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Sample records for anne aan olevi

  1. State neurologic societies and the AAN

    PubMed Central

    Narayanaswami, Pushpa; Showers, Dave; Levi, Bruce; Showers, Melissa; Jones, Elaine C.; Busis, Neil A.; Comella, Cynthia L.; Pulst, Stefan M.; Hosey, Jonathan P.; Griggs, Robert C.

    2014-01-01

    Summary This report considers the recommendations of the State Society Task Force (SSTF), which evaluated how the relationship between the American Academy of Neurology (AAN) and neurologic societies of individual states can foster the care of patients with neurologic diseases. The task force also evaluated the role of state neurosociety and state medical society interactions in supporting the profession of neurology. The SSTF recommended that the AAN expand current support services to state neurosocieties and foster additional neurosociety development. Specific services to be considered by the AAN include online combined AAN/state neurosociety dues payment and enhanced Web support. The role of the AAN as a liaison between state neurosocieties and state medical societies is important to facilitate state level advocacy for neurology. PMID:25110622

  2. Ann Wagner, Mechanical Engineer.

    ERIC Educational Resources Information Center

    Bennett, Betsy K.

    1996-01-01

    Presents a profile of Ann Wagner, a mechanical engineer at the Goddard Space Flight Center in Maryland, and her job responsibilities there. Also includes a brief history of mechanical engineering as well as a sample graph and data activity sheet with answers. (AIM)

  3. Estimate product quality with ANNs

    SciTech Connect

    Brambilla, A.; Trivella, F.

    1996-09-01

    Artificial neural networks (ANNs) have been applied to predict catalytic reformer octane number (ON) and gasoline splitter product qualities. Results show that ANNs are a valuable tool to derive fast and accurate product quality measurements, and offer a low-cost alternative to online analyzers or rigorous mathematical models. The paper describes product quality measurements, artificial neural networks, ANN structure, estimating gasoline octane numbers, and estimating naphtha splitter product qualities.

  4. The 2015 AANS Presidential Address: Neurosurgery's founding principles.

    PubMed

    Harbaugh, Robert E

    2015-12-01

    These are turbulent times for American neurosurgery. It is important to look ahead and prepare for the future but it is also important to look back-for it is memory and tradition that prevent the tyranny of the present. It is impossible to know where we are going if we don't remember where we were. In this paper I want to discuss the founding principles of neurosurgery-the principles that have allowed neurosurgery to prosper in its first century-and to stress the importance of adhering to these principles in times of change. I also want to talk to you about how the American Association of Neurological Surgeons (AANS) is helping neurosurgeons honor our founding principles, while preparing neurosurgery for its second century. PMID:26620322

  5. Awards, lectures, and fellowships sponsored by the AANS/CNS Section on Tumors.

    PubMed

    Lau, Darryl; Barker, Fred G; Aghi, Manish K

    2014-09-01

    A major goal of the Section on Tumors of the American Association of Neurological Surgery (AANS) and Congress of Neurological Surgeons (CNS) since it was founded in 1984 has been to foster both education and research in the field of brain tumor treatment and development. In support of this goal, the Section sponsors a number of awards, named lectures, and fellowships at the annual meetings of the AANS and CNS. In this article, we describe the awards given by the AANS/CNS Section on Tumors since its foundation, the recipients of the awards, and their philanthropic donors. The subsequent history of awardees and their work is briefly examined. Specifically for the Preuss and Mahaley Awards, this article also examines the rates of publication among the award-winning abstracts and achievement of grant funding by awardees. PMID:24893731

  6. ANNs pinpoint underground distribution faults

    SciTech Connect

    Glinkowski, M.T.; Wang, N.C.

    1995-10-01

    Many offline fault location techniques in power distribution circuits involve patrolling along the lines or cables. In overhead distribution lines, most of the failures can be located quickly by visual inspection without the aid of special equipment. However, locating a fault in underground cable systems is more difficult. It involves additional equipment (e.g., thumpers, radars, etc.) to transform the invisibility of the cable into other forms of signals, such as acoustic sound and electromagnetic pulses. Trained operators must carry the equipment above the ground, follow the path of the signal, and draw lines on their maps in order to locate the fault. Sometimes, even smelling the burnt cable faults is a way of detecting the problem. These techniques are time consuming, not always reliable, and, as in the case of high-voltage dc thumpers, can cause additional damage to the healthy parts of the cable circuit. Online fault location in power networks that involve interconnected lines (cables) and multiterminal sources continues receiving great attention, with limited success in techniques that would provide simple and practical solutions. This article features a new online fault location technique that: uses the pattern recognition feature of artificial neural networks (ANNs); utilizes new capabilities of modern protective relaying hardware. The output of the neural network can be graphically displayed as a simple three-dimensional (3-D) chart that can provide an operator with an instantaneous indication of the location of the fault.

  7. Phosphorus component in AnnAGNPS

    USGS Publications Warehouse

    Yuan, Y.; Bingner, R.L.; Theurer, F.D.; Rebich, R.A.; Moore, P.A.

    2005-01-01

    The USDA Annualized Agricultural Non-Point Source Pollution model (AnnAGNPS) has been developed to aid in evaluation of watershed response to agricultural management practices. Previous studies have demonstrated the capability of the model to simulate runoff and sediment, but not phosphorus (P). The main purpose of this article is to evaluate the performance of AnnAGNPS on P simulation using comparisons with measurements from the Deep Hollow watershed of the Mississippi Delta Management Systems Evaluation Area (MDMSEA) project. A sensitivity analysis was performed to identify input parameters whose impact is the greatest on P yields. Sensitivity analysis results indicate that the most sensitive variables of those selected are initial soil P contents, P application rate, and plant P uptake. AnnAGNPS simulations of dissolved P yield do not agree well with observed dissolved P yield (Nash-Sutcliffe coefficient of efficiency of 0.34, R2 of 0.51, and slope of 0.24); however, AnnAGNPS simulations of total P yield agree well with observed total P yield (Nash-Sutcliffe coefficient of efficiency of 0.85, R2 of 0.88, and slope of 0.83). The difference in dissolved P yield may be attributed to limitations in model simulation of P processes. Uncertainties in input parameter selections also affect the model's performance.

  8. Katherine Anne Porter on Her Contemporaries.

    ERIC Educational Resources Information Center

    Bridges, Phyllis

    Personal experiences with and critical judgments of leading artists and intellectuals of the twentieth century are recorded in Katherine Anne Porter's essays, letters and conversations which provide snapshots of her attitudes and encounters. Porter's commentaries about such contemporaries as Ernest Hemingway, William Faulkner, Saul Bellow,…

  9. Ann Arbor, Michigan: Solar in Action (Brochure)

    SciTech Connect

    Not Available

    2011-10-01

    This brochure provides an overview of the challenges and successes of Ann Arbor, Michigan, a 2007 Solar America City awardee, on the path toward becoming a solar-powered community. Accomplishments, case studies, key lessons learned, and local resource information are given.

  10. Obituary: Anne Barbara Underhill, 1920-2003

    NASA Astrophysics Data System (ADS)

    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

  11. 75 FR 13334 - Notice of Availability of Draft Environmental Assessment; Ann Arbor Municipal Airport, Ann Arbor, MI

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-03-19

    ... Federal Aviation Administration Notice of Availability of Draft Environmental Assessment; Ann Arbor Municipal Airport, Ann Arbor, MI AGENCY: The Federal Aviation Administration is issuing this notice on... extension of runway 6/24 at the Ann Arbor Municipal Airport. While not required for an EA, the FAA...

  12. Obituary: Anne Barbara Underhill, 1920-2003

    NASA Astrophysics Data System (ADS)

    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

  13. An Overview of ANN Application in the Power Industry

    NASA Technical Reports Server (NTRS)

    Niebur, D.

    1995-01-01

    The paper presents a survey on the development and experience with artificial neural net (ANN) applications for electric power systems, with emphasis on operational systems. The organization and constraints of electric utilities are reviewed, motivations for investigating ANN are identified, and a current assessment is given from the experience of 2400 projects using ANN for load forecasting, alarm processing, fault detection, component fault diagnosis, static and dynamic security analysis, system planning, and operation planning.

  14. An ANN That Applies Pragmatic Decision on Texts.

    ERIC Educational Resources Information Center

    Aretoulaki, Maria; Tsujii, Jun-ichi

    A computer-based artificial neural network (ANN) that learns to classify sentences in a text as important or unimportant is described. The program is designed to select the sentences that are important enough to be included in composition of an abstract of the text. The ANN is embedded in a conventional symbolic environment consisting of…

  15. Literary Relations: Anne Shirley and Her American Cousins.

    ERIC Educational Resources Information Center

    Dawson, Janis

    2002-01-01

    Examines similarities between L.M. Montgomery's "Anne of Green Gables" and Kate Douglas Wiggin's "Rebecca of Sunnybrook Farm." Raises questions about the Canadianness of Montgomery's novel and considers the author's literary indebtedness to American authors and contemporary children's literature. Argues that as a literary work, "Anne of Green…

  16. 77 FR 75629 - Pramaggiore, Anne R.; Notice of Filing

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-12-21

    ... Energy Regulatory Commission Pramaggiore, Anne R.; Notice of Filing Take notice that on December 14, 2012, Anne R. Pramaggiore submitted for filing, an application for authority to hold interlocking positions... the ``eFiling'' link at http://www.ferc.gov . Persons unable to file electronically should submit...

  17. Ann Eliza Young: A Nineteenth Century Champion of Women's Rights.

    ERIC Educational Resources Information Center

    Cullen, Jack B.

    Concentrating on the efforts of such nineteenth century women's rights advocates as Susan B. Anthony and Elizabeth Cady Stanton, communication researchers have largely overlooked the contributions made to the cause by Ann Eliza Young. The nineteenth wife of Mormon leader Brigham Young, Ann Eliza Young left her husband and took to the speaker's…

  18. Applications of Artificial Neural Networks (ANNs) in Food Science

    SciTech Connect

    HUang, Yiqun; Kangas, Lars J.; Rasco, Barbara A.

    2007-02-01

    Abstract Artificial neural networks (ANNs) have been applied in almost every aspect of food science over the past two decade, although most applications are in the development stage. ANNs are useful tools for food safety and quality analyses, which include modeling of microbial growth and from this predicting food safety, interpreting spectroscopic data, and predicting physical, chemical, functional and sensory properties of various food products during processing and distribution. ANNs have a great deal of promise for modeling complex tasks in process control and simulation, and in applications of machine perception including machine vision and the electronic nose for food safety and quality control. This review discusses the basic theory of the ANN technology and its applications in food science, providing food scientists and the research community an overview of the current research and future trend of the applications of ANN technology in this field.

  19. Playing tag with ANN: boosted top identification with pattern recognition

    NASA Astrophysics Data System (ADS)

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

    2015-07-01

    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.

  20. Risk Quantification for ANN Based Short-Term Load Forecasting

    NASA Astrophysics Data System (ADS)

    Iwashita, Daisuke; Mori, Hiroyuki

    A new risk assessment method for short-term load forecasting is proposed. The proposed method makes use of an Artificial Neural Network (ANN) to forecast one-step ahead daily maximum loads and evaluate uncertainty of in load forecasting. As ANN the model, the Radial Basis Function (RBF) network is employed to forecast loads due to the good performance. Sufficient realistic pseudo-scenarios are required to carry out quantitative risk analysis. The multivariate normal distribution with the correlation between input variables is used to give more realistic results to ANN. In addition, the method of Moment Matching is used to improve the accuracy of the multivariate normal distribution. The Peak Over Threshold (POT) approach is used to evaluate risk that exceeds the upper bounds of generation capacity. The proposed method is successfully applied to real data of daily maximum load forecasting.

  1. Decolonizing the Choctaws: Teaching LeAnne Howe's "Shell Shaker"

    ERIC Educational Resources Information Center

    Hollrah, Patrice

    2004-01-01

    "Shell Shaker" (2001) by LeAnne Howe (Choctaw) is a novel that gives students an opportunity to learn that the history and culture of the Choctaw Nation of Oklahoma are alive today. Winner of the Before Columbus Foundation American Book Award in 2002, the novel deals with two parallel stories that converge in the present, one about the eighteenth…

  2. Anne S. Young: Professor and Variable Star Observer Extraordinaire

    NASA Astrophysics Data System (ADS)

    Bracher, Katherine

    2011-05-01

    Anne Sewell Young (1871-1961) was one of the eight original members of the AAVSO, to which she contributed more than 6500 observations over 33 years. She also taught astronomy for 37 years at Mount Holyoke College; among her students was Helen Sawyer Hogg. This paper will look at her life and career both at Mount Holyoke and with the AAVSO.

  3. AnnAGNPS Application and Evaluation in NE Indiana

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Annualized Agricultural Non-Point Source (AnnAGNPS) pollution model was developed for simulation of runoff, sediment, nutrient, and pesticide losses from ungaged agricultural watersheds. Here, the model was applied to the 707 km2 Cedar Creek Watershed (CCW) and the 45 km2 Matson Ditch Sub-Catchm...

  4. FLOYDS Classification of Gaia16ann as an AGN

    NASA Astrophysics Data System (ADS)

    Hosseinzadeh, G.; Arcavi, I.; Howell, D. A.; McCully, C.; Valenti, S.

    2016-07-01

    We obtained a spectrum of Gaia16ann on 2016 July 7.5 UT with the robotic FLOYDS instrument mounted on the LCOGT 2-meter telescope on Haleakala, Hawai'i. Using SNID (Blondin & Tonry 2007, ApJ, 666, 1024), we find a good fit to an AGN at redshift z=0.196.

  5. Prediction aluminum corrosion inhibitor efficiency using artificial neural network (ANN)

    NASA Astrophysics Data System (ADS)

    Ebrahimi, Sh; Kalhor, E. G.; Nabavi, S. R.; Alamiparvin, L.; Pogaku, R.

    2016-06-01

    In this study, activity of some Schiff bases as aluminum corrosion inhibitor was investigated using artificial neural network (ANN). Hence, corrosion inhibition efficiency of Schiff bases (in any type) were gathered from different references. Then these molecules were drawn and optimized in Hyperchem software. Molecular descriptors generating and descriptors selection were fulfilled by Dragon software and principal component analysis (PCA) method, respectively. These structural descriptors along with environmental descriptors (ambient temperature, time of exposure, pH and the concentration of inhibitor) were used as input variables. Furthermore, aluminum corrosion inhibition efficiency was used as output variable. Experimental data were split into three sets: training set (for model building) and test set (for model validation) and simulation (for general model). Modeling was performed by Multiple linear regression (MLR) methods and artificial neural network (ANN). The results obtained in linear models showed poor correlation between experimental and theoretical data. However nonlinear model presented satisfactory results. Higher correlation coefficient of ANN (R > 0.9) revealed that ANN can be successfully applied for prediction of aluminum corrosion inhibitor efficiency of Schiff bases in different environmental conditions.

  6. Reactions to Ann Arbor: Vernacular Black English and Education.

    ERIC Educational Resources Information Center

    Whiteman, Marcia Farr, Ed.

    The papers in this collection provide a brief state-of-the-art statement on the role of non-standard dialects of English in education and on some implications of the Ann Arbor decision. The following papers are included: (1) "Vernacular Black English: Setting the Issues in Time," by Roger W. Shuy; (2) "Beyond Black English: Implications of the Ann…

  7. Professor Ann De Vaney and a Good Conversation.

    ERIC Educational Resources Information Center

    Nichols, Randall G.

    The author begins this paper by explaining that in examining 10 works by Ann De Vaney his goal is to see what her writing generally reveals about her playing close attention to people-to research subjects, to subjects otherwise addressed in the works, to readers of her works. The author attempts to address each by asking basic questions: (1) What…

  8. Research Review: Ann Markusen's Concept of Artistic Dividend

    ERIC Educational Resources Information Center

    Hornbacher, Judy, Ed.

    2008-01-01

    This issue of the "Research Review" features the work of Ann Markusen, Director of the Humphrey Institute's Project on Regional and Industrial Economics at the University of Minnesota. Through the six articles reviewed here, Markusen develops the concept of "The Artistic Dividend," examines the impact of Artists' Centers, explores how artists earn…

  9. An Interview with Dr. Anne LaBastille.

    ERIC Educational Resources Information Center

    Griffin, Elizabeth

    1982-01-01

    Anne LaBastille, a role model for women interested in exploring the wilderness, gives hints on lessening the effects of acid rain, tells outdoor educators to encourage women to explore the wilderness and to take children outdoors to experience nature, and predicts a future economic slump for outdoor education. (LC)

  10. Comparison of Conventional and ANN Models for River Flow Forecasting

    NASA Astrophysics Data System (ADS)

    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.

  11. Space partitioning strategies for indoor WLAN positioning with cascade-connected ANN structures.

    PubMed

    Borenović, Miloš; Nešković, Aleksandar; Budimir, Djuradj

    2011-02-01

    Position information in indoor environments can be procured using diverse approaches. Due to the ubiquitous presence of WLAN networks, positioning techniques in these environments are the scope of intense research. This paper explores two strategies for space partitioning when utilizing cascade-connected Artificial Neural Networks (ANNs) structures for indoor WLAN positioning. A set of cascade-connected ANN structures with different space partitioning strategies are compared mutually and to the single ANN structure. The benefits of using cascade-connected ANNs structures are shown and discussed in terms of the size of the environment, number of subspaces and partitioning strategy. The optimal cascade-connected ANN structures with space partitioning show up to 50% decrease in median error and up to 12% decrease in the average error with respect to the single ANN model. Finally, the single ANN and the optimal cascade-connected ANN model are compared against other well-known positioning techniques. PMID:21243727

  12. 78 FR 70099 - Requested Administrative Waiver of the Coastwise Trade Laws: Vessel LADY ANN; Invitation for...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-11-22

    ... From the Federal Register Online via the Government Publishing Office DEPARTMENT OF TRANSPORTATION Maritime Administration Requested Administrative Waiver of the Coastwise Trade Laws: Vessel LADY ANN... of the vessel LADY ANN is: Intended Commercial Use Of Vessel: ``Charter cruises.'' Geographic...

  13. Groundwater Pollution Source Identification Using Trained ANN Model

    NASA Astrophysics Data System (ADS)

    Ayaz, M.; Srivastava, R.

    2012-04-01

    Remediation of groundwater contamination is one of the foremost challenges for the present generation. Exact knowledge of the location of the pollution source is essential to tackle this problem. Pollution sources have several important characteristics - location, strength and release period - that can be employed to single out a specific source. Breakthrough curves, which are the temporal distribution of concentration data at a given location, can be utilized to identify the location of an unknown pollution source. However, there is a lag between the time when the readings are taken at the observation well and the time when the source becomes active. In real field situations there is little or no information about this lag. We develop a methodology to identify the location of a pollution source, without using the lag time or the source strength as known parameters, by using an Artificial Neural Network (ANN) based technique. Breakthrough curves are primarily dependent on four variables, namely, source location, strength, release period and lag time. To develop an ANN model, the impact because of strength and lag time has been eliminated in a step-wise fashion. First, the breakthrough curve is normalized, between 0 and 1, by dividing concentration data by the maximum concentration value observed. Then, only the portion of the breakthrough curve near the peak is used as an input to train the ANN model. It has been shown that the breakthrough curve under these conditions is only dependent on the source location and release period, and is unique for a given combination of source strength and release period. An ANN model with one hidden layer is trained using the Levenberg-Marquardt algorithm. The modified breakthrough curve is used as an input to the ANN model while the source strength and release period constitute the output. The number of neurons in the hidden layer has been selected by minimizing the mean squared error for different number of hidden neurons

  14. 75 FR 418 - Certificate of Alternative Compliance for the Offshore Supply Vessel KELLY ANN CANDIES

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-01-05

    ... SECURITY Coast Guard Certificate of Alternative Compliance for the Offshore Supply Vessel KELLY ANN CANDIES... Alternative Compliance was issued for the offshore supply vessel KELLY ANN CANDIES as required by 33 U.S.C.... SUPPLEMENTARY INFORMATION: Background and Purpose The offshore supply vessel KELLY ANN CANDIES will be used...

  15. Anne S. Young: Professor and Variable Star Observer Extraordinaire

    NASA Astrophysics Data System (ADS)

    Bracher, K.

    2012-06-01

    One of the original eight members of the AAVSO, but not well known today, was Professor Anne Sewell Young of Mount Holyoke College. Miss Young taught there for thirty-seven years, and trained many women astronomers during the first third of the 20th century. This paper will attempt to present her life as an inspiring teacher, as well as a contributor of more than 6,500 variable star observations to the AAVSO.

  16. Jo Ann Rinaudo, PhD | Division of Cancer Prevention

    Cancer.gov

    Dr. Jo Ann Rinaudo is a Program Director in the Cancer Biomarkers Research Group in the Division of Cancer Prevention at the National Cancer Institute. She received a doctoral degree from the University of Toronto, where she studied chemical carcinogenesis in the liver. She was in the pathology department and has a broad background in human disease. Post-graduate training included further studies on the cell cycle during liver regeneration and cancer. |

  17. A Hybrid FEM-ANN Approach for Slope Instability Prediction

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

    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.

  18. Coupling SWAT and ANN models for enhanced daily streamflow prediction

    NASA Astrophysics Data System (ADS)

    Noori, Navideh; Kalin, Latif

    2016-02-01

    To improve daily flow prediction in unmonitored watersheds a hybrid model was developed by combining a quasi-distributed watershed model and artificial neural network (ANN). Daily streamflow data from 29 nearby watersheds in and around the city of Atlanta, Southeastern United States, with leave-one-site-out jackknifing technique were used to build the flow predictive models during warm and cool seasons. Daily streamflow was first simulated with the Soil and Water Assessment Tool (SWAT) and then the SWAT simulated baseflow and stormflow were used as inputs to ANN. Out of the total 29 test watersheds, 62% and 83% of them had Nash-Sutcliffe values above 0.50 during the cool and warm seasons, respectively (considered good or better). As the percent forest cover or the size of test watershed increased, the performances of the models gradually decreased during both warm and cool seasons. This indicates that the developed models work better in urbanized watersheds. In addition, SWAT and SWAT Calibration Uncertainty Procedure (SWAT-CUP) program were run separately for each station to compare the flow prediction accuracy of the hybrid approach to SWAT. Only 31% of the sites during the calibration and 34% of validation runs had ENASH values ⩾0.50. This study showed that coupling ANN with semi-distributed models can lead to improved daily streamflow predictions in ungauged watersheds.

  19. Improved Artificial Neural Network-Pedotransfer Functions (ANN-PTFs) for Estimating Soil Hydraulic Parameters

    NASA Astrophysics Data System (ADS)

    Gautam, M. R.; Zhu, J.; Ye, M.; Meyer, P. D.; Hassan, A. E.

    2008-12-01

    ANN-PTFs have become popular means of mapping easily available soil data into hard-to-measure soil hydraulic parameters in the recent years. These parameters and their distributions are the indispensable inputs to subsurface flow and transport models which provide basis for environmental planning, management and decision making. While improved ANN prediction together with the preservation of probability distributions of hydraulic parameters in ANN training is important, ANN-PTFs have been typically found using conventional ANN training approach with the mean square error as an error function, which may not preserve the probability distribution of the parameters. Moreover, the conventional ANN training can itself introduce correlation among predicted parameters and could not preserve the actual correlation among the measured parameters. The present study describes approaches to deal with such shortcomings of conventional ANN- PTF training algorithms by using new types of error functions and presents a group of improved ANN-PTF models developed on the basis of the new approaches with different levels of data availability. In the study, the bootstrap method is used as part of ANN-PTF development for generating independent training and validation sets, and calculating uncertainty estimates of the ANN predictions. The results demonstrate the merit of the new approaches of the ANN training and the physical significance of various types of less costly soil data in the prediction of soil hydraulic parameters.

  20. Input Variable Selection for Hydrologic Modeling Using Anns

    NASA Astrophysics Data System (ADS)

    Ganti, R.; Jain, A.

    2011-12-01

    The use of artificial neural network (ANN) models in water resources applications has grown considerably over the last couple of decades. In learning problems, where a connectionist network is trained with a finite sized training set, better generalization performance is often obtained when unneeded weights in the network are eliminated. One source of unneeded weights comes from the inclusion of input variables that provide little information about the output variables. Hence, in the ANN modeling methodology, one of the approaches that has received little attention, is the selection of appropriate model inputs. In the past, different methods have been used for identifying and eliminating these input variables. Normally, linear methods of Auto Correlation Function (ACF) and Partial Auto Correlation Function (PACF) have been adopted. For nonlinear physical systems e.g. hydrological systems, model inputs selected based on the linear correlation analysis among input and output variables cannot assure to capture the non-linearity in the system. In the present study, two of the non-linear methods have been explored for the Input Variable Selection (IVS). The linear method employing ACF and PACF is also used for comparison purposes. The first non-linear method utilizes a measure of the Mutual Information Criterion (MIC) to characterize the dependence between a potential model input and the output, which is a step wise input selection procedure. The second non-linear method is improvement over the first method which eliminates redundant inputs based on a partial measure of mutual information criterion (PMIC), which is also a step wise procedure. Further, the number of input variables to be considered for the development of ANN model was determined using the Principal Component Analysis (PCA), which previously used to be done by trial and error approach. The daily river flow data derived from Godavari River Basin @ Polavaram, Andhra Pradesh, India, and the daily average

  1. Groundwater Pollution Source Identification using Linked ANN-Optimization Model

    NASA Astrophysics Data System (ADS)

    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

  2. ANN expert system screening for illicit amphetamines using molecular descriptors

    NASA Astrophysics Data System (ADS)

    Gosav, S.; Praisler, M.; Dorohoi, D. O.

    2007-05-01

    The goal of this study was to develop and an artificial neural network (ANN) based on computed descriptors, which would be able to classify the molecular structures of potential illicit amphetamines and to derive their biological activity according to the similarity of their molecular structure with amphetamines of known toxicity. The system is necessary for testing new molecular structures for epidemiological, clinical, and forensic purposes. It was built using a database formed by 146 compounds representing drugs of abuse (mainly central stimulants, hallucinogens, sympathomimetic amines, narcotics and other potent analgesics), precursors, or derivatized counterparts. Their molecular structures were characterized by computing three types of descriptors: 38 constitutional descriptors (CDs), 69 topological descriptors (TDs) and 160 3D-MoRSE descriptors (3DDs). An ANN system was built for each category of variables. All three networks (CD-NN, TD-NN and 3DD-NN) were trained to distinguish between stimulant amphetamines, hallucinogenic amphetamines, and nonamphetamines. A selection of variables was performed when necessary. The efficiency with which each network identifies the class identity of an unknown sample was evaluated by calculating several figures of merit. The results of the comparative analysis are presented.

  3. Hip Fractures: The St Ann's Bay Regional Hospital Experience

    PubMed Central

    O'Connor, I; McDowell, D; Barnes, D

    2014-01-01

    Objectives: To study the outcome of hip fractures in a cohort of patients from two different time periods (2002–2003 and 2006–2008). Methods: Patients treated for hip fractures at the St Ann's Bay Regional Hospital, which provides orthopaedic care for the parishes of St Ann, St Mary and Portland, were retrospectively analysed between 2002–2003 and 2006–2008. Results: A significant increase in the recorded incidence of hip fractures, from 19 in the 2002–2003 time period to 101 in the 2006–2008 time period was noted. There was a drastic fall in the in-hospital mortality rate (43% in the 2002–2003 time period compared to 4.5% in the 2006–2008 time period). In the 2006–2008 period, 82.9% of patients were ambulant at discharge compared to 36% from the 2002–2003 time period. Conclusion: Early surgical fixation is necessary to allow rapid mobilization in these patients for whom the consequences of bed rest would otherwise be devastating. PMID:25303247

  4. Upper Wisconsinan submarine end moraines off Cape Ann, Massachusetts

    USGS Publications Warehouse

    Oldale, R.N.

    1985-01-01

    Seismic profiles across the southwest end of Jeffreys Ledge, a bathymetric high north of Cape Ann, Massachusetts, reveal two end moraines. The moraines overlie upper Wisconsinan glacialmarine silty clay and are composed mostly of subaqueous ice-contact deposits and outwash. They were formed below sea level in water depths of as much as 120 m during fluctuations of a calving ice front. The moraines are late Wisconsinan in age and were formed after the Cambridge readvance, about 14,000 yr B.P., and before the Kennebunk readvance, about 13,000 yr B.P. They represent fluctuations of the ice front during overall retreat of Laurentide ice from the Gulf of Maine and New England. ?? 1985.

  5. Evaluation of AnnAGNPS in cold and temperate regions.

    PubMed

    Das, S; Rudra, R P; Goel, P K; Gharabaghi, B; Gupta, N

    2006-01-01

    Identification of the pollution sources and understanding the processes related to runoff generation and pollution transportation is effective for the water quality management and selection of the Best Management Practices. The ANNualized AGricultural Non-Point Source (AnnAGNPS) model was applied to a watershed in Southern Ontario to evaluate the hydrology and sediment component from the non-point sources. The model was run for two years (1998 to 1999); one year's data was used to calibrate and the second year's data was used for validation purposes. The model has under predicted runoff amount and over predicted the sediment yield. However, the simulated runoff and sediment yield compared fairly well with the observed data indicating that the model had an acceptable performance in simulation of runoff and sediment. The study is still in progress to assess its performance for estimation of TMDL and improvements needed for the model to use under Ontario conditions. PMID:16594345

  6. A drowned Holocene barrier spit off Cape Ann, Massachusetts

    USGS Publications Warehouse

    Oldale, Robert N.

    1985-01-01

    Seismic profiles and bathymetric contours reveal a drowned barrier spit on Jeffreys Ledge off Cape Ann, Massachusetts. Seaward-dipping internal reflectors indicate that a regressive barrier formed during the early Holocene low sea-level stillstand. Preservation of the barrier spit may have been favored by its large size (as much as 20 m thick), by an ample sediment supply from unconsolidated glacial drift, and by the subsequent rapid sea-level rise. The barrier spit is present in water depths of 50 to 70 m and indicates a low relative sea-level stand of −50 m. This value confirms the low relative sea-level stand of −47 m postulated by Oldale et al. (1983) for northeast Massachusetts and New Hampshire on the basis of the submerged delta of the Merrimack River, and it indicates that the barrier and delta were contemporaneous (Oldale et al., 1983).

  7. Reduction of the number of material parameters by ANN approximation

    NASA Astrophysics Data System (ADS)

    Sumelka, Wojciech; Łodygowski, Tomasz

    2013-08-01

    Modern industrial standards require advanced constitutive modeling to obtain satisfactory numerical results. This approach however, is causing significant increase in number of material parameters which can not be easily obtained from standard and commonly known experimental techniques. Therefore, it is desirable to introduce procedure decreasing the number of the material parameters. This reduction however, should not lead to misunderstanding the fundamental physical phenomena. This paper proposes the reduction of the number of material parameters by using ANN approximation. Recently proposed viscoplasticity formulation for anisotropic solids (metals) developed by authors is used as an illustrative example. In this model one needs to identify 28 material parameters to handle particular metal behaviour under adiabatic conditions as reported by Glema et al (J Theor Appl Mech 48:973-1001, 2010), (Int J Damage Mech 18:205-231, 2009) and Sumelka (Poznan University of Technology, Poznan, 2009). As a result of proposed approach, authors decreased the number of material parameters to 19.

  8. The role of atmospheric stability/turbulence on wakes at the Egmond aan Zee offshore wind farm

    NASA Astrophysics Data System (ADS)

    Barthelmie, R. J.; Churchfield, M. J.; Moriarty, P. J.; Lundquist, J. K.; Oxley, G. S.; Hahn, S.; Pryor, S. C.

    2015-06-01

    The aim of the paper is to present results from the NREL SOWFA project that compares simulations from models of different fidelity to meteorological and turbine data from the Egmond aan Zee wind farm. Initial results illustrate that wake behavior and impacts are strongly impacted by turbulence intensity [1]. This includes both power losses from wakes and loading illustrated by the out of plane bending moment. Here we focus on understanding the relationship between turbulence and atmospheric stability and whether power losses due to wakes can effectively be characterized by measures of turbulence alone or whether atmospheric stability as a whole plays a fundamental role in wake behavior. The study defines atmospheric stability using the Monin-Obukhov length estimated based on the temperature difference between 116 and 70 m. The data subset selected using this method for the calculation of the Monin-Obukhov length indicate little diurnal or directional dependence of the stability classes but a dominance of stable classes in the spring/unstable classes in fall and of near-neutral classes at high wind speeds (Figure 2). The analysis is complicated by the need to define turbulence intensity. We can select the ratio of the standard deviation of wind speed to mean wind speed in each observation period using data from the meteorological mast, in which case a substantial amount of data must be excluded due to the presence of the wind farm. An alternative is to use data from the wind turbines which could provide a larger data set for analysis. These approaches are examined and compared to illustrate their robustness. Finally, power losses from wakes are categorized according to stability and/or turbulence in order to understand their relative importance in determining the behavior of wind turbine wakes.

  9. Applicability of Ann in the ARGO-YBJ experiment

    NASA Astrophysics Data System (ADS)

    Zhu, Q. Q.; Tan, Y. H.; Yang, X. C.; Argo-Ybj Coll.

    We report the applicability of Artificial Neural Networks (ANN) in the ARGO-YBJ data analysis, i.e. inner or outer shower core position identification and γ-proton separation, With the MC samples from Corsika and a standard feed forward neural network, the results indicate that the rejection of outer showers induced by protons is more than 60% and the enhancement in the gamma ray sensitivity is about 37% 1 Motivation The Sino-Italian ARGO-YBJ experiment locates at YangBa-Jing (90o 31'50"E, 30o 6'38"N, 4300m a.s.l.) of Tibet, China. The main goal of the experiment is to search for Very High Energy γ point sources and HE Gamma Ray Bursts. The experimental setup is a coverage RPC carpet with an area of 97m x 103m(D'Ettorre et al., 1999) which consists of 14040 PADs. Each PAD is the detector minimum unit with 8 readout strips (i.e. the maximum number of recorded particles = 8). In order to increase the ratio of signals to noises, we have done a preliminary study on the γ-proton seperation using Artificial Neural Networks(ANN) technique(Bussino 1999). Our further Monte Carlo study indicates that the determination accuracy of event core position will affect the γ-proton identification power significantly and the key point for the determination of event core position is inner or outer event classcification. Here inner (or outer) event means the event real core located inside (or outside) of the central 71m x 74m full coverage carpet. In this note we mainly discuss on the identification power for the two classes of events.

  10. 46 CFR 7.10 - Eastport, ME to Cape Ann, MA.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 46 Shipping 1 2013-10-01 2013-10-01 false Eastport, ME to Cape Ann, MA. 7.10 Section 7.10 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY PROCEDURES APPLICABLE TO THE PUBLIC BOUNDARY LINES Atlantic Coast § 7.10 Eastport, ME to Cape Ann, MA. (a) A line drawn from the easternmost extremity of...

  11. 33 CFR 80.120 - Cape Ann, MA to Marblehead Neck, MA.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false Cape Ann, MA to Marblehead Neck, MA. 80.120 Section 80.120 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Atlantic Coast § 80.120 Cape Ann, MA...

  12. 46 CFR 7.10 - Eastport, ME to Cape Ann, MA.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 46 Shipping 1 2010-10-01 2010-10-01 false Eastport, ME to Cape Ann, MA. 7.10 Section 7.10 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY PROCEDURES APPLICABLE TO THE PUBLIC BOUNDARY LINES Atlantic Coast § 7.10 Eastport, ME to Cape Ann, MA. (a) A line drawn from the easternmost extremity of...

  13. 33 CFR 80.120 - Cape Ann, MA to Marblehead Neck, MA.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 33 Navigation and Navigable Waters 1 2011-07-01 2011-07-01 false Cape Ann, MA to Marblehead Neck, MA. 80.120 Section 80.120 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Atlantic Coast § 80.120 Cape Ann, MA...

  14. 46 CFR 7.10 - Eastport, ME to Cape Ann, MA.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 46 Shipping 1 2014-10-01 2014-10-01 false Eastport, ME to Cape Ann, MA. 7.10 Section 7.10 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY PROCEDURES APPLICABLE TO THE PUBLIC BOUNDARY LINES Atlantic Coast § 7.10 Eastport, ME to Cape Ann, MA. (a) A line drawn from the easternmost extremity of...

  15. 33 CFR 80.120 - Cape Ann, MA to Marblehead Neck, MA.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 33 Navigation and Navigable Waters 1 2013-07-01 2013-07-01 false Cape Ann, MA to Marblehead Neck, MA. 80.120 Section 80.120 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Atlantic Coast § 80.120 Cape Ann, MA...

  16. 33 CFR 80.120 - Cape Ann, MA to Marblehead Neck, MA.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 33 Navigation and Navigable Waters 1 2012-07-01 2012-07-01 false Cape Ann, MA to Marblehead Neck, MA. 80.120 Section 80.120 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Atlantic Coast § 80.120 Cape Ann, MA...

  17. 33 CFR 80.120 - Cape Ann, MA to Marblehead Neck, MA.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 33 Navigation and Navigable Waters 1 2014-07-01 2014-07-01 false Cape Ann, MA to Marblehead Neck, MA. 80.120 Section 80.120 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Atlantic Coast § 80.120 Cape Ann, MA...

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

    ERIC Educational Resources Information Center

    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…

  19. 75 FR 12563 - Patuxent Research Refuge, Anne Arundel and Prince George's Counties, MD

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-03-16

    ... Fish and Wildlife Service Patuxent Research Refuge, Anne Arundel and Prince George's Counties, MD... process for developing a CCP for Patuxent Research Refuge, in Anne Arundel and Prince George's Counties... the Patuxent and Little Patuxent Rivers between Washington, DC, and Baltimore, Maryland, the...

  20. Evaluation of the use of remotely sensed evapotranspiration estimates into AnnAGNPS pollution model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The utilization of evapotranspiration (ET) estimates, derived from satellite remote sensing, into the Annualized Agricultural Non-Point Source (AnnAGNPS) pollution model was investigated. Modifications within AnnAGNPS were performed to allow the internal calculations of ET based on climate parameter...

  1. Modification of an RBF ANN-Based Temperature Compensation Model of Interferometric Fiber Optical Gyroscopes

    PubMed Central

    Cheng, Jianhua; Qi, Bing; Chen, Daidai; Jr. Landry, René

    2015-01-01

    This paper presents modification of Radial Basis Function Artificial Neural Network (RBF ANN)-based temperature compensation models for Interferometric Fiber Optical Gyroscopes (IFOGs). Based on the mathematical expression of IFOG output, three temperature relevant terms are extracted, which include: (1) temperature of fiber loops; (2) temperature variation of fiber loops; (3) temperature product term of fiber loops. Then, the input-modified RBF ANN-based temperature compensation scheme is established, in which temperature relevant terms are transferred to train the RBF ANN. Experimental temperature tests are conducted and sufficient data are collected and post-processed to form the novel RBF ANN. Finally, we apply the modified RBF ANN based on temperature compensation model in two IFOGs with temperature compensation capabilities. The experimental results show the proposed temperature compensation model could efficiently reduce the influence of environment temperature on the output of IFOG, and exhibit a better temperature compensation performance than conventional scheme without proposed improvements. PMID:25985163

  2. ANN Models for Prediction of Sound and Penetration Rate in Percussive Drilling

    NASA Astrophysics Data System (ADS)

    Kivade, Sangshetty B.; Murthy, Chivukula Surya Naryana; Vardhan, Harsha

    2015-10-01

    In the recent years, new techniques such as; Artificial Neural Network (ANN) were employed for developing of the predictive models to estimate the needed parameters. Soft computing techniques are now being used as alternate statistical tool. In this study, ANN models were developed to predict rock properties of sedimentary rock, by using penetration and sound level produced during percussive drilling. The data generated in the laboratory investigation was utilized for the development of ANN models for predicting rock properties like, uniaxial compressive strength, abrasivity, tensile strength, and Schmidt rebound number using air pressure, thrust, bit diameter, penetration rate and sound level. Further, ANN models were also developed for predicting penetration rate and sound level using air pressure, thrust, bit diameter and rock properties as input parameters. The constructed models were checked using various prediction performance indices. ANN models were more acceptable for predicting rock properties.

  3. iAnn: an event sharing platform for the life sciences

    PubMed Central

    Jimenez, Rafael C.; Albar, Juan P.; Bhak, Jong; Blatter, Marie-Claude; Blicher, Thomas; Brazas, Michelle D.; Brooksbank, Cath; Budd, Aidan; De Las Rivas, Javier; Dreyer, Jacqueline; van Driel, Marc A.; Dunn, Michael J.; Fernandes, Pedro L.; van Gelder, Celia W. G.; Hermjakob, Henning; Ioannidis, Vassilios; Judge, David P.; Kahlem, Pascal; Korpelainen, Eija; Kraus, Hans-Joachim; Loveland, Jane; Mayer, Christine; McDowall, Jennifer; Moran, Federico; Mulder, Nicola; Nyronen, Tommi; Rother, Kristian; Salazar, Gustavo A.; Schneider, Reinhard; Via, Allegra; Villaveces, Jose M.; Yu, Ping; Schneider, Maria V.; Attwood, Teresa K.; Corpas, Manuel

    2013-01-01

    Summary: We present iAnn, an open source community-driven platform for dissemination of life science events, such as courses, conferences and workshops. iAnn allows automatic visualisation and integration of customised event reports. A central repository lies at the core of the platform: curators add submitted events, and these are subsequently accessed via web services. Thus, once an iAnn widget is incorporated into a website, it permanently shows timely relevant information as if it were native to the remote site. At the same time, announcements submitted to the repository are automatically disseminated to all portals that query the system. To facilitate the visualization of announcements, iAnn provides powerful filtering options and views, integrated in Google Maps and Google Calendar. All iAnn widgets are freely available. Availability: http://iann.pro/iannviewer Contact: manuel.corpas@tgac.ac.uk PMID:23742982

  4. Daily reservoir inflow forecasting combining QPF into ANNs model

    NASA Astrophysics Data System (ADS)

    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.

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

    SciTech Connect

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

    2011-01-17

    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.

  6. ANN application for prediction of atmospheric nitrogen deposition to aquatic ecosystems.

    PubMed

    Palani, Sundarambal; Tkalich, Pavel; Balasubramanian, Rajasekhar; Palanichamy, Jegathambal

    2011-06-01

    The occurrences of increased atmospheric nitrogen deposition (ADN) in Southeast Asia during smoke haze episodes have undesired consequences on receiving aquatic ecosystems. A successful prediction of episodic ADN will allow a quantitative understanding of its possible impacts. In this study, an artificial neural network (ANN) model is used to estimate atmospheric deposition of total nitrogen (TN) and organic nitrogen (ON) concentrations to coastal aquatic ecosystems. The selected model input variables were nitrogen species from atmospheric deposition, Total Suspended Particulates, Pollutant Standards Index and meteorological parameters. ANN models predictions were also compared with multiple linear regression model having the same inputs and output. ANN model performance was found relatively more accurate in its predictions and adequate even for high-concentration events with acceptable minimum error. The developed ANN model can be used as a forecasting tool to complement the current TN and ON analysis within the atmospheric deposition-monitoring program in the region. PMID:21481425

  7. ANN hybrid model versus ARIMA and ARIMAX models of runoff coefficient

    NASA Astrophysics Data System (ADS)

    Pektaş, Ali Osman; Kerem Cigizoglu, H.

    2013-09-01

    In this study, monthly runoff coefficients of seven southern large basins are calculated and modeled to forecast a holdout dataset by using univariate autoregressive integrated moving average (ARIMA), multivariate ARIMA (ARIMAX), and Artificial neural network (ANN) models. The applied traditional model performances are found insufficient, since the characteristic behaviors of the time series of direct runoff coefficients are very complicated. Therefore, a new Hybrid approach is adopted by using time series decomposition procedure and ANN. ARIMA, ARIMAX, ANN, and Hybrid models are compared with each other. The results indicate that the new generated Hybrid approach can be generalized to boost the prediction capability of ANNs in complicated time series data. It is seen that the new model captures the physical behavior of the direct runoff coefficient time series. The semi-random spikes of the direct runoff coefficient series are approximated sufficiently.

  8. Monitoring and ANN modeling of coal stockpile behavior under different atmospheric conditions

    SciTech Connect

    Ozdeniz, A.H.; Ozbay, Y.; Yilmaz, N.; Sensogut, C.

    2008-07-01

    In this study, an industrial-sized stockpile of 5 m width, 4 m height, and 10 m length was built in a coal stock area to investigate coal stockpile behavior under different atmospheric conditions. The effective parameters on the coal stockpile that were time, weather temperature, atmospheric pressure, air humidity, velocity, and direction of wind values were automatically measured by means of a computer-aided measurement system to obtain Artificial Neural Network (ANN) input data. The coal stockpiles, which should be continuously observed, are capable of spontaneous combustion and then causing serious economical losses due to the mentioned parameters. Afterwards, these measurement values were used for training and testing of the ANN model. Comparison of the experimental and ANN results, accuracy rates of training, and testing were found as 98.6% and 98.7%, respectively. It is shown that possible coal stockpile behavior with this ANN model is powerfully estimated.

  9. A Poem Is a House for Words: NCTE Profiles Mary Ann Hoberman

    ERIC Educational Resources Information Center

    McClure, Amy A.; Ernst, Shirley B.

    2004-01-01

    A profile of Mary Ann Hoberman, the 13th winner of the NCTE Award for Excellence in Poetry for Children is given. She uses poetic techniques in innovative ways, yet her poems are very accessible to young children.

  10. 4. JoAnn SieburgBaker, Photographer, September 1977. VIEW OF POWER BUILDING ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    4. JoAnn Sieburg-Baker, Photographer, September 1977. VIEW OF POWER BUILDING (ELECTRICAL TRANSFORMER). - Salem Manufacturing Company, Arista Cotton Mill, Brookstown & Marshall Streets, Winston-Salem, Forsyth County, NC

  11. Fiber nonlinearity-induced penalty reduction in CO-OFDM by ANN-based nonlinear equalization.

    PubMed

    Giacoumidis, Elias; Le, Son T; Ghanbarisabagh, Mohammad; McCarthy, Mary; Aldaya, Ivan; Mhatli, Sofien; Jarajreh, Mutsam A; Haigh, Paul A; Doran, Nick J; Ellis, Andrew D; Eggleton, Benjamin J

    2015-11-01

    We experimentally demonstrate ∼2  dB quality (Q)-factor enhancement in terms of fiber nonlinearity compensation of 40  Gb/s 16 quadrature amplitude modulation coherent optical orthogonal frequency-division multiplexing at 2000 km, using a nonlinear equalizer (NLE) based on artificial neural networks (ANN). Nonlinearity alleviation depends on escalation of the ANN training overhead and the signal bit rate, reporting ∼4  dBQ-factor enhancement at 70  Gb/s, whereas a reduction of the number of ANN neurons annihilates the NLE performance. An enhanced performance by up to ∼2  dB in Q-factor compared to the inverse Volterra-series transfer function NLE leads to a breakthrough in the efficiency of ANN. PMID:26512532

  12. Application of artificial neural networks (ANN) in the development of solid dosage forms.

    PubMed

    Bourquin, J; Schmidli, H; van Hoogevest, P; Leuenberger, H

    1997-05-01

    The application of ANN in pharmaceutical development has been assessed using theoretical as well as typical pharmaceutical technology examples. The aim was to quantitatively describe the achieved data fitting and predicting abilities of the models developed with a view to using ANN in the development of solid dosage forms. The comparison between the ANN and a traditional statistical (i.e., response surface methodology, RSM) modeling technique was carried out using the squared correlation coefficient R2. Using a highly nonlinear arbitrary function the ANN models showed better fitting (R2 = 0.931 vs. R2 = 0.424) as well as predicting (R2 = 0.810 vs. R2 = 0.547) abilities. Experimental data from a tablet compression study were fitted using two types of ANN models (i.e., multilayer perceptrons and a hybrid network composed of a self-organising feature map joined to a multilayer perception). The achieved data fitting was comparable for the three methods (MLP R2 = 0.911, SOFM-MLP R2 = 0.850, and RSM R2 = 0.897). ANN methodology represents a promising modeling technique when applied to pharmaceutical technology data sets. PMID:9552437

  13. RegnANN: Reverse Engineering Gene Networks Using Artificial Neural Networks

    PubMed Central

    Grimaldi, Marco; Visintainer, Roberto; Jurman, Giuseppe

    2011-01-01

    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. PMID:22216103

  14. Damage detection and identification in smart structures using SVM and ANN

    NASA Astrophysics Data System (ADS)

    Farooq, M.; Zheng, H.; Nagabhushana, A.; Roy, S.; Burkett, S.; Barkey, M.; Kotru, S.; Sazonov, E.

    2012-04-01

    A critical part of structural health monitoring is accurate detection of damages in the structure. This paper presents the results of two multi-class damage detection and identification approaches based on classification using Support Vector Machine (SVM) and Artificial Neural Networks (ANN). The article under test was a fiber composite panel modeled by a Finite Element Model (FEM). Static strain data were acquired at 6 predefined locations and mixed with Gaussian noise to simulate performance of real strain sensors. Strain data were then normalized by the mean of the strain values. Two experiments were performed for the performance evaluation of damage detection and identification. In both experiments, one healthy structure and two damaged structures with one and two small cracks were simulated with varying material properties and loading conditions (45 cases for each structure). The SVM and ANN models were trained with 70% of these samples and the remaining 30% samples were used for validation. The objective of the first experiment was to detect whether or not the panel was damaged. In this two class problem the average damage detection accuracy for ANN and SVM were 93.2% and 96.66% respectively. The objective of second experiment was to detect the severity of the damage by differentiating between structures with one crack and two cracks. In this three class problem the average prediction accuracy for ANN and SVM were 83.5% and 90.05% respectively. These results suggest that for noisy data, SVM may perform better than ANN for this problem.

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

    NASA Astrophysics Data System (ADS)

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

    2010-10-01

    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 & 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.

  16. Chromatic analysis of burn scar based on ANN by using photoelectrical technology

    NASA Astrophysics Data System (ADS)

    Wan, Baikun; Qi, Hongzhi; Ming, Dong; Zhang, Mingjian; Wang, Qifang

    2005-01-01

    In this paper a novel method for the chromatic analysis of burn scar is proposed. The aim of the algorithm is to evaluate the curative effect and set up the treatment plan pertinently, because the scar color is an impersonal parameter reflects the degree of scar hypertrophy. The method is based on artificial neural network (ANN) by using photoelectrical technique, and composed of three main parts: firstly capture the digital color images of the burn scar using CCD camera, then change the RGB color data of the burn scar into that of HSB color space and emend it using ANN, lastly judge the degree of burn scar hypertrophy by chromatic analysis using ANN again. The experimental results were good conformed to the degrees of scar hypertrophy given by clinical evaluations. It suggests that the chromatic analysis technique of the burn scar is valuable for further study and apply to the clinical engineering.

