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Sample records for classified removable electronic

  1. Sixty Percent Conceptual Design Report: Enterprise Accountability System for Classified Removable Electronic Media

    Energy Technology Data Exchange (ETDEWEB)

    B. Gardiner; L.Graton; J.Longo; T.Marks, Jr.; B.Martinez; R. Strittmatter; C.Woods; J. Joshua

    2003-05-03

    Classified removable electronic media (CREM) are tracked in several different ways at the Laboratory. To ensure greater security for CREM, we are creating a single, Laboratory-wide system to track CREM. We are researching technology that can be used to electronically tag and detect CREM, designing a database to track the movement of CREM, and planning to test the system at several locations around the Laboratory. We focus on affixing ''smart tags'' to items we want to track and installing gates at pedestrian portals to detect the entry or exit of tagged items. By means of an enterprise database, the system will track the entry and exit of tagged items into and from CREM storage vaults, vault-type rooms, access corridors, or boundaries of secure areas, as well as the identity of the person carrying an item. We are considering several options for tracking items that can give greater security, but at greater expense.

  2. Multiple-electron removal and molecular fragmentation of CO by fast F4+ impact

    International Nuclear Information System (INIS)

    Ben-Itzhak, I.; Ginther, S.G.; Carnes, K.D.

    1993-01-01

    Multiple-electron removal from and molecular fragmentation of carbon monoxide molecules caused by collisions with 1-MeV/amu F 4+ ions were studied using the coincidence time-of-flight technique. In these collisions, multiple-electron removal of the target molecule is a dominant process. Cross sections for the different levels of ionization of the CO molecule during the collision were determined. The relative cross sections of ionization decrease with increasing number of electrons removed in a similar way as seen in atomic targets. This behavior is in agreement with a two-step mechanism, where first the molecule is ionized by a Franck-Condon ionization and then the molecular ion dissociates. Most of the highly charged intermediate states of the molecule dissociate rapidly. Only CO + and CO 2+ molecular ions have been seen to survive long enough to be detected as molecular ions. The relative cross sections for the different breakup channels were evaluated for collisions in which the molecule broke into two charged fragments as well as for collisions where only a single charged molecular ion or fragment were produced. The average charge state of each fragment resulting from CO Q+ →C i+ +O j+ breakup increases with the number of electrons removed from the molecule approximately following the relationship bar i=bar j=Q/2 as long as K-shell electrons are not removed. This does not mean that the charge-state distribution is exactly symmetric, as, in general, removing electrons from the carbon fragment is slightly more likely than removing electrons from the oxygen due to the difference in binding energy. The cross sections for molecular breakup into a charged fragment and a neutral fragment drop rapidly with an increasing number of electrons removed

  3. Removing Contamination-Induced Reconstruction Artifacts from Cryo-electron Tomograms

    Science.gov (United States)

    Fernandez, Jose-Jesus; Laugks, Ulrike; Schaffer, Miroslava; Bäuerlein, Felix J.B.; Khoshouei, Maryam; Baumeister, Wolfgang; Lucic, Vladan

    2016-01-01

    Imaging of fully hydrated, vitrified biological samples by electron tomography yields structural information about cellular protein complexes in situ. Here we present a computational procedure that removes artifacts of three-dimensional reconstruction caused by contamination present in samples during imaging by electron microscopy. Applying the procedure to phantom data and electron tomograms of cellular samples significantly improved the resolution and the interpretability of tomograms. Artifacts caused by surface contamination associated with thinning by focused ion beam, as well as those arising from gold fiducial markers and from common, lower contrast contamination, could be removed. Our procedure is widely applicable and is especially suited for applications that strive to reach a higher resolution and involve the use of recently developed, state-of-the-art instrumentation. PMID:26743046

  4. Evaluation of secondary electron filter for removing contaminant electrons from high-energy 6 MV x-ray beam

    International Nuclear Information System (INIS)

    Kumagai, Kozo

    1988-01-01

    When using high energy X-rays, the dose increases at the skin surface and build-up region of beam contamination of secondary electrons coming out from the inner surface of the lineac head. At our radiotherapy department, many cases of external otitis from severe skin reactions, particularly resulting from whole brain irradiation of primary and metastatic brain tumors with a 6 MV X-ray lineac, have been encountered. An investigation was made of the physical aspects of a 6 MV X-ray beam using three electron filters, lead lucite, lead glass and lucite to remove secondary electrons. Transparent materials for filters should be preferable for locating the light field. The following results were obtained: 1) For removing secondary electrons, a lead lucite filter was found best. 2) The lead lucite filter proved most effective for removing secondary electrons from the area of treatment. It reduced the dose of irradiation to the skin surface and build-up region, and furthermore improved the depth dose relative to that without filters. 3) From a clinical standpoint, skin reactions such as external otitis remarkably decreased using a lead lucite filter. 4) It thus appears necessary to use a high energy X-ray with newly designed filters to reduce beam contamination of secondary electrons. (author)

  5. Studies of toxic metals removal in industrial wastewater after electron-beam treatment

    International Nuclear Information System (INIS)

    Ribeiro, Marcia Almeida

    2002-01-01

    The Advanced Oxidation Process, using electron-beam, have been studied by scientific community due to its capacity to mineralize the toxic organic compound from highly reactive radical's formation. The electron-beam treatment process has been adopted by several countries for organic compounds removal and to effluents and sewers biological degradation. In this work, studies of metals removal in the simulated aqueous solutions and in the actual industrial effluents were carried out, using electron-beam treatment. The effluents samples were collected at ETE/SABESP (Governmental Wastewater Treatment Plant) in Suzano, SP city. The sampling was outlined at three distinctive sites: Industrial Receiver Unit, Medium Bar, and Final Effluent. The effluents samples were irradiated using different irradiation doses (20, 50, 100, 200 and 500 kGy). The removal behavior of metals Ca, CI, S, P, K, Al, Fe, As, Ni, Cr, Zn, Si, Co, Mn, As, Se, Cd, Hg and Pb was verified. The elements determination was accomplished with the x-ray fluorescence (WD-XRFS) technique using Fundamental Parameters method and thin film samples. The elements Fe, Zn, Cr and Co presented a removal > 99% to 200 kGy of irradiation dose in industrial effluent. At the same dose, P, Al and Si presented a removal of 81.8%, 97.6% and 98.7%, respectively. Ca and S were removed more than 80% at 20 kGy and Na, CI and K did not presented any degree of removal. As, Se, Cd, Hg and Pb removal was studied in the simulated aqueous solutions and industrial effluents with scavengers addition (EDTA and HCOONa). The elements As and Hg presented a removal of 92% and 99%, respectively, with HCOONa, at 500 kGy irradiation dose. The Se presented a 96.5% removal at same irradiation dose without scavengers addition. The removal of Cd and Pb did not give a significant removal, once all of the assay were carried out in the oxidant medium. (author)

  6. High-Energy Electron Beam Application to Air Pollutants Removal

    International Nuclear Information System (INIS)

    Ighigeanu, D.; Martin, D.; Manaila, E.; Craciun, G.; Calinescu, I.

    2009-01-01

    The advantage of electron beam (EB) process in pollutants removal is connected to its high efficiency to transfer high amount of energy directly into the matter under treatment. Disadvantage which is mostly related to high investment cost of accelerator may be effectively overcome in future as the result of use accelerator new developments. The potential use of medium to high-energy high power EB accelerators for air pollutants removal is demonstrated in [1]. The lower electrical efficiencies of accelerators with higher energies are partially compensated by the lower electron energy losses in the beam windows. In addition, accelerators with higher electron energies can provide higher beam powers with lower beam currents [1]. The total EB energy losses (backscattering, windows and in the intervening air space) are substantially lower with higher EB incident energy. The useful EB energy is under 50% for 0.5 MeV and about 95% above 3 MeV. In view of these arguments we decided to study the application of high energy EB for air pollutants removal. Two electron beam accelerators are available for our studies: electron linear accelerators ALIN-10 and ALID-7, built in the Electron Accelerator Laboratory, INFLPR, Bucharest, Romania. Both accelerators are of traveling-wave type, operating at a wavelength of 10 cm. They utilize tunable S-band magnetrons, EEV M 5125 type, delivering 2 MW of power in 4 μ pulses. The accelerating structure is a disk-loaded tube operating in the 2 mode. The optimum values of the EB peak current IEB and EB energy EEB to produce maximum output power PEB for a fixed pulse duration EB and repetition frequency fEB are as follows: for ALIN-10: EEB = 6.23 MeV; IEB =75 mA; PEB 164 W (fEB = 100 Hz, EB = 3.5 s) and for ALID-7: EEB 5.5 MeV; IEB = 130 mA; PEB = 670 W (fEB = 250 Hz, EB = 3.75 s). This paper presents a special designed installation, named SDI-1, and several representative results obtained by high energy EB application to SO 2 , NOx and VOCs

  7. Removal of Vesicle Structures from Transmission Electron Microscope Images

    DEFF Research Database (Denmark)

    Jensen, Katrine Hommelhoff; Sigworth, Fred; Brandt, Sami Sebastian

    2015-01-01

    In this paper, we address the problem of imaging membrane proteins for single-particle cryo-electron microscopy reconstruction of the isolated protein structure. More precisely, we propose a method for learning and removing the interfering vesicle signals from the micrograph, prior to reconstruct...

  8. Electronic nose with a new feature reduction method and a multi-linear classifier for Chinese liquor classification

    Energy Technology Data Exchange (ETDEWEB)

    Jing, Yaqi; Meng, Qinghao, E-mail: qh-meng@tju.edu.cn; Qi, Peifeng; Zeng, Ming; Li, Wei; Ma, Shugen [Tianjin Key Laboratory of Process Measurement and Control, Institute of Robotics and Autonomous Systems, School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China)

    2014-05-15

    An electronic nose (e-nose) was designed to classify Chinese liquors of the same aroma style. A new method of feature reduction which combined feature selection with feature extraction was proposed. Feature selection method used 8 feature-selection algorithms based on information theory and reduced the dimension of the feature space to 41. Kernel entropy component analysis was introduced into the e-nose system as a feature extraction method and the dimension of feature space was reduced to 12. Classification of Chinese liquors was performed by using back propagation artificial neural network (BP-ANN), linear discrimination analysis (LDA), and a multi-linear classifier. The classification rate of the multi-linear classifier was 97.22%, which was higher than LDA and BP-ANN. Finally the classification of Chinese liquors according to their raw materials and geographical origins was performed using the proposed multi-linear classifier and classification rate was 98.75% and 100%, respectively.

  9. Electronic nose with a new feature reduction method and a multi-linear classifier for Chinese liquor classification

    International Nuclear Information System (INIS)

    Jing, Yaqi; Meng, Qinghao; Qi, Peifeng; Zeng, Ming; Li, Wei; Ma, Shugen

    2014-01-01

    An electronic nose (e-nose) was designed to classify Chinese liquors of the same aroma style. A new method of feature reduction which combined feature selection with feature extraction was proposed. Feature selection method used 8 feature-selection algorithms based on information theory and reduced the dimension of the feature space to 41. Kernel entropy component analysis was introduced into the e-nose system as a feature extraction method and the dimension of feature space was reduced to 12. Classification of Chinese liquors was performed by using back propagation artificial neural network (BP-ANN), linear discrimination analysis (LDA), and a multi-linear classifier. The classification rate of the multi-linear classifier was 97.22%, which was higher than LDA and BP-ANN. Finally the classification of Chinese liquors according to their raw materials and geographical origins was performed using the proposed multi-linear classifier and classification rate was 98.75% and 100%, respectively

  10. VOC removal by microwave, electron beam and catalyst technique

    International Nuclear Information System (INIS)

    IghigeanuI, D.; Martin, D.; OproiuI, C.; Manaila, E.; Craciun, G.; Calinescu, I.; Zissulescu, E.

    2007-01-01

    A hybrid technique, developed for VOCs removal using microwave (MW) treatment, electron beam (EB) irradiation and catalyst method, is presented. Two hybrid laboratory installations, developed for the study of air pollution control by combined EB irradiation, MW irradiation and catalyst, are described. Air loaded with toluene was treated at different MW power levels, water content, flow rates, and different irradiation modes, separately and combined with MW and EB. Also, simultaneous EB and MW irradiation method was applied to SO 2 and NO x removal. Real synergy effects between EB induced NTP, MW induced NTP and catalysis can be observed

  11. Removal of VOCs by hybrid electron beam reactor with catalyst bed

    International Nuclear Information System (INIS)

    Kim, Jinkyu; Han, Bumsoo; Kim, Yuri; Lee, J.H.; Park, C.R.; Kim, J.C.; Kim, J.C.; Kim, K.J.

    2004-01-01

    Electron beam decomposition of volatile organic compounds (VOCs) was studied in order to obtain information for developing effective treatment method of off-gases from industries. We have examined the combination of electron beam and catalyst honeycomb which is either 1% platinum based or ceramic honeycomb- based aluminum oxide, using a hybrid reactor in order to improve removal efficiency and CO 2 formation; and to suppress undesirable by-product formation e.g. O 3 , aerosol, H x C y. , and tar. The experiments were conducted using a pilot-scale treatment system (maximum capacity; 1800 N m 3 /h) that fitted the field size to scale up from the traditional laboratory scale system for VOC removal with electron beam irradiation. Toluene was selected as a typical VOC that was irradiated to investigate product formation, effect of ceramic and catalyst, and factors effecting overall efficiency of degradation. Styrene was selected as the most odorous compound among the VOCs of interest. It was found that VOCs could be destroyed more effectively using a hybrid system with catalyst bed than with electron beam irradiation only

  12. Error minimizing algorithms for nearest eighbor classifiers

    Energy Technology Data Exchange (ETDEWEB)

    Porter, Reid B [Los Alamos National Laboratory; Hush, Don [Los Alamos National Laboratory; Zimmer, G. Beate [TEXAS A& M

    2011-01-03

    Stack Filters define a large class of discrete nonlinear filter first introd uced in image and signal processing for noise removal. In recent years we have suggested their application to classification problems, and investigated their relationship to other types of discrete classifiers such as Decision Trees. In this paper we focus on a continuous domain version of Stack Filter Classifiers which we call Ordered Hypothesis Machines (OHM), and investigate their relationship to Nearest Neighbor classifiers. We show that OHM classifiers provide a novel framework in which to train Nearest Neighbor type classifiers by minimizing empirical error based loss functions. We use the framework to investigate a new cost sensitive loss function that allows us to train a Nearest Neighbor type classifier for low false alarm rate applications. We report results on both synthetic data and real-world image data.

  13. Pixel Classification of SAR ice images using ANFIS-PSO Classifier

    Directory of Open Access Journals (Sweden)

    G. Vasumathi

    2016-12-01

    Full Text Available Synthetic Aperture Radar (SAR is playing a vital role in taking extremely high resolution radar images. It is greatly used to monitor the ice covered ocean regions. Sea monitoring is important for various purposes which includes global climate systems and ship navigation. Classification on the ice infested area gives important features which will be further useful for various monitoring process around the ice regions. Main objective of this paper is to classify the SAR ice image that helps in identifying the regions around the ice infested areas. In this paper three stages are considered in classification of SAR ice images. It starts with preprocessing in which the speckled SAR ice images are denoised using various speckle removal filters; comparison is made on all these filters to find the best filter in speckle removal. Second stage includes segmentation in which different regions are segmented using K-means and watershed segmentation algorithms; comparison is made between these two algorithms to find the best in segmenting SAR ice images. The last stage includes pixel based classification which identifies and classifies the segmented regions using various supervised learning classifiers. The algorithms includes Back propagation neural networks (BPN, Fuzzy Classifier, Adaptive Neuro Fuzzy Inference Classifier (ANFIS classifier and proposed ANFIS with Particle Swarm Optimization (PSO classifier; comparison is made on all these classifiers to propose which classifier is best suitable for classifying the SAR ice image. Various evaluation metrics are performed separately at all these three stages.

  14. Investigation of carrier removal in electron irradiated silicon diodes

    International Nuclear Information System (INIS)

    Taylor, S.J.; Yamaguchi, M.; Matsuda, S.; Hisamatsu, T.; Kawasaki, O.

    1997-01-01

    We present a detailed study of n + p p + silicon diodes irradiated with fluences of 1 MeV electrons high enough to cause device failure due to majority carrier removal. Capacitance voltage (C V) measurements were used to monitor the change in the carrier concentration of the base of the device as a function of radiation fluence. These were compared to the defect spectra in the same region obtained by deep level transient spectroscopy, and to the current voltage characteristics of the device, both before and after annealing. We observed the expected deep levels with activation energies of 0.18 and 0.36 eV, but the C endash V results imply that other trap levels must play a more important role in the carrier removal process. copyright 1997 American Institute of Physics

  15. Electron beam treatment removes both sulphur and nitrogen oxides

    International Nuclear Information System (INIS)

    Kawamura, K.; Miller, G.A.

    1985-01-01

    The Ebara Corporation in Japan has developed an electron beam flue gas treatment (e-beam fgt) process. The process offers the following features: simultaneous removal of SO 2 and NOsub(x); a dry process which involves no slurry recycling, no sludge disposal, and no gas reheating; turndown and load following capabilities with a minimum of process control; SO 2 and NOsub(x) are converted into saleable fertiliser. The demonstration plant is described. (author)

  16. Mechanism of NOx removal by electron beam process in the presence of scavengers

    International Nuclear Information System (INIS)

    Chmielewski, A.G.; Sun Yongxia; Zimek, Z.; Bulka, S.; Licki, J.

    2002-01-01

    In this study NO x removal efficiency, with/without SO 2 in electron beam flue gas treatment process, was evaluated in the presence of different additives: ammonia, water, and alcohol. It was found that NO x removal efficiency increased by 20% and in the presence of alcohol, more than 70% NO x was oxidized/reduced at 6 kGy for the initial concentration of 500 ppm NO. Humidity and ammonia addition increased the NO x removal efficiency but not more than 10%. Organic products and inorganic products were analyzed by a GC-MS and ion chromatography, respectively. The focus of this paper is on the mechanism that accounts for the increased efficiency in NO x removal

  17. The Investigation of Electron Beam Catalytical Oxidation Process Efficiency with Potassium Persulfate in Removal Humic Acid from Aqueous Solutions

    Directory of Open Access Journals (Sweden)

    MT Ghaneian

    2015-05-01

    Results: Based on the results, changes in pH had little effect on the Humic acid removal efficiency. The average, with increasing of pH from 4 to 10, the removal efficiency of humic acid from 72.59% to 73.36% increased, respectively. The results showed that increasing of the dose from 1 to 15 kGy, humic acid removal efficiency increases. Based on results by increasing of persulfate concentration, the removal efficiency increased so that with increasing of concentration of potassium persulfate from 0.1 to 0.5 mmol/100cc, removal efficiency from 69.43% to 83.82% was increased. Kinetic experiments showed that the decomposition of humic acid by electron beam radiation followed the second-order kinetic. Conclusion: The data from this study showed that the aqueous solution containing acid Humic is decomposed effectively by electron beams irradiation. Addition of potassium persulfate can be have significant improvements in removal efficiency of humic acid in the presence of electron beam.

  18. Terra MODIS Band 27 Electronic Crosstalk Effect and Its Removal

    Science.gov (United States)

    Sun, Junqiang; Xiong, Xiaoxiong; Madhavan, Sriharsha; Wenny, Brian

    2012-01-01

    The MODerate-resolution Imaging Spectroradiometer (MODIS) is one of the primary instruments in the NASA Earth Observing System (EOS). The first MODIS instrument was launched in December, 1999 on-board the Terra spacecraft. MODIS has 36 bands, covering a wavelength range from 0.4 micron to 14.4 micron. MODIS band 27 (6.72 micron) is a water vapor band, which is designed to be insensitive to Earth surface features. In recent Earth View (EV) images of Terra band 27, surface feature contamination is clearly seen and striping has become very pronounced. In this paper, it is shown that band 27 is impacted by electronic crosstalk from bands 28-30. An algorithm using a linear approximation is developed to correct the crosstalk effect. The crosstalk coefficients are derived from Terra MODIS lunar observations. They show that the crosstalk is strongly detector dependent and the crosstalk pattern has changed dramatically since launch. The crosstalk contributions are positive to the instrument response of band 27 early in the mission but became negative and much larger in magnitude at later stages of the mission for most detectors of the band. The algorithm is applied to both Black Body (BB) calibration and MODIS L1B products. With the crosstalk effect removed, the calibration coefficients of Terra MODIS band 27 derived from the BB show that the detector differences become smaller. With the algorithm applied to MODIS L1B products, the Earth surface features are significantly removed and the striping is substantially reduced in the images of the band. The approach developed in this report for removal of the electronic crosstalk effect can be applied to other MODIS bands if similar crosstalk behaviors occur.

  19. Using Neural Networks to Classify Digitized Images of Galaxies

    Science.gov (United States)

    Goderya, S. N.; McGuire, P. C.

    2000-12-01

    Automated classification of Galaxies into Hubble types is of paramount importance to study the large scale structure of the Universe, particularly as survey projects like the Sloan Digital Sky Survey complete their data acquisition of one million galaxies. At present it is not possible to find robust and efficient artificial intelligence based galaxy classifiers. In this study we will summarize progress made in the development of automated galaxy classifiers using neural networks as machine learning tools. We explore the Bayesian linear algorithm, the higher order probabilistic network, the multilayer perceptron neural network and Support Vector Machine Classifier. The performance of any machine classifier is dependant on the quality of the parameters that characterize the different groups of galaxies. Our effort is to develop geometric and invariant moment based parameters as input to the machine classifiers instead of the raw pixel data. Such an approach reduces the dimensionality of the classifier considerably, and removes the effects of scaling and rotation, and makes it easier to solve for the unknown parameters in the galaxy classifier. To judge the quality of training and classification we develop the concept of Mathews coefficients for the galaxy classification community. Mathews coefficients are single numbers that quantify classifier performance even with unequal prior probabilities of the classes.

  20. Pilot-plant for NOx, SO2, HCl removal from flue-gas of municipal waste incinerator by electron beam irradiation

    International Nuclear Information System (INIS)

    Doi, Takeshi; Suda, Shoichi; Morishige, Atsushi; Tokunaga, Okihiro; Aoki, Yasushi; Sato, Shoichi; Komiya, Mikihisa; Hashimoto, Nobuo; Nakajima, Michihiro.

    1992-01-01

    A pilot-Plant for NO x , SO 2 and HCl removal from flue-gas of municipal waste incinerator by electron beam irradiation was designed and its construction at Matsudo City Waste Disposal Center was planned. The flue-gas of 1,000 Nm 3 /hr is guided from the waste incinerator flue-gas line of 30,000 Nm 3 /hr to the Pilot-Plant to be processed by spraying Ca(OH) 2 slurry (NKK-LIMAR Process) and irradiating high-energy electron beam of an accelerator. NO x , SO 2 and HCl are removed simultaneously from the flue-gas by the enhanced reaction with Ca(OH) 2 under irradiation. According to the basic research performed using a small size reactor at TRCRE of JAERI, the electron beam irradiation process was proved to be very effective for these harmful gases removal. Based on this result, the Pilot-Plant was designed for the demonstration of NO x , SO 2 and HCl removal performance using electron accelerator of maximum energy 0.95 MeV and maximum power 15 kW. The designing and planning were promoted by NKK in cooperation with JAERI and Matsudo City. (author)

  1. Electron removal from H and He atoms in collisions with C q+ , O q+ ions

    Science.gov (United States)

    Janev, R. K.; McDowell, M. R. C.

    1984-06-01

    Cross sections for electron capture and ionisation in collision of partially and completely stripped C q+ , N q+ and O q+ ions with hydrogen and helium atoms have been calculated at selected energies. The classical trajectory Monte Carlo method was used with a variable-charge pseudopotential to describe the interaction of the active electron with the projectile ion. A scalling relationship has been derived for the electron removal (capture and ionisation) cross section which allows a unifield representation of the data.

  2. Role of aqueous electron and hydroxyl radical in the removal of endosulfan from aqueous solution using gamma irradiation

    Energy Technology Data Exchange (ETDEWEB)

    Shah, Noor S., E-mail: samadchemistry@gmail.com [Institute of Chemical Sciences, University of Swat, Swat 19130 (Pakistan); Radiation Chemistry Laboratory, National Centre of Excellence in Physical Chemistry, University of Peshawar, Peshawar 25120 (Pakistan); Khan, Javed Ali; Nawaz, Shah; Khan, Hasan M. [Radiation Chemistry Laboratory, National Centre of Excellence in Physical Chemistry, University of Peshawar, Peshawar 25120 (Pakistan)

    2014-08-15

    Highlights: • Removal of endosulfan was assessed by gamma irradiation under different conditions. • Removal of endosulfan by gamma irradiation was mainly due to reaction of aqueous electron. • The radiation yield value decreased while dose constant increased with increasing gamma-ray dose-rate. • Second-order rate constant of endosulfan with aqueous electron was determined by competition kinetic method. • Degradation pathways were proposed from the nature of identified by-products. - Abstract: The removal of endosulfan, an emerging water pollutant, from water was investigated using gamma irradiation based advanced oxidation and reduction processes (AORPs). A significant removal, 97% of initially 1.0 μM endosulfan was achieved at an absorbed dose of 1020 Gy. The removal of endosulfan by gamma-rays irradiation was influenced by an absorbed dose and significantly increased in the presence of aqueous electron (e{sub aq}{sup −}). However, efficiency of the process was inhibited in the presence of e{sub aq}{sup −} scavengers, such as N{sub 2}O, NO{sub 3}{sup −}, acid, and Fe{sup 3+}. The observed dose constant decreased while radiation yield (G-value) increased with increasing initial concentrations of the target contaminant and decreasing dose-rate. The removal efficiency of endosulfan II was lower than endosulfan I. The degradation mechanism of endosulfan by the AORPs was proposed showing that reductive pathways involving e{sub aq}{sup −} started at the chlorine attached to the ring while oxidative pathway was initiated due to attack of hydroxyl radical at the S=O bond. The mass balance showed 95% loss of chloride from endosulfan at an absorbed dose of 1020 Gy. The formation of chloride and acetate suggest that gamma irradiation based AORPs are potential methods for the removal of endosulfan and its by-products from contaminated water.

  3. The Effects of the Removal of Electronic Devices for 48 Hours on Sleep in Elite Judo Athletes.

    Science.gov (United States)

    Dunican, Ian C; Martin, David T; Halson, Shona L; Reale, Reid J; Dawson, Brian T; Caldwell, John A; Jones, Maddison J; Eastwood, Peter R

    2017-10-01

    This study examined the effects of evening use of electronic devices (i.e., smartphones, etc.) on sleep quality and next-day athletic and cognitive performance in elite judo athletes. Over 6 consecutive days and nights, 23 elite Australian judo athletes were monitored while attending a camp at the Australian Institute of Sport (AIS). In 14 athletes, all electronic devices were removed on days 3 and 4 (i.e., for 48 hours: the "device-restricted group"), whereas 9 were permitted to use their devices throughout the camp (the "control group"). All athletes wore an activity monitor (Readiband) continuously to provide measures of sleep quantity and quality. Other self-reported (diary) measures included time in bed, electronic device use, and rate of perceived exertion during training periods. Cognitive performance (Cogstate) and physical performance (single leg triple hop test) were also measured. When considering night 2 as a "baseline" for each group, removal of electronic devices on nights 3 and 4 (device-restricted group) resulted in no significant differences in any sleep-related measure between the groups. When comparing actigraphy-based measures of sleep to subjective measures, all athletes significantly overestimated sleep duration by 58 ± 85 minutes (p = 0.001) per night and underestimated time of sleep onset by 37 ± 72 minutes (p = 0.001) per night. No differences in physical or cognitive function were observed between the groups. This study has shown that the removal of electronic devices for a period of two nights (48 hours) during a judo camp does not affect sleep quality or quantity or influence athletic or cognitive performance.

  4. Probing the Hypothesis of SAR Continuity Restoration by the Removal of Activity Cliffs Generators in QSAR.

    Science.gov (United States)

    Cruz-Monteagudo, Maykel; Medina-Franco, José L; Perera-Sardiña, Yunier; Borges, Fernanda; Tejera, Eduardo; Paz-Y-Miño, Cesar; Pérez-Castillo, Yunierkis; Sánchez-Rodríguez, Aminael; Contreras-Posada, Zuleidys; Cordeiro, M Natália D S

    2016-01-01

    In this work we report the first attempt to study the effect of activity cliffs over the generalization ability of machine learning (ML) based QSAR classifiers, using as study case a previously reported diverse and noisy dataset focused on drug induced liver injury (DILI) and more than 40 ML classification algorithms. Here, the hypothesis of structure-activity relationship (SAR) continuity restoration by activity cliffs removal is tested as a potential solution to overcome such limitation. Previously, a parallelism was established between activity cliffs generators (ACGs) and instances that should be misclassified (ISMs), a related concept from the field of machine learning. Based on this concept we comparatively studied the classification performance of multiple machine learning classifiers as well as the consensus classifier derived from predictive classifiers obtained from training sets including or excluding ACGs. The influence of the removal of ACGs from the training set over the virtual screening performance was also studied for the respective consensus classifiers algorithms. In general terms, the removal of the ACGs from the training process slightly decreased the overall accuracy of the ML classifiers and multi-classifiers, improving their sensitivity (the weakest feature of ML classifiers trained with ACGs) but decreasing their specificity. Although these results do not support a positive effect of the removal of ACGs over the classification performance of ML classifiers, the "balancing effect" of ACG removal demonstrated to positively influence the virtual screening performance of multi-classifiers based on valid base ML classifiers. Specially, the early recognition ability was significantly favored after ACGs removal. The results presented and discussed in this work represent the first step towards the application of a remedial solution to the activity cliffs problem in QSAR studies.

  5. Removal of micropollutants with coarse-ground activated carbon for enhanced separation with hydrocyclone classifiers.

    Science.gov (United States)

    Otto, N; Platz, S; Fink, T; Wutscherk, M; Menzel, U

    2016-01-01

    One key technology to eliminate organic micropollutants (OMP) from wastewater effluent is adsorption using powdered activated carbon (PAC). To avoid a discharge of highly loaded PAC particles into natural water bodies a separation stage has to be implemented. Commonly large settling tanks and flocculation filters with the application of coagulants and flocculation aids are used. In this study, a multi-hydrocyclone classifier with a downstream cloth filter has been investigated on a pilot plant as a space-saving alternative with no need for a dosing of chemical additives. To improve the separation, a coarser ground PAC type was compared to a standard PAC type with regard to elimination results of OMP as well as separation performance. With a PAC dosing rate of 20 mg/l an average of 64.7 wt% of the standard PAC and 79.5 wt% of the coarse-ground PAC could be separated in the hydrocyclone classifier. A total average separation efficiency of 93-97 wt% could be reached with a combination of both hydrocyclone classifier and cloth filter. Nonetheless, the OMP elimination of the coarse-ground PAC was not sufficient enough to compete with the standard PAC. Further research and development is necessary to find applicable coarse-grained PAC types with adequate OMP elimination capabilities.

  6. Energy consumption of SO2 removal from humid air under electron beam and electric field influence

    International Nuclear Information System (INIS)

    Nichipor, H.; Radjuk, E.; Chmielewski, A.G.; Zimek, Z.

    1998-01-01

    The kinetic of SO 2 oxidation in humid air under influence of electron beam and electrical field was investigated by computer simulation method in steady state and pulse mode. SO 2 oxidation process was stimulated by radical and ion reactions. The calculation model has included 46 different particles and 160 chemical reactions. Gas mixture containing 1000 ppm of SO 2 concentration was investigated at temperature T=67 deg. C and pressure p=1 at. Water content was within the range 2-12%. Electron beam parameters were as follows: average beam current density 0.0032-3,2 mA/cm 2 , pulse duration 400 μs, repetition rate 50 Hz. Electrical field density was E/n =10 -15 Vcm 2 . Electrical pulse duration was changed within the range 5 x10 -7 -10 -5 s. The influence of the parameters of synchronized electron beam and electrical field pulses on energy deposition was under consideration. Energy cost of SO 2 removal on 90% level was estimated in steady state and pulse modes. It was found that total electron beam and electrical field energy losses in pulse mode are 6 times lower to compare with steady state conditions. The optimum of electrical field pulse duration from point of view minimum energy cost of SO 2 removal was found for different electron beam pulse current levels

  7. Increased electric sail thrust through removal of trapped shielding electrons by orbit chaotisation due to spacecraft body

    Directory of Open Access Journals (Sweden)

    P. Janhunen

    2009-08-01

    Full Text Available An electric solar wind sail is a recently introduced propellantless space propulsion method whose technical development has also started. The electric sail consists of a set of long, thin, centrifugally stretched and conducting tethers which are charged positively and kept in a high positive potential of order 20 kV by an onboard electron gun. The positively charged tethers deflect solar wind protons, thus tapping momentum from the solar wind stream and producing thrust. The amount of obtained propulsive thrust depends on how many electrons are trapped by the potential structures of the tethers, because the trapped electrons tend to shield the charged tether and reduce its effect on the solar wind. Here we present physical arguments and test particle calculations indicating that in a realistic three-dimensional electric sail spacecraft there exist a natural mechanism which tends to remove the trapped electrons by chaotising their orbits and causing them to eventually collide with the conducting tethers. We present calculations which indicate that if these mechanisms were able to remove trapped electrons nearly completely, the electric sail performance could be about five times higher than previously estimated, about 500 nN/m, corresponding to 1 N thrust for a baseline construction with 2000 km total tether length.

  8. Effects of different external carbon sources and electron acceptors on interactions between denitrification and phosphorus removal in biological nutrient removal processes.

    Science.gov (United States)

    Hu, Xiang; Sobotka, Dominika; Czerwionka, Krzysztof; Zhou, Qi; Xie, Li; Makinia, Jacek

    The effects of two different external carbon sources (acetate and ethanol) and electron acceptors (dissolved oxygen, nitrate, and nitrite) were investigated under aerobic and anoxic conditions with non-acclimated process biomass from a full-scale biological nutrient removal-activated sludge system. When acetate was added as an external carbon source, phosphate release was observed even in the presence of electron acceptors. The release rates were 1.7, 7.8, and 3.5 mg P/(g MLVSS·h) (MLVSS: mixed liquor volatile suspended solids), respectively, for dissolved oxygen, nitrate, and nitrite. In the case of ethanol, no phosphate release was observed in the presence of electron acceptors. Results of the experiments with nitrite showed that approximately 25 mg NO 2 -N/L of nitrite inhibited anoxic phosphorus uptake regardless of the concentration of the tested external carbon sources. Furthermore, higher denitrification rates were obtained with acetate (1.4 and 0.8 mg N/(g MLVSS·h)) compared to ethanol (1.1 and 0.7 mg N/ (g MLVSS·h)) for both anoxic electron acceptors (nitrate and nitrite).

  9. Detection of Fundus Lesions Using Classifier Selection

    Science.gov (United States)

    Nagayoshi, Hiroto; Hiramatsu, Yoshitaka; Sako, Hiroshi; Himaga, Mitsutoshi; Kato, Satoshi

    A system for detecting fundus lesions caused by diabetic retinopathy from fundus images is being developed. The system can screen the images in advance in order to reduce the inspection workload on doctors. One of the difficulties that must be addressed in completing this system is how to remove false positives (which tend to arise near blood vessels) without decreasing the detection rate of lesions in other areas. To overcome this difficulty, we developed classifier selection according to the position of a candidate lesion, and we introduced new features that can distinguish true lesions from false positives. A system incorporating classifier selection and these new features was tested in experiments using 55 fundus images with some lesions and 223 images without lesions. The results of the experiments confirm the effectiveness of the proposed system, namely, degrees of sensitivity and specificity of 98% and 81%, respectively.

  10. Use of information barriers to protect classified information

    International Nuclear Information System (INIS)

    MacArthur, D.; Johnson, M.W.; Nicholas, N.J.; Whiteson, R.

    1998-01-01

    This paper discusses the detailed requirements for an information barrier (IB) for use with verification systems that employ intrusive measurement technologies. The IB would protect classified information in a bilateral or multilateral inspection of classified fissile material. Such a barrier must strike a balance between providing the inspecting party the confidence necessary to accept the measurement while protecting the inspected party's classified information. The authors discuss the structure required of an IB as well as the implications of the IB on detector system maintenance. A defense-in-depth approach is proposed which would provide assurance to the inspected party that all sensitive information is protected and to the inspecting party that the measurements are being performed as expected. The barrier could include elements of physical protection (such as locks, surveillance systems, and tamper indicators), hardening of key hardware components, assurance of capabilities and limitations of hardware and software systems, administrative controls, validation and verification of the systems, and error detection and resolution. Finally, an unclassified interface could be used to display and, possibly, record measurement results. The introduction of an IB into an analysis system may result in many otherwise innocuous components (detectors, analyzers, etc.) becoming classified and unavailable for routine maintenance by uncleared personnel. System maintenance and updating will be significantly simplified if the classification status of as many components as possible can be made reversible (i.e. the component can become unclassified following the removal of classified objects)

  11. Energy-Efficient Neuromorphic Classifiers.

    Science.gov (United States)

    Martí, Daniel; Rigotti, Mattia; Seok, Mingoo; Fusi, Stefano

    2016-10-01

    Neuromorphic engineering combines the architectural and computational principles of systems neuroscience with semiconductor electronics, with the aim of building efficient and compact devices that mimic the synaptic and neural machinery of the brain. The energy consumptions promised by neuromorphic engineering are extremely low, comparable to those of the nervous system. Until now, however, the neuromorphic approach has been restricted to relatively simple circuits and specialized functions, thereby obfuscating a direct comparison of their energy consumption to that used by conventional von Neumann digital machines solving real-world tasks. Here we show that a recent technology developed by IBM can be leveraged to realize neuromorphic circuits that operate as classifiers of complex real-world stimuli. Specifically, we provide a set of general prescriptions to enable the practical implementation of neural architectures that compete with state-of-the-art classifiers. We also show that the energy consumption of these architectures, realized on the IBM chip, is typically two or more orders of magnitude lower than that of conventional digital machines implementing classifiers with comparable performance. Moreover, the spike-based dynamics display a trade-off between integration time and accuracy, which naturally translates into algorithms that can be flexibly deployed for either fast and approximate classifications, or more accurate classifications at the mere expense of longer running times and higher energy costs. This work finally proves that the neuromorphic approach can be efficiently used in real-world applications and has significant advantages over conventional digital devices when energy consumption is considered.

  12. Removal of nonorthogonality in the Born theory used for study of electron capture in high energy ion-atom collisions

    International Nuclear Information System (INIS)

    Kimura, M.

    1989-01-01

    We show the complete removal of the nonorthogonality of wave functions between initial and final states in the Born theory. Hence, this treatment offers more realistic electron capture cross sections in high energy ion-atom collisions. Representative results for resonant electron capture in H + + H collision are discussed in conjunction with other perturbative results. 10 refs., 1 fig

  13. Effects of electron acceptors on removal of antibiotic resistant Escherichia coli, resistance genes and class 1 integrons under anaerobic conditions

    Energy Technology Data Exchange (ETDEWEB)

    Yuan, Heyang; Miller, Jennifer H. [Department of Civil and Environmental Engineering, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061 (United States); Abu-Reesh, Ibrahim M. [Department of Chemical Engineering, Qatar University, P.O. Box 2713, Doha (Qatar); Pruden, Amy [Department of Civil and Environmental Engineering, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061 (United States); He, Zhen, E-mail: zhenhe@vt.edu [Department of Civil and Environmental Engineering, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061 (United States)

    2016-11-01

    Anaerobic biotechnologies can effectively remove antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs), but there is a need to better understand the mechanisms. Here we employ bioelectrochemical systems (BES) as a platform to investigate the fate of a native tetracycline and sulfonamide-resistant Escherichia coli strain and its ARGs. The E. coli strain carrying intI1, sulI and tet(E) was isolated from domestic wastewater and dosed into a tubular BES. The BES was first operated as a microbial fuel cell (MFC), with aeration in the cathode, which resulted in enhanced removal of E. coli and ARGs by ~ 2 log (i.e., order of magnitude) when switched from high current to open circuit operation mode. The BES was then operated as a microbial electrolysis cell (MEC) to exclude the effects of oxygen diffusion, and the removal of E. coli and ARGs during the open circuit configuration was again 1–2 log higher than that at high current mode. Significant correlations of E. coli vs. current (R{sup 2} = 0.73) and ARGs vs. E. coli (R{sup 2} ranged from 0.54 to 0.87), and the fact that the BES substrate contained no electron acceptors, implied that the persistence of the E. coli and its ARGs was determined by the availability of indigenous electron acceptors in the BES, i.e., the anode electrode or the electron shuttles generated by the exoelectrogens. Subsequent experiments with pure-culture tetracycline and sulfonamide-resistant E. coli being incubated in a two-chamber MEC and serum bottles demonstrated that the E. coli could survive by respiring anode electrode and/or electron shuttles released by exoelectrogens, and ARGs persisted with their host E. coli. - Highlights: • The fate of an antibiotic resistant E. coli stain and its ARGs in BES is studied. • The removal of the E. coli and its ARGs is enhanced with decreased current. • The ARGs are removed when the host E. coli dies and persist when the host survives. • The survival of the E. coli depends

  14. Effects of electron acceptors on removal of antibiotic resistant Escherichia coli, resistance genes and class 1 integrons under anaerobic conditions

    International Nuclear Information System (INIS)

    Yuan, Heyang; Miller, Jennifer H.; Abu-Reesh, Ibrahim M.; Pruden, Amy; He, Zhen

    2016-01-01

    Anaerobic biotechnologies can effectively remove antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs), but there is a need to better understand the mechanisms. Here we employ bioelectrochemical systems (BES) as a platform to investigate the fate of a native tetracycline and sulfonamide-resistant Escherichia coli strain and its ARGs. The E. coli strain carrying intI1, sulI and tet(E) was isolated from domestic wastewater and dosed into a tubular BES. The BES was first operated as a microbial fuel cell (MFC), with aeration in the cathode, which resulted in enhanced removal of E. coli and ARGs by ~ 2 log (i.e., order of magnitude) when switched from high current to open circuit operation mode. The BES was then operated as a microbial electrolysis cell (MEC) to exclude the effects of oxygen diffusion, and the removal of E. coli and ARGs during the open circuit configuration was again 1–2 log higher than that at high current mode. Significant correlations of E. coli vs. current (R"2 = 0.73) and ARGs vs. E. coli (R"2 ranged from 0.54 to 0.87), and the fact that the BES substrate contained no electron acceptors, implied that the persistence of the E. coli and its ARGs was determined by the availability of indigenous electron acceptors in the BES, i.e., the anode electrode or the electron shuttles generated by the exoelectrogens. Subsequent experiments with pure-culture tetracycline and sulfonamide-resistant E. coli being incubated in a two-chamber MEC and serum bottles demonstrated that the E. coli could survive by respiring anode electrode and/or electron shuttles released by exoelectrogens, and ARGs persisted with their host E. coli. - Highlights: • The fate of an antibiotic resistant E. coli stain and its ARGs in BES is studied. • The removal of the E. coli and its ARGs is enhanced with decreased current. • The ARGs are removed when the host E. coli dies and persist when the host survives. • The survival of the E. coli depends on the

  15. Removal of NOsub(x) and SO2 by the electron beam process

    International Nuclear Information System (INIS)

    Fuchs, P.; Roth, B.; Schwing, U.; Angele, H.; Gottstein, J.

    1988-01-01

    The electron beam process (EBP) is a dry method of flue gas purification for the simultaneous removal of NOsub(x) and SO 2 . The process has the potential to be used as a retrofit for existing coal fired power plants. Since the beginning of last year Badenwerk AG, in an association with other partners, has run a pilot plant incorporating this process in the new Unit No. 7 of the Rheinhafen-Dampfkraftwerk in Karlsruhe. The design and the operation as well as an account of test results and the experience accumulated during the operation of the facility are presented. (author)

  16. Classifying Microorganisms

    DEFF Research Database (Denmark)

    Sommerlund, Julie

    2006-01-01

    This paper describes the coexistence of two systems for classifying organisms and species: a dominant genetic system and an older naturalist system. The former classifies species and traces their evolution on the basis of genetic characteristics, while the latter employs physiological characteris......This paper describes the coexistence of two systems for classifying organisms and species: a dominant genetic system and an older naturalist system. The former classifies species and traces their evolution on the basis of genetic characteristics, while the latter employs physiological...... characteristics. The coexistence of the classification systems does not lead to a conflict between them. Rather, the systems seem to co-exist in different configurations, through which they are complementary, contradictory and inclusive in different situations-sometimes simultaneously. The systems come...

  17. Optimization of arsenic removal water treatment system through characterization of terminal electron accepting processes.

    Science.gov (United States)

    Upadhyaya, Giridhar; Clancy, Tara M; Brown, Jess; Hayes, Kim F; Raskin, Lutgarde

    2012-11-06

    Terminal electron accepting process (TEAP) zones developed when a simulated groundwater containing dissolved oxygen (DO), nitrate, arsenate, and sulfate was treated in a fixed-bed bioreactor system consisting of two reactors (reactors A and B) in series. When the reactors were operated with an empty bed contact time (EBCT) of 20 min each, DO-, nitrate-, sulfate-, and arsenate-reducing TEAP zones were located within reactor A. As a consequence, sulfate reduction and subsequent arsenic removal through arsenic sulfide precipitation and/or arsenic adsorption on or coprecipitation with iron sulfides occurred in reactor A. This resulted in the removal of arsenic-laden solids during backwashing of reactor A. To minimize this by shifting the sulfate-reducing zone to reactor B, the EBCT of reactor A was sequentially lowered from 20 min to 15, 10, and 7 min. While 50 mg/L (0.81 mM) nitrate was completely removed at all EBCTs, more than 90% of 300 μg/L (4 μM) arsenic was removed with the total EBCT as low as 27 min. Sulfate- and arsenate-reducing bacteria were identified throughout the system through clone libraries and quantitative PCR targeting the 16S rRNA, dissimilatory (bi)sulfite reductase (dsrAB), and dissimilatory arsenate reductase (arrA) genes. Results of reverse transcriptase (RT) qPCR of partial dsrAB (i.e., dsrA) and arrA transcripts corresponded with system performance. The RT qPCR results indicated colocation of sulfate- and arsenate-reducing activities, in the presence of iron(II), suggesting their importance in arsenic removal.

  18. Advances in technologies for decay heat removal

    International Nuclear Information System (INIS)

    Yadigaroglu, G.; Berkovich, V.; Bianchi, A.; Chen B.; Meseth, J.; Vecchiarelli, J.; Vidard, M.

    1999-01-01

    The various decay heat removal concepts that have been used for the evolutionary water reactor plant designs developed worldwide are examined and common features identified. Although interesting new features of the 'classical' plants are mentioned, the emphasis is on passive core and containment decay heat removal systems. The various systems are classified according to the function they have to accomplish; they often share common characteristics and similar equipment. (author)

  19. Bayes classifiers for imbalanced traffic accidents datasets.

    Science.gov (United States)

    Mujalli, Randa Oqab; López, Griselda; Garach, Laura

    2016-03-01

    Traffic accidents data sets are usually imbalanced, where the number of instances classified under the killed or severe injuries class (minority) is much lower than those classified under the slight injuries class (majority). This, however, supposes a challenging problem for classification algorithms and may cause obtaining a model that well cover the slight injuries instances whereas the killed or severe injuries instances are misclassified frequently. Based on traffic accidents data collected on urban and suburban roads in Jordan for three years (2009-2011); three different data balancing techniques were used: under-sampling which removes some instances of the majority class, oversampling which creates new instances of the minority class and a mix technique that combines both. In addition, different Bayes classifiers were compared for the different imbalanced and balanced data sets: Averaged One-Dependence Estimators, Weightily Average One-Dependence Estimators, and Bayesian networks in order to identify factors that affect the severity of an accident. The results indicated that using the balanced data sets, especially those created using oversampling techniques, with Bayesian networks improved classifying a traffic accident according to its severity and reduced the misclassification of killed and severe injuries instances. On the other hand, the following variables were found to contribute to the occurrence of a killed causality or a severe injury in a traffic accident: number of vehicles involved, accident pattern, number of directions, accident type, lighting, surface condition, and speed limit. This work, to the knowledge of the authors, is the first that aims at analyzing historical data records for traffic accidents occurring in Jordan and the first to apply balancing techniques to analyze injury severity of traffic accidents. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. Palladium and gold removal and recovery from precious metal solutions and electronic scrap leachates by Desulfovibrio desulfuricans.

    Science.gov (United States)

    Creamer, Neil J; Baxter-Plant, Victoria S; Henderson, John; Potter, M; Macaskie, Lynne E

    2006-09-01

    Biomass of Desulfovibrio desulfuricans was used to recover Au(III) as Au(0) from test solutions and from waste electronic scrap leachate. Au(0) was precipitated extracellularly by a different mechanism from the biodeposition of Pd(0). The presence of Cu(2+) ( approximately 2000 mg/l) in the leachate inhibited the hydrogenase-mediated removal of Pd(II) but pre-palladisation of the cells in the absence of added Cu(2+) facilitated removal of Pd(II) from the leachate and more than 95% of the Pd(II) was removed autocatalytically from a test solution supplemented with Cu(II) and Pd(II). Metal recovery was demonstrated in a gas-lift electrobioreactor with electrochemically generated hydrogen, followed by precipitation of recovered metal under gravity. A 3-stage bioseparation process for the recovery of Au(III), Pd(II) and Cu(II) is proposed.

  1. Possible use of electron beam treatment for removal of SO2 in off-gases from copper smelters. Preliminary tests results

    International Nuclear Information System (INIS)

    Villanueva, L.; Ahumanda, L.; Chmielewski, A.; Zimek, A.; Budka, S.; Licki, J.

    1996-01-01

    The Chilean Nuclear Energy Commission is currently performing a previous feasibility study concerning possible utilization of electron-beam process for removal of SO 2 from different types of sulfurous streams from copper smelters. First part of the project was related to verify, in a experimental line at Institute of Nuclear Chemistry and Technology, INCT, Poland, the behaviour of the process for simulated off-gases with very high SO 2 content, between 5% to 15% by volume. Tests were performed at laboratory stage and with flowrate of 5 Nm 3 /hr, using an ILU-6 electron accelerator, with the following results: High removal efficiencies of SO 2 , up to 90% were achieved for simulated off-gases containing up to 15% of SO 2 ; Required dose was in the range 5 to 8 kGy; Big influence of NH 3 stoichiometry and gas humidity on SO 2 removal efficiency; Rapid generation of sub-micron solid by-product, in great amount, that causes deposits on ducts and filtration units. This work presents the experimental results and discuss is technical projections in the field of interest. (author)

  2. Removal of brominated flame retardant from electrical and electronic waste plastic by solvothermal technique

    International Nuclear Information System (INIS)

    Zhang, Cong-Cong; Zhang, Fu-Shen

    2012-01-01

    Highlights: ► A process for brominated flame retardants (BFRs) removal in plastic was established. ► The plastic became bromine-free with the structure maintained after this treatment. ► BFRs transferred into alcohol solvent were easily debrominated by metallic copper. - Abstract: Brominated flame retardants (BFRs) in electrical and electronic (E and E) waste plastic are toxic, bioaccumulative and recalcitrant. In the present study, tetrabromobisphenol A (TBBPA) contained in this type of plastic was tentatively subjected to solvothermal treatment so as to obtain bromine-free plastic. Methanol, ethanol and isopropanol were examined as solvents for solvothermal treatment and it was found that methanol was the optimal solvent for TBBPA removal. The optimum temperature, time and liquid to solid ratio for solvothermal treatment to remove TBBPA were 90 °C, 2 h and 15:1, respectively. After the treatment with various alcohol solvents, it was found that TBBPA was finally transferred into the solvents and bromine in the extract was debrominated catalyzed by metallic copper. Bisphenol A and cuprous bromide were the main products after debromination. The morphology and FTIR properties of the plastic were generally unchanged after the solvothermal treatment indicating that the structure of the plastic maintained after the process. This work provides a clean and applicable process for BFRs-containing plastic disposal.

  3. Scanning electron microscopic evaluation of efficacy of 17% Ethylenediaminetetraacetic acid and chitosan for smear layer removal with ultrasonics: An In vitro study

    Directory of Open Access Journals (Sweden)

    Aradhana Babu Kamble

    2017-01-01

    Full Text Available Introduction: The main aim of root canal treatment is cleaning, shaping and then obturating three dimensionally to prevent reinfection. This includes chemicomechanical cleansing by instrumentation and the use of irrigating solutions. Therefore, the purpose of this study was to compare the smear layer removal from root canal dentine subjected to two root canal irrigants, 17% EDTA and 0.2% Chitosan, a new irrigant using Scanning Electron Microscope. Methodology: 40 single rooted premolars were decoronated followed by instrumentation with I Race files and intermediate irrigation with 3% sodium hypochlorite and activation with ultrasonics. Then the samples were longitudinally sectioned and place in the respective test solutions and their controls for 5 minutes. Scanning Electron Microscopic evaluation was further carried out. Results: The results of the present study indicates that the Chitosan which was proved effective in removing smear layer. Conclusion: A moderate concentration of 0.2% chitosan removes the smear layer with greater efficiency.

  4. A Novel Design of 4-Class BCI Using Two Binary Classifiers and Parallel Mental Tasks

    Directory of Open Access Journals (Sweden)

    Tao Geng

    2008-01-01

    Full Text Available A novel 4-class single-trial brain computer interface (BCI based on two (rather than four or more binary linear discriminant analysis (LDA classifiers is proposed, which is called a “parallel BCI.” Unlike other BCIs where mental tasks are executed and classified in a serial way one after another, the parallel BCI uses properly designed parallel mental tasks that are executed on both sides of the subject body simultaneously, which is the main novelty of the BCI paradigm used in our experiments. Each of the two binary classifiers only classifies the mental tasks executed on one side of the subject body, and the results of the two binary classifiers are combined to give the result of the 4-class BCI. Data was recorded in experiments with both real movement and motor imagery in 3 able-bodied subjects. Artifacts were not detected or removed. Offline analysis has shown that, in some subjects, the parallel BCI can generate a higher accuracy than a conventional 4-class BCI, although both of them have used the same feature selection and classification algorithms.

  5. Removal of brominated flame retardant from electrical and electronic waste plastic by solvothermal technique

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Cong-Cong [Research Center For Eco-Environmental Sciences, Chinese Academy of Sciences, 18 Shuangqing Road, Beijing 100085 (China); Zhang, Fu-Shen, E-mail: fszhang@rcees.ac.cn [Research Center For Eco-Environmental Sciences, Chinese Academy of Sciences, 18 Shuangqing Road, Beijing 100085 (China)

    2012-06-30

    Highlights: Black-Right-Pointing-Pointer A process for brominated flame retardants (BFRs) removal in plastic was established. Black-Right-Pointing-Pointer The plastic became bromine-free with the structure maintained after this treatment. Black-Right-Pointing-Pointer BFRs transferred into alcohol solvent were easily debrominated by metallic copper. - Abstract: Brominated flame retardants (BFRs) in electrical and electronic (E and E) waste plastic are toxic, bioaccumulative and recalcitrant. In the present study, tetrabromobisphenol A (TBBPA) contained in this type of plastic was tentatively subjected to solvothermal treatment so as to obtain bromine-free plastic. Methanol, ethanol and isopropanol were examined as solvents for solvothermal treatment and it was found that methanol was the optimal solvent for TBBPA removal. The optimum temperature, time and liquid to solid ratio for solvothermal treatment to remove TBBPA were 90 Degree-Sign C, 2 h and 15:1, respectively. After the treatment with various alcohol solvents, it was found that TBBPA was finally transferred into the solvents and bromine in the extract was debrominated catalyzed by metallic copper. Bisphenol A and cuprous bromide were the main products after debromination. The morphology and FTIR properties of the plastic were generally unchanged after the solvothermal treatment indicating that the structure of the plastic maintained after the process. This work provides a clean and applicable process for BFRs-containing plastic disposal.

  6. Localization and Recognition of Dynamic Hand Gestures Based on Hierarchy of Manifold Classifiers

    Science.gov (United States)

    Favorskaya, M.; Nosov, A.; Popov, A.

    2015-05-01

    Generally, the dynamic hand gestures are captured in continuous video sequences, and a gesture recognition system ought to extract the robust features automatically. This task involves the highly challenging spatio-temporal variations of dynamic hand gestures. The proposed method is based on two-level manifold classifiers including the trajectory classifiers in any time instants and the posture classifiers of sub-gestures in selected time instants. The trajectory classifiers contain skin detector, normalized skeleton representation of one or two hands, and motion history representing by motion vectors normalized through predetermined directions (8 and 16 in our case). Each dynamic gesture is separated into a set of sub-gestures in order to predict a trajectory and remove those samples of gestures, which do not satisfy to current trajectory. The posture classifiers involve the normalized skeleton representation of palm and fingers and relative finger positions using fingertips. The min-max criterion is used for trajectory recognition, and the decision tree technique was applied for posture recognition of sub-gestures. For experiments, a dataset "Multi-modal Gesture Recognition Challenge 2013: Dataset and Results" including 393 dynamic hand-gestures was chosen. The proposed method yielded 84-91% recognition accuracy, in average, for restricted set of dynamic gestures.

  7. LOCALIZATION AND RECOGNITION OF DYNAMIC HAND GESTURES BASED ON HIERARCHY OF MANIFOLD CLASSIFIERS

    Directory of Open Access Journals (Sweden)

    M. Favorskaya

    2015-05-01

    Full Text Available Generally, the dynamic hand gestures are captured in continuous video sequences, and a gesture recognition system ought to extract the robust features automatically. This task involves the highly challenging spatio-temporal variations of dynamic hand gestures. The proposed method is based on two-level manifold classifiers including the trajectory classifiers in any time instants and the posture classifiers of sub-gestures in selected time instants. The trajectory classifiers contain skin detector, normalized skeleton representation of one or two hands, and motion history representing by motion vectors normalized through predetermined directions (8 and 16 in our case. Each dynamic gesture is separated into a set of sub-gestures in order to predict a trajectory and remove those samples of gestures, which do not satisfy to current trajectory. The posture classifiers involve the normalized skeleton representation of palm and fingers and relative finger positions using fingertips. The min-max criterion is used for trajectory recognition, and the decision tree technique was applied for posture recognition of sub-gestures. For experiments, a dataset “Multi-modal Gesture Recognition Challenge 2013: Dataset and Results” including 393 dynamic hand-gestures was chosen. The proposed method yielded 84–91% recognition accuracy, in average, for restricted set of dynamic gestures.

  8. Just-in-time adaptive classifiers-part II: designing the classifier.

    Science.gov (United States)

    Alippi, Cesare; Roveri, Manuel

    2008-12-01

    Aging effects, environmental changes, thermal drifts, and soft and hard faults affect physical systems by changing their nature and behavior over time. To cope with a process evolution adaptive solutions must be envisaged to track its dynamics; in this direction, adaptive classifiers are generally designed by assuming the stationary hypothesis for the process generating the data with very few results addressing nonstationary environments. This paper proposes a methodology based on k-nearest neighbor (NN) classifiers for designing adaptive classification systems able to react to changing conditions just-in-time (JIT), i.e., exactly when it is needed. k-NN classifiers have been selected for their computational-free training phase, the possibility to easily estimate the model complexity k and keep under control the computational complexity of the classifier through suitable data reduction mechanisms. A JIT classifier requires a temporal detection of a (possible) process deviation (aspect tackled in a companion paper) followed by an adaptive management of the knowledge base (KB) of the classifier to cope with the process change. The novelty of the proposed approach resides in the general framework supporting the real-time update of the KB of the classification system in response to novel information coming from the process both in stationary conditions (accuracy improvement) and in nonstationary ones (process tracking) and in providing a suitable estimate of k. It is shown that the classification system grants consistency once the change targets the process generating the data in a new stationary state, as it is the case in many real applications.

  9. Numerical investigation on the variation of welding stresses after material removal from a thick titanium alloy plate joined by electron beam welding

    International Nuclear Information System (INIS)

    Liu, Chuan; Zhang, Jianxun; Wu, Bing; Gong, Shuili

    2012-01-01

    Highlights: → After less materials removal from the top, stresses on the bottom remain unchanged. → The transverse stress within the weld decreases significantly with material removal. → Local material removal does not influence the longitudinal stress significantly. -- Abstract: The stress modification after material removal from a 50 mm thick titanium alloy plate jointed by electron beam welding (EBW) was investigated through the finite element method (FEM). The welding experiment and milling process were carried out to experimentally determine the stresses induced by EBW and their modification after local material removal. The modification of as-welded stresses due to the local material removal method and the whole layer removal method was discussed with the finite element analysis. Investigated results showed that with less materials removal from the top, the stresses on the bottom surface remain almost unchanged; after material removal from the top and bottom part, the transverse stress on the newly-formed surface decreases significantly as compared to the as-welded stresses at the same locations; however, the stress modification only occurs at the material removal region in the case of local region removal method; the longitudinal stress decreases with the whole layer removal method while remains almost unchanged with the local region removal method.

  10. Effects of electron acceptors on removal of antibiotic resistant Escherichia coli, resistance genes and class 1 integrons under anaerobic conditions.

    Science.gov (United States)

    Yuan, Heyang; Miller, Jennifer H; Abu-Reesh, Ibrahim M; Pruden, Amy; He, Zhen

    2016-11-01

    Anaerobic biotechnologies can effectively remove antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs), but there is a need to better understand the mechanisms. Here we employ bioelectrochemical systems (BES) as a platform to investigate the fate of a native tetracycline and sulfonamide-resistant Escherichia coli strain and its ARGs. The E. coli strain carrying intI1, sulI and tet(E) was isolated from domestic wastewater and dosed into a tubular BES. The BES was first operated as a microbial fuel cell (MFC), with aeration in the cathode, which resulted in enhanced removal of E. coli and ARGs by ~2 log (i.e., order of magnitude) when switched from high current to open circuit operation mode. The BES was then operated as a microbial electrolysis cell (MEC) to exclude the effects of oxygen diffusion, and the removal of E. coli and ARGs during the open circuit configuration was again 1-2 log higher than that at high current mode. Significant correlations of E. coli vs. current (R(2)=0.73) and ARGs vs. E. coli (R(2) ranged from 0.54 to 0.87), and the fact that the BES substrate contained no electron acceptors, implied that the persistence of the E. coli and its ARGs was determined by the availability of indigenous electron acceptors in the BES, i.e., the anode electrode or the electron shuttles generated by the exoelectrogens. Subsequent experiments with pure-culture tetracycline and sulfonamide-resistant E. coli being incubated in a two-chamber MEC and serum bottles demonstrated that the E. coli could survive by respiring anode electrode and/or electron shuttles released by exoelectrogens, and ARGs persisted with their host E. coli. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Whole acute toxicity removal from industrial and domestic effluents treated by electron beam radiation: emphasis on anionic surfactants

    International Nuclear Information System (INIS)

    Moraes, M.C.F.; Romanelli, M.F; Sena, H.C.; Pasqualini da Silva, G.; Sampa, M.H.O.; Borrely, S.I.

    2004-01-01

    Electron beam radiation has been applied to improve real industrial and domestic effluents received by Suzano wastewater treatment plant. Radiation efficacy has been evaluated as toxicity reduction, using two biological assays. Three sites were sampled and submitted for toxicity assays, anionic surfactant determination and electron beam irradiation. This paper shows the reduction of acute toxicity for both test-organisms, the marine bacteria Vibrio fischeri and the crustacean Daphnia similis. The raw toxic effluents exibitted from 0.6 ppm up to 11.67 ppm for anionic surfactant before being treated by the electron beam. Radiation processing resulted in reduction of the acute toxicity as well as surfactant removal. The final biological effluent was in general less toxic than other sites but the presence of anionic surfactants was evidenced

  12. Whole acute toxicity removal from industrial and domestic effluents treated by electron beam radiation: emphasis on anionic surfactants

    Energy Technology Data Exchange (ETDEWEB)

    Moraes, M.C.F. E-mail: mariacristinafm@uol.com.br; Romanelli, M.F; Sena, H.C.; Pasqualini da Silva, G.; Sampa, M.H.O.; Borrely, S.I

    2004-10-01

    Electron beam radiation has been applied to improve real industrial and domestic effluents received by Suzano wastewater treatment plant. Radiation efficacy has been evaluated as toxicity reduction, using two biological assays. Three sites were sampled and submitted for toxicity assays, anionic surfactant determination and electron beam irradiation. This paper shows the reduction of acute toxicity for both test-organisms, the marine bacteria Vibrio fischeri and the crustacean Daphnia similis. The raw toxic effluents exibitted from 0.6 ppm up to 11.67 ppm for anionic surfactant before being treated by the electron beam. Radiation processing resulted in reduction of the acute toxicity as well as surfactant removal. The final biological effluent was in general less toxic than other sites but the presence of anionic surfactants was evidenced.

  13. Hybrid classifiers methods of data, knowledge, and classifier combination

    CERN Document Server

    Wozniak, Michal

    2014-01-01

    This book delivers a definite and compact knowledge on how hybridization can help improving the quality of computer classification systems. In order to make readers clearly realize the knowledge of hybridization, this book primarily focuses on introducing the different levels of hybridization and illuminating what problems we will face with as dealing with such projects. In the first instance the data and knowledge incorporated in hybridization were the action points, and then a still growing up area of classifier systems known as combined classifiers was considered. This book comprises the aforementioned state-of-the-art topics and the latest research results of the author and his team from Department of Systems and Computer Networks, Wroclaw University of Technology, including as classifier based on feature space splitting, one-class classification, imbalance data, and data stream classification.

  14. Removal of bromates from water

    Science.gov (United States)

    Barlokova, D.; Ilavsky, J.; Marko, I.; Tkacova, J.

    2017-10-01

    Bromates are substances that are usually not present in drinking water. They are obtained by ozone disinfection in the presence of bromine ions in water, as an impurity of sodium hypochlorite, respectively. Because of their specific properties, bromates are classified as vary dangers substances, that can cause serious illnesses in humans. There are several technological processes that have been used to the removal of bromates from water at present. In this article, the removal of the bromates from water by the adsorption using various sorbent materials (activated carbon, zeolite, Klinopur-Mn, Bayoxide E33, GEH, Read-As and Activated alumina) are presented. The effectiveness of selected sorbent materials in the removal of bromates from drinking water moves in the interval from 10 to 40%. Based on laboratory results, the zeolite can be used to reduce the concentration of bromates in water.

