Airborne MSS data processing for multichannel SWIR sensor

Energy Technology Data Exchange (ETDEWEB)

Urai, Minoru; Yamaguchi, Yasushi

1988-05-17

This paper describes the specification of an airborne multi-channel spectrum scanner (MSS) and data processing. MSS has 13 channels of frequencies in the visible - heat infrared region. The channels 1 - 3 correspond to a visible image, the channels 4, 5 to the absorption bands of iron oxides, the channels 6 - 9 (2.2 (m)m band) to the absorption bands of O-H group and carbonates, and the channels 10 - 13 to absorption bands in the heat infrared region. By the least squares residual (LSR) method, a mineral having an absorption band of 2.2 (m)m was further examined. As a result, the LSR image displayed an orange-colored portion. This portion was identified to correspond to epidote. Silica, which has an absorption band of 8 - 10 (m)m in the heat infrared region, was displayed in blue color. A high frequency resolution sensor has a great potential for discrimination and identification of minerals. (2 figs, 2 tabs, 2 refs)

[On-board medical support system (MSS) of flights of promising aerospace sets (design)].

Science.gov (United States)

Ushakov, I B; Bednenko, V S

2010-01-01

It was suggested as the main compositive fractions MSS to consider the base system of automated evaluation of blood redistribution (BR) in body means of crew members protection and prophylaxis (CMPP) of unfavourable effects of flight factors to organism and also the automated circuit of CMPP' control. The advanced MSS includes 4 original measuring channels for registration of the base physiologic indices (electrocardiogram, venous-arterial pulsegram of neck vessels, reogram of head, earlap vessels pulsegram) the dynamic of which allows to determine with the help of computer the BR-integral parameter. The CMPP automated control circuit unites the separate protecting means in common system and executes the individual selection of regimes and CM PP-composition in accord with, first of all, body reactions manifestation and, secondly, individual physiologic status of spaceman. As CMPP was selected the negative pressure production around lower body part. Approlation of constructed active laboratory engineering mock-up MSS has performed investigations with participation of 29 subjects (Volunteers) under the modeling of hemodynamic shifts, developing in human body in short-term antiorthostatic hypokinesia (-10 degrees), as well as, in combined effect of antiorthostatic hypokinesia (-10 degrees), Coriolis acceleration and optokinetic stimulation. Results of investigations have showed, that the use of advanced MSS gives the indices of operator professional activity on the average of 17-32% under the decrease of hemodynamic stressful.

Anne Fine

Directory of Open Access Journals (Sweden)

Philip Gaydon

2015-04-01

Full Text Available An interview with Anne Fine with an introduction and aside on the role of children’s literature in our lives and development, and our adult perceptions of the suitability of childhood reading material. Since graduating from Warwick in 1968 with a BA in Politics and History, Anne Fine has written over fifty books for children and eight for adults, won the Carnegie Medal twice (for Goggle-Eyes in 1989 and Flour Babies in 1992, been a highly commended runner-up three times (for Bill’s New Frock in 1989, The Tulip Touch in 1996, and Up on Cloud Nine in 2002, been shortlisted for the Hans Christian Andersen Award (the highest recognition available to a writer or illustrator of children’s books, 1998, undertaken the positon of Children’s Laureate (2001-2003, and been awarded an OBE for her services to literature (2003. Warwick presented Fine with an Honorary Doctorate in 2005. Philip Gaydon’s interview with Anne Fine was recorded as part of the ‘Voices of the University’ oral history project, co-ordinated by Warwick’s Institute of Advanced Study.

Ann Tenno salapaigad / Margit Tõnson

Index Scriptorium Estoniae

Tõnson, Margit, 1978-

2011-01-01

Fotograaf Ann Tenno aiandushuvist, pildistamisest maailma erinevates paikades. Uutest suundadest (fototöötlus, fractal art, soojuskaameraga pildistamine) tema loomingus. Katkendeid Ann Tenno 2010. aastal ilmunud proosaraamatust "Üle unepiiri"

The Mean Sea Surface DTU10mss - Comparison With Gps And Tide Gauges

DEFF Research Database (Denmark)

Andersen, Ole Baltazar; Knudsen, Per; Bondo, Torsten

2010-01-01

Satellite altimetry and the Global Position System (GPS) are conveniently given in the same reference frame and can therefore be used to construct a vertical reference surface for offshore navigation. Here a new Mean Sea Surface DTU10MSS is presented with a vertical accuracy better than 10 cm...... in most areas of the world confirmed by extensive comparison with GPS leveled tide gauges around Britain and Norway. It is proposed that this model is used as a global vertical reference. This paper briefly outlines the update of the previous DTU model to DTU10MSS and presents comparisons on GPS positions...

Annely Peebo kutsus presidendi kontserdile / Maria Ulfsak

Index Scriptorium Estoniae

Ulfsak, Maria, 1981-

2003-01-01

Laulja Anneli Peebo kohtus president Arnold Rüütliga, et anda üle kutse Andrea Bocelli ja Annely Peebo ühiskontserdile. Vt. samas: Andrea Bocelli ja Annely Peebo kontsert Tallinna lauluväljakul 23. augustil; Andrea Bocelli

Forest cover of North America in the 1970s mapped using Landsat MSS data

Science.gov (United States)

Feng, M.; Sexton, J. O.; Channan, S.; Townshend, J. R.

2015-12-01

The distribution and changes in Earth's forests impact hydrological, biogeochemical, and energy fluxes, as well as ecosystems' capacity to support biodiversity and human economies. Long-term records of forest cover are needed across a broad range of investigation, including climate and carbon-cycle modeling, hydrological studies, habitat analyzes, biological conservation, and land-use planning. Satellite-based observations enable mapping and monitoring of forests at ecologically and economically relevant resolutions and continental or even global extents. Following early forest-mapping efforts using coarser resolution remote sensing data such as the Advanced Very High Resolution Radiometer (AVHRR) and MODerate-resolution Imaging Spectroradiometer (MODIS), forests have been mapped regionally at developed by the Global Land Cover Facility (GLCF) as reference, we developed an automated approach to detect forests using MSS data by leveraging the multispectral and phenological characteristics of forests observed in MSS time-series. The forest-cover map is produced with layers representing the year of observation, detection of forest-cover change relative to 1990, and the uncertainty of forest-cover and -change layers. The approach has been implemented with open-source libraries to facilitate processing large volumes of Landsat MSS images on high-performance computing machines. As the first result of our global mapping effort, we present the forest cover for North America. More than 25,000 Landsat MSS scenes were processed to provide a 120-meter resolution forest cover for North America, which will be made publicly available on the GLCF website (http://www.landcover.org).

Identification of unique interactions between the flexible linker and the RecA-like domains of DEAD-box helicase Mss116

International Nuclear Information System (INIS)

Zhang, Yuan; Palla, Mirkó; Liao, Jung-Chi; Sun, Andrew

2013-01-01

DEAD-box RNA helicases are ATP-dependent proteins implicated in nearly all aspects of RNA metabolism. The yeast DEAD-box helicase Mss116 is unique in its functions of splicing group I and group II introns and activating mRNA translation, but the structural understanding of why it performs these unique functions remains unclear. Here we used sequence analysis and molecular dynamics simulation to identify residues in the flexible linker specific for yeast Mss116, potentially associated with its unique functions. We first identified residues that are 100% conserved in Mss116 of different species of the Saccharomycetaceae family. The amino acids of these conserved residues were then compared with the amino acids of the corresponding residue positions of other RNA helicases to identify residues that have distinct amino acids from other DEAD-box proteins. Four residues in the flexible linker, i.e. N334, E335, P336 and H339, are conserved and Mss116-specific. Molecular dynamics simulation was conducted for the wild-type Mss116 structure and mutant models to examine mutational effects of the linker on the conformational equilibrium. Relatively short MD simulation runs (within 20 ns) were enough for us to observe mutational effects, suggesting serious structural perturbations by these mutations. The mutation of E335 depletes the interactions between E335 and K95 in domain 1. The interactions between N334/P336 and N496/I497 of domain 2 are also abolished by mutation. Our results suggest that tight interactions between the Mss116-specific flexible linker and the two RecA-like domains may be mechanically required to crimp RNA for the unique RNA processes of yeast Mss116. (paper)

Identification of unique interactions between the flexible linker and the RecA-like domains of DEAD-box helicase Mss116

Science.gov (United States)

Zhang, Yuan; Palla, Mirkó; Sun, Andrew; Liao, Jung-Chi

2013-09-01

DEAD-box RNA helicases are ATP-dependent proteins implicated in nearly all aspects of RNA metabolism. The yeast DEAD-box helicase Mss116 is unique in its functions of splicing group I and group II introns and activating mRNA translation, but the structural understanding of why it performs these unique functions remains unclear. Here we used sequence analysis and molecular dynamics simulation to identify residues in the flexible linker specific for yeast Mss116, potentially associated with its unique functions. We first identified residues that are 100% conserved in Mss116 of different species of the Saccharomycetaceae family. The amino acids of these conserved residues were then compared with the amino acids of the corresponding residue positions of other RNA helicases to identify residues that have distinct amino acids from other DEAD-box proteins. Four residues in the flexible linker, i.e. N334, E335, P336 and H339, are conserved and Mss116-specific. Molecular dynamics simulation was conducted for the wild-type Mss116 structure and mutant models to examine mutational effects of the linker on the conformational equilibrium. Relatively short MD simulation runs (within 20 ns) were enough for us to observe mutational effects, suggesting serious structural perturbations by these mutations. The mutation of E335 depletes the interactions between E335 and K95 in domain 1. The interactions between N334/P336 and N496/I497 of domain 2 are also abolished by mutation. Our results suggest that tight interactions between the Mss116-specific flexible linker and the two RecA-like domains may be mechanically required to crimp RNA for the unique RNA processes of yeast Mss116.

Cassini Mission Sequence Subsystem (MSS)

Science.gov (United States)

Alland, Robert

2011-01-01

This paper describes my work with the Cassini Mission Sequence Subsystem (MSS) team during the summer of 2011. It gives some background on the motivation for this project and describes the expected benefit to the Cassini program. It then introduces the two tasks that I worked on - an automatic system auditing tool and a series of corrections to the Cassini Sequence Generator (SEQ_GEN) - and the specific objectives these tasks were to accomplish. Next, it details the approach I took to meet these objectives and the results of this approach, followed by a discussion of how the outcome of the project compares with my initial expectations. The paper concludes with a summary of my experience working on this project, lists what the next steps are, and acknowledges the help of my Cassini colleagues.

Determining the rate of forest conversion in Mato Grosso, Brazil, using Landsat MSS and AVHRR data

Science.gov (United States)

Nelson, Ross; Horning, Ned; Stone, Thomas A.

1987-01-01

AVHRR-LAC thermal data and Landsat MSS and TM spectral data were used to estimate the rate of forest clearing in Mato Grosso, Brazil, between 1981 and 1984. The Brazilian state was stratified into forest and nonforest. A list sampling procedure was used in the forest stratum to select Landsat MSS scenes for processing based on estimates of fire activity in the scenes. Fire activity in 1984 was estimated using AVHRR-LAC thermal data. State-wide estimates of forest conversion indicate that between 1981 and 1984, 353,966 ha + or - 77,000 ha (0.4 percent of the state area) were converted per year. No evidence of reforestation was found in this digital sample. The relationship between forest clearing rate (based on MSS-TM analysis) and fire activity (estimated using AVHRR data) was noisy (R-squared = 0.41). The results suggest that AVHRR data may be put to better use as a stratification tool than as a subsidiary variable in list sampling.

Super capacitor modeling with artificial neural network (ANN)

Energy Technology Data Exchange (ETDEWEB)

Marie-Francoise, J.N.; Gualous, H.; Berthon, A. [Universite de Franche-Comte, Lab. en Electronique, Electrotechnique et Systemes (L2ES), UTBM, INRETS (LRE T31) 90 - Belfort (France)

2004-07-01

This paper presents super-capacitors modeling using Artificial Neural Network (ANN). The principle consists on a black box nonlinear multiple inputs single output (MISO) model. The system inputs are temperature and current, the output is the super-capacitor voltage. The learning and the validation of the ANN model from experimental charge and discharge of super-capacitor establish the relationship between inputs and output. The learning and the validation of the ANN model use experimental results of 2700 F, 3700 F and a super-capacitor pack. Once the network is trained, the ANN model can predict the super-capacitor behaviour with temperature variations. The update parameters of the ANN model are performed thanks to Levenberg-Marquardt method in order to minimize the error between the output of the system and the predicted output. The obtained results with the ANN model of super-capacitor and experimental ones are in good agreement. (authors)

Anne-Mette Langes plan for ADHD kongressen

DEFF Research Database (Denmark)

Lange, Anne-Mette

2017-01-01

http://medicinsktidsskrift.dk/behandlinger/psykiatri/699-anne-mette-langes-plan-for-adhd-kongressen.html......http://medicinsktidsskrift.dk/behandlinger/psykiatri/699-anne-mette-langes-plan-for-adhd-kongressen.html...

2011 : Qu'elle année !

CERN Multimedia

Staff Association

2012-01-01

« Quelle année ! Et quelle fin d’année ! La star de l’année a été le LHC, avec ses expériences, qui une fois de plus ont été sous les feux de la rampe. Mais on doit aussi citer toute une troupe d’acteurs importants, dans des domaines aussi différents que l’antimatière et l’expérience CLOUD. » Voilà ce que le Directeur général nous a écrit le 20 décembre dans son message avec ses vœux de fin d’année. Sans oublier, bien sûr, les fameux neutrinos hyperrapides vers Gran Sasso qui ont mis le CERN sur le devant de la scène mondiale. Ces succès qui font la fierté et la force de l’Organisation ont été rendus possibles «&...

Feature Selection and ANN Solar Power Prediction

Directory of Open Access Journals (Sweden)

Daniel O’Leary

2017-01-01

Full Text Available A novel method of solar power forecasting for individuals and small businesses is developed in this paper based on machine learning, image processing, and acoustic classification techniques. Increases in the production of solar power at the consumer level require automated forecasting systems to minimize loss, cost, and environmental impact for homes and businesses that produce and consume power (prosumers. These new participants in the energy market, prosumers, require new artificial neural network (ANN performance tuning techniques to create accurate ANN forecasts. Input masking, an ANN tuning technique developed for acoustic signal classification and image edge detection, is applied to prosumer solar data to improve prosumer forecast accuracy over traditional macrogrid ANN performance tuning techniques. ANN inputs tailor time-of-day masking based on error clustering in the time domain. Results show an improvement in prediction to target correlation, the R2 value, lowering inaccuracy of sample predictions by 14.4%, with corresponding drops in mean average error of 5.37% and root mean squared error of 6.83%.

Biogas engine performance estimation using ANN

Directory of Open Access Journals (Sweden)

Yusuf Kurtgoz

2017-12-01

Full Text Available Artificial neural network (ANN method was used to estimate the thermal efficiency (TE, brake specific fuel consumption (BSFC and volumetric efficiency (VE values of a biogas engine with spark ignition at different methane (CH4 ratios and engine load values. For this purpose, the biogas used in the biogas engine was produced by the anaerobic fermentation method from bovine manure and different CH4 contents (51%, 57%, 87% were obtained by purification of CO2 and H2S. The data used in the ANN models were obtained experimentally from a 4-stroke four-cylinder, spark ignition engine, at constant speed for different load and CH4 ratios. Using some of the obtained experimental data, ANN models were developed, and the rest was used to test the developed models. In the ANN models, the CH4 ratio of the fuel, engine load, inlet air temperature (Tin, air fuel ratio and the maximum cylinder pressure are chosen as the input parameters. TE, BSFC and VE are used as the output parameters. Root mean square error (RMSE, mean absolute percentage error (MAPE and correlation coefficient (R performance indicators are used to compare measured and predicted values. It has been shown that ANN models give good results in spark ignition biogas engines with high correlation and low error rates for TE, BSFC and VE values.

Obituary: Anne Barbara Underhill, 1920-2003

Science.gov (United States)

Roman, Nancy Grace

2003-12-01

Anne was born in Vancouver, British Columbia on 12 June 1920. Her parents were Frederic Clare Underhill, a civil engineer and Irene Anna (née Creery) Underhill. She had a twin brother and three younger brothers. As a young girl she was active in Girl Guides and graduated from high school winning the Lieutenant Governor's medal as one of the top students in the Province. She also excelled in high school sports. Her mother died when Anne was 18 and, while undertaking her university studies, Anne assisted in raising her younger brothers. Her twin brother was killed in Italy during World War II (1944), a loss that Anne felt deeply. Possibly because of fighting to get ahead in astronomy, a field overwhelming male when she started, she frequently appeared combative. At the University of British Columbia, Anne obtained a BA (honors) in Chemistry (1942), followed by a MA in 1944. After working for the NRC in Montreal for a year, she studied at the University of Toronto prior to entering the University of Chicago in 1946 to obtain her PhD. Her thesis was the first model computed for a multi-layered stellar atmosphere (1948). During this time she worked with Otto Struve, developing a lifetime interest in hot stars and the analysis of their high dispersion spectra. She received two fellowships from the University Women of Canada. She received a U.S. National Research Fellowship to work at the Copenhagen Observatory, and upon its completion, she returned to British Columbia to work at the Dominion Astrophysical Observatory as a research scientist from 1949--1962. During this period she spent a year at Harvard University as a visiting professor and at Princeton where she used their advanced computer to write the first code for modeling stellar atmospheres. Anne was invited to the University of Utrecht (Netherlands) as a full professor in 1962. She was an excellent teacher, well liked by the students in her classes, and by the many individuals that she guided throughout her

Anneli Randla kaitses doktorikraadi Cambridge'is / Anneli Randla ; interv. Reet Varblane

Index Scriptorium Estoniae

Randla, Anneli, 1970-

1999-01-01

5. mail kaitses Cambridge'is esimese eesti kunstiteadlasena doktorikraadi Anneli Randla. Töö teema: kerjusmungaordukloostrite arhitektuur Põhja-Euroopas. Juhendaja dr. Deborah Howard. Doktorikraadile esitatavatest nõudmistest, doktoritöö kaitsmisest, magistrikraadi kaitsnu õppimisvõimalustest Cambridge's.

Somatic mutation profiles of MSI and MSS colorectal cancer identified by whole exome next generation sequencing and bioinformatics analysis.

Directory of Open Access Journals (Sweden)

Bernd Timmermann

Full Text Available BACKGROUND: Colorectal cancer (CRC is with approximately 1 million cases the third most common cancer worldwide. Extensive research is ongoing to decipher the underlying genetic patterns with the hope to improve early cancer diagnosis and treatment. In this direction, the recent progress in next generation sequencing technologies has revolutionized the field of cancer genomics. However, one caveat of these studies remains the large amount of genetic variations identified and their interpretation. METHODOLOGY/PRINCIPAL FINDINGS: Here we present the first work on whole exome NGS of primary colon cancers. We performed 454 whole exome pyrosequencing of tumor as well as adjacent not affected normal colonic tissue from microsatellite stable (MSS and microsatellite instable (MSI colon cancer patients and identified more than 50,000 small nucleotide variations for each tissue. According to predictions based on MSS and MSI pathomechanisms we identified eight times more somatic non-synonymous variations in MSI cancers than in MSS and we were able to reproduce the result in four additional CRCs. Our bioinformatics filtering approach narrowed down the rate of most significant mutations to 359 for MSI and 45 for MSS CRCs with predicted altered protein functions. In both CRCs, MSI and MSS, we found somatic mutations in the intracellular kinase domain of bone morphogenetic protein receptor 1A, BMPR1A, a gene where so far germline mutations are associated with juvenile polyposis syndrome, and show that the mutations functionally impair the protein function. CONCLUSIONS/SIGNIFICANCE: We conclude that with deep sequencing of tumor exomes one may be able to predict the microsatellite status of CRC and in addition identify potentially clinically relevant mutations.

Ann tuleb Rakverest Võrru

Index Scriptorium Estoniae

2009-01-01

Võru kultuurimajas Kannel etendub 17. aprillil Rakvere teatri noortelavastus "Kuidas elad? ...Ann?!" Aidi Valliku jutustuse põhjal. Lavastaja Sven Heiberg. Mängivad ka Viljandi Kultuuriakadeemia teatritudengid

Uma biblioteca de pontos de controle para imagens MSS Landsat

OpenAIRE

Fernando Augusto Mitsuo Ii

1985-01-01

O objetivo deste trabalho e desenvolver um sistema para criacao, manutencao e gerenciamento de uma biblioteca de pontos de controle para imagens MSS Landsat. Um ponto de controle e uma caracteristica fisicamente detectavel numa cena, cuja localizacao geodesica e precisamente conhecida. O uso destes pontos e de fundamental importancia num sistema de correcao geometrica de imagens de satelite. A biblioteca permitira que pontos de controle pertencentes a uma dada cena sejam recuperados de uma ma...

Anne Veski : "Ju siis ei ole minu rahvusvaheline kuulsus meie presidendi kõrvu jõudnud" / Anne Veski ; interv. Tiia Linnard

Index Scriptorium Estoniae

Veski, Anne, 1956-

2008-01-01

Laulja Anne Veski arutlusi kontserttegevusest Venemaal ja elust Eestis. Muuhulgas on juttu ka sellest, et Anne Veskit pole kunagi kutsutud presidendi iseseisvuspäeva vastuvõtule. Ilmunud ka: Severnoje Poberezhje 20. märts 2008, lk. 6

A 10-bit 120-MS/s pipelined ADC with improved switch and layout scaling strategy

International Nuclear Information System (INIS)

Zhou Jia; Xu Lili; Li Fule; Wang Zhihua

2015-01-01

A 10 bit, 120 MS/s two-channel pipelined analog-to digital converter (ADC) is presented. The ADC is featured with improved switch by using the body effect to improve its conduction performance. A scaling down strategy is proposed to get more efficiency in the OTAs layout design. Implemented in a 0.18-μm CMOS technology, the ADC's prototype occupied an area of 2.05 × 1.83 mm 2 . With a sampling rate of 120-MS/s and an input of 4.9 MHz, the ADC achieves a spurious-free-dynamic range of 74.32 dB and signal-to-noise-and-distortion ratio of 55.34 dB, while consuming 220-mW/channel at 3-V supply. (paper)

An 8 bit 1 MS/s SAR ADC with 7.72-ENOB

Science.gov (United States)

Duan, Jihai; Zhu, Zhiyong; Deng, Jinli; Xu, Weilin

2017-08-01

This paper presents a low power 8-bit 1 MS/s SAR ADC with 7.72-bit ENOB. Without an op-amp, an improved segmented capacitor DAC is proposed to reduce the capacitance and the chip area. A dynamic latch comparator with output offset voltage storage technology is used to improve the precision. Adding an extra positive feedback in the latch is to increase the speed. What is more, two pairs of CMOS switches are utilized to eliminate the kickback noise introduced by the latch. The proposed SAR ADC was fabricated in SMIC 0.18 {{μ }}{{m}} CMOS technology. The measured results show that this design achieves an SFDR of 61.8 dB and an ENOB of 7.72 bits, and it consumes 67.5 μW with the FOM of 312 fJ/conversion-step at 1 MS/s sample under 1.8 V power supply. Project supported by the National Natural Science Foundation of China (Nos. 61161003, 61264001, 61166004) and the Guangxi Key Laboratory of Precision Navigation Technology and Application Foundation (No. DH201501).

Mary Anne Chambers | IDRC - International Development Research ...

International Development Research Centre (IDRC) Digital Library (Canada)

A former Member of Provincial Parliament, Mary Anne served as Minister of Training, Colleges and Universities, and Minister of Children and Youth Services in the Government of Ontario. She is also a former senior vice-president of Scotiabank. A graduate of the University of Toronto, Mary Anne has received honorary ...

Results of agriclimatological studies using multiple satellite sensors like NOAA AVHRR; GMS IR and LANDSAT MSS and TM

International Nuclear Information System (INIS)

Choudhury, A.M.

1990-08-01

Bangladesh Space Research and Remote Sensing Organization (SPARRSO) routinely receives NOAA and GMS imagery and uses them in agrometeorological monitoring, it also uses LANDSAT MSS and TM data for this purpose. Analysis of multiple satellite sensor data shows advantages for high resolution sensors. However, in the ease of crop monitoring, a good correlation has been obtained between results obtained with NOAA AVHRR and LANDSAT MSS for vegetation index. Crop estimation has been made using all kinds of sensors and it has been found that higher resolution data always give more accurate results. (author). 3 refs

A 100 MS/s 9 bit 0.43 mW SAR ADC with custom capacitor array

Science.gov (United States)

Jingjing, Wang; Zemin, Feng; Rongjin, Xu; Chixiao, Chen; Fan, Ye; Jun, Xu; Junyan, Ren

2016-05-01

A low power 9 bit 100 MS/s successive approximation register analog-to-digital converter (SAR ADC) with custom capacitor array is presented. A brand-new 3-D MOM unit capacitor is used as the basic capacitor cell of this capacitor array. The unit capacitor has a capacitance of 1 fF. Besides, the advanced capacitor array structure and switch mode decrease the power consumption a lot. To verify the effectiveness of this low power design, the 9 bit 100 MS/s SAR ADC is implemented in TSMC IP9M 65 nm LP CMOS technology. The measurement results demonstrate that this design achieves an effective number of bits (ENOB) of 7.4 bit, a signal-to-noise plus distortion ratio (SNDR) of 46.40 dB and a spurious-free dynamic range (SFDR) of 62.31 dB at 100 MS/s with 1 MHz input. The SAR ADC core occupies an area of 0.030 mm2 and consumes 0.43 mW under a supply voltage of 1.2 V. The figure of merit (FOM) of the SAR ADC achieves 23.75 fJ/conv. Project supported by the National High-Tech Research and Development Program of China (No. 2013AA014101).

A 10MS/s 8-bit charge-redistribution ADC for hybrid pixel applications in 65m CMOS

CERN Document Server

Kishishita, T; Krüger, H; Koch, M; Germic, L; Wermes, N

2013-01-01

The design and measurement results of an 8-bit SAR ADC, based on a charge-redistribution DAC, are presented. This ADC is characterized by superior power efficiency and small area, realized by employing a lateral metal–metal capacitor array and a dynamic two-stage comparator. To avoid the need for a highspeed clock and its associated power consumption, an asynchronous logic was implemented in a logic control cell. A test chip has been developed in a 65 nm CMOS technology, including eight ADC channels with different layout flavors of the capacitor array, a transimpedance amplifier as a signal input structure, a serializer, and a custom-made LVDS driver for data transmission. The integral (INL) and differential (DNL) nonlinearities are measured below 0.5 LSB and 0.8 LSB, respectively, for the best channel operating at a sampling frequency of 10 MS/s. The area occupies 40 μm 70 μm for one ADC channel. The power consumption is estimated as 4 μW at 1 MS/s and 38 μW at 10 MS/s with a supply rail of 1.2 V. Th...

An ANN application for water quality forecasting.

Science.gov (United States)

Palani, Sundarambal; Liong, Shie-Yui; Tkalich, Pavel

2008-09-01

Rapid urban and coastal developments often witness deterioration of regional seawater quality. As part of the management process, it is important to assess the baseline characteristics of the marine environment so that sustainable development can be pursued. In this study, artificial neural networks (ANNs) were used to predict and forecast quantitative characteristics of water bodies. The true power and advantage of this method lie in its ability to (1) represent both linear and non-linear relationships and (2) learn these relationships directly from the data being modeled. The study focuses on Singapore coastal waters. The ANN model is built for quick assessment and forecasting of selected water quality variables at any location in the domain of interest. Respective variables measured at other locations serve as the input parameters. The variables of interest are salinity, temperature, dissolved oxygen, and chlorophyll-alpha. A time lag up to 2Delta(t) appeared to suffice to yield good simulation results. To validate the performance of the trained ANN, it was applied to an unseen data set from a station in the region. The results show the ANN's great potential to simulate water quality variables. Simulation accuracy, measured in the Nash-Sutcliffe coefficient of efficiency (R(2)), ranged from 0.8 to 0.9 for the training and overfitting test data. Thus, a trained ANN model may potentially provide simulated values for desired locations at which measured data are unavailable yet required for water quality models.

Final Technical Report, Wind Generator Project (Ann Arbor)

Energy Technology Data Exchange (ETDEWEB)

Geisler, Nathan [City of Ann Arbor, MI (United States)

2017-03-20

A Final Technical Report (57 pages) describing educational exhibits and devices focused on wind energy, and related outreach activities and programs. Project partnership includes the City of Ann Arbor, MI and the Ann Arbor Hands-on Museum, along with additional sub-recipients, and U.S. Department of Energy/Office of Energy Efficiency and Renewable Energy (EERE). Report relays key milestones and sub-tasks as well as numerous graphics and images of five (5) transportable wind energy demonstration devices and five (5) wind energy exhibits designed and constructed between 2014 and 2016 for transport and use by the Ann Arbor Hands-on Museum.

An 11-bit 200 MS/s subrange SAR ADC with low-cost integrated reference buffer

Science.gov (United States)

He, Xiuju; Gu, Xian; Li, Weitao; Jiang, Hanjun; Li, Fule; Wang, Zhihua

2017-10-01

This paper presents an 11-bit 200 MS/s subrange SAR ADC with an integrated reference buffer in 65 nm CMOS. The proposed ADC employs a 3.5-bit flash ADC for coarse conversion, and a compact timing scheme at the flash/SAR boundary to speed up the conversion. The flash decision is used to control charge compensating for the reference voltage to reduce its input-dependent fluctuation. Measurement results show that the fabricated ADC has achieved significant improvement by applying the reference charge compensation. In addition, the ADC achieves a maximum signal-to-noise-and-distortion ratio of 59.3 dB at 200 MS/s. It consumes 3.91 mW from a 1.2 V supply, including the reference buffer. Project supported by the Zhongxing Telecommunication Equipment Corporation and Beijing Microelectronics Technology Institute.

UCM BH MSS 133: catalogación de los once manuscritos encuadernados en este volumen facticio

Directory of Open Access Journals (Sweden)

Durán Barceló, Javier

2012-01-01

Full Text Available En 1878 Villa-Amil y Castro publicó el primer catálogo impreso de los manuscritos procedentes del Colegio de San Ildefonso de la Universidad de Alcalá de Henares. Para su trabajo Villa-Amil dependió estrechamente de las catalogaciones efectuadas antes en 1745 y de nuevo en 1800. Recientemente, Paul Oskar Kristeller ha puesto su atención en los manuscritos humanistas de esta colección; la cual es esencial para el estudio del humanismo en la universidad hispana del Renacimiento temprano. Desde este punto de vista se hace necesaria una nueva catalogación de los manuscritos del Colegio de San Ildefonso. Por ejemplo, el volumen facticio MSS 133 contiene once manuscritos de mediados del siglo XV entre los cuales se conserva el único testimonio de una de las obras latinas de Alfonso de Palencia. El objeto de este trabajo es una descripción bibliográfica más detallada de estos once manuscritos encuadernados en UCM BH MSS 133. In 1878 Villa-Amil y Castro published the first printed catalogue of the manuscript collection of the old Colegio de San Ildefonso at the University of Alcalá de Henares. In his work Villa-Amil followed closely the catalogues produced earlier in 1745 and again in 1800. More recently, Paul Oskar Kristeller has focused his interest on the humanistic manuscripts of this collection, as this library becomes essential in the study of humanism in the hispanic universities during the early Renaissance. From this point of view it is necessary a closer examination to the manuscripts belonging to the old Colegio de San Ildefonso. For example, volume MSS 133 contains eleven manuscritpts from the mid 15th century among them a unique testimony of a Latin composition by Alfonso de Palencia. The object of this paper is a more detailed bibliographical description of these eleven manuscripts in UCM BH MSS 133.

Anne Frank relaunched in the world of comics and graphic novels

NARCIS (Netherlands)

Ribbens, Kees

2017-01-01

Recently the Basel-based Anne Frank Fonds proudly presented the Graphic Diary of Anne Frank. The impression is created as if this is the first ever comic book version of Anne Frank’s narrative. This article shows that there were various predecessors.

Depolarization in Delivering Public Services? Impacts of Minimum Service Standards (MSS on the Quality of Health Services in Indonesia

Directory of Open Access Journals (Sweden)

Mohammad Roudo

2016-03-01

Full Text Available Abstract. Some scholars argue that decentralization policy tends to create polarization, i.e. an increase of inequality/disparity among districts. To deal with this problem, Minimum Service Standards (MSS were introduced as a key strategy in decentralizing Indonesia. In this research, we tried to find out through MSS performance measurements whether imposing standards can be effective in a decentralized system by seeking its impacts on polarization/depolarization in the delivery of public services, specifically in the health sector. This question is basically a response to the common criticism that decentralization is good to create equality between central government and local governments but often does not work to achieve equality among local governments. Using self-assessment data from a sample of 54 districts from 534 districts in Indonesia, from 2010 to 2013, we found that the existence of depolarization in the delivery of public services could potentially occur among regions by reducing the gap between their public service performance and the targets of MSS. We acknowledge that there are weaknesses in the validity of the self-assessment data, caused by a lack of knowledge and skills to execute the self-assessment according to the official guidelines, by the overrating of target achievements, as well as the lack of data from independent sources to confirm the self-assessment outcomes. We also acknowledge that differences in financial capacity are still the main determinant why one district is more successful in achieving the MSS targets compared to other districts. Keywords. Decentralization, Public Service, Minimum Standard Service

Use of feature extraction techniques for the texture and context information in ERTS imagery. [discrimination of land use categories in Kansas from MSS textural-spectral features

Science.gov (United States)

Haralick, R. M.; Kelly, G. L. (Principal Investigator); Bosley, R. J.

1973-01-01

The author has identified the following significant results. The land use category of subimage regions over Kansas within an MSS image can be identified with an accuracy of about 70% using the textural-spectral features of the multi-images from the four MSS bands.

A 10 MS/s 8-bit charge-redistribution ADC for hybrid pixel applications in 65 m CMOS

International Nuclear Information System (INIS)

Kishishita, Tetsuichi; Hemperek, Tomasz; Krüger, Hans; Koch, Manuel; Germic, Leonard; Wermes, Norbert

2013-01-01

The design and measurement results of an 8-bit SAR ADC, based on a charge-redistribution DAC, are presented. This ADC is characterized by superior power efficiency and small area, realized by employing a lateral metal–metal capacitor array and a dynamic two-stage comparator. To avoid the need for a high-speed clock and its associated power consumption, an asynchronous logic was implemented in a logic control cell. A test chip has been developed in a 65 nm CMOS technology, including eight ADC channels with different layout flavors of the capacitor array, a transimpedance amplifier as a signal input structure, a serializer, and a custom-made LVDS driver for data transmission. The integral (INL) and differential (DNL) nonlinearities are measured below 0.5 LSB and 0.8 LSB, respectively, for the best channel operating at a sampling frequency of 10 MS/s. The area occupies 40μm×70μm for one ADC channel. The power consumption is estimated as 4μW at 1 MS/s and 38μW at 10 MS/s with a supply rail of 1.2 V. These excellent performance features and the natural radiation hardness of the design, due to the thin gate oxide thickness of transistors, are very interesting for front-end electronics ICs of future hybrid-pixel detector systems

A 10 MS/s 8-bit charge-redistribution ADC for hybrid pixel applications in 65 m CMOS

Energy Technology Data Exchange (ETDEWEB)

Kishishita, Tetsuichi, E-mail: kisisita@physik.uni-bonn.de; Hemperek, Tomasz; Krüger, Hans; Koch, Manuel; Germic, Leonard; Wermes, Norbert

2013-12-21

The design and measurement results of an 8-bit SAR ADC, based on a charge-redistribution DAC, are presented. This ADC is characterized by superior power efficiency and small area, realized by employing a lateral metal–metal capacitor array and a dynamic two-stage comparator. To avoid the need for a high-speed clock and its associated power consumption, an asynchronous logic was implemented in a logic control cell. A test chip has been developed in a 65 nm CMOS technology, including eight ADC channels with different layout flavors of the capacitor array, a transimpedance amplifier as a signal input structure, a serializer, and a custom-made LVDS driver for data transmission. The integral (INL) and differential (DNL) nonlinearities are measured below 0.5 LSB and 0.8 LSB, respectively, for the best channel operating at a sampling frequency of 10 MS/s. The area occupies 40μm×70μm for one ADC channel. The power consumption is estimated as 4μW at 1 MS/s and 38μW at 10 MS/s with a supply rail of 1.2 V. These excellent performance features and the natural radiation hardness of the design, due to the thin gate oxide thickness of transistors, are very interesting for front-end electronics ICs of future hybrid-pixel detector systems.

[Anne Arold. Kontrastive Analyse...] / Paul Alvre

Index Scriptorium Estoniae

Alvre, Paul, 1921-2008

2001-01-01

Arvustus: Arold, Anne. Kontrastive analyse der Wortbildungsmuster im Deutschen und im Estnischen (am Beispiel der Aussehensadjektive). Tartu, 2000. (Dissertationes philologiae germanicae Universitatis Tartuensis)

Historia de los MSS BH 133 y 128 de Alfonso de Palencia

Directory of Open Access Journals (Sweden)

Durán Barceló, Javier

2012-07-01

Full Text Available El investigador que inspeccione los volúmenes UCM BH MSS 133 y 128 de Alfonso de Palencia encontrará un buen número de marcas y cotas librarias acumuladas a lo largo de su historia. Como veremos en este trabajo, estas signaturas tienen su correspondencia en los inventarios y catálogos de la biblioteca del Colegio de San Ildefonso desde 1720, 1745, 1800 y 1878. Además, la historia de estos manuscritos se puede rastrear hasta la fundación del Colegio mediante un examen analítico de los primitivos inventarios de la librería ildefonsina incluso más allá del año 1517.The researcher who inspects volumes UCM BH MSS 133 and 128 of Alfonso de Palencia will encounter a great variety of old call numbers and librarian marks accumulated throughout their history. As we will find out in this paper, these call numbers have also a parallel existence in the inventories and catalogues of the Library of the Colegio de San Ildefonso produced since 1720, 1745, 1800 y 1878. But the history of these manuscripts can be also traced back to the foundation of the College, as it is demonstrated by an analytical examination of the earlier Library inventories as far as 1517 and beyond.

Deforestation in Mwanza District, Malawi, from 1981 to 1992 as determined from Landsat MSS imagery

Science.gov (United States)

Andrew T. Hudak; Carol A. Wessman

2000-01-01

Malawi is critically short of fuelwood, the primary energy source for its poverty-stricken populace. Deforestation from 1981 to 1992 in Mwanza District in southern Malawi was assessed using Normalized Difference Vegetation Index (NDVI) values calculated from multitemporal Landsat Multispectral Scanner (MSS) images. A control site, where vegetation change was assumed to...

A preliminary study of the feasibility of detecting the floating macrophytes by means of digital processing of MSS/LANDSAT data

Science.gov (United States)

Valeriano, D. D. (Principal Investigator)

1984-01-01

The feasibility of mapping the floating macrophytes (mostly water hyacinth: (Eichornia crassipes) in the Salto Grande reservoir in Americana, SP, by means of digital processing of MSS/LANDSAT data is described. The area occupied by the macrophytes was extracted by exclusion after the merging of two thematic masks representing the area of vegetation free water surface. One of the masks was obtained from a date when the vegetal cover is insignificant, while the other represents a large infestation episode. The utilization of digital processing of MSS/LANDSAT data techniques for the documentation of macrophytes infestation is feasible only when the phenomenon occurs in large areas.

Optimising training data for ANNs with Genetic Algorithms

OpenAIRE

Kamp , R. G.; Savenije , H. H. G.

2006-01-01

International audience; Artificial Neural Networks (ANNs) have proved to be good modelling tools in hydrology for rainfall-runoff modelling and hydraulic flow modelling. Representative datasets are necessary for the training phase in which the ANN learns the model's input-output relations. Good and representative training data is not always available. In this publication Genetic Algorithms (GA) are used to optimise training datasets. The approach is tested with an existing hydraulic model in ...

Optimising training data for ANNs with Genetic Algorithms

OpenAIRE

R. G. Kamp; R. G. Kamp; H. H. G. Savenije

2006-01-01

Artificial Neural Networks (ANNs) have proved to be good modelling tools in hydrology for rainfall-runoff modelling and hydraulic flow modelling. Representative datasets are necessary for the training phase in which the ANN learns the model's input-output relations. Good and representative training data is not always available. In this publication Genetic Algorithms (GA) are used to optimise training datasets. The approach is tested with an existing hydraulic model in The Netherlands. An...

Assessment of ANN and SVM models for estimating normal direct irradiation (H_b)

International Nuclear Information System (INIS)

Santos, Cícero Manoel dos; Escobedo, João Francisco; Teramoto, Érico Tadao; Modenese Gorla da Silva, Silvia Helena

2016-01-01

Highlights: • The performance of SVM and ANN in estimating Normal Direct Irradiation (H_b) was evaluated. • 12 models using different input variables are developed (hourly and daily partitions). • The most relevant input variables for DNI are kt, H_s_c and insolation ratio (r′ = n/N). • Support Vector Machine (SVM) provides accurate estimates and outperforms the Artificial Neural Network (ANN). - Abstract: This study evaluates the estimation of hourly and daily normal direct irradiation (H_b) using machine learning techniques (ML): Artificial Neural Network (ANN) and Support Vector Machine (SVM). Time series of different meteorological variables measured over thirteen years in Botucatu were used for training and validating ANN and SVM. Seven different sets of input variables were tested and evaluated, which were chosen based on statistical models reported in the literature. Relative Mean Bias Error (rMBE), Relative Root Mean Square Error (rRMSE), determination coefficient (R"2) and “d” Willmott index were used to evaluate ANN and SVM models. When compared to statistical models which use the same set of input variables (R"2 between 0.22 and 0.78), ANN and SVM show higher values of R"2 (hourly models between 0.52 and 0.88; daily models between 0.42 and 0.91). Considering the input variables, atmospheric transmissivity of global radiation (kt), integrated solar constant (H_s_c) and insolation ratio (n/N, n is sunshine duration and N is photoperiod) were the most relevant in ANN and SVM models. The rMBE and rRMSE values in the two time partitions of SVM models are lower than those obtained with ANN. Hourly ANN and SVM models have higher rRMSE values than daily models. Optimal performance with hourly models was obtained with ANN4"h (rMBE = 12.24%, rRMSE = 23.99% and “d” = 0.96) and SVM4"h (rMBE = 1.75%, rRMSE = 20.10% and “d” = 0.96). Optimal performance with daily models was obtained with ANN2"d (rMBE = −3.09%, rRMSE = 18.95% and “d” = 0

RegnANN: Reverse Engineering Gene Networks using Artificial Neural Networks.

Directory of Open Access Journals (Sweden)

Marco Grimaldi

Full Text Available RegnANN is a novel method for reverse engineering gene networks based on an ensemble of multilayer perceptrons. The algorithm builds a regressor for each gene in the network, estimating its neighborhood independently. The overall network is obtained by joining all the neighborhoods. RegnANN makes no assumptions about the nature of the relationships between the variables, potentially capturing high-order and non linear dependencies between expression patterns. The evaluation focuses on synthetic data mimicking plausible submodules of larger networks and on biological data consisting of submodules of Escherichia coli. We consider Barabasi and Erdös-Rényi topologies together with two methods for data generation. We verify the effect of factors such as network size and amount of data to the accuracy of the inference algorithm. The accuracy scores obtained with RegnANN is methodically compared with the performance of three reference algorithms: ARACNE, CLR and KELLER. Our evaluation indicates that RegnANN compares favorably with the inference methods tested. The robustness of RegnANN, its ability to discover second order correlations and the agreement between results obtained with this new methods on both synthetic and biological data are promising and they stimulate its application to a wider range of problems.

Playing tag with ANN: boosted top identification with pattern recognition

International Nuclear Information System (INIS)

Almeida, Leandro G.; Backović, Mihailo; Cliche, Mathieu; Lee, Seung J.; Perelstein, Maxim

2015-01-01

Many searches for physics beyond the Standard Model at the Large Hadron Collider (LHC) rely on top tagging algorithms, which discriminate between boosted hadronic top quarks and the much more common jets initiated by light quarks and gluons. We note that the hadronic calorimeter (HCAL) effectively takes a “digital image" of each jet, with pixel intensities given by energy deposits in individual HCAL cells. Viewed in this way, top tagging becomes a canonical pattern recognition problem. With this motivation, we present a novel top tagging algorithm based on an Artificial Neural Network (ANN), one of the most popular approaches to pattern recognition. The ANN is trained on a large sample of boosted tops and light quark/gluon jets, and is then applied to independent test samples. The ANN tagger demonstrated excellent performance in a Monte Carlo study: for example, for jets with p T in the 1100–1200 GeV range, 60% top-tag efficiency can be achieved with a 4% mis-tag rate. We discuss the physical features of the jets identified by the ANN tagger as the most important for classification, as well as correlations between the ANN tagger and some of the familiar top-tagging observables and algorithms.

Playing tag with ANN: boosted top identification with pattern recognition

Energy Technology Data Exchange (ETDEWEB)

Almeida, Leandro G. [Institut de Biologie de l’École Normale Supérieure (IBENS), Inserm 1024- CNRS 8197,46 rue d’Ulm, 75005 Paris (France); Backović, Mihailo [Center for Cosmology, Particle Physics and Phenomenology - CP3,Universite Catholique de Louvain,Louvain-la-neuve (Belgium); Cliche, Mathieu [Laboratory for Elementary Particle Physics, Cornell University,Ithaca, NY 14853 (United States); Lee, Seung J. [Department of Physics, Korea Advanced Institute of Science and Technology,335 Gwahak-ro, Yuseong-gu, Daejeon 305-701 (Korea, Republic of); School of Physics, Korea Institute for Advanced Study,Seoul 130-722 (Korea, Republic of); Perelstein, Maxim [Laboratory for Elementary Particle Physics, Cornell University,Ithaca, NY 14853 (United States)

2015-07-17

Many searches for physics beyond the Standard Model at the Large Hadron Collider (LHC) rely on top tagging algorithms, which discriminate between boosted hadronic top quarks and the much more common jets initiated by light quarks and gluons. We note that the hadronic calorimeter (HCAL) effectively takes a “digital image' of each jet, with pixel intensities given by energy deposits in individual HCAL cells. Viewed in this way, top tagging becomes a canonical pattern recognition problem. With this motivation, we present a novel top tagging algorithm based on an Artificial Neural Network (ANN), one of the most popular approaches to pattern recognition. The ANN is trained on a large sample of boosted tops and light quark/gluon jets, and is then applied to independent test samples. The ANN tagger demonstrated excellent performance in a Monte Carlo study: for example, for jets with p{sub T} in the 1100–1200 GeV range, 60% top-tag efficiency can be achieved with a 4% mis-tag rate. We discuss the physical features of the jets identified by the ANN tagger as the most important for classification, as well as correlations between the ANN tagger and some of the familiar top-tagging observables and algorithms.

47 CFR 25.147 - Licensing provision for NGSO MSS feeder downlinks in the band 6700-6875 MHz.

Science.gov (United States)

2010-10-01

... 47 Telecommunication 2 2010-10-01 2010-10-01 false Licensing provision for NGSO MSS feeder downlinks in the band 6700-6875 MHz. 25.147 Section 25.147 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Applications and Licenses Space...

Hybrid LSA-ANN Based Home Energy Management Scheduling Controller for Residential Demand Response Strategy

Directory of Open Access Journals (Sweden)

Maytham S. Ahmed

2016-09-01

Full Text Available Demand response (DR program can shift peak time load to off-peak time, thereby reducing greenhouse gas emissions and allowing energy conservation. In this study, the home energy management scheduling controller of the residential DR strategy is proposed using the hybrid lightning search algorithm (LSA-based artificial neural network (ANN to predict the optimal ON/OFF status for home appliances. Consequently, the scheduled operation of several appliances is improved in terms of cost savings. In the proposed approach, a set of the most common residential appliances are modeled, and their activation is controlled by the hybrid LSA-ANN based home energy management scheduling controller. Four appliances, namely, air conditioner, water heater, refrigerator, and washing machine (WM, are developed by Matlab/Simulink according to customer preferences and priority of appliances. The ANN controller has to be tuned properly using suitable learning rate value and number of nodes in the hidden layers to schedule the appliances optimally. Given that finding proper ANN tuning parameters is difficult, the LSA optimization is hybridized with ANN to improve the ANN performances by selecting the optimum values of neurons in each hidden layer and learning rate. Therefore, the ON/OFF estimation accuracy by ANN can be improved. Results of the hybrid LSA-ANN are compared with those of hybrid particle swarm optimization (PSO based ANN to validate the developed algorithm. Results show that the hybrid LSA-ANN outperforms the hybrid PSO based ANN. The proposed scheduling algorithm can significantly reduce the peak-hour energy consumption during the DR event by up to 9.7138% considering four appliances per 7-h period.

Ado Vabbe preemia Anne Parmastole

Index Scriptorium Estoniae

2003-01-01

Tartu Kunstimajas Tartu kunsti aastalõpunäitus. Kujundaja Mari Nõmmela. Anne Parmastole A. Vabbe, Silja Salmistule E-Kunstisalongi, Lii Jürgensonile EDA, Jüri Marranile Wilde kohviku, Sami Makkonenile AS Vunder ja Tartu Õlletehase A. Le Coq ning Eda Lõhmusele AS Merko Tartu preemia

A low-voltage low-power 10-bit 200 MS/s pipelined ADC in 90 nm CMOS

NARCIS (Netherlands)

Abdinia, S.; Yavari, M.

2010-01-01

This paper presents a low-power 10-bit 200 MS/s pipelined ADC in a 90 nm CMOS technology with 1 V supply voltage. To decrease the power dissipation efficiently, a new architecture using a combination of two power reduction techniques named double-sampling and opamp-sharing has been used to reduce

Anne Veesaar astus Valgas üles uudses rollis / Jaan Rapp

Index Scriptorium Estoniae

Rapp, Jaan

2010-01-01

2010. aasta iga kuu viimasel reedel esitab näitlejanna Anne Veesaar Raadio Ruudus katkendeid Valgamaa kirjanike loomingust. 14. jaanuaril kohtumisel lugejatega rääkis Valgas sündinud näitlejanna oma elulooraamatust "Anne Veesaar : elus, see on kõige tähtsam", mille on kirja pannud Helen Eelrand, ja oma praegustest tegemistest

Kõnelused Tartus / Anne Untera

Index Scriptorium Estoniae

Untera, Anne, 1951-

2007-01-01

8.-10. V Tartus toimunud eesti, läti ja saksa kunstiteadlaste ühisseminarist. Alexander Knorre rääkis Karl August Senffi, Ilona Audere Friedrich Ludwig von Maydelli, Mai Levin Karl Alexander von Winkleri, Kristiana Abele Johann Walter-Kurau (1869-1932), Anne Untera Konstantin ja Sally von Kügelgeni, Epp Preem Julie Hagen-Schwartzi, Friedrich Gross Eduard von Gebhardti ja Katharina Hadding Ida Kerkoviuse (1879-1970) loomingust

Solar radiation modelling using ANNs for different climates in China

International Nuclear Information System (INIS)

Lam, Joseph C.; Wan, Kevin K.W.; Yang, Liu

2008-01-01

Artificial neural networks (ANNs) were used to develop prediction models for daily global solar radiation using measured sunshine duration for 40 cities covering nine major thermal climatic zones and sub-zones in China. Coefficients of determination (R 2 ) for all the 40 cities and nine climatic zones/sub-zones are 0.82 or higher, indicating reasonably strong correlation between daily solar radiation and the corresponding sunshine hours. Mean bias error (MBE) varies from -3.3 MJ/m 2 in Ruoqiang (cold climates) to 2.19 MJ/m 2 in Anyang (cold climates). Root mean square error (RMSE) ranges from 1.4 MJ/m 2 in Altay (severe cold climates) to 4.01 MJ/m 2 in Ruoqiang. The three principal statistics (i.e., R 2 , MBE and RMSE) of the climatic zone/sub-zone ANN models are very close to the corresponding zone/sub-zone averages of the individual city ANN models, suggesting that climatic zone ANN models could be used to estimate global solar radiation for locations within the respective zones/sub-zones where only measured sunshine duration data are available. (author)

LFC based adaptive PID controller using ANN and ANFIS techniques

Directory of Open Access Journals (Sweden)

Mohamed I. Mosaad

2014-12-01

Full Text Available This paper presents an adaptive PID Load Frequency Control (LFC for power systems using Neuro-Fuzzy Inference Systems (ANFIS and Artificial Neural Networks (ANN oriented by Genetic Algorithm (GA. PID controller parameters are tuned off-line by using GA to minimize integral error square over a wide-range of load variations. The values of PID controller parameters obtained from GA are used to train both ANFIS and ANN. Therefore, the two proposed techniques could, online, tune the PID controller parameters for optimal response at any other load point within the operating range. Testing of the developed techniques shows that the adaptive PID-LFC could preserve optimal performance over the whole loading range. Results signify superiority of ANFIS over ANN in terms of performance measures.

Flow forecast by SWAT model and ANN in Pracana basin, Portugal

NARCIS (Netherlands)

Demirel, M.C.; Venancio, Anabela; Kahya, Ercan

2009-01-01

This study provides a unique opportunity to analyze the issue of flow forecast based on the soil and water assessment tool (SWAT) and artificial neural network (ANN) models. In last two decades, the ANNs have been extensively applied to various water resources system problems. In this study, the

Identification of drought in Dhalai river watershed using MCDM and ANN models

Science.gov (United States)

Aher, Sainath; Shinde, Sambhaji; Guha, Shantamoy; Majumder, Mrinmoy

2017-03-01

An innovative approach for drought identification is developed using Multi-Criteria Decision Making (MCDM) and Artificial Neural Network (ANN) models from surveyed drought parameter data around the Dhalai river watershed in Tripura hinterlands, India. Total eight drought parameters, i.e., precipitation, soil moisture, evapotranspiration, vegetation canopy, cropping pattern, temperature, cultivated land, and groundwater level were obtained from expert, literature and cultivator survey. Then, the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) were used for weighting of parameters and Drought Index Identification (DII). Field data of weighted parameters in the meso scale Dhalai River watershed were collected and used to train the ANN model. The developed ANN model was used in the same watershed for identification of drought. Results indicate that the Limited-Memory Quasi-Newton algorithm was better than the commonly used training method. Results obtained from the ANN model shows the drought index developed from the study area ranges from 0.32 to 0.72. Overall analysis revealed that, with appropriate training, the ANN model can be used in the areas where the model is calibrated, or other areas where the range of input parameters is similar to the calibrated region for drought identification.

Application of MSS/LANDSAT images to the structural study of recent sedimentary areas: Campos Sedimentary Basin, Rio de Janeiro, Brazil

Science.gov (United States)

Parada, N. D. J. (Principal Investigator); Barbosa, M. P.

1983-01-01

Visual and computer aided interpretation of MSS/LANDSAT data identified linear and circular features which represent the ""reflexes'' of the crystalline basement structures in the Cenozoic sediments of the emergent part of the Campos Sedimentary Basin.

A 10-bit 50-MS/s subsampling pipelined ADC based on SMDAC and opamp sharing

Energy Technology Data Exchange (ETDEWEB)

Chen Lijie; Zhou Yumei; Wei Baoyue, E-mail: frankdhz@yahoo.com.cn [Institute of Microelectronics, Chinese Academy of Sciences, Beijing 100029 (China)

2010-11-15

This paper describes a 10-bit, 50-MS/s pipelined A/D converter (ADC) with proposed area- and power-efficient architecture. The conventional dedicated sample-hold-amplifier (SHA) is eliminated and the matching requirement between the first multiplying digital-to-analog converter (MDAC) and sub-ADC is also avoided by using the SHA merged with the first MDAC (SMDAC) architecture, which features low power and stabilization. Further reduction of power and area is achieved by sharing an opamp between two successive pipelined stages, in which the effect of opamp offset and crosstalk between stages is decreased. So the 10-bit pipelined ADC is realized using just four opamps. The ADC demonstrates a maximum signal-to-noise distortion ratio and spurious free dynamic range of 52.67 dB and 59.44 dB, respectively, with a Nyquist input at full sampling rate. Constant dynamic performance for input frequencies up to 49.7 MHz, which is the twofold Nyquist rate, is achieved at 50 MS/s. The ADC prototype only occupies an active area of 1.81 mm{sup 2} in a 0.35 {mu}m CMOS process, and consumes 133 mW when sampling at 50 MHz from a 3.3-V power supply.

Ann Arbor Session I: Breaking Ground.

Science.gov (United States)

Music Educators Journal, 1979

1979-01-01

Summarizes the first session of the National Symposium on the Applications of Psychology to the Teaching and Learning of Music held at Ann Arbor from October 30 to November 2, 1978. Sessions concerned auditory perception, motor learning, child development, memory and information processing, and affect and motivation. (SJL)

ANN based optimization of a solar assisted hybrid cooling system in Turkey

Energy Technology Data Exchange (ETDEWEB)

Ozgur, Arif; Yetik, Ozge; Arslan, Oguz [Mechanical Eng. Dept., Engineering Faculty, Dumlupinar University (Turkey)], email: maozgur@dpu.edu.tr, email: ozgeyetik@dpu.edu.tr, email: oarslan@dpu.edu.tr

2011-07-01

This study achieved optimization of a solar assisted hybrid cooling system with refrigerants such as R717, R141b, R134a and R123 using an artificial neural network (ANN) model based on average total solar radiation, ambient temperature, generator temperature, condenser temperature, intercooler temperature and fluid types. ANN is a new tool; it works rapidly and can thus be a solution for design and optimization of complex power cycles. A unique flexible ANN algorithm was introduced to evaluate the solar ejector cooling systems because of the nonlinearity of neural networks. The conclusion was that the best COPs value obtained with the ANN is 1.35 and COPc is 3.03 when the average total solar radiation, ambient temperature, generator temperature, condenser temperature, intercooler temperature and algorithm are respectively 674.72 W/m2, 17.9, 80, 15 and 13 degree celsius and LM with 14 neurons in single hidden layer, for R717.

A Hybrid FEM-ANN Approach for Slope Instability Prediction

Science.gov (United States)

Verma, A. K.; Singh, T. N.; Chauhan, Nikhil Kumar; Sarkar, K.

2016-09-01

Assessment of slope stability is one of the most critical aspects for the life of a slope. In any slope vulnerability appraisal, Factor Of Safety (FOS) is the widely accepted index to understand, how close or far a slope from the failure. In this work, an attempt has been made to simulate a road cut slope in a landslide prone area in Rudrapryag, Uttarakhand, India which lies near Himalayan geodynamic mountain belt. A combination of Finite Element Method (FEM) and Artificial Neural Network (ANN) has been adopted to predict FOS of the slope. In ANN, a three layer, feed- forward back-propagation neural network with one input layer and one hidden layer with three neurons and one output layer has been considered and trained using datasets generated from numerical analysis of the slope and validated with new set of field slope data. Mean absolute percentage error estimated as 1.04 with coefficient of correlation between the FOS of FEM and ANN as 0.973, which indicates that the system is very vigorous and fast to predict FOS for any slope.

Comparison of Conventional and ANN Models for River Flow Forecasting

Science.gov (United States)

Jain, A.; Ganti, R.

2011-12-01

Hydrological models are useful in many water resources applications such as flood control, irrigation and drainage, hydro power generation, water supply, erosion and sediment control, etc. Estimates of runoff are needed in many water resources planning, design development, operation and maintenance activities. River flow is generally estimated using time series or rainfall-runoff models. Recently, soft artificial intelligence tools such as Artificial Neural Networks (ANNs) have become popular for research purposes but have not been extensively adopted in operational hydrological forecasts. There is a strong need to develop ANN models based on real catchment data and compare them with the conventional models. In this paper, a comparative study has been carried out for river flow forecasting using the conventional and ANN models. Among the conventional models, multiple linear, and non linear regression, and time series models of auto regressive (AR) type have been developed. Feed forward neural network model structure trained using the back propagation algorithm, a gradient search method, was adopted. The daily river flow data derived from Godavari Basin @ Polavaram, Andhra Pradesh, India have been employed to develop all the models included here. Two inputs, flows at two past time steps, (Q(t-1) and Q(t-2)) were selected using partial auto correlation analysis for forecasting flow at time t, Q(t). A wide range of error statistics have been used to evaluate the performance of all the models developed in this study. It has been found that the regression and AR models performed comparably, and the ANN model performed the best amongst all the models investigated in this study. It is concluded that ANN model should be adopted in real catchments for hydrological modeling and forecasting.

Annäherung Approaching

Directory of Open Access Journals (Sweden)

Carola Hilmes

2007-03-01

Full Text Available Das von Stefan Moses zusammengestellte „Bilderbuch“ zeigt Fotos von Ilse Aichinger. Sie selbst kommt durch eine Reihe von Geschichten und Gedichten zu Wort. In diesen intimen Dialog werden auch die Leser/-innen einbezogen. Das ermöglicht Annäherung.This “Picture Book”, compiled by Stefan Moses, displays photographs of Ilse Aichinger. She is also given voice through a series of stories and poems. The reader is also drawn into this intimate dialogue, thus making it possible for image, text, and reader to converge.