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

    PubMed

    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. PMID:23261404

  18. Modeling and forecasting of KLCI weekly return using WT-ANN integrated model

    NASA Astrophysics Data System (ADS)

    Liew, Wei-Thong; Liong, Choong-Yeun; Hussain, Saiful Izzuan; Isa, Zaidi

    2013-04-01

    The forecasting of weekly return is one of the most challenging tasks in investment since the time series are volatile and non-stationary. In this study, an integrated model of wavelet transform and artificial neural network, WT-ANN is studied for modeling and forecasting of KLCI weekly return. First, the WT is applied to decompose the weekly return time series in order to eliminate noise. Then, a mathematical model of the time series is constructed using the ANN. The performance of the suggested model will be evaluated by root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE). The result shows that the WT-ANN model can be considered as a feasible and powerful model for time series modeling and prediction.

  19. Estimating Parameters of Delaminations in GRP Pipes Using Thermal NDE and ANN

    SciTech Connect

    Vijayaraghavan, G. K.; Ramachandran, K. P.; Muruganandam, A.; Govindarajan, L.; Majumder, M. C.

    2010-10-26

    Thermographic Non-Destructive Evaluation (TNDE) is one of the techniques that have been widely used over the decades to evaluate the integrity of structures. To meet the increased demand for robust and effective inspection in complex TNDE tasks, Artificial Neural Networks (ANNs) have been recently deployed in many problems. The aim of the paper is to adopt an inverse technique using ANNs in the field of TNDE to estimate various parameters of delamination in Glass Reinforced Polymer (GRP) pipes by supplying thermal contrast evolution data as input. A Radial Basis Network (RBN) is employed with 80 input and 3 output neurons. The estimation capability of the network was evaluated with the data obtained from numerical simulations. The overall absolute errors show that the estimation capability of ANN is good.

  20. Wavelet and ANN combination model for prediction of daily suspended sediment load in rivers.

    PubMed

    Rajaee, Taher

    2011-07-01

    In this research, a new wavelet artificial neural network (WANN) model was proposed for daily suspended sediment load (SSL) prediction in rivers. In the developed model, wavelet analysis was linked to an artificial neural network (ANN). For this purpose, daily observed time series of river discharge (Q) and SSL in Yadkin River at Yadkin College, NC station in the USA were decomposed to some sub-time series at different levels by wavelet analysis. Then, these sub-time series were imposed to the ANN technique for SSL time series modeling. To evaluate the model accuracy, the proposed model was compared with ANN, multi linear regression (MLR), and conventional sediment rating curve (SRC) models. The comparison of prediction accuracy of the models illustrated that the WANN was the most accurate model in SSL prediction. Results presented that the WANN model could satisfactorily simulate hysteresis phenomenon, acceptably estimate cumulative SSL, and reasonably predict high SSL values. PMID:21546062

  1. ANN-Assisted Planning of Conjunctive Use of Canal and Ground Water in Canal Commands

    NASA Astrophysics Data System (ADS)

    Kashyap, Deepak; Ghosh, Susmita

    2010-05-01

    Presented herein is an algorithm for ANN-assisted planning of the optimal cropping pattern and the associated groundwater development in a canal command area, followed by an illustration. The planning in the illustration ensures the maximization of the cropped area subject to the constraint of limiting the maximum water table depth to an acceptable limit. A multilayer feed forward ANN model, relating the maximum water table depth to the crop areas, is trained using back-propagation learning algorithm. The data invoked for the training comprise an array of the cropping patterns, and the corresponding maximum water table depths. These data are generated through a pre-calibrated numerical model of groundwater flow. Subsequently, the trained ANN model is linked to a GA based optimizer for arriving at the optimal cropping pattern and the associated pumping pattern.

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

    PubMed Central

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

    2013-01-01

    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. PMID:23261404

  3. PkANN: Non-Linear Matter Power Spectrum Interpolation through Artificial Neural Networks

    NASA Astrophysics Data System (ADS)

    Agarwal, Shankar

    We investigate the interpolation of power spectra of matter fluctuations using artificial neural networks (ANNs). We present a new approach to confront small-scale non-linearities in the matter power spectrum. This ever-present and pernicious uncertainty is often the Achilles' heel in cosmological studies and must be reduced if we are to see the advent of precision cosmology in the late-time Universe. We detail how an accurate interpolation of the matter power spectrum is achievable with only a sparsely sampled grid of cosmological parameters. We show that an optimally trained ANN, when presented with a set of cosmological parameters (Omh2 , Obh2, ns, w0, sigma8, sum mnu and z), can provide a worst-case error ≤ 1 per cent (for redshift z ≤ 2) fit to the non-linear matter power spectrum deduced through large-scale N-body simulations, for modes up to k ≤ 0.9 hMpc-1 . Our power spectrum interpolator, which we label 'PkANN', is designed to simulate a range of cosmological models including massive neutrinos and dark energy equation of state w 0 ≠ -1. PkANN is accurate in the quasi-non-linear regime (0.1 hMpc-1 ≤ k ≤ 0.9 hMpc -1) over the entire parameter space and marks a significant improvement over some of the current power spectrum calculators. The response of the power spectrum to variations in the cosmological parameters is explored using PkANN. Using a compilation of existing peculiar velocity surveys, we investigate the cosmic Mach number statistic and show that PkANN not only successfully accounts for the non-linear motions on small scales, but also, unlike N-body simulations which are computationally expensive and/or infeasible, it can be an extremely quick and reliable tool in interpreting cosmological observations and testing theories of structure-formation.

  4. Multi-output ANN Model for Prediction of Seven Meteorological Parameters in a Weather Station

    NASA Astrophysics Data System (ADS)

    Raza, Khalid; Jothiprakash, V.

    2014-12-01

    The meteorological parameters plays a vital role for determining various water demand in the water resource systems, planning, management and operation. Thus, accurate prediction of meteorological variables at different spatial and temporal intervals is the key requirement. Artificial Neural Network (ANN) is one of the most widely used data driven modelling techniques with lots of good features like, easy applications, high accuracy in prediction and to predict the multi-output complex non-linear relationships. In this paper, a Multi-input Multi-output (MIMO) ANN model has been developed and applied to predict seven important meteorological parameters, such as maximum temperature, minimum temperature, relative humidity, wind speed, sunshine hours, dew point temperature and evaporation concurrently. Several types of ANN, such as multilayer perceptron, generalized feedforward neural network, radial basis function and recurrent neural network with multi hidden layer and varying number of neurons at the hidden layer, has been developed, trained, validated and tested. From the results, it is found that the recurrent MIMO-ANN having 28 neurons in a single hidden layer, trained using hyperbolic tangent transfer function with a learning rate of 0.3 and momentum factor of 0.7 performed well over the other types of MIMO-ANN models. The MIMO ANN model performed well for all parameters with higher correlation and other performance indicators except for sunshine hours. Due to erratic nature, the importance of each of the input over the output through sensitivity analysis indicated that relative humidity has highest influence while others have equal influence over the output.

  5. A multi-stage methodology for selecting input variables in ANN forecasting flows

    NASA Astrophysics Data System (ADS)

    Panagoulia, Dionysia; Tsekouras, George; Kousiouris, George

    2016-04-01

    Recently, several methods have more or less efficiently dealt with the selection of input variables to artificial neural networks (ANNs) in the hydrology and water resources domain. While the ultimate purpose is to approximate an effective and computationally parsimonious method accounting for non linear input variables to ANNs, very few approaches could reach this target. Moreover, none of these has considered the seasonality as input to ANNs which may be attributed to the influence of natural or anthropogenic variability to hydro-meteorological time series. To this end, a novel methodology is developed for selecting input variables used in artificial neural network (ANNs) models for flow forecasting. The proposed methodology is generic, multi-stage and makes use of data correlations together with a set of crucial statistical indices for optimizing model performance, both in terms of ANN structure (e.g. neurons, momentum rate, learning rate, activation functions) but also in terms of inputs selection. Daily areal precipitation and temperature data coupled with atmospheric circulation in the form of circulation patterns, observed river flow data, and time expressed via functions of sine and cosine (seasonality) were the potential vectors for inputs selection. The historical data concern the mountainous Mesochora catchment in Central-Western Greece. The proposed methodology revealed the river flow of past four days, the precipitation of past three days and the seasonality as robust input variables. However, the temperature of three past days should be considered as an alternative against the seasonality. The produced models forecasting ability was validated by comparing its one-step ahead flow prediction ability to two other approaches (an auto regressive model and a GA-optimized single input ANN).

  6. How can we deal with ANN in flood forecasting? As a simulation model or updating kernel!

    NASA Astrophysics Data System (ADS)

    Hassan Saddagh, Mohammad; Javad Abedini, Mohammad

    2010-05-01

    Flood forecasting and early warning, as a non-structural measure for flood control, is often considered to be the most effective and suitable alternative to mitigate the damage and human loss caused by flood. Forecast results which are output of hydrologic, hydraulic and/or black box models should secure accuracy of flood values and timing, especially for long lead time. The application of the artificial neural network (ANN) in flood forecasting has received extensive attentions in recent years due to its capability to capture the dynamics inherent in complex processes including flood. However, results obtained from executing plain ANN as simulation model demonstrate dramatic reduction in performance indices as lead time increases. This paper is intended to monitor the performance indices as it relates to flood forecasting and early warning using two different methodologies. While the first method employs a multilayer neural network trained using back-propagation scheme to forecast output hydrograph of a hypothetical river for various forecast lead time up to 6.0 hr, the second method uses 1D hydrodynamic MIKE11 model as forecasting model and multilayer neural network as updating kernel to monitor and assess the performance indices compared to ANN alone in light of increase in lead time. Results presented in both graphical and tabular format indicate superiority of MIKE11 coupled with ANN as updating kernel compared to ANN as simulation model alone. While plain ANN produces more accurate results for short lead time, the errors increase expeditiously for longer lead time. The second methodology provides more accurate and reliable results for longer forecast lead time.

  7. Understanding Anne Frank's "The Diary of a Young Girl": A Student Casebook to Issues, Sources, and Historical Documents.

    ERIC Educational Resources Information Center

    Kopf, Hedda Rosner

    Anne Frank's "The Diary of a Young Girl" is the most widely read text about the Holocaust, yet it represents only one example of the tragic consequences of the Nazi policy to eliminate the Jews of Europe during World War II. This casebook enriches Anne Frank's remarkable personal account with a variety of historical documents that illuminate the…

  8. Overexpression of a cotton annexin gene, GhAnn1, enhances drought and salt stress tolerance in transgenic cotton.

    PubMed

    Zhang, Feng; Li, Shufen; Yang, Shuming; Wang, Like; Guo, Wangzhen

    2015-01-01

    Plant annexins are members of a diverse, multigene protein family that has been associated with a variety of cellular processes and responses to abiotic stresses. GhAnn1, which encodes a putative annexin protein, was isolated from a cotton (Gossypium hirsutum L. acc 7235) cDNA library. Tissue-specific expression showed that GhAnn1 is expressed at differential levels in all tissues examined and strongly induced by various phytohormones and abiotic stress. In vivo and in vitro subcellular localization suggested that GhAnn1 is located in the plasma membrane. In response to drought and salt stress, transgenic cotton plants overexpressing GhAnn1 showed significantly higher germination rates, longer roots, and more vigorous growth than wild-type plants. In addition, plants overexpressing GhAnn1 had higher total chlorophyll content, lower lipid peroxidation levels, increased peroxidase activities, and higher levels of proline and soluble sugars, all of which contributed to increased salt and drought stress tolerance. However, transgenic cotton plants in which the expression of GhAnn1 was suppressed showed the opposite results compared to the overexpressing plants. These findings demonstrated that GhAnn1 plays an important role in the abiotic stress response, and that overexpression of GhAnn1 in transgenic cotton improves salt and drought tolerance. PMID:25330941

  9. The influence of emerging administrative scientists: an interview with Anne Miller.

    PubMed

    Miller, Anne; Adams, Jeffrey M

    2015-04-01

    This department highlights emerging nursing leaders and scientists demonstrating promise in advancing innovation and patient care leadership in practice, policy, research, education, and theory. This interview profiles Anne Miller, PhD, BA, assistant professor jointly appointed to the Center of Interdisciplinary Health Workforce Studies and the School of Nursing at Vanderbilt University Medical Center. PMID:25803799

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

    ERIC Educational Resources Information Center

    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…

  11. Constructing Anne Frank: Critical Literacy and the Holocaust in Eighth-Grade English

    ERIC Educational Resources Information Center

    Spector, Karen; Jones, Stephanie

    2007-01-01

    Using the assumption that texts actively work to position readers and readers actively work to position texts, the authors argue that moral lessons emerge from the interactions between texts, readers, and the ideological narratives that inspire both. After differentiating versions of Anne Frank's diary and explicating motives behind their…

  12. Should You Teach "Anne Frank: The Diary of a Young Girl"?

    ERIC Educational Resources Information Center

    Rochman, Hazel

    1998-01-01

    Considers the value of teaching "Anne Frank" and suggests that the book be just a starting point for exposing readers to other views of the Holocaust. Annotated bibliographies are included for other personal accounts of the Holocaust, with appropriate grade levels indicated. (LRW)

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

    ERIC Educational Resources Information Center

    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 Jung was…

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

    ERIC Educational Resources Information Center

    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)

  15. Childhood and Modernity: Dark Themes in Carol Ann Duffy's Poetry for Children

    ERIC Educational Resources Information Center

    Whitley, David

    2007-01-01

    Carol Ann Duffy's three volumes of children's poetry are important and interesting because they emerge from the work of a writer whose adult poetry has persistently associated childhood with dark and difficult areas of experience. This article explores what happens to such challenging material when a poet of major significance changes the focus of…

  16. 33 CFR 80.115 - Portland Head, ME to Cape Ann, MA.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 33 Navigation and Navigable Waters 1 2011-07-01 2011-07-01 false Portland Head, ME to Cape Ann, MA. 80.115 Section 80.115 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY..., MA. (a) Except inside lines specifically described in this section, the 72 COLREGS shall apply on...

  17. 33 CFR 80.115 - Portland Head, ME to Cape Ann, MA.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 33 Navigation and Navigable Waters 1 2013-07-01 2013-07-01 false Portland Head, ME to Cape Ann, MA. 80.115 Section 80.115 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY..., MA. (a) Except inside lines specifically described in this section, the 72 COLREGS shall apply on...

  18. 33 CFR 80.115 - Portland Head, ME to Cape Ann, MA.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false Portland Head, ME to Cape Ann, MA. 80.115 Section 80.115 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY..., MA. (a) Except inside lines specifically described in this section, the 72 COLREGS shall apply on...

  19. 33 CFR 80.115 - Portland Head, ME to Cape Ann, MA.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 33 Navigation and Navigable Waters 1 2012-07-01 2012-07-01 false Portland Head, ME to Cape Ann, MA. 80.115 Section 80.115 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY..., MA. (a) Except inside lines specifically described in this section, the 72 COLREGS shall apply on...

  20. 33 CFR 80.115 - Portland Head, ME to Cape Ann, MA.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 33 Navigation and Navigable Waters 1 2014-07-01 2014-07-01 false Portland Head, ME to Cape Ann, MA. 80.115 Section 80.115 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY..., MA. (a) Except inside lines specifically described in this section, the 72 COLREGS shall apply on...

  1. Master Builder of Bridges between Research and Practice: An Interview with Ann Robinson

    ERIC Educational Resources Information Center

    Henshon, Suzanna E.

    2010-01-01

    This article presents an interview with Ann Robinson, a professor of educational psychology and founding director of the Center for Gifted Education at the University of Arkansas at Little Rock. She is the president of the National Association for Gifted Children (NAGC), a former editor of the Gifted Child Quarterly (GCQ), and was the first Editor…

  2. USDA-AnnAGNPS Model Capabilities and Applications for Watershed Conservation Planning

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The US Department of Agriculture (USDA) Annualized Agricultural Non-Point Source Pollutant Loading (AnnAGNPS) model has been developed as a planning tool used in the evaluation of watershed responses to agricultural management practices. Since the first release of the continuous, daily time step, w...

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

    NASA Astrophysics Data System (ADS)

    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.

  4. A Case Study of the Ann Sullivan Center in Lima, Peru

    ERIC Educational Resources Information Center

    Noto, Lori A.

    2005-01-01

    A qualitative study was conducted to describe and explain the educational program at the Ann Sullivan Center, a nationally and internationally recognized program for individuals with disabilities in Peru. The program provides educational programming to individuals with autism, severe disabilities and challenging behaviors across the lifespan. A…

  5. 77 FR 61624 - Patuxent Research Refuge, Prince George's and Anne Arundel Counties, MD; Draft Comprehensive...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-10-10

    ... Federal Register (75 FR 12563; March 16, 2010). Patuxent RR was established in 1936 by Executive Order by... Fish and Wildlife Service Patuxent Research Refuge, Prince George's and Anne Arundel Counties, MD... environmental assessment (CCP/EA) for Patuxent Research Refuge (Patuxent RR), located in Prince George's...

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

    ERIC Educational Resources Information Center

    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 writer. Over…

  7. Audits of Meaning: A Festschrift in Honor of Ann E. Berthoff.

    ERIC Educational Resources Information Center

    Smith, Louise Z., Ed.

    A tribute to the work of Ann Berthoff, this book--a collection of 6 poems and 21 essays--explores issues in the philosophy and teaching of composition. Each of the five sections is introduced with a poem by Marie Ponsot. Essays and their authors consist of (1) "Genre Theory, Academic Discourse, and Writing within Disciplines" (James F. Slevin);…

  8. The Search for Family: Comedy and Pathos in Anne Tyler's Later Novels.

    ERIC Educational Resources Information Center

    Zoghby, Mary D.

    Anne Tyler's rare talent for combining comedy and pathos enables her to create characters whose pain is felt by the reader or student even as that same reader is led into laughter by the ludicrous situations in which Tyler places these characters. In her last three novels, "Dinner at the Homesick Restaurant,""The Accidental Tourist," and…

  9. Bethany Ann Teachman: Award for Distinguished Scientific Early Career Contributions to Psychology

    ERIC Educational Resources Information Center

    American Psychologist, 2012

    2012-01-01

    Presents a short biography of one of the winners of the American Psychological Association's Award for Distinguished Scientific Early Career Contributions to Psychology. The 2012 winner is Bethany Ann Teachman for transformative, translational research integrating social cognition, life-span, and perceptual approaches to investigating clinical…

  10. 78 FR 41993 - Ann Arbor Railroad, Inc.-Lease Exemption-Norfolk Southern Railway Company

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-07-12

    ... Surface Transportation Board Ann Arbor Railroad, Inc.--Lease Exemption--Norfolk Southern Railway Company... authority to determine whether to issue notices of exemption under 49 U.S.C. 10502 for lease and operation... for lease and operation of the rail line at issue in this case. The Board determines that this...

  11. 78 FR 67086 - Safety Zone, Submarine Cable Replacement Operations, Kent Island Narrows; Queen Anne's County, MD

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-11-08

    ...The Coast Guard proposes to establish a temporary safety zone encompassing certain waters of Kent Island Narrows in Queen Anne's County, MD. This action is necessary to provide for the safety of mariners and their vessels on navigable waters during submarine cable replacement operations at the Kent Island Narrows (MD-18B) Bridge. This action is intended to restrict vessel traffic movement to......

  12. Application of ANN to evaluate effective parameters affecting failure load and displacement of RC buildings

    NASA Astrophysics Data System (ADS)

    Hakan Arslan, M.

    2009-06-01

    This study investigated the efficiency of an artificial neural network (ANN) in predicting and determining failure load and failure displacement of multi story reinforced concrete (RC) buildings. The study modeled a RC building with four stories and three bays, with a load bearing system composed of columns and beams. Non-linear static pushover analysis of the key parameters in change defined in Turkish Earthquake Code (TEC-2007) for columns and beams was carried out and the capacity curves, failure loads and displacements were obtained. Totally 720 RC buildings were analyzed according to the change intervals of the parameters chosen. The input parameters were selected as longitudinal bar ratio (ρl) of columns, transverse reinforcement ratio (Asw/sc), axial load level (N/No), column and beam cross section, strength of concrete (fc) and the compression bar ratio (ρ'/ρ) on the beam supports. Data from the nonlinear analysis were assessed with ANN in terms of failure load and failure displacement. For all outputs, ANN was trained and tested using of 11 back-propagation methods. All of the ANN models were found to perform well for both failure loads and displacements. The analyses also indicated that a considerable portion of existing RC building stock in Turkey may not meet the safety standards of the Turkish Earthquake Code (TEC-2007).

  13. Optimization of culture medium and modeling of curdlan production from Paenibacillus polymyxa by RSM and ANN.

    PubMed

    Rafigh, Sayyid Mahdi; Yazdi, Ali Vaziri; Vossoughi, Manouchehr; Safekordi, Ali Akbar; Ardjmand, Mehdi

    2014-09-01

    Paenibacillus polymyxa ATCC 21830 was used for the production of curdlan gum for first time. A Box-Behnken experimental design was applied to optimize six variables of batch fermentation culture each at three levels. Statistical analyses were employed to investigate the direct and interactive effects of variables on curdlan production. Optimum cultural conditions were temperature (50°C), pH (7), fermentation time (96 h), glucose (100 g/L), yeast extract (3 g/L) and agitation speed (150 rpm). The yield of curdlan production was 6.89 g/L at optimum condition medium. Response surface methodology (RSM) and artificial neural network (ANN) were used to model cultural conditions of curdlan production. The maximum yield of curdlan production were predicted to be 6.68 and 6.85 g/L by RSM and ANN at optimum condition. The prediction capabilities of RSM and ANN were then statistically compared. The results showed that the ANN model is much more accurate in prediction as compared to the RSM. The infrared (IR) and NMR spectra, the thermogram of DSC and pattern of X-ray diffraction for the curdlan of the present study were almost identical to those of the commercial curdlan sample. The average molecular weight of the purified curdlan was determined to be 170 kDa by gel permeation chromatography. PMID:25062991

  14. Application of ANN and fuzzy logic algorithms for streamflow modelling of Savitri catchment

    NASA Astrophysics Data System (ADS)

    Kothari, Mahesh; Gharde, K. D.

    2015-07-01

    The streamflow prediction is an essentially important aspect of any watershed modelling. The black box models (soft computing techniques) have proven to be an efficient alternative to physical (traditional) methods for simulating streamflow and sediment yield of the catchments. 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 (1992-2011) rainfall and other hydrological data were considered, of which 13 years (1992-2004) was for training and rest 7 years (2005-2011) for validation of the models. The mode performance was evaluated by R, RMSE, EV, CE, and MAD statistical parameters. It was found that, ANN model performance improved with increasing input vectors. The results with fuzzy logic models predict the streamflow with single input as rainfall better in comparison to multiple input vectors. While comparing both ANN and FL algorithms for prediction of streamflow, ANN model performance is quite superior.

  15. Development Opportunities: The Effect of UMES on the Town of Princess Anne, Maryland.

    ERIC Educational Resources Information Center

    Sann, David; Tervala, Victor K.

    A study was done of the potential economic effect of the University of Maryland Eastern Shore (UMES) campus on the nearby town of Princess Anne, a small rural community. The study used estimates made by a UMES faculty member which projected that UMES students in 1990 spent over $7 million on goods and services unrelated to educational expenses.…

  16. 76 FR 81991 - Tecumseh Products Corporation, Ann Arbor, MI; Notice of Termination of Investigation

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-12-29

    ... FR 59176). Workers at the subject firm are engaged in activities related to the production of... Employment and Training Administration Tecumseh Products Corporation, Ann Arbor, MI; Notice of Termination of... Application for Reconsideration applicable to workers and former workers of Tecumseh Products Corporation,...

  17. English for Specific Purposes: The State of the Art (An Online Interview with Ann M. Johns)

    ERIC Educational Resources Information Center

    Johns, Ann M.; Salmani Nodoushan, M. A.

    2015-01-01

    This forum paper is based on a friendly and informative interview conducted with Professor Ann M. Johns. In providing answers to the interview questions, Professor Johns suggests that all good teaching is ESP, and also distinguishes between EOP and ESP in that the former entails much more "just in time" learning while the latter may be…

  18. A soil moisture index as an auxiliary ANN input for stream flow forecasting

    NASA Astrophysics Data System (ADS)

    Anctil, François; Michel, Claude; Perrin, Charles; Andréassian, Vazken

    2004-01-01

    This study tests the short-term forecasting improvement afforded by the inclusion of low-frequency inputs to artificial neural network (ANN) rainfall-runoff models that are first optimized by using only fast response components, i.e. using stream flow and rainfall as inputs. Ten low-frequency ANN input candidates are considered: the potential evapotranspiration, the antecedent precipitation index (API i, i=7, 15, 30, 60, and 120 days) and a proposed soil moisture index time series (SMI A, for A=100, 200, 400 and 800 mm). As the ANNs considered are for use in real-time lead-time-L forecasting, forecast performance is expressed in terms of the persistence index, rather than the conventional Nash-Sutcliffe index. The API i are the non-decayed moving average precipitation series, while the SMI A are calculated through the soil moisture accounting reservoir of the lumped conceptual rainfall-runoff model GR4J. Results, based on daily data of the Serein and Leaf rivers, reveal that only the SMI A time series are useful for one-day-ahead stream flow forecasting, with both the potential evapotranspiration and the API itime series failing to improve the ANN performance.

  19. Evaluation of the AnnAGNPS model for atrazine prediction in NE Indiana

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Annualized Agricultural Non-Point Source (AnnAGNPS) pollution model was developed for simulation of runoff, sediment, nutrient, and pesticide losses from ungauged agricultural watersheds. Here, the model was applied to the 707 km^2 Cedar Creek Watershed (CCW) and the 45 km^2 Matson Ditch Sub-Cat...

  20. Beneficial application of landfill mining Millersville Landfill, Anne Arundel County, MD

    SciTech Connect

    Vanetti, D.J.

    1995-09-01

    Several studies and investigations have been completed for the Millersville Sanitary Landfill in Anne Arundel County, Maryland. The studies and reports range from detailed hydrogeologic investigations through review of closure alternatives for the individual refuse disposal cells located at the landfill. As a result of the evaluations and studies, one recommendation that was put before Anne Arundel County is the excavation and relocation of refuse from Cell 3 to: (1) create an infiltration basin; and (2) reduce the overall refuse footprint at the site, resulting in reduce long term environmental impacts and closure costs. Subsequent to this recommendation, several preliminary reviews have been held between Anne Arundel County, regulatory agencies and their consultants, Stearns & Wheler. These discussions indicated that it would be feasible, and the concept acceptable, to relocate the refuse in Cell 3 to ultimately create an infiltration basin. Subsequent to the preliminary meetings, a project plan and construction Contract Documents and Drawings were developed by Stearns & Wheler. The Project Plan was submitted to the State regulatory agencies (Maryland and Department of Environment (MDE) and Maryland Department of Natural Resources (DNR)), Millersville Landfill Citizen`s Advisory Committee, and Anne Arundel County (Department of public Works (DPW), Permit Acquisition and Code Enforcement (PACE) and Soil Conservation District (SCD)) for review and comment prior to undertaking the relocation of refuse in Cell 3.

  1. 78 FR 65360 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-31

    ... National Park Service Notice of Inventory Completion: University of Michigan, Ann Arbor, MI AGENCY... inventory of human remains and associated funerary objects, in consultation with the appropriate Indian... American Graves Protection and Repatriation Act (NAGPRA), 25 U.S.C. 3003, of the completion of an...

  2. 78 FR 65376 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-31

    ... National Park Service Notice of Inventory Completion: University of Michigan, Ann Arbor, MI AGENCY... inventory of human remains and associated funerary objects, in consultation with the appropriate Indian... American Graves Protection and Repatriation Act (NAGPRA), 25 U.S.C. 3003, of the completion of an...

  3. 78 FR 65357 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-31

    ... National Park Service Notice of Inventory Completion: University of Michigan, Ann Arbor, MI AGENCY... inventory of human remains and associated funerary objects, in consultation with the appropriate Indian... American Graves Protection and Repatriation Act (NAGPRA), 25 U.S.C. 3003, of the completion of an...

  4. 78 FR 65371 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-31

    ... National Park Service Notice of Inventory Completion: University of Michigan, Ann Arbor, MI AGENCY... inventory of human remains and associated funerary objects, in consultation with the appropriate Indian... American Graves Protection and Repatriation Act (NAGPRA), 25 U.S.C. 3003, of the completion of an...

  5. 78 FR 65366 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-31

    ... National Park Service Notice of Inventory Completion: University of Michigan, Ann Arbor, MI AGENCY... inventory of human remains, in consultation with the appropriate Indian tribes or Native Hawaiian... Act (NAGPRA), 25 U.S.C. 3003, of the completion of an inventory of human remains under the control...

  6. 78 FR 65369 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-31

    ... National Park Service Notice of Inventory Completion: University of Michigan, Ann Arbor, MI AGENCY... inventory of human remains, in consultation with the appropriate Indian tribes or Native Hawaiian... Act (NAGPRA), 25 U.S.C. 3003, of the completion of an inventory of human remains under the control...

  7. 78 FR 65380 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-31

    ... National Park Service Notice of Inventory Completion: University of Michigan, Ann Arbor, MI AGENCY... inventory of human remains, in consultation with the appropriate Indian tribes or Native Hawaiian... Act (NAGPRA), 25 U.S.C. 3003, of the completion of an inventory of human remains under the control...

  8. 78 FR 65382 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-31

    ... National Park Service Notice of Inventory Completion: University of Michigan, Ann Arbor, MI AGENCY... inventory of human remains, in consultation with the appropriate Indian tribes or Native Hawaiian... Act (NAGPRA), 25 U.S.C. 3003, of the completion of an inventory of human remains under the control...

  9. 78 FR 65367 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-31

    ... National Park Service Notice of Inventory Completion: University of Michigan, Ann Arbor, MI AGENCY... inventory of human remains and associated funerary objects, in consultation with the appropriate Indian... American Graves Protection and Repatriation Act (NAGPRA), 25 U.S.C. 3003, of the completion of an...

  10. 78 FR 65364 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-31

    ... National Park Service Notice of Inventory Completion: University of Michigan, Ann Arbor, MI AGENCY... inventory of human remains and associated funerary objects, in consultation with the appropriate Indian... American Graves Protection and Repatriation Act (NAGPRA), 25 U.S.C. 3003, of the completion of an...

  11. 78 FR 65375 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-31

    ... National Park Service Notice of Inventory Completion: University of Michigan, Ann Arbor, MI AGENCY... inventory of human remains and associated funerary objects, in consultation with the appropriate Indian... inventory of human remains and associated funerary objects under the control of the University of...

  12. Exploring Social Studies through Multicultural Literature: "Legend of the St Ann's Flood"

    ERIC Educational Resources Information Center

    Fry, Sara Winstead

    2009-01-01

    The search for literature that is of high quality and interest, is written at age-appropriate levels for adolescent readers, addresses social studies topics, and presents multicultural perspectives can be daunting. "Legend of the St Ann's Flood" is a fiction trade book that meets all of these criteria. Its setting in Trinidad and Tobago provides…

  13. Evaluation of alternative management practices with the AnnAGNPS model in the Carapelle Watershed

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Annualized Agricultural Non-point Source (AnnAGNPS) model can be used to analyze the effectiveness of management and conservation practices that can control the impact of erosion and subsequent sediment loads in agricultural watersheds. A Mediterranean medium-size watershed (Carapelle) in Apulia...

  14. Basic concepts of artificial neural network (ANN) modeling and its application in pharmaceutical research.

    PubMed

    Agatonovic-Kustrin, S; Beresford, R

    2000-06-01

    Artificial neural networks (ANNs) are biologically inspired computer programs designed to simulate the way in which the human brain processes information. ANNs gather their knowledge by detecting the patterns and relationships in data and learn (or are trained) through experience, not from programming. An ANN is formed from hundreds of single units, artificial neurons or processing elements (PE), connected with coefficients (weights), which constitute the neural structure and are organised in layers. The power of neural computations comes from connecting neurons in a network. Each PE has weighted inputs, transfer function and one output. The behavior of a neural network is determined by the transfer functions of its neurons, by the learning rule, and by the architecture itself. The weights are the adjustable parameters and, in that sense, a neural network is a parameterized system. The weighed sum of the inputs constitutes the activation of the neuron. The activation signal is passed through transfer function to produce a single output of the neuron. Transfer function introduces non-linearity to the network. During training, the inter-unit connections are optimized until the error in predictions is minimized and the network reaches the specified level of accuracy. Once the network is trained and tested it can be given new input information to predict the output. Many types of neural networks have been designed already and new ones are invented every week but all can be described by the transfer functions of their neurons, by the learning rule, and by the connection formula. ANN represents a promising modeling technique, especially for data sets having non-linear relationships which are frequently encountered in pharmaceutical processes. In terms of model specification, artificial neural networks require no knowledge of the data source but, since they often contain many weights that must be estimated, they require large training sets. In addition, ANNs can combine

  15. PkANN - I. Non-linear matter power spectrum interpolation through artificial neural networks

    NASA Astrophysics Data System (ADS)

    Agarwal, Shankar; Abdalla, Filipe B.; Feldman, Hume A.; Lahav, Ofer; Thomas, Shaun A.

    2012-08-01

    We investigate the interpolation of power spectra of matter fluctuations using artificial neural networks (PkANN). We present a new approach to confront small-scale non-linearities in the power spectrum of matter fluctuations. This ever-present and pernicious uncertainty is often the Achilles heel in cosmological studies and must be reduced if we are to see the advent of precision cosmology in the late-time Universe. We show that an optimally trained artificial neural network (ANN), when presented with a set of cosmological parameters (? and redshift z), can provide a worst-case error ≤1 per cent (for z≤ 2) fit to the non-linear matter power spectrum deduced through N-body simulations, for modes up to k≤ 0.7 h Mpc-1. Our power spectrum interpolator is accurate over the entire parameter space. This is a significant improvement over some of the current matter power spectrum calculators. In this paper, we detail how an accurate interpolation of the matter power spectrum is achievable with only a sparsely sampled grid of cosmological parameters. Unlike large-scale N-body simulations which are computationally expensive and/or infeasible, a well-trained ANN can be an extremely quick and reliable tool in interpreting cosmological observations and parameter estimation. This paper is the first in a series. In this method paper, we generate the non-linear matter power spectra using HALOFIT and use them as mock observations to train the ANN. This work sets the foundation for Paper II, where a suite of N-body simulations will be used to compute the non-linear matter power spectra at sub-per cent accuracy, in the quasi-non-linear regime (0.1 ≤k≤ 0.9 h Mpc-1). A trained ANN based on this N-body suite will be released for the scientific community.

  16. Comparison of the Dynamic Wake Meandering Model, Large-Eddy Simulation, and Field Data at the Egmond aan Zee Offshore Wind Plant: Preprint

    SciTech Connect

    Churchfield, M. J.; Moriarty, P. J.; Hao, Y.; Lackner, M. A.; Barthelmie, R.; Lundquist, J.; Oxley, G. S.

    2014-12-01

    The focus of this work is the comparison of the dynamic wake meandering model and large-eddy simulation with field data from the Egmond aan Zee offshore wind plant composed of 36 3-MW turbines. The field data includes meteorological mast measurements, SCADA information from all turbines, and strain-gauge data from two turbines. The dynamic wake meandering model and large-eddy simulation are means of computing unsteady wind plant aerodynamics, including the important unsteady meandering of wakes as they convect downstream and interact with other turbines and wakes. Both of these models are coupled to a turbine model such that power and mechanical loads of each turbine in the wind plant are computed. We are interested in how accurately different types of waking (e.g., direct versus partial waking), can be modeled, and how background turbulence level affects these loads. We show that both the dynamic wake meandering model and large-eddy simulation appear to underpredict power and overpredict fatigue loads because of wake effects, but it is unclear that they are really in error. This discrepancy may be caused by wind-direction uncertainty in the field data, which tends to make wake effects appear less pronounced.

  17. Overexpression of Arabidopsis AnnAt8 Alleviates Abiotic Stress in Transgenic Arabidopsis and Tobacco

    PubMed Central

    Yadav, Deepanker; Ahmed, Israr; Shukla, Pawan; Boyidi, Prasanna; Kirti, Pulugurtha Bharadwaja

    2016-01-01

    Abiotic stress results in massive loss of crop productivity throughout the world. Because of our limited knowledge of the plant defense mechanisms, it is very difficult to exploit the plant genetic resources for manipulation of traits that could benefit multiple stress tolerance in plants. To achieve this, we need a deeper understanding of the plant gene regulatory mechanisms involved in stress responses. Understanding the roles of different members of plant gene families involved in different stress responses, would be a step in this direction. Arabidopsis, which served as a model system for the plant research, is also the most suitable system for the functional characterization of plant gene families. Annexin family in Arabidopsis also is one gene family which has not been fully explored. Eight annexin genes have been reported in the genome of Arabidopsis thaliana. Expression studies of different Arabidopsis annexins revealed their differential regulation under various abiotic stress conditions. AnnAt8 (At5g12380), a member of this family has been shown to exhibit ~433 and ~175 fold increase in transcript levels under NaCl and dehydration stress respectively. To characterize Annexin8 (AnnAt8) further, we have generated transgenic Arabidopsis and tobacco plants constitutively expressing AnnAt8, which were evaluated under different abiotic stress conditions. AnnAt8 overexpressing transgenic plants exhibited higher seed germination rates, better plant growth, and higher chlorophyll retention when compared to wild type plants under abiotic stress treatments. Under stress conditions transgenic plants showed comparatively higher levels of proline and lower levels of malondialdehyde compared to the wild-type plants. Real-Time PCR analyses revealed that the expression of several stress-regulated genes was altered in AnnAt8 over-expressing transgenic tobacco plants, and the enhanced tolerance exhibited by the transgenic plants can be correlated with altered expressions of

  18. A calcium-binding protein, rice annexin OsANN1, enhances heat stress tolerance by modulating the production of H2O2.

    PubMed

    Qiao, Bei; Zhang, Qian; Liu, Dongliang; Wang, Haiqi; Yin, Jingya; Wang, Rui; He, Mengli; Cui, Meng; Shang, Zhonglin; Wang, Dekai; Zhu, Zhengge

    2015-09-01

    OsANN1 is a member of the annexin protein family in rice. The function of this protein and the mechanisms of its involvement in stress responses and stress tolerance are largely unknown. Here it is reported that OsANN1 confers abiotic stress tolerance by modulating antioxidant accumulation under abiotic stress. OsANN1-knockdown [RNA interference (RNAi)] plants were more sensitive to heat and drought stresses, whereas OsANN1-overexpression (OE) lines showed improved growth with higher expression of OsANN1 under abiotic stress. Overexpression of OsANN1 promoted SOD (superoxide dismutase) and CAT (catalase) activities, which regulate H2O2 content and redox homeostasis, suggesting the existence of a feedback mechanism between OsANN1 and H2O2 production under abiotic stress. Higher expression of OsANN1 can provide overall cellular protection against abiotic stress-induced damage, and a significant accumulation of OsANN1-green fluorescent protein (GFP) signals was found in the cytosol after heat shock treatment. OsANN1 also has calcium-binding and ATPase activities in vitro, indicating that OsANN1 has multiple functions in rice growth. Furthermore, yeast two-hybrid and bimolecular fluorescence complementation (BiFC) assays demonstrated that OsANN1 interacts with OsCDPK24. This cross-talk may provide additional layers of regulation in the abiotic stress response. PMID:26085678

  19. [Estimation of forest volume in Huzhong forest area based on RS, GIS and ANN].

    PubMed

    Liu, Zhi-Hua; Chang, Yu; Chen, Hong-Wei

    2008-09-01

    Based on remote sensing (RS) which has integrated and realistic characteristics, geographic information system (GIS) which has powerful spatial analysis ability, and artificial neutral network (ANN) which can optimize nonlinear complex systems, the forest volume in Huzhong forest area was estimated. The results showed that there was an obvious negative correlation between the forest volume and infrared band, indicating that infrared band had definite potential in estimating forest volume. The forest volume also negatively correlated with visible band and PC1. Among the topographic factors, altitude exerted more influence than aspect and slope on the estimation of forest volume. The correlation coefficient of predicted value and actual value reached to 0.973, when the optimal ANN parameter, suitable GIS information, and RS bands were adopted. After principal component transformation, the amount of observation data was effectively reduced, while the predicted precision only had a small decline (R2 = 0.934). PMID:19102299

  20. Discrete wavelet transform coupled with ANN for daily discharge forecasting into Três Marias reservoir

    NASA Astrophysics Data System (ADS)

    Santos, C. A. G.; Freire, P. K. M. M.; Silva, G. B. L.; Silva, R. M.

    2014-09-01

    This paper proposes the use of discrete wavelet transform (DWT) to remove the high-frequency components (details) of an original signal, because the noises generally present in time series (e.g. streamflow records) may influence the prediction quality. Cleaner signals could then be used as inputs to an artificial neural network (ANN) in order to improve the model performance of daily discharge forecasting. Wavelet analysis provides useful decompositions of original time series in high and low frequency components. The present application uses the Coiflet wavelets to decompose hydrological data, as there have been few reports in the literature. Finally, the proposed technique is tested using the inflow records to the Três Marias reservoir in São Francisco River basin, Brazil. This transformed signal is used as input for an ANN model to forecast inflows seven days ahead, and the error RMSE decreased by more than 50% (i.e. from 454.2828 to 200.0483).

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

    PubMed

    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. PMID:27279067

  2. ANN based Estimation of Ultra High Energy (UHE) Shower Size using Radio Data

    NASA Astrophysics Data System (ADS)

    Sinha, Kalpana Roy; Datta, Pranayee; Sarma, Kandarpa Kumar

    2013-02-01

    Size estimation is a challenging area in the field of Ultra High Energy (UHE) showers where actual measurements are always associated with uncertainty of events and imperfections in detection mechanisms. The subtle variations resulting out of such factors incorporate certain random behaviour in the readings provided by shower detectors for subsequent processing. Field strength recorded by radio detectors may also be affected by this statistical nature. Hence there is a necessity of development of a system which can remain immune to such random behaviour and provide resilient readings to subsequent stages. Here, we propose a system based on Artificial Neural Network (ANN) which accepts radio field strength recorded by radio detectors and provides estimates of shower sizes in the UHE region. The ANN in feed-forward form is trained with a range of shower events with which it can effectively handle the randomness observed in the detector reading due to imperfections in the experimental apparatus and related set-up.

  3. An ANN-Based Smart Tomographic Reconstructor in a Dynamic Environment

    PubMed Central

    de Cos Juez, Francisco J.; Lasheras, Fernando Sánchez; Roqueñí, Nieves; Osborn, James

    2012-01-01

    In astronomy, the light emitted by an object travels through the vacuum of space and then the turbulent atmosphere before arriving at a ground based telescope. By passing through the atmosphere a series of turbulent layers modify the light's wave-front in such a way that Adaptive Optics reconstruction techniques are needed to improve the image quality. A novel reconstruction technique based in Artificial Neural Networks (ANN) is proposed. The network is designed to use the local tilts of the wave-front measured by a Shack Hartmann Wave-front Sensor (SHWFS) as inputs and estimate the turbulence in terms of Zernike coefficients. The ANN used is a Multi-Layer Perceptron (MLP) trained with simulated data with one turbulent layer changing in altitude. The reconstructor was tested using three different atmospheric profiles and compared with two existing reconstruction techniques: Least Squares type Matrix Vector Multiplication (LS) and Learn and Apply (L + A). PMID:23012524

  4. Design and improvement of laser tracking control system using ANN technique

    NASA Astrophysics Data System (ADS)

    Shi, Ying; Zhang, Guoxiong; Li, Xingfei

    2005-01-01

    Laser tracking method for space coordinates measurement is a newly developed technique that possesses the characteristics of high accuracy, large measuring range, flexible and dynamic measurement and so on. Laser tracking interferometer system based on this method has become an important measuring tool in many industrial fields. However, the control system sometimes acts nonlinearly because of long-range measurement and various applications. To solve this problem, artificial neural network (ANN) controller is introduced as an advanced adaptive control configuration in laser tracking interferometer system. The reason is that artificial neural network which is an important branch of intelligent control area has great potential ability in dealing with high nonlinearity and indeterminate factors. Then the simulation of tracking control system based on either conventional PID controller or ANN controller is carried out separately and the result of comparison is given.

  5. Processing RoxAnn sonar data to improve its categorization of lake bed surficial sediments

    USGS Publications Warehouse

    Cholwek, Gary; Bonde, John; Li, Xing; Richards, Carl; Yin, Karen

    2000-01-01

    To categorize spawning and nursery habitat for lake trout in Minnesota's near shore waters of Lake Superior, data was collected with a single beam echo sounder coupled with a RoxAnn bottom classification sensor. Test areas representative of different bottom surficial substrates were sampled. The collected data consisted of acoustic signals which showed both depth and substrate type. The location of the signals was tagged in real-time with a DGPS. All data was imported into a GIS database. To better interpret the output signal from the RoxAnn, several pattern classifiers were developed by multivariate statistical method. From the data a detailed and accurate map of lake bed bathymetry and surficial substrate types was produced. This map will be of great value to fishery and other natural resource managers.

  6. An ANN-based smart tomographic reconstructor in a dynamic environment.

    PubMed

    de Cos Juez, Francisco J; Sánchez Lasheras, Fernando; Roqueñí, Nieves; Osborn, James

    2012-01-01

    In astronomy, the light emitted by an object travels through the vacuum of space and then the turbulent atmosphere before arriving at a ground based telescope. By passing through the atmosphere a series of turbulent layers modify the light's wave-front in such a way that Adaptive Optics reconstruction techniques are needed to improve the image quality. A novel reconstruction technique based in Artificial Neural Networks (ANN) is proposed. The network is designed to use the local tilts of the wave-front measured by a Shack Hartmann Wave-front Sensor (SHWFS) as inputs and estimate the turbulence in terms of Zernike coefficients. The ANN used is a Multi-Layer Perceptron (MLP) trained with simulated data with one turbulent layer changing in altitude. The reconstructor was tested using three different atmospheric profiles and compared with two existing reconstruction techniques: Least Squares type Matrix Vector Multiplication (LS) and Learn and Apply (L + A). PMID:23012524

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

    PubMed

    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. PMID:19999636

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

    NASA Astrophysics Data System (ADS)

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

    2007-05-01

    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.

  9. A Practically Validated Intelligent Calibration Circuit Using Optimized ANN for Flow Measurement by Venturi

    NASA Astrophysics Data System (ADS)

    Venkata, Santhosh Krishnan; Roy, Binoy Krishna

    2016-03-01

    Design of an intelligent flow measurement technique using venturi flow meter is reported in this paper. The objectives of the present work are: (1) to extend the linearity range of measurement to 100 % of full scale input range, (2) to make the measurement technique adaptive to variations in discharge coefficient, diameter ratio of venturi nozzle and pipe (β), liquid density, and liquid temperature, and (3) to achieve the objectives (1) and (2) using an optimized neural network. The output of venturi flow meter is differential pressure. It is converted to voltage by using a suitable data conversion unit. A suitable optimized artificial neural network (ANN) is added, in place of conventional calibration circuit. ANN is trained, tested with simulated data considering variations in discharge coefficient, diameter ratio between venturi nozzle and pipe, liquid density, and liquid temperature. The proposed technique is then subjected to practical data for validation. Results show that the proposed technique has fulfilled the objectives.

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

    PubMed

    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. PMID:26140748

  11. Carbon Cycle 2.0: Mary Ann Piette: Impact of efficient buildings

    SciTech Connect

    Mary Ann Piette

    2010-02-09

    Mary Ann Piette speaks at the Carbon Cycle 2.0 kick-off symposium Feb. 2, 2010. We emit more carbon into the atmosphere than natural processes are able to remove - an imbalance with negative consequences. Carbon Cycle 2.0 is a Berkeley Lab initiative to provide the science needed to restore this balance by integrating the Labs diverse research activities and delivering creative solutions toward a carbon-neutral energy future. http://carboncycle2.lbl.gov/

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

    Cancer.gov

    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 psychosocial issues, such as distress, anxiety and depression. |

  13. Carbon Cycle 2.0: Mary Ann Piette: Impact of efficient buildings

    ScienceCinema

    Mary Ann Piette

    2010-09-01

    Mary Ann Piette speaks at the Carbon Cycle 2.0 kick-off symposium Feb. 2, 2010. We emit more carbon into the atmosphere than natural processes are able to remove - an imbalance with negative consequences. Carbon Cycle 2.0 is a Berkeley Lab initiative to provide the science needed to restore this balance by integrating the Labs diverse research activities and delivering creative solutions toward a carbon-neutral energy future. http://carboncycle2.lbl.gov/

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

    PubMed

    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. PMID:25230533

  15. Clustering of soybean genotypes via Ward-MLM and ANNs associated with mixed models.

    PubMed

    Teodoro, P E; Torres, F E; Corrêa, A M

    2016-01-01

    The objectives of this study were to use mixed models to confirm the presence of genetic variability in 16 soybean genotypes, to compare clusters generated by artificial neural networks (ANNs) with those created by the Ward modified location model (MLM) technique, and to indicate parental combinations that hold promise for obtaining superior segregating populations of soybean. A field trial was conducted between November 2014 and February 2015 at Universidade Estadual de Mato Grosso do Sul, Aquidauana, MS. The experimental design consisted of four replications of randomized blocks, each containing 16 treatments. We assessed the following agronomic traits: plant height, first pod height, number of branches per plant, number of pods per plant, number of grains per pod, hundred-grain weight, and grain yield. Mixed models were used to estimate variance components and genetic parameters, and obtain genotypic values for each trait. After verifying the presence of genetic variability for all traits, genotypic values were submitted to both a Ward-MLM procedure and ANNs to estimate genetic divergence among genotypes. The number of groups formed by both methods was the same, but there were differences in group constitutions. ANN analysis improved soybean genotypes clustering patterns compared to Ward-MLM procedure. Based on these methods, divergent crosses may be made between genotype 97R73 with genotypes AS3797 and SYN9070, whereas convergent crosses may be made between genotypes AS3797 and SYN9070. PMID:27525912

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

    NASA Astrophysics Data System (ADS)

    Patel, Raj Kumar; Giri, V. K.

    2016-07-01

    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.

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

    PubMed Central

    Fakhri, Mansour

    2014-01-01

    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. PMID:24688400

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

    PubMed Central

    G. S., Vijay; H. S., Kumar; Pai P., Srinivasa; N. S., Sriram; Rao, Raj B. K. N.

    2012-01-01

    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. PMID:23213323

  19. Dynamics of a mesoscale eddy off Cape Ann, Massachusetts in May 2005

    NASA Astrophysics Data System (ADS)

    Jiang, Mingshun; Zhou, Meng; Libby, Scott P.; Anderson, Donald M.