  15. Automatic removal of eye-movement and blink artifacts from EEG signals.

    Science.gov (United States)

    Gao, Jun Feng; Yang, Yong; Lin, Pan; Wang, Pei; Zheng, Chong Xun

    2010-03-01

    Frequent occurrence of electrooculography (EOG) artifacts leads to serious problems in interpreting and analyzing the electroencephalogram (EEG). In this paper, a robust method is presented to automatically eliminate eye-movement and eye-blink artifacts from EEG signals. Independent Component Analysis (ICA) is used to decompose EEG signals into independent components. Moreover, the features of topographies and power spectral densities of those components are extracted to identify eye-movement artifact components, and a support vector machine (SVM) classifier is adopted because it has higher performance than several other classifiers. The classification results show that feature-extraction methods are unsuitable for identifying eye-blink artifact components, and then a novel peak detection algorithm of independent component (PDAIC) is proposed to identify eye-blink artifact components. Finally, the artifact removal method proposed here is evaluated by the comparisons of EEG data before and after artifact removal. The results indicate that the method proposed could remove EOG artifacts effectively from EEG signals with little distortion of the underlying brain signals.

  16. DFRFT: A Classified Review of Recent Methods with Its Application

    Directory of Open Access Journals (Sweden)

    Ashutosh Kumar Singh

    2013-01-01

    Full Text Available In the literature, there are various algorithms available for computing the discrete fractional Fourier transform (DFRFT. In this paper, all the existing methods are reviewed, classified into four categories, and subsequently compared to find out the best alternative from the view point of minimal computational error, computational complexity, transform features, and additional features like security. Subsequently, the correlation theorem of FRFT has been utilized to remove significantly the Doppler shift caused due to motion of receiver in the DSB-SC AM signal. Finally, the role of DFRFT has been investigated in the area of steganography.

  17. SpectraClassifier 1.0: a user friendly, automated MRS-based classifier-development system

    Directory of Open Access Journals (Sweden)

    Julià-Sapé Margarida

    2010-02-01

    Full Text Available Abstract Background SpectraClassifier (SC is a Java solution for designing and implementing Magnetic Resonance Spectroscopy (MRS-based classifiers. The main goal of SC is to allow users with minimum background knowledge of multivariate statistics to perform a fully automated pattern recognition analysis. SC incorporates feature selection (greedy stepwise approach, either forward or backward, and feature extraction (PCA. Fisher Linear Discriminant Analysis is the method of choice for classification. Classifier evaluation is performed through various methods: display of the confusion matrix of the training and testing datasets; K-fold cross-validation, leave-one-out and bootstrapping as well as Receiver Operating Characteristic (ROC curves. Results SC is composed of the following modules: Classifier design, Data exploration, Data visualisation, Classifier evaluation, Reports, and Classifier history. It is able to read low resolution in-vivo MRS (single-voxel and multi-voxel and high resolution tissue MRS (HRMAS, processed with existing tools (jMRUI, INTERPRET, 3DiCSI or TopSpin. In addition, to facilitate exchanging data between applications, a standard format capable of storing all the information needed for a dataset was developed. Each functionality of SC has been specifically validated with real data with the purpose of bug-testing and methods validation. Data from the INTERPRET project was used. Conclusions SC is a user-friendly software designed to fulfil the needs of potential users in the MRS community. It accepts all kinds of pre-processed MRS data types and classifies them semi-automatically, allowing spectroscopists to concentrate on interpretation of results with the use of its visualisation tools.

  18. Classifying smoking urges via machine learning.

    Science.gov (United States)

    Dumortier, Antoine; Beckjord, Ellen; Shiffman, Saul; Sejdić, Ervin

    2016-12-01

    Smoking is the largest preventable cause of death and diseases in the developed world, and advances in modern electronics and machine learning can help us deliver real-time intervention to smokers in novel ways. In this paper, we examine different machine learning approaches to use situational features associated with having or not having urges to smoke during a quit attempt in order to accurately classify high-urge states. To test our machine learning approaches, specifically, Bayes, discriminant analysis and decision tree learning methods, we used a dataset collected from over 300 participants who had initiated a quit attempt. The three classification approaches are evaluated observing sensitivity, specificity, accuracy and precision. The outcome of the analysis showed that algorithms based on feature selection make it possible to obtain high classification rates with only a few features selected from the entire dataset. The classification tree method outperformed the naive Bayes and discriminant analysis methods, with an accuracy of the classifications up to 86%. These numbers suggest that machine learning may be a suitable approach to deal with smoking cessation matters, and to predict smoking urges, outlining a potential use for mobile health applications. In conclusion, machine learning classifiers can help identify smoking situations, and the search for the best features and classifier parameters significantly improves the algorithms' performance. In addition, this study also supports the usefulness of new technologies in improving the effect of smoking cessation interventions, the management of time and patients by therapists, and thus the optimization of available health care resources. Future studies should focus on providing more adaptive and personalized support to people who really need it, in a minimum amount of time by developing novel expert systems capable of delivering real-time interventions. Copyright © 2016 Elsevier Ireland Ltd. All rights

  19. Removal of SO2 and NO/sub x/ from flue gas by means of a spray dryer/electron beam combination: a feasibility study

    International Nuclear Information System (INIS)

    Helfritch, D.J.; Feldman, P.L.; Ray, A.B.; Morgan, J.R.; Hildreth, G.A.

    1982-04-01

    This study examines the feasibility of adding an electron beam between the spray dryer and the fabric filter of dry scrubber flue gas desulfurization (FGD) systems. The beam promises effective removal of nitrogen oxides (NO/sub x/) and sulfur dioxide (SO 2 ), even at higher coal-sulfur levels than usually economic for dry scrubbers. The beam excites gas molecules, promoting reactions that convert SO 2 and NO/sub x/ to acids that then react with calcium compounds and are removed by the filter. Concerns examined here are feasibility and waste disposal. The cost findings are promising for both manufacture and operation. The system uses commercially available components. The relatively low temperatures and high humidity downstream of the spray dryer favor economic beam operation. The beam removes SO 2 , so the dryer can be run for economy, not high removal. The beam's incidental heating effect reduces reheat cost. Safe landfilling of the nitrate-rich waste appears practical, with leachate carrying no more nitrate than natural rain and dustfall. We expect natural pozzolanic reactions between alumina-silica compounds in the fly ash and lime compounds from the spray dryer to form an impermeable concrete-like material within 10 days after landfilling. Dry scrubber with electron beam appears competitive with commercial FGD systems, and we recommend a pilot scale operation

  20. Quantum ensembles of quantum classifiers.

    Science.gov (United States)

    Schuld, Maria; Petruccione, Francesco

    2018-02-09

    Quantum machine learning witnesses an increasing amount of quantum algorithms for data-driven decision making, a problem with potential applications ranging from automated image recognition to medical diagnosis. Many of those algorithms are implementations of quantum classifiers, or models for the classification of data inputs with a quantum computer. Following the success of collective decision making with ensembles in classical machine learning, this paper introduces the concept of quantum ensembles of quantum classifiers. Creating the ensemble corresponds to a state preparation routine, after which the quantum classifiers are evaluated in parallel and their combined decision is accessed by a single-qubit measurement. This framework naturally allows for exponentially large ensembles in which - similar to Bayesian learning - the individual classifiers do not have to be trained. As an example, we analyse an exponentially large quantum ensemble in which each classifier is weighed according to its performance in classifying the training data, leading to new results for quantum as well as classical machine learning.

  1. Technical and economical aspects of SO2 and NOx removal from flue gas by electron beam irradiation

    International Nuclear Information System (INIS)

    Turhan, S.; Karadeniz, S.; Tugluoglu, N.; Eken, M.; Oktar, O.; Ercan, I.

    2001-01-01

    The emission of sulfur dioxide (SO 2 , also SO 3 ) and nitrogen oxides (NO, NO 2 , called NO x ) from fossil fuel burning power and industrial plants is one of the major sources of environmental pollution. These pollutants are named as acid gases causing acid rain and also indirect greenhouse gases contributing greenhouse effect. Acid rain damages forest, agriculture fields and flora, and cause public health concerns in regions having a number of industrial plants. Today, many countries have started to impose industrial emission limits and this movement has generated renewed interest in finding viable and cost effective solutions to SO 2 and NO x pollution control. The conventional technologies, wet scrubbing de-SO 2 and de-NO x , now reached their full potential therefore these methods are not expected to provide further improvements in terms of efficiency or reduction in construction costs. However, new technologies are being investigated for industrial scale commercial viability. One of them is electron beam process, which is dry scrubbing process and simultaneously removes SO 2 and NO x , and useful by-product for agriculture fertilizer. In this study, the economical and technical aspects of electron beam flue gas treatment process are discussed. Because an electron accelerator facility with electron beam energy of 500 KeV and electron beam current of 20 mA will be installed at ANRTC in TURKEY

  2. A Graphical, Self-Organizing Approach to Classifying Electronic Meeting Output.

    Science.gov (United States)

    Orwig, Richard E.; Chen, Hsinchun; Nunamaker, Jay F., Jr.

    1997-01-01

    Describes research using an artificial intelligence approach in the application of a Kohonen Self-Organizing Map (SOM) to the problem of classification of electronic brainstorming output and an evaluation of the results. The graphical representation of textual data produced by the Kohonen SOM suggests many opportunities for improving information…

  3. Effect of high electron donor supply on dissimilatory nitrate reduction pathways in a bioreactor for nitrate removal

    DEFF Research Database (Denmark)

    Behrendt, Anna; Tarre, Sheldon; Beliavski, Michael

    2014-01-01

    The possible shift of a bioreactor for NO3- removal from predominantly denitrification (DEN) to dissimilatory nitrate reduction to ammonium (DNRA) by elevated electron donor supply was investigated. By increasing the C/NO3- ratio in one of two initially identical reactors, the production of high...... sulfide concentrations was induced. The response of the dissimilatory NO3- reduction processes to the increased availability of organic carbon and sulfide was monitored in a batch incubation system. The expected shift from a DEN- towards a DNRA-dominated bioreactor was not observed, also not under...

  4. Efficient electron-induced removal of oxalate ions and formation of copper nanoparticles from copper(II oxalate precursor layers

    Directory of Open Access Journals (Sweden)

    Kai Rückriem

    2016-06-01

    Full Text Available Copper(II oxalate grown on carboxy-terminated self-assembled monolayers (SAM using a step-by-step approach was used as precursor for the electron-induced synthesis of surface-supported copper nanoparticles. The precursor material was deposited by dipping the surfaces alternately in ethanolic solutions of copper(II acetate and oxalic acid with intermediate thorough rinsing steps. The deposition of copper(II oxalate and the efficient electron-induced removal of the oxalate ions was monitored by reflection absorption infrared spectroscopy (RAIRS. Helium ion microscopy (HIM reveals the formation of spherical nanoparticles with well-defined size and X-ray photoelectron spectroscopy (XPS confirms their metallic nature. Continued irradiation after depletion of oxalate does not lead to further particle growth giving evidence that nanoparticle formation is primarily controlled by the available amount of precursor.

  5. Classifying threats with a 14-MeV neutron interrogation system.

    Science.gov (United States)

    Strellis, Dan; Gozani, Tsahi

    2005-01-01

    SeaPODDS (Sea Portable Drug Detection System) is a non-intrusive tool for detecting concealed threats in hidden compartments of maritime vessels. This system consists of an electronic neutron generator, a gamma-ray detector, a data acquisition computer, and a laptop computer user-interface. Although initially developed to detect narcotics, recent algorithm developments have shown that the system is capable of correctly classifying a threat into one of four distinct categories: narcotic, explosive, chemical weapon, or radiological dispersion device (RDD). Detection of narcotics, explosives, and chemical weapons is based on gamma-ray signatures unique to the chemical elements. Elements are identified by their characteristic prompt gamma-rays induced by fast and thermal neutrons. Detection of RDD is accomplished by detecting gamma-rays emitted by common radioisotopes and nuclear reactor fission products. The algorithm phenomenology for classifying threats into the proper categories is presented here.

  6. 29 CFR 1904.9 - Recording criteria for cases involving medical removal under OSHA standards.

    Science.gov (United States)

    2010-07-01

    ... surveillance requirements of an OSHA standard, you must record the case on the OSHA 300 Log. (b) Implementation—(1) How do I classify medical removal cases on the OSHA 300 Log? You must enter each medical removal case on the OSHA 300 Log as either a case involving days away from work or a case involving restricted...

  7. Impact of the amount of working fluid in loop heat pipe to remove waste heat from electronic component

    Directory of Open Access Journals (Sweden)

    Smitka Martin

    2014-03-01

    Full Text Available One of the options on how to remove waste heat from electronic components is using loop heat pipe. The loop heat pipe (LHP is a two-phase device with high effective thermal conductivity that utilizes change phase to transport heat. It was invented in Russia in the early 1980’s. The main parts of LHP are an evaporator, a condenser, a compensation chamber and a vapor and liquid lines. Only the evaporator and part of the compensation chamber are equipped with a wick structure. Inside loop heat pipe is working fluid. As a working fluid can be used distilled water, acetone, ammonia, methanol etc. Amount of filling is important for the operation and performance of LHP. This work deals with the design of loop heat pipe and impact of filling ratio of working fluid to remove waste heat from insulated gate bipolar transistor (IGBT.

  8. Cooled electronic system with thermal spreaders coupling electronics cards to cold rails

    Science.gov (United States)

    Chainer, Timothy J; Gaynes, Michael A; Graybill, David P; Iyengar, Madhusudan K; Kamath, Vinod; Kochuparambil, Bejoy J; Schmidt, Roger R; Schultz, Mark D; Simco, Daniel P; Steinke, Mark E

    2013-07-23

    Liquid-cooled electronic systems are provided which include an electronic assembly having an electronics card and a socket with a latch at one end. The latch facilitates securing of the card within the socket or removal of the card from the socket. A liquid-cooled cold rail is disposed at the one end of the socket, and a thermal spreader couples the electronics card to the cold rail. The thermal spreader includes first and second thermal transfer plates coupled to first and second surfaces on opposite sides of the card, and thermally conductive extensions extending from end edges of the plates, which couple the respective transfer plates to the liquid-cooled cold rail. The thermally conductive extensions are disposed to the sides of the latch, and the card is securable within or removable from the socket using the latch without removing the cold rail or the thermal spreader.

  9. IAEA safeguards and classified materials

    International Nuclear Information System (INIS)

    Pilat, J.F.; Eccleston, G.W.; Fearey, B.L.; Nicholas, N.J.; Tape, J.W.; Kratzer, M.

    1997-01-01

    The international community in the post-Cold War period has suggested that the International Atomic Energy Agency (IAEA) utilize its expertise in support of the arms control and disarmament process in unprecedented ways. The pledges of the US and Russian presidents to place excess defense materials, some of which are classified, under some type of international inspections raises the prospect of using IAEA safeguards approaches for monitoring classified materials. A traditional safeguards approach, based on nuclear material accountancy, would seem unavoidably to reveal classified information. However, further analysis of the IAEA's safeguards approaches is warranted in order to understand fully the scope and nature of any problems. The issues are complex and difficult, and it is expected that common technical understandings will be essential for their resolution. Accordingly, this paper examines and compares traditional safeguards item accounting of fuel at a nuclear power station (especially spent fuel) with the challenges presented by inspections of classified materials. This analysis is intended to delineate more clearly the problems as well as reveal possible approaches, techniques, and technologies that could allow the adaptation of safeguards to the unprecedented task of inspecting classified materials. It is also hoped that a discussion of these issues can advance ongoing political-technical debates on international inspections of excess classified materials

  10. NOx and PAHs removal from industrial flue gas by using electron beam technology in the alcohol addition

    International Nuclear Information System (INIS)

    Sun, Y.X.; Chmielewski, A.G.; Bulka, S.; Zimek, Z.; Licki, J.; Kubica, K.

    2002-01-01

    Complete text of publication follows. The preliminary test of NO x and Polycyclic Aromatic Hydrocarbons (PAHs) removal from flue gas were investigated in the alcohol addition by using electron beam irradiation in EPS Kaweczyn. Experimental conditions were as follows: flue gas flow rate 5000 nM 3 /hr; humidity 4-5%; inlet concentrations of SO 2 and NO x , which were emitted from power station, were 192 ppm and 106 ppm, respectively; ammonia addition is 2.75 m 3 /hr; alcohol addition is 600 l/hr. It was found that NO x removal efficiency in the presence of alcohol was increased by 10% than without alcohol addition when the absorbed dose was below 6 kGy. The NO x removal efficiency was decreased when the absorbed dose was higher than 10 kGy. In order to understand PAHs' behavior under EB irradiation, inlet PAHs (emitted from coal combustion process) sample and outlet PAHs (after irradiation) sample were collected by using a condensed bottle connected with XAD-2 adsorbent and active carbon adsorbent and were analyzed by a GC-MS. It is found that: at the 8 kGy adsorbed dose, concentrations of PAHs with small aromatic rings (≤3, except Acenaphthylene) are reduced and concentrations of PAHs with large aromatic rings (≤4) are increased. A possible mechanism is proposed

  11. Gold removal rate by ion sputtering as a function of ion-beam voltage and raster size using Auger electron spectroscopy. Final report

    International Nuclear Information System (INIS)

    Boehning, C.W.

    1983-01-01

    Gold removal rate was measured as a function of ion beam voltage and raster size using Auger electron spectroscopy (AES). Three different gold thicknesses were developed as standards. Two sputter rate calibration curves were generated by which gold sputter rate could be determined for variations in ion beam voltage or raster size

  12. Classification of Multiple Chinese Liquors by Means of a QCM-based E-Nose and MDS-SVM Classifier.

    Science.gov (United States)

    Li, Qiang; Gu, Yu; Jia, Jing

    2017-01-30

    Chinese liquors are internationally well-known fermentative alcoholic beverages. They have unique flavors attributable to the use of various bacteria and fungi, raw materials, and production processes. Developing a novel, rapid, and reliable method to identify multiple Chinese liquors is of positive significance. This paper presents a pattern recognition system for classifying ten brands of Chinese liquors based on multidimensional scaling (MDS) and support vector machine (SVM) algorithms in a quartz crystal microbalance (QCM)-based electronic nose (e-nose) we designed. We evaluated the comprehensive performance of the MDS-SVM classifier that predicted all ten brands of Chinese liquors individually. The prediction accuracy (98.3%) showed superior performance of the MDS-SVM classifier over the back-propagation artificial neural network (BP-ANN) classifier (93.3%) and moving average-linear discriminant analysis (MA-LDA) classifier (87.6%). The MDS-SVM classifier has reasonable reliability, good fitting and prediction (generalization) performance in classification of the Chinese liquors. Taking both application of the e-nose and validation of the MDS-SVM classifier into account, we have thus created a useful method for the classification of multiple Chinese liquors.

  13. Classification of Multiple Chinese Liquors by Means of a QCM-based E-Nose and MDS-SVM Classifier

    Directory of Open Access Journals (Sweden)

    Qiang Li

    2017-01-01

    Full Text Available Chinese liquors are internationally well-known fermentative alcoholic beverages. They have unique flavors attributable to the use of various bacteria and fungi, raw materials, and production processes. Developing a novel, rapid, and reliable method to identify multiple Chinese liquors is of positive significance. This paper presents a pattern recognition system for classifying ten brands of Chinese liquors based on multidimensional scaling (MDS and support vector machine (SVM algorithms in a quartz crystal microbalance (QCM-based electronic nose (e-nose we designed. We evaluated the comprehensive performance of the MDS-SVM classifier that predicted all ten brands of Chinese liquors individually. The prediction accuracy (98.3% showed superior performance of the MDS-SVM classifier over the back-propagation artificial neural network (BP-ANN classifier (93.3% and moving average-linear discriminant analysis (MA-LDA classifier (87.6%. The MDS-SVM classifier has reasonable reliability, good fitting and prediction (generalization performance in classification of the Chinese liquors. Taking both application of the e-nose and validation of the MDS-SVM classifier into account, we have thus created a useful method for the classification of multiple Chinese liquors.

  14. Evaluation of sustained release polylactate electron donors for removal of hexavalent chromium from contaminated groundwater

    Energy Technology Data Exchange (ETDEWEB)

    Brodie, E.L.; Joyner, D. C.; Faybishenko, B.; Conrad, M. E.; Rios-Velazquez, C.; Mork, B.; Willet, A.; Koenigsberg, S.; Herman, D.; Firestone, M. K.; Hazen, T. C.; Malave, Josue; Martinez, Ramon

    2011-02-15

    To evaluate the efficacy of bioimmobilization of Cr(VI) in groundwater at the Department of Energy Hanford site, we conducted a series of microcosm experiments using a range of commercial electron donors with varying degrees of lactate polymerization (polylactate). These experiments were conducted using Hanford Formation sediments (coarse sand and gravel) immersed in Hanford groundwater, which were amended with Cr(VI) and several types of lactate-based electron donors (Hydrogen Release Compound, HRC; primer-HRC, pHRC; extended release HRC) and the polylactate-cysteine form (Metal Remediation Compound, MRC). The results showed that polylactate compounds stimulated an increase in bacterial biomass and activity to a greater extent than sodium lactate when applied at equivalent carbon concentrations. At the same time, concentrations of headspace hydrogen and methane increased and correlated with changes in the microbial community structure. Enrichment of Pseudomonas spp. occurred with all lactate additions, and enrichment of sulfate-reducing Desulfosporosinus spp. occurred with almost complete sulfate reduction. The results of these experiments demonstrate that amendment with the pHRC and MRC forms result in effective removal of Cr(VI) from solution most likely by both direct (enzymatic) and indirect (microbially generated reductant) mechanisms.

  15. A Solid Trap and Thermal Desorption System with Application to a Medical Electronic Nose

    Directory of Open Access Journals (Sweden)

    Xuntao Xu

    2008-11-01

    Full Text Available In this paper, a solid trap/thermal desorption-based odorant gas condensation system has been designed and implemented for measuring low concentration odorant gas. The technique was successfully applied to a medical electronic nose system. The developed system consists of a flow control unit, a temperature control unit and a sorbent tube. The theoretical analysis and experimental results indicate that gas condensation, together with the medical electronic nose system can significantly reduce the detection limit of the nose system and increase the system’s ability to distinguish low concentration gas samples. In addition, the integrated system can remove the influence of background components and fluctuation of operational environment. Even with strong disturbances such as water vapour and ethanol gas, the developed system can classify the test samples accurately.

  16. Classifying features in CT imagery: accuracy for some single- and multiple-species classifiers

    Science.gov (United States)

    Daniel L. Schmoldt; Jing He; A. Lynn Abbott

    1998-01-01

    Our current approach to automatically label features in CT images of hardwood logs classifies each pixel of an image individually. These feature classifiers use a back-propagation artificial neural network (ANN) and feature vectors that include a small, local neighborhood of pixels and the distance of the target pixel to the center of the log. Initially, this type of...

  17. A deep learning method for classifying mammographic breast density categories.

    Science.gov (United States)

    Mohamed, Aly A; Berg, Wendie A; Peng, Hong; Luo, Yahong; Jankowitz, Rachel C; Wu, Shandong

    2018-01-01

    Mammographic breast density is an established risk marker for breast cancer and is visually assessed by radiologists in routine mammogram image reading, using four qualitative Breast Imaging and Reporting Data System (BI-RADS) breast density categories. It is particularly difficult for radiologists to consistently distinguish the two most common and most variably assigned BI-RADS categories, i.e., "scattered density" and "heterogeneously dense". The aim of this work was to investigate a deep learning-based breast density classifier to consistently distinguish these two categories, aiming at providing a potential computerized tool to assist radiologists in assigning a BI-RADS category in current clinical workflow. In this study, we constructed a convolutional neural network (CNN)-based model coupled with a large (i.e., 22,000 images) digital mammogram imaging dataset to evaluate the classification performance between the two aforementioned breast density categories. All images were collected from a cohort of 1,427 women who underwent standard digital mammography screening from 2005 to 2016 at our institution. The truths of the density categories were based on standard clinical assessment made by board-certified breast imaging radiologists. Effects of direct training from scratch solely using digital mammogram images and transfer learning of a pretrained model on a large nonmedical imaging dataset were evaluated for the specific task of breast density classification. In order to measure the classification performance, the CNN classifier was also tested on a refined version of the mammogram image dataset by removing some potentially inaccurately labeled images. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were used to measure the accuracy of the classifier. The AUC was 0.9421 when the CNN-model was trained from scratch on our own mammogram images, and the accuracy increased gradually along with an increased size of training samples

  18. Energy-aware embedded classifier design for real-time emotion analysis.

    Science.gov (United States)

    Padmanabhan, Manoj; Murali, Srinivasan; Rincon, Francisco; Atienza, David

    2015-01-01

    Detection and classification of human emotions from multiple bio-signals has a wide variety of applications. Though electronic devices are available in the market today that acquire multiple body signals, the classification of human emotions in real-time, adapted to the tight energy budgets of wearable embedded systems is a big challenge. In this paper we present an embedded classifier for real-time emotion classification. We propose a system that operates at different energy budgeted modes, depending on the available energy, where each mode is constrained by an operating energy bound. The classifier has an offline training phase where feature selection is performed for each operating mode, with an energy-budget aware algorithm that we propose. Across the different operating modes, the classification accuracy ranges from 95% - 75% and 89% - 70% for arousal and valence respectively. The accuracy is traded off for less power consumption, which results in an increased battery life of up to 7.7 times (from 146.1 to 1126.9 hours).

  19. Effect of Repeated Screw Joint Closing and Opening Cycles and Cyclic Loading on Abutment Screw Removal Torque and Screw Thread Morphology: Scanning Electron Microscopy Evaluation.

    Science.gov (United States)

    Arshad, Mahnaz; Mahgoli, Hosseinali; Payaminia, Leila

    To evaluate the effect of repeated screw joint closing and opening cycles and cyclic loading on abutment screw removal torque and screw thread morphology using scanning electron microscopy (SEM). Three groups (n = 10 in each group) of implant-abutment-abutment screw assemblies were created. There were also 10 extra abutment screws as new screws in group 3. The abutment screws were tightened to 12 Ncm with an electronic torque meter; then they were removed and removal torque values were recorded. This sequence was repeated 5 times for group 1 and 15 times for groups 2 and 3. The same screws in groups 1 and 2 and the new screws in group 3 were then tightened to 12 Ncm; this was also followed by screw tightening to 30 Ncm and retightening to 30 Ncm 15 minutes later. Removal torque measurements were performed after screws were subjected to cyclic loading (0.5 × 10⁶ cycles; 1 Hz; 75 N). Moreover, the surface topography of one screw from each group before and after cyclic loading was evaluated with SEM and compared with an unused screw. All groups exhibited reduced removal torque values in comparison to insertion torque in each cycle. However, there was a steady trend of torque loss in each group. A comparison of the last cycle of the groups before loading showed significantly greater torque loss value in the 15th cycle of groups 2 and 3 compared with the fifth cycle of group 1 (P abutment is definitively placed.

  20. High-temperature radiation-induced removal of gaseous air pollutants

    International Nuclear Information System (INIS)

    Medina Rojas, I.; Thomson, M.J.

    2001-01-01

    This paper explores the use of high-temperature electron beam irradiation to simultaneous remove aromatic hydrocarbons, chlorinated hydrocarbons and nitrogen oxides. Detailed chemical kinetic modeling with validated mechanisms predicts that electron beam irradiation will simultaneously reduce NO with the thermal De-NO x process and oxidize benzene or ethyl chloride over a wide temperature range. Electron beam dosage of 2-10 kGy more than double the width of the temperature window over which the thermal De-NO x process is effective. At these dosages, the benzene and ethyl chloride removal efficiencies can exceed 90% within this temperature window. (author)

  1. LCC: Light Curves Classifier

    Science.gov (United States)

    Vo, Martin

    2017-08-01

    Light Curves Classifier uses data mining and machine learning to obtain and classify desired objects. This task can be accomplished by attributes of light curves or any time series, including shapes, histograms, or variograms, or by other available information about the inspected objects, such as color indices, temperatures, and abundances. After specifying features which describe the objects to be searched, the software trains on a given training sample, and can then be used for unsupervised clustering for visualizing the natural separation of the sample. The package can be also used for automatic tuning parameters of used methods (for example, number of hidden neurons or binning ratio). Trained classifiers can be used for filtering outputs from astronomical databases or data stored locally. The Light Curve Classifier can also be used for simple downloading of light curves and all available information of queried stars. It natively can connect to OgleII, OgleIII, ASAS, CoRoT, Kepler, Catalina and MACHO, and new connectors or descriptors can be implemented. In addition to direct usage of the package and command line UI, the program can be used through a web interface. Users can create jobs for ”training” methods on given objects, querying databases and filtering outputs by trained filters. Preimplemented descriptors, classifier and connectors can be picked by simple clicks and their parameters can be tuned by giving ranges of these values. All combinations are then calculated and the best one is used for creating the filter. Natural separation of the data can be visualized by unsupervised clustering.

  2. High speed intelligent classifier of tomatoes by colour, size and weight

    Energy Technology Data Exchange (ETDEWEB)

    Cement, J.; Novas, N.; Gazquez, J. A.; Manzano-Agugliaro, F.

    2012-11-01

    At present most horticultural products are classified and marketed according to quality standards, which provide a common language for growers, packers, buyers and consumers. The standardisation of both product and packaging enables greater speed and efficiency in management and marketing. Of all the vegetables grown in greenhouses, tomatoes are predominant in both surface area and tons produced. This paper will present the development and evaluation of a low investment classification system of tomatoes with these objectives: to put it at the service of producing farms and to classify for trading standards. An intelligent classifier of tomatoes has been developed by weight, diameter and colour. This system has optimised the necessary algorithms for data processing in the case of tomatoes, so that productivity is greatly increased, with the use of less expensive and lower performance electronics. The prototype is able to achieve very high speed classification, 12.5 ratings per second, using accessible and low cost commercial equipment for this. It decreases fourfold the manual sorting time and is not sensitive to the variety of tomato classified. This system facilitates the processes of standardisation and quality control, increases the competitiveness of tomato farms and impacts positively on profitability. The automatic classification system described in this work represents a contribution from the economic point of view, as it is profitable for a farm in the short term (less than six months), while the existing systems, can only be used in large trading centers. (Author) 36 refs.

  3. 15 CFR 4.8 - Classified Information.

    Science.gov (United States)

    2010-01-01

    ... 15 Commerce and Foreign Trade 1 2010-01-01 2010-01-01 false Classified Information. 4.8 Section 4... INFORMATION Freedom of Information Act § 4.8 Classified Information. In processing a request for information..., the information shall be reviewed to determine whether it should remain classified. Ordinarily the...

  4. Kinetic modeling and simulation of PCE and TCE removal in aqueous solutions by electron-beam irradiation

    International Nuclear Information System (INIS)

    Nickelsen, Michael G.; Cooper, William J.; Secker, David A.; Rosocha, Louis A.; Kurucz, Charles N.; Waite, Thomas D.

    2002-01-01

    The irradiation of aqueous solutions of TCE and PCE using a high-energy electron-beam results in the rapid decomposition of both chemicals. It is known that both TCE and PCE react with the aqueous electron and the hydroxyl radical with bimolecular rate constants greater than 10 9 M -1 s -1 for each reaction. The fact that high-energy electrons produce significant concentrations of both e aq - and ·OH radicals in water makes it an effective process for the removal of TCE and PCE from aqueous solution. We have employed steady state and computer-based chemical kinetic models to simulate and better understand the chemistry and kinetics of e-beam irradiation when applied to natural water systems. Model results were benchmarked to experimental data, allowing for the optimization of the reaction of DOC with the ·OH radical. Values for the associated second-order reaction rate constant were found to be 2.5x10 8 and 4.0x10 8 M -1 s -1 , consistent with reported values for k OH,DOC . The models were also used to investigate the possibility of incomplete irradiation during treatment and the presence of proposed chemical reactions of by-products. The reactions involve radicals and radical-adduct species formed by the reaction of TCE and PCE with the hydroxyl radical

  5. Fingerprint prediction using classifier ensembles

    CSIR Research Space (South Africa)

    Molale, P

    2011-11-01

    Full Text Available ); logistic discrimination (LgD), k-nearest neighbour (k-NN), artificial neural network (ANN), association rules (AR) decision tree (DT), naive Bayes classifier (NBC) and the support vector machine (SVM). The performance of several multiple classifier systems...

  6. Electron radiography

    Science.gov (United States)

    Merrill, Frank E.; Morris, Christopher

    2005-05-17

    A system capable of performing radiography using a beam of electrons. Diffuser means receive a beam of electrons and diffuse the electrons before they enter first matching quadrupoles where the diffused electrons are focused prior to the diffused electrons entering an object. First imaging quadrupoles receive the focused diffused electrons after the focused diffused electrons have been scattered by the object for focusing the scattered electrons. Collimator means receive the scattered electrons and remove scattered electrons that have scattered to large angles. Second imaging quadrupoles receive the collimated scattered electrons and refocus the collimated scattered electrons and map the focused collimated scattered electrons to transverse locations on an image plane representative of the electrons' positions in the object.

  7. Classifying Sluice Occurrences in Dialogue

    DEFF Research Database (Denmark)

    Baird, Austin; Hamza, Anissa; Hardt, Daniel

    2018-01-01

    perform manual annotation with acceptable inter-coder agreement. We build classifier models with Decision Trees and Naive Bayes, with accuracy of 67%. We deploy a classifier to automatically classify sluice occurrences in OpenSubtitles, resulting in a corpus with 1.7 million occurrences. This will support....... Despite this, the corpus can be of great use in research on sluicing and development of systems, and we are making the corpus freely available on request. Furthermore, we are in the process of improving the accuracy of sluice identification and annotation for the purpose of created a subsequent version...

  8. Classifiers based on optimal decision rules

    KAUST Repository

    Amin, Talha

    2013-11-25

    Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

  9. Classifiers based on optimal decision rules

    KAUST Repository

    Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

    2013-01-01

    Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

  10. Robust Framework to Combine Diverse Classifiers Assigning Distributed Confidence to Individual Classifiers at Class Level

    Directory of Open Access Journals (Sweden)

    Shehzad Khalid

    2014-01-01

    Full Text Available We have presented a classification framework that combines multiple heterogeneous classifiers in the presence of class label noise. An extension of m-Mediods based modeling is presented that generates model of various classes whilst identifying and filtering noisy training data. This noise free data is further used to learn model for other classifiers such as GMM and SVM. A weight learning method is then introduced to learn weights on each class for different classifiers to construct an ensemble. For this purpose, we applied genetic algorithm to search for an optimal weight vector on which classifier ensemble is expected to give the best accuracy. The proposed approach is evaluated on variety of real life datasets. It is also compared with existing standard ensemble techniques such as Adaboost, Bagging, and Random Subspace Methods. Experimental results show the superiority of proposed ensemble method as compared to its competitors, especially in the presence of class label noise and imbalance classes.

  11. Organic substrates as electron donors in permeable reactive barriers for removal of heavy metals from acid mine drainage.

    Science.gov (United States)

    Kijjanapanich, P; Pakdeerattanamint, K; Lens, P N L; Annachhatre, A P

    2012-12-01

    This research was conducted to select suitable natural organic substrates as potential carbon sources for use as electron donors for biological sulphate reduction in a permeable reactive barrier (PRB). A number of organic substrates were assessed through batch and continuous column experiments under anaerobic conditions with acid mine drainage (AMD) obtained from an abandoned lignite coal mine. To keep the heavy metal concentration at a constant level, the AMD was supplemented with heavy metals whenever necessary. Under anaerobic conditions, sulphate-reducing bacteria (SRB) converted sulphate into sulphide using the organic substrates as electron donors. The sulphide that was generated precipitated heavy metals as metal sulphides. Organic substrates, which yielded the highest sulphate reduction in batch tests, were selected for continuous column experiments which lasted over 200 days. A mixture of pig-farm wastewater treatment sludge, rice husk and coconut husk chips yielded the best heavy metal (Fe, Cu, Zn and Mn) removal efficiencies of over 90%.

  12. 76 FR 34761 - Classified National Security Information

    Science.gov (United States)

    2011-06-14

    ... MARINE MAMMAL COMMISSION Classified National Security Information [Directive 11-01] AGENCY: Marine... Commission's (MMC) policy on classified information, as directed by Information Security Oversight Office... of Executive Order 13526, ``Classified National Security Information,'' and 32 CFR part 2001...

  13. Aggregation Operator Based Fuzzy Pattern Classifier Design

    DEFF Research Database (Denmark)

    Mönks, Uwe; Larsen, Henrik Legind; Lohweg, Volker

    2009-01-01

    This paper presents a novel modular fuzzy pattern classifier design framework for intelligent automation systems, developed on the base of the established Modified Fuzzy Pattern Classifier (MFPC) and allows designing novel classifier models which are hardware-efficiently implementable....... The performances of novel classifiers using substitutes of MFPC's geometric mean aggregator are benchmarked in the scope of an image processing application against the MFPC to reveal classification improvement potentials for obtaining higher classification rates....

  14. Classification of Focal and Non Focal Epileptic Seizures Using Multi-Features and SVM Classifier.

    Science.gov (United States)

    Sriraam, N; Raghu, S

    2017-09-02

    Identifying epileptogenic zones prior to surgery is an essential and crucial step in treating patients having pharmacoresistant focal epilepsy. Electroencephalogram (EEG) is a significant measurement benchmark to assess patients suffering from epilepsy. This paper investigates the application of multi-features derived from different domains to recognize the focal and non focal epileptic seizures obtained from pharmacoresistant focal epilepsy patients from Bern Barcelona database. From the dataset, five different classification tasks were formed. Total 26 features were extracted from focal and non focal EEG. Significant features were selected using Wilcoxon rank sum test by setting p-value (p z > 1.96) at 95% significance interval. Hypothesis was made that the effect of removing outliers improves the classification accuracy. Turkey's range test was adopted for pruning outliers from feature set. Finally, 21 features were classified using optimized support vector machine (SVM) classifier with 10-fold cross validation. Bayesian optimization technique was adopted to minimize the cross-validation loss. From the simulation results, it was inferred that the highest sensitivity, specificity, and classification accuracy of 94.56%, 89.74%, and 92.15% achieved respectively and found to be better than the state-of-the-art approaches. Further, it was observed that the classification accuracy improved from 80.2% with outliers to 92.15% without outliers. The classifier performance metrics ensures the suitability of the proposed multi-features with optimized SVM classifier. It can be concluded that the proposed approach can be applied for recognition of focal EEG signals to localize epileptogenic zones.

  15. Decoloration and degradation of Reactive Red-120 dye by electron beam irradiation in aqueous solution

    International Nuclear Information System (INIS)

    Paul, Jhimli; Rawat, K.P.; Sarma, K.S.S.; Sabharwal, S.

    2011-01-01

    The decoloration and degradation of aqueous solution of the reactive azo dye viz. Reactive Red-120 (RR-120) was carried out by electron beam irradiation. The change in decoloration percentage, removal of chemical oxygen demand (COD) and total organic carbon (TOC), solution pH and five-day biochemical oxygen demand (BOD 5 ) were investigated with respect to the applied dose. However, the concentration of the dye in the solution showed a great influence on all these observables. During the radiolysis process, it was found that the decoloration of dye was caused by the destruction of the chromophore group of the dye molecule, whereas COD and TOC removal were depended on the extent of mineralization of the dye. The decrease in pH during the radiolysis process indicated the fragmentation of the large dye molecule into smaller organic components mostly like smaller organic acids. The BOD 5 /COD ratio of the unirradiated dye solution was in the range of 0.1-0.2, which could be classified as non-biodegradable wastewater. However, the BOD 5 /COD ratio increased upon irradiation and it indicated the transformation of non-biodegradable dye solution into biodegradable solution. This study showed that electron beam irradiation could be a promising method for treatment of textile wastewater containing RR-120 dye.

  16. Composite Classifiers for Automatic Target Recognition

    National Research Council Canada - National Science Library

    Wang, Lin-Cheng

    1998-01-01

    ...) using forward-looking infrared (FLIR) imagery. Two existing classifiers, one based on learning vector quantization and the other on modular neural networks, are used as the building blocks for our composite classifiers...

  17. New concept of gas purification by electron attachment

    International Nuclear Information System (INIS)

    Tamon, Hajime; Mizota, Hirotoshi; Sano, Noriaki; Schulze, S.; Okazaki, Morio

    1995-01-01

    Recently, the public has become interested in the following types of gas purification: (1) removal of indoor air pollutants; (2) complete removal of dioxin from incineration plants; (3) complete removal of radioactive iodine compounds; (4) simultaneous removal of NOx and SOx in exhaust gases from cogeneration plants; (5) removal and decomposition of halocarbons; (6) ultrahigh purification of gas sued for semiconductor industries. A new concept of gas purification by electron attachment is proposed. Low-energy electrons generated in a corona-discharge reactor are captured by electronegative impurities, producing negative ions. The ions drift to the anode in the electric field and are removed at the anode of the reactor. Two types of reactors were used to remove the negative ions: a deposition-type reactor, which deposits negative ions at the anode surface; a sweep-out-type reactor, which sweeps out enriched electronegative impurities through the porous anode. Removals of dilute sulfur compounds, oxygen and iodine from nitrogen were conducted to verify the concept of gas purification. Simulation models were used to estimate removal efficiencies of these compounds, by taking into account electron attachment, and experimental constants of the models were determined. The removal efficiency correlated by the models agreed well with the experimental one

  18. Hybrid Neuro-Fuzzy Classifier Based On Nefclass Model

    Directory of Open Access Journals (Sweden)

    Bogdan Gliwa

    2011-01-01

    Full Text Available The paper presents hybrid neuro-fuzzy classifier, based on NEFCLASS model, which wasmodified. The presented classifier was compared to popular classifiers – neural networks andk-nearest neighbours. Efficiency of modifications in classifier was compared with methodsused in original model NEFCLASS (learning methods. Accuracy of classifier was testedusing 3 datasets from UCI Machine Learning Repository: iris, wine and breast cancer wisconsin.Moreover, influence of ensemble classification methods on classification accuracy waspresented.

  19. Effect of residual chips on the material removal process of the bulk metallic glass studied by in situ scratch testing inside the scanning electron microscope

    Directory of Open Access Journals (Sweden)

    Hu Huang

    2012-12-01

    Full Text Available Research on material removal mechanism is meaningful for precision and ultra-precision manufacturing. In this paper, a novel scratch device was proposed by integrating the parasitic motion principle linear actuator. The device has a compact structure and it can be installed on the stage of the scanning electron microscope (SEM to carry out in situ scratch testing. Effect of residual chips on the material removal process of the bulk metallic glass (BMG was studied by in situ scratch testing inside the SEM. The whole removal process of the BMG during the scratch was captured in real time. Formation and growth of lamellar chips on the rake face of the Cube-Corner indenter were observed dynamically. Experimental results indicate that when lots of chips are accumulated on the rake face of the indenter and obstruct forward flow of materials, materials will flow laterally and downward to find new location and direction for formation of new chips. Due to similar material removal processes, in situ scratch testing is potential to be a powerful research tool for studying material removal mechanism of single point diamond turning, single grit grinding, mechanical polishing and grating fabrication.

  20. 36 CFR 1256.46 - National security-classified information.

    Science.gov (United States)

    2010-07-01

    ... 36 Parks, Forests, and Public Property 3 2010-07-01 2010-07-01 false National security-classified... Restrictions § 1256.46 National security-classified information. In accordance with 5 U.S.C. 552(b)(1), NARA... properly classified under the provisions of the pertinent Executive Order on Classified National Security...

  1. Class-specific Error Bounds for Ensemble Classifiers

    Energy Technology Data Exchange (ETDEWEB)

    Prenger, R; Lemmond, T; Varshney, K; Chen, B; Hanley, W

    2009-10-06

    The generalization error, or probability of misclassification, of ensemble classifiers has been shown to be bounded above by a function of the mean correlation between the constituent (i.e., base) classifiers and their average strength. This bound suggests that increasing the strength and/or decreasing the correlation of an ensemble's base classifiers may yield improved performance under the assumption of equal error costs. However, this and other existing bounds do not directly address application spaces in which error costs are inherently unequal. For applications involving binary classification, Receiver Operating Characteristic (ROC) curves, performance curves that explicitly trade off false alarms and missed detections, are often utilized to support decision making. To address performance optimization in this context, we have developed a lower bound for the entire ROC curve that can be expressed in terms of the class-specific strength and correlation of the base classifiers. We present empirical analyses demonstrating the efficacy of these bounds in predicting relative classifier performance. In addition, we specify performance regions of the ROC curve that are naturally delineated by the class-specific strengths of the base classifiers and show that each of these regions can be associated with a unique set of guidelines for performance optimization of binary classifiers within unequal error cost regimes.

  2. Deconvolution When Classifying Noisy Data Involving Transformations

    KAUST Repository

    Carroll, Raymond

    2012-09-01

    In the present study, we consider the problem of classifying spatial data distorted by a linear transformation or convolution and contaminated by additive random noise. In this setting, we show that classifier performance can be improved if we carefully invert the data before the classifier is applied. However, the inverse transformation is not constructed so as to recover the original signal, and in fact, we show that taking the latter approach is generally inadvisable. We introduce a fully data-driven procedure based on cross-validation, and use several classifiers to illustrate numerical properties of our approach. Theoretical arguments are given in support of our claims. Our procedure is applied to data generated by light detection and ranging (Lidar) technology, where we improve on earlier approaches to classifying aerosols. This article has supplementary materials online.

  3. Deconvolution When Classifying Noisy Data Involving Transformations.

    Science.gov (United States)

    Carroll, Raymond; Delaigle, Aurore; Hall, Peter

    2012-09-01

    In the present study, we consider the problem of classifying spatial data distorted by a linear transformation or convolution and contaminated by additive random noise. In this setting, we show that classifier performance can be improved if we carefully invert the data before the classifier is applied. However, the inverse transformation is not constructed so as to recover the original signal, and in fact, we show that taking the latter approach is generally inadvisable. We introduce a fully data-driven procedure based on cross-validation, and use several classifiers to illustrate numerical properties of our approach. Theoretical arguments are given in support of our claims. Our procedure is applied to data generated by light detection and ranging (Lidar) technology, where we improve on earlier approaches to classifying aerosols. This article has supplementary materials online.

  4. Just-in-time classifiers for recurrent concepts.

    Science.gov (United States)

    Alippi, Cesare; Boracchi, Giacomo; Roveri, Manuel

    2013-04-01

    Just-in-time (JIT) classifiers operate in evolving environments by classifying instances and reacting to concept drift. In stationary conditions, a JIT classifier improves its accuracy over time by exploiting additional supervised information coming from the field. In nonstationary conditions, however, the classifier reacts as soon as concept drift is detected; the current classification setup is discarded and a suitable one activated to keep the accuracy high. We present a novel generation of JIT classifiers able to deal with recurrent concept drift by means of a practical formalization of the concept representation and the definition of a set of operators working on such representations. The concept-drift detection activity, which is crucial in promptly reacting to changes exactly when needed, is advanced by considering change-detection tests monitoring both inputs and classes distributions.

  5. Deconvolution When Classifying Noisy Data Involving Transformations

    KAUST Repository

    Carroll, Raymond; Delaigle, Aurore; Hall, Peter

    2012-01-01

    In the present study, we consider the problem of classifying spatial data distorted by a linear transformation or convolution and contaminated by additive random noise. In this setting, we show that classifier performance can be improved if we carefully invert the data before the classifier is applied. However, the inverse transformation is not constructed so as to recover the original signal, and in fact, we show that taking the latter approach is generally inadvisable. We introduce a fully data-driven procedure based on cross-validation, and use several classifiers to illustrate numerical properties of our approach. Theoretical arguments are given in support of our claims. Our procedure is applied to data generated by light detection and ranging (Lidar) technology, where we improve on earlier approaches to classifying aerosols. This article has supplementary materials online.

  6. 78 FR 3317 - Removal of Persons From the Entity List Based on Removal Request; Implementation of Entity List...

    Science.gov (United States)

    2013-01-16

    ... a burden hour estimate of 43.8 minutes for a manual or electronic submission. This rule does not... removing under France, the two French entities: ``Laurence Mattiucci, 8 Rue de la Bruyere, 31120 Pinsaguel...

  7. A random forest classifier for detecting rare variants in NGS data from viral populations

    Directory of Open Access Journals (Sweden)

    Raunaq Malhotra

    Full Text Available We propose a random forest classifier for detecting rare variants from sequencing errors in Next Generation Sequencing (NGS data from viral populations. The method utilizes counts of varying length of k-mers from the reads of a viral population to train a Random forest classifier, called MultiRes, that classifies k-mers as erroneous or rare variants. Our algorithm is rooted in concepts from signal processing and uses a frame-based representation of k-mers. Frames are sets of non-orthogonal basis functions that were traditionally used in signal processing for noise removal. We define discrete spatial signals for genomes and sequenced reads, and show that k-mers of a given size constitute a frame.We evaluate MultiRes on simulated and real viral population datasets, which consist of many low frequency variants, and compare it to the error detection methods used in correction tools known in the literature. MultiRes has 4 to 500 times less false positives k-mer predictions compared to other methods, essential for accurate estimation of viral population diversity and their de-novo assembly. It has high recall of the true k-mers, comparable to other error correction methods. MultiRes also has greater than 95% recall for detecting single nucleotide polymorphisms (SNPs and fewer false positive SNPs, while detecting higher number of rare variants compared to other variant calling methods for viral populations. The software is available freely from the GitHub link https://github.com/raunaq-m/MultiRes. Keywords: Sequencing error detection, Reference free methods, Next-generation sequencing, Viral populations, Multi-resolution frames, Random forest classifier

  8. Comparing classifiers for pronunciation error detection

    NARCIS (Netherlands)

    Strik, H.; Truong, K.; Wet, F. de; Cucchiarini, C.

    2007-01-01

    Providing feedback on pronunciation errors in computer assisted language learning systems requires that pronunciation errors be detected automatically. In the present study we compare four types of classifiers that can be used for this purpose: two acoustic-phonetic classifiers (one of which employs

  9. Gaseous Electronics Tables, Atoms, and Molecules

    CERN Document Server

    Raju, Gorur Govinda

    2011-01-01

    With the constant emergence of new research and application possibilities, gaseous electronics is more important than ever in disciplines including engineering (electrical, power, mechanical, electronics, and environmental), physics, and electronics. The first resource of its kind, Gaseous Electronics: Tables, Atoms, and Molecules fulfills the author's vision of a stand-alone reference to condense 100 years of research on electron-neutral collision data into one easily searchable volume. It presents most--if not all--of the properly classified experimental results that scientists, researchers,

  10. Effectiveness of four different final irrigation activation techniques on smear layer removal in curved root canals : a scanning electron microscopy study.

    Directory of Open Access Journals (Sweden)

    Puneet Ahuja

    2014-02-01

    Full Text Available The aim of this study was to assess the efficacy of apical negative pressure (ANP, manual dynamic agitation (MDA, passive ultrasonic irrigation (PUI and needle irrigation (NI as final irrigation activation techniques for smear layer removal in curved root canals.Mesiobuccal root canals of 80 freshly extracted maxillary first molars with curvatures ranging between 25° and 35° were used. A glide path with #08-15 K files was established before cleaning and shaping with Mtwo rotary instruments (VDW, Munich, Germany up to size 35/0.04 taper. During instrumentation, 1 ml of 2.5% NaOCl was used at each change of file. Samples were divided into 4 equal groups (n=20 according to the final irrigation activation technique: group 1, apical negative pressure (ANP (EndoVac; group 2, manual dynamic agitation (MDA; group 3, passive ultrasonic irrigation (PUI; and group 4, needle irrigation (NI. Root canals were split longitudinally and subjected to scanning electron microscopy. The presence of smear layer at coronal, middle and apical levels was evaluated by superimposing 300-μm square grid over the obtained photomicrographs using a four-score scale with X1,000 magnification.Amongst all the groups tested, ANP showed the overall best smear layer removal efficacy (p < 0.05. Removal of smear layer was least effective with the NI technique.ANP (EndoVac system can be used as the final irrigation activation technique for effective smear layer removal in curved root canals.

  11. Classifier Fusion With Contextual Reliability Evaluation.

    Science.gov (United States)

    Liu, Zhunga; Pan, Quan; Dezert, Jean; Han, Jun-Wei; He, You

    2018-05-01

    Classifier fusion is an efficient strategy to improve the classification performance for the complex pattern recognition problem. In practice, the multiple classifiers to combine can have different reliabilities and the proper reliability evaluation plays an important role in the fusion process for getting the best classification performance. We propose a new method for classifier fusion with contextual reliability evaluation (CF-CRE) based on inner reliability and relative reliability concepts. The inner reliability, represented by a matrix, characterizes the probability of the object belonging to one class when it is classified to another class. The elements of this matrix are estimated from the -nearest neighbors of the object. A cautious discounting rule is developed under belief functions framework to revise the classification result according to the inner reliability. The relative reliability is evaluated based on a new incompatibility measure which allows to reduce the level of conflict between the classifiers by applying the classical evidence discounting rule to each classifier before their combination. The inner reliability and relative reliability capture different aspects of the classification reliability. The discounted classification results are combined with Dempster-Shafer's rule for the final class decision making support. The performance of CF-CRE have been evaluated and compared with those of main classical fusion methods using real data sets. The experimental results show that CF-CRE can produce substantially higher accuracy than other fusion methods in general. Moreover, CF-CRE is robust to the changes of the number of nearest neighbors chosen for estimating the reliability matrix, which is appealing for the applications.

  12. THE PECULIARITIES OF THE ACCOUNTING OF CONSUMPTIONS CONCERNING GAPS REMOVAL IN VINEYARDS

    Directory of Open Access Journals (Sweden)

    Tatiana ŞEVCIUC

    2013-01-01

    Full Text Available Today’s methodology of the accounting of the economic operations concerning gaps removal in vineyards is imperfect; it generates numerous uncertainties and it doesn’t take into account some factors that directly influence gaps removal technology. In our opinion, the rationality of gaps removal in fruitful vineyards may be argued from both economic and biological points. Some authors suggest solving this problem by classifying current accounts that is doubtful as these suggestions don’t have a sound accounting basis and they neglect the fundamental principles of the accounting. That is why, this article suggests the economic way of solving this problem by determining the time of consumptions recovery when planting, caring and growing the cuttings till they give fruit.

  13. Hierarchical mixtures of naive Bayes classifiers

    NARCIS (Netherlands)

    Wiering, M.A.

    2002-01-01

    Naive Bayes classifiers tend to perform very well on a large number of problem domains, although their representation power is quite limited compared to more sophisticated machine learning algorithms. In this pa- per we study combining multiple naive Bayes classifiers by using the hierar- chical

  14. A Supervised Multiclass Classifier for an Autocoding System

    Directory of Open Access Journals (Sweden)

    Yukako Toko

    2017-11-01

    Full Text Available Classification is often required in various contexts, including in the field of official statistics. In the previous study, we have developed a multiclass classifier that can classify short text descriptions with high accuracy. The algorithm borrows the concept of the naïve Bayes classifier and is so simple that its structure is easily understandable. The proposed classifier has the following two advantages. First, the processing times for both learning and classifying are extremely practical. Second, the proposed classifier yields high-accuracy results for a large portion of a dataset. We have previously developed an autocoding system for the Family Income and Expenditure Survey in Japan that has a better performing classifier. While the original system was developed in Perl in order to improve the efficiency of the coding process of short Japanese texts, the proposed system is implemented in the R programming language in order to explore versatility and is modified to make the system easily applicable to English text descriptions, in consideration of the increasing number of R users in the field of official statistics. We are planning to publish the proposed classifier as an R-package. The proposed classifier would be generally applicable to other classification tasks including coding activities in the field of official statistics, and it would contribute greatly to improving their efficiency.

  15. Removal of diclofenac from surface water by electron beam irradiation combined with a biological aerated filter

    Science.gov (United States)

    He, Shijun; Wang, Jianlong; Ye, Longfei; Zhang, Youxue; Yu, Jiang

    2014-12-01

    The degradation of DCF was investigated in aqueous solution by using electron beam (EB) technology. When the initial concentration was between 10 and 40 mg/L, almost 100% of the DCF was degraded at a dose of 0.5 kGy. However, only about 6.5% of DCF was mineralized even at 2 kGy according to total organic carbon (TOC) measurements. A combined process of EB and biological aerated filter (BAF) was therefore developed to enhance the treatment of DCF contaminated surface water. The effluent quality of combined process was substantially improved by EB pretreatment due to the degradation of DCF and related intermediates. Both irradiation and biological treatment reduced the toxicity of the treated water. The experimental results showed that EB is effective for removing DCF from artificial aqueous solution and real surface water.

  16. Classification of root canal microorganisms using electronic-nose and discriminant analysis

    Directory of Open Access Journals (Sweden)

    Özbilge Hatice

    2010-11-01

    Full Text Available Abstract Background Root canal treatment is a debridement process which disrupts and removes entire microorganisms from the root canal system. Identification of microorganisms may help clinicians decide on treatment alternatives such as using different irrigants, intracanal medicaments and antibiotics. However, the difficulty in cultivation and the complexity in isolation of predominant anaerobic microorganisms make clinicians resort to empirical medical treatments. For this reason, identification of microorganisms is not a routinely used procedure in root canal treatment. In this study, we aimed at classifying 7 different standard microorganism strains which are frequently seen in root canal infections, using odor data collected using an electronic nose instrument. Method Our microorganism odor data set consisted of 5 repeated samples from 7 different classes at 4 concentration levels. For each concentration, 35 samples were classified using 3 different discriminant analysis methods. In order to determine an optimal setting for using electronic-nose in such an application, we have tried 3 different approaches in evaluating sensor responses. Moreover, we have used 3 different sensor baseline values in normalizing sensor responses. Since the number of sensors is relatively large compared to sample size, we have also investigated the influence of two different dimension reduction methods on classification performance. Results We have found that quadratic type dicriminant analysis outperforms other varieties of this method. We have also observed that classification performance decreases as the concentration decreases. Among different baseline values used for pre-processing the sensor responses, the model where the minimum values of sensor readings in the sample were accepted as the baseline yields better classification performance. Corresponding to this optimal choice of baseline value, we have noted that among different sensor response model and

  17. The effect of electron range on electron beam induced current collection and a simple method to extract an electron range for any generation function

    International Nuclear Information System (INIS)

    Lahreche, A.; Beggah, Y.; Corkish, R.

    2011-01-01

    The effect of electron range on electron beam induced current (EBIC) is demonstrated and the problem of the choice of the optimal electron ranges to use with simple uniform and point generation function models is resolved by proposing a method to extract an electron range-energy relationship (ERER). The results show that the use of these extracted electron ranges remove the previous disagreement between the EBIC curves computed with simple forms of generation model and those based on a more realistic generation model. The impact of these extracted electron ranges on the extraction of diffusion length, surface recombination velocity and EBIC contrast of defects is discussed. It is also demonstrated that, for the case of uniform generation, the computed EBIC current is independent of the assumed shape of the generation volume. -- Highlights: → Effect of electron ranges on modeling electron beam induced current is shown. → A method to extract an electron range for simple form of generation is proposed. → For uniform generation the EBIC current is independent of the choice of it shape. → Uses of the extracted electron ranges remove some existing literature ambiguity.

  18. Logarithmic learning for generalized classifier neural network.

    Science.gov (United States)

    Ozyildirim, Buse Melis; Avci, Mutlu

    2014-12-01

    Generalized classifier neural network is introduced as an efficient classifier among the others. Unless the initial smoothing parameter value is close to the optimal one, generalized classifier neural network suffers from convergence problem and requires quite a long time to converge. In this work, to overcome this problem, a logarithmic learning approach is proposed. The proposed method uses logarithmic cost function instead of squared error. Minimization of this cost function reduces the number of iterations used for reaching the minima. The proposed method is tested on 15 different data sets and performance of logarithmic learning generalized classifier neural network is compared with that of standard one. Thanks to operation range of radial basis function included by generalized classifier neural network, proposed logarithmic approach and its derivative has continuous values. This makes it possible to adopt the advantage of logarithmic fast convergence by the proposed learning method. Due to fast convergence ability of logarithmic cost function, training time is maximally decreased to 99.2%. In addition to decrease in training time, classification performance may also be improved till 60%. According to the test results, while the proposed method provides a solution for time requirement problem of generalized classifier neural network, it may also improve the classification accuracy. The proposed method can be considered as an efficient way for reducing the time requirement problem of generalized classifier neural network. Copyright © 2014 Elsevier Ltd. All rights reserved.

  19. Application of chemical oxidation for removal of pharmaceuticals in wastewater effluents

    DEFF Research Database (Denmark)

    Hey, G.; Ledin, A.; la Cour Jansen, J.

    2012-01-01

    treatment dose is comparable to ClO2. Nevertheless, ozonation significantly enhanced the removal of most APIs including carbamazepine, metoprolol, flutamide, bupropion and beclomethasone. In addition, ozonation allows removal of ibuprofen at higher oxidant dose. APIs that possess the reactive electron...

  20. DECISION TREE CLASSIFIERS FOR STAR/GALAXY SEPARATION

    International Nuclear Information System (INIS)

    Vasconcellos, E. C.; Ruiz, R. S. R.; De Carvalho, R. R.; Capelato, H. V.; Gal, R. R.; LaBarbera, F. L.; Frago Campos Velho, H.; Trevisan, M.

    2011-01-01

    We study the star/galaxy classification efficiency of 13 different decision tree algorithms applied to photometric objects in the Sloan Digital Sky Survey Data Release Seven (SDSS-DR7). Each algorithm is defined by a set of parameters which, when varied, produce different final classification trees. We extensively explore the parameter space of each algorithm, using the set of 884,126 SDSS objects with spectroscopic data as the training set. The efficiency of star-galaxy separation is measured using the completeness function. We find that the Functional Tree algorithm (FT) yields the best results as measured by the mean completeness in two magnitude intervals: 14 ≤ r ≤ 21 (85.2%) and r ≥ 19 (82.1%). We compare the performance of the tree generated with the optimal FT configuration to the classifications provided by the SDSS parametric classifier, 2DPHOT, and Ball et al. We find that our FT classifier is comparable to or better in completeness over the full magnitude range 15 ≤ r ≤ 21, with much lower contamination than all but the Ball et al. classifier. At the faintest magnitudes (r > 19), our classifier is the only one that maintains high completeness (>80%) while simultaneously achieving low contamination (∼2.5%). We also examine the SDSS parametric classifier (psfMag - modelMag) to see if the dividing line between stars and galaxies can be adjusted to improve the classifier. We find that currently stars in close pairs are often misclassified as galaxies, and suggest a new cut to improve the classifier. Finally, we apply our FT classifier to separate stars from galaxies in the full set of 69,545,326 SDSS photometric objects in the magnitude range 14 ≤ r ≤ 21.

  1. Quantum Hooke's Law to Classify Pulse Laser Induced Ultrafast Melting

    Science.gov (United States)

    Hu, Hao; Ding, Hepeng; Liu, Feng

    2015-02-01

    Ultrafast crystal-to-liquid phase transition induced by femtosecond pulse laser excitation is an interesting material's behavior manifesting the complexity of light-matter interaction. There exist two types of such phase transitions: one occurs at a time scale shorter than a picosecond via a nonthermal process mediated by electron-hole plasma formation; the other at a longer time scale via a thermal melting process mediated by electron-phonon interaction. However, it remains unclear what material would undergo which process and why? Here, by exploiting the property of quantum electronic stress (QES) governed by quantum Hooke's law, we classify the transitions by two distinct classes of materials: the faster nonthermal process can only occur in materials like ice having an anomalous phase diagram characterized with dTm/dP < 0, where Tm is the melting temperature and P is pressure, above a high threshold laser fluence; while the slower thermal process may occur in all materials. Especially, the nonthermal transition is shown to be induced by the QES, acting like a negative internal pressure, which drives the crystal into a ``super pressing'' state to spontaneously transform into a higher-density liquid phase. Our findings significantly advance fundamental understanding of ultrafast crystal-to-liquid phase transitions, enabling quantitative a priori predictions.

  2. 32 CFR 2400.28 - Dissemination of classified information.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Dissemination of classified information. 2400.28... SECURITY PROGRAM Safeguarding § 2400.28 Dissemination of classified information. Heads of OSTP offices... originating official may prescribe specific restrictions on dissemination of classified information when...

  3. Technical Requirements for Fabrication and Installation of Removable Shield for CNRF in HANARO

    Energy Technology Data Exchange (ETDEWEB)

    Ryu, Jeong Soo; Cho, Yeong Garp; Lee, Jung Hee; Shin, Jin Won

    2008-04-15

    This report details the technical requirements for the fabrication and installation of the removable shield for the Cold Neutron Research Facility (CNRF) in HANARO reactor hall. The removable shield is classified as non-nuclear safety (NNS), seismic category II, and quality class T. The main function of the removable shield is to do the biological shielding of neutrons and gamma from the CN port and the guides. The removable shield consists of block type walls and roofs that can be necessarily assembled, disassembled and moveable. These will be installed between the reactor pool wall and the CNS guide bunker in. This report describes technical requirements for the removable shield such as quality assurance, seismic analysis requirements, configuration, concrete compositions, fabrication and installation requirements, test and inspection, shipping, delivery, etc. Appendix is the technical specification of structural design and analysis. Attachments are composed of the technical specification for the fabrication of the removable shield, shielding design drawings and procurement quality requirements. These technical requirements will be provided to a contract for the manufacturing and installation.

  4. Nitrate removal from drinking water with a focus on biological methods: a review.

    Science.gov (United States)

    Rezvani, Fariba; Sarrafzadeh, Mohammad-Hossein; Ebrahimi, Sirous; Oh, Hee-Mock

    2017-05-31

    This article summarizes several developed and industrial technologies for nitrate removal from drinking water, including physicochemical and biological techniques, with a focus on autotrophic nitrate removal. Approaches are primarily classified into separation-based and elimination-based methods according to the fate of the nitrate in water treatment. Biological denitrification as a cost-effective and promising method of biological nitrate elimination is reviewed in terms of its removal process, applicability, efficiency, and associated disadvantages. The various pathways during biological nitrate removal, including assimilatory and dissimilatory nitrate reduction, are also explained. A comparative study was carried out to provide a better understanding of the advantages and disadvantages of autotrophic and heterotrophic denitrification. Sulfur-based and hydrogen-based denitrifications, which are the most common autotrophic processes of nitrate removal, are reviewed with the aim of presenting the salient features of hydrogenotrophic denitrification along with some drawbacks of the technology and research areas in which it could be used but currently is not. The application of algae-based water treatment is also introduced as a nature-inspired approach that may broaden future horizons of nitrate removal technology.

