response in the systemic arteries and the passive pulmonary resistance response in the pulmonary arteries. Cardiac output is measured by a turbine flowmeter in the systemic circulation. Results using the Kwan-Gett artificial heart show a good comparison between the mock circulatory system response and the calf response.

  7. Collision avoidance planning in multi-robot system based on improved artificial potential field and rules

    Institute of Scientific and Technical Information of China (English)

    YUAN Xin; ZHU Qi-dan; YAN Yong-jie

    2009-01-01

    For real-time and distributed features of multi-robot system, the strategy of combining the improved artificial potential field method and the mles based on priority is proposed to study the collision avoidance planning in multi-robot systems. The improved artificial potential field based on simulated annealing algorithm satisfactorily overcomes the drawbacks of traditional artificial potential field method, so that robots can find a local collision-free path in the complex environment. According to the movement vector trail of robots, collisions between robots can be detected, thereby the collision avoidance rules can be obtained. Coordination between robots by the priority based rules improves the real-time property of multi-robot system. The combination of these two methods can help a robot to find a collision-free path from a starting point to the goal quickly in an environment with many obstacles. The feasibility of the proposed method is validated in the VC-basod simulated environment.

  8. Platforms for artificial neural networks : neurosimulators and performance prediction of MIMD-parallel systems

    NARCIS (Netherlands)

    Vuurpijl, L.G.

    1998-01-01

    In this thesis, two platforms for simulating artificial neural networks are discussed: MIMD-parallel processor systems as an execution platform and neurosimulators as a research and development platform. Because of the parallelism encountered in neural networks, distributed processor systems seem to

  9. Platforms for artificial neural networks : neurosimulators and performance prediction of MIMD-parallel systems

    NARCIS (Netherlands)

    Vuurpijl, L.G.

    1998-01-01

    In this thesis, two platforms for simulating artificial neural networks are discussed: MIMD-parallel processor systems as an execution platform and neurosimulators as a research and development platform. Because of the parallelism encountered in neural networks, distributed processor systems seem to

  10. Developing a scalable artificial photosynthesis technology through nanomaterials by design

    Science.gov (United States)

    Lewis, Nathan S.

    2016-12-01

    An artificial photosynthetic system that directly produces fuels from sunlight could provide an approach to scalable energy storage and a technology for the carbon-neutral production of high-energy-density transportation fuels. A variety of designs are currently being explored to create a viable artificial photosynthetic system, and the most technologically advanced systems are based on semiconducting photoelectrodes. Here, I discuss the development of an approach that is based on an architecture, first conceived around a decade ago, that combines arrays of semiconducting microwires with flexible polymeric membranes. I highlight the key steps that have been taken towards delivering a fully functional solar fuels generator, which have exploited advances in nanotechnology at all hierarchical levels of device construction, and include the discovery of earth-abundant electrocatalysts for fuel formation and materials for the stabilization of light absorbers. Finally, I consider the remaining scientific and engineering challenges facing the fulfilment of an artificial photosynthetic system that is simultaneously safe, robust, efficient and scalable.

  11. Developing a scalable artificial photosynthesis technology through nanomaterials by design.

    Science.gov (United States)

    Lewis, Nathan S

    2016-12-06

    An artificial photosynthetic system that directly produces fuels from sunlight could provide an approach to scalable energy storage and a technology for the carbon-neutral production of high-energy-density transportation fuels. A variety of designs are currently being explored to create a viable artificial photosynthetic system, and the most technologically advanced systems are based on semiconducting photoelectrodes. Here, I discuss the development of an approach that is based on an architecture, first conceived around a decade ago, that combines arrays of semiconducting microwires with flexible polymeric membranes. I highlight the key steps that have been taken towards delivering a fully functional solar fuels generator, which have exploited advances in nanotechnology at all hierarchical levels of device construction, and include the discovery of earth-abundant electrocatalysts for fuel formation and materials for the stabilization of light absorbers. Finally, I consider the remaining scientific and engineering challenges facing the fulfilment of an artificial photosynthetic system that is simultaneously safe, robust, efficient and scalable.

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

    Science.gov (United States)

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

    1987-01-01

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

  13. Magnetostatic bias in Kagome artificial spin ice systems

    Energy Technology Data Exchange (ETDEWEB)

    Panagiotopoulos, I., E-mail: ipanagio@cc.uoi.gr

    2016-04-01

    The magnetostatic bias in elongated nanomagnetic elements arranged in artificial Kagome spin ice arrays is studied by micromagnetic simulations. Using the Nmag package the reversal of a given element has been simulated under the influence of its four nearest neighbors with their magnetic states fixed in all possible configurations, which amount to 2{sup 4}=16 states that can be classified under five distinct cases. The hysteresis loop of each element is greatly influenced by the magnetic state of the nearest neighbors, not only by the expected shift due to dipolar interaction bias, but as it regards the loop shape and width itself. This presents a correction to the usual macrospin calculation based on the assumption that the loop is shifted by a biasing field (equal to the local dipole field) but the loop width (and shape in general) does not change. Although coercive and biasing fields depend strongly on the dimensions their relative strength has only weak thickness dependence for a fixed length to width aspect ratio. Therefore the behavior of such arrays is expected to be to a large degree size invariant apart from an appropriate maximum external applied field scaling.

  14. 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.

  15. Assembly of Photosynthetic Antenna Protein Complexes from Algae for Development of Nano-biodevice and Its Fuelization

    Science.gov (United States)

    2013-05-20

    Task 1 : Artificial domain assembly of LH pigment complexes from photosynthetic bacterial membranes on nano-patterning and lipid modified...public release; distribution unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT The purpose of this proposal is to use photosynthetic antenna pigment ...nanobiophotonics) and its fuelization. The advantage of these pigment complexes from algae as well as from plants and photosynthetic bacteria is its

  16. 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.

  17. A multiuser detector based on artificial bee colony algorithm for DS-UWB systems.

    Science.gov (United States)

    Yin, Zhendong; Liu, Xiaohui; Wu, Zhilu

    2013-01-01

    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.

  18. 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.

  19. A Hybrid Course Recommendation System by Integrating Collaborative Filtering and Artificial Immune Systems

    Directory of Open Access Journals (Sweden)

    Pei-Chann Chang

    2016-07-01

    Full Text Available This research proposes a two-stage user-based collaborative filtering process using an artificial immune system for the prediction of student grades, along with a filter for professor ratings in the course recommendation for college students. We test for cosine similarity and Karl Pearson (KP correlation in affinity calculations for clustering and prediction. This research uses student information and professor information datasets of Yuan Ze University from the years 2005–2009 for the purpose of testing and training. The mean average error and confusion matrix analysis form the testing parameters. A minimum professor rating was tested to check the results, and observed that the recommendation systems herein provide highly accurate results for students with higher mean grades.

  20. A New Method Based on Multi Agent System and Artificial Immune System for Systematic Maintenance

    Directory of Open Access Journals (Sweden)

    Adel Abdelhadi

    2014-05-01

    Full Text Available This study propose a novel method for the integration of systematic preventive maintenance policies in hybrid flow shop scheduling. The proposed approach is inspired by the behavior of the human body. We have implemented a problem-solving approach for optimizing the processing time, methods based on Métaheuristiques. This hybridization is between a Multi agent system and inspirations of the human body, especially artificial immune system. The effectiveness of our approach has been demonstrated repeatedly in this study. The proposed approach is applied to three preventive maintenance policies. These policies are intended to maximize the availability or to maintain a minimum level of reliability during the production chain. The results show that our algorithm outperforms existing algorithms. We assumed that the machines might be unavailable periodically during the production scheduling.

  1. 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.

  2. Artificial Intelligence for Explosive Ordnance Disposal System (AI-EOD)

    Energy Technology Data Exchange (ETDEWEB)

    Madrid, R.; Williams, B.; Holland, J.

    1992-03-01

    Based on a dynamically configurable neural net that learns in a single pass of the training data, this paper describes a system used by the military in the identification of explosive ordnance. Allowing the technician to input incomplete, contradictory, and wrong information, this system combines expert systems and neural nets to provide a state-of-the-art search, retrieval, and image and text management system.

  3. 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.

  4. Learning Efficiency of Consciousness System for Robot Using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Osama Shoubaky

    2014-12-01

    Full Text Available This paper presents learning efficiency of a consciousness system for robot using artificial neural network. The proposed conscious system consists of reason system, feeling system and association system. The three systems are modeled using Module of Nerves for Advanced Dynamics (ModNAD. Artificial neural network of the type of supervised learning with the back propagation is used to train the ModNAD. The reason system imitates behaviour and represents self-condition and other-condition. The feeling system represents sensation and emotion. The association system represents behaviour of self and determines whether self is comfortable or not. A robot is asked to perform cognition and tasks using the consciousness system. Learning converges to about 0.01 within about 900 orders for imitation, pain, solitude and the association modules. It converges to about 0.01 within about 400 orders for the comfort and discomfort modules. It can be concluded that learning in the ModNAD completed after a relatively small number of times because the learning efficiency of the ModNAD artificial neural network is good. The results also show that each ModNAD has a function to imitate and cognize emotion. The consciousness system presented in this paper may be considered as a fundamental step for developing a robot having consciousness and feelings similar to humans.

  5. Multi-agent systems and decentralized artificial superintelligence

    OpenAIRE

    Ponomarev, S.; Voronkov, A. E.

    2017-01-01

    Multi-agents systems communication is a technology, which provides a way for multiple interacting intelligent agents to communicate with each other and with environment. Multiple-agent systems are used to solve problems that are difficult for solving by individual agent. Multiple-agent communication technologies can be used for management and organization of computing fog and act as a global, distributed operating system. In present publication we suggest technology, which combines decentrali...

  6. Modeling of human colonic blood flow for a novel artificial anal sphincter system

    Institute of Scientific and Technical Information of China (English)

    Peng ZAN; Guo-zheng YAN; Hua LIU

    2008-01-01

    A novel artificial anal sphincter system has been developed to simulate the normal physiology of the human anorectum. With the goal of engineering a safe and reliable device, the model of human colonic blood flow has been built and the relationship between the colonic blood flow rate and the operating occlusion pressure of the anorectum is achieved. The tissue ischemia is analyzed based on constitutive relations for human anorectum. The results suggest that at the planned operating occlusion pressure of less than 4 kPa the artificial anal sphincter should not risk the vaseularity of the human colon.

  7. 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.

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

    Directory of Open Access Journals (Sweden)

    Schramm H.

    2013-03-01

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

  10. 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...

  11. 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

    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...

  12. 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...

  13. 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.

  14. 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.

  15. Automatic control systems of daylighting and artificial lighting; Saiko shomei setsubi no seigyo system

    Energy Technology Data Exchange (ETDEWEB)

    Saito, M. [Obayashi Corp., Tokyo (Japan)

    1997-06-05

    Means for controlling illumination include a blind for adjusting the light coming directly from the sun, system for maintaining environmental comfort by controlling light-modulating glass and the like, labor-saving system incorporating a control center governing multiple buildings in the vicinity, and system intended for improved energy efficiency. Energy saving efforts include an occupancy sensor control for the automatic turn-on/off of lighting by detecting the presence or absence of people in a chamber, optimum lighting control using sensors for adjusting illumination to the designed level, time-scheduled control for the turning-on/off of lighting according to the time of the day, daylight utilizing control for adjusting artificial lighting according to the amount of incident daylight, guidance light control system for turning on guidance lights upon sensing a decrease in incident daylight. Other than these, there are controls of lighting for performance and demonstration. Examples of practical application include the system adopted by Museum of Contemporary Art, Tokyo, for keeping incident light homogeneous, and the optimum illumination control and daylight utilizing control of Research & Development Center, The Tokyo Electric Power Co., Ltd. 8 refs., 10 figs.

  16. Artificial Immune System for Flight Envelope Estimation and Protection

    Science.gov (United States)

    2014-12-31

    Figure 1.7. AIS-Based ACM Process 31 Figure 1.8. AIS-Based ACM System Design 32 Figure 1.9. On-Line AC Detection... ACM ) based on the AIS paradigm can be considered to include three main components functionally connected in a closed loop as shown in Figure 1.7...off-line ACM system design and implementation  on-line AC detection, identification, evaluation, and accommodation  post-processing of flight data

  17. 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.

  18. Implementation of hybrid short-term load forecasting system using artificial neural networks and fuzzy expert systems

    Energy Technology Data Exchange (ETDEWEB)

    Kim, K.H. [Kangwon National Univ. (Korea, Republic of). Dept. of Electrical Engineering; Park, J.K. [Seoul National Univ. (Korea, Republic of). Dept. of Electrical Engineering; Hwang, K.J. [Univ. of Ulsan (Korea, Republic of). Dept. of Electrical Engineering; Kim, S.H. [Korea Electric Power Co., Seoul (Korea, Republic of). Power System Control Dept.

    1995-08-01

    In this paper, a hybrid model for short-term load forecast that integrates artificial neural networks and fuzzy expert systems is presented. The forecasted load is obtained by passing through two steps. In the first procedure, the artificial neural networks are trained with the load patterns corresponding to the forecasting hour, and the provisional forecasted load is obtained by the trained artificial neural networks. In the second procedure, the fuzzy expert systems modify the provisional forecasted load considering the possibility of load variation due to changes in temperature and the load behavior of holiday. In the test case of 1994 for implementation in short term load forecasting expert system of Korea Electric Power Corporation (KEPCO), the proposed hybrid model provided good forecasting accuracy of the mean absolute percentage errors below 1.3%. The comparison results with exponential smoothing method showed the efficiency and accuracy of the hybrid model.

  19. 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.

  20. On Three Challenges of Artificial Living Systems and Embodied Evolution

    CERN Document Server

    Kernbach, Serge

    2011-01-01

    Creating autonomous, self-supporting, self-replicating, sustainable systems is a great challenge. To some extent, understanding life means not only being able to create it from scratch, but also improving, supporting, saving it, or even making it even more advanced. This can be thought of as a long-term goal of living technologies and embodied evolution. Current research agenda targets several short- and middle-term steps towards achieving such a vision: connection of ICT and bio-/chemo- developments, advances in "soft" and "wet" robotics, integration of material science into developmental robotics, and potentially, addressing the self-replication in autonomous systems.

  1. 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

  2. Guidance for human interface with artificial intelligence systems

    Science.gov (United States)

    Potter, Scott S.; Woods, David D.

    1991-01-01

    The beginning of a research effort to collect and integrate existing research findings about how to combine computer power and people is discussed, including problems and pitfalls as well as desirable features. The goal of the research is to develop guidance for the design of human interfaces with intelligent systems. Fault management tasks in NASA domains are the focus of the investigation. Research is being conducted to support the development of guidance for designers that will enable them to make human interface considerations into account during the creation of intelligent systems.

  3. Optimization with artificial neural network systems - A mapping principle and a comparison to gradient based methods

    Science.gov (United States)

    Leong, Harrison Monfook

    1988-01-01

    General formulae for mapping optimization problems into systems of ordinary differential equations associated with artificial neural networks are presented. A comparison is made to optimization using gradient-search methods. The performance measure is the settling time from an initial state to a target state. A simple analytical example illustrates a situation where dynamical systems representing artificial neural network methods would settle faster than those representing gradient-search. Settling time was investigated for a more complicated optimization problem using computer simulations. The problem was a simplified version of a problem in medical imaging: determining loci of cerebral activity from electromagnetic measurements at the scalp. The simulations showed that gradient based systems typically settled 50 to 100 times faster than systems based on current neural network optimization methods.

  4. 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.

  5. Development of a Through Tubing (Microhole) Artificial Lift System

    Energy Technology Data Exchange (ETDEWEB)

    Steve Bodden

    2006-09-30

    The goal of this project was to develop a small diameter pump system capable of being deployed through existing production tubing strings in oil/gas wells. The pump system would then pump water up an inner tubing string (likely coil tubing) and allow gas to flow in the annulus between the coil tubing and production tubing. Accomplishing this would allow wells that are currently loaded up (unable to flow at high enough rates to lift the fluid out of the wellbore) to continue to produce additional gas/oil reserves. The project was unable to complete a working test system due to unforeseen complexities in coupling the system components together in part due to the small diameter. Although several of the individual components were sourced and secured, coupling them together and getting electricity to the motor proved technically more difficult than expected. Thus, the project is no longer active due primarily to the complications realized in coupling the components and the difficulties in getting electricity to the submersible motor in a slimhole system. The other problem in finishing this project was the lack of financial resources. When the grant was first applied for it was expected that it would be awarded in early 2004. Since the grant was not actually awarded until the end of August 2004, GPS had basically run out of $$$ and the principle developer (Steve Bodden) had to find a full time job which began in late July 2004. When the grant was finally awarded in late August, it was still hoped that the project could proceed as a part time development but with less financial exposure to the partners in GPS. This became very problematic as it still had many technical obstacles to overcome to get it to the stage of prototype testing.

  6. 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.

  7. Multi-objective Scheduling Using an Artificial Immune System

    Institute of Scientific and Technical Information of China (English)

    杨建国; 李蓓智

    2003-01-01

    Production scheduling is one of the most important problems to be considered in the effective performance of the automatic manufacturing system.It is the typical kind of NP-complete problem. The methods commonly used are not suitable to solve complicated problems because the calculating time rises exponentially with the increase of the problem size. In this paper, a new algorithm - immune based scheduling algorithm (IBSA) is proposed. After the description of the mathematics model and the calculating procedure of immune based scheduling,some examples are tested in the software system called HM IM& C that is developed usingVC+ +6.0. The testing results show that IBSA has high efficiency to solve scheduling problem.

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

    OpenAIRE

    Kathryn Elizabeth Merrick; Kamran eShafi

    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 motivati...

  9. Artificial Immune Systems Metaphor for Agent Based Modeling of Crisis Response Operations

    OpenAIRE

    Khalil, Khaled M.; Abdel-Aziz, M.; Nazmy, Taymour T.; Salem, Abdel-Badeeh M.

    2010-01-01

    Crisis response requires information intensive efforts utilized for reducing uncertainty, calculating and comparing costs and benefits, and managing resources in a fashion beyond those regularly available to handle routine problems. This paper presents an Artificial Immune Systems (AIS) metaphor for agent based modeling of crisis response operations. The presented model proposes integration of hybrid set of aspects (multi-agent systems, built-in defensive model of AIS, situation management, a...

  10. 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

  11. Event detection challenges, methods, and applications in natural and artificial systems

    OpenAIRE

    Kerman, Mitchell C.; Jiang, Wei; Blumberg, Alan F.; Buttrey, Samuel E.

    2009-01-01

    A system is a combination of elements whose collaborative actions produce results generally not attainable by the elements acting alone, and an event is a significant occurrence or large-scale activity that is unusual relative to normal patterns of behavior. Event detection, or the process of identifying the occurrence of an event, within both natural and artificial (or man-made) systems has long been a topic of research, and a variety of techniques have been developed to address event detec...

  12. Repeated action of a constant magnetic field on the blood coagulation system in artificially produced anemia

    Science.gov (United States)

    Zabrodina, L. V.

    1974-01-01

    Changes are discussed in the coagulatory system of the blood in rabbits under the influence of a constant magnetic field of an intensity of 2500 oersteds against the background of artificially induced anemia. Reversibility of the changes produced and the presence of the adaptational effect are noted. Taking all this into consideration, the changes involving the coagulatory system of the blood which arise under the influence of a constant magnetic field may be considered to have a nerve-reflex nature.