    2011-11-01

    Observations and numerical modeling indicate that a mesoscale anti-cyclonic eddy formed south of Cape Ann at the northern entrance of Massachusetts Bay (MB) during May 2005, when large river discharges in the western Gulf of Maine and two strong Nor'easters passing through the regions led to an unprecedented toxic Alexandrium fundyense bloom (red tide). Both model results and field measurements suggest that the western Maine Coastal Current separated from Cape Ann around May 7-8, and the eddy formed on around May 10. The eddy was trapped at the formation location for about a week before detaching from the coastline and moving slowly southward on May 17. Both model results and theoretical analysis suggest that the separation of the coastal current from the coast and subsequent eddy formation were initiated at the subsurface by an adverse pressure gradient between Cape Ann and MB due to the higher sea level set up by onshore Ekman transport and higher density in downstream MB. After the formation, the eddy was maintained by the input of vorticity transported by the coastal current from the north, and local vorticity generation around the cape by the horizontal gradients of wind-driven currents, bottom stress, and water density induced by the Merrimack River plume. Observations and model results indicate that the anti-cyclonic eddy significantly changed the pathway of nutrient and biota transport into the coastal areas and enhanced phytoplankton including Alexandrium abundances around the perimeter of the eddy and in the western coast of MB.

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

    NASA Astrophysics Data System (ADS)

    Chandrasekaran, Muthumari; Tamang, Santosh

    2016-06-01

    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.

  1. [The family relationships of Antoine Brulon, apothecary to the king, and his wife, Anne de Furnes, in Auvergne and Paris in the 17th century. Anne de Furnes and Molière in Paris and the village of Auteuil].

    PubMed

    Warolin, Christian

    2011-07-01

    This article presents the biography of Anne de Fumes, wife of Antoine Brulon, the king's apothecary. Due to the successive deaths of her husband and her only daughter, Geneviève, her sisters-in-law, Géraude and Anne Brulon, living in Auvergne, inherited the property of their niece. Anne de Fumes, who inherited the movable assets, carried out a series of transactions to acquire the totality of the property rights, which she obtained, but at the considerable cost of 100,000 pounds. After her death, her five nephews and nieces, her sole legatees, inherited her estate. From 1666, Molière was the tenant of an apartment in a building in the Rue Saint-Thomas-du-Louvre, Place du Palais-Royal, in Paris, which belonged to Anne de Fumes. She lived in the neighbouring house in the Rue Saint-Honoré of which she was also the owner. Three apothecaries, Philibert Boudin, Jean Morel and Pierre Frapin, successively rented the shop and entresol of the house in the Rue Saint-Thomas-du-Louvre. Pierre Frapin, tenant of the shop from 1668, supplied Molière with medicine. Like Molière, Anne de Fumes rented accommodation in a house in the village of Auteuil belonging to Jacques de Grout de Beaufort and his wife Marie Filz. Reports show that the famous actor and Anne de Fumes cohabited in Auteuil during the period 1667 to 1672. PMID:21998974

  2. Assessment of AnnAGNPS model capacity to simulate ephemeral gullies initiation and development

    NASA Astrophysics Data System (ADS)

    Chahor, Youssef; Giménez, Rafael; Casalí, Javier

    2015-04-01

    The relatively recent recognition of the importance of ephemeral gully erosion in agricultural fields in Europe explains that so far only a few mathematical models have included algorithms to simulate this type of concentrated flow erosion. Precisely, a conceptual and numerical framework was recently incorporated in the Annualized Agricultural Non-Point Source (AnnAGNPS) model to simulate gully initiation and development in order to assess the impact of gully erosion (sediment production) on management practices at watershed scale. More precisely, the Compound Topographic Index (CTI) approach was integrated within the existing AnnAGNPS GIS interface in order to identify the Potential Ephemeral Gully (PEG) mouth throughout a watershed. In addition, the Tillage-Induced Ephemeral Gully Erosion Model (TIEGEM) was also incorporated into AnnAGNPS to estimate ephemeral gully development. The aim of this work was to assess the capability of AnnAGNPS for predicting (i) PEG location and (ii) gully erosion rate and gully geometry. The study was carried out in the region of Pitillas (southern Navarre, Spain; under continental Mediterranean climate), in several field sites cultivated with wheat. First, thirty-one EGs observed in the fields and depicted in aerial photographs were taken as references. A DEM of the study area (5 x 5 m) was processed using AGNPS ArcView interface to determine the CTI values of each raster grid. Then, seven cumulative percentage values of CTI thresholds (94%, 95%, 96%, 97%, 98%, 99% and 99.5%) were used to create seven potential scenarios of PEG mouths locations in the study area. These scenarios were compared with the reference EGs. The CTI cumulative percentage thresholds of 95% presented the best performance in predicting EGs locations. However, the accuracy of the CTI approach notably decreased in low slope areas. On the other hand, four EGs developed and surveyed in the same study area -in different years between 1996 and 2001- were used to

  3. Estimation of Release History of Pollutant Source and Dispersion Coefficient of Aquifer Using Trained ANN Model

    NASA Astrophysics Data System (ADS)

    Srivastava, R.; Ayaz, M.; Jain, A.

    2013-12-01

    Knowledge of the release history of a groundwater pollutant source is critical in the prediction of the future trend of the pollutant movement and in choosing an effective remediation strategy. Moreover, for source sites which have undergone an ownership change, the estimated release history can be utilized for appropriate allocation of the costs of remediation among different parties who may be responsible for the contamination. Estimation of the release history with the help of concentration data is an inverse problem that becomes ill-posed because of the irreversible nature of the dispersion process. Breakthrough curves represent the temporal variation of pollutant concentration at a particular location, and contain significant information about the source and the release history. Several methodologies have been developed to solve the inverse problem of estimating the source and/or porous medium properties using the breakthrough curves as a known input. A common problem in the use of the breakthrough curves for this purpose is that, in most field situations, we have little or no information about the time of measurement of the breakthrough curve with respect to the time when the pollutant source becomes active. We develop an Artificial Neural Network (ANN) model to estimate the release history of a groundwater pollutant source through the use of breakthrough curves. It is assumed that the source location is known but the time dependent contaminant source strength is unknown. This temporal variation of the strength of the pollutant source is the output of the ANN model that is trained using the Levenberg-Marquardt algorithm utilizing synthetically generated breakthrough curves as inputs. A single hidden layer was used in the neural network and, to utilize just sufficient information and reduce the required sampling duration, only the upper half of the curve is used as the input pattern. The second objective of this work was to identify the aquifer parameters. An

  4. Precipitation Estimation from Remotely Sensed Information using ANN-Cloud Classification System

    NASA Astrophysics Data System (ADS)

    Hong, Y.; Hsu, K.; Sorooshian, S.

    2003-12-01

    Artificial Neural Network (ANN) models, which contain flexible architectures and are capable of discerning the underlying functional relationships from data, are recognized as very useful tools in geophysical applications. In this study, we demonstrate a hybrid ANN modeling system to estimate surface rainfall from satellite infrared imagery. The proposed network, Precipitation Estimation from Remotely Sensed Information using ANN-Cloud Classification System (PERSIANN-CCS), includes several components: (1) cloud image segmentation, (2) cloud patch feature selection, (3) patch feature classification using a self-organizing feature map network, and (4) patch-based rainfall estimates from a group of multiple nonlinear cloud top temperature and rainfall functions. The PERSIANN-CCS model was first calibrated using observations from Geostationary Operational Environmental Satellite (GOES) infrared imagery and the Next Generation Radar (NEXRAD) rainfall network. To further extend PERSIANN-CCS rainfall estimates over the remote regions, Tropical Rainfall Measurement Mission (TRMM) microwave rainfall estimates (TMI product 2A12) were used to adjust PERSIANN-CCS model parameters. The calibrated nonlinear cloud top temperature and rainfall (Tb-R) functions of classified cloud patches show highly variability, reflecting the complexity of dominant cloud-precipitation processes over various regions. Case studies show that PERSIANN-CCS captures the variability in rain rate at 12kmx12km grid and 3-hour resolutions, with a standard error of 3.0mm/hr and a correlation coefficient around 0.65. Additional insights into the cloud evolution and precipitation process from the classified PERSIANN-CCS cloud patch features and rainfall distributions are discussed.

  5. [Modelling pollutant loads and management alternatives in Jiulong River watershed with AnnAGNPS].

    PubMed

    Hong, Hua-Sheng; Huang, Jin-Liang; Zhang, Luo-Ping; Du, Peng-Fei

    2005-07-01

    The modelling package Annualized Agricultural Nonpoint Source Model (AnnAGNPS) was used to predict pollutant loads, and simulate catchment processes and management practices in Jiulong River watershed, a medium-sized mountainous watershed in southeast of China. Four typical sub-watersheds were primarily chosen to calibrate AnnAGNPS model by data collected from storm events during the period of April to September, 2003. The model was further validated in the two biggest branches of Jiulong River watershed, i.e. West river and North river by the data regarding climate, and land using condition in 2002 - 2003. The simulation results show that annual total nitrogen load was 24.76kg/(hm2 x a) and 10.28kg/(hm2 x a) in the West river and North river, respectively, and annual total phosphorus load was 0.67 kg/(hm2 x a) and 0.40 kg/(hm2 x a) in the West river and North river, respectively. With the support of AnnAGNPS model, several management alternatives were separately simulated in the typical sub-watersheds, West river and North river. In the specific cell with cell-ID of 92 in Tianbao and Xiandu sub-watershed, after reforesting in sloping field, runoff surface, sediment yield, total nitrogen load and total phosphorus load cut down with 21.6%, 25.9%, 96% and 79.2%, respectively. In West river, with the cultivation plant changing from banana into rice, the total nitrogen, dissolved nitrogen, total phosphorus and dissolved phosphorus cut down with 23.83%, 25.44%, 9.08% and 19.84%, respectively. In North river, when removing all the hoggerys, nitrogen and dissolved nitrogen cut down with 63.54% and 76.92% , respectively. PMID:16212170

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

    SciTech Connect

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

    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.

  7. ANN modeling for flood prediction in the upstream Eure's catchment (France)

    NASA Astrophysics Data System (ADS)

    Kharroubi, Ouissem; masson, Eric; Blanpain, Olivier; Lallahem, Sami

    2013-04-01

    Rainfall-Runoff relationship at basin scale is strongly depending on the catchment complexity including multi-scale interactions. In extreme events cases (i.e. floods and droughts) this relationship is even more complex and differs from average hydrological conditions making extreme runoff prediction very difficult to achieve. However, flood warning, flood prevention and flood mitigation rely on the possibility to predict both flood peak runoff and lag time. This point is crucial for decision making and flood warning to prevent populations and economical stakes to be damaged by extreme hydrological events. Since 2003 in France, a dedicated state service is in charge of producing flood warning from national level (i.e. SCHAPI) to regional level (i.e. SPC). This flood warning service is combining national weather forecast agency (i.e. Meteo France) together with a fully automated realtime hydrological network (i.e. Rainfall-Runoff) in order to produce a flood warning national map online and provide a set of hydro-meteorological data to the SPC in charge of flood prediction from regional to local scale. The SPC is in fact the flood service delivering hydrological prediction at operational level for decision making about flood alert for municipalities and first help services. Our research in collaboration with the SPC SACN (i.e. "Seine Aval et fleuves Côtiers Normands") is focused on the implementation of an Artificial Neural Network model (ANN) for flood prediction in deferent key points of the Eure's catchment and main subcatchment. Our contribution will focus on the ANN model developed for Saint-Luperce gauging station in the upstream part of the Eure's catchment. Prediction of extreme runoff at Saint-Luperce station is of high importance for flood warning in the Eure's catchment because it gives a good indicator on the extreme status and the downstream propagation of a potential flood event. Despite a good runoff monitoring since 27 years Saint Luperce flood

  8. Internal Model Controller of an ANN Speed Sensorless Controlled Induction Motor Drives

    NASA Astrophysics Data System (ADS)

    Hamed Mouna, Ben; Lassaad, Sbita

    This study deals with the performance analysis and implementation of a robust sensorless speed controller. The robustness is guaranteed by the use of the Internal Model Controller (IMC). An intelligent algorithm is evolved to eliminate the mechanical speed. It is based on the Artificial Neural Network (ANN) principle. Verification of the proposed robust sensorless controller is provided by experimental realistic tests on a scalar controlled induction motor drive. Sensorless robust speed control at low speeds and in field weakening region (high speeds) is studied in order to show the robustness of the speed controller under a wide range of load.

  9. Identification of Unknown Groundwater Pollution Source Using Linked ANN-Optimization Model

    NASA Astrophysics Data System (ADS)

    Ayaz, M.; Srivastava, R.

    2011-12-01

    Identification of groundwater pollution sources is a major step in groundwater pollution remediation, particularly for assigning fractions of the remediation cost to different polluters. Identification of unknown groundwater pollution source is an inverse problem which is generally ill-posed. A pollution source is said to be identified completely when its source characteristics (location, strength and release period) are known. In practice, the lag time between the first reading at observation well and the time at which the source becomes active is not known. For such cases, pollution source identification problem becomes more difficult. We propose a linked ANN-Optimization model for complete identification of unknown groundwater pollution sources. Spatial and temporal data of observed and simulated concentration is used to formulate the objective function. An optimization model is then used to minimize the objective function. We define the lag time as the time from the start of the pollutant release to the peak of the breakthrough curve observed at a monitoring well. Lag time for a particular monitoring well is then dependent only on the source location and release period. An ANN model is trained for different source locations and release periods as input data to determine the lag time for breakthrough curve. In the proposed model, the ANN model is linked externally with the optimization model to identify the pollution sources. The main advantage of the proposed model is to identify the unique solution for pollution sources when lag time is not known. The performance of the model is evaluated for a one dimensional case with error-free and erroneous data. The measurement errors incorporated in the data vary from 0% to 10% of the analytically computed values. The results indicate that the proposed linked ANN-Optimization model is able to predict the source parameters quite well for the error-free data. For the observations subjected to random measurement errors, the

  10. Explosion with a slow-burning fuse: origins of holography in Ann Arbor, Michigan

    NASA Astrophysics Data System (ADS)

    Johnston, Sean F.

    2006-05-01

    The subject today known as holography emerged from research in three diverse locations and having distinct origins, aims and methods: at a commercial electrical laboratory in Rugby, England, from the late 1940s until the mid 1950s; at the Vavilov State Optical Institute in Leningrad from the late 1950s and again from the mid 1960s; and, from a classified research laboratory operated by the University of Michigan beginning in the mid 1950s and accelerating from the early 1960s. The scientists, engineers, artisans, entrepreneurs and companies in that third location dominated the subject through the 1960s, making Ann Arbor, for a time, the 'holography capital of the world'. Based on extensive unpublished documents, artifacts and interviews with some two-dozen participants (much of it as yet unavailable in publicly accessible archives), this paper focuses on the origins of the subject in Ann Arbor, Michigan. It also explores how the initial explosion of interest was transmitted to other research groups, firms, artists and the wider public.

  11. The Automatic Classification with ANN of sunspot groups using the Solar Feature Catalogue

    NASA Astrophysics Data System (ADS)

    Zharkov, S. I.; Schetinin, V.; Zharkova, V. V.

    The sample 4 months Solar Feature Catalogue of sunspots created from the SOHO/MDI white light images and magnetograms with the automated detection technique is used for a classification of sunspots into groups and production of an automated activity index. The detection techniques are applied to a pair consisting of SOHO/MDI 'white light' continuum image and the magnetogram image from the same source, which are synchronised to the POV of countinuum. As a result we are able to extract the following information from each of sunspot: area, diameter, position (on the disk and on the solar sphere), umbral area, sunspot and umbral intensities and maximum and minimum magnetic flux and some others. The parameters were to classify the detection results by segmenting sunspots detected on a single image into sunspot groups using Artificial Neural Network. The two manual training sets of sunspot detection are used - Locarno Sunspot Drawings and Mount Wilson Classification. Based on them we try to identify the classifiers with the ANN, which have a best fit with the manual classifications above. The trained ANN is tested on a few testing sets from the both sources that revealed a good accuracy of classification. In the future this classification can replace the manual practices in the observatories and can used in solar activity forecast.

  12. An ANN approach in predicting solar radio enhancements at 11 cm wavelength

    NASA Astrophysics Data System (ADS)

    Molinaro, Marco; Gregorio, Anna; Messerotti, Mauro

    The decimetric radio emission from the solar corona is both an effective indicator of solar activity and a proxy for the EUV solar emission, which can cause perturbations in the terrestrial ionosphere. Therefore the 10.7 cm solar radio index is widely used in various ionospheric models and in any models where a reliable quantitative measure of the solar activity level is needed. The time evolution of this radio index closely matches that of the 1-min Soft X-Ray (SXR) measurements, resulting in an effective diagnostics for flaring processes. In fact, the occurrence of decimetric radio flares is associated with that of the correspondent SXR signature. Hence, the capability of predicting decimetric radio flares is a fundamental feature for space weather applications. In this work, we present preliminary results obtained via an Artificial Neural Network (ANN) approach for the prediction of solar radio enhancements at 11 cm wavelength. The data used to feed and run the ANN are the 1-min average radio index provided by the Trieste Solar Radio System, a dedicated multichannel solar radio polarimeters' set operated by the INAF-Astronomical Observatory of Trieste. Different use cases are discussed in the framework of future developments for advanced space weather nowcasting and forecasting via radio diagnostics, based on the unique feature of TSRS which acquires the data with a routinary time cadence of 1 millisecond and this allows to get deeper insights of the events' time evolution and prediction.

  13. Controlling the Twin Wire Arc Spray Process Using Artificial Neural Networks (ANN)

    NASA Astrophysics Data System (ADS)

    Hartz-Behrend, K.; Schaup, J.; Zierhut, J.; Schein, J.

    2016-01-01

    One approach for controlling the twin wire arc spray process is to use optical properties of the particle beam as input parameters for a process control. The idea is that changes in the process like eroded contact nozzles or variations of current, voltage, and/or atomizing gas pressure may be detected through observation of the particle beam. It can be assumed that if these properties deviate significantly from those obtained from a beam recorded for an optimal coating process, the spray particle and thus the coating properties change significantly. The goal is to detect these deviations and compensate the occurring errors by adjusting appropriate process parameters for the wire arc spray unit. One method for monitoring optical properties is to apply the diagnostic system particle flux imaging (PFI): PFI fits an ellipse to an image of a particle beam thereby defining easy to analyze characteristical parameters by relating optical beam properties to ellipse parameters. Using artificial neural networks (ANN), mathematical relations between ellipse and process parameters can be defined. It will be shown that in the case of a process disturbance through the use of an ANN-based control new process parameters can be computed to compensate particle beam deviations.

  14. Elemental Study on Auscultaiting Diagnosis Support System of Hemodialysis Shunt Stenosis by ANN

    NASA Astrophysics Data System (ADS)

    Suzuki, Yutaka; Fukasawa, Mizuya; Mori, Takahiro; Sakata, Osamu; Hattori, Asobu; Kato, Takaya

    It is desired to detect stenosis at an early stage to use hemodailysis shunt for longer time. Stethoscope auscultation of vascular murmurs is useful noninvasive diagnostic approach, but an experienced expert operator is necessary. Some experts often say that the high-pitch murmurs exist if the shunt becomes stenosed, and some studies report that there are some features detected at high frequency by time-frequency analysis. However, some of the murmurs are difficult to detect, and the final judgment is difficult. This study proposes a new diagnosis support system to screen stenosis by using vascular murmurs. The system is performed using artificial neural networks (ANN) with the analyzed frequency data by maximum entropy method (MEM). The author recorded vascular murmurs both before percutaneous transluminal angioplasty (PTA) and after. Examining the MEM spectral characteristics of the high-pitch stenosis murmurs, three features could be classified, which covered 85 percent of stenosis vascular murmurs. The features were learnt by the ANN, and judged. As a result, a percentage of judging the classified stenosis murmurs was 100%, and that of normal was 86%.

  15. Identification of pain from infant cry vocalizations using artificial neural networks (ANNs)

    NASA Astrophysics Data System (ADS)

    Petroni, Marco; Malowany, Alfred S.; Johnston, C. Celeste; Stevens, Bonnie J.

    1995-04-01

    The analysis of infant cry vocalizations has been the focus of a number of efforts over the past thirty years. Since the infant cry is one of the only means that an infant has for communicating with its care-giving environment, it is thought that information regarding the state of an infant, such as hunger or pain, can be determined from an infant's cry. To date, research groups have determined that adult listeners can differentiate between different types of cries auditorialy, and at least one group has attempted to automate this classification process. This paper presents the results of another attempt at automating the discrimination process, this time using artificial neural networks (ANNs). The input data consists of successive frames of one or two parametric representations generated from the first second of a cry following the application of either an anger, fear, or pain stimulus. From tests conducted to date, it is determined that ANNs are a useful tool for cry classification and merit further study in this domain.

  16. Prediction of Cutting Forces Using ANNs Approach in Hard Turning of AISI 52100 steel

    SciTech Connect

    Makhfi, Souad; Habak, Malek; Velasco, Raphael; Haddouche, Kamel; Vantomme, Pascal

    2011-05-04

    In this study, artificial neural networks (ANNs) was used to predict cutting forces in the case of machining the hard turning of AISI 52100 bearing steel using cBN cutting tool. Cutting forces evolution is considered as the key factors which affect machining. Predicting cutting forces evolution allows optimizing machining by an adaptation of cutting conditions. In this context, it seems interesting to study the contribution that could have artificial neural networks (ANNs) on the machining forces prediction in both numerical and experiment studies. Feed-forward multi-layer neural networks trained by the error back-propagation (BP) algorithm are used. Levenberg-Marquardt (LM) optimization algorithm was used for finding out weights. The training of the network is carried out with experimental machining data.The input dataset used are cutting speed, feed rate, cutting depth and hardness of the material. The output dataset used are cutting forces (Ft-cutting force, Fa- feed force and Fr- radial force).Results of the neural networks approach, in comparison with experimental data are discussed in last part of this paper.

  17. Clearance Rate and BP-ANN Model in Paraquat Poisoned Patients Treated with Hemoperfusion

    PubMed Central

    Hu, Lufeng; Hong, Guangliang; Ma, Jianshe; Wang, Xianqin; Lin, Guanyang; Zhang, Xiuhua; Lu, Zhongqiu

    2015-01-01

    In order to investigate the effect of hemoperfusion (HP) on the clearance rate of paraquat (PQ) and develop a clearance model, 41 PQ-poisoned patients who acquired acute PQ intoxication received HP treatment. PQ concentrations were determined by high performance liquid chromatography (HPLC). According to initial PQ concentration, study subjects were divided into two groups: Low-PQ group (0.05–1.0 μg/mL) and High-PQ group (1.0–10 μg/mL). After initial HP treatment, PQ concentrations decreased in both groups. However, in the High-PQ group, PQ levels remained in excess of 0.05 μg/mL and increased when the second HP treatment was initiated. Based on the PQ concentrations before and after HP treatment, the mean clearance rate of PQ calculated was 73 ± 15%. We also established a backpropagation artificial neural network (BP-ANN) model, which set PQ concentrations before HP treatment as input data and after HP treatment as output data. When it is used to predict PQ concentration after HP treatment, high prediction accuracy (R = 0.9977) can be obtained in this model. In conclusion, HP is an effective way to clear PQ from the blood, and the PQ concentration after HP treatment can be predicted by BP-ANN model. PMID:25695058

  18. Solving Capelin Time Series Ecosystem Problem Using Hybrid ANN-GAs Model and Multiple Linear Regression Model

    NASA Astrophysics Data System (ADS)

    Eghnam, Karam M.; Sheta, Alaa F.

    2008-06-01

    Development of accurate models is necessary in critical applications such as prediction. In this paper, a solution to the stock prediction problem of the Barents Sea capelin is introduced using Artificial Neural Network (ANN) and Multiple Linear model Regression (MLR) models. The Capelin stock in the Barents Sea is one of the largest in the world. It normally maintained a fishery with annual catches of up to 3 million tons. The Capelin stock problem has an impact in the fish stock development. The proposed prediction model was developed using an ANNs with their weights adapted using Genetic Algorithm (GA). The proposed model was compared to traditional linear model the MLR. The results showed that the ANN-GA model produced an overall accuracy of 21% better than the MLR model.

  19. QSPR modeling of soil sorption coefficients (K(OC)) of pesticides using SPA-ANN and SPA-MLR.

    PubMed

    Goudarzi, Nasser; Goodarzi, Mohammad; Araujo, Mario Cesar Ugulino; Galvão, Roberto Kawakami Harrop

    2009-08-12

    A quantitative structure-property relationship (QSPR) study was conducted to predict the adsorption coefficients of some pesticides. The successive projection algorithm feature selection (SPA) strategy was used as descriptor selection and model development method. Modeling of the relationship between selected molecular descriptors and adsorption coefficient data was achieved by linear (multiple linear regression; MLR) and nonlinear (artificial neural network; ANN) methods. The QSPR models were validated by cross-validation as well as application of the models to predict the K(OC) of external set compounds, which did not contribute to model development steps. Both linear and nonlinear methods provided accurate predictions, although more accurate results were obtained by the ANN model. The root-mean-square errors of test set obtained by MLR and ANN models were 0.3705 and 0.2888, respectively. PMID:19722589

  20. The Use of ANN to Predict the Hot Deformation Behavior of AA7075 at Low Strain Rates

    NASA Astrophysics Data System (ADS)

    Jenab, A.; Karimi Taheri, A.; Jenab, K.

    2013-03-01

    In this study, artificial neural network (ANN) was used to model the hot deformation behavior of 7075 aluminum alloy during compression test, in the strain rate range of 0.0003-1 s-1 and temperature range of 200-450 °C. The inputs of the model were temperature, strain rate, and strain, while the output of the model was the flow stress. The feed-forward back-propagation network with two hidden layers was built and successfully trained at different deformation domains by Levenberg-Marquardt training algorithm. Comparative analysis of the results obtained from the hyperbolic sine, the power law constitutive equations, and the ANN shows that the newly developed ANN model has a better performance in predicting the hot deformation behavior of 7075 aluminum alloy.

  1. Assessment of maximum likelihood (ML) and artificial neural network (ANN) algorithms for classification of remote sensing data

    NASA Astrophysics Data System (ADS)

    Gupta, R. K.; Prasad, T. S.; Vijayan, D.; Balamanikavelu, P. M.

    Due to mix-up of contributions from varied features on the ground surface, getting back of individual feature in remote sensing data using pattern recognition techniques is an ill-defined inverse problem. By placing maximum likelihood (ML) constraint, the available operational softwares classify the image. Without placing any parametric constraint, the image could also be classified using artificial neural networks (ANN). As GIS overlay, developed professionally by forest officials, was available for Antilova reserve forest in Andhra Pradesh, India (170 50^' to 170 56^' N, 810 45^' to 810 54^' E), the IRS-1C LISS-III image of February 11, 1999 was used for assessing the limits of classification accuracy attainable from ML and ANN classifiers. In ML classifier, full GIS overlay was used to give training sets over whole of the image (approach `a') and in approach `b', a priori probability (normally taken equal for all the classes in operational softwares) was assigned (in addition to full spectral signature) based on the fraction areas under each class in GIS overlay. Under such ideal situation of inputs, the achieved accuracy, i.e. Kappa coefficients were 0.709 and 0.735 for approaches `a' and `b' , respectively (called iteration `0'). Using fraction area under each class in the classified output to assign a priori probability for the next iteration, the convergence (within 2% variation) was achieved for 2nd and 3rd iterations with Kappa coefficient values of 0.773 and 0.797 for approaches `a' and `b', respectively. The non-attaining of 100% classification accuracy under ideal inputs situation could be due to assumption of guassian distribution in spectral signatures. In back propagation technique based ANN classifier, spectral signatures for training were identified from GIS overlay. The number of learning iterations were 20,000 with momentum and learning rate of 0.7 and 0.25, respectively. With one hidden layer the Kappa coefficient for ANN classifier was 0

  2. Queer paradox/paradoxical queer: Anne Garréta's Pas un jour (2002).

    PubMed

    Cairns, Lucille

    2007-01-01

    This paper shows how Anne Garréta's Pas un jour (2002) is a decidedly queer text, in both the new and the old sense of that contested epithet. I examine three interrelated concerns central to Pas un jour. First, I analyze Garréta's mediation of desire in general: her own experiences of it; modalities thereof which subvert more 'normative' models of lesbianism; and her convergences with other gay, but male writers and theorists of desire such as Guy Hocquenghem, Gilles Deleuze and Michel Foucault. Second, I interrogate Garréta's dichotomy between desire and friendship, and adumbrate contrasts with Foucauldian theory. Finally, I scrutinize the meaning and value attributed to the particular body of desire with which Garréta is most commonly associated-homosexuality- and their links with those of a contemporary gay male writer, Dominique Fernandez. PMID:17804371

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

    NASA Astrophysics Data System (ADS)

    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.

  4. STS-103 Commander Curtis L. Brown Jr. and fiancee Ann Brickert at Pad 39B

    NASA Technical Reports Server (NTRS)

    1999-01-01

    STS-103 Commander Curtis L. Brown Jr. and his fiancee, Ann Brickert, pose for a photograph at Launch Pad 39B during a meeting of the STS-103 crew with their family and friends. The lights in the background are on the Fixed Service Structure next to Space Shuttle Discovery. The mission, to service the Hubble Space Telescope, is scheduled for launch Dec. 17 at 8:47 p.m. EST from Launch Pad 39B. Mission objectives include replacing gyroscopes and an old computer, installing another solid state recorder, and replacing damaged insulation in the telescope. The mission is expected to last about 8 days and 21 hours. Discovery is expected to land at KSC Sunday, Dec. 26, at about 6:25 p.m. EST.

  5. Processing/formulation parameters determining dispersity of chitosan particles: an ANNs study.

    PubMed

    Esmaeilzadeh-Gharehdaghi, Elina; Faramarzi, Mohammad Ali; Amini, Mohammad Ali; Moazeni, Esmaeil; Amani, Amir

    2014-01-01

    Although a great number of studies may be found in literature about the parameters affecting the size of chitosan nanoparticles, no systematic work so far has detailed the factors affecting the polydispersity of chitosan as an important factor determining the quality of many preparations. Herein, using artificial neural networks (ANNs), four independent variables, namely, pH and concentration of chitosan solution as well as time and amplitude of sonication of the solution were studied to determine their influence on the polydispersity of solution. We found that in an ultrasound prepared nanodispersion of chitosan, all the four input parameters have reverse but non-linear relation with the polydispersity of the nanoparticles. PMID:23795904

  6. [The utility boiler low NOx combustion optimization based on ANN and simulated annealing algorithm].

    PubMed

    Zhou, Hao; Qian, Xinping; Zheng, Ligang; Weng, Anxin; Cen, Kefa

    2003-11-01

    With the developing restrict environmental protection demand, more attention was paid on the low NOx combustion optimizing technology for its cheap and easy property. In this work, field experiments on the NOx emissions characteristics of a 600 MW coal-fired boiler were carried out, on the base of the artificial neural network (ANN) modeling, the simulated annealing (SA) algorithm was employed to optimize the boiler combustion to achieve a low NOx emissions concentration, and the combustion scheme was obtained. Two sets of SA parameters were adopted to find a better SA scheme, the result show that the parameters of T0 = 50 K, alpha = 0.6 can lead to a better optimizing process. This work can give the foundation of the boiler low NOx combustion on-line control technology. PMID:14768567

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

    PubMed Central

    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 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. PMID:21776225

  8. Evaluation of a non-point source pollution model, AnnAGNPS, in a tropical watershed

    USGS Publications Warehouse

    Polyakov, V.; Fares, A.; Kubo, D.; Jacobi, J.; Smith, C.

    2007-01-01

    Impaired water quality caused by human activity and the spread of invasive plant and animal species has been identified as a major factor of degradation of coastal ecosystems in the tropics. The main goal of this study was to evaluate the performance of AnnAGNPS (Annualized Non-Point Source Pollution Model), in simulating runoff and soil erosion in a 48 km2 watershed located on the Island of Kauai, Hawaii. The model was calibrated and validated using 2 years of observed stream flow and sediment load data. Alternative scenarios of spatial rainfall distribution and canopy interception were evaluated. Monthly runoff volumes predicted by AnnAGNPS compared well with the measured data (R2 = 0.90, P < 0.05); however, up to 60% difference between the actual and simulated runoff were observed during the driest months (May and July). Prediction of daily runoff was less accurate (R2 = 0.55, P < 0.05). Predicted and observed sediment yield on a daily basis was poorly correlated (R2 = 0.5, P < 0.05). For the events of small magnitude, the model generally overestimated sediment yield, while the opposite was true for larger events. Total monthly sediment yield varied within 50% of the observed values, except for May 2004. Among the input parameters the model was most sensitive to the values of ground residue cover and canopy cover. It was found that approximately one third of the watershed area had low sediment yield (0-1 t ha-1 y-1), and presented limited erosion threat. However, 5% of the area had sediment yields in excess of 5 t ha-1 y-1. Overall, the model performed reasonably well, and it can be used as a management tool on tropical watersheds to estimate and compare sediment loads, and identify "hot spots" on the landscape. ?? 2007 Elsevier Ltd. All rights reserved.

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

    PubMed

    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. PMID:21776225

  10. Feasibility of a Cooperative Processing Center for Anne Arundel, Baltimore, Montgomery and Prince Georges Counties in Maryland.

    ERIC Educational Resources Information Center

    Pfefferle, Richard A.; Hines, Theodore C.

    A study was conducted for the public library systems of Anne Arundel, Baltimore, Montgomery and Prince Georges Counties to determine what aspects of their acquisitions, cataloging and processing operations, if any, might be carried on cooperatively for lower costs and improved services. Conclusions and recommendations were that: (1) the growth of…

  11. A Report to the Board of Education of Anne Arundel County on the Status of the Schools.

    ERIC Educational Resources Information Center

    Anne Arundel County Board of Education, Annapolis, MD.

    This annual report for the 1979-1980 school year summarizes and gives the status of the main objectives of the major programs within the public school system of Anne Arundel County. Project objectives for the 1981-82 school year as well as the one immediately following are also presented and explained. In his statement, the Superintendent of…

  12. Evaluation and Assessment of Conservation Management Practice Effects on Water Quality – AnnAGNPS Watershed Modeling Studies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The United States Department of Agriculture (USDA)–Annualized Agricultural Non-Point Source Pollutant Loading model (AnnAGNPS) is a watershed scale, continuous simulation, daily time step, conservation management planning tool that is currently utilized in many field and watershed-scale locations ar...

  13. 78 FR 72745 - Bureau of Political-Military Affairs; Administrative Debarment of LeAnne Lesmeister Under the...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-12-03

    ... of Political-Military Affairs; Administrative Debarment of LeAnne Lesmeister Under the Arms Export... CONTACT: Sue Gainor, Director, Office of Defense Trade Controls Compliance, Bureau of Political-Military... services. Section 127.7(a) of the ITAR authorizes the Assistant Secretary of State for...

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

    PubMed

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

    2016-07-01

    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/. PMID:27179030

  15. Bodies in Space/Bodies in Motion/Bodies in Character: Adolescents Bear Witness to Anne Frank

    ERIC Educational Resources Information Center

    Chisholm, James S.; Whitmore, Kathryn F.

    2016-01-01

    Situated at the intersection of research on Holocaust education and embodied literacies this study examines how an arts-based instructional approach engaged middle school learners in developing empathetic perspectives on the Anne Frank narrative. We addressed the research question: What can adolescents who are using their bodies to gain empathy…

  16. Prediction of the Rock Mass Diggability Index by Using Fuzzy Clustering-Based, ANN and Multiple Regression Methods

    NASA Astrophysics Data System (ADS)

    Saeidi, Omid; Torabi, Seyed Rahman; Ataei, Mohammad

    2014-03-01

    Rock mass classification systems are one of the most common ways of determining rock mass excavatability and related equipment assessment. However, the strength and weak points of such rating-based classifications have always been questionable. Such classification systems assign quantifiable values to predefined classified geotechnical parameters of rock mass. This causes particular ambiguities, leading to the misuse of such classifications in practical applications. Recently, intelligence system approaches such as artificial neural networks (ANNs) and neuro-fuzzy methods, along with multiple regression models, have been used successfully to overcome such uncertainties. The purpose of the present study is the construction of several models by using an adaptive neuro-fuzzy inference system (ANFIS) method with two data clustering approaches, including fuzzy c-means (FCM) clustering and subtractive clustering, an ANN and non-linear multiple regression to estimate the basic rock mass diggability index. A set of data from several case studies was used to obtain the real rock mass diggability index and compared to the predicted values by the constructed models. In conclusion, it was observed that ANFIS based on the FCM model shows higher accuracy and correlation with actual data compared to that of the ANN and multiple regression. As a result, one can use the assimilation of ANNs with fuzzy clustering-based models to construct such rigorous predictor tools.

  17. Bridge-Builders and Storytellers: Anne M. Dunn, Ojibwe Storyteller, Shares in the Revival of Teaching and Learning Stories.

    ERIC Educational Resources Information Center

    Merritt, Judy

    1995-01-01

    Based on her belief that all of our lives are stories that are pieces to a puzzle forming the truth behind the sacredness of life, Anne Dunn--Ojibwe storyteller and author--seeks to build bridges between cultures, between generations, and between oral and written storytelling. Includes a review of her book "When Beaver Was Very Great." (SV)

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

    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 & 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.

  19. "Anne of Green Gables": A One-Act Musical Based on Lucy Maud Montgomery's Novel. Cue Sheet for Teachers.

    ERIC Educational Resources Information Center

    Flynn, Rosalind

    This performance guide is designed for teachers to use with students before and after a performance of the one-act musical based on Lucy Maud Montgomery's novel, "Anne of Green Gables," with music by Richard DeRosa and book and lyrics by Greg Gunning. The guide is designed to help teachers foster students' appreciation of theatre, dance, and…

  20. Quantifying the impact of conservation practices at the Choptank watershed in Maryland using AnnAGNPS Model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This study is being conducted at the Choptank watershed under the USDA-CEAP program with the objective of quantifying the environmental benefits of conservation practices such as cover crops using AnnAGNPS (Annualized Agricultural Non-Point Source) model. Choptank is nearly 800 square miles watersh...

  1. Boundary Crosser: Anne Whitelaw and Her Leadership Role in Girls' Secondary Schooling in England, New Zealand and East Africa

    ERIC Educational Resources Information Center

    Matthews, Kay Morris

    2005-01-01

    This paper highlights the intersections of history, gender and educational administration through a case study of an influential woman educator, Anne Whitelaw. It draws upon manuscripts, school archives, school histories, official files and periodicals from "both sides" of the world. Although known in New Zealand as the first Headmistress of…

  2. Ann Hutchinson (as subject), Dr. Joan Vernikos (R), Dee O'Hara (L), J. Evans and E. Lowe pose for

    NASA Technical Reports Server (NTRS)

    1993-01-01

    Ann Hutchinson (as subject), Dr. Joan Vernikos (R), Dee O'Hara (L), J. Evans and E. Lowe pose for pictures in the NASA Magazine aritcle 'How it Feels to be a Human Test Subject' as they prepare for a bed rest study to simulate the efects of microgravity on the human body.

  3. 78 FR 10172 - Lisa Anne Cornell and G. Ware Cornell, Jr. v. Princess Cruise Lines, Ltd. (Corp), Carnival PLC...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-13

    ... Lisa Anne Cornell and G. Ware Cornell, Jr. v. Princess Cruise Lines, Ltd. (Corp), Carnival PLC, and..., Jr., hereinafter ``Complainants,'' against Princess Cruise Lines, Ltd (Corp), Carnival plc, and... common carrier for hire of passengers from ports in the United States;'' Respondent Carnival plc ``is...

  4. Development of experimental design approach and ANN-based models for determination of Cr(VI) ions uptake rate from aqueous solution onto the solid biodiesel waste residue.

    PubMed

    Shanmugaprakash, M; Sivakumar, V

    2013-11-01

    In the present work, the evaluation capacities of two optimization methodologies such as RSM and ANN were employed and compared for predication of Cr(VI) uptake rate using defatted pongamia oil cake (DPOC) in both batch and column mode. The influence of operating parameters was investigated through a central composite design (CCD) of RSM using Design Expert 8.0.7.1 software. The same data was fed as input in ANN to obtain a trained the multilayer feed-forward networks back-propagation algorithm using MATLAB. The performance of the developed ANN models were compared with RSM mathematical models for Cr(VI) uptake rate in terms of the coefficient of determination (R(2)), root mean square error (RMSE) and absolute average deviation (AAD). The estimated values confirm that ANN predominates RSM representing the superiority of a trained ANN models over RSM models in order to capture the non-linear behavior of the given system. PMID:24080294

  5. Using an Artificial Neural Networks (ANNs) Model for Prediction of Intensive Care Unit (ICU) Outcome and Length of Stay at Hospital in Traumatic Patients

    PubMed Central

    Gholipour, Changiz; Rahim, Fakher; Fakhree, Abolghasem

    2015-01-01

    Introduction Currently applications of artificial neural network (ANN) models in outcome predicting of patients have made considerable strides in clinical medicine. This project aims to use a neural network for predicting survival and length of stay of patients in the ward and the intensive care unit (ICU) of trauma patients and to obtain predictive power of the current method. Materials and Methods We used Neuro-Solution software (NS), a leading-edge neural network software for data mining to create highly accurate and predictive models using advanced preprocessing techniques, intelligent automated neural network topology through cutting-edge distributed computing. This ANN model was used based on back-propagation, feed forward, and fed by Trauma and injury severity score (TRISS) components, biochemical findings, risk factors and outcome of 95 patients. In the next step a trained ANN was used to predict outcome, ICU and ward length of stay for 30 test group patients by processing primary data. Results The sensitivity and specificity of an ANN for predicting the outcome of traumatic patients in this study calculated 75% and 96.26%, respectively. 93.33% of outcome predictions obtained by ANN were correct. In 3.33% of predictions, results of ANN were optimistic and 3.33% of cases predicted ANN results were worse than the actual outcome of patients. Neither difference in average length of stay in the ward and ICU with predicted ANN results, were statistically significant. Correlation coefficient of two variables of ANN prediction and actual length of stay in hospital was equal to 0.643. Conclusion Using ANN model based on clinical and biochemical variables in patients with moderate to severe traumatic injury, resulted in satisfactory outcome prediction when applied to a test set. PMID:26023581

  6. ANN modelling of sediment concentration in the dynamic glacial environment of Gangotri in Himalaya.

    PubMed

    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

  7. Long-Term Precipitation Forecasting Using Large Scale Climate Indices: An ANN Approach

    NASA Astrophysics Data System (ADS)

    Jaw, T. C.; Hsu, K.; Sorooshian, S.

    2009-12-01

    Seasonal to interannual forecasting for precipitation and streamflow is needed for water resources planning. Many studies have indicated that statistical-based approaches show better skills than numerical weather models do for long-term climate forecasting. In this study an ANN model, named Self-Organizing Linear Output map (SOLO), is applied to predict long-term, watershed-scale mean areal precipitation (MAP). Several climate indices (e.g. ENSO, Nino3.4, NAO, PDO, etc.) representing large-scale climate anomalies relevant to long-term precipitation are used as the input variables of the SOLO. The SOLO classifies the selected multiple climate indices into suitable categories and maps the input variables into the MAP forecasts by the multivariate linear regressions. Two watersheds located at Northern and Southern California (the Feather River and the Santa Ana River Watershed respectively) are evaluated by the SOLO. During the test period from 1951 to 2008, the hindcast results show the SOLO forecast has more substantial skills over wet seasons than over dry seasons, while the climatology is viewed as the comparing benchmark. Moreover, the varying degrees of improvement due to the different climate index sets and forecast seasons reflect the impact of the selected indices on the regional precipitation variation.

  8. An ANN Approach to Classification of Galaxy Spectra for the 2DF Galaxy Redshift Survey

    NASA Astrophysics Data System (ADS)

    Folkes, S. R.; Lahav, O.; Maddox, S. J.

    We present a method for automated classification of galaxies with low signal-to-noise (S/N) spectra typical of redshift surveys. We develop spectral simulations based on the parameters for the 2dF Galaxy Redshift Survey, and with these simulations we investigate the technique of Principal Component Analysis when applied specifically to spectra of low S/N. We relate the objective principal components to features in the spectra and use a small number of components to successfully reconstruct the underlying signal from the low quality spectra. Using the principal components as input, we train an Artificial Neural Network (ANN) to classify the noisy simulated spectra into morphological classes, revealing the success of the classification against the observed bJ magnitude of the source, which we compare with alternative methods of classification. We find that more than 90% of our sample of normal galaxies are correctly classified into one of five broad morphological classes for simulations at bJ = 19.7. We also show the application of these methods to spectra from other sources.

  9. The Anne Frank Haven: A case of an alternative educational program in an integrative Kibbutz setting

    NASA Astrophysics Data System (ADS)

    Ben-Peretz, Miriam; Giladi, Moshe; Dror, Yuval

    1992-01-01

    The essential features of the programme of the Anne Frank Haven are the complete integration of children from low SES and different cultural backgrounds with Kibbutz children; a holistic approach to education; and the involvement of the whole community in an "open" residential school. After 33 years, it is argued that the experiment has proved successful in absorbing city-born youth in the Kibbutz, enabling at-risk populations to reach significant academic achievements, and ensuring their continued participation in the dominant culture. The basic integration model consists of "layers" of concentric circles, in dynamic interaction. The innermost circle is the class, the learning community. The Kibbutz community and the foster parents form a supportive, enveloping circle, which enables students to become part of the outer community and to intervene in it. A kind of meta-environment, the inter-Kibbutz partnership and the Israeli educational system, influence the program through decision making and guidance. Some of the principles of the Haven — integration, community involvement, a year's induction for all new students, and open residential settings — could be useful for cultures and societies outside the Kibbutz. The real "secret" of success of an alternative educational program is the dedicated, motivated and highly trained staff.

  10. Spatio-temporal analysis of soil erosion risk and runoff using AnnAGNPS

    NASA Astrophysics Data System (ADS)

    Yeshaneh, Eleni; Wagner, Wolfgang; Blöschl, Günter

    2014-05-01

    Soil erosion is one form of land degradation in Ethiopia deteriorating the fertility and productivity of the land. This fact indicates the need to delineate high erosion risk areas for appropriate soil and conservation measures. Land use/cover change is one of the important factors in soil erosion. This study attempts test and implement AnnAGNPS model to estimate the spatio-temporal patterns of soil erosion and runoff associated with land use changes in the past 50 years in the 9900 ha upstream part of the Koga catchment. High erosion risk areas will then be delineated for simulation of the appropriate soil and water conservation measures that would reduce the soil loss. The study is based on two years high temporal resolution data on discharge, sediment, and rain fall accompanied by historical land use/cover data generated from satellite imagery. In addition, it uses several documented physical parameters of the study area. The Koga catchment is one of the agriculture dominated typical catchments in the North Western Ethiopian highlands with high population density that lead to increased pressure on natural resources.

  11. ANN modeling of water consumption in the lead-acid batteries

    NASA Astrophysics Data System (ADS)

    Karimi, Mohammad Ali; Karami, Hassan; Mahdipour, Maryam

    Due to importance of the quantity of water loss in the life cycle of lead-acid batteries, water consumption tests were performed on 72 lead-acid batteries with low antimony grid alloy at different charge voltages and temperatures. Weight loss of batteries was measured during a period of 10 days. The behavior of batteries in different charge voltages and temperatures were modeled by artificial neural networks (ANNs) using MATLAB 7 media. Four temperatures were used in the training set, out of which three were used in prediction set and one in validation set. The network was trained by training and prediction data sets, and then was used for predicting water consumption in all three temperatures of prediction set. Finally, the network obtained was verified while being used in predicting water loss in defined temperatures of validation set. To achieve a better evaluation of the model ability, three models with different validation temperatures were used (model 1 = 50 °C, model 2 = 60 °C and model 3 = 70 °C). There was a good agreement between predicted and experimental results at prediction and validation sets for all the models. Mean prediction errors in modeling charge voltage-temperature-time behavior in the water consumption quantity for models 1-3 were below 0.99%, 0.03%, and 0.76%, respectively. The model can be simply used by inexpert operators working in lead-acid battery industry.

  12. Comparing ANNs, EAs, and Trees: a basic machine-learning approach to predictive environmental models.

    NASA Astrophysics Data System (ADS)

    Williams, J.; Poff, N.

    2005-05-01

    Machine learning techniques for ecological applications or "eco-informatics" are becoming increasingly useful and accessible for ecologists. We evaluated the predictive ability of three commercially available (i.e. user-friendly) software packages for artificial neural networks (ANNs), evolutionary algorithms (EAs), and classification/regression trees (Trees). We analyzed fish and habitat data for streams in the mid-Atlantic region of the U.S., which was collected by the U.S. Environmental Protection Agency (EPA). The data includes over 200 environmental descriptors summarizing watershed, stream, and water chemistry characteristics in addition to derived fish community metrics (i.e. richness, IBI scores, % exotics). In our analysis we predicted individual species presence/absence and fish community metrics as a function of these local and regional scale habitat variables. Predictive ability is evaluated with independent validation data. These approaches could prove especially useful for conservation or management applications where ecologists seek to utilize the most comprehensive data to make predictions at various scales. By employing "user-friendly" software we hope to show that ecologists, without extensive knowledge of computational science, can benefit from these techniques by extracting more information about complex ecosystems. Relative strengths and weaknesses of these three approaches are compared and recommendations for their use in conservation applications are presented.

  13. [Simulation of nitrogen and phosphorus loss in Siling Reservoir watershed with AnnAGNPS].

    PubMed

    Bian, Jin-yun; Wang, Fei-er; Yang, Jia; Yu, Jie; Lou, Li-ping; Yu, Dan-ping

    2012-08-01

    By using annual agricultural non-point source model (AnnAGNPS), this study simulated the export loading of nitrogen and phosphorus in Siling Reservoir watershed in Tiaoxi Basin, and integrated with the simulation results, the spatial distribution characteristics of non-point source pollution in the watershed was analyzed. The result showed that the export loading of nitrogen and phosphorus had similar characteristics: in the study area, the export loading of nutrients were higher in southern and western regions and lower in northern and eastern regions. Forest land mainly made up of bamboo was the main export source of nitrogen and phosphorus loading with the contribution above 90% of nutrient load of whole watershed. Three fertilization practices such as no fertilizer (CK), site-specific nutrient management (SSNM) and farmers' fertilizaction practice (FFP) were used in the scenario analysis. The scenario analysis showed that to a certain degree, SSNM could reduce the nitrogen and phosphorus loss. Comparing with FFP, the reduction of SSNM in dissolved nitrogen (DN), particle nitrogen (PN), dissolved phosphorus (DP) and particle phosphorus (PP) was 8.17%, 4.33%, 9.08% and 1.02%, respectively. PMID:23213887

  14. ANN implementation of stereo vision using a multi-layer feedback architecture

    SciTech Connect

    Mousavi, M.S.; Schalkoff, R.J.