  5. Organic micro-pollutants’ removal via anaerobic membrane bioreactor with ultrafiltration and nanofiltration

    KAUST Repository

    Wei, Chunhai

    2015-12-15

    The removal of 15 organic micro-pollutants (OMPs) in synthetic municipal wastewater was investigated in a laboratory-scale mesophilic anaerobic membrane bioreactor (AnMBR) using ultrafiltration and AnMBR followed by nanofiltration (NF), where powdered activated carbon (PAC) was added to enhance OMPs removal. No significant effects of OMPs spiking and NF connection on bulk organics removal and biogas production were observed. Amitriptyline, diphenhydramine, fluoxetine, sulfamethoxazole, TDCPP and trimethoprim showed readily biodegradable characteristics with consistent biological removal over 80%. Atrazine, carbamazepine, DEET, Dilantin, primidone and TCEP showed refractory characteristics with biological removal below 40%. Acetaminophen, atenolol and caffeine showed a prolonged adaption time of around 45 d, with initial biological removal below 40% and up to 50-80% after this period. Most readily biodegradable OMPs contained a strong electron donating group. Most refractory OMPs contained a strong electron withdrawing group or a halogen substitute. NF showed consistent high rejection of 80-92% with an average of 87% for all OMPs, which resulted in higher OMPs removal in AnMBR-NF than in AnMBR alone, especially for refractory OMPs. Limited sorption performance of PAC for OMPs removal was mainly due to low and batch dosage (100 mg/L) as well as the competitive sorption caused by bulk organics.

  6. Word2Vec inversion and traditional text classifiers for phenotyping lupus.

    Science.gov (United States)

    Turner, Clayton A; Jacobs, Alexander D; Marques, Cassios K; Oates, James C; Kamen, Diane L; Anderson, Paul E; Obeid, Jihad S

    2017-08-22

    Identifying patients with certain clinical criteria based on manual chart review of doctors' notes is a daunting task given the massive amounts of text notes in the electronic health records (EHR). This task can be automated using text classifiers based on Natural Language Processing (NLP) techniques along with pattern recognition machine learning (ML) algorithms. The aim of this research is to evaluate the performance of traditional classifiers for identifying patients with Systemic Lupus Erythematosus (SLE) in comparison with a newer Bayesian word vector method. We obtained clinical notes for patients with SLE diagnosis along with controls from the Rheumatology Clinic (662 total patients). Sparse bag-of-words (BOWs) and Unified Medical Language System (UMLS) Concept Unique Identifiers (CUIs) matrices were produced using NLP pipelines. These matrices were subjected to several different NLP classifiers: neural networks, random forests, naïve Bayes, support vector machines, and Word2Vec inversion, a Bayesian inversion method. Performance was measured by calculating accuracy and area under the Receiver Operating Characteristic (ROC) curve (AUC) of a cross-validated (CV) set and a separate testing set. We calculated the accuracy of the ICD-9 billing codes as a baseline to be 90.00% with an AUC of 0.900, the shallow neural network with CUIs to be 92.10% with an AUC of 0.970, the random forest with BOWs to be 95.25% with an AUC of 0.994, the random forest with CUIs to be 95.00% with an AUC of 0.979, and the Word2Vec inversion to be 90.03% with an AUC of 0.905. Our results suggest that a shallow neural network with CUIs and random forests with both CUIs and BOWs are the best classifiers for this lupus phenotyping task. The Word2Vec inversion method failed to significantly beat the ICD-9 code classification, but yielded promising results. This method does not require explicit features and is more adaptable to non-binary classification tasks. The Word2Vec inversion is

  7. Electron beam irradiation of simulated diluted sulfurous off-gases from copper smelters

    International Nuclear Information System (INIS)

    Villanueva, L.; Ahumada, L.; Chmielewski, A.G.; Zimek, Z.; Bulka, S.; Licki, J.

    1998-01-01

    An experimental work for the verification of potential use of electron-beam irradiation processing for S O 2 removal from reduced-S O 2 -strength gases, between 1,000 and 10,000 ppm, was conducted in a laboratory unit equipped with a multi-purpose electron accelerator working with beam energy of 800 keV. During experimental tests performed, influence of different operating parameters on the overall S O 2 removal process was established. Tests were conducted under two main conditions, using only electron beam irradiation and using electron beam irradiation plus ammonia injection. Tests results proved the technical feasibility to move S O 2 from off-gases under working experimental conditions, i.e., S O 2 removal is achieved under the two modes of operation. When using only electron beam irradiation S O 2 removal efficiencies found were rather low, up to 40%, but in the case of using electron beam irradiation in conjunction with ammonia injection, it was found that S O 2 removal efficiency raises up to 85% under experimental conditions. (author)

  8. Energy Efficient Removal of Volatile Organic Compounds (VOCs) and Organic Hazardous Air Pollutants (o-HAPs) from Industrial Waste Streams by Direct Electron Oxidation

    Energy Technology Data Exchange (ETDEWEB)

    Testoni, A. L.

    2011-10-19

    This research program investigated and quantified the capability of direct electron beam destruction of volatile organic compounds and organic hazardous air pollutants in model industrial waste streams and calculated the energy savings that would be realized by the widespread adoption of the technology over traditional pollution control methods. Specifically, this research determined the quantity of electron beam dose required to remove 19 of the most important non-halogenated air pollutants from waste streams and constructed a technical and economic model for the implementation of the technology in key industries including petroleum refining, organic & solvent chemical production, food & beverage production, and forest & paper products manufacturing. Energy savings of 75 - 90% and green house gas reductions of 66 - 95% were calculated for the target market segments.

  9. Neural Network Classifiers for Local Wind Prediction.

    Science.gov (United States)

    Kretzschmar, Ralf; Eckert, Pierre; Cattani, Daniel; Eggimann, Fritz

    2004-05-01

    This paper evaluates the quality of neural network classifiers for wind speed and wind gust prediction with prediction lead times between +1 and +24 h. The predictions were realized based on local time series and model data. The selection of appropriate input features was initiated by time series analysis and completed by empirical comparison of neural network classifiers trained on several choices of input features. The selected input features involved day time, yearday, features from a single wind observation device at the site of interest, and features derived from model data. The quality of the resulting classifiers was benchmarked against persistence for two different sites in Switzerland. The neural network classifiers exhibited superior quality when compared with persistence judged on a specific performance measure, hit and false-alarm rates.

  10. 3D Bayesian contextual classifiers

    DEFF Research Database (Denmark)

    Larsen, Rasmus

    2000-01-01

    We extend a series of multivariate Bayesian 2-D contextual classifiers to 3-D by specifying a simultaneous Gaussian distribution for the feature vectors as well as a prior distribution of the class variables of a pixel and its 6 nearest 3-D neighbours.......We extend a series of multivariate Bayesian 2-D contextual classifiers to 3-D by specifying a simultaneous Gaussian distribution for the feature vectors as well as a prior distribution of the class variables of a pixel and its 6 nearest 3-D neighbours....

  11. Toxic Gas Removal by Dielectric Discharge with Corona Effect

    International Nuclear Information System (INIS)

    Moreno, H.; Pacheco, M.; Mercado, A.; Cruz, A.; Pacheco, J.; Yousfi, M.; Eichwald, O.; Benhenni, M.

    2006-01-01

    In this work, a theoretical and experimental study on SO2 and NOx removal by non-thermal plasma technology, more specifically a dielectric barrier (DBD) discharge combined with the Corona effect, is presented. Results obtained from a theoretical study describe the chemical kinetic model of SO2 and NOx removal processes; the effect of OH radicals in removal of both gases is noteworthy. Experimental results of de-SO2 process are reported. Also, optical emission spectroscopy study was applied on some atomic helium lines to obtain temperature of electrons in the non-thermal plasma

  12. Efficient on-chip hotspot removal combined solution of thermoelectric cooler and mini-channel heat sink

    International Nuclear Information System (INIS)

    Hao, Xiaohong; Peng, Bei; Xie, Gongnan; Chen, Yi

    2016-01-01

    Highlights: • A combined solution of thermoelectric cooler (TEC) and mini-channel heat sink to remove the hotspot of the chip has been proposed. • The TEC's mathematical model is established to assess its work performance. • A comparative study on the proposed efficient On-Chip Hotspot Removal Combined Solution. - Abstract: Hotspot will significantly degrade the reliability and performance of the electronic equipment. The efficient removal of hotspot can make the temperature distribution uniform, and ensure the reliable operation of the electronic equipment. This study proposes a combined solution of thermoelectric cooler (TEC) and mini-channel heat sink to remove the hotspot of the chip in the electronic equipment. Firstly, The TEC's mathematical model is established to assess its work performance under different boundary conditions. Then, the hotspot removal capability of the TEC is discussed for different cooling conditions, which has shown that the combined equipment has better hotspot removal capability compared with others. Finally, A TEC is employed to investigate the hotspot removal capacity of the combined solution, and the results have indicated that it can effectively remove hotspot in the diameter of 0.5 mm, the power density of 600W/cm 2 when its working current is 3A and heat transfer thermal resistance is 0 K/W.

  13. A CLASSIFIER SYSTEM USING SMOOTH GRAPH COLORING

    Directory of Open Access Journals (Sweden)

    JORGE FLORES CRUZ

    2017-01-01

    Full Text Available Unsupervised classifiers allow clustering methods with less or no human intervention. Therefore it is desirable to group the set of items with less data processing. This paper proposes an unsupervised classifier system using the model of soft graph coloring. This method was tested with some classic instances in the literature and the results obtained were compared with classifications made with human intervention, yielding as good or better results than supervised classifiers, sometimes providing alternative classifications that considers additional information that humans did not considered.

  14. Carbon classified?

    DEFF Research Database (Denmark)

    Lippert, Ingmar

    2012-01-01

    . Using an actor- network theory (ANT) framework, the aim is to investigate the actors who bring together the elements needed to classify their carbon emission sources and unpack the heterogeneous relations drawn on. Based on an ethnographic study of corporate agents of ecological modernisation over...... a period of 13 months, this paper provides an exploration of three cases of enacting classification. Drawing on ANT, we problematise the silencing of a range of possible modalities of consumption facts and point to the ontological ethics involved in such performances. In a context of global warming...

  15. Study of device of electron-ion treatment of mother baking yeasts

    International Nuclear Information System (INIS)

    Ostapenkov, A.M.; Merinov, N.S.; Nazarov, V.N.; Balan, E.L.

    1980-01-01

    Devices for electron- ion treatment of mother baking yeasts are considered and classified by the way of aerions removal from the ionization zone: the first ones - by means of the electric field, the other - by air directed flux. Devices of the first type require high voltage - 20-60 kV. Electrodynamic ion generator has been applied as a device of the second type; considered is its construction, principal of operation, given are diagrams of ion flux dependence. The methods of process calculations in the generator and experimental results are presented. The main advantage of the generator of the second type is operation at low (3-5 kV) voltages. It is shown, that the yeast growth module can achieve 36% at essential increase of biomass when using these yeasts as sowing. The device can be used for biostimulation and antisepting of food raw materials

  16. Local-global classifier fusion for screening chest radiographs

    Science.gov (United States)

    Ding, Meng; Antani, Sameer; Jaeger, Stefan; Xue, Zhiyun; Candemir, Sema; Kohli, Marc; Thoma, George

    2017-03-01

    Tuberculosis (TB) is a severe comorbidity of HIV and chest x-ray (CXR) analysis is a necessary step in screening for the infective disease. Automatic analysis of digital CXR images for detecting pulmonary abnormalities is critical for population screening, especially in medical resource constrained developing regions. In this article, we describe steps that improve previously reported performance of NLM's CXR screening algorithms and help advance the state of the art in the field. We propose a local-global classifier fusion method where two complementary classification systems are combined. The local classifier focuses on subtle and partial presentation of the disease leveraging information in radiology reports that roughly indicates locations of the abnormalities. In addition, the global classifier models the dominant spatial structure in the gestalt image using GIST descriptor for the semantic differentiation. Finally, the two complementary classifiers are combined using linear fusion, where the weight of each decision is calculated by the confidence probabilities from the two classifiers. We evaluated our method on three datasets in terms of the area under the Receiver Operating Characteristic (ROC) curve, sensitivity, specificity and accuracy. The evaluation demonstrates the superiority of our proposed local-global fusion method over any single classifier.

  17. Rheological evaluation of pretreated cladding removal waste

    International Nuclear Information System (INIS)

    McCarthy, D.; Chan, M.K.C.; Lokken, R.O.

    1986-01-01

    Cladding removal waste (CRW) contains concentrations of transuranic (TRU) elements in the 80 to 350 nCi/g range. This waste will require pretreatment before it can be disposed of as glass or grout at Hanford. The CRW will be pretreated with a rare earth strike and solids removal by centrifugation to segregate the TRU fraction from the non-TRU fraction of the waste. The centrifuge centrate will be neutralized with sodium hydroxide. This neutralized cladding removal waste (NCRW) is expected to be suitable for grouting. The TRU solids removed by centrifugation will be vitrified. The goal of the Rheological Evaluation of Pretreated Cladding Removal Waste Program was to evaluate those rheological and transport properties critical to assuring successful handling of the NCRW and TRU solids streams and to demonstrate transfers in a semi-prototypic pumping environment. This goal was achieved by a combination of laboratory and pilot-scale evaluations. The results obtained during these evaluations were correlated with classical rheological models and scaled-up to predict the performance that is likely to occur in the full-scale system. The Program used simulated NCRW and TRU solid slurries. Rockwell Hanford Operations (Rockwell) provided 150 gallons of simulated CRW and 5 gallons of simulated TRU solid slurry. The simulated CRW was neutralized by Pacific Northwest Laboratory (PNL). The physical and rheological properties of the NCRW and TRU solid slurries were evaluated in the laboratory. The properties displayed by NCRW allowed it to be classified as a pseudoplastic or yield-pseudoplastic non-Newtonian fluid. The TRU solids slurry contained very few solids. This slurry exhibited the properties associated with a pseudoplastic non-Newtonian fluid

  18. Intelligent Recognition of Lung Nodule Combining Rule-based and C-SVM Classifiers

    Directory of Open Access Journals (Sweden)

    Bin Li

    2012-02-01

    Full Text Available Computer-aided detection(CAD system for lung nodules plays the important role in the diagnosis of lung cancer. In this paper, an improved intelligent recognition method of lung nodule in HRCT combing rule-based and cost-sensitive support vector machine(C-SVM classifiers is proposed for detecting both solid nodules and ground-glass opacity(GGO nodules(part solid and nonsolid. This method consists of several steps. Firstly, segmentation of regions of interest(ROIs, including pulmonary parenchyma and lung nodule candidates, is a difficult task. On one side, the presence of noise lowers the visibility of low-contrast objects. On the other side, different types of nodules, including small nodules, nodules connecting to vasculature or other structures, part-solid or nonsolid nodules, are complex, noisy, weak edge or difficult to define the boundary. In order to overcome the difficulties of obvious boundary-leak and slow evolvement speed problem in segmentatioin of weak edge, an overall segmentation method is proposed, they are: the lung parenchyma is extracted based on threshold and morphologic segmentation method; the image denoising and enhancing is realized by nonlinear anisotropic diffusion filtering(NADF method; candidate pulmonary nodules are segmented by the improved C-V level set method, in which the segmentation result of EM-based fuzzy threshold method is used as the initial contour of active contour model and a constrained energy term is added into the PDE of level set function. Then, lung nodules are classified by using the intelligent classifiers combining rules and C-SVM. Rule-based classification is first used to remove easily dismissible nonnodule objects, then C-SVM classification are used to further classify nodule candidates and reduce the number of false positive(FP objects. In order to increase the efficiency of SVM, an improved training method is used to train SVM, which uses the grid search method to search the optimal

  19. Intelligent Recognition of Lung Nodule Combining Rule-based and C-SVM Classifiers

    Directory of Open Access Journals (Sweden)

    Bin Li

    2011-10-01

    Full Text Available Computer-aided detection(CAD system for lung nodules plays the important role in the diagnosis of lung cancer. In this paper, an improved intelligent recognition method of lung nodule in HRCT combing rule-based and costsensitive support vector machine(C-SVM classifiers is proposed for detecting both solid nodules and ground-glass opacity(GGO nodules(part solid and nonsolid. This method consists of several steps. Firstly, segmentation of regions of interest(ROIs, including pulmonary parenchyma and lung nodule candidates, is a difficult task. On one side, the presence of noise lowers the visibility of low-contrast objects. On the other side, different types of nodules, including small nodules, nodules connecting to vasculature or other structures, part-solid or nonsolid nodules, are complex, noisy, weak edge or difficult to define the boundary. In order to overcome the difficulties of obvious boundary-leak and slow evolvement speed problem in segmentatioin of weak edge, an overall segmentation method is proposed, they are: the lung parenchyma is extracted based on threshold and morphologic segmentation method; the image denoising and enhancing is realized by nonlinear anisotropic diffusion filtering(NADF method;candidate pulmonary nodules are segmented by the improved C-V level set method, in which the segmentation result of EM-based fuzzy threshold method is used as the initial contour of active contour model and a constrained energy term is added into the PDE of level set function. Then, lung nodules are classified by using the intelligent classifiers combining rules and C-SVM. Rule-based classification is first used to remove easily dismissible nonnodule objects, then C-SVM classification are used to further classify nodule candidates and reduce the number of false positive(FP objects. In order to increase the efficiency of SVM, an improved training method is used to train SVM, which uses the grid search method to search the optimal parameters

  20. High dimensional classifiers in the imbalanced case

    DEFF Research Database (Denmark)

    Bak, Britta Anker; Jensen, Jens Ledet

    We consider the binary classification problem in the imbalanced case where the number of samples from the two groups differ. The classification problem is considered in the high dimensional case where the number of variables is much larger than the number of samples, and where the imbalance leads...... to a bias in the classification. A theoretical analysis of the independence classifier reveals the origin of the bias and based on this we suggest two new classifiers that can handle any imbalance ratio. The analytical results are supplemented by a simulation study, where the suggested classifiers in some...

  1. Balanced sensitivity functions for tuning multi-dimensional Bayesian network classifiers

    NARCIS (Netherlands)

    Bolt, J.H.; van der Gaag, L.C.

    Multi-dimensional Bayesian network classifiers are Bayesian networks of restricted topological structure, which are tailored to classifying data instances into multiple dimensions. Like more traditional classifiers, multi-dimensional classifiers are typically learned from data and may include

  2. Recognition of pornographic web pages by classifying texts and images.

    Science.gov (United States)

    Hu, Weiming; Wu, Ou; Chen, Zhouyao; Fu, Zhouyu; Maybank, Steve

    2007-06-01

    With the rapid development of the World Wide Web, people benefit more and more from the sharing of information. However, Web pages with obscene, harmful, or illegal content can be easily accessed. It is important to recognize such unsuitable, offensive, or pornographic Web pages. In this paper, a novel framework for recognizing pornographic Web pages is described. A C4.5 decision tree is used to divide Web pages, according to content representations, into continuous text pages, discrete text pages, and image pages. These three categories of Web pages are handled, respectively, by a continuous text classifier, a discrete text classifier, and an algorithm that fuses the results from the image classifier and the discrete text classifier. In the continuous text classifier, statistical and semantic features are used to recognize pornographic texts. In the discrete text classifier, the naive Bayes rule is used to calculate the probability that a discrete text is pornographic. In the image classifier, the object's contour-based features are extracted to recognize pornographic images. In the text and image fusion algorithm, the Bayes theory is used to combine the recognition results from images and texts. Experimental results demonstrate that the continuous text classifier outperforms the traditional keyword-statistics-based classifier, the contour-based image classifier outperforms the traditional skin-region-based image classifier, the results obtained by our fusion algorithm outperform those by either of the individual classifiers, and our framework can be adapted to different categories of Web pages.

  3. Classifier fusion for VoIP attacks classification

    Science.gov (United States)

    Safarik, Jakub; Rezac, Filip

    2017-05-01

    SIP is one of the most successful protocols in the field of IP telephony communication. It establishes and manages VoIP calls. As the number of SIP implementation rises, we can expect a higher number of attacks on the communication system in the near future. This work aims at malicious SIP traffic classification. A number of various machine learning algorithms have been developed for attack classification. The paper presents a comparison of current research and the use of classifier fusion method leading to a potential decrease in classification error rate. Use of classifier combination makes a more robust solution without difficulties that may affect single algorithms. Different voting schemes, combination rules, and classifiers are discussed to improve the overall performance. All classifiers have been trained on real malicious traffic. The concept of traffic monitoring depends on the network of honeypot nodes. These honeypots run in several networks spread in different locations. Separation of honeypots allows us to gain an independent and trustworthy attack information.

  4. Fast Most Similar Neighbor (MSN) classifiers for Mixed Data

    OpenAIRE

    Hernández Rodríguez, Selene

    2010-01-01

    The k nearest neighbor (k-NN) classifier has been extensively used in Pattern Recognition because of its simplicity and its good performance. However, in large datasets applications, the exhaustive k-NN classifier becomes impractical. Therefore, many fast k-NN classifiers have been developed; most of them rely on metric properties (usually the triangle inequality) to reduce the number of prototype comparisons. Hence, the existing fast k-NN classifiers are applicable only when the comparison f...

  5. Feature extraction for dynamic integration of classifiers

    NARCIS (Netherlands)

    Pechenizkiy, M.; Tsymbal, A.; Puuronen, S.; Patterson, D.W.

    2007-01-01

    Recent research has shown the integration of multiple classifiers to be one of the most important directions in machine learning and data mining. In this paper, we present an algorithm for the dynamic integration of classifiers in the space of extracted features (FEDIC). It is based on the technique

  6. Classifying Returns as Extreme

    DEFF Research Database (Denmark)

    Christiansen, Charlotte

    2014-01-01

    I consider extreme returns for the stock and bond markets of 14 EU countries using two classification schemes: One, the univariate classification scheme from the previous literature that classifies extreme returns for each market separately, and two, a novel multivariate classification scheme tha...

  7. Electronic air cleaners and the indoor environment

    International Nuclear Information System (INIS)

    Krafthefer, B.

    1986-01-01

    The growing awareness over the quality of air in the indoor environment is driving the search for effective control methods for the contaminants of concern. Electronic air cleaners can control such pollutants as dust, pollen, tobacco smoke, radon decay products, and other particulates. This paper presents an examination of the various types of electronic air cleaners and their effects on indoor pollutants. It also examines the mechanism for contaminant removal, the relationship of the efficiency to the characteristics of the contaminant, and what type of contaminants can be controlled with the electronic air cleaner, with particular emphasis placed on the removal of radon decay products. From a study on radon product removal in residences, the electronic air cleaner was found to have an efficiency of up to 70%. Not only was there a reduction in the residential working level, but the fluctuations in the working level were also reduced. With this information, they can better understand how to solve the air treatment problem of the inhabited space. 17 references, 8 figures

  8. The Protection of Classified Information: The Legal Framework

    National Research Council Canada - National Science Library

    Elsea, Jennifer K

    2006-01-01

    Recent incidents involving leaks of classified information have heightened interest in the legal framework that governs security classification, access to classified information, and penalties for improper disclosure...

  9. Removal of silver nanoparticles by coagulation processes

    International Nuclear Information System (INIS)

    Sun, Qian; Li, Yan; Tang, Ting; Yuan, Zhihua; Yu, Chang-Ping

    2013-01-01

    Highlights: • This study investigated the removal of AgNP suspensions by four regular coagulants. • The optimal removal efficiencies for the four coagulants were achieved at pH 7.5. • The removal efficiency of AgNPs was affected by the natural water characteristics. • TEM and XRD showed that AgNPs or silver-containing NPs were adsorbed onto the flocs. -- Abstract: Commercial use of silver nanoparticles (AgNPs) will lead to a potential route for human exposure via potable water. Coagulation followed by sedimentation, as a conventional technique in the drinking water treatment facilities, may become an important barrier to prevent human from AgNP exposures. This study investigated the removal of AgNP suspensions by four regular coagulants. In the aluminum sulfate and ferric chloride coagulation systems, the water parameters slightly affected the AgNP removal. However, in the poly aluminum chloride and polyferric sulfate coagulation systems, the optimal removal efficiencies were achieved at pH 7.5, while higher or lower of pH could reduce the AgNP removal. Besides, the increasing natural organic matter (NOM) would reduce the AgNP removal, while Ca 2+ and suspended solids concentrations would also affect the AgNP removal. In addition, results from the transmission electron microscopy and X-ray diffraction showed AgNPs or silver-containing nanoparticles were adsorbed onto the flocs. Finally, natural water samples were used to validate AgNP removal by coagulation. This study suggests that in the case of release of AgNPs into the source water, the traditional water treatment process, coagulation/sedimentation, can remove AgNPs and minimize the silver ion concentration under the well-optimized conditions

  10. Sn whiskers removed by energy photo flashing

    International Nuclear Information System (INIS)

    Jiang, N.; Yang, M.; Novak, J.; Igor, P.; Osterman, M.

    2012-01-01

    Highlights: ► Sn whiskers were sintered by intense light flashing (Photosintering). ► Photosintering can effectively eliminate Sn whiskers. ► Photosintering would not damage electronic devices. ► Photosintering is a very promising approach to improve Sn-based electronic surface termination. - Abstract: Sn whiskers have been known to be the major issue resulting in electronic circuit shorts. In this study, we present a novel energy photo flashing approach (photosintering) to shorten and eliminate Sn whiskers. It has been found that photosintering is very effective to modify and remove Sn whiskers; only a sub-millisecond duration photosintering can amazingly get rid of over 90 vol.% of Sn whiskers. Moreover, this photosintering approach has also been proved to cause no damages to electronic devices, suggesting it is a potentially promising way to improve Sn-based electronic surface termination.

  11. Consistency Analysis of Nearest Subspace Classifier

    OpenAIRE

    Wang, Yi

    2015-01-01

    The Nearest subspace classifier (NSS) finds an estimation of the underlying subspace within each class and assigns data points to the class that corresponds to its nearest subspace. This paper mainly studies how well NSS can be generalized to new samples. It is proved that NSS is strongly consistent under certain assumptions. For completeness, NSS is evaluated through experiments on various simulated and real data sets, in comparison with some other linear model based classifiers. It is also ...

  12. METHOD OF ELECTRON BEAM PROCESSING

    DEFF Research Database (Denmark)

    2003-01-01

    As a rule, electron beam welding takes place in a vacuum. However, this means that the workpieces in question have to be placed in a vacuum chamber and have to be removed therefrom after welding. This is time−consuming and a serious limitation of a process the greatest advantage of which is the o......As a rule, electron beam welding takes place in a vacuum. However, this means that the workpieces in question have to be placed in a vacuum chamber and have to be removed therefrom after welding. This is time−consuming and a serious limitation of a process the greatest advantage of which...... is the option of welding workpieces of large thicknesses. Therefore the idea is to guide the electron beam (2) to the workpiece via a hollow wire, said wire thereby acting as a prolongation of the vacuum chamber (4) down to workpiece. Thus, a workpiece need not be placed inside the vacuum chamber, thereby...... exploiting the potential of electron beam processing to a greater degree than previously possible, for example by means of electron beam welding...

  13. Waste water treatment plants with removal of nitrogens and phosphorous; Planta de tratamiento de aguas residuales con eliminacion de fosforo y nitrogeno

    Energy Technology Data Exchange (ETDEWEB)

    Kroiss, H.

    1996-10-01

    Wherever waste water is discharged into a receiving water of a sensitive area the treatment efficiency has to be increased beyond the removal of easily biodegradable carbonaceous compounds (BOD{sub 5}). The main requirements are then the removal of nitrogens and phosphorous compounds in order to prevent eutrophication in the receiving water. With these requirements a much better removal of carbonaceous matter is achieved too. One of this prerequisites for nitrogen removal is the nitrification process wich removes ammonia toxicity from the waste water. The removal of ammonia from the waste water can easily be monitored by the treatment plant operators and can be classified as the best indicator for a stable high treatment efficiency for every waste water.

  14. Phosphate removal from digested sludge supernatant using modified fly ash.

    Science.gov (United States)

    Xu, Ke; Deng, Tong; Liu, Juntan; Peng, Weigong

    2012-05-01

    The removal of phosphate in digested sludge supernatant by modified coal fly ash was investigated in this study. Modification of the fly ash by the addition of sulfuric acid could significantly enhance its immobilization ability. The experimental results also showed that adsorption of phosphate by the modified fly ash was rapid with the removal percentage of phosphate reaching an equilibrium of 98.62% in less than 5 minutes. The optimum pH for phosphate removal was 9 and the removal percentage increased with increasing adsorbent dosage. The effect of temperature on phosphate removal efficiency was not significant from 20 to 40 degrees C. X-ray diffraction and scanning electron microscope analyses showed that phosphate formed an amorphous precipitate with water-soluble calcium, aluminum, and iron ions in the modified fly ash.

  15. Verification of classified fissile material using unclassified attributes

    International Nuclear Information System (INIS)

    Nicholas, N.J.; Fearey, B.L.; Puckett, J.M.; Tape, J.W.

    1998-01-01

    This paper reports on the most recent efforts of US technical experts to explore verification by IAEA of unclassified attributes of classified excess fissile material. Two propositions are discussed: (1) that multiple unclassified attributes could be declared by the host nation and then verified (and reverified) by the IAEA in order to provide confidence in that declaration of a classified (or unclassified) inventory while protecting classified or sensitive information; and (2) that attributes could be measured, remeasured, or monitored to provide continuity of knowledge in a nonintrusive and unclassified manner. They believe attributes should relate to characteristics of excess weapons materials and should be verifiable and authenticatable with methods usable by IAEA inspectors. Further, attributes (along with the methods to measure them) must not reveal any classified information. The approach that the authors have taken is as follows: (1) assume certain attributes of classified excess material, (2) identify passive signatures, (3) determine range of applicable measurement physics, (4) develop a set of criteria to assess and select measurement technologies, (5) select existing instrumentation for proof-of-principle measurements and demonstration, and (6) develop and design information barriers to protect classified information. While the attribute verification concepts and measurements discussed in this paper appear promising, neither the attribute verification approach nor the measurement technologies have been fully developed, tested, and evaluated

  16. Reinforcement Learning Based Artificial Immune Classifier

    Directory of Open Access Journals (Sweden)

    Mehmet Karakose

    2013-01-01

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

  17. Electron Bifurcation: Thermodynamics and Kinetics of Two-Electron Brokering in Biological Redox Chemistry

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Peng; Yuly, Jonathon L.; Lubner, Carolyn E. [National Renewable Energy Laboratory, Golden, Colorado 80401, United States; Mulder, David W. [National Renewable Energy Laboratory, Golden, Colorado 80401, United States; King, Paul W. [National Renewable Energy Laboratory, Golden, Colorado 80401, United States; Peters, John W. [Institute; Beratan, David N. [Department

    2017-08-23

    How can proteins drive two electrons from a redox active donor onto two acceptors at very different potentials and distances? And how can this transaction be conducted without dissipating very much energy or violating the laws of thermodynamics? Nature appears to have addressed these challenges by coupling thermodynamically uphill and downhill electron transfer reactions, using two-electron donor cofactors that have very different potentials for the removal of the first and second electron. Although electron bifurcation is carried out with near perfection from the standpoint of energy conservation and electron delivery yields, it is a biological energy transduction paradigm that has only come into focus recently. This Account provides an exegesis of the biophysical principles that underpin electron bifurcation.

  18. Arsenic removal in a sulfidogenic fixed-bed column bioreactor

    Energy Technology Data Exchange (ETDEWEB)

    Altun, Muslum, E-mail: muslumaltun@hotmail.com [Hacettepe University, Department of Chemistry, Beytepe, Ankara (Turkey); Sahinkaya, Erkan [Istanbul Medeniyet University, Bioengineering Department, Goztepe, Istanbul (Turkey); Durukan, Ilknur; Bektas, Sema [Hacettepe University, Department of Chemistry, Beytepe, Ankara (Turkey); Komnitsas, Kostas [Technical University of Crete, Department of Mineral Resources Engineering, Chania (Greece)

    2014-03-01

    Highlights: • Sulfidogenic treatment of As-containing AMD was investigated. • High rate simultaneous removal of As and Fe was achieved. • As was removed without adding alkalinity or adjusting pH. • As and Fe removal mechanisms were elucidated. - Abstract: In the present study, the bioremoval of arsenic from synthetic acidic wastewater containing arsenate (As{sup 5+}) (0.5–20 mg/L), ferrous iron (Fe{sup 2+}) (100–200 mg/L) and sulfate (2000 mg/L) was investigated in an ethanol fed (780–1560 mg/L chemical oxygen demand (COD)) anaerobic up-flow fixed bed column bioreactor at constant hydraulic retention time (HRT) of 9.6 h. Arsenic removal efficiency was low and averaged 8% in case iron was not supplemented to the synthetic wastewater. Neutral to slightly alkaline pH and high sulfide concentration in the bioreactor retarded the precipitation of arsenic. Addition of 100 mg/L Fe{sup 2+} increased arsenic removal efficiency to 63%. Further increase of influent Fe{sup 2+} concentration to 200 mg/L improved arsenic removal to 85%. Decrease of influent COD concentration to its half, 780 mg/L, resulted in further increase of As removal to 96% when Fe{sup 2+} and As{sup 5+} concentrations remained at 200 mg/L and 20 mg/L, respectively. As a result of the sulfidogenic activity in the bioreactor the effluent pH and alkalinity concentration averaged 7.4 ± 0.2 and 1736 ± 239 mg CaCO{sub 3}/L respectively. Electron flow from ethanol to sulfate averaged 72 ± 10%. X-ray diffraction (XRD), X-ray fluorescence (XRF), scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS) analyses were carried out to identify the nature of the precipitate generated by sulfate reducing bacteria (SRB) activity. Precipitation of arsenic in the form of As{sub 2}S{sub 3} (orpiment) and co-precipitation with ferrous sulfide (FeS), pyrite (FeS{sub 2}) or arsenopyrite (FeAsS) were the main arsenic removal mechanisms.

  19. Intelligent Garbage Classifier

    Directory of Open Access Journals (Sweden)

    Ignacio Rodríguez Novelle

    2008-12-01

    Full Text Available IGC (Intelligent Garbage Classifier is a system for visual classification and separation of solid waste products. Currently, an important part of the separation effort is based on manual work, from household separation to industrial waste management. Taking advantage of the technologies currently available, a system has been built that can analyze images from a camera and control a robot arm and conveyor belt to automatically separate different kinds of waste.

  20. Correlation Dimension-Based Classifier

    Czech Academy of Sciences Publication Activity Database

    Jiřina, Marcel; Jiřina jr., M.

    2014-01-01

    Roč. 44, č. 12 (2014), s. 2253-2263 ISSN 2168-2267 R&D Projects: GA MŠk(CZ) LG12020 Institutional support: RVO:67985807 Keywords : classifier * multidimensional data * correlation dimension * scaling exponent * polynomial expansion Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 3.469, year: 2014

  1. Preparation of new conductive polymer nanocomposites for cadmium removal from industrial wastewaters

    International Nuclear Information System (INIS)

    Zoleikani, Leila; Issazadeh, Hossein; ZareNezhad, Bahman

    2015-01-01

    Different conductive polymer nanocomposites have been synthesized, characterized and tested, regarding the removal of cadmium from industrial wastewaters. The chemical structure and morphology are studied by FTIR spectroscopy, scanning electron microscopy (SEM) and X-ray diffraction (XRD). The cadmium removal performance, using the produced polypyrrole, polyaniline and polythiophene nanocomposites, are about 40.2 %, 59 % and 99.94 %, respectively, suggesting the superior performance of synthesized polythiophene conductive nanocomposite for cadmium removal from industrial wastewaters. It is shown that the Langmuir adsorption model can be used for accurate description of cadmium removal mechanism using different synthesized conductive nanocomposites. Keywords : wastewater, nanocomposite, polythiophene, cadmium removal, conductive polymer.

  2. Phenotype analysis of early risk factors from electronic medical records improves image-derived diagnostic classifiers for optic nerve pathology

    Science.gov (United States)

    Chaganti, Shikha; Nabar, Kunal P.; Nelson, Katrina M.; Mawn, Louise A.; Landman, Bennett A.

    2017-03-01

    We examine imaging and electronic medical records (EMR) of 588 subjects over five major disease groups that affect optic nerve function. An objective evaluation of the role of imaging and EMR data in diagnosis of these conditions would improve understanding of these diseases and help in early intervention. We developed an automated image processing pipeline that identifies the orbital structures within the human eyes from computed tomography (CT) scans, calculates structural size, and performs volume measurements. We customized the EMR-based phenome-wide association study (PheWAS) to derive diagnostic EMR phenotypes that occur at least two years prior to the onset of the conditions of interest from a separate cohort of 28,411 ophthalmology patients. We used random forest classifiers to evaluate the predictive power of image-derived markers, EMR phenotypes, and clinical visual assessments in identifying disease cohorts from a control group of 763 patients without optic nerve disease. Image-derived markers showed more predictive power than clinical visual assessments or EMR phenotypes. However, the addition of EMR phenotypes to the imaging markers improves the classification accuracy against controls: the AUC improved from 0.67 to 0.88 for glaucoma, 0.73 to 0.78 for intrinsic optic nerve disease, 0.72 to 0.76 for optic nerve edema, 0.72 to 0.77 for orbital inflammation, and 0.81 to 0.85 for thyroid eye disease. This study illustrates the importance of diagnostic context for interpretation of image-derived markers and the proposed PheWAS technique provides a flexible approach for learning salient features of patient history and incorporating these data into traditional machine learning analyses.

  3. An ensemble classifier to predict track geometry degradation

    International Nuclear Information System (INIS)

    Cárdenas-Gallo, Iván; Sarmiento, Carlos A.; Morales, Gilberto A.; Bolivar, Manuel A.; Akhavan-Tabatabaei, Raha

    2017-01-01

    Railway operations are inherently complex and source of several problems. In particular, track geometry defects are one of the leading causes of train accidents in the United States. This paper presents a solution approach which entails the construction of an ensemble classifier to forecast the degradation of track geometry. Our classifier is constructed by solving the problem from three different perspectives: deterioration, regression and classification. We considered a different model from each perspective and our results show that using an ensemble method improves the predictive performance. - Highlights: • We present an ensemble classifier to forecast the degradation of track geometry. • Our classifier considers three perspectives: deterioration, regression and classification. • We construct and test three models and our results show that using an ensemble method improves the predictive performance.

  4. Data characteristics that determine classifier performance

    CSIR Research Space (South Africa)

    Van der Walt, Christiaan M

    2006-11-01

    Full Text Available available at [11]. The kNN uses a LinearNN nearest neighbour search algorithm with an Euclidean distance metric [8]. The optimal k value is determined by performing 10-fold cross-validation. An optimal k value between 1 and 10 is used for Experiments 1... classifiers. 10-fold cross-validation is used to evaluate and compare the performance of the classifiers on the different data sets. 3.1. Artificial data generation Multivariate Gaussian distributions are used to generate artificial data sets. We use d...

  5. Classifying images using restricted Boltzmann machines and convolutional neural networks

    Science.gov (United States)

    Zhao, Zhijun; Xu, Tongde; Dai, Chenyu

    2017-07-01

    To improve the feature recognition ability of deep model transfer learning, we propose a hybrid deep transfer learning method for image classification based on restricted Boltzmann machines (RBM) and convolutional neural networks (CNNs). It integrates learning abilities of two models, which conducts subject classification by exacting structural higher-order statistics features of images. While the method transfers the trained convolutional neural networks to the target datasets, fully-connected layers can be replaced by restricted Boltzmann machine layers; then the restricted Boltzmann machine layers and Softmax classifier are retrained, and BP neural network can be used to fine-tuned the hybrid model. The restricted Boltzmann machine layers has not only fully integrated the whole feature maps, but also learns the statistical features of target datasets in the view of the biggest logarithmic likelihood, thus removing the effects caused by the content differences between datasets. The experimental results show that the proposed method has improved the accuracy of image classification, outperforming other methods on Pascal VOC2007 and Caltech101 datasets.

  6. Disassembly and Sanitization of Classified Matter

    International Nuclear Information System (INIS)

    Stockham, Dwight J.; Saad, Max P.

    2008-01-01

    The Disassembly Sanitization Operation (DSO) process was implemented to support weapon disassembly and disposition by using recycling and waste minimization measures. This process was initiated by treaty agreements and reconfigurations within both the DOD and DOE Complexes. The DOE is faced with disassembling and disposing of a huge inventory of retired weapons, components, training equipment, spare parts, weapon maintenance equipment, and associated material. In addition, regulations have caused a dramatic increase in the need for information required to support the handling and disposition of these parts and materials. In the past, huge inventories of classified weapon components were required to have long-term storage at Sandia and at many other locations throughout the DoE Complex. These materials are placed in onsite storage unit due to classification issues and they may also contain radiological and/or hazardous components. Since no disposal options exist for this material, the only choice was long-term storage. Long-term storage is costly and somewhat problematic, requiring a secured storage area, monitoring, auditing, and presenting the potential for loss or theft of the material. Overall recycling rates for materials sent through the DSO process have enabled 70 to 80% of these components to be recycled. These components are made of high quality materials and once this material has been sanitized, the demand for the component metals for recycling efforts is very high. The DSO process for NGPF, classified components established the credibility of this technique for addressing the long-term storage requirements of the classified weapons component inventory. The success of this application has generated interest from other Sandia organizations and other locations throughout the complex. Other organizations are requesting the help of the DSO team and the DSO is responding to these requests by expanding its scope to include Work-for- Other projects. For example

  7. A Robust and Fast Computation Touchless Palm Print Recognition System Using LHEAT and the IFkNCN Classifier

    Directory of Open Access Journals (Sweden)

    Haryati Jaafar

    2015-01-01

    Full Text Available Mobile implementation is a current trend in biometric design. This paper proposes a new approach to palm print recognition, in which smart phones are used to capture palm print images at a distance. A touchless system was developed because of public demand for privacy and sanitation. Robust hand tracking, image enhancement, and fast computation processing algorithms are required for effective touchless and mobile-based recognition. In this project, hand tracking and the region of interest (ROI extraction method were discussed. A sliding neighborhood operation with local histogram equalization, followed by a local adaptive thresholding or LHEAT approach, was proposed in the image enhancement stage to manage low-quality palm print images. To accelerate the recognition process, a new classifier, improved fuzzy-based k nearest centroid neighbor (IFkNCN, was implemented. By removing outliers and reducing the amount of training data, this classifier exhibited faster computation. Our experimental results demonstrate that a touchless palm print system using LHEAT and IFkNCN achieves a promising recognition rate of 98.64%.

  8. Characterization of banana peel by scanning electron microscopy and FT-IR spectroscopy and its use for cadmium removal.

    Science.gov (United States)

    Memon, Jamil R; Memon, Saima Q; Bhanger, M I; Memon, G Zuhra; El-Turki, A; Allen, Geoffrey C

    2008-10-15

    This study describes the use of banana peel, a commonly produced fruit waste, for the removal of Cd(II) from environmental and industrial wastewater. The banana peel was characterized by FT-IR and scanning electron microscopy (SEM) coupled with energy dispersive X-ray (EDX) analysis. The parameters pH, contact time, initial metal ion concentration and temperature were investigated and found to be rapid ( approximately 97% within 10 min). The Langmuir adsorption isotherm was used to describe partitioning behavior for the system at room temperature. The value of Q(L) was found to be (35.52 mg g(-1)) higher than the previously reported materials. The binding of metal ions was found to be pH-dependent with the optimal sorption occurring at pH 8. The retained species were eluted with 5 mL of 5 x 10(-3)M HNO(3) with the detection limit of 1.7 x 10(-3)mg L(-1). Kinetics of sorption followed the pseudo-first-order rate equation with the rate constant k, equal to 0.13+/-0.01 min(-1). Thermodynamic parameters such as Gibbs free energy at 303K (-7.41+/-0.13 kJ mol(-1)) and enthalpy (40.56+/-2.34 kJ mol(-1)) indicated the spontaneous and endothermic nature of the sorption process. The developed method was utilized for the removal of Cd(II) ions from environmental and industrial wastewater samples using flame atomic absorption spectrophotometer (FAAS).

  9. The Dismantling Project for the Large Electron Positron (LEP) Collider

    CERN Document Server

    Poole, John

    2002-01-01

    The LEP accelerator was installed in a circular tunnel 27 km in length with nine access points distributed around the circumference in the countryside and villages which surround CERN's sites. The dismantling project involved the removal in less than 15 months of around 29000 tonnes of equipment from the accelerator itself and a further 10000 tonnes from the four experiments - all of which were located at an average depth of 100 m below ground level. There was no contamination risk in the project and less than 3% of the materials removed were classified as radioactive. However, the materials which were classified as radioactive have to be temporarily stored and they consume considerable resources. The major difficulties for the project were in the establishment of the theoretical radiological zoning, implementation of the traceability systems and making appropriate radiation measurements to confirm the zoning. The absence of detailed guidelines from the French authorities, having no threshold levels for relea...

  10. Frog sound identification using extended k-nearest neighbor classifier

    Science.gov (United States)

    Mukahar, Nordiana; Affendi Rosdi, Bakhtiar; Athiar Ramli, Dzati; Jaafar, Haryati

    2017-09-01

    Frog sound identification based on the vocalization becomes important for biological research and environmental monitoring. As a result, different types of feature extractions and classifiers have been employed to evaluate the accuracy of frog sound identification. This paper presents a frog sound identification with Extended k-Nearest Neighbor (EKNN) classifier. The EKNN classifier integrates the nearest neighbors and mutual sharing of neighborhood concepts, with the aims of improving the classification performance. It makes a prediction based on who are the nearest neighbors of the testing sample and who consider the testing sample as their nearest neighbors. In order to evaluate the classification performance in frog sound identification, the EKNN classifier is compared with competing classifier, k -Nearest Neighbor (KNN), Fuzzy k -Nearest Neighbor (FKNN) k - General Nearest Neighbor (KGNN)and Mutual k -Nearest Neighbor (MKNN) on the recorded sounds of 15 frog species obtained in Malaysia forest. The recorded sounds have been segmented using Short Time Energy and Short Time Average Zero Crossing Rate (STE+STAZCR), sinusoidal modeling (SM), manual and the combination of Energy (E) and Zero Crossing Rate (ZCR) (E+ZCR) while the features are extracted by Mel Frequency Cepstrum Coefficient (MFCC). The experimental results have shown that the EKNCN classifier exhibits the best performance in terms of accuracy compared to the competing classifiers, KNN, FKNN, GKNN and MKNN for all cases.

  11. Intelligent Image Analysis for Image-Guided Laser Hair Removal and Skin Therapy

    Science.gov (United States)

    Walker, Brian; Lu, Thomas; Chao, Tien-Hsin

    2012-01-01

    We present the development of advanced automatic target recognition (ATR) algorithms for the hair follicles identification in digital skin images to accurately direct the laser beam to remove the hair. The ATR system first performs a wavelet filtering to enhance the contrast of the hair features in the image. The system then extracts the unique features of the targets and sends the features to an Adaboost based classifier for training and recognition operations. The ATR system automatically classifies the hair, moles, or other skin lesion and provides the accurate coordinates of the intended hair follicle locations. The coordinates can be used to guide a scanning laser to focus energy only on the hair follicles. The intended benefit would be to protect the skin from unwanted laser exposure and to provide more effective skin therapy.

  12. Graphene oxide/ferric hydroxide composites for efficient arsenate removal from drinking water

    International Nuclear Information System (INIS)

    Zhang Kai; Dwivedi, Vineet; Chi Chunyan; Wu Jishan

    2010-01-01

    A series of novel composites based on graphene oxide (GO) cross-linked with ferric hydroxide was developed for effective removal of arsenate from contaminated drinking water. GO, which was used as a supporting matrix here, was firstly treated with ferrous sulfate. Then, the ferrous compound cross-linked with GO was in situ oxidized to ferric compound by hydrogen peroxide, followed by treating with ammonium hydroxide. The morphology and composition of the composites were analyzed by X-ray diffraction, scanning electron microscopy and transmission electron microscopy. The ferric hydroxide was found to be homogenously impregnated onto GO sheets in amorphous form. These composites were evaluated as absorbents for arsenate removal from contaminated drinking water. For the water with arsenate concentration at 51.14 ppm, more than 95% of arsenate was absorbed by composite GO-Fe-5 with an absorption capacity of 23.78 mg arsenate/g of composite. Effective arsenate removal occurred in a wide range of pH from 4 to 9. However, the efficiency of arsenate removal was decreased when pH was increased to higher than 8.

  13. Enhanced azo dye removal in a continuously operated up-flow anaerobic filter packed with henna plant biomass

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Jingang, E-mail: hjg@hdu.edu.cn [Institute of Environmental Science and Engineering, Hangzhou Dianzi University, Hangzhou 310018 (China); State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092 (China); Wu, Mengke; Chen, Jianjun; Liu, Xiuyan; Chen, Tingting [Institute of Environmental Science and Engineering, Hangzhou Dianzi University, Hangzhou 310018 (China); Wen, Yue [State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092 (China); Tang, Junhong; Xie, Zhengmiao [Institute of Environmental Science and Engineering, Hangzhou Dianzi University, Hangzhou 310018 (China)

    2015-12-15

    Highlights: • Henna stem mixed with ceramic media in UAF enhanced the removal of AO7. • Bio-reduction was the main AO7 removal pathway in henna-added UAF. • Adsorption and endogenous reduction were the main removal pathways in the control. • Henna played a multiple role in providing electron donors and redox mediator. - Abstract: Effects of henna plant biomass (stem) packed in an up-flow anaerobic bio-filter (UAF) on an azo dye (AO7) removal were investigated. AO7 removal, sulfanilic acid (SA) formation, and pseudo first-order kinetic constants for these reactions (k{sub AO7} and k{sub SA}) were higher in the henna-added UAF (R2) than in the control UAF without henna (R1). The maximum k{sub AO7} in R1 and R2 were 0.0345 and 0.2024 cm{sup −1}, respectively, on day 18; the corresponding molar ratios of SA formation to AO7 removal were 0.582 and 0.990. Adsorption and endogenous bio-reduction were the main AO7 removal pathways in R1, while in R2 bio-reduction was the dominant. Organics in henna could be released and fermented to volatile fatty acids, acting as effective electron donors for AO7 reduction, which was accelerated by soluble and/or fixed lawsone. Afterwards, the removal process weakened over time, indicating the demand of electron donation and lawsone-releasing during the long-term operation of UAF.

  14. 32 CFR 2400.30 - Reproduction of classified information.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Reproduction of classified information. 2400.30... SECURITY PROGRAM Safeguarding § 2400.30 Reproduction of classified information. Documents or portions of... the originator or higher authority. Any stated prohibition against reproduction shall be strictly...

  15. Electron linacs

    Energy Technology Data Exchange (ETDEWEB)

    Loew, G A; Schriber, S O [ed.

    1976-11-01

    A study was made of the present status of the thousand or so electron linacs in the world, and future trends in the field. These machines were classified according to their use: medical, industrial, and nuclear physics. In the medical category, two types of electron linacs are discussed: the conventional ones which are used for x-ray and electron therapy, and those which may in the future be used for negative pion therapy. Industrial machines discussed include linacs for radiographic and other specialized applications. In the nuclear physics category, the status of conventional low- and medium-energy as well as high duty cycle linacs is reviewed. The question of how one might obtain a c-w, 1 GeV, 100..mu..A electron linac is raised, and various options using recirculation and stretchers are examined. In this connection, the status of rf superconductivity is summarized. A review is given of linacs for injectors into synchrotrons and e/sup +-/ storage rings, and recent work done to upgrade the only multi-GeV linac, namely SLAC, is described.

  16. Electron linacs

    International Nuclear Information System (INIS)

    Loew, G.A.

    1976-01-01

    To study the present status of the thousand or so electron linacs in the world, and future trends in the field, we have classified these machines according to their use: medical, industrial, and nuclear physics. In the medical category, two types of electron linacs are discussed: the conventional ones which are used for X-ray and electron therapy, and those which may in the future be used for negative pion therapy. The section on industrial machines includes linacs for radiographic and other specialized applications. In the nuclear physics category, the status of conventional low- and medium-energy as well as high duty cycle linacs is reviewed. The question of how one might obtain a C.W., 1 GeV, 100 μA electron linac is raised and various options using recirculation and stretchers are examined. In this connection, the status of RF superconductivity is summarized. Following, there is a review of linacs for injectors into synchrotrons and e +- storage rings. The paper ends with a description of recent work done to upgrade the only multi-GeV linac, namely SLAC. (author)

  17. Removal of uranium from gravel using soil washing method

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Ilgook; Kim, Kye-Nam; Kim, Seung-Soo; Choi, Jong-Won [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2015-10-15

    The development of nuclear technology has led to increasing radioactive waste containing uranium being released and disposed in the nuclear sites. Fine grained soils with a size of less than 4 mm are normally decontaminated using soil washing and electro-kinetic technologies. However, there have been few studies on the decontamination of gravels with a size of more than 4 mm. Therefore, it is necessary to study the decontamination of gravel contaminated with radionuclides. The main objective of the present study on soil washing was to define the optimal condition for acid treatment of uranium-polluted gravel. In this study, soil washing method was applied to remove uranium from gravel. The gravel was crushed and classified as particle sizes. The gravel particles were treated with sulfuric acid in a shaking incubator at 60 .deg. C and 150 rpm for 3 h. The optimal particle size of gravel for soil washing in removal of uranium was between 0.45 and 2.0 mm.

  18. Three data partitioning strategies for building local classifiers (Chapter 14)

    NARCIS (Netherlands)

    Zliobaite, I.; Okun, O.; Valentini, G.; Re, M.

    2011-01-01

    Divide-and-conquer approach has been recognized in multiple classifier systems aiming to utilize local expertise of individual classifiers. In this study we experimentally investigate three strategies for building local classifiers that are based on different routines of sampling data for training.

  19. 32 CFR 2001.23 - Classification marking in the electronic environment.

    Science.gov (United States)

    2010-07-01

    ... environment. 2001.23 Section 2001.23 National Defense Other Regulations Relating to National Defense... environment. (a) General. Classified national security information in the electronic environment shall be: (1... electronic environment cannot be marked in this manner, a warning shall be applied to alert users that the...

  20. High electron mobility InN

    International Nuclear Information System (INIS)

    Jones, R. E.; Li, S. X.; Haller, E. E.; van Genuchten, H. C. M.; Yu, K. M.; Ager, J. W. III; Liliental-Weber, Z.; Walukiewicz, W.; Lu, H.; Schaff, W. J.

    2007-01-01

    Irradiation of InN films with 2 MeV He + ions followed by thermal annealing below 500 deg. C creates films with high electron concentrations and mobilities, as well as strong photoluminescence. Calculations show that electron mobility in irradiated samples is limited by triply charged donor defects. Subsequent thermal annealing removes a fraction of the defects, decreasing the electron concentration. There is a large increase in electron mobility upon annealing; the mobilities approach those of the as-grown films, which have 10 to 100 times smaller electron concentrations. Spatial ordering of the triply charged defects is suggested to cause the unusual increase in electron mobility

  1. Robust Combining of Disparate Classifiers Through Order Statistics

    Science.gov (United States)

    Tumer, Kagan; Ghosh, Joydeep

    2001-01-01

    Integrating the outputs of multiple classifiers via combiners or meta-learners has led to substantial improvements in several difficult pattern recognition problems. In this article we investigate a family of combiners based on order statistics, for robust handling of situations where there are large discrepancies in performance of individual classifiers. Based on a mathematical modeling of how the decision boundaries are affected by order statistic combiners, we derive expressions for the reductions in error expected when simple output combination methods based on the the median, the maximum and in general, the ith order statistic, are used. Furthermore, we analyze the trim and spread combiners, both based on linear combinations of the ordered classifier outputs, and show that in the presence of uneven classifier performance, they often provide substantial gains over both linear and simple order statistics combiners. Experimental results on both real world data and standard public domain data sets corroborate these findings.

  2. Knowledge Uncertainty and Composed Classifier

    Czech Academy of Sciences Publication Activity Database

    Klimešová, Dana; Ocelíková, E.

    2007-01-01

    Roč. 1, č. 2 (2007), s. 101-105 ISSN 1998-0140 Institutional research plan: CEZ:AV0Z10750506 Keywords : Boosting architecture * contextual modelling * composed classifier * knowledge management, * knowledge * uncertainty Subject RIV: IN - Informatics, Computer Science

  3. An overview of electron acceptors in microbial fuel cells

    DEFF Research Database (Denmark)

    Ucar, Deniz; Zhang, Yifeng; Angelidaki, Irini

    2017-01-01

    Microbial fuel cells (MFC) have recently received increasing attention due to their promising potential in sustainable wastewater treatment and contaminant removal. In general, contaminants can be removed either as an electron donor via microbial catalyzed oxidization at the anode or removed at t...... acceptors (e.g., nitrate, iron, copper, perchlorate) and mediators....

  4. Investigation of the mechanism of mercury removal from a silver dental amalgam alloy

    Directory of Open Access Journals (Sweden)

    M. DJURDJEVIC

    2004-12-01

    Full Text Available An investigation of silver dental amalgam decomposition and the mercury removal mechanism was performed. The decomposition process was analysed during thermal treatment in the temperature interval from 400 °C to 850 °C and for times from 0.5 to 7.5 h. The chemical compositions of the silver dental amalgam alloy and the treated alloy were tested and microstructure analysis using optical and scanning electron microscopy was carried out. The phases were identified using energy disperse electron probe microanalysis. A mechanism for the mercury removal process from silver dental amalgam alloy is suggested.

  5. Robust Template Decomposition without Weight Restriction for Cellular Neural Networks Implementing Arbitrary Boolean Functions Using Support Vector Classifiers

    Directory of Open Access Journals (Sweden)

    Yih-Lon Lin

    2013-01-01

    Full Text Available If the given Boolean function is linearly separable, a robust uncoupled cellular neural network can be designed as a maximal margin classifier. On the other hand, if the given Boolean function is linearly separable but has a small geometric margin or it is not linearly separable, a popular approach is to find a sequence of robust uncoupled cellular neural networks implementing the given Boolean function. In the past research works using this approach, the control template parameters and thresholds are restricted to assume only a given finite set of integers, and this is certainly unnecessary for the template design. In this study, we try to remove this restriction. Minterm- and maxterm-based decomposition algorithms utilizing the soft margin and maximal margin support vector classifiers are proposed to design a sequence of robust templates implementing an arbitrary Boolean function. Several illustrative examples are simulated to demonstrate the efficiency of the proposed method by comparing our results with those produced by other decomposition methods with restricted weights.

  6. Electronic Nose Technology to Measure Soil Microbial Activity and Classify Soil Metabolic Status

    OpenAIRE

    Fabrizio De Cesare; Elena Di Mattia; Simone Pantalei; Emiliano Zampetti; Vittorio Vinciguerra; Antonella Macagnano

    2011-01-01

    The electronic nose (E-nose) is a sensing technology that has been widely used to monitor environments in the last decade. In the present study, the capability of an E-nose, in combination with biochemical and microbiological techniques, of both detecting the microbial activity and estimating the metabolic status of soil ecosystems, was tested by measuring on one side respiration, enzyme activities and growth of bacteria in natural but simplified soil ecosystems over 23 days of incubation thr...

  7. The decision tree classifier - Design and potential. [for Landsat-1 data

    Science.gov (United States)

    Hauska, H.; Swain, P. H.

    1975-01-01

    A new classifier has been developed for the computerized analysis of remote sensor data. The decision tree classifier is essentially a maximum likelihood classifier using multistage decision logic. It is characterized by the fact that an unknown sample can be classified into a class using one or several decision functions in a successive manner. The classifier is applied to the analysis of data sensed by Landsat-1 over Kenosha Pass, Colorado. The classifier is illustrated by a tree diagram which for processing purposes is encoded as a string of symbols such that there is a unique one-to-one relationship between string and decision tree.

  8. Representative Vector Machines: A Unified Framework for Classical Classifiers.

    Science.gov (United States)

    Gui, Jie; Liu, Tongliang; Tao, Dacheng; Sun, Zhenan; Tan, Tieniu

    2016-08-01

    Classifier design is a fundamental problem in pattern recognition. A variety of pattern classification methods such as the nearest neighbor (NN) classifier, support vector machine (SVM), and sparse representation-based classification (SRC) have been proposed in the literature. These typical and widely used classifiers were originally developed from different theory or application motivations and they are conventionally treated as independent and specific solutions for pattern classification. This paper proposes a novel pattern classification framework, namely, representative vector machines (or RVMs for short). The basic idea of RVMs is to assign the class label of a test example according to its nearest representative vector. The contributions of RVMs are twofold. On one hand, the proposed RVMs establish a unified framework of classical classifiers because NN, SVM, and SRC can be interpreted as the special cases of RVMs with different definitions of representative vectors. Thus, the underlying relationship among a number of classical classifiers is revealed for better understanding of pattern classification. On the other hand, novel and advanced classifiers are inspired in the framework of RVMs. For example, a robust pattern classification method called discriminant vector machine (DVM) is motivated from RVMs. Given a test example, DVM first finds its k -NNs and then performs classification based on the robust M-estimator and manifold regularization. Extensive experimental evaluations on a variety of visual recognition tasks such as face recognition (Yale and face recognition grand challenge databases), object categorization (Caltech-101 dataset), and action recognition (Action Similarity LAbeliNg) demonstrate the advantages of DVM over other classifiers.

  9. Ammonium nitrogen removal from coking wastewater by chemical precipitation recycle technology.

    Science.gov (United States)

    Zhang, Tao; Ding, Lili; Ren, Hongqiang; Xiong, Xiang

    2009-12-01

    Ammonium nitrogen removal from wastewater has been of considerable concern for several decades. In the present research, we examined chemical precipitation recycle technology (CPRT) for ammonium nitrogen removal from coking wastewater. The pyrolysate resulting from magnesium ammonium phosphate (MAP) pyrogenation in sodium hydroxide (NaOH) solution was recycled for ammonium nitrogen removal from coking wastewater. The objective of this study was to investigate the conditions for MAP pyrogenation and to characterize of MAP pyrolysate for its feasibility in recycling. Furthermore, MAP pyrolysate was characterized by scanning electron microscope (FESEM), transmission electron microscope (TEM), Fourier transform infrared spectroscopy (FTIR) as well as X-ray diffraction (XRD). The MAP pyrolysate could be produced at the optimal condition of a hydroxyl (OH(-)) to ammonium molar ratio of 2:1, a heating temperature of 110 degrees C, and a heating time of 3h. Surface characterization analysis indicated that the main component of the pyrolysate was amorphous magnesium sodium phosphate (MgNaPO(4)). The pyrolysate could be recycled as a magnesium and phosphate source at an optimum pH of 9.5. When the recycle times were increased, the ammonium nitrogen removal ratio gradually decreased if the pyrolysate was used without supplementation. When the recycle times were increased, the ammonium nitrogen removal efficiency was not decreased if the added pyrolysate was supplemented with MgCl(2).6H(2)O plus Na(2)HPO(4).12H(2)O during treatment. A high ammonium nitrogen removal ratio was obtained by using pre-formed MAP as seeding material.

  10. 41 CFR 105-62.102 - Authority to originally classify.

    Science.gov (United States)

    2010-07-01

    ... originally classify. (a) Top secret, secret, and confidential. The authority to originally classify information as Top Secret, Secret, or Confidential may be exercised only by the Administrator and is delegable...

  11. Spatial and temporal correlation in dynamic, multi-electron quantum systems

    Energy Technology Data Exchange (ETDEWEB)

    Godunov, A.L.; McGuire, J.H.; Shakov, Kh.Kh. [Department of Physics, Tulane University, New Orleans, LA (United States); Ivanov, P.B.; Shipakov, V.A. [Troitsk Institute for Innovation and Fusion Research, Troitsk (Russian Federation); Merabet, H.; Bruch, R.; Hanni, J. [Department of Physics, University of Nevada Reno, Reno, NV (United States)

    2001-12-28

    Cross sections for ionization with excitation and for double excitation in helium are evaluated in a full second Born calculation. These full second Born calculations are compared to calculations in the independent electron approximation, where spatial correlation between the electrons is removed. Comparison is also made to calculations in the independent time approximation, where time correlation between the electrons is removed. The two-electron transitions considered here are caused by interactions with incident protons and electrons with velocities ranging between 2 and 10 au. Good agreement is found between our full calculations and experiment, except for the lowest velocities, where higher Born terms are expected to be significant. Spatial electron correlation, arising from internal electron-electron interactions, and time correlation, arising from time ordering of the external interactions, can both give rise to observable effects. Our method may be used for photon impact. (author)

  12. Copper removal using electrosterically stabilized nanocrystalline cellulose.

    Science.gov (United States)

    Sheikhi, Amir; Safari, Salman; Yang, Han; van de Ven, Theo G M

    2015-06-03

    Removal of heavy metal ions such as copper using an efficient and low-cost method with low ecological footprint is a critical process in wastewater treatment, which can be achieved in a liquid phase using nanoadsorbents such as inorganic nanoparticles. Recently, attention has turned toward developing sustainable and environmentally friendly nanoadsorbents to remove heavy metal ions from aqueous media. Electrosterically stabilized nanocrystalline cellulose (ENCC), which can be prepared from wood fibers through periodate/chlorite oxidation, has been shown to have a high charge content and colloidal stability. Here, we show that ENCC scavenges copper ions by different mechanisms depending on the ion concentration. When the Cu(II) concentration is low (C0≲200 ppm), agglomerates of starlike ENCC particles appear, which are broken into individual starlike entities by shear and Brownian motion, as evidenced by photometric dispersion analysis, dynamic light scattering, and transmission electron microscopy. On the other hand, at higher copper concentrations, the aggregate morphology changes from starlike to raftlike, which is probably due to the collapse of protruding dicarboxylic cellulose (DCC) chains and ENCC charge neutralization by copper adsorption. Such raftlike structures result from head-to-head and lateral aggregation of neutralized ENCCs as confirmed by transmission electron microscopy. As opposed to starlike aggregates, the raftlike structures grow gradually and are prone to sedimentation at copper concentrations C0≳500 ppm, which eliminates a costly separation step in wastewater treatment processes. Moreover, a copper removal capacity of ∼185 mg g(-1) was achieved thanks to the highly charged DCC polyanions protruding from ENCC. These properties along with the biorenewability make ENCC a promising candidate for wastewater treatment, in which fast, facile, and low-cost removal of heavy metal ions is desired most.

  13. Hexavalent chromium removal using aerobic activated sludge batch ...

    African Journals Online (AJOL)

    The following Cr(VI) removal systems were tested: activated sludge alone; activated sludge with an external electron donor (5 g/. of lactose); activated sludge with PAC addition (4 g/.); activated sludge with both PAC and lactose; and PAC alone. The results reported here showed that activated sludges are capable of ...

  14. DEVICES FOR COOLING ELECTRONIC CIRCUIT BOARDS

    OpenAIRE

    T. A. Ismailov; D. V. Evdulov; A. G. Mustafaev; D. K. Ramazanova

    2014-01-01

    In the work described structural variants of devices for cooling electronic circuit boards, made on the basis of thermoelectric batteries and consumable working substances, implementing uneven process of removing heat from heat-generating components. A comparison of temperature fields of electronic circuit simulator with his uniform and non-uniform cooling. 