  13. 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.

  14. On Three Challenges of Artificial Living Systems and Embodied Evolution

    OpenAIRE

    Kernbach, Serge

    2011-01-01

    Creating autonomous, self-supporting, self-replicating, sustainable systems is a great challenge. To some extent, understanding life means not only being able to create it from scratch, but also improving, supporting, saving it, or even making it even more advanced. This can be thought of as a long-term goal of living technologies and embodied evolution. Current research agenda targets several short- and middle-term steps towards achieving such a vision: connection of ICT and bio-/chemo- deve...

  15. HYBRID HEURISTIC-BASED ARTIFICIAL IMMUNE SYSTEM FOR TASK SCHEDULING

    OpenAIRE

    2011-01-01

    Task scheduling problem in heterogeneous systems is the process of allocating tasks of an application to heterogeneous processors interconnected by high-speed networks, so that minimizing the finishing time of application as much as possible. Tasks are processing units of application and have precedenceconstrained, communication and also, are presented by Directed Acyclic Graphs (DAGs). Evolutionary algorithms are well suited for solving task scheduling problem in heterogeneous environment. I...

  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. Hybrid Systems for Knowledge Representation in Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Rajeswari P.V N

    2012-11-01

    Full Text Available There are few knowledge representation (KR techniques available for efficiently representing knowledge. However, with the increase in complexity, better methods are needed. Some researchers came up with hybrid mechanisms by combining two or more methods. In an effort to construct an intelligent computer system, a primary consideration is to represent large amounts of knowledge in a way that allows effective use and efficiently organizing information to facilitate making the recommended inferences. There are merits and demerits of combinations, and standardized method of KR is needed. In this paper, various hybrid schemes of KR were explored at length and details presented.

  18. Artificial intelligence methods in diagnostics of analog systems

    Directory of Open Access Journals (Sweden)

    Bilski Piotr

    2014-06-01

    Full Text Available The paper presents the state of the art and advancement of artificial intelligence methods in analog systems diagnostics. Firstly, the diagnostic domain is introduced and its problems explained. Then, computational intelligence approaches usable for fault detection and identification are reviewed. Particular groups of methods are presented in detail, explaining their usefulness and drawbacks. Examples, such as the induction motor or the electronic filter, are provided to show the applicability of the presented approaches for monitoring the state of analog objects from engineering domains. The discussion section reviews the presented approaches, their future prospects and problems to be solved.

  19. 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.

  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. Risk assessment of sewer condition using artificial intelligence tools: application to the SANEST sewer system.

    Science.gov (United States)

    Sousa, V; Matos, J P; Almeida, N; Saldanha Matos, J

    2014-01-01

    Operation, maintenance and rehabilitation comprise the main concerns of wastewater infrastructure asset management. Given the nature of the service provided by a wastewater system and the characteristics of the supporting infrastructure, technical issues are relevant to support asset management decisions. In particular, in densely urbanized areas served by large, complex and aging sewer networks, the sustainability of the infrastructures largely depends on the implementation of an efficient asset management system. The efficiency of such a system may be enhanced with technical decision support tools. This paper describes the role of artificial intelligence tools such as artificial neural networks and support vector machines for assisting the planning of operation and maintenance activities of wastewater infrastructures. A case study of the application of this type of tool to the wastewater infrastructures of Sistema de Saneamento da Costa do Estoril is presented.

  2. 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.

  3. An innovative artificial recharge system to enhance groundwater storage in basaltic terrain: example from Maharashtra, India

    Science.gov (United States)

    Bhusari, Vijay; Katpatal, Y. B.; Kundal, Pradeep

    2016-08-01

    The management of groundwater poses challenges in basaltic terrain as its availability is not uniform due to the absence of primary porosity. Indiscriminate excessive withdrawal from shallow as well as deep aquifers for meeting increased demand can be higher than natural recharge, causing imbalance in demand and supply and leading to a scarcity condition. An innovative artificial recharge system has been conceived and implemented to augment the groundwater sources at the villages of Saoli and Sastabad in Wardha district of Maharashtra, India. The scheme involves resectioning of a stream bed to achieve a reverse gradient, building a subsurface dam to arrest subsurface flow, and installation of recharge shafts to recharge the deeper aquifers. The paper focuses on analysis of hydrogeological parameters like porosity, specific yield and transmissivity, and on temporal groundwater status. Results indicate that after the construction of the artificial recharge system, a rise of 0.8-2.8 m was recorded in the pre- and post-monsoon groundwater levels in 12 dug wells in the study area; an increase in the yield was also noticed which solved the drinking water and irrigation problems. Spatial analysis was performed using a geographic information system to demarcate the area of influence of the recharge system due to increase in yields of the wells. The study demonstrates efficacy, technical viability and applicability of an innovative artificial recharge system constructed in an area of basaltic terrain prone to water scarcity.

  4. Artificial duplicate reads in sequencing data of 454 Genome Sequencer FLX System

    Institute of Scientific and Technical Information of China (English)

    Hui Dong; Yangyi Chen; Yan Shen; Shengyue Wang; Guoping Zhao; Weirong Jin

    2011-01-01

    The 454 Genome Sequencer (GS) FLX System is one of the next-generation sequencing systems featured by long reads, high accuracy, and ultra-high throughput.Based on the mechanism of emulsion PCR, a unique DNA template would only generate a unique sequence read after being amplified and sequenced on GS FLX.However,biased amplification of DNA templates might occur in the process of emulsion PCR, which results in production of artificial duplicate reads.Under the condition that each DNA template is unique to another, 3.49%-18.14% of total reads in GS FLX-sequencing data were found to be artificial duplicate reads.These duplicate reads may lead to misunderstanding of sequencing data and special attention should be paid to the potential biases they introduced to the data.

  5. 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.

  6. Evolution of immune systems from self/not self to danger to artificial immune systems (AIS)

    Science.gov (United States)

    Cooper, Edwin L.

    2010-03-01

    self/not self model. The review will end with certain perspectives on artificial immune systems new on the scene and the product of computational immunologists. The tentative view is to question if the immune systems of invertebrates might be amenable to such an analysis? This would offer more credence to the innate system, often pushed aside thus favoring the adaptive responses.

  7. Evaluation of a novel artificial pancreas: closed loop glycemic control system with continuous blood glucose monitoring.

    Science.gov (United States)

    Tsukamoto, Yuuki; Kinoshita, Yoshihiko; Kitagawa, Hiroyuki; Munekage, Masaya; Munekage, Eri; Takezaki, Yuka; Yatabe, Tomoaki; Yamashita, Koichi; Yamazaki, Rie; Okabayashi, Takehiro; Tarumi, Masatoshi; Kobayashi, Masaki; Mishina, Suguru; Hanazaki, Kazuhiro

    2013-04-01

    A closed-loop glycemic control system using an artificial pancreas has been applied with many clinical benefits in Japan since 1987. To update this system incorporating user-friendly features, we developed a novel artificial pancreas (STG-55). The purpose of this study was to evaluate STG-55 for device usability, performance of blood glucose measurement, glycemic control characteristics in vivo in animal experiments, and evaluate its clinical feasibility. There are several features for usability improvement based on the design concepts, such as compactness, display monitor, batteries, guidance function, and reduction of the preparation time. All animal study data were compared with a clinically available artificial pancreas system in Japan (control device: STG-22). We examined correlations of both blood glucose levels between two groups (STG-55 vs. control) using Clarke's error grid analysis, and also compared mean glucose infusion rate (GIR) during glucose clamp. The results showed strong correlation in blood glucose concentrations (Pearson's product-moment correlation coefficient: 0.97; n = 1636). Clarke's error grid analysis showed that 98.4% of the data fell in Zones A and B, which represent clinically accurate or benign errors, respectively. The difference in mean GIRs was less than 0.2 mg/kg/min, which was considered not significant. Clinical feasibility study demonstrated sufficient glycemic control maintaining target glucose range between 80 and 110 (mg/dL), and between 140 and 160 without any hypoglycemia. In conclusion, STG-55 was a clinically acceptable artificial pancreas with improved interface and usability. A closed-loop glycemic control system with STG-55 would be a useful tool for surgical and critical patients in intensive care units, as well as diabetic patients.

  8. Single Robot Localisation Approach for Indoor Robotic Systems through Integration of Odometry and Artificial Landmarks

    OpenAIRE

    Ņikitenko, A; Liekna, A; Ekmanis, M.; Kuļikovskis, G; Andersone, I

    2013-01-01

    we present an integrated approach for robot localization that allows to integrate for the artificial landmark localization data with odometric sensors and signal transfer function data to provide means for different practical application scenarios. The sensor data fusion deals with asynchronous sensor data using inverse Laplace transform. We demonstrate a simulation software system that ensures smooth integration of the odometry-based and signal transfer – based localization into one approach.

  9. Exploring User Experience and Affect to Enhance Creative Artificial Intelligence Systems

    OpenAIRE

    Salevati, Sara

    2015-01-01

    In recent years, Creative Artificial Intelligence Systems (CAIS) have transformed the nature of creative practices. This transformation has created a need for research on the importance of the human collaborator, the user experience (UX) and practical applications of CAIS.This dissertation addresses the need for research in this respect through three interrelated studies, that focus on supporting the collaboration between users and CAIS in the generation of creative artefacts. The first study...

  10. New Artificial Immune System Approach Based on Monoclonal Principle for Job Recommendation

    OpenAIRE

    Shaha Al-Otaibi; Mourad Ykhlef

    2016-01-01

    Finding the best solution for an optimization problem is a tedious task, specifically in the presence of enormously represented features. When we handle a problem such as job recommendations that have a diversity of their features, we should rely to metaheuristics. For example, the Artificial Immune System which is a novel computational intelligence paradigm achieving diversification and exploration of the search space as well as exploitation of the good solutions were reached in reasonable t...

  11. Investigating Artificial Immune Systems For Job Shop Rescheduling In Changing Environments

    CERN Document Server

    Uwe, Aickelin; Aniza, Din

    2008-01-01

    Artificial immune system can be used to generate schedules in changing environments and it has been proven to be more robust than schedules developed using a genetic algorithm. Good schedules can be produced especially when the number of the antigens is increased. However, an increase in the range of the antigens had somehow affected the fitness of the immune system. In this research, we are trying to improve the result of the system by rescheduling the same problem using the same method while at the same time maintaining the robustness of the schedules.

  12. Towards autotrophic tissue engineering: Photosynthetic gene therapy for regeneration.

    Science.gov (United States)

    Chávez, Myra Noemi; Schenck, Thilo Ludwig; Hopfner, Ursula; Centeno-Cerdas, Carolina; Somlai-Schweiger, Ian; Schwarz, Christian; Machens, Hans-Günther; Heikenwalder, Mathias; Bono, María Rosa; Allende, Miguel L; Nickelsen, Jörg; Egaña, José Tomás

    2016-01-01

    The use of artificial tissues in regenerative medicine is limited due to hypoxia. As a strategy to overcome this drawback, we have shown that photosynthetic biomaterials can produce and provide oxygen independently of blood perfusion by generating chimeric animal-plant tissues during dermal regeneration. In this work, we demonstrate the safety and efficacy of photosynthetic biomaterials in vivo after engraftment in a fully immunocompetent mouse skin defect model. Further, we show that it is also possible to genetically engineer such photosynthetic scaffolds to deliver other key molecules in addition to oxygen. As a proof-of-concept, biomaterials were loaded with gene modified microalgae expressing the angiogenic recombinant protein VEGF. Survival of the algae, growth factor delivery and regenerative potential were evaluated in vitro and in vivo. This work proposes the use of photosynthetic gene therapy in regenerative medicine and provides scientific evidence for the use of engineered microalgae as an alternative to deliver recombinant molecules for gene therapy.

  13. 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.

  14. Assessment of Passive Intestinal Permeability Using an Artificial Membrane Insert System.

    Science.gov (United States)

    Berben, Philippe; Brouwers, Joachim; Augustijns, Patrick

    2017-08-18

    Despite reasonable predictive power of current cell-based and cell-free absorption models for the assessment of intestinal drug permeability, high costs and/or lengthy preparation steps hamper their use. The use of a simple artificial membrane (without any lipids present) as intestinal barrier substitute would overcome these hurdles. In the present study, a set of 14 poorly water-soluble drugs, dissolved in two different media [fasted state simulated/human intestinal fluids (FaSSIF/FaHIF)], were applied to the donor compartment of an artificial membrane insert system (AMI-system) containing a regenerated cellulose membrane. Furthermore, to investigate the predictive capacity of the AMI-system as substitute for the well-established Caco-2 system to assess intestinal permeability, the same set of 14 drugs dissolved in FaHIF, were applied to the donor compartment of a Caco-2 system. For 14 drugs, covering a broad range of physicochemical parameters, a reasonable correlation between both absorption systems was observed, characterized by a Pearson correlation coefficient r of 0.95 (FaHIF). Using the AMI-system, an excellent predictive capacity of FaSSIF as surrogate medium for FaHIF was demonstrated (r = 0.96). Based on the acquired data, the AMI-system appears to be a time- and cost-effective tool for the early-stage estimation of passive intestinal permeability for poorly water-soluble drugs. Copyright © 2017. Published by Elsevier Inc.

  15. 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.

  16. Periodic Pattern of Genetic and Fitness Diversity during Evolution of an Artificial Cell-Like System.

    Science.gov (United States)

    Ichihashi, Norikazu; Aita, Takuyo; Motooka, Daisuke; Nakamura, Shota; Yomo, Tetsuya

    2015-12-01

    Genetic and phenotypic diversity are the basis of evolution. Despite their importance, however, little is known about how they change over the course of evolution. In this study, we analyzed the dynamics of the adaptive evolution of a simple evolvable artificial cell-like system using single-molecule real-time sequencing technology that reads an entire single artificial genome. We found that the genomic RNA population increases in fitness intermittently, correlating with a periodic pattern of genetic and fitness diversity produced by repeated diversification and domination. In the diversification phase, a genomic RNA population spreads within a genetic space by accumulating mutations until mutants with higher fitness are generated, resulting in an increase in fitness diversity. In the domination phase, the mutants with higher fitness dominate, decreasing both the fitness and genetic diversity. This study reveals the dynamic nature of genetic and fitness diversity during adaptive evolution and demonstrates the utility of a simplified artificial cell-like system to study evolution at an unprecedented resolution.

  17. Review Paper on Performance Evaluation of Nut and Bolt Recognition System Using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Shruti Paunikar

    2013-09-01

    Full Text Available There is constant research going on in the field of recognition by means of artificial intelligence to enhance the productivity. The automotive industry requires an automated system to sort different sizes and shapes nut and bolt which are the mainly used component in the industry, to improve the overall productivity. This review paper deals with some feature extraction techniques and its performance impact on the artificial neural network efficiency for the recognition of nut and bolt. The main feature extraction techniques analysed for this review paper are stationary wavelet transform, principle component analysis and radius analysis. The aforementioned techniques are already tested and simulation is done on MATLAB.The results obtained varies depending on pre-processing techniques used for the nut and bolt recognition.

  18. 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.

  19. Artificial immune system based neural networks for solving multi-objective programming problems

    Directory of Open Access Journals (Sweden)

    Waiel F. Abd El-Wahed

    2010-12-01

    Full Text Available In this paper, a hybrid artificial intelligent approach based on the clonal selection principle of artificial immune system (AIS and neural networks is proposed to solve multi-objective programming problems. Due to the sensitivity to the initial values of initial population of antibodies (Ab’s, neural networks is used to initialize the boundary of the antibodies for AIS to guarantee that all the initial population of Ab’s is feasible. The proposed approach uses dominance principle and feasibility to identify solutions that deserve to be cloned, and uses two types of mutation: uniform mutation is applied to the clones produced and non-uniform mutation is applied to the “not so good” antibodies. A secondary (or external population that stores the nondominated solutions found along the search process is used. Such secondary population constitutes the elitist mechanism of our approach and it allows it to move towards the Pareto front.

  20. 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

  1. Two-step image registration by artificial immune system and chamfer matching

    Institute of Scientific and Technical Information of China (English)

    Famao Ye; Shaoping Xu; Yuhong Xiong

    2008-01-01

    Image registration is the precondition and foundation in the fusion of multi-source image data. A two-step approach based on artificial immune system and chamfer matching to register images from different types of sensors is presented. In the first step, it extracts the large edges and takes chamfer distance between the input image and the reference image as similarity measure and uses artificial immune network algorithm to speed up the searching of the initial transformation parameters. In the second step, an area-based method is utilized to refine the initial transformation and enhance the registration accuracy. Experimental results show that the proposed approach is a promising method for registration of multi-sensor images.

  2. THE ARTIFICIAL BOUNDARY CONDITIONS FOR NUMERICAL SIMULATIONS OF THE COMPLEX AMPLITUDE IN A COUPLED BAY-RIVER SYSTEM

    Institute of Scientific and Technical Information of China (English)

    Hou-de Han; Xin Wen

    2004-01-01

    We consider the numerical approximations of the complex amplitude in a coupled bay-river system in this work. One half-circumference is introduced as the artificial boundary in the open sea, and one segment is introduced as the artificial boundary in the river if the river is semi-infinite. On the artificial boundary a sequence of high-order artificial boundary conditions are proposed. Then the original problem is solved in a finite computational domain, which is equivalent to a variational problem. The numerical approximations for the original problem are obtained by solving the variational problem with the finite element method. The numerical examples show that the artificial boundary conditions given in this work are very effective.

  3. Artificial quantum thermal bath: Engineering temperature for a many-body quantum system

    Science.gov (United States)

    Shabani, Alireza; Neven, Hartmut

    2016-11-01

    Temperature determines the relative probability of observing a physical system in an energy state when that system is energetically in equilibrium with its environment. In this paper we present a theory for engineering the temperature of a quantum system different from its ambient temperature. We define criteria for an engineered quantum bath that, when coupled to a quantum system with Hamiltonian H , drives the system to the equilibrium state e/-H/TTr (e-H /T) with a tunable parameter T . This is basically an analog counterpart of the digital quantum metropolis algorithm. For a system of superconducting qubits, we propose a circuit-QED approximate realization of such an engineered thermal bath consisting of driven lossy resonators. Our proposal opens the path to simulate thermodynamical properties of many-body quantum systems of size not accessible to classical simulations. Also we discuss how an artificial thermal bath can serve as a temperature knob for a hybrid quantum-thermal annealer.

  4. Artificial tritrophic exposure system for environmental risk analysis on aphidophagous predators

    Directory of Open Access Journals (Sweden)

    DÉBORA P. PAULA

    Full Text Available ABSTRACT We evaluated an artificial tritrophic exposure system for use in ecotoxicological evaluations of environmental stressors on aphidophagous predators. It consists of an acrylic tube with a Parafilm M sachet containing liquid aphid diet, into which can be added environmental stressors. Immature Cycloneda sanguinea, Harmonia axyridis and Chrysoperla externa, and adult H. axyridis were reared on Myzus persicae. Larval and pupal development and survival of all species and reproductive parameters of H. axyridis were similar to published results. The system provides a suitable tritrophic exposure route, enables ex-ante evaluation of stressors, and improves the accuracy of the assessment.