    1994-08-01

    An Artificial Neural Network (ANN), consisting of three interacting neural modules, is developed for stereo vision. The first module locates sharp intensity changes in each of the images. The edge detection process is basically a bottom-up, one-to-one input-output mapping process with a network structure which is time-invariant. In the second module, a multilayered connectionist network is used to extract the features or primitives for disparity analysis (matching). A similarity measure is defined and computed for each pair of primitive matches and is passed to the third module. The third module solves the difficult correspondence problem by mapping it into a constraint satisfaction problem. Intra- and inter-scanline constraints are used in order to restrict possible feature matches. The inter-scanline constraints are implemented via interconnections of a three-dimensional neural network. The overall process is iterative. At the end of each network iteration, the output of the third constraint satisfaction module feeds back updated information on matching pairs as well as their corresponding location in the left and right images to the input of the second module. This iterative process continues until the output of the third module converges to an stable state. Once the matching process is completed, the disparity can be calculated, and camera calibration parameters can be used to find the three-dimensional location of object points. Results using this computational architecture are shown. 26 refs.

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

    PubMed

    Delnavaz, M; Ayati, B; Ganjidoust, H

    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. PMID:20399558

  16. Prediction of fatigue crack propagation rate on the interface of wood-FRP using the artificial neural network (ANN)

    NASA Astrophysics Data System (ADS)

    Zhang, Liang; Jia, Junhui; Liu, Yongjun

    2008-11-01

    Crack propagation rate of the interface of fiber reinforced polymer (FRP) bonded to red maple wood, is analyzed and predicted using an artificial neural network (ANN) method. The performance of Multilayer Perceptron (MLP) and Modular Neural Network (MNN) is compared to obtain an optimal ANN model to predict the crack propagation rate. The effect of various parameters of the MNN and MLP models are investigated. The number of input vectors of MLP and MNN models is studied to see if this will affect the training and predicting performance by the scatter of input vectors. At last, a new method called sensitivity analysis is adopted to explore the influenced proportion of the input vectors and the effect of load ratio, frequency, et al., on the crack propagation rate.

  17. William Henry, Duke of Gloucester (1689-1700), son of Queen Anne (1665-1714), could have ruled Great Britain.

    PubMed

    Holmes, G E F; Holmes, F F

    2008-02-01

    Hope for continuation of the Stuart dynasty in Britain ended with the death, from pneumonia in 1700, of the 11-year-old son of Princess Anne and Prince George, William Henry Duke of Gloucester. Considered by some to have been physically and mentally unfit to reign, careful examination of primary source materials shows him to have been a bright and interesting boy with mild hydrocephalus. Had he lived, he could have ruled. PMID:18463064

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

    PubMed Central

    Zou, Hui-Qin; Li, Shuo; Huang, Ying-Hua; Liu, Yong; Bauer, Rudolf; Peng, Lian; Tao, Ou; Yan, Su-Rong; Yan, Yong-Hong

    2014-01-01

    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. PMID:25214873

  19. AE index forecast at different time scales through an ANN algorithm based on L1 IMF and plasma measurements

    NASA Astrophysics Data System (ADS)

    Pallocchia, G.; Amata, E.; Consolini, G.; Marcucci, M. F.; Bertello, I.

    2008-02-01

    The AE index is known to have two main components, one directly driven by the solar wind and the other related to the magnetotail unloading process. As regards the role played by the IMF and solar wind parameters, recently several authors used artificial neural networks (ANN) to forecast AE from solar wind data. Following this track, in this paper we present a study of the AE forecast at different time scales, from 5 min to 1 h, in order to check whether the performance of the ANN prediction varies significantly as a function of the AE time resolution.The study is based on a new ANN Elman network with Bz (in GSM) and Vx as inputs, one hidden layer containing four neurons, four context units and one output neuron. We find that the forecast AE values, during disturbed AE periods, result to be always smaller than the experimental values; on the other hand, the algorithm performance improves as the time scale increases, i.e. the total standard deviation (calculated over a test data set) between the forecast and the Kyoto AE decreases as the averaging time increases. Under the hypothesis that this decrease follows an exponential law, we find that the 1 h scale normalised standard deviation is 0.975, very close to the asymptotic value of 0.95 for an infinite averaging time. We interpret our results in the sense that the unloading component of the AE variations cannot be predicted from IMF and solar wind parameters only.

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

    PubMed

    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. PMID:24732215

  1. Data fusion with artificial neural networks (ANN) for classification of earth surface from microwave satellite measurements

    NASA Technical Reports Server (NTRS)

    Lure, Y. M. Fleming; Grody, Norman C.; Chiou, Y. S. Peter; Yeh, H. Y. Michael

    1993-01-01

    A data fusion system with artificial neural networks (ANN) is used for fast and accurate classification of five earth surface conditions and surface changes, based on seven SSMI multichannel microwave satellite measurements. The measurements include brightness temperatures at 19, 22, 37, and 85 GHz at both H and V polarizations (only V at 22 GHz). The seven channel measurements are processed through a convolution computation such that all measurements are located at same grid. Five surface classes including non-scattering surface, precipitation over land, over ocean, snow, and desert are identified from ground-truth observations. The system processes sensory data in three consecutive phases: (1) pre-processing to extract feature vectors and enhance separability among detected classes; (2) preliminary classification of Earth surface patterns using two separate and parallely acting classifiers: back-propagation neural network and binary decision tree classifiers; and (3) data fusion of results from preliminary classifiers to obtain the optimal performance in overall classification. Both the binary decision tree classifier and the fusion processing centers are implemented by neural network architectures. The fusion system configuration is a hierarchical neural network architecture, in which each functional neural net will handle different processing phases in a pipelined fashion. There is a total of around 13,500 samples for this analysis, of which 4 percent are used as the training set and 96 percent as the testing set. After training, this classification system is able to bring up the detection accuracy to 94 percent compared with 88 percent for back-propagation artificial neural networks and 80 percent for binary decision tree classifiers. The neural network data fusion classification is currently under progress to be integrated in an image processing system at NOAA and to be implemented in a prototype of a massively parallel and dynamically reconfigurable Modular

  2. Assessment of strawberry aroma through SPME/GC and ANN methods. Classification and discrimination of varieties.

    PubMed

    Urruty, Louise; Giraudel, Jean-Luc; Lek, Sovan; Roudeillac, Philippe; Montury, Michel

    2002-05-22

    To provide an efficient and running analytical tool to strawberry plant breeders who have to characterize and compare the aromatic properties of new cultivars to those already known, a HS-SPME/GC-MS analysis method has been coupled with a statistical treatment method issued from the current development of artificial neuron networks (ANN), and more specifically, the unsupervised learning systems called Kohonen self-organizing maps (SOMs). So, 70 strawberry samples harvested at CIREF from 17 known varieties have been extracted by using a DVB/Carboxen/PDMS SPME fiber according to the headspace procedure, and then chromatographed. A panel of 23 characteristic aromatic constituents has been selected according to published results relative to strawberry aroma. The complex resulting matrix, collecting the relative abundance of the 23 selected constituents for each sample, has been input into the SOM software adapted and optimized from the Kohonen approach described by one of the authors. After a period of training, the self-organized system affords a map of virtual strawberries to which real samples are compared and plotted in the best matching unit (BMU) of the map. The efficiency for discriminating the real samples according to their variety is dependent on the number of units selected to define the map. In this case, a 24-unit map allowed the complete discrimination of the 17 selected varieties. Moreover, to test the validity of this approach, two additional samples were blind-analyzed and the results were computed according to the same procedure. At the end of this treatment, both samples were plotted into the same unit as those of the same variety used for training the map. PMID:12009974

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

    PubMed Central

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

    2007-01-01

    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 played by NP in the hippocampus

  4. Classification of input vectors of ANN model into "regular event" and "extreme event" subsets with fuzzy c-means algorithm

    NASA Astrophysics Data System (ADS)

    Kentel, Elcin

    2010-05-01

    Estimating future river flows is essential in water resources planning and management. Artificial neural network (ANN) models have been extensively utilized for rainfall-runoff modeling in the last decade. One of the major weaknesses of artificial neural network models is that they may fail to generate good estimates for extreme events, i.e. events that do not occur at all or often enough in the training set. If reliable estimates can be distinguished from unreliable ones, the former can be used with greater confidence in planning and management of the water resources. A fuzzy c-means algorithm is developed to cluster the estimates of the artificial neural networks into reliable and less-reliable river flow values (Kentel, 2009). The proposed algorithm is only tested for a single case (i.e. Güvenç River, Turkey) and produced promising results. In this study, applicability of the fuzzy c-means algorithm for different catchments in Turkey is tested. Three flow gauging stations are selected at four different catchments in mid and south Turkey. First, an ANN is developed for each gauging station; then fuzzy c-means algorithm is used together with the outputs of ANN models to test the success of the clustering algorithm in identifying input vectors that are susceptible to produce unreliable estimates. Results obtained for 12 gauging stations are used to identify the drawbacks of fuzzy c-means algorithm and to suggest modifications to improve the algorithm. Key words: Future river flow estimation; Artificial Neural Network; fuzzy c-means clustering Kentel, E. (2009) "Estimation of River Flow by Artificial Neural Networks and Identification of Input Vectors Susceptible to Producing Unreliable Flow Estimates," Journal of Hydrology, 375, 481-488.

  5. Selection Site for Artificial Recharge of Groundwater in Hard Rocks Using ANN with Special Reference to India

    NASA Astrophysics Data System (ADS)

    Banerjee, Pallavi

    2010-05-01

    In the recent years there has been overall development in the field of agriculture and industry in the Asian countries, particularly in India. The growth in urbanization has also been increasing. All these have lead to ever increasing demand for water. It has resulted into indiscriminate exploitation of groundwater resources, which is major source of fresh water in hard rock terrain. The hard rocks pose special problems for artificial recharge due to the limited extent of aquifer horizons, heterogeneity and low hydraulic conductivity. The fracture system may have good storativity. One such area is Kurmapalli watershed covering an area of about 108 sq km in Nalgonda district (Andhra Pradesh), India. It is drought prone area. This basin is characterized by poor land soil, scarce vegetation, erratic rainfall, heavy runoff and lack of soil moisture for most part of the year. Recurring drought coupled with increase in groundwater exploitation results in decline in the groundwater levels. Artificial Neural Network (ANN) method is a paradigm shift towards research methodology in the field of hydrology. An approach based on Back Propagation Neural Network (BPNN) algorithm is developed to estimate the best location for artificial recharge. The proposed technique is applied to climatic and hydrological data of wells gathered from the different locations of the study area. Feed Forward BPNN is used to train the predefined inputs and outputs. After successful completion of training with appropriate data, different ANN models are developed to estimate the proper site for artificial recharge. High degree of predictive accuracy of the Feed-Forward Network based predictive model proves ANN techniques is a potential tool for hydrological studies.

  6. Using ANN to predict E. coli accumulation in coves based on interaction amongst various physical, chemical and biological factors

    NASA Astrophysics Data System (ADS)

    Dwivedi, D.; Mohanty, B. P.; Lesikar, B. J.

    2008-12-01

    The accumulation of Escherichia Coli (E. coli) in canals, coves and streams is the result of a number of interacting processes operating at multiple spatial and temporal scales. Fate and transport of E. coli in surface water systems is governed by different physical, chemical, and biological processes. Various models developed to quantify each of these processes occurring at different scales are not so far pooled into a single predictive model. At present, very little is known about the fate and transport of E. coli in the environment. We hypothesize that E. coli population heterogeneity in canals and coves is affected by physical factors (average stream width and/ depth, secchi depth, flow and flow severity, day since precipitation, aquatic vegetation, solar radiation, dissolved and total suspended solids etc.); chemical factors (basic water quality, nutrients, organic compounds, pH, and toxicity etc.); and biological factors (type of bacterial strain, predation, and antagonism etc.). The specific objectives of this study are to: (1) examine the interactions between E. coli and various coupled physical, chemical and biological factors; (2) examine the interactions between E. coli and toxic organic pollutants and other pathogens (viruses); and (3) evaluate qualitatively the removal efficiency of E. coli. We suggest that artificial neural networks (ANN) may be used to provide a possible solution to this problem. To demonstrate the application of the approach, we develop an ANN representing E. coli accumulation in two polluted sites at Lake Granbury in the upper part of the Brazos River in North Central Texas. The graphical structure of ANN explicitly represents cause- and-effect relationship between system variables. Each of these relationships can then be quantified independently using an approach suitable for the type and scale of information available. Preliminary results revealed that E. coli concentrations in canals show seasonal variations regardless of change

  7. The potential of different artificial neural network (ANN) techniques in daily global solar radiation modeling based on meteorological data

    SciTech Connect

    Behrang, M.A.; Assareh, E.; Ghanbarzadeh, A.; Noghrehabadi, A.R.

    2010-08-15

    The main objective of present study is to predict daily global solar radiation (GSR) on a horizontal surface, based on meteorological variables, using different artificial neural network (ANN) techniques. Daily mean air temperature, relative humidity, sunshine hours, evaporation, and wind speed values between 2002 and 2006 for Dezful city in Iran (32 16'N, 48 25'E), are used in this study. In order to consider the effect of each meteorological variable on daily GSR prediction, six following combinations of input variables are considered: (I)Day of the year, daily mean air temperature and relative humidity as inputs and daily GSR as output. (II)Day of the year, daily mean air temperature and sunshine hours as inputs and daily GSR as output. (III)Day of the year, daily mean air temperature, relative humidity and sunshine hours as inputs and daily GSR as output. (IV)Day of the year, daily mean air temperature, relative humidity, sunshine hours and evaporation as inputs and daily GSR as output. (V)Day of the year, daily mean air temperature, relative humidity, sunshine hours and wind speed as inputs and daily GSR as output. (VI)Day of the year, daily mean air temperature, relative humidity, sunshine hours, evaporation and wind speed as inputs and daily GSR as output. Multi-layer perceptron (MLP) and radial basis function (RBF) neural networks are applied for daily GSR modeling based on six proposed combinations. The measured data between 2002 and 2005 are used to train the neural networks while the data for 214 days from 2006 are used as testing data. The comparison of obtained results from ANNs and different conventional GSR prediction (CGSRP) models shows very good improvements (i.e. the predicted values of best ANN model (MLP-V) has a mean absolute percentage error (MAPE) about 5.21% versus 10.02% for best CGSRP model (CGSRP 5)). (author)

  8. AnnAGNPS model as a potential tool for seeking adequate agriculture land management in Navarre (Spain)

    NASA Astrophysics Data System (ADS)

    Chahor, Y.; Giménez, R.; Casalí, J.

    2012-04-01

    Nowadays agricultural activities face two important challenges. They must be efficient from an economic point of view but with low environment impacts (soil erosion risk, nutrient/pesticide contamination, greenhouse gases emissions, etc.). In this context, hydrological and erosion models appear as remarkable tools when looking for the best management practices. AnnAGNPS (Annualized Agricultural Non Point Source Pollution) is a continuous simulation watershed-scale model that estimates yield and transit of surface water, sediment, nutrients, and pesticides through a watershed. This model has been successfully evaluated -in terms of annual runoff and sediment yield- in a small (around 200 ha) agricultural watershed located in central eastern part of Navarre (Spain), named Latxaga. The watershed is under a humid Sub-Mediterranean climate. It is cultivated almost entirely with winter cereals (wheat and barley) following conventional soil and tillage management practices. The remaining 15% of the watershed is covered by urban and shrub areas. The aim of this work is to evaluate in Latxga watershed the effect of potential and realistic changes in land use and management on surface runoff and sediment yield by using AnnAGNPS. Six years (2003 - 2008) of daily climate data were considered in the simulation. This dataset is the same used in the model evaluation previously made. Six different scenarios regarding soil use and management were considered: i) 60% cereals25% sunflower; ii) 60% cereals, 25% rapeseed; iii) 60% cereals, 25% legumes; iv) 60% cereals, 25% sunflower + rapeseed+ legumes, in equal parts; v) cereals, and alternatively different amount of shrubs (from 20% to 100% ); vi) only cereal but under different combinations of conventional tillage and no-tillage management. Overall, no significant differences in runoff generation were observed with the exception of scenario iii (in which legume is the main alternative crops), whit a slight increase in predicted

  9. Multi-objective optimization of process parameters in Electro-Discharge Diamond Face Grinding based on ANN-NSGA-II hybrid technique

    NASA Astrophysics Data System (ADS)

    Yadav, Ravindra Nath; Yadava, Vinod; Singh, G. K.

    2013-09-01

    The effective study of hybrid machining processes (HMPs), in terms of modeling and optimization has always been a challenge to the researchers. The combined approach of Artificial Neural Network (ANN) and Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) has attracted attention of researchers for modeling and optimization of the complex machining processes. In this paper, a hybrid machining process of Electrical Discharge Face Grinding (EDFG) and Diamond Face Grinding (DFG) named as Electrical Discharge Diamond face Grinding (EDDFG) have been studied using a hybrid methodology of ANN-NSGA-II. In this study, ANN has been used for modeling while NSGA-II is used to optimize the control parameters of the EDDFG process. For observations of input-output relations, the experiments were conducted on a self developed face grinding setup, which is attached with the ram of EDM machine. During experimentation, the wheel speed, pulse current, pulse on-time and duty factor are taken as input parameters while output parameters are material removal rate (MRR) and average surface roughness ( R a). The results have shown that the developed ANN model is capable to predict the output responses within the acceptable limit for a given set of input parameters. It has also been found that hybrid approach of ANN-NSGAII gives a set of optimal solutions for getting appropriate value of outputs with multiple objectives.

  10. Modeling daily reference ET in the karst area of northwest Guangxi (China) using gene expression programming (GEP) and artificial neural network (ANN)

    NASA Astrophysics Data System (ADS)

    Wang, Sheng; Fu, Zhi-yong; Chen, Hong-song; Nie, Yun-peng; Wang, Ke-lin

    2015-08-01

    Nonlinear complexity is a characteristic of hydrologic processes. Using fewer model parameters is recommended to reduce error. This study investigates, and compares, the ability of gene expression programming (GEP) and artificial neural network (ANN) techniques in modeling ET0 by using fewer meteorological parameters in the karst area of northwest Guangxi province, China. Over a 5-year period (2008-2012), meteorological data consisting of maximum and minimum air temperature, relative humidity, wind speed, and sunshine duration were collected from four weather stations: BaiSe, DuAn, HeChi, and RongAn. The ET0 calculated by the FAO-56 PM equation was used as a reference to evaluate results for GEP, ANN, and Hargreaves models. The coefficient of determination (R 2) and the root mean square error (RMSE) were used as statistical indicators. Evaluations revealed that GEP, and ANN, can be used to successfully model ET0. In most cases, when using the same input variables, ANN models were superior to GEP. We then established ET0 equations with fewer parameters under various conditions. GEP can produce simple explicit mathematical formulations which are easier to use than the ANN models.

  11. A Characterization of Hot Flow Behaviors Involving Different Softening Mechanisms by ANN for As-Forged Ti-10V-2Fe-3Al Alloy

    NASA Astrophysics Data System (ADS)

    Quan, Guo-zheng; Zou, Zhen-yu; Wen, Hai-rong; Pu, Shi-ao; Lv, Wen-quan

    2015-11-01

    The isothermal compressions of as-forged Ti-10V-2Fe-3Al alloy at the deformation temperature range of 948-1,123 K and the strain rates in the range of 0.001-10 s-1 with a height reduction of 60% were conducted on a Gleeble-3500 thermo-mechanical simulator. The flow behaviors show nonlinear sensitivity to strain, strain rate and temperature. Based on the experimental data, an artificial neural network (ANN) with back-propagation algorithm was developed to deal with the complex deformation behavior characteristics. In the present ANN model, strain, strain rate and temperature were taken as inputs, and flow stress as output. A comparative study on the constitutive relationships based on regression and ANN methods was conducted. According to the predicted and experimental results, the predictabilities of the two models have been evaluated in terms of correlation coefficient (R) and average absolute relative error (AARE). The R-value and the AARE-value at strain of 0.5 from the ANN model is 0.9998 and 0.572%, respectively, better than 0.9902 and 6.583% from the regression model. The predicted strain-stress curves outside of experimental conditions indicate similar characteristics with experimental curves. The results have sufficiently articulated that the well-trained ANN model with back-propagation algorithm has excellent capability to deal with the complex flow behaviors of as-forged Ti-10V-2Fe-3Al alloy.

  12. Optimization of delignification of two Pennisetum grass species by NaOH pretreatment using Taguchi and ANN statistical approach.

    PubMed

    Mohaptra, Sonali; Dash, Preeti Krishna; Behera, Sudhanshu Shekar; Thatoi, Hrudayanath

    2016-01-01

    In the bioconversion of lignocelluloses for bioethanol, pretreatment seems to be the most important step which improves the elimination of the lignin and hemicelluloses content, exposing cellulose to further hydrolysis. The present study discusses the application of dynamic statistical techniques like the Taguchi method and artificial neural network (ANN) in the optimization of pretreatment of lignocellulosic biomasses such as Hybrid Napier grass (HNG) (Pennisetum purpureum) and Denanath grass (DG) (Pennisetum pedicellatum), using alkali sodium hydroxide. This study analysed and determined a parameter combination with a low number of experiments by using the Taguchi method in which both the substrates can be efficiently pretreated. The optimized parameters obtained from the L16 orthogonal array are soaking time (18 and 26 h), temperature (60°C and 55°C), and alkali concentration (1%) for HNG and DG, respectively. High performance liquid chromatography analysis of the optimized pretreated grass varieties confirmed the presence of glucan (47.94% and 46.50%), xylan (9.35% and 7.95%), arabinan (2.15% and 2.2%), and galactan/mannan (1.44% and 1.52%) for HNG and DG, respectively. Physicochemical characterization studies of native and alkali-pretreated grasses were carried out by scanning electron microscopy and Fourier transformation Infrared spectroscopy which revealed some morphological differences between the native and optimized pretreated samples. Model validation by ANN showed a good agreement between experimental results and the predicted responses. PMID:26584152

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

    NASA Astrophysics Data System (ADS)

    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

  14. Optoelectronic performance and artificial neural networks (ANNs) modeling of n-InSe/p-Si solar cell

    NASA Astrophysics Data System (ADS)

    Darwish, A. A. A.; Hanafy, T. A.; Attia, A. A.; Habashy, D. M.; El-Bakry, M. Y.; El-Nahass, M. M.

    2015-07-01

    Nanostructure thin film of InSe deposited on p-Si single crystal to fabricate n-InSe/p-Si heterojunction. Electrical and photoelectrical have been studied by the current density-voltage (J-V). The fabricated cell exhibited rectifying characteristics. Analyzing the results of dark forward J-V shows that there are differrent conduction mechanisms. At low voltages, the current density is controlled by a Schottky emission mechanism. While at a relatively high voltage, a space charge-limited-conduction mechanism is observed with a single trap level. The cell also exhibited a photovoltaic characteristic with a power conversion efficiency of 3.42%. Moreover, artificial neural networks (ANNs) are adopted to model the J-V through the obtained functions. Different network configurations and many runs were trying to achieve good performance and finally obtained the current density, J, as a function of the junction temperature, T, and applied voltage, V. In all cases studied, we compared our obtained functions produced by the ANN technique with the corresponding experimental data and the excellent matching was so clear.

  15. A method to improve the stability and accuracy of ANN- and SVM-based time series models for long-term groundwater level predictions

    NASA Astrophysics Data System (ADS)

    Yoon, Heesung; Hyun, Yunjung; Ha, Kyoochul; Lee, Kang-Kun; Kim, Gyoo-Bum

    2016-05-01

    The prediction of long-term groundwater level fluctuations is necessary to effectively manage groundwater resources and to assess the effects of changes in rainfall patterns on groundwater resources. In the present study, a weighted error function approach was utilised to improve the performance of artificial neural network (ANN)- and support vector machine (SVM)-based recursive prediction models for the long-term prediction of groundwater levels in response to rainfall. The developed time series models were applied to groundwater level data from 5 groundwater-monitoring stations in South Korea. The results demonstrated that the weighted error function approach can improve the stability and accuracy of recursive prediction models, especially for ANN models. The comparison of the model performance showed that the recursive prediction performance of the SVM was superior to the performance of the ANN in this case study.

  16. Comparison of estimation capabilities of response surface methodology (RSM) with artificial neural network (ANN) in lipase-catalyzed synthesis of palm-based wax ester

    PubMed Central

    Basri, Mahiran; Rahman, Raja Noor Zaliha Raja Abd; Ebrahimpour, Afshin; Salleh, Abu Bakar; Gunawan, Erin Ryantin; Rahman, Mohd Basyaruddin Abd

    2007-01-01

    Background Wax esters are important ingredients in cosmetics, pharmaceuticals, lubricants and other chemical industries due to their excellent wetting property. Since the naturally occurring wax esters are expensive and scarce, these esters can be produced by enzymatic alcoholysis of vegetable oils. In an enzymatic reaction, study on modeling and optimization of the reaction system to increase the efficiency of the process is very important. The classical method of optimization involves varying one parameter at a time that ignores the combined interactions between physicochemical parameters. RSM is one of the most popular techniques used for optimization of chemical and biochemical processes and ANNs are powerful and flexible tools that are well suited to modeling biochemical processes. Results The coefficient of determination (R2) and absolute average deviation (AAD) values between the actual and estimated responses were determined as 1 and 0.002844 for ANN training set, 0.994122 and 1.289405 for ANN test set, and 0.999619 and 0.0256 for RSM training set respectively. The predicted optimum condition was: reaction time 7.38 h, temperature 53.9°C, amount of enzyme 0.149 g, and substrate molar ratio 1:3.41. The actual experimental percentage yield was 84.6% at optimum condition, which compared well to the maximum predicted value by ANN (83.9%) and RSM (85.4%). The order of effective parameters on wax ester percentage yield were; respectively, time with 33.69%, temperature with 30.68%, amount of enzyme with 18.78% and substrate molar ratio with 16.85%, whereas R2 and AAD were determined as 0.99998696 and 1.377 for ANN, and 0.99991515 and 3.131 for RSM respectively. Conclusion Though both models provided good quality predictions in this study, yet the ANN showed a clear superiority over RSM for both data fitting and estimation capabilities. PMID:17760990

  17. Forward Greedy ANN input selection in a stacked framework with Adaboost.RT - A streamflow forecasting case study exploiting radar rainfall estimates

    NASA Astrophysics Data System (ADS)

    Brochero, D.; Anctil, F.; Gagné, C.

    2012-04-01

    In input selection (or feature selection), modellers are interested in identifying k of the d dimensions that provide the most information. In hydrology, this problem is particularly relevant when dealing with temporally and spatially distributed data such as radar rainfall estimates or meteorological ensemble forecasts. The most common approaches for input determination of artifitial neural networks (ANN) in water resources are cross-correlation, heuristics, embedding window analysis (chaos theory), and sensitivity analyses. We resorted here to Forward Greedy Selection (FGS), a sensitivity analysis, for identifying the inputs that maximize the performance of ANN forecasting. It consists of a pool of ANNs with different structures, initial weights, and training data subsets. The stacked ANN model was setup through the joint use of stop training and a special type of boosting for regression known as AdaBoost.RT. Several ANN are then used in series, each one exploiting, with incremental probability, data with relative estimation error higher than a pre-set threshold value. The global estimate is then obtained from the aggregation of the estimates of the models (here the median value). Two schemes are compared here, which differ in their input type. The first scheme looks at lagged radar rainfall estimates averaged over entire catchment (the average scenario), while the second scheme deals with the spatial variation fields of the radar rainfall estimates (the distributed scenario). Results lead to three major findings. First, stacked ANN response outperforms the best single ANN (in the same way as many others reports). Second, a positive gain in the test subset of around 20%, when compared to the average scenario, is observed in the distributed scenario. However, the most important result from the selecting process is the final structure of the inputs, for the distributed scenario clearly outlines the areas with the greatest impact on forecasting in terms of the

  18. Dating of pollen samples from the sediment core of Lake St Anne in the East Carpathian Mountains, Romania

    NASA Astrophysics Data System (ADS)

    Hubay, Katalin; Katalin Magyari, Enikö; Braun, Mihály; Schabitz, Frank; Molnár, Mihály

    2016-04-01

    Lake St Anne (950 m a.s.l.) is situated in the Ciomadul volcano crater, the youngest volcano in the Carpathians. Aims driving forward the studies there are twofold, one is dating the latest eruption of the Ciomadul volcano and the other is the multi-proxy palaeoenvironmental reconstruction of this region. The sediment of Lake St Anne was sampled several times already, but never reached the bottom of the lake before. During the winter of 2013 at a new core location drilling started at 600 cm water depth and finally reached the bottom of the lake sediment at approximately 2300 cm including water depth. As for all multi-proxy studies essential requirement was to build a reliable chronology. Sediments were dated by radiocarbon method. Previous radiocarbon dates were measured on plant macrofossils, charcoal, Cladocera eggs, chironomid head capsules and bulk lake sediments. Lake St Anne has volcanic origin and there is intensive upwelling of CO2it is important to study and take into consideration, whether there is any local reservoir effect at the case of samples where it could be problematic. Furthermore the late part of the sediment section (between 15,000 and 30,000 cal. yr BP) has low organic matter content (less than 2-4%) with scarcity of datable plant macrofossil material. In this review a different fraction of pollen samples with terrestrial origin was tested and studied as a novel sample type for the radiocarbon dating. Pollen samples were extracted from the lake sediment cores. This type of organic material could be an ideal candidate for radiocarbon based chronological studies as it has terrestrial source and is present in the whole core in contrast with the terrestrial macrofossils. Although the pollen remains were present in the whole core, in many cases their amount give a challenge even for the AMS technic. Samples were measured with EnvironMICADAS AMS and its gas ion source in the HEKAL laboratory (Debrecen, Hungary). We examine the reliability the

  19. Estimation of runoff and sediment yield in the Redrock Creek watershed using AnnAGNPS and GIS

    USGS Publications Warehouse

    Tsou, M.-S.; Zhan, X.-Y.

    2004-01-01

    Sediment has been identified as a significant threat to water quality and channel clogging that in turn may lead to river flooding. With the increasing awareness of the impairment from sediment to water bodies in a watershed, identifying the locations of the major sediment sources and reducing the sediment through management practices will be important for an effective watershed management. The annualized agricultural non-point source pollution (AnnAGNPS) model and newly developed GIS interface for it were applied in a small agricultural watershed, Redrock Creek watershed, Kansas, in this pilot study for exploring the effectiveness of using this model as a management tool. The calibrated model appropriately simulated monthly runoff and sediment yield through the practices in this study and potentially suggested the ways of sediment reduction through evaluating the changes of land use and field operation in the model for the purpose of watershed management.

  20. Estimating sediment, nitrogen, and phosphorous loads from the Pipestem Creek watershed, North Dakota, using AnnAGNPS

    NASA Astrophysics Data System (ADS)

    Pease, Lyndon M.; Oduor, P.; Padmanabhan, G.

    2010-03-01

    Agricultural pollution is a significant problem in North Dakota. Water quality in the Pipestem Creek watershed upstream of Pingree, North Dakota, USA, has been a major environmental concern amongst other adjacent watersheds within the region. The annualized agricultural non-point source (AnnAGNPS) model, a large-scale watershed model designed to predict sediment and nutrient loads, was used to evaluate non-point source pollution in a typical agricultural watershed. The best available data were assembled and used in the analysis. The model predicted runoff of 0.31 m 3/s, compared to a measured value of 0.46 m 3/s. A poor correlation was observed when comparing the model's predicted nitrogen, phosphorus, and sediment with the observed counterparts. The model's poor performance was most likely a result of the large size of the study area and the high variability in land use and management practices.

  1. Modeling and prediction of surface roughness for running-in wear using Gauss-Newton algorithm and ANN

    NASA Astrophysics Data System (ADS)

    Hanief, M.; Wani, M. F.

    2015-12-01

    In this paper, surface roughness model for running-in and steady state of the wear process is proposed. In this work monotonously decreasing trend of surface roughness during running-in was assumed. The model was developed by considering the surface roughness as an explicit function of time during running-in, keeping other system parameters (velocity, load, hardness, etc.) constant. The proposed model being non-linear, optimal values of the model parameters were evaluated by Gauss-Newton (GN) algorithm. The experimental results adopted from the literature, for steel and Cu-Zn alloy specimens, were used for validation of the model. Artificial neural network (ANN) based model was also developed and was compared with the proposed model on the basis of statistical methods (coefficient of determination (R2), mean square error (MSE) and mean absolute percentage error (MAPE)).

  2. Predicting spatial kelp abundance in shallow coastal waters using the acoustic ground discrimination system RoxAnn

    NASA Astrophysics Data System (ADS)

    Mielck, F.; Bartsch, I.; Hass, H. C.; Wölfl, A.-C.; Bürk, D.; Betzler, C.

    2014-04-01

    Kelp forests represent a major habitat type in coastal waters worldwide and their structure and distribution is predicted to change due to global warming. Despite their ecological and economical importance, there is still a lack of reliable spatial information on their abundance and distribution. In recent years, various hydroacoustic mapping techniques for sublittoral environments evolved. However, in turbid coastal waters, such as off the island of Helgoland (Germany, North Sea), the kelp vegetation is present in shallow water depths normally excluded from hydroacoustic surveys. In this study, single beam survey data consisting of the two seafloor parameters roughness and hardness were obtained with RoxAnn from water depth between 2 and 18 m. Our primary aim was to reliably detect the kelp forest habitat with different densities and distinguish it from other vegetated zones. Five habitat classes were identified using underwater-video and were applied for classification of acoustic signatures. Subsequently, spatial prediction maps were produced via two classification approaches: Linear discriminant analysis (LDA) and manual classification routine (MC). LDA was able to distinguish dense kelp forest from other habitats (i.e. mixed seaweed vegetation, sand, and barren bedrock), but no variances in kelp density. In contrast, MC also provided information on medium dense kelp distribution which is characterized by intermediate roughness and hardness values evoked by reduced kelp abundances. The prediction maps reach accordance levels of 62% (LDA) and 68% (MC). The presence of vegetation (kelp and mixed seaweed vegetation) was determined with higher prediction abilities of 75% (LDA) and 76% (MC). Since the different habitat classes reveal acoustic signatures that strongly overlap, the manual classification method was more appropriate for separating different kelp forest densities and low-lying vegetation. It became evident that the occurrence of kelp in this area is not

  3. The use of artificial neural network (ANN) for the prediction and simulation of oil degradation in wastewater by AOP.

    PubMed

    Mustafa, Yasmen A; Jaid, Ghydaa M; Alwared, Abeer I; Ebrahim, Mothana

    2014-06-01

    The application of advanced oxidation process (AOP) in the treatment of wastewater contaminated with oil was investigated in this study. The AOP investigated is the homogeneous photo-Fenton (UV/H2O2/Fe(+2)) process. The reaction is influenced by the input concentration of hydrogen peroxide H2O2, amount of the iron catalyst Fe(+2), pH, temperature, irradiation time, and concentration of oil in the wastewater. The removal efficiency for the used system at the optimal operational parameters (H2O2 = 400 mg/L, Fe(+2) = 40 mg/L, pH = 3, irradiation time = 150 min, and temperature = 30 °C) for 1,000 mg/L oil load was found to be 72%. The study examined the implementation of artificial neural network (ANN) for the prediction and simulation of oil degradation in aqueous solution by photo-Fenton process. The multilayered feed-forward networks were trained by using a backpropagation algorithm; a three-layer network with 22 neurons in the hidden layer gave optimal results. The results show that the ANN model can predict the experimental results with high correlation coefficient (R (2) = 0.9949). The sensitivity analysis showed that all studied variables (H2O2, Fe(+2), pH, irradiation time, temperature, and oil concentration) have strong effect on the oil degradation. The pH was found to be the most influential parameter with relative importance of 20.6%. PMID:24595749

  4. Women's translations of scientific texts in the 18th century: a case study of Marie-Anne Lavoisier.

    PubMed

    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. PMID:22606747

  5. [Discriminating and quantifying potential adulteration in virgin olive oil by near infrared spectroscopy with BP-ANN and PLS].

    PubMed

    Weng, Xin-Xin; Lu, Feng; Wang, Chuan-Xian; Qi, Yun-Peng

    2009-12-01

    In the present paper, the use of near infrared spectroscopy (NIR) as a rapid and cost-effective classification and quantification techniques for the authentication of virgin olive oil were preliminarily investigated. NIR spectra in the range of 12 000 - 3 700 cm(-1) were recorded for pure virgin olive oil and virgin olive oil samples adulterated with varying concentrations of sesame oil, soybean oil and sunflower oil (5%-50% adulterations in the weight of virgin olive oil). The spectral range from 12 000 to 5 390 cm(-1) was adopted to set up an analysis model. In order to handle these data efficiently, after pretreatment, firstly, principal component analysis (PCA) was used to compress thousands of spectral data into several variables and to describe the body of the spectra, and the analysis suggested that the cumulate reliabilities of the first six components was more than 99.999%. Then ANN-BP was chosen as further research method. The six components were secondly applied as ANN-BP inputs. The experiment took a total of 100 samples as original model examples and left 52 samples as unknown samples to predict. Finally, the results showed that the 52 test samples were discriminated accurately. And the calibration models of quantitative analysis were built using partial-least-square (PLS). The R values for PLS model are 98.77, 99.37 and 99.44 for sesame oil, soybean oil and sunflower oil respectively, the root mean standard errors of cross validation (RMSECV) are 1.3, 1.1 and 1.04 respectively. Overall, the near infrared spectroscopic method in the present paper played a good role in the discrimination and quantification, and offered a new approach to the rapid discrimination of pure and adulterated virgin olive oil. PMID:20210151

  6. Proceedings of Workshop on Priority Great Lakes Environmental Research Initiatives (Great Lakes Environmental Research Laboratory, Ann Arbor, Michigan, October 10-11, 1974).

    ERIC Educational Resources Information Center

    Pinsak, Arthur P., Ed.

    This publication contains the proceedings of a workshop held in Ann Arbor, Michigan to identify the priority Great Lakes environmental research initiatives. The five major objectives of the workshop include the determination of research initiatives, opportunities for university research communities to discuss and recommend future research…

  7. Evaluation of the AnnAGNPS model for predicting runoff and sediment yield in a small Mediterranean agricultural watershed in Navarre (Spain)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    AnnAGNPS (Annualized Agricultural Non-Point Source Pollution Model) is a system of computer models developed to predict non-point source pollutant loadings within agricultural watersheds. It contains a daily time step distributed parameter continuous simulation surface runoff model designed to assis...

  8. Comparison of artificial neural network (ANN) and response surface methodology (RSM) in optimization of the immobilization conditions for lipase from Candida rugosa on Amberjet(®) 4200-Cl.

    PubMed

    Fatiha, Benamia; Sameh, Bouchagra; Youcef, Saihi; Zeineddine, Djeghaba; Nacer, Rebbani

    2013-01-01

    Candida rugosa lipase (CRL) is an important industrial enzyme that is successfully utilized in a variety of hydrolysis and esterification reactions. This work describes the optimization of immobilization conditions (enzyme/support ratio, immobilization temperature, and buffer concentration) of CRL on the anionic resin Amberjet® 4200-Cl, using enantioselectivity (E) as the reference parameter. The model reaction used for this purpose is the acylation of (R,S)-1-phenylethanol. Optimal conditions for immobilization have been investigated through a response surface methodology (RSM) and artificial neural network (ANN). The coefficient of determination (R(2)) and the root mean square error (RMSE) values between the calculated and estimated responses were respectively equal to 0.99 and 0.06 for the ANN training set, 0.97 and 0.2 for the ANN testing set, and 0.94 and 0.4 for the RSM training set. Both models provided good quality predictions, yet the ANN showed a clear superiority over RSM for both data fitting and estimation capabilities. PMID:23215653

  9. Artificial neural network (ANN) modeling of adsorption of methylene blue by NaOH-modified rice husk in a fixed-bed column system.

    PubMed

    Chowdhury, Shamik; Saha, Papita Das

    2013-02-01

    In this study, rice husk was modified with NaOH and used as adsorbent for dynamic adsorption of methylene blue (MB) from aqueous solutions. Continuous removal of MB from aqueous solutions was studied in a laboratory scale fixed-bed column packed with NaOH-modified rice husk (NMRH). Effect of different flow rates and bed heights on the column breakthrough performance was investigated. In order to determine the most suitable model for describing the adsorption kinetics of MB in the fixed-bed column system, the bed depth service time (BDST) model as well as the Thomas model was fitted to the experimental data. An artificial neural network (ANN)-based model was also developed for describing the dynamic dye adsorption process. An extensive error analysis was carried out between experimental data and data predicted by the models by using the following error functions: correlation coefficient (R(2)), average relative error, sum of the absolute error and Chi-square statistic test (χ(2)). Results show that with increasing bed height and decreasing flow rate, the breakthrough time was delayed. All the error functions yielded minimum values for the ANN model than the traditional models (BDST and Thomas), suggesting that the ANN model is the most suitable model to describe the fixed-bed adsorption of MB by NMRH. It is also more rational and reliable to interpret dynamic dye adsorption data through a process of ANN architecture. PMID:22562342

  10. Application of calibrated AnnAGNPS model to assess stream flow, pesticide loading, and conservation tillage effects in the Cedar Creek Watershed

    Technology Transfer Automated Retrieval System (TEKTRAN)

    AnnAGNPS was applied to the Cedar Creek Watershed and its Matson Ditch sub-catchment in the St. Joseph River Watershed to assess its effectiveness at predicting monthly hydrology and pesticide loading at different scales. The model was also utilized to assess the effects that conservation tillage ha...

  11. [BISPHENOL A--AN INFAMOUS MOLECULE].

    PubMed

    Gutman, Aharona; Shoenfeld, Yehuda

    2015-11-01

    Bisphenol A (BPA) is a monomer found in plastic products used daily for the storage and consumption of food and beverages, such as plastic bottles, containers, and even toys. The molecule leaches out into the food, increasingly if exposed to warm temperatures and high acidity. BPA is known for many negative effects on the human body; for instance it acts as an xenoestrogen and influences fertility and gestation and might also have carcinogenic effects, causing breast and prostate cancer. Although it has not yet been proven as a direct cause of autoimmunity, many of the effects of BPA can be related to the pathogenesis of autoimmune disease (AID). Its estrogenic behavior modulates the immune system, it encourages the secretion of Prolactin that is known to be associated to AID, it creates oxidative stress that triggers the immune system and so on. Therefore there is room to advise individuals at risk for AID to avoid the consumption of BPA, similar to guidelines for pregnant women. PMID:26821503

  12. Down-regulating annexin gene GhAnn2 inhibits cotton fiber elongation and decreases Ca2+ influx at the cell apex.

    PubMed

    Tang, Wenxin; He, Yonghui; Tu, Lili; Wang, Maojun; Li, Yang; Ruan, Yong-Ling; Zhang, Xianlong

    2014-08-01

    Cotton fiber is a single cell that differentiates from the ovule epidermis and undergoes synchronous elongation with high secretion and growth rate. Apart from economic importance, cotton fiber provides an excellent single-celled model for studying mechanisms of cell-growth. Annexins are Ca(2+)- and phospholipid-binding proteins that have been reported to be localized in multiple cellular compartments and involved in control of vesicle secretions. Although several annexins have been found to be highly expressed in elongating cotton fibers, their functional roles in fiber development remain unknown. Here, 14 annexin family members were identified from the fully sequenced diploid G. raimondii (D5 genome), half of which were expressed in fibers of the cultivated tetraploid species G. hirsutum (cv. YZ1). Among them, GhAnn2 from the D genome of the tetraploid species displayed high expression level in elongating fiber. The expression of GhAnn2 could be induced by some phytohormones that play important roles in fiber elongation, such as IAA and GA3. RNAi-mediated down-regulation of GhAnn2 inhibited fiber elongation and secondary cell wall synthesis, resulting in shorter and thinner mature fibers in the transgenic plants. Measurement with non-invasive scanning ion-selective electrode revealed that the rate of Ca(2+) influx from extracellular to intracellular was decreased at the fiber cell apex of GhAnn2 silencing lines, in comparison to that in the wild type. These results indicate that GhAnn2 may regulate fiber development through modulating Ca(2+) fluxes and signaling. PMID:24890373

  13. Evaluation of the AnnAGNPS model for predicting runoff and sediment yield in a small Mediterranean agricultural watershed

    NASA Astrophysics Data System (ADS)

    Chahor, Youssef; Casalí, Javier; Goñi, Mikel; Giménez, Rafael; Campo, Miguel A.; Del Valle de Lersundi, Jokin

    2010-05-01

    Four experimental watersheds with contrasting land uses located in Navarre (Spain), and maintained by the local government have been monitored and studied since 1996 (La Tejería and Latxaga) and 2001 (Oskotz principal and Oskotz woodland). As a result, a detailed description and a general characterization of the hydrological and erosion behaviour of these watersheds were published recently by the same authors of this current research. This information is of great utility for evaluation of modelling tools; however, we have been done few efforts until now in this research line. The Annualized Agricultural Non Point Source Pollution Model (AnnAGNPS) is a well known and widely used model developed by the USDA-ARS and the USDA- NRCS, to assess the hydrologic and water quality responses of watersheds. More precisely, it is a distributed parameter, physically based, continuous simulation, and daily time step model. The purpose of this study is then to evaluate the AnnAGNPS model capability to simulate runoff and sediment yield with data sets from one of our agricultural watershed: Latxaga. Latxaga watershed covers an area of 207 ha and is located in the central eastern part of Navarre. Its climate is humid Sub-Mediterranean, with an average annual precipitation of 835 mm, and an average annual temperature of 12.8 °C. Geologically, the area is underlined by clay marls and sandstones. Prevailing soils are alkaline with a fine texture top-layer. Regarding land use, 80-90% of the total area is cultivated with winter grain crops. The model was calibrated using two years (2003 and 2004) of continuous 10-min/daily data, whereas another whole year (2005) was used for model validation. The calibration process was carried out by modifying Curve Number (CN) values obtained by standard procedure. CN represents a key factor in obtaining accurate prediction of runoff and sediment yield; besides it is the most important input parameter to which the runoff is sensitive. The target

  14. BP-ANN for Fitting the Temperature-Germination Model and Its Application in Predicting Sowing Time and Region for Bermudagrass

    PubMed Central

    Pi, Erxu; Mantri, Nitin; Ngai, Sai Ming; Lu, Hongfei; Du, Liqun

    2013-01-01

    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 R2 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 of

  15. Carol Anne Bond v the United States of America: how a woman scorned threatened the Chemical Weapons Convention.

    PubMed

    Muldoon, Anna; Kornblet, Sarah; Katz, Rebecca

    2011-09-01

    The case of Carol Anne Bond v the United States of America stemmed from a domestic dispute when Ms. Bond attempted to retaliate against her best friend by attacking her with chemical agents. What has emerged is a much greater issue--a test of standing on whether a private citizen can challenge the Tenth Amendment. Instead of being prosecuted in state court for assault, Ms. Bond was charged and tried in district court under a federal criminal statute passed as part of implementation of the Chemical Weapons Convention (CWC). Ms. Bond's argument rests on the claim that the statute exceeded the federal government's enumerated powers in criminalizing her behavior and violated the Constitution, while the government contends legislation implementing treaty obligations is well within its purview. This question remains unanswered because there is dispute among the lower courts as to whether Ms. Bond, as a citizen, even has the right to challenge an amendment guaranteeing states rights when a state is not a party to the action. The Supreme Court heard the case on February 22, 2011, and, if it decides to grant Ms. Bond standing to challenge her conviction, the case will be returned to the lower courts. Should the court decide Ms. Bond has the standing to challenge her conviction and further questions the constitutionality of the law, it would be a significant blow to implementation of the CWC in the U.S. and the effort of the federal government to ensure we are meeting our international obligations. PMID:21819227

  16. The collaboration of Antoine and Marie-Anne Lavoisier and the first measurements of human oxygen consumption.

    PubMed

    West, John B

    2013-12-01

    Antoine Lavoisier (1743-1794) was one of the most eminent scientists of the late 18th century. He is often referred to as the father of chemistry, in part because of his book Elementary Treatise on Chemistry. In addition he was a major figure in respiratory physiology, being the first person to recognize the true nature of oxygen, elucidating the similarities between respiration and combustion, and making the first measurements of human oxygen consumption under various conditions. Less well known are the contributions made by his wife, Marie-Anne Lavoisier. However, she was responsible for drawings of the experiments on oxygen consumption when the French revolution was imminent. These are of great interest because written descriptions are not available. Possible interpretations of the experiments are given here. In addition, her translations from English to French of papers by Priestley and others were critical in Lavoisier's demolition of the erroneous phlogiston theory. She also provided the engravings for her husband's textbook, thus documenting the extensive new equipment that he developed. In addition she undertook editorial work, for example in preparing his posthumous memoirs. The scientific collaboration of this husband-wife team is perhaps unique among the giants of respiratory physiology. PMID:24097559

  17. Controller development of photo bioreactor for closed-loop regulation of O2 production based on ANN model reference control and computer simulation

    NASA Astrophysics Data System (ADS)

    Hu, Dawei; Zhang, Houkai; Zhou, Rui; Li, Ming; Sun, Yi

    2013-02-01

    When Bioregenerative Life Support System (BLSS) is used for long-term deep space exploration in the future, it is possible to perform closed-loop control on growth of microalgae to effectively regulate O2 production process in emergencies. However, designing controller of microalgae cultivating device (MCD) by means of traditional methods is very difficult or even impossible due to its highly nonlinearity and large operation scope. In our research, the Artificial Neural Network Model Reference Control (ANN-MRC) method was therefore utilized for model identification and controller design for O2 production process of a specific MCD prototype—photo bioreactor (PBR), based on actual experiment and computer simulation. The results demonstrated that the ANN-MRC servo controller could robustly and self-adaptively control and regulate the light intensity of PBR to make O2 concentrations in vent pipe be in line with step reference concentrations with prescribed dynamic response performance.

  18. Factors influencing future transit efficiency: Evaluation of the demographic impact on guideway transit systems using GIS and ANN technologies. Report for September 1994-December 1995

    SciTech Connect

    Shen, L.D.; Huang, J.; Lee, Y.K.; Zhao, F.

    1995-12-01

    In this report, various demographic factors influencing urban guideway transit ridership have been identifed and evaluated by geographic information system technology. Demographic trends at the national level have been summarized with respect to the aging population, suburbanization, automobile. This study centers around three major U.S. metropolitan areas including Greater Washington, D.C., Boston, Massachusetts, and Chicago, Illinois. The relationship between guideway transit ridership and demographic characteristics is modeled using the artificial neural network (ANN) technology.