  15. Method of fabricating a cooled electronic system

    Science.gov (United States)

    Chainer, Timothy J; Gaynes, Michael A; Graybill, David P; Iyengar, Madhusudan K; Kamath, Vinod; Kochuparambil, Bejoy J; Schmidt, Roger R; Schultz, Mark D; Simco, Daniel P; Steinke, Mark E

    2014-02-11

    A method of fabricating a liquid-cooled electronic system is provided which includes an electronic assembly having an electronics card and a socket with a latch at one end. The latch facilitates securing of the card within the socket. The method includes providing a liquid-cooled cold rail at the one end of the socket, and a thermal spreader to couple the electronics card to the cold rail. The thermal spreader includes first and second thermal transfer plates coupled to first and second surfaces on opposite sides of the card, and thermally conductive extensions extending from end edges of the plates, which couple the respective transfer plates to the liquid-cooled cold rail. The extensions are disposed to the sides of the latch, and the card is securable within or removable from the socket using the latch without removing the cold rail or the thermal spreader.

  16. A media maniac's guide to removable mass storage media

    Science.gov (United States)

    Kempster, Linda S.

    1996-01-01

    This paper addresses at a high level, the many individual technologies available today in the removable storage arena including removable magnetic tapes, magnetic floppies, optical disks and optical tape. Tape recorders represented below discuss logitudinal, serpantine, logitudinal serpantine,and helical scan technologies. The magnetic floppies discussed will be used for personal electronic in-box applications.Optical disks still fill the role for dense long-term storage. The media capacities quoted are for native data. In some cases, 2 KB ASC2 pages or 50 KB document images will be referenced.

  17. A cardiorespiratory classifier of voluntary and involuntary electrodermal activity

    Directory of Open Access Journals (Sweden)

    Sejdic Ervin

    2010-02-01

    Full Text Available Abstract Background Electrodermal reactions (EDRs can be attributed to many origins, including spontaneous fluctuations of electrodermal activity (EDA and stimuli such as deep inspirations, voluntary mental activity and startling events. In fields that use EDA as a measure of psychophysiological state, the fact that EDRs may be elicited from many different stimuli is often ignored. This study attempts to classify observed EDRs as voluntary (i.e., generated from intentional respiratory or mental activity or involuntary (i.e., generated from startling events or spontaneous electrodermal fluctuations. Methods Eight able-bodied participants were subjected to conditions that would cause a change in EDA: music imagery, startling noises, and deep inspirations. A user-centered cardiorespiratory classifier consisting of 1 an EDR detector, 2 a respiratory filter and 3 a cardiorespiratory filter was developed to automatically detect a participant's EDRs and to classify the origin of their stimulation as voluntary or involuntary. Results Detected EDRs were classified with a positive predictive value of 78%, a negative predictive value of 81% and an overall accuracy of 78%. Without the classifier, EDRs could only be correctly attributed as voluntary or involuntary with an accuracy of 50%. Conclusions The proposed classifier may enable investigators to form more accurate interpretations of electrodermal activity as a measure of an individual's psychophysiological state.

  18. The prognostic value of visually assessing enamel microcracks: Do debonding and adhesive removal contribute to their increase?

    Science.gov (United States)

    Dumbryte, Irma; Jonavicius, Tomas; Linkeviciene, Laura; Linkevicius, Tomas; Peciuliene, Vytaute; Malinauskas, Mangirdas

    2016-05-01

    To find a correlation between the severity of enamel microcracks (EMCs) and their increase during debonding and residual adhesive removal (RAR). Following their examination with scanning electron microscopy (SEM), 90 extracted human premolars were divided into three groups of 30: group 1, teeth having pronounced EMCs (visible with the naked eye under normal room illumination); group 2, teeth showing weak EMCs (not apparent under normal room illumination but visible by SEM); and group 3, a control group. EMCs have been classified into weak and pronounced, based on their visibility. Metal brackets (MB) and ceramic brackets (CB), 15 of each type, were bonded to all the teeth from groups 1 and 2. Debonding was performed with pliers, followed by RAR. The location, length, and width of the longest EMCs were measured using SEM before and after debonding. The mean overall width (Woverall) was higher for pronounced EMCs before and after debonding CB (P < .05), and after the removal of MB. Pronounced EMCs showed greater length values using both types of brackets. After debonding, the increase in Woverall of pronounced EMCs was 0.57 µm with MB (P < .05) and 0.30 µm with CB; for weak EMCs, - 0.32 µm with MB and 0.30 µm with CB. Although the teeth having pronounced EMCs showed higher width and length values, this did not predispose to greater EMCs increase after debonding MB and CB followed by RAR.

  19. Learning to classify wakes from local sensory information

    Science.gov (United States)

    Alsalman, Mohamad; Colvert, Brendan; Kanso, Eva; Kanso Team

    2017-11-01

    Aquatic organisms exhibit remarkable abilities to sense local flow signals contained in their fluid environment and to surmise the origins of these flows. For example, fish can discern the information contained in various flow structures and utilize this information for obstacle avoidance and prey tracking. Flow structures created by flapping and swimming bodies are well characterized in the fluid dynamics literature; however, such characterization relies on classical methods that use an external observer to reconstruct global flow fields. The reconstructed flows, or wakes, are then classified according to the unsteady vortex patterns. Here, we propose a new approach for wake identification: we classify the wakes resulting from a flapping airfoil by applying machine learning algorithms to local flow information. In particular, we simulate the wakes of an oscillating airfoil in an incoming flow, extract the downstream vorticity information, and train a classifier to learn the different flow structures and classify new ones. This data-driven approach provides a promising framework for underwater navigation and detection in application to autonomous bio-inspired vehicles.

  20. Bayesian Classifier for Medical Data from Doppler Unit

    Directory of Open Access Journals (Sweden)

    J. Málek

    2006-01-01

    Full Text Available Nowadays, hand-held ultrasonic Doppler units (probes are often used for noninvasive screening of atherosclerosis in the arteries of the lower limbs. The mean velocity of blood flow in time and blood pressures are measured on several positions on each lower limb. By listening to the acoustic signal generated by the device or by reading the signal displayed on screen, a specialist can detect peripheral arterial disease (PAD.This project aims to design software that will be able to analyze data from such a device and classify it into several diagnostic classes. At the Department of Functional Diagnostics at the Regional Hospital in Liberec a database of several hundreds signals was collected. In cooperation with the specialist, the signals were manually classified into four classes. For each class, selected signal features were extracted and then used for training a Bayesian classifier. Another set of signals was used for evaluating and optimizing the parameters of the classifier. Slightly above 84 % of successfully recognized diagnostic states, was recently achieved on the test data. 

  1. An ensemble self-training protein interaction article classifier.

    Science.gov (United States)

    Chen, Yifei; Hou, Ping; Manderick, Bernard

    2014-01-01

    Protein-protein interaction (PPI) is essential to understand the fundamental processes governing cell biology. The mining and curation of PPI knowledge are critical for analyzing proteomics data. Hence it is desired to classify articles PPI-related or not automatically. In order to build interaction article classification systems, an annotated corpus is needed. However, it is usually the case that only a small number of labeled articles can be obtained manually. Meanwhile, a large number of unlabeled articles are available. By combining ensemble learning and semi-supervised self-training, an ensemble self-training interaction classifier called EST_IACer is designed to classify PPI-related articles based on a small number of labeled articles and a large number of unlabeled articles. A biological background based feature weighting strategy is extended using the category information from both labeled and unlabeled data. Moreover, a heuristic constraint is put forward to select optimal instances from unlabeled data to improve the performance further. Experiment results show that the EST_IACer can classify the PPI related articles effectively and efficiently.

  2. Classifying Linear Canonical Relations

    OpenAIRE

    Lorand, Jonathan

    2015-01-01

    In this Master's thesis, we consider the problem of classifying, up to conjugation by linear symplectomorphisms, linear canonical relations (lagrangian correspondences) from a finite-dimensional symplectic vector space to itself. We give an elementary introduction to the theory of linear canonical relations and present partial results toward the classification problem. This exposition should be accessible to undergraduate students with a basic familiarity with linear algebra.

  3. Classified facilities for environmental protection

    International Nuclear Information System (INIS)

    Anon.

    1993-02-01

    The legislation of the classified facilities governs most of the dangerous or polluting industries or fixed activities. It rests on the law of 9 July 1976 concerning facilities classified for environmental protection and its application decree of 21 September 1977. This legislation, the general texts of which appear in this volume 1, aims to prevent all the risks and the harmful effects coming from an installation (air, water or soil pollutions, wastes, even aesthetic breaches). The polluting or dangerous activities are defined in a list called nomenclature which subjects the facilities to a declaration or an authorization procedure. The authorization is delivered by the prefect at the end of an open and contradictory procedure after a public survey. In addition, the facilities can be subjected to technical regulations fixed by the Environment Minister (volume 2) or by the prefect for facilities subjected to declaration (volume 3). (A.B.)

  4. Defending Malicious Script Attacks Using Machine Learning Classifiers

    Directory of Open Access Journals (Sweden)

    Nayeem Khan

    2017-01-01

    Full Text Available The web application has become a primary target for cyber criminals by injecting malware especially JavaScript to perform malicious activities for impersonation. Thus, it becomes an imperative to detect such malicious code in real time before any malicious activity is performed. This study proposes an efficient method of detecting previously unknown malicious java scripts using an interceptor at the client side by classifying the key features of the malicious code. Feature subset was obtained by using wrapper method for dimensionality reduction. Supervised machine learning classifiers were used on the dataset for achieving high accuracy. Experimental results show that our method can efficiently classify malicious code from benign code with promising results.

  5. Simultaneous removal of selected oxidized contaminants in groundwater using a continuously stirred hydrogen-based membrane biofilm reactor.

    Science.gov (United States)

    Xia, Siqing; Liang, Jun; Xu, Xiaoyin; Shen, Shuang

    2013-01-01

    A laboratory trial was conducted for evaluating the capability of a continuously stirred hydrogen-based membrane biofilm reactor to simultaneously reduce nitrate (NO(3-)-N), sulfate (SO4(2-)), bromate (BrO3-), hexavalent chromium (Cr(VI)) and parachloronitrobenzene (p-CNB). The reactor contained two bundles of hollow fiber membranes functioning as an autotrophic biofilm carrier and hydrogen pipe as well. On the condition that hydrogen was supplied as electron donor and diffused into water through membrane pores, autohydrogenotrophic bacteria were capable of reducing contaminants to forms with lower toxicity. Reduction occurred within 1 day and removal fluxes for NO(3-)-N, SO4(2-), BrO3-, Cr(VI), and p-CNB reached 0.641, 2.396, 0.008, 0.016 and 0.031 g/(day x m2), respectively after 112 days of continuous operation. Except for the fact that sulfate was 37% removed under high surface loading, the other four contaminants were reduced by over 95%. The removal flux comparison between phases varying in surface loading and H2 pressure showed that decreasing surface loading or increasing H2 pressure would promote removal flux. Competition for electrons occurred among the five contaminants. Electron-equivalent flux analysis showed that the amount of utilized hydrogen was mainly controlled by NO(3-)-N and SO4(2-) reduction, which accounted for over 99% of the electron flux altogether. It also indicated the electron acceptor order, showing that nitrate was the most prior electron acceptor while suIfate was the second of the five contaminants.

  6. Fisher classifier and its probability of error estimation

    Science.gov (United States)

    Chittineni, C. B.

    1979-01-01

    Computationally efficient expressions are derived for estimating the probability of error using the leave-one-out method. The optimal threshold for the classification of patterns projected onto Fisher's direction is derived. A simple generalization of the Fisher classifier to multiple classes is presented. Computational expressions are developed for estimating the probability of error of the multiclass Fisher classifier.

  7. Reducing variability in the output of pattern classifiers using histogram shaping

    International Nuclear Information System (INIS)

    Gupta, Shalini; Kan, Chih-Wen; Markey, Mia K.

    2010-01-01

    Purpose: The authors present a novel technique based on histogram shaping to reduce the variability in the output and (sensitivity, specificity) pairs of pattern classifiers with identical ROC curves, but differently distributed outputs. Methods: The authors identify different sources of variability in the output of linear pattern classifiers with identical ROC curves, which also result in classifiers with differently distributed outputs. They theoretically develop a novel technique based on the matching of the histograms of these differently distributed pattern classifier outputs to reduce the variability in their (sensitivity, specificity) pairs at fixed decision thresholds, and to reduce the variability in their actual output values. They empirically demonstrate the efficacy of the proposed technique by means of analyses on the simulated data and real world mammography data. Results: For the simulated data, with three different known sources of variability, and for the real world mammography data with unknown sources of variability, the proposed classifier output calibration technique significantly reduced the variability in the classifiers' (sensitivity, specificity) pairs at fixed decision thresholds. Furthermore, for classifiers with monotonically or approximately monotonically related output variables, the histogram shaping technique also significantly reduced the variability in their actual output values. Conclusions: Classifier output calibration based on histogram shaping can be successfully employed to reduce the variability in the output values and (sensitivity, specificity) pairs of pattern classifiers with identical ROC curves, but differently distributed outputs.

  8. Electron-stimulated purification of platinum nanostructures grown via focused electron beam induced deposition

    Directory of Open Access Journals (Sweden)

    Brett B. Lewis

    2015-04-01

    Full Text Available Platinum–carbon nanostructures deposited via electron beam induced deposition from MeCpPt(IVMe3 are purified during a post-deposition electron exposure treatment in a localized oxygen ambient at room temperature. Time-dependent studies demonstrate that the process occurs from the top–down. Electron beam energy and current studies demonstrate that the process is controlled by a confluence of the electron energy loss and oxygen concentration. Furthermore, the experimental results are modeled as a 2nd order reaction which is dependent on both the electron energy loss density and the oxygen concentration. In addition to purification, the post-deposition electron stimulated oxygen purification process enhances the resolution of the EBID process due to the isotropic carbon removal from the as-deposited materials which produces high-fidelity shape retention.

  9. Removal of a Broken Cannulated Intramedullary Nail: Review of the Literature and a Case Report of a New Technique

    Directory of Open Access Journals (Sweden)

    Amr A. Abdelgawad

    2013-01-01

    Full Text Available Nonunion of long bones fixed with nails may result in implant failure. Removal of a broken intramedullary nail may be a real challenge. Many methods have been described to allow for removal of the broken piece of the nail. In this paper, we are reviewing the different techniques to extract a broken nail, classifying them into different subsets, and describing a new technique that we used to remove a broken tibial nail with narrow canal. Eight different categories of implant removal methods were described, with different methods within each category. This classification is very comprehensive and was never described before. We described a new technique (hook captured in the medulla by flexible nail introduced from the locking hole which is a valuable technique in cases of nail of a small diameter where other methods cannot be used because of the narrow canal of the nail. Our eight categories for broken nail removal methods simplify the concepts of nail removal and allow the surgeon to better plan for the removal procedure.

  10. An ensemble of dissimilarity based classifiers for Mackerel gender determination

    Science.gov (United States)

    Blanco, A.; Rodriguez, R.; Martinez-Maranon, I.

    2014-03-01

    Mackerel is an infravalored fish captured by European fishing vessels. A manner to add value to this specie can be achieved by trying to classify it attending to its sex. Colour measurements were performed on Mackerel females and males (fresh and defrozen) extracted gonads to obtain differences between sexes. Several linear and non linear classifiers such as Support Vector Machines (SVM), k Nearest Neighbors (k-NN) or Diagonal Linear Discriminant Analysis (DLDA) can been applied to this problem. However, theyare usually based on Euclidean distances that fail to reflect accurately the sample proximities. Classifiers based on non-Euclidean dissimilarities misclassify a different set of patterns. We combine different kind of dissimilarity based classifiers. The diversity is induced considering a set of complementary dissimilarities for each model. The experimental results suggest that our algorithm helps to improve classifiers based on a single dissimilarity.

  11. An ensemble of dissimilarity based classifiers for Mackerel gender determination

    International Nuclear Information System (INIS)

    Blanco, A; Rodriguez, R; Martinez-Maranon, I

    2014-01-01

    Mackerel is an infravalored fish captured by European fishing vessels. A manner to add value to this specie can be achieved by trying to classify it attending to its sex. Colour measurements were performed on Mackerel females and males (fresh and defrozen) extracted gonads to obtain differences between sexes. Several linear and non linear classifiers such as Support Vector Machines (SVM), k Nearest Neighbors (k-NN) or Diagonal Linear Discriminant Analysis (DLDA) can been applied to this problem. However, theyare usually based on Euclidean distances that fail to reflect accurately the sample proximities. Classifiers based on non-Euclidean dissimilarities misclassify a different set of patterns. We combine different kind of dissimilarity based classifiers. The diversity is induced considering a set of complementary dissimilarities for each model. The experimental results suggest that our algorithm helps to improve classifiers based on a single dissimilarity

  12. Classifying sows' activity types from acceleration patterns

    DEFF Research Database (Denmark)

    Cornou, Cecile; Lundbye-Christensen, Søren

    2008-01-01

    An automated method of classifying sow activity using acceleration measurements would allow the individual sow's behavior to be monitored throughout the reproductive cycle; applications for detecting behaviors characteristic of estrus and farrowing or to monitor illness and welfare can be foreseen....... This article suggests a method of classifying five types of activity exhibited by group-housed sows. The method involves the measurement of acceleration in three dimensions. The five activities are: feeding, walking, rooting, lying laterally and lying sternally. Four time series of acceleration (the three...

  13. Naive Bayesian classifiers for multinomial features: a theoretical analysis

    CSIR Research Space (South Africa)

    Van Dyk, E

    2007-11-01

    Full Text Available The authors investigate the use of naive Bayesian classifiers for multinomial feature spaces and derive error estimates for these classifiers. The error analysis is done by developing a mathematical model to estimate the probability density...

  14. Negative impact of oxygen molecular activation on Cr(VI) removal with core–shell Fe@Fe2O3 nanowires

    International Nuclear Information System (INIS)

    Mu, Yi; Wu, Hao; Ai, Zhihui

    2015-01-01

    Highlights: • The presence of oxygen inhibited Cr(VI) removal efficiency with nZVI by near 3 times. • Cr(VI) removal with nZVI was related to adsorption, reduction, co-precipitation, and adsorption reactions. • Molecular oxygen activation competed donor electrons from Fe 0 core and surface bound Fe(II) of nZVI. • Thicker Cr(III)/Fe(III)/Cr(VI) oxyhydroxides shell of nZVI leaded to the electron transfer inhibition. - Abstract: In this study, we demonstrate that the presence of oxygen molecule can inhibit Cr(VI) removal with core–shell Fe@Fe 2 O 3 nanowires at neutral pH of 6.1. 100% of Cr(VI) removal was achieved by the Fe@Fe 2 O 3 nanowires within 60 min in the anoxic condition, in contrast, only 81.2% of Cr(VI) was sequestrated in the oxic condition. Removal kinetics analysis indicated that the presence of oxygen could inhibit the Cr(VI) removal efficiency by near 3 times. XRD, SEM, and XPS analysis revealed that either the anoxic or oxic Cr(VI) removal was involved with adsorption, reduction, co-precipitation, and re-adsorption processes. More Cr(VI) was bound in a reduced state of Cr(III) in the anoxic process, while a thicker Cr(III)/Fe(III)/Cr(VI) oxyhydroxides shell, leading to inhibiting the electron transfer, was found under the oxic process. The negative impact of oxygen molecule was attributed to the oxygen molecular activation which competed with Cr(VI) adsorbed for the consumption of donor electrons from Fe 0 core and ferrous ions bound on the iron oxides surface under the oxic condition. This study sheds light on the understanding of the fate and transport of Cr(VI) in oxic and anoxic environment, as well provides helpful guide for optimizing Cr(VI) removal conditions in real applications

  15. Enhanced biological phosphorus removal. Carbon sources, nitrate as electron acceptor, and characterization of the sludge community

    Energy Technology Data Exchange (ETDEWEB)

    Christensson, M

    1997-10-01

    Enhanced biological phosphorus removal (EBPR) was studied in laboratory scale experiments as well as in a full scale EBPR process. The studies were focused on carbon source transformations, the use of nitrate as an electron acceptor and characterisation of the microflora. A continuous anaerobic/aerobic laboratory system was operated on synthetic wastewater with acetate as sole carbon source. An efficient EBPR was obtained and mass balances over the anaerobic reactor showed a production of 1.45 g poly-{beta}-hydroxyalcanoic acids (PHA), measured as chemical oxygen demand (COD), per g of acetic acid (as COD) taken up. Furthermore, phosphate was released in the anaerobic reactor in a ratio of 0.33 g phosphorus (P) per g PHA (COD) formed and 0.64 g of glycogen (COD) was consumed per g of acetic acid (COD) taken up. Microscopic investigations revealed a high amount of polyphosphate accumulating organisms (PAO) in the sludge. Isolation and characterisation of bacteria indicated Acinetobacter spp. to be abundant in the sludge, while sequencing of clones obtained in a 16S rDNA clone library showed a large part of the bacteria to be related to the high mole % G+C Gram-positive bacteria and only a minor fraction to be related to the gamma-subclass of proteobacteria to which Acinetobacter belongs. Operation of a similar anaerobic/aerobic laboratory system with ethanol as sole carbon source showed that a high EBPR can be achieved with this compound as carbon source. However, a prolonged detention time in the anaerobic reactor was required. PHA were produced in the anaerobic reactor in an amount of 1.24 g COD per g of soluble DOC taken up, phosphate was released in an amount of 0.4-0.6 g P per g PHA (COD) produced and 0.46 g glycogen (COD) was consumed per g of soluble COD taken up. Studies of the EBPR in the UCT process at the sewage treatment plant in Helsingborg, Sweden, showed the amount of volatile fatty acids (VFA) available to the PAO in the anaerobic stage to be

  16. DEVICES FOR COOLING ELECTRONIC CIRCUIT BOARDS

    Directory of Open Access Journals (Sweden)

    T. A. Ismailov

    2014-01-01

    Full Text Available In the work described structural variants of devices for cooling electronic circuit boards, made on the basis of thermoelectric batteries and consumable working substances, implementing uneven process of removing heat from heat-generating components. A comparison of temperature fields of electronic circuit simulator with his uniform and non-uniform cooling. 

  17. Comparing performance of 30-day readmission risk classifiers among hospitalized primary care patients.

    Science.gov (United States)

    Garrison, Gregory M; Robelia, Paul M; Pecina, Jennifer L; Dawson, Nancy L

    2017-06-01

    Hospital readmission within 30 days of discharge occurs in almost 20% of US Medicare patients and may be a marker of poor quality inpatient care, ineffective hospital to home transitions, or disease severity. Within a patient centered medical home, care transition interventions may only be practical from cost and staffing perspectives if targeted at patients with the greatest risk of readmission. Various scoring algorithms attempt to predict patients at risk for 30-day readmission, but head-to-head comparison of performance is lacking. Compare published scoring algorithms which use generally available electronic medical record data on the same set of hospitalized primary care patients. The LACE index, the LACE+ index, the HOSPITAL score, and the readmission risk score were computed on a consecutive cohort of 26,278 hospital admissions. Classifier performance was assessed by plotting receiver operating characteristic curves comparing the computed score with the actual outcome of death or readmission within 30 days. Statistical significance of differences in performance was assessed using bootstrapping techniques. Correct readmission classification on this cohort was moderate with the following c-statistics: Readmission risk score 0.666; LACE 0.680; LACE+ 0.662; and HOSPITAL 0.675. There was no statistically significant difference in performance between classifiers. Logistic regression based classifiers yield only moderate performance when utilized to predict 30-day readmissions. The task is difficult due to the variety of underlying causes for readmission, nonlinearity, and the arbitrary time period of concern. More sophisticated classification techniques may be necessary to increase performance and allow patient centered medical homes to effectively focus efforts to reduce readmissions. © 2016 John Wiley & Sons, Ltd.

  18. Scanning electron microscopy analysis of the growth of dental plaque on the surfaces of removable orthodontic aligners after the use of different cleaning methods

    Directory of Open Access Journals (Sweden)

    Levrini L

    2015-12-01

    Full Text Available Luca Levrini, Francesca Novara, Silvia Margherini, Camilla Tenconi, Mario Raspanti Department of Surgical and Morphological Sciences, Dental Hygiene School, Research Centre Cranio Facial Disease and Medicine, University of Insubria, Varese, Italy Background: Advances in orthodontics are leading to the use of minimally invasive technologies, such as transparent removable aligners, and are able to meet high demands in terms of performance and esthetics. However, the most correct method of cleaning these appliances, in order to minimize the effects of microbial colonization, remains to be determined. Purpose: The aim of the present study was to identify the most effective method of cleaning removable orthodontic aligners, analyzing the growth of dental plaque as observed under scanning electron microscopy. Methods: Twelve subjects were selected for the study. All were free from caries and periodontal disease and were candidates for orthodontic therapy with invisible orthodontic aligners. The trial had a duration of 6 weeks, divided into three 2-week stages, during which three sets of aligners were used. In each stage, the subjects were asked to use a different method of cleaning their aligners: 1 running water (control condition; 2 effervescent tablets containing sodium carbonate and sulfate crystals followed by brushing with a toothbrush; and 3 brushing alone (with a toothbrush and toothpaste. At the end of each 2-week stage, the surfaces of the aligners were analyzed under scanning electron microscopy. Results: The best results were obtained with brushing combined with the use of sodium carbonate and sulfate crystals; brushing alone gave slightly inferior results. Conclusion: On the basis of previous literature results relating to devices in resin, studies evaluating the reliability of domestic ultrasonic baths for domestic use should be encouraged. At present, pending the availability of experimental evidence, it can be suggested that dental

  19. Differential profiling of volatile organic compound biomarker signatures utilizing a logical statistical filter-set and novel hybrid evolutionary classifiers

    Science.gov (United States)

    Grigsby, Claude C.; Zmuda, Michael A.; Boone, Derek W.; Highlander, Tyler C.; Kramer, Ryan M.; Rizki, Mateen M.

    2012-06-01

    A growing body of discoveries in molecular signatures has revealed that volatile organic compounds (VOCs), the small molecules associated with an individual's odor and breath, can be monitored to reveal the identity and presence of a unique individual, as well their overall physiological status. Given the analysis requirements for differential VOC profiling via gas chromatography/mass spectrometry, our group has developed a novel informatics platform, Metabolite Differentiation and Discovery Lab (MeDDL). In its current version, MeDDL is a comprehensive tool for time-series spectral registration and alignment, visualization, comparative analysis, and machine learning to facilitate the efficient analysis of multiple, large-scale biomarker discovery studies. The MeDDL toolset can therefore identify a large differential subset of registered peaks, where their corresponding intensities can be used as features for classification. This initial screening of peaks yields results sets that are typically too large for incorporation into a portable, electronic nose based system in addition to including VOCs that are not amenable to classification; consequently, it is also important to identify an optimal subset of these peaks to increase classification accuracy and to decrease the cost of the final system. MeDDL's learning tools include a classifier similar to a K-nearest neighbor classifier used in conjunction with a genetic algorithm (GA) that simultaneously optimizes the classifier and subset of features. The GA uses ROC curves to produce classifiers having maximal area under their ROC curve. Experimental results on over a dozen recognition problems show many examples of classifiers and feature sets that produce perfect ROC curves.

  20. Neural network classifier of attacks in IP telephony

    Science.gov (United States)

    Safarik, Jakub; Voznak, Miroslav; Mehic, Miralem; Partila, Pavol; Mikulec, Martin

    2014-05-01

    Various types of monitoring mechanism allow us to detect and monitor behavior of attackers in VoIP networks. Analysis of detected malicious traffic is crucial for further investigation and hardening the network. This analysis is typically based on statistical methods and the article brings a solution based on neural network. The proposed algorithm is used as a classifier of attacks in a distributed monitoring network of independent honeypot probes. Information about attacks on these honeypots is collected on a centralized server and then classified. This classification is based on different mechanisms. One of them is based on the multilayer perceptron neural network. The article describes inner structure of used neural network and also information about implementation of this network. The learning set for this neural network is based on real attack data collected from IP telephony honeypot called Dionaea. We prepare the learning set from real attack data after collecting, cleaning and aggregation of this information. After proper learning is the neural network capable to classify 6 types of most commonly used VoIP attacks. Using neural network classifier brings more accurate attack classification in a distributed system of honeypots. With this approach is possible to detect malicious behavior in a different part of networks, which are logically or geographically divided and use the information from one network to harden security in other networks. Centralized server for distributed set of nodes serves not only as a collector and classifier of attack data, but also as a mechanism for generating a precaution steps against attacks.

  1. Case study for one-piece removal method of reactor vessel of nuclear ship 'Mutsu'

    International Nuclear Information System (INIS)

    Nagane, Satoru; Kitahara, Katsumi; Yoshikawa, Seiji; Miyasaka, Yasuhiko; Fukumura, Nobuo; Nisizawa, Ichiou

    2010-01-01

    A reactor installed at the center part of the nuclear ship 'Mutsu' has been stored safely and exhibited in a reactor room building since 1996. The reactor vessel and its internals are key components because of main radioactive wastes for the reasonable decommissioning plan in the future. This report describes the one-piece removal method as the one package of the reactor vessel with its internals intact with a shipping container or additional shields. The reactor vessel package (Max.100ton) will be classified acceptable for burial at the low level radioactive waste (LLW), which will be buried at a LLW pit facility under waste disposal regulations. And also, the package will be classified as an IP-2-equivalent package according to the requirement for Shipments and Packagings. (author)

  2. An Ensemble Method with Integration of Feature Selection and Classifier Selection to Detect the Landslides

    Science.gov (United States)

    Zhongqin, G.; Chen, Y.

    2017-12-01

    Abstract Quickly identify the spatial distribution of landslides automatically is essential for the prevention, mitigation and assessment of the landslide hazard. It's still a challenging job owing to the complicated characteristics and vague boundary of the landslide areas on the image. The high resolution remote sensing image has multi-scales, complex spatial distribution and abundant features, the object-oriented image classification methods can make full use of the above information and thus effectively detect the landslides after the hazard happened. In this research we present a new semi-supervised workflow, taking advantages of recent object-oriented image analysis and machine learning algorithms to quick locate the different origins of landslides of some areas on the southwest part of China. Besides a sequence of image segmentation, feature selection, object classification and error test, this workflow ensemble the feature selection and classifier selection. The feature this study utilized were normalized difference vegetation index (NDVI) change, textural feature derived from the gray level co-occurrence matrices (GLCM), spectral feature and etc. The improvement of this study shows this algorithm significantly removes some redundant feature and the classifiers get fully used. All these improvements lead to a higher accuracy on the determination of the shape of landslides on the high resolution remote sensing image, in particular the flexibility aimed at different kinds of landslides.

  3. Technology for meat-grinding systems to improve removal of hard particles from ground meat.

    Science.gov (United States)

    Zhao, Y; Sebranek, J G

    1997-03-01

    With increased consumption of ground meat, especially ground beef, quality issues for these products have become more important to industry and consumers alike. Ground meats are usually obtained from relatively low-value cuts and trimmings, and may on occasion contain undesirable hard particles. Hard particles in coarse-ground meat products may include bone chips or fragments, cartilage and dense connective tissue; all of which are considered undesirable defects and which can be reduced by utilizing hard-particle removal systems during grinding operations. This review discusses the principles of hard-particle separation from ground meat, the factors which influence performance of particle separation and some commercially available particle removal systems. Product and processing parameters such as initial bone and connective tissue content, fat content, temperature, pre-grinding size and grinder knife design are considered important for removing hard particles effectively. Pressure gradient on the grinder knife/plate interface was found to play a significant role in particle separation from soft (fat and lean) tissue. Various commercial systems, which are classified as central removal and periphery removal systems, are also discussed. Finally, the authors suggest some processing considerations for meat grinding to help achieve the best quality ground meat for consumers' satisfaction.

  4. SVM classifier on chip for melanoma detection.

    Science.gov (United States)

    Afifi, Shereen; GholamHosseini, Hamid; Sinha, Roopak

    2017-07-01

    Support Vector Machine (SVM) is a common classifier used for efficient classification with high accuracy. SVM shows high accuracy for classifying melanoma (skin cancer) clinical images within computer-aided diagnosis systems used by skin cancer specialists to detect melanoma early and save lives. We aim to develop a medical low-cost handheld device that runs a real-time embedded SVM-based diagnosis system for use in primary care for early detection of melanoma. In this paper, an optimized SVM classifier is implemented onto a recent FPGA platform using the latest design methodology to be embedded into the proposed device for realizing online efficient melanoma detection on a single system on chip/device. The hardware implementation results demonstrate a high classification accuracy of 97.9% and a significant acceleration factor of 26 from equivalent software implementation on an embedded processor, with 34% of resources utilization and 2 watts for power consumption. Consequently, the implemented system meets crucial embedded systems constraints of high performance and low cost, resources utilization and power consumption, while achieving high classification accuracy.

  5. PredictSNP: robust and accurate consensus classifier for prediction of disease-related mutations.

    Directory of Open Access Journals (Sweden)

    Jaroslav Bendl

    2014-01-01

    Full Text Available Single nucleotide variants represent a prevalent form of genetic variation. Mutations in the coding regions are frequently associated with the development of various genetic diseases. Computational tools for the prediction of the effects of mutations on protein function are very important for analysis of single nucleotide variants and their prioritization for experimental characterization. Many computational tools are already widely employed for this purpose. Unfortunately, their comparison and further improvement is hindered by large overlaps between the training datasets and benchmark datasets, which lead to biased and overly optimistic reported performances. In this study, we have constructed three independent datasets by removing all duplicities, inconsistencies and mutations previously used in the training of evaluated tools. The benchmark dataset containing over 43,000 mutations was employed for the unbiased evaluation of eight established prediction tools: MAPP, nsSNPAnalyzer, PANTHER, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT and SNAP. The six best performing tools were combined into a consensus classifier PredictSNP, resulting into significantly improved prediction performance, and at the same time returned results for all mutations, confirming that consensus prediction represents an accurate and robust alternative to the predictions delivered by individual tools. A user-friendly web interface enables easy access to all eight prediction tools, the consensus classifier PredictSNP and annotations from the Protein Mutant Database and the UniProt database. The web server and the datasets are freely available to the academic community at http://loschmidt.chemi.muni.cz/predictsnp.

  6. Removal of Chromium (III from Water by Using Modified and Nonmodified Carbon Nanotubes

    Directory of Open Access Journals (Sweden)

    Muataz Ali Atieh

    2010-01-01

    Full Text Available This study was carried out to evaluate the environmental application of modified and nonmodified carbon nanotubes through the experiment removal of chromium trivalent (III from water. The aim was to find the optimal condition of the chromium (III removal from water under different treatment conditions of pH, adsorbent dosage, contact time and agitation speed. Multi wall carbon nanotubes (MW-CNTs were characterized by field emission scanning electron microscopy (FE-SEM and transmission electron microscopy (TEM. The diameter of the carbon nanotubes produced varied from 20–40 nm with average diameter of 24 nm and 10 micrometer in length. Adsorption isotherms were used to model the adsorption behavior and to calculate the adsorption capacity of the absorbents. The results showed that, 18% of chromium (III removal was achieved using modified carbon nanotubes (M-CNTs at pH 7, 150 rpm, and 2 hours for a dosage of 150 mg of CNTs. The removal of Cr (III is mainly attributed to the affinity of chromium (III to the physical and chemical properties of the CNTs. The adsorption isotherms plots were well fitted with experimental data.

  7. Performance of classification confidence measures in dynamic classifier systems

    Czech Academy of Sciences Publication Activity Database

    Štefka, D.; Holeňa, Martin

    2013-01-01

    Roč. 23, č. 4 (2013), s. 299-319 ISSN 1210-0552 R&D Projects: GA ČR GA13-17187S Institutional support: RVO:67985807 Keywords : classifier combining * dynamic classifier systems * classification confidence Subject RIV: IN - Informatics, Computer Science Impact factor: 0.412, year: 2013

  8. SAR Target Recognition Based on Multi-feature Multiple Representation Classifier Fusion

    Directory of Open Access Journals (Sweden)

    Zhang Xinzheng

    2017-10-01

    Full Text Available In this paper, we present a Synthetic Aperture Radar (SAR image target recognition algorithm based on multi-feature multiple representation learning classifier fusion. First, it extracts three features from the SAR images, namely principal component analysis, wavelet transform, and Two-Dimensional Slice Zernike Moments (2DSZM features. Second, we harness the sparse representation classifier and the cooperative representation classifier with the above-mentioned features to get six predictive labels. Finally, we adopt classifier fusion to obtain the final recognition decision. We researched three different classifier fusion algorithms in our experiments, and the results demonstrate thatusing Bayesian decision fusion gives thebest recognition performance. The method based on multi-feature multiple representation learning classifier fusion integrates the discrimination of multi-features and combines the sparse and cooperative representation classification performance to gain complementary advantages and to improve recognition accuracy. The experiments are based on the Moving and Stationary Target Acquisition and Recognition (MSTAR database,and they demonstrate the effectiveness of the proposed approach.

  9. Nonparametric, Coupled ,Bayesian ,Dictionary ,and Classifier Learning for Hyperspectral Classification.

    Science.gov (United States)

    Akhtar, Naveed; Mian, Ajmal

    2017-10-03

    We present a principled approach to learn a discriminative dictionary along a linear classifier for hyperspectral classification. Our approach places Gaussian Process priors over the dictionary to account for the relative smoothness of the natural spectra, whereas the classifier parameters are sampled from multivariate Gaussians. We employ two Beta-Bernoulli processes to jointly infer the dictionary and the classifier. These processes are coupled under the same sets of Bernoulli distributions. In our approach, these distributions signify the frequency of the dictionary atom usage in representing class-specific training spectra, which also makes the dictionary discriminative. Due to the coupling between the dictionary and the classifier, the popularity of the atoms for representing different classes gets encoded into the classifier. This helps in predicting the class labels of test spectra that are first represented over the dictionary by solving a simultaneous sparse optimization problem. The labels of the spectra are predicted by feeding the resulting representations to the classifier. Our approach exploits the nonparametric Bayesian framework to automatically infer the dictionary size--the key parameter in discriminative dictionary learning. Moreover, it also has the desirable property of adaptively learning the association between the dictionary atoms and the class labels by itself. We use Gibbs sampling to infer the posterior probability distributions over the dictionary and the classifier under the proposed model, for which, we derive analytical expressions. To establish the effectiveness of our approach, we test it on benchmark hyperspectral images. The classification performance is compared with the state-of-the-art dictionary learning-based classification methods.

  10. Classifying a smoker scale in adult daily and nondaily smokers.

    Science.gov (United States)

    Pulvers, Kim; Scheuermann, Taneisha S; Romero, Devan R; Basora, Brittany; Luo, Xianghua; Ahluwalia, Jasjit S

    2014-05-01

    Smoker identity, or the strength of beliefs about oneself as a smoker, is a robust marker of smoking behavior. However, many nondaily smokers do not identify as smokers, underestimating their risk for tobacco-related disease and resulting in missed intervention opportunities. Assessing underlying beliefs about characteristics used to classify smokers may help explain the discrepancy between smoking behavior and smoker identity. This study examines the factor structure, reliability, and validity of the Classifying a Smoker scale among a racially diverse sample of adult smokers. A cross-sectional survey was administered through an online panel survey service to 2,376 current smokers who were at least 25 years of age. The sample was stratified to obtain equal numbers of 3 racial/ethnic groups (African American, Latino, and White) across smoking level (nondaily and daily smoking). The Classifying a Smoker scale displayed a single factor structure and excellent internal consistency (α = .91). Classifying a Smoker scores significantly increased at each level of smoking, F(3,2375) = 23.68, p smoker identity, stronger dependence on cigarettes, greater health risk perceptions, more smoking friends, and were more likely to carry cigarettes. Classifying a Smoker scores explained unique variance in smoking variables above and beyond that explained by smoker identity. The present study supports the use of the Classifying a Smoker scale among diverse, experienced smokers. Stronger endorsement of characteristics used to classify a smoker (i.e., stricter criteria) was positively associated with heavier smoking and related characteristics. Prospective studies are needed to inform prevention and treatment efforts.

  11. Classifying spaces with virtually cyclic stabilizers for linear groups

    DEFF Research Database (Denmark)

    Degrijse, Dieter Dries; Köhl, Ralf; Petrosyan, Nansen

    2015-01-01

    We show that every discrete subgroup of GL(n, ℝ) admits a finite-dimensional classifying space with virtually cyclic stabilizers. Applying our methods to SL(3, ℤ), we obtain a four-dimensional classifying space with virtually cyclic stabilizers and a decomposition of the algebraic K-theory of its...

  12. Intuitive Action Set Formation in Learning Classifier Systems with Memory Registers

    NARCIS (Netherlands)

    Simões, L.F.; Schut, M.C.; Haasdijk, E.W.

    2008-01-01

    An important design goal in Learning Classifier Systems (LCS) is to equally reinforce those classifiers which cause the level of reward supplied by the environment. In this paper, we propose a new method for action set formation in LCS. When applied to a Zeroth Level Classifier System with Memory

  13. Data Stream Classification Based on the Gamma Classifier

    Directory of Open Access Journals (Sweden)

    Abril Valeria Uriarte-Arcia

    2015-01-01

    Full Text Available The ever increasing data generation confronts us with the problem of handling online massive amounts of information. One of the biggest challenges is how to extract valuable information from these massive continuous data streams during single scanning. In a data stream context, data arrive continuously at high speed; therefore the algorithms developed to address this context must be efficient regarding memory and time management and capable of detecting changes over time in the underlying distribution that generated the data. This work describes a novel method for the task of pattern classification over a continuous data stream based on an associative model. The proposed method is based on the Gamma classifier, which is inspired by the Alpha-Beta associative memories, which are both supervised pattern recognition models. The proposed method is capable of handling the space and time constrain inherent to data stream scenarios. The Data Streaming Gamma classifier (DS-Gamma classifier implements a sliding window approach to provide concept drift detection and a forgetting mechanism. In order to test the classifier, several experiments were performed using different data stream scenarios with real and synthetic data streams. The experimental results show that the method exhibits competitive performance when compared to other state-of-the-art algorithms.

  14. Design of Robust Neural Network Classifiers

    DEFF Research Database (Denmark)

    Larsen, Jan; Andersen, Lars Nonboe; Hintz-Madsen, Mads

    1998-01-01

    This paper addresses a new framework for designing robust neural network classifiers. The network is optimized using the maximum a posteriori technique, i.e., the cost function is the sum of the log-likelihood and a regularization term (prior). In order to perform robust classification, we present...... a modified likelihood function which incorporates the potential risk of outliers in the data. This leads to the introduction of a new parameter, the outlier probability. Designing the neural classifier involves optimization of network weights as well as outlier probability and regularization parameters. We...... suggest to adapt the outlier probability and regularisation parameters by minimizing the error on a validation set, and a simple gradient descent scheme is derived. In addition, the framework allows for constructing a simple outlier detector. Experiments with artificial data demonstrate the potential...

  15. The effect of root surface conditioning on smear layer removal in periodontal regeneration (a scanning electron microscopic study)

    Science.gov (United States)

    Fidyawati, D.; Soeroso, Y.; Masulili, S. L. C.

    2017-08-01

    The role of root surface conditioning treatment on smear layer removal of human teeth is affected by periodontitis in periodontal regeneration. The objective of this study is to analyze the smear layer on root surface conditioned with 2.1% minocycline HCl ointment (Periocline), and 24% EDTA gel (Prefgel). A total of 10 human teeth indicated for extraction due to chronic periodontitis were collected and root planed. The teeth were sectioned in thirds of the cervical area, providing 30 samples that were divided into three groups - minocycline ointment treatment, 24% EDTA gel treatment, and saline as a control. The samples were examined by scanning electron microscope. No significant differences in levels of smear layer were observed between the minocycline group and the EDTA group (p=0.759). However, there were significant differences in the level of smear layer after root surface treatment in the minocycline and EDTA groups, compared with the control group (p=0.00). There was a relationship between root surface conditioning treatment and smear layer levels following root planing.

  16. Safe Handover : Safe Patients - The Electronic Handover System.

    Science.gov (United States)

    Till, Alex; Sall, Hanish; Wilkinson, Jonathan

    2014-01-01

    Failure of effective handover is a major preventable cause of patient harm. We aimed to promote accurate recording of high-quality clinical information using an Electronic Handover System (EHS) that would contribute to a sustainable improvement in effective patient care and safety. Within our hospital the human factors associated with poor communication were compromising patient care and unnecessarily increasing the workload of staff due to the poor quality of handovers. Only half of handovers were understood by the doctors expected to complete them, and more than half of our medical staff felt it posed a risk to patient safety. We created a standardised proforma for handovers that contained specific sub-headings, re-classified patient risk assessments, and aided escalation of care by adding prompts for verbal handover. Sources of miscommunication were removed, accountability for handovers provided, and tasks were re-organised to reduce the workload of staff. Long-term, three-month data showed that each sub-heading achieved at least 80% compliance (an average improvement of approximately 40% for the overall quality of handovers). This translated into 91% of handovers being subjectively clear to junior doctors. 87% of medical staff felt we had reduced a risk to patient safety and 80% felt it increased continuity of care. Without guidance, doctors omit key information required for effective handover. All organisations should consider implementing an electronic handover system as a viable, sustainable and safe solution to handover of care that allows patient safety to remain at the heart of the NHS.

  17. Combining multiple classifiers for age classification

    CSIR Research Space (South Africa)

    Van Heerden, C

    2009-11-01

    Full Text Available The authors compare several different classifier combination methods on a single task, namely speaker age classification. This task is well suited to combination strategies, since significantly different feature classes are employed. Support vector...

  18. Maximum margin classifier working in a set of strings.

    Science.gov (United States)

    Koyano, Hitoshi; Hayashida, Morihiro; Akutsu, Tatsuya

    2016-03-01

    Numbers and numerical vectors account for a large portion of data. However, recently, the amount of string data generated has increased dramatically. Consequently, classifying string data is a common problem in many fields. The most widely used approach to this problem is to convert strings into numerical vectors using string kernels and subsequently apply a support vector machine that works in a numerical vector space. However, this non-one-to-one conversion involves a loss of information and makes it impossible to evaluate, using probability theory, the generalization error of a learning machine, considering that the given data to train and test the machine are strings generated according to probability laws. In this study, we approach this classification problem by constructing a classifier that works in a set of strings. To evaluate the generalization error of such a classifier theoretically, probability theory for strings is required. Therefore, we first extend a limit theorem for a consensus sequence of strings demonstrated by one of the authors and co-workers in a previous study. Using the obtained result, we then demonstrate that our learning machine classifies strings in an asymptotically optimal manner. Furthermore, we demonstrate the usefulness of our machine in practical data analysis by applying it to predicting protein-protein interactions using amino acid sequences and classifying RNAs by the secondary structure using nucleotide sequences.

  19. Electron beam induced Hg desorption and the electronic structure of the Hg depleted surface of Hg1/sub -//sub x/Cd/sub x/Te

    International Nuclear Information System (INIS)

    Shih, C.K.; Friedman, D.J.; Bertness, K.A.; Lindau, I.; Spicer, W.E.; Wilson, J.A.

    1986-01-01

    Auger electron spectroscopy (AES), x-ray photoemission spectroscopy (XPS), low energy electron diffraction (LEED), and angle-resolved ultraviolet photoemission spectroscopy (ARPES) were used to study the electron beam induced Hg desorption from a cleaved (110)Hg/sub 1-//sub x/Cd/sub x/Te surface and the electronic structure of the Hg depleted surface. Solid state recrystallized Hg/sub 1-//sub x/Cd/sub x/Te single crystals were used. It was found that the electron beam heating dominated the electron beam induced Hg desorption on Hg/sub 1-//sub x/Cd/sub x/Te. At the electron beam energy used, the electron beam heating extended several thousand angstroms deep. However, the Hg depletion saturated after a few monolayers were depleted of Hg atoms. At the initial stage of Hg loss (only 3%), the surface band bends upward (more p type). The ARPES spectrum showed the loss of some E vs k dispersion after 22% Hg atoms were removed from the surface region, and no dispersion was observed after 43% Hg atoms were removed. These results have important implications on the electronic structure of the surfaces and interfaces of which the stoichiometry is altered

  20. Current Directional Protection of Series Compensated Line Using Intelligent Classifier

    Directory of Open Access Journals (Sweden)

    M. Mollanezhad Heydarabadi

    2016-12-01

    Full Text Available Current inversion condition leads to incorrect operation of current based directional relay in power system with series compensated device. Application of the intelligent system for fault direction classification has been suggested in this paper. A new current directional protection scheme based on intelligent classifier is proposed for the series compensated line. The proposed classifier uses only half cycle of pre-fault and post fault current samples at relay location to feed the classifier. A lot of forward and backward fault simulations under different system conditions upon a transmission line with a fixed series capacitor are carried out using PSCAD/EMTDC software. The applicability of decision tree (DT, probabilistic neural network (PNN and support vector machine (SVM are investigated using simulated data under different system conditions. The performance comparison of the classifiers indicates that the SVM is a best suitable classifier for fault direction discriminating. The backward faults can be accurately distinguished from forward faults even under current inversion without require to detect of the current inversion condition.

  1. Obscenity detection using haar-like features and Gentle Adaboost classifier.

    Science.gov (United States)

    Mustafa, Rashed; Min, Yang; Zhu, Dingju

    2014-01-01

    Large exposure of skin area of an image is considered obscene. This only fact may lead to many false images having skin-like objects and may not detect those images which have partially exposed skin area but have exposed erotogenic human body parts. This paper presents a novel method for detecting nipples from pornographic image contents. Nipple is considered as an erotogenic organ to identify pornographic contents from images. In this research Gentle Adaboost (GAB) haar-cascade classifier and haar-like features used for ensuring detection accuracy. Skin filter prior to detection made the system more robust. The experiment showed that, considering accuracy, haar-cascade classifier performs well, but in order to satisfy detection time, train-cascade classifier is suitable. To validate the results, we used 1198 positive samples containing nipple objects and 1995 negative images. The detection rates for haar-cascade and train-cascade classifiers are 0.9875 and 0.8429, respectively. The detection time for haar-cascade is 0.162 seconds and is 0.127 seconds for train-cascade classifier.

  2. Obscenity Detection Using Haar-Like Features and Gentle Adaboost Classifier

    Directory of Open Access Journals (Sweden)

    Rashed Mustafa

    2014-01-01

    Full Text Available Large exposure of skin area of an image is considered obscene. This only fact may lead to many false images having skin-like objects and may not detect those images which have partially exposed skin area but have exposed erotogenic human body parts. This paper presents a novel method for detecting nipples from pornographic image contents. Nipple is considered as an erotogenic organ to identify pornographic contents from images. In this research Gentle Adaboost (GAB haar-cascade classifier and haar-like features used for ensuring detection accuracy. Skin filter prior to detection made the system more robust. The experiment showed that, considering accuracy, haar-cascade classifier performs well, but in order to satisfy detection time, train-cascade classifier is suitable. To validate the results, we used 1198 positive samples containing nipple objects and 1995 negative images. The detection rates for haar-cascade and train-cascade classifiers are 0.9875 and 0.8429, respectively. The detection time for haar-cascade is 0.162 seconds and is 0.127 seconds for train-cascade classifier.

  3. Quantifying explainable discrimination and removing illegal discrimination in automated decision making

    KAUST Repository

    Kamiran, Faisal

    2012-11-18

    Recently, the following discrimination-aware classification problem was introduced. Historical data used for supervised learning may contain discrimination, for instance, with respect to gender. The question addressed by discrimination-aware techniques is, given sensitive attribute, how to train discrimination-free classifiers on such historical data that are discriminative, with respect to the given sensitive attribute. Existing techniques that deal with this problem aim at removing all discrimination and do not take into account that part of the discrimination may be explainable by other attributes. For example, in a job application, the education level of a job candidate could be such an explainable attribute. If the data contain many highly educated male candidates and only few highly educated women, a difference in acceptance rates between woman and man does not necessarily reflect gender discrimination, as it could be explained by the different levels of education. Even though selecting on education level would result in more males being accepted, a difference with respect to such a criterion would not be considered to be undesirable, nor illegal. Current state-of-the-art techniques, however, do not take such gender-neutral explanations into account and tend to overreact and actually start reverse discriminating, as we will show in this paper. Therefore, we introduce and analyze the refined notion of conditional non-discrimination in classifier design. We show that some of the differences in decisions across the sensitive groups can be explainable and are hence tolerable. Therefore, we develop methodology for quantifying the explainable discrimination and algorithmic techniques for removing the illegal discrimination when one or more attributes are considered as explanatory. Experimental evaluation on synthetic and real-world classification datasets demonstrates that the new techniques are superior to the old ones in this new context, as they succeed in

  4. A systems biology-based classifier for hepatocellular carcinoma diagnosis.

    Directory of Open Access Journals (Sweden)

    Yanqiong Zhang

    Full Text Available AIM: The diagnosis of hepatocellular carcinoma (HCC in the early stage is crucial to the application of curative treatments which are the only hope for increasing the life expectancy of patients. Recently, several large-scale studies have shed light on this problem through analysis of gene expression profiles to identify markers correlated with HCC progression. However, those marker sets shared few genes in common and were poorly validated using independent data. Therefore, we developed a systems biology based classifier by combining the differential gene expression with topological features of human protein interaction networks to enhance the ability of HCC diagnosis. METHODS AND RESULTS: In the Oncomine platform, genes differentially expressed in HCC tissues relative to their corresponding normal tissues were filtered by a corrected Q value cut-off and Concept filters. The identified genes that are common to different microarray datasets were chosen as the candidate markers. Then, their networks were analyzed by GeneGO Meta-Core software and the hub genes were chosen. After that, an HCC diagnostic classifier was constructed by Partial Least Squares modeling based on the microarray gene expression data of the hub genes. Validations of diagnostic performance showed that this classifier had high predictive accuracy (85.88∼92.71% and area under ROC curve (approximating 1.0, and that the network topological features integrated into this classifier contribute greatly to improving the predictive performance. Furthermore, it has been demonstrated that this modeling strategy is not only applicable to HCC, but also to other cancers. CONCLUSION: Our analysis suggests that the systems biology-based classifier that combines the differential gene expression and topological features of human protein interaction network may enhance the diagnostic performance of HCC classifier.

  5. Measurement and production of electron deflection using a sweeping magnetic device in radiotherapy

    International Nuclear Information System (INIS)

    Damrongkijudom, N.; Oborn, B.; Rosenfeld, A.; Butson, M.

    2006-01-01

    The deflection and removal of high energy electrons produced by a medical linear accelerator has been attained by a Neodymium Iron Boron (NdFeB) permanent magnetic deflector device. This work was performed in an attempt to confirm the theoretical amount of electron deflection which could be produced by a magnetic field for removal of electrons from a clinical x-ray beam. This was performed by monitoring the paths of mostly monoenergetic clinical electron beams (6MeV to 20MeV) swept by the magnetic fields using radiographic film and comparing to first order deflection models. Results show that the measured deflection distance for 6 MeV electrons was 18 ± 6 cm and the calculated deflection distance was 21.3 cm. For 20 MeV electrons, this value was 5 ± 2 cm for measurement and 5.1 cm for calculation. The magnetic fields produced can thus reduce surface dose in treatment regions of a patient under irradiation by photon beams and we can predict the removal of all electron contaminations up to 6 MeV from a 6 MV photon beam with the radiation field size up to 10 x 10 cm 2 . The model can also estimate electron contamination still present in the treatment beam at larger field sizes

  6. A Customizable Text Classifier for Text Mining

    Directory of Open Access Journals (Sweden)

    Yun-liang Zhang

    2007-12-01

    Full Text Available Text mining deals with complex and unstructured texts. Usually a particular collection of texts that is specified to one or more domains is necessary. We have developed a customizable text classifier for users to mine the collection automatically. It derives from the sentence category of the HNC theory and corresponding techniques. It can start with a few texts, and it can adjust automatically or be adjusted by user. The user can also control the number of domains chosen and decide the standard with which to choose the texts based on demand and abundance of materials. The performance of the classifier varies with the user's choice.

  7. A survey of decision tree classifier methodology

    Science.gov (United States)

    Safavian, S. R.; Landgrebe, David

    1991-01-01

    Decision tree classifiers (DTCs) are used successfully in many diverse areas such as radar signal classification, character recognition, remote sensing, medical diagnosis, expert systems, and speech recognition. Perhaps the most important feature of DTCs is their capability to break down a complex decision-making process into a collection of simpler decisions, thus providing a solution which is often easier to interpret. A survey of current methods is presented for DTC designs and the various existing issues. After considering potential advantages of DTCs over single-state classifiers, subjects of tree structure design, feature selection at each internal node, and decision and search strategies are discussed.

  8. Recognition of Arabic Sign Language Alphabet Using Polynomial Classifiers

    Directory of Open Access Journals (Sweden)

    M. Al-Rousan

    2005-08-01

    Full Text Available Building an accurate automatic sign language recognition system is of great importance in facilitating efficient communication with deaf people. In this paper, we propose the use of polynomial classifiers as a classification engine for the recognition of Arabic sign language (ArSL alphabet. Polynomial classifiers have several advantages over other classifiers in that they do not require iterative training, and that they are highly computationally scalable with the number of classes. Based on polynomial classifiers, we have built an ArSL system and measured its performance using real ArSL data collected from deaf people. We show that the proposed system provides superior recognition results when compared with previously published results using ANFIS-based classification on the same dataset and feature extraction methodology. The comparison is shown in terms of the number of misclassified test patterns. The reduction in the rate of misclassified patterns was very significant. In particular, we have achieved a 36% reduction of misclassifications on the training data and 57% on the test data.

  9. Comparison of Classifier Architectures for Online Neural Spike Sorting.

    Science.gov (United States)

    Saeed, Maryam; Khan, Amir Ali; Kamboh, Awais Mehmood

    2017-04-01

    High-density, intracranial recordings from micro-electrode arrays need to undergo Spike Sorting in order to associate the recorded neuronal spikes to particular neurons. This involves spike detection, feature extraction, and classification. To reduce the data transmission and power requirements, on-chip real-time processing is becoming very popular. However, high computational resources are required for classifiers in on-chip spike-sorters, making scalability a great challenge. In this review paper, we analyze several popular classifiers to propose five new hardware architectures using the off-chip training with on-chip classification approach. These include support vector classification, fuzzy C-means classification, self-organizing maps classification, moving-centroid K-means classification, and Cosine distance classification. The performance of these architectures is analyzed in terms of accuracy and resource requirement. We establish that the neural networks based Self-Organizing Maps classifier offers the most viable solution. A spike sorter based on the Self-Organizing Maps classifier, requires only 7.83% of computational resources of the best-reported spike sorter, hierarchical adaptive means, while offering a 3% better accuracy at 7 dB SNR.

  10. 32 CFR 2004.21 - Protection of Classified Information [201(e)].

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Protection of Classified Information [201(e... PROGRAM DIRECTIVE NO. 1 Operations § 2004.21 Protection of Classified Information [201(e)]. Procedures for... coordination process. ...

  11. Removal of stored particle background via the electric dipole method in the KATRIN main spectrometer

    Energy Technology Data Exchange (ETDEWEB)

    Hilk, Daniel [Institut fuer Experimentelle Kernphysik, KIT, Karlsruhe (Germany); Collaboration: KATRIN-Collaboration

    2016-07-01

    The goal of the KArlsruhe TRItium Neutrino (KATRIN) experiment is to determine the effective mass of the electron anti neutrino by measuring the electron energy spectrum of tritium beta decay near the endpoint. The goal is to reach a sensitivity on the neutrino mass of 200 meV for which a low background level of 10{sup -2} counts per second is mandatory. Electrons from single radioactive decays of radon and tritium in the KATRIN main spectrometer with energies in the keV range can be magnetically stored for hours. While cooling down via ionization of residual gas molecules, they produce hundreds of secondary electrons, which can reach the detector and contribute to the background signals. In order to suppress this background component, several methods are investigated to remove stored electrons, such as the application of an electric dipole field and the application of magnetic pulses. This talk introduces the mechanism of background production due to stored electrons and their removal by the electric dipole method in the main spectrometer. In context of the spectrometer- and detector-commissioning phase in summer 2015, measurement results of the application of the electric dipole method are presented.

  12. Seasonal variation of meteor decay times observed at King Sejong Station (62.22°S, 58.78°W), Antarctica

    Science.gov (United States)

    Kim, Jeong-Han; Kim, Yong Ha; Lee, Chang-Sup; Jee, Geonhwa

    2010-07-01

    We analyzed meteor decay times measured by a VHF radar at King Sejong Station by classifying strong and weak meteors according to their estimated electron line densities. The height profiles of monthly averaged decay times show a peak whose altitude varies with season at altitudes of 80-85 km. The higher peak during summer is consistent with colder temperatures that cause faster chemical reactions of electron removal. By adopting temperature dependent empirical recombination rates from rocket experiments and meteor electron densities of 2×105-2×106 cm-3 in a decay time model, we are able to account for decreasing decay times below the peak for all seasons without invoking meteor electron removal by hypothetical icy particles.

  13. Anaerobic bacterial systems result in the removal of soluble uranium

    International Nuclear Information System (INIS)

    Thomson, B.M.; Barton, L.L.; Steenhoudt, K.; Tucker, M.D.

    1994-01-01

    Sulfate-reducing bacteria, nitrate-reducing bacteria and bacteria present in sewage sludge were examined for their ability to reduce the level of soluble U(VI) in enriched media. Cultures of Desulfovibrio desulfuricans, D. gigas, and D. vulgaris were grown in sulfate-containing media while Pseudomonas putida and P. denitrificans were cultivated in nitrate media. The amount of U(VI) removed from solution was dependent on metabolism because greater levels of uranium were removed when U(VI) was added to a growing culture than when added to a culture in stationary phase. The presence of vanadate, arsenate, selenate or molybdate at 0.1 and 0.01 M levels in sulfate-reducing cultures, nitrate-respiring cultures or in sludge cultures did not have an effect on the amount of uranium removed. In all cultures the amount of uranium in solution was markedly reduced after 10 to 20 days and reduced uranium, as U(IV), was detected in several cultures. Present in the cultures of D. desulfuricans were crystals of uranium. Examination of these cultures by electron microscopy indicates that the uranium (IV) is deposited outside of the cell and these needle-like crystals are associated with cellular material. X-ray probe analysis with the electron microscope gave an image that was in close agreement with U(IV). With D. desulfuricans in a continuous stirred tank reactor, kinetic parameters have been calculated for uranium reduction. Over a period of 20 to 60 hours, the amount of soluble uranium removed from the bioreactor was proportional to residence time over a period of 20 to 60 hours

  14. Rock excavation by pulsed electron beams

    International Nuclear Information System (INIS)

    Avery, R.T.; Keefe, D.; Brekke, T.L.; Finnie, I.

    1976-03-01

    If an intense short pulse of megavolt electrons is deposited in a brittle solid, dynamic spalling can be made to occur with removal of material. Experiments were made on several types of hard rock; results are reproducible and well-described theoretically. An accelerator with a rapidly-pulsed scanning electron beam was designed that could tunnel in hard rock about ten times faster than conventional drill/blast methods

  15. A low sludge generated anode by hybrid solar electrocoagulation for the removal of lead

    Science.gov (United States)

    Hussin, F.; Aroua, M. K.

    2017-06-01

    In this work, perforated zinc is proposed as a new anode for lead removal by hybrid solar electrocoagulation. The characteristics of the sludge were investigated to understand the behaviour of lead removal during electrocoagulation. Sludge products formed were characterised using X-ray diffraction (XRD), X-ray fluorescence (XRF) and Field Emission Scanning Electron Microscopy (FESEM). In addition, the pH variation during electrocoagulation and effects on the sludge products were examined. At optimum conditions showed that the perforated zinc electrode produced better performance with high removal efficiency, low sludge volume index and less energy consumption.

  16. A novel statistical method for classifying habitat generalists and specialists

    DEFF Research Database (Denmark)

    Chazdon, Robin L; Chao, Anne; Colwell, Robert K

    2011-01-01

    in second-growth (SG) and old-growth (OG) rain forests in the Caribbean lowlands of northeastern Costa Rica. We evaluate the multinomial model in detail for the tree data set. Our results for birds were highly concordant with a previous nonstatistical classification, but our method classified a higher......: (1) generalist; (2) habitat A specialist; (3) habitat B specialist; and (4) too rare to classify with confidence. We illustrate our multinomial classification method using two contrasting data sets: (1) bird abundance in woodland and heath habitats in southeastern Australia and (2) tree abundance...... fraction (57.7%) of bird species with statistical confidence. Based on a conservative specialization threshold and adjustment for multiple comparisons, 64.4% of tree species in the full sample were too rare to classify with confidence. Among the species classified, OG specialists constituted the largest...

  17. Ensemble of classifiers based network intrusion detection system performance bound

    CSIR Research Space (South Africa)

    Mkuzangwe, Nenekazi NP

    2017-11-01

    Full Text Available This paper provides a performance bound of a network intrusion detection system (NIDS) that uses an ensemble of classifiers. Currently researchers rely on implementing the ensemble of classifiers based NIDS before they can determine the performance...

  18. Neutralizing trapped electrons on the hydrogenated surface of a diamond amplifier

    Directory of Open Access Journals (Sweden)

    Xiangyun Chang

    2012-01-01

    Full Text Available We discuss our investigation of electron trapping in a diamond amplifier (DA. Our previous work demonstrated that some electrons reaching the DA’s hydrogenated surface are not emitted. The state and the removal of these electrons is important for DA applications. We found that these stopped electrons are trapped, and cannot be removed by a strong reversed-polarity electric field; to neutralize this surface charge, holes must be sent to the hydrogenated surface to recombine with the trapped electrons through the Shockley-Read-Hall surface-recombination mechanism. We measured the time taken for such recombination on the hydrogenated surface, viz. the recombination time, as less than 5 ns, limited by the resolution of our test system. With this measurement, we demonstrated that DA could be operated in an rf cavity with frequency of a few hundred megahertz.

  19. 3 CFR - Implementation of the Executive Order, “Classified National Security Information”

    Science.gov (United States)

    2010-01-01

    ... 29, 2009 Implementation of the Executive Order, “Classified National Security Information” Memorandum..., “Classified National Security Information” (the “order”), which substantially advances my goals for reforming... or handles classified information shall provide the Director of the Information Security Oversight...

  20. The need for an electronic multilingual dictionary

    Directory of Open Access Journals (Sweden)

    Anna Kisiel

    2014-09-01

    Full Text Available The need for an electronic multilingual dictionary The paper analyses the issue of providing adequate equivalents in multilingual dictionaries. If equivalents are adequate, it means that: (1 the scope of meaning of one item is identical to its equivalent (cf. drive: drive a nail vs. drive a car; and (2 the collocations of the equivalents overlap. Two significant problems arise when searching for adequate equivalents: the lack of equivalents whose meanings are identical (narrower/wider meanings, partial overlap of meanings, more than equally good equivalent, and equivalents with homographs in a given language. Because such issues are difficult to resolve in a printed dictionary, we put forward some methods of addressing the problems in an electronic dictionary. The paper offers an example entry from such a dictionary, which presents a suggestion of a layout. We also took into consideration the potential problems which may appear if the entry is presented in this manner: first, one must set a limit for the description (a defined number of lexical units; second, one must avoid circularity, but at the same time also strive for an exhaustive description. Electronic dictionaries offer greater possibilities of presenting modern vocabulary and adding new classifiers (e.g. a classifier of politeness.