ANN-based wavelet analysis for predicting electrical signal from photovoltaic power supply system

Energy Technology Data Exchange (ETDEWEB)

Mellit, A. [Medea Univ., Medea (Algeria). Inst. of Science Engineering, Dept. of Electronics

2007-07-01

This study was conducted to predict different electrical signals from a photovoltaic power supply system (PVPS) using an artificial neural networks (ANN) with wavelet analysis. It involved the creation of a database of electrical signals (PV-generator current, voltage, battery current voltage, regulator current and voltage) obtained from an experimental PVPS system installed in the south of Algeria. The potential applications were for sizing and analyzing the performance of PVPS systems; control of maximum power point tracker (MPPT) in order to deliver the maximum energy from the PV-array; prediction of the optimal configuration (PV-array and battery sizing) of PVPS systems; expert configuration of PV-systems; faults diagnosis; supervision; and, control and monitoring. First, based on the wavelet analysis each electrical signal was mapped in several time frequency domains. The PV-system was then divided into 3-subsystems corresponding to ANN-PV generator model, ANN-battery model, and ANN-regulator model. An example of day-by-day prediction for each electrical signal was presented. The results of the proposed approach were in good agreement with experimental results. In addition, the accuracy of the proposed approach was more satisfactory when only ANN was used. It was concluded that this methodology offers the possibility of developing a new expert configuration of PVPS by implementing the soft computing ANN-wavelet program with a digital signal processing (DSP) circuit. 26 refs., 1 tab., 5 figs.

Visual NNet: An Educational ANN's Simulation Environment Reusing Matlab Neural Networks Toolbox

Science.gov (United States)

Garcia-Roselló, Emilio; González-Dacosta, Jacinto; Lado, Maria J.; Méndez, Arturo J.; Garcia Pérez-Schofield, Baltasar; Ferrer, Fátima

2011-01-01

Artificial Neural Networks (ANN's) are nowadays a common subject in different curricula of graduate and postgraduate studies. Due to the complex algorithms involved and the dynamic nature of ANN's, simulation software has been commonly used to teach this subject. This software has usually been developed specifically for learning purposes, because…

Ehe seep Eesti moodi / Anneli Aasmäe

Index Scriptorium Estoniae

Aasmäe, Anneli, 1973-

2008-01-01

Produtsent Kristian Taska Kalev Spordis näidatav Venezuela seebiseriaali Eesti oludele mugandatud variant "Kalevi naised" : lavastaja Ingomar Vihman : osades Andrus Vaarik, Anne Reemann, Piret Kalda, Ken Saan jt.

The use of Landsat-4 MSS digital data in temporal data sets and the evaluation of scene-to-scene registration accuracy

Science.gov (United States)

Anderson, J. E.

1985-01-01

The MSS sensor on Landsat 4 is, in certain performance aspects, diferent from those of Landsats 1 through 3. These differences created some concern in the NASA research community as to whether individual data sets can be registered accurately enough to produce acceptable data sets for multitemporal data analysis. The use of Landsat 4 MSS digital data in temporal data sets is examined and a method is presented for estimating temporal registration accuracy based on the use of an X-Y digitizer and grey tone electrostatic plots. Results indicate that the RMS temporal registration errors are not significantly different from the temporal data sets generated using Landsat 4 and Landsat 2 data (33.35 meters) and the temporal data set constructed from two Landsat 2 data sets (33.61 meters). A derivation of the model used to evaluate the temporal registration is included.

Simulation model of ANN based maximum power point tracking controller for solar PV system

Energy Technology Data Exchange (ETDEWEB)

Rai, Anil K.; Singh, Bhupal [Department of Electrical and Electronics Engineering, Ajay Kumar Garg Engineering College, Ghaziabad 201009 (India); Kaushika, N.D.; Agarwal, Niti [School of Research and Development, Bharati Vidyapeeth College of Engineering, A-4 Paschim Vihar, New Delhi 110063 (India)

2011-02-15

In this paper the simulation model of an artificial neural network (ANN) based maximum power point tracking controller has been developed. The controller consists of an ANN tracker and the optimal control unit. The ANN tracker estimates the voltages and currents corresponding to a maximum power delivered by solar PV (photovoltaic) array for variable cell temperature and solar radiation. The cell temperature is considered as a function of ambient air temperature, wind speed and solar radiation. The tracker is trained employing a set of 124 patterns using the back propagation algorithm. The mean square error of tracker output and target values is set to be of the order of 10{sup -5} and the successful convergent of learning process takes 1281 epochs. The accuracy of the ANN tracker has been validated by employing different test data sets. The control unit uses the estimates of the ANN tracker to adjust the duty cycle of the chopper to optimum value needed for maximum power transfer to the specified load. (author)

Optimization of Nd: YAG Laser Marking of Alumina Ceramic Using RSM And ANN

International Nuclear Information System (INIS)

Peter, Josephine; Doloi, B.; Bhattacharyya, B.

2011-01-01

The present research papers deals with the artificial neural network (ANN) and the response surface methodology (RSM) based mathematical modeling and also an optimization analysis on marking characteristics on alumina ceramic. The experiments have been planned and carried out based on Design of Experiment (DOE). It also analyses the influence of the major laser marking process parameters and the optimal combination of laser marking process parametric setting has been obtained. The output of the RSM optimal data is validated through experimentation and ANN predictive model. A good agreement is observed between the results based on ANN predictive model and actual experimental observations.

Klaas ja mõis / Maie-Ann Raun

Index Scriptorium Estoniae

Raun, Maie-Ann, 1938-

2007-01-01

Klaasikunstinäitus "Ringkäik" Albu mõisas, kuraatorid Virve Kiil, Kati Kerstna, Kairi Orgusaar. Eksponeeritakse Tiina Sarapu, Mare Saare, Eeva Käsperi, Kai Kiudsoo-Värvi, Pilvi Ojamaa, Merle Bukoveci, Kalli Seina, Viivi-Ann Keerdo, Liisi Junolaineni, Kristiina Uslari, Ivo Lille töid

Prediction of Splitting Tensile Strength of Concrete Containing Zeolite and Diatomite by ANN

Directory of Open Access Journals (Sweden)

E. Gülbandılar

2017-01-01

Full Text Available This study was designed to investigate with two different artificial neural network (ANN prediction model for the behavior of concrete containing zeolite and diatomite. For purpose of constructing this model, 7 different mixes with 63 specimens of the 28, 56 and 90 days splitting tensile strength experimental results of concrete containing zeolite, diatomite, both zeolite and diatomite used in training and testing for ANN systems was gathered from the tests. The data used in the ANN models are arranged in a format of seven input parameters that cover the age of samples, Portland cement, zeolite, diatomite, aggregate, water and hyper plasticizer and an output parameter which is splitting tensile strength of concrete. In the model, the training and testing results have shown that two different ANN systems have strong potential as a feasible tool for predicting 28, 56 and 90 days the splitting tensile strength of concrete containing zeolite and diatomite.

Application of ANN-SCE model on the evaluation of automatic generation control performance

Energy Technology Data Exchange (ETDEWEB)

Chang-Chien, L.R.; Lo, C.S.; Lee, K.S. [National Cheng Kung Univ., Tainan, Taiwan (China)

2005-07-01

An accurate evaluation of load frequency control (LFC) performance is needed to balance minute-to-minute electricity generation and demand. In this study, an artificial neural network-based system control error (ANN-SCE) model was used to assess the performance of automatic generation controls (AGC). The model was used to identify system dynamics for control references in supplementing AGC logic. The artificial neural network control error model was used to track a single area's LFC dynamics in Taiwan. The model was used to gauge the impacts of regulation control. Results of the training, evaluating, and projecting processes showed that the ANN-SCE model could be algebraically decomposed into components corresponding to different impact factors. The SCE information obtained from testing of various AGC gains provided data for the creation of a new control approach. The ANN-SCE model was used in conjunction with load forecasting and scheduled generation data to create an ANN-SCE identifier. The model successfully simulated SCE dynamics. 13 refs., 10 figs.

Groundwater Pollution Source Identification using Linked ANN-Optimization Model

Science.gov (United States)

Ayaz, Md; Srivastava, Rajesh; Jain, Ashu

2014-05-01

Groundwater is the principal source of drinking water in several parts of the world. Contamination of groundwater has become a serious health and environmental problem today. Human activities including industrial and agricultural activities are generally responsible for this contamination. Identification of groundwater pollution source is a major step in groundwater pollution remediation. Complete knowledge of pollution source in terms of its source characteristics is essential to adopt an effective remediation strategy. Groundwater pollution source is said to be identified completely when the source characteristics - location, strength and release period - are known. Identification of unknown groundwater pollution source is an ill-posed inverse problem. It becomes more difficult for real field conditions, when the lag time between the first reading at observation well and the time at which the source becomes active is not known. We developed a linked ANN-Optimization model for complete identification of an unknown groundwater pollution source. The model comprises two parts- an optimization model and an ANN model. Decision variables of linked ANN-Optimization model contain source location and release period of pollution source. An objective function is formulated using the spatial and temporal data of observed and simulated concentrations, and then minimized to identify the pollution source parameters. In the formulation of the objective function, we require the lag time which is not known. An ANN model with one hidden layer is trained using Levenberg-Marquardt algorithm to find the lag time. Different combinations of source locations and release periods are used as inputs and lag time is obtained as the output. Performance of the proposed model is evaluated for two and three dimensional case with error-free and erroneous data. Erroneous data was generated by adding uniformly distributed random error (error level 0-10%) to the analytically computed concentration

Prediction of Film Cooling Effectiveness on a Gas Turbine Blade Leading Edge Using ANN and CFD

Science.gov (United States)

Dávalos, J. O.; García, J. C.; Urquiza, G.; Huicochea, A.; De Santiago, O.

2018-05-01

In this work, the area-averaged film cooling effectiveness (AAFCE) on a gas turbine blade leading edge was predicted by employing an artificial neural network (ANN) using as input variables: hole diameter, injection angle, blowing ratio, hole and columns pitch. The database used to train the network was built using computational fluid dynamics (CFD) based on a two level full factorial design of experiments. The CFD numerical model was validated with an experimental rig, where a first stage blade of a gas turbine was represented by a cylindrical specimen. The ANN architecture was composed of three layers with four neurons in hidden layer and Levenberg-Marquardt was selected as ANN optimization algorithm. The AAFCE was successfully predicted by the ANN with a regression coefficient R2<0.99 and a root mean square error RMSE=0.0038. The ANN weight coefficients were used to estimate the relative importance of the input parameters. Blowing ratio was the most influential parameter with relative importance of 40.36 % followed by hole diameter. Additionally, by using the ANN model, the relationship between input parameters was analyzed.

Quick and reliable estimation of power distribution in a PHWR by ANN

International Nuclear Information System (INIS)

Dubey, B.P.; Jagannathan, V.; Kataria, S.K.

1998-01-01

Knowledge of the distribution of power in all the channels of a Pressurised Heavy Water Reactor (PHWR) as a result of a perturbation caused by one or more of the regulating devices is very important from the operation and maintenance point of view of the reactor. Theoretical design codes available for this purpose take several minutes to calculate the channel power distribution on modern PCs. Artificial Neural networks (ANNs) have been employed in predicting channel power distribution of Indian PHWRs for any given configuration of regulating devices of the reactor. ANNs produce the result much faster and with good accuracy. This paper describes the methodology of ANN, its reliability, the validation range, and scope for its possible on-line use in the actual reactor

The Royal Summer Palace, Ferdinand I and Anne

Czech Academy of Sciences Publication Activity Database

Dobalová, Sylva

2015-01-01

Roč. 7, č. 2 (2015), s. 162-175 ISSN 1804-1132 Institutional support: RVO:68378033 Keywords : Anne of Jagiello * Prague Castle * Ferdinand I of Habsburg * olive tree * dynasticism Subject RIV: AL - Art, Architecture, Cultural Heritage

Comparison of ANN and RKS approaches to model SCC strength

Science.gov (United States)

Prakash, Aravind J.; Sathyan, Dhanya; Anand, K. B.; Aravind, N. R.

2018-02-01

Self compacting concrete (SCC) is a high performance concrete that has high flowability and can be used in heavily reinforced concrete members with minimal compaction segregation and bleeding. The mix proportioning of SCC is highly complex and large number of trials are required to get the mix with the desired properties resulting in the wastage of materials and time. The research on SCC has been highly empirical and no theoretical relationships have been developed between the mixture proportioning and engineering properties of SCC. In this work effectiveness of artificial neural network (ANN) and random kitchen sink algorithm(RKS) with regularized least square algorithm(RLS) in predicting the split tensile strength of the SCC is analysed. Random kitchen sink algorithm is used for mapping data to higher dimension and classification of this data is done using Regularized least square algorithm. The training and testing data for the algorithm was obtained experimentally using standard test procedures and materials available. Total of 40 trials were done which were used as the training and testing data. Trials were performed by varying the amount of fine aggregate, coarse aggregate, dosage and type of super plasticizer and water. Prediction accuracy of the ANN and RKS model is checked by comparing the RMSE value of both ANN and RKS. Analysis shows that eventhough the RKS model is good for large data set, its prediction accuracy is as good as conventional prediction method like ANN so the split tensile strength model developed by RKS can be used in industries for the proportioning of SCC with tailor made property.

Ilmus artiklikogumik "Eesti teadlased paguluses" / Anne Valmas

Index Scriptorium Estoniae

Valmas, Anne, 1941-2017

2009-01-01

TLÜ AR väliseesti kirjanduse keskuse ja TTÜ Raamatukogu koostöös 24.03.2009 toimunud konverentsist "Eesti teadlased paguluses", mis tutvustas väliseesti teadlaste osa maailmateaduses. Ettekannete põhjal valminud artiklikogumikust "Eesti teadlased paguluses", koostajad Vahur Mägi ja Anne Valmas. Tallinn : Tallinna Ülikooli Kirjastus, 2009

Perbandingan Metode ANN-PSO Dan ANN-GA Dalam Pemodelan Komposisi Pakan Kambing Peranakan Etawa (PE Untuk Optimasi Kandungan Gizi

Directory of Open Access Journals (Sweden)

Canny Amerilyse Caesar

2016-09-01

Abstract Milk is one of the animal protein sources which it contains all of the substances needed by human body. The main milk producer cattle in Indonesia is dairy cow, however its milk production has not fulfilled the society needs. The alternative is the goat, the Etawa crossbreed (PE. The high quality of milk nutrients content is greatly influenced by some factors one of them, is the food factor. The PE goat livestock division of the UPT Cattle Breeding and the Cattle Food Greenery in Singosari-Malang still faces the problem, it is the low ability in giving the food composition for PE goat. This flaw affects the quality of the produced milk. It needs the artificial science of the milk nutrients contain in order to determine the food composition to produce premium milk with the optimum nutrients contain. The writer uses the method of the Artificial Neural Network (ANN and the Particle Swarm Optimization (PSO to make the modeling of goat food in optimizing the content of goat milk nutrients. In the analysis of the examination that is done with the case of 36 kg goat weight, also the food type used is the 70 % Odot grass and 30% Raja grass can increase the nutrients contain of the protein milk for 0.707% and decrease the fat nutrients contain for 0.879%. If uses the method of Artificial Neural Network (ANN and Genethic Algorithm (GA can increase the nutriens contain of the protein for 0.0852% and decrease the fat nutients contain for 2.3254%.   Key Words : Goat Milk, Optimization, Artificial Neural Network (ANN, Particle Swarm Optimization (PSO, Genetic Algorithm (GA, the food nutrients contain.

Eesti NATO ukselävel / Mari-Ann Kelam

Index Scriptorium Estoniae

Kelam, Mari-Ann, 1946-

2002-01-01

Seda, et NATO liitumisläbirääkimistele kutsutavate seas on ka Eesti, saab veel tänagi pidada üheks meie iseseisva riikluse suursaavutuseks, kui mitte imeks, kirjutab Riigikogu liige Mari-Ann Kelam. Autor: Isamaaliit. Parlamendisaadik

A Sensitive ANN Based Differential Relay for Transformer Protection with Security against CT Saturation and Tap Changer Operation

OpenAIRE

KHORASHADI-ZADEH, Hassan; LI, Zuyi

2014-01-01

This paper presents an artificial neural network (ANN) based scheme for fault identification in power transformer protection. The proposed scheme is featured by the application of ANN to identifying system patterns, the unique choice of harmonics of positive sequence differential currents as ANN inputs, the effective handling of current transformer (CT) saturation with an ANN based approach, and the consideration of tap changer position for correcting secondary CT current. Performanc...

Inter-comparison of state-of-the-art MSS and geoid models in the Arctic Ocean

DEFF Research Database (Denmark)

Skourup, Henriette; Farrell, Sinead; Hendricks, Stefan

in errors in the estimated freeboard heights, especially in areas with a sparse lead distribution in consolidated ice conditions. Additionally these errors can impact ocean geostrophic current estimates and remaining biases in the models may impact longer-term, multi-sensor oceanographic time-series of sea......State-of-the-art Arctic Ocean mean sea surface (MSS) and geoid models are used to support sea ice freeboard estimation from satellite altimeters, and for oceanographic studies. However, errors in a given model in the high frequency domain, e.g. due to unresolved gravity features, can result...

47 CFR 25.257 - Special requirements for operations in the band 29.1-29.25 GHz between NGSO MSS and LMDS.

Science.gov (United States)

2010-10-01

... 47 Telecommunication 2 2010-10-01 2010-10-01 false Special requirements for operations in the band 29.1-29.25 GHz between NGSO MSS and LMDS. 25.257 Section 25.257 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Technical Standards § 25...

Igal mõisal on oma lugu / Mari-Ann Remmel

Index Scriptorium Estoniae

Remmel, Mari-Ann

2008-01-01

Kirjastuselt "Tänapäev" ilmus raamat "Mõisalegendid. Harjumaa", koostaja Mari-Ann Remmel, kujundaja Angelika Schneider. Kogumik sisaldab ka ajaloolist ning genealoogilist teavet mõisahoonete ning -omanike kohta

A page is turned with the departure of Anne-Sylvie Catherin

CERN Multimedia

Staff Association

2016-01-01

The Staff Association wants to thank Anne Sylvie Catherin for her achievements during her career at CERN, and in particular during her mandate of head of the Human Resources Department. Anne-Sylvie Catherin arrived at CERN as a lawyer specialized in labor law of International Organizations, and she brought along her knowledge, as well as an unparalleled energy and professionalism. The Staff Association has particularly appreciated her collaborative approach during discussions in the concertation process. This attitude has clearly contributed to the implementation of significant change in the management of human resources, while preserving social peace. We expect that the person who will succeed Anne-Sylvie Catherin will have the same constructive attitude, in respect of the concertation process, as well as a continuity in the definition and implementation of HR processes. Finally, we hope that the new head of HR will be able to develop a long-term vision for the Organization and its staff, measuring to the vi...

Many Saccharomyces cerevisiae Cell Wall Protein Encoding Genes Are Coregulated by Mss11, but Cellular Adhesion Phenotypes Appear Only Flo Protein Dependent.

Science.gov (United States)

Bester, Michael C; Jacobson, Dan; Bauer, Florian F

2012-01-01

The outer cell wall of the yeast Saccharomyces cerevisiae serves as the interface with the surrounding environment and directly affects cell-cell and cell-surface interactions. Many of these interactions are facilitated by specific adhesins that belong to the Flo protein family. Flo mannoproteins have been implicated in phenotypes such as flocculation, substrate adhesion, biofilm formation, and pseudohyphal growth. Genetic data strongly suggest that individual Flo proteins are responsible for many specific cellular adhesion phenotypes. However, it remains unclear whether such phenotypes are determined solely by the nature of the expressed FLO genes or rather as the result of a combination of FLO gene expression and other cell wall properties and cell wall proteins. Mss11 has been shown to be a central element of FLO1 and FLO11 gene regulation and acts together with the cAMP-PKA-dependent transcription factor Flo8. Here we use genome-wide transcription analysis to identify genes that are directly or indirectly regulated by Mss11. Interestingly, many of these genes encode cell wall mannoproteins, in particular, members of the TIR and DAN families. To examine whether these genes play a role in the adhesion properties associated with Mss11 expression, we assessed deletion mutants of these genes in wild-type and flo11Δ genetic backgrounds. This analysis shows that only FLO genes, in particular FLO1/10/11, appear to significantly impact on such phenotypes. Thus adhesion-related phenotypes are primarily dependent on the balance of FLO gene expression.

Process Control Strategies for Dual-Phase Steel Manufacturing Using ANN and ANFIS

Science.gov (United States)

Vafaeenezhad, H.; Ghanei, S.; Seyedein, S. H.; Beygi, H.; Mazinani, M.

2014-11-01

In this research, a comprehensive soft computational approach is presented for the analysis of the influencing parameters on manufacturing of dual-phase steels. A set of experimental data have been gathered to obtain the initial database used for the training and testing of both artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS). The parameters used in the strategy were intercritical annealing temperature, carbon content, and holding time which gives off martensite percentage as an output. A fraction of the data set was chosen to train both ANN and ANFIS, and the rest was put into practice to authenticate the act of the trained networks while seeing unseen data. To compare the obtained results, coefficient of determination and root mean squared error indexes were chosen. Using artificial intelligence methods, it is not necessary to consider and establish a preliminary mathematical model and formulate its affecting parameters on its definition. In conclusion, the martensite percentages corresponding to the manufacturing parameters can be determined prior to a production using these controlling algorithms. Although the results acquired from both ANN and ANFIS are very encouraging, the proposed ANFIS has enhanced performance over the ANN and takes better effect on cost-reduction profit.

Use of topographic and climatological models in a geographical data base to improve Landsat MSS classification for Olympic National Park

Science.gov (United States)

Cibula, William G.; Nyquist, Maurice O.

1987-01-01

An unsupervised computer classification of vegetation/landcover of Olympic National Park and surrounding environs was initially carried out using four bands of Landsat MSS data. The primary objective of the project was to derive a level of landcover classifications useful for park management applications while maintaining an acceptably high level of classification accuracy. Initially, nine generalized vegetation/landcover classes were derived. Overall classification accuracy was 91.7 percent. In an attempt to refine the level of classification, a geographic information system (GIS) approach was employed. Topographic data and watershed boundaries (inferred precipitation/temperature) data were registered with the Landsat MSS data. The resultant boolean operations yielded 21 vegetation/landcover classes while maintaining the same level of classification accuracy. The final classification provided much better identification and location of the major forest types within the park at the same high level of accuracy, and these met the project objective. This classification could now become inputs into a GIS system to help provide answers to park management coupled with other ancillary data programs such as fire management.

Anne-Marie Sargueil: ilu on kasulik / intervjueerinud Emilie Toomela

Index Scriptorium Estoniae

Sargueil, Anne-Marie

2015-01-01

Prantsuse Disainiinstituudi juht Anne-Marie Sargueil rääkis prantsuse ja skandinaavia disainist, prantslaste disainieelistustest, uutest suundadest disaini valdkonnas, Eesti Tarbekunsti- ja Disainimuuseumis avatud näitusest "20 prantsuse disainiikooni"

Application of ANN and fuzzy logic algorithms for streamflow ...

Indian Academy of Sciences (India)

1Department of Soil and Water Engineering, College of Technology and Engineering, Maharana Pratap. University of ... It was found that, ANN model performance improved with increasing .... algorithm uses supervised learning that provides.

Novel Formulation of Adaptive MPC as EKF Using ANN Model: Multiproduct Semibatch Polymerization Reactor Case Study.

Science.gov (United States)

Kamesh, Reddi; Rani, Kalipatnapu Yamuna

2017-12-01

In this paper, a novel formulation for nonlinear model predictive control (MPC) has been proposed incorporating the extended Kalman filter (EKF) control concept using a purely data-driven artificial neural network (ANN) model based on measurements for supervisory control. The proposed scheme consists of two modules focusing on online parameter estimation based on past measurements and control estimation over control horizon based on minimizing the deviation of model output predictions from set points along the prediction horizon. An industrial case study for temperature control of a multiproduct semibatch polymerization reactor posed as a challenge problem has been considered as a test bed to apply the proposed ANN-EKFMPC strategy at supervisory level as a cascade control configuration along with proportional integral controller [ANN-EKFMPC with PI (ANN-EKFMPC-PI)]. The proposed approach is formulated incorporating all aspects of MPC including move suppression factor for control effort minimization and constraint-handling capability including terminal constraints. The nominal stability analysis and offset-free tracking capabilities of the proposed controller are proved. Its performance is evaluated by comparison with a standard MPC-based cascade control approach using the same adaptive ANN model. The ANN-EKFMPC-PI control configuration has shown better controller performance in terms of temperature tracking, smoother input profiles, as well as constraint-handling ability compared with the ANN-MPC with PI approach for two products in summer and winter. The proposed scheme is found to be versatile although it is based on a purely data-driven model with online parameter estimation.

Kui vana on kunstnik? / Anneli Porri

Index Scriptorium Estoniae

Porri, Anneli, 1980-

2003-01-01

Rahvusvahelise kunstihariduse konverentsi "InSea on Sea" raames Kunstiakadeemia galeriis Karin Laansoo kureeritud Tallinna Kunstikooli õpilaste tööde näitus "MÄRKmed", Draakoni galeriis Mari Sobolevi kureeritud Viljandi Maagümnaasiumi kunstistuudio näitus "Sisseastumiseksam maailma", rahvusraamatukogus Anneli Porri kureeritud näitus "Kokkuvõte" EKA tänavuste lõpetajate töödest ja näitus "Leitud tagahoovist", Kullo galeriis rahvusvaheline näitus "Dialoog erinevuste vahel"

Light Detection and Ranging (LiDAR and Multispectral Scanner (MSS Studies Examine Coastal Environments Influenced by Mining

Directory of Open Access Journals (Sweden)

W. Charles Kerfoot

2014-01-01

Full Text Available There are numerous examples of past and present mine disposal into freshwater and marine coastal bays and riverine environments. Due to its high spatial resolution and extended water penetration, coastal light detection and ranging (LiDAR, coupled with multispectral scanning (MSS, has great promise for resolving disturbed shoreline features in low turbidity environments. Migrating mine tailings present serious issues for Lake Superior and coastal marine environments. Previous investigations in Lake Superior uncovered a metal-rich “halo” around the Keweenaw Peninsula, related to past copper mining practices. For over a century, waste rock migrating from shoreline tailing piles has moved along extensive stretches of coastline, compromising critical fish breeding grounds, damming stream outlets, transgressing into wetlands and along recreational beaches and suppressing benthic invertebrate communities. In Grand (Big Traverse Bay, Buffalo Reef is an important spawning area for lake trout and whitefish threatened by drifting tailings. The movement of tailings into Buffalo Reef cobble fields may interfere with the hatching of fish eggs and fry survival, either by filling in crevices where eggs are deposited or by toxic effects on eggs, newly hatched larvae or benthic communities. Here, we show that the coastal tailing migration is not “out of sight, out of mind”, but clearly revealed by using a combination of LiDAR and MSS techniques.

Modeling of an Aged Porous Silicon Humidity Sensor Using ANN Technique

Directory of Open Access Journals (Sweden)

Tarikul ISLAM

2006-10-01

Full Text Available Porous silicon (PS sensor based on capacitive technique used for measuring relative humidity has the advantages of low cost, ease of fabrication with controlled structure and CMOS compatibility. But the response of the sensor is nonlinear function of humidity and suffers from errors due to aging and stability. One adaptive linear (ADALINE ANN model has been developed to model the behavior of the sensor with a view to estimate these errors and compensate them. The response of the sensor is represented by third order polynomial basis function whose coefficients are determined by the ANN technique. The drift in sensor output due to aging of PS layer is also modeled by adapting the weights of the polynomial function. ANN based modeling is found to be more suitable than conventional physical modeling of PS humidity sensor in changing environment and drift due to aging. It helps online estimation of nonlinearity as well as monitoring of the fault of the PS humidity sensor using the coefficients of the model.

Artificial Neural Networks (ANNs for flood forecasting at Dongola Station in the River Nile, Sudan

Directory of Open Access Journals (Sweden)

Sulafa Hag Elsafi

2014-09-01

Full Text Available Heavy seasonal rains cause the River Nile in Sudan to overflow and flood the surroundings areas. The floods destroy houses, crops, roads, and basic infrastructure, resulting in the displacement of people. This study aimed to forecast the River Nile flow at Dongola Station in Sudan using an Artificial Neural Network (ANN as a modeling tool and validated the accuracy of the model against actual flow. The ANN model was formulated to simulate flows at a certain location in the river reach, based on flow at upstream locations. Different procedures were applied to predict flooding by the ANN. Readings from stations along the Blue Nile, White Nile, Main Nile, and River Atbara between 1965 and 2003 were used to predict the likelihood of flooding at Dongola Station. The analysis indicated that the ANN provides a reliable means of detecting the flood hazard in the River Nile.

Steni muinasjutuvõistluse võitjad selgunud / Ants Roos, Ann Roos

Index Scriptorium Estoniae

Roos, Ants

2008-01-01

Steni XVI muinasjutuvõistluse žüriisse kuulusid: Ann Roos, Ants Roos, Leelo Tungal, Krista Kumberg, Leida Olszak, Ülle Väljataga. Tulemused: I koht Siim Niinelaid, II koht Julius Air Kull, III koht Mihkel Rammu. Žürii eriauhinnad: Anna Kristin Peterson, Elis Ruus, Rain Hallikas, Mariliis Peterson, Marjaliisa Palu, Karl Kirsimäe, Margaret Pulk. Ergutusauhinnad: Karmel Klaus, Martti Kaljuste, Kristina Korell, Mirjam Võsaste, Mihkel Põder, Iirys Kalde, Miriam Jamul, Mari-Ann Mägi, Ketlin Saar, Liisbeth Kirss. Muud eriauhinnad said: Allan Läll, Berle Mees, Anett Kuuse, Karl Erik Kübarsepp, Grete Tamm, Siim Niinelaid, Kaisa Marie Sipelgas, Ellen Anett Põldmaa, Evelin Laul, Karl Laas, Karl Stamm, Kerli Retter

14-bit 100 MS/s 121 mW pipelined ADC

International Nuclear Information System (INIS)

Chen Yongzhen; Chen Chixiao; Feng Zemin; Ye Fan; Ren Junyan

2015-01-01

This paper presents a high-speed high-resolution pipelined ADC with low power and small area. The proposed ADC is designed based on the analysis of the stage scaling theory and the residual amplifiers are shared by two cascading MDACs to reduce power consumption. Shared op-amps with two split input paths are presented in this paper to eliminate the nonlinearity effects such as memory effect and crosstalk. Dynamic pre-amplified comparators are employed to decrease the static power consumption and suppress the kick-back in the comparators. This ADC is implemented in SMIC 0.18 μm CMOS process with an area of 3.1 mm 2 . With a sampling rate of 100 MS/s, spurious-free dynamic range (SFDR) and signal-to-noise plus distortion ratio (SNDR) of the ADC are 82.7 dB and 69.1 dB, respectively. For signals up to 100 MHz, the SFDR and SNDR achieve 81.4 dB and 65.8 dB. The power consumption is 121 mW with a 1.8 V supply voltage. (paper)

Mechanistic study on the nuclear modifier gene MSS1 mutation suppressing neomycin sensitivity of the mitochondrial 15S rRNA C1477G mutation in Saccharomyces cerevisiae.

Science.gov (United States)

Zhou, Qiyin; Wang, Wei; He, Xiangyu; Zhu, Xiaoyu; Shen, Yaoyao; Yu, Zhe; Wang, Xuexiang; Qi, Xuchen; Zhang, Xuan; Fan, Mingjie; Dai, Yu; Yang, Shuxu; Yan, Qingfeng

2014-01-01

The phenotypic manifestation of mitochondrial DNA (mtDNA) mutations can be modulated by nuclear genes and environmental factors. However, neither the interaction among these factors nor their underlying mechanisms are well understood. The yeast Saccharomyces cerevisiae mtDNA 15S rRNA C1477G mutation (PR) corresponds to the human 12S rRNA A1555G mutation. Here we report that a nuclear modifier gene mss1 mutation suppresses the neomycin-sensitivity phenotype of a yeast C1477G mutant in fermentable YPD medium. Functional assays show that the mitochondrial function of the yeast C1477G mutant was impaired severely in YPD medium with neomycin. Moreover, the mss1 mutation led to a significant increase in the steady-state level of HAP5 (heme activated protein), which greatly up-regulated the expression of glycolytic transcription factors RAP1, GCR1, and GCR2 and thus stimulated glycolysis. Furthermore, the high expression of the key glycolytic enzyme genes HXK2, PFK1 and PYK1 indicated that enhanced glycolysis not only compensated for the ATP reduction from oxidative phosphorylation (OXPHOS) in mitochondria, but also ensured the growth of the mss1(PR) mutant in YPD medium with neomycin. This study advances our understanding of the phenotypic manifestation of mtDNA mutations.

Luksuslik ruum kõigile : vestlus arhitekt Anne Lacatoniga = Luxury space for everyone : interview with Anne Lacaton / intervjueerinud Katrin Paadam

Index Scriptorium Estoniae

Lacaton, Anne, 1955-

2013-01-01

Prantsuse arhitekt Anne Lacaton oma büroo (Lacaton & Vassal, Frédéric Druot, 2011) linnaehituslikult uuendusliku projekti järgi ümber ehitatud 1960. aastate korterelamust Tour du Bois-le-Prêtre Pariisis, sotsiaalelamute ehitusest Prantsusmaal, 1960.-1970. aastatel ehitatud elamute taaskasutusega seotud probleemidest, rekonstrueerimise kasulikkusest võrreldes elamu lammutamise ja uuesti ehitamisega, linnas elavatele inimestele paremate elamistingimuste loomisest, linnaplaneerimisest

Using ANN and EPR models to predict carbon monoxide concentrations in urban area of Tabriz

Directory of Open Access Journals (Sweden)

Mohammad Shakerkhatibi

2015-09-01

Full Text Available Background: Forecasting of air pollutants has become a popular topic of environmental research today. For this purpose, the artificial neural network (AAN technique is widely used as a reliable method for forecasting air pollutants in urban areas. On the other hand, the evolutionary polynomial regression (EPR model has recently been used as a forecasting tool in some environmental issues. In this research, we compared the ability of these models to forecast carbon monoxide (CO concentrations in the urban area of Tabriz city. Methods: The dataset of CO concentrations measured at the fixed stations operated by the East Azerbaijan Environmental Office along with meteorological data obtained from the East Azerbaijan Meteorological Bureau from March 2007 to March 2013, were used as input for the ANN and EPR models. Results: Based on the results, the performance of ANN is more reliable in comparison with EPR. Using the ANN model, the correlation coefficient values at all monitoring stations were calculated above 0.85. Conversely, the R2 values for these stations were obtained <0.41 using the EPR model. Conclusion: The EPR model could not overcome the nonlinearities of input data. However, the ANN model displayed more accurate results compared to the EPR. Hence, the ANN models are robust tools for predicting air pollutant concentrations.

Predicting the Deflections of Micromachined Electrostatic Actuators Using Artificial Neural Network (ANN

Directory of Open Access Journals (Sweden)

Hing Wah LEE

2009-03-01

Full Text Available In this study, a general purpose Artificial Neural Network (ANN model based on the feed-forward back-propagation (FFBP algorithm has been used to predict the deflections of a micromachined structures actuated electrostatically under different loadings and geometrical parameters. A limited range of simulation results obtained via CoventorWare™ numerical software will be used initially to train the neural network via back-propagation algorithm. The micromachined structures considered in the analyses are diaphragm, fixed-fixed beams and cantilevers. ANN simulation results are compared with results obtained via CoventorWare™ simulations and existing analytical work for validation purpose. The proposed ANN model accurately predicts the deflections of the micromachined structures with great reduction of simulation efforts, establishing the method superiority. This method can be extended for applications in other sensors particularly for modeling sensors applying electrostatic actuation which are difficult in nature due to the inherent non-linearity of the electro-mechanical coupling response.

Ants Orasest ja Anne Lange monograafiast / Jüri Talvet

Index Scriptorium Estoniae

Talvet, Jüri, 1945-

2005-01-01

Arvustus: Oras, Ants. Luulekool. I, Apoloogia / koostajad Hando Runnel ja Jaak Rähesoo. Tartu : Ilmamaa, 2003 ; Oras, Ants. Luulekool II, Meistriklass. Tartu : Ilmamaa, 2004 ; Lange, Anne. Ants Oras : [kirjandusteadlane, -kriitik ja tõlkija (1900-1982)]. Tartu : Ilmamaa, 2004

Structural mapping from MSS-LANDSAT imagery: A proposed methodology for international geological correlation studies

Science.gov (United States)

Dejesusparada, N. (Principal Investigator); Crepani, E.; Martini, P. R.

1980-01-01

A methodology is proposed for international geological correlation studies based on LANDSAT-MSS imagery, Bullard's model of continental fit and compatible structural trends between Northeast Brazil and the West African counterpart. Six extensive lineaments in the Brazilian study area are mapped and discussed according to their regional behavior and in relation to the adjacent continental margin. Among the first conclusions, correlations were found between the Sobral Pedro II Lineament and the megafaults that surround the West African craton; and the Pernambuco Lineament with the Ngaurandere Linemanet in Cameroon. Ongoing research to complete the methodological stages includes the mapping of the West African structural framework, reconstruction of the pre-drift puzzle, and an analysis of the counterpart correlations.

Hiina tervendus / kommenteerivad Anne, Julia, Weihong Song, Fagang Ren

Index Scriptorium Estoniae

2013-01-01

Tallinnas Tulika 19 asuvast Bai Lan Hiina massaažisalongist, kus ravitakse kuputeraapia, gua sha kraapimisplaatide, moksa, nõelravi ja punktmassaaži abil. Tui na massaaži ja hiina loodusteraapia protseduure kommenteerivad spetsialistid ning patsiendid Anne ja Julia

Vene ja prantsuse kunsti imetlemisest Londonis / Ann Alari

Index Scriptorium Estoniae

Alari, Ann

2008-01-01

Näitus "Venemaalt pärit prantsuse ja vene shedöövrid" kuningliku kunstiakadeemia saalides Londonis. Vaatluse all oli ajavahemik 1870 kuni 1925. Tööd olid pärit Moskvas elanud tekstiilitöösturitest suurärimeeste Sergei Shtshukini ja Ivan Morozovi kogudest, mis 1917. a. natsionaliseeriti. Kuraator Ann Dumas

ANN-PSO Integrated Optimization Methodology for Intelligent Control of MMC Machining

Science.gov (United States)

Chandrasekaran, Muthumari; Tamang, Santosh

2017-08-01

Metal Matrix Composites (MMC) show improved properties in comparison with non-reinforced alloys and have found increased application in automotive and aerospace industries. The selection of optimum machining parameters to produce components of desired surface roughness is of great concern considering the quality and economy of manufacturing process. In this study, a surface roughness prediction model for turning Al-SiCp MMC is developed using Artificial Neural Network (ANN). Three turning parameters viz., spindle speed ( N), feed rate ( f) and depth of cut ( d) were considered as input neurons and surface roughness was an output neuron. ANN architecture having 3 -5 -1 is found to be optimum and the model predicts with an average percentage error of 7.72 %. Particle Swarm Optimization (PSO) technique is used for optimizing parameters to minimize machining time. The innovative aspect of this work is the development of an integrated ANN-PSO optimization method for intelligent control of MMC machining process applicable to manufacturing industries. The robustness of the method shows its superiority for obtaining optimum cutting parameters satisfying desired surface roughness. The method has better convergent capability with minimum number of iterations.

Prediction of scour below submerged pipeline crossing a river using ANN.

Science.gov (United States)

Azamathulla, H M; Zakaria, Nor Azazi

2011-01-01

The process involved in the local scour below pipelines is so complex that it makes it difficult to establish a general empirical model to provide accurate estimation for scour. This paper describes the use of artificial neural networks (ANN) to estimate the pipeline scour depth. The data sets of laboratory measurements were collected from published works and used to train the network or evolve the program. The developed networks were validated by using the observations that were not involved in training. The performance of ANN was found to be more effective when compared with the results of regression equations in predicting the scour depth around pipelines.

47 CFR 25.258 - Sharing between NGSO MSS Feeder links Stations and GSO FSS services in the 29.25-29.5 GHz Bands.

Science.gov (United States)

2010-10-01

... 47 Telecommunication 2 2010-10-01 2010-10-01 false Sharing between NGSO MSS Feeder links Stations and GSO FSS services in the 29.25-29.5 GHz Bands. 25.258 Section 25.258 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Technical Standards § 25...

Artificial neural network (ANN) approach for modeling Zn(II) adsorption in batch process

Energy Technology Data Exchange (ETDEWEB)

Yildiz, Sayiter [Engineering Faculty, Cumhuriyet University, Sivas (Turkmenistan)

2017-09-15

Artificial neural networks (ANN) were applied to predict adsorption efficiency of peanut shells for the removal of Zn(II) ions from aqueous solutions. Effects of initial pH, Zn(II) concentrations, temperature, contact duration and adsorbent dosage were determined in batch experiments. The sorption capacities of the sorbents were predicted with the aid of equilibrium and kinetic models. The Zn(II) ions adsorption onto peanut shell was better defined by the pseudo-second-order kinetic model, for both initial pH, and temperature. The highest R{sup 2} value in isotherm studies was obtained from Freundlich isotherm for the inlet concentration and from Temkin isotherm for the sorbent amount. The high R{sup 2} values prove that modeling the adsorption process with ANN is a satisfactory approach. The experimental results and the predicted results by the model with the ANN were found to be highly compatible with each other.

Artificial neural network (ANN) approach for modeling Zn(II) adsorption in batch process

International Nuclear Information System (INIS)

Yildiz, Sayiter

2017-01-01

Artificial neural networks (ANN) were applied to predict adsorption efficiency of peanut shells for the removal of Zn(II) ions from aqueous solutions. Effects of initial pH, Zn(II) concentrations, temperature, contact duration and adsorbent dosage were determined in batch experiments. The sorption capacities of the sorbents were predicted with the aid of equilibrium and kinetic models. The Zn(II) ions adsorption onto peanut shell was better defined by the pseudo-second-order kinetic model, for both initial pH, and temperature. The highest R"2 value in isotherm studies was obtained from Freundlich isotherm for the inlet concentration and from Temkin isotherm for the sorbent amount. The high R"2 values prove that modeling the adsorption process with ANN is a satisfactory approach. The experimental results and the predicted results by the model with the ANN were found to be highly compatible with each other.

Intelligent MRTD testing for thermal imaging system using ANN

Science.gov (United States)

Sun, Junyue; Ma, Dongmei

2006-01-01

The Minimum Resolvable Temperature Difference (MRTD) is the most widely accepted figure for describing the performance of a thermal imaging system. Many models have been proposed to predict it. The MRTD testing is a psychophysical task, for which biases are unavoidable. It requires laboratory conditions such as normal air condition and a constant temperature. It also needs expensive measuring equipments and takes a considerable period of time. Especially when measuring imagers of the same type, the test is time consuming. So an automated and intelligent measurement method should be discussed. This paper adopts the concept of automated MRTD testing using boundary contour system and fuzzy ARTMAP, but uses different methods. It describes an Automated MRTD Testing procedure basing on Back-Propagation Network. Firstly, we use frame grabber to capture the 4-bar target image data. Then according to image gray scale, we segment the image to get 4-bar place and extract feature vector representing the image characteristic and human detection ability. These feature sets, along with known target visibility, are used to train the ANN (Artificial Neural Networks). Actually it is a nonlinear classification (of input dimensions) of the image series using ANN. Our task is to justify if image is resolvable or uncertainty. Then the trained ANN will emulate observer performance in determining MRTD. This method can reduce the uncertainties between observers and long time dependent factors by standardization. This paper will introduce the feature extraction algorithm, demonstrate the feasibility of the whole process and give the accuracy of MRTD measurement.

Q&A: Grace Anne Koppel, Living Well with COPD

Science.gov (United States)

... their own lives back is the most rewarding thing we have ever done. Read More "The Challenge of COPD" Articles Q&A: Grace Anne Koppel, Living Well with COPD / What is COPD? / What Causes COPD? / Getting Tested / Am I at Risk? / COPD Quiz Fall ...

2017-2018 Travel Expense Reports for Mary Anne Chambers ...

International Development Research Centre (IDRC) Digital Library (Canada)

Chantal Taylor

Ottawa. Airfare: $368.41. Other. Transportation: $69.95. Accommodation: $542.79. Meals and. Incidentals: $164.42. Other: $0.00. Total: $1,145.57. Comments: From residence in Thornhill, Ontario. 2017-2018 Travel Expense Reports for Mary. Anne Chambers, Governor, Chairperson of the. Human Resources Committee.

2017-2018 Travel Expense Reports for Mary Anne Chambers ...

International Development Research Centre (IDRC) Digital Library (Canada)

Chantal Taylor

Ottawa. Airfare: $563.72. Other. Transportation: $74.26. Accommodation: $0.00. Meals and. Incidentals: $46.17. Other: $30.00. Total: $714.15. Comments: From residence in Thornhill, Ontario. 2017-2018 Travel Expense Reports for Mary. Anne Chambers, Governor, Chairperson of the. Human Resources Committee.

Professor Anne Khademian named National Academy of Public Administration Fellow

OpenAIRE

Chadwick, Heather Riley

2009-01-01

Anne Khademian, professor with Virginia Tech's Center for Public Administration and Policy, School of Public and International Affairs, at the Alexandria, Va., campus has been elected a National Academy of Public Administration (NAPA) Fellow.

Theory Study and Application of the BP-ANN Method for Power Grid Short-Term Load Forecasting

Institute of Scientific and Technical Information of China (English)

Xia Hua; Gang Zhang; Jiawei Yang; Zhengyuan Li

2015-01-01

Aiming at the low accuracy problem of power system short⁃term load forecasting by traditional methods, a back⁃propagation artifi⁃cial neural network (BP⁃ANN) based method for short⁃term load forecasting is presented in this paper. The forecast points are re⁃lated to prophase adjacent data as well as the periodical long⁃term historical load data. Then the short⁃term load forecasting model of Shanxi Power Grid (China) based on BP⁃ANN method and correlation analysis is established. The simulation model matches well with practical power system load, indicating the BP⁃ANN method is simple and with higher precision and practicality.

La légitimation du rock en URSS dans les années 1970-1980

OpenAIRE

Zaytseva, Anna

2017-01-01

RésuméL'article analyse le chemin parcouru par le rock en URSS puis en Russie, de l'état d'une (sous)culture occidentalisée anglophone, ayant trouvé refuge dans les discothèques des années 1960-1970, jusqu'au canon du russkij rok actuel, devenu presque synonyme de poésie chantée, via sa légitimation progressive dans les années 1980. Celle-ci a été amorcée à la fin des années 1970 avec l’arrivée en force d'une nouvelle génération artistique au sein de l'underground rock (« nouvelle vague » de ...

Vegetarian Eco-feminist Consciousness in Carol Ann Duffy’s Poetry

Directory of Open Access Journals (Sweden)

Jie Zhou

2015-07-01

Full Text Available This paper discusses vegetarian eco-feminist consciousness in Carol Ann Duffy’s poetry by close analysis of two poems, namely “The Dolphins” and “A Healthy Diet” from her poem collection Standing Female Nude. The former is a dramatic monologue of a dolphin, which is exploited by people, and the latter is a dramatic monologue of an omnipotent observer in a restaurant. Both poems criticized the species-ism, and together, they showed the poet’s vegetarian eco-feminist consciousness. A close reading of the two poems from the eco-feminist perspective helps the reader understand why Carol Ann Duffy is honored as the first woman poet laureate in British history, and better understand vegetarian eco-feminism and its influence in British society. Keywords: eco-feminism; consciousness, species-ism, vegetarian, animal, diet

Data-Driven Modeling of Complex Systems by means of a Dynamical ANN

Science.gov (United States)

Seleznev, A.; Mukhin, D.; Gavrilov, A.; Loskutov, E.; Feigin, A.

2017-12-01

The data-driven methods for modeling and prognosis of complex dynamical systems become more and more popular in various fields due to growth of high-resolution data. We distinguish the two basic steps in such an approach: (i) determining the phase subspace of the system, or embedding, from available time series and (ii) constructing an evolution operator acting in this reduced subspace. In this work we suggest a novel approach combining these two steps by means of construction of an artificial neural network (ANN) with special topology. The proposed ANN-based model, on the one hand, projects the data onto a low-dimensional manifold, and, on the other hand, models a dynamical system on this manifold. Actually, this is a recurrent multilayer ANN which has internal dynamics and capable of generating time series. Very important point of the proposed methodology is the optimization of the model allowing us to avoid overfitting: we use Bayesian criterion to optimize the ANN structure and estimate both the degree of evolution operator nonlinearity and the complexity of nonlinear manifold which the data are projected on. The proposed modeling technique will be applied to the analysis of high-dimensional dynamical systems: Lorenz'96 model of atmospheric turbulence, producing high-dimensional space-time chaos, and quasi-geostrophic three-layer model of the Earth's atmosphere with the natural orography, describing the dynamics of synoptical vortexes as well as mesoscale blocking systems. The possibility of application of the proposed methodology to analyze real measured data is also discussed. The study was supported by the Russian Science Foundation (grant #16-12-10198).

2016-2017 Travel Expense Reports for Mary Anne Chambers ...

International Development Research Centre (IDRC) Digital Library (Canada)

Beata Bialic

Date(s):. 2016-07-06. Destination(s):. Ottawa. Airfare: $482.11. Other. Transportation: $64.30. Accommodation: $0.00. Meals and. Incidentals: $25.28. Other: $0.00. Total: $571.69. Comments: 2016-2017 Travel Expense Reports for Mary. Anne Chambers, Governor, Chairperson of the. Human Resources Committee.

Mapping brain circuits of reward and motivation: in the footsteps of Ann Kelley.

Science.gov (United States)

Richard, Jocelyn M; Castro, Daniel C; Difeliceantonio, Alexandra G; Robinson, Mike J F; Berridge, Kent C

2013-11-01

Ann Kelley was a scientific pioneer in reward neuroscience. Her many notable discoveries included demonstrations of accumbens/striatal circuitry roles in eating behavior and in food reward, explorations of limbic interactions with hypothalamic regulatory circuits, and additional interactions of motivation circuits with learning functions. Ann Kelley's accomplishments inspired other researchers to follow in her footsteps, including our own laboratory group. Here we describe results from several lines of our research that sprang in part from earlier findings by Kelley and colleagues. We describe hedonic hotspots for generating intense pleasure 'liking', separate identities of 'wanting' versus 'liking' systems, a novel role for dorsal neostriatum in generating motivation to eat, a limbic keyboard mechanism in nucleus accumbens for generating intense desire versus intense dread, and dynamic limbic transformations of learned memories into motivation. We describe how origins for each of these themes can be traced to fundamental contributions by Ann Kelley. Copyright © 2013 Elsevier Ltd. All rights reserved.

Anne Sütü ve Mikrobiyota Gelişimi

OpenAIRE

GÜNEY, Rabiye; ÇINAR, Nursan

2017-01-01

Sağlıklı mikrobiyotanın etkisine yönelik yapılan çalışmalarda, çocukların gelecekteki sağlığı için mikrobiyota gelişiminin büyük önem taşıdığı vurgulanmaktadır. Astım, şeker hastalığı, obezite gibi birçok hastalığın zarar görmüş ya da gelişmemiş bağırsak mikrobiyotası ile yakın ilişkisi bulunmaktadır. Anne sütü, sağlıklı bir bağırsak mikrobiyotasının gelişmesi için bebeğe aktarılan çok sayıda non-patojen bakteriyi içinde barındırmaktadır. Bununla birlikte, anne sütündeki mikroorganizmaların n...

Prediction of Tourism Demand in Iran by Using Artificial Neural Network (ANN and Supporting Vector Machine (SVR

Directory of Open Access Journals (Sweden)

Seyedehelham Sadatiseyedmahalleh

2016-02-01

Full Text Available This research examines and proves this effectiveness connected with artificial neural networks (ANNs as an alternative approach to the use of Support Vector Machine (SVR in the tourism research. This method can be used for the tourism industry to define the turism’s demands in Iran. The outcome reveals the use of ANNs in tourism research might result in better quotations when it comes to prediction bias and accuracy. Even more applications of ANNs in the context of tourism demand evaluation is needed to establish and validate the effects.

2016-2017 Travel Expense Reports for Margaret Ann Biggs ...

International Development Research Centre (IDRC) Digital Library (Canada)

Beata Bialic

Purpose: Internal IDRC meetings. Date(s):. 2016-07-04 to 2016-07-06. Destination(s):. Ottawa. Airfare: $0.00. Other. Transportation: $39.00. Accommodation: $0.00. Meals and. Incidentals: $25.43. Other: $0.00. Total: $64.43. Comments: 2016-2017 Travel Expense Reports for. Margaret Ann Biggs, Chairperson.

2016-2017 Travel Expense Reports for Mary Anne Chambers ...

International Development Research Centre (IDRC) Digital Library (Canada)

chantal taylor

Purpose: Board meetings. Date(s):. 2017-03-19 to 2017-03-22. Destination(s):. Ottawa. Airfare: $121.05. Other. Transportation: $51.92. Accommodation: $926.48. Meals and. Incidentals: $190.40. Other: $0.00. Total: $1,289.85. Comments: 2016-2017 Travel Expense Reports for Mary. Anne Chambers, Governor ...

ANN-Benchmarks: A Benchmarking Tool for Approximate Nearest Neighbor Algorithms

DEFF Research Database (Denmark)

Aumüller, Martin; Bernhardsson, Erik; Faithfull, Alexander

2017-01-01

This paper describes ANN-Benchmarks, a tool for evaluating the performance of in-memory approximate nearest neighbor algorithms. It provides a standard interface for measuring the performance and quality achieved by nearest neighbor algorithms on different standard data sets. It supports several...... visualise these as images, Open image in new window plots, and websites with interactive plots. ANN-Benchmarks aims to provide a constantly updated overview of the current state of the art of k-NN algorithms. In the short term, this overview allows users to choose the correct k-NN algorithm and parameters...... for their similarity search task; in the longer term, algorithm designers will be able to use this overview to test and refine automatic parameter tuning. The paper gives an overview of the system, evaluates the results of the benchmark, and points out directions for future work. Interestingly, very different...

A 0.7V 7-to-10bit 0-to-2MS/s Flexible SAR ADC for Ultra Low-Power Wireless Sensor Nodes

NARCIS (Netherlands)

Harpe, P.J.A.; Dolmans, G.; Philips, K.J.P.; Groot, de H.W.H.

2012-01-01

This paper presents a flexible SAR ADC in 90nm CMOS for wireless sensor nodes. By supporting resolutions from 7 to 10bit and sample rates from DC to 2MS/s, this design can be used for a variety of applications such as sensor interfacing and receiver frontends. Flexibility is achieved by a

A Fault Diagnosis Model Based on LCD-SVD-ANN-MIV and VPMCD for Rotating Machinery

Directory of Open Access Journals (Sweden)

Songrong Luo

2016-01-01

Full Text Available The fault diagnosis process is essentially a class discrimination problem. However, traditional class discrimination methods such as SVM and ANN fail to capitalize the interactions among the feature variables. Variable predictive model-based class discrimination (VPMCD can adequately use the interactions. But the feature extraction and selection will greatly affect the accuracy and stability of VPMCD classifier. Aiming at the nonstationary characteristics of vibration signal from rotating machinery with local fault, singular value decomposition (SVD technique based local characteristic-scale decomposition (LCD was developed to extract the feature variables. Subsequently, combining artificial neural net (ANN and mean impact value (MIV, ANN-MIV as a kind of feature selection approach was proposed to select more suitable feature variables as input vector of VPMCD classifier. In the end of this paper, a novel fault diagnosis model based on LCD-SVD-ANN-MIV and VPMCD is proposed and proved by an experimental application for roller bearing fault diagnosis. The results show that the proposed method is effective and noise tolerant. And the comparative results demonstrate that the proposed method is superior to the other methods in diagnosis speed, diagnosis success rate, and diagnosis stability.

A 10 bit 200 MS/s pipeline ADC using loading-balanced architecture in 0.18 μm CMOS

Science.gov (United States)

Wang, Linfeng; Meng, Qiao; Zhi, Hao; Li, Fei

2017-07-01

A new loading-balanced architecture for high speed and low power consumption pipeline analog-to-digital converter (ADC) is presented in this paper. The proposed ADC uses SHA-less, op-amp and capacitor-sharing technique, capacitor-scaling scheme to reduce the die area and power consumption. A new capacitor-sharing scheme was proposed to cancel the extra reset phase of the feedback capacitors. The non-standard inter-stage gain increases the feedback factor of the first stage and makes it equal to the second stage, by which, the load capacitor of op-amp shared by the first and second stages is balanced. As for the fourth stage, the capacitor and op-amp no longer scale down. From the system’s point of view, all load capacitors of the shared OTAs are balanced by employing a loading-balanced architecture. The die area and power consumption are optimized maximally. The ADC is implemented in a 0.18 μm 1P6M CMOS technology, and occupies a die area of 1.2 × 1.2 mm{}2. The measurement results show a 55.58 dB signal-to-noise-and-distortion ratio (SNDR) and 62.97 dB spurious-free dynamic range (SFDR) with a 25 MHz input operating at a 200 MS/s sampling rate. The proposed ADC consumes 115 mW at 200 MS/s from a 1.8 V supply.

Summary of Current Radiometric Calibration Coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI Sensors

Science.gov (United States)

Chander, Gyanesh; Markham, Brian L.; Helder, Dennis L.

2009-01-01

This paper provides a summary of the current equations and rescaling factors for converting calibrated Digital Numbers (DNs) to absolute units of at-sensor spectral radiance, Top-Of- Atmosphere (TOA) reflectance, and at-sensor brightness temperature. It tabulates the necessary constants for the Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Advanced Land Imager (ALI) sensors. These conversions provide a basis for standardized comparison of data in a single scene or between images acquired on different dates or by different sensors. This paper forms a needed guide for Landsat data users who now have access to the entire Landsat archive at no cost.

Application of ANN and fuzzy logic algorithms for streamflow ...

Indian Academy of Sciences (India)

The present study focusses on development of models using ANN and fuzzy logic (FL) algorithm for predicting the streamflow for catchment of Savitri River Basin. The input vector to these models were daily rainfall, mean daily evaporation, mean daily temperature and lag streamflow used. In the present study, 20 years ...

2016-2017 Travel Expense Reports for Mary Anne Chambers ...

International Development Research Centre (IDRC) Digital Library (Canada)

Beata Bialic

Purpose: Board meetings. Date(s):. 2016-11-20 to 2016-11-23. Destination(s):. Ottawa. Airfare: $445.14. Other. Transportation: $29.05. Accommodation: $786.80. Meals and. Incidentals: $76.79. Other: $0.00. Total: $1,337.78. Comments: 2016-2017 Travel Expense Reports for Mary. Anne Chambers, Governor, Chairperson ...

2016-2017 Travel Expense Reports for Mary Anne Chambers ...

International Development Research Centre (IDRC) Digital Library (Canada)

Beata Bialic

Date(s):. 2016-08-14 to 2016-08-23. Destination(s):. Peru/Colombia. Airfare: $3,484.87. Other. Transportation: $0.00. Accommodation: $1,942.21. Meals and. Incidentals: $395.27. Other: $75.50. Total: $5,897.85. Comments: 2016-2017 Travel Expense Reports for Mary. Anne Chambers, Governor, Chairperson of the.

Aspekte van die outeursfunksie in Antjie Krog se Lady Anne (1989)

OpenAIRE

M. Crous

2002-01-01

Aspects of the author function in Antjie Krog’s Lady Anne (1989) The purpose of this essay is to investigate the Foucauldian notion of the so-called “author function” in Antjie Krog’s seventh volume of poetry, viz. Lady Anne (1989). It is an attempt to show how the notion of the death of the author (Barthes) links up with this theorisation of Foucault. Furthermore, it is also an attempt to indicate the characteristic features of the so-called “author function” in the late eighties in Afr...

Mart ja Mari-Ann Susi taotlevad omanikena Concordia pankrotti / Andri Maimets

Index Scriptorium Estoniae

Maimets, Andri, 1979-

2003-01-01

Concordia Ülikooli rektor Mart Susi esitas kohtule avalduse, milles taotleb ülikooli pidanud Concordia Varahalduse OÜ pankroti väljakuulutamist. Vt. samas: Mari-Ann Susi õigustas ülikooli raha kasutamist

A radiation-hard dual-channel 12-bit 40 MS/s ADC prototype for the ATLAS liquid argon calorimeter readout electronics upgrade at the CERN LHC

Energy Technology Data Exchange (ETDEWEB)

Kuppambatti, J. [Columbia University, Dept. of Electrical Engineering, New York, NY (United States); Ban, J. [Columbia University, Nevis Laboratories, Irvington, NY (United States); Andeen, T., E-mail: tandeen@utexas.edu [Columbia University, Nevis Laboratories, Irvington, NY (United States); Brown, R.; Carbone, R. [Columbia University, Nevis Laboratories, Irvington, NY (United States); Kinget, P. [Columbia University, Dept. of Electrical Engineering, New York, NY (United States); Brooijmans, G.; Sippach, W. [Columbia University, Nevis Laboratories, Irvington, NY (United States)

2017-05-21

The readout electronics upgrade for the ATLAS Liquid Argon Calorimeters at the CERN Large Hadron Collider requires a radiation-hard ADC. The design of a radiation-hard dual-channel 12-bit 40 MS/s pipeline ADC for this use is presented. The design consists of two pipeline A/D channels each with four Multiplying Digital-to-Analog Converters followed by 8-bit Successive-Approximation-Register analog-to-digital converters. The custom design, fabricated in a commercial 130 nm CMOS process, shows a performance of 67.9 dB SNDR at 10 MHz for a single channel at 40 MS/s, with a latency of 87.5 ns (to first bit read out), while its total power consumption is 50 mW/channel. The chip uses two power supply voltages: 1.2 and 2.5 V. The sensitivity to single event effects during irradiation is measured and determined to meet the system requirements.