  19. Use of Artificial Neural Networks (ANNs) for the Analysis and Modeling of Factors That Affect Occupational Injuries in Large Construction Industries

    PubMed Central

    Mohammadfam, Iraj; Soltanzadeh, Ahmad; Moghimbeigi, Abbas; Savareh, Behrouz Alizadeh

    2015-01-01

    Introduction Occupational injuries as a workforce’s health problem are very important in large-scale workplaces. Analysis and modeling the health-threatening factors are good ways to promote the workforce’s health and a fundamental step in developing health programs. The purpose of this study was ANN modeling of the severity of occupational injuries to determine the health-threatening factors and to introduce a model to predict the severity of occupational injuries. Methods This analytical chain study was conducted in 10 large construction industries during a 10-year period (2005–2014). Nine hundred sixty occupational injuries were analyzed and modeled based on feature weighting by the rough set theory and artificial neural networks (ANNs). Two analytical software programs, i.e., RSES and MATLAB 2014 were used in the study. Results The severity of occupational injuries was calculated as 557.47 ± 397.87 days. The findings of both models showed that the injuries’ severity as a health problem resulted in various factors, including individual, organizational, health and safety (H&S) training, and risk management factors, which could be considered as causal and predictive factors of accident severity rate (ASR). Conclusion The results indicated that ANNs were a reliable tool that can be used to analyze and model the severity of occupational injuries as one of the important health problems in large-scale workplaces. Additionally, the combination of rough set and ANNs is a good and proper chain approach to modeling the factors that threaten the health of workforces and other H&S problems. PMID:26767107

  20. Modeling of biosorption of Cu(II) by alkali-modified spent tea leaves using response surface methodology (RSM) and artificial neural network (ANN)

    NASA Astrophysics Data System (ADS)

    Ghosh, Arpita; Das, Papita; Sinha, Keka

    2015-06-01

    In the present work, spent tea leaves were modified with Ca(OH)2 and used as a new, non-conventional and low-cost biosorbent for the removal of Cu(II) from aqueous solution. Response surface methodology (RSM) and artificial neural network (ANN) were used to develop predictive models for simulation and optimization of the biosorption process. The influence of process parameters (pH, biosorbent dose and reaction time) on the biosorption efficiency was investigated through a two-level three-factor (23) full factorial central composite design with the help of Design Expert. The same design was also used to obtain a training set for ANN. Finally, both modeling methodologies were statistically compared by the root mean square error and absolute average deviation based on the validation data set. Results suggest that RSM has better prediction performance as compared to ANN. The biosorption followed Langmuir adsorption isotherm and it followed pseudo-second-order kinetic. The optimum removal efficiency of the adsorbent was found as 96.12 %.

  1. The adventures of Ann: A case study of a kindergarten teacher and her beliefs as she explored integrating science into her literacy curriculum

    NASA Astrophysics Data System (ADS)

    Potter, Gregory Ralph

    Science education is an often neglected portion of the curriculum in elementary school, particularly in the primary grades. While early childhood educators have many choices in their curricula, two constants remain, literacy and math education. Ideally, young children need science along with literacy and mathematics. This study investigated how one kindergarten teacher used science to enhance her literacy program and how this use of science in her classroom affected her teaching beliefs. The case study took place in a publicly funded early childhood education center devoted to teaching kindergarten children in the small town of Summers in rural northern California. "Ann" was a master kindergarten teacher who historically used developmentally appropriate activities to support her literacy instruction. She was posed with the suggestion of infusing science into her literacy program and over the course of one school year, she was observed planning, implementing, and reflecting on six integrated science and literacy units. Ann's general teaching beliefs as well as her beliefs about teaching literacy and science were explored in order to investigate whether her experience with the integrated science and literacy units had altered her teaching beliefs. It was discovered that not only had Ann significantly changed the way she taught science, her beliefs about teaching science had changed and had moved towards mimicking her pro-active and positive beliefs about teaching literacy.

  2. An Experimental Investigation into the Optimal Processing Conditions for the CO2 Laser Cladding of 20 MnCr5 Steel Using Taguchi Method and ANN

    NASA Astrophysics Data System (ADS)

    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.

  3. Modeling of biosorption of Cu(II) by alkali-modified spent tea leaves using response surface methodology (RSM) and artificial neural network (ANN)

    NASA Astrophysics Data System (ADS)

    Ghosh, Arpita; Das, Papita; Sinha, Keka

    2014-04-01

    In the present work, spent tea leaves were modified with Ca(OH)2 and used as a new, non-conventional and low-cost biosorbent for the removal of Cu(II) from aqueous solution. Response surface methodology (RSM) and artificial neural network (ANN) were used to develop predictive models for simulation and optimization of the biosorption process. The influence of process parameters (pH, biosorbent dose and reaction time) on the biosorption efficiency was investigated through a two-level three-factor (23) full factorial central composite design with the help of Design Expert. The same design was also used to obtain a training set for ANN. Finally, both modeling methodologies were statistically compared by the root mean square error and absolute average deviation based on the validation data set. Results suggest that RSM has better prediction performance as compared to ANN. The biosorption followed Langmuir adsorption isotherm and it followed pseudo-second-order kinetic. The optimum removal efficiency of the adsorbent was found as 96.12 %.

  4. Blending single beam RoxAnn and multi-beam swathe QTC hydro-acoustic discrimination techniques for the Stonehaven area, Scotland, UK

    NASA Astrophysics Data System (ADS)

    Serpetti, Natalia; Heath, Mike; Armstrong, Eric; Witte, Ursula

    2011-05-01

    Surface properties of the seabed in a 180 km 2 area of coastal waters (14-57 m depth) off northeast Scotland were mapped by hydro-acoustic discrimination using single and multi-beam echosounders linked to signal processing systems (RoxAnn for the single beam, and Questor Tangent Corporation (QTC) Multiview for the multibeam). Subsequently, two ground truthing surveys were carried out, using grab and TV sampling. The RoxAnn and QTC-Multiview outputs showed strong similarity in their classifications of seabed types. Classifications generated by QTC-Multiview were used to supervise those based on seabed roughness and hardness indices produced by the RoxAnn system and thereby develop a 'blended' map based on both systems. The resulting hydro-acoustic classes agreed well with a cluster analysis of data on sediment grain sizes from the grab sampling, and indicated that the area could be described by distinct regions of surface texture and surficial sediments ranging from muddy sand to boulders and rock.

  5. Prediction of the likely impact of climate change on monthly mean maximum and minimum temperature in the Chaliyar river basin, India, using ANN-based models

    NASA Astrophysics Data System (ADS)

    Chithra, N. R.; Thampi, Santosh G.; Surapaneni, Sujith; Nannapaneni, Revanth; Reddy, A. Ashok Kumar; Kumar, J. Dinesh

    2015-08-01

    In this work, an approach based on Artificial Neural Networks (ANN) has been employed to assess the likely impact of climate change on mean monthly maximum and minimum temperature ( T max and T min) in the Chaliyar river basin, Kerala, India. ANN is trained to downscale temperature from the General Circulation Model (GCM) from a coarser resolution to the required resolution of the river basin. The work aims to estimate the GCMs' output to the scales compatible with that employed in a hydrologic model of the river basin. In order to satiate this purpose, predictor variables were obtained from the National Centre for Environmental Prediction and National Centre for Atmospheric Research (NCEP/NCAR) reanalysis data; this was utilized for training the ANN using a feed-forward network with a back-propagation algorithm. These models were validated further and used to downscale CGCM3 GCM simulations for the scenarios outlined in the IPCC Special Report on Emission Scenarios (SRES). Results showed that both T max and T min are increasing consistently in all the scenarios. T max exhibited an average increase of maximum 3 °C during the dry season (December-May) and 1 °C during the wet season (June-November) by the year 2100, while T min showed an average increase of 2.5 °C in the dry season and 0.5 °C in the wet season.

  6. Evaluation of runoff prediction capability at the event scale in a large olive-grove Mediterranean watershed with AnnAGNPS model

    NASA Astrophysics Data System (ADS)

    Bombino, Giuseppe; Denisi, Pietro; Fortugno, Diego; Gomez, Josè Alfonso; Taguas, Encarnacion; Zema, Demetrio Antonio; Marcello Zimbone, Santo

    2013-04-01

    The distributed parameter and continuous simulation AnnAGNPS model was implemented in the Anzur watershed (Andalusia, Spain) to evaluate its prediction capability of surface runoff under the Mediterranean semi-arid conditions. The experimental watershed (308 km2) is mainly covered by olive groves (more than 75% of the area); the prevalent soil texture is silt loam. Model implementation was performed using a 5-year database with hydrological, geomorphologic and land use data on the experimental watershed. Two hundred and forty-two runoff events were modelled by AnnAGNPS and compared to the corresponding observations recorded at the watershed outlet through the statistical, efficiency and difference indexes commonly used in modelling experiences. The analysis was carried out at event, monthly and yearly scales, considering all the events and a separate analysis was performed on a selection of 46 erosive events (following rainfalls higher than 13 mm), in order to assess AnnAGNPS suitability to simulate those events determining the highest erosive rates under semi-arid conditions. The initial parameterisation was established by following AnnAGNPS model and literature data arranged for a watershed with similar characteristics. Then, the model was calibrated by adjusting of Curve Numbers which meant the best values Nash-Sutcliffe coefficient and root mean square error. Before calibration extreme runoff events were strongly overestimated by the AnnAGNPS model, while prediction capability of the ordinary runoff volumes was more accurate, but always unsatisfactory (coefficients of efficiency of Nash and Sutcliffe E << 0 and correlations between predicted and observed events close to zero). After many calibration trials (with CN 35 for olive grove for soil hydrologic group "B" instead of 31 default value) model performance slightly improved, even though its prediction capability of runoff was poor at all the analysed time scales (best E < 0.30). The inaccuracy shown by the

  7. Ann Richards Middle School.

    ERIC Educational Resources Information Center

    Kell, John H.

    2001-01-01

    Presents photos and basic information about a Texas middle school whose architecture reflects the hybrid culture of the borderlands and "regionalism" in which it is located. A line drawing of the site plan is included. (GR)

  8. Reply to Ann Bradshaw.

    PubMed Central

    Allmark, Peter

    1996-01-01

    My original paper suggested that an ethics of care which failed to specify how, and about what, to care would be devoid of normative and descriptive content. Bradshaw's approach provides such a specification and is, therefore, not devoid of such content. However, as all ethical approaches suggest something about the 'what' and 'how' of care, they are all 'ethics of care' in this broader sense. This reinforces rather than undermines my original conclusion. Furthermore, Bradshaw's 'ethics of care' has philosophical and historical problems which I outline. PMID:11644877

  9. Assessment of runoff and sediment yields using the AnnAGNPS model in a Three-Gorge watershed of China.

    PubMed

    Hua, Lizhong; He, Xiubin; Yuan, Yongping; Nan, Hongwei

    2012-05-01

    Soil erosion has been recognized as one of the major threats to our environment and water quality worldwide, especially in China. To mitigate nonpoint source water quality problems caused by soil erosion, best management practices (BMPs) and/or conservation programs have been adopted. Watershed models, such as the Annualized Agricultural Non-Point Source Pollutant Loading model (AnnAGNPS), have been developed to aid in the evaluation of watershed response to watershed management practices. The model has been applied worldwide and proven to be a very effective tool in identifying the critical areas which had serious erosion, and in aiding in decision-making processes for adopting BMPs and/or conservation programs so that cost/benefit can be maximized and non-point source pollution control can be achieved in the most efficient way. The main goal of this study was to assess the characteristics of soil erosion, sediment and sediment delivery of a watershed so that effective conservation measures can be implemented. To achieve the overall objective of this study, all necessary data for the 4,184 km(2) Daning River watershed in the Three-Gorge region of the Yangtze River of China were assembled. The model was calibrated using observed monthly runoff from 1998 to 1999 (Nash-Sutcliffe coefficient of efficiency of 0.94 and R(2) of 0.94) and validated using the observed monthly runoff from 2003 to 2005 (Nash-Sutcliffe coefficient of efficiency of 0.93 and R(2) of 0.93). Additionally, the model was validated using annual average sediment of 2000-2002 (relative error of -0.34) and 2003-2004 (relative error of 0.18) at Wuxi station. Post validation simulation showed that approximately 48% of the watershed was under the soil loss tolerance released by the Ministry of Water Resources of China (500 t·km(-2)·y(-1)). However, 8% of the watershed had soil erosion of exceeding 5,000 t·km(-2)·y(-1). Sloping areas and low coverage areas are the main source of soil loss in the

  10. Assessment of Runoff and Sediment Yields Using the AnnAGNPS Model in a Three-Gorge Watershed of China

    PubMed Central

    Hua, Lizhong; He, Xiubin; Yuan, Yongping; Nan, Hongwei

    2012-01-01

    Soil erosion has been recognized as one of the major threats to our environment and water quality worldwide, especially in China. To mitigate nonpoint source water quality problems caused by soil erosion, best management practices (BMPs) and/or conservation programs have been adopted. Watershed models, such as the Annualized Agricultural Non-Point Source Pollutant Loading model (AnnAGNPS), have been developed to aid in the evaluation of watershed response to watershed management practices. The model has been applied worldwide and proven to be a very effective tool in identifying the critical areas which had serious erosion, and in aiding in decision-making processes for adopting BMPs and/or conservation programs so that cost/benefit can be maximized and non-point source pollution control can be achieved in the most efficient way. The main goal of this study was to assess the characteristics of soil erosion, sediment and sediment delivery of a watershed so that effective conservation measures can be implemented. To achieve the overall objective of this study, all necessary data for the 4,184 km2 Daning River watershed in the Three-Gorge region of the Yangtze River of China were assembled. The model was calibrated using observed monthly runoff from 1998 to 1999 (Nash-Sutcliffe coefficient of efficiency of 0.94 and R2 of 0.94) and validated using the observed monthly runoff from 2003 to 2005 (Nash-Sutcliffe coefficient of efficiency of 0.93 and R2 of 0.93). Additionally, the model was validated using annual average sediment of 2000–2002 (relative error of −0.34) and 2003–2004 (relative error of 0.18) at Wuxi station. Post validation simulation showed that approximately 48% of the watershed was under the soil loss tolerance released by the Ministry of Water Resources of China (500 t·km−2·y−1). However, 8% of the watershed had soil erosion of exceeding 5,000 t·km−2·y−1. Sloping areas and low coverage areas are the main source of soil loss in the

  11. Prediction of high spatio-temporal resolution land surface temperature under cloudy conditions using microwave vegetation index and ANN

    NASA Astrophysics Data System (ADS)

    Shwetha, H. R.; Kumar, D. Nagesh

    2016-07-01

    Land Surface Temperature (LST) with high spatio-temporal resolution is in demand for hydrology, climate change, ecology, urban climate and environmental studies, etc. Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the most commonly used sensors owing to its high spatial and temporal availability over the globe, but is incapable of providing LST data under cloudy conditions, resulting in gaps in the data. In contrast, microwave measurements have a capability to penetrate under clouds. The current study proposes a methodology by exploring this property to predict high spatio-temporal resolution LST under cloudy conditions during daytime and nighttime without employing in-situ LST measurements. To achieve this, Artificial Neural Networks (ANNs) based models are employed for different land cover classes, utilizing Microwave Polarization Difference Index (MPDI) at finer resolution with ancillary data. MPDI was derived using resampled (from 0.25° to 1 km) brightness temperatures (Tb) at 36.5 GHz channel of dual polarization from Advance Microwave Scanning Radiometer (AMSR)-Earth Observing System and AMSR2 sensors. The proposed methodology is tested over Cauvery basin in India and the performance of the model is quantitatively evaluated through performance measures such as correlation coefficient (r), Nash Sutcliffe Efficiency (NSE) and Root Mean Square Error (RMSE). Results revealed that during daytime, AMSR-E(AMSR2) derived LST under clear sky conditions corresponds well with MODIS LST resulting in values of r ranging from 0.76(0.78) to 0.90(0.96), RMSE from 1.76(1.86) K to 4.34(4.00) K and NSE from 0.58(0.61) to 0.81(0.90) for different land cover classes. During nighttime, r values ranged from 0.76(0.56) to 0.87(0.90), RMSE from 1.71(1.70) K to 2.43(2.12) K and NSE from 0.43(0.28) to 0.80(0.81) for different land cover classes. RMSE values found between predicted LST and MODIS LST during daytime under clear sky conditions were within acceptable

  12. 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.

    PubMed

    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. PMID:21350755

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

    PubMed

    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. PMID:25710600

  14. An integrated, multistudy analysis of the safety of Ann Arbor strain live attenuated influenza vaccine in children aged 2–17 years

    PubMed Central

    Ambrose, Christopher S; Yi, Tingting; Falloon, Judith

    2011-01-01

    Background Trivalent, Ann Arbor strain, live attenuated influenza vaccine (LAIV) is approved in several countries for use in eligible children aged ≥2 years. Objective To describe the safety of Ann Arbor strain LAIV in children aged 2–17 years. Methods An integrated analysis of randomized, controlled trials of LAIV. Results A total of 4245 and 10 693 children received ≥1 dose of LAIV in year 1 of 6 trivalent inactivated influenza vaccine (TIV)-controlled and 14 placebo-controlled studies, respectively; 3212 children were revaccinated in year 2 of 4 placebo-controlled studies. Compared with placebo for days 0–10 post-vaccination, LAIV recipients exhibited increased runny/stuffy nose (+7%), headache (+7%), and tiredness/decreased activity (+2%) after dose 1; and a higher rate of decreased appetite (+4%) after year 2 revaccination. Compared with TIV, only runny/stuffy nose was increased (dose 1, +12%; dose 2, +4%). Compared with initial vaccination, LAIV reactogenicity was lower after dose 2 in year 1 and revaccination in year 2. Unsolicited adverse events (AEs) increased with LAIV in some comparisons were headache, nasal congestion/rhinorrhea, rhinitis, and pyrexia; ear pain and lower respiratory illness were decreased. There was no evidence of an increase in any potential vaccine-related serious AE in LAIV recipients. Among children aged 2–17 years and specifically aged 24–35 months, there was no evidence that lower respiratory illness or wheezing illness occurred at a higher rate in LAIV recipients. Conclusion This analysis supports the safety of Ann Arbor strain LAIV in children aged 2–17 years and provides a consensus assessment of events expected after vaccination. PMID:21668683

  15. Artificial neural network (ANN) approach for modeling of Pb(II) adsorption from aqueous solution by Antep pistachio (Pistacia Vera L.) shells.

    PubMed

    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. PMID:17980484

  16. Evaluation of the AnnAGNPS Model for Predicting Runoff and Nutrient Export in a Typical Small Watershed in the Hilly Region of Taihu Lake

    PubMed Central

    Luo, Chuan; Li, Zhaofu; Li, Hengpeng; Chen, Xiaomin

    2015-01-01

    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. PMID:26364642

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

    PubMed

    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

  18. A[Bi(3)Ti(4)O(13)] and A[Bi(3)PbTi(5)O(16)] (A = K, Cs): New n = 4 and n = 5 Members of the Layered Perovskite Series, A[A'(n)()(-)(1)B(n)()O(3)(n)()(+1)], and Their Hydrates.

    PubMed

    Gopalakrishnan, J.; Sivakumar, T.; Thangadurai, V.; Subbanna, G. N.

    1999-06-14

    We describe the synthesis and structural characterization of new layered bismuth titanates, A[Bi(3)Ti(4)O(13)] and A[Bi(3)PbTi(5)O(16)] for A = K, Cs, corresponding to n = 4 and 5 members of the Dion-Jacobson series of layered perovskites of the general formula, A[A'(n)()(-)(1)B(n)()O(3)(n)()(+1)]. These materials have been prepared by solid state reaction of the constituents containing excess alkali, which is required to suppress the formation of competitive Aurivillius phases. Unlike the isostructural niobates and niobium titanates of the same series, the new phases reported here are spontaneously hydrated-a feature which could make them potentially useful as photocatalysts for water splitting reaction. On hydration of the potassium compounds, the c axis expands by ca. 2 Å and loses its doubling [for example, the tetragonal lattice parameters of K[Bi(3)Ti(4)O(13)] and its dihydrate are respectively a = 3.900(1) Å, c = 37.57(2) Å; a = 3.885(1) Å, c = 20.82(4) Å]; surprisingly, the cesium analogues do not show a similar change on hydration. PMID:11671024

  19. 3D fluid-structure modelling and vibration analysis for fault diagnosis of Francis turbine using multiple ANN and multiple ANFIS

    NASA Astrophysics Data System (ADS)

    Saeed, R. A.; Galybin, A. N.; Popov, V.

    2013-01-01

    This paper discusses condition monitoring and fault diagnosis in Francis turbine based on integration of numerical modelling with several different artificial intelligence (AI) techniques. In this study, a numerical approach for fluid-structure (turbine runner) analysis is presented. The results of numerical analysis provide frequency response functions (FRFs) data sets along x-, y- and z-directions under different operating load and different position and size of faults in the structure. To extract features and reduce the dimensionality of the obtained FRF data, the principal component analysis (PCA) has been applied. Subsequently, the extracted features are formulated and fed into multiple artificial neural networks (ANN) and multiple adaptive neuro-fuzzy inference systems (ANFIS) in order to identify the size and position of the damage in the runner and estimate the turbine operating conditions. The results demonstrated the effectiveness of this approach and provide satisfactory accuracy even when the input data are corrupted with certain level of noise.

  20. Anne O'Tate: A tool to support user-driven summarization, drill-down and browsing of PubMed search results

    PubMed Central

    Smalheiser, Neil R; Zhou, Wei; Torvik, Vetle I

    2008-01-01

    Background PubMed is designed to provide rapid, comprehensive retrieval of papers that discuss a given topic. However, because PubMed does not organize the search output further, it is difficult for users to grasp an overview of the retrieved literature according to non-topical dimensions, to drill-down to find individual articles relevant to a particular individual's need, or to browse the collection. Results In this paper, we present Anne O'Tate, a web-based tool that processes articles retrieved from PubMed and displays multiple aspects of the articles to the user, according to pre-defined categories such as the "most important" words found in titles or abstracts; topics; journals; authors; publication years; and affiliations. Clicking on a given item opens a new window that displays all papers that contain that item. One can navigate by drilling down through the categories progressively, e.g., one can first restrict the articles according to author name and then restrict that subset by affiliation. Alternatively, one can expand small sets of articles to display the most closely related articles. We also implemented a novel cluster-by-topic method that generates a concise set of topics covering most of the retrieved articles. Conclusion Anne O'Tate is an integrated, generic tool for summarization, drill-down and browsing of PubMed search results that accommodates a wide range of biomedical users and needs. It can be accessed at [4]. Peer review and editorial matters for this article were handled by Aaron Cohen. PMID:18279519

  1. Mass Digitization: Implications for Information Policy: Report from "Scholarship and Libraries in Transition: A Dialogue about the Impacts of Mass Digitization Projects" Symposium (Ann Arbor, Michigan, March 10-11, 2006)

    ERIC Educational Resources Information Center

    US National Commission on Libraries and Information Science, 2006

    2006-01-01

    The U.S. National Commission on Libraries and Information Science (NCLIS) sponsored the symposium "Scholarship and Libraries in Transition: A Dialogue about the Impacts of Mass Digitization Projects" in March 2006 at the University of Michigan-Ann Arbor. The symposium was organized with a keynote and several other individual presentations, as well…

  2. Sensitivity analysis of artificial neural network (ANN) brightness temperature predictions over snow-covered regions in North America using the Advanced Microwave Sounding Radiometer (AMSR-E) from 2002 to 2011

    NASA Astrophysics Data System (ADS)

    Xue, Y.; Forman, B. A.

    2013-12-01

    Snow is a significant contributor to the earth's hydrologic cycle, energy cycle, and climate system. Further, up to 80% of freshwater supply in the western United States originates as snow (and ice). Characterization of the mass of snow, or snow water equivalent (SWE), across regional and continental scales has commonly been conducted using satellite-based passive microwave (PMW) brightness temperatures (Tb) within a SWE retrieval algorithm. However, SWE retrievals often suffer from deficiencies related to deep snow, wet snow, snow evolution, snow aging, overlying vegetation, surface and internal ice lenses, depth hoar, and sub-grid scale lakes. As an alternative to SWE retrievals, this study explores the potential for using PMW Tb and machine learning within a data assimilation framework. An artificial neural network (ANN) is presented for eventual use as an observation operator to map the land surface model states into Tb space. This study explores the sensitivity of an ANN as a computationally efficient measurement model operator for the prediction of PMW Tb across North America. The analysis employs normalized sensitivity coefficients and a one-at-a-time approach such that each of the 11 different inputs could be examined separately in order to quantify the impact of perturbations to each input on the multi-frequency, multi-polarization Tb output from the ANN. Spatiotemporal variability in the Tb predictions across regional spatial scales and seasonal timescales is investigated from 2002 to 2011. Preliminary results suggest ANN-based Tb predictions are sensitive to certain snow states, such as SWE, snow density, and snow temperature in non-vegetated or sparsely vegetated regions. Further, sensitivity of ANN prediction of ΔTb=Tb, 18v*-Tb, 36v* to changes in SWE suggest the likelihood for success when the ANN is eventually implemented into a data assimilation framework. Despite the promise in these initial results, challenges remain at enhancing ANN sensitivity

  3. Preliminary Analysis of the efficacy of Artificial neural Network (ANN) and Cellular Automaton (CA) based Land Use Models in Urban Land-Use Planning

    NASA Astrophysics Data System (ADS)

    Harun, R.

    2013-05-01

    This research provides an opportunity of collaboration between urban planners and modellers by providing a clear theoretical foundations on the two most widely used urban land use models, and assessing the effectiveness of applying the models in urban planning context. Understanding urban land cover change is an essential element for sustainable urban development as it affects ecological functioning in urban ecosystem. Rapid urbanization due to growing inclination of people to settle in urban areas has increased the complexities in predicting that at what shape and size cities will grow. The dynamic changes in the spatial pattern of urban landscapes has exposed the policy makers and environmental scientists to great challenge. But geographic science has grown in symmetry to the advancements in computer science. Models and tools are developed to support urban planning by analyzing the causes and consequences of land use changes and project the future. Of all the different types of land use models available in recent days, it has been found by researchers that the most frequently used models are Cellular Automaton (CA) and Artificial Neural Networks (ANN) models. But studies have demonstrated that the existing land use models have not been able to meet the needs of planners and policy makers. There are two primary causes identified behind this prologue. First, there is inadequate understanding of the fundamental theories and application of the models in urban planning context i.e., there is a gap in communication between modellers and urban planners. Second, the existing models exclude many key drivers in the process of simplification of the complex urban system that guide urban spatial pattern. Thus the models end up being effective in assessing the impacts of certain land use policies, but cannot contribute in new policy formulation. This paper is an attempt to increase the knowledge base of planners on the most frequently used land use model and also assess the

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

    PubMed Central

    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<0,05 a été considéré comme statistiquement significatif. Résultats Parmi les 414 étudiants régulièrement inscrits les données de 407 ont pu être exploitées. Ils étaient âgés de 15 à 31 ans; 262 (64,4%) étaient de sexe masculin. 98 étaient admis avec un taux de succès de 23,7%. Le sexe masculin, la note obtenue en mathématiques, en sciences physiques, la moyenne au BAC et la mention étaient associés au succès en fin d'année mais en analyse multivariée seule une note en sciences physiques > 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

  5. Modelling the contribution of ephemeral gully erosion under different soil management in an olive orchard microcatchment using the AnnAGNPS model

    NASA Astrophysics Data System (ADS)

    Taguas, E. V.; Bingner, R.; Yuan, Y.; Gómez, J. A.

    2010-05-01

    In Spain, few studies have been carried out to explore the erosion caused by processes other than inter-rill and rill erosion, such as gully and ephemeral gully erosion, especially because most of the available studies have evaluated the erosion at the plot scale. A study was undertaken into the environmental and economic impact of different soil management strategies, spontaneous grass cover with and without gully control (SC/SCGC) or conventional tillage with and without gully control (T/TGC), based on the experimental results obtained in an 6.1 ha olive crop microcatchment. Initially, two years of rainfall-runoff-sediment load data series, (34 events) recorded under the current management (SCGC), was used for the calibration of the AnnAGNPS model at event and monthly scales providing suitable adjustments of runoff, peak flow and sediment loads (E >70, r >0.85). Ephemeral gullies were also identified using aerial orthophotography and field work. The module of the AnnAGNPS model for simulating ephemeral gully generation and the tillage operations based on a bibliographical review were used to compare different scenarios and to perform a 10 year-analysis. The results showed mean runoff coefficients of 10.0% for SC/SCGC and of 3.2% for T/TGC while the average sediment loads were 2.0 t.ha-1year-1 (SCGC), 3.5 t.ha-1year-1 (SC), 3.3 t.ha-1year-1 (TGC) and 4 t.ha-1year-1 (T). Significant differences in sediment sources (rill/inter-rill erosion and ephemeral gullies) were evaluated between SC (46% of gully contribution) and T (19% of gully contribution), in order to optimize the environmental and economic effort required in each case. Finally, the annual costs associated with soil losses were estimated (< 1 €.ha-1year-1). SC was the most profitable alternative for soil management. Despite the additional reduction in soil losses of the SCGC approach, the higher cost of its implementation and the minor effect on yield losses in the medium term suggest that without

  6. Safety, immunogencity, and efficacy of a cold-adapted A/Ann Arbor/6/60 (H2N2) vaccine in mice and ferrets

    SciTech Connect

    Chen, Grace L.; Lamirande, Elaine W.; Jin Hong; Kemble, George; Subbarao, Kanta

    2010-03-01

    We studied the attenuation, immunogenicity and efficacy of the cold-adapted A/Ann Arbor/6/60 (AA ca) (H2N2) virus in mice and ferrets to evaluate its use in the event of an H2 influenza pandemic. The AA ca virus was restricted in replication in the respiratory tract of mice and ferrets. In mice, 2 doses of vaccine elicited a > 4-fold rise in hemagglutination-inhibition (HAI) titer and resulted in complete inhibition of viral replication following lethal homologous wild-type virus challenge. In ferrets, a single dose of the vaccine elicited a > 4-fold rise in HAI titer and conferred complete protection against homologous wild-type virus challenge in the upper respiratory tract. In both mice and ferrets, the AA ca virus provided significant protection from challenge with heterologous H2 virus challenge in the respiratory tract. The AA ca vaccine is safe, immunogenic, and efficacious against homologous and heterologous challenge in mice and ferrets, supporting the evaluation of this vaccine in clinical trials.

  7. First principles study of structural, electronic, mechanical and magnetic properties of actinide nitrides AnN (An = U, Np and Pu)

    NASA Astrophysics Data System (ADS)

    Murugan, A.; Priyanga, G. Sudha; Rajeswarapalanichamy, R.; Santhosh, M.; Iyakutti, K.

    2016-09-01

    The electronic, structural, mechanical and magnetic properties of Actinide nitrides AnN (An = U, Np and Pu) are investigated in three cubic phases, namely, NaCl (B1), CsCl (B2) and zinc blende (B3). At normal pressure, UN is stable in antiferromagnetic state while the other two nitrides are stable in the ferromagnetic state with NaCl (B1) structure. A pressure induced structural phase transition from B1 to B3 phase is predicted in these nitrides. The electronic structure reveals that these nitrides are metallic in nature. The magnetic phase transition from antiferromagnetic to non-magnetic state is observed in UN at a pressure of 127 GPa while ferromagnetic to non-magnetic state is observed in NpN and PuN at the pressures of 67 GPa and 102.3 GPa respectively. The computed structural parameters, bulk modulus density of states and charge density distributions are compared with experimental and other theoretical calculations.

  8. Hydrology and sediment budget of Los Laureles Canyon, Tijuana, MX: Modelling channel, gully, and rill erosion with 3D photo-reconstruction, CONCEPTS, and AnnAGNPS

    NASA Astrophysics Data System (ADS)

    Taniguchi, Kristine; Gudiño, Napoleon; Biggs, Trent; Castillo, Carlos; Langendoen, Eddy; Bingner, Ron; Taguas, Encarnación; Liden, Douglas; Yuan, Yongping

    2015-04-01

    Several watersheds cross the US-Mexico boundary, resulting in trans-boundary environmental problems. Erosion in Tijuana, Mexico, increases the rate of sediment deposition in the Tijuana Estuary in the United States, altering the structure and function of the ecosystem. The well-being of residents in Tijuana is compromised by damage to infrastructure and homes built adjacent to stream channels, gully formation in dirt roads, and deposition of trash. We aim to understand the dominant source of sediment contributing to the sediment budget of the watershed (channel, gully, or rill erosion), where the hotspots of erosion are located, and what the impact of future planned and unplanned land use changes and Best Management Practices (BMPs) will be on sediment and storm flow. We will be using a mix of field methods, including 3D photo-reconstruction of stream channels, with two models, CONCEPTS and AnnAGNPS to constrain estimates of the sediment budget and impacts of land use change. Our research provides an example of how 3D photo-reconstruction and Structure from Motion (SfM) can be used to model channel evolution.

  9. PC-ANN assisted to the determination of Vanadium (IV) ion using an optical sensor based on immobilization of Eriochorome Cyanine R on a triacetylcellulose film.

    PubMed

    Bordbar, Mohammad Mahdi; Khajehsharifi, Habibollah; Solhjoo, Aida

    2015-12-01

    More detailed analytical studies of an optical sensor based on immobilization of Eriochorome Cyanine R (ECR) on a triacetylcellulose film have been described to determine Vanadium (IV) ions in some real samples. The sensor based on complex formation between Vanadium (IV) ions and ECR in acidic media caused the color of the film to change from violet to blue along with the appearance of a strong peak appears at 595 nm. At the optimal conditions, the calibration curve showed a linear range of 9.90×10(-7)-8.25×10(-5)mol L(-1). Vanadium (IV) ions can be detected with a detection limit of 1.03×10(-7)mol L(-1) within 15 min depending on its concentration. Also, the working range was improved by using PC-ANN algorithm. The sensor could regenerate with dilute acetic acid solution and could be completely reversible. The proposed sensor was successfully applied for determining V (IV) ions in environmental water and tea leaves. PMID:26142655

  10. Removal of Pb(II) ions from aqueous solution using water hyacinth root by fixed-bed column and ANN modeling.

    PubMed

    Mitra, Tania; Singha, Biswajit; Bar, Nirjhar; Das, Sudip Kumar

    2014-05-30

    Hyacinth root was used as a biosorbent for generating adsorption data in fixed-bed glass column. The influence of different operating parameters like inlet Pb(II) ion concentration, liquid flow rate and bed height on the breakthrough curves and the performance of the column was studied. The result showed that the adsorption efficiency increased with increase in bed height and decreased with increase in inlet Pb(II) ion concentration and flow rate. Increasing the flow rate resulted in shorter time for bed saturation. The result showed that as the bed height increased the availability of more number of adsorption sites in the bed increased, hence the throughput volume of the aqueous solution also increased. The adsorption kinetics was analyzed using different models. It was observed that maximum adsorption capacity increased with increase in flow rate and initial Pb(II) ion concentration but decreased with increase in bed height. Applicability of artificial neural network (ANN) modeling for the prediction of Pb(II) ion removal was also reported by using multilayer perceptron with backpropagation, Levenberg-Marquardt and scaled conjugate algorithms and four different transfer functions in a hidden layer and a linear output transfer function. PMID:24727010

  11. Improving chronic illness care for veterans within the framework of the Patient-Centered Medical Home: experiences from the Ann Arbor Patient-Aligned Care Team Laboratory.

    PubMed

    Piette, John D; Holtz, Bree; Beard, Ashley J; Blaum, Caroline; Greenstone, C Leo; Krein, Sarah L; Tremblay, Adam; Forman, Jane; Kerr, Eve A

    2011-12-01

    While key components of the Patient-Centered Medical Home (PCMH) have been described, improved patient outcomes and efficiencies have yet to be conclusively demonstrated. We describe the rationale, conceptual framework, and progress to date as part of the VA Ann Arbor Patient-Aligned Care Team (PACT) Demonstration Laboratory, a clinical care-research partnership designed to implement and evaluate PCMH programs. Evidence and experience underlying this initiative is presented. Key components of this innovation are: (a) a population-based registry; (b) a navigator system that matches veterans to programs; and (c) a menu of self-management support programs designed to improve between-visit support and leverage the assistance of patient-peers and informal caregivers. This approach integrates PCMH principles with novel implementation tools allowing patients, caregivers, and clinicians to improve disease management and self-care. Making changes within a complex organization and integrating programmatic and research goals represent unique opportunities and challenges for evidence-based healthcare improvements in the VA. PMID:24073085

  12. QSAR studies of bioactivities of 1-(azacyclyl)-3-arylsulfonyl-1H-pyrrolo[2,3-b]pyridines as 5-HT6 receptor ligands using physicochemical descriptors and MLR and ANN-modeling.

    PubMed

    Goodarzi, Mohammad; Freitas, Matheus P; Ghasemi, Nahid

    2010-09-01

    Four molecular descriptors were selected from a pool of variables using genetic algorithm, and then used to built a QSAR model for a series of 1-(azacyclyl)-3-arylsulfonyl-1H-pyrrolo[2,3-b]pyridines as 5-HT(6) receptor agonists or antagonists, useful for the treatment of central nervous system disorders. Simple multiple linear regression (MLR) and a nonlinear method, artificial neural network (ANN), were used to model the bioactivities of the compounds; while MLR gave an acceptable model for predictions, the ANN-based model improved significantly the predictive ability, being more reliable for the prediction and design of novel 5-HT(6) receptor ligands. Topology and molecular/group sizes are important requirements to take into account during the development of novel analogs. PMID:20547432

  13. Geology of the Round Bay quadrangle, Anne Arundel County, Maryland, with a section on Dinoflagellate-acritarch palynology, and a section on Cretaceous pollen

    USGS Publications Warehouse

    Minard, James Pierson; May, Fred E.; Christopher, Raymond A.

    1980-01-01

    Six Coastal Plain formations and one group crop out in the Round Bay quadrangle near the inner edge of the Atlantic Coastal Plain physiographic province. The quadrangle lies astride the Severn River, in Anne Arundel County, near Annapolis, Md. The seven stratigraphic units aggregate as much as 128 m in outcrop. In ascending order, the units are: the upper part of the Potomac Group and the Magothy, Matawan, and Severn Formations, all of Cretaceous age; the Brightseat and Aquia Formations of Paleocene age and the Calvert Formation of Miocene age. Quaternary deposits are thin and cover only small areas; they are all mapped under one unit. Several small, thin deposits of Tertiary alluvium are mapped separately. The largely unconsolidated Cretaceous and Tertiary formations consist chiefly of quartz, glauconite, clays, muscovite, chlorite, lignite, feldspar, and pyrite. Quaternary sediments are mostly locally derived sands, silts, and clays with some gravel and, in the finer sediments, considerable amounts of organic matter. The Cretaceous and Tertiary units strike generally northeast; the younger the formation, the more easterly it strikes. Dips are gentle, 3.6 to 15 m per kilometer toward the southeast, and decrease upward through the section. The Round Bay quadrangle is near the southern limit of several formations that thin progressively toward the southwest from New Jersey. Some pinch out between Betterton, on the eastern shore of Chesapeake Bay, and Round Bay, on the western shore, whereas others are present only as thin remnants 1-2 m thick. Resources of the quadrangle include abundant ground water, sand, and high land values near water.

  14. Optimization of metformin HCl 500 mg sustained release matrix tablets using Artificial Neural Network (ANN) based on Multilayer Perceptrons (MLP) model.

    PubMed

    Mandal, Uttam; Gowda, Veeran; Ghosh, Animesh; Bose, Anirbandeep; Bhaumik, Uttam; Chatterjee, Bappaditya; Pal, Tapan Kumar

    2008-02-01

    The aim of the present study was to apply the simultaneous optimization method incorporating Artificial Neural Network (ANN) using Multi-layer Perceptron (MLP) model to the development of a metformin HCl 500 mg sustained release matrix tablets with an optimized in vitro release profile. The amounts of HPMC K15M and PVP K30 at three levels (-1, 0, +1) for each were selected as casual factors. In vitro dissolution time profiles at four different sampling times (1 h, 2 h, 4 h and 8 h) were chosen as output variables. 13 kinds of metformin matrix tablets were prepared according to a 2(3) factorial design (central composite) with five extra center points, and their dissolution tests were performed. Commercially available STATISTICA Neural Network software (Stat Soft, Inc., Tulsa, OK, U.S.A.) was used throughout the study. The training process of MLP was completed until a satisfactory value of root square mean (RSM) for the test data was obtained using feed forward back propagation method. The root mean square value for the trained network was 0.000097, which indicated that the optimal MLP model was reached. The optimal tablet formulation based on some predetermined release criteria predicted by MLP was 336 mg of HPMC K15M and 130 mg of PVP K30. Calculated difference (f(1) 2.19) and similarity (f(2) 89.79) factors indicated that there was no difference between predicted and experimentally observed drug release profiles for the optimal formulation. This work illustrates the potential for an artificial neural network with MLP, to assist in development of sustained release dosage forms. PMID:18239298

  15. The 2012 AANS Presidential Address. We are neurosurgery.

    PubMed

    McCormick, Paul C

    2012-12-01

    The theme of the 80th Annual Meeting of the American Association of Neurological Surgeons and the title of this presidential address, "We are neurosurgery," is a simple 3-word affirmation of who neurosurgeons are, what they have achieved, and how much there is yet to accomplish. Recent advances in neurobiology and the clinical neurosciences have brought an unprecedented understanding of the human nervous system in both health and disease. As a specialty, neurosurgery has translated knowledge, expanded techniques, and incorporated technology to exponentially expand the science and scope of neurosurgical practice. However, the rapidly advancing, divergently evolving growth of neurosurgery has had profound effects on all aspects of neurosurgery. In this address, the author examines the contemporary meaning of the annual meeting's theme as it relates to the science, practice, specialty, and profession of neurosurgery, as well as the neurosurgeon. In doing so, the author reveals his interpretation of "We are neurosurgery," which he hopes will have an effect on others. PMID:23198859

  16. Biological Laboratory, Ann Arbor, Michigan

    USGS Publications Warehouse

    Moffett, James W.

    1963-01-01

    This laboratory located about 40 miles west of Detroit, near the intersection of highways I-94 and US-23, can be reached by bus, railroad, or via commercial airlines to Detroit Willow Run or Metropolitan airports. Field biological stations are located in Wisconsin at Ashland; in Ohio at Sandusky; and in Michigan at Ludington, Marquette, Millersburg, and Northville.

  17. 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)

    PubMed Central

    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

  18. Ultrasound assisted biodiesel production from sesame (Sesamum indicum L.) oil using barium hydroxide as a heterogeneous catalyst: Comparative assessment of prediction abilities between response surface methodology (RSM) and artificial neural network (ANN).

    PubMed

    Sarve, Antaram; Sonawane, Shriram S; Varma, Mahesh N

    2015-09-01

    The present study estimates the prediction capability of response surface methodology (RSM) and artificial neural network (ANN) models for biodiesel synthesis from sesame (Sesamum indicum L.) oil under ultrasonication (20 kHz and 1.2 kW) using barium hydroxide as a basic heterogeneous catalyst. RSM based on a five level, four factor central composite design, was employed to obtain the best possible combination of catalyst concentration, methanol to oil molar ratio, temperature and reaction time for maximum FAME content. Experimental data were evaluated by applying RSM integrating with desirability function approach. The importance of each independent variable on the response was investigated by using sensitivity analysis. The optimum conditions were found to be catalyst concentration (1.79 wt%), methanol to oil molar ratio (6.69:1), temperature (31.92°C), and reaction time (40.30 min). For these conditions, experimental FAME content of 98.6% was obtained, which was in reasonable agreement with predicted one. The sensitivity analysis confirmed that catalyst concentration was the main factors affecting the FAME content with the relative importance of 36.93%. The lower values of correlation coefficient (R(2)=0.781), root mean square error (RMSE=4.81), standard error of prediction (SEP=6.03) and relative percent deviation (RPD=4.92) for ANN compared to those R(2) (0.596), RMSE (6.79), SEP (8.54) and RPD (6.48) for RSM proved better prediction capability of ANN in predicting the FAME content. PMID:25630700

  19. Estimation of the chemical-induced eye injury using a Weight-of-Evidence (WoE) battery of 21 artificial neural network (ANN) c-QSAR models (QSAR-21): part II: corrosion potential.

    PubMed

    Verma, Rajeshwar P; Matthews, Edwin J

    2015-03-01

    This is part II of an in silico investigation of chemical-induced eye injury that was conducted at FDA's CFSAN. Serious eye damage caused by chemical (eye corrosion) is assessed using the rabbit Draize test, and this endpoint is an essential part of hazard identification and labeling of industrial and consumer products to ensure occupational and consumer safety. There is an urgent need to develop an alternative to the Draize test because EU's 7th amendment to the Cosmetic Directive (EC, 2003; 76/768/EEC) and recast Regulation now bans animal testing on all cosmetic product ingredients and EU's REACH Program limits animal testing for chemicals in commerce. Although in silico methods have been reported for eye irritation (reversible damage), QSARs specific for eye corrosion (irreversible damage) have not been published. This report describes the development of 21 ANN c-QSAR models (QSAR-21) for assessing eye corrosion potential of chemicals using a large and diverse CFSAN data set of 504 chemicals, ADMET Predictor's three sensitivity analyses and ANNE classification functionalities with 20% test set selection from seven different methods. QSAR-21 models were internally and externally validated and exhibited high predictive performance: average statistics for the training, verification, and external test sets of these models were 96/96/94% sensitivity and 91/91/90% specificity. PMID:25510831

  20. Estimation of the chemical-induced eye injury using a weight-of-evidence (WoE) battery of 21 artificial neural network (ANN) c-QSAR models (QSAR-21): part I: irritation potential.

    PubMed

    Verma, Rajeshwar P; Matthews, Edwin J

    2015-03-01

    Evaluation of potential chemical-induced eye injury through irritation and corrosion is required to ensure occupational and consumer safety for industrial, household and cosmetic ingredient chemicals. The historical method for evaluating eye irritant and corrosion potential of chemicals is the rabbit Draize test. However, the Draize test is controversial and its use is diminishing - the EU 7th Amendment to the Cosmetic Directive (76/768/EEC) and recast Regulation now bans marketing of new cosmetics having animal testing of their ingredients and requires non-animal alternative tests for safety assessments. Thus, in silico and/or in vitro tests are advocated. QSAR models for eye irritation have been reported for several small (congeneric) data sets; however, large global models have not been described. This report describes FDA/CFSAN's development of 21 ANN c-QSAR models (QSAR-21) to predict eye irritation using the ADMET Predictor program and a diverse training data set of 2928 chemicals. The 21 models had external (20% test set) and internal validation and average training/verification/test set statistics were: 88/88/85(%) sensitivity and 82/82/82(%) specificity, respectively. The new method utilized multiple artificial neural network (ANN) molecular descriptor selection functionalities to maximize the applicability domain of the battery. The eye irritation models will be used to provide information to fill the critical data gaps for the safety assessment of cosmetic ingredient chemicals. PMID:25497990

  1. The cold adapted and temperature sensitive influenza A/Ann Arbor/6/60 virus, the master donor virus for live attenuated influenza vaccines, has multiple defects in replication at the restrictive temperature

    SciTech Connect

    Chan, Winnie; Zhou, Helen; Kemble, George; Jin Hong

    2008-10-25

    We have previously determined that the temperature sensitive (ts) and attenuated (att) phenotypes of the cold adapted influenza A/Ann Arbor/6/60 strain (MDV-A), the master donor virus for the live attenuated influenza A vaccines (FluMist), are specified by the five amino acids in the PB1, PB2 and NP gene segments. To understand how these loci control the ts phenotype of MDV-A, replication of MDV-A at the non-permissive temperature (39 deg. C) was compared with recombinant wild-type A/Ann Arbor/6/60 (rWt). The mRNA and protein synthesis of MDV-A in the infected MDCK cells were not significantly reduced at 39 deg. C during a single-step replication, however, vRNA synthesis was reduced and the nuclear-cytoplasmic export of viral RNP (vRNP) was blocked. In addition, the virions released from MDV-A infected cells at 39 deg. C exhibited irregular morphology and had a greatly reduced amount of the M1 protein incorporated. The reduced M1 protein incorporation and vRNP export blockage correlated well with the virus ts phenotype because these defects could be partially alleviated by removing the three ts loci from the PB1 gene. The virions and vRNPs isolated from the MDV-A infected cells contained a higher level of heat shock protein 70 (Hsp70) than those of rWt, however, whether Hsp70 is involved in thermal inhibition of MDV-A replication remains to be determined. Our studies demonstrate that restrictive replication of MDV-A at the non-permissive temperature occurs in multiple steps of the virus replication cycle.

  2. [Antoine Brulon, a wealthy privileged apothecary in Paris in the seventeenth century, and Anne de Furnes, his wife. Their illustrious tenant in the Place du Palais Royal - Molière].

    PubMed

    Warolin, Christian

    2009-04-01

    In the seventeenth century, Antoine Brulon, originally from the Auvergne, had a particularly prosperous career. He acquired a privilege as apothecary and was syndic for the Society of royal and princely apothecaries. He spent his whole life in the Rue Saint-Honoré where he practised pharmacy in his status of privileged apothecary. In 1651 he bought a house close to the Quinze-Vingts hospital, and the following year he married Anne de Furnes, the daughter of a lawyer. In 1658 he bought three old houses on the Rue Saint-Thomas-du-Louvre, soon selling two of them to Louis-Henry Daquin, doctor in ordinary to the king. They both built new houses. Daquin let two apartments in succession to Molière between the years 1661 and 1665. In January 1666, Molière became the tenant of the house built by Antoine Brulon and owned by his widow, Anne de Furnes. This building was occupied successively by three royal apothecaries who rented the shop and its outbuildings: Philbert Boudin, apothecary in ordinary to the Queen, Jean Morel, apothecary to the King's camp and armies, and finally Pierre Frapin, apothecary to the Grande Ecurie, and supplier of medicine to Molière, as we have previously shown. The two latter apothecaries thus lived in turn in the same building as Molière between January 1666 and July 1672. Antoine Brulon died 5th March 1665. The inventory of his goods indicates not only the rich décor of his apartment, but also a sum of 75,780 livres in cash, representing 96% of his total fortune. This was remarkable wealth for a Paris apothecary of the time. PMID:19824347

  3. Épidémiologie descriptive de la brûlure dans un territoire de santé exemple du « territoire nord franche-comté » durant l’année 2014

    PubMed Central

    Fortin, J.L.; Bitar, M.P.; Marx, T.; Macher, J.M.; Desmettre, T.; Ravat, F.; Labourey, J.M.; Capellier, G.

    2015-01-01

    Summary Cette étude est une analyse épidémiologique rétrospective du recours aux services de santé du nord de la Franche-Comté en raison d’une brûlure durant l’année 2014 (114 patients). L’âge moyen était de 26 ans (8 mois-81 ans), 1/3 des brûlures ont touché des enfants de moins de 15 ans. Les brûlures, plus fréquentes l’été, surviennent principalement autour de l’heure des repas, les jours « sans école », à domicile, avec un liquide chaud. Elles sont peu étendues (4,81% de la SCT) et souvent superficielles. Elles nécessitent un passage dans un Service d’Accueil des Urgences dans 88,59% des cas, suivi d’un transfert en CTB (Lyon plus que Nancy ou Metz) dans 12,28% des cas. PMID:27252605

  4. Reply to Tone Kvernbekk and Ann Lewis

    ERIC Educational Resources Information Center

    Tangen, Reidun

    2008-01-01

    The purpose of this reply to Kvernbekk and Lewis's comments regarding the discussion on epistemological and ethical problems of listening to children's voices, is not to propose a coherent foundation free from any epistemological tensions. Rather, Tangen's intent is primarily to explore different perspectives in order to disclose some of their…

  5. ANN prediction of the Dst index.

    NASA Astrophysics Data System (ADS)

    Pallocchia, G.; Amata, E.; Consolini, G.; Marcucci, M. F.; Bertello, I.