  5. Selectivity Control of CO2 Reduction in an Inorganic Artificial Photosynthesis System

    Science.gov (United States)

    Hashiba, Hiroshi; Yotsuhashi, Satoshi; Deguchi, Masahiro; Yamada, Yuka; Ohkawa, Kazuhiro

    2013-09-01

    We demonstrated that the selectivity of photo electrochemical CO2 reduction can be controlled in an inorganic artificial photosynthesis system using an AlGaN/GaN photo electrode. By increasing input light intensity and the use of a gold cathode, the Faradaic efficiency of CO dramatically increases from 30% to over 80% while that of H2 decreases. We observed that the cathode potential resulting from illumination determines the ratio of CO and H2. With this system, it is possible to switch the main reaction product from CO to HCOOH, which is also effective even under intense illumination.

  6. Artificial tritrophic exposure system for environmental risk analysis on aphidophagous predators.

    Science.gov (United States)

    Paula, Débora P; Souza, Lucas M DE; Andow, David A; Sousa, Alex A T Cortês DE; Pires, Carmen S S; Sujii, Edison R

    2016-09-01

    We evaluated an artificial tritrophic exposure system for use in ecotoxicological evaluations of environmental stressors on aphidophagous predators. It consists of an acrylic tube with a Parafilm M sachet containing liquid aphid diet, into which can be added environmental stressors. Immature Cycloneda sanguinea, Harmonia axyridis and Chrysoperla externa, and adult H. axyridis were reared on Myzus persicae. Larval and pupal development and survival of all species and reproductive parameters of H. axyridis were similar to published results. The system provides a suitable tritrophic exposure route, enables ex-ante evaluation of stressors, and improves the accuracy of the assessment.

  7. Artificial Immune Systems Metaphor for Agent Based Modeling of Crisis Response Operations

    CERN Document Server

    Khalil, Khaled M; Nazmy, Taymour T; Salem, Abdel-Badeeh M

    2010-01-01

    Crisis response requires information intensive efforts utilized for reducing uncertainty, calculating and comparing costs and benefits, and managing resources in a fashion beyond those regularly available to handle routine problems. This paper presents an Artificial Immune Systems (AIS) metaphor for agent based modeling of crisis response operations. The presented model proposes integration of hybrid set of aspects (multi-agent systems, built-in defensive model of AIS, situation management, and intensity-based learning) for crisis response operations. In addition, the proposed response model is applied on the spread of pandemic influenza in Egypt as a case study.

  8. 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...

  9. A Systems Engineering Survey of Artificial Intelligence and Smart Sensor Networks in a Network-Centric Environment

    Science.gov (United States)

    2009-09-01

    This is an academic paper published by The Artificial Life and Adaptive Robotics Laboratory ( ALAR ) that proposes “a novel network centric multi...Sarker, and M. Barlow, "Network centric multi-agent systems: A novel architecture," The Artificial Life and Adaptive Robotics Laboratory ( ALAR ...Technical Report Series, pp. 1–13, ALAR , Canberra, Australia, Pub. No. TR- ALAR -200504004, 2008. [46] D. M. Buede, The Engineering Design of Systems

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

    Energy Technology Data Exchange (ETDEWEB)

    Reifman, J.; Wei, T.Y.C.; Vitela, J.E. [Argonne National Lab., IL (United States); Applequist, C. A. [Commonwealth Research Corp., Chicago, IL (United States); Chasensky, T.M. [Commonwealth Edison Co., Chicago, IL (United States)

    1996-03-01

    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.

  11. Influences of quantum mechanically mixed electronic and vibrational pigment states in 2D electronic spectra of photosynthetic systems: Strong electronic coupling cases

    CERN Document Server

    Fujihashi, Yuta; Ishizaki, Akihito

    2015-01-01

    In 2D electronic spectroscopy studies, long-lived quantum beats have recently been observed in photosynthetic systems, and it has been suggested that the beats are produced by quantum mechanically mixed electronic and vibrational states. Concerning the electronic-vibrational quantum mixtures, the impact of protein-induced fluctuations was examined by calculating the 2D electronic spectra of a weakly coupled dimer with vibrational modes in the resonant condition [J. Chem. Phys. 142, 212403 (2015)]. This analysis demonstrated that quantum mixtures of the vibronic resonance are rather robust under the influence of the fluctuations at cryogenic temperatures, whereas the mixtures are eradicated by the fluctuations at physiological temperatures. However, this conclusion cannot be generalized because the magnitude of the coupling inducing the quantum mixtures is proportional to the inter-pigment coupling. In this study, we explore the impact of the fluctuations on electronic-vibrational quantum mixtures in a strongl...

  12. Trends in Artificial Intelligence.

    Science.gov (United States)

    Hayes, Patrick

    1978-01-01

    Discusses the foundations of artificial intelligence as a science and the types of answers that may be given to the question, "What is intelligence?" The paradigms of artificial intelligence and general systems theory are compared. (Author/VT)

  13. The INCA system: a further step towards a telemedical artificial pancreas.

    Science.gov (United States)

    Gómez, Enrique J; Hernando Pérez, M Elena; Vering, Thomas; Rigla Cros, Mercedes; Bott, Oliver; García-Sáez, Gema; Pretschner, Peter; Brugués, Eulalia; Schnell, Oliver; Patte, Caroline; Bergmann, Joachim; Dudde, Ralf; de Leiva, Alberto

    2008-07-01

    Biomedical engineering research efforts have accomplished another level of a "technological solution" for diabetes: an artificial pancreas to be used by patients and supervised by healthcare professionals at any time and place. Reliability of continuous glucose monitoring, availability of real-time programmable insulin pumps, and validation of safe and efficient control algorithms are critical components for achieving that goal. Nevertheless, the development and integration of these new technologies within a telemedicine system can be the basis of a future artificial pancreas. This paper introduces the concept, design, and evaluation of the "intelligent control assistant for diabetes, INCA" system. INCA is a personal digital assistant (PDA)-based personal smart assistant to provide patients with closed-loop control strategies (personal and remote loop), based on a real-time continuous glucose sensor (Guardian RT, Medtronic), an insulin pump (D-TRON, Disetronic Medical Systems), and a mobile general packet radio service (GPRS)-based telemedicine communication system. Patient therapeutic decision making is supervised by doctors through a multiaccess telemedicine central server that provides to diabetics and doctors a Web-based access to continuous glucose monitoring and insulin infusion data. The INCA system has been technically and clinically evaluated in two randomized and crossover clinical trials showing an improvement on glycaemic control of diabetic patients.

  14. Proposal of a system of function-discovery using a bug type of artificial life

    Energy Technology Data Exchange (ETDEWEB)

    Serikawa, S.; Shimomura, T. [Kyushu Institute of Technology, Kitakyushu (Japan)

    1998-02-01

    The effectiveness of artificial life is investigated from an engineering point of view. A system (named S-system) of function-discovery using a bug type of artificial life is proposed in this study. Some functions are extracted by the system. The chromosome of a bug consists of functions, constants and variables. A tree structure is used for the expression of the chromosome. Some observation data are provided for the bugs. After obtaining the data, they reproduce. The concept of sexual / asexual reproduction is introduced in this study. The number of homogeneous bugs is limited for a variety of species. These ideas are very effective for a function-search. A part of the chromosome changes by mutation. As the generation proceeds, the bugs with the function in agreement with the observation data survive selectively, and finally determine the true function. For the validity of this system, some data which obey the known laws have been given for the bugs. The bugs have evolved and discovered some functions in agreement with the laws. As for an unknown function, observation data on glossiness have been provided. They have also discovered the function. In addition, they have determined the multiple curves included in the image data. The S-system has the characteristics that the solution tends to converge and stabilizes in comparison with Genetic Programming. Moreover, the form of the function is relatively simple. 11 refs., 14 figs., 3 tabs.

  15. The potential of the skin as a readout system to test artificial turf systems: clinical and immunohistological effects of a sliding on natural grass and artificial turf

    NARCIS (Netherlands)

    Peppelman, M.; Eijnde, W.A. van den; Langewouters, A.M.G.; Weghuis, M.O.; Erp, P.E.J. van

    2013-01-01

    The purpose of this study was to investigate the interaction of skin with natural grass and artificial turf at clinical, histological and immunohistochemical level. Therefore, 14 male volunteers performed slidings on dry natural grass, wet natural grass and artificial turf. Directly and 24 h after t

  16. Photosynthetic Diurnal Variation of Soybean Cultivars with High Photosynthetic Efficiency

    Institute of Scientific and Technical Information of China (English)

    MAN Wei-qun; DU Wei-guang; ZHANG Gui-ru; LUAN Xiao-yan; GE Qiao-ying; HAO Nai-bin; CHEN Yi

    2002-01-01

    The photosynthetic characters were investigated among soybean cultivars with high photosynthetic efficiency and high yield. The results indicated that: 1) There were significant differences in photosynthetic rate (Ph) and dark respiration rate (DR) under saturation light intensity and appropriate temperature.2) There were a little difference in light compensation point among them. Photo flux density (PFD) were mong the cultivars. Diurnal variation of Pn was shown a curve with two peaks. 4) The cultivars with high photosynthetic efficiency were subjected less to photoinhibition than that with high yield. Critical temperatures of photoinhibition in high photosynthetic efficiency cultivars were higher than that of high yield.

  17. Supervised Online Adaptive Control of Inverted Pendulum System Using ADALINE Artificial Neural Network with Varying System Parameters and External Disturbance

    Directory of Open Access Journals (Sweden)

    Sudeep Sharma

    2012-07-01

    Full Text Available Generalized Adaptive Linear Element (GADALINE Artificial Neural Network (ANN as an Artificial Intelligence (AI technique is used in this paper to online adaptive control of a Non-linear Inverted Pendulum (IP system. The ANN controller is designed with specifications as: network type is three (Input, Hidden and Output layered Feed-Forward Network (FFN, training is done by Widrow-Hoffs delta rule or Least Mean Square algorithm (LMS, that updates weight and bias states to minimize the error function. The research is focused on how to adapt the control actions to solve the problem of “parameter variations”. The method is applied to the Nonlinear IP model with the application of some uncertainties, and the experimental results show that the system responds very well to handle those uncertainties.

  18. Test system for defect detection in cementitious material with artificial neural network

    Directory of Open Access Journals (Sweden)

    Saowanee Saechai

    2013-04-01

    Full Text Available This paper introduces a newly developed test system for defect detection, classification of number of defects andidentification of defect materials in cement-based products. With the system, the pattern of ultrasonic waves for each case ofspecimen can be obtained from direct and indirect measurements. The machine learning algorithm called artificial neuralnetwork classifier with back-propagation model is employed for classification and verification of the wave patterns obtainedfrom different specimens. By applying the system, the presence or absence of a defect in mortar can be identified. Moreover,the system is applied to identify the number and materials of defects inside the mortar. The methodology is explained and theclassification results are discussed. The effectiveness of the developed test system is evaluated. Comparison of the classification results between different input features with different number of training sets is demonstrated. The results show that thistechnique based on pattern recognition has a potential for practical inspection of concrete structures.

  19. A General Architecture for Robotics Systems: A Perception-Based Approach to Artificial Life.

    Science.gov (United States)

    Young, Rupert

    2017-01-01

    Departing from the conventional view of the reasons for the behavior of living systems, this research presents a radical and unique view of that behavior, as the observed side effects of a hierarchical set of simple, continuous, and dynamic negative feedback control systems, by way of an experimental model implemented on a real-world autonomous robotic rover. Rather than generating specific output from input, the systems control their perceptual inputs by varying output. The variables controlled do not exist in the environment, but are entirely internal perceptions constructed as a result of the layout and connections of the neural architecture. As the underlying processes are independent of the domain, the architecture is universal and thus has significant implications not only for understanding natural living systems, but also for the development of robotics systems. The central process of perceptual control has the potential to unify the behavioral sciences and is proposed as the missing behavioral principle of Artificial Life.

  20. 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

    2013-01-01

    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. PMID:23367113

  1. 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.

  2. An Artificial Immune System Model for Multi Agents Resource Sharing in Distributed Environments

    Directory of Open Access Journals (Sweden)

    Tejbanta Singh Chingtham

    2010-08-01

    Full Text Available Natural Immune system plays a vital role in the survival of the all living being. It provides a mechanism to defend itself from external predates making it consistent systems, capable of adapting itself for survival incase of changes. The human immune system has motivated scientists and engineers for finding powerful information processing algorithms that has solved complex engineering tasks. This paper explores one of the various possibilities for solving problem in a Multiagent scenario wherein multiple robots are deployed to achieve agoal collectively. The final goal is dependent on the performance of individual robot and its survival without having to lose its energy beyond a predetermined threshold value by deploying an evolutionary computational technique otherwise called the artificial immune system that imitates the biological immune system.

  3. An Artificial Immune System Model for Multi-Agents Resource Sharing in Distributed Environments

    CERN Document Server

    Chingtham, Tejbanta Singh; Ghose, M K

    2011-01-01

    Natural Immune system plays a vital role in the survival of the all living being. It provides a mechanism to defend itself from external predates making it consistent systems, capable of adapting itself for survival incase of changes. The human immune system has motivated scientists and engineers for finding powerful information processing algorithms that has solved complex engineering tasks. This paper explores one of the various possibilities for solving problem in a Multiagent scenario wherein multiple robots are deployed to achieve a goal collectively. The final goal is dependent on the performance of individual robot and its survival without having to lose its energy beyond a predetermined threshold value by deploying an evolutionary computational technique otherwise called the artificial immune system that imitates the biological immune system.

  4. 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.

  5. Photorespiration provides the chance of cyclic electron flow to operate for the redox-regulation of P700 in photosynthetic electron transport system of sunflower leaves.

    Science.gov (United States)

    Takagi, Daisuke; Hashiguchi, Masaki; Sejima, Takehiro; Makino, Amane; Miyake, Chikahiro

    2016-09-01

    To elucidate the molecular mechanism to oxidize the reaction center chlorophyll, P700, in PSI, we researched the effects of partial pressure of O2 (pO2) on photosynthetic characteristic parameters in sunflower (Helianthus annuus L.) leaves. Under low CO2 conditions, the oxidation of P700 was stimulated; however the decrease in pO2 suppressed its oxidation. Electron fluxes in PSII [Y(II)] and PSI [Y(I)] showed pO2-dependence at low CO2 conditions. H(+)-consumption rate, estimated from Y(II) and CO2-fixation/photorespiration rates (JgH(+)), showed the positive curvature relationship with the dissipation rate of electrochromic shift signal (V H (+) ), which indicates H(+)-efflux rate from lumen to stroma in chloroplasts. Therefore, these electron fluxes contained, besides CO2-fixation/photorespiration-dependent electron fluxes, non-H(+)-consumption electron fluxes including Mehler-ascorbate peroxidase (MAP)-pathway. Y(I) that was larger than Y(II) surely implies the functioning of cyclic electron flow (CEF). Both MAP-pathway and CEF were suppressed at lower pO2, with plastoquinone-pool reduced. That is, photorespiration prepares the redox-poise of photosynthetic electron transport system for CEF activity as an electron sink. Excess Y(II), [ΔY(II)] giving the curvature relationship with V H (+) , and excess Y(I) [ΔCEF] giving the difference between Y(I) and Y(II) were used as an indicator of MAP-pathway and CEF activity, respectively. Although ΔY(II) was negligible and did not show positive relationship to the oxidation-state of P700, ΔCEF showed positive linear relationship to the oxidation-state of P700. These facts indicate that CEF cooperatively with photorespiration regulates the redox-state of P700 to suppress the over-reduction in PSI under environmental stress conditions.

  6. A Hybrid Model For Phrase Chunking Employing Artificial Immunity System And Rule Based Methods

    Directory of Open Access Journals (Sweden)

    Bindu.M.S

    2011-11-01

    Full Text Available Natural language Understanding (NLU, an important field of Artificial Intelligence (AI is concerned with the speech and language understanding between human and computer. Understanding language means knowing what concept a word or phrase stands for and how to link them to form meaningful sentence. Identification of phrases or phrase chunking is an important step in natural language understanding (NLU. Chunker identifies and divides sentences into syntactically correlated word groups. Question Answering (QA systems, another important application of Artificial Intelligence (AImostly requires retrieval of nouns or noun phrases as answers to the questions raised by the users. Also Chunking is an important preprocessing step in full parsing. Due to high ambiguity of natural language, exact parsing of text may become very complex. This ambiguity may be partially resolved by using chunking as an intermediate step. To the best of our knowledge no known work or tag set is available for phrase chunking in Malayalam. To separate the chunks in a document it must be labeled with parts-ofspeech (POS tags. POS Tagging is a difficult task in Malayalam as it is a complex and compounding language. In this paper we describe the application of artificial immunity system (AIS for chunking which is implemented and obtained an accurate output with 96% precision and 93% recall. This system istested on corpuses collected from reputed news papers and magazines. These corpuses contained documents from five different domains such as sports, health, agriculture, science and politics and each document contained sentences –simple, compound, complex-of various levels of complexity. POS tag set with 52 tags is developed for preparing the tagged corpus for Malayalam. The phrase tag set contains 20 phrase tags.

  7. Enhanced practical photosynthetic CO2 mitigation

    Science.gov (United States)

    Bayless, David J.; Vis-Chiasson, Morgan L.; Kremer, Gregory G.

    2003-12-23

    This process is unique in photosynthetic carbon sequestration. An on-site biological sequestration system directly decreases the concentration of carbon-containing compounds in the emissions of fossil generation units. In this process, photosynthetic microbes are attached to a growth surface arranged in a containment chamber that is lit by solar photons. A harvesting system ensures maximum organism growth and rate of CO.sub.2 uptake. Soluble carbon and nitrogen concentrations delivered to the cyanobacteria are enhanced, further increasing growth rate and carbon utilization.

  8. Artificial Neural Network Integrated Artificial Endocrine System Model%一种与人工神经网络结合的人工内分泌系统模型

    Institute of Scientific and Technical Information of China (English)

    林广栋; 王煦法; 尤海峰

    2012-01-01

    Endocrine system of human body is highly self-adaptive and self-regulated. In endocrine system, thyroid hormone plays an important role. It enables humans to react violently in emergence, thus increases the chance of survival. In this work, a new artificial endocrine model called TAES (Thyroid hormone inspired Artificial Endocrine System) is proposed. TAES is inspired by the secretion, storage, and release mechanism of thyroid hormone. It can increase system's adaptability towards dynamic environment. In this work, TAES is applied to robot control system. Simulated experiments are carried out and the experimental results prove the TAES's validity.%人体的内分泌系统具有强大的自适应、自调节能力.在人体的内分泌系统中,甲状腺激素能使人类在紧急情况下产生异常迅速的反应,从而增加人类的生存概率.本文借鉴甲状腺激素的分泌,储存和释放机制,提出一种新的与人工神经网络结合的人工内分泌模型,称为TAES(Thyroid hormone inspired Artificial Endocrine System)模型.TAES模型可以增加控制系统对动态环境的适应性.本文将TAES模型应用于机器人避障实验中.实验结果表明,该系统可以增加机器人在紧急情况下的避障能力.

  9. 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...... 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...

  10. 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.