Benthic Habitat Mapping - Dry Tortugas RoxAnn Acoustic Sensor Data Points

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — During April 2001 RoxAnn single-beam acoustic surveys were conducted at the North Unit of the Tortugas Ecological Reserve, Florida. Thirteen transects associated...

A 14-bit 50 MS/s sample-and-hold circuit for pipelined ADC

International Nuclear Information System (INIS)

Yue Sen; Zhao Yiqiang; Pang Ruilong; Sheng Yun

2014-01-01

A high performance sample-and-hold (S/H) circuit used in a pipelined analog-to-digital converter (ADC) is presented. Capacitor flip-around architecture is used in this S/H circuit with a novel gain-boosted differential folded cascode operational transconductance amplifier. A double-bootstrapped switch is designed to improve the performance of the circuit. The circuit is implemented using a 0.18 μm 1P6M CMOS process. Measurement results show that the effective number of bits is 14.03 bits, the spurious free dynamic range is 94.62 dB, the signal to noise and distortion ratio is 86.28 dB, and the total harmonic distortion is −91:84 dB for a 5 MHz input signal with 50 MS/s sampling rate. A pipeline ADC with the designed S/H circuit has been implemented. (semiconductor integrated circuits)

Development and Application of ANN Model for Worker Assignment into Virtual Cells of Large Sized Configurations

International Nuclear Information System (INIS)

Murali, R. V.; Fathi, Khalid; Puri, A. B.

2010-01-01

This paper presents an extended version of study already undertaken on development of an artificial neural networks (ANNs) model for assigning workforce into virtual cells under virtual cellular manufacturing systems (VCMS) environments. Previously, the same authors have introduced this concept and applied it to virtual cells of two-cell configuration and the results demonstrated that ANNs could be a worth applying tool for carrying out workforce assignments. In this attempt, three-cell configurations problems are considered for worker assignment task. Virtual cells are formed under dual resource constraint (DRC) context in which the number of available workers is less than the total number of machines available. Since worker assignment tasks are quite non-linear and highly dynamic in nature under varying inputs and conditions and, in parallel, ANNs have the ability to model complex relationships between inputs and outputs and find similar patterns effectively, an attempt was earlier made to employ ANNs into the above task. In this paper, the multilayered perceptron with feed forward (MLP-FF) neural network model has been reused for worker assignment tasks of three-cell configurations under DRC context and its performance at different time periods has been analyzed. The previously proposed worker assignment model has been reconfigured and cell formation solutions available for three-cell configuration in the literature are used in combination to generate datasets for training ANNs framework. Finally, results of the study have been presented and discussed.

ANNE TONER. Ellipsis in English Literature: Signs of Omission

DEFF Research Database (Denmark)

Lupton, Tina Jane

2016-01-01

As a freshman, I once met a PhD Student writing about the use of the comma in Jane Austen. For years the thesis topic kept me entertained as an example of how narrowly focused literary study could become. Reading Anne Toner's Ellipsis in English Literature commits me to a recantation of that joke...

Estimation of Costs and Durations of Construction of Urban Roads Using ANN and SVM

Directory of Open Access Journals (Sweden)

Igor Peško

2017-01-01

Full Text Available Offer preparation has always been a specific part of a building process which has significant impact on company business. Due to the fact that income greatly depends on offer’s precision and the balance between planned costs, both direct and overheads, and wished profit, it is necessary to prepare a precise offer within required time and available resources which are always insufficient. The paper presents a research of precision that can be achieved while using artificial intelligence for estimation of cost and duration in construction projects. Both artificial neural networks (ANNs and support vector machines (SVM are analysed and compared. The best SVM has shown higher precision, when estimating costs, with mean absolute percentage error (MAPE of 7.06% compared to the most precise ANNs which has achieved precision of 25.38%. Estimation of works duration has proved to be more difficult. The best MAPEs were 22.77% and 26.26% for SVM and ANN, respectively.

Integration of the Mini-Sulfide Sulfite Anthraquinone (MSS-AQ) Pulping Process and Black Liquor Gasification in a Pulp Mill

Energy Technology Data Exchange (ETDEWEB)

Hasan Jameel, North Carolina State University; Adrianna Kirkman, North Carolina State University; Ravi Chandran,Thermochem Recovery International Brian Turk Research Triangle Institute; Brian Green, Research Triangle Institute

2010-01-27

As many of the recovery boilers and other pieces of large capital equipment of U.S. pulp mills are nearing the end of their useful life, the pulp and paper industry will soon need to make long-term investments in new technologies. The ability to install integrated, complete systems that are highly efficient will impact the industry’s energy use for decades to come. Developing a process for these new systems is key to the adoption of state-of-the-art technologies in the Forest Products industry. This project defined an integrated process model that combines mini-sulfide sulfite anthraquinone (MSS-AQ) pulping and black liquor gasification with a proprietary desulfurization process developed by the Research Triangle Institute. Black liquor gasification is an emerging technology that enables the use of MSS-AQ pulping, which results in higher yield, lower bleaching cost, lower sulfur emissions, and the elimination of causticization requirements. The recently developed gas cleanup/absorber technology can clean the product gas to a state suitable for use in a gas turbine and also regenerate the pulping chemicals needed to for the MSS-AQ pulping process. The combination of three advanced technologies into an integrated design will enable the pulping industry to achieve a new level of efficiency, environmental performance, and cost savings. Because the three technologies are complimentary, their adoption as a streamlined package will ensure their ability to deliver maximum energy and cost savings benefits. The process models developed by this project will enable the successful integration of new technologies into the next generation of chemical pulping mills. When compared to the Kraft reference pulp, the MSS-AQ procedures produced pulps with a 10-15 % yield benefit and the ISO brightness was 1.5-2 times greater. The pulp refined little easier and had a slightly lower apparent sheet density (In both the cases). At similar levels of tear index the MSS-AQ pulps also

Why philosophy and history matter : A conversation with Ann Taves

NARCIS (Netherlands)

von Stuckrad, C.K.M.

2010-01-01

The article picks up some ideas that Ann Taves presents in her book Religious Experience Reconsidered, and looks at possible conversations that are not fleshed out in detail in Taves' book. In particular, it is argued that the disciplinary confrontation with philosophy and with historiography is of

Artificial neural network (ANN)-based prediction of depth filter loading capacity for filter sizing.

Science.gov (United States)

Agarwal, Harshit; Rathore, Anurag S; Hadpe, Sandeep Ramesh; Alva, Solomon J

2016-11-01

This article presents an application of artificial neural network (ANN) modelling towards prediction of depth filter loading capacity for clarification of a monoclonal antibody (mAb) product during commercial manufacturing. The effect of operating parameters on filter loading capacity was evaluated based on the analysis of change in the differential pressure (DP) as a function of time. The proposed ANN model uses inlet stream properties (feed turbidity, feed cell count, feed cell viability), flux, and time to predict the corresponding DP. The ANN contained a single output layer with ten neurons in hidden layer and employed a sigmoidal activation function. This network was trained with 174 training points, 37 validation points, and 37 test points. Further, a pressure cut-off of 1.1 bar was used for sizing the filter area required under each operating condition. The modelling results showed that there was excellent agreement between the predicted and experimental data with a regression coefficient (R 2 ) of 0.98. The developed ANN model was used for performing variable depth filter sizing for different clarification lots. Monte-Carlo simulation was performed to estimate the cost savings by using different filter areas for different clarification lots rather than using the same filter area. A 10% saving in cost of goods was obtained for this operation. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1436-1443, 2016. © 2016 American Institute of Chemical Engineers.

A 12-bit 40 MS/s pipelined ADC with over 80 dB SFDR

Energy Technology Data Exchange (ETDEWEB)

Wei Qi; Yin Xiumei; Han Dandan; Yang Huazhong, E-mail: q-wei05@mails.tsinghua.edu.c [Department of Electronic Engineering, Tsinghua University, Beijing 100084 (China)

2010-02-15

This paper describes a 12-bit 40 MS/s calibration-free pipelined analog-to-digital converter (ADC), which is optimized for high spurious free dynamic range (SFDR) performance and low power dissipation. With a 4.9 MHz sine wave input, the prototype ADC implemented in a 0.18-{mu}m 1P6M CMOS process shows measured differential nonlinearity and integral nonlinearity within 0.78 and 1.32 least significant bits at the 12-bit level without any trimming or calibration. The ADC, with a total die area of 3.1 x 2.1 mm{sup 2}, demonstrates a maximum signal-to-noise distortion ratio (SNDR) and SFDR of 66.32 and 83.38 dB, respectively, at a 4.9 MHz analog input and a power consumption of 102 mW from a 1.8 V supply. (semiconductor integrated circuits)

A computation ANN model for quantifying the global solar radiation: A case study of Al-Aqabah-Jordan

International Nuclear Information System (INIS)

Abolgasem, I M; Alghoul, M A; Ruslan, M H; Chan, H Y; Khrit, N G; Sopian, K

2015-01-01

In this paper, a computation model is developed to predict the global solar radiation (GSR) in Aqaba city based on the data recorded with association of Artificial Neural Networks (ANN). The data used in this work are global solar radiation (GSR), sunshine duration, maximum and minimum air temperature and relative humidity. These data are available from Jordanian meteorological station over a period of two years. The quality of GSR forecasting is compared by using different Learning Algorithms. The decision of changing the ANN architecture is essentially based on the predicted results to obtain the best ANN model for monthly and seasonal GSR. Different configurations patterns were tested using available observed data. It was found that the model using mainly sunshine duration and air temperature as inputs gives accurate results. The ANN model efficiency and the mean square error values show that the prediction model is accurate. It is found that the effect of the three learning algorithms on the accuracy of the prediction model at the training and testing stages for each time scale is mostly within the same accuracy range. (paper)

An IP-oriented 11-bit 160 MS/s 2-channel current-steering DAC

International Nuclear Information System (INIS)

Xu Ning; Li Fule; Zhang Chun; Wang Zhihua

2014-01-01

This paper presents an 11-bit 160 MS/s 2-channel current-steering digital-to-analog converter (DAC) IP. The circuit and layout are carefully designed to optimize its performance and area. A 6-2-3 segmented structure is used for the trade-off among linearity, area and layout complexity. The sizes of current source transistors are calculated out according to the process matching parameter. The unary current cells are placed in a one-dimension distribution to simplify the layout routing, spare area and wiring layer. Their sequences are also carefully designed to reduce integral nonlinearity. The test result presents an SFDR of 72 dBc at 4.88 MHz input signal with DNL ⩽ 0.25 LSB, INL ⩽ 0.8 LSB. The full-scale output current is 5 mA with a 2.5 V analog power supply. The core of each channel occupies 0.08 mm 2 in a 1P-8M 55 nm CMOS process. (semiconductor integrated circuits)

Measurement and ANN prediction of pH-dependent solubility of nitrogen-heterocyclic compounds.

Science.gov (United States)

Sun, Feifei; Yu, Qingni; Zhu, Jingke; Lei, Lecheng; Li, Zhongjian; Zhang, Xingwang

2015-09-01

Based on the solubility of 25 nitrogen-heterocyclic compounds (NHCs) measured by saturation shake-flask method, artificial neural network (ANN) was employed to the study of the quantitative relationship between the structure and pH-dependent solubility of NHCs. With genetic algorithm-multivariate linear regression (GA-MLR) approach, five out of the 1497 molecular descriptors computed by Dragon software were selected to describe the molecular structures of NHCs. Using the five selected molecular descriptors as well as pH and the partial charge on the nitrogen atom of NHCs (QN) as inputs of ANN, a quantitative structure-property relationship (QSPR) model without using Henderson-Hasselbalch (HH) equation was successfully developed to predict the aqueous solubility of NHCs in different pH water solutions. The prediction model performed well on the 25 model NHCs with an absolute average relative deviation (AARD) of 5.9%, while HH approach gave an AARD of 36.9% for the same model NHCs. It was found that QN played a very important role in the description of NHCs and, with QN, ANN became a potential tool for the prediction of pH-dependent solubility of NHCs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Estimating SPT-N Value Based on Soil Resistivity using Hybrid ANN-PSO Algorithm

Science.gov (United States)

Nur Asmawisham Alel, Mohd; Ruben Anak Upom, Mark; Asnida Abdullah, Rini; Hazreek Zainal Abidin, Mohd

2018-04-01

Standard Penetration Resistance (N value) is used in many empirical geotechnical engineering formulas. Meanwhile, soil resistivity is a measure of soil’s resistance to electrical flow. For a particular site, usually, only a limited N value data are available. In contrast, resistivity data can be obtained extensively. Moreover, previous studies showed evidence of a correlation between N value and resistivity value. Yet, no existing method is able to interpret resistivity data for estimation of N value. Thus, the aim is to develop a method for estimating N-value using resistivity data. This study proposes a hybrid Artificial Neural Network-Particle Swarm Optimization (ANN-PSO) method to estimate N value using resistivity data. Five different ANN-PSO models based on five boreholes were developed and analyzed. The performance metrics used were the coefficient of determination, R2 and mean absolute error, MAE. Analysis of result found that this method can estimate N value (R2 best=0.85 and MAEbest=0.54) given that the constraint, Δ {\\bar{l}}ref, is satisfied. The results suggest that ANN-PSO method can be used to estimate N value with good accuracy.

SU-E-T-206: Improving Radiotherapy Toxicity Based On Artificial Neural Network (ANN) for Head and Neck Cancer Patients

Energy Technology Data Exchange (ETDEWEB)

Cho, Daniel D; Wernicke, A Gabriella; Nori, Dattatreyudu; Chao, KSC; Parashar, Bhupesh; Chang, Jenghwa [Weill Cornell Medical College, NY, NY (United States)

2014-06-01

Purpose/Objective(s): The aim of this study is to build the estimator of toxicity using artificial neural network (ANN) for head and neck cancer patients Materials/Methods: An ANN can combine variables into a predictive model during training and considered all possible correlations of variables. We constructed an ANN based on the data from 73 patients with advanced H and N cancer treated with external beam radiotherapy and/or chemotherapy at our institution. For the toxicity estimator we defined input data including age, sex, site, stage, pathology, status of chemo, technique of external beam radiation therapy (EBRT), length of treatment, dose of EBRT, status of post operation, length of follow-up, the status of local recurrences and distant metastasis. These data were digitized based on the significance and fed to the ANN as input nodes. We used 20 hidden nodes (for the 13 input nodes) to take care of the correlations of input nodes. For training ANN, we divided data into three subsets such as training set, validation set and test set. Finally, we built the estimator for the toxicity from ANN output. Results: We used 13 input variables including the status of local recurrences and distant metastasis and 20 hidden nodes for correlations. 59 patients for training set, 7 patients for validation set and 7 patients for test set and fed the inputs to Matlab neural network fitting tool. We trained the data within 15% of errors of outcome. In the end we have the toxicity estimation with 74% of accuracy. Conclusion: We proved in principle that ANN can be a very useful tool for predicting the RT outcomes for high risk H and N patients. Currently we are improving the results using cross validation.

SU-E-T-206: Improving Radiotherapy Toxicity Based On Artificial Neural Network (ANN) for Head and Neck Cancer Patients

International Nuclear Information System (INIS)

Cho, Daniel D; Wernicke, A Gabriella; Nori, Dattatreyudu; Chao, KSC; Parashar, Bhupesh; Chang, Jenghwa

2014-01-01

Purpose/Objective(s): The aim of this study is to build the estimator of toxicity using artificial neural network (ANN) for head and neck cancer patients Materials/Methods: An ANN can combine variables into a predictive model during training and considered all possible correlations of variables. We constructed an ANN based on the data from 73 patients with advanced H and N cancer treated with external beam radiotherapy and/or chemotherapy at our institution. For the toxicity estimator we defined input data including age, sex, site, stage, pathology, status of chemo, technique of external beam radiation therapy (EBRT), length of treatment, dose of EBRT, status of post operation, length of follow-up, the status of local recurrences and distant metastasis. These data were digitized based on the significance and fed to the ANN as input nodes. We used 20 hidden nodes (for the 13 input nodes) to take care of the correlations of input nodes. For training ANN, we divided data into three subsets such as training set, validation set and test set. Finally, we built the estimator for the toxicity from ANN output. Results: We used 13 input variables including the status of local recurrences and distant metastasis and 20 hidden nodes for correlations. 59 patients for training set, 7 patients for validation set and 7 patients for test set and fed the inputs to Matlab neural network fitting tool. We trained the data within 15% of errors of outcome. In the end we have the toxicity estimation with 74% of accuracy. Conclusion: We proved in principle that ANN can be a very useful tool for predicting the RT outcomes for high risk H and N patients. Currently we are improving the results using cross validation

Assessment of spatial distribution of soil heavy metals using ANN-GA, MSLR and satellite imagery.

Science.gov (United States)

Naderi, Arman; Delavar, Mohammad Amir; Kaboudin, Babak; Askari, Mohammad Sadegh

2017-05-01

This study aims to assess and compare heavy metal distribution models developed using stepwise multiple linear regression (MSLR) and neural network-genetic algorithm model (ANN-GA) based on satellite imagery. The source identification of heavy metals was also explored using local Moran index. Soil samples (n = 300) were collected based on a grid and pH, organic matter, clay, iron oxide contents cadmium (Cd), lead (Pb) and zinc (Zn) concentrations were determined for each sample. Visible/near-infrared reflectance (VNIR) within the electromagnetic ranges of satellite imagery was applied to estimate heavy metal concentrations in the soil using MSLR and ANN-GA models. The models were evaluated and ANN-GA model demonstrated higher accuracy, and the autocorrelation results showed higher significant clusters of heavy metals around the industrial zone. The higher concentration of Cd, Pb and Zn was noted under industrial lands and irrigation farming in comparison to barren and dryland farming. Accumulation of industrial wastes in roads and streams was identified as main sources of pollution, and the concentration of soil heavy metals was reduced by increasing the distance from these sources. In comparison to MLSR, ANN-GA provided a more accurate indirect assessment of heavy metal concentrations in highly polluted soils. The clustering analysis provided reliable information about the spatial distribution of soil heavy metals and their sources.

Wind speed forecasting in three different regions of Mexico, using a hybrid ARIMA-ANN model

Energy Technology Data Exchange (ETDEWEB)

Cadenas, Erasmo [Facultad de Ingenieria Mecanica, Universidad Michoacana de San Nicolas de Hidalgo, Santiago Tapia No. 403, Centro (Mexico); Rivera, Wilfrido [Centro de Ivestigacion en Energia, Universidad Nacional Autonoma de Mexico, Apartado Postal 34, Temixco 62580, Morelos (Mexico)

2010-12-15

In this paper the wind speed forecasting in the Isla de Cedros in Baja California, in the Cerro de la Virgen in Zacatecas and in Holbox in Quintana Roo is presented. The time series utilized are average hourly wind speed data obtained directly from the measurements realized in the different sites during about one month. In order to do wind speed forecasting Hybrid models consisting of Autoregressive Integrated Moving Average (ARIMA) models and Artificial Neural Network (ANN) models were developed. The ARIMA models were first used to do the wind speed forecasting of the time series and then with the obtained errors ANN were built taking into account the nonlinear tendencies that the ARIMA technique could not identify, reducing with this the final errors. Once the Hybrid models were developed 48 data out of sample for each one of the sites were used to do the wind speed forecasting and the results were compared with the ARIMA and the ANN models working separately. Statistical error measures such as the mean error (ME), the mean square error (MSE) and the mean absolute error (MAE) were calculated to compare the three methods. The results showed that the Hybrid models predict the wind velocities with a higher accuracy than the ARIMA and ANN models in the three examined sites. (author)

Enamik Mõtteloo Sihtkapitali rahast kasvab USA aktsiates / Mart Trummal ; interv. Anne Oja

Index Scriptorium Estoniae

Trummal, Mart

2006-01-01

Intervjuu Eesti Mõtteloo Sihtkapitali juhi Mart Trummaliga. Tabel: Mõtteloo Sihtkapitali vara on USA-s noteeritud indeksifondides; Investeeringud Eesti aktsiatesse. Diagramm: Finantsinvesteeringute maht. Vt. samas: Anne Oja. Dividendisaajate esirinnas. Kommenteerib Annika Matson

Artificial Neural Network (ANN) Model to Predict Depression among Geriatric Population at a Slum in Kolkata, India.

Science.gov (United States)

Sau, Arkaprabha; Bhakta, Ishita

2017-05-01

Depression is one of the most important causes of mortality and morbidity among the geriatric population. Although, the aging brain is more vulnerable to depression, it cannot be considered as physiological and an inevitable part of ageing. Various sociodemographic and morbidity factors are responsible for the depression among them. Using Artificial Neural Network (ANN) model depression can be predicted from various sociodemographic variables and co morbid conditions even at community level by the grass root level health care workers. To predict depression among geriatric population from sociodemographic and morbidity attributes using ANN. An observational descriptive study with cross-sectional design was carried out at a slum under the service area of Bagbazar Urban Health and Training Centre (UHTC) in Kolkata. Among 126 elderlies under Bagbazar UHTC, 105 were interviewed using predesigned and pretested schedule. Depression status was assessed using 30 item Geriatric Depression Scale. WEKA 3.8.0 was used to develop the ANN model and test its performance. Prevalence of depression among the study population was 45.7%. Various sociodemographic variables like age, gender, literacy, living spouse, working status, personal income, family type, substance abuse and co morbid conditions like visual problem, mobility problem, hearing problem and sleeping problem were taken into consideration to develop the model. Prediction accuracy of this ANN model was 97.2%. Depression among geriatric population can be predicted accurately using ANN model from sociodemographic and morbidity attributes.

47 CFR 25.250 - Sharing between NGSO MSS Feeder links Earth Stations in the 19.3-19.7 GHz and 29.1-29.5 GHz Bands.

Science.gov (United States)

2010-10-01

... 47 Telecommunication 2 2010-10-01 2010-10-01 false Sharing between NGSO MSS Feeder links Earth Stations in the 19.3-19.7 GHz and 29.1-29.5 GHz Bands. 25.250 Section 25.250 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Technical Standards § 25...

Modelling and automatic reactive power control of isolated wind-diesel hybrid power systems using ANN

International Nuclear Information System (INIS)

Bansal, R.C.

2008-01-01

This paper presents an artificial neural network (ANN) based approach to tune the parameters of the static var compensator (SVC) reactive power controller over a wide range of typical load model parameters. The gains of PI (proportional integral) based SVC are optimised for typical values of the load voltage characteristics (n q ) by conventional techniques. Using the generated data, the method of multi-layer feed forward ANN with error back propagation training is employed to tune the parameters of the SVC. An ANN tuned SVC controller has been applied to control the reactive power of a variable slip/speed isolated wind-diesel hybrid power system. It is observed that the maximum deviations of all parameters are more for larger values of n q . It has been shown that initially synchronous generator supplies the reactive power required by the induction generator and/or load, and the latter reactive power is purely supplied by the SVC

Modelling and automatic reactive power control of isolated wind-diesel hybrid power systems using ANN

Energy Technology Data Exchange (ETDEWEB)

Bansal, R.C. [Electrical and Electronics Engineering Division, School of Engineering and Physics, The University of the South Pacific, Suva (Fiji)

2008-02-15

This paper presents an artificial neural network (ANN) based approach to tune the parameters of the static var compensator (SVC) reactive power controller over a wide range of typical load model parameters. The gains of PI (proportional integral) based SVC are optimised for typical values of the load voltage characteristics (n{sub q}) by conventional techniques. Using the generated data, the method of multi-layer feed forward ANN with error back propagation training is employed to tune the parameters of the SVC. An ANN tuned SVC controller has been applied to control the reactive power of a variable slip/speed isolated wind-diesel hybrid power system. It is observed that the maximum deviations of all parameters are more for larger values of n{sub q}. It has been shown that initially synchronous generator supplies the reactive power required by the induction generator and/or load, and the latter reactive power is purely supplied by the SVC. (author)

Application of ann-based decision making pattern recognition to fishing operations

Energy Technology Data Exchange (ETDEWEB)

Akhlaghinia, M.; Torabi, F.; Wilton, R.R. [University of Regina, Saskatchewan (Canada). Faculty of Engineering. Dept. of Petroleum Engineering], e-mail: Farshid.Torabi@uregina.ca

2010-10-15

Decision making is a crucial part of fishing operations. Proper decisions should be made to prevent wasted time and associated costs on unsuccessful operations. This paper presents a novel model to help drilling managers decide when to commence and when to quit a fishing operation. A decision making model based on Artificial Neural Network (ANN) has been developed that utilizes Pattern Recognition based on 181 fishing incidents from one of the most fish-prone fields of the southwest of Iran. All parameters chosen to train the ANN-Based Pattern Recognition Tool are assumed to play a role in the success of the fishing operation and are therefore used to decide whether a fishing operation should be performed or not. If the tool deems the operation suitable for consideration, a cost analysis of the fishing operation can then be performed to justify its overall cost. (author)

Sexuality and gender in contemporary women's Gothic fiction - Angela Carter's and Anne Rice's Vampires: Angela Carter's and Anne Rice's Vampires

OpenAIRE

Fernanda Sousa Carvalho

2009-01-01

xxx In this thesis, I provide an analysis of Angela Carter's and Anne Rice's works based on their depiction of vampires. My corpus is composed by Carter's short stories 'The Loves of Lady Purple' and 'The Lady of the House of Love' and by Rice's novels The Vampire Lestat and The Queen of the Damned. My analysis of this corpus is based on four approaches: a comparison between Carter's and Rice's works, supported by their common use of vampire characters; an investigation of how this use con...

Design of a 12-bit 80-MS/s CMOS digital-to-analog converter for PLC-VDSL applications

Science.gov (United States)

Ruiz-Amaya, Jesus; Delgado-Restituto, Manuel; Fernandez-Bootello, J. Francisco; de la Rosa, Jose M.

2005-06-01

This paper describes the design of a 12-bit 80MS/s Digital-to-Analog converter implemented in 0.13mm CMOS logic technology. The design has been computer-aided by a developed toolbox for the simulation and verification of Nyquist-Rate Analog-to-Digital and Digital-to-Analog converters in MATLAB. The embedded simulator uses SIMULINK C-coded S-functions to model all required subcircuits including their main error mechanisms. This approach allows to drastically speed up the simulation CPU-time and makes the proposed tool an advantageous alternative for fast exploration of requirements and as a design validation tool. The converter is segmented in a unary current-cell matrix for 8 MSB's and a binary-weighted array for 4 LSB's. Current sources of the converter are laid out separately from current-cell switching matrix core block and distribute in double centroid to reduce random errors and transient noise coupling. The linearity errors caused by remaining gradient errors are reduced by a modified Q2 Random-Walk switching sequence. Simulation results show that the Spurious-Free Dynamic-Range is better than 58.5dB up to 80MS/s. The estimated Signal-to-Noise Distortion Ratio yield is 99.7% and it is supposed to be better than 58dB from DC to Nyquist frequency. Multi-Tone Power Ratio is higher 59dB for several DMT test signals. The converter dissipates less than 129mW from a 3.3V supply and occupies less than 1.7mm2 die area. The results have been checked with all process corners from -40° to 85° and power supply from 3V to 3.6V.

Thesis defence: Anneli Baran Possibilities for studying semantics in phraseology / Outi Lauhakangas

Index Scriptorium Estoniae

Lauhakangas, Outi

2011-01-01

15. märtsil 2011 kaitses Anneli Baran Tartu Ülikooli kultuuriteaduste ja kunstide instituudis doktoriväitekirja Fraseologismide semantika uurimisvõimalused, juhendaja Arvo Krikmann (Eesti Kirjandusmuuseum), oponent dr Outi Lauhakangas (Soome Kirjanduse Selts)

Prediction of Ryznar Stability Index for Treated Water of WTPs Located on Al-Karakh Side of Baghdad City using Artificial Neural Network (ANN Technique

Directory of Open Access Journals (Sweden)

Awatif Soaded Alsaqqar

2016-06-01

Full Text Available In this research an Artificial Neural Network (ANN technique was applied for the prediction of Ryznar Index (RI of the flowing water from WTPs in Al-Karakh side (left side in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3 have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For Al-Dora WTP, ANN 3 model could be used as R was 92.8%.

Identification of Constitutive Parameters Using Inverse Strategy Coupled to an ANN Model

International Nuclear Information System (INIS)

Aguir, H.; Chamekh, A.; BelHadjSalah, H.; Hambli, R.

2007-01-01

This paper deals with the identification of material parameters using an inverse strategy. In the classical methods, the inverse technique is generally coupled with a finite element code which leads to a long computing time. In this work an inverse strategy coupled with an ANN procedure is proposed. This method has the advantage of being faster than the classical one. To validate this approach an experimental plane tensile and bulge tests are used in order to identify material behavior. The ANN model is trained from finite element simulations of the two tests. In order to reduce the gap between the experimental responses and the numerical ones, the proposed method is coupled with an optimization procedure to identify material parameters for the AISI304. The identified material parameters are the hardening curve and the anisotropic coefficients

Les premières années de The Himalayan Journal (1929-1940

Directory of Open Access Journals (Sweden)

Michel Raspaud

2001-05-01

Full Text Available IntroductionLa création de The Himalayan Club, sur le territoire de l’Empire des Indes à la fin de l’année 1927, s’accompagne presque aussitôt de la publication de The Himalayan Journal, en février 1929, soit mois de dix-huit mois après la création officielle de l’institution. L’objet du présent texte concerne donc la vie de The Himalayan Club lors de ses premières années d’existence, depuis la date de sa création jusqu’au début de la seconde guerre mondiale. Cependant, l’intérêt se focaliser...

Practitioner Profile: An Interview with Anne Brennan Malec, Ph.D.

Directory of Open Access Journals (Sweden)

Anne Brennan Malec

2015-12-01

Full Text Available Dr. Anne Brennan Malec is the founder and managing partner of Symmetry Counseling, a counseling, coaching, and psychotherapy group practice located in downtown Chicago. She has been the driving force behind Symmetry Counseling’s success – what started in 2011 with six offices and five counselors now houses over 25 clinicians.

Doktoritööd : [2007, Anne Lange jt.

Index Scriptorium Estoniae

2007-01-01

20. veebr. kaitseb Anne Lange doktoritööd "The poetics of translation of Ants Oras". 19. jaan. kaitses Tuuli Oder doktoritööd "The model of contemporary professional foreign language teacher". 16. jaan. kaitses Tiit Maran doktoritööd "Conservation biology of the European mink, Mustela lutreola (Linnaeus 1761): decline and causes of extinction". 12. jaan. kaitses Maris Saagpakk doktoritööd "Deutschbaltische Autobiographien als Dokumente des Zeit- und Selbstempfindens: vom Ende des 19. Jh. bis zur Umsiedlung 1939"

A 10-bit 80-MS/s opamp-sharing pipelined ADC with a switch-embedded dual-input MDAC

Energy Technology Data Exchange (ETDEWEB)

Yin Rui; Zhang Wei; Tang Zhangwen [ASIC and System State Key Laboratory, Fudan University, Shanghai 201203 (China); Liao Youchun, E-mail: zwtang@fudan.edu.cn [Ratio Microelectronics Co., Ltd, Shanghai 200433 (China)

2011-02-15

A 10-bit 80-MS/s opamp-sharing pipelined ADC is implemented in a 0.18-{mu}m CMOS. An opamp-sharing MDAC with a switch-embedded dual-input opamp is proposed to eliminate the non-resetting and successive-stage crosstalk problems observed in the conventional opamp-sharing technique. The ADC achieves a peak SNDR of 60.1 dB (ENOB = 9.69 bits) and a peak SFDR of 76 dB, while maintaining more than 9.6 ENOB for the full Nyquist input bandwidth. The core area of the ADC is 1.1 mm{sup 2} and the chip consumes 28 mW with a 1.8 V power supply. (semiconductor integrated circuits)

ANN based Performance Evaluation of BDI for Condition Monitoring of Induction Motor Bearings

Science.gov (United States)

Patel, Raj Kumar; Giri, V. K.

2017-06-01

One of the critical parts in rotating machines is bearings and most of the failure arises from the defective bearings. Bearing failure leads to failure of a machine and the unpredicted productivity loss in the performance. Therefore, bearing fault detection and prognosis is an integral part of the preventive maintenance procedures. In this paper vibration signal for four conditions of a deep groove ball bearing; normal (N), inner race defect (IRD), ball defect (BD) and outer race defect (ORD) were acquired from a customized bearing test rig, under four different conditions and three different fault sizes. Two approaches have been opted for statistical feature extraction from the vibration signal. In the first approach, raw signal is used for statistical feature extraction and in the second approach statistical features extracted are based on bearing damage index (BDI). The proposed BDI technique uses wavelet packet node energy coefficients analysis method. Both the features are used as inputs to an ANN classifier to evaluate its performance. A comparison of ANN performance is made based on raw vibration data and data chosen by using BDI. The ANN performance has been found to be fairly higher when BDI based signals were used as inputs to the classifier.

Effectiveness of ANN for seismic behaviour prediction considering geometric configuration effect in concrete gravity dams

Directory of Open Access Journals (Sweden)

Mohd. Saqib

2016-09-01

Full Text Available In this study, an Artificial Neural Networks (ANN model is built and verified for quick estimation of the structural parameter obtained for a concrete gravity dam section due to seismic excitation. The database of numerous inputs and outputs obtained through Abaqus which are further converted into dimensionless forms in the statistical software (MATLAB to build the ANN model. The developed model can be used for accurate estimation of this parameter. The results showed an excellent capability of the model to predict the outputs with high accuracy and reduced computational time.

WEPP and ANN models for simulating soil loss and runoff in a semi-arid Mediterranean region.

Science.gov (United States)

Albaradeyia, Issa; Hani, Azzedine; Shahrour, Isam

2011-09-01

This paper presents the use of both the Water Erosion Prediction Project (WEPP) and the artificial neural network (ANN) for the prediction of runoff and soil loss in the central highland mountainous of the Palestinian territories. Analyses show that the soil erosion is highly dependent on both the rainfall depth and the rainfall event duration rather than on the rainfall intensity as mostly mentioned in the literature. The results obtained from the WEPP model for the soil loss and runoff disagree with the field data. The WEPP underestimates both the runoff and soil loss. Analyses conducted with the ANN agree well with the observation. In addition, the global network models developed using the data of all the land use type show a relatively unbiased estimation for both runoff and soil loss. The study showed that the ANN model could be used as a management tool for predicting runoff and soil loss.

An ANN-based approach to predict blast-induced ground vibration of Gol-E-Gohar iron ore mine, Iran

Directory of Open Access Journals (Sweden)

Mahdi Saadat

2014-02-01

Full Text Available Blast-induced ground vibration is one of the inevitable outcomes of blasting in mining projects and may cause substantial damage to rock mass as well as nearby structures and human beings. In this paper, an attempt has been made to present an application of artificial neural network (ANN to predict the blast-induced ground vibration of the Gol-E-Gohar (GEG iron mine, Iran. A four-layer feed-forward back propagation multi-layer perceptron (MLP was used and trained with Levenberg–Marquardt algorithm. To construct ANN models, the maximum charge per delay, distance from blasting face to monitoring point, stemming and hole depth were taken as inputs, whereas peak particle velocity (PPV was considered as an output parameter. A database consisting of 69 data sets recorded at strategic and vulnerable locations of GEG iron mine was used to train and test the generalization capability of ANN models. Coefficient of determination (R2 and mean square error (MSE were chosen as the indicators of the performance of the networks. A network with architecture 4-11-5-1 and R2 of 0.957 and MSE of 0.000722 was found to be optimum. To demonstrate the supremacy of ANN approach, the same 69 data sets were used for the prediction of PPV with four common empirical models as well as multiple linear regression (MLR analysis. The results revealed that the proposed ANN approach performs better than empirical and MLR models.

Symbolism--The Main Artistic Style of Katherine Anne Porter's Short Stories

Science.gov (United States)

Wang, Ru

2010-01-01

The paper takes Katherine Anne Porter's two short stories: "Flowering Judas", "The Grave" as objects of study. It will try to analyze Porter's writing style through her imaginary conception, vivid psychological description and multiple symbolisms so that we can understand her studies and her attitudes to female psychological…

Kriminalinė pasaka: žanrų suliejimas istorijos atpirkimui Jayne Anne Phillips romane „Quiet Dell“

OpenAIRE

Milvidaitė, Salomėja

2016-01-01

Fairy Tale True Crime: Genre Bending for the Redemption of History in Jayne Anne Phillips' “Quiet Dell” Jayne Anne Phillips’ novel Quiet Dell (2013) depicts a true story concerning the infamous murders in the eponymous hamlet near Phillips’ hometown in West Virginia. The true crime story, however, is given a twist when the first ghostly appearance takes place. The purpose of the present BA paper is to analyse how, by employing various fantastic elements, the genres of true crime and fairy tal...

"I am the vampire for these times": Representations of Postmodernity in Anne Rice's The Vampire Chronicles

OpenAIRE

RINNE, ANTTI

2013-01-01

Anne Ricen The Vampire Chronicles -kirjasarjaa voidaan pitää vampyyrinarratiivien uutena aaltona 1970-luvulta lähtien. Ricen romaaneissa vampyyrit itse nousivat pääosaan kirjojen päähenkilöinä, ja romaanit tietyssä määrin irtautuivat vanhemman vampyyrikirjallisuuden kaavoista. Tutkimukseni aiheena ovat Anne Ricen romaanisarjan kolme ensimmäistä teosta, Interview with the Vampire (1976), The Vampire Lestat (1985) ja The Queen of the Damned (1988). Tutkielmani keskittyy siihen, kuinka kyseiset ...

A single-channel 10-bit 160 MS/s SAR ADC in 65 nm CMOS

International Nuclear Information System (INIS)

Lu Yuxiao; Sun Lu; Li Zhe; Zhou Jianjun

2014-01-01

This paper demonstrates a single-channel 10-bit 160 MS/s successive-approximation-register (SAR) analog-to-digital converter (ADC) in 65 nm CMOS process with a 1.2 V supply voltage. To achieve high speed, a new window-opening logic based on the asynchronous SAR algorithm is proposed to minimize the logic delay, and a partial set-and-down DAC with binary redundancy bits is presented to reduce the dynamic comparator offset and accelerate the DAC settling. Besides, a new bootstrapped switch with a pre-charge phase is adopted in the track and hold circuits to increase speed and reduce area. The presented ADC achieves 52.9 dB signal-to-noise distortion ratio and 65 dB spurious-free dynamic range measured with a 30 MHz input signal at 160 MHz clock. The power consumption is 9.5 mW and a core die area of 250 × 200 μm 2 is occupied. (semiconductor integrated circuits)

Application of back-propagation artificial neural network (ANN) to predict crystallite size and band gap energy of ZnO quantum dots

Science.gov (United States)

Pelicano, Christian Mark; Rapadas, Nick; Cagatan, Gerard; Magdaluyo, Eduardo

2017-12-01

Herein, the crystallite size and band gap energy of zinc oxide (ZnO) quantum dots were predicted using artificial neural network (ANN). Three input factors including reagent ratio, growth time, and growth temperature were examined with respect to crystallite size and band gap energy as response factors. The generated results from neural network model were then compared with the experimental results. Experimental crystallite size and band gap energy of ZnO quantum dots were measured from TEM images and absorbance spectra, respectively. The Levenberg-Marquardt (LM) algorithm was used as the learning algorithm for the ANN model. The performance of the ANN model was then assessed through mean square error (MSE) and regression values. Based on the results, the ANN modelling results are in good agreement with the experimental data.

Applying a supervised ANN (artificial neural network) approach to the prognostication of driven wheel energy efficiency indices

International Nuclear Information System (INIS)

Taghavifar, Hamid; Mardani, Aref

2014-01-01

This paper examines the prediction of energy efficiency indices of driven wheels (i.e. traction coefficient and tractive power efficiency) as affected by wheel load, slippage and forward velocity at three different levels with three replicates to form a total of 162 data points. The pertinent experiments were carried out in the soil bin testing facility. A feed-forward ANN (artificial neural network) with standard BP (back propagation) algorithm was practiced to construct a supervised representation to predict the energy efficiency indices of driven wheels. It was deduced, in view of the statistical performance criteria (i.e. MSE (mean squared error) and R 2 ), that a supervised ANN with 3-8-10-2 topology and Levenberg–Marquardt training algorithm represented the optimal model. Modeling implementations indicated that ANN is a powerful technique to prognosticate the stochastic energy efficiency indices as affected by soil-wheel interactions with MSE of 0.001194 and R 2 of 0.987 and 0.9772 for traction coefficient and tractive power efficiency. It was found that traction coefficient and tractive power efficiency increase with increased slippage. A similar trend is valid for the influence of wheel load on the objective parameters. Wherein increase of velocity led to an increment of tractive power efficiency, velocity had no significant effect on traction coefficient. - Highlights: • Energy efficiency indexes were assessed as affected by tire parameters. • ANN was applied for prognostication of the objective parameters. • A 3-8-10-2 ANN with MSE of 0.001194 and R 2 of 0.987 and 0.9772 was designated as optimal model. • Optimal values of learning rate and momentum were found 0.9 and 0.5, respectively

Jo Ann Baumgartner and Sam Earnshaw: Organizers and Farmers

OpenAIRE

Rabkin, Sarah

2010-01-01

Jo Ann Baumgartner directs the Wild Farm Alliance, based in Watsonville, California. WFA’s mission, as described on the organization’s website, is “to promote agriculture that helps to protect and restore wild Nature.” Through research, publications, presentations, events, policy work, and consulting, the organization works to “connect food systems with ecosystems.” Sam Earnshaw is Central Coast regional coordinator of the Community Alliance with Family Farmers. Working with CAFF’s f...

Exploring QSARs of the interaction of flavonoids with GABA (A) receptor using MLR, ANN and SVM techniques.

Science.gov (United States)

Deeb, Omar; Shaik, Basheerulla; Agrawal, Vijay K

2014-10-01

Quantitative Structure-Activity Relationship (QSAR) models for binding affinity constants (log Ki) of 78 flavonoid ligands towards the benzodiazepine site of GABA (A) receptor complex were calculated using the machine learning methods: artificial neural network (ANN) and support vector machine (SVM) techniques. The models obtained were compared with those obtained using multiple linear regression (MLR) analysis. The descriptor selection and model building were performed with 10-fold cross-validation using the training data set. The SVM and MLR coefficient of determination values are 0.944 and 0.879, respectively, for the training set and are higher than those of ANN models. Though the SVM model shows improvement of training set fitting, the ANN model was superior to SVM and MLR in predicting the test set. Randomization test is employed to check the suitability of the models.

Mart ja Mari-Ann Susi taotlevad omanikena Concordia pankrotti / Andri Maimets

Index Scriptorium Estoniae

Maimets, Andri

2003-01-01

Concordia Ülikooli rektori kohast loobunud Mart Susi ning prorektori ametikohalt lahkunud Mari-Ann Susi taotlevad neile kuuluvat ülikooli pidanud miljonivõlgades firma pankrotti. Hiljuti loodi õppejõududest, tudengitest js töötajatest mittetulundusühing Concordia Akadeemiline Ühisus (CAU), selle nõukogu esimees on Hagi Šein

On-line dynamic monitoring automotive exhausts: using BP-ANN for distinguishing multi-components

Science.gov (United States)

Zhao, Yudi; Wei, Ruyi; Liu, Xuebin

2017-10-01

Remote sensing-Fourier Transform infrared spectroscopy (RS-FTIR) is one of the most important technologies in atmospheric pollutant monitoring. It is very appropriate for on-line dynamic remote sensing monitoring of air pollutants, especially for the automotive exhausts. However, their absorption spectra are often seriously overlapped in the atmospheric infrared window bands, i.e. MWIR (3 5μm). Artificial Neural Network (ANN) is an algorithm based on the theory of the biological neural network, which simplifies the partial differential equation with complex construction. For its preferable performance in nonlinear mapping and fitting, in this paper we utilize Back Propagation-Artificial Neural Network (BP-ANN) to quantitatively analyze the concentrations of four typical industrial automotive exhausts, including CO, NO, NO2 and SO2. We extracted the original data of these automotive exhausts from the HITRAN database, most of which virtually overlapped, and established a mixed multi-component simulation environment. Based on Beer-Lambert Law, concentrations can be retrieved from the absorbance of spectra. Parameters including learning rate, momentum factor, the number of hidden nodes and iterations were obtained when the BP network was trained with 80 groups of input data. By improving these parameters, the network can be optimized to produce necessarily higher precision for the retrieved concentrations. This BP-ANN method proves to be an effective and promising algorithm on dealing with multi-components analysis of automotive exhausts.

Numerical weather prediction (NWP) and hybrid ARMA/ANN model to predict global radiation

International Nuclear Information System (INIS)

Voyant, Cyril; Muselli, Marc; Paoli, Christophe; Nivet, Marie-Laure

2012-01-01

We propose in this paper an original technique to predict global radiation using a hybrid ARMA/ANN model and data issued from a numerical weather prediction model (NWP). We particularly look at the multi-layer perceptron (MLP). After optimizing our architecture with NWP and endogenous data previously made stationary and using an innovative pre-input layer selection method, we combined it to an ARMA model from a rule based on the analysis of hourly data series. This model has been used to forecast the hourly global radiation for five places in Mediterranean area. Our technique outperforms classical models for all the places. The nRMSE for our hybrid model MLP/ARMA is 14.9% compared to 26.2% for the naïve persistence predictor. Note that in the standalone ANN case the nRMSE is 18.4%. Finally, in order to discuss the reliability of the forecaster outputs, a complementary study concerning the confidence interval of each prediction is proposed. -- Highlights: ► Time series forecasting with hybrid method based on the use of ALADIN numerical weather model, ANN and ARMA. ► Innovative pre-input layer selection method. ► Combination of optimized MLP and ARMA model obtained from a rule based on the analysis of hourly data series. ► Stationarity process (method and control) for the global radiation time series.

Modelling the spectral irradiance distribution in sunny inland locations using an ANN-based methodology

International Nuclear Information System (INIS)

Torres-Ramírez, M.; Elizondo, D.; García-Domingo, B.; Nofuentes, G.; Talavera, D.L.

2015-01-01

This work is aimed at verifying that in sunny inland locations artificial intelligence techniques may provide an estimation of the spectral irradiance with adequate accuracy for photovoltaic applications. An ANN (artificial neural network) based method was developed, trained and tested to model the spectral distributions between wavelengths ranging from 350 to 1050 nm. Only commonly available input data such as geographical information regarding location, specific date and time together with horizontal global irradiance and ambient temperature are required. Historical information from a 24-month experimental campaign carried out in Jaén (Spain) provided the necessary data to train and test the ANN tool. A Kohonen self-organized map was used as innovative technique to classify the whole input dataset and build a small and representative training dataset. The shape of the spectral irradiance distribution, the in-plane global irradiance (G T ) and irradiation (H T ) and the APE (average photon energy) values obtained through the ANN method were statistically compared to the experimental ones. In terms of shape distribution fitting, the mean relative deformation error stays below 4.81%. The root mean square percentage error is around 6.89% and 0.45% when estimating G T and APE, respectively. Regarding H T , errors lie below 3.18% in all cases. - Highlights: • ANN-based model to estimate the spectral irradiance distribution in sunny inland locations. • MRDE value stay below 4.81% in spectral irradiance distribution shape fitting. • RMSPE is about 6.89% for the in-plane global irradiance and 0.45% for the average photon energy. • Errors stay below 3.18% for all the months of the year in incident irradiation terms. • Improvement of assessment of the impact of the solar spectrum in the performance of a PV module

Development of ANN-based models to predict the static response and dynamic response of a heat exchanger in a real MVAC system

International Nuclear Information System (INIS)

Hu Qinhua; So, Albert T P; Tse, W L; Ren, Qingchang

2005-01-01

This paper presents a systematic approach to develop artificial neural network (ANN) models to predict the performance of a heat exchanger operating in real mechanical ventilation and air-conditioning (MVAC) system. Two approaches were attempted and presented. Every detailed components of the MVAC system have been considered and we attempt to model each of them by one ANN. This study used the neural network technique to obtain a static and a dynamic model for a heat exchanger mounted in an air handler unit (AHU), which is the key component of the MVAC system. It has been verified that almost all of the predicted values of the ANN model were within 95% - 105% of the measured values, with a consistent mean relative error (MRE) smaller than 2.5%. The paper details our experiences in using ANNs, especially those with back-propagation (BP) structures. Also, the weights and biases of our trained-up ANN models are listed out, which serve as good reference for readers to deal with their own situations

Alice-Anne Martin (1926 - 2016)

CERN Multimedia

2016-01-01

Alice-Anne Martin, known as “Schu” from her maiden name Schubert, passed away on 8 January 2016.   (Image: Gérard Bertin) Hired the year CERN was founded, 1954, when the construction of the Laboratory had not even begun, Schu first worked at the Villa de Cointrin (a historic building now within the grounds of Geneva airport) as a secretary. In this role, she typed the convention between CERN and the Swiss Confederation, prepared by Stéphanie Tixier, as well as some of the "Yellow Reports" that have marked key points in the Laboratory’s history. For example, using a special typewriter with two keyboards – Latin and Greek – she typed the Yellow Report on the KAM theorem by Rolf Hagedorn. Schu also worked with Felix Bloch, the first Director-General of CERN, and later became the secretary of Herbert Coblenz, the first CERN librarian. She was head of the team that edited the proceedings of the ...

The Sally-Anne Test: An Interactional Analysis of a Dyadic Assessment

Science.gov (United States)

Korkiakangas, Terhi; Dindar, Katja; Laitila, Aarno; Kärnä, Eija

2016-01-01

Background: The Sally-Anne test has been extensively used to examine children's theory of mind understanding. Many task-related factors have been suggested to impact children's performance on this test. Yet little is known about the interactional aspects of such dyadic assessment situations that might contribute to the ways in which children…

2006 Maryland Department of Natural Resources Lidar: Caroline, Kent and Queen Anne Counties

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Maryland Department of Natural Resources requested the collection of LIDAR data over Kent, Queen Anne and Caroline Counties, MD. In response, EarthData acquired the...

Predicting PM10 concentration in Seoul metropolitan subway stations using artificial neural network (ANN).

Science.gov (United States)

Park, Sechan; Kim, Minjeong; Kim, Minhae; Namgung, Hyeong-Gyu; Kim, Ki-Tae; Cho, Kyung Hwa; Kwon, Soon-Bark

2018-01-05

The indoor air quality of subway systems can significantly affect the health of passengers since these systems are widely used for short-distance transit in metropolitan urban areas in many countries. The particles generated by abrasion during subway operations and the vehicle-emitted pollutants flowing in from the street in particular affect the air quality in underground subway stations. Thus the continuous monitoring of particulate matter (PM) in underground station is important to evaluate the exposure level of PM to passengers. However, it is difficult to obtain indoor PM data because the measurement systems are expensive and difficult to install and operate for significant periods of time in spaces crowded with people. In this study, we predicted the indoor PM concentration using the information of outdoor PM, the number of subway trains running, and information on ventilation operation by the artificial neural network (ANN) model. As well, we investigated the relationship between ANN's performance and the depth of underground subway station. ANN model showed a high correlation between the predicted and actual measured values and it was able to predict 67∼80% of PM at 6 subway station. In addition, we found that platform shape and depth influenced the model performance. Copyright © 2017 Elsevier B.V. All rights reserved.

78 FR 65380 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

Science.gov (United States)

2013-10-31

... the University of Michigan, Ann Arbor, MI. The human remains were removed from Alpena, Isabella, Grand... removed from the Devil River Mound site (20AL1) in Alpena County, MI. A resident of Ossineke, MI...

Prediction of temperature and HAZ in thermal-based processes with Gaussian heat source by a hybrid GA-ANN model

Science.gov (United States)

Fazli Shahri, Hamid Reza; Mahdavinejad, Ramezanali

2018-02-01

Thermal-based processes with Gaussian heat source often produce excessive temperature which can impose thermally-affected layers in specimens. Therefore, the temperature distribution and Heat Affected Zone (HAZ) of materials are two critical factors which are influenced by different process parameters. Measurement of the HAZ thickness and temperature distribution within the processes are not only difficult but also expensive. This research aims at finding a valuable knowledge on these factors by prediction of the process through a novel combinatory model. In this study, an integrated Artificial Neural Network (ANN) and genetic algorithm (GA) was used to predict the HAZ and temperature distribution of the specimens. To end this, a series of full factorial design of experiments were conducted by applying a Gaussian heat flux on Ti-6Al-4 V at first, then the temperature of the specimen was measured by Infrared thermography. The HAZ width of each sample was investigated through measuring the microhardness. Secondly, the experimental data was used to create a GA-ANN model. The efficiency of GA in design and optimization of the architecture of ANN was investigated. The GA was used to determine the optimal number of neurons in hidden layer, learning rate and momentum coefficient of both output and hidden layers of ANN. Finally, the reliability of models was assessed according to the experimental results and statistical indicators. The results demonstrated that the combinatory model predicted the HAZ and temperature more effective than a trial-and-error ANN model.

A call for water-efficient technologies (an interview with dr. Anne Elings)

NARCIS (Netherlands)

Elings, A.

2012-01-01

During the recent International Flower Trade Expo in Nairobi, Wageningen UR Greenhouse Horticulture project leader and greenhouse horticulture specialist Anne Elings pointed out that Kenya is not a water scarce country but management of the same is wanting. HortiNews had a chat with him.

Intra- and inter-population polymorphism in Coletinia maggii (Grassi, 1887) (Zygentoma: Nicoletiidae), an inhabitant of soil, mesovoid shallow substratum (MSS) and caves--A challenge for the strict classification of subterranean fauna?

Science.gov (United States)

Gilgado, José D; Ortuño, Vicente M

2015-02-19

New locations of Coletinia maggii (Grassi, 1887) have been discovered in the center of the Iberian Peninsula in different types of subterranean environments, such as a stony layer in the subsoil of an alluvial plain, an alluvial Mesovoid Shallow Substratum or Milieu Souterrain Superficiel (MSS) and a gypsum cave. This is the first record of both an alluvial MSS in the center of the Iberian Peninsula and of a subterranean species living in it. The high number of specimens captured allowed the first detailed study of the morphological intra- and inter-population variations of this species. The implications of its presence in these different environments, its wide distribution area across Europe, and the relevance of the morphological variation in the characters for the taxonomy of this species are discussed. Based on the results, Coletinia hernandoi Molero, Bach & Gaju, 2013 is proposed as a new synonym of C. maggii.

Comparing SVM and ANN based Machine Learning Methods for Species Identification of Food Contaminating Beetles.

Science.gov (United States)

Bisgin, Halil; Bera, Tanmay; Ding, Hongjian; Semey, Howard G; Wu, Leihong; Liu, Zhichao; Barnes, Amy E; Langley, Darryl A; Pava-Ripoll, Monica; Vyas, Himansu J; Tong, Weida; Xu, Joshua

2018-04-25

Insect pests, such as pantry beetles, are often associated with food contaminations and public health risks. Machine learning has the potential to provide a more accurate and efficient solution in detecting their presence in food products, which is currently done manually. In our previous research, we demonstrated such feasibility where Artificial Neural Network (ANN) based pattern recognition techniques could be implemented for species identification in the context of food safety. In this study, we present a Support Vector Machine (SVM) model which improved the average accuracy up to 85%. Contrary to this, the ANN method yielded ~80% accuracy after extensive parameter optimization. Both methods showed excellent genus level identification, but SVM showed slightly better accuracy  for most species. Highly accurate species level identification remains a challenge, especially in distinguishing between species from the same genus which may require improvements in both imaging and machine learning techniques. In summary, our work does illustrate a new SVM based technique and provides a good comparison with the ANN model in our context. We believe such insights will pave better way forward for the application of machine learning towards species identification and food safety.

Dispersion compensation of fiber optic communication system with direct detection using artificial neural networks (ANNs)

Science.gov (United States)

Maghrabi, Mahmoud M. T.; Kumar, Shiva; Bakr, Mohamed H.

2018-02-01

This work introduces a powerful digital nonlinear feed-forward equalizer (NFFE), exploiting multilayer artificial neural network (ANN). It mitigates impairments of optical communication systems arising due to the nonlinearity introduced by direct photo-detection. In a direct detection system, the detection process is nonlinear due to the fact that the photo-current is proportional to the absolute square of the electric field intensity. The proposed equalizer provides the most efficient computational cost with high equalization performance. Its performance is comparable to the benchmark compensation performance achieved by maximum-likelihood sequence estimator. The equalizer trains an ANN to act as a nonlinear filter whose impulse response removes the intersymbol interference (ISI) distortions of the optical channel. Owing to the proposed extensive training of the equalizer, it achieves the ultimate performance limit of any feed-forward equalizer (FFE). The performance and efficiency of the equalizer is investigated by applying it to various practical short-reach fiber optic communication system scenarios. These scenarios are extracted from practical metro/media access networks and data center applications. The obtained results show that the ANN-NFFE compensates for the received BER degradation and significantly increases the tolerance to the chromatic dispersion distortion.

A comparative study of ANN and neuro-fuzzy for the prediction of ...

Indian Academy of Sciences (India)

Istanbul Technical University, Faculty of Civil Engineering, Hydraulics and Water. Resources Division, Maslak 34469, Istanbul, Turkey. Singh et al (2005) examined the potential of the ANN and neuro-fuzzy systems application for the prediction of dynamic constant of rockmass. However, the model proposed by them has ...

ANN Surface Roughness Optimization of AZ61 Magnesium Alloy Finish Turning: Minimum Machining Times at Prime Machining Costs

Directory of Open Access Journals (Sweden)

Adel Taha Abbas

2018-05-01

Full Text Available Magnesium alloys are widely used in aerospace vehicles and modern cars, due to their rapid machinability at high cutting speeds. A novel Edgeworth–Pareto optimization of an artificial neural network (ANN is presented in this paper for surface roughness (Ra prediction of one component in computer numerical control (CNC turning over minimal machining time (Tm and at prime machining costs (C. An ANN is built in the Matlab programming environment, based on a 4-12-3 multi-layer perceptron (MLP, to predict Ra, Tm, and C, in relation to cutting speed, vc, depth of cut, ap, and feed per revolution, fr. For the first time, a profile of an AZ61 alloy workpiece after finish turning is constructed using an ANN for the range of experimental values vc, ap, and fr. The global minimum length of a three-dimensional estimation vector was defined with the following coordinates: Ra = 0.087 μm, Tm = 0.358 min/cm3, C = $8.2973. Likewise, the corresponding finish-turning parameters were also estimated: cutting speed vc = 250 m/min, cutting depth ap = 1.0 mm, and feed per revolution fr = 0.08 mm/rev. The ANN model achieved a reliable prediction accuracy of ±1.35% for surface roughness.

Development of a new software tool, based on ANN technology, in neutron spectrometry and dosimetry research

International Nuclear Information System (INIS)

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

2007-01-01

Artificial Intelligence is a branch of study which enhances the capability of computers by giving them human-like intelligence. The brain architecture has been extensively studied and attempts have been made to emulate it as in the Artificial Neural Network technology. A large variety of neural network architectures have been developed and they have gained wide-spread popularity over the last few decades. Their application is considered as a substitute for many classical techniques that have been used for many years, as in the case of neutron spectrometry and dosimetry research areas. In previous works, a new approach called Robust Design of Artificial Neural network was applied to build an ANN topology capable to solve the neutron spectrometry and dosimetry problems within the Mat lab programming environment. In this work, the knowledge stored at Mat lab ANN's synaptic weights was extracted in order to develop for first time a customized software application based on ANN technology, which is proposed to be used in the neutron spectrometry and simultaneous dosimetry fields. (Author)

Development of a new software tool, based on ANN technology, in neutron spectrometry and dosimetry research

Energy Technology Data Exchange (ETDEWEB)

Ortiz R, J.M.; Martinez B, M.R.; Vega C, H.R. [Universidad Autonoma de Zacatecas, Av. Ramon Lopez Velarde 801, A.P. 336, 98000 Zacatecas (Mexico)

2007-07-01

Artificial Intelligence is a branch of study which enhances the capability of computers by giving them human-like intelligence. The brain architecture has been extensively studied and attempts have been made to emulate it as in the Artificial Neural Network technology. A large variety of neural network architectures have been developed and they have gained wide-spread popularity over the last few decades. Their application is considered as a substitute for many classical techniques that have been used for many years, as in the case of neutron spectrometry and dosimetry research areas. In previous works, a new approach called Robust Design of Artificial Neural network was applied to build an ANN topology capable to solve the neutron spectrometry and dosimetry problems within the Mat lab programming environment. In this work, the knowledge stored at Mat lab ANN's synaptic weights was extracted in order to develop for first time a customized software application based on ANN technology, which is proposed to be used in the neutron spectrometry and simultaneous dosimetry fields. (Author)

Comparative study of landslides susceptibility mapping methods: Multi-Criteria Decision Making (MCDM) and Artificial Neural Network (ANN)

Science.gov (United States)

Salleh, S. A.; Rahman, A. S. A. Abd; Othman, A. N.; Mohd, W. M. N. Wan

2018-02-01

As different approach produces different results, it is crucial to determine the methods that are accurate in order to perform analysis towards the event. This research aim is to compare the Rank Reciprocal (MCDM) and Artificial Neural Network (ANN) analysis techniques in determining susceptible zones of landslide hazard. The study is based on data obtained from various sources such as local authority; Dewan Bandaraya Kuala Lumpur (DBKL), Jabatan Kerja Raya (JKR) and other agencies. The data were analysed and processed using Arc GIS. The results were compared by quantifying the risk ranking and area differential. It was also compared with the zonation map classified by DBKL. The results suggested that ANN method gives better accuracy compared to MCDM with 18.18% higher accuracy assessment of the MCDM approach. This indicated that ANN provides more reliable results and it is probably due to its ability to learn from the environment thus portraying realistic and accurate result.