  1. Removal of toxicity the pharmaceutical propranolol and your mixture with fluoxetine hydrochloride in aqueous solution using radiation with electron beam

    International Nuclear Information System (INIS)

    Boiani, Nathalia Fonseca

    2016-01-01

    Environmental health has been damage due to incorrect disposal of products and by-products. Among emerging pollutants it is possible to account with several pharmaceuticals, causing those problems when disposed in the environment by effluents. Conventional processing techniques are insufficient in removal of the pharmaceuticals, for having resistant waste and low biodegradability. Thus the advanced oxidation processes have been studied as an alternative for the treatment of different types of effluents. The objective of this study was to apply the process of irradiation with electron beam in order to reduce the toxic effects of propranolol, and the mixture with fluoxetine hydrochloride in aqueous solution. Ecotoxicological tests conducted with propranolol, and the mixture with fluoxetine hydrochloride, for Daphnia similis microcrustacean, and the Vibrio fischeri bacterium. It was observed that D. similis was more sensitive to propranolol drug and to the mixture, when compared to bacterium V.fischeri. After being subjected to the treatment with ionizing radiation, all applied doses to the propranolol and the mixture, showed significant reduction of toxicity, for D. similis. Different were the results for V. fischeri, when only 5.0 kGy reduced toxicity to propranolol. The mixture of pharmaceuticals required 2.5 and 5.0 kGy for reducing toxicity. 5.0 kGy showed the best removal efficiency for toxicity: 79.94 % for D. similis and 15.64 % for V. fischeri, when exposed to propranolol. The mixture reduction efficacy were 81.59% and 26.93 % for D.similis and V.fischeri, respectively. (author)

  2. Implications of physical symmetries in adaptive image classifiers

    DEFF Research Database (Denmark)

    Sams, Thomas; Hansen, Jonas Lundbek

    2000-01-01

    It is demonstrated that rotational invariance and reflection symmetry of image classifiers lead to a reduction in the number of free parameters in the classifier. When used in adaptive detectors, e.g. neural networks, this may be used to decrease the number of training samples necessary to learn...... a given classification task, or to improve generalization of the neural network. Notably, the symmetrization of the detector does not compromise the ability to distinguish objects that break the symmetry. (C) 2000 Elsevier Science Ltd. All rights reserved....

  3. Removal of iodomethane from air using a plot-scale corona discharge scrubber

    International Nuclear Information System (INIS)

    Dickson, L.W.; Toft-Hall, A.; Torgerson, D.F.

    1985-12-01

    This report presents the results of a study of the removal of iodomethane from air using a pilot-scale corona discharge scrubber. The removal was measured in the following parameter ranges: bulk air flow, 30 to 350 m 3 /h; initial CH 3 I concentration, 6 to 230 μmol/m 3 ; and discharge current, 0 to 75 mA DC (negative polarity). Approximately five to ten moles of iodomethane are removed per mole of electrons added to the air stream at a discharge voltage of ∼ 10 kV. This removal efficiency suggests that both ion-molecule and radical-molecule reactions may be important in the removal of iodomethane from air in a corona discharge. The results of this pilot-scale demonstration indicate that a corona discharge scrubber would be suitable for removing iodine species from air as part of the emergency filtered-air discharge system of a nuclear reactor. The application of this technology to the control of nitrogen oxide, sulfur dioxide and hydrogen sulfide emissions is being investigated. 15 refs

  4. Discrimination of chicken seasonings and beef seasonings using electronic nose and sensory evaluation.

    Science.gov (United States)

    Tian, Huaixiang; Li, Fenghua; Qin, Lan; Yu, Haiyan; Ma, Xia

    2014-11-01

    This study examines the feasibility of electronic nose as a method to discriminate chicken and beef seasonings and to predict sensory attributes. Sensory evaluation showed that 8 chicken seasonings and 4 beef seasonings could be well discriminated and classified based on 8 sensory attributes. The sensory attributes including chicken/beef, gamey, garlic, spicy, onion, soy sauce, retention, and overall aroma intensity were generated by a trained evaluation panel. Principal component analysis (PCA), discriminant factor analysis (DFA), and cluster analysis (CA) combined with electronic nose were used to discriminate seasoning samples based on the difference of the sensor response signals of chicken and beef seasonings. The correlation between sensory attributes and electronic nose sensors signal was established using partial least squares regression (PLSR) method. The results showed that the seasoning samples were all correctly classified by the electronic nose combined with PCA, DFA, and CA. The electronic nose gave good prediction results for all the sensory attributes with correlation coefficient (r) higher than 0.8. The work indicated that electronic nose is an effective method for discriminating different seasonings and predicting sensory attributes. © 2014 Institute of Food Technologists®

  5. 36 CFR 1256.70 - What controls access to national security-classified information?

    Science.gov (United States)

    2010-07-01

    ... national security-classified information? 1256.70 Section 1256.70 Parks, Forests, and Public Property... HISTORICAL MATERIALS Access to Materials Containing National Security-Classified Information § 1256.70 What controls access to national security-classified information? (a) The declassification of and public access...

  6. Scanning electron microscopy analysis of the growth of dental plaque on the surfaces of removable orthodontic aligners after the use of different cleaning methods.

    Science.gov (United States)

    Levrini, Luca; Novara, Francesca; Margherini, Silvia; Tenconi, Camilla; Raspanti, Mario

    2015-01-01

    Advances in orthodontics are leading to the use of minimally invasive technologies, such as transparent removable aligners, and are able to meet high demands in terms of performance and esthetics. However, the most correct method of cleaning these appliances, in order to minimize the effects of microbial colonization, remains to be determined. The aim of the present study was to identify the most effective method of cleaning removable orthodontic aligners, analyzing the growth of dental plaque as observed under scanning electron microscopy. Twelve subjects were selected for the study. All were free from caries and periodontal disease and were candidates for orthodontic therapy with invisible orthodontic aligners. The trial had a duration of 6 weeks, divided into three 2-week stages, during which three sets of aligners were used. In each stage, the subjects were asked to use a different method of cleaning their aligners: 1) running water (control condition); 2) effervescent tablets containing sodium carbonate and sulfate crystals followed by brushing with a toothbrush; and 3) brushing alone (with a toothbrush and toothpaste). At the end of each 2-week stage, the surfaces of the aligners were analyzed under scanning electron microscopy. The best results were obtained with brushing combined with the use of sodium carbonate and sulfate crystals; brushing alone gave slightly inferior results. On the basis of previous literature results relating to devices in resin, studies evaluating the reliability of domestic ultrasonic baths for domestic use should be encouraged. At present, pending the availability of experimental evidence, it can be suggested that dental hygienists should strongly advise patients wearing orthodontic aligners to clean them using a combination of brushing and commercially available tablets for cleaning oral appliances.

  7. Investigation and in situ removal of spatter generated during laser ablation of aluminium composites

    International Nuclear Information System (INIS)

    Popescu, A.C.; Delval, C.; Shadman, S.; Leparoux, M.

    2016-01-01

    Highlights: • Study of spatter generated during laser irradiation of an aluminium nanocomposite. • Number of droplets was 1.5–3 times higher for laser in depth vs surface focused beams. • High speed imaging revealed particles exploding in flight similar to a fireworks effect. • Three methods were selected for droplets removal in situ and the results are analyzed. - Abstract: Spatter generated during laser irradiation of an aluminium alloy nanocomposite (AlMg5 reinforced with Al_2O_3 nanoparticles) was monitored by high speed imaging. Droplets trajectory and speed were assessed by computerized image analysis. The effects of laser peak power and laser focusing on the plume expansion and expulsed droplet speeds were studied in air or under argon flow. It was found that the velocity of visible droplets expulsed laterally or at the end of the plume emission from the metal surface was not dependent on the plasma plume speed. The neighbouring area of irradiation sites was studied by optical and scanning electron microscopy. Droplets deposited on the surface were classified according to their size and counted using a digital image processing software. It was observed that the number of droplets on surface was 1.5–3 times higher when the laser beam was focused in depth as compared to focused beams, even though the populations average diameter were comparable. Three methods were selected for removing droplets in situ, during plume expansion: an argon gas jet crossing the plasma plume, a fused silica plate collector transparent to the laser wavelength placed parallel to the irradiated surface and a mask placed onto the aluminium composite surface. The argon gas jet was efficient only for low power irradiation conditions, the fused silica plate failed in all tested conditions and the mask was successful for all irradiation regimes.

  8. Optimization of short amino acid sequences classifier

    Science.gov (United States)

    Barcz, Aleksy; Szymański, Zbigniew

    This article describes processing methods used for short amino acid sequences classification. The data processed are 9-symbols string representations of amino acid sequences, divided into 49 data sets - each one containing samples labeled as reacting or not with given enzyme. The goal of the classification is to determine for a single enzyme, whether an amino acid sequence would react with it or not. Each data set is processed separately. Feature selection is performed to reduce the number of dimensions for each data set. The method used for feature selection consists of two phases. During the first phase, significant positions are selected using Classification and Regression Trees. Afterwards, symbols appearing at the selected positions are substituted with numeric values of amino acid properties taken from the AAindex database. In the second phase the new set of features is reduced using a correlation-based ranking formula and Gram-Schmidt orthogonalization. Finally, the preprocessed data is used for training LS-SVM classifiers. SPDE, an evolutionary algorithm, is used to obtain optimal hyperparameters for the LS-SVM classifier, such as error penalty parameter C and kernel-specific hyperparameters. A simple score penalty is used to adapt the SPDE algorithm to the task of selecting classifiers with best performance measures values.

  9. Rock excavation by pulsed electron beams

    International Nuclear Information System (INIS)

    Avery, R.T.; Keefe, D.; Brekke, T.L.; Finnie, I.

    1976-01-01

    If an intense short pulse of megavolt electrons is deposited in a brittle solid, dynamic spalling can be made to occur with removal of material. Experiments have been made on several types of hard rock; results are reproducible and well-described theoretically. An accelerator with a rapid-pulsed scanning electron-beam has been designed that could tunnel in hard rock about ten times faster than conventional drill/blast methods. (author)

  10. A support vector machine classifier reduces interscanner variation in the HRCT classification of regional disease pattern in diffuse lung disease: Comparison to a Bayesian classifier

    Energy Technology Data Exchange (ETDEWEB)

    Chang, Yongjun; Lim, Jonghyuck; Kim, Namkug; Seo, Joon Beom [Department of Radiology, University of Ulsan College of Medicine, 388-1 Pungnap2-dong, Songpa-gu, Seoul 138-736 (Korea, Republic of); Lynch, David A. [Department of Radiology, National Jewish Medical and Research Center, Denver, Colorado 80206 (United States)

    2013-05-15

    Purpose: To investigate the effect of using different computed tomography (CT) scanners on the accuracy of high-resolution CT (HRCT) images in classifying regional disease patterns in patients with diffuse lung disease, support vector machine (SVM) and Bayesian classifiers were applied to multicenter data. Methods: Two experienced radiologists marked sets of 600 rectangular 20 Multiplication-Sign 20 pixel regions of interest (ROIs) on HRCT images obtained from two scanners (GE and Siemens), including 100 ROIs for each of local patterns of lungs-normal lung and five of regional pulmonary disease patterns (ground-glass opacity, reticular opacity, honeycombing, emphysema, and consolidation). Each ROI was assessed using 22 quantitative features belonging to one of the following descriptors: histogram, gradient, run-length, gray level co-occurrence matrix, low-attenuation area cluster, and top-hat transform. For automatic classification, a Bayesian classifier and a SVM classifier were compared under three different conditions. First, classification accuracies were estimated using data from each scanner. Next, data from the GE and Siemens scanners were used for training and testing, respectively, and vice versa. Finally, all ROI data were integrated regardless of the scanner type and were then trained and tested together. All experiments were performed based on forward feature selection and fivefold cross-validation with 20 repetitions. Results: For each scanner, better classification accuracies were achieved with the SVM classifier than the Bayesian classifier (92% and 82%, respectively, for the GE scanner; and 92% and 86%, respectively, for the Siemens scanner). The classification accuracies were 82%/72% for training with GE data and testing with Siemens data, and 79%/72% for the reverse. The use of training and test data obtained from the HRCT images of different scanners lowered the classification accuracy compared to the use of HRCT images from the same scanner. For

  11. A support vector machine classifier reduces interscanner variation in the HRCT classification of regional disease pattern in diffuse lung disease: Comparison to a Bayesian classifier

    International Nuclear Information System (INIS)

    Chang, Yongjun; Lim, Jonghyuck; Kim, Namkug; Seo, Joon Beom; Lynch, David A.

    2013-01-01

    Purpose: To investigate the effect of using different computed tomography (CT) scanners on the accuracy of high-resolution CT (HRCT) images in classifying regional disease patterns in patients with diffuse lung disease, support vector machine (SVM) and Bayesian classifiers were applied to multicenter data. Methods: Two experienced radiologists marked sets of 600 rectangular 20 × 20 pixel regions of interest (ROIs) on HRCT images obtained from two scanners (GE and Siemens), including 100 ROIs for each of local patterns of lungs—normal lung and five of regional pulmonary disease patterns (ground-glass opacity, reticular opacity, honeycombing, emphysema, and consolidation). Each ROI was assessed using 22 quantitative features belonging to one of the following descriptors: histogram, gradient, run-length, gray level co-occurrence matrix, low-attenuation area cluster, and top-hat transform. For automatic classification, a Bayesian classifier and a SVM classifier were compared under three different conditions. First, classification accuracies were estimated using data from each scanner. Next, data from the GE and Siemens scanners were used for training and testing, respectively, and vice versa. Finally, all ROI data were integrated regardless of the scanner type and were then trained and tested together. All experiments were performed based on forward feature selection and fivefold cross-validation with 20 repetitions. Results: For each scanner, better classification accuracies were achieved with the SVM classifier than the Bayesian classifier (92% and 82%, respectively, for the GE scanner; and 92% and 86%, respectively, for the Siemens scanner). The classification accuracies were 82%/72% for training with GE data and testing with Siemens data, and 79%/72% for the reverse. The use of training and test data obtained from the HRCT images of different scanners lowered the classification accuracy compared to the use of HRCT images from the same scanner. For integrated ROI

  12. Safe Handover : Safe Patients – The Electronic Handover System

    Science.gov (United States)

    Till, Alex; Sall, Hanish; Wilkinson, Jonathan

    2014-01-01

    Failure of effective handover is a major preventable cause of patient harm. We aimed to promote accurate recording of high-quality clinical information using an Electronic Handover System (EHS) that would contribute to a sustainable improvement in effective patient care and safety. Within our hospital the human factors associated with poor communication were compromising patient care and unnecessarily increasing the workload of staff due to the poor quality of handovers. Only half of handovers were understood by the doctors expected to complete them, and more than half of our medical staff felt it posed a risk to patient safety. We created a standardised proforma for handovers that contained specific sub-headings, re-classified patient risk assessments, and aided escalation of care by adding prompts for verbal handover. Sources of miscommunication were removed, accountability for handovers provided, and tasks were re-organised to reduce the workload of staff. Long-term, three-month data showed that each sub-heading achieved at least 80% compliance (an average improvement of approximately 40% for the overall quality of handovers). This translated into 91% of handovers being subjectively clear to junior doctors. 87% of medical staff felt we had reduced a risk to patient safety and 80% felt it increased continuity of care. Without guidance, doctors omit key information required for effective handover. All organisations should consider implementing an electronic handover system as a viable, sustainable and safe solution to handover of care that allows patient safety to remain at the heart of the NHS. PMID:26734244

  13. Comparison of decomposition characteristics between aromatic and aliphatic VOCs using electron beam

    International Nuclear Information System (INIS)

    Kim, Jo-Chun

    2011-01-01

    The removal efficiency of n-decane (C 10 H 22 ) by electron beam was the highest among aliphatic VOCs of concern, and that of n-hexane (C 6 H 14 ), n-butane (C 4 H 10 ), and methane (CH 4 ) followed. On the other hand, in terms of aromatic VOC decomposition efficiencies, benzene (C 6 H 6 ) decomposition was the lowest and that of toluene (C 7 H 8 ), ethylbenzene (C 8 H 10 ), and p-xylene (C 8 H 10 ) were similar. It was also found that there was increase in by-product (untreated VOC, CO, CO 2 , O 3 , and other compounds) formation as well as all VOC removal efficiencies. It was demonstrated that the removal efficiency of VOC increased as its concentration decreased and the irradiation dose increased. In addition, low removal efficiency was observed because helium was relatively stable compared to the other gases, and nothing but electrons produced by electron accelerator reacted with VOC. It was also found that relative humidity had some effects on the decomposition rates of VOC. The removal efficiency at the 100% RH condition was slightly higher than that at 7.4% RH (dry condition) due to OH radical formation. (author)

  14. Silicon nanowire arrays as learning chemical vapour classifiers

    International Nuclear Information System (INIS)

    Niskanen, A O; Colli, A; White, R; Li, H W; Spigone, E; Kivioja, J M

    2011-01-01

    Nanowire field-effect transistors are a promising class of devices for various sensing applications. Apart from detecting individual chemical or biological analytes, it is especially interesting to use multiple selective sensors to look at their collective response in order to perform classification into predetermined categories. We show that non-functionalised silicon nanowire arrays can be used to robustly classify different chemical vapours using simple statistical machine learning methods. We were able to distinguish between acetone, ethanol and water with 100% accuracy while methanol, ethanol and 2-propanol were classified with 96% accuracy in ambient conditions.

  15. Synthesis, characterization and adsorption properties of microcrystalline cellulose based nanogel for dyes and heavy metals removal.

    Science.gov (United States)

    El-Naggar, Mehrez E; Radwan, Emad K; El-Wakeel, Shaimaa T; Kafafy, Hany; Gad-Allah, Tarek A; El-Kalliny, Amer S; Shaheen, Tharwat I

    2018-07-01

    Recently, naturally occurring biopolymers have attracted the attention as potential adsorbents for the removal of water contaminants. In this work, we present the development of microcrystalline cellulose (MCC)-based nanogel grafted with acrylamide and acrylic acid in the presence of methylene bisacrylamide and potassium persulphate as a crosslinking agent and initiator, respectively. World-class facilities such as X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), surface analysis, field emission scanning electron microscopy (FE-SEM), high resolution transmission electron microscopy (HR-TEM) and zeta sizer were used to characterize the synthesized MCC based nanogel. The prepared nanogel was applied to remove reactive red 195 (RR195) dye and Cd (II) from aqueous medium at different operational conditions. The adsorption experiments showed that the feed concentration of monomers has a significant effect on the removal of RR195 which peaked (93% removal) after 10min of contact time at pH2 and a dose of 1.5g/L. On contrary, the feed concentration has insignificant effect on the removal of Cd (II) which peaked (97% removal) after 30min of contact time at pH6 and a dose of 0.5g/L. The adsorption equilibrium data of RR195 and Cd (II) was best described by Freundlich and Langmuir, respectively. Conclusively, the prepared MCC based nanogels were proved as promising adsorbents for the removal of organic pollutants as well as heavy metals. Copyright © 2018 Elsevier B.V. All rights reserved.

  16. 48 CFR 8.608 - Protection of classified and sensitive information.

    Science.gov (United States)

    2010-10-01

    ... Prison Industries, Inc. 8.608 Protection of classified and sensitive information. Agencies shall not enter into any contract with FPI that allows an inmate worker access to any— (a) Classified data; (b) Geographic data regarding the location of— (1) Surface and subsurface infrastructure providing communications...

  17. Classified Component Disposal at the Nevada National Security Site (NNSS) - 13454

    Energy Technology Data Exchange (ETDEWEB)

    Poling, Jeanne; Arnold, Pat [National Security Technologies, LLC (NSTec), P.O. Box 98521, Las Vegas, NV 89193-8521 (United States); Saad, Max [Sandia National Laboratories, P.O. Box 5800, Albuquerque, NM 87185 (United States); DiSanza, Frank [E. Frank DiSanza Consulting, 2250 Alanhurst Drive, Henderson, NV 89052 (United States); Cabble, Kevin [U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office, P.O. Box 98518, Las Vegas, NV 89193-8518 (United States)

    2013-07-01

    The Nevada National Security Site (NNSS) has added the capability needed for the safe, secure disposal of non-nuclear classified components that have been declared excess to national security requirements. The NNSS has worked with U.S. Department of Energy, National Nuclear Security Administration senior leadership to gain formal approval for permanent burial of classified matter at the NNSS in the Area 5 Radioactive Waste Management Complex owned by the U.S. Department of Energy. Additionally, by working with state regulators, the NNSS added the capability to dispose non-radioactive hazardous and non-hazardous classified components. The NNSS successfully piloted the new disposal pathway with the receipt of classified materials from the Kansas City Plant in March 2012. (authors)

  18. Classified Component Disposal at the Nevada National Security Site (NNSS) - 13454

    International Nuclear Information System (INIS)

    Poling, Jeanne; Arnold, Pat; Saad, Max; DiSanza, Frank; Cabble, Kevin

    2013-01-01

    The Nevada National Security Site (NNSS) has added the capability needed for the safe, secure disposal of non-nuclear classified components that have been declared excess to national security requirements. The NNSS has worked with U.S. Department of Energy, National Nuclear Security Administration senior leadership to gain formal approval for permanent burial of classified matter at the NNSS in the Area 5 Radioactive Waste Management Complex owned by the U.S. Department of Energy. Additionally, by working with state regulators, the NNSS added the capability to dispose non-radioactive hazardous and non-hazardous classified components. The NNSS successfully piloted the new disposal pathway with the receipt of classified materials from the Kansas City Plant in March 2012. (authors)

  19. NOx reduction by compact electron beam processing

    International Nuclear Information System (INIS)

    Penetrante, B.M.; Hsiao, M.C.; Merritt, B.T.; Wallman, P.H.; Vogtlin, G.E.

    1995-01-01

    Among the new methods being investigated for the post-combustion removal of nitrogen oxides (NO x ) are based on non-thermal plasmas. These plasmas can be produced by electrical discharge methods or electron beam irradiation. The application of electron beam irradiation for NO x removal in power plant flue gases has been investigated since the early 1970's in both laboratory- and pilot-scale experiments. Electrical discharge methods are relatively new entrants in the field of flue gas cleanup. Pulsed corona and dielectric-barrier discharge techniques are two of the more commonly used electrical discharge methods for producing nonthermal plasmas at atmospheric pressure. There are basically two types of reactions responsible for the depletion of NO by non-thermal plasmas: oxidation and reduction

  20. An Active Learning Classifier for Further Reducing Diabetic Retinopathy Screening System Cost

    Directory of Open Access Journals (Sweden)

    Yinan Zhang

    2016-01-01

    Full Text Available Diabetic retinopathy (DR screening system raises a financial problem. For further reducing DR screening cost, an active learning classifier is proposed in this paper. Our approach identifies retinal images based on features extracted by anatomical part recognition and lesion detection algorithms. Kernel extreme learning machine (KELM is a rapid classifier for solving classification problems in high dimensional space. Both active learning and ensemble technique elevate performance of KELM when using small training dataset. The committee only proposes necessary manual work to doctor for saving cost. On the publicly available Messidor database, our classifier is trained with 20%–35% of labeled retinal images and comparative classifiers are trained with 80% of labeled retinal images. Results show that our classifier can achieve better classification accuracy than Classification and Regression Tree, radial basis function SVM, Multilayer Perceptron SVM, Linear SVM, and K Nearest Neighbor. Empirical experiments suggest that our active learning classifier is efficient for further reducing DR screening cost.

  1. Generalization in the XCSF classifier system: analysis, improvement, and extension.

    Science.gov (United States)

    Lanzi, Pier Luca; Loiacono, Daniele; Wilson, Stewart W; Goldberg, David E

    2007-01-01

    We analyze generalization in XCSF and introduce three improvements. We begin by showing that the types of generalizations evolved by XCSF can be influenced by the input range. To explain these results we present a theoretical analysis of the convergence of classifier weights in XCSF which highlights a broader issue. In XCSF, because of the mathematical properties of the Widrow-Hoff update, the convergence of classifier weights in a given subspace can be slow when the spread of the eigenvalues of the autocorrelation matrix associated with each classifier is large. As a major consequence, the system's accuracy pressure may act before classifier weights are adequately updated, so that XCSF may evolve piecewise constant approximations, instead of the intended, and more efficient, piecewise linear ones. We propose three different ways to update classifier weights in XCSF so as to increase the generalization capabilities of XCSF: one based on a condition-based normalization of the inputs, one based on linear least squares, and one based on the recursive version of linear least squares. Through a series of experiments we show that while all three approaches significantly improve XCSF, least squares approaches appear to be best performing and most robust. Finally we show how XCSF can be extended to include polynomial approximations.

  2. Electron beam treatment of simulated marine diesel exhaust gases

    Directory of Open Access Journals (Sweden)

    Licki Janusz

    2015-09-01

    Full Text Available The exhaust gases from marine diesel engines contain high SO2 and NOx concentration. The applicability of the electron beam flue gas treatment technology for purification of marine diesel exhaust gases containing high SO2 and NOx concentration gases was the main goal of this paper. The study was performed in the laboratory plant with NOx concentration up to 1700 ppmv and SO2 concentration up to 1000 ppmv. Such high NOx and SO2 concentrations were observed in the exhaust gases from marine high-power diesel engines fuelled with different heavy fuel oils. In the first part of study the simulated exhaust gases were irradiated by the electron beam from accelerator. The simultaneous removal of SO2 and NOx were obtained and their removal efficiencies strongly depend on irradiation dose and inlet NOx concentration. For NOx concentrations above 800 ppmv low removal efficiencies were obtained even if applied high doses. In the second part of study the irradiated gases were directed to the seawater scrubber for further purification. The scrubbing process enhances removal efficiencies of both pollutants. The SO2 removal efficiencies above 98.5% were obtained with irradiation dose greater than 5.3 kGy. For inlet NOx concentrations of 1700 ppmv the NOx removal efficiency about 51% was obtained with dose greater than 8.8 kGy. Methods for further increase of NOx removal efficiency are presented in the paper.

  3. Purification technology for flue/off gases using electron beams

    International Nuclear Information System (INIS)

    Kojima, Takuji

    2004-01-01

    The present paper describes research and development on purification technology using electron beams for flue/off gases containing pollutants: removal of sulfate oxide and nitrogen oxide from flue gases of coal/oil combustion power plants, decomposition of dioxins in waste incineration flue gas, and decomposition/removal of toxic volatile organic compounds from off gas. (author)

  4. Statistical and Machine-Learning Classifier Framework to Improve Pulse Shape Discrimination System Design

    Energy Technology Data Exchange (ETDEWEB)

    Wurtz, R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Kaplan, A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2015-10-28

    Pulse shape discrimination (PSD) is a variety of statistical classifier. Fully-­realized statistical classifiers rely on a comprehensive set of tools for designing, building, and implementing. PSD advances rely on improvements to the implemented algorithm. PSD advances can be improved by using conventional statistical classifier or machine learning methods. This paper provides the reader with a glossary of classifier-­building elements and their functions in a fully-­designed and operational classifier framework that can be used to discover opportunities for improving PSD classifier projects. This paper recommends reporting the PSD classifier’s receiver operating characteristic (ROC) curve and its behavior at a gamma rejection rate (GRR) relevant for realistic applications.

  5. Classifier-ensemble incremental-learning procedure for nuclear transient identification at different operational conditions

    Energy Technology Data Exchange (ETDEWEB)

    Baraldi, Piero, E-mail: piero.baraldi@polimi.i [Dipartimento di Energia - Sezione Ingegneria Nucleare, Politecnico di Milano, via Ponzio 34/3, 20133 Milano (Italy); Razavi-Far, Roozbeh [Dipartimento di Energia - Sezione Ingegneria Nucleare, Politecnico di Milano, via Ponzio 34/3, 20133 Milano (Italy); Zio, Enrico [Dipartimento di Energia - Sezione Ingegneria Nucleare, Politecnico di Milano, via Ponzio 34/3, 20133 Milano (Italy); Ecole Centrale Paris-Supelec, Paris (France)

    2011-04-15

    An important requirement for the practical implementation of empirical diagnostic systems is the capability of classifying transients in all plant operational conditions. The present paper proposes an approach based on an ensemble of classifiers for incrementally learning transients under different operational conditions. New classifiers are added to the ensemble where transients occurring in new operational conditions are not satisfactorily classified. The construction of the ensemble is made by bagging; the base classifier is a supervised Fuzzy C Means (FCM) classifier whose outcomes are combined by majority voting. The incremental learning procedure is applied to the identification of simulated transients in the feedwater system of a Boiling Water Reactor (BWR) under different reactor power levels.

  6. Classifier-ensemble incremental-learning procedure for nuclear transient identification at different operational conditions

    International Nuclear Information System (INIS)

    Baraldi, Piero; Razavi-Far, Roozbeh; Zio, Enrico

    2011-01-01

    An important requirement for the practical implementation of empirical diagnostic systems is the capability of classifying transients in all plant operational conditions. The present paper proposes an approach based on an ensemble of classifiers for incrementally learning transients under different operational conditions. New classifiers are added to the ensemble where transients occurring in new operational conditions are not satisfactorily classified. The construction of the ensemble is made by bagging; the base classifier is a supervised Fuzzy C Means (FCM) classifier whose outcomes are combined by majority voting. The incremental learning procedure is applied to the identification of simulated transients in the feedwater system of a Boiling Water Reactor (BWR) under different reactor power levels.

  7. Removing NDMA (N,N-dimethylnitrosamine) from natural waters

    Energy Technology Data Exchange (ETDEWEB)

    Mezyk, S P [California State University Long Beach, (United States); Cooper, W J [University of North Carolina at Wilmington, (United States); Bartels, D M [Argonne National Laboratory, (United States)

    2003-07-01

    Nitrosoamines are ubiquitous in water environments, and are of concern as they are potent carcinogens. In particular, N,N-dimethylnitrosamine (NDMA, (CH{sub 3}){sub 2} NNO) is volatile, and therefore has been detected around factories producing secondary amines or rocket fuel, in areas near industrial plants that use dimethylamine in organic synthesis, and even in foods and beverages that contain nitrite or which have been exposed to nitrous oxides. Various technologies have been suggested for removing trace levels of NDMA contamination from aqueous systems. However, Advanced Oxidation Technologies (AOTs), such as ozone, UV/ozone, and UV/H{sub 2}O{sub 2} , which use oxidation via the hydroxyl radical ({sup .}OH), or heterogeneous catalysis by TiO{sub 2} , sonolysis, or the electron beam process, which produce a mixture of oxidizing {sup .}OH radicals with reducing hydrated electrons (e{sup -}{sub aq} ) and hydrogen atoms ({sup .} H), may also produce unwanted stable products in the treatment. Some of these stable products, such as secondary amines, allow regeneration of NDMA to occur. To ensure that any process applied to NDMA contaminated water occurs efficiently and quantitatively a complete understanding of the chemistry involved under the conditions of use is necessary. This requires mathematical modeling of the process, which in turn needs reaction rate constants and mechanisms. In this study, absolute rate constants at room temperature for the reaction of the hydroxyl radical, hydrated electron, and hydrogen atom with NDMA in water have been determined using electron pulse radiolysis and absorption spectroscopy, (e{sup -}{sub aq} and {sup .}OH) and EPR free induction decay attenuation ({sup .}H) measurements. The specific values of (4.30{+-} 0.12) x 10 8 , (1.41 {+-} 0.02) x 10 10 , and (2.01 {+-} 0.03) x 10{sup 8} M{sup -1} s{sup -1} , respectively, demonstrate that the reductive destruction of this nitrosoamine would be the dominant removal pathway in any

  8. Removing NDMA (N,N-dimethylnitrosamine) from natural waters

    International Nuclear Information System (INIS)

    Mezyk, S.P.; Cooper, W.J.; Bartels, D.M.

    2003-01-01

    Nitrosoamines are ubiquitous in water environments, and are of concern as they are potent carcinogens. In particular, N,N-dimethylnitrosamine (NDMA, (CH 3 ) 2 NNO) is volatile, and therefore has been detected around factories producing secondary amines or rocket fuel, in areas near industrial plants that use dimethylamine in organic synthesis, and even in foods and beverages that contain nitrite or which have been exposed to nitrous oxides. Various technologies have been suggested for removing trace levels of NDMA contamination from aqueous systems. However, Advanced Oxidation Technologies (AOTs), such as ozone, UV/ozone, and UV/H 2 O 2 , which use oxidation via the hydroxyl radical ( . OH), or heterogeneous catalysis by TiO 2 , sonolysis, or the electron beam process, which produce a mixture of oxidizing . OH radicals with reducing hydrated electrons (e - aq ) and hydrogen atoms ( . H), may also produce unwanted stable products in the treatment. Some of these stable products, such as secondary amines, allow regeneration of NDMA to occur. To ensure that any process applied to NDMA contaminated water occurs efficiently and quantitatively a complete understanding of the chemistry involved under the conditions of use is necessary. This requires mathematical modeling of the process, which in turn needs reaction rate constants and mechanisms. In this study, absolute rate constants at room temperature for the reaction of the hydroxyl radical, hydrated electron, and hydrogen atom with NDMA in water have been determined using electron pulse radiolysis and absorption spectroscopy, (e - aq and . OH) and EPR free induction decay attenuation ( . H) measurements. The specific values of (4.30± 0.12) x 10 8 , (1.41 ± 0.02) x 10 10 , and (2.01 ± 0.03) x 10 8 M -1 s -1 , respectively, demonstrate that the reductive destruction of this nitrosoamine would be the dominant removal pathway in any remediation process. Based on these data we have begun modeling the large-scale electron

  9. Removing nickel from nickel-coated carbon fibers

    Science.gov (United States)

    Hardianto, A.; Hertleer, C.; De Mey, G.; Van Langenhove, L.

    2017-10-01

    Conductive fibers/yarns are one of the most important materials for smart textiles because of their electrically conductive functionality combined with flexibility and light weight. They can be applied in many fields such as the medical sector, electronics, sensors and even as thermoelectric generators. Temperature sensors, for example, can be made using the thermocouple or thermopile principle which usually uses two different metal wires that can produce a temperature-dependent voltage. However, if metal wires are inserted into a textile structure, they will decrease the flexibility properties of the textile product. Nickel-coated Carbon Fiber (NiCF), a conductive textile yarn, has a potential use as a textile-based thermopile if we can create an alternating region of carbon and nickel along the fiber which in turn it can be used for substituting the metallic thermopile. The idea was to remove nickel from NiCF in order to obtain a yarn that contains alternating zones of carbon and nickel. Due to no literature reporting on how to remove nickel from NiCF, in this paper we investigated some chemicals to remove nickel from NiCF.

  10. Surfactant modified zeolite as amphiphilic and dual-electronic adsorbent for removal of cationic and oxyanionic metal ions and organic compounds.

    Science.gov (United States)

    Tran, Hai Nguyen; Viet, Pham Van; Chao, Huan-Ping

    2018-01-01

    A hydrophilic Y zeolite was primarily treated with sodium hydroxide to enhance its cation exchange capacity (Na-zeolite). The organo-zeolite (Na-H-zeolite) was prepared by a modification process of the external surface of Na-zeolite with a cationic surfactant (hexadecyltrimethylammonium; HDTMA). Three adsorbents (i.e., pristine zeolite, Na-zeolite, and Na-H-zeolite) were characterized with nitrogen adsorption/desorption isotherms, scanning electron microscopy coupled with energy dispersive X-ray spectroscopy, cation exchange capacities, and zeta potential. Results demonstrated that HDTMA can be adsorbed on the surface of Na-zeolite to form patchy bilayers. The adsorption capacity of several hazardous pollutants (i.e., Pb 2+ , Cu 2+ , Ni 2+ , Cr 2 O 7 2- , propylbenzene, ethylbenzene, toluene, benzene, and phenol) onto Na-H-zeolite was investigated in a single system and multiple-components. Adsorption isotherm was measured to further understand the effects of the modification process on the adsorption behaviors of Na-H-zeolite. Adsorption performances indicated that Na-H-zeolite can simultaneously adsorb the metal cations (on the surface not covered by HDTMA), oxyanions (on the surface covered by HDTMA). Na-H-zeolite also exhibited both hydrophilic and hydrophobic surfaces to uptake organic compounds with various water solubilities (from 55 to 75,000mg/L). It was experimentally concluded that Na-H-zeolite is a potential dual-electronic and amphiphilic adsorbent for efficiently removing a wide range of potentially toxic pollutants from aquatic environments. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Iceberg Semantics For Count Nouns And Mass Nouns: Classifiers, measures and portions

    Directory of Open Access Journals (Sweden)

    Fred Landman

    2016-12-01

    It is the analysis of complex NPs and their mass-count properties that is the focus of the second part of this paper. There I develop an analysis of English and Dutch pseudo- partitives, in particular, measure phrases like three liters of wine and classifier phrases like three glasses of wine. We will study measure interpretations and classifier interpretations of measures and classifiers, and different types of classifier interpretations: container interpretations, contents interpretations, and - indeed - portion interpretations. Rothstein 2011 argues that classifier interpretations (including portion interpretations of pseudo partitives pattern with count nouns, but that measure interpretations pattern with mass nouns. I will show that this distinction follows from the very basic architecture of Iceberg semantics.

  12. 18 CFR 3a.12 - Authority to classify official information.

    Science.gov (United States)

    2010-04-01

    ... efficient administration. (b) The authority to classify information or material originally as Top Secret is... classify information or material originally as Secret is exercised only by: (1) Officials who have Top... information or material originally as Confidential is exercised by officials who have Top Secret or Secret...

  13. Electronic Nose Odor Classification with Advanced Decision Tree Structures

    Directory of Open Access Journals (Sweden)

    S. Guney

    2013-09-01

    Full Text Available Electronic nose (e-nose is an electronic device which can measure chemical compounds in air and consequently classify different odors. In this paper, an e-nose device consisting of 8 different gas sensors was designed and constructed. Using this device, 104 different experiments involving 11 different odor classes (moth, angelica root, rose, mint, polis, lemon, rotten egg, egg, garlic, grass, and acetone were performed. The main contribution of this paper is the finding that using the chemical domain knowledge it is possible to train an accurate odor classification system. The domain knowledge about chemical compounds is represented by a decision tree whose nodes are composed of classifiers such as Support Vector Machines and k-Nearest Neighbor. The overall accuracy achieved with the proposed algorithm and the constructed e-nose device was 97.18 %. Training and testing data sets used in this paper are published online.

  14. Human Activity Recognition by Combining a Small Number of Classifiers.

    Science.gov (United States)

    Nazabal, Alfredo; Garcia-Moreno, Pablo; Artes-Rodriguez, Antonio; Ghahramani, Zoubin

    2016-09-01

    We consider the problem of daily human activity recognition (HAR) using multiple wireless inertial sensors, and specifically, HAR systems with a very low number of sensors, each one providing an estimation of the performed activities. We propose new Bayesian models to combine the output of the sensors. The models are based on a soft outputs combination of individual classifiers to deal with the small number of sensors. We also incorporate the dynamic nature of human activities as a first-order homogeneous Markov chain. We develop both inductive and transductive inference methods for each model to be employed in supervised and semisupervised situations, respectively. Using different real HAR databases, we compare our classifiers combination models against a single classifier that employs all the signals from the sensors. Our models exhibit consistently a reduction of the error rate and an increase of robustness against sensor failures. Our models also outperform other classifiers combination models that do not consider soft outputs and an Markovian structure of the human activities.

  15. Manipulating the electron distribution through a combination of electron injection and MacKenzie’s Maxwell Demon

    International Nuclear Information System (INIS)

    Yip, Chi-Shung; Hershkowitz, Noah

    2015-01-01

    Experiments on electron heating are performed in a biased hot filament-produced argon plasma. Electrons are confined by multi-dipole magnetic fields on the radial wall of the cylindrical chamber but not the planar end walls. Electron heating is provided by a combination of cold electron injection (Hershowitz N and Leung K N 1975 Appl. Phys. Lett. 26 607) and a MacKenzie Maxwell Demon (Mackenzie K R et al 1971 Appl. Phys. Lett. 18 529). This approach allows the manipulation of the electrons by introducing a depleted tail into the electron energy distribution function or by removing a depleted tail. It is found that the injected electrons mimic and thermalize with the electron species with the closest average energy or temperature. The effect of the injected electrons is optimal when they mimic the secondary electrons emitted from the wall instead of the degraded primary electrons. Both approaches combine to achieve increases in electron temperature T e from 0.67 to 2.8 eV, which was not significantly higher than using each approach alone. (paper)

  16. Automatic denoising of functional MRI data: combining independent component analysis and hierarchical fusion of classifiers.

    Science.gov (United States)

    Salimi-Khorshidi, Gholamreza; Douaud, Gwenaëlle; Beckmann, Christian F; Glasser, Matthew F; Griffanti, Ludovica; Smith, Stephen M

    2014-04-15

    Many sources of fluctuation contribute to the fMRI signal, and this makes identifying the effects that are truly related to the underlying neuronal activity difficult. Independent component analysis (ICA) - one of the most widely used techniques for the exploratory analysis of fMRI data - has shown to be a powerful technique in identifying various sources of neuronally-related and artefactual fluctuation in fMRI data (both with the application of external stimuli and with the subject "at rest"). ICA decomposes fMRI data into patterns of activity (a set of spatial maps and their corresponding time series) that are statistically independent and add linearly to explain voxel-wise time series. Given the set of ICA components, if the components representing "signal" (brain activity) can be distinguished form the "noise" components (effects of motion, non-neuronal physiology, scanner artefacts and other nuisance sources), the latter can then be removed from the data, providing an effective cleanup of structured noise. Manual classification of components is labour intensive and requires expertise; hence, a fully automatic noise detection algorithm that can reliably detect various types of noise sources (in both task and resting fMRI) is desirable. In this paper, we introduce FIX ("FMRIB's ICA-based X-noiseifier"), which provides an automatic solution for denoising fMRI data via accurate classification of ICA components. For each ICA component FIX generates a large number of distinct spatial and temporal features, each describing a different aspect of the data (e.g., what proportion of temporal fluctuations are at high frequencies). The set of features is then fed into a multi-level classifier (built around several different classifiers). Once trained through the hand-classification of a sufficient number of training datasets, the classifier can then automatically classify new datasets. The noise components can then be subtracted from (or regressed out of) the original

  17. Laser removal of water repellent treatments on limestone

    Energy Technology Data Exchange (ETDEWEB)

    Gomez-Heras, Miguel; Alvarez de Buergo, Monica; Rebollar, Esther; Oujja, Mohamed; Castillejo, Marta; Fort, Rafael

    2003-12-15

    Protective and water repellent treatments are applied on stone materials used on buildings or sculptures of artistic value to reduce water intrusion without limiting the natural permeability to water vapour of the material. The effect of the wavelength associated with the laser removal of two water repellent treatments applied on limestone, Paraloid B-72, a copolymer of methyl acrylate and ethyl methacrylate, and Tegosivin HL-100, a modified polysiloxane resin, was investigated by using the four harmonics of a Q-switched Nd:YAG laser (1064, 532, 355 and 266 nm). The modifications induced on the surface of limestone samples by laser irradiation were studied using colorimetry, roughness measurements and scanning electron microscopy (SEM). The removal of the treatments was found to be dependent on the laser irradiation conditions and on the characteristics of the coatings. The fundamental laser radiation was effective in removing both treatments, but thermal alteration processes were induced on the constituent calcite crystals. The best results were obtained by irradiation in the near UV at 355 nm.

  18. Classifying objects in LWIR imagery via CNNs

    Science.gov (United States)

    Rodger, Iain; Connor, Barry; Robertson, Neil M.

    2016-10-01

    The aim of the presented work is to demonstrate enhanced target recognition and improved false alarm rates for a mid to long range detection system, utilising a Long Wave Infrared (LWIR) sensor. By exploiting high quality thermal image data and recent techniques in machine learning, the system can provide automatic target recognition capabilities. A Convolutional Neural Network (CNN) is trained and the classifier achieves an overall accuracy of > 95% for 6 object classes related to land defence. While the highly accurate CNN struggles to recognise long range target classes, due to low signal quality, robust target discrimination is achieved for challenging candidates. The overall performance of the methodology presented is assessed using human ground truth information, generating classifier evaluation metrics for thermal image sequences.

  19. Organic micro-pollutants’ removal via anaerobic membrane bioreactor with ultrafiltration and nanofiltration

    KAUST Repository

    Wei, Chunhai; Hoppe-Jones, Christiane; Amy, Gary L.; Leiknes, TorOve

    2015-01-01

    and caffeine showed a prolonged adaption time of around 45 d, with initial biological removal below 40% and up to 50-80% after this period. Most readily biodegradable OMPs contained a strong electron donating group. Most refractory OMPs contained a strong

  20. Preparation of Polyaniline/Filter-paper Composite for Removal of Coomassie Brilliant Blue

    DEFF Research Database (Denmark)

    Liu, Wanwan; Li, Xiaoqiang; Li, Mengjuan

    2015-01-01

    Polyaniline/filter-paper (PANI/FP) composite was prepared by in-situ polymerization of polyaniline onto filter-paper and subsequently evaluated for the removal of Coomassie brilliant blue (CBB) from aqueous solution. Scanning electron microscopy (SEM), thermogravimetric analysis (TGA) and Fourier...

  1. ARSENIC REMOVAL BY IRON REMOVAL PROCESSES

    Science.gov (United States)

    Presentation will discuss the removal of arsenic from drinking water using iron removal processes that include oxidation/filtration and the manganese greensand processes. Presentation includes results of U.S. EPA field studies conducted in Michigan and Ohio on existing iron remo...

  2. Classifying web pages with visual features

    NARCIS (Netherlands)

    de Boer, V.; van Someren, M.; Lupascu, T.; Filipe, J.; Cordeiro, J.

    2010-01-01

    To automatically classify and process web pages, current systems use the textual content of those pages, including both the displayed content and the underlying (HTML) code. However, a very important feature of a web page is its visual appearance. In this paper, we show that using generic visual

  3. Dynamic integration of classifiers in the space of principal components

    NARCIS (Netherlands)

    Tsymbal, A.; Pechenizkiy, M.; Puuronen, S.; Patterson, D.W.; Kalinichenko, L.A.; Manthey, R.; Thalheim, B.; Wloka, U.

    2003-01-01

    Recent research has shown the integration of multiple classifiers to be one of the most important directions in machine learning and data mining. It was shown that, for an ensemble to be successful, it should consist of accurate and diverse base classifiers. However, it is also important that the

  4. Bias and Stability of Single Variable Classifiers for Feature Ranking and Selection.

    Science.gov (United States)

    Fakhraei, Shobeir; Soltanian-Zadeh, Hamid; Fotouhi, Farshad

    2014-11-01

    Feature rankings are often used for supervised dimension reduction especially when discriminating power of each feature is of interest, dimensionality of dataset is extremely high, or computational power is limited to perform more complicated methods. In practice, it is recommended to start dimension reduction via simple methods such as feature rankings before applying more complex approaches. Single Variable Classifier (SVC) ranking is a feature ranking based on the predictive performance of a classifier built using only a single feature. While benefiting from capabilities of classifiers, this ranking method is not as computationally intensive as wrappers. In this paper, we report the results of an extensive study on the bias and stability of such feature ranking method. We study whether the classifiers influence the SVC rankings or the discriminative power of features themselves has a dominant impact on the final rankings. We show the common intuition of using the same classifier for feature ranking and final classification does not always result in the best prediction performance. We then study if heterogeneous classifiers ensemble approaches provide more unbiased rankings and if they improve final classification performance. Furthermore, we calculate an empirical prediction performance loss for using the same classifier in SVC feature ranking and final classification from the optimal choices.

  5. Digital circuit for the introduction and later removal of dither from an analog signal

    Science.gov (United States)

    Borgen, Gary S.

    1994-05-01

    An electronics circuit is presented for accurately digitizing an analog audio or like data signal into a digital equivalent signal by introducing dither into the analog signal and then subsequently removing the dither from the digitized signal prior to its conversion to an analog signal which is a substantial replica of the incoming analog audio or like data signal. The electronics circuit of the present invention is characterized by a first pseudo-random number generator which generates digital random noise signals or dither for addition to the digital equivalent signal and a second pseudo-random number generator which generates subtractive digital random noise signals for the subsequent removal of dither from the digital equivalent signal prior its conversion to the analog replica signal.

  6. Highly efficient removal of arsenic metal ions with high superficial area hollow magnetite nanoparticles synthetized by AACVD method

    Energy Technology Data Exchange (ETDEWEB)

    Monárrez-Cordero, B.; Amézaga-Madrid, P.; Antúnez-Flores, W.; Leyva-Porras, C.; Pizá-Ruiz, P. [Centro de Investigación en Materiales Avanzados S.C., and Laboratorio Nacional de Nanotecnología, Miguel de Cervantes 120, Chihuahua, Chih. C.P. 31109 (Mexico); Miki-Yoshida, M., E-mail: mario.miki@cimav.edu.mx [Centro de Investigación en Materiales Avanzados S.C., and Laboratorio Nacional de Nanotecnología, Miguel de Cervantes 120, Chihuahua, Chih. C.P. 31109 (Mexico)

    2014-02-15

    Highlights: ► Fast and high arsenic removal efficiency, almost 100% in one minute. ► Successful synthesis of high purity magnetite hollow nanoparticles is reported. ► They were synthesized by one step aerosol assisted CVD technique. ► Detailed microstructural characterization by electron microscopy was performed. -- Abstract: New nanotechnology alternatives and methodologies have been developed in order to overcome the limitations of conventional techniques for metal ions removal from water. Currently, the removal of heavy metals requires multiple steps which include the separation and post-treatment of the generated sludge. Usually, this sludge is composed of dangerous environmental pollutants mixed with the material used for removing the metal ion. Thus, the removal of these metals becomes a challenging task. Herein we report the synthesis of magnetite nanoparticles with high specific area by the aerosol assisted chemical vapour deposition method. Deposition temperature were fixed at 450 °C and a mixture of Ar–air were used as a carrier gas, a flow of 1.0 and 0.015 L min{sup −1} were used for Ar and air, respectively. The precursor solution was a dilution of Fe (II) chloride in methanol, with different concentration 0.01, 0.05 and 0.1 mol dm{sup −3}. The crystalline structure of the nanoparticles was characterized by grazing incidence X-ray diffraction. Morphology and microstructure were analyzed by field emission scanning electron microscopy, scanning probe microscopy and transmission electron microscopy. Magnetic properties were evaluated with a vibrating sample magnetometer and specific area was measured by the Brunauer–Emmett–Teller method. To determine the removal efficiency of arsenic ion from water, several tests were carried out at six exposition times 1, 3, 5, 10, 20 and 30 min. Results showed high removal efficiency, more than 99%, in less than 1 min.

  7. Electronic structure and correlated wave functions of a few electron quantum dots

    Energy Technology Data Exchange (ETDEWEB)

    Sako, Tokuei [Laboratory of Physics, College of Science and Technology, Nihon University, 7-24-1 Narashinodai, Funabashi, Chiba 274-8501 (Japan); Ishida, Hiroshi [College of Humanities and Sciences, Nihon University, Tokyo 156-8550 (Japan); Fujikawa, Kazuo [Institute of Quantum Science, College of Science and Technology, Nihon University, Chiyoda-ku, Tokyo 101-8308 (Japan)

    2015-01-22

    The energy spectra and wave functions of a few electrons confined by a quasi-one-dimensional harmonic and anharmonic potentials have been studied by using a full configuration interaction method employing a Cartesian anisotropic Gaussian basis set. The energy spectra are classified into three regimes of the strength of confinement, namely, large, medium and small. The polyad quantum number defined by a total number of nodes in the wave functions is shown to be a key ingredient to interpret the energy spectra for the whole range of the confinement strength. The nodal pattern of the wave functions exhibits normal modes for the harmonic confining potential, indicating collective motions of electrons. These normal modes are shown to undergo a transition to local modes for an anharmonic potential with large anharmonicity.

  8. Classifying Radio Galaxies with the Convolutional Neural Network

    Energy Technology Data Exchange (ETDEWEB)

    Aniyan, A. K.; Thorat, K. [Department of Physics and Electronics, Rhodes University, Grahamstown (South Africa)

    2017-06-01

    We present the application of a deep machine learning technique to classify radio images of extended sources on a morphological basis using convolutional neural networks (CNN). In this study, we have taken the case of the Fanaroff–Riley (FR) class of radio galaxies as well as radio galaxies with bent-tailed morphology. We have used archival data from the Very Large Array (VLA)—Faint Images of the Radio Sky at Twenty Centimeters survey and existing visually classified samples available in the literature to train a neural network for morphological classification of these categories of radio sources. Our training sample size for each of these categories is ∼200 sources, which has been augmented by rotated versions of the same. Our study shows that CNNs can classify images of the FRI and FRII and bent-tailed radio galaxies with high accuracy (maximum precision at 95%) using well-defined samples and a “fusion classifier,” which combines the results of binary classifications, while allowing for a mechanism to find sources with unusual morphologies. The individual precision is highest for bent-tailed radio galaxies at 95% and is 91% and 75% for the FRI and FRII classes, respectively, whereas the recall is highest for FRI and FRIIs at 91% each, while the bent-tailed class has a recall of 79%. These results show that our results are comparable to that of manual classification, while being much faster. Finally, we discuss the computational and data-related challenges associated with the morphological classification of radio galaxies with CNNs.

  9. Classifying Radio Galaxies with the Convolutional Neural Network

    Science.gov (United States)

    Aniyan, A. K.; Thorat, K.

    2017-06-01

    We present the application of a deep machine learning technique to classify radio images of extended sources on a morphological basis using convolutional neural networks (CNN). In this study, we have taken the case of the Fanaroff-Riley (FR) class of radio galaxies as well as radio galaxies with bent-tailed morphology. We have used archival data from the Very Large Array (VLA)—Faint Images of the Radio Sky at Twenty Centimeters survey and existing visually classified samples available in the literature to train a neural network for morphological classification of these categories of radio sources. Our training sample size for each of these categories is ˜200 sources, which has been augmented by rotated versions of the same. Our study shows that CNNs can classify images of the FRI and FRII and bent-tailed radio galaxies with high accuracy (maximum precision at 95%) using well-defined samples and a “fusion classifier,” which combines the results of binary classifications, while allowing for a mechanism to find sources with unusual morphologies. The individual precision is highest for bent-tailed radio galaxies at 95% and is 91% and 75% for the FRI and FRII classes, respectively, whereas the recall is highest for FRI and FRIIs at 91% each, while the bent-tailed class has a recall of 79%. These results show that our results are comparable to that of manual classification, while being much faster. Finally, we discuss the computational and data-related challenges associated with the morphological classification of radio galaxies with CNNs.

  10. Classifying Radio Galaxies with the Convolutional Neural Network

    International Nuclear Information System (INIS)

    Aniyan, A. K.; Thorat, K.

    2017-01-01

    We present the application of a deep machine learning technique to classify radio images of extended sources on a morphological basis using convolutional neural networks (CNN). In this study, we have taken the case of the Fanaroff–Riley (FR) class of radio galaxies as well as radio galaxies with bent-tailed morphology. We have used archival data from the Very Large Array (VLA)—Faint Images of the Radio Sky at Twenty Centimeters survey and existing visually classified samples available in the literature to train a neural network for morphological classification of these categories of radio sources. Our training sample size for each of these categories is ∼200 sources, which has been augmented by rotated versions of the same. Our study shows that CNNs can classify images of the FRI and FRII and bent-tailed radio galaxies with high accuracy (maximum precision at 95%) using well-defined samples and a “fusion classifier,” which combines the results of binary classifications, while allowing for a mechanism to find sources with unusual morphologies. The individual precision is highest for bent-tailed radio galaxies at 95% and is 91% and 75% for the FRI and FRII classes, respectively, whereas the recall is highest for FRI and FRIIs at 91% each, while the bent-tailed class has a recall of 79%. These results show that our results are comparable to that of manual classification, while being much faster. Finally, we discuss the computational and data-related challenges associated with the morphological classification of radio galaxies with CNNs.

  11. An expert computer program for classifying stars on the MK spectral classification system

    International Nuclear Information System (INIS)

    Gray, R. O.; Corbally, C. J.

    2014-01-01

    This paper describes an expert computer program (MKCLASS) designed to classify stellar spectra on the MK Spectral Classification system in a way similar to humans—by direct comparison with the MK classification standards. Like an expert human classifier, the program first comes up with a rough spectral type, and then refines that spectral type by direct comparison with MK standards drawn from a standards library. A number of spectral peculiarities, including barium stars, Ap and Am stars, λ Bootis stars, carbon-rich giants, etc., can be detected and classified by the program. The program also evaluates the quality of the delivered spectral type. The program currently is capable of classifying spectra in the violet-green region in either the rectified or flux-calibrated format, although the accuracy of the flux calibration is not important. We report on tests of MKCLASS on spectra classified by human classifiers; those tests suggest that over the entire HR diagram, MKCLASS will classify in the temperature dimension with a precision of 0.6 spectral subclass, and in the luminosity dimension with a precision of about one half of a luminosity class. These results compare well with human classifiers.

  12. An expert computer program for classifying stars on the MK spectral classification system

    Energy Technology Data Exchange (ETDEWEB)

    Gray, R. O. [Department of Physics and Astronomy, Appalachian State University, Boone, NC 26808 (United States); Corbally, C. J. [Vatican Observatory Research Group, Tucson, AZ 85721-0065 (United States)

    2014-04-01

    This paper describes an expert computer program (MKCLASS) designed to classify stellar spectra on the MK Spectral Classification system in a way similar to humans—by direct comparison with the MK classification standards. Like an expert human classifier, the program first comes up with a rough spectral type, and then refines that spectral type by direct comparison with MK standards drawn from a standards library. A number of spectral peculiarities, including barium stars, Ap and Am stars, λ Bootis stars, carbon-rich giants, etc., can be detected and classified by the program. The program also evaluates the quality of the delivered spectral type. The program currently is capable of classifying spectra in the violet-green region in either the rectified or flux-calibrated format, although the accuracy of the flux calibration is not important. We report on tests of MKCLASS on spectra classified by human classifiers; those tests suggest that over the entire HR diagram, MKCLASS will classify in the temperature dimension with a precision of 0.6 spectral subclass, and in the luminosity dimension with a precision of about one half of a luminosity class. These results compare well with human classifiers.

  13. Carrier removal and defect behavior in p-type InP

    Science.gov (United States)

    Weinberg, I.; Swartz, C. K.; Drevinsky, P. J.

    1992-01-01

    A simple expression, obtained from the rate equation for defect production, was used to relate carrier removal to defect production and hole trapping rates in p-type InP after irradiation by 1-MeV electrons. Specific contributions to carrier removal from defect levels H3, H4, and H5 were determined from combined deep-level transient spectroscopy (DLTS) and measured carrier concentrations. An additional contribution was attributed to one or more defects not observed by the present DLTS measurements. The high trapping rate observed for H5 suggests that this defect, if present in relatively high concentration, could be dominant in p-type InP.

  14. Ship localization in Santa Barbara Channel using machine learning classifiers.

    Science.gov (United States)

    Niu, Haiqiang; Ozanich, Emma; Gerstoft, Peter

    2017-11-01

    Machine learning classifiers are shown to outperform conventional matched field processing for a deep water (600 m depth) ocean acoustic-based ship range estimation problem in the Santa Barbara Channel Experiment when limited environmental information is known. Recordings of three different ships of opportunity on a vertical array were used as training and test data for the feed-forward neural network and support vector machine classifiers, demonstrating the feasibility of machine learning methods to locate unseen sources. The classifiers perform well up to 10 km range whereas the conventional matched field processing fails at about 4 km range without accurate environmental information.

  15. Analytical electron microscopy characterization of Fernald soils. Annual report, October 1993--September 1994

    International Nuclear Information System (INIS)

    Buck, E.C.; Brown, N.R.; Dietz, N.L.

    1995-03-01

    A combination of backscattered electron imaging and analytical electron microscopy (AEM) with electron diffraction have been used to determine the physical and chemical properties of uranium contamination in soils from the Fernald Environmental Management Project in Ohio. The information gained from these studies has been used in the development and testing of remediation technologies. Most chemical washing techniques have been reasonably effective with uranyl [U(VI)] phases, but U(IV) phases have proven difficult to remove from the soils. Carbonate leaching in an oxygen environment (heap leaching) has removed some of the U(IV) phases, and it appears to be the most effective technique developed in the program. The uranium metaphosphate, which was found exclusively at an incinerator site, has not been removed by any of the chemical methods. We suggest that a physical extraction procedure (either a magnetic separation or aqueous biphasic process) be used to remove this phase. Analytical electron microscopy has also been used to determine the effect of the chemical agents on the uranium phases. It has also been used to examine soils from the Portsmouth site in Ohio. The contamination there took the form of uranium oxide and uranium calcium oxide phases. Technology transfer efforts over FY 1994 have led to industry-sponsored projects involving soil characterization

  16. Novel chitosan/PVA/zerovalent iron biopolymeric nanofibers with enhanced arsenic removal applications.

    Science.gov (United States)

    Chauhan, Divya; Dwivedi, Jaya; Sankararamakrishnan, Nalini

    2014-01-01

    Enhanced removal application of both forms of inorganic arsenic from arsenic-contaminated aquifers at near-neutral pH was studied using a novel electrospun chitosan/PVA/zerovalent iron (CPZ) nanofibrous mat. CPZ was carefully examined using scanning electron microscopy (SEM) equipped with energy-dispersive X-ray analysis (EDX), transmission electron microscopy (TEM), atomic fluorescence spectroscopy (AFM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), and thermal gravimetric analysis (TGA). Application of the adsorbent towards the removal of total inorganic arsenic in batch mode has also been studied. A suitable mechanism for the adsorption has also been discussed. CPZ nanofibers mat was found capable to remove 200.0±10.0 mg g(-1) of As(V) and 142.9±7.2 mg g(-1) of As(III) from aqueous solution of pH 7.0 at ambient condition. Addition of ethylenediaminetetraacetic acid (EDTA) enabled the stability of iron in zerovalent state (ZVI). Enhanced capacity of the fibrous mat could be attributed to the high surface area of the fibers, presence of ZVI, and presence of functional groups such as amino, carboxyl, and hydroxyl groups of the chitosan and EDTA. Both Langmuir and Freundlich adsorption isotherms were applicable to describe the removal process. The possible mechanism of adsorption has been explained in terms of electrostatic attraction between the protonated amino groups of chitosan/arsenate ions and oxidation of arsenite to arsenate by Fentons generated from ZVI and subsequent complexation of the arsenate with the oxidized iron. These CPZ nanofibrous mats has been prepared with environmentally benign naturally occurring biodegradable biopolymer chitosan, which offers unique advantage in the removal of arsenic from contaminated groundwater.

  17. Deconstructing Cross-Entropy for Probabilistic Binary Classifiers

    Directory of Open Access Journals (Sweden)

    Daniel Ramos

    2018-03-01

    Full Text Available In this work, we analyze the cross-entropy function, widely used in classifiers both as a performance measure and as an optimization objective. We contextualize cross-entropy in the light of Bayesian decision theory, the formal probabilistic framework for making decisions, and we thoroughly analyze its motivation, meaning and interpretation from an information-theoretical point of view. In this sense, this article presents several contributions: First, we explicitly analyze the contribution to cross-entropy of (i prior knowledge; and (ii the value of the features in the form of a likelihood ratio. Second, we introduce a decomposition of cross-entropy into two components: discrimination and calibration. This decomposition enables the measurement of different performance aspects of a classifier in a more precise way; and justifies previously reported strategies to obtain reliable probabilities by means of the calibration of the output of a discriminating classifier. Third, we give different information-theoretical interpretations of cross-entropy, which can be useful in different application scenarios, and which are related to the concept of reference probabilities. Fourth, we present an analysis tool, the Empirical Cross-Entropy (ECE plot, a compact representation of cross-entropy and its aforementioned decomposition. We show the power of ECE plots, as compared to other classical performance representations, in two diverse experimental examples: a speaker verification system, and a forensic case where some glass findings are present.

  18. High Efficient Nanocomposite for Removal of Heavy Metals (Hg2+ and Pb2+ from Aqueous Solution

    Directory of Open Access Journals (Sweden)

    M. Ebadi

    2016-01-01

    Full Text Available In current work, CdS/black carbon nanocomposites were successfully synthesized with the aid of chestnut and cadmium nitrate as the starting reagents. Besides, the effects of preparation parameters such as reaction time, and precursor concentration on the morphology of products and removal of heavy metals (Hg+2, Pb+2 were studied by scanning electron microscopy images and batch adsorption mode. CdS/black carbon nanocomposite introduced as new and high efficient system for removal of heavy metal ions. The as-synthesized products were characterized by powder X-ray diffraction, scanning electron microscopy, and spectra energy dispersive analysis of X-ray.

  19. Improved multi-stage neonatal seizure detection using a heuristic classifier and a data-driven post-processor.

    Science.gov (United States)

    Ansari, A H; Cherian, P J; Dereymaeker, A; Matic, V; Jansen, K; De Wispelaere, L; Dielman, C; Vervisch, J; Swarte, R M; Govaert, P; Naulaers, G; De Vos, M; Van Huffel, S

    2016-09-01

    After identifying the most seizure-relevant characteristics by a previously developed heuristic classifier, a data-driven post-processor using a novel set of features is applied to improve the performance. The main characteristics of the outputs of the heuristic algorithm are extracted by five sets of features including synchronization, evolution, retention, segment, and signal features. Then, a support vector machine and a decision making layer remove the falsely detected segments. Four datasets including 71 neonates (1023h, 3493 seizures) recorded in two different university hospitals, are used to train and test the algorithm without removing the dubious seizures. The heuristic method resulted in a false alarm rate of 3.81 per hour and good detection rate of 88% on the entire test databases. The post-processor, effectively reduces the false alarm rate by 34% while the good detection rate decreases by 2%. This post-processing technique improves the performance of the heuristic algorithm. The structure of this post-processor is generic, improves our understanding of the core visually determined EEG features of neonatal seizures and is applicable for other neonatal seizure detectors. The post-processor significantly decreases the false alarm rate at the expense of a small reduction of the good detection rate. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  20. Electron beam induced conductivity in 'PET' and 'FEP'

    International Nuclear Information System (INIS)

    Walzade, S.J.; Jog, J.P.; Dake, S.B.; Bhoraskar, S.V.