  11. Optimal Solution for an Engineering Applications Using Modified Artificial Immune System

    Science.gov (United States)

    Padmanabhan, S.; Chandrasekaran, M.; Ganesan, S.; patan, Mahamed Naveed Khan; Navakanth, Polina

    2017-03-01

    An Engineering optimization leads a essential role in several engineering application areas like process design, product design, re-engineering and new product development, etc. In engineering, an awfully best answer is achieved by comparison to some completely different solutions by utilization previous downside information. An optimization algorithms provide systematic associate degreed economical ways that within which of constructing and comparison new design solutions so on understand at best vogue, thus on best solution efficiency and acquire the foremost wonderful design impact. In this paper, a new evolutionary based Modified Artificial Immune System (MAIS) algorithm used to optimize an engineering application of gear drive design. The results are compared with existing design.

  12. Transcutaneous Optical Information Transmission System for a Totally Implantable Artificial Heart

    Science.gov (United States)

    Yamamoto, Takahiko; Koshiji, Kohji

    A transcutaneous optical information transmission system (TOITS) offers the most promising method for noninvasively transmitting the information to control a total artificial heart (TAH). We had used light-emitting diode (LED) and photo diode (PD) with different wavelengths for full-duplex bidirectional communication in the TOITS. In this study, reduction of optical crosstalk in full-duplex bidirectional communication was investigated by using a combination of two orthogonal polarizers with the same wavelength. As a result, we confirmed that optical crosstalk could be prevented for communication through a cow's skin (3.5 mm thick) and that the signal waveform could be transmitted satisfactorily.

  13. 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.

  14. Supervised pixel classification using a feature space derived from an artificial visual system

    Science.gov (United States)

    Baxter, Lisa C.; Coggins, James M.

    1991-01-01

    Image segmentation involves labelling pixels according to their membership in image regions. This requires the understanding of what a region is. Using supervised pixel classification, the paper investigates how groups of pixels labelled manually according to perceived image semantics map onto the feature space created by an Artificial Visual System. Multiscale structure of regions are investigated and it is shown that pixels form clusters based on their geometric roles in the image intensity function, not by image semantics. A tentative abstract definition of a 'region' is proposed based on this behavior.

  15. 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.

  16. 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.

  17. APPLICATION OF ARTIFICIAL NEURAL NETWORK IN COMPLEX SYSTEMS OF REGIONAL SUSTAINABLE DEVELOPMENT

    Institute of Scientific and Technical Information of China (English)

    SHI Chun; Philip JAMES; GUO Zhong-yang

    2004-01-01

    Meeting the challenge of sustainable development requires substantial advances in understanding the interaction of natural and human systems. The dynamics of regional sustainable development could be addressed in the context of complex system thinking. Three features of complex systems are that they are uncertain, non-linear and self-organizing. Modeling regional development requires a consideration of these features. This paper discusses the feasibility of using the artificial neural networt(ANN) to establish an adjustment prediction model for the complex systems of sustainable development (CSSD). Shanghai Municipality was selected as the research area to set up the model, from which reliable prediction data were produced in order to help regional development planning. A new approach, which could help to manage regional sustainable development, is then explored.

  18. Artificial immune system via Euclidean Distance Minimization for anomaly detection in bearings

    Science.gov (United States)

    Montechiesi, L.; Cocconcelli, M.; Rubini, R.

    2016-08-01

    In recent years new diagnostics methodologies have emerged, with particular interest into machinery operating in non-stationary conditions. In fact continuous speed changes and variable loads make non-trivial the spectrum analysis. A variable speed means a variable characteristic fault frequency related to the damage that is no more recognizable in the spectrum. To overcome this problem the scientific community proposed different approaches listed in two main categories: model-based approaches and expert systems. In this context the paper aims to present a simple expert system derived from the mechanisms of the immune system called Euclidean Distance Minimization, and its application in a real case of bearing faults recognition. The proposed method is a simplification of the original process, adapted by the class of Artificial Immune Systems, which proved to be useful and promising in different application fields. Comparative results are provided, with a complete explanation of the algorithm and its functioning aspects.

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

    Science.gov (United States)

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

    2016-09-01

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

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

    Directory of Open Access Journals (Sweden)

    Matija Štrbac

    2014-01-01

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

  1. 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.

  2. 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.

  3. Toward an artificial sensory feedback system for prosthetic mobility rehabilitation: Examination of sensorimotor responses

    Directory of Open Access Journals (Sweden)

    Aman Sharma, MHSc

    2014-10-01

    Full Text Available People with lower-limb amputation have reduced mobility due to loss of sensory information, which may be restored by artificial sensory feedback systems built into prostheses. For an effective system, it is important to understand how humans sense, interpret, and respond to the feedback that would be provided. The goal of this study was to examine sensorimotor responses to mobility-relevant stimuli. Three experiments were performed to examine the effects of location of stimuli, frequency of stimuli, and means for providing the response. Stimuli, given as vibrations, were applied to the thigh region, and responses involved leg movements. Sensorimotor reaction time (RT was measured as the duration between application of the stimulus and initiation of the response. Accuracy of response was also measured. Overall average RTs for one response option were 0.808 +/– 0.142 s, and response accuracies were >90%. Higher frequencies (220 vs 140 Hz of vibration stimulus provided in anterior regions of the thigh produced the fastest RTs. When participants were presented with more than one stimulus and response option, RTs increased. Findings suggest that long sensorimotor responses may be a limiting factor in the development of an artificial feedback system for mobility rehabilitation applications; however, feed-forward techniques could potentially help to address these limitations

  4. Heterogeneous systems biocatalysis; the path to the fabrication of self-sufficient artificial metabolic cells.

    Science.gov (United States)

    López-Gallego, Fernando; Jackson, Eriene; Betancor, Lorena

    2017-09-26

    Industrial biocatalysis is playing a key role in the development of the global bio-economy that must change our current productive model to pair the socio-economical development with the preservation of our already harmed planet. The exploitation of isolated multi-enzyme systems and the discovery of novel biocatalytic activities are leading us to manufacture chemicals that were inaccessible through biological routes in the early past. These endeavors have been grouped in the concept of Systems biocatalysis. However, by using isolated biological machineries, fundamental features underlying the protein confinement found inside the living cells are missed. To re-gain these properties such concept can be expanded to a new concept; heterogeneous systems biocatalysis. This new concept is based on the fabrication of heterogeneous biocatalysts inspired by the spatial organization and compartmentalization that orchestrate metabolic pathways within cells. By assembling biological machineries (including enzymes and cofators) into artificial solid chassis, one can fabricate self-sufficient and robust cell-free systems able to catalyze orchestrated chemical processes. Furthermore, the confinement of enzymes and "artificial cofactor" inside solid materials has also attracted our attention since these self-sufficient systems exert de novo and non natural functionalities. Herein, we pursue going beyond immobilization of multi-enzyme systems, discussing only those enzymatic systems that have been co-immobilized with their cofactor or exogenous partners to enhance their cooperative action. In this article, we review the latest architectures developed to fabricate self-sufficient heterogeneous biocatalysts with application in chemical manufacturing, biosensing or energy production. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

    Directory of Open Access Journals (Sweden)

    Vicen-Bueno R

    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.

  6. 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.

  7. Artificial Immune Systems (AIS) - A New Paradigm for Heuristic Decision Making

    CERN Document Server

    Uwe, Aickelin

    2008-01-01

    Over the last few years, more and more heuristic decision making techniques have been inspired by nature, e.g. evolutionary algorithms, ant colony optimisation and simulated annealing. More recently, a novel computational intelligence technique inspired by immunology has emerged, called Artificial Immune Systems (AIS). This immune system inspired technique has already been useful in solving some computational problems. In this keynote, we will very briefly describe the immune system metaphors that are relevant to AIS. We will then give some illustrative real-world problems suitable for AIS use and show a step-by-step algorithm walkthrough. A comparison of AIS to other well-known algorithms and areas for future work will round this keynote off. It should be noted that as AIS is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from the examples given here.

  8. A thermodynamic evaluation of chilled water central air conditioning systems using artificial intelligence tools

    Directory of Open Access Journals (Sweden)

    Juan Carlos Armas

    2011-05-01

    Full Text Available  An analysis of a chilled water central air conditioning system is presented. The object was to calculate main cycle component irreversibility, as well as evaluating this indicator’s sensitivity to operational variations. Artificial neural networks (ANN, genetic algorithms (GA and Matlab tools were used to calculate refrigerant thermodynamic properties during each cycle stage. These tools interacted with equations describing the system’s thermodynamic behaviour. Refrigerant temperature, when released from the compressor, was determined by a hybrid model combining the neural model with a simple genetic algorithm used as optimisation tool; the cycle’s components which were most sensitive to changes in working conditions were identified. It was concluded that the compressor, evaporator and expansion mechanism (in that order represented significant exergy losses reaching 85.62% of total system irreversibility. A very useful tool was thus developed for evaluating these systems

  9. 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.

  10. 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.

  11. 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. PMID:24198797

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. A 2-transistor/1-resistor artificial synapse capable of communication and stochastic learning forneuromorphic systems

    Directory of Open Access Journals (Sweden)

    Zhongqiang eWang

    2015-01-01

    Full Text Available 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.

  17. 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.

  18. Photosynthetic Pigments in Diatoms

    OpenAIRE

    Paulina Kuczynska; Malgorzata Jemiola-Rzeminska; Kazimierz Strzalka

    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...

  19. Detection of artificial water flows by the lateral line system of a benthic feeding cichlid fish.

    Science.gov (United States)

    Schwalbe, Margot A B; Sevey, Benjamin J; Webb, Jacqueline F

    2016-04-01

    The mechanosensory lateral line system of fishes detects water motions within a few body lengths of the source. Several types of artificial stimuli have been used to probe lateral line function in the laboratory, but few studies have investigated the role of flow sensing in benthic feeding teleosts. In this study, we used artificial flows emerging from a sandy substrate to assess the contribution of flow sensing to prey detection in the peacock cichlid, Aulonocara stuartgranti, which feeds on benthic invertebrates in Lake Malawi. Using a positive reinforcement protocol, we trained fish to respond to flows lacking the visual and chemical cues generated by tethered prey in prior studies with A. stuartgranti Fish successfully responded to artificial flows at all five rates presented (characterized using digital particle image velocimetry), and showed a range of flow-sensing behaviors, including an unconditioned bite response. Immediately after lateral line inactivation, fish rarely responded to flows and the loss of vital fluorescent staining of hair cells (with 4-di-2-ASP) verified lateral line inactivation. Within 2 days post-treatment, some aspects of flow-sensing behavior returned and after 7 days, flow-sensing behavior and hair cell fluorescence both returned to pre-treatment levels, which is consistent with the reported timing of hair cell regeneration in other vertebrates. The presentation of ecologically relevant water flows to assess flow-sensing behaviors and the use of a positive reinforcement protocol are methods that present new opportunities to study the role of flow sensing in the feeding ecology of benthic feeding fishes.

  20. Spectroscopic Studies of Photosynthetic Systems and Their Application in Photovoltaic Devices - Equipment Only: Cooperative Research and Development Final Report, CRADA Number CRD-06-175

    Energy Technology Data Exchange (ETDEWEB)

    Seibert, M.

    2014-09-01

    Spectral hole-burning (SHB) and single photosynthetic complex spectroscopy (SPCS) will be used to study the excitonic structure and excitation energy transfer (EET) processes of several photosynthetic protein complexes at low temperatures. The combination of SHB on bulk samples and SPCS is a powerful frequency domain approach for obtaining data that will address a number of issues that are key to understanding excitonic structure and energy transfer dynamics. The long-term goal is to reach a better understanding of the ultrafast solar energy driven primary events of photosynthesis as they occur in higher plants, cyanobacteria, purple bacteria, and green algae. A better understanding of the EET and charge separation (CS) processes taking place in photosynthetic complexes is of great interest, since photosynthetic complexes might offer attractive architectures for a future generation of circuitry in which proteins are crystallized.

  1. Use of artificial neural networks for analysis of complex physical systems

    Energy Technology Data Exchange (ETDEWEB)

    Benjamin, A.; Altman, B.; O`Gorman, C.; Rodeman, R.; Paez, T.L.

    1996-12-31

    Mathematical models of physical systems are used, among other purposes, to improve our understanding of the behavior of physical systems, predict physical system response, and control the responses of systems. Phenomenological models are frequently used to simulate system behavior, but an alternative is available - the artificial neural network (ANN). The ANN is an inductive, or data-based model for the simulation of input/output mappings. The ANN can be used in numerous frameworks to simulate physical system behavior. ANNs require training data to learn patterns of input/output behavior, and once trained, they can be used to simulate system behavior within the space where they were trained.They do this by interpolating specified inputs among the training inputs to yield outputs that are interpolations of =Ming outputs. The reason for using ANNs for the simulation of system response is that they provide accurate approximations of system behavior and are typically much more efficient than phenomenological models. This efficiency is very important in situations where multiple response computations are required, as in, for example, Monte Carlo analysis of probabilistic system response. This paper describes two frameworks in which we have used ANNs to good advantage in the approximate simulation of the behavior of physical system response. These frameworks are the non-recurrent and recurrent frameworks. It is assumed in these applications that physical experiments have been performed to obtain data characterizing the behavior of a system, or that an accurate finite element model has been run to establish system response. The paper provides brief discussions on the operation of ANNs, the operation of two different types of mechanical systems, and approaches to the solution of some special problems that occur in connection with ANN simulation of physical system response. Numerical examples are presented to demonstrate system simulation with ANNs.

  2. Thermal phase transition in artificial spin ice systems induces the formation and migration of monopole-like magnetic excitations

    Science.gov (United States)

    León, Alejandro

    2016-11-01

    Artificial spin ice systems exhibit monopole-like magnetic excitations. We develop here a theoretical study of the thermal phase transition of an artificial spin ice system, and we elucidate the role of the monopole excitations in the transition temperature. The dynamics of the spin ice is described by an efficient model based on cellular automata, which considers both thermal effects and dipolar interactions. We have established the critical temperature of the phase transition as function of the magnetic moment and the energy barrier of reversion. In addition, we predict that thermal gradients in the system induce the motion of elementary excitations, which could permit to manipulate monopole-like states.

  3. Thermal phase transition in artificial spin ice systems induces the formation and migration of monopole-like magnetic excitations

    Energy Technology Data Exchange (ETDEWEB)

    León, Alejandro

    2016-11-01

    Artificial spin ice systems exhibit monopole-like magnetic excitations. We develop here a theoretical study of the thermal phase transition of an artificial spin ice system, and we elucidate the role of the monopole excitations in the transition temperature. The dynamics of the spin ice is described by an efficient model based on cellular automata, which considers both thermal effects and dipolar interactions. We have established the critical temperature of the phase transition as function of the magnetic moment and the energy barrier of reversion. In addition, we predict that thermal gradients in the system induce the motion of elementary excitations, which could permit to manipulate monopole-like states.

  4. Concurrent study of stability and cytotoxicity of a novel nanoemulsion system - an artificial neural networks approach.

    Science.gov (United States)

    Seyedhassantehrani, Negar; Karimi, Roya; Tavoosidana, Gholamreza; Amani, Amir

    2017-05-01

    Problems commonly associated with using nanoemulsions are their cytotoxic effects and low stability profiles. Here, for the first time, concentrations of ingredients of a nanoemulsion system were investigated to obtain the most stable nanoemulsion system with the least cytotoxic effect on MCF7 cell line. Artificial neural networks (ANNs) were used to model the experimentally obtained data. Surfactant concentration was found to be the dominant factor in determining the stability - surfactant concentration above a critical point made the preparation unstable, while it appeared not to be influencing the cytotoxicity. Concentration of oil showed a direct relationship to the cytotoxicity with a minimum value required to provide an acceptable safety profile for the preparation. Co-surfactant appeared not to be considerably effective on neither stability nor cytotoxicity. To obtain the optimum preparation with maximum stability and minimum cytotoxicity, surfactant and oil values need to be kept at their maximum and minimum possible, respectively.

  5. 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.

  6. 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.

  7. 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.

  8. Using Decision Support System to Find Suitable Sites for Groundwater Artificial Recharge

    Science.gov (United States)

    Ghasemian, D.; Winter, C. L.; Kheirkhah Zarkesh, M. M.; Moradi, H. R.

    2014-12-01

    Some parts of Iran are considered as one of the driest regions of the world, where water is a limiting factor for lasting life therefore using seasonal floodwaters is very important in these arid regions. On the other hand, special attention has been paid to artificial groundwater recharge in these regions. Floodwater spreading on the permeable terrain is one of the flood control and utilization methods. Determination of appropriate site for water spreading is one of the most important stages of this project. Parameters considered in the selection of groundwater artificial recharge locations are diverse and complex. These factors consist of earth sciences (geology, geomorphology and soils), hydrology (runoff, sediment yield, infiltration and groundwater conditions) and socio-economic aspects (irrigated agriculture, flood damage mitigation, environment, job creation and so on). Hence, decision making depends on criteria of diverse nature. The goal of this study is defining a Decision Support System for floodwater site selection in Shahriary area. Four main criteria were selected in this research which are floodwater characters, infiltration, water applications and flood damage. In order to determine the weight of factors, Analytical Hierarchy Process was used. The results showed that soil texture and floodwater volume of infiltration are the most important factors. After providing output maps which had been defined in five scenarios, Kappa Index was used to evaluate the model. Based on the obtained results, the maps showed an acceptable agreement with control zones.

  9. 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

  10. 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.

  11. 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.

  12. Intelligent Monitoring System on Prediction of Building Damage Index using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Reni Suryanita

    2012-03-01

    Full Text Available An earthquake potentially destroys a tall building. The building damage can be indexed by FEMA into three categories namely Immediate Occupancy (IO, Life Safety (LS, and Collapse Prevention (CP. To determine the damage index, the building model has been simulated into structure analysis software. Acceleration data has been analyzed using non linear method in structure analysis program. The earthquake load is time history at surface, PGA=0105g. This work proposes an intelligent monitoring system utilizing Artificial Neural Network to predict the building damage index. The system also provides an alert system and notification to inform the status of the damage. Data learning is trained on ANN utilizing feed forward and back propagation algorithm. The alert system is designed to be able to activate the alarm sound, view the alert bar or text, and send notification via email to the security or management. The system is tested using sample data represented in three conditions involving IO, LS, and CP. The results show that the proposed intelligent monitoring system could provide prediction of up to 92% rate of accuracy and activate the alert. Implementation of the system in building monitoring would allow for rapid, intelligent and accurate prediction of the building damage index due to earthquake.

  13. Artificial Cooperative Search Algorithm based Load Frequency Control of Interconnected Power Systems with AC-DC Tie-lines

    Directory of Open Access Journals (Sweden)

    S. Ramesh kumar

    2014-05-01

    Full Text Available A maiden effort for optimal tuning of load frequency controller parameters using Artificial Cooperative Search (ACS algorithm for a two area interconnected power system with AC-DC parallel tie-lines has been presented in this paper. ACS is a recent swarm intelligence algorithm developed for solving numerical optimization problems. The swarm intelligence philosophy behind ACS algorithm is based on the migration of two artificial superorganisms as they biologically interact to achieve the global minimum value pertaining to the problem. The HVDC link in parallel with AC tie-line is used as system interconnection to effectively damp the frequency oscillations of the AC system. An integral square error criterion (ISE has been used as performance index to design the optimal parameters. A comparative study of tuned values has been presented to show the effectiveness of the Artificial Cooperative Search algorithm. The results demonstrate the success of ACS algorithm in solving Load frequency control (LFC optimization problem.