Les crises soudanaises des années 80

OpenAIRE

Ahmed, Medani M.; al-Shazali, Salah al-Din; al-Shazali, Salah al-Din; al-Shazali, Salah al-Din; al-Shazali, Salah al-Din; Al-Tom, Abdulahi Osman; Babiker, Mustafa; Babiker, Mustafa; Blin, Louis; Conte, Édouard; Elmekki, Abdelgalil M.; Gore, Paul W.; Hamid, Mohammed Beshir; Ireton, François; Jacquemond, Richard

2008-01-01

Ce dossier est constitué, dans sa quasi-totalité, de contributions de chercheurs et universitaires soudanais proposant une analyse de certains des problèmes cruciaux que leur pays a connus depuis le début des années 80. Les articles qui le composent correspondent aux communications qui devaient initialement être présentées lors d’un colloque portant sur le même thème, prévu à Paris pour décembre 1991 et qui n'a pu avoir lieu du fait de l’impossibilité où se trouvaient certains de ses particip...

Ann modeling of kerf transfer in Co2 laser cutting and optimization of cutting parameters using monte carlo method

Directory of Open Access Journals (Sweden)

Miloš Madić

2015-01-01

Full Text Available In this paper, an attempt has been made to develop a mathematical model in order to study the relationship between laser cutting parameters such as laser power, cutting speed, assist gas pressure and focus position, and kerf taper angle obtained in CO2 laser cutting of AISI 304 stainless steel. To this aim, a single hidden layer artificial neural network (ANN trained with gradient descent with momentum algorithm was used. To obtain an experimental database for the ANN training, laser cutting experiment was planned as per Taguchi’s L27 orthogonal array with three levels for each of the cutting parameters. Statistically assessed as adequate, ANN model was then used to investigate the effect of the laser cutting parameters on the kerf taper angle by generating 2D and 3D plots. It was observed that the kerf taper angle was highly sensitive to the selected laser cutting parameters, as well as their interactions. In addition to modeling, by applying the Monte Carlo method on the developed kerf taper angle ANN model, the near optimal laser cutting parameter settings, which minimize kerf taper angle, were determined.

A vitamini ve anne çocuk sağlığı Derleme

OpenAIRE

Günlemez, Ayla; Atasay, Begüm; Arsan, Saadet

2014-01-01

A vitamini normal görmede hücre farklılaşmasında çoğalmasında ve epitelial bütünlüğün sağlanmasında kritik rol oynar Gelişmekte olan ülkelerde A vitamini eksikliği önemli ve önlenebilir halk sağlığı sorunlarından biridir Bu makalede dünyada ve Türkiye’de A vitamini eksikliği ve anne çocuk sağlığı üzerine etkileri tartışılmaktadır Anahtar Kelimeler: A vitamini anne sağlığı çocuk sağlığıSummaryVitamin A has a critical role in normal vision cell differantiation proliferation and maintanence of e...

Prediction by Artificial Neural Networks (ANN of the diffusivity, mass, moisture, volume and solids on osmotically dehydrated yacon (Smallantus sonchifolius

Directory of Open Access Journals (Sweden)

Julio Rojas Naccha

2012-09-01

Full Text Available The predictive ability of Artificial Neural Network (ANN on the effect of the concentration (30, 40, 50 y 60 % w/w and temperature (30, 40 y 50°C of fructooligosaccharides solution, in the mass, moisture, volume and solids of osmodehydrated yacon cubes, and in the coefficients of the water means effective diffusivity with and without shrinkage was evaluated. The Feedforward type ANN with the Backpropagation training algorithms and the Levenberg-Marquardt weight adjustment was applied, using the following topology: 10-5 goal error, 0.01 learning rate, 0.5 moment coefficient, 2 input neurons, 6 output neurons, one hidden layer with 18 neurons, 15 training stages and logsig-pureline transfer functions. The overall average error achieved by the ANN was 3.44% and correlation coefficients were bigger than 0.9. No significant differences were found between the experimental values and the predicted values achieved by the ANN and with the predicted values achieved by a statistical model of second-order polynomial regression (p > 0.95.

Artificial Neural Network (ANN) design for Hg-Se interactions and their effect on reduction of Hg uptake by radish plant

International Nuclear Information System (INIS)

Kumar Rohit Raj; Abhishek Kardam; Shalini Srivastava; Jyoti Kumar Arora

2010-01-01

The tendency of selenium to interact with heavy metals in presence of naturally occurring species has been exploited for the development of green bioremediation of toxic metals from soil using Artificial Neural Network (ANN) modeling. The cross validation of the data for the reduction in uptake of Hg(II) ions in the plant R. sativus grown in soil and sand culture in presence of selenium has been used for ANN modeling. ANN model based on the combination of back propagation and principal component analysis was able to predict the reduction in Hg uptake with a sigmoid axon transfer function. The data of fifty laboratory experimental sets were used for structuring single layer ANN model. Series of experiments resulted into the performance evaluation based on considering 20% data for testing and 20% data for cross validation at 1,500 Epoch with 0.70 momentums The Levenberg-Marquardt algorithm (LMA) was found as the best of BP algorithms with a minimum mean squared error at the eighth place of the decimal for training (MSE) and cross validation. (author)

Ann Modeling for Grey Particles Produced from Interactions of Different Projectiles with Emulsion Nuclei at 4.5 AGEV/C

International Nuclear Information System (INIS)

El-Bakry, M.N.Y.; Basha, A.M.; Rashed, N.; Mahmoud, M.A.; Radi, A.

2008-01-01

Artificial Neural Network (ANN) is one of the important tools in high energy physics. In this paper, we are using ANN for modeling the multiplicity distributions of grey particles produced from interactions of P, 3 He, 4 He, 6 Li, 12 C, 24 Mg, and 32 S with emulsion nuclei, light nuclei (CNO), and heavy nuclei (Ag Br). The equations of these distributions were obtained

Rimbaud’s influence on Jayne Anne Phillips: from Sweethearts to Shelter

Directory of Open Access Journals (Sweden)

Stéphanie Durrans

2012-06-01

Full Text Available Arthur Rimbaud emerges from Jayne Anne Phillips���s essays as a continual source of fascination. This paper explores the patterns of convergence that unite these two writers one century apart while aiming to provide a deeper and more meaningful appreciation of Phillips’ accomplishments in Shelter. It focuses on Rimbaud’s and Phillips’ conception of language and their emphasis on "visionary writing", before investigating the significance of such patterns on Shelter and exploring the stylistic affinities linking their respective works. In the end, linguistic deconstruction and regeneration appears as one of the ways in which both writers seek to express the hidden traumas of a society in the grips of violence.A en juger par les quelques essais de Jayne Anne Phillips dans lesquels il est mentionné, Arthur Rimbaud semble avoir exercé une véritable fascination sur la jeune nouvelliste et romancière américaine au moins jusque dans les années 1990. Cet article explore la filiation littéraire entre deux auteurs mus par un même souci de renouveler la langue par l’élaboration d’une « écriture visionnaire », à rebours des cadres normatifs et de toute pensée logique. A ce titre, le roman Shelter (1994 apparaît comme l’hommage le plus appuyé rendu par Phillips au poète français, notamment par le double processus de déconstruction et de régénération linguistique qui permet à son auteur d’exprimer les traumatismes individuels et collectifs d’une société hantée par la violence.

BP-ANN for fitting the temperature-germination model and its application in predicting sowing time and region for Bermudagrass.

Directory of Open Access Journals (Sweden)

Erxu Pi

Full Text Available Temperature is one of the most significant environmental factors that affects germination of grass seeds. Reliable prediction of the optimal temperature for seed germination is crucial for determining the suitable regions and favorable sowing timing for turf grass cultivation. In this study, a back-propagation-artificial-neural-network-aided dual quintic equation (BP-ANN-QE model was developed to improve the prediction of the optimal temperature for seed germination. This BP-ANN-QE model was used to determine optimal sowing times and suitable regions for three Cynodon dactylon cultivars (C. dactylon, 'Savannah' and 'Princess VII'. Prediction of the optimal temperature for these seeds was based on comprehensive germination tests using 36 day/night (high/low temperature regimes (both ranging from 5/5 to 40/40°C with 5°C increments. Seed germination data from these temperature regimes were used to construct temperature-germination correlation models for estimating germination percentage with confidence intervals. Our tests revealed that the optimal high/low temperature regimes required for all the three bermudagrass cultivars are 30/5, 30/10, 35/5, 35/10, 35/15, 35/20, 40/15 and 40/20°C; constant temperatures ranging from 5 to 40°C inhibited the germination of all three cultivars. While comparing different simulating methods, including DQEM, Bisquare ANN-QE, and BP-ANN-QE in establishing temperature based germination percentage rules, we found that the R(2 values of germination prediction function could be significantly improved from about 0.6940-0.8177 (DQEM approach to 0.9439-0.9813 (BP-ANN-QE. These results indicated that our BP-ANN-QE model has better performance than the rests of the compared models. Furthermore, data of the national temperature grids generated from monthly-average temperature for 25 years were fit into these functions and we were able to map the germination percentage of these C. dactylon cultivars in the national scale

Damage level prediction of non-reshaped berm breakwater using ANN, SVM and ANFIS models

Digital Repository Service at National Institute of Oceanography (India)

Mandal, S.; SubbaRao; Harish, N.; Lokesha

Marine Structures Laboratory, Department of Applied Mechanics and Hydraulics, NITK, Surathkal, India. Soft computing techniques like Artificial Neural Network (ANN), Support Vector Machine (SVM) and Adaptive Neuro Fuzzy Inference system (ANFIS) models...

Prediction of Frequency for Simulation of Asphalt Mix Fatigue Tests Using MARS and ANN

Directory of Open Access Journals (Sweden)

Ali Reza Ghanizadeh

2014-01-01

Full Text Available Fatigue life of asphalt mixes in laboratory tests is commonly determined by applying a sinusoidal or haversine waveform with specific frequency. The pavement structure and loading conditions affect the shape and the frequency of tensile response pulses at the bottom of asphalt layer. This paper introduces two methods for predicting the loading frequency in laboratory asphalt fatigue tests for better simulation of field conditions. Five thousand (5000 four-layered pavement sections were analyzed and stress and strain response pulses in both longitudinal and transverse directions was determined. After fitting the haversine function to the response pulses by the concept of equal-energy pulse, the effective length of the response pulses were determined. Two methods including Multivariate Adaptive Regression Splines (MARS and Artificial Neural Network (ANN methods were then employed to predict the effective length (i.e., frequency of tensile stress and strain pulses in longitudinal and transverse directions based on haversine waveform. It is indicated that, under controlled stress and strain modes, both methods (MARS and ANN are capable of predicting the frequency of loading in HMA fatigue tests with very good accuracy. The accuracy of ANN method is, however, more than MARS method. It is furthermore shown that the results of the present study can be generalized to sinusoidal waveform by a simple equation.

Transient stability enhancement of wind farms connected to a multi-machine power system by using an adaptive ANN-controlled SMES

International Nuclear Information System (INIS)

Muyeen, S.M.; Hasanien, Hany M.; Al-Durra, Ahmed

2014-01-01

Highlights: • We present an ANN-controlled SMES in this paper. • The objective is to enhance transient stability of WF connected to power system. • The control strategy depends on a PWM VSC and DC–DC converter. • The effectiveness of proposed controller is compared with PI controller. • The validity of the proposed system is verified by simulation results. - Abstract: This paper presents a novel adaptive artificial neural network (ANN)-controlled superconducting magnetic energy storage (SMES) system to enhance the transient stability of wind farms connected to a multi-machine power system during network disturbances. The control strategy of SMES depends mainly on a sinusoidal pulse width modulation (PWM) voltage source converter (VSC) and an adaptive ANN-controlled DC–DC converter using insulated gate bipolar transistors (IGBTs). The effectiveness of the proposed adaptive ANN-controlled SMES is then compared with that of proportional-integral (PI)-controlled SMES optimized by response surface methodology and genetic algorithm (RSM–GA) considering both of symmetrical and unsymmetrical faults. For realistic responses, real wind speed data and two-mass drive train model of wind turbine generator system is considered in the analyses. The validity of the proposed system is verified by the simulation results which are performed using the laboratory standard dynamic power system simulator PSCAD/EMTDC. Notably, the proposed adaptive ANN-controlled SMES enhances the transient stability of wind farms connected to a multi-machine power system

Ann O'Mara, PhD, RN, MPH | Division of Cancer Prevention

Science.gov (United States)

Dr. Ann O'Mara is Head of Palliative Research in the NCI Division of Cancer Prevention. She manages a portfolio of symptom management and palliative and end-of-life care research projects. The majority of these projects focus on the more common morbidities associated with cancer and its treatment, e.g., pain, chemotherapy induced neuropathy, fatigue, sleep disturbances, and

Rapport de frais de 2017-2018 pour Mary Anne Chambers | CRDI ...

International Development Research Centre (IDRC) Digital Library (Canada)

Rapport de frais de 2017-2018 pour Mary Anne Chambers. Total des frais de déplacement : CAD$17,362.55. Réunion du Conseil des gouverneurs. 19 novembre 2017 au 24 novembre 2017. CAD$2,185.41. Réunions au CRDI 1 novembre 2017 CAD$714.15. Constatation de l'impact de la recherche en Afrique de l'Est.

Anne Applebaum: Kas NATO lõpp on lähedal? / Indrek Veiserik

Index Scriptorium Estoniae

Veiserik, Indrek

2009-01-01

USA ajakirjaniku Anne Applebaumi kriitikast NATO kui organisatsiooni toimimise ja Afganistani missiooni suhtes. Kesknädala arvates võiks president Toomas Hendrik Ilves, kes on annetanud A. Applebaumile Maarjamaa Risti III klassi teenetemärgi, kuulata tema välispoliitilisi seisukohti. Viidatakse ka Kanada kindrali Rick Hillieri kriitikale NATO kohta

Inverse problems using ANN in long range atmospheric dispersion with signature analysis picked scattered numerical sensors from CFD

International Nuclear Information System (INIS)

Sharma, Pavan K.; Gera, B.; Ghosh, A.K.; Kushwaha, H.S.

2010-01-01

Scalar dispersion in the atmosphere is an important area wherein different approaches are followed in development of good analytical model. The analyses based on Computational Fluid Dynamics (CFD) codes offer an opportunity of model development based on first principles of physics and hence such models have an edge over the existing models. Both forward and backward calculation methods are being developed for atmospheric dispersion around NPPs at BARC Forward modeling methods, which describe the atmospheric transport from sources to receptors, use forward-running transport and dispersion models or computational fluid dynamics models which are run many times, and the resulting dispersion field is compared to observations from multiple sensors. Backward or inverse modeling methods use only one model run in the reverse direction from the receptors to estimate the upwind sources. Inverse modeling methods include adjoint and tangent linear models, Kalman filters, and variational data assimilation, and neural network. The present paper is aimed at developing a new approach where the identified specific signatures at receptor points form the basis for source estimation or inversions. This approach is expected to reduce the large transient data sets to reduced and meaningful data sets. In fact this reduces the inherently transient data set into a time independent mean data set. Forward computation were carried out with CFD code for various case to generate a large set of data to train the ANN. Specific signature analysis was carried out to find the parameters of interest for ANN training like peak concentration, time to reach peak concentration and time to fall, the ANN was trained with data and source strength and location were predicted from ANN. Inverse problem was performed using ANN approach in long range atmospheric dispersion. An illustration of application of CFD code for atmospheric dispersion studies for a hypothetical case is also included in the paper. (author)

Optimization of thermal conductivity lightweight brick type AAC (Autoclaved Aerated Concrete) effect of Si & Ca composition by using Artificial Neural Network (ANN)

Science.gov (United States)

Zulkifli; Wiryawan, G. P.

2018-03-01

Lightweight brick is the most important component of building construction, therefore it is necessary to have lightweight thermal, mechanical and aqustic thermal properties that meet the standard, in this paper which is discussed is the domain of light brick thermal conductivity properties. The advantage of lightweight brick has a low density (500-650 kg/m3), more economical, can reduce the load 30-40% compared to conventional brick (clay brick). In this research, Artificial Neural Network (ANN) is used to predict the thermal conductivity of lightweight brick type Autoclaved Aerated Concrete (AAC). Based on the training and evaluation that have been done on 10 model of ANN with number of hidden node 1 to 10, obtained that ANN with 3 hidden node have the best performance. It is known from the mean value of MSE (Mean Square Error) validation for three training times of 0.003269. This ANN was further used to predict the thermal conductivity of four light brick samples. The predicted results for each of the AAC1, AAC2, AAC3 and AAC4 light brick samples were 0.243 W/m.K, respectively; 0.29 W/m.K; 0.32 W/m.K; and 0.32 W/m.K. Furthermore, ANN is used to determine the effect of silicon composition (Si), Calcium (Ca), to light brick thermal conductivity. ANN simulation results show that the thermal conductivity increases with increasing Si composition. Si content is allowed maximum of 26.57%, while the Ca content in the range 20.32% - 30.35%.

Exploration of artificial neural network [ANN] to predict the electrochemical characteristics of lithium-ion cells

Energy Technology Data Exchange (ETDEWEB)

Parthiban, Thirumalai; Ravi, R.; Kalaiselvi, N. [Central Electrochemical Research Institute (CECRI), Karaikudi 630006 (India)

2007-12-31

CoO anode, as an alternate to the carbonaceous anodes of lithium-ion cells has been prepared and investigated for electrochemical charge-discharge characteristics for about 50 cycles. Artificial neural networks (ANNs), which are useful in estimating battery performance, has been deployed for the first time to forecast and to verify the charge-discharge behavior of lithium-ion cells containing CoO anode for a total of 50 cycles. In this novel approach, ANN that has one input layer with one neuron corresponding to one input variable, viz., cycles [charge-discharge cycles] and a hidden layer consisting of three neurons to produce their outputs to the output layer through a sigmoid function has been selected for the present investigation. The output layer consists of two neurons, representing the charge and discharge capacity, whose activation function is also the sigmoid transfer function. In this ever first attempt to exploit ANN as an effective theoretical tool to understand the charge-discharge characteristics of lithium-ion cells, an excellent agreement between the calculated and observed capacity values was found with CoO anodes with the best fit values corresponding to an error factor of <1%, which is the highlight of the present study. (author)

La presa di parola di Anne Hutchinson. Insubordinazione e conflitto nella giovane America puritana

Directory of Open Access Journals (Sweden)

Itala Vivan

2016-04-01

Full Text Available Anne Hutchinson lasciò l’Inghilterra nel 1634 per emigrare nel Massachusetts puritano, dove nel 1637 e 1638 fu processata, condannata, scomunicata ed espulsa come donna insubordinata, deviante e pericolosa. Il suo ruolo intellettuale e politico nell’alba incandescente della prima America viene qui analizzato e discusso ascoltando da presso il racconto che promana dalla voce della stessa Anne Hutchinson attraverso i verbali dei due processi, trascritti dai contemporanei con la fedeltà letterale che era tipica del puritanesimo americano. La drammatica controversia che ebbe al centro la presa di parola di questa donna segnò la prima grande crisi della neonata società coloniale – la cosiddetta crisi antinomiana -- e ne determinò gli sviluppi futuri, indirizzandoli verso un sistema di potere politico su basi teocratiche.

ANN Surface Roughness Optimization of AZ61 Magnesium Alloy Finish Turning: Minimum Machining Times at Prime Machining Costs.

Science.gov (United States)

Abbas, Adel Taha; Pimenov, Danil Yurievich; Erdakov, Ivan Nikolaevich; Taha, Mohamed Adel; Soliman, Mahmoud Sayed; El Rayes, Magdy Mostafa

2018-05-16

Magnesium alloys are widely used in aerospace vehicles and modern cars, due to their rapid machinability at high cutting speeds. A novel Edgeworth⁻Pareto optimization of an artificial neural network (ANN) is presented in this paper for surface roughness ( Ra ) prediction of one component in computer numerical control (CNC) turning over minimal machining time ( T m ) and at prime machining costs ( C ). An ANN is built in the Matlab programming environment, based on a 4-12-3 multi-layer perceptron (MLP), to predict Ra , T m , and C , in relation to cutting speed, v c , depth of cut, a p , and feed per revolution, f r . For the first time, a profile of an AZ61 alloy workpiece after finish turning is constructed using an ANN for the range of experimental values v c , a p , and f r . The global minimum length of a three-dimensional estimation vector was defined with the following coordinates: Ra = 0.087 μm, T m = 0.358 min/cm³, C = $8.2973. Likewise, the corresponding finish-turning parameters were also estimated: cutting speed v c = 250 m/min, cutting depth a p = 1.0 mm, and feed per revolution f r = 0.08 mm/rev. The ANN model achieved a reliable prediction accuracy of ±1.35% for surface roughness.

DeAnnIso: a tool for online detection and annotation of isomiRs from small RNA sequencing data.

Science.gov (United States)

Zhang, Yuanwei; Zang, Qiguang; Zhang, Huan; Ban, Rongjun; Yang, Yifan; Iqbal, Furhan; Li, Ao; Shi, Qinghua

2016-07-08

Small RNA (sRNA) Sequencing technology has revealed that microRNAs (miRNAs) are capable of exhibiting frequent variations from their canonical sequences, generating multiple variants: the isoforms of miRNAs (isomiRs). However, integrated tool to precisely detect and systematically annotate isomiRs from sRNA sequencing data is still in great demand. Here, we present an online tool, DeAnnIso (Detection and Annotation of IsomiRs from sRNA sequencing data). DeAnnIso can detect all the isomiRs in an uploaded sample, and can extract the differentially expressing isomiRs from paired or multiple samples. Once the isomiRs detection is accomplished, detailed annotation information, including isomiRs expression, isomiRs classification, SNPs in miRNAs and tissue specific isomiR expression are provided to users. Furthermore, DeAnnIso provides a comprehensive module of target analysis and enrichment analysis for the selected isomiRs. Taken together, DeAnnIso is convenient for users to screen for isomiRs of their interest and useful for further functional studies. The server is implemented in PHP + Perl + R and available to all users for free at: http://mcg.ustc.edu.cn/bsc/deanniso/ and http://mcg2.ustc.edu.cn/bsc/deanniso/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

ANN-based calibration model of FTIR used in transformer online monitoring

Science.gov (United States)

Li, Honglei; Liu, Xian-yong; Zhou, Fangjie; Tan, Kexiong

2005-02-01

Recently, chromatography column and gas sensor have been used in online monitoring device of dissolved gases in transformer oil. But some disadvantages still exist in these devices: consumption of carrier gas, requirement of calibration, etc. Since FTIR has high accuracy, consume no carrier gas and require no calibration, the researcher studied the application of FTIR in such monitoring device. Experiments of "Flow gas method" were designed, and spectrum of mixture composed of different gases was collected with A BOMEM MB104 FTIR Spectrometer. A key question in the application of FTIR is that: the absorbance spectrum of 3 fault key gases, including C2H4, CH4 and C2H6, are overlapped seriously at 2700~3400cm-1. Because Absorbance Law is no longer appropriate, a nonlinear calibration model based on BP ANN was setup to in the quantitative analysis. The height absorbance of C2H4, CH4 and C2H6 were adopted as quantitative feature, and all the data were normalized before training the ANN. Computing results show that the calibration model can effectively eliminate the cross disturbance to measurement.

ANN-GA based optimization of a high ash coal-fired supercritical power plant

International Nuclear Information System (INIS)

Suresh, M.V.J.J.; Reddy, K.S.; Kolar, Ajit Kumar

2011-01-01

Highlights: → Neuro-genetic power plant optimization is found to be an efficient methodology. → Advantage of neuro-genetic algorithm is the possibility of on-line optimization. → Exergy loss in combustor indicates the effect of coal composition on efficiency. -- Abstract: The efficiency of coal-fired power plant depends on various operating parameters such as main steam/reheat steam pressures and temperatures, turbine extraction pressures, and excess air ratio for a given fuel. However, simultaneous optimization of all these operating parameters to achieve the maximum plant efficiency is a challenging task. This study deals with the coupled ANN and GA based (neuro-genetic) optimization of a high ash coal-fired supercritical power plant in Indian climatic condition to determine the maximum possible plant efficiency. The power plant simulation data obtained from a flow-sheet program, 'Cycle-Tempo' is used to train the artificial neural network (ANN) to predict the energy input through fuel (coal). The optimum set of various operating parameters that result in the minimum energy input to the power plant is then determined by coupling the trained ANN model as a fitness function with the genetic algorithm (GA). A unit size of 800 MWe currently under development in India is considered to carry out the thermodynamic analysis based on energy and exergy. Apart from optimizing the design parameters, the developed model can also be used for on-line optimization when quick response is required. Furthermore, the effect of various coals on the thermodynamic performance of the optimized power plant is also determined.

Anmeldelse: Anne Gjelsvik & Rikke Schubart : Women of ice and fire: Gender, Game of Thrones, and multiple media engagements, New York/London: Bloomsbury, 2016

DEFF Research Database (Denmark)

Konzack, Lars

2017-01-01

Anmeldelse af bogen Women of Ice and F ire: Gender, Game of Thrones redigeret af Anne Gjelsvik & Rikke Schubart.......Anmeldelse af bogen Women of Ice and F ire: Gender, Game of Thrones redigeret af Anne Gjelsvik & Rikke Schubart....

Implementation of ANN on CCHP system to predict trigeneration performance with consideration of various operative factors

International Nuclear Information System (INIS)

Anvari, Simin; Taghavifar, Hadi; Saray, Rahim Khoshbakhti; Khalilarya, Shahram; Jafarmadar, Samad

2015-01-01

Highlights: • ANN modeling tool was implemented on the CCHP system. • The best ANN topology was detected 10–8–9 with Levenberg–Marquadt algorithm. • The system is more sensitive of CC outlet temperature and turbine isentropic efficiency. • The lowest RMSE = 3.13e−5 and the best R 2 = 0.999 is related to lambda and second law efficiency terms, respectively. - Abstract: A detailed investigation was aimed based on numerical thermodynamic survey and artificial neural network (ANN) modeling of the trigeneration system. The results are presented in two pivotal frameworks namely the sensitivity analysis and ANN prediction capability of proposed modeling. The underlying operative parameters were chosen as input parameters from different cycles and components, while the exergy efficiency, exergy loss, coefficient of performance, heating load exergy, lambda, gas turbine power, exergy destruction, actual outlet air compressor temperature, and heat recovery gas steam generator (HRSG) outlet temperature were taken as objective output parameters for the modeling purpose. Up to now, no significant step was taken to investigate the compound power plant with thermodynamic analyses and network predictability hybrid in such a detailed oriented approach. It follows that multilayer perceptron neural network with back propagation algorithm deployed with 10–8–9 configuration results in the modeling reliability ranged within R 2 = 0.995–0.999. When dataset treated with trainlm learning algorithm and diversified neurons, the mean square error (MSE) is obtained equal to 0.2175. This denotes a powerful modeling achievement in both scientific and industrial scale to save considerable computational cost on combined cooling, heating, and power system in accomplishment of boosting the energy efficiency and system maintenance

Application of Artificial Neural Networks (ANNs for Weight Predictions of Blue Crabs (Callinectes sapidus RATHBUN, 1896 Using Predictor Variables

Directory of Open Access Journals (Sweden)

C. TURELI BILEN

2011-10-01

Full Text Available An evaluation of the performance of artificial networks (ANNs to estimate the weights of blue crab (Callinectes sapidus catches in Yumurtalık Cove (Iskenderun Bay that uses measured predictor variables is presented, including carapace width (CW, sex (male, female and female with eggs, and sampling month. Blue crabs (n=410 were collected each month between 15 September 1996 and 15 May 1998. Sex, CW, and sampling month were used and specified in the input layer of the network. The weights of the blue crabs were utilized in the output layer of the network. A multi-layer perception architecture model was used and was calibrated with the Levenberg Marguardt (LM algorithm. Finally, the values were determined by the ANN model using the actual data. The mean square error (MSE was measured as 3.3, and the best results had a correlation coefficient (R of 0.93. We compared the predictive capacity of the general linear model (GLM versus the Artificial Neural Network model (ANN for the estimation of the weights of blue crabs from independent field data. The results indicated the higher performance capacity of the ANN to predict weights compared to the GLM (R=0.97 vs. R=0.95, raw variable when evaluated against independent field data.

Development of LC-MS determination method and back-propagation ANN pharmacokinetic model of corynoxeine in rat.

Science.gov (United States)

Ma, Jianshe; Cai, Jinzhang; Lin, Guanyang; Chen, Huilin; Wang, Xianqin; Wang, Xianchuan; Hu, Lufeng

2014-05-15

Corynoxeine(CX), isolated from the extract of Uncaria rhynchophylla, is a useful and prospective compound in the prevention and treatment for vascular diseases. A simple and selective liquid chromatography mass spectrometry (LC-MS) method was developed to determine the concentration of CX in rat plasma. The chromatographic separation was achieved on a Zorbax SB-C18 (2.1 mm × 150 mm, 5 μm) column with acetonitrile-0.1% formic acid in water as mobile phase. Selective ion monitoring (SIM) mode was used for quantification using target ions m/z 383 for CX and m/z 237 for the carbamazepine (IS). After the LC-MS method was validated, it was applied to a back-propagation artificial neural network (BP-ANN) pharmacokinetic model study of CX in rats. The results showed that after intravenous administration of CX, it was mainly distributed in blood and eliminated quickly, t1/2 was less than 1h. The predicted concentrations generated by BP-ANN model had a high correlation coefficient (R>0.99) with experimental values. The developed BP-ANN pharmacokinetic model can be used to predict the concentration of CX in rats. Copyright © 2014 Elsevier B.V. All rights reserved.

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

Science.gov (United States)

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

2018-05-01

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

Detecting agricultural to urban land use change from multi-temporal MSS digital data. [Salt Lake County, Utah

Science.gov (United States)

Ridd, M. K.; Merola, J. A.; Jaynes, R. A.

1983-01-01

Conversion of agricultural land to a variety of urban uses is a major problem along the Wasatch Front, Utah. Although LANDSAT MSS data is a relatively coarse tool for discriminating categories of change in urban-size plots, its availability prompts a thorough test of its power to detect change. The procedures being applied to a test area in Salt Lake County, Utah, where the land conversion problem is acute are presented. The identity of land uses before and after conversion was determined and digital procedures for doing so were compared. Several algorithms were compared, utilizing both raw data and preprocessed data. Verification of results involved high quality color infrared photography and field observation. Two data sets were digitally registered, specific change categories internally identified in the software, results tabulated by computer, and change maps printed at 1:24,000 scale.

Facteurs prédictifs de succès des étudiants en première année de ...

African Journals Online (AJOL)

Introduction: Plusieurs facteurs dont les notes obtenues au BAC peuvent influencer les performances académiques des étudiants en première année de médecine. L'objectif de cette étude était d'évaluer la relation entre les résultats des étudiants au BAC et le succès en première année de médecine. Méthodes: Nous ...

[The embroidery work of the lady at Saint-Anne Hospital].

Science.gov (United States)

Thillaud, Pierre L; Postel, Jacques

2014-01-01

In July 1974, a 72 old woman had been a patient for forty years in Sainte-Anne Hospital, Ward C. As she had again a violent brawl with her neighbour patient, she revealed being a tremendous artist. She had been confined on account of dementia paralytica in the Mecca of malariotherapy, and passionately devoted herself to embroidery. Her fancy work was rather a matter for Jean Dubuffet's art through its perfect expression and deserved being known.

"Boob teab" / Kalju Komissarov ja Rait Avestik ; kommenteerinud ja toimetanud Anneli Saro

Index Scriptorium Estoniae

Komissarov, Kalju, 1946-2017

2010-01-01

Teatriseminar sarjast "Eesti algupärandid Eesti teatris" toimus Tartu Kirjanduse Maja krüptis 28. märtsil 2005, seminari juhtis Anneli Saro. Urmas Lennuki näidendi kolmest lavastusest: Tallinna Linnateatris (esietendus 28. veebruaril 2004, lavastas Jaanus Rohumaa), Rakvere Teatris (esietendus 10. septembril 2004, lavastas Kalju Komissarov) ja Vikerraadios (esietendus 4. septembril 2004, lavastas Tamur Tohver)

Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques. [south carolina

Science.gov (United States)

Hoffer, R. M. (Principal Investigator)

1979-01-01

A literature review on radar and spectral band information was conducted and a NC-130 mission was flown carrying the NS001 scanner system which basically corresponds to the channel configuration of the proposed thematic mapper. Aerial photography and other reference data were obtained for the study site, an area approximately 290 sq miles in north central South Carolina. A cover type map was prepared and methods were devised for reformatting and geometrically correcting MSS CRT data. Arrangements were made to obtain LANDSAT data for dates approximating the NC-130 mission. Because of the waveband employed to obtain SEASAT radar data, it was decided to determine if X-band (2.40 cm to 3.75 cm wavelength) imagery is available.

78 FR 65382 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

Science.gov (United States)

2013-10-31

....S.C. 3003, of the completion of an inventory of human remains under the control of the University of....R50000] Notice of Inventory Completion: University of Michigan, Ann Arbor, MI AGENCY: National Park Service, Interior. ACTION: Notice. SUMMARY: The University of Michigan has completed an inventory of human...

78 FR 65369 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

Science.gov (United States)

2013-10-31

....S.C. 3003, of the completion of an inventory of human remains under the control of the University of....R50000] Notice of Inventory Completion: University of Michigan, Ann Arbor, MI AGENCY: National Park Service, Interior. ACTION: Notice. SUMMARY: The University of Michigan has completed an inventory of human...

78 FR 65366 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

Science.gov (United States)

2013-10-31

....S.C. 3003, of the completion of an inventory of human remains under the control of the University of....R50000] Notice of Inventory Completion: University of Michigan, Ann Arbor, MI AGENCY: National Park Service, Interior. ACTION: Notice. SUMMARY: The University of Michigan has completed an inventory of human...

Performance evaluation of an irreversible Miller cycle comparing FTT (finite-time thermodynamics) analysis and ANN (artificial neural network) prediction

International Nuclear Information System (INIS)

Mousapour, Ashkan; Hajipour, Alireza; Rashidi, Mohammad Mehdi; Freidoonimehr, Navid

2016-01-01

In this paper, the first and second-laws efficiencies are applied to performance analysis of an irreversible Miller cycle. In the irreversible cycle, the linear relation between the specific heat of the working fluid and its temperature, the internal irreversibility described using the compression and expansion efficiencies, the friction loss computed according to the mean velocity of the piston and the heat-transfer loss are considered. The effects of various design parameters, such as the minimum and maximum temperatures of the working fluid and the compression ratio on the power output and the first and second-laws efficiencies of the cycle are discussed. In the following, a procedure named ANN is used for predicting the thermal efficiency values versus the compression ratio, and the minimum and maximum temperatures of the Miller cycle. Nowadays, Miller cycle is widely used in the automotive industry and the obtained results of this study will provide some significant theoretical grounds for the design optimization of the Miller cycle. - Highlights: • The performance of an irreversible Miller cycle is investigated using FFT. • The effects of design parameters on the performance of the cycle are investigated. • ANN is applied to predict the thermal efficiency and the power output values. • There is an excellent correlation between FTT and ANN data. • ANN can be applied to predict data where FTT analysis has not been performed.

Statistical optimization of the phytoremediation of arsenic by Ludwigia octovalvis- in a pilot reed bed using response surface methodology (RSM) versus an artificial neural network (ANN).

Science.gov (United States)

Titah, Harmin Sulistiyaning; Halmi, Mohd Izuan Effendi Bin; Abdullah, Siti Rozaimah Sheikh; Hasan, Hassimi Abu; Idris, Mushrifah; Anuar, Nurina

2018-06-07

In this study, the removal of arsenic (As) by plant, Ludwigia octovalvis, in a pilot reed bed was optimized. A Box-Behnken design was employed including a comparative analysis of both Response Surface Methodology (RSM) and an Artificial Neural Network (ANN) for the prediction of maximum arsenic removal. The predicted optimum condition using the desirability function of both models was 39 mg kg -1 for the arsenic concentration in soil, an elapsed time of 42 days (the sampling day) and an aeration rate of 0.22 L/min, with the predicted values of arsenic removal by RSM and ANN being 72.6% and 71.4%, respectively. The validation of the predicted optimum point showed an actual arsenic removal of 70.6%. This was achieved with the deviation between the validation value and the predicted values being within 3.49% (RSM) and 1.87% (ANN). The performance evaluation of the RSM and ANN models showed that ANN performs better than RSM with a higher R 2 (0.97) close to 1.0 and very small Average Absolute Deviation (AAD) (0.02) and Root Mean Square Error (RMSE) (0.004) values close to zero. Both models were appropriate for the optimization of arsenic removal with ANN demonstrating significantly higher predictive and fitting ability than RSM.

Evaluation of Effectiveness of Wavelet Based Denoising Schemes Using ANN and SVM for Bearing Condition Classification

Directory of Open Access Journals (Sweden)

Vijay G. S.

2012-01-01

Full Text Available The wavelet based denoising has proven its ability to denoise the bearing vibration signals by improving the signal-to-noise ratio (SNR and reducing the root-mean-square error (RMSE. In this paper seven wavelet based denoising schemes have been evaluated based on the performance of the Artificial Neural Network (ANN and the Support Vector Machine (SVM, for the bearing condition classification. The work consists of two parts, the first part in which a synthetic signal simulating the defective bearing vibration signal with Gaussian noise was subjected to these denoising schemes. The best scheme based on the SNR and the RMSE was identified. In the second part, the vibration signals collected from a customized Rolling Element Bearing (REB test rig for four bearing conditions were subjected to these denoising schemes. Several time and frequency domain features were extracted from the denoised signals, out of which a few sensitive features were selected using the Fisher’s Criterion (FC. Extracted features were used to train and test the ANN and the SVM. The best denoising scheme identified, based on the classification performances of the ANN and the SVM, was found to be the same as the one obtained using the synthetic signal.

IDI diesel engine performance and exhaust emission analysis using biodiesel with an artificial neural network (ANN

Directory of Open Access Journals (Sweden)

K. Prasada Rao

2017-09-01

Full Text Available Biodiesel is receiving increasing attention each passing day because of its fuel properties and compatibility. This study investigates the performance and emission characteristics of single cylinder four stroke indirect diesel injection (IDI engine fueled with Rice Bran Methyl Ester (RBME with Isopropanol additive. The investigation is done through a combination of experimental data analysis and artificial neural network (ANN modeling. The study used IDI engine experimental data to evaluate nine engine performance and emission parameters including Exhaust Gas Temperature (E.G.T, Brake Specific Fuel Consumption (BSFC, Brake Thermal Efficiency (B.The and various emissions like Hydrocarbons (HC, Carbon monoxide (CO, Carbon dioxide (CO2, Oxygen (O2, Nitrogen oxides (NOX and smoke. For the ANN modeling standard back propagation algorithm was found to be the optimum choice for training the model. A multi-layer perception (MLP network was used for non-linear mapping between the input and output parameters. It was found that ANN was able to predict the engine performance and exhaust emissions with a correlation coefficient of 0.995, 0.980, 0.999, 0.985, 0.999, 0.999, 0.980, 0.999, and 0.999 for E.G.T, BSFC, B.The, HC, O2, CO2, CO, NOX, smoke respectively.

Strategic planning for minimizing CO2 emissions using LP model based on forecasted energy demand by PSO Algorithm and ANN

Energy Technology Data Exchange (ETDEWEB)

Yousefi, M.; Omid, M.; Rafiee, Sh. [Department of Agricultural Machinery Engineering, University of Tehran, Karaj (Iran, Islamic Republic of); Ghaderi, S. F. [Department of Industrial Engineering, University of Tehran, Tehran (Iran, Islamic Republic of)

2013-07-01

Iran's primary energy consumption (PEC) was modeled as a linear function of five socioeconomic and meteorological explanatory variables using particle swarm optimization (PSO) and artificial neural networks (ANNs) techniques. Results revealed that ANN outperforms PSO model to predict test data. However, PSO technique is simple and provided us with a closed form expression to forecast PEC. Energy demand was forecasted by PSO and ANN using represented scenario. Finally, adapting about 10% renewable energy revealed that based on the developed linear programming (LP) model under minimum CO2 emissions, Iran will emit about 2520 million metric tons CO2 in 2025. The LP model indicated that maximum possible development of hydropower, geothermal and wind energy resources will satisfy the aim of minimization of CO2 emissions. Therefore, the main strategic policy in order to reduce CO2 emissions would be exploitation of these resources.

Dynamically stable associative learning: a neurobiologically based ANN and its applications

Science.gov (United States)

Vogl, Thomas P.; Blackwell, Kim L.; Barbour, Garth; Alkon, Daniel L.

1992-07-01

Most currently popular artificial neural networks (ANN) are based on conceptions of neuronal properties that date back to the 1940s and 50s, i.e., to the ideas of McCullough, Pitts, and Hebb. Dystal is an ANN based on current knowledge of neurobiology at the cellular and subcellular level. Networks based on these neurobiological insights exhibit the following advantageous properties: (1) A theoretical storage capacity of bN non-orthogonal memories, where N is the number of output neurons sharing common inputs and b is the number of distinguishable (gray shade) levels. (2) The ability to learn, store, and recall associations among noisy, arbitrary patterns. (3) A local synaptic learning rule (learning depends neither on the output of the post-synaptic neuron nor on a global error term), some of whose consequences are: (4) Feed-forward, lateral, and feed-back connections (as well as time-sensitive connections) are possible without alteration of the learning algorithm; (5) Storage allocation (patch creation) proceeds dynamically as associations are learned (self- organizing); (6) The number of training set presentations required for learning is small (different expressions and/or corrupted by noise, and on reading hand-written digits (98% accuracy) and hand-printed Japanese Kanji (90% accuracy) is demonstrated.

Friendly Letters on the Correspondence of Helen Keller, Anne Sullivan, and Alexander Graham Bell.

Science.gov (United States)

Blatt, Burton

1985-01-01

Excerpts from the letters between Alexander Graham Bell and Anne Sullivan and Helen Keller are given to illustrate the educational and personal growth of Helen Keller as well as the educational philosophy of Bell regarding the education of the deaf blind. (DB)

'In the developed world, people talk and shop'- a review by Anne ...

African Journals Online (AJOL)

'In the developed world, people talk and shop'- a review by Anne Derges. A. Salleh. http://dx.doi.org/10.4314/safere.v3i1.23966 · AJOL African Journals Online. HOW TO USE AJOL... for Researchers · for Librarians · for Authors · FAQ's · More about AJOL · AJOL's Partners · Terms and Conditions of Use · Contact AJOL ...

Prophecy, patriarchy, and violence in the early modern household: the revelations of Anne Wentworth.

Science.gov (United States)

Johnston, Warren

2009-10-01

In 1676 the apostate Baptist prophet Anne Wentworth (1629/30-1693?) published "A True Account of Anne Wentworths Being Cruelly, Unjustly, and Unchristianly Dealt with by Some of Those People called Anabaptists," the first in a series of pamphlets that would continue to the end of the decade. Orignially a member of a London Baptist church, Wentworth left the congregation and eventually her own home after her husband used physical force to stop her writing and prophesying. Yet Wentworth persisted in her "revelations." These prophecies increasingly focused on her response to those who were trying to stop her efforts, especially within her own household. This article examines Wentworth's writings as an effort by an early modern woman, using arguments of spiritual agency, to assert ideas about proper gender roles and household responsibilities to denounce her husband and rebut those who criticized and attempted to suppress her.

Rapid Identification of Asteraceae Plants with Improved RBF-ANN Classification Models Based on MOS Sensor E-Nose

Directory of Open Access Journals (Sweden)

Hui-Qin Zou

2014-01-01

Full Text Available Plants from Asteraceae family are widely used as herbal medicines and food ingredients, especially in Asian area. Therefore, authentication and quality control of these different Asteraceae plants are important for ensuring consumers’ safety and efficacy. In recent decades, electronic nose (E-nose has been studied as an alternative approach. In this paper, we aim to develop a novel discriminative model by improving radial basis function artificial neural network (RBF-ANN classification model. Feature selection algorithms, including principal component analysis (PCA and BestFirst + CfsSubsetEval (BC, were applied in the improvement of RBF-ANN models. Results illustrate that in the improved RBF-ANN models with lower dimension data classification accuracies (100% remained the same as in the original model with higher-dimension data. It is the first time to introduce feature selection methods to get valuable information on how to attribute more relevant MOS sensors; namely, in this case, S1, S3, S4, S6, and S7 show better capability to distinguish these Asteraceae plants. This paper also gives insights to further research in this area, for instance, sensor array optimization and performance improvement of classification model.

Comparison of the accuracy of SST estimates by artificial neural networks (ANN) and other quantitative methods using radiolarian data from the Antarctic and Pacific Oceans

Digital Repository Service at National Institute of Oceanography (India)

Gupta, S.M.; Malmgren, B.A.

) regression, the maximum likelihood (ML) method, and artificial neural networks (ANNs), based on radiolarian faunal abundance data from surface sediments from the Antarctic and Pacific Oceans. Recent studies have suggested that ANNs may represent one...

Evaluation Of The Advanced Operating System Of The Ann Arbor Transportation Authority : AATA Web Survey

Science.gov (United States)

1999-01-01

During 1997, visitors to the Ann Arbor (Michigan) Transportation Authority's worldwide web site were invited to complete an electronic questionnaire about their experience with the site. Eighty surveys were collected, representing a non-scientific se...

Tallinna Ülikool / Leif Kalev, Anneli Leinpere, Tiit Land, Alessandro Centonze, Hannes Palang, Liis Kelberg

Index Scriptorium Estoniae

2008-01-01

Ülikooli ja seal õpetatavaid erialasid tutvustavad dotsent Leif Kalev, kunstimagistrant Anneli Leinpere, professor Tiit Land, välisüliõpilane Milanost Alessandro Centonze, vanemteadur Hannes Palang ning kirjaliku tõlke magistrant Liis Kelberg

A Comparison of SWAT and ANN Models for Daily Runoff Simulation in Different Climatic Zones of Peninsular Spain

Directory of Open Access Journals (Sweden)

Patricia Jimeno-Sáez

2018-02-01

Full Text Available Streamflow data are of prime importance to water-resources planning and management, and the accuracy of their estimation is very important for decision making. The Soil and Water Assessment Tool (SWAT and Artificial Neural Network (ANN models have been evaluated and compared to find a method to improve streamflow estimation. For a more complete evaluation, the accuracy and ability of these streamflow estimation models was also established separately based on their performance during different periods of flows using regional flow duration curves (FDCs. Specifically, the FDCs were divided into five sectors: very low, low, medium, high and very high flow. This segmentation of flow allows analysis of the model performance for every important discharge event precisely. In this study, the models were applied in two catchments in Peninsular Spain with contrasting climatic conditions: Atlantic and Mediterranean climates. The results indicate that SWAT and ANNs were generally good tools in daily streamflow modelling. However, SWAT was found to be more successful in relation to better simulation of lower flows, while ANNs were superior at estimating higher flows in all cases.

Estimation of Optimum Dilution in the GMAW Process Using Integrated ANN-GA

Directory of Open Access Journals (Sweden)

P. Sreeraj

2013-01-01

Full Text Available To improve the corrosion resistant properties of carbon steel, usually cladding process is used. It is a process of depositing a thick layer of corrosion resistant material over carbon steel plate. Most of the engineering applications require high strength and corrosion resistant materials for long-term reliability and performance. By cladding these properties can be achieved with minimum cost. The main problem faced on cladding is the selection of optimum combinations of process parameters for achieving quality clad and hence good clad bead geometry. This paper highlights an experimental study to optimize various input process parameters (welding current, welding speed, gun angle, and contact tip to work distance and pinch to get optimum dilution in stainless steel cladding of low carbon structural steel plates using gas metal arc welding (GMAW. Experiments were conducted based on central composite rotatable design with full replication technique, and mathematical models were developed using multiple regression method. The developed models have been checked for adequacy and significance. In this study, artificial neural network (ANN and genetic algorithm (GA techniques were integrated and labeled as integrated ANN-GA to estimate optimal process parameters in GMAW to get optimum dilution.

Strategic planning for minimizing CO2 emissions using LP model based on forecasted energy demand by PSO Algorithm and ANN

Energy Technology Data Exchange (ETDEWEB)

Yousefi, M.; Omid, M.; Rafiee, Sh. [Department of Agricultural Machinery Engineering, University of Tehran, Karaj (Iran, Islamic Republic of); Ghaderi, S.F. [Department of Industrial Engineering, University of Tehran, Tehran (Iran, Islamic Republic of)

2013-07-01

Iran's primary energy consumption (PEC) was modeled as a linear function of five socioeconomic and meteorological explanatory variables using particle swarm optimization (PSO) and artificial neural networks (ANNs) techniques. Results revealed that ANN outperforms PSO model to predict test data. However, PSO technique is simple and provided us with a closed form expression to forecast PEC. Energy demand was forecasted by PSO and ANN using represented scenario. Finally, adapting about 10% renewable energy revealed that based on the developed linear programming (LP) model under minimum CO2 emissions, Iran will emit about 2520 million metric tons CO2 in 2025. The LP model indicated that maximum possible development of hydropower, geothermal and wind energy resources will satisfy the aim of minimization of CO2 emissions. Therefore, the main strategic policy in order to reduce CO2 emissions would be exploitation of these resources.

Using AnnAGNPS to Predict the Effects of Tile Drainage Control on Nutrient and Sediment Loads for a River Basin.

Science.gov (United States)

Que, Z; Seidou, O; Droste, R L; Wilkes, G; Sunohara, M; Topp, E; Lapen, D R

2015-03-01

Controlled tile drainage (CTD) can reduce pollutant loading. The Annualized Agricultural Nonpoint Source model (AnnAGNPS version 5.2) was used to examine changes in growing season discharge, sediment, nitrogen, and phosphorus loads due to CTD for a ∼3900-km agriculturally dominated river basin in Ontario, Canada. Two tile drain depth scenarios were examined in detail to mimic tile drainage control for flat cropland: 600 mm depth (CTD) and 200 mm (CTD) depth below surface. Summed for five growing seasons (CTD), direct runoff, total N, and dissolved N were reduced by 6.6, 3.5, and 13.7%, respectively. However, five seasons of summed total P, dissolved P, and total suspended solid loads increased as a result of CTD by 0.96, 1.6, and 0.23%. The AnnAGNPS results were compared with mass fluxes observed from paired experimental watersheds (250, 470 ha) in the river basin. The "test" experimental watershed was dominated by CTD and the "reference" watershed by free drainage. Notwithstanding environmental/land use differences between the watersheds and basin, comparisons of seasonal observed and predicted discharge reductions were comparable in 100% of respective cases. Nutrient load comparisons were more consistent for dissolved, relative to particulate water quality endpoints. For one season under corn crop production, AnnAGNPS predicted a 55% decrease (CTD) in dissolved N from the basin. AnnAGNPS v. 5.2 treats P transport from a surface pool perspective, which is appropriate for many systems. However, for assessment of tile drainage management practices for relatively flat tile-dominated systems, AnnAGNPS may benefit from consideration of P and particulate transport in the subsurface. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Exact estimation of biodiesel cetane number (CN) from its fatty acid methyl esters (FAMEs) profile using partial least square (PLS) adapted by artificial neural network (ANN)

International Nuclear Information System (INIS)

Hosseinpour, Soleiman; Aghbashlo, Mortaza; Tabatabaei, Meisam; Khalife, Esmail

2016-01-01

Highlights: • Estimating the biodiesel CN from its FAMEs profile using ANN-based PLS approach. • Comparing the capability of ANN-adapted PLS approach with the standard PLS model. • Exact prediction of biodiesel CN from it FAMEs profile using ANN-based PLS method. • Developing an easy-to-use software using ANN-PLS model for computing the biodiesel CN. - Abstract: Cetane number (CN) is among the most important properties of biodiesel because it quantifies combustion speed or in better words, ignition quality. Experimental measurement of biodiesel CN is rather laborious and expensive. However, the high proportionality of biodiesel fatty acid methyl esters (FAMEs) profile with its CN is very appealing to develop straightforward and inexpensive computerized tools for biodiesel CN estimation. Unfortunately, correlating the chemical structure of biodiesel to its CN using conventional statistical and mathematical approaches is very difficult. To solve this issue, partial least square (PLS) adapted by artificial neural network (ANN) was introduced and examined herein as an innovative approach for the exact estimation of biodiesel CN from its FAMEs profile. In the proposed approach, ANN paradigm was used for modeling the inner relation between the input and the output PLS score vectors. In addition, the capability of the developed method in predicting the biodiesel CN was compared with the basal PLS method. The accuracy of the developed approaches for computing the biodiesel CN was assessed using three statistical criteria, i.e., coefficient of determination (R"2), mean-squared error (MSE), and percentage error (PE). The ANN-adapted PLS method predicted the biodiesel CN with an R"2 value higher than 0.99 demonstrating the fidelity of the developed model over the classical PLS method with a markedly lower R"2 value of about 0.85. In order to facilitate the use of the proposed model, an easy-to-use computer program was also developed on the basis of ANN-adapted PLS

Development of an ANN optimized mucoadhesive buccal tablet containing flurbiprofen and lidocaine for dental pain.

Science.gov (United States)

Hussain, Amjad; Syed, Muhammad Ali; Abbas, Nasir; Hanif, Sana; Arshad, Muhammad Sohail; Bukhari, Nadeem Irfan; Hussain, Khalid; Akhlaq, Muhammad; Ahmad, Zeeshan

2016-06-01

A novel mucoadhesive buccal tablet containing flurbiprofen (FLB) and lidocaine HCl (LID) was prepared to relieve dental pain. Tablet formulations (F1-F9) were prepared using variable quantities of mucoadhesive agents, hydroxypropyl methyl cellulose (HPMC) and sodium alginate (SA). The formulations were evaluated for their physicochemical properties, mucoadhesive strength and mucoadhesion time, swellability index and in vitro release of active agents. Release of both drugs depended on the relative ratio of HPMC:SA. However, mucoadhesive strength and mucoadhesion time were better in formulations, containing higher proportions of HPMC compared to SA. An artificial neural network (ANN) approach was applied to optimise formulations based on known effective parameters (i.e., mucoadhesive strength, mucoadhesion time and drug release), which proved valuable. This study indicates that an effective buccal tablet formulation of flurbiprofen and lidocaine can be prepared via an optimized ANN approach.

EEG-Based Computer Aided Diagnosis of Autism Spectrum Disorder Using Wavelet, Entropy, and ANN

Directory of Open Access Journals (Sweden)

Ridha Djemal

2017-01-01

Full Text Available Autism spectrum disorder (ASD is a type of neurodevelopmental disorder with core impairments in the social relationships, communication, imagination, or flexibility of thought and restricted repertoire of activity and interest. In this work, a new computer aided diagnosis (CAD of autism ‎based on electroencephalography (EEG signal analysis is investigated. The proposed method is based on discrete wavelet transform (DWT, entropy (En, and artificial neural network (ANN. DWT is used to decompose EEG signals into approximation and details coefficients to obtain EEG subbands. The feature vector is constructed by computing Shannon entropy values from each EEG subband. ANN classifies the corresponding EEG signal into normal or autistic based on the extracted features. The experimental results show the effectiveness of the proposed method for assisting autism diagnosis. A receiver operating characteristic (ROC curve metric is used to quantify the performance of the proposed method. The proposed method obtained promising results tested using real dataset provided by King Abdulaziz Hospital, Jeddah, Saudi Arabia.

[Reinhold Reith. Torsten Meyer (Hrsg.) Luxus und Konsum : eine historische Annäherung] / Raimo Pullat

Index Scriptorium Estoniae

Pullat, Raimo, 1935-

2009-01-01

Arvustus: Reith, Reinhold. Torsten Meyer (Hrsg.) Luxus und Konsum : eine historische Annäherung. Cottbuser Studien zur Geschichte von Technik, Arbeit und Umwelt. hrsg. von Günter Bayerl. Bd. 21. 2003. Collegium Johann Beckmann'i kolmanda teaduskonverentsi ettekannete kogumikust

Neuropathological findings processed by artificial neural networks (ANNs) can perfectly distinguish Alzheimer's patients from controls in the Nun Study.

Science.gov (United States)

Grossi, Enzo; Buscema, Massimo P; Snowdon, David; Antuono, Piero

2007-06-21

Many reports have described that there are fewer differences in AD brain neuropathologic lesions between AD patients and control subjects aged 80 years and older, as compared with the considerable differences between younger persons with AD and controls. In fact some investigators have suggested that since neurofibrillary tangles (NFT) can be identified in the brains of non-demented elderly subjects they should be considered as a consequence of the aging process. At present, there are no universally accepted neuropathological criteria which can mathematically differentiate AD from healthy brain in the oldest old. The aim of this study is to discover the hidden and non-linear associations among AD pathognomonic brain lesions and the clinical diagnosis of AD in participants in the Nun Study through Artificial Neural Networks (ANNs) analysis The analyses were based on 26 clinically- and pathologically-confirmed AD cases and 36 controls who had normal cognitive function. The inputs used for the analyses were just NFT and neuritic plaques counts in neocortex and hippocampus, for which, despite substantial differences in mean lesions counts between AD cases and controls, there was a substantial overlap in the range of lesion counts. By taking into account the above four neuropathological features, the overall predictive capability of ANNs in sorting out AD cases from normal controls reached 100%. The corresponding accuracy obtained with Linear Discriminant Analysis was 92.30%. These results were consistently obtained in ten independent experiments. The same experiments were carried out with ANNs on a subgroup of 13 non severe AD patients and on the same 36 controls. The results obtained in terms of prediction accuracy with ANNs were exactly the same. Input relevance analysis confirmed the relative dominance of NFT in neocortex in discriminating between AD patients and controls and indicated the lesser importance played by NP in the hippocampus. The results of this study

'Transatlantic Print Culture, 1880-1940: Emerging Media, Emerging Modernisms', edited by Ann Ardis and Patrick Collier

Directory of Open Access Journals (Sweden)

Janet Floyd

2009-11-01

Full Text Available A review of 'Transatlantic Print Culture, 1880-1940: Emerging Media, Emerging Modernisms', edited by Ann Ardis and Patrick Collier (London: Palgrave Macmillan, 2008. Hardback, 259 pages, £50, ISBN 9780554269.

History of psychosurgery at Sainte-Anne Hospital, Paris, France, through translational interactions between psychiatrists and neurosurgeons.

Science.gov (United States)

Zanello, Marc; Pallud, Johan; Baup, Nicolas; Peeters, Sophie; Turak, Baris; Krebs, Marie Odile; Oppenheim, Catherine; Gaillard, Raphael; Devaux, Bertrand

2017-09-01

Sainte-Anne Hospital is the largest psychiatric hospital in Paris. Its long and fascinating history began in the 18th century. In 1952, it was at Sainte-Anne Hospital that Jean Delay and Pierre Deniker used the first neuroleptic, chlorpromazine, to cure psychiatric patients, putting an end to the expansion of psychosurgery. The Department of Neuro-psychosurgery was created in 1941. The works of successive heads of the Neurosurgery Department at Sainte-Anne Hospital summarized the history of psychosurgery in France. Pierre Puech defined psychosurgery as the necessary cooperation between neurosurgeons and psychiatrists to treat the conditions causing psychiatric symptoms, from brain tumors to mental health disorders. He reported the results of his series of 369 cases and underlined the necessity for proper follow-up and postoperative re-education, illustrating the relative caution of French neurosurgeons concerning psychosurgery. Marcel David and his assistants tried to follow their patients closely postoperatively; this resulted in numerous publications with significant follow-up and conclusions. As early as 1955, David reported intellectual degradation 2 years after prefrontal leucotomies. Jean Talairach, a psychiatrist who eventually trained as a neurosurgeon, was the first to describe anterior capsulotomy in 1949. He operated in several hospitals outside of Paris, including the Sarthe Psychiatric Hospital and the Public Institution of Mental Health in the Lille region. He developed stereotactic surgery, notably stereo-electroencephalography, for epilepsy surgery but also to treat psychiatric patients using stereotactic lesioning with radiofrequency ablation or radioactive seeds of yttrium-90. The evolution of functional neurosurgery has been marked by the development of deep brain stimulation, in particular for obsessive-compulsive disorder, replacing the former lesional stereotactic procedures. The history of Sainte-Anne Hospital's Neurosurgery Department sheds

Interrater reliability of the Saint-Anne Dargassies Scale in assessing the neurological patterns of healthy preterm newborns

Directory of Open Access Journals (Sweden)

Carla Ismirna Santos Alves

Full Text Available Abstract Objectives: to assess the interrater reliability of the Saint-Anne Dargassies Scale in assessing neurological patterns of healthy preterm newborns. Methods: twenty preterm newborns met the inclusion criteria for participation in this prospective study. The neurologic examination was performed using the Saint-Anne Dargassies Scale, showing normal serial cranial ultrasound examination. In order to test the reliability, the study was structured as follows: group I (rater 1/physiotherapist; rater 2/neonatologist; group II (rater 3/physiotherapist; rater 4/child neurologist and the gold standard (expert and professor in pediatric neurology. Results: high interrater agreement was observed between groups I - II compared with the gold standard in assessing postural pattern (p<0.01. Regarding the assessment ofprimitive reflexes, greater agreement was observed in the evaluation of palmar grasp reflex and Moro reflex (p< 0.01 for group I compared with the gold standard. An analysis of tone demonstrated heterogeneous agreement, without compromising the reliability of the scale. The probability of equality between measurements of head circumference in the two groups, compared with the gold standard, was observed. Conclusions: the Saint-Anne Dargassies Scale demonstrated high reliability and homogeneity with significant power of reproducibility and may be capable to identify preterm newborns suspected of having neurological deficits.