    We describe an artificial neural network algorithm for the prediction of the Dst index, developed in the framework of the Pilot Project on Space Weather Applications of the European Space Agency. We then discuss the need to develop a similar algorithm based on IMF data only and report on preliminary work and tests for such an algorithm.

  6. Alice Cogswell and Anne Sullivan Macy Act

    THOMAS, 113th Congress

    Rep. Cartwright, Matt [D-PA-17

    2014-02-11

    06/13/2014 Referred to the Subcommittee on Early Childhood, Elementary, and Secondary Education. (All Actions) Tracker: This bill has the status IntroducedHere are the steps for Status of Legislation:

  7. Child Protagonists: The "Anne Franks" of Today

    ERIC Educational Resources Information Center

    Klein, Ana Maria

    2003-01-01

    The literary works surveyed here were written by authors who, as children, witnessed apartheid, holocaust, imprisonment, escape, genocide, ethnic cleansing, and other horrors that marked their lives. In each case, the selected texts are rendered as diaries or as first-person narratives describing disturbing situations which are resolved either…

  8. Ann Richards Middle School, La Joya, Texas.

    ERIC Educational Resources Information Center

    Dillon, David

    2003-01-01

    Describes the title school building, including the educational context and design goals. Includes information on the architects, manufacturers/suppliers, and construction team; a general building description; and a commentary on the design. Also includes the floor plan and photographs. (EV)

  9. Morbidité et mortalité des nouveau-nés hospitalisés sur 10 années à la Clinique El Fateh-Suka (Ouagadougou, Burkina Faso)

    PubMed Central

    Nagalo, Kisito; Dao, Fousséni; Tall, François Housséini; Yé, Diarra

    2013-01-01

    Introduction La mortalité néonatale demeure un problème majeur de santé publique dans les pays en développement. Notre étude avait pour but de déterminer la morbidité et la mortalité des nouveau-nés à Ouagadougou, Burkina Faso. Méthodes Une étude rétrospective sur 10 années a permis d'inclure tous les nouveau-nés admis dans l'Unité de Néonatologie de la Clinique El Fateh-Suka. Résultats Au total, 697 nouveau-nés étaient hospitalisés sur la période d'étude. Les principaux diagnostics étaient les infections néonatales (23.5%), les anomalies liées à la durée de la gestation et à la croissance du fætus (17.9%) et le paludisme congénital (15.1%). Les 91 (13.1%) décès étaient dus aux anomalies liées à la durée de la grossesse et à la croissance du fætus (46.1%), à l'hypoxie intra-utérine et à l'asphyxie obstétricale (20,9%) et aux infections néonatales (17.6%). Ces décès survenaient dans 81.3% dans les 72 heures, dans 93.4% des cas dans la première semaine d'hospitalisation. Le facteur de risque associé à ces décès était la voie basse d'accouchement (p = 0.02). Conclusion Cette étude a identifié des pathologies évitables déjà décrites comme les principales causes d'hospitalisations et de décès néonatals. La voie basse d'accouchement était le facteur de risque associé à ces décès, ce qui n'avait pas encore été rapporté. Les efforts pour améliorer la qualité des services de soins périnatals doivent être intensifiés afin de réduire la mortalité néonatale dans les pays en développement. PMID:23785558

  10. Reconciling the clinical practice guidelines on Bell's palsy from the AAO-HNSF and the AAN.

    PubMed

    Schwartz, Seth R; Jones, Stephanie L; Getchius, Thomas S D; Gronseth, Gary S

    2014-05-27

    Bell palsy, named after the Scottish anatomist Sir Charles Bell, is the most common acute mononeuropathy, or disorder affecting a single nerve, and is the most common diagnosis associated with facial nerve weakness/paralysis. In the past 2 years, both the American Academy of Neurology and the Academy of Otolaryngology-Head and Neck Surgery Foundation have published clinical practice guidelines aimed at improving the quality of care and outcomes for patients diagnosed with Bell palsy. This commentary aims to address the similarities and differences in the scope and final recommendations made by each guideline development group. PMID:24793182

  11. A Sieving ANN for Emotion-Based Movie Clip Classification

    NASA Astrophysics Data System (ADS)

    Watanapa, Saowaluk C.; Thipakorn, Bundit; Charoenkitkarn, Nipon

    Effective classification and analysis of semantic contents are very important for the content-based indexing and retrieval of video database. Our research attempts to classify movie clips into three groups of commonly elicited emotions, namely excitement, joy and sadness, based on a set of abstract-level semantic features extracted from the film sequence. In particular, these features consist of six visual and audio measures grounded on the artistic film theories. A unique sieving-structured neural network is proposed to be the classifying model due to its robustness. The performance of the proposed model is tested with 101 movie clips excerpted from 24 award-winning and well-known Hollywood feature films. The experimental result of 97.8% correct classification rate, measured against the collected human-judges, indicates the great potential of using abstract-level semantic features as an engineered tool for the application of video-content retrieval/indexing.

  12. Simulating Ephemeral Gully Erosion in AnnAGNPS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Ephemeral gullies serve as a major source and transport mechanism of sediment and associated agrichemicals from upland areas. Accurate prediction technology is necessary to assess the magnitude of these phenomena and to identify areas where mitigation measures are critical. Current ephemeral gully p...

  13. Jo Ann Rinaudo, PhD | Division of Cancer Prevention

    Cancer.gov

    The Division of Cancer Prevention (DCP) conducts and supports research to determine a person's risk of cancer and to find ways to reduce the risk. This knowledge is critical to making progress against cancer because risk varies over the lifespan as genetic and epigenetic changes can transform healthy tissue into invasive cancer.

  14. Modelling of Reservoir Operations using Fuzzy Logic and ANNs

    NASA Astrophysics Data System (ADS)

    Van De Giesen, N.; Coerver, B.; Rutten, M.

    2015-12-01

    Today, almost 40.000 large reservoirs, containing approximately 6.000 km3 of water and inundating an area of almost 400.000 km2, can be found on earth. Since these reservoirs have a storage capacity of almost one-sixth of the global annual river discharge they have a large impact on the timing, volume and peaks of river discharges. Global Hydrological Models (GHM) are thus significantly influenced by these anthropogenic changes in river flows. We developed a parametrically parsimonious method to extract operational rules based on historical reservoir storage and inflow time-series. Managing a reservoir is an imprecise and vague undertaking. Operators always face uncertainties about inflows, evaporation, seepage losses and various water demands to be met. They often base their decisions on experience and on available information, like reservoir storage and the previous periods inflow. We modeled this decision-making process through a combination of fuzzy logic and artificial neural networks in an Adaptive-Network-based Fuzzy Inference System (ANFIS). In a sensitivity analysis, we compared results for reservoirs in Vietnam, Central Asia and the USA. ANFIS can indeed capture reservoirs operations adequately when fed with a historical monthly time-series of inflows and storage. It was shown that using ANFIS, operational rules of existing reservoirs can be derived without much prior knowledge about the reservoirs. Their validity was tested by comparing actual and simulated releases with each other. For the eleven reservoirs modelled, the normalised outflow, <0,1>, was predicted with a MSE of 0.002 to 0.044. The rules can be incorporated into GHMs. After a network for a specific reservoir has been trained, the inflow calculated by the hydrological model can be combined with the release and initial storage to calculate the storage for the next time-step using a mass balance. Subsequently, the release can be predicted one time-step ahead using the inflow and storage.

  15. Simulating Ephemeral Gully Erosion in AnnAGNPS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Ephemeral gully erosion can cause severe soil degradation and contribute significantly to total soil losses in agricultural areas. Physically-based prediction technology is necessary to assess the magnitude of these phenomena so that appropriate conservation measures can be implemented, but such te...

  16. Comparison of Two ANN Methods for Classification of Spirometer Data

    NASA Astrophysics Data System (ADS)

    Manoharan, Sujatha C.; Veezhinathan, Mahesh; Ramakrishnan, Swaminathan

    2008-01-01

    In this work, classification of spirometric pulmonary function test data performed using two artificial neural network methods is compared and reported. The pulmonary function data (N=150) were obtained from volunteers, using commercially available Spirometer, and recorded by standard data acquisition protocol. The data were then used to train (N=100) as well as to test (N=50) the neural networks. The classification was carried out using back propagation and radial basis function neural networks. The results confirm that the artificial neural network methods are useful for the classification of spirometric pulmonary function data. Further, it appears that the Radial basis function neural network is more sensitive when compared to back propagation neural networks. In this paper, the methodology, data collection procedure and neural network based analysis are described in details.

  17. The Community Arbitration Project, Anne Arundel County, Maryland.

    ERIC Educational Resources Information Center

    Blew, Carol Holliday; Rosenblum, Robert

    This examines an exemplary project of community arbitration, a juvenile justice alternative. Essential elements of this project are described and include: (1) prompt case processing, (2) court-like setting, (3) involvement of victims, (4) assurance of due process, (5) use of community resources, and (6) constructive dispositions. Facets of CAP…

  18. For an always promising transplant prediction, call ANN.

    PubMed

    Gjertson, David W; Clark, Bill D

    2008-11-27

    With apologies to Sherlock Holmes, "You can never foretell when any one man's kidney transplant will fail, but you can say with precision when an average number will fail. ... So says the statistician." PMID:19034001

  19. Ann pale kreyol: An Introductory Course in Haitian Creole.

    ERIC Educational Resources Information Center

    Valdman, Albert

    This set of instructional materials is designed to provide beginning and intermediate learners of Haitian Creole with a foundation in the phonology, grammar, and vocabulary of the language. It is intended for use by individuals wanting to communicate with monolingual Haitians. A revision of earlier materials, this set emphasizes authentic…

  20. Addressing Barriers to Minority Ethnic Students' Learning in a Performative Culture: Possible or Aan U Suuragelin? Niemozliwe? Nemoguce? ???????

    ERIC Educational Resources Information Center

    Gallagher, Kathleen; Beckett, Lori

    2014-01-01

    This article, written by a research-active teacher of English with an academic partner, recounts the circumstances of forging a partnership way of working in an urban high school that is consistently targeted for closure in the north of England. This is connected to performance and achievement against Ofsted inspection criteria and school data…

  1. Unambiguous Detection of Multiple TP53 Gene Mutations in AAN-Associated Urothelial Cancer in Belgium Using Laser Capture Microdissection

    PubMed Central

    Aydin, Selda; Dekairelle, Anne-France; Ambroise, Jérôme; Durant, Jean-François; Heusterspreute, Michel; Guiot, Yves

    2014-01-01

    In the Balkan and Taiwan, the relationship between exposure to aristolochic acid and risk of urothelial neoplasms was inferred from the A>T genetic hallmark in TP53 gene from malignant cells. This study aimed to characterize the TP53 mutational spectrum in urothelial cancers consecutive to Aristolochic Acid Nephropathy in Belgium. Serial frozen tumor sections from female patients (n = 5) exposed to aristolochic acid during weight-loss regimen were alternatively used either for p53 immunostaining or laser microdissection. Tissue areas with at least 60% p53-positive nuclei were selected for microdissecting sections according to p53-positive matching areas. All areas appeared to be carcinoma in situ. After DNA extraction, mutations in the TP53 hot spot region (exons 5–8) were identified using nested-PCR and sequencing. False-negative controls consisted in microdissecting fresh-frozen tumor tissues both from a patient with a Li-Fraumeni syndrome who carried a p53 constitutional mutation, and from KRas mutated adenocarcinomas. To rule out false-positive results potentially generated by microdissection and nested-PCR, a phenacetin-associated urothelial carcinoma and normal fresh ureteral tissues (n = 4) were processed with high laser power. No unexpected results being identified, molecular analysis was pursued on malignant tissues, showing at least one mutation in all (six different mutations in two) patients, with 13/16 exonic (nonsense, 2; missense, 11) and 3/16 intronic (one splice site) mutations. They were distributed as transitions (n = 7) or transversions (n = 9), with an equal prevalence of A>T and G>T (3/16 each). While current results are in line with A>T prevalence previously reported in Balkan and Taiwan studies, they also demonstrate that multiple mutations in the TP53 hot spot region and a high frequency of G>T transversion appear as a complementary signature reflecting the toxicity of a cumulative dose of aristolochic acid ingested over a short period of time. PMID:25184754

  2. Zuivere en toegepaste wetenschap in de tropen : biologisch onderzoek aan particuliere proefstations in Nederlands-Indië 1870-1940

    NASA Astrophysics Data System (ADS)

    van der Schoor, W. J.

    2012-04-01

    Most experiment stations originated from the cooperation between entrepreneurs and the government. From the 1890s onwards, the government, together with the well organised colonial entrepreneurs, established research departments for several plantation crops at the Botanical Gardens at Buitenzorg (now Bogor), that eventually became independent experiment stations in the first decades of the twentieth century. By the 1920s, the ‘proefstationswezen’ (experiment station system) numbered some fifteen private experiment stations or sub-stations. After the war, the private experiment stations together with the government experiment stations at Buitenzorg were to provide the backbone of Indonesian agricultural science. Dutch biologists in particular, made a striking plea for pursuing the natural sciences in the tropical colonies. First, they pointed out the scientific importance of the tropics. Secondly, they stressed the role of the natural sciences, in particular biology, as a natural ally of colonial agriculture. Pure science was seen as a leading force for technical and social progress. The third motive was the cultural value of science for the Netherlands and its colonies. The cultivation of science in the colonies gave international prestige and strengthened self-confidence in the imperial struggle around 1900. Science had a civilising effect; scientific research, however, was to remain in the hands of western, colonial scientists. From the 1880s and 1890s onward, the experiment stations in the Indies were characterised by their strategic aims and scientific orientation. Up to 1910, the ‘academic’ views of biologists like Treub and Went concerning science and practice were predominant, and research was considered to be the central aim. From 1910 onwards, advice became more central and special extension services were established at the experiment stations. Due to diverging views of science, tasks and aims became a battlefield for discussions in the next decades. In the background of these debates were the rise of Wageningen Agricultural College, the rise and institutionalisation of applied agricultural sciences and the increasing competition between Wageningen and university trained scientist. Genetics and breeding in particular were at the core of the research programmes. The practical aim of the breeding work, however, did not leave too much opportunity for more fundamental investigations. The impetus for pure research came from individual researchers. In tobacco and sugar cane breeding, new scientific theories provided inspiration, but to a large extent the practical breeding work built on nineteenth-century breeding techniques. In many respects, plant breeding and university genetics became separate disciplines. Circa one in six Dutch biologist worked for at least some time in the colony. The colonial experiment stations instilled a practical and pragmatic attitude to Dutch science into quite a number of biologists. Besides, the experiment stations system provided Dutch biologists with an extensive network and international contacts with fellow scientists, entrepreneurs and captains of industry. The scientific nationalism of Treub and Went, the bloom of the experiment stations and the ambitions of the Indies colonial elite did not result in the establishment of an independent, ‘Indische’ scientific community. Essentially, the Dutch East Indies were an exploitation province of Dutch science

  3. Report of the Ann Arbor Workshop on an International Social Science Research Program on Global Change (Ann Arbor, Michigan, September 9-10, 1987).

    ERIC Educational Resources Information Center

    Jacobson, Harold K.; Shanks, Cheryl

    The International Geosphere-Biosphere Programme: A Study of Global Change (IGBP), a natural science research program, has been inaugurated by the International Council of Scientific Unions (ICSU). Recently, initial steps have been taken to develop an international social science research program on global change that would either be part of the…

  4. Assessment of Subsurface Drainage and Fertilizer Management Practices to Reduce Nutrient Loadings using AnnAGNPS

    EPA Science Inventory

    The Future Midwest Landscape (FML) project is part of the US Environmental Protection Agency (EPA)’s new Ecological Service Research Program (ESRP), undertaken to examine the variety of ways in which landscapes that include crop lands, conservation areas, wetlands, lakes, and str...

  5. 46 CFR 7.10 - Eastport, ME to Cape Ann, MA.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... Head to latitude 44°54′45″ N. longitude 66°58′30″ W.; thence to the range marker located in approximate position latitude 44°51′45″ N. longitude 66°59″ W. (b) A line drawn from West Quoddy Head Light to latitude 44°48.5′ N. longitude 66°56.4′ W. (Sail Rock Lighted Whistle Buoy “1”); thence to latitude 44°37.5′...

  6. 46 CFR 7.10 - Eastport, ME to Cape Ann, MA.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... Head to latitude 44°54′45″ N. longitude 66°58′30″ W.; thence to the range marker located in approximate position latitude 44°51′45″ N. longitude 66°59″ W. (b) A line drawn from West Quoddy Head Light to latitude 44°48.5′ N. longitude 66°56.4′ W. (Sail Rock Lighted Whistle Buoy “1”); thence to latitude 44°37.5′...

  7. Adaptive Selective Harmonic Minimization Based on ANNs for Cascade Multilevel Inverters With Varying DC Sources

    SciTech Connect

    Filho, Faete; Maia, Helder Z; Mateus, Tiago Henrique D; Ozpineci, Burak; Tolbert, Leon M; Pinto, Joao Onofre P

    2013-01-01

    A new approach for modulation of an 11-level cascade multilevel inverter using selective harmonic elimination is presented in this paper. The dc sources feeding the multilevel inverter are considered to be varying in time, and the switching angles are adapted to the dc source variation. This method uses genetic algorithms to obtain switching angles offline for different dc source values. Then, artificial neural networks are used to determine the switching angles that correspond to the real-time values of the dc sources for each phase. This implies that each one of the dc sources of this topology can have different values at any time, but the output fundamental voltage will stay constant and the harmonic content will still meet the specifications. The modulating switching angles are updated at each cycle of the output fundamental voltage. This paper gives details on the method in addition to simulation and experimental results.

  8. AnnAGNPS Model Application for the Future Midwest Landscape Study

    EPA Science Inventory

    The Future Midwest Landscape (FML) project is part of the US Environmental Protection Agency (EPA)’s new Ecosystem Services Research Program, undertaken to examine the variety of ways in which landscapes that include crop lands, conservation areas, wetlands, lakes, and streams af...

  9. "[This] Book of Odd Tales/Which Transform the Brothers Grimm": Teaching Anne Sexton's "Transformations"

    ERIC Educational Resources Information Center

    Keely, Karen A.

    2008-01-01

    Folklorist Andrew Lang, in his Preface to his 1910 edited collection "The Lilac Fairy Book", celebrates the ongoing repetition and retelling of fairy tales, including both the cozy retelling by the family fireplace. In the century since Lang wrote these words, many authors have joined the ranks of Shakespeare and Homer in putting fairy tale…

  10. Stream-temperature patterns of the Muddy Creek basin, Anne Arundel County, Maryland

    USGS Publications Warehouse

    Pluhowski, E.J.

    1981-01-01

    Using a water-balance equation based on a 4.25-year gaging-station record on North Fork Muddy Creek, the following mean annual values were obtained for the Muddy Creek basin: precipitation, 49.0 inches; evapotranspiration, 28.0 inches; runoff, 18.5 inches; and underflow, 2.5 inches. Average freshwater outflow from the Muddy Creek basin to the Rhode River estuary was 12.2 cfs during the period October 1, 1971, to December 31, 1975. Harmonic equations were used to describe seasonal maximum and minimum stream-temperature patterns at 12 sites in the basin. These equations were fitted to continuous water-temperature data obtained periodically at each site between November 1970 and June 1978. The harmonic equations explain at least 78 percent of the variance in maximum stream temperatures and 81 percent of the variance in minimum temperatures. Standard errors of estimate averaged 2.3C (Celsius) for daily maximum water temperatures and 2.1C for daily minimum temperatures. Mean annual water temperatures developed for a 5.4-year base period ranged from 11.9C at Muddy Creek to 13.1C at Many Fork Branch. The largest variations in stream temperatures were detected at thermograph sites below ponded reaches and where forest coverage was sparse or missing. At most sites the largest variations in daily water temperatures were recorded in April whereas the smallest were in September and October. The low thermal inertia of streams in the Muddy Creek basin tends to amplify the impact of surface energy-exchange processes on short-period stream-temperature patterns. Thus, in response to meteorologic events, wide ranging stream-temperature perturbations of as much as 6C have been documented in the basin. (USGS)

  11. Assessment of subsurface drainage management practices to reduce nitrogen loadings using AnnAGNPS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The goal of the Future Midwest Landscape project is to quantify current and future landscape services across the region and examine changes expected to occur as a result of two alternative drivers of future change: the growing demand for biofuels; and hypothetical increases in incentives for the use...

  12. "INDEPENDENT CONFIRMATORY SURVEY SUMMARY AND RESULTS FOR THE FORD NUCLEAR REACTOR, REVISION 1, ANN ARBOR, MICHIGAN

    SciTech Connect

    ALTIC, NICK A

    2013-08-01

    At the NRC's request, ORAU conducted confirmatory surveys of the FNR during the period of December 4 through 6, 2012. The survey activities included visual inspections and measurement and sampling activities. Confirmatory activities also included the review and assessment of UM's project documentation and methodologies. Surface scans identified elevated activity in two areas. The first area was on a wall outside of Room 3103 and the second area was in the southwest section on the first floor. The first area was remediated to background levels. However, the second area was due to gamma shine from a neighboring source storage area. A retrospective analysis of UM's FSS data shows that for the SUs investigated by the ORAU survey team, UM met the survey requirements set forth in the FSSP. The total mean surface activity values were directly compared with the mean total surface activity reported by UM. Mean surface activity values determined by UM were within two standard deviations of the mean determined by ORAU. Additionally, all surface activity values were less than the corresponding gross beta DCGL{sub W}. Laboratory analysis of the soil showed that COC concentrations were less than the respective DCGL{sub W} values. For the inter-lab comparison, the DER was above 3 for only one sample. However, since the sum of fractions for each of the soil samples was below 1, thus none of the samples would fail to meet release guidelines. Based on the findings of the side-by-side direct measurements, and after discussion with the NRC and ORAU, UM decided to use a more appropriate source efficiency in their direct measurement calculations and changed their source efficiency from 0.37 to 0.25.

  13. INDEPENDENT CONFIRMATORY SURVEY SUMMARY AND RESULTS FOR THE FORD NUCLEAR REACTOR, ANN ARBOR, MICHIGAN

    SciTech Connect

    ALTIC, NICK A

    2013-07-25

    At the NRC's request, ORAU conducted confirmatory surveys of the FNR during the period of December 4 through 6, 2012. The survey activities included visual inspections and measurement and sampling activities. Confirmatory activities also included the review and assessment of UM's project documentation and methodologies. Surface scans identified elevated activity in two areas. The first area was on a wall outside of Room 3103 and the second area was in the southwest section on the first floor. The first area was remediated to background levels. However, the second area was due to gamma shine from a neighboring source storage area. A retrospective analysis of UM's FSS data shows that for the SUs investigated by the ORAU survey team, UM met the survey requirements set forth in the FSSP. The total mean surface activity values were directly compared with the mean total surface activity reported by UM. Mean surface activity values determined by UM were within two standard deviations of the mean determined by ORAU. Additionally, all surface activity values were less than the corresponding gross beta DCGLW. Laboratory analysis of the soil showed that COC concentrations were less than the respective DCGLW values. For the inter-lab comparison, the DER was above 3 for only one sample. However, since the sum of fractions for each of the soil samples was below 1, thus none of the samples would fail to meet release guidelines. Based on the findings of the side-by-side direct measurements, and after discussion with the NRC and ORAU, UM decided to use a more appropriate source efficiency in their direct measurement calculations and changed their source efficiency from 0.37 to 0.25.

  14. Living Well with COPD, Q&A: Grace Anne Koppel | NIH MedlinePlus the Magazine

    MedlinePlus

    ... needs to be done to address this gender disparity? Through recent research, we have come to realize ... and Prevention (CDC). COPD kills more women than breast cancer or ovarian cancer combined. We have smaller bodies. ...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 different phosphorus fertilization rates on phosphorus losses, the USDA Annualized AGricu...

  16. Real-time video compression using entropy-biased ANN codebooks

    NASA Astrophysics Data System (ADS)

    Ahalt, Stanley C.; Fowler, James E.

    1994-03-01

    We describe hardware that has been built to compress video in real time using full-search vector quantization (VQ). This architecture implements a differential-vector-quantization (DVQ) algorithm which features entropy-biased codebooks designed using an artificial neural network. A special-purpose digital associative memory, the VAMPIRE chip, performs the VQ processing. We describe the DVQ algorithm, its adaptations for sampled NTSC composite- color video, and details of its hardware implementation. We conclude by presenting results drawn from real-time operation of the DVQ hardware.

  17. Multiple ANN Recognizers for Adaptive Recognition of the Speech of Dysarthric Patients in AAL Systems.

    PubMed

    Nagy, Gabriella; Kutor, Laszlo

    2015-01-01

    People suffering from neuromuscular disorders are one of the main target groups of speech-controlled Ambient Assisted Living systems. However, the speech of these patients is often distorted because of the dysarthric symptoms of the disease. The dysarthria is known to become worse as the disease progresses. We propose a framework for an adaptive speech recognition system that may be able to follow the slow deterioration of speech quality without risking the accuracy of the system from incorrect data. PMID:26294603

  18. Assessment of Subsurface Drainage Management Practices to Reduce Nutrient Loadings using AnnAGNPS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Future Midwest Landscape (FML) project is part of the US Environmental Protection Agency (EPA)’s new Ecological Service Research Program (ESRP), undertaken to examine the variety of ways in which landscapes that include crop lands, conservation areas, wetlands, lakes, and streams affect human we...

  19. Innovation and application of ANN in Europe demonstrated by Kohonen maps

    NASA Technical Reports Server (NTRS)

    Goser, Karl

    1994-01-01

    One of the most important contributions to neural networks comes from Kohonen, Helsinki/Espoo, Finland, who had the idea of self-organizating maps in 1981. He verified his idea by an algorithm of which many applications make use of. The impetus for this idea came from biology, a field where the Europeans have always been very active at several research laboratories. The challenge was to model the self-organization found in the brain. Today one goal is the development of more sophisticated neurons which model the biological neurons more exactly. They should come to a better performance of neural nets with only a few complex neurons instead of many simple ones. A lot of application concepts arise from this idea: Kohonen himself applied it to speech recognition, but the project did not overcome much more than the recognition of the numerals one to ten at that time. A more promising application for self-organizing maps is process control and process monitoring. Several proposals were made which concern parameter classification of semiconductor technologies, design of integrated circuits, and control of chemical processes. Self-organizing maps were applied to robotics. The neural concept was introduced into electric power systems. At Dortmund we are working on a system which has to monitor the quality and the reliability of gears and electrical motors in equipment installed in coal mines. The results are promising and the probability to apply the system in the field is very high. A special feature of the system is that linguistic rules which are embedded in a fuzzy controller analyze the data of the self-organizing map in regard to life expectation of the gears. It seems that the fuzzy technique will introduce the technology of neural networks in a tandem mode. These technologies together with the genetic algorithms start to form the attractive field of computational intelligence.

  20. 75 FR 23745 - Jo-Ann Stores, Inc., Provisional Acceptance of a Settlement Agreement and Order

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-05-04

    ... ensure that they did not bear or contain lead-containing paint, thereby creating a risk of lead poisoning... Lead-Containing Paint and Certain Consumer Products Bearing Lead-Containing Paint, 16 CFR part 1303 (the ``Lead-Paint Ban''). Under the Lead-Paint Ban, toys and other children's articles must not bear...

  1. Distributed Genetic Algorithm for Feature Selection in Gaia RVS Spectra: Application to ANN Parameterization

    NASA Astrophysics Data System (ADS)

    Fustes, Diego; Ordóñez, Diego; Dafonte, Carlos; Manteiga, Minia; Arcay, Bernardino

    This work presents an algorithm that was developed to select the most relevant areas of a stellar spectrum to extract its basic atmospheric parameters. We consider synthetic spectra obtained from models of stellar atmospheres in the spectral region of the radial velocity spectrograph instrument of the European Space Agency's Gaia space mission. The algorithm that demarcates the areas of the spectra sensitive to each atmospheric parameter (effective temperature and gravity, metallicity, and abundance of alpha elements) is a genetic algorithm, and the parameterization takes place through the learning of artificial neural networks. Due to the high computational cost of processing, we present a distributed implementation in both multiprocessor and multicomputer environments.

  2. Listening to the Voice of Living Life with Aphasia: Anne's Story

    ERIC Educational Resources Information Center

    Barrow, Rozanne

    2008-01-01

    Background: Listening to how people talk about the consequences of acquired aphasia helps one gain insight into how people construe disability and communication disability in particular. It has been found that some of these construals can be more of a disabling barrier in re-engaging with life than the communication impairment itself. Aims: To…

  3. Prediction of autistic disorder using neuro fuzzy system by applying ANN technique.

    PubMed

    Arthi, K; Tamilarasi, A

    2008-11-01

    The major challenge in medical field is to diagnose disorder rather than a disease. In this paper, a neuro fuzzy based model is designed for identification or diagnosis of autism. The problematic areas are gathered from every individual and the related linguistic inputs are converted into fuzzy input values which are in turn given as input to feed forward multilayer neural network. The network is trained using back propagation training algorithm and tested for its performance with the expertise. PMID:18706991

  4. Simulation of Wetland Nitrogen Removal at the Watershed Scale Using AnnAGNPS

    EPA Science Inventory

    The Future Midwest Landscape (FML) project is part of the U.S. Environmental Protection Agency’s new Ecosystem Services Research Program, undertaken to examine the variety of ways in which landscapes that include crop lands, conservation areas, wetlands, lakes and streams affect...

  5. [50 years after Anne Frank: reactive of a transgenerational trauma in countertransference].

    PubMed

    Halberstadt-Freud, H C

    1995-01-01

    Traumatizations suffered in the course of the atrocities perpetrated by the National Socialists defy symbolization and, if unresolved, are passed on to subsequent generations. With reference to the psychoanalytic treatment of a forty-year-old homosexual of the "second generation", the author traces the problematic of the transgenerational handing-down of unresolved traumatizations. The son of a Jewess whose brother was murdered in a concentration camp, the patient had to stand in for his lost uncle and remained caught up in a "symbiotic illusion" with this omni-present/absent object and with the mother, thus being unable to attain to a personality of his own and achieve the Oedipal triad. The article concentrates entirely on this case and provides an impressive record of the mechanisms of transference and counter-transference involved and the various stages of the psychoanalytic process. PMID:7871187

  6. Living Well with COPD, Q&A: Grace Anne Koppel | NIH MedlinePlus the Magazine

    MedlinePlus

    ... What have you done to help slow the effects of COPD in your own case since you ... was to exercise. Understand, though, we're not training for the Olympics. We're ... Better® program encourages Breathe Better Network members and all those ...

  7. Annual Adult Education Research Conference. Proceedings (20th, Ann Arbor, Michigan, April 4-6, 1979).

    ERIC Educational Resources Information Center

    1979

    Papers from numerous research areas in the adult education field are presented. The proceedings contain thirty-five papers, five symposia, one alternate symposium, and eighteen alternate papers. Among the papers included are "A Comparison of Approaches to Measuring Outcomes in Adult Basic Education,""A Critical Analysis of Hill's 'Cognitive Style…

  8. 77 FR 34991 - Notice of Inventory Completion: Museum of Anthropology, University of Michigan, Ann Arbor, MI...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-06-12

    ... FR 42094-42095, August 20, 2009). In the Federal Register (74 FR 42094, August 20, 2009), paragraph... FR 42094, August 20, 2009), paragraph four is corrected by inserting the following sentences at the... Native American ancestry. In the Federal Register (74 FR 42094, August 20, 2009), paragraph seven...

  9. Evaluating ephemeral gully erosion impact on Zea mays L. yield and economics using AnnAGNPS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Ephemeral gully erosion causes serious water quality and economic problems in the Midwest United States. A critical barrier to soil conservation practice adoption is often the implementation cost, although it is recognized that erosion reduces farm income. Yet few, if any, understand the relationshi...

  10. 78 FR 76169 - Patuxent Research Refuge, Prince George's and Anne Arundel Counties, MD; Final Comprehensive...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-12-16

    ... process for Patuxent RR. We started this process through a notice of intent in the Federal Register (76 FR... the public and requested comments in a notice of availability in the Federal Register (77 FR 24929) on... Alternatives, Including the Selected Alternative Our draft CCP/EA (77 FR 24929) addressed several key...

  11. On the use of ANN interconnection weights in optimal structural design

    NASA Technical Reports Server (NTRS)

    Hajela, P.; Szewczyk, Z.

    1992-01-01

    The present paper describes the use of interconnection weights of a multilayer, feedforward network, to extract information pertinent to the mapping space that the network is assumed to represent. In particular, these weights can be used to determine an appropriate network architecture, and an adequate number of training patterns (input-output pairs) have been used for network training. The weight analysis also provides an approach to assess the influence of each input parameter on a selected output component. The paper shows the significance of this information in decomposition driven optimal design.

  12. Issues in Software System Safety: Polly Ann Smith Co. versus Ned I. Ludd

    NASA Technical Reports Server (NTRS)

    Holloway, C. Michael

    2002-01-01

    This paper is a work of fiction, but it is fiction with a very real purpose: to stimulate careful thought and friendly discussion about some questions for which thought is often careless and discussion is often unfriendly. To accomplish this purpose, the paper creates a fictional legal case. The most important issue in this fictional case is whether certain proffered expert testimony about software engineering for safety critical systems should be admitted. Resolving this issue requires deciding the extent to which current practices and research in software engineering, especially for safety-critical systems, can rightly be considered based on knowledge, rather than opinion.

  13. Morrow, Reiff, Receive 2013 Space Physics and Aeronomy Richard Carrington Awards: Citation for Cherilynn Ann Morrow

    NASA Astrophysics Data System (ADS)

    Lopez, Ramon

    2014-08-01

    The Space Physics and Aeronomy Richard Carrington (SPARC) Education and Public Outreach Award for Cherilynn Morrow recognizes years of pioneering work on behalf of the space science community in the area of education and public outreach (E/PO).

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

    Cancer.gov

    The Division of Cancer Prevention (DCP) conducts and supports research to determine a person's risk of cancer and to find ways to reduce the risk. This knowledge is critical to making progress against cancer because risk varies over the lifespan as genetic and epigenetic changes can transform healthy tissue into invasive cancer.

  15. AnnAGNPS Model Application for Nitrogen Loading Assessment for the Future Midwest Landscape Study

    EPA Science Inventory

    The Future Midwest Landscape (FML) project is part of the US Environmental Protection Agency (EPA)’s new Ecosystem Services Research Program, undertaken to examine the variety of ways in which landscapes that include crop lands, conservation areas, wetlands, lakes, and streams af...

  16. Living Well with COPD, Q&A: Grace Anne Koppel | NIH MedlinePlus the Magazine

    MedlinePlus

    ... What needs to be done to address this gender disparity? Through recent research, we have come to ... also that women have a more toxic reaction. Gender is not the only disparity in COPD. Those ...

  17. Refinement and design of rare earth doped photonic crystal fibre amplifier using an ANN approach

    NASA Astrophysics Data System (ADS)

    Mescia, Luciano; Fornarelli, Girolamo; Magarielli, Donato; Prudenzano, Francesco; De Sario, Marco; Vacca, Francesco

    2011-10-01

    A number of numerical and analytical methods with different complexity can be exploited to analyse fibre amplifiers. Conventional approaches make the refinement and design of the devices extremely time consuming, especially when several design parameters have to be simultaneously optimised to obtain the desired performance in terms of gain and noise figure. In order to tackle this issue, a method based on an artificial neural network to perform the refinement and design of erbium doped photonic crystal fibre amplifiers is proposed in this paper. The capability of the neural network to capture the nonlinear functional link among the physical and geometrical characteristics of the fibre amplifier and its gain and noise figure is exploited. In the refinement it is employed to determine the optimal values of the parameters maximising the gain. In the design, it is used to develop an inverse problem solver in order to determine the values of the parameters corresponding to the known values of gain. Numerical results show that the proposed approach finds the refinement/design parameters in good accordance with respect to the conventional one.

  18. Zimbabweite, a new alkali-lead arsenic tantalate from St Anns mine, Karoi district, Zimbabwe.

    USGS Publications Warehouse

    Foord, E.E.; Taggart, J.E.; Gaines, R.V.; Grubb, P.L.C.; Kristiansen, R.

    1986-01-01

    Zimbabweite occurs as honey yellow-brown crystals (= or 2.10, 2Vgamma approx 80o, dispersion very strong v > r; alpha (pale yellow brown) = c, beta (light reddish brown = b, gamma (reddish brown) = a. Mean reflectance in air for an (010) = alpha -gamma cleavage plate is 16.6% at 589 nm. Chemical analysis gave Ta2O5 46.5, As2O3 26.5, PbO 15.0, Nb2O5 4.8, Na2O 3.1 K2O 1.5, TiO2 1.4, BaO 0.4, UO2 0.3, Bi2O3 0.2, H2O 0.19, SnO2 0.1, F 0.04, SrO 0.02, less O = F 0.02, = 100.05, leading to the idealized formula (Na,K)2PbAs4(Ta,Nb,Ti)4O18. Indexed XRD powder data are tabulated; strongest lines 3.195(100), 2.990(70), 2.882(70), 3.033(60), 3.823(55), 2.548(50), 1.913(50) A; a 12.233, b 15.292, c 8.665; A; space group Ccma or Cc2a, Z = 4. The TG curve shows a rapid weight loss of approx 22.5% at 840-900oC, due to the loss of As2O5.-R.A.H.

  19. Prediction Model for Predicting Powdery Mildew using ANN for Medicinal Plant—Picrorhiza kurrooa

    NASA Astrophysics Data System (ADS)

    Shivling, V. D.; Ghanshyam, C.; Kumar, Rakesh; Kumar, Sanjay; Sharma, Radhika; Kumar, Dinesh; Sharma, Atul; Sharma, Sudhir Kumar

    2016-06-01

    Plant disease fore casting system is an important system as it can be used for prediction of disease, further it can be used as an alert system to warn the farmers in advance so as to protect their crop from being getting infected. Fore casting system will predict the risk of infection for crop by using the environmental factors that favor in germination of disease. In this study an artificial neural network based system for predicting the risk of powdery mildew in Picrorhiza kurrooa was developed. For development, Levenberg-Marquardt backpropagation algorithm was used having a single hidden layer of ten nodes. Temperature and duration of wetness are the major environmental factors that favor infection. Experimental data was used as a training set and some percentage of data was used for testing and validation. The performance of the system was measured in the form of the coefficient of correlation (R), coefficient of determination (R2), mean square error and root mean square error. For simulating the network an inter face was developed. Using this interface the network was simulated by putting temperature and wetness duration so as to predict the level of risk at that particular value of the input data.

  20. 76 FR 80392 - Notice of Inventory Completion: University of Michigan Museum of Anthropology, Ann Arbor, MI

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-12-23

    ... abrader, 64 faunal bones, 45 fragments of charcoal, 8 eroded daub fragments, 8 pieces of fire cracked rock... charcoal samples, but the results were inconclusive. Determinations Made by the University of...

  1. ANN modeling of cold cranking test for sealed lead-acid batteries

    NASA Astrophysics Data System (ADS)

    Karami, Hassan; Karimi, Mohammad Ali; Mahdipour, Maryam

    A cold cranking test for 17 sealed lead-acid batteries with grids of lead-calcium alloy at -18 °C was performed at different discharge currents. Time-voltage behavior of the batteries during 10 s discharge, voltage values at discharge times of 30, 60 and 90 s, and time of discharge to reach a final voltage of 6 V are critical points in the cold cranking test. These were modeled by artificial neural networks in MATLAB 7 media. Nine discharge currents were used for the training set, five discharge currents for the prediction set and three discharge currents for the validation set. Maximum prediction errors in the modeling of the time-voltage behavior during a 10 s discharge (model 1), the voltage of critical points of 30, 60, 90 s (model 2) and the time to reach a final voltage of 6 V (model 3) were under 3.1%, 3.3%, and 3.5%, respectively for each model. The results obtained showed that the models can be used in the battery industry for the prediction of the cold cranking behavior of lead-acid batteries at high discharge currents based on experimental cold cranking data at low discharge currents without the use of expensive and complex instruments. A file (EXE file) based on the model obtained by WinNN 32 was prepared to enable inexpert operators in the lead-acid battery industry to use the method.

  2. Establishing the Balance: Re-Examining Students' Androcentric Readings of Katherine Anne Porter's "Rope."

    ERIC Educational Resources Information Center

    Nudd, Donna Marie

    1991-01-01

    Analyzes undergraduates' interpretations of a short story that presents a relatively balanced argument between a man and a woman. Finds both male and female students arrived at androcentric readings by solving text ambiguities in favor of the male character. Presents methods that encourage students to recognize and reevaluate their reading…

  3. Classifying Sources Influencing Indoor Air Quality (IAQ) Using Artificial Neural Network (ANN)

    PubMed Central

    Mad Saad, Shaharil; Melvin Andrew, Allan; Md Shakaff, Ali Yeon; Mohd Saad, Abdul Rahman; Muhamad Yusof @ Kamarudin, Azman; Zakaria, Ammar

    2015-01-01

    Monitoring indoor air quality (IAQ) is deemed important nowadays. A sophisticated IAQ monitoring system which could classify the source influencing the IAQ is definitely going to be very helpful to the users. Therefore, in this paper, an IAQ monitoring system has been proposed with a newly added feature which enables the system to identify the sources influencing the level of IAQ. In order to achieve this, the data collected has been trained with artificial neural network or ANN—a proven method for pattern recognition. Basically, the proposed system consists of sensor module cloud (SMC), base station and service-oriented client. The SMC contain collections of sensor modules that measure the air quality data and transmit the captured data to base station through wireless network. The IAQ monitoring system is also equipped with IAQ Index and thermal comfort index which could tell the users about the room’s conditions. The results showed that the system is able to measure the level of air quality and successfully classify the sources influencing IAQ in various environments like ambient air, chemical presence, fragrance presence, foods and beverages and human activity. PMID:26007724

  4. Assessment of Subsurface Drainage Management Practices to Reduce Nitrogen Loadings Using AnnAGNPS

    EPA Science Inventory

    The goal of the Future Midwest Landscape project is to quantify current and future landscape services across the region and examine changes expected to occur as a result of two alternative drivers of future change: the growing demand for biofuels; and hypothetical increases in in...

  5. 77 FR 45532 - Approval and Promulgation of Implementation Plans; Michigan; Detroit-Ann Arbor Nonattainment Area...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-08-01

    ... Reviews I. Background On July 18, 1997 (62 FR 38652), EPA established an annual PM 2.5 NAAQS at 15.0... January 5, 2005 (70 FR 944), EPA published its air quality designations and classifications for the 1997... monitoring data for the 2007-2009 and 2008-2010 design value periods. On July 5, 2012 (77 FR 39659)...

  6. The Study of PID Work at DAMPE by Using ANN Method

    NASA Astrophysics Data System (ADS)

    Zhang, Yunlong

    A multilayered perceptrons' neural network technique has been applied in the particle identification at DArk Matter Particle Explore. Good electrons and protons are separated from networks by using the Monte Carlo samples.

  7. Living Well with COPD, Q&A: Grace Anne Koppel | NIH MedlinePlus the Magazine

    MedlinePlus

    ... The NIH's COPD Learn More Breathe Better ® Campaign Network is now in all 50 states and the ... Learn More Breathe Better® program encourages Breathe Better Network members and all those interested in raising COPD ...

  8. AnnAGNPS model application for nitrogen loading assessment for the future midwest landscape study

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Future Midwest Landscape (FML) project is part of the US Environmental Protection Agency (EPA)’s new Ecosystem Services Research Program, undertaken to examine the variety of ways in which landscapes that include crop lands, conservation areas, wetlands, lakes, and streams affect human well-bein...

  9. 77 FR 66547 - Approval and Promulgation of Implementation Plans; Michigan; Detroit-Ann Arbor Nonattainment Area...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-11-06

    ... Order Reviews I. What action is EPA taking? On August 1, 2012 (77 FR 45532), EPA published a proposed... refer to EPA's proposed rulemaking at 77 FR 45532. Section 172(c)(3) of the CAA requires areas to submit... the Office of Management and Budget under Executive Order 12866 (58 FR 51735, October 4, 1993);...

  10. Simulating land use change by integrating landscape metrics into ANN-CA in a new way

    NASA Astrophysics Data System (ADS)

    Yang, Xin; Zhao, Yu; Chen, Rui; Zheng, Xinqi

    2016-06-01

    Landscape metrics are measurements of landuse patterns and land-use change, but even so, have rarely been integrated into land-use change simulation models. This paper proposes a new artificial neural network-cellular automaton by integrating landscape metrics into the model. In this model, each cell acquires unique landscape metric values. The landscape metric values of each cell are actually the landscape metric values of land use type in its neighborhood, which takes the cell as center. The calculation of landscape metrics ensures that those of each cell can represent cellular spatial environmental characteristics. The model is used to simulate land use change in the Changping district of Beijing, China. Comparisons of the simulated land use map with the actual map show that the proposed model is effective for land use change simulation. The validation is further carried out by comparing the simulated land use map with that simulated by an artificial neural network-cellular automaton model, which has not been integrated with landscape metrics. Results indicate that the proposed model is more appropriate for simulating both quantity and spatial distribution of land use change in the study area.

  11. Pancreatic Reference Set Application- Ann Killary-MD Anderson (2012) — EDRN Public Portal

    Cancer.gov

    ELISA assays. We propose to screen a two gene panel (TNC/TFPI) from functional genomic pathways approaches, by ELISA assays, in a collection of blinded plasma samples with the PCCG. In subsequent years, we will add to this panel additional candidates identified in the parent EDRN grant that are in the migration signature network or the 20q amplicon. For ELISA assays, we will utilize commercially available kits. Plasma levels of the predominant isoform of TNC, TNC-large variant (TNC-L) will be determined using a Human Tenascin-C Large (HMV) (FNIII-B) ELISA kit (IBL-America, Minneapolis, MN), which detects human TNC high molecular weight variant by sandwich ELISA. Plasma TFPI levels will be determined using a commercially available Quantikine Human TFPI ELISA kit (DTFP10) (R&D; Systems, Inc. Minneapolis, MN), which detects predominantly free TFPI and a very small percentage of LDL and HDL-bound TFPI by sandwich ELISA. Additional ELISA assays will be added in years 2-3 using ingenuity network analysis to identify secreted proteins that interact with migration signature proteins identified using functional genomic approaches. In addition, Dr. Sen’s lab has identified candidate biomarkers mapping with the 20q amplicon and which are both amplified and overexpressed as well as are secreted proteins. In years 2-3, we will examine all candidate markers by ELISA to determine 20q pathway markers increase the sensitivity and specificity of the 3p panel. Validation of a 4 miR Panel. For assaying the levels of miRs in plasma, qRT-PCR assays will be performed, as described (9). For the selected panel of miRs, we propose to develop a high throughput qRT-PCR assay by adapting our published method to a 96 well format where the critical steps of purification, such as LiCl precipitation and DNAse treatments will be done in successive steps in the same plates. In years 2-3, additional miRs that target both the 20q amplicon genes as well as miRs that target migration genes in Dr. Killary’

  12. Analysis of ultraviolet absorption spectrum of Chinese herbal medicine-Cortex Fraxini by double ANN

    NASA Astrophysics Data System (ADS)

    Bai, Lifei; Zhang, Haitao; Wang, Hongxia; Li, Junfeng; Lu, Lei; Zhang, Hanqi; Wang, Hongyan

    2006-11-01

    A fast, accurate and convenient method for the simultaneous determination of multi-component in the Chinese herbal medicine was proposed by using ultraviolet absorption spectrum. In this method, dummy components were added to training sample, and a double artificial neural network (DANN) that has the function of high self-revision and self-simulation was used. Effect of other interference components could be eliminated by adjusting concentration of dummy components. Therefore, the accuracy of concentration prediction for multi-component in the complicated Chinese herbal medicine was improved. It has been realized that two effective components of Cortex Fraxini, aesculin and aesculetin, were simultaneously determined, without any separation. The predicted accuracy was 92% within the permitted relative errors. The measurement precisions of the aesculin and aesculetin were 0.37% and 1.5%, respectively.

  13. Computer aided detection of tumor and edema in brain FLAIR magnetic resonance image using ANN

    NASA Astrophysics Data System (ADS)

    Pradhan, Nandita; Sinha, A. K.

    2008-03-01

    This paper presents an efficient region based segmentation technique for detecting pathological tissues (Tumor & Edema) of brain using fluid attenuated inversion recovery (FLAIR) magnetic resonance (MR) images. This work segments FLAIR brain images for normal and pathological tissues based on statistical features and wavelet transform coefficients using k-means algorithm. The image is divided into small blocks of 4×4 pixels. The k-means algorithm is used to cluster the image based on the feature vectors of blocks forming different classes representing different regions in the whole image. With the knowledge of the feature vectors of different segmented regions, supervised technique is used to train Artificial Neural Network using fuzzy back propagation algorithm (FBPA). Segmentation for detecting healthy tissues and tumors has been reported by several researchers by using conventional MRI sequences like T1, T2 and PD weighted sequences. This work successfully presents segmentation of healthy and pathological tissues (both Tumors and Edema) using FLAIR images. At the end pseudo coloring of segmented and classified regions are done for better human visualization.

  14. 76 FR 36151 - Notice of Inventory Completion: Museum of Anthropology, University of Michigan, Ann Arbor, MI

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-06-21

    ... Corydon La Ford, MD (tenure 1854-1894), University of Michigan, Medical School, Department of Anatomy. The... individuals until the early 20th century. The collection was used for anatomy teaching in the Medical...

  15. Effects on the Mount St. Helens volcanic cloud on turbidity at Ann Arbor, Michigan

    SciTech Connect

    Ryznar, E.; Weber, M.R.; Hallaron, T.S.

    1981-11-01

    Measurements of turbidity were made at the University of Michigan irradiance and metorlogical measurement facility just prior to, during and after the passage of the volcanic cloud from the 18 May 1980 eruption of Mount St. Helens. They were made with a Volz sunphotometer at wavelengths of 500 and 880 nm.