  14. Fuzzy Artificial Bee Colony System with Cooling Schedule for the Segmentation of Medical Images by Using of Spatial Information

    Directory of Open Access Journals (Sweden)

    Jzau-sheng Lin

    2013-02-01

    Full Text Available In this study, segmentation of medical images using a fuzzy artificial bee colony algorithm with a cooling schedule is created. In this study, we embedded fuzzy inference strategy into the artificial bee colony system to construct a segmentation system named Fuzzy Artificial Bee Colony System (FABCS. A conventional FCM algorithm did not utilize the spatial information in the image. We set a local circular area with a variable radius by using a cooling schedule for each bee to search suitable cluster centers with the FCM algorithm in an image. The cluster centers can be calculated by each bee with the membership states in the FABCS and then updated iteratively for all bees in order to find near-global solution in MR image segmentation. The proposed FABCS found the cluster centers with local spatial information instead of global pixels’ intensities. In the simulation and real medical-image segmentation results, the proposed FABCS network can reserve the segmentation performance.

  15. Numerical Comparison of Artificial Recharge by Small-diameter Wells to Common Systems

    Science.gov (United States)

    Händel, F.; Liu, G.; Dietrich, P.; Liedl, R.; Fank, J.; Fank, A.; Butler, J. J.

    2013-12-01

    Scarcity of potable water has reached to a critical level all around the world. To address the temporal inequality of demand and availability of water resources, as well as additional purposes like enhancing water quality, artificial recharge is increasingly used. For shallow infiltration, such recharge methods as surface infiltration basins and trenches are commonly applied. However, these methods have significant disadvantages, e.g., enhanced clogging, evaporation, and an increased need of land use. Therefore, a new method for artificial recharge using shallow small-diameter wells is investigated. Such wells can be installed by Direct Push (DP) and water is allowed to infiltrate into aquifers by natural gravity, so that their installation and operation costs are very low. In this work, this method is compared numerically to a surface infiltration basin and a system applying horizontal filter pipes. For this, the work is divided into two parts. First, a rigorous comparison is done between the DP well and the infiltration basin. The simulated aquifer is composed of an unsaturated zone of 12 m and a saturated zone of 8 m. The results show the dependency of both methods on different components of the hydraulic conductivity, and highlight the advantages of the DP well over the basin. A small number of 5-cm shallow wells of 12 m length can be used to recharge water at the same infiltration rate as from a 60 m2 basin. When a layer of low hydraulic conductivity is present, the infiltration capacity of surface basins is significantly reduced while the adverse impacts on the wells are less pronounced due to the horizontal flow above the low conductivity layer (larger distance of water movement away from the screen). In the second part of this work, the DP wells will be compared to an operating horizontal, vadose zone artificial recharge system in Southern Styria, Austria. The water table is 3 m deep and horizontal filter pipes are used to recharge water into the shallow

  16. Artificial Root Exudate System (ARES): a field approach to simulate tree root exudation in soils

    Science.gov (United States)

    Lopez-Sangil, Luis; Estradera-Gumbau, Eduard; George, Charles; Sayer, Emma

    2016-04-01

    The exudation of labile solutes by fine roots represents an important strategy for plants to promote soil nutrient availability in terrestrial ecosystems. Compounds exuded by roots (mainly sugars, carboxylic and amino acids) provide energy to soil microbes, thus priming the mineralization of soil organic matter (SOM) and the consequent release of inorganic nutrients into the rhizosphere. Studies in several forest ecosystems suggest that tree root exudates represent 1 to 10% of the total photoassimilated C, with exudation rates increasing markedly under elevated CO2 scenarios. Despite their importance in ecosystem functioning, we know little about how tree root exudation affect soil carbon dynamics in situ. This is mainly because there has been no viable method to experimentally control inputs of root exudates at field scale. Here, I present a method to apply artificial root exudates below the soil surface in small field plots. The artificial root exudate system (ARES) consists of a water container with a mixture of labile carbon solutes (mimicking tree root exudate rates and composition), which feeds a system of drip-tips covering an area of 1 m2. The tips are evenly distributed every 20 cm and inserted 4-cm into the soil with minimal disturbance. The system is regulated by a mechanical timer, such that artificial root exudate solution can be applied at frequent, regular daily intervals. We tested ARES from April to September 2015 (growing season) within a leaf-litter manipulation experiment ongoing in temperate deciduous woodland in the UK. Soil respiration was measured monthly, and soil samples were taken at the end of the growing season for PLFA, enzymatic activity and nutrient analyses. First results show a very rapid mineralization of the root exudate compounds and, interestingly, long-term increases in SOM respiration, with negligible effects on soil moisture levels. Large positive priming effects (2.5-fold increase in soil respiration during the growing

  17. Use of Wearable Sensors and Biometric Variables in an Artificial Pancreas System

    Directory of Open Access Journals (Sweden)

    Kamuran Turksoy

    2017-03-01

    Full Text Available 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.

  18. 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

    2017-03-07

    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.

  19. 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.

  20. 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

  1. 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

  2. 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.

  3. 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].

  4. 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.

  5. Topological defects from doping and quenched disorder in artificial ice systems

    Energy Technology Data Exchange (ETDEWEB)

    Reichhardt, Charles [Los Alamos National Laboratory; Reichhardt, Cynthia J [Los Alamos National Laboratory; Libal, A [BABES-BOLYAI UNIV

    2010-01-01

    We examine the ice-rule obeying and ice-rule breaking vertices in an artificial spin ice system created using magnetic vortices in type-II superconductors with nanostructured pinning arrays. We show that this system can be doped by changing the external field to move the number of vortices away from commensurability and create sites that contain two or zero vortices. For a square ice, the doping leads to the formation of a grain boundary of vertices that do not obey the ice rules. In commensurate systems where the ice rules are obeyed, we can introduce random disorder at the individual pinning sites to create regions where vortices may not be able to flip from one side of the trap to another. For weak disorder, all of the vertices still obey the ice rules, while at intermediate levels of disorder we find grain boundaries of vertices which do not obey the ice rules. For strong disorder it is possible to create isolated paired vertices that do not obey the ice rules. In summary, we have shown that an artificial square ice can be created using vortices in a type-II superconductor interacting with a periodic array of pinning sites where each site has a double well potential. By defining the direction of the effective spin according to the side of the double well occupied by the vortex, we find that this system obeys the ice rules for square ice. We add disorder to the system in the form of randomness of the height of the potential barrier at the center of the well, and obtain vertex configurations using a rotating drive protocol which is similar to the shaking ac magnetic field used in nanomagnetic systems. For weak disorder the entire system still obeys the square ice rules. For intermediate disorder, ice-rule breaking vertices appear and form grain boundaries, while for strong disorder there are both gain boundaries and isolated paired defects. In a system with uniform potential barrier heights, we introduce disorder by moving away from commensurability and creating

  6. 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.

  7. A distributed optical fiber sensing system for dynamic strain measurement based on artificial reflector

    Science.gov (United States)

    Sun, Zhenhong; Shan, Yuanyuan; Li, Yanting; Zhang, Yixin; Zhang, Xuping

    2016-10-01

    Phase sensitive optical time domain reflectometry (Φ-OTDR) has been widely used in many applications for its distributed sensing ability on weak disturbance all along the sensing fiber. However, traditional Φ-OTDR cannot make quantitative measurement on the external disturbance due to the randomly distributed position and reflectivity of scatters within the optical fiber. Recently, some methods have been proposed to realize quantitative measurement of dynamic strain. In these literatures, the fiber with or without FBGs in practice was easily damaged and with difficulty of maintenance. PZT is employed to generate strain event in the fiber. There is a large gap compared with the real detecting environment, which will not reveal the full performance of the sensing system. In this paper, a distributed optical fiber sensing (DOFS) system for dynamic strain measurement based on artificial reflector is proposed and demonstrated experimentally. The fiber under test (FUT) is composed by four 20-meter long single mode optical fiber patch cords (OFPCs), which are cascaded with ferrule contactor/physical contact (FC/PC) connectors via fiber flanges. The fiber facet of FC/PC connector forms an artificial reflector. When the interval between the two reflectors is changed, the phase of the interference signal will also be changed. A symmetric 3×3 coupler with table-look-up scheme is introduced to discriminate the phase change through interference intensity. In our experiment, the center 10m section of the second OFPC is attached to the bottom of an aluminum alloy plate. An ordinary loudspeaker box was located on the top of the aluminum alloy plate. The dynamic strain generated by the loudspeaker box is transmitted from the aluminum alloy plate to the OFPC. Experimental results show that the proposed method has a good frequency response characteristic up to 3.2 kHz and a linear intensity response of R2=0.9986 while the optical probe pulse width and repetition rate were 100ns

  8. 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...

  9. Implementation of a Vision System for a Landmine Detecting Robot Using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Roger Achkar

    2012-09-01

    Full Text Available Landmines, specifically anti-tank mines, cluster bombs, and unexploded ordnance form a serious problem in many countries. Several landmine sweeping techniques are used for minesweeping. This paper presents the design and the implementation of the vision system of an autonomous robot for landmines localization. The proposed work develops state-of-the-art techniques in digital image processing for pre-processing captured images of the contaminated area. After enhancement, Artificial Neural Network (ANN is used in order to identify, recognize and classify the landmines’ make and model. The Back-Propagation algorithm is used for training the network. The proposed work proved to be able to identify and classify different types of landmines under various conditions (rotated landmine, partially covered landmine with a success rate of up to 90%.

  10. Implementation of a Vision System for a Landmine Detecting Robot Using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Roger Achkar

    2012-10-01

    Full Text Available Landmines, specifically anti-tank mines, cluster bombs, and unexploded ordnance form a serious problemin many countries. Several landmine sweeping techniques are used for minesweeping. This paper presentsthe design and the implementation of the vision system of an autonomous robot for landmines localization.The proposed work develops state-of-the-art techniques in digital image processing for pre-processingcaptured images of the contaminated area. After enhancement, Artificial Neural Network (ANN is used inorder to identify, recognize and classify the landmines’ make and model. The Back-Propagation algorithmis used for training the network. The proposed work proved to be able to identify and classify different typesof landmines under various conditions (rotated landmine, partially covered landmine with a success rateof up to 90%.

  11. Analysis of Environmental Stress Factors Using an Artificial Growth System and Plant Fitness Optimization

    Directory of Open Access Journals (Sweden)

    Meonghun Lee

    2015-01-01

    Full Text Available The environment promotes evolution. Evolutionary processes represent environmental adaptations over long time scales; evolution of crop genomes is not inducible within the relatively short time span of a human generation. Extreme environmental conditions can accelerate evolution, but such conditions are often stress inducing and disruptive. Artificial growth systems can be used to induce and select genomic variation by changing external environmental conditions, thus, accelerating evolution. By using cloud computing and big-data analysis, we analyzed environmental stress factors for Pleurotus ostreatus by assessing, evaluating, and predicting information of the growth environment. Through the indexing of environmental stress, the growth environment can be precisely controlled and developed into a technology for improving crop quality and production.

  12. 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.

  13. 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.

  14. Preliminary evaluation of the tactile feedback system based on artificial skin and electrotactile stimulation.

    Science.gov (United States)

    Franceschi, M; Seminara, L; Pinna, L; Dosen, S; Farina, D; Valle, M

    2015-08-01

    This research is motivated by the need of integrating cutaneous sensing into a prosthetic device, enabling a bidirectional communication between the amputee and the prosthetic limb. An electronic skin based on piezoelectric polymer sensors transduces mechanical contact into electrical response which is conveyed to the human subject by electrotactile stimulation. Rectangular electrode arrays are placed on each patient's forearm and experiments are conducted on five different subjects to determine how well the orientation, position and direction of single lines are recognized. Overall, subjects discriminate the different touch modalities with acceptable success rates. In particular, the direction is identified at best and longitudinal lines on the patient's skin are recognized with the highest success rates. These preliminary results assess the feasibility of the artificial skin - electrostimulation system for prosthetic applications.

  15. Analysis of environmental stress factors using an artificial growth system and plant fitness optimization.

    Science.gov (United States)

    Lee, Meonghun; Yoe, Hyun

    2015-01-01

    The environment promotes evolution. Evolutionary processes represent environmental adaptations over long time scales; evolution of crop genomes is not inducible within the relatively short time span of a human generation. Extreme environmental conditions can accelerate evolution, but such conditions are often stress inducing and disruptive. Artificial growth systems can be used to induce and select genomic variation by changing external environmental conditions, thus, accelerating evolution. By using cloud computing and big-data analysis, we analyzed environmental stress factors for Pleurotus ostreatus by assessing, evaluating, and predicting information of the growth environment. Through the indexing of environmental stress, the growth environment can be precisely controlled and developed into a technology for improving crop quality and production.

  16. 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.

  17. A gene expression atlas of the central nervous system based on bacterial artificial chromosomes.

    Science.gov (United States)

    Gong, Shiaoching; Zheng, Chen; Doughty, Martin L; Losos, Kasia; Didkovsky, Nicholas; Schambra, Uta B; Nowak, Norma J; Joyner, Alexandra; Leblanc, Gabrielle; Hatten, Mary E; Heintz, Nathaniel

    2003-10-30

    The mammalian central nervous system (CNS) contains a remarkable array of neural cells, each with a complex pattern of connections that together generate perceptions and higher brain functions. Here we describe a large-scale screen to create an atlas of CNS gene expression at the cellular level, and to provide a library of verified bacterial artificial chromosome (BAC) vectors and transgenic mouse lines that offer experimental access to CNS regions, cell classes and pathways. We illustrate the use of this atlas to derive novel insights into gene function in neural cells, and into principal steps of CNS development. The atlas, library of BAC vectors and BAC transgenic mice generated in this screen provide a rich resource that allows a broad array of investigations not previously available to the neuroscience community.

  18. Design and implementation of a low power mobile CPU based embedded system for artificial leg control.

    Science.gov (United States)

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

    2013-01-01

    This paper presents the design and implementation of a new neural-machine-interface (NMI) for control of artificial legs. The requirements of high accuracy, real-time processing, low power consumption, and mobility of the NMI place great challenges on the computation engine of the system. By utilizing the architectural features of a mobile embedded CPU, we are able to implement our decision-making algorithm, based on neuromuscular phase-dependant support vector machines (SVM), with exceptional accuracy and processing speed. To demonstrate the superiority of our NMI, real-time experiments were performed on an able bodied subject with a 20 ms window increment. The 20 ms testing yielded accuracies of 99.94% while executing our algorithm efficiently with less than 11% processor loads.

  19. 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.

  20. Minimum Variance Distortionless Response Beamformer with Enhanced Nulling Level Control via Dynamic Mutated Artificial Immune System

    Directory of Open Access Journals (Sweden)

    Tiong Sieh Kiong

    2014-01-01

    Full Text Available In smart antenna applications, the adaptive beamforming technique is used to cancel interfering signals (placing nulls and produce or steer a strong beam toward the target signal according to the calculated weight vectors. Minimum variance distortionless response (MVDR beamforming is capable of determining the weight vectors for beam steering; however, its nulling level on the interference sources remains unsatisfactory. Beamforming can be considered as an optimization problem, such that optimal weight vector should be obtained through computation. Hence, in this paper, a new dynamic mutated artificial immune system (DM-AIS is proposed to enhance MVDR beamforming for controlling the null steering of interference and increase the signal to interference noise ratio (SINR for wanted signals.

  1. Design and Mechanics Simulation of Bionic Lubrication System of Artificial Joints

    Institute of Scientific and Technical Information of China (English)

    S. H. Su; Z. K. Hua; J. H. Zhang

    2006-01-01

    We propose a new structure for artificial joints with a joint capsule which is designed to overcome the drawback of current prostheses that omit many functions of the lubricant and the joint capsule. The new structure is composed of three components:lubricant, artificial joint and artificial joint capsule. The lubricant sealed in the capsule can not only reduce the wear of the artificial joint but also prevents the wear particles leaking into the body. So unexpected reactions between the wear particles and body can be avoided completely. A three-dimensional (3-D) finite element analysis (FEA) model was created for a bionic knee joint with capsule. The stresses and their distribution in the artificial capsule were simulated with different thickness, loadings,and flexion angles. The results show that the maximum stress occurs in the area between the artificial joint and the capsule. The effects of capsule thickness and the angles of flexion on stress are discussed in detail.

  2. 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.

  3. 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.

  4. Monitoring Immune System Function and Reactivation of Latent Viruses in the Artificial Gravity Pilot Study

    Science.gov (United States)

    Mehta, Satish; Crusian, Brian; Pierson, Duane; Sams, Clarence; Stowe, Raymond

    2007-01-01

    Numerous studies have indicated that dysregulation of the immune system occurs during or after spaceflight. Using 21 day -6 deg. head-down tilt bed rest as a spaceflight analog, this study describes the effects of artificial gravity as a daily countermeasure on immunity, stress and reactivation of clinically important latent herpes viruses. The specific aims were to evaluate psychological and physiological stress, to determine the status of the immune system and to quantify reactivation of latent herpes viruses. Blood, saliva, and urine samples were collected from each participating subject at different times throughout the study. An immune assessment was performed on all treatment and control subjects that consisted of a comprehensive peripheral immunophenotype analysis, intracellular cytokine profiles and a measurement of T cell function. The treatment group displayed no differences throughout the course of the study with regards to peripheral leukocyte distribution, cytokine production or T cell function. Shedding of EBV and CMV was quantified by real time PCR in saliva and urine samples, respectively. There was no significant difference in CMV DNA in the treatment group as compared to the control group. EBV and VZV on the other hand showed a mild reactivation during the study. There were no significant differences in plasma cortisol between the control and treatment groups. In addition, no significant differences between antiviral antibody titers (EBV-VCA, -EA, -EBNA, CMV) or tetramer-positive (EBV, CMV) were found between the two groups. EBV DNA copies in blood were typically undetectable but never exceeded 1,500 copies per 10(exp 6) PBMCs. These data indicate that the artificial gravity countermeasure and the 21 day head-down tilt bed rest regimen had no observable adverse effect on immune function.

  5. 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).

  6. Is artificial recharge promoting microbial activity and biodegradation processes in groundwater systems?

    Science.gov (United States)

    Barba Ferrer, Carme; Folch, Albert; Gaju, Núria; Martínez-Alonso, Maira; Carrasquilla, Marc; Grau-Martínez, Alba; Sanchez-Vila, Xavier

    2016-04-01

    Managed Artificial Recharge (MAR) represents a strategic tool for managing water resources, especially during scarce periods. On one hand, it can increase water stored in aquifers and extract it when weather conditions do not permit exclusive exploitation of surface resources. On the other, it allows improve water quality due the processes occurring into the soil whereas water crosses vadose zone. Barcelona (Catalonia, Spain) conurbation is suffering significant quantitative and qualitative groundwater disturbances. For this reason, Sant Vicenç MAR system, constituted by a sedimentation and an infiltration pond, was constructed in 2009 as the strategic water management infrastructure. Compared with other MAR facilities, this infiltration pond has a reactive bed formed by organic compost and local material. The objective is to promote different redox states allowing more and different degradation of chemical compounds than regular MAR systems. In previous studies in the site, physical and hydrochemical parameters demonstrated that there was indeed a degradation of different pollutants. However, to go a step further understanding the different biogeochemical processes and the related degradation processes occurring in the system, we studied the existing microbial communities. So, molecular techniques were applied in water and soil samples in two different scenarios; the first one, when the system was fully operating and the second when the system was not operating during some months. We have specifically compared microbial diversity and richness indexes and both cluster dendrograms obtained from DGGEs analysis made in each sampling campaign.