A study of using smartphone to detect and identify construction workers' near-miss falls based on ANN

Science.gov (United States)

Zhang, Mingyuan; Cao, Tianzhuo; Zhao, Xuefeng

2018-03-01

As an effective fall accident preventive method, insight into near-miss falls provides an efficient solution to find out the causes of fall accidents, classify the type of near-miss falls and control the potential hazards. In this context, the paper proposes a method to detect and identify near-miss falls that occur when a worker walks in a workplace based on artificial neural network (ANN). The energy variation generated by workers who meet with near-miss falls is measured by sensors embedded in smart phone. Two experiments were designed to train the algorithm to identify various types of near-miss falls and test the recognition accuracy, respectively. At last, a test was conducted by workers wearing smart phones as they walked around a simulated construction workplace. The motion data was collected, processed and inputted to the trained ANN to detect and identify near-miss falls. Thresholds were obtained to measure the relationship between near-miss falls and fall accidents in a quantitate way. This approach, which integrates smart phone and ANN, will help detect near-miss fall events, identify hazardous elements and vulnerable workers, providing opportunities to eliminate dangerous conditions in a construction site or to alert possible victims that need to change their behavior before the occurrence of a fall accident.

Modeling Multi-Event Non-Point Source Pollution in a Data-Scarce Catchment Using ANN and Entropy Analysis

Directory of Open Access Journals (Sweden)

Lei Chen

2017-06-01

Full Text Available Event-based runoff–pollutant relationships have been the key for water quality management, but the scarcity of measured data results in poor model performance, especially for multiple rainfall events. In this study, a new framework was proposed for event-based non-point source (NPS prediction and evaluation. The artificial neural network (ANN was used to extend the runoff–pollutant relationship from complete data events to other data-scarce events. The interpolation method was then used to solve the problem of tail deviation in the simulated pollutographs. In addition, the entropy method was utilized to train the ANN for comprehensive evaluations. A case study was performed in the Three Gorges Reservoir Region, China. Results showed that the ANN performed well in the NPS simulation, especially for light rainfall events, and the phosphorus predictions were always more accurate than the nitrogen predictions under scarce data conditions. In addition, peak pollutant data scarcity had a significant impact on the model performance. Furthermore, these traditional indicators would lead to certain information loss during the model evaluation, but the entropy weighting method could provide a more accurate model evaluation. These results would be valuable for monitoring schemes and the quantitation of event-based NPS pollution, especially in data-poor catchments.

Review: Jennifer Browdy de Hernandez, Pauline Dongala, Omotayo Jolaosho and Anne Serafin (eds., African Women Writing Resistance: An Anthology of Contemporary Voices (2010 Buchbesprechung: Jennifer Browdy de Hernandez, Pauline Dongala, Omotayo Jolaosho und Anne Serafin (Hrsg., African Women Writing Resistance: An Anthology of Contemporary Voices (2010

Directory of Open Access Journals (Sweden)

Anja Oed

2011-01-01

Full Text Available Review of the edited volume: Jennifer Browdy de Hernandez, Pauline Dongala, Omotayo Jolaosho and Anne Serafin (eds., African Women Writing Resistance: An Anthology of Contemporary Voices, Oxford: Pambazuka Press, 2010, ISBN 978-0-299-23664-9, 376 pp.Besprechung des Sammelbandes: Jennifer Browdy de Hernandez, Pauline Dongala, Omotayo Jolaosho und Anne Serafin (Hrsg., African Women Writing Resistance: An Anthology of Contemporary Voices, Oxford: Pambazuka Press, 2010, ISBN 978-0-299-23664-9, 376 Seiten

Uudised : Indi-sahinad. Anne Erm ja Eero Raun on heliloojad. Imelaste lemmik on heavy metal

Index Scriptorium Estoniae

2007-01-01

Ameerika laulja Kimya Dawson 7. juulil Kilingi-Nõmmel minifestivalil "Schilling". Pianist Martti Raide esitab festivali Eesti muusika päevad 2007 suurkontserdil 16. aprillil Eero Rauna klaveripala "Tritonata", üllatusheliloojaks on ka "Jazzkaare" produtsent Anne Erm. Inglismaal Noorte Talentide Rahvuslikus Akadeemias tehtud uuringust

SA Virumaa Muuseumid Viru-Nigula pastopraadimuuseum / Fredi-Armand Tomps, Leila Pärtelpoeg, Annes Hermann

Index Scriptorium Estoniae

Tomps, Fredi-Armand, 1928

2008-01-01

12 ill.; fotod: Sven Arbet, Arvi Kriis; pastoraadimajas on renoveeritud esimesed ruumid, s.h. saal (arhitekt Fredi Tomps, sisearhitekt Leila Pärtelpoeg); sohva koopia on valminud 1990-ndate algul L. Pärtelpoja jooniste järgi Tartu kunstikooli mööbliosakonna õpilaste diplomitööna Annes Hermanni juhendamisel

The Nation behind the Diary: Anne Frank and the Holocaust of the Dutch Jews

Science.gov (United States)

Foray, Jennifer L.

2011-01-01

Since its first appearance in 1947, "The Diary of Anne Frank" has been translated into sixty-five different languages, including Welsh, Esperanto, and Faroese. Millions and perhaps even billions of readers, scattered throughout the globe and now spanning multiple generations, are familiar with the life and work of this young Jewish…

Development of an ANN optimized mucoadhesive buccal tablet containing flurbiprofen and lidocaine for dental pain

Directory of Open Access Journals (Sweden)

Hussain Amjad

2016-06-01

Full Text Available A novel mucoadhesive buccal tablet containing flurbiprofen (FLB and lidocaine HCl (LID was prepared to relieve dental pain. Tablet formulations (F1-F9 were prepared using variable quantities of mucoadhesive agents, hydroxypropyl methyl cellulose (HPMC and sodium alginate (SA. The formulations were evaluated for their physicochemical properties, mucoadhesive strength and mucoadhesion time, swellability index and in vitro release of active agents. Release of both drugs depended on the relative ratio of HPMC:SA. However, mucoadhesive strength and mucoadhesion time were better in formulations, containing higher proportions of HPMC compared to SA. An artificial neural network (ANN approach was applied to optimise formulations based on known effective parameters (i.e., mucoadhesive strength, mucoadhesion time and drug release, which proved valuable. This study indicates that an effective buccal tablet formulation of flurbiprofen and lidocaine can be prepared via an optimized ANN approach.

Prediction of IRI in short and long terms for flexible pavements: ANN and GMDH methods

NARCIS (Netherlands)

Ziari, H.; Sobhani, J.; Ayoubinejad, J.; Hartmann, Timo

2015-01-01

Prediction of pavement condition is one of the most important issues in pavement management systems. In this paper, capabilities of artificial neural networks (ANNs) and group method of data handling (GMDH) methods in predicting flexible pavement conditions were analysed in three levels: in 1 year,

Tunnustati parimaid üliõpilasteadlasi / Elsa Suuster, Marit Alas, Annely Aleksejev ; küsitlenud Vilma Rauniste

Index Scriptorium Estoniae

Putku, Elsa, 1984-

2009-01-01

Vestlus üliõpilaste teadustööde riikliku konkursi kolme laureaadiga, kelle uurimistöö oli tehtud Saare maakonnas. Nendeks on Elsa Suuster ja Annely Aleksejev Eesti Maaülikoolist ning Marit Alas Tallinna Ülikoolist

CUDA-accelerated genetic feedforward-ANN training for data mining

International Nuclear Information System (INIS)

Patulea, Catalin; Peace, Robert; Green, James

2010-01-01

We present an implementation of genetic algorithm (GA) training of feedforward artificial neural networks (ANNs) targeting commodity graphics cards (GPUs). By carefully mapping the problem onto the unique GPU architecture, we achieve order-of-magnitude speedup over a conventional CPU implementation. Furthermore, we show that the speedup is consistent across a wide range of data set sizes, making this implementation ideal for large data sets. This performance boost enables the genetic algorithm to search a larger subset of the solution space, which results in more accurate pattern classification. Finally, we demonstrate this method in the context of the 2009 UC San Diego Data Mining Contest, achieving a world-class lift on a data set of 94682 e-commerce transactions.

2011 : Année internationale de la chimie

OpenAIRE

2011-01-01

Lors de la 63e assemblée générale des Nations Unies, 2011 a été proclamée année internationale de la chimie. En France, les acteurs de la chimie sont mobilisés pour promouvoir quatre objectifs : mettre l’accent sur l’importance de la chimie pour un développement durable dans tous les aspects de la vie sur la planète ; accroître chez les jeunes l’intérêt pour la chimie ; susciter l’enthousiasme pour une chimie tournée vers l’avenir ; célébrer les travaux de Marie Curie et la contribution des f...

CUDA-accelerated genetic feedforward-ANN training for data mining

Energy Technology Data Exchange (ETDEWEB)

Patulea, Catalin; Peace, Robert; Green, James, E-mail: cpatulea@sce.carleton.ca, E-mail: rpeace@sce.carleton.ca, E-mail: jrgreen@sce.carleton.ca [School of Systems and Computer Engineering, Carleton University, Ottawa, K1S 5B6 (Canada)

2010-11-01

We present an implementation of genetic algorithm (GA) training of feedforward artificial neural networks (ANNs) targeting commodity graphics cards (GPUs). By carefully mapping the problem onto the unique GPU architecture, we achieve order-of-magnitude speedup over a conventional CPU implementation. Furthermore, we show that the speedup is consistent across a wide range of data set sizes, making this implementation ideal for large data sets. This performance boost enables the genetic algorithm to search a larger subset of the solution space, which results in more accurate pattern classification. Finally, we demonstrate this method in the context of the 2009 UC San Diego Data Mining Contest, achieving a world-class lift on a data set of 94682 e-commerce transactions.

FPGA implementation of adaptive ANN controller for speed regulation of permanent magnet stepper motor drives

Energy Technology Data Exchange (ETDEWEB)

Hasanien, Hany M., E-mail: Hanyhasanien@ieee.or [Dept. of Elec. Power and Machines, Faculty of Eng., Ain Shams Univ., Cairo (Egypt)

2011-02-15

This paper presents a novel adaptive artificial neural network (ANN) controller, which applies on permanent magnet stepper motor (PMSM) for regulating its speed. The dynamic response of the PMSM with the proposed controller is studied during the starting process under the full load torque and under load disturbance. The effectiveness of the proposed adaptive ANN controller is then compared with that of the conventional PI controller. The proposed methodology solves the problem of nonlinearities and load changes of PMSM drives. The proposed controller ensures fast and accurate dynamic response with an excellent steady state performance. Matlab/Simulink tool is used for this dynamic simulation study. The main contribution of this work is the implementation of the proposed controller on field programmable gate array (FPGA) hardware to drive the stepper motor. The driver is built on FPGA Spartan-3E Starter from Xilinx. Experimental results are presented to demonstrate the validity and effectiveness of the proposed control scheme.

ANN based controller for three phase four leg shunt active filter for power quality improvement

Directory of Open Access Journals (Sweden)

J. Jayachandran

2016-03-01

Full Text Available In this paper, an artificial neural network (ANN based one cycle control (OCC strategy is proposed for the DSTATCOM shunted across the load in three phase four wire distribution system. The proposed control strategy mitigates harmonic/reactive currents, ensures balanced and sinusoidal source current from the supply mains that are nearly in phase with the supply voltage and compensates neutral current under varying source and load conditions. The proposed control strategy is superior over conventional methods as it eliminates, the sensors needed for sensing load current and coupling inductor current, in addition to the multipliers and the calculation of reference currents. ANN controllers are implemented to maintain voltage across the capacitor and as a compensator to compensate neutral current. The DSTATCOM performance is validated for all possible conditions of source and load by simulation using MATLAB software and simulation results prove the efficacy of the proposed control over conventional control strategy.

FPGA implementation of adaptive ANN controller for speed regulation of permanent magnet stepper motor drives

International Nuclear Information System (INIS)

Hasanien, Hany M.

2011-01-01

This paper presents a novel adaptive artificial neural network (ANN) controller, which applies on permanent magnet stepper motor (PMSM) for regulating its speed. The dynamic response of the PMSM with the proposed controller is studied during the starting process under the full load torque and under load disturbance. The effectiveness of the proposed adaptive ANN controller is then compared with that of the conventional PI controller. The proposed methodology solves the problem of nonlinearities and load changes of PMSM drives. The proposed controller ensures fast and accurate dynamic response with an excellent steady state performance. Matlab/Simulink tool is used for this dynamic simulation study. The main contribution of this work is the implementation of the proposed controller on field programmable gate array (FPGA) hardware to drive the stepper motor. The driver is built on FPGA Spartan-3E Starter from Xilinx. Experimental results are presented to demonstrate the validity and effectiveness of the proposed control scheme.

Development of wavelet-ANN models to predict water quality parameters in Hilo Bay, Pacific Ocean.

Science.gov (United States)

Alizadeh, Mohamad Javad; Kavianpour, Mohamad Reza

2015-09-15

The main objective of this study is to apply artificial neural network (ANN) and wavelet-neural network (WNN) models for predicting a variety of ocean water quality parameters. In this regard, several water quality parameters in Hilo Bay, Pacific Ocean, are taken under consideration. Different combinations of water quality parameters are applied as input variables to predict daily values of salinity, temperature and DO as well as hourly values of DO. The results demonstrate that the WNN models are superior to the ANN models. Also, the hourly models developed for DO prediction outperform the daily models of DO. For the daily models, the most accurate model has R equal to 0.96, while for the hourly model it reaches up to 0.98. Overall, the results show the ability of the model to monitor the ocean parameters, in condition with missing data, or when regular measurement and monitoring are impossible. Copyright © 2015 Elsevier Ltd. All rights reserved.

Facteurs prédictifs de succès des étudiants en première année de médecine à l'université de Parakou

Science.gov (United States)

Adoukonou, Thierry; Tognon-Tchegnonsi, Francis; Mensah, Emile; Allodé, Alexandre; Adovoekpe, Jean-Marie; Gandaho, Prosper; Akpona, Simon

2016-01-01

Introduction Plusieurs facteurs dont les notes obtenues au BAC peuvent influencer les performances académiques des étudiants en première année de médecine. L'objectif de cette étude était d’évaluer la relation entre les résultats des étudiants au BAC et le succès en première année de médecine. Méthodes Nous avons réalisé une étude analytique ayant inclus l'ensemble des étudiants régulièrement inscrits en première année à la Faculté de Médecine de l'université de Parakou durant l'année académique 2010-2011. Les données concernant les notes par discipline et mention obtenue au BAC ont été collectées. Une analyse multivariée utilisant la régression logistique et la régression linéaire multiple a permis d’établir les meilleurs prédicteurs du succès et de la moyenne de l’étudiant en fin d'année. Le logiciel SPSS version 17.0 a été utilisé pour l'analyse des données et un p 15/20 était associée au succès (OR: 2,8 [1,32- 6,00]). Pour la moyenne générale obtenue en fin d'année seule une mention bien obtenue au BAC était associée (coefficient de l'erreur standard: 0,130 Bêta =0,370 et p=0,00001). Conclusion Les meilleurs prédicateurs du succès en première année étaient une bonne moyenne en sciences physiques au BAC et une mention bien. La prise en compte de ces éléments dans le recrutement des étudiants en première année pourrait améliorer les résultats académiques. PMID:27313819

Neuropathological findings processed by artificial neural networks (ANNs can perfectly distinguish Alzheimer's patients from controls in the Nun Study

Directory of Open Access Journals (Sweden)

Snowdon David

2007-06-01

Full Text Available Abstract Background Many reports have described that there are fewer differences in AD brain neuropathologic lesions between AD patients and control subjects aged 80 years and older, as compared with the considerable differences between younger persons with AD and controls. In fact some investigators have suggested that since neurofibrillary tangles (NFT can be identified in the brains of non-demented elderly subjects they should be considered as a consequence of the aging process. At present, there are no universally accepted neuropathological criteria which can mathematically differentiate AD from healthy brain in the oldest old. The aim of this study is to discover the hidden and non-linear associations among AD pathognomonic brain lesions and the clinical diagnosis of AD in participants in the Nun Study through Artificial Neural Networks (ANNs analysis Methods The analyses were based on 26 clinically- and pathologically-confirmed AD cases and 36 controls who had normal cognitive function. The inputs used for the analyses were just NFT and neuritic plaques counts in neocortex and hippocampus, for which, despite substantial differences in mean lesions counts between AD cases and controls, there was a substantial overlap in the range of lesion counts. Results By taking into account the above four neuropathological features, the overall predictive capability of ANNs in sorting out AD cases from normal controls reached 100%. The corresponding accuracy obtained with Linear Discriminant Analysis was 92.30%. These results were consistently obtained in ten independent experiments. The same experiments were carried out with ANNs on a subgroup of 13 non severe AD patients and on the same 36 controls. The results obtained in terms of prediction accuracy with ANNs were exactly the same. Input relevance analysis confirmed the relative dominance of NFT in neocortex in discriminating between AD patients and controls and indicated the lesser importance

Kuis saada läbi Siirita? / Mari-Ann Kelam, Erika Salumäe, Sirje Endre

Index Scriptorium Estoniae

Kelam, Mari-Ann, 1946-

2001-01-01

Riigikogu uude juhatusse ei kuulu ühtegi naist : Keskerakond valis Siiri Oviiri asemele Riigikogu aseesimehe kohale Peeter Kreitzbergi. Naiste osalemisvõimalust poliitikas kommenteerivad Riigikogu naisliikmed Mari-Ann Kelam, Erika Salumäe, Sirje Endre, Jaana Padrik, Viive Rosenberg, Mai Treial, Ivi Eenmaa, Liis Klaar, Liia Hänni, Laine Tarvis

75 FR 23745 - Jo-Ann Stores, Inc., Provisional Acceptance of a Settlement Agreement and Order

Science.gov (United States)

2010-05-04

... Acceptance of a Settlement Agreement and Order AGENCY: Consumer Product Safety Commission. ACTION: Notice... under the laws of the State of Ohio, with its principal offices located in Hudson, Ohio. At all times relevant hereto, Jo-Ann imported, offered for sale and sold various children's products. Staff Allegations...

E-kursus nõuab aega ja pühendumist / Ivo Leito, Irja Helm, Anne Krull ; intervjueerinud Laura Vetik

Index Scriptorium Estoniae

Leito, Ivo, 1972-

2015-01-01

Intervjuu Tartu Ülikooli keemiakursuse "Estimation of Measurement Uncertainty in Chemical Analysis" autorite Ivo Leito ja Irja Helmiga ning Tartu Kutsehariduskeskuse e-kursuse "Praktiline keemia" autori Anne Krulliga

Konverentsimuljeid tegijailt ja osalejailt / Monika Läänesaar, Ann Lumiste, Andrus Laansalu...[jt.] ; interv. Madis Kolk

Index Scriptorium Estoniae

2000-01-01

Rahvusvahelisest konverentsist "Lavailm" ja näitusest "Teatrikunstnik...kes ta on?" (kuraator Ann Lumiste) Rotermanni soolalaos, teatrikunstniku positsioonist teatris, uue meedia ja teatri koostöö võimalikkusest, keskkonna ja visuaalsete elementide mõju lavastaja- ja näitlejatööle.

DESIGN OF A VISUAL INTERFACE FOR ANN BASED SYSTEMS

Directory of Open Access Journals (Sweden)

Ramazan BAYINDIR

2008-01-01

Full Text Available Artificial intelligence application methods have been used for control of many systems with parallel of technological development besides conventional control techniques. Increasing of artificial intelligence applications have required to education in this area. In this paper, computer based an artificial neural network (ANN software has been presented to learning and understanding of artificial neural networks. By means of the developed software, the training of the artificial neural network according to the inputs provided and a test action can be performed by changing the components such as iteration number, momentum factor, learning ratio, and efficiency function of the artificial neural networks. As a result of the study a visual education set has been obtained that can easily be adapted to the real time application.

Les années d’apprentissage des 'Annales révolutionnaires' (1908-1918)

NARCIS (Netherlands)

den Boer, P.

2008-01-01

Entre le passé radical et l'horizon communiste, voici les années d'apprentissage des 'Annales révolutionnaires'. En rétrospective, des révolutions de gauche eçhouées et des expériences douloureuses de défaite de 1794, de 1830, de 1848, des Quarante-huitards déçus, des Communards tués ou exilés. En

Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

Science.gov (United States)

Hoffer, R. M. (Principal Investigator); Knowlton, D. J.; Dean, M. E.

1981-01-01

Supervised and cluster block training statistics were used to analyze the thematic mapper simulation MSS data (both 1979 and 1980 data sets). Cover information classes identified on SAR imagery include: hardwood, pine, mixed pine hardwood, clearcut, pasture, crops, emergent crops, bare soil, urban, and water. Preliminary analysis of the HH and HV polarized SAR data indicate a high variance associated with each information class except for water and bare soil. The large variance for most spectral classes suggests that while the means might be statistically separable, an overlap may exist between the classes which could introduce a significant classification error. The quantitative values of many cover types are much larger on the HV polarization than on the HH, thereby indicating the relative nature of the digitized data values. The mean values of the spectral classes in the areas with larger look angles are greater than the means of the same cover type in other areas having steeper look angles. Difficulty in accurately overlaying the dual polarization of the SAR data was resolved.

Evaluación de un programa de maestría en Educación a través de la MSS

Directory of Open Access Journals (Sweden)

José Roberto Ramos Mendoza

2016-05-01

Full Text Available La evaluación de los programas de posgrado es una necesidad para su adecuación a las demandas sociales y laborales. El objetivo fue evaluar el Programa de Maestría en Administración en Gestión y Desarrollo de la Educación de la Escasto-IPN, a través de la metodología de los sistemas suaves (MSS, que facilitó un pensamiento integral de los actores intervinientes en el problema, haciendo análisis particular mediante la nemotecnia Catwoe, con un resultado integral conforme los criterios PNPC-CONACyT. Se aplicaron tres cuestionarios validados. Un resultado destacado es la necesidad de formación de cuadros directivos en ámbitos como inteligencia emocional, normatividad, ética y transparencia. En conclusión, el posgrado adquiere un nuevo compromiso: dejar de lado la mercantilización de la educación y convertirse en generador de personas críticas, analíticas y sobre todo propositivas que a su vez sean generadoras de innovaciones en pro de la calidad educativa. AbstractThe assessment of graduate programs is a necessity for adaptation to social and labor demands. The objective was to evaluate the MBA program in Management and Development of Education of the ESCASTO-IPN, through the Soft Systems Methodology (MSS, it provided a comprehensive thinking of the actors involved in the issue, doing CATWOE particular analysis by mnemonic, achieving a comprehensive income based on the PNPC criteria - CONACyT. Three questionnaires were applied validated. A prominent result is the need for training of cadres in areas such as: emotional intelligence, regulation, ethics and transparency. In conclusion, the graduate acquires a new commitment, neglecting the commodification of education and become generator critics, analytical and proactive especially in turn are generating innovations in favor of quality education.

Algõpetuse peajoon ja harupedagoogikad / Sirje Piht, Elve Voltein, Anne Uusen, Inge Timoštšuk

Index Scriptorium Estoniae

2012-01-01

Intervjuu Sirje Pihti ja Anne Uuseniga Tallinna Ülikooli algõpetuse osakonnast, Elve Volteiniga Tartu Ülikooli haridusteaduste instituudi õpetajate seminarist ja Inge Timoštšukiga Tallinna Ülikooli kasvatusteaduste instituudi pedagoogilise praktika keskusest

Tagasipöördumine esteetika juurde = Return to aesthetics / Keith Moxey, Michael Ann Holly ; interv. Anu Allas

Index Scriptorium Estoniae

Moxey, Keith

2007-01-01

Ameerika kunstiajaloolased Keith Moxey ning Michael Ann Holly tutvustavad uut lähenemist kunstiajaloole (new art history). Nn. naasmine esteetika juurde tähendab püüet integreerida kunstiajalukku ja -teooriasse uuesti ja tugevamalt kunstiteos

76 FR 80392 - Notice of Inventory Completion: University of Michigan Museum of Anthropology, Ann Arbor, MI

Science.gov (United States)

2011-12-23

...: University of Michigan Museum of Anthropology, Ann Arbor, MI AGENCY: National Park Service, Interior. ACTION... Michigan officials and its Museum of Anthropology professional staff in consultation with representatives... accessioned into the Museum of Anthropology. Between 2007 and 2009 the remains were inventoried at the...

Aivar Riisalu : loomulikult läksin üle piiri ja vabandan / Aivar Riisalu ; interv. Anneli Ammas

Index Scriptorium Estoniae

Riisalu, Aivar, 1961-

2006-01-01

Aivar Riisalu selgitab oma mõtteavaldusi Kanal 2 telesaates "Top 10" ning ütleb, et temas ei ole rassivaenu. Vt. samas: Anneli Ammas, Sigrid Laev. Kaitsepolitsei võib algatada kriminaalasja; Sigrid Laev. Riisalu pääses kriminaalmenetlusest. Lisa: Riisalu avaldused "Top 10" saates

12-bit 32 channel 500 MS/s low-latency ADC for particle accelerators real-time control

Science.gov (United States)

Karnitski, Anton; Baranauskas, Dalius; Zelenin, Denis; Baranauskas, Gytis; Zhankevich, Alexander; Gill, Chris

2017-09-01

Particle beam control systems require real-time low latency digital feedback with high linearity and dynamic range. Densely packed electronic systems employ high performance multichannel digitizers causing excessive heat dissipation. Therefore, low power dissipation is another critical requirement for these digitizers. A described 12-bit 500 MS/s ADC employs a sub-ranging architecture based on a merged sample & hold circuit, a residue C-DAC and a shared 6-bit flash core ADC. The core ADC provides a sequential coarse and fine digitization featuring a latency of two clock cycles. The ADC is implemented in a 28 nm CMOS process and consumes 4 mW of power per channel from a 0.9 V supply (interfacing and peripheral circuits are excluded). Reduced power consumption and small on-chip area permits the implementation of 32 ADC channels on a 10.7 mm2 chip. The ADC includes a JESD204B standard compliant output data interface operated at the 7.5 Gbps/ch rate. To minimize the data interface related time latency, a special feature permitting to bypass the JESD204B interface is built in. DoE Phase I Award Number: DE-SC0017213.

Beginning and ending of Anne Hebert's 'Burden of Dreams' : Polysemy of a journey of identity

NARCIS (Netherlands)

Lintvelt, Jaap

2007-01-01

The protagonist of Anne Hebert's Burden of Dreams (1992) goes on a journey from Quebec to Paris that contributes to the evolution of his personal and cultural identity The novel's title already tells us that "dreams" will play. a key role both on a thematic level and in shaping the reading protocol.

La decision de Anne (2009: estudio de la creación de embriones genéticamente seleccionados para la curación de pacientes crónicos

Directory of Open Access Journals (Sweden)

Ester CASILLAS SAGRADO

2016-09-01

Full Text Available La decisión de Anne/ My sister´s keeper (2009 es una película de Nick Cassavetes que cuenta la historia de Anne Fitzgerald, una niña de 11 años que fue concebida para salvar a su hermana mayor, Karen, con Leucemia Promielocítica Aguda. Cuando se le plantea la necesidad de realizar un trasplante de riñón a su hermana enferma, Anne decide demandar a sus padres sobre los derechos de su cuerpo para no tener que someterse a ese procedimiento que puede condicionar para siempre su calidad de vida. Ante esta situación la madre de Anne comienza una lucha judicial contra la menor de sus hijas en un intento de disuadirla para que realice la donación aunque esto implique seguir siendo el soporte del que dependa la supervivencia de su hermana de forma indefinida.

USING ARTIFICIAL NEURAL NETWORKS (ANNs FOR SEDIMENT LOAD FORECASTING OF TALKHEROOD RIVER MOUTH

Directory of Open Access Journals (Sweden)

Vahid Nourani

2009-01-01

Full Text Available Without a doubt the carried sediment load by a river is the most important factor in creating and formation of the related Delta in the river mouth. Therefore, accurate forecasting of the river sediment load can play a significant role for study on the river Delta. However considering the complexity and non-linearity of the phenomenon, the classic experimental or physical-based approaches usually could not handle the problem so well. In this paper, Artificial Neural Network (ANN as a non-linear black box interpolator tool is used for modeling suspended sediment load which discharges to the Talkherood river mouth, located in northern west Iran. For this purpose, observed time series of water discharge at current and previous time steps are used as the model input neurons and the model output neuron will be the forecasted sediment load at the current time step. In this way, various schemes of the ANN approach are examined in order to achieve the best network as well as the best architecture of the model. The obtained results are also compared with the results of two other classic methods (i.e., linear regression and rating curve methods in order to approve the efficiency and ability of the proposed method.

Prediction of groundwater levels from lake levels and climate data using ANN approach

OpenAIRE

Dogan, Ahmet; Demirpence, Husnu; Cobaner, Murat

2008-01-01

There are many environmental concerns relating to the quality and quantity of surface and groundwater. It is very important to estimate the quantity of water by using readily available climate data for managing water resources of the natural environment. As a case study an artificial neural network (ANN) methodology is developed for estimating the groundwater levels (upper Floridan aquifer levels) as a function of monthly averaged precipitation, evaporation, and measured levels of Magnolia an...

Classification of molecular structure images by using ANN, RF, LBP, HOG, and size reduction methods for early stomach cancer detection

Science.gov (United States)

Aytaç Korkmaz, Sevcan; Binol, Hamidullah

2018-03-01

Patients who die from stomach cancer are still present. Early diagnosis is crucial in reducing the mortality rate of cancer patients. Therefore, computer aided methods have been developed for early detection in this article. Stomach cancer images were obtained from Fırat University Medical Faculty Pathology Department. The Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG) features of these images are calculated. At the same time, Sammon mapping, Stochastic Neighbor Embedding (SNE), Isomap, Classical multidimensional scaling (MDS), Local Linear Embedding (LLE), Linear Discriminant Analysis (LDA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Laplacian Eigenmaps methods are used for dimensional the reduction of the features. The high dimension of these features has been reduced to lower dimensions using dimensional reduction methods. Artificial neural networks (ANN) and Random Forest (RF) classifiers were used to classify stomach cancer images with these new lower feature sizes. New medical systems have developed to measure the effects of these dimensions by obtaining features in different dimensional with dimensional reduction methods. When all the methods developed are compared, it has been found that the best accuracy results are obtained with LBP_MDS_ANN and LBP_LLE_ANN methods.

ANN Model-Based Simulation of the Runoff Variation in Response to Climate Change on the Qinghai-Tibet Plateau, China

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Chang Juan

2017-01-01

Full Text Available Precisely quantitative assessments of stream flow response to climatic change and permafrost thawing are highly challenging and urgent in cold regions. However, due to the notably harsh environmental conditions, there is little field monitoring data of runoff in permafrost regions, which has limited the development of physically based models in these regions. To identify the impacts of climate change in the runoff process in the Three-River Headwater Region (TRHR on the Qinghai-Tibet Plateau, two artificial neural network (ANN models, one with three input variables (previous runoff, air temperature, and precipitation and another with two input variables (air temperature and precipitation only, were developed to simulate and predict the runoff variation in the TRHR. The results show that the three-input variable ANN model has a superior real-time prediction capability and performs well in the simulation and forecasting of the runoff variation in the TRHR. Under the different scenarios conditions, the forecasting results of ANN model indicated that climate change has a great effect on the runoff processes in the TRHR. The results of this study are of practical significance for water resources management and the evaluation of the impacts of climatic change on the hydrological regime in long-term considerations.

Joseph Campbell, Jung, Anne Tyler, and "The Cards": The Spiritual Journey in "Searching for Caleb."

Science.gov (United States)

Thomson, Karen M.

Joseph Campbell, Carl Jung, and Anne Tyler have all dealt with spiritual journeys and card reading in their writings. In his book "Tarot Revelations," Joseph Campbell discusses his first association with tarot cards, dating from 1943, when he was introduced to the symoblism of playing cards by his friend and mentor, Heinrich Zimmer. Carl…

Fact and fiction: subverting orientalism in Ann Bridge's The dark moment

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Isil Bas

2013-12-01

Full Text Available While postcolonial criticism has extensively traced the Western women writers's accounts of the Orient, Ann Bridge's contribution to the genre remained unheard-of. In The Dark Moment she tells the story of the foundation of the Turkish republic after the struggle against Western imperialism, a theme highly controversial for a British diplomat's wife. Moreover, she plays with the conventions and representational strategies of traditional Orientalist narratives inverting each in turn to create an unprejudiced awareness of the historical context and the social and cultural specificities of Turkey and the Turk thereby foregrounding dialogical transculturality over intercultural penetration.

Kommunikatsioonijuht saab aidata arsti ja patsienti / Eda Amur, Anneli Bogens, Svea Talving, Krista Valdvee ; intervjueerinud Küllike Heide

Index Scriptorium Estoniae

2013-01-01

Meditsiinivaldkonna kommunikatsiooniga seotud küsimuste ja probleemide üle arutlevad nelja haigla kommunikatsioonijuhid: Eda Amur Pärnu haiglast, Anneli Bogens Ida-Viru keskhaiglast, Svea Talving Ida-Tallinna keskhaiglast ning Krista Valdvee Viljandi haiglast

76 FR 73670 - Notice of Inventory Completion: University of Michigan Museum of Anthropology, Ann Arbor, MI

Science.gov (United States)

2011-11-29

...: University of Michigan Museum of Anthropology, Ann Arbor, MI AGENCY: National Park Service, Interior. ACTION... Museum of Anthropology NAGPRA collections staff in consultation with representatives of the Bay Mills... Anthropology purchased the human remains from Reverend L. P. Rowland in November of 1924 as part of a larger...

Comparative study on the predictability of statistical models (RSM and ANN) on the behavior of optimized buccoadhesive wafers containing Loratadine and their in vivo assessment.

Science.gov (United States)

Chakraborty, Prithviraj; Parcha, Versha; Chakraborty, Debarupa D; Ghosh, Amitava

2016-01-01

Buccoadhesive wafer dosage form containing Loratadine is formulated utilizing Formulation by Design (FbD) approach incorporating sodium alginate and lactose monohydrate as independent variable employing solvent casting method. The wafers were statistically optimized using Response Surface Methodology (RSM) and Artificial Neural Network algorithm (ANN) for predicting physicochemical and physico-mechanical properties of the wafers as responses. Morphologically wafers were tested using SEM. Quick disintegration of the samples was examined employing Optical Contact Angle (OCA). The comparison of the predictability of RSM and ANN showed a high prognostic capacity of RSM model over ANN model in forecasting mechanical and physicochemical properties of the wafers. The in vivo assessment of the optimized buccoadhesive wafer exhibits marked increase in bioavailability justifying the administration of Loratadine through buccal route, bypassing hepatic first pass metabolism.

Régis Boulat, Jean Fourastié, un expert en productivité. La modernisation de la France (années 1930–années 1950)

OpenAIRE

Denord, François

2011-01-01

De Jean Fourastié, beaucoup se souviennent qu’il a inventé la formule « les Trente Glorieuses ». Sa renommée aurait pu à elle seule justifier une biographie. Issu d’une thèse de doctorat d’histoire soutenue à l’université de Franche-Comté, le livre de Régis Boulat doit pourtant peu à ce genre académique. S’il rend compte de la trajectoire de Jean Fourastié, c’est comme véhicule de la notion de productivité en France entre les années 1930 et 1950. Praticien et expert de l’économie, haut foncti...

Evaluation of SLAR and simulated thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

Science.gov (United States)

Hoffer, R. M.; Dean, M. E.; Knowlton, D. J.; Latty, R. S.

1982-01-01

Kershaw County, South Carolina was selected as the study site for analyzing simulated thematic mapper MSS data and dual-polarized X-band synthetic aperture radar (SAR) data. The impact of the improved spatial and spectral characteristics of the LANDSAT D thematic mapper data on computer aided analysis for forest cover type mapping was examined as well as the value of synthetic aperture radar data for differentiating forest and other cover types. The utility of pattern recognition techniques for analyzing SAR data was assessed. Topics covered include: (1) collection and of TMS and reference data; (2) reformatting, geometric and radiometric rectification, and spatial resolution degradation of TMS data; (3) development of training statistics and test data sets; (4) evaluation of different numbers and combinations of wavelength bands on classification performance; (5) comparison among three classification algorithms; and (6) the effectiveness of the principal component transformation in data analysis. The collection, digitization, reformatting, and geometric adjustment of SAR data are also discussed. Image interpretation results and classification results are presented.

La ville selon Babar: espace urbain et ville-modèle dans les années 1930

Directory of Open Access Journals (Sweden)

Laurent GRISON

1997-03-01

Full Text Available L'analyse de deux représentations urbaines présentes dans les albums pour enfants de Jean de Brunhoff nous permet de mettre en évidence la diffusion des recherches géographiques et urbanistiques dans les années 1930.

76 FR 44947 - Notice of Intent To Repatriate Cultural Items: University of Michigan Museum of Anthropology, Ann...

Science.gov (United States)

2011-07-27

... Cultural Items: University of Michigan Museum of Anthropology, Ann Arbor, MI AGENCY: National Park Service, Interior. ACTION: Notice. SUMMARY: The University of Michigan Museum of Anthropology, in consultation with... contact the University of Michigan Museum of Anthropology. DATES: Representatives of any Indian tribe that...

The modelling of lead removal from water by deep eutectic solvents functionalized CNTs: artificial neural network (ANN) approach.

Science.gov (United States)

Fiyadh, Seef Saadi; AlSaadi, Mohammed Abdulhakim; AlOmar, Mohamed Khalid; Fayaed, Sabah Saadi; Hama, Ako R; Bee, Sharifah; El-Shafie, Ahmed

2017-11-01

The main challenge in the lead removal simulation is the behaviour of non-linearity relationships between the process parameters. The conventional modelling technique usually deals with this problem by a linear method. The substitute modelling technique is an artificial neural network (ANN) system, and it is selected to reflect the non-linearity in the interaction among the variables in the function. Herein, synthesized deep eutectic solvents were used as a functionalized agent with carbon nanotubes as adsorbents of Pb 2+ . Different parameters were used in the adsorption study including pH (2.7 to 7), adsorbent dosage (5 to 20 mg), contact time (3 to 900 min) and Pb 2+ initial concentration (3 to 60 mg/l). The number of experimental trials to feed and train the system was 158 runs conveyed in laboratory scale. Two ANN types were designed in this work, the feed-forward back-propagation and layer recurrent; both methods are compared based on their predictive proficiency in terms of the mean square error (MSE), root mean square error, relative root mean square error, mean absolute percentage error and determination coefficient (R 2 ) based on the testing dataset. The ANN model of lead removal was subjected to accuracy determination and the results showed R 2 of 0.9956 with MSE of 1.66 × 10 -4 . The maximum relative error is 14.93% for the feed-forward back-propagation neural network model.

Anne K. Bang: Islamic Sufi Networks in the Western Indian Ocean (c. 1880-1940. Ripples of Reform.

Directory of Open Access Journals (Sweden)

Angelika Brodersen

2015-03-01

Full Text Available This contribution offers a review of Anne K. Bang's book: Islamic Sufi Networks in the Western Indian Ocean (c. 1880-1940. Ripples of Reform. Islam in Africa, Volume 16. Leiden: Brill 2014. xiv + 227 pages, € 104.00, ISBN 978-900-425-1342.

Design of an Experiment to Measure ann Using 3H(γ, pnn at HIγS★

Directory of Open Access Journals (Sweden)

Friesen F.Q.L.

2016-01-01

Full Text Available We provide an update on the development of an experiment at TUNL for determining the 1S0 neutron-neutron (nn scattering length (ann from differential cross-section measurements of three-body photodisintegration of the triton. The experiment will be conducted using a linearly polarized gamma-ray beam at the High Intensity Gamma-ray Source (HIγS and tritium gas contained in thin-walled cells. The main components of the planned experiment are a 230 Ci gas target system, a set of wire chambers and silicon strip detectors on each side of the beam axis, and an array of neutron detectors on each side beyond the silicon detectors. The protons emitted in the reaction are tracked in the wire chambers and their energy and position are measured in silicon strip detectors. The first iteration of the experiment will be simplified, making use of a collimator system, and silicon detectors to interrogate the main region of interest near 90° in the polar angle. Monte-Carlo simulations based on rigorous 3N calculations have been conducted to validate the sensitivity of the experimental setup to ann.

Usefulness of ANN-based model for copper removal from aqueous solutions using agro industrial waste materials

Directory of Open Access Journals (Sweden)

Petrović Marija S.

2015-01-01

Full Text Available The purpose of this study was to investigate the adsorption properties of locally available lignocelluloses biomaterials as biosorbents for the removal of copper ions from aqueous solution. Materials are generated from juice production (apricot stones and from the corn milling process (corn cob. Such solid wastes have little or no economic value and very often present a disposal problem. Using batch adsorption techniques the effects of initial Cu(II ions concentration (Ci, amount of biomass (m and volume of metal solution (V, on biosorption efficiency and capacity were studied for both materials, without any pre-treatments. The optimal parameters for both biosorbents were selected depending on a highest sorption capability of biosorbent, in removal of Cu(II. Experimental data were compared with second order polynomial regression models (SOPs and artificial neural networks (ANNs. SOPs showed acceptable coefficients of determination (0.842 - 0.997, while ANNs performed high prediction accuracy (0.980-0.986 in comparison to experimental results. [Projekat Ministarstva nauke Republike Srbije, br. TR 31003, TR 31055

Une Nouvelle Forme d’Autobiographie dans Les Années d’Annie Ernaux: Autobiographie Impersonnelle

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Seçil Yücedağ

2017-12-01

Full Text Available Annie Ernaux, considérée comme l’une des femmes écrivaines les plus célèbres du XXIe siècle, a exprimé l’angoisse commune de son âge et de son passé en rédigeant Les Années. Elle n’avait pas non seulement le but de décrire sa vie, mais aussi d’esquisser l’histoire de la société française à laquelle elle appartient. Lorsqu’elle est venue au monde en 1940, le monde était au seuil de la Seconde Guerre mondiale. Etant élevée dans cette atmosphère chaotique, elle a appris beaucoup de choses de sa société, de sa famille et de son environnement. Annie Ernaux a découvert le monde comme une jeune fille, une mère, une épouse et une grand-mère. Ses expériences sociales et familiales l’ont beaucoup mûrie et elle a commencé à rédiger ses pensées. Ses souvenirs ont fait partie de ses écritures autobiographiques. Dans Les Années, Annie Ernaux a profité de toutes ses expériences personnelles et sociales avec de différents moyens. Elle a essayé d’établir des liens entre l’histoire de sa vie et celle de la société. Elle a accordé une importance à la vie sociale plutôt que sa propre vie dans Les Années. Elle y a développé des propres techniques d’écriture en se servant des photos familiales et personnelles, d’un film, d’une vidéo, des marques de publicité, des chansons, d’un tableau, des notes de journal ainsi que des événements sociologiques et historiques. Elle a ainsi créé une nouvelle forme d’autobiographie : autobiographie impersonnelle.

降雨が流出に影響を及ぼす日数のANN^※を利用した推測

OpenAIRE

山田, 幸寿; 四俵, 正俊

2000-01-01

Groundwater runoff is originated from the rain of the past. The influential period of rain on groundwater runoff is said to be from one month to one year. The authors carried out long term runoff estimation for Shonai River Basin, Chubu, Japan by means of artificial neural networks (ANN). The period of strong influence of rain on the runoff was sought by comparing the accuracy of estimations with various periods of rain used as inputs of ANN. One month was found probable as the influential pe...

Prediction of moving bed biofilm reactor (MBBR) performance for the treatment of aniline using artificial neural networks (ANN)

Energy Technology Data Exchange (ETDEWEB)

Delnavaz, M. [Tarbiat Modares University, Civil Engineering Department, Environmental Engineering Division, Tehran (Iran, Islamic Republic of); Ayati, B., E-mail: ayati_bi@modares.ac.ir [Tarbiat Modares University, Civil Engineering Department, Environmental Engineering Division, Tehran (Iran, Islamic Republic of); Ganjidoust, H. [Tarbiat Modares University, Civil Engineering Department, Environmental Engineering Division, Tehran (Iran, Islamic Republic of)

2010-07-15

In this study, the results of 1-year efficiency forecasting using artificial neural networks (ANN) models of a moving bed biofilm reactor (MBBR) for a toxic and hard biodegradable aniline removal were investigated. The reactor was operated in an aerobic batch and continuous condition with 50% by volume which was filled with light expanded clay aggregate (LECA) as carrier. Efficiency evaluation of the reactors was obtained at different retention time (RT) of 8, 24, 48 and 72 h with an influent COD from 100 to 4000 mg/L. Exploratory data analysis was used to detect relationships between the data and dependent evaluated one. The appropriate architecture of the neural network models was determined using several steps of training and testing of the models. The ANN-based models were found to provide an efficient and a robust tool in predicting MBBR performance for treating aromatic amine compounds.

Assessing the Long Term Impact of Phosphorus Fertilization on Phosphorus Loadings Using AnnAGNPS

OpenAIRE

Yuan, Yongping; Bingner, Ronald L.; Locke, Martin A.; Stafford, Jim; Theurer, Fred D.

2011-01-01

High phosphorus (P) loss from agricultural fields has been an environmental concern because of potential water quality problems in streams and lakes. To better understand the process of P loss and evaluate the effects of different phosphorus fertilization rates on phosphorus losses, the USDA Annualized AGricultural Non-Point Source (AnnAGNPS) pollutant loading model was applied to the Ohio Upper Auglaize watershed, located in the southern portion of the Maumee River Basin. In this study, the ...

FE-ANN based modeling of 3D Simple Reinforced Concrete Girders for Objective Structural Health Evaluation : Tech Transfer Summary

Science.gov (United States)

2017-06-01

The objective of this study was to develop an objective, quantitative method for evaluating damage to bridge girders by using artificial neural networks (ANNs). This evaluation method, which is a supplement to visual inspection, requires only the res...

Review: Miller, Michelle Ann (2009, Rebellion and Reform in Indonesia – Jakarta’s Security and Autonomy Policies in Aceh

Directory of Open Access Journals (Sweden)

Antje Missbach

2009-01-01

Full Text Available Review of the monograph: Miller, Michelle Ann, Rebellion and Reform in Indonesia – Jakarta’s Security and Autonomy Policies in Aceh, London/ New York: Routledge, 2009, ISBN 13: 978-0-415-45467-4, 240 pages.

Optimal factor evaluation for the dissolution of alumina from Azaraegbelu clay in acid solution using RSM and ANN comparative analysis

Directory of Open Access Journals (Sweden)

P.E. Ohale

2017-12-01

Full Text Available Artificial neural network (ANN and Response Surface Methodology based on a 25−1 fractional factorial design were used as tools for simulation and optimisation of the dissolution process for Azaraegbelu clay. A feedforward neural network model with Levenberg–Marquard back propagating training algorithm was adapted to predict the response (alumina yield. The studied input variables were temperature, stirring speed, clay to acid dosage, leaching time and leachant concentration. The raw clay was characterized for structure elucidation via FTIR, SEM and X-ray diffraction spectroscopic techniques and the result indicates that the clay is predominantly kaolinite. Leachant concentration and dosage ratio were found to be the most significant process parameter with p-value of 0.0001. The performance of the ANN and RSM model showed adequate prediction of the response, with AAD of 11.6% and 3.6%, and R2 of 0.9733 and 0.9568, respectively. A non-dominated optimal response of 81.45% yield of alumina at 4.6 M sulphuric acid concentration, 214 min leaching time, 0.085 g/ml dosage and 214 rpm stirring speed was established as a viable route for reduced material and operating cost via RSM. Keywords: Alumina dissolution, ANN modelling, Azaraegbelu, Clay, RSM

Prediction of shear and tensile strength of the diffusion bonded AA5083 and AA7075 aluminium alloy using ANN

International Nuclear Information System (INIS)

Sagai Francis Britto, A.; Raj, R. Edwin; Mabel, M. Carolin

2017-01-01

Diffusion bonding is a pressure welding technique to establish bonds by inter diffusion of atoms. Bonding characteristics were generated by varying the significant process conditions such as the bonding temperature, the pressing load and the duration of pressure while bonding the aluminium alloys AA5083 and AA7075. Deriving analytical correlation with the process variables to weld strength is quite involved due to the non-linear dependency of the process variables with the mechanical strength of the joints. An arbitrary function approximation mechanism, the artificial neural network (ANN) is therefore employed to develop the models for predicting the mechanical properties of the bonded joints. Back propagation technique, which alters the network weights to minimize the mean square error was used to develop the ANN models. The models were tested, validated and found to be satisfactory with good prediction accuracy.

Prediction of shear and tensile strength of the diffusion bonded AA5083 and AA7075 aluminium alloy using ANN

Energy Technology Data Exchange (ETDEWEB)

Sagai Francis Britto, A. [Department of Mechanical Engineering, St.Xavier' s Catholic College of Engineering, Nagercoil 629003,Tamil Nadu (India); Raj, R. Edwin, E-mail: redwinraj@gmail.com [Department of Mechanical Engineering, St.Xavier' s Catholic College of Engineering, Nagercoil 629003,Tamil Nadu (India); Mabel, M. Carolin [Department of Electrical and Electronics Engineering, St.Xavier' s Catholic College of Engineering, Nagercoil 629003,Tamil Nadu (India)

2017-04-24

Diffusion bonding is a pressure welding technique to establish bonds by inter diffusion of atoms. Bonding characteristics were generated by varying the significant process conditions such as the bonding temperature, the pressing load and the duration of pressure while bonding the aluminium alloys AA5083 and AA7075. Deriving analytical correlation with the process variables to weld strength is quite involved due to the non-linear dependency of the process variables with the mechanical strength of the joints. An arbitrary function approximation mechanism, the artificial neural network (ANN) is therefore employed to develop the models for predicting the mechanical properties of the bonded joints. Back propagation technique, which alters the network weights to minimize the mean square error was used to develop the ANN models. The models were tested, validated and found to be satisfactory with good prediction accuracy.

The Short Fiction of Bobbie Ann Mason: Silent Voices, Silenced Voices, Voicing Silence.

OpenAIRE

Delgado Marín, Candela

2015-01-01

La presente tesis doctoral se enmarca dentro del campo de los estudios norteamericanos, centrándose en el relato breve de la escritora sureña Bobbie Ann Mason. El título de este proyecto apunta al foco de la investigación: el silencio. He utilizado tres puntos de vista diferentes para examinar los cuentos de esta escritora: el contexto socio-cultural, estudios comparativos literarios y teóricos y, por último, el análisis textual de su narrativa. Considero la producción literaria de Bobbie ...

Support vector machine regression (LS-SVM)--an alternative to artificial neural networks (ANNs) for the analysis of quantum chemistry data?

Science.gov (United States)

Balabin, Roman M; Lomakina, Ekaterina I

2011-06-28

A multilayer feed-forward artificial neural network (MLP-ANN) with a single, hidden layer that contains a finite number of neurons can be regarded as a universal non-linear approximator. Today, the ANN method and linear regression (MLR) model are widely used for quantum chemistry (QC) data analysis (e.g., thermochemistry) to improve their accuracy (e.g., Gaussian G2-G4, B3LYP/B3-LYP, X1, or W1 theoretical methods). In this study, an alternative approach based on support vector machines (SVMs) is used, the least squares support vector machine (LS-SVM) regression. It has been applied to ab initio (first principle) and density functional theory (DFT) quantum chemistry data. So, QC + SVM methodology is an alternative to QC + ANN one. The task of the study was to estimate the Møller-Plesset (MPn) or DFT (B3LYP, BLYP, BMK) energies calculated with large basis sets (e.g., 6-311G(3df,3pd)) using smaller ones (6-311G, 6-311G*, 6-311G**) plus molecular descriptors. A molecular set (BRM-208) containing a total of 208 organic molecules was constructed and used for the LS-SVM training, cross-validation, and testing. MP2, MP3, MP4(DQ), MP4(SDQ), and MP4/MP4(SDTQ) ab initio methods were tested. Hartree-Fock (HF/SCF) results were also reported for comparison. Furthermore, constitutional (CD: total number of atoms and mole fractions of different atoms) and quantum-chemical (QD: HOMO-LUMO gap, dipole moment, average polarizability, and quadrupole moment) molecular descriptors were used for the building of the LS-SVM calibration model. Prediction accuracies (MADs) of 1.62 ± 0.51 and 0.85 ± 0.24 kcal mol(-1) (1 kcal mol(-1) = 4.184 kJ mol(-1)) were reached for SVM-based approximations of ab initio and DFT energies, respectively. The LS-SVM model was more accurate than the MLR model. A comparison with the artificial neural network approach shows that the accuracy of the LS-SVM method is similar to the accuracy of ANN. The extrapolation and interpolation results show that LS-SVM is

Valorization of aquaculture waste in removal of cadmium from aqueous solution: optimization by kinetics and ANN analysis

Science.gov (United States)

Aditya, Gautam; Hossain, Asif

2018-05-01

Cadmium is one of the most hazardous heavy metal concerning human health and aquatic pollution. The removal of cadmium through biosorption is a feasible option for restoration of the ecosystem health of the contaminated freshwater ecosystems. In compliance with this proposition and considering the efficiency of calcium carbonate as biosorbent, the shell dust of the economically important snail Bellamya bengalensis was tested for the removal of cadmium from aqueous medium. Following use of the flesh as a cheap source of protein, the shells of B. bengalensis made up of CaCO3 are discarded as aquaculture waste. The biosorption was assessed through batch sorption studies along with studies to characterize the morphology and surface structures of waste shell dust. The data on the biosorption were subjected to the artificial neural network (ANN) model for optimization of the process. The biosorption process changed as functions of pH of the solution, concentration of heavy metal, biomass of the adsorbent and time of exposure. The kinetic process was well represented by pseudo second order ( R 2 = 0.998), and Langmuir equilibrium ( R 2 = 0.995) had better fits in the equilibrium process with 30.33 mg g-1 of maximum sorption capacity. The regression equation ( R 2 = 0.948) in the ANN model supports predicted values of Cd removal satisfactorily. The normalized importance analysis in ANN predicts Cd2+ concentration, and pH has the most influence in removal than biomass dose and time. The SEM and EDX studies show clear peaks for Cd confirming the biosorption process while the FTIR study depicts the main functional groups (-OH, C-H, C=O, C=C) responsible for the biosorption process. The study indicated that the waste shell dust can be used as an efficient, low cost, environment friendly, sustainable adsorbent for the removal of cadmium from aqueous solution.

Biosurfactant-biopolymer driven microbial enhanced oil recovery (MEOR) and its optimization by an ANN-GA hybrid technique.

Science.gov (United States)

Dhanarajan, Gunaseelan; Rangarajan, Vivek; Bandi, Chandrakanth; Dixit, Abhivyakti; Das, Susmita; Ale, Kranthikiran; Sen, Ramkrishna

2017-08-20

A lipopeptide biosurfactant produced by marine Bacillus megaterium and a biopolymer produced by thermophilic Bacillus licheniformis were tested for their application potential in the enhanced oil recovery. The crude biosurfactant obtained after acid precipitation effectively reduced the surface tension of deionized water from 70.5 to 28.25mN/m and the interfacial tension between lube oil and water from 18.6 to 1.5mN/m at a concentration of 250mgL -1 . The biosurfactant exhibited a maximum emulsification activity (E 24 ) of 81.66% against lube oil. The lipopeptide micelles were stabilized by addition of Ca 2+ ions to the biosurfactant solution. The oil recovery efficiency of Ca 2+ conditioned lipopeptide solution from a sand-packed column was optimized by using artificial neural network (ANN) modelling coupled with genetic algorithm (GA) optimization. Three important parameters namely lipopeptide concentration, Ca 2+ concentration and solution pH were considered for optimization studies. In order to further improve the recovery efficiency, a water soluble biopolymer produced by Bacillus licheniformis was used as a flooding agent after biosurfactant incubation. Upon ANN-GA optimization, 45% tertiary oil recovery was achieved, when biopolymer at a concentration of 3gL -1 was used as a flooding agent. Oil recovery was only 29% at optimal conditions predicted by ANN-GA, when only water was used as flooding solution. The important characteristics of biopolymers such as its viscosity, pore plugging capabilities and bio-cementing ability have also been tested. Thus, as a result of biosurfactant incubation and biopolymer flooding under the optimal process conditions, a maximum oil recovery of 45% was achieved. Therefore, this study is novel, timely and interesting for it showed the combined influence of biosurfactant and biopolymer on solubilisation and mobilization of oil from the soil. Copyright © 2017 Elsevier B.V. All rights reserved.

Wives, love and animals: themes in the Poetry of Adrienne Rich and Carol Ann Duffy

Directory of Open Access Journals (Sweden)

Eleonora Rao

2013-10-01

Full Text Available This paper discusses firstly, the  poetical space of celebrated American poet Adrienne Rich who died in March 2012, at the age of 82. The analysis focuses on Rich’s complex  figurations of female subjectivity as well as on her nuanced positions in relation to the public role of the poet today. Rich’s attention to the political dimension did not exclude intimate reflections on personal relationships and on their modalities. In this respect her poetry is close to another important lesbian author, the poet laureate Coral Ann Duffy. In The World’s Wife (1999, Carol Ann Duffy presents thirty sketches of famed men from both history and mythology by their wives. Each wife extols or criticizes her own husband in a combination of sarcasm and sentimentalism, with peaks of  extreme bitterness and self-pity. Such singular and irreverent feminine versions show a series of references to the animal world. As a matter of fact, Duffy creates a downright vast and varied bestiary, which focuses on the problematic association between the female and the animal body. The aim of this essay is to explore the multiple possibilities of representation and placement of the human body in the space, through the lenses of ecocriticism and posthumanism.

Prediction of Chl-a concentrations in an eutrophic lake using ANN models with hybrid inputs

Science.gov (United States)

Aksoy, A.; Yuzugullu, O.

2017-12-01

Chlorophyll-a (Chl-a) concentrations in water bodies exhibit both spatial and temporal variations. As a result, frequent sampling is required with higher number of samples. This motivates the use of remote sensing as a monitoring tool. Yet, prediction performances of models that convert radiance values into Chl-a concentrations can be poor in shallow lakes. In this study, Chl-a concentrations in Lake Eymir, a shallow eutrophic lake in Ankara (Turkey), are determined using artificial neural network (ANN) models that use hybrid inputs composed of water quality and meteorological data as well as remotely sensed radiance values to improve prediction performance. Following a screening based on multi-collinearity and principal component analysis (PCA), dissolved-oxygen concentration (DO), pH, turbidity, and humidity were selected among several parameters as the constituents of the hybrid input dataset. Radiance values were obtained from QuickBird-2 satellite. Conversion of the hybrid input into Chl-a concentrations were studied for two different periods in the lake. ANN models were successful in predicting Chl-a concentrations. Yet, prediction performance declined for low Chl-a concentrations in the lake. In general, models with hybrid inputs were superior over the ones that solely used remotely sensed data.

Anne-Sylvie Catherin, Head of the Human Resources Department

CERN Multimedia

2009-01-01

Anne-Sylvie Catherin has been appointed Head of the Human Resources Department with effect from 1 August 2009. Mrs Catherin is a lawyer specialized in International Administration and joined CERN in 1996 as legal advisor within the Office of the HR Department Head. After having been promoted to the position of Group Leader responsible for social and statutory conditions in 2000, Mrs Catherin was appointed Deputy of the Head of the Human Resources Department and Group Leader responsible for Strategy, Management and Development from 2005 to date. Since 2005, she has also served as a member of CCP and TREF. In the execution of her mandate as Deputy HR Department Head, Mrs Catherin closely assisted the HR Department Head in the organization of the Department and in devising new HR policies and strategies. She played an instrumental role in the last five-yearly review and in the revision of the Staff Rules and Regulations.

Modeling of policies for reduction of GHG emissions in energy sector using ANN: case study-Croatia (EU).

Science.gov (United States)

Bolanča, Tomislav; Strahovnik, Tomislav; Ukić, Šime; Stankov, Mirjana Novak; Rogošić, Marko

2017-07-01

This study describes the development of tool for testing different policies for reduction of greenhouse gas (GHG) emissions in energy sector using artificial neural networks (ANNs). The case study of Croatia was elaborated. Two different energy consumption scenarios were used as a base for calculations and predictions of GHG emissions: the business as usual (BAU) scenario and sustainable scenario. Both of them are based on predicted energy consumption using different growth rates; the growth rates within the second scenario resulted from the implementation of corresponding energy efficiency measures in final energy consumption and increasing share of renewable energy sources. Both ANN architecture and training methodology were optimized to produce network that was able to successfully describe the existing data and to achieve reliable prediction of emissions in a forward time sense. The BAU scenario was found to produce continuously increasing emissions of all GHGs. The sustainable scenario was found to decrease the GHG emission levels of all gases with respect to BAU. The observed decrease was attributed to the group of measures termed the reduction of final energy consumption through energy efficiency measures.

Satellite image analysis and a hybrid ESSS/ANN model to forecast solar irradiance in the tropics

International Nuclear Information System (INIS)

Dong, Zibo; Yang, Dazhi; Reindl, Thomas; Walsh, Wilfred M.