    1983-01-01

    Electron Beam Induced Conductivity (EBIC), classified into EBIC (bulk) and EBIC (surface) have been measured in PET and FEP respectively. The peculiar oscillatory nature of the induced gain versus beam energy variations is explained in terms of the spatial distributions of the trapping centres near the surface of the polymers. (author)

  1. Loess clay based copolymer for removing Pb(II) ions

    International Nuclear Information System (INIS)

    He, Yu-Feng; Zhang, Ling; Wang, Rong-Min; Li, Hui-Ru; Wang, Yan

    2012-01-01

    Highlights: ► The loess clay based copolymer was prepared using functional monomers. ► Characterization of the polymer adsorbent and the raw material were carried out. ► The adsorption behavior of the complex for Pb(II) ions was evaluated. ► The removal rate of Pb(II) got to 99% and the adsorption capacity got to 356.9 mg/g. - Abstract: Functional monomers, such as acrylic acid and 2-hydroxyethyl methacrylate were supported into loess clay in situ polymerization, which afforded loess clay based copolymer (LC/PAAHM), a new kind of polymer adsorbent for removing Pb(II) ions from aqueous solution. Characterization of the polymer adsorbent was carried out by different sophisticated methods, such as Fourier transformation infrared spectrometry (FTIR), scanning electron microscopy (SEM), X-ray diffractometry (XRD), thermogravimetric analysis (TGA), and Zetasizer. Batch experiments were carried out to evaluate the factors affecting the removal efficiency, in which the pH, the adsorbent dosage, temperature and initial Pb(II) concentration all found in positive relevance to the increase of Pb(II) removal efficiency. The removal rate of Pb(II) got to 99% at room temperature and the adsorption capacity got to 356.9 mg/g. The pseudo-first-order and pseudo-second-order kinetic models were applied to test the experimental data, and Langmuir and Freundlich models have been applied to study the adsorption equilibrium, respectively.

  2. The development of a risk score for unplanned removal of peripherally inserted central catheter in newborns

    Directory of Open Access Journals (Sweden)

    Priscila Costa

    2015-06-01

    Full Text Available OBJECTIVE: to develop a risk score for unplanned removal of peripherally inserted central catheter in newborns.METHOD: prospective cohort study conducted in a neonatal intensive care unit with newborn babies who underwent 524 catheter insertions. The clinical characteristics of the newborn, catheter insertion and intravenous therapy were tested as risk factors for the unplanned removal of catheters using bivariate analysis. The risk score was developed using logistic regression. Accuracy was internally validated based on the area under the Receiver Operating Characteristic curve.RESULTS: the risk score was made up of the following risk factors: transient metabolic disorders; previous insertion of catheter; use of a polyurethane double-lumen catheter; infusion of multiple intravenous solutions through a single-lumen catheter; and tip in a noncentral position. Newborns were classified into three categories of risk of unplanned removal: low (0 to 3 points, moderate (4 to 8 points, and high (≥ 9 points. Accuracy was 0.76.CONCLUSION: the adoption of evidence-based preventative strategies based on the classification and risk factors faced by the newborn is recommended to minimize the occurrence of unplanned removals.

  3. Effect of halide impregnation on elemental mercury removal of activated carbons

    Energy Technology Data Exchange (ETDEWEB)

    Yim, Yoon Ji; Park, Soo Jin [Dept. of Chemistry, Inha University, Incheon (Korea, Republic of)

    2017-02-15

    Activated carbons (ACs) were impregnated with potassium halides (KX) to enhance the removal efficiency of elemental mercury (Hg{sup 0}). In this work, the impregnation effect of potassium bromide (KBr) and potassium iodine (KI) were investigated. The surface properties of KX-ACs were determined by scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). The pore structures and total pore volumes of the KX-ACs were analyzed using the N{sub 2} /77 K adsorption isotherms. The Hg{sup 0} removal efficiency of KBr-ACs and KI-ACs was studied under simulated flue gas conditions. The effects of KI and KBr loading, adsorption temperature, and flue gas components on Hg{sup 0} removal efficiency were also investigated. The results showed that the Hg{sup 0} removal efficiency of the ACs was significantly enhanced by KI or KBr impregnation, and KI-ACs showed higher Hg{sup 0} removal efficiency than KBr-ACs under the same conditions. An increase in KI or KBr loading and higher adsorption temperatures improved the Hg{sup 0} removal efficiency, indicating that chemisorption occurred due to the reaction between X− and Hg{sup 0}. The lower extent of Hg{sup 0} removal exhibited by the KBr-ACs than by the KI-ACs was due to the difficulty of Br{sub 2} formation on the surfaces.

  4. Dry cleaning of fluorocarbon residues by low-power electron cyclotron resonance hydrogen plasma

    CERN Document Server

    Lim, S H; Yuh, H K; Yoon Eui Joon; Lee, S I

    1988-01-01

    A low-power ( 50 W) electron cyclotron resonance hydrogen plasma cleaning process was demonstrated for the removal of fluorocarbon residue layers formed by reactive ion etching of silicon dioxide. The absence of residue layers was confirmed by in-situ reflection high energy electron diffraction and cross-sectional high resolution transmission electron microscopy. The ECR hydrogen plasma cleaning was applied to contact cleaning of a contact string structure, resulting in comparable contact resistance arising during by a conventional contact cleaning procedure. Ion-assisted chemical reaction involving reactive atomic hydrogen species generated in the plasma is attributed for the removal of fluorocarbon residue layers.

  5. Evaluation of Classifier Performance for Multiclass Phenotype Discrimination in Untargeted Metabolomics.

    Science.gov (United States)

    Trainor, Patrick J; DeFilippis, Andrew P; Rai, Shesh N

    2017-06-21

    Statistical classification is a critical component of utilizing metabolomics data for examining the molecular determinants of phenotypes. Despite this, a comprehensive and rigorous evaluation of the accuracy of classification techniques for phenotype discrimination given metabolomics data has not been conducted. We conducted such an evaluation using both simulated and real metabolomics datasets, comparing Partial Least Squares-Discriminant Analysis (PLS-DA), Sparse PLS-DA, Random Forests, Support Vector Machines (SVM), Artificial Neural Network, k -Nearest Neighbors ( k -NN), and Naïve Bayes classification techniques for discrimination. We evaluated the techniques on simulated data generated to mimic global untargeted metabolomics data by incorporating realistic block-wise correlation and partial correlation structures for mimicking the correlations and metabolite clustering generated by biological processes. Over the simulation studies, covariance structures, means, and effect sizes were stochastically varied to provide consistent estimates of classifier performance over a wide range of possible scenarios. The effects of the presence of non-normal error distributions, the introduction of biological and technical outliers, unbalanced phenotype allocation, missing values due to abundances below a limit of detection, and the effect of prior-significance filtering (dimension reduction) were evaluated via simulation. In each simulation, classifier parameters, such as the number of hidden nodes in a Neural Network, were optimized by cross-validation to minimize the probability of detecting spurious results due to poorly tuned classifiers. Classifier performance was then evaluated using real metabolomics datasets of varying sample medium, sample size, and experimental design. We report that in the most realistic simulation studies that incorporated non-normal error distributions, unbalanced phenotype allocation, outliers, missing values, and dimension reduction

  6. Hair Removal

    Science.gov (United States)

    ... Staying Safe Videos for Educators Search English Español Hair Removal KidsHealth / For Teens / Hair Removal What's in ... you need any of them? Different Types of Hair Before removing hair, it helps to know about ...

  7. Anaerobic ammonia removal in presence of organic matter: A novel route

    International Nuclear Information System (INIS)

    Sabumon, P.C.

    2007-01-01

    This study describes the feasibility of anaerobic ammonia removal process in presence of organic matter. Different sources of biomass collected from diverse eco-systems containing ammonia and organic matter (OM) were screened for potential anaerobic ammonia removal. Sequential batch studies confirmed the possibility of anaerobic ammonia removal in presence of OM, but ammonia was oxidized anoxically to nitrate (at oxidation reduction potential; ORP -248 ± 25 mV) by an unknown mechanism unlike in the reported anammox process. The oxygen required for oxidation of ammonia might have been generated through catalase enzymatic activity of facultative anaerobes in mixed culture. The oxygen generation possibility by catalase enzyme route was demonstrated. Among the inorganic electron acceptors (NO 2 - , NO 3 - and SO 4 2- ) studied, NO 2 - was found to be most effective in total nitrogen removal. Denitrification by the developed culture was much effective and faster compared to ammonia oxidation. The results of this study show that anaerobic ammonia removal is feasible in presence of OM. The novel nitrogen removal route is hypothesized as enzymatic anoxic oxidation of NH 4 + to NO 3 - , followed by denitrification via autotrophic and/or heterotrophic routes. The results of batch study were confirmed in continuous reactor operation

  8. LOCALIZATION AND RECOGNITION OF DYNAMIC HAND GESTURES BASED ON HIERARCHY OF MANIFOLD CLASSIFIERS

    OpenAIRE

    M. Favorskaya; A. Nosov; A. Popov

    2015-01-01

    Generally, the dynamic hand gestures are captured in continuous video sequences, and a gesture recognition system ought to extract the robust features automatically. This task involves the highly challenging spatio-temporal variations of dynamic hand gestures. The proposed method is based on two-level manifold classifiers including the trajectory classifiers in any time instants and the posture classifiers of sub-gestures in selected time instants. The trajectory classifiers contain skin dete...

  9. The Classification of Types of Business-to-Business Electronic Commerce: A Framework Construction

    Directory of Open Access Journals (Sweden)

    Jong-min Choe

    2017-01-01

    Full Text Available Based on the degree of information sharing between buyers and suppliers as well as the level of supplier power, we suggested a framework that can be useful for classifying types of business to business (B2B electronic commerce (EC in the manufacturing firms. According to this framework, four kinds of B2B EC were theoretically proposed, classified, and empirically confirmed. These four are: an electronic marketplace, electronic procurement, electronic partnerships, and electronic distribution. Many prior studies have investigated and proposed some kinds of B2B EC. However, these studies focused mostly on one or two types of B2B EC, and did not develop or suggest a framework for the classification of forms of B2B EC. The framework constructed in this research can be utilized variously. Specifically, when a firm wants to initiate B2B EC with its suppliers, this framework can help a firm to decide and select an appropriate kind of B2B EC. This framework can also be applied to evaluate whether the proper form of B2B EC has been adopted or not.

  10. Supervised retinal vessel segmentation from color fundus images based on matched filtering and AdaBoost classifier.

    Directory of Open Access Journals (Sweden)

    Nogol Memari

    Full Text Available The structure and appearance of the blood vessel network in retinal fundus images is an essential part of diagnosing various problems associated with the eyes, such as diabetes and hypertension. In this paper, an automatic retinal vessel segmentation method utilizing matched filter techniques coupled with an AdaBoost classifier is proposed. The fundus image is enhanced using morphological operations, the contrast is increased using contrast limited adaptive histogram equalization (CLAHE method and the inhomogeneity is corrected using Retinex approach. Then, the blood vessels are enhanced using a combination of B-COSFIRE and Frangi matched filters. From this preprocessed image, different statistical features are computed on a pixel-wise basis and used in an AdaBoost classifier to extract the blood vessel network inside the image. Finally, the segmented images are postprocessed to remove the misclassified pixels and regions. The proposed method was validated using publicly accessible Digital Retinal Images for Vessel Extraction (DRIVE, Structured Analysis of the Retina (STARE and Child Heart and Health Study in England (CHASE_DB1 datasets commonly used for determining the accuracy of retinal vessel segmentation methods. The accuracy of the proposed segmentation method was comparable to other state of the art methods while being very close to the manual segmentation provided by the second human observer with an average accuracy of 0.972, 0.951 and 0.948 in DRIVE, STARE and CHASE_DB1 datasets, respectively.

  11. A Multi-Functional Power Electronic Converter in Distributed Generation Power Systems

    DEFF Research Database (Denmark)

    Chen, Zhe; Blaabjerg, Frede; Pedersen, John Kim

    2005-01-01

    of the converter interfacing a wind power generation unit is also given. The power electronic interface performs the optimal operation in the wind turbine system to extract the maximum wind power, while it also plays a key role in a hybrid compensation system that consists of the active power electronic converter......This paper presents a power electronic converter which is used as an interface for a distributed generation unit/energy storage device, and also functioned as an active power compensator in a hybrid compensation system. The operation and control of the converter have been described. An example...... and passive filters connected to each distorting load or distributed generation (DG) unit. The passive filters are distributely located to remove major harmonics and provide reactive power compensation. The active power electronic filter corrects the system unbalance, removes the remaining harmonic components...

  12. COMPARISON OF SVM AND FUZZY CLASSIFIER FOR AN INDIAN SCRIPT

    Directory of Open Access Journals (Sweden)

    M. J. Baheti

    2012-01-01

    Full Text Available With the advent of technological era, conversion of scanned document (handwritten or printed into machine editable format has attracted many researchers. This paper deals with the problem of recognition of Gujarati handwritten numerals. Gujarati numeral recognition requires performing some specific steps as a part of preprocessing. For preprocessing digitization, segmentation, normalization and thinning are done with considering that the image have almost no noise. Further affine invariant moments based model is used for feature extraction and finally Support Vector Machine (SVM and Fuzzy classifiers are used for numeral classification. . The comparison of SVM and Fuzzy classifier is made and it can be seen that SVM procured better results as compared to Fuzzy Classifier.

  13. Comparison of multivariate preprocessing techniques as applied to electronic tongue based pattern classification for black tea

    International Nuclear Information System (INIS)

    Palit, Mousumi; Tudu, Bipan; Bhattacharyya, Nabarun; Dutta, Ankur; Dutta, Pallab Kumar; Jana, Arun; Bandyopadhyay, Rajib; Chatterjee, Anutosh

    2010-01-01

    In an electronic tongue, preprocessing on raw data precedes pattern analysis and choice of the appropriate preprocessing technique is crucial for the performance of the pattern classifier. While attempting to classify different grades of black tea using a voltammetric electronic tongue, different preprocessing techniques have been explored and a comparison of their performances is presented in this paper. The preprocessing techniques are compared first by a quantitative measurement of separability followed by principle component analysis; and then two different supervised pattern recognition models based on neural networks are used to evaluate the performance of the preprocessing techniques.

  14. Comparison of decomposition characteristics between aromatic and aliphatic VOCs using electron beam

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jo-Chun [Department of Environmental Engineering, Konkuk University, Seoul (Korea, Republic of)

    2011-07-01

    The removal efficiency of n-decane (C{sub 10}H{sub 22}) by electron beam was the highest among aliphatic VOCs of concern, and that of n-hexane (C{sub 6}H{sub 14}), n-butane (C{sub 4}H{sub 10}), and methane (CH{sub 4}) followed. On the other hand, in terms of aromatic VOC decomposition efficiencies, benzene (C{sub 6}H{sub 6}) decomposition was the lowest and that of toluene (C{sub 7}H{sub 8}), ethylbenzene (C{sub 8}H{sub 10}), and p-xylene (C{sub 8}H{sub 10}) were similar. It was also found that there was increase in by-product (untreated VOC, CO, CO{sub 2}, O{sub 3}, and other compounds) formation as well as all VOC removal efficiencies. It was demonstrated that the removal efficiency of VOC increased as its concentration decreased and the irradiation dose increased. In addition, low removal efficiency was observed because helium was relatively stable compared to the other gases, and nothing but electrons produced by electron accelerator reacted with VOC. It was also found that relative humidity had some effects on the decomposition rates of VOC. The removal efficiency at the 100% RH condition was slightly higher than that at 7.4% RH (dry condition) due to OH radical formation. (author)

  15. Improved Background Removal in Sounding Rocket Neutral Atom Imaging Data

    Science.gov (United States)

    Smith, M. R.; Rowland, D. E.

    2017-12-01

    The VISIONS sounding rocket, launched into a substorm on Feb 7, 2013 from Poker Flat, Alaska had a novel miniaturized energetic neutral atom (ENA) imager onboard. We present further analysis of the ENA data from this rocket flight, including improved removal of ultraviolet and electron contamination. In particular, the relative error source contributions due to geocoronal, auroral, and airglow UV, as well as energetic electrons from 10 eV to 3 keV were assessed. The resulting data provide a more clear understanding of the spatial and temporal variations of the ion populations that are energized to tens or hundreds of eV.

  16. A Nearest Neighbor Classifier Employing Critical Boundary Vectors for Efficient On-Chip Template Reduction.

    Science.gov (United States)

    Xia, Wenjun; Mita, Yoshio; Shibata, Tadashi

    2016-05-01

    Aiming at efficient data condensation and improving accuracy, this paper presents a hardware-friendly template reduction (TR) method for the nearest neighbor (NN) classifiers by introducing the concept of critical boundary vectors. A hardware system is also implemented to demonstrate the feasibility of using an field-programmable gate array (FPGA) to accelerate the proposed method. Initially, k -means centers are used as substitutes for the entire template set. Then, to enhance the classification performance, critical boundary vectors are selected by a novel learning algorithm, which is completed within a single iteration. Moreover, to remove noisy boundary vectors that can mislead the classification in a generalized manner, a global categorization scheme has been explored and applied to the algorithm. The global characterization automatically categorizes each classification problem and rapidly selects the boundary vectors according to the nature of the problem. Finally, only critical boundary vectors and k -means centers are used as the new template set for classification. Experimental results for 24 data sets show that the proposed algorithm can effectively reduce the number of template vectors for classification with a high learning speed. At the same time, it improves the accuracy by an average of 2.17% compared with the traditional NN classifiers and also shows greater accuracy than seven other TR methods. We have shown the feasibility of using a proof-of-concept FPGA system of 256 64-D vectors to accelerate the proposed method on hardware. At a 50-MHz clock frequency, the proposed system achieves a 3.86 times higher learning speed than on a 3.4-GHz PC, while consuming only 1% of the power of that used by the PC.

  17. Learning Bayesian network classifiers for credit scoring using Markov Chain Monte Carlo search

    NARCIS (Netherlands)

    Baesens, B.; Egmont-Petersen, M.; Castelo, R.; Vanthienen, J.

    2001-01-01

    In this paper, we will evaluate the power and usefulness of Bayesian network classifiers for credit scoring. Various types of Bayesian network classifiers will be evaluated and contrasted including unrestricted Bayesian network classifiers learnt using Markov Chain Monte Carlo (MCMC) search.

  18. Foreign object detection and removal to improve automated analysis of chest radiographs

    International Nuclear Information System (INIS)

    Hogeweg, Laurens; Sánchez, Clara I.; Melendez, Jaime; Maduskar, Pragnya; Ginneken, Bram van; Story, Alistair; Hayward, Andrew

    2013-01-01

    Purpose: Chest radiographs commonly contain projections of foreign objects, such as buttons, brassier clips, jewellery, or pacemakers and wires. The presence of these structures can substantially affect the output of computer analysis of these images. An automated method is presented to detect, segment, and remove foreign objects from chest radiographs.Methods: Detection is performed using supervised pixel classification with a kNN classifier, resulting in a probability estimate per pixel to belong to a projected foreign object. Segmentation is performed by grouping and post-processing pixels with a probability above a certain threshold. Next, the objects are replaced by texture inpainting.Results: The method is evaluated in experiments on 257 chest radiographs. The detection at pixel level is evaluated with receiver operating characteristic analysis on pixels within the unobscured lung fields and an A z value of 0.949 is achieved. Free response operator characteristic analysis is performed at the object level, and 95.6% of objects are detected with on average 0.25 false positive detections per image. To investigate the effect of removing the detected objects through inpainting, a texture analysis system for tuberculosis detection is applied to images with and without pathology and with and without foreign object removal. Unprocessed, the texture analysis abnormality score of normal images with foreign objects is comparable to those with pathology. After removing foreign objects, the texture score of normal images with and without foreign objects is similar, while abnormal images, whether they contain foreign objects or not, achieve on average higher scores.Conclusions: The authors conclude that removal of foreign objects from chest radiographs is feasible and beneficial for automated image analysis

  19. Snoring classified: The Munich-Passau Snore Sound Corpus.

    Science.gov (United States)

    Janott, Christoph; Schmitt, Maximilian; Zhang, Yue; Qian, Kun; Pandit, Vedhas; Zhang, Zixing; Heiser, Clemens; Hohenhorst, Winfried; Herzog, Michael; Hemmert, Werner; Schuller, Björn

    2018-03-01

    Snoring can be excited in different locations within the upper airways during sleep. It was hypothesised that the excitation locations are correlated with distinct acoustic characteristics of the snoring noise. To verify this hypothesis, a database of snore sounds is developed, labelled with the location of sound excitation. Video and audio recordings taken during drug induced sleep endoscopy (DISE) examinations from three medical centres have been semi-automatically screened for snore events, which subsequently have been classified by ENT experts into four classes based on the VOTE classification. The resulting dataset containing 828 snore events from 219 subjects has been split into Train, Development, and Test sets. An SVM classifier has been trained using low level descriptors (LLDs) related to energy, spectral features, mel frequency cepstral coefficients (MFCC), formants, voicing, harmonic-to-noise ratio (HNR), spectral harmonicity, pitch, and microprosodic features. An unweighted average recall (UAR) of 55.8% could be achieved using the full set of LLDs including formants. Best performing subset is the MFCC-related set of LLDs. A strong difference in performance could be observed between the permutations of train, development, and test partition, which may be caused by the relatively low number of subjects included in the smaller classes of the strongly unbalanced data set. A database of snoring sounds is presented which are classified according to their sound excitation location based on objective criteria and verifiable video material. With the database, it could be demonstrated that machine classifiers can distinguish different excitation location of snoring sounds in the upper airway based on acoustic parameters. Copyright © 2018 Elsevier Ltd. All rights reserved.

  20. A comparative study on Pb removal efficiencies of fired clay soils of ...

    African Journals Online (AJOL)

    user

    2013-08-01

    Aug 1, 2013 ... facture of storage batteries, pigments, leaded glass, fuels and photographic materials (Bhattacharyya and Gupta,. 2006). Conventionally, lead is removed from waste water ...... thermodynamics study. Electronic J. Biotechnol. 12:1-17. Renu S, Shiv PR, Kaushik CP (2008). Defluoridation of Drinking Water.

  1. General and Local: Averaged k-Dependence Bayesian Classifiers

    Directory of Open Access Journals (Sweden)

    Limin Wang

    2015-06-01

    Full Text Available The inference of a general Bayesian network has been shown to be an NP-hard problem, even for approximate solutions. Although k-dependence Bayesian (KDB classifier can construct at arbitrary points (values of k along the attribute dependence spectrum, it cannot identify the changes of interdependencies when attributes take different values. Local KDB, which learns in the framework of KDB, is proposed in this study to describe the local dependencies implicated in each test instance. Based on the analysis of functional dependencies, substitution-elimination resolution, a new type of semi-naive Bayesian operation, is proposed to substitute or eliminate generalization to achieve accurate estimation of conditional probability distribution while reducing computational complexity. The final classifier, averaged k-dependence Bayesian (AKDB classifiers, will average the output of KDB and local KDB. Experimental results on the repository of machine learning databases from the University of California Irvine (UCI showed that AKDB has significant advantages in zero-one loss and bias relative to naive Bayes (NB, tree augmented naive Bayes (TAN, Averaged one-dependence estimators (AODE, and KDB. Moreover, KDB and local KDB show mutually complementary characteristics with respect to variance.

  2. Entropy based classifier for cross-domain opinion mining

    Directory of Open Access Journals (Sweden)

    Jyoti S. Deshmukh

    2018-01-01

    Full Text Available In recent years, the growth of social network has increased the interest of people in analyzing reviews and opinions for products before they buy them. Consequently, this has given rise to the domain adaptation as a prominent area of research in sentiment analysis. A classifier trained from one domain often gives poor results on data from another domain. Expression of sentiment is different in every domain. The labeling cost of each domain separately is very high as well as time consuming. Therefore, this study has proposed an approach that extracts and classifies opinion words from one domain called source domain and predicts opinion words of another domain called target domain using a semi-supervised approach, which combines modified maximum entropy and bipartite graph clustering. A comparison of opinion classification on reviews on four different product domains is presented. The results demonstrate that the proposed method performs relatively well in comparison to the other methods. Comparison of SentiWordNet of domain-specific and domain-independent words reveals that on an average 72.6% and 88.4% words, respectively, are correctly classified.

  3. Removal of Na+ from Ionic Liquids by Zeolite for High Quality Electrolyte Manufacture

    International Nuclear Information System (INIS)

    Cho, Wonje; Seo, Yongseong; Jung, Soon Jae; Lee, Won Gil; Kim, Byung Chul; Yu, Kookhyun

    2013-01-01

    This study develops a novel method to remove the free cations created during the synthesis of ionic liquid. The cations are removed from the ionic liquid by size-selective adsorption onto chemically surface-modified Zeolite. The porous crystal nano-structure of Zeolite has several electron-rich Al sites to attract cations. While large cations of an ionic liquid cannot access the Zeolite nano-structure, small cations like Na + have ready access and are adsorbed. This study confirms that: Na + can be removed from ionic liquid effectively using Zeolite; and, in contrast to the conventional and extensively applied ion exchange resin method or solvent extraction methods, this can be done without changing the nature of the ionic liquid

  4. A Gene Expression Classifier of Node-Positive Colorectal Cancer

    Directory of Open Access Journals (Sweden)

    Paul F. Meeh

    2009-10-01

    Full Text Available We used digital long serial analysis of gene expression to discover gene expression differences between node-negative and node-positive colorectal tumors and developed a multigene classifier able to discriminate between these two tumor types. We prepared and sequenced long serial analysis of gene expression libraries from one node-negative and one node-positive colorectal tumor, sequenced to a depth of 26,060 unique tags, and identified 262 tags significantly differentially expressed between these two tumors (P < 2 x 10-6. We confirmed the tag-to-gene assignments and differential expression of 31 genes by quantitative real-time polymerase chain reaction, 12 of which were elevated in the node-positive tumor. We analyzed the expression levels of these 12 upregulated genes in a validation panel of 23 additional tumors and developed an optimized seven-gene logistic regression classifier. The classifier discriminated between node-negative and node-positive tumors with 86% sensitivity and 80% specificity. Receiver operating characteristic analysis of the classifier revealed an area under the curve of 0.86. Experimental manipulation of the function of one classification gene, Fibronectin, caused profound effects on invasion and migration of colorectal cancer cells in vitro. These results suggest that the development of node-positive colorectal cancer occurs in part through elevated epithelial FN1 expression and suggest novel strategies for the diagnosis and treatment of advanced disease.

  5. Building an automated SOAP classifier for emergency department reports.

    Science.gov (United States)

    Mowery, Danielle; Wiebe, Janyce; Visweswaran, Shyam; Harkema, Henk; Chapman, Wendy W

    2012-02-01

    Information extraction applications that extract structured event and entity information from unstructured text can leverage knowledge of clinical report structure to improve performance. The Subjective, Objective, Assessment, Plan (SOAP) framework, used to structure progress notes to facilitate problem-specific, clinical decision making by physicians, is one example of a well-known, canonical structure in the medical domain. Although its applicability to structuring data is understood, its contribution to information extraction tasks has not yet been determined. The first step to evaluating the SOAP framework's usefulness for clinical information extraction is to apply the model to clinical narratives and develop an automated SOAP classifier that classifies sentences from clinical reports. In this quantitative study, we applied the SOAP framework to sentences from emergency department reports, and trained and evaluated SOAP classifiers built with various linguistic features. We found the SOAP framework can be applied manually to emergency department reports with high agreement (Cohen's kappa coefficients over 0.70). Using a variety of features, we found classifiers for each SOAP class can be created with moderate to outstanding performance with F(1) scores of 93.9 (subjective), 94.5 (objective), 75.7 (assessment), and 77.0 (plan). We look forward to expanding the framework and applying the SOAP classification to clinical information extraction tasks. Copyright © 2011. Published by Elsevier Inc.

  6. Localizing genes to cerebellar layers by classifying ISH images.

    Directory of Open Access Journals (Sweden)

    Lior Kirsch

    Full Text Available Gene expression controls how the brain develops and functions. Understanding control processes in the brain is particularly hard since they involve numerous types of neurons and glia, and very little is known about which genes are expressed in which cells and brain layers. Here we describe an approach to detect genes whose expression is primarily localized to a specific brain layer and apply it to the mouse cerebellum. We learn typical spatial patterns of expression from a few markers that are known to be localized to specific layers, and use these patterns to predict localization for new genes. We analyze images of in-situ hybridization (ISH experiments, which we represent using histograms of local binary patterns (LBP and train image classifiers and gene classifiers for four layers of the cerebellum: the Purkinje, granular, molecular and white matter layer. On held-out data, the layer classifiers achieve accuracy above 94% (AUC by representing each image at multiple scales and by combining multiple image scores into a single gene-level decision. When applied to the full mouse genome, the classifiers predict specific layer localization for hundreds of new genes in the Purkinje and granular layers. Many genes localized to the Purkinje layer are likely to be expressed in astrocytes, and many others are involved in lipid metabolism, possibly due to the unusual size of Purkinje cells.

  7. Arabic Handwriting Recognition Using Neural Network Classifier

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... an OCR using Neural Network classifier preceded by a set of preprocessing .... Artificial Neural Networks (ANNs), which we adopt in this research, consist of ... advantage and disadvantages of each technique. In [9],. Khemiri ...

  8. Lung Nodule Image Classification Based on Local Difference Pattern and Combined Classifier.

    Science.gov (United States)

    Mao, Keming; Deng, Zhuofu

    2016-01-01

    This paper proposes a novel lung nodule classification method for low-dose CT images. The method includes two stages. First, Local Difference Pattern (LDP) is proposed to encode the feature representation, which is extracted by comparing intensity difference along circular regions centered at the lung nodule. Then, the single-center classifier is trained based on LDP. Due to the diversity of feature distribution for different class, the training images are further clustered into multiple cores and the multicenter classifier is constructed. The two classifiers are combined to make the final decision. Experimental results on public dataset show the superior performance of LDP and the combined classifier.

  9. Lung Nodule Image Classification Based on Local Difference Pattern and Combined Classifier

    Directory of Open Access Journals (Sweden)

    Keming Mao

    2016-01-01

    Full Text Available This paper proposes a novel lung nodule classification method for low-dose CT images. The method includes two stages. First, Local Difference Pattern (LDP is proposed to encode the feature representation, which is extracted by comparing intensity difference along circular regions centered at the lung nodule. Then, the single-center classifier is trained based on LDP. Due to the diversity of feature distribution for different class, the training images are further clustered into multiple cores and the multicenter classifier is constructed. The two classifiers are combined to make the final decision. Experimental results on public dataset show the superior performance of LDP and the combined classifier.

  10. Detection of microaneurysms in retinal images using an ensemble classifier

    Directory of Open Access Journals (Sweden)

    M.M. Habib

    2017-01-01

    Full Text Available This paper introduces, and reports on the performance of, a novel combination of algorithms for automated microaneurysm (MA detection in retinal images. The presence of MAs in retinal images is a pathognomonic sign of Diabetic Retinopathy (DR which is one of the leading causes of blindness amongst the working age population. An extensive survey of the literature is presented and current techniques in the field are summarised. The proposed technique first detects an initial set of candidates using a Gaussian Matched Filter and then classifies this set to reduce the number of false positives. A Tree Ensemble classifier is used with a set of 70 features (the most commons features in the literature. A new set of 32 MA groundtruth images (with a total of 256 labelled MAs based on images from the MESSIDOR dataset is introduced as a public dataset for benchmarking MA detection algorithms. We evaluate our algorithm on this dataset as well as another public dataset (DIARETDB1 v2.1 and compare it against the best available alternative. Results show that the proposed classifier is superior in terms of eliminating false positive MA detection from the initial set of candidates. The proposed method achieves an ROC score of 0.415 compared to 0.2636 achieved by the best available technique. Furthermore, results show that the classifier model maintains consistent performance across datasets, illustrating the generalisability of the classifier and that overfitting does not occur.

  11. Dynamic cluster generation for a fuzzy classifier with ellipsoidal regions.

    Science.gov (United States)

    Abe, S

    1998-01-01

    In this paper, we discuss a fuzzy classifier with ellipsoidal regions that dynamically generates clusters. First, for the data belonging to a class we define a fuzzy rule with an ellipsoidal region. Namely, using the training data for each class, we calculate the center and the covariance matrix of the ellipsoidal region for the class. Then we tune the fuzzy rules, i.e., the slopes of the membership functions, successively until there is no improvement in the recognition rate of the training data. Then if the number of the data belonging to a class that are misclassified into another class exceeds a prescribed number, we define a new cluster to which those data belong and the associated fuzzy rule. Then we tune the newly defined fuzzy rules in the similar way as stated above, fixing the already obtained fuzzy rules. We iterate generation of clusters and tuning of the newly generated fuzzy rules until the number of the data belonging to a class that are misclassified into another class does not exceed the prescribed number. We evaluate our method using thyroid data, Japanese Hiragana data of vehicle license plates, and blood cell data. By dynamic cluster generation, the generalization ability of the classifier is improved and the recognition rate of the fuzzy classifier for the test data is the best among the neural network classifiers and other fuzzy classifiers if there are no discrete input variables.

  12. A Bayesian Classifier for X-Ray Pulsars Recognition

    Directory of Open Access Journals (Sweden)

    Hao Liang

    2016-01-01

    Full Text Available Recognition for X-ray pulsars is important for the problem of spacecraft’s attitude determination by X-ray Pulsar Navigation (XPNAV. By using the nonhomogeneous Poisson model of the received photons and the minimum recognition error criterion, a classifier based on the Bayesian theorem is proposed. For X-ray pulsars recognition with unknown Doppler frequency and initial phase, the features of every X-ray pulsar are extracted and the unknown parameters are estimated using the Maximum Likelihood (ML method. Besides that, a method to recognize unknown X-ray pulsars or X-ray disturbances is proposed. Simulation results certificate the validity of the proposed Bayesian classifier.

  13. Hexavalent chromium removal by chitosan modified-bioreduced nontronite

    Science.gov (United States)

    Singh, Rajesh; Dong, Hailiang; Zeng, Qiang; Zhang, Li; Rengasamy, Karthikeyan

    2017-08-01

    Recent efforts have focused on structural Fe(II) in chemically or biologically reduced clay minerals to immobilize Cr(VI) from aqueous solution, but the coulombic repulsion between the negatively charged clay surface and the polyanionic form of Cr(VI), e.g., dichromate, can hinder the effectiveness of this process. The purpose of this study was to investigate the efficiency and mechanism of Cr(VI) removal by a charge-reversed nontronite (NAu-2), an Fe-rich smectite. Chitosan, a linear polysaccharide derived from chitin found in soil and groundwater, was used to reverse the charge of NAu-2. Intercalation of chitosan into NAu-2 interlayer increased the basal d-spacing of NAu-2 from 1.23 nm to 1.83 nm and zeta potential from -27.17 to +34.13 mV, with the amount of increase depending on chitosan/NAu-2 ratio. Structural Fe(III) in chitosan-exchanged NAu-2 was then biologically reduced by an iron-reducing bacterium Shewanella putrefaciens CN32 in bicarbonate buffer with lactate as the sole electron donor, with and without electron shuttle, AQDS. Without AQDS, the extent of Fe(III) reduction increased from the lowest (∼9%) for the chitosan-free NAu-2 to the highest (∼12%) for the highest chitosan loaded NAu-2 (3:1 ratio). This enhancement of Fe(III) reduction was likely due to the attachment of negatively charged bacterial cells to charge-reversed (e.g., positively charged) NAu-2 surfaces, facilitating the electron transfer between cells and structural Fe(III). With AQDS, Fe(III) reduction extent doubled relative to those without AQDS, but the enhancement effect was similar across all chitosan loadings, suggesting that AQDS was more important than chitosan in enhancing Fe(III) bioreduction. Chitosan-exchanged, biologically reduced NAu-2 was then utilized for removing Cr(VI) in batch experiments with three consecutive spikes of 50 μM Cr. With the first Cr spike, the rate of Cr(VI) removal by charged-reversed NAu-2 that was bioreduced without and with AQDS was ∼1

  14. Adaptation in P300 braincomputer interfaces: A two-classifier cotraining approach

    DEFF Research Database (Denmark)

    Panicker, Rajesh C.; Sun, Ying; Puthusserypady, Sadasivan

    2010-01-01

    A cotraining-based approach is introduced for constructing high-performance classifiers for P300-based braincomputer interfaces (BCIs), which were trained from very little data. It uses two classifiers: Fishers linear discriminant analysis and Bayesian linear discriminant analysis progressively...

  15. Text mining electronic hospital records to automatically classify admissions against disease: Measuring the impact of linking data sources.

    Science.gov (United States)

    Kocbek, Simon; Cavedon, Lawrence; Martinez, David; Bain, Christopher; Manus, Chris Mac; Haffari, Gholamreza; Zukerman, Ingrid; Verspoor, Karin

    2016-12-01

    Text and data mining play an important role in obtaining insights from Health and Hospital Information Systems. This paper presents a text mining system for detecting admissions marked as positive for several diseases: Lung Cancer, Breast Cancer, Colon Cancer, Secondary Malignant Neoplasm of Respiratory and Digestive Organs, Multiple Myeloma and Malignant Plasma Cell Neoplasms, Pneumonia, and Pulmonary Embolism. We specifically examine the effect of linking multiple data sources on text classification performance. Support Vector Machine classifiers are built for eight data source combinations, and evaluated using the metrics of Precision, Recall and F-Score. Sub-sampling techniques are used to address unbalanced datasets of medical records. We use radiology reports as an initial data source and add other sources, such as pathology reports and patient and hospital admission data, in order to assess the research question regarding the impact of the value of multiple data sources. Statistical significance is measured using the Wilcoxon signed-rank test. A second set of experiments explores aspects of the system in greater depth, focusing on Lung Cancer. We explore the impact of feature selection; analyse the learning curve; examine the effect of restricting admissions to only those containing reports from all data sources; and examine the impact of reducing the sub-sampling. These experiments provide better understanding of how to best apply text classification in the context of imbalanced data of variable completeness. Radiology questions plus patient and hospital admission data contribute valuable information for detecting most of the diseases, significantly improving performance when added to radiology reports alone or to the combination of radiology and pathology reports. Overall, linking data sources significantly improved classification performance for all the diseases examined. However, there is no single approach that suits all scenarios; the choice of the

  16. Presentation of the verbs in Bulgarian-Polish electronic dictionary

    Directory of Open Access Journals (Sweden)

    Ludmila Dimitrova

    2014-09-01

    Full Text Available Presentation of the verbs in Bulgarian-Polish electronic dictionary This paper briefly discusses the presentation of the verbs in the first electronic Bulgarian-Polish dictionary that is currently being developed under a bilateral collaboration between IMI-BAS and ISS-PAS. Special attention is given to the digital entry classifiers that describe Bulgarian and Polish verbs. Problems related to the correspondence between natural language phenomena and their presentations are discussed. Some examples illustrate the different types of dictionary entries for verbs.

  17. Infrared and ultraviolet laser removal of crustose lichens on dolomite heritage stone

    Energy Technology Data Exchange (ETDEWEB)

    Sanz, Mikel; Oujja, Mohamed [Instituto de Química Física Rocasolano (IQFR), CSIC, Serrano 119, 28006 Madrid (Spain); Ascaso, Carmen; Ríos, Asunción de los; Pérez-Ortega, Sergio [Museo Nacional de Ciencia Naturales (MNCN), CSIC, Serrano 115 bis, 28006 Madrid (Spain); Souza-Egipsy, Virginia [Instituto de Ciencias Agrarias (ICA), CSIC, Serrano 115 bis, 28006 Madrid (Spain); Wierzchos, Jacek; Speranza, Mariela [Museo Nacional de Ciencia Naturales (MNCN), CSIC, Serrano 115 bis, 28006 Madrid (Spain); Cañamares, Maria Vega [Instituto de Estructura de la Materia (ICEM), CSIC, Serrano 121, 28006 Madrid (Spain); Castillejo, Marta, E-mail: marta.castillejo@iqfr.csic.es [Instituto de Química Física Rocasolano (IQFR), CSIC, Serrano 119, 28006 Madrid (Spain)

    2015-08-15

    Graphical abstract: - Highlights: • Laser irradiation at 1064 nm (IR) or 355 nm (UV) partially removes epilithic lichens on dolostone. • Irradiation in a sequential, dual IR–UV mode efficiently eliminates lichen thalli. • Dual IR–UV irradiation mode induces severe damage on endolithic colonizers of dolostone. - Abstract: Laser removal of biodeteriogen layers warrants detailed studies due to the advantages it brings with respect to mechanical elimination or the use of biocides. We have investigated elimination of biological crusts on dolomite stones from heritage sites in central Spain. The samples were colonized by epilithic crustose lichens of different species, such as Caloplaca sp. and Verrucaria nigrescens. A comparative study was carried out by applying infrared (1064 nm) and ultraviolet (355 nm) nanosecond laser pulses and sequences pulses of the two wavelengths using a Q-switched Nd:YAG system. To detect anatomical and ultrastructural damage to the lichens, and to assess possible morphological and chemical changes on the underlying stone induced by laser irradiation, we used stereomicroscopy, scanning electron microscopy with backscattered electron imaging and Fourier transform Raman spectroscopy. The optimal conditions for removal of the colonization crust, while ensuring preservation of the lithic substrate, were obtained for dual infrared-ultraviolet sequential irradiation.

  18. Binary naive Bayesian classifiers for correlated Gaussian features: a theoretical analysis

    CSIR Research Space (South Africa)

    Van Dyk, E

    2008-11-01

    Full Text Available classifier with Gaussian features while using any quadratic decision boundary. Therefore, the analysis is not restricted to Naive Bayesian classifiers alone and can, for instance, be used to calculate the Bayes error performance. We compare the analytical...

  19. Automating the construction of scene classifiers for content-based video retrieval

    NARCIS (Netherlands)

    Khan, L.; Israël, Menno; Petrushin, V.A.; van den Broek, Egon; van der Putten, Peter

    2004-01-01

    This paper introduces a real time automatic scene classifier within content-based video retrieval. In our envisioned approach end users like documentalists, not image processing experts, build classifiers interactively, by simply indicating positive examples of a scene. Classification consists of a

  20. Center for electron nanoscopy, DTU

    DEFF Research Database (Denmark)

    Horsewell, Andy; Somers, Marcel A. J.; Chorkendorff, Ib

    2006-01-01

    front is in the field of scanning electron microscopy, SEM, which has already seen major advances due to field emission electron guns, FEG: I) Adding a focussed ion beam, so that specimen surface layers can be removed by controlled sputtering, a dual-beam FEGSEM FIB allows reconstruction...... image reconstruction from multiple images acquired through 70o tilts, TEM tomography can map nanostructures in 3D; III) Observation of TEM specimens in an environmental cell, at temperature and in a controlled gaseous environment, can provide in-situ observations of gas-solid interactions. The second...

  1. [Evaluation of cermet fillings in abutment teeth in removable partial prostheses].

    Science.gov (United States)

    Saulic, S; Tihacek-Sojic, Lj

    2001-01-01

    The aim of the study was to describe the clinical process of setting the purpose filling on abutment teeth, after finishing the removable partial dentures. The aim was also to investigate the use of cermet glass-ionomer cement for the purpose filling in the abutment teeth for removable partial dentures, as well as to investigate the surface of the purpose filling. For the clinical evaluation of purpose filling slightly modified criteria according to Ryg's were used in 20 patients with different type of edentulousness. Changes occurring on the surface of purpose filling have been experimentally established by the method of scanning electron microscopy on the half-grown third molars in seven patients. It could be concluded that cement glass-ionomer was not the appropriate material for the purpose fillings in abutment teeth for removable partial dentures.

  2. A unified classifier for robust face recognition based on combining multiple subspace algorithms

    Science.gov (United States)

    Ijaz Bajwa, Usama; Ahmad Taj, Imtiaz; Waqas Anwar, Muhammad

    2012-10-01

    Face recognition being the fastest growing biometric technology has expanded manifold in the last few years. Various new algorithms and commercial systems have been proposed and developed. However, none of the proposed or developed algorithm is a complete solution because it may work very well on one set of images with say illumination changes but may not work properly on another set of image variations like expression variations. This study is motivated by the fact that any single classifier cannot claim to show generally better performance against all facial image variations. To overcome this shortcoming and achieve generality, combining several classifiers using various strategies has been studied extensively also incorporating the question of suitability of any classifier for this task. The study is based on the outcome of a comprehensive comparative analysis conducted on a combination of six subspace extraction algorithms and four distance metrics on three facial databases. The analysis leads to the selection of the most suitable classifiers which performs better on one task or the other. These classifiers are then combined together onto an ensemble classifier by two different strategies of weighted sum and re-ranking. The results of the ensemble classifier show that these strategies can be effectively used to construct a single classifier that can successfully handle varying facial image conditions of illumination, aging and facial expressions.

  3. Degradation and toxicity assessment of sulfamethoxazole and chlortetracycline using electron beam, ozone and UV

    International Nuclear Information System (INIS)

    Kim, Tae-Hun; Kim, Sang Don; Kim, Hyun Young; Lim, Seung Joo; Lee, Myunjoo; Yu, Seungho

    2012-01-01

    Highlights: ► The degradation efficiency and trends for antibiotics were different between AOPs. ► The toxicities of target antibiotics were mainly affected by parent compounds. ► E-beam was electrically more energy efficient than ozone and UV-C. ► Application of AOPs should be considered according to the types of pharmaceuticals. - Abstract: Recently, the occurrence of antibiotics in sewage treatment plant effluent, as well as drinking water, has raised concern about their potential impacts on the environment and public health. Antibiotics are found in surface and ground waters, which indicate their ineffective removal by conventional wastewater treatment processes. Therefore, advanced oxidation processes (AOPs) have received considerable attention for the removal of antibiotics. This study was conducted to evaluate the degradation and mineralization of antibiotics (sulfamethoxazole and chlortetracycline) using an electron beam, ozone and UV, and the change of toxicity. Also, the electrical energy consumption based on the EE/O parameter (the electrical energy required per order of pollutants removal in 1 m 3 wastewater) was used to quantify the energy cost associated with the different AOPs (electron beam, ozone and UV) for the degradation of antibiotics. The results showed that an electron beam effective for the removals of both sulfamethoxazole and chlortetracycline in aqueous solutions. However, degradation of the target compounds by ozone and UV showed different trends. The oxidation efficiency of each organic compound was very dependent upon the AOP used. Algal toxicity was significantly reduced after each treatment. However, based on the electrical energy, the electron beam was more efficient than ozone and UV. Electron beam treatment could be an effective and safe method for the removal of antibiotic compounds.

  4. Optimal threshold estimation for binary classifiers using game theory.

    Science.gov (United States)

    Sanchez, Ignacio Enrique

    2016-01-01

    Many bioinformatics algorithms can be understood as binary classifiers. They are usually compared using the area under the receiver operating characteristic ( ROC ) curve. On the other hand, choosing the best threshold for practical use is a complex task, due to uncertain and context-dependent skews in the abundance of positives in nature and in the yields/costs for correct/incorrect classification. We argue that considering a classifier as a player in a zero-sum game allows us to use the minimax principle from game theory to determine the optimal operating point. The proposed classifier threshold corresponds to the intersection between the ROC curve and the descending diagonal in ROC space and yields a minimax accuracy of 1-FPR. Our proposal can be readily implemented in practice, and reveals that the empirical condition for threshold estimation of "specificity equals sensitivity" maximizes robustness against uncertainties in the abundance of positives in nature and classification costs.

  5. Comparison of artificial intelligence classifiers for SIP attack data

    Science.gov (United States)

    Safarik, Jakub; Slachta, Jiri

    2016-05-01

    Honeypot application is a source of valuable data about attacks on the network. We run several SIP honeypots in various computer networks, which are separated geographically and logically. Each honeypot runs on public IP address and uses standard SIP PBX ports. All information gathered via honeypot is periodically sent to the centralized server. This server classifies all attack data by neural network algorithm. The paper describes optimizations of a neural network classifier, which lower the classification error. The article contains the comparison of two neural network algorithm used for the classification of validation data. The first is the original implementation of the neural network described in recent work; the second neural network uses further optimizations like input normalization or cross-entropy cost function. We also use other implementations of neural networks and machine learning classification algorithms. The comparison test their capabilities on validation data to find the optimal classifier. The article result shows promise for further development of an accurate SIP attack classification engine.

  6. Least Square Support Vector Machine Classifier vs a Logistic Regression Classifier on the Recognition of Numeric Digits

    Directory of Open Access Journals (Sweden)

    Danilo A. López-Sarmiento

    2013-11-01

    Full Text Available In this paper is compared the performance of a multi-class least squares support vector machine (LSSVM mc versus a multi-class logistic regression classifier to problem of recognizing the numeric digits (0-9 handwritten. To develop the comparison was used a data set consisting of 5000 images of handwritten numeric digits (500 images for each number from 0-9, each image of 20 x 20 pixels. The inputs to each of the systems were vectors of 400 dimensions corresponding to each image (not done feature extraction. Both classifiers used OneVsAll strategy to enable multi-classification and a random cross-validation function for the process of minimizing the cost function. The metrics of comparison were precision and training time under the same computational conditions. Both techniques evaluated showed a precision above 95 %, with LS-SVM slightly more accurate. However the computational cost if we found a marked difference: LS-SVM training requires time 16.42 % less than that required by the logistic regression model based on the same low computational conditions.

  7. Gene-expression Classifier in Papillary Thyroid Carcinoma

    DEFF Research Database (Denmark)

    Londero, Stefano Christian; Jespersen, Marie Louise; Krogdahl, Annelise

    2016-01-01

    BACKGROUND: No reliable biomarker for metastatic potential in the risk stratification of papillary thyroid carcinoma exists. We aimed to develop a gene-expression classifier for metastatic potential. MATERIALS AND METHODS: Genome-wide expression analyses were used. Development cohort: freshly...

  8. Cross-field Mobility in a Pure Electron Plasma

    International Nuclear Information System (INIS)

    Fossum, E.C.; King, L.B.

    2006-01-01

    An electron trapping apparatus was constructed in order to study electron dynamics in the defining electric and magnetic field of a Hall-effect thruster. The approach presented here decouples the cross-field mobility from plasma effects by conducting measurements on a pure electron plasma in a highly controlled environment. Dielectric walls are removed completely eliminating all wall effect; thus, electrons are confined solely by a radial magnetic field and a crossed, independently-controlled, axial electric field that induces the closed-drift azimuthal Hall current. Electron trajectories and cross-field mobility were examined in response to electric and magnetic field strength and background neutral density

  9. A History of Classified Activities at Oak Ridge National Laboratory

    Energy Technology Data Exchange (ETDEWEB)

    Quist, A.S.

    2001-01-30

    The facilities that became Oak Ridge National Laboratory (ORNL) were created in 1943 during the United States' super-secret World War II project to construct an atomic bomb (the Manhattan Project). During World War II and for several years thereafter, essentially all ORNL activities were classified. Now, in 2000, essentially all ORNL activities are unclassified. The major purpose of this report is to provide a brief history of ORNL's major classified activities from 1943 until the present (September 2000). This report is expected to be useful to the ORNL Classification Officer and to ORNL's Authorized Derivative Classifiers and Authorized Derivative Declassifiers in their classification review of ORNL documents, especially those documents that date from the 1940s and 1950s.

  10. Simultaneous nitrogen and phosphorus removal in the sulfur cycle-associated Enhanced Biological Phosphorus Removal (EBPR) process.

    Science.gov (United States)

    Wu, Di; Ekama, George A; Wang, Hai-Guang; Wei, Li; Lu, Hui; Chui, Ho-Kwong; Liu, Wen-Tso; Brdjanovic, Damir; van Loosdrecht, Mark C M; Chen, Guang-Hao

    2014-02-01

    Hong Kong has practiced seawater toilet flushing since 1958, saving 750,000 m(3) of freshwater every day. A high sulfate-to-COD ratio (>1.25 mg SO4(2-)/mg COD) in the saline sewage resulting from this practice has enabled us to develop the Sulfate reduction, Autotrophic denitrification and Nitrification Integrated (SANI(®)) process with minimal sludge production and oxygen demand. Recently, the SANI(®) process has been expanded to include Enhanced Biological Phosphorus Removal (EBPR) in an alternating anaerobic/limited-oxygen (LOS-EBPR) aerobic sequencing batch reactor (SBR). This paper presents further development - an anaerobic/anoxic denitrifying sulfur cycle-associated EBPR, named as DS-EBPR, bioprocess in an alternating anaerobic/anoxic SBR for simultaneous removal of organics, nitrogen and phosphorus. The 211 day SBR operation confirmed the sulfur cycle-associated biological phosphorus uptake utilizing nitrate as electron acceptor. This new bioprocess cannot only reduce operation time but also enhance volumetric loading of SBR compared with the LOS-EBPR. The DS-EBPR process performed well at high temperatures of 30 °C and a high salinity of 20% seawater. A synergistic relationship may exist between sulfur cycle and biological phosphorus removal as the optimal ratio of P-release to SO4(2-)-reduction is close to 1.0 mg P/mg S. There were no conventional PAOs in the sludge. Copyright © 2013 Elsevier Ltd. All rights reserved.

  11. Identification and classification of human cytomegalovirus capsids in textured electron micrographs using deformed template matching

    Directory of Open Access Journals (Sweden)

    Söderberg-Nauclér Cecilia

    2006-08-01

    Full Text Available Abstract Background Characterization of the structural morphology of virus particles in electron micrographs is a complex task, but desirable in connection with investigation of the maturation process and detection of changes in viral particle morphology in response to the effect of a mutation or antiviral drugs being applied. Therefore, we have here developed a procedure for describing and classifying virus particle forms in electron micrographs, based on determination of the invariant characteristics of the projection of a given virus structure. The template for the virus particle is created on the basis of information obtained from a small training set of electron micrographs and is then employed to classify and quantify similar structures of interest in an unlimited number of electron micrographs by a process of correlation. Results Practical application of the method is demonstrated by the ability to locate three diverse classes of virus particles in transmission electron micrographs of fibroblasts infected with human cytomegalovirus. These results show that fast screening of the total number of viral structures at different stages of maturation in a large set of electron micrographs, a task that is otherwise both time-consuming and tedious for the expert, can be accomplished rapidly and reliably with our automated procedure. Using linear deformation analysis, this novel algorithm described here can handle capsid variations such as ellipticity and furthermore allows evaluation of properties such as the size and orientation of a virus particle. Conclusion Our methodological procedure represents a promising objective tool for comparative studies of the intracellular assembly processes of virus particles using electron microscopy in combination with our digitized image analysis tool. An automated method for sorting and classifying virus particles at different stages of maturation will enable us to quantify virus production in all stages of the

  12. Oblique decision trees using embedded support vector machines in classifier ensembles

    NARCIS (Netherlands)

    Menkovski, V.; Christou, I.; Efremidis, S.

    2008-01-01

    Classifier ensembles have emerged in recent years as a promising research area for boosting pattern recognition systems' performance. We present a new base classifier that utilizes oblique decision tree technology based on support vector machines for the construction of oblique (non-axis parallel)

  13. Stack filter classifiers

    Energy Technology Data Exchange (ETDEWEB)

    Porter, Reid B [Los Alamos National Laboratory; Hush, Don [Los Alamos National Laboratory

    2009-01-01

    Just as linear models generalize the sample mean and weighted average, weighted order statistic models generalize the sample median and weighted median. This analogy can be continued informally to generalized additive modeels in the case of the mean, and Stack Filters in the case of the median. Both of these model classes have been extensively studied for signal and image processing but it is surprising to find that for pattern classification, their treatment has been significantly one sided. Generalized additive models are now a major tool in pattern classification and many different learning algorithms have been developed to fit model parameters to finite data. However Stack Filters remain largely confined to signal and image processing and learning algorithms for classification are yet to be seen. This paper is a step towards Stack Filter Classifiers and it shows that the approach is interesting from both a theoretical and a practical perspective.

  14. 29 CFR 1926.407 - Hazardous (classified) locations.

    Science.gov (United States)

    2010-07-01

    ...) locations, unless modified by provisions of this section. (b) Electrical installations. Equipment, wiring..., DEPARTMENT OF LABOR (CONTINUED) SAFETY AND HEALTH REGULATIONS FOR CONSTRUCTION Electrical Installation Safety... electric equipment and wiring in locations which are classified depending on the properties of the...

  15. Application of a new adsorbent for fluoride removal from aqueous solutions

    International Nuclear Information System (INIS)

    Srivastav, Arun Lal; Singh, Prabhat K.; Srivastava, Varsha; Sharma, Yogesh C.

    2013-01-01

    Highlights: • A new adsorbent has been prepared. • The adsorbent is non-toxic and easy to synthesize. • HBO 1 has displayed best capacity for the removal of fluoride. • Unlike most adsorbents, HBO 1 is suitable for the removal of fluoride from water. • The process of removal has been optimized. -- Abstract: Hydrous bismuth oxides (HBOs) have been investigated as a possible adsorbent for fluoride removal from water. Apart from bismuth trioxide (Bi 2 O 3 ) compound, three additional HBOs, named as HBO 1 , HBO 2 , and HBO 3 were synthesized in the laboratory and examined for their relative potentials for fluoride removal from aqueous solutions. HBO 1 was observed to have highest fluoride removal at 10 mg/L initial concentration in aqueous environment. Among competitive anions, sulfate and chloride affect the fluoride removal by HBO 1 more adversely than bicarbonate. Characterization of HBOs using X-ray diffraction (XRD) pattern analyses indicated crystalline structures, and the broad chemical composition of materials showed successive increase of Bi(OH) 3 from HBO 1 to HBO 3 , with decrease of BiOCl in the same order. Fourier Transform Infrared (FTIR) spectroscopy analyses indicated presence of Bi-O bond and successively increasing number of peaks corresponding to OH ion from HBO 1 to HBO 3 . Scanning Electron Microscopic (SEM) images of HBOs show rough and porous structure of the materials. Presence of higher proportion of chloride compound in HBO 1 with respect to others appears to be the factor responsible for its better performance in fluoride removal from aqueous solutions

  16. Precision shape modification of nanodevices with a low-energy electron beam

    Science.gov (United States)

    Zettl, Alex; Yuzvinsky, Thomas David; Fennimore, Adam

    2010-03-09

    Methods of shape modifying a nanodevice by contacting it with a low-energy focused electron beam are disclosed here. In one embodiment, a nanodevice may be permanently reformed to a different geometry through an application of a deforming force and a low-energy focused electron beam. With the addition of an assist gas, material may be removed from the nanodevice through application of the low-energy focused electron beam. The independent methods of shape modification and material removal may be used either individually or simultaneously. Precision cuts with accuracies as high as 10 nm may be achieved through the use of precision low-energy Scanning Electron Microscope scan beams. These methods may be used in an automated system to produce nanodevices of very precise dimensions. These methods may be used to produce nanodevices of carbon-based, silicon-based, or other compositions by varying the assist gas.

  17. Required ozone doses for removing pharmaceuticals from wastewater effluents

    DEFF Research Database (Denmark)

    Antoniou, Maria; Hey, Gerly; Rodríguez Vega, Sergio

    2013-01-01

    of each investigated API (DDO3) was determined for each effluent by fitting a first order equation to the remaining concentration of API at each applied ozone dose. Ozone dose requirements were found to vary significantly between effluents depending on their matrix characteristics.The specific ozone dose...... was then normalized to the dissolved organic carbon (DOC) of each effluent. The DDO3/DOC ratios were comparable for each API between the effluents.15 of the 42 investigated APIs could be classified as easily degradable (DDO3/DOC≤0.7), while 19 were moderately degradable (0.71.4). Furthermore, we predict...... that a reasonable estimate of the ozone dose required to remove any of the investigated APIs may be attained by multiplying the experimental average DDO3/DOC obtained with the actual DOC of any effluent....

  18. Influence of wavelength on the laser removal of lichens colonizing heritage stone

    International Nuclear Information System (INIS)

    Sanz, M.; Oujja, M.; Ascaso, C.; Pérez-Ortega, S.; Souza-Egipsy, V.; Fort, R.; Rios, A. de los; Wierzchos, J.; Cañamares, M.V.; Castillejo, M.

    2017-01-01

    Highlights: • Optimal laser removal conditions depend on light absorption of lichen species. • Highly UV absorbing species (C. vitellina) removed by 266 nm nanosecond pulses. • Dual 1064-266/355 nm irradiation strongly damages a large variety of lichen species. • Calcium inside the lichen thallus prevents the damaging effect of laser irradiation. - Abstract: Laser irradiation of lichen thalli on heritage stones serves for the control of epilithic and endolithic biological colonizations. In this work we investigate rock samples from two quarries traditionally used as source of monumental stone, sandstone from Valonsadero (Soria, Spain) and granite from Alpedrete (Madrid, Spain), in order to find conditions for efficient laser removal of lichen thalli that ensure preservation of the lithic substrate. The samples presented superficial areas colonized by different types of crustose lichens, i.e. Candelariella vitellina, Aspicilia viridescens, Rhizocarpon disporum and Protoparmeliopsis muralis in Valonsadero samples and P. cf. bolcana and A. cf. contorta in Alpedrete samples. A comparative laser cleaning study was carried out on the mentioned samples with ns Q-switched Nd:YAG laser pulses of 1064 nm (fundamental radiation), 355 nm (3rd harmonic) and 266 nm (4th harmonic) and sequences of IR-UV pulses. A number of techniques such as UV-Vis absorption spectroscopy, stereomicroscopy, scanning electron microscopy (SEM) at low vacuum, SEM with backscattered electron imaging (SEM-BSE), electron dispersive spectroscopy (EDS) and FT-Raman spectroscopy were employed to determine the best laser irradiation conditions and to detect possible structural, morphological and chemical changes on the irradiated surfaces. The results show that the laser treatment does not lead to the complete removal of the studied lichen thalli, although clearly induces substantial damage, in the form of loss of the lichen upper cortex and damage to the algal layer. In the medium term these

  19. Influence of wavelength on the laser removal of lichens colonizing heritage stone

    Energy Technology Data Exchange (ETDEWEB)

    Sanz, M., E-mail: mikel.sanz@iqfr.csic.es [Instituto de Química Física Rocasolano (IQFR-CSIC), Serrano 119, 28006, Madrid (Spain); Oujja, M. [Instituto de Química Física Rocasolano (IQFR-CSIC), Serrano 119, 28006, Madrid (Spain); Ascaso, C. [Museo Nacional de Ciencias Naturales (MNCN-CSIC), José Gutiérrez Abascal 2, 28006, Madrid (Spain); Pérez-Ortega, S. [Real Jardín Botánico (RJB-CSIC), Plaza de Murillo 2, 28014, Madrid (Spain); Souza-Egipsy, V. [Instituto de Estructura de la Materia (IEM-CSIC), Serrano 121, 28006, Madrid (Spain); Fort, R. [Instituto de Geociencias (IGEO-CSIC, UCM), José Antonio Nováis 12, 28040, Madrid (Spain); Rios, A. de los; Wierzchos, J. [Museo Nacional de Ciencias Naturales (MNCN-CSIC), José Gutiérrez Abascal 2, 28006, Madrid (Spain); Cañamares, M.V. [Instituto de Estructura de la Materia (IEM-CSIC), Serrano 121, 28006, Madrid (Spain); Castillejo, M. [Instituto de Química Física Rocasolano (IQFR-CSIC), Serrano 119, 28006, Madrid (Spain)

    2017-03-31

    Highlights: • Optimal laser removal conditions depend on light absorption of lichen species. • Highly UV absorbing species (C. vitellina) removed by 266 nm nanosecond pulses. • Dual 1064-266/355 nm irradiation strongly damages a large variety of lichen species. • Calcium inside the lichen thallus prevents the damaging effect of laser irradiation. - Abstract: Laser irradiation of lichen thalli on heritage stones serves for the control of epilithic and endolithic biological colonizations. In this work we investigate rock samples from two quarries traditionally used as source of monumental stone, sandstone from Valonsadero (Soria, Spain) and granite from Alpedrete (Madrid, Spain), in order to find conditions for efficient laser removal of lichen thalli that ensure preservation of the lithic substrate. The samples presented superficial areas colonized by different types of crustose lichens, i.e. Candelariella vitellina, Aspicilia viridescens, Rhizocarpon disporum and Protoparmeliopsis muralis in Valonsadero samples and P. cf. bolcana and A. cf. contorta in Alpedrete samples. A comparative laser cleaning study was carried out on the mentioned samples with ns Q-switched Nd:YAG laser pulses of 1064 nm (fundamental radiation), 355 nm (3rd harmonic) and 266 nm (4th harmonic) and sequences of IR-UV pulses. A number of techniques such as UV-Vis absorption spectroscopy, stereomicroscopy, scanning electron microscopy (SEM) at low vacuum, SEM with backscattered electron imaging (SEM-BSE), electron dispersive spectroscopy (EDS) and FT-Raman spectroscopy were employed to determine the best laser irradiation conditions and to detect possible structural, morphological and chemical changes on the irradiated surfaces. The results show that the laser treatment does not lead to the complete removal of the studied lichen thalli, although clearly induces substantial damage, in the form of loss of the lichen upper cortex and damage to the algal layer. In the medium term these

  20. Development of chemically engineered porous metal oxides for phosphate removal

    International Nuclear Information System (INIS)

    Delaney, Paul; McManamon, Colm; Hanrahan, John P.; Copley, Mark P.; Holmes, Justin D.; Morris, Michael A.

    2011-01-01

    In this study, the application of ordered mesoporous silica (OMS) doped with various metal oxides (Zr, Ti, Fe and Al) were studied for the removal of (ortho) phosphate ions from water by adsorption. The materials were characterized by means of N 2 physisorption (BET), powder X-ray diffraction (PXRD) and transmission electron microscopy (TEM). The doped materials had surface areas between 600 and 700 m 2 g -1 and exhibited pore sizes of 44-64 A. Phosphate adsorption was determined by measurement of the aqueous concentration of orthophosphate using ultraviolet-visible (UV-vis) spectroscopy before and after extraction. The effects of different metal oxide loading ratios, initial concentration of phosphate solution, temperature and pH effects on the efficiency of phosphate removal were investigated. The doped mesoporous materials were effective adsorbents of orthophosphate and up to 100% removal was observed under appropriate conditions. 'Back extracting' the phosphate from the doped silica (following water treatment) was also investigated and shown to have little adverse effect on the adsorbent.

  1. A scanning electron microscopy study of root surface smear layer removal after topical application of EDTA plus a detergent

    OpenAIRE

    Sampaio, José Eduardo Cezar; Campos, Flávia Pavan; Pilatti, Gibson Luiz; Theodoro, Letícia Helena; Leite, Fábio Renato Manzolli

    2005-01-01

    The aim of the present study was to compare root surface smear layer removal following topical application of EDTA and EDTA-T (Texapon). Extracted human teeth had their cementum removed and were mechanically scaled. A total of 220 root specimens were obtained and were randomly assigned to the following groups: I-saline solution(control), II-EDTA; III-EDTAT. Groups II and III specimens were assigned to different EDTA gel concentrations: 5%, 10%, 15%, 20% and 24%. Smear layer removal score was ...