  7. 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.

  8. Shade shelters increase survival and photosynthetic performance of oak transplants at abandoned fields in semi-arid climates

    Institute of Scientific and Technical Information of China (English)

    Claudia González-Salvatierra; Ernesto Iván Badano; Joel Flores; Juan Pablo Rodas

    2013-01-01

    Forest restorations conducted in semiarid,seasonally dry climates must deal with the intense drought stress that affects tree seedlings during the dry season.Although this water deficit is the most commonly invoked source of mortality for seedlings,several other environmental factors may also preclude survival of transplants.For instance,it has been widely reported that excessive light reduces the efficiency of the photosynthetic apparatus,hence decreasing plant survival,but most seedling transplants in deforested areas are conducted under these light conditions.This study is focused in determining whether excessive light affects the photosynthetic performance and survival of Quercus coccolobifolia,a Mexican oak species,when their seedlings are transplanted in semiarid deforested areas.Further,this study tests the possibility of using artificial shade shelters to improve the ecophysiological performance and survival of seedlings.Oak seedlings were transplanted under full sunlight conditions and beneath artificial shade shelters of two different colors:white and black.To reduce water stress,and hence isolate the effects of light treatments,a drip irrigation system was implemented at each experimental plot.Seedling survival was monitored weekly for 128 days and photosynthetic performance was assessed by measuring chlorophyll fluorescence at three opportunities during the experiment.Sun-exposed seedlings showed lower photosynthetic performance and survival rates than those beneath shelters of both colors.These results suggest that sunlight damage can reduce seedling survival when they are transplanted in exposed sites,and that shade shelters can improve the success of forest restoration programs in semiarid climates.

  9. 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.

  10. 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.

  11. 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

  12. 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

    2016-12-09

    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.

  13. A Parallelized Pumpless Artificial Placenta System Significantly Prolonged Survival Time in a Preterm Lamb Model.

    Science.gov (United States)

    Miura, Yuichiro; Matsuda, Tadashi; Usuda, Haruo; Watanabe, Shimpei; Kitanishi, Ryuta; Saito, Masatoshi; Hanita, Takushi; Kobayashi, Yoshiyasu

    2016-05-01

    An artificial placenta (AP) is an arterio-venous extracorporeal life support system that is connected to the fetal circulation via the umbilical vasculature. Previously, we published an article describing a pumpless AP system with a small priming volume. We subsequently developed a parallelized system, hypothesizing that the reduced circuit resistance conveyed by this modification would enable healthy fetal survival time to be prolonged. We conducted experiments using a premature lamb model to test this hypothesis. As a result, the fetal survival period was significantly prolonged (60.4 ± 3.8 vs. 18.2 ± 3.2 h, P < 0.01), and circuit resistance and minimal blood lactate levels were significantly lower in the parallel circuit group, compared with our previous single circuit group. Fetal physiological parameters remained stable until the conclusion of the experiments. In summary, parallelization of the AP system was associated with reduced circuit resistance and lactate levels and allowed preterm lamb fetuses to survive for a significantly longer period when compared with previous studies.

  14. Diagnostic system for identification of accident scenarios in nuclear power plants using artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Santosh, T.V. [Health, Safety and Environment Group, Bhabha Atomic Research Centre, Trombay, Mumbai 400 085 (India)], E-mail: santutv@barc.gov.in; Srivastava, A.; Sanyasi Rao, V.V.S.; Ghosh, A.K.; Kushwaha, H.S. [Health, Safety and Environment Group, Bhabha Atomic Research Centre, Trombay, Mumbai 400 085 (India)

    2009-03-15

    This paper presents the work carried out towards developing a diagnostic system for the identification of accident scenarios in 220 MWe Indian PHWRs. The objective of this study is to develop a methodology based on artificial neural networks (ANNs), which assists in identifying a transient quickly and suggests the operator to initiate the corrective actions during abnormal operations of the reactor. An operator support system, known as symptom-based diagnostic system (SBDS), has been developed using ANN that diagnoses the transients based on reactor process parameters, and continuously displays the status of the reactor. As a pilot study, the large break loss of coolant accident (LOCA) with and without the emergency core cooling system (ECCS) in reactor headers has been considered. Several break scenarios of large break LOCA have been analyzed. The time-dependent transient data have been generated using the RELAP5 thermal hydraulic code assuming an equilibrium core, which conforms to a realistic estimation. The diagnostic results obtained from the ANN study are satisfactory. These results have been incorporated in the SBDS software for operator assistance. A few important outputs of the SBDS have been discussed in this paper.

  15. [Features of legionella biofilm formation in artificial and natural water systems].

    Science.gov (United States)

    Dronina, Iu E; Karpova, T I; Sadretdinova, O V; Didenko, L V; Tartakovskiĭ, I S

    2012-01-01

    Study the ability to form monospecies and associative biofilms as a characteristic oflegionella strains and features of organization of natural legionella biofilms in potentially dangerous water systems. Comparative evaluation ofthe ability of 28 strains of Legionella spp. to form biofilms was determined in water according to previously developed procedure. Samples from biofilm of industrial enterprise coolers and systems of hot water supply of public buildings (hotels, trade centers, hospitals) were studied. Biofilms were studied by scanning and transmission electron microscopy methods. Legionella strains are divided into 3 groups by the ability to form biofilms. L. pneumophila BLR-05 strain that has the most pronounced ability to form monospecies biofilm and persistence in association with Pseudomonas aeruginosa was detected. Formation of massive legionella biofilm in association with bacteria of other taxonomic groups was detected on protective antibacterial filters in the system of hot water supply of a department of a therapeutic prophylaxis institution in the course of 2-3 weeks. Legionella biofilms on the surface of coolers resemble an aggregate of fungi, bacteria and blue-green algae enclosed into matrix. The ability to form artificial monospecies and associative biofilm may be a useful characteristic of legionella strains for evaluation of their adhesion and be used to evaluate epidemiological significance of the isolated strains. Prevention of formation of natural legionella biofilms in potentially dangerous water systems is necessary as an essential component of modern strategy of legionellosis prophylaxis.

  16. A time delay artificial neural network approach for flow routing in a river system

    Directory of Open Access Journals (Sweden)

    M. J. Diamantopoulou

    2006-09-01

    Full Text Available River flow routing provides basic information on a wide range of problems related to the design and operation of river systems. In this paper, three layer cascade correlation Time Delay Artificial Neural Network (TDANN models have been developed to forecast the one day ahead daily flow at Ilarionas station on the Aliakmon river, in Northern Greece. The networks are time lagged feed-formatted with delayed memory processing elements at the input layer. The network topology is using multiple inputs, which include the time lagged daily flow values further up at Siatista station on the Aliakmon river and at Grevena station on the Venetikos river, which is a tributary to the Aliakmon river and a single output, which are the daily flow values at Ilarionas station. The choice of the input variables introduced to the input layer was based on the cross-correlation. The use of cross-correlation between the ith input series and the output provides a short cut to the problem of the delayed memory determination. Kalman's learning rule was used to modify the artificial neural network weights. The networks are designed by putting weights between neurons, by using the hyperbolic-tangent function for training. The number of nodes in the hidden layer was determined based on the maximum value of the correlation coefficient. The results show a good performance of the TDANN approach for forecasting the daily flow values, at Ilarionas station and demonstrate its adequacy and potential for river flow routing. The TDANN approach introduced in this study is sufficiently general and has great potential to be applicable to many hydrological and environmental applications.

  17. 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.

  18. 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

  19. Artificial Neural Networks, and Evolutionary Algorithms as a systems biology approach to a data-base on fetal growth restriction.

    Science.gov (United States)

    Street, Maria E; Buscema, Massimo; Smerieri, Arianna; Montanini, Luisa; Grossi, Enzo

    2013-12-01

    One of the specific aims of systems biology is to model and discover properties of cells, tissues and organisms functioning. A systems biology approach was undertaken to investigate possibly the entire system of intra-uterine growth we had available, to assess the variables of interest, discriminate those which were effectively related with appropriate or restricted intrauterine growth, and achieve an understanding of the systems in these two conditions. The Artificial Adaptive Systems, which include Artificial Neural Networks and Evolutionary Algorithms lead us to the first analyses. These analyses identified the importance of the biochemical variables IL-6, IGF-II and IGFBP-2 protein concentrations in placental lysates, and offered a new insight into placental markers of fetal growth within the IGF and cytokine systems, confirmed they had relationships and offered a critical assessment of studies previously performed.

  20. 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 able...

  1. Protein-matrix coupling/uncoupling in "dry" systems of photosynthetic reaction center embedded in trehalose/sucrose: the origin of trehalose peculiarity.

    Science.gov (United States)

    Francia, Francesco; Dezi, Manuela; Mallardi, Antonia; Palazzo, Gerardo; Cordone, Lorenzo; Venturoli, Giovanni

    2008-08-06

    Trehalose is a nonreducing disaccharide of glucose found in organisms, which can survive adverse conditions such as extreme drought and high temperatures. Furthermore, isolated structures, as enzymes or liposomes, embedded in trehalose are preserved against stressing conditions [see, e.g., Crowe, L. M. Comp. Biochem. Physiol. A 2002, 131, 505-513]. Among other hypotheses, such protective effect has been suggested to stem, in the case of proteins, from the formation of a water-mediated, hydrogen bond network, which anchors the protein surface to the water-sugar matrix, thus coupling the internal degrees of freedom of the biomolecule to those of the surroundings [Giuffrida, S.; et al. J. Phys. Chem. B 2003, 107, 13211-13217]. Analogous protective effect is also accomplished by other saccharides, although with a lower efficiency. Here, we studied the recombination kinetics of the primary, light-induced charge separated state (P(+)Q(A)(-)) and the thermal stability of the photosynthetic reaction center (RC) of Rhodobacter sphaeroides in trehalose-water and in sucrose-water matrixes of decreasing water content. Our data show that, in sucrose, at variance with trehalose, the system undergoes a "nanophase separation" when the water/sugar mole fraction is lower than the threshold level approximately 0.8. We rationalize this result assuming that the hydrogen bond network, which anchors the RC surface to its surrounding, is formed in trehalose but not in sucrose. We suggest that both the couplings, in the case of trehalose, and the nanophase separation, in the case of sucrose, start at low water content when the components of the system enter in competition for the residual water.

  2. 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)

  3. Fuzzy Logic, Neural Networks, Genetic Algorithms: Views of Three Artificial Intelligence Concepts Used in Modeling Scientific Systems

    Science.gov (United States)

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

    2003-01-01

    Students' conceptions of three major artificial intelligence concepts used in the modeling of systems in science, fuzzy logic, neural networks, and genetic algorithms were investigated before and after a higher education science course. Students initially explored their prior ideas related to the three concepts through active tasks. Then,…

  4. Imaging dipole flow sources using an artificial lateral-line system made of biomimetic hair flow sensors

    NARCIS (Netherlands)

    Dagamseh, Ahmad; Wiegerink, Remco; Lammerink, Theo; Krijnen, Gijs

    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 t

  5. New Artificial Immune System Approach Based on Monoclonal Principle for Job Recommendation

    Directory of Open Access Journals (Sweden)

    Shaha Al-Otaibi

    2016-04-01

    Full Text Available Finding the best solution for an optimization problem is a tedious task, specifically in the presence of enormously represented features. When we handle a problem such as job recommendations that have a diversity of their features, we should rely to metaheuristics. For example, the Artificial Immune System which is a novel computational intelligence paradigm achieving diversification and exploration of the search space as well as exploitation of the good solutions were reached in reasonable time. Unfortunately, in problems with diversity nature such job recommendation, it produces a huge number of antibodies that causes a large number of matching processes affect the system efficiency. To leverage this issue, we present a new intelligence algorithm inspired by immunology based on monoclonal antibodies production principle that, up to our knowledge, has never applied in science and engineering problems. The proposed algorithm recommends ranked list of best applicants for a certain job. We discussed the design issues, as well as the immune system processes that should be applied to the problem. Finally, the experiments are conducted that shown an excellence of our approach.

  6. 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.

  7. A multilayer perceptron solution to the match phase problem in rule-based artificial intelligence systems

    Science.gov (United States)

    Sartori, Michael A.; Passino, Kevin M.; Antsaklis, Panos J.

    1992-01-01

    In rule-based AI planning, expert, and learning systems, it is often the case that the left-hand-sides of the rules must be repeatedly compared to the contents of some 'working memory'. The traditional approach to solve such a 'match phase problem' for production systems is to use the Rete Match Algorithm. Here, a new technique using a multilayer perceptron, a particular artificial neural network model, is presented to solve the match phase problem for rule-based AI systems. A syntax for premise formulas (i.e., the left-hand-sides of the rules) is defined, and working memory is specified. From this, it is shown how to construct a multilayer perceptron that finds all of the rules which can be executed for the current situation in working memory. The complexity of the constructed multilayer perceptron is derived in terms of the maximum number of nodes and the required number of layers. A method for reducing the number of layers to at most three is also presented.

  8. Review of Artificial Immune System to Enhance Security in Mobile Ad-hoc Networks

    Directory of Open Access Journals (Sweden)

    Tarun Dalal

    2012-04-01

    Full Text Available Mobile Ad-hoc Networks consist of wireless host that communicate with each other. The routes in a Mobile Ad-hoc Network may consist of many hops through other hosts between source and destination. The hosts are not fixed in a Mobile Adhoc Network; due to host mobility topology can change any time. Mobile Ad-hoc Networks are much more vulnerable to security attacks. Current research works on securing Mobile Adhoc Networks mainly focus on confidentiality, integrity,authentication, availability, and fairness. Design of routingprotocols is very much crucial in Mobile Ad-hoc Network. There are various techniques for securing Mobile Ad-hoc Network i.e. cryptography. Cryptography provides efficient mechanism to provide security, but it creates very much overhead. So, an approach is used which is analogous to Biological Immune System, known as Artificial Immune System (AIS. There is a reason of AIS to be used for security purposes because the Human Immune System (HIS protects the body against damage from an extremely large number of harmfulbacteria, viruses, parasites and fungi, termed pathogens. It doesthis largely without prior knowledge of the structure of thesepathogens. AIS provide security by determining non-trusted nodes and eliminate all non-trusted nodes from the network.

  9. Non-Markovian Second-Order Quantum Master Equation and Its Markovian Limit: Electronic Energy Transfer in Model Photosynthetic Systems

    CERN Document Server

    Singh, Navinder

    2011-01-01

    A direct numerical algorithm for solving the time-nonlocal non-Markovian master equation in the second Born approximation is introduced and the range of utility of this approximation, and of the Markov approximation, is analyzed for the traditional dimer system that models excitation energy transfer in photosynthesis. Specifically, the coupled integro-differential equations for the reduced density matrix are solved by an efficient auxiliary function method in both the energy and site representations. In addition to giving exact results to this order, the approach allows us to computationally assess the range of the reorganization energy and decay rates of the phonon auto-correlation function for which the Markovian Redfield theory and the second order approximation is valid. For example, the use of Redfield theory for $\\lambda> 10 \\textrm{cm}^{-1}$ in systems like Fenna-Mathews-Olson (FMO) type systems is shown to be in error. In addition, analytic inequalities are obtained for the regime of validity of the M...

  10. Imaging dipole flow sources using an artificial lateral-line system made of biomimetic hair flow sensors.

    Science.gov (United States)

    Dagamseh, Ahmad; Wiegerink, Remco; Lammerink, Theo; Krijnen, Gijs

    2013-06-01

    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 take advantage of both biomimetic artificial hair-based flow sensors arranged as LSS and beamforming techniques to demonstrate dipole-source localization in air. Modelling and measurement results show the artificial lateral-line ability to image the position of dipole sources accurately with estimation error of less than 0.14 times the array length. This opens up possibilities for flow-based, near-field environment mapping that can be beneficial to, for example, biologists and robot guidance applications.

  11. 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

  12. Parameter estimation of an artificial respiratory system under mechanical ventilation following a noisy regime

    Directory of Open Access Journals (Sweden)

    Marcus Henrique Victor Júnior

    Full Text Available Abstract Introduction: This work concerns the assessment of a novel system for mechanical ventilation and a parameter estimation method in a bench test. The tested system was based on a commercial mechanical ventilator and a personal computer. A computational routine was developed do drive the mechanical ventilator and a parameter estimation method was utilized to estimate positive end-expiratory pressure, resistance and compliance of the artificial respiratory system. Methods The computational routine was responsible for establishing connections between devices and controlling them. Parameters such as tidal volume, respiratory rate and others can be set for standard and noisy ventilation regimes. Ventilation tests were performed directly varying parameters in the system. Readings from a calibrated measuring device were the basis for analysis. Adopting a first-order linear model, the parameters could be estimated and the outcomes statistically analysed. Results Data acquisition was effective in terms of sample frequency and low noise content. After filtering, cycle detection and estimation took place. Statistics of median, mean and standard deviation were calculated, showing consistent matching with adjusted values. Changes in positive end-expiratory pressure statistically imply changes in compliance, but not the opposite. Conclusion The developed system was satisfactory in terms of clinical parameters. Statistics exhibited consistent relations between adjusted and estimated values, besides precision of the measurements. The system is expected to be used in animals, with a view to better understand the benefits of noisy ventilation, by evaluating the estimated parameters and performing cross relations among blood gas, ultrasonography and electrical impedance tomography.

  13. Multiscale photosynthetic exciton transfer

    CERN Document Server

    Ringsmuth, A K; Stace, T M; 10.1038/nphys2332

    2012-01-01

    Photosynthetic light harvesting provides a natural blueprint for bioengineered and biomimetic solar energy and light detection technologies. Recent evidence suggests some individual light harvesting protein complexes (LHCs) and LHC subunits efficiently transfer excitons towards chemical reaction centers (RCs) via an interplay between excitonic quantum coherence, resonant protein vibrations, and thermal decoherence. The role of coherence in vivo is unclear however, where excitons are transferred through multi-LHC/RC aggregates over distances typically large compared with intra-LHC scales. Here we assess the possibility of long-range coherent transfer in a simple chromophore network with disordered site and transfer coupling energies. Through renormalization we find that, surprisingly, decoherence is diminished at larger scales, and long-range coherence is facilitated by chromophoric clustering. Conversely, static disorder in the site energies grows with length scale, forcing localization. Our results suggest s...

  14. [Membrane-based photochemical systems as models for photosynthetic cells]. Progress report, February 15, 1990--August 31, 1992

    Energy Technology Data Exchange (ETDEWEB)

    Hurst, J.K.