  16. User Activity Recognition in Smart Homes Using Pattern Clustering Applied to Temporal ANN Algorithm.

    PubMed

    Bourobou, Serge Thomas Mickala; Yoo, Younghwan

    2015-01-01

    This paper discusses the possibility of recognizing and predicting user activities in the IoT (Internet of Things) based smart environment. The activity recognition is usually done through two steps: activity pattern clustering and activity type decision. Although many related works have been suggested, they had some limited performance because they focused only on one part between the two steps. This paper tries to find the best combination of a pattern clustering method and an activity decision algorithm among various existing works. For the first step, in order to classify so varied and complex user activities, we use a relevant and efficient unsupervised learning method called the K-pattern clustering algorithm. In the second step, the training of smart environment for recognizing and predicting user activities inside his/her personal space is done by utilizing the artificial neural network based on the Allen's temporal relations. The experimental results show that our combined method provides the higher recognition accuracy for various activities, as compared with other data mining classification algorithms. Furthermore, it is more appropriate for a dynamic environment like an IoT based smart home. PMID:26007738

  17. User Activity Recognition in Smart Homes Using Pattern Clustering Applied to Temporal ANN Algorithm

    PubMed Central

    Bourobou, Serge Thomas Mickala; Yoo, Younghwan

    2015-01-01

    This paper discusses the possibility of recognizing and predicting user activities in the IoT (Internet of Things) based smart environment. The activity recognition is usually done through two steps: activity pattern clustering and activity type decision. Although many related works have been suggested, they had some limited performance because they focused only on one part between the two steps. This paper tries to find the best combination of a pattern clustering method and an activity decision algorithm among various existing works. For the first step, in order to classify so varied and complex user activities, we use a relevant and efficient unsupervised learning method called the K-pattern clustering algorithm. In the second step, the training of smart environment for recognizing and predicting user activities inside his/her personal space is done by utilizing the artificial neural network based on the Allen’s temporal relations. The experimental results show that our combined method provides the higher recognition accuracy for various activities, as compared with other data mining classification algorithms. Furthermore, it is more appropriate for a dynamic environment like an IoT based smart home. PMID:26007738

  18. Assessing Long Term Impact of Phosphorus Fertilization on Phosphorus Loadings Using AnnAGNPS

    EPA Science Inventory

    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 different phosphorus fertilization rates on phosphorus losses, the US...

  19. Booknote: Core Organic Chemistry, 2nd Edition (by Marye Anne Fox and James K. Whitesell)

    NASA Astrophysics Data System (ADS)

    Stradling, Samuel S.

    1998-11-01

    Jones and Bartlett: Sudbury, MA, 1997. 928 pp. ISBN 0763703672. 71.25. "This version...answers your request for an organic chemistry text that you can cover completely in a two-semester course." Such is Jones and Bartlett's rationale for omitting the special-topics chapters 17-23 from the second edition of Fox and Whitesell's more ambitious Organic Chemistry text. The 16 chapters that remain as this Core Organic Chemistry text are identical to those in the parent text. The strengths and advantages of the authors' approach to presenting organic chemistry remain, of course (J. Chem. Educ. 1997, 74, 1045-1046). To select a text on the basis of whether most pages can be covered seems a tenuous choice. A more important question is what value to the student is gained or lost by the choice made. Is it of greater value to provide a less voluminous (by 320 pages), less weighty (by about 1.2 pounds), and less expensive (88.75 vs $71.25) book, or to provide the students with the opportunity to read, perhaps on their own initiative, chapters on polymeric materials, naturally occurring oxygen and nitrogen compounds, noncovalent interactions and molecular recognition, molecular recognition of chiral molecules, catalyzed reactions, cofactors for biological reactions, energy storage in organic molecules, and molecular basis for drug action? I would argue that the potential for benefit to the student is better served by having those topics available for perusal, even if not formally presented in the class. It should be noted that arrangements can be made to purchase any of these special topics separately, and integrate them into a course as desired.

  20. 76 FR 73670 - Notice of Inventory Completion: University of Michigan Museum of Anthropology, Ann Arbor, MI

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-11-29

    ...The University of Michigan has completed an inventory of human remains and associated funerary objects, in consultation with the appropriate Indian tribes, and has determined that there is no cultural affiliation between the remains and any present-day Indian tribe. Representatives of any Indian tribe that believes itself to be culturally affiliated with the human remains may contact the......

  1. Research for fluid impurity detection based on ANN and infrared spectrum analysis technology

    NASA Astrophysics Data System (ADS)

    Ma, Huiping; Yuan, Feng

    2011-08-01

    A series of economic losses is caused by the biofilm of water pipe in industrial real water systems. Combined optical fiber self-relative technology with infrared spectrum analysis technology, real time detection technique for forming thickness and ingredient is put forward in the paper, which provides technical support and reliable data for analyzing biofouling influencing factors, contaminant separation and warning. Schematic diagram of biofouling detection is presented. Compensation technology based on radial basis function (RBF) neural network and learning algorithm are studied in order to solve the problem of measurement precision and range. Biofouling forming and optical characteristics in industrial real water systems are researched and standard specimen collection is set up. Correcting model explaining quantitatively relation between substance ingredient content and infrared spectrum based on partial least squares (PLS) method. A new method is provided for the research on biofouling in real water system, which can be used in other fields such as mining, environment protection, medical treatment and transportation of oil, gas and water.

  2. [Establishment of hepatitis B virus (HBV) chronic infection mouse model by in vivo transduction with a recombinant adeno-associated virus 8 carrying 1. 3 copies of HBV genome (rAAN8-1. 3HBV)].

    PubMed

    Dong, Xiao-Yan; Yu, Chi-Jie; Wang, Gang; Tian, Wen-Hong; Lu, Yue; Zhang, Feng-Wei; Wang, Wen; Wang, Yue; Tan, Wen-Jie; Wu, Xiao-Bing

    2010-11-01

    In this report, we developed a HBV infection model in C57BL/6 mouse line by in vivo injection of a recombinant adeno-associated virus 8 vector carrying 1. 3 copies of HBV genome (ayw subtype) (rAAV8-1. 3HBV). We firstly prepared and purified the rAAV8-1. 3HBV and then injected it into three C57BL/6 mice with the dose of 2 x 10e11vg, respectively. HBsAg and HBeAg were assayed in sera collected at different time points post injection. Ten weeks post injection, the three mice were sacrificed and blood and liver tissue were taken for assay. Copies of HBV DNA were detected by real time PCR and the way of HBV DNA replication was identified by PCR. Subsequently, detection of HBV antigen by immunohistochemistry and pathology analysis of liver tissue of mice were performed. The results suggested that expression of HBsAg and HBeAg lasted for at least 10 weeks in mice sera. Among mice injected with rAAV8-1. 3HBV, HBsAg levels were showed an 'increasing-decreasing-increasing' pattern (the lowest level at the 4th week post injection), while HBeAg levels were kept high and relatively stable. HBV DNA copies were 4.2 x 10(3), 3.6 x 10(3), 2.5 x 10(3) copies/mL in sera and 8.0 x 10(6), 5.7 x 10(6), 2.6 x 10(6) copies/g in hepatic tissues of three mice, respectively. We found that the linear 1. 3HBV DNA in the rAAV8-1. 3HBV could self form into circular HBV genome and replicate in livers of HBV transfected mice. HBsAg and HBcAg were both positive in liver tissue of mice injected with rAAV8-1. 3HBV and no obvious pathological characters were found in liver of mice injected with rAAV8-1. 3HBV. In conclusion, we successfully developed a HBV chronic infection model in C57BL/6 mouse line by in vivo transduction with the recombinant virus rAAV8-1. 3HBV, in which HBV genes could be continuously expressed and replicated over 10 weeks, and paved a way for further characterization of the human chronic hepatitis B virus infection and evaluation of vaccine and anti-HBV agents. PMID:21344744

  3. Prevention of Antisocial Behavior: Starting at (Pre-)Conception? Tendencies in Care and Family Support = Preventie van antisociaal gedrag: Starten bij de (pre-)conceptie? Tendensen in hulpverlening en opvoeding sondersteuning aan gezinnen.

    ERIC Educational Resources Information Center

    De Mey, Wim, Ed.; Moens, Ellen, Ed.; Van Leeuwen, Karla, Ed.; Verhofstadt-Deneve, Leni, Ed.

    Behavioral problems are the most common mental health problem in children and adolescents worldwide. For several decades there has been a growing body of scientific knowledge of the factors influencing the development of antisocial behavior. There are several intervention and prevention programs, the most effective of which activate parents,…

  4. Corrigendum to "Convergence of Feynman integrals in Coulomb gauge QCD" [Ann. Phys. 351 (2014) 407-417

    NASA Astrophysics Data System (ADS)

    Andraši, A.; Taylor, J. C.

    2015-12-01

    In our previous paper, there were algebraic errors in the derivations of Eqs. (5.2) and (5.8). These led to consequent errors in some subsequent equations. The corrected equations are listed below with their original equation numbers.

  5. QSBR study of bitter taste of peptides: application of GA-PLS in combination with MLR, SVM, and ANN approaches.

    PubMed

    Soltani, Somaieh; Haghaei, Hossein; Shayanfar, Ali; Vallipour, Javad; Asadpour Zeynali, Karim; Jouyban, Abolghasem

    2013-01-01

    Detailed information about the relationships between structures and properties/activities of peptides as drugs and nutrients is useful in the development of drugs and functional foods containing peptides as active compounds. The bitterness of the peptides is an undesirable property which should be reduced during drug/nutrient production, and quantitative structure bitter taste relationship (QSBR) studies can help researchers to design less bitter peptides with higher target efficiency. Calculated structural parameters were used to develop three different QSBR models (i.e., multiple linear regression, support vector machine, and artificial neural network) to predict the bitterness of 229 peptides (containing 2-12 amino acids, obtained from the literature). The developed models were validated using internal and external validation methods, and the prediction errors were checked using mean percentage deviation and absolute average error values. All developed models predicted the activities successfully (with prediction errors less than experimental error values), whereas the prediction errors for nonlinear methods were less than those for linear methods. The selected structural descriptors successfully differentiated between bitter and nonbitter peptides. PMID:24371826

  6. Making the Past Relevant to Future Generations. The Work of the Anne Frank House in Latin America

    ERIC Educational Resources Information Center

    Chyrikins, Mariela; Vieyra, Magdalena

    2010-01-01

    This paper provides the context and outlines the barriers and opportunities for developing promising Holocaust education programmes in Latin America, especially working with diverse communities and societies. In particular, the conflictual history of Latin American and recent democratization processes present opportunities for educational work. It…

  7. Tolerance Education in Morocco. "Anne Frank: A History for Today"--Learning about Our Past--Contributing to Our Future

    ERIC Educational Resources Information Center

    Polak, Karen

    2010-01-01

    This paper describes recent developments in the field of history education and human rights education in Morocco. Educational reform in Morocco is ongoing and includes measures such as mandating that all schools create after-school Human Rights Clubs. These developments are then related to the possibility of teaching about the history of the…

  8. ANN based inversion of DC resistivity data for groundwater exploration in hard rock terrain of western Maharashtra (India)

    NASA Astrophysics Data System (ADS)

    Maiti, Saumen; Erram, Vinit C.; Gupta, Gautam; Tiwari, Ram Krishna

    2012-09-01

    SummaryInversion of vertical electrical sounding (VES) data, especially from the crystalline hard rock area, assumes a special significance for groundwater exploration. Here we used a newly developed algorithm based on the Bayesian neural network (BNN) theory combined with Hybrid Monte Carlo (HMC)/Markov Chain Monte Carlo (MCMC) simulation scheme to invert the Direct Current (DC) VES measurements obtained from 30-locations around Tenduli-Vengurla, Sindhudurg district, Maharashtra, India. The inversion results suggest that the top layer is mostly comprised of laterites followed by mixture of clay/clayey sand and garnulites/granite as basement rocks. The source of groundwater appears to be accessible in weathered/semi-weathered layer of laterite/clayey sand that exists within the depth of 10-15 m from the surface. The NW-SE trending major lineaments and its criss-crosses are also identified from the apparent and true resistivity surface map. The pseudo-section at different depths in the western part of the area, near Nivti, shows extensive influence of saltwater intrusion and its impact reaching up to the depth of 30 m from the surface along the coastal area. Our results also show that intrusion of saline water decreases from the western part to the eastern part of the region. Two dimensional modeling of four resistivity profiles from the study region identified two potential groundwater reservoirs; one lying between Path-Tenduli and another in between Mat and Zaraph. The deduced true electrical resistivity section against depth correlates well with available borehole lithology in the area. The results presented here would be useful for interpreting the geological signatures like fractures, major joints and lineaments, which in turn will be helpful for identifying groundwater reservoirs and drainage pattern in the crystalline hard rock area. The newly developed HMC-based BNN method is robust and would provide insights for constraining the geophysical models and criteria for modeling resistivity data.

  9. Tissue distribution model and pharmacokinetics of nuciferine based on UPLC-MS/MS and BP-ANN

    PubMed Central

    Xu, Yanyan; Bao, Shihui; Tian, Weiqiang; Wen, Congcong; Hu, Lufeng; Lin, Chongliang

    2015-01-01

    Nuciferine has shown remarkable biological activities and been considered as a promising drug. In this study, a sensitive and selective ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was developed and validated for determination of nuciferine in tissue and plasma. An electrospray ionization source was applied and operated in positive ion mode; multiple reactions monitoring (MRM) mode was used for quantification using target fragment ions m/z 296.0→265.1 for nuciferine, and m/z 322.0→307.0 for berberrubine internal standard (IS). Based on the UPLC-MS/MS method, the tissue distribution profile of nuciferine in mice and plasma pharmacokinetics in rat were studied. The results showed nuciferine was absorbed through intestinal tract and distributed into tissues rapidly. The bioavailability of nuciferine was identified at 17.9%. It can across through blood brain barrier, the concentrations in liver and kidney are highest, then followed by spleen, lung heart and brain. Nuciferine is eliminated quickly in the tissues and plasma, the t1/2 within 5 hour. The concentrations in these tissues are correlated to each other, and can be predicted by a back-propagation artificial neural network model. PMID:26770351

  10. From "Lawrence Kohlberg's Approach to Moral Education" by F. Clark Power, Ann Higgins, and Lawrence Kohlberg, with Judy Codding (1989)

    ERIC Educational Resources Information Center

    Schools: Studies in Education, 2011

    2011-01-01

    This article is an excerpt from "Lawrence Kohlberg's Approach to Moral Education." It refers several times to Kohlberg's "six stages of moral development." Stages 3 and 4 belong to the second level of moral development, which Kohlberg calls "conventional." At stage 3, one becomes aware of conventions as one sees what is right in terms of living up…

  11. Comparison of SWAT and AnnAGNPS Applications to a Sub-Watershed Within the Chesapeake Bay Watershed in Maryland

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This study was conducted under the USDA-CEAP program on the Choptank watershed which is located within the Chesapeake Bay watershed in the Eastern Shore region of Maryland. The watershed is nearly 400 square mile and is dominated by corn and soybean productions. Poultry manure is being used heavil...

  12. High energy gamma-ray astronomy; Proceedings of the International Conference, ANN Arbor, MI, Oct. 2-5, 1990

    NASA Astrophysics Data System (ADS)

    Matthews, James

    The present volume on high energy gamma-ray astronomy discusses the composition and properties of heavy cosmic rays greater than 10 exp 12 eV, implications of the IRAS Survey for galactic gamma-ray astronomy, gamma-ray emission from young neutron stars, and high-energy diffuse gamma rays. Attention is given to observations of TeV photons at the Whipple Observatory, TeV gamma rays from millisecond pulsars, recent data from the CYGNUS experiment, and recent results from the Woomera Telescope. Topics addressed include bounds on a possible He/VHE gamma-ray line signal of Galactic dark matter, albedo gamma rays from cosmic ray interactions on the solar surface, source studies, and the CANGAROO project. Also discussed are neural nets and other methods for maximizing the sensitivity of a low-threshold VHE gamma-ray telescope, a prototype water-Cerenkov air-shower detector, detection of point sources with spark chamber gamma-ray telescopes, and real-time image parameterization in high energy gamma-ray astronomy using transputers. (For individual items see A93-25002 to A93-25039)

  13. IEEE National Radar Conference, 3rd, University of Michigan, Ann Arbor, MI, Apr. 20, 21, 1988, Proceedings

    NASA Astrophysics Data System (ADS)

    The present conference discusses topics in radar systems and subsystems, radar techniques, radar signal processing, and radar phenomenology. Attention is given to mm-wave radar system tradeoffs, polarimetric X/L/C-band SAR, a VHF radar for tropical jungle terrain elevation modeling, low probability of intercept techniques and implementations, target tracking in maneuver-centered coordinates, advanced techniques for extension of SAR depth-of-focus under arbitrary aircraft maneuvers, and iterative noncoherent angular superresolution. Also discussed are the effect of codebook size on the vector quantization of SAR data, the application of knowledge-based systems to surveillance, digital filters for SAR, novel radar pulse compression waveforms, the theory and application of SAR oceanography, autoregressive modeling of radar data with application to target identification, and a coherent model of radar weather clutter.

  14. Proceedings of the Annual Conference of the Midwest Philosophy of Education Society (Ann Arbor, Michigan, November 10-11, 1978).

    ERIC Educational Resources Information Center

    Merritt, James, Ed.; And Others

    The Midwest Philosophy of Education Society strives to enhance and deepen the level of conversation about education in the modern world and to evaluate, in moral terms, the relationship of education to the larger society. The following papers were presented at the 1978 annual meeting of the Society: "Educational Evaluation and Emancipation" (Gary…

  15. Development and Application of Gully Erosion Components within the USDA AnnAGNPS Watershed Model for Precision Conservation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A watershed scale assessment of the effect of conservation practices on the environment is critical when recommending conservation management practices to agricultural producers. The identification of all sources of sediment and subsequent tracking of the movement of sediment downstream is a ...

  16. VizieR Online Data Catalog: Morphologies of z<0.01 SDSS-DR7 galaxies (Ann+, 2015)

    NASA Astrophysics Data System (ADS)

    Ann, H. B.; Seo, M.; Ha, D. K.

    2015-05-01

    This paper presents a catalog of the morphological types of galaxies whose redshifts are less than z=0.01. The morphological types are determined by a visual inspection of the color images provided by SDSS DR7 (II/294). The majority of galaxies in the present sample come from the KIAS-VAGC (Choi et al. 2010JKAS...43..191C) which is based on the spectroscopic target galaxies of the SDSS DR7 complemented by the bright galaxies with known redshifts from various catalogs. (1 data file).

  17. AnnAGNPS GIS-based tool for watershed-scale identification and mapping of cropland potential ephemeral gullies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The formation of ephemeral gullies in agricultural fields has been recognized as an important source of sediment contributing to environmental degradation and compromising crop productivity. Methodologies are being developed for assessing gully formation and gully sediment yield. The Annualized Agri...

  18. Proceedings of the Conference on Nutrition and Mental Retardation (Ann Arbor, Michigan, February 10-11, 1971).

    ERIC Educational Resources Information Center

    Springer, Ninfa Saturnino, Ed.

    The conference, planned primarily for nutritionists and dieticians, dealt with the role of nutrition in the prevention and management of mental retardation. Proceedings include an overview of mental retardation, an examination of nutrition manpower needs in the fields of mental health and mental retardation on both the national and state levels,…

  19. Watershed runoff and sediment transport impacts from management decisions using integrated AnnAGNPS and CCHE1D models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Conservation planning tools that consider all sources of erosion, sheet and rill, gully, and channels, is critical to developing an effective watershed management plan that considers the integrated effect of all practices on the watershed system. The Annualized Agricultural Non-Point Source polluta...

  20. Performance Parameters Analysis of an XD3P Peugeot Engine Using Artificial Neural Networks (ANN) Concept in MATLAB

    NASA Astrophysics Data System (ADS)

    Rangaswamy, T.; Vidhyashankar, S.; Madhusudan, M.; Bharath Shekar, H. R.

    2015-04-01

    The current trends of engineering follow the basic rule of innovation in mechanical engineering aspects. For the engineers to be efficient, problem solving aspects need to be viewed in a multidimensional perspective. One such methodology implemented is the fusion of technologies from other disciplines in order to solve the problems. This paper mainly deals with the application of Neural Networks in order to analyze the performance parameters of an XD3P Peugeot engine (used in Ministry of Defence). The basic propaganda of the work is divided into two main working stages. In the former stage, experimentation of an IC engine is carried out in order to obtain the primary data. In the latter stage the primary database formed is used to design and implement a predictive neural network in order to analyze the output parameters variation with respect to each other. A mathematical governing equation for the neural network is obtained. The obtained polynomial equation describes the characteristic behavior of the built neural network system. Finally, a comparative study of the results is carried out.

  1. Symposium (International) on Combustion, 20th, University of Michigan, Ann Arbor, MI, August 12-17, 1984, Proceedings

    NASA Technical Reports Server (NTRS)

    1985-01-01

    The present conference on combustion phenomena considers topics in automotive engine combustion, turbulent reacting flows, the modeling of practical combustion systems, reaction kinetics, combustion-generated particulates, combustion diagnostics, coal combustion process characteristics, fire-related phenomena, explosion/detonation phenomena, spray combustion, ignition/extinction, laminar flames, pollutant formation processes, practical combustor devices, and rocket propellant combustion. Attention is given to the contributions of combustion science to piston engine design, modeling and measurement techniques for turbulent combustion, the specific effects of energy, collisions, and transport processes in combustion chemistry kinetics, the formation of large molecules, particulates and ions in premixed hydrocarbon flames, the application of laser diagnostics to combustion systems, spark ignition energies for dust-air mixtures, the controlling mechanisms of flow-assisted flame spread, the ignition and combustion of coal-water slurries, spontaneous ignition of methane, turbulent and accelerating dust flames, and the temperature sensitivity of double base propellants.

  2. Health assessment for Metal Working Shop Site, Lake Ann, Michigan, Region 5. CERCLIS No. MID980992952. Preliminary report

    SciTech Connect

    Not Available

    1988-09-30

    The Metal Working Shop Site is listed on the National Priorities List. The site consists of an operating metal-working facility in a sparsely populated rural area in Benzie, Michigan. Identified contaminants of potential concern on the site include chromium, tetrachloroethylene (PCE), trichloroethane, and toluene in water and trichloroethylene (TCE), trichloroethane, xylenes, ethylbenzene, and toluene in soil. The site is considered to be of potential public health concern because of the risk to human health caused by the possibility of exposure to hazardous substances via contaminated well water and soil. Confirmation of sampling results that show contamination in well water and soil is needed.

  3. Assessment of the Effect of Blast Hole Diameter on the Number of Oversize Boulders Using ANN Model

    NASA Astrophysics Data System (ADS)

    Dhekne, Prakash; Pradhan, Manoj; Jade, Ravi Krishnarao

    2016-04-01

    Now-a-days, blasts are planned using large diameter blast holes. The loading density (kg/m) and subsequently the energy available for the breakage of the rockmass increase with the diameter. The in-hole velocity of detonation (VoD) of non-ideal explosive also boosts up with the increase in diameter till the optimum diameter is reached. The increase in the energy content and in-hole VoD cause a sizable effect on the rock fragmentation. The effect can be assessed by counting the number of oversize boulders. This paper explains as to how the technique of artificial neural network modeling was used to predict the number of oversize boulders resulting from ANFO and SME blasts with blast holes of different diameters. The results from ANFO blasts indicated that there was no significant variation in the number of oversize boulders with the diameter whereas a perceptible variation was noticed in case of SME blasts with the change in the diameter. The change in the number of oversize boulders in ANFO blasts was negligible because mean energy factor remained almost same even when the diameter of the blast holes was altered. The decrease in the number of oversize boulders in SME blasts was on account of increase in mean energy factor when the blast hole diameter was increased. The increase in the in-hole VoD due to increase in the diameter of the hole was not found to have an effect on the generation of oversize boulders as this increase was not substantial both in SME and ANFO blasts.

  4. GIS-based channel flow and sediment transport simulation using CCHE1D coupled with AnnAGNPS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    CCHE1D (Center for Computational Hydroscience and Engineering 1-Dimensional model) simulates unsteady free-surface flows with nonequilibrium, nonuniform sediment transport in dendritic channel networks. Since early 1990’s, the model and its software packages have been developed and continuously main...

  5. Offline signature verification and skilled forgery detection using HMM and sum graph features with ANN and knowledge based classifier

    NASA Astrophysics Data System (ADS)

    Mehta, Mohit; Choudhary, Vijay; Das, Rupam; Khan, Ilyas

    2010-02-01

    Signature verification is one of the most widely researched areas in document analysis and signature biometric. Various methodologies have been proposed in this area for accurate signature verification and forgery detection. In this paper we propose a unique two stage model of detecting skilled forgery in the signature by combining two feature types namely Sum graph and HMM model for signature generation and classify them with knowledge based classifier and probability neural network. We proposed a unique technique of using HMM as feature rather than a classifier as being widely proposed by most of the authors in signature recognition. Results show a higher false rejection than false acceptance rate. The system detects forgeries with an accuracy of 80% and can detect the signatures with 91% accuracy. The two stage model can be used in realistic signature biometric applications like the banking applications where there is a need to detect the authenticity of the signature before processing documents like checks.

  6. Improvement of Adaptive GAs and Back Propagation ANNs Performance in Condition Diagnosis of Multiple Bearing System Using Grey Relational Analysis

    PubMed Central

    Wulandhari, Lili A.; Wibowo, Antoni; Desa, Mohammad I.

    2014-01-01

    Condition diagnosis of multiple bearings system is one of the requirements in industry field, because bearings are used in many equipment and their failure can result in total breakdown. Conditions of bearings commonly are reflected by vibration signals data. In multiple bearing condition diagnosis, it will involve many types of vibration signals data; thus, consequently, it will involve many features extraction to obtain precise condition diagnosis. However, large number of features extraction will increase the complexity of the diagnosis system. Therefore, in this paper, we presented a diagnosis method which is hybridization of adaptive genetic algorithms (AGAs), back propagation neural networks (BPNNs), and grey relational analysis (GRA) to diagnose the condition of multiple bearings system. AGAs are used in the diagnosis algorithm to determine the best initial weights of BPNNs in order to improve the diagnosis accuracy. In addition, GRA is applied to determine and select the dominant features from the vibration signal data which will provide good diagnosis of multiple bearings system in less features extraction. The experiments results show that AGAs-BPNNs with GRA approaches can increase the accuracy of diagnosis in shorter processing time, compared with the AGAs-BPNNs without the GRA. PMID:25587265

  7. Application of PCA-based data compression in the ANN-supported conceptual cost estimation of residential buildings

    NASA Astrophysics Data System (ADS)

    Juszczyk, Michał

    2016-06-01

    The paper presents concisely some research results on the application of principal component analysis for the data compression and the use of compressed data as the variables describing the model in the issue of conceptual cost estimation of residential buildings. The goal of the research was to investigate the possibility of use of compressed input data of the model in neural modelling - the basic information about residential buildings available in the early stage of design and construction cost. The results for chosen neural networks that were trained with use of the compressed input data are presented in the paper. In the summary the results obtained for the neural networks with PCA-based data compression are compared with the results obtained in the previous stage of the research for the network committees.

  8. Establishing causes of eradication failure based on genetics: case study of ship rat eradication in Ste. Anne archipelago.

    PubMed

    Abdelkrim, Jawad; Pascal, Michel; Samadi, Sarah

    2007-06-01

    Determining the causes of a failed eradication of a pest species is important because it enables an argued adjustment of the methodologies used and the improvement of the protocols for future attempts. We examined how molecular monitoring can help distinguish between the two main reasons for an eradication failure (i.e., survival of some individuals vs. recolonization after eradication). We investigated genetic variation in seven microsatellite loci in ship rat (Rattus rattus) populations from four islets off the Martinique coast (French Caribbean). In 1999 an eradication attempt was conducted on the four islets. Three years later rats were observed again on two of them. We compared the genetic signatures of the populations before and after the eradication attempt. On one of the islands, the new rat population was likely a subset of the pre-eradication population. A weak genetic differentiation was found between them, with almost no new alleles observed in the new population and moderate F(ST) values (0.15). Moreover, assignment procedures clustered the two populations together. In contrast, on the other islet, many new alleles were observed after the eradication attempt, resulting in an increase in genetic diversity (from 2.57 to 3.57 mean number of alleles per locus) and strong F(ST) values (0.39). Moreover, genetic clustering clearly separated the two samples (i.e., before and after the eradication attempt) in two different populations. Thus, to achieve long-term eradication on these islets, it seems necessary to redevelop the eradication procedure to avoid individuals surviving and to prevent reinvasion, probably from the mainland, by installing permanent trapping and poisoning devices and conducting regular monitoring. We strongly encourage wildlife managers conducting eradication campaigns to integrate molecular biological tools in their protocols, which can be done easily for most common invasive species. PMID:17531050

  9. 76 FR 44947 - Notice of Intent To Repatriate Cultural Items: University of Michigan Museum of Anthropology, Ann...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-07-27

    ...The University of Michigan Museum of Anthropology, in consultation with the appropriate Indian tribe, has determined that the items meet the definition of sacred objects and repatriation to the Indian tribe stated below may occur if no additional claimants come forward. Representatives of any Indian tribe that believes itself to be culturally affiliated with the sacred objects may contact the......

  10. International Symposium on Space Terahertz Technology, 1st, University of Michigan, Ann Arbor, Mar. 5, 6, 1990, Proceedings

    NASA Astrophysics Data System (ADS)

    Ulaby, Fawwaz; Haddad, George; Kukkonen, Carl

    1991-01-01

    Problems, proposed solutions, and recent results related to the development of solid-state oscillators, detectors, mixers, diode multipliers, and antennas at THz frequencies are addressed. Individual topics considered include: submillimeter heterodyne remote sensing of upper atmospheric gases, planar dipole array antenna with an elliptical lens, twin slot antenna structures integrated with microbolometer detectors for 94-GHz imaging. Also discussed are: quantum-well and quantum-barrier diodes for generating submillimeter wave power, planar Schottky barrier mixer diodes for space applications at submillimeter wavelengths, GaAs Schottky barrier varactor diodes for submillimeter wavelength power generation, planar doped barrier devices for subharmonic mixers.

  11. Smad7 protects against chronic aristolochic acid nephropathy in mice

    PubMed Central

    Huang, Xiao-Ru; Fu, Ping; Lan, Hui-Yao

    2015-01-01

    Chronic Aristolochic Acid Nephropathy (AAN) is a progressive chronic kidney disease related to herb medicine. However, treatment for chronic AAN remains ineffective. We report here that Smad7 is protective and has therapeutic potential for chronic AAN. In a mouse model of chronic AAN, progressive renal injury was associated with a loss of renal Smad7 and disruption of Smad7 largely aggravated the severity of chronic AAN as demonstrated by a significant increase in levels of 24-hour urinary protein excretion, serum creatinine, and progressive renal fibrosis and inflammation. In contrast, restored Smad7 locally in the kidneys of Smad7 knockout mice prevented the progression of chronic AAN. Further studies revealed that worsen chronic AAN in Smad7 knockout mice was associated with enhanced activation of TGF-β/Smad3 and NF-κB signaling pathways, which was reversed when renal Smad7 was restored. Importantly, we also found that overexpression of Smad7 locally in the kidneys with established chronic AAN was capable of attenuating progressive chronic AAN by inactivating TGF-β/Smad3-medated renal fibrosis and NF-κB-driven renal inflammation. In conclusion, Smad7 plays a protective role in the pathogenesis of chronic AAN and overexpression of Smad7 may represent a novel therapeutic potential for chronic AAN. PMID:25883225

  12. ADMINISTERING COMMUNITY COLLEGE STUDENT PERSONNEL SERVICES, REPORT OF THE ANNUAL PRESIDENTS' INSTITUTE, MIDWEST COMMUNITY COLLEGE LEADERSHIP PROGRAM (5TH, ANN ARBOR, 1965).

    ERIC Educational Resources Information Center

    MEALEY, F.R.

    THIS INSTITUTE (JULY 1965) COVERED BOTH IMMEDIATE AND PERIPHERAL ASPECTS OF STUDENT PERSONNEL SERVICES, WITH APPROPRIATE EMPHASIS ON THE SEMIPROFESSIONAL AND OCCUPATIONAL CURRICULUM. COUNSELING SHOULD PROVIDE THE STUDENT WITH (1) ORIENTATION TO COLLEGE LIFE, (2) APPRAISAL OF HIS ABILITIES AND APTITUDES, (3) FIRM REGULATIONS FOR SUITABLE COURSE…

  13. AnnAGNPS – A United States Department of Agriculture Watershed Conservation Management Planning Tool for Non-Point Source Pollution Control

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A watershed scale assessment of the effect of conservation practices on the environment is critical when recommending best management practices to agricultural producers. The environmental benefits of these practices have not been widely quantified at the watershed scale, which would require extens...

  14. Providing for the reappointment of Shirley Ann Jackson as a citizen regent of the Board of Regents of the Smithsonian Institution.

    THOMAS, 112th Congress

    Rep. Johnson, Sam [R-TX-3

    2011-02-16

    02/16/2011 Referred to the House Committee on House Administration. (All Actions) Notes: For further action, see S.J.RES.7, which became Public Law 112-19 on 6/24/2011. Tracker: This bill has the status IntroducedHere are the steps for Status of Legislation:

  15. The Ann Arbor Criteria for Appropriate Urinary Catheter Use in Hospitalized Medical Patients: Results Obtained by Using the RAND/UCLA Appropriateness Method.

    PubMed

    Meddings, Jennifer; Saint, Sanjay; Fowler, Karen E; Gaies, Elissa; Hickner, Andrew; Krein, Sarah L; Bernstein, Steven J

    2015-05-01

    Interventions to reduce urinary catheter use involve lists of "appropriate" indications developed from limited evidence without substantial multidisciplinary input. Implementing these lists, however, is challenging given broad interpretation of indications, such as "critical illness." To refine criteria for appropriate catheter use-defined as use in which benefits outweigh risks-the RAND/UCLA Appropriateness Method was applied. After reviewing the literature, a 15-member multidisciplinary panel of physicians, nurses, and specialists in infection prevention rated scenarios for catheter use as appropriate, inappropriate, or of uncertain appropriateness by using a standardized, multiround rating process. The appropriateness of Foley catheters, intermittent straight catheters (ISCs), and external condom catheters for hospitalized adults on medical services was assessed in 299 scenarios, including urinary retention, incontinence, wounds, urine volume measurement, urine sample collection, and comfort. The scenarios included patient-specific issues, such as difficulty turning and catheter placement challenges. The panel rated 105 Foley scenarios (43 appropriate, 48 inappropriate, 14 uncertain), 97 ISC scenarios (15 appropriate, 66 inappropriate, 16 uncertain), and 97 external catheter scenarios (30 appropriate, 51 inappropriate, 16 uncertain). The refined criteria clarify that Foley catheters are appropriate for measuring and collecting urine only when fluid status or urine cannot be assessed by other means; specify that patients in the intensive care unit (ICU) need specific medical indications for catheters because ICU location alone is not an appropriate indication; and recognize that Foley and external catheters may be pragmatically appropriate to manage urinary incontinence in select patients. These new appropriateness criteria can inform large-scale collaborative and bedside efforts to reduce inappropriate urinary catheter use. PMID:25938928

  16. Proceedings of the Annual Midwest Research-to-Practice Conference in Adult and Continuing Education (4th, Ann Arbor, Michigan, October 10-11, 1985).

    ERIC Educational Resources Information Center

    Berlin, L. S., Ed.

    This document contains the following papers on practical applications of research on adult and continuing education: "Elderly Criminal Behavior: Linking Research to Practice," by Donald J. Bachand and Carl I. Brahce; "Father? Teacher? Friend? Instructor-Student Relationships in a Refugee Class," by Gary J. Bekker; "The Small Group: Understanding…

  17. International Symposium on Remote Sensing of Environment, 9th, University of Michigan, Ann Arbor, Mich., April 15-19, 1974, Proceedings. Volumes 1, 2 & 3

    NASA Technical Reports Server (NTRS)

    1974-01-01

    The present work gathers together numerous papers describing the use of remote sensing technology for mapping, monitoring, and management of earth resources and man's environment. Studies using various types of sensing equipment are described, including multispectral scanners, radar imagery, spectrometers, lidar, and aerial photography, and both manual and computer-aided data processing techniques are described. Some of the topics covered include: estimation of population density in Tokyo districts from ERTS-1 data, a clustering algorithm for unsupervised crop classification, passive microwave sensing of moist soils, interactive computer processing for land use planning, the use of remote sensing to delineate floodplains, moisture detection from Skylab, scanning thermal plumes, electrically scanning microwave radiometers, oil slick detection by X-band synthetic aperture radar, and the use of space photos for search of oil and gas fields. Individual items are announced in this issue.

  18. A Classroom Exercise for Testing Urban Myth: Does Wedding Rice Cause Birds to Explode or Were Ann Landers, Martha Stewart & Bart Simpson Wrong?

    ERIC Educational Resources Information Center

    Krupa, James J.

    2005-01-01

    In this article, the author first provides the history of the wedding rice myth. He then details an interactive class activity that involved students in his large, non-majors biology classes. These students developed a series of experiments that scientifically determined if rice could be harmful to birds. Finally, he provides suggestions on how…

  19. Proceedings of the Annual Eastern Michigan University Conference on Languages for Business and the Professions (5th, Ann Arbor, Michigan, April 10-12, 1986).

    ERIC Educational Resources Information Center

    Voght, Geoffrey M., Comp.

    Forty-five conference papers are presented in six sections: getting started in languages for special purposes (concerning teaching, curriculum development, finding, and resources); Spanish for business and the professions; French for business and the professions; other languages (English as a second language, German, Arabic, Mandarin Chinese, and…

  20. Implementation of artificial neural networks (ANNs) to analysis of inter-taxa communities of benthic microorganisms and macroinvertebrates in a polluted stream.

    PubMed

    Kim, Byunghyuk; Lee, Se-Eun; Song, Mi-Young; Choi, Jung-Hye; Ahn, Soon-Mo; Lee, Kun-Seop; Cho, Eungchun; Chon, Tae-Soo; Koh, Sung-Cheol

    2008-02-01

    This study was performed to gain an understanding of the structural and functional relationships between inter-taxa communities (macroinvertebrates as consumers, and microbes as decomposers or preys for the invertebrates) in a polluted stream using artificial neural networks techniques. Sediment samples, carrying microorganisms (eubacteria) and macroinvertebrates, were seasonally collected from similar habitats in streams with different levels of pollution. Microbial community taxa and densities were determined using polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) and 16S rDNA sequence analysis techniques. The identity and density of macroinvertebrates were concurrently determined. In general, differences were observed on grouping by self-organizing map (SOM) in polluted, clean and recovering sites based on the microbial densities, while the community patterns were partly dependent on the sampling period. A Spearman rank order correlation analysis revealed correlations of several eubacterial species with those of macroinvertebrates: a negative correlation was observed between Acidovorax sp. (from polluted sites) and Gammaridae (mostly from the clean site), while Herbaspirillum sp. and Janthinobacterium sp. appeared to have positive correlations with some macroinvertebrate species. The population dynamics of the tolerant texa, Tubificidae and Chironomidae, appeared to be related with changes in the densities of Acidovorax sp. This study revealed community relationships between macroinvertebrates and microorganisms, reflecting the connectivity between the two communities via the food chain. A further physio-ecological and symbiological study on the invertebrate-microorganism relationships will be required to understand the degradation and utilization of detritus in aquatic ecosystems as well as to elucidate the roles of the inter-taxa in the recovery of polluted aquatic environments. PMID:17964635

  1. Predicting Student Grade Based on Free-Style Comments Using Word2Vec and ANN by Considering Prediction Results Obtained in Consecutive Lessons

    ERIC Educational Resources Information Center

    Luo, Jingyi; Sorour, Shaymaa E.; Goda, Kazumasa; Mine, Tsunenori

    2015-01-01

    Continuously tracking students during a whole semester plays a vital role to enable a teacher to grasp their learning situation, attitude and motivation. It also helps to give correct assessment and useful feedback to them. To this end, we ask students to write their comments just after each lesson, because student comments reflect their learning…

  2. Girls and Science and Technology. Proceedings and Contributions of the GASAT Conference (4th, Ann Arbor, Michigan, July 24-29, 1987).

    ERIC Educational Resources Information Center

    Daniels, Jane Zimmer, Ed.; Kahle, Jane Butler, Ed.

    In 1979, North European researchers met informally to discuss issues regarding women in science. In addition to discovering that the issues raised crossed national boundaries and cultural differences, they found that numerous efforts were underway to address their concerns. What started as an informal meeting has evolved today into an…

  3. Modeling soil organic carbon stock after 10 years of cover crops in Mediterranean vineyards: improving ANN prediction by digital terrain analysis.

    NASA Astrophysics Data System (ADS)

    Lo Papa, Giuseppe; Novara, Agata; Santoro, Antonino; Gristina, Luciano

    2014-05-01

    Estimate changes in soil organic carbon (SOC) stock after Agro Environment Measures adoption are strategically for national and regional scale. Uncertainty in estimates also represents a very important parameter in terms of evaluation of the exact costs and agro environment payments to farmers. In this study we modeled the variation of SOC stock after 10-year cover crop adoption in a vine growing area of South-Eastern Sicily. A paired-site approach was chosen to study the difference in SOC stocks. A total 100 paired sites (i.e. two adjacent plots) were chosen and three soil samples (Ap soil horizons, circa 0-30 cm depth) were collected in each plot to obtain a mean value of organic carbon concentration for each plot. The variation of soil organic carbon (SOCv) for each plot was calculated by differences between concentrations of the plot subjected to cover crops (SOC10) and the relative plot subjected to traditional agronomic practices (SOC0). The feasibility of using artificial neural networks as a method to predict soil organic carbon stock variation and the contribution of digital terrain analysis to improve the prediction were tested. We randomly subdivided the experimental values of SOC-stock difference in 80 learning samples and 20 test samples for model validation. SOCv was strongly correlated to the SOC0 concentration. Model validation using only SOCv as unique covariate showed a training and test perfection of 0.724 and 0.871 respectively. We hypothesized that terrain-driven hydrological flow patterns, mass-movement and local micro-climatic factors could be responsible processes contributing for SOC redistributions, thus affecting soil carbon stock in time. Terrain attributes were derived by digital terrain analysis from the 10 m DEM of the study area. A total of 37 terrain attributes were calculated and submitted to statistical feature selection. The Chi-square ranking indicated only 4 significant covariates among the terrain attributes (slope height, valley depth, protection index, surface area). Model validation using SOCv and the selected terrain attributes as predictors showed a training and test perfection of 0.889 and 0.921 respectively. Results confirmed that after 10 years of cover crop practices the SOC concentrations generally increased in the topsoil horizon and this increment is affected by the initial SOC concentration and terrain-driven factors.

  4. International Symposium on Remote Sensing of Environment, 10th, University of Michigan, Ann Arbor, Mich., October 6-10, 1975, Proceedings. Volumes 1 & 2

    NASA Technical Reports Server (NTRS)

    1975-01-01

    Topics treated include the application of a Fourier transform spectrometer to infrared remote sensing, the performance optimization of a satellite-borne thematic mapper, a data handling system to be integrated with a digital airborne multispectral scanner, infrared thermography for micro- and mesometeorological measurements, satellite interrogated data collection platforms for river and flood forecasting and the automatic measurement of sea surface temperature from a GOES satellite. Solar and atmospheric effects on satellite imagery derived from aircraft reflectance measurements, methods for determining haze levels from multispectral scanner data, restoration of Landsat images by discrete two-dimensional deconvolution and the automatic classification of aircraft and satellite multispectral images using mixed integer programming are also discussed. Individual items are announced in this issue.

  5. Modeling the Contribution of Ephemeral Gully Erosion Under Different Soil Management in An Olive Orchard Microcatchment Using AnnAGNPS Model

    EPA Science Inventory

    In Spain, few studies have been carried out to explore the erosion caused by processes other than interrill and rill erosion, such as gully and ephemeral gully erosion, especially because most of the available studies have evaluated the erosion at plot scale. A study about the en...

  6. International Symposium on Remote Sensing of Environment, 13th, Ann Arbor, Mich., April 23-27, 1979, Proceedings. Volumes 1, 2 & 3

    NASA Technical Reports Server (NTRS)

    1979-01-01

    The presentations document current activities in the field of remote sensing. Papers include those concerned with data collection, processing, and analysis hardware and methodology, as well as the application of this technology to monitoring and managing the earth's resources and man's global environment. Ground-based, airborne, and spaceborne sensor systems and both manual and machine-assisted data analysis and interpretation are considered.

  7. International Symposium on Remote Sensing of Environment, 15th, University of Michigan, Ann Arbor, MI, May 11-15, 1981, Proceedings. Volumes 1, 2 & 3

    NASA Technical Reports Server (NTRS)

    1981-01-01

    Developments related to advanced sensors and sensor systems are being examined, taking into account advanced aerospace remote sensing systems for global resource applications, spaceborne radar observation of the earth surface, a concept for an advanced earth resources satellite system, technologies for the multispectral mapping of earth resources, and the use of Landsat images and morphologic analogs in space exploration. Other topics discussed are related to modeling for terrain analysis, digital processing and analysis of remotely sensed data, microwave remote sensing, new discoveries from planetary remote sensing, and data base utilization. Advances in the area of luminescence are also considered along with future plans and prospects concerning the remote sensing of the earth from space.

  8. Assessment of Runoff and Sediment Yields Using the AnnAGNPS Model from the Daning River Watershed in Three-Gorge Area of China

    EPA Science Inventory

    Soil erosion has been recognized as one of the major threats to our environment and water quality worldwide, especially in China. To mitigate nonpoint source water quality problems caused by soil erosion, best management practices (BMPs) and/or conservation programs have been ado...

  9. Modeling the contribution of ephemeral gully erosion under different soil managements: A case study in an olive orchard microcatchment using the AnnAGNPS model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In Spain, few studies have been carried out to explore the erosion caused by processes other than interril and rill erosion, such as gully and ephemeral gully erosion, especially because most of the available studies have evaluated the erosion at plot scale. A study about the environmental and econo...

  10. Strates de croissance et cinématique à court-terme de la déformation (dizaines à centaines de milliers d'années)

    NASA Astrophysics Data System (ADS)

    Castelltort, Sébastien; Pochat, Stéphane; Van den Driessche, Jean

    2004-02-01

    High-frequency stratigraphic cycles (10 s to 100 s ka) often show, at a specific location, an alternation of 'dynamic' (proximal-energetic), and 'non-dynamic' (distal-pelagic) processes with time. When sedimentation is syn-deformation, these processes tend respectively to fill-up tectonically-induced topography or to drape it. As a consequence, growth strata are alternatively thickened and isopach across the growth structure. High-resolution kinematic studies of growth structures (folds and faults), which assume that sedimentation always fills up topographies ('fill-to-the-top' model), may therefore mistake sedimentary cyclicity for tectonic cyclicity. We address this problem with one example of growth anticline in the Spanish Pyrenees, and we discuss the fill-to-the-top model. To cite this article: S. Castelltort et al., C. R. Geoscience 336 (2004).

  11. Integration of Watershed Model AnnAGNPS and Stream Network Model CCHE1D for the Development of a New GIS-Based BMP Planning Tool

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper presents a new GIS-based Best Management Practice (BMP) Tool developed for watershed managers to assist in the decision making process by simulating various scenarios using various combinations of Best Management Practices (BMPs). The development of this BMPTool is based on the integratio...

  12. An Ensemble System Based on Hybrid EGARCH-ANN with Different Distributional Assumptions to Predict S&P 500 Intraday Volatility

    NASA Astrophysics Data System (ADS)

    Lahmiri, S.; Boukadoum, M.

    2015-10-01

    Accurate forecasting of stock market volatility is an important issue in portfolio risk management. In this paper, an ensemble system for stock market volatility is presented. It is composed of three different models that hybridize the exponential generalized autoregressive conditional heteroscedasticity (GARCH) process and the artificial neural network trained with the backpropagation algorithm (BPNN) to forecast stock market volatility under normal, t-Student, and generalized error distribution (GED) assumption separately. The goal is to design an ensemble system where each single hybrid model is capable to capture normality, excess skewness, or excess kurtosis in the data to achieve complementarity. The performance of each EGARCH-BPNN and the ensemble system is evaluated by the closeness of the volatility forecasts to realized volatility. Based on mean absolute error and mean of squared errors, the experimental results show that proposed ensemble model used to capture normality, skewness, and kurtosis in data is more accurate than the individual EGARCH-BPNN models in forecasting the S&P 500 intra-day volatility based on one and five-minute time horizons data.

  13. La santé des pasteurs mobiles au Sahel - Bilan de 15 années de recherches et développement.

    PubMed

    Montavon, A; Jean-Richard, V; Bechir, M; Daugla, D M; Abdoulaye, M; Bongo Naré, R N; Diguimbaye-Djaibé, C; Alfaroukh, I O; Schelling, E; Wyss, K; Tanner, M; Zinsstag, J

    2013-07-13

    Dans le Sahel, entre la Mauritanie et la Somalie incluant le Nord Kenya, environ 20 à 30 millions de personnes vivent en transhumance. Le rythme de leur migration suit l'évolution saisonnière du climat et la disponibilité des ressources, telle que l'eau, le pâturage et le sel. Malgré une exposition élevée à certaines maladies comme les zoonoses et les problèmes conditionnés liés au climat, les pasteurs mobiles sont parmi les populations quasiment exclues du système de santé, car la mise à disposition des services sociaux adaptés à un mode de vie mobile est difficile. Suivant l'objectif de recherche d'un meilleur accès aux soins des pasteurs mobiles, l'Institut Tropical et de Santé Publique Suisse, en partenariat avec plusieurs institutions dans la région, est actif au Sahel depuis 15 ans, aussi bien dans le domaine de la recherche, que celui des actions de développement. Basées sur une approche orientée vers les besoins des pasteurs mobiles pour leur développement, des recherches interdisciplinaires ont contribué à mieux comprendre la situation et les problèmes des éleveurs. En relation de la proximité entre l'homme et son bétail, une approche unissant la santé humaine et animale s'est avérée bonne et la valeur ajoutée d'une meilleure collaboration entre médecine humaine, animale et l'environnement a été démontrée. Ces approches utiles devraient être poursuivies et consolidées dans les recherches et le développement des actions futurs. PMID:23848258

  14. Thermospheric wind effects on the global distribution of helium in the earth's upper atmosphere. Ph.D. Thesis - Michigan Univ., Ann Arbor

    NASA Technical Reports Server (NTRS)

    Reber, C. A.

    1973-01-01

    The momentum and continuity equations for a minor gas are combined with the momentum equation for the major constituents to obtain the time dependent continuity equation for the minor species reflecting a wind field in the background gas. This equation is used to study the distributions of helium and argon at times of low, medium, and high solar activity for a variety of latitudinal-seasonal wind cells. For helium, the exospheric return flow at the higher thermospheric temperatures dominates the distribution to the extent that much larger latitudinal gradients can be maintained during periods of low solar activity than during periods of high activity. By comparison to the exospheric flow, the smoothing effect of horizontal diffusion is almost negligible. The latitudinal variation of helium observed by satellite mass spectrometers can be reproduced by the effect of a wind system of air rising in the summer hemisphere, flowing across the equator with speeds on the order of 100 to 200 m/sec, and descending in the winter hemisphere. Argon, being heavier than the mean mass in the lower thermosphere, reacts oppositely to helium in that it is enhanced in the summer hemisphere and depleted in the winter.