  2. A scanning electron microscopy study of root surface smear layer removal after topical application of EDTA plus a detergent

    OpenAIRE

    Sampaio,José Eduardo Cezar; Campos,Flávia Pavan; Pilatti,Gibson Luiz; Theodoro,Letícia Helena; Leite,Fábio Renato Manzolli

    2005-01-01

    The aim of the present study was to compare root surface smear layer removal following topical application of EDTA and EDTA-T (Texapon). Extracted human teeth had their cementum removed and were mechanically scaled. A total of 220 root specimens were obtained and were randomly assigned to the following groups: I-saline solution (control), II-EDTA; III-EDTA-T. Groups II and III specimens were assigned to different EDTA gel concentrations: 5%, 10%, 15%, 20% and 24%. Smear layer removal score wa...

  3. Implementation of a classifier didactical machine for learning mechatronic processes

    Directory of Open Access Journals (Sweden)

    Alex De La Cruz

    2017-06-01

    Full Text Available The present article shows the design and construction of a classifier didactical machine through artificial vision. The implementation of the machine is to be used as a learning module of mechatronic processes. In the project, it is described the theoretical aspects that relate concepts of mechanical design, electronic design and software management which constitute popular field in science and technology, which is mechatronics. The design of the machine was developed based on the requirements of the user, through the concurrent design methodology to define and materialize the appropriate hardware and software solutions. LabVIEW 2015 was implemented for high-speed image acquisition and analysis, as well as for the establishment of data communication with a programmable logic controller (PLC via Ethernet and an open communications platform known as Open Platform Communications - OPC. In addition, the Arduino MEGA 2560 platform was used to control the movement of the step motor and the servo motors of the module. Also, is used the Arduino MEGA 2560 to control the movement of the stepper motor and servo motors in the module. Finally, we assessed whether the equipment meets the technical specifications raised by running specific test protocols.

  4. Ensembles of novelty detection classifiers for structural health monitoring using guided waves

    Science.gov (United States)

    Dib, Gerges; Karpenko, Oleksii; Koricho, Ermias; Khomenko, Anton; Haq, Mahmoodul; Udpa, Lalita

    2018-01-01

    Guided wave structural health monitoring uses sparse sensor networks embedded in sophisticated structures for defect detection and characterization. The biggest challenge of those sensor networks is developing robust techniques for reliable damage detection under changing environmental and operating conditions (EOC). To address this challenge, we develop a novelty classifier for damage detection based on one class support vector machines. We identify appropriate features for damage detection and introduce a feature aggregation method which quadratically increases the number of available training observations. We adopt a two-level voting scheme by using an ensemble of classifiers and predictions. Each classifier is trained on a different segment of the guided wave signal, and each classifier makes an ensemble of predictions based on a single observation. Using this approach, the classifier can be trained using a small number of baseline signals. We study the performance using Monte-Carlo simulations of an analytical model and data from impact damage experiments on a glass fiber composite plate. We also demonstrate the classifier performance using two types of baseline signals: fixed and rolling baseline training set. The former requires prior knowledge of baseline signals from all EOC, while the latter does not and leverages the fact that EOC vary slowly over time and can be modeled as a Gaussian process.

  5. Source removal strategy development for manufactured gas plant sites

    International Nuclear Information System (INIS)

    Golchin, J.; Nelson, S.

    1994-01-01

    A source removal action plan was developed by Midwest Gas and the Iowa Department of Natural Resources to address the source coal tar contamination within the underground gas holder basin at former Manufactured Gas Plant (MGP) sites. The procedure utilizes a mixture of coal, contaminated soil and coal rat sludge to provide a material that had suitable material handling characteristics for shipment and burning in high efficiency utility boilers. Screening of the mixture was required to remove oversized debris and ferrous metal. The resulting mixture did not exhibit toxic characteristics when tested under the Toxicity Characteristics Leaching Procedure (TCLP). Test results on the coal tar sludges have indicated that the more pure coal tar materials may fail the TCLP test and be classified as a RCRA hazardous waste. The processing procedure was designed to stabilize the coal tar sludges and render those sludges less hazardous and, as a result, able to pass the TCLP test. This procedure was adopted by the Edison Electric Institute to develop a national guidance document for remediation of MGP sites. The EPA Office of Solid Waste and Emergency Response recommended this strategy to the Regional Waste Management Directors as a practical tool for handling wastes that may exhibit the RCRA characteristics

  6. Classifier for gravitational-wave inspiral signals in nonideal single-detector data

    Science.gov (United States)

    Kapadia, S. J.; Dent, T.; Dal Canton, T.

    2017-11-01

    We describe a multivariate classifier for candidate events in a templated search for gravitational-wave (GW) inspiral signals from neutron-star-black-hole (NS-BH) binaries, in data from ground-based detectors where sensitivity is limited by non-Gaussian noise transients. The standard signal-to-noise ratio (SNR) and chi-squared test for inspiral searches use only properties of a single matched filter at the time of an event; instead, we propose a classifier using features derived from a bank of inspiral templates around the time of each event, and also from a search using approximate sine-Gaussian templates. The classifier thus extracts additional information from strain data to discriminate inspiral signals from noise transients. We evaluate a random forest classifier on a set of single-detector events obtained from realistic simulated advanced LIGO data, using simulated NS-BH signals added to the data. The new classifier detects a factor of 1.5-2 more signals at low false positive rates as compared to the standard "reweighted SNR" statistic, and does not require the chi-squared test to be computed. Conversely, if only the SNR and chi-squared values of single-detector events are available, random forest classification performs nearly identically to the reweighted SNR.

  7. Box-Behnken experimental design for chromium(VI) ions removal by bacterial cellulose-magnetite composites.

    Science.gov (United States)

    Stoica-Guzun, Anicuta; Stroescu, Marta; Jinga, Sorin Ion; Mihalache, Nicoleta; Botez, Adriana; Matei, Cristian; Berger, Daniela; Damian, Celina Maria; Ionita, Valentin

    2016-10-01

    In this study bacterial cellulose-magnetite composites were synthesised for the removal of chromium(VI) from aqueous solutions. Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), thermogravimetric analysis and X-ray Photoelectron Spectroscopy (XPS) were used to characterize the bacterial cellulose-magnetite composites and to reveal the uniform dispersion of nanomagnetite in the BC matrix. Magnetic properties were also measured to confirm the magnetite immobilization on bacterial cellulose membrane. The effects of initial Cr(VI) concentration, solution pH and solid/liquid ratio upon chromium removal were examined using the statistical Box-Behnken Design. Because of the possibility of magnetite dissolution during chromium(VI) adsorption, the degree of iron leaching was also analysed in the same conditions as Cr(VI) adsorption. From the factors affecting chromium(VI) adsorption the most important was solution pH. The highest Cr(VI) removal efficiency was observed at pH 4, accompanied by the lowest iron leaching in the solution. The adsorption experiments also indicated that the adsorption process of chromium(VI) is well described by Freundlich adsorption model. Our results proved that the BC-magnetite composites could be used for an efficient removal of chromium(VI) from diluted solutions with a minimum magnetite dissolution during operation. Copyright © 2016 Elsevier B.V. All rights reserved.

  8. Scoring and Classifying Examinees Using Measurement Decision Theory

    Directory of Open Access Journals (Sweden)

    Lawrence M. Rudner

    2009-04-01

    Full Text Available This paper describes and evaluates the use of measurement decision theory (MDT to classify examinees based on their item response patterns. The model has a simple framework that starts with the conditional probabilities of examinees in each category or mastery state responding correctly to each item. The presented evaluation investigates: (1 the classification accuracy of tests scored using decision theory; (2 the effectiveness of different sequential testing procedures; and (3 the number of items needed to make a classification. A large percentage of examinees can be classified accurately with very few items using decision theory. A Java Applet for self instruction and software for generating, calibrating and scoring MDT data are provided.

  9. Classifier utility modeling and analysis of hypersonic inlet start/unstart considering training data costs

    Science.gov (United States)

    Chang, Juntao; Hu, Qinghua; Yu, Daren; Bao, Wen

    2011-11-01

    Start/unstart detection is one of the most important issues of hypersonic inlets and is also the foundation of protection control of scramjet. The inlet start/unstart detection can be attributed to a standard pattern classification problem, and the training sample costs have to be considered for the classifier modeling as the CFD numerical simulations and wind tunnel experiments of hypersonic inlets both cost time and money. To solve this problem, the CFD simulation of inlet is studied at first step, and the simulation results could provide the training data for pattern classification of hypersonic inlet start/unstart. Then the classifier modeling technology and maximum classifier utility theories are introduced to analyze the effect of training data cost on classifier utility. In conclusion, it is useful to introduce support vector machine algorithms to acquire the classifier model of hypersonic inlet start/unstart, and the minimum total cost of hypersonic inlet start/unstart classifier can be obtained by the maximum classifier utility theories.

  10. Hollow Electron Beam Collimation For HL-LHC - Effect On The Beam Core

    CERN Document Server

    Fitterer, M; Valishev, A; Bruce, R; Papadopoulou, S; Papotti, G; Pellegrini, D; Redaelli, S; Valuch, D; Wagner, J F

    2017-01-01

    Collimation with hollow electron beams or lenses (HEL) is currently one of the most promising concepts for active halo control in HL-LHC. In previous studies it has been shown that the halo can be efficiently removed with a hollow electron lens. Equally important as an efficient removal of the halo, is also to demonstrate that the core stays unperturbed. In this paper, we present a summary of the experiment at the LHC and simulations in view of the effect of the HEL on the beam core in case of a pulsed operation.

  11. Feature selection for Bayesian network classifiers using the MDL-FS score

    NARCIS (Netherlands)

    Drugan, Madalina M.; Wiering, Marco A.

    When constructing a Bayesian network classifier from data, the more or less redundant features included in a dataset may bias the classifier and as a consequence may result in a relatively poor classification accuracy. In this paper, we study the problem of selecting appropriate subsets of features

  12. Comparing cosmic web classifiers using information theory

    Energy Technology Data Exchange (ETDEWEB)

    Leclercq, Florent [Institute of Cosmology and Gravitation (ICG), University of Portsmouth, Dennis Sciama Building, Burnaby Road, Portsmouth PO1 3FX (United Kingdom); Lavaux, Guilhem; Wandelt, Benjamin [Institut d' Astrophysique de Paris (IAP), UMR 7095, CNRS – UPMC Université Paris 6, Sorbonne Universités, 98bis boulevard Arago, F-75014 Paris (France); Jasche, Jens, E-mail: florent.leclercq@polytechnique.org, E-mail: lavaux@iap.fr, E-mail: j.jasche@tum.de, E-mail: wandelt@iap.fr [Excellence Cluster Universe, Technische Universität München, Boltzmannstrasse 2, D-85748 Garching (Germany)

    2016-08-01

    We introduce a decision scheme for optimally choosing a classifier, which segments the cosmic web into different structure types (voids, sheets, filaments, and clusters). Our framework, based on information theory, accounts for the design aims of different classes of possible applications: (i) parameter inference, (ii) model selection, and (iii) prediction of new observations. As an illustration, we use cosmographic maps of web-types in the Sloan Digital Sky Survey to assess the relative performance of the classifiers T-WEB, DIVA and ORIGAMI for: (i) analyzing the morphology of the cosmic web, (ii) discriminating dark energy models, and (iii) predicting galaxy colors. Our study substantiates a data-supported connection between cosmic web analysis and information theory, and paves the path towards principled design of analysis procedures for the next generation of galaxy surveys. We have made the cosmic web maps, galaxy catalog, and analysis scripts used in this work publicly available.

  13. Comparing cosmic web classifiers using information theory

    International Nuclear Information System (INIS)

    Leclercq, Florent; Lavaux, Guilhem; Wandelt, Benjamin; Jasche, Jens

    2016-01-01

    We introduce a decision scheme for optimally choosing a classifier, which segments the cosmic web into different structure types (voids, sheets, filaments, and clusters). Our framework, based on information theory, accounts for the design aims of different classes of possible applications: (i) parameter inference, (ii) model selection, and (iii) prediction of new observations. As an illustration, we use cosmographic maps of web-types in the Sloan Digital Sky Survey to assess the relative performance of the classifiers T-WEB, DIVA and ORIGAMI for: (i) analyzing the morphology of the cosmic web, (ii) discriminating dark energy models, and (iii) predicting galaxy colors. Our study substantiates a data-supported connection between cosmic web analysis and information theory, and paves the path towards principled design of analysis procedures for the next generation of galaxy surveys. We have made the cosmic web maps, galaxy catalog, and analysis scripts used in this work publicly available.

  14. Selenate removal in methanogenic and sulfate-reducing upflow anaerobic sludge bed reactors

    NARCIS (Netherlands)

    Lenz, M.; Hullebusch, van E.D.; Hommes, G.; Corvini, P.F.X.; Lens, P.N.L.

    2008-01-01

    This paper evaluates the use of upflow anaerobic sludge bed (UASB) bioreactors (30 degrees C, pH = 7.0) to remove selenium oxyanions from contaminated waters (790 mu g Se L-1) under methanogenic and sulfate-reducing conditions using lactate as electron donor. One UASB reactor received sulfate at

  15. The removal of sulphate from mine water by precipitation as ettringite and the utilisation of the precipitate as a sorbent for arsenate removal.

    Science.gov (United States)

    Tolonen, Emma-Tuulia; Hu, Tao; Rämö, Jaakko; Lassi, Ulla

    2016-10-01

    The aim of this research was to investigate sulphate removal from mine water by precipitation as ettringite (Ca6Al2(SO4)3(OH)12·26H2O) and the utilisation of the precipitate as a sorbent for arsenate removal. The mine water sulphate concentration was reduced by 85-90% from the initial 1400 mg/L during ettringite precipitation depending on the treatment method. The precipitation conditions were also simulated with MINEQL + software, and the computational results were compared with the experimental results. The precipitated solids were characterised with X-ray diffraction and a scanning electron microscope. The precipitated solids were tested as sorbents for arsenate removal from the model solution. The arsenic(V) model solution concentration reduced 86-96% from the initial 1.5 mg/L with a 1 g/L sorbent dosage. The effect of initial arsenate concentration on the sorption of arsenate on the precipitate was studied and Langmuir, Freundlich, and Langmuir-Freundlich sorption isotherm models were fitted to the experimental data. The maximum arsenate sorption capacity (qm = 11.2 ± 4.7 mg/g) of the precipitate was obtained from the Langmuir-Freundlich isotherm. The results indicate that the precipitate produced during sulphate removal from mine water by precipitation as ettringite could be further used as a sorbent for arsenate removal. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. Classifier-Guided Sampling for Complex Energy System Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Backlund, Peter B. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Eddy, John P. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

    2015-09-01

    This report documents the results of a Laboratory Directed Research and Development (LDRD) effort enti tled "Classifier - Guided Sampling for Complex Energy System Optimization" that was conducted during FY 2014 and FY 2015. The goal of this proj ect was to develop, implement, and test major improvements to the classifier - guided sampling (CGS) algorithm. CGS is type of evolutionary algorithm for perform ing search and optimization over a set of discrete design variables in the face of one or more objective functions. E xisting evolutionary algorithms, such as genetic algorithms , may require a large number of o bjecti ve function evaluations to identify optimal or near - optimal solutions . Reducing the number of evaluations can result in significant time savings, especially if the objective function is computationally expensive. CGS reduce s the evaluation count by us ing a Bayesian network classifier to filter out non - promising candidate designs , prior to evaluation, based on their posterior probabilit ies . In this project, b oth the single - objective and multi - objective version s of the CGS are developed and tested on a set of benchm ark problems. As a domain - specific case study, CGS is used to design a microgrid for use in islanded mode during an extended bulk power grid outage.

  17. 77 FR 22760 - Proposed Information Collection; Comment Request; Southeast Region Gulf of Mexico Electronic...

    Science.gov (United States)

    2012-04-17

    ... electronic logbook memory chip will be removed from the unit and downloaded at the contractor site in College Station, Texas. A new logbook memory chip will replace the removed memory chip, a process taking less than...

  18. Empirical study of classification process for two-stage turbo air classifier in series

    Science.gov (United States)

    Yu, Yuan; Liu, Jiaxiang; Li, Gang

    2013-05-01

    The suitable process parameters for a two-stage turbo air classifier are important for obtaining the ultrafine powder that has a narrow particle-size distribution, however little has been published internationally on the classification process for the two-stage turbo air classifier in series. The influence of the process parameters of a two-stage turbo air classifier in series on classification performance is empirically studied by using aluminum oxide powders as the experimental material. The experimental results show the following: 1) When the rotor cage rotary speed of the first-stage classifier is increased from 2 300 r/min to 2 500 r/min with a constant rotor cage rotary speed of the second-stage classifier, classification precision is increased from 0.64 to 0.67. However, in this case, the final ultrafine powder yield is decreased from 79% to 74%, which means the classification precision and the final ultrafine powder yield can be regulated through adjusting the rotor cage rotary speed of the first-stage classifier. 2) When the rotor cage rotary speed of the second-stage classifier is increased from 2 500 r/min to 3 100 r/min with a constant rotor cage rotary speed of the first-stage classifier, the cut size is decreased from 13.16 μm to 8.76 μm, which means the cut size of the ultrafine powder can be regulated through adjusting the rotor cage rotary speed of the second-stage classifier. 3) When the feeding speed is increased from 35 kg/h to 50 kg/h, the "fish-hook" effect is strengthened, which makes the ultrafine powder yield decrease. 4) To weaken the "fish-hook" effect, the equalization of the two-stage wind speeds or the combination of a high first-stage wind speed with a low second-stage wind speed should be selected. This empirical study provides a criterion of process parameter configurations for a two-stage or multi-stage classifier in series, which offers a theoretical basis for practical production.

  19. Arsenic removal in water by means of coagulation-flocculation processes

    International Nuclear Information System (INIS)

    Franco, M. F.; Carro P, M. E.

    2014-01-01

    Arsenic and arsenical compounds are considered as carcinogenic and risky for humans according to epidemiological evidence related with the ingestion of arsenical water during a long period. In many places the only source of drinking water contains arsenic and, therefore, removal strategies have to be investigated. This work shows experimental results of coagulation-flocculation processes implemented to evaluate the efficiency in the removal of arsenic from drinking water. The main objectives include the evaluation of the relevant aspect that controls the removal efficiency. Experimental tests were performed with coagulant concentrations from 5 to 500 mg/L, solid particle concentrations from 0 to 6000 mg/L, and initial arsenic concentrations from 0.5 to 5 mg/L. These variables were simultaneously varied in more than 100 experiments. The efficiency in remediation ranged from 0% to 95%. Removal efficiency near 95% was obtained when using ferric chloride as coagulant, and was close to 80% when using aluminium sulfate as coagulant in arsenate solutions. The remediation efficiency decreased significantly when the ferric chloride concentration was higher than 50 mg/L in relation to the obtained results for aluminum sulfate for different type and concentration of soil particles. The highest removal efficiency were obtained at ph between 3 and 5 in oxidized solutions. Obtained results simulated by means of multiple linear regression analysis (R>0.90) allow determining that the main parameters that control the removal of arsenic from drinking water are coagulant concentration, ph, and solid particles concentration. Conversely, particle mineralogy and coagulant type have less significant effect on the removal by means of coagulation-flocculation mechanisms. Obtained results are relevant for the removal of As in water treatment plants as well as for the development of small scale filters. The samples were studied by scanning electron microscopy and energy dispersive X

  20. Integrated bio-oxidation and adsorptive filtration reactor for removal of arsenic from wastewater.

    Science.gov (United States)

    Kamde, Kalyani; Dahake, Rashmi; Pandey, R A; Bansiwal, Amit

    2018-01-08

    Recently, removal of arsenic from different industrial effluent discharged using simple, efficient and low-cost technique has been widely considered. In this study, removal of arsenic (As) from real wastewater has been studied employing modified bio-oxidation followed by adsorptive filtration method in a novel continuous flow through the reactor. This method includes biological oxidation of ferrous to ferric ions by immobilized Acidothiobacillus ferrooxidans bacteria on granulated activated carbon (GAC) in fixed bed bio-column reactor with the adsorptive filtration unit. Removal efficiency was optimized regarding the initial flow rate of media and ferrous ions concentration. Synthetic wastewater sample having different heavy metal ions such as Arsenic (As), Cobalt (Co), Chromium (Cr), Copper (Cu), Iron (Fe), Lead (Pb) and Manganese (Mn) were also used in the study. The structural and surface changes occurring after the treatment process were scrutinized using FT-IR and Scanning Electron Microscopy (SEM) analysis. The finding showed that not only arsenic can be removed considerably in the bioreactor system, but also removing efficiency was much more (oxidation with adsorptive filtration method improves the removal efficiency of arsenic and other heavy metal ions in wastewater sample.

  1. Case base classification on digital mammograms: improving the performance of case base classifier

    Science.gov (United States)

    Raman, Valliappan; Then, H. H.; Sumari, Putra; Venkatesa Mohan, N.

    2011-10-01

    Breast cancer continues to be a significant public health problem in the world. Early detection is the key for improving breast cancer prognosis. The aim of the research presented here is in twofold. First stage of research involves machine learning techniques, which segments and extracts features from the mass of digital mammograms. Second level is on problem solving approach which includes classification of mass by performance based case base classifier. In this paper we build a case-based Classifier in order to diagnose mammographic images. We explain different methods and behaviors that have been added to the classifier to improve the performance of the classifier. Currently the initial Performance base Classifier with Bagging is proposed in the paper and it's been implemented and it shows an improvement in specificity and sensitivity.

  2. Novelty Detection Classifiers in Weed Mapping: Silybum marianum Detection on UAV Multispectral Images.

    Science.gov (United States)

    Alexandridis, Thomas K; Tamouridou, Afroditi Alexandra; Pantazi, Xanthoula Eirini; Lagopodi, Anastasia L; Kashefi, Javid; Ovakoglou, Georgios; Polychronos, Vassilios; Moshou, Dimitrios

    2017-09-01

    In the present study, the detection and mapping of Silybum marianum (L.) Gaertn. weed using novelty detection classifiers is reported. A multispectral camera (green-red-NIR) on board a fixed wing unmanned aerial vehicle (UAV) was employed for obtaining high-resolution images. Four novelty detection classifiers were used to identify S. marianum between other vegetation in a field. The classifiers were One Class Support Vector Machine (OC-SVM), One Class Self-Organizing Maps (OC-SOM), Autoencoders and One Class Principal Component Analysis (OC-PCA). As input features to the novelty detection classifiers, the three spectral bands and texture were used. The S. marianum identification accuracy using OC-SVM reached an overall accuracy of 96%. The results show the feasibility of effective S. marianum mapping by means of novelty detection classifiers acting on multispectral UAV imagery.

  3. Nonlinear electron-phonon heat exchange

    International Nuclear Information System (INIS)

    Woods, L.M.; Mahan, G.D.

    1998-01-01

    A calculation of the energy exchange between phonons and electrons is done for a metal at very low temperatures. We consider the energy exchange due to two-phonon processes. Second-order processes are expected to be important at temperatures less than 1 K. We include two different second-order processes: (i) the Compton-like scattering of phonons, and (ii) the electron-dual-phonon scattering from the second-order electron-phonon interaction. It is found that the Compton-like process contains a singular energy denominator. The singularity is removed by introducing quasiparticle damping. For pure metals we find that the energy exchange depends upon the lifetime of the electrons and it is proportional to the temperature of the lattice as T L 8 . The same calculation is performed for the electron-dual-phonon scattering and it is found that the temperature dependence is T L 9 . The results can be applied to quantum dot refrigerators. copyright 1998 The American Physical Society

  4. Adsorptive removal of selected pharmaceuticals by mesoporous silica SBA-15

    International Nuclear Information System (INIS)

    Bui, Tung Xuan; Choi, Heechul

    2009-01-01

    The removal of five selected pharmaceuticals, viz., carbamazepine, clofibric acid, diclofenac, ibuprofen, and ketoprofen was examined by batch sorption experiments onto a synthesized mesoporous silica SBA-15. SBA-15 was synthesized and characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), N 2 adsorption-desorption measurement, and point of zero charge (PZC) measurement. Pharmaceutical adsorption kinetics was rapid and occurred on a scale of minutes, following a pseudo-second-order rate expression. Adsorption isotherms were best fitted by the Freundlich isotherm model. High removal rates of individual pharmaceuticals were achieved in acidic media (pH 3-5) and reached 85.2% for carbamazepine, 88.3% for diclofenac, 93.0% for ibuprofen, 94.3% for ketoprofen, and 49.0% for clofibric acid at pH 3 but decreased with increase in pH. SBA-15 also showed high efficiency for removal of a mixture of 5 pharmaceuticals. Except for clofibric acid (35.6%), the removal of pharmaceuticals in the mixture ranged from 75.2 to 89.3%. Based on adsorption and desorption results, the mechanism of the selected pharmaceuticals was found to be a hydrophilic interaction, providing valuable information for further studies to design materials for the purpose. The results of this study suggest that mesoporous-silica-based materials are promising adsorbents for removing pharmaceuticals from not only surface water but also wastewater of pharmaceutical industrial manufactures.

  5. Adsorptive removal of selected pharmaceuticals by mesoporous silica SBA-15

    Energy Technology Data Exchange (ETDEWEB)

    Bui, Tung Xuan, E-mail: bxtung@gist.ac.kr [Department of Environmental Science and Engineering, Gwangju Institute of Science and Technology (GIST), 261 Cheomdan-gwagiro, Buk-gu, Gwangju 500-712 (Korea, Republic of); Choi, Heechul, E-mail: hcchoi@gist.ac.kr [Department of Environmental Science and Engineering, Gwangju Institute of Science and Technology (GIST), 261 Cheomdan-gwagiro, Buk-gu, Gwangju 500-712 (Korea, Republic of)

    2009-09-15

    The removal of five selected pharmaceuticals, viz., carbamazepine, clofibric acid, diclofenac, ibuprofen, and ketoprofen was examined by batch sorption experiments onto a synthesized mesoporous silica SBA-15. SBA-15 was synthesized and characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), N{sub 2} adsorption-desorption measurement, and point of zero charge (PZC) measurement. Pharmaceutical adsorption kinetics was rapid and occurred on a scale of minutes, following a pseudo-second-order rate expression. Adsorption isotherms were best fitted by the Freundlich isotherm model. High removal rates of individual pharmaceuticals were achieved in acidic media (pH 3-5) and reached 85.2% for carbamazepine, 88.3% for diclofenac, 93.0% for ibuprofen, 94.3% for ketoprofen, and 49.0% for clofibric acid at pH 3 but decreased with increase in pH. SBA-15 also showed high efficiency for removal of a mixture of 5 pharmaceuticals. Except for clofibric acid (35.6%), the removal of pharmaceuticals in the mixture ranged from 75.2 to 89.3%. Based on adsorption and desorption results, the mechanism of the selected pharmaceuticals was found to be a hydrophilic interaction, providing valuable information for further studies to design materials for the purpose. The results of this study suggest that mesoporous-silica-based materials are promising adsorbents for removing pharmaceuticals from not only surface water but also wastewater of pharmaceutical industrial manufactures.

  6. Application of electron beam irradiation. 4. Treatment of pollutants by electron beam irradiation

    International Nuclear Information System (INIS)

    Tokunaga, Okihiro; Arai, Hidehiko

    1994-01-01

    Electron beam irradiation is capable of dissolving and removing pollutants, such as sulfur oxides, nitrogen oxides, and organic compounds, by easy production of OH radicals in flue gas and water. This paper deals with current status in the search for techniques for treating flue gas and waste water, using electron beam irradiation. Pilot tests have been conducted during the period 1991-1994 for the treatment of flue gas caused by coal and garbage burning and road tunnels. Firstly, techniques for cleaning flue gas with electron beams are outlined, with special reference to their characteristics and process of research development. Secondly, the application of electron beam irradiation in the treatment of waste water is described in terms of the following: (1) disinfection of sewage, (2) cleaning of water polluted with toxic organic compounds, (3) treatment for eliminating sewage sludge, (4) promotion of sewage sludge sedimentation, (5) disinfection and composting of sewage sludge, and (6) regeneration of activated carbon used for the treatment of waste water. (N.K.)

  7. Magnetic removal of Entamoeba cysts from water using chitosan oligosaccharide-coated iron oxide nanoparticles

    Directory of Open Access Journals (Sweden)

    Shukla S

    2015-07-01

    Full Text Available Sudeep Shukla,1 Vikas Arora,2 Alka Jadaun,3 Jitender Kumar,1 Nishant Singh,1 Vinod Kumar Jain1 1School of Environmental Sciences, Jawaharlal Nehru University, New Delhi, Delhi, India; 2Department of Chemistry, Indian Institute of Technology, New Delhi, Delhi, India; 3School of Biotechnology, Jawaharlal Nehru University, New Delhi, Delhi, India Abstract: Amebiasis, a major health problem in developing countries, is the second most common cause of death due to parasitic infection. Amebiasis is usually transmitted by the ingestion of Entamoeba histolytica cysts through oral–fecal route. Herein, we report on the use of chitosan oligosaccharide-functionalized iron oxide nanoparticles for efficient capture and removal of pathogenic protozoan cysts under the influence of an external magnetic field. These nanoparticles were synthesized through a chemical synthesis process. The synthesized particles were characterized by transmission electron microscopy, Fourier transform infrared spectroscopy, X-ray diffraction, and zeta potential analysis. The particles were found to be well dispersed and uniform in size. The capture and removal of pathogenic cysts were demonstrated by fluorescent microscopy, transmission electron microscopy, and scanning electron microscopy (SEM. Three-dimensional modeling of various biochemical components of cyst walls, and thereafter, flexible docking studies demonstrate the probable interaction mechanism of nanoparticles with various components of E. histolytica cyst walls. Results of the present study suggest that E. histolytica cysts can be efficiently captured and removed from contaminated aqueous systems through the application of synthesized nanoparticles. Keywords: amebiasis, water treatment, nanotechnology

  8. Variants of the Borda count method for combining ranked classifier hypotheses

    NARCIS (Netherlands)

    van Erp, Merijn; Schomaker, Lambert; Schomaker, Lambert; Vuurpijl, Louis

    2000-01-01

    The Borda count is a simple yet effective method of combining rankings. In pattern recognition, classifiers are often able to return a ranked set of results. Several experiments have been conducted to test the ability of the Borda count and two variant methods to combine these ranked classifier

  9. Should OCD be classified as an anxiety disorder in DSM-V?

    NARCIS (Netherlands)

    Stein, Dan J.; Fineberg, Naomi A.; Bienvenu, O. Joseph; Denys, Damiaan; Lochner, Christine; Nestadt, Gerald; Leckman, James F.; Rauch, Scott L.; Phillips, Katharine A.

    2010-01-01

    In DSM-III, DSM-III-R, and DSM-IV, obsessive-compulsive disorder (OCD) was classified as an anxiety disorder. In ICD-10, OCD is classified separately from the anxiety disorders, although within the same larger category as anxiety disorders (as one of the "neurotic, stress-related, and somatoform

  10. 29 CFR 1910.307 - Hazardous (classified) locations.

    Science.gov (United States)

    2010-07-01

    ... equipment at the location. (c) Electrical installations. Equipment, wiring methods, and installations of... covers the requirements for electric equipment and wiring in locations that are classified depending on... provisions of this section. (4) Division and zone classification. In Class I locations, an installation must...

  11. Improved classification of Alzheimer's disease data via removal of nuisance variability.

    Directory of Open Access Journals (Sweden)

    Juha Koikkalainen

    Full Text Available Diagnosis of Alzheimer's disease is based on the results of neuropsychological tests and available supporting biomarkers such as the results of imaging studies. The results of the tests and the values of biomarkers are dependent on the nuisance features, such as age and gender. In order to improve diagnostic power, the effects of the nuisance features have to be removed from the data. In this paper, four types of interactions between classification features and nuisance features were identified. Three methods were tested to remove these interactions from the classification data. In stratified analysis, a homogeneous subgroup was generated from a training set. Data correction method utilized linear regression model to remove the effects of nuisance features from data. The third method was a combination of these two methods. The methods were tested using all the baseline data from the Alzheimer's Disease Neuroimaging Initiative database in two classification studies: classifying control subjects from Alzheimer's disease patients and discriminating stable and progressive mild cognitive impairment subjects. The results show that both stratified analysis and data correction are able to statistically significantly improve the classification accuracy of several neuropsychological tests and imaging biomarkers. The improvements were especially large for the classification of stable and progressive mild cognitive impairment subjects, where the best improvements observed were 6% units. The data correction method gave better results for imaging biomarkers, whereas stratified analysis worked well with the neuropsychological tests. In conclusion, the study shows that the excess variability caused by nuisance features should be removed from the data to improve the classification accuracy, and therefore, the reliability of diagnosis making.

  12. Parameterization of a fuzzy classifier for the diagnosis of an industrial process

    International Nuclear Information System (INIS)

    Toscano, R.; Lyonnet, P.

    2002-01-01

    The aim of this paper is to present a classifier based on a fuzzy inference system. For this classifier, we propose a parameterization method, which is not necessarily based on an iterative training. This approach can be seen as a pre-parameterization, which allows the determination of the rules base and the parameters of the membership functions. We also present a continuous and derivable version of the previous classifier and suggest an iterative learning algorithm based on a gradient method. An example using the learning basis IRIS, which is a benchmark for classification problems, is presented showing the performances of this classifier. Finally this classifier is applied to the diagnosis of a DC motor showing the utility of this method. However in many cases the total knowledge necessary to the synthesis of the fuzzy diagnosis system (FDS) is not, in general, directly available. It must be extracted from an often-considerable mass of information. For this reason, a general methodology for the design of a FDS is presented and illustrated on a non-linear plant

  13. An SVM classifier to separate false signals from microcalcifications in digital mammograms

    Energy Technology Data Exchange (ETDEWEB)

    Bazzani, Armando; Bollini, Dante; Brancaccio, Rosa; Campanini, Renato; Riccardi, Alessandro; Romani, Davide [Department of Physics, University of Bologna (Italy); INFN, Bologna (Italy); Lanconelli, Nico [Department of Physics, University of Bologna, and INFN, Bologna (Italy). E-mail: nico.lanconelli@bo.infn.it; Bevilacqua, Alessandro [Department of Electronics, Computer Science and Systems, University of Bologna, and INFN, Bologna (Italy)

    2001-06-01

    In this paper we investigate the feasibility of using an SVM (support vector machine) classifier in our automatic system for the detection of clustered microcalcifications in digital mammograms. SVM is a technique for pattern recognition which relies on the statistical learning theory. It minimizes a function of two terms: the number of misclassified vectors of the training set and a term regarding the generalization classifier capability. We compare the SVM classifier with an MLP (multi-layer perceptron) in the false-positive reduction phase of our detection scheme: a detected signal is considered either microcalcification or false signal, according to the value of a set of its features. The SVM classifier gets slightly better results than the MLP one (Az value of 0.963 against 0.958) in the presence of a high number of training data; the improvement becomes much more evident (Az value of 0.952 against 0.918) in training sets of reduced size. Finally, the setting of the SVM classifier is much easier than the MLP one. (author)

  14. Synergistic Cytotoxicity from Drugs and Cytokines In Vitro as an Approach to Classify Drugs According to Their Potential to Cause Idiosyncratic Hepatotoxicity: A Proof-of-Concept Study.

    Science.gov (United States)

    Maiuri, Ashley R; Wassink, Bronlyn; Turkus, Jonathan D; Breier, Anna B; Lansdell, Theresa; Kaur, Gurpreet; Hession, Sarah L; Ganey, Patricia E; Roth, Robert A

    2017-09-01

    Idiosyncratic drug-induced liver injury (IDILI) typically occurs in a small fraction of patients and has resulted in removal of otherwise efficacious drugs from the market. Current preclinical testing methods are ineffective in predicting which drug candidates have IDILI liability. Recent results suggest that immune mediators such as tumor necrosis factor- α (TNF) and interferon- γ (IFN) interact with drugs that cause IDILI to kill hepatocytes. This proof-of-concept study was designed to test the hypothesis that drugs can be classified according to their ability to cause IDILI in humans using classification modeling with covariates derived from concentration-response relationships that describe cytotoxic interaction with cytokines. Human hepatoma (HepG2) cells were treated with drugs associated with IDILI or with drugs lacking IDILI liability and cotreated with TNF and/or IFN. Detailed concentration-response relationships were determined for calculation of parameters such as the maximal cytotoxic effect, slope, and EC 50 for use as covariates for classification modeling using logistic regression. These parameters were incorporated into multiple classification models to identify combinations of covariates that most accurately classified the drugs according to their association with human IDILI. Of 14 drugs associated with IDILI, almost all synergized with TNF to kill HepG2 cells and were successfully classified by statistical modeling. IFN enhanced the toxicity mediated by some IDILI-associated drugs in the presence of TNF. In contrast, of 10 drugs with little or no IDILI liability, none synergized with inflammatory cytokines to kill HepG2 cells and were classified accordingly. The resulting optimal model classified the drugs with extraordinary selectivity and specificity. Copyright © 2017 by The American Society for Pharmacology and Experimental Therapeutics.

  15. Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies

    Science.gov (United States)

    Theis, Fabian J.

    2017-01-01

    Epidemiological studies often utilize stratified data in which rare outcomes or exposures are artificially enriched. This design can increase precision in association tests but distorts predictions when applying classifiers on nonstratified data. Several methods correct for this so-called sample selection bias, but their performance remains unclear especially for machine learning classifiers. With an emphasis on two-phase case-control studies, we aim to assess which corrections to perform in which setting and to obtain methods suitable for machine learning techniques, especially the random forest. We propose two new resampling-based methods to resemble the original data and covariance structure: stochastic inverse-probability oversampling and parametric inverse-probability bagging. We compare all techniques for the random forest and other classifiers, both theoretically and on simulated and real data. Empirical results show that the random forest profits from only the parametric inverse-probability bagging proposed by us. For other classifiers, correction is mostly advantageous, and methods perform uniformly. We discuss consequences of inappropriate distribution assumptions and reason for different behaviors between the random forest and other classifiers. In conclusion, we provide guidance for choosing correction methods when training classifiers on biased samples. For random forests, our method outperforms state-of-the-art procedures if distribution assumptions are roughly fulfilled. We provide our implementation in the R package sambia. PMID:29312464

  16. Removal of pharmaceutical and personal care products (PPCPs) under nitrifying and denitrifying conditions.

    Science.gov (United States)

    Suarez, Sonia; Lema, Juan M; Omil, Francisco

    2010-05-01

    The contribution of volatilization, sorption and transformation to the removal of 16 Pharmaceutical and Personal Care Products (PPCPs) in two lab-scale conventional activated sludge reactors, working under nitrifying (aerobic) and denitrifying (anoxic) conditions for more than 1.5 years, have been assessed. Pseudo-first order biological degradation rate constants (k(biol)) were calculated for the selected compounds in both reactors. Faster degradation kinetics were measured in the nitrifying reactor compared to the denitrifying system for the majority of PPCPs. Compounds could be classified according to their k(biol) into very highly (k(biol)>5Lg(SS)(-1)d(-1)), highly (1fragrances (HHCB, AHTN and ADBI) were transformed to a large extent under aerobic (>75%) and anoxic (>65%) conditions, whereas naproxen (NPX), ethinylestradiol (EE2), roxithromycin (ROX) and erythromycin (ERY) were only significantly transformed in the aerobic reactor (>80%). The anti-depressant citalopram (CTL) was moderately biotransformed under both, aerobic and anoxic conditions (>60% and >40%, respectively). Some compounds, as carbamazepine (CBZ), diazepam (DZP), sulfamethoxazole (SMX) and trimethoprim (TMP), manifested high resistance to biological transformation. Solids Retention Time (SRT(aerobic) >50d and 20d and <20d) had a slightly positive effect on the removal of FLX, NPX, CTL, EE2 and natural estrogens (increase in removal efficiencies <10%). Removal of diclofenac (DCF) in the aerobic reactor was positively affected by the development of nitrifying biomass and increased from 0% up to 74%. Similarly, efficient anoxic transformation of ibuprofen (75%) was observed after an adaptation period of 340d. Temperature (16-26 degrees C) only had a slight effect on the removal of CTL which increased in 4%.

  17. Learning for VMM + WTA Embedded Classifiers

    Science.gov (United States)

    2016-03-31

    Learning for VMM + WTA Embedded Classifiers Jennifer Hasler and Sahil Shah Electrical and Computer Engineering Georgia Institute of Technology...enabling correct classification of each novel acoustic signal (generator, idle car, and idle truck ). The classification structure requires, after...measured on our SoC FPAA IC. The test input is composed of signals from urban environment for 3 objects (generator, idle car, and idle truck

  18. A Comparative Scanning Electron Microscopy Evaluation of Smear ...

    African Journals Online (AJOL)

    2018-02-07

    Feb 7, 2018 ... scanning electron microscopy evaluation of smear layer removal with chitosan and .... this compound has considerably increased its concentration in rivers and .... of the images was done by three investigators who calibrated ...

  19. 75 FR 707 - Classified National Security Information

    Science.gov (United States)

    2010-01-05

    ... classified at one of the following three levels: (1) ``Top Secret'' shall be applied to information, the... exercise this authority. (2) ``Top Secret'' original classification authority may be delegated only by the... official has been delegated ``Top Secret'' original classification authority by the agency head. (4) Each...

  20. A distributed approach for optimizing cascaded classifier topologies in real-time stream mining systems.

    Science.gov (United States)

    Foo, Brian; van der Schaar, Mihaela

    2010-11-01

    In this paper, we discuss distributed optimization techniques for configuring classifiers in a real-time, informationally-distributed stream mining system. Due to the large volume of streaming data, stream mining systems must often cope with overload, which can lead to poor performance and intolerable processing delay for real-time applications. Furthermore, optimizing over an entire system of classifiers is a difficult task since changing the filtering process at one classifier can impact both the feature values of data arriving at classifiers further downstream and thus, the classification performance achieved by an ensemble of classifiers, as well as the end-to-end processing delay. To address this problem, this paper makes three main contributions: 1) Based on classification and queuing theoretic models, we propose a utility metric that captures both the performance and the delay of a binary filtering classifier system. 2) We introduce a low-complexity framework for estimating the system utility by observing, estimating, and/or exchanging parameters between the inter-related classifiers deployed across the system. 3) We provide distributed algorithms to reconfigure the system, and analyze the algorithms based on their convergence properties, optimality, information exchange overhead, and rate of adaptation to non-stationary data sources. We provide results using different video classifier systems.

  1. The three-dimensional origin of the classifying algebra

    International Nuclear Information System (INIS)

    Fuchs, Juergen; Schweigert, Christoph; Stigner, Carl

    2010-01-01

    It is known that reflection coefficients for bulk fields of a rational conformal field theory in the presence of an elementary boundary condition can be obtained as representation matrices of irreducible representations of the classifying algebra, a semisimple commutative associative complex algebra. We show how this algebra arises naturally from the three-dimensional geometry of factorization of correlators of bulk fields on the disk. This allows us to derive explicit expressions for the structure constants of the classifying algebra as invariants of ribbon graphs in the three-manifold S 2 xS 1 . Our result unravels a precise relation between intertwiners of the action of the mapping class group on spaces of conformal blocks and boundary conditions in rational conformal field theories.

  2. Novel thermally stable poly(vinyl chloride) composites for sulfate removal

    Energy Technology Data Exchange (ETDEWEB)

    Nadagouda, Mallikarjuna N., E-mail: Nadagouda.mallikarjuna@epa.gov [Water Supply and Water Resources Division, National Risk Management Research Laboratory U.S. Environmental Protection Agency, 26 W. Martin Luther King Drive Cincinnati, Ohio 45268 (United States); Pressman, Jonathan; White, Colin; Speth, Thomas F.; McCurry, Daniel L. [Water Supply and Water Resources Division, National Risk Management Research Laboratory U.S. Environmental Protection Agency, 26 W. Martin Luther King Drive Cincinnati, Ohio 45268 (United States)

    2011-04-15

    Graphical abstract: Barium carbonate and/or barium carbonate-loaded silica aero-gels dispersed polyvinyl chloride (PVC) composites were prepared by dissolving PVC in tetrahydrofuran (THF), dispersing BaCO{sub 3} and/or BaCO{sub 3}-loaded silica aero-gels, re-precipitating the PVC with water at room temperature. The PVC composites were then characterized using scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray mapping, X-ray diffraction (XRD), thermogravimetric analysis (TGA) and inductively coupled plasma mass spectrometry (ICP-MS) analysis. The obtained composites had better thermal properties than the control PVC. The composites were tested for sulfate removal and found to significantly reduce sulfate when compared with control PVC. - Abstract: BaCO{sub 3} dispersed PVC composites were prepared through a polymer re-precipitation method. The composites were tested for sulfate removal using rapid small scale column test (RSSCT) and found to significantly reduce sulfate concentration. The method was extended to synthesize barium carbonate-loaded silica aero-gels-polyvinyl chloride (PVC) polymer composites. The PVC composites were characterized using scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray mapping, X-ray diffraction (XRD), thermogravimetric analysis (TGA) and inductively coupled plasma mass spectrometry (ICP-MS) analysis. The method has advantages over conventional sulfate precipitation (sulfate removal process) using BaCO{sub 3} wherein clogging of the filter can be avoided. The method is environmentally friendly and does not interfere with natural organic matter as the conventional resin does. Some of the composites were thermally more stable as compared with the pure PVC discussed in the literature.

  3. Novel thermally stable poly(vinyl chloride) composites for sulfate removal

    International Nuclear Information System (INIS)

    Nadagouda, Mallikarjuna N.; Pressman, Jonathan; White, Colin; Speth, Thomas F.; McCurry, Daniel L.

    2011-01-01

    Graphical abstract: Barium carbonate and/or barium carbonate-loaded silica aero-gels dispersed polyvinyl chloride (PVC) composites were prepared by dissolving PVC in tetrahydrofuran (THF), dispersing BaCO 3 and/or BaCO 3 -loaded silica aero-gels, re-precipitating the PVC with water at room temperature. The PVC composites were then characterized using scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray mapping, X-ray diffraction (XRD), thermogravimetric analysis (TGA) and inductively coupled plasma mass spectrometry (ICP-MS) analysis. The obtained composites had better thermal properties than the control PVC. The composites were tested for sulfate removal and found to significantly reduce sulfate when compared with control PVC. - Abstract: BaCO 3 dispersed PVC composites were prepared through a polymer re-precipitation method. The composites were tested for sulfate removal using rapid small scale column test (RSSCT) and found to significantly reduce sulfate concentration. The method was extended to synthesize barium carbonate-loaded silica aero-gels-polyvinyl chloride (PVC) polymer composites. The PVC composites were characterized using scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray mapping, X-ray diffraction (XRD), thermogravimetric analysis (TGA) and inductively coupled plasma mass spectrometry (ICP-MS) analysis. The method has advantages over conventional sulfate precipitation (sulfate removal process) using BaCO 3 wherein clogging of the filter can be avoided. The method is environmentally friendly and does not interfere with natural organic matter as the conventional resin does. Some of the composites were thermally more stable as compared with the pure PVC discussed in the literature.

  4. Removal of chlorinated organic compounds from gas phase using electron beam technology

    Energy Technology Data Exchange (ETDEWEB)

    Sun, Y.; Bulka, S.; Zimek, A. [Institute of Nuclear Chemistry and Technology, Warsaw (Poland); Chmielewski, A. G. [Institute of Nuclear Chemistry and Technology, Warsaw (Poland); Faculty of Chemical and Process Engineering, Warsaw University of Technology, Warsaw (Poland)

    2011-07-01

    Selected chlorinated organic compounds (Cl-HC), which are emitted from coal fired power plants, waste incinerators, chemical industry etc., are very harmful to the environment and human’s health. Some of them are listed as carcinogenic compounds by USA EPA. Recent studies show that some chlorinated organic compounds are suspected to be precursors for dioxins formation. Chlorinated organic compounds decomposition in air in an electron beam (EB) generated plasma reactor technology was studied. We selected cis-dichloroethylene (cis-DCE), 1,4-dichlorobenznene(1,4-DCB), 1-chloronaphthalene as studied objects. It is found that chlorinated organic compounds can be decomposed in an electron beam generated plasma reactor. The order of decomposition efficiency of these compounds are: cis-DCE > 1,4-DCB> 1-chloronaphthalene. (author)

  5. Electron beam treatment of industrial wastewater

    International Nuclear Information System (INIS)

    Han, Bumsoo; Kim, JinKyu; Kim, Yuri

    2004-01-01

    For industrial wastewater with low impurity levels such as contaminated ground water, cleaning water and etc., purification only with electron beam is possible, but it should be managed carefully with reducing required irradiation doses as low as possible. Also for industrial wastewater with high impurity levels such as dyeing wastewater, leachate and etc., purification only with electron beam requires high amount of doses and far beyond economies. Electron beam treatment combined with conventional purification methods such as coagulation, biological treatment, etc. is suitable for reduction of non-biodegradable impurities in wastewater and will extend the application area of electron beam. A pilot plant with electron beam for treating 1,000 m 3 /day of wastewater from dyeing industries has constructed and operated continuously since Oct 1998. Electron beam irradiation instead of chemical treatment shows much improvement in removing impurities and increases the efficiency of biological treatment. Actual plant is under consideration based upon the experimental results. (author)

  6. Potential application of electron accelerators in Malaysia

    Energy Technology Data Exchange (ETDEWEB)

    Alang Md Rashid, Nahrul Khair; Mohd Dahlan, Khairul Zaman [Nuclear Energy Unit, Bangi, Selangor (Malaysia)

    1994-12-31

    Briefly discussed some applications of electron accelerators i.e. sterilization, pasteurization (high energy EBM - up to 10 MV), crosslinking of wire and cable and insulation (medium energy EBM - 1 to 5 MV), treatment of flue gases for removal of NO sub x and SO sub x from burning coal(low energy EBM - 700 to 900 kV), curing of surface coatings, printing ink, adhesives (low energy EBM - 200 to 500 kV); advantages and electron beam processing.

  7. Potential application of electron accelerators in Malaysia

    International Nuclear Information System (INIS)

    Nahrul Khair Alang Md Rashid; Khairul Zaman Mohd Dahlan

    1994-01-01

    Briefly discussed some applications of electron accelerators i.e. sterilization, pasteurization (high energy EBM - up to 10 MV), crosslinking of wire and cable and insulation (medium energy EBM - 1 to 5 MV), treatment of flue gases for removal of NO sub x and SO sub x from burning coal(low energy EBM - 700 to 900 kV), curing of surface coatings, printing ink, adhesives (low energy EBM - 200 to 500 kV); advantages and electron beam processing

  8. Introduction to the theory of low-energy electron diffraction

    International Nuclear Information System (INIS)

    Fingerland, A.; Tomasek, M.

    1975-01-01

    An elementary introduction to the basic principles of the theory of low-energy electron diffraction is presented. General scattering theory is used to classify the hitherto known approaches to the problem (optical potential and one-electron approximation; formal scattering theory: Born expansion and multiple scattering; translational symmetry: Ewald construction; classification of LEED theories by means of the T matrix; pseudokinematical theory for crystal with clean surface and with an adsorbed monomolecular layer; dynamical theory; inclusion of inelastic collisions; discussion of a simple example by means of the band-structure approach)

  9. 77 FR 73455 - Transportation Workers Identification Card (TWIC) Removal for Commercial Users To Access...

    Science.gov (United States)

    2012-12-10

    ... Manager at [email protected]us.army.mil . References: Department of Defense Instruction number 8520.2... DEPARTMENT OF DEFENSE Department of the Army Transportation Workers Identification Card (TWIC) Removal for Commercial Users To Access Electronic Transportation Acquisition (ETA) AGENCY: Department of...

  10. Removal of pesticides from white and red wines by microfiltration

    Energy Technology Data Exchange (ETDEWEB)

    Doulia, Danae S., E-mail: ntoulia@mail.ntua.gr [Laboratory of Organic Chemical Technology, School of Chemical Engineering, National Technical University of Athens, Zografou Campus, 9 Iroon Politechniou, GR-15780 Athens (Greece); Anagnos, Efstathios K. [Laboratory of Organic Chemical Technology, School of Chemical Engineering, National Technical University of Athens, Zografou Campus, 9 Iroon Politechniou, GR-15780 Athens (Greece); Liapis, Konstantinos S. [Pesticide Residue Laboratory, Benaki Phytopathological Institute, 7 Ekalis Str., Kiphissia, Athens GR-14561 (Greece); Klimentzos, Demetrios A. [Laboratory of Organic Chemical Technology, School of Chemical Engineering, National Technical University of Athens, Zografou Campus, 9 Iroon Politechniou, GR-15780 Athens (Greece)

    2016-11-05

    Highlights: • Various mixtures of 23 pesticides were determined by SPE and GC-ECD in wine. • The removal of pesticides is affected by the type of membrane and wine. • The higher the pesticide’s hydrophobicity, the higher its removal. • Antagonistic and synergistic effects of pesticides in wines were estimated. - Abstract: The aim of this work is the investigation of microfiltration in removing pesticides from a white and a red Greek wine. Six membranes with pore size 0.45 μm were investigated. Two mixtures of 23 and 9 pesticides, and single pesticide solutions were added in the wine. The pesticides tested belong to 11 chemical groups. Solid phase extraction (SPE) followed by gas chromatography (GC) with electron capture detector (ECD) were performed to analyze pesticide residues of the filtered fortified wine. Distinct behavior was exhibited by each membrane. Cellulose acetate and cellulose nitrate showed higher mean pesticide removal for both wines, followed by polyethersulfone, regenerated cellulose, and polyamides. The filtration effectiveness was correlated to the membrane type and to the pesticide chemical structure and properties (octanol-water partition coefficient, water solubility) and compared for the wines tested. In most cases, the more hydrophobic pesticides (pyrethroids and aldrin) showed higher removal from red wine than white wine. Adsorption on membranes was increased by increasing hydrophobicity and decreasing hydrophilicity of organic pesticide molecule. The removal of each pesticide from its single solution was generally higher than that from its mixtures, allowing the estimation of the antagonistic and synergistic effects of pesticides in the mixtures.

  11. Removal of pesticides from white and red wines by microfiltration

    International Nuclear Information System (INIS)

    Doulia, Danae S.; Anagnos, Efstathios K.; Liapis, Konstantinos S.; Klimentzos, Demetrios A.

    2016-01-01

    Highlights: • Various mixtures of 23 pesticides were determined by SPE and GC-ECD in wine. • The removal of pesticides is affected by the type of membrane and wine. • The higher the pesticide’s hydrophobicity, the higher its removal. • Antagonistic and synergistic effects of pesticides in wines were estimated. - Abstract: The aim of this work is the investigation of microfiltration in removing pesticides from a white and a red Greek wine. Six membranes with pore size 0.45 μm were investigated. Two mixtures of 23 and 9 pesticides, and single pesticide solutions were added in the wine. The pesticides tested belong to 11 chemical groups. Solid phase extraction (SPE) followed by gas chromatography (GC) with electron capture detector (ECD) were performed to analyze pesticide residues of the filtered fortified wine. Distinct behavior was exhibited by each membrane. Cellulose acetate and cellulose nitrate showed higher mean pesticide removal for both wines, followed by polyethersulfone, regenerated cellulose, and polyamides. The filtration effectiveness was correlated to the membrane type and to the pesticide chemical structure and properties (octanol-water partition coefficient, water solubility) and compared for the wines tested. In most cases, the more hydrophobic pesticides (pyrethroids and aldrin) showed higher removal from red wine than white wine. Adsorption on membranes was increased by increasing hydrophobicity and decreasing hydrophilicity of organic pesticide molecule. The removal of each pesticide from its single solution was generally higher than that from its mixtures, allowing the estimation of the antagonistic and synergistic effects of pesticides in the mixtures.

  12. Electron Beam Technology for Environmental Pollution Control.

    Science.gov (United States)

    Chmielewski, Andrzej G; Han, Bumsoo

    2016-10-01

    Worldwide, there are over 1700 electron beam (EB) units in commercial use, providing an estimated added value to numerous products, amounting to 100 billion USD or more. High-current electron accelerators are used in diverse industries to enhance the physical and chemical properties of materials and to reduce undesirable contaminants such as pathogens, toxic byproducts, or emissions. Over the past few decades, EB technologies have been developed aimed at ensuring the safety of gaseous and liquid effluents discharged to the environment. It has been demonstrated that EB technologies for flue gas treatment (SO x and NO x removal), wastewater purification, and sludge hygienization can be effectively deployed to mitigate environmental degradation. Recently, extensive work has been carried out on the use of EB for environmental remediation, which also includes the removal of emerging contaminants such as VOCs, endocrine disrupting chemicals (EDCs), and potential EDCs.

  13. 75 FR 37253 - Classified National Security Information

    Science.gov (United States)

    2010-06-28

    ... ``Secret.'' (3) Each interior page of a classified document shall be marked at the top and bottom either... ``(TS)'' for Top Secret, ``(S)'' for Secret, and ``(C)'' for Confidential will be used. (2) Portions... from the informational text. (1) Conspicuously place the overall classification at the top and bottom...

  14. Classifying cognitive profiles using machine learning with privileged information in Mild Cognitive Impairment

    Directory of Open Access Journals (Sweden)

    Hanin Hamdan Alahmadi

    2016-11-01

    Full Text Available Early diagnosis of dementia is critical for assessing disease progression and potential treatment. State-or-the-art machine learning techniques have been increasingly employed to take on this diagnostic task. In this study, we employed Generalised Matrix Learning Vector Quantization (GMLVQ classifiers to discriminate patients with Mild Cognitive Impairment (MCI from healthy controls based on their cognitive skills. Further, we adopted a ``Learning with privileged information'' approach to combine cognitive and fMRI data for the classification task. The resulting classifier operates solely on the cognitive data while it incorporates the fMRI data as privileged information (PI during training. This novel classifier is of practical use as the collection of brain imaging data is not always possible with patients and older participants.MCI patients and healthy age-matched controls were trained to extract structure from temporal sequences. We ask whether machine learning classifiers can be used to discriminate patients from controls based on the learning performance and whether differences between these groups relate to individual cognitive profiles. To this end, we tested participants in four cognitive tasks: working memory, cognitive inhibition, divided attention, and selective attention. We also collected fMRI data before and after training on the learning task and extracted fMRI responses and connectivity as features for machine learning classifiers. Our results show that the PI guided GMLVQ classifiers outperform the baseline classifier that only used the cognitive data. In addition, we found that for the baseline classifier, divided attention is the only relevant cognitive feature. When PI was incorporated, divided attention remained the most relevant feature while cognitive inhibition became also relevant for the task. Interestingly, this analysis for the fMRI GMLVQ classifier suggests that (1 when overall fMRI signal for structured stimuli is

  15. Study on decomposition and removal of organic pollutants in gases using electron beams

    International Nuclear Information System (INIS)

    Hakoda, Teruyuki

    2006-01-01

    Volatile organic compounds (VOC) used as solvents and de-oil reagents have been emitted to the atmosphere and oxidized subsequently into toxic photochemical oxidants in the atmosphere. Reduction of the emission of VOC has been required under law and regulations for factories/plants at which huge amounts of VOC are used. The electron beam (EB) treatment is suitable for purification of high flow-rate ventilation air containing dilute VOC emitted from such factories/plants. The purification processes of such ventilation air have been developed based on the decomposition reactions and property changes of VOC. The results for chloro-ethylenes and aromatic hydrocarbons, which have been emitted with abundant quantities, are introduced in the present paper. Chloroethylenes, except for monochloroethylene, were oxidized into water-soluble primary products through chain reactions in EB irradiated humid air. The chain oxidation reactions of such chloro-ethylenes were initiated exclusively by a reaction with OH radicals, but electron-attachment dissociation under EB irradiation. Gas-phase termination reactions involved the bimolecular reaction of alkylperoxyl radicals for tri- and di-chloroethylenes, and the reaction of alkylperoxyl radicals and alkyl radicals beside such a bimolecular reaction for tetrachloroethylene. The deposition of the alkyl-peroxyl radicals on an irradiation vessel wall also terminated the chain oxidation reactions. The solid-phase termination reaction was negligible to the gas-phase termination reactions under irradiation with high-dose rate so that the oxidation of chloro-ethylenes was achieved with lower doses under high-dose rate irradiation like EB irradiation. The hydrolysis of the primary products combined with EB irradiation is prospective to be applied to the purification of chloroethylenes/air mixtures with lower doses. Under irradiation of aromatic hydrocarbons/air mixtures, toxic and oxidation-resistant particles with mean diameters of a few

  16. Probing the electronic structure of redox species and direct determination of intrinsic reorganization energies of electron transfer reactions

    International Nuclear Information System (INIS)

    Wang, Xue-Bin; Wang, Lai-Sheng

    2000-01-01

    An experimental technique capable of directly determining the intrinsic reorganization energies of bimolecular electron transfer reactions is described. Appropriate solution phase redox species are prepared in the gas phase using electrospray ionization and probed using photodetachment spectroscopy. Five metal complex anions involved in the Fe 2+ -Fe 3+ redox couple are investigated and the intramolecular reorganization energies are measured directly from spectral features due to removing the most loosely bound 3d electron from the Fe(II)-complexes. The photodetachment spectra also yield electronic structure information about the Fe 2+ -Fe 3+ redox couple and provide a common electronic structure origin for the reducing capability of the Fe(II)-complexes, the most common redox reagents. (c) 2000 American Institute of Physics

  17. Analysis of patient setup accuracy using electronic portal imaging device

    International Nuclear Information System (INIS)

    Onogi, Yuzo; Aoki, Yukimasa; Nakagawa, Keiichi

    1996-01-01

    Radiation therapy is performed in many fractions, and accurate patient setup is very important. This is more significant nowadays because treatment planning and radiation therapy are more precisely performed. Electronic portal imaging devices and automatic image comparison algorithms let us analyze setup deviations quantitatively. With such in mind we developed a simple image comparison algorithm. Using 2459 electronic verification images (335 ports, 123 treatment sites) generated during the past three years at our institute, we evaluated the results of the algorithm, and analyzed setup deviations according to the area irradiated, use of a fixing device (shell), and arm position. Calculated setup deviation was verified visually and their fitness was classified into good, fair, bad, and incomplete. The result was 40%, 14%, 22%, 24% respectively. Using calculated deviations classified as good (994 images), we analyzed setup deviations. Overall setup deviations described in 1 SD along axes x, y, z, was 1.9 mm, 2.5 mm, 1.7 mm respectively. We classified these deviations into systematic and random components, and found that random error was predominant in our institute. The setup deviations along axis y (cranio-caudal direction) showed larger distribution when treatment was performed with the shell. Deviations along y (cranio-caudal) and z (anterior-posterior) had larger distribution when treatment occurred with the patient's arm elevated. There was a significant time-trend error, whose deviations become greater with time. Within all evaluated ports, 30% showed a time-trend error. Using an electronic portal imaging device and automatic image comparison algorithm, we are able to analyze setup deviations more precisely and improve setup method based on objective criteria. (author)

  18. Characteristics of a cold cathode electron source combined with secondary electron emission in a FED

    International Nuclear Information System (INIS)

    Lei Wei; Zhang Xiaobing; Zhou Xuedong; Zhu Zuoya; Lou Chaogang; Zhao Hongping

    2005-01-01

    In electron beam devices, the voltage applied to the cathode (w.r.t. grid voltage) provides the initial energy for the electrons. Based on the type of electron emission, the electron sources are (mainly) classified into thermionic cathodes and cold cathodes. The power consumption of a cold cathode is smaller than that of a thermionic cathode. The delay time of the electron emission from a cold cathode following the voltage rise is also smaller. In cathode ray tubes, field emission display (=FED) panels and other devices, the electron current emitted from the cathode needs to be modulated. Since the strong electric field, which is required to extract electrons from the cold cathode, accelerates the electrons to a high velocity near the gate electrode, the required voltage swing for the current modulation is also high. The design of the driving circuit becomes quite difficult and expensive for a high driving voltage. In this paper, an insulator plate with holes is placed in front of a cold cathode. When the primary electrons hit the surface of the insulator tunnels, secondary electrons are generated. In this paper, the characteristics of the secondary electrons emitted from the gate structure are studied. Because the energies of the secondary electrons are smaller than that of the primary electron, the driving voltage for the current modulation is decreased by the introduction of the insulator tunnels, resulting in an improved energy uniformity of the electron beam. Triode structures with inclined insulator tunnels and with double insulator plates are also fabricated and lead to further improvements in the energy uniformity. The improved energy uniformity predicted by the simulation calculations is demonstrated by the improved brightness uniformity in the screen display images

  19. A Novel Cascade Classifier for Automatic Microcalcification Detection.

    Directory of Open Access Journals (Sweden)

    Seung Yeon Shin

    Full Text Available In this paper, we present a novel cascaded classification framework for automatic detection of individual and clusters of microcalcifications (μC. Our framework comprises three classification stages: i a random forest (RF classifier for simple features capturing the second order local structure of individual μCs, where non-μC pixels in the target mammogram are efficiently eliminated; ii a more complex discriminative restricted Boltzmann machine (DRBM classifier for μC candidates determined in the RF stage, which automatically learns the detailed morphology of μC appearances for improved discriminative power; and iii a detector to detect clusters of μCs from the individual μC detection results, using two different criteria. From the two-stage RF-DRBM classifier, we are able to distinguish μCs using explicitly computed features, as well as learn implicit features that are able to further discriminate between confusing cases. Experimental evaluation is conducted on the original Mammographic Image Analysis Society (MIAS and mini-MIAS databases, as well as our own Seoul National University Bundang Hospital digital mammographic database. It is shown that the proposed method outperforms comparable methods in terms of receiver operating characteristic (ROC and precision-recall curves for detection of individual μCs and free-response receiver operating characteristic (FROC curve for detection of clustered μCs.

  20. Effect of Gamma and Electron Beam Irradiation on Textile Waste Water

    International Nuclear Information System (INIS)

    Selambakkannu, S.; Khomsaton Abu Bakar; Ting, T.M.

    2011-01-01

    In this studies gamma and electron beam irradiation was used to treat textile waste water. Comparisons between both types of irradiation in terms of effectiveness to degrade the pollutants present in textile waste water was done. Prior to irradiation, the raw wastewater was diluted using distilled water to a target concentration of COD 400 mg/l. The sample was irradiated at selected doses between the ranges of 10 kGy to 100 kGy. The results showed that irradiation has significantly contributed in the reduction of the highly colored refractory organic pollutants. The COD removal at the lowest dose, 10 kGy, was reduced to 390 mg/l for gamma and 400 mg/l for electron beam. Meanwhile, at the highest dose, 100 kGy, the COD was reduced to 125 mg/l for gamma and 144 mg/l for electron beam. The degree of removal is influenced by the dose introduced during the treatment process. As the dose increased, the higher the removal of organic pollutant was recorded. However, gamma irradiation is more effective although the differences are not significant between gamma and electron beam irradiation. On the other hand, other properties of the wastewater such as pH, turbidity, suspended solid, BOD and color also shows a gradual decrease as the dose increases for both types of irradiation. (author)

  1. Feature weighting using particle swarm optimization for learning vector quantization classifier

    Science.gov (United States)

    Dongoran, A.; Rahmadani, S.; Zarlis, M.; Zakarias

    2018-03-01

    This paper discusses and proposes a method of feature weighting in classification assignments on competitive learning artificial neural network LVQ. The weighting feature method is the search for the weight of an attribute using the PSO so as to give effect to the resulting output. This method is then applied to the LVQ-Classifier and tested on the 3 datasets obtained from the UCI Machine Learning repository. Then an accuracy analysis will be generated by two approaches. The first approach using LVQ1, referred to as LVQ-Classifier and the second approach referred to as PSOFW-LVQ, is a proposed model. The result shows that the PSO algorithm is capable of finding attribute weights that increase LVQ-classifier accuracy.