    1992-12-31

    The objectives of this research are to improve our conceptual view of the ways in which membranes and interfaces can be used to control chemical reactivity. We have focused on understanding three elementary processes that are central to developing membrane-based integrated chemical systems for water photolysis or related photoconversion/photostorage processes. Specifically, we have sought to identify: the influence of interfaces upon charge separation/recombination reactions, pathways for transmembrane charge separation across hydrocarbon bilayer membranes, and mechanisms of water oxidation catalyzed by transition metal coordination complexes. Historically, the chemical dynamics of each of these processes has been poorly understood, with numerous unresolved issues and conflicting viewpoints appearing in the literature. As described in this report our recent research has led to considerable clarification of the underlying reaction mechanisms.

  15. 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.

  16. 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.

  17. Thermal Conductivity Prediction of Soil in Complex Plant Soil System using Artificial Neural Networks

    Science.gov (United States)

    Wardani, A. K.; Purqon, A.

    2016-08-01

    Thermal conductivity is one of thermal properties of soil in seed germination and plants growth. Different soil types have different thermal conductivity. One of soft-computing promising method to predict thermal conductivity of soil types is Artificial Neural Network (ANN). In this study, we estimate the thermal conductivity of soil prediction in a soil-plant complex systems using ANN. With a feed-forward multilayer trained with back-propagation with 4, 10 and 1 on the input, hidden and output layers respectively. Our input are heating time, temperature and thermal resistance with thermal conductivity of soil as a target. ANN prediction demonstrates a good agreement with Mean Squared Error-testing (MSEte) of 9.56 x 10-7 for soils with green beans and those of bare soils is 7.00 × 10-7 respectively Green beans grow only on black-clay soil with a thermal conductivity of 0.7 W/m K with a sufficient water content. Our results demonstrate that temperature, moisture content, colour, texture and structure of soil are greatly affect to the thermal conductivity of soil in seed germination and plant growth. In future, it is potentially applied to estimate more complex compositions of plant-soil systems.

  18. The influence of an antitumor lipid - erucylphosphocholine - on artificial lipid raft system modeled as Langmuir monolayer.

    Science.gov (United States)

    Wnętrzak, Anita; Łątka, Kazimierz; Makyła-Juzak, Katarzyna; Zemla, Joanna; Dynarowicz-Łątka, Patrycja

    2015-01-01

    Outer layer of cellular membrane contains ordered domains enriched in cholesterol and sphingolipids, called 'lipid rafts', which play various biological roles, i.e., are involved in the induction of cell death by apoptosis. Recent studies have shown that these domains may constitute binding sites for selected drugs. For example alkylphosphocholines (APCs), which are new-generation antitumor agents characterized by high selectivity and broad spectrum of activity, are known to have their molecular targets located at cellular membrane and their selective accumulation in tumor cells has been hypothesized to be linked with the alternation of biophysical properties of lipid rafts. To get a deeper insight into this issue, interactions between representative APC: erucylphosphocholine, and artificial lipid raft system, modeled as Langmuir monolayer (composed of cholesterol and sphingomyelin mixed in 1:2 proportion) were investigated. The Langmuir monolayer experiments, based on recording surface pressure-area isotherms, were complemented with Brewster angle microscopy results, which enabled direct visualization of the monolayers structure. In addition, the investigated monolayers were transferred onto solid supports and studied with AFM. The interactions between model raft system and erucylphosphocholine were analyzed qualitatively (with mean molecular area values) as well as quantitatively (with ΔG(exc) function). The obtained results indicate that erucylphosphocholine introduced to raft-mimicking model membrane causes fluidizing effect and weakens the interactions between cholesterol and sphingomyelin, which results in phase separation at high surface pressures. This leads to the redistribution of cholesterol molecules in model raft, which confirms the results observed in biological studies.

  19. SINR Prediction in Mobile CDMA Systems by Linear and Nonlinear Artificial Neural-Network-Based Predictors

    Directory of Open Access Journals (Sweden)

    Nahid Ardalani

    2011-07-01

    Full Text Available This article describes linear and nonlinear Artificial Neural Network(ANN-based predictors as Autoregressive Moving Average models with Auxiliary input (ARMAX process for Signal to Interference plus Noise Ratio (SINR prediction in Direct Sequence Code Division Multiple Access (DS/CDMA systems. The Multi Layer Perceptron (MLP neural network with nonlinear function is used as nonlinear neural network and Adaptive Linear (Adaline predictor is used as linear predictor. The problem of complexity of the MLP and Adaline structures is solved by using the Minimum Mean Squared Error (MMSE principle to select the optimal numbers of input and hidden nodes by try and error role. Simulation results show that both of MLP and Adaline optimal neural networks can track the effect of deep fading due to using a 1.8 GHZ carrier frequency at the urban mobile speeds of 10 km/h, 50 km/h and 120 km/h with tolerable estimation errors. Therefore, the neural networkbased predictor is well suitable SINR-based predictor in closedloop power control to combat multi path fading in CDMA systems.

  20. 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.

  1. Artificial equilibrium points in binary asteroid systems with continuous low-thrust

    Science.gov (United States)

    Bu, Shichao; Li, Shuang; Yang, Hongwei

    2017-08-01

    The positions and dynamical characteristics of artificial equilibrium points (AEPs) in the vicinity of a binary asteroid with continuous low-thrust are studied. The restricted ellipsoid-ellipsoid model of binary system is employed for the binary asteroid system. The positions of AEPs are obtained by this model. It is found that the set of the point L1 or L2 forms a shape of an ellipsoid while the set of the point L3 forms a shape like a "banana". The effect of the continuous low-thrust on the feasible region of motion is analyzed by zero velocity curves. Because of using the low-thrust, the unreachable region can become reachable. The linearized equations of motion are derived for stability's analysis. Based on the characteristic equation of the linearized equations, the stability conditions are derived. The stable regions of AEPs are investigated by a parametric analysis. The effect of the mass ratio and ellipsoid parameters on stable region is also discussed. The results show that the influence of the mass ratio on the stable regions is more significant than the parameters of ellipsoid.

  2. Hybrid artificial neural network system for short-term load forecasting

    Directory of Open Access Journals (Sweden)

    Ilić Slobodan A.

    2012-01-01

    Full Text Available This paper presents a novel hybrid method for Short-Term Load Forecasting (STLF. The system comprises of two Artificial Neural Networks (ANN, assembled in a hierarchical order. The first ANN is a Multilayer Perceptron (MLP which functions as integrated load predictor (ILP for the forecasting day. The output of the ILP is then fed to another, more complex MLP, which acts as an hourly load predictor (HLP for a forecasting day. By using a separate ANN that predicts the integral of the load (ILP, additional information is presented to the actual forecasting ANN (HLP, while keeping its input space relatively small. This property enables online training and adaptation, as new data become available, because of the short training time. Different sizes of training sets have been tested, and the optimum of 30 day sliding time-window has been determined. The system has been verified on recorded data from Serbian electrical utility company. The results demonstrate better efficiency of the proposed method in comparison to non-hybrid methods because it produces better forecasts and yields smaller mean average percentage error (MAPE.

  3. Prediction of breeding values for dairy cattle using artificial neural networks and neuro-fuzzy systems.

    Science.gov (United States)

    Shahinfar, Saleh; Mehrabani-Yeganeh, Hassan; Lucas, Caro; Kalhor, Ahmad; Kazemian, Majid; Weigel, Kent A

    2012-01-01

    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.

  4. 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.

  5. Photosynthetic Regulation of the Cyanobacterium Synechocystis sp. PCC 6803 Thioredoxin System and Functional Analysis of TrxB (Trx x) and TrxQ (Trx y) Thioredoxins

    Institute of Scientific and Technical Information of China (English)

    M. Esther Pérez-Pérez; Eugenio Martín-Figueroa; Francisco J. Florencio

    2009-01-01

    The expression of the genes encoding the ferredoxin-thioredoxin system including the ferredoxin-thiore-doxin reductase (FTR) genes ftrC and ftrV and the four different thioredoxin genes trxA (m-type; slr0623), trxB (x-type; slr1139), trxC (sll1057) and trxQ (y-type; slr0233) of the cyanobacterium Synechocystis sp. PCC 6803 has been studied according to changes in the photosynthetic conditions. Experiments of light-dark transition indicate that the expression of all these genes except trxQ decreases in the dark in the absence of glucose in the growth medium. The use of two electron transport inhibitors, 3-(3,4-dichlorophenyl)-1,1-dimethylurea (DCMU) and 2,5-dibromo-3-methyl-6-isopropyl-p-benzoquinone (DBMIB), reveals a differential effect on thioredoxin genes expression being trxC and trxQ almost unaf-fected, whereas trxA, trxB, and the ftr genes are down-regulated. In the presence of glucose, DCMU does not affect gene expression but DBMIB still does. Analysis of the single TrxB or TrxQ and the double TrxB TrxQ Synechocystis mutant strains reveal different functions for each of these thioredoxins under different growth conditions. Finally, a Synechocystis strain was generated containing a mutated version of TrxB (TrxBC34S), which was used to identify the potential in-vivo targets of this thioredoxin by a proteomic analysis.

  6. Synthetic Antenna Functioning As Light Harvester in the Whole Visible Region for Enhanced Hybrid Photosynthetic Reaction Centers.

    Science.gov (United States)

    Hassan Omar, Omar; la Gatta, Simona; Tangorra, Rocco Roberto; Milano, Francesco; Ragni, Roberta; Operamolla, Alessandra; Argazzi, Roberto; Chiorboli, Claudio; Agostiano, Angela; Trotta, Massimo; Farinola, Gianluca M

    2016-07-20

    The photosynthetic reaction center (RC) from the Rhodobacter sphaeroides bacterium has been covalently bioconjugated with a NIR-emitting fluorophore (AE800) whose synthesis was specifically tailored to act as artificial antenna harvesting light in the entire visible region. AE800 has a broad absorption spectrum with peaks centered in the absorption gaps of the RC and its emission overlaps the most intense RC absorption bands, ensuring a consistent increase of the protein optical cross section. The covalent hybrid AE800-RC is stable and fully functional. The energy collected by the artificial antenna is transferred to the protein via FRET mechanism, and the hybrid system outperforms by a noteworthy 30% the overall photochemical activity of the native protein under the entire range of visible light. This improvement in the optical characteristic of the photoenzyme demonstrates the effectiveness of the bioconjugation approach as a suitable route to new biohybrid materials for energy conversion, photocatalysis, and biosensing.

  7. Persistence of artificial sweeteners in a 15-year-old septic system plume

    Science.gov (United States)

    Robertson, W. D.; Van Stempvoort, D. R.; Solomon, D. K.; Homewood, J.; Brown, S. J.; Spoelstra, J.; Schiff, S. L.

    2013-01-01

    SummaryGroundwater contamination from constituents such as NO3-, often occurs where multiple sources are present making source identification difficult. This study examines a suite of major ions and trace organic constituents within a well defined septic system plume in southern Ontario, Canada (Long Point site) for their potential use as wastewater tracers. The septic system has been operating for 20 years servicing a large, seasonal-use campground and tritium/helium age dating indicates that the 200 m long monitored section of the plume is about 15 years old. Four parameters are elevated along the entire length of the plume as follows; the mean electrical conductivity value (EC) in the distal plume zone is 926 μS/cm which is 74% of the mean value below the tile bed, Na+ (14.7 mg/L) is 43%, an artificial sweetener, acesulfame (12.1 μg/L) is 23% and Cl- (71.5 mg/L) is 137%. EC and Cl- appear to be affected by dispersive dilution with overlying background groundwater that has lower EC but has locally higher Cl- as result of the use of a dust suppressant (CaCl2) in the campground. Na+, in addition to advective dilution, could be depleted by weak adsorption. Acesulfame, in addition to the above processes could be influenced by increasing consumer use in recent years. Nonetheless, both Na+ and acesulfame remain elevated throughout the plume by factors of more than 100 and 1000 respectively compared to background levels, and are strong indicators of wastewater impact at this site. EC and Cl- are less useful because their contrast with background values is much less (EC) or because other sources are present (Cl-). Nutrients (NO3-, NH4+, PO43-, K+) and pathogens (Escherichia coli) do not persist in the distal plume zone and are less useful as wastewater indicators here. The artificial sweetener, acesulfame, has persisted at high concentrations in the Long Point plume for at least 15 years (and this timing agrees with tritium/helium-3 dating) and this compound likely

  8. Testing Earth System Model Assumptions of Photosynthetic Parameters with in situ Leaf Measurements from a Temperate Zone Forest.

    Science.gov (United States)

    Cheng, S. J.; Thomas, R. Q.; Wilkening, J. V.; Curtis, P.; Sharkey, T. D.; Nadelhoffer, K. J.

    2015-12-01

    Estimates of global land CO2 uptake vary widely across Earth system models. This uncertainty around model estimates of land-atmosphere CO2 fluxes may result from differences in how models parameterize and scale photosynthesis from the leaf-to-global level. To test model assumptions about photosynthesis, we derive rates of maximum carboxylation (Vc,max), electron transport (J), and triose phosphate utilization (TPU) from in situ leaf measurements from a forest representative of the Great Lakes region. Leaf-level gas exchange measurements were collected across a temperature range from sun and shade leaves of canopy-dominant tree species typically grouped into the same plant functional type. We evaluate the influence of short-term increases in leaf temperature, nitrogen per leaf area (Narea), species, and leaf light environment on Vc,max, J, and TPU by testing contrasting model equations that isolate the influence of these factors on these rate-limiting steps in leaf photosynthesis. Results indicate that patterns in Vc,max are best explained by a model that includes temperature and Narea. However, J varied with species and leaf light environment in addition to temperature. TPU also varied with leaf light environment and possibly with temperature. These variations in J and TPU with species or between sun and shade leaves suggest that plant traits outside of Narea are needed to explain patterns in J and TPU. This study provides in situ evidence on how Vc,max, J, and TPU vary within a forest canopy and highlight how leaf responses to changes in climate, forest species composition, and canopy structure may alter forest CO2 uptake.

  9. Laboratory Simulation of an Iron(II)-rich Precambrian Marine Upwelling System to Explore the Growth of Photosynthetic Bacteria.

    Science.gov (United States)

    Maisch, Markus; Wu, Wenfang; Kappler, Andreas; Swanner, Elizabeth D

    2016-07-24

    A conventional concept for the deposition of some Precambrian Banded Iron Formations (BIF) proceeds on the assumption that ferrous iron [Fe(II)] upwelling from hydrothermal sources in the Precambrian ocean was oxidized by molecular oxygen [O2] produced by cyanobacteria. The oldest BIFs, deposited prior to the Great Oxidation Event (GOE) at about 2.4 billion years (Gy) ago, could have formed by direct oxidation of Fe(II) by anoxygenic photoferrotrophs under anoxic conditions. As a method for testing the geochemical and mineralogical patterns that develop under different biological scenarios, we designed a 40 cm long vertical flow-through column to simulate an anoxic Fe(II)-rich marine upwelling system representative of an ancient ocean on a lab scale. The cylinder was packed with a porous glass bead matrix to stabilize the geochemical gradients, and liquid samples for iron quantification could be taken throughout the water column. Dissolved oxygen was detected non-invasively via optodes from the outside. Results from biotic experiments that involved upwelling fluxes of Fe(II) from the bottom, a distinct light gradient from top, and cyanobacteria present in the water column, show clear evidence for the formation of Fe(III) mineral precipitates and development of a chemocline between Fe(II) and O2. This column allows us to test hypotheses for the formation of the BIFs by culturing cyanobacteria (and in the future photoferrotrophs) under simulated marine Precambrian conditions. Furthermore we hypothesize that our column concept allows for the simulation of various chemical and physical environments - including shallow marine or lacustrine sediments.

  10. 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.

  11. 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.

  12. Rapid transfer of photosynthetic carbon through the plant-soil system in differently managed species-rich grasslands

    Directory of Open Access Journals (Sweden)

    G. B. De Deyn

    2011-05-01

    in the plant-soil system. Moreover, across all treatments we found that plant-derived C is rapidly transferred specifically to AMF and decomposer fungi, indicating their consistent key role in the cycling of recent plant derived C.

  13. 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

  14. An Arabic Text-To-Speech System Based on Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Ghadeer Al-Said

    2009-01-01

    Full Text Available Problem statement: With the rapid advancement in information technology and communications, computer systems increasingly offer the users the opportunity to interact with information through speech. The interest in speech synthesis and in building voices is increasing. Worldwide, speech synthesizers have been developed for many popular languages English, Spanish and French and many researches and developments have been applied to those languages. Arabic on the other hand, has been given little attention compared to other languages of similar importance and the research in Arabic is still in its infancy. Based on these ideas, we introduced a system to transform Arabic text that was retrieved from a search engine into spoken words. Approach: We designed a text-to-speech system in which we used concatenative speech synthesis approach to synthesize Arabic text. The synthesizer was based on artificial neural networks, specifically the unsupervised learning paradigm. Different sizes of speech units had been used to produce spoken utterances, which are words, diphones and triphones. We also built a dictionary of 500 common words of Arabic. The smaller speech units (diphones and triphones used for synthesis were chosen to achieve unlimited vocabulary of speech, while the word units were used for synthesizing limited set of sentences. Results: The system showed very high accuracy in synthesizing the Arabic text and the output speech was highly intelligible. For the word and diphone unit experiments, we could reach an accuracy of 99% while for the triphone units we reached an accuracy of 86.5%. Conclusion: An Arabic text-to-speech synthesizer was built with the ability to produce unlimited number of words with high quality voice.

  15. Performance evaluation of a reverse-gradient artificial recharge system in basalt aquifers of Maharashtra, India

    Science.gov (United States)

    Bhusari, Vijay; Katpatal, Y. B.; Kundal, Pradeep

    2016-12-01

    Drinking water scarcity in rural parts of central India in basaltic terrain is common. Most of the rural population depends on groundwater sources located in the fractured and weathered zone of the basaltic aquifers. Long-term indiscriminate withdrawal has caused an alarming rate of depletion of groundwater levels in both pre- and post-monsoon periods. The aquifer is not replenished through precipitation under natural conditions. To overcome this situation, an innovative artificial recharge system, called the reverse-gradient recharge system (RGRS), was implemented in seven villages of Wardha district of Maharashtra. The study described here presents a comparative analysis of recharge systems constructed in the year 2012 downstream of dug-well locations in these seven villages. The post-project comparative analysis reveals that the area of influence (AOI) of the groundwater recharge system, within which increases in groundwater levels and yield are observed, is directly related to the specific yield, thickness of the weathered and fractured zone, porosity, and transmissivity of the aquifer, showing high correlation coefficients of 0.92, 0.88, 0.85 and 0.83, respectively. The study indicates that the RGRS is most effective in vesicular weathered and fractured basalt, recording a maximum increase in well yield of 65-82 m3/day, while a minimum increase in yield of 15-30 m3/day was observed in weathered vesicular basalt. The comparative analysis thus identifies the controlling factors which facilitate groundwater recharge through the proposed RGRS. After implementation of these projects, the groundwater availability in these villages increased significantly, solving their drinking water problems.