  15. Ethics, Law and Professional Issues Gallagher Ann and Hodge Sue Ethics, Law and Professional Issues 192pp £20.99 Palgrave Macmillan 9780230279940 0230279945 [Formula: see text].

    PubMed

    2014-10-01

    THE EDITORS provide a sound introduction to ethics, law and professional issues in health care. Scenarios before each chapter help the reader to digest and comprehend the information. My only criticism is that it is not directly relevant to nursing alone. Although there is some benefit in being aware of how other practitioners may be affected by these issues, another book aimed at nurses would be more appropriate. Later chapters about responding to unprofessional practice and promoting professional healthcare practice may be of more interest to nursing students and recently qualified healthcare professionals. PMID:25358983

  16. Estimation of runoff, peak discharge and sediment load at the event scale in a medium-size Mediterranean watershed using the AnnAGNPS model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Sediment transport in rivers is an indicator of soil eroded from various sediment sources, of which agricultural land can be a significant one, and the intensity of the phenomenon provides a measure of land degradation at a watershed level. The use of distributed models to solve problems in water r...

  17. The Growth Edge: Creative Use of Computers for Facilitating Learning and Enhancing Personal Development. Papers from the Workshop (Ann Arbor, Michigan, June 27-30, 1986).

    ERIC Educational Resources Information Center

    Walz, Garry R., Ed.; Bleuer, Jeanne C., Ed.

    This document is the fourth publication in a series devoted to the use of computers in counseling. The outgrowth of the 1986 ERIC/CAPS workshop, it contains four of the major presentations made at the conference. "The Impact of Computers on the Future of Counseling: Boom or Boomerang" (Edwin L. Herr) examines the effect of technology upon society…

  18. International Symposium on Remote Sensing of Environment, 17th, University of Michigan, Ann Arbor, MI, May 9-13, 1983, Proceedings. Volumes 1, 2 & 3

    NASA Technical Reports Server (NTRS)

    1984-01-01

    The collection, processing, and analysis of remote-sensing data from ground-based, airborne, and spaceborne instruments for application to the monitoring and management of the earth and environment and resources are examined in reviews and reports, some in summary form. Subject areas covered include US policy and directions on remote sensing (RS); the future of terrestrial RS from space; RS of land, oceans, and atmosphere from a global perspective; RS in hydrological modeling; microprocessing technology; array processors; geobased information systems; artificial intelligence; the Shuttle imaging radar; and current results from Landsat-4. Among the specific topics discussed are RS application to hydrocarbon exploration, airborne gamma-radiation assessment of snow water equivalent, surface-vegetation-biomass modeling from AVHRR and Landsat data, Landsat imagery of Mediterranean pollution, fast two-dimensional filtering of thermal-scanner data, RS of severe convective storms, registration of rotated images by invariant moments, and the geometric accuracy of Landsat-4 Thematic-Mapper P-tapes.

  19. International Symposium on Remote Sensing of Environment, 11th, University of Michigan, Ann Arbor, Mich., April 25-29, 1977, Proceedings. Volumes 1 & 2

    NASA Technical Reports Server (NTRS)

    1977-01-01

    Consideration is given to remote sensor development and sensor data analysis and interpretation, and to the following fields of application of remote sensors: geology and mineral resources, meteorology, agriculture, forestry and rangeland, ocean and coastal regions, and environmental quality. Attention is also given to economic and institutional issues and technology transfer in the field of remote sensing, to microwave remote sensing and to the current and future role of remote sensing in operational programs.

  20. International Symposium on Remote Sensing of Environment, 19th, Ann Arbor, MI, October 21-25, 1985, Proceedings. Volumes 1 & 2

    NASA Technical Reports Server (NTRS)

    1986-01-01

    The technology and applications of terrestrial remote sensing (RS) are discussed in reviews and reports. Topics examined include the future of the NASA earth-sciences program, NOAA plans for earth observations in the 1990s, space RS in France, international coordination of RS satellite programs, and applications of geocoded imagery. Consideration is given to spatial and tabular databases for order-three soil surveys, an AVHRR and Landsat regional inventory of irrigated agriculture, classification of wetlands, microwave radiometry of ocean surface winds and sea ice, and floodplain land-cover mapping with Thematic-Mapper data.

  1. International Symposium on Remote Sensing of Environment, 8th, University of Michigan, Ann Arbor, Mich., October 2-6, 1972, Proceedings. Volumes 1 & 2.

    NASA Technical Reports Server (NTRS)

    1973-01-01

    Recent developments in remote sensing techniques and applications are described in papers dealing with (1) ground-based, airborne, and space-borne sensor systems, (2) machine assisted data analysis and interpretation, and (3) specific uses of sensing techniques by various government units. Topics covered include monitoring of environmental quality factors, delineation of geological formations and mineral deposits, watershed management, observation of vegetative parameters in forestry and agriculture, design and performance details of various sensor systems and equipment, interpretation of multispectral imagery, and applications of ERTS-1 satellite imagery in resource study programs. Individual items are announced in this issue.

  2. International Symposium on Remote Sensing of Environment, 7th, University of Michigan, Ann Arbor, Mich., May 17-21, 1971, Proceedings. Volumes 1, 2 & 3.

    NASA Technical Reports Server (NTRS)

    1971-01-01

    The sessions dealt in full detail with basic research in geology and soils; manual interpretation of data on land use, snow, and ice; machine assisted data handling; instrumentation; basic research in water, snow, and ice; manual interpretation of data on vegetation, soils, and geology; user studies and instrumentation; and operational systems. Individual items are abstracted in this issue.

  3. International Symposium on Remote Sensing of Environment, 21st, University of Michigan, Ann Arbor, Oct. 26-30, 1987, Proceedings. Volumes 1 and 2

    SciTech Connect

    Not Available

    1987-01-01

    Papers on remote sensors, data systems, and scientific investigations related to land, open ocean, ice, astmosphere, and climate research are presented. Topics include the High-Resolution Imaging Spectrometer for NASA's Earth Observing System; the future of remote sensing techniques; airborne electrooptical imaging; airborne stereo line imager data; a helicopter-borne scatterometer; SAR image data compression; international remote-sensing satellites; Radarsat; the integration of remote sensing and geographic information systems; the Argos system; TM data screening; surveillance radar; the use of microwave radiometry in hydrology; and the use of Landsat, AVHRR, and SPOT data in environmental studies. Research using remote-sensing techniques is presented, covering topics such as the measurement of currents, intense and tornadic thunderstorms, suspended sediments in estuaries, calculating land and forest cover, flash flood potential, sea-level variations, agricultural monitoring, fire detection, anaylsis of marine shallow water-bottom features, detection of human-induced environmental change, crop yield estimation, the composition of volcanic rocks, ice surveillance, snow-cover mapping, road detection, surface wind-speed measurements, and mineral exploration.

  4. "H TEXNH: Research Methods and Topics for the History of Rhetoric"; Proceedings of the Speech Communications Association Doctoral Honors Seminar (Ann Arbor, Michigan, March 3-5, 1978).

    ERIC Educational Resources Information Center

    Enos, Richard Leo, Ed.; Wiethoff, William E., Ed.

    The interpretation of the history of rhetoric was the subject of the seminar reported in this document. After a preface and a discussion of the "promise" of rhetoric, abstracts of seminar presentations are grouped under the headings of rhetoric and culture, rhetoric and philosophy, methodological considerations, and discourse analysis. Abstracts…

  5. Awareness and utilization of the hepatitis B vaccine among young men in the Ann Arbor area who have sex with men.

    PubMed

    Neighbors, K; Oraka, C; Shih, L; Lurie, P

    1999-01-01

    The authors conducted a preliminary assessment of hepatitis B vaccination rates among men 18- to 37-years-old who have sex with men in a college town to determine what proportion were willing to be vaccinated. Participants, who were sampled in gay bars, gay advocacy groups, a swim team, and a dance club, completed a 25-item questionnaire. Sixty-seven percent were aware of the hepatitis B vaccine, yet only 22% had received the full series of three injections; only 37% had been tested for the virus. On a scale of 1 to 10 for willingness to be vaccinated (10 being most willing), 58% indicated a 10 (M = 8.5). Thirty percent indicated they received safer sex information from university health services, and 14% reported they had received hepatitis B vaccination information there. Hepatitis B vaccination of men who have sex with men in college towns should be a high priority for university health services. PMID:9919848

  6. A Critical Review of Ann Rinaldi's "My Heart Is on the Ground: The Diary of Nannie Little Rose, A Sioux Girl, Carlisle Indian School, Pennsylvania, 1880."

    ERIC Educational Resources Information Center

    Reese, Debby; Slapin, Beverly; Landis, Barb; Atleo, Marlene; Caldwell, Naomi; Mendoza, Jean; Miranda, Deborah; Rose, La Vera; Smith, Cynthia

    This paper critically reviews the book, "My Heart Is On the Ground: The Diary of Nannie Little Rose, a Sioux Girl, Carlisle Indian School, 1800." The review begins with a profile of Captain Richard Henry Pratt who founded the Carlisle (Pennsylvania) Indian Industrial School in 1879. Pratt's philosophy was to "kill the Indian and save the man."…

  7. ARSENIC REMOVAL FROM DRINKING WATER BY ADSORPTIVE MEDIA. EPA DEMONSTRATION PROJECT AT QUEEN ANNES COUNTY, MARYLAND SIX-MONTH EVALUATION REPORT

    EPA Science Inventory

    This report documents the activities performed and the results obtained from the first six months of the arsenic removal treatment technology demonstration project at the community of Prospect Bay at Grasonville in Queen Anne’s County, MD. The objectives of the project were to ev...

  8. Applications of artificial neural networks; Proceedings of the Meeting, Orlando, FL, Apr. 18-20, 1990

    SciTech Connect

    Rogers, S.K.

    1990-01-01

    The present conference discusses artificial neural networks (ANNs) for automatic target recognition, theory of networks for learning, abductive networks, target recognition in parallel networks, ANN recognition of atomic and molecular species, multispectral image fusion with ANNs, radar warning/emitter identification processing by ANNs, IR target motion estimation by ANNs, and the analog hardware implementation of neocognition networks. Also discussed are a multidimensional Kohonen net on a HyperCube, robot learning, probabilistic neural networks, ANNs for interpolation and extrapolation, knowledge-base browsing with hybrid distributed/local connectionist networks, predicate calculus for ANNs, abductive networks for electronic warfare, uncertainty computations in ANNs, and the classification power of multiple-layer ANNs.

  9. 2. HISTORIC AMERICAN BUILDINGS SURVEY. S. Lucas, Photographer, 1934 MAIN ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    2. HISTORIC AMERICAN BUILDINGS SURVEY. S. Lucas, Photographer, 1934 MAIN PORTICO JUDGE WILSON HOUSE, ANN ARBOR, MICH. - Judge R. S. Wilson House, East Ann & North Division Streets, Ann Arbor, Washtenaw County, MI

  10. 3. HISTORIC AMERICAN BUILDINGS SURVEY. S. Lucas, Photographer, 1934. INTERIOR ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    3. HISTORIC AMERICAN BUILDINGS SURVEY. S. Lucas, Photographer, 1934. INTERIOR JUDGE WILSON HOUSE, ANN ARBOR, MICH. - Judge R. S. Wilson House, East Ann & North Division Streets, Ann Arbor, Washtenaw County, MI

  11. 1. S. Lucas, Photographer, 1934. HISTORIC AMERICAN BUILDINGS SURVEY. WEST ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    1. S. Lucas, Photographer, 1934. HISTORIC AMERICAN BUILDINGS SURVEY. WEST SIDE JUDGE WILSON HOUSE, ANN ARBOR, MICH. - Judge R. S. Wilson House, East Ann & North Division Streets, Ann Arbor, Washtenaw County, MI

  12. Methods to improve neural network performance in daily flows prediction

    NASA Astrophysics Data System (ADS)

    Wu, C. L.; Chau, K. W.; Li, Y. S.

    2009-06-01

    SummaryIn this paper, three data-preprocessing techniques, moving average (MA), singular spectrum analysis (SSA), and wavelet multi-resolution analysis (WMRA), were coupled with artificial neural network (ANN) to improve the estimate of daily flows. Six models, including the original ANN model without data preprocessing, were set up and evaluated. Five new models were ANN-MA, ANN-SSA1, ANN-SSA2, ANN-WMRA1, and ANN-WMRA2. The ANN-MA was derived from the raw ANN model combined with the MA. The ANN-SSA1, ANN-SSA2, ANN-WMRA1 and ANN-WMRA2 were generated by using the original ANN model coupled with SSA and WMRA in terms of two different means. Two daily flow series from different watersheds in China (Lushui and Daning) were used in six models for three prediction horizons (i.e., 1-, 2-, and 3-day-ahead forecast). The poor performance on ANN forecast models was mainly due to the existence of the lagged prediction. The ANN-MA, among six models, performed best and eradicated the lag effect. The performances from the ANN-SSA1 and ANN-SSA2 were similar, and the performances from the ANN-WMRA1 and ANN-WMRA2 were also similar. However, the models based on the SSA presented better performance than the models based on the WMRA at all forecast horizons, which meant that the SSA is more effective than the WMRA in improving the ANN performance in the current study. Based on an overall consideration including the model performance and the complexity of modeling, the ANN-MA model was optimal, then the ANN model coupled with SSA, and finally the ANN model coupled with WMRA.

  13. Neural network accuracy measures and data transforms applied to the seismic parameter estimation problem

    SciTech Connect

    Glover, C.W.; Barhen, J.; Aminzadeh, F.; Toomarian, N.B.

    1997-01-01

    The accuracy of an artificial neural network (ANN) algorithm is a crucial issue in the estimation of an oil field reservoir`s properties from remotely sensed seismic data. This paper demonstrates the use of the k-fold cross validation technique to obtain confidence bounds on an ANN`s accuracy statistic from a finite sample set. In addition, we also show that an ANN`s classification accuracy is dramatically improved by transforming the ANN`s input feature space to a dimensionally smaller, new input space. The new input space represents a feature space that maximizes the linear separation between classes. Thus, the ANN`s convergence time and accuracy are improved because the ANN must merely find nonlinear perturbations to the starting linear decision boundaries. These techniques for estimating ANN accuracy bounds and feature space transformations are demonstrated on the problem of estimating the sand thickness in an oil field reservoir based only on remotely sensed seismic data.

  14. Des analogues naturels de sites de stockage de déchets nucléaires vieux de 2 milliards d'années : les réacteurs de fission nucléaire naturels du Gabon (Afrique)

    NASA Astrophysics Data System (ADS)

    Gauthier-Lafaye, François

    2002-10-01

    Two billion years ago, the increase of oxygen in atmosphere and the high 235U/ 238U uranium ratio (>3%) made possible the occurrence of natural nuclear reactors on Earth. These reactors are considered to be a good natural analogue for nuclear waste disposal. Their preservation during such a long period of time is mainly due to the geological stability of the site, the occurrence of clays surrounding the reactors and acting as an impermeable shield, and the occurrence of organic matter that maintained the environment in reducing conditions, favourable for the stability of uraninite. Hydrogeochemical studies and modelling have shown the complexity of the geochemical system at Oklo and Bangombé (Gabon) and the lack of precise data about uranium and fission products retention and migration mechanisms in geological environments. To cite this article: F. Gauthier-Lafaye, C. R. Physique 3 (2002) 839-849.

  15. Parental Acceptance/Involvement, Self-Esteem and Academic Achievement: The Role of Hope as a Mediator (Anne-Babadan Algilanan Kabul/Ilgi, Benlik Saygisi Ve Akademik Basari: Umudun Araci Rolü)

    ERIC Educational Resources Information Center

    Aydin, Betül; Sari, Serkan Volkan; Sahin, Mustafa

    2014-01-01

    In this study, examining the relationship of parental acceptance/involvement to self-esteem, hope and academic achievement besides, mediating role of hope on the relationship between perception of parental acceptance/involvement, self esteem and academic achievement were aimed. The study was carried out with 297 students from different…

  16. Voices in American Education: Conversations with Patricia Biehl, Derek Bok, Daniel Callahan, Robert Coles, Edwin Dorn, Georgie Anne Geyer, Henry Giroux, Ralph Ketcham, Christopher Lasch, Elizabeth Minnich, Frank Newman, Robert Payton, Douglas Sloan, and Manfred Stanley.

    ERIC Educational Resources Information Center

    Murchland, Bernard

    Interviews expressing a variety of viewpoints on the present and future status of education on a national and global scale are offered by 14 major educators and public figures. The theme of educational reform frames each interview. Patricia Biehl reflects on the diminishing effectiveness of secondary education. Derek Bok favors the teaching of…

  17. Academic Renewal: Advancing Higher Education toward the Nineties. A Collection of Essays Based upon Presentations at the Conference on Academic Renewal Held at the University of Michigan (Ann Arbor, MI, June 1983).

    ERIC Educational Resources Information Center

    Waggoner, Michael, Ed.; And Others

    New directions for higher education are discussed in 13 essays based on a 1983 conference on academic renewal. Six topics are covered: the challenge of renewal, organizational strategies for renewal, environmental contexts for renewal, curriculum developments, faculty renewal, and academic leadership. Titles and authors include: "Observations on…

  18. Dynamics of detonations and explosions: Detonations; International Colloquium on Dynamics of Explosions and Reactive Systems, 12th, University of Michigan, Ann Arbor, July 23-28, 1989, Technical Papers

    SciTech Connect

    Kuhl, A.L.; Leyer, J.-C.; Borisov, A.A.; Sirignano, W.A.

    1991-01-01

    The present volume on the dynamics of gaseous detonations, detonation initiation and transmission, multiphase detonations, and nonideal detonations and boundary effects, discusses the detonability of hydrocarbon fuels in air, the detonation of cryogenic gaseous hydrogen-oxygen mixtures, chemical kinetics-detonation structure correlations for gaseous explosives, the initiation of hydrogen-air detonations by turbulent fluorine-air jets, and the initiation of a detonation wave due to multistage self-ignition. Also discussed are the limit criterion for detonation in circular cubes, oblique detonation at hypersonic velocities, the mechanisms of detonation propagation in porous structures, surface detonations and indirect ignition processes, the detonation of unconfined large-scale fuel-spray/air clouds, the detonation structure of corn starch particles-oxygen mixtures, and the lean detonation limit of sensitized kerosene sprays in air.

  19. Corrigendum to "Resonance scattering of a dielectric sphere illuminated by electromagnetic Bessel non-diffracting (vortex) beams with arbitrary incidence and selective polarizations" [Ann. Phys. 361 (2015) 120-147

    NASA Astrophysics Data System (ADS)

    Mitri, F. G.; Li, R. X.; Guo, L. X.; Ding, C. Y.

    2015-12-01

    In the concerned article Mitri et al. (2015), misprints that have occurred are corrected in six equations. They are Eqs. (60)-(64) and (68). These corrections do neither alter the results and plots displayed in Mitri et al. (2015), nor the conclusions as the numerical computations used the correct equations.

  20. Artificial neural networks in medicine

    SciTech Connect

    Keller, P.E.

    1994-07-01

    This Technology Brief provides an overview of artificial neural networks (ANN). A definition and explanation of an ANN is given and situations in which an ANN is used are described. ANN applications to medicine specifically are then explored and the areas in which it is currently being used are discussed. Included are medical diagnostic aides, biochemical analysis, medical image analysis and drug development.

  1. Evaluation of equations predicting the net portal appearance of amino acid nitrogen in ruminants.

    PubMed

    Martineau, R; Côrtes, C; Ortigues-Marty, I; Ouellet, D R; Lapierre, H

    2014-03-01

    A better assessment of digestible protein and AA flows is required to improve the predictions of animal performance in ruminants (e.g., growth and yields of milk and milk protein). In that respect, 2 recent meta-analyses were conducted in our laboratory to establish the relationships between net portal appearance of AA nitrogen (NPA-AAN) and dietary characteristics either from the National Research Council (Washington, DC) or Institut National de la Recherche Agronomique (INRA; St Genès Champanelle, France). Three prediction equations were selected from these meta-analyses: one equation based only on N intake (NI) and 2 equations based on NI, the intake of neutral detergent fiber, plus the dietary concentration of either total digestible nutrients or digestible organic matter. In the current meta-analysis, 2 new equations were developed to predict NPA-AAN from the estimated supply of metabolizable protein (MP) and the protein truly digestible in the intestine (PDI). The reliability of these 5 equations to predict NPA-AAN was evaluated using an independent database. On average, NPA-AAN predictions based on the supply of MP or PDI had the highest coefficient of determination and the lowest root of mean square prediction error and mean and regression biases compared with predictions based on dietary characteristics, suggesting better reliability with the former. No major difference was detected between NPA-AAN predictions based on parameters from the National Research Council or INRA, except that predictions based on MP had the lowest mean and regression biases. In each equation, mean of residual NPA-AAN (observed NPA-AAN minus predicted values) was lowest and negative for sheep compared with dairy cows, suggesting that NPA-AAN were overpredicted in sheep. Many continuous variables biased NPA-AAN predictions based on NI only, but none of the tested variables biased the predictions based on the supply of MP or PDI, corroborating the better reliability for the

  2. Positive dermal hypersensitivity and specific antibodies in workers exposed to bio-engineered enzymes

    SciTech Connect

    Biagini, R.E.; Henningsen, G.M.; Driscoll, R.; MacKenzie, B.A.; Wilcox, T.; Scinto, J.D.; Bernstein, D.M.; Swanson, M. Mayo Clinic, Rochester, MN )

    1991-03-15

    Thirty-six employees who produced industrial enzymes from bio-engineered strains of bacteria and fungi were evaluated by skin prick testing and enzyme linked immunosorbent assays for specific IgE and IgG antibodies. The workers complained of asthma- and flu-like' symptoms which generally lessened away from work. The enzymes evaluated were {alpha}-amylase from A. niger (ind-AAN), B. licheniformis (ind-AAL) and B. subtilis (ind-AAS); purified {alpha}-amylase from B. subtilis (AAS) and A. niger (AAN); alkaline protease from B. licheniformis (ind-APL) and purified alkaline protease (APL); amylase glucosidase from A. niger (ind-AGN) and purified amylase glucosidase (AGN). Significantly positive skin tests were found for APL, AGN and ind-AAN. Significantly elevated specific IgE results were observed for AAN, AGN, and ind-AAN; elevated specific IgGs were observed for AAN, ind-AAN, ind-AAS, ind-AAL and ind-AGN. Radioimmunoassays of air filter samples (using sera with high Ab titers) for 4 of the ind-enzymes showed only ind-AAN at extremely high environmental levels. These results indicate that occupational exposure to some ind-enzymes causes immediate onset dermal hypersensitivity reactions. The results are equivocal as to whether these reactions are IgE mediated, as IgE titers were low. Contrary to this, IgG titers were extremely high and suggest that these biomarkers can be used as indicators of both individual exposure and environmental analyses.

  3. Targeting c-fms kinase attenuates chronic aristolochic acid nephropathy in mice.

    PubMed

    Dai, Xiao Y; Huang, Xiao R; Zhou, Li; Zhang, Lin; Fu, Ping; Manthey, Carl; Nikolic-Paterson, David J; Lan, Hui Y

    2016-03-01

    Aristolochic acid nephropathy (AAN) is a progressive kidney disease caused by some Chinese herbal medicines, but treatment remains ineffective. Macrophage accumulation is an early feature in human and experimental AAN; however, the role of macrophages in chronic AAN is unknown. We report here that targeting macrophages with fms-I, a selective inhibitor of the tyrosine kinase activity of the macrophage colony-stimulating factor receptor, suppressed disease progression in a mouse model of chronic AAN. Treatment with fms-I (10mg/kg/BID) from day 0 to 28 (prevention study) or from day 14 to 28 (intervention study) substantially inhibited macrophage accumulation and significantly improved renal dysfunction including a reduction in proteinuria and tubular damage. Progressive interstitial fibrosis (myofibroblast accumulation and collagen deposition) and renal inflammation (increased expression of MCP-1, MIF, and TNF-α) were also attenuated by fms-I treatment. These protective effects involved inhibition of TGF-β/Smad3 and NF-kB signaling. In conclusion, the present study establishes that macrophages are key inflammatory cells that exacerbates progressive tubulointerstitial damage in chronic AAN via mechanisms associated with TGF-β/Smad3-mediated renal fibrosis and NF-κB-driven renal inflammation. Targeting macrophages via a c-fms kinase inhibitor may represent a novel therapy for chronic AAN. PMID:26909597

  4. Targeting c-fms kinase attenuates chronic aristolochic acid nephropathy in mice

    PubMed Central

    Zhou, Li; Zhang, Lin; Fu, Ping; Manthey, Carl; Nikolic-Paterson, David J.; Lan, Hui Y.

    2016-01-01

    Aristolochic acid nephropathy (AAN) is a progressive kidney disease caused by some Chinese herbal medicines, but treatment remains ineffective. Macrophage accumulation is an early feature in human and experimental AAN; however, the role of macrophages in chronic AAN is unknown. We report here that targeting macrophages with fms-I, a selective inhibitor of the tyrosine kinase activity of the macrophage colony-stimulating factor receptor, suppressed disease progression in a mouse model of chronic AAN. Treatment with fms-I (10mg/kg/BID) from day 0 to 28 (prevention study) or from day 14 to 28 (intervention study) substantially inhibited macrophage accumulation and significantly improved renal dysfunction including a reduction in proteinuria and tubular damage. Progressive interstitial fibrosis (myofibroblast accumulation and collagen deposition) and renal inflammation (increased expression of MCP-1, MIF, and TNF-α) were also attenuated by fms-I treatment. These protective effects involved inhibition of TGF-β/Smad3 and NF-kB signaling. In conclusion, the present study establishes that macrophages are key inflammatory cells that exacerbates progressive tubulointerstitial damage in chronic AAN via mechanisms associated with TGF-β/Smad3-mediated renal fibrosis and NF-κB-driven renal inflammation. Targeting macrophages via a c-fms kinase inhibitor may represent a novel therapy for chronic AAN. PMID:26909597

  5. Technical and analytical support to the ARPA Artificial Neural Network Technology Program

    SciTech Connect

    1995-09-16

    Strategic Analysis (SA) has provided ongoing work for the Advanced Research Projects Agency (ARPA) Artificial Neural Network (ANN) technology program. This effort provides technical and analytical support to the ARPA ANN technology program in support of the following information areas of interest: (1) Alternative approaches for application of ANN technology, hardware approaches that utilize the inherent massive parallelism of ANN technology, and novel ANN theory and modeling analyses. (2) Promising military applications for ANN technology. (3) Measures to use in judging success of ANN technology research and development. (4) Alternative strategies for ARPA involvement in ANN technology R&D. These objectives were accomplished through the development of novel information management tools, strong SA knowledge base, and effective communication with contractors, agents, and other program participants. These goals have been realized. Through enhanced tracking and coordination of research, the ANN program is healthy and recharged for future technological breakthroughs.

  6. Just 6 Percent of Chest Pain Cases in ER Are Life-Threatening

    MedlinePlus

    ... department and director of medical education at Mount Carmel St. Ann's Hospital, in Westerville, Ohio. Weinstock's own ... chairman, Emergency Department, and director, medical education, Mount Carmel St. Ann's Hospital, Westerville, Ohio. June 13, 2016, ...

  7. 76 FR 76980 - Notice of Listing of Members of the Food and Drug Administration's Senior Executive Service...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-12-09

    ... Keller Barbara Schneeman Michael Landa Rachel Sherman Caroline Lewis Jeffrey Shuren Eric Lindblom Ann... Brian Trent Mary Lou Valdez Steven Vaughn Stephen Veneruso Helen Winkle Ann Wion Dated: December 1,...

  8. Hepatitis B

    MedlinePlus

    ... U.S. Preventive Services Task Force recommendation statement. Ann Intern Med . 2014;161(1):58-66. PMID 24863637 ... Development Conference Statement: Management of hepatitis B. Ann Intern Med . 2009;150:104-10. PMID: 19124811 www. ...

  9. 78 FR 54246 - Agency Emergency Information Collection Reinstatement

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-09-03

    ...Anne E. Gordon, Associate CIO for IT Planning, Architecture, and E-Government, Office of the Chief... August 26, 2013. TheAnne E. Gordon, Associate CIO for IT Planning, Architecture and E-Government,...

  10. NIH Quickfinder and NIH Medline Plus Advisory Group | NIH MedlinePlus the Magazine

    MedlinePlus

    ... National Institute on Deafness and Other Communication Disorders Ann London, National Institute of Allergy and Infectious Diseases ... Siegal, National Institute of Alcohol Abuse and Alcoholism Ann Taubenheim, National Heart, Lung, and Blood Institute Natalie ...

  11. Genetics Home Reference: adult polyglucosan body disease

    MedlinePlus

    ... Tyr329Ser mutation in the glycogen-branching enzyme gene. Ann Neurol. 1998 Dec;44(6):867-72. Citation ... Natural History and Key Magnetic Resonance Imaging Findings. Ann Neurol. 2012 Sep;72(3):433-41. doi: ...

  12. Program Cut Catheter-Associated Urinary Tract Infections

    MedlinePlus

    ... internal medicine at the University of Michigan in Ann Arbor. Roughly 250,000 such infections occur in ... P.H., professor, internal medicine, University of Michigan, Ann Arbor; Susan Huang, M.D., M.P.H., ...

  13. Absent pulmonary valve

    MedlinePlus

    ... absent pulmonary valve syndrome associated with bronchial obstruction. Ann Thoracic Surg. 2006;82:2221-2226. PMID: 17126138 ... of airway compression in absent pulmonary valve syndrome. Ann Thorac Surg . 2006;81:1802-1807. PMID: 16631676 ...

  14. 78 FR 2481 - Watco Holdings, Inc., Watco Railroad Company Holdings, Inc., & Watco Acquisition Sub, Inc...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-11

    ... Acquisition Sub, Inc.--Acquisition of Control Exemption--Ann Arbor Railroad, Inc. Watco Holdings, Inc. (Watco... Holdings to indirectly control, and for Watco Railroad to directly control, Ann Arbor Railroad, Inc....

  15. HVAC pipe/duct sizing using artificial neural networks

    SciTech Connect

    Yeh, S.J.D.; Wong, K.F.V.

    1995-12-31

    The main objective of this study is to demonstrate that artificial neural networks (ANN`s) serve as useful aids to Heating, Ventilating and Air-Conditioning (HVAC) system design. In the present work, the design process for sizing fluid systems in HVAC is simulated by using ANN`S. Four ANN`s have been constructed in a personal computer, one for air duct sizing and three for pipe sizing. The air duct network was trained to output the friction rate and duct size. The three pipe sizing neural networks product pressure drops and pipe diameters. By using the trained artificial neural networks, data can be obtained instantly with errors less than 3%. Thus, ANN`s have been shown to simplify traditional methods and procedures in HVAC pipe and air duct sizing.

  16. If Younger Sibling Arrives Before 1st Grade, Kids Less Likely to Be Obese

    MedlinePlus

    ... of pediatrics at the University of Michigan, in Ann Arbor. Conversely, those children who did not have ... M.D., associate professor, pediatrics, University of Michigan, Ann Arbor; Elsie Taveras, M.D., chief, general pediatrics, ...

  17. Head Lice No Cause for Panic, Expert Says

    MedlinePlus

    ... Sheehan, a pediatric emergency medicine specialist at the Ann & Robert H. Lurie Children's Hospital of Chicago. Children ... detection and treatment of head lice infestations. SOURCE: Ann & Robert H. Lurie Children's Hospital of Chicago, news ...

  18. Incidence of and significant risk factors for aminoglycoside-associated nephrotoxicity in patients dosed by using individualized pharmacokinetic monitoring.

    PubMed

    Bertino, J S; Booker, L A; Franck, P A; Jenkins, P L; Franck, K R; Nafziger, A N

    1993-01-01

    Incidence of and risk factors for aminoglycoside-associated nephrotoxicity (AAN) were evaluated in 1489 patients prospectively monitored with individualized pharmacokinetic monitoring (IPM). Incidence of AAN was 7.9% with individual (univariate) risk factors including advanced age, decreased albumin, poor nutritional status, pneumonia, concurrent furosemide, amphotericin B, vancomycin, cephalosporin, or piperacillin, intensive care unit treatment, leukemia, rapidly fatal illness, liver or renal disease, reduced aminoglycoside clearance, elevated initial steady-state trough concentration (Cminss), volume of distribution or half-life, duration of therapy, total dose, fever, male gender, shock, pleural effusion, and ascites. Multiple logistic regression revealed that Cminss, concurrent clindamycin, vancomycin, piperacillin, or cephalosporin, ascites, advanced age, male gender, decreased albumin, duration of therapy, and leukemia were significant independent risk factors for AAN. Positive predictive value of the model was 30.8%; negative predictive value was 91.7%. No identifiable risk factor alone or in combination was of sufficient sensitivity to reliably predict AAN, but use of IPM may lower the incidence of AAN. PMID:8418164

  19. Metabolomics analysis reveals the association between lipid abnormalities and oxidative stress, inflammation, fibrosis, and Nrf2 dysfunction in aristolochic acid-induced nephropathy

    PubMed Central

    Zhao, Ying-Yong; Wang, Hui-Ling; Cheng, Xian-Long; Wei, Feng; Bai, Xu; Lin, Rui-Chao; Vaziri, Nosratola D.

    2015-01-01

    Alternative medicines are commonly used for the disease prevention and treatment worldwide. Aristolochic acid (AAI) nephropathy (AAN) is a common and rapidly progressive interstitial nephropathy caused by ingestion of Aristolochia herbal medications. Available data on pathophysiology and molecular mechanisms of AAN are limited and were explored here. SD rats were randomized to AAN and control groups. AAN group was treated with AAI by oral gavage for 12 weeks and observed for additional 12 weeks. Kidneys were processed for histological evaluation, Western blotting, and metabolomics analyses using UPLC-QTOF/HDMS. The concentrations of two phosphatidylcholines, two diglycerides and two acyl-carnitines were significantly altered in AAI treated rats at week 4 when renal function and histology were unchanged. Data obtained on weeks 8 to 24 revealed progressive tubulointerstitial fibrosis, inflammation, renal dysfunction, activation of NF-κB, TGF-β, and oxidative pathways, impaired Nrf2 system, and profound changes in lipid metabolites including numerous PC, lysoPC, PE, lysoPE, ceramides and triglycerides. In conclusion, exposure to AAI results in dynamic changes in kidney tissue fatty acid, phospholipid, and glycerolipid metabolisms prior to and after the onset of detectable changes in renal function or histology. These findings point to participation of altered tissue lipid metabolism in the pathogenesis of AAN. PMID:26251179

  20. Distribution of free and liposomal annamycin within human plasma is regulated by plasma triglyceride concentrations but not by lipid transfer protein.

    PubMed

    Wasan, K M; Perez-Soler, R

    1995-09-01

    Annamycin (Ann) is a lipophilic and non-cross-resistant anthracycline antibiotic currently in clinical development as a liposomal formulation (L-Ann) composed of dimyristoylphosphatidylcholine (DMPC) and dimyristoylphosphatidylglycerol (DMPG). Previous studies have demonstrated that the incorporation of Ann into these liposomes prolongs its terminal serum half-life and increases the tumor levels of the drug. However, an explanation for the altered pharmacokinetics and pharmacodynamics of doxorubicin and Ann when entrapped into these multilamellar lipid vesicles remains unknown. Since the distribution of lipophilic compounds within plasma lipoproteins has been shown to influence the pharmacokinetics and organ distribution of a number of lipophilic compounds and this distribution appears to be regulated by lipid transfer protein (LTP), we studied the distribution of Ann and L-Ann among plasma lipoproteins and the influence of LTP on the distribution of Ann and L-Ann among plasma lipoproteins. Our results concluded that when Ann was incorporated into liposomes composed of DMPC and DMPG, over 65% of the initial Ann concentration would distribute into the high density lipoprotein (HDL) fraction and that free Ann and L-Ann distribution within human plasma was independent of LTP activity. In addition, we observed that the increase in total plasma triglyceride (TG) concentrations (through the increase of very low-density lipoproteins (VLDL)) resulted in the increase distribution of Ann and L-Ann within the TG-rich VLDL fraction. However, increasing the VLDL core TG/cholesterol ratio decreased Ann distribution into VLDL. These findings suggest that initial Ann distribution is regulated by a mechanism that does not involve LTP, but through its interaction with plasma VLDL-TG.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:8537888

  1. Application of artificial neural networks in hydrological modeling: A case study of runoff simulation of a Himalayan glacier basin

    NASA Technical Reports Server (NTRS)

    Buch, A. M.; Narain, A.; Pandey, P. C.

    1994-01-01

    The simulation of runoff from a Himalayan Glacier basin using an Artificial Neural Network (ANN) is presented. The performance of the ANN model is found to be superior to the Energy Balance Model and the Multiple Regression model. The RMS Error is used as the figure of merit for judging the performance of the three models, and the RMS Error for the ANN model is the latest of the three models. The ANN is faster in learning and exhibits excellent system generalization characteristics.

  2. Reflective Learning in Practice.

    ERIC Educational Resources Information Center

    Brockbank, Anne, Ed.; McGill, Ian, Ed.; Beech, Nic, Ed.

    This book contains 22 papers on reflective learning in practice. The following papers are included: "Our Purpose" (Ann Brockbank, Ian McGill, Nic Beech); "The Nature and Context of Learning" (Ann Brockbank, Ian McGill, Nic Beech); "Reflective Learning and Organizations" (Ann Brockbank, Ian McGill, Nic Beech); "Reflective Learning in Practice" (Ann…

  3. Achieving Consistent Near-Optimal Pattern Recognition Accuracy Using Particle Swarm Optimization to Pre-Train Artificial Neural Networks

    ERIC Educational Resources Information Center

    Nikelshpur, Dmitry O.

    2014-01-01

    Similar to mammalian brains, Artificial Neural Networks (ANN) are universal approximators, capable of yielding near-optimal solutions to a wide assortment of problems. ANNs are used in many fields including medicine, internet security, engineering, retail, robotics, warfare, intelligence control, and finance. "ANNs have a tendency to get…

  4. 30 CFR 941.780 - Surface mining permit applications-minimum requirements for reclamation and operation plan.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... demonstrate compliance with the South Dakota laws on air pollution, S. D. Comp. Laws Ann. Chap. 34A-1, water pollution control, S. D. Comp. Laws Ann. Chap. 34A-2, and solid waste disposal, S. D. Comp. Laws Ann. Chap... 30 Mineral Resources 3 2012-07-01 2012-07-01 false Surface mining permit...

  5. 40 CFR Appendix Q to Part 50 - Reference Method for the Determination of Lead in Particulate Matter as PM10 Collected From...

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ..., Ann Arbor Science Publishers Inc., 1977. 5. Code of Federal Regulations (CFR) 40, Part 136, Appendix B... 40 CFR Part 53 (Reference and Equivalent Methods). This FRM specifically applies to the analysis of...., Ann Arbor Science Publishers, Ann Arbor, MI, pp. 153-181. 12. Harmonization of Interlaboratory...

  6. Real-time support for high performance aircraft operation

    NASA Technical Reports Server (NTRS)

    Vidal, Jacques J.

    1989-01-01

    The feasibility of real-time processing schemes using artificial neural networks (ANNs) is investigated. A rationale for digital neural nets is presented and a general processor architecture for control applications is illustrated. Research results on ANN structures for real-time applications are given. Research results on ANN algorithms for real-time control are also shown.

  7. Modelling for Prediction vs. Modelling for Understanding: Commentary on Musso et al. (2013)

    ERIC Educational Resources Information Center

    Edelsbrunner, Peter; Schneider, Michael

    2013-01-01

    Musso et al. (2013) predict students' academic achievement with high accuracy one year in advance from cognitive and demographic variables, using artificial neural networks (ANNs). They conclude that ANNs have high potential for theoretical and practical improvements in learning sciences. ANNs are powerful statistical modelling tools but they can…

  8. 30 CFR 910.700 - Georgia Federal program.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ...) of the Act, they shall not be construed to be inconsistent with the Act: (1) Georgia Code Ann. section 56-412 pertaining to limitation of risks for insurance companies. (2) Georgia Code Ann. section..., preempted and superseded: (1) The Georgia Surface Mining Act of 1968, Georgia Code Ann. Section 43-1401...

  9. Inside the Actors' Studio: Exploring Dietetics Education Practices through Dialogical Inquiry

    ERIC Educational Resources Information Center

    Fox, Ann L.; Gingras, Jacqui

    2012-01-01

    Two colleagues, Ann and Jacqui, came together, within the safety of an imagined actors' studio, to explore the challenges that Ann faced in planning a new graduate program in public health nutrition. They met before, during, and after program implementation to discuss Ann's experiences, and audio-taped and transcribed the discussions. When all…

  10. 30 CFR 910.700 - Georgia Federal program.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ...) of the Act, they shall not be construed to be inconsistent with the Act: (1) Georgia Code Ann. section 56-412 pertaining to limitation of risks for insurance companies. (2) Georgia Code Ann. section..., preempted and superseded: (1) The Georgia Surface Mining Act of 1968, Georgia Code Ann. Section 43-1401...

  11. 30 CFR 910.700 - Georgia Federal program.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ...) of the Act, they shall not be construed to be inconsistent with the Act: (1) Georgia Code Ann. section 56-412 pertaining to limitation of risks for insurance companies. (2) Georgia Code Ann. section..., preempted and superseded: (1) The Georgia Surface Mining Act of 1968, Georgia Code Ann. Section 43-1401...

  12. In memoriam of Professor Theodore L. Munsat (1930-2013): his outstanding legacy with the WFN.

    PubMed

    Medina, Marco T

    2014-04-15

    The World Federation of Neurology (WFN) lost an outstanding leader on November 22, 2013 with the death of Professor Theodore Leon Munsat ("Ted"), in Waltham, Massachusetts, USA. Professor Munsat was Emeritus professor of Neurology at Tufts University School of Medicine and served the WFN in several capacities as trustee, chairman of the WFN Education and research committees, chairman of the WFN ALS Research group and founding director of the WFN Seminars in Clinical Neurology. He was president of the American Academy of Neurology (AAN), 1989-1991, chairman of the Continuing Educational Committee of the AAN and founding director of AAN's premier continuing medical education journal Continuum: Lifelong Learning in Neurology. He left an outstanding legacy with the WFN. PMID:24560375

  13. Music, musicians, and the brain: an exploration of musical genius. The 2004 presidential address.

    PubMed

    Popp, A John

    2004-12-01

    The concept of musical genius used to frame a discussion of the "art" practiced by neurosurgeons is the focus of the 2004 Presidential Address to the American Association of Neurological Surgeons (AANS). The musical genius, in contrast to the musically talented individual, is profiled and placed in the pantheon of those who have demonstrated extraordinary creativity. Observations and speculations about the specialization and elaboration of brain structures in musicians evolve into a discussion of artificial intelligence as a foil to what constitutes the essence of humanity. Taking an inductive approach, the author juxtaposes the conclusion about "music, musicians, and the brain" with the theme of the 2004 annual meeting of the AANS, "Advancing Patient Care Through Technology and Creativity," to elaborate on the characteristics of the consummate neurosurgeon. (Note: Musical vignettes used in the address can be found in the accompanying article posted on Neurosurgical Focus http://www.aans.org/education/journal/neurosurgical). PMID:15597747

  14. The cataphoric use of the indefinite this in spoken narratives

    PubMed Central

    Gernsbacher, Morton Ann; Shroyer, Suzanne

    2015-01-01

    Are concepts that were introduced with the unstressed, indefinite article this, as opposed to the indefinite a/an, more accessible from listeners' mental representations? Subjects heard and then verbally continued each of a series of informal narratives. The last clause of each narrative introduced a new noun phrase that began with either the indefinite this or the indefinite a/an (e.g., this egg or an egg). When the concepts were introduced with the indefinite this, the subjects referred to them more frequently, often within the first clauses that they produced, and typically via pronouns. In contrast, when the concepts were introduced with a/an, the subjects referred to them less frequently and typically via full noun phrases. Thus, concepts introduced with the indefinite this were more accessible; therefore, the indefinite this appears to operate cataphorically to improve referential access. PMID:2796738

  15. Intelligent mobility for robotic vehicles in the army after next

    NASA Astrophysics Data System (ADS)

    Gerhart, Grant R.; Goetz, Richard C.; Gorsich, David J.

    1999-07-01

    The TARDEC Intelligent Mobility program addresses several essential technologies necessary to support the army after next (AAN) concept. Ground forces in the AAN time frame will deploy robotic unmanned ground vehicles (UGVs) in high-risk missions to avoid exposing soldiers to both friendly and unfriendly fire. Prospective robotic systems will include RSTA/scout vehicles, combat engineering/mine clearing vehicles, indirect fire artillery and missile launch platforms. The AAN concept requires high on-road and off-road mobility, survivability, transportability/deployability and low logistics burden. TARDEC is developing a robotic vehicle systems integration laboratory (SIL) to evaluate technologies and their integration into future UGV systems. Example technologies include the following: in-hub electric drive, omni-directional wheel and steering configurations, off-road tires, adaptive tire inflation, articulated vehicles, active suspension, mine blast protection, detection avoidance and evasive maneuver. This paper will describe current developments in these areas relative to the TARDEC intelligent mobility program.

  16. Adaptive conventional power system stabilizer based on artificial neural network

    SciTech Connect

    Kothari, M.L.; Segal, R.; Ghodki, B.K.

    1995-12-31

    This paper deals with an artificial neural network (ANN) based adaptive conventional power system stabilizer (PSS). The ANN comprises an input layer, a hidden layer and an output layer. The input vector to the ANN comprises real power (P) and reactive power (Q), while the output vector comprises optimum PSS parameters. A systematic approach for generating training set covering wide range of operating conditions, is presented. The ANN has been trained using back-propagation training algorithm. Investigations reveal that the dynamic performance of ANN based adaptive conventional PSS is quite insensitive to wide variations in loading conditions.

  17. Forensic pathology of companion animal abuse and neglect.

    PubMed

    Gerdin, J A; McDonough, S P

    2013-11-01

    Submission of cases of suspected animal abuse and neglect (AAN) to veterinary pathologists is increasingly frequent. These cases require modification of postmortem procedures and written reports, as the questions asked by courts typically differ from those asked in routine diagnostic cases. Here we review the practice of veterinary forensic pathology as it applies to cases of companion AAN, as well as the fundamental principles of forensic pathology, the components of a forensic necropsy, and the goals of the necropsy in cases of blunt-force trauma, projectile wounds, and starvation. Future directions and endeavors in veterinary forensic pathology are broached. PMID:23686766

  18. Assay-specific artificial neural networks for five different PSA assays and populations with PSA 2-10 ng/ml in 4,480 men.

    PubMed

    Stephan, Carsten; Xu, Chuanliang; Cammann, Henning; Graefen, Markus; Haese, Alexander; Huland, Hartwig; Semjonow, Axel; Diamandis, Eleftherios P; Remzi, Mesut; Djavan, Bob; Wildhagen, Mark F; Blijenberg, Bert G; Finne, Patrik; Stenman, Ulf-Hakan; Jung, Klaus; Meyer, Hellmuth-Alexander

    2007-03-01

    Use of percent free PSA (%fPSA) and artificial neural networks (ANNs) can eliminate unnecessary prostate biopsies. In a total of 4,480 patients from five centers with PSA concentrations in the range of 2-10 ng/ml an IMMULITE PSA-based ANN (iANN) was compared with other PSA assay-adapted ANNs (nANNs) to investigate the impact of different PSA assays. ANN data were generated with PSA, fPSA (assays from Abbott, Beckman, DPC, Roche or Wallac), age, prostate volume, and DRE status. In 15 different ROC analyses, the area under the curve (AUC) in the PSA ranges 2-4, 2-10, and 4-10 ng/ml for the nANN was always significantly larger than the AUC for %fPSA or PSA. The nANN and logistic regression models mostly also performed better than the iANN. Therefore, for each patient population, PSA assay-specific ANNs should be used to optimize the ANN outcome in order to reduce the number of unnecessary biopsies. PMID:17333205

  19. Monthly river flow forecasting using artificial neural network and support vector regression models coupled with wavelet transform

    NASA Astrophysics Data System (ADS)

    Kalteh, Aman Mohammad

    2013-04-01

    Reliable and accurate forecasts of river flow is needed in many water resources planning, design development, operation and maintenance activities. In this study, the relative accuracy of artificial neural network (ANN) and support vector regression (SVR) models coupled with wavelet transform in monthly river flow forecasting is investigated, and compared to regular ANN and SVR models, respectively. The relative performance of regular ANN and SVR models is also compared to each other. For this, monthly river flow data of Kharjegil and Ponel stations in Northern Iran are used. The comparison of the results reveals that both ANN and SVR models coupled with wavelet transform, are able to provide more accurate forecasting results than the regular ANN and SVR models. However, it is found that SVR models coupled with wavelet transform provide better forecasting results than ANN models coupled with wavelet transform. The results also indicate that regular SVR models perform slightly better than regular ANN models.

  20. The skill of seasonal ensemble low flow forecasts for four different hydrological models

    NASA Astrophysics Data System (ADS)

    Demirel, M. C.; Booij, M. J.; Hoekstra, A. Y.

    2014-05-01

    This paper investigates the skill of 90 day low flow forecasts using two conceptual hydrological models and two data-driven models based on Artificial Neural Networks (ANNs) for the Moselle River. One data-driven model, ANN-Indicator (ANN-I), requires historical inputs on precipitation (P), potential evapotranspiration (PET), groundwater (G) and observed discharge (Q), whereas the other data-driven model, ANN-Ensemble (ANN-E), and the two conceptual models, HBV and GR4J, use forecasted meteorological inputs (P and PET), whereby we employ ensemble seasonal meteorological forecasts. We compared low flow forecasts without any meteorological forecasts as input (ANN-I) and five different cases of seasonal meteorological forcing: (1) ensemble P and PET forecasts; (2) ensemble P forecasts and observed climate mean PET; (3) observed climate mean P and ensemble PET forecasts; (4) observed climate mean P and PET and (5) zero P and ensemble PET forecasts as input for the other three models (GR4J, HBV and ANN-E). The ensemble P and PET forecasts, each consisting of 40 members, reveal the forecast ranges due to the model inputs. The five cases are compared for a lead time of 90 days based on model output ranges, whereas the four models are compared based on their skill of low flow forecasts for varying lead times up to 90 days. Before forecasting, the hydrological models are calibrated and validated for a period of 30 and 20 years respectively. The smallest difference between calibration and validation performance is found for HBV, whereas the largest difference is found for ANN-E. From the results, it appears that all models are prone to over-predict low flows using ensemble seasonal meteorological forcing. The largest range for 90 day low flow forecasts is found for the GR4J model when using ensemble seasonal meteorological forecasts as input. GR4J, HBV and ANN-E under-predicted 90 day ahead low flows in the very dry year 2003 without precipitation data, whereas ANN