  2. Ammonia removal in electrochemical oxidation: Mechanism and pseudo-kinetics

    International Nuclear Information System (INIS)

    Li Liang; Liu Yan

    2009-01-01

    This paper investigated the mechanism and pseudo-kinetics for removal of ammonia by electrochemical oxidation with RuO 2 /Ti anode using batch tests. The results show that the ammonia oxidation rates resulted from direct oxidation at electrode-liquid interfaces of the anode by stepwise dehydrogenation, and from indirect oxidation by hydroxyl radicals were so slow that their contribution to ammonia removal was negligible under the condition with Cl - . The oxidation rates of ammonia ranged from 1.0 to 12.3 mg N L -1 h -1 and efficiency reached nearly 100%, primarily due to the indirect oxidation of HOCl, and followed pseudo zero-order kinetics in electrochemical oxidation with Cl - . About 88% ammonia was removed from the solution. The removed one was subsequently found in the form of N 2 in the produced gas. The rate at which Cl - lost electrons at the anode was a major factor in the overall ammonia oxidation. Current density and Cl - concentration affected the constant of the pseudo zero-order kinetics, expressed by k = 0.0024[Cl - ] x j. The ammonia was reduced to less than 0.5 mg N L -1 after 2 h of electrochemical oxidation for the effluent from aerobic or anaerobic reactors which treated municipal wastewater. This result was in line with the strict discharge requirements

  3. Accuracy Evaluation of C4.5 and Naive Bayes Classifiers Using Attribute Ranking Method

    Directory of Open Access Journals (Sweden)

    S. Sivakumari

    2009-03-01

    Full Text Available This paper intends to classify the Ljubljana Breast Cancer dataset using C4.5 Decision Tree and Nai?ve Bayes classifiers. In this work, classification is carriedout using two methods. In the first method, dataset is analysed using all the attributes in the dataset. In the second method, attributes are ranked using information gain ranking technique and only the high ranked attributes are used to build the classification model. We are evaluating the results of C4.5 Decision Tree and Nai?ve Bayes classifiers in terms of classifier accuracy for various folds of cross validation. Our results show that both the classifiers achieve good accuracy on the dataset.

  4. A Constrained Multi-Objective Learning Algorithm for Feed-Forward Neural Network Classifiers

    Directory of Open Access Journals (Sweden)

    M. Njah

    2017-06-01

    Full Text Available This paper proposes a new approach to address the optimal design of a Feed-forward Neural Network (FNN based classifier. The originality of the proposed methodology, called CMOA, lie in the use of a new constraint handling technique based on a self-adaptive penalty procedure in order to direct the entire search effort towards finding only Pareto optimal solutions that are acceptable. Neurons and connections of the FNN Classifier are dynamically built during the learning process. The approach includes differential evolution to create new individuals and then keeps only the non-dominated ones as the basis for the next generation. The designed FNN Classifier is applied to six binary classification benchmark problems, obtained from the UCI repository, and results indicated the advantages of the proposed approach over other existing multi-objective evolutionary neural networks classifiers reported recently in the literature.

  5. 40 CFR 260.32 - Variances to be classified as a boiler.

    Science.gov (United States)

    2010-07-01

    ... 40 Protection of Environment 25 2010-07-01 2010-07-01 false Variances to be classified as a boiler... be classified as a boiler. In accordance with the standards and criteria in § 260.10 (definition of “boiler”), and the procedures in § 260.33, the Administrator may determine on a case-by-case basis that...

  6. A Machine Learning Ensemble Classifier for Early Prediction of Diabetic Retinopathy.

    Science.gov (United States)

    S K, Somasundaram; P, Alli

    2017-11-09

    The main complication of diabetes is Diabetic retinopathy (DR), retinal vascular disease and it leads to the blindness. Regular screening for early DR disease detection is considered as an intensive labor and resource oriented task. Therefore, automatic detection of DR diseases is performed only by using the computational technique is the great solution. An automatic method is more reliable to determine the presence of an abnormality in Fundus images (FI) but, the classification process is poorly performed. Recently, few research works have been designed for analyzing texture discrimination capacity in FI to distinguish the healthy images. However, the feature extraction (FE) process was not performed well, due to the high dimensionality. Therefore, to identify retinal features for DR disease diagnosis and early detection using Machine Learning and Ensemble Classification method, called, Machine Learning Bagging Ensemble Classifier (ML-BEC) is designed. The ML-BEC method comprises of two stages. The first stage in ML-BEC method comprises extraction of the candidate objects from Retinal Images (RI). The candidate objects or the features for DR disease diagnosis include blood vessels, optic nerve, neural tissue, neuroretinal rim, optic disc size, thickness and variance. These features are initially extracted by applying Machine Learning technique called, t-distributed Stochastic Neighbor Embedding (t-SNE). Besides, t-SNE generates a probability distribution across high-dimensional images where the images are separated into similar and dissimilar pairs. Then, t-SNE describes a similar probability distribution across the points in the low-dimensional map. This lessens the Kullback-Leibler divergence among two distributions regarding the locations of the points on the map. The second stage comprises of application of ensemble classifiers to the extracted features for providing accurate analysis of digital FI using machine learning. In this stage, an automatic detection

  7. Local curvature analysis for classifying breast tumors: Preliminary analysis in dedicated breast CT

    International Nuclear Information System (INIS)

    Lee, Juhun; Nishikawa, Robert M.; Reiser, Ingrid; Boone, John M.; Lindfors, Karen K.

    2015-01-01

    Purpose: The purpose of this study is to measure the effectiveness of local curvature measures as novel image features for classifying breast tumors. Methods: A total of 119 breast lesions from 104 noncontrast dedicated breast computed tomography images of women were used in this study. Volumetric segmentation was done using a seed-based segmentation algorithm and then a triangulated surface was extracted from the resulting segmentation. Total, mean, and Gaussian curvatures were then computed. Normalized curvatures were used as classification features. In addition, traditional image features were also extracted and a forward feature selection scheme was used to select the optimal feature set. Logistic regression was used as a classifier and leave-one-out cross-validation was utilized to evaluate the classification performances of the features. The area under the receiver operating characteristic curve (AUC, area under curve) was used as a figure of merit. Results: Among curvature measures, the normalized total curvature (C_T) showed the best classification performance (AUC of 0.74), while the others showed no classification power individually. Five traditional image features (two shape, two margin, and one texture descriptors) were selected via the feature selection scheme and its resulting classifier achieved an AUC of 0.83. Among those five features, the radial gradient index (RGI), which is a margin descriptor, showed the best classification performance (AUC of 0.73). A classifier combining RGI and C_T yielded an AUC of 0.81, which showed similar performance (i.e., no statistically significant difference) to the classifier with the above five traditional image features. Additional comparisons in AUC values between classifiers using different combinations of traditional image features and C_T were conducted. The results showed that C_T was able to replace the other four image features for the classification task. Conclusions: The normalized curvature measure

  8. Reducing false positives of microcalcification detection systems by removal of breast arterial calcifications.

    Science.gov (United States)

    Mordang, Jan-Jurre; Gubern-Mérida, Albert; den Heeten, Gerard; Karssemeijer, Nico

    2016-04-01

    In the past decades, computer-aided detection (CADe) systems have been developed to aid screening radiologists in the detection of malignant microcalcifications. These systems are useful to avoid perceptual oversights and can increase the radiologists' detection rate. However, due to the high number of false positives marked by these CADe systems, they are not yet suitable as an independent reader. Breast arterial calcifications (BACs) are one of the most frequent false positives marked by CADe systems. In this study, a method is proposed for the elimination of BACs as positive findings. Removal of these false positives will increase the performance of the CADe system in finding malignant microcalcifications. A multistage method is proposed for the removal of BAC findings. The first stage consists of a microcalcification candidate selection, segmentation and grouping of the microcalcifications, and classification to remove obvious false positives. In the second stage, a case-based selection is applied where cases are selected which contain BACs. In the final stage, BACs are removed from the selected cases. The BACs removal stage consists of a GentleBoost classifier trained on microcalcification features describing their shape, topology, and texture. Additionally, novel features are introduced to discriminate BACs from other positive findings. The CADe system was evaluated with and without BACs removal. Here, both systems were applied on a validation set containing 1088 cases of which 95 cases contained malignant microcalcifications. After bootstrapping, free-response receiver operating characteristics and receiver operating characteristics analyses were carried out. Performance between the two systems was compared at 0.98 and 0.95 specificity. At a specificity of 0.98, the sensitivity increased from 37% to 52% and the sensitivity increased from 62% up to 76% at a specificity of 0.95. Partial areas under the curve in the specificity range of 0.8-1.0 were

  9. CLEARING OF ELECTRON CLOUD IN SNS

    International Nuclear Information System (INIS)

    WANG, L.; LEE, Y.Y.; RAPRIA, D.

    2004-01-01

    In this paper we describe a mechanism using the clearing electrodes to remove the electron cloud in the Spallation Neutron Source (SNS) accumulator ring, where strong multipacting could happen at median clearing fields. A similar phenomenon was reported in an experimental study at Los Alamos laboratory's Proton Synchrotron Ring (PSR). We also investigated the effectiveness of the solenoid's clearing mechanism in the SNS, which differs from the short bunch case, such as in B-factories. The titanium nitride (TiN) coating of the chamber walls was applied to reduce the secondary electron yield (SEY)

  10. How large a training set is needed to develop a classifier for microarray data?

    Science.gov (United States)

    Dobbin, Kevin K; Zhao, Yingdong; Simon, Richard M

    2008-01-01

    A common goal of gene expression microarray studies is the development of a classifier that can be used to divide patients into groups with different prognoses, or with different expected responses to a therapy. These types of classifiers are developed on a training set, which is the set of samples used to train a classifier. The question of how many samples are needed in the training set to produce a good classifier from high-dimensional microarray data is challenging. We present a model-based approach to determining the sample size required to adequately train a classifier. It is shown that sample size can be determined from three quantities: standardized fold change, class prevalence, and number of genes or features on the arrays. Numerous examples and important experimental design issues are discussed. The method is adapted to address ex post facto determination of whether the size of a training set used to develop a classifier was adequate. An interactive web site for performing the sample size calculations is provided. We showed that sample size calculations for classifier development from high-dimensional microarray data are feasible, discussed numerous important considerations, and presented examples.

  11. Attribute measurement equipment for the verification of plutonium in classified forms for the Trilateral Initiative

    International Nuclear Information System (INIS)

    Langner, D.G.; Hsue, S.-T.; Macarthur, D.W.

    2001-01-01

    of these storage containers, together with the requirement to validate the equipment with unclassified reference materials, have led to the design requirement that the attribute measurement equipment must be large and state-of-the-art. The experts also have determined that simultaneous measurement of attributes is desirable to reduce the amount of classified information that resides in the system at any time. This adds further complexity to the system. Certain ancillary equipment has been proposed to provide additional confidence in a Trilateral Initiative verification approach. In situ probes and a simulation/ authentication tool have been proposed and are under development. In situ probes are simple gross radiation measurement devices that could be used to provide confidence that an item placed in a storage position has remained in storage. The authentication tool is an electronic pulse simulator that mimics the output of a radiation measurement device. With this tool, an inspector can exercise a system that has an information barrier that is independent of host-controlled reference materials. This tool has also been identified as potentially being very useful in training inspectors, in exercising electronics packages, and in applying safeguards as well. Two working prototypes of an attribute measurement system with an information barrier have been fabricated and demonstrated in the United States, and the Russian Federation has begun preliminary design work for a system that could be built in Russia. This paper will also describe these systems and give-the status of current activities. (author)

  12. Three-dimensional machining of carbon nanotube forests using water-assisted scanning electron microscope processing

    Energy Technology Data Exchange (ETDEWEB)

    Rajabifar, Bahram; Maschmann, Matthew R., E-mail: MaschmannM@missouri.edu [Department of Mechanical and Aerospace Engineering, University of Missouri, Columbia, Missouri 65211 (United States); Kim, Sanha; Hart, A. John [Department of Mechanical Engineering and Laboratory for Manufacturing and Productivity, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Slinker, Keith [Materials and Manufacturing Directorate, AFRL/RX, Air Force Research Lab, Ohio 45433 (United States); Universal Technology Corporation, Beavercreek, Ohio 45424 (United States); Ehlert, Gregory J. [Materials and Manufacturing Directorate, AFRL/RX, Air Force Research Lab, Ohio 45433 (United States)

    2015-10-05

    We demonstrate that vertically aligned carbon nanotubes (CNTs) can be precisely machined in a low pressure water vapor ambient using the electron beam of an environmental scanning electron microscope. The electron beam locally damages the irradiated regions of the CNT forest and also dissociates the water vapor molecules into reactive species including hydroxyl radicals. These species then locally oxidize the damaged region of the CNTs. The technique offers material removal capabilities ranging from selected CNTs to hundreds of cubic microns. We study how the material removal rate is influenced by the acceleration voltage, beam current, dwell time, operating pressure, and CNT orientation. Milled cuts with depths between 0–100 microns are generated, corresponding to a material removal rate of up to 20.1 μm{sup 3}/min. The technique produces little carbon residue and does not disturb the native morphology of the CNT network. Finally, we demonstrate direct machining of pyramidal surfaces and re-entrant cuts to create freestanding geometries.

  13. Three-dimensional machining of carbon nanotube forests using water-assisted scanning electron microscope processing

    Science.gov (United States)

    Rajabifar, Bahram; Kim, Sanha; Slinker, Keith; Ehlert, Gregory J.; Hart, A. John; Maschmann, Matthew R.

    2015-10-01

    We demonstrate that vertically aligned carbon nanotubes (CNTs) can be precisely machined in a low pressure water vapor ambient using the electron beam of an environmental scanning electron microscope. The electron beam locally damages the irradiated regions of the CNT forest and also dissociates the water vapor molecules into reactive species including hydroxyl radicals. These species then locally oxidize the damaged region of the CNTs. The technique offers material removal capabilities ranging from selected CNTs to hundreds of cubic microns. We study how the material removal rate is influenced by the acceleration voltage, beam current, dwell time, operating pressure, and CNT orientation. Milled cuts with depths between 0-100 microns are generated, corresponding to a material removal rate of up to 20.1 μm3/min. The technique produces little carbon residue and does not disturb the native morphology of the CNT network. Finally, we demonstrate direct machining of pyramidal surfaces and re-entrant cuts to create freestanding geometries.

  14. Cadmium Tolerance and Removal from Cunninghamella elegans Related to the Polyphosphate Metabolism

    Directory of Open Access Journals (Sweden)

    Hercília M. L. Rolim

    2013-03-01

    Full Text Available The aim of the present work was to study the cadmium effects on growth, ultrastructure and polyphosphate metabolism, as well as to evaluate the metal removal and accumulation by Cunninghamella elegans (IFM 46109 growing in culture medium. The presence of cadmium reduced growth, and a longer lag phase was observed. However, the phosphate uptake from the culture medium increased 15% when compared to the control. Moreover, C. elegans removed 70%–81% of the cadmium added to the culture medium during its growth. The C. elegans mycelia showed a removal efficiency of 280 mg/g at a cadmium concentration of 22.10 mg/L, and the removal velocity of cadmium was 0.107 mg/h. Additionally, it was observed that cadmium induced vacuolization, the presence of electron dense deposits in vacuoles, cytoplasm and cell membranes, as well as the distinct behavior of polyphosphate fractions. The results obtained with C. elegans suggest that precipitation, vacuolization and polyphosphate fractions were associated to cadmium tolerance, and this species demonstrated a higher potential for bioremediation of heavy metals.

  15. Removing Hair Safely

    Science.gov (United States)

    ... For Consumers Home For Consumers Consumer Updates Removing Hair Safely Share Tweet Linkedin Pin it More sharing ... related to common methods of hair removal. Laser Hair Removal In this method, a laser destroys hair ...

  16. 75 FR 733 - Implementation of the Executive Order, ``Classified National Security Information''

    Science.gov (United States)

    2010-01-05

    ... of the Executive Order, ``Classified National Security Information'' Memorandum for the Heads of... Security Information'' (the ``order''), which substantially advances my goals for reforming the security... classified information shall provide the Director of the Information Security Oversight Office (ISOO) a copy...

  17. Building Keypoint Mappings on Multispectral Images by a Cascade of Classifiers with a Resurrection Mechanism

    Directory of Open Access Journals (Sweden)

    Yong Li

    2015-05-01

    Full Text Available Inspired by the boosting technique for detecting objects, this paper proposes a cascade structure with a resurrection mechanism to establish keypoint mappings on multispectral images. The cascade structure is composed of four steps by utilizing best bin first (BBF, color and intensity distribution of segment (CIDS, global information and the RANSAC process to remove outlier keypoint matchings. Initial keypoint mappings are built with the descriptors associated with keypoints; then, at each step, only a small number of keypoint mappings of a high confidence are classified to be incorrect. The unclassified keypoint mappings will be passed on to subsequent steps for determining whether they are correct. Due to the drawback of a classification rule, some correct keypoint mappings may be misclassified as incorrect at a step. Observing this, we design a resurrection mechanism, so that they will be reconsidered and evaluated by the rules utilized in subsequent steps. Experimental results show that the proposed cascade structure combined with the resurrection mechanism can effectively build more reliable keypoint mappings on multispectral images than existing methods.

  18. Observation of advanced particle removal rates in pump limiter simulation experiments

    International Nuclear Information System (INIS)

    Goebel, D.M.; Conn, R.W.

    1984-05-01

    The performance of particle removal schemes for density and impurity control in tokamaks and mirror machines depends strongly on the plasma parameters and local recycling near the plasma neutralizier plates and gas pumping ducts. The relationship between plasma density, electron temperature, ion energy and gas flow and particle removal rate through a pumping duct located near a plasma neutralizer plate has been experimentally investigated in the steady state plasma device PISCES. Results indicate that initially the particle removal by pumps at the end of the duct is proportional to the plasma flux to the plate. A nonlinear increase in the pumping rate occurs when the ionization mean free path for neutrals from the plate becomes less than the plasma radius. The transition from a transparent to an opaque plasma due to local ionization of the neutrals produced at the neutralizer plate greatly enhances the particle removal rate by recycling of the neutral gas as it flows away from the neutralizer plate or out of the pumping ducts. Parameters were varied to determine the importance of ballistic scattering of higher energy ions from the plate, but no effects were found in these experiments

  19. Proposed hybrid-classifier ensemble algorithm to map snow cover area

    Science.gov (United States)

    Nijhawan, Rahul; Raman, Balasubramanian; Das, Josodhir

    2018-01-01

    Metaclassification ensemble approach is known to improve the prediction performance of snow-covered area. The methodology adopted in this case is based on neural network along with four state-of-art machine learning algorithms: support vector machine, artificial neural networks, spectral angle mapper, K-mean clustering, and a snow index: normalized difference snow index. An AdaBoost ensemble algorithm related to decision tree for snow-cover mapping is also proposed. According to available literature, these methods have been rarely used for snow-cover mapping. Employing the above techniques, a study was conducted for Raktavarn and Chaturangi Bamak glaciers, Uttarakhand, Himalaya using multispectral Landsat 7 ETM+ (enhanced thematic mapper) image. The study also compares the results with those obtained from statistical combination methods (majority rule and belief functions) and accuracies of individual classifiers. Accuracy assessment is performed by computing the quantity and allocation disagreement, analyzing statistic measures (accuracy, precision, specificity, AUC, and sensitivity) and receiver operating characteristic curves. A total of 225 combinations of parameters for individual classifiers were trained and tested on the dataset and results were compared with the proposed approach. It was observed that the proposed methodology produced the highest classification accuracy (95.21%), close to (94.01%) that was produced by the proposed AdaBoost ensemble algorithm. From the sets of observations, it was concluded that the ensemble of classifiers produced better results compared to individual classifiers.

  20. Classifier models and architectures for EEG-based neonatal seizure detection

    International Nuclear Information System (INIS)

    Greene, B R; Marnane, W P; Lightbody, G; Reilly, R B; Boylan, G B

    2008-01-01

    Neonatal seizures are the most common neurological emergency in the neonatal period and are associated with a poor long-term outcome. Early detection and treatment may improve prognosis. This paper aims to develop an optimal set of parameters and a comprehensive scheme for patient-independent multi-channel EEG-based neonatal seizure detection. We employed a dataset containing 411 neonatal seizures. The dataset consists of multi-channel EEG recordings with a mean duration of 14.8 h from 17 neonatal patients. Early-integration and late-integration classifier architectures were considered for the combination of information across EEG channels. Three classifier models based on linear discriminants, quadratic discriminants and regularized discriminants were employed. Furthermore, the effect of electrode montage was considered. The best performing seizure detection system was found to be an early integration configuration employing a regularized discriminant classifier model. A referential EEG montage was found to outperform the more standard bipolar electrode montage for automated neonatal seizure detection. A cross-fold validation estimate of the classifier performance for the best performing system yielded 81.03% of seizures correctly detected with a false detection rate of 3.82%. With post-processing, the false detection rate was reduced to 1.30% with 59.49% of seizures correctly detected. These results represent a comprehensive illustration that robust reliable patient-independent neonatal seizure detection is possible using multi-channel EEG

  1. Classifying hot water chemistry: Application of MULTIVARIATE STATISTICS

    OpenAIRE

    Sumintadireja, Prihadi; Irawan, Dasapta Erwin; Rezky, Yuanno; Gio, Prana Ugiana; Agustin, Anggita

    2016-01-01

    This file is the dataset for the following paper "Classifying hot water chemistry: Application of MULTIVARIATE STATISTICS". Authors: Prihadi Sumintadireja1, Dasapta Erwin Irawan1, Yuano Rezky2, Prana Ugiana Gio3, Anggita Agustin1

  2. Removal of Strontium Ions by Immobilized Saccharomyces Cerevisiae in Magnetic Chitosan Microspheres

    Directory of Open Access Journals (Sweden)

    Yanan Yin

    2017-02-01

    Full Text Available A novel biosorbent, immobilized Saccharomyces cerevisiae in magnetic chitosan microspheres was prepared, characterized, and used for the removal of Sr2+ from aqueous solution. The structure and morphology of immobilized S. cerevisiae before and after Sr2+adsorption were observed using scanning electron microscopy with energy dispersive X-ray spectroscopy. The experimental results showed that the Langmuir and Freundlich isotherm models could be used to describe the Sr2+ adsorption onto immobilized S. cerevisiae microspheres. The maximal adsorption capacity (qm was calculated to be 81.96 mg/g by the Langmuir model. Immobilized S. cerevisiae was an effective adsorbent for the Sr2+ removal from aqueous solution.

  3. Microbial metabolism and activity in terms of nitrate removal in bioelectrochemical systems

    International Nuclear Information System (INIS)

    Huang, Baocheng; Feng, Huajun; Ding, Yangcheng; Zheng, Xin; Wang, Meizhen; Li, Na; Shen, Dongsheng; Zhang, Haiyang

    2013-01-01

    Highlights: • Influence of current on biofilm formation in BES was investigated. • Biofilm formation activity supplying with organic differed with inorganic. • Discussed the influence of signaling molecule and EPS on biofilm formation. -- Abstract: Bioelectrochemical systems (BESs) are a promising technology for generating energy while treating wastewater. By utilizing the electron transfer between the anode and cathode, nitrate can be effectively removed from the BES. Our previous studies show that the carbon source and C/N ratio influences nitrate removal performance. The study presented here investigates how biofilm formation, nitrate removal and signaling molecule release are related in the BESs fed with glucose, starch and HCO 3 − . The results indicate that increasing the current can benefit signaling molecule (DSF) release and extracellular polymeric substances (EPS) excretion, which improves biofilm formation. However, when the current exceeds the optimum value, the influence becomes adverse. Nitrate removal was also improved with increased current, though different carbon sources showed different trends. The highest nitrate removal efficiency of 1.23 ± 0.27, 1.38 ± 0.09, 1.80 ± 0.02 mmol L −1 d −1 for the BESs fed with glucose, starch and HCO 3 − were achieved, respectively. This paper studied the bacterial habits in a BES to better acquire and regulate the reaction process, with the aim of achieving good pollutant removal performance

  4. Removal effects of the Nd:YAG laser and Carisolv on carious dentin.

    Science.gov (United States)

    Yamada, Y; Hossain, M; Kawanaka, T; Kinoshita, J; Matsumoto, K

    2000-10-01

    The purpose of this study was to investigate the removal effect of the Nd:YAG laser irradiation and Carisolv on carious dentin. Many previous studies have reported several simple and alternative techniques, such as lasers and chemicals, for caries removal. Carisolv was applied on the surface of 20 extracted human anterior and molar teeth for 1 min and then the Nd:YAG laser was irradiated with a continuous water spray for another 1 min. The energy densities were varied from 2 to 6W with a repetition rate of 20 pps. As caries removal progressed, the cavity was carefully assessed by DIAGNOdent. Each lesion was photographed before and after treatment, and the treated cavity was observed microscopically using a stereoscope and with scanning electron microscope (SEM). Thermal change at the time of laser irradiation was measured by thermovision. Our results revealed that application of Carisolv followed by Nd:YAG laser irradiation at 4-6W pulse energy effectively removed dentin caries. The total procedure was usually repeated once or twice for complete caries removal. From the SEM study, it was found that the cavity surface treated with the laser revealed various patterns of microirregularity, often accompanied by microfissure propagation. There was also no smear layer. It was revealed that Nd:YAG laser and Carisolv could provide an alternative technique for caries removal instead of the conventional mechanical drilling and cutting.

  5. In vitro assessment of cutting efficiency and durability of zirconia removal diamond rotary instruments.

    Science.gov (United States)

    Kim, Joon-Soo; Bae, Ji-Hyeon; Yun, Mi-Jung; Huh, Jung-Bo

    2017-06-01

    Recently, zirconia removal diamond rotary instruments have become commercially available for efficient cutting of zirconia. However, research of cutting efficiency and the cutting characteristics of zirconia removal diamond rotary instruments is limited. The purpose of this in vitro study was to assess and compare the cutting efficiency, durability, and diamond rotary instrument wear pattern of zirconia diamond removal rotary instruments with those of conventional diamond rotary instruments. In addition, the surface characteristics of the cut zirconia were assessed. Block specimens of 3 mol% yttrium cation-doped tetragonal zirconia polycrystal were machined 10 times for 1 minute each using a high-speed handpiece with 6 types of diamond rotary instrument from 2 manufacturers at a constant force of 2 N (n=5). An electronic scale was used to measure the lost weight after each cut in order to evaluate the cutting efficiency. Field emission scanning electron microscopy was used to evaluate diamond rotary instrument wear patterns and machined zirconia block surface characteristics. Data were statistically analyzed using the Kruskal-Wallis test, followed by the Mann-Whitney U test (α=.05). Zirconia removal fine grit diamond rotary instruments showed cutting efficiency that was reduced compared with conventional fine grit diamond rotary instruments. Diamond grit fracture was the most dominant diamond rotary instrument wear pattern in all groups. All machined zirconia surfaces were primarily subjected to plastic deformation, which is evidence of ductile cutting. Zirconia blocks machined with zirconia removal fine grit diamond rotary instruments showed the least incidence of surface flaws. Although zirconia removal diamond rotary instruments did not show improved cutting efficiency compared with conventional diamond rotary instruments, the machined zirconia surface showed smoother furrows of plastic deformation and fewer surface flaws. Copyright © 2016 Editorial Council

  6. Discrimination-Aware Classifiers for Student Performance Prediction

    Science.gov (United States)

    Luo, Ling; Koprinska, Irena; Liu, Wei

    2015-01-01

    In this paper we consider discrimination-aware classification of educational data. Mining and using rules that distinguish groups of students based on sensitive attributes such as gender and nationality may lead to discrimination. It is desirable to keep the sensitive attributes during the training of a classifier to avoid information loss but…

  7. Two-categorical bundles and their classifying spaces

    DEFF Research Database (Denmark)

    Baas, Nils A.; Bökstedt, M.; Kro, T.A.

    2012-01-01

    -category is a classifying space for the associated principal 2-bundles. In the process of proving this we develop a lot of powerful machinery which may be useful in further studies of 2-categorical topology. As a corollary we get a new proof of the classification of principal bundles. A calculation based...

  8. Molecular analysis by electron microscopy of the removal of psoralen-photoinduced DNA cross-links in normal and Fanconi's anemia fibroblasts

    International Nuclear Information System (INIS)

    Rousset, S.; Nocentini, S.; Revet, B.; Moustacchi, E.

    1990-01-01

    The induction and fate of psoralen-photoinduced DNA interstrand cross-links in the genome of Fanconi's anemia (FA) fibroblasts of complementation groups A and B, and of normal human fibroblasts, were investigated by quantitative analysis of totally denatured DNA fragments visualized by electron microscopy. 8-Methoxypsoralen (5 x 10(-5) M) interstrand cross-links were induced as a function of the near ultraviolet light dose. With time of postexposure incubation, a fraction of interstrand cross-links disappeared in all cell lines. However, 24 h after treatment, this removal was significantly lower in the two FA group A cell lines examined (34-39%) than in the FA group B and normal cell lines (43-53 and 47-57%, respectively). These data indicate that FA cells are at least able to recognize and incise interstrand cross-links, as normal cells do, although group A cells seem somewhat hampered in this process. This is in accord with data obtained on the same cell lines using another biochemical assay. Since the fate of cross-links in FA constituted a controversial matter, it is important to stress that two different methodologies applied to genetically well defined cell lines led to the same conclusions

  9. A Bayesian classifier for symbol recognition

    OpenAIRE

    Barrat , Sabine; Tabbone , Salvatore; Nourrissier , Patrick

    2007-01-01

    URL : http://www.buyans.com/POL/UploadedFile/134_9977.pdf; International audience; We present in this paper an original adaptation of Bayesian networks to symbol recognition problem. More precisely, a descriptor combination method, which enables to improve significantly the recognition rate compared to the recognition rates obtained by each descriptor, is presented. In this perspective, we use a simple Bayesian classifier, called naive Bayes. In fact, probabilistic graphical models, more spec...

  10. Air classifier technology (ACT) in dry powder inhalation. Part 1 : Introduction of a novel force distribution concept (FDC) explaining the performance of a basic air classifier on adhesive mixtures

    NARCIS (Netherlands)

    de Boer, A H; Hagedoorn, P; Gjaltema, D; Goede, J; Frijlink, H W

    2003-01-01

    Air classifier technology (ACT) is introduced as part of formulation integrated dry powder inhaler development (FIDPI) to optimise the de-agglomeration of inhalation powders. Carrier retention and de-agglomeration results obtained with a basic classifier concept are discussed. The theoretical

  11. Colloids removal from water resources using natural coagulant: Acacia auriculiformis

    Science.gov (United States)

    Abdullah, M.; Roslan, A.; Kamarulzaman, M. F. H.; Erat, M. M.

    2017-09-01

    All waters, especially surface waters contain dissolved, suspended particles and/or inorganic matter, as well as several biological organisms, such as bacteria, algae or viruses. This material must be removed because it can affect the water quality that can cause turbidity and colour. The objective of this study is to develop water treatment process from Seri Alam (Johor, Malaysia) lake water resources by using natural coagulant Acacia auriculiformis pods through a jar test experiment. Jar test is designed to show the effectiveness of the water treatment. This process is a laboratory procedure that will simulate coagulation/flocculation with several parameters selected namely contact time, coagulant dosage and agitation speed. The most optimum percentage of colloids removal for each parameter is determined at 0.2 g, 90 min and 80 rpm. FESEM (Field-emission Scanning Electron Microscope) observed the small structures of final floc particles for optimum parameter in this study to show that the colloids coagulated the coagulant. All result showed that the Acacia auriculiformis pods can be a very efficient coagulant in removing colloids from water.

  12. Contribution of scanning Auger microscopy to electron beam damage study

    International Nuclear Information System (INIS)

    Fontaine, J.M.

    1983-04-01

    Electron bombardment can produce surface modifications of the analysed sample. The electron beam effects on solid surfaces which have been discussed in the published literature can be classified into the following four categories: (1) heating and its consequent effects, (2) charge accumulation in insulators and its consequent effects, (3) electron stimulated adsorption (ESA), and (4) electron stimulated desorption and/or decomposition (ESD). In order to understand the physico-chemical processes which take place under electron irradiation in an Al-O system, we have carried out experiments in which, effects, such as heating, charging and gas contamination, were absent. Our results point out the role of an enhanced surface diffusion of oxygen during electron bombardment of an Al (111) sample. The importance of this phenomenon and the contribution of near-elastic scattering of the primary electrons (5 keV) to the increase of the oxidation degree observed on Al (111) are discussed, compared to the generally studied effects

  13. Removal of antibiotics from water in the coexistence of suspended particles and natural organic matters using amino-acid-modified-chitosan flocculants: A combined experimental and theoretical study

    International Nuclear Information System (INIS)

    Jia, Shuying; Yang, Zhen; Ren, Kexin; Tian, Ziqi; Dong, Chang; Ma, Ruixue; Yu, Ge; Yang, Weiben

    2016-01-01

    Highlights: • Novel amino-acid-modified-chitosan flocculants are employed to remove antibiotics. • Effects of different structures of amino acids and antibiotics are investigated. • Correlation analysis shows coexisted kaolin and HA have synergistic removal effect. • Theoretical DFT calculation clarifies the interactions in molecular level. - Abstract: Contamination of trace antibiotics is widely found in surface water sources. This work delineates removal of trace antibiotics (norfloxacin (NOR), sulfadiazine (SDZ) or tylosin (TYL)) from synthetic surface water by flocculation, in the coexistence of inorganic suspended particles (kaolin) and natural organic matter (humic acid, HA). To avoid extra pollution caused by petrochemical products-based modification reagents, environmental-friendly amino-acid-modified-chitosan flocculants, Ctrp and Ctyr, with different functional aromatic-rings structures were employed. Jar tests at various pHs exhibited that, Ctyr, owning phenol groups as electron donors, was favored for elimination of cationic NOR (∼50% removal; optimal pH: 6; optimal dosage: 4 mg/L) and TYL (∼60% removal; optimal pH: 7; optimal dosage: 7.5 mg/L), due to π–π electron donator-acceptor (EDA) effect and unconventional H-bonds. Differently, Ctrp with indole groups as electron acceptor had better removal rate (∼50%) of SDZ anions (electron donator). According to correlation analysis, the coexisted kaolin and HA played positive roles in antibiotics’ removal. Detailed pairwise interactions in molecular level among different components were clarified by spectral analysis and theoretical calculations (density functional theory), which are important for both the structural design of new flocculants aiming at targeted contaminants and understanding the environmental behaviors of antibiotics in water.

  14. Removal of antibiotics from water in the coexistence of suspended particles and natural organic matters using amino-acid-modified-chitosan flocculants: A combined experimental and theoretical study

    Energy Technology Data Exchange (ETDEWEB)

    Jia, Shuying [School of Chemistry and Materials Science, Jiangsu Provincial Key Laboratory of Materials Cycling and Pollution Control, Nanjing Normal University, Nanjing 210023 (China); Yang, Zhen, E-mail: yangzhen@njnu.edu.cn [School of Chemistry and Materials Science, Jiangsu Provincial Key Laboratory of Materials Cycling and Pollution Control, Nanjing Normal University, Nanjing 210023 (China); Ren, Kexin [School of Chemistry and Materials Science, Jiangsu Provincial Key Laboratory of Materials Cycling and Pollution Control, Nanjing Normal University, Nanjing 210023 (China); Tian, Ziqi [Department of Chemistry, University of California, Riverside, CA 92521 (United States); Dong, Chang; Ma, Ruixue; Yu, Ge [School of Chemistry and Materials Science, Jiangsu Provincial Key Laboratory of Materials Cycling and Pollution Control, Nanjing Normal University, Nanjing 210023 (China); Yang, Weiben, E-mail: yangwb007@njnu.edu.cn [School of Chemistry and Materials Science, Jiangsu Provincial Key Laboratory of Materials Cycling and Pollution Control, Nanjing Normal University, Nanjing 210023 (China)

    2016-11-05

    Highlights: • Novel amino-acid-modified-chitosan flocculants are employed to remove antibiotics. • Effects of different structures of amino acids and antibiotics are investigated. • Correlation analysis shows coexisted kaolin and HA have synergistic removal effect. • Theoretical DFT calculation clarifies the interactions in molecular level. - Abstract: Contamination of trace antibiotics is widely found in surface water sources. This work delineates removal of trace antibiotics (norfloxacin (NOR), sulfadiazine (SDZ) or tylosin (TYL)) from synthetic surface water by flocculation, in the coexistence of inorganic suspended particles (kaolin) and natural organic matter (humic acid, HA). To avoid extra pollution caused by petrochemical products-based modification reagents, environmental-friendly amino-acid-modified-chitosan flocculants, Ctrp and Ctyr, with different functional aromatic-rings structures were employed. Jar tests at various pHs exhibited that, Ctyr, owning phenol groups as electron donors, was favored for elimination of cationic NOR (∼50% removal; optimal pH: 6; optimal dosage: 4 mg/L) and TYL (∼60% removal; optimal pH: 7; optimal dosage: 7.5 mg/L), due to π–π electron donator-acceptor (EDA) effect and unconventional H-bonds. Differently, Ctrp with indole groups as electron acceptor had better removal rate (∼50%) of SDZ anions (electron donator). According to correlation analysis, the coexisted kaolin and HA played positive roles in antibiotics’ removal. Detailed pairwise interactions in molecular level among different components were clarified by spectral analysis and theoretical calculations (density functional theory), which are important for both the structural design of new flocculants aiming at targeted contaminants and understanding the environmental behaviors of antibiotics in water.

  15. Theory of hot electrons on the liquid 4He surface, 2

    International Nuclear Information System (INIS)

    Aoki, Takayuki; Saitoh, Motohiko

    1979-01-01

    Theoretical study is given of the high field transport of surface state electrons on the liquid 4 He. The explicit form of the electron distribution function is solved by the use of the Boltzmann transport equation where the electron-ripplon and electron-He gas interactions are considered as dominant scattering mechanisms, and the electron-electron interactions are completely neglected. Inter-subband and intra-subband transitions are treated equally. The S-shaped non-linear behaviors predicted to occur at low temperature region in the electron temperature approximation have been removed. Experimentally observed hysteresis, if any, in the widths of the plasmon resonance and cyclotron resonance may thus be attributed to the electron-electron interaction. (author)

  16. Analysis and minimization of overtraining effect in rule-based classifiers for computer-aided diagnosis

    International Nuclear Information System (INIS)

    Li Qiang; Doi Kunio

    2006-01-01

    Computer-aided diagnostic (CAD) schemes have been developed to assist radiologists detect various lesions in medical images. In CAD schemes, classifiers play a key role in achieving a high lesion detection rate and a low false-positive rate. Although many popular classifiers such as linear discriminant analysis and artificial neural networks have been employed in CAD schemes for reduction of false positives, a rule-based classifier has probably been the simplest and most frequently used one since the early days of development of various CAD schemes. However, with existing rule-based classifiers, there are major disadvantages that significantly reduce their practicality and credibility. The disadvantages include manual design, poor reproducibility, poor evaluation methods such as resubstitution, and a large overtraining effect. An automated rule-based classifier with a minimized overtraining effect can overcome or significantly reduce the extent of the above-mentioned disadvantages. In this study, we developed an 'optimal' method for the selection of cutoff thresholds and a fully automated rule-based classifier. Experimental results performed with Monte Carlo simulation and a real lung nodule CT data set demonstrated that the automated threshold selection method can completely eliminate overtraining effect in the procedure of cutoff threshold selection, and thus can minimize overall overtraining effect in the constructed rule-based classifier. We believe that this threshold selection method is very useful in the construction of automated rule-based classifiers with minimized overtraining effect

  17. Effective Sequential Classifier Training for SVM-Based Multitemporal Remote Sensing Image Classification

    Science.gov (United States)

    Guo, Yiqing; Jia, Xiuping; Paull, David

    2018-06-01

    The explosive availability of remote sensing images has challenged supervised classification algorithms such as Support Vector Machines (SVM), as training samples tend to be highly limited due to the expensive and laborious task of ground truthing. The temporal correlation and spectral similarity between multitemporal images have opened up an opportunity to alleviate this problem. In this study, a SVM-based Sequential Classifier Training (SCT-SVM) approach is proposed for multitemporal remote sensing image classification. The approach leverages the classifiers of previous images to reduce the required number of training samples for the classifier training of an incoming image. For each incoming image, a rough classifier is firstly predicted based on the temporal trend of a set of previous classifiers. The predicted classifier is then fine-tuned into a more accurate position with current training samples. This approach can be applied progressively to sequential image data, with only a small number of training samples being required from each image. Experiments were conducted with Sentinel-2A multitemporal data over an agricultural area in Australia. Results showed that the proposed SCT-SVM achieved better classification accuracies compared with two state-of-the-art model transfer algorithms. When training data are insufficient, the overall classification accuracy of the incoming image was improved from 76.18% to 94.02% with the proposed SCT-SVM, compared with those obtained without the assistance from previous images. These results demonstrate that the leverage of a priori information from previous images can provide advantageous assistance for later images in multitemporal image classification.

  18. The pilot plant experiment of electron beam irradiation process for removal of NOx and SOx from sinter plant exhaust gas in the iron and steel industry

    International Nuclear Information System (INIS)

    Kawamura, K.; Katayama, T.; Kawamura, Ke.

    1981-01-01

    Air pollution problem has become more important in the progress of industry. Nitrogen oxides (NOx, mostly NO) and sulfur oxides (SOx, mostly SO 2 ) which are contained in a sinter plant exhaust gas, are known as serious air pollutants. In such circumstances, an attempt has been made to simultaneously remove NOx and SOx from the sinter plant exhaust gas by means of a new electron beam irradiation process. The process consists of adding a small amount of NH 3 to the exhaust gas, irradiating the gas by electron beam, forming ammonium salts by reactions of NOx and SOx with the NH 3 and collecting ammonium salts by dry electrostatic precipitator (E.P.). Basic research on the present process had been performed using heavy oil combustion gas. Based on the results research was launched to study the applicability of the process to the treatment of sinter plant exhaust gas. A pilot plant, capable of treating a gas flow of 3000 Nm 3 /H was set up, and experiments were performed from July 1977 to June 1978. The plant is described and the results are presented. (author)

  19. Statistical text classifier to detect specific type of medical incidents.

    Science.gov (United States)

    Wong, Zoie Shui-Yee; Akiyama, Masanori

    2013-01-01

    WHO Patient Safety has put focus to increase the coherence and expressiveness of patient safety classification with the foundation of International Classification for Patient Safety (ICPS). Text classification and statistical approaches has showed to be successful to identifysafety problems in the Aviation industryusing incident text information. It has been challenging to comprehend the taxonomy of medical incidents in a structured manner. Independent reporting mechanisms for patient safety incidents have been established in the UK, Canada, Australia, Japan, Hong Kong etc. This research demonstrates the potential to construct statistical text classifiers to detect specific type of medical incidents using incident text data. An illustrative example for classifying look-alike sound-alike (LASA) medication incidents using structured text from 227 advisories related to medication errors from Global Patient Safety Alerts (GPSA) is shown in this poster presentation. The classifier was built using logistic regression model. ROC curve and the AUC value indicated that this is a satisfactory good model.

  20. A Naive-Bayes classifier for damage detection in engineering materials

    Energy Technology Data Exchange (ETDEWEB)

    Addin, O. [Laboratory of Intelligent Systems, Institute of Advanced Technology, Universiti Putra Malaysia, 43400 Serdang, Selangor (Malaysia); Sapuan, S.M. [Department of Mechanical and Manufacturing Engineering, Universiti Putra Malaysia, 43400 Serdang, Selangor (Malaysia)]. E-mail: sapuan@eng.upm.edu.my; Mahdi, E. [Department of Aerospace Engineering, Universiti Putra Malaysia, 43400 Serdang, Selangor (Malaysia); Othman, M. [Department of Communication Technology and Networks, Universiti Putra Malaysia, 43400 Serdang, Selangor (Malaysia)

    2007-07-01

    This paper is intended to introduce the Bayesian network in general and the Naive-Bayes classifier in particular as one of the most successful classification systems to simulate damage detection in engineering materials. A method for feature subset selection has also been introduced too. The method is based on mean and maximum values of the amplitudes of waves after dividing them into folds then grouping them by a clustering algorithm (e.g. k-means algorithm). The Naive-Bayes classifier and the feature sub-set selection method were analyzed and tested on two sets of data. The data sets were conducted based on artificial damages created in quasi isotopic laminated composites of the AS4/3501-6 graphite/epoxy system and ball bearing of the type 6204 with a steel cage. The Naive-Bayes classifier and the proposed feature subset selection algorithm have been shown as efficient techniques for damage detection in engineering materials.

  1. Discovering mammography-based machine learning classifiers for breast cancer diagnosis.

    Science.gov (United States)

    Ramos-Pollán, Raúl; Guevara-López, Miguel Angel; Suárez-Ortega, Cesar; Díaz-Herrero, Guillermo; Franco-Valiente, Jose Miguel; Rubio-Del-Solar, Manuel; González-de-Posada, Naimy; Vaz, Mario Augusto Pires; Loureiro, Joana; Ramos, Isabel

    2012-08-01

    This work explores the design of mammography-based machine learning classifiers (MLC) and proposes a new method to build MLC for breast cancer diagnosis. We massively evaluated MLC configurations to classify features vectors extracted from segmented regions (pathological lesion or normal tissue) on craniocaudal (CC) and/or mediolateral oblique (MLO) mammography image views, providing BI-RADS diagnosis. Previously, appropriate combinations of image processing and normalization techniques were applied to reduce image artifacts and increase mammograms details. The method can be used under different data acquisition circumstances and exploits computer clusters to select well performing MLC configurations. We evaluated 286 cases extracted from the repository owned by HSJ-FMUP, where specialized radiologists segmented regions on CC and/or MLO images (biopsies provided the golden standard). Around 20,000 MLC configurations were evaluated, obtaining classifiers achieving an area under the ROC curve of 0.996 when combining features vectors extracted from CC and MLO views of the same case.

  2. A Topic Model Approach to Representing and Classifying Football Plays

    KAUST Repository

    Varadarajan, Jagannadan

    2013-09-09

    We address the problem of modeling and classifying American Football offense teams’ plays in video, a challenging example of group activity analysis. Automatic play classification will allow coaches to infer patterns and tendencies of opponents more ef- ficiently, resulting in better strategy planning in a game. We define a football play as a unique combination of player trajectories. To this end, we develop a framework that uses player trajectories as inputs to MedLDA, a supervised topic model. The joint maximiza- tion of both likelihood and inter-class margins of MedLDA in learning the topics allows us to learn semantically meaningful play type templates, as well as, classify different play types with 70% average accuracy. Furthermore, this method is extended to analyze individual player roles in classifying each play type. We validate our method on a large dataset comprising 271 play clips from real-world football games, which will be made publicly available for future comparisons.

  3. A novel ultrasound based technique for classifying gas bubble sizes in liquids

    International Nuclear Information System (INIS)

    Hussein, Walid; Khan, Muhammad Salman; Zamorano, Juan; Espic, Felipe; Yoma, Nestor Becerra

    2014-01-01

    Characterizing gas bubbles in liquids is crucial to many biomedical, environmental and industrial applications. In this paper a novel method is proposed for the classification of bubble sizes using ultrasound analysis, which is widely acknowledged for being non-invasive, non-contact and inexpensive. This classification is based on 2D templates, i.e. the average spectrum of events representing the trace of bubbles when they cross an ultrasound field. The 2D patterns are obtained by capturing ultrasound signals reflected by bubbles. Frequency-domain based features are analyzed that provide discrimination between bubble sizes. These features are then fed to an artificial neural network, which is designed and trained to classify bubble sizes. The benefits of the proposed method are that it facilitates the processing of multiple bubbles simultaneously, the issues concerning masking interference among bubbles are potentially reduced and using a single sinusoidal component makes the transmitter–receiver electronics relatively simpler. Results from three bubble sizes indicate that the proposed scheme can achieve an accuracy in their classification that is as high as 99%. (paper)

  4. Histogram deconvolution - An aid to automated classifiers

    Science.gov (United States)

    Lorre, J. J.

    1983-01-01

    It is shown that N-dimensional histograms are convolved by the addition of noise in the picture domain. Three methods are described which provide the ability to deconvolve such noise-affected histograms. The purpose of the deconvolution is to provide automated classifiers with a higher quality N-dimensional histogram from which to obtain classification statistics.

  5. Etch pit investigation of free electron concentration controlled 4H-SiC

    Science.gov (United States)

    Kim, Hong-Yeol; Shin, Yun Ji; Kim, Jung Gon; Harima, Hiroshi; Kim, Jihyun; Bahng, Wook

    2013-04-01

    Etch pits were investigated using the molten KOH selective etching method to examine dependence of etch pit shape and size on free electron concentration. The free electron concentrations of highly doped 4H-silicon carbide (SiC) were controlled by proton irradiation and thermal annealing, which was confirmed by a frequency shift in the LO-phonon-plasmon-coupled (LOPC) mode on micro-Raman spectroscopy. The proton irradiated sample with 5×1015 cm-2 fluence and an intrinsic semi-insulating sample showed clearly classified etch pits but different ratios of threading screw dislocation (TSD) and threading edge dislocation (TED) sizes. Easily classified TEDs and TSDs on proton irradiated 4H-SiC were restored as highly doped 4H-SiC after thermal annealing due to the recovered carrier concentrations. The etched surface of proton irradiated 4H-SiC and boron implanted SiC showed different surface conditions after activation.

  6. Magnetite nanoparticles coated glass wool for As(V) removal from drinking water

    International Nuclear Information System (INIS)

    Kango, Sarita; Kumar, Rajesh

    2015-01-01

    Arsenic (As) removal from contaminated groundwater is a key environmental concern worldwide. In this study, glass wool was coated with magnetite nanoparticles under argon gas flow and magnetite coated glass wool have been investigated for application as an adsorbent for As(V) removal from water. The adsorbent was characterized by using Scanning Electron Microscopy (SEM) and arsenic contaminated water treated with adsorbent was analyzed by Inductively Coupled Plasma Mass Spectroscopy (ICP-MS). The ICP-MS results showed that 10 g/L of adsorbent removed 99.4% of As(V) within 5 hours at pH-7 and initial arsenic concentration of 360µg/L. Adsorption kinetics data fitted well in pseudo-first-order kinetics model with high correlation coefficient (R 2 = 0.995). As magnetite nanoparticles coated glass wool showed favorable adsorption behavior for As(V), it can be a promising tool for water purification

  7. Magnetite nanoparticles coated glass wool for As(V) removal from drinking water

    Energy Technology Data Exchange (ETDEWEB)

    Kango, Sarita; Kumar, Rajesh, E-mail: rajesh.kumar@juit.ac.in [Department of Physics and Materials Science, Jaypee University of Information Technology, Waknaghat, District Solan (H.P.)- 173 234 (India)

    2015-08-28

    Arsenic (As) removal from contaminated groundwater is a key environmental concern worldwide. In this study, glass wool was coated with magnetite nanoparticles under argon gas flow and magnetite coated glass wool have been investigated for application as an adsorbent for As(V) removal from water. The adsorbent was characterized by using Scanning Electron Microscopy (SEM) and arsenic contaminated water treated with adsorbent was analyzed by Inductively Coupled Plasma Mass Spectroscopy (ICP-MS). The ICP-MS results showed that 10 g/L of adsorbent removed 99.4% of As(V) within 5 hours at pH-7 and initial arsenic concentration of 360µg/L. Adsorption kinetics data fitted well in pseudo-first-order kinetics model with high correlation coefficient (R{sup 2} = 0.995). As magnetite nanoparticles coated glass wool showed favorable adsorption behavior for As(V), it can be a promising tool for water purification.

  8. Self-organizing map classifier for stressed speech recognition

    Science.gov (United States)

    Partila, Pavol; Tovarek, Jaromir; Voznak, Miroslav

    2016-05-01

    This paper presents a method for detecting speech under stress using Self-Organizing Maps. Most people who are exposed to stressful situations can not adequately respond to stimuli. Army, police, and fire department occupy the largest part of the environment that are typical of an increased number of stressful situations. The role of men in action is controlled by the control center. Control commands should be adapted to the psychological state of a man in action. It is known that the psychological changes of the human body are also reflected physiologically, which consequently means the stress effected speech. Therefore, it is clear that the speech stress recognizing system is required in the security forces. One of the possible classifiers, which are popular for its flexibility, is a self-organizing map. It is one type of the artificial neural networks. Flexibility means independence classifier on the character of the input data. This feature is suitable for speech processing. Human Stress can be seen as a kind of emotional state. Mel-frequency cepstral coefficients, LPC coefficients, and prosody features were selected for input data. These coefficients were selected for their sensitivity to emotional changes. The calculation of the parameters was performed on speech recordings, which can be divided into two classes, namely the stress state recordings and normal state recordings. The benefit of the experiment is a method using SOM classifier for stress speech detection. Results showed the advantage of this method, which is input data flexibility.

  9. Comprehensive benchmarking and ensemble approaches for metagenomic classifiers.

    Science.gov (United States)

    McIntyre, Alexa B R; Ounit, Rachid; Afshinnekoo, Ebrahim; Prill, Robert J; Hénaff, Elizabeth; Alexander, Noah; Minot, Samuel S; Danko, David; Foox, Jonathan; Ahsanuddin, Sofia; Tighe, Scott; Hasan, Nur A; Subramanian, Poorani; Moffat, Kelly; Levy, Shawn; Lonardi, Stefano; Greenfield, Nick; Colwell, Rita R; Rosen, Gail L; Mason, Christopher E

    2017-09-21

    One of the main challenges in metagenomics is the identification of microorganisms in clinical and environmental samples. While an extensive and heterogeneous set of computational tools is available to classify microorganisms using whole-genome shotgun sequencing data, comprehensive comparisons of these methods are limited. In this study, we use the largest-to-date set of laboratory-generated and simulated controls across 846 species to evaluate the performance of 11 metagenomic classifiers. Tools were characterized on the basis of their ability to identify taxa at the genus, species, and strain levels, quantify relative abundances of taxa, and classify individual reads to the species level. Strikingly, the number of species identified by the 11 tools can differ by over three orders of magnitude on the same datasets. Various strategies can ameliorate taxonomic misclassification, including abundance filtering, ensemble approaches, and tool intersection. Nevertheless, these strategies were often insufficient to completely eliminate false positives from environmental samples, which are especially important where they concern medically relevant species. Overall, pairing tools with different classification strategies (k-mer, alignment, marker) can combine their respective advantages. This study provides positive and negative controls, titrated standards, and a guide for selecting tools for metagenomic analyses by comparing ranges of precision, accuracy, and recall. We show that proper experimental design and analysis parameters can reduce false positives, provide greater resolution of species in complex metagenomic samples, and improve the interpretation of results.

  10. Novel MBR_based main stream biological nutrient removal process: high performance and microbial community.

    Science.gov (United States)

    Zhang, Chuanyi; Xu, Xinhai; Zhao, Kuixia; Tang, Lianggang; Zou, Siqi; Yuan, Limei

    2018-02-01

    For municipal wastewater treatment, main stream biological nutrient removal (BNR) process is becoming more and more important. This lab-scale study, novel MBR_based BNR processes (named A 2 N-MBR and A 2 NO-MBR) were built. Comparison of the COD removal, results obtained demonstrated that COD removal efficiencies were almost the same in three processes, with effluent concentration all bellowed 30 mg L -1 . However, the two-sludge systems (A 2 N-MBR and A 2 NO-MBR) had an obvious advantage over the A 2 /O for denitrification and phosphorus removal, with the average TP removal rates of 91.20, 98.05% and TN removal rates of 73.00, 79.49%, respectively, higher than that of 86.45 and 61.60% in A 2 /O process. Illumina Miseq sequencing revealed that Candidatus_Accumulibacter, which is capable of using nitrate as an electron acceptor for phosphorus and nitrogen removal simultaneously, was the dominant phylum in both A 2 N-MBR and A 2 NO-MBR process, accounting for 28.74 and 23.98%, respectively. Distinguishingly, major organism groups related to nitrogen and phosphorus removal in A 2 /O system were Anaerolineaceae_uncultured, Saprospiraceae_uncultured and Thauera, with proportions of 11.31, 8.56 and 5.00%, respectively. Hence, the diversity of dominant PAOs group was likely responsible for the difference in nitrogen and phosphorus removal in the three processes.

  11. Characterization and Cadmium Ion-Removing Property of Adsorbents Synthesized from Inorganic Wastes

    Energy Technology Data Exchange (ETDEWEB)

    Ooishi, Kou; Ogino, Kana; Nishioka, Hiroshi; Muramatsu, Yasuji, E-mail: hnisioka@eng.u-hyogo.ac.jp [Department of Material Science and Chemistry, Graduate School of Engineering, University of Hyogo, 2167 Shosha, Himeji, Hyogo (Japan)

    2011-10-29

    Adsorbents for removing cadmium ions from water were synthesized from inorganic wastes such as oyster shells, drinking-water-treatment sludge (DWTS), and waste glass. The oyster shells and DWTS were pretreated by heating for 2 h at 1173 K before hydrothermal synthesis was started. The Al/(Al+Si) ratio was adjusted, and then, the mixture of pretreated materials was hydrothermally treated in a sodium hydroxide solution for 72 h at 423 K to synthesize the adsorbents. The synthesized adsorbent specimens were characterized by X-ray diffraction (XRD), thermogravimetric-differential thermal analysis (TG-DTA) measurements, and scanning electron microscopy (SEM). The main components of these specimens were aluminum-substituted tobermorite and sodalite. The formation of sodalite was dependent on the mass ratio of DWTS to glass. The maximum amount of cadmium ions were removed when the mass ratio of the pretreated material was 1:1:1. In the cadmium removal test, the adsorbent with this mass ratio removed almost 100% of the cadmium in a solution with a concentration of 10 mg L-1. Even in the presence of a 1000-fold excess of potassium ions or 10000-fold excess of sodium ions, approximately 80% of the cadmium ions were removed.

  12. Patentna zaštita poverljivih pronalazaka / Patent protection of classified invention

    Directory of Open Access Journals (Sweden)

    Obrad T. Čabarkapa

    2008-10-01

    Full Text Available Svaki pronalazak za koji se utvrdi da je značajan za odbranu i bezbednost Republike Srbije smatra se poverljivim. Za patentnu zaštitu poverljivih pronalazaka podnosi se prijava organu nadležnom za poslove odbrane, koji ima isključivo pravo da raspolaže poverljivim pronalascima1. U organizacijskoj jedinici nadležnoj za poslove naučne i inovacione delatnosti2 realizuje postupak ispitivanja poverljivih prijava patenata. Da bi se donela ocena o poverljivosti prijavljenog pronalaska neophodno je realizovati određene faze u postupku ispitivanja prijave. Poverljivi pronalazak se ne objavljuje, a pronalazač, nakon priznavanja patenta, u skladu sa zakonskim propisima, ima određena moralna i materijalna prava. / Every invention established to be of significance for defense or security of the Republic of Serbia is considered to be a classified invention. For the purpose of patent protection of classified inventions, a confidential application must be submitted to a relevant defense authority having the exclusive right to deal with classified inventions3. An organizational unit competent for scientific and innovation issues carries out the examination of classified patent applications. In order to evaluate classification of the submitted invention, regarding its significance for defense or security of the country as well as to make the final decision on the application, the examination procedure should be carried out through several phases. A classified invention is not to be published and once the patent has been approved, the inventor enjoys moral and material rights in accordance with law.

  13. 14 CFR 1213.106 - Preventing release of classified information to the media.

    Science.gov (United States)

    2010-01-01

    ... ADMINISTRATION RELEASE OF INFORMATION TO NEWS AND INFORMATION MEDIA § 1213.106 Preventing release of classified... interviews, audio/visual) to the news media is prohibited. The disclosure of classified information to unauthorized individuals may be cause for prosecution and/or disciplinary action against the NASA employee...

  14. Classifying galaxy spectra at 0.5 < z < 1 with self-organizing maps

    Science.gov (United States)

    Rahmani, S.; Teimoorinia, H.; Barmby, P.

    2018-05-01

    The spectrum of a galaxy contains information about its physical properties. Classifying spectra using templates helps elucidate the nature of a galaxy's energy sources. In this paper, we investigate the use of self-organizing maps in classifying galaxy spectra against templates. We trained semi-supervised self-organizing map networks using a set of templates covering the wavelength range from far ultraviolet to near infrared. The trained networks were used to classify the spectra of a sample of 142 galaxies with 0.5 K-means clustering, a supervised neural network, and chi-squared minimization. Spectra corresponding to quiescent galaxies were more likely to be classified similarly by all methods while starburst spectra showed more variability. Compared to classification using chi-squared minimization or the supervised neural network, the galaxies classed together by the self-organizing map had more similar spectra. The class ordering provided by the one-dimensional self-organizing maps corresponds to an ordering in physical properties, a potentially important feature for the exploration of large datasets.

  15. Fruit removal of a wild tomato, Solanum granulosoleprosum Dunal (Solanaceae, by birds, bats and non-flying mammals in an urban Brazilian environment

    Directory of Open Access Journals (Sweden)

    Cáceres Nilton Carlos

    2003-01-01

    Full Text Available A study of removal of fruits of the wild tomato, Solanum granulosoleprosum Dunal (N = 5 plants, by vertebrates was carried out in an urban environment of southern Brazil from January to May 1997 and February 1998. To verify diurnal and nocturnal removals, fruits were counted in several fruit bunches, being classified by size and color. Diurnal observations were made on plants to verify bird removal. A mist net was placed among the plants from the evening to 23:00 h to verify bat consumption. Live traps baited with S. granulosoleprosum fruits were placed on the ground among plants to verify terrestrial removers. On average it was found two ripe fruits available per bunch/day, but unripe, small, fruits were dominant (70%. Nocturnal mammals and birds-diurnal mammals partitioned fruits similarly. Bats removing fruits were Artibeus lituratus (Olfers, 1818, Pygoderma bilabiatum (Wagner, 1843 and Sturnira lilium (E. Geoffroy, 1810. Birds were Saltator similis Lafresnaye & d'Orbigny, 1837 and Thraupis sayaca (Linnaeus, 1766. Terrestrial mammals were a marsupial and three rodent species. Except for rodents, these vertebrates must be promoting the seed dispersal of S. granulosoleprosum seeds in disturbed mixed forests of southern Brazil.

  16. Neural Network Classifier Based on Growing Hyperspheres

    Czech Academy of Sciences Publication Activity Database

    Jiřina Jr., Marcel; Jiřina, Marcel

    2000-01-01

    Roč. 10, č. 3 (2000), s. 417-428 ISSN 1210-0552. [Neural Network World 2000. Prague, 09.07.2000-12.07.2000] Grant - others:MŠMT ČR(CZ) VS96047; MPO(CZ) RP-4210 Institutional research plan: AV0Z1030915 Keywords : neural network * classifier * hyperspheres * big -dimensional data Subject RIV: BA - General Mathematics

  17. Electronic Structure of Au25 Clusters: Between Discrete and Continuous

    KAUST Repository

    Katsiev, Khabiboulakh

    2016-07-15

    Here, an approach based on synchrotron resonant photoemission is emplyed to explore the transition between quantization and hybridization of the electronic structure in atomically precise ligand-stabilized nanoparticles. While the presence of ligands maintains quantization in Au25 clusters, their removal renders increased hybridization of the electronic states at the vicinity of the Fermi level. These observations are supported by DFT studies.

  18. Electronic Structure of Au25 Clusters: Between Discrete and Continuous

    KAUST Repository

    Katsiev, Khabiboulakh; Lozova, Nataliya; Wang, Lu; Katla, Saikrishna; Li, Ruipeng; Mei, Wai Ning; Skrabalak, Sara; Challa, Challa; Losovyj, Yaroslav

    2016-01-01

    Here, an approach based on synchrotron resonant photoemission is emplyed to explore the transition between quantization and hybridization of the electronic structure in atomically precise ligand-stabilized nanoparticles. While the presence of ligands maintains quantization in Au25 clusters, their removal renders increased hybridization of the electronic states at the vicinity of the Fermi level. These observations are supported by DFT studies.

  19. Inter-satellite calibration of FengYun 3 medium energy electron fluxes with POES electron measurements

    Science.gov (United States)

    Zhang, Yang; Ni, Binbin; Xiang, Zheng; Zhang, Xianguo; Zhang, Xiaoxin; Gu, Xudong; Fu, Song; Cao, Xing; Zou, Zhengyang

    2018-05-01

    We perform an L-shell dependent inter-satellite calibration of FengYun 3 medium energy electron measurements with POES measurements based on rough orbital conjunctions within 5 min × 0.1 L × 0.5 MLT. By comparing electron flux data between the U.S. Polar Orbiting Environmental Satellites (POES) and Chinese sun-synchronous satellites including FY-3B and FY-3C for a whole year of 2014, we attempt to remove less reliable data and evaluate systematic uncertainties associated with the FY-3B and FY-3C datasets, expecting to quantify the inter-satellite calibration factors for the 150-350 keV energy channel at L = 2-7. Compared to the POES data, the FY-3B and FY-3C data generally exhibit a similar trend of electron flux variations but more or less underestimate them within a factor of 5 for the medium electron energy 150-350 keV channel. Good consistency in the flux conjunctions after the inter-calibration procedures gives us certain confidence to generalize our method to calibrate electron flux measurements from various satellite instruments.

  20. Performance evaluation of various classifiers for color prediction of rice paddy plant leaf

    Science.gov (United States)

    Singh, Amandeep; Singh, Maninder Lal

    2016-11-01

    The food industry is one of the industries that uses machine vision for a nondestructive quality evaluation of the produce. These quality measuring systems and softwares are precalculated on the basis of various image-processing algorithms which generally use a particular type of classifier. These classifiers play a vital role in making the algorithms so intelligent that it can contribute its best while performing the said quality evaluations by translating the human perception into machine vision and hence machine learning. The crop of interest is rice, and the color of this crop indicates the health status of the plant. An enormous number of classifiers are available to solve the purpose of color prediction, but choosing the best among them is the focus of this paper. Performance of a total of 60 classifiers has been analyzed from the application point of view, and the results have been discussed. The motivation comes from the idea of providing a set of classifiers with excellent performance and implementing them on a single algorithm for the improvement of machine vision learning and, hence, associated applications.