2014-01-01

Highlights: • Satellite image analysis is performed and cloud cover index is classified using self-organizing maps (SOM). • The ESSS model is used to forecast cloud cover index. • Solar irradiance is estimated using multi-layer perceptron (MLP). • The proposed model shows better accuracy than other investigated models. - Abstract: We forecast hourly solar irradiance time series using satellite image analysis and a hybrid exponential smoothing state space (ESSS) model together with artificial neural networks (ANN). Since cloud cover is the major factor affecting solar irradiance, cloud detection and classification are crucial to forecast solar irradiance. Geostationary satellite images provide cloud information, allowing a cloud cover index to be derived and analysed using self-organizing maps (SOM). Owing to the stochastic nature of cloud generation in tropical regions, the ESSS model is used to forecast cloud cover index. Among different models applied in ANN, we favour the multi-layer perceptron (MLP) to derive solar irradiance based on the cloud cover index. This hybrid model has been used to forecast hourly solar irradiance in Singapore and the technique is found to outperform traditional forecasting models

Evaluation of Seasonal, ANN, and Hybrid Models in Modeling Urban Water Consumption A Case Study of Rash City

Directory of Open Access Journals (Sweden)

Seyed Nematollah Mousavi

2016-09-01

Full Text Available Forecasting future water consumption in cities to plan for the required capacities in urban water supply systems (including water transmission networks and water treatment facilities depends on the application of behavioral models of uban water consumption. Being located in the North-South corridor, Rasht City is assuming a new role to play in the national economy as a foreign trade center. It will, thus, be necessary to review its present urban infrastructure in order to draft the required infrastructural development plans for meeting the city’s future water demands. The three Seasonal Autoregressive Integrated Moving Average (SARIMA, Artificial Neural Network (ANN, and SARIMABP approaches were employed in present study to model and forecast Rasht urban water consumption using monthly time series for the period 2001‒2008 of urban water consumption in Rasht. The seasonal unit root test was applied to develop the relevant SARIMA model. Results showed that all the seasonal and non-seasonal unit roots are present in all the frequencies in the monthly time series for Rasht urban water consumption. Using a proper filter, the SAIMA patterns were estimated. In a second stage the SARIMA output was used to determine the ANN output and the hybrid SARIMABP structure was accordingly constructed. The values for Rasht urban water consumption predicted by the three models indicated the superiority of the SARIMABP hybrid model as evidenced by the forecast error index of 0.41% obtained for this model. The other two models of SARIMA and ANN were, however, found to yield acceptable results for urban water managers since the forecasting error recorded for them was below 1%.

Comparison Between Wind Power Prediction Models Based on Wavelet Decomposition with Least-Squares Support Vector Machine (LS-SVM and Artificial Neural Network (ANN

Directory of Open Access Journals (Sweden)

Maria Grazia De Giorgi

2014-08-01

Full Text Available A high penetration of wind energy into the electricity market requires a parallel development of efficient wind power forecasting models. Different hybrid forecasting methods were applied to wind power prediction, using historical data and numerical weather predictions (NWP. A comparative study was carried out for the prediction of the power production of a wind farm located in complex terrain. The performances of Least-Squares Support Vector Machine (LS-SVM with Wavelet Decomposition (WD were evaluated at different time horizons and compared to hybrid Artificial Neural Network (ANN-based methods. It is acknowledged that hybrid methods based on LS-SVM with WD mostly outperform other methods. A decomposition of the commonly known root mean square error was beneficial for a better understanding of the origin of the differences between prediction and measurement and to compare the accuracy of the different models. A sensitivity analysis was also carried out in order to underline the impact that each input had in the network training process for ANN. In the case of ANN with the WD technique, the sensitivity analysis was repeated on each component obtained by the decomposition.

Tandem Paul ja Anne Daniela Rodgers, Kaunase modernistid ja arenev Meiu Münt / Juta Kivimäe

Index Scriptorium Estoniae

Kivimäe, Juta, 1952-

2006-01-01

Kuni 23. IV Tartu Kunstimuuseumis avatud Paul ja Anne Daniela Rodgersi näitusest. 15. II-13. III Tartu kaheksas galeriis avatud Kaunase kunstnike näitusest, Arvidas Zhalpyse installatsioonist "Kõik toolist" ja Agne Jonkute maalist "Olematuse faktid" Tartu Kunstimajas. Kuni 25. III G-galeriis avatud Meiu Mündi näitusest "Päev on pime"

A soft computing scheme incorporating ANN and MOV energy in fault detection, classification and distance estimation of EHV transmission line with FSC.

Science.gov (United States)

Khadke, Piyush; Patne, Nita; Singh, Arvind; Shinde, Gulab

2016-01-01

In this article, a novel and accurate scheme for fault detection, classification and fault distance estimation for a fixed series compensated transmission line is proposed. The proposed scheme is based on artificial neural network (ANN) and metal oxide varistor (MOV) energy, employing Levenberg-Marquardt training algorithm. The novelty of this scheme is the use of MOV energy signals of fixed series capacitors (FSC) as input to train the ANN. Such approach has never been used in any earlier fault analysis algorithms in the last few decades. Proposed scheme uses only single end measurement energy signals of MOV in all the 3 phases over one cycle duration from the occurrence of a fault. Thereafter, these MOV energy signals are fed as input to ANN for fault distance estimation. Feasibility and reliability of the proposed scheme have been evaluated for all ten types of fault in test power system model at different fault inception angles over numerous fault locations. Real transmission system parameters of 3-phase 400 kV Wardha-Aurangabad transmission line (400 km) with 40 % FSC at Power Grid Wardha Substation, India is considered for this research. Extensive simulation experiments show that the proposed scheme provides quite accurate results which demonstrate complete protection scheme with high accuracy, simplicity and robustness.

Global Alliance'i president: harige ennast, sest kogemusest tänapäeval ei piisa / Anne Gregory ; intervjueerinud Annela Laaneots

Index Scriptorium Estoniae

Gregory, Anne

2013-01-01

Intervjuu ajakirja Kaja mõttekojas esinenud maailma suhtekorralduse ja kommunikatsioonijuhtimise organisatsioonide ühenduse Global Alliance presidendi Anne Gregoryga, kes annab nõu, mida kommunikatsioonijuht peaks tegema, et olla organisatsioonis hinnatud ning enda eesmärkidest Global Alliance'i presidendina

Performance measurement of plate fin heat exchanger by exploration: ANN, ANFIS, GA, and SA

Directory of Open Access Journals (Sweden)

A.K. Gupta

2017-01-01

Full Text Available An experimental work is conducted on counter flow plate fin compact heat exchanger using offset strip fin under different mass flow rates. The training, testing, and validation set of data has been collected by conducting experiments. Next, artificial neural network merged with Genetic Algorithm (GA utilized to measure the performance of plate-fin compact heat exchanger. The main aim of present research is to measure the performance of plate-fin compact heat exchanger and to provide full explanations. An artificial neural network predicted simulated data, which verified with experimental data under 10–20% error. Then, the authors examined two well-known global search techniques, simulated annealing and the genetic algorithm. The proposed genetic algorithm and Simulated Annealing (SA results have been summarized. The parameters are impartially important for good results. With the emergence of a new data-driven modeling technique, Neuro-fuzzy based systems are established in academic and practical applications. The neuro-fuzzy interference system (ANFIS has also been examined to undertake the problem related to plate-fin heat exchanger performance measurement under various parameters. Moreover, Parallel with ANFIS model and Artificial Neural Network (ANN model has been created with emphasizing the accuracy of the different techniques. A wide range of statistical indicators used to assess the performance of the models. Based on the comparison, it was revealed that technical ANFIS improve the accuracy of estimates in the small pool and tropical ANN.

Evaluation Of The Advanced Operating System Of The Ann Arbor Transportation Authority : Driver And Dispatcher Perceptions Of AATA'S Advanced Operating System

Science.gov (United States)

1999-01-01

In 1997, the Ann Arbor (Michigan) Transportation Authority began deploying advanced public transportation systems (APTS) technologies in its fixed route and paratransit operations. The project's concept is the integration of a range of such technolog...

Design of an Experiment to Measure ann Using 3H(γ, pn)n at HIγS★

Science.gov (United States)

Friesen, F. Q. L.; Ahmed, M. W.; Crowe, B. J.; Crowell, A. S.; Cumberbatch, L. C.; Fallin, B.; Han, Z.; Howell, C. R.; Malone, R. M.; Markoff, D.; Tornow, W.; Witała, H.

2016-03-01

We provide an update on the development of an experiment at TUNL for determining the 1S0 neutron-neutron (nn) scattering length (ann) from differential cross-section measurements of three-body photodisintegration of the triton. The experiment will be conducted using a linearly polarized gamma-ray beam at the High Intensity Gamma-ray Source (HIγS) and tritium gas contained in thin-walled cells. The main components of the planned experiment are a 230 Ci gas target system, a set of wire chambers and silicon strip detectors on each side of the beam axis, and an array of neutron detectors on each side beyond the silicon detectors. The protons emitted in the reaction are tracked in the wire chambers and their energy and position are measured in silicon strip detectors. The first iteration of the experiment will be simplified, making use of a collimator system, and silicon detectors to interrogate the main region of interest near 90° in the polar angle. Monte-Carlo simulations based on rigorous 3N calculations have been conducted to validate the sensitivity of the experimental setup to ann. This research supported in part by the DOE Office of Nuclear Physics Grant Number DE-FG02-97ER41033

Land Degradation Monitoring in the Ordos Plateau of China Using an Expert Knowledge and BP-ANN-Based Approach

Directory of Open Access Journals (Sweden)

Yaojie Yue

2016-11-01

Full Text Available Land degradation monitoring is of vital importance to provide scientific information for promoting sustainable land utilization. This paper presents an expert knowledge and BP-ANN-based approach to detect and monitor land degradation in an effort to overcome the deficiencies of image classification and vegetation index-based approaches. The proposed approach consists of three generic steps: (1 extraction of knowledge on the relationship between land degradation degree and predisposing factors, which are NDVI and albedo, from domain experts; (2 establishment of a land degradation detecting model based on the BP-ANN algorithm; and (3 land degradation dynamic analysis. A comprehensive analysis was conducted on the development of land degradation in the Ordos Plateau of China in 1990, 2000 and 2010. The results indicate that the proposed approach is reliable for monitoring land degradation, with an overall accuracy of 91.2%. From 1990–2010, a reverse trend of land degradation is observed in Ordos Plateau. Regions with relatively high land degradation dynamic were mostly located in the northeast of Ordos Plateau. Additionally, most of the regions have transferred from a hot spot of land degradation to a less changed area. It is suggested that land utilization optimization plays a key role for effective land degradation control. However, it should be highlighted that the goals of such strategies should aim at the main negative factors causing land degradation, and the land use type and its quantity must meet the demand of population and be reconciled with natural conditions. Results from this case study suggest that the expert knowledge and BP-ANN-based approach is effective in mapping land degradation.

Uhked naised / Kozik, Eerika; Tomingas, Triin; Sepp, Karin; Liik, Kadi; Kliimask, Katrin; Saunpere, Anne ; tekst Kärt Kross

Index Scriptorium Estoniae

2007-01-01

Mille üle oled enda juures tõeliselt uhke, mida võid enda kiituseks öelda? Küsimusele vastavad Starland Salongi omanik ja Loyd Tootmine OÜ osanik Eerika Kozik, psühholoog Triin Tomingas, Kontuur Leo Burnett projektidirektor Karin Sepp, Tallinna Ülikooli õppejõud Kadi Liik, AS Koolibri turundusjuht Katrin Kliimask ja eraettevõtja Anne Saunpere

Huviharidus ei ole ainult soe bussipeatus / Piret Hartman, Ardo Rohtla, Annely Köster ... [jt.] ; intervjueerinud Maris Hellrand

Index Scriptorium Estoniae

2016-01-01

Noorte huvitegevuse toetussüsteemi kontseptsioon toob järgmisel sügisel valdkonda lisaraha. Vestlusringis huvihariduse probleemide üle osalesid kultuuriministri nõunik Piret Hartman, haridus- ja teadusministeeriumi noorteosakonna asejuhataja Ardo Rohtla, Sally Stuudio juhataja Annely Köster, Eesti Muusikakoolide Liidu juhatuse esimees Kadri Leivategija, Rakvere abilinnapea Kairit Pihlak, Eesti Teadushuvihariduse Liidu juhatuse liige Heilo Altin ja MTÜ Loovkirjutamise Keskus juhatuse liige Katriin Fisch-Uibopuu

Baring Skills, Not Soul: Carol Ann Duffy’s Intertextual Games

Directory of Open Access Journals (Sweden)

Catherine LANONE

2008-10-01

Full Text Available Maîtrisant à merveille la contre-interpellation ludique dans The World’s Wife, Carol Ann Duffy  est réputée pour ses jeux intertextuels et ses réécritures féministes des grands mythes, donnant la parole aux figures féminines que l’histoire effaçait pour faire triompher le féminin et rire du masculin. Mais son recueil Rapture, publié en 2005, s’écarte radicalement du modèle féministe pour tenter une appropriation plus discrète de la tradition pétrarquisante de la poésie amoureuse. Resémiotisant les clichés, jouant sur une simplicité incantatoire, Duffy pratique ici l’écho plutôt que la réécriture, dans un dépouillement sensuel, explorant amour puis désamour au rythme d’une poésie qui emprunte au jazz ses variations fluides ou syncopées.

Assessing the long term impact of phosphorus fertilization on phosphorus loadings using AnnAGNPS.

Science.gov (United States)

Yuan, Yongping; Bingner, Ronald L; Locke, Martin A; Stafford, Jim; Theurer, Fred D

2011-06-01

High phosphorus (P) loss from agricultural fields has been an environmental concern because of potential water quality problems in streams and lakes. To better understand the process of P loss and evaluate the effects of different phosphorus fertilization rates on phosphorus losses, the USDA Annualized AGricultural Non-Point Source (AnnAGNPS) pollutant loading model was applied to the Ohio Upper Auglaize watershed, located in the southern portion of the Maumee River Basin. In this study, the AnnAGNPS model was calibrated using USGS monitored data; and then the effects of different phosphorus fertilization rates on phosphorus loadings were assessed. It was found that P loadings increase as fertilization rate increases, and long term higher P application would lead to much higher P loadings to the watershed outlet. The P loadings to the watershed outlet have a dramatic change after some time with higher P application rate. This dramatic change of P loading to the watershed outlet indicates that a "critical point" may exist in the soil at which soil P loss to water changes dramatically. Simulations with different initial soil P contents showed that the higher the initial soil P content is, the less time it takes to reach the "critical point" where P loadings to the watershed outlet increases dramatically. More research needs to be done to understand the processes involved in the transfer of P between the various stable, active and labile states in the soil to ensure that the model simulations are accurate. This finding may be useful in setting up future P application and management guidelines.

Vähem formaalsust, rohkem julgust ja enesekriitikat! / Marko Mäetamm, Anneli Porri, Tiit Pääsuke ... [jt.] ; intervjueerinud Reet Varblane

Index Scriptorium Estoniae

2009-01-01

Kunstiõpetamise võimalikkuse ja vajalikkuse üle vestlesid Eesti Kunstiakadeemia vabade kunstide teaduskonna dekaan Marko Mäetamm, fotokunsti osakonna õppejõud Anneli Porri, emeriitprofessor Tiit Pääsuke, prorektor Liina Siib, graafilise disaini osakonna õppejõud Indrek Sirkel ja ehtekunsti osakonna õppejõud Tanel Veenre

Predicting fuelwood prices in Greece with the use of ARIMA models, artificial neural networks and a hybrid ARIMA-ANN model

International Nuclear Information System (INIS)

Koutroumanidis, Theodoros; Ioannou, Konstantinos; Arabatzis, Garyfallos

2009-01-01

Throughout history, energy resources have acquired a strategic significance for the economic growth and social welfare of any country. The large-scale oil crisis of 1973 coupled with various environmental protection issues, have led many countries to look for new, alternative energy sources. Biomass and fuelwood in particular, constitutes a major renewable energy source (RES) that can make a significant contribution, as a substitute for oil. This paper initially provides a description of the contribution of renewable energy sources to the production of electricity, and also examines the role of forests in the production of fuelwood in Greece. Following this, autoregressive integrated moving average (ARIMA) models, artificial neural networks (ANN) and a hybrid model are used to predict the future selling prices of the fuelwood (from broadleaved and coniferous species) produced by Greek state forest farms. The use of the ARIMA-ANN hybrid model provided the optimum prediction results, thus enabling decision-makers to proceed with a more rational planning for the production and fuelwood market. (author)

The Sacred Object: Anne Carson and Simone Weil

Directory of Open Access Journals (Sweden)

Elizabeth Coles

2014-01-01

Full Text Available Este artículo examina la relación entre la lectura crítica y el objeto crítico en laobra de la poeta y ensayista canadiense Anne Carson, principalmente los textosque surgen de su largo acercamiento a los escritos de la filósofa y mística cristiana Simone Weil. Mi lectura de Carson se centra en los deseos conflictuales de la relación crítica que se encuentran confesados y no confesados en su obra, y en las formas de intimidad que sus respuestas logran con la obra de Weil. Agudizadas por su encuentro con el pensamiento y la fe de Weil, las preguntasde Carson para la crítica ―sobre sus propios objetos y la resistencia de ellos ala interpretación, sobre la distinción entre crítica y literatura, y sobre la vanidadde la estética de la crítica misma― encuentran su articulación en varios génerosde la escritura: estudiando la complicidad de cada uno de estos con Weil, yla capacidad de cada uno a radicalizar sus cuestiones, llego a unas conclusionspropias para la crítica literaria.

Kaasaegne kunstiõpetus, uks praegusesse ülevisualiseeritud maailma / Tõnu Talve, Anne Susanna Lindström ; interv. Reet Varblane

Index Scriptorium Estoniae

Talve, Tõnu

2007-01-01

Soome kunstiõpetaja, Eesti Kunstiakadeemia õpetajate koolituskeskuse dotsent Anne Susanna Lindström ja Keila gümnaasiumi kunstiõpetaja Tõnu Talve Heidelbergi ja Karlsruhe pedagoogikaülikooli organiseeritud kunstiõpetajate maailmakongressist "Horisondid 2007" ning kunstiõpetusest. A. S Lindström tutvustas kongressil Eesti ja Soome kunstiõpetuse ainekavade võrdlev-ajaloolist uuringut ja T. Talve esitles videofilmi "Fragile kunstitund 3"

Vampiros humanizados: análise da obra Interview with the vampire de Anne Rice

OpenAIRE

Patricia Hradec

2014-01-01

Esta dissertação tem por objetivo analisar o romance Interview with the Vampire de Anne Rice que é o primeiro livro dos dez que constituem suas Crônicas Vampirescas . Pretende-se com esta pesquisa demonstrar como os vampiros apresentados por Rice são humanizados. Inicia-se com um estudo histórico sobre os vampiros, tanto lendários quanto literários, depois há um estudo sobre a vida e obra da escritora norte-americana bem como um levantamento das diferenças entre os vampiros de Rice e outros ...

ANN Synthesis Model of Single-Feed Corner-Truncated Circularly Polarized Microstrip Antenna with an Air Gap for Wideband Applications

Directory of Open Access Journals (Sweden)

Zhongbao Wang

2014-01-01

Full Text Available A computer-aided design model based on the artificial neural network (ANN is proposed to directly obtain patch physical dimensions of the single-feed corner-truncated circularly polarized microstrip antenna (CPMA with an air gap for wideband applications. To take account of the effect of the air gap, an equivalent relative permittivity is introduced and adopted to calculate the resonant frequency and Q-factor of square microstrip antennas for obtaining the training data sets. ANN architectures using multilayered perceptrons (MLPs and radial basis function networks (RBFNs are compared. Also, six learning algorithms are used to train the MLPs for comparison. It is found that MLPs trained with the Levenberg-Marquardt (LM algorithm are better than RBFNs for the synthesis of the CPMA. An accurate model is achieved by using an MLP with three hidden layers. The model is validated by the electromagnetic simulation and measurements. It is enormously useful to antenna engineers for facilitating the design of the single-feed CPMA with an air gap.

Narratifs Médiatiques sur la relation entre le corps et les jeux olympiques dans les années 1890 et 1900

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Fausto Amaro

2016-09-01

Full Text Available Les jeux olympiques se présentées devenus l’habitant de Rio de Janeiro des années 1890 et 1900 comme quelque chose au-delà du sport. Cirque, théâtre et cinéma étaient espaces culturels où ces événements pourraient être assistés, comme les journaux annonçaient. Les Jeux Olympiques du Comité International Olympique ont également été publiés, mais rivalisaient à l’attention du lecteur de Rio avec des jeux non officiels, tels que ceux qui sont détenus à Montevideo en l’année 1907. Compris ce contexte, je présente dans cet article quelques questions concernant le corps idéal dans cette période et son dialogue avec la nouveauté représenté par les jeux olympiques.

Master-Leader-Slave Cuckoo Search with Parameter Control for ANN Optimization and Its Real-World Application to Water Quality Prediction.

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Najmeh Sadat Jaddi

Full Text Available Artificial neural networks (ANNs have been employed to solve a broad variety of tasks. The selection of an ANN model with appropriate weights is important in achieving accurate results. This paper presents an optimization strategy for ANN model selection based on the cuckoo search (CS algorithm, which is rooted in the obligate brood parasitic actions of some cuckoo species. In order to enhance the convergence ability of basic CS, some modifications are proposed. The fraction Pa of the n nests replaced by new nests is a fixed parameter in basic CS. As the selection of Pa is a challenging issue and has a direct effect on exploration and therefore on convergence ability, in this work the Pa is set to a maximum value at initialization to achieve more exploration in early iterations and it is decreased during the search to achieve more exploitation in later iterations until it reaches the minimum value in the final iteration. In addition, a novel master-leader-slave multi-population strategy is used where the slaves employ the best fitness function among all slaves, which is selected by the leader under a certain condition. This fitness function is used for subsequent Lévy flights. In each iteration a copy of the best solution of each slave is migrated to the master and then the best solution is found by the master. The method is tested on benchmark classification and time series prediction problems and the statistical analysis proves the ability of the method. This method is also applied to a real-world water quality prediction problem with promising results.

Master-Leader-Slave Cuckoo Search with Parameter Control for ANN Optimization and Its Real-World Application to Water Quality Prediction.

Science.gov (United States)

Jaddi, Najmeh Sadat; Abdullah, Salwani; Abdul Malek, Marlinda

2017-01-01

Artificial neural networks (ANNs) have been employed to solve a broad variety of tasks. The selection of an ANN model with appropriate weights is important in achieving accurate results. This paper presents an optimization strategy for ANN model selection based on the cuckoo search (CS) algorithm, which is rooted in the obligate brood parasitic actions of some cuckoo species. In order to enhance the convergence ability of basic CS, some modifications are proposed. The fraction Pa of the n nests replaced by new nests is a fixed parameter in basic CS. As the selection of Pa is a challenging issue and has a direct effect on exploration and therefore on convergence ability, in this work the Pa is set to a maximum value at initialization to achieve more exploration in early iterations and it is decreased during the search to achieve more exploitation in later iterations until it reaches the minimum value in the final iteration. In addition, a novel master-leader-slave multi-population strategy is used where the slaves employ the best fitness function among all slaves, which is selected by the leader under a certain condition. This fitness function is used for subsequent Lévy flights. In each iteration a copy of the best solution of each slave is migrated to the master and then the best solution is found by the master. The method is tested on benchmark classification and time series prediction problems and the statistical analysis proves the ability of the method. This method is also applied to a real-world water quality prediction problem with promising results.

Determining degree of roasting in cocoa beans by artificial neural network (ANN)-based electronic nose system and gas chromatography/mass spectrometry (GC/MS).

Science.gov (United States)

Tan, Juzhong; Kerr, William L

2018-08-01

Roasting is a critical step in chocolate processing, where moisture content is decreased and unique flavors and texture are developed. The determination of the degree of roasting in cocoa beans is important to ensure the quality of chocolate. Determining the degree of roasting relies on human specialists or sophisticated chemical analyses that are inaccessible to small manufacturers and farmers. In this study, an electronic nose system was constructed consisting of an array of gas sensors and used to detect volatiles emanating from cocoa beans roasted for 0, 20, 30 and 40 min. The several signals were used to train a three-layer artificial neural network (ANN). Headspace samples were also analyzed by gas chromatography/mass spectrometry (GC/MS), with 23 select volatiles used to train a separate ANN. Both ANNs were used to predict the degree of roasting of cocoa beans. The electronic nose had a prediction accuracy of 94.4% using signals from sensors TGS 813, 826, 822, 830, 830, 2620, 2602 and 2610. In comparison, the GC/MS predicted the degree of roasting with an accuracy of 95.8%. The electronic nose system is able to predict the extent of roasting, as well as a more sophisticated approach using GC/MS. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Miks lootusrikkalt tehtud plaanid nurjuvad? / Anneli Lorenz, Jakob Kübarsepp, Kätlin Tiigi, Mikk Kasesalk ; küsitlenud Anna-Liisa Mets

Index Scriptorium Estoniae

2014-01-01

Õpingute poolelijätmise põhjusi analüüsivad Eesti Maaülikooli õppeosakonna juhataja Anneli Lorenz, TTÜ õppeprorektor Jakob Kübarsepp, TTÜ Üliõpilaskonna juhatuse liige Kätlin Tiigi ja Tallinn Ülikooli karjäärinõustaja Mikk Kasesalk

News from HR: a word from Anne-Sylvie Catherin

CERN Multimedia

2016-01-01

Anne-Sylvie Catherin, head of HR Department, looks back over her years at CERN before taking up her new position at the European Central Bank.   At the end of July, I will be leaving CERN on a special leave of absence to take up a new position at the European Central Bank. This is a new chapter in my career, in a new context with its own challenges, and as I prepare for it, I would like to take a little time to look back over my years at CERN and share with you the enriching journey it has been, both for myself and for HR. It has always been my strong belief that any organisation’s greatest asset is its people. When an HR professional believes that, it’s only a short step to the conclusion that the best way to nurture those people is by adopting a professional approach to HR. In this respect, I arrived at a very fortuitous time. Enrico Chiaveri was head of HR and, although his background is in physics, we shared that same conviction. Enrico was the icebreaker in driving change, a...

Ali, Cunich: Halley's Churches: Halley and the London Queen Anne Churches

Science.gov (United States)

Ali, Jason R.; Cunich, Peter

2005-04-01

Edmond Halley's enormous contribution to science has received much attention. New research adds an intriguing chapter to his story and concerns his hitherto unexplored association with the baroque architectural visionary Nicholas Hawksmoor, and some important Temple-inspired churches that were built in London in the early 1700s. We argue that Christchurch Spitalfields and St Anne's Limehouse, which were both started in the summer of 1714, were aligned exactly eastwards using ``corrected'' magnetic-compass bearings and that Halley influenced or aided Hawksmoor. By this time the men had probably known each other for 30 years and had recently worked together on the Clarendon Building in Oxford. Despite there being more than 1500 years of Chinese and about 500 years of Western compass technology at the time, these probably represent the first constructions planned using a modern-day ``scientific'' technique. The research also throws light on Halley's contended religious position.

Optimization of microwave-assisted extraction of total extract, stevioside and rebaudioside-A from Stevia rebaudiana (Bertoni) leaves, using response surface methodology (RSM) and artificial neural network (ANN) modelling.

Science.gov (United States)

Ameer, Kashif; Bae, Seong-Woo; Jo, Yunhee; Lee, Hyun-Gyu; Ameer, Asif; Kwon, Joong-Ho

2017-08-15

Stevia rebaudiana (Bertoni) consists of stevioside and rebaudioside-A (Reb-A). We compared response surface methodology (RSM) and artificial neural network (ANN) modelling for their estimation and predictive capabilities in building effective models with maximum responses. A 5-level 3-factor central composite design was used to optimize microwave-assisted extraction (MAE) to obtain maximum yield of target responses as a function of extraction time (X 1 : 1-5min), ethanol concentration, (X 2 : 0-100%) and microwave power (X 3 : 40-200W). Maximum values of the three output parameters: 7.67% total extract yield, 19.58mg/g stevioside yield, and 15.3mg/g Reb-A yield, were obtained under optimum extraction conditions of 4min X 1 , 75% X 2 , and 160W X 3 . The ANN model demonstrated higher efficiency than did the RSM model. Hence, RSM can demonstrate interaction effects of inherent MAE parameters on target responses, whereas ANN can reliably model the MAE process with better predictive and estimation capabilities. Copyright © 2017. Published by Elsevier Ltd.

Application of Ann for Prediction of Co2+, Cd2+ and Zn2+ Ions Uptake by R. Squarrosus Biomass in Single and Binary Mixtures

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Nemeček Peter

2014-06-01

Full Text Available Discharge of heavy metals into aquatic ecosystems has become a matter of concern over the last few decades. The search for new technologies involving the removal of toxic metals from wastewaters has directed the attention to biosorption, based on metal binding capacities of various biological materials. Degree of sorbent affinity for the sorbate determines its distribution between the solid and liquid phases and this behavior can be described by adsorption isotherm models (Freundlich and Langmuir isotherm models representing the classical approach. In this study, an artificial neural network (ANN was proposed to predict the sorption efficiency in single and binary component solutions of Cd2+, Zn2+ and Co2+ ions by biosorbent prepared from biomass of moss Rhytidiadelphus squarrosus. Calculated non-linear ANN models presented in this paper are advantageous for its capability of successful prediction, which can be problematic in the case of classical isotherm approach. Quality of prediction was proved by strong agreement between calculated and measured data, expressed by the coefficient of determination in both, single and binary metal systems (R2= 0.996 and R2= 0.987, respectively. Another important benefit of these models is necessity of significantly smaller amount of data (about 50% for the model calculation. Also, it is possible to calculate Qeq for all studied metals by one combined ANN model, which totally overcomes a classical isotherm approach

Preliminary Study on Application of Artificial Neural Networks (ANN) for Determining the Peroxide Value of Three Commercial Palm Oil Based FTIR Spectrum)

International Nuclear Information System (INIS)

Azwan Mat Lazim; Musa Ahmad; Zuriati Zakaria; Mohd Suzeren Jamil; Suria Ramli; Faiz Zainuddin; Mohd Nasir Taib; Mat Nasir Mat Arip

2013-01-01

Peroxide value is one of the measurements that being used to determine the peroxide in oil samples produce from the peroxide compound and hydroperoxide group at the primary level of lipid oxidation. In this study, 3 commercial palm cooking oils were selected and labeled as A, B and C. Two different conditions were applied to the samples. First, the oil sample was exposed to the air for three months (labeled as A) while samples B and C were used for frying for many times. Two inputs from FTIR spectra (3444 cm -1 and 3450 cm -1 ) were chosen for the ANN training. The suitable architecture for this training is 2:20:1. The prediction made by ANN was very accurate and compatible to the result which obtained from the standard method. A low average error (0.48) was obtained when the hidden neuron (20) and the epochs (300) were used. (author)

Modeling and Investigation of the Wear Resistance of Salt Bath Nitrided Aisi 4140 via ANN

Science.gov (United States)

Ekinci, Şerafettin; Akdemir, Ahmet; Kahramanli, Humar

2013-05-01

Nitriding is usually used to improve the surface properties of steel materials. In this way, the wear resistance of steels is improved. We conducted a series of studies in order to investigate the microstructural, mechanical and tribological properties of salt bath nitrided AISI 4140 steel. The present study has two parts. For the first phase, the tribological behavior of the AISI 4140 steel which was nitrided in sulfinuz salt bath (SBN) was compared to the behavior of the same steel which was untreated. After surface characterization using metallography, microhardness and sliding wear tests were performed on a block-on-cylinder machine in which carbonized AISI 52100 steel discs were used as the counter face. For the examined AISI 4140 steel samples with and without surface treatment, the evolution of both the friction coefficient and of the wear behavior were determined under various loads, at different sliding velocities and a total sliding distance of 1000 m. The test results showed that wear resistance increased with the nitriding process, friction coefficient decreased due to the sulfur in salt bath and friction coefficient depended systematically on surface hardness. For the second part of this study, four artificial neural network (ANN) models were designed to predict the weight loss and friction coefficient of the nitrided and unnitrided AISI 4140 steel. Load, velocity and sliding distance were used as input. Back-propagation algorithm was chosen for training the ANN. Statistical measurements of R2, MAE and RMSE were employed to evaluate the success of the systems. The results showed that all the systems produced successful results.

Statistical analysis and ANN modeling for predicting hydrological extremes under climate change scenarios: the example of a small Mediterranean agro-watershed.

Science.gov (United States)

Kourgialas, Nektarios N; Dokou, Zoi; Karatzas, George P

2015-05-01

The purpose of this study was to create a modeling management tool for the simulation of extreme flow events under current and future climatic conditions. This tool is a combination of different components and can be applied in complex hydrogeological river basins, where frequent flood and drought phenomena occur. The first component is the statistical analysis of the available hydro-meteorological data. Specifically, principal components analysis was performed in order to quantify the importance of the hydro-meteorological parameters that affect the generation of extreme events. The second component is a prediction-forecasting artificial neural network (ANN) model that simulates, accurately and efficiently, river flow on an hourly basis. This model is based on a methodology that attempts to resolve a very difficult problem related to the accurate estimation of extreme flows. For this purpose, the available measurements (5 years of hourly data) were divided in two subsets: one for the dry and one for the wet periods of the hydrological year. This way, two ANNs were created, trained, tested and validated for a complex Mediterranean river basin in Crete, Greece. As part of the second management component a statistical downscaling tool was used for the creation of meteorological data according to the higher and lower emission climate change scenarios A2 and B1. These data are used as input in the ANN for the forecasting of river flow for the next two decades. The final component is the application of a meteorological index on the measured and forecasted precipitation and flow data, in order to assess the severity and duration of extreme events. Copyright © 2015 Elsevier Ltd. All rights reserved.

Prediction ofWater Quality Parameters (NO3, CL in Karaj Riverby Usinga Combinationof Wavelet Neural Network, ANN and MLRModels

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T. Rajaee

2016-10-01

Full Text Available IntroductionThe water quality is an issue of ongoing concern. Evaluation of the quantity and quality of running waters is considerable in hydro-environmental management.The prediction and control of the quality of Karaj river water, as one of the important needed water supply sources of Tehran, possesses great importance. In this study, Performance of Artificial Neural Network (ANN, Wavelet Neural Network combination (WANN and multi linear regression (MLR models, to predict next month the Nitrate (NO3 and Chloride (CL ions of "gate ofBylaqan sluice" station located in Karaj River has been evaluated. Materials and MethodsIn this research two separate ANN models for prediction of NO3 and CL has been expanded. Each one of the parameters for prediction (NO3 / CL has been put related to the past amounts of the same time series (NO3 / CL and its amounts of Q in past months.From astatisticalperiod of10yearswas usedforthe input of the models. Hence 80% of entire data from (96 initial months of data as training set, next 10% of data (12 months and 10% of the end of time series (terminal 12 months were considered as for validation and test of the models, respectively. In WANNcombination model, the real monthly observed time series of river discharge (Q and mentioned qualityparameters(NO3 / CL were decomposed to some sub-time series at different levels by wavelet analysis.Then the decomposed quality parameters to predict and Q time series were used at different levels as inputs to the ANN technique for predicting one-step-ahead Nitrate and Chloride. These time series play various roles in the original time series and the behavior of each is distinct, so the contribution to the original time series varies from each other. In addition, prediction of high NO3 and CL values greater than mean of data that have great importancewere investigated by the models. The capability of the models was evaluated by Coefficient of Efficiency (E and the Root Mean Square

Prediction of GWL with the help of GRACE TWS for unevenly spaced time series data in India : Analysis of comparative performances of SVR, ANN and LRM

Science.gov (United States)

Mukherjee, Amritendu; Ramachandran, Parthasarathy

2018-03-01

Prediction of Ground Water Level (GWL) is extremely important for sustainable use and management of ground water resource. The motivations for this work is to understand the relationship between Gravity Recovery and Climate Experiment (GRACE) derived terrestrial water change (ΔTWS) data and GWL, so that ΔTWS could be used as a proxy measurement for GWL. In our study, we have selected five observation wells from different geographic regions in India. The datasets are unevenly spaced time series data which restricts us from applying standard time series methodologies and therefore in order to model and predict GWL with the help of ΔTWS, we have built Linear Regression Model (LRM), Support Vector Regression (SVR) and Artificial Neural Network (ANN). Comparative performances of LRM, SVR and ANN have been evaluated with the help of correlation coefficient (ρ) and Root Mean Square Error (RMSE) between the actual and fitted (for training dataset) or predicted (for test dataset) values of GWL. It has been observed in our study that ΔTWS is highly significant variable to model GWL and the amount of total variations in GWL that could be explained with the help of ΔTWS varies from 36.48% to 74.28% (0.3648 ⩽R2 ⩽ 0.7428) . We have found that for the model GWL ∼ Δ TWS, for both training and test dataset, performances of SVR and ANN are better than that of LRM in terms of ρ and RMSE. It also has been found in our study that with the inclusion of meteorological variables along with ΔTWS as input parameters to model GWL, the performance of SVR improves and it performs better than ANN. These results imply that for modelling irregular time series GWL data, ΔTWS could be very useful.

Comparative ANNs with Different Input Layers and GA-PLS Study for Simultaneous Spectrofluorimetric Determination of Melatonin and Pyridoxine HCl in the Presence of Melatonin’s Main Impurity

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Amer M. Alanazi

2013-01-01

Full Text Available Melatonin (MLT has many health implications, therefore it is important to develop specific analytical methods for the determination of MLT in the presence of its main impurity, N-{2-[1-({3-[2-(acetylaminoethyl]-5-methoxy-1H-indol-2-yl}methyl-5-methoxy-1H-indol-3-yl]ethyl}acetaamide (DMLT and pyridoxine HCl (PNH as a co-formulated drug. This work describes simple, sensitive, and reliable four multivariate calibration methods, namely artificial neural network preceded by genetic algorithm (GA-ANN, principal component analysis (PCA-ANN and wavelet transform procedures (WT-ANN as well as partial least squares preceded by genetic algorithm (GA-PLS for the spectrofluorimetric determination of MLT and PNH in the presence of DMLT. Analytical performance of the proposed methods was statistically validated with respect to linearity, accuracy, precision and specificity. The proposed methods were successfully applied for the assay of MLT in laboratory prepared mixtures containing up to 15% of DMLT and in commercial MLT tablets with recoveries of no less than 99.00%. No interference was observed from common pharmaceutical additives and the results compared favorably with those obtained by a reference method.

Reliable and accurate point-based prediction of cumulative infiltration using soil readily available characteristics: A comparison between GMDH, ANN, and MLR

Science.gov (United States)

Rahmati, Mehdi

2017-08-01

Developing accurate and reliable pedo-transfer functions (PTFs) to predict soil non-readily available characteristics is one of the most concerned topic in soil science and selecting more appropriate predictors is a crucial factor in PTFs' development. Group method of data handling (GMDH), which finds an approximate relationship between a set of input and output variables, not only provide an explicit procedure to select the most essential PTF input variables, but also results in more accurate and reliable estimates than other mostly applied methodologies. Therefore, the current research was aimed to apply GMDH in comparison with multivariate linear regression (MLR) and artificial neural network (ANN) to develop several PTFs to predict soil cumulative infiltration point-basely at specific time intervals (0.5-45 min) using soil readily available characteristics (RACs). In this regard, soil infiltration curves as well as several soil RACs including soil primary particles (clay (CC), silt (Si), and sand (Sa)), saturated hydraulic conductivity (Ks), bulk (Db) and particle (Dp) densities, organic carbon (OC), wet-aggregate stability (WAS), electrical conductivity (EC), and soil antecedent (θi) and field saturated (θfs) water contents were measured at 134 different points in Lighvan watershed, northwest of Iran. Then, applying GMDH, MLR, and ANN methodologies, several PTFs have been developed to predict cumulative infiltrations using two sets of selected soil RACs including and excluding Ks. According to the test data, results showed that developed PTFs by GMDH and MLR procedures using all soil RACs including Ks resulted in more accurate (with E values of 0.673-0.963) and reliable (with CV values lower than 11 percent) predictions of cumulative infiltrations at different specific time steps. In contrast, ANN procedure had lower accuracy (with E values of 0.356-0.890) and reliability (with CV values up to 50 percent) compared to GMDH and MLR. The results also revealed

Applying of the Artificial Neural Networks (ANN) to Identify and Characterize Sweet Spots in Shale Gas Formations

Science.gov (United States)

Puskarczyk, Edyta

2018-03-01

The main goal of the study was to enhance and improve information about the Ordovician and Silurian gas-saturated shale formations. Author focused on: firstly, identification of the shale gas formations, especially the sweet spots horizons, secondly, classification and thirdly, the accurate characterization of divisional intervals. Data set comprised of standard well logs from the selected well. Shale formations are represented mainly by claystones, siltstones, and mudstones. The formations are also partially rich in organic matter. During the calculations, information about lithology of stratigraphy weren't taken into account. In the analysis, selforganizing neural network - Kohonen Algorithm (ANN) was used for sweet spots identification. Different networks and different software were tested and the best network was used for application and interpretation. As a results of Kohonen networks, groups corresponding to the gas-bearing intervals were found. The analysis showed diversification between gas-bearing formations and surrounding beds. It is also shown that internal diversification in sweet spots is present. Kohonen algorithm was also used for geological interpretation of well log data and electrofacies prediction. Reliable characteristic into groups shows that Ja Mb and Sa Fm which are usually treated as potential sweet spots only partially have good reservoir conditions. It is concluded that ANN appears to be useful and quick tool for preliminary classification of members and sweet spots identification.

Ferréol Gilles, Mamontoff Anne-Marie, ss. Dir., Tourisme et sociétés

Directory of Open Access Journals (Sweden)

Régis Malige

2010-10-01

Full Text Available Le colloque international et pluridisciplinaire organisé en octobre 2008, à l’initiative de l’UFR “Sports, tourisme et hôtellerie” de l’université de Perpignan Via Domitia et du laboratoire de socio-anthropologie (LASA de l’université de Franche-Comté, s’est intéressé aux relations unissant tourisme, loisirs et sociétés. Coordonné par Gilles Ferréol assisté d’Anne-Marie Mamontoff, l’ouvrage, rassemblant des participants appartenant à diverses institutions académiques, regroupe une douzaine d...

Evaluation Of The Advanced Operating System Of The Ann Arbor Transportation Authority : Cost Study : Before, During And After AOS Implementation (October 1996-May 1999)

Science.gov (United States)

1999-01-01

In 1997, the Ann Arbor (Michigan) Transportation Authority (AATA) began deploying advanced public transportation systems (APTS) technologies in its fixed route and paratransit operations. The project's concept is the integration of a range of such te...

Continental visions: Ann Seidman, Reginald H. Green and the economics of African unity in 1960s Ghana

OpenAIRE

Serra, Gerardo

2014-01-01

The paper presents the history of the contribution of two American economists to a radical cause: the establishment of a socialist and politically united Africa. The setting is 1960s Ghana which under Kwame Nkrumah, the man who led the country to independence from British colonial rule, emerged as the epicentre of this Pan-African vision. Ann Seidman and Reginald H. Green became, as members of the research team on 'The Economics of African Unity' established at the University of Ghana in 1963...

A Comparison of SWAT and ANN Models for Daily Runoff Simulation in Different Climatic Zones of Peninsular Spain

OpenAIRE

Patricia Jimeno-Sáez; Javier Senent-Aparicio; Julio Pérez-Sánchez; David Pulido-Velazquez

2018-01-01

Streamflow data are of prime importance to water-resources planning and management, and the accuracy of their estimation is very important for decision making. The Soil and Water Assessment Tool (SWAT) and Artificial Neural Network (ANN) models have been evaluated and compared to find a method to improve streamflow estimation. For a more complete evaluation, the accuracy and ability of these streamflow estimation models was also established separately based on their performance during differe...

Daily reservoir inflow forecasting combining QPF into ANNs model

Science.gov (United States)

Zhang, Jun; Cheng, Chun-Tian; Liao, Sheng-Li; Wu, Xin-Yu; Shen, Jian-Jian

2009-01-01

Daily reservoir inflow predictions with lead-times of several days are essential to the operational planning and scheduling of hydroelectric power system. The demand for quantitative precipitation forecasting (QPF) is increasing in hydropower operation with the dramatic advances in the numerical weather prediction (NWP) models. This paper presents a simple and an effective algorithm for daily reservoir inflow predictions which solicits the observed precipitation, forecasted precipitation from QPF as predictors and discharges in following 1 to 6 days as predicted targets for multilayer perceptron artificial neural networks (MLP-ANNs) modeling. An improved error back-propagation algorithm with self-adaptive learning rate and self-adaptive momentum coefficient is used to make the supervised training procedure more efficient in both time saving and search optimization. Several commonly used error measures are employed to evaluate the performance of the proposed model and the results, compared with that of ARIMA model, show that the proposed model is capable of obtaining satisfactory forecasting not only in goodness of fit but also in generalization. Furthermore, the presented algorithm is integrated into a practical software system which has been severed for daily inflow predictions with lead-times varying from 1 to 6 days of more than twenty reservoirs operated by the Fujian Province Grid Company, China.

An Experimental Investigation into the Optimal Processing Conditions for the CO2 Laser Cladding of 20 MnCr5 Steel Using Taguchi Method and ANN

Science.gov (United States)

Mondal, Subrata; Bandyopadhyay, Asish.; Pal, Pradip Kumar

2010-10-01

This paper presents the prediction and evaluation of laser clad profile formed by means of CO2 laser applying Taguchi method and the artificial neural network (ANN). Laser cladding is one of the surface modifying technologies in which the desired surface characteristics of any component can be achieved such as good corrosion resistance, wear resistance and hardness etc. Laser is used as a heat source to melt the anti-corrosive powder of Inconel-625 (Super Alloy) to give a coating on 20 MnCr5 substrate. The parametric study of this technique is also attempted here. The data obtained from experiments have been used to develop the linear regression equation and then to develop the neural network model. Moreover, the data obtained from regression equations have also been used as supporting data to train the neural network. The artificial neural network (ANN) is used to establish the relationship between the input/output parameters of the process. The established ANN model is then indirectly integrated with the optimization technique. It has been seen that the developed neural network model shows a good degree of approximation with experimental data. In order to obtain the combination of process parameters such as laser power, scan speed and powder feed rate for which the output parameters become optimum, the experimental data have been used to develop the response surfaces.

An experimental study on the geochemical behavior of highly siderophile elements (HSE) and metalloids (As, Se, Sb, Te, Bi) in a mss-iss-pyrite system at 650 °C: A possible magmatic origin for Co-HSE-bearing pyrite and the role of metalloid-rich phases in the fractionation of HSE

Science.gov (United States)

Cafagna, Fabio; Jugo, Pedro J.

2016-04-01

Pyrite, the most abundant sulfide in the Earth's crust, is an accessory mineral in several magmatic sulfide deposits. Although most pyrite is hydrothermal, previous experimental studies have shown that pyrite can also have a primary magmatic origin, by exsolving from monosulfide solid solution (mss) during cooling of a sulfide melt, if sulfur fugacity is sufficiently high. Pyrite from some localities has significant amounts of Co, and complex zonation in some low-melting-point chalcophile elements (LMCE), such as As, Se, Sb, Te, Bi (henceforth referred to as metalloids) and some platinum-group elements (PGE: Ru, Rh, Pd, Os, Ir, Pt). However, the origin of such pyrite and the causes of zonation are not clear. Because the distribution of some of these elements is heterogeneous and seems to be developed in concentric zones, the zonation has been interpreted to represent growth stages, some of them secondary and caused partly by hydrothermal fluids. Better constraints on the origin of Co-PGE-bearing pyrite could help unravel the geochemical processes affecting the sulfide assemblages in which it is found; thus, an experimental study was undertaken to characterize pyrite formation in magmatic sulfide environments and its relationship with metalloids and highly siderophile elements (HSE: PGE, Re, Au). Natural pyrrhotite, chalcopyrite, pentlandite and elemental S were mixed and doped with approximately 50 ppm of each HSE. A mixture of metalloids was added at 0.2 wt.% or 3 wt.% to aliquots of sulfide mixtures. Starting materials were sealed in evacuated silica tubes and fused at 1200 °C. The temperature was subsequently reduced to 750 °C (at 60 °C/h), then to 650 °C (at 0.5 °C/h) to produce relatively large euhedral pyrite crystals, then quenched. The experiments were analyzed using reflected light, SEM, EPMA and LA-ICP-MS. Experimental products contained euhedral pyrite, mss, intermediate solid solution (iss) and metalloid-rich phases, interpreted as quench product

ERTS data user no. 119: Effective use of ERTS multisensor data in the Great Plains. ERTS-1 MSS imagery: A tool for identifying soil associations

Science.gov (United States)

Myers, V. I. (Principal Investigator); Westin, F. C.

1973-01-01

The author has identified the following significant results. Soil association maps show the spatial relationships of land units developed in unique climatic, geologic, and topographic environments, and having characteristic slopes, soil depths, textures, available water capacities, permeabilities, and the like. ERTS-1 imagery was found to be a useful tool in the identification of soil associations since it provides a synoptic view of an 8 million acre scene, which is large enough so that the effect can be seen on soils of climate, topography, and geology. A regional view also allows soil associations to be observed over most, if not all, of their extent. ERTS-1 MSS imagery also provides four spectral bands taken every 18 days which give data on relief, hydrology, and vegetation, all of which bear on the delineation and interpretation of soil associations. Enlarged prints derived from the individual spectral bands and shown in gray tones were useful for identifying soil associations.

Mapeamento da antiga cobertura vegetal de várzea do Baixo Amazonas a partir de imagens históricas (1975-1981 do Sensor MSS-Landsat Mapping ancient vegetation cover of the Amazon floodplain using historical MSS/Landsat images (1975-1981

Directory of Open Access Journals (Sweden)

Vivian Fróes Renó

2011-03-01

Full Text Available Este estudo apresenta um mapa da cobertura vegetal da planície de inundação do Rio Amazonas entre as cidades de Parintins (AM e Almeirim (PA, com base em imagens Landsat-MSS adquiridas entre 1975 e 1981. O processamento digital dessas imagens envolveu a transformação para imagens-fração de vegetação, solo e água escura (sombra, seguido da aplicação de técnicas de segmentação e classificação por região. O mapa resultante da classificação foi organizado em quatro classes de cobertura do solo: floresta de várzea, vegetação não-florestal de várzea, solo exposto e água aberta. A precisão do mapa foi estimada a partir de dois tipos de informações coletadas em campo: 1 pontos de descrição: para validação das classes de cobertura não sujeitas a grandes alterações, como é o caso dos corpos d'água permanentes, e identificação de indicadores dos tipos de cobertura original presentes na paisagem na ocasião da obtenção das imagens (72 pontos; 2 entrevistas com moradores antigos para a recuperação da memória sobre a cobertura vegetal existente há 30 anos (44 questionários. Ao todo foram coletadas informações em 116 pontos distribuídos ao longo da área de estudo. Esses pontos foram utilizados para calcular o Índice Kappa de concordância entre os dados de campo e o mapa resultante da classificação automática, cujo valor (0,78 indica a boa qualidade do mapa de cobertura vegetal da várzea. Os resultados mostram que a região possuía uma cobertura florestal de várzea de aproximadamente 8.650 km2 no período de aquisição das imagens.This study presents a vegetation map of the Amazon River floodplain between the towns of Parintins (AM and Almeirim (PA, based on Landsat-MSS scenes from 1975 to 1981. Digital processing involved the transformation of multispectral images into fraction-images of vegetation, soil and dark water (shadow, followed by the application of segmentation and region

Prediction of size-fractionated airborne particle-bound metals using MLR, BP-ANN and SVM analyses.

Science.gov (United States)

Leng, Xiang'zi; Wang, Jinhua; Ji, Haibo; Wang, Qin'geng; Li, Huiming; Qian, Xin; Li, Fengying; Yang, Meng

2017-08-01

Size-fractionated heavy metal concentrations were observed in airborne particulate matter (PM) samples collected from 2014 to 2015 (spanning all four seasons) from suburban (Xianlin) and industrial (Pukou) areas in Nanjing, a megacity of southeast China. Rapid prediction models of size-fractionated metals were established based on multiple linear regression (MLR), back propagation artificial neural network (BP-ANN) and support vector machine (SVM) by using meteorological factors and PM concentrations as input parameters. About 38% and 77% of PM 2.5 concentrations in Xianlin and Pukou, respectively, were beyond the Chinese National Ambient Air Quality Standard limit of 75 μg/m 3 . Nearly all elements had higher concentrations in industrial areas, and in winter among the four seasons. Anthropogenic elements such as Pb, Zn, Cd and Cu showed larger percentages in the fine fraction (ø≤2.5 μm), whereas the crustal elements including Al, Ba, Fe, Ni, Sr and Ti showed larger percentages in the coarse fraction (ø > 2.5 μm). SVM showed a higher training correlation coefficient (R), and lower mean absolute error (MAE) as well as lower root mean square error (RMSE), than MLR and BP-ANN for most metals. All the three methods showed better prediction results for Ni, Al, V, Cd and As, whereas relatively poor for Cr and Fe. The daily airborne metal concentrations in 2015 were then predicted by the fully trained SVM models and the results showed the heaviest pollution of airborne heavy metals occurred in December and January, whereas the lightest pollution occurred in June and July. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison of ANN and SVM for classification of eye movements in EOG signals

Science.gov (United States)

Qi, Lim Jia; Alias, Norma

2018-03-01

Nowadays, electrooculogram is regarded as one of the most important biomedical signal in measuring and analyzing eye movement patterns. Thus, it is helpful in designing EOG-based Human Computer Interface (HCI). In this research, electrooculography (EOG) data was obtained from five volunteers. The (EOG) data was then preprocessed before feature extraction methods were employed to further reduce the dimensionality of data. Three feature extraction approaches were put forward, namely statistical parameters, autoregressive (AR) coefficients using Burg method, and power spectral density (PSD) using Yule-Walker method. These features would then become input to both artificial neural network (ANN) and support vector machine (SVM). The performance of the combination of different feature extraction methods and classifiers was presented and analyzed. It was found that statistical parameters + SVM achieved the highest classification accuracy of 69.75%.

Validation of the Manchester scoring system for predicting BRCA1/2 mutations in 9,390 families suspected of having hereditary breast and ovarian cancer.

Science.gov (United States)

Kast, Karin; Schmutzler, Rita K; Rhiem, Kerstin; Kiechle, Marion; Fischer, Christine; Niederacher, Dieter; Arnold, Norbert; Grimm, Tiemo; Speiser, Dorothee; Schlegelberger, Brigitte; Varga, Dominic; Horvath, Judit; Beer, Marit; Briest, Susanne; Meindl, Alfons; Engel, Christoph

2014-11-15

The Manchester scoring system (MSS) allows the calculation of the probability for the presence of mutations in BRCA1 or BRCA2 genes in families suspected of having hereditary breast and ovarian cancer. In 9,390 families, we determined the predictive performance of the MSS without (MSS-2004) and with (MSS-2009) consideration of pathology parameters. Moreover, we validated a recalibrated version of the MSS-2009 (MSS-recal). Families were included in the registry of the German Consortium for Hereditary Breast and Ovarian Cancer, using defined clinical criteria. Receiver operating characteristics (ROC) analysis was used to determine the predictive performance. The recalibrated model was developed using logistic regression analysis and tested using an independent random validation sample. The area under the ROC curves regarding a mutation in any of the two BRCA genes was 0.77 (95%CI 0.75-0.79) for MSS-2004, 0.80 (95%CI 0.78-0.82) for MSS-2009, and 0.82 (95%CI 0.80-0.83) for MSS-recal. Sensitivity at the 10% mutation probability cutoff was similar for all three models (MSS-2004 92.2%, MSS-2009 92.2%, and MSS-recal 90.3%), but specificity of MSS-recal (46.0%) was considerably higher than that of MSS-2004 (25.4%) and MSS-2009 (32.3%). In the MSS-recal model, almost all predictors of the original MSS were significantly predictive. However, the score values of some predictors, for example, high grade triple negative breast cancers, differed considerably from the originally proposed score values. The original MSS performed well in our sample of high risk families. The use of pathological parameters increased the predictive performance significantly. Recalibration improved the specificity considerably without losing much sensitivity. © 2014 UICC.

Prediction of the Effect of Using Stone Column in Clayey Soil on the Behavior of Circular Footing by ANN Model

Directory of Open Access Journals (Sweden)

Omar Khaleel Ismael Al-Kubaisi

2018-05-01

Full Text Available Shallow foundations are usually used for structures with light to moderate loads where the soil underneath can carry them. In some cases, soil strength and/or other properties are not adequate and require improvement using one of the ground improvement techniques. Stone column is one of the common improvement techniques in which a column of stone is installed vertically in clayey soils. Stone columns are usually used to increase soil strength and to accelerate soil consolidation by acting as vertical drains. Many researches have been done to estimate the behavior of the improved soil. However, none of them considered the effect of stone column geometry on the behavior of the circular footing. In this research, finite element models have been conducted to evaluate the behavior of a circular footing with different stone column configurations. Moreover, an Artificial Neural Network (ANN model has been generated for predicting these effects. The results showed a reduction in the bending moment, the settlement, and the vertical stresses with the increment of the stone column length, while both the horizontal stress and the shear force were increased. ANN model showed a good relationship between the predicted and the calculated results.

[Study of building quantitative analysis model for chlorophyll in winter wheat with reflective spectrum using MSC-ANN algorithm].

Science.gov (United States)

Liang, Xue; Ji, Hai-yan; Wang, Peng-xin; Rao, Zhen-hong; Shen, Bing-hui

2010-01-01

Preprocess method of multiplicative scatter correction (MSC) was used to reject noises in the original spectra produced by the environmental physical factor effectively, then the principal components of near-infrared spectroscopy were calculated by nonlinear iterative partial least squares (NIPALS) before building the back propagation artificial neural networks method (BP-ANN), and the numbers of principal components were calculated by the method of cross validation. The calculated principal components were used as the inputs of the artificial neural networks model, and the artificial neural networks model was used to find the relation between chlorophyll in winter wheat and reflective spectrum, which can predict the content of chlorophyll in winter wheat. The correlation coefficient (r) of calibration set was 0.9604, while the standard deviation (SD) and relative standard deviation (RSD) was 0.187 and 5.18% respectively. The correlation coefficient (r) of predicted set was 0.9600, and the standard deviation (SD) and relative standard deviation (RSD) was 0.145 and 4.21% respectively. It means that the MSC-ANN algorithm can reject noises in the original spectra produced by the environmental physical factor effectively and set up an exact model to predict the contents of chlorophyll in living leaves veraciously to replace the classical method and meet the needs of fast analysis of agricultural products.

Application of ANNS in tube CHF prediction: effect on neuron number in hidden layer

International Nuclear Information System (INIS)

Han, L.; Shan, J.; Zhang, B.

2004-01-01

Prediction of the Critical Heat Flux (CHF) for upward flow of water in uniformly heated vertical round tube is studied with Artificial Neuron Networks (ANNs) method utilizing different neuron number in hidden layers. This study is based on thermal equilibrium conditions. The neuron number in hidden layers is chosen to vary from 5 to 30 with the step of 5. The effect due to the variety of the neuron number in hidden layers is analyzed. The analysis shows that the neuron number in hidden layers should be appropriate, too less will affect the prediction accuracy and too much may result in abnormal parametric trends. It is concluded that the appropriate neuron number in two hidden layers should be [15 15]. (authors)

Design of a 12-bit 80MS/s pipeline analog-to-digital converter for PLC-VDSL applications

Science.gov (United States)

Ruiz-Amaya, Jesus; Delgado-Restituto, Manuel; Fernandez-Bootello, Juan F.; de la Rosa, Jose M.

2005-06-01

This paper describes the design of a 12-bit 80MS/s pipeline Analog-to-Digital converter implemented in 0.13mm CMOS logic technology. The design has been computer-aided by a developed toolbox for the simulation, synthesis and verification of Nyquist-Rate Analog-to-Digital and Digital-to-Analog Converters in MATLAB. The embedded simulator uses SIMULINK C-coded S-functions to model all required subcircuits including their main error mechanisms. This approach allows to drastically speed up the simulation CPU-time and makes the proposed tool an advantageous alternative for fast exploration of requirements and as a design validation tool. The converter is based on a 10-stage pipeline preceded by a sample/hold with bootstrapping technique. Each stage gives 1.5 effective bits, except for the first one which provides 2.5 effective bits to improve linearity. The Analog-to-Digital architecture uses redundant bits for digital correction, it is planned to be implemented without using calibration and employs a subranging pipeline look-ahead technique to increase speed. Substrate biased MOSFETs in the depletion region are used as capacitors, linearized by a series compensation. Simulation results show that the Multi-Tone Power Ratio is higher than 56dB for several DMT test signals and the estimated Signal-to-Noise Ratio yield is supposed to be better than 62 dB from DC to Nyquist frequency. The converter dissipates less than 150mW from a 3.3V supply and occupies less than 4 mm2 die area. The results have been checked with all process corners from -40° to 85° and power supply from 3V to 3.6V.

Lääne-Virumaad kimbutab spetsialistipõud, töötajate eest hoolitsetakse aga ülihästi / Anne Nõgu, Rainer Miltop ; interv. Tiina Saar

Index Scriptorium Estoniae

Nõgu, Anne

2008-01-01

Rakveres asuva Art Cafe omanik Anne Nõgu kohviku juhtimisest ning endast kui tööandjast. Vt. samas: Õmblusettevõttest turu nõudmisel multitegijaks. Küsimustele vastab Multi Margeri juht Rainer Miltop; Piimatööstus paistab silma stabiilsusega.