  16. Performance evaluation of a reverse-gradient artificial recharge system in basalt aquifers of Maharashtra, India

    Science.gov (United States)

    Bhusari, Vijay; Katpatal, Y. B.; Kundal, Pradeep

    2017-05-01

    Drinking water scarcity in rural parts of central India in basaltic terrain is common. Most of the rural population depends on groundwater sources located in the fractured and weathered zone of the basaltic aquifers. Long-term indiscriminate withdrawal has caused an alarming rate of depletion of groundwater levels in both pre- and post-monsoon periods. The aquifer is not replenished through precipitation under natural conditions. To overcome this situation, an innovative artificial recharge system, called the reverse-gradient recharge system (RGRS), was implemented in seven villages of Wardha district of Maharashtra. The study described here presents a comparative analysis of recharge systems constructed in the year 2012 downstream of dug-well locations in these seven villages. The post-project comparative analysis reveals that the area of influence (AOI) of the groundwater recharge system, within which increases in groundwater levels and yield are observed, is directly related to the specific yield, thickness of the weathered and fractured zone, porosity, and transmissivity of the aquifer, showing high correlation coefficients of 0.92, 0.88, 0.85 and 0.83, respectively. The study indicates that the RGRS is most effective in vesicular weathered and fractured basalt, recording a maximum increase in well yield of 65-82 m3/day, while a minimum increase in yield of 15-30 m3/day was observed in weathered vesicular basalt. The comparative analysis thus identifies the controlling factors which facilitate groundwater recharge through the proposed RGRS. After implementation of these projects, the groundwater availability in these villages increased significantly, solving their drinking water problems.

  17. 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.

  18. Artificial Gravity

    CERN Document Server

    Clément, Gilles

    2007-01-01

    Protecting the health, safety, and performance of exploration-class mission crews against the physiological deconditioning resulting from long-term weightlessness during transit and long-term reduced gravity during surface operations will require effective, multi-system countermeasures. Artificial gravity, which would replace terrestrial gravity with inertial forces generated by rotating the transit vehicle or by short-radius human centrifuge devices within the transit vehicle or surface habitat, has long been considered a potential solution. However, despite its attractiveness as an efficient

  19. 人工肝支持系统的临床应用%The clinical application of artificial liver support system

    Institute of Scientific and Technical Information of China (English)

    陈煜; 李爽

    2016-01-01

    ABSTRACT:The main treatment strategies for liver failure include drug therapy,artificial liver support system and liver transplantation etc. At present, non biological artificial liver, including plasma exchange, plasma diafiltration,hemoperfusiuon,molecular adsorbent recirculating system(MARS)and Prometheus are commonly used in clinical treatment,and the therapeutic effect is discussed.In addition,the progress of bioartificial liver in recent years,and the construction of a new artificial liver are summarized.The problems and new trends of artificial liver are also summarized.%肝衰竭治疗主要包括内科药物治疗、人工肝治疗以及肝移植等手段。本文将介绍目前临床常用的非生物型人工肝,包括血浆置换、血浆滤过透析、血液灌流、分子吸附再循环系统以及 Prometheus 系统等,并对其疗效进行重点讨论。此外,还概括了近年来生物型人工肝的进展,以及新型人工肝脏的构建。归纳了未来人工肝发展待解决的问题以及新趋势。

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

    OpenAIRE

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

    2014-01-01

    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...

  1. The right touch: design of artificial antigen-presenting cells to stimulate the immune system

    NARCIS (Netherlands)

    Weijden, J. van der; Paulis, L.E.M.; Verdoes, M.; Hest, J.C. van; Figdor, C.G.

    2014-01-01

    With the ever expanding possibilities to build supramotecutar structures, chemists are challenged to mimic nature including the construction of artificial cells or function thereof. Within the field of immunology, effective immunotherapy critically depends on efficient production of antigen-specific

  2. The artificial leaf.

    Science.gov (United States)

    Nocera, Daniel G

    2012-05-15

    To convert the energy of sunlight into chemical energy, the leaf splits water via the photosynthetic process to produce molecular oxygen and hydrogen, which is in a form of separated protons and electrons. The primary steps of natural photosynthesis involve the absorption of sunlight and its conversion into spatially separated electron-hole pairs. The holes of this wireless current are captured by the oxygen evolving complex (OEC) of photosystem II (PSII) to oxidize water to oxygen. The electrons and protons produced as a byproduct of the OEC reaction are captured by ferrodoxin of photosystem I. With the aid of ferrodoxin-NADP(+) reductase, they are used to produce hydrogen in the form of NADPH. For a synthetic material to realize the solar energy conversion function of the leaf, the light-absorbing material must capture a solar photon to generate a wireless current that is harnessed by catalysts, which drive the four electron/hole fuel-forming water-splitting reaction under benign conditions and under 1 sun (100 mW/cm(2)) illumination. This Account describes the construction of an artificial leaf comprising earth-abundant elements by interfacing a triple junction, amorphous silicon photovoltaic with hydrogen- and oxygen-evolving catalysts made from a ternary alloy (NiMoZn) and a cobalt-phosphate cluster (Co-OEC), respectively. The latter captures the structural and functional attributes of the PSII-OEC. Similar to the PSII-OEC, the Co-OEC self-assembles upon oxidation of an earth-abundant metal ion from 2+ to 3+, may operate in natural water at room temperature, and is self-healing. The Co-OEC also activates H(2)O by a proton-coupled electron transfer mechanism in which the Co-OEC is increased by four hole equivalents akin to the S-state pumping of the Kok cycle of PSII. X-ray absorption spectroscopy studies have established that the Co-OEC is a structural relative of Mn(3)CaO(4)-Mn cubane of the PSII-OEC, where Co replaces Mn and the cubane is extended in a

  3. Artificial Gravity as a Multi-System Countermeasure to Bed Rest Deconditioning: Pilot Study Overview

    Science.gov (United States)

    Paloski, William H.; Young, L. R.

    2007-01-01

    Efficient, effective, multi-system countermeasures will likely be required to protect the health, safety, and performance of crews aboard planned exploration-class space flight missions to Mars and beyond. To that end, NASA, DLR, and IMBP initiated a multi-center international project to begin systematically exploring the utility of artificial gravity (AG) as a multi-system countermeasure in ground based venues using test subjects deconditioned by bed rest. The goal of this project is to explore the efficacy of short-radius, intermittent AG as a countermeasure to bone, muscle, cardiovascular, and sensory-motor adaptations to hypogravity. This session reports the results from a pilot study commissioned to validate a standardized protocol to be used by all centers involved in the project. Subject selection criteria, medical monitoring requirements, medical care procedures, experiment control procedures, and standardized dependent measures were established jointly. Testing was performed on 15 rigorously screened male volunteers subjected to 21 days of 6deg HDT bed rest. (All provided written consent to volunteer after the nature of the study and its hazards were clearly explained to them.) Eight were treated with daily 1hr AG exposures (2.5g at the feet decreasing to 1.0g at the heart) aboard a short radius (3m) centrifuge, while the other seven served as controls. Multiple tests of multiple dependent measures were made in each of the primary physiological systems of interest during a 10 day acclimatization period prior to HDT bed rest and again during an 8 day recovery period after the bed rest period was complete. Analyses of these data (presented in other papers in this session) suggest the AG prescription had salutary effects on aspects of the bone, muscle, and cardiovascular systems, with no untoward effects on the vestibular system, the immune system, or cognitive function. Furthermore, treatment subjects were able to tolerate 153/160 centrifuge sessions over

  4. Development of a reflected optical fiber system for measuring oxygen saturation in an integrated artificial heart-lung system.

    Science.gov (United States)

    Yasuda, Toshitaka; Saito, Tomohiko; Kihara, Tatsuya; Takatani, Setsuo; Funakubo, Akio

    2008-03-01

    The purpose of this study was to develop a blood oxygen saturation (OS) monitoring system for use with an integrated artificial heart-lung system (IAHLS). The OS monitoring system consists of two paired optical fiber probes (OFPs) and a measurement system. To investigate the effect of the OFP configuration and incident light wavelength on the relationship between OS and the reflectance ratio for wavelengths of 810 and 645 nm, we performed theoretical analyses of the relationship between OS and R810/R645 using a diffusion equation. The prototype OFP located on the blood outlet port of our IAHLS housing was evaluated using an in vitro test. An OS range of 65-100% was adjusted to supply oxygen and nitrogen gas to the IAHLS. The blood flow rate was maintained at 3 L/min by the rotational speed of an impeller in the IAHLS. The OS-corrected blood from the IAHLS was measured using a commercial gas analyzer. The correlation coefficients (r(2)) between the theoretical ratio of R810/R645 and OS, and between measured OS and the reflectance ratio of R810/R645 were 0.97 and 0.78, respectively. In conclusion, we confirmed that the development of this oximetry system is applicable for IAHLS.

  5. 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.

  6. 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.

  7. 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.

  8. Photoactive Nanomaterials Inspired by Nature: LTL Zeolite Doped with Laser Dyes as Artificial Light Harvesting Systems

    Directory of Open Access Journals (Sweden)

    Leire Gartzia-Rivero

    2017-05-01

    Full Text Available The herein reported work describes the development of hierarchically-organized fluorescent nanomaterials inspired by plant antenna systems. These hybrid materials are based on nanostructured zeolitic materials (LTL zeolite doped with laser dyes, which implies a synergism between organic and inorganic moieties. The non-interconnected channeled structure and pore dimensions (7.1 Å of the inorganic host are ideal to order and align the allocated fluorophores inside, inferring also high thermal and chemical stability. These artificial antennae harvest a broad range of chromatic radiation and convert it into predominant red-edge or alternatively white-light emission, just choosing the right dye combination and concentration ratio to modulate the efficiency of the ongoing energy transfer hops. A further degree of organization can be achieved by functionalizing the channel entrances of LTL zeolite with specific tailor-made (stopcock molecules via a covalent linkage. These molecules plug the channels to avoid the leakage of the guest molecules absorbed inside, as well as connect the inner space of the zeolite with the outside thanks to energy transfer processes, making the coupling of the material with external devices easier.

  9. Polarimetric synthetic aperture radar image unsupervised classification method based on artificial immune system

    Science.gov (United States)

    Jie, Yu; Gang, Wang; Teng, Zhu; Xiaojuan, Li; Qin, Yan

    2014-01-01

    An unsupervised classification method based on the H/α classifier and artificial immune system (AIS) is proposed to overcome the inefficiencies that arise when traditional classification methods deal with polarimetric synthetic aperture radar (PolSAR) data having large numbers of overlapping pixels and excess polarimetric information. The method is composed of two steps. First, Cloude-Pottier decomposition is used to obtain the entropy H and the scattering angle α. The classification result based on the H/α plane is used to initialize the AIS algorithm. Second, to obtain accurate results, the AIS clonal selection algorithm is used to perform an iterative calculation. As a self-organizing, self-recognizing, and self-optimizing algorithm, the AIS is able to obtain a global optimal solution and better classification results by making use of both the scattering mechanism of ground features and polarimetric scattering characteristics. The effectiveness and feasibility of this method are demonstrated by experiments using a NASA-JPL PolSAR image and a high-resolution PolSAR image of Lingshui autonomous county in Hainan Province.

  10. 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.

  11. Evolution of Collective Behaviour in an Artificial World Using Linguistic Fuzzy Rule-Based Systems.

    Science.gov (United States)

    Demšar, Jure; Lebar Bajec, Iztok

    2017-01-01

    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.

  12. Prediction of subsidence risk by FMEA using artificial neural network and fuzzy inference system

    Institute of Scientific and Technical Information of China (English)

    Rafie Meraj; Samimi Namin Farhad

    2015-01-01

    Construction of metro tunnels in dense and crowded urban areas is faced with many risks, such as sub-sidence. The purpose of this paper was the prediction of subsidence risk by failure mode and effect anal-ysis (FMEA) and fuzzy inference system (FIS). Fuzzy theory will be able to model uncertainties. Fuzzy FMEA provides a tool that can work in a better way with vague concepts and without sufficient informa-tion than conventional FMEA. In this paper, S and D are obtained from fuzzy rules and O is obtained from artificial neural network (ANN). FMEA is performed by developing a fuzzy risk priority number (FRPN). The FRPN for two stations in Tehran No.4 subway line is 3.1 and 5.5, respectively. To investigate the suit-ability of this approach, the predictions by FMEA have been compared with actual data. The results show that this method can be useful in the prediction of subsidence risk in urban tunnels.

  13. Impacts of artificial ocean alkalinization on the carbon cycle and climate in Earth system simulations

    Science.gov (United States)

    González, Miriam Ferrer; Ilyina, Tatiana

    2016-06-01

    Using the state-of-the-art emissions-driven Max Planck Institute Earth system model, we explore the impacts of artificial ocean alkalinization (AOA) with a scenario based on the Representative Concentration Pathway (RCP) framework. Addition of 114 Pmol of alkalinity to the surface ocean stabilizes atmospheric CO2 concentration to RCP4.5 levels under RCP8.5 emissions. This scenario removes 940 GtC from the atmosphere and mitigates 1.5 K of global warming within this century. The climate adjusts to the lower CO2 concentration preventing the loss of sea ice and high sea level rise. Seawater pH and the carbonate saturation state (Ω) rise substantially above levels of the current decade. Pronounced differences in regional sensitivities to AOA are projected, with the Arctic Ocean and tropical oceans emerging as hot spots for biogeochemical changes induced by AOA. Thus, the CO2 mitigation potential of AOA comes at a price of an unprecedented ocean biogeochemistry perturbation with unknown ecological consequences.

  14. A Robust Damage Detection Method Developed for Offshore Jacket Platforms Using Modified Artificial Immune System Algorithm

    Institute of Scientific and Technical Information of China (English)

    Mojtahedi,A.; Lotfollahi Yaghin,M.A.; Hassanzadeh,Y.; Abbasidoust,F.; Ettefagh,M.M.; Aminfar,M.H.

    2012-01-01

    Steel jacket-type platforms are the common kind of the offshore structures and health monitoring is an important issue in their safety assessment.In the present study,a new damage detection method is adopted for this kind of structures and inspected experimentally by use of a laboratory model.The method is investigated for developing the robust damage detection technique which is less sensitive to both measurement and analytical model uncertainties.For this purpose,incorporation of the artificial immune system with weighted attributes (AISWA) method into finite element (FE) model updating is proposed and compared with other methods for exploring its effectiveness in damage identification.Based on mimicking immune recognition,noise simulation and attributes weighting,the method offers important advantages and has high success rates.Therefore,it is proposed as a suitable method for the detection of the failures in the large civil engineering structures with complicated structural geometry,such as the considered case study.

  15. Fifteen years of experience with Integral-Leg-Prosthesis: Cohort study of artificial limb attachment system.

    Science.gov (United States)

    Juhnke, Dora-Lisa; Beck, James P; Jeyapalina, Sujee; Aschoff, Horst H

    2015-01-01

    Integral-Leg-Prosthesis (ILP) is a comparatively new attachment system that allows direct skeletal docking of artificial limbs. Between January 1999 and December 2013, 69 patients with transfemoral amputation were fitted with ILPs by a single German surgeon. Device design iterations and surgical techniques evolved during these years. For the purposes of comparison, patients receiving the first two designs and procedure iterations were placed in group 1 and the patients fitted with the final design were placed in group 2. Infection rate and planned and unplanned surgical interventions were statistically compared using Fisher exact test. Data demonstrated that the high rate of stoma-associated infections seen in group 1 was dramatically reduced in group 2. Of the 39 patients with 42 implants in group 2, none had operative interventions secondary to infection. All group 2 patients remained infection-free without the use of antibiotics by following a simple but defined wound-hygiene protocol. We concluded that the final iteration of the osseointegrated intramedullary device with a low energy surface at the soft tissue and prosthesis interface allowed a biologically stable skin stoma that remained infection-free without chronic use of antibiotics. The reduction in the infection rate was attributed to the clinically based, empirically driven changes in design and surgical techniques.

  16. Fifteen years of experience with Integral-Leg-Prosthesis: Cohort study of artificial limb attachment system

    Directory of Open Access Journals (Sweden)

    Dora-Lisa Juhnke, MD

    2015-08-01

    Full Text Available Integral-Leg-Prosthesis (ILP is a comparatively new attachment system that allows direct skeletal docking of artificial limbs. Between January 1999 and December 2013, 69 patients with transfemoral amputation were fitted with ILPs by a single German surgeon. Device design iterations and surgical techniques evolved during these years. For the purposes of comparison, patients receiving the first two designs and procedure iterations were placed in group 1 and the patients fitted with the final design were placed in group 2. Infection rate and planned and unplanned surgical interventions were statistically compared using Fisher exact test. Data demonstrated that the high rate of stoma-associated infections seen in group 1 was dramatically reduced in group 2. Of the 39 patients with 42 implants in group 2, none had operative interventions secondary to infection. All group 2 patients remained infection-free without the use of antibiotics by following a simple but defined wound-hygiene protocol. We concluded that the final iteration of the osseointegrated intramedullary device with a low energy surface at the soft tissue and prosthesis interface allowed a biologically stable skin stoma that remained infection-free without chronic use of antibiotics. The reduction in the infection rate was attributed to the clinically based, empirically driven changes in design and surgical techniques.

  17. 紧凑型人造草皮系统%Compact artificial turf system

    Institute of Scientific and Technical Information of China (English)

    S. Beyer; J. Weinhold; 陈月君(译); 王依民(校)

    2012-01-01

    为了能使用少量的线性低密度聚乙烯、高密度聚乙烯和聚丙烯纱线高效地制造人造草皮,位于德国Chemnitz的Oerlikon Barmag公司发明了一种紧凑型生产线,其可提供180kg/h的产能,为普通系统正常生产能力的一半,投资成本也仅为大型生产线的50%%To be able to efficqeutly manufacture artificial turf made from LLDPE, HDPE and polypropylene yarns in small quantities, Oerlikon Barmag, Chemnitz;ernmny, has developed a onpat line, whih offers with anoulpul of 180 kg/h - around half of the normal capacity of a standard system - all at just 50% of file investment costs of a large-scale production lille.

  18. 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.

  19. Artificially Augmented Training for Anomaly-based Network Intrusion Detection Systems

    Directory of Open Access Journals (Sweden)

    Chockalingam Karuppanchetty

    2015-09-01

    Full Text Available Attacks on web servers are becoming increasingly prevalent; the resulting social and economic impact of successful attacks is also exacerbated by our dependency on web-based applications. There are many existing attack detection and prevention schemes, which must be carefully configured to ensure their efficacy. In this paper, we present a study challenges that arise in training network payload anomaly detection schemes that utilize collected network traffic for tuning and configuration. The advantage of anomaly-based intrusion detection is in its potential for detecting zero day attacks. These types of schemes, however, require extensive training to properly model the normal characteristics of the system being protected. Usually, training is done through the use of real data collected by monitoring the activity of the system. In practice, network operators or administrators may run into cases where they have limited availability of such data. This issue can arise due to the system being newly deployed (or heavily modified or due to the content or behavior that leads to normal characterization having been changed. We show that artificially generated packet payloads can be used to effectively augment the training and tuning. We evaluate the method using real network traffic collected at a server site; We illustrate the problem at first (use of highly variable and unsuitable training data resulting in high false positives of 3.6∼10%, then show improvements using the augmented training method (false positives as low as 0.2%. We also measure the impact on network performance, and present a lookup based optimization that can be used to improve latency and throughput.

  20. 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