Designing the input vector to ANN-based models for short-term load forecast in electricity distribution systems

International Nuclear Information System (INIS)

Santos, P.J.; Martins, A.G.; Pires, A.J.

2007-01-01

The present trend to electricity market restructuring increases the need for reliable short-term load forecast (STLF) algorithms, in order to assist electric utilities in activities such as planning, operating and controlling electric energy systems. Methodologies such as artificial neural networks (ANN) have been widely used in the next hour load forecast horizon with satisfactory results. However, this type of approach has had some shortcomings. Usually, the input vector (IV) is defined in a arbitrary way, mainly based on experience, on engineering judgment criteria and on concern about the ANN dimension, always taking into consideration the apparent correlations within the available endogenous and exogenous data. In this paper, a proposal is made of an approach to define the IV composition, with the main focus on reducing the influence of trial-and-error and common sense judgments, which usually are not based on sufficient evidence of comparative advantages over previous alternatives. The proposal includes the assessment of the strictly necessary instances of the endogenous variable, both from the point of view of the contiguous values prior to the forecast to be made, and of the past values representing the trend of consumption at homologous time intervals of the past. It also assesses the influence of exogenous variables, again limiting their presence at the IV to the indispensable minimum. A comparison is made with two alternative IV structures previously proposed in the literature, also applied to the distribution sector. The paper is supported by a real case study at the distribution sector. (author)

A TLBO based gradient descent learning-functional link higher order ANN: An efficient model for learning from non-linear data

Directory of Open Access Journals (Sweden)

Bighnaraj Naik

2018-01-01

Full Text Available All the higher order ANNs (HONNs including functional link ANN (FLANN are sensitive to random initialization of weight and rely on the learning algorithms adopted. Although a selection of efficient learning algorithms for HONNs helps to improve the performance, on the other hand, initialization of weights with optimized weights rather than random weights also play important roles on its efficiency. In this paper, the problem solving approach of the teaching learning based optimization (TLBO along with learning ability of the gradient descent learning (GDL is used to obtain the optimal set of weight of FLANN learning model. TLBO does not require any specific parameters rather it requires only some of the common independent parameters like number of populations, number of iterations and stopping criteria, thereby eliminating the intricacy in selection of algorithmic parameters for adjusting the set of weights of FLANN model. The proposed TLBO-FLANN is implemented in MATLAB and compared with GA-FLANN, PSO-FLANN and HS-FLANN. The TLBO-FLANN is tested on various 5-fold cross validated benchmark data sets from UCI machine learning repository and analyzed under the null-hypothesis by using Friedman test, Holm’s procedure and post hoc ANOVA statistical analysis (Tukey test & Dunnett test.

Nouveaux formats, nouvelles images : les expériences des années cinquante

OpenAIRE

Berthomé, Jean-Pierre

2013-01-01

Le cinéma américain ne se porte pas bien, en ce début des années cinquante. Après l’euphorie d’une courte période qui a vu ses recettes culminer en 1946 avec 90 millions d’entrées par semaine, la désaffection du public a commencé à se manifester, accélérée par l’obligation faite aux grands studios de se séparer de leurs circuits de cinémas. En 1950, les entrées sont tombées à 60 millions par semaine. Il n’y en aura plus que 46 en 1953, 40 en 1960. Parallèlement, les 14 000 postes de télévisio...

Finding the Hole in the Wreck: Shamanic practice in the Poetry of Adrienne Rich and Anne Sexton

DEFF Research Database (Denmark)

Elias, Camelia

2013-01-01

In this paper I draw a concrete line from shamanism to confessional poetry. I’m interested in looking at how the cathartic function of confessional writing is even stronger when passed through the traditional shamanic hole that leads to experiencing the underworld of the unconscious. I want...... to argue that both Adrienne Rich and Anne Sexton manipulate with visualization techniques in their symbolic imagery in order to create an atmosphere that is akin to a shamanic journey. The poetic examples that I want to discuss demonstrate how the “language of the suicides” (Sexton) and “the thing itself...

Evaluation Of The Advanced Operating System Of The Ann Arbor Transportation Authority : Transfer And On-Time Performance Study : Before And After AOS Implementation, October 1996 - May 1999

Science.gov (United States)

1999-01-01

In 1997, the Ann Arbor (Michigan) Transportation Authority began deploying advanced public transportation systems (APTS) technologies in its fixed route and paratransit operations. The project's concept is the integration of a range of such technolog...

ANN Model for Predicting the Impact of Submerged Aquatic Weeds Existence on the Hydraulic Performance of Branched Open Channel System Accompanied by Water Structures

International Nuclear Information System (INIS)

Abdeen, Mostafa A. M.; Abdin, Alla E.

2007-01-01

The existence of hydraulic structures in a branched open channel system urges the need for considering the gradually varied flow criterion in evaluating the different hydraulic characteristics in this type of open channel system. Computations of hydraulic characteristics such as flow rates and water surface profiles in branched open channel system with hydraulic structures require tremendous numerical effort especially when the flow cannot be assumed uniform. In addition, the existence of submerged aquatic weeds in this branched open channel system adds to the complexity of the evaluation of the different hydraulic characteristics for this system. However, this existence of aquatic weeds can not be neglected since it is very common in Egyptian open channel systems. Artificial Neural Network (ANN) has been widely utilized in the past decade in civil engineering applications for the simulation and prediction of the different physical phenomena and has proven its capabilities in the different fields. The present study aims towards introducing the use of ANN technique to model and predict the impact of submerged aquatic weeds existence on the hydraulic performance of branched open channel system. Specifically the current paper investigates a branched open channel system that consists of main channel supplies water to two branch channels that are infested by submerged aquatic weeds and have water structures such as clear over fall weirs and sluice gates. The results of this study showed that ANN technique was capable, with small computational effort and high accuracy, of predicting the impact of different infestation percentage for submerged aquatic weeds on the hydraulic performance of branched open channel system with two different hydraulic structures

Trente années qui ébranlèrent la physique histoire de la théorie quantique

CERN Document Server

Gamow, George

1968-01-01

G. Gamow, dans cet ouvrage, déploie une fois encore ses qualités d'historien, de vulgarisateur et d'homme d'esprit. L'"histoire de la théorie quantique" raconte la naissance de la physique moderne au cours des trente premières années du siècle, en nous guidant ainsi à travers cette galerie de portraits où les grands noms de la physique sont présentés, par les textes, les photographies et les croquis, sous leur aspect le moins académique.

Louis Kahni mateeria, valguse ja energia arhitektuur = Louis Kahn's Architecture of Matter, Light and Energy / Anne Griswold Tyng ; tõlk. Tiina Randus

Index Scriptorium Estoniae

Tyng, Anne Griswold

2007-01-01

Louis Kahni betoonarhitektuurist (Weissi maja, 1947-1949), Yale'i kunstigaleriist (1951-1953), City Toweri projektist (1952-1958), Trentoni supelmajast (1954-1956), Salki instituudist (1959-1965, La Jolla, California), Kimbelli kunstimuuseumist (1968-1974), pealinnakompleksist Dhakas (1965-1974). Anne Griswold Tyng hakkas L. Kahni juures tööle 1945. a., tema algkooli projektist (1949-50), oma Philadelphia maja juurdeehitusest (1965-1968)

Enhancement of RWSN Lifetime via Firework Clustering Algorithm Validated by ANN

Directory of Open Access Journals (Sweden)

Ahmad Ali

2018-03-01

Full Text Available Nowadays, wireless power transfer is ubiquitously used in wireless rechargeable sensor networks (WSNs. Currently, the energy limitation is a grave concern issue for WSNs. However, lifetime enhancement of sensor networks is a challenging task need to be resolved. For addressing this issue, a wireless charging vehicle is an emerging technology to expand the overall network efficiency. The present study focuses on the enhancement of overall network lifetime of the rechargeable wireless sensor network. To resolve the issues mentioned above, we propose swarm intelligence based hard clustering approach using fireworks algorithm with the adaptive transfer function (FWA-ATF. In this work, the virtual clustering method has been applied in the routing process which utilizes the firework optimization algorithm. Still now, an FWA-ATF algorithm yet not applied by any researcher for RWSN. Furthermore, the validation study of the proposed method using the artificial neural network (ANN backpropagation algorithm incorporated in the present study. Different algorithms are applied to evaluate the performance of proposed technique that gives the best results in this mechanism. Numerical results indicate that our method outperforms existing methods and yield performance up to 80% regarding energy consumption and vacation time of wireless charging vehicle.

Hybrid intelligence systems and artificial neural network (ANN approach for modeling of surface roughness in drilling

Directory of Open Access Journals (Sweden)

Ch. Sanjay

2014-12-01

Full Text Available In machining processes, drilling operation is material removal process that has been widely used in manufacturing since industrial revolution. The useful life of cutting tool and its operating conditions largely controls the economics of machining operations. Drilling is most frequently performed material removing process and is used as a preliminary step for many operations, such as reaming, tapping, and boring. Drill wear has a bad effect on the surface finish and dimensional accuracy of the work piece. The surface finish of a machined part is one of the most important quality characteristics in manufacturing industries. The primary objective of this research is the prediction of suitable parameters for surface roughness in drilling. Cutting speed, cutting force, and machining time were given as inputs to the adaptive fuzzy neural network and neuro-fuzzy analysis for estimating the values of surface roughness by using 2, 3, 4, and 5 membership functions. The best structures were selected based on minimum of summation of square with the actual values with the estimated values by artificial neural fuzzy inference system (ANFIS and neuro-fuzzy systems. For artificial neural network (ANN analysis, the number of neurons was selected from 1, 2, 3, … , 20. The learning rate was selected as .5 and .5 smoothing factor was used. The inputs were selected as cutting speed, feed, machining time, and thrust force. The best structures of neural networks were selected based on the criteria as the minimum of summation of square with the actual value of surface roughness. Drilling experiments with 10 mm size were performed at two cutting speeds and feeds. Comparative analysis has been done between the actual values and the estimated values obtained by ANFIS, neuro-fuzzy, and ANN analysis.

Wavelet transform and ANNs for detection and classification of power signal disturbances

International Nuclear Information System (INIS)

Memon, A.P.; Uqaili, M.A.; Memon, Z.A.

2012-01-01

This article proposes WT (Wavelet Transform) and an ANN (Artificial Neural Network) based approach for detection and classification of EPQDs (Electrical Power Quality Disturbances). A modified WT known as ST (Stockwell Transform) is suggested for feature extraction and PNN (probabilistic Neural Network) for pattern classification. The ST possesses outstanding time-frequency resolution characteristics and its phase correction techniques determine the phase of the WT to the zero time point The feature vectors for the input of PNN are extracted using ST technique and these obtained features are discrete, logical, and unaffected to noisy data of distorted signals. The data of the models required to develop the distorted EPQ (Electrical Power Quality) signals, is obtained within the ranges specified by IEEE 1159-1995 in its literatures. The features vectors including noisy time varying data during steady state or transient condition and extracted using the ST, are trained through PNN for pattern classification. Their simulation results demonstrate that the proposed methodology is successful and can classify EPQDs even under a noisy environment very efficiently with an average classification accuracy of 96%. (author)

Results of the radiological survey at 14 Saint Ann Place, Rochelle Park, New Jersey (MJ032)

International Nuclear Information System (INIS)

Foley, R.D.; Floyd, L.M.

1990-03-01

Maywood Chemical Works (MCW) of Maywood, New Jersey, generated process wastes and residues associated with the production and refining of thorium and thorium compounds from monazite ores from 1916 to 1956. At the request of the US Department of Energy (DOE), a group from Oak Ridge National Laboratory conducts investigative radiological surveys of properties in the vicinity of MCW to determine whether a property is contaminated with radioactive residues, principally 232 Th, derived from the MCW site. The survey typically includes direct measurement of gamma radiation levels and soil sampling for radionuclide analyses. The survey of this site, 14 Saint Ann Place, Rochelle Park, New Jersey (MJ032), was conducted during 1987. 4 refs., 3 tabs

Evaluación de un programa de maestría en educación en México, a través de la MSS

Directory of Open Access Journals (Sweden)

José Ramos Mendoza

2016-01-01

Full Text Available El objetivo de esta investigación fue evaluar la situación real del programa de Maes- tría en Administración en Gestión y Desarrollo de la Educación (MAGDE de la Escuela Supe- rior de Comercio y Administración, Unidad Santo Tomás (ESCASTO del Instituto Politécnico Nacional (IPN mediante la Metodología de los Sistemas Suaves (MSS. Ésta plantea siete pasos lexibles que conducen al investigador a generar situaciones problema desde la interacción con el sistema y la obtención de información a través del pensamiento sistémico. Se recurrió al método de estudio de caso y se aplicaron tres cuestionarios validados. Algunas conclusiones reieren que el programa bajo una dimensión social es complejo y abierto, lo que genera constante caos. Ante ello se recurrió a un pensamiento holístico para replantear la dirección, pertinencia y objetivo del programa para el que fue creado, que le permitieron su incursión en un programa de Postgrado de Calidad.

Ensemble ANNs-PSO-GA Approach for Day-ahead Stock E-exchange Prices Forecasting

Directory of Open Access Journals (Sweden)

Yi Xiao

2013-02-01

Full Text Available Stock e-exchange prices forecasting is an important financial problem that is receiving increasing attention. This study proposes a novel three-stage nonlinear ensemble model. In the proposed model, three different types of neural-network based models, i.e. Elman network, generalized regression neural network (GRNN and wavelet neural network (WNN are constructed by three non-overlapping training sets and are further optimized by improved particle swarm optimization (IPSO. Finally, a neural-network-based nonlinear meta-model is generated by learning three neural-network based models through support vector machines (SVM neural network. The superiority of the proposed approach lies in its flexibility to account for potentially complex nonlinear relationships. Three daily stock indices time series are used for validating the forecasting model. Empirical results suggest the ensemble ANNs-PSO-GA approach can significantly improve the prediction performance over other individual models and linear combination models listed in this study.

Comparison between Possibilistic c-Means (PCM and Artificial Neural Network (ANN Classification Algorithms in Land use/ Land cover Classification

Directory of Open Access Journals (Sweden)

Ganchimeg Ganbold

2017-03-01

Full Text Available There are several statistical classification algorithms available for landuse/land cover classification. However, each has a certain bias orcompromise. Some methods like the parallel piped approach in supervisedclassification, cannot classify continuous regions within a feature. Onthe other hand, while unsupervised classification method takes maximumadvantage of spectral variability in an image, the maximally separableclusters in spectral space may not do much for our perception of importantclasses in a given study area. In this research, the output of an ANNalgorithm was compared with the Possibilistic c-Means an improvementof the fuzzy c-Means on both moderate resolutions Landsat8 and a highresolution Formosat 2 images. The Formosat 2 image comes with an8m spectral resolution on the multispectral data. This multispectral imagedata was resampled to 10m in order to maintain a uniform ratio of1:3 against Landsat 8 image. Six classes were chosen for analysis including:Dense forest, eucalyptus, water, grassland, wheat and riverine sand. Using a standard false color composite (FCC, the six features reflecteddifferently in the infrared region with wheat producing the brightestpixel values. Signature collection per class was therefore easily obtainedfor all classifications. The output of both ANN and FCM, were analyzedseparately for accuracy and an error matrix generated to assess the qualityand accuracy of the classification algorithms. When you compare theresults of the two methods on a per-class-basis, ANN had a crisperoutput compared to PCM which yielded clusters with pixels especiallyon the moderate resolution Landsat 8 imagery.

ANN modelling of sediment concentration in the dynamic glacial environment of Gangotri in Himalaya.

Science.gov (United States)

Singh, Nandita; Chakrapani, G J

2015-08-01

The present study explores for the first time the possibility of modelling sediment concentration with artificial neural networks (ANNs) at Gangotri, the source of Bhagirathi River in the Himalaya. Discharge, rainfall and temperature have been considered as the main controlling factors of variations in sediment concentration in the dynamic glacial environment of Gangotri. Fourteen feed forward neural networks with error back propagation algorithm have been created, trained and tested for prediction of sediment concentration. Seven models (T1-T7) have been trained and tested in the non-updating mode whereas remaining seven models (T1a-T7a) have been trained in the updating mode. The non-updating mode refers to the scenario where antecedent time (previous time step) values are not used as input to the model. In case of the updating mode, antecedent time values are used as network inputs. The inputs applied in the models are either the variables mentioned above as individual factors (single input networks) or a combination of them (multi-input networks). The suitability of employing antecedent time-step values as network inputs has hence been checked by comparative analysis of model performance in the two modes. The simple feed forward network has been improvised with a series parallel non-linear autoregressive with exogenous input (NARX) architecture wherein true values of sediment concentration have been fed as input during training. In the glacial scenario of Gangotri, maximum sediment movement takes place during the melt period (May-October). Hence, daily data of discharge, rainfall, temperature and sediment concentration for five consecutive melt periods (May-October, 2000-2004) have been used for modelling. High Coefficient of determination values [0.77-0.88] have been obtained between observed and ANN-predicted values of sediment concentration. The study has brought out relationships between variables that are not reflected in normal statistical analysis. A

ANN and RSM modelling of antioxidant characteristics of kombucha fermented milk beverages with peppermint

Directory of Open Access Journals (Sweden)

Jasmina Vitas

2018-01-01

Full Text Available Antioxidant activity to stable DPPH radical (AADPPH and unstable hydroxyl radicals (AA.OH and nutraceuticals (monounsaturated fatty acids (MUFAs, polyunsaturated fatty acids (PUFAs and ascorbic acid content of kombucha fermented milks with peppermint (KFM-P were modelled and optimised. Beverages were produced by the addition of 10 % of kombucha peppermint inoculum to the milk containing 0.8, 1.6 and 2.8 % milk fat at 37, 40 and 43 °C. Response surface methodology (RSM indicated opposite response surfaces for AADPPH and AA.OH PUFAs and ascorbic acid, as most significant and influential factors, were included in graphical optimization and gave the working region for obtaining products of highest antioxidant quality: lower temperatures and milk fat up to 1.8 %; higher temperatures and milk fat of maximum 1.6 %. ANN modelling of antioxidant characteristics of kombucha fermented milk beverages with peppermint was, as expected, more accurate than RSM.

Teeninduse taseme hoidmine ja heade teenindajate leidmine on tööandjatele võtmeküsimus / Anu-Mall Naarits, Anneli Mere, Kristjan Laja, Inge Suder

Index Scriptorium Estoniae

2009-01-01

Anu-Mall Naarits Maratist, Anneli Mere Matkasport OÜ-st, Kristjan Laja Ambient Marketingist ning Inge Suder AS-ist Eesti Post vastavad küsimustele, mis puudutavad tagasisidet teenindusele, teenindajatele pakutavaid koolitusi ja motivatsioonipakette, teeninduse taset Eestis, teenindustöötajate palgataset, hea teenindaja isikuomadusi ning raskemaid ülesandeid teenindaja töös

Poly(lactide-co-glycolide) encapsulated hydroxyapatite microspheres for sustained release of doxycycline

International Nuclear Information System (INIS)

Wang Xiaoyun; Xu Hui; Zhao Yanqiu; Wang Shaoning; Abe, Hiroya; Naito, Makio; Liu Yanli; Wang Guoqing

2012-01-01

Highlights: ► PLGA encapsulated HAP-MSs were used for the sustained delivery of Doxycycline (Doxy, a broad spectrum tetracycline antibiotic). ► Sustained Doxy release without obvious burst was observed. ► Mechanism of the sustained Doxy release was illustrated. ► Sustained Doxy release character in vivo was also obtained, the plasma Doxy levels were relatively lower and steady compared to that of the un-encapsulated HAP-MSs. - Abstract: The purpose of this study was to prepare a poly(lactide-co-glycolide) (PLGA) encapsulated hydroxyapatite microspheres (HAP-MSs) as injectable depot for sustained delivery of Doxycycline (Doxy). Doxy loaded HAP-MSs (Doxy-HAP-MSs) were encapsulated with PLGA by solid-in-oil-in-water (S/O/W) emulsion-solvent evaporation technique, the effects of the PLGA used (various intrinsic viscosity and LA/GA ratio) and ratio of PLGA/HAP-MSs on the formation of Doxy-HAP-MSs and in vitro release of Doxy were studied. The results showed that sustained drug release without obvious burst was obtained by using PLGA encapsulated HAP-MSs as the carrier, also the drug release rate could be tailored by changing the ratio of PLGA/HAP-MSs, or PLGA of various intrinsic viscosities or LA/GA ratio. Lower ratio of PLGA/HAP-MSs corresponded faster Doxy release, e.g. for the microspheres of PLGA/HAP-MSs ratio of 8 and 0.25, the in vitro Doxy release percents at the end of 7days were about 23% and 76%, respectively. Higher hydrophilicity (higher ratio of GA to LA) and lower molecular weight of PLGA corresponded to higher Doxy release rates. For in vivo release study, PLGA encapsulated HAP-MSs were subcutaneously injected to the back of mice, and the results showed good correlation between the in vivo and in vitro drug release. Meanwhile, the plasma Doxy levels after subcutaneous administration of PLGA encapsulated Doxy-HAP-MSs were relatively lower and steady compared to that of the un-encapsulated microspheres. In conclusion, PLGA encapsulated HAP-MSs may

Le Yémen dans les années 80 : entre crises et développement

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Paul Dresch

2002-09-01

Full Text Available Au cours des années 1980 se sont dessinées les tendances structurelles qui allaient modeler le régime politique et le développement économique du Yémen du Nord et, par la suite, le pays tout entier. Les « bonnes feuilles » qui suivent sont extraites de l’ouvrage A History of Modern Yemen, de Paul Dresch. Elles ont une double vocation : donner quelques aperçus de cet arrière-plan historique essentiel et encourager le lecteur à aller découvrir, dans cet ouvrage fondamental, des clefs de lecture qui lui permettront de décrypter la situation complexe du  Yémen contemporain.

The Myopic Stable Set for Social Environments (RM/17/002-revised)

NARCIS (Netherlands)

Demuynck, Thomas; Herings, P. Jean-Jacques; Saulle, Riccardo; Seel, Christian

2018-01-01

We introduce a new solution concept for models of coalition formation, called the myopic stable set (MSS). The MSS is defined for a general class of social environments and allows for an infinite state space. An MSS exists and, under minor continuity assumptions, it is also unique. The MSS

Support vector machine regression (SVR/LS-SVM)--an alternative to neural networks (ANN) for analytical chemistry? Comparison of nonlinear methods on near infrared (NIR) spectroscopy data.

Science.gov (United States)

Balabin, Roman M; Lomakina, Ekaterina I

2011-04-21

In this study, we make a general comparison of the accuracy and robustness of five multivariate calibration models: partial least squares (PLS) regression or projection to latent structures, polynomial partial least squares (Poly-PLS) regression, artificial neural networks (ANNs), and two novel techniques based on support vector machines (SVMs) for multivariate data analysis: support vector regression (SVR) and least-squares support vector machines (LS-SVMs). The comparison is based on fourteen (14) different datasets: seven sets of gasoline data (density, benzene content, and fractional composition/boiling points), two sets of ethanol gasoline fuel data (density and ethanol content), one set of diesel fuel data (total sulfur content), three sets of petroleum (crude oil) macromolecules data (weight percentages of asphaltenes, resins, and paraffins), and one set of petroleum resins data (resins content). Vibrational (near-infrared, NIR) spectroscopic data are used to predict the properties and quality coefficients of gasoline, biofuel/biodiesel, diesel fuel, and other samples of interest. The four systems presented here range greatly in composition, properties, strength of intermolecular interactions (e.g., van der Waals forces, H-bonds), colloid structure, and phase behavior. Due to the high diversity of chemical systems studied, general conclusions about SVM regression methods can be made. We try to answer the following question: to what extent can SVM-based techniques replace ANN-based approaches in real-world (industrial/scientific) applications? The results show that both SVR and LS-SVM methods are comparable to ANNs in accuracy. Due to the much higher robustness of the former, the SVM-based approaches are recommended for practical (industrial) application. This has been shown to be especially true for complicated, highly nonlinear objects.

Women's translations of scientific texts in the 18th century: a case study of Marie-Anne Lavoisier.

Science.gov (United States)

Kawashima, Keiko

2011-01-01

In the 18th century, many outstanding translations of scientific texts were done by women. These women were important mediators of science. However, I would like to raise the issue that the 'selection,' which is the process by which intellectual women chose to conduct translation works, and those 'selections' made by male translators, would not be made at the same level. For example, Émilie du Châtelet (1706-1749), the only French translator of Newton's "Principia," admitted her role as participating in important work, but, still, she was not perfectly satisfied with the position. For du Châtelet, the role as a translator was only an option under the current conditions that a female was denied the right to be a creator by society. In the case of Marie-Anne Lavoisier (1743-1794), like du Châtelet, we find an acute feeling in her mind that translation was not the work of creators. Because of her respect toward creative geniuses and her knowledge about the practical situation and concrete results of scientific studies, the translation works done by Marie-Anne Lavoisier were excellent. At the same time, the source of this excellence appears paradoxical at a glance: this excellence of translation was related closely with her low self-estimation in the field of science. Hence, we should not forget the gender problem that is behind such translations of scientific works done by women in that era. Such a possibility was a ray of light that was grasped by females, the sign of a gender that was eliminated from the center of scientific study due to social systems and norms and one of the few valuable opportunities to let people know of her own existence in the field of science.

[Sensitivity analysis of AnnAGNPS model's hydrology and water quality parameters based on the perturbation analysis method].

Science.gov (United States)

Xi, Qing; Li, Zhao-Fu; Luo, Chuan

2014-05-01

Sensitivity analysis of hydrology and water quality parameters has a great significance for integrated model's construction and application. Based on AnnAGNPS model's mechanism, terrain, hydrology and meteorology, field management, soil and other four major categories of 31 parameters were selected for the sensitivity analysis in Zhongtian river watershed which is a typical small watershed of hilly region in the Taihu Lake, and then used the perturbation method to evaluate the sensitivity of the parameters to the model's simulation results. The results showed that: in the 11 terrain parameters, LS was sensitive to all the model results, RMN, RS and RVC were generally sensitive and less sensitive to the output of sediment but insensitive to the remaining results. For hydrometeorological parameters, CN was more sensitive to runoff and sediment and relatively sensitive for the rest results. In field management, fertilizer and vegetation parameters, CCC, CRM and RR were less sensitive to sediment and particulate pollutants, the six fertilizer parameters (FR, FD, FID, FOD, FIP, FOP) were particularly sensitive for nitrogen and phosphorus nutrients. For soil parameters, K is quite sensitive to all the results except the runoff, the four parameters of the soil's nitrogen and phosphorus ratio (SONR, SINR, SOPR, SIPR) were less sensitive to the corresponding results. The simulation and verification results of runoff in Zhongtian watershed show a good accuracy with the deviation less than 10% during 2005- 2010. Research results have a direct reference value on AnnAGNPS model's parameter selection and calibration adjustment. The runoff simulation results of the study area also proved that the sensitivity analysis was practicable to the parameter's adjustment and showed the adaptability to the hydrology simulation in the Taihu Lake basin's hilly region and provide reference for the model's promotion in China.

Anne von Streit: Entgrenzter Alltag – Arbeiten ohne Grenzen? Das Internet und die raum-zeitlichen Organisationsstrategien von Wissensarbeitern. Bielefeld: transcript Verlag 2011.

Directory of Open Access Journals (Sweden)

Tanja M. Brinkmann

2012-05-01

Full Text Available Anne von Streit geht in dieser Veröffentlichung ihrer Dissertation der Fragestellung nach, wie sich die räumlich und zeitlich flexibilisierten Arbeitsbedingungen auf die Alltagsgestaltung von selbständigen Frauen und Männern in der Internetbranche auswirken. Als Geographin geht es ihr dabei nicht nur um zeitliche, sondern auch um räumliche Entgrenzungsprozesse. Diese teildisziplinäre Grenzüberschreitung liefert einige Erkenntnisse. In der durchaus geschlechtersensiblen Studie mit einem komplexen, vorwiegend qualitativen Design kann die Autorin aus geschlechterbezogener Perspektive sowohl deutliche Unterschiede wie auch Homogenitäten zwischen den Geschlechtern nachweisen. Dieses genauer auszubuchstabieren und zu begründen, bleibt sie jedoch weitgehend schuldig.In this published dissertation, Anne von Streit considers the question of how the flexibilization of spatial and temporal working conditions of self-employed women and men in the internet industry affects their daily routine. As a geographer, she is not only interested in temporal, but also in spatial processes of debordering. This subdisciplinary border crossing leads to several insights. In this, indeed gender-sensitive, study with a complex and mainly qualitative design, the author is able to prove, from a gender-related perspective, both striking differences and homogeneities between the genders. However, she largely fails to explain and spell this out in more detail.

Determination of zinc oxide content of mineral medicine calamine using near-infrared spectroscopy based on MIV and BP-ANN algorithm

Science.gov (United States)

Zhang, Xiaodong; Chen, Long; Sun, Yangbo; Bai, Yu; Huang, Bisheng; Chen, Keli

2018-03-01

Near-infrared (NIR) spectroscopy has been widely used in the analysis fields of traditional Chinese medicine. It has the advantages of fast analysis, no damage to samples and no pollution. In this research, a fast quantitative model for zinc oxide (ZnO) content in mineral medicine calamine was explored based on NIR spectroscopy. NIR spectra of 57 batches of calamine samples were collected and the first derivative (FD) method was adopted for conducting spectral pretreatment. The content of ZnO in calamine sample was determined using ethylenediaminetetraacetic acid (EDTA) titration and taken as reference value of NIR spectroscopy. 57 batches of calamine samples were categorized into calibration and prediction set using the Kennard-Stone (K-S) algorithm. Firstly, in the calibration set, to calculate the correlation coefficient (r) between the absorbance value and the ZnO content of corresponding samples at each wave number. Next, according to the square correlation coefficient (r2) value to obtain the top 50 wave numbers to compose the characteristic spectral bands (4081.8-4096.3, 4188.9-4274.7, 4335.4, 4763.6,4794.4-4802.1, 4809.9, 4817.6-4875.4 cm- 1), which were used to establish the quantitative model of ZnO content using back propagation artificial neural network (BP-ANN) algorithm. Then, the 50 wave numbers were operated by the mean impact value (MIV) algorithm to choose wave numbers whose absolute value of MIV greater than or equal to 25, to obtain the optimal characteristic spectral bands (4875.4-4836.9, 4223.6-4080.9 cm- 1). And then, both internal cross and external validation were used to screen the number of hidden layer nodes of BP-ANN. Finally, the number 4 of hidden layer nodes was chosen as the best. At last, the BP-ANN model was found to enjoy a high accuracy and strong forecasting capacity for analyzing ZnO content in calamine samples ranging within 42.05-69.98%, with relative mean square error of cross validation (RMSECV) of 1.66% and coefficient of

A frequency-domain approach to improve ANNs generalization quality via proper initialization.

Science.gov (United States)

Chaari, Majdi; Fekih, Afef; Seibi, Abdennour C; Hmida, Jalel Ben

2018-08-01

The ability to train a network without memorizing the input/output data, thereby allowing a good predictive performance when applied to unseen data, is paramount in ANN applications. In this paper, we propose a frequency-domain approach to evaluate the network initialization in terms of quality of training, i.e., generalization capabilities. As an alternative to the conventional time-domain methods, the proposed approach eliminates the approximate nature of network validation using an excess of unseen data. The benefits of the proposed approach are demonstrated using two numerical examples, where two trained networks performed similarly on the training and the validation data sets, yet they revealed a significant difference in prediction accuracy when tested using a different data set. This observation is of utmost importance in modeling applications requiring a high degree of accuracy. The efficiency of the proposed approach is further demonstrated on a real-world problem, where unlike other initialization methods, a more conclusive assessment of generalization is achieved. On the practical front, subtle methodological and implementational facets are addressed to ensure reproducibility and pinpoint the limitations of the proposed approach. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Segmentation of Point Clouds with K-Means and ANN (artifical Neural Network)

Science.gov (United States)

Kuçak, R. A.; Özdemir, E.; Erol, S.

2017-05-01

Segmentation of point clouds is recently used in many Geomatics Engineering applications such as the building extraction in urban areas, Digital Terrain Model (DTM) generation and the road or urban furniture extraction. Segmentation is a process of dividing point clouds according to their special characteristic layers. The present paper discusses K-means and self-organizing map (SOM) which is a type of ANN (Artificial Neural Network) segmentation algorithm which treats the segmentation of point cloud. The point clouds which generate with photogrammetric method and Terrestrial Lidar System (TLS) were segmented according to surface normal, intensity and curvature. Thus, the results were evaluated. LIDAR (Light Detection and Ranging) and Photogrammetry are commonly used to obtain point clouds in many remote sensing and geodesy applications. By photogrammetric method or LIDAR method, it is possible to obtain point cloud from terrestrial or airborne systems. In this study, the measurements were made with a Leica C10 laser scanner in LIDAR method. In photogrammetric method, the point cloud was obtained from photographs taken from the ground with a 13 MP non-metric camera.

THE SEGMENTATION OF POINT CLOUDS WITH K-MEANS AND ANN (ARTIFICAL NEURAL NETWORK

Directory of Open Access Journals (Sweden)

R. A. Kuçak

2017-05-01

Full Text Available Segmentation of point clouds is recently used in many Geomatics Engineering applications such as the building extraction in urban areas, Digital Terrain Model (DTM generation and the road or urban furniture extraction. Segmentation is a process of dividing point clouds according to their special characteristic layers. The present paper discusses K-means and self-organizing map (SOM which is a type of ANN (Artificial Neural Network segmentation algorithm which treats the segmentation of point cloud. The point clouds which generate with photogrammetric method and Terrestrial Lidar System (TLS were segmented according to surface normal, intensity and curvature. Thus, the results were evaluated. LIDAR (Light Detection and Ranging and Photogrammetry are commonly used to obtain point clouds in many remote sensing and geodesy applications. By photogrammetric method or LIDAR method, it is possible to obtain point cloud from terrestrial or airborne systems. In this study, the measurements were made with a Leica C10 laser scanner in LIDAR method. In photogrammetric method, the point cloud was obtained from photographs taken from the ground with a 13 MP non-metric camera.

Imposition des fortunes et finance offshore durant les années 1920: Aux origines de la concurrence fiscale internationale

OpenAIRE

Farquet, Christophe

2015-01-01

En se fondant sur un large panel de sources inédites issues de différentes archives européennes, l’article analyse l’impact des fuites de capitaux, de la finance offshore et de l’évasion fiscale internationale sur les systèmes d’imposition dans les années suivant la Première Guerre mondiale. Après avoir fourni des données sur l’ampleur du contournement par les détenteurs de capitaux des nouvelles taxes introduites à la sortie du conflit, le papier montre que la pression structurelle exercée s...

The use of artificial neural networks (ANN) for modeling of decolorization of textile dye solution containing C. I. Basic Yellow 28 by electrocoagulation process

International Nuclear Information System (INIS)

Daneshvar, N.; Khataee, A.R.; Djafarzadeh, N.

2006-01-01

In this paper, electrocoagulation has been used for removal of color from solution containing C. I. Basic Yellow 28. The effect of operational parameters such as current density, initial pH of the solution, time of electrolysis, initial dye concentration, distance between the electrodes, retention time and solution conductivity were studied in an attempt to reach higher removal efficiency. Our results showed that the increase of current density up to 80 A m -2 enhanced the color removal efficiency, the electrolysis time was 7 min and the range of pH was determined 5-8. It was found that for achieving a high color removal percent, the conductivity of the solution and the initial concentration of dye should be 10 mS cm -1 and 50 mg l -1 , respectively. An artificial neural networks (ANN) model was developed to predict the performance of decolorization efficiency by EC process based on experimental data obtained in a laboratory batch reactor. A comparison between the predicted results of the designed ANN model and experimental data was also conducted. The model can describe the color removal percent under different conditions

The use of artificial neural networks (ANN) for modeling of decolorization of textile dye solution containing C. I. Basic Yellow 28 by electrocoagulation process

Energy Technology Data Exchange (ETDEWEB)

Daneshvar, N. [Water and Wastewater Treatment Research Laboratory, Department of Applied Chemistry, Faculty of Chemistry, University of Tabriz, Tabriz (Iran, Islamic Republic of)]. E-mail: nezam_daneshvar@yahoo.com; Khataee, A.R. [Water and Wastewater Treatment Research Laboratory, Department of Applied Chemistry, Faculty of Chemistry, University of Tabriz, Tabriz (Iran, Islamic Republic of)]. E-mail: ar_khataee@yahoo.com; Djafarzadeh, N. [Water and Wastewater Treatment Research Laboratory, Department of Applied Chemistry, Faculty of Chemistry, University of Tabriz, Tabriz (Iran, Islamic Republic of)]. E-mail: n.jafarzadeh@gmail.com

2006-10-11

In this paper, electrocoagulation has been used for removal of color from solution containing C. I. Basic Yellow 28. The effect of operational parameters such as current density, initial pH of the solution, time of electrolysis, initial dye concentration, distance between the electrodes, retention time and solution conductivity were studied in an attempt to reach higher removal efficiency. Our results showed that the increase of current density up to 80 A m{sup -2} enhanced the color removal efficiency, the electrolysis time was 7 min and the range of pH was determined 5-8. It was found that for achieving a high color removal percent, the conductivity of the solution and the initial concentration of dye should be 10 mS cm{sup -1} and 50 mg l{sup -1}, respectively. An artificial neural networks (ANN) model was developed to predict the performance of decolorization efficiency by EC process based on experimental data obtained in a laboratory batch reactor. A comparison between the predicted results of the designed ANN model and experimental data was also conducted. The model can describe the color removal percent under different conditions.

Poly(lactide-co-glycolide) encapsulated hydroxyapatite microspheres for sustained release of doxycycline

Energy Technology Data Exchange (ETDEWEB)

Wang Xiaoyun [School of Pharmacy, Shenyang Pharmaceutical University, 103, Wenhua Road, Shenyang 110016 (China); Department of Pharmacy, Shandong Drug and Food Vocational College, Science and Technology Town, Hightech Industrial Development Zone, Weihai 264210 (China); Xu Hui; Zhao Yanqiu [School of Pharmacy, Shenyang Pharmaceutical University, 103, Wenhua Road, Shenyang 110016 (China); Wang Shaoning, E-mail: wsn-xh@126.com [School of Pharmaceutical Engineering, Shenyang Pharmaceutical University, 103, Wenhua Road, Shenyang 110016 (China); Abe, Hiroya; Naito, Makio [Joining and Welding Research Institute, Osaka University, 11-1, Mihogaoka, Ibaraki, Osaka 567-0047 (Japan); Liu Yanli [School of Pharmacy, Shenyang Pharmaceutical University, 103, Wenhua Road, Shenyang 110016 (China); Wang Guoqing [School of Pharmaceutical Engineering, Shenyang Pharmaceutical University, 103, Wenhua Road, Shenyang 110016 (China)

2012-03-15

Highlights: Black-Right-Pointing-Pointer PLGA encapsulated HAP-MSs were used for the sustained delivery of Doxycycline (Doxy, a broad spectrum tetracycline antibiotic). Black-Right-Pointing-Pointer Sustained Doxy release without obvious burst was observed. Black-Right-Pointing-Pointer Mechanism of the sustained Doxy release was illustrated. Black-Right-Pointing-Pointer Sustained Doxy release character in vivo was also obtained, the plasma Doxy levels were relatively lower and steady compared to that of the un-encapsulated HAP-MSs. - Abstract: The purpose of this study was to prepare a poly(lactide-co-glycolide) (PLGA) encapsulated hydroxyapatite microspheres (HAP-MSs) as injectable depot for sustained delivery of Doxycycline (Doxy). Doxy loaded HAP-MSs (Doxy-HAP-MSs) were encapsulated with PLGA by solid-in-oil-in-water (S/O/W) emulsion-solvent evaporation technique, the effects of the PLGA used (various intrinsic viscosity and LA/GA ratio) and ratio of PLGA/HAP-MSs on the formation of Doxy-HAP-MSs and in vitro release of Doxy were studied. The results showed that sustained drug release without obvious burst was obtained by using PLGA encapsulated HAP-MSs as the carrier, also the drug release rate could be tailored by changing the ratio of PLGA/HAP-MSs, or PLGA of various intrinsic viscosities or LA/GA ratio. Lower ratio of PLGA/HAP-MSs corresponded faster Doxy release, e.g. for the microspheres of PLGA/HAP-MSs ratio of 8 and 0.25, the in vitro Doxy release percents at the end of 7days were about 23% and 76%, respectively. Higher hydrophilicity (higher ratio of GA to LA) and lower molecular weight of PLGA corresponded to higher Doxy release rates. For in vivo release study, PLGA encapsulated HAP-MSs were subcutaneously injected to the back of mice, and the results showed good correlation between the in vivo and in vitro drug release. Meanwhile, the plasma Doxy levels after subcutaneous administration of PLGA encapsulated Doxy-HAP-MSs were relatively lower and steady

Spříznění (s) orální historií aneb Malá biografická skica Donalda a Anne Ritchie

Czech Academy of Sciences Publication Activity Database

Mücke, Pavel

2012-01-01

Roč. 2, č. 2 (2012), s. 17-27 ISSN 1804-753X R&D Projects: GA ČR(CZ) GAP410/11/1352 Institutional support: RVO:68378114 Keywords : oral history * Donald Ritchie * Anne Ritchie Subject RIV: AB - History https://docs. google .com/file/d/0Bxcn8cZ-v0QrVzVkR2RfV0JJQTg/edit?usp=sharing&pli=1

Musculoskeletal symptoms associated with posterior load carriage: An assessment of manual material handling workers in Indonesia.

Science.gov (United States)

Muslim, Khoirul; Nussbaum, Maury A

2015-06-05

Concerns have been raised regarding the high prevalence of musculoskeletal symptoms (MSS) among manual material handling (MMH) workers. However, limited investigations have been undertaken among one large group of workers using a particular MMH method called posterior load carriage (PLC). This is typically done without the use of a backpack in developing countries, and involves exposure to known risk factors for MSS such as heavy loads, non-neutral postures, and high levels of repetition. To 1) determine the types and prevalence of MSS among PLC workers and the impacts of these MSS on workers, 2) explore job demands potentially contributing to MSS, and (3) obtain input from workers regarding possible improvements to facilitate future interventions. Structured interview applied to 108 workers to assess PLC worker characteristics and job demands in eight cities in Indonesia. MSS were reported in all anatomical regions evaluated, with symptoms most commonly reported at the lower back (72.2%), feet (69.4%), knees (64%), shoulders (47.2%), and neck (41.7%). Logistic regression indicated that MSS in the lower back were associated with longer work hours/day, MSS in the hands were associated with load mass, and MSS in the ankles/feet were associated with stature and load carriage frequency. MSS were reported to interfere with daily activity, but only few workers sought medical treatment. Possible improvements included the use of a belt, hook, or backpack/frame, and changes in the carriage method. The study suggests that PLC workers incur a relatively high MSS burden. Future studies are needed to develop and evaluate practical interventions and specific guidelines to improve working conditions and occupational health and safety for PLC workers.

Překlad a stylistická analýza jedné kapitoly románu The Vampire Lestat od Anne Riceové

OpenAIRE

Dušková, Hana

2015-01-01

The main aim of this bachelor thesis is to point out the most common problems that the translators from English to Czech may encounter, exemplified by real solutions in the proces of translating modern fiction. This work consists of two parts. The theoretical part of is the the actual translation of one chapter of the novel The Vampire Lestat by american author Anne Rice. The theoretical part contains the stylistic analysis of the translated text and it is aimed at the probles I have encounte...

24 années d’épidémie de sida dans l’archipel indonésien

Directory of Open Access Journals (Sweden)

Laurence Husson

2012-10-01

Full Text Available L’ONUSIDA dans son bilan 2007 estimait le nombre de personnes infectées par le VIH dans le monde à 33 millions, avec 2,7 millions de nouvelles contaminations et 2 millions de décès dans l’année. Si l’Afrique subsaharienne était de loin la région du monde la plus durement touchée avec 22 millions de personnes infectées, l’Asie du Sud et du Sud-Est était aussi très concernée avec 4,2 millions de personnes porteuses du virus. Au sein de cette Asie, l’Indonésie, avec 240 millions d’habitants en 2...

Juhtidega kommunikatsioonist: Eesti juhtidel jääb puudu väljendusoskusest / Anneli Kannus, Jüri Pruulmann, Magnus Lužkov ...[jt.] ; intervjueerinud Kertu Kärk

Index Scriptorium Estoniae

2014-01-01

Organisatsiooni sise- ja väliskommunikatsiooni korraldusest, juhi rollist selles, enda kogemustest kommuniatsiooni vallas, Eesti juhtide kommunikatsioonioskusest ja koolitusvajadusest räägivad vestlusringis Tartu Tervishoiu Kõrgkooli rektor Anneli Kannus, ettevõtja Jüri Pruulmann, reklaamiagentuuri Optimist tegevjuht ja strateeg Magnus Lužkov, resideeruv ettevõtja Arengufondis Tiit Paananen ning juhtide coach ja personaliotsingu konsultant Tõnis Arro

Preparation of core-shell structured CaCO3 microspheres as rapid and recyclable adsorbent for anionic dyes

Science.gov (United States)

Zhao, Mengen; Chen, Zhenhua; Lv, Xinyan; Zhou, Kang; Zhang, Jie; Tian, Xiaohan; Ren, Xiuli; Mei, Xifan

2017-09-01

Core-shell structured CaCO3 microspheres (MSs) were prepared by a facile, one-pot method at room temperature. The adsorbent dosage and adsorption time of the obtained CaCO3 MSs were investigated. The results suggest that these CaCO3 MSs can rapidly and efficiently remove 99-100% of anionic dyes within the first 2 min. The obtained CaCO3 MSs have a high Brunauer-Emmett-Teller surface area (211.77 m2 g-1). In addition, the maximum adsorption capacity of the obtained CaCO3 MSs towards Congo red was 99.6 mg g-1. We also found that the core-shell structured CaCO3 MSs have a high recycling capability for removing dyes from water. Our results demonstrate that the prepared core-shell structured CaCO3 MSs can be used as an ideal, rapid, efficient and recyclable adsorbent to remove dyes from aqueous solution.

Artificial neural network (ANN) approach for modeling of Pb(II) adsorption from aqueous solution by Antep pistachio (Pistacia Vera L.) shells.

Science.gov (United States)

Yetilmezsoy, Kaan; Demirel, Sevgi

2008-05-30

A three-layer artificial neural network (ANN) model was developed to predict the efficiency of Pb(II) ions removal from aqueous solution by Antep pistachio (Pistacia Vera L.) shells based on 66 experimental sets obtained in a laboratory batch study. The effect of operational parameters such as adsorbent dosage, initial concentration of Pb(II) ions, initial pH, operating temperature, and contact time were studied to optimise the conditions for maximum removal of Pb(II) ions. On the basis of batch test results, optimal operating conditions were determined to be an initial pH of 5.5, an adsorbent dosage of 1.0 g, an initial Pb(II) concentration of 30 ppm, and a temperature of 30 degrees C. Experimental results showed that a contact time of 45 min was generally sufficient to achieve equilibrium. After backpropagation (BP) training combined with principal component analysis (PCA), the ANN model was able to predict adsorption efficiency with a tangent sigmoid transfer function (tansig) at hidden layer with 11 neurons and a linear transfer function (purelin) at output layer. The Levenberg-Marquardt algorithm (LMA) was found as the best of 11 BP algorithms with a minimum mean squared error (MSE) of 0.000227875. The linear regression between the network outputs and the corresponding targets were proven to be satisfactory with a correlation coefficient of about 0.936 for five model variables used in this study.

Caving thickness effects of surrounding rocks macro stress shell evolving characteristics

Institute of Scientific and Technical Information of China (English)

XIE Guang-xiang; YANG Ke

2009-01-01

In order to explore the influence of different caving thicknesses on the MSS dis-tribution and evolving characteristics of surrounding rocks in unsymmetrical disposal and fully mechanized top-coal caving (FMTC), based on unsymmetrical disposal characteris-tics, the analyses of numerical simulation, material simulation and in-situ observation were synthetically applied according to the geological and technical conditions of the 1151(3) working face in Xieqiao Mine. The results show that the stress peak value of the MSS-base and the ratio of MSS-body height to caving thickness are nonlinear and inversely proportional to the caving thickness. The MSS-base width, the MSS-body height, the MSS-base distance to working face wall and the rise distance of MSS-base beside coal pillar are nonlinear and directly proportional to the caving thickness. The characteristics of MSS distribution and its evolving rules of surrounding rocks and the integrated caving thickness effects are obtained. The investigations will provide lots of theoretic references to the surrounding rocks' stability control of the working face and roadway, roadway layout, gas extraction and exploitation, and efficiency of caving, etc.

Review of Artificial Neural Networks (ANN) applied to corrosion monitoring

International Nuclear Information System (INIS)

Mabbutt, S; Picton, P; Shaw, P; Black, S

2012-01-01

The assessment of corrosion within an engineering system often forms an important aspect of condition monitoring but it is a parameter that is inherently difficult to measure and predict. The electrochemical nature of the corrosion process allows precise measurements to be made. Advances in instruments, techniques and software have resulted in devices that can gather data and perform various analysis routines that provide parameters to identify corrosion type and corrosion rate. Although corrosion rates are important they are only useful where general or uniform corrosion dominates. However, pitting, inter-granular corrosion and environmentally assisted cracking (stress corrosion) are examples of corrosion mechanisms that can be dangerous and virtually invisible to the naked eye. Electrochemical noise (EN) monitoring is a very useful technique for detecting these types of corrosion and it is the only non-invasive electrochemical corrosion monitoring technique commonly available. Modern instrumentation is extremely sensitive to changes in the system and new experimental configurations for gathering EN data have been proven. In this paper the identification of localised corrosion by different data analysis routines has been reviewed. In particular the application of Artificial Neural Network (ANN) analysis to corrosion data is of key interest. In most instances data needs to be used with conventional theory to obtain meaningful information and relies on expert interpretation. Recently work has been carried out using artificial neural networks to investigate various types of corrosion data in attempts to predict corrosion behaviour with some success. This work aims to extend this earlier work to identify reliable electrochemical indicators of localised corrosion onset and propagation stages.

Rezension von: Catherine M. Orr, Ann Braithwaite, Diane Lichtenstein (Eds.: Rethinking Women’s and Gender Studies. London: Routledge 2012.

Directory of Open Access Journals (Sweden)

Jennifer Bühner

2014-03-01

Full Text Available Der Sammelband von Catherine M. Orr, Ann Braithwaite und Diane Lichtenstein bietet eine aktuelle Auseinandersetzung mit den zentralen Konzepten der Selbst-/Zuschreibung in den Women’s and Gender Studies (WGS im Kontext der gegenwärtigen Umstrukturierung der Universitäten – wie z. B. Methoden, Pädagogik, Community, Disziplin und Institutionalisierung. Dabei wird zum einen ein genealogischer Zugang gewählt, um die Funktionsweise dieser Konzepte aufzuzeigen, und zum anderen werden durch Selbstreflexion der Autor_innen auf ihre eigene Lehre und Position innerhalb der WGS Änderungsvorschläge eingebracht, um potentiell neue Richtungen für die Frauen- und Geschlechterforschung aufzuzeigen.

Fra radikalt samfunnsportrett til borgerlig idyll? En resepsjonsanalyse av Anne-Cath. Vestlys forfatterskap med hovedvekt på Aurora-bøkene

OpenAIRE

Vatnedalen, Mariell Bugge

2015-01-01

I min avhandling gjennomgår jeg utviklingen og tendensene i resepsjonen til Anne-Cath. Vestlys forfatterskap fra samtiden og fram til i dag, med Aurora-serien til å eksemplifisere. Jeg støtter meg til bøkene om Aurora i blokk Z (1966) og Aurora og pappa (1967), som tar for seg en familie som bryter med de tradisjonelle kjønnsrollemønstrene. Far er hjemmeværende student, glad i husarbeid og passer barn. Mor på den annen side er jurist i jobb og kjører bil - alt de...

Complementary structure for designer localized surface plasmons

Science.gov (United States)

Gao, Zhen; Gao, Fei; Zhang, Youming; Zhang, Baile

2015-11-01

Magnetic localized surface plasmons (LSPs) supported on metallic structures corrugated by very long and curved grooves have been recently proposed and demonstrated on an extremely thin metallic spiral structure (MSS) in the microwave regime. However, the mode profile for the magnetic LSPs was demonstrated by measuring only the electric field, not the magnetic field. Here, based on Babinet's principle, we propose a Babinet-inverted, or complementary MSS whose electric/magnetic mode profiles match the magnetic/electric mode profiles of MSS. This complementarity of mode profiles allows mapping the magnetic field distribution of magnetic LSP mode profile on MSS by measuring the electric field distribution of the corresponding mode on complementary MSS. Experiment at microwave frequencies also demonstrate the use of complementary MSS in sensing refractive-index change in the environment.

Evaluation of the AnnAGNPS Model for Predicting Runoff and Nutrient Export in a Typical Small Watershed in the Hilly Region of Taihu Lake

Directory of Open Access Journals (Sweden)

Chuan Luo

2015-09-01

Full Text Available The application of hydrological and water quality models is an efficient approach to better understand the processes of environmental deterioration. This study evaluated the ability of the Annualized Agricultural Non-Point Source (AnnAGNPS model to predict runoff, total nitrogen (TN and total phosphorus (TP loading in a typical small watershed of a hilly region near Taihu Lake, China. Runoff was calibrated and validated at both an annual and monthly scale, and parameter sensitivity analysis was performed for TN and TP before the two water quality components were calibrated. The results showed that the model satisfactorily simulated runoff at annual and monthly scales, both during calibration and validation processes. Additionally, results of parameter sensitivity analysis showed that the parameters Fertilizer rate, Fertilizer organic, Canopy cover and Fertilizer inorganic were more sensitive to TN output. In terms of TP, the parameters Residue mass ratio, Fertilizer rate, Fertilizer inorganic and Canopy cover were the most sensitive. Based on these sensitive parameters, calibration was performed. TN loading produced satisfactory results for both the calibration and validation processes, whereas the performance of TP loading was slightly poor. The simulation results showed that AnnAGNPS has the potential to be used as a valuable tool for the planning and management of watersheds.

First and Second-Law Efficiency Analysis and ANN Prediction of a Diesel Cycle with Internal Irreversibility, Variable Specific Heats, Heat Loss, and Friction Considerations

Directory of Open Access Journals (Sweden)

M. M. Rashidi

2014-04-01

Full Text Available The variability of specific heats, internal irreversibility, heat and frictional losses are neglected in air-standard analysis for different internal combustion engine cycles. In this paper, the performance of an air-standard Diesel cycle with considerations of internal irreversibility described by using the compression and expansion efficiencies, variable specific heats, and losses due to heat transfer and friction is investigated by using finite-time thermodynamics. Artificial neural network (ANN is proposed for predicting the thermal efficiency and power output values versus the minimum and the maximum temperatures of the cycle and also the compression ratio. Results show that the first-law efficiency and the output power reach their maximum at a critical compression ratio for specific fixed parameters. The first-law efficiency increases as the heat leakage decreases; however the heat leakage has no direct effect on the output power. The results also show that irreversibilities have depressing effects on the performance of the cycle. Finally, a comparison between the results of the thermodynamic analysis and the ANN prediction shows a maximum difference of 0.181% and 0.194% in estimating the thermal efficiency and the output power. The obtained results in this paper can be useful for evaluating and improving the performance of practical Diesel engines.

Application of Particle Swarm Optimization Algorithm for Optimizing ANN Model in Recognizing Ripeness of Citrus

Science.gov (United States)

Diyana Rosli, Anis; Adenan, Nur Sabrina; Hashim, Hadzli; Ezan Abdullah, Noor; Sulaiman, Suhaimi; Baharudin, Rohaiza

2018-03-01

This paper shows findings of the application of Particle Swarm Optimization (PSO) algorithm in optimizing an Artificial Neural Network that could categorize between ripeness and unripeness stage of citrus suhuensis. The algorithm would adjust the network connections weights and adapt its values during training for best results at the output. Initially, citrus suhuensis fruit’s skin is measured using optically non-destructive method via spectrometer. The spectrometer would transmit VIS (visible spectrum) photonic light radiation to the surface (skin of citrus) of the sample. The reflected light from the sample’s surface would be received and measured by the same spectrometer in terms of reflectance percentage based on VIS range. These measured data are used to train and test the best optimized ANN model. The accuracy is based on receiver operating characteristic (ROC) performance. The result outcomes from this investigation have shown that the achieved accuracy for the optimized is 70.5% with a sensitivity and specificity of 60.1% and 80.0% respectively.

Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO Using an Artificial Neural Network-Genetic Algorithm (ANN-GA

Directory of Open Access Journals (Sweden)

Xuedan Shi

2017-06-01

Full Text Available Rhodamine B (Rh B is a toxic dye that is harmful to the environment, humans, and animals, and thus the discharge of Rh B wastewater has become a critical concern. In the present study, reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO was used to treat Rh B aqueous solutions. The nZVI/rGO composites were synthesized with the chemical deposition method and were characterized using scanning electron microscopy (SEM, X-ray diffraction (XRD, Raman spectroscopy, N2-sorption, and X-ray photoelectron spectroscopy (XPS analysis. The effects of several important parameters (initial pH, initial concentration, temperature, and contact time on the removal of Rh B by nZVI/rGO were optimized by response surface methodology (RSM and artificial neural network hybridized with genetic algorithm (ANN-GA. The results suggest that the ANN-GA model was more accurate than the RSM model. The predicted optimum value of Rh B removal efficiency (90.0% was determined using the ANN-GA model, which was compatible with the experimental value (86.4%. Moreover, the Langmuir, Freundlich, and Temkin isotherm equations were applied to fit the adsorption equilibrium data, and the Freundlich isotherm was the most suitable model for describing the process for sorption of Rh B onto the nZVI/rGO composites. The maximum adsorption capacity based on the Langmuir isotherm was 87.72 mg/g. The removal process of Rh B could be completed within 20 min, which was well described by the pseudo-second order kinetic model.

Grenzgängerin in der Frauenbewegung. Eine biographische Annäherung an Marie Stritt

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Katja Weller

2005-11-01

Full Text Available Im politischen Wirken der Frauenrechtlerin Marie Stritt (1855–1928 liefen unterschiedliche Traditionslinien der organisierten bürgerlichen Frauenbewegung zusammen. Stritt stand sowohl dem kleinen Kreis kompromissloser Stimmrechtsaktivistinnen und Sexualreformerinnen nahe, der damals wie heute häufig als ‚radikal‘ bezeichnet wird. Beeinflusst war sie aber auch von der als ‚gemäßigt‘ etikettierten Majorität im Bund Deutscher Frauenvereine (BDF. Sie lehnte das Denken in vereinfachenden, polarisierenden Kategorien ab und bemühte sich vor allem in ihrer Funktion als Vorsitzende des BDF von 1899 bis 1910 um Vermittlung zwischen den konkurrierenden Frauenkreisen. Zu einer Zeit, in der sich die Frauenvereinsbewegung immer stärker ausdifferenzierte und politisierte, agierte Stritt an der Schnittstelle der verschiedenen treibenden Kräfte. Dass Marie Stritts Vita bislang nur oberflächlich untersucht wurde, erstaunt angesichts dieser herausgehobenen Bedeutung. Elke Schüllers quellengesättigte „biographische Annäherung“ (S. 89 füllt diese Forschungslücke jetzt dankenswerter Weise und bietet dabei neue Erkenntnisse über die Geschichte des BDF.

Gênero e tradução: a escritora quebequense Anne Hébert em foco

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Lilian Virginia Porto

2014-07-01

Full Text Available http://dx.doi.org/10.5007/2175-7968.2014v1n33p51 Este trabalho tem por objetivo mostrar a importância da escritora quebequense Anne Hébert (1916-2000 no desencadeamento de uma nova prática de tradução no Canadá, a tradução feminista, que tem como maiores representantes Barbara Godard, Susanne de Lotbinière-Harwood, Luise von Flotow e Sherry Simon. Destaca-se a discussão, entre Hébert e Frank Scott, em torno da tradução do poema hebertiano Le tombeau des rois, realizada por Scott. São mencionados os temas recorrentes da obra de Hébert que, a partir dos anos de 1990, passou a ser lida pelo viés feminista: relações familiares conflituosas, revolta e violência das personagens, clausura interior do ser humano e seu desejo de liberação, ressaltando-se o tratamento dado ao universo feminino. São comentados, ainda, problemas de gênero envolvendo duas traduções do romance hebertiano Kamouraska.

Book review. Ann-Hege Lorvik Waterhouse: In the material world: Perspectives and practices in kindergarten art activities

Directory of Open Access Journals (Sweden)

Nina Scott Frisch

2013-12-01

Full Text Available In the review of Ann-Hege Lorvik Waterhouse’s book I materialenes verden; perspektiver og praksiser i barnehagens kunstneriske virksomhet (In the material world: Perspectives and practices in kindergarten art activities,  Frisch states that despite the fact that the author is in some ways critical of the impact Reggio Emilia has had on Norwegian kindergartens, in her opinion, the book's content rests on the shoulders of the exploratory child-centred educational philosophy. The book offers great, relevant images related to new reflective concrete ideas, and it has a beautiful layout. Waterhouse points out her core argument several places in the text: a good kindergarten teacher is a creative kindergarten teacher – and the book reviewer adds, a good kindergarten teacher is a reading, reflecting kindergarten teacher.

Descending into the swamp. An analysis of the relationship between Louis and Lestat in Anne Rice's “Interview with the vampire” and the consequences of their unspoken love.

OpenAIRE

Haukås, Hege

2017-01-01

My thesis explores the relationship of Anne Rice's characters Louis de Pointe du Lac and Lestat Lioncourt, with emphasis on the consequences of their unspoken love. Focusing on the several emotional bonds that tie them together through transformation of becoming a vampire, of their vampire family and the consequences of their unrealised love.

What is the optimum minimum segment size used in step and shoot IMRT for prostate cancer?

International Nuclear Information System (INIS)

Takahashi, Yutaka; Sumida, Iori; Koizumi, Masahiko

2010-01-01

Although the use of small segments in step and shoot intensity modulated radiation therapy (IMRT) provides better dose distribution, extremely small segments decrease treatment accuracy. The purpose of this study was to determine the optimum minimum segment size (MSS) in two-step optimization in prostate step and shoot IMRT with regard to both planning quality and dosimetric accuracy. The XiO treatment planning system and Oncor Impression Plus were used. Results showed that the difference in homogeneity index (HI), defined as the ratio of maximum to minimum doses for planning target volume, between the MSS 1.0 cm and 1.5 cm plans, and 2.0 cm plans, was 0.1%, and 9.6%, respectively. With regard to V107 of planning target volume (PTV), the volume receiving 107% of the prescribed dose of the PTV, the difference between MSS 1.0 cm and 1.5 cm was 2%. However, the value of the MSS 2.0 cm or greater plans was more than 2.5-fold that of the MSS 1.0 cm plan. With regard to maximum rectal dose, a significant difference was seen between the MSS 1.5 cm and 2.0 cm plans, whereas no significant difference was seen between the MSS 1.0 cm and 1.5 cm plans. Composite plan verification revealed a greater than 5% dose difference between planned and measured dose in many regions with the MSS 1.0 cm plan, but in only limited regions in the MSS 1.5 cm plan. Our data suggest that the MSS should be determined with regard to both planning quality and dosimetric accuracy. (author)

Characterization of in vitro healthy and pathological human liver tissue periodicity using backscattered ultrasound signals.

Science.gov (United States)

Machado, Christiano Bittencourt; Pereira, Wagner Coelho de Albuquerque; Meziri, Mahmoud; Laugier, Pascal

2006-05-01

This work studied the periodicity of in vitro healthy and pathologic liver tissue, using backscattered ultrasound (US) signals. It utilized the mean scatterer spacing (MSS) as a parameter of tissue characterization, estimated by three methods: the spectral autocorrelation (SAC), the singular spectrum analysis (SSA) and the quadratic transformation method (SIMON). The liver samples were classified in terms of tissue status using the METAVIR scoring system. Twenty tissue samples were classified in four groups: F0, F1, F3 and F4 (five samples for each). The Kolmogorov-Smirnov test (applied on group pairs) resulted as nonsignificant (p > 0.05) for two pairs only: F1/F3 (for SSA) and F3/F4 (for SAC). A discriminant analysis was applied using as parameters the MSS mean (MSS) and standard deviation (sigmaMSS), the estimates histogram mode (mMSS), and the speed of US (mc(foie)) in the medium, to evaluate the degree of discrimination among healthy and pathologic tissues. The better accuracy (Ac) with SAC (80%) was with parameter group (MSS, sigmaMSS, mc(foie)), achieving a sensitivity (Ss) of 92.3% and a specificity (Sp) of 57.1%. For SSA, the group with all four parameters showed an Ac of 75%, an Ss of 78.6% and an Sp of 66.70%. SIMON obtained the best Ac of all (85%) with group (MSS, mMSS, mc(foie)), an Ss of 100%, but with an Sp of 50%.

Beneficial synergistic effect on bio-oil production from co-liquefaction of sewage sludge and lignocellulosic biomass.

Science.gov (United States)

Leng, Lijian; Li, Jun; Yuan, Xingzhong; Li, Jingjing; Han, Pei; Hong, Yuchun; Wei, Feng; Zhou, Wenguang

2018-03-01

Co-liquefaction of municipal sewage sludge (MSS) and lignocellulosic biomass such as rice straw or wood sawdust at different mixing ratios and the characterization of the obtained bio-oil and bio-char were investigated. Synergistic effects were found during co-processing of MSS with biomass for production of bio-oil with higher yield and better fuel properties than those from individual feedstock. The co-liquefaction of MSS/rice straw (4/4, wt) increased the bio-oil yield from 22.74% (bio-oil yield from liquefaction of MSS individually) or 23.67% (rice straw) to 32.45%. Comparable increase on bio-oil yield was also observed for MSS/wood sawdust mixtures (2/6, wt). The bio-oils produced from MSS/biomass mixtures were mainly composed of esters and phenols with lower boiling points (degradation temperatures) than those from individual feedstock (identified with higher heavy bio-oil fractions). These synergistic effects were probably resulted from the interactions between the intermittent products of MSS and those of biomass during processing. Copyright © 2017 Elsevier Ltd. All rights reserved.

SSVEP and ANN based optimal speller design for Brain Computer Interface

Directory of Open Access Journals (Sweden)

Irshad Ahmad Ansari

2015-07-01

Full Text Available This work put forwards an optimal BCI (Brain Computer Interface speller design based on Steady State Visual Evoked Potentials (SSVEP and Artificial Neural Network (ANN in order to help the people with severe motor impairments. This work is carried out to enhance the accuracy and communication rate of  BCI system. To optimize the BCI system, the work has been divided into two steps: First, designing of an encoding technique to choose characters from the speller interface and the second is the development and implementation of feature extraction algorithm to acquire optimal features, which is used to train the BCI system for classification using neural network. Optimization of speller interface is focused on representation of character matrix and its designing parameters. Then again, a lot of deliberations made in order to optimize selection of features and user’s time window. Optimized system works nearly the same with the new user and gives character per minute (CPM of 13 ± 2 with an average accuracy of 94.5% by choosing first two harmonics of power spectral density as the feature vectors and using the 2 second time window for each selection. Optimized BCI performs better with experienced users with an average accuracy of 95.1%. Such a good accuracy has not been reported before in account of fair enough CPM.DOI: 10.15181/csat.v2i2.1059

Design and characterization of a 12-bit 10MS/s 10mW pipelined SAR ADC for CZT-based hard X-ray imager

Science.gov (United States)

Xue, F.; Gao, W.; Duan, Y.; Zheng, R.; Hu, Y.

2018-02-01

This paper presents a 12-bit pipelined successive approximation register (SAR) ADC for CZT-based hard X-ray Imager. The proposed ADC is comprised of a first-stage 6-bit SAR-based Multiplying Digital Analog Converter (MDAC) and a second-stage 8-bit SAR ADC. A novel MDAC architecture using Vcm-based Switching method is employed to maximize the energy efficiency and improve the linearity of the ADC. Moreover, the unit-capacitor array instead of the binary-weighted capacitor array is adopted to improve the conversion speed and linearity of the ADC in the first-stage MDAC. In addition, a new layout design method for the binary-weighted capacitor array is proposed to reduce the capacitor mismatches and make the routing become easier and less-time-consuming. Finally, several radiation-hardened-by-design technologies are adopted in the layout design against space radiation effects. The prototype chip was fabricated in 0.18 μm mixed-signal 1.8V/3.3V process and operated at 1.8 V supply. The chip occupies a core area of only 0.58 mm2. The proposed pipelined SAR ADC achieves a peak signal-to-noise-and-distortion ratio (SNDR) of 66.7 dB and a peak spurious-free dynamic range (SFDR) of 78.6 dB at 10 MS/s sampling rate and consumes 10 mW. The figure of merit (FOM) of the proposed ADC is 0.56 pJ/conversion-step.

“Smoke pH”: A Review

Directory of Open Access Journals (Sweden)

Rodgman A

2014-12-01

Full Text Available The analytical methods developed since the 1950s to determine the “smoke pH” of cigarette mainstream smoke (MSS are reviewed. Most of the methods involve averaging the values obtained with all the puffs from a cigarette or averaging values from the total number of puffs from several cigarettes plus solution of the MSS in various quantities of water prior to pH determination. “Smoke pH” values thus obtained have little relevance to the situation involving a smoker who smokes a cigarette one puff at a time. In the human biological situation, the smoke components must traverse a layer of buffered fluid separating the smoke-filled respiratory tract cavity and the underlying tissue. Seldom is the effect of either the volume or the pH of the buffered fluid taken into account in determining the “smoke pH” of cigarette MSS taken one puff at a time. While numerous recent discussions have dealt with the effect of pH on the nature (degree of protonation of nicotine in cigarette MSS and its rate of absorption by the smoker, seldom is the volume and/or pH of oral cavity saliva or of the fluid coating the lung surface considered in the assessment of either the nature or absorption of nicotine by the smoker. If the degree of protonation of nicotine be pH dependent, then the degree of protonation of nicotine as it traverses the film of fluid separating the respiratory tract cavity and the underlying tissue must be dependent on the pH of the buffered fluid and not on the “smoke pH” per se. Statements that adjustment of the “smoke pH” by ammoniation of one or more tobacco blend components increases both the level of MSS nicotine and its rate of absorption, thus resulting in greater consumer acceptance and continuation of smoking, fail to take into account the other changes that occur in the MSS composition to enhance its consumer acceptability. Inclusion of modest percentages of ammoniated tobacco in the blend increases the “smoke pH” of

Venezuela : Vargas : Centrale thermo-électrique de Tacoa dans les années 1980 : littoral caraïbe de Catia La Mar

OpenAIRE

Pouyllau , Michel

1981-01-01

La Centrale thermo-électrique de Tacoa (connue actuellement comme Complejo Generador Josefina Joaquina Sánchez de Tacoa) a été construite en plusieurs étapes sur le littoral caraïbe de Catia La Mar (quartier Arrecife). Elle participe à l'approvisionnement électrique du Littoral de l'Etat de Vargas (villes de La Guaira, Maiquetia) ainsi que, pour partie, de la capitale Caracas. L'image correspond à une extension réalisée à la fin des années 1970 par Electricidad de Caracas et la compagnie belg...

An innovative design for using flexible printed coils for magnetostrictive-based longitudinal guided wave sensors in steel strand inspection

International Nuclear Information System (INIS)

Tse, P W; Liu, X C; Wang, X J; Liu, Z H; Wu, B; He, C F

2011-01-01

Magnetostrictive sensors (MsSs) that can excite and receive guided waves are commonly used in detecting defects that may occur in cables and strands for supporting heavy structures. A conventional MsS has a hard sensing coil that is wound onto a bobbin with electric wires to generate the necessary dynamic magnetic field to excite the desired guided waves. This tailor-made hard coil is usually bulky and is not flexible enough to fit steel strands of various sizes. The conventional MsS also cannot be mounted to any steel strand that does not have a free end to allow the bobbin to pass through the structure of the tested strand. Such inflexibilities limit the use of conventional MsSs in practical situations. To solve these limitations, an innovative type of coil, called a flexible printed coil (FPC), which is made out of flexible printed film, has been designed to replace the inflexible hard coil. The flexible structure of the FPC ensures that the new MsS can be easily installed on and removed from steel strands with different diameters and without free ends. Moreover, the FPC-based MsS can be wrapped into multiple layers due to its thin and flexible design. Although multi-layer FPC creates a minor asymmetry in the dynamic magnetic field, the results of finite element analysis and experiments confirm that the longitudinal guided waves excited by a FPC-based MsS are comparable to those excited by a conventional hard coil MsS. No significant reduction in defect inspection performance was found; in fact, further advantages were identified when using the FPC-based MsS. When acting as the transmitter, the innovative FPC-based MsS can cover a longer inspection length of strand. When acting as the receiver, the FPC-based MsS is more sensitive to smaller defects that are impossible to detect using a hard coil MsS. Hence, the multi-layer FPC-based MsS has great potential for replacing the conventional hard coil MsS because of its convenient installation, and ease of fitting to

Controlled delivery of tauroursodeoxycholic acid from biodegradable microspheres slows retinal degeneration and vision loss in P23H rats.

Directory of Open Access Journals (Sweden)

Laura Fernández-Sánchez

Full Text Available Successful drug therapies for treating ocular diseases require effective concentrations of neuroprotective compounds maintained over time at the site of action. The purpose of this work was to assess the efficacy of intravitreal controlled delivery of tauroursodeoxycholic acid (TUDCA encapsulated in poly(D,L-lactic-co-glycolic acid (PLGA microspheres for the treatment of the retina in a rat model of retinitis pigmentosa. PLGA microspheres (MSs containing TUDCA were produced by the O/W emulsion-solvent evaporation technique. Particle size and morphology were assessed by light scattering and scanning electronic microscopy, respectively. Homozygous P23H line 3 rats received a treatment of intravitreal injections of TUDCA-PLGA MSs. Retinal function was assessed by electroretinography at P30, P60, P90 and P120. The density, structure and synaptic contacts of retinal neurons were analyzed using immunofluorescence and confocal microscopy at P90 and P120. TUDCA-loaded PLGA MSs were spherical, with a smooth surface. The production yield was 78%, the MSs mean particle size was 23 μm and the drug loading resulted 12.5 ± 0.8 μg TUDCA/mg MSs. MSs were able to deliver the loaded active compound in a gradual and progressive manner over the 28-day in vitro release study. Scotopic electroretinografic responses showed increased ERG a- and b-wave amplitudes in TUDCA-PLGA-MSs-treated eyes as compared to those injected with unloaded PLGA particles. TUDCA-PLGA-MSs-treated eyes showed more photoreceptor rows than controls. The synaptic contacts of photoreceptors with bipolar and horizontal cells were also preserved in P23H rats treated with TUDCA-PLGA MSs. This work indicates that the slow and continuous delivery of TUDCA from PLGA-MSs has potential neuroprotective effects that could constitute a suitable therapy to prevent neurodegeneration and visual loss in retinitis pigmentosa.

Synthesis and characterization of α-MoO3 microspheres packed with nanoflakes

International Nuclear Information System (INIS)

Sharma, Rabindar K; Reddy, G B

2014-01-01

In this paper, we report the fabrication of three-dimensional molybdenum oxide (α-MoO 3 ) microspheres (MSs) packed with nanoflakes by facile and eco-friendly physical vapour deposition processes. Synthesis processes include sequences of plasma-assisted sublimation and thermal evaporation routes on a nickel-coated glass substrate in three individual stages. It is observed that nanostructured films deposited in the first and second stages function as seed layers for the growth of MoO 3 MSs. The structural study divulged that the MoO 3 MSs are polycrystalline in nature with pure orthorhombic phase. The morphological study endorses the uniform growth of MSs on a large area scale having diameters in the range of 0.7–2 µm with the finely packed single crystalline nanoflakes with mean thicknesses of nearly 60 nm. These single crystalline flakes are not individual but in the form of randomly distributed bunches embedded on the surface of MSs. Vibrational study of molybdenum and oxygen atoms in the MSs is carried out by Raman and Fourier transform infrared analysis, which further assured the existence of a pure orthorhombic crystal phase of MoO 3 MSs and also justified the x-ray diffractogram findings. The MoO 3 MSs show intense photoluminescence emission at room temperature with the five prominent peaks located at 424, 457, 486, 521 and 536 nm in accordance with the improvement in the degree of crystallinity. The possible growth strategy of α-MoO 3 MSs packed with nanoflakes is proposed in this paper briefly. (paper)

Obtaining health care in another European Union Member State: how easy is it to find relevant information?

Science.gov (United States)

Santoro, Alessio; Silenzi, Andrea; Ricciardi, Walter; McKee, Martin

2015-02-01

The European Union Directive on cross-border health care places an obligation on member states (MSs) to establish one or more national contact points (NCPs). We evaluated whether MSs were meeting their legal obligations. Two researchers created a set of criteria, drawn from the Directive, to evaluate the information that 18 MSs provide on their NCP websites. Some 15 of the 18 MSs evaluated provided >75% of the information sought. This report shows examples of best practices that could be used to encourage other MSs to improve the quality and quantity of information provided. © The Author 2014. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

A comparison RSM and ANN surface roughness models in thin-wall machining of Ti6Al4V using vegetable oils under MQL-condition

Science.gov (United States)

Mohruni, Amrifan Saladin; Yanis, Muhammad; Sharif, Safian; Yani, Irsyadi; Yuliwati, Erna; Ismail, Ahmad Fauzi; Shayfull, Zamree

2017-09-01

Thin-wall components as usually applied in the structural parts of aeronautical industry require significant challenges in machining. Unacceptable surface roughness can occur during machining of thin-wall. Titanium product such Ti6Al4V is mostly applied to get the appropriate surface texture in thin wall designed requirements. In this study, the comparison of the accuracy between Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) in the prediction of surface roughness was conducted. Furthermore, the machining tests were carried out under Minimum Quantity Lubrication (MQL) using AlCrN-coated carbide tools. The use of Coconut oil as cutting fluids was also chosen in order to evaluate its performance when involved in end milling. This selection of cutting fluids is based on the better performance of oxidative stability than that of other vegetable based cutting fluids. The cutting speed, feed rate, radial and axial depth of cut were used as independent variables, while surface roughness is evaluated as the dependent variable or output. The results showed that the feed rate is the most significant factors in increasing the surface roughness value followed by the radial depth of cut and lastly the axial depth of cut. In contrary, the surface becomes smoother with increasing the cutting speed. From a comparison of both methods, the ANN model delivered a better accuracy than the RSM model.

Development of a novel AMX-loaded PLGA/zein microsphere for root canal disinfection

Energy Technology Data Exchange (ETDEWEB)

Sousa, F F O [Capes Foundation, Ministry of Education of Brazil, Cx. Postal 365, BrasIlia DF 70359-970 (Brazil); Luzardo-Alvarez, A; Blanco-Mendez, J [Department of Pharmacy and Pharmaceutical Technology, School of Pharmacy, University of Santiago de Compostela, Campus Universitario Sur s/n, 15782, Santiago de Compostela (Spain); Perez-Estevez, A; Seoane-Prado, R, E-mail: franciscofabio.oliveira@rai.usc.e [Departament of Microbiology and Parasitology, Medical School, University of Santiago de Compostela, R/de San Francisco, s/n, 15782, Santiago de Compostela (Spain)

2010-10-01

The aim of this study was to develop polymeric biodegradable microspheres (MSs) of poly(d-l lactide-co-glycolide) (PLGA) and zein capable of delivering amoxicillin (AMX) at significant levels for root canal disinfection. PLGA/zein MSs were prepared using a spray-drying technique. The systems were characterized in terms of particle size, morphology, drug loading and in vitro release. Drug levels were reached to be effective during the intracanal dressing in between visits during the endodontic treatment. In vitro release studies were carried out to understand the release profile of the MSs. Antimicrobial activity of AMX was performed by antibiograms. Enterococcus faecalis was the bacteria selected due to its prevalence in endodontic failure. Drug microencapsulation yielded MSs with spherical morphology and an average particle size of between 5 and 38 {mu}m. Different drug-release patterns were obtained among the formulations. Release features related to the MSs were strongly dependent on drug nature as it was demonstrated by using a hydrophobic drug (indomethacin). Finally, AMX-loaded MSs were efficient against E faecalis as demonstrated by the antibiogram results. In conclusion, PLGA/zein MSs prepared by spray drying may be a useful drug delivery system for root canal disinfection.

Enhancement and wavelength-shifted emission of Cerenkov luminescence using multifunctional microspheres

International Nuclear Information System (INIS)

Li, Joanne; Dobrucki, Lawrence W; Marjanovic, Marina; Chaney, Eric J; Suslick, Kenneth S; Boppart, Stephen A

2015-01-01

Cerenkov luminescence (CL) imaging is a new molecular imaging modality that utilizes the photons emitted during radioactive decay when charged particles travel faster than the phase velocity of light in a dielectric medium. Here we present a novel agent to convert and increase CL emission at longer wavelengths using multimodal protein microspheres (MSs). The 64 Cu-labeled protein microspheres contain quantum dots (QDs) encapsulated within a high-refractive-index-oil core. Dark box imaging of the MSs was conducted to demonstrate the improvement in CL emission at longer wavelengths. To illustrate the versatile design of these MSs and the potential of CL in disease diagnosis, these MSs were utilized for in vitro cell targeting and ex vivo CL-excited QD fluorescence (CL-FL) imaging of atherosclerotic plaques in rats. It was shown that by utilizing both QDs and MSs with a high-refractive-index-oil core, the CL emission increases by four-fold at longer wavelengths. Furthermore, we demonstrate that these MSs generate both an in vivo and ex vivo contrast signal. The design concept of utilizing QDs and high-index core MSs may contribute to future developments of in vivo CL imaging. (paper)

Development of a novel AMX-loaded PLGA/zein microsphere for root canal disinfection

International Nuclear Information System (INIS)

Sousa, F F O; Luzardo-Alvarez, A; Blanco-Mendez, J; Perez-Estevez, A; Seoane-Prado, R

2010-01-01

The aim of this study was to develop polymeric biodegradable microspheres (MSs) of poly(d-l lactide-co-glycolide) (PLGA) and zein capable of delivering amoxicillin (AMX) at significant levels for root canal disinfection. PLGA/zein MSs were prepared using a spray-drying technique. The systems were characterized in terms of particle size, morphology, drug loading and in vitro release. Drug levels were reached to be effective during the intracanal dressing in between visits during the endodontic treatment. In vitro release studies were carried out to understand the release profile of the MSs. Antimicrobial activity of AMX was performed by antibiograms. Enterococcus faecalis was the bacteria selected due to its prevalence in endodontic failure. Drug microencapsulation yielded MSs with spherical morphology and an average particle size of between 5 and 38 μm. Different drug-release patterns were obtained among the formulations. Release features related to the MSs were strongly dependent on drug nature as it was demonstrated by using a hydrophobic drug (indomethacin). Finally, AMX-loaded MSs were efficient against E faecalis as demonstrated by the antibiogram results. In conclusion, PLGA/zein MSs prepared by spray drying may be a useful drug delivery system for root canal disinfection.

Cinquante années de recherches sur les débuts de l'Aurignacien en Europe occidentale

Directory of Open Access Journals (Sweden)

François Djindjian

2002-01-01

Full Text Available Une histoire des cinquante dernières années de rechercties sur les débuts de l'Aurignacien est tentée ici. Cet historique retrace brièvement les débuts entre 1860 et 1950 de la connaissance de l'Aurignacien resituant dans leur contexte les apports respectifs de Lartet, De Mortlllet, Breuil et Peyrony. Puis, les résultats des recherches des années 1950 à 1990 des différents acteurs (D. de Sonnevllle-Bordes, F. Bordes, H. M. Movius, H. Delporte, G. Laplace, J. Hahn, N. Soler, F. Bazile, F. Champagne, etc. concernant les débuts de l'Aurignacien sont analysés à la lueur des nouvelles données de fouilles en Aquitaine (Roc de Combe, La Ferrassie, Le Facteur, Caminade, Le Flageolet I, Le Plage, en Pyrénées (Gatzarria, Cueva h/iorin, en Jura-Souabe (Geissenklosterle et sur la côte méditerranéenne (abri l\\Aochi, La Laouza, l'Arbreda, L'Esquicho-Grapaou. Les apports des recherches sur le paléoenvironnement pour la reconstitution du climat et des méthodes mathématiques et informatiques dans les années 70 à la structuration chronologique de l'Aurignacien sont développés. Les différentes données à l'origine de l'existence d'un Protoaurignacien, d'un Aurignacien 0 en Périgord, d'un Aurignacien initial et la question de l'interstratification entre Castelperronien et Aurignacien sont discutées. Les récentes critiques depuis le début des années 90 concernant la fiabilité du cadre paléoclimatique des remplissages d'abrissous- roctie et la pertinence des approches typologiques sont examinées. Les conclusions amènent l'auteur à proposer suggérer que les débuts de I'Aurignacien, encore mal connus, ne sont pas uniformes suivant les régions et dans le temps. En Europe occidentale, l'existence d'un Aurignacien initial semble prouvé sur la côte méditerranéenne de la Ligurie jusqu'en Catalogne. L'expansion aurignacienne suit alors la bordure septentrionale pyrénéenne de l'Aude jusqu'en Cantabres et en Asturies. Puis, sous

The educational challenge of Paediatric Virology: An interview with Professor of Neonatology Anne Greenough.

Science.gov (United States)

Mammas, Ioannis N; Spandidos, Demetrios A

2017-10-01

According to Professor Anne Greenough, Professor of Neonatology and Clinical Respiratory Physiology at the King's College London (London, UK), Paediatric Virology is indeed a rapidly increasing educational challenge. Professor Greenough, who in 1992 wrote her book on congenital, perinatal and neonatal infections, believes that during the past 3 decades, paediatric health professionals are becoming increasingly involved in specialised care and follow-up of paediatric patients with viral diseases, who require advanced medical care and innovative technological services. Moreover, she highlights the expected role of new vaccines and antiviral agents that are currently under investigation, as well as the impact of emerging viral diseases that require novel prevention strategies and therapeutic protocols. However, she notes that the number of Paediatric Virologists in any one country is likely to be small; hence, a separate paediatric subspecialty needs to be considered carefully. In the context of the 3rd Workshop on Paediatric Virology, which will be held in Athens, Greece, on October 7th, 2017, Professor Greenough will give her plenary lecture on the impact of viral infections on the long term outcomes of prematurely born infants.

Biosorption of chromium (VI) from aqueous solutions and ANN modelling.

Science.gov (United States)

Nag, Soma; Mondal, Abhijit; Bar, Nirjhar; Das, Sudip Kumar

2017-08-01

The use of sustainable, green and biodegradable natural wastes for Cr(VI) detoxification from the contaminated wastewater is considered as a challenging issue. The present research is aimed to assess the effectiveness of seven different natural biomaterials, such as jackfruit leaf, mango leaf, onion peel, garlic peel, bamboo leaf, acid treated rubber leaf and coconut shell powder, for Cr(VI) eradication from aqueous solution by biosorption process. Characterizations were conducted using SEM, BET and FTIR spectroscopy. The effects of operating parameters, viz., pH, initial Cr(VI) ion concentration, adsorbent dosages, contact time and temperature on metal removal efficiency, were studied. The biosorption mechanism was described by the pseudo-second-order model and Langmuir isotherm model. The biosorption process was exothermic, spontaneous and chemical (except garlic peel) in nature. The sequence of adsorption capacity was mango leaf > jackfruit leaf > acid treated rubber leaf > onion peel > bamboo leaf > garlic peel > coconut shell with maximum Langmuir adsorption capacity of 35.7 mg g -1 for mango leaf. The treated effluent can be reused. Desorption study suggested effective reuse of the adsorbents up to three cycles, and safe disposal method of the used adsorbents suggested biodegradability and sustainability of the process by reapplication of the spent adsorbent and ultimately leading towards zero wastages. The performances of the adsorbents were verified with wastewater from electroplating industry. The scale-up study reported for industrial applications. ANN modelling using multilayer perception with gradient descent (GD) and Levenberg-Marquart (LM) algorithm had been successfully used for prediction of Cr(VI) removal efficiency. The study explores the undiscovered potential of the natural waste materials for sustainable existence of small and medium sector industries, especially in the third world countries by protecting the environment by eco-innovation.

Auction based spectrum management of cognitive radio networks

DEFF Research Database (Denmark)

Chang, H. B.; Chen, K.-C.; Prasad, Ramjee

2009-01-01

(PS-MSs), and we therefore construct a cognitive radio network (CRN) consisting of a PRN with multiple CR-MSs. We propose a spectrum management policy framework such that CR-MSs can compete in utilization of the PRN spectrum bands available to opportunistic transmission of CR-MSs by Vickrey auction...... to the PRN, the overall spectrum utilization, the profit of the service provider, the spectrum access opportunity of the CR-MSs are increased to achieve cowin situation for every party in cognitive radio networks.......Cognitive radio (CR) technology is considered as an effective solution to enhance overall spectrum efficiency, especially primary radio network (PRN) typically having relatively low spectrum utilization. However, to realize CR concept, it is essential to provide enough incentives to PRN and extra...

Multispectral remote sensing of inland wetlands in South Carolina: selecting the appropriate sensor

International Nuclear Information System (INIS)

Jensen, J.R.; Hodgson, M.; Christensen, E.J.; Mackey, H.E.; Sharitz, R.R.

1984-01-01

This research summarizes the utility of remote sensing for mapping both local (SRP) and regional wetlands including: stream delta areas, using aircraft multispectral scanner (MSS) imagery and large scale aerial photography; the SRP river swamp, using aircraft MSS and LANDSAT thematic mapper imagery; the Savannah River watershed, using LANDSAT MSS Imagery

Vincristine sulfate loaded dextran microspheres amalgamated with thermosensitive gel offered sustained release and enhanced cytotoxicity in THP-1, human leukemia cells: In vitro and in vivo study.

Science.gov (United States)

Thakur, Vivek; Kush, Preeti; Pandey, Ravi Shankar; Jain, Upendra Kumar; Chandra, Ramesh; Madan, Jitender

2016-04-01

Vincristine sulfate (VCS) is a drug of choice for the treatment of childhood and adult acute lymphocytic leukemia, Hodgkin's, non-Hodgkin's lymphoma as well as solid tumors including sarcomas. However, poor biopharmaceutical and pharmacokinetic traits of VCS like short serum half-life (12 min), high dosing frequency (1.4 mg/m(2) per week for 4 weeks) and extensive protein binding (75%) limit the clinical potential of VCS in cancer therapy. In present investigation, injectable vincristine sulfate loaded dextran microspheres (VCS-Dextran-MSs) were prepared and amalgamated with chitosan-β-glycerophosphate gel (VCS-Dextran-MSs-Gel) to surmount the biopharmaceutical and pharmacokinetic limitations of VCS that consequently induced synergistic sustained release pattern of the drug. Particle size and zeta-potential of VCS-Dextran-MSs were measured to be 6.8 ± 2.4 μm and -18.3 ± 0.11 mV along with the encapsulation efficiency of about 60.4 ± 4.5%. Furthermore, VCS-Dextran-MSs and VCS-Dextran-MSs-Gel exhibited slow release pattern and 94.7% and 95.8% of the drug was released in 72 h and 720 h, respectively. Results from cell viability assay and pharmacokinetic as well as histopathological analysis in mice indicated that VCS-Dextran-MSs-Gel offers superior therapeutic potential and higher AUClast than VCS-Dextran-MSs and drug solution. In conclusion, VCS-Dextran-MSs-Gel warrants further preclinical tumor growth study to scale up the technology. Copyright © 2015 Elsevier B.V. All rights reserved.

Düşünme Stilleri Ve Anne-Baba Tutumları Arasındaki İlişki

OpenAIRE

Palut, Birsen

2008-01-01

Düşünme stili bireyin zihninde olup bitenlerin ve düşünme süreçlerinin farklı şekillerde dışa yansıması olarak tanımlanmaktadır. Düşünme stillerinin oluşum ve gelişim sürecinde bireyin sosyalleşme süreci önemli bir yer tutmaktadır. Bu süreçte anne ve baba tutumları bireylerde hangi tür düşünme süreçlerinin baskın hale geleceğinin belirlenmesinde en önemli faktörlerden birini oluşturmaktadır. Ailelerin içinde yaşadığı kültürel değerler ve inançlar ebeveynlerin çocuk yetiştirme değerlerini, gel...

Anne-Hélène Pitel, Le prosimètre dans l’oeuvre de fiction de Lope de Vega, de «La Arcadia» (1598 à «La Dorotea» (1632

Directory of Open Access Journals (Sweden)

Javier Rubiera

2013-05-01

Full Text Available Review of Anne-Hélène Pitel, Le prosimètre dans l’oeuvre de fiction de Lope de Vega, de «La Arcadia» (1598 à «La Dorotea» (1632, Editorial Academia del Hispanismo, Vigo, 2011, 400 pp. ISBN: 978-84-96915-98-5.

Work-Related Musculoskeletal Symptoms and Job Factors Among Large-Herd Dairy Milkers.

Science.gov (United States)

Douphrate, David I; Nonnenmann, Matthew W; Hagevoort, Robert; Gimeno Ruiz de Porras, David

2016-01-01

Dairy production in the United States is moving towards large-herd milking operations, resulting in an increase in task specialization and work demands. The objective of this project was to provide preliminary evidence of the association of a number of specific job conditions that commonly characterize large-herd parlor milking operations with work-related musculoskeletal symptoms (MSS). A modified version of the Standardized Nordic Questionnaire was administered to assess MSS prevalence among 450 US large-herd parlor workers. Worker demographics and MSS prevalences were generated. Prevalence ratios were also generated to determine associations of a number of specific job conditions that commonly characterize large-herd parlor milking operations with work-related MSS. Work-related MSS are prevalent among large-herd parlor workers, since nearly 80% report 12-month prevalences of one or more symptoms, which are primarily located in the upper extremities, specifically shoulders and wrist/hand. Specific large-herd milking parlor job conditions are associated with MSS in multiple body regions, including performing the same task repeatedly, insufficient rest breaks, working when injured, static postures, adverse environmental conditions, and reaching overhead. These findings support the need for administrative and engineering solutions aimed at reducing exposure to job risk factors for work-related MSS among large-herd parlor workers.

Sexualité des adolescents et concurrence des classes sociales : étude comparative entre les États-Unis et les Pays-Bas depuis les années 1880

NARCIS (Netherlands)

Wouters, Cas

2014-01-01

Cette étude a pour but de comparer l’évolution du processus sociologique des bonnes sociétés néerlandaises et américaines depuis les années 1880, alors que les usages pour faire la cour étaient encore sous le contrôle strict des parents. Elle décrit de quelle manière le système de rendez-vous aux

An investigation of co-combustion municipal sewage sludge with biomass in a 20kW BFB combustor under air-fired and oxygen-enriched condition.

Science.gov (United States)

Kumar, Rajesh; Singh, Ravi Inder

2017-12-01

The behavior of municipal sewage sludge (MSS) with biomass (Guar stalks (GS), Mustard Husk (MH), Prosopis Juliflora Wood (PJW)) has been investigated in a 20kW bubbling fluidized bed (BFB) combustor under both air-fired (A-F) and oxygen-enriched (O-E) conditions. The work presented is divided into three parts, first part cover the thermogravimetric analysis (TGA), second part cover the experimental investigation of BFB combustor, and third part covers the ash analysis. TGA was performed with a ratio of 50%MSS/50%biomass (GS, MH, PJW) and results show that 50%MSS/50%GS has highest combustion characteristic factor (CCF). The experimental investigation of BFB combustor was performed for two different ratios of MSS/biomass (50%/50% and 25%/75%) and the combustion characteristics of blends were distinctive under both A-F and O-E condition. Despite 50%MSS/50%GS showing the highest combustion performance in TGA analysis, it formed agglomerates during burning in BFB. Due to this formation of large amount of agglomerates, de-fluidization was observed in the combustor bed after 65-75min in A-F conditions. The rate of de-fluidization increased under O-E condition. The de-fluidization problem disappeared when the share of MSS was reduced to 25%, but small amounts of the agglomerate were still present in the bed. With oxygen enhancement, the combustion efficiency of BFB combustor was improved and flue gasses were found within permissible limit. The maximum conceivable combustion efficiency (97.1%) for BFB combustor was accomplished by using 50% MSS/50%PJW under O-E condition. Results show that a ratio of 25%MSS/75%biomass combusted successfully inside the BFB combustor and extensive work is required for efficient utilization of significant share of MSS with biomass. SEM/EDS analyses were performed for agglomerate produced and for the damaged heater to study the surface morphology and compositions. The elemental heterogeneity of fly ash generated during MSS/biomass combustion

Heavy metals in summer squash fruits grown in soil amended with municipal sewage sludge.

Science.gov (United States)

Antonious, George F; Snyder, John C; Dennis, Sam O

2010-02-01

The increasing awareness of the value of vegetables and fruits in the human diet requires monitoring of heavy metals in food crops. The effects of amending soil with compost made from municipal sewage sludge (MSS) and MSS mixed with yard waste (MSS-YW) on Cd, Cr, Mo, Cu, Zn, Pb, and Ni concentrations in soil and the potential bioaccumulation of heavy metals in squash fruits at harvest were investigated. A field study was conducted in a silty-loam soil at Kentucky State University Research Farm. Eighteen plots of 22 x 3.7 m each were separated using metal borders and the soil in six plots was mixed with MSS at 15 t acre(-1), six plots were mixed with MSS-YW at 15 t acre(-1) (on dry weight basis), and six unamended plots (no-mulch) were used for comparison purposes. Plots were planted with summer squash and heavy metals were analyzed in soil and mature fruits at harvest. Analysis of heavy metals in squash fruits was conducted using inductively coupled plasma spectrometry. Zinc and Cu concentrations in soil mixed with MSS were extremely high compared to other metals. In squash fruits, concentrations of Zn were generally greater than Cu. Total squash marketable yield was greatest in MSS-YW and MSS treatments compared to no-mulch conventional soil. Concentrations of Cd and Pb in soil amended with MSS averaged 0.1 and 1.4 mg kg(-1), respectively. These levels were much lower than the limits in the U.S. guidelines for using MSS in land farming. Data revealed that maximum concentrations of Cd and Pb in squash fruits were 0.03 and 0.01 microg g(-1) dry fruit, respectively. Nickel concentration in squash fruits fluctuated among harvest dates reaching a maximum of 2.5 microg g(-1) dry fruit. However, these concentrations were far below their permissible limits in edible fruits.

Identification of Relevant Phytochemical Constituents for Characterization and Authentication of Tomatoes by General Linear Model Linked to Automatic Interaction Detection (GLM-AID) and Artificial Neural Network Models (ANNs).

Science.gov (United States)

Hernández Suárez, Marcos; Astray Dopazo, Gonzalo; Larios López, Dina; Espinosa, Francisco

2015-01-01

There are a large number of tomato cultivars with a wide range of morphological, chemical, nutritional and sensorial characteristics. Many factors are known to affect the nutrient content of tomato cultivars. A complete understanding of the effect of these factors would require an exhaustive experimental design, multidisciplinary scientific approach and a suitable statistical method. Some multivariate analytical techniques such as Principal Component Analysis (PCA) or Factor Analysis (FA) have been widely applied in order to search for patterns in the behaviour and reduce the dimensionality of a data set by a new set of uncorrelated latent variables. However, in some cases it is not useful to replace the original variables with these latent variables. In this study, Automatic Interaction Detection (AID) algorithm and Artificial Neural Network (ANN) models were applied as alternative to the PCA, AF and other multivariate analytical techniques in order to identify the relevant phytochemical constituents for characterization and authentication of tomatoes. To prove the feasibility of AID algorithm and ANN models to achieve the purpose of this study, both methods were applied on a data set with twenty five chemical parameters analysed on 167 tomato samples from Tenerife (Spain). Each tomato sample was defined by three factors: cultivar, agricultural practice and harvest date. General Linear Model linked to AID (GLM-AID) tree-structured was organized into 3 levels according to the number of factors. p-Coumaric acid was the compound the allowed to distinguish the tomato samples according to the day of harvest. More than one chemical parameter was necessary to distinguish among different agricultural practices and among the tomato cultivars. Several ANN models, with 25 and 10 input variables, for the prediction of cultivar, agricultural practice and harvest date, were developed. Finally, the models with 10 input variables were chosen with fit's goodness between 44 and 100

Identification of Relevant Phytochemical Constituents for Characterization and Authentication of Tomatoes by General Linear Model Linked to Automatic Interaction Detection (GLM-AID and Artificial Neural Network Models (ANNs.

Directory of Open Access Journals (Sweden)

Marcos Hernández Suárez

Full Text Available There are a large number of tomato cultivars with a wide range of morphological, chemical, nutritional and sensorial characteristics. Many factors are known to affect the nutrient content of tomato cultivars. A complete understanding of the effect of these factors would require an exhaustive experimental design, multidisciplinary scientific approach and a suitable statistical method. Some multivariate analytical techniques such as Principal Component Analysis (PCA or Factor Analysis (FA have been widely applied in order to search for patterns in the behaviour and reduce the dimensionality of a data set by a new set of uncorrelated latent variables. However, in some cases it is not useful to replace the original variables with these latent variables. In this study, Automatic Interaction Detection (AID algorithm and Artificial Neural Network (ANN models were applied as alternative to the PCA, AF and other multivariate analytical techniques in order to identify the relevant phytochemical constituents for characterization and authentication of tomatoes. To prove the feasibility of AID algorithm and ANN models to achieve the purpose of this study, both methods were applied on a data set with twenty five chemical parameters analysed on 167 tomato samples from Tenerife (Spain. Each tomato sample was defined by three factors: cultivar, agricultural practice and harvest date. General Linear Model linked to AID (GLM-AID tree-structured was organized into 3 levels according to the number of factors. p-Coumaric acid was the compound the allowed to distinguish the tomato samples according to the day of harvest. More than one chemical parameter was necessary to distinguish among different agricultural practices and among the tomato cultivars. Several ANN models, with 25 and 10 input variables, for the prediction of cultivar, agricultural practice and harvest date, were developed. Finally, the models with 10 input variables were chosen with fit's goodness

NOx, FINE PARTICLE AND TOXIC METAL EMISSIONS FROM THE COMBUSTION OF SEWAGE SLUDGE/COAL MIXTURES: A SYSTEMATIC ASSESSMENT

Energy Technology Data Exchange (ETDEWEB)

Jost O.L. Wendt

2002-08-15

This research project focuses on pollutants from the combustion of mixtures of dried municipal sewage sludge (MSS) and coal. The objective is to determine the relationship between (1) fraction sludge in the sludge/coal mixture, and (2) combustion conditions on (a) NOx concentrations in the exhaust, (b) the size segregated fine and ultra-fine particle composition in the exhaust, and (c) the partitioning of toxic metals between vapor and condenses phases, within the process. The proposed study will be conducted in concert with an existing ongoing research on toxic metal partitioning mechanisms for very well characterized pulverized coals alone. Both high NOx and low NOx combustion conditions will be investigated (unstaged and staged combustion). Tradeoffs between CO2 control, NOx control, and inorganic fine particle and toxic metal emissions will be determined. Previous research has yielded data on trace metal partitioning for MSS by itself, with natural gas assist, for coal plus MSS combustion together, and for coal alone. We have re-evaluated the inhalation health effects of ash aerosol from combustion of MSS both by itself and also together with coal. We have concluded that ash from the co-combustion of MSS and coal is very much worse from an inhalation health point of view, than ash from either MSS by itself or coal by itself. The reason is that ZnO is not the ''bad actor'' as had been suspected before, but the culprit is, rather, sulfated Zn. The MSS supplies the Zn and the coal supplies the sulfur, and so it is the combination of coal and MSS that makes that process environmentally bad. If MSS is to be burned, it should be burned without coal, in the absence of sulfur.

Mitochondrial Cytochrome c Oxidase Biogenesis Is Regulated by the Redox State of a Heme-Binding Translational Activator.

Science.gov (United States)

Soto, Iliana C; Barrientos, Antoni

2016-02-20

Mitochondrial cytochrome c oxidase (COX), the last enzyme of the respiratory chain, catalyzes the reduction of oxygen to water and therefore is essential for cell function and viability. COX is a multimeric complex, whose biogenesis is extensively regulated. One type of control targets cytochrome c oxidase subunit 1 (Cox1), a key COX enzymatic core subunit translated on mitochondrial ribosomes. In Saccharomyces cerevisiae, Cox1 synthesis and COX assembly are coordinated through a negative feedback regulatory loop. This coordination is mediated by Mss51, a heme-sensing COX1 mRNA-specific processing factor and translational activator that is also a Cox1 chaperone. In this study, we investigated whether Mss51 hemylation and Mss51-mediated Cox1 synthesis are both modulated by the reduction-oxidation (redox) environment. We report that Cox1 synthesis is attenuated under oxidative stress conditions and have identified one of the underlying mechanisms. We show that in vitro and in vivo exposure to hydrogen peroxide induces the formation of a disulfide bond in Mss51 involving CPX motif heme-coordinating cysteines. Mss51 oxidation results in a heme ligand switch, thereby lowering heme-binding affinity and promoting its release. We demonstrate that in addition to affecting Mss51-dependent heme sensing, oxidative stress compromises Mss51 roles in COX1 mRNA processing and translation. H2O2-induced downregulation of mitochondrial translation has so far not been reported. We show that high H2O2 concentrations induce a global attenuation effect, but milder concentrations specifically affect COX1 mRNA processing and translation in an Mss51-dependent manner. The redox environment modulates Mss51 functions, which are essential for regulation of COX biogenesis and aerobic energy production.

[Neuronal activity of monkey dorso-lateral premotor cortex during tasks of figure recognition guided motor sequence vs memorized spatial motor sequence].

Science.gov (United States)

Chen, Y C; Huang, F D; Chen, N H; Shou, J Y; Wu, L

1998-04-01

In the last 2-3 decades the role of the premotor cortex (PM) of monkey in memorized spatial sequential (MSS) movements has been amply investigated. However, it is as yet not known whether PM participates in the movement sequence behaviour guided by recognition of visual figures (i.e. the figure-recognition sequence, FRS). In the present work three monkeys were trained to perform both FRS and MSS tasks. Postmortem examination showed that 202 cells were in the dorso-lateral premotor cortex. Among 111 cells recorded during the two tasks, more than 50% changed their activity during the cue periods in either task. During the response period, the ratios of cells with changes of firing rate in both FRS and MSS were high and roughly equal to each other, while during the image period, the proportion in the FRS (83.7%) was significantly higher than that in the MSS (66.7%). Comparison of neuronal activities during same motor sequence of two different tasks showed that during the image periods PM neuronal activities were more closely related to the FRS task, while during the cue periods no difference could be found. Analysis of cell responses showed that the neurons with longer latency were much more in MSS than in FRS in either cue or image period. The present results indicate that the premotor cortex participates in FRS motor sequence as well as in MSS and suggest that the dorso-lateral PM represents another subarea in function shared by both FRS and MSS tasks. However, in view of the differences of PM neuronal responses in cue or image periods of FRS and MSS tasks, it seems likely that neural networks involved in FRS and MSS tasks are different.

Co-composting of municipal solid waste mixed with matured sewage sludge: The relationship between N2O emissions and denitrifying gene abundance.

Science.gov (United States)

Bian, Rongxing; Sun, Yingjie; Li, Weihua; Ma, Qiang; Chai, Xiaoli

2017-12-01

Aerobic composting is an alternative measure to the disposal of municipal solid waste (MSW). However, it produces nitrous oxide (N 2 O), a highly potent greenhouse via microbial nitrification and denitrification. In this study, the effects of matured sewage sludge (MSS) amendment on N 2 O emissions and the inter-relationships between N 2 O emissions and the abundance of denitrifying bacteria were investigated during aerobic composting of MSW. The results demonstrated that MSW composting with MSS amendments (C1, and C2, with a MSW to MSS ratio of 2:1 and 4:1, (v/v), respectively) significantly increased N 2 O emissions during the initial stage, yet contributed to the mitigation of N 2 O emissions during the cooling and maturation stage. MSS amended composting emitted a total of 18.4%-25.7% less N 2 O than the control treatment without MSS amendment (CK). Matured sewage sludge amendment also significantly altered the abundance of denitrifying bacteria. The quantification of denitrifying functional genes revealed that the N 2 O emission rate had a significant positive correlation with the abundance of the nirS, nirK genes in both treatments with MSS amendment. The nosZ/(nirS + nirK) ratio could be a good indicator for predicting N 2 O emissions. The higher N 2 O emission rate during the initial stage of composting mixed with MSS was characterized by lower nosZ/(nirS + nirK) ratios, compared to CK treatment. Higher ratios of nosZ/(nirS + nirK) were measured during the cooling and maturation stage in treatments with MSS which resulted in a reduction of the N 2 O emissions. These results demonstrated that MSS amendment could be a valid strategy for mitigating N 2 O emissions during MSW composting. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development of intelligent interface for simulation execution by module-based simulation system

International Nuclear Information System (INIS)

Yoshikawa, Hidekazu; Mizutani, Naoki; Shimoda, Hiroshi; Wakabayashi, Jiro

1988-01-01

An intelligent user support for the two phases of simulation execution was newly developed for Module-based Simulation System (MSS). The MSS has been in development as a flexible simulation environment to improve software productivity in complex, large-scale dynamic simulation of nuclear power plant. The AI programing by Smalltalk-80 was applied to materialize the two user-interface programs for (i) semantic diagnosis of the simulation program generated automatically by MSS, and (ii) consultation system by which user can set up consistent numerical input data files necessary for executing a MSS-generated program. Frame theory was utilized in those interface programs to represent the four knowledge bases, which are (i) usage information on module library in MSS and MSS-generated program, and (ii) expertise knowledge on nuclear power plant analysis such as material properties and reactor system configuration. Capabilities of those interface programs were confirmed by some example practice on LMFBR reactor dynamic calculation, and it was demonstrated that the knowledge-based systemization was effective to improve software work environment. (author)

Charter for Systems Engineer Working Group

Science.gov (United States)

Suffredini, Michael T.; Grissom, Larry

2015-01-01

This charter establishes the International Space Station Program (ISSP) Mobile Servicing System (MSS) Systems Engineering Working Group (SEWG). The MSS SEWG is established to provide a mechanism for Systems Engineering for the end-to-end MSS function. The MSS end-to-end function includes the Space Station Remote Manipulator System (SSRMS), the Mobile Remote Servicer (MRS) Base System (MBS), Robotic Work Station (RWS), Special Purpose Dexterous Manipulator (SPDM), Video Signal Converters (VSC), and Operations Control Software (OCS), the Mobile Transporter (MT), and by interfaces between and among these elements, and United States On-Orbit Segment (USOS) distributed systems, and other International Space Station Elements and Payloads, (including the Power Data Grapple Fixtures (PDGFs), MSS Capture Attach System (MCAS) and the Mobile Transporter Capture Latch (MTCL)). This end-to-end function will be supported by the ISS and MSS ground segment facilities. This charter defines the scope and limits of the program authority and document control that is delegated to the SEWG and it also identifies the panel core membership and specific operating policies.

Development of a partial least squares-artificial neural network (PLS-ANN) hybrid model for the prediction of consumer liking scores of ready-to-drink green tea beverages.

Science.gov (United States)

Yu, Peigen; Low, Mei Yin; Zhou, Weibiao

2018-01-01

In order to develop products that would be preferred by consumers, the effects of the chemical compositions of ready-to-drink green tea beverages on consumer liking were studied through regression analyses. Green tea model systems were prepared by dosing solutions of 0.1% green tea extract with differing concentrations of eight flavour keys deemed to be important for green tea aroma and taste, based on a D-optimal experimental design, before undergoing commercial sterilisation. Sensory evaluation of the green tea model system was carried out using an untrained consumer panel to obtain hedonic liking scores of the samples. Regression models were subsequently trained to objectively predict the consumer liking scores of the green tea model systems. A linear partial least squares (PLS) regression model was developed to describe the effects of the eight flavour keys on consumer liking, with a coefficient of determination (R 2 ) of 0.733, and a root-mean-square error (RMSE) of 3.53%. The PLS model was further augmented with an artificial neural network (ANN) to establish a PLS-ANN hybrid model. The established hybrid model was found to give a better prediction of consumer liking scores, based on its R 2 (0.875) and RMSE (2.41%). Copyright © 2017 Elsevier Ltd. All rights reserved.

La correspondance de jeunesse d’Henri Poincaré les années de formation de l'École polytechnique à l'École des mines (1873-1878)

CERN Document Server

2017-01-01

Ce cinquième volume de la correspondance d’Henri Poincaré rassemble l’ensemble des lettres envoyées par le mathématicien à sa famille durant ses années de formation à l’École polytechnique puis à l’École des mines de Paris. De 1873 à 1878, Poincaré écrit plus de 300 lettres à sa mère, à sa sœur et à son père. Une part importante de cette correspondance concerne ses études pour devenir ingénieur. Poincaré évoque ainsi les différents événements – importants ou anodins – qui ponctuent son parcours de formation dans les deux écoles: les cours et les examens, les voyages d’études en France et à l’étranger, les relations avec les professeurs, les rituels étudiants, la naissance de ses ambitions mathématiques. Cependant, ces lettres de jeunesse permettent également de reconstituer les réseaux familiaux et amicaux de Poincaré ainsi que l’univers socio-culturel dans lequel il évolue dans les années 1870. Elles fourmillent donc de récits pittoresques sur ses visit...

L’enseignement-apprentissage de la lecture en classe de FLE le cas d’une classe de 3ème année primaire.

OpenAIRE

BENCHOHRA, Khadda

2016-01-01

L’enseignement / apprentissage de la lecture en Français est un domaine très important de la didactique de l’écrit. L’acquisition de cette compétence est primordiale voire capitale, elle l’est encore plus lorsqu’elle est engagée avec de jeunes apprenants, en premier contact scolaire avec la langue. Notre recherche porte sur la découverte des méthodes et moyens contribuant à l’installation de cette compétence, chez les apprenants en première année de Français. Il s’agit de re...

ANN Control Based on Patterns Recognition for a Robotic Hand under Different Load Conditions

Directory of Open Access Journals (Sweden)

Ihsan Abdulhussein Baqer ihsan.qadi@gmail.com

2018-03-01

Full Text Available In this paper, the Artificial Neural Network (ANN is trained on the patterns of the normal component to tangential component ratios at the time of slippage occurrence, so that it can be able to distinguish the slippage occurrence under different type of load (quasi-static and dynamic loads, and then generates a feedback signal used as an input signal to run the actuator. This process is executed without the need for any information about the characteristics of the grasped object, such as weight, surface texture, shape, coefficient of the friction and the type of the load exerted on the grasped object. For fulfillment this approach, a new fingertip design has been proposed in order to detect the slippage in multi-direction between the grasped object and the artificial fingertips. This design is composed of two under-actuated fingers with an actuation system which includes flexible parts (compressive springs. These springs operate as a compensator for the grasping force at the time of slippage occurrence in spite of the actuator is in stopped situation. The contact force component ratios can be calculated via a conventional sensor (Flexiforce sensor after processed the force data using Matlab/Simulink program through a specific mathematical model which is derived according to the mechanism of the artificial finger.

A Map of Things Known and Lost in Anne Enright’s The Green Road

Directory of Open Access Journals (Sweden)

Margarita Estévez-Saá

2016-03-01

Full Text Available The present contribution interprets Anne Enright’s most recent novel, The Green Road (2015, as the story of two decades of an Irish family that is used by the writer to offer an alternative fictional rendering of the history of Ireland and the Irish from the 1980s till the early twenty-first century, as well as, formally speaking, a further contribution to the Irish writers’ penchant for destabilizing the conventions of a literary genre too frequently associated with British settlement and stability (Eagleton 1995 and with nineteenth-century realism (Hand 2011; and, therefore, recurrently considered as unable to apprehend the disruptive and multifaceted condition of Ireland and the Irish. Enright goes from the particular to the universal: the story of the Madigans serves to cover the recent history of Ireland as well as to deal with concerns such as motherhood, religion, sex, aging depression, illness, materialism and migrations, among others. Formally speaking, Enright’s latest novel is undoubtedly the most daring and innovative text in her already vast literary output and can and should be interpreted as the author’s most remarkable contribution to a literary genre with which Irish writers have not ceased to experiment.

Maternity care and maternal serum screening. Do male and female family physicians care for women differently?

Science.gov (United States)

Woodward, C A; Carroll, J C; Ryan, G; Reid, A J; Permaul-Woods, J A; Arbitman, S; Domb, S B; Fallis, B; Kilthei, J

1997-06-01

To examine whether male and female family physicians practise maternity care differently, particularly regarding the maternal serum screening (MSS) program. Mailed survey fielded between October 1994 and March 1995. Ontario family practices. Random sample of 2000 members of the College of Family Physicians of Canada who care for pregnant women. More than 90% of eligible physicians responded. Attitudes toward, knowledge about, and behaviour toward MSS. Women physicians were more likely than men to practise part time, in groups, and in larger communities. Men physicians were more likely to perform deliveries; women were more likely to do shared care. Despite a shorter work week, on average, female physicians cared for more pregnant women than male physicians did. Among those providing intrapartum care, women performed more deliveries, on average, than men. Women physicians were more likely than men to offer MSS to all pregnant patients. Although average time spent discussing MSS before the test was similar, women physicians had better knowledge of when best to do the test and its true-positive rate. All differences reported were statistically significant (P women, women physicians cared for more pregnant women than men did. Both spent similar time discussing MSS with their patients before offering screening, but more women physicians offered MSS to all their patients and were more knowledgeable about MSS than men physicians.

Application of FrontPage 98 to the Development of Web Sites for the Science Division and the Center for the Advancement of Learning and Teaching (CALT) at Anne Arundel Community College.

Science.gov (United States)

Bird, Bruce

This paper discusses the development of two World Wide Web sites at Anne Arundel Community College (Maryland). The criteria for the selection of hardware and software for Web site development that led to the decision to use Microsoft FrontPage 98 are described along with its major components and features. The discussion of the Science Division Web…

The Composition of Cigarette Smoke: Problems with Lists of Tumorigens

Directory of Open Access Journals (Sweden)

Rodgman A

2014-12-01

Full Text Available Since the mid-1960s, various investigators, agencies, and institutions have disseminated lists of cigarette mainstream smoke (MSS components reported to be tumorigenic on the basis of laboratory bioassays conducted under conditions significantly different from those encountered by the smoker during exposure to the components in the cigarette MSS aerosol. Since 1990, numerous lists of cigarette MSS components, defined as significant tumorigens, have been compiled by American Health Foundation personnel, Occupational Safety and Health Administration (OSHA, Fowles and Bates, and R.J. Reynolds R&D personnel. The purpose of most of the reports was to define human risk assessment and to dissuade smokers from smoking. Various investigators and agencies have frequently cited the earlier and/or the more recent lists of tumorigenic entities. The recent compilations, involving nearly 80 MSS components, suffer from serious deficiencies including: a Use of per cigarette delivery ranges for specified components which often include analytical data from cigarettes manufactured in the 1950s and 1960s which are not comparable to lower-'tar’ yield cigarettes manufactured since the mid-1970s. b Absence of standard analytical procedures for most of the listed components. c Methodological considerations regarding bioassays used to determine tumorigenicity of the listed MSS components. d Difficulty in extrapolating in vivo bioassay data obtained by non-inhalation modes of administration of a single compound to the human smoking situation involving inhalation of a complex aerosol containing that compound. e Inhalation data inadequacies regarding the tumorigenicity of many of the components. f Several tobacco smoke components are listed despite the fact their presence has not been confirmed, their MSS level has not been defined, or their MSS level is no longer relevant. g Insufficient consideration of inhibitors of tumorigenesis and mutagenesis found in MSS. h

Optimum coagulant forecasting by modeling jar test experiments using ANNs

Science.gov (United States)

Haghiri, Sadaf; Daghighi, Amin; Moharramzadeh, Sina

2018-01-01

Currently, the proper utilization of water treatment plants and optimizing their use is of particular importance. Coagulation and flocculation in water treatment are the common ways through which the use of coagulants leads to instability of particles and the formation of larger and heavier particles, resulting in improvement of sedimentation and filtration processes. Determination of the optimum dose of such a coagulant is of particular significance. A high dose, in addition to adding costs, can cause the sediment to remain in the filtrate, a dangerous condition according to the standards, while a sub-adequate dose of coagulants can result in the reducing the required quality and acceptable performance of the coagulation process. Although jar tests are used for testing coagulants, such experiments face many constraints with respect to evaluating the results produced by sudden changes in input water because of their significant costs, long time requirements, and complex relationships among the many factors (turbidity, temperature, pH, alkalinity, etc.) that can influence the efficiency of coagulant and test results. Modeling can be used to overcome these limitations; in this research study, an artificial neural network (ANN) multi-layer perceptron (MLP) with one hidden layer has been used for modeling the jar test to determine the dosage level of used coagulant in water treatment processes. The data contained in this research have been obtained from the drinking water treatment plant located in Ardabil province in Iran. To evaluate the performance of the model, the mean squared error (MSE) and correlation coefficient (R2) parameters have been used. The obtained values are within an acceptable range that demonstrates the high accuracy of the models with respect to the estimation of water-quality characteristics and the optimal dosages of coagulants; so using these models will allow operators to not only reduce costs and time taken to perform experimental jar tests

A Highly Stable and Magnetically Recyclable Nanocatalyst System: Mesoporous Silica Spheres Embedded with FeCo/Graphitic Shell Magnetic Nanoparticles and Pt Nanocatalysts.

Science.gov (United States)

Kim, Da Jeong; Li, Yan; Kim, Yun Jin; Hur, Nam Hwi; Seo, Won Seok

2015-12-01

We have developed a highly stable and magnetically recyclable nanocatalyst system for alkene hydrogenation. The materials are composed of mesoporous silica spheres (MSS) embedded with FeCo/graphitic shell (FeCo/GC) magnetic nanoparticles and Pt nanocatalysts (Pt-FeCo/GC@MSS). The Pt-FeCo/GC@MSS have superparamagnetism at room temperature and show type IV isotherm typical for mesoporous silica, thereby ensuring a large enough inner space (surface area of 235.3 m(2)  g(-1), pore volume of 0.165 cm(3)  g(-1), and pore diameter of 2.8 nm) to undergo catalytic reactions. We have shown that the Pt-FeCo/GC@MSS system readily converts cyclohexene into cyclohexane, which is the only product isolated and Pt-FeCo/GC@MSS can be seperated very quickly by an external magnetic field after the catalytic reaction is finished. We have demonstrated that the recycled Pt-FeCo/GC@MSS can be reused further for the same hydrogenation reaction at least four times without loss in the initial catalytic activity